bluuebunny/crossref_metadata_2025_split huggingface dataset:
An increase in dendritic plateau potentials is associated with experience-dependent cortical map reorganization
Authors: Pages Stéphane , Chenouard Nicolas , Chéreau Ronan , Kouskoff Vladimir , Gambino Frédéric , Holtmaat Anthony 
Published: July 2020

ABSTRACTThe organization of sensory maps in the cerebral cortex depends on experience, which drives homeostatic and long-term synaptic plasticity of cortico-cortical circuits. In the mouse primary somatosensory cortex (S1) afferents from the higher-order, posterior medial thalamic nucleus (POm) gate synaptic plasticity in layer (L) 2/3 pyramidal neurons via disinhibition and the production of dendritic plateau potentials. Here we address whether these thalamocortically mediated responses play a role in whisker map plasticity in S1. We find that trimming all but two whiskers causes a partial fusion of the representations of the two spared whiskers, concomitantly with an increase in the occurrence of POm-driven, N-methyl-D-aspartate receptor (NMDAR)-dependent plateau potentials. Blocking the plateau potentials restores the archetypical organization of the sensory map. Our results reveal a novel mechanism for experience-dependent cortical map plasticity in which higher-order thalamocortically mediated plateau potentials facilitate the fusion of normally segregated cortical representations.
Liquid-liquid phase separation driven compartmentalization of reactive nucleoplasm
Authors: Laghmach Rabia , Potoyan Davit A 
Published: July 2020

AbstractThe nucleus of eukaryotic cells harbors active and out of equilibrium environments conducive to diverse gene regulatory processes. On a molecular scale, gene regulatory processes take place within hierarchically compartmentalized sub-nuclear bodies. While the impact of nuclear structure on gene regulation is widely appreciated, it has remained much less clear whether and how gene regulation is impacting nuclear order itself. Recently, the liquid-liquid phase separation emerged as a fundamental mechanism driving the formation of biomolecular condensates, including membrane-less organelles, chromatin territories, and transcriptional domains. The transience and environmental sensitivity of biomolecular condensation are strongly suggestive of kinetic gene-regulatory control of phase separation. To better understand kinetic aspects controlling biomolecular phase-separation, we have constructed a minimalist model of the reactive nucleoplasm. The model is based on the Cahn-Hilliard formulation of ternary protein-RNA-nucleoplasm components coupled to non-equilibrium and spatially dependent gene expression. We find a broad range of kinetic regimes through an extensive set of simulations where the interplay of phase separation and reactive timescales can generate heterogeneous multi-modal gene expression patterns. Furthermore, the significance of this finding is that heterogeneity of gene expression is linked directly with the heterogeneity of length-scales in phase-separated condensates.
Overexpression of HLA class I predominantly on alpha cell in at risk individuals for type 1 diabetes
Authors: Benkahla Mehdi A. , Sabouri Somayeh , Kiosses William B. , Rajendran Sakthi , Quesada-Masachs Estefania , von Herrath Matthias 
Published: July 2020

AbstractHuman leukocyte antigens of class-I (HLA-I) molecules are hyper-expressed in insulin-containing islets (ICI) of type 1 diabetic (T1D) donors. This study investigated the HLA-I expression in autoantibody positive (AAB+) donors and more closely defined its intra-islet and intracellular localization as well as proximity to infiltrating CD8 T cells with high-resolution confocal microscopy. We found HLA-I hyper-expression had already occurred prior to clinical diagnosis of T1D in islets of AAB+ donors. Interestingly, throughout all stages of disease, HLA-I was mostly expressed by alpha cells. Hyper-expression in AAB+ and T1D donors was associated with intra-cellular accumulation in the Golgi. Proximity analysis showed a moderate but significant correlation between HLA-I and infiltrating CD8 T cells only in ICI of T1D donors, but not in AAB+ donors. These observations not only demonstrate a very early, islet-intrinsic immune-independent increase of HLA-I during diabetes pathogenesis, but also point towards a role for alpha cells in T1D.SummaryHuman leukocyte antigens of class-I (HLA-I) are hyper-expressed in insulin-containing islets of type 1 diabetic (T1D) donors. This study finds HLA-I hyper-expression occurs prior to clinical diagnosis of T1D in islets of autoantibody-positive donors and mostly expressed by alpha cells.
Spontaneous alpha-band amplitude predicts subjective visibility but not discrimination accuracy during high-level perception
Authors: Samaha Jason , LaRocque Joshua J. , Postle Bradley R. 
Published: July 2020

