Input: Task: corroborate the claim using the given text. Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: cerevisiae H5S5K23 (ethanol-producing and -tolerant, citric acid-non-converting, acid- and heat-tolerant), Liml. fermentum 222 (formerly known as Lb. fermentum 222; heterofermentative, citric acid-converting, mannitol-producing, moderately acid-tolerant) and A. pasteurianus 386B (ethanol- and lactic acid-oxidizing, acetic acid-producing and -overoxidizing, acid- and heat-tolerant) (Lefeber et al. 2010, 2011b, 2012; Moens, Lefeber and 2014). Whole-genome sequence analysis of these LAB and AAB strains has confirmed their competitiveness and functional properties, such as the presence of relevant and unique carbohydrate and amino acid consumption genes as well as genes for environmental adaptations and stress responses (Illeghems, and Weckx 2013; Illeghems, Weckx and 2015a; Illeghems et al. 2016; Pelicaen et al. 2019). The prevalence of facultatively heterofermentative Lacp. plantarum strains, for instance, may be ascribed to possible heterofermentation of carbohydrates, several stress responses and the possibility of bacteriocin production to enhance their competitiveness under cocoa pulp-bean mass fermentation conditions (Illeghems, and Weckx 2015a; Illeghems, Weckx and 2015b). Finally, this mixed-strain starter culture has been implemented on farms in both and Malaysia, by adding a liquid yeast culture and/or rehydrated lyophilized LAB and AAB powders (Lefeber et al. 2012). Its application has shown that uniformly fermented cocoa beans can be obtained within four days of fermentation, due to an early onset and accelerated carbohydrate fermentation, consistent ethanol production and fast citric acid conversion. This has also indicated the importance of the inclusion of a yeast strain to manufacture bulk dark chocolate without unfermented flavours (Lefeber et al. 2012), likely ascribed to its added value concerning the production of flavour-active compounds (Ho, Zhao and Fleet 2014, 2015; Ho, Fleet and Zhao 2018). [SEP] Justify:

Output: The text corroborates the claim by discussing the role of lactic acid bacteria (LAB) in various fermentation processes, particularly highlighting their competitiveness and functional properties in the context of cocoa pulp-bean mass fermentation. It notes how these LAB, such as Liml. fermentum and Lacp. plantarum, are essential for accelerating carbohydrate fermentation and producing key flavor-active compounds in the production of bulk dark chocolate.


Input: Task: contrast the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: Therefore, rather than excluding neurons with postsaccadic responses, we included neurons with small postsaccadic responses that did not differ between blocks 1 (saccades that will, in block 2, bring the spatial location of the vanished stimulus into the receptive field, but in which no stimulus ever appeared on the screen) and block 2 (different saccades that brought the receptive field away from the stimulus whose memory is being established, Wilcoxon signed rank: p-value=0. 4; p-value=0. 3). Although the stimulus never appeared in the neuron’s receptive field, the cells responded when the saccade brought the spatial location of the vanished stimulus into the receptive field (Figure 7). The population exhibited a robust memory response (Figure 8, poststimulus histogram for all cells we studied). The population histogram shows, for one monkey, a small postsaccadic burst in the stimulus appearing trials of block 2. One could argue, by looking at the postsaccadic response in the trials where the monkey made the saccade that brought the visual stimulus to a location outside of our estimate of the cell’s receptive field, that this postsaccadic response was a visual response. However, we saw the same postsaccadic response in block 1, where the monkey made a different saccade and no visual stimulus had ever appeared in the receptive field. Thus, the identical postsaccadic response in block two cannot be a visual response. Figure 8 Download asset Open asset Population responses in the No-RF memory task: from (left panel) and and C (right panel). Block descriptions are as in Figure 7. 26% (8/30) of neurons and 57% of monkey C neurons (8/14) exhibited environmental memory in the No-RF task. (Figure 7 for a single cell and Figure 8 for the entire population of cells that we studied). The neurons showed a significant difference (p<0. 05 by Wilcoxon rank sum) in the post saccadic response in Block 1 and the probe stimulus-absent trials in Block 2 (black traces and raster symbols versus magenta traces and raster symbols). They had a visual response in Block 4 when the saccade brought the stimulus into the receptive field. As in the basic task, this visual response was larger and had a longer shorter latency than the memory response. [SEP] Justify:

Output: The text contrasts the claim by indicating that the neurons exhibited a memory response without a visual stimulus ever appearing in the receptive field. It elaborates on how neurons responded to stimuli that were not directly present and highlights that similar postsaccadic responses occurred even in conditions where no visual input was provided. This demonstrates that memory responses can occur under conditions that do not align with the idea of perfect recall from a stimulus.


Input: Task: pass the claim using the given text. Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: The regressions shown in this figure are scaled by the absolute value of the largest regression across all combinations of pairs in the sequence. Figure 8. Regressions of off values onto the second order orthogonal polynomial when including the entire sequence. (A) It shows regressions of OFF values on pairs of nucleotides, one at site 3 and one at site 5, independent of the first order contributions of each site. (B) It shows regressions of OFF values on pairs of nucleotides at site 3 and at site 21. (C) It shows regressions of OFF values on pairs of nucleotides at site 5 and at site 21. All values are scaled by the absolute value of the largest regression in the set of all combinations of pairs (i. e. 780 pairs formed by two sites across the 40 site long sequence). Open in new tabDownload slideTo determine the effect of increasing distance between a pair of sites on the phenotype, we took the distances between the sites and plotted them against the absolute values of the maximum regressions (these are regressions of the phenotype onto two sites at a time). Figure 9A shows the sampling distribution of these regressions. It can be seen that a few regressions exist at the very tail end of the distribution as shown in the red part of the histogram. These regressions, all greater than 35 000, are also shown as a cloud of points, colored red, that appear in the top part of Figure 9B. To visualize which sites made up these site pairs and which nucleotides at these sites correspond to the high positive or negative regressions, a plot similar to the covariance figure (Figure 5) was constructed (Figure 9C) with actual values given in S2. For example, the blue curve connecting ‘A’ at site 5 with ‘C’ at site 15 means that having that combination contributes substantially to the OFF value, independently of the individual contributions of these sites by themselves. This visualization shows that there is no tendency for strongly interacting sites to be adjacent. In addition, there does not appear to be high regressions of the phenotype onto site pairs in the 5′ part of the sequence (as predicted by the covariance structure in Figure 5). Figure 9. Regressions of the phenotype onto 780 site pairs along the STAR sequence. [SEP] Justify:

Output: The text is irrelevant to the claim about the importance of bioinformatics in genomic data analysis. It provides detailed information on statistical regressions involving nucleotide pairs and their contributions to phenotypes but does not explicitly discuss bioinformatics or its significance in genomic analysis.


Input: Task: corroborate the claim using the given text. Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: Another screening study has evaluated the technological potential of yeast, LAB and AAB strains in CPSM supplemented with fresh cocoa pulp-bean mass and carried out in 2-L glass bottles; the strains used have been isolated from natural cocoa fermentation processes performed at bench-scale (plastic containers of 0. 5 L) and pilot-scale (stainless steel tank of 15 L) (Pereira et al. 2012). Several yeast species have been proposed as candidate starter cultures, such as Candida humilis, Debaryomyces etchellsii, P. kudriavzevii and P. kluyveri, together with S. cerevisiae. However, their success will depend on their prevalence, as mentioned above. These researchers have also suggested a three-strain inoculum, composed of S. cerevisiae (7. 04; ethanol-producing and acid-, ethanol- and heat-tolerant), Liml. fermentum (8. 12; citric acid-fermenting, lactic acid-producing and acid-, ethanol- and heat-tolerant), and A. tropicalis (16. 01; ethanol- and lactic acid-oxidizing, acetic acid-producing and acid-, ethanol- and heat-tolerant). Finally, the impact of yeast strains isolated from a spontaneous Malaysian cocoa fermentation process, belonging to the genera Candida, Hanseniaspora, Saccharomyces and Wickerhamomyces, on the antioxidant properties of cured cocoa beans has been evaluated, making use of a modified CPSM supplemented with fresh cocoa pulp-bean mass (500 mL), and has emphasized the potential of strains of Hanseniaspora thailandica and P. kudriavzevii as functional yeast starter cultures (Ooi, Sepiah and 2016; Ooi, Ting and Siow 2020). Regarding other mixed-strain and -species starter cultures tested, it has been shown that a starter culture composed of strains of K. marxianus (KM16–6; pectinolytic Ghanaian cocoa isolate), P. kluyveri (highly aromatic commercial wine strain), Liml. fermentum (L18; Ghanaian cocoa isolate) and A. [SEP] Justify:

Output: The text corroborates the claim as it discusses the role of lactic acid bacteria (LAB) in fermentation processes, specifically inside the context of mixed-strain cultures for cocoa fermentation. The mention of Liml. fermentum as a lactic acid-producing strain highlights its importance in the fermentation process, thus supporting the claim regarding the significance of lactic acid bacteria.


