bluuebunny/crossref_metadata_2025_split huggingface dataset:
Budget impact analysis for implementation decision making, planning, and financing
Authors: Smith Natalie Riva , Levy Douglas E 
Published: September 2023

Abstract
Shelley et al. (in Accelerating integration of tobacco use treatment in the context of lung cancer screening: relevance and application of implementation science to achieving policy and practice. Transl Behav Med 2022;12:1076–1083) laid out how implementation science frameworks and methods can advance the delivery of tobacco use treatment services during lung cancer screening services, which until recently was mandated by the Centers for Medicare and Medicaid Services. Their discussion provides an important overview of the full process of implementation and highlights the vast number of decisions that must be made when planning for implementation of an evidence-based practice such as tobacco use treatment: what specific tobacco use treatment services to deliver, when to deliver those services within the lung cancer screening process, and what implementation strategies to use. The costs of implementation play a major role in decision making and are a key implementation determinant discussed in major implementation frameworks. When making decisions about what and how to implement, budget impact analyses (BIAs) can play an important role in informing decision making by helping practitioners understand the overall affordability of a given implementation effort. BIAs can also inform the development of financing strategies to support the ongoing sustainment of tobacco use treatment service provision. More attention is needed by the research community to produce high-quality, user-friendly, and flexible BIAs to inform implementation decision making in health system and community settings. The application of BIA can help ensure that the considerable time and effort spent to develop and evaluate evidence-based programs has the best chance to inform implementation practice.
Aminoacyl‐tRNA synthetase – a molecular multitasker
Authors: Gupta Swadha , Jani Jaykumar , Vijayasurya  , Mochi Jigneshkumar , Tabasum Saba , Sabarwal Akash , Pappachan Anju 
Published: September 2023

AbstractAminoacyl‐tRNA synthetases (AaRSs) are valuable “housekeeping” enzymes that ensure the accurate transmission of genetic information in living cells, where they aminoacylated tRNA molecules with their cognate amino acid and provide substrates for protein biosynthesis. In addition to their translational or canonical function, they contribute to nontranslational/moonlighting functions, which are mediated by the presence of other domains on the proteins. This was supported by several reports which claim that AaRS has a significant role in gene transcription, apoptosis, translation, and RNA splicing regulation. Noncanonical/ nontranslational functions of AaRSs also include their roles in regulating angiogenesis, inflammation, cancer, and other major physio‐pathological processes. Multiple AaRSs are also associated with a broad range of physiological and pathological processes; a few even serve as cytokines. Therefore, the multifunctional nature of AaRSs suggests their potential as viable therapeutic targets as well. Here, our discussion will encompass a range of noncanonical functions attributed to Aminoacyl‐tRNA Synthetases (AaRSs), highlighting their links with a diverse array of human diseases.
Wastewater-based epidemiology for comprehensive communitywide exposome surveillance: A gradient of metals exposure
Authors: Cai Lu , Holm Rochelle H. , Biddle Donald J. , Zhang Charlie H. , Talley Daymond , Smith Ted , States J. Christopher 
Published: September 2023

AbstractCommunity wastewater surveillance is an established means to measure health threats. Exposure to toxic metals as one of the key environmental contaminants has been attracting public health attention as exposure can be related to contamination across air, water, and soil as well as associated with individual factors. This research uses Jefferson County, Kentucky, as an urban exposome case study to analyze sub-county metal concentrations in wastewater as a possible indicator of community toxicant exposure risk, and to test the feasibility of using wastewater to identify potential community areas of elevated metals exposure. Variability in wastewater metal concentrations were observed across the county; 19 of the 26 sites had one or more metal results greater than one standard deviation above the mean and were designated areas of concern. Additionally, thirteen of the nineteen sites were of increased concern with levels greater than two standard deviations above the mean. This foundational research found variability in several instances between smaller nested upstream contributing neighborhood sewersheds when measured in the associated downstream treatment plant. Wastewater provides an opportunity to look at integrated toxicology to complement other toxicology data, looking at where people live and what toxicants need to be focused on to protect the health of people in that area.
Exploring the role of the private sector in tuberculosis detection and management in Lima, Peru: a mixed-methods patient pathway analysis
Authors: Wippel Christoph , Farroñay Sheyla , Gilbert Hannah N. , Millones Ana Karina , Acosta Diana , Torres Isabel , Jimenez Judith , Lecca Leonid , Yuen Courtney M. 
Published: September 2023

