bluuebunny/crossref_metadata_2025_split huggingface dataset:
Combined aerobic and resistance exercise training alters the spatial transcriptome of skeletal muscle in young adults
Authors: Stec Michael J. , Graham Zachary A. , Su Qi , Adler Christina , Ni Min , Rouzic Valerie Le , Golann David R. , Ferrara Patrick J. , Halasz Gabor , Sleeman Mark W. , Lavin Kaleen M. , Broderick Timothy J. , Bamman Marcas M. 
Published: June 2024

SummaryChronic exercise training substantially improves skeletal muscle function and performance. The repeated demands and stressors of each exercise bout drive coordinated molecular adaptations within multiple cell types in muscle tissue, leading to enhanced neuromuscular recruitment and contractile function, stem cell activation, myofiber hypertrophy, mitochondrial biogenesis, and angiogenesis, among others. To comprehensively profile molecular changes induced by combined resistance and endurance exercise training, we employed spatial transcriptomics coupled with immunofluorescence and computational approaches to resolve effects on myofiber and mononuclear cell populations in human muscle. By computationally identifying fast and slow myofibers using immunofluorescence data of spatially sequenced tissue sections, we identified fiber type-specific, exercise-induced gene expression changes that correlated with muscle functional improvements. Additionally, spatial transcriptome profiling and integration of human muscle single cell RNAseq data identified an exercise-induced shift in interstitial cell populations coincident with angiogenesis. Overall, these data provide a unique spatial molecular profiling resource for exploring muscle adaptations to exercise, and provide a pipeline and rationale for future studies in human muscle.
Infiltrating lipid-rich macrophage subpopulations identified as a regulator of increasing prostate size in human benign prostatic hyperplasia
Authors: Lanman Nadia A. , Meco Era , Fitchev Philip , Kolliegbo Andree K. , Broman Meaghan M. , Filipovich Yana , Kothandaraman Harish , Cresswell Gregory M. , Talaty Pooja , Antoniak Malgorzata , Brumer Svetlana , Glaser Alexander P. , Higgins Andrew M. , Helfand Brian T. , Franco Omar E. , Crawford Susan E. , Ratliff Timothy L. , Hayward Simon W. , Vickman Renee E. 
Published: June 2024

AbstractMacrophages exhibit marked phenotypic heterogeneity within and across disease states, with lipid metabolic reprogramming contributing to macrophage activation and heterogeneity. Chronic inflammation has been observed in human benign prostatic hyperplasia (BPH) tissues, however macrophage activation states and their contributions to this hyperplastic disease have not been defined. We postulated that a shift in macrophage phenotypes with increasing prostate size could involve metabolic alterations resulting in prostatic epithelial or stromal hyperplasia. Single-cell RNA-seq of CD45+transition zone leukocytes from 10 large (>90 grams) and 10 small (<40 grams) human prostates was conducted. Macrophage subpopulations were defined using marker genes. BPH macrophages do not distinctly categorize into M1 and M2 phenotypes. Instead, macrophages with neither polarization signature preferentially accumulate in large versus small prostates. Specifically, macrophage subpopulations with altered lipid metabolism pathways, demarcated byTREM2andMARCOexpression, significantly accumulate with increased prostate volume.TREM2+andMARCO+macrophage abundance positively correlates with patient body mass index and urinary symptom scores. TREM2+macrophages have significantly higher neutral lipid than TREM2−macrophages from BPH tissues. Lipid-rich macrophages were observed to localize within the stroma in BPH tissues.In vitrostudies indicate that lipid-loaded macrophages increase prostate epithelial and stromal cell proliferation compared to control macrophages. These data define two new BPH immune subpopulations, TREM2+and MARCO+macrophages, and suggest that lipid-rich macrophages may exacerbate lower urinary tract symptoms in patients with large prostates. Further investigation is needed to evaluate the therapeutic benefit of targeting these cells in BPH.
Identification of a gene expression signature of vascular invasion and recurrence in stage I lung adenocarcinoma via bulk and spatial transcriptomics
Authors: Steiner Dylan , Sultan Lila , Sullivan Travis , Liu Hanqiao , Zhang Sherry , LeClerc Ashley , Alekseyev Yuriy O. , Liu Gang , Mazzilli Sarah A. , Zhang Jiarui , Rieger-Christ Kimberly , Burks Eric J. , Beane Jennifer , Lenburg Marc E. 
Published: June 2024

