An Enriched Environment Improves Sensorimotor Function Post-Ischemic Stroke

Objective. An enriched environment (EE) refers to conditions that facilitate or enhance sensory, cognitive, motor, and social stimulation relative to standard (laboratory) conditions. Despite numerous published studies investigating this concept in animal stroke models, there is still debate around its efficacy. The authors performed a systematic review and meta-analysis to determine the efficacy of an EE on neurobehavioral scores, learning, infarct size, and mortality in animal models of ischemic stroke. Methods. Systematic review of controlled studies of the use of an EE in experimental stroke was conducted. Data extracted were analyzed using weighted mean difference meta-analysis. For pooled tests of neurobehavioral scores, a random effects standardized method was used. Results. Animals recovering in an EE poststroke had mean neurobehavioral scores 0.9 standard deviations (95% confidence interval [CI] = 0.5-1.3; P &lt; .001) above the mean scores of animals recovering in standard conditions and showed a trend toward improvement in learning (25.1% improvement; 95% CI = 3.7-46.6; P = .02). There was no significant increase in death. Animals exposed to an EE had 8.0% larger infarcts than control animals (95% CI = 1.8-14.1; P = .015). Conclusions. The results indicate significant improvements in sensorimotor function with EE poststroke but suggest a small increase in infarct volume. Clarification of the underlying mechanisms requires further study but should not overshadow the observed functional improvements and their application to clinical trials during stroke rehabilitation.</p

Statistical competencies for medical research learners: What is fundamental?

IntroductionIt is increasingly essential for medical researchers to be literate in statistics, but the requisite degree of literacy is not the same for every statistical competency in translational research. Statistical competency can range from 'fundamental' (necessary for all) to 'specialized' (necessary for only some). In this study, we determine the degree to which each competency is fundamental or specialized.MethodsWe surveyed members of 4 professional organizations, targeting doctorally trained biostatisticians and epidemiologists who taught statistics to medical research learners in the past 5 years. Respondents rated 24 educational competencies on a 5-point Likert scale anchored by 'fundamental' and 'specialized.'ResultsThere were 112 responses. Nineteen of 24 competencies were fundamental. The competencies considered most fundamental were assessing sources of bias and variation (95%), recognizing one's own limits with regard to statistics (93%), identifying the strengths, and limitations of study designs (93%). The least endorsed items were meta-analysis (34%) and stopping rules (18%).ConclusionWe have identified the statistical competencies needed by all medical researchers. These competencies should be considered when designing statistical curricula for medical researchers and should inform which topics are taught in graduate programs and evidence-based medicine courses where learners need to read and understand the medical research literature

Innate immune responses and antioxidant/oxidant imbalance are major determinants of human Chagas disease.

We investigated the pathological and diagnostic role of selected markers of inflammation, oxidant/antioxidant status, and cellular injury in human Chagas disease. METHODS: Seropositive/chagasic subjects characterized as clinically-symptomatic or clinically-asymptomatic (n = 116), seronegative/cardiac subjects (n = 102), and seronegative/healthy subjects (n = 45) were analyzed for peripheral blood biomarkers. RESULTS: Seropositive/chagasic subjects exhibited an increase in sera or plasma levels of myeloperoxidase (MPO, 2.8-fold), advanced oxidation protein products (AOPP, 56%), nitrite (5.7-fold), lipid peroxides (LPO, 12-17-fold) and malondialdehyde (MDA, 4-6-fold); and a decline in superoxide dismutase (SOD, 52%) and glutathione (GSH, 75%) contents. Correlation analysis identified a significant (p0.95). The MPO (r = 0.664) and LPO (r = 0.841) levels were also correlated with clinical disease state in chagasic subjects (p<0.001). Seronegative/cardiac subjects exhibited up to 77% decline in SOD, 3-5-fold increase in LPO and glutamate pyruvate transaminase (GPT) levels, and statistically insignificant change in MPO, AOPP, MDA, GPX, GSH, and creatine kinase (CK) levels. CONCLUSIONS: The interlinked effects of innate immune responses and antioxidant/oxidant imbalance are major determinants of human Chagas disease. The MPO, LPO and nitrite are excellent biomarkers for diagnosing seropositive/chagasic subjects, and MPO and LPO levels have potential utility in identifying clinical severity of Chagas diseaseFil: Dhiman, Monisha. University Of Texas Medical Branch. Department Of Microbiology & Immunology And Pathology; United State of America;Fil: Coronado, Yun A.. University Of Texas Medical Branch. Department Of Microbiology & Immunology And Pathology; United State of America;Fil: Vallejo, Cecilia K.. University Of Texas Medical Branch. Department Of Microbiology & Immunology And Pathology; United State of America;Fil: Petersen, John R.. University of Texas Medical Branch. Department of Pathology; United States of America;Fil: Ejilemele, Adetoum. University of Texas Medical Branch. Department of Pathology; United States of America;Fil: Nuñez, Sonia. Hospital Público de Gestión Descentralizada San Bernardo (HPGDSA); Argentina;Fil: Zago, María Paola. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - CONICET - Salta. Instituto de Patologia Experimental; Argentina;Fil: Spratt, Heidi. Departments of Biochemistry and Molecular Biology and Preventive Medicine and Community Health. University of Texas Medical Branch; United States of America;Fil: Garg, Nisha Jain. University of Texas Medical Branch. Department of Pathology; United States of America

