bluuebunny/crossref_metadata_2025 huggingface dataset:
Genomic loci for sclerotinia stem rot resistance and chlorophyll stability inBrassica napus: integrating GWAS with microbiome insights
Authors: Chawade Aakash , Thuraga Vishnukiran , Sepp Siim Samuel , Ghosh Samrat , Ghadamgahi Farideh , Odilbekov Firuz , Muthusamy Saraladevi , Vetukuri Ramesh R , Abreha Kibrom B.
Published: August 2024

Sclerotinia Stem Rot (SSR) disease is one of the most serious diseases affecting the yield and quality of oilseed rape (Brassica napus). Understanding the genetic basis of the resistance trait in oilseed rape to SSR and microbiome composition for enhanced resistance is crucial for developing resistant varieties and sustainably mitigate the impact of the disease. In this study, in a panel of 168 oilseed rape accessions, most resistant (NGB 13503 and NGB 13834) and susceptible (NGB 13497 and NGB 13897) accessions are identified. A Genome-wide association study (GWAS) identified 47 SNPs linked to the SSR lesion length, lesion area, and lesion relative to the leaf area. Among the SNPs significantly linked to lesion length were Bn-A04-p10555408, Bn-A07-p12487549, Bn-A09-p4652268, Bn-A09-p4916858 and to our knowledge, these SNPs have not been previously linked to SSR resistance in oilseed rape. Moreover, the study identified 24 SNPs linked with chlorophyll content before SSR inoculation (SPADH), after the SSR inoculation (SPADI), and chlorophyll index (CI). Maintaining the chlorophyll level is correlated with the SSR resistance. Furthermore, bacterial taxa (e.g.Pseudomonas,Methylobacterium, andAquabacterium) and fungal taxa (e.g.Mycosphaerellales,Thelebolales, andAkanthomyces) were enriched in the resistant compared to in the susceptible oilseed rape accessions. The SNPs linked to lesion length showed consistent haplotype variation between these selected accessions. Given the absence of complete resistance against SSR, the study provides insights into the significance of maintaining chlorophyll levels and considering microbiome composition for enhancing the level of existing partial resistance to SSR in oilseed rape.
APPROACHES TO DIMENSIONALITY REDUCTION FOR ULTRA-HIGH DIMENSIONAL MODELS
Authors: Kotlarz Krzysztof , Słomian Dawid , Szyda Joanna
Published: August 2024

The rapid advancement of high-throughput sequencing technologies has revolutionised genomic research by providing access to large amounts of genomic data. However, the most important disadvantage of using Whole Genome Sequencing (WGS) data is its statistical nature, the so-called p>>n problem. This study aimed to compare three approaches of feature selection allowing for circumventing the p>>n problem, among which one is a novel modification of Supervised Rank Aggregation (SRA). The use of the three methods was demonstrated in the classification of 1,825 individuals representing the 1000 Bull Genomes Project to 5 breeds, based on 11,915,233 SNP genotypes from WGS. In the first step, we applied three feature (i.e. SNP) selection methods: the mechanistic approach(SNP tagging)and two approaches considering biological and statistical contexts by fitting a multiclass logistic regression model followed by either 1-dimensional clustering(1D-SRA)or multi-dimensional feature clustering(MD-SRA)that was originally proposed in this study. Next, we perform the classification based on a Deep Learning architecture composed of Convolutional Neural Networks. The classification quality of the test data set was expressed by macro F1-Score. The SNPs selected bySNP taggingyielded the least satisfactory results (86.87%). Still, this approach offered rapid computing times by focussing only on pairwise LD between SNPs and disregarding the effects of SNP on classification.1D-SRAwas less suitable for ultra-high-dimensional applications due to computational, memory and storage limitations, however, the SNP set selected by this approach provided the best classification quality (96.81%).MD-SRAprovided a very good balance between classification quality (95.12%) and computational efficiency (17x lower analysis time and 14x lower data storage), outperforming other methods. Moreover, unlikeSNP tagging, both SRA-based approaches are universal and not limited to feature selection for genomic data. Our work addresses the urgent need for computational techniques that are both effective and efficient in the analysis and interpretation of large-scale genomic datasets. We offer a model suitable for the classification of ultra-high-dimensional data that implements fusing feature selection and deep learning techniques.
Plasma Membrane Remodelling in GM2 Gangliosidoses Drives Synaptic Dysfunction
Authors: Nicholson Alex S. , Priestman David A. , Antrobus Robin , Williamson James C. , Bush Reuben , Barrow Henry G. , Smith Emily , Dobrenis Kostantin , Bright Nicholas A. , Platt Frances M. , Deane Janet E.
Published: August 2024

