bluuebunny/crossref_metadata_2025_split huggingface dataset:
Signals of significantly increased vaccine breakthrough, decreased hospitalization rates, and less severe disease in patients with COVID-19 caused by the Omicron variant of SARS-CoV-2 in Houston, Texas
Authors: Christensen Paul A. , Olsen Randall J. , Long S. Wesley , Snehal Richard , Davis James J. , Saavedra Matthew Ojeda , Reppond Kristina , Shyer Madison N. , Cambric Jessica , Gadd Ryan , Thakur Rashi M. , Batajoo Akanksha , Mangham Regan , Pena Sindy , Trinh Trina , Kinskey Jacob C. , Williams Guy , Olson Robert , Gollihar Jimmy , Musser James M. 
Published: January 2022

AbstractGenetic variants of SARS-CoV-2 continue to dramatically alter the landscape of the COVID-19 pandemic. The recently described variant of concern designated Omicron (B.1.1.529) has rapidly spread worldwide and is now responsible for the majority of COVID-19 cases in many countries. Because Omicron was recognized very recently, many knowledge gaps exist about its epidemiology, clinical severity, and disease course. A genome sequencing study of SARS-CoV-2 in the Houston Methodist healthcare system identified 4,468 symptomatic patients with infections caused by Omicron from late November 2021 through January 5, 2022. Omicron very rapidly increased in only three weeks to cause 90% of all new COVID-19 cases, and at the end of the study period caused 98% of new cases. Compared to patients infected with either Alpha or Delta variants in our healthcare system, Omicron patients were significantly younger, had significantly increased vaccine breakthrough rates, and were significantly less likely to be hospitalized. Omicron patients required less intense respiratory support and had a shorter length of hospital stay, consistent with on average decreased disease severity. Two patients with Omicron “stealth” sublineage BA.2 also were identified. The data document the unusually rapid spread and increased occurrence of COVID-19 caused by the Omicron variant in metropolitan Houston, and address the lack of information about disease character among US patients.
Prelimbic proBDNF facilitates memory destabilization by regulation of neuronal function in juveniles
Authors: Sun Wei , Chen Xiao , Mei Yazi , Yang Yang , Li Xiaoliang , An Lei 
Published: January 2022

AbstractFear regulation changes as a function of age and adolescence is a key developmental period for the continued maturation of fear neural circuitry. The involvement of prelimbic proBDNF in fear memory extinction and its mediated signaling were reported previously. Given the inherent high level of proBDNF during juvenile period, we tested whether prelimbic proBDNF regulated synaptic and neuronal functions allowing to influencing retrieval-dependent memory processing. By examining freezing behavior of auditory fear conditioned rats, we found high levels of prelimbic proBDNF in juvenile rats enhanced destabilization of the retrieval-dependent weak but not strong fear memory through activating p75NTR-GluN2B signaling. This modification was attributed to the increment in proportion of thin type spine and promotion in synaptic function, as evidence by facilitation of NMDA-mediated EPSCs and GluN2B-dependent synaptic depression. The strong prelimbic theta- and gamma-oscillation coupling predicted the suppressive effect of proBDNF on the recall of post-retrieval memory. Our results critically emphasize the importance of developmental proBDNF for modification of retrieval-dependent memory and provide a potential critical targeting to inhibit threaten memories associated with neurodevelopment disorders.
Dynamic characteristics and Functional Analysis Provide new insights into the role of GauERF105 in resistance against Verticillium wilt in Cotton
Authors: Wang Yanqing , Umer Muhammad Jawad , Hou Yuqing , Xu Yanchao , Mehari Teame Gereziher , Zheng Jie , Wang Yuhong ,   CAI, Zhou Zhongli , Li Zhikun , Liu Fang 
Published: January 2022

AbstractVerticillium wilt is the most devastating disease of cotton and it results in huge yield losses every year in the fields. The underlying mechanisms of VW in cotton are not well explored yet. In the current approach we used the transcriptome data from G. australe in response to Verticillium wilt attack to mine the ERF TFs and prove their potential role in resistance against VW attack in cotton. We identified 23 ERFs in total, and on the basis of expression at different time points i.e., 24h, 48h and 72h post inoculation and selected GauERF105 for further validation. We performed VIGS in cotton and over expression in Arabidopsis respectively. Moreover, DAB and trypan staining also suggests that the impact of disease was more in the wildtype as compared to transgene lines. On the basis of our results, we confirmed that GauERF105 is the key candidate and playing a key role for defending cotton against VW attack. Current finding might be helpful for generating resistance germplasm in cotton and it will be beneficial to recover the yield losses in field.
Predicting COVID-19 severity using major risk factors and received vaccines
Authors: Israel Ariel , Schäffer Alejandro A. , Merzon Eugene , Green Ilan , Magen Eli , Golan-Cohen Avivit , Vinker Shlomo , Ruppin Eytan 
Published: January 2022

