bluuebunny/crossref_metadata_2025 huggingface dataset:
High-content profiling reveals a unified model of copper ionophore dependent cell death in oesophageal adenocarcinoma
Authors: Hughes Rebecca E. , Elliott Richard J. R. , Li Xiaodun , Munro Alison F. , Makda Ashraff , Carter Roderick N. , Morton Nicholas M. , Fujihara Kenji , Clemons Nicholas J. , Fitzgerald Rebecca , O’Neill J. Robert , Hupp Ted , Carragher Neil O.
Published: October 2021

Background and Aims

Oesophageal adenocarcinoma (OAC) is of increasing global concern due to increasing incidence, a lack of effective treatments, and poor prognosis. Therapeutic target discovery and clinical trials have been hindered by the heterogeneity of the disease, lack of driver mutations, and the dominance of large-scale genomic rearrangements. In this work we have characterised three potent and selective hit compounds identified in an innovative high-content phenotypic screening assay. The three hits include two approved drugs; elesclomol and disulfiram, and another small molecule compound, ammonium pyrrolidinedithiocarbamate. We uncover their mechanism of action, discover a targetable vulnerability, and gain insight into drug sensitivity for biomarker-based clinical trials in OAC.

Methods

Elesclomol, disulfiram, and ammonium pyrrolidinedithiocarbamate were systematically characterised across panels of oesophageal cell lines and patient-derived organoids. Drug treated oesophageal cell lines were morphologically profiled using a high-content, imaging platform. Compounds were assessed for efficacy across patient-derived organoids. Metabolomics and transcriptomics were assessed for the identification of oesophageal-cancer specific drug mechanisms and patient stratification hypotheses.

Results

High-content profiling revealed that all three compounds were highly selective for OAC over tissue-matched controls. Comparison of gene expression and morphological signatures unveiled a unified mechanism of action involving the accumulation of copper selectively in cancer cells, leading to dysregulation of proteostasis and cancer cell death. Basal omic analyses revealed proteasome and metabolic markers of drug sensitivity, forming the basis for biomarker-based clinical trials in OAC.

Conclusions

Integrated analysis of high-content imaging, transcriptomic and metabolomic data has revealed a new therapeutic mechanism for the treatment of OAC and represents an alternative target-agnostic drug discovery strategy.
DeepSTARR predicts enhancer activity from DNA sequence and enables thede novodesign of enhancers
Authors: de Almeida Bernardo P. , Reiter Franziska , Pagani Michaela , Stark Alexander
Published: October 2021

Enhancer sequences control gene expression and comprise binding sites (motifs) for different transcription factors (TFs). Despite extensive genetic and computational studies, the relationship between DNA sequence and regulatory activity is poorly understood and enhancerde novodesign is considered impossible. Here we built a deep learning model, DeepSTARR, to quantitatively predict the activities of thousands of developmental and housekeeping enhancers directly from DNA sequence inDrosophila melanogasterS2 cells. The model learned relevant TF motifs and higher-order syntax rules, including functionally non-equivalent instances of the same TF motif that are determined by motif-flanking sequence and inter-motif distances. We validated these rules experimentally and demonstrated their conservation in human by testing more than 40,000 wildtype and mutantDrosophilaand human enhancers. Finally, we designed and functionally validated synthetic enhancers with desired activitiesde novo.
Network Segregation Predicts Processing Speed in the Cognitively Healthy Oldest-old
Authors: Nolin SA , Faulkner ME , Stewart P , Fleming L , Merritt S , Rezaei RF , Bharadwaj PK , Franchetti MK , Raichlen DA , Jessup CJ , Edwards L , Hishaw GA , Van Etten EJ , Trouard TP , Geldmacher D , Wadley VG , Alperin N , Porges EC , Woods AJ , Cohen RA , Levin BE , Rundek T , Alexander GE , Visscher KM
Published: October 2021

Functional connections among groups of brain areas give insight into the brain’s organization. The cognitive effects of aging may relate to the brain’s large-scale organization. Examining the relationship between individual differences in brain organization and cognitive function in healthy older adults can help us understand how these networks support healthy cognitive aging. We investigated functional network segregation in 146 cognitively healthy participants aged 85+ in the McKnight Brain Aging Registry. We found that the segregation of the cortical association system and the segregation of individual networks within that system [the fronto-parietal network (FPN), cingulo-opercular network (CON) and default mode network (DMN)], were strong predictors of overall cognition and processing speed. We also provide a healthy oldest-old (85+) cortical parcellation that can be used in future work in this age group. This study shows that network segregation of the oldest-old brain is closely linked to cognitive performance. This work adds to the growing body of knowledge about differentiation in the aged brain by demonstrating that cognitive ability is associated with differentiated functional networks in very old individuals experiencing successful cognitive aging.
Comprehensive characterization of the antibody responses to SARS-CoV-2 Spike protein after infection and/or vaccination
Authors: Garrett Meghan E. , Galloway Jared G. , Wolf Caitlin , Logue Jennifer K. , Franko Nicholas , Chu Helen Y. , Matsen Frederick A. , Overbaugh Julie
Published: October 2021

Background

Control of the COVID-19 pandemic will rely on SARS-CoV-2 vaccine-elicited antibodies to protect against emerging and future variants; an understanding of the unique features of the humoral responses to infection and vaccination, including different vaccine platforms, is needed to achieve this goal.

