bluuebunny/crossref_metadata_2025 huggingface dataset:
Linked deterioration of early visual perception, function and structure in healthy human aging
Authors: Silva Maria Fatima , Harvey Ben M , Jorge Lília , Canário Nádia , Machado Fátima , Soares Mário , Castelo-Branco Miguel
Published: August 2020

Low-level visual perception deteriorates during healthy aging. We hypothesized that age-related retinal and cortical structure deteriorations affect perception through specific disruptions of neural function. We measured perceptual visual acuity in fifty healthy adults aged 20-80 years. We then measured these participants’ early visual field map (V1, V2 and V3) functional population receptive field (pRF) sizes and structural surface areas using fMRI, and their retinal structure using high-definition optical coherence tomography. With increasing age visual acuity decreased, pRF sizes increased, visual field maps surface areas decreased, and retinal thickness decreased. Among these measures, only functional pRF sizes predicted perceptual visual acuity. PRF sizes were in turn predicted by cortical structure only (surface areas), which were only predicted by retinal structure (thickness). We propose that age-related retinal structural deterioration disrupts cortical structure, thereby disrupting cortical functional neural interactions that normally sharpen visual position selectivity: the resulting functional disruption underlies age-related perceptual deterioration.
DDR1-INDUCED NEUTROPHIL EXTRACELLULAR TRAPS DRIVE PANCREATIC CANCER METASTASIS
Authors: Deng Jenying , Kang Yaan , Cheng Chien-Chia , Li Xinqun , Dai Bingbing , Katz Matthew H. , Men Taoyan , Kim Michael P. , Koay Eugene A. , Huang Huocong , Brekken Rolf A. , Fleming Jason B.
Published: August 2020

Pancreatic ductal adenocarcinoma (PDAC) tumors are characterized by a desmoplastic reaction and dense collagen that is known to promote cancer progression. A central mediator of pro-tumorigenic collagen signaling is the receptor tyrosine kinase discoid domain receptor 1 (DDR1). DDR1 is a critical driver of a mesenchymal and invasive cancer cell PDAC phenotype. Previous studies have demonstrated that genetic or pharmacologic inhibition of DDR1 prevents PDAC tumorigenesis and metastasis. Here, we investigated whether DDR1 signaling has cancer cell non-autonomous effects that promote PDAC progression and metastasis. We demonstrate that collagen-induced DDR1 activation in cancer cells is a major stimulus for CXCL5 production, resulting in the recruitment of tumor-associated neutrophils (TANs), the formation of neutrophil extracellular traps (NETs) and subsequent cancer cell invasion and metastasis. Moreover, we have identified that collagen-induced CXCL5 production was mediated by a DDR1-PKCθ-SYK-NFκB signaling cascade. Together, these results highlight the critical contribution of collagen I-DDR1 interaction in the formation of an immune microenvironment that promotes PDAC metastasis.

Deng et al find that collagen signaling via DDR1 on human pancreatic cancer cells drives production and release of the cytokine, CXCL5, into systemic circulation. CXCL5 then triggers infiltration of neutrophils into the tumor where they promote cancer cell progression.
Neuron-intrinsic NF-κB Signaling Mediates Reovirus Virulence
Authors: Pruijssers Andrea J. , Taylor Gwen , Brigleb Pamela , Shang Pengcheng , Urbanek Kelly , Brown Judy J. , Dermody Terence S.
Published: August 2020

Pathological effects of apoptosis associated with viral infections of the central nervous system are an important cause of morbidity and mortality. Reovirus is a neurotropic virus that causes apoptosis in neurons, leading to lethal encephalitis in newborn mice. Reovirus-induced encephalitis is diminished in mice with germline ablation of NF-κB subunit p50. It is not known whether the pro-apoptotic function of NF-κB is mediated by neuron-intrinsic processes, NF-κB-regulated cytokine production by inflammatory cells, or a combination of both. To determine the contribution of cell type-specific NF-κB signaling in reovirus-induced neuronal injury, we established mice that lack NF-κB p65 expression in neurons using theCre/loxPrecombination system. Following intracranial inoculation of reovirus, 50% of wild-type (WT) mice succumbed to infection, whereas more than 90% of mice lacking neural NF-κB p65 (Nsp65−/−) mice survived. While viral loads in brains of WT and Nsp65−/−were comparable, histological analysis revealed that reovirus antigen-positive areas in the brain of WT mice displayed enhanced cleaved caspase-3 immunoreactivity, a marker of apoptosis, compared with Nsp65−/−mice. These data suggest that neuron-intrinsic NF-κB-dependent factors are essential mediators of reovirus neurovirulence. RNA sequencing analysis of reovirus-infected cortices of WT and Nsp65−/−mice suggests that NF-κB activation in neurons upregulates genes involved in innate immunity, inflammation, and cell death following reovirus infection. A better understanding of the contribution of cell type-specific NF-κB-dependent signaling to viral neuropathogenesis could inform development of new therapeutics that target and protect highly vulnerable cell populations
Dendrimer-targeted immunosuppression of microglia reactivity super-accelerates photoreceptor regeneration kinetics in the zebrafish retina
Authors: Emmerich Kevin B. , White David T. , Kambhampati Siva P. , Lee Grace Y. , Fu Tian-Ming , Sahoo Arpan , Saxena Meera T. , Betzig Eric , Kannan Rangaramanujam M. , Mumm Jeff S.
Published: August 2020

