High-density microbioreactor process designed for automated point-of- care manufacturing of CAR T cells

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Review of methods for detecting glycemic disorders

Prediabetes (intermediate hyperglycemia) consists of two abnormalities, impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) detected by a standardized 75-gram oral glucose tolerance test (OGTT). Individuals with isolated IGT or combined IFG and IGT have increased risk for developing type 2 diabetes (T2D) and cardiovascular disease (CVD). Diagnosing prediabetes early and accurately is critical in order to refer high-risk individuals for intensive lifestyle modification. However, there is currently no international consensus for diagnosing prediabetes with HbA1c or glucose measurements based upon American Diabetes Association (ADA) and the World Health Organization (WHO) criteria that identify different populations at risk for progressing to diabetes. Various caveats affecting the accuracy of interpreting the HbA1c including genetics complicate this further. This review describes established methods for detecting glucose disorders based upon glucose and HbA1c parameters as well as novel approaches including the 1-hour plasma glucose (1-h PG), glucose challenge test (GCT), shape of the glucose curve, genetics, continuous glucose monitoring (CGM), measures of insulin secretion and sensitivity, metabolomics, and ancillary tools such as fructosamine, glycated albumin (GA), 1,5- anhydroglucitol (1,5-AG). Of the approaches considered, the 1-h PG has considerable potential as a biomarker for detecting glucose disorders if confirmed by additional data including health economic analysis. Whether the 1-h OGTT is superior to genetics and omics in providing greater precision for individualized treatment requires further investigation. These methods will need to demonstrate substantially superiority to simpler tools for detecting glucose disorders to justify their cost and complexity

Sleep and Economic Status are Linked to Daily Life Stress in African-born Blacks Living in America.

To identify determinants of daily life stress in Africans in America, 156 African-born Blacks (Age: 40 ± 10 years (mean ± SD), range 22-65 years) who came to the United States as adults (age ≥ 18 years) were asked about stress, sleep, behavior and socioeconomic status. Daily life stress and sleep quality were assessed with the Perceived Stress Scale (PSS) and Pittsburgh Sleep Quality Index (PSQI), respectively. High-stress was defined by the threshold of the upper quartile of population distribution of PSS (≥16) and low-stress as PSS \u3c 16. Poor sleep quality required PSQI \u3e 5. Low income was defined as groups, PSS were: 21 ± 4 versus 9 ± 4, p \u3c 0.001 and PSQI were: 6 ± 3 versus 4 ± 3, p \u3c 0.001, respectively. PSS and PSQI were correlated (r = 0.38, p \u3c 0.001). The odds of high-stress were higher among those with poor sleep quality (OR 5.11, 95% CI: 2.07, 12.62), low income (OR 5.03, 95% CI: 1.75, 14.47), and no health insurance (OR 3.01, 95% CI: 1.19, 8.56). Overall, in African-born Blacks living in America, daily life stress appears to be linked to poor quality sleep and exacerbated by low income and lack of health insurance

High-intensity focused ultrasound: past, present, and future in neurosurgery

Since Lynn and colleagues first described the use of focused ultrasound (FUS) waves for intracranial ablation in 1942, many strides have been made toward the treatment of several brain pathologies using this novel technology. In the modern era of minimal invasiveness, high-intensity focused ultrasound (HIFU) promises therapeutic utility for multiple neurosurgical applications, including treatment of tumors, stroke, epilepsy, and functional disorders. Although the use of HIFU as a potential therapeutic modality in the brain has been under study for several decades, relatively few neuroscientists, neurologists, or even neurosurgeons are familiar with it. In this extensive review, the authors intend to shed light on the current use of HIFU in different neurosurgical avenues and its mechanism of action, as well as provide an update on the outcome of various trials and advances expected from various preclinical studies in the near future. Although the initial technical challenges have been overcome and the technology has been improved, only very few clinical trials have thus far been carried out. The number of clinical trials related to neurological disorders is expected to increase in the coming years, as this novel therapeutic device appears to have a substantial expansive potential. There is great opportunity to expand the use of HIFU across various medical and surgical disciplines for the treatment of different pathologies. As this technology gains recognition, it will open the door for further research opportunities and innovation

Identification of biomarkers for type 2 diabetes: analysis of a primary prevention study among Asian Indians with impaired glucose tolerance