Methods

The epitopes and pathways of escape for Spike-specific antibodies in individuals with diverse infection and vaccination history were profiled using Phage-DMS. Principal component analysis was performed to identify regions of antibody binding along the Spike protein that differentiate the samples from one another. Within these epitope regions we determined potential escape mutations by comparing antibody binding of peptides containing wildtype residues versus peptides containing a mutant residue.

Results

Individuals with mild infection had antibodies that bound to epitopes in the S2 subunit within the fusion peptide and heptad-repeat regions, whereas vaccinated individuals had antibodies that additionally bound to epitopes in the N- and C-terminal domains of the S1 subunit, a pattern that was also observed in individuals with severe disease due to infection. Epitope binding appeared to change over time after vaccination, but other covariates such as mRNA vaccine dose, mRNA vaccine type, and age did not affect antibody binding to these epitopes. Vaccination induced a relatively uniform escape profile across individuals for some epitopes, whereas there was much more variation in escape pathways in in mildly infected individuals. In the case of antibodies targeting the fusion peptide region, which was a common response to both infection and vaccination, the escape profile after infection was not altered by subsequent vaccination.

Conclusions

The finding that SARS-CoV-2 mRNA vaccination resulted in binding to additional epitopes beyond what was seen after infection suggests protection could vary depending on the route of exposure to Spike antigen. The relatively conserved escape pathways to vaccine-induced antibodies relative to infection-induced antibodies suggests that if escape variants emerge, they may be readily selected for across vaccinated individuals. Given that the majority of people will be first exposed to Spike via vaccination and not infection, this work has implications for predicting the selection of immune escape variants at a population level.

Funding

This work was supported by NIH grants AI138709 (PI Overbaugh) and AI146028 (PI Matsen). Julie Overbaugh received support as the Endowed Chair for Graduate Education (FHCRC). The research of Frederick Matsen was supported in part by a Faculty Scholar grant from the Howard Hughes Medical Institute and the Simons Foundation. Scientific Computing Infrastructure at Fred Hutch was funded by ORIP grant S10OD028685.
Ultra-precise all-optical manipulation of neural circuits with multifunctional Cre-dependent transgenic mice
Authors: Bounds Hayley A. , Sadahiro Masato , Hendricks William D. , Gajowa Marta , Gopakumar Karthika , Quintana Daniel , Tasic Bosiljka , Daigle Tanya L. , Zeng Hongkui , Oldenburg Ian Antón , Adesnik Hillel
Published: October 2021

Determining which features of the neural code drive perception and behavior requires the ability to simultaneous read out and write in neural activity patterns with high precision across many neurons. All-optical systems that combine two photon (2p) calcium imaging and targeted 2p photostimulation enable the activation of specific, functionally defined groups of neurons in behaving animals. However, these techniques do not yet have the ability to reveal how the specific distribution of firing rates across a relevant neural population mediates neural computation and behavior. The key technical obstacle is the inability to transform single-cell calcium signals into accurate estimates of firing rate changes and then write in these cell-specific firing rate changes to each individual neuron in a targeted population. To overcome this challenge, we made two advances: first we introduce a new genetic line of mice for robust Cre-dependent co-expression of a high-performance calcium indicator and a potent soma-targeted microbial opsin. Second, using this line, we developed a pipeline that enables the read-out and write-in of precise population vectors of neural activity across a targeted group of neurons. The combination of the new multifunctional transgenic line and the photostimulation paradigm offer a powerful and convenient platform for investigating the neural codes of computation and behavior. It may prove particularly useful for probing causal features of the geometry of neural representations where the ability to directly control the topology of population activity is essential.
At a snail’s pace: the influence of habitat disturbance on terrestrial snail movement using experimentally manipulated mesocosms
Authors: Denief Emily E. , Turner Julie W. , Prokopenko Christina M. , Robitaille Alec L. , Wal Eric Vander
Published: October 2021

The Anthropocene marks great changes to environments and the animals that inhabit them. Changes, such as disturbance, can affect the manner in which animals interact with their environments, such as moving and selecting habitats. To test how animals might respond to changing disturbance regimes, we employ an experimental approach to movement ecology. We used integrated step selection analysis (iSSA) to test the behavioural responses of individually-marked grove snails (Cepaea nemoralis) exposed to a gradient of physical disturbance in their habitat. We used a before-after control-impact (BACI) experimental design within semi-controlled mesocosms to manipulate edge and disturbance variables by altering the area of the mesocosm covered by bricks. We showed that grove snails perceive edges of enclosures and edges of bricks as risks, and responded to such risks by altering their movement. Grove snails displayed a bimodal response to risk by taking shelter in place or moving faster to be farther from the disturbance. Furthermore, individuals tended to modulate their behavioural response to the degree of risk. Our study highlights the usefulness of experimental mesocosms in movement ecology and in determining the effects of habitat alteration and human-imposed risk on movement behaviour.
Metabolic regulation inferred from Jacobian and Hessian matrices of metabolic functions
Authors: Nägele Thomas
Published: October 2021