Input: Task: contrast the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: There was no significant difference in the postsaccadic responses in Block 1, when no stimulus appeared on the screen, and the memory forming trials in Block 2, when a stimulus appeared on the screen but did not appear in the receptive field of the neuron (Figure 7, for a single cell and Figure 8 for the population of memory cells black traces and raster symbols) (Monkey A, p=0. 4; Monkey C, p=0. 3, Wilcoxon signed rank). Because the postsaccadic responses in Block 1 and the memory-forming trials in block to were not different, the much larger postsaccadic response in the memory trials of Block 2 could not have been a visual response. Each population of neurons, including the statistically significant and the statistically non-significant neurons, taken as a whole, showed a statistically significant memory response (Figure 9a). The population showed a significant environmental memory response comparing the responses in Block 1 and the memory trials of Block 3 (Monkey A, p=0. 006, Monkey B, p=0,007, Wilcoxon signed rank). Figure 9 Download asset Open asset Population data in the No-RF memory task: All recorded units (open circles and triangles) and units which showed significant differences between baseline and memory blocks (filled symbols, trial per trial peak comparisons, Wilcoxon signed rank, population p<0. 001, within-cell Wilcoxon rank sum <0. 05). (A) Comparison of peak activity in the baseline and memory conditions (Block 1 vs Block 2, no probe stimulus trials). Each point represents a single cell. Cells with memory activity lie above the x = y line (diagonal). Monkey A: blue circles; Monkey C: red triangles. Insets: index (Block 2 versus Block 1) histograms for the whole population, out of which the statistically significant units are shown in shaded circles and triangles on the scatter plot. A median (numbers above index histograms) and rank sum and KS test confirmed memory activity as they both showed that the index distribution for the parent population was positively skewed. (B) Peak memory activity plotted against visual activity. Blue and red lines in the scatter plots are polynomial fits to each population data. They both indicate positive shift of neural responses towards memory activity. (C) Latency of memory response versus the latency of visual response for cells. (D) Normalized decay activity. [SEP] Justify:

Output: The text contrasts the claim by indicating that there was no significant difference in the postsaccadic responses when no stimulus was presented compared to when a stimulus appeared but did not affect the receptive field of the neuron. The findings suggest that simply providing a stimulus does not guarantee perfect recall of memory, as evidenced by the statistical results indicating no significant enhancement of memory response with the stimulus presented.


Input: Task: pass the claim using the given text. Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: A hybrid approach combining the tensor-based orthogonal polynomial method described here with a deep neural network trained on sequence and phenotype data is a promising area of further investigation. Application of our method to the case of these regulatory RNAs showcase that even though a cluster of sites near the 5′ end are correlated with other sites throughout the sequence, there is no obvious preference for correlations concentrated at the ends of the sequence. It turned out that the correlation structure shown in Figure 5 did not have any functional relationship with the phenotype when the phenotype of OFF fluorescence values was regressed onto the sequence space. After identifying sites along the STAR sequence that are correlated with each other, we built second and third order orthogonal polynomials that quantified the effect of the phenotype on two-way and three-way combinations of sites (S5–10). In order to test whether the 5′ region contained combinations of sites that had a greater effect on the phenotype than those at the 3′ end, we built second order polynomials of combinations of two pairs of sites across the STAR sequence. Since the sequence is 40 sites long, there were 780 unique combinations. When projecting the phenotype onto these pairs of sites, we assessed the impact of distance between the pair of sites on the degree to which they influence phenotype, and whether combinations of sites in the 5′ region would have a greater effect on phenotype. As seen in Figure 9, instead of one region of the sequence being more important than the other, there seems to be a global structure to the interacting site pairs across the sequence that have high regressions. The interaction data (Figure 9) does show some long range interactions, but it also shows a cluster of interacting sites in the middle. Furthermore, the pattern of interaction between sites in their impact on phenotype is not predicted by the nucleotide correlations between sites. Interactions at the 3′ and 5′ ends of the site, combined with those occurring in the middle of the sequence, suggest the possibility of competing intramolecular interactions and secondary structure formation in the absence of the target RNA. The authors utilized aiming to minimize competing intramolecular interactions, however, our analyses indicate that there exist substantial competing intramolecular interactions that can interfere with the intermolecular interaction between the STAR:target complex. This aspect was not predicted sufficiently by the algorithm. [SEP] Justify:

Output: The text does not address the importance of bioinformatics in analyzing genomic data; instead, it discusses a specific method and its application related to regulatory RNAs. Since it does not provide support or contradiction to the claim, it is deemed irrelevant.


Input: Task: corroborate the claim using the given text. Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: pasteurianus (A149; Ghanaian cocoa isolate) results in minor physical and chemical differences in fermentation characteristics during small-scale heap and plastic tray (20 kg; mixed Forastero hybrids) fermentation processes carried out in Ghana, compared to a spontaneous control (Crafack et al. 2013, 2014). In contrast, pronounced differences in flavour volatile compound compositions have been found in the roasted cocoa liquors and in the flavour profiles of the concomitant non-conched chocolates. However, the yeast strains added have never dominated the cocoa fermentation process, likely because of the low-cell-density inocula used and the poor drainage that occurred. Also, besides yeast strains, several strains of LAB and AAB species have been screened as to their tolerance toward acidity, ethanol, heat and osmotic stress (Visintin et al. 2016). A reduction from seven to three days of fermentation has been achieved with an optimal inoculum size and microbial succession of a mixed-strain starter culture consisting of S. cerevisiae MTCC 173, Lacp. plantarum MTCC 5422 (formerly known as Lb. plantarum MTCC 5422) and A. aceti MTCC 3347, applied during 10-kg box fermentations in India, resulting in consistently fermented cocoa beans with desirable characteristics for the production of acceptable chocolates (Sandhya et al. 2016). Also, the inoculation of strains of S. cerevisiae 0200, Lacp. plantarum CCMA 0238 (formerly known as Lb. plantarum CCMA 0238), and A. pasteurianus CCMA 0241 during box fermentations (100 kg of cocoa pulp-bean mass from hybrid PH15) has resulted in faster glucose and fructose consumption and chocolates with distinct flavours (Moreira et al. 2017). The use of a starter culture composed of a strain of S. cerevisiae (CCMA 0681) and a strain of Liml. fermentum (8. 12; inoculum of 1. 0 log less than the yeast strain) and applied during Brazilian cocoa box fermentations (100 kg of hybrid PH16) has affected the microbial communities involved and has impacted the sensory quality of the chocolates produced (astringent, bitter and sour taste; less cocoa notes) (Miguel et al. 2017). Inocula consisting of strains of S. [SEP] Justify:

Output: The text corroborates the claim by discussing the involvement of lactic acid bacteria (LAB) in fermentation processes of cocoa. It mentions that several strains of LAB have been screened for their tolerance towards various stresses during fermentation and highlights the successful application of mixed-strain starter cultures that include LAB in achieving desirable characteristics for cocoa chocolates. Additionally, the text implies that LAB contribute significantly to improving fermentation efficiency and flavor profile, supporting their importance in fermentation.


Input: Task: contrast the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: Memory response gradually decays after the last trial in which the probe appeared. The regression lines are data fits using a first order exponential. As indicated in ‘D’ legend, open squares and triangles are neural activities during decay trials compared to (normalized by) the mean of the last five trials with the probe stimulus (left y-axis). Similar to the basic memory task, the memory cells were not just the expected tail of a population distribution. The No-RF task population indices (mixed trials in Block 2 versus Block 1, Figure 9a inserts) were shifted to positive median values (median >= 0. 1 and medc of 0. 2 for both monkeys; Wilcoxon signed rank p=2. 3087e-08 for Monkey A; and 0. 007 for Monkey C). Here also, leftward shift (increased slope vs identity line) of a polynomial fit line (red and blue lines in Figure 9a) signified positive skewness of the memory responses (compared to baseline). As in the basic task, the larger visual response in Block 4 was larger than the memory response in Block 2 (Monkey A, p<0. 0001, p=0. 03 Wilcoxon signed rank). This shows that whatever decay we saw in Block 3 was not due to our losing the cell over this rather long experiment. The memory response had a longer latency than the neuron’s visual response (Figure 9c) (Wilcoxon signed rank p=0. 008 for Monkey A, and 0. 006 for Monkey C; mean visual/memory latency: 39/101 ms for Monkey A, 25/106 ms for Monkey C). As with data from the basic memory task, the normalized decay activity of the population (Figure 9d) could be fit to a first-order exponential. had a decay rate constant of 0. 09 trials and R2 of −0. 06; Monkey C, decay 0. 07 trials, R2 = 0. 12. Significant p-values were found using a Wilcoxon signed rank test between trial mean comparisons of the first and the last 10 trials in the 50-trial decay epoch considered (Wilcoxon signed rank for Monkey A: p=0. 0002, p=0. 01 for Monkey C). [SEP] Justify:

Output: The text contrasts the claim by providing evidence that memory response decays over time, as indicated by the experimental results showing a gradual decay in memory response after the last probe trial. It notes that memory responses are not stable and can be described by a decay function rather than perfect recall, which counters the idea that memory can be perfectly recalled given the right stimulus.


Input: Task: pass the claim using the given text. Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: , Kel-Margoulis O. , Wingender E. Match(TM): a tool for searching transcription factor binding sites in DNA sequences. Res. 2003; 31:3576–3579. 3. Ho-Sui S. , Mortimer J. , Arenillas D. , Brumm J. , Walsh C. , Kennedy B. , Wasserman1 W. o: identification of over-represented transcription factor binding sites in co-expressed genes. Res. 2005; 33:3154–3164. 4. Moss W. Lorsch J. Computational prediction of RNA secondary structure. Methods in Enzymology. 2013; NYElsevier Inc3–65. 5. Jaganathan K. , Panagiotopoulou S. K. , McRae J. F. , Darbandi S. F. , Knowles D. , Li Y. I. , Kosmicki J. A. , Arbelaez J. , Cui W. , Schwartz G. B. et al. . Predicting splicing from primary sequence with deep learning. Cell. 2019; 176:535–548. 6. Torrisi M. , Pollastri G. , Le Q. Deep learning methods in protein structure prediction. Comput. Struct. Biotechnol. 2020; 18:1301–1310. 7. Rice S. H. Universal rules for the interaction of selection and transmission in evolution. Philos. T. R. Soc. B. 2020; 375:doi:10. 1098/rstb. 2019-0353. 8. Lin Y. , Yuan J. , Kolmogorov M. , Shen M. , Chaisson M. , Pevzner P. Assembly of long error-prone reads using de Bruijn graphs. PNAS. 2016; 113:E8396–E8405. 9. Benoit G. , Lemaitre C. , Lavenier D. , Drezen E. , Dayris T. , Uricaru R. , Rizk G. Reference-free compression of high throughput sequencing data with a probabilistic de Bruijn graph. BMC Bioinformatics. 2015; 16:288. 10. Rahman A. , Hallgrímsdóttir I. , Eisen M. , Pachter L. [SEP] Justify:

