bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tissue-engineered models of lung cancer premalignancy
Authors: Blomberg Rachel , Sompel Kayla , Hauer Caroline , Peña Brisa , Driscoll Jennifer , Hume Patrick S. , Merrick Daniel T. , Tennis Meredith A. , Magin Chelsea M. 
Published: March 2023

AbstractLung cancer is the leading global cause of cancer-related deaths. Although smoking cessation is the best preventive action, nearly 50% of all lung cancer diagnoses occur in people who have already quit smoking. Research into treatment options for these high-risk patients has been constrained to rodent models of chemical carcinogenesis, which are time-consuming, expensive, and require large numbers of animals. Here we show that embedding precision-cut lung slices within an engineered hydrogel and exposing this tissue to a carcinogen from cigarette smoke creates anin vitromodel of lung cancer premalignancy. Hydrogel formulations were selected to promote early lung cancer cellular phenotypes and extend PCLS viability up to six weeks. In this study, hydrogel-embedded lung slices were exposed to the cigarette smoke derived carcinogen vinyl carbamate, which induces adenocarcinoma in mice. At six weeks, analysis of proliferation, gene expression, histology, tissue stiffness, and cellular content revealed that vinyl carbamate induced the formation of premalignant lesions with a mixed adenoma/squamous phenotype. Two putative chemoprevention agents were able to freely diffuse through the hydrogel and induce tissue-level changes. The design parameters selected using murine tissue were validated with hydrogel-embedded human PCLS and results showed increased proliferation and premalignant lesion gene expression patterns. This tissue-engineered model of human lung cancer premalignancy is the starting point for more sophisticatedex vivomodels and a foundation for the study of carcinogenesis and chemoprevention strategies.
HBV rewires liver cancer signaling by altering PP2A complexes
Authors: Pitea Adriana , Turnham Rigney E , Eckhardt Manon , Jang Gwendolyn M , Xu Zhong , Lim Huat C , Choi Alex , Von Dollen John , Levin Rebecca S. , Webber James T , McCarthy Elizabeth , Hu Junjie , Li Xiaolei , Che Li , Chan Gary , Kelley R. Katie , Swaney Danielle , Zhang Wei , Bandyopadhyay Sourav , Theis Fabian J , Chen Xin , Shokat Kevan , Ideker Trey , Krogan Nevan J , Gordan John D 
Published: March 2023

SummaryInfection by hepatitis B virus (HBV) increases risk for liver cancer by inducing inflammation, cellular stress and cell death. To elucidate the molecular pathways by which HBV promotes cancer development and progression, we used affinity purification mass spectrometry to comprehensively map a network of 145 physical interactions between HBV and human host proteins in hepatocellular carcinoma (HCC). We find that viral proteins target host factors that are preferentially mutated in non-HBV-associated HCC, implicating cancer pathways whose interaction with HBV plays a role in HCC. Focusing on proteins that directly interact with the HBV oncoprotein X (HBx), we show that HBx remodels the PP2A phosphatase complex, altering its effect on tumor signaling. HBx excludes striatin-family regulatory subunits from PP2A, causing Hippo kinase activation and unmasking a requirement for mTOR complex 2 to maintain expression of the YAP oncoprotein in HCC. Thus, HBV rewires HCC to expose potentially targetable signaling dependencies.SignificancePrecision medicine has revolutionized cancer treatment but remains elusive for HCC. We used proteomics to define HBV/host interactions and integrated them with HCC mutations. The results implicate modifiers of HCC behavior via remodeling of host complexes and illuminate new biological mechanisms in advanced disease for therapeutic investigation.
Shaken, not shifted: Genotypic variation tunes how interspecific competition shapes niches
Authors: Costa-Pereira Raul , Fragata Inês , Mira André , de la Masselière Maud Charlery , Hortal Joaquin , Magalhães Sara 
Published: March 2023

