bluuebunny/crossref_metadata_2025 huggingface dataset:
Ensuring that fundamentals of quantitative microbiology are reflected in microbial diversity analyses based on next-generation sequencing
Authors: Schmidt Philip J. , Cameron Ellen S. , Müller Kirsten M. , Emelko Monica B.
Published: June 2021

Diversity analysis of amplicon sequencing data is mainly limited to plug-in estimates calculated using normalized data to obtain a single value of an alpha diversity metric or a single point on a beta diversity ordination plot for each sample. As recognized for count data generated using classical microbiological methods, read counts obtained from a sample are random data linked to source properties by a probabilistic process. Thus, diversity analysis has focused on diversity of (normalized) samples rather than probabilistic inference about source diversity. This study applies fundamentals of statistical analysis for quantitative microbiology (e.g., microscopy, plating, most probable number methods) to sample collection and processing procedures of amplicon sequencing methods to facilitate inference reflecting the probabilistic nature of such data and evaluation of uncertainty in diversity metrics. Types of random error are described and clustering of microorganisms in the source, differential analytical recovery during sample processing, and amplification are found to invalidate a multinomial relative abundance model. The zeros often abounding in amplicon sequencing data and their implications are addressed, and Bayesian analysis is applied to estimate the source Shannon index given unnormalized data (both simulated and real). Inference about source diversity is found to require knowledge of the exact number of unique variants in the source, which is practically unknowable due to library size limitations and the inability to differentiate zeros corresponding to variants that are actually absent in the source from zeros corresponding to variants that were merely not detected. Given these problems with estimation of diversity in the source even when the basic multinomial model is valid, sample-level diversity analysis approaches are discussed.

Highlights

Random error in amplicon sequencing method should be considered in diversity analysis

Clustering, amplification, and differential recovery distort sample diversity

The multinomial model for compositional count data is compromised by amplification

There are three types of zeros in amplicon sequencing data, including missing zeros

Source alpha diversity estimates are biased by unknown number of unique variants
A dose-sensitive OGT-TET3 complex is necessary for normal Xist RNA distribution and function
Authors: Martin Elizabeth Allene , Maynard Jason C. , Hrit Joel , Augspurger Katherine , Picard Colette L. , Feng Suhua , Jacobsen Steven E. , Burlingame Alma L. , Panning Barbara
Published: June 2021

Female (XX) mouse embryonic stem cells (mESCs) differ from their male (XY) counterparts because they have lower levels of 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC). This difference in DNA modifications is a result of having two X chromosomes (Xs), both of which are active at this developmental stage. We identified an X-linked gene, Ogt, that controls levels of 5mC and 5hmC in mESCs. OGT is a post-translational modification enzyme and we identified the 5-methylcytosine dioxygenase TET3 as an OGT target that is differentially modified in XX and XY mESCs. In addition to influencing 5mC and 5hmC abundance, OGT dose also controls TET3 and OGT distribution. OGT and TET3 are predominantly nuclear in XX mESCs and cytoplasmic in XY mESCs. Furthermore, these proteins are present in different complexes in XX and XY mESCs. Mutational analysis revealed that TET3 determines the XX-specific abundance of 5mC and 5hmC in mESCs. While TET3 null XX mESCs exhibited modest changes in gene expression, there were substantial alterations upon differentiation into epiblast-like cells (mEpiLCs). In addition, these TET3 null XX mESCs did not undergo X-chromosome inactivation (XCI) when differentiated. These data suggest that an X-dose sensitive complex containing OGT and TET3 regulates cytosine modifications and XCI.
The effect of self- vs. externally generated actions on timing, duration and amplitude of BOLD response for visual feedback processing
Authors: Kavroulakis Eleftherios , van Kemenade Bianca M. , Arikan B. Ezgi , Kircher Tilo , Straube Benjamin
Published: June 2021

It has been widely assumed that internal forward models use efference copies to create predictions about the sensory consequences of our own actions. While these predictions had been frequently associated with reduced neural processing in sensory cortices, the timing and duration of the hemodynamic response of self-generated as opposed to externally generated movements is poorly investigated. In the present study we tested the hypothesis that predictive mechanisms for self-generated actions lead to early and shorter neural processing compared with externally generated movements. Using a first and second-order Taylor approximation in terms of the temporal (TD) and dispersion (DD) derivatives of a canonical hemodynamic response function, we investigated the timing and duration of activation for self-generated and externally generated movements using a custom-made fMRI-compatible movement device. Visual video feedback of the active and passive hand movements were presented in real time or with variable delays (0 - 417 ms). Participants had to judge, whether the feedback was delayed. We found earlier feedback processing for self-generated compared to externally generated movements in several regions including the supplementary motor area, cerebellum, subcortical structures such as the putamen and visual cortices. Shorter processing was found in areas, which show also lower blood oxygen level dependent (BOLD) amplitudes, such as the SMA, occipital and parietal cortex. Specifically, earlier activation in the putamen, of self-generated movements was associated with worse performance in detecting delays. These findings support our hypothesis, that efference copy based predictive mechanisms enable earlier processing of action feedback, as potential source for behavioral effects.
Pathway-based approach reveals differential sensitivity of glioblastoma to E2F1 inhibition
Authors: Alvarado Alvaro G. , Tessema Kaleab , Muthukrishnan Sree Deepthi , Sober Mackenzie , Kawaguchi Riki , Bhaduri Aparna , Swarup Vivek , Nathanson David A , Goldman Steven A. , Kornblum Harley I.
Published: June 2021

