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

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

Output: The text corroborates the claim by detailing how L. plantarum employs glycolysis and fermentation processes to produce lactate, ethanol, and acetate, which are key aspects of lactic acid fermentation. The text explains that shifting production towards acetate can increase ATP yield during fermentation, emphasizing the role of lactic acid bacteria in energy conservation and metabolic processes during fermentation. This supports the claim regarding the significance of lactic acid bacteria in fermentation.


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

Output: The text appears to be a list of references and citations related to geomorphology and geological studies, but it does not directly address the claim about fossils being infallible indicators of past environments. As such, it does not provide supporting or contrasting evidence regarding the accuracy of fossils in indicating past environments, making it irrelevant to the claim.


Input: Task: pass the claim using the given text. Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: In a small data set, one can use the elbow test or similar methods to detect the changing shape for the decay of the spectrum of SVD to determine the layout dimension. In a large data set, one feasible approach is to use stochastic methods by cross-validation to measure the layout dimension [11]. MethodsWe first describe SC-MDS using a simple case, and for convenience we use the classical MDS (CMDS) as the default MDS method to show how we can improve it. Assume that x i ∈ Rpare the coordinates of data points for i = 1,. . . ,N and p <<N. We define di,j= ||x i - x j ||2 as the Euclidean distance between x i and x j. N is large such that applying the CMDS technique is impractical. We split the points into two overlapping sets S1 and S2, and the intersection of these two sets contains more than p points. The main idea is to apply MDS to each individual set to get the configuration, and to use the information of the overlapping points to combine the two sets into one. There are two problems that need to be solved: (1) how to combine two sets into one and (2) what is the sufficient condition for this solution to be equivalent to that obtained by working directly with the full set? The solutions to these two problems are proposed in the next subsections. Combination MethodWhen we split the whole set of data points into two overlapping subsets of equal sizes, the combined size of the two distance matrices for the two subsets is less than that for the whole set. Assume that the configurations of these two subsets obtained from MDS are xi,1and xi,2and the dimensions of the two configurations are the same. We can fix the coordinates of the data points in the first set and use the overlapping data points to find an affine mapping U(·) + b such that for each intersection point xk,1∈ S1, xk,1= Uxj,2+ b, where xj,2∈ S2 for some j. Note that the matrix U of the affine mapping is a unitary matrix, which is a volume-preserving operator. The affine mapping can be found as follows. [SEP] Justify:

Output: The text is irrelevant to the claim regarding the importance of bioinformatics in genomic data analysis. It discusses specific mathematical methodologies, including methods for dimensionality reduction using Stochastic methods and MDS, without mentioning bioinformatics or its relevance to genomic data.


Input: Task: corroborate the claim using the given text. Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: 75 x more fermentation products per each mol of mannitol utilized (Yfermentation, Table 1). The culture medium pH was also significantly lower than under OC (Figure 5B), a result which may indicate that EET conferred higher levels of acid stress on L. plantarum, and therefore, reductions in cell viability, despite EET leading to higher cell numbers overall (as measured by dry cell weight) (Figure 4A–B). A similar acidification of the medium was observed for ΔpplA, but not for Δndh2, when an anode was present as electron acceptor, indicating that ndh2-dependent EET is needed to decrease the pH (Figure 3—figure supplement 2B). When much lower, sub-physiological levels of DHNA were supplied (0. 01 μg/mL), a smaller but significant decrease in the pH of the medium was also observed (Figure 1—figure supplement 3C). Overall, these results show that EET allows L. plantarum to ferment to ~1. 75 x greater extent and to acidify the medium to a greater extent as well. Figure 5 with 2 supplements see all Download asset Open asset Fermentation fluxes are increased when an anode is provided as an extracellular electron acceptor. Results are from the same set of experiments as the current density plot shown in Figure 3C. (A) Metabolic yields of L. plantarum end-fermentation products under open circuit conditions (OC) and current circulating conditions (EET) in mCDM supplemented with 20 μg/mL DHNA. (B) pH measurements and (C) mannitol, (D) lactate, (E) acetate, and (F) ethanol concentrations over time under OC and EET conditions. (G) Schematic of proposed model for NADH regeneration during fermentation of mannitol in the presence of an anode as electron sink for L. plantarum. The avg ± stdev of three biological replicates is shown. Significant differences were determined by one-way ANOVA with Dunn-Sidak post-hoc (n = 3), ** p < 0. 01. See also Figure 5—figure supplement 1 and Figure 5—figure supplement 2 and related data in Figure 5—source data 1. Figure 5—source data 1 Raw data of Figure 5A–F. [SEP] Justify:

Output: The text corroborates the claim by providing evidence that L. plantarum (a type of lactic acid bacteria) can produce significantly more fermentation products per mole of mannitol utilized under certain conditions (75 times more). It outlines the impacts of electrochemical processes on fermentation yields and acidification of the medium, demonstrating that lactic acid bacteria play a crucial role in fermentation, specifically enhancing the extent of fermentation and the production of acid compounds.


Input: Task: contrast the claim using the given text. Claim: Dinosaurs were all warm-blooded and behaved like modern birds. [SEP] Text: In certain nonavian maniraptorans, long pennaceous feathers attach to the distal part of the tail, either in a fan-like fashion or giving the tail the frond-like appearance common to primitive birds such as Archaeopteryx (Fig. 1a). Long pennaceous feathers also attach to the tip of the forelimbs of some of these maniraptorans, and in the case of the peculiar dromaeosaurid Microraptor (Norell and Xu 2005), they form a wing of essentially modern design. Despite the evidence of plumage being restricted to a handful of nonavian dinosaurs, the fact that these fossils span a large portion of the family tree of theropods and display a great diversity of sizes, appearances, and lifestyles, hints at a much larger and yet undocumented diversity (Fig. 3)—even the colossal T. rex may have been covered with a cloak of feathers at some early stage of its life. It is an amazing experience to gaze at the entirely modern feathers of animals, whereas their skeletal characteristics are so unquestionable dinosaurian. Fig. 3Genealogical relationships of feathered nonavian theropods. Current evidence supports the hypothesis that filamentous and vaned feathers evolved with the divergence of coelurosaurs and maniraptorans, respectivelyFull size imageAn important corollary of these discoveries is that feathers did not evolve in the context of flight. With the sole exception of Microraptor, it is certain that none of these feathered dinosaurs were able to take to the air. The forelimbs and their feathers are both much shorter than in flying birds and their bodies are larger. The evolutionary transition toward birds and the origin of their flight involved a dramatic reduction in body size. These feathered dinosaurs indicate that, at their onset, feathers must have had a different function, perhaps insulating the bodies of animals that had metabolically diverged from their cold-blooded, reptilian ancestors. My research has suggested that vaned feathers may have originated in the context of thrust, evolving in running nonavian theropods that by flapping their feathered arms were able to increase their running speed (Burgers and Chiappe 1999). In the end, however, we simply do not have an answer for what was the original function of feathers; nonetheless, we have been able to eliminate flight as an option. [SEP] Justify:

Output: The text contrasts the claim by discussing that evidence suggests feathers in certain nonavian dinosaurs might not have evolved for flight but rather for insulation, indicating that these dinosaurs were likely still cold-blooded. The passage states that none of these feathered dinosaurs, except for Microraptor, were able to take to the air and that the evolutionary changes necessary for flight involved a dramatic reduction in body size, aligning more with cold-blooded characteristics rather than those of warm-blooded modern birds.


Input: Task: pass the claim using the given text. Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: Assume X1 and X2 are matrices in which the columns are the two coordinates of the overlapping points obtained by applying MDS to two data sets, and X ¯ 1 MathType@MTEF@5@5@+=feaafiart1ev1aaat9MDH5MBPbIqV92AaeXatLxBI9g6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaae@2E42@ and X ¯ 2 MathType@MTEF@5@5@+=feaafiart1ev1aaat9MDH5MBPbIqV92AaeXatLxBI9g6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaae@2E44@ are the means of columns of X1 and X2, respectively. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses mathematical concepts related to matrices and multidimensional scaling, without mentioning bioinformatics or its role in analyzing genomic data.


Input: Task: corroborate the claim using the given text. Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: Download elife-70684-fig5-data1-v2. xlsx We also observed that EET led to higher cellular metabolic fluxes, that is, higher changes in metabolites per cell per unit time. Although the final OD600nm and dry cell weight were not significantly different (Supplementary file 1), L. plantarum utilized mannitol and produced acetate and lactate more rapidly under EET than OC conditions (Figure 5C–F). Cells performing EET were ~2 fold faster at consuming mannitol (Figure 5C) between days 1 and 3. Mannitol consumption increased between day 1 and day 2, approximately when the cells transitioned to higher current density (Figure 3C), suggesting that increased EET drove that increased consumption. The overall rates of acetate and lactate production also increased 3. 4 and 3. 6 times (Figure 5D–E), respectively. Measurements of metabolites produced by ΔpplA and Δndh2 strains confirmed that, like for current production to an anode, the EET-associated increased metabolic flux in L. plantarum requires the presence of Ndh2, but not PplA (Figure 3—figure supplement 2C). Overall, these data indicate that ndh2-dependent EET increases both the flux and final yield of fermentation in L. plantarum. Because the production of acetate yields ATP, these results also suggested that the increase in ATP generation under EET conditions may be due to substrate-level phosphorylation. To probe whether EET-associated increase in fermentative flux could account for the changes in ATP generation, we calculated fermentation balances (Table 1). Our measurements account for 80% of the carbon under EET conditions (see Supplementary file 1), leaving a maximum of ~20% systematic uncertainty in these calculations. The concentrations of fermentation products detected (Supplementary file 1) were used to estimate the total ATP in the presence and absence of EET. The estimated ATP was 3-fold higher under EET conditions than OC conditions (Table 1), a result that is consistent with the ~2. 5 fold higher accumulation of ATP measured at maximum current density (Figure 4D). Overall, this quantitative analysis shows that the vast majority of the increased energy conservation under EET conditions can be accounted for by an increase in fermentation yield and substrate-level phosphorylation. EET shifts how L. [SEP] Justify:

Output: The text corroborates the claim by explaining how L. plantarum, a type of lactic acid bacteria, increases both the flux and final yield of fermentation processes under EET (electroactive extracellular electron transfer) conditions. It highlights that the production of metabolites like acetate and lactate is enhanced in the presence of EET, which supports the idea that lactic acid bacteria play a significant role in fermentation.


