Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: Figure 2Histogram of allelic loss for the Gleeson data setFull size imageFor the Gleeson data set, the two-component beta-binomial/binomial model, the two-component binomial model and the uni-component beta-binomial model are all favored over the two-component beta-binomial model and the uni-component binomial model (4). Because two of the two-component models as well as the uni-component beta-binomial model are comparable fits to the data, this may imply there is not strong enough evidence of more than one group of chromosome arms. However, while the uni-component beta-binomial model and the two-component beta-binomial/binomial model appear to fit similarly, the two-component binomial model appears to be a slightly better fit than these two as shown by the corresponding posterior probabilities. Maximum likelihood estimates obtained from fitting both the two-component beta-binomial and the beta-binomial/binomial model imply both components follow a binomial distribution as the dispersion parameter estimates are 0. Fits of all three two-component models yield identical parameter estimates, and therefore the rule obtained from the two-component binomial model which has the highest posterior probability is equivalent to that obtained from the other two-component models. Classification using this model places six chromosome arms in the TSG group. These are identified as chromosome arms 4q, 9p, 9q, 12q, 17p, and 18q. Note that three of these chromosome arms (4q, 9q and 12q) exhibit lower than the average background loss rate in the Barrett data set. However, 9p and 17p are categorized along with 5q in the TSG group. Furthermore, although not classified in the TSG group, chromosome arm 18q exhibits the fourth highest allelic-loss rate in the Barrett data set. data setdata set consists of 30 esophageal adenocarcinomas on 39 chromosome arms (the same arms included in the Gleeson data set). A histogram of the Hammoud data set is presented in Figure 3. Chromosome arms 4q and 17p have been identified on the plot as they appear to stand out from the others as having relatively high allelic-loss rates. The mean allelic-loss rate is 0. 20 and the median allelic-loss rate is 0. 18.

Output: pass


Input: Claim: Symbiotic relationships in microbiomes can influence health. [SEP] Text: Few studies describe the presence of archaea in human nasal, lung, and vaginal microbiomes [39••] (Fig. 2). As mentioned for animals, the vast majority of human-associated archaea is found in the intestine, accounting for up to 10% of the anaerobic community [40] (Fig. 2). The abundance of methanogenic archaea in the human gut is highly variable and represented by two physiological types of humans regarding gas exhalation (methane emitters and non-emitters) [41•]. While the specific role of non-methanogenic archaea in the human body remains to be explored, methanogens maintain numerous syntrophic relationships with resident bacteria by being involved in fermentation processes through hydrogen removal [28••]. M. smithii was the first archaeon isolated from human feces and is the most abundant archaeon found in the intestine [42]. M. smithii genomes displayed genomic adaptations to the human gut, such as producing surface glycans and adhesion-like proteins [30]. These adaptations are considered to originate from bacteria through lateral gene transfer [43]. Besides M. smithii, other methanogens such as Methanosphaera stadtmanae, and Methanomassiliicoccus luminyensis have been detected in human stool samples [44]. The use of modern high-throughput sequencing techniques revealed the presence of additional community members from the Eury- and Crenarchaeota, such as and Thermoplasmatales within the human intestine [45]. Fig. 2Human archaeome. Archaea identified in different body sites of humans. Created in BioRender. comFull size imageAlthough archaea can generally be considered commensal or beneficial organisms, and no archaeal pathogen is currently known, reports of archaeal involvement in human diseases are accumulating, particularly in immunocompromised individuals [46••]. Archaea have been found to have immunomodulatory abilities. For example, certain species of archaea can stimulate the immune system, increasing the production of cytokines and other immune cells [28••, 42, 47]. Other studies have suggested that archaea can exert anti-inflammatory effects by reducing the production of pro-inflammatory cytokines, such as methanogenic archaea, or increasing the production of anti-inflammatory cytokines [42, 48].

Output: corroborate


Input: Claim: Quantum mechanics can be completely understood through classical physics. [SEP] Text: None of these entities are number invariant, but in practice, that does not matter. The user does not convert just a single object; the user converts a whole tensor equation. The index-converting g entities typically occur in pairs, and the pairs contract to number invariant objects. When they don’t occur in pairs, they do occur on both sides of an equation, and cannot affect the issue of equation form invariance. Another two of these of g ’s are g β α and g α β. They function to do X β = ( g α β ) X α and X α = ( g α β ) X β or X β = g β α ( X α ) and X α = g β α ( X β ). As a pair, they contract to ( g β γ ) ( g γ α ) = g β α or to ( g γ β ) ( g α γ ) = g β α both of which are number invariant. The final four indexed g ’s are g α β g α β g α β and g α β. They can all function to change a regular index into a trans one, or a trans one into a regular one, but with a twist: ‘co’ goes to ‘contra’, or ‘contra’ goes to ‘co’. That is, X ′ α = ( g α β ) X β X α = ( g α β )  X β g α β ( X α ) = X β and g α β ( X α ) = X β. As noted above, the contractions ( g β γ ) ( g γ α ) = g β α and ( g β γ ) ( g γ α ) = g β α are number invariant. The bottom line is this: to be sure of invariance under arbitrary transformation, not just Lorentz transformation, always contract a regular index with a trans index. 6. 6. General invariance for Maxwell’s equations Maxwell’s equations in current tensor notation read: ∂ α F α β = 4 π c J β E51 and ∂ α D α β = 0 β E52 The two-index F α β and D α β tensors refer to the electromagnetic field and the ‘dual’ thereof.

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: Figure 3Histogram of allelic loss for the Hammoud data setFull size imageThe pairwise comparisons using the Bayes factors for the Hammoud data set (4) demonstrate that both the two-component beta-binomial/binomial model and the two-component binomial model give the best fits to the data. Note that the posterior probabilities of these models are practically the same indicating these models are equally good fits to the data. As only two-component models are selected from the class, there is strong evidence to suggest that a second group of chromosome arms with TSGs exists. Classification using both the two-component beta-binomial/binomlal model and the two-component binomial model places chromosome arms 4q and 17p in the TSG group. Both models yield similar conditional probabilities of group membership for the arms, and as in the other data sets, both models yield the same classification rule. Note that chromosome arm 4q is implicated by our analysis of the Gleeson data set and 17p is implicated by our analyses of all three previous data sets. ConclusionsTesting of one versus two components in a mixture model is problematic as the likelihood ratio test is not applicable. Bayes factors provide a natural solution to this problem. Although we make only crude comparisons using the Bayes factors, the results favor the right model most of the time for data arising from a two-component model. More importantly, when comparing a two-component model versus a one-component model for these data, the two-component model is generally chosen. For data that arise from a one-component beta-binomial model, the Bayes factors were not able to choose as well between the true model and a two-component model. Specifically, when comparing the true model to the two-component binomial, the false-positive rate was 16%. On the other hand, the Bayes factors are inconclusive for 62% of the data sets when making this comparison. This is actually encouraging when considering some frequentist options. Standard applicable frequentist methods such as an exact test and the dispersion score test are limited to testing for one versus more than one group of chromosome arms [8, 9]. Simulation studies examining these methods for these data reject the hypothesis of one group 93 and 89 percent of the time, respectively [10]. Based on this, one might conclude that a model with two (or more) groups would be appropriate.

Output: pass


Input: Claim: Symbiotic relationships in microbiomes can influence health. [SEP] Text: The exact mechanisms by which archaea exert their immunomodulatory effects are not yet fully understood, but it is thought that they may act through interactions with the gut microbiome and the gut epithelial cells [28••]. Other studies have proposed that archaea may interact with Toll-like receptors (TLRs) on immune cells, activating immune responses [49]. It is assumed that M. smithii may contribute to developing autoimmune diseases through various mechanisms, including producing metabolites, like methane, that activate immune cells and stimulate inflammation [34••]. In addition to its direct effects on the immune system, M. smithii may also indirectly contribute to autoimmune disease development by altering the gut microbiome and disrupting the balance of commensal microorganisms [50, 51]. Dysbiosis has been implicated in the development of various autoimmune diseases (reviewed in [28••]). Furthermore, M. stadtmanae was more abundant in the gut microbiome of patients with inflammatory bowel disease (IBD) [52] and may be associated with an increased risk of other autoimmune diseases, such as type 1 diabetes [53]. However, the effects of these interactions are not yet fully understood, and more research is needed to determine the precise ways archaea may affect the human immune system. It is also possible that different species of archaea may have different effects on the immune system and that the effects may depend on the context in which the interaction occurs. Increasing evidence suggests that archaea may play a role in the development and progression of cancer in humans through various mechanisms, including the production of carcinogenic metabolites, modulation of immune responses, and alteration of the tumor microenvironment [54, 55]. Further, alterations in the abundance and diversity of archaeal populations may be associated with an increased risk of colorectal cancer [55]. For example, certain species of archaea, such as M. smithii, may be more abundant in the gut microbiome of individuals with colorectal cancer than in healthy individuals [56]. Similarly, hydrogen sulfide-producing archaea have been implicated in the development of gastric cancer due to the ability of hydrogen sulfide to cause DNA damage and inhibit apoptosis [57]. Other studies have suggested that archaea may be involved in oral infections and periodontitis [36, 58]. In particular, Methanobrevibacter oralis has been identified in the oral microbiomes of patients with periodontitis [59].

Output: corroborate


Input: Claim: Quantum mechanics can be completely understood through classical physics. [SEP] Text: The electromagnetic field tensor F α β has merates that are components of the three-dimensional electric and magnetic field vectors, E and B. α β is the dual to F α β whose merates are components of B and − E. The one-index tensors J β and ∂ α refer to the source charge-current density vector and the differential operator vector. The indices α and β take the four values 0 1 2 3. The seeming limitation of Maxwell’s equations to invariance only under Lorentz transformation arises entirely from the differential operator being written as a covariant vector. In the extended tensor algebra, this operator is identified as transcovariant, and then Maxwell’s equations look like: ( ∂ α ) F α β = 4 π c J β E53 and ( ∂ α ) D α β = 0 β E54 Written this way, Maxwell’s equations are manifestly form invariant, not only under Lorentz transformation, but also under any arbitrary (just well-behaved) transformation, including Galilean transformation. Advertisement 7. Maxwell’s equations and photons: Photons have a life history that begins with emission as an electromagnetic pulse pulse, proceeds with development into a waveform, then changes into regression back to a pulse, and ends with absorption by a receiver. This life history of the photon can be modeled by imagining some mirrors that apply boundary conditions corresponding to the desired scenario, feeding a Gaussian pulse at the source to Maxwell’s equations, watching Hermite polynomials then emerge, and then finally pile up at the receiver. About EM signals and photons: The life history of the photon suggests that the assumption upon which Einstein’s SRT is founded is over-simplified. If we will make the founding assumption more realistic, then we will get more believable results. The more believable results can help us reconcile SRT with the QM of atoms. We can understand why Planck’s constant occurs. It represents the balance between competing phenomena: on the one hand, energy loss due to radiation from accelerating charges; on the other hand, energy gain due to internal torquing within the atomic system due to finite speed of signal propagation. About Atoms: Viewed in the right way, chemical and spectroscopic data reveal a tremendous amount of regularity.

