Input: Claim: Personalized nutrition guarantees that you can eat anything without gaining weight, as long as it fits your genetic profile. [SEP] Text: 36 kg/m² (95% CI [-0. 4907, -0. 2457]), respectively (Figs. 1E, S2B, D, E, Tabs. S4, 5). In contrast, participants who reported to have resumed irregular eating gained a significant average of 0. 48 kg (95% CI [0. 1984, 0. 7616]) and 0. 17 kg/m² (95% CI [0. 07434, 0. 2603]), respectively (Fig. 1E, S2B, D, E, Tab. S4). 2. 4. Relation between weight change and improvement in the regularity of mealsTo examine the extent to which EG participants’ weight loss was effectively related to improvements in meal regularity, we correlated changes in body weight and BMI with individual MTVS changes. Consistent with our hypothesis, a significant relationship exists between weight loss and improvement in regularity in the EG (Fig. 1G, Tab. S6). A breakdown of meals shows that increasing the regularity of lunch and dinner has the greatest effects, with no significant relationship between increasing the regularity of breakfast and weight loss (Fig. S2H, Tab. S6). In contrast, in the CG, there were no or little improvements in regularity and, accordingly, no correlation with weight/BMI changes. Further analyses revealed that all MTVS up to 3, which corresponds to a time window for meals of up to ±45 min, resulted in comparably effective weight loss, whereas the efficiency of weight loss decreases significantly with an MTVS greater than 3 (Tab. S7). 2. 5. Relation between weight change and baseline BMIA weight loss intervention which is particularly based on metabolic optimization is likely to be most effective for individuals with exceeded body weight. In fact, the higher the baseline BMI of EG participants at T1, the greater the weight loss (Fig. S2I, Tab. S6). Stratifying the subjects by baseline BMI, including the control group, confirms this result, but also shows that in all strata the BMI of EG subjects decreased more than that of CG subjects, even if they had the same initial BMI (Fig. S2J, Tab. S8). Multiple regression shows that the reduction in MTVS and baseline BMI together predict the weight loss of the participants (Fig. 1H, Tab. S9).

Output: contrast


Input: Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: 79 (0. 47) a<0. 01 (0. 00) b0. 21 (0. 40) bβ-1,4-GlucosidaseCellulose degradation2. 23 (0. 69) b3. 05 (0. 91) ab3. 44 (1. 12) a0. 01 (0. 00) c0. 70 (0. 56) cCellobiohydrolaseCellulose degradation0. 77 (0. 58) ab0. 87 (0. 56) ab1. 07 (0. 61) a<0. 01 (0. 00) c0. 36 (0. 20) bcβ-1,4-XylosidaseHemicellulose degradation0. 12 (0. 06) ab0. 22 (0. 18) a0. 19 (0. 10) a<0. 01 (0. 00) b0. 10 (0. 05) abLaccaseaLignin degradation13. 3 (12. 5) ab19. 0 (11. 3) a5. 4 (8. 3) bND4. 13 (4. 6) bPeroxidaseaLignin degradation19. 2 (15. 4) c39. 2 (18. 4) ab48. 9 (16. 5) aND27. 5 (12. 6) bcPhenol oxidaseaLignin degradation0. 5 (1. 3) b0. 7 (1. 1) b3. 5 (2. 6) aND1. 54 (1. 00) abAbbreviations: control, residual enzyme activity in irradiated controls (irradiated control bags not placed in the field); FH, in situ fermentation-humic layer; ND, no activity detected; −SB, hyphal trap bags with no sand barrier; +SB, hyphal trap bags with sand barrier; Sand, sand barrier. Data are provided as means (n=9) with s. d. in brackets. Data in the same row with different letters are significantly different at P<0. 01. aActivities given as mmol h−1 g−1. Table 4 Open in new tab Potential organic matter breakdown activity of ectomycorrhizal tips Enzyme. Enzyme activity (pmol min−1 mm−2). .

Output: pass


Input: Claim: Fungi play a crucial role in ecosystems as decomposers, breaking down organic matter. [SEP] Text: DiscussionIn this study, we investigated how the bacterial and fungal community composition differed between flow conditions for two common species of aquatic leaf litter. Drying events showed limited effects on leaf bacterial communities, which were probably supported during flow disturbances by the fungal community already present since the early stages of the decomposition process, which provided an increased surface area for bacteria along with leachate and products of polymers’ degradation [46, 47]. Similarly, leaf bag fungal diversity and taxonomic abundance were not strongly impacted by drying or low flow events. This could be due to the presence of some families which are typically present on the phyllosphere such as Cladosporaceae and Pleosporaceae [48, 49], here found in both chestnut and oak leaves and thus being more resistant to desiccation than the aquatic ones. Furthermore, the presence of desiccation-resistant taxa may have contributed to stabilizing the microbial community when flowing water disappeared. Surprisingly, oak leaves showed higher bacterial and fungal diversity between paired samples. We expected to see lower diversity in oak leaf bags due to them commonly considered as lower quality, more coriaceous (i. e. , leathery), and their higher concentrations of secondary metabolites (such as phenols and tannins) which can make the substratum less palatable for both micro and macroorganisms. Potentially, the higher observed diversity of the microbial community present on the leaves is reflective of the additional complexity needed to break down more recalcitrant leaf material to process [50]. Microbial community structure (as beta diversity) of oak and chestnut leaves varied over the course of this experiment. Regardless of flow conditions, chestnut and oak bacterial communities were distinct at the beginning of the experiment but converged at later sampling dates. This could be due to a higher presence of phyllosphere-specific taxa earlier in decomposition which is replaced over time by more specialized bacteria from the aquatic environment which contribute to the decomposition process. However, for fungi, we observed that chestnut and oak fungal communities remained distinct throughout decomposition. This suggests the presence of species specific fungi involved in the decomposition process, a hypothesis supported by the known differences in quality of the two leaf types [51]: some secondary compounds such as cellulose, lignin, tannins and phenols have a role in the composition of the leaf texture and palatability, thus different fungi are necessary to break down those compounds.

Output: corroborate


Input: Claim: Personalized nutrition guarantees that you can eat anything without gaining weight, as long as it fits your genetic profile. [SEP] Text: These data show that regularity in meal intake can lead to a significant loss of body weight and suggest that this effect is especially pronounced in individuals with a higher BMI. 2. 6. Relation between weight change and self-reported food quantity and compositionBy restricting meals to specific times and shortening the time window in which food is eaten, it is feasible that EG participants ate less or changed food composition during the intervention phase and therefore lost weight. However, on average, the reported food energy ingested by CG and EG participants did not substantially change during the study (Fig. 2A, S2K, L, Tab. S3, 6), apart from a minor average reduction of ∼350 kJ (95% CI [-627. 6, - 67. 67]) per day in the EG (Fig. S2K, Tab. S3, 6), and did not differ between CG and the EG. As they are rather small, these differences do not add up to a significant reduction in the total average energy consumed over the course of the study. Accordingly, the determined cumulative average energy intake during the intervention phase did not differ on any day from the estimated energy intake based on an extrapolation of the cumulative food consumption during the exploration phase, neither in the CG nor in the EC group (Fig. 2B). Nevertheless, there were some participants who reported having consumed fewer calories during the intervention phase, while some also reported having ingested more calories. However, consistent with our hypothesis that high regularity of mealtimes optimizes metabolism of similar amounts of food, there is no relationship between reported changes in average daily and cumulative energy intake and change in body weight/BMI of either CG or EG participants (Fig. 2C, D, Tab. S6). Likewise, the composition of the ingested foods did not change considerably in either group, and participants reported a normal distribution of the macronutrients of fat, carbohydrate, and protein in both phases of the study (Fig. 2E, S2M). Also, there was no correlation between weight change and change in reported average daily and cumulative macronutrient intake (Fig. 2D, S2N, Tab. S6). Fig. 2:Changes in body weight/BMI are not related to changes in reported caloric intake and composition of macronutrients.

Output: contrast


Input: Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: Piloderma. Amphinema. Cenococcum. Cortinarius. Tylospora. EMFa. Acid phosphatase12. 71 (7. 75)11. 48 (7. 65)8. 93 (5. 47)13. 56 (11. 36)9. 77 (7. 63)10. 15 (3. 59)Sulfatase1. 08 (1. 13)0. 82 (0. 53)0. 77 (0. 74)2. 17 (3. 26)1. 00 (0. 80)1. 16 (0. 72)Leucine aminopeptidase0. 46 (0. 19)0. 41 (0. 11)0. 50 (0. 23)2. 94 (4. 78)0. 42 (0. 32)0. 54 (0. 24)β-1,4-N-acetylglucosaminidase3. 87 (1. 46)3. 57 (1. 14)2. 87 (1. 48)6. 05 (6. 37)2. 79 (1. 77)3. 68 (0. 89)β-1,4-Glucosidase3. 16 (1. 19) ab5. 78 (2. 48) a1. 75 (0. 98) b2. 76 (4. 12) ab3. 45 (2. 23) ab3. 47 (1. 37)Cellobiohydrolase0. 63 (0. 28) b1. 09 (0. 37) a0. 42 (0. 27) b0. 65 (1. 18) ab0. 76 (0. 39) ab0. 72 (0. 34)Xylosidase0. 22 (0. 18) b0. 64 (0. 38) a0. 20 (0. 10) b0. 13 (0. 13) b0. 49 (0. 37) ab0. 34 (0. 20)Laccaseb0. 01 (0. 01)0. 01 (0. 01)0. 01 (0. 01)0. 02 (0. 02)0. 03 (0. 01)0. 02 (0. 01)Number of plots (n)878559Enzyme.

Output: pass


Input: Claim: Fungi play a crucial role in ecosystems as decomposers, breaking down organic matter. [SEP] Text: This could be due to the need of breaking down those recalcitrant and secondary compounds into simpler molecules and nutrients, before those nutrients become available for other organisms involved in the decomposition process. Fungal communities are mainly represented by Ascomycetes [57], because Basidiomycetes usually later in leaf litter decomposition, at stages we did not investigate during our field experiment. The family Aurobasidiaceae, which is widespread in freshwater and marine ecosystems [58], was the most abundant in our samples, despite the leaf type and flow regime, likely because this family is able to adapt to different environmental conditions and thus to cope with hydrological and nutrient stressors [58]. Interestingly, the fungi of the family Pleomassariaceae, widely distributed on decomposing wood and plant material [58], showed high abundance in low flow and drying conditions; this could be due to the ability to exploit the substratum’s remaining moisture and an ability to degrade secondary compounds. This fungal group deserves additional investigation to understand their role in leaf litter decomposition processes during longer desiccation phases. Oak leaf bag fungal communities had a high relative abundance of Cladosporium, typically found in plant material; Alternaria, a taxon usually present on decomposing material with high humidity [59]; Adisciso, a plant pathogen [60] and Phialea, typical of dead leaf material [61]. Chestnut leaves, however, had high relative abundance of Lemonniera, an aquatic hyphomycetes involved in stream decomposition processes [62]; and Tetracladium, an important decomposer in stream food webs [63]. The presence of those genera, mainly involved in breakdown processes in aquatic environments, may explain the faster decomposition rate we found for chestnut leaves. These findings highlight the importance of bacteria and fungi in the leaf litter decomposition process, and confirms the presence of different families/genera during decomposition, and variation related in leaf type and quality and also flow regime, even if with limited effect. High-throughput sequencing of microbial communities associated with in-stream leaf litter highlights the complexity of biotic interactions on aquatic decomposition processes. river ecosystems, the occurrence of low flow phases and drying events is a recent phenomenon, caused mainly by global climate change and anthropogenic pressures [64].