ABSTRACTIn Latin America, little is known about the involvement of private healthcare providers in TB detection and management. We sought to gain a better understanding of current and potential roles of the private sector in delivering TB services in Peru. We conducted a mixed-methods study in Lima, Peru. The quantitative component comprised a patient pathway analysis assessing the alignment of TB services with patient care-seeking behavior. The qualitative component comprised in-depth interviews with 18 private healthcare providers and 5 key informants. We estimated that 77% of patients initially sought care at a facility with TB diagnostic capacity and 59% at a facility with TB treatment capacity. The lack of TB services at initial care-seeking location was driven by the 41% of patients estimated to seek care first at a private facility. Among private facilities, 43% offered smear microscopy, 13% offered radiography, and none provided TB treatment. Among public sector facilities, 100% offered smear microscopy, 26% offered radiography, and 99% provided TB treatment. Interviews revealed that private providers believed that they offered shorter wait times and a quicker diagnosis, but they struggled with a lack of follow-up systems and communication barriers with the public sector. While expressing willingness to collaborate with public sector programs for diagnosis and referral, private providers had limited interest in treating TB. This study highlights the role of private providers in Peru as an entry point for TB care. Public-private collaboration is necessary to harness the potential of the private sector as an ally for early diagnosis.
Longitudinal and multimodal auditing of tumor adaptation to CDK4/6 inhibitors in HR+ metastatic breast cancers
Authors: Creason Allison L. , Egger Jay , Watson Cameron , Sivagnanam Shamilene , Chin Koei , MacPherson Kevin , Lin Jia-Ren , Chen Yu-An , Johnson Brett E. , Feiler Heidi S. , Galipeau Danielle , Navin Nicholas E. , Demir Emek , Chang Young Hwan , Corless Christopher L. , Mitri Zahi I. , Sorger Peter K. , Thomas George V. , Coussens Lisa M. , Adey Andrew C. , Gray Joe W. , Mills Gordon B. , Goecks Jeremy 
Published: September 2023

AbstractCDK4/6 inhibitors (CDK4/6i) have transformed the treatment of hormone receptor-positive (HR+), HER2-negative (HR+) breast cancers as they are effective across all clinicopathological, age, and ethnicity subgroups for metastatic HR+ breast cancer. In metastatic ER+ breast cancer, CDK4/6i lead to strong and consistent improvement in survival across different lines of therapy. To improve understanding of how metastatic HR+ breast cancers become refractory to CDK4/6i, we have created a multimodal and longitudinal tumor atlas to investigate therapeutic adaptations in malignant cells and in the tumor immune microenvironment. This atlas is part of the NCI Cancer Moonshot Human Tumor Atlas Network and includes seven pairs of pre- and on-progression biopsies from five metastatic HR+ breast cancer patients treated with CDK4/6i. Biopsies were profiled with bulk genomics, transcriptomics, and proteomics as well as single-cell ATAC-seq and multiplex tissue imaging for spatial, single-cell resolution. These molecular datasets were then linked with detailed clinical metadata to create an atlas for understanding tumor adaptations during therapy. Analysis of our atlas datasets suggests a diverse set of tumor adaptations to CDK4/6i therapy. Malignant cells may adapt to therapy via mTORC1 activation, cell cycle bypass, and increased replication stress. The tumor immune microenvironment displayed evidence of both immune activation and immune suppression during therapy. Together, our metastatic ER+ breast cancer atlas represents a rich multimodal resource to better understand HR+ breast cancer tumor therapeutic adaptations to CDK4/6i therapy.
Lifelong dietary protein restriction accelerates skeletal muscle loss and reduces muscle fibre size by impairing proteostasis and mitochondrial homeostasis
Authors: Ersoy Ufuk , Alameddine Moussira , Kanakis Ioannis , Peffers Mandy Jayne , Jackson Malcolm J. , Goljanek-Whysall Katarzyna , Vasilaki Aphrodite , Ozanne Susan E , Vazquez Gibran Pedraza 
Published: September 2023