ABSTRACTMicroscopic vascular invasion (VI) is predictive of recurrence and benefit from lobectomy in stage I lung adenocarcinoma (LUAD) but is difficult to assess in resection specimens and cannot be accurately predicted prior to surgery. Thus, new biomarkers are needed to identify this aggressive subset of stage I LUAD tumors. To assess molecular and microenvironment features associated with angioinvasive LUAD we profiled 162 resected stage I tumors with and without VI by RNA-seq and explored spatial patterns of gene expression in a subset of 15 samples by high-resolution spatial transcriptomics (stRNA-seq). Despite the small size of invaded blood vessels, we identified a gene expression signature of VI from the bulk RNA-seq discovery cohort (n=103) and found that it was associated with VI foci, desmoplastic stroma, and high-grade patterns in our stRNA-seq data. We observed a stronger association with high-grade patterns from VI+compared with VI-tumors. Using the discovery cohort, we developed a transcriptomic predictor of VI, that in an independent validation cohort (n=60) was associated with VI (AUROC=0.86; p=5.42×10-6) and predictive of recurrence-free survival (HR=1.98; p=0.024), even in VI-LUAD (HR=2.76; p=0.003). To determine our VI predictor’s robustness to intra-tumor heterogeneity we used RNA-seq data from multi-region sampling of stage I LUAD cases in TRACERx, where the predictor scores showed high correlation (R=0.87, p<2.2×10-16) between two randomly sampled regions of the same tumor. Our study suggests that VI-associated gene expression changes are detectable beyond the site of intravasation and can be used to predict the presence of VI. This may enable the prediction of angioinvasive LUAD from biopsy specimens, allowing for more tailored medical and surgical management of stage I LUAD.
Fine-scale cellular deconvolution via generalized maximum entropy on canonical correlation features
Authors: Kamm Jack 
Published: June 2024

AbstractWe propose a method for estimating probability distributions over single cells, which we apply to fine-scale cellular deconvolution, which quantifies the composition of external bulk RNAseq samples at high resolution (i.e. at the single-cell or neighborhood level). Our method is based on a computationally-efficient convex optimization problem, which is also generalization of the Maximum Entropy method. Our method has a much higher resolution than traditional approaches that require computing gene expression profiles at the cell-type level, and also compares favorably to recent high-resolution cellular deconvolution methods, with orders-of-magnitude speedup in computational efficiency. We implement this method in a Python package quipcell, available athttps://github.com/genentech/quipcell.
Efficacy and Safety of Metronomic Capecitabine in Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis
Authors: Gupta Nandini , Verma Neelkant , Patel Bhoomika 
Published: June 2024

AbstractBackground and ObjectiveMetronomic capecitabine has been found to be useful in several types of cancers such as pancreatic cancer, breast cancer, gastrointestinal cancers, nasopharyngeal carcinoma, metastatic colorectal cancer etc. This unique systematic literature review and meta-analysis was undertaken to assess the effectiveness and safety of metronomic capecitabine as a treatment regimen for hepatocellular carcinoma.MethodA systematic search of major databases was performed. Eight studies that dealt with the use of metronomic capecitabine for HCC were selected, seven were non-RCTs, and one was an RCT. Meta-analysis of these studies was performed using Review manager v5.3 and STATA 15.1 software. The pooled prevalence of OS, PFS, ORR, Grade 1-2 AE, Grade 3-4 AEs were determined, including publication bias and sensitivity analysis.ResultEight studies met the inclusion criteria, combining the pooled data of 476 patients from safety and efficacy studies. The pooled prevalence of DCR and ORR achieved with metronomic capecitabine were 36% (95% CI 32-41) and 7% (95% CI 5-9) respectively. The median PFS and median OS were 3.57 months (95% CI 3.29-3.85) and 11.75 months (95% CI 10.56-12.95) respectively. The incidence of 3-4 grade AEs and 1-2 grade AEs were 38% (95% CI 32-44) and 73% (95% CI 67-79) respectively.ConclusionThis meta-analysis highlights metronomic capecitabine as a potential second-line therapy for HCC. However, effective management of capecitabine’s side effects is essential.
An immunoediting map of human cancers
Authors: Gan Rui , Ren Xianwen 
Published: June 2024

