bluuebunny/crossref_metadata_2025_split huggingface dataset:
Metformin Suppresses SARS-CoV-2 in Cell Culture
Authors: Parthasarathy Haripriya , Tandel Dixit , Siddiqui Abdul Hamid , Harshan Krishnan H. 
Published: November 2021

ABSTRACTComorbidities such as diabetes worsen COVID-19 severity and recovery. Metformin, a first-line medication for type 2 diabetes, has antiviral properties and certain studies have also indicated its prognostic potential in COVID-19. Here, we report that metformin significantly inhibits SARS-CoV-2 growth in cell culture models. First, a steady increase in AMPK phosphorylation was detected as infection progressed, suggesting its important role during viral infection. Activation of AMPK in Calu3 and Caco2 cell lines using metformin revealed that metformin suppresses SARS-CoV-2 infectious titers up to 99%, in both naïve as well as infected cells. TCID50 values from dose-variation studies in infected cells were found to be 0.8 and 3.5 mM in Calu3 and Caco2 cells, respectively. Role of AMPK in metformin’s antiviral suppression was further confirmed using other pharmacological compounds, AICAR and Compound C. Collectively, our study demonstrates that metformin is effective in limiting the replication of SARS-CoV-2 in cell culture and thus possibly could offer double benefits s diabetic COVID-19 patients by lowering both blood glucose levels and viral load.
A tripartite structure, the complex nuclear receptor element (cNRE), is a cis-regulatory module of viral origin required for atrial chamber preferential gene expression
Authors: Santos Luana Nunes , da Souza Costa Ângela Maria , Nikolov Martin , Sampaio Allysson Coelho , Stockdale Frank E. , Wangø Gang F , Castillo Hozana Andrade , Grizante Mariana Bortoletto , Dudczig Stefanie , Vasconcelos Michelle , Rosenthal Nadia , Jusuf Patricia Regina , de Oliveira Paulo , de Freitas Matos Tatiana Guimarães , Nikovits William , Schubert Michael , Ramialison Mirana , Xavier-Neto José 
Published: November 2021

AbstractOptimal cardiac function requires appropriate contractile proteins in each heart chamber. Atria require slow myosins to act as variable reservoirs, while ventricles demand fast myosin for swift pumping functions. Hence, myosin is under chamber-biased cis-regulatory control to achieve this functional distribution. Failure in proper regulation of myosin genes can lead to severe congenital heart dysfunction. The precise regulatory input leading to cardiac chamber-biased expression remains uncharted. To address this, we computationally and molecularly dissected the quail Slow Myosin Heavy Chain III (SMyHC III) promoter that drives specific gene expression to the atria to uncover the regulatory information leading to chamber expression and understand their evolutionary origins. We show that SMyHC III gene states are autonomously orchestrated by a complex nuclear receptor cis-regulatory element (cNRE), a 32- bp sequence with hexanucleotide binding repeats. Using in vivo transgenic assays in zebrafish and mouse models, we demonstrate that preferential atrial expression is achieved by the combinatorial regulatory input composed of atrial activation motifs and ventricular repression motifs. Through comparative genomics, we provide evidence that the cNRE emerged from an endogenous viral element, most likely through infection of an ancestral host germline. Our study reveals an evolutionary pathway to cardiac chamber-specific expression.
Eliminating fibroblast activation protein-α expressing cells by photoimmunotheranostics
Authors: Jin Jiefu , Barnett James D. , Krishnamachary Balaji , Mironchik Yelena , Luo Catherine K. , Kobayashi Hisataka , Bhujwalla Zaver M. 
Published: November 2021