Targeting glioblastoma (GBM) based on molecular subtyping have not yet translated into successful therapies. Here, we used gene set enrichment analysis (GSEA) to conduct an unsupervised clustering analysis to condense the gene expression data from bulk patient samples and patient-derived gliomasphere lines into new gene lists. We then identified key molecular pathways differentially regulated between tumors. These gene lists associated not only with cell cycle and stemness signatures, but also with cell-type specific markers and different cellular states of GBM. We identified the transcription factor E2F1 as a key regulator of tumor cell proliferation and self-renewal in only the subset of proliferating gliomasphere cultures predicted to be E2F1-activated and validated its functional significance in tumor formation capacity. E2F1 inhibition also sensitized E2F1-activated gliomasphere cultures to radiation treatment. Our findings indicate that a pathway-based approach can be leveraged to deconstruct inter-tumoral heterogeneity and uncover key therapeutic vulnerabilities for targeting GBM.
Statistics of eigenvalue dispersion indices: quantifying the magnitude of phenotypic integration
Authors: Watanabe Junya
Published: June 2021

Quantification of the magnitude of trait covariation plays a pivotal role in the study of phenotypic evolution, for which statistics based on dispersion of eigenvalues of a covariance or correlation matrix—eigenvalue dispersion indices—are commonly used. This study remedies major issues over the use of these statistics, namely, a lack of clear understandings on their statistical justifications and sampling properties. The relative eigenvalue variance of a covariance matrix is known in the statistical literature a test statistic for sphericity, thus is an appropriate measure of eccentricity of variation. The same of a correlation matrix is equal to the average squared correlation, which has a straightforward interpretation as a measure of integration. Expressions for the mean and variance of these statistics are analytically derived under multivariate normality, clarifying the effects of sample sizeN, number of variablesp, and parameters on sampling bias and error. Simulations confirmed that approximations involved are reasonably accurate with a moderate sample size (N≥ 16–64). Importantly, sampling properties of these indices are not adversely affected by a highp:Nratio, promising their utility in high-dimensional phenotypic analyses. They can furthermore be applied to shape variables and phylogenetically structured data with appropriate modifications.
Long-term molecular turnover of actin stress fibers revealed by advection-reaction analysis in fluorescence recovery after photobleaching
Authors: Saito Takumi , Matsunaga Daiki , Matsui Tsubasa S. , Deguchi Shinji
Published: June 2021

Fluorescence recovery after photobleaching (FRAP) is a versatile technique to evaluate the intracellular molecular exchange called turnover. Physicochemical models of FRAP typically consider the molecular diffusion and chemical reaction that simultaneously occur on a time scale of seconds to minutes. Particularly for long-term measurements, however, an advection effect can no longer be ignored, which transports the proteins in specific directions within the cells and accordingly shifts the spatial distribution of the local chemical equilibrium. Nevertheless, existing FRAP models have not considered the spatial shift, and as such, the turnover rate is often analyzed without considering the spatiotemporally updated chemical equilibrium. Here we develop a new FRAP model aimed at long-term measurements to quantitatively determine the two distinct effects of the advection and chemical reaction, i.e., the different major sources of the change in fluorescence intensity. To validate this approach, we carried out FRAP experiments on actin in stress fibers over a time period of more than 900 s, and the advection rate was shown to be comparable in magnitude to the chemical dissociation rate. We further found that the actin–myosin interaction and actin polymerization differently affect the advection and chemical dissociation. Our results thus suggest that the distinction between the two effects is indispensable to extract the intrinsic chemical properties of the actin cytoskeleton from the observations of complicated turnover in cells.
Development of opioid-induced hyperalgesia depends on reactive astrocytes controlled by Wnt5a signaling
Authors: Liu Xin , Bae Chilman , Liu Bolong , Zhang Yongmei , Zhou Xiangfu , Zhang Donghang , Zhou Cheng , DiBua Adriana , Schutz Livia , Kaczocha Martin , Puopolo Michelino , Yamaguchi Terry P. , Chung Jin Mo , Tang Shao-Jun
Published: June 2021