AbstractNear-threshold perception is a paradigm case of perceptual reports diverging from reality – perception of an unchanging stimulus can vacillate from undetected to clearly perceived. Among the many factors that predict whether a stimulus will reach awareness, the amplitude of low-frequency brain oscillations - particularly in the alpha frequency band (8-13 Hz) - has emerged as a reliable predictor of trial-to-trial variability in perceptual decisions. Analysis grounded in signal detection theory suggest that strong prestimulus alpha oscillations diminish subjective perception without affecting the accuracy or sensitivity (d’) of perceptual decisions. These results, coupled with recent studies on sensory responses, point to an inhibitory influence of alpha-band amplitude on early visuocortical activity. The findings to date have been based on simple, low-level visual stimuli, which warrant a focus on early visual processing. However, the physiology of alpha in higher-level visual areas is known to be distinct from early visual cortex, with evidence indicating that alpha amplitude in the inferior temporal (IT) cortex is excitatory (rather than inhibitory, as in early visual cortex). Here, we addressed the question of how spontaneous oscillatory amplitude impacts subjective and objective aspects of perception using a high-level perceptual decision task. Human observers completed a near-threshold face/house discrimination task with subjective visibility ratings while electroencephalograms (EEG) were recorded. Using a single-trial multiple regression analysis, we found that spontaneous fluctuations in pre-stimulus alpha-band amplitude were negatively related to visibility ratings but did not predict trial-by-trial accuracy. These results suggest that the inhibitory influence of prestimulus alpha activity in early visual cortex, rather than the excitatory influence of alpha in IT, comes to bias high-level perceptual reports. Our findings provide further evidence that ongoing alpha amplitude dissociates subjective and objective measures of visual perception.
Photochemical NOT Gate for DNA Computing
Authors: Emanuelson Cole , Bardhan Anirban , Deiters Alexander 
Published: July 2020

AbstractDNA-based Boolean logic gates (AND, OR and NOT) can be assembled into complex computational circuits that generate an output signal in response to specific patterns of oligonucleotide inputs. However, the fundamental nature of NOT gates, which convert the absence of an input into an output, makes their implementation within DNA-based circuits difficult. Premature execution of a NOT gate before completion of its upstream computation introduces an irreversible error into the circuit. We developed a novel DNA gate design utilizing photocaging groups that prevents gate function until irradiation at a certain time-point. Optical activation provides temporal control over circuit performance by preventing premature computation and is orthogonal to all components of DNA computation devices. Using this approach, we designed NAND and NOR logic gates that respond to synthetic microRNA inputs. We further demonstrate the utility of the NOT gate within multi-layer circuits in response to a specific pattern of four microRNAs.
Roles of motor on-rate and cargo mobility in intracellular transport
Authors: Bovyn Matthew J. , Reddy Babu J.N. , Gross Steven P. , Allard Jun F. 
Published: July 2020

AbstractMolecular motors like kinesin are critical for cellular organization and biological function including in neurons. There is detailed understanding of how they move and how factors such as applied force and the presence of microtubule-associated proteins can alter this single-motor travel. In order to walk, the cargo-motor complex must first attach to a microtubule. This attachment process is less studied. Here, we use a combination of single-molecule bead experiments, modeling, and simulation to examine how cargos with kinesin-1 bind to microtubules. In experiment, we find that increasing cargo size and environment viscosity both signficantly slow cargo binding time. We use modeling and simulation to examine how the single motor on rate translates to the on rate of the cargo. Combining experiment and modeling allows us to estimate the single motor on rate as 100 s−1. This is a much higher value than previous estimates. We attribute the difference between our measurements and previous estimates to two factors: first, we are directly measuring initial motor attachment (as opposed to re-binding of a second motor) and second, the theoretical framework allows us to account for missed events (i.e. binding events not detected by the experiments due to their short duration). This indicates that the mobility of the cargo itself, determined by its size and interaction with the cytoplasmic environment, play a previously underestimated role in determining intracellular transport kinetics.
Development of a data-driven COVID-19 prognostication tool to inform triage and step-down care for hospitalised patients in Hong Kong: A population-based cohort study
Authors: Tsui Eva L.H. , Lui Carrie S.M. , Woo Pauline P.S. , Cheung Alan T.L. , Lam Peggo K.W. , Tang Van T.W. , Yiu C.F. , Wan C.H. , Lee Libby H.Y. 
Published: July 2020

