Identifying biochemical changes in the kidney using proton nuclear magnetic resonance in an adenine diet chronic kidney disease mouse model.

This study aimed to investigate the metabolic changes in the kidneys in a murine adenine-diet model of chronic kidney disease (CKD). Kidney fibrosis is the common pathological manifestation across CKD aetiologies. Sustained inflammation and fibrosis cause changes in preferred energy metabolic pathways in the cells of the kidney. Kidney cortical tissue from mice receiving a control or adenine-supplemented diet for 8 weeks (late inflammation and fibrosis) and 12 weeks (8 weeks of treatment followed by 4 weeks recovery) were analysed by 2D-correlated nuclear magnetic resonance spectroscopy and compared with histopathology and biomarkers of kidney damage. Tissue metabolite and lipid levels were assessed using the MestreNova software. Expression of genes related to inflammation, fibrosis, and metabolism were measured using quantitative polymerase chain reaction. Animals showed indicators of severely impaired kidney function at 8 and 12 weeks. Significantly increased fibrosis was present at 8 weeks but not in the recovery group suggesting some reversal of fibrosis and amelioration of inflammation. At 8 weeks, metabolites associated with glycolysis were increased, while lipid signatures were decreased. Genes involved in fatty acid oxidation were decreased at 8 weeks but not 12 weeks while genes associated with glycolysis were significantly increased at 8 weeks but not at 12 weeks. In this murine model of CKD, kidney fibrosis was associated with the accumulation of triglyceride and free lactate. There was an up-regulation of glycolytic enzymes and down-regulation of lipolytic enzymes. These metabolic changes reflect the energy demands associated with progressive kidney disease where there is a switch from fatty acid oxidation to that of glycolysis.

Heat hardening improves thermal tolerance in abalone, without the trade-offs associated with chronic heat exposure.

Marine animals are challenged by chronically raised temperatures alongside an increased frequency of discrete, severe warming events. Exposure to repeated heat shocks could result in heat hardening, where sub-lethal exposure to thermal stress temporarily enhances thermotolerance, and may be an important mechanism by which marine species will cope with future thermal challenges. However, we have relatively little understanding of the effects of heat hardening in comparison to chronic exposure to elevated temperatures. Therefore, we compared the effects of heat hardening from repeated exposure to acute heat shocks and chronic exposure to elevated temperatures on thermal tolerance in the European abalone, Haliotis tuberculata. Adult abalones were exposed to either control temperature (15 °C), chronic warming (20 °C) or a regime of two events of repeated acute heat shock cycles (23-25 °C) during six months, and their thermal tolerance and performance, based upon cardiac activity, compared using a dynamic ramping assay. The cost associated with each treatment was also estimated via measurements of condition index (CI). Abalone exposed to both temperature treatments had higher upper thermal limits than the control, but heat-hardened individuals had significantly higher CI values, indicating an enhancement in condition status. Differences in the shape of the thermal performance curve suggest different mechanisms may be at play under different temperature exposure treatments. We conclude that heat hardening can boost thermal tolerance in this species, without performance trade-offs associated with chronic warming.

Prevalence of alcohol use disorders documented in electronic health records in primary care across intersections of race or ethnicity, sex, and socioeconomic status.

BACKGROUND: Diagnosis of alcohol use disorder (AUD) in primary care is critical for increasing access to alcohol treatment. However, AUD is underdiagnosed and may be inequitably diagnosed due to societal structures that determine access to resources (e.g., structural racism that limits opportunities for some groups and influences interpersonal interactions in and beyond health care). This study described patterns of provider-documented AUD in primary care across intersections of race, ethnicity, sex, and community-level socioeconomic status (SES). METHODS: This cross-sectional study used EHR data from a regional healthcare system with 35 primary care clinics that included adult patients who completed alcohol screenings between 3/1/2015 and 9/30/2020. The prevalence of provider-documented AUD in primary care based on International Classification of Diseases-9 (ICD-9) and ICD-10 diagnoses was compared across intersections of race, ethnicity, sex, and community-level SES. RESULTS: Among 439,375 patients, 6.6% were Latine, 11.0% Asian, 5.4% Black, 1.3% Native Hawaiian/Pacific Islander (NH/PI), 1.5% American Indian/Alaska Native (AI/AN), and 74.2% White, and 58.3% women. The overall prevalence of provider-documented AUD was 1.0% and varied across intersecting identities. Among women, the prevalence was highest for AI/AN women with middle SES, 1.5% (95% CI 1.0-2.3), and lowest for Asian women with middle SES, 0.1% (95% CI 0.1-0.2). Among men, the prevalence was highest for AI/AN men with high and middle SES, 2.0% (95% CI 1.1-3.4) and 2.0% (95% CI 1.2-3.2), respectively, and lowest for Asian men with high SES, 0.5% (95% CI 0.3-0.7). Black and Latine patients tended to have a lower prevalence of AUD than White patients, across all intersections of sex and SES except for Black women with high SES. There were no consistent patterns of the prevalence of AUD diagnosis that emerged across SES. CONCLUSION: The prevalence of provider-documented AUD in primary care was highest in AI/AN men and women and lowest in Asian men and women. Findings of lower prevalence of provider-documented AUD in Black and Hispanic than White patients across most intersections of sex and SES differed from prior studies. Findings may suggest that differences in access to resources, which vary in effects across these identity characteristics and lived experiences, influence the diagnosis of AUD in clinical care.

