bluuebunny/crossref_metadata_2025_split huggingface dataset:
Advances in AI and machine learning for predictive medicine
Authors: Sharma Alok , Lysenko Artem , Jia Shangru , Boroevich Keith A. , Tsunoda Tatsuhiko 
Published: February 2024

AbstractThe field of omics, driven by advances in high-throughput sequencing, faces a data explosion. This abundance of data offers unprecedented opportunities for predictive modeling in precision medicine, but also presents formidable challenges in data analysis and interpretation. Traditional machine learning (ML) techniques have been partly successful in generating predictive models for omics analysis but exhibit limitations in handling potential relationships within the data for more accurate prediction. This review explores a revolutionary shift in predictive modeling through the application of deep learning (DL), specifically convolutional neural networks (CNNs). Using transformation methods such as DeepInsight, omics data with independent variables in tabular (table-like, including vector) form can be turned into image-like representations, enabling CNNs to capture latent features effectively. This approach not only enhances predictive power but also leverages transfer learning, reducing computational time, and improving performance. However, integrating CNNs in predictive omics data analysis is not without challenges, including issues related to model interpretability, data heterogeneity, and data size. Addressing these challenges requires a multidisciplinary approach, involving collaborations between ML experts, bioinformatics researchers, biologists, and medical doctors. This review illuminates these complexities and charts a course for future research to unlock the full predictive potential of CNNs in omics data analysis and related fields.
BZW2 promotes malignant progression in lung adenocarcinoma through enhancing the ubiquitination and degradation of GSK3β
Authors: Jin Kai , Li Yongmeng , Wei Ruyuan , Liu Yanfei , Wang Shuai , Tian Hui 
Published: February 2024

AbstractThe role of Basic leucine zipper and W2 domains 2 (BZW2) in the advancement of different types of tumors is noteworthy, but its involvement and molecular mechanisms in lung adenocarcinoma (LUAD) remain uncertain. Through this investigation, it was found that the upregulation of BZW2 was observed in LUAD tissues, which was associated with an unfavorable prognosis for individuals diagnosed with LUAD, as indicated by data from Gene Expression Omnibus and The Cancer Genome Atlas databases. Based on the clinicopathologic characteristics of LUAD patients from the tissue microarray, both univariate and multivariate analyses indicated that BZW2 functioned as an independent prognostic factor for LUAD. In terms of mechanism, BZW2 interacted with glycogen synthase kinase-3 beta (GSK3β) and enhanced the ubiquitination-mediated degradation of GSK3β through slowing down of the dissociation of the ubiquitin ligase complex, which consists of GSK3β and TNF receptor-associated factor 6. Moreover, BZW2 stimulated Wnt/β-catenin signaling pathway through GSK3β, thereby facilitating the advancement of LUAD. In conclusion, BZW2 was a significant promoter of LUAD. The research we conducted identified a promising diagnostic and therapeutic target for LUAD.
High-throughput barcoding of nanoparticles identifies cationic, degradable lipid-like materials for mRNA delivery to the lungs in female preclinical models
Authors: Xue Lulu , Hamilton Alex G. , Zhao Gan , Xiao Zebin , El-Mayta Rakan , Han Xuexiang , Gong Ningqiang , Xiong Xinhong , Xu Junchao , Figueroa-Espada Christian G. , Shepherd Sarah J. , Mukalel Alvin J. , Alameh Mohamad-Gabriel , Cui Jiaxi , Wang Karin , Vaughan Andrew E. , Weissman Drew , Mitchell Michael J. 
Published: February 2024