AbstractPhotoimmunotherapy (PIT) using an antibody conjugated to a near infrared dye IR700 is achieving significant success in target-specific elimination of cells. Fibroblast activation protein alpha (FAP-α) is an important target in cancer because of its expression by cancer associated fibroblasts (CAFs) as well as by some cancer cells. CAFs that express FAP-α have protumorigenic and immune suppressive functions. Using immunohistochemistry of human breast cancer tissue microarrays, we identified an increase of FAP-α+ CAFs in invasive breast cancer tissue compared to adjacent normal tissue. We found FAP-α expression increased in fibroblasts co-cultured with cancer cells. In proof-of-principle studies, we engineered human FAP-α overexpressing MDA-MB-231 and HT-1080 cancer cells and murine FAP-α overexpressing NIH-3T3 fibroblasts to evaluate several anti-FAP-α antibodies and selected AF3715 based on its high binding-affinity with both human and mouse FAP-α. After conjugation of AF3715 with the phthalocyanine dye IR700, the resultant antibody conjugate, FAP-α-IR700, was evaluated in cells and tumors for its specificity and effectiveness in eliminating FAP-α expressing cell populations with PIT. FAP-α-IR700-PIT resulted in effective FAP-α-specific cell killing in the engineered cancer cells and in two patient-derived CAFs in a dose-dependent manner. Following an intravenous injection, FAP-α-IR700 retention was three-fold higher than IgG-IR700 in FAP-α overexpressing tumors, and two-fold higher compared to wild-type tumors. FAP-α-IR700-PIT resulted in significant growth inhibition of tumors derived from FAP-α overexpressing human cancer cells. A reduction of endogenous FAP-α+ murine CAFs was identified at 7 days after FAP-α-IR700-PIT. FAP-α-targeted NIR-PIT presents a promising strategy to eliminate FAP-α+ CAFs.
Weighted Shoes in the Wild: Initial Insights into the Relationship Between the Effort of Walking and the Amount of Walking Performed
Authors: Wu Mailing R. , Adamczyk Peter G. , Collins Steven H. 
Published: November 2021

ABSTRACTPurposeWalking comprises a large portion of active energy expenditure in humans. Interventions that increase or decrease the energy expended on each step, such as ankle weights or energy-saving orthoses, may therefore strongly impact fitness. The overall effect of increasing or decreasing per-step energy use is unclear, however, because people may choose to walk less or more, respectively, in response.MethodsIn this study, healthy college students with normal body mass index wore weighted and unweighted shoes embedded with an inertial measurement unit for one week each. Community-based walking data were analyzed for number of steps, distance traveled and walking speed. Oxygen consumption using each set of shoes at a range of speeds were measured in a laboratory setting and used to estimate metabolic energy expended during community-based walking. A survey measured subjective response to each pair of shoes.ResultsThe weighted shoes increased per-step energy cost by about 26%. Subjects strongly disliked the weighted shoes (P = 0.001) and found them tiring (P = 0.003). Despite this dislike, subjects did not significantly reduce distance walked (P = 0.6), number of steps (P = 0.7), or average speed (P = 0.9) compared to normal shoes. This led to a small but not statistically significant increase in energy expended during walking over a five-day period (12.3 ± 9.6% increase, P = 0.2). On the final collection day this trend appeared to reverse, with fewer steps taken and lower metabolic energy expended with the weighted shoes. Twenty-four subjects were recruited but only ten completed the protocol, with dislike of the weighted shoe condition being the primary reason for dropout.ConclusionsIncreasing the energy cost of each step led to greater energy expended through walking. However, there are indications that behavioral changes would be greater with a longer intervention or increased retention. For example, the large dropout rate suggests that some subjects avoided walking with the weighted shoes entirely, simply by leaving the study. Follow-on studies among patient groups may reveal a fitness benefit to either increasing or reducing the energy cost of walking.
Induction of virus-induced gene silencing andin plantavalidation in cucurbits using the CFMMV-Cm vector
Authors: Rhee Sun-Ju , Jang Yoon Jeong , Park Jun-Young , Lee Gung Pyo 
Published: November 2021