Receipt of Medications for Alcohol Use Disorder in the Veterans Health Administration: Comparison of Rates at the Intersections of Racialized and Ethnic Identity With Both Sex and Transgender Status.

OBJECTIVES: Medications for alcohol use disorder (MAUDs) are recommended for patients with alcohol use disorder yet are underprescribed. Consistent with Minority Stress and Intersectionality theories, persons with multiple sociodemographically marginalized identities (eg, Black women) often experience greater barriers to care and have poorer health outcomes. We use data from the Veterans Health Administration to assess disparities in Federal Drug Administration (FDA)-approved MAUDs and all effective MAUDs between the following groups: racialized and ethnic identity, sex, transgender status, and their intersections. METHODS: Among all Veterans Health Administration outpatients between August 1, 2015, and July 31, 2017, with documented alcohol screenings and an International Classification of Diseases diagnosis for alcohol use disorder in the 0-365 days prior (N = 308,238), we estimated the prevalence and 95% confidence intervals of receiving FDA-approved MAUDs and any MAUDs in the following year and compared them using χ2 or Fisher's exact test. Analyses are unadjusted to present true prevalence and group differences. RESULTS: The overall prevalence for MAUDs was low (FDA-MAUDs = 8.7%, any MAUDs = 20.0%). Within sex, Black males had the lowest rate of FDA-MAUDs (7.3%, [7.1-7.5]), whereas American Indian/Alaskan Native females had the highest (18.4%, [13.8-23.0]). Among those identified as transgender, Asian and Black transgender persons had the lowest rates of FDA-MAUDs (0%; 4.3%, [1.8-8.5], respectively), whereas American Indian/Alaskan Native transgender patients had the highest (33.3%, [2.5-64.1]). Similar patterns were observed for any MAUDs, with higher rates overall. CONCLUSIONS: Substantial variation exists in MAUD prescribing, with marginalized veterans disproportionately receiving MAUDs at lower and higher rates than average. Implementation and quality improvement efforts are needed to improve MAUD prescribing practices and reduce disparities.

Analysis of risk factors for late arteriovenous fistula failure and patency rates after angioplasty in hemodialysis patients: a retrospective cohort study.

Background: The incidence of chronic kidney disease (CKD) and end-stage kidney disease (ESKD) is increasing worldwide. Hemodialysis (HD) is the mainstay of renal replacement therapy for patients with ESKD. Risk factors associated with late arteriovenous fistula (AVF) failure in HD patients are poorly investigated. Therefore, the aim of this study was to identify factors associated with late AVF failure in HD patients. Methods: Patients with end-stage renal disease (ESRD) who underwent forearm or upper arm AVF angioplasty at Second Affiliated Hospital of Chongqing Medical University between September 2009 and August 2018 were included. Patients were followed up for 36 months. Baseline characteristics were collected using electronic medical records (EMRs). Variables associated with late AVF failure were identified using Cox proportional hazards models. Results: There were 137 patients (64% male, 36% female) included in this study, with 50 (36.5%) experiencing AVF failure. Univariable log-rank analysis showed that age, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), intact parathyroid hormone (iPTH), albumin (ALB), and AVF patency rate were significantly different between patients who did and did not experience AVF failure. Cox regression analysis showed that CRP [P=0.002, hazard ratio (HR) =2.719, 95% confidence interval (CI) for HR: 1.432-5.164], ESR (P=0.030, HR =2.431, 95% CI: 1.088-5.434), iPTH (P=0.013, HR =0.325, 95% CI: 0.133-0.793), and ALB (P=0.040, HR =0.539, 95% CI: 0.299-0.972) were independently associated with AVF failure. Kaplan-Meier survival analysis showed that the cumulative patency rates of AVF at 6, 12, 18, 24, 30, and 36 months were 84%, 74%, 69%, 64%, 64%, and 64%, respectively. Conclusions: CRP, ESR, iPTH, and ALB were associated with AVF failure and should be used as reference in clinical practice.