Input: Task: pass the claim using the given text. Claim: All brain functions can be mapped with current technology. [SEP] Text: The position and orientation of each 2D slice within the embryo is indicated on the Nissl-stained two photon reference image to the right of the panel. Scale bar: 100 μm. (A) the fezf2 expression domain is highly disorganized in multiple regions of the diencephalon and telencephalon. (B) Vmat2 expression is largely unaffected in DA clusters of the telencephalon (arrow). (C) Expression of glyt1, a marker of astrocytic and glycinergic neuronal differentiation, is upregulated in the ventricular zone of the dorsal telencephalon (arrow). (D) Telencephalic expression of the GABAergic marker gad1b undergoes a shift away from the midline in mutant embryos (asterisk) but is not significantly reduced. (E) Expression of tbr1b, a transcription factor that plays an essential role in specifying glutamatergic pyramidal neurons, is significantly reduced. (F) Expression of emx3, a transcription factor that is broadly expressed within the telencephalon, is significantly reduced. (G) Expression of the neural progenitor marker eomesa is substantially reduced. (H) The neural progenitor marker neurog1 undergoes an anterior shift in regions of the diencephalon that closely neighbor the telencephalon (arrow). (I) The neural progenitor marker zic2a is shifted ventrally and possibly expanded in the dorsal telencephalon and surrounding regions. Figure 5—figure supplement 2 Download asset Open asset 3D segmentations of telencephalic expression domains. 3D segmentations of gene expression domains within and immediately adjacent to telencephalon at 2 dpf are generated in a semi-automated manner using adaptive thresholding. The gray background segmentation represents the union of telencephalic segmentations for all probes in the library and serves as an estimation for the outline for the telencephalon. Segmentations were generated from averaged 3D reconstructions. All segmentations are shown in front view (dorsal is to the top) and side view (anterior is to the left) for both wild-type and fezf2 mutant embryos. Scale bar: 100 μm. Figure 6 with 1 supplement Download asset Open asset Segmentation and volume measurements. [SEP] Justify:

Output: The text does not address the claim regarding the mapping of all brain functions with current technology. Instead, it describes observations related to gene expression in specific brain regions during embryo development, which does not provide information that supports, contrasts, or is relevant to the claim.


Input: Task: pass the claim using the given text. Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: In order to use the same orthogonal basis to represent these vertices, we apply QR factorization to X 1 − X ¯ 1 1 ˙ T MathType@MTEF@5@5@+=feaafiart1ev1aaat9MDH5MBPbIqV92AaeXatLxBI9g6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaae1aa@33EF@ and X 2 − X ¯ 2 1 ˙ T MathType@MTEF@5@5@+=feaafiart1ev1aaat9MDH5MBPbIqV92AaeXatLxBI9g6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaae1aa@33F3@ so that X 1 − X ¯ 1 1 ˙ T = Q 1 R 1 MathType@MTEF@5@5@+=feaafiart1ev1aaat9MDH5MBPbIqV92AaeXatLxBI9g6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaae1aa2da9iabdgfarnaa1aaSbaaSqaaiabigdaXaqabaaaaa@3999@ and X 2 − X ¯ 2 1 ˙ T = Q 2 R 2 MathType@MTEF@5@5@+= [SEP] Justify:

Output: The text provides a complex mathematical explanation involving QR factorization, but it does not explicitly discuss bioinformatics or its role in analyzing genomic data. Therefore, the text 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: plantarum uses electron acceptors and converts ATP into biomass Thus far, our results provided an unusual picture of the energy metabolism of L. plantarum under EET conditions; while EET significantly shifted the intracellular redox state to a more respiratory-like balance, its increased ATP yield was mainly accounted for by an increased fermentative yield. Another major difference in fermentation and anaerobic respiration is the use of the endogenous versus exogenous electron acceptors. To more deeply understand how L. plantarum uses organic molecules and the anode as electron acceptors when performing EET, the electron balances under EET and OC conditions were calculated (Table 1 and Supplementary file 1). We estimated the NADH produced using two different methods (see Supplementary file 1 for methodology) and the NADH re-oxidized through the reduction of the anode (measured as current) and via substrate-level phosphorylation. This allowed us to obtain a global balance of the NAD+/NADH ratio. Under OC conditions between 35% and 66% of the NADH produced from the oxidation of mannitol to pyruvate (a range is given using the two methods used) was re-oxidized to NAD+ (5. 5 mM NADH consumed, Table 1), qualitatively agreeing with the low NAD+/NADH ratios measured (Figure 4E). In contrast, electron balance calculations showed that between 77% and 96% of the NADH produced under EET conditions was re-oxidized (17 mM NADH consumed, Table 1), a result that is consistent with the significantly higher NAD+/NADH ratios measured (Figure 4E). Interestingly, these calculations estimate that 55–69% of the total NADH generated was oxidized through fermentation, while 21–28% of the NADH was oxidized using the electrode as a terminal electron acceptor (Table 1). Thus, L. plantarum growing under EET conditions achieves a more oxidized intracellular redox balance by more completely fermenting mannitol to lactate and ethanol and by using the electrode as a terminal electron acceptor (Figure 5G). These observations reinforce that the energy metabolism of L. plantarum under EET conditions utilizes elements of both fermentation and anaerobic respiration. In rapidly dividing cells, energy conservation, a catabolic process, is associated with growth, an anabolic process. [SEP] Justify:

Output: The text corroborates the claim by discussing how _L. plantarum_ utilizes fermentation as a significant process for energy metabolism. It states that '55–69% of the total NADH generated was oxidized through fermentation,' indicating that fermentation is a primary pathway for energy conservation in this bacterial species. Furthermore, it details that _L. plantarum_ ferment mannitol to lactate and ethanol, which is a clear example of the role of lactic acid bacteria in fermentation.


Input: Task: contrast the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: However, in contrast to previous suggestions, we additionally observed a connectivity difference along the anteroposterior axis (repeated-measures ANOVA: main effect of network, F(1,21) = 13. 2, p = 0. 001) and post-hoc t-tests showed that the anterior parts of EC connected more with the AT compared to the PM network (T(21) = 2. 7: p = 0. 01; posterior EC: T(21) = −0. 49, p = 0. 63). Table 1 Selection of regions associated with the posterior-medial (PM) and the anterior-temporal (AT) system (Libby et al. , 2012). The coordinates of the PM system reflect peak voxel coordinates of a seed-based connectivity contrast of right parahippocampal cortex > right perirhinal cortex connectivity reported by Libby et al. (Libby et al. , 2012). The coordinates of the AT system reflect peak voxel coordinates of a seed-based connectivity contrast of right perirhinal cortex > right parahippocampal cortex connectivity. Coordinates are in MNI space. [SEP] Justify:

Output: The text contrasts the claim by discussing connectivity differences in brain networks related to memory but does not support the idea that memory can be perfectly recalled with the right stimulus. Rather, it highlights the complexity of memory systems and their connectivity, suggesting that recall may be influenced by multiple factors rather than being a perfect process.


