bluuebunny/crossref_metadata_2025_split huggingface dataset:
Malassezia responds to environmental pH signals through the conserved Rim/Pal pathway
Authors: Pianalto Kaila M. , Telzrow Calla L. , Harding Hannah Brown , Brooks Jacob T. , Granek Joshua A. , Gushiken-Ibañez Eduardo , LeibundGut-Landmann Salomé , Heitman Joseph , Ianiri Giuseppe , Alspaugh J. Andrew 
Published: July 2024

AbstractDuring mammalian colonization and infection, microorganisms must be able to rapidly sense and adapt to changing environmental conditions including alterations in extracellular pH. The fungus-specific Rim/Pal signaling pathway is one process that supports microbial adaptation to alkaline pH. This cascading series of interacting proteins terminates in the proteolytic activation of the highly conserved Rim101/PacC protein, a transcription factor that mediates microbial responses that favor survival in neutral/alkaline pH growth conditions, including many mammalian tissues. We identified the putative Rim pathway proteins Rim101 and Rra1 in the human skin colonizing fungusMalassezia sympodialis. Gene deletion by transconjugation and homologous recombination revealed that Rim101 and Rra1 are required forM. sympodialisgrowth at higher pH. Additionally, comparative transcriptional analysis of the mutant strains compared to wild-type suggested mechanisms for fungal adaptation to alkaline conditions. These pH-sensing signaling proteins are required for optimal growth in a murine model of atopic dermatitis, a pathological condition associated with increased skin pH. Together these data elucidate both conserved and phylum-specific features of microbial adaptation to extracellular stresses.ImportanceThe ability to adapt to host pH has been previously associated with microbial virulence in several pathogenic fungal species. Here we demonstrate that a fungal-specific alkaline response pathway is conserved in the human skin commensal fungusMalassezia sympodialis(Ms). This pathway is characterized by the pH-dependent activation of the Rim101/PacC transcription factor that controls cell surface adaptations to changing environmental conditions. By disrupting genes encoding two predicted components of this pathway, we demonstrated that the Rim/Pal pathway is conserved in this fungal species as a facilitator of alkaline pH growth. Moreover, targeted gene mutation and comparative transcriptional analysis supports the role of theMsRra1 protein as a cell surface pH sensor conserved within the basidiomycete fungi, a group including plant and human pathogens. Using an animal model of atopic dermatitis, we demonstrate the importance ofMsRim/Pal signaling in this common inflammatory condition characterized by increased skin pH.
Commensal-pathogen dynamics structure disease outcomes duringClostridioides difficilecolonization
Authors: Fishbein Skye R. S. , DeVeaux Anna L. , Khanna Sakshi , Ferreiro Aura L. , Liao James , Agee Wesley , Ning Jie , Mahmud Bejan , Wallace Miranda J. , Hink Tiffany , Reske Kimberly A. , Guruge Janaki , Leekha Sidh , Dubberke Erik R. , Dantas Gautam 
Published: July 2024

AbstractGastrointestinal colonization byClostridioides difficileis common in healthcare settings and ranges in clinical presentation from asymptomatic carriage to lethalC. difficileinfection (CDI). We used a systems biology approach to investigate why patients colonized withC. difficilehave a range of outcomes. Microbiota-humanization of germ-free mice with fecal samples from toxigenic C. difficile carriers revealed a spectrum of virulence among clade 1 lineages and identified commensalBlautiaassociated with markers of non-pathogenic colonization. Using gnotobiotic mice engrafted with defined human microbiota, we observed strain-specific CDI severity across clade 1 strains. Yet, mice engrafted with a higher diversity community were protected from severe disease across all strains without suppression ofC. difficilecolonization. These results indicate that when colonization resistance has been breached without overt infection, commensals can attenuate a diversity of virulent strains without inhibiting pathogen colonization, providing insight into determinants of stableC. difficilecarriage.
Direct testing of natural twister ribozymes from over a thousand organisms reveals a broad tolerance for structural imperfections
Authors: McKinley Lauren N. , Meyer McCauley O. , Sebastian Aswathy , Chang Benjamin K. , Messina Kyle J. , Albert Istvan , Bevilacqua Philip C. 
Published: July 2024

