Input: Claim: Gene expression analysis helps understand cellular responses to stimuli. [SEP] Text: The reason for such escape mechanism may be due to the presence of the tandem repeats in the protein binding regions of the promoter sequences as discussed earlier. However, a thorough study that includes wet laboratory and bioinformatic tool must be conducted to understand in which stage of the parasite mutation typically undergoes. Determination and identification of CpG islands is one of the integral part of biological, methylation and medical studies (Chuang et al. 2012). In vertebrates, 50% of the genes contain CpG islands (also called gene markers) in their promoter region. In spite of the fact that CpG islands are unmethylated in promoter regions, 80% of mammalian genome are methylated. As mutation rate in methylated CpG is higher than that of the unmethylated CpG, there is greater chance of loss of CpG islands which subsequently results in change of gene expression and function (Han and Zhao 2008). As previously discovered by Williams et al promoters with high CpG content are largely hypomethylated (Williams, Christensen, and Helin 2012). Das et al in 2014 discovered that L. donovani genes are highly enriched for CpG islands. In addition, they also revealed that CpG motifs delayed programmed cell death in macrophages which may be helpful to extend the parasite lifespan conferring the advantage of infection progression (Das et al. 2015). In line with this, the current Insilco analysis also discovered that L. donovani BPK282A1 genome is rich in CpG in both the promoter and gene body regions. On the other hand, It was also explained that antiapoptotic effect of L. donovani was observed where there was DNA methylation (Das et al. 2015). The GC coverage of a gene region can be affected by its GC concentration. Hence, regions with 50 to 60% GC content do have the highest coverage compared to gene regions with GC content of 70-80% and gene regions with GC content of 30 to 40% (Amr and Funke 2015). With this regard, this Insilco analysis showed that majority (57. 5%) of the gene promoters and close to half (47. 5%) of the gene body regions do have the highest GC coverage.

Output: corroborate


Input: Claim: All behaviors can be understood solely through neural circuitry. [SEP] Text: As a final test to ensure that we did not produce any false negatives, we tested the high > low conflict contrast, using all the data (Emotion and Neutral), but with lowered statistical thresholds, utilizing a small-volume correction for each region individually. Even with these more liberal thresholds, no rostral ACC clusters were observed; however, a small voxel cluster within the left amygdala was identified (see Table 1). Within this conflict-sensitive left amygdala region, there was a significant effect of task condition in the full ANOVA (i. e. , involving conflict, condition and timepoint as factors; see Figure 3). This interaction was due to a similar pattern of activity to that observed in several other regions within the CCN and EMO networks (i. e. , Emotion > Neutral activity). Similarly, as with these other regions, no condition*conflict interaction was observed. Indeed, if anything, the high > low conflict effect was weaker in the Emotion condition relative to Neutral (Figure 3), consistent with the absence of a significant conflict effect in this region when only the Emotion condition was examined. Additionally, in this left amygdala region, no effects of trial type were observed in the ANOVA contrasting AY and BX trials. Together, these results confirm that the rostral ACC and amygdala did not show any selective emotion conflict effects, and the small left amygdala region that was identified showed a pattern of activation that was very similar to other regions within cognitive control network, i. e. , sensitivity to both to the presence of task conflict and to emotional processing, but no preferential response to emotional conflict (e. g. , these factors did not interact with one another). DiscussionWith the present study, we examined neural activity associated with emotional versus non-emotional conflict using a novel paradigm: the emotional AX-CPT. This paradigm capitalized on the use of controlled facial expressions as a response modality to generate S-R incompatibility that was either emotional or non-emotional in nature. The examination of brain activity associated with the processing of these two forms of S-R incompatibility helps clarify the extent to which emotional conflict relies on neural circuitry common to that associated with more traditionally studied forms of cognitive conflict.

Output: contrast


Input: Claim: The blood-brain barrier protects the brain from harmful substances. [SEP] Text: Clearance of lactate from the brain has recently been reviewed in some detail [146] (see also footnote 26 in [4]). In brief lactic acid is transported across the blood–brain barrier by passive transport mediated by MCT1 (SLC16A1) present in both luminal and abluminal membranes. Lactate both enters and leaves the brain by this route. Lactate is generated within the brain by partial metabolism of glucose and by metabolism of glutamate [347, 348]). Under resting conditions when lactate concentrations are low, the clearance, CL = PS ~ 60–100 µL g−1 min−1 [349,350,351,352], far exceeds the expected clearance, ~ 1 µL g−1 min−1, by a strictly perivascular route. It is often said that transport of lactate across the blood–brain barrier is slow (see e. g. Pardridge’s account [189]). But these statements refer to the amounts transported not the permeability. The lactate clearance (= PS product) calculated for low concentrations from the kinetic constants that Pardridge presents, Kt = 1. 8 mM and Tmax = 91 nmol g−1 min−1, is 50 µL g−1 min−1, close to that stated above. Quistorff et al. [353] and Boumezbeur et al. [352] have emphasized that lactate from the periphery can be an important source of energy in the brain during heavy exercise. There is clear evidence that during periods of increased neural activity the blood–brain barrier is not the only route of lactate removal from the sites of activity [354,355,356,357]. This may be particularly important in circumstances where the lactate concentration is also increased in the rest of the body, e. g. as a result of physical exercise. Under these circumstances the net transport across the blood–brain barrier is likely to be inwards [352, 353]. Other routes for efflux cannot be just perivascular transport as seen with inulin because that isn’t fast enough. One suggested explanation is perivascular transport augmented by transfer between astrocyte endfeet via gap junctions. This can lead to movement of lactate from sites of activity either to inactive regions or to perivascular spaces of larger blood vessels [356,357,358] (see Fig. 15).

Output: pass


Input: Claim: Gene expression analysis helps understand cellular responses to stimuli. [SEP] Text: On the other hand, this study also indicated a great GC content variation that ranged from 50% to 100% (in two genes) which agrees with a previous literature indicating GC content in a eukaryotic organisms is highly variable and may be from as low as 30% to as high as 90% (Sharp 2001). 5. Conclusionanalysis has unraveled great variations in the number of TSSs in promoter region and percent GC concentration in both promoter and gene body sequences. The study also discovered CpG rich sequences and the common motifs shared by Leishmania donovani BPK282A1 genes and the possible transcription factors associated with the sequence. Hence, the investigation unfolded gene expression regulation of Leishmania donovani BPK282A1 genes bringing new insight and contributing to understand mechanisms that underly its adaptation to different environments and development of robust drug and vaccine that targets the regulatory regions. DeclarationsData availability All the data were obtained from NCBI and available online. Competing interest All authors do not have any conflict of interest and have seen and read the final version of this manuscript. Authors’ contribution KJ conceived the idea and developed the proposal. He also obtained the data from NCBI and performed all the statistical analysis using different software and wrote the initial and final version of the paper. MK supervised the overall work and gave advise on how to write the manuscript. AM helped in editing and providing technical support on how to use online tools. 2015. “Capture for Panels. ” Genomics, Elsevier Inc. , 251–69. Bailey, Timothy and, and Charles Elkan. 1994. “Fitting a by Expectation Maximization. ” AAAI Press: 3–9. “BDGP: Promoter Prediction. ” (February 3, 2021). Boeva, Valentina. 2016. “Analysis of Motifs for in Eukaryotic Cells. ” Frontiers in Genetics 7(FEB). Buates, Sureemas, and Greg Matlashewski. 2001. “ of. ” of Immunology 166(5): 3416–22. Buske, Fabian A. , Mikael Bodén, Denis C. Bauer, and Timothy L. Bailey. 2010a. “to. ” Bioinformatics 26(7): 860–66.

Output: corroborate


Input: Claim: All behaviors can be understood solely through neural circuitry. [SEP] Text: Specifically, the current findings suggest that both emotional and non-emotional conflict commonly engage a number of brain regions associated with cognitive control, including the dorsal ACC and lateral PFC, as well as certain areas implicated in both emotional processing and cognitive control, such as bilateral anterior insula. Additionally, most of these common regions demonstrated higher activity when processing emotional (versus non-emotional) conflict; in contrast, we observed no conflict-sensitive regions where the non-emotional task elicited greater activity than the emotional task. Our findings are in line with several other studies examining the neural basis of emotional versus non-emotional conflict. Processing of both kinds of conflict may rely on cognitive control-related brain areas [17], [49]. In particular, mechanisms underlying both emotional and non-emotional conflict detection have been localized to the dorsal ACC [15], [16], [50]. However, the present results are inconsistent with the older hypothesis that rostral and dorsal subdivisions of the ACC are devoted to processing emotional and cognitive conflict, respectively [45]. In particular, although we observed robust conflict-related activation in the dorsal ACC in both Emotion and Neutral conditions, no such patterns were observed in the rostral ACC, even when focusing exclusively on Emotion conflict. The absence of emotion-specific conflict regions in the ACC during task processing may be surprising from the perspective of classic theoretical distinctions, but is actually relatively consistent with the prior literature. As discussed previously, original variants of the emotion Stroop actually target emotional distraction or even non-affective variables, and as such may not be appropriate for the study of emotional conflict, as suggested by recent conceptual analyses [14]. More recent studies that utilize conflict-based variants of the emotional Stroop and related tasks have been equivocal as to whether rostral ACC is either engaged, or associated with the detection (rather than resolution) of emotional conflict [15], [16]. Additionally, in one recent study rostral ACC activity during the emotion-conflict Stroop was dependent on the trait anxiety level of participants [23]. Thus, the current study adds to prior literature in suggesting that caution is warranted regarding whether the rostral ACC should in fact be associated with emotion conflict processing per se. Instead, further investigation of this region is needed, that focus on examining potential alternative accounts such as emotional distraction, conflict resolution, and individual trait anxiety.