AbstractIndividual variation in resource use as well as in the response to competitors has been recognized as playing an important role is species interactions. Still, we have as yet little information on whether such responses have a genetic basis as well as on how they affect each other. Here, we tested whether 20 genetically inbred lines of the spider miteTetranychus evansivary in their response to a gradient of cadmium concentration within plants as well as in their propensity to reshape niches when facing interspecific competition along this gradient. In absence of interspecific competitors, most lines were negatively affected by cadmium, albeit often in a non-linear fashion. Morevoer, half of the lines exhibited changes in the curvature of the relationship between number of females and cadmium concentration when facing competition with the congenericT. urticae. Inbred lines also showed a shallower decay in offspring number along the cadmium gradient in presence of interspecific competition. Our findings provide evidence for large, partly genetic, variation in resource use and in the response to interspecific competition in heterogeneous environments. Moreover, we show that genotype responses to interspecific competition is contingent upon their response to an environmental gradient. Together, our results thus emphasize the importance of considering intraspecific variation in responses to interspecific competition, providing novel insights to link intra- and interspecific levels of biodiversity.
A Novel Silver-Containing Antimicrobial potentiates aminoglycoside activity againstPseudomonas aeruginosa
Authors: Donkor Gracious Yoofi , Anderson Greg M. , Stadler Michael , Tawiah Patrick Ofori , Orellano Carl D. , Edwards Kevin A. , Dahl Jan-Ulrik 
Published: March 2023

ABSTRACTThe rapid dissemination of antibiotic resistance combined with the decline in the discovery of novel antibiotics represents a major challenge for infectious disease control that can only be mitigated by investments into novel treatment strategies. Alternative antimicrobials, including silver, have regained interest due to their diverse mechanisms of inhibiting microbial growth. One such example is AGXX®, a broad-spectrum silver containing antimicrobial that produces highly cytotoxic reactive oxygen species (ROS) to inflict extensive macromolecular damage. Due to connections identified between ROS production and antibiotic lethality, we hypothesized that AGXX® could potentially increase the activity of conventional antibiotics. Using the gram-negative pathogenPseudomonas aeruginosa, we screened possible synergistic effects of AGXX® on several antibiotic classes. We found that the combination of AGXX® and aminoglycosides tested at sublethal concentrations led to a rapid exponential decrease in bacterial survival and restored sensitivity of a kanamycin-resistant strain. ROS production contributes significantly to the bactericidal effects of AGXX®/aminoglycoside treatments, which is dependent on oxygen availability and can be reduced by the addition of ROS scavengers. Additionally,P. aeruginosastrains deficient in ROS detoxifying/repair genes were more susceptible to AGXX®/aminoglycoside treatment. We further demonstrate that this synergistic interaction was associated with significant increase in outer and inner membrane permeability, resulting in increased antibiotic influx. Our study also revealed that AGXX®/aminoglycoside-mediated killing requires an active proton motive force across the bacterial membrane. Overall, our findings provide an understanding of cellular targets that could be inhibited to increase the activity of conventional antimicrobials.IMPORTANCEThe emergence of drug-resistant bacteria coupled with the decline in antibiotic development highlights the need for novel alternatives. Thus, new strategies aimed at repurposing conventional antibiotics have gained significant interest. The necessity of these interventions is evident especially in gram-negative pathogens as they are particularly difficult to treat due to their outer membrane. This study highlights the effectiveness of the silver containing antimicrobial AGXX® in potentiating aminoglycoside activities againstP. aeruginosa. The combination of AGXX® and aminoglycosides not only reduces bacterial survival rapidly but also significantly re-sensitizes aminoglycoside-resistantP. aeruginosastrains. In combination with gentamicin, AGXX® induces increased endogenous oxidative stress, membrane damage and iron sulfur cluster disruption. These findings emphasize AGXX®’s potential as a route of antibiotic adjuvant development and shed light into potential targets to enhance aminoglycoside activity.
NanoSquiggleVar: A method for direct analysis of targeted variants based on nanopore sequencing signals
Authors: Lang Jidong 
Published: March 2023