Opioids are the frontline analgesics for managing various types of pain. Paradoxically, repeated use of opioid analgesics may cause an exacerbated pain state known as opioid-induced hyperalgesia (OIH), which significantly contributes to dose escalation and consequently opioid overdose. Neuronal malplasticity in pain circuits has been the predominant proposed mechanism of OIH expression. Although glial cells are known to become reactive in OIH animal models, their biological contribution to OIH remains to be defined and their activation mechanism remains to be elucidated. Here, we show that reactive astrocytes (a.k.a. astrogliosis) are critical for OIH development in both male and female mice. Genetic ablation of astrogliosis inhibited the expression of OIH and morphine-induced neural circuit polarization (NCP) in the spinal dorsal horn (SDH). We found that Wnt5a is a neuron-to-astrocyte signal that is required for morphine-induced astrogliosis. Conditional knock-out of Wnt5a in neurons or its co-receptor ROR2 in astrocytes blocked not only morphine-induced astrogliosis but also OIH and NCP. Furthermore, we showed that the Wnt5a-ROR2 signaling-dependent astrogliosis contributes to OIH via inflammasome-regulated IL-1β. Our results reveal an important role of morphine-induced astrogliosis in OIH pathogenesis and elucidate a neuron-to-astrocyte intercellular Wnt signaling pathway that controls the astrogliosis.
Visual stimulation induces distinct forms of sensitization of On-Off direction-selective ganglion cell responses in the dorsal and ventral retina
Authors: Huang Xiaolin , Kim Alan Jaehyun , Ledesma Héctor Acarón , Ding Jennifer , Smith Robert G. , Wei Wei
Published: June 2021

Experience-dependent modulation of neuronal responses is a key attribute in sensory processing. In the mammalian retina, the On-Off direction-selective ganglion cell (On-Off DSGC) is well known for its robust direction selectivity. However, how the On-Off DSGC light responsiveness dynamically adjusts to the changing visual environment is underexplored. Here, we report that the On-Off DSGC can be transiently sensitized by prior stimuli. Notably, distinct sensitization patterns are found in dorsal and ventral DSGCs that receive visual inputs from lower and upper visual fields respectively. Although responses of both dorsal and ventral DSGCs to dark stimuli (Off responses) are sensitized, only dorsal cells show sensitization of responses to bright stimuli (On responses). Visual stimulation to the dorsal retina potentiates a sustained excitatory input from Off bipolar cells, leading to tonic depolarization of dorsal DSGCs. Such tonic depolarization propagates from the Off to the On dendritic arbor of the DSGC to sensitize its On response. We also identified a previously overlooked feature of DSGC dendritic architecture that can support direct electrotonic propagation between On and Off dendritic layers. By contrast, ventral DSGCs lack a sensitized tonic depolarization and thus do not exhibit sensitization of their On responses. Our results highlight a topographic difference in Off bipolar cell inputs underlying divergent sensitization patterns of dorsal and ventral On-Off DSGCs. Moreover, substantial crossovers between dendritic layers of On-Off DSGCs suggest an interactive dendritic algorithm for processing On and Off signals before they reach the soma.
Supervised Learning Model Predicts Protein Adsorption to Carbon Nanotubes
Authors: Pinals Rebecca L , Ouassil Nicholas , Del Bonis-O'Donnell Jackson Travis , Wang Jeffrey W , Landry Markita P
Published: June 2021

Engineered nanoparticles are advantageous for numerous biotechnology applications, including biomolecular sensing and delivery. However, testing the compatibility and function of nanotechnologies in biological systems requires a heuristic approach, where unpredictable biofouling via protein corona formation often prevents effective implementation. Moreover, rational design of biomolecule-nanoparticle conjugates requires prior knowledge of such interactions or extensive experimental testing. Toward better applying engineered nanoparticles in biological systems, herein, we develop a random forest classifier (RFC) trained with proteomic mass spectrometry data that identifies proteins that adsorb to nanoparticles, based solely on the protein's amino acid sequence. We model proteins that populate the corona of a single-walled carbon nanotube (SWCNT)-based optical nanosensor and study whether there is a relationship between the protein's amino acid-based properties and the protein's adsorption to SWCNTs. We optimize the classifier and characterize the classifier performance against other models. To evaluate the predictive power of our model, we apply the classifier to rapidly identify proteins with high binding affinity to SWCNTs, followed by experimental validation. We further determine protein features associated with increased likelihood of SWCNT binding: high content of solvent-exposed glycine residues and non-secondary structure-associated amino acids. Conversely, proteins with high content of leucine residues and beta-sheet-associated amino acids are less likely to form the SWCNT protein corona. The classifier presented herein provides a step toward undertaking the otherwise intractable problem of predicting protein-nanoparticle interactions, which is needed for more rapid and effective translation of nanobiotechnologies from in vitro synthesis to in vivo use.
Nutrient-sensitive reinforcement learning in monkeys
Authors: Huang Fei-Yang , Grabenhorst Fabian
Published: June 2021