Output: The text lists various published studies and methodologies in the field of bioinformatics and computational biology, including tools for searching transcription factor binding sites and predicting RNA secondary structures. However, it does not directly address the claim regarding the importance of bioinformatics for analyzing genomic data, therefore it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: cerevisiae, Lb. delbrueckii subsp. lactis (formerly known as Lb. lactis), and A. aceti have been assessed as well (Apriyanto et al. 2017). As mentioned above, Ho, Fleet and Zhao (2018) have studied the impact of yeasts, LAB and AAB on the quality of cured cocoa beans and chocolates produced thereof under carefully controlled conditions, making use of an variety and 12. 5-L plastic containers containing 3. 5 kg of cocoa pulp-bean mass, thereby testing various inocula based on different mixtures of strains of the yeasts Hanseniaspora guilliermondii, K. marxianus, P. kudriavzevii and S. cerevisiae, the LAB Liml. fermentum and Lacp. plantarum and/or the AAB A. pasteurianus and Gluconobacter frateurii. The use of these starter cultures has resulted in cured cocoa beans with slightly different concentrations of lactic acid and acetic acid, being highest in the presence of LAB and AAB, respectively, without significant differences regarding the sensory evaluation of the chocolates produced, underlining the primordial role of yeasts for cocoa fermentation. Still other studies have screened LAB strains, including them as producers of organic acids and/or bacteriocins and yeast strains, serving as producers of proteinaceous antifungal compounds, in a slightly modified CPSM as to their capacity to use them as co-cultures for the biological control of mycotoxin-producing fungi (et al. 2015; Ruggirello et al. 2019; Romanens et al. 2019). This set-up has been successful to inhibit an aflatoxin-producing strain of Aspergillus flavus. The combination of strains of Pichia mexicana and Bacillus pumilus has accelerated the fermentation (in plastic bags containing 1. 5 kg of fresh cocoa pulp-bean mass) and drying (aluminium pans) processes and has reduced the growth of mycotoxin-producing fungi during a cocoa fermentation experiment carried out in the Philippines (Gibe and Pangan 2015). [SEP] Justify:

Output: The text corroborates the claim by detailing studies that highlight the role of lactic acid bacteria (LAB) in fermentation processes, particularly in cocoa fermentation. It specifically notes that the use of LAB in starter cultures results in different concentrations of lactic acid, which is vital for the quality of the final product. Additionally, the mention of LAB as producers of organic acids supports their significance in fermentation.


Input: Task: contrast the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: The negative R2 in demonstrates the slowness of the decay and that a first-order exponential is not the best fit (it caused non-optimal line fit). This fit is used in the figures for consistency and visual clarity. this set of experiments, we demonstrate that LIP neurons exhibit an environmental memory signal, which lasts over a duration of multiple trials, decays slowly, and updates with eye movements. In addition, we demonstrate that a neuron does not require visual stimulation or a particular training saccade to establish memory activity. There is a similar signal in the frontal eye field (Umeno and Goldberg, 2001), in visual and visuomovement cells, but not movement cells. Those preliminary experiments, however, had two confounds. First, the memory was always established by stimulating the receptive field. Second, the saccade that evoked the memory was identical to the saccade used to establish it, so the memory could have been related to the saccadic process. In our experiments, we show that memory can be evoked by a stimulus that never appeared in the neuron’s receptive field, and that the memory response manifested even when the saccade used to evoke it differed from the saccade used to establish it. Furthermore, as in the FEF (Umeno and Goldberg, 2001), memory activity occurred both in neurons which did exhibit saccadic remapping as well as those that did not. In sum, these results suggest that LIP has access to a supraretinal representation of the visual world despite the fact that all of its explicit responses are retinotopic, and that this memory response cannot be simply ascribed to saccadic remapping or saccade planning. Our results can explain previous clinical observations regarding the role of parietal cortex in spatial memory. Patients with bilateral parietal lesions cannot point to an object in their room with their eyes closed, although they can easily do it with their eyes open (Levine et al. , 1985). This suggests that these patients do not have access to a remembered spatial representation of their environment. More importantly, patients with right parietal lesions report their spatial memory in a retinotopic frame. Bisiach and Luzzatti (1978) asked two Milanese patients with right parietal damage to describe their memory of the Piazza del Duomo in Milan. [SEP] Justify:

Output: The text contrasts the claim by discussing how memory responses, particularly from LIP neurons, can be evoked by stimuli that were not present in the neuron's receptive field, suggesting that recall is not always perfect or reliant on specific stimuli. It highlights the complexity of memory recall, indicating that factors such as spatial representation and the mechanism of memory retrieval complicate the notion of perfect recall.


Input: Task: pass the claim using the given text. Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: Association mapping from sequencing reads using k-mers. eLife. 2018; 7:e32920. 11. Zou J. , Huss M. , Abid A. , Mohammadi P. , Torkamani A. , Telenti A. A primer on deep learning in genomics. Nat. Genet. 2018; 51:12–18. 12. Reeder J. , Giegerich R. Design, implementation and evaluation of a practical pseudoknot folding algorithm based on thermodynamics. BMC Bioinformatics. 2004; 5:104. 13. Wakeman C. , Winkler W. , Dann C. Structural features of metabolite-sensing riboswitches. Trends Biochem. Sci. 2007; 32:415–424. 14. Chappell J. , Watters K. , Takahashi M. , Lucks J. A renaissance in RNA synthetic biology: new mechanisms, applications and tools for the future. Curr. Opin. Chem. Biol. 2015; 28:47–56. 15. Mutalik V. , Qi L. , Guimaraes J. , Lucks J. , Arkin A. Rationally designed families of orthogonal RNA regulators of translation. Nat. Chem. Biol. 2012; 8:447–454. 16. Lucks J. , Qi L. , Mutalik V. , Wang D. , Arkin A. Versatile RNA-sensing transcriptional regulators for engineering genetic networks. Proc. Natl. Acad. Sci. U. S. A. . 2011; 108:8617–8622. 17. Rice S. H. Evolutionary Theory: Mathematical and Conceptual Foundations. 2004; Sunderland, MASinauer. 18. Zeng Z. , Huang B. , Huang S. , Zhang R. , Yan S. , Yu X. , Shu Y. , Zhao C. , Lei J. , Zhang W. et al. . The development of a sensitive fluorescent protein-based transcript reporter for high throughput screening of negative modulators of lncRNAs. Genes Dis. 2018; 5:62–74. 19. Chappell J. , Westbrook A. , Verosloff M. , Luckscorresponding J. B. [SEP] Justify:

Output: The text lists various studies and papers relevant to bioinformatics and genomic analyses but does not specifically address or affirm the claim that bioinformatics is crucial for analyzing genomic data. It merely cites sources without establishing a direct relationship to the claim.


Input: Task: corroborate the claim using the given text. Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: is Open Access? is an initiative that aims to make scientific research freely available to all. To date our community has made over 100 million downloads. It’s based on principles of collaboration, unobstructed discovery, and, most importantly, scientific progression. As PhD students, we found it difficult to access the research we needed, so we decided to create a new publisher that levels the playing field for scientists across the world. How? By making research easy to access, and puts the academic needs of the researchers before the business interests of publishers. are a community of more than 103,000 authors and editors from 3,291 institutions spanning 160 countries, including winners and some of the world’s most-cited researchers. Publishing on IntechOpen allows authors to earn 10. 5772/50456 this 1. Choose citation style Select style to clipboard Get citation 2. Choose citation style Select format Bibtex RIS Download citation & D for Food, Health and Edited by J. From the Bacteria - R & D for Food, Health and Edited by purchase hard copies of this book, please contact the representative in India: CBS Publishers & Distributors Pvt. Ltd. www. cbspd. com | customercare@cbspd. com 1. Choose citation style Select style to clipboard Get citation 2. Choose citation style Select format Bibtex RIS Download citation Impact of this 1. IntroductionLactic acid bacteria (LAB) have diverse applications for both animals and humans. Food, pharmaceutical and chemical industries rely on these microorganisms to produce fermented beverage, foods and other important compounds of industrial interests. In recent years the industrial relevance of lactic acid bacteria is on an increasing trend because of the application of lactic acid as chemical for the production of biodegradable plastics [1]. Typical LAB are Gram-positive, non-sporing, catalase-negative, devoid of cytochromes, anaerobic but aerotolerant cocci or rods that are acid-tolerant and produce lactic acid as the major end product during sugar fermentation [2]. Although most LAB are unable to degrade starch because of the lack of the amylolytic activity, a few exhibit this activity and are qualified as amylolytic lactic acid bacteria (ALAB) which are able to decompose starchy material through the amylases production during the fermentation processes [3]. [SEP] Justify:

Output: The text corroborates the claim by detailing the diverse applications of lactic acid bacteria (LAB) in fermentation processes, mentioning their role in producing fermented beverages and foods. It indicates that multiple industries, including food, pharmaceutical, and chemical sectors, rely on LAB for essential products, which directly supports the importance of LAB in fermentation.


