Development of a Spectral Flow Cytometry Analysis Pipeline for High-dimensional Immune Cell Characterization.

Flow cytometry is used for immune cell analysis for cell composition and function. Spectral flow cytometry allows for high-dimensional analysis of immune cells, overcoming limitations of conventional flow cytometry. However, analyzing data from large Ab panels is challenging using traditional biaxial gating strategies. We present, to our knowledge, a novel analysis pipeline to improve analysis of spectral flow cytometry. We employ this method to identify rare T cell populations in aging. We isolated splenocytes from young (2-3 mo old) and aged (18-19 mo old) female C57BL/6N mice and then stained these with a panel of 20 fluorescently labeled Abs. We performed spectral flow cytometry and then data processing and analysis using Python within a Jupyter Notebook environment to perform dimensionality reduction, batch correction, unsupervised clustering, and differential expression analysis. Our analysis of 3,776,804 T cells from 11 spleens revealed 35 distinct T cell clusters identified by surface marker expression. We observed significant differences between young and aged mice, with clusters enriched in one age group over the other. Naive, effector memory, and central memory CD8+ and CD4+ T cell subsets exhibited age-associated changes in abundance and marker expression. We also demonstrate the utility of our pipeline in a human PBMC dataset that used a 50-fluorescent color panel. By leveraging high-dimensional analysis methods, we provide insights into the immune aging process. This approach offers a robust and easily implemented analysis pipeline for spectral flow cytometry data that may facilitate the discovery of novel therapeutic targets for age-related immune dysfunction.

Client perspectives: Telehealth for mental health services.

OBJECTIVE: The COVID-19 pandemic required mental health clinicians globally to transition to the delivery of care via telehealth. This study aimed to gain an understanding of clients' satisfaction with and attitudes towards telehealth mental health services. METHOD: Seventy adults who had attended a clinic for mood and anxiety disorders, and participated in at least one telehealth consultation with a psychologist or psychiatrist, completed an anonymous online survey. RESULTS: The majority of participants (81.5%) reported satisfaction with telehealth mental health care provided during the COVID-19 pandemic. However, satisfaction overall was significantly higher amongst participants who had received both telehealth and face-to-face mental health care, compared to participants who received care via telehealth only. Advantages of telehealth care reported included convenience and increased access to mental health clinicians. However, disadvantages of telehealth care included greater difficulty developing a rapport with a clinician and expressing oneself via telehealth. CONCLUSIONS: Whilst client satisfaction with telehealth mental health care for mood and anxiety disorders is generally high, clinicians should consider the limitations of telehealth from clients' perspectives. In particular, strategies to enhance therapeutic connection during telehealth sessions may be needed, and client preferences for mode of delivery should be taken into consideration when possible.

Development of a Spectral Flow Cytometry Analysis Pipeline for High-Dimensional Immune Cell Characterization.

Flow cytometry is a widely used technique for immune cell analysis, offering insights into cell composition and function. Spectral flow cytometry allows for high-dimensional analysis of immune cells, overcoming limitations of conventional flow cytometry. However, analyzing data from large antibody panels can be challenging using traditional bi-axial gating strategies. Here, we present a novel analysis pipeline designed to improve analysis of spectral flow cytometry. We employ this method to identify rare T cell populations in aging. We isolated splenocytes from young (2-3 months) and aged (18-19 months) female mice then stained these with a panel of 20 fluorescently labeled antibodies. Spectral flow cytometry was performed, followed by data processing and analysis using Python within a Jupyter Notebook environment to perform batch correction, unsupervised clustering, dimensionality reduction, and differential expression analysis. Our analysis of 3,776,804 T cells from 11 spleens revealed 34 distinct T cell clusters identified by surface marker expression. We observed significant differences between young and aged mice, with certain clusters enriched in one age group over the other. Naïve, effector memory, and central memory CD8+ and CD4+ T cell subsets exhibited age-associated changes in abundance and marker expression. Additionally, γδ T cell clusters showed differential abundance between age groups. By leveraging high-dimensional analysis methods borrowed from single-cell RNA sequencing analysis, we identified age-related differences in T cell subsets, providing insights into the immune aging process. This approach offers a robust, free, and easily implemented analysis pipeline for spectral flow cytometry data that may facilitate the discovery of novel therapeutic targets for age-related immune dysfunction.