AbstractVirus-induced gene silencing (VIGS) has been employed for the high-throughput analysis of endogenous gene function. We developed a CaMV 35S promoter-driven cucumber fruit mottle mosaic virus-Cm vector (pCF93) for the efficient generation of viral transcripts in plants. Using the novel pCF93 vector, we identified genes related to male sterility in watermelon (Citrullus lanatus), which is recalcitrant to genetic transformation. We previously reported reference-based andde novotranscriptomic profiling for the detection of differentially expressed genes between a male fertile line (DAH3615) and its near isogenic male sterile line (DAH3615-MS). Based on the RNA-seq results, we identified 38de novo-exclusive differentially expressed genes (DEDEGs) that are potentially responsible for male sterility. Partial genes of 200∼300bp were cloned into pCF93 which was then inoculated into DAH, a small type of watermelon that enables high-throughput screening with a small cultivation area. In this manner, we simultaneously characterized phenotypes associated with the 38 candidate genes in a common-sized greenhouse. Eight out of the 38 gene-silenced plants produced male sterile flowers with abnormal stamens and no pollens. Gene expression levels in flowers were validated via RT-qPCR. Stamen histological sections from male sterile floral buds and mature flowers showed developmental disruption and shrunken pollen sacs. Based on the current findings, we believe that the novel pCF93 vector and our VIGS system facilitate high-throughput analysis for the study of gene function in watermelons.One sentence summaryThe CaMV 35S promoter-driven cucumber fruit mottle mosaic virus-Cm vector (pCF93) facilitates large-scale validation of male sterility-related gene functions in watermelon.
Allele segregation analysis of F1 hybrids between independent Brassica allohexaploid lineages
Authors: Quezada-Martinez Daniela , Zou Jun , Zhang Wenshan , Meng Jinling , Batley Jacqueline , Mason Annaliese S. 
Published: November 2021

ABSTRACTIn the Brassica genus we find both diploid species (one genome) and allotetraploid species (two different genomes) but no naturally occurring hexaploid species (three different genomes, AABBCC). Although hexaploids can be produced via human intervention, these neo- polyploids have quite unstable genomes and usually suffer from severe genome reshuffling. Whether these genome rearrangements continue in later generations and whether genomic arrangements follow similar, reproducible patterns between different lines is still unknown. We crossed Brassica hexaploids resulting from different species combinations to produce five F1 hybrids, and analyzed the karyotypes of the parents and the F1 hybrids, as well as allele segregation in a resulting test-cross population via molecular karyotyping using SNP array genotyping. Although some genomic regions were found to be more likely to be duplicated, deleted or rearranged, a consensus pattern was not shared between genotypes. Brassica hexaploids had a high tolerance for fixed structural rearrangements, but which rearrangements occur and become fixed over many generations does not seem to show either strong reproducibility or to indicate selection for stability. On average, we observed 10 de novo chromosome rearrangements contributed almost equally from both parents to the F1 hybrids. At the same time, the F1 hybrid meiosis produced on average 8.6 new rearrangements. Hence, the increased heterozygosity in the F1 hybrid did not significantly improve genome stability in our hexaploid hybrids, and might have had the opposite effect. However, hybridization between lineages was readily achieved and may be exploited for future genetics and breeding purposes.
Cell Painting predicts impact of lung cancer variants
Authors: Caicedo Juan C. , Arevalo John , Piccioni Federica , Bray Mark-Anthony , Hartland Cathy L. , Wu Xiaoyun , Brooks Angela N. , Berger Alice H. , Boehm Jesse S. , Carpenter Anne E. , Singh Shantanu 
Published: November 2021

