bluuebunny/crossref_metadata_2025_split huggingface dataset:
Computational Elucidation of Recombinant Fusion Protein Effect on Peptide-Directed Nanoparticles
Authors: Polasa Adithya , Mosleh Imann , Losey James , Abbaspourrad Alireza , Beitle Robert , Moradi Mahmoud 
Published: March 2021

AbstractNanoparticles synthesized using various peptides have optimized properties and functional abilities which can be achieved via peptide flexibility and site specificity. Using peptide Pd4 and other alanine substitution combinations of Pd4 attached to a green fluorescent protein (GFPuv), nanoparticles with well-defined sizes that are soluble in aqueous solutions can be produced. In this study, extensive molecular dynamics simulations explored the structural and functional differences between the free peptides and the peptides bound to the GFPuv used in nanoparticle production. Binding affinities of histidines of Pd4 peptide and its two mutants A6 and A11 to a palladium atom were calculated using the free energy perturbation method. Interestingly, the average particle sizes obtained from transmission electron microscopy (TEM) images correlated with our calculated free energies of different peptide sequences. Remarkably, when the peptide was bound to GFPuv, the free energies of histidine were very similar in the wild-type and other mutated peptides. However, this trend is not observed with free peptide simulations, where binding affinities differ by mutation of histidine residues. This study describes, at a molecular level, the role of amino acid sequence on binding affinity of the peptide to the surface of the palladium particles, and the functional ability of the GFPuv protein controlling these free energies irrespective of peptide sequence. Our study will provide a framework for designing free and protein attached peptides that facilitate peptide-mediated nanoparticle formation with well-regulated properties.
Emerging variants of concern in SARS-CoV-2 membrane protein: a highly conserved target with potential pathological and therapeutic implications
Authors: Shen Lishuang , Bard Jennifer Dien , Triche Timothy J. , Judkins Alexander R. , Biegel Jaclyn A. , Gai Xiaowu 
Published: March 2021

AbstractMutations in the SARS-CoV-2 Membrane (M) gene are relatively uncommon. The M gene encodes the most abundant viral structural protein, and is implicated in multiple viral functions, including initial attachment to the host cell via heparin sulfate proteoglycan, viral protein assembly in conjunction with the N and E genes, and enhanced glucose transport. We have identified a recent spike in the frequency of reported SARS-CoV-2 genomes carrying M gene mutations. This is associated with emergence of a new sub-B.1 clade defined by the previously unreported M:I82T mutation within TM3, the third of three membrane spanning helices implicated in glucose transport. The frequency of this mutation increased in the USA from 0.014% in October 2020 to 1.62% in February 2021, a 116-fold change. While constituting 0.7% of the isolates overall, M:I82T sub-B.1 lineage accounted for 14.4% of B.1 lineage isolates in February 2021, similar to the rapid initial increase previously seen with the B.1.1.7 and B.1.429 lineages, which quickly became the dominant lineages in Europe and California over a period of several months. A similar increase in incidence was also noted in another related mutation, V70L, also within the TM2 transmembrane helix. The rapid emergence of this sub-B.1 clade with recurrent I82T mutation suggests that this M gene mutation is more biologically fit, perhaps related to glucose uptake during viral replication, and should be included in ongoing genomic surveillance efforts and warrants further evaluation for potentially increased pathogenic and therapeutic implications.
Ras guanine nucleotide exchange factor RasGRP1 promotes acute inflammatory response and restricts inflammation-contributed cancer cell growth
Authors: Wang Cong , Li Xue , Yu Changping , Wang Luoling , Deng Rilin , Liu Hui , Chen Zihao , Zhang Yingdan , Fan Suping , Sun Hungyu , Zhu Haizhen , Wang Jianli , Tang Songqing 
Published: March 2021