Müller glia (MG) function as injury-induced retinal stem cells in zebrafish but not mammals. Insights from zebrafish, however, have been used to stimulate limited regenerative responses from mammalian MG. Microglia/macrophages regulate MG stem cell activity in the chick, zebrafish and mouse. We previously showed that dexamethasone can accelerate retinal regeneration in zebrafish. Similarly, microglia ablation enhances regenerative outcomes in the mouse retina. Targeted immunomodulation may therefore enhance the regenerative potential of human MG. Nanoparticle-based immunomodulation is an emerging field with immense therapeutic potential. Here, we investigated how regeneration-enhancing dexamethasone treatments alter microglia behavior and how dendrimer-based targeting of dexamethasone to reactive microglia impact retinal regeneration kinetics. Intravital time-lapse imaging revealed specific dexamethasone-induced changes in microglia reactivity. Dendrimer-conjugated dexamethasone treatments resulted in: 1) decreased toxicity, 2) selective targeting of reactive microglia and, 3) “super-accelerated” retinal regeneration kinetics. These data support the use of dendrimer-based drug formulations for modulating microglia reactivity in degenerative disease contexts, especially as therapeutic strategies for promoting regenerative responses to neuronal cell loss.
Computational Model for Biological Neural Network for Localisation of Sound in the Vertical Plane
Authors: De Anandita , Cox Daniel
Published: August 2020

We build a computational rate model for a biological neural network found in mammals that is thought to be important in the localisation of the sound in the vertical plane. We find the response of neurons in the brain stem that participate in the localisation neural circuit to pure tones, broad band noise and notched noise and compare them to experimentally obtained response of these neurons. Our model is able to reproduce the sensitivity of these neurons in the brain stem to spectral properties of sounds that are important in localisation. This is the first rate based population model that elucidates all the response properties of the neurons in the vertical localisation pathway to our knowledge.
Musculoskeletal Model Personalization Affects Metabolic Cost Estimates for Walking
Authors: Arones Marleny , Shourijeh Mohammad , Patten Carolynn , Fregly Benjamin J.
Published: August 2020

Assessment of metabolic energy cost as a metric for human performance has expanded across various fields within the scientific, clinical, and engineering communities. As an alternative to measuring metabolic cost experimentally, musculoskeletal models incorporating metabolic cost models have been developed. However, to utilize these models for practical applications, the accuracy of their metabolic cost predictions requires improvement. Previous studies have reported the benefits of using personalized musculoskeletal models for various applications, yet no study has evaluated how model personalization affects metabolic cost estimation. This study investigated the effect of musculoskeletal model personalization on estimates of metabolic cost of transport (CoT) during post-stroke walking using three commonly used metabolic cost models. We analyzed data previously collected from two male stroke survivors with right-sided hemiparesis. The three metabolic cost models were implemented within three musculoskeletal modeling approaches involving different levels of personalization. The first approach used a scaled generic OpenSim model and found muscle activations via static optimization (SOGen). The second approach used a personalized EMG-driven musculoskeletal model with personalized functional axes but found muscle activations via static optimization (SOCal). The third approach used the same personalized EMG-driven model but calculated muscle activations directly from EMG data (EMGCal). For each approach, the muscle activation estimates were used to calculate each subject’s cost of transport (CoT) at different gait speeds using three metabolic cost models (Umberger 2003, Umberger 2010, and Bhargava 2004). The calculated CoT values were compared with published CoT trends as a function of stance time, double support time, step positions, walking speed, and severity of motor impairment (i.e., Fugl-Meyer score). Overall, U10-SOCal, U10-EMGCal, U03-SOCal, and U03-EMGCal were able to produce slopes between CoT and the different measures of walking asymmetry that were statistically similar to those found in the literature. Although model personalization seemed to improve CoT estimates, further tuning of parameters associated with the different metabolic cost models in future studies may allow for realistic CoT predictions. An improvement in CoT predictions may allow researchers to predict human performance, surgical, and rehabilitation outcomes reliably using computational simulations.
QTL mapping in an interspecific sorghum population uncovers candidate regulators of salinity tolerance
Authors: Hostetler Ashley N. , Govindarajulu Rajanikanth , Hawkins Jennifer S.
Published: August 2020

Salt stress impedes plant growth and disrupts normal metabolic processes, resulting in decreased biomass and increased leaf senescence. Therefore, the ability of a plant to maintain biomass when exposed to salinity stress is critical for the production of salt tolerant crops. To identify the genetic basis of salt tolerance in an agronomically important grain crop, we used a recombinant inbred line (RIL) population derived from an interspecific cross between domesticatedSorghum bicolor(inbred Tx7000) and a wild relative,Sorghum propinquum. A high-density genetic map was generated from 177 F3:5RILs and covered the 10Sorghumchromosomes with 1991 markers. The genetic map was used to identify 19 total QTL related to plant growth and overall health in optimal and saline conditions. Of these 19 QTL detected, 10 were specific to the salt stress response. The salt-responsive QTL contained numerous genes that have been previously shown to play a role in ionic tolerance, tissue tolerance, and osmotic tolerance, including many aquaporins.
MultiSurv: Long-term cancer survival prediction using multimodal deep learning
Authors: Vale-Silva Luís A. , Rohr Karl
Published: August 2020

