bluuebunny/crossref_metadata_2025_split huggingface dataset:
Elucidating Collective Translocation of Nanoparticles Across the Skin Lipid Barrier: A Molecular Dynamics Study
Authors: Badhe Yogesh , Sharma Pradyumn , Gupta Rakesh , Rai Beena 
Published: January 2022

AbstractThe top layer of skin, the stratum corneum, provides a formidable barrier to the skin. Nanoparticles are utilized and further explored for personal and health care applications related to the skin. In past years several researchers have studied the translocation and permeation of nanoparticles of various shapes, sizes, and surface chemistry through the cell membranes. Most of these studies focused on a single nanoparticle and a simple bilayer system, whereas skin has a highly complex lipid membrane architecture. Moreover, it is highly unlikely that a nanoparticle formulation applied on the skin will not have multiple nanoparticle-nanoparticle and skin-nanoparticle interactions. In this study, we have utilized coarse-grained MARTINI molecular dynamics simulations to assess the interactions of two types (bare and dodecane-thiol coated) of nanoparticles with two models (single bilayer and double bilayer) of skin lipid membranes. The nanoparticles were found to be partitioned from the water layer to the lipid membrane as an individual entity as well as in the cluster form. It was discovered that each nanoparticle reached the interior of both single bilayer and double bilayer membrane irrespective of nanoparticle type and concentration, though coated particles were observed to efficiently traverse across bilayer when compared with bare particles. The coated nanoparticles also created a single large cluster inside the membrane, whereas bare nanoparticles were found in small clusters. Both the nanoparticles exhibited preferential interactions with cholesterol molecules present in the lipid membrane as compared to other lipid components of the membrane. We have also observed that the single membrane model exhibited unrealistic instability at moderate to the higher concentration of nanoparticles, and hence for translocation study, at minimum double bilayer model should be employed.
Network architecture producing swing to stance transitions in an insect walking system
Authors: Strohmer Beck , Mantziaris Charalampos , Kynigopoulos Demos , Manoonpong Poramate , Larsen Leon Bonde , Büschges Ansgar 
Published: January 2022

AbstractThe walking system of the stick insect is one of the most thoroughly described invertebrate systems. We know a lot about the role of sensory input in the control of stepping of a single leg. However, the neuronal organization and connectivity of the central neural networks underlying the rhythmic activation and coordination of leg muscles still remain elusive. It is assumed that these networks can couple in the absence of phasic sensory input due to the observation of spontaneous recurrent patterns (SRPs) of coordinated motor activity equivalent to fictive stepping-phase transitions. Here we sought to quantify the phase of motor activity within SRPs in the isolated and interconnected meso- and metathoracic ganglia. We show that SRPs occur not only in the meso-, but also in the metathoracic ganglia of the stick insect, discovering a qualitative difference between them. We construct a network based on neurophysiological data capable of reproducing the measured SRP phases to investigate this difference. By comparing network output to the biological measurements we confirm the plausibility of the architecture and provide a hypothesis to account for these qualitative differences. The neural architecture we present couples individual central pattern generators to reproduce the fictive stepping-phase transitions observed in deafferented stick insect preparations after pharmacological activation, providing insights into the neural architecture underlying coordinated locomotion.
Automatically tracking feeding behavior in populations of foraging C. elegans
Authors: Bonnard Elsa , Liu Jun , Zjacic Nicolina , Alvarez Luis , Scholz Monika 
Published: January 2022

AbstractC. elegans feeds on bacteria and other small microorganisms which it ingests using its pharynx, a neuromuscular pump. Currently, measuring feeding behavior requires tracking a single animal, indirectly estimating food intake from population-level metrics, or using restrained animals. To enable large throughput feeding measurements of unrestrained, crawling worms on agarose plates at a single worm resolution, we developed an imaging protocol and a complementary image analysis tool called PharaGlow. We image up to 50 unrestrained crawling worms simultaneously and extract locomotion and feeding behaviors. We demonstrate the tool’s robustness and high-throughput capabilities by measuring feeding in different use-case scenarios, such as through development, with genetic and chemical perturbations that result in faster and slower pumping, and in the presence or absence of food. Finally, we demonstrate that our tool is capable of long-term imaging by showing behavioral dynamics of mating animals over an hour. The low-resolution fluorescence microscopes required are readily available in C. elegans laboratories, and in combination with our python-based analysis workflow makes this methodology easily accessible. PharaGlow therefore enables the observation and analysis of the temporal dynamics of food intake and locomotory behaviors with high-throughput and precision in a user-friendly system.
rrQNet: protein contact map quality estimation by deep evolutionary reconciliation
Authors: Roche Rahmatullah , Bhattacharya Sutanu , Shuvo Md Hossain , Bhattacharya Debswapna 
Published: January 2022