AbstractMost variants in most genes across most organisms have an unknown impact on the function of the corresponding gene. This gap in knowledge is especially acute in cancer, where clinical sequencing of tumors now routinely reveals patient-specific variants whose functional impact on the corresponding gene is unknown, impeding clinical utility. Transcriptional profiling was able to systematically distinguish these variants of unknown significance (VUS) as impactful vs. neutral in an approach called expression-based variant-impact phenotyping (eVIP). We profiled a set of lung adenocarcinoma-associated somatic variants using Cell Painting, a morphological profiling assay that captures features of cells based on microscopy using six stains of cell and organelle components. Using deep-learning-extracted features from each cell’s image, we found that cell morphological profiling (cmVIP) can predict variants’ functional impact and, particularly at the single-cell level, reveals biological insights into variants which can be explored in our public online portal. Given its low cost, convenient implementation, and single-cell resolution, cmVIP profiling therefore seems promising as an avenue for using non-gene-specific assays to systematically assess the impact of variants, including disease-associated alleles, on gene function.
evSeq: Cost-Effective Amplicon Sequencing of Every Variant in a Protein Library
Authors: Wittmann Bruce J. , Johnston Kadina E. , Almhjell Patrick J. , Arnold Frances H. 
Published: November 2021

ABSTRACTWidespread availability of protein sequence-fitness data would revolutionize both our biochemical understanding of proteins and our ability to engineer them. Unfortunately, even though thousands of protein variants are generated and evaluated for fitness during a typical protein engineering campaign, most are never sequenced, leaving a wealth of potential sequence-fitness information untapped. This largely stems from the fact that sequencing is unnecessary for many protein engineering strategies; the added cost and effort of sequencing is thus unjustified. Here, we present every variant sequencing (evSeq), an efficient protocol for sequencing a variable region within every variant gene produced during a protein engineering campaign at a cost of cents per variant. Execution of evSeq is simple, requires no sequencing experience to perform, relies only on resources and services typically available to biology labs, and slots neatly into existing protein engineering workflows. Analysis of evSeq data is likewise made simple by its accompanying software (found atgithub.com/fhalab/evSeq, documentation atfhalab.github.io/evSeq), which can be run on a personal laptop and was designed to be accessible to users with no computational experience. Low-cost and easy to use, evSeq makes collection of extensive protein variant sequence-fitness data practical.
TCR-BERT: learning the grammar of T-cell receptors for flexible antigen-xbinding analyses
Authors: Wu Kevin , Yost Kathryn E. , Daniel Bence , Belk Julia A. , Xia Yu , Egawa Takeshi , Satpathy Ansuman , Chang Howard Y. , Zou James 
Published: November 2021

AbstractThe T-cell receptor (TCR) allows T-cells to recognize and respond to antigens presented by infected and diseased cells. However, due to TCRs’ staggering diversity and the complex binding dynamics underlying TCR antigen recognition, it is challenging to predict which antigens a given TCR may bind to. Here, we present TCR-BERT, a deep learning model that applies self-supervised transfer learning to this problem. TCR-BERT leverages unlabeled TCR sequences to learn a general, versatile representation of TCR sequences, enabling numerous downstream applications. We demonstrate that TCR-BERT can be used to build state-of-the-art TCR-antigen binding predictors with improved generalizability compared to prior methods. TCR-BERT simultaneously facilitates clustering sequences likely to share antigen specificities. It also facilitates computational approaches to challenging, unsolved problems such as designing novel TCR sequences with engineered binding affinities. Importantly, TCR-BERT enables all these advances by focusing on residues with known biological significance. TCR-BERT can be a useful tool for T-cell scientists, enabling greater understanding and more diverse applications, and provides a conceptual framework for leveraging unlabeled data to improve machine learning on biological sequences.
Algorithmic Parameter Estimation and Uncertainty Quantification for Hodgkin-Huxley Neuron Models
Authors: Wang Y. Curtis , Sinha Nirvik , Rudi Johann , Velasco James , Idumah Gideon , Powers Randall K. , Heckman Charles J. , Chardon Matthieu 
Published: November 2021

