Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: When the data fit the model well, the term of log-likelihood becomes larger. We assume that the standard deviations of the multivariate normal distributions are the same, so that there are (k+1)p parameters, k means, and one standard deviation in the p dimensional space, in these k clusters (models). If a model becomes complicated, i. e. , the number of the model parameters becomes large, the BIC score will decay. In Fig. 8, the dash line is reduced by taking the average of 30 repeats and the solid line is reduced by taking the maximal value of 30 repeats. We can see that the maximal value of solid line occurs in 45 clusters and the maximal of the dash line occurs in 61 clusters. Hence, we partition 5006 genes into 61 clusters in our example. Figure 8The curve of BIC Scores vs. number of clusters in K-means. The solid line denotes the max of 30 repeats of the BIC score. The dash line denotes the average of 30 repeats of the BIC score. The maximal value of the average curve occurs at 61 clusters. After 61 clusters the average curve starts decaying. Full size imageWe cluster the original data set and the reduced 7-dimensional space data set from SC-MDS separately, and each data set gives rise to 61 distinct gene clusters. Then we input gene names from these clusters to the. The outputs indicate that 13 clusters of the original clustering data set are significant to the cell cycle (p-value is smaller than 10-3). In contrast, 14 clusters of the 7-dimensional data set are significant to the cell cycle function. Twenty pairs of almost matched clusters, which consist of highly similar genes, are found by comparing the clusters from the two data sets. Nine clusters of the 7-dimensional data set are not annotated to any function, while 13 clusters of the original clustering data set are not annotated. The details of these paired clusters are shown in Additional file 1 and file 2. There are many unpaired clusters, which contain lower proportions (the match rate < 80%) of similar genes. In Figs. 9 to 11, we show these lower matched pairs that are related to cell cycle. In Figs. 9 and 10 the biological validation shows that these clusters obtained from SC-MDS are better than the corresponding clusters from the original 23-dimensional space data. In Fig. 9(a), 45.

Output: pass


Input: Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: The yeasts preferentially grow on the available glucose, fermenting it to pyruvate through glycolysis for ATP and reducing equivalent production and further producing ethanol and carbon dioxide (which maintains the anaerobic conditions) for redox balancing (Fig. 2). Alternatively, the LAB species that first grow in the cocoa pulp-bean mass and do not require oxygen for growth prefer to consume fructose and perform citric acid conversion (Fig. 2). Fructose is metabolized either homofermentatively (glycolysis) or heterofermentatively (phosphoketolase pathway) to pyruvate, while citric acid is converted into acetic acid and oxaloacetic acid. The latter is further converted into pyruvate as well, which will finally yield either lactic acid, acetic acid, or pyruvate metabolites, in particular 2,3-butanedione (diacetyl; buttery notes), 3-hydroxy-2-butanone (acetoin; buttery notes) and 2,3-butanediol (Gänzle 2015; von Wright and Axelsson 2019). The conversion of citric acid into lactic acid and acetic acid causes an increase of the pH from 3. 0 to 4. 0, because of the higher pKa values of the latter organic acids compared to citric acid. This low pH course contributes to the maintenance of a microbiologically stable environment, which is dominated by dedicated acid-tolerant yeast and LAB species. The growth of LAB may even be favoured by the carbon dioxide production by the yeasts and, later on, by the release of vitamins and other nutrients from yeast cells that autolyze upon fermentation (Agyirifo et al. 2019). It is assumed that yeasts do not contribute to citric acid conversion during cocoa fermentation, as citric acid metabolism by yeasts is aerobic (and Weckx 2016b). Nonetheless, citric acid assimilation can sometimes be shown in vitro for yeast isolates from fermenting cocoa pulp-bean mass (Jespersen et al. 2005; Daniel et al. 2009; Ho, Zhao and Fleet 2014; Samagaci et al. 2016).

Output: corroborate


Input: Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: Here, we asked if neurons in the lateral intraparietal area (LIP), an area with visual, oculomotor, and mnemonic connections that serves as a priority map of the environment (Bisley and Goldberg, 2010), also exhibits an environmental memory signal. Indeed, we found that neurons in LIP did convey an environmental memory signal. Further, we found that the memory signal could be established even when the probe stimulus never appeared in the receptive field of the neuron, and occurred despite the fact that the monkey made a different saccade to bring the spatial location of the vanished probe stimulus into the receptive field. These results suggest that LIP has access to a representation of the visual world in at least supraretinal coordinates. Because saccades and reaching movements are coded in the parietal cortex in retinotopic coordinates (Duhamel et al. , 1992; Andersen et al. , 1998), these results suggest that one role of LIP is to transform a supraretinal representation of the remembered environment into a retinotopic representation more useful for the generation of action. We recorded the activity of 131 neurons in three monkeys: 79 in Monkey A, 15 in Monkey B, and 37 in Monkey C. Because we had only a small number of cells in each monkey and the results from and C were comparable, these two data sets were combined for several analyses. All neurons in our sample had visual responses to the onset of a saccade target in their receptive fields, and exhibited delay-period and/or presaccadic activity in a memory-guided delayed saccade task. Furthermore, we only studied the memory-related activity of neurons whose postsaccadic responses were not contaminated by the phasic and tonic components of an eye position signal often found in parietal neurons (Andersen et al. , 1998). All neurons were situated in the lateral bank of the intraparietal sulcus, as determined by structural MRI (Figure 1). Figure 1 Download asset Open asset Location of LIP recordings. (A) A tungsten microelectrode (250 µm thick, straight shadow) located in the target area based on known LIP activity and the commonly used atlas-defined coordinates (Paxinos et al. , 1999; Saleem and Logothetis, 2012) within the given coronal slice of the brain. This electrode location was at −2 AP and +10 ML.