ABSTRACTProtein contact maps have proven to be a valuable tool in the deep learning revolution of protein structure prediction, ushering in the recent breakthrough by AlphaFold2. However, self-assessment of the quality of predicted structures are typically performed at the granularity of 3D coordinates as opposed to directly exploiting the rotation- and translation-invariant 2D contact maps. Here we present rrQNet, a deep learning method for self-assessment in 2D by contact map quality estimation. Our approach is based on the intuition that for a contact map to be of high quality, the residue pairs predicted to be in contact should be mutually consistent with the evolutionary context of the protein. The deep neural network architecture of rrQNet implements this intuition by cascading two deep modules—one encoding the evolutionary context and the other performing evolutionary reconciliation. The penultimate stage of rrQNet estimates the quality scores at the interacting residue-pair level, which are then aggregated for estimating the quality of a contact map. This design choice offers versatility at varied resolutions from individual residue pairs to full-fledged contact maps. Trained on multiple complementary sources of contact predictors, rrQNet facilitates generalizability across various contact maps. By rigorously testing using publicly available datasets and comparing against several in-house baseline approaches, we show that rrQNet accurately reproduces the true quality score of a predicted contact map and successfully distinguishes between accurate and inaccurate contact maps predicted by a wide variety of contact predictors. The open-source rrQNet software package is freely available at https://github.com/Bhattacharya-Lab/rrQNet.
Pairwise and higher-order epistatic effects among somatic cancer mutations across oncogenesis
Authors: Alfaro-Murillo Jorge A. , Townsend Jeffrey P. 
Published: January 2022

AbstractCancer occurs as a consequence of multiple somatic mutations that lead to uncontrolled cell growth. Mutual exclusivity and co-occurrence of mutations imply—but do not prove—that they can exert synergistic or antagonistic epistatic effects on oncogenesis. Knowledge of these interactions, and the consequent trajectories of mutation and selection that lead to cancer has been a longstanding goal within the cancer research community. Recent research has revealed mutation rates and scaled selection coefficients for specific recurrent variants across many cancer types. However, estimation of pairwise and higher-order effects—essential to estimation of the trajectory of likely cancer genotoypes—has been a challenge. Therefore, we have developed a continuous-time Markov chain model that enables the estimation of mutation origination and fixation (flux), dependent on somatic cancer genotype. Coupling the continuous-time Markov chain model with a deconvolution approach provides estimates of underlying mutation rates and selection across the trajectory of oncogenesis. We demonstrate computation of fluxes and selection coefficients in a somatic evolutionary model for the four most frequently variant driver genes (TP53, LRP1B, KRASandSTK11) from 565 cases of lung adenocarcinoma. Our analysis reveals multiple antagonistic epistatic effects that reduce the possible routes of oncogenesis, and inform cancer research regarding viable trajectories of somatic evolution whose progression could be forestalled by precision medicine. Synergistic epistatic effects are also identified, most notably in the somatic genotypeTP53+LRP1Bfor mutations in theKRASgene, and in somatic genotypes containingKRASorTP53mutations for mutations in theSTK11gene. Large positive fluxes ofKRASvariants were driven by large selection coefficients, whereas the flux towardLRP1Bmutations was substantially aided by a large mutation rate for this gene. The approach enables inference of the most likely routes of site-specific variant evolution and estimation of the strength of selection operating on each step along the route, a key component of what we need to know to develop and implement personalized cancer therapies.
Quantitative proteomics of the CDK9 interactome reveals a novel function of the HSP90-CDC37-P-TEFb complex for BETi-induced HIV-1 latency reactivation
Authors: Wang Cong , Pan Zhenrui , He Yaohui , Zhang Zhanming , Liu Rongdiao , Xue Yuhua , Zhou Qiang , Gao Xiang 
Published: January 2022

