bluuebunny/crossref_metadata_2025_split huggingface dataset:
Inorganic polyphosphate and the stringent response coordinately control cell division and cell morphology inEscherichia coli
Authors: Hamm Christopher W. , Gray Michael J. 
Published: September 2024

ABSTRACTBacteria encounter numerous stressors in their constantly changing environments and have evolved many methods to deal with stressors quickly and effectively. One well known and broadly conserved stress response in bacteria is the stringent response, mediated by the alarmone (p)ppGpp. (p)ppGpp is produced in response to amino acid starvation and other nutrient limitations and stresses and regulates both the activity of proteins and expression of genes.Escherichia colialso makes inorganic polyphosphate (polyP), an ancient molecule evolutionary conserved across most bacteria and other cells, in response to a variety of stress conditions, including amino acid starvation. PolyP can act as an energy and phosphate storage pool, metal chelator, regulatory signal, and chaperone, among other functions. Here we report thatE. colilacking both (p)ppGpp and polyP have a complex phenotype indicating previously unknown overlapping roles for (p)ppGpp and polyP in regulating cell division, cell morphology, and metabolism. Disruption of either (p)ppGpp or polyP synthesis led to formation of filamentous cells, but simultaneous disruption of both pathways resulted in cells with heterogenous cell morphologies, including highly branched cells, severely mislocalized Z-rings, and cells containing substantial void spaces. These mutants also failed to grow when nutrients were limited, even when amino acids were added. These results provide new insights into the relationship between polyP synthesis and the stringent response in bacteria and point towards their having a joint role in controlling metabolism, cell division, and cell growth.IMPORTANCECell division is a fundamental biological process, and the mechanisms that control it inEscherichia colihave been the subject of intense research scrutiny for many decades. Similarly, both the (p)ppGpp-dependent stringent response and inorganic polyphosphate (polyP) synthesis are well-studied, evolutionarily ancient, and widely conserved pathways in diverse bacteria. Our results indicate that these systems, normally studied as stress-response mechanisms, play a coordinated and novel role in regulating cell division, morphology, and metabolism even under non-stress conditions.
A Sex-specific Mendelian Randomization-Phenome-Wide Association Study of Body Mass Index
Authors: Jiesisibieke Zhu Liduzi , Chan Io Ieong , Ng Jack Chun Man , Schooling C Mary 
Published: September 2024

ABSTRACTBackgroundTrials of incretins are making it increasingly clear that body mass index (BMI) is linked to several diseases throughout life, but trials cannot provide a comprehensive assessment of the role of BMI in health-related attributes for men and women. To systematically investigate the role of BMI, we conducted a sex-specific Mendelian randomization-phenome-wide association study.MethodsWe comprehensively examined the associations of genetically predicted BMI in women (n: 194,174) and men (n: 167,020) with health-related attributes from the UK Biobank with inverse variance weighting and sensitivity analysis.ResultsBMI impacted 232 of 776 traits considered in women and 204 of 681 traits in men, after adjusting for false discovery; differences by sex were found for 105 traits. BMI was more strongly positively associated with heart disease, heart failure and hypertensive heart disease in men than women. BMI was more strongly positively associated with apolipoprotein B (ApoB), diastolic blood pressure, neuroticism, arthritis and triglycerides in women than men.ConclusionOur study revealed that BMI might affect a wide range of health-related attributes and highlights notable sex differences in its impact, including opposite associations for certain attributes, such as ApoB and neuroticism. These findings emphasize the importance of maintaining a healthy BMI.FundingNone
Building and validating a predictive model for stroke risk in Chinese community-dwelling patients with chronic obstructive pulmonary disease using machine learning methods
Authors: Chen Yong , Yu Yonglin , Yang Dongmei , Chen Xiaoju 
Published: September 2024