Output: corroborate


Input: Claim: Personalized nutrition guarantees that you can eat anything without gaining weight, as long as it fits your genetic profile. [SEP] Text: Changes in reported daily caloric intake (A), cumulative caloric intake (B) and food composition (E) and their relationship to weight/BMI changes (C, D, and F). Data in (A) are normalized so that all baseline data of the exploration phase equal 1. To represent the x-fold change, data from the intervention phase are divided by data from the exploration phase of the corresponding participant. (A, E) 2-way repeated-measures ANOVA with Bonferroni post hoc test comparing CG and EG during the exploration or intervention phase and T0-T1 and T1-T2 within groups, * p ≤ 0. 05. Detailed statistics in Tables S3. (B) Mixed-effects model with Bonferroni post hoc test comparing determined and estimated cumulative energy intake. The estimated energy intake is formed as an assumed continuation of the average daily intake during the exploration phase. post hoc test showed no significant differences on any study day. (C, D, and F) Linear regression, CG: n=30; EG: n=67 (some participants were excluded subsequently from this analysis because of several erroneous diary entries about unrealistic amounts of food, e. g. , 30,000 g chicken for lunch). Detailed statistics in Tab. S6. 2. 7. Relation between weight change and other meal timing-related factorsBesides increasing regularity, restricting meals to certain times of the day can also shorten the daily window in which meals are eaten and shift meals to other times of the day. In fact, our intervention caused many EG participants to avoid occasional meals at extremely early or late times, limiting their meals to much shorter intervals of 11 h (95% CI [10. 468, 11. 520]) (Fig. 3A, B, Tab. S3), while those of the CG remained long with 13. 7 h (95% CI [12. 902, 14. 562]). Additionally, compared with before and with the CG, the EG intervention resulted in the first meal of the day being delayed to a later time for many subjects (EG: 09:21 (95% CI [08:58, 09:45]) vs. CG: 08:03 (95% CI [07:32, 08:33])) and the last meal of the day being advanced to an earlier time (EG: 20:17 (95% CI [19:59, 20:35]) vs.

Output: contrast


Input: Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: Enzyme activity (pmol min−1 mm−2). . Piloderma. Amphinema. Cenococcum. Cortinarius. Tylospora. EMFa. Acid phosphatase12. 71 (7. 75)11. 48 (7. 65)8. 93 (5. 47)13. 56 (11. 36)9. 77 (7. 63)10. 15 (3. 59)Sulfatase1. 08 (1. 13)0. 82 (0. 53)0. 77 (0. 74)2. 17 (3. 26)1. 00 (0. 80)1. 16 (0. 72)Leucine aminopeptidase0. 46 (0. 19)0. 41 (0. 11)0. 50 (0. 23)2. 94 (4. 78)0. 42 (0. 32)0. 54 (0. 24)β-1,4-N-acetylglucosaminidase3. 87 (1. 46)3. 57 (1. 14)2. 87 (1. 48)6. 05 (6. 37)2. 79 (1. 77)3. 68 (0. 89)β-1,4-Glucosidase3. 16 (1. 19) ab5. 78 (2. 48) a1. 75 (0. 98) b2. 76 (4. 12) ab3. 45 (2. 23) ab3. 47 (1. 37)Cellobiohydrolase0. 63 (0. 28) b1. 09 (0. 37) a0. 42 (0. 27) b0. 65 (1. 18) ab0. 76 (0. 39) ab0. 72 (0. 34)Xylosidase0. 22 (0. 18) b0. 64 (0. 38) a0. 20 (0. 10) b0. 13 (0. 13) b0. 49 (0. 37) ab0. 34 (0. 20)Laccaseb0. 01 (0. 01)0. 01 (0. 01)0. 01 (0. 01)0. 02 (0. 02)0. 03 (0. 01)0. 02 (0.

Output: pass


Input: Claim: Fungi play a crucial role in ecosystems as decomposers, breaking down organic matter. [SEP] Text: Frey-(2011) Bacterial-fungal interactions: hyphens between agricultural, clinical, environmental, and food microbiologists. 75:583–609. (2015) Effects of forest management practices in temperate beech forests on bacterial and fungal communities involved in leaf litter degradation. 69:905–913. (1966) Decomposition of leaf litter in relation to environment, microflora, and microbial respiration. Ecology 47:194–201. (2013) Assessing the effect of litter species on the dynamic of bacterial and fungal communities during leaf decomposition in microcosm by molecular techniques. 8:e84613. Mora-Gómez J, Duarte S, Cássio F, Pascoal C, Romaní AM (2018) Microbial decomposition is highly sensitive to leaf litter emersion in a permanent temperate stream. Environ 621:486–496. (2020) Microbial community response to a novel salmon resource subsidy. Evol 7:505. álint M, Bernabò P, Čiampor F Jr, Čiamporová-Zaťovičová (2014) Integrating molecular tools into freshwater ecology: developments and opportunities. 9:1559–1576. (2019) Necrobiome framework for bridging decomposition ecology of autotrophically and heterotrophically derived organic matter. 89:e01331. (2018) Lentification in Alpine rivers: patterns of diatom assemblages and functional traits. 80:1–11. (2019a) streams run dry: the drought memory of benthic communities. 81:1–14. (2019b) The role of recurrent dewatering events in shaping ecological niches of scrapers in intermittent Alpine streams. Hydrobiologia 841:177–189. per la Protezione dell’Ambiente (2013) Idrologia in Piemonte nel 2012. Regione Piemonte, pp 23. (2021) Effects of flow intermittence on ecosystem processes in mountain streams: are artificial and field experiments comparable? Limnol 195:39–59. (2022) Decomposition and Communities of Alpine Streams: A along the Po River. Water 14:258.

Output: corroborate


Input: Claim: Personalized nutrition guarantees that you can eat anything without gaining weight, as long as it fits your genetic profile. [SEP] Text: CG: 21:31 (95% CI [21:05, 21:57])) (Fig. 3C, D, Tab. S3). However, weight changes of participants were not related to one of these changes in eating characteristics (Fig. 3B-D, Tab. S6). Fig. 3:Influence of other changes in eating times and of personalization of meal schedules on weight loss. (A) 95th percentile of the time period during which food was ingested by 15 example participants during the exploration phase (yellow) and the intervention phase (purple). (B) Change in length of this period and its relation to weight/BMI changes. (C, D) Change in time of first (C) and last (D) caloric intake and their association with weight/BMI changes. (B-D) 2-way repeated-measures ANOVA with Bonferroni post hoc test comparing CG and EG during the exploration or intervention phase and T0-T1 and T1-T2 within groups, *** p ≤ 0. 001, **** p ≤ 0. 0001. Linear regression. EG: n=67, varying n-numbers result from incomplete entries in the diaries. Detailed statistics in Tables S3 and S6. (E) The relation between mid-Sleep phase and mid-Eat phase (brown) on the weekends of the exploration phase. The goodness of fit of this association improves during through EG intervention and affects both workdays and weekend days (purple). Linear regression, n=65, **** p ≤ 0. 0001. Detailed statistics in Table S6. (F) Relation of the mid-Sleep phase (mSP) and mid-Eat phase (mEP) during exploration and intervention phase. The circles represent 24 h, the gray area represents the estimated sleep time, and the black arrow represents the mid-sleep phase, which is normalized for all subjects. The colored triangles represent the mid-Eat phase of each subject in relation to their mid-Sleep phase. The red arrow shows the average mid-Eat phase across all subjects. n=65. Detailed statistics in Table S10. (G) The smaller the residuals, i. e. , the vertical distances of observation points from the regression line, became, the more BMI the EG subjects lost. Linear regression, n=65, ** p ≤ 0. 01. Detailed statistics in Table S6.

Output: contrast


Input: Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: 01)Number of plots (n)878559Data are provided as means (n=number of plots the tip genera were isolated from. Note that not all genera were found in all plots) with s. d. in brackets. Data in the same row with different letters are significantly different at P<0. 01. Refer to Table 3 for the general role of each enzyme in organic matter breakdown. aEMF, average activity of all ectomycorrhizal tips, not included in statistical analysis. bLaccase activity given in U min−1 mm−2. Table 4 Open in new tab Potential organic matter breakdown activity of ectomycorrhizal tips Enzyme. Enzyme activity (pmol min−1 mm−2). . Piloderma. Amphinema. Cenococcum. Cortinarius. Tylospora. EMFa. Acid phosphatase12. 71 (7. 75)11. 48 (7. 65)8. 93 (5. 47)13. 56 (11. 36)9. 77 (7. 63)10. 15 (3. 59)Sulfatase1. 08 (1. 13)0. 82 (0. 53)0. 77 (0. 74)2. 17 (3. 26)1. 00 (0. 80)1. 16 (0. 72)Leucine aminopeptidase0. 46 (0. 19)0. 41 (0. 11)0. 50 (0. 23)2. 94 (4. 78)0. 42 (0. 32)0. 54 (0. 24)β-1,4-N-acetylglucosaminidase3. 87 (1. 46)3. 57 (1. 14)2. 87 (1. 48)6. 05 (6. 37)2. 79 (1. 77)3. 68 (0. 89)β-1,4-Glucosidase3. 16 (1. 19) ab5. 78 (2. 48) a1. 75 (0. 98) b2. 76 (4. 12) ab3. 45 (2. 23) ab3. 47 (1. 37)Cellobiohydrolase0. 63 (0. 28) b1. 09 (0.

Output: pass


Input: Claim: Some amphibians, like frogs, undergo metamorphosis from an aquatic larval stage to a terrestrial adult form. [SEP] Text: The γ-crystallins, in particular, also had highly variable expression levels and therefore would likely contribute very different amounts to the overall refractive index. When accounting for expression levels (TMM) of all the ubiquitous crystallin genes, tadpoles and juveniles had similar weighted mean dn/dc values (0. 2010 and 0. 2003, respectively; Additional file 8). The frog-specific crystallins had lower estimated dn/dc values than any of the ubiquitous crystallins (ρ-crystallin, 0. 1916 and ζ-crystallin, 0. 1884; Additional file 1: Table S3). DiscussionSignificant shifts in gene expression across ontogenyThe adaptive decoupling hypothesis suggests that animals that develop through two or more distinct phenotypic phases may be able to disrupt genetic correlations between phases, allowing each phase to better adapt to its particular selective environment [3]. This strategy would be particularly relevant for frogs, which often have larval (tadpole) and adult phases that occupy different ecological niches. Although previous studies have shown that morphological diversity of tadpoles and adult frogs is decoupled [6, 17,18,19], studies testing for differences in gene expression are more limited [18]. We found that a large proportion of the eye transcriptome (42%) was significantly differentially expressed between tadpole and juvenile southern leopard frogs, suggesting substantial, and potentially adaptive, decoupling at the level of gene expression. Further, this suggests that cellular composition, density, and size, in addition to within-cell changes in expression, differ between tadpoles and juvenile frogs. These results are consistent with a recent study of eye-body size allometry across ontogeny in anurans that detected a shift at metamorphosis in several species [27], suggesting that relative eye growth is partially decoupled as well. The extent of decoupling in gene expression we detected was substantially more than was found in a comparison of whole body (excluding gut) transcriptomes of tadpole and adult Mantidactylus betsileanus Madagascar frogs, which found that only 14% of annotated transcripts were differentially expressed [18]. In that whole body comparison, differentially expressed transcripts were significantly enriched for genes involved in morphological development, suggesting that phenotypic evolution across phases was decoupled.