Quantitative analysis of experimental metabolic data is frequently challenged by non-intuitive, complex patterns which emerge from regulatory networks. Quantitative output of metabolic regulation can be summarised by metabolic functions which comprise information about dynamics of metabolite concentrations. They reflect the sum of biochemical reactions which affect a metabolite concentration. Derivatives of metabolic functions provide essential information about system dynamics. The Jacobian matrix of a reaction network summarises first-order partial derivatives of metabolic functions with respect to metabolite concentrations while Hessian matrices summarise second-order partial derivatives. Here, a simple model of invertase-driven sucrose hydrolysis is simulated and both Jacobian and Hessian matrices of metabolic functions are derived for quantitative analysis of kinetic regulation of sucrose metabolism. Based on previous experimental observations, metabolite dynamics are quantitatively explained in context of underlying metabolic functions. Their potential regulatory role during plant cold acclimation is derived from Jacobian and Hessian matrices.
The importance of residue-level filtering, and the Top2018 best-parts dataset of high-quality protein residues
Authors: Williams Christopher J. , Richardson David C. , Richardson Jane S.
Published: October 2021

We have curated a high-quality, “best parts” reference dataset of about 3 million protein residues in about 15,000 PDB-format coordinate files, each containing only residues with good electron density support for a physically acceptable model conformation. The resulting pre-filtered data typically contains the entire core of each chain, in quite long continuous fragments. Each reference file is a single protein chain, and the total set of files were selected for low redundancy, high resolution, good MolProbity score, and other chain-level criteria. Then each residue was critically tested for adequate local map quality to firmly support its conformation, which must also be free of serious clashes or covalent-geometry outliers. The resulting Top2018 pre-filtered datasets have been released on the Zenodo online web service and is freely available for all uses under a Creative Commons license. Currently, one dataset is residue-filtered on mainchain plus Cβ atoms, and a second dataset is full-residue filtered; each is available at 4 different sequence-identity levels. Here, we illustrate both statistics and examples that show the beneficial consequences of residue-level filtering. That process is necessary because even the best of structures contain a few highly disordered local regions with poor density and low-confidence conformations that should not be included in reference data. Therefore the open distribution of these very large, pre-filtered reference datasets constitutes a notable advance for structural bioinformatics and the fields that depend upon it.

The Top2018 dataset provides the first representative sample of 3D protein structure for which excellence of experimental data constrains the detailed local conformation to be correct for essentially all 3 million residues included. Earlier generations of residue-filtered datasets were central in developing MolProbity validation used worldwide, and now Zenodo has enabled anyone to use out latest version as a sound basis for structural bioinformatics, protein design, prediction, improving biomedically important structures, or other applications.
Neural networks implicated in autobiographical memory training
Authors: Cȋrneci Dragoş , Onu Mihaela , Papasteri Claudiu C. , Georgescu Dana , Poalelungi Catalina , Sofonea Alexandra , Puşcaşu Nicoleta , Tanase Dumitru , Rădeanu Teofila , Toader Maria-Yaelle , Dogaru Andreea L. , Podină Ioana R. , Berceanu Alexandru I. , Carcea Ioana
Published: October 2021

Training of autobiographical memory has been proposed as intervention to improve cognitive functions. The neural substrates for such improvements are poorly understood. Several brain networks have been previously linked to autobiographical recollections, including the default mode network (DMN) and the sensorimotor network. Here we tested the hypothesis that different neural networks support distinct aspects of memory improvement in response to training on a group of 59 subjects. We found that memory training increases DMN connectivity, and this associates with improved recollection of cue-specific memories. On the contrary, training decreased connectivity in the sensorimotor network, a decrease that correlated with improved ability for voluntary recall. Moreover, only decreased sensorimotor connectivity associated with training-induced decrease in the TNFα immunological factor, which has been previously linked to improved cognitive performance. We identified functional and biochemical factors that associate with distinct memory processes improved by autobiographical training. Pathways which connect autobiographical memory to both high level cognition and somatic physiology are discussed.
A Minimum Perturbation Theory of Deep Perceptual Learning
Authors: Shan Haozhe , Sompolinsky Haim
Published: October 2021

Perceptual learning (PL) involves long-lasting improvement in perceptual tasks following extensive training and is accompanied by modified neuronal responses in sensory cortical areas in the brain. Understanding the dynamics of PL and the resultant synaptic changes is important for causally connecting PL to the observed neural plasticity. This is theoretically challenging because learning-related changes are distributed across many stages of the sensory hierarchy. In this work, we modeled the sensory hierarchy as a deep nonlinear neural network and studied PL of fine discrimination, a common and well-studied paradigm of PL. Using tools from statistical physics, we developed a mean-field theory of the network in the limit of large number of neurons and large number of examples. Our theory suggests that, in this “thermodynamic” limit, the input-output function of the network can be exactly mapped to that of a deep linear network, allowing us to characterize the space of solutions for the task. Surprisingly, we found that modifications of synaptic weights in lower levels of the hierarchy are both sufficient and necessary for PL. To address the degeneracy of the space of solutions, we postulate that PL dynamics are constrained by a normative “minimum perturbation” (MP) principle, which favors weight matrices with minimal changes relative to their pre-learning values. Interestingly, MP plasticity induces changes to weights and neural representations in all layers of the network, except for the readout weight vector. In addition, such plasticity can be learned simply through slow learning. We further elucidate the properties of MP changes and compare them against experimental findings. Overall, our statistical mechanics theory of PL provides mechanistic and normative understanding of several important empirical findings of PL.
Improved Ultrasound Localization Microscopy based on Microbubble Uncoupling via Transmit Excitation (MUTE)
Authors: Kim Jihun , Lowerison Mathew R. , Sekaran Nathiya Chandra , Kou Zhengchang , Dong Zhijie , Oelze Michael L. , Llano Daniel A. , Song Pengfei
Published: October 2021