AbstractBackgroundThe occurrence of stroke in patients with chronic obstructive pulmonary disease (COPD) can have potentially devastating consequences; however, there is still a lack of predictive models that accurately predict the risk of stroke in community-based COPD patients in China. The aim of this study was to construct a novel predictive model that accurately predicts the predictive model for the risk of stroke in community-based COPD patients by applying a machine learning methodology within the Chinese community.MethodsThe clinical data of 809 Community COPD patients were analyzed by using the 2020 China Health and Retirement Longitudinal Study (CHARLS) database. The least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression were used to analyze predictors. Multiple machine learning (ML) classification models are integrated to analyze and identify the optimal model, and Shapley Additive exPlanations (SHAP) interpretation was developed for personalized risk assessment.ResultsThe following six variables:Heart_disease,Hyperlipidemia,Hypertension,ADL_score, Cesd_score and Parkinson are predictors of stroke in community-based COPD patients. Logistic classification model was the optimal model, test set area under curve (AUC) (95% confidence interval, CI):0.913 (0.835-0.992), accuracy: 0.823, sensitivity: 0.818, and specificity: 0.823.ConclusionsThe model constructed in this study has relatively reliable predictive performance, which helps clinical doctors identify high-risk populations of community COPD patients prone to stroke at an early stage.
Impact of the WHELD/Brief Psychosocial Therapy intervention on psychosis in people with dementia: A Cluster Randomized Trial
Authors: Ballard C , McDermid J , Mills K , Sweetnam A , Fossey J 
Published: September 2024

AbstractNeuropsychiatric Symptoms (NPS), particularly psychosis, are common in dementia and can significantly impact patient outcomes, caregivers and disease trajectory. Psychosis, which includes hallucinations and delusions, occurs in up to 50% of people with dementia and has been linked with lower quality of life and faster cognitive decline. While best practice guidelines have highlighted the importance of non-pharmacological treatments for NPS, evidence-based non-pharmacological approaches are limited. This exploratory analysis of a cluster randomized control trial (RCT) from the WHELD programme compares the WHELD/Brief Psychosocial Therapy intervention with treatment as usual in a 9-month trial across 69 UK nursing homes (N=8477, 553 completed). The current report analyzed outcomes for the participants with dementia-related psychosis (N=163) participating in the trial. Whilst the WHELD/Brief Psychosocial Therapy intervention did not significantly reduce NPI psychosis score, it did significantly improve apathy (p=0.006), agitation (p=0.038) and quality of life (p=0.01) in participants with psychosis. In addition there was a non-significant numerical improvement in caregiver perceived disruptiveness. These findings suggest that whilst the WHELD/ Brief Psychosocial Therapy intervention does not directly alleviate psychosis in people with dementia, it does significantly improve related neuropsychiatric symptoms and quality of life, offering meaningful benefits to people with dementia experiencing distressing psychotic symptoms.
Scoping Review: Outpatient Psychotherapeutic Care for Children and Adolescents in Germany – Status Quo and Challenges in Assessment
Authors: Rodney-Wolf Kristin , Schmitz Julian 
Published: September 2024

AbstractIn the context of multiple global crises, including the COVID-19 pandemic, climate change, and global conflicts, children and adolescents worldwide are experiencing heightened psychological stress. As the foundation for lifelong mental health is established during childhood and adolescence, early prevention and treatment of mental health problems, such as through psychotherapy, are crucial. In Germany, current outpatient psychotherapeutic care capacities appear inadequate, while systematic evaluations of the care situation are lacking. This study investigates the state of statutory health insurance-funded outpatient psychotherapeutic care for children and adolescents in Germany and evaluates various methodological approaches for its assessment. We conducted a scoping review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. Publications from January 2018 to December 2023 were sourced from PubPsych, PubMed, APA PsycInfo, Google Scholar, and ProQuest. Included studies reported quantitative primary data on the mental health of community samples of children and adolescents in Germany or their outpatient psychotherapeutic care. We included 41 publications comprising epidemiological studies, administrative data, and psychotherapist and patient reports. A lack of systematic and standardized research approaches resulted in significant variance in data. Nonetheless, qualitative analysis revealed that approximately one four children and adolescents in Germany is affected by mental health problems, while one in six to seven children and adolescents requires psychotherapeutic treatment. Yet, only up to one in fifty receives guideline-based psychotherapy. Most requests for initial psychotherapeutic consultations are unmet, with waiting times for guideline-based psychotherapy exceeding six months for at least half of the patients. Overall, our findings suggest that outpatient psychotherapeutic care for children and adolescents in Germany is still insufficient. They advocate for a systematic, multimodal, and longitudinal assessment of statutory health insurance-funded outpatient psychotherapeutic care, along with an expansion of treatment capacities to enhance access for children and adolescents in Germany.
Methodological issues in visible LED therapy dermatological research and reporting
Authors: Grimes David Robert 
Published: September 2024