Animals make adaptive food choices to acquire nutrients that are essential for survival. In reinforcement learning (RL), animals choose by assigning values to options and update these values with new experiences. This framework has been instrumental for identifying fundamental learning and decision variables, and their neural substrates. However, canonical RL models do not explain how learning depends on biologically critical intrinsic reward components, such as nutrients, and related homeostatic regulation. Here, we investigated this question in monkeys making choices for nutrient-defined food rewards under varying reward probabilities. We found that the nutrient composition of rewards strongly influenced monkeys’ choices and learning. The animals preferred rewards high in nutrient content and showed individual preferences for specific nutrients (sugar, fat). These nutrient preferences affected how the animals adapted to changing reward probabilities: the monkeys learned faster from preferred nutrient rewards and chose them frequently even when they were associated with lower reward probability. Although more recently experienced rewards generally had a stronger influence on monkeys’ choices, the impact of reward history depended on the rewards’ specific nutrient composition. A nutrient-sensitive RL model captured these processes. It updated the value of individual sugar and fat components of expected rewards from experience and integrated them into scalar values that explained the monkeys’ choices. Our findings indicate that nutrients constitute important reward components that influence subjective valuation, learning and choice. Incorporating nutrient-value functions into RL models may enhance their biological validity and help reveal unrecognized nutrient-specific learning and decision computations.
Resting-state functional connectivity relates to interindividual variations in positive memory
Authors: Isato Ayako , Suhara Tetsuya , Yamada Makiko
Published: June 2021

Individual differences in positive memory recollection are of interest in mental health, as positive memories can help protect people against stress and depression. However, it is unclear how individual differences in positive memory recollection are reflected in brain activity in the resting state. Here, we investigate the resting-state functional connectivity (FC) associated with interindividual variations in positive memory by employing cluster-level inferences based on randomization/permutation region of interest (ROI)-to-ROI analyses. We identified a cluster of FCs that was positively associated with positive memory performance, including the frontal operculum, central operculum, parietal operculum, Heschl’s gyrus, and planum temporale. The current results suggest that positive memory is innervated by frontotemporal network connectivity, which may have implications for future investigations of vulnerability to stress and depression.
Functional network motifs defined through integration of protein-protein and genetic interactions
Authors: Sahoo Amruta , Pechmann Sebastian
Published: June 2021

Cells are enticingly complex systems. The identification of feedback regulation is critically important for understanding this complexity. Network motifs defined as small graphlets that occur more frequently than expected by chance have revolutionized our understanding of feed-back circuits in cellular networks. However, with their definition solely based on statistical over-representation, network motifs often lack biological context, which limits their usefulness. Here, we define functional network motifs (FNMs) through the systematic integration of genetic interaction data that directly informs on functional relationships between genes and encoded proteins. Occurring two orders of magnitude less frequently than conventional network motifs, we found FNMs significantly enriched in genes known to be functionally related. Moreover, our comprehensive analyses of FNMs in yeast showed that they are powerful at capturing both known and putative novel regulatory interactions, thus suggesting a promising strategy towards the systematic identification of feedback regulation in biological networks. Many FNMs appeared as excellent candidates for the prioritization of follow-up biochemical characterization, which is a recurring bottleneck in the targeting of complex diseases. More generally, our work highlights a fruitful avenue for integrating and harnessing genomic network data.
Wnt/β-catenin signaling and p68 conjointly regulate CHIP in colorectal cancer
Authors: Kal Satadeepa , Chakraborty Shrabastee , Karmakar Subhajit , Ghosh Mrinal K
Published: June 2021

The differential expression pattern of Carboxy terminus of Hsc70 Interacting Protein (CHIP, alias STIP1 Homology and U–box Containing Protein 1 or STUB1) in cancers is associated with ubiquitination mediated degradation of its client proteins. Emerging evidences suggest its abundant expression of CHIP in colorectal cancer compared to normal tissues, but the mechanistic detail of this augmented expression pattern is unclear. The signature driver of canonical Wnt pathway, β-catenin, and its co-activator RNA helicase p68, are also overexpressed in colorectal cancer. In this study, we describe a novel mechanism of Wnt/β-catenin and p68 mediated transcriptional activation of CHIP gene leading to enhanced proliferation of colorectal cancer cells. Wnt3A treatment and pharmacological activation of canonical Wnt signaling pathway resulted in increased nuclear translocation of β-catenin and elevated expression of CHIP. Likewise, overexpression and knockdown of β-catenin and p68 upregulated and downregulated CHIP expression, respectively, at both mRNA and protein levels. After cloning CHIP promoter, the increased and decreased promoter activities of CHIP induced by overexpression and knockdown of either β-catenin or p68 further confirmed transcriptional regulation of CHIP gene by Wnt/β-catenin signaling cascade. p68 along with β-catenin were found to occupy Transcription Factor 4 (TCF4) binding sites on endogenous CHIP promoter and regulate its transcription. Finally, enhanced cellular propagation and migration of colorectal cancer cells induced by ‘Wnt/β-catenin-p68–CHIP’ axis established the significance of this pathway in oncogenesis. To the best of our knowledge, this is the first report elucidating the mechanistic details of transcriptional regulation of CHIP (STUB1) gene expression.
A Novel Membrane Protein in the Rhodobacter sphaeroides LH1-RC Photocomplex
Authors: Tani K. , Nagashima K. V. P. , Kanno R. , Kawamura S. , Kikuchi R. , Hall M. , Yu L.-J. , Kimura Y. , Madigan M. T. , Mizoguchi A. , Humbel B. M. , Wang-Otomo Z.-Y.
Published: June 2021