Input: Task: contrast the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: They found that these patients could only describe the recalled environmental landmarks that would fall in their unaffected (right) hemifield, which depended on their (imagined) vantage point. For example, when they described Piazza del Duomo as if they were standing with their back to the cathedral they remembered only the landmarks to the right of the cathedral. However, when they described the Piazza del Duomo as if they were facing the cathedral they only remembered the landmarks on the other side of the square, which were now to the right of their imagined vantage point. This experiment demonstrates two key ideas; (1) The brain stores long-term memory of environments in supraretinal coordinates in an area unaffected by a parietal lesion, since the patients could, under certain circumstances, remember the entire Piazza del Duomo. (2) Retrieving that memory requires the parietal cortex, but the right parietal patients could only report (and therefore mentally represent) objects on the right side of their imagined vantage point. They had a mnemonic left hemianopia for a remembered environment. If their memory were reportable in a supraretinal frame they should have been able to report the entire scene. Because they could not do so, and could only report objects in the non-neglected hemifield, the report of their environmental memory must be processed by the retinotopic map of the parietal cortex. Our results are consistent with this result. The memory of an environment can be stored a supraretinal frame, but must be reported by neurons with retinotopic receptive fields. The neurons that we have reported here fit that description. They have access to a supraretinal representation of the visual field, because environmental memory does not require stimulating their receptive fields, but they only report that memory when the spatial location of the remembered stimuli lies in their receptive field. The memory response has both a longer latency and a lesser intensity than a simple reafferent visual response. This suggests that it does not arise from a feedforward mechanism, just as task-related pattern selectivity in V4 requires a late, presumably feedback, mechanism (Ipata et al. , 2012). There are two known mechanisms by which LIP can create a spatially accurate representation of space despite a constantly moving eye. [SEP] Justify:

Output: The text contrasts the claim by detailing how memory retrieval is limited by the function of the parietal cortex, which affects the ability to report certain memories. It explains that patients could only recall landmarks that were within their unaffected field of vision, suggesting that perfect recall is not achievable under all conditions, as memory relies on the spatial location of stimuli within the retinal field.


Input: Task: pass the claim using the given text. Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: Computational design of small transcription activating RNAs for versatile and dynamic gene regulation. Nat Commun. 2017; 8:1051. 20. Krebs J. , Goldstein E. , Kilpatrick T. Lewin’s Genes XII. 2018; Burlington, MAJones & Bartlett Learning. 21. Zadeh J. , Steenberg C. , Bois J. , Wolfe B. , Pierce M. , Khan A. , Dirks R. , Pierce N. : analysis and design of nucleic acid systems. J. Comput. Chem. 2011; 32:170–173. 22. Caldelari I. , Chao Y. , Romby P. , Vogel J. RNA-mediated regulation in pathogenic bacteria. Harb. Perspect. Med. 2013; 3:a010298. 23. Takahashi M. , Lucks J. A modular strategy for engineering orthogonal chimeric RNA transcription regulators. Res. 2013; 41:7577–7588. 24. Bervoets I. , Charlier D. Diversity, versatility and complexity of bacterial gene regulation mechanisms: opportunities and drawbacks for applications in synthetic biology. FEMS Microbiol. Rev. 2019; 43:304–339. 25. Le D. , Shimko T. , Adithamb A. , Keysc A. , Longwellb S. , Orensteine Y. , Fordycea P. Comprehensive, high-resolution binding energy landscapes reveal context dependencies of transcription factor binding. Proc. Natl. Acad. Sci. U. S. A. 2018; 115:E3702–E3711. 26. Yang S. S. , Tseng C. S. An orthogonal neural network for function approximation. IEEE Transactions onSystems, Man, and Cybernetics, (Cybernetics). 1996; 26:779–785. 27. Sher C. F. , Tseng C. S. , Chen C. S. Properties and performance of orthogonal neural network in function approximation. Int. J. Intell. Syst. 2001; 16:1377–1392. 28. Singh J. , Hanson J. , Paliwal K. , Zhou Y. RNA secondary structure prediction using an ensemble of two-dimensional deep neural networks and transfer learning. Nat. Commun. [SEP] Justify:

Output: The text lists various scientific studies and references related to gene regulation, transcription factors, and RNA without directly discussing bioinformatics or its role in analyzing genomic data. Thus, it does not provide evidence for or against the claim, making it irrelevant.


Input: Task: corroborate the claim using the given text. Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: Regarding the importance and availability of starchy biomass in the world, amylases and lactic acid production from starch appear as two potential industrial applications of ALAB. Amylases play important role in degradation of starch and are produced in bulk from microorganisms and represent about 25 to 33% of the world enzyme market [4]. The spectrum of amylases application has widened in many fields, such as clinical, medical and analytical chemistry as well as in the textile, food, fermentation, paper, distillery and brewing industries [4]. The advantages of using thermostable amylases in industrial processes include the decreased risk of contamination, cost of external cooling and increased diffusion rate [4]. Several thermostable α-amylases have been purified from Bacillus sp. and the factors influencing their thermostability have been investigated [5]. However, no study has yet dealt with thermostable amylase from lactic acid bacteria (LAB). The use of thermostable amylases from Lactobacillus is of advantage as they are generally non-pathogenic. On the other hand, the major end product of LAB fermentation, lactate, has applications as a preservative, acidulant and flavouring agent in the food industry, because of the tartness provided by lactate and also because lactate is generally regarded as safe (GRAS) [6]. Thus a thermostable amylase producing lactic acid bacterium would be a potential candidate for food industries and especially for the making of high density gruel from starchy raw material as corn or wheat [7]. This would require a good knowledge of the conditions required to optimally produce amylase and lactic acid of good quality. The present study deals with the co-production of thermostable α-amylase and lactic acid from a LAB, Lactobacillus fermentum 04BBA19, isolated from a starchy waste of a soil sample from the western region of Cameroon. Advertisement 2. Background and significance2. 1. Amylolytic lactic acid bacteriaAmylolytic lactic acid bacteria (ALAB) have been reported from different tropical starchy fermented foods, made especially from roots as cassava and sweet potato or grains as maize sorghum and rice. Strains of Lactobacillus plantarum have been isolated from African cassava-based fermented products [8], L. [SEP] Justify:

Output: The text corroborates the claim by emphasizing the role of lactic acid bacteria (LAB) in fermentation processes, particularly highlighting their significance in producing lactate, which has numerous applications in the food industry as a preservative, acidulant, and flavoring agent. It notes that 'the major end product of LAB fermentation, lactate, has applications as a preservative, acidulant and flavouring agent in the food industry.' This illustrates the importance of LAB in fermentation, aligning directly with the claim.


Input: Task: contrast the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: The first is through remapping, in which a neuron will respond immediately after a saccade brings the spatial location of a recently vanished stimulus into its receptive field (Duhamel et al. , 1991; Sun and Goldberg, 2016). This effectively changes the spatial origin of the retinotopic coordinate system from the presaccadic fixation point to the saccade target. The next saccade could just as easily remap the current retinotopic representation into a coordinate system centered on the next saccade target, and so on, through a number of saccades. This is unlikely to be the basis of our results, however, because many cells that show environmental memory do not show pre-saccadic remapping when a saccade brings a stimulus into its receptive field. The second mechanism creates a spatially accurate retinotopic representation from a supraretinal representation. There is excellent human psychophysical evidence that the saccadic system has access to a supraretinal representation of space that does not involve remapping. Karn et al. (1997) showed that there is little difference in the inaccuracy of memory-guided saccades after two or six intervening visually-guided saccades. Reliance on a remapping mechanism for accuracy would entail the concatenation of errors from saccade to saccade, whereas access to a supraretinal coordinate frame would enable a more stable representation of space across multiple saccades. In a similar experiment, Poletti et al. (2013) asked humans to make different numbers of intervening saccades between the presentation of a target for a memory-guided saccade and executing the actual saccade. For the first few intervening saccades, the variability of the memory-guided saccade increased linearly, as expected if the error of each remapping process would concatenate. However, after the first few saccades, the increase in variability decreased with each subsequent saccade, as if the representation of the saccade target had shifted to a supraretinal frame which would not increase its error with each saccade. To explain this phenomenon, they proposed a model that entails a shift from an early remapping mechanisms to a subsequent supraretinal mechanism. This late supraretinal representation could arise from a gain-field mechanism. Visual responses in LIP are linearly modulated by the position of the eye in the orbit, the gain field. [SEP] Justify:

Output: The text contrasts the claim by detailing mechanisms of memory retrieval and suggesting that memory accuracy can be influenced by factors such as remapping and the access to a supraretinal representation. It argues that the reliance on remapping would likely increase errors with subsequent saccades, indicating that memory recall is not infallible even with the right stimulus, as demonstrated through various experiments.


Input: Task: pass the claim using the given text. Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: Skip to main content Explore journals Get published About BMC My account Search all BMC 1. Signatures from different studies share almost no genes, which indicates that the signatures depend to a large degree on the datasets rather than being prognostic for breast cancer [17]. In fact, Michiels et al. [18] showed that, even within a study, the subset of patients used for signature derivation strongly influenced which genes were selected. 2. The reported performance estimates of the signatures have been questioned [18]; this suggests that worse performance is likely to be obtained when applied to new data. Also, the confidence intervals of the performance estimates (if reported at all) have been disputed [4, 18]. This makes it difficult to assess the level of accuracy in the reported results. In fact, both these concerns arise due to the small sample sizes typically used in microarray studies relative to the number of profiled genes (i. e. the curse of dimensionality). We employed the eScience-Bayes strategy described in Fig. 1 to address this problem. In accordance with the practice in most previous 2. 0/DOC/esoap_help. html. NetPath is a curated resource of genes reported to be transcriptionally regulated by cancer-signalling pathways. All genes on the HG-U133A array listed in NetPath were used to text mine PubMed for all free fulltext 0. 76 (0. 71; 0. 80), 0. 57 (0. 55; 0. 58), and 0. 51 (0. 44; 0. 60), respectively (numbers in parentheses show the Bayesian confidence intervals). The predictive performance of trained with multiple datasets and informative priors was found to be significantly better than when using noninformative priors and with only a single dataset for training (Bayesian p-value < 0. 0005 in both cases). (B) KM curves [44] for patients predicted by (at 80% specificity) indicate the probability that patients develop distant metastases before (red) and after (cyan) 5 years. (C) Survival times predicted by Model II. The KM curves show survival of patients belonging to the predicted percentiles 0-33, 34-66, 67-100 (red, green, and red curves, respectively). The difference between the three groups is significant (Bayesian P-value < 0. 003). [SEP] Justify:

Output: The text does not directly address the importance of bioinformatics in analyzing genomic data. It discusses issues related to the performance and accuracy of gene signatures in studies, which are related to genomic data but do not explicitly mention the role or significance of bioinformatics in this analysis.