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: One-hot encoding refers to denoting a given nucleotide at a site with a 1 and the rest of the nucleotides as zeros. Many of these algorithms are deep learning methods that are based on neural networks with many layers that attempt to understand the underlying variation in sequence data and predict phenotypes (11). In our system, we represent monomers not with individual numbers or sets of words (kmers), but with vectors. This is similar to one-hot encoding of nucleotides, in which a nucleotide is represented as an array to be used in computational genomics or ML methods. In our approach, however, the array is treated mathematically as a vector (a tensor of rank one). Note that a vector here represents a single site, not a sequence; a pair of sites is captured with a tensor of rank 2 (a matrix). These vectors and matrices can then be incorporated into mathematical functions, such as polynomials. In contrast to computational approaches, denoting nucleotides as mathematical objects in this way allows us to do formal mathematics with sequence information. For example, the mean vector at a site gives the distribution of nucleotides at that site, same as what a sequence logo plot gives, and the mean outer product of two sites gives us a matrix that is the covariance matrix (see ‘Materials and Methods’ section). After denoting each site in a sequence as a vector (instead of the entire sequence being a vector), we then build orthogonal polynomials based on these vectors and project the phenotypes onto the polynomial space. This reveals not only first order interactions between parts of sequences but also quantifies higher order effects of having particular nucleotides at given sites. Thus, doing purely mathematical analyses with this representation of nucleotides yields biologically meaningful results. Note that both the ML and the mathematical approaches share the common fundamental step of one-hot encoding the nucleotides but this is in contrast to kmer methods which denote sets of nucleotides as words of length k. In the case of RNA sequence analysis, secondary structure prediction is an active area of development. For example, predicting pseudoknots without constraints is impossible and is an NP-complete problem (12).

Output: pass


Input: Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: 2009; Pereira et al. 2012; Crafack et al. 2013; Maura et al. 2016; Samagaci et al. 2016; Visintin et al. 2016). Another factor that may determine the abundance of certain yeast species is killer toxin production, i. e. the production of oligopeptides that inhibit the growth of other yeasts that do not show killer activity, albeit in a temperature-dependent manner (Samagaci et al. 2014, 2016; Meersman et al. 2015; Romanens et al. 2019; Ruggirello et al. 2019). From the above it can be concluded that yeasts, being represented by several species, have a determining impact on the efficiency and outcome of the cocoa fermentation process, either directly or indirectly. LAB Once the yeast counts start to decline, because of less favourable environmental conditions (less glucose, less anaerobic conditions, a slightly higher pH and an increasing temperature) and an increasing competitiveness for growth with the LAB, the latter microbial group further proliferates thanks to the appropriate growth conditions arising after 24–72 h of fermentation (Schwan and Wheals 2004; and Weckx 2016a,b; Figueroa-Hernández et al. 2019; Muñoz et al. 2019). At the start of the cocoa fermentation process, the prevailing fructophilic LAB species use fructose as energy source, with or without citric acid conversion, thereby avoiding too much competition from the yeasts. After the prevailing yeast phase, mainly heterofermentative LAB species grow, which ferment glucose to lactic acid, acetic acid, ethanol, carbon dioxide and/or mannitol (Fig. 2; Ardhana and Fleet 2003; Camu et al. 2007, 2008a; Gálvez et al. 2007; Nielsen et al. 2007a; Kostinek et al. 2008; Lefeber et al. 2010, 2011,a, 2012; Papalexandratou et al. 2011a,b,c, 2013, 2019; Pereira et al. 2012, 2013a; Adler et al. 2013; Crafack et al. 2013; Meersman et al. 2013; Moreira et al. 2013, 2016; Pereira, Magalhães-Guedes and Schwan 2013b; Ouattara et al.

Output: corroborate


Input: Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: Task 1: Basic memory task We studied 72 LIP neurons using a task based on that used to demonstrate environmental memory in the frontal eye field (Umeno and Goldberg, 2001) (Figure 2). After determining the spatial tuning properties of the neuron being recorded, the monkey performed the basic memory task which is comprised of four blocks. We customized the arrangement of the stimuli (fixation point, saccade target, and probe stimulus) according to the spatial properties of each neuron’s receptive field. In the first block, we asked the monkey to perform 20 visually guided saccade trials in which no probe stimuli appeared on the screen (Figure 2, Block 1). In these trials, no stimulus, including the saccade target, encroached on the receptive field of the neuron. Next, we asked the monkey to perform a block of 30 visually guided saccade trials in which a task-irrelevant probe stimulus appeared at a location that would be brought into the receptive field by the required saccade (i. e. the future receptive field of the neuron) (Figure 2, Block 2). Then, we pseudorandomly interleaved trials in which the probe stimulus appeared on the screen with those in which no probe stimulus appeared (Figure 2, Block 3). Finally, we presented the monkey with a block of 100 trials in which, again, the probe stimulus never appeared (Figure 2, Block 4). Figure 2 Download asset Open asset The basic memory task. The different trials types were performed in blocks. 1 (baseline), the monkey made a visually guided saccade to a point outside the neuron’s response field, to show that the saccade itself does not evoke neural activity. In the cartoon, the fixation point is a white square, the saccade target a red square, the presaccadic spatial location of the receptive field a white circle, the postsaccadic receptive field a magenta circle. The presentation times of the fixation point, saccade target and, when appropriate, probe stimuli are shown in the traces below. 2 (visual max), the monkey made the same saccade, but now the saccade brought the probe stimulus into the receptive field. If the monkey made a saccade to the probe stimulus, the trial was terminated. 3 (form and recall memory), for half of the trials, the probe stimulus appeared on the screen and was brought into the RF by the saccade.