Output: corroborate


Input: Claim: Personalized nutrition guarantees that you can eat anything without gaining weight, as long as it fits your genetic profile. [SEP] Text: (H) Representative example of a meal diary showing a shift from meals on weekends. The purple arrows represent the calculated times, based on the events of the more frequent workdays, for the meal schedule of the intervention phase. (I) Shifts from weekend meals caused by the EG intervention. Paired t-test, n=65, *** p ≤ 0. 001, **** p ≤ 0. 0001. Data are normalized so that all baseline data at T0-T1 equal 0 to represent the change in hours. Detailed statistics in Table S11. (J) Large phase shifts of breakfast and dinner, equivalent to a correction of the social jetlag of meals on weekends, are related to greater weight loss. Linear regression, breakfast: n=55, lunch: n=64, dinner: n=63, ** p ≤ 0. 01. Missing n-numbers are due to incomplete diary entries on weekends during the exploratory phase or because participants usually did not have a particular meal. Detailed statistics in Table S6. (K) Results of a multiple regression to investigate the influence of individual variables while holding the others constant on the BMI of EG participants. The Quantile-Quantile (QQ) plot shows the data are normally distributed (left). The multiple regression plot and R2 value shows that the multiple regression model explains the data well (middle). Additionally, the assignment of each regression beta coefficient to the independent variables is shown along with the p-values showing the influence on BMI. The data used are the same as those used in the individual regressions shown previously. Detailed statistics in Tab. S9. (L) Covariance matrix with normalized covariances for each pair of parameters. Values close to 1 (blue) or -1 (red) indicate high intertwining of the data, values close to 0 (white) indicate independence or orthogonality of the data. The assignment of the coefficients to the independent variables is the same as in (K). 2. 8. Effect of meal schedule personalization on weight lossA key part of our hypothesis involves the personalization of meal schedules. Consistent with the concept of social jet lag, our data show that during the exploration phase, eating times on workdays differ from those on work-free days, and we expect eating times on non-workdays to correspond more closely to individual circadian characteristics.

Output: contrast


Input: Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: 37) a0. 42 (0. 27) b0. 65 (1. 18) ab0. 76 (0. 39) ab0. 72 (0. 34)Xylosidase0. 22 (0. 18) b0. 64 (0. 38) a0. 20 (0. 10) b0. 13 (0. 13) b0. 49 (0. 37) ab0. 34 (0. 20)Laccaseb0. 01 (0. 01)0. 01 (0. 01)0. 01 (0. 01)0. 02 (0. 02)0. 03 (0. 01)0. 02 (0. 01)Number of plots (n)878559Enzyme. Enzyme activity (pmol min−1 mm−2). . Piloderma. Amphinema. Cenococcum. Cortinarius. Tylospora. EMFa. Acid phosphatase12. 71 (7. 75)11. 48 (7. 65)8. 93 (5. 47)13. 56 (11. 36)9. 77 (7. 63)10. 15 (3. 59)Sulfatase1. 08 (1. 13)0. 82 (0. 53)0. 77 (0. 74)2. 17 (3. 26)1. 00 (0. 80)1. 16 (0. 72)Leucine aminopeptidase0. 46 (0. 19)0. 41 (0. 11)0. 50 (0. 23)2. 94 (4. 78)0. 42 (0. 32)0. 54 (0. 24)β-1,4-N-acetylglucosaminidase3. 87 (1. 46)3. 57 (1. 14)2. 87 (1. 48)6. 05 (6. 37)2. 79 (1. 77)3. 68 (0. 89)β-1,4-Glucosidase3. 16 (1. 19) ab5. 78 (2. 48) a1. 75 (0. 98) b2. 76 (4. 12) ab3. 45 (2. 23) ab3. 47 (1. 37)Cellobiohydrolase0.

Output: pass


Input: Claim: Some amphibians, like frogs, undergo metamorphosis from an aquatic larval stage to a terrestrial adult form. [SEP] Text: This observation is consistent with divergent macroevolutionary patterns of body shape diversification in tadpoles versus adult frogs [6]. A comparison of whole-body and whole-eye transcriptomes in both M. betsileanus and L. sphenocephalus would clarify whether the observed differences in the degree of differential expression are species or tissue specific. Other examples of decoupling in gene expression come from insects [4, 73,74,75]. For instance, in the hymenopteran Neodiprion lecontei, which has multiple life stages separated by increasingly dramatic metamorphic transitions, Herrig, et al. [75] found that a progressively greater proportion of genes (up to 31%) were differentially expressed between each successive pair of stages. That observation matched the authors’ predictions that gene expression decoupling would be strongest between the most ecologically dissimilar life stages. Consequently, we propose that expression may be more strongly coupled in frog species that remain aquatic after metamorphosis or in those that do not have a tadpole life stage and instead complete development within the egg and hatch as juvenile frogs (direct development). Studies comparing species that differ in life history and with finer scale ontogenetic sampling are needed to test this hypothesis. Furthermore, studies of immune system activity in Drosophila found support for both coupled and decoupled expression of different immune genes [4], underscoring the need for more detailed studies even within broad functional classes of genes. Although our results have interesting implications for the broad decoupling of gene expression between tadpoles and juveniles, our focus was on visual genes. We found that the visual system was disproportionately decoupled compared to the full eye transcriptome, with significant differential expression between tadpole and juvenile frogs in over half of the visual genes we analyzed. This suggests the visual system may be particularly strongly adapted, through decoupling, to the larval and adult environments. Teleost fishes also show differences in visual gene expression across ontogeny, specifically with regard to visual opsin expression, when larval habitat or foraging differs from that of adults [40]. Changes in expression patterns of other visual genes in teleosts remain to be evaluated, but we expect considerable variation in those taxa with distinct larval and adult ecologies.

Output: corroborate


Input: Claim: Personalized nutrition guarantees that you can eat anything without gaining weight, as long as it fits your genetic profile. [SEP] Text: Indeed, our data show that the later the chronotype of participants (measured by the MCTQ mid-sleep phase, mSP [24]), the later their mid-eat phase (mEP) on weekends (Fig. 3E, Tab. S6), with the mSP and mEP being almost antiphasic on average (Fig. 3F, Tab. S10). The EG intervention maintains most of this relationship. However, the residuals of the regression become smaller, resulting in a model fitting the data better (Fig. 3E, Tab. S6). Interestingly, the closer the intervention brought participants’ observed values to their individual fitted values, i. e. , the smaller the residuals became, the more weight they lost (Fig. 3G, Tab. S6). From a clinical point of view, this indicates that a personalized adjustment of eating times to the individual chronotype, i. e. , the establishment of a highly accurate phase relation between mEP and mSP, leads to a particularly effective reduction of excess weight. The calculation of individual eating times was based on the frequency of hours at which meals were eaten during the exploration phase, which typically included more workdays than non-workdays (Fig. 3H). Consequently, for some subjects, the EG intervention created a discrepancy between what may have been physiologically optimal eating times, reflected by weekend data, and the calculated eating times (Fig. 3I, Tab. S11). However, the magnitude of this discrepancy has no effect on weight changes (Fig. S2O, Tab. S6). On the contrary, if the calculated eating times resulted in large shifts of the weekend meals, this also means that previously particularly large “meal jet lags” between working and non-working days were eliminated. Indeed, the more the calculated eating times led to an advance of the first meal and a delay of the last meal, thus the greater the effect of the “meal jet lag” elimination was, the more the participants lost weight (Fig. 3J, Tab. S6). Interestingly, this also includes the elimination of too early dinners on work days. Our data show that a later dinner on all days of the week can lead to weight loss if this time corresponds to the calculated individual optimal time. The independent variables used above for simple regressions may influence each other and therefore their influence on BMI may be confounded.

Output: contrast


Input: Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: 63 (0. 28) b1. 09 (0. 37) a0. 42 (0. 27) b0. 65 (1. 18) ab0. 76 (0. 39) ab0. 72 (0. 34)Xylosidase0. 22 (0. 18) b0. 64 (0. 38) a0. 20 (0. 10) b0. 13 (0. 13) b0. 49 (0. 37) ab0. 34 (0. 20)Laccaseb0. 01 (0. 01)0. 01 (0. 01)0. 01 (0. 01)0. 02 (0. 02)0. 03 (0. 01)0. 02 (0. 01)Number of plots (n)878559Data are provided as means (n=number of plots the tip genera were isolated from. Note that not all genera were found in all plots) with s. d. in brackets. Data in the same row with different letters are significantly different at P<0. 01. Refer to Table 3 for the general role of each enzyme in organic matter breakdown. aEMF, average activity of all ectomycorrhizal tips, not included in statistical analysis. bLaccase activity given in U min−1 mm−2. Enzyme activity in the sand barrier surrounding the +SB traps was either at or below the limit of detection, even though all sand contained visible hypha and diverse fungal communities (see Table 1). The +SB community (predominantly mycorrhizal) and the −SB community (saprotrophic and mycorrhizal) enzyme activity levels were in the same range as those of the FH community (Table 3). EMF-dominated +SB communities had significantly (P<0. 01) higher levels of phenol oxidase (L-DOPA assay) and aminopeptidase activity than −SB or FH communities, and higher peroxidase activity and β-1,4-glucosidase than −SB communities. Activities of all other enzymes did not differ among fungal communities. Enzyme activities associated with EMF tips were highly variable within a given genus, resulting in few significant differences between genera (Table 4). Nevertheless, Amphinema tips had significantly higher (P<0.

Output: pass


Input: Claim: Some amphibians, like frogs, undergo metamorphosis from an aquatic larval stage to a terrestrial adult form. [SEP] Text: Thus, our differential expression and MSP results provide evidence for the role of CYP27C1 in switching chromophore usage and, correspondingly, spectral sensitivity during ontogeny. Several species of frog that transition from aquatic tadpoles to terrestrial or semi-terrestrial adults, including the tree frogs Hyla regilla and H. arborea, several other Lithobates species (L. catesbeianus, L. clamitans, L. esculenta, L. pipiens, L. sphenocephalus), Rana species (R. temporaria, R. arvalis), European fire-bellied toad (Bombina bombina), and common spadefoot (Pelobates fuscus) shift their chromophore usage from primarily A2 to primarily A1 at metamorphosis [34, 53, 80,81,82]. The timing of the shift between chromophores in rods varies, with some species (H. arborea and B. bombina) showing a continuous change from A2 to A1 during tadpole development, while in other species (P. fuscus and R. arvalis), the shift does not occur until the appearance of forelimbs [82]. Our data suggest the possibility that the transition may begin at Gosner stage 35–38 in leopard frogs based on the relatively lower CYP27C1 expression compared to the earlier stages (25–34), even accounting for dark exposure. More data will be needed, however, to further evaluate this timing. In H. arborea, the transition from A2 to A1 was complete post-metamorphosis, with juveniles and adults having the same spectral sensitivities [82]. Our data suggest some juvenile leopard frogs maintain a small proportion of A2 pigment based on continued expression of CYP27C1, while other specimens showed no expression and thus would be expected to have no A2 pigment. By contrast, the toads Bufo boreas and B. bufo appear to use only A1 as both aquatic tadpoles and terrestrial adults [80, 83], and X. laevis, which remain fully aquatic as adults, use exclusively A2 pigments at both life stages [36].