AbstractLipid nanoparticles for delivering mRNA therapeutics hold immense promise for the treatment of a wide range of lung-associated diseases. However, the lack of effective methodologies capable of identifying the pulmonary delivery profile of chemically distinct lipid libraries poses a significant obstacle to the advancement of mRNA therapeutics. Here we report the implementation of a barcoded high-throughput screening system as a means to identify the lung-targeting efficacy of cationic, degradable lipid-like materials. We combinatorially synthesize 180 cationic, degradable lipids which are initially screened in vitro. We then use barcoding technology to quantify how the selected 96 distinct lipid nanoparticles deliver DNA barcodes in vivo. The top-performing nanoparticle formulation delivering Cas9-based genetic editors exhibits therapeutic potential for antiangiogenic cancer therapy within a lung tumor model in female mice. These data demonstrate that employing high-throughput barcoding technology as a screening tool for identifying nanoparticles with lung tropism holds potential for the development of next-generation extrahepatic delivery platforms.
The transcription factor ChREBP Orchestrates liver carcinogenesis by coordinating the PI3K/AKT signaling and cancer metabolism
Authors: Benichou Emmanuel , Seffou Bolaji , Topçu Selin , Renoult Ophélie , Lenoir Véronique , Planchais Julien , Bonner Caroline , Postic Catherine , Prip-Buus Carina , Pecqueur Claire , Guilmeau Sandra , Alves-Guerra Marie-Clotilde , Dentin Renaud 
Published: February 2024

AbstractCancer cells integrate multiple biosynthetic demands to drive unrestricted proliferation. How these cellular processes crosstalk to fuel cancer cell growth is still not fully understood. Here, we uncover the mechanisms by which the transcription factor Carbohydrate responsive element binding protein (ChREBP) functions as an oncogene during hepatocellular carcinoma (HCC) development. Mechanistically, ChREBP triggers the expression of the PI3K regulatory subunit p85α, to sustain the activity of the pro-oncogenic PI3K/AKT signaling pathway in HCC. In parallel, increased ChREBP activity reroutes glucose and glutamine metabolic fluxes into fatty acid and nucleic acid synthesis to support PI3K/AKT-mediated HCC growth. Thus, HCC cells have a ChREBP-driven circuitry that ensures balanced coordination between PI3K/AKT signaling and appropriate cell anabolism to support HCC development. Finally, pharmacological inhibition of ChREBP by SBI-993 significantly suppresses in vivo HCC tumor growth. Overall, we show that targeting ChREBP with specific inhibitors provides an attractive therapeutic window for HCC treatment.
Learning stochastic dynamics and predicting emergent behavior using transformers
Authors: Casert Corneel , Tamblyn Isaac , Whitelam Stephen 
Published: February 2024

AbstractWe show that a neural network originally designed for language processing can learn the dynamical rules of a stochastic system by observation of a single dynamical trajectory of the system, and can accurately predict its emergent behavior under conditions not observed during training. We consider a lattice model of active matter undergoing continuous-time Monte Carlo dynamics, simulated at a density at which its steady state comprises small, dispersed clusters. We train a neural network called a transformer on a single trajectory of the model. The transformer, which we show has the capacity to represent dynamical rules that are numerous and nonlocal, learns that the dynamics of this model consists of a small number of processes. Forward-propagated trajectories of the trained transformer, at densities not encountered during training, exhibit motility-induced phase separation and so predict the existence of a nonequilibrium phase transition. Transformers have the flexibility to learn dynamical rules from observation without explicit enumeration of rates or coarse-graining of configuration space, and so the procedure used here can be applied to a wide range of physical systems, including those with large and complex dynamical generators.
Inequalities in healthcare use during the COVID-19 pandemic
Authors: Frey Arun , Tilstra Andrea M. , Verhagen Mark D. 
Published: February 2024

AbstractThe COVID-19 pandemic led to reductions in non-COVID related healthcare use, but little is known whether this burden is shared equally. This study investigates whether reductions in administered care disproportionately affected certain sociodemographic strata, in particular marginalised groups. Using detailed medical claims data from the Dutch universal health care system and rich full population registry data, we predict expected healthcare use based on pre-pandemic trends (2017 – Feb 2020) and compare these expectations with observed healthcare use in 2020 and 2021. Our findings reveal a 10% decline in the number of weekly treated patients in 2020 and a 3% decline in 2021 relative to prior years. These declines are unequally distributed and are more pronounced for individuals below the poverty line, females, older people, and individuals with a migrant background, particularly during the initial wave of COVID-19 hospitalisations and for middle and low urgency procedures. While reductions in non-COVID related healthcare decreased following the initial shock of the pandemic, inequalities persist throughout 2020 and 2021. Our results demonstrate that the pandemic has not only had an unequal toll in terms of the direct health burden of the pandemic, but has also had a differential impact on the use of non-COVID healthcare.
A druggable conformational switch in the c-MYC transactivation domain
Authors: Lama Dilraj , Vosselman Thibault , Sahin Cagla , Liaño-Pons Judit , Cerrato Carmine P. , Nilsson Lennart , Teilum Kaare , Lane David P. , Landreh Michael , Arsenian Henriksson Marie 
Published: February 2024