Ultrasound localization microscopy (ULM) demonstrates great potential for visualization of tissue microvasculature at depth with high spatial resolution. The success of ULM heavily depends on the robust localization of isolated microbubbles (MBs), which can be challenging in vivo especially within larger vessels where MBs can overlap and cluster close together. While MB dilution alleviates the issue of MB overlap to a certain extent, it drastically increases the data acquisition time needed for MBs to populate the microvasculature, which is already on the order of several minutes using recommended MB concentrations. Inspired by optical super-resolution imaging based on stimulated emission depletion (STED), here we propose a novel ULM imaging sequence based on microbubble uncoupling via transmit excitation (MUTE). MUTE “silences” MB signals by creating acoustic nulls to facilitate MB separation, which leads to robust localization of MBs especially under high concentrations. The efficiency of localization accomplished via the proposed technique was first evaluated in simulation studies with conventional ULM as a benchmark. Then an in vivo study based on the chorioallantoic membrane (CAM) of chicken embryos showed that MUTE could reduce the data acquisition time by half thanks to the enhanced MB separation and localization. Finally, the performance of MUTE was validated in an in vivo mouse brain study. These results demonstrate the high MB localization efficacy of MUTE-ULM, which contributes to a reduced data acquisition time and improved temporal resolution for ULM.
Intergenerational transport of double-stranded RNA inC. eleganscan limit heritable epigenetic changes
Authors: Shugarts Nathan , Sathya Aishwarya , Yi Andrew L. , Chan Winnie M. , Marré Julia A. , Jose Antony M.
Published: October 2021

RNAs in circulation carry sequence-specific regulatory information between cells in plant, animal, and host-pathogen systems. Such RNA can cross generational boundaries, as evidenced by somatic double-stranded RNA (dsRNA) in the nematodeC. eleganssilencing genes of matching sequence in progeny. Here we dissect the intergenerational path taken by dsRNA from parental circulation and discover that cytosolic import through the dsRNA importer SID-1 in the parental germline and/or developing progeny varies with developmental time and dsRNA substrates. Loss of SID-1 enhances initiation of heritable RNA silencing within the germline and causes changes in the expression of thesid-1-dependentgenesdg-1that last for more than 100 generations after restoration of SID-1. The SDG-1 protein is enriched in perinuclear germ granules required for heritable RNA silencing but is expressed from a retrotransposon targeted by such silencing. This auto-inhibitory loop suggests how retrotransposons could persist by hosting genes that regulate their own silencing.
De novoSNP calling reveals the candidate genes regulating days to flowering through interspecies GWAS ofAmaranthusgenus
Authors: Lin Ya-Ping , Wu Tien-Hor , Chan Yan-Kuang , van Zonneveld Maarten , Schafleitner Roland
Published: October 2021

Amaranths serve as pseudo cereals and also as traditional leafy vegetables worldwide. In addition to high vigor and richness in nutrients, drought and salinity tolerance of amaranth makes it a promising vegetable to acclimatize to the effects of global climate change. The World Vegetable Center genebank conserves about 1,000 amaranth accessions and various agronomic properties of these accessions were recorded during seed regeneration over decades. In this study, we verified the taxonomic annotation of the germplasm based on a 15K SNP set. Besides, in the assumption that the yield components of grain amaranths are different from those of leaf amaranths, we observed that grain amaranths presented larger inflorescences and earlier flowering than leaf amaranths. Dual-purpose amaranth showed larger leaves than leaf amaranths and later flowering than grain amaranths, which seemed reasonable because farmers can harvest more leaves during the prolonged vegetable stage, which also provides recovery time to enrich grain production. Considering frequent interspecies hybridization among grain amaranth complex, we proposed an interspecies GWAS for days to flowering, identifying aAGL20/SOC1homolog. Meanwhile, another GWAS using onlyA. tricoloraccessions revealed six candidate genes homologous tolba1,bri1,sgs1andfca. These homologous genes were involved in the regulation of flowering time in Arabidopsis. This study revealed the usefulness of genotypes for species demarcation in the genusAmaranthusand the potential of interspecies GWAS to detect QTLs across different species, opening up the possibility of targeted introduction of specific genetic variants into differentAmaranthusspecies.
Cryo-sensitive aggregation triggers NLRP3 inflammasome assembly in cryopyrin-associated periodic syndrome
Authors: Karasawa Tadayoshi , Komada Takanori , Yamada Naoya , Aizawa Emi , Mizushina Yoshiko , Watanabe Sachiko , Baatarjav Chintogtokh , Matsumura Takayoshi , Takahashi Masafumi
Published: October 2021