Glycosphingolipids (GSL) are important bioactive components of cellular membranes. Complex GSLs, containing sialic acid residues are known as gangliosides and are highly abundant in the brain. Diseases of ganglioside metabolism often result in severe, early-onset neurodegeneration. The ganglioside GM2 is the substrate of the hydrolytic lysosomal β- hexosaminidase A (HexA) enzyme and when subunits of this enzyme are non-functional, GM2 lipid accumulates in cells leading to the GM2 gangliosidoses, Tay-Sachs and Sandhoff diseases. We have developed high-quality i3Neuron-based models of Tay-Sachs and Sandhoff diseases, that demonstrate storage of GM2, formation of membrane whorls and accumulation of endolysosomal proteins consistent with disease phenotypes. Importantly, in addition to lysosomal dysfunction, the composition of the plasma membrane (PM) is significantly impacted in these diseases with changes in the abundance of both lipids and proteins. The changes to the PM proteome are driven in part by exocytosis of lysosomal material resulting in the aberrant accumulation of lysosomal proteins and lipids on the cell surface. The altered abundance of GM2 at the PM was striking, bringing the abundance of this precursor lipid up to that of the common neuronal gangliosides. Furthermore, the PM profiling identifies significant changes in synaptic protein abundances with direct functional impact on neuronal activity including rapid electrical firing consistent with neuronal hyperactivity. This work provides mechanistic insights into neuronal dysfunction in the GM2 gangliosidoses and highlights that these are also severe PM disorders. This work has broad implications for other lysosomal storage disorders and late-onset neurodegenerative diseases involving sphingolipid dysregulation.
Temperate phage-antibiotic synergy is widespread, but varies by phage, host, and antibiotic pairing
Authors: Fatima Rabia , Hynes Alexander P.
Published: August 2024

With a decline in antibiotic effectiveness, there is a renewed interest in bacteriophage (phage) therapy. Phages are bacterial-specific viruses that can be used alone or with antibiotics to reduce bacterial load. Most phages are unsuitable for therapy because they are ‘temperate’ and can integrate into the host genome, forming a lysogen which is protected from subsequent phage infections. However, integrated phages can be awakened by stressors such as antibiotics. This interaction was previously reported to result in a potent synergy between antibiotic classes and a modelE. colitemperate phage, which can readily eradicate the bacterium at sub-lethal concentrations of antibiotics, despite the poor effectiveness of the phage alone. Here we explore the generalizability of this synergy to a clinically relevant pathogen:Pseudomonas aeruginosa. Thirty-six temperate phages isolated from clinical strains were screened for synergy with six antibiotics (ciprofloxacin, levofloxacin, meropenem, piperacillin, tobramycin, polymyxin B), using checkerboard assays. Interestingly, our screen identified phages that can synergize with each antibiotic, despite their widely differing targets - however, these are highly phage-antibiotic and phage-host pairing specific. Screening the strongest pairings across multiple clinical strains reveal that these phages can reduce the antibiotic minimum inhibitory concentration up to 32-fold, even in a resistant isolate, functionally re-sensitizing the bacterium to the antibiotic. When meropenem and tobramycin were effective synergistic agents, they did not reduce the frequency of lysogens, suggesting a mechanism of action independent of the temperate nature of the phages. In contrast, ciprofloxacin and piperacillin were able to reduce the frequency of lysogeny, the former by inducing phages – as previously reported inE. coli. Curiously, synergy with piperacillin reduced the frequency of lysogeny, but not by inducing the phages, and therefore likely acts by biasing the phage away from lysogeny in the initial infection. Overall, our findings indicate that temperate phages can act as adjuvants to antibiotics in clinically relevant pathogens, even in the presence of antibiotic resistance, thereby drastically expanding their therapeutic potential.
Severe deviation in protein fold prediction by advanced AI: a case study
Authors: López-Sagaseta Jacinto , Urdiciain Alejandro
Published: August 2024

Artificial intelligence (AI) and deep learning are making groundbreaking strides in protein structure prediction. AlphaFold is remarkable in this arena for its outstanding accuracy in modelling proteins fold based solely on their amino acid sequences. In spite of these remarkable advances, experimental structure determination remains critical. Here we report severe deviations (>30 Å) between the experimental structure of a two-domain protein and its equivalent AI-prediction. These observations are particularly relevant to the relative orientation of the domains within the global protein scaffold. Significant divergence between experimental structures and AI-predicted models echoes the presence of unusual conformations, insufficient training data and high complexity in protein folding that can ultimately lead to current limitations in protein structure prediction.
Re-evaluating the relationship between female social bonds and infant survival in wild baboons
Authors: Creighton Maria J.A. , Lerch Brian A. , Lange Elizabeth C. , Silk Joan B. , Tung Jenny , Archie Elizabeth A. , Alberts Susan C.
Published: August 2024

Over the past few decades studies have provided strong evidence that the robust links between the social environment, health, and survival found in humans also extend to non-human social animals. A number of these studies emphasize the early life origins of these effects. For example, in several social mammals, more socially engaged mothers have infants with higher rates of survival compared to less socially engaged mothers, suggesting that positive maternal social relationships causally improve offspring survival. Here we show that the relationship between infant survival and maternal sociality is confounded by previously underappreciated variation in female social behavior linked to changes in reproductive state and the presence of a live infant. Using data from a population of wild baboons living in the Amboseli basin of Kenya – a population where high levels of maternal sociality have previously been linked to improved infant survival – we find that infant- and reproductive state-dependent changes in female social behavior drive a statistically significant relationship between maternal sociality and infant survival. After accounting for these state-dependent changes in social behavior, maternal sociality is no longer positively associated with infant survival in this population. Our results emphasize the importance of considering multiple explanatory pathways—including third-variable effects—when studying the social determinants of health in natural populations.
Archaic introgression and the distribution of shared variation under stabilizing selection
Authors: Ragsdale Aaron P.
Published: August 2024