AbstractThe c-MYC oncogene is activated in over 70% of all human cancers. The intrinsic disorder of the c-MYC transcription factor facilitates molecular interactions that regulate numerous biological pathways, but severely limits efforts to target its function for cancer therapy. Here, we use a reductionist strategy to characterize the dynamic and structural heterogeneity of the c-MYC protein. Using probe-based Molecular Dynamics (MD) simulations and machine learning, we identify a conformational switch in the c-MYC amino-terminal transactivation domain (termed coreMYC) that cycles between a closed, inactive, and an open, active conformation. Using the polyphenol epigallocatechin gallate (EGCG) to modulate the conformational landscape of coreMYC, we show through biophysical and cellular assays that the induction of a closed conformation impedes its interactions with the transformation/transcription domain-associated protein (TRRAP) and the TATA-box binding protein (TBP) which are essential for the transcriptional and oncogenic activities of c-MYC. Together, these findings provide insights into structure-activity relationships of c-MYC, which open avenues towards the development of shape-shifting compounds to target c-MYC as well as other disordered transcription factors for cancer treatment.
Attenuation of phytofungal pathogenicity of Ascomycota by autophagy modulators
Authors: Woo Jongchan , Jung Seungmee , Kim Seongbeom , Li Yurong , Chung Hyunjung , Roubtsova Tatiana V. , Zhang Honghong , Caseys Celine , Kliebenstein Dan , Kim Kyung-Nam , Bostock Richard M. , Lee Yong-Hwan , Dickman Martin B. , Choi Doil , Park Eunsook , Dinesh-Kumar Savithramma P. 
Published: February 2024

AbstractAutophagy in eukaryotes functions to maintain homeostasis by degradation and recycling of long-lived and unwanted cellular materials. Autophagy plays important roles in pathogenicity of various fungal pathogens, suggesting that autophagy is a novel target for development of antifungal compounds. Here, we describe bioluminescence resonance energy transfer (BRET)-based high-throughput screening (HTS) strategy to identify compounds that inhibit fungal ATG4 cysteine protease-mediated cleavage of ATG8 that is critical for autophagosome formation. We identified ebselen (EB) and its analogs ebselen oxide (EO) and 2-(4-methylphenyl)−1,2-benzisothiazol-3(2H)-one (PT) as inhibitors of fungal pathogens Botrytis cinerea and Magnaporthe oryzae ATG4-mediated ATG8 processing. The EB and its analogs inhibit spore germination, hyphal development, and appressorium formation in Ascomycota pathogens, B. cinerea, M. oryzae, Sclerotinia sclerotiorum and Monilinia fructicola. Treatment with EB and its analogs significantly reduced fungal pathogenicity. Our findings provide molecular insights to develop the next generation of antifungal compounds by targeting autophagy in important fungal pathogens.
Dioxygen compatible electron donor-acceptor catalytic system and its enabled aerobic oxygenation
Authors: Wei Jialiang , Meng Junhong , Zhang Caifang , Liu Yameng , Jiao Ning 
Published: February 2024

AbstractThe photochemical properties of Electron Donor-Acceptor (EDA) complexes present exciting opportunities for synthetic chemistry. However, these strategies often require an inert atmosphere to maintain high efficiency. Herein, we develop an EDA complex photocatalytic system through rational design, which overcomes the oxygen-sensitive limitation of traditional EDA photocatalytic systems and enables aerobic oxygenation reactions through dioxygen activation. The mild oxidation system transfers electrons from the donor to the effective catalytic acceptor upon visible light irradiation, which are subsequently captured by molecular oxygen to form the superoxide radical ion, as demonstrated by the specific fluorescent probe, dihydroethidine (DHE). Furthermore, this visible-light mediated oxidative EDA protocol is successfully applied in the aerobic oxygenation of boronic acids. We believe that this photochemical dioxygen activation strategy enabled by EDA complex not only provides a practical approach to aerobic oxygenation but also promotes the design and application of EDA photocatalysis under ambient conditions.
Exploring the variances of climate change opinions in Germany at a fine-grained local scale
Authors: Mewes Lars , Tuitjer Leonie , Dirksmeier Peter 
Published: February 2024