Input: Task: pass the claim using the given text. Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: feaafiart1ev1aaat9MDH5MBPbIqV92AaeXatLxBI9g6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaae1aa2da9iabdgfarnaa1aaSbaaSqaaiabikdaYaqabaaaaa@39A1@. [SEP] Justify:

Output: The text does not provide any relevant information regarding bioinformatics or its importance in analyzing genomic data. Instead, it appears to be a series of nonsensical characters, making it irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: However, catabolism need not be coupled with anabolism (Russell and Cook, 1995). To determine how catabolic and anabolism are connected under EET conditions, the ATP requirements to grow biomass (YATP) were estimated using the calculated ATP and the measured dry weight. Under OC conditions, the YATP obtained (8. 06 ± 0. 8 g dw/mol ATP) for L. plantarum was similar to that observed previously (10. 9 g-dw/mol ATP) (Dirar and Collins, 1972). Hence, without EET, the ATP generated from fermentation was converted into biomass nearly at the expected efficiency. In contrast, a significantly lower YATP was reached for L. plantarum performing EET (3. 07 ± 0. 35 g dw/mol ATP) (Table 1). This observation indicates that under EET conditions, either more ATP is required to produce biomass or more ATP is utilized by other functions such as for PMF-generation and intracellular pH regulation (Russell and Cook, 1995). EET conditions also resulted in 79% more ATP per mol of fermented mannitol (Ymannitol). Consequently, molar biomass yields (g-dw/mol-mannitol) under EET conditions were significantly lower (Table 1), in agreement with previous observations in respiratory electroactive species (Esteve-Núñez et al. , 2005). These calculations show that when L. plantarum performs EET, anabolism and catabolism processes are differently coupled than under OC conditions. ATP is produced more efficiently, but this it is less efficiently utilized to make biomass. Overall, these results show an intriguing pattern of coupling between anabolism and catabolism, indicative of a novel energy metabolism in L. plantarum during EET. EET is active in vegetable fermentations Our results inspired us to explore whether EET could occur in a physiological niche of LAB such as fermented foods. LAB are necessary for the making of many fermented fruit and vegetable foods and the properties of those foods depend on the metabolic diversity of the LAB strains present (Gänzle, 2015). Plant tissues also contain a much wider variety of carbon substrates and potential electron acceptors than the CDM used in our prior experiments. [SEP] Justify:

Output: The text corroborates the claim by stating that lactic acid bacteria (LAB) are necessary for the making of many fermented fruit and vegetable foods. It emphasizes the importance of LAB in fermentation processes and notes that the properties of these foods depend on the metabolic diversity of the LAB strains present, thus supporting the claim of their significance.


Input: Task: pass the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: Both model-based and data-driven connectivity analyses, as well as sensitivity to non-spatial vs spatial stimuli provide evidence for an anterior-lateral and a PM localisation of the homologues of the rodent LEC and MEC, respectively. Maass et al confirmed these findings in a study with two high-resolution, high-field fMRI datasets by focusing on local connectivity between regions of the medial temporal lobes. They found preferential connectivity of PRC and proximal subiculum to anterior-lateral parts of the EC, whereas posterior-medial parts of the EC were more connected to PHC and distal subiculum. This corresponds well with our findings (Figure 2—figure supplement 1). In line with the present study, Maass et al (Maass et al. , 2015) report local connectivity fingerprints of the human anterior-lateral and posterior-medial EC that mimicked those of the rodent LEC and MEC, respectively. In addition to the change in functional connectivity from PM to anterior-lateral, our data-driven connectivity analysis also revealed a second organisation structure approximately perpendicular to the first (Figure 3—figure supplement 1), which might reflect bands of intra-entorhinal projections that are known to cross the LEC/MEC boundary in a roughly orthogonal orientation in rodents (Canto et al. , 2008) and in primates (Chrobak and Amaral, 2007). The selective sensitivity to spatial and non-spatial information, or ‘context vs content’ more broadly (Knierim et al. , 2013), points towards fundamental difference in computations of the LEC and MEC. How to characterise those differences most accurately remains an open question (Knierim et al. , 2013), but our results can help to inform future studies on the role of the human alEC and pmEC in higher-level cognition. Notably, the present findings confirm three out of four complementary criteria for the definition of cortical areas that have traditionally been advocated (Van Essen, 1985), namely topographic organization, connectivity and functional properties (the fourth one being cyto- and myeloarchitectonic organization). Previous neuroimaging studies in humans reported differences between medial and lateral aspects of EC that mimicked differences between the rodent MEC and LEC and assumed that both subregions are present on coronal slices of the EC (Schultz et al. [SEP] Justify:

Output: The text does not address the claim regarding the perfect recall of memory with the right stimulus. Instead, it discusses details of connectivity analyses in the medial temporal lobes and provides insights into the differences between spatial and non-spatial processing in the entorhinal cortex. It does not confirm, contrast, or relate to the capability of perfect memory recall.


Input: Task: pass the claim using the given text. Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: Since these two coordinates represent the same points, the triangular matrices R1 and R2 should be identical when there is no rounding error from computing the QR factorization in X1 and X2. The positive and negative signs of columns of Q i could be arbitrarily assigned in the computation of QR factorization. Hence, the signs of columns of Q i should be adjusted according to the corresponding diagonal elements of R i so that the signs of diagonal elements of R1 and R2 become the same. After the signs of columns of Q i are modified, we conclude Q 1 T ( X 1 − X ¯ 1 1 ˙ T ) = Q 2 T ( X 2 − X ¯ 2 1 ˙ T ). [SEP] Justify:

Output: The text does not address the claim regarding the importance of bioinformatics in analyzing genomic data. Instead, it discusses computational aspects of QR factorization, which is unrelated to the overarching concept of bioinformatics and genomics.


Input: Task: corroborate the claim using the given text. Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: To study the physiological and biotechnological relevance of EET in food fermentations, kale juice was fermented using L. plantarum as a starter culture (Figure 6A). The fermentation of kale juice was measured under EET conditions (a polarized anode with or without DHNA), and an OC control (a nonpolarized anode with DHNA) was used to separate the role of DHNA and electron flow to the anode on the fermentation process. An additional bioreactor without cells, but with DHNA, was operated to identify any possible electrochemical-driven conversion of substrates. When L. plantarum was added to the prepared kale juice, approximately 10-fold more current was generated during EET conditions with DHNA (EET+ DHNA) as compared to abiotic and biological non-EET promoting conditions (no DHNA) (Figure 6B). This current was comparable to the current generated in laboratory medium (Figure 3C), indicating that robust EET by LAB is possible in the complex physiological conditions of a food fermentation. Figure 6 with 1 supplement see all Download asset Open asset EET in a kale juice increases the production of fermentation end products. (A) Preparation of kale juice medium used for fermentation in bioelectrochemical reactors. (B) Current density production measured from kale juice medium over time in the presence of L. plantarum and 20 μg/mL DHNA, no DHNA, or under abiotic conditions with addition of 20 μg/mL DHNA. The anode polarization was maintained at 0. 2 VAg/AgCl. (C) Normalized total quantities of the metabolites detected per cell (CFUmax used for calculations). (D) pH measurements over time under different conditions tested on a second set of kale juice fermentations performed under the same conditions. (E) Production rate per viable cell, r, of lactate, acetate, and succinate. The avg ± stdev of three biological replicates is shown. See also Figure 6—figure supplement 1 and related data in Figure 6—source data 1. Figure 6—source data 1 Raw data of Figure 6B–E. Download elife-70684-fig6-data1-v2. xlsx We next investigated the impact of EET on L. plantarum growth and metabolism in the kale juice fermentation. [SEP] Justify:

Output: The text corroborates the claim by detailing the role of L. plantarum, a lactic acid bacterium, in the fermentation of kale juice. It describes how the addition of L. plantarum significantly enhances current generation during fermentation and supports the idea that lactic acid bacteria contribute to important metabolic processes, such as the production of fermentation end products.


Input: Task: contrast the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: Correction to: of on Nonverbal Memory: Meta-regression of Stimulus- and Task-related. Bentvelzen1,2, Roy P. C. Kessels3,4, Nicholas A. Badcock5,6 & …Greg Savage2 Show authors 1710 Accesses 1 all metrics 10. 1007/s11065-021-09514-3 In the original published paper, it was belatedly discovered that there was a data entry error in coding one test-related factor for the (BVRT) only, for which the factor Format was incorrectly coded as Recognition, when it should have been coded as Recall. While only a minor error in isolation this had widespread ramifications for the paper since a key unique aspect of the analysis was comparing the relative impact of stimulus- and test-related factors on the association between nonverbal memory tests and identifying right (versus left) temporal lobe pathology. In addition, there were k = 10 papers on the BVRT, which is enough that it possibly meant that this could impact statistically on the results and therefore the interpretation and conclusions. The section within the Results entitled “Meta‑regression of Type and Test‑related Moderators” effectively required a complete rewrite. It was therefore considered essential to write this erratum. The remaining tests were thoroughly checked, and thankfully this type of error was not replicated elsewhere. In addition to the edits due to the coding error, there were some additional minor errors in the manuscript I have taken the opportunity to also correct. 1 The sentences. “Stimulus type significantly moderated the size of the right-lateralization effect (faces > designs) for postsurgical patients, test format moderated the size of the right-lateralization effect for presurgical-postsurgical change (recognition > recall) but learning format and test delay had no right-lateralization effect for either sample. For presurgical patients, none of the task-related factors significantly increased right-lateralization effects. ” are replaced by: “For presurgical patients the size of the right-lateralization effect was significantly moderated by stimulus type (faces > designs), testing format (recall > recognition), and its interaction with the learning format (repeated trials more affected by format effect than single trials) of the nonverbal memory tests. [SEP] Justify:

Output: The text contrasts the claim by indicating that a coding error in the analysis significantly affected the interpretation of how different factors (stimulus type and test format) moderated the right-lateralization effects in memory tests. This suggests that memory recall is not perfect with the right stimulus, as the analysis was complicated by errors and seemed to fluctuate based on varying conditions, implying that memory recall can be influenced by more than just the stimulus.


Input: Task: pass the claim using the given text. Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: MathType@MTEF@5@5@+=feaafiart1ev1aaat9MDH5MBPbIqV92AaeXatLxBI9g6xNi=xI8qi9v8qqaqFr0xc9vqFj0dXdbba91qpepeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaaeGaciGaaiaabeqaaeqabiWaaaGcbaGaemyuae1aa0baa09aqpcq1aa6caUaaa@48C5@ (5) Furthermore, we can obtain X 1 = Q 1 Q 2 T X 2 − Q 1 Q 2 T ( X ¯ 2 1 ˙ T ) + X ¯ 1 1 ˙ T. [SEP] Justify:

Output: The text does not address the claim regarding bioinformatics and its role in analyzing genomic data. It appears to be a mathematical expression without any discussion or relevance to bioinformatics or genomic analysis.