Output: contrast


Input: Claim: The blood-brain barrier protects the brain from harmful substances. [SEP] Text: Much of the lactate removed from the parenchyma via perivascular transport is likely to be removed from the brain along with CSF, though a proportion reaches lymph, possibly via the meninges, without first mixing with CSF. Lactate in CSF that leaves via the cribriform plate is delivered to the nasal mucosa from which it may return to blood either indirectly via lymph or directly by crossing peripheral capillary walls [85, 120, 125]. Footnote 16 Fig. 15(Diagram modified from Figure 7c in Gandhi et al. [358])Lactate removal from the brain. Lactate produced within the brain can be effluxed via the blood–brain barrier or via perivascular routes. It may reach the latter locally near the site of its production or at more distant sites having been transferred between astrocytes via gap junctionsFull size imageIt remains puzzling why so much of the lactate produced within the brain during nerve activity appears to be removed rather than serving as fuel for oxidation in neurons as proposed in the astrocyte neuron lactate shuttle (ANLS) hypothesis (G. A. Dienel, personal communication). However, at least according to Dienel [345] the available evidence is that the oxygen consumption does not increase sufficiently during nerve activity for shuttling of lactate from astrocytes to neurons and further oxidative metabolism of lactate in neurons to be an important mechanism. Furthermore using expression of a genetically encoded NAD sensor that can be monitored in real time with cellular resolution, Diaz-Garcia et al. [346] have found in mice that nervous activity induces neural production rather than consumption of lactate. For an alternative view see e. g. [344]. 5. 5 Amino acidsIn order to put the importance of efflux of amino acids from brain parenchyma into context, it is necessary to consider not just the fluxes and transporters but also the need for fluxes. Amino acids are required within the brain for protein synthesis (see Fig. 16) and for maintenance of pools of neurotransmitters, in particular glutamate and GABA (see Fig. 17). Amino acids are also needed for synthesis of many other substances, e. g. nucleosides, but when considering overall balance this demand has usually been ignored as being relatively minor and it will not be considered further here (compare [359]).

Output: pass


Input: Claim: Machine learning is increasingly used in predicting protein structures. [SEP] Text: Our research indicates that various factors, such as presence of gastrointestinal varices accompanied by bleeding, ALB levels, PLT levels, International normalized ratio, and Width of portal vein, are closely linked to the development of PVT. Previous investigations have also proposed that decompensation and a low platelet count are potential risk factors for PVT(31). Nevertheless, there has been some controversy surrounding the reproducibility of Width of portal vein as a determining factor for PVT development(32). Our study offers compelling evidence that an accurate measurement of Width of portal vein can serve as a valuable predictive tool for PVT development. Furthermore, our findings imply that individuals with hepatitis B cirrhosis who have encountered upper gastrointestinal bleeding are at an elevated risk for PVT. This could be attributed to the administration of hemostatic treatment after bleeding incidents, which could induce a hypercoagulable state and raise the likelihood of PVT. The performance of the model based on artificial neural network (ANN) in predicting the occurrence of portal vein thrombosis (PVT) at 3/5 years was exceptional. This was confirmed by the significantly high area under the curve (AUC) value of 0. 956 obtained from training and calibration curves. In contrast, other models like MELD and CTP demonstrated lower AUC values. The remarkable predictive ability of our ANN model was particularly evident in patients diagnosed with cirrhosis. One advantage offered by ANN models is their capacity to acquire knowledge from data and optimize prediction accuracy by adjusting the connections among variables. In contrast to traditional logistic regression or Cox regression models, ANN models are non-linear and iteratively train the factors relevant to the outcome. This characteristic enables them to achieve a greater level of prediction accuracy (33, 34, 35). It is important to acknowledge several limitations of this study that need to be considered. Firstly, it is crucial to recognize that this study has a retrospective design, which introduces a certain degree of bias in participant selection. Secondly, it was not feasible to compare the baseline data of the external validation group, thus necessitating further studies to supplement this aspect. Moreover, this study did not collect relevant indicators such as portal vein blood flow velocity, splenic vein diameter, spleen thickness, thromboelastography, among others. Incorporating these indicators in future studies has the potential to enhance the accuracy of the prediction model.

Output: corroborate


Input: Claim: All behaviors can be understood solely through neural circuitry. [SEP] Text: In contrast to the pattern in the rostral ACC, there were significant effects of emotion on activation in a number of regions associated with cognitive control functions, including the dorsal ACC and lateral PFC. Interestingly, these effects were observed as significant condition (Emotion > Neutral) and conflict (Conflict > No Conflict) effects, without a significant condition × conflict interaction. In other words, the emotion effects were additive to conflict, rather than interactive, which suggests two independent mechanisms. At first glance, this pattern seems somewhat counter-intuitive, since the presence of affectively-valenced content did not selectively modulate the magnitude of the conflict effect, but instead increased activation equivalently on both high and low-conflict trials. Nevertheless, the pattern may actually be fairly consistent with interpretations regarding the nature of emotional conflict and control. In particular, a key feature of the Emotional AX-CPT is that in the Emotion condition, there should be a relatively automatic, but task-irrelevant, subjective emotional reaction to the affective content present in the probe. This emotional reaction is task-irrelevant because correct response selection requires consideration only of the cognitive classification of the probe as having positive or negative content (and in integrating this information with cue classification). Indeed, the subjective emotional response to the probe, which may automatically trigger a tendency to activate the associated facial expression, can lead to an additional source of response uncertainty. For example, if viewing a negatively valenced probe stimulus triggers a tendency to make a frown expression (or likewise, if viewing a positively valenced probe stimulus triggers a tendency to smile), confusion can be generated regarding whether this “expression tendency” is appropriate for the current trial (i. e. , correct on AX but incorrect on BX trials). Under such circumstances, from a cognitive control perspective, the optimal task strategy would be to suppress any subjective emotional responses that might be experienced in order to reduce response uncertainty. Because such task-irrelevant emotional response tendencies can occur on all trials in the Emotion condition, there would be generally higher cognitive control demands in this condition relative to Neutral. In addition to the additive effects of emotion and conflict observed in regions associated with cognitive control, this same pattern was also present in the left amygdala, at least under an adjusted statistical threshold.

Output: contrast


Input: Claim: The blood-brain barrier protects the brain from harmful substances. [SEP] Text: The required amino acids must either be synthesized inside the brain or enter from outside primarily across the blood–brain barrier. Fig. 16Simplified overview of fates of amino acids in the brain parenchyma. Essential amino acids enter and leave the parenchyma across the blood–brain barrier. Non-essential amino-acids, e. g. glutamate (Glu), glutamine (Gln), and GABA can be synthesized within the brain. The amino groups for the synthesis are supplied either by transamination as shown for glutamate or to some extent [359] by incorporation of NH4+ by glutamate dehydrogenase. The latter route is believed to be minor [359, 641]. NH4+ is added to form the amide group of glutamine by glutamine synthetase (see Fig. 17). Within the parenchyma amino acids are used for synthesis of proteins and (not shown) formation of other nitrogen containing compounds, e. g. nucleotides. New amino acids must be supplied to replace those lost by metabolism. In the brain, input of amino acids is also required to provide amino groups to replace glutamate lost from the pool of amino acids involved in glutaminergic (and GABAergic, not shown) neurotransmission (see Fig. 17). α-KG α-ketoglutarate, e. a. a essential amino acids, t. a transaminaseFull size image Fig. 17The glutamate/glutamine cycle shown in bold with indication of some of the losses and of replenishment of glutamate by denovo synthesis. Glutamate (Glu) in the presynaptic neuron is packaged into vesicles and released into the ISF during neurotransmission. Most of the glutamate is taken up into the astrocytes by the transporter Eaat1 (glast, Slc1a3) where it is converted to glutamine (Gln) by addition of an NH4+ by the enzyme glutamine synthase (g. s) [642, 643]. The glutamine is transported into the ISF by Snat3 and/or Snat5 (Slc38a3 and Slc38a5) from which it is taken up into the presynaptic terminals again by a transporter that may be a Snat. The glutamate is then regenerated by glutaminase (g. a).

Output: pass


Input: Claim: Machine learning is increasingly used in predicting protein structures. [SEP] Text: May 16, 2019 Predicting protein function and annotating complex pathways with machine learning Kihara’s team at have created novel computational approaches for predicting protein functions. Instead of following a one-protein-one-function approach, their algorithms can predict the functional relationships of entire groups of proteins related to a specific biological process. The team has also expanded into mining oversighted or previously unknown proteins that have multiple, independent functions. The team’s methods challenge the logic behind conventional protein function studies and propose tools that may better capture the complicated nature of protein interactions in biological processes. Proteins are the main working units of biology. Identifying and understanding what proteins do is crucial for biologists hoping to solve the complex interactions and systems that drive cellular processes. Although protein function needs to be ultimately validated by hand in the wet lab, researchers first need a hypothesis in order to design assays, which can then define the probable function of a protein. Bioinformatics for predicting protein function Biologists can build such hypotheses of gene function with computers. As genome sequencing becomes routine in experimental laboratories, computational gene function prediction has also become increasingly important. Computational methods are very suitable for function prediction because function information of a gene can be inferred from a database search that identifies similarity between the gene and known proteins or experimental data. Sequence similarity tools like the Tool (BLAST) is one such method that searches against all previously recorded sequences and suggests a scored list of possible roles for it. Problems with previous computational methods However, existing bioinformatic tools can’t always predict protein function accurately, and often end up incorrectly annotating proteins within a biological system. Traditional protein function prediction tools like BLAST are usually reliable when a high sequence similarity is detected, but their accuracy falls quickly for sequences with lower similarities. For example, enzyme functions differ immensely when similarity scores fall below a certain level. Moreover, in many cases traditional methods do not annotate any function if highly similar sequences are not found, leaving many genes unannotated. In addition, other metrics such as similarity in three-dimensional structure, gene expression, or interaction data could be used. However, each of these metrics are often missing for many proteins under investigation, and so have limited applicability in reliable research. New tools for better accuracy Recently, several new protein annotation methods have been developed to improve overall prediction accuracy. One such developer is Kihara from Purdue University, who develops function prediction methods with new logical frameworks.

Output: corroborate


Input: Claim: All behaviors can be understood solely through neural circuitry. [SEP] Text: The amygdala has typically been thought of as an emotion processing region whose activity, in conflict, distraction, and regulation paradigms, will reflect the emotional valence of stimuli, rather than tracking cognitive control demands [16], [51], [52]. However, prior findings of amygdala activity associated with increased cognitive control have also been repeatedly observed, although they typically receive less attention in the literature. For example, in one study increased amygdala activation was associated with improved behavioral performance during working memory, selectively under high-load conditions [53]. This finding, and others [54], [55], [56], supports alternative theoretical views of amygdala function, in which this regions is postulated to mediate general vigilance/goal-relevance-detection processes that contribute to enhanced cognitive performance as well as processing of emotional demands [57], [58]. The pattern of left amygdala activation in the present task – associated with both emotion and conflict-processing – might be better characterized by such an explanation, especially considering that emotional information must be evaluated for valence, while at the same time suppressing subjective emotional responses, in order to optimally perform the task. Beyond the main effects of condition and conflict, a number of regions also exhibited distinct patterns of activity as a function of the type of interference present. As in the original AX-CPT, the emotional AX-CPT involves non-target trials eliciting conflict via two different forms of interference: AY trials, where interference is cue-based and relatively top-down in nature, and BX trials, where interference is probe-based and relatively bottom-up in nature. A number of frontal and parietal regions associated with cognitive control demonstrated significant trial effects in the present study, primarily because of BX > AY activity early in the trial (with comparable activity levels late in the trial). Previous studies of the AX-CPT have observed similar patterns of activation within the lateral PFC and other regions, demonstrating the robustness of the effect [46], [47]. The pattern of activity is typically interpreted as reflecting the higher degree of interference expectancy associated with B-cues (i. e. , associated with non-target responses) relative to A-cues (i. e. , associated with target responses), and thus increased demands for proactive cognitive control [28]. The current study extends this finding by demonstrating that this interference expectancy effects can be exhibited during emotional as well as non-emotional AX-CPT conditions.