Cryopyrin-associated periodic syndrome (CAPS) is an autoinflammatory syndrome caused by mutations of NLRP3, which was originally identified as cryopyrin. Familial cold autoinflammatory syndrome (FCAS), the mildest form of CAPS, is characterized by cold-induced inflammation induced by the overproduction of IL-1β. However, the molecular mechanism of how mutated NLRP3 causes inflammasome activation in CAPS remains unclear. Here, we found that CAPS-associated NLRP3 mutants form cryo-sensitive aggregates that function as a scaffold for inflammasome activation. Cold exposure promoted inflammasome assembly and subsequent IL-1β release triggered by mutated NLRP3. While K+ efflux was dispensable, Ca2+ was indispensable for mutated NLRP3-mediated inflammasome assembly. Notably, Ca2+ influx was induced during mutated NLRP3-mediated inflammasome assembly. Furthermore, caspase-1 inhibition prevented Ca2+ influx and inflammasome assembly induced by the mutated NLRP3, suggesting a feed-forward Ca2+ influx loop triggered by mutated NLRP3. Thus, the mutated NLRP3 forms cryo-sensitive aggregates to promote inflammasome assembly distinct from canonical NLRP3 inflammasome activation.
quickBAM: a parallelized BAM file access API for high throughput sequence analysis informatics
Authors: Pitman T. Anders , Huang Xiaomeng , Marth Gabor T. , Qiao Yi
Published: October 2021

Motivation

In time-critical clinical settings, such as precision medicine, genomic data needs to be processed as fast as possible to arrive at data-informed treatment decisions in a timely fashion. While sequencing throughput has dramatically increased over the past decade, bioinformatics analysis throughput has not, and consequently has now turned into the primary bottleneck. Modern computational hardware are capable of much higher performance than current genomic informatics algorithms can typically utilize, therefore presenting opportunities for significant improvement of performance. Accessing the raw sequencing data from BAM files, for example, is a necessary and time-consuming step in nearly all sequence analysis tools, however existing programming libraries for BAM access do not take full advantage of the parallel input/output capabilities of storage devices.

Results

In an effort to stimulate the development of a new generation of faster sequence analysis tools, We developed quickBAM, a software library to accelerate sequencing data access by exploiting the parallelism in commodity storage hardware currently widely available. We demonstrate that analysis software ported to quickBAM consistently outperforms their current versions, in some cases finishing an analysis in under 4 minutes while the original version took 1.5 hours, using the same storage solution.

Availability and Implementation

Open source and freely available athttps://gitlab.com/yiq/quickbam/, we envision that quickBAM will enable a new generation of high performance informatics tools, either directly boosting their performance if they are currently dataaccess bottlenecked, or allow data-access to keep up with further optimizations in algorithms and compute techniques.

Contact

yi.qiao@genetics.utah.edu.
SARS-CoV-2 hijacks neutralizing dimeric IgA for enhanced nasal infection and injury
Authors: Zhou Biao , Zhou Runhong , Chan Jasper Fuk-Woo , Zeng Jianwei , Zhang Qi , Yuan Shuofeng , Liu Li , Robinot Rémy , Shan Sisi , Ge Jiwan , Kwong Hugo Yat-Hei , Zhou Dongyan , Xu Haoran , Chan Chris Chung-Sing , Poon Vincent Kwok-Man , Chu Hin , Yue Ming , Kwan Ka-Yi , Chan Chun-Yin , Liu Na , Chan Chris Chun-Yiu , Chik Kenn Ka-Heng , Du Zhenglong , Au Ka-Kit , Huang Haode , Man Hiu-On , Cao Jianli , Li Cun , Wang Ziyi , Zhou Jie , Song Youqiang , Yeung Man-Lung , To Kelvin Kai-Wang , Ho David D. , Chakrabarti Lisa A. , Wang Xinquan , Zhang Linqi , Yuen Kwok-Yung , Chen Zhiwei
Published: October 2021

Robust severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection in nasal turbinate (NT) accounts for high viral transmissibility, yet whether neutralizing IgA antibodies can control it remains unknown. Here, we evaluated receptor binding domain (RBD)-specific monomeric B8-mIgA1 and B8-mIgA2, and dimeric B8-dIgA1 and B8-dIgA2 against intranasal SARS-CoV-2 challenge in Syrian hamsters. These antibodies exhibited comparably potent neutralization against authentic virus by competing with human angiotensin converting enzyme-2 (ACE2) receptor for RBD binding. While reducing viruses in lungs, pre-exposure intranasal B8-dIgA1 or B8-dIgA2 led to 81-fold more infectious viruses and severer damage in NT than placebo. Virus-bound B8-dIgA1 and B8-dIgA2 could engage CD209 as an alternative receptor for entry into ACE2-negative cells and allowed viral cell-to-cell transmission. Cryo-EM revealed B8 as a class II neutralizing antibody binding trimeric RBDs in 3-up or 2-up/1-down conformation. Therefore, RBD-specific neutralizing dIgA engages an unexpected action for enhanced SARS-CoV-2 nasal infection and injury in Syrian hamsters.
The Evolution of Larger Size in High Altitude Drosophila melanogaster has a Polymorphic Genetic Architecture
Authors: Sprengelmeyer Quentin D. , Lack Justin B. , Braun Dylan T. , Monette Matthew J. , Pool John E.
Published: October 2021

Important uncertainties persist regarding the genetic architecture of adaptive trait evolution in natural populations, including the number of genetic variants involved, whether they are drawn from standing genetic variation, and whether directional selection drives them to complete fixation. Here, we take advantage of a unique natural population of Drosophila melanogaster from the Ethiopian highlands, which has evolved larger body size than any other known population of this species. We apply a bulk segregant quantitative trait locus (QTL) mapping approach to four unique crosses between highland Ethiopian and lowland Zambian populations for both thorax length and wing length. Results indicated a persistently variable genetic basis for these evolved traits (with largely distinct sets of QTLs for each cross), and at least a moderately polygenic architecture with relatively strong effects present. We complemented these mapping experiments with population genetic analyses of QTL regions and gene ontology enrichment analysis, generating strong hypotheses for specific genes and functional processes that may have contributed to these adaptive trait changes.