Input: Task: corroborate the claim using the given text. Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: Significant changes in the pH and fermentation products were detected under EET conditions (Figure 6C–D). These differences occurred in the absence of significant changes in viable cell numbers (Figure 6—figure supplement 1A) at the time points measured. As previously observed using laboratory culture media, an approximately 2-fold greater accumulation of total end-fermentation products per cell was obtained when cells interacted with an anode in the presence of DHNA (Figure 6C). In the kale juice fermentation, EET+ DHNA conditions enhanced both lactate and acetate production per cell without changing the distribution of metabolites (Figure 6E and Figure 6—figure supplement 1B). Thus, when DHNA was provided, EET enhanced the overall yield of fermentation end-products and their production rates per cell, mimicking our observations in laboratory medium (Figure 5C–D). EET also led to a significantly higher acidification of the kale juice compared to OC conditions, and the presence of DHNA dramatically enhanced this pH drop (Figure 6D). In general, when no DHNA was supplied but an anode was present as an electron acceptor, the fermentation process was very similar to OC conditions. This means in kale juice, a source of quinones is essential to support L. plantarum EET activity. Overall, these results show that EET under physiological conditions impacts cellular metabolism in L. plantarum by increasing metabolic flux which ultimately can affect the flavor profile of fermented foods (Chen et al. , 2017). in fermentation and energy conservation from EET have important bioenergetic implications for the mainly fermentative LAB. We showed that L. plantarum and other diverse LAB species perform EET if riboflavin and quinones are present. L. plantarum EET activity requires an NADH dehydrogenase (Ndh2) and conditionally requires an extracellular, flavin-binding reductase (PplA). EET in L. plantarum generates a high NAD+/NADH ratio, increases fermentation yield and flux, shortens lag phase, and increases ATP production. Thus, EET in L. plantarum is a hybrid energy metabolism that contains metabolic features of fermentation, redox features of anaerobic respiration, and predominately uses substrate-level phosphorylation to conserve energy. This pathway is active in L. [SEP] Justify:

Output: The text corroborates the claim by detailing how EET (Electroactive Electron Transfer) enhances fermentation processes in L. plantarum, a lactic acid bacterium (LAB). It explains that EET impacts cellular metabolism, increases metabolic flux, and enhances the overall yield of fermentation end-products, all of which are crucial aspects of fermentation. Additionally, it notes that the presence of LAB species, like L. plantarum, is integral to the fermentation process, supporting the assertion that lactic acid bacteria are vital for fermentation.


Input: Task: contrast the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: The results for Format were notable as Format was not significant in the additive model when the Stimulus factor was present (note that a Stimulus x Format interaction could not, by definition, be included in the interactive model as there were no Faces-Recall tests to complete all cross-combinations of Stimulus x Format). We therefore considered it possible that tests with design stimuli may be disproportionately explaining the right-lateralized Recall effect. To explore these results further, contrasts with Bonferroni-correction to account for multiple comparisons (i. e. , p = 0. 05/2 = 0. 025) showed that the right-lateralization effect for Faces-Recognition was not significantly larger than for Designs-Recognition, and the right-lateralization effect for Designs-Recall was not significantly larger than for Designs-Recognition (see Fig. 3D), together suggesting that the Stimulus effect (right-lateralized Faces) and Format effect (right-lateralized Recall) were independent. Bonferroni contrasts to explore the Learning x Format effect (i. e. , p = 0. 05/3 = 0. 017) showed a right-lateralization effect of Format (Recall > Recognition) that was stronger for tests with repeated learning trials than for tests with single learning trials (d = -0. 10, p =. 004), while the Format effect was not significant within individual learning trial (i. e. , each of single and repeated learning trial types; see Fig. 3E). Figure 3C shows the results for specific moderator levels. Taken together, for presurgical patients, the small-sized performance decrement on nonverbal memory tests for RTLE versus LTLE patients was significantly moderated by both stimulus type and task-based factors (testing format on its own and interacting with learning format) of the nonverbal memory tests. Fig. 4A shows that for the additive meta-regression model, the moderators were significant as a group, QM = 20. 43, p < 0. 001, but there was only a borderline significant trend for the Stimulus effect on right-lateralization (Faces > Designs, d = -0. 25, p = 0. 052). No other moderators were significant. Figure 4B shows the moderators were collectively significant for the interactive model, QM = 20. 15, p = 0. [SEP] Justify:

Output: The text contrasts the claim by discussing how the effects of stimulus and format on recall were independent, suggesting that the interaction of stimulus and the correct format does not guarantee perfect recall. It indicates that even with specific stimuli, there are limitations to recall accuracy, as seen in the results that show significant performance decrements among different patient groups based on stimulus type and task-based factors.


Input: Task: pass the claim using the given text. Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: MathType@MTEF@5@5@+=feaafiart1ev1aaat9MDH5MBPbIqV92AaeXatLxBI9g6xNi=xI8qi9v8qqaqFr0xc9vqFj0dXdbba91qpepeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaae1aa9aqpcq1aa0baa4ka@4BAC@ (6) That is, the unitary operator is U = Q 1 Q 2 T MathType@MTEF@5@5@+=feaafiart1ev1aaat9MDH5MBPbIqV92AaeXatLxBI9g6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaae0Jaemyuae1aa@33DA@ and the shifting operator is b = − Q 1 Q 2 T X ¯ 2 + X ¯ 1 MathType@MTEF@5@5@+=feaafiart1ev1aaat9MDH5MBPbIqV92AaeXatLxBI9g6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaae0JaeyOeI0Iaemyuae1aa@3AB3@. In practice, one problem with the X1 and X2 obtained by CMDS from a distance matrix is that some of the eigenvalues of the double centered distance matrix can be negative. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses mathematical operators and problems related to eigenvalues in distance matrices, without mentioning bioinformatics, genomic data, or their relationship.


Input: Task: corroborate the claim using the given text. Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: plantarum with physiologically relevant DHNA concentrations and in a food fermentation and results in an increased metabolic flux and acidification rate. The combined EET fermentation hybrid metabolism is distinct from anaerobic respiration, fermentation, and other energy conservation strategies When performing EET, the metabolism of L. plantarum, a primarily fermentative bacterial species, is fundamentally different from EET-driven, anaerobic respiration of metal-reducing bacteria. Although aspects of EET in L. plantarum and metal-reducing Geobacter spp. are similar, such as the upregulation of NADH dehydrogenase, the reduction rate of extracellular electron acceptors, and the high NAD+/NADH ratio, other aspects of energy metabolism during EET in these two organisms are starkly different (see comparison in Supplementary file 2). Geobacter spp. direct their metabolic flux through the TCA cycle, rely almost exclusively on extracellular electron acceptors to regenerate NADH, and produce ATP exclusively through oxidative phosphorylation. In contrast, L. plantarum regenerates a substantial fraction of its NADH by directing metabolic flux through fermentative pathways. Additionally, oxidative phosphorylation is not a major mechanism of energy conservation in L. plantarum during EET, as supported by three lines of evidence: the marginal metabolic flux through the reduced branch of TCA cycle, no involvement of known PMF-generating proteins, and that increased ATP levels can be accounted for by increased substrate-level phosphorylation. While additional data are required to eliminate the possibility that oxidative phosphorylation is occurring in L. plantarum during EET, we can qualitatively state that substrate-level phosphorylation is the major mechanism for ATP generation. Comparing EET and respiratory metabolism in LAB also reveals substantial differences in these metabolisms (Supplementary file 2). While both metabolisms require quinones, respiration also requires exogenous heme. Our findings and similar findings in E. faecalis (Pankratova et al. , 2018) confirm that heme is not required for EET. Moreover, EET also differs from respiration in LAB because it occurs at the start of or prior to exponential phase growth, does not change the final cell density, and increases fermentation with no effect on the resultant proportions of lactate, acetate, and ethanol (Duwat et al. , 2001). [SEP] Justify:

Output: The text corroborates the claim by discussing the role of L. plantarum, a lactic acid bacteria species, in fermentation processes. It highlights how the metabolism of L. plantarum is primarily fermentative, where it significantly contributes to the metabolic flux and acidification rate during the fermentation process. The assertion that L. plantarum regenerates NADH through fermentative pathways and emphasizes substrate-level phosphorylation as a major mechanism for ATP generation further supports the importance of lactic acid bacteria in fermentation.