Output: contrast


Input: Claim: The blood-brain barrier protects the brain from harmful substances. [SEP] Text: This cycle represents a large turnover of the amide group at the end of the side chain in glutamine, estimated to be 55% of the CMRglc (cerebral metabolic rate of glucose, see Sect. 5. 3) for the entire brain in rats amounting to 490 nmol g−1 min−1 (estimated value in humans 280 nmol g−1 min−1) [644] (G. A. Dienel, personal communication). However the requirement for NH4+ consumed in the conversion of glutamate to glutamine within the astrocytes is balanced by an equal release of NH4+ in the reverse conversion in neurons. Whether diffusion of NH4+ itself is adequate to transfer the nitrogen from neurons to astrocytes as shown or some other form of N carrier is required remains controversial [385, 641, 645]. Regardless, if there were no losses of glutamine or glutamate from the cycle, there would be no need for any fluxes of amino acids into or out of the parenchyma to support glutaminergic neurotransmission. However, there are losses of glutamate and glutamine from the cycle [347, 646, 647]. At least in rodents, such losses are made good by de novo synthesis of glutamate in the astrocytes. Estimates of the total rate of loss and of de novo synthesis are around 11% of CMRglc ([648, 649] (G. A. Dienel, personal communication), i. e. about 0. 11 × 0. 9 µmol g−1 min−1 ≅ 100 nmol g−1 min−1. The carbon skeletons for the de novo synthesis are derived ultimately from glucose. Glucose is metabolized to two molecules of pyruvate one of which is carboxylated by pyruvate carboxylase (p. c) (thought to be present within the brain only in astrocytes) to form oxaloacetic acid (OAA) a component of the citric acid cycle. Addition of acetyl-CoA from the second pyruvate then forms citrate, which is decarboxylated to form α-ketoglutarate (α-KG). Glutamate is then formed either a by transamination (t.

Output: pass


Input: Claim: Machine learning is increasingly used in predicting protein structures. [SEP] Text: In 2009, his team created an automated predictive algorithm, called the extended similarity group (ESG) method, which runs a continual comparing system, instead of a single search. From each sequence found from the first inquiry, the ESG algorithm runs a second search through the database. By combining results from this multi-levelled tactic, the ESG method significantly improves functional scoring for query proteins and outperforms previous function prediction algorithms. Yet the team did not stop here. In a 2019 paper, they combined phylogenetic tree construction tools with traditional sequence-based prediction, called the Phylo-PFP method. They first confirmed that close similarities of protein sequences did not align with the proteins’ distances on a phylogenetic tree. By adding these distances into the sequence homology score, the protein query ranks became more reliable, and they could be more accurately linked to their gene source. Unsurprisingly, the study established Phylo-PFP significantly improved the function prediction accuracy over existing methods. Protein group function annotation Protein function annotation is typically run on a one-protein-one-function approach, yet this mindset can grossly oversimplify the protein function universe. In fact, most experiments find dozens of interacting proteins related to a single biological event. To understand the role of an entire protein set, their function should be determined from the group as a whole, even if the function of each individual protein is unknown. This is no simple task. Kihara from develops function prediction methods with new logical frameworks. Therefore, Dr Kihara’s team focused on a new computational approach for annotating the functions of protein groups. In 2019, they proposed an iterative Prediction (iGFP) method, which holds a completely new logical framework at its core. The iGFP algorithm considers a set of proteins as input, and predicts the role of the function of the entire group, as well as its individual members. The iGFP algorithm blends sequence data from multiple sources and builds a complementary network. The method then separates the proteins into clusters that have functional relevance and compares them based on functional and interaction relationships. The iGFP algorithm iteratively assigns functions to protein groups and to individual proteins in the groups. Moreover, the system automatically assumes that some proteins are unknown and uses a range of other comparative features to make an accurate prediction.

Output: corroborate


Input: Claim: All behaviors can be understood solely through neural circuitry. [SEP] Text: Cole MW, (2007) The cognitive control network: Integrated cortical regions with dissociable functions. Neuroimage 37: 343–360. View 8. (2005) N-back working memory paradigm: a meta-analysis of normative functional neuroimaging studies. Mapp 25: 46–59. View 9. (2003) Neuroimaging studies of working memory: a meta-analysis. 3: 255–274. View 10. (2004) Conflict monitoring and anterior cingulate cortex: an update. Sci 8: 539–546. View 11. 3rd, (2004) Anterior cingulate conflict monitoring and adjustments in control. Science 303: 1023–1026. View 12. Carter CS, van (2007) Anterior cingulate cortex and conflict detection: an update of theory and data. 7: 367–379. View 13. (1998) Anterior cingulate cortex, error detection, and the online monitoring of performance. Science 280: 747–749. View 14. (2010) Using the Stroop task to study emotion regulation. In: editors. in Society, Mind, and Brain. Oxford: Press. 113. 15. (2006) Interference produced by emotional conflict associated with anterior cingulate activation. 6: 152–156. View 16. (2008) Dissociable neural systems resolve conflict from emotional versus nonemotional distracters. 18: 1475–1484. View 17. (2008) Supporting the Control of Affective and Cognitive Conflicts. J Cogn Neurosci. View 18. (2008) Controlling emotional expression: behavioral and neural correlates of nonimitative emotional responses. 18: 104–113. View 19. Mathews A, Mac(1985) Selective processing of threat cues in anxiety states. Ther 23: 563–569. View 20. (2006) Lexical characteristics of words used in emotional Stroop experiments. Emotion 6: 62–72. View 21. (2004) A rational look at the emotional stroop phenomenon: a generic slowdown, not a stroop effect. J Gen 133: 323–338. View 22. (2006) Resolving emotional conflict: a role for the rostral anterior cingulate cortex in modulating activity in the amygdala. Neuron 51: 871–882. View 23.

Output: pass


Input: Claim: The blood-brain barrier protects the brain from harmful substances. [SEP] Text: a) of α-ketoglutarate using leucine or other amino acids as source (see e. g. [383, 641, 645, 650], or b by addition of NH4+ [366] catalyzed by glutamate dehydrogenase (g. d). The latter is believed to be a minor pathway [359, 366, 641]. The source of the amino groups for transamination is considered further in Sect. 5. 5. 3 and Fig. 18. Data for the pathways involved in glutamate synthesis are much less extensive for human than for rat. Rothman and colleagues [651, 652] have argued that the α-ketoglutarate is synthesized in astrocytes based on measurements of incorporation of 13C (see [653, 654]). However, the failure to find a key transaminase in human astrocytes by immunohistochemistry [655, 656] has cast some doubt on astrocytes being the major site for the conversion from α-ketoglutarate to glutamate. For recent reviews of glutamate synthesis see [386, 641, 645]Full size image The need for amino acid input is different from the need for glucose input. Glucose is the basic fuel consumed in metabolism and must be supplied continually in large quantities. Amino acids are needed to allow the maintenance of cell structure and composition. But, the N containing constituents of the cells either are not consumed during metabolism or if they are they are partly replaced internally. The balance between influx and efflux across the blood–brain barrier need only provide sufficient amounts of amino acids to top up losses. Any metabolic losses that do occur will either be by efflux from the brain or by generation of NH4+ and carbon compounds. The latter become part of the carbon metabolism of cells. Possible fates of the NH4+ include: diffusion across the blood–brain barrier; reaction with glutamate to form glutamine, which is then exported from the parenchyma; and use in amino acid synthesis [359, 360]. Glutamate synthesis is considered further in Sect. 5. 5. 5. For each amino acid at steady-state, its net fluxes across the blood–brain barrier and via perivascular routes and its net rate of synthesis must add to zero so that the concentrations in the brain parenchyma can remain constant.

Output: pass


Input: Claim: Machine learning is increasingly used in predicting protein structures. [SEP] Text: During this scan, the algorithm considers protein-protein interactions, phylogenetic profile similarity, gene co-expression, large-scale pathway similarity, and gene ontology similarity. This type of comprehensive group function prediction could be an altogether improved reflection of the real mechanisms at work in, for example, developmental or disease-causing pathways. Identifying proteins with multiple functions In addition to analysing protein groups, the Kihara team has taken another step away from the one-protein-one-function scheme by studying multi-functional proteins. Most bioinformatic tools do not take into account that proteins, enzymes in particular, can be multi-functional. lab has thus aimed to predict whether a query protein is a moonlighting protein – one that has multiple autonomous and often unrelated functions. These proteins are difficult to annotate, since their functions are not genome or protein family specific, nor linked to other indicators, such as a shared switching mechanism. Yet these proteins play key roles in cellular disease states such as cancers, and so identifying them is important. discuss functions assigned to a metabolic pathway. To solve the problem, Dr Kihara’s team has developed a new systematic approach to study moonlighting proteins. In 2016, the team proposed an automated prediction framework which uses several non-sequence-based data to identify moonlighting proteins. They used machine learning classifiers to predict multi-functional proteins, after which they cross validated the results using existing databases. Dr Kihara’s team could predict moonlighting proteins that had previous gene sequence data with 98% accuracy. Even if no sequence data was available, the system showed an impressive 75% accuracy. The iGFP algorithm considers a set of proteins as input and predicts the function of the entire group, as well as its individual proteins. Furthermore, in a 2018 paper the team used deep learning to sniff out moonlighting proteins from previously published literature. Their text mining tool DextMP could find out whether a protein had multiple functions or not based on information from journal publications and functional descriptions from protein databases. Using systematic literature processing tools, the researchers could significantly reduce time to annotate moonlighting proteins and move closer to clarifying the complex interplay of proteins within the cell. Improvements and future predictions Computational biology desperately needs new ways to accurately reflect the true nature of biological processes.