Finally, we find that the genetic architectures our QTL mapping results for size traits mirror those from similar experiments on other recently-evolved traits in this species. Collectively, these studies suggest a recurring pattern of polygenic adaptation in this species, in which causative variants do not approach fixation and moderately strong effect loci are present.
Ligands with poly-fluorophenyl moieties promote a local structural rearrangement in the Spinach2 and Broccoli aptamers that increases ligand affinities
Authors: Anisuzzaman Sharif , Geraskin Ivan M , Ilgu Muslum , Bendickson Lee , Kraus George A , Nilsen-Hamilton Marit
Published: October 2021

The interaction of nucleic acids with their molecular targets often involves structural reorganization that may traverse a complex folding landscape. With the more recent recognition that many RNAs, both coding and noncoding, may regulate cellular activities by interacting with target molecules, it becomes increasingly important to understand the means by which nucleic acids interact with their targets and how drugs might be developed that can influence critical folding transitions. We have extensively investigated the interaction of the Spinach2 and Broccoli aptamers with a library of small molecule ligands modified by various extensions from the imido nitrogen of DFHBI (3,5-difluoro-4-hydroxybenzylidene imidazolinone) that reach out from the Spinach2 ligand binding pocket. Studies of the interaction of these compounds with the aptamers revealed that poly-fluorophenyl-modified ligands initiate a slow change in aptamer affinity that takes an extended time (half-life of ~40 min) to achieve. The change in affinity appears to involve an initial disruption of the entrance to the ligand binding pocket followed by a gradual lockdown for which the most likely driving force is an interaction of the gateway adenine with a nearby 2’OH group. These results suggest that poly-fluorophenyl modifications might increase the ability of small molecule drugs to disrupt local structure and promote RNA remodeling.
The Effect of Headgear Use on Concussion Injury Rates in High School Lacrosse
Authors: Herman Daniel C. , Caswell Shane V. , Kelshaw Patricia M. , Vincent Heather K. , Lincoln Andrew E.
Published: October 2021

Objectives

The use of headgear is a controversial issue in girls’ lacrosse. We compared concussion rates among high school lacrosse players wearing versus not wearing lacrosse headgear.

Methods

Study participants included a sample of convenience of high schools with girls’ lacrosse from across the United States. Certified athletic trainers reported athlete exposure and injury data via the National Athletic Treatment, Injury and Outcomes Network during the 2019 through 2021 seasons. The Headgear cohort was inclusive of high schools from the state of Florida, which mandate the use of ASTM standard F3137 headgear, while the Non-Headgear cohort was inclusive of the remaining states, none of which have headgear mandates. Incidence Rate Ratios (IRR) and 95% Confidence Intervals (CI) were calculated. IRRs with corresponding CIs that excluded 1.00 were deemed statistically significant.

Results

141 concussions (Headgear: 25; Non-Headgear: 116) and 357,225 Athlete Exposures (AE) were reported (Headgear: 91,074AE; Non-Headgear: 266,151AE) across all games and practices. Overall, the concussion injury rate per 1000AE was significantly higher in the Non-Headgear cohort (0.44) than the Headgear Cohort (0.27) (IRR=1.59, 95% CI:1.03 - 2.45). The IRR was significantly higher for the Non-Headgear cohort during games (1.74, 95% CI: 1.00, 3.02) but not for practices (1.42, 95% CI: 0.71, 2.83).

Conclusions

These findings indicate that concussion rates among high school girls’ lacrosse players not wearing headgear were 59% higher than those wearing headgear. These data support the use of protective headgear to reduce the risk of concussion among high school female lacrosse athletes.

What are the new findings

The use of lacrosse headgear meeting the ASTM F3137 standard was associated with a lower risk of experiencing a concussion injury among high school girls’ lacrosse players.

How might these findings impact clinical practice in the future?

Lacrosse headgear may be warranted for use for concussion risk mitigation among high school girls’ lacrosse players.

Lacrosse headgear may be considered for concussion risk mitigation at other levels of play such as the youth or collegiate levels; further study is warranted.
Minority and Rural Coronavirus Insights Study (MRCIS): The Need for Targeted SARS CoV-2 Vaccination Efforts in Minority Populations
Authors: Landry Latrice G. , Lee LaTasha , Chalasani Nishanth , Xu Liou , Stair Taylor , Puckrein Gary , Meyer William A. , Wiltz Gary , Sampson Marian , Gregerson Paul , Barron Charles , Marable Jeffrey , Akinboboye Ola
Published: October 2021

Importance

Racial and ethnic minority populations have been disproportionately affected in terms of hospitalizations and deaths during the COVID-19 pandemic. Vaccine uptake remains a barrier to full population inoculation against this highly infectious disease.

Objective

The purpose of this report is to describe SARS-CoV-2 vaccine interest rates in a racially, geographically, and ethnically diverse study cohort and characterize vaccine interest across a racially, ethnically, and geographically diverse study population.