AbstractAcute inflammatory response needs to be tightly regulated for promoting the elimination of pathogens and preveting the risk of tumorigenesis, but the mechanism has not been fully elucidated. Here, we report that Ras guanine nucleotide releasing protein 1 (RasGRP1) plays a bifunctional regulator that promotes acute inflammation and inhibits inflammation-associated cancer. At the mRNA level,RasGRP1strengthens the inflammatory response by functioning as a competing endogenous RNA to specifically promote IL-6 expression by sponging let-7a.In vivooverexpression of theRasGRP13’ untranslated region significantly aggravated lipopolysaccharide-induced systemic inflammation and dextran sulphate sodium-induced colitis inIL-6+/+mice but not inIL-6-/-mice. At the protein level, RasGRP1 restricts the growth of inflammation-contributed cancer cells by impairing EGFR-SOS1-Ras-AKT signalling. Tumour patients with high RasGRP1 expression showed a better clinical outcome than those with low expression. Considering acute inflammation rarely leads to tumorigenesis, this work reveals that RasGRP1 is an essential bifunctional regulator for acute inflammatory response.
PBN-PVT projection modulates negative affective states in mice
Authors: Zhu Ya-Bing , Wang Yan , Hua Xiao-Xiao , Xu Ling , Liu Ming-Zhe , Zhang Rui , Liu Peng-Fei , Li Jin-Bao , Zhang Ling , Mu Di 
Published: March 2021

AbstractLong-lasting negative affections dampen enthusiasm for life, and dealing with negative affective states is essential for individual survival. The parabrachial nucleus (PBN) and the thalamic paraventricular nucleus (PVT) are critical for modulating affective states in mice. However, the functional role of the PBN-PVT projection in modulating affective states remains elusive. Here, we show that the PBN neurons send dense projection fibers to the PVT and form direct excitatory synapses with the PVT neurons. Activation of the PBN-PVT projection or PVT-projecting PBN neurons induces robust anxiety-like, aversion-like, and fear-like behaviors without affecting nociceptive behaviors. Inhibition of the PBN-PVT projection or PVT-projecting PBN neurons reduces fear-like and aversion-like behaviors. Furthermore, the PVT neurons innervated by the PBN are activated by aversive stimulation, and activation of PBN-PVT projection enhances the neuronal activity of PVT neurons in response to the aversive stimulus. Activation of these downstream PVT neurons induces anxiety-like behavior behaviors. Thus, our study indicates that the PBN-PVT projection modulates negative affective states in mice.
On the generality and cognitive basis of base-rate neglect
Authors: Stengård Elina , Juslin Peter , Hahn Ulrike , van den Berg Ronald 
Published: March 2021

ABSTRACTBase rate neglect refers to people’s apparent tendency to underweight or even ignore base rate information when estimating posterior probabilities for events, such as the probability that a person with a positive cancer-test outcome actually does have cancer. While often replicated, almost all evidence for the phenomenon comes from studies that used problems with extremely low base rates, high hit rates, and low false alarm rates. It is currently unclear whether the effect generalizes to reasoning problems outside this “corner” of the entire problem space. Another limitation of previous studies is that they have focused on describing empirical patterns of the effect at the group level and not so much on the underlying strategies and individual differences. Here, we address these two limitations by testing participants on a broader problem space and modelling their responses at a single-participant level. We find that the empirical patterns that have served as evidence for base-rate neglect generalize to a larger problem space, albeit with large individual differences in the extent with which participants “neglect” base rates. In particular, we find a bi-modal distribution consisting of one group of participants who almost entirely ignore the base rate and another group who almost entirely account for it. This heterogeneity is reflected in the cognitive modeling results: participants in the former group were best captured by a linear-additive model, while participants in the latter group were best captured by a Bayesian model. We find little evidence for heuristic models. Altogether, these results suggest that the effect known as “base-rate neglect” generalizes to a large set of reasoning problems, but varies largely across participants and may need a reinterpretation in terms of the underlying cognitive mechanisms.
Rapid tissue-specific screening ofWolbachia,CardiniumandRickettsiain Flies (Diptera: Sepsidae; Drosophilidae)
Authors: Wei Yuan Cher , Huicong Ding , Puniamoorthy Nalini 
Published: March 2021

