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Clinical case reports (CCRs) provide an important means of sharing clinical experiences about atypical disease phenotypes and new therapies. However, published case reports contain largely unstructured and heterogeneous clinical data, posing a challenge to mining relevant information. Current indexing approaches generally concern document-level features and have not been specifically designed for CCRs. To address this disparity, we developed a standardized metadata template and identified text corresponding to medical concepts within 3,100 curated CCRs spanning 15 disease groups and more than 750 reports of rare diseases. We also prepared a subset of metadata on reports on selected mitochondrial diseases and assigned ICD-10 diagnostic codes to each. The resulting resource, Metadata Acquired from Clinical Case Reports (MACCRs), contains text associated with high-level clinical concepts, including demographics, disease presentation, treatments, and outcomes for each report. Our template and MACCR set render CCRs more findable, accessible, interoperable, and reusable (FAIR) while serving as valuable resources for key user groups, including researchers, physician investigators, clinicians, data scientists, and those shaping government policies for clinical trials.

Clinical case reports (CCRs) provide an important means of sharing clinical experiences about atypical disease phenotypes and new therapies. However, published case reports contain largely unstructured and heterogeneous clinical data, posing a challenge to mining relevant information. Current indexing approaches generally concern document-level features and have not been specifically designed for CCRs. To address this disparity, we developed a standardized metadata template and identified text corresponding to medical concepts within 3,100 curated CCRs spanning 15 disease groups and more than 750 reports of rare diseases. We also prepared a subset of metadata on reports on selected mitochondrial diseases and assigned ICD-10 diagnostic codes to each. The resulting resource, Metadata Acquired from Clinical Case Reports (MACCRs), contains text associated with high-level clinical concepts, including demographics, disease presentation, treatments, and outcomes for each report. Our template and MACCR set render CCRs more findable, accessible, interoperable, and reusable (FAIR) while serving as valuable resources for key user groups, including researchers, physician investigators, clinicians, data scientists, and those shaping government policies for clinical trials.

The microphthalmia family of transcription factors (MiT/TFEs) controls lysosomal biogenesis and is negatively regulated by the nutrient sensor mTORC1. However, the mechanisms by which cells with constitutive mTORC1 signaling maintain lysosomal catabolism remain to be elucidated. Using the murine epidermis as a model system, we found that epidermal Tsc1 deletion resulted in a phenotype characterized by wavy hair and curly whiskers, and was associated with increased EGFR and HER2 degradation. Unexpectedly, constitutive mTORC1 activation with Tsc1 loss increased lysosomal content via upregulated expression and activity of MiT/TFEs, whereas genetic deletion of Rheb or Rptor or prolonged pharmacologic mTORC1 inactivation had the reverse effect. This paradoxical increase in lysosomal biogenesis by mTORC1 was mediated by feedback inhibition of AKT, and a resulting suppression of AKT-induced MiT/TFE downregulation. Thus, inhibiting hyperactive AKT signaling in the context of mTORC1 loss-of-function fully restored MiT/TFE expression and activity. These data suggest that signaling feedback loops work to restrain or maintain cellular lysosomal content during chronically inhibited or constitutively active mTORC1 signaling, respectively, and reveal a mechanism by which mTORC1 regulates upstream receptor tyrosine kinase signaling., Introduction The microphthalmia family of transcription factors (MiT/TFEs) is composed of 4 conserved members (Mitf/Tfe3/Tfeb/Tfec) that are essential regulators of lysosomal biogenesis and autophagy. MiTs are functionally redundant and regulate [...]

Ovarian cancer (OC) is one among most significantly fatal gynecological cancers, with late-stage detection and an inadequate prognosis. Plasminogen activator inhibitor-1 ( PAI1 ) gene anticipates negative outcomes in many different kinds of malignancies. Several research investigations are currently being done to examine the biological role of PAI1 in OC and the possible benefits of targeted pharmacotherapies. The PAI1 gene has been linked to the emergence and development of cancer in the ovary. PAI1 , an inhibitor of serine protease, influences the fibrinolysis and extracellular matrix remodeling, both of which are crucial for tumor expansion and metastatic growth. PAI1 levels have been discovered to be subsequently more elevated in malignant ovarian tissues than in usual ovarian tissue, demonstrating a potential connection among PAI1 overexpression and OC development. PAI1 promotes tumor cell proliferation, movement, and an invasion by influencing the urokinase-plasminogen activators and through interactions with cell surface receptors. In addition, PAI1 gene contributes to angiogenesis and apoptotic cell death, which contribute to the more hostile phenotypes of OC. The prognostic and therapeutic consequences of focusing on PAI1 in OC are explored, demonstrating PAI1 's potential to be a biomarker and emphasizing for novel treatment approaches. The PAI1 gene possesses several functions in OC, affecting tumor development, an invasion, and metastatic growth. Comprehending the complicated interactions and mechanisms that regulate PAI1 in OC may lead to more efficient evaluation and treatment strategies and ultimately enhance patient outcomes., Competing Interests: Conflict of Interest None declared., (The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. ( https://creativecommons.org/licenses/by/4.0/ ).)