Primary prevention of type 2 diabetes (T2DM) is an important strategy for curbing its rising global burden. Though lifestyle modification has provided an effective method of preventing/delaying incidence of diabetes in high-risk individuals, it has not been widely implemented even in developed countries due to its high-cost, need for expertise and difficulties in translating the benefits of lifestyle intervention to the community at large. Hence, there is an urgent need to identify an alternate mode of delivery to transmit healthy lifestyle information to high-risk individuals. In this trial, we sought to determine whether lifestyle advice through mobile phone text messaging could reduce incident diabetes compared to standard lifestyle advice in Asian Indian men with prediabetes. The study showed for the first time that mobile phone messaging is an effective and acceptable method to deliver advice and support towards lifestyle modification to prevent T2DM in men at high risk. The identification of novel predictors for T2DM is an arduous task. The glycaemic markers of diabetes (fasting plasma glucose, 2hr post glucose load and HbA1c) are, in fact, risk factors for microvascular complications of diabetes and it was on this basis that diagnostic cut-offs’ for diabetes were arrived at. Nevertheless, elevated levels of glycaemic markers in the sub-clinical, or pre-diabetic, range are associated with increased risk of progression to diabetes. However, there is already considerable deterioration of beta cell function by the time diabetic dysglycaemia occurs. The way forward is clearly to identify biomarkers that serve as reliable predictors of progression to diabetes rather than simply reflecting accompanying levels of glycaemia. In this thesis using the database of the above mentioned trial it was aimed to identify the predictors of T2DM in Asian Indian cohort with prediabetes at baseline. The classical risk factors studied here are: 1) increased prevalence of the hypertriglyceridemic waist phenotype, 2) a combination of HbA1c and gamma glutamyl transferase and 3) a measure of beta cell compensation (disposition index) predicted incident diabetes. Among these, the disposition index was the most powerful predictor in the cohort. In addition to these classical risk factors mentioned above, in a small nested-case control, cross sectional study, the association of adipokines (adiponectin, leptin, interleukin-6 (IL-6), retinol-binding protein4 (RBP4)) and vitamin D3 were assessed to study the mechanistic link of novel biomarkers with diabetes. In this cohort, lower levels of baseline adiponectin, and higher IL-6 and RBP4 were associated with diabetes. Though, many of these provided a novel mechanistic pathogenic link with diabetes they did not improve prediction over and above that of glycaemic measures in identifying individuals with diabetes. However, the non-glycaemic biomarkers appear to have a role in the underlying pathogenesis of diabetes.Open Acces

Urbanization and kidney function decline in low and middle income countries

Abstract Urbanization is expected to increase in low and middle-income countries (LMICs), and might contribute to the increased disease burden. The association between urbanization and CKD is incompletely understood among LMICs. Recently, Inoue et al., explored the association of urbanization on renal function from the China Health and Nutrition Survey. The study found that individuals living in an urban environment had a higher odds of reduced renal function independent of behavioral and cardiometabolic measures, and this effect increased in a dose dependent manner. In this commentary, we discuss the results of these findings and explain the need for more surveillance studies among LMICs

Systems Biology Genetic Approach Identifies Serotonin Pathway as a Possible Target for Obstructive Sleep Apnea: Results from a Literature Search Review

Rationale. Overall validity of existing genetic biomarkers in the diagnosis of obstructive sleep apnea (OSA) remains unclear. The objective of this systematic genetic study is to identify “novel” biomarkers for OSA using systems biology approach. Methods. Candidate genes for OSA were extracted from PubMed, MEDLINE, and Embase search engines and DisGeNET database. The gene ontology (GO) analyses and candidate genes prioritization were performed using Enrichr tool. Genes pertaining to the top 10 pathways were extracted and used for Ingenuity Pathway Analysis. Results. In total, we have identified 153 genes. The top 10 pathways associated with OSA include (i) serotonin receptor interaction, (ii) pathways in cancer, (iii) AGE-RAGE signaling in diabetes, (iv) infectious diseases, (v) serotonergic synapse, (vi) inflammatory bowel disease, (vii) HIF-1 signaling pathway, (viii) PI3-AKT signaling pathway, (ix) regulation lipolysis in adipocytes, and (x) rheumatoid arthritis. After removing the overlapping genes, we have identified 23 candidate genes, out of which >30% of the genes were related to the genes involved in the serotonin pathway. Among these 4 serotonin receptors SLC6A4, HTR2C, HTR2A, and HTR1B were strongly associated with OSA. Conclusions. This preliminary report identifies several potential candidate genes associated with OSA and also describes the possible regulatory mechanisms