AbstractMaternally transmitted endosymbionts can negatively influence the reproduction of their arthropod hosts (e.g. male-killing, cytoplasmic incompatibility). However, such infections are rarely assessed in insect models such as Sepsidae or Drosophilidae that are routinely used in sexual selection studies. To detect infection and bacterial localisation in the host, we developed and optimised a tissue-specific multiplex screening protocol forWolbachia,CardiniumandRickettsiathat can be completed in a day. The robustness of the protocol was tested with the screening of multiple species and populations of flies commonly used in reproductive studies (N=147 flies; n=426 tissues). With triplex PCRs and more effective duplex PCRs, we detected both single and co-infections in most individuals from both families (Drosophilidae | Sepsidae; Single infection: 51.4% | 62.7%; Dual infection: 29.2% | 9.3%; Triple infection: 4.2% | 0%). Surprisingly, we documented the presence of all three reproductive bacteria in 32 wild-caught drosophilids from Singapore. Also, we note that most sepsid populations (19 out of 22) tested positive forCardinium. We found that theRickettsiainfection was overall low, but it was predominantly detected in the gastrointestinal tract instead of the reproductive tract, suggesting a potential horizontal transmission. Finally, we found that amplicon sequences of equivalent sizes between the three tissues from the same individuals share at least 98.8% identity, which suggests that the same endosymbiont strain inhabits within the whole arthropod. Overall, we believe this protocol is effective in detecting co-infections and understanding the transmission of various reproductive endosymbionts. It can also be used to assess endosymbiont infections in other insects.
Functional characterization of a DNA-dependent AAA ATPase inSimranZ1, a F cluster mycobacteriophage
Authors: Das Ritam , Bajpai Urmi 
Published: March 2021

AbstractMycobacteriophages are viruses ofMycobacteriumspp. with promising diagnostic and therapeutic potential. Phage genome exploration and characterization of their proteomes are essential to gain a better understanding of their role in phage biology. So far, about 2014 mycobacteriophages have been genomically defined and 1563 phage protein families (phamilies) are identified. However, the function of only a fraction (about 15%) is known and a majority of ORFs in phage genomes are hypothetical proteins. In this study, from the annotated genome of a F1 cluster mycobacteriophageSimranZ1, a putative AAA ATPase (Gp65, Pham 9410) is characterized as a DNA-dependent ATPase. Sequence-based functional annotation predicted Gp65 to belong to the P-loop NTPase superfamily, having AAA_24 and RecA/RadA domains which are known to be involved in ATP-dependent DNA repair/maintenance mechanism. On molecular docking, Gly21 and Ser23 of Gp65 showed specific binding with ATP. Using a microtiter plate assay, ATPase activity of Gp65 was experimentally verified which was found to increase in the presence of dsDNA. Gel electrophoresis under non-denaturing condition showed the oligomeric states of Gp65 and Transmission Electron Microscopy revealed it to exist as a hexamer having a prominent central pore with a diameter of 1.9 nm. In summary, functional characterization of Gp65 as a DNA dependent AAA ATPase indicates its role in DNA repair/maintenance mechanism in mycobacteriophages.
Direct Extraction of Signal and Noise Correlations from Two-Photon Calcium Imaging of Ensemble Neuronal Activity
Authors: Rupasinghe Anuththara , Francis Nikolas A , Liu Ji , Bowen Zac , Kanold Patrick O , Babadi Behtash 
Published: March 2021

AbstractNeuronal activity correlations are key to understanding how populations of neurons collectively encode information. While two-photon calcium imaging has created a unique opportunity to record the activity of large populations of neurons, existing methods for inferring correlations from these data face several challenges. First, the observations of spiking activity produced by two-photon imaging are temporally blurred and noisy. Secondly, even if the spiking data were perfectly recovered via deconvolution, inferring network-level features from binary spiking data is a challenging task due to the non-linear relation of neuronal spiking to endogenous and exogenous inputs. In this work, we propose a methodology to explicitly model and directly estimate signal and noise correlations from two-photon fluorescence observations, without requiring intermediate spike deconvolution. We provide theoretical guarantees on the performance of the proposed estimator and demonstrate its utility through applications to simulated and experimentally recorded data from the mouse auditory cortex.
A Proposal of New Feature Selection Method Sensitive to Outliers and Correlation
Authors: Demirarslan Mert , Suner Aslı 
Published: March 2021