AbstractBrd4 has been intensively investigated as a promising drug target because of its implicated functions in oncogenesis, inflammation and HIV-1 transcription. The formation of the Brd4-P-TEFb (CDK9/Cyclin T1) complex and its regulation of transcriptional elongation is critical for HIV latency reactivation and expression of many oncogenes. To further investigate the mechanism of the Brd4-P-TEFb complex in controlling elongation, mass spectrometry-based quantitative proteomics of the CDK9 interactome was performed. Upon treatment with the selective BET bromodomain inhibitor (BETi) JQ1, 535 proteins were successfully identified with high confidence as CDK9-interacting proteins. Among them, that increased bindings of HSP90 and CDC37 to CDK9 were particularly striking, and our data suggest that the HSP90-CDC37-P-TEFb complex is involved in controlling P-TEFb’s dynamic equilibrium during BETi-induced HIV-1 latency reactivation. Furthermore, the HSP90-CDC37-P-TEFb complex directly regulates HIV-1 transcription and relies on the recruitment by heat shock factor 1 (HSF1) for binding to the HIV-1 promoter. These results advance the understanding of HSP90-CDC37-P-TEFb in HIV-1 latency reversal and enlighten the development of potential strategies to eradicate HIV-1 using a combination of targeted drugs.
Combination of Spironolactone and Sitagliptin Improves Clinical Outcomes of Outpatients with COVID-19: A Prospective Cohort Study
Authors: Davarpanah Mohammad Ali , Adatorwovor Reuben , Mansoori Yasaman , Ramsheh Fatemeh Sadat Rajaie , Parsa Amir , Hajiani Mehdi , Faramarzi Hossein , Kavuluru Ramakanth , Asadipooya Kamyar 
Published: January 2022

AbstractRationaleCoronavirus disease 2019 (COVID-19) leads to hospitalization and death, especially in elderly and those with comorbidities. There are evidences showing that sitagliptin and spironolactone can potentially improve the clinical outcomes of COVID-19 cases.ObjectiveIn this observational study on acutely symptomatic outpatient COVID-19 cases, we investigated the effects of spironolactone and sitagliptin on the outcomes of the disease.MethodsThis prospective cohort study was conducted at Shiraz University of Medical Sciences Clinics during the fifth wave of the COVID-19 pandemic between July 2021 and September 2021. We followed mild to moderate symptomatic COVID-19 patients, who were treated with either combination (spironolactone 100 mg daily and sitagliptin 100 mg daily) or standard (steroid, antiviral and/or supportive care) therapy up to 30 days. Our primary outcome was hospitalization rate. The secondary outcomes included ER visit, duration of disease, and complications, such as hypoglycemia, low blood pressure or altered mental status.ResultsOf the 206 patients referred to clinics, 103 received standard therapy and 103 treated with combination therapy. There were no significant differences in baseline characteristics, except for slightly higher clinical score in control group (6.92 ± 4.01 control, 4.87 ± 2.92 combination; P <0.0001). Treatment with combination therapy was associated with lower admission rate (5.8% combination, 22.3% control; P = 0.0011), ER visits (7.8% combination, 23.3% control; P = 0.0021) and average duration of symptoms (6.67 ± 2.30 days combination, 18.71 ± 6.49 days control; P =<0.0001).ConclusionIn this prospective cohort study of acutely ill outpatients with COVID-19, the combination of sitagliptin and spironolactone reduced duration of COVID infection and hospital visits better than standard therapeutic approaches. The effects of combination of sitagliptin and spironolactone in COVID-19 patients should be further verified in a double blind, randomized, placebo-controlled trial.Iranian Registry of Clinical TrialsIRCT registration number: IRCT20201003048904N2, Registration date: December 10, 2020.
Quantifying the direct and indirect protection provided by insecticide treated bed nets against malaria
Authors: Unwin H. Juliette T. , Smith Ellie Sherrard , Churcher Thomas S. , Ghani Azra C. 
Published: January 2022