An Exogenous Ketone Ester Slows Tumor Progression in Murine Breast and Renal Cancer Models.

BACKGROUND/OBJECTIVES: Ketone esters (KEs) exhibit promise as anti-cancer agents but their impact on spontaneous metastases remains poorly understood. Although consumption of a ketogenic diet (KD) that is low in carbohydrates and high in fats can lead to KE production in vivo, the restrictive composition of KDs may diminish adherence in cancer patients. METHODS: We investigated the effects of an exogenous ketone ester-supplemented (eKET), carbohydrate-replete diet on tumor growth, metastasis, and underlying mechanisms in orthotopic models of metastatic breast (4T1-Luc) and renal (Renca-Luc) carcinomas. Mice were randomized to diet after tumor challenge. RESULTS: Administration of KEs did not alter tumor cell growth in vitro. However, in mice, our eKET diet increased circulating ß-hydroxybutyrate and inhibited primary tumor growth and lung metastasis in both models. Body composition analysis illustrated the overall safety of eKET diet use, although it was associated with a loss of fat mass in mice with renal tumors. Immunogenetic profiling revealed divergent intratumoral eKET-related changes by tumor type. In mammary tumors, Wnt and TGFß pathways were downregulated, whereas in renal tumors, genes related to hypoxia and DNA damage repair were downregulated. CONCLUSIONS: Thus, our eKET diet exerts potent antitumor and antimetastatic effects in both breast and renal cancer models, albeit with different modes of action and physiologic effects. Its potential as an adjuvant dietary approach for patients with diverse cancer types should be explored further.

Synthetic Health Data Can Augment Community Research Efforts to Better Inform the Public During Emerging Pandemics.

The COVID-19 pandemic had disproportionate effects on the Veteran population due to the increased prevalence of medical and environmental risk factors. Synthetic electronic health record (EHR) data can help meet the acute need for Veteran population-specific predictive modeling efforts by avoiding the strict barriers to access, currently present within Veteran Health Administration (VHA) datasets. The U.S. Food and Drug Administration (FDA) and the VHA launched the precisionFDA COVID-19 Risk Factor Modeling Challenge to develop COVID-19 diagnostic and prognostic models; identify Veteran population-specific risk factors; and test the usefulness of synthetic data as a substitute for real data. The use of synthetic data boosted challenge participation by providing a dataset that was accessible to all competitors. Models trained on synthetic data showed similar but systematically inflated model performance metrics to those trained on real data. The important risk factors identified in the synthetic data largely overlapped with those identified from the real data, and both sets of risk factors were validated in the literature. Tradeoffs exist between synthetic data generation approaches based on whether a real EHR dataset is required as input. Synthetic data generated directly from real EHR input will more closely align with the characteristics of the relevant cohort. This work shows that synthetic EHR data will have practical value to the Veterans' health research community for the foreseeable future.

Phenotyping respiratory decompensation following definitive closure of the patent ductus arteriosus in preterm infants.

OBJECTIVE: To identify risk factors associated with high-frequency ventilation (HFV) following definitive closure of the patent ductus arteriosus (PDA). METHODS: We performed a retrospective study of premature infants (<37 weeks) who were mechanically ventilated before and after surgical or transcatheter PDA closure. Primary outcome was HFV requirement within 24 h of procedure. Logistic regression was used to estimate clinical associations with post procedure HFV requirement. RESULTS: We identified 110 infants who were mechanically ventilated before PDA closure, of which 48 (44%) escalated to HFV within 24 h after closure. In the multivariable model, surgical ligation (OR 21.5, 95% CI 1.6-284), elevated Respiratory Severity Score (RSS) 1 h post-procedure (OR 1.78, 95% CI 1.07-2.99) and 12 h post-procedure (OR 2.12, 95% CI 1.37-3.26) were independent predictors of HFV. CONCLUSION: Surgical ligation and elevated RSS values over the first 12 h after PDA closure are risk factors for HFV.