AbstractIn disease diagnosis classification, ensemble learning algorithms enable strong and successful models by training more than one learning function simultaneously. This study aimed to eliminate the irrelevant variable problem with the proposed new feature selection method and compare the ensemble learning algorithms’ classification performances after eliminating the problems such as missing observation, classroom noise, and class imbalance that may occur in the disease diagnosis data. According to the findings obtained; In the preprocessed data, it was seen that the classification performance of the algorithms was higher than the raw version of the data. When the algorithms’ classification performances for the new proposed advanced t-Score and the old t-Score method were compared, the feature selection made with the proposed method showed statistically higher performance in all data sets and all algorithms compared to the old t-Score method (p = 0.0001).
Extracellular matrix gene expression signatures as cell type and cell state identifiers
Authors: Sacher Fabio , Feregrino Christian , Tschopp Patrick , Ewald Collin Y. 
Published: March 2021

AbstractTranscriptomic signatures based on cellular mRNA expression profiles can be used to categorize cell types and states. Yet whether different functional groups of genes perform better or worse in this process remains largely unexplored. Here we test the core matrisome - that is, all genes coding for structural proteins of the extracellular matrix - for its ability to delineate distinct cell types in embryonic single-cell RNA-sequencing (scRNA-seq) data. We show that even though expressed core matrisome genes correspond to less than 2% of an entire cellular transcriptome, their RNA expression levels suffice to recapitulate important aspects of cell type-specific clustering. Notably, using scRNA-seq data from the embryonic limb, we demonstrate that core matrisome gene expression outperforms random gene subsets of similar sizes and can match and exceed the predictive power of transcription factors. While transcription factor signatures generally perform better in predicting cell types at early stages of chicken and mouse limb development,i.e.,when cells are less differentiated, the information content of the core matrisome signature increases in more differentiated cells. Our findings suggest that each cell type produces its own unique extracellular matrix, or matreotype, which becomes progressively more refined and cell type-specific as embryonic tissues mature.HighlightsCell types produce unique extracellular matrix compositionsDynamic extracellular matrix gene expression profiles hold predictive power for cell type and cell state identification
Pheniqs 2.0: accurate, high performance Bayesian decoding and confidence estimation for combinatorial barcode indexing
Authors: Galanti Lior , Shasha Dennis , Gunsalus Kristin C. 
Published: March 2021

AbstractBackgroundSystems biology increasingly relies on deep sequencing with combinatorial index tags to associate biological sequences with their sample, cell, or molecule of origin. Accurate data interpretation depends on the ability to classify sequences based on correct decoding of these combinatorial barcodes. The probability of correct decoding is influenced by both sequence quality and the number and arrangement of barcodes. The rising complexity of experimental designs calls for a probability model that accounts for both sequencing errors and random noise, generalizes to multiple combinatorial tags, and can handle any barcoding scheme. The needs for reproducibility and community benchmark standards demand a peer-reviewed tool that preserves decoding quality scores and provides tunable control over classification confidence that balances precision and recall. Moreover, continuous improvements in sequencing throughput require a fast, parallelized and scalable implementation.ResultsWe developed a flexible, robustly engineered software that performs probabilistic decoding and supports arbitrarily complex barcoding designs. Pheniqs computes the full posterior decoding error probability of observed barcodes by consulting basecalling quality scores and prior distributions, and reports sequences and confidence scores in Sequence Alignment/Map (SAM) fields. The product of posteriors for multiple independent barcodes provides an overall confidence score for each read. Pheniqs achieves greater accuracy than minimum edit distance or simple maximum likelihood estimation, and it scales linearly with core count to enable the classification of >11 billion reads in 1h15m using <50 megabytes of memory. Pheniqs has been in production use for seven years in our genomics core facility.ConclusionsWe introduce a computationally efficient software that implements both probabilistic and minimum distance decoders and show that decoding barcodes using posterior probabilities is more accurate than available methods. Pheniqs allows fine-tuning of decoding sensitivity using intuitive confidence thresholds and is extensible with alternative decoders and new error models. Any arbitrary arrangement of barcodes is easily configured, enabling computation of combinatorial confidence scores for any barcoding strategy. An optimized multithreaded implementation assures that Pheniqs is faster and scales better with complex barcode sets than existing tools. Support for POSIX streams and multiple sequencing formats enables easy integration with automated analysis pipelines.
Plant generaCannabisandHumulusshare the same pair of well-differentiated sex chromosomes
Authors: Prentout D , Stajner N , Cerenak A , Tricou T , Brochier-Armanet C , Jakse J , Käfer J , Marais GAB 
Published: March 2021