AbstractLong lasting insecticide treated mosquito nets (LLINs) provide both direct and indirect protection against bites from mosquitoes potentially transmitting malaria. Direct personal protection is provided to net users given both the net’s physical barrier and its insecticidal action. Indirect mass protection for the community is afforded through reduced infectious bites per person annually (entomological inoculation rate, EIR). Quantifying these protective effects can help strategize options for net interventions, particularly as insecticide-resistant mosquitoes spread.These types of protection are inherently linked, rendering it impossible to empirically quantify the contribution of each to the overall ‘community effect’, instead we investigate this with a modelling framework and compare model predictions to trends with Demographic Health Survey (DHS) data.Our modelling exercise predicts that in a situation with an EIR of 100, the reduction in EIR from an untreated net used by 80% of the population is 52% [95% CI: 12% - 84%] for users and 21% [95% CI: 0% - 57%] for non-users. Due to the impact of the insecticide, the reduction in EIR for LLINs is 89% [95% CI: 67% - 98%] for users and 74% [95% CI: 48% - 92%] for non-users, but this protection reduces as insecticide resistance in mosquitoes increases. Modelled trends in the difference in protection between users and non-users across endemicity and net usage levels are consistent with DHS data (2000-2018).This study supports the concept of a community effect from LLINs, highlights the value of blocking and killing mosquitoes for community protection. Achieving high LLIN usage is always preferential, but there remains protection to non-users as the number of people using nets increases.
Claspin is required for growth recovery from serum starvation through regulating the PI3K-PDK1-mTOR pathway
Authors: Yang Chi-Chun , Masai Hisao 
Published: January 2022

AbstractGrowth recovery from serum starvation requires the activation of PI3 kinase (PI3K)-PDK1-Akt-mTOR pathways. Claspin plays multiple important roles in regulation of DNA replication as a mediator for the cellular response to replication stress, an integral replication fork factor that facilitates replication fork progression and a factor that promotes initiation by recruiting Cdc7 kinase. Here, we report a novel role of Claspin in growth recovery from serum starvation. In the absence of Claspin, cells do not proceed into S phase and eventually die. Claspin interacts with PI3K and mTOR, and is required for activation of PI3K-PDK1-mTOR and for that of mTOR downstream factors, p70S6K and 4E-BP1, but not for p38 MAPK cascade during the recovery from serum starvation. PDK1 interacts with Claspin, notably with CKBD, in a manner dependent on phosphorylation of the latter protein, and is required for interaction of mTOR with Claspin. p53 and ROS (Reactive Oxygen Species) inhibitors increased survival of Claspin-deficient cells released from serum starvation. Thus, Claspin plays a novel role as a mediator/protein platform for nutrition-induced proliferation/survival signaling by activating the mTOR pathway.
Molecular and connectomic vulnerability shape cross-disorder cortical abnormalities
Authors: Hansen Justine Y. , Shafiei Golia , Vogel Jacob W. , Smart Kelly , Bearden Carrie E. , Hoogman Martine , Franke Barbara , van Rooij Daan , Buitelaar Jan , McDonald Carrie R. , Sisodiya Sanjay M. , Schmaal Lianne , Veltman Dick J. , van den Heuvel Odile A. , Stein Dan J. , van Erp Theo G. M. , Ching Christopher R. K. , Andreassen Ole A. , Hajek Tomas , Opel Nils , Modinos Gemma , Aleman André , van der Werf Ysbrand , Jahanshad Neda , Thomopoulos Sophia I. , Thompson Paul M. , Carson Richard E. , Dagher Alain , Misic Bratislav 
Published: January 2022

AbstractNumerous brain disorders demonstrate structural brain abnormalities, which are thought to arise from molecular perturbations or connectome miswiring. The unique and shared contributions of these molecular and connectomic vulnerabilities to brain disorders remain unknown, and has yet to be studied in a single multi-disorder framework. Using MRI morphometry from the ENIGMA consortium, we construct maps of cortical abnormalities for thirteen neurodevelopmental, neurological, and psychiatric disorders from N = 21 000 patients and N = 26 000 controls, collected using a harmonized processing protocol. We systematically compare cortical maps to multiple micro-architectural measures, including gene expression, neurotransmitter density, metabolism, and myelination (molecular vulnerability), as well as global connectomic measures including number of connections, centrality, and connection diversity (connectomic vulnerability). We find that regional molecular vulnerability and macroscale brain network architecture interact to drive the spatial patterning of cortical abnormalities in multiple disorders. Local attributes, particularly neurotransmitter receptor profiles, constitute the best predictors of both disorder-specific cortical morphology and cross-disorder similarity. Finally, we find that cross-disorder abnormalities are consistently subtended by a small subset of network epicentres in bilateral sensory-motor, medial temporal lobe, precuneus, and superior parietal cortex. Collectively, our results highlight how local biological attributes and global connectivity jointly shape cross-disorder cortical abnormalities.
An atlas of plant full-length RNA reveals tissue-specific and evolutionarily-conserved regulation of poly(A) tail length
Authors: Jia Jinbu , Lu Wenqin , Liu Bo , Yu Yiming , Jin Xianhao , Shu Yi , Long Yanping , Zhai Jixian 
Published: January 2022