AbstractThe early life environment significantly affects the development of age-related skeletal muscle disorders. However, the long-term effects of lactational protein restriction on skeletal muscle are still poorly defined. Our study revealed that male mice nursed by dams fed a low-protein diet during lactation exhibited skeletal muscle growth restriction. This was associated with a dysregulation in the expression levels of genes related to the ribosome, mitochondria and skeletal muscle development. We reported that lifelong protein restriction accelerated loss of type-IIa muscle fibres and reduced muscle fibre size by impairing mitochondrial homeostasis and proteostasis at 18 months of age. However, feeding a normal-protein diet following lactational protein restriction prevented accelerated fibre loss and fibre size reduction in later life. These findings provide novel insight into the mechanisms by which lactational protein restriction hinders skeletal muscle growth and includes evidence that lifelong dietary protein restriction accelerated skeletal muscle loss in later life.
A Mechanistically Integrated Model of Exploitative and Interference Competition over a Single Resource Produces Widespread Coexistence
Authors: Smith Daniel J.B. , Masel Joanna 
Published: September 2023

ABSTRACTMany ecological models treat exploitative competition in isolation from interference competition. Corresponding theory centers around theR*rule, according to which consumers who share a single limiting resource cannot coexist. Here we model motile consumers that directly interfere while handling resources, mechanistically capturing both exploitative and interference competition. Our analytical coexistence conditions show that interference competition readily promotes coexistence. In contrast to previous theory, coexistence does not require intra-specific interference propensities to exceed inter-specific interference propensities, nor for interference behaviors to carry a direct (rather than merely an opportunity) cost. The underlying mechanism of coexistence can resemble the hawk-dove game, the dominance-discovery trade-off (akin to the competition-colonization trade-off), or a novel trade-off we call the “dove-discovery trade-off”, depending on parameter values. Competitive exclusion via theR*rule occurs only when differences in exploitative abilities swamp other differences between species, and more easily when differences inR*reflect different search speeds than when they reflect different handling times. Our model provides a mathematically tractable framework that integrates exploitative and interference competition, and synthesizes previous disparate models.
Deepurify: a multi-modal deep language model to remove contamination from metagenome-assembled genomes
Authors: Zou Bohao , Wang Jingjing , Ding Yi , Zhang Zhenmiao , Huang Yufen , Fang Xiaodong , Cheung Ka Chun , See Simon , Zhang Lu 
Published: September 2023

AbstractMetagenome-assembled genomes (MAGs) offer valuable insights into the exploration of microbial dark matter using metagenomic sequencing data. However, there is a growing concern that contamination in MAGs may significantly impact the downstream analysis results. Existing MAG decontamination methods heavily rely on marker genes but do not fully leverage genomic sequences. To address the limitations, we have introduced a novel decontamination approach named Deepurify, which utilizes a multi-modal deep language model employing contrastive learning to learn taxonomic similarities of genomic sequences. Deepurify utilizes inferred taxonomic lineages to guide the allocation of contigs into a MAG-separated tree and employs a tree traversal strategy for maximizing the total number of medium- and high-quality MAGs. Extensive experiments were conducted on two simulated datasets, CAMI I, and human gut metagenomic sequencing data. These results demonstrate that Deepurify significantly outperforms other decontamination methods.
FetoML: Interpretable predictions of the fetotoxicity of drugs based on machine learning approaches
Authors: Jeong Myeonghyeon , Yoo Sunyong 
Published: September 2023