AbstractBackgroundThis is the first study on prognostication in an entire cohort of laboratory-confirmed COVID-19 patients in the city of Hong Kong. Prognostic tool is essential in the contingency response for the next wave of outbreak. This study aims to develop prognostic models to predict COVID-19 patients’ clinical outcome on day 1 and day 5 of hospital admission.MethodsWe did a retrospective analysis of a complete cohort of 1,037 COVID-19 laboratory-confirmed patients in Hong Kong as of 30 April 2020, who were admitted to 16 public hospitals with their data sourced from an integrated electronic health records system. It covered demographic information, chronic disease(s) history, presenting symptoms as well as the worst clinical condition status, biomarkers’ readings and Ct value of PCR tests on Day-1 and Day-5 of admission. The study subjects were randomly split into training and testing datasets in a 8:2 ratio. Extreme Gradient Boosting (XGBoost) model was used to classify the training data into three disease severity groups on Day-1 and Day-5.ResultsThe 1,037 patients had a mean age of 37.8 (SD±17.8), 53.8% of them were male. They were grouped under three disease outcome: 4.8% critical/serious, 46.8% stable and 48.4% satisfactory. Under the full models, 30 indicators on Day-1 and Day-5 were used to predict the patients’ disease outcome and achieved an accuracy rate of 92.3% and 99.5%. With a trade-off between practical application and predictive accuracy, the full models were reduced into simpler models with seven common specific predictors, including the worst clinical condition status (4-level), age group, and five biomarkers, namely, CRP, LDH, platelet, neutrophil/lymphocyte ratio and albumin/globulin ratio. Day-1 model’s accuracy rate, macro- and micro-averaged sensitivity and specificity were 91.3%, 84.9%-91.3% and 96.0%-95.7% respectively, as compared to 94.2%, 95.9%-94.2% and 97.8%-97.1% under Day-5 model.ConclusionsBoth Day-1 and Day-5 models can accurately predict the disease severity. Relevant clinical management could be planned according to the predicted patients’ outcome. The model is transformed into a simple online calculator to provide convenient clinical reference tools at the point of care, with an aim to inform clinical decision on triage and step-down care.
The consequences of adjustment, correction and selection in genome-wide association studies used for two-sample Mendelian randomization
Authors: Walker Venexia M , Harrison Sean , Carter Alice R , Gill Dipender , Tzoulaki Ioanna , Davies Neil M 
Published: July 2020

ABSTRACTIntroductionGenome-wide association studies (GWASs) often adjust for covariates, correct for medication use, or select on medication users. If these summary statistics are used in two-sample Mendelian randomization analyses, estimates may be biased. We used simulations to investigate how GWAS adjustment, correction and selection affects these estimates and performed an analysis in UK Biobank to provide an empirical example.MethodsWe simulated six GWASs: no adjustment for a covariate, correction for medication use, or selection on medication users; adjustment only; selection only; correction only; both adjustment and selection; and both adjustment and correction. We then ran two-sample Mendelian randomization analyses using these GWASs to evaluate bias. We also performed equivalent GWASs using empirical data from 306,560 participants in UK Biobank with systolic blood pressure as the exposure and body mass index as the covariate and ran two-sample Mendelian randomization with coronary heart disease as the outcome.ResultsThe simulation showed that estimates from GWASs with selection can produce biased two-sample Mendelian randomization estimates. Yet, we observed relatively little difference between empirical estimates of the effect of systolic blood pressure on coronary artery disease across the six scenarios.ConclusionsGiven the potential for bias from using GWASs with selection on Mendelian randomization estimates demonstrated in our simulation, careful consideration before using this approach is warranted. However, based on our empirical results, using adjusted, corrected or selected GWASs is unlikely to make a large difference to two-sample Mendelian randomization estimates in practice.
Two New Models for Epidemics with Application to the COVID-19 Pandemic in the United States, Italy, and the United Kingdom
Authors: Roberts David H. 
Published: July 2020