We present a cryo-EM structure of the monomeric light-harvesting-reaction center (LH1-RC) core complex from photosynthetic purple bacterium Rhodobacter (Rba.) sphaeroides at 2.9 Å resolution. The LH1 complex forms a C-shaped structure composed of 14 αβ-polypeptides around the RC with a large ring opening. From the cryo-EM density map, a previously unrecognized integral membrane protein, referred to as protein-U, was identified. Protein-U has a U-shaped conformation near the LH1-ring opening and was annotated as a hypothetical protein in the Rba. sphaeroides genome. Deletion of protein-U resulted in a mutant strain that expressed a much-reduced amount of the dimeric LH1-RC, indicating an important role for protein-U in dimerization of the LH1-RC complex. PufX was located opposite protein-U on the LH1-ring opening, and both its position and conformation differed from that of previous reports of dimeric LH1-RC structures obtained at low-resolution. Twenty-six molecules of the carotenoid spheroidene arranged in two distinct configurations were resolved in the Rba. sphaeroides LH1 and were positioned within the complex to block its pores. Our findings offer a new view of the core photocomplex of Rba. sphaeroides and the connections between structure and function in bacterial photocomplexes in general.
Pan-Cancer Analysis of DNA Methylation Identifies Genes and Biological Functions Associated with Overall Survival
Authors: Cavet Romola , Yue Peng , Cavet Guy
Published: June 2021

DNA methylation influences gene expression and is altered in many cancers, but the relationship between DNA methylation and cancer outcomes is not yet fully understood. If methylation of specific genes is associated with better or worse outcomes, it could implicate genes in driving cancer and suggest therapeutic strategies. To advance our understanding of DNA methylation in cancer biology, we conducted a pan-cancer analysis of the relationship between methylation and overall survival. Using data on 28 tumor types from The Cancer Genome Atlas (TCGA), we identified genes and genomic regions whose methylation was recurrently associated with survival across multiple cancer types. While global DNA methylation levels are associated with outcome in some cancers, we found that the gene-specific associations were largely independent of these global effects. Genes with recurrent associations across cancer types were enriched for certain biological functions, such as immunity and cell-cell adhesion. While these recurrently associated genes were found throughout the genome, they were enriched in certain genomic regions, which may further implicate certain gene families and gene clusters in affecting survival. By finding common features across cancer types, our results link DNA methylation to patient outcomes, identify biological mechanisms that could explain survival differences, and support the potential value of treatments that modulate the methylation of tumor DNA.
Unigems: plasmids and parts to facilitate teaching on assembly, gene expression control and logic in E. coli
Authors: Siddall Alex , Williams Abbie Ann , Sanders Jason , Denton Jai A. , Madden Dean , Schollar John , Bryk Jarosław
Published: June 2021

Synthetic biology is as an excellent vehicle for education, as it enables creative combination of engineering and molecular biology approaches for quantitative characterisations of the assembled constructs. However, there is a limited number of resources available for such applications in the educational context, where straightforward setup, easily measurable phenotypes and extensibility are of particular importance. To expand the availability of education-friendly resources to teach synthetic biology and genetic engineering, we developed Unigems, a set of 10 plasmids that enable out-of-the-box investigations of principles of gene expression control, as well as more complex designs a biological logic gate. The system uses a common high-copy plasmid backbone and a common set of primers to enable Gibson-assembly of PCR-generated or synthesised parts into a target vector. It currently has two reporter genes with either two constitutive (high- or low-level) or two inducible (lactose- or arabinose-) promoters, as well as a single-plasmid implementation of an AND logic gate. The Unigems system has already been employed in undergraduate teaching settings, during outreach events and for training of iGEM teams. All plasmids have been deposited in Addgene.
Urocortin 3 in the posterodorsal medial amygdala mediates psychosocial stress-induced suppression of LH pulsatility in female mice
Authors: Ivanova Deyana , Li Xiao-Feng , McIntyre Caitlin , Liu Yali , Kong Lingsi , O’Byrne Kevin T
Published: June 2021