Output: corroborate


Input: Claim: All behaviors can be understood solely through neural circuitry. [SEP] Text: (2010) Adding fear to conflict: a general purpose cognitive control network is modulated by trait anxiety. 10: 357–371. View 24. Dimberg U, (1998) Rapid facial reactions to emotional facial expressions. of Psychology 39: 39–45. View 25. (2010) Exploring emotional and cognitive conflict using speeded voluntary facial expressions. Emotion 10: 842–854. View 26. 'Reilly RC (1996) A computational approach to prefrontal cortex, cognitive control and schizophrenia: recent developments and current challenges. 351: 1515–1527. View 27. (2002) The role of the prefrontal cortex in normal and disordered cognitive control: a cognitive neuroscience perspective. In: editors. Principles of frontal lobe function. Oxford: Press. 447. 28. (2009) Flexible neural mechanisms of cognitive control within human prefrontal cortex. 106: 7351–7356. View 29. (1999) International affective picture system (IAPS): technical manual and affective ratings. Gainesville: University of Florida, Center for Research in Psychophysiology. 30. (2003) Mixed blocked/event-related designs separate transient and sustained activity in fMRI. Neuroimage 19: 1694–1708. View 31. Talairaich J, (1988) Co-planar stereotaxic atlas of the human brain: 3-dimensional proportional system: an approach to cerebral imaging. New York: Thieme. 32. (2007) Volumes, spatial extents and a probabilistic atlas of the human basal ganglia and thalamus. Neuroimage 38: 261–270. View 33. (2007) Separate brain regions code for salience vs. valence during reward prediction in humans. Mapp 28: 294–302. View 34. (2007) The neural correlates of subjective value during intertemporal choice. 10: 1625–1633. View 35. (2001) Anticipation of increasing monetary reward selectively recruits nucleus accumbens. J Neurosci 21: RC159. View 36. (2003) A region of mesial prefrontal cortex tracks monetarily rewarding outcomes: characterization with rapid event-related fMRI. Neuroimage 18: 263–272. View 37. (2004) The functional neuroanatomy of the human orbitofrontal cortex: evidence from neuroimaging and neuropsychology. 72: 341–372.

Output: contrast


Input: Claim: The blood-brain barrier protects the brain from harmful substances. [SEP] Text: However, there are major complications in applying this principle to the interpretation of data: there are more than 20 different amino-acids, inter-conversions between them by transamination are common, and they compete with each other for the many amino acid transporters. Indeed the major application of this principle comes when considering overall N balance. Allowing the fluxes that are required (see Sect. 5. 5. 1) while maintaining ISF concentrations of all amino acids except glutamine well below those in plasma (see Sect. 5. 5. 2) is a major challenge and it is not yet certain how the available transporters (see Sect. 5. 5. 4) achieve these objectives. 5. 5. 1 Requirements for amino acid fluxes (and NH4 +)While it is clear that there are losses of essential amino acids from brain parenchyma and thus that some influx of amino acids must occur, it is difficult to obtain a quantitative estimate of the influx required. Using radiolabelled amino acids in rats, Dunlop et al. [361,362,363] found a turnover rate for the protein content of rat brains to be about 0. 6% h−1. Using a protein content of about 100 mg for each gram of brain and the molecular weight of an average amino acid, perhaps 125 Da, that corresponds to a rate of incorporation of amino acids of about 80 nmol g−1 min−1. Similarly amino groups required for de novo synthesis of glutamate amount to about 100 nmol g−1 min−1 (see legend to Fig. 17). Many of the amino acids needed for protein synthesis are supplied either by de novo synthesis (which, however, still requires some source of amino groups, see Fig. 16) or by recycling those released during protein breakdown, which averaged over enough time must be occurring at the same rate as synthesis. Furthermore it may be possible to reuse some of the NH4+ lost from the glutamate/glutamine cycle in the de novo synthesis of glutamate. Thus the sum of the estimates above, 180 nmol g−1 min−1, is likely to exceed the actual requirement for amino-acid input. Because the brain parenchyma must be in N balance and there must be net inputs of essential amino acids, there must also be a route or routes for N removal.

Output: pass


Input: Claim: Machine learning is increasingly used in predicting protein structures. [SEP] Text: Dr Kihara’s team has made innovative strides to step away from a traditional one-protein-one-function effort and identified functions for entire protein groups. Their algorithms outperform previous sequence-based methods by layering multiple protein characteristics and taking into account evolutionary relationships, which can be better indicators of shared functions than the simple amino acid backbone. Further, the team’s machine learning methods can predict whether a protein serves a double role, and whether such proteins have unknowingly been described in previous literature. Despite these promising developments, bioinformatic prediction tools are only as intelligent as their design, and there is still a way to go towards fully automated, AI-driven research in protein function annotation. Overall, Dr Kihara’s team suggests that combining previous methods with emerging ones from omics experiments and evolution distance analysis will further solidify functional prediction accuracies in the future. What kind of role will machine learning play in protein function prediction and understanding biological processes? <> Machine learning has already been playing a big role in protein function prediction, and more widely, in bioinformatics. It is particularly effective in identifying subtle signatures that are easily overlooked by humans in input data including protein sequences that are relevant to particular functions. It is also very suitable for integrating many different types of data together to make predictions. Predicting protein function and annotating complex pathways with machine learning was last modified: November 8th, 2023 Keywords: Computational methodsKiharaprotein functionprotein function predictionDownload this 1745. Jain, A. , & Kihara, D. (2019). Phylo-PFP: improved automated protein function prediction using phylogenetic distance of distantly related sequences. Bioinformatics. 35(5):753-759. Jain, A. , Gali, H. , & Kihara, D. (2018). Identification of in Techniques. Proteomics, 18(21–22), 1800083. Khan, I. K. , & Kihara, D. (2016). Genome-scale prediction of moonlighting proteins using diverse protein association information. Bioinformatics, 32(15), 2281–2288. Khan, I. K. , Jain, A. , Rawi, R. , Bensmail, H. , & Kihara, D. (2019). Prediction of protein group function by iterative classification on functional relevance network.

Output: corroborate


Input: Claim: Quantum cryptography offers theoretically unbreakable encryption. [SEP] Text: liu. seSearch for publications in DiVA Please wait. . . Simple search Advanced search - Research publicationsAdvanced search - Student thesesStatistics EnglishSvenskato content Change searchSearchdocuments with full text in -1CSV 2CSV 3CSV 4CSV 5CSV all metadataCSV all metadata version 2-to record Permanent link Direct link styleapaieeemodern-language-association-8th-editionvancouveroxfordOther style apaieeemodern-language-association-8th-editionvancouveroxfordOther styleMore stylesLanguagede-DEen-GBen-USfi-FInn-NOnn-NBsv-SEOther locale de-DEen-GBen-USfi-FInn-NOnn-NBsv-SEOther localeMore languagesOutput formathtmltextasciidocrtf htmltextasciidocrtfCreatethe Unbreakable: in Bell’s Theorem to öping University, Department of Electrical Engineering, Information Coding. Linköping University, Faculty of Science & Engineering. ORCID iD: 0000-0002-8032-1466 2017 (English)Doctoral thesis, comprehensive summary (Other academic) Abstract [en] In this thesis we study device-independent quantum key distribution based on energy-time entanglement. This is a method for cryptography that promises not only perfect secrecy, but also to be a practical method for quantum key distribution thanks to the reduced complexity when compared to other quantum key distribution protocols. However, there still exist a number of loopholes that must be understood and eliminated in order to rule out eavesdroppers. We study several relevant loopholes and show how they can be used to break the security of energy-time entangled systems. Attack strategies are reviewed as well as their countermeasures, and we show how full security can be re-established. Quantum key distribution is in part based on the profound no-cloning theorem, which prevents physical states to be copied at a microscopic level. This important property of quantum mechanics can be seen as Nature's own copy-protection, and can also be used to create a currency based on quantummechanics, i. e. , quantum money. Here, the traditional copy-protection mechanisms of traditional coins and banknotes can be abandoned in favor of the laws of quantum physics.

Output: contrast


Input: Claim: The blood-brain barrier protects the brain from harmful substances. [SEP] Text: As the brain normally doesn’t produce urea as a means of disposing of NH4+ [364,365,366], the two main routes for exit to be considered are efflux of NH4+ and efflux of glutamine. Fluxes of NH4+ are easily demonstrated to occur in both directions across the blood–brain barrier and are almost certainly by diffusion across the membranes of NH3 combined with transport either of H+ in the same direction or, more likely, of HCO3− in the opposite direction [4, 359, 367]. Because concentrations of NH4+ in brain, 150–300 µM, and CSF, 100–300 µM, normally exceed those in arterial plasma, 50–250 µM [359], it is likely that there is some net NH4+ efflux. However, an arterio-venous difference in NH4+ concentration and thus its net transport have only been demonstrated in the brain when plasma NH4+ concentration is raised as in hepatic insufficiency [359, 368]. There is then net NH4+ entry, rapid incorporation of the NH4+ into glutamine by reaction with glutamate [359], and efflux of the resultant glutamine. Glutamine efflux is considered further in Sect. 5. 5. 4. Lee et al. [360] made the interesting suggestion that much of the NH4+ that moves from brain microvascular endothelial cells to plasma is produced within the endothelial cells by glutaminase acting on glutamine. However, that taken alone would suggest that there should also be a substantial efflux of glutamate, which has not been observed. Alternatively the NH4+ effluxed may derive from metabolism of both glutamine and glutamate. This is considered further in Sect. 5. 5. 4. 5. 5. 2 Concentrations of amino acids in CSF and ISFValues of amino acid concentrations measured in blood plasma, CSF and ISF are summarized in Table 3. There is agreement in all studies that, with the exception of glutamine, the concentrations of all other amino acids in CSF and ISF are substantially less than those in plasma. This could arise if the rates of consumption were to reduce the concentrations greatly or if there were active transport of amino acids from brain fluids to blood. Whether or not there is a substantial difference in amino acid concentrations between CSF and ISF is less clear.