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: RNAs are extremely versatile molecules and play important regulatory roles in gene expression by affecting transcription and translation through various different mechanisms, including intermolecular (trans) and intramolecular (cis) interactions (13). Of particular importance is the ability of RNA to control transcription initiation or termination through secondary structure formation of hairpins and loops (14). In recent years, much work has been done to understand the role of sequence composition in the regulatory potential of RNAs by not only studying the ones that occur naturally in bacterial systems but also synthetically constructing these regulators de novo (15,16). This presents a unique opportunity to employ novel mathematical tools to quantify the sequence–function relationship between RNAs and their resulting regulatory activity in both synthetic and natural systems. In general, given sequence information and corresponding phenotype data, one important objective is to quantify exactly how the underlying sequence, whether or protein, gives rise to variation in phenotype. We use the term ‘phenotype’ broadly, to refer to any measurable biological trait that is (potentially) influenced by one or more sequences. This could include whole organism properties as well as molecular traits, such as the rate of expression of a gene product (as in (17)) or binding propensity of a transcription factor. Though we will use molecular traits as examples — since there is more data available relating these to sequence variation — the methods that we present could be applied in exactly the same way to whole organism traits such as morphology or expression of a disease. In the case of RNA regulators, one measurable phenotype is the regulatory activity of an RNA as captured experimentally through the use of fluorescent reporters (18). We have applied this method to a case of regulatory RNAs called (STARs) that were synthetically constructed and whose regulatory activity was quantified experimentally by monitoring levels of green fluorescent protein expression (Figure 1, (19)). Our methods showcase important characteristics about the sequence composition of these synthetic RNAs and the corresponding target RNAs that they bind to. When analyzing just the variation in the given sequences, covariation patterns emerge that indicate interactions between the two ends of the STAR linear region. However, somewhat surprisingly, this pattern does not emerge when the phenotype values (fluorescence indicating transcription termination activity) are projected onto the sequence space. When looking at second order effects and projecting the phenotype onto pairs of nucleotides, we find a few notable interactions spread out along the sequence indicating potential intramolecular binding.

Output: pass


Input: Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: Although lactic acid itself may not play the same role as acetic acid in modulating bean pH, peptides and flavanols, the effects of citric acid conversion in the pulp (avoiding citric acid transfer into the beans) and reduction of fructose to mannitol (possibly diffusing into the beans) can result into other processes that contribute to the cocoa flavour than those caused by acetic acid. This refers in particular to the conversion of amino acids in the pulp (contributing to cocoa flavour production as yeasts do) and the provision of a sweet and cool taste due to mannitol accumulation (Lefeber et al. 2010, 2011b; and Weckx 2016a,b; John et al. 2020). As is the case for acetic acid, lactic acid may display a flavanol-protective effect, i. e. reducing polyphenol degradation (Evina et al. 2016; John et al. 2019). Desirable volatile organic compounds contributing to the cocoa flavour produced by LAB encompass pyruvate metabolites (diacetyl and acetoin; buttery/creamy notes) and amino acid conversion metabolites, such as the aldehydes 2-methylbutanal and 3-methylbutanal (malty and chocolate notes) produced from isoleucine and leucine, respectively, as well as benzaldehyde (almond and bitter notes) produced from phenylalanine (see below). The exhaustion of the energy sources glucose and fructose, a continuous increase of the ethanol, lactic acid and acetic acid concentrations, and a rise in temperature of the fermenting cocoa pulp-bean mass eventually cause a decline of the LAB counts and a further decline of the yeast counts (Schwan and Wheals 2004; and Weckx 2016b). The LAB species diversity recovered from fermenting cocoa pulp-bean mass is rather restricted. Fructophilic species that occur in the early stages of the cocoa fermentation process encompass Fructobacillus pseudoficulneus, Fructobacillus tropeaoli and Leuconostoc pseudomesenteroides, as well as Lactobacillus plantarum, the latter species being reclassified as Lactiplantibacillus plantarum (Ardhana and Fleet 2003; Camu et al. 2007, 2008a; Gálvez et al.

Output: pass


Input: Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: These trials were pseudorandomly intermixed with trials in which no probe stimulus appeared and the monkey made the same saccade. In block 4 (forget), the monkey made the same saccade but, as in Block 1, the probe stimulus never appeared. 22/49 of neurons in (45%), and 11/23 (48%) exhibited environmental memory in the basic task: There was a significant difference (p < 0. 05 by Wilcoxon rank sum) in the post saccadic response in Block 1 and the probe stimulus-absent trials in Block 3 (Figure 3 for single cell and Figure 4 for the population of all cells (p<0. 001 Wilcoxon signed ran), black traces and raster symbols versus magenta traces and raster symbols). There was no significant post-saccadic response in Block 1 (Figure 3, for a single cell and Figure 4 for the population of all cells black traces and raster symbols). There was a response to the probe stimulus in Block 2 when the saccade brought the probe stimulus into the receptive field (Figure 3, for a single cell and Figure 4 for the population of all cells green traces and raster symbols). Neurons responded similarly in Block 3 as they did in Block 2 on the half of trials in which the probe stimulus appeared in the future receptive field (Figure 3 for a single cell and Figure 4 for the population of all cells, red traces and raster symbols). However, on the interleaved half of the trials in Block 3 in which a probe stimulus did not appear, the cells responded when the monkey made a saccade bringing the vanished probe location into the receptive field (Figure 3 for a single cell and Figure 4 for the population of memory cells, magenta traces and raster symbols). This response, which occurred after the saccade brought the spatial location of the probe stimulus into the receptive field even though no probe appeared on that trial, is the environmental memory response. Finally, after a block of forgetting trials in which the probe stimulus never appeared (Block 4 trials, identical to Block 1 trials for a single cell), the environmental memory response waned and, in some cases, disappeared entirely.