AbstractUnderstanding how cancer immunoediting sculpts tumor microenvironments is essential to disentangling tumor immune evasion mechanisms and developing immunotherapies. Here, we construct a comprehensive immunoediting map of human cancers via single-cell deconvolution of 11057 tumor-derived samples across 33 cancer types from TCGA and comparison with 17382 healthy samples across 30 tissues from GTEx. The map covers >1000 different cell states across all the major immune cell types. Mast cells, megakaryocytes, macrophages, neutrophils, plasma cells and T cells are up-regulated across a wide range of tumor types while natural killer cells and platelets are down-regulated in most tumor types, suggesting common cancer immunoediting events. While tumor heterogeneity is higher than the normal corresponding tissues, significant immune homogeneity exists among different tumor types compared with the distinct immune composition among normal tissues and organs. Our study provides a new holistic perspective to understanding cancer immunoediting. Our findings may provide important hints for developing novel cancer immunotherapies, and the high-resolution immunoediting map may serve as a rich resource for further pan-cancer investigation.
Determination of the absolute concentration of Rayleigh particles via scattering microscopy
Authors: Lee Il-Buem , Moon Hyun-Min , Park Jin-Sung , Lee Se-Hwan , Lee Jaewon , Park Sung Hun , Lee Seungwoo , Hong Seok-Cheol , Cho Minhaeng 
Published: June 2024

AbstractNanoparticles are crucial in diverse fields such as healthcare, electronics, and energy. Their small size allows them to cross biological barriers, enhancing drug delivery but also posing health risks. Accurate characterization of nanoparticles is essential for assessing their safety and efficacy, particularly in medical applications. Traditional methods such as dynamic light scattering and mass spectrometry have limitations in sensitivity and range of application. To address these challenges, we introduce the interferometric Concentration Analyzer and Ultrasmall Nanoparticle Tracker (iCAUNT), a technique for detecting and quantifying nanoparticles smaller than one-tenth of the imaging light wavelength. As a non-invasive method, iCAUNT provides precise size and concentration measurements of biological and synthetic nanoparticles, offering significant potential for diagnostics, therapeutics, and broader nanoscience applications.
A Computational Workflow for Analysis of Missense Mutations in Precision Oncology
Authors: Khan Rayyan Tariq , Pokorna Petra , Stourac Jan , Borko Simeon , Arefiev Ihor , Planas-Iglesias Joan , Dobias Adam , Pinto Gaspar , Szotkowska Veronika , Sterba Jaroslav , Slaby Ondrej , Damborsky Jiri , Mazurenko Stanislav , Bednar David 
Published: June 2024

AbstractEvery year, more than 19 million cancer cases are diagnosed, and this number continues to increase annually. Since standard treatment options have varying success rates for different types of cancer, understanding the biology of an individual’s tumour becomes crucial, especially for cases that are difficult to treat. Personalised high-throughput profiling, using next-generation sequencing, allows for a comprehensive examination of biopsy specimens. Furthermore, the widespread use of this technology has generated a wealth of information on cancer-specific gene alterations. However, there exists a significant gap between identified alterations and their proven impact on protein function. Here, we present a bioinformatics pipeline that enables fast analysis of a missense mutation’s effect on stability and function in known oncogenic proteins. This pipeline is coupled with a predictor that summarises the outputs of different tools used throughout the pipeline, providing a single probability score, achieving the balanced accuracy above 86%. The pipeline incorporates a virtual screening method to suggest potential FDA/EMA-approved drugs to be considered for treatment. We showcase three case studies to demonstrate the timely utility of this pipeline. To facilitate access and analysis of cancer-related mutations, we have packaged the pipeline as a web server, which is freely available athttps://loschmidt.chemi.muni.cz/predictonco/.
Targeting miRNA for Colorectal Cancer:In SilicoIdentification and Physics-basedDe NovoModeling of Oncogenic miR-135b for Small Molecule RNA Therapy
Authors: Demir Berat , Oktay Lalehan , Durdağı Serdar 
Published: June 2024