The age of precision medicine demands powerful computational techniques to handle high-dimensional patient data. We present MultiSurv, a multimodal deep learning method for long-term pan-cancer survival prediction. MultiSurv is composed of three main modules. A feature representation module includes a dedicated submodel for each input data modality. A data fusion layer aggregates the multimodal representations. Finally, a prediction submodel yields conditional survival probabilities for a predefined set of follow-up time intervals. We trained MultiSurv on clinical, imaging, and four different high-dimensional omics data modalities from patients diagnosed with one of 33 different cancer types. We evaluated unimodal input configurations against several previous methods and different multimodal data combinations. MultiSurv achieved the best results according to different time-dependent metrics and delivered highly accurate long-term patient survival curves. The best performance was obtained when combining clinical information with either gene expression or DNA methylation data, depending on the evaluation metric. Additionally, MultiSurv can handle missing data, including missing values and complete data modalitites. Interestingly, for unimodal data we found that simpler modeling approaches, including the classical Cox proportional hazards method, can achieve results rivaling those of more complex methods for certain data modalities. We also show how the learned feature representations of MultiSurv can be used to visualize relationships between cancer types and individual patients, after embedding into a low-dimensional space.
A combined pipeline for quantitative analysis of human brain cytoarchitecture
Authors: Costantini Irene , Mazzamuto Giacomo , Roffilli Matteo , Laurino Annunziatina , Castelli Filippo Maria , Neri Mattia , Lughi Giovanni , Simonetto Andrea , Lazzeri Erica , Pesce Luca , Destrieux Christophe , Silvestri Ludovico , Conti Valerio , Guerrini Renzo , Pavone Francesco S.
Published: August 2020

The 3D analysis of the human brain architecture at cellular resolution is still a big challenge. In this work, we propose a pipeline that solves the problem of performing neuronal mapping in large human brain samples at micrometer resolution. First, we introduce the SWITCH/TDE protocol: a robust methodology to clear and label human brain tissue. Then, we implement the 2.5D method based on a Convolutional Neural Network, to automatically detect and segment all neurons. Our method proved to be highly versatile and was applied successfully on specimens from different areas of the cortex originating from different subjects (young, adult and elderly, both healthy and pathological). We quantitatively evaluate the density and, more importantly, the mean volume of the thousands of neurons identified within the specimens. In conclusion, our pipeline makes it possible to study the structural organization of the brain and expands the histopathological studies to the third dimension.
Morphologically constrained modeling of spinous inhibition in the somato-sensory cortex
Authors: Gemin Olivier , Serna Pablo , Assendorp Nora , Fossati Matteo , Rostaing Philippe , Triller Antoine , Charrier Cécile
Published: August 2020

Pyramidal neurons are covered by thousands of dendritic spines receiving excitatory synaptic inputs. The ultrastructure of dendritic spines shapes signal compartmentalization but ultrastructural diversity is rarely taken into account in computational models of synaptic integration. Here, we developed a 3D correlative light-electron microscopy (3D-CLEM) approach allowing the analysis of specific populations of synapses in genetically defined neuronal types in intact brain circuits. We used it to reconstruct segments of basal dendrites of layer 2/3 pyramidal neurons of adult mouse somatosensory cortex and quantify spine ultrastructural diversity. We found that 10% of spines were dually-innervated and 38% of inhibitory synapses localized to spines. Using our morphometric data to constrain a model of synaptic signal compartmentalization, we assessed the impact of spinous versus dendritic shaft inhibition. Our results indicate that spinous inhibition is locally more efficient than shaft inhibition and that it can decouple voltage and calcium signaling, potentially impacting synaptic plasticity.
Sequestration to lipid droplets promotes histone availability by preventing turnover of excess histones
Authors: Stephenson Roxan A. , Thomalla Jonathon M. , Chen Lili , Kolkhof Petra , Beller Mathias , Welte Michael A.
Published: August 2020

Because dearth and overabundance of histones result in cellular defects, histone synthesis and demand are typically tightly coupled. InDrosophilaembryos, histones H2B/H2A/H2Av accumulate on lipid droplets (LDs), cytoplasmic fat storage organelles. Without this binding, maternally provided H2B/H2A/H2Av are absent; however, the molecular basis of how LDs ensure histone storage is unclear. Using quantitative imaging, we uncover when during oogenesis these histones accumulate, and which step of accumulation is LD-dependent. LDs originate in nurse cells and are transported to the oocyte. Although H2Av accumulates on LDs in nurse cells, the majority of the final H2Av pool is synthesized in oocytes. LDs promote intercellular transport of the histone-anchor Jabba and thus its presence in the ooplasm. Jabba prevents ooplasmic H2Av from degradation, safeguarding the H2Av stockpile. Our findings provide insight into the mechanism for establishing histone stores duringDrosophilaoogenesis and shed light on the function of LDs as protein-sequestration sites.
Peptide Antidotes to SARS-CoV-2 (COVID-19)
Authors: Watson Andre , Ferreira Leonardo , Hwang Peter , Xu Jinbo , Stroud Robert
Published: August 2020