A proposed multi-domain, digital model for capturing functional status and health-related quality of life in oncology.

Whereas traditional oncology clinical trial endpoints remain key for assessing novel treatments, capturing patients' functional status is increasingly recognized as an important aspect for supporting clinical decisions and assessing outcomes in clinical trials. Existing functional status assessments suffer from various limitations, some of which may be addressed by adopting digital health technologies (DHTs) as a means of collecting both objective and self-reported outcomes. In this mini-review, we propose a device-agnostic multi-domain model for oncology capturing functional status, which includes physical activity data, vital signs, sleep variables, and measures related to health-related quality of life enabled by connected digital tools. By using DHTs for all aspects of data collection, our proposed model allows for high-resolution measurement of objective data as patients navigate their daily lives outside of the hospital setting. This is complemented by electronic questionnaires administered at intervals appropriate for each instrument. Preliminary testing and practical considerations to address before adoption are also discussed. Finally, we highlight multi-institutional pre-competitive collaborations as a means of successfully transitioning the proposed digitally enabled data collection model from feasibility studies to interventional trials and care management.

Predictive accuracy of risk prediction models for recurrence, metastasis and survival for early-stage cutaneous melanoma: a systematic review.

OBJECTIVES: To identify prognostic models for melanoma survival, recurrence and metastasis among American Joint Committee on Cancer stage I and II patients postsurgery; and evaluate model performance, including overall survival (OS) prediction. DESIGN: Systematic review and narrative synthesis. DATA SOURCES: Searched MEDLINE, Embase, CINAHL, Cochrane Library, Science Citation Index and grey literature sources including cancer and guideline websites from 2000 to September 2021. ELIGIBILITY CRITERIA: Included studies on risk prediction models for stage I and II melanoma in adults ≥18 years. Outcomes included OS, recurrence, metastases and model performance. No language or country of publication restrictions were applied. DATA EXTRACTION AND SYNTHESIS: Two pairs of reviewers independently screened studies, extracted data and assessed the risk of bias using the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies checklist and the Prediction study Risk of Bias Assessment Tool. Heterogeneous predictors prevented statistical synthesis. RESULTS: From 28 967 records, 15 studies reporting 20 models were included; 8 (stage I), 2 (stage II), 7 (stages I-II) and 7 (stages not reported), but were clearly applicable to early stages. Clinicopathological predictors per model ranged from 3-10. The most common were: ulceration, Breslow thickness/depth, sociodemographic status and site. Where reported, discriminatory values were ≥0.7. Calibration measures showed good matches between predicted and observed rates. None of the studies assessed clinical usefulness of the models. Risk of bias was high in eight models, unclear in nine and low in three. Seven models were internally and externally cross-validated, six models were externally validated and eight models were internally validated. CONCLUSIONS: All models are effective in their predictive performance, however the low quality of the evidence raises concern as to whether current follow-up recommendations following surgical treatment is adequate. Future models should incorporate biomarkers for improved accuracy. PROSPERO REGISTRATION NUMBER: CRD42018086784.

High risk clear cell renal cell carcinoma microenvironments contain protumour immunophenotypes lacking specific immune checkpoints.