Input: Task: corroborate the claim using the given text. Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: plantarum A6 (LMG 18053) have been isolated from retted cassava in the Congo [9] and Lactobacillus manihotivorans OND32 have been isolated from cassava sour starch fermentations in Colombia [10]. Amylolytic strains of Lactobacillus fermentum were isolated for the first time from Benin maize sourdough (ogi and mawè) by Agati et al. [11]. Sanni et al. [12] described amylolytic strains of L. plantarum and L. fermentum strains in various Nigerian traditional amylaceous fermented foods. ALAB are generally screened in fermented amylaceous foods. Owing to their relatively high starch content, starchy biomass appears as an important eco-niche for the screening and isolation of ALAB, which can be industrially applied to convert starch into mono- and disaccharides for lactic acid fermentation. The composition of the microbiota and in particular the occurrence of ALAB is determined by the way the raw material is processed [13]. Most ALAB isolated belong to the Lactobacillus genus, however few studies reported the existence of amylolytic activity in some strains of Bifidobacterium isolated from the human large intestinal tract [14, 15]. The distribution of amylolytic microorganisms in the human large intestinal tract has been investigated in various individuals of different ages using anaerobic cultures techniques. So far, twenty one amylolytic bifidobacteria have been isolated from adult faeces and tested for rice fermentation [16]. Owing to the ability of their α-amylases to partially hydrolyze raw starch, ALAB can ferment different types of amylaceous raw material, such as corn [17], potato [18], or cassava [19] and different starchy substrates [20, 21, 8]. Amylolytic LAB utilize starchy biomass and convert it into lactic acid in a single step fermentation. ALAB are mainly used in food fermentation, they are involved in cereal based fermented foods such as European sour rye bread, Asian salt bread, sour porridges, dumplings and non-alcoholic beverage production. Few of them are used for production of lactic acid in single step fermentation of starch [1]. [SEP] Justify:

Output: The text corroborates the claim by discussing the role of amylolytic lactic acid bacteria (ALAB) in fermentation processes, specifically in converting starchy biomass into lactic acid. It mentions various sources from which these bacteria have been isolated and highlights their application in food fermentation, indicating their importance in these processes. Furthermore, it states that ALAB utilize starchy biomass to ferment it into lactic acid, reinforcing the claim about their significance in fermentation.


Input: Task: contrast the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: The eye position signal that modulates the gain fields in LIP could come from the representation of eye position in area 3a (Zhang et al. , 2008). It is mathematically trivial to calculate target position in supraretinal coordinates from retinotopic gain fields (Zipser and Andersen, 1988; Salinas and Abbott, 1997; Pouget and Sejnowski, 1994). Although gain fields are inaccurate immediately after a saccade (Xu et al. , 2012), they could contribute to a late, accurate, supraretinal representation that develops when the eye position signal is accurate, as one would expect if the eye position signal arose from proprioception. The neurons that we studied did not have eye position modulation of their visual responses – such neurons often have a phasic and tonic postsaccadic response that arises from the eye position signal itself (Wang et al. ). Indeed, because the memory of the stimulus was established well before the saccade that evoked the memory, the supraretinal representation of the remembered stimulus could easily be implicitly encoded in the gain-field responses of LIP neurons (Zipser and Andersen, 1988). Data from patients with parietal lesions, such as the previously described results from Bisiach and Luzzatti, suggest that although LIP might calculate target position in retinotopic coordinates, the parietal cortex does not store the results of that calculation. Instead, a supraretinal representation of space could be stored elsewhere, possibly in the medial temporal lobe. O’Keefe discovered that neurons in the rat hippocampus (the ‘place cells’) discharge when rats enter spatial location that they have seen before (O'Keefe and Dostrovsky, 1971). Other studies have duplicated this result in the monkey hippocampus (Ono et al. , 1993; Rolls et al. , 1989). Grid cells in entorhinal cortex are thought to be the precursors of hippocampal place cells (Moser et al. , 2008) and these have been found in the monkey (Buffalo, 2015) as well as in humans (Jacobs et al. , 2013). It is known that there is a direct, reciprocal connection between the parahippocampal gyrus and LIP (Suzuki and Amaral, 1994; Baizer et al. , 1991). [SEP] Justify:

Output: The text contrasts the claim by discussing the complexities and limitations surrounding memory recall. It points out that, while certain neural mechanisms such as gain fields in lateral intraparietal (LIP) neurons can contribute to the remembrance of stimuli, there are inaccuracies immediately after eye movements (saccades). Furthermore, it indicates that memory might not be perfectly recalled as it implicates different areas of the brain in memory storage and recall processes, such as the parietal cortex not storing calculations for target positions, which suggests that memory retrieval is not straightforward or perfect even with stimuli.


Input: Task: pass the claim using the given text. Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: Full size imageTo validate the value of using prior information, we tested with non-informative prior distributions (i. e. we assigned equal prior probability for all variables to be included in the variable selection; see Methods for further details) and compared the results to those obtained with informative priors (Fig. 3a, green curve; Additional file 1, Fig. S1, green curves; Table S1). This clearly showed that the use of relevant prior information significantly improves the classification accuracy of (Bayesian P-value < 0. 001, related to the curves in Fig. 3a). The dramatic improvement was due to the fact that the prior information focused the model to include relevant genes in the signature, thus reducing the risk of detecting spurious relationships and overfitting the model. Analogously, the use of prior information enforced consistency in signature selection across disparate datasets: 15. 2% of the genes were selected all five times with informative priors was fit, which may be compared to 1% when noninformative priors were used, and 0% among the original signatures. The median of the pairwise overlap between two different model fits was 27. 5%, compared to 3% among the original signatures and 12% reported in Chuang et al. [6]. We also assessed the advantage of using multiple datasets by using only single datasets for training (with informative priors); results are shown in Fig. 3a (blue curve), Additional file 1, Fig. S1 (blue curves) and Table S1. A significant improvement was found when multiple datasets were used for model training compared to when only a single dataset was used (Bayesian P-value < 0. 001, related to the curves in Fig. 3a). In a final comparison, we modified to use only the expression data that corresponded to the respective gene signatures derived in Wang et al. [13], Miller et al. [14], Sotiriou et al. [15], and Pawitan et al. [16], together with noninformative priors (only the genes printed on the HG-U133A were used for the Miller et al. [14] and Pawitan et al. [16] signatures). Again, we found that (with informative priors) performed significantly better than when the signatures from Wang et al. [13], Miller et al. [14], Sotiriou et al. [15], and Pawitan et al. [SEP] Justify:

Output: The text does not directly address the claim about the importance of bioinformatics in analyzing genomic data. Instead, it discusses the validation of prior information in the context of model selection and classification accuracy, which is not primarily focused on bioinformatics or genomic data analysis as indicated in the claim.


Input: Task: corroborate the claim using the given text. Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: The common method to produce lactic acid from starchy biomass involves the pretreatment for gelatinisation and hydrolysis (liquefaction and saccharification). The liquefaction of the starch is carried out at high temperatures of 90–130 °C for 15 min followed by enzymatic saccharification to glucose and subsequent conversion of glucose to lactic acid by fermentation [22, 1]. This two-step process involving consecutive enzymatic hydrolysis and fermentation makes it economically unattractive. The bioconversion of carbohydrate materials to lactic acid can be made much more effective by coupling the enzymatic hydrolysis of carbohydrate substrates and microbial fermentation of the derived glucose into a single step. This has been successfully employed for lactic acid production from raw starch materials with many representative bacteria including Lactobacillus and Lactococcus species [23, 20, 24, 21]. Because at industrial scale, the use of glucose addition is an expensive alternative, there is interest in the use of a cheaper source of carbon, such as starch, the most abundantly available raw material on earth next to cellulose. This, in combination with amylolytic lactic acid bacteria may help to decrease the cost of the overall fermentation process. Amylolytic lactic acid bacteria can convert the starch directly into lactic acid. Development of production strains which ferment starch to lactic acid in a single step is necessary to make the process economical. Very few bacteria have been reported so far for direct fermentation of starch to lactic acid [1, 25, 26] Approximately 3. 5 billion tonnes of agricultural residues are produced per annum in the world [27]. The use of a specific carbohydrate feedstock depends on its price, availability, and purity. Although agro-industrial residues are rich in carbohydrates, their utilization is limited [27]. Different food/agro-industrial products or residues form the cheaper alternatives to refined sugars as substrates for lactic acid production. Sucrose-containing materials such as molasses are commonly exploited raw materials for lactic acid production. Starch produced from various plant products is a potentially interesting raw material based on cost and availability. Laboratory-scale fermentations have been reported for lactic acid production from starch by Lactobacillus amylophilus GV6 [20], L. [SEP] Justify:

Output: The text corroborates the claim by explaining the role of lactic acid bacteria in the fermentation process to convert glucose into lactic acid. It specifically mentions that representative bacteria such as Lactobacillus and Lactococcus species are employed for lactic acid production, highlighting their importance in the fermentation process.