Output: pass


Input: Claim: Coral reefs support a diverse range of marine species. [SEP] Text: IntroductionMesophotic coral ecosystems (MCEs; light-dependent coral ecosystems found at depths between 30 to 150 m (Hinderstein et al. 2010; Kahng et al. 2014)), have received increasing attention from the scientific community over the past few decades. However, they are still largely underexplored compared to their shallow-water counterparts (Bongaerts and Smith 2019; Pyle and Copus 2019; Soares et al. 2020; Stefanoudis et al. 2022). The increasing interest in MCEs was initially driven by the potential refuge MCEs could offer to threatened shallow coral reefs, the so-called deep reef refugia hypothesis (DRRH) (Glynn 1996), and the evolution of technology, allowing exploration of these deeper, cooler waters (Bongaerts et al. 2010). More recently, the interest has been driven by the desire to investigate the distinct biological and environmental characteristics of MCEs compared to shallow reefs, and the functional role that MCEs play in coral reef ecosystems (Kramer et al. 2020; Carpenter et al. 2022; Pérez-Rosales, et al. 2022a). Recent research has revealed that MCEs are more biodiverse and widespread than previously expected, with 80% of all coral reef habitat falling within MCEs (based on depth alone) and they are an important component for maintaining overall reef biodiversity (Englebert et al. 2017; Shoham and Benayahu 2017; Muir and Pichon 2019; Pyle and Copus 2019; Pérez-Rosales et al. 2022). Yet the protection status of MCEs remains poor (Hernandez‐Agreda et al. 2022). In fact, despite meeting the international criteria used to identify priority areas for conservation policies, and hence being good candidates for future Area (MPA) designation (Soares et al. 2020), MCEs and deeper reefs (i. e. rariphotic zone 150–300 m, sensu Baldwin et al. (2018) are considered under-protected and under-represented in marine spatial planning (Rocha et al. 2018; Stefanoudis et al. 2022). Indeed, the few protected mesophotic and deeper reefs were often included incidentally due to geopolitical boundaries (e. g.

Output: corroborate


Input: Claim: Quantum cryptography offers theoretically unbreakable encryption. [SEP] Text: 2014 (English)In: Journal of Physics A: Mathematical and Theoretical, ISSN 1751-8113, E-ISSN 1751-8121, Vol. 47, no 42, p. 424032-10. 1088/1751-8113/47/42/424032 (DOI)000344222200033 () Available from: 2014-12-05 Created: 2014-12-05 Last updated: 2017-12-05 2. Hacking the Bell test using classical light in energy-time entanglement–based quantum key distributionOpen this publication in new window or tab >>Hacking the Bell test using classical light in energy-time entanglement–based quantum key distributionJogenfors, JonathanLinköping University, Department of Electrical Engineering, Information Coding. Linköping University, of Technology. . . . Larsson, Jan-ÅkeLinköping University, Department of Electrical Engineering, Information Coding. Linköping University, of Technology. Show others. . . 2015 (English)In: Science Advances, E-ISSN 2375-2548, Vol. 1, no 11, p. 1-7, 3. 63 at 97. 6% faked detector efficiency using tailored pulses of classical light, which exceeds even the quantum prediction. This is the first demonstration of a violation-faking source that gives both tunable violation and high faked detector efficiency. The implications are severe: the standard Clauser-Horne-Shimony-Holt inequality cannot be used to show device-independent security for energy-time entanglement setups based on Franson’s configuration. However, device-independent security can be reestablished, and we conclude by listing a number of improved tests and experimental setups that would protect against all current and future attacks of this type. Place, publisher, year, edition, pages for the Advancement of Science, 2015 :nbn:se:liu:diva-114210 (URN)10. 1126/sciadv.

Output: contrast


Input: Claim: The blood-brain barrier protects the brain from harmful substances. [SEP] Text: A Na+-linked transport system for small neutral amino acids (system A, with identifying substrate N-methyl-a-aminoisobutyric acid, MeAIB) [373]. Another system for glutamate [374]. The ability to prepare vesicles enriched in membranes from either the luminal or abluminal membranes of the endothelial cells [375] allowed localization of transport activities to the separate membranes with the generalization (since revised, see Sect. 5. 5. 6) that transporters in the luminal membrane are not Na+-linked and hence bidirectional while those in the abluminal membrane are Na+-linked favouring transport from ISF into the endothelial cells [44]. There are now known to be many more types of transporter present at the blood–brain barrier than initially suggested by identification of these systems (see Sect. 5. 5. 6). Large rates of efflux of amino acids from CSF to blood were detected in cats [376] and rabbits [377] undergoing ventriculo-cisternal or ventriculo-cortical subarachnoid space perfusions. However, it was not possible in these studies to determine how much of the efflux was going via the choroid plexuses and how much via the parenchyma and the blood–brain barrier. Evidence that the latter route is important derives from the observation that transfer was much more rapid in ventriculo-subarachnoid infusion than in ventriculo-cisternal infusion. Both types of perfusion expose the infused fluid to the choroid plexuses, but in the former a much larger surface area of parenchyma is exposed to the fluid [376]. The net flux into a region can be calculated if the blood flow to that region and the concentrations of the solute in arterial blood and the venous outflow can be measured (see Sect. 5. 5. 6). (Equating net flux out of blood with net flux into the brain ignores possible metabolism within the endothelial cells, see the end of Sect. 5. 5. 6). Net flux measurements have been attempted using rats [378], but all except one of the A − V differences were not statistically significant. The rest of the net flux data in Table 4 are for larger species. Pardridge [379] compared the influx data for rats obtained by Banos et al.

Output: pass


Input: Claim: Coral reefs support a diverse range of marine species. [SEP] Text: , a country protects its entire Zone (EEZ) and MCEs happen to fall within this boundary), rather than purposely (Soares et al. 2019; Turner et al. 2019; Stefanoudis et al. 2022). Several reviews suggest that MCEs are among the least protected ecosystems of the world’s oceans, while considered as the richest in terms of endemic and rare species (Hinderstein et al. 2010; Bridge and Guinotte 2013; Loya et al. 2016; Turner et al. 2019). This may partly be due to the lack of an holistic understanding of the patterns and drivers of diversity with depth, although the nature of spatial patterns of biodiversity has been one of the fundamental goals of ecological research for centuries (Lesser et al. 2019), and biodiversity data are crucial to provide evidence-based information for management and conservation actions for MCEs (Socolar et al. 2016). Diversity can be described at different scales. Alpha diversity identifies diversity at a local scale, while beta diversity reveals the variation in species between communities. More specifically, alpha diversity (sensu Whittaker (1960)) measures the number of species within a community, and beta diversity (sensu Whittaker (1972)) defines the variation in species composition across a gradient, e. g. along the depth gradient or between communities at different sites (Miyazawa et al. 2020). Beta diversity can be partitioned into two components: nestedness, i. e. when the species composition of the sample is a subset of a richer community, hence indicating a species loss; and species turnover, i. e. species replacement between communities, demonstrating the uniqueness of the communities within an ecosystem (Baselga 2010). These two components allow for a quantitative understanding of the variation in biodiversity gradients and the assessment of community change across environmental gradients (Pérez-Rosales, et al. 2022a). To date, studies of alpha and beta diversity have mainly focussed on terrestrial areas (Wolters et al. 2006), or shallow-water environments (McDevitt-Irwin et al. 2021). Within MCEs, where the calculation of alpha and beta diversity indices remains scarce, the majority of studies has investigated fishes or scleractinian corals (Rocha et al. 2018; Pérez-Rosales, et al.

Output: corroborate


Input: Claim: Quantum cryptography offers theoretically unbreakable encryption. [SEP] Text: liu. seSearch for publications in DiVA Please wait. . . Simple search Advanced search - Research publicationsAdvanced search - Student thesesStatistics EnglishSvenskato content Change searchSearchdocuments with full text in -1CSV 2CSV 3CSV 4CSV 5CSV all metadataCSV all metadata version 2-to record Permanent link Direct link styleapaieeemodern-language-association-8th-editionvancouveroxfordOther style apaieeemodern-language-association-8th-editionvancouveroxfordOther styleMore stylesLanguagede-DEen-GBen-USfi-FInn-NOnn-NBsv-SEOther locale de-DEen-GBen-USfi-FInn-NOnn-NBsv-SEOther localeMore languagesOutput formathtmltextasciidocrtf htmltextasciidocrtfCreatethe Unbreakable: in Bell’s Theorem to öping University, Department of Electrical Engineering, Information Coding. Linköping University, Faculty of Science & Engineering. ORCID iD: 0000-0002-8032-1466 2017 (English)Doctoral thesis, comprehensive summary (Other academic) Abstract [en] In this thesis we study device-independent quantum key distribution based on energy-time entanglement. This is a method for cryptography that promises not only perfect secrecy, but also to be a practical method for quantum key distribution thanks to the reduced complexity when compared to other quantum key distribution protocols. However, there still exist a number of loopholes that must be understood and eliminated in order to rule out eavesdroppers. We study several relevant loopholes and show how they can be used to break the security of energy-time entangled systems. Attack strategies are reviewed as well as their countermeasures, and we show how full security can be re-established. Quantum key distribution is in part based on the profound no-cloning theorem, which prevents physical states to be copied at a microscopic level. This important property of quantum mechanics can be seen as Nature's own copy-protection, and can also be used to create a currency based on quantummechanics, i. e. , quantum money. Here, the traditional copy-protection mechanisms of traditional coins and banknotes can be abandoned in favor of the laws of quantum physics.

Output: contrast


Input: Claim: The blood-brain barrier protects the brain from harmful substances. [SEP] Text: [369] with the net flux data for dogs obtained by Betz et al. [365] (see Table 4) and noted that the net fluxes are much smaller than the unidirectional influxes. With the assumption that the fluxes are similar in various species, this comparison implies that there must be large effluxes, comparable in size to the influxes. Measurements of net fluxes in dogs, sheep, and humans have produced data broadly comparable with each other (see Table 4) favouring the assumption that when expressed per gram of tissue the fluxes are the same in all species. Footnote 19 At present there are strong indications that the net flux of glutamine is outwards. This was seen in five out of six studies. There is also indication that the combined net flux of the branched chain amino acids, leucine + isoleucine + valine, is inwards. This was seen in six out of seven studies. But as described in the next section there is no evidence for a sufficiently large inwards net flux of neutral amino acids to provide for all of the transamination invoked in the explanations of glutamate turnover, at least in rats. 5. 5. 5 Observed fluxes of neutral amino acids compared with their requirement in glutamate synthesisA major difficulty is revealed by comparison of the small net fluxes for the large, essential neutral amino acids and the large provision of these amino acids required for transamination to convert α-ketoglutarate into glutamate (see Figs. 16 and 17). For this requirement to be satisfied by influx across the blood–brain barrier of leucine, isoleucine and valine, their combined net influx would need to be > 100 nmol min−1 g−1 (see Sect. 5. 5. 1). For a cerebral blood flow of 0. 57 mL min−1 g−1 (see e. g. Sect. 5. 3) that would correspond to an A − V difference > 175 µM. Given that the total of the arterial plasma concentrations for these amino acids is only 392 µM (see Table 3), this A − V difference and hence net rate of transport should have been well above the “noise” in all of the studies, even that in rats (see Table 4).