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: By showing proof of concept of this method applied to these synthetic RNAs, we demonstrate its ability to capture nucleotide (or amino acids in the case of proteins) interactions across sequences and quantify sequence–phenotype interactions can be leveraged when applied to other biological systems. Figure 1. STAR and Target RNA mechanism. (A) illustrates the case in which a target DNA sequence is transcribed into an intrinsic terminator hairpin which displaces the polymerase, preventing transcription of the downstream gene. (B) shows that when STAR binds to the target RNA, the terminator hairpin is prevented from forming and transcription of the downstream gene continues. The purple region in the target RNA indicates the terminator helix which is disrupted upon binding of STAR. The 40 nt linear region in both the target RNA and STAR is depicted with a black line. This was the sequence that was varied while the terminator hairpin sequence remained the same across all 99 variants. Figure adapted from (19). Open in new tabDownload slideThe case of is particularly interesting to study at the sequence level due to the impact that both intra- and intermolecular interactions may have on the function of this type of RNA. Our method described herein enables prediction of nucleotide sequence covariation both positively and negatively impacting the function of this RNA-based regulator. These findings have the potential to uncover critical intra- and intermolecular interactions within the regulatory system. The impact of nucleotide covariation on both intra- and intermolecular interactions is highlighted in the examples from Figure 2 depicting the ability of different hairpin sequences to potentially form an intermolecular interaction with an unchanging target sequence. In the scenario shown in Figure 2A, a favorable intramolecular interaction forming a strong hairpin is likely to prevent the formation of the less favorable intermolecular interaction. In the scenario shown in Figure 2B, a slight sequence change in the hairpin RNA has shifted the balance to a far more favorable intermolecular interaction likely to outperform the relatively weak intramolecular interaction. Interestingly, a covariation on the other end of the potential hairpin restores a favorable intramolecular interaction without impacting the theoretical strength of the intermolecular interaction (Figure 2C). Despite the theoretical strength of the intermolecular interaction depicted in Figure 2C, the competing intramolecular structure is likely to impair full intermolecular function.

Output: pass


Input: Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: The fructophilic LAB species use fructose as energy source and ferment it to lactic acid with or without citric acid as co-substrate. The use of the glycolysis as main carbon flux by strains of Lacp. plantarum may explain the low competitiveness of this LAB species upon further fermentation, despite their tolerance toward acidity and ethanol, as opposed to heterofermentation that can lead to extra ATP generation as mentioned above (Lefeber et al. 2010; Adler et al. 2013; Illeghems, and Weckx 2015a). The prevalence of strictly heterofermentative Liml. fermentum strains can be ascribed to their conversion of citric acid, production of mannitol and tolerance toward acidity, ethanol and heat (Lefeber et al. 2010, 2011b; Adler et al. 2013; Illeghems, and Weckx 2015a). However, distinction can be made between heterolactic Liml. fermentum strains that consume glucose as energy source, fructose as alternative external electron acceptor and citric acid as co-substrate, to maintain their redox balance and to increase their intracellular pH and ATP generation for competitiveness, and strains that consume fructose as energy source and citrate as co-substrate, to increase their citrate flux toward lactic acid to produce enough ATP under glucose-limiting conditions (Adler et al. 2013). In the beginning of the cocoa fermentation process, also species belonging to the genera Enterococcus and Weissella may occur (Camu et al. 2007,2008a; et al. 2008, 2010; Snauwaert et al. 2013; Bortolini et al. 2016; Papalexandratou et al. 2019), whereas sometimes other species of the Lactobacillaceae (encompassing lactobacilli, Lactobacillus-related genera and pediococci) are found during the main LAB fermentation phase (Nielsen et al. 2007b; Kostinek et al. 2008; et al. 2009; Illeghems et al. 2012; Moreira et al. 2013; Papalexandratou et al. 2013, 2019; Ramos et al. 2014; Ho, Zhao and Fleet 2015; Batista et al. 2016; Menezes et al.

Output: corroborate


Input: Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: The peristimulus time histogram (PSTH) figures do not include an average forgetting trace because the wide variation of forgetting traces made such an average uninformative Figure 3 Download asset Open asset Single-cell responses in the basic memory task: from (left panel) and and C (right panel). Neural activity aligned to the beginning of the saccade. Shaded regions in the peristimulus time histograms (PSTHs) are standard errors of means calculated using all the trials in the given block. Black traces and raster dots: activity in Block 1, stimulus absent. Green traces and raster dots: activity in Block 2, 100% stimulus present. Red (broken) traces and raster dots: activity in stimulus-present trials in Block 3. Magenta traces and raster dots: activity in probe stimulus-absent trials in Block 3. Here, there is a brisk response that shows the expected latency advance evoked by predictive remapping (Duhamel et al. , 1992). Note that the latency of the memory response is nearly 100 ms longer after the saccade than the predictive response. The memory decays after many (up to 100) trials. H and V are horizontal and vertical eye movements smoothed using a 10 ms sliding causal filter. Figure 4 Download asset Open asset Population responses in the basic memory task: from (left panel) and and C (right panel). Block descriptions are as in Figure 3. Both populations of neurons, including the statistically significant and the statistically non-significant neurons showed statistically significant memory responses (Figure 5a). The population showed a significant environmental memory response comparing the responses in Block one and the memory trials of Block 3 (Monkey A, p=0. 0002 by Wilcoxon signed rank). and C (p=0. 0003, Wilcoxon signed rank). (Figure 5a, in blue and and C in red, significant cells filled symbols). The environmental memory response was weaker than the visual response evoked when the monkey made a saccade that brought the stimulus into the receptive field (Figure 5b, p<0. 001 by rank). The latency of the environmental memory response was greater than the visual response evoked when a saccade brought the stimulus into the receptive field (Figure 5c) (Wilcoxon signed rank p=0. 02 for and B, and 0.