3D printed brachytherapy jig for Reference Air Kerma Rate calibration.

3D printing in modern radiotherapy allows users the ability to create custom devices which can be a valuable tool for use in brachytherapy source calibration. Radiotherapy centres may verify their brachytherapy source activity with a calibrated Farmer chamber. For this purpose, a jig was designed, 3D printed and commissioned for in-air source strength calibration. Measurements on four afterloaders with varied equipment and environments were completed. A full uncertainty budget was developed and measurements with the in-air jig were consistently within 3% of the certificate source strength, and within the 4.1% combined uncertainty for comparing a well chamber measurement (1.7%) with the in air jig (3.75%). By creating a jig that is able to be customised to multiple catheter sizes and cylindrical chamber designs, centres can be provided with the option of independently checking their source strength with ease and for little cost.

Family Child Care Providers' Nutrition Practices and Policies: Happy Healthy Homes.

OBJECTIVE: Determine the impact of family child care home providers' nutrition knowledge, confidence, and perceived barriers on program nutrition best practices and written nutrition policies. METHODS: Cross-sectional analysis of self-reported surveys of 49 female providers in Oklahoma City analyzed with Spearman correlation, multivariate linear and logistic regression (α < 0.05). RESULTS: Confidence and barriers were significantly correlated (rs(47) = -0.4, P = 0.004). Independent variables explained 36% of practices (r2 = 0.357). Nutrition knowledge (standard ß = 0.442, P = 0.001) and confidence (standard ß = 0.358, P = 0.008) were significantly associated with practices; barriers were not. No significant association between independent variables and written policies resulted. CONCLUSIONS AND IMPLICATIONS: Provider nutrition knowledge and confidence appear to be suitable targets to improve nutrition practices. Further research can evaluate possible influences on the presence and quality of family child care home written nutrition policies and specific nutrition policy topics associated with healthier nutrition practices.

Mortality Risk Factors in Preterm Infants Treated with High-Frequency Jet Ventilation.

BACKGROUND: High-frequency jet ventilation (HFJV) has been used in conjunction with conventional ventilation for premature infants with respiratory failure. We sought to identify parameters that were associated with mortality in subjects who underwent HFJV. METHODS: Subjects were enrolled if birthweight was ≤ 2,000 g and they were ≤ 34 weeks gestational age. Subjects were excluded if they received HFJV at the time of admission because we aimed to study subjects who failed conventional ventilation. Subject demographics, ventilator parameters, and laboratory data were extracted and analyzed. The Mann-Whitney U-test was used to assess differences in continuous variables, and the chi-square and Fisher exact tests were used for categorical variables between the groups. To assess variables that were predictive of mortality, we used both univariate and multivariate logistic regression analysis. Independent predictors of mortality were identified and used to create a multivariate risk score. Receiver operating characteristic curves were constructed to evaluate the predictive accuracy of the multivariate risk score. RESULTS: A total of 53 premature subjects (n = 37 male) were studied, of whom 39 (74%) survived to discharge or transfer back to referring hospital. In the univariate model, female sex, older gestational age, higher birthweight, HFJV peak inspiratory pressure at 1 h, and oxygen saturation index at 4 h were associated with mortality. In the final multivariate logistic regression model, female sex (odds ratio 4.1, 95% CI 1.2-19.8, P = .044), closed ductus arteriosus (odds ratio 7.7, 95% CI 1.3-39.5, P = .016), and oxygen saturation index > 5.5 (odds ratio 6.0, 95% CI 1.5-28.3, P = .02) were independent predictors of mortality. CONCLUSIONS: We identified that oxygen saturation index > 5.5 after 4 h of HFJV, female sex, and closed ductus arteriosus were independent predictors of mortality.