Input: Task: contrast the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: Thus, LIP could send an eye-position modulated visual signal to the medial temporal lobe, which could serve as a building block for a supraretinal memory. The medial temporal lobe could then use this activity to generate the supraretinal component of place cell activity and send this supraretinal signal back to LIP. LIP itself would only be activated when the spatial location of the vanished stimulus can be described by a retinotopic vector from the center of gaze to the receptive field of the neuron. Thus, LIP has access to a supraretinal representation, but expresses only a retinotopic representation. It is important to emphasize that LIP is part of a spatial network that includes the FEF and the superior colliculus. Although neuropsychological studies suggest that parietal damage affects spatial memory, we do not know if damage to other parts of the network has a similar effect. Although early models posited that the oculomotor system uses a supraretinal representation (Zee et al. , 1976), it is clear that the parietal cortex sends a spatially accurate retinotopic signal to the oculomotor (Pare and Wurtz, 1997) and skeletomotor (Batista et al. , 1999) systems. Even auditory stimuli, which are initially coded in craniotopic coordinates, are converted to retinotopic coordinates for the oculomotor (Jay and Sparks, 1987b; Jay and Sparks, 1987a) and skeletal motor system (Grunewald et al. , 1999; Cohen and Andersen, 2000) in parietal cortex, and the oculomotor system of the superior colliculus (Jay and Sparks, 1984). We suggest that the environmental memory signal in LIP is an example of the conversion of a supraretinal signal to a retinotopic signal for memory and spatial attention as well as for motor control. Materials and methods Care and at and the Institute approved all of the animal protocols in this study as complying with the guidelines established in the for the Care and Use of (protocol NYSPI-1225-C). We used one female and two male rhesus monkeys (Macaca mulatta) with weights between 6 and 13 kg. We first trained monkeys to sit in a primate chair using a pole and collar technique. [SEP] Justify:

Output: The text contrasts the claim by suggesting that while environmental memory signals exist in the lateral intraparietal area (LIP), the system primarily operates through retinotopic representations which may not guarantee perfect recall. Although it discusses mechanisms for processing stimuli (e.g., converting supraretinal to retinotopic signals), it implies a complex interaction that does not support the notion of perfect recall, indicating potential limitations and dependencies on other factors and damage in the spatial memory network.


Input: Task: pass the claim using the given text. Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: [16] were used. Results are displayed in Additional file 1, Fig. S4 and Table S1. To derive a "final" gene signature, we fitted using all five datasets and informative priors. Some genes were included in this signature that a priori had been regarded as non-relevant to breast cancer; these genes were strongly supported by the data and may be of interest for future experimental investigations. The genes included in the signature are shown in Additional file 1, Table S2, stratified into genes that were relevant a priori as well as a posteriori, and genes that were regarded non-relevant a priori but relevant a posteriori. In order to further demonstrate the eScience-Bayes approach, we used it to create a model that predicted the probability of distant metastasis development as a function of time. This model would provide finer granularity in the prognosis predictions of future patients compared to the current practice of stratifying patients into only two classes (metastases or no metastases within five years). Patient stratification into two classes discards information by discretizing a continuous variable (time to development of distant metastasis) into an arbitrarily defined binary variable (yes/no development of distant metastasis within five years). Because not all patients had developed distant metastases before the last follow-up in the studies, this required a consideration of the censoring of the data (Methods). We created a multilevel Bayesian accelerated failure time (AFT) (Methods; Sha et al. [21]) model with the expression data as explanatory variables and the informative prior distributions (Model II, see Methods for details). Analogously to the assessment of Models I, we assessed Model II by fitting it five times, each time using three of the datasets as a training set and the remaining two datasets as test sets to assess the performance of Model II. The results implied that we indeed could provide more fine-grained prognoses predictions, compared to the binary classification afforded with (Fig. 3c). In this example, we provided evidence for that adopting the eScience-Bayes approach can significantly improve consistency in gene signature selection and in the predictive performance of the constructed models. In contrast to previous studies, our results were presented together with Bayesian confidence intervals, which permit assessment of the level of accuracy in the results [4]. [SEP] Justify:

Output: The text does not directly address the importance of bioinformatics in the analysis of genomic data. Instead, it focuses on specific methods used for developing a predictive model and gene signatures without mentioning bioinformatics as a general concept. Therefore, it is classified as irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: amylophilus B4437 [28], Lactobacillus amylovorus [29, 23, Lactococcus lactis combined with Aspergillus awamorii [30] and Rhizopus arrhizus [31]. L. amylophilus NRRL B4437 [32], L. amylovorus [17] and L. amylophilus GV6 are exceptions that have been described to actively ferment starch to lactic acid and this may lead to alternative process of industrial lactic acid production [23, 20]. To make the process cost effective in terms of substrate, various groups have worked on acid/enzyme hydrolysis of starchy substrates followed by Lactobacillus fermentation or simultaneous saccharification and fermentation by co-culture/mixed culture fermentations. It has been reported that starch is used as substrate in two steps [1]. 2. 2. Thermostable amylasesAmylases are among the most important enzymes and are of great significance in present-day biotechnology. Although they can be derived from several sources, such as plants, animals and microorganisms; enzymes from microbial sources generally meet industrial demands. The spectrum of amylase application has widened in many other fields, such as clinical, medical and analytical chemistries, as well as their widespread application in starch saccharification and in the textile, food, brewing and distilling industries. Thermostability is one of the main features of many enzymes sold for bulk industrial usage. Thermostable α-amylases are of interest because of their potential industrial applications. They have extensive commercial applications in starch liquefaction, brewing, sizing in textile industries, paper and detergent manufacturing processes. [33,34, 35]. The advantages of using thermostable amylases in industrial processes include the decreased risk of contamination and cost of external cooling, a better solubility of substrates, a lower viscosity allowing accelerated mixing and pumping [36]. Several thermostable α-amylase have been purified from Bacillus sp. and the factors influencing their thermostability have been investigated, but the thermostability of amylases from lactic acid bacteria have attracted very few scientific attention. [SEP] Justify:

Output: The text corroborates the claim by discussing the role of specific lactic acid bacteria, such as Lactobacillus amylovorus and Lactococcus lactis, in the fermentation processes that convert starch to lactic acid. It highlights that these bacteria can actively ferment starch and contribute to industrial lactic acid production, indicating their importance in fermentation.


Input: Task: pass the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: All PSTHs were normalized to baseline activity (block 1) and were constructed from 2 ms spike bins, smoothed using a 10 ms sliding causal filter. Baseline calculations were made in the −426 to −226 ms (pre-saccade onset) window. To quantify the decay, perisaccadic memory and visual responses, we selected the time point of peak activity in the window from 125 ms before the saccade onset (to include any predictive remapping) to 500 ms after. We then looked at the median of raw spike count over a window extending 100 ms before and after this point to calculate response latencies, as described next. To obtain a latency value of the memory response, we used a median threshold-crossing and sustained response method. In short, this analysis compared the median activity in the baseline and response windows. We derived a ‘cut off’ value by determining the spike count values which would fall above at least the 75% percentile of the baseline median. By comparing the median spike counts in the response window to this ‘cut off’ value, we could determine when a minimum of five bins (of 2 ms each) contained a greater spike count than the ‘cut off’ value. We took the first of these bins as the response latency, and verified visually by looking at the corresponding time on the PSTH. Since the baseline activity can vary between different trials in the same experiment, we first chose a window within the time from fixation to −226 ms before saccade onset. Within this wide window, we made 200 ms wide sliding windows, in 1 ms steps. By finding the median spike count within these smaller windows, we picked the window closest to the start of the response window (but still had the same median as the population of these several 200 ms wide windows). This median was chosen to look at the response window in which a threshold crossing for at least 20 ms was picked as the response latency. We could not calculate latencies for a few neurons using this method, because the baseline (pre-saccadic) memory block response was as high as post-saccadic activity. There were also a few other units whose latencies were automatically picked by the aforementioned median method but a more precise time point could be picked by doing yet another median-based analysis. [SEP] Justify:

Output: The text does not provide any information directly related to the claim about the perfect recall of memory with the right stimulus. Instead, it discusses technical methods for analyzing neural responses related to memory, without supporting or contrasting the idea of perfect recall.


Input: Task: pass the claim using the given text. Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: Proteomics data: Analyzing PDZ domain-peptide interactionsPDZ domains mediate protein-protein interactions and have been extensively studied over the last fifteen years. Recently, a large-scale PDZ domain-peptide interaction dataset was published in Stiffler et al. [22] and follow-up studies were later described in Chen et al. [23]. The combined data from these two publications comprise 2306 observations of interactions between peptides and PDZ domains from mouse, C. elegans, and D. melanogaster. We reanalyzed these data using the eScience-Bayes approach. To this end, we modeled the PDZ domain-peptide interactions using a multilevel Bayesian probit model with physicochemical properties of the PDZ domains and peptides as explanatory variables and a binary variable as response, indicating whether or not a PDZ domain and a peptide bound to each other (Model III). We derived informative prior distributions from 3D structural information using the by Structure [24] (SAS), a tool for annotating a protein sequence with structural information based on all solved 3D structures of the proteins in the Bank [25] (PDB). Using the SAS Web service [26] (WSsas) we estiamted the number of contacts made between residues in each PDZ domain and in the peptide ligands. Similarly to the breast cancer demonstration, we used the informative prior distributions to "guide" the variable selection in order to reduce the dimensionality of the model based on the assumption that the importance of a PDZ domain residue for the interaction is reflected in the number of contacts it makes with the ligand (see Methods for details). Fig. 4 shows the work flow for the prior elicitation and modeling. Fig. 5a summarizes the predictive performance of Model III in a receiver operating characteristics (ROC, see Methods) curve based on a 10-fold cross-validation, and shows a comparison with the predictive performance when noninformative prior distributions were used (i. e. equal prior probability for all variables to be included in the variable selection; see Methods). We observed a nonsignificant (Bayesian P-value = 0. 11) improvement in the predictive performance with informative compared to noninformative priors (Fig. 5a). Figure 4eScience-Bayes applied to protein-protein interaction data. [SEP] Justify:

Output: The text does not directly address the claim about bioinformatics and its role in analyzing genomic data. It focuses on proteomics data and statistical modeling of protein interactions, which is related to biological data analysis but does not specifically discuss genomic data or the overarching role of bioinformatics in that context.