Many phenotypic traits are under stabilizing selection, which maintains a population’s mean phenotypic value near some optimum. The dynamics of traits and trait architectures under stabilizing selection have been extensively studied for single populations at steady state. However, natural populations are seldom at steady state and are often structured in some way. Admixture and introgression events may be common, including over human evolutionary history. Because stabilizing selection results in selection against the minor allele at a trait-affecting locus, alleles from the minor parental ancestry will be selected against after admixture. We show that the site-frequency spectrum can be used to model the genetic architecture of such traits, allowing for the study of trait architecture dynamics in complex multi-population settings. We use a simple deterministic two-locus model to predict the reduction of introgressed ancestry around trait-contributing loci. From this and individual-based simulations, we show that introgressed-ancestry deserts are enriched around such loci. When introgression between two diverged populations occurs in both directions, as has been inferred between humans and Neanderthals, the locations of introgressed-ancestry deserts will tend to be shared across populations. We argue that stabilizing selection for shared phenotypic optima may explain recent observations in which regions of depleted human-introgressed ancestry in the Neanderthal genome overlap with Neanderthal-ancestry deserts in humans.
PHeP: TrustAlert Open-Source Platform for Enhancing Predictive Healthcare with Deep Learning
Authors: Contaldo Sandro Gepiro , Pietropaolo Emanuele , Bosio Lorenzo , Pernice Simone , Terrone Irene , Baccega Daniele , Wang Yuting , Sahoo Rahul Kumar , Rizzo Giuseppe , Visconti Alessia , Berchialla Paola , Beccuti Marco
Published: August 2024

Predictive healthcare, a field revolutionized by the availability of large medical datasets and computational advancements, plays a pivotal role in enhancing patient care and healthcare system performance. Despite its significance, the training and deployment of predictive healthcare models present substantial challenges. To address these, we introduce the Predictive Healthcare Platform (PHeP), an open-source platform that simplifies the use of pretrained models. PHeP, developed under the TrustAlert project, offers an intuitive web-based graphical interface, making advanced predictive healthcare accessible to users without extensive computational skills or expensive computational resources. This paper presents the design and functionality of PHeP, demonstrating its effectiveness in predictive healthcare tasks, such as predicting re-hospitalization at three months using pre-trained BERT models.
Examining the impact of outdoor walk group attendance on health among older adults with mobility limitations in the Getting Older Adults Outdoors (GO-OUT) randomized trial
Authors: Su Tai-Te , Barclay Ruth , Moineddin Rahim , Salbach Nancy M.
Published: August 2024

Objective

The Getting Older Adults Outdoors randomized trial showed a 10-week outdoor walk group (OWG) program was not superior to 10 weekly phone reminders on increasing physical and mental health; however, OWG attendance varied. This study examined whether a dose-response relationship existed between OWG attendance and improvement in physical and mental health among older adults with mobility limitations.

Methods

We analyzed data from 98 older adults randomized to a 10-week park-based OWG program. Participants were classified as attending 0–9, 10–15, and 16–20 OWG sessions based on attendance tertiles. Outcomes included change in scores on measures of walking endurance, comfortable and fast walking speed, balance, lower extremity strength, walking self-efficacy, and emotional well-being pre- to post-intervention.

Results

Seventy-nine older adults with complete information on the seven health outcomes were included (age=74.7±6.6 years, 72% female). Compared to those who attended 0–9 OWG sessions, participants attending 16–20 sessions exhibited a 52.7-meter greater improvement in walking endurance (95% CI:12.3, 93.1); 0.15-meter/second greater improvement in comfortable walking speed (95% CI:0.00, 0.29); and 0.17-meter/second greater improvement in fast walking speed (95% CI:0.02, 0.33). Higher attendance was also associated with higher odds of experiencing an improvement in walking self-efficacy (OR=4.03; 95% CI:1.05, 16.85) and fast walking speed (OR=9.00, 95% CI:1.59, 61.73). No significant dose-response relationships for balance, lower extremity strength, and emotional well-being were observed.

Conclusions

Higher attendance in outdoor walking interventions is associated with greater improvements in walking endurance, walking speed, and walking self-efficacy among older adults with mobility limitations.
Evaluating Anti-LGBTQIA+ Medical Bias in Large Language Models
Authors: Chang Crystal T. , Srivathsa Neha , Bou-Khalil Charbel , Swaminathan Akshay , Lunn Mitchell R. , Mishra Kavita , Daneshjou Roxana , Koyejo Sanmi
Published: August 2024

From drafting responses to patient messages to clinical decision support to patient-facing educational chatbots, Large Language Models (LLMs) present many opportunities for use in clinical situations. In these applications, we must consider potential harms to minoritized groups through the propagation of medical misinformation or previously-held misconceptions. In this work, we evaluate the potential of LLMs to propagate anti-LGBTQIA+ medical bias and misinformation. We prompted 4 LLMs (Gemini 1.5 Flash, Claude 3 Haiku, GPT-4o, Stanford Medicine Secure GPT (GPT-4.0)) with a set of 38 prompts consisting of explicit questions and synthetic clinical notes created by medically trained reviewers and LGBTQIA+ health experts. The prompts explored clinical situations across two axes: (i) situations where historical bias has been observed vs. not observed, and (ii) situations where LGBTQIA+ identity is relevant to clinical care vs. not relevant. Medically trained reviewers evaluated LLM responses for appropriateness (safety, privacy, hallucination/accuracy, and bias) and clinical utility. We find that all 4 LLMs evaluated generated inappropriate responses to our prompt set. LLM performance is strongly hampered by learned anti-LGBTQIA+ bias and over-reliance on the mentioned conditions in prompts. Given these results, future work should focus on tailoring output formats according to stated use cases, decreasing sycophancy and reliance on extraneous information in the prompt, and improving accuracy and decreasing bias for LGBTQIA+ patients and care providers.
The chloroplast located HKT transporter plays an important role in sporophyte development inPhyscomitrium patens
Authors: Yanez-Dominguez Carolina , Macedo-Osorio Karla , Lagunas-Gomez Daniel , Torres-CIfuentes Diana , Castillo-Gonzalez Juan , Zavala Guadalupe , Pantoja Omar
Published: August 2024