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: The results presented here would not support such a conclusion, at least most of the time. However, it is important to note that if such variability exists in the data as is expected and is ignored, the false-positive rate can be quite high. For example, if comparing a two-component binomial model and a one-component binomial model when there is only one group of chromosome arms exhibiting background loss, the two-component model would likely be favored. Thus, in practice it is recommended that several comparisons are made before selecting a model. In addition, it may be desirable to consider the posterior probabilities of all models jointly. When examining the posterior probabilities of each of the models for the four scenarios considered here, we found that the true model had the highest median posterior probability. Table 3 summarizes the results of applying our approach to three esophageal adenocarcinoma data sets. It is important to note that a common locus on a chromosome arm was rarely chosen across the three studies. In fact, there were only a handful of loci that were investigated by at least two of the three data sets. Not surprisingly, chromosome arm 17p is chosen by the two-component models for all data sets as being in the TSG group. Chromosome arm 17p harbors a well known TSG called p53, which has been implicated in several cancers, including colon cancer, breast cancer and non-small cell lung cancer to name a few [1]. Also note that chromosome arm 9p is placed in the TSG group for the Barrett data set as well as the Gleeson data set. Similarly, chromosome arm 4q has been identified in both the Gleeson and Hammoud data sets. data set also characterizes chromosome arm 5q as harboring a TSG, which has been previously identified in other studies as having a high frequency of allelic loss in colon cancer, non-small cell lung cancer, as well as renal cancer [1]. Similarly, 18q, identified in the Gleeson data set, is suspected of playing a causal role in colon cancer and osteosarcoma based on high allelic-loss frequencies there [1]. Also, chromosome arm 3p has been identified as having high loss in renal and non-small cell lung cancer [1]. The results from applying our methods to the three data sets differ somewhat from those of the previously published analyses.

Output: pass


Input: Claim: Symbiotic relationships in microbiomes can influence health. [SEP] Text: Principles of Archaea-— ExamplesSeveral types of symbiosis are known for microorganisms, including mutualism, commensalism, amensalism, parasitism, and predation [60]. These different types of symbiosis can have significant implications for microbial communities’ ecology and function and host organisms’ health and well-being. An example of a mutualistic relationship involving archaea, also called syntrophy, is the previously mentioned interaction between methanogenic archaea and anaerobic bacteria in the gut of ruminants [61] (Fig. 3, mutualism). Ruminants, such as cows, have a complex digestive system that allows them to break down rigid plant materials through fermentation. Methanogenic archaea are an essential part of this process, as they produce methane as a byproduct of the fermentation process. However, methane production is energetically costly, and the methanogens rely on other microbes in the gut to provide them with the necessary substrates for methane production. In exchange for these substrates, the methanogens provide the other microbes with an environment free of hydrogen gas, which is toxic [61, 62]. Moreover, the archaeon Acidianus and the bacterium Desulfurococcus coexist in acidic hot springs to perform sulfur cycling [63]. Acidianus oxidizes elemental sulfur to sulfuric acid, while Desulfurococcus reduces sulfate to sulfide. The interaction between these two microorganisms benefits both, as Acidianus provides Desulfurococcus with the sulfuric acid it needs to produce energy, and in turn, Desulfurococcus consumes the toxic sulfide produced by Acidianus. Within nitrogen cycling, the ammonia-oxidizing archaeon N. maritimus and the nitrite-oxidizing bacterium Nitrospira coexist in marine environments [64]. N. maritimus provides Nitrospira with the nitrite it needs to produce energy, and in turn, Nitrospira consumes the toxic nitrite produced by N. maritimus. Commensal symbiosis including archaea was shown in the guts of termites and humans, where one organism benefits from the association while the other is neither benefited nor harmed [65]. Similarly, methanogens at the surface of corals detoxify the environment [66](Fig.

Output: corroborate


Input: Claim: Quantum mechanics can be completely understood through classical physics. [SEP] Text: So we are well enabled to interpolate and extrapolate for situations where actual data is not available. We can analyze scenarios where electrons are subtracted from or added to an atom, all at once, or one at a time; whatever we need. But take care: in the existing literature, the distinction between ‘all-at-once’ and ‘one-at-a-time’ is often obscure, so be careful. and Newton: There should have been no conflict between Maxwell’s equations and Newton’s equations over the issue of transformation invariance. Maxwell’s equations are form invariant under Galilean transformations, just as they are form invariant under Lorentz transformations. Physics does not have conflicts. Only people have conflicts. And people can resolve their conflicts. The conflict perceived in the case of Newton vs. Maxwell is resolved with an extension of mathematical formalism. in General: This work has shown that SRT deserves a moment of caution, and the reader may reasonably worry that GRT deserves some caution too. So it may be premature to develop a theory of quantum gravity. Placing the QG capstone onto the RT and QM pillars of 20th century physics may produce something that resembles the ancient constructions at Stonehenge, but not the Gothic cathedrals of Europe, much less anything modern. Advertisement 8. 1. Numerical data on ionization potentials for all elements Periods 1, 2 and 3. Period 4. Period 5. Period 6. Period 7. Advertisement 1. Aspden H. 1990 ‘Electron Clusters’ (Correspondence) 1 81 82. 2. Beckmann P. 1990 “Electron Clusters”, 1 55 58see also vol. 1, 82. 3. Kiein R. M. 2009 Non-, 4 Adventures in Applied Topology, especially Sect. 2. 2. 3, 4. Piestrup M. A. Puthoff H. E. Ebert P. J. 1998 of Electrons, 9 43 49. 5. Putz M. V. 2009 of Atoms and. 6. Rowlands P. 2007 Zero to Infinity- of Physics, 7. Thomas L. H. 1927 of an electron with an Axis, Phil. Mag. S. 7, 3 13 1 22. 8. Wheeler J. A.

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: First a potential bias exists in the design of current allelic-loss studies, and is seen in the design of the Barrett and Gleeson studies. Chromosome arms suspected of harboring TSGs are evaluated at more loci than other arms. The proportion of tumors with allelic loss on an arm is then defined as the number of tumors with allelic loss at at least one of the informative loci divided by the number of tumors informative at at least one of the loci. For example in the Barrett study, one locus is investigated for most chromosome arms, but two loci are assessed for loss on arms 13q, 17p, and 18q. This increases the probability that allelic loss will be observed at those arms examined at two loci than at those examined at only one. To address this issue, our analysis considers only one locus (the most informative) per chromosome arm. In the analysis presented by Barrett et al. (1996), the authors consider a uni-component binomial distribution for the background loss [1]. Frequencies falling far out in the tails of the binomial distribution, assuming a background loss rate of 0. 23, correspond to chromosome arms with potential TSGs. However, it should be noted that the model upon which we base our results (two-component beta-binomial/binomial model) is selected over that assumed by Barrett et al. (1996), where our model has a corresponding posterior probability of 0. 814 and the uni-component binomial has a posterior probability < 0. 001 [1]. The results from Barrett et al. (1996) indicate that chromosome arms with significantly high loss rates are 5q, 9p, 13q, and 17p (with corresponding p-values < 0. 05) [1]. Our approach also yields classification of 5q, 9p, and 17p in the TSG group. Although the fourth highest conditional probability corresponds to arm 13q, assuming a two-component beta-binomial/binomial model, the probability that it is in the TSG group is estimated to be quite low (0. 084) with our approach. Barrett et al. (1996) also implicate chromosome arms 1p and 18q as potentially harboring TSGs (p-values < 0. 10 and > 0. 05) [1].

Output: pass


Input: Claim: Symbiotic relationships in microbiomes can influence health. [SEP] Text: 3, commensalism), and in the soil, they degrade complex organic matter used by other microbes [67]. Amensalism describes a relationship with one partner negatively impacted by the presence of another organism while this organism is unaffected at all. One example of amensalism involving archaea can be again found in human guts [68]. M. smithii produces methane as a byproduct of its metabolism, while Desulfovibrio piger produces hydrogen sulfide as a byproduct. The presence of D. piger in the gut can reduce the sulfate levels available for M. smithii, thus inhibiting the growth and activity of the archaeon [30, 69] (Fig. 3, amensalism). Sulfur compounds are also essential for the survival of archaea and bacteria in deep-sea hydrothermal vents; consequently, the organisms compete with each other and get both negatively impacted [70]. For instance, Thermococcus can outcompete sulfur-reducing bacteria for sulfur compounds, using specialized enzymes that enable them to oxidize sulfur compounds to sulfate, releasing energy in the process [71] (Fig. 3, competition). Other archaea, such as Methanosarcina, can also outcompete sulfur-reducing bacteria by consuming hydrogen and carbon dioxide, which can limit the availability of these compounds for bacterial growth [72]. Archaea, like Methanosaeta harundinacea and Haloferax volcanii, compete with other microorganisms for space in their environment by forming biofilms and thus preventing the colonization of others [73]. There are currently no verified examples of archaea that are obligate parasites of other organisms. However, some archaea interact with other organisms in a way that can be considered to be parasitic [74]. For instance, some archaeal species have been found to live as endosymbionts in protists or amoebae [44]. M. luminyensis has been found in the ciliate protozoan Trimyema compressum [75], M. arboriphilicus in the amoeba Acanthamoeba polyphaga [76], and M. stadtmanae in the ciliate protozoan Metopus contortus [77].