Input: Task: corroborate the claim using the given text. Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: Lactobacillus amylovorus, Lactobacillus plantarum, Lactobacillus manihotivorans, and Lactobacillus fermentum are some of the lactic acid bacteria exhibiting amylolytic activity which have been studied [37, 10, 38, 5, 39, 40]. However, most of α-amylase from these bacteria presented weak thermostability compared to those of genus Bacillus. Owing to the important acidification of fermenting medium by most lactic acid bacteria, the production of thermostable amylase by a lactic acid bacterium under submerged or solid-state fermentation can help to reduce the risk of contamination caused by undesirable micro-organisms during the process [41, 42]. Another advantage is the non-pathogen character of the genus Lactobacillus that allows their utilization in food fermentation processes. 2. 3. Lactic acidLactic acid a water soluble and highly hygroscopic aliphatic acid is present in humans, animals and microorganisms. It is the first biotechnologically produced multi-functional versatile organic acid having wide range of applications [1], namely as a preservative in many food products. It can be produce by LAB trough fermentation or synthetically from lactonitrile [43]. It is non-volatile, odorless organic acid and is classified as GRAS (As Safe) for use as a general purpose food additive. The lactic acid consumption market is dominated by the food and beverage sector since 1982 [1]. More than 50% of lactic acid produced is used as emulsifying agent in bakery products [44]. It is used as acidulant/flavoring/pH buffering agent or inhibitor of bacterial spoilage in a wide variety of processed foods, such as candy, breads and bakery products, soft drinks, soups, sherbets, dairy products, beer, jams and jellies, mayonnaise, and processed eggs, often in conjunction with other acidulants. Lactic acid or its salts are used in the disinfection and packaging of carcasses, particularly those of poultry and fish, where the addition of aqueous solutions during processing increased shelf life and reduced microbial spoilage. The esters of calcium and sodium salts of lactate with longer chain fatty acids have been used as very good dough conditioners and emulsifiers in bakery products. [SEP] Justify:

Output: The text corroborates the claim by discussing the role of lactic acid bacteria (LAB) such as Lactobacillus in fermentation processes. It highlights their ability to acidify the fermenting medium and their non-pathogenic nature, both of which are beneficial for food fermentation. Additionally, it notes that lactic acid, produced by LAB through fermentation, is widely used in various food products, thereby supporting the importance of these bacteria in fermentation.


Input: Task: contrast the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: In a second round, we shuffled the object positions and repeated the task. Here three of the subjects made a mistake, presumably owing to interference with the memory formed on the previous round. Sighted subjects who inspected the scene visually performed similarly on the recall task (Figure 2—figure supplement 1). These experiments suggest that active exploration of object voices builds an effective mental representation of the scene that supports subsequent recall and orientation in the environment. Figure 2 with 1 supplement see all Download asset Open asset Spatial memory task. (A) Five objects are arranged on a half-circle; the subject explores the scene, then reports the recalled object identities and locations. (B) Recall performance during blocks 1 (left) and 2 (right). Recalled target angle potted against true angle. Shaded bar along the diagonal shows the 30 deg width of each object; data points within the bar indicate perfect recall. Dotted lines are linear regressions. (C) Slope and (D) correlation coefficient for the regressions in panel (B). Direct navigation Here, the subject was instructed to walk to a virtual chair, located 2 m away at a random location (Figure 3A). mode, the chair called out its name on every clicker press. All subjects found the chair after walking essentially straight-line trajectories (Figure 3B–C, Figure 3—figure supplement 1). Most users followed a two-phase strategy: first localize the voice by turning in place, then walk swiftly toward it (Figure 3—figure supplement 1D–E). On rare occasions (~5 of 139 trials), a subject started walking in the opposite direction, then reversed course (Figure 3—figure supplement 1C), presumably owing to ambiguities in azimuthal sound cues (McAnally and Martin, 2014). Subject seven aimed consistently to the left of the target (just as in the task of Figure 1) and thus approached the chair in a spiral trajectory (Figure 3C). Regardless, for all subjects the average trajectory was only 11–25% longer than the straight-line distance (Figure 3E, Figure 3—figure supplement 1A). Figure 3 with 2 supplements see all Download asset Open asset Direct navigation task. (A) For each trial, a target chair is randomly placed at one of four locations. [SEP] Justify:

Output: The text contrasts the claim by suggesting that memory can be affected by interference, as noted when three subjects made mistakes presumably due to such interference with previously formed memories. The findings illustrate that while certain tasks can support recall, they do not guarantee perfect memory recall, as indicated by the mistakes and the mention of ambiguities in sound cues that affected navigation behavior.


Input: Task: pass the claim using the given text. Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: Modeling of the PDZ domain-peptide interaction data with the eScience-Bayes approach. (Color-coding is as in Fig. 1. ) (A) All PDZ and peptide sequences and interaction data were retrieved from the supplementary material of Chen et al. [23] via PubMed Central. The PDZ sequences were aligned using the service. Prior information was retrieved using the SAS Web service. SAS was used to determine the number of contacts made between PDZ domain residues and ligand residues from the 3D complexes available in the Bank. (B) The aligned PDZ domain and peptide sequences were characterized by numbers capturing their physicochemical properties. The characterizations of the PDZ domain-peptide interactions were correlated to a 1 or a 0 in a binary response variable, which indicated whether a PDZ domain and a peptide could bind or not to each other. Analogous to the breast cancer demonstration, we reduce the dimensionality of the model guided by the prior information derived in (A) (see Methods). (C) The models were fit on an HPC resource. Full size imageFigure 5Model III results. (A) The ROC curves for Model III; the red and blue lines show the results when the prior information was or was not used, respectively. Solid lines denote the mode of the ROC curve distribution, and the dotted lines the 95% Bayesian confidence intervals. The area under the curves (AUC) are 0. 92 (0. 89;0. 93) (red) and 0. 90 (0. 87;0. 92) (blue). (B) Trends in differences between different PDZ domains were obtained by allowing the regression coefficients to vary with PDZ domains, and then subjecting the resulting matrix of regression coefficients to a principal component analysis (PCA) and plotting the PDZ domains in the space of the first three principal components. It should be noted that the regression coefficients are evenly distributed, which supports the relaxation of the canonical PDZ classes proposed in e. g. Stiffler et al. [22] and Tonikian et al. [37]. The regression coefficients from interactions in C. elegans (green dots) and D. melanogaster (blue dots) cluster together in the outskirts of the mouse interactions (red dots). (C) Differences in predicted networks between different PDZ domains. [SEP] Justify:

Output: The text discusses various methods related to the PDZ domain-peptide interactions and describes the application of statistical models such as PCA and ROC curves in analyzing these interactions. However, it does not specifically mention bioinformatics or directly address its significance in the broader context of genomic data analysis. Therefore, it is considered irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: SamplesTwenty-eight samples of soils were collected from main geographic zones of Cameroon in four localities: (Ngaoundere, Yaounde, Bafoussam and Mbouda) at the factories where starchy wastes are frequently submitted to natural fermentation. Four kinds of factories were investigated: “gari” factories, corn and cassava mills, cassava plantation after harvesting and treatment of tubers and flour markets. At the site where degradation of starchy material was remarkable and visible, one to five grams of soils were collected and transferred to polyethylene aseptic bag, the factory age recorded; the samples were finally transported to the laboratory and analyzed in the same week. 3. 2. Screening of thermostable amylases and lactic acid producing bacteriaThe starch degrading amylolytic lactic acid bacterial strains were isolated from different samples of soil. Amylolytic micro-organisms were firstly enriched by introduction of 1 g of soil sample in 100 ml Erlenmeyer flasks containing 50 ml of enrichment liquid medium, composed of (gram per litre): 5 g soluble starch, 5 g peptone, 5 g yeast extract 0. 5 g MgSO4. 7H2O, 0. 01g FeSO4. 7H2O, 0. 01 g NaCl. Enrichment of thermostable amylases producing bacteria was carried out by heating Erlenmeyer flasks at 90°C for 5 min followed by incubation in an alternative shaker at 37-40°C and speed of 150 oscillations per minute for 24 h. Amylases producing bacteria strains were screened on agar plate, containing (gram per liter): 10 g soluble starch, 5 g peptone, 5 g yeast extract, 0. 5 g MgSO4. 7H2O, 0. 01g FeSO4. 7H2O, 0. 01 g NaCl, 15 g agar. Incubation at 37-40°C was carried out for 48 h, after which the plates were stained with lugol solution (Gram iodine solution: 0. 1% I2 and 1% KI). The colonies with the largest halo forming zone were pre-selected and tested for Gram staining and catalase activity. Preliminary tests were carried out to determine the heat stability of the amylase of each isolate as we described previously [47, 48]. [SEP] Justify:

Output: The text corroborates the claim by discussing the isolation of lactic acid-producing bacteria from soil samples in Cameroon, specifically in the context of fermentation processes involving starchy materials. The extraction and screening of these bacteria highlight their role in the fermentation of starchy wastes, thereby supporting the assertion that lactic acid bacteria are indeed important for such processes.