Design

This report describes responses to a survey administered between November 2020 and May 2021 using a community convenience sample through a partnership between the National Minority Quality Forum (NMQF) and Federally Qualified Health Centers (FQHCs) as part of the Minority and Rural Coronavirus Insights Study (MRCIS). Analysis of survey responses from 3,624 participants are provided.

Results

Early data from the MRCIS cohort suggest that “SARS-CoV-2 vaccine hesitancy” is more prevalent in Black versus Non-Hispanic Whites survey respondents, and the Hispanic community has positive interest in the vaccine, to a similar degree as Whites. The persistent presence of “vaccine undecideds” across different sites and racial/ethnic groups uncovers the need for more public health efforts to influence positive views about vaccination.

Conclusion

These findings highlights the urgent need for interventional educational campaigns targeted at populations at risk of low vaccine interest. Focused efforts are needed to combat misinformation and explain the vaccine’s safety and effectiveness to promote its uptake and avoid low inoculation rates. Public health communication must consider differences in population groups, regions, and social determinants of health to fully address vaccine uptake disparities and overcome alleged hesitancy.

Key Points

Willingness to receive the SARS CoV-2 varies among minority populations.

“SARS-CoV-2 vaccine hesitancy” is more prevalent in the non-Hispanic Black population than the non-Hispanic White and Hispanic populations.

Public health infrastructure is needed in underserved communities for efficient assessment and targeted communication of public health priorities such as the SARS CoV-2 vaccination.
Using sero-epidemiology to monitor disparities in vaccination and infection with SARS-CoV-2
Authors: Routledge Isobel , Takahashi Saki , Epstein Adrienne , Hakim Jill , Janson Owen , Turcios Keirstinne , Vinden Jo , Risos John Tomas , Baniqued Margaret Rose , Pham Lori , Di Germanio Clara , Busch Michael , Kushel Margot , Greenhouse Bryan , Rodríguez-Barraquer Isabel
Published: October 2021

Background

As COVID-19 vaccines continue to be rolled-out, the “double burden” of health disparities in both exposure to infection and vaccination coverage intersect to determine the current and future patterns of infection, immunity, and mortality. Serology provides a unique opportunity to measure biomarkers of infection and vaccination simultaneously, and to relate these metrics to demographic and geographic factors.

Methods

Leveraging algorithmically selected residual serum samples from two hospital networks in San Francisco, we sampled 1014 individuals during February 2021, capturing transmission during the first 11 months of the epidemic and the early roll out of vaccination. These samples were tested using two serologic assays: one detecting antibodies elicited by infection, and not by vaccines, and one detecting antibodies elicited by both infection and vaccination. We used Bayesian statistical models to estimate the proportion of the population that was naturally infected and the proportion protected due to vaccination.

Findings

We estimated that the risk of prior infection of Latinx residents was 5.3 (95% CI: 3.2 - 10.3) times greater than the risk of white residents aged 18-64 and that white San Francisco residents over the age of 65 were twice as likely (2.0, 95% CI: 1.1 - 4.6) to be vaccinated as Black residents. We also found socioeconomically deprived zipcodes in the city had high probabilities of natural infections and lower vaccination coverage than wealthier zipcodes.

Interpretation

Using a platform we created for SARS-CoV-2 serologic data collection in San Francisco, we characterized and quantified the stark disparities in infection rates and vaccine coverage by demographic groups over the first year of the pandemic. While the arrival of the SARS-CoV-2 vaccine has created a ‘light at the end of the tunnel’ for this pandemic, ongoing challenges in achieving and maintaining equity must also be considered.

Funding

NIH, NIGMS, Schmidt Science Fellows in partnership with the Rhodes Trust and the Chan Zuckerberg Biohub.
Beyond the limits of circadian entrainment: Non-24-hour sleep-wake disorder, shift work, and social jet lag
Authors: Diekman Casey O. , Bose Amitabha
Published: October 2021

Abstract

While the vast majority of humans are able to entrain their circadian rhythm to the 24-hour light-dark cycle, there are numerous individuals who are not able to do so due to disease or societal reasons. We use computational and mathematical methods to analyze a well-established model of human circadian rhythms to address cases where individuals do not entrain to the 24-hour light-dark cycle, leading to misalignment of their circadian phase. For each case, we provide a mathematically justified strategy for how to minimize circadian misalignment. In the case of non-24-hour sleep-wake disorder, we show why appropriately timed bright light therapy induces entrainment. With regard to shift work, we explain why reentrainment times following transitions between day and night shifts are asymmetric, and how higher light intensity enables unusually rapid reentrainment after certain transitions. Finally, with regard to teenagers who engage in compensatory catch-up sleep on weekends, we propose a rule of thumb for sleep and wake onset times that minimizes circadian misalignment due to this type of social jet lag. In all cases, the primary mathematical approach involves understanding the dynamics of entrainment maps that measure the phase of the entrained rhythm with respect to the daily onset of lights.
The Contribution of Health Behaviors to Depression Risk across Birth Cohorts
Authors: Gueltzow Maria , Bijlsma Maarten J. , van Lenthe Frank J. , Myrskylä Mikko
Published: October 2021

Background

More recent birth cohorts are at a higher depression risk than cohorts born in the early twentieth century. We aimed to investigate to what extent changes in alcohol consumption, smoking, physical activity and obesity, contribute to these birth cohort variations.