AbstractPregnant females may use medications to manage health problems that develop during pregnancy or that they had prior to pregnancy. However, using medications during pregnancy has a potential risk to the fetus. Assessing the fetotoxicity of drugs is essential to ensure safe treatments, but the current process is challenged by ethical issues, time, and cost. Therefore, the need forin silicomodels to efficiently assess the fetotoxicity of drugs has recently emerged. Previous studies have proposed successful machine learning models for fetotoxicity prediction and even suggest molecular substructures that are possibly associated with fetotoxicity risks or protective effects. However, the interpretation of the decisions of the models on fetotoxicity prediction for each drug is still insufficient. This study constructed machine learning-based models that can predict the fetotoxicity of drugs while providing explanations for the decisions. For this, permutation feature importance was used to identify the general features that the model made significant in predicting the fetotoxicity of drugs. In addition, features associated with fetotoxicity for each drug were analyzed using the attention mechanism. The predictive performance of all the constructed models was significantly high (AUROC: 0.854–0.974, AUPR: 0.890–0.975). Furthermore, we conducted literature reviews on the predicted important features and found that they were highly associated with fetotoxicity. We expect that our model will benefit fetotoxicity research by providing an evaluation of fetotoxicity risk for drugs or drug candidates, along with an interpretation of that prediction.Author summaryDrugs are often necessary for the treatment of diseases in pregnant females. However, some drugs can potentially cause fetotoxicities, such as teratogenicity and abortion. Therefore, it is essential to study fetotoxicity, but traditional toxicity testing demands time, money, and labor. To modernize these testing methods,in silicoapproaches for predicting the fetotoxicity of drugs are emerging. The proposed models so far have successfully predicted the fetotoxicity of drugs and proposed some fetotoxicity-related substructures, but the interpretation of the model’s determination is still insufficient. In this study, we proposed FetoML to predict the fetotoxicity of drugs based on machine learning and provide the substructures that the model focused on in predicting fetotoxicity for each drug. We confirmed the significant predictive performance and interpretability of the model through a quantitative performance evaluation and literature review. We expect FetoML to benefit fetotoxicity studies of drugs by modernizing the paradigm of fetotoxicity testing and providing insights to researchers.
Timing specific parental effects of ocean warming in a coral reef fish
Authors: Bonzi L.C. , Spinks R.K. , Donelson J.M. , Munday P.L. , Ravasi T. , Schunter C. 
Published: September 2023

AbstractPopulation and species persistence in a rapidly warming world will be determined by an organisms’ ability to acclimate to warmer conditions, especially across generations. There is potential for transgenerational acclimation, but the importance of ontogenetic timing in the transmission of environmentally induced parental effects remains mostly unknown. We aimed to disentangle the contributions of two critical ontogenetic stages (juvenile development and adult reproduction) to transgenerational plasticity, by exposing the coral reef fishAcanthochromis polyacanthusto simulated ocean warming with natural diel thermal fluctuations across two generations. By using hepatic transcriptomics, we discovered that the developmental environment of the offspring themselves had little effect on their acclimation potential at 2.5 months of life. Instead, the developmental experience of parents increased regulatory RNA production and protein synthesis, which could improve the offspring’s response to warming. Conversely, reproduction in warmer water elicited stress response mechanisms, with suppression of translation and mitochondrial respiration. Mismatches between temperatures in the parental ontogenetic thermal experience deeply affected offspring gene expression profiles, and detrimental effects were also evident when warming occurred both during parents’ development and reproduction. This study reveals that the previous generation’s developmental temperature contributes substantially to thermal acclimation potential during early life, however prolonged heat stress will likely have adverse effects on the species’ persistence.
Visuomotor memory is not bound to visual motion
Authors: Warburton Matthew , Campagnoli Carlo , Mon-Williams Mark , Mushtaq Faisal , Morehead J. Ryan 
Published: September 2023