ABSTRACTTwister ribozymes are an extensively studied class of nucleolytic RNAs. Thousands of natural twisters have been proposed using sequence homology and structural descriptors. Yet, most of these candidates have not been validated experimentally. To address this gap, we developed CHiTA (Cleavage High-Throughput Assay), a high-throughput pipeline utilizing massively parallel oligonucleotide synthesis and next-generation sequencing to test putative ribozymesen massein a scarless fashion. As proof of principle, we applied CHiTA to a small set of known active and mutant ribozymes. We then used CHiTA to test two large sets of naturally occurring twister ribozymes: over 1, 600 previously reported putative twisters and ∼1, 000 new candidate twisters. The new candidates were identified computationally in ∼1, 000 organisms, representing a massive increase in the number of ribozyme-harboring organisms. Approximately 94% of the twisters we tested were active and cleaved site-specifically. Analysis of their structural features revealed that many substitutions and helical imperfections can be tolerated. We repeated our computational search with structural descriptors updated from this analysis, whereupon we identified and confirmed the first intrinsically active twister ribozyme in mammals. CHiTA broadly expands the number of active twister ribozymes found in nature and provides a powerful method for functional analyses of other RNAs.GRAPHICAL ABSTRACT
Beyond the Black Box: Avenues for Transparency in Regulating Radiological AI/ML-enabled SaMD via the FDA 510(k) Pathway
Authors: Youssef Alaa , Fronk David , Grimes John Nicholas , Cheuy Lina , Larson David B. 
Published: July 2024

AbstractBackgroundThe majority of AI/ML-enabled software as a medical device (SaMD) has been cleared through the FDA 510(k) pathway, but with limited transparency on algorithm development details. Because algorithm quality depends on the quality of the training data and algorithmic input, this study aimed to assess the availability of algorithm development details in the 510(k) summaries of AI/ML-enabled SaMD. Then, clinical and/or technical equivalence between predicate generations was assessed by mapping the predicate lineages of all cleared computer-assisted detection (CAD) devices, to ensure equivalence in diagnostic function.MethodsThe FDA’s public database was searched for CAD devices cleared through the 510(k) pathway. Details on algorithmic input, including annotation instructions and definition of ground truth, were extracted from summary statements, product webpages, and relevant publications. These findings were cross-referenced with the American College of Radiology–Data Science Institute AI Central database. Predicate lineages were also manually mapped through product numbers included within the 510(k) summaries.ResultsIn total, 98 CAD devices had been cleared at the time of this study, with the majority being computer-assisted triage (CADt) devices (67/98). Notably, none of the cleared CAD devices provided image annotation instructions in their summaries, and only one provided access to its training data. Similarly, more than half of the devices did not disclose how the ground truth was defined. Only 13 CAD devices were reported in peer-reviewed publications, and only two were evaluated in prospective studies. Significant deviations in clinical function were seen between cleared devices and their claimed predicate.ConclusionThe lack of imaging annotation instructions and signicant mismatches in clinical function between predicate generations raise concerns about whether substantial equivalence in the 510(k) pathway truly equates to equivalent diagnostic function. Avenues for greater transparency are needed to enable independent evaluations of safety and performance and promote trust in AI/ML-enabled devices.
Multimodal Prehabilitation in People Awaiting Acute Inpatient Cardiac Surgery: Study Protocol for a Pilot Feasibility Trial (PreP-ACe)
Authors: Raut Sarah , Hales Aaron , Twiddy Maureen , Dixon Lili , Ngaage Dumbor , Yates David , Danjoux Gerard , Ingle Lee 
Published: July 2024