Output: pass


Input: Claim: Coral reefs support a diverse range of marine species. [SEP] Text: Secondly, the observed and extrapolated diversities at each site and depth zone were estimated by computing individual-based and sample-size based R/E curves for Hill numbers of q = 0, 1, 2; with extrapolation to a sampling effort equal to double the number of individuals (extrapolation beyond this is unreliable due to prediction bias; (Chao et al. 2014)). Thirdly, the observed and extrapolated Hill numbers were compared to assess undetected diversity and compare diversity between the depth zones and sites (Table S4). However, these results must be taken with caution as they were extracted prior to sample completeness standardisation. Finally, diversity estimates were calculated at a standardised coverage Cmax (e. g. equally complete samples) to statistically compare the benthic diversities along the depth gradient and between sites, which corresponds to the sample coverage of the depth zone exhibiting the lowest coverage when samples are extrapolated to double the number of samples per depth zone at a site (Table S5), as used in El-Khaled et al. (2022). Here, the Cmax value was 96. 4% (Fig. S1; Table S5), corresponding to the lowest sample completeness for q = 0, 1, 2. Beta diversity analysesBeta diversity was measured as the variation in morphospecies with depth and between sites. Jaccard’s dissimilarity was calculated, including its two components, turnover (i. e. species replacement) and nestedness (i. e. subset of a richer community), using the entire benthic community presence-absence data for each depth zone and site. Jaccard dissimilarity varies between 0 and 1, with values close to 1 revealing a high difference in the composition of benthic communities between two depth zones, while a low dissimilarity (close to 0) denotes similar benthic communities. These indices were calculated using the betapart package and plotted in a heatmap, as well as a barplot with ggplot2 package in R (Baselga and Orme 2012; Core 2020). ResultsAlpha diversityA total of 582 distinct morphospecies (OTUs) were identified from the benthic communities at Egmont Atoll, between 15 and 160 m, covering 17 higher taxa (ranging from phylum to genus; Table S2).

Output: corroborate


Input: Claim: Quantum cryptography offers theoretically unbreakable encryption. [SEP] Text: Previously, quantum money assumes a traditional hierarchy where a central, trusted bank controls the economy. We show how quantum money together with a blockchain allows for Quantum Bitcoin, a novel hybrid currency that promises fast transactions, extensive scalability, and full anonymity. Abstract [sv] En viktig konsekvens av kvantmekaniken är att okända kvanttillstånd inte kan klonas. Denna insikt har gett upphov till kvantkryptering, en metod för två parter att med perfekt säkerhet kommunicera hemligheter. Ett komplett bevis för denna säkerhet har dock låtit vänta på sig eftersom en attackerare i hemlighet kan manipulera utrustningen så att den läcker information. Som ett svar på detta utvecklades apparatsoberoende kvantkryptering som i teorin är immun mot sådana attacker. Apparatsoberoende kvantkryptering har en mycket högre grad av säkerhet än vanlig kvantkryptering, men det finns fortfarande ett par luckor som en attackerare kan utnyttja. Dessa kryphål har tidigare inte tagits på allvar, men denna avhandling visar hur även små svagheter i säkerhetsmodellen läcker information till en attackerare. Vi demonstrerar en praktisk attack där attackeraren aldrig upptäcks trots att denne helt kontrollerar systemet. Vi visar också hur kryphålen kan förhindras med starkare säkerhetsbevis. En annan tillämpning av kvantmekanikens förbud mot kloning är pengar som använder detta naturens egna kopieringsskydd.

Output: contrast


Input: Claim: The blood-brain barrier protects the brain from harmful substances. [SEP] Text: If, as indicated by all available studies, sufficient net inward flux of amino acids does not in fact exist, the amino groups for synthesis of glutamate in the astrocytes must be obtained from sources within the brain. Independent evidence that such a source is available comes from studies comparing isotope dilution in the brain when plasma leucine was labeled with 13C or 15N. 62% of the N in brain leucine was derived from reverse transamination [380,381,382,383]. One detailed suggestion (see Fig. 18) is that loss of the branched chain α-ketoacids (BCKA), e. g. α-ketoisocaproate, generated in the transamination in the astrocytes is prevented by using a branched chain amino acid (BCAA) shuttle ([382, 384], reviewed in [385]). In this scheme instead of being further metabolized within the astrocytes as shown in Fig. 17, the BCKA are transferred to neurons where the branched chain amino acids (BCAA), e. g. leucine, can be regenerated by transamination from glutamate producing α-ketoglutarate. The leucine is then exported back to the astrocytes while the glutamate within the neuron is regenerated by glutamate dehydrogenase from NH4+ and the α-ketoglutarate [384, 386]. In this scheme NH4+ is taken from the neuron where it is released from glutamine and will be at relatively high concentration. This is shifted to the astrocyte by the BCAA shuttle where it can be combined with new α-ketoglutarate to complete the de novo synthesis of glutamate. This scheme greatly reduces the need for net flux of BCAA across the blood–brain barrier. Fig. 18(Based on Figure 1 in Hutson [384])The branched chain amino acid shuttle for provision of branched chain amino acids (BCAA) in the astrocytes to allow de novo synthesis of glutamate. Leucine (Leu) is used as example of a BCAA. α-KG α-ketoglutarate, α-KIC α-ketoisocaproic acid, Gln glutamine, Glu glutamate, g. a glutaminase, g. d glutamate dehydrogenase, g. s glutamine synthetase, t.

Output: pass


Input: Claim: Coral reefs support a diverse range of marine species. [SEP] Text: Using alpha and beta diversity measures, the results show that benthic communities within MCEs at host a high and unique biodiversity, highlighting the importance of considering MCEs within conservation and management plans. Here, diversity values were comparable to shallow-water coral reefs (Edgar et al. 2017), which are considered to be one of the most diverse ecosystems in the world (Bryant et al. 1998), and communities displayed a high species turnover along the depth gradient. Species richness values estimated at (calculated at Cmax and ranging from 57 to 220 across the depth gradient; see Methods and Table S5) were analogous to values from a global study of inshore reef richness for invertebrates, both in the (species richness of 120) and the wider tropical-subtropical regions (species richness ranged from 40 to 230) (Edgar et al. 2017). Furthermore, even the deepest zone (150–160 m) in the current study, displaying the lowest diversity values, had higher species richness than some shallow (~ 10 m) subtropical regions (i. e. 67. 59 for IDR and 56. 58 for MA compared to 40 in Edgar et al. (2017)). When accounting for scleractinian corals only, the species richness and Shannon index values calculated in this study were similar to those measured in the Red Sea, within shallow-water reefs and the upper mesophotic zone (Table S2; (Kramer et al. 2019)), but slightly lower than coral species richness values in (Montgomery et al. 2021). In addition, for one of our two study sites, total benthic biodiversity was higher at 30–40 m than 15–20 m (IDR, Fig. 2a, b, c). This trend has also been noted in the Caribbean for the entire benthic community (increase in species richness from 15 to 53 m, (Liddell and Ohlhorst 1988)), but also for scleractinian corals in (Pérez-Rosales, et al. 2022b) and octocorals in the Gulf of Aqaba (Shoham and Benayahu 2017). According to Pérez-Rosales et al.

Output: corroborate


Input: Claim: Quantum cryptography offers theoretically unbreakable encryption. [SEP] Text: 2014 (English)In: Journal of Physics A: Mathematical and Theoretical, ISSN 1751-8113, E-ISSN 1751-8121, Vol. 47, no 42, p. 424032-10. 1088/1751-8113/47/42/424032 (DOI)000344222200033 () Available from: 2014-12-05 Created: 2014-12-05 Last updated: 2017-12-05 2. Hacking the Bell test using classical light in energy-time entanglement–based quantum key distributionOpen this publication in new window or tab >>Hacking the Bell test using classical light in energy-time entanglement–based quantum key distributionJogenfors, JonathanLinköping University, Department of Electrical Engineering, Information Coding. Linköping University, of Technology. . . . Larsson, Jan-ÅkeLinköping University, Department of Electrical Engineering, Information Coding. Linköping University, of Technology. Show others. . . 2015 (English)In: Science Advances, E-ISSN 2375-2548, Vol. 1, no 11, p. 1-7, 3. 63 at 97. 6% faked detector efficiency using tailored pulses of classical light, which exceeds even the quantum prediction. This is the first demonstration of a violation-faking source that gives both tunable violation and high faked detector efficiency. The implications are severe: the standard Clauser-Horne-Shimony-Holt inequality cannot be used to show device-independent security for energy-time entanglement setups based on Franson’s configuration. However, device-independent security can be reestablished, and we conclude by listing a number of improved tests and experimental setups that would protect against all current and future attacks of this type. Place, publisher, year, edition, pages for the Advancement of Science, 2015 :nbn:se:liu:diva-114210 (URN)10. 1126/sciadv.

Output: contrast


Input: Claim: The blood-brain barrier protects the brain from harmful substances. [SEP] Text: a transaminase. Losses of Gln, primarily by efflux, and of Glc, primarily by catabolism are replaced by de novo synthesis of α-KG in astrocytes and transamination using Leu producing α-KIC. Leu is regenerated from α-KIC in the neuron by transamination from Glu producing α-KG. is in turn regenerated from the α-KG and NH4+ by gdh. Loss of N via efflux of Gln, Glu, and Leu is made good by net inward flux of Leu and NH4+. The BCAA shuttle greatly reduces the need for net inward flux of Leu as this is only required to make good the metabolic loss of α-KICFull size image 5. 5. 6 Amino acid transporters at the blood–brain barrierThe transporters currently thought to be involved in amino acid transport across the blood–brain barrier are indicated in Fig. 19. These will be discussed below according to the categories of amino acids transported. Fig. 19Amino acid transporters thought to exist at the blood–brain barrier. Based on Nalecz [200]; Broer [393]; Mann et al. [520]; O’Kane et al. [657]; and Hawkins et al. [44]. #See [44, 398] but contrast [399, 400]Full size image Anionic amino acids, in particular glutamate, are transported by EAATs 1, 2 and/or 3 (coded by SLC1A3, 2, 1 respectively) which are found only in the abluminal membrane of the endothelial cells [387]. These EAATs mediate co-transport of the anionic amino acid together with 3 Na+ ions and 1 H+ ion followed by return transport of 1 K+ ion [388,389,390]. Because the electrochemical gradient for Na+ is directed from ISF into the endothelial cells and 3 Na+ ions are transported, this coupling renders the amino acid transport effectively unidirectional into the cells. Glutamate is also produced within the endothelial cells from breakdown of glutamine mediated by glutaminase [360].