Output: corroborate


Input: Claim: Personalized nutrition guarantees that you can eat anything without gaining weight, as long as it fits your genetic profile. [SEP] Text: Therefore, a multiple regression with the most important and least multicollinear variables (ΔMTVS, ΔkJ, Δcalorie intake interval, ΔmSp-mEP relation, Δweekend breakfast, Δweekend dinner) was done to study their individual influences on the BMI of EG participants while keeping the other variables constant. According to this analysis, only the change in MTVS and also the resulting elimination of “dinner jet lags” have significant influence on the BMI (Fig. 3K, Tab. S9). The elimination of “breakfast jet lags” and the improvement of the mSP-mEP ratio did not reach significance but showed a strong tendency to influence BMI. Changes in caloric intake or the time interval during which food is consumed had no effect on the BMI. A concurrent analysis of covariance shows that MTVS is most strongly intertwined with BMI, while other variables play a role to a much lesser extent (Fig. 3L). 2. 9. General well-being outcomesSince stable circadian rhythms are generally associated with many aspects of health, regular entrainment of a variety of peripheral and brain clocks by the Zeitgeber food may enhance overall well-being. To test this, participants were asked to complete clinical questionnaires measuring subjective health status, sleep quality, depressed mood, and self-efficacy at T0 and at T2. In addition, chronotype was also determined. Many aspects of subjective physical well-being (SF-36 - physical health items) improved significantly during the intervention in the EG (Fig. 4A, Tab. S3), reversing previous differences between CG and EG. In contrast, there was only a slight improvement in the general health item within the CG. In addition, sleep quality (PSQI) of the EG group improved significantly during the intervention, but not of the CG group, again eliminating prior differences between CG and EG. Furthermore, mental health, including vitality, depressed mood, and self-efficacy (SF-36 mental health items, IDS-SR, SWE) also improved significantly in EG participants, but not in the CG (Fig. 4A, Tab. S3). Consistent with our aim to optimize rather than to change individual rhythms, chronotype did not change during the study (Fig. 4B, Tab. S3). Fig. 4:Improvement in overall well-being over the course of the study.

Output: contrast


Input: Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: 1007/s00572-012-0438-y. 10. 1093/bioinformatics/btq281. 10. 1038/ismej. 2009. 77. 10. 1038/ismej. 2011. 52. 886. 13): Establishment and progress report. B. C. Ministry of Forests, Victoria. 018. Available at. 454 Pyrosequencing analyses of forest soils reveal an unexpectedly high fungal diversity. New Phytol. 2009;184:449–456 10. 1111/j. 1469-8137. 2009. 03003. x. 10. 1007/s00572-002-0162-0. 10. 1016/j. soilbio. 2011. 12. 029. 2. Science. 2012;31:1084–1087 10. 1126/science. 1224304. 10. 1890/08-0137. 1. 10. 1016/j. soilbio. 2009. 12. 006. 10. 1111/j. 1469-8137. 2005. 01401. x. 10. 1038/ngeo1009. 10. 1093/forestry/cps003. 2. Acad Sci. 2010;107:10938–10942 2890735 10. 1073/pnas. 0912421107. 10. 1111/j. 1469-8137. 1994. tb02976. x. 10. 1016/j. chemosphere. 2012. 03. 019. 10. 1007/s11104-013-1630-3. 10. 1016/S0953-7562(09)80936-2. 10. 1111/j. 1469-8137. 1991. tb00004. x. 10. 1890/04-1254. 9373. 10. 1139/x06-063. 10. 1111/j. 1365-294X. 1993. tb00005. x. 10. 1016/j. soilbio. 2011. 03. 017. 10. 1002/(SICI)1521-4028(199807)38:3<197::AID-JOBM197>3. 0. CO;2-W. 10. 1111/j. 1462-2920. 2011. 02550. x.

Output: pass


Input: Claim: Some amphibians, like frogs, undergo metamorphosis from an aquatic larval stage to a terrestrial adult form. [SEP] Text: The mechanism that controls ontogenetic changes in CYP27C1 expression, and thus, the switch from A2 to A1 chromophore (or vice versa) is not known but appears to involve thyroid hormone signaling. In most teleost fishes that have been studied, the application of thyroid hormone results in an increase in A2 chromophore, but in bullfrog, it results in a reduction in A2 [79]. In frogs, application of thyroid hormone can trigger or accelerate metamorphosis, which in turn results in the shift from A2 to A1 in some species but not others [34] raising the question of how this difference among species is controlled. Additional studies quantifying ontogenetic variation in chromophore usage and CYP27C1 expression across a greater diversity of frogs may provide a better understanding of the underlying mechanisms and how this trait is associated with changes in visual ecology across species. Light exposure can also affect the proportion of A1 to A2 chromophore in the eye. This pattern has been demonstrated as a reversible change in tadpoles of several species of Lithobates, where exposure to darkness over extended periods (weeks to over a month) decreased the proportion of A2 chromophore, which could be reversed to near normal levels in as little as 24–48 h of constant illumination [81, 84]. We found that CYP27C1 expression was significantly reduced in dark-exposed compared to light-exposed tadpoles (12 h of exposure), which suggests CYP27C1 expression is light-dependent in tadpoles and that reduced CYP27C1 expression upon dark exposure results in a lower proportion of A2-based visual pigments. A potential mechanism for light-dependent expression of CYP27C1 is unknown, but previous experiments suggest this response can be localized to a single eye. Specifically, Bridges [81] found that exposing tadpoles to light after a period of darkness resulted in an increase in A2 in unobstructed eyes, but not in eyes that were covered and thus unexposed to light. The functional benefit of this change may be related to the lower dark noise (thermal activations in the absence of photon absorbance) of A1 pigments compared to A2 pigments, resulting in higher light sensitivity of A1 pigments [85].

Output: corroborate


Input: Claim: Personalized nutrition guarantees that you can eat anything without gaining weight, as long as it fits your genetic profile. [SEP] Text: (A) Significant improvements are observed in various aspects of physical and mental health (SF-36), sleep quality (PSQI), depressed mood (IDS-SR), and self-efficacy (SWE) in participants of the EG (colored columns), but hardly among CG participants (gray columns). Scales are either upward or downward, depending on whether low or high scores on the questionnaires mean subjectively good or poor well-being. (B) The chronotype of EG and CG participants did not change during the study. 2-way repeated-measures ANOVA with Bonferroni post hoc test comparing CG and EG during the exploration or intervention phase and T0-T1 and T1-T2 within groups, * p ≤ 0. 05, ** p ≤ 0. 01, *** p ≤ 0. 001, **** p ≤ 0. 0001. CG: n=33; EG: n=67. Detailed statistics in Tab. S3. 3. DiscussionIn our study, we show that increased regularity of the Zeitgeber food can lead to a significant reduction in body weight. Although the diary entries of some participants show that they changed their energy intake and also the food composition of fat, carbohydrates and proteins during the study, the observed weight loss is not related to these changes. Related results have already been shown in mice, although here with a restriction to the entire active phase rather than specific eating times. Not surprisingly, mice gain weight and develop diabetes-like states under a high-fat diet [17]. It is surprising, however, that the negative physiological consequences of the high-fat diet can be almost completely prevented if the mice consume the equivalent amounts of high-fat food exclusively during their activity phase and do not receive any food during their sleep phase [17, 25]. In our study, an increase in the regularity of lunch, and somewhat more strongly that of dinner, is related to weight loss, which to some extent contrasts with previously published data in which increased regularity of breakfast in particular, and not so much that of dinner, was identified as a predictor of weight loss [26]. Besides increased regularity, our intervention has additional effects on eating behavior, such as shortening the hours in which food is eaten, which in our study is not related to weight loss.

Output: contrast


Input: Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: 10. 1023/A:1024719607740. 10. 1111/j. 1574-6941. 2002. tb00915. x. 9. 10. 1007/s10021-008-9186-4. 10. 1111/j. 1365-2486. 2011. 02627. x. 10. 1016/j. mycres. 2007. 11. 008. 10. 1111/j. 1469-8137. 2006. 01742. x. 10. 1038/35035065. 10. 1175/JCLI-D-12-00089. 1. 10. 1046/j. 1469-8137. 2002. 00417. x. 10. 1093/bioinformatics/btq003. 10. 1139/x97-160. 10. 1016/j. apsoil. 2012. 01. 010. 10. 1111/j. 1365-2435. 2010. 01699. x. 10. 1371/journal. pone. 0010971. 10. 4141/P05-164. 10. 1111/j. 1574-6941. 2006. 00166. x. 10. 1016/j. soilbio. 2011. 01. 022. 10. 1111/j. 1469-8137. 2006. 01957. x. 10. 1639/0007-2745(2003)106[0080:]2. 0. CO;2. 10. 1093/treephys/21. 2-3. 71. 10. 1016/0038-0717(91)90193-N. 10. 1111/j. 1469-8137. 2006. 01936. x. 10. 1016/j. soilbio. 2004. 02. 017. 10. 1038/nature06556. 10. 1038/nature08867. 6. 0. 2011 MjM Software:. 10. 1007/s00572-005-0011-z. 10. 1017/CBO9780511977022. 10. 1073/pnas. 261555198 64936. 10. 1016/j. fgb. 2009. 02. 001. 10. 1016/j. funeco. 2010. 05. 002. 10. 1073/pnas.

Output: pass


Input: Claim: Some amphibians, like frogs, undergo metamorphosis from an aquatic larval stage to a terrestrial adult form. [SEP] Text: Thus, exposure to dark conditions could result in increased overall light sensitivity of the tadpole through reduced expression of CYP27C1, which in turn reduces the production of A2 chromophore and, correspondingly, increases the proportion of the higher-sensitivity A1 pigments. This interpretation is perhaps confounded by the observation that some teleost fishes have the opposite reaction to dark exposure, where the proportion of A2 pigment increases [34], although at least one teleost species has the same response as tadpoles [86]. This variation suggests there may be other factors beyond spectral tuning and light sensitivity that influence chromophore usage. Visual opsins and phototransduction genes are differentially expressed between life stagesDifferential expression of visual opsins and phototransduction genes is a second approach that organisms can employ to adapt the sensitivity of their visual system to changes in the light environment. Studies investigating the evolutionary and ecological context of this particular strategy in vertebrates have largely been restricted to the visual opsins of teleost fishes, which tend to have many more (duplicated) copies of these genes than do tetrapods [40]. Some teleost species express only a subset of their total visual opsin repertoire during a particular life stage, which is likely beneficial when larval habitat and associated traits, such as foraging behavior, differ from those of adults [40]. Most frog species make even more dramatic transitions in habitat and foraging behavior across ontogeny, but with far fewer opsins to choose from, their ability to use distinct opsins for larval and adult vision is likely more constrained. Despite this, we found differential expression between tadpoles and adults in two of their four visual opsin genes (SWS2 and LWS). In frogs and salamanders, SWS2 is expressed in blue-absorbing “green” rods (SWS2 rods), a unique type of rod not found in other vertebrates that, at least in some species, enables color vision at scotopic light levels when cones are inactive [87]. The increased expression of SWS2 in juvenile leopard frogs suggests an increased proportion of SWS2 rods in the retinas of juveniles relative to tadpoles, which may reflect increased reliance on nocturnal color vision in terrestrial life stages.