AbstractExperimental data-based parameter search for Hodgkin–Huxley-style (HH) neuron models is a major challenge for neuroscientists and neuroengineers. Current search strategies are often computationally expensive, are slow to converge, have difficulty handling nonlinearities or multimodalities in the objective function, or require good initial parameter guesses. Most important, many existing approaches lack quantification of uncertainties in parameter estimates even though such uncertainties are of immense biological significance. We propose a novel method for parameter inference and uncertainty quantification in a Bayesian framework using the Markov chain Monte Carlo (MCMC) approach. This approach incorporates prior knowledge about model parameters (as probability distributions) and aims to map the prior to a posterior distribution of parameters informed by both the model and the data. Furthermore, using the adaptive parallel tempering strategy for MCMC, we tackle the highly nonlinear, noisy, and multimodal loss function, which depends on the HH neuron model. We tested the robustness of our approach using the voltage trace data generated from a 9-parameter HH model using five levels of injected currents (0.0, 0.1, 0.2, 0.3, and 0.4 nA). Each test consisted of running the ground truth with its respective currents to estimate the model parameters. To simulate the condition for fitting a frequency-current (F-I) curve, we also introduced an aggregate objective that runs MCMC against all five levels simultaneously. We found that MCMC was able to produce many solutions with acceptable loss values (e.g., for 0.0 nA, 889 solutions were within 0.5% of the best solution and 1,595 solutions within 1% of the best solution). Thus, an adaptive parallel tempering MCMC search provides a “landscape” of the possible parameter sets with acceptable loss values in a tractable manner. Our approach is able to obtain an intelligently sampled global view of the solution distributions within a search range in a single computation. Additionally, the advantage of uncertainty quantification allows for exploration of further solution spaces, which can serve to better inform future experiments.
Nonquantal Transmission at the Vestibular Hair Cell-Calyx Synapse: KLV Currents Modulate Fast Electrical and Slow K+ Potentials in the Synaptic Cleft
Authors: Govindaraju Aravind Chenrayan , Quraishi Imran H. , Lysakowski Anna , Eatock Ruth Anne , Raphael Robert M. 
Published: November 2021

AbstractVestibular hair cells transmit information about head position and motion across synapses to primary afferent neurons. At some of these synapses, the afferent neuron envelopes the hair cell, forming an enlarged synaptic terminal called a calyx. The vestibular hair cell-calyx synapse supports a mysterious form of electrical transmission that does not involve gap junctions termed nonquantal transmission (NQT). The NQT mechanism is thought to involve the flow of ions from the pre-synaptic hair cell to the post-synaptic calyx through low-voltage-activated channels driven by changes in cleft [K+] as K+ exits the hair cell. However, this hypothesis has not been tested with a quantitative model and the possible role of an electrical potential in the cleft has remained speculative. Here we present a computational model that captures salient experimental observations of NQT and identifies overlooked features that corroborate the existence of an electrical potential (ϕ) in the synaptic cleft. We show that changes in cleft ϕ reduce transmission latency and illustrate the relative contributions of both cleft [K+] and ϕ to the gain and phase of NQT. We further demonstrate that the magnitude and speed of NQT depend on calyx morphology and that increasing calyx height reduces action potential latency in the calyx afferent. These predictions are consistent with the idea that the calyx evolved to enhance NQT and speed up vestibular signals that drive neural circuits controlling gaze, balance, and orientation.Significance StatementThe ability of the vestibular system to drive the fastest reflexes in the nervous system depends on rapid transmission of mechanosensory signals at vestibular hair cell synapses. In mammals and other amniotes, afferent neurons form unusually large calyx terminals on certain hair cells, and communication at these synapses includes nonquantal transmission (NQT), which avoids the synaptic delay of quantal transmission. We present a quantitative model that shows how NQT depends on the extent of the calyx covering the hair cell and attributes the short latency of NQT to changes in synaptic cleft electrical potential caused by current flowing through open potassium channels in the hair cell. This previously undescribed mechanism may act at other synapses.