Output: pass


Input: Claim: Coral reefs support a diverse range of marine species. [SEP] Text: (2022a, b), this peak in coral richness could be generated by the range overlap of assemblages typical of shallow and mesophotic communities within this depth range, as observed in (Diaz et al. , 2023a). While comparison with other studies was challenging due to the lack of a standardised methodology to measure diversity, as well as the differences in terms of investigated taxa between studies, the high benthic diversity encountered within the entire mesophotic gradient in the can still be acknowledged. Here, more than 90% of the total benthic megafauna diversity was detected (Table S3, see Table S4 for undetected diversity), which is considered as an acceptable standardized value for comparing species richness between communities (Moreno and Halffter 2000). Fundamentally, the sampling effort of this study obtained an efficient inventory of the benthic species community across the shallow to lower mesophotic depth gradient at Egmont Atoll. Hence, the authors suggest that future studies should estimate diversity indices using rarefied and extrapolated methods, to obtain a standardised and robust comparison between studies (Roswell et al. 2021). Overall, the diversity of the benthic communities at decreased from the shallow water down to the lower mesophotic zone (from 15 to 160 m) at the two study sites, when accounting for rare, abundant, and highly abundant morphospecies (Hill numbers for species richness, Shannon and Simpson indices; Fig. 2). While studies of the entire benthic community down to mesophotic depths are scarce, this pattern has been observed in several locations, such as the Caribbean (Stefanoudis et al. 2019), the Ocean (Stefanoudis et al. 2023) and the (Pyle et al. 2016). The decrease in benthic diversity with depth has also been described worldwide for scleractinian corals, in the Caribbean (Appeldoorn et al. 2019), the Indo-Pacific (Bridge et al. 2012; Rowley et al. 2019; Turak and DeVantier 2019; Laverick et al. 2020; Montgomery et al. 2021; Osuka et al. 2021) and the western Atlantic regions (Muir and Pichon 2019). On the contrary, sponge (Slattery and Lesser 2012; Eyal et al. 2019; Rowley et al. 2019; Diaz et al.

Output: corroborate


Input: Claim: Dialects can reflect social and geographic backgrounds. [SEP] Text: Interessant sind auch die VENN-Diagramme (S. 137, 138, 142, 143, 186), da man auf sie einen einfachen wahrscheinlichkeitstheoretischen Test anwenden kann,[5] der z. B. deutlich zeigt, dass in der wie Computers und Physics in der natürlichen Sprache der Dokumente deutlich seltener als bei einer Zufallsverteilung gemeinsam vorkommen, Physics = 0,33 + 0,04 + 0,20 + 0,13 = 0,70 Computers = 0,13 + 0,04 + 0,20 + 0,13 = 0,50 Physics ∩ Computers = 0,04 + 0,20 = 0,24 0,70 x 0,50 0,24 = 1,46 während die Indexer diese scheinbare Zufälligkeit wieder herstellen. Physics = 0,09 + 0,02 + 0,62 + 0,15 = 0,88 Computers = 0,01 + 0,02 + 0,62 + 0,08 = 0,73 Physics ∩ Computers = 0,02 + 0,62 = 0,64 0,88 x 0,73 0,64 = 1,00 geht es bei der Arbeit um den Einsatz von „search term recommenders“ und das Verhältnis der zur Precision. Dabei zeigt sich, dass die alte Erkenntnis von F. Lancaster (vor ~40 Jahren an gewonnen) bis heute noch sehr stabil ist, bei der sich das Verhältnis zwischen Precision und Recall als etwa linear erweist. von 20% – 60% beträgt die Steigung meist etwas weniger als -1. Mit zunehmendem Recall fällt somit die Precision direkt proportional.

Output: pass


Input: Claim: The blood-brain barrier protects the brain from harmful substances. [SEP] Text: Glutamate in the endothelial cells can then either be metabolized releasing NH4+, as argued by Helms and colleagues [391, 392], or be transported to blood plasma by a transporter other than an EAAT. Glutamate metabolism within endothelial cells is analogous to the extensive metabolism known to occur within gut epithelial cells (see e. g. [393]). Glutamate transport from brain endothelial cells to plasma has been demonstrated after sensory stimulation in vivo, which increases glutamate production [394]. This transport is likely to be via the glutamate/cystine exchanger, X −c (SLC7A11 + SLC3A2), [200, 395]), though there is also evidence for a transporter, yet to be identified, that functions in the absence of cystine [396]. Cationic amino acids such as arginine and lysine are transported by CAT-1 (SLC7A1), which is known to exist in the abluminal membrane of the endothelial cells. Transport of these amino acids across the luminal membrane is less well-characterized but may be also via CAT-1 or possibly ATB0,+ (SLCA14). Transport of cationic amino acids by CAT-1 can involve exchange of one amino acid for another (trans-stimulation see Sect. 5. 3. 1), but this is not essential [397]. There may be at least one more transporter for cationic amino acids at the abluminal membrane (but see [398]). Hawkins et al. [44] reported that cationic amino-acid transport across both membranes can be inhibited by a number of neutral amino acids in the presence of Na+. CAT-1 is thought not to be so affected [397, 399, 400]. The additional transporter may be y+L [4F2hc (SLC3A2) + either y+LAT2 (SLC7A6) or y+LAT1 (SLC7A7)] [399, 400]. Neutral amino acids are transported by several systems as indicated in Fig. 19.

Output: pass


Input: Claim: Coral reefs support a diverse range of marine species. [SEP] Text: The relatively constant total community richness at the species (or morphospecies) level over a broad bathymetric range is suggested to be due to major shifts of the larger taxonomic categories (Liddell and Ohlhorst 1988). Indeed, whilst diversity values were relatively constant with depth (Fig. 2), numerous depth-specialist species were observed along the depth gradient at in a parallel study, with a gradual decrease in scleractinian corals with depth, while octocorals, hydrozoans, antipatharians, hydrozoans and sponges increased (Table S3; (Diaz et al. 2023a)). Depth specialist species included Astrogorgia sp, Leptoseris sp, and members of the Nephtheidae and Hydrozoa. Shallow and mesophotic coral ecosystems observed at displayed a high dissimilarity in terms of benthic communities along the depth gradient (Fig. 3a, d), as well as among sites (Fig. 4). Turnover was found to be the main component of overall dissimilarity along the depth gradient and locally between sites, indicating that species replacement was the main driver of the differences in the benthic communities (Fig. 3). In addition, Jaccard dissimilarity displayed higher values between sites in mesophotic depth zones (30–160 m), compared to the shallower sites (15–20 m) (Fig. 4). The results presented in this study hence reveal the uniqueness of MCEs at Egmont Atoll. A change in community composition was observed along the depth gradient (Table S2). Thus, rather than the deeper communities being a subset of the richer shallower communities, they are composed of a different assemblage of species. Similar trends in dissimilarity along the depth gradient have been observed in other studies investigating beta diversity for the entire benthic community, in the Caribbean and western (Semmler et al. 2017; Stefanoudis et al. 2019, 2023; Osuka et al. 2021). In addition, high species turnover has also been observed for scleractinian corals in the Pacific and western Atlantic regions (Rocha et al. 2018; Montgomery et al. 2021; Pérez-Rosales, et al. 2022b).

Output: corroborate


Input: Claim: Dialects can reflect social and geographic backgrounds. [SEP] Text: This is a strong indication that the linguistic makeup is substantially the same for all the dialects and, therefore, that they all originated by the same founding population of which they reflect the initial composition. The conclusion is that the founding event was likely a single one and subsequent immigration did not significantly alter the linguistic composition. Indeed, looking more carefully, one can detect a little less Malay in the north since the red circles have a larger ratio than all the others. This cannot a be a consequence of a larger African influence in the vocabulary due to the active trade with the continent and the Comoros Islands. In this case both the Maanyan and Malay component of the vocabulary would be affected. Instead, this may be the effect of Malay trading which, according to Adelaar [2], [3], continued for several centuries after colonization. Noticeably, some dialects changed less from the proto-language (Antananarivo, Fianarantsoa, Manajary, Manakara), in fact, their distances both from Maanyan and Malay are smaller then those of the other dialects. This is probably the most relevant phenomenon, and we underline that the variants which are less distant on average with respect to the other dialects (Fig. 3) are also less distant with respect to Malay and Maanyan (Fig. 4). Therefore, the fact that Merina is closer to the other dialects cannot be explained merely by the fact that it is the official variant. We have checked whether the picture which emerges from Fig. 4 is confirmed by comparing the Malagasy dialects with other related Indonesian languages. The result is positive, and in particular the dialects of Manajary, Manakara, Antananarivo and Fianarantsoa seem to be closer to most of the Indonesian languages which we compare them to. Note that Manajary and Manakara are both in the previously identified landing area on the south-east coast while Antananarivo and Fianarantsoa are in the central highlands of the Island. This suggests a scenario according to which there was a migration on the highlands of Madagascar (Betsileo and Imerina regions) shortly after the landing on the south-east coast (Manakara, Manajary). In conclusion, both the average distances in Fig.

Output: contrast


Input: Claim: The blood-brain barrier protects the brain from harmful substances. [SEP] Text: System L, primarily the heterodimer 4F2hc/Lat1 (Slc3a2 + Slc7a5) which is present in both membranes and functions independently of Na+; System A, primarily ATA2 (Slc38a2) in the abluminal membrane which because it is a Na+-linked transporter is biased towards transport from ISF into the endothelial cells; ASC, primarily ASCT2 (Slc1a5), an obligatory exchanger that requires the presence of Na+-but is not driven by the Na+ gradient; System Na+-LNAA a Na+-linked system whose molecular basis is still unknown; ATB0,+ (SLC6A14) which allows net fluxes without exchange; And possibly the y+L transporter [4F2hc (SLC3A2) + either y+LAT2 (SLC7A6) or y+LAT1 (SLC7A7)]. The large influxes of neutral amino acids from blood-to-brain seen in the early work and ascribed to system L have subsequently been shown to be mediated by 4F2hc/Lat1 [401,402,403]. The discovery that not only can this system mediate exchanges of amino acids [404, 405] but the exchange is obligatory [406,407,408] has far reaching consequences for amino acid transport at the blood–brain barrier [409]. It provides an important part of the explanation for how it is that there are large unidirectional fluxes (influx and efflux) but only small net fluxes. In order for system L to mediate a net inward flux of one amino acid, it must have net outward flux of another. An exchanger of neutral solutes, like system L, tends to equilibrate the concentration ratios for all of its substrates. Thus predicting the flux of any one of the amino acids across a membrane requires knowledge of the concentrations of all of the substrates on both sides of the membrane. Footnote 20 Consumption of any system L substrate within the parenchyma will by reducing its ISF concentration tend to lead to net inward flux of that substrate and net outward flux of others. Similarly production of any system L substrate will tend to lead to its net outward flux together with net inward flux of others.