The design of an immunogenic scaffold that serves a role in treating a pathogen, and can be rapidly and predictively modeled, has remained an elusive feat.Here, we demonstrate that SARS-BLOCK™ synthetic peptide scaffolds act as antidotes to SARS-CoV-2 spike protein-mediated infection of human ACE2-expressing cells. Critically, SARS-BLOCK™ peptides are able to potently and competitively inhibit SARS-CoV-2 S1 spike protein receptor binding domain (RBD) binding to ACE2, the main cellular entry pathway for SARS-CoV-2, while also binding to neutralizing antibodies against SARS-CoV-2. In order to create this potential therapeutic antidote-vaccine, we designed, simulated, synthesized, modeled epitopes, predicted peptide folding, and characterized behavior of a novel set of synthetic peptides. The biomimetic technology is modeled off the receptor binding motif of the SARS-CoV-2 coronavirus, and modified to provide enhanced stability and folding versus the truncated wildtype sequence. These novel peptides attain single-micromolar binding affinities for ACE2 and a neutralizing antibody against the SARS-CoV-2 receptor binding domain (RBD), and demonstrate significant reduction of infection in nanomolar doses. We also demonstrate that soluble ACE2 abrogates binding of RBD to neutralizing antibodies, which we posit is an essential immune-evasive mechanism of the virus. SARS-BLOCK™ is designed to “uncloak” the viral ACE2 coating mechanism, while also binding to neutralizing antibodies with the intention of stimulating a specific neutralizing antibody response. Our peptide scaffolds demonstrate promise for future studies evaluating specificity and sensitivity of immune responses to our antidote-vaccine. In summary, SARS-BLOCK™ peptides are a promising COVID-19 antidote designed to combine the benefits of a therapeutic and vaccine, effectively creating a new generation of prophylactic and reactive antiviral therapeutics whereby immune responses can be enhanced rather than blunted.
Landscape genetics and species delimitation in the Andean palm rocket frog,Rheobatesspp
Authors: Genty Gabrielle , Guarnizo Carlos E. , Ramírez Juan P. , Barrientos Lucas , Crawford Andrew J.
Published: August 2020

The complex topography of the species-rich northern Andes creates heterogeneous environmental landscapes that are hypothesized to have promoted population fragmentation and diversification by vicariance, gradients and/or the adaptation of species. Previous phylogenetic work on the Palm Rocket Frog (Anura: Aromobatidae:Rheobatesspp.), endemic to mid-elevation forests of Colombia, suggested valleys were important in promoting divergence between lineages. In this study, we use a spatially, multi-locus population genetic approach of two mitochondrial and four nuclear genes from 25 samples representing the complete geographic range of the genus to delimit species and test for landscape effects on genetic divergence withinRheobates. We tested three landscape genetic models: isolation by distance, isolation by resistance, and isolation by environment. Bayesian species delimitation (BPP) and a Poisson Tree Process (PTP) model both recovered five highly divergent genetic lineages withinRheobates, rather than the three inferred in a previous study. We found that an isolation by environment provided the only variable significantly correlated with genetic distances for both mitochondrial and nuclear genes, suggesting that local adaptation may have a role driving the genetic divergence within this genus of frogs. Thus, genetic divergence inRheobatesmay be driven by the local environments where these frogs live, even more so that by the environmental characteristics of the intervening regions among populations (i.e., geographic barriers).
High-resolution mapping ofRym14Hb, a wild relative resistance gene to barley yellow mosaic disease
Authors: Pidon Hélène , Wendler Neele , Habekuβ Antje , Maasberg Anja , Ruge-Wehling Brigitte , Perovic Dragan , Ordon Frank , Stein Nils
Published: August 2020

Barley yellow mosaic disease is caused by Barley yellow mosaic virus and Barley mild mosaic virus, and leads to severe yield losses in barley (Hordeum vulgare) in Central Europe and East-Asia. Several resistance loci are used in barley breeding. However, cases of resistance-breaking viral strains are known, raising concerns about the durability of those genes.Rym14Hbis a dominant major resistance gene on chromosome 6HS, originating from barley’s secondary genepool wild relativeHordeum bulbosum. As such, the resistance mechanism may represent a case of non-host resistance, which could enhance its durability. A susceptible barley variety and a resistantH. bulbosumintrogression line were crossed to produce a large F2mapping population (n=7,500), to compensate for a ten-fold reduction in recombination rate compared to intraspecific barley crosses. After high-throughput genotyping, theRym14Hblocus was assigned to a 2Mbp telomeric interval on chromosome 6HS. The co-segregating markers developed in this study can be used for marker-assisted introgression of this locus into barley elite germplasm with a minimum of linkage drag.
matchms - processing and similarity evaluation of mass spectrometry data
Authors: Huber Florian , Verhoeven Stefan , Meijer Christiaan , Spreeuw Hanno , Castilla Efraín Manuel Villanueva , Geng Cunliang , van der Hooft Justin J. J. , Rogers Simon , Belloum Adam , Diblen Faruk , Spaaks Jurriaan H.
Published: August 2020