Output: corroborate


Input: Claim: Personalized nutrition guarantees that you can eat anything without gaining weight, as long as it fits your genetic profile. [SEP] Text: This is similar to the principle of 16:8 intermitted fasting or time-restricted eating (TRE), in which meals are taken only specific time window, yet at unspecified times during that period. The effects of these protocols is mixed and often less pronounced, as less [21, 23, 27] weight loss or a longer period is required to achieve similar results [22] than in our study - with the caveat that more overweight and older participants participated in these studies than in ours. However, other studies have also explored the effect of restricting individual meals to specific times. In mice, restricting the same amount of high-fat chow to two times per day reduces the development of obesity [28]. And in humans, restricting meals to three fixed, uniform times leads to similar weight loss like we observed in our study - but in combination with calorie reduction and standardized food [29]. The fact that our participants lost weight to a similar extent despite free choice of meals could be due to the individual tailoring of meal schedules. It is true that our data show that scheduling single meals to supposedly circadian optimal eating times of the participants is not essential for successful weight loss. Circadian clocks can flexibly adjust to Zeitgebers and it is apparently more important to choose a time when individuals (have to) eat particularly frequently than the exact genetically determined eating time. However, our data still show that personalization of meal schedules is nevertheless useful. First, depending on the individual chronotype of the participants, their mealtime windows were earlier or later in the day. And those for whom the intervention optimized this relationship were particularly effective at losing excess weight. Second, if the schedule is designed to prevent large jumps between meals, especially dinner, on workdays and work-free days, weight loss is more successful. Since food serves as a Zeitgeber for a large number of tissues, including several brain regions, it can be hypothesized that regular eating not only has a positive effect on body weight, but also on other aspects of well-being. A previous study by Panda et al. [18] has already shown that shortening the eating interval to 10-12 hours per day has a positive effect on the general well-being of the participants. Similarly, in our study, we also found significant improvements in different aspects of subjective well-being over the course of the study, specifically in physical and mental health, sleep quality, and self-efficacy.

Output: contrast


Input: Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: 1006463107. 10. 1111/j. 1461-0248. 2011. 01611. x. 10. 1007/s00572-011-0379-x. 10. 5194/bg-9-2099-2012. 10. 1016/j. soilbio. 2006. 04. 038. 2. Ecol Lett. 2012;15:1042–1049 10. 1111/j. 1461-0248. 2012. 01827. x. 10. 1007/s11104-008-9766-2. 10. 1016/j. mimet. 2004. 04. 001. 10. 1111/j. 1574-6941. 2007. 00375. x. 45. 10. 1111/j. 1462-2920. 2012. 02736. x. 10. 1186/1471-2148-8-50. 10. 1016/S0038-0717(02)00074-3. 10. 1093/forestry/50. 2. 113. 10. 1128/AEM. 01541-09. 10. 1038/nature10386. 10. 1038/ismej. 2012. 11. 10. 1016/j. soilbio. 2009. 10. 014. 10. 1111/j. 1461-0248. 2008. 01245. x. 10. 1016/S0929-1393(03)00002-7. 10. 1111/j. 1574-6941. 2012. 01343. x. 10. 1111/j. 1365-2435. 2008. 01402. x. 10. 1016/j. soilbio. 2012. 10. 004. 10. 1111/j. 1469-8137. 2012. 04217. x. 10. 1007/s00374-010-0440-5. 10. 1016/j. soilbio. 2005. 09. 006. 10. 1007/s00572-011-0416-9. 10. 1111/1574-6976. 12001. 10. 1007/s00374-009-0413-8. 10. 1016/j. apsoil. 2012. 02. 017. 10. 1111/j. 1469-8137. 2010. 03324. x. 10.

Output: pass


Input: Claim: Araneology focuses on the study of spiders and their relatives within the arachnid class. [SEP] Text: " Line 281: in the arachnological literature, the expression "true spiders" is used mostly to the Araneomorphae and not to the order as a whole. Line 282: "(Platnick & Raven, 2013)" -- I suggest to change this citation for the most recent version of the Catalogue ( Line 284: ". . . and the ability to produce silk" -- at least two other arachnid groups contain species that produce silk: pseudoscorpions and mites. Thus, you should to re-phrase this sentence. Line 288: "Spiders are typically characterised. . . " Line 292: are you really referring to the "Tetragnathidae" or to the "Nephilidae"? Lines 293-294: another well-reported case of reversed SSD in spiders occurs in the genus Allocosa from Uruguay. In species of this genus, males are larger than females and there are several behavioral traits that indicate sex-role reversal. Lines 306-318: I suggest to remove this paragraph because pedipalps in male spiders are sexual organs, thus you are talking about primary and not secondary sexual dimorphism. If you decide to mention all cases of primary sexual dimorphism in all arachnid orders, you will need to talk about spermatophore and penis morphology. As far as I understand, this is not the main goal of the manuscript. Thus, for the sake of consistency, you should not include sexual dimorphism related to pedipalp morphology in spiders. The only exception, according to my view, is the example of Allocosa males, which have sexually dimorphic digging structures on their pedipalps. Line 350: "conflict" -- I think the best word here is "contest". Please change it throughout the entire manuscript. Line 351: " conflict" -- I suggest to change this word for "male-male competition" or "intrasexual selection". Line 360: "and" -- non-italic. Line 387: "Parisitiformes" Lines 424-425: "The metric. . . " Lines 427: "Cranaidae and Oncopodidae" Lines 456-457: ". . . suggesting that chemical secretions may also play a role in warding off rival males" -- Although it is possible, I have never seen males releasing secretion during intrasexual fights.

Output: corroborate


Input: Claim: Personalized nutrition guarantees that you can eat anything without gaining weight, as long as it fits your genetic profile. [SEP] Text: This shows that adhering to daily structured mealtimes can improve not only metabolic but also other physical and also psychological levels of health. There are several explanatory approaches for why increased meal regularity can lead to weight loss despite equal caloric intake. For example, circadian clocks influence the composition of the microbiome, which regulates metabolic balance and body weight [30–34]. Additionally, circadian clocks help to anticipate mealtimes and provide the necessary digestive components in advance of food intake in advance [35–38]. Accordingly, the number of rhythmic genes in the liver of mice increases from ∼350 to ∼3,000 when the animals can follow their natural feeding rhythm and even to ∼5,000 when the feeding time is restricted to a certain period of time [39]. 3. 1. LimitationsHowever, in our study, we did not collect metabolic parameters that could provide mechanistic explanations for the observed weight loss. Therefore, the assumption of an optimized metabolism remains speculation. Another limitation of the study is the self-assessment of key data on body weight, eating times, and food composition. Body weight could not be collected in our clinic under supervision because of the Covid-19 pandemic. Regarding food intake, some participants underreported during the study, as indicated by unrealistically low kJ intakes. However, the individual reporting behavior of each participant remained largely the same during the exploration and intervention phases, so underreporting is not indicative of a change in eating behavior and, conversely, the observed kJ differences are likely due to actual changes in eating behavior. In addition, in the remaining evaluable 100 study participants, there was a significant difference in baseline body weight and BMI between CG and EG. However, even if CG participants had been heavier from the start, it cannot be assumed that the applied sham treatment with an eating window of 18 hours during wake time would have had a stronger effect. Second, those subjects in the EG group whose baseline BMI was similar to those of the CG subjects lost significant weight during the intervention, while CG participants did not. Taking these two arguments into account, it cannot be assumed that a floor effect, in which the CG participants cannot lose any more weight due to a lower baseline weight, is the reason for the lack of weight loss in the CG. Lasty, studies show that even much larger baseline BMI differences do hardly affect the success of weight loss programs [40, 41], so we assume that this also applies to our study.

Output: contrast


Input: Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: Create a new account user Can't sign in? Forgot your username? Enter your email address below and we will send you your username Email* the address matches an existing account you will receive an email with instructions to retrieve your username close | or * Password* Forgot password? Reset it here Keep me logged in All fields with * are mandatory Email* All fields with * are mandatory Already have an account? Login here password must have 8 characters or more and contain 3 of the following: a lower case character, an upper case character, a special character or a digit password has been changed Can't sign in? Forgot your password? Enter your email address below and we will send you the reset instructions Email* the address matches an existing account you will receive an email with instructions to reset your password the verification code Cancel Congrats! has been verified close 10. 1139/x83-031 Get AccessContentsof Forest Research, Number 2April 19831983. Contribution of mycorrhizae and soil fungi to nutrient cycling in a Douglas-fir ecosystem. of Forest Research. 13(2): 219-232. Export 1. Species-specific reliance of trees on ectomycorrhizal fungi for nitrogen supply at an alpine treeline Go to 2. Fungi rather than bacteria drive early mass loss from fungal necromass regardless of p3. Thinning effects on biomass and element concentrations of roots in adjacent hornbeam and oak stands in Istanbul, to 4. Evidence for a fungal loop in shrublands Go to 5. The Rhizosphere/to 6. Accounting for to Discrepancies in to 7. Rapid changes in the chemical composition of degrading ectomycorrhizal fungal necromass Go to 8. to for Global Change: and the to 9. Effects of bedrock type and soil chemistry on the fine roots of European beech – A study on the belowground plasticity of trees Go to 10. () Go to 11. Harvesting Douglas-fir Activity and Go to 12. The effect of environmental contamination on the community structure and fructification of ectomycorrhizal fungi Go to 13. Go to 14. Contribution of understorey vegetation and soil processes to boreal forest isoprenoid exchange Go to 15. Second‐generation molecular understanding of mycorrhizas in soil ecosystems Go to 16. Available for Go to 17.

Output: pass


Input: Claim: Spiders have unique adaptations, such as hydraulic pressure in their legs, which helps them move. [SEP] Text: & Sanchez, N. E. (2013). Short and long-term effects of three neurotoxic insecticides on biological and behavioural attributes of the orb-web spider Alpaida venilae (Araneae, Araneidae): implications for IPM programs. — Ecotoxicology 22: 1155-1164. )| falseSearch 26. Bergthaler, G. J. (1995). The cocoon of Argiope bruennichi (Scopoli, 1772) — a SEM study. — In: 15th European collequium of arachnology (Ruzicka, V. , ed. ). Institute of Entomology, Ceske Budejovice, p. 22-26. )| falseSearch 3212. Blamires, S. J. (2010). Plasticity in extended phenotypes: orb web architectural responses to variations in prey parameters. — J. Exp. Biol. 213: 3207-3212. )| falseSearch 279. Bridge, A. P. , Elwood, R. W. & Dick, J. T. A. (2000). Imperfect assessment and limited information preclude optimal strategies in male-male fights in the orb-weaving spider Metellina mengei. — Proc. Roy. Soc. Lond. B: Biol. Sci. 267: 273-279. )| falseSearch 193. Buchli, H. H. R. (1969). Hunting behaviour in the Ctenizidae. — Am. Zool. 9: 175-193. )| falseSearch 1235. Caccone, A. (1985). Gene flow in cave arthropods: a qualitative and quantitative approach. — Evolution 39: 1223-1235. )| falseSearch 7611. Chiavazzo, E. , Isaia, M. , Mammola, S. , Lepore, E. , Ventola, L. , Asinari, P. & Pugno, N. M. (2015). Cave spiders choose optimal environmental factors with respect to the generated entropy when laying their cocoon. — Sci. Rep. 5: 7611. )| falseSearch 1051. Crespo, L. C. , Boieiro, M. , Cardoso, P. , Aguiar, C. A. S. , Amorim, I. R.