Output: corroborate


Input: Claim: Quantum mechanics can be completely understood through classical physics. [SEP] Text: Feynman R. P. 1945 Interaction with the Absorber as the Mechanism of Radiation, Revs. Mod. Phys. , 17 2 & 3 157 181. 9. Wheeler J. A. Feynman R. P. 1949 in Terms of Direct Interp10. Whitney C. K. 2012 Algebraic Chemistry: Applications and Origins, Publishers. that I speak of MED, not of (CED) in general. CED involves, not only the works of Maxwell, but also those of a large number of other individuals. I am inclined to trust results from Maxwell, but question some of those from other authors, as reported in the present work. Wheeler and Feynman were looking to time symmetry as the basis for an electromagnetic generalization of instantaneous (Newtonian) gravitational interaction. There are important differences between the regressing waveforms introduced above and the Wheeler-Feynman advanced solutions: 1) Wheeler and Feynman were looking at interactions between essentially point sources and receivers, and so had to be looking at spherically expanding retarded solutions and spherically contracting advanced solutions, not at essentially one-dimensional expanding and contracting wavelets. 2) The Wheeler-Feynman expansion or contraction is related to the spherical area of a wave front, not the waveform in the radial propagation direction. 3) A lengthy discussion of the paradox of advanced actions is necessitated in the Wheeler-Feynman work, whereas the ‘regressing’ solutions introduced here are not in fact ‘advanced’ at all; they are just regressing, in real time, in the propagation direction. information 1. Introduction2. Maxwell’s electrodynamics and QM’s photons3. EM signals as photons4. EM fields within atoms5. Extensions and extrapolations from hydrogen6. Unification between Newton and Maxwell7. Conclusions8. 1. Numerical data on ionization potentials for all elements1. Choose citation style Select style to clipboard Get citation 2. Choose citation style Select format Bibtex RIS Download citation 1. Choose citation style Select style to clipboard Get citation 2. Choose citation style Select format Bibtex RIS Download citation © 2012 The Author(s). Licensee IntechOpen. This 3. 0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: Our analysis demonstrates that these arms are not likely to be classified in the TSG group with conditional probabilities of 0. 077 and 0. 123, respectively. The analytic approach employed by Gleeson et al. (1997) is to select a chromosome arm with a corresponding allelic-loss rate above an arbitrarily chosen cut-off of 50% as criterion for potentially harboring a TSG [11]. With this approach, Gleeson et al. (1997) implicate the following 10 chromosome arms; 3p, 4q, 5q, 8p, 9p, 9q, 12q, 13q, 17p, and 18q [11]. Our method gives the following conditional probabilities of harboring a TSG for these arms respectively: 0. 003, 0. 982, 0. 327, 0. 012, 0. 916, 0. 813, 0. 859, 0. 121, and 0. 998. While our method also selects six of these arms, the conditional probability of the unselected four are estimated to be fairly low. Interestingly our conclusions regarding the Hammoud analysis correspond well to those of the authors. The criterion the authors used for selection of a chromosome arm into the TSG group was that the chromosome arm's allelic-loss rate should exceed two standard deviations above the observed mean allelic-loss rate. This approach is similar to that of Barrett et al. (1996) and more sound than that employed by Gleeson et al. (1997) as it assumes a reasonable model for the allelic-loss rate (in this case a normal distribution) and selects those outliers to the right of the distribution as suspicious [1, 11]. Our approach, however, is more flexible in that multiple models consistent with the biological nature of the data are considered and compared and further, conditional probabilities of harboring a TSG are provided for each chromosome arm. For the arms selected by both us and Hammoud et al. (1996), the two arms selected, 4q and 17p, have conditional probabilities of 0. 968 and 0. 994 for harboring TSGs, respectively [4]. Results from the Bayes factors for the Gleeson data set are not completely clear. They cast doubt on whether the true underlying distribution really has two components or whether the two-component models chosen also provide a reasonable fit (relative to all the models considered) to overdispersed data exhibiting only background loss.

Output: pass


Input: Claim: Symbiotic relationships in microbiomes can influence health. [SEP] Text: Αρχική Πλοήγηση Επιστημονικό πεδίο Ημερομηνία Συγγραφέας Χώρα Γλώσσα Ίδρυμα Σχετικά με το ΕΑΔΔ Κατάθεση Διατριβής Συχνές Ερωτήσεις Κέντρο Υποστήριξης Χρηστών Επικοινωνία Ανοικτά Δεδομένα Είσοδος Εγγραφή Ξέχασα τον κωδικό A- A0 A+ | EN Συμβιωτικές σχέσεις σπόγγων και κυανοβακτηρίων στο Βόρειο Αιγαίο Περίληψη Τα κυανοβακτήρια έχουν κυρίαρχη θέση ανάμεσα στους μικροοργανισμούς που αναπτύσσουν συμβιωτικές σχέσεις με τους σπόγγους

Output: corroborate


Input: Claim: Every problem has a quantum solution available today. [SEP] Text: December 01 2021 Israel has become a powerhouse in quantum technologies A supportive government, available capital, and world-class academic institutions are some of the factors behind the nation’s quantum ascendance. Search for other works by this author on: PubMed 10. 1063/PT. 3. 4898 Open the PDF for in another window and Israel has become a powerhouse in quantum technologies. 1 December 2021; 74 (12): 24–27. Download citation file: Ris (Zotero) toolbar search Menu toolbar search search input Search input auto suggest filter your search computing, Quantum information, Industry, News and events Ron Folman, a quantum physicist, was taken aback when a delegation of top officials from the paid an unexpected visit to his lab at Ben-of the Negev (BGU) about 15 years ago. “I asked them, ‘Why are you here? You have a thousand times more money, scientists, and space,’” Folman recalls. “The head of the delegation answered, ‘I heard what you guys are doing, and I wanted to see with my own eyes this Israeli chutzpah. ’” To Folman, the quote neatly characterizes Israel’s outsize global footprint in quantum science and technology. It’s no accident that Israel is punching above its weight in quantum fields. Despite the turmoil that has roiled Israeli politics in recent years, the Knesset committed 1. 25 billion shekels ($400 million) to a five-year Initiative, which kicked off in late 2019. Tal David, an experimental physicist who heads the initiative, says it gained a boost from Israel’s economic stimulus program during the COVID-19 pandemic. The program includes $60 million to build the country’s first quantum computer, which is expected to consist of 30–40 qubits. Assembly is due to get underway early next year. “We don’t aspire at least in the next few years to beat IBM or Google,” says David. “We need to first form a basis for an ecosystem in Israel and that will be the purpose of the project. Maybe in a few years, we’ll be able to jump into the deep end of the pond and compete with the big ones. ” Today 60% or more of the initiative’s funds is spent in academia, says David.

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: Recall the simulation study where we demonstrate that for data arising from a uni-component beta-binomial model, the Bayes factors indicate that both the true model and the two-component binomial model are often both reasonable fits to the data. This motivates incorporating Bayesian model averaging (BMA) into the inference process [12]. An alternative would be to compute the posterior odds of a second component. First, the posterior probability of a two-component model could be obtained by averaging over the three two-component models. Second, the posterior probability of a uni-component model could be computed by averaging over the relevant uni-component models. The averaged Bayes factor would then be a ratio of the posterior probability of a two-component model to the posterior probability of a one-component model. Furthermore, one could use Bayesian model averaging when estimating the conditional probability of group membership for each of the chromosome arms. Maximum likelihood estimates from different high probability models could lead to different inferences about parameters. Thus, this approach of averaging the conditional probability over the various models to classify the arms or weighting the parameter estimates by the posterior probability of a given model may be more desirable than choosing a single best model from which to make inference. Specifically, one could weight estimates by P(H j |X). For example, suppose chromosome arm 13q is suspected of harboring a TSG from past experiments and we desire a probability that Z13q= 1 based on these data. Because of model uncertainty we may be hesitant to compute the probability based solely on one model. Instead, we could estimate this probability as: where j indexes over all of the models considered. This is a potential alternative to classifying the chromosome arms using the classical maximum likelihood approach that needs to be further explored. It is interesting to note that the two-component beta-binomial mixture model was never chosen for any of the data sets. Although it was certainly favored over the one-component binomial model in all data sets and over the uni-component beta-binomial model in the Barrett data set, it was never chosen to be in the set of candidate models. The class of models considered here is based on our beliefs of the biology of the data. However, the ability to screen the tumor cell genome for chromosome arms which harbor TSGs lies in a better understanding of the background distribution. Characterizing the background distribution would allow a more definitive identification of arms exhibiting abnormal loss.

Output: pass


Input: Claim: Symbiotic relationships in microbiomes can influence health. [SEP] Text: Η συμβιωτική σχέση που αναπτύσσουν οι σπόγγοι με τα κυανοβακτήρια αποτελεί μια από τις αρχαιότερες γνωστές αλληλεπιδράσεις μεταξύ ζώων και μικροοργανισμών. Ένα μεγάλο μέρος της υπάρχουσα γνώσης για την ποικιλότητα, την οικολογία και τη λειτουργία των συμβιωτικών με σπόγγους κυανοβακτηρίων είναι «κρυμμένο» σε έρευνες μεταγονιδιωματικής που εξετάζουν ολόκληρη τη μικροβιακή κοινότητα ενός σπόγγου στο ταξινομικό επίπεδο του Φύλου.

Output: corroborate


Input: Claim: Every problem has a quantum solution available today. [SEP] Text: A similar consortium is organized around quantum cryptography, where David says activity is “moving much faster than we anticipated” from universities to industry, and into applications in large organizations and the government. A third consortium aims to enlarge Israel’s presence in quantum computing, where, he says, “we have a very good start, but it’s small. ” Well positioned Davidson is developing a cold-atom gravimeter that will be useful both as an accelerometer in inertial navigation systems and in basic science. LightSolver, a quantum-inspired technology, emerged from Davidson’s lab. While not technically a quantum computer, the desktop device that is under development will use a coupled laser array to perform computations. Davidson says the jury is still out on whether quantum computation will come into widespread use in the next decade, but “if it does it will be a game changer, and people will invest huge sums. ” Well positioned to benefit in that event is Quantum Machines, founded by three physicists who earned their PhDs in the lab of Weizmann physicist Moty Heiblum. The company’s quantum orchestration platforms communicate complex software to quantum processors and perform quantum error correction. Notably, the devices will work with whatever type of quantum computing platform becomes dominant. (See “What’s under the hood of a quantum computer? ,” online, 5 March 2021. ) Itamar Sivan, CEO and cofounder of Quantum Machines, says he has no doubt that quantum computing will take off. “The question is when. ” He attributes much of his 70-employee company’s success to the ready availability of funding. “And there are great engineers and amazing talent in Israel. We can find people here who are both experts in quantum but also have some engineering background. ” Many of them have come from the defense sector. Folman’s lab has already delivered two quantum prototypes to industry: a compact, robust cold-atom atomic clock and a sensitive magnetic atomic sensor. left Folman’s lab seven years ago to work for AccuBeat, an Israeli manufacturer of rubidium clocks. He continues working with BGU researchers to commercialize the new clock technology he helped to develop there.