Perioperative immune checkpoint inhibitor (ICI) trials for intermediate high-risk clear cell renal cell carcinoma (ccRCC) have failed to consistently demonstrate improved patient outcomes. These unsuccessful ICI trials suggest that the tumour infiltrating immunophenotypes, termed here as the immune cell types, states and their spatial location within the tumour microenvironment (TME), were unfavourable for ICI treatment. Defining the tumour infiltrating immune cells may assist with the identification of predictive immunophenotypes within the TME that are favourable for ICI treatment. To define the immunophenotypes within the ccRCC TME, fresh para-tumour (pTME, n = 2), low-grade (LG, n = 4, G1-G2) and high-grade (HG, n = 4, G3-G4) tissue samples from six patients with ccRCC presenting at a tertiary referral hospital underwent spatial transcriptomics sequencing (ST-seq). Within the generated ST-seq datasets, immune cell types and states, termed here as exhausted/pro-tumour state or non-exhausted/anti-tumour state, were identified using multiple publicly available single-cell RNA and T-cell receptor sequencing datasets as references. HG TMEs revealed abundant exhausted/pro-tumour immune cells with no consistent increase in expression of PD-1, PD-L1 and CTLA4 checkpoints and angiogenic genes. Additional HG TME immunophenotype characteristics included: pro-tumour tissue-resident monocytes with consistently increased expression of HAVCR2 and LAG3 checkpoints; an exhausted CD8+ T cells sub-population with stem-like progenitor gene expression; and pro-tumour tumour-associated macrophages and monocytes within the recurrent TME with the expression of TREM2. Whilst limited by a modest sample size, this study represents the largest ST-seq dataset on human ccRCC. Our study reveals that high-risk ccRCC TMEs are infiltrated by exhausted/pro-tumour immunophenotypes lacking specific checkpoint gene expression confirming that HG ccRCC TME are immunogenic but not ICI favourable.

Self-reported and digital-trace measures of computer science students' self-regulated learning in blended course designs.

This study investigated the extent to which self-report and digital-trace measures of students' self-regulated learning in blended course designs align with each other amongst 145 first-year computer science students in a blended "computer systems" course. A self-reported Motivated Strategies for Learning Questionnaire was used to measure students' self-efficacy, intrinsic motivation, test anxiety, and use of self-regulated learning strategies. Frequencies of interactions with six different online learning activities were digital-trace measures of students' online learning interactions. Students' course marks were used to represent their academic performance. SPSS 28 was used to analyse the data. A hierarchical cluster analysis using self-reported measures categorized students as better or poorer self-regulated learners; whereas a hierarchical cluster analysis using digital-trace measures clustered students as more active or less active online learners. One-way ANOVAs showed that: 1) better self-regulated learners had higher frequencies of interactions with three out of six online learning activities than poorer self-regulated learners. 2) More active online learners reported higher self-efficacy, higher intrinsic motivation, and more frequent use of positive self-regulated learning strategies, than less active online learners. Furthermore, a cross-tabulation showed significant (p < .01) but weak association between student clusters identified by self-reported and digital-trace measures, demonstrating self-reported and digital-trace descriptions of students' self-regulated learning experiences were consistent to a limited extent. To help poorer self-regulated learners improve their learning experiences in blended course designs, teachers may invite better self-regulated learners to share how they approach learning in class.

SNP discovery and genetic structure in blue mussel species using low coverage sequencing and a medium density 60 K SNP-array.

Blue mussels from the genus Mytilus are an abundant component of the benthic community, found in the high latitude habitats. These foundation species are relevant to the aquaculture industry, with over 2 million tonnes produced globally each year. Mussels withstand a wide range of environmental conditions and species from the Mytilus edulis complex readily hybridize in regions where their distributions overlap. Significant effort has been made to investigate the consequences of environmental stress on mussel physiology, reproductive isolation, and local adaptation. Yet our understanding on the genomic mechanisms underlying such processes remains limited. In this study, we developed a multi species medium-density 60 K SNP-array including four species of the Mytilus genus. SNPs included in the platform were called from 138 mussels from 23 globally distributed mussel populations, sequenced using a whole-genome low coverage approach. The array contains polymorphic SNPs which capture the genetic diversity present in mussel populations thriving across a gradient of environmental conditions (~59 K SNPs) and a set of published and validated SNPs informative for species identification and for diagnosis of transmissible cancer (610 SNPs). The array will allow the consistent genotyping of individuals, facilitating the investigation of ecological and evolutionary processes in these taxa. The applications of this array extend to shellfish aquaculture, contributing to the optimization of this industry via genomic selection of blue mussels, parentage assignment, inbreeding assessment and traceability. Further applications such as genome wide association studies (GWAS) for key production traits and those related to environmental resilience are especially relevant to safeguard aquaculture production under climate change.