AbstractBackgroundVaccines are highly effective in preventing severe disease and death from COVID-19, and new medications that can reduce severity of disease have been approved. However, many countries are facing limited supply of vaccine doses and medications. A model estimating the probabilities for hospitalization and mortality according to individual risk factors and vaccine doses received could help prioritize vaccination and yet scarce medications to maximize lives saved and reduce the burden on hospitalization facilities.MethodsElectronic health records from 101,039 individuals infected with SARS-CoV-2, since the beginning of the pandemic and until November 30, 2021 were extracted from a national healthcare organization in Israel. Logistic regression models were built to estimate the risk for subsequent hospitalization and death based on the number of BNT162b2 mRNA vaccine doses received and few major risk factors (age, sex, body mass index, hemoglobin A1C, kidney function, and presence of hypertension, pulmonary disease and malignancy).ResultsThe models built predict the outcome of newly infected individuals with remarkable accuracy: area under the curve was 0.889 for predicting hospitalization, and 0.967 for predicting mortality. Even when a breakthrough infection occurs, having received three vaccination doses significantly reduces the risk of hospitalization by 66% (OR=0.339) and of death by 78% (OR=0.223).ConclusionsThe models enable rapid identification of individuals at high risk for hospitalization and death when infected. These patients can be prioritized to receive booster vaccination and the yet scarce medications. A calculator based on these models is made publicly available on http://covidest.web.app
Anin vivopig model for testing novel PET radioligands targeting cerebral protein aggregates
Authors: Raval Nakul Ravi , Nasser Arafat , Madsen Clara Aabye , Beschorner Natalie , Beaman Emily Eufaula , Juhl Morten , Lehel Szabolcs , Palner Mikael , Svarer Claus , Plavén-Sigray Pontus , Jørgensen Louise Møller , Knudsen Gitte Moos 
Published: January 2022

AbstractPositron emission tomography (PET) has become an essential clinical tool for diagnosing neurodegenerative diseases with abnormal accumulation of proteins like amyloid-β or tau. Despite many attempts, it has not been possible to develop an appropriate radioligand for imaging aggregated α-synuclein in the brain for diagnosing, e.g., Parkinson’s Disease. Access to a large animal model with α-synuclein pathology would critically enable a more translationally appropriate evaluation of novel radioligands.We here establish a pig model with cerebral injections of α-synuclein preformed fibrils or brain homogenate from postmortem human brain tissue from individuals with Alzheimer’s disease (AD) or dementia with Lewy body (DLB) into the pig’s brain, using minimally invasive surgery and validated against saline injections. In the absence of a suitable α-synuclein radioligand, we validated the model with the unselective amyloid-β tracer [11C]PIB, which has a high affinity for β-sheet structures in aggregates. Gadolinium-enhanced MRI confirmed that the blood-brain barrier was intact. A few hours post-injection, pigs were PET scanned with [11C]PIB. Quantification was done with Logan invasive graphical analysis and simplified reference tissue model 2 using the occipital cortex as a reference region. After the scan, we retrieved the brains to confirm successful injection using autoradiography and immunohistochemistry.We found four times higher [11C]PIB uptake in AD-homogenate-injected regions and two times higher uptake in regions injected with α-synuclein-preformed-fibrils compared to saline. The [11C]PIB uptake was the same in non-injected (occipital cortex, cerebellum) and injected (DLB-homogenate, saline) regions. With its large brains and ability to undergo repeated PET scans as well as neurosurgical procedures, the pig provides a robust, cost-effective, and good translational model for assessment of novel radioligands including, but not limited to, proteinopathies.
AVATAR: AI Vision Analysis for Three-dimensional Action in Real-time
Authors: Kim Dae-Gun , Shin Anna , Jeong Yong-Cheol , Park Seahyung , Kim Daesoo 
Published: January 2022