Input: Task: contrast the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: Using CARA, subjects found the key efficiently (Figure 5D). Using vOICe none of the subjects were able to locate the key (Figure 5D), although two of them encountered it once by accident (Figure 5—figure supplement 1). These experiments illustrate the use of a standardized testing environment. Naive subjects performed well on these real-world tasks using CARA, but not using vOICe. It should be said that interpreting the vOICe sounds is very non-intuitive. Our subjects received the basic instructions offered on the vOICe web site and the ‘Exercise’ mode of vOICe (Sound, 2018), followed by a short period of practice. Extensive training with vOICe confers blind subjects with some ability to distinguish high contrast shapes on a clean background (Auvray et al. , 2007; Striem-Amit et al. , 2012). Conceivably an experienced vOICe user might perform better on the tests described here. Other investigators can attempt to demonstrate this using our published code and specifications (Liu and Meister, 2018; copy archived at Discussion ‘Seeing is knowing what is where by looking’ (Marr, 1982). The cognitive assistant CARA enables exactly this process while replacing the eye and early visual system. CARA conveys ‘what’ by the names of objects and ‘where’ by the location from where each object calls. ‘Looking’ occurs when the user actively requests these calls. The principal reason sighted people rely on vision much more than audition is that almost all objects in the world emit useful light signals almost all the time, whereas useful sound signals from our surroundings are few and sporadic. CARA can change this calculus fundamentally, such that all the relevant objects emit easily interpretable sounds. It is conceivable that the extended use of such an intuitive modality eventually produces subjective qualia that resemble the feeling of seeing. The use of spatialized sound in assistive devices has been considered for some time (Spagnol et al. , 2018), although to date there are few practical implementations with test results. For the purpose of outdoor navigation, Loomis et al. (2005) tested a system that guides the user along a path by virtual sounds emitted from way points. [SEP] Justify:

Output: The text contrasts the claim by discussing the efficacy of different stimuli (CARA vs. vOICe) in aiding memory recall and navigation. It highlights that while CARA assists subjects in locating objects efficiently, vOICe does not allow for successful recall, illustrating that memory cannot be perfectly retrieved with just any stimulus, particularly one that is described as non-intuitive and sporadic in providing useful auditory signals.


Input: Task: pass the claim using the given text. Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: Five residues (spacefilled) located outside the binding pocket that were estimated with Model III to be allosterically linked to residues in the binding peptide (light green) in representative PDZ domains: (i) mouse α 1-syntrophin(1/1), (ii) D. melanogaster Lap4(2/4), and (iii) C. elegans Lin7(1/1). The network residues are color coded according to the physicochemical property that is estimated to be important for the network: blue = size; red = polarity. Full size imageIn this example, the main advantage of adopting an eScience-Bayes approach was the increase in information that we obtained. For example, Model III enabled an analysis of the differences between PDZ domains. By allowing the regression coefficients to vary between PDZ domains (Methods), we found differences in the estimated nonzero coefficients for different PDZ domains (Fig. 5b). This suggests that there may be variations among the PDZ domains in the networks of residues that are important for interacting with ligands [27]. Interestingly, some of these residues are located far away from the binding site. Although the tertiary structures of PDZ domains are very similar, their primary structures vary substantially [28]. This may cause differences in the intramolecular interactions within different PDZ domains. Networks of such intramolecular interaction have previously been reported for PDZ domains [28, 29]. The results from studies by Gianni et al. [29] and Chi et al. [30] support the notion that the networks may differ among PDZ domains; for example, a network present in a PDZ domain from mouse tyrosine phosphatase BL was not found in the human PSD-95 PDZ3. The eScience-Bayes approach allowed analysis of these differences across a large set of PDZ domains. Model III further indicated that the PDZ domains from C. elegans and D. melanogaster may form two clusters (Fig. 5b). Given the small datasets from C. elegans and D. melanogaster, which contain only seven PDZ domains each (Fig. 4), the clustering might be a sampling or an experimental artifact. Nevertheless, it is tantalizing to hypothesize that there are general trends in the intramolecular interaction networks in PDZ domains that differ between species. [SEP] Justify:

Output: The text does not address the claim directly. Instead, it discusses the structural variations and interaction networks of PDZ domains in different species, with a focus on the eScience-Bayes approach for analysis. This content is largely technical and specific to protein structures, lacking any mention of bioinformatics or its role in genomic data analysis.


Input: Task: corroborate the claim using the given text. Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: The gas production from glucose, growth at different temperature (10, 40, 45 °C) as well as the ability to grow in different concentration of NaCl was determined as described by Schillinger and Lucke [49] and Dykes et al [50]. The isolates which were Gram positive and catalase negative, non-motile and producing heat stable amylase and lactic acid were finally selected and identified using API 50 CH test kit (bioMerieux, France). database identification was used to interpret the results. 3. 3. Microbial growth, amylase and lactic acid productionIn order to study microbial growth, amylase and lactic acid production, the microorganism was propagated at 40°C for 70 h in 50 ml of a basal medium containing: soluble starch, 1% (w/v); yeast extract, 0. 5 % (w/v) placed in 100 ml Erlenmeyer flask with shaking at 150 oscillations per minute in an alternative shaker (Kotterman, Germany). The initial pH of the medium was adjusted to 6. 5 using 0. 1 M HCl. After removal of cells by centrifugation (8000xg, 30 min, 4°C) in centrifugator (Heraeus, Germany), the supernatant was considered as the crude enzyme solution and was also used for lactic acid evaluation. 3. 4. Optimisation of raw starch degrading thermostable amylase and lactic acid productionThe amylase and lactic acid production was optimized by studying the effect of cultural and environmental variables (carbohydrate and nitrogen sources, metal salts and surfactants) individually and simultaneously. The effect of carbohydrate sources was studied by replacing soluble starch in basal medium with different sugars, gelatinized and raw natural crude starch sources (glucose, fructose, maltose, amylose, amylopectine, cassava, corn, rice tapioca, and sorghum flours at final concentration of 1% (w/v)). Nitrogen sources were tested by replacing yeast extract with various nitrogen sources (peptone, tryptone, beef extract, soyabean meal, ammonium sulphate, and urea at final concentration of 1. 5% (w/v)). The effect of metal salts was studied by adding individually various metal salts (CaCl2. 2H2O, MgSO4. [SEP] Justify:

Output: The text corroborates the claim by discussing the production of lactic acid through the optimization of microbial growth and enzyme production, which are contextually related to fermentation processes. It notes that 'the amylase and lactic acid production was optimized by studying the effect of cultural and environmental variables,' thereby highlighting the role of lactic acid, which is a key product in fermentation.


Input: Task: contrast the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: Natural spatialized sound is computed based on a generic head-related transfer function (Wenzel et al. , 1993); nothing about the software was customized to individual users. Object names and guide commands are translated into English using the text-to-speech engine from HoloToolkit. The user provides input by moving the head to point at objects, pressing a wireless Clicker, using hand gesture commands or English voice commands. In addition to instructions shown in the main body of the 4. Task design Task 1, object localization (Figure 1): In each trial, a single target is placed 1 m from the subject at a random azimuth angle drawn from a uniform distribution between 0 and 360 degrees. To localize the target, the subject presses the Clicker to hear a spatialized call from the target. After aiming the face at the object the subject confirms via a voice command (‘Target confirmed’). When the location is successfully registered, the device plays a feedback message confirming the voice command and providing the aiming error. The subject was given 10–15 practice trials to learn the interaction with CARA, followed by 21 experimental trials. To estimate the upper limit on performance in this task, two sighted subjects performed the task with eyes open: this produced a standard deviation across trials of 0. 31 and 0. 36 degrees, and a bias of 0. 02 and 0. 06 degrees. That includes instrumentation errors as well as uncertainties in the subject’s head movement. Note that these error sources are insignificant compared to the accuracy and bias reported in Figures 1 and 2. Task 2, spatial memory (Figure 2): This task consists of an exploration phase in which the subject scans the scene, followed by a recall phase with queries about the scene. Five objects are placed two meters from the subject at azimuth angles of −60°, −30°, 0°, 30°, 60° from the subject’s initial orientation. Throughout the experiment, a range between −7. 5° and 7. 5° in azimuth angle is marked by ‘sonar beeps’ to provide the subject a reference orientation. During the 60 s exploration phase, the subject uses ‘Spotlight Mode’: This projects a virtual spotlight cone of 30° aperture around the direction the subject is facing and activates object voices inside this spotlight. Typically subjects scan the virtual scene repeatedly, while listening to the voices. [SEP] Justify:

Output: The text contrasts the claim by discussing a spatial memory task where subjects must recall the locations of objects after an exploration phase. It highlights that even with aids like spatialized sounds and practice trials, there are errors in the subjects' recall, indicating that memory recall is not perfect even with stimuli. Specifically, it notes standard deviations in performance, which signifies limitations in accuracy, thereby refuting the notion of perfectly recalled memory.


Input: Task: pass the claim using the given text. Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: c X thus represents the c-values of the tciz-coded residues r1,. . . ,r67 and p1,. . . ,p10 incremented by 1. The c-values were incremented by 1 to ensure that all variables in H have a chance of being selected (i. e. including those with c-values equal to zero). Model IIIWe modeled the interaction between PDZ domains and peptides using a Bayesian hierarchical probit model according to: (6) where is the i th row in (the rows of H corresponding to PDZ domain ϕ). d j is the j th value in the row vector cX, H(X). Hence, the a priori probability of a variable to be selected is larger, the larger the number of contacts the PDZ residue it is derived from makes with the ligand (the assumption being that the more contact a PDZ residue makes with the ligand, the greater our a priori belief that the residue is important for the interaction). The other denotations are analogous to the ones used in Model I. The prior for m, i. e. the parameter controlling the number of selected variables, was chosen so that roughly one twentieth of the total number of variables was selected (i. e. so that = 11935/20, where E denotes the expectation operator). The mean of the prior distribution for m was estimated using cross-validation on the training data. Model III was also modified to assess the use of the prior information about which residues that are important for governing the interaction between PDZ domains and peptides. We then set p = 1/11935. Residue coupling depicted in Fig. 5cThe coupling was estimated by studying the interaction terms in H formed between tciz scales from one residue in the PDZ domain and one in the peptide as outlined in Prusis et al. [38]. The figure displays the five such interaction terms with the largest (absolute-valued) modes of the regression coefficient's distributions. The network residues are color coded according to the physicochemical property that is estimated to be important for the network; residue size is shown in blue and residue polarity in red. [SEP] Justify:

Output: The text is irrelevant ('pass') to the claim as it does not address bioinformatics or its role in analyzing genomic data. Instead, it discusses modeling interactions between PDZ domains and peptides without any mention of bioinformatics or genomic analysis.