Association between CT-based body composition assessment and patient outcomes during neoadjuvant chemotherapy for epithelial ovarian cancer.

OBJECTIVE: The aim of this study was to characterize the body composition of patients undergoing neoadjuvant chemotherapy (NACT) for epithelial ovarian cancer (EOC), identify factors associated with sarcopenia at diagnosis, and evaluate the impact of pretreatment sarcopenia and changes in body composition parameters during therapy on perioperative and disease-related outcomes. METHODS: Patients undergoing NACT for EOC between 2008 and 2020 were identified. Pre-treatment and post-treatment contrast-enhanced CT scans were reviewed to determine skeletal muscle index (SMI) and visceral adipose tissue (VAT) area at the mid-fourth lumbar vertebral level. SMI and VAT were analyzed for association with clinical and treatment variables. RESULTS: 174 patients were identified. Mean pretreatment SMI and VAT were 38.3 cm2/m2 ± 7.9 and 51.2 cm2/m2 ± 34.3, respectively. Comparatively, mean post-treatment SMI and VAT were 37.8 cm2/m2 ± 7.9 and 43.7 cm2/m2 ± 29.7, respectively. Most patients exhibited an overall decrease in SMI from pretreatment to posttreatment scans. Caucasian race, older age, and lower body mass index at diagnosis were associated with lower pretreatment SMI. Lower pre-treatment SMI was associated with lower surgical complexity scores (p < 0.001) and estimated blood loss (p = 0.029). Decrease in SMI after NACT was associated with increased rates of ICU admissions and length of stay. While there was no association between SMI and overall survival (OS) or progression-free survival (PFS), >2% decrease per 100 days in VAT was significantly associated with worse OS. CONCLUSIONS: Patients with lower pretreatment SMI tend to undergo less complex surgery than those with higher SMI despite NACT. Decrease in VAT may be a potential indicator of worse OS. Information on body composition can aid in clinical decision making in patients with EOC.

Impacts of Climate Change and Air Pollution on Neurologic Health, Disease, and Practice: A Scoping Review.

BACKGROUND AND OBJECTIVES: Although the international community collectively seeks to reduce global temperature rise to less than 1.5°C before 2100, irreversible environmental changes have already occurred, and as the planet warms, these changes will continue to occur. As we witness the effects of a warming planet on human health, it is imperative that neurologists anticipate how the epidemiology and incidence of neurologic disease may change. In this review, we organized our analysis around 3 key themes related to climate change and neurologic health: extreme weather events and temperature fluctuations, emerging neuroinfectious diseases, and pollutant impacts. Across each of these themes, we appraised and reviewed recent literature relevant to neurologic disease and practice. METHODS: Studies were identified using search terms relating to climate change, pollutants, and neurologic disease in PubMed, OVID MEDLINE, EMBASE, PsycInfo, and gray literature. Studies published between 1990 and 2022 were included if they pertained to human incidence or prevalence of disease, were in English, and were relevant to neurologic disease. RESULTS: We identified a total of 364 articles, grouped into the 3 key themes of our study: extreme weather events and temperature fluctuations (38 studies), emerging neuroinfectious diseases (37 studies), and pollutant impacts (289 studies). The included studies highlighted the relationships between neurologic symptom exacerbation and temperature variability, tick-borne infections and warming climates, and airborne pollutants and cerebrovascular disease incidence and severity. DISCUSSION: Temperature extremes and variability both associated with stroke incidence and severity, migraine headaches, hospitalization in patients with dementia, and multiple sclerosis exacerbations. Exposure to airborne pollutants, especially PM2.5 and nitrates, associated with stroke incidence and severity, headaches, dementia risk, Parkinson disease, and MS exacerbation. Climate change has demonstrably expanded favorable conditions for zoonotic diseases beyond traditional borders and poses the risk of disease in new, susceptible populations. Articles were biased toward resource-rich regions, suggesting a discordance between where research occurs and where changes are most acute. As such, 3 key priorities emerged for further study: neuroinfectious disease risk mitigation, understanding the pathophysiology of airborne pollutants on the nervous system, and methods to improve delivery of neurologic care in the face of climate-related disruptions.