ABSTRACTThe Distributed Logistic Model and the Adaptive Logistic Model of epidemics are formulated and used to study the course of cases and deaths during the COVID-19 pandemic. The distributed model is designed to account for a spread of initiation times of hot spots across a country; it does especially well at capturing the initial and linear phases of epidemics. The adaptive model accounts for the development of social mitigation factors, and does especially well at capturing the declining phases of epidemics. The historical data for the U.S., Italy, and the U.K. are analyzed in detail. The parameters of the fits to the two models provide complementary information about the pandemic. The initial infection rate constant was r0 ≃ 0.29 day−1 for each country, and the effective infection rate constants evolved with time in essentially the same way for each. This suggests that mitigation effects were equally effective in all three countries. Analysis with the distributed model suggests that it took somewhat different times T for the epidemic to spread across each country, with T (US)≃ 50 days significantly greater than the T ‘s of Italy or the U.K. The mortality ratio in the U.S. was about 0.061 while in Italy and U.K. it was much larger at about 0.15.
Studies on the Biosorption Potential of Copper byRhizopus arrhizusBiomass
Authors: Chauhan Jyoti , Saini Ishan , Kaushik Prashant 
Published: July 2020

AbstractDue to rapid industrialization and global urbanization, heavy metal pollution of water reservoirs is a severe environmental threat. Moreover, the removal of these heavy metal ions of copper from the wastewaters using conventional methods are costly, time taking, and less effective. Whereas, biosorption proved as a better alternative technique over the traditional methods for the removal of metal ions from the water bodies. Biological materials or biosorbents have been used for the adsorption of metal ions from the aquatic system. Therefore, Rhizopusarrhizus(living biomass) for the biosorption of copper (Cu) metal was used as biosorbent in the present investigation. The pH and temperature at which biosorption occurs are critical. In case ofR. arrhizusthe maximum adsorption was recorded at pH 7.0, and a temperature of 35°C.Whereas, the maximum adsorption capacity (Q value) of 100 mg biomass ofRhizopus arrhizuswas observed as 94.46 % at 80 ppm concentration. The maximum adsorption capacity of 200 mg biomass of test fungi was reported as 97.32 % at the metal concentration of 80 ppm. Maximum Q value (biosorption capacity, i.e. mg metal per g biosorbent) was 37.785 mg/g at an 80-ppm concentration in case of 100 mg biomass. In the case of 200 mg biomass, the maximum Q value was 19.464 mg/g observed at 80 ppm concentration. Overall, the present study showed that 100 mg and 200 mgRhizopus arrhizusbiomass acts as an excellent adsorbing material for the adsorption of Cu metal ions.
Accurate recognition of colorectal cancer with semi-supervised deep learning on pathological images
Authors: Yu Gang , Xie Ting , Xu Chao , Shi Xing-Hua , Wu Chong , Sun Kai , Meng Run-Qi , Meng Xiang-He , Wang Kuan-Song , Xiao Hong-Mei , Deng Hong-Wen 
Published: July 2020

AbstractBackgroundMachine-assisted recognition of colorectal cancer (CRC) has been mainly focused on supervised deep learning that suffers from a significant bottleneck of requiring massive labeled data. We hypothesize that semi-supervised deep learning leveraging a small amount of labeled data with abundant available unlabeled data can provide a powerful alternative strategy.MethodWe proposed a semi-supervised model based on the mean teacher architecture that provides pathological predictions at both patch- and patient-levels. We demonstrated the general utility of the model utilizing 13,111 CRC whole slide images from 8,803 subjects gathered from 13 independent centers. We compared our proposed method with the prevailing supervised learning and six pathologists. Two extended evaluations on 15,000 lung and 294,912 lymph node images were also performed to confirm the generality of utility of semi-supervised learning for different cancers.ResultsWith a small amount of labeled training patches (∼3,150 labeled, ∼40,950 unlabeled or ∼6,300 labeled, ∼37,800 unlabeled), the semi-supervised learning (SSL) performed significantly better than the supervised learning (SL, which only used the labeled data) (area under the curve, AUC: 0.90 ± 0.06 vs. 0.84 ± 0.07,Pvalue = 0.02 or AUC: 0.98 ± 0.01 vs. 0.92 ± 0.04,Pvalue = 0.0004). Moreover, we found no significant difference between SL using massive ∼44,100 labeled patches and SSL (∼6,300 labeled, ∼37,800 unlabeled) at patch-level diagnoses (AUC:0.98 ± 0.01 vs. 0.987 ± 0.01,Pvalue = 0.134) and patient-level diagnoses (average AUC: 0.974 vs. 0.980,Pvalue = 0.117). SSL was close to human pathologists in diagnosis performance (average AUC: 0.972 vs. 0.969). This extended evaluation on lung and lymph node also confirmed when a small amount of labeled data were used, SSL was better than SL, and achieved similar performance as that of SL with massive labeling.ConclusionsWe reported that SSL can achieve excellent performance through a multi-center study. Because SSL dramatically reduces the need and cost of pathological image annotation, it has great potential to effectively build pathological artificial intelligence (AI) platforms in practice.
Autographa californica Multiple Nucleopolyhedrovirusorf13is Required for Efficient Nuclear Egress of Nucleocapsids
Authors: Chen Xingang , Yang Xiaoqin , Lei Chengfeng , Qin Fujun , Hu Jia , Sun Xiulian 
Published: July 2020