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: MethodsDataThe three data sets to which we apply our methods were previously published and analyzed using other techniques [1, 4, 11]. factors for the proposed class of mixture modelsfactors can be challenging as non-trivial integration is often required to estimate the marginal probabilities under each model considered. Specifically, calculating Bayes factors involves integrating the likelihood over the entire parameter space for each model considered. Thus, the integrals tend to be high-dimensional. In general, we need to computeI = ∫ Pr(X|λ, H)π(λ|H)d λ. This can be quite computationally intensive. When the integral is of high dimension (> 6), quadrature methods can be unreliable [13]. In addition, and more relevant to our situation, for moderate to large sample sizes (> 35), numerical methods can be both inefficient and unreliable [7, 14]. An alternative approach is to use Gibbs sampling techniques. However, for mixture models, these methods often miss important mass as the chain tends to get stuck near one mode resulting in an underestimate of the integral [14]. Furthermore, because the sampling is not independent, there is no simple way of self-monitoring convergence. Another method of estimating integrals is simple Monte Carlo, that involves sampling from the prior distribution, π(λ). The simple estimate of the integral is the averaged likelihood at the sampled parameter values or This has been shown to be a good estimate for likelihoods that are relatively flat. However, if the posterior is concentrated relative to the prior, the variance of the estimate will be large, and convergence to a Gaussian will be slow [7]. Thus, sampling from the prior distribution is often not very efficient. A potential solution to this problem is to do importance sampling that involves sampling from π*(λ), the importance sampling function [7, 14]. The estimate then becomes where is known as the importance sampling ratio. The simple estimate is a special case of importance sampling where π*(·) is chosen to be the prior distribution. However, the importance sampling estimate can be an improvement over the simple estimate if π*(·) is chosen such that the sampling is more efficient, e. g. , if π*(·) is centered around the mass. There has been some success with importance sampling in a non-mixture model setting [14]. Our solution is to first write the likelihood in its complete-data form.

Output: pass


Input: Claim: Symbiotic relationships in microbiomes can influence health. [SEP] Text: H ανασκόπηση αποκάλυψε ότι η ποικιλότητα των συμβιωτικών κυανο. . . Τα κυανοβακτήρια έχουν κυρίαρχη θέση ανάμεσα στους μικροοργανισμούς που αναπτύσσουν συμβιωτικές σχέσεις με τους σπόγγους. Η συμβιωτική σχέση που αναπτύσσουν οι σπόγγοι με τα κυανοβακτήρια αποτελεί μια από τις αρχαιότερες γνωστές αλληλεπιδράσεις μεταξύ ζώων και μικροοργανισμών.

Output: corroborate


Input: Claim: Every problem has a quantum solution available today. [SEP] Text: Davidson says that despite its success with Council grants, “where the only criterion is scientific excellence,” Israel hasn’t done as well with international collaborations that are funded by the European Union’s 10-year program, which began in 2018. Other disciplines must get involved to fully exploit quantum’s potential. “Even if you build the heart of a quantum device, there are many layers and technologies needed to be able to work,” says Folman. But materials science, engineering, chemistry, and even biomedicine have yet to team up with physics and computer science, either in Israel or worldwide. “These disciplines today do very little connected to quantum technology. It should be an interdisciplinary effort, and eventually it will be. ” Shai Lev, head of business development and partnerships at the quantum algorithm design company Classiq, took on a pro bono role as cofounder of Qubit, a grassroots quantum community effort meant to attract disciplines outside of physics and computer science into the quantum world. While most of the periodic seminars the group organizes are highly technical, some are also devoted to the financial aspects of starting a business. Lichtig, a product operations manager at Soluto and another Qubit co-organizer, says the sessions soared in popularity and became international after the pandemic forced them into virtual mode. Since then, such quantum oracles as from London; from University of California, Santa Barbara; and Chad Rigetti, CEO of Rigetti Computing, have contributed talks. Paradoxically, another reason for Israel’s big presence in tech may be its tiny size. “The maximum distance between universities here is like 200 kilometers,” says Lev. “People know each other, and people are always looking for the next thing, and around them you have a vibrant community. ” 1. C. Middleton, 74(10), 42 (2021). Feder, 73(11), 22 (2020). Middleton, “What’s under the hood of a quantum computer? ,” Phys. Today, 5 March 2021.

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: The likelihood for the mixture of two beta-binomial distributions is written as follows: where z= (z1, z2,. . . ,z N )Tand the z i s are unobserved group membership indicators such that z i = 0 if x i is from the background component and z i = 1 if x i is from the TSG component. Then the marginal probability of X becomes where I denotes the marginal probability of the data (or integrated likelihood) and where g is the prior distribution of θ. We then estimate this integral using a method we developed called the Method (UDM). This method is a variant on importance sampling and involves a combination of either quadrature or exact integration and sampling of the membership vectors, Z. The idea behind the method is to use P(Z|θ= x) where is the MLE of θ to provide information on the important groupings, i. e. , which chromosome arms are likely to be clustered together. While the membership vectors are sampled independently, the membership values within a group are sampled dependently, making these groupings more likely to be maintained than if the values were sampled independently. The development and assessment of UDM is discussed in detail in Desai (2000) and demonstrates solid performance in estimating these integrals [10]. Software for implementing the method is available by contacting the first author. Note that for all analyses presented in this paper, uniform priors are assumed for the unknown parameters. AbbreviationsTSG: tumor suppressor gene MLE: maximum likelihood estimate 2 bb: two-component beta-binomial model 2 bb/bin: two-component beta-binomial/binomial model 2 bin: two-component binomial model 1 bb: uni-coniponent beta-binomial model 1 bin: uni-component binomial model BMA: Bayesian model averaging UDM: uniform distance method 1878. CAS PubMed 326. 10. 1016/0092-8674(91)90641-B957. 4. 1996, 56: 4499–4502. CAS PubMed 145. 1445. 10. 1002/(SICI)1097-0258(19980715)17:13<1425::AID-SIM861>3. 0. CO;2-V795. 1995. 97. 2000. 1465. 448. 272. 1996.

Output: pass


Input: Claim: Symbiotic relationships in microbiomes can influence health. [SEP] Text: περισσότερα Περίληψη σε άλλη γλώσσα Cyanobacteria are among the most dominant and important sponge symbionts, and their association with sponges has attracted research interest from an ecological, evolutionary, and biotechnological perspective. Our current knowledge for their diversity, ecology and functioning is limited to few uncultivated taxa, while a great part is “hidden” in metagenomics research studying the entire microbial communities of sponges. The present thesis aimed to explore sponge-cyanobacteria associations in a previously unexplored eastern Mediterranean ecoregion, the Aegean Sea, by a culture-dependent approach. An extensive evaluation of the literature on the diversity of sponge-cyanobacteria association was performed. The review raised the number of sponge species known for hosting cyanobacteria to 311, and revealed that the global cyanobacterial diversity reported from sponges remains underestimated due to the phylum-wide investigations on sponge microbiome. The culture-dependent approach, performed. . . Cyanobacteria are among the most dominant and important sponge symbionts, and their association with sponges has attracted research interest from an ecological, evolutionary, and biotechnological perspective. Our current knowledge for their diversity, ecology and functioning is limited to few uncultivated taxa, while a great part is “hidden” in metagenomics research studying the entire microbial communities of sponges. The present thesis aimed to explore sponge-cyanobacteria associations in a previously unexplored eastern Mediterranean ecoregion, the Aegean Sea, by a culture-dependent approach. An extensive evaluation of the literature on the diversity of sponge-cyanobacteria association was performed. The review raised the number of sponge species known for hosting cyanobacteria to 311, and revealed that the global cyanobacterial diversity reported from sponges remains underestimated due to the phylum-wide investigations on sponge microbiome. The culture-dependent approach, performed in the present thesis in the sponges, resulted in the isolation of 15 sponge-associated cyanobacterial strains from 12 sponge species, which were found to form novel clades inside the orders Synechococcales and Pleurocapsales.

Output: corroborate


Input: Claim: Every problem has a quantum solution available today. [SEP] Text: power: The only available solution to global warming 8 April 2013 New fission technologies not only eliminate the concerns about safety and waste that plague today's reactors; they can also consume existing nuclear waste. Arthur R. Williams DOI: Content License::1945-0699 Topics: Commentary & warming, energy independence, water scarcity and third-world economic growth are all amenable to a common, safe, clean, cost-competitive and field-tested nuclear solution. Why isn’t this solution universally embraced and implemented? I suggest two reasons. First, we humans respond much more strongly to dramatic events, like earthquakes, violent weather and terrorist acts, than we do to steady-state threats, such as auto accidents, medical errors and coal p2996. The death tolls in the US from auto accidents (30 000), medical errors (44 000–200 000), and coal dust (13 000) are not only higher, but also perennial. The gradual character of carbon dioxide emissions and global warming is elevating our “boiling frog” tendencies to an entirely new scale of danger. Although the problem may not excite us, our pot is warming so quickly that we must leap to survive. A measure of the magnitude and urgency of this challenge can be found in Bill Gates’ summary of his wonderful TED lecture on this topic: Despite the time, effort and money he has devoted to new vaccines and seeds, if he could be granted a single wish for the coming decades, it would be for a practical, CO2-free energy source. That explicit prioritization reflects his awareness of an especially unfortunate feature of warming, that its burden falls most heavily on the politically voiceless poor, and less heavily on those with the means to address the challenge. The disparity adds to our inertia. The second reason lies in deeply entrenched myths (which for my purposes I shall define as untruths breeding complacency), rooted in unrealistically high expectations for renewable energy and unrealistically negative expectations for nuclear power. Criticism of nuclear power focuses on history and ignores dramatic advances in fission technology. This incomplete picture gives rise to myths that conflict directly with the assertions of Gates and of John Parmentola, the US army's director of research and laboratory management: that nuclear fission is the only “practical” solution in view.