Exposure to psychosocial stress disrupts reproductive function and interferes with pulsatile luteinising hormone (LH) secretion in mammals. The posterodorsal sub-nucleus of the medial amygdala (MePD) is part of the limbic brain and is an upstream modulator of the reproductive axis as well as stress and anxiety states. Corticotropin releasing factor type-2 receptors (CRFR2) are activated in the presence of psychosocial stress together with an increased expression of the CRFR2 ligand Urocortin3 (Ucn3) in MePD of rodents. We investigate whether Ucn3 signalling in the MePD is involved in mediating the suppressive effect of psychosocial stress exposure on LH pulsatility. Firstly, we administered Ucn3 into the MePD and monitored the effect on pulsatile LH secretion in ovariectomised mice. Next, we delivered Astressin2B, a highly selective CRFR2 antagonist, intra-MePD in the presence of predator odor, 2,4,5-Trimethylthiazole (TMT) and examined the effect on LH pulses. Subsequently, we virally infected ovariectomised Ucn3-cre-tdTomato mice with inhibitory DREADDs targeting the MePD Ucn3 neurons while exposing the mice to TMT or restraint stress and examined the effect on LH pulsatility as well as corticosterone (CORT) release. Administration of Ucn3 into the MePD dose-dependently inhibited pulsatile LH secretion and intra-MePD administration of Astressin2B blocked the suppressive effect TMT on LH pulsatility. Additionally, DREADDs inhibition of MePD Ucn3 neurons blocked TMT and restraint stress-induced inhibition of LH pulses as well as CORT release in the presence of TMT. These results demonstrate for the first time that Ucn3 neurons in the MePD mediate psychosocial stress-induced suppression of the GnRH pulse generator and psychosocial stress-induced CORT secretion. Ucn3 signalling in the MePD plays a fundamental role in modulating the hypothalamic-pituitary-ganadal and hypothalamic-pituitary-adrenal axes, and this brain locus may represent a nodal centre in the crosstalk between the reproductive and stress axes.
Autogenous and anautogenousCulex pipiensbioforms exhibit insulin-like peptide signaling pathway gene expression differences that are not dependent upon larval nutrition
Authors: Cheatle Jarvela Alys M. , Bell Katherine L. , Noreuil Anna , Fritz Megan L.
Published: June 2021

Culex pipiensformpipiensandCx. pipiensformmolestusdiffer in their ability to produce eggs without a bloodmeal. Autogenous mosquitoes, such as themolestusbioform ofCx. pipiens, depend on nutrition acquired as larvae instead of a bloodmeal to fuel the energy intensive process of vitellogenesis, which requires abundant production of yolk proteins. In anautogenous mosquito systems, ovary ecdysteroidogenic hormone (OEH) and insulin-like peptides (ILPs) transduce nutritional signals and trigger egg maturation in response to a bloodmeal. It is unclear to what extent the process is conserved in autogenous mosquitoes and how the bloodmeal trigger has been replaced by teneral reserves. Here, we measured the effects of a series of nutritional regimens on autogeny, time to pupation, and survival inCx. pipiensformmolestusand formpipiens. We find that abundant nutrients never result in autogenous formpipiensand extremely poor food availability rarely eliminates autogeny from formmolestus. However, the number of autogenous eggs generated increases with nutrient availability. Similarly, using qPCR to quantify gene expression, we find several differences in the expression levels ofilpsbetween bioforms that are reduced and delayed by poor nutrition, but not extinguished. Changes inOEHexpression do not explain bioform-specific differences in autogeny. Surprisingly, the source of most of the gene expression differences correlated with autogeny is the abdomen, not the brain. Overall, our results suggest that autogeny is modulated by nutritional availability, but the trait is encoded by genetic differences between forms and these impact the expression of ILPs.
Improvement of association between confidence and accuracy after integration of separate evidence over time
Authors: Azizi Zahra , Zabbah Sajjad , Jahanitabesh Azra , Ebrahimpour Reza
Published: June 2021

When making decisions in real-life, we may receive discrete evidence during a time period. Although participants can integrate information from separate cues to improve their accuracy, it is still debatable how confidence changes after receiving discrete information. Nevertheless, based on the strong positive relationship between accuracy and confidence, we predicted that similar to what is observed in accuracy, confidence would improve following the integration of separate pieces of information. We used a Random-dot-motion discrimination task in which one or two brief stimuli (i.e., pulse[s]) were presented, and participants had to indicate the predominant direction of dot motions by saccadic eye movement. Two pulses intervals (up to 1s) were randomly selected, where color-coded targets facilitated indicating confidence simultaneously. Using behavioral data, computational models, pupillometry, and EEG methodology, our data revealed that compared to single-pulse trials, in double-pulse trials, participants improve their confidence resolution rather than reporting higher confidence and that the EEG signal (centro-parietal-positivity) and pupil dynamics appear to follow confidence levels but only in double-pulse trials. Overall, our findings suggest that evidence integration helps to improve the associations between confidence and accuracy.
In silico tool for Predicting, Designing and Scanning IL-2 inducing peptides
Authors: Mehta Naman Kumar , Lathwal Anjali , Kumar Rajesh , Kaur Dilraj , Raghava Gajendra P. S.
Published: June 2021