AbstractThe advent of mass-market Light Emitting Diodes (LEDs) has seen considerable interest in potential dermatological applications of LED light photobiomodulation (PBM) for a range of conditions, with a thriving market for direct-to-consumer LED treatments, including red light, blue light, and yellow light wavelengths. Evidence of efficacy for many conditions is however decidedly mixed, with starkly different outcomes reported by different authors. Due to the wide range of irradiances and wavelengths used, interpretation, comparison, and even efficacy evaluation is often impossible or prohibitive, impeding evidence synthesis. This work establishes a framework for objectively cross-comparing patient dose in terms of fluence, and a model for contrasting received dose to typical solar dose at ground level to facilitate interpretation of results and evidence synthesis. This allowes direct cross-comparison of patient skin fluence from LED PMB treatments under different regimes, and a means for evidence synthesis. This was applied to LED PMB data from 27 clinical trials to examine fluences and patient-equivalent solar exposure from LED light-sources for dermatological conditions, including acne vulgaris, wrinkle-reduction, wound-healing, psoriasis severity, and erythemal index. The results of this analysis suggest that fluences, wavelengths, and solar exposure equivalent differed by orders of magnitude in he studies analysed, with effective doses often comparable to typical daily solar exposure. Better dose quantification and plausible biological justification for various wavelengths and fluences are imperative if LED therapy studies for dermatology are to be informative and research replicability improved.
Forecasting local surges in COVID-19 hospitalizations through adaptive decision tree classifiers
Authors: Murray-Watson Rachel E. , Bilinski Alyssa , Yaesoubi Reza 
Published: September 2024

AbstractDuring the COVID-19 pandemic, many communities across the US experienced surges in hospitalizations, which strained the local hospital capacity and affected the overall quality of care. Even when effective vaccines became available, many communities remained at high risk of surges in COVID-19-related hospitalizations due to waning immunity, low uptake of booster vaccinations, and the continual emergence of new variations of SARS-CoV-2. Some risk metrics, such as the CDC’s Community Levels, were developed to predict the impact of COVID-19 on the community-level healthcare system based on routine surveillance data. However, they had limited utility as they were not routinely updated based on accumulating data and were not directly linked to specific outcomes, such as surges in COVID-19 hospitalizations beyond local capacities. Regression models could resolve these limitations, but they have limited interpretability and do not convey the reasoning behind their predictions. In this paper, we evaluated decision tree classifiers that were developed in “real-time” to predict surges in local hospitalizations due to COVID-19 between July 2020 and November 2022. These classifiers would have provided visually intuitive and interpretable decision rules for local decision-makers to understand and act upon, and by being updated weekly, would have responded to changes in the epidemic. We showed that these classifiers exhibit reasonable predictive ability with the area under the receiver operating characteristic curve (auROC) > 80%. These classifiers maintained their performance temporally (i.e, over the duration of the pandemic) and spatially (i.e., across US counties). We also showed that these classifiers outperformed the CDC’s Community Levels for predicting high hospital occupancy.Significance StatementA major concern during the COVID-19 pandemic was the risk of exceeding local healthcare capacity due to COVID-19-related hospitalizations. To assess this risk and inform mitigating strategies, several risk assessment tools were developed during the pandemic. Many of these tools, however, did not predict local outcomes, were not updated as the pandemic progressed, and/or were not interpretable by decision-makers. We propose an adaptive framework of decision tree classifiers to predict whether COVID-19-related hospital occupancy would exceed a given capacity threshold. This framework would provide interpretable classification rules to predict surges in local hospitalizations,and maintained its performance over time and across US counties, and outperformed the CDC’s Community Level tool.
Mitochondrial metabolism is a key determinant of chemotherapy sensitivity in Colorectal Cancer
Authors: Moss Deborah Y. , Brown Connor , Shaw Andrew , McCann Christopher , Lewis Nikita , Phillips Aaron , Gallagher Sarah , McDaid William J. , Roe Andrew , Coughlan Aisling Y. , Cavanagh Brenton , Ormsby Callum , Falcone Fiammetta , McCole Rachel , Monteith Scott , Rogan Emily , Downs Matilda , Malla Sudhir B. , Emerson Alexandra J , Mohammed-Smith Letitia , Sharkey Shaun , Gallagher Peter F. , Banerjee Arindam , Pandor Sufyan , Greer Brett , Elliott Christopher , Ryan Aideen , Dunne Philip D. , Coyle Vicky , Mills Ian G. , McDade Simon S. , Sansom Owen , Chonghaile Triona Ni , Longley Daniel B. , LaBonte Melissa J. , Kerr Emma M. 
Published: September 2024