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: Skip to main content Explore journals Get published About BMC My account Search all BMC 1. 67 GHz and 2G memory. We review typical MDS techniques in the following and propose a new MDS method to solve the problem of large data sets in Section 3. We split the data into overlapping subsets, apply our MDS technique to each subset, and then recombine the configurations of the subsets into the same space. We call this method the split-and-combine MDS (SC-MDS) method. The complexity of SC-MDS is O(p2 N), where p is the dimension of the feature space, which is far smaller than the number of data points N. 4, we evaluate the performance of SC-MDS using simulation, apply SC-MDS to the GO database, and lastly, improve the K-means clustering of gene expression profiles by applying SC-MDS to yeast cell cycle microarray data [5]. There are many different categories of MDS techniques. For example, a distinction can be made between metric and non-metric MDSs, between weighted and unweighted MDSs, between single matrix and multiple matrices, and between deterministic and probabilistic matrices [3, 6]. In this section, we introduce three typical MDS methods that are relevant to the present work. Classical MDS (CMDS)Torgerson [7] proposed the first MDS method. The distance is the Euclidian distance, and the similarity matrix is complete (with no missing data) and symmetric. The main idea was that given the Euclidean distances or the inner products among points, it is possible to construct a matrix X of Cartesian coordinates of these points in the Euclidean space. Torgerson derived matrix X from the distance (or similarity) matrix D and showed what to do when the distance matrix includes noisy data. The key is to apply the double centering operator and singular value decomposition (SVD). Double centering is the process of subtracting the row and column means of a matrix from its elements and adding the grand mean. For example, suppose that D is a product matrix, that is, D = XTX, where X is a p × N matrix with each column of X being a vector in a p -dimension space.

Output: pass


Input: Claim: Symbiotic relationships in microbiomes can influence health. [SEP] Text: Genomic hallmarks for a symbiotic lifestyle were revealed, such as evidence of genome reduction and detection of genes encoding for eukaryotic-like proteins. Genome-mining analysis revealed a great number of natural product biosynthetic gene clusters (BGCs) in Leptothoe genomes, suggesting that strains of this genus deserve to be further explored for novel natural products. περισσότερα Διαβάστε τη διατριβή (Online) Κατεβάστε τη διατριβή σε μορφή PDF (11. 35 MB) (Η υπηρεσία είναι διαθέσιμη μετά από δωρεάν εγγραφή) Δηλώνω ότι έλαβα γνώση και ανεπιφύλακτα συμφωνώ και αποδέχομαι τους Όρους Χρήσης του Εθνικού Αρχείου Διδακτορικών Διατριβών, καθώς και της Κατέβασμα αρχείου PDF Όλα τα τεκμήρια στο ΕΑΔΔ προστατεύονται από πνευματικά δικαιώματα. DOI10.

Output: corroborate


Input: Claim: Every problem has a quantum solution available today. [SEP] Text: The remainder of this essay comments on Gates’ criteria for “practicality,” and examines the factors of availability, reliability, cost, scale, safety, proliferation and waste. The good news is that new fission technologies make fission clean, safe, competitively inexpensive, and resistant to terrorism. Moreover, they solve the nuclear-waste challenge. One technology claims to reduce the high-level waste output of a typical power plant from 20 tons per year to a few kilograms. American startups are pursuing commercialization, but much of the action is in other countries, notably China and India. Gates and Parmentola also emphasize the urgency for halting CO2 emissions. In my view, the following six widespread and paralyzing myths must be addressed. Myth #1: Wind and solar can do it Renewable sources, like wind, solar, and tide, emit no CO2, and that’s undeniably good. While the discussion of renewables often focuses on cost, it is power density and intermittency that conspire with cost to prevent these technologies from providing adequate solutions. puts it, technologies for renewable energy represent energy farming. Because the intrinsic power density of renewable sources is orders of magnitude lower than that of hydrocarbons and nuclear processes, large tracts of land are required to reap even modest quantities of power. Even if large tracts of land, such as those in the Sahara or the American Southwest, are employed, the electricity produced is inherently intermittent, and must be stored and transported. For example, Gates estimates that all the world’s existing batteries can store only about 10 minutes of electricity consumption. Also, because land is not available near population centers, transport such as high-tension towers must be provided. While the relative cost of renewable sources is improving, cost still represents a disadvantage of several hundred percent that has been compensated by government subsidies. Subsidies might continue, but as Hargraves emphasizes in his extensively researched book, Thorium: than Coal the prospects for eliminating CO2 emissions are greatly improved if the alternative power source is cheaper than hydrocarbons. The high energy density and availability of coal make it misleadingly attractive. Hargraves concludes that at least one of the next-generation breed-and-burn fission technologies can produce electricity for about $0. 03/kWh, making it cost-competitive, even with coal.

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: We define i as a N × 1 vector in which every element is one and B = ( X − 1 N X 1 ˙ 1 ˙ T ) T ( X − 1 N X 1 ˙ 1 ˙ T ) MathType@MTEF@5@5@+=feaafiart1ev1aaat9MDH5MBPbIqV92AaeXatLxBI9g6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaae00scfa4aa4eaa@45A0@ as the similarity matrix with the means of the column vectors being zero.

Output: pass


Input: Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: conservation in microorganisms is classically categorized into respiration and fermentation; however, recent work shows some species can use mixed or alternative bioenergetic strategies. We explored the use of extracellular electron transfer for energy conservation in diverse lactic acid bacteria (LAB), microorganisms that mainly rely on fermentative metabolism and are important in food fermentations. The LAB Lactiplantibacillus plantarum uses extracellular electron transfer to increase its NAD+/NADH ratio, generate more ATP through substrate-level phosphorylation, and accumulate biomass more rapidly. This novel, hybrid metabolism is dependent on a type-dehydrogenase (Ndh2) and conditionally requires a flavin-binding extracellular lipoprotein (PplA) under laboratory conditions. It confers increased fermentation product yield, metabolic flux, and environmental acidification in laboratory media and during kale juice fermentation. The discovery of a single pathway that simultaneously blends features of fermentation and respiration in a primarily fermentative microorganism expands our knowledge of energy conservation and provides immediate biotechnology applications. Editor's evaluation In this study, the authors describe unique metabolic strategies, including extracellular electron transfer, utilized by the lactic acid bacterium Lactiplantibacillus plantarum. The ability to shift and/or accelerate metabolism of lactic acid bacteria capable of extracellular electron transfer may have interesting biotechnological applications. Decision letter Reviews on Sciety eLife's review process eLife digest Bacteria produce the energy they need to live through two processes, respiration and fermentation. While respiration is often more energetically efficient, many bacteria rely on fermentation as their sole means of energy production. Respiration normally depends on the presence of small soluble molecules, such as oxygen, that can diffuse inside the cell, but some bacteria can use metals or other insoluble compounds found outside the cell to perform ‘extracellular electron transfer’. Lactic acid bacteria are a large group of bacteria that have several industrial uses and live in many natural environments. These bacteria survive using fermentation, but they also carry a group of genes needed for extracellular electron transfer. It is unclear whether they use these genes for respiration or if they have a different purpose. Tejedor-Sanz, Stevens et al.

Output: corroborate


Input: Claim: Every problem has a quantum solution available today. [SEP] Text: In today’s solid-fuel reactors the fuel is clad in metals that can tolerate only a limited amount of neutron bombardment, necessitating removal of the fuel long before it is fully consumed. This distinction is the basis of the claim by the MIT-based startup, Transatomic Power, that waste production can be reduced from tons to kilograms, increasing by a factor of 30 the energy obtained from a given quantity of fuel. Refueling frequency is also reduced in molten-salt reactors by the continuous removal of neutron-absorbing xenon, whose accumulation in solid-fuel reactors also reduces the time that fuel can remain in the reactor. A bonus, but not a surprise, given the connection between breed-and-burn reactors and reprocessing, is that some new reactors can consume existing nuclear waste—both depleted and spent fuel. In this way, next-generation fission can solve the waste problem created by present-generation fission. Myth #4: Fission may provide electricity, but it neither fuels transportation nor provides clean water Fission produces cheap heat, which is broadly useful. In the present context, the cost-effective heat produced by fission is symbiotic with two highly developed technologies that address two of our most critical challenges, CO2-free transportation and seawater desalination. Transportation consumes a large fraction of the energy budget. Its fractional share is approaching that of industry, which is about twice that of both residential and commercial energy consumption. Since fission reactors are unlikely to be placed in cars and trucks, in what sense can fission contribute to CO2-free transportation? The answer is the synthesis of ammonia. NH3 synthesis is among the most promising exploitations of heat from fission. NH3 can be viewed as an especially effective medium for hydrogen storage and delivery. The infrastructure for NH3 production and distribution is already widespread. NH3 has about half the energy content by weight of gasoline, but its much lower cost gives it a price-performance advantage. Most importantly, NH3 burns to form air and water: 4NH3 + 3O2 = 2N2 + 6H2O Fission also offers a choice between electrically powered reverse osmosis and traditional distillation as means to produce potable water. Distillation can use fission-produced heat directly, whereas reverse osmosis is very energy demanding, and can use fission-produced electricity.

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: Then we have B = ( X − 1 N X 1 ˙ 1 ˙ T ) T ( X − 1 N X 1 ˙ 1 ˙ T ) = X T X − 1 N X T X 1 ˙ 1 ˙ T − 1 N 1 ˙ 1 ˙ T X T X + 1 N 2 1 ˙ 1 ˙ T X T X 1 ˙ 1 ˙ T = D − 1 N D 1 ˙ 1 ˙ T − 1 N 1 ˙ 1 ˙ T D + 1 N 2 1 ˙ 1 ˙ T D 1 ˙ 1 ˙ T = D − D ¯ r − D ¯ c + D ¯ g MathType@MTEF@5@5@+=feaafiart1ev1aaat9MDH5MBPbIqV92AaeXatLxBI9g6xNi=xI8qi9v8qqaqFr0xc9vqFj0dXdbba91qpepeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaae00scfa4aa4eaa0JaemiwaG1aa6eaobaakiabd0scfa4aa40aa0JaemiraqKaeyOeI0scfa4aa6eaobaacuq40aa2da9iabdseaejabgk4ka4zaCgabeaakiabcYcaSaaaaaa@9C5B@ (1) where D ¯ r MathType@MTEF@5@5@+=feaafiart1ev1aaat9MDH5MBPbIqV92AaeXatLxBI9g6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaae@2E97@ denotes the row means, D ¯ c MathType