Introductory paragraphPoly(A) tail is a hallmark of eukaryotic mRNA and its length plays an essential role in regulating mRNA metabolism1–3. However, a comprehensive resource for plant poly(A) tail length has yet to be established. Here, we applied a poly(A)-enrichment-free, Nanopore-based method4,5 to profile full-length RNA with poly(A) tail information in plants. Our atlas contains over 120 million polyadenylated mRNA molecules from seven different tissues of Arabidopsis, as well as the shoot tissue of maize, soybean and rice. In most tissues, the size of plant poly(A) tails shows peaks at approximately 20 and 45 nt, presumably the sizes protected by one and two poly(A) binding proteins (PABP), respectively2,6, while the poly(A) tails in pollen exhibit a distinct pattern with strong peaks centered at 55 and 80 nt. Moreover, poly(A) tail length is regulated in a gene-specific manner — mRNAs with short half-lives in general have long poly(A) tails, while mRNAs with long half-lives are featured with relatively short poly(A) tails that peak at ~45 nt, suggesting that protection of poly(A) tail in this size by PABP is essential for mRNA stability. Across species, poly(A) tails in the nucleus are almost twice as long as in the cytoplasm, implying a conserved rapid shortening process of poly(A) tail occurs before the mRNA is stabilized in cytoplasm. Our comprehensive dataset lays the groundwork for future functional and evolutionary studies on poly(A) tail length regulation in plants.
VCF2Prot: An Efficient and Parallel Tool for Generating Personalized Proteomes from VCF Files
Authors: ElAbd Hesham , Degenhardt Frauke , Lenz Tobias L. , Franke Andre , Wendorff Mareike 
Published: January 2022

AbstractMotivationThe ability to generate sample-specific protein sequences is a crucial step in neo-antigen discovery, cancer vaccine development, and proteogenomics. The revolutionary increase in the throughput of sequencers has fueled large-scale genomic and transcriptomic studies, holding great promises for the emerging field of personalized medicine. However, most sequencing projects store their sequencing data in an abbreviated variant calling format (VCF) that is not immediately amenable to subsequent proteomic and peptidomic analyses. Furthermore, data processing of such increasingly massive genome-scale datasets calls for parallel and concurrent programming, and consequently refactoring of existing algorithms and/or the development of new parallel algorithms.ResultsHere, we introduce sequence intermediate representation (SIR), a novel and generic algorithm for generating personalized or sample-specific protein sequences from a consequence-called VCF file and the corresponding reference proteome. An implementation of SIR, named VCF2Prot, was developed to aid personalized medicine and proteogenomics by generating personalized proteomes in FASTA format from a collection of consequence-called genomic alterations stored in a VCF file. Benchmarking VCF2Prot against the recently published PrecisionProDB showed an ~1000-fold improvement in runtime (depending on the input size). Furthermore, in a scale-up study VCF2Prot processed a VCF file containing 99,254 variants observed across 8,192 patients in ~ 11 minutes, demonstrating the massive improvement in the execution speed and the utility of SIR and VCF2prot in bridging large-scale genomic and proteomic studies.Availability and ImplementationVCF2Prot comes with a permissive MIT-license, enabling the commercial and non-commercial utilization of the tool. The source code along with precompiled versions for Linux/Mac OS are available at https://github.com/ikmb/vcf2prot. The modular units used for building VCF2Prot are available as a Rust crate at https://crates.io/crates/ppgg with documentations and examples at https://docs.rs/ppgg/0.1.4/ppgg/ under the same MIT-license.