ABSTRACTAutographa californica multiple nucleopolyhedrovirus (AcMNPV)orf13(ac13) is a conserved gene in all sequenced alphabaculoviruses. However, its function in the viral life cycle remains unknown. In this study we found thatac13was a late gene and that the encoded protein, bearing a putative nuclear localization signal motif in the DUF3627 domain, colocalized with the nuclear membrane. Deletion ofac13did not affect viral DNA replication, gene transcription, nucleocapsid assembly or occlusion body (OB) formation, but reduced virion budding from infected cells by approximately 400-fold compared with the wild-type virus. Deletion ofac13substantially impaired the egress of nucleocapsids from the nucleus to the cytoplasm, while the number of occlusion-derived viruses embedded within OBs was unaffected. Taken together, our results indicated thatac13was required for efficient nuclear egress of nucleocapsids during virion budding, but was dispensable for OB formation.IMPORTANCEEgress of baculovirus nucleocapsids from the nucleus is an essential process for morphogenesis of mature budded viruses, which is required to spread infection within susceptible cells and tissues. Although many viral and host proteins are required for nucleocapsid egress, the specific mechanisms underlying this process in baculoviruses remain somewhat enigmatic. In the present study, we found that theac13gene, in addition toac11, ac51, ac66, ac75, ac78, gp41, ac93, p48, exon0andac142, was required for efficient nuclear egress of nucleocapsids. Our results contribute to a better understanding of nucleocapsid egress in baculoviruses.
Structural engraftment and topographic spacing of transplanted human stem cell-derived retinal ganglion cells
Authors: Zhang Kevin Y , Tuffy Caitlyn , Mertz Joseph L , Quillen Sarah , Wechsler Laurence , Quigley Harry A , Zack Donald J , Johnson Thomas V 
Published: July 2020

AbstractRetinal ganglion cell (RGC) replacement and optic nerve regeneration hold potential for restoring vision lost to optic neuropathy. Following transplantation, RGCs must integrate into the neuroretinal circuitry in order to receive afferent visual signals for processing and transmission to central targets. To date, the efficiency of RGC retinal integration following transplantation has been limited. We sought to characterize spontaneous interactions between transplanted human embryonic stem cell-derived RGCs and the recipient mature mammalian retina, and to identify and overcome barriers to the structural integration of transplanted neurons. Using anin vitromodel system, following transplantation directly onto the inner surface of organotypic mouse retinal explants, human RGC somas form compact clusters and extend bundled neurites that remain superficial to the neural retinal tissue, hindering any potential for afferent synaptogenesis. To enhance integration, we explored methods to increase the cellular permeability of the internal limiting membrane (ILM). Digestion of extracellular matrix components using proteolytic enzymes was titrated to achieve disruption of the ILM while minimizing retinal toxicity and preserving endogenous retinal glial reactivity. Such ILM disruption is associated with dispersion rather than clustering of transplanted RGC bodies and neurites, and with a marked increase in transplanted RGC neurite extension into retinal parenchyma. The ILM appears to be a barrier to afferent retinal connectivity by transplanted RGCs and its circumvention may be necessary for successful functional RGC replacement through transplantation.