Output: pass


Input: Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: used a lactic acid bacterium called Lactiplantibacillus plantarum to study whether and how this group of bacteria use extracellular electron transfer. Analysis of L. plantarum and its effect on its surroundings showed that these bacteria use a hybrid process to produce energy: the cells use aspects of extracellular respiration to increase the yield and efficiency of fermentation. Combining these two approaches may allow L. plantarum to adapt to different environments and grow faster, allowing it to compete against other species. Tejedor-Sanz, Stevens et al. provide new information on a widespread group of bacteria that are often used in food production and industry. The next step will be to understand how the hybrid system is controlled and how it varies among species. Understanding this process could result in new biotechnologies and foods that are healthier, produce less waste, or have different tastes and textures. ways in which microorganisms extract energy to maintain cellular functions are directly linked to their environment, including the availability of nutrients and cooperative or antagonistic interactions with other organisms (Haruta and Kanno, 2015). Microorganisms must also maintain redox homeostasis by responding to oxidative and reductive changes inside and outside the cell (Sporer et al. , 2017). Ultimately, microorganisms that can effectively generate cellular energy while also managing redox requirements will maintain higher growth and survival rates, and therefore exhibit greater ecological fitness. All organisms possess mechanisms to conserve energy, that is, to convert light or chemical energy into cellular energy in the form of ATP (Russell and Cook, 1995). During respiration, microorganisms rely on either oxygen (aerobic respiration) or other exogenous substrates (anaerobic respiration) as terminal electron acceptors. Some microorganisms, most notably Geobacter spp. , can anaerobically respire using electron acceptors outside the cell, such as iron (III) oxides or an electrode (Renslow et al. , 2013; Richter et al. , 2012). This process is called extracellular electron transfer (EET). Regardless of the identity of the electron acceptor, ATP synthesis during respiration occurs via oxidative phosphorylation (Kim and Gadd, 2019). In oxidative phosphorylation, electrons from electron carriers are transported by an electron transport chain, which creates a proton motive force (PMF) for ATP generation.

Output: corroborate


Input: Claim: Dinosaurs coexisted with humans in the past. [SEP] Text: It is not the various play themes in evidence in children’s bedrooms that forge links among themselves; the rooms feature knights next to dinosaurs and pirates, alongside books about the Stone Age. But there are children who connect dragons with dinosaurs of their own accord; they create their own logic. It appears unsurprising that children set up their own explanatory models for the dragon–dinosaur connection. One of my students, Beatrice Wieser, in an auto-ethnographic piece written in 2017, describes her memories of her childhood around the turn of the millennium thus: On receiving dinosaur figures as a gift from the boy next door, another passion was awakened in me: dinosaurs. I collected the figures and swapped them with others. My walls were covered with all the different species of extinct mammals [sic]. Be it Tyrannosaurus, Sauropoda, Compsognathus or Struthiosaurus – I had them all at home, in miniature format or as posters. I have just realised while writing this report that I can no longer think of many of the names – a pity, really. I also notice that, at the age of eight, I never wondered whether it was historically possible for a society of knights to keep dinosaurs outside their castle. I thought about it some more and [asked] my mother, [who] was able to tell me that she had once asked me if I thought that the real knights had had dinosaurs in their gardens. I justified my YES! by saying that my knights’ castle also had a dragon, which I evidently put in the same category as dinosaurs. As the [dragon] was part of the knights’ castle set, I must have assumed that dinosaurs and knights had been around at the same time. Exposing children to a range of toys clearly provides optimum stimulation for their imaginations. At the same time, children try to comprehend regimes and systems. The analogy constructed in the example above between dinosaurs and dragons – the latter having been supplied with the knights’ castle – means that the child created a little dinosaur garden in the castle grounds. Returning to the children’s bedrooms of today, as they appear in our study, I note a perception, held by two boys in the sample, of an evolution from dinosaurs to dragons.

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: @MTEF@5@5@+=feaafiart1ev1aaat9MDH5MBPbIqV92AaeXatLxBI9g6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaae4yamgabeaaaaa@2E79@ denotes the column means and D ¯ g MathType@MTEF@5@5@+=feaafiart1ev1aaat9MDH5MBPbIqV92AaeXatLxBI9g6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaae4zaCgabeaaaaa@2E81@ denotes the grand mean.

Output: pass


Input: Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: Under anaerobic conditions, some cells can also conserve energy using fermentation. In fermentation, microorganisms use internally supplied electron acceptors, and ATP is generated mainly through substrate-level phosphorylation (Kim and Gadd, 2019). In substrate-level phosphorylation, ATP is generated in the cytoplasm by transfer of phosphate from metabolic intermediates to ADP (Kim and Gadd, 2019). Lactic acid bacteria (LAB) are a diverse group of aerotolerant, saccharolytic microorganisms in the Firmicutes phylum which mainly use fermentation for energy conservation. LAB are essential for many food fermentations, including fermented milk and meats, fruits and vegetables, and grains (Tamang et al. , 2020). Strains of LAB are also used for industrial chemical production (Sauer et al. , 2017) and as probiotics to benefit human and animal health (Vinderola et al. , 2019). LAB are generally grouped by their differences in hexose metabolism (Salvetti et al. , 2013). Some species perform homofermentation, reducing pyruvate to lactate as the sole metabolic end-product from glycolysis. Other LAB perform heterofermentation, producing lactate along with ethanol, acetate, and CO2 by the phosphoketolase pathway. However, for redox balancing, homofermentative LAB can also shift to a mixed acid fermentation and heterofermentative LAB use alternative electron acceptors, like fructose or citrate (Hansen, 2018). Although some LAB can respire in the presence of heme and menaquinone, those bacteria are unable to synthesize heme and many are also auxotrophic for menaquinone (Pedersen et al. , 2012). Even those species capable of respiration still use fermentation metabolism as the primary mechanism to conserve energy (Pedersen et al. , 2012). Therefore, LAB growth rates and cell yields are constrained by access to electron acceptors used to maintain intracellular redox balance during substrate-level phosphorylation. The bioenergetics of anaerobic bacteria have been tightly linked to oxidative phosphorylation for anaerobic respiration and substrate-level phosphorylation for fermentation. However, experimental evidence shows a concurrent use of oxidative phosphorylation and substrate-level phosphorylation.

Output: corroborate


Input: Claim: Dinosaurs coexisted with humans in the past. [SEP] Text: As a result of reading a children’s book, an 8-year-old boy (Case 9m) clearly believed that knights and dragons belong together, pre-dated by dinosaurs; he explained: ‘And when all [dinosaurs] died, then the dragons [came]. ’ An 11-year-old boy (Case 3m) came to similar conclusions. During the interview in his room, he showed the interviewer a puzzle depicting various dinosaurs: Interviewer: … Do you like dinosaurs? Boy: Yes, they’re great. They’re so dangerous and look so fierce. I have another [puzzle] of them. Mama probably put that in here, too. Ah! Here it is! [Shows a puzzle with two dragons on the cover (Ravensburger, No. 19638)] Interviewer: Oh, and what can we see there? Boy: Dinosaurs too, you can see that. Interviewer: I see. And why do they look so different? Boy: Yes, because these lived earlier [points to the puzzle with the dinosaurs (Ravensburger, No. 13695)]. They don’t have those wild prongs on their heads yet and don’t all have wings yet. And later on they looked like this [points to the puzzle with the dragon motif]. Well, they certainly weren’t the same, but you can see that on the one [puzzle] you don’t see anything except grass and stuff. That’s why. Look, I’ve even got a few dinosaurs over there. See how fierce they look [points to dinosaur figures]. The reference to the two puzzles in particular gives us an insight into children’s thinking in this regard. The puzzle boxes present the dinosaurs in what is intended to be a natural landscape, and the dragons in a foggy setting of ruins, suggestive of human life. Additionally, the level of detail evident on the dragon puzzle box seems to indicate a higher evolutionary stage than that attained by the dinosaurs. The sense of twilight and fog on the dragon box, probably intended to conjure a mythical atmosphere, eludes decoding, which is why the boy did not perceive it. There were also children in the sample – one instance is a 12-year-old girl (Case 7w) who we interviewed – who do not think that dinosaurs actually existed.

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: = 1 − 1 N 1 ˙ 1 ˙ T MathType@MTEF@5@5@+=feaafiart1ev1aaat9MDH5MBPbIqV92AaeXatLxBI9g6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaae0JaeGymaeJaeyOeI0scfa4aa@35D0@ (1) can be simplified asB = HDH. After performing double centering on D, one can apply SVD to B. is symmetric, the decomposition is of the formB = UVUT.

Output: pass


Input: Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: Here, we explored EET across LAB and studied the implications of this trait at a metabolic and energetic level in Lactiplantibacillus plantarum, a homofermentative LAB capable of mixed acid fermentation and which can respire in the presence of exogenous heme and menaquinone. L. plantarum is of particular interest as it is a generalist LAB species found in insect, animal, and human digestive tracts and is essential for the production of many fermented foods (Behera et al. , 2018; Duar et al. , 2017). These findings have significance for the understanding of energy conservation strategies in primarily fermentative microorganisms and on lactic acid fermentations in food biotechnology. Results L. plantarum reduces extracellular electron acceptors To determine whether L. plantarum can reduce extracellular electron acceptors, we first measured its ability to reduce insoluble ferrihydrite (iron (III) oxyhydroxide). Incubation of the model strain L. plantarum NCIMB8826 in the presence of ferrihydrite showed that this strain reduces Fe3+ to Fe2+ (Figure 1A and Figure 1—figure supplement 1A). Viable cells are required for iron reduction and this activity is dependent on the presence of exogenous quinone (DHNA, 1,4-dihydroxy-2-naphthoic acid) (Figure 1A and Figure 1—figure supplement 1A-B). The requirement for DHNA was hypothesized because DHNA is a precursor of demethylmenaquinone (DMK), a membrane electron shuttle utilized by L. monocytogenes for EET (Light et al. , 2018), and L. plantarum lacks a complete DHNA biosynthetic pathway (Brooijmans et al. , 2009a). For full activity, an electron donor (such as mannitol or glucose) was required to be present (Figure 1A and Figure 1—figure supplement 1A). Like L. monocytogenes (Light et al. , 2018), the addition of riboflavin during the iron reduction assay also increased Fe3+ reduction in a dose-dependent manner (Figure 1—figure supplement 1C). Thus, L. plantarum reduces insoluble iron in a manner similar to L. monocytogenes.