Cell survival depends on the maintenance of cell homeostasis that involves all the biochemical, genomic and transport processes that take place in all the organelles within an eukaryote cell. In particular, ion homeostasis is required to regulate the membrane potential and solute transport across all membranes, any alteration in these parameters will reflect in the malfunctioning of any organelle. In plant cells, sodium transporters play a central role in keeping the concentrations of this cation across all membranes under physiological conditions to prevent its toxic effects. HKT transporters are a family of membrane proteins exclusively present in plants, with some homologs being present in prokaryotes. HKT transporters have been associated to salt tolerance in plants, retrieving any leak of the cation into the xylem, or removing it from aerial parts to be transported to the roots along the phloem. This function has been assigned as most of the HKT transporters are located at the plasma membrane. Here, we report the localization of the moss HKT fromPhyscomitrium patensto the thylakoid membrane, and its mutation that leads to several alterations in the phenotype of the organism, together with the changes in expression of close to 1000 genes. Down regulation of photosynthesis related genes and the upregulation of glycolysis/respiration and ion transport genes help to explain the observed phenotype.
Gasdermin D deficiency attenuates development of ascending aortic dissections in a novel mouse model
Authors: Javed Muhammad J. , Howard Rachael M. , Li Hua , Carrasco Laura , Dirain Marvin L.S , Su Gang , Cai Guoshuai , Upchurch Gilbert R. , Jiang Zhihua
Published: August 2024

Background

Thoracic aortic dissection (TAD) is a silent killer. Approximately two-thirds of the cases occur in the ascending aorta (i.e. type A dissection) and majority of them are unrelated to genetic mutations. However, animal models of spontaneous type A dissection are not widely available. In the present study, a novel mouse TAD model was created. Further, the role of gasdermin D (GSDMD) in TAD development was evaluated.

Methods

TADs were created by treating ascending aorta of adult mice (C57BL/6J) with active elastase (40.0 U/ml) and β-aminopropionitrile (Act E+BAPN). The temporal progress of the TAD pathology was rigorously characterized by histological evaluation and scanning electron microscopy, while potential mechanisms explored with bulk RNA sequencing of specimens collected at multiple timepoints. With this novel TAD model, further experiments were performed with Gsdmd−/−mice to evaluate its impact on TAD formation.

Results

The ascending aorta challenged with Act E+BAPN developed pathology characterized by an early onset of intimomedial tears (complete penetration) and intramural hematoma, followed by progressive medial loss and aortic dilation. Ingenuity Pathway Analysis and functional annotation of differentially expressed genes suggested that a unique inflammatory micro-environment, rather than general inflammation, promoted the onset of TADs by specifically recruiting neutrophils to the aortic wall, while the pathology at the advanced stage was driven by T-cell mediated immune injury. Gsdmd−/−attenuated medial loss, adventitial fibrosis, and dilation of TADs. This protective effect was associated with a reduced number of TUNEL (terminal deoxynucleotidyl transferase dUTP nick end labeling) positive cells and T-cells in TADs.

Conclusions

A novel mouse TAD model was created in the ascending aorta. It produces a unique microenvironment to activate different immune cell subsets, promoting onset and subsequent remodeling of TADs. Consistently, Gsdmd−/−attenuates TAD development, with modulation of cell death and T-cell response likely acting as the underlying mechanism.

Graphical Abstract
Adoption of the OMOP CDM for Cancer Research using Real-world Data: Current Status and Opportunities
Authors: Wang Liwei , Wen Andrew , Fu Sunyang , Ruan Xiaoyang , Huang Ming , Li Rui , Lu Qiuhao , Williams Andrew , Liu Hongfang
Published: August 2024

Background: The Observational Medical Outcomes Partnership (OMOP) common data model (CDM) that is developed and maintained by the Observational Health Data Sciences and Informatics (OHDSI) community supports large scale cancer research by enabling distributed network analysis. As the number of studies using the OMOP CDM for cancer research increases, there is a growing need for an overview of the scope of cancer research that relies on the OMOP CDM ecosystem. Objectives: In this study, we present a comprehensive review of the adoption of the OMOP CDM for cancer research and offer some insights on opportunities in leveraging the OMOP CDM ecosystem for advancing cancer research. Materials and Methods: Published literature databases were searched to retrieve OMOP CDM and cancer-related English language articles published between January 2010 and December 2023. A charting form was developed for two main themes, i.e., clinically focused data analysis studies and infrastructure development studies in the cancer domain. Results: In total, 50 unique articles were included, with 30 for the data analysis theme and 23 for the infrastructure theme, with 3 articles belonging to both themes. The topics covered by the existing body of research was depicted. Conclusion: Through depicting the status quo of research efforts to improve or leverage the potential of the OMOP CDM ecosystem for advancing cancer research, we identify challenges and opportunities surrounding data analysis and infrastructure including data quality, advanced analytics methodology adoption, in-depth phenotypic data inclusion through NLP, and multisite evaluation.
Multi-omic and functional screening reveal targetable vulnerabilities inTP53mutated multiple myeloma
Authors: Tsallos Dimitrios , Ikonen Nemo , Miettinen Juho J. , Majumder Muntasir Mamun , Eldfors Samuli , Västrik Imre , Parsons Alun , Suvela Minna , Dunphy Katie , Dowling Paul , Bazou Despina , O’Gorman Peter , Lievonen Juha , Silvennoinen Raija , Anttila Pekka , Heckman Caroline A.
Published: August 2024