AbstractBackgroundNanopore sequencing is a fourth-generation sequencing technology that has developed rapidly in recent years. It has long sequencing read lengths and does not require the polymerase chain reaction to be performed. These characteristics give it unique advantages over the next-generation sequencing technology under certain usage scenarios. The number of bioinformatics analysis algorithms and/or tools developed with nanopore sequencing has increased sharply during the past years, undoubtedly providing great help and support for the application of nanopore sequencing in scientific research and practical scenarios.ResultsWe developed NanoSquiggleVar, a method for direct analysis of targeted variants based on nanopore sequencing signals. It first establishes a set of wild-type and mutant-type target signals within the same experimental and sequencing system, named wild squiggle set and variant squiggle set, respectively. In each sequencing iteration, the signal is sliced into fragments by a moving window of 1-unit step size. Then, dynamic time warping is used to compare the signal squiggles to the detected variants. Point mutations, insertions and deletions (indels), and homopolymer sequences were simulated and generated by Scrappie and then analyzed and evaluated with NanoSquiggleVar. We found that all of these variants were efficiently detected and discriminated, and the results were consistent with the expectations.ConclusionsNanoSquiggleVar can directly identify targeted variants from the nanopore sequencing electrical signal without the requirement of base calling, sequence alignment, or variant detection with downstream analysis. We hope that this method can complement targeted variant detection using nanopore sequencing and potentially serve as a reference for real-time sequencing and analysis.
Design and Mathematical Analysis of Activating Amplifiers that Enable Modular Temporal Control in Synthetic Circuits
Authors: Lam Calvin 
Published: March 2023

ABSTRACTThe ability to control mammalian cells such that they self-organize or enact therapeutic effects as desired has incredible implications. Not only would it further our understanding of native processes such as development and the immune response, but it would also have powerful applications in medical fields such as regenerative medicine and immunotherapy. This control is typically obtained by synthetic circuits that use synthetic receptors, but control remains incomplete. For example, the synthetic juxtacrine receptors (SJRs) are widely used as they are fully modular and enable spatial control, but they have limited gene expression amplification and temporal control. I therefore designed transcription factor based amplifiers that amplify gene expression and enable unidirectional temporal control by prolonging duration of target gene expression. Using anin silicoframework for SJR signaling, I combined these amplifiers with SJRs and show that these SJR amplifier circuits can improve the quality of self-organization and direct different spatiotemporal patterning. I then show that these circuits can improve chimeric antigen receptor (CAR) T cell tumor killing against heterogenous and homogenous antigen expression tumors. These amplifiers are flexible tools that improve control over SJR based circuits and have both basic and therapeutic applications.Graphical Abstract
Improving inversion of model parameters from action potential recordings with kernel methods
Authors: Oslandsbotn Andreas , Cloninger Alexander , Forsch Nickolas 
Published: March 2023

AbstractCurrent methods for solving inverse problems in cardiac electrophysiology are limited by their accuracy, scalability, practicality, or a combination of these. In this proof-of-concept study we demonstrate the feasibility of using kernel methods to solve the inverse problem of estimating the parameters of ionic membrane currents from observations of corresponding action potential (AP) traces. In particular, we consider AP traces generated by a cardiac cell action potential model, which mimics those obtained experimentally in measurablein vitrocardiac systems. Using synthetic training data from the 1977 Beeler-Reuter AP model of mammalian ventricular cardiomyocytes, we demonstrate our recently proposed boosted kernel ridge regression (KRR) solver StreaMRAK, which is particularly robust and well-adapted for high-complexity functions. We show that this method is less memory demanding, estimates the model parameters with higher accuracy, and is less exposed to parameter sensitivity issues than existing methods, such as standard KRR solvers and loss-minimization schemes based on nearest-neighbor heuristics.
Multiple sequence-alignment-based RNA language model and its application to structural inference
Authors: Zhang Yikun , Lang Mei , Jiang Jiuhong , Gao Zhiqiang , Xu Fan , Litfin Thomas , Chen Ke , Singh Jaswinder , Huang Xiansong , Song Guoli , Tian Yonghong , Zhan Jian , Chen Jie , Zhou Yaoqi 
Published: March 2023

AbstractCompared to proteins, DNA and RNA are more difficult languages to interpret because 4-letter-coded DNA/RNA sequences have less information content than 20-letter-coded protein sequences. While BERT (Bidirectional Encoder Representations from Transformers)-like language models have been developed for RNA, they are ineffective at capturing the evolutionary information from homologous sequences because unlike proteins, RNA sequences are less conserved. Here, we have developed an unsupervised Multiple sequence-alignment-based RNA language model (RNA-MSM) by utilizing homologous sequences from an automatic pipeline, RNAcmap. The resulting unsupervised, two-dimensional attention maps and one-dimensional embeddings from RNA-MSM can be directly mapped with high accuracy to 2D base pairing probabilities and 1D solvent accessibilities, respectively. Further fine-tuning led to significantly improved performance on these two downstream tasks over existing state-of-the-art techniques. We anticipate that the pre-trained RNA-MSM model can be fine-tuned on many other tasks related to RNA structure and function.
Discovery of a Novel 3site State as the Multi-Substrate Bound State of P450cam
Authors: Sahil Mohammad , Singh Tejender , Ghosh Soumya , Mondal Jagannath 
Published: March 2023