Interleukin-2 (IL-2) based immunotherapy has been approved for treating certain types of cancer, as IL-2 plays a crucial role in regulating the immune system. In this study, we developed a method for predicting IL-2-inducing peptides. Our method was trained, tested, and validated on a main dataset containing 6,574 experimentally validated Major histocompatibility complex (MHC) binders, including 3,429 IL-2-inducing and 3,145 non-inducing peptides. A primary analysis of IL-2 inducing and non-inducing peptides revealed that certain residues, such as alanine and leucine, are more abundant in IL-2-inducing peptides. Initially, we developed alignment-based methods, which demonstrated high precision but limited coverage. Subsequently, we developed artificial intelligence-based models, including machine learning (ML), deep learning (DL), and large language models (LLM), to predict IL-2-inducing peptides. Our Extra Tree-based model, developed using dipeptide composition and peptide length, achieved a maximum AUC of 0.82. Finally, we constructed ensemble models that combined artificial intelligence and alignment-based methods. Our best ensemble model, which integrates the Extra Tree-based model with MERCI, achieved the highest AUC of 0.84 and an MCC of 0.51 on the main dataset. One limitation of the main dataset is that both IL-2-inducing and non-inducing peptides are MHC binders. To address this limitation, we created two additional datasets: Alternate Dataset 1, consisting of 3,429 IL-2-inducing peptides and 3,429 non-inducing peptides (MHC non-binders), and Alternate Dataset 2, consisting of 3,429 IL-2-inducing peptides and 3,439 non-inducing peptides (MHC binders + MHC non-binders). Our best ensemble model achieved AUCs of 0.9 and 0.8 with MCCs of 0.61 and 0.44 on Alternate Datasets 1 and 2, respectively. To assist the scientific community, we have integrated the best models from this study into a standalone software and web server, IL2pred, which enables users to predict, scan, and design IL-2-inducing peptides (https://webs.iiitd.edu.in/raghava/il2pred/).

Highlights

Development of alignment-based techniques for predicting IL-2-inducing peptides.

Identification of amino acid patterns associated with IL-2 induction.

Implementation of machine learning, deep learning, and LLM-based models for peptide prediction.

Ensemble approaches combining alignment-based and AI-driven methods and integration into the webserver.
Developmental plasticity in visual cortex is necessary for normal visuomotor integration and visuomotor skill learning
Authors: Widmer Felix C , Keller Georg B
Published: June 2021

The experience of coupling between motor output and visual feedback is necessary for the development of visuomotor skills and shapes visuomotor integration in visual cortex. Whether these experience-dependent changes involve plasticity in visual cortex remains unclear. Here, we probed the role of NMDA receptor-dependent plasticity in mouse primary visual cortex (V1) during visuomotor development. Using a conditional knockout of NMDA receptors and a photoactivatable inhibitor of CaMKII, we locally perturbed plasticity in V1 during first visual experience, recorded neuronal activity in V1, and tested the mice in a visuomotor task. We found that perturbing plasticity before, but not after, first visuomotor experience reduces responses to unpredictable stimuli, diminishes the suppression of predictable feedback in V1, and impairs visuomotor skill learning later in life. Our results demonstrate that plasticity in the local V1 circuit during early life is critical for shaping visuomotor integration.
BehaviorDEPOT: a tool for automated behavior classification and analysis in rodents
Authors: Gabriel Christopher J , Zeidler Zachary , Jin Benita , Guo Changliang , Wu Anna , Delaney Molly , Cheung Jovian , DiFazio Lauren E. , Sharpe Melissa J. , Aharoni Daniel , Wilke Scott A. , DeNardo Laura A.
Published: June 2021

Quantitative descriptions of animal behavior are essential to understand the underlying neural substrates. Many behavioral analyses are performed by hand or with expensive and inflexible commercial software that often fail on animals with attached head implants, such as those used for in vivo optogenetics and calcium imaging. With the development of machine learning algorithms that can estimate animal positions across time and space, it is becoming easier for users with no prior coding experience to perform automated animal tracking in behavioral video recordings. Yet classifying discrete behaviors based on positional tracking data remains a significant challenge. To achieve this, we must start with reliable ground truth definitions of behavior, a process that is hindered by unreliable human annotations. To overcome these barriers, we developed BehaviorDEPOT (DEcoding behavior based on POsitional Tracking), a MATLAB-based application comprising six independent modules and a graphical user interface. In the Analysis Module we provide hard-coded classifiers for freezing and rearing. Optionally applied spatiotemporal filters allow users to analyze behaviors in varied experimental designs (e.g. cued tasks or optogenetic manipulations). Even inexperienced users can generate organized behavioral data arrays that can be seamlessly aligned with neurophysiological recordings for detailed analyses of the neural substrates. Four additional modules create an easy-to-use pipeline for establishing reliable ground-truth definitions of behaviors as well as custom behavioral classifiers. Finally, our Experiment Module runs fear conditioning experiments using an Arduino-based design that interfaces with commercialhardware and significantly reduces associated costs. We demonstrate the utility and flexibility of BehaviorDEPOT in widely used behavioral assays including fear conditioning, avoidance, and decision-making tasks. We also demonstrate the robustness of the BehaviorDEPOT freezing classifier across multiple camera types and in mice and rats wearing optogenetic patch cables and head-mounted Miniscopes. BehaviorDEPOT provides a simple, flexible, automated pipeline to move from pose tracking to reliably quantifying a wide variety of task-relevant behaviors.
Linking spatial self-organization to community assembly and biodiversity
Authors: Bera Bidesh K. , Tzuk Omer , Bennett Jamie J. R. , Meron Ehud
Published: June 2021