Despite development of several effective therapies for multiple myeloma (MM), the prognosis of patients with partial deletion of chromosome 17 (del(17p)) andTP53aberrations remains poor. By applying comprehensive multi-omics profiling analyses (whole exome and transcriptome sequencing plus proteomics) and functionalex vivodrug screening to samples from 167 patients with MM, we uncovered novel therapeutic vulnerabilities specific toTP53mutated MM. Our findings revealed a distinct sensitivity profile to a range of inhibitors (mitotic, topoisomerase, HDAC, HSP90, IGF1R and PI3K/AKT/mTOR inhibitors) irrespective of 17p deletion status. Conversely, no increase in sensitivity was observed for monoallelicTP53(del(17p) with WTTP53) when compared to WTTP53samples, highlighting the remaining unmet clinical need. Notably, plicamycin, an RNA synthesis inhibitor linked to modulation of chromatin structure and increased transcription, emerged as particularly efficacious forTP53mutated MM. The increased sensitivity correlated with higher protein expression of the drug targets: HDAC2, HSP90AA1 and multiple ribosomal subunits. Additionally, we observed increased RNA expression of G2M checkpoint, E2F targets and mTORC1 signaling in our cohort and the MMRF-CoMMpass (NCT01454297) study inTP53mutated MM. Harmonization of multi-omics data withex vivodrug screening results revealed thatTP53mutated MM is functionally distinct from MM with monoallelicTP53, and demonstrates that MM with mutatedTP53, with and without del(17p), may be targetable by approved drugs. These results further indicate the need for regular monitoring by sequencing to identify these patients.

KEY POINTS

TP53mutation in myeloma confers sensitivity to multiple compounds, including approved drugs, irrespective of del(17p) status.

TP53mutated myeloma links to higher expression of drug targets involved in cell proliferation, mRNA processing, and chromatin modulation.
Motor and Nonmotor Features of p.A53T Alpha-Synuclein PD vs idiopathic PD: Longitudinal Data from the PPMI Study.
Authors: Simitsi Athina Maria , Sfikas Evangelos , Koros Christos , Papagiannakis Nikolaos , Beratis Ion , Papadimitriou Dimitra , Antonelou Roubina , Fragkiadaki Styliani , Kontaxopoulou Dionysia , Picillo Marina , Pachi Ioanna , Alefanti Ioanna , Stamelou Maria , Barone Paolo , Stefanis Leonidas
Published: August 2024

Background and Objectives: The phenotype of p.A53T-SNCA Parkinson's Disease (PD) mutation carriers appears more severe than that of iPD patients, however comprehensive comparative prospective studies are lacking. Here we conducted a longitudinal study to investigate, using multiple parameters, the progression of motor and nonmotor features of p.A53T-PD compared to iPD. Methods: Longitudinal 3-year data, concerning both motor and non-motor features, of 16 p.A53T-PD and 48 iPD, matched for age and disease duration at baseline, were downloaded from the Parkinson's Progression Markers Initiative (PPMI) database and compared between the two groups. Additionally, a cognitive composite score was generated by 5 cognitive tests, focused on executive/visuospatial function to better study cognitive change. Results: Neuropsychological assessments of global cognitive (MOCA), and especially executive/visuospatial function, reflected in the composite score, revealed significant cognitive decline in A53T-PD compared to iPD, but also across time for the group of A53T-PD. Autonomic dysfunction and items of MDS-UPDRS I, reflecting global cognitive function and psychotic features, were more prominent in A53T-PD. Motor assessments showed worse performance in A53T-PD, even though LEDD was significantly higher in A53T-PD. Discussion: The current longitudinal study indicates that A53T-PD represents a rapidly progressing subtype of PD, with accelerated decline in both motor and non-motor parameters, especially in cognitive function. Such data may set the stage for the application of targeted disease-modifying therapies in this particular subtype, in which the etiological link to alpha-synuclein is established, while generated data may be relevant to iPD, which is largely a sporadic synucleinopathy.
Generative AI Enables Medical Image Segmentation in Ultra Low-Data Regimes
Authors: Zhang Li , Jindal Basu , Alaa Ahmed , Weinreb Robert , Wilson David , Segal Eran , Zou James , Xie Pengtao
Published: August 2024