AbstractHow and why climate change opinions vary within countries at a small geographic scale is rarely investigated. Previous research has focused on public opinions at the individual or national level, leaving local differences within countries and their underlying factors largely unexplored. The lack of research at subnational levels is problematic, as adaptation and mitigation policies depend on collective support and action involving multiple stakeholders at the local scale. It is thus crucial to identify geographic differences in climate change opinions and to unravel their determinants at a fine-grained local scale. We examine public CCOs across 4,667 municipalities in Germany by relying on a representative survey of households. Here we show substantial and systematic differences in public climate change opinions across locations that manifest between urban vs. rural and prospering vs. declining areas. Besides these geographic features, more complex historical and cultural differences between places play an important role.
The evolutionary impact of childhood cancer on the human gene pool
Authors: Stoltze Ulrik Kristoffer , Foss-Skiftesvik Jon , Hansen Thomas van Overeem , Rasmussen Simon , Karczewski Konrad J. , Wadt Karin A. W. , Schmiegelow Kjeld 
Published: February 2024

AbstractGermline pathogenic variants associated with increased childhood mortality must be subject to natural selection. Here, we analyze publicly available germline genetic metadata from 4,574 children with cancer [11 studies; 1,083 whole exome sequences (WES), 1,950 whole genome sequences (WGS), and 1,541 gene panel] and 141,456 adults [125,748 WES and 15,708 WGS]. We find that pediatric cancer predisposition syndrome (pCPS) genes [n = 85] are highly constrained, harboring only a quarter of the loss-of-function variants that would be expected. This strong indication of selective pressure on pCPS genes is found across multiple lines of germline genomics data from both pediatric and adult cohorts. For six genes [ELP1, GPR161, VHL and SDHA/B/C], a clear lack of mutational constraint calls the pediatric penetrance and/or severity of associated cancers into question. Conversely, out of 23 known pCPS genes associated with biallelic risk, two [9%, DIS3L2 and MSH2] show significant constraint, indicating that they may monoallelically increase childhood cancer risk. In summary, we show that population genetic data provide empirical evidence that heritable childhood cancer leads to natural selection powerful enough to have significantly impacted the present-day gene pool.
Simultaneous enhancement of strength and conductivity via self-assembled lamellar architecture
Authors: Han Tielong , Hou Chao , Zhao Zhi , Jiao Zengbao , Li Yurong , Jiang Shuang , Lu Hao , Wang Haibin , Liu Xuemei , Nie Zuoren , Song Xiaoyan 
Published: February 2024

AbstractSimultaneous improvement of strength and conductivity is urgently demanded but challenging for bimetallic materials. Here we show by creating a self-assembled lamellar (SAL) architecture in W-Cu system, enhancement in strength and electrical conductivity is able to be achieved at the same time. The SAL architecture features alternately stacked Cu layers and W lamellae containing high-density dislocations. This unique layout not only enables predominant stress partitioning in the W phase, but also promotes hetero-deformation induced strengthening. In addition, the SAL architecture possesses strong crack-buffering effect and damage tolerance. Meanwhile, it provides continuous conducting channels for electrons and reduces interface scattering. As a result, a yield strength that doubles the value of the counterpart, an increased electrical conductivity, and a large plasticity were achieved simultaneously in the SAL W-Cu composite. This study proposes a flexible strategy of architecture design and an effective method for manufacturing bimetallic composites with excellent integrated properties.
Exploring the gut DNA virome in fecal immunochemical test stool samples reveals associations with lifestyle in a large population-based study
Authors: Istvan Paula , Birkeland Einar , Avershina Ekaterina , Kværner Ane S. , Bemanian Vahid , Pardini Barbara , Tarallo Sonia , de Vos Willem M. , Rognes Torbjørn , Berstad Paula , Rounge Trine B. 
Published: February 2024