Drier climates impose environmental stresses on plant communities that may result in community reassembly and threatened ecosystem services, but also may trigger self-organization in spatial patterns of biota and resources, which act to relax these stresses. The complex relationships between these counteracting processes – community reassembly and spatial self-organization – have hardly been studied. Using a spatio-temporal model of dryland plant communities and a trait-based approach, we study the response of such communities to imposed water stress of increasing degrees. We first show that spatial patterning acts to reverse shifts from fast-growing species to stress-tolerant species, as well as to reverse functional-diversity loss. We then show that spatial re-patterning buffers the impact of further stress on community structure. Finally, we identify multistability ranges of uniform and patterned community states and use them to propose forms of non-uniform ecosystem management that integrate the need for provisioning ecosystem services with the need to preserve community structure.
Crystal structure and computational study of an oxo-bridged bis-titanium(III) complex
Authors: Bloomfield Hannah R. , Hollett Joshua W. , Ritch Jamie S.
Published: June 2021

The solid-state structure of the new compound μ-oxido-bis[dichloridotris(tetrahydrofuran-κO)titanium(III)], [Ti2Cl4O(C4H8O)6], at 150 K has been determined. The crystal has monoclinic (C2/c) symmetry and the complex features C
2 symmetry about the bridging O atom. Positional disorder is evident in one of the three tetrahydrofuran environments. A post-Hartree–Fock computational analysis indicates that the complex has nearly degenerate triplet and singlet spin states, with the former favoured slightly by ca 2 kJ mol−1.
When to stop computing and start investing
Authors: Aguilar Sean R. , Kosheleva Olga
Published: June 2021

Purpose

The purpose of the study is to analyze when — while predicting the future price of a financial instrument — we should stop computations and start using this information for the actual investment.

Design/methodology/approach

We derive the explicit formulas explaining how the resulting gain depends on the duration of computations.

Findings

We provide an algorithm that enables us to decide the computation time that leads to the largest possible gain.

Originality/value

To the best of our knowledge, this is the first solution to the problem. Following our recommendations will allow investors to select the computation time for which the resulting gain is the largest possible.
On subcopula estimation for discrete models
Authors: Tasena Santi
Published: June 2021

Purpose

To discuss subcopula estimation for discrete models.

Design/methodology/approach

The convergence of estimators is considered under the weak convergence of distribution functions and its equivalent properties known in prior works.

Findings

The domain of the true subcopula associated with discrete random variables is found to be discrete on the interior of the unit hypercube. The construction of an estimator in which their domains have the same form as that of the true subcopula is provided, in case, the marginal distributions are binomial.

Originality/value

To the best of our knowledge, this is the first time such an estimator is defined and proved to be converged to the true subcopula.
TOPSIS model based on entropy and similarity measure for market segment selection and evaluation
Authors: Duong Truong Thi Thuy , Thao Nguyen Xuan
Published: June 2021

Purpose

The paper aims to propose a practical model for market segment selection and evaluation. The paper carries out a technique of order preference similarity to the ideal solution (TOPSIS) approach to make an operation systematic dealing with multi-criteria decision- making problem.

Design/methodology/approach

Introducing a multi-criteria decision-making problem based on TOPSIS approach. A new entropy and new similarity measure under neutrosopic environment are proposed to evaluate the weights of criteria and the relative closeness coefficient in TOPSIS model.

Findings

The outcomes show that the TOPSIS model based on new entropy and similarity measure is effective for evaluation and selection market segment. Profitability, growth of the market, the likelihood of sustainable differential advantages are the most important insights of criteria.

Originality/value

This paper put forward an effective multi-criteria decision-making dealing with uncertain information.
Impact of idiosyncratic and macroeconomic risks on capital structure: evidence from SADC countries
Authors: Marcelle Amelot Lydie Myriam , Subadar Agathee Ushad
Published: June 2021

Purpose

The purpose of this study is to investigate the impact of idiosyncratic and macroeconomic risks on capital structure on SADC countries.

Design/methodology/approach

Employing data from the African Financials database, the analysis is conducted over a ten year period spanning from 2009 to 2018 for 309 companies. Unit Root Fisher Chi-Square test and Granger Causality test were employed to test for unidirectional and bidirectional relationships cross-sectionally. To resolve endogeneity issues, System GMM was used as main topology for panel regression analysis.

Findings

The study confirmed that companies become risk averse when there is an increase in idiosyncratic and macroeconomic risk and therefore take less leverage. According to the perking order theory, a higher variability in earnings shows that the bankruptcy probability amplifies. Hence, institutions with high income employ more internal finance during periods of high idiosyncratic and macroeconomic uncertainty thereby lowering leverage. A positive significant and statistically relationship is also confirmed between idiosyncratic risk and leverage in Botswana, South Africa and Tanzania. Companies with higher leverage make riskier investment in line with the trade-off theory. In short, executives from the SADC region consider more importance to fluctuations in risk while accelerating or diminishing leverage in their capital structure.

Originality/value

The study is among one of the pioneering work underpinning the idiosyncratic risk and macroeconomic risk on capital structure and relying on a large number of companies across the SADC region. In this respect, it adds contribution to the existing literature on risks and capital structure to the socio-economic goals of the SADC region.