Mass spectrometry data is at the heart of numerable applications in the biomedical and life sciences. With growing use of high throughput techniques researchers need to analyse larger and more complex datasets. In particular through joint effort in the research community, fragmentation mass spectrometry datasets are growing in size and number. Platforms such as MassBank (Horai et al. 2010), GNPS (Wang et al. 2016) or MetaboLights (Haug et al. 2020) serve as an open-access hub for sharing of raw, processed, or annotated fragmentation mass spectrometry data (MS/MS). Without suitable tools, however, exploitation of such datasets remains overly challenging. In particular, large collected datasets contain data aquired using different instruments and measurement conditions, and can further contain a significant fraction of inconsistent, wrongly labeled, or incorrect metadata (annotations).
Opposing functions of the plantTOPLESSgene family during SNC1-mediated autoimmunity
Authors: Garner Christopher M. , Spears Benjamin J. , Su Jianbin , Cseke Leland , Smith Samantha N. , Rogan Conner J. , Gassmann Walter
Published: August 2020

Regulation of the plant immune system is important for controlling the specificity and amplitude of responses to pathogens and in preventing growth-inhibiting autoimmunity that leads to reductions in plant fitness. In previous work, we reported that SRFR1, a negative regulator of effector-triggered immunity, interacts with SNC1 and EDS1. WhenSRFR1is non-functional in the Arabidopsis accession Col-0,SNC1levels increase, causing a cascade of events that lead to autoimmunity phenotypes. Previous work showed that some members of the transcriptional co-repressor family TOPLESS interact with SNC1 to repress negative regulators of immunity. Therefore, to explore potential connections betweenSRFR1andTOPLESSfamily members, we took a genetic approach that examined the effect of eachTOPLESSmember in thesrfr1mutant background. The data indicated that an additive genetic interaction exists betweenSRFR1and two members of theTOPLESSfamily,TPR2andTPR3, as demonstrated by increased stunting and elevatedPR2expression insrfr1 tpr2andsrfr1 tpr2 tpr3mutants. Furthermore, thetpr2mutation intensifies autoimmunity in the auto-activesnc1-1mutant, indicating a novel role of theseTOPLESSfamily members in negatively regulatingSNC1-dependent phenotypes. This negative regulation can also be reversed by overexpressingTPR2in thesrfr1 tpr2background. Thus, this work uncovers diverse functions of individual members of the TOPLESS family in Arabidopsis and provides evidence for the additive effect of transcriptional and post-transcriptional regulation ofSNC1.

Author Summary

The immune system is a double-edged sword that affords organisms with protection against infectious diseases but can also lead to negative effects if not properly controlled. Plants only possess an innate antimicrobial immune system that relies on rapid upregulation of defenses once immune receptors detect the presence of microbes. Plant immune receptors known as resistance proteins play a key role in rapidly triggering defenses if pathogens breach other defenses. A common model of unregulated immunity in the reference Arabidopsis variety Columbia-0 involves a resistance gene calledSNC1. When the SNC1 protein accumulates to unnaturally high levels or possesses auto-activating mutations, the visible manifestations of immune overactivity include stunted growth and low biomass and seedset. Consequently, expression of this gene and accumulation of the encoded protein are tightly regulated on multiple levels. Despite careful study the mechanisms ofSNC1gene regulation are not fully understood. Here we present data on members of the well-known TOPLESS family of transcriptional repressors. While previously characterized members were shown to function in indirect activation of defenses, TPR2 and TPR3 are shown here to function in preventing high defense activity. This study therefore contributes to the understanding of complex regulatory processes in plant immunity.
Classic articles in Apoptotic Research: A Bibliometric Analysis
Authors: Jallow Amadou W. , Lee Shin-Da , Ho Yuh-Shan
Published: August 2020

Background

Classic articles are defined as research papers with a total citation of one thousand or more. The present study is to identify and analyse the characteristics of the classic articles in apoptosis research.

Method

Classic articles with total of 1,000 or more citations from Web of Science Core Collection since year of publication to the end of 2017 were basically assessed regarding their document types, languages, journals, and Web of Science categories within 1900 to 2017.

Result

The study showed 418 classic documents in apoptotic research including 260 articles published between 1972 and 2012. The most productive Web of Science category was multidisciplinary sciences.Naturepublished most of these classic articles followed byCell, andScience. The most productive country and institution were United States and Harvard University respectively. The author S.J. Korsmeyer from Harvard University was the most productive in apoptosis field and published 13 classic apoptosis articles while the author J.C Reed had more potential to publish classic apoptosis articles in future. The author J.C. Reed and V.A. Fadok had equal potential to publish the same number of classic articles as first- and corresponding-author. Article of Kerr et al. in 1972 was the most popular and cited apoptosis article. The most impact article in 2017 was article entitled “Tumor-associated B7-H1 promotes T-cell apoptosis: A potential mechanism of immune evasion” by Dong et al. in 2002.