AbstractTherapy resistance is attributed to over 80% of cancer deaths per year emphasizing the urgent need to overcome this challenge for improved patient outcomes. Despite its widespread use in colorectal cancer (CRC) treatment, resistance to 5-fluorouracil (5FU) remains poorly understood. Here, we investigate the transcriptional responses of CRC cells to 5FU treatment, revealing significant metabolic reprogramming towards heightened mitochondrial activity. Utilizing CRC models, we demonstrate sustained enhancement of mitochondrial biogenesis and function following 5FU treatment, leading to resistance in both in vitro and in vivo settings. Furthermore, we show that targeting mitochondrial metabolism, specifically by inhibiting Complex I (CI), sensitizes CRC cells to 5FU, resulting in delayed tumour growth and prolonged survival in preclinical models. Additionally, our analysis of patient data suggests that oxidative metabolism signatures may predict responses to 5FU-based chemotherapy. These findings shed light on mechanisms underlying 5FU resistance and propose a rational strategy for combination therapy in CRC, emphasizing the potential clinical benefit of targeting mitochondrial metabolism to overcome resistance and enhance patient outcomes.
Biantennary N-glycans As Receptors for MARTX Toxins inVibrioPathogenesis
Authors: Chen Jiexi , Goerdeler Felix , Jaroentomeechai Thapakorn , Hernandez Francisco X. S. , Wang Xiaozhong , Clausen Henrik , Narimatsu Yoshiki , Satchell Karla J. F. 
Published: September 2024

ABSTRACTMultifunctional Autoprocessing Repeats-in-Toxin (MARTX) toxins are a diverse effector delivery platform of many Gram-negative bacteria that infect mammals, insects, and aquatic animal hosts. The mechanisms by which these toxins recognize host cell receptors for translocation of toxic effectors into the cell have remained elusive. Here, we map the first surface receptor-binding domain of a MARTX toxin from the highly lethal foodborne pathogenVibrio vulnificus. This domain corresponds to a 273-amino acid sequence with predicted symmetrical immunoglobulin-like folds. We demonstrate that this domain binds internalN-acetylglucosamine on complex biantennary N-glycans with select preference for L1CAM and other N-glycoproteins with multiple N-glycans on host cell surfaces. This receptor binding domain is essential forV. vulnificuspathogenesis during intestinal infection. The identification of a highly conserved motif universally present as part of all N-glycans correlates with theV. vulnificusMARTX toxin boasting broad specificity and targeting nearly all cell types.
pr-independent biogenesis of infectious mature Zika virus particles
Authors: Dowd Kimberly A. , Schroeder Michelle , Sanchez Egan , Brumbaugh Beniah , Foreman Bryant M. , Burgomaster Katherine E. , Shi Wei , Wang Lingshu , Caputo Natalie , Gordon David N. , Schwartz Cindi L. , Hansen Bryan T. , Aleshnick Maya , Kong Wing-Pui , Morabito Kaitlyn M. , Hickman Heather D. , Graham Barney S. , Fischer Elizabeth R. , Pierson Theodore C. 
Published: September 2024

AbstractFlavivirus assembly at the endoplasmic reticulum is driven by the structural proteins envelope (E) and premembrane (prM). Here, contrary to the established paradigm for flavivirus assembly, we demonstrate that the biogenesis of flavivirus particles does not require an intact prM nor proteolytic activation. The expression of E preceded by a truncated version of prM (M-E) was sufficient for the formation of non-infectious Zika virus subviral particles and pseudo-infectious reporter virions. Subviral particles encoded by a ZIKV M-E DNA vaccine elicited a neutralizing antibody response that was insensitive to the virion maturation state, a feature of flavivirus humoral immunity shown to correlate with protection. M-E vaccines that uniformly present structural features shared with mature virions offer a higher quality and broadly applicable approach to flavivirus vaccination.
Computational studies reveal structural characterization and novel families ofPuccinia striiformisf. sp.triticieffectors
Authors: Asghar Raheel , Wu Nan , Ali Noman , Wang Yulei , Akkaya Mahinur 
Published: September 2024