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: For instance, when doing just first order analysis for the 40 site STAR sequences, the runtime is efficient but doing second order on all 40 sites is not computationally feasible. One can, however, do second order on sections of the sequence (e. g. 10-site regions) or two sites at a time which is what we have done in this work. The analysis for this paper, along with data and files that generate the figures, has been uploaded to this Github project page. Application to STARs (small transcription activating RNAs) We applied our methods to the case of a synthetic RNA regulator designed by (19) known as STARs. In this system, a target DNA sequence, containing the necessary information for termination, is placed upstream of a gene. When transcribed, this sequence turns into an intrinsic terminator with a linear region and a hairpin structure. Upon formation of this structure, the polymerase gets knocked off, preventing the transcription of the downstream gene (Figure 1A, (19,20)). This is known as the ‘OFF state’. In the ‘ON state’, a STAR is constructed such that upon binding to the target RNA, terminator hairpin formation is prevented and the polymerase continues transcription of the downstream gene (Figure 1B). In this system, it was determined that the linear region of the STAR binding to the corresponding part on the target RNA was critical to the activation of the downstream gene. To establish this, linear regions of 100 STAR:target RNA variants were constructed de novo using a software package known as (21). In this construction, only the linear recognition region was varied while the terminator hairpin remained the same for all variants. This linear region was 40 nt long, as determined experimentally, and it was hypothesized that variation in this part of the sequence would give rise to distinct OFF and ON states for all STAR:target variants (see ‘Materials and Methods’ section in (19) for details). For the application of our methods to this system, this set of 40 nt long sequences in the STAR and target RNA were used to build first and higher order orthogonal polynomials. Fold and off values were then projected onto the space of the orthogonal polynomials.

Output: pass


Input: Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: 2016; Miescher Schwenninger, Freimüller Leischtfeld and Gantenbein-Demarchi 2016; Miguel et al. 2017; Agyirifo et al. 2019). Aerobic acetic acid bacteria phase The AAB species that are already present from the beginning of the cocoa fermentation process and have survived the anaerobic yeast and LAB growth phases start to grow during the aerobic phase, which occurs after approximately 48 h of fermentation (Schwan and Wheals 2004; and Weckx 2016a,b; Figueroa-Hernández et al. 2019; Muñoz et al. 2019). This is enabled by further air ingress upon sweating and regular mixing of the cocoa pulp-bean mass during fermentation. They reach their maximal counts after 72–96 h of fermentation. Possessing a non-functional glycolysis, AAB, in particular Acetobacter species, oxidize the ethanol produced by the yeasts into acetic acid (partial oxidation for ATP generation) (Fig. 2). Because of this exothermic reaction, they increase the temperature to and even beyond 50°C. Whereas ethanol serves as the main energy source, lactate produced by the LAB is the main carbon source for the Acetobacter species (Camu et al. 2007, 2008a; Adler et al. 2014; Moens, Lefeber and 2014; Pelicaen et al. 2019). Simultaneously with the oxidation of ethanol, lactic acid is oxidized mainly into acetoin (via α-acetolactate) and, to a low extent, into acetic acid because of a low pyruvate decarboxylase activity of Acetobacter (Fig. 2; Adler et al. 2014; Moens, Lefeber and 2014; Pelicaen et al. 2019). Moreover, lactic acid can be used as the sole carbon source by Acetobacter pasteurianus (Pelicaen et al. 2019). Hence, the highest acetic acid concentrations are produced in the presence of both yeasts and LAB, underlying the importance of the latter microbial group, as balanced concentrations of ethanol and lactic acid are necessary for optimal growth of Acetobacter (Adler et al. 2014). This produces the necessary acetic acid for bean curing.

Output: corroborate


Input: Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: 0005 for Monkey C; mean visual/memory latency: 36/77 ms for Monkey A, 9/116 ms for and C). Of note some, but not all, of the cells exhibiting environmental memory had a shorter visual latency than one would expect given the minimal latency to a stimulus flashed in the receptive field. This latency advance is characteristic of the remapping response (Duhamel et al. , 1991). However, because the memory responses for some neurons increased gradually, we were unable to establish memory latencies for all neurons using our latency method (for these neurons, we used other approaches, as described in the Materials and methods section). Figure 5 Download asset Open asset Population data for the basic memory task: For all recorded units (open circles and triangles) and for units which showed significant differences between baseline and memory blocks (filled circles and triangles, trial per trial peak comparisons, Wilcoxon signed rank, population p<0. 001, within-cell Wilcoxon rank sum <0. 05). (A) Comparison of peak activity in the baseline and memory conditions (Block 1 vs Block 3, no probe stimulus trials). Each point represents a single cell. Cells with memory activity lie above the x = y line (diagonal). Monkey A: blue circles; and C: red triangles (*=and C). Insets: index (Block 3 versus Block 1) histograms for the whole population, out of which the statistically significant units are shown in shaded circles and triangles on the scatter plot. A median (numbers above index histograms) and rank sum and KS test confirmed memory activity as they both showed that the index distribution for the parent population was positively skewed. (B) Peak memory activity plotted against visual activity. Blue and red lines in the scatter plots (B and C) are polynomial fits to each population data. They both indicate a positive shift of neural responses towards memory activity. (C) Latency of memory response versus the latency of visual response for cells. (D) Normalized decay activity. The memory response gradually decays after the last trial in which the probe appeared. The regression lines are data fits using a first order exponential. As indicated in ‘D’ legend, open squares and triangles are neural activities during decay trials compared to (normalized by) the mean of the last five trials with the probe stimulus (left y-axis).

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: showcase nucleotide interactions across STAR sites As part of first order analysis, means, variances and covariances were computed for all 40 sites across the population of STAR and target RNA sequences. The 40 site long linear region was determined experimentally as being the optimal length to activate transcription (see ‘Materials and Methods’ section in (19)). Figure 4 shows frequencies of nucleotides along the 99 sequences of the target RNA. consist of nucleotides cytosine (C), thymine (T), and uracil (U, in the case of RNA). Purines consist of adenine (A) and guanine (G). Figure 4. Means of nucleotides present at each site. Frequencies of nucleotides present at each site of the target RNA (from 3 prime to 5 prime) sequence generated by the software. Open in new tabDownload slideThe covariance analysis yields matrices for all pairs of sites, across the 40 sites and quantifies the relation between having a particular nucleotide at one site and another nucleotide at another site. Since there are 40 sites in this system, there are 780 unique pairs of sites. The covariance between each pair of sites is a matrix and thus, there are 780 4×4 matrices which account for all sites and all possible nucleotides at each site. To understand the distribution of these covariances, a histogram was constructed and different cutoffs were analyzed (S1, 3 and 4). S1 shows that as the cutoff became larger, the number of ‘highly covarying’ pairs became smaller. The cutoff of −0. 05 and 0. 05 was selected after testing multiple different cutoffs which showed the same patterns (S3 and 4 showing cutoffs of 0. 04 and 0. 03, respectively). The cutoff of 0. 05 yields 32 site pairs, indicating nucleotides at specific sites covarying highly and positively with each other and nucleotides at other sites covarying highly and negatively with each other (see S1 for actual values). These large positive and negative covariances are visualized as seen in Figure 5 and S2 The start of the sequence, depicted as site 1, is the 5′ end of the STAR while the end of the sequence is the 3′ end.