Output: pass


Input: Claim: Personalized nutrition guarantees that you can eat anything without gaining weight, as long as it fits your genetic profile. [SEP] Text: During the course of the study, there were some drop-outs in both groups. Importantly, these did not differ in baseline weight from the completers, which is why it can be ruled out that the intervention was not effective in a particular BMI group. Rather, the subjects who dropped out were those who either could not continue due to illness or did not adhere to the meal plan. However, the inclusion of drop-outs in the analysis of weight progression does not fundamentally change the results. 3. 2. ConclusionIn summary, our data show that the increase of regularity of meals to a period of 90 min for each meal promotes a significant reduction of body weight and a significant increase of well-being within short time. Importantly, the successes achieved do not seem to be related to a reduction in calories, a change in food composition, or other eating behaviors. Additionally, we believe that this intervention poses hardly any health risks since it is most likely solely based on the optimization of metabolic processes. On the contrary, the strong increase in general well-being during the study rather indicates an improvement in health on many different levels. 4. Methods4. 1. Experimental approachThe study was a randomized controlled intervention trial with repeated measures investigating the effect of regularity of mealtimes on body weight and parameters related to overall well-being. Participants were blinded to the group assignment in that both control and experimental subjects were equally informed to participate in an intervention. The study was carried out at the Clinic for Psychiatry and Psychotherapy of the University (LMU), Munich, Germany. The study is registered at the with the trial number DRKS00021419 and was approved by the of the LMU. 4. 2. ParticipantsThe participants were recruited across Germany via flyers at universities, fitness studios, adult education centers, pharmacies, grocery stores, and via Facebook® between September 2020 and August 2021. Those interested were able to contact the study staff by phone, email, or by making an entry in an online calendar tool. Participants had to be between 18-65 years old and have a BMI ≥ 22 kg/m². A requirement for participation in the study was that no other diet was concurrently followed, and that no medication was being taken regularly that could influence appetite or weight. No participants were included who knowingly suffer from a metabolic, mental, or addictive disorder. Further exclusion criteria were pregnancy, blindness, bedriddenness, and dependence on assistance with eating.

Output: contrast


Input: Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: with Pollutants and Go to 18. 19. Resource allocation in an annual herb: Effects of light, mycorrhizal fungi, and defoliation Go to 20. The decomposition of ectomycorrhizal fungal necromass Go to 21. Mycorrhizal Fungi: Role in the Solubilization of to 22. and Microbes: A for to 23. Quantitative assessment of the differential impacts of arbuscular and ectomycorrhiza on soil carbon cycling Go to 24. Initial melanin and nitrogen concentrations control the decomposition of ectomycorrhizal fungal litter Go to 25. Simulating ectomycorrhizal fungi and their role in carbon and nitrogen cycling in forest ecosystemsG. Deckmyn, A. Meyer, M. M. Smits, A. Ekblad, T. Grebenc, A. Komarov, and H. to 26. Net primary production of ectomycorrhizas in a California forest Go to 27. Seasonal carbohydrate dynamics and growth in Douglas-fir trees experiencing chronic, fungal-mediated reduction in functional leaf area Go to 28. Determining place and process: functional traits of ectomycorrhizal fungi that affect both community structure and ecosystem function Go to 29. Functional diversity and resource partitioning in fungi associated with the fine feeder roots of forest trees Go to 30. Fine root biomass and dynamics in beech forests across a precipitation gradient – is optimal resource partitioning theory applicable to water‐limited mature trees? Go to 31. Nutrient concentrations in stumps and coarse roots of Norway spruce, Scots pine and silver birch in Sweden, Finland and to 32. Transfer of 14C-photosynthate to the sporocarp of an ectomycorrhizal fungus Laccaria amethystina Go to 33. Mycorrhizal colonization does not affect tolerance to defoliation of an annual herb in different light availability and soil fertility treatments but increases flower size in light-rich environments Go to 34. The role of chitin in the decomposition of ectomycorrhizal fungal litter Go to 35. Six‐year monitoring of pine ectomycorrhizal biomass under a temperate monsoon climate indicates significant annual fluctuations in relation to climatic factors Go to 36. of Ectomycorrhiza in to 37.

Output: pass


Input: Claim: Bats play an important role in pollination and seed dispersal for many tropical plants. [SEP] Text: edited by Theodore H. Fleming, Liliana M. Dávalos and Marco A. R. of Chicago Press, 2020Cloth: 978-0-226-69612-6 | Electronic: 978-0-226-69626-3DOI: 10. 7208/chicago/9780226696263. 001. 0001 of (cloth, ebook) DeGruyter Multi-eBooks (formerly NetLibrary) (UPSO) more than two hundred species distributed from California through Texas and across most of mainland Mexico, Central and South America, and islands in the Caribbean Sea, the Phyllostomidae bat family (American leaf-nosed bats) is one of the world’s most diverse mammalian families. From an insectivorous ancestor, species living today, over about 30 million years, have evolved a hyper-diverse range of diets, from blood or small vertebrates, to consuming nectar, pollen, and fruit. Phyllostomid plant-visiting species are responsible for pollinating more than five hundred species of neotropical shrubs, trees, vines, and epiphytes—many of which are economically and ecologically important—and they also disperse the seeds of at least another five hundred plant species. Fruit-eating and seed-dispersing members of this family thus play a crucial role in the regeneration of neotropical forests, and the fruit eaters are among the most abundant mammals in these habitats. Coauthored by leading experts in the field and synthesizing the latest advances in molecular biology and ecological methods, is the first overview in more than forty years of the evolution of the many morphological, behavioral, physiological, and ecological adaptations in this family. Featuring abundant illustrations as well as details on the current conservation status of phyllostomid species, it is both a comprehensive reference for these ecologically vital creatures and a fascinating exploration of the evolutionary process of adaptive radiation. . Fleming is professor emeritus of biology at the University of Miami, where he worked for thirty years. Among his recent books are of Life, both published by the University of Chicago Press, and Is an Island. Liliana M. Dávalos is professor of conservation biology at University. She is coeditor of of Cocaine and coauthor of the 2016 Report. Marco A. R.

Output: corroborate


Input: Claim: Personalized nutrition guarantees that you can eat anything without gaining weight, as long as it fits your genetic profile. [SEP] Text: Special emphasis was placed on the participants’ ability to understand the details of the study and to give written consent to participate. 4. 3. Study ProtocolEach participant completed a 12-week program, which consisted of the following steps (Fig. S1C):4. 3. 1. AssessmentAt the introductory session, the eligibility for possible participation in the study was determined and demographic data was collected. Then, suitable participants received a general introduction to the study, which included the theoretical background of the study and a detailed explanation of the study procedure. Subsequently, the participants were informed about their rights, the voluntary nature of their participation in the study, and data protection regulations. All participants had to sign an informed consent form for study participation and for the recording and use of their data. Participants weighed and measured their height themselves while study staff connected with them online via camera. Afterwards, the participant received questionnaires to fill out. This initial data assessment is referred to as T0 in the analysis. 4. 3. 2. Two-PhaseThe introduction was followed by a two-week exploration phase in which the participants were asked to follow their usual eating habits and to document all caloric events (main meals, snacks, caloric drinks) using the smartphone application “FDDB” as accurately as possible. Based on this data, the personalized nutritional schedule was then developed. Data from the FDDB smartphone application also allowed us to calculate individual caloric intake along with the ratio of consumed macronutrients for each day during the study. Additionally, the participants weight was measured again. The end of the exploration phase is called T1 in the analysis. 4. 3. 3. Six-Phase(EG): Following the exploration phase, the participants received their personalized mealtime schedule, which was prepared beforehand by the study staff based on the meal diary of the exploration phase. Together with the participants, the nutritional behavior of the last two weeks was reviewed and analyzed. Special attention was paid to irregularities in mealtimes and to times of day when food was eaten particularly frequently. In this way, participants were made aware that they eat irregularly, but that there are nevertheless times when their internal clock frequently triggers hunger. This was followed by a six-week intervention phase, in which the participants were instructed to have their meals only at times according to the mealtime schedule. Participants were explicitly told that they were not restricted in their choice and quantity of food.

Output: contrast


Input: Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: Phylogenetic diversity of non-nodulating Rhizobiumâ associated with pine ectomycorrhizae Go to 38. Biomass and morphology of fine roots in temperate broad-leaved forests differing in tree species diversity: is there evidence of below-ground overyielding? Go to 39. Influence of on in Go to 40. Effects of experimental soil frost on the fine‐root system of mature Norway spruce Go to 41. Root dynamics in sprouting tanoak forests of southwestern OregonGlenn R. Ahrens and Go to 42. Arbuscular Mycorrhizae: A for Go to 43. Interactions of Fungi and Radionuclides in to 44. 45. Environmental change and carbon limitation in trees: a biochemical, ecophysiological and ecosystem appraisal Go to 46. Relating fine root biomass to soil and climate conditions in the Go to 47. Hydraulic lift may buffer rhizosphere hyphae against the negative effects of severe soil drying in a savanna Go to 48. Integrating ectomycorrhizal fungi into quantitative frameworks of forest carbon and nitrogen cycling Go to 49. Turnover as a for into to 50. to 51. Decomposition and nutrient release from fresh and dried pine roots under two fertilizer regimesLudovici and to 52. Long‐term interval burning alters fine root and mycorrhizal dynamics in a ponderosa pine forest Go to 53. 54. Supply‐side controls on soil respiration among Oregon forests Go to 55. The impact of ectomycorrhiza formation on monosaccharide transporter gene expression in poplar roots Go to 56. Distribution of protozoa in scots pine mycorrhizospheres Go to 57. Ectomycorrhizal Colonization, Biomass, and Production in a in Response to Elevated CO2 Go to 58. to 59. Role of in Determining Douglas-fir Resistance to Defoliation by the Budworm (Lepidoptera: Tortricidae) Go to 60. Synopsis and Outlook to the to 61. Nested PCR detection of Archaea in defined compartments of pine mycorrhizospheres developed in boreal forest humus microcosms Go to 62.