SummaryWe recently described, inCannabis sativa, the oldest sex chromosome system documented so far in plants. Based on our estimate of its age, we predicted that it should be shared by its sister genusHumulus, which is known to also possess XY sex chromosomes.Here, we used transcriptome sequencing of a F1 family ofHumulus lupulusto identify and study the sex chromosomes in this species using the probabilistic method SEX-DETector.We identified 265 sex-linked genes inH. lupulus, located on the chromosome that is also theC. sativasex chromosome pair. Using phylogenies of sex-linked genes, we show that a region of these chromosomes had already stopped recombining in the common ancestor of the two species. Furthermore, as inC. sativa, Y gene expression was reduced in correlation to the position on the X chromosome, and strongly Y degenerated genes showed dosage compensation.Here we report, for the first time in the Angiosperms, a sex chromosome system that is shared by two different genera. Recombination suppression started at least 21-25 My ago, and then (either gradually or step-wise) spread to a large part of the sex chromosomes, leading to a strongly degenerated Y.
THINGSvision: a Python toolbox for streamlining the extraction of activations from deep neural networks
Authors: Muttenthaler Lukas , Hebart Martin N. 
Published: March 2021

AbstractOver the past decade, deep neural network (DNN) models have received a lot of attention due to their near-human object classification performance and their excellent prediction of signals recorded from biological visual systems. To better understand the function of these networks and relate them to hypotheses about brain activity and behavior, researchers need to extract the activations to images across different DNN layers. The abundance of different DNN variants, however, can often be unwieldy, and the task of extracting DNN activations from different layers may be non-trivial and error-prone for someone without a strong computational background. Thus, researchers in the fields of cognitive science and computational neuroscience would benefit from a library or package that supports a user in the extraction task.THINGSvisionis a new Python module that aims at closing this gap by providing a simple and unified tool for extracting layer activations for a wide range of pretrained and randomly-initialized neural network architectures, even for users with little to no programming experience. We demonstrate the general utility ofTHINGsvisionby relating extracted DNN activations to a number of functional MRI and behavioral datasets using representational similarity analysis, which can be performed as an integral part of the toolbox. Together,THINGSvisionenables researchers across diverse fields to extract features in a streamlined manner for their custom image dataset, thereby improving the ease of relating DNNs, brain activity, and behavior, and improving the reproducibility of findings in these research fields.
ChAdOx1 nCoV-19 (AZD1222) protects Syrian hamsters against SARS-CoV-2 B.1.351 and B.1.1.7
Authors: Fischer Robert J. , van Doremalen Neeltje , Adney Danielle R. , Yinda Claude Kwe , Port Julia R. , Holbrook Myndi G. , Schulz Jonathan E. , Williamson Brandi N. , Thomas Tina , Barbian Kent , Anzick Sarah L. , Ricklefs Stacy , Smith Brian J. , Long Dan , Martens Craig , Saturday Greg , de Wit Emmie , Gilbert Sarah C. , Lambe Teresa , Munster Vincent J. 
Published: March 2021

AbstractWe investigated ChAdOx1 nCoV-19 (AZD1222) vaccine efficacy against SARS-CoV-2 variants of concern (VOCs) B.1.1.7 and B.1.351 in Syrian hamsters. We previously showed protection against SARS-CoV-2 disease and pneumonia in hamsters vaccinated with a single dose of ChAdOx1 nCoV-19. Here, we observed a 9.5-fold reduction of virus neutralizing antibody titer in vaccinated hamster sera against B.1.351 compared to B.1.1.7. Vaccinated hamsters challenged with B.1.1.7 or B.1.351 did not lose weight compared to control animals. In contrast to control animals, the lungs of vaccinated animals did not show any gross lesions. Minimal to no viral subgenomic RNA (sgRNA) and no infectious virus was detected in lungs of vaccinated animals. Histopathological evaluation showed extensive pulmonary pathology caused by B.1.1.7 or B.1.351 replication in the control animals, but none in the vaccinated animals. These data demonstrate the effectiveness of the ChAdOx1 nCoV-19 vaccine against clinical disease caused by B.1.1.7 or B.1.351 VOCs.