bluuebunny/crossref_metadata_2025_split huggingface dataset:
Interventions for burnout and well-being in homelessness staff: a systematic scoping review
Authors: Ng L , Adams E , Henderson D , Donaghy E , Mercer SW 
Published: August 2024

AbstractBackgroundHomelessness staff often experience high job demands, limited resources, and significant emotional strains; with high levels of burnout, stress, and trauma being common within the workforce. Despite growing recognition of these issues, limited information exists regarding interventions to address this.AimTo conduct a systematic scoping review of interventions aimed at improving well-being and reducing burnout among homelessness staff.MethodsAll eligible studies needed to include an intervention addressing burnout and/or well-being in homelessness staff, published in English with primary data. Evidence sources were left open with no data restrictions. Following a registered protocol (available at osf.io/jp5yx), a systematic search of five electronic databases (Medline, APA PsychInfo, Global Health, ASSIA, CINAHL) and Google Scholar was conducted. Studies were double-screened for inclusion. Methodological quality was assessed using the Mixed Methods Appraisal Tool.ResultsOut of 5,775 screened studies, six met the inclusion criteria: two peer-reviewed and four non-peer-reviewed publications. No studies were retrieved from Google Scholar. The included studies comprised four quantitative non-randomised designs, one randomised controlled trial, and one mixed-methods study, with four being complex interventions. Three were therapy-based, two included supervision, and two comprised one-time educational sessions. Most were conducted in the United States (n=4), with two in the United Kingdom. The total pooled sample was 347 participants, though four studies were missing demographic data (age and gender). The studies used heterogenous measures and outcomes. Limitations included restrictions to English-only publications, potential gaps in capturing well-being measures, and a limited grey literature scope.ConclusionThere is a lack of research on well-being and burnout interventions in frontline homelessness staff. Identified studies were generally of low quality with a heterogeneity of measures and outcomes used to assess well-being and burnout, limiting generalisability of findings. More robust study designs, along with standardised measures and outcomes, are needed going forwards.
PriMAT: A robust multi-animal tracking model for primates in the wild
Authors: Vogg Richard , Nuske Matthias , Weis Marissa A. , Lüddecke Timo , Karakoç Elif , Ahmed Zurna , Pereira Sofia M. , Malaivijitnond Suchinda , Meesawat Suthirote , Wörgötter Florentin , Kappeler Peter M. , Gail Alexander , Ostner Julia , Schülke Oliver , Fichtel Claudia , Ecker Alexander S. 
Published: August 2024

AbstractDetection and tracking of animals is an important first step for automated behavioral studies in videos. Nowadays, animal tracking is mostly done using deep learning frameworks based on keypoints, which show remarkable results in lab settings with fixed cameras, backgrounds, and lighting. In contrast, multi-animal tracking in the wild is currently underexplored as it presents numerous challenges such as high background variability, lighting conditions, complex motion, and occlusion.We propose a multi-animal tracking model, PriMAT, for nonhuman primates in the wild. The model learns to detect and track primates and other objects of interest from labeled videos or single images using bounding boxes instead of keypoints. Using bounding boxes significantly facilitates data annotation and allows for more robust results. Our one-stage model is conceptually simple but highly flexible, and we add a classification branch that allows us to train individual identification.To evaluate the performance of our model, we applied it in two case studies with Assamese macaques and redfronted lemurs in the wild. We show that with only a few hundred frames labeled with bounding boxes, we can achieve robust tracking results. Combining these results with the classification branch, our model shows an accuracy of 83% in predicting lemur identities.Our approach presents a promising solution for accurately tracking and identifying animals in the wild using deep learning based bounding box tracking, offering researchers a tool to study animal behavior in their natural habitats. Our code, models, training images, and evaluation video sequences are publicly available (https://github.com/ecker-lab/PriMAT-tracking), facilitating its use for animal behavior analyses and future research in this field.
Joint Impacts of Nutrition and Socioeconomic Status on SARS-CoV-2 Antibody Titer in a Prospective Birth Cohort in Brazil
Authors: Vahora Moin , Leão Otávio , da Silveira Mariângela Freitas , Domingues Marlos Rodrigues , Hallal Pedro , Kraay Alicia N.M. 
Published: August 2024