Health App Use Among US Mobile Phone Users: Analysis of Trends by Chronic Disease Status

Background: Mobile apps hold promise for serving as a lifestyle intervention in public health to promote wellness and attenuate chronic conditions, yet little is known about how individuals with chronic illness use or perceive mobile apps. Objective: The objective of this study was to explore behaviors and perceptions about mobile phone-based apps for health among individuals with chronic conditions. Methods: Data were collected from a national cross-sectional survey of 1604 mobile phone users in the United States that assessed mHealth use, beliefs, and preferences. This study examined health app use, reason for download, and perceived efficacy by chronic condition. Results: Among participants, having between 1 and 5 apps was reported by 38.9% (314/807) of respondents without a condition and by 6.6% (24/364) of respondents with hypertension. Use of health apps was reported 2 times or more per day by 21.3% (172/807) of respondents without a condition, 2.7% (10/364) with hypertension, 13.1% (26/198) with obesity, 12.3% (20/163) with diabetes, 12.0% (32/267) with depression, and 16.6% (53/319) with high cholesterol. Results of the logistic regression did not indicate a significant difference in health app download between individuals with and without chronic conditions (P>.05). Compared with individuals with poor health, health app download was more likely among those with self-reported very good health (odds ratio [OR] 3.80, 95% CI 2.38-6.09, P < .001) and excellent health (OR 4.77, 95% CI 2.70-8.42, P < .001). Similarly, compared with individuals who report never or rarely engaging in physical activity, health app download was more likely among those who report exercise 1 day per week (OR 2.47, 95% CI 1.6-3.83, P < .001), 2 days per week (OR 4.77, 95% CI 3.27-6.94, P < .001), 3 to 4 days per week (OR 5.00, 95% CI 3.52-7.10, P < .001), and 5 to 7 days per week (OR 4.64, 95% CI 3.11-6.92, P < .001). All logistic regression results controlled for age, sex, and race or ethnicity. Conclusions: Results from this study suggest that individuals with poor self-reported health and low rates of physical activity, arguably those who stand to benefit most from health apps, were least likely to report download and use these health tools

Health App Use Among US Mobile Phone Users: Analysis of Trends by Chronic Disease Status

Background: Mobile apps hold promise for serving as a lifestyle intervention in public health to promote wellness and attenuate chronic conditions, yet little is known about how individuals with chronic illness use or perceive mobile apps. Objective: The objective of this study was to explore behaviors and perceptions about mobile phone-based apps for health among individuals with chronic conditions. Methods: Data were collected from a national cross-sectional survey of 1604 mobile phone users in the United States that assessed mHealth use, beliefs, and preferences. This study examined health app use, reason for download, and perceived efficacy by chronic condition. Results: Among participants, having between 1 and 5 apps was reported by 38.9% (314/807) of respondents without a condition and by 6.6% (24/364) of respondents with hypertension. Use of health apps was reported 2 times or more per day by 21.3% (172/807) of respondents without a condition, 2.7% (10/364) with hypertension, 13.1% (26/198) with obesity, 12.3% (20/163) with diabetes, 12.0% (32/267) with depression, and 16.6% (53/319) with high cholesterol. Results of the logistic regression did not indicate a significant difference in health app download between individuals with and without chronic conditions (P>.05). Compared with individuals with poor health, health app download was more likely among those with self-reported very good health (odds ratio [OR] 3.80, 95% CI 2.38-6.09, P < .001) and excellent health (OR 4.77, 95% CI 2.70-8.42, P < .001). Similarly, compared with individuals who report never or rarely engaging in physical activity, health app download was more likely among those who report exercise 1 day per week (OR 2.47, 95% CI 1.6-3.83, P < .001), 2 days per week (OR 4.77, 95% CI 3.27-6.94, P < .001), 3 to 4 days per week (OR 5.00, 95% CI 3.52-7.10, P < .001), and 5 to 7 days per week (OR 4.64, 95% CI 3.11-6.92, P < .001). All logistic regression results controlled for age, sex, and race or ethnicity. Conclusions: Results from this study suggest that individuals with poor self-reported health and low rates of physical activity, arguably those who stand to benefit most from health apps, were least likely to report download and use these health tools