Semantic segmentation of medical images is pivotal in applications like disease diagnosis and treatment planning. While deep learning has excelled in automating this task, a major hurdle is the need for numerous annotated segmentation masks, which are resource-intensive to produce due to the required expertise and time. This scenario often leads to ultra low-data regimes, where annotated images are extremely limited, posing significant challenges for the generalization of conventional deep learning methods on test images. To address this, we introduce a generative deep learning framework, which uniquely generates high-quality paired segmentation masks and medical images, serving as auxiliary data for training robust models in data-scarce environments. Unlike traditional generative models that treat data generation and segmentation model training as separate processes, our method employs multi-level optimization for end-to-end data generation. This approach allows segmentation performance to directly influence the data generation process, ensuring that the generated data is specifically tailored to enhance the performance of the segmentation model. Our method demonstrated strong generalization performance across 9 diverse medical image segmentation tasks and on 16 datasets, in ultra-low data regimes, spanning various diseases, organs, and imaging modalities. When applied to various segmentation models, it achieved performance improvements of 10-20\% (absolute), in both same-domain and out-of-domain scenarios. Notably, it requires 8 to 20 times less training data than existing methods to achieve comparable results. This advancement significantly improves the feasibility and cost-effectiveness of applying deep learning in medical imaging, particularly in scenarios with limited data availability.
Comparative Effectiveness Of Bedaquiline On One-Year Mortality In Rifampicin-Resistant Tuberculosis: A Target Trial Emulation
Authors: Ngarega Miriam , Ndebele Felex , Segwaba Pulane , Bohlela Sthabiso , Sibeko Zandile , Setlhare Leole , Scott Lesly E , Stevens Wendy , Fanampe Boitumelo , Charalambous Salome , Churchyard Gavin , Van Rie Annelies
Published: August 2024

Background

Three phase II clinical trials generated the evidence for recommending bedaquiline for the treatment of rifampicin-resistant tuberculosis (RR-TB). These trials were not powered to assess the effect of bedaquiline on mortality. Observational studies reported lower mortality in patients treated with bedaquiline-containing regimens but did not fully account for differences between patients who did and did not receive bedaquiline in the real world.

Methods

Using data from two studies on 622 patients, of whom 195 initiated a bedaquiline-containing regimen, we applied rigorous causal inference by emulating a trial that would randomize patients diagnosed with RR-TB by the Xpert MTB/RIF assay to a bedaquiline-containing regimen or a non-bedaquiline-containing regimen. We used multiple imputation to address missing data, inverse probability of treatment weighting (IPTW) to emulate randomized assignment and estimated the odds of one-year mortality using a marginal structural logistic model.

Results

By using IPTW, we achieved conditional exchangeability for observed differences in age, gender, HIV status,Mycobacterium tuberculosisresistance pattern, and history of tuberculosis treatment between patients who did or did not initiate a bedaquiline-containing regimen. By emulating the design of a randomized trial, we found that had all patients been treated with a bedaquiline-containing regimen, there would have been a 67% reduction in the odds of one-year mortality compared to when none of the patients initiated a bedaquiline-containing regimen (OR: 0·33, 95%CI: 0·19-0·59)

Conclusion

By emulating a randomized trial using real-world data, our results demonstrate that the initiation of a bedaquiline-containing regimen causes a 67% reduction in the odds of one-year mortality.

Key message

We assessed the causal effect of initiating a bedaquiline-containing regimen compared to a non-bedaquiline-containing regimen on one-year mortality. We found that a bedaquiline-containing regimen causes a 67% reduction in the odds of one-year mortality, underscoring the need for expanded access to such effective regimens.
Implementation of digital chest radiography for childhood tuberculosis diagnosis at district hospital level in six high tuberculosis burden and resources limited countries
Authors: Melingui Bernard Fortune , Joshi Basant , Taguebue Jean-Voisin , Massom Douglas Mbang , Terquem Etienne Leroy , Norval Pierre-Yves , Salomao Angelica , Bunnet Dim , Eap Tek Chhen , Borand Laurence , Khosa Celso , Moh Raoul , Mwanga-Amumpere Juliet , Eang Mao Tan , Manhiça Ivan , Mustapha Ayeshatu , Balestre Eric , Beneteau Samuel , Wobudeya Eric , Marcy Olivier , Orne-Gliemann Joanna , Bonnet Maryline
Published: August 2024

Objectives

Chest X-ray (CXR) plays an important role in childhood tuberculosis (TB) diagnosis but access to quality CXR remains a major challenge in resource-limited settings. Digital CXR (d-CXR) can solve some image quality issues and facilitate their transfer for quality control. We describe the implementation of introducing d-CXR in twelve district hospitals (DH) in 2021-22 across Cambodia, Cameroon, Ivory Coast, Mozambique, Sierra Leone and Uganda as part of the TB-Speed decentralization study on childhood tuberculosis diagnosis.

Methods

For digitization of CXR Digital Radiography (DR) plates was set-up on existing analogue radiography machines. D-CXR were transferred to an international server at Bordeaux University and downloaded by sites’ clinicians for interpretation. We assessed the pre-intervention (baseline situation and d-CXR set-up) and per-intervention (uptake, challenges and health care workers’ (HCW) perceptions) of d-CXR implementation. We used a convergent mixed method approach utilizing process data, individual interviews with 113 HCWs involved in performing or interpreting d-CXRs and site support supervision reports.

Results

Of 3104 children with presumptive TB, 1642 (52.9%) had at least one d-CXR including 1505, 136 and 1 children with one, two and three d-CXR respectively, resulting in a total of 1780 d-CXR. Of them, 1773 (99.6%) were of good quality and 1772/1773 (99.9%) were interpreted by sites’ clinicians. 164 children had no d-CXR performed despite attending the radiography department: 126, 37 and 1 with one, two and three attempts, respectively. D-CXRs were not performed in 21.6% (44/203) due to connectivity problem between the DR plate captor and the computer. HCWs reported good perceptions of d-CXR and of the DR plates provided. The main challenge was the upload to and download from the server of d-CXRs, due to limited internet access.