AbstractPurposeIn this study, we examine the joint effects of stunting and socioeconomic status (SES) on COVID-19 serostatus in Brazil and whether these patterns vary by COVID-19 vaccine status.MethodsWe use data from birth through the 7-year follow-up of the Pelotas 2015 birth cohort, including anthropometry, demographics, vaccination status, and COVID-19 antibody test results. We use linear regression models to examine the associations between SES (exposure) and stunting (effect modifier) on COVID-19 antibody titer among children who had not been vaccinated for COVID-19 (n=1,103) and among children who had been vaccinated (n=1,875).ResultsAll SES strata had a statistically identical probability of testing positive. While not statistically significant, stunted children who were unvaccinated tended to have lower COVID-19 titers (difference -0.10, 95% CI: -0.21,0.004) compared with children who were not stunted, and this difference was attenuated among stunted children who were vaccinated. Duration of school enrollment was associated with increased antibody titer, with each month being associated with a 0.17 unit higher increase in OD titer (95% CI: 0.15, 0.18).ConclusionsThis result may suggest that stunted children have poorer immune responses to natural infection and thus lower immunity, but vaccination can overcome this deficit. Future recommendations include population-wide follow-up vaccination, particularly for stunted children. Given increasing antibody titer with a longer duration of school attendance, primary COVID-19 vaccination and potential boosters may be useful for children prior to school entry to reduce the risk of natural infection.
Explainable, federated deep learning model predicts disease progression risk of cutaneous squamous cell carcinoma
Authors: Pisula Juan I. , Helbig Doris , Sancéré Lucas , Persa Oana-Diana , Bürger Corinna , Fröhlich Anne , Lorenz Carina , Bingmann Sandra , Niebel Dennis , Drexler Konstantin , Landsberg Jennifer , Thomas Roman , Bozek Katarzyna , Brägelmann Johannes 
Published: August 2024

AbstractPredicting cancer patient disease progression is a key step towards personalized medicine and secondary prevention. The ability to predict which patients are at an elevated risk of developing local recurrences or metastases would allow for tailored surveillance of these high-risk patients as well as enhanced and timely interventions.We developed a deep learning transformer-based approach for prediction of progression of cutaneous squamous cell carcinoma (cSCC) patients based on diagnostic histopathology slides of the tumor. Our model, trained in a federated manner on patient cohorts from three clinical centers, reached an accuracy of AUROC=0.82, surpassing the predictive power of clinico-pathological parameters used to assess progression risk. We conducted an interpretability analysis, systematically comparing a broad range of spatial and morphological features that characterize tissue regions predictive of patient progression. Our findings suggest that information located at the tumor boundaries is predictive of patient progression and that heterogeneity of tissue morphology and organization are characteristic of progressive cSCCs. Trained in a federated fashion exclusively on standard diagnostic slides obtained during routine care of cSCC patients, our model can be deployed and expanded across other clinical centers. This approach thereby offers a potentially powerful tool for improved screening and thus better clinical management of cSCC patients.
Baseline drug treatments and long-term outcomes in COVID-19-hospitalized patients: results of the 2020 AUTCOV study
Authors: Graf Alexandra Christine , Reichardt Berthold , Wagenlechner Christine , Krotka Pavla , Traxler-Weidenauer Denise , Mildner Michael , Mascherbauer Julia , Aigner Clemens , Auer Johann , Wendt Ralph , Ankersmit Hendrik Jan 
Published: August 2024