Input: Task: pass the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: 003, with a significant effect of Format (Recognition > Recall, d = -0. 38, p < 0. 001), but no other moderators were significant. Fig. 4 Standardized effect sizes (Cohen’s d) and 95% confidence intervals of lateralization (left minus right TLR performance) for postsurgical patients, by type of moderator analysis and individual moderator levels. Negative effect sizes indicate poorer performance for right than left TLR patients. Sample size (k, studies) inferential statistics, heterogeneity and fail-safe N measures are in 10. Contrasts used mean differences and t-statistic For the same reasons as described in the section above for the presurgical sample, we used Bonferroni-corrected contrasts (i. e. , p = 0. 05/2 = 0. 025) to determine whether this Format effect for the right TLR group was influenced by the borderline significant effect of Stimulus (see Fig. 4D). These showed the right-lateralization effect for Designs-Recognition was significantly larger than for Designs-Recall, while the effect size for Faces-Recognition was not significantly larger than for Designs-Recognition (see Fig. 4D). Therefore, when taken together, for postsurgical patients the lateralization effects (right < left performance) were affected by testing format (recognition > recall) that appeared to overshadow and explain the effects of stimulus type (faces > designs). For postsurgical change, the additive meta-regression model showed that for left TLR patients the moderators were significant as a group, QM = 12. 95, p = 0. 01, with a significant effect of Format (Recognition more left-lateralized than Recall, d = 0. 22, p = 0. 4), but no other moderators were significant (see Fig. 5A). The interactive model (Fig. 5B) was also significant, QM = 15. 15, p = 0. 01, again with a significant effect of Format only (Recognition more left-lateralized than Recall, d = 0. 25, p = 0. 007). Fig. [SEP] Justify:

Output: The text does not directly address the claim regarding the perfect recall of memory with the right stimulus. Instead, it discusses effects of different testing formats (recognition vs. recall) and provides statistical analysis related to performance in postsurgical patients. The information is more focused on lateralization effects and does not support or contrast with the idea of perfect memory recall.


Input: Task: pass the claim using the given text. Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: This has been mentioned in [3], where the information of both the neighborhood and afar is used for the spring model. If one puts only the neighboring points into the same group, the rotation effect will hamper the performance of the low dimensional layout (see Fig. 1d later). These two conditions are sufficient to guarantee good performance in a low dimension layout. The layout of the correct approximation solution of our method is outlined (see Fig. 1b). Figure 12D simulation results. a. The 2D CMDS projection of 2000 simulation points. b. The 2D layout of an approximate solution by SC-MDS with no dimension loss (N i = 30, N g = 200). The points in a group were chosen randomly. c. The 2D layout of the approximate solution by SC-MDS with a loss of 12 dimensions (N I = 5, N g = 200). The points in a group were chosen randomly. d. The 2D layout of the approximate solution by SC-MDS with a loss of 12 dimensions (N I = 5, N g = 200). The points in a group were chosen by the neighboring method. Full size imageReductionWe now show how SC-MDS reduces the computational complexity of CMDS from O(N3) to O(N) when p <<N. Assume that there are N points in a data set, N I is the number of points in each intersection region, and N g is the number of points in each group. [SEP] Justify:

Output: The text does not provide information relevant to the claim. It discusses the computational aspects of a spring model and low dimensional layout without mentioning bioinformatics or genomic data analysis specifically.


Input: Task: corroborate the claim using the given text. Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: Thus, EET in LAB diverges from respiration in metal-reducing bacteria or LAB in its metabolic pattern and energetic consequences. In addition, while EET provokes a shift in fermentative metabolism in other bacteria upon the addition of artificial mediators (Vassilev et al. , 2021; Emde and Schink, 1990), L. plantarum EET is active upon the presence of a mediator present in a complex food system. This EET mechanism is also a novel energy conservation strategy compared to known fermentative metabolisms in LAB (comparison in Supplementary file 2). L. plantarum and other LAB, reduce alternative intracellular electron acceptors like citrate, fructose, and phenolic acids, resulting in increased intracellular NAD+/NADH ratios (Hansen, 2018). This metabolic activity is especially important for heterofermentative LAB in order to synthesize additional ATP through acetate kinase (Gänzle, 2015). Unlike these examples, however, the reduction of extracellular Fe3+ or an anode by EET requires a respiratory protein (Ndh2) and the shuttling of electrons outside of the cell. In addition, the reduction of the oxygen and organic compounds for cofactor regeneration by LAB leads to a metabolic shift toward acetate production and altered metabolic end-product ratios (Gänzle, 2015), which does not occur during EET. These differences show how the hybrid metabolism under EET conditions is distinct from other pathways that alleviate reduced intracellular conditions in LAB. Previous studies have reported a simultaneous use of fermentation and electron transport elements, such as in respiro-fermentation in Saccharomyces cerevisiae (Blom et al. , 2000). However, respiro-fermentation produces ATP and maintains intracellular redox balance through substrate-level phosphorylation and/or oxidative phosphorylation using separate pathways. Our data strongly suggests a single pathway is responsible for both ATP generation and intracellular redox balance. This hybrid fermentation mode is also different from the electron bifurcating mechanism, in which the extra ATP generation is driven by the creation of a H+ or Na+ potential from the oxidation of a ferredoxin (Buckel and Thauer, 2013). [SEP] Justify:

Output: The text corroborates the claim by discussing the metabolic activities of lactic acid bacteria (LAB), specifically their importance in fermentation processes. It details how EET in LAB is a novel energy conservation strategy linked to fermentative metabolism, highlighting that L. plantarum and other LAB are involved in metabolic activities that are crucial for synthesizing ATP through fermentative pathways. The mention of heterofermentative LAB synthesizing additional ATP through acetate kinase emphasizes the role 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: Sample size (k, studies) inferential statistics, heterogeneity and fail-safe N measures are in 13. Contrasts used mean differences and t-statistic In summary, for postsurgical change, there was an effect of testing format in favor of improved recognition over recall for left TLR patients, and when comparing left and right TLR the lateralization effects (left > right improvement) were affected by testing format (recognition > recall) that appeared to overshadow and explain the effects of stimulus type (faces > designs). 12 For clarity we replace the entire second and third paragraph concerning the moderating effects of stimulus-related and task-related factors, and the initial section of the following paragraph, corrected version: This study revealed several novel findings. Taking all nonverbal memory tests together, patients with RTLE performed slightly worse than patients with LTLE, in both the presurgical and postsurgical patient groups, with larger differences for the postsurgical group compared to the presurgical groups. For presurgical patients, lateralization effects (right < left) were consistently small and differed by stimulus type (faces > designs) and testing format (recall > recognition), in a manner that interacted with learning type, i. e. , larger effect size change for repeated than single learning trials). For postsurgical patients, lateralization effects (right < left) also differed by format but in the opposite direction (recognition > recall), that appeared to overshadow and explain the borderline non-significant effects of stimulus type (faces > designs). Change in nonverbal memory performance following TLR showed an overall pattern of mild improvement in left TLR patients and no change in right TLR patients. In left TLR patients, the degree of improvement differed by format (recognition > recall) that appeared to overshadow and explain the borderline non-significant effects of stimulus type (faces > designs). In right TLR patients, the effect size was not significant and did not differ for any of the moderators. This advantage for recognition over recall was maintained when comparing postsurgical change for left and right TLR patients and did not appear to differ by the type of stimulus. Patient age (at the time of the assessment) had no significant effect on nonverbal memory performance in any patient sample, while patients with left TLR performed worse on nonverbal memory tests following surgery when the age of epilepsy onset was younger. [SEP] Justify:

Output: The text contrasts the claim by indicating that recognition (the ability to identify previously learned information) is favored over recall (the ability to retrieve information without cues), particularly in patients with left TLR (temporal lobe resection) where the testing format influenced results. It states that improved recognition overshadowed the effects of stimulus type and that the degree of improvement differed based on testing format, suggesting that perfect recall is not achievable merely through stimulus manipulation.


Input: Task: pass the claim using the given text. Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: When we split N points into K overlapping groups, we have KN g - (K-1)N I = N, and we have K = ( N − N I ) ( N g − N I ~ O ( N ) MathType@MTEF@5@5@+=feaafiart1ev1aaat9MDH5MBPbIqV92AaeXatLxBI9g6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaaeGaciGaaiaabeqaaeqabiWaaaGcbaGaem4saSKaeyypa0tcfa4aa40aa6eaonaa+b@410C@. For each group, we apply CMDS to compute the coordinates of the group data, which costs O ( N g 3 ) MathType@MTEF@5@5@+=feaafiart1ev1aaat9MDH5MBPbIqV92AaeXatLxBI9g6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaaeGaciGaaiaabeqaaeqabiWaaaGcbaGaem4ta8KaeiikaGIaemOta40aa0baa@3255@ computation time. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses a mathematical computation process involving overlapping groups and computation time, without mentioning bioinformatics or its significance in analyzing genomic data.