Cardiovascular disease continues to be a major burden facing healthcare systems worldwide. In the developed world, cardiovascular magnetic resonance (CMR) is a well-established non-invasive imaging modality in the diagnosis of cardiovascular disease. However, there is significant global inequality in availability and access to CMR due to its high cost, technical demands as well as existing disparities in healthcare and technical infrastructures across high-income and low-income countries. Recent renewed interest in low-field CMR has been spurred by the clinical need to provide sustainable imaging technology capable of yielding diagnosticquality images whilst also being tailored to the local populations and healthcare ecosystems. This review aims to evaluate the technical, practical and cost considerations of low field CMR whilst also exploring the key barriers to implementing sustainable MRI in both the developing and developed world., (© The Author(s) 2022. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Purpose: The ATM (ataxia telangiectasia mutated) gene is mutated in a subset of prostate cancers, and ATM mutation may confer specific therapeutic vulnerabilities, although ATM-deficient prostate cancers have not been well-characterized., Experimental Design: We genetically validated a clinical grade IHC assay to detect ATM protein loss and examined the frequency of ATM loss among tumors with pathogenic germline ATM mutations and genetically unselected primary prostate carcinomas using tissue microarrays (TMAs). Immunostaining results were correlated with targeted somatic genomic sequencing and clinical outcomes., Results: ATM protein loss was found in 13% (7/52) of primary Gleason pattern 5 cancers with available sequencing data and was 100% sensitive for biallelic ATM inactivation. In a separate cohort with pathogenic germline ATM mutations, 74% (14/19) had ATM protein loss of which 70% (7/10) of evaluable cases had genomic evidence of biallelic inactivation, compared with zero of four of cases with intact ATM expression. By TMA screening, ATM loss was identified in 3% (25/831) of evaluable primary tumors, more commonly in grade group 5 (17/181; 9%) compared with all other grades (8/650; 1%; P < 0.0001). Of those with available sequencing, 80% (4/5) with homogeneous ATM protein loss and 50% (6/12) with heterogeneous ATM protein loss had detectable pathogenic ATM alterations. In surgically treated patients, ATM loss was not significantly associated with clinical outcomes in random-effects Cox models after adjusting for clinicopathologic variables., Conclusions: ATM loss is enriched among high-grade prostate cancers. Optimal evaluation of ATM status requires both genomic and IHC studies and will guide development of molecularly targeted therapies., (©2020 American Association for Cancer Research.)

Extracellular matrix (ECM) proteins have been shown to play important roles regulating multiple biological processes in an array of organ systems, including the cardiovascular system. Using a novel bioinformatics text-mining tool, we studied six categories of cardiovascular disease (CVD), namely, ischemic heart disease, cardiomyopathies, cerebrovascular accident, congenital heart disease, arrhythmias, and valve disease, anticipating novel ECM protein-disease and protein-protein relationships hidden within vast quantities of textual data. We conducted a phrase-mining analysis, delineating the relationships of 709 ECM proteins with the 6 groups of CVDs reported in 1,099,254 abstracts. The technology pipeline known as Context-Aware Semantic Online Analytical Processing was applied to semantically rank the association of proteins to each CVD and all six CVDs, performing analyses to quantify each protein-disease relationship. We performed principal component analysis and hierarchical clustering of the data, where each protein was visualized as a six-dimensional vector. We found that ECM proteins display variable degrees of association with the six CVDs; certain CVDs share groups of associated proteins, whereas others have divergent protein associations. We identified 82 ECM proteins sharing associations with all 6 CVDs. Our bioinformatics analysis ascribed distinct ECM pathways (via Reactome) from this subset of proteins, namely, insulin-like growth factor regulation and interleukin-4 and interleukin-13 signaling, suggesting their contribution to the pathogenesis of all six CVDs. Finally, we performed hierarchical clustering analysis and identified protein clusters predominantly associated with a targeted CVD; analyses of these proteins revealed unexpected insights underlying the key ECM-related molecular pathogenesis of each CVD, including virus assembly and release in arrhythmias. NEW & NOTEWORTHY The present study is the first application of a text-mining algorithm to characterize the relationships of 709 extracellular matrix-related proteins with 6 categories of cardiovascular disease described in 1,099,254 abstracts. Our analysis informed unexpected extracellular matrix functions, pathways, and molecular relationships implicated in the six cardiovascular diseases.