AbstractBackgroundThe concept of “prehabilitation,” or optimising individual physical and mental well-being prior to surgery is well established in cancer and orthopaedic populations. However, amongst the cardiac surgery population, the concept is relatively new. Of the few studies available, all focus on the elective surgical population. This pilot feasibility trial is novel as it will focus on the impact of multimodal prehabilitation on the acute inpatient cardiac surgical population.MethodsThis single centre, prospective, single arm pilot feasibility trial will recruit 20 inpatients awaiting cardiac surgery. Measurements will be collected at the start of the trial (baseline), 7 days after intervention, and 14 days after the intervention or before the day of surgery. The primary outcome measure will be feasibility and practicality of the programme in an acute inpatient population. We will be looking into participant eligibility, acceptability, recruitment rates, completion rates and barriers to implementing a prehabilitation programme. Secondary outcomes include incidence of study-related adverse events, improvement in 6 minutes walk test (6MWT), hand grip strength, quality of life, anxiety scores and spirometry. At the end of the trial, we will be seeking the feedback of the participants on key components of the programme to help us inform future work. We hypothesise that light to moderate structured exercise training is low risk and feasible in patients awaiting inpatient cardiac surgery. The study was approved by Health Research Authority and Heath and Care Research Wales (Yorkshire & the Humber-Bradford Leeds Research Ethics Committee: REC reference 23/YH/0255) on the 8th November 2023.DiscussionMultimodal prehabilitation could improve individual physical and mental wellbeing whilst awaiting inpatient cardiac surgery. Prehabilitation can provide individuals with a sense of ownership and control over their condition, improve their motivation and independence, and enhance their mental and physical recovery after surgery. Traditionally, patients waiting for cardiac surgery are discouraged from physical activity/ structured exercise training and receive limited information regarding their health. Appropriate physical and psychological support could improve their confidence to mobilise sooner after surgery. This may then facilitate earlier discharge leading to improved hospital bed utilisation and patient flow.
Pretrained Language Models for Semantics-Aware Data Harmonisation of Observational Clinical Studies in the Era of Big Data
Authors: Dylag Jakub , Zlatev Zlatko , Boniface Michael 
Published: July 2024

AbstractBackgroundIn clinical research, there is a strong drive to leverage big data from population cohort studies and routine electronic healthcare records to design new interventions, improve health outcomes and increase efficiency of healthcare delivery. Yet, realising these potential demands requires substantial efforts in harmonising source datasets and curating study data, which currently relies on costly and time-consuming manual and labour-intensive methods.ObjectivesWe evaluate the applicability of AI methods for natural language processing (NLP) and unsupervised machine learning (ML) to the challenges of big data semantic harmonisation and curation. Our aim is to establish an efficient and robust technological foundation for the development of automated tools supporting data curation of large clinical datasets.MethodsWe assess NLP and unsupervised ML algorithms and propose two pipelines for automated semantic harmonisation: a pipeline for semantics-aware search for domain relevant variables and a pipeline for clustering of semantically similar variables. We evaluate pipeline performance using 94,037 textual variable descriptions from the English Longitudinal Study of Ageing (ELSA) database.ResultsWe observe high accuracy of our Semantic Search pipeline with an AUC of 0.899 (SD=0.056). Our Semantic Clustering pipeline achieves a V-measure of 0.237 (SD=0.157), which is on par with leading implementations in other relevant domains. Automation can significantly accelerate the process of dataset harmonization. Manual labelling was performed at a speed of 2.1 descriptions per minute, with our automated labelling increasing speed to 245 descriptions per minute.ConclusionsOur study findings underscore the potential of AI technologies, such as NLP and unsupervised ML, in automating the harmonisation and curation of big data for clinical research. By establishing a robust technological foundation, we pave the way for the development of automated tools that streamline the process, enabling health data scientists to leverage big data more efficiently and effectively in their studies, accelerating insights from data for clinical benefit.
RBD amplicon sequencing of wastewater reveals patterns of variant emergence and evolution
Authors: Chen Xingwen , Balliew John , Bauer Cici X. , Deegan Jennifer , Gitter Anna , Hanson Blake M. , Maresso Anthony W. , Tisza Michael J. , Troisi Catherine L. , Rios Janelle , Mena Kristina D. , Boerwinkle Eric , Wu Fuqing 
Published: July 2024