Output: pass


Input: Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: Here, the role of yeasts and LAB is thus of primordial importance to produce (sugar/higher) alcohols, aldehydes and/or esters during fermentation of the cocoa pulp-bean mass. Although pyrazines may also be produced by bacilli during (prolonged) fermentation, they are mainly formed during drying (in particular tetra- and trimethylpyrazine) and roasting (all pyrazines). However, the production of flavour-active compounds is not always desirable and can in some instances lead to sensory defects (Schwan and Wheals 2004; Afoakwa et al. 2008). Although it is not always fully clear what is driving this problem of off-flavours, over-fermentation and poor drying may be causal factors, the former leading to an increase in certain bacilli and filamentous fungi and the latter often being ascribed to failing infrastructure that can both produce these off-flavour compounds. Such off-flavours are mostly composed of amyl acetates, short- and medium-chain fatty acids and phenols (e. g. 2-methoxyphenol or guaiacol), which deliver undesirable, hammy, putrid and smoky notes when formed in excess. Use of starter cultures The knowledge on the microbial succession and activities of the most prevalent yeast, LAB and AAB species involved in cocoa fermentation processes obtained during the last decades has prompted the search for appropriate single- or mixed-strain starter cultures for controlled and steered cocoa fermentation processes (Schwan and Wheals 2004; Saltini, Akkerman and Frosch 2013; Pereira, Soccol and Soccol 2016; and Weckx 2016a,b; Ozturk and Young 2017; Castro-Alayo et al. 2019; Figueroa-Hernández et al. 2019; Muñoz et al. 2019; Mota-Gutierrez et al. 2019b). It is now generally accepted that the microbial activities during fermentation and the subsequent transfer of volatile organic compounds into the beans play a determining role in the flavour development of cured cocoa beans and, possibly, chocolates produced thereof.

Output: corroborate


Input: Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: 4, in which the probe stimulus no longer appeared, the memory response gradually decayed (Figure 5d). On an individual cell basis, this decay (measured in the memory window as described in the Materials and methods section) was quite noisy and variable among cells. As a population, the normalized decay activity could be fit to a first-order exponential. To control for fast memory buildups and/or in-between block fluctuations, we normalized the decay activity with stimulus presentation block. had a decay rate constant of 0. 3 trials (i. e. versus stimulus/block-one trials, first-order exponential) (R2 = 0. 7). and C had similar results (decay rate constant = 0. 13; R2 = 0. 6). For both monkeys and comparisons, the first and last 10 trials in the 50-trial forgetting block (Block 4) are statistically different (Wilcoxon signed rank, p<0001). The memory cells were not just the expected tail of a population distribution. To investigate the population median shift, we used a classical median approach. We analyzed the distribution of index histograms and found that memory activity significantly increased the median (medians > 0. 1 and compared with the index histograms with a mean-deducted version of the same distribution Wilcoxon signed rank p=3. 7034e-12 for and 1. 4923e-06 for and C). We also used a non-parametric and robust skewness estimator called the medcouple (medc) measure (Brys et al. , 2004). Unlike classical histogram descriptors such as skewness and kurtosis, this approach finds the scaled median difference between the left and right sides of a distribution. Its values range from −1 to 1 (left to right skewed, respectively). Analysis using this method for mixed trials in Block 3 (memory) versus Block 1 (baseline) indices (Figure 5a inserts) revealed that the population data was skewed toward a memory response (positive medc, ~1). The positive skewness of the memory responses (compared to baseline) is also indicated by an increased slope of a polynomial fit line (red and blue lines in Figure 5a) which is shifted to left of the identity line (black dashed line). Task 2: No-RF task This task tested whether environmental memory could be evoked in the absence of receptive field stimulation.

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: It can be immediately noted that sites near the 5′ end of the sequence (sites 2–6) covary with themselves and with all other sites, no other sites covary with anything else except with one of those. And the sites that sites 2–6 connect with are fairly evenly distributed throughout the rest of the sequence. Additionally, there is a lack of notable correlation between sites in the middle portion of the sequence. One possible explanation for this result is that this interaction between sites at the ends of the sequence is preventing any potential binding between the linear region and the hairpin part of the RNA so that the hairpin region can stay intact and pursue its function of terminating transcription of the downstream gene. This type of function for transacting regulatory RNAs has been well described in other contexts ((19), (22), (23), (24)). Figure 5. Strong correlations between nucleotides at sites across STAR. (A) Distribution of covariances between nucleotides at each site. Red bars indicate cutoffs of −0. 05 and 0. 05. (B) Large positive covariances with absolute magnitude >0. 05 across the 40 site long linear region of STAR (shown here from 5′ to 3′). (C) Large negative covariances. Table S1 for actual values. Open in new tabDownload slideAnother possible explanation for this result could be related to the way these sequences were designed by the algorithm. The objective of this software program is to calculate equilibrium distributions of the given nucleic acid strands (21). However, as has been noted by the authors of the STAR paper, STAR ‘regulation is governed by kinetic, out-of-equilibrium folding regimes’ and thus, the design of STAR sequences may not resemble natural sequences (19). Therefore, the apparent importance of sites at the 5′ end of the sequence could be an artifact of the software used to design the sequences. This warrants further investigation. The covariation pattern here indicates the potential importance of sites 2–6 to the functionality of this sequence, however, the fact that these sites appear to be correlated with a lot of other sites might suggest that they’re interacting with those other sites. Therefore, a functional variable must be projected onto this sequence space to find out the relative importance of these sites.