AbstractUnderstanding the biological functions ofPuccinia striiformisf. sp.tritici(Pst) effectors is fundamental for uncovering the mechanisms of pathogenicity and variability, thereby paving the way for developing durable and effective control strategies for stripe rust. However, due to the lack of an efficient genetic transformation system inPst, progress in effector function studies has been slow. Here, we modeled the structures of 15,201 effectors from twelvePstraces or isolates, aPuccinia striiformisisolate, and onePuccinia striiformisf. sp.hordeiisolate using AlphaFold2. Of these, 8,102 folds were successfully predicted, and we performed sequence- and structure-based annotations of these effectors. These effectors were classified into 410 structure clusters and 1,005 sequence clusters. Sequence lengths varied widely, with a concentration between 101-250 amino acids, and motif analysis revealed the presence of known effector motifs such as [Y/F/W]xC and RxLR. Subcellular localization predictions indicated a predominant cytoplasmic localization, with notable chloroplast and nuclear presence. Clear annotations based on sequence and structure included superoxide dismutase and trehalose-6-phosphate phosphatase. A common feature observed was the formation of similar structures from different sequences. In our study, one of the comparative structural analyses revealed a new structure family with a core structure of four helices, including Pst27791, PstGSRE4, and PstSIE1, which target key wheat immune pathway proteins, impacting the host immune function. Further comparative structural analysis showed similarities betweenPsteffectors and effectors from other pathogens such as AvrSr35, AvrSr50, Zt-KP4-1, and MoHrip2, highlighting convergent evolutionary strategies. This comprehensive analysis provides novel insights intoPsteffectors’ structural and functional characterization, advancing our understanding ofPstpathogenicity and evolution.Author SummaryStripe rust, caused by the fungusPuccinia striiformisf. sp.tritici(Pst), is a major threat to wheat crops worldwide. The fungus uses special proteins, called effectors, to bypass the plant’s immune defenses and establish infection. To better understand how these effectors work, we used a computational tool, AlphaFold2, to predict the structures of over 15,000Psteffector proteins. Interestingly, some of the effectors resemble proteins found in other plant pathogens, suggesting that different fungi may evolve similar ways to infect plants. Our research offers new insights into the infection strategies ofPstand could lead to new methods for protecting wheat from stripe rust.
Anin vitromodelling of resolving macrophage with Raw 264.7 macrophage cell line
Authors: Yee Karen Kar Lye , Morooka Nobukatsu , Sato Takashi 
Published: September 2024

AbstractIn acute inflammation, macrophages polarises its phenotype in order to participate effectively in the inflammatory, anti-inflammatory and resolving phases. Particularly, the resolving phase is vital for homeostatic recovery. Thein vivomurine peritonitis model had identified various subtypes of resolving macrophages. However, thein vivomodel has limitations in deciphering the molecular mechanisms required for resolving macrophage polarisation. Therefore the aim of this study is to establish anin vitromodel that could simplify the reproduction of resolving macrophage polarisation. This model will be a useful tool to screen for molecular mechanisms essential for triggering resolution. Ourin vitromodel showed Raw 264.7 cells exhibited classical inflammatory-like (M1-like) phenotype between 2-24 h with increased interleukin-1β expression and tumour necrosis factor-α secretion. Concurrently, at 22-24 h there was an increase in Raw 264.7 cells polarising to anti-inflammatory like (M2-like) phenotype. These M2-like macrophages were increased in arginase activity and interleukin-10 expression. By 48 h, Raw 264.7 cells were polarised to resolving-like (Mres-like/CD11blow) phenotype. These macrophages were characterised by high efferocytic index and a decrease in inflammatory cytokine expression, low arginase activity and low CD11b expression. In summary, thisin vitroresolution model showed resolving-like polarisation in a macrophage cell line.