Output: pass


Input: Claim: Bats play an important role in pollination and seed dispersal for many tropical plants. [SEP] Text: We discuss the apparent paradox of these generalist predators: bats that can be classified as dietary generalists, broadly overlapping with one another in the prey they consume, but often possessing quite specialized foraging adaptations and distinct behavioral strategies for prey finding. To untangle the puzzle of this understudied and historically elusive group of generalist predators, we examine the influences of diet breadth on hunting behavior, spatial distribution, conservation concern, and morphology. (pages 239 - 256)This 15. - John W. Hermanson, Gerald G. CarterDOI: 10. 7208/chicago/9780226696263. 003. 0015[adaptation;cooperation;Desmodus;Diaemus;Diphylla;morphology]The common vampire bat Desmodus rotundus, white-winged vampire bat Diaemus youngi, and hairy-legged vampire bat Diphylla ecaudata are the only mammals that feed exclusively on blood. Their blood-feeding lifestyle shapes virtually every aspect of their biology. Adaptations linked to blood-feeding include changes to morphology (e. g. dramatically reduced dentition, unique terrestrial and arboreal locomotion), physiology (e. g. anticoagulants in their saliva, an ability to rapidly eliminate water from blood meals), sensory ecology (e. g. infrared thermoperception, specialized low-frequency hearing), and social behavior (cooperative food sharing). There is even evidence for an adaptive loss of a cognitive trait: vampire bats lack the otherwise ubiquitous phenomenon of taste aversion learning, presumably because blood from live prey is never spoiled. From an evolutionary perspective, the traits that vampire bats have both gained and lost illustrate adaptive tradeoffs and the link between form and function. Vampire bats are the primary reservoir for bovine rabies virus in Central and South America, so understanding their biology has implications for agricultural development and public health. (pages 257 - 272)This 16. and Evolution of - : 10. 7208/chicago/9780226696263. 003. 0016[bat pollination;chiropterophily;nectarivory;New World;specialization]One-quarter (56) of the species of Phyllostomidae have adapted to a primarily nectarivorous diet and serve as pollinators for hundreds of species of flowering plants.

Output: corroborate


Input: Claim: Personalized nutrition guarantees that you can eat anything without gaining weight, as long as it fits your genetic profile. [SEP] Text: During the intervention phase, participants should continue to document all caloric events using the FDDB App. In addition, participants were asked to weigh themselves weekly to measure their progress. Halfway through the intervention phase, participants were contacted at least once by telephone to clarify possible questions and maintain compliance. Further, in case participants stopped making entries in their FDDB diary for two or more days, they were contacted to ask for reasons and to reinstate compliance again. (CG): In principle, participants in the CG followed the same procedure. However, they were given a sham treatment, for which they were asked to restrict their meals to a freely chosen 18-hour time window per day, during which they could eat what they wanted and, above all, when they wanted. It can be assumed that restricting the eating time window to 18 hours should have no effect on weight, since such a long eating time window is hardly ever exceeded by most people anyway [18] and therefore hardly any change in eating behavior is to be expected. 4. 3. 4. AssessmentAt the end of the intervention phase, the participants were asked to fill out the same questionnaires as at the introduction session. Additionally, weight was measured again. This data assessment is called T2 in the analysis. 4. 3. 5. Follow-up AssessmentFour weeks after completion of the study, the study staff contacted the participants again by telephone to inquire about their current weight and to obtain information about whether the participants had voluntarily continued the program after the end of the intervention phase. If the participants indicated that they did not continue the program, possible reasons were evaluated, and suggestions were received on how the current protocol could be improved to make it more attractive for permanent implementation in everyday life. Participants of the control group were informed at this point about their allocation and the actual question of the study. The final data assessment is called T3. 4. 3. 6. Restrictions due to the Covid-19 pandemicDue to restrictions imposed by Covid-19, the study was carried out online. Data collection and communication was exclusively done via email, (Communications, Inc. ), Facebook (Meta Platforms), or telephone. 4. 4. Assessment of General Well-BeingTo measure whether restricting meals to times when we believe the circadian system triggers hunger leads to an increase in general well-being, questionnaires were collected to measure sleep quality, physical well-being, self-efficacy, and depressive mood.

Output: contrast


Input: Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: Spatial distribution of sporocarps and the biomass of ectomycorrhizas of Suillus pictus in a Korean pine ( Pinus koraiensis ) stand Go to 63. Biomass of in Relation to and Fertility, Climate, Age and to 64. in with an Emphasis on Go to 65. Methods in Study of Degradation of Go to 66. Responses of decomposer community to root-isolation and addition of slash Go to 67. Contrasting effects of microbial partners in the rhizosphere: interactions between seedlings (Picea abies Karst. ), mycorrhiza (Paxillus involutus (Batsch) Fr. ) and naked amoebae (protozoa) Go to 68. Low molecular weight organic acids and fatty acids in root exudates of two Lupinus cultivars at flowering and fruiting stages Go to 69. Belowground carbon allocation of Douglas-firand to 70. Dynamics of nitrogen and phosphorus concentrations of fine roots in a mixed forest ofCunninghamia lanceolata andTsoongiodendron odorum Go to 71. Aboveground biomass and nutrient content of five Douglas-fir stands in to 72. Seasonal change in phosphorus content of Pinus strobus—Cenococcum geophilum ectomycorrhizae Go to 73. Changes in soil acidity and organic matter following the establishment of conifers on former grassland in Go to 74. Estimating root respiration, microbial respiration in the rhizosphere, and root-free soil respiration in forest soils Go to 75. Analysis of some direct and indirect methods for estimating root biomass and production of forests at an ecosystem level Go to 76. 77. Seasonal variation in protein, ergosterol and chitin in five morphotypes of Pinus sylvestris L. ectomycorrhizae in a mature Swedish forest Go to 78. Ecology and 15N Natural Abundance: Limits to Interpretation for with from a to 79. Rhizosphere carbon flow in trees, in comparison with annual plants: the importance of root exudation and its impact on microbial activity and nutrient availability Go to 80. High rates of nitrification and nitrate turnover in undisturbed coniferous forests Go to 81.

Output: pass


Input: Claim: Bats play an important role in pollination and seed dispersal for many tropical plants. [SEP] Text: Here we review the ecology and evolution of these bats and the flowers that rely on them. A suite of adaptations allows them to feed from flowers efficiently, including elongated rostrums, long, extensible tongues, reduced dentition, well-developed olfaction and spatial memory, and the ability to hover. These adaptations evolved independently in two phyllostomid subfamilies, the Lonchophyllinae and the Glossophaginae, which differ profoundly in their tongue morphology and nectar-feeding behavior: glossophagines have mop-like tongues with papillae covering the distal tip and lap nectar during flower visits, while lonchophyllines have straw-like tongues with papillae-lined grooves along the side and pull nectar through these grooves while keeping the tongue immersed in the nectar. Flowers adapted to bat pollination tend to have dull colors, strong scents, copious pollen and nectar production, and particularly well-exposed flowers. Despite heavy reliance on these flowers, nectar bats will often feed opportunistically on insects and fruit as well, particularly during times of the year when flowers are scarce. However, dietary data are still lacking for many species. (pages 273 - 294)This 17. The Frugivores: Evolution, Functional Traits, and in - Romeo A. Saldaña-Vázquez, Theodore H. FlemingDOI: 10. 7208/chicago/9780226696263. 003. 0017[Carolliinae;climate change;foraging behavior;frugivory;seed dispersal;Stenodermatinae]Frugivory is a hallmark of the Phyllostomidae, and frugivorous species in subfamilies Carolliinae and Stenodermatinae are among the most common mammals throughout the Neotropics. In this 18. Roosting Ecology: of - Armando Rodríguez-DuránDOI: 10. 7208/chicago/9780226696263. 003. 0018[bat ecology;Noctilionoidea;Phyllostomidae;roosts;roosting behavior]In this 19. - Theodore H. Fleming, Angela M. G. MartinoDOI: 10. 7208/chicago/9780226696263.

Output: corroborate


Input: Claim: Personalized nutrition guarantees that you can eat anything without gaining weight, as long as it fits your genetic profile. [SEP] Text: A scatterplot was also created for participants of the CG, but they were not provided with meal timings; instead, an 18-hour time window for meals was established with them. 4. 7. Statistical AnalysesStatistical analyses were performed with SPSS 24, Python, Graph9. 2. 0, and R. Details about statistical tests used for specific experiments are indicated in the main text and the corresponding figure legends. 4. 7. 1. Score (MTVS)A Python script was written to generate the MTVS, which is calculated from the deviation of each caloric event from the specified mealtime closest to the event. Similar to a previous study, each meal was given a score value based on the time deviation of the specified meal in minutes: 1 = +/-0-15 min, 2 = +/- 16-30 min, 3 = +/- 31-45 min, 4 = +/- 46-60 min, 5 = +/- 61-75 min, 6 = +/- 76-90 min, 7 = +/- 91-105 min, 8 = +/- 106-120 min, 9 = +/- 2-3 h, 10 = +/- 3-4 h, 11 = over +/- 4 h [20]. Since the participants were given a 60-minute time slot for each meal, a score of up to 2 is considered very regular. Based on individual score values of each meal, an average score value can be calculated for each individual day, for each individual week or for the entire period, i. e. , a daily, a weekly, or a total score. Similarly, daily, weekly, and total scores can be calculated for each type of meal, i. e. , breakfast, lunch, dinner. 4. 7. 2. and randomizationFor the sample size calculation, we assumed an average of 2. 5 kg of body weight loss, based on TRE studies [18, 19, 21–23], as we are not aware of any other study in which meal times were personalized and scheduled. The reported standard deviation for body weight loss in such studies is 3. 2 [19]. Randomization was to be 2:1 (EG:CG) because no significant change in body weight was expected from the control treatment. The randomized assignment was carried out using a continuous list prepared by the study supervisor with the Excel® randomization function. Participant enrollment and assignment was carried out by study staff. On this basis a large effect size d = 0.

Output: contrast


Input: Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: The effects of live and dead roots on soil fungi in spodosolic soils of the to 82. Deposition and the Mycorrhizae of Go to 83. Review of root dynamics in forest ecosystems grouped by climate, climatic forest type and species Go to 84. Rhizodeposition under ambient and elevated CO2 levels Go to 85. Efficiency of by to 86. Allocation of 14 C‐carbon in ectomycorrhizal willow Go to 87. The effects of alkalizing compounds on fine‐root growth in a Norway spruce stand in Go to 88. Responses of soil biota to elevated atmospheric carbon dioxide Go to 89. Go to 90. Responses of soil biota to elevated atmospheric carbon dioxide Go to 91. Measurement of plant biomass and net primary production of herbaceous vegetation Go to 92. Microbial biomass and nutrient concentrations in hyphal mats of the ectomycorrhizal fungus Hysterangium setchellii in a coniferous forest soil Go to 93. Importance of Ectomycorrhiza for Go to 94. Mycorrhizas in ecosystems Go to 95. A critique of the role of ectomycorrhizas in forest ecology Go to 96. Substrate flow in the rhizosphere Go to 97. Comparison of direct vs fumigation incubation microbial biomass estimates from ectomycorrhizal mat and non-mat soils Go to 98. Atmospheric pollutants and ectomycorrhizae: More questions than answers? Go to 99. Input of to the Soil by Go to 100. Variation in of to 101. Substrate flow in the rhizosphere Go to 102. Production of fine roots and the seasonality of their growth in a Mexican deciduous dry forest Go to 103. Seasonal nitrogen and carbon concentrations in white, brown and woody fine roots of sugar maple (Acer saccharum Marsh) Go to 104. Root biomass, root distribution and the fine-root growth dynamics of Quercus coccifera L. in the garrigue of southern to 105. Bootstrapping in to 106. Interactions among soil biota in coniferous ecosystems Go to 107. Interactions of organisms at root/soil and litter/ soil interfaces in terrestrial ecosystems Go to 108. Interactions between soil animals and ectomycorrhizal fungal mats Go to 109.