Output: corroborate


Input: Claim: Dinosaurs coexisted with humans in the past. [SEP] Text: Of particular interest in this context are the views of a 10-year-old boy (Case 2m), who cited knowledge whose sources are to be found in his room: There was no such thing as dragons. They’re imaginary creatures. I’ve got an audio CD about someone called … he invented the dinosaurs, … I mean, he discovered them … when younger children are 4, 5 years old or smaller, they think that dragons also belonged to the Middle Ages. That’s just meant for younger ones. And if they, like, have a castle, then a giant dragon comes along and they play ‘Oh no, the giant dragon is attacking me! We’re all going to die! We’ve got to barricade ourselves in the castle, then maybe we’ll survive! ’ These ethnographic observations enable us to propose an initial rough model of children’s conceptual patterns of thought around these topics, which fall into three types: (1) dragons as real, extinct beings; (2) dragons as real beings in evolutionary proximity to dinosaurs; and (3) dragons as imaginary beings. It is unfortunate that we are unable at this stage to supplement these qualitative findings with quantitative data on primary-age children’s capacity to differentiate fantasy from (past) reality, as previous studies have obtained for younger children (see Morison and Gardner, 1978). We should not overlook the determining influence of the toy industry in this. A comparative analysis of Playmobil catalogues issued by the toy manufacturer geobra Brandstätter Stiftung & Co. KG between 2000 and 2018 (Figure 4) is illustrative of the extent to which dragons and dinosaurs, like other phenomena, are subject to economic cycles. This analysis counted the number of instances, in the principal catalogues issued by the company for each year, of individual illustrations depicting dragons and dinosaurs within set sceneries and products containing one or more dragons or dinosaurs. Figure 4: Business cycle of dinosaurs (n=299) and dragons (n=297) in Playmobil catalogues Playmobil’s products aimed at the German and Austrian markets provide a good basis for tracing the inclusion and evolution of dragons in historical play themes. We observe almost identical numbers of dinosaurs and dragons, although dragons represent the more stable variable if we consider the distribution per year within the range, and the number of dinosaurs is subject to greater fluctuations.

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: Hence, B = X − 1 N X 11 T = U V 1 2 MathType@MTEF@5@5@+=feaafiart1ev1aaat9MDH5MBPbIqV92AaeXatLxBI9g6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaae9aqpcq6eaobaakiabd0JaemyvauLaemOvay1aa@3D8C@ where the columns of B MathType@MTEF@5@5@+=feaafiart1ev1aaat9MDH5MBPbIqV92AaeXatLxBI9g6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaae@2CFD@ are the coordinates of data, with the mean of the data being moved to the original point.

Output: pass


Input: Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: DHNA is found in concentrations of 0. 089–0. 44 μg/mL in commercial fermented beverages (Eom et al. , 2012), and under laboratory conditions, microbes can synthesize and secrete DHNA leading to concentrations of 0. 37–48 μg/mL (Isawa et al. , 2002; Furuichi et al. , 2006; Kang et al. , 2015). To test whether EET in L. plantarum is relevant under these physiological concentrations, we probed whether L. plantarum can perform EET with a sub-physiological DHNA concentration of 0. 01 μg/mL. Indeed, L. plantarum can reduce iron and produce significant current density (Figure 1—figure supplement 3A-B), although the magnitude of iron reduction and current was smaller than what was observed with 20 μg/mL. These results show that the concentrations of DHNA found in niches of L. plantarum can support EET and suggest the magnitude of EET will depend on the DHNA concentration. Iron reduction by LAB is associated with the presence of ndh2 and pplA Because iron reduction by L. monocytogenes requires the genes in a 8. 5 kb gene locus encoding a flavin-based EET (FLEET) pathway (Light et al. , 2018), we looked for the presence of these genes in 1,788 LAB genomes deposited in NCBI. Homology searches identified the complete FLEET locus in 11 out of 38 genera including diverse LAB such as Enterococcus and Lacticaseibacillus (Figure 2A). The other LAB genera either lack multiple FLEET pathway genes or, as was observed for all 68 strains of Lactococcus, contain all genes except for pplA, which is predicted to encode an extracellular flavin-binding reductase. Among the lactobacilli, genomes of 19 out of 94 species contain the entire FLEET system (Figure 2—figure supplement 1). The lactobacilli species with the entire FLEET locus are homofermentative and are distributed between different phylogenetic groups (Zheng et al. , 2020). These data show that the FLEET locus is conserved across LAB genera besides L. plantarum, including other homofermentative LAB species known to colonize host and food environments.

Output: corroborate


Input: Claim: All dinosaur species have been discovered and classified. [SEP] Text: If the second-generation individual’s spouse does not possess these informative alleles, we can look in the children of the second-generation individual to see if they have inherited both the de novo allele and the nearby informative alleles. This pattern of inheritance is only possible if the de novo allele and informative alleles are on the same haplotype; thus, in this example, we see that the de novo allele is on the maternal grandfather’s haplotype, and is paternal in origin. (b) A toy sample of paired-end sequencing reads is shown for each member of a trio (mother, father, and child). In this strategy, we identify informative alleles (shown in blue) that are present in one of the two parents, and within a read length (500 bp) of the de novo allele in the child (shown in red). Then, we identify individual sequencing reads that span the de novo and informative alleles. If the de novo allele is always present in the same read as the informative allele, then we can phase the de novo allele to the parent with the informative allele, and vice versa. Figure 2 with 2 supplements Download asset Open asset Effects of parental age and sex on autosomal DNM counts and mutation types in the second generation. (a) Numbers of phased paternal and maternal de novo variants as a function of parental age at birth. Poisson regressions (with 95% confidence bands, calculated as 1. 96 times the standard error) were fit for mothers and fathers separately using an identity link. Germline mutation rates, as a function of both paternal and maternal ages, are presented in Figure 2—figure supplement 1. (b) Mutation spectra in autosomal DNMs phased to the paternal (n = 3,584) and maternal (n = 880) haplotypes. Asterisks indicate significant differences between paternal and maternal fractions at a false-discovery rate of 0. 05 (Benjamini-Hochberg procedure), using a Chi-squared test of independence. P-values for each comparison are: C > G: 0. 719, T > G: 4. 93e-3, T > A: 8. 60e-2, T > C: 8. 02e-2, C > A: 0. 159, C > T: 7. 65e-6, indel: 8.

Output: pass


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: is a distance matrix, d i j = ( x i − x j ) T ( x i − x j ) MathType@MTEF@5@5@+=feaafiart1ev1aaat9MDH5MBPbIqV92AaeXatLxBI9g6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaaeGaciGaaiaabeqaaeqabiWaaaGcbaGaemizaq2aa9aqpdaGcaaqaaiabcIcaOiabdIha4naa0IaemiEaG3aa4naa0IaemiEaG3aa@44E7@ where x i is the configuration of the i-th data point. The double centering of D2 is equal to -2B, provided that ∑ i = 1 N x i = 0 MathType@MTEF@5@5@+=feaafiart1ev1aaat9MDH5MBPbIqV92AaeXatLxBI9g6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaae4ba2da9iabicda0JaeGymaedabaGaemOta4eaniabggHiLdaaaa@378B@.

Output: pass


Input: Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: Figure 2 with 2 supplements see all Download asset Open asset genes ndh2 and pplA are associated with iron reduction by LAB. (A) Heatmap showing the genera in the Lactobacillales order containing FLEET genes. Homology searches were conducted using tBLASTx for 1788 complete LAB genomes in NCBI (downloaded 02/25/2021) against the L. plantarum NCIMB8826 FLEET locus. A match was considered positive with a Bit-score >50 and an E-value of <10–3. Arrows designate genera tested for iron reduction activity; green = EET-active with Fe3+, red = EET-inactive with Fe3+. (B) Reduction of ferrihydrite in PBS with 20 μg/mL DHNA and 55 mM mannitol after growth in mMRS supplemented with 20 μg/mL DHNA and 1. 25 mM ferric ammonium citrate. The avg ± stdev of three biological replicates per strain is shown. (C) Relative expression of NCIMB8826 FLEET locus genes in mMRS with 20 μg/mL DHNA and 1. 25 mM ferric ammonium citrate compared to growth in mMRS. Significant differences in expression were determined by the Wald test (n = 3) with a Log2 (fold change) > 0. 5 and an FDR-adjusted p-value of <0. 05. See also Figure 2—figure supplement 1 and Figure 2—figure supplement 2 and related data in Figure 2—source data 1. Figure 2—source data 1 EET locus homology matches at genus level via tBLASTx from complete Lactobacillales genome dataset for Figure 2A, raw data for Figure 2B and relative expression data of Figure 2C. Download elife-70684-fig2-data1-v2. xlsx To determine whether gene presence was associated with EET activity, a diverse collection of LAB strains were examined for their capacity to reduce ferrihydrite. The assay showed that isolates of L.

Output: corroborate


Input: Claim: All dinosaur species have been discovered and classified. [SEP] Text: Author response image 3 Download asset Open asset Lack of correlation between sibling number and either slope or intercept. For each CEPH/Utah family, we fit a linear model predicting DNM counts as a function of paternal age (see Figure 3). We then assessed whether the number of third-generation siblings in these families was predictive of either the (a) slope or (b) intercept point estimate in the regression. Neither slope (p = 0. 654) or intercept (p = 0. 718) are significantly associated with sibling number. Author response image 4 Download asset Open asset Allele balance distributions in transmitted and untransmitted DNMs. Allele balance was calculated as the fraction of reads supporting the alternate (i. e. , de novo) allele at a particular site. As there are substantially more transmitted than untransmitted DNMs in the plot, the y-axis is shown as the normalized count of DNMs. Author response image 5 Download asset Open asset Range of missed heterozygote rates across CEPH families. (a) For each unique set of second-generation parents and third-generation children, we counted the total number of DNMs in the third generation for which we saw evidence in the first generation (i. e. , grandparents). The missed heterozygote rate (MHR) therefore represents the fraction of DNMs in each family that were likely “missed” in the second generation, as a percentage of the total number of DNMs identified in the third-generation children. (b) Comparison of mutation spectra in autosomal filtered germline third-generation DNMs (n=22,644) and autosomal third-generation DNMs that were removed due to evidence in a genotyped grandparent (n=83). No significant differences for particular mutation types were found at a false-discovery rate of 0. 05 (Benjamini-Hochberg procedure) using a Chi-squared test of independence. resources table Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional informationSoftware, algorithmToolkit (GATK)DePristo et al. , 2011v3. 5. 0; RRID:SCR_001876Software, algorithmpeddyPedersen and Quinlan, 2017av0. 4.