AbstractArtificial intelligence (AI) is an emerging tool for high-resolution behavioural analysis and conduction of human-free behavioural experiments. Here, we applied an AI-based system, AVATAR, which automatically virtualises 3D motions from the detection of 9 body parts. This allows quantification, classification and detection of specific action sequences in real-time and facilitates closed-loop manipulation, triggered by the onset of specific behaviours, in freely moving mice.
Importance of small diameter woody plants and treelet species in tropical wet evergreen forest of southern western ghats, india
Authors: Sreejith K. A. , Sanil M.S. , Prasad T.S. , Prejith M. P. , Sreekumar V.B. , Murali Akhil 
Published: January 2022

AbstractTropical forests have long been accepted for their productivity and ecosystem services on account of their high diversity and stand structural attributes. In spite of their significance, tropical forests, and especially those of Asia, remain understudied. Until recently, most forest inventories in Asia have concentrated on trees 10 cm in diameter. Floristic composition, plant species diversity, above ground biomass, basal area and diversity were investigated across different life form and two-diameter classes in a large scale 10-ha plot, in the undisturbed tropical seasonal rain forest of Southern Western Ghats, Kerala, India. Regeneration pattern of the study area was examined by evaluating fisher’s alpha and IVI (Important Value Index) across three layer of vegetation (seedling, sapling, and tree). Within the plot, we recorded 25,390 woody plant species ≥1 cm dbh from 45 families, 91 genera, and 106 species. Plant density was 2539 woody individuals per hectare, with a basal area of 47.72 m2/ha and an above-ground biomass of 421.77 Mg/ha. By basal area, density, and frequency, the Rubiaceae, Sapotaceae, and Malvaceae families were the most important. Small-diameter trees (1 cm ≤ dbh ≤10 cm) found to be 78 percent of the total tree population, 20.2 percent of the basal area, and 1.4 percent of the aboveground biomass. They also possessed 6 percent more diversity at the family level, 10% more diversity at the genus level, and 12% more diversity at the species level than woody individuals under 10 cm dbh.. Woody individuals of treelets life form and small-diameter classes were much more diverse and dense than the other groups, indicating that results based only on larger canopy trees and larger diameter class may be not an appropriate representation of the diversity status of a particular tropical forest type. Lower density of individuals in initial girth class indicates the vulnerability of the forest system to anthropogenic, natural disturbance and a changing climate. Reduce the minimum diameter limit down to 1 cm, in contrast to 10 cm limit used in most of the evergreen forest inventories, revealed a high density and diversity in thelower stories.
Expectation violations produce error signals in mouse V1
Authors: Price Byron H. , Jensen Cambria M. , Khoudary Anthony A. , Gavornik Jeffrey P. 
Published: January 2022

AbstractRepeated exposure to visual sequences changes the form of evoked activity in the primary visual cortex (V1). Predictive coding theory provides a potential explanation for this, namely that plasticity shapes cortical circuits to encode spatiotemporal predictions and that subsequent responses are modulated by the degree to which actual inputs match these expectations. Here we use a recently developed statistical modeling technique called Model-Based Targeted Dimensionality Reduction (MbTDR) to study visually-evoked dynamics in mouse V1 in context of a previously described experimental paradigm called “sequence learning”. We report that evoked spiking activity changed significantly with training, in a manner generally consistent with the predictive coding framework. Neural responses to expected stimuli were suppressed in a late window (100-150ms) after stimulus onset following training, while responses to novel stimuli were not. Omitting predictable stimuli led to increased firing at the expected time of stimulus onset, but only in trained mice. Substituting a novel stimulus for a familiar one led to changes in firing that persisted for at least 300ms. In addition, we show that spiking data can be used to accurately decode time within the sequence. Our findings are consistent with the idea that plasticity in early visual circuits is involved in coding spatiotemporal information.
Reduced synaptic activity and dysregulated extracellular matrix pathways are common phenotypes in midbrain neurons derived from sporadic and mutation-associated Parkinson’s disease patients
Authors: Stern Shani , Lau Shong , Manole Andreea , Rosh Idan , Percia Menahem , Ezer Ran Ben , Shokhirev Maxim N. , Qiu Fan , Schafer Simon , Mansour Abed , Stern Tchelet , Ofer Pola , Stern Yam , Diniz Ana Mendes , Moore Lynne Randolph , Nayak Ritu , Aicher Aidan , Rhee Amanda , Wong Thomas L. , Nguyen Thao , Linker Sara B. , Winner Beate , Freitas Beatriz C. , Jones Eugenia , Bardy Cedric , Brice Alexis , Winkler Juergen , Marchetto Maria C. , Gage Fred H. 
Published: January 2022

