Citations

We investigated the link between enhancement of SI (by hyperinsulinemic–euglycemic clamp) and muscle metabolites after 12 weeks of aerobic (high-intensity interval training [HIIT]), resistance training (RT), or combined training (CT) exercise in 52 lean healthy individuals. Muscle RNA sequencing revealed a significant association between SI after both HIIT and RT and the branched-chain amino acid (BCAA) metabolic pathway. Concurrently with increased expression and activity of branched-chain ketoacid dehydrogenase enzyme, many muscle amino metabolites, including BCAAs, glutamate, phenylalanine, aspartate, asparagine, methionine, and γ-aminobutyric acid, increased with HIIT, supporting the substantial impact of HIIT on amino acid metabolism. Short-chain C3 and C5 acylcarnitines were reduced in muscle with all three training modes, but unlike RT, both HIIT and CT increased tricarboxylic acid metabolites and cardiolipins, supporting greater mitochondrial activity with aerobic training. Conversely, RT and CT increased more plasma membrane phospholipids than HIIT, suggesting a resistance exercise effect on cellular membrane protection against environmental damage. Sex and age contributed modestly to the exercise-induced changes in metabolites and their association with cardiometabolic parameters. Integrated transcriptomic and metabolomic analyses suggest various clusters of genes and metabolites are involved in distinct effects of HIIT, RT, and CT. These distinct metabolic signatures of different exercise modes independently link each type of exercise training to improved SI and cardiometabolic risk. Article Highlights We aimed to understand the link between skeletal muscle metabolites and cardiometabolic health after exercise training. Although aerobic, resistance, and combined exercise training each enhance muscle insulin sensitivity as well as other cardiometabolic parameters, they disparately alter amino and citric acid metabolites as well as the lipidome, linking these metabolomic changes independently to the improvement of cardiometabolic risks with each exercise training mode. These findings reveal an important layer of the unique exercise mode–dependent changes in muscle metabolism, which may eventually lead to more informed exercise prescription for improving SI.

Few proton magnetic resonance spectroscopy studies have explored chemotherapy-related biochemical changes in brain regions. This observational study aimed to longitudinally assess short-term cognitive changes and brain metabolite concentrations in women undergoing chemotherapy for breast cancer. We analyzed 11 women with newly diagnosed stage 1 to 3 breast cancer. Patients were evaluated via objective cognitive testing, and patient self-report tests. Patients were examined using single voxel proton magnetic resonance spectroscopy in the medial frontal cortex, posterior cingulate gyrus, and left thalamus at baseline and after the completion of chemotherapy on a 1.5 Tesla scanner. At the posttreatment evaluation as compared to baseline, 7 of the 10 (70%) patients reported worsening memory on the MD Anderson symptom inventory (annualized change = 1.82 ± 2.88, P = .08), while the delayed recall raw score of the Rey Osterrieth complex figure test did not change from pre- to post-chemotherapy (mean annualized change = 5.00 ± 14.38, P = .30). The annualized change in the creatine concentration in the posterior cingulate gyrus was statistically significant. The annualized change in the MD Anderson symptom inventory was negatively correlated with the annualized change in the medial frontal N-acetylaspartate (Spearman correlation coefficient [rho] = −0.78, P = .01) and positively correlated with the annualized change in the posterior cingulate gyrus creatine (rho = 0.66, P = .04). Annualized changes in the Rey Osterrieth complex figure test were positively correlated with annualized changes in choline (rho = 0.83, P = .01) in the medial frontal cortex, choline (rho = 0.76, P = .04) in the left thalamus, and creatine (rho = 0.73, P = .02) in the medial frontal cortex. Our data suggest that chemotherapy may lead to the worsening of self-reported memory function, which is associated with alterations in brain metabolites.