Conclusion

D-CXR using DR plates was feasible at district hospital level and provided good quality images but required overcoming operational challenges.
Extracellular microvesicle microRNAs, along with imaging metrics, improve detection of aggressive prostate cancer
Authors: Avasthi Kapil K , Choi Jung W , Glushko Tetiana , Manley Brandon J , Yu Alice , Paw-Sang Julio M , Robert Gatenby , Wang Liang , Yoga Balagurunathan
Published: August 2024

Prostate cancer is the most commonly diagnosed cancer in men worldwide. Early diagnosis of the disease provides better treatment options for these patients. Magnetic resonance imaging (MRI) provides an overall assessment of prostate disease. Quantitative metrics (radiomics) from the MRI provide a better evaluation of the tumor and have been shown to improve disease detection. Recent studies have demonstrated that plasma extracellular vesicle microRNAs (miRNAs) are functionally linked to cancer progression, metastasis, and aggressiveness. In our study, we analyzed a matched cohort with baseline blood plasma and MRI to access tumor morphology using imaging-based radiomics and cellular characteristics using miRNAs-based transcriptomics. Our findings indicate that the univariate feature-based model with the highest Youden index achieved average areas under the receiver operating characteristic curve (AUC) of 0.76, 0.82, and 0.84 for miRNA, MR-T2W, and MR-ADC features, respectively, in identifying clinically aggressive (Gleason grade) disease. The multivariable feature-based model demonstrated an average AUC of 0.88 and 0.95 using combinations of miRNA markers with imaging features in MR-ADC and MR- T2W, respectively. Our study demonstrates combining miRNA markers with MRI-based radiomics improves predictability of clinically aggressive prostate cancer.
Air pollution exposure, respiratory consequences, and perceptions among urban African children living in poor conditions – a case study in Abidjan, Côte d'Ivoire
Authors: Pajot Auriane , Yapo Marie , Coulibaly Sarah , Doumbia Madina , Gnamien Sylvain , Kouao Kouassi , Ahoua Stephane , Adjoua Dje Sonia , Liousse Cathy , Moh Raoul , Orne-Gliemann Joanna , Dick Amon Tanoh Flore , Marcy Olivier , Yoboue Véronique
Published: August 2024

Air pollution can severely impact child lung health but is often not considered a public health priority by policy-makers and population in low-and-middle income countries. We did an interdisciplinary mixed method study to assess exposure to air pollution and respiratory health in children aged 5-10 living in poorly condition in Yopougon, a district of Abidjan, Côte d’Ivoire, and parent and child perceptions and knowledge of air pollution. We assessed pollution exposure with indoor and outdoor PM10 and PM2.5 concentrations and questionnaires, children’s respiratory health with ISAAC questionnaire, clinical evaluation, spirometry or RINT, depending on their ability to perform a forced expiration, their perception of air pollution with a “Draw and express yourself” activity and that of parents with semi-structured interviews and questionnaires. We enrolled 124 children from 65 households, that used mixed cooking with gas and charcoal in settings with important environmental air pollution. Median 48-hour PM10 and PM2.5 concentrations were 126.7 (IQR: 82.7) and 60.8 (IQR: 50.7) μg/m3, indoor respectively, and 113.4 (IQR: 64.2) and 58.2 (IQR: 36.9) μg/m3, outdoor in courtyards. 21 (16.9%) children reported wheezing in the previous year, 65 (52.4%) reported dry cough at night, and 63 (72.4%) had lung function impairment on spirometry with 24 (27.6%) asthma, 19 (21.8%) non reversible obstruction and 20 (23.0%) restrictive pattern. Adults and children were able to identify visible sources of air pollution but largely ignored effects on health. Despite a high exposure to air pollution with particulate matter concentrations far exceeding WHO recommendations in this district of Abidjan, and a high prevalence of respiratory symptoms, lung function impairment and asthma, among children, children and adults, perception of air pollution as a health issue was very limited. Recommendations and awareness-raising for parents and children, starting at primary school level, are needed to limit the exposure to and respiratory consequences of air pollution.
The impact of financial support and budgeting on medication availability and purchasing behavior in the Nigerian primary healthcare system
Authors: Hagedorn Brittany , Han Rui
Published: August 2024

Previous work has shown that primary healthcare facilities can benefit from both in-kind support (e.g., medication shipments) as well as increased cash-on-hand to spend to address service readiness gaps. However, there is limited evidence on how facility managers choose to spend available cash or how their decisions to manage their facility budgets are affected by in-kind support.

Economic theory suggests that the optimal allocation of cash resources would depend on the context and constraints to how it can be spent, and expenditures would in turn affect the availability of supplies and medications. We test this theory using regression analysis on data from the Nigeria Service Delivery Indicators for Health (SDI), a health facility survey from twelve states in 2013 that included both hospitals and primary healthcare centers (PHCs).

We find that facilities with financial resources available to them have higher availability of essential medicines, especially if the facility had earmarked some cash for medication expenditures. However, earmarking for other expenditure categories did not have the same effect on medication availability, which indicates that budgeting processes are an important factor in ensuring medication availability. We find that cash support had large effect (p < 0.001) on availability and that in-kind donations had a negative effect on the probability of expenditure of medications. Additionally, we find the difference between hospitals and PHCs is due to their financial situation (variables become insignificant once support variables were in regressions).