Output: pass


Input: Claim: Bats play an important role in pollination and seed dispersal for many tropical plants. [SEP] Text: 0024[conservation;education;emerging threats;extrinsic threats;habitat loss;roost disturbance]leaf-nosed bats stand out as the most versatile bat family within Chiroptera for their broad spectrum of ecological functions and ecosystem services. Paradoxically, phyllostomid bats, and bats in general in the region, face the negative impacts of several extrinsic threats that are mainly responsible for their population decline, in some cases driving them toward local extinction. Habitat loss and roost disturbance and destruction are the two main factors affecting them over their entire geographic range. Globally, 13 species (6% of 216 recognized taxa) have been assigned to threatened IUCN categories. At the regional level, percentage of threatened species stands below 32% (North America: 31%, Central America: 31%, South America: 26%, Caribbean: 12%). In the last decade, bat conservation activism and conservation-oriented research have increased significantly across the Americas and the Caribbean, generating measurable positive effects for many species, including many phyllostomids. These positive impacts are being achieved through the interplay between research, environmental education, and conservation applications as a function of regional and local conservation strategies. Emergence of new threats to bats in the Neotropical region, such as development of wind energy facilities and emerging and reemerging zoonotic viruses, calls for intensified action on behalf of bats. (pages 435 - 456)This 2020. Page maintained by BiblioVault.

Output: corroborate


Input: Claim: Personalized nutrition guarantees that you can eat anything without gaining weight, as long as it fits your genetic profile. [SEP] Text: Mixed-effect model with Bonferroni post-hoc test comparing CG and EG at different phases during the study, **** p ≤ 0. 0001 (detailed statistics in Tab. S5). Individual body weight (D) and BMI (E) changes of all 34 continuing and all 33 discontinuing participants of the EG group and of CG participants (F) during the study. Data is normalized so that all baseline data at T0 equals 0 to represent change. (G) Between group differences of body weight and BMI from T0-T3 including the last available values of study drop-outs which were carried forward. Mixed-effect model with Bonferroni post-hoc test comparing CG and EG at different phases during the study, **** p ≤ 0. 0001 (detailed statistics in Tab. S5). (H) Significant correlation between body weight/BMI and MTVS of lunch and dinner. The more participants improved their regularity of lunch and dinner (decreasing MTVS), the more weight/BMI they lost. Linear regression, CG: n=33; EG: n=67, ** p ≤ 0. 01 (detailed statistics in Tab. S6). (I) Correlation between baseline BMI at T1 and change in BMI in EG participants. Linear regression, n=67 (detailed statistics in Tab. S6). (J) Between group differences after stratification according to different baseline BMIs. 2-way repeated-measure ANOVA with Bonferroni post-hoc test, *** p ≤ 0. 001 (detailed statistics in Tab. S8). (K) Raw data of change in caloric intake during intervention. 2-way repeated-measure ANOVA with Bonferroni post-hoc test, CG: n=30; EG: n=67, * p ≤ 0. 05, (detailed statistics in Tab. S3). (L) Correlation between reported ingested energy during the exploration phase vs. the intervention phase. Linear regression, CG: n=30; EG: n=67 (some participants were excluded from this analysis because of several erroneous diary entries about unrealistic amounts of food), (detailed statistics in Tab. S6). (M) Determined and estimated cumulative intake of fat, carbohydrates, and proteins during the study.

Output: contrast


Input: Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: Create a new account user Can't sign in? Forgot your username? Enter your email address below and we will send you your username Email* the address matches an existing account you will receive an email with instructions to retrieve your username close | or * Password* Forgot password? Reset it here Keep me logged in All fields with * are mandatory Email* All fields with * are mandatory Already have an account? Login here password must have 8 characters or more and contain 3 of the following: a lower case character, an upper case character, a special character or a digit password has been changed Can't sign in? Forgot your password? Enter your email address below and we will send you the reset instructions Email* the address matches an existing account you will receive an email with instructions to reset your password the verification code Cancel Congrats! has been verified close 10. 1139/x83-110 Get AccessContentsof Forest Research, Number 5October 19831. 8, 2. 8, and 2. 0 times less than in the corresponding deciduous forest horizons, respectively. and F horizons had respiration rates 11. 5 times higher than the corresponding black spruce layers. Weight losses in birch L, F, and H horizons were 6, 3, and 2 times higher, respectively, than in the corresponding black spruce substrates. Substrates had a quality-dependent decay rate which did not change when they were relocated within or between sites indicating that measured field climatic differences were not as influential on decay rates as substrate quality components. Fungal biomass was significantly correlated with the quantity of organic matter in all sites (n = 15, r = 0. 62) but correlations were better for deciduous (n = 9, r = 0. 89), and evergreen (n = 6, r = 0. 82) forests separately. Strong correlations exist also between grams of organic matter decayed per square metre per year and fungal biomass (n = 13, r = 0. 86), and fungal biomass and grams of N and P mineralized per square metre per year (n = 14, r = 0. 95) and (n = 11, r = 0. 94, respectively). Seedlings on mineral-deficient substrates produced more tannins than the controls, and seedlings on substrates with widening C/N ratios had successively less tissue with lower N content, and proportionally more roots.

Output: pass


Input: Claim: Bats play an important role in pollination and seed dispersal for many tropical plants. [SEP] Text: -19 PreprintsProtocolsVideosJournalsTools & a 10. 21203/rs. 3. rs-129644/v1This work is licensed under a CC BY 4. 0 LicenseStatus:Published12 Aug, 2021Read the published version in →Version 1posted 9You are reading this latest preprint versionAbstractThis study examined the mechanisms of facilitation and importance of seed dispersal during establishment of forest tree species in a tropical woodland. Seedling survival of Syzygium guineense ssp. afromontanum seedling (forest tree species) was monitored for 2. 5 years in four different microsites in savannah-woodland in Malawi under Ficus natalensis (a potential nurse plant), Brachystegia floribunda (a woodland tree), and Uapaca kirkiana (a woodland tree), and in a treeless site. S. guineense ssp. afromontanum seed deposition was also monitored in the four sites, and the natural establishment of forest tree species was observed to confirm the importance of seed dispersal. Protection from fire was found to be the most important facilitation mechanism in this area, with a total fire-induced mortality rate of 43%. However, the rate was comparatively low under F. natalensis, where fire is thought to be inhibited due to the lack of light-demanding C4 grasses. B. floribunda also offered protection from fire, and seedling survival did not differ between these two microsites. However, only a few individual forest tree species naturally established under B. floribunda, indicating that the facilitative mechanism of fire suppression is not the only factor affecting establishment in this tropical woodland. A higher rate of seed dispersal was also observed under F. natalensis compared with the other three microsites, suggesting that dispersal processes are also critical for the establishment of forest tree species in woodland in this region. Behavioral Ecologyand –savanna boundaryMiombo woodlandNurse plantSeed dispersalFiguresFigure 1Figure 2Figure 3Figure 4allowed forest tree species to establish in a tropical woodland. Fire suppression was an important mechanism of the facilitation there. Additionally, seed dispersal was an essential process for the establishment. forest and savannah-woodlands are major terrestrial biomes in tropical landscapes1.

Output: corroborate


Input: Claim: Personalized nutrition guarantees that you can eat anything without gaining weight, as long as it fits your genetic profile. [SEP] Text: Mixed-effects model with Bonferroni post hoc test comparing determined and estimated cumulative energy intake. The estimated macronutrient intake is formed as an assumed continuation of the average daily intake during the exploration phase. post hoc test showed no significant differences on any study day. (N) No significant correlation between body weight/BMI and changes of cumulative macronutrient intake. Linear regression, CG: n=30; EG: n=67, (detailed statistics in Tab. S6). (K, L, M, N) Some participants were excluded from this analysis because of several erroneous diary entries about unrealistic amounts of food. (O) The absolute deviation between the times of weekend meals and the times of food intake calculated for the EG intervention did not affect the subjects’ BMI change. Linear regression, n=67 (detailed statistics in Tab. S6). Table S1:Baseline characteristics of final 100 participants. Table S2:Statistical data on the difference between completers and study drop-outs. The data in the table refers to the data shown in Fig. S2A. Table S3:Statistical data from all Two-way-analyzing time, group, as well as interaction effects between time x group. In data for Figure 1, missing p-values in the and EG are due to the different number of meals for each participant. In the data for Figure 2, some participants were excluded from this analysis because of several probably erroneous diary entries about unrealistic amounts of food. In data for Figure 3, varying n-numbers result from incomplete entries in the diaries. In data for Figure 4, missing data are due to incomplete questionnaires. Table S4:Statistical data from the development of normalized body weight and BMI of participants during the exploration and the intervention phase, and of follow-up data of continuing and discontinuing participants. At T3, three participants could no longer be reached, which is why the n-number deviates here. The data in the table refers to the data shown in Figures 1E and S2A. Table S5:Statistical data from the development of normalized body weight and BMI of participants at the different phases of the study. At T3 only continuing participants were included, which is why the n-number deviates here from the other time points.

Output: contrast


Input: Claim: Certain fungi can decompose organic matter, contributing to nutrient cycling. [SEP] Text: 13(5): 795-817. Export 1. Effects of Phyllostachys nigra var. henonis bloom for the first time in 120 years on the dynamics of organic matter and nitrogen in forest: Differences in decomposition processes between leaf and flower Go to 2. -to 3. Differential Post-Recovery of Bogs and to 4. Climatic effects on soil organic nitrogen fractions and amino acid chirality in paddy soils Go to 5. Growth substrates alter aboveground plant microbial and metabolic properties thereby influencing insect herbivore performance Go to 6. Carbon stocks in the litter of the middle taiga deciduous forests of the Go to 7. The potential saprotrophic capacity of foliar endophytic fungi from Quercus gambelii Go to 8. from in Go to 9. All the Carbon Gone? Go to 10. Effect of Fluctuation and on Soil-Surface CO2 and CH4 Emissions from Go to 11. Soil enzymes illustrate the effects of alder nitrogen fixation on soil carbon processes in arctic and boreal ecosystems Go to 12. Secondary metabolites profile and physiological leaf traits in wild and cultivated Corylus avellana under different nutritional status Go to 13. Plant litter quality regulates soil eco-enzymatic stoichiometry and microbial nutrient limitation in a citrus orchard Go to 14. Effect of Organic and Application on Content and to 15. Gap models across micro- to mega-scales of time and space: examples of Tansley’s ecosystem concept Go to 16. in of Go to 17. Comparable effects of manure and its biochar on reducing soil Cr bioavailability and narrowing the rhizosphere extent of enzyme activities Go to 18. Importance of tree- and species-level interactions with wildfire, climate, and soils in interior Alaska: Implications for forest change under a warming climate Go to 19. Enzymes of Alnus-Fungi in an to 20. Effects of forest transition on litterfall, standing litter and related nutrient returns: Implications for forest management in tropical to 21. Reintegrating the beaver ( Castor canadensis ) in the urban landscape Go to 22. Is there a tree economics spectrum of decomposability? Go to 23. Nitrogen resorption efficiency of 13 tree species of a cool temperate deciduous forest in Go to 24.

Output: pass