AbstractRapid evolution of SARS-CoV-2 has resulted in the emergence of numerous variants, posing significant challenges to public health surveillance. Clinical genome sequencing, while valuable, has limitations in capturing the full epidemiological dynamics of circulating variants in the general population. This study utilized receptor-binding domain (RBD) amplicon sequencing of wastewater samples to monitor the SARS-CoV-2 community dynamics and evolution in El Paso, TX. Over 17 months, we identified 91 variants and observed waves of dominant variants transitioning from BA.2 to BA.2.12.1, BA.4&5, BQ.1, and XBB.1.5. Our findings demonstrated early detection of variants and identification of unreported outbreaks, while showing strong consistency with clinical genome sequencing data at the local, state, and national levels. Alpha diversity analyses revealed significant periodical variations, with the highest diversity observed in winter and the outbreak lag phases, likely due to lower competition among variants before the outbreak growth phase. The data underscores the importance of low transmission periods for rapid mutation and variant evolution. This study highlights the effectiveness of integrating RBD amplicon sequencing with wastewater surveillance in tracking viral evolution, understanding variant emergence, and enhancing public health preparedness.
Large-scale genome-wide interaction analyses on multiple cardiometabolic risk factors to identify age-specific genetic risk factors
Authors: Ao Linjun , van Heemst Diana , Luo Jiao , Teder-Laving Maris , Mägi Reedik ,   Estonian Biobank Research Team, Frikke-Schmidt Ruth , van Dijk Ko Willems , Noordam Raymond 
Published: July 2024

AbstractBackgroundThe genetic landscape of cardiometabolic risk factors has been explored extensively. However, insight in the effects of genetic variation on these risk factors over the life course is sparse. Here, we performed genome-wide interaction studies (GWIS) on different cardiometabolic risk factors to identify age-specific genetic risks.MethodsThis study included 270,276 unrelated European-ancestry participants from the UK Biobank (54.2% women, a median age of 58 [interquartile range (IQR): 50, 63] years). GWIS models with interaction terms between genetic variants and age were performed on apolipoprotein B (ApoB), low-density lipoprotein-cholesterol (LDL-C), log-transformed triglycerides (TG), body mass index (BMI), and systolic blood pressure (SBP). Replication was subsequently performed in the Copenhagen General Population Study (CGPS) and the Estonian Biobank (EstBB).ResultsMultiple lead variants were identified to have genome-wide significant interactions with age (Pinteraction<1e-08). In detail, rs429358 (taggingAPOE4) was identified for ApoB (Pinteraction= 9.0e-14) and TG (Pinteraction= 5.4e-16). Three additional lead variants were identified for ApoB: rs11591147 (R46L inPCSK9,Pinteraction= 3.9e-09), rs34601365 (nearAPOB,Pinteraction= 8.4e-09), and rs17248720 (nearLDLR,Pinteraction= 2.0e-09). Effect sizes of the identified lead variants were generally closer to the null with increasing age. No variant-age interactions were identified for LDL-C, SBP and BMI. The significant interactions of rs429358 with age on ApoB and TG were replicated in both CGPS and EstBB.ConclusionsThe majority of genetic effects on cardiometabolic risk factors remains relatively constant over age, with the noted exceptions of specific genetic effects on ApoB and TG.
A Machine Learning-Based Prediction of Hospital Mortality in Mechanically Ventilated ICU Patients
Authors: Li Hexin , Ashrafi Negin , Kang Chris , Zhao Guanlan , Chen Yubing , Pishgar Maryam 
Published: July 2024

AbstractBackgroundMechanical ventilation (MV) is vital for critically ill ICU patients but carries significant mortality risks. This study aims to develop a predictive model to estimate hospital mortality among MV patients, utilizing comprehensive health data to assist ICU physicians with early-stage alerts.MethodsWe developed a Machine Learning (ML) framework to predict hospital mortality in ICU patients receiving MV. Using the MIMIC-III database, we identified 25,202 eligible patients through ICD-9 codes. We employed backward elimination and the Lasso method, selecting 32 features based on clinical insights and literature. Data preprocessing included eliminating columns with over 90% missing data and using mean imputation for the remaining missing values. To address class imbalance, we used the Synthetic Minority Over-sampling Technique (SMOTE). We evaluated several ML models, including CatBoost, XGBoost, Decision Tree, Random Forest, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Logistic Regression, using a 70/30 train-test split. The CatBoost model was chosen for its superior performance in terms of accuracy, precision, recall, F1-score, AUROC metrics, and calibration plots.ResultsThe study involved a cohort of 25,202 patients on MV. The CatBoost model attained an AUROC of 0.862, an increase from an initial AUROC of 0.821, which was the best reported in the literature. It also demonstrated an accuracy of 0.789, an F1-score of 0.747, and better calibration, outperforming other models. These improvements are due to systematic feature selection and the robust gradient boosting architecture of CatBoost.ConclusionThe preprocessing methodology significantly reduced the number of relevant features, simplifying computational processes, and identified critical features previously overlooked. Integrating these features and tuning the parameters, our model demonstrated strong generalization to unseen data. This highlights the potential of ML as a crucial tool in ICUs, enhancing resource allocation and providing more personalized interventions for MV patients.
Polycomb-associated and Trithorax-associated developmental conditions – phenotypic convergence and heterogeneity
Authors: Smail Alice , Jawahiri Eema , Baker Kate 
Published: July 2024