Biomarkers for Myocarditis and Inflammatory Cardiomyopathy.

PURPOSE OF REVIEW: Myocarditis is a disease caused by inflammation of the heart that can progress to dilated cardiomyopathy, heart failure, and eventually death in many patients. Several etiologies are implicated in the development of myocarditis including autoimmune, drug-induced, infectious, and others. All causes lead to inflammation which causes damage to the myocardium followed by remodeling and fibrosis. This review aims to summarize recent findings in biomarkers for myocarditis and highlight the most promising candidates. RECENT FINDINGS: Current methods of diagnosing myocarditis, including imaging and endomyocardial biopsy, are invasive, expensive, and often not done early enough to affect progression. Research is being done to find biomarkers of myocarditis that are cost-effective, accurate, and prognostically informative. These biomarkers would allow for earlier screening for myocarditis, as well as earlier treatment, and a better understanding of the disease course for specific patients. Early diagnosis of myocarditis with biomarkers may allow for prompt treatment to improve outcomes in patients.

Characterization of cardiac amyloidosis using cardiac magnetic resonance fingerprinting.

BACKGROUND: Cardiac amyloidosis (CA) is an infiltrative cardiomyopathy with poor prognosis absent appropriate treatment. Elevated native myocardial T1 and T2 have been reported for CA, and tissue characterization by cardiac MRI may expedite diagnosis and treatment. Cardiac Magnetic Resonance Fingerprinting (cMRF) has the potential to enable tissue characterization for CA through rapid, simultaneous T1 and T2 mapping. Furthermore, cMRF signal timecourses may provide additional information beyond myocardial T1 and T2. METHODS: Nine CA patients and five controls were scanned at 3 T using a prospectively gated cMRF acquisition. Two cMRF-based analysis approaches were examined: (1) relaxometric-based linear discriminant analysis (LDA) using native T1 and T2, and (2) signal timecourse-based LDA. The Fisher coefficient was used to compare the separability of patient and control groups from both approaches. Leave-two-out cross-validation was employed to evaluate the classification error rates of both approaches. RESULTS: Elevated myocardial T1 and T2 was observed in patients vs controls (T1: 1395 ± 121 vs 1240 ± 36.4 ms, p < 0.05; T2: 36.8 ± 3.3 vs 31.8 ± 2.6 ms, p < 0.05). LDA scores were elevated in patients for relaxometric-based LDA (0.56 ± 0.28 vs 0.18 ± 0.13, p < 0.05) and timecourse-based LDA (0.97 ± 0.02 vs 0.02 ± 0.02, p < 0.05). The Fisher coefficient was greater for timecourse-based LDA (60.8) vs relaxometric-based LDA (1.6). Classification error rates were lower for timecourse-based LDA vs relaxometric-based LDA (12.6 ± 24.3 vs 22.5 ± 30.1%, p < 0.05). CONCLUSIONS: These findings suggest that cMRF may be a valuable technique for the detection and characterization of CA. Analysis of cMRF signal timecourse data may improve tissue characterization as compared to analysis of native T1 and T2 alone.

lncRNAKB, a knowledgebase of tissue-specific functional annotation and trait association of long noncoding RNA.

Long non-coding RNA Knowledgebase (lncRNAKB) is an integrated resource for exploring lncRNA biology in the context of tissue-specificity and disease association. A systematic integration of annotations from six independent databases resulted in 77,199 human lncRNA (224,286 transcripts). The user-friendly knowledgebase covers a comprehensive breadth and depth of lncRNA annotation. lncRNAKB is a compendium of expression patterns, derived from analysis of RNA-seq data in thousands of samples across 31 solid human normal tissues (GTEx). Thousands of co-expression modules identified via network analysis and pathway enrichment to delineate lncRNA function are also accessible. Millions of expression quantitative trait loci (cis-eQTL) computed using whole genome sequence genotype data (GTEx) can be downloaded at lncRNAKB that also includes tissue-specificity, phylogenetic conservation and coding potential scores. Tissue-specific lncRNA-trait associations encompassing 323 GWAS (UK Biobank) are also provided. LncRNAKB is accessible at http://www.lncrnakb.org/ , and the data are freely available through Open Science Framework ( https://doi.org/10.17605/OSF.IO/RU4D2 ).