Output: pass


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: Hence, the CMDS method performs double centering on D2, multiplies by − 1 2 MathType@MTEF@5@5@+=feaafiart1ev1aaat9MDH5MBPbIqV92AaeXatLxBI9g6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaae0scfa4aa@2F42@ and then performs SVD, which gives the configurations of the data. Thus, the key scheme of PCA is embedded in this CMDS method. When we want to find out the r dimensional configurations of the data in the space generated by the r principal components, we only use the first leading r spectrums and r columns of U to generate X, that is, X = V r U r MathType@MTEF@5@5@+=feaafiart1ev1aaat9MDH5MBPbIqV92AaeXatLxBI9g6xNi=xI8qi9v8qqaqFr0xc9vqFj0dXdbba91qpepeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaae01aa@3500@ (4) where V r is the r × r sub-matrix of V and U r is a matrix of size N × r. There are many drawbacks of this method [8]. For example, missing data is not allowed and the computational complexity is O(N3). Hence, this method is not suitable for massive data sets. Chalmer's AlgorithmOne of the force-based models of MDS is the spring model [9]. It considers each point of the data as a vertex in a low dimensional space, with springs connecting each vertex and the distance (or the spring length) between vertices proportional to their high dimensional distance.

Output: pass


Input: Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: plantarum NCIMB8826 was incubated in mMRS supplemented with DHNA and iron (Figure 2C and Figure 1—figure supplement 1D). Both ndh2 and pplA were induced (~1. 6 fold, p < 0. 05) in MRS containing mannitol, DHNA, and ferric ammonium citrate (Figure 2C), but were not upregulated when either DHNA or ferric ammonium citrate were omitted from the culture medium (Figure 2—figure supplement 2C). Taken together, these data show that widespread iron reduction in LAB is tightly associated with the presence and upregulation of ndh2 and pplA, suggesting they are required for EET. Ndh2 is required and PplA is conditionally required for L. plantarum EET In order to confirm the necessity of ndh2 and pplA for EET in L. plantarum, we constructed ndh2 and ppA deletion mutants of L. plantarum NCIMB8826. Both mutants were significantly impaired in their capacities to reduce ferrihydrite compared with the wild-type strain (Figure 3A). The ndh2 and pplA deletion mutants also had different effects on the oxidation-reduction potential (ORP) of mMRS. ORP is defined as the ratio of all oxidative to reductive components in an environment (Killeen et al. , 2018) and is an important environmental condition which influences the outcome of LAB fermentations such as flavor development in cheese (Morandi et al. , 2016) and the growth of spoilage microorganisms (Olsen and Pérez-Díaz, 2009). Expectedly for the L. plantarum EET phenotype, significant reductions in monly occurred during L. plantarum growth when DHNA was included in the culture medium (Figure 3—figure supplement 1A). Although ORP declined for all three strains in a manner consistent with other ORP-reducing enzymatic activities (for example the reduction of oxygen by NADH oxidase) (Tachon et al. , 2010), wild-type L. plantarum resulted in greater reductions in ORP compared to either mutant in mMRS, and these differences were significant at most time points measured over a 12 hr period (Figure 3B).

Output: corroborate


Input: Claim: Fossils are infallible indicators of past environments. [SEP] Text: Skip to main content Skip to main navigation menu Skip to site footer Start typing the of Geography. in Mountains – are they indicators of past environments? Home Tors in Mountains – are they indicators of past environments? Home Archives No. 16 (2019) 10. 2478/bgeo-2019-0005 Keywords Tors, deep weathering, periglacial, glacial erosion, rock control, surface degradation, represent one of the most characteristic landforms in the uplands and mountains of Central Europe, including the Sudetes, Czech-Moravian Highlands, Šumava/Bayerischer Wald, Fichtelgebirge or Harz. These features occur in a range of lithologies, although granites and gneisses are particularly prone to tor formation. Various models of tor formation and development have been presented, and for each model the tors were thought to have evolved under specific environmental conditions. The two most common theories emphasised their progressive emergence from pre-Quaternary weathering mantles in a two-stage scenario, and their development across slopes under periglacial conditions in a one-stage scenario. More recently, tors have been analysed in relation to ice sheet extent, the selectivity of glacial erosion, and the preservation of landforms under ice. In this paper we describe tor distribution across along with hypotheses relating to their formation and development, arguing that specific evolutionary histories are not supported by unequivocal evidence and that the scenarios presented were invariably model-driven. Several examples from the Sudetes are presented to demonstrate that tor morphology is strongly controlled by lithology and structure. The juxtaposition of tors of different types is not necessarily evidence that they differ in their mode of origin or age. Pathways of tor remodelling and degradation under subaerial conditions are identified and it is argued that processes of tor formation and development are ongoing. Thus, tors are not reliable indicators of past environments, because they are considerably influenced by both geological factors, such as lithology and structure, and geomorphological factors such as hillslope setting. 460. ANDRÉ M. -F. , 2004, The geomorphic impact of glaciers as indicated by tors in (Aurivaara, 68° N). Geomorphology, 57: 403–421. . ,.

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: If di, jdenotes the high dimensional distance between vertices i and j, and δi, jdenotes the low dimensional distance, then the stress between vertices i and j is proportional to |di,j- δi, j|. The spring model computes (N - 1) forces at each vertex per iteration, and the computational complexity of this model is O(N2) per iteration. Chalmers [8] proposed a linear iteration time layout algorithm. Instead of computing all the forces at each point, he computed only constant forces in the neighborhood of each point and randomly chose another constant point that is not in the neighborhood to compute the large distance effect. Only constant points are computed at each point, so that the computational complexity is reduced to O(N) per iteration. This spring model does not find the steady state solution in general. One can only process a fixed number of iterations, say 8 or 10, as opposed to finding the converged solution. Note that the constant forces are selected in both the neighborhood and afar. Failure to incorporate one of these two forces will diminish the performance of this method [8]. MethodAs in Chalmers' linear layout algorithm, in the anchor point MDS method [10] only a portion of data is used to reconstruct the layout for intermediate steps. The data are grouped into clusters, so that the distances between points in different clusters are less meaningful than the distances between points in the same cluster. In this method, some points in the same cluster are chosen as anchors and others are considered as floaters. Distance information of anchors is used to construct the coarse structure of layout, and the floaters are used to update the fine structure. When a small number of K anchor points are chosen, a modified MDS procedure only computes the N × K matrix. Buja et al. [10] showed that the number of anchors could not be smaller than the dimension p of the given data. Moreover, the anchors should be chosen carefully because random choices of anchors do not work [10]. This is challenging when the grouping structure is unknown. From these two methods, we can see that the intermediate steps for calculating MDS do not need to employ all entries of the dissimilarity matrix. We can use this property to reduce the computational complexity of MDS. Another important issue is choosing the number of dimensions for layout.

Output: pass


Input: Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: Moreover, we did not detect any intermediates of the reductive branch of the TCA cycle, that is oxalacetate, malate, or fumarate. This indicates that EET did not cause additional metabolic flux through its TCA cycle. Thus, none of the known metabolic pathways or electron transport proteins associated with anaerobic respiration, besides Ndh2, are required for EET. These results suggest increased energy conservation during EET in L. plantarum is not through canonical anaerobic respiration. An alternative hypothesis is that increased energy conservation under EET conditions is driven by changes in fermentation. L. plantarum uses glycolysis to convert mannitol to two molecules of pyruvate which are then converted mainly to lactate or ethanol via NADH-consuming steps, or acetate via an ATP-generating reaction using substrate-level phosphorylation (Dirar and Collins, 1972). Thus, shifting toward production of acetate from to lactate or ethanol production can increase ATP yield during fermentation. Additionally, NADH can be re-generated by oxidizing pyruvate to yield 2,3-butanediol, using acetoin as an intermediate. Fermentation in L. plantarum also decreases the pH of the surrounding media. To probe changes in fermentation, we measured the concentrations of mannitol, acetate, lactate, ethanol, acetoin, 2,3-butanediol, formate, and pyruvate and the pH in L. plantarum cultures during OC and EET conditions. After four days, we accounted for ~80% and ~ 55% of the total carbon under EET and OC conditions (for all metabolite concentrations see Supplementary file 1), giving us a quantitative view of metabolism under EET conditions. Surprisingly, under EET conditions, the distribution of major end-fermentation products (acetate, lactate, and ethanol) did not change, but their yield per cell was 2. 6-fold higher compared to OC conditions (Figure 5A). While we did not detect acetoin or 2,3-butanediol, formate was found at trace levels, and pyruvate was found at similar, low levels under EET and OC conditions (Figure 5—figure supplement 2). After accounting for mannitol consumption, we observed that EET allowed cells to produce ~1.

Output: corroborate


Input: Claim: Fossils are infallible indicators of past environments. [SEP] Text: , 2010, The first stages of erosion by ice sheets: evidence from central Europe. Geomorphology, 123: 349–363. HALL A. . R. ,. W. ,. , 2012, Examples: – A Pre-glacial Landscape. Journal, 129, 1: 2-14. . , ROHRMÜLLER J. ,. , LOTH G. , PÜRNER T. , 2012, Hundert Meisterwerke. Die schönsten Geotope Bayerns. für Umwelt, Augsburg: 288. . H. , 1999, der Granitverwitterung und Abtragung im nordwestlichen Waldviertel. [in:] Steininger F. F. (eds), Erdgeschichte des Waldviertels (2nd ed. ), Waldviertler Heimatbund, Horn–Waidhofen/Thaya: 113–132. IVAN A. , 1983, Geomorfologické poměry Žulovské pahorkatiny. Zprávy GgÚ ČSAV, 20, 4: 49–69. JAHN A. , 1952, W sprawie wygładów lodowcowych w Sudetach. Czasopismo Geograficzne, 21/22: 360–366. JAHN A. , 1962, Geneza skałek granitowych. Czasopismo Geograficzne, 33: 19–40. JAHN A. , 1974, Granite tors in the Sudeten Mountains. [in:] Brown E. H. , Waters R. S. (eds), Progress in Geomorphology. Geographers, 7, London: 53–61. . ,. J. , MIGOŃ P. , 2017, Mechanisms of granite alteration into grus, Karkonosze granite, SW Poland. Catena, 150: 230–245. . , DUSZYŃSKI F. ,. ,. , RÓŻYCKA M. , MIGOŃ P. , 2016, (Central Sudetes, SW Poland) – a case of a collapsed mountain. Geological Quarterly, 60: 695–713. . ,. ,.

Output: pass