Objective and Background: Clinically significant posthepatectomy liver failure (PHLF B+C) remains the main cause of mortality after major hepatic resection. This study aimed to establish an aspartate aminotransferase to platelet ratio combined with an albumin-bilirubin grade (APRI+ALBI), based multivariable model (MVM) to predict PHLF and compare its performance to indocyanine green clearance (ICG-R15 or ICG-PDR) and albumin-ICG evaluation (ALICE). Methods: A total of 12,056 patients from the National Surgical Quality Improvement Program database were used to generate a MVM to predict PHLF B+C. The model was determined using stepwise backwards elimination. The performance of the model was tested using receiver operating characteristic curve analysis and validated in an international cohort of 2525 patients. In 620 patients, the APRI+ALBI MVM, trained in the National Surgical Quality Improvement Program cohort, was compared with the MVM’s based on other liver function tests (ICG clearance, ALICE) by comparing the areas under the curve (AUC). Results: A MVM including APRI+ALBI, age, sex, tumor type, and extent of resection was found to predict PHLF B+C with an AUC of 0.77, with comparable performance in the validation cohort (AUC: 0.74). In direct comparison with other MVM’s based on more expensive and time-consuming liver function tests (ICG clearance, ALICE), the APRI+ALBI MVM demonstrated equal predictive potential for PHLF B+C. A smartphone application for the calculation of the APRI+ALBI MVM was designed. Conclusion: Risk assessment through the APRI+ALBI MVM for PHLF B+C increases preoperative predictive accuracy and represents a universally available and cost-effective risk assessment before hepatectomy, facilitated by a freely available smartphone app.

The chimeric antigen receptor (CAR) design, first invented by Zelig Eshhar, paved the way for the use of genetically modified T-cells in targeted therapy against cancer cells. Since then, it has gone through many generations, especially with the integration of co-stimulation in the second and third-generation CARs. However, it also mounts a hyperactive immune response named as cytokine release syndrome with the release of several cytokines eventually resulting in multiple end-organ toxicities. The severity of cytokine release syndrome depends upon certain factors such as the tumor burden, choice of co-stimulation, and degree of lymphodepletion, and can manifest as pulmonary edema, vascular leak, renal dysfunction, cardiac problems, hepatic failure, and coagulopathy. Many grading criteria have been used to define these clinical manifestations but they lack harmonization. Neurotoxicity has also been significantly associated with CAR T-cell therapy but it has not been studied much in previous literature. This review aims to provide a comprehensive account of the clinical manifestations, diagnosis, management, and treatment of CAR T-cell associated neurotoxicity.

Purpose of review Acute kidney injury (AKI) is a highly prevalent clinical syndrome that substantially impacts patient outcomes. It is accepted by the clinical communities that the management of AKI is time-sensitive. Unfortunately, despite growing proof of its preventability, AKI management remains suboptimal in community, acute care, and postacute care settings. Digital health solutions comprise various tools and models to improve care processes and patient outcomes in multiple medical fields. AKI development, progression, recovery, or lack thereof, offers tremendous opportunities for developing, validating, and implementing digital health solutions in multiple settings. This article will review the definitions and components of digital health, the characteristics of AKI that allow digital health solutions to be considered, and the opportunities and threats in implementing these solutions. Recent findings Over the past two decades, the academic output related to the use of digital health solutions in AKI has exponentially grown. While this indicates the growing interest in the topic, most topics are primarily related to clinical decision support by detecting AKI within hospitals or using artificial intelligence or machine learning technologies to predict AKI within acute care settings. However, recently, projects to assess the impact of digital health solutions in more complex scenarios, for example, managing nephrotoxins among adults of pediatric patients who already have AKI, is increasing. Depending on the type of patients, chosen digital health solution intervention, comparator groups, and selected outcomes, some of these studies showed benefits, while some did not indicate additional gain in care processes or clinical outcomes. Summary Careful needs assessment, selection of the correct digital health solution, and appropriate clinical validation of the benefits while avoiding additional health disparities are moral, professional, and ethical obligations for all individuals using these healthcare tools, including clinicians, data scientists, and administrators.