Input: Task: corroborate the claim using the given text. Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: Unlike in this example, EET in LAB does not involve PMF creating elements and EET drives ATP generation through substrate-level phosphorylation. Another poorly understood example of the use of substrate-level phosphorylation and electron transport chains to balance intracellular redox state is found in the non-fermentative bacterium S. oneidensis. Although this species is a respiratory bacterium, it relies predominately on substrate-level phosphorylation to grow anaerobically with the exogenous electron acceptor fumarate (Hunt et al. , 2010). In this scenario, it is unclear if there are changes in intracellular redox state or metabolism in this species. In contrast to and expanding upon these studies, our work elucidates a qualitatively and quantitatively different blending of fermentation and respiration. L. plantarum EET-associated metabolism contains features of both fermentation (e. g. substrate-level phosphorylation, high fermentation product yields) and respiratory metabolisms (e. g. NAD+/NADH ratios, NADH dehydrogenase required) (Supplementary file 2). Quantitatively, this hybrid metabolism leads to an overall ~1. 75x-more efficient and ~1. 75x-faster energy conservation (increased Ymannitol, mannitol flux), but an overall ~1. 5 fold weaker coupling between anabolism and catabolism (lower YATP). Additionally, the increased NAD+/NADH ratio arises from using an ~2:1 ratio of endogenous to extracellular electron acceptors. Thus, to our knowledge, the hybrid strategy that L. plantarum uses to generate ATP performing EET constitutes a novel mode of energy conservation in a primarily fermentative microorganism. Different mechanisms of EET appear to be widespread in LAB Based on our observations and others, we propose that EET is widespread in LAB and occurs by different mechanisms. Besides L. plantarum, we showed that L. lactis is able to generate current despite lacking pplA. Current generation by L. lactis was observed previously, found to be riboflavin dependent, and resulted in a small metabolic shift (yet to be defined) in which the flux through NADH-oxidizing pathways was reduced and ATP generating pathways were increased (Freguia et al. , 2009; Masuda et al. , 2010). [SEP] Justify:

Output: The text corroborates the claim by discussing the fermentation processes in lactic acid bacteria (LAB) such as L. plantarum and L. lactis. It specifically highlights the hybrid strategy used by L. plantarum in generating ATP through a blend of fermentation and respiration, emphasizing the features of fermentation, such as substrate-level phosphorylation and high fermentation product yields.


Input: Task: contrast the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: Our meta-analysis shows that the testing format moderates the capacity of nonverbal memory tests to reveal memory decline following surgery (i. e. , recognition > recall) for right TLR patients and that recognition tests better discriminate postsurgical change of left and right TLR patients. This suggests that a recognition format may more specifically test memory consolidation and storage functions linked to the medial temporal lobe than a recall format (Lowndes & Savage, 2007; Mayes et al. , 2007). In contrast, other test attributes including stimulus type, learning format and test delay did not impact the right-lateralization effect for the postsurgical change group (cf. Jones-Gotman et al. , 2000; Majdan et al. , 1996). For presurgical patients there was a more complex pattern that indicated a slight advantage of recall over recognition that depended on an interaction with learning type. The interpretation of this finding is less clear but suggests that for presurgical patients tests with particular combinations of learning and format type (e. g. , learning with repeated trials, tested via recall) may on average slightly outperform tests with other combinations. Our findings support the recommendations of the (ILAE; Wilson et al. , 2015) report regarding the use of recognition testing alongside recall measures for comparison, from the same tests where applicable. Page 13 For the fifth paragraph under the heading “Limitations and Further Research”, we changed the original version of the first sentence: Given the modest effect sizes of most tests examined and the lack of moderating effects of test-related factors on the capacity of nonverbal memory tests to indicate impairment in RTLE presurgical samples, there remains a clear and urgent need for improved tests to predict the effects of right temporal lobe pathology. To the corrected version: Given the modest effect sizes of most tests examined particularly for presurgical patients, there remains a clear and urgent need for improved tests to predict the effects of right temporal lobe pathology. For the first sentence under “Conclusion” we changed: “This comprehensive meta-analysis has shown the value of nonverbal recognition measures in detecting postsurgical change in right TLR patients. ” To the corrected version: This comprehensive meta-analysis has shown the value of nonverbal recall measures in detecting presurgical right TLE, and the value of recognition measures in detecting postsurgical performance in right TLR patients and postsurgical improvement in left TLR patients. The original 10. [SEP] Justify:

Output: The text contrasts the claim by discussing the findings of a meta-analysis that indicates the testing format affects memory performance, particularly noting that recognition tests may be more effective than recall tests for revealing memory decline. The distinction made between recognition and recall suggests that memory recall is not perfect and can vary based on the type of stimulus and testing method utilized. Furthermore, the text mentions the necessity for better tests to address memory assessment, highlighting the limitations of current methods in accurately measuring memory against surgical impacts.


Input: Task: pass the claim using the given text. Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: At each overlapping region, we apply QR factorization to compute the affine transform, which costs O ( N I 3 ) MathType@MTEF@5@5@+=feaafiart1ev1aaat9MDH5MBPbIqV92AaeXatLxBI9g6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaaeGaciGaaiaabeqaaeqabiWaaaGcbaGaem4ta8KaeiikaGIaemOta40aa0baaSqaaiabdMeajbqaaiabiodaZaaakiabcMcaPaaa@3219@ computation time. Since the lower bound of N I is p+1, we can assume that N g = αp for some constant α. Then the total computation time is about N − p ( α − 1 ) p O ( α 3 p 3 ) + N − α p ( α − 1 ) p O ( p 3 ) ~ O ( p 2 N ). MathType@MTEF@5@5@+=feaafiart1ev1aaat9MDH5MBPbIqV92AaeXatLxBI9g6xNi=xI8qi9v8qqaqFr0xc9vqFj0dXdbba91qpepeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaaeGaciGaaiaabeqaaeqabiWaaaGcbaqcfa4aa4mamdaaOGaeiykaKIaey4kaSscfa4aa6ha+jabd+eapjabc4KaeiykaKIaeiOla4caaa@5AB4@ (7) Thus, when p <<N, the computation time of the SC-MDS becomes O(p2N). [SEP] Justify:

Output: The text is largely focused on a mathematical computation related to overlapping regions and does not provide any information connecting directly to the claim. It discusses specific computation techniques without addressing the broader context of 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: L. lactis can also perform EET by reduction of tetrazolium violet and this activity depends on the presence of both quinones and an NADH dehydrogenase (NoxAB) (Tachon et al. , 2009). E. faecalis is another LAB that performs EET, and similar to L. plantarum, it requires quinones (Pankratova et al. , 2018) and a type-dehydrogenase (Ndh3) (Hederstedt et al. , 2020) for Fe3+ reduction. In contrast to this mechanistic similarity, E. faecalis performs EET using matrix-associated iron resulting in both increased final cell biomass and intracellular iron (Keogh et al. , 2018). Moreover, unlike L. plantarum and L. lactis, the presence of PplA is not necessary for anode reduction or Fe3+ reduction (Hederstedt et al. , 2020). The conditional need for PplA in EET may be explained by the different prior growth conditions used and/or related to the existence of different mechanisms and proteins depending on the redox potential of the extracellular electron acceptor. Other flavin-binding, extracellular reductases amongst Gram-positive organisms, such as FrdA (acting on fumarate) have been identified in L. monocytogenes and UrdA (acting on urocanate) in Enterococcus rivorum (Light et al. , 2019). Thus, there may exist a yet unidentified extracellular reductase in L. plantarum and L. lactis required for anode reduction. Thus, our findings elucidate a new pattern of metabolic changes associated with EET. It seems likely that these many mechanisms reflect the ability of EET to alleviate constraints of intracellular redox balance in fermentative metabolism across LAB. EET has important implications for ecology and biotechnology of LAB Conservation of the FLEET locus among different LAB species supports the premise that this hybrid fermentation with EET provides an important metabolic strategy for these bacteria in their natural habitats. LAB with a complete FLEET locus are homofermentative, thus underscoring the distinct ways homofermentative and heterofermentative LAB have evolved for energy conservation (Salvetti et al. , 2013). L. [SEP] Justify:

Output: The text corroborates the claim by discussing the metabolic processes of lactic acid bacteria (LAB), particularly emphasizing the role of extracellular electron transfer (EET) in fermentative metabolism. It notes how EET allows LAB to alleviate constraints of intracellular redox balance in their metabolic processes, highlighting the ecological and biotechnological importance of LAB in fermentation. Furthermore, it addresses how different LAB species have evolved distinct mechanisms for energy conservation, reinforcing 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: multivariate autoregressive models have failed to adequately account for the complexity of neural signals, researchers have predominantly relied on non-parametric methods when studying the relations between brain and behavior. Using medial temporal lobe (MTL) recordings from 96 neurosurgical patients, we show that time series models with volatility described by a multivariate stochastic latent-variable process and lagged interactions between signals in different brain regions provide new insights into the dynamics of brain function. The implied volatility inferred from our process positively correlates with high-frequency spectral activity, a signal that correlates with neuronal activity. We show that volatility features derived from our model can reliably decode memory states, and that this classifier performs as well as those using spectral features. Using the directional connections between brain regions during complex cognitive process provided by the model, we uncovered perirhinal-hippocampal desynchronization in the MTL regions that is associated with successful memory encoding. advances in neuroscience have enabled researchers to measure brain function with both high spatial and temporal resolution, leading to significant advances in our ability to relate complex behaviors to underlying neural signals. Because neural activity gives rise to electrical potentials, much of our knowledge concerning the neural correlates of cognition derive from the analyses of multi-electrode recordings, which yield a multivariate time series of voltage recorded at varying brain locations (denoted here as 𝐲t). Such signals may be measured non-invasively, using scalp electroencephalography (EEG), or invasively, using subdural grids or intraparenchymal depth electrodes in human neurosurgical patients. In recent years, intracranially recorded (iEEG) signals have yielded detailed information on correlations between time-series measures and a wide range of behaviors including perception, attention, learning, memory, language, problem solving and decision making (Jacobs and Kahana, 2010). Whereas other fields that grapple with complex multivariate time series have made effective use of parametric models such as economics and engineering (Kim et al. , 1998; Blanchard and Simon, 2001; West, 1996), neuroscientists largely ceded early parametric approaches (e. g. linear autoregressive models) in favor of non-parametric spectral decomposition methods, as a means of uncovering features of neural activity that may correlate with behavior. [SEP] Justify:

Output: The text contrasts the claim by discussing the complexity of neural signals and the challenges in modeling memory states. It highlights that while advances in neuroscience have provided insights into brain function and memory encoding, the notion of perfect recall is undermined by the intricacies of brain dynamics and the limitations of various modeling approaches. This suggests that memory recall is not as straightforward as the claim implies.