Output: pass


Input: Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: In addition, the cocoa genotype (in particular cocoa bean storage proteins, polysaccharides and polyphenols) and the temperature and pH courses during fermentation, which determine the enzymatic activities in the beans, are of crucial importance (Schwan and Wheals 2004; Lima et al. 2011; Saltini, Akkerman and Frosch 2013; and Weckx 2016a,b; Castro-Alayo et al. 2019; Figueroa-Hernández et al. 2019; Muñoz et al. 2019). It is not clear yet if the fermentation method applied may influence flavour development, as literature on the comparison of heap, box and tray fermentations is controversial, although there are indications that different fermentation methods may alter the flavour characteristics of cocoa liquors and conched chocolates (Owusu, Petersen and Heimdal 2012, 2013; Crafack et al. 2014; Ganeswari et al. 2015; Mota-Gutierrez et al. 2018). The use of starter cultures may allow faster, time-controlled and efficient cocoa fermentation processes and deliver high yields of cured cocoa beans of consistent and high quality. In turn, this may result in more profit for the farmers, the cocoa traders and the chocolate manufacturers, as further outlined below. Introducing the practice of starter culture-initiated cocoa fermentation processes has of course been a challenge, but once proof-of-principle was delivered the research focus shifted from accelerated and time-controlled fermentation processes (directed by the speed of pulp degradation and carbohydrate conversion) toward the use of starter cultures with extra functional properties, in particular regarding flavour formation. The first starter cultures that have been developed indeed have targeted an enhanced flow of sweatings by means of pectinolytic strains of dedicated yeast species applied as the sole starter cultures, among which S. cerevisiae var. chevalieri and Kluyveromyces fragilis (not necessarily fermenting cocoa pulp-bean mass isolates), to improve the pulp breakdown. Although this may increase the aeration of the fermenting cocoa pulp-bean mass and decrease the amounts of pulp monosaccharides available for fermentation to organic acids, leading to reduced bean acidity, it has not affected the cocoa bean quality significantly [Sanchez et al.

Output: corroborate


Input: Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: The basic memory task demonstrated that LIP neurons respond when a saccade brings the spatial location of a previously presented (now vanished) probe stimulus into their receptive field. However, because we established memory by having the monkey make a saccade that brought a stimulus into the receptive field, and then demonstrated the memory by having the monkey make the same saccade without a stimulus present, we could not know whether the memory response was independent of receptive field stimulation, or if it required visual stimulation or the receptive field to be established. Furthermore, we also could not determine whether the memory response was independent of the saccade used to establish it. To answer these questions, we used a modified version of the basic memory task, the No-RF task, in which the probe stimulus never appeared in the receptive field of the neuron and the monkey was required to make two different saccades on different trials (Figure 6). Figure 6 Download asset Open asset The No-RF task. Trials occurred in blocks. The first block (block 1, baseline) was used to establish the baseline activity of the neuron for saccade 1, prior to introduction to the probe stimulus. Block 2 (mixed, form and recall memory) introduced a task-irrelevant probe stimulus in half of the trials. In the half of trials where the probe stimulus appeared, the monkey was instructed to make a different saccade (saccade 2), which relocated the cell’s receptive field away from the probe location (Block 2, orange). In the other half of trials, no probe stimulus was presented and the monkey made saccade 1, bringing the location of the (previously presented) probe stimulus into the cell’s receptive field (Block 2, magenta). 3 (forget, identical to Block 1), to measure the decay of the memory response, the monkey was instructed to make saccade one and no probe was presented. Finally, in Block 4 (visual max), to measure the visual response of the cell to the probe, the monkey was instructed to make saccade 1, and the probe stimulus was presented in the cell’s receptive field. Trials in the first block of the No-RF task were identical to those in Block 1 of the basic memory task.

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: Given the covariance structure in the STAR linear sequence sequence (which is complementary to the target linear region) (Figure 5), we expected the regressions onto the sites to show a similar pattern of connection between sites at the 3′ end of the sequence and sites at the 5′ end. However, this pattern of correlations does not emerge when projecting the OFF fluorescence values onto the sequence space. Though there exists a dynamic range of GFP expression in the STAR library, as indicated by the OFF fluorescence values, the sequence correlation structure identified earlier does not seem to be functionally relevant when this phenotype is projected onto the sequence space. This is evidenced by the fact that when looking at just each site on its own, no particular sets of sites stick out as being more important than other parts of the sequence. To investigate this further, we built second order orthogonal polynomials and projected the phenotype onto them in order to identify pairs of interacting sites and any potential long-range interactions. Overrepresentation of purines While there is no spatial pattern in the magnitudes of regression coefficients, as was originally expected due to the sequence covariance pattern, there is a strong relationship between the kind of nucleotide at a site and the regression of the off phenotype values on it. Almost all the purines have positive regressions while almost all the pyrimidines have negative values. This means that there is a preference for having purines along the target RNA sequence while pyrimidines are disfavored. The hairpin of the target RNA, the intrinsic terminator, includes a string of guanines and cytosines which implies that these nucleotides would not be preferred along the linear region (19). But then this would mean that As and Us would have positive regressions here while Gs and Cs would be disfavored and have negative values. But that’s not what we see, we see that Gs and As have positive regressions and Cs and Us have negative regressions. So this is a somewhat mysterious result that warrants further investigation. After noting the purine/pyrimidine distinction, we were led to an additional hypothesis regarding molecular weights. There is a positive relationship between the magnitude of regression and the molecular weight of the nucleotide. Guanine is the heaviest molecule, followed by adenine, uracil and cytosine (Figure 6B).