AbstractArchetypal metalloenzyme Cytochrome P450cam (CYP101A1) catalyzes regioselective hydroxylation of its native substrate camphor in heme active site. However, the proposal of potential existence of additional substrate binding modes distal from the active site in P450cam and their concomitant roles in regulating recognition at active site have remained a matter of recurring discourse. Herein we report the discovery of a novel3sitestate in P450cam, where three substrate molecules were observed to simultaneously bind to P450cam at three distinct sites including the heme active site. These three binding modes, hereby referred ascatalytic,waitingandallostericbinding modes in3sitestate, are allosterically inter-linked and function in mutually synergistic fashion. The3sitestate possesses regio-selective conformations of substrate essential for catalysis and establishes substrate-ingress and product exit process to and from the active site via two distinct channels. The ensemble of three-state binding modes are found to be self-consistent with NMR pseudo-contact shift data obtained from TROSY-HSQC measurements and DEER based predictions. Binding of redox partner Putidaredoxin with3sitemodel retains closed conformation of 3site state, siding with NMR based hypothesis that the catalysis would take place in closed insulation of P450cam even in presence of its redox partner.Statement of SignificanceUbiquitous superfamily of mono-oxygenases cytochrome P450s are involved in broad range of metabolic process in all domains of life and are also important drug targets. Apart from the well known and established binding mode in heme active site, the substrate bindings at additional distal sites have been postulated in multitude of P450s. Using the archetypal bacterial cytochrome P450 i.e., P450cam, a novel3sitestate of cytochrome P450 is elucidated in this work. The novel 3site state has two additional binding modes namelywaitingandallosteric(also postulated previously), apart from known binding modecatalyticin the active site. The known functions of P450cam are found to be most optimally explained by this 3site state, instead of single substrate bound catalytic state. This state can be of critical importance for CYP superfamily at large and potentially be useful in understanding the non-Michaelis behaviour, observed in many P450s.
Uncovering the Hidden Gems of Psoriasis Literature: An Neural Language Model-Assisted Interactive Web Tool
Authors: Wu Sunsi , Gu Xinpei , Xiao Ruiheng , Gao Hongzhi , Yang Bo , Kang Yanlan 
Published: March 2023

AbstractBACKGROUNDThe comprehensive data on psoriasis research are numerous and complex, making it difficult to retrieve and classify manually. The ability to quickly mine literature based on various fine topics using deep learning natural language processing technology to assess research topics and trends in the field of psoriasis disease will have a significant impact on doctors’ research and patients’ health educationMETHODA neural topic model is used to identify fine topics of psoriasis literature published in the PubMed database from 2000 to 2021. Dermatologists evaluate the algorithm-modeled topics, summarize the categories into the most effective topics, and perform linear trend model analysis. The accurate classified topics are presented on an interactive web page to identify research hotspots and trends.RESULTSAt the categorical level, after review by clinicians, 158 out of 160 generated topics were found effective and categorized into 8 groups: Therapeutic methods (34.34%), pathological mechanisms (23.46%), comorbidity (20.04%), Clinical manifestations and differential diagnosis (12.77%), experimental modalities and methods (3.22%), diagnostic tools (2.99%), epidemiology (1.75%), and meetings/guidelines (1.43%). A linear regression model had good accuracy (MSE=0.252602, SSE=42.1845) and strong correlation (R-Squared=0.898009). ANOVA results showed that categories significantly impacted the model (p<=0.05), with experimental modalities and methods having the strongest relationship with year, and clinical manifestations and differential diagnosis having the weakest. An interactive web tool (https://psknlr.github.io) facilitates quick retrieval of titles, journals, and abstracts in different categories, as well as browsing literature information under specific topics and accessing corresponding article pages for professional knowledge on psoriasis.CONCLUSIONSThe neural topic model and interactive web tool can effectively identify the research hotspots and trends in psoriasis literature, assisting clinicians and patients in retrieving and comparing pertinent topics and research accomplishments of various years.
Adaptive-learning physics-aware light-field microscopy enables day-long and millisecond-scale super-resolution imaging of 3D subcellular dynamics
Authors: Zhu Lanxin , Sun Jiahao , Yi Chengqiang , Zhang Meng , Huang Yihang , Wu Sicen , He Mian , Chen Liting , Zhang Yicheng , Zheng Chunhong , Chen Hao , Zhang Yuhui , Li Dongyu , Fei Peng 
Published: March 2023