Input: Task: pass the claim using the given text. Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: Discretize θ into N-1 intervals and let θ i = 2π + idθ, d θ = 3 π N − 1 MathType@MTEF@5@5@+=feaafiart1ev1aaat9MDH5MBPbIqV92AaeXatLxBI9g6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaae0tcfa4aa@3633@. At each θ i k points are constructed with noise. [SEP] Justify:

Output: The text does not address the claim regarding the importance of bioinformatics for analyzing genomic data. Instead, it focuses on a mathematical aspect of discretization and noise construction, which is unrelated to bioinformatics or genomic data analysis.


Input: Task: corroborate the claim using the given text. Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: plantarum and other LAB with FLEET systems such as L. casei are genetically and metabolically diverse and grow in a variety of nutrient rich environments including dairy and plant foods and the digestive tract (Cai et al. , 2009; Martino et al. , 2016; Siezen et al. , 2010a). Those environments also are rich sources of sources of quinones, flavins, and extracellular electron acceptors such as iron (Cataldi et al. , 2003; Fenn et al. , 2017; Kim, 2017; Roughead and McCormick, 1990; Walther et al. , 2013). Increased organic acid production and environmental acidification by LAB with this hybrid metabolism would provide an effective mechanism to inhibit competing microorganisms and confer a competitive advantage for growth. The increased ATP relative to biomass generation observed during growth on mannitol might also give sufficient readiness for using this energy later on to outcompete neighboring organisms (Russell and Cook, 1995). These effects of EET may be particularly important on plant tissues and intestinal environments, wherein LAB tend to be present in low numbers. Besides our observation that L. plantarum performs EET in kale juice, the FLEET pathway is important for intestinal colonization by both L. monocytogenes (Light et al. , 2018) and E. faecalis (Lam et al. , 2019), and L. plantarum FLEET genes including ndh2 and pplA were highly induced in the small intestine of rhesus macaques (Golomb et al. , 2016). The hybrid fermentation metabolism of LAB also has technological relevance. For many LAB food fermentations, acidification of the food matrix is required to prevent the growth of undesired microorganisms and result in a more consistent and reproducible product (Marco et al. , 2021). Starter cultures are frequently selected based on their capacity for rapid growth and acid production (Bintsis, 2018). In the presence of an anode, exposure of L. plantarum to EET conditions during kale juice fermentation increased the acidification rate. Thus, this shows that EET metabolism is active in complex nutritive environments such as kale leaf tissues that contain other potential electron acceptors besides the anode and diverse electron donors (glucose, fructose, sucrose) (Thavarajah et al. , 2016). [SEP] Justify:

Output: The text corroborates the claim by detailing the role of lactic acid bacteria (LAB) in fermentation processes. It explains that LAB, such as L. plantarum, contribute to the acidification of food matrices, which is crucial for preventing the growth of undesired microorganisms. Furthermore, it mentions that the capacity for acid production is a key factor in selecting starter cultures for food fermentation, thereby underscoring the importance of LAB in these processes.


Input: Task: contrast the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: We employed a Bayesian approach to estimate the latent volatility series and the parameters of the MSV model using the forward filtering backward sampling and algorithms. We validated the MSV model in a unique dataset comprising depth-electrode recordings from 96 neurosurgical patients. These patients volunteered to participate in a verbal recall memory task while they were undergoing clinical monitoring to localize the epileptogenic foci responsible for seizure onset. Our analyses focused on the subset of electrodes (n=718) implanted in medial temporal lobe (MTL) regions, including hippocampus, parahippocampal cortex, entorhinal cortex and perirhinal cortex. We chose to focus on these regions given their prominent role in the encoding and retrieval of episodic memories (Davachi et al. , 2003; Kirwan and Stark, 2004; Kreiman et al. , 2000; Sederberg et al. , 2007). We show that the MSV model, which allows for interactions between regions, provides a substantially superior fit to MTL recordings than univariate stochastic volatility (SV) models. The implied volatility in these models positively correlates with non-parametric estimates of spectral power, especially in the gamma frequency band. We demonstrate the utility of our method for decoding cognitive states by using a penalized logistic regression classifier trained on the implied volatility data across MTL electrodes to predict which studied items will be subsequently recalled. We find that the MSV-derived features outperform spectral features in decoding cognitive states, supporting the value of this model-based time-series analysis approach to the study of human cognition. Furthermore, using the MSV model to construct a directional MTL connectivity network, we find that significant bidirectional desynchronization between the perirhinal cortex and the hippocampus predicts successful memory encoding. Volatility models for iEEG Volatility of iEEG is stochastic Previous studies have shown that variance of EEG recordings is time-varying (Wong et al. , 2006; Galka et al. , 2010). Klonowski et al. (2004) demonstrated a striking similarity between the timeseries of the index during economic recessions (big crashes) and the timeseries of iEEG during epileptic seizures. These timeseries typically possess 'big spikes' that are associated with abrupt changes in the variance of the measured signal. [SEP] Justify:

Output: The text contrasts the claim by implying limitations in perfect memory recall. It discusses a study where patients performed a verbal recall memory task, suggesting that memory encoding and retrieval are complex processes influenced by various factors, including brain regions and interactions targeted by the MSV model. It highlights that even with advanced modeling, the task is to predict recall, which implies that memory recall might not be perfect, as it depends on several cognitive and physiological factors.


Input: Task: pass the claim using the given text. Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: The following steps generate the data:Construct two raw vectors q1 and q2, q 1 i = 2 θ ⌊ i k ⌋ cos θ ⌊ i k ⌋ + n i q 2 i = 2 θ ⌊ i k ⌋ sin θ ⌊ i k ⌋ + n i MathType@MTEF@5@5@+=feaafiart1ev1aaat9MDH5MBPbIqV92AaeXatLxBI9g6xNi=xI8qi9v8qqaqFr0xc9vqFj0dXdbba91qpepeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaae0JaeGOmaiJaeqiUde3aa4la8Iaem45+4daabeaakiGbcogaJjabc+gaVjabcohaZjabeI7aXnaaBaaaleaadaGbdaqaaiabdMgaPjabc+caViabdUgaRbGaayj84laawUp+aaqaba0JaeGOmaiJaeqiUde3aa4la8Iaem45+4daabeaakiGbcohaZjabcMgaPjabc6gaUjabeI7aXnaaBaaaleaadaGbdaqaaiabdMgaPjabc+caViabdUgaRbGaayj84laawUp+aaqaba@760C@ where n i is a random variable with normal distribution n i ~ N(0,1), for i = 1⋯kN. Then we add some p-2 dimensional randomness into the coordinate matrix as follows. = ⟨α j ui,j⟩, ui,j~ N(0,1), for i = 1⋯kN and j = 1⋯p - 2, where α j is the parameter to control the standard deviation of random variables. The final reference coordinates matrix X isX = [q1, q2, Z]T= [x1, x2,. . . [SEP] Justify:

Output: The text provides a detailed mathematical description related to data generation and does not mention bioinformatics or its role in 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: This example also shows how electro-fermentation, the technological process by which fermentation is modulated using electrodes, can be used to control food fermentations (Moscoviz et al. , 2016; Schievano et al. , 2016; Vassilev et al. , 2021). Because L. plantarum also increased fermentation flux when the electrode was available as an electron sink, higher quantities of organic acid flavor compounds were formed. Therefore, by the manipulation of extracellular redox potential, food electro-fermentations may be used to control microbial growth. This would allow the creation of new or altered sensory profiles in fermented foods, such as through altered organic acid production and metabolism or synthesis of other compounds that alter food flavors, aromas, and textures. Final perspective We expect that our study will improve the current understanding of energy conservation in primarily fermentative microorganisms and contribute to establishing the ecological relevance of EET in lactic acid bacteria. This work will ultimately allow the use of EET to electronically modulate the flavor and textural profiles of fermented foods and expand the use of lactic acid bacteria in bioelectronics, biomedicine, and bioenergy (Moscoviz et al. , 2016). The identification of the precise components and full bioenergetics involved in L. plantarum EET will be key to unravel physiological and ecological questions and to develop other biotechnological applications. Materials and methods Key resources table Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional informationStrain, strain background (Lactiplantibacillus plantarum)NCIMB8826Dandekar, 2019 Strain information listed in Supplementary file 3Strain, strain background (Lactiplantibacillus plantarum)NCIMB8826-RYin et al. [SEP] Justify:

Output: The text corroborates the claim by discussing the role of Lactiplantibacillus plantarum, a lactic acid bacterium, in enhancing fermentation processes. It highlights that L. plantarum increased fermentation flux and the production of organic acid flavor compounds, indicating its importance in controlling food fermentations and contributing to the sensory profiles of fermented foods. Additionally, the text mentions the application of lactic acid bacteria in bioelectronics, biomedicine, and bioenergy, further supporting their relevance in fermentation.