AbstractSeveral mutations that cause Parkinson’s disease (PD) have been identified over the past decade. These account for 15-25% of PD cases; the rest of the cases are considered sporadic. Currently, it is accepted that PD is not a single monolithic disease but rather a constellation of diseases with some common phenotypes. While rodent models exist for some of the PD-causing mutations, research on the sporadic forms of PD is lagging due to a lack of cellular models. In our study, we differentiated PD patient-derived dopaminergic (DA) neurons from induced pluripotent stem cells (iPSCs) of several PD-causing mutations as well as from sporadic PD patients. Strikingly, we observed a common neurophysiological phenotype: Neurons derived from PD patients had a severe reduction in the rate of synaptic currents compared to those derived from healthy controls. While the relationship between mutations in genes such as the SNCA and LRRK2 and a reduction in synaptic transmission has been investigated before, here we show evidence that the pathogenesis of the synapses in neurons is a general phenotype in PD. Analysis of RNA sequencing results displayed changes in gene expression in different synaptic mechanisms as well as other affected pathways such as extracellular matrix-related pathways. Some of these dysregulated pathways are common to all PD patients (monogenic or idiopathic). Our data, therefore, shows changes that are central and convergent to PD and suggests a strong involvement of the tetra-partite synapse in PD pathophysiology.
Low-cost arabinose induced genetic circuit for protein production: Modeling
Authors: Gómez Christian J. Flores , García Barrera Jorge L. , de la Cruz Edgar Valeria 
Published: January 2022

AbstractA low-cost reagent-producing genetic circuit was designed during this work. Its functioning is based on a positive feedback loop induced by a small amount of arabinose, allowing users to obtain reactants in a safe, constant, and controlled manner. The “design only” approach to the project allows us to work in different kinds of computational models, thus, an ODE-based model was thoroughly developed and a cellular automata-based one was experimented with.Working on the ODE model, equilibrium states and system stability were studied. Circuit properties were also focused on one of which was a high concentration of interest protein produced by low inductor inputs. As a result, a mathematical expression capable of describing the quantity of produced reagent was obtained. In addition, the cellular automata model offers a new perspective, given its differences from the ODE model e.g. this type of model is a stochastic analysis and describes each cell individually instead of describing the whole cellular population.
STReTCh: a strategy for facile detection of mechanical forces across proteins in cells
Authors: Zhong Brian L. , Vachharajani Vipul T. , Dunn Alexander R. 
Published: January 2022

ABSTRACTNumerous proteins experience and respond to mechanical forces as an integral part of their cellular functions, but measuring these forces remains a practical challenge. Here, we present a compact, 11 kDa molecular tension sensor termed STReTCh (Sensing Tension by Reactive Tag Characterization). Unlike existing genetically encoded tension sensors, STReTCh does not rely on experimentally demanding Förster resonance energy transfer (FRET)-based measurements and is compatible with typical fix-and-stain protocols. Using a magnetic tweezers assay, we calibrate the STReTCh module and show that it responds to physiologically relevant, piconewton forces. As proof-of-concept, we use an extracellular STReTCh-based sensor to visualize cell-generated forces at integrin-based adhesion complexes. In addition, we incorporate STReTCh into vinculin, a cytoskeletal adaptor protein, and show that STReTCh reports on forces transmitted between the cytoskeleton and cellular adhesion complexes. These data illustrate the utility of STReTCh as a broadly applicable tool for the measurement molecular-scale forces in biological systems.
Viscoelastic RNA entanglement and advective flow underlie nucleolar form and function
Authors: Riback Joshua A. , Eeftens Jorine M. , Lee Daniel S. W. , Quinodoz Sofia A. , Beckers Lien , Becker Lindsay A. , Brangwynne Clifford P. 
Published: January 2022

AbstractThe nucleolus facilitates transcription, processing, and assembly of ribosomal RNA (rRNA), the most abundant RNA in cells. Nucleolar function is facilitated by its multiphase liquid properties, but nucleolar fluidity and its connection to ribosome biogenesis remain unclear. Here, we used quantitative imaging, mathematical modeling, and pulse-chase nucleotide labelling to map nucleolar rRNA dynamics. Inconsistent with a purely diffusive process, rRNA steadily expands away from the transcriptional sites, moving in a slow (~1Å/s), radially-directed fashion. This motion reflects the viscoelastic properties of a highly concentrated gel of entangled rRNA, whose constant polymerization drives steady outward flow. We propose a new viscoelastic rRNA release model, where nucleolar rRNA cleavage and processing reduce entanglement, fluidizing the nucleolar periphery to facilitate release of mature pre-ribosomal particles.
Neuronal cell-type and circuit basis for visual predictive processing
Authors: Zou Jinmao , Huang Lawrence , Wang Lizhao , Xu Yuanyuan , Li Chenchang , Peng Qilin , Zeng Hongkui , Zhang Siyu , Li Lu 
Published: January 2022