ABSTRACTColorectal cancer is one of the leading causes of cancer deaths worldwide. In the current study, we have identified miR-135b, a microRNA to be differentially expressed in colorectal cancer, through an analysis of the differentially expressed miRNAs from the Gene Expression Omnibus database. Subsequently, the target genes associated with miR-135b were pinpointed, and pathway and functional enrichment analyses were performed to gain a comprehensive understanding of the underlying biological processes involved. Ade novothree-dimensional model of its tertiary structure was developed for small-molecule targeting at the Dicer cleavage site. Dicer binds to the terminal loop region of the pre-miRNA and cleaves to generate double stranded miRNA duplex. The miRNA duplex is unwound, one of the strands, guide miRNA, is loaded into the RNA-induced silencing complex (RISC) for miRNA-mRNA target interaction and post-transcriptional gene silencing. Following results from molecular docking simulations initiated with the ChemDiv miRNA-targeted small molecule library (∼20.000 compounds), top-scoring compound’s commercial analogues were then searched within the ZINC library using SwissSimilarity. These analogues were docked to the Dicer cleavage site and their optimized docking scores were obtained. These top-scoring molecules were then subject to all-atom molecular dynamics simulations and post-simulation analyses were conducted to assess the dynamic interactions between the miRNA and the selected hit ligands.
Missense Mutant Gain-of-Function Causes Inverted Formin 2 (INF2)-Related Focal Segmental Glomerulosclerosis (FSGS)
Authors: Subramanian Balajikarthick , Williams Sarah , Karp Sophie , Hennino Marie-Flore , Jacas Sonako , Lee Miriam , Riella Cristian V. , Alper Seth L. , Higgs Henry N. , Pollak Martin R. 
Published: June 2024

ABSTRACTInverted formin-2 (INF2) gene mutations are among the most common causes of genetic focal segmental glomerulosclerosis (FSGS) with or without Charcot-Marie-Tooth (CMT) disease. Recent studies suggest that INF2, through its effects on actin and microtubule arrangement, can regulate processes including vesicle trafficking, cell adhesion, mitochondrial calcium uptake, mitochondrial fission, and T-cell polarization. Despite roles for INF2 in multiple cellular processes, neither the human pathogenic R218Q INF2 point mutation nor the INF2 knock-out allele is sufficient to cause disease in mice. This discrepancy challenges our efforts to explain the disease mechanism, as the link between INF2-related processes, podocyte structure, disease inheritance pattern, and their clinical presentation remains enigmatic. Here, we compared the kidney responses to puromycin aminonucleoside (PAN) induced injury between R218Q INF2 point mutant knock-in and INF2 knock-out mouse models and show that R218Q INF2 mice are susceptible to developing proteinuria and FSGS. This contrasts with INF2 knock-out mice, which show only a minimal kidney phenotype. Co-localization and co-immunoprecipitation analysis of wild-type and mutant INF2 coupled with measurements of cellular actin content revealed that the R218Q INF2 point mutation confers a gain-of-function effect by altering the actin cytoskeleton, facilitated in part by alterations in INF2 localization. Differential analysis of RNA expression in PAN-stressed heterozygous R218Q INF2 point-mutant and heterozygous INF2 knock-out mouse glomeruli showed that the adhesion and mitochondria-related pathways were significantly enriched in the disease condition. Mouse podocytes with R218Q INF2, and an INF2-mutant human patient’s kidney organoid-derived podocytes with an S186P INF2 mutation, recapitulate the defective adhesion and mitochondria phenotypes. These results link INF2-regulated cellular processes to the onset and progression of glomerular disease. Thus, our data demonstrate that gain-of-function mechanisms drive INF2-related FSGS and explain the autosomal dominant inheritance pattern of this disease.
Cross-Modality Synthetic Data Augmentation using GANs: Enhancing Brain MRI and Chest X-ray Classification
Authors: Dhawan Kunaal , Nijhawan Siddharth S. 
Published: June 2024