Input: Task: contrast the claim using the given text. Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: Since spectral powers of neighboring frequencies exhibit high correlations, we utilized a Gaussian regression model (Rasmussen, 2004) to estimate the correlation between volatility and spectral power as a function of frequency, which allows for a non-linear relation. Figure 3 indicates that the correlation between volatility and spectral power is significantly positive across the spectrum and increasing in frequency. This illustrates the broadband nature of the volatility measure, but also suggests that volatility may more closely relate to previous neuroscientific findings observed for high-frequency as compared with low-frequency activity. Having established that the MSV model outperforms the more traditional SV approach, and having shown that the implied volatility of the series reliably correlates with high-frequency neural activity, we next asked whether we can use the model-derived time series of volatility to predict subjects’ behavior in a memory task. Figure 3 Download asset Open asset Correlation between volatility and spectral power over a frequency range from 3 to 180 Hz. We fit a Gaussian process model to estimate the functional form of the correlation function between volatility and spectral power (solid blue line). The 95% confidence bands were constructed from 96 subjects (dashed gray lines). The red line shows the null model. We observe a significantly positive correlation between volatility and spectral power, and the correlation increases with frequency. Classification of subsequent memory recall Extensive previous work on the electrophysiological correlates of memory encoding has shown that spectral power, in both the low-frequency (4–8 Hz) theta band and at frequencies about 40 Hz (so-called gamma activity), reliably predicts which studied words will be subsequently recalled or recognized (Sederberg et al. , 2003). Here, we ask whether the implied volatility derived from the MSV model during word encoding can also reliably predict subsequent recall. To benchmark our MSV findings, we conducted parallel analyses of wavelet-derived spectral power at frequencies ranging between 3 and 180 Hz. To aggregate across MTL electrodes within each subject we applied an L2-penalized logistic regression classifier using features extracted during the encoding period to predict subsequent memory performance (Ezzyat et al. , 2017; Ezzyat et al. , 2018). To estimate the generalization of the classifier, we utilized a nested cross-validation procedure in which we trained the model on N-1 sessions using the optimal penalty parameter selected via another inner cross-validation procedure on the same training data (see 0. [SEP] Justify:

Output: The text contrasts the claim by discussing the limitations of recalling memory, specifically highlighting that while certain factors (like spectral power) can predict memory recall, it does not imply that memory recall can be perfected or guaranteed with the right stimulus. The mention of predicting 'subsequent recall' suggests variability in recall success rather than perfection.


Input: Task: pass the claim using the given text. Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: ,x kN ],where x i ∈ Rp. So the distance matrix is D = ⟨di, j⟩ with di,j= ||x i - x j ||. In this simulation, p = 17 is used. Fig. 1a is the 2D projection obtained by applying CMDS to 2000 simulation points. Then, in the first application of SC-MDS, we set the number of points in each group to N g = 200 and the number of points in each intersection region to N I = 30 such that the number of the overlapping points is greater than the real dimension 17. All points in each group are chosen randomly. In order to measure the difference between classical MDS and SC-MDS, we use the (Kruskal's goodness of fit index) to compute the error between the distance matrixes. [SEP] Justify:

Output: The text does not address the role of bioinformatics in analyzing genomic data. Instead, it discusses a mathematical simulation related to distance matrices and the application of techniques such as CMDS and SC-MDS. Therefore, it is irrelevant to the claim that bioinformatics is crucial for genomic analysis.


Input: Task: corroborate the claim using the given text. Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: in through your institution issuesearch term Advance 10. 1093/femsre/fuaa014 Published: 18 May 2020 10. 1093/femsre/fuaa014 Select format. ris (Mendeley, Papers, Zotero). enw (EndNote). bibtex (BibTex). txt (Medlars, RefWorks) Download citation issuesearch term issuesearch term cocoa beans are obtained through a post-harvest, batchwise process of fermentation and drying carried out on farms in the equatorial zone. Fermentation of cocoa pulp-bean mass is performed mainly in heaps or boxes. It is made possible by a succession of yeast, lactic acid bacteria (LAB) and acetic acid bacteria (AAB) activities. Yeasts ferment the glucose of the cocoa pulp into ethanol, perform pectinolysis and produce flavour compounds, such as (higher) alcohols, aldehydes, organic acids and esters. LAB ferment the glucose, fructose and citric acid of the cocoa pulp into lactic acid, acetic acid, mannitol and pyruvate, generate a microbiologically stable fermentation environment, provide lactate as carbon source for the indispensable growth of AAB, and contribute to the cocoa and chocolate flavours by the production of sugar alcohols, organic acids, (higher) alcohols and aldehydes. AAB oxidize the ethanol into acetic acid, which penetrates into the bean cotyledons to prevent seed germination. Destruction of the subcellular seed structure in turn initiates enzymatic and non-enzymatic conversions inside the cocoa beans, which provides the necessary colour and flavour precursor molecules (hydrophilic peptides, hydrophobic amino acids and reducing sugars) for later roasting of the cured cocoa beans, the first step of the chocolate-making. acetic acid bacteria, chocolate, cocoa fermentation, flavour, lactic acid bacteria, yeasts of perishable raw materials originating from plant agriculture and animal husbandry is an ancient biotechnological process that is practiced to produce stable and safe fermented food products of high microbiological, organoleptic, nutritional and health-beneficial quality (Leroy and 2004; Bourdichon et al. 2012; Wolfe and Dutton 2015; Tamang, Watanabe and Holzapfel 2016; Marco et al. 2017; Rezac et al. 2018). [SEP] Justify:

Output: The text corroborates the claim by describing the role of lactic acid bacteria (LAB) in the fermentation of cocoa pulp. It explains how LAB ferment glucose, fructose, and citric acid into lactic acid and other compounds, generating a microbiologically stable fermentation environment and contributing to the flavors of cocoa and chocolate. This demonstrates the significance of LAB 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: 53 (95% CI, from 0. 51 to 0. 55). AUCs reliably exceeded chance levels in 72 percent of subjects (30 out of 42 subjects who contributed at least 3 sessions of data). Figure 4 compares these findings against results obtained using wavelet-derived power. Here we see that implied volatility does as well as, or better than, spectral measures at nearly all frequencies. In order to capture the correlation between spectral powers (thus their corresponding classifiers’ performances), we fit a Gaussian regression model to test the functional form of ΔAUC. We find that the ΔAUC function is significantly different from the 0 function (χ112=42, P < 10-5) (Benavoli and Mangili, 2015), which indicates that on average volatility performs significantly better than spectral power in predicting subsequent memory recall. Figure 4 Download asset Open asset Classification of subsequent memory recall. (A) Average AUC of the classifier trained on spectral power across 42 subjects with at least three sessions of recording (blue). The red line indicates the average AUC of the classifier trained on volatility. (B) ΔAUC = AUCvol−AUCpower as a function of frequency estimated by using a Gaussian regression model (dashed gray lines indicate 95% confidence bands). The red line shows the null model. We observe that the classifier trained on volatility performs at least as well as the one trained on spectral power across the frequency spectrum. We find that functional form of ΔAUC is significantly different from the function (χ112=42, P < 10-5) using a Gaussian process model, suggesting that the difference in performance between the volatility classifier and the spectral power classifier is significant. Directional connectivity analysis Having established that volatility is predictive of subsequent memory recall, we now seek to identify directional connections between MTL subregions that are related to successful memory encoding. To investigate the intra-MTL directional connectivity patterns that correlate with successful memory encoding, we utilize a subsequent memory effect (SME) paradigm in which we compare the MTL directional connectivity patterns (regression coefficient matrix 𝜷) associated with recalled (R) word items to those associated with non-recalled (NR) items. [SEP] Justify:

Output: The text contrasts the claim by indicating that while volatility may be predictive of subsequent memory recall, it does not support the notion of perfect recall with the right stimulus. The findings emphasize variability in memory retrieval, suggesting that memory recall is influenced by multiple factors, rather than being perfectly retrievable through specific stimuli.


Input: Task: pass the claim using the given text. Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: The formula of is = ∑ i j ( d i j − d ˜ i j ) 2 ∑ i j d i j 2 MathType@MTEF@5@5@+=feaafiart1ev1aaat9MDH5MBPbIqV92AaeXatLxBI9g6xNi=xI8qi9v8qqaqFr0xc9vqFj0dXdbba91qpepeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaaeGaciGaaiaabeqaaeqabiWaaaGcbaGaem4uamLaemivaqLaemOuaiLaemyrauKaem4uamLaem4uamLaeyypa0tcfa4aaOaaaeaadaWcaaqaamaaqafabaGaeiikaGIaemizaq2aa5aaqaamaaqafabaGaemizaq2aa0baaeaacq@54CE@ where di,jrefers to the distance matrix of the original data and d ˜ i j MathType@MTEF@5@5@+=feaafiart1ev1aaat9MDH5MBPbIqV92AaeXatLxBI9g6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaae@30F9@ refers to that for the SC-MDS reconstruction. In this spiral example, the of computing errors for SC-MDS is only 3. 93 × 10-14, and the for CMDS is only 1. 25 × 10-15. These errors are here considered as rounding errors. Thus, SC-MDS can reconstruct the configuration as does CMDS; the result of our method (Fig 1b) is similar to the 2D projection in Fig. 1a. [SEP] Justify:

Output: The text does not directly address the claim about the importance of bioinformatics in analyzing genomic data. Instead, it discusses a specific mathematical formula related to distance matrices and SC-MDS reconstruction without mentioning bioinformatics or its relevance to genomic data analysis.