AbstractSensory feedback plays a critical role in motor control and motor learning, with both processes adjusting outgoing motor commands relative to the error between actual sensory feedback and the predictions of a forward model. However, models of motor control rarely specify the exact nature of these predictions. We hypothesized that large differences in low-level perceptual feedback would delineate contextual boundaries for motor memory, as sufficiently different feedback would require a distinct mapping between motor commands and sensory states. We tested this hypothesis by measuring transfer of visuomotor adaptation across contexts where hand movements caused visual motion in opposite directions. Instead of observing that visual feedback is bound to distinct internal models, we found nearly complete transfer of learning across the contexts, with evidence that the motor memory was bound to the planned displacement of the hand, rather than visual features of the task space.
ecDNA amplification ofMYCdrives intratumor copy-number heterogeneity and adaptation to stress in PDAC
Authors: Malinova Antonia , Schreyer Daniel , Fiorini Elena , Pasini Davide , Bevere Michele , D’Agosto Sabrina , Andreani Silvia , Lupo Francesca , Veghini Lisa , Grimaldi Sonia , Pedron Serena , Nourse Craig , Salvia Roberto , Malleo Giuseppe , Ruzzenente Andrea , Guglielmi Alfredo , Milella Michele , Lawlor Rita T. , Luchini Claudio , Pilarsky Christian , Scarpa Aldo , Tuveson David A. , Bailey Peter , Corbo Vincenzo 
Published: September 2023

AbstractIntratumor heterogeneity and phenotypic plasticity drive tumour progression and therapy resistance. Oncogene dosage variation contributes to cell state transitions and phenotypic heterogeneity, thereby providing a substrate for somatic evolution. Nonetheless, the genetic mechanisms underlying phenotypic heterogeneity are still poorly understood. Here, we show that extrachromosomal DNA (ecDNA) is a major source of high-level focal amplification in key oncogenes and a major contributor ofMYCheterogeneity in pancreatic ductal adenocarcinoma (PDAC). We demonstrate that ecDNA can drive exceptionally high dosage ofMYCand afford cancer cells rapid adaptation to microenvironmental changes. The continued maintenance of extrachromosomalMYCis uniquely ensured by the presence of the selective pressure. We also show that MYC dosage affects cell morphology and dependence of cancer cells on stromal niche factors, with the highest MYC levels correlating with squamous-like phenotypes. Our work provides the first detailed analysis of ecDNAs in PDAC and describes a new genetic mechanism drivingMYCheterogeneity in PDAC.
Finding Antibodies in Cryo-EM densities with CrAI
Authors: Mallet Vincent , Rapisarda Chiara , Minoux Hervé , Ovsjanikov Maks 
Published: September 2023

AbstractTherapeutic antibodies have emerged as a prominent class of new drugs due to their high specificity and their ability to bind to several protein targets. Once an initial antibody has been identified, an optimization of this hit compound follows based on the 3D structure, when available. Cryo-EM is currently the most efficient method to obtain such structures, supported by well-established methods that can transform raw data into a potentially noisy 3D map. These maps need to be further interpreted by inferring the number, position and structure of antibodies and other proteins that might be present. Unfortunately, existing automated methods addressing this last step have a limited accuracy and usually require additional inputs, high resolution maps, and exhibit long running times.We propose the first fully automatic and efficient method dedicated to finding antibodies in cryo-EM densities:CrAI. This machine learning approach leverages the conserved structure of antibodies and exploits a dedicated novel database that we built to solve this problem. Running a prediction takes only a few seconds, instead of hours, and requires nothing but the cryo-EM density, seamlessly integrating in automated analysis pipelines. Our method is able to find the location of both Fabs and VHHs, at resolutions up to 10Å and is significantly more reliable than existing methods. It also provides an accurate estimation of the antibodies’ pose, even in challenging examples such as Fab binding to VHHs and vice-versa. We make our method available as a ChimeraX[44] bundle.1