Heterogeneity in Intrahepatic Macrophage Populations and Druggable Target Expression in Patients With Steatotic Liver Disease-Related Fibrosis

BACKGROUND & AIMS: Clinical trials for reducing fibrosis in steatotic liver disease (SLD) have targeted macrophages with variable results. We evaluated intrahepatic macrophages in patients with SLD to determine if activity scores or fibrosis stages influenced phenotypes and expression of druggable targets, such as CCR2 and galectin-3. METHODS: Liver biopsies from controls or patients with minimal or advanced fibrosis were subject to gene expression analysis using nCounter to determine differences in macrophage-related genes (n = 30). To investigate variability among individual patients, we compared additional biopsies by staining them with multiplex antibody panels (CD68/CD14/CD16/CD163/Mac387 or CD163/CCR2/galectin-3/Mac387) followed by spectral imaging and spatial analysis. Algorithms that utilize deep learning/artificial intelligence were applied to create cell cluster plots, phenotype profile maps, and to determine levels of protein expression (n = 34). RESULTS: Several genes known to be pro-fibrotic ( CONCLUSIONS: Patients with SLD have markedly varied macrophage- and druggable target-related gene and protein expression in their livers. Several patients had relatively high expression, while others were like controls. Overall, patients with more advanced disease had significantly higher expression of CCR2 and galectin-3 at both the gene and protein levels. IMPACT AND IMPLICATIONS: Appreciating individual differences within the hepatic microenvironment of patients with SLD may be paramount to developing effective treatments. These results may explain why such a small percentage of patients have responded to macrophage-targeting therapies and provide additional support for precision medicine-guided treatment of chronic liver diseases

Heterogeneity in Intrahepatic Macrophage Populations and Druggable Target Expression in Patients With Steatotic Liver Disease-Related Fibrosis

BACKGROUND & AIMS: Clinical trials for reducing fibrosis in steatotic liver disease (SLD) have targeted macrophages with variable results. We evaluated intrahepatic macrophages in patients with SLD to determine if activity scores or fibrosis stages influenced phenotypes and expression of druggable targets, such as CCR2 and galectin-3. METHODS: Liver biopsies from controls or patients with minimal or advanced fibrosis were subject to gene expression analysis using nCounter to determine differences in macrophage-related genes (n = 30). To investigate variability among individual patients, we compared additional biopsies by staining them with multiplex antibody panels (CD68/CD14/CD16/CD163/Mac387 or CD163/CCR2/galectin-3/Mac387) followed by spectral imaging and spatial analysis. Algorithms that utilize deep learning/artificial intelligence were applied to create cell cluster plots, phenotype profile maps, and to determine levels of protein expression (n = 34). RESULTS: Several genes known to be pro-fibrotic ( CONCLUSIONS: Patients with SLD have markedly varied macrophage- and druggable target-related gene and protein expression in their livers. Several patients had relatively high expression, while others were like controls. Overall, patients with more advanced disease had significantly higher expression of CCR2 and galectin-3 at both the gene and protein levels. IMPACT AND IMPLICATIONS: Appreciating individual differences within the hepatic microenvironment of patients with SLD may be paramount to developing effective treatments. These results may explain why such a small percentage of patients have responded to macrophage-targeting therapies and provide additional support for precision medicine-guided treatment of chronic liver diseases