In vivo functional analysis of non-conserved human lncRNAs associated with cardiometabolic traits.

Unlike protein-coding genes, the majority of human long non-coding RNAs (lncRNAs) are considered non-conserved. Although lncRNAs have been shown to function in diverse pathophysiological processes in mice, it remains largely unknown whether human lncRNAs have such in vivo functions. Here, we describe an integrated pipeline to define the in vivo function of non-conserved human lncRNAs. We first identify lncRNAs with high function potential using multiple indicators derived from human genetic data related to cardiometabolic traits, then define lncRNA's function and specific target genes by integrating its correlated biological pathways in humans and co-regulated genes in a humanized mouse model. Finally, we demonstrate that the in vivo function of human-specific lncRNAs can be successfully examined in the humanized mouse model, and experimentally validate the predicted function of an obesity-associated lncRNA, LINC01018, in regulating the expression of genes in fatty acid oxidation in humanized livers through its interaction with RNA-binding protein HuR.

IKAP-Identifying K mAjor cell Population groups in single-cell RNA-sequencing analysis.

BACKGROUND: In single-cell RNA-sequencing analysis, clustering cells into groups and differentiating cell groups by differentially expressed (DE) genes are 2 separate steps for investigating cell identity. However, the ability to differentiate between cell groups could be affected by clustering. This interdependency often creates a bottleneck in the analysis pipeline, requiring researchers to repeat these 2 steps multiple times by setting different clustering parameters to identify a set of cell groups that are more differentiated and biologically relevant. FINDINGS: To accelerate this process, we have developed IKAP-an algorithm to identify major cell groups and improve differentiating cell groups by systematically tuning parameters for clustering. We demonstrate that, with default parameters, IKAP successfully identifies major cell types such as T cells, B cells, natural killer cells, and monocytes in 2 peripheral blood mononuclear cell datasets and recovers major cell types in a previously published mouse cortex dataset. These major cell groups identified by IKAP present more distinguishing DE genes compared with cell groups generated by different combinations of clustering parameters. We further show that cell subtypes can be identified by recursively applying IKAP within identified major cell types, thereby delineating cell identities in a multi-layered ontology. CONCLUSIONS: By tuning the clustering parameters to identify major cell groups, IKAP greatly improves the automation of single-cell RNA-sequencing analysis to produce distinguishing DE genes and refine cell ontology using single-cell RNA-sequencing data.

Regenerative and durable small-diameter graft as an arterial conduit.

Despite significant research efforts, clinical practice for arterial bypass surgery has been stagnant, and engineered grafts continue to face postimplantation challenges. Here, we describe the development and application of a durable small-diameter vascular graft with tailored regenerative capacity. We fabricated small-diameter vascular grafts by electrospinning fibrin tubes and poly(ε-caprolactone) fibrous sheaths, which improved suture retention strength and enabled long-term survival. Using surface topography in a hollow fibrin microfiber tube, we enable immediate, controlled perfusion and formation of a confluent endothelium within 3-4 days in vitro with human endothelial colony-forming cells, but a stable endothelium is noticeable at 4 weeks in vivo. Implantation of acellular or endothelialized fibrin grafts with an external ultrathin poly(ε-caprolactone) sheath as an interposition graft in the abdominal aorta of a severe combined immunodeficient Beige mouse model supports normal blood flow and vessel patency for 24 weeks. Mechanical properties of the implanted grafts closely approximate the native abdominal aorta properties after just 1 week in vivo. Fibrin mediated cellular remodeling, stable tunica intima and media formation, and abundant matrix deposition with organized collagen layers and wavy elastin lamellae. Endothelialized grafts evidenced controlled healthy remodeling with delayed and reduced macrophage infiltration alongside neo vasa vasorum-like structure formation, reduced calcification, and accelerated tunica media formation. Our studies establish a small-diameter graft that is fabricated in less than 1 week, mediates neotissue formation and incorporation into the native tissue, and matches the native vessel size and mechanical properties, overcoming main challenges in arterial bypass surgery.