Methods

We analyzed panel data from US adults born 1916-1966 enrolled in the Health and Retirement Study (N=163,760 person-years). We performed a counterfactual decomposition analysis by combining age-period-cohort models with g-computation. This allowed us to compare the predicted probability of elevated depressive symptoms (CES-D 8 score ≥3) in the natural course to a counterfactual scenario where all birth cohorts had the health behavior of the 1945 birth cohort. We stratified analyses by sex and race/ethnicity.

Results

Depression risk of the 1916-1949 and 1950-1966 birth cohort would be on average 2% (-2.3 to -1.7) and 0.5% (-0.9 to -0.1) higher had they had the alcohol consumption levels of the 1945 cohort. In the counterfactual with the 1945 BMI distribution, depression risk is on average 2.1% (1.8 to 2.4) higher for the 1916-1940 cohorts and 1.8% (-2.2 to -1.5) lower for the 1950-1966 cohorts. We find no cohort variations in depression risk for smoking and physical activity. The contribution of alcohol is more pronounced for Whites than for other race/ethnicity groups, and the contribution of BMI more pronounced for women than for men.

Conclusion

Increased obesity levels exacerbated depression risk in recent birth cohorts in the US, while drinking patterns only played a minor role.
Prediction of Unplanned 30- day Readmission for ICU Patients with Heart Failure
Authors: Pishgar M , Theis J , Del Rios M , Ardati A , Anahideh H , Darabi H
Published: October 2021

Background

Intensive Care Unit (ICU) readmissions in patients with Heart Failure (HF) result in a significant risk of death and financial burden for patients and healthcare systems. Prediction of at-risk patients for readmission allows for targeted interventions that reduce morbidity and mortality.

Methods and Results

We presented a process mining approach for the prediction of unplanned 30-day readmission of ICU patients with HF. A patient’s health records can be understood as a sequence of observations called event logs; used to discover a process model. Time information was extracted using the DREAM (Decay Replay Mining) algorithm. Demographic information and severity scores upon admission were then combined with the time information and fed to a Neural Network (NN) model to further enhance the prediction efficiency.

Results

By using the Medical Information Mart for Intensive Care III (MIMIC-III) dataset of 3411 ICU patients with HF, our proposed model yielded an Area Under the Receiver Operating Characteristics (AUROC) of 0.920.

Conclusions

The proposed approach was capable of modeling the time-related variables and incorporating the medical history of patients from prior hospital visits for prediction. Thus, our approach significantly improved the outcome prediction compared to that of other ML-based models and health calculators.
Use of Machine Learning for Long Term Planning and Cost Minimization in Healthcare Management
Authors: Kabir Sadia Binta , Shuvo Salman Sadiq , Ahmed Helal Uddin
Published: October 2021

The Healthcare system of a country is a crucial infrastructure that requires long-term capacity planning. The covid 19 outbreak pointed to the necessity of adequate hospital capacity, especially for developing countries like Bangladesh. The existing infrastructure planning of these countries emphasizes short-term goals and lacks vision planning for a long time horizon. It is in the country’s best interest to make long-term capacity expansion plans, a strategy the developed countries banked to provide adequate healthcare facilities to their residents. However, no single solution is appropriate for a different region. Hence, it is required to comprehensively study the situation and constraints of the specific region before providing expensive capacity expansion plans. This work focuses on applying a deep Reinforcement Learning based long-term hospital bed capacity expansion plan. We utilize the RNN-LSTM based population forecast, deep Reinforcement Learning (RL) based policy-making, and state-of-the-art Artificial Intelligence techniques to provide a solution. We perform a case study for the Abhaynagar Upazila of Jessore, one of the largest cities in the southwest part of Bangladesh, to analyze the benefits of such an approach compared to existing myopic policies. The experiment results show that the deep RL-based policy significantly minimizes cost over a 30-year expansion plan.
Covid-19 vaccine perceptions in Senegal and in Mali: a mixed approach
Authors: Fournier-Tombs Eleonore , Diouf Massamba , Maiga Abdine , Faye Sylvain , Ndoye Tidiane , Haidara Lalla , Batchily Moussa , Castet-Renard Céline
Published: October 2021

This paper presents the results of two qualitative surveys in Senegal and in Mali, which include questions about hesitancy to the COVID-19 vaccine between April and June 2021. It took place within a larger 2-year research project involving researchers in Senegal, Mali and Canada which examines the uses of artificial intelligence technologies in the fight against COVID-19. The study involved 1000 respondents in Senegal and 555 in Mali. The researchers found that overall, 55% of respondents in Senegal and 52% of respondents in Mali did not plan to be vaccinated. Hesitancy was much higher in youth aged 15-35 in both cases, with 70% of youth in Senegal and 57% of youth in Mali not planning to be vaccinated, compared to only 42% of elderly in Senegal and 37% of elderly in Mali. The researchers did not find disparities between male and female respondents in Senegal but found some in Mali. They also found that those who had a member of the family with chronic disease (diabetes or hypertension) were slightly more likely to want to be vaccinated. Reasons for vaccine hesitancy fell in several categories, including fear of vaccine side-effects, disbelief in vaccine efficacy or usefulness, and general distrust in the public health system.