Toward Standardization, Harmonization, and Integration of Social Determinants of Health Data: A Texas Clinical and Translational Science Award Institutions Collaboration

INTRODUCTION: The focus on social determinants of health (SDOH) and their impact on health outcomes is evident in U.S. federal actions by Centers for Medicare & Medicaid Services and Office of National Coordinator for Health Information Technology. The disproportionate impact of COVID-19 on minorities and communities of color heightened awareness of health inequities and the need for more robust SDOH data collection. Four Clinical and Translational Science Award (CTSA) hubs comprising the Texas Regional CTSA Consortium (TRCC) undertook an inventory to understand what contextual-level SDOH datasets are offered centrally and which individual-level SDOH are collected in structured fields in each electronic health record (EHR) system potentially for all patients. METHODS: Hub teams identified American Community Survey (ACS) datasets available via their enterprise data warehouses for research. Each hub\u27s EHR analyst team identified structured fields available in their EHR for SDOH using a collection instrument based on a 2021 PCORnet survey and conducted an SDOH field completion rate analysis. RESULTS: One hub offered ACS datasets centrally. All hubs collected eleven SDOH elements in structured EHR fields. Two collected Homeless and Veteran statuses. Completeness at four hubs was 80%-98%: Ethnicity, Race; \u3c 10%: Education, Financial Strain, Food Insecurity, Housing Security/Stability, Interpersonal Violence, Social Isolation, Stress, Transportation. CONCLUSION: Completeness levels for SDOH data in EHR at TRCC hubs varied and were low for most measures. Multiple system-level discussions may be necessary to increase standardized SDOH EHR-based data collection and harmonization to drive effective value-based care, health disparities research, translational interventions, and evidence-based policy

Toward Standardization, Harmonization, and Integration of Social Determinants of Health Data: A Texas Clinical and Translational Science Award Institutions Collaboration

INTRODUCTION: The focus on social determinants of health (SDOH) and their impact on health outcomes is evident in U.S. federal actions by Centers for Medicare & Medicaid Services and Office of National Coordinator for Health Information Technology. The disproportionate impact of COVID-19 on minorities and communities of color heightened awareness of health inequities and the need for more robust SDOH data collection. Four Clinical and Translational Science Award (CTSA) hubs comprising the Texas Regional CTSA Consortium (TRCC) undertook an inventory to understand what contextual-level SDOH datasets are offered centrally and which individual-level SDOH are collected in structured fields in each electronic health record (EHR) system potentially for all patients. METHODS: Hub teams identified American Community Survey (ACS) datasets available via their enterprise data warehouses for research. Each hub\u27s EHR analyst team identified structured fields available in their EHR for SDOH using a collection instrument based on a 2021 PCORnet survey and conducted an SDOH field completion rate analysis. RESULTS: One hub offered ACS datasets centrally. All hubs collected eleven SDOH elements in structured EHR fields. Two collected Homeless and Veteran statuses. Completeness at four hubs was 80%-98%: Ethnicity, Race; \u3c 10%: Education, Financial Strain, Food Insecurity, Housing Security/Stability, Interpersonal Violence, Social Isolation, Stress, Transportation. CONCLUSION: Completeness levels for SDOH data in EHR at TRCC hubs varied and were low for most measures. Multiple system-level discussions may be necessary to increase standardized SDOH EHR-based data collection and harmonization to drive effective value-based care, health disparities research, translational interventions, and evidence-based policy

Erratum: Toward Standardization, Harmonization, and Integration of Social Determinants of Health Data: A Texas Clinical and Translational Science Award Institutions Collaboration - Corrigendum

This corrects the article Toward standardization, harmonization, and integration of social determinants of health data: A Texas Clinical and Translational Science Award institutions collaboration in volume 8, e17

NSAID use and clinical outcomes in COVID-19 patients: a 38-center retrospective cohort study.