Conclusion

This study seems to identify the most industrious authors, institutions, and countries in the field of apoptosis research. It also tends to reveal the historical and discoveries related to the pathophysiology of apoptosis as well as the most impact publications on apoptosis studies.
Single amino acid mutations effect Zika virus replicationin vitroand virulencein vivo
Authors: Collette Nicole M. , Lao Victoria H.I. , Weilhammer Dina R. , Zingg Barbara , Cohen Shoshana D. , Hwang Mona , Coffey Lark L. , Grady Sarah L. , Zemla Adam T. , Borucki Monica K.
Published: August 2020

The 2014-2016 Zika virus (ZIKV) epidemic in the Americas resulted in large deposits of next-generation sequencing data from clinical samples. This resource was mined to identify emerging mutations and trends in mutations as the outbreak progressed over time. Information on transmission dynamics, prevalence and persistence of intra-host mutants, and the position of a mutation on a protein were then used to prioritize 544 reported mutations based on their ability to impact ZIKV phenotype. Using this criteria, six mutants (representing naturally occurring mutations) were generated as synthetic infectious clones using a 2015 Puerto Rican epidemic strain PRVABC59 as the parental backbone. The phenotypes of these naturally occurring variants were examined using both cell culture and murine model systems. Mutants had distinct phenotypes, including changes in replication rate, embryo death, and decreased head size. In particular, a NS2B mutant previously detected duringin vivostudies in rhesus macaques was found to cause lethal infections in adult mice, abortions in pregnant females, and increased viral genome copies in both brain tissue and blood of female mice. Additionally, mutants with changes in the region of NS3 that interfaces with NS5 during replication displayed reduced replication in the blood of adult mice. This analytical pathway, integrating both bioinformatic and wet lab experiments, provides a foundation for understanding how naturally occurring single mutations affect disease outcome and can be used to predict the of severity of future ZIKV outbreaks.

Author summary

To determine if naturally occurring individual mutations in the Zika virus epidemic genotype effect viral virulence or replication ratein vitroorin vivo, we generated an infectious clone representing the epidemic genotype of stain Puerto Rico, 2015. Using this clone, six mutants were created by changing nucleotides in the genome to cause one to two amino acid substitutions in the encoded proteins. The six mutants we generated represent mutations that differentiated the early epidemic genotype from genotypes that were either ancestral or that occurred later in the epidemic. We assayed each mutant for changes in growth rate, and for virulence in adult mice and pregnant mice. Three of the mutants caused catastrophic embryo effects including increased embryonic death or significant decrease in head diameter. Three other mutants that had mutations in a genome region associated with replication resulted in changes inin vitroandin vivoreplication rates. These results illustrate the potential impact of individual mutations in viral phenotype.
Genetic Disruption of WASHC4 Drives Endo-lysosomal Dysfunction and Cognitive-Movement Impairments in Mice and Humans
Authors: Courtland Jamie L. , Bradshaw Tyler W. A. , Waitt Greg , Soderblom Erik J. , Ho Tricia , Rajab Anna , Vancini Ricardo , Kim Hwan , Soderling Scott H.
Published: August 2020

Mutation of the WASH complex subunit, SWIP, is implicated in human intellectual disability, but the cellular etiology of this association is unknown. We identify the neuronal WASH complex proteome, revealing a network of endosomal proteins. To uncover how dysfunction of endosomal SWIP leads to disease, we generate a mouse model of the humanWASHC4c.3056C>Gmutation. Quantitative spatial proteomics analysis of SWIPP1019Rmouse brain reveals that this mutation destabilizes the WASH complex and uncovers significant perturbations in both endosomal and lysosomal pathways. Cellular and histological analyses confirm that SWIPP1019Rresults in endo-lysosomal disruption and uncover indicators of neurodegeneration. We find that SWIPP1019Rnot only impacts cognition, but also causes significant progressive motor deficits in mice. Remarkably, a retrospective analysis of SWIPP1019Rpatients confirms motor deficits in humans. Combined, these findings support the model that WASH complex destabilization, resulting from SWIPP1019R, drives cognitive and motor impairments via endo-lysosomal dysfunction in the brain.
Confidence-controlled Hebbian learning efficiently extracts category membership from stimuli encoded in view of a categorization task
Authors: Berlemont Kevin , Nadal Jean-Pierre
Published: August 2020

Abstract

In experiments on perceptual decision-making, individuals learn a categorization task through trial-and-error protocols. We explore the capacity of a decision-making attractor network to learn a categorization task through reward-based, Hebbian type, modifications of the weights incoming from the stimulus encoding layer. For the latter, we assume a standard layer of a large number of stimulus specific neurons. Within the general framework of Hebbian learning, authors have hypothesized that the learning rate is modulated by the reward at each trial. Surprisingly, we find that, when the coding layer has been optimized in view of the categorization task, such reward-modulated Hebbian learning (RMHL) fails to extract efficiently the category membership. In a previous work we showed that the attractor neural networks nonlinear dynamics accounts for behavioral confidence in sequences of decision trials. Taking advantage of these findings, we propose that learning is controlled by confidence, as computed from the neural activity of the decision-making attractor network. Here we show that this confidence-controlled, reward-based, Hebbian learning efficiently extracts categorical information from the optimized coding layer. The proposed learning rule is local, and, in contrast to RMHL, does not require to store the average rewards obtained on previous trials. In addition, we find that the confidence-controlled learning rule achieves near optimal performance.
Similarities and dissimilarities between psychiatric cluster disorders
Authors: Smail Marissa A. , Wu Xiaojun , Henkel Nicholas D. , Eby Hunter M. , Herman James P. , McCullumsmith Robert E. , Shukla Rammohan
Published: August 2020