AbstractLimited data are available on long-term morbidity and mortality after COVID-19 hospitalization. In this population-based study, we investigated the long-term mortality and morbidity after COVID-19 hospitalization and associations with baseline drug treatments. Data were provided on hospitalized COVID-19 patients in 2020 and matched controls by the Austrian Health Insurance Funds. The primary outcome was all-cause mortality. Secondary outcomes were all-cause mortality conditional on COVID-hospital survival and re-hospitalization due to any reason. The median follow-up was 600 days. 22 571 patients aged >18 years were hospitalized in Austria in 2020 due to COVID-19. The risk of all-cause mortality was significantly higher with polypharmacy. With the exception of the youngest age group (19-40 years), antiepileptics, antipsychotics and the medicament group of iron supplements, erythropoietic stimulating agents, Vitamin B12, and folic acid were significantly associated with a higher risk of death (all p<0,001). For Non-steroidal anti-inflammatory drugs and other anti-inflammatory drugs, significantly increased survival was observed (all p<0,001). Patients had a higher drug prescription load than the control population. Long-term mortality and the risk of re-hospitalization due to any reason were also significantly greater in the patients. Antipsychotics are assumed to be an underrecognized medication group linked to worse outcomes after COVID-19 hospitalization.
Lung functions among children and adolescents with sickle cell disease receiving care at Jaramogi Oginga Odinga Teaching and Referral Hospital Kisumu, Kenya
Authors: Olewe Fredrick O. , Tenge Constance N. , Marete Irene K. 
Published: August 2024

AbstractSickle cell disease is a genetic disorder associated with lifelong symptoms of anemia, vaso-oclusive crisis and organ damage. Pulmonary complications and declining lung functions are contributors to morbidity and mortality. Determination of lung functions can enable early diagnosis and institution of appropriate intervention.The objectives were; To determine the prevalence, patterns, and the factors associated with abnormal lung functions in children and adolescents aged 6-17 years with confirmed diagnosis Sickle Cell Disease.This was a cross sectional study done at Jaramogi Oginga Odinga Teaching and Referral Hospital in Kisumu, Kenya. A total of 138 participants were recruited. A structured data collection tool was used to collect Socio-demographics and clinical characteristics. The spirometry was done using NDD Easy-On PC spirometer and results entered into database, cleaned and analyzed for proportions, frequency, mean, range and odds ratio at 95% confidence level.Females were 65(47%), males 73(53%), and the mean age was 10.99 years with SD of 3.15. A total of 79(57%) were from rural and fuel used was fired wood 41%. Hospital admission were 84(61%), vaso-oclusive crisis 104 (75%), acute chest syndrome 61(44%) and blood transfusions 56(40%) in the last 12 months. Prevalence of abnormal lung functions was 28 % (39), restrictive pattern 26(67%) and obstructive pattern 13(33%). Urban setting (OR 24.101 p value 0.163), being female (OR 18.911 p value 0.069), and blood transfusion (OR 11.683 p value 0.195) had high odds ratio while, stable hydroxyurea use (OR 0.525 p value 0.678) and hospital admission (OR 0.048 p value 0.121) had low odds ratio, but not statistically significant.One third had abnormal lung function mostly restrictive followed by obstructive pattern. Residence in urban setting, being female and blood transfusion had high odds ratio, while stable hydroxyurea use and hospital admission had low odds ratio but no statistically significant.
Comparison of Peripheral Nerve Injury Outcomes Between COVID-19 Survivors and Non-COVID Rehabilitation Inpatients: A Retrospective Study
Authors: Mondríguez-González Antonio , Rothemich Brian M. , Sheth Manasi , Swong Kevin N. , Franz Colin K. 
Published: August 2024