Regression analyses also showed that facilities that received in-kind medications had higher availability, but this only had a significant effect in facilities that did not have cash available to spend on medications, implying that facilities are able to address their own supply needs when they have resources available to them. Thus, in-kind supplies should be targeted to facilities that cannot otherwise procure them. Overall, facilities appear to be making effective trade-offs in the context of limited resources and they should receive both cash and support for appropriate budgeting and procurement practices.
U-Net as a deep learning-based method for platelets segmentation in microscopic images
Authors: de Sousa Eva Maria Valerio , Kumar Ajay , Coupland Charlie , Vaz Tânia F. , Jones Will , Valcarce-Diñeiro Rubén , Calaminus Simon D.J.
Published: August 2024

Manual counting of platelets, in microscopy images, is greatly time-consuming. Our goal was to automatically segment and count platelets images using a deep learning approach, applying U-Net and Fully Convolutional Network (FCN) modelling. Data preprocessing was done by creating binary masks and utilizing supervised learning with ground-truth labels. Data augmentation was implemented, for improved model robustness and detection. The number of detected regions was then retrieved as a count. The study investigated the U-Net models performance with different datasets, indicating notable improvements in segmentation metrics as the dataset size increased, while FCN performance was only evaluated with the smaller dataset and abandoned due to poor results. U-Net surpassed FCN in both detection and counting measures in the smaller dataset Dice 0.90, accuracy of 0.96 (U-Net) vs Dice 0.60 and 0.81 (FCN). When tested in a bigger dataset U-Net produced even better values (Dice 0.99, accuracy of 0.98). The U-Net model proves to be particularly effective as the dataset size increases, showcasing its versatility and accuracy in handling varying cell sizes and appearances. These data show potential areas for further improvement and the promising application of deep learning in automating cell segmentation for diverse life science research applications.
The Data Burden of Digital Learning
Authors: Umoren Rachel , Asangansi Ime , Afenir Dillon , Bresnahan Brian W. , Kotler Annabelle , White Cailin , Cook Matt , Lowman Casey , Berkelhamer Sara
Published: August 2024

The costs of participating in training programs that rely on video conferencing vary by mechanics of use and the specific platform. We proposed practical solutions to limiting costs in low resource settings with the use of video conferencing calls. Scenarios in which facilitators have their video on and expect learners to participate with continuous video result in the greatest data burden, while use of intermittent video by both facilitator and learners can significantly lower data use, and thus costs. The choice of a platform also impacts teleprogramming, with creative options for use of lower cost platforms to reduce participant and training organization costs. These might include sharing educational content or video via chat groups and limiting conference to audio alone. In the context of COVID-19 where virtual meetings have become prevalent, it is critical that data burden is considered by program directors and funders. Looking forward, hybrid training that includes virtual and in-person training will likely become the norm in global health settings, but achieving this model will still require thoughtful consideration of data costs. Further, our findings are relevant to many other fields and advocate for evaluation of costs and data burden along with the growing use of teleprogramming in these settings.
International healthcare workers’ experiences and perceptions of the 2022 multi-country mpox outbreak
Authors: Apea Vanessa , Titanji Boghuma K. , Dakin Francesca H. , Hayes Rosalie , Smuk Melanie , Kawu Habiba , Waters Laura , Levy Itsik , Kuritzkes Daniel R. , Gandhi Monica , Rockstroh Jürgen , Schechter Mauro , Holt Martin , Palich Romain , Cortes Claudia P. , Nozza Silvia , Mussini Cristina , Calmy Aleaxandra , Crabtree Ramirez Brenda E. , Blanco José L. , Bhagani Sanjay , Dewsnap Claire , Orkin Chloe ,   the Mpox SHARE-NET writing group
Published: August 2024

In May 2022, the most widespread outbreak of sustained transmission of mpox outside of countries historically affected countries in Western and Central Africa occurred. We aimed to examine the personal and clinical experiences of international healthcare workers (HCWs) during this public health emergency. We conducted an international cross-sectional survey study between August and October 2022, examining the experiences and perceptions of HCWs clinically involved with the 2022 mpox response. Respondents were recruited via an international network of sexual health and HIV clinicians responding to mpox and promoted through clinical associations and social media. Survey domains included: clinical workload; preparedness; training and support at work; psychological well-being and vaccination. 725 multi-national healthcare workers across 41 countries were included in the analysis. 91% were physicians specialised in Sexual Health or Infectious Diseases; with 34% (n=247) of all respondents involved in mpox policy. A substantial proportion of respondents (n=296, 41%) reported working longer hours during the mpox outbreak, with no concomitant removal of other clinical responsibilities. 30% (n=218) of respondents reported that they had never heard of mpox before the outbreak and over 25% of the respondents reported that they had misdiagnosed someone initially. This culminated in a high prevalence of moral distress at 30%. Less than 9% of HCWs in the region of the Caribbean, Central America and South America had been offered a vaccine as compared to almost 1/3 in the other regions. Where offered, there were high levels of uptake across all regions. Our findings highlight a critical need for addressing the profound gaps in HCW knowledge about re-emerging diseases with pandemic potential. Strengthening the resilience of global health systems and prioritising internationally coordinated approaches to global vaccine deployment is imperative.