The common molecular mechanisms underlying psychiatric disorders are not well understood. Prior attempts to assess the pathological mechanisms responsible for psychiatric disorders have been limited by biased selection of comparable disorders, datasets as well as challenges associated with data normalization. However, publicly available databases offer a unique opportunity to expand such investigations both in terms of the number and types of diseases. Here, we used DisGeNET, a database of over 24,000 gene-disease associations to investigate the similarities and dissimilarities associated with enrichment of pathways, cell-types, drug targets, and human chromosomes within an unbiased cluster of psychiatric disorders. We show that cognition and neurotransmission related pathways are involved across all disorders, whereas those associated with immune system and signal-response coupling (cell-surface receptors, signal-transduction, gene-expression, and metabolic process) are associated with few disorders of the cluster. The drug-target based enrichment confirms the involvement of neurotransmission related changes across these disorders. At cell-type level, dendrite targeting interneurons, across all layers, are most involved across all disorders. Finally, using a clustering-based similarity index, we showed that the similarity between the disorders are influenced most at chromosomal level and to some extent at cellular level. Collectively, the results provide a comprehensive comparison of many psychiatric diseases in an unbiased manner and expand our understanding of the cellular and molecular pathologies associated with similar and comorbid psychiatric disorders.
Somatosensory versus cerebellar contributions to proprioceptive changes associated with motor skill learning: A theta burst stimulation study
Authors: Mirdamadi Jasmine L. , Block Hannah J.
Published: August 2020

Background

It is well established that proprioception (position sense) is important for motor control, yet its role in motor learning and associated plasticity is not well understood. We previously demonstrated that motor skill learning is associated with enhanced proprioception and changes in sensorimotor neurophysiology. However, the neural substrates mediating these effects are unclear.

Objective

To determine whether suppressing activity in the cerebellum and somatosensory cortex (S1) affects proprioceptive changes associated with motor skill learning.

Methods

54 healthy young adults practiced a skill involving visually-guided 2D reaching movements through an irregular-shaped track using a robotic manipulandum with their right hand. Proprioception was measured using a passive two-alternative choice task before and after motor practice. Continuous theta burst stimulation (cTBS), was delivered over S1 or the cerebellum (CB) at the end of training for two consecutive days. We compared group differences (S1, CB, Sham) in proprioception and motor skill, quantified by a speed-accuracy function, measured on a third consecutive day (retention).

Results

As shown previously, the Sham group demonstrated enhanced proprioceptive sensitivity after training and at retention. The S1 group had impaired proprioceptive function at retention through online changes during practice, whereas the CB group demonstrated offline decrements in proprioceptive function. All groups demonstrated motor skill learning, however, the magnitude of learning differed between the CB and Sham groups, consistent with a role for the cerebellum in motor learning.

Conclusion

Overall, these findings suggest that the cerebellum and S1 are important for distinct aspects of proprioceptive changes during skill learning.
Nutrient dominance governs the assembly of microbial communities in mixed nutrient environments
Authors: Estrela Sylvie , Sanchez-Gorostiaga Alicia , Vila Jean C.C. , Sanchez Alvaro
Published: August 2020

A major open question in microbial community ecology is whether we can predict how the components of a diet collectively determine the taxonomic composition of microbial communities. Motivated by this challenge, we investigate whether communities assembled in pairs of nutrients can be predicted from those assembled in every single nutrient alone. We first find that although the null, naturally additive model generally predicts well the family-level community composition, there exist systematic deviations from the additive predictions that reflect generic patterns of nutrient dominance at the family-level. Pairs of more similar nutrients (e.g. two sugars) are on average more additive than pairs of more dissimilar nutrients (one sugar-one organic acid). Second, a simple dominance rule emerges: sugars generally dominate organic acids. These findings may be explained by family-level asymmetries in nutrient benefits. Overall, our results suggest that regularities in how nutrients interact may help predict communities responses to dietary changes.
Cutting across structural and transcriptomic scales translates time across the lifespan and resolves frontal cortex development in human evolution
Authors: Charvet Christine J.
Published: August 2020

How the unique capacities of human cognition arose in evolution is a question of enduring interest. It is still unclear which developmental programs are responsible for the emergence of the human brain. The inability to determine corresponding ages between humans and apes has hampered progress in detecting developmental programs leading to the emergence of the human brain. I harness temporal variation in anatomical, behavioral, and transcriptional variation to determine corresponding ages from fetal to postnatal development and aging, between humans and chimpanzees. This multi-dimensional approach results in 137 corresponding time points across the lifespan, from embryonic day 44 to ∼55 years of age, in humans and their equivalent ages in chimpanzees. I used these data to test whether developmental programs, such as the timeline of prefrontal cortex maturation, previously claimed to differ between humans and chimpanzees, do so once variation in developmental schedules is controlled for. I compared the maturation of frontal cortex projections from structural magnetic resonance (MR) scans and from temporal variation in the expression of genes used to track long-range projecting neurons (i.e., supragranular-enirhced genes) in chimpanzees and humans. Contrary to what has been suggested, the timetable of prefrontal cortex maturation is not unusually extended in humans. This dataset, which is the largest with which to determine corresponding ages across humans and chimpanzees, provides a rigorous approach to control for variation in developmental schedules and to identify developmental programs responsible for unique features of the human brain.
An Organotypic Mammary Duct Model Capturing Distinct Events of DCIS Progression
Authors: Kulwatno Jonathan , Gong Xiangyu , DeVaux Rebecca , Herschkowitz Jason I. , Mills Kristen Lynn
Published: August 2020