BACKGROUND: Non-steroidal anti-inflammatory drugs (NSAIDs) are commonly used to reduce pain, fever, and inflammation but have been associated with complications in community-acquired pneumonia. Observations shortly after the start of the COVID-19 pandemic in 2020 suggested that ibuprofen was associated with an increased risk of adverse events in COVID-19 patients, but subsequent observational studies failed to demonstrate increased risk and in one case showed reduced risk associated with NSAID use. METHODS: A 38-center retrospective cohort study was performed that leveraged the harmonized, high-granularity electronic health record data of the National COVID Cohort Collaborative. A propensity-matched cohort of 19,746 COVID-19 inpatients was constructed by matching cases (treated with NSAIDs at the time of admission) and 19,746 controls (not treated) from 857,061 patients with COVID-19 available for analysis. The primary outcome of interest was COVID-19 severity in hospitalized patients, which was classified as: moderate, severe, or mortality/hospice. Secondary outcomes were acute kidney injury (AKI), extracorporeal membrane oxygenation (ECMO), invasive ventilation, and all-cause mortality at any time following COVID-19 diagnosis. RESULTS: Logistic regression showed that NSAID use was not associated with increased COVID-19 severity (OR: 0.57 95% CI: 0.53-0.61). Analysis of secondary outcomes using logistic regression showed that NSAID use was not associated with increased risk of all-cause mortality (OR 0.51 95% CI: 0.47-0.56), invasive ventilation (OR: 0.59 95% CI: 0.55-0.64), AKI (OR: 0.67 95% CI: 0.63-0.72), or ECMO (OR: 0.51 95% CI: 0.36-0.7). In contrast, the odds ratios indicate reduced risk of these outcomes, but our quantitative bias analysis showed E-values of between 1.9 and 3.3 for these associations, indicating that comparatively weak or moderate confounder associations could explain away the observed associations. CONCLUSIONS: Study interpretation is limited by the observational design. Recording of NSAID use may have been incomplete. Our study demonstrates that NSAID use is not associated with increased COVID-19 severity, all-cause mortality, invasive ventilation, AKI, or ECMO in COVID-19 inpatients. A conservative interpretation in light of the quantitative bias analysis is that there is no evidence that NSAID use is associated with risk of increased severity or the other measured outcomes. Our results confirm and extend analogous findings in previous observational studies using a large cohort of patients drawn from 38 centers in a nationally representative multicenter database

Potential Utility of Protein Targets of Cysteine-S-Nitrosylation in Identifying Clinical Disease Status in Human Chagas Disease

Trypanosoma cruzi (Tc) infection causes Chagas disease (ChD) presented by dilated cardiomyopathy and heart failure. During infection, oxidative and nitrosative stresses are elicited by the immune cells for control the pathogen; however, excess nitric oxide and superoxide production can result in cysteine S-nitrosylation (SNO) of host proteins that affects cellular homeostasis and may contribute to disease development. To identify the proteins with changes in SNO modification levels as a hallmark of ChD, we obtained peripheral blood mononuclear cells (PBMC) from seronegative, normal healthy (NH, n = 30) subjects, and from seropositive clinically asymptomatic (ChD CA, n = 25) or clinically symptomatic (ChD CS, n = 28) ChD patients. All samples were treated (Asc+) or not-treated (Asc−) with ascorbate (reduces nitrosylated thiols), labeled with the thiol-labeling BODIPY FL-maleimide dye, resolved by two-dimensional electrophoresis (total 166 gels), and the protein spots that yielded significant differences in abundance or SNO level at p-value of ≤ 0.05t−test/Welch/BH were identified by MALDI-TOF/TOF MS or OrbiTrap LC-MS/MS. Targeted analysis of a new cohort of PBMC samples (n = 10–14/group) was conducted to verify the differential abundance/SNO levels of two of the proteins in ChD (vs. NH) subjects. The multivariate adaptive regression splines (MARS) modeling, comparing differences in relative SNO level (Asc−/Asc+ ratio) of the protein spots between any two groups yielded SNO biomarkers that exhibited ≥90% prediction success in classifying ChD CA (582-KRT1 and 884-TPM3) and ChD CS (426-PNP, 582-KRT1, 486-ALB, 662-ACTB) patients from NH controls. Ingenuity Pathway Analysis (IPA) of the SNO proteome dataset normalized to changes in protein abundance suggested the proteins belonging to the signaling networks of cell death and the recruitment and migration of immune cells were most affected in ChD CA and ChD CS (vs. NH) subjects. We propose that SNO modification of the select panel of proteins identified in this study have the potential to identify ChD severity in seropositive individuals exposed to Tc infection