AbstractBayesian Brain theory suggests brain utilises predictive processing framework to interpret the noisy world1-11. Predictive processing is essential to perception, action, cognition and psychiatric disease12, but underlying neural circuit mechanisms remain undelineated. Here we show the neuronal cell-type and circuit basis for visual predictive processing in awake, head-fixed mice during self-initiated running. Preceding running, vasoactive intestinal peptide (VIP)-expressing inhibitory interneurons (INs) in primary visual cortex (V1) are robustly activated in absence of structured visual stimuli. This pre-running activation is mediated via distal top-down projections from frontal, parietal and retrosplenial areas known for motion planning, but not local excitatory inputs associated with the bottom-up pathway. Somatostatin (SST) INs show pre-running suppression and post-running activation, indicating a VIP-SST motif. Differential VIP-SST peri-running dynamics anisotropically suppress neighbouring pyramidal (Pyr) neurons, preadapting Pyr neurons to the incoming running. Our data delineate key neuron types and circuit elements of predictive processing brain employs in action and perception.One Sentence SummaryVIP-SST-Pyr microcircuit in visual predictive processing during voluntary running
Cyanopeptides Restriction and Degradation Co-mediate Microbiota Assembly During a Freshwater Cyanobacterial Harmful Algal Bloom (CyanoHAB)
Authors: Gao Han , Zhao Ze , Zhang Lu , Ju Feng 
Published: January 2022

AbstractCyanobacterial harmful algal blooms (CyanoHABs) are globally intensifying and exacerbated by climate change and eutrophication. However, microbiota assembly mechanisms underlying CyanoHABs remain scenario specific and elusive. Especially, cyanopeptides, as a group of bioactive secondary metabolites of cyanobacteria, could affect microbiota assembly and ecosystem function. Here, the trajectory of cyanopeptides were followed and linked to microbiota duringMicrocystis-dominated CyanoHABs in lake Taihu, China. The most abundant cyanopeptide classes detected included microginin, spumigin, microcystin, nodularin and cyanopeptolin with total MC-LR-equivalent concentrations between 0.23 and 2051.54 ppb, of which cyanotoxins beyond microcystins (e.g., cyanostatin B and nodularin_R etc.) far exceeded reported organismal IC50and negatively correlated with microbiota diversity, exerting potential collective eco-toxicities stronger than microcystins alone. The microbial communities were differentiated by size fraction and sampling date throughout CyanoHABs, and surprisingly, their variances were better explained by cyanopeptides (19-38%) than nutrients (0-16%). Cyanopeptides restriction (e.g., inhibition) and degradation are first quantitatively verified as the deterministic drivers governing community assembly, with stochastic processes being mediated by interplay between cyanopeptide dynamics and lake microbiota. This study presents an emerging paradigm in which cyanopeptides restriction and degradation co-mediate lake water microbiota assembly, unveiling new insights about the ecotoxicological significance of CyanoHABs to freshwater ecosystems.
Whole genome sequencing of hematologically stained cells catapulted from Cell smears
Authors: Bae Sangwook , Jung Yushin , Kim Sungsik , Kim Jinhyun , Lee Amos Chungwon , Lee Dongsoon , Kwon Sunghoon 
Published: January 2022

AbstractAnalyzing archived peripheral blood smears is a potential route towards gaining cell morphology and genome information of blood cell types from various diseases. Yet, acquiring whole genome information from morphologically targeted cells was difficult, especially for rare cell types. The main causes for such difficulty were the inevitable usage of cell stains leading to whole genome amplification inhibition, and insufficient cell isolation performance of previously introduced laser microdissection (LMD) techniques. Here, we introduce a new laser-based cell isolation technique and a whole genome amplification (WGA) protocol optimized for whole genome analysis from minute input of hematologically stained cells. We were able to perform whole genome copy number profiling and SNP analysis from as little as 5 cells.