AbstractIntroductionPeripheral nerve injury (PNI) is associated with severe Coronavirus disease 2019 (COVID-19) survivorship. The diagnosis of PNI is often made by a physiatrist during a detailed functional assessment during an inpatient rehabilitation stay. COVID-19 patients have elevated rates of medical comorbidities, including risk factors for acquired PNI, such as diabetes mellitus and obesity. It is not known if the functional prognosis from PNI in COVID-19 survivors differs substantially from PNI in other inpatient rehabilitation populations.ObjectiveTo determine the prognosis of PNI associated with severe COVID-19 survivorship and compare it to PNI associated with other inpatient rehabilitation populations.DesignRetrospective chart review study.SettingSingle-center inpatient rehabilitation hospital in a large urban city.PatientsAdult patients admitted to an inpatient rehabilitation hospital with PNI(s).InterventionsNot applicable.Main Outcome MeasuresThe primary outcome was the change in manual muscle testing (MMT) over time. Secondary outcomes included the rate of peripheral nerve surgery and the number of distinct PNI sites per patient.ResultsThe analysis consisted of 60 subjects with PNI. We identified 30 subjects who had PNI associated with COVID-19 and were matched with 30 subjects with PNI not associated with COVID-19 who were diagnosed during their inpatient rehabilitation admission. The data collected included basic demographics, COVID-19 status immediately before inpatient rehabilitation admission, medical comorbidities, acute rehabilitation inpatient diagnosis, nerve injury location and mechanism of injury, muscles affected, and change in serial MMT, plus documentation of any surgical intervention. No significant difference was found between the improvement of MMT, surgery rate, or number of nerve injuries and COVID-19 status.ConclusionPNIs associated with severe COVID-19 survivorship have similar recovery patterns as those of other etiologies. This data is reassuring that PNI associated with COVID-19 may be managed similarly to other types of PNI.
SERS Analysis Of Sialic Acid In Single Dendritic Cells Within The Tumor Microenvironment
Authors: Li Xingrui , Ma Lingling , Yang Xiaofei , Wang Nian , Bai Shiyu , Zhao Qiongzhen , Yang Yu , Huang Weidong , Su Zhengding , Li Jinyao 
Published: August 2024

AbstractThe crucial role of Dendritic Cells (DCs) in anti-tumor immune responses depends on surface Sialic Acid (SA). The regulation of DC surface sialic acid in the Tumor Microenvironment (TME) remains underexplored. Current methods struggle to provide highly sensitive, multiplex analyses of SA and other immune protein changes in single DCs within the tumor microenvironment. Here, we employed a SERS tags method for specific and highly sensitive analysis of SA, MHCII, CD86, and CD40 in DCs using a single DC analysis microfluidic platform. We also explored the differential regulatory effects of various immune-modulating drugs and tumor supernatant on multiple immunophenotypes of DCs in different immune states. The expanded two-cell microfluidic system further allows for phenotypic analysis of DCs at different time points within the tumor microenvironment. Given this method enables highly sensitive single-cell analysis of DCs, further development of this technology for tumor microenvironment applications will aid in deeply understanding the tumor-induced suppression of DC immune function, providing valuable insights for DC-mediated tumor immunotherapy research.
SOI: Robust identification of orthologous synteny with theOrthology Indexand broad applications in evolutionary genomics
Authors: Zhang Ren-Gang , Shang Hong-Yun , Milne Richard Ian , Almeida-Silva Fabricio , Chen Hengchi , Zhou Min-Jie , Shu Heng , Jia Kai-Hua , Van de Peer Yves , Ma Yong-Peng 
Published: August 2024

AbstractWith the explosive growth of whole-genome datasets, the accurate detection of orthologous synteny has become crucial for the reconstruction of evolutionary history. However, the currently available methods for the identification of orthologous synteny have great limitations: the methods are difficult to scale with varying polyploidy histories, and the accurate removal of out-paralogy is challenging. In this study, we developed a scalable and robust approach, theOrthology Index(OI), to identify orthologous synteny. Our evaluation of a large-scale dataset with diverse polyploidization events demonstrated that the technique is highly reliable. This discovery highlightsOIas a potentially unified criterion for the identification of orthologous synteny, and this is further validated using simulation-based benchmarks. In addition, we explore its broad applications in reconstructing the evolutionary histories of plant genomes, including inference of polyploidy, identification of reticulation, and phylogenomics. In conclusion,OIoffers a robust, interpretable, and scalable approach for identifying orthologous synteny, significantly enhancing our analytical prowess in plant evolutionary genomics.
Sensitive and modular amplicon sequencing ofPlasmodium falciparumdiversity and resistance for research and public health
Authors: Aranda-Díaz Andrés , Vickers Eric Neubauer , Murie Kathryn , Palmer Brian , Hathaway Nicholas , Gerlovina Inna , Boene Simone , Garcia-Ulloa Manuel , Cisteró Pau , Katairo Thomas , Semakuba Francis Ddumba , Nsengimaana Bienvenu , Gwarinda Hazel , García-Fernández Carla , Louie William , Esayas Endashaw , Silva Clemente Da , Datta Debayan , Kiyaga Shahiid , Wiringilimaana Innocent , Fekele Sindew Mekasha , Bennett Adam , Smith Jennifer L. , Gadisa Endalamaw , Parr Jonathan B. , Conrad Melissa , Raman Jaishree , Tukwasibwe Stephen , Ssewanyana Isaac , Rovira-Vallbona Eduard , Tato Cristina M. , Briggs Jessica , Mayor Alfredo , Greenhouse Bryan 
Published: August 2024