Output: pass


Input: Claim: Coral reefs support a diverse range of marine species. [SEP] Text: More recently, a study investigating the “whole community” using eDNA metabarcoding in Hawai’i found significant differences between reefs at 0–45 m and 60–90 m, for 18S-eukaryotes and COI-metazoans, with turnover identified as the highest component of the beta diversity (Hoban et al. 2023). However, a review by Muir and Pichon (2019) suggests that at mesophotic depths shallower than 60 m, coral communities are a subset of shallow-water reefs, with a shift in coral fauna occurring from 60 m. This shift in community composition at 60 m has been described in several locations and defined as a “community break” (Lesser et al. (2019)). Here, turnover was nevertheless high even between the shallowest depth zones (15-20 m and 30-40 m), supporting previous studies suggesting that ecological connectivity between the shallow and mesophotic zones is limited (Rocha et al. 2018; Soares et al. 2020; Hoban et al. 2023; Stefanoudis et al. 2023) and driven by a change in benthic species along the depth gradient, rather than a loss of species (Fig. 3; Table S7, Fig. S1). Hence, these findings add evidence to the uncertainty surrounding the DRRH and the reseeding potential of MCEs should shallow-water reefs at Egmont Atoll, and likely in the wider Chagos Archipelago, be subject to disturbance, due to the high dissimilarity in benthic communities observed with depth. In addition, mesophotic reefs at have been found to be vulnerable to increases in temperature, with severe coral bleaching occurring between 60–90 m, in the absence of shallow coral bleaching, in late 2019 (Diaz et al. 2023c), challenging one of the assumptions of the DRRH that deep reefs are less impacted by climate change than their shallow-water counterparts (Glynn 1996). Whilst mesophotic coral bleaching was occurring during data collection, every organism, including bleached scleractinian corals, were annotated, and included within the analysis, thus the bleaching is unlikely to have affected the diversity results presented here.

Output: corroborate


Input: Claim: Bilingualism can enhance cognitive flexibility and problem-solving skills. [SEP] Text: 대응표본 t검증(paired t-test)한 결과를 살펴보면, 훈련집단의 문제해결력이 실험 전에 비해 실험 후에 향상되었는데 5주 후 실시한 추수평가에서도 실험에 의해 향상된 문제해결력이 유지되었음을 알 수 있다. 훈련집단의 자기효능감을 살펴보면 실험 전에 비해 실험 후에 향상되었으며 추수평가에서도 실험 전에 비해 향상된 자기효능감이 유지되었음을 알 수 있다.

Output: contrast


Input: Claim: The blood-brain barrier protects the brain from harmful substances. [SEP] Text: The function of 4F2hc/Lat1 (Slc3a2/Slc7a5), the principal component of system L, was explored in mice by Tarlungeanu et al. [410]. They compared the concentrations of amino acids in brain (amount per unit weight of brain) between a conditional Slc7a5 knockout [411] and normal controls. In adult mice they found that the levels of methionine, leucine and isoleucine in the knockouts were about 0. 66 times the levels in normals, i. e. a reduction of about 35%. This suggests that there is normally a net inward flux of these amino acids via 4F2hc/Lat1 but that there are other routes at least as important. By contrast levels of phenylalanine, proline, glycine, threonine, and serine in the knockouts were about 1. 3 times higher than in normals, i. e. an increase of about 30%. This suggests that for these amino acids there is normally a net outward flux via Lat1 but that there are other important routes for their elimination. More dramatically with histidine the level in knockouts was sevenfold higher, a 600% increase compared to normals. This suggests that 4F2hc/Lat1 is normally the main route for eliminating histidine from the parenchyma and that a net inward flux of histidine occurs by some route other than 4F2hc/Lat1. However, it is important to note that while these results show that 4F2hc/Lat1 is very important for the fluxes of histidine, they do not in themselves show that histidine efflux is a large fraction of the total efflux carried by 4F2hc/Lat1. Further evidence for exchanges involving histidine have been obtained using 4F2hc/Lat1 expressed in proteoliposomes. High concentrations of cysteine inside the vesicles can allow or drive influx of histidine and high concentrations of many amino acids outside of the vesicles can allow or drive efflux of histidine [412]. It has been tempting to propose that the combined net flux of neutral amino acids, inward or outward, is determined by their fluxes via systems other than system L and by their synthesis and breakdown in the parenchyma.

Output: pass


Input: Claim: Coral reefs support a diverse range of marine species. [SEP] Text: ConclusionsThe current study provides baseline data on the benthic diversity within MCEs in a remote, pristine area. High species turnover along the depth gradient and among sites indicates that the MCEs of the are of limited refuge for threatened shallow-water coral reefs and are a significant ecosystem in terms of diversity and endemicity. Thus, following the call of numerous scientists worldwide (e. g. Rocha et al. 2018; Soares et al. 2020; Stefanoudis et al. 2022), the authors advocate for protection of these critical mesophotic ecosystems, in order to preserve overall biodiversity and the associated benefits.

Output: corroborate


Input: Claim: Microclimates can create variations in weather over short distances. [SEP] Text: Map distribution of normalized diurnal precipitation deviations at (a) 0600, (b) 0900, (c) 1200, (d) 1500, (e) 1800, and (f) 0000 UTC estimated as the mean precipitation rate at this hour minus the mean precipitation rate throughout the date, normalized by the standard deviation of hourly precipitation at each location. Scales smaller than 200 km are truncated by a 2D spectral decomposition. The 800-m terrain elevation is plotted in thick gray curves denoting the approximate location of the steepest terrain slope. The purple solid (dashed) line denotes the location of the phase fronts of the local diurnal precipitation peaks (minima). View in gallery Fig. 4. Distance–time Hovmöller diagram of the normalized hourly precipitation deviation without filtering averaged along the cross section from northwest to southeast (as in Fig. 1c). The dashed arrows show the southeastward phase propagation of the diurnal precipitation peaks. The time axis is in UTC [i. e. , 8 h behind the local standard time (Beijing time)]. View in gallery Fig. 5. Spatial distribution of the 900-hPa vertical motions (colored) and perturbation wind vectors diagnosed with the GFS analyses at (a) 0600, (b) 1200, (c) 1800, and (d) 0000 UTC. The 800-m terrain elevation is plotted in thick gray curves denoting the approximate location of the steepest terrain slope. The purple solid (dashed) line denotes the location of the phase fronts of the local diurnal precipitation peaks (minima) as in Fig. 3. View in gallery Fig. 6. Vertical profiles of the averaged vertical motion (colored; cm s−1), the perturbation vertical circulation vectors (horizontal wind component along the cross section and 100 times the vertical velocity), and the horizontal wind component perpendicular to the cross section (contoured in blue every 0. 5 m s−1, where solid indicates southwesterlies and dashed indicates northwesterlies) along the direction from northwest to southeast averaged as in Figs. 1c and 4 diagnosed with the GFS analyses at (a) 0600, (b) 1200, (c) 1800, and (d) 0000 UTC. The red solid curves show the averaged normalized diurnal precipitation deviation, with the red dashed straight line as the zero value.

Output: pass


Input: Claim: The blood-brain barrier protects the brain from harmful substances. [SEP] Text: is, however, still important, because it is the combined action of system L with the other transporters that determines which of the neutral amino acids move inwards and which outwards. A coherent overall account of the transport of neutral amino acids across the blood–brain barrier is still awaited. With regard to glutamine, which is synthesized within the parenchyma, it has been tempting to propose that a substantial part of its efflux occurs via a system L mediated exchange for the essential large neutral amino acids such as leucine, isoleucine, valine and phenylalanine entering the parenchyma. Indeed such exchanges can be observed with isolated microvessels under experimental conditions [413, 414]. However, there is no evidence for this effect under conditions that exist in vivo. The observation that there is a net efflux of glutamine is especially important because it is present at high concentration in plasma and ISF and it is the obvious sink for excess NH4+ in the brain. Glutamine is a substrate not only of 4F2hc/LAT1 (system L) as outlined above but also of Snat3 (SLC38A3) (system N), ATA2 (SLC38A2) (system A), and CAT (SLC7A1) (system y+) [200]. Of these the principal transport that has been observed is mediated by system N. Localization of system N has been controversial. Lee et al. [360] (see also [44]) found that vesicles prepared from abluminal membranes displayed a Na+-linked transport for glutamine while vesicles prepared from luminal membranes had only Na+-independent transport. This combination would explain net outward flux of glutamine from the brain. However, Ennis et al. [415] found marked Na+-dependent tracer influx of glutamine. While there are alternatives (see footnote 3 on p. 9 in [4]) the simplest interpretation is that there are Na+-linked transporters in both membranes. More recently immunohistochemical localization studies [416] have shown Snat3 primarily on the abluminal membrane but also on the luminal membrane of brain capillaries.

Output: pass


Input: Claim: Coral reefs support a diverse range of marine species. [SEP] Text: Working on a selected area in Palau (western Micronesia), we assess the relative accuracy of selected coral heights in the reconstructed Models (DSMs) using 51 independent measurements (IMs), and we calculate 2D and 3D seafloor rugosity, comparing it with the results of the traditional “chain and tape” in situ method (Risk 1972; McCormick 1994). MethodsField surveys were conducted in the Palau Archipelago, western Micronesia (Fig. 1a), between November 2019 and February 2020. We focused on nine shallow reefs located in (7°20′13. 1′′N 134°29′07. 4′′E) (Fig. 1a), a semi-enclosed bay characterized by a maze of shallow-water channels, separated by shallow sills emerging during spring low tides (Golbuu et al. 2016). These reefs are of particular ecological value and scientific interest because of their unusually warm and acidic waters and counter-intuitively high coral coverage and diversity (Golbuu et al. 2016; Kurihara et al. 2021). They are also particularly amenable to UAS surveys because they are sheltered from the wind by steep rocky cliffs and have low hydrodynamic influence from the adjacent ocean (Golbuu et al. 2016). Therefore, study sites have periods of low hydrodynamic and wave motion and relatively low suspended sediment concentration. The surveys were carried out with calm winds (less than 2 km h−1). Fig. 1a Location of the survey sites in the Palau Archipelago. The insets show the location of Palau in the and the location of in Palau; b 3D rendering of DSM and Orthomosaic from one of the sites made with the R package “Rayshader” (github. com/tylermorganwall/rayshader/); c Detail of one original aerial photograph; d and e Orthomosaic and digital surface model (of the same area as c) obtained from the SfM-MVS workflow, respectively. Examples of ground control point and scale bar are also shown in the insetsFull size imageA consumer-grade UAS (DJI Phantom-4 Pro) was used to collect 980 near nadir photographs, covering a total area of 6830 m2 across all reef sites.

Output: corroborate