II.AbstractBrain MRI scans and chest X-ray imaging are pivotal in diagnosing and managing neurological and respiratory diseases, respectively. Given their importance in diagnosis, the datasets to train the artificial intelligence (AI) models for automated diagnosis remain scarce. As an example, annotated chest X-ray datasets, especially those containing rare or abnormal cases like bacterial pneumonia, are scarce. Conventional dataset collection methods are labor-intensive and costly, exacerbating the data scarcity issue. To overcome these challenges, we propose a specialized Generative Adversarial Network (GAN) architecture for generating synthetic chest X-ray data representing healthy lungs and various pneumonia conditions, including viral and bacterial pneumonia. Additionally, we extended our experiments to brain MRI scans by simply swapping the training dataset and demonstrating the power of our GAN approach across different medical imaging contexts. Our method aims to streamline data collection and labeling processes while addressing privacy concerns associated with patient data. We demonstrate the effectiveness of synthetic data in facilitating the development and evaluation of machine learning algorithms, particularly leveraging an EfficientNet v2 model. Through comprehensive experimentation, we evaluate our approach on both real and synthetic datasets, showcasing the potential of synthetic data augmentation in improving disease classification accuracy across diverse pathological conditions. Indeed, the classifier performance when trained with fake + real data on brain MRI classification task shows highest accuracy at 85.9%. Our findings underscore the promising role of synthetic data in advancing automated diagnosis and treatment planning for pneumonia, other respiratory conditions, and brain pathologies.
Implicit bias in Critical Care Data: Factors affecting sampling frequencies and missingness patterns of clinical and biological variables in ICU Patients
Authors: Shi Junming (Seraphina) , Hubbard Alan E. , Fong Nicholas , Pirracchio Romain 
Published: June 2024

AbstractThe presence of missing values in Electronic Health Records (EHRs) is a widespread and inescapable issue. Publicly available data sets mirror the incompleteness found in EHRs. Although the existing literature largely approaches missing data as a random phenomenon, the mechanisms behind these missing values are often not random with respect to important characteristics of the patients. Similarly, the sampling frequency of clinical or biological parameters is likely informative. The possible informative nature of patterns in missing data is often overlooked. For both missingness and sampling frequency, we hypothesize that the underlying mechanism may be at least consistent with implicit bias.To investigate this important issue, we introduce a novel analytical framework designed to rigorously examine missing data and sampling frequency in EHRs. We utilize the MIMIC-III dataset as a case study, given its frequent use in training machine learning models for healthcare applications. Our approach incorporates Targeted Machine Learning (TML) to study the impact of a series of demographic variables, including protected attributes such as age, sex, race, and ethnicity on the rate of missing data and sampling frequency for key clinical and biological variables in critical care settings. Our results expose underlying differences in the sampling frequency and missing data patterns of vital sign measurements and laboratory tests between different demographic groups. In addition, we find that these measurement patterns can provide significant predictive insights into patient outcomes. Consequently, we urge a reevaluation of the conventional understanding of missing data and sampling frequencies in EHRs. Acknowledging and addressing these biases is essential for advancing equitable and accurate healthcare through machine learning applications.
Distribution, Prevalence, and Antibiotic Resistance of Non-Tuberculous Mycobacteria on Hainan Island
Authors: Xu Xinru , Huang Jingjing , Wang Hongkun , Xiang Tianchen , Liu Jun , Zheng Li 
Published: June 2024

ABSTRACTBackgroundNon-tuberculous mycobacteria (NTM) represent a diverse group of environmental mycobacteria, with certain species implicated in infections affecting multiple tissues, including the lungs. The incidence of NTM-related diseases has been on the rise globally, particularly in developing countries. This study aimed to systematically investigate the ecological distribution, molecular identification, and antibiotic susceptibility profiles of NTM isolates in Hainan Island, furnishing a scientific basis for local control and prevention strategies. Methods: From 2015 to 2018, 158 suspected NTM samples were collected across 14 cities on Hainan Island. Following standardized sample processing and DNA extraction, molecular identification was conducted through PCR amplification of the rpoB and hsp65 genes, and sequencing, with species confirmation via GenBank database comparison. Phylogenetic analysis was performed to elucidate interspecies relationships and drug susceptibility testing was carried out for five antibiotics on M. abscessus isolates. Results: 118 NTM isolates were successfully identified, encompassing 24 distinct species. M. abscessus and M. intracellulare, accounting for 23.73% and 22.03% respectively, were the most prevalent. Phylogenetic analysis revealed clusters indicative of pathogenic and potentially pathogenic traits among different NTM species, with M. abscessus and M. fortuitum clustering as rapidly growing, pathogenic mycobacteria. Drug sensitivity testing indicated universal resistance of M. abscessus to doxycycline, yet high sensitivity to amikacin (71.4%) and linezolid (50.0%). Additionally, non-NTM species such as Nocardia thailandica, and Tsukamurella paurometabola were detected, suggesting potential misdiagnosis in clinical settings. Conclusion: This study provides a comprehensive dataset on the ecological distribution, molecular characterization, and antibiotic resistance of NTM in Hainan Island, highlighting the dominance of M. abscessus and M. intracellulare in local NTM infections.