AbstractBackgroundTargeted amplicon sequencing is a powerful and efficient tool for interrogating thePlasmodium falciparumgenome, generating actionable data from infections to complement traditional malaria epidemiology. For maximum impact, genomic tools should be multi-purpose, robust, sensitive, and reproducible.MethodsWe developed, characterized, and implemented MAD4HatTeR, an amplicon sequencing panel based on Multiplex Amplicons for Drug, Diagnostic, Diversity, and Differentiation Haplotypes using Targeted Resequencing, along with a bioinformatic pipeline for data analysis. Additionally, we introduce an analytical approach to detect gene duplications and deletions from amplicon sequencing data. Laboratory control and field samples were used to demonstrate the panel’s high sensitivity and robustness.ResultsMAD4HatTeR targets 165 highly diverse loci, focusing on multiallelic microhaplotypes, key markers for drug and diagnostic resistance (including duplications and deletions), andcspand potential vaccine targets. The panel can also detect non-falciparum Plasmodiumspecies. MAD4HatTeR successfully generated data from low-parasite-density dried blood spot and mosquito midgut samples, and detected minor alleles at within-sample allele frequencies as low as 1% with high specificity in high-parasite-density dried blood spot samples. Gene deletions and duplications were reliably detected in mono- and polyclonal controls. Data generated by MAD4HatTeR were highly reproducible across multiple laboratories.ConclusionsThe successful implementation of MAD4HatTeR in five laboratories, including three in malaria-endemic African countries, showcases its feasibility and reproducibility in diverse settings. MAD4HatTeR is thus a powerful tool for research and a robust resource for malaria public health surveillance and control.
Deconvolution of cancer methylation patterns determines that altered methylation in cancer is dominated by a non-disease associated proliferation signal
Authors: Lalchungnunga H , Atasoy H , Schwalbe EC , Bacon CM , Strathdee G 
Published: August 2024

AbstractAll cancers are associated with massive reorganisation of cellular epigenetic patterns, including extensive changes in the genomic patterns of DNA methylation. However, the huge scale of these changes has made it very challenging to identify key DNA methylation changes responsible for driving cancer development. Here, we present a novel approach to address this problem called methylation mapping. Through comparison of multiple types of B-lymphocyte derived malignancies and normal cell populations, this approach can define the origins of methylation changes as proliferation-driven, differentiation-driven and disease-driven (including both cancer-specific changes and cancer absent changes). Each of these categories of methylation change were found to occur at genomic regions that vary in sequence context, chromatin structure and associated transcription factors, implying underlying mechanistic differences behind the acquisition of methylation at each category. This analysis determined that only a very small fraction (about 3%) of DNA methylation changes in B-cell cancers are disease related, with the overwhelming majority (97%) being driven by normal biological processes, predominantly cell proliferation. Furthermore, the low level of true disease-specific changes can potentially simplify identification of functionally relevant DNA methylation changes, allowing identification of previously unappreciated candidate drivers of cancer development, as illustrated here by the identification and functional confirmation ofSLC22A15as a novel tumour suppressor candidate in acute lymphoblastic leukaemia. Overall, this approach should lead to a clearer understanding of the role of altered DNA methylation in cancer development, facilitate the identification of DNA methylation targeted genes with genuine functional roles in cancer development and thus identify novel therapeutic targets.