Since hemorrhage is a leading cause of preventable death in both civilian and military settings, the development of advanced decision support monitoring capabilities is necessary to promote improved clinical outcomes. The emergence of lower body negative pressure (LBNP) has provided a bioengineering technology for inducing progressive reductions in central blood volume shown to be accurate as a model for the study of the early compensatory stages of hemorrhage. In this context, the specific aim of this study was to provide for the first time a systematic technical evaluation to meet a commonly accepted engineering standard based on the FDA-recognized Standard for Assessing Credibility of Modeling through Verification and Validation (V&V) for Medical Devices (ASME standard V&V 40) specifically highlighting LBNP as a valuable resource for the safe study of hemorrhage physiology in humans. As an experimental tool, evidence is presented that LBNP is credible, repeatable, and validated as an analog for the study of human hemorrhage physiology compared to actual blood loss. The LBNP tool can promote the testing and development of advanced monitoring algorithms and evaluating wearable sensors with the goal of improving clinical outcomes during use in emergency medical settings.

In this paper we report on the inaugural meetings of the Musical Care International Network held online in 2022. The term “musical care” is defined by Spiro and Sanfilippo (2022) as “the role of music—music listening as well as music-making—in supporting any aspect of people's developmental or health needs” (pp. 2–3). Musical care takes varied forms in different cultural contexts and involves people from different disciplines and areas of expertise. Therefore, the Musical Care International Network takes an interdisciplinary and international approach and aims to better reflect the disciplinary, geographic, and cultural diversity relevant to musical care. Forty-two delegates participated in 5 inaugural meetings over 2 days, representing 24 countries and numerous disciplines and areas of practice. Based on the meetings, the aims of this paper are to (1) better understand the diverse practices, applications, contexts, and impacts of musical care around the globe and (2) introduce the Musical Care International Network. Transcriptions of the recordings, alongside notes taken by the hosts, were used to summarise the conversations. The discussions developed ideas in three areas: (a) musical care as context-dependent and social, (b) musical care's position within the broader research and practice context, and (c) debates about the impact of and evidence for musical care. We can conclude that musical care refers to context-dependent and social phenomena. The term musical care was seen as useful in talking across boundaries while not minimizing individual disciplinary and professional expertise. The use of the term was seen to help balance the importance and place of multiple disciplines, with a role to play in the development of a collective identity. This collective identity was seen as important in advocacy and in helping to shape policy. The paper closes with proposed future directions for the network and its emerging mission statement.

Acral melanoma (AM) has distinct characteristics as compared with cutaneous melanoma and exhibits poor response to immune checkpoint inhibitors (ICIs). Tumor-intrinsic mechanisms of immune exclusion have been identified in many cancers but less studied in AM. We characterized clinically annotated tumors from patients diagnosed with AM at our institution in correlation with ICI response using whole transcriptome RNAseq, whole exome sequencing, CD8 immunohistochemistry, and multispectral immunofluorescence imaging. A defined interferon-γ-associated T cell-inflamed gene signature was used to categorize tumors into non-T cell-inflamed and T cell-inflamed phenotypes. In combination with AM tumors from two published studies, we systematically assessed the immune landscape of AM and detected differential gene expression and pathway activation in a non-T cell-inflamed tumor microenvironment (TME). Two single-cell(sc) RNAseq AM cohorts and 11 bulk RNAseq cohorts of various tumor types were used for independent validation on pathways associated with lack of ICI response. In total, 892 specimens were included in this study. 72.5% of AM tumors showed low expression of the T cell-inflamed gene signature, with 23.9% of total tumors categorized as the non-T cell-inflamed phenotype. Patients of low CD3 + CD8 + PD1 + intratumoral T cell density showed poor prognosis. We identified 11 oncogenic pathways significantly upregulated in non-T cell-inflamed relative to T cell-inflamed TME shared across all three acral cohorts (MYC, HGF, MITF, VEGF, EGFR, SP1, ERBB2, TFEB, SREBF1, SOX2, and CCND1). scRNAseq analysis revealed that tumor cell-expressing pathway scores were significantly higher in low versus high T cell-infiltrated AM tumors. We further demonstrated that the 11 pathways were enriched in ICI non-responders compared with responders across cancers, including AM, cutaneous melanoma, triple-negative breast cancer, and non-small cell lung cancer. Pathway activation was associated with low expression of interferon stimulated genes, suggesting suppression of antigen presentation. Across the 11 pathways, fatty acid synthase and CXCL8 were unifying downstream target molecules suggesting potential nodes for therapeutic intervention. A unique set of pathways is associated with immune exclusion and ICI resistance in AM. These data may inform immunotherapy combinations for immediate clinical translation.