AbstractPolycomb group (PcG) and Trithorax group (TrxG) complexes represent two major components of the epigenetic machinery. This study aimed to delineate phenotypic similarities and differences across developmental conditions arising from rare variants in PcG and TrxG genes, using data-driven approaches.462 patients with a PcG or TrxG-associated condition were identified in the DECIPHER dataset. We analysed Human Phenotype Ontology (HPO) data to identify phenotypes enriched in this group, in comparison to other monogenic conditions within DECIPHER. We then assessed phenotypic relationships between single gene diagnoses within the PcG and TrxG group, by applying semantic similarity analysis and hierarchical clustering. Finally, we analysed patient-level phenotypic heterogeneity in this group, irrespective of specific genetic diagnosis, by applying the same clustering approach. Collectively, PcG/TrxG diagnoses were associated with increased reporting of HPO terms relating to integument, growth, head & neck, limb and digestive abnormalities. Gene group analysis identified three multi-gene clusters differentiated by microcephaly, limb/digit dysmorphologies, growth abnormalities and atypical behavioural phenotypes. Patient-level analysis identified two large clusters differentiated by neurodevelopmental abnormalities and facial dysmorphologies respectively, as well as smaller clusters associated with more specific phenotypes including behavioural characteristics, eye abnormalities, growth abnormalities and skull dysmorphologies. Importantly, patient-level phenotypic clusters did not align with genetic diagnoses. Data-driven approaches can highlight pathway-level and gene-level phenotypic convergences, and individual-level phenotypic heterogeneities. Future studies are needed to understand the multi-level mechanisms contributing to both convergence and variability within this population, and to extend data collection and analyses to later-emerging health characteristics.
Oxidative stress promotes axonal atrophy through alterations in microtubules and EB1 function
Authors: Shields Samuel , Wilkes Oliver , Gozes Illana , Sanchez-Soriano Natalia 
Published: July 2024

AbstractAxons are crucial for transmitting neurochemical signals. As organisms age, the ability of neurons to maintain their axons declines; hence aged axons are more susceptible to damage or dysfunction. Understanding what causes axonal vulnerability is crucial for developing strategies to enhance overall resilience of neurons, and to prevent their deterioration during ageing or in age-related neurodegenerative diseases.Increasing levels of reactive oxygen species (ROS) causes oxidative stress, a hallmark of ageing and age-related diseases. Despite this association, a causal relationship between oxidative stress and neuronal ageing remains unclear, particularly how subcellular physiology is affected by ROS.By usingDrosophila-derived primary neuronal cultures and a recently developedin vivoneuronal model of ageing, which involves the visualisation ofDrosophilamedulla neurons, we investigated the interplay between oxidative stress, neuronal ageing and the microtubule cytoskeleton. We find that oxidative stress as a key driver of axonal and synaptic decay, including the appearance of axonal swellings, microtubule alterations in both axons and synapses and the morphological transformation of axonal terminals during ageing. We demonstrate that increased ROS sensitises the microtubule plus end binding factor, end-binding protein 1 (EB1), leading to microtubule defects, affecting neuronal integrity. Furthermore, manipulating EB1 proved to be a valuable therapeutic strategy to prevent ageing hallmarks observed in conditions of elevated ROS. In summary, we demonstrate a mechanistic pathway linking cellular oxidative stress, the microtubule cytoskeleton and axonal deterioration during ageing and provide evidence of the therapeutic potential of enhancing microtubule plus end physiology to improve the resilience of axons.