Ductal carcinomain situ(DCIS) is a pre-cancerous stage breast cancer, where abnormal cells are contained within the duct, but have not invaded into the surrounding tissue. However, only 30-40% of DCIS cases are likely to progress into an invasive ductal carcinoma (IDC), while the remainder are innocuous. Since little is known about what contributes to the transition from DCIS to IDC, clinicians and patients tend to opt for treatment, leading to concerns of overdiagnosis and overtreatment.In vitromodels are currently being used to probe how DCIS transitions into IDC, but many models do not take into consideration the macroscopic tissue architecture and the biomechanical properties of the microenvironment. Here, we developed an organotypic mammary duct model by molding a channel within a collagen matrix and lining it with a basement membrane. By adjusting the concentration of collagen, we effectively modulated the stiffness and morphological properties of the matrix and examined how an assortment of breast cells responded to changing density and stiffness of the matrix. We first validated the model using two established, phenotypically divergent breast cancer cell lines by demonstrating the ability of the cells to either invade (MDA-MB-231) or cluster (MCF7). We then examined how cells of the isogenic MCF10 series—spanning the range from healthy to aggressive—behaved within our model and observed distinct characteristics of breast cancer progression such as hyperplasia and invasion, in response to collagen concentration. Our results show that the model can recapitulate different stages of breast cancer progression and that the MCF10 series is adaptable to physiologically relevantin vitrostudies, demonstrating the potential of both the model and cell lines to elucidate key factors that may contribute to understanding the transition from DCIS to IDC.

IMPACT STATEMENT

The success of early preventative measures for breast cancer has left patients susceptible to overdiagnosis and overtreatment. Limited knowledge of factors driving an invasive transition has inspired the development ofin vitromodels that accurately capture this phenomenon. However, current models tend to neglect the macroscopic architecture and biomechanical properties of the mammary duct. Here, we introduce an organotypic model that recapitulates the cylindrical geometry of the tissue and the altered stroma seen in tumor microenvironments. Our model was able to capture distinct features associated with breast cancer progression, demonstrating its potential to uncover novel insights into disease progression.
Inhibition of SARS-CoV-2 polymerase by nucleotide analogs: a single molecule perspective
Authors: Seifert Mona , Bera Subhas Chandra , van Nies Pauline , Kirchdoerfer Robert N. , Shannon Ashleigh , Le Thi-Tuyet-Nhung , Meng Xiangzhi , Xia Hongjie , Wood James M. , Harris Lawrence D. , Papini Flávia S. , Arnold Jamie J. , Almo Steven C. , Grove Tyler L. , Shi Pei-Yong , Xiang Yan , Canard Bruno , Depken Martin , Cameron Craig E. , Dulin David
Published: August 2020

The nucleotide analog Remdesivir (RDV) is the only FDA-approved antiviral therapy to treat infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The physical basis for efficient utilization of RDV by SARS-CoV-2 polymerase is unknown. Here, we characterize the impact of RDV and other nucleotide analogs on RNA synthesis by the polymerase using a high-throughput, single-molecule, magnetic-tweezers platform. The location of the modification in the ribose or in the base dictates the catalytic pathway(s) used for its incorporation. We reveal that RDV incorporation does not terminate viral RNA synthesis, but leads the polymerase into deep backtrack, which may appear as termination in traditional ensemble assays. SARS-CoV-2 is able to evade the endogenously synthesized product of the viperin antiviral protein, ddhCTP, though the polymerase incorporates this nucleotide analog well. This experimental paradigm is essential to the discovery and development of therapeutics targeting viral polymerases.

Teaser

We revise Remdesivir’s mechanism of action and reveal SARS-CoV-2 ability to evade interferon-induced antiviral ddhCTP
Ubiquitous selfish toxin-antidote elements inCaenorhabditisspecies
Authors: Ben-David Eyal , Pliota Pinelopi , Widen Sonya A. , Koreshova Alevtina , Lemus-Vergara Tzitziki , Verpukhovskiy Philipp , Mandali Sridhar , Braendle Christian , Burga Alejandro , Kruglyak Leonid
Published: August 2020

Toxin-antidote elements (TAs) are selfish genetic dyads that spread in populations by selectively killing non-carriers. TAs are common in prokaryotes, but few examples are known in animals. We discovered five maternal-effect TAs in the nematodeCaenorhabditis tropicalisand one inC. briggsae. Unlike previously reported TAs, five of these novel toxins do not kill embryos but instead cause larval arrest or developmental delay. We identified the genes underlying a TA causing developmental delay,slow-1/grow-1, and found that the toxin,slow-1,is homologous to nuclear hormone receptors. Last, we found that balancing selection of conflicting TAs hampers their ability to drive in populations, leading to more stable genetic incompatibilities. Our results show that TAs are common inCaenorhabditisspecies, target a wide range of developmental processes, and may act as barriers preventing gene flow.