AbstractLong-term and high-spatiotemporal-resolution 3D imaging of living cells remains an unmet challenge for super-resolution microscopy, owing to the noticeable phototoxicity and limited scanning speed. While emerging light-field microscopy can mitigate this issue through three-dimensionally capturing biological dynamics with merely single snapshot, it suffers from suboptimal resolution insufficient for resolving subcellular structures. Here we propose an Adaptive Learning PHysics-Aware Light-Field Microscopy (Alpha-LFM) with a physics-aware deep learning framework and adaptive-tuning strategies capable for highly-generalizable light-field reconstruction of diverse subcellular dynamics. Alpha-LFM delivers sub-diffraction-limit spatial resolution (∼120 nm) while maintaining high temporal resolution and low phototoxicity. It enables rapid (at hundreds of volumes per second), long-term (up to 60 hours) 3D super-resolution imaging of diverse intracellular dynamics with exceptional details. Using Alpha-LFM approach, we finely resolve the lysosome-mitochondrial interactions, capture rapid motion of peroxisome and the endoplasmic reticulum, and reveal the variations in mitochondrial fission activity throughout two complete cell cycles.
Serial SARS-CoV-2 antibody titers in vaccinated dialysis patients: prevalence of unrecognized infection and duration of seroresponse
Authors: Hsu Caroline M. , Weiner Daniel E. , Manley Harold J. , Miskulin Dana , Ladik Vladimir , Frament Jill , Argyropoulos Christos , Abreo Kenneth , Chin Andrew , Gladish Reginald , Salman Loay , Johnson Doug , Lacson Eduardo K. 
Published: March 2023

AbstractRationale & ObjectiveSARS-CoV-2 infections are likely underdiagnosed, but the degree of underdiagnosis among maintenance dialysis patients is unknown. Durability of the immune response after third vaccine doses in this population also remains uncertain. This study tracked antibody levels to 1) assess the rate of undiagnosed infections and 2) characterize seroresponse durability after third doses.Study DesignRetrospective observational studySetting & ParticipantsSARS-CoV-2 vaccinated patients receiving maintenance dialysis through a national dialysis provider. Immunoglobulin G spike antibodies (anti-spike IgG) titers were assessed monthly following vaccination.Exposure(s)Two and three doses of SARS-CoV-2 vaccineOutcome(s)Undiagnosed and diagnosed SARS-CoV-2 infections; anti-spike IgG titers over timeAnalytical Approach“Undiagnosed” SARS-CoV-2 infections were identified as an increase in anti-spike IgG titer of ≥ 100 BAU/mL, not associated with receipt of vaccine or “diagnosed” SARS-CoV-2 infection (by PCR or antigen test). In descriptive analyses, anti-spike IgG titers were followed over time.ResultsAmong 2660 patients without prior COVID-19 who received an initial two-dose vaccine series, 371 (76%) SARS-CoV-2 infections were diagnosed and 115 (24%) were undiagnosed. Among 1717 patients without prior COVID-19 who received a third vaccine dose, 155 (80%) SARS-CoV-2 infections were diagnosed and 39 (20%) were undiagnosed. In both cohorts, anti-spike IgG levels declined over time. Of the initial two-dose cohort, 66% had a titer ≥ 500 BAU/mL in the first month, with 23% maintaining a titer ≥ 500 BAU/mL at six months. Of the third dose cohort, 95% had a titer ≥ 500 BAU/mL in the first month after the third dose, with 76% maintaining a titer ≥ 500 BAU/mL at six months.LimitationsAssays used had upper limits.ConclusionsAmong maintenance dialysis patients, 20-24% of SARS-CoV-2 infections were undiagnosed. Given this population’s vulnerability to COVID-19, ongoing infection control measures are needed. A three-dose primary mRNA vaccine series optimizes seroresponse rate and durability.