AbstractStool samples for fecal immunochemical tests (FIT) are collected in large numbers worldwide as part of colorectal cancer screening programs. Employing FIT samples from 1034 CRCbiome participants, recruited from a Norwegian colorectal cancer screening study, we identify, annotate and characterize more than 18000 DNA viruses, using shotgun metagenome sequencing. Only six percent of them are assigned to a known taxonomic family, with Microviridae being the most prevalent viral family. Linking individual profiles to comprehensive lifestyle and demographic data shows 17/25 of the variables to be associated with the gut virome. Physical activity, smoking, and dietary fiber consumption exhibit strong and consistent associations with both diversity and relative abundance of individual viruses, as well as with enrichment for auxiliary metabolic genes. We demonstrate the suitability of FIT samples for virome analysis, opening an opportunity for large-scale studies of this enigmatic part of the gut microbiome. The diverse viral populations and their connections to the individual lifestyle uncovered herein paves the way for further exploration of the role of the gut virome in health and disease.
Drug target prediction through deep learning functional representation of gene signatures
Authors: Chen Hao , King Frederick J. , Zhou Bin , Wang Yu , Canedy Carter J. , Hayashi Joel , Zhong Yang , Chang Max W. , Pache Lars , Wong Julian L. , Jia Yong , Joslin John , Jiang Tao , Benner Christopher , Chanda Sumit K. , Zhou Yingyao 
Published: February 2024

AbstractMany machine learning applications in bioinformatics currently rely on matching gene identities when analyzing input gene signatures and fail to take advantage of preexisting knowledge about gene functions. To further enable comparative analysis of OMICS datasets, including target deconvolution and mechanism of action studies, we develop an approach that represents gene signatures projected onto their biological functions, instead of their identities, similar to how the word2vec technique works in natural language processing. We develop the Functional Representation of Gene Signatures (FRoGS) approach by training a deep learning model and demonstrate that its application to the Broad Institute’s L1000 datasets results in more effective compound-target predictions than models based on gene identities alone. By integrating additional pharmacological activity data sources, FRoGS significantly increases the number of high-quality compound-target predictions relative to existing approaches, many of which are supported by in silico and/or experimental evidence. These results underscore the general utility of FRoGS in machine learning-based bioinformatics applications. Prediction networks pre-equipped with the knowledge of gene functions may help uncover new relationships among gene signatures acquired by large-scale OMICs studies on compounds, cell types, disease models, and patient cohorts.
Viral potential to modulate microbial methane metabolism varies by habitat
Authors: Zhong Zhi-Ping , Du Jingjie , Köstlbacher Stephan , Pjevac Petra , Orlić Sandi , Sullivan Matthew B. 
Published: February 2024

AbstractMethane is a potent greenhouse gas contributing to global warming. Microorganisms largely drive the biogeochemical cycling of methane, yet little is known about viral contributions to methane metabolism (MM). We analyzed 982 publicly available metagenomes from host-associated and environmental habitats containing microbial MM genes, expanding the known MM auxiliary metabolic genes (AMGs) from three to 24, including seven genes exclusive to MM pathways. These AMGs are recovered on 911 viral contigs predicted to infect 14 prokaryotic phyla including Halobacteriota, Methanobacteriota, and Thermoproteota. Of those 24, most were encoded by viruses from rumen (16/24), with substantially fewer by viruses from environmental habitats (0–7/24). To search for additional MM AMGs from an environmental habitat, we generate metagenomes from methane-rich sediments in Vrana Lake, Croatia. Therein, we find diverse viral communities, with most viruses predicted to infect methanogens and methanotrophs and some encoding 13 AMGs that can modulate host metabolisms. However, none of these AMGs directly participate in MM pathways. Together these findings suggest that the extent to which viruses use AMGs to modulate host metabolic processes (e.g., MM) varies depending on the ecological properties of the habitat in which they dwell and is not always predictable by habitat biogeochemical properties.