Output: pass


Input: Claim: Lactic acid bacteria are important for fermentation processes. [SEP] Text: Concerning the choice of candidate functional starter cultures, distinction should be made between studies that have tested culture collection or commercial strains that do not necessarily originate from fermenting cocoa pulp-bean mass and studies that have first initiated a thorough screening of strains with desirable functional properties. In almost all studies the starter cultures were applied as liquid cultures. All studies have used different fermentation recipients and batch sizes. Yeast starter cultures Except for an early Brazilian study (Schwan 1998), the first starter culture-initiated cocoa fermentation studies all dealt with single- or mixed-strain starter cultures involving yeasts. Indeed, Schwan (1998) was the first to evaluate the use of a consortium of cocoa pulp-bean mass-derived strains as starter culture for cocoa fermentation processes carried out in wooden boxes (200 kg, Comum hybrid), applying the microbial inoculum either at the start of the fermentation process or through phased addition. The selected strains in this study belong to the pectinolytic, acid-tolerant and ethanol-tolerant yeast species S. cerevisiae var. chevalieri, the lactic acid-producing, acid-tolerant and heat-tolerant LAB species Lactobacillus lactis (now reclassified as Lactobacillus delbrueckii subsp. lactis) and Lacp. plantarum and the ethanol-(over)oxidizing, acetic acid-producing, heat-tolerant AAB species Acetobacter aceti and Gluconobacter oxydans. This has resulted in a fermentation process comparable with a natural one, normally cured cocoa beans and acceptable chocolates, but with no enhanced quality. This proof-of-principle study has been followed by tests with pectinase-producing or flavour-producing yeast strains to accelerate the cocoa fermentation process (flow of sweatings) and improve the flavour of the cured cocoa beans and chocolates produced thereof. First, as follow-up of the study of Sanchez et al.

Output: corroborate


Input: Claim: Memory can be perfectly recalled with the right stimulus. [SEP] Text: 1, the monkey made a visually guided saccade (saccade 1) to a target outside of the neuron’s receptive field and no probe stimulus appeared (Figure 6, Block 1). 2, two trial types were pseudorandomly interleaved: no-probe trials identical to those in Block 1 (requiring saccade 1), and trials in which the probe stimulus appeared, but the monkey had to make a different saccade (saccade 2). In the latter trials, the probe stimulus appeared in the location corresponding the neuron’s receptive field after saccade 1. However, instead of making saccade 1, monkeys were instructed to make saccade 2, which relocated the neuron’s receptive field away from the probe stimulus location, thus preventing it from ever visually stimulating the cell. Block 3 was identical to Block 1, allowing us to measure the decay rate of the memory response. 4, the monkey was instructed to make saccade one and the probe stimulus was presented in the receptive field, visually stimulating the cell. This enabled us to compare the memory and visual responses (Figure 6, block 4 and Figure 7, green trace), and ensure that we had not lost the neuron during Block 3 while we observed the memory response decay. Figure 7 Download asset Open asset Single-cell responses in the No-RF memory task: from (left panel) and (right panel). Block descriptions are as in Figure 6. Black traces and raster dots: activity in Block 1, stimulus absent. Red (broken) traces and raster dots: activity in stimulus-present trials in Block 2. Magenta traces and raster dots: activity in probe stimulus-absent trials in Block 2. The memory decays after many (up to 100) trials. Green traces and raster dots: activity in Block 4, 100% stimulus present. H and V are horizontal and vertical eye movements smoothed using a 10 ms sliding causal filter. We studied 44 neurons (30 in Monkey A, 14 in Monkey C) in the No-RF task, in which the stimulus never appeared in the cell’s receptive field before and during the establishment of the memory. Some LIP neurons have a brief postsaccadic response to eye movements in all directions, including those away from their receptive fields (Wang and Goldberg, in preparation).

Output: contrast


Input: Claim: Bioinformatics is crucial for analyzing genomic data. [SEP] Text: The regressions were the largest for heaviest molecules and decreased as the molecular weights decreased. Furthermore, adenine and guanine are capable of hydrogen bonding with uracil. Guanine has a triple bond with cytosine and can form a double (wobbly) bond with uracil. As both of these nucleotides are capable of hydrogen bonding with uracil and this is a unique feature that distinguishes them from the pyrimidines, it might be the case that these nucleotides are more preferred. Regressions of ON values onto STAR sites In addition to projecting OFF values onto target RNA sites, ON values were projected onto the space of the sequences comprising the STAR linear region. The ON values are a measure of how good a STAR is at binding to the target RNA and activating the downstream gene. Since the STAR sequence is complementary to the target RNA, as expected, the regressions of having pyrimidines in the STAR linear region are positive while the regressions of having purines is negative (Figure 7). Figure 7. Regressions onto STAR sites. (A) Regressions of off values onto each STAR site orthogonalized within each vector (5′ to 3′). (B) Regressions of ON values onto STAR sites (orthogonalized within each vector). Open in new tabDownload slide Second order analysis on all pairs of sites across the STAR sequence The first order analysis, which includes calculating covariances and variances of nucleotides at each site, revealed a number of highly correlated sites (absolute values of covariances being >0. 05) sequestered in the 5′ region of STAR. In order to test the hypothesis that sites that are correlated (Figure 5) are interacting in their effect on the phenotype, we built second order polynomials for each pair of sites across the STAR sequence (with 780 unique pairs in total). See the corresponding supplementary section that shows an example of how this is done with a different set of sites. After building second order polynomials for each pair of sites across the STAR sequence, regressions of the phenotype onto each pair of sites were computed. For a given pair of sites, this results in a 4×4 matrix, with 16 total values that each correspond to a given nucleotide at the first site and another nucleotide at the second site. Figure 8 shows an example of this for sites 3, 5 and 21.

Output: pass


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

Output: corroborate


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

Output: contrast


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

Output: pass


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

Output: corroborate


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

Output: contrast


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

Output: pass


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

Output: corroborate


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

Output: contrast


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

Output: pass


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

Output: corroborate


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

Output: contrast


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

Output: pass


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

Output: corroborate


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

Output: contrast


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

Output: pass


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

Output: corroborate


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

Output: contrast


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

Output: pass


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

Output: corroborate