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Advances in stem cell engineering have opened new avenues for more accurately developing in vitro models of the human blood-brain barrier (BBB). Here, we highlight state-of-the-art human BBB-on-a-chip technologies and discuss the importance of human brain cells for better modeling the human brain pathophysiology.

This study aimed to investigate the possible association of neck circumference with cardiometabolic risk factors, and to find out the possible cutoff points of neck circumference for the diagnosis of metabolic syndrome among the Iranian population.

This is a cross-sectional study in 1619 participants who were selected through clustered random sampling, as a part of a health cohort in Amol, Iran. Diagnosis of metabolic syndrome (MetS) was based on the modified criteria of the National Cholesterol Educational Program Adult Treatment Panel (NCEP ATP III). Associations of neck circumference with Mets and its components were studied using logistic regression. The optimal cutoff point of neck circumference for MetS diagnosis was calculated based on the Youden index.

Metabolic syndrome was diagnosed in 433 (26.7%) of patients. Neck circumference was shown to be significantly associated with central obesity, hypertension, hypertriglyceridemia, impaired fasting glucose, and low serum high-density lipoprotein (HDL) level, as well as MetS. NVP-2 mouse The optimal cutoff points of neck circumference in the diagnosis of MetS are 36 cm and 42 cm for women and men, respectively. Sensitivity of the optimal cut-off point of NC for diagnosing patients with MetS was higher in women compared to men (70.6% compared to 55.9%).

A significant association was observed between neck circumference and the presence of MetS among the Iranian population and neck circumference can be offered as a new index in screening and diagnosis for MetS and assessing cardiometabolic risk factors.

A significant association was observed between neck circumference and the presence of MetS among the Iranian population and neck circumference can be offered as a new index in screening and diagnosis for MetS and assessing cardiometabolic risk factors.

To describe the characteristics and antidiabetic treatment among type 2 diabetes patients according to the clinical conditions prioritized in the Spanish 2020 RedGDPS (Primary Care Diabetes Study Groups Network) therapeutic algorithm obesity, older than 75 years, chronic kidney disease, cardiovascular disease, and heart failure.

Retrospective, cross-sectional study. Clinical characteristics, the use of antidiabetic drugs and the KDIGO renal risk categories at 31.12.2016 were retrieved from the SIDIAP (Information System for Research in Primary Care) database (Catalonia, Spain).

From a total of 373,185 type 2 diabetes patients, 37% were older than 75 years, 45% obese, 33% had chronic kidney disease, 23.2% cardiovascular disease and 6.9% heart failure. Insulin was more frequently prescribed in chronic kidney disease, cardiovascular disease and heart failure whereas Sodium-Glucose cotransporter 2 inhibitors and Glucagon Like Peptide 1 receptor agonists were scarcely prescribed (2.6% and 1.4%, respectively). Among patients with severe renal failure, contraindicated drugs like metformin (16%) and sulfonylureas (6.1%) were still in use. The 2012 KDIGO renal risk categories distribution was Low 60.9%, Moderate 21.6%, High 9.8% and Very high 7.7%.

Almost 80% of our T2DM patients meet one of the five clinical conditions that should be considered for treatment individualization. Importantly, a relevant number of patients with severe renal failure were found to use contraindicated drugs.

Almost 80% of our T2DM patients meet one of the five clinical conditions that should be considered for treatment individualization. Importantly, a relevant number of patients with severe renal failure were found to use contraindicated drugs.

An estimated 35 million individuals in the United States have diabetes. The American Diabetes Association recommends metformin as first-line pharmacologic treatment. The primary objective of this study was to evaluate the metformin initiation rate in veterans with recently identified type 2 diabetes.

Veterans with new onset type 2 diabetes were identified using National Veterans Health Administration Data. Retrospective information was obtained from those with a first A1C ≥ 6.5% (48 mmol/mol) between 2013 and 2018. Veterans with at least one additional A1C < 6.5% (48 mmol/mol) documented in the three years prior to the A1C diagnostic for diabetes were included in the analysis.

A total of 144,180 veterans were included. Of those, 45,776 (31.7%) were started on metformin within one year of diabetes diagnosis. The median time to metformin initiation was 12 days and median time to initiation of any anti-hyperglycemic was 11 days. Approximately 16,000 veterans were referred for lifestyle interventions within 90 days.

Metformin initiation occurred in fewer patients than expected given metformin is a generic, well-tolerated medication recommended as first-line pharmacologic treatment option regardless of A1C. Further studies are needed to assess the barriers of initiating metformin at time of diabetes diagnosis.

Metformin initiation occurred in fewer patients than expected given metformin is a generic, well-tolerated medication recommended as first-line pharmacologic treatment option regardless of A1C. Further studies are needed to assess the barriers of initiating metformin at time of diabetes diagnosis.

The objective of this study was to compare the diagnostic performance of magnetic resonance imaging (MRI) and computed tomography (CT) in differentiating pleomorphic adenomas from Warthin tumors using radiomics.

We retrospectively reviewed 626 patients who underwent preoperative MRI or CT for parotid tumor diagnosis. Patient groups were balanced by propensity score matching (PSM) and 123 radiomic features were extracted from tumor images. Radiomic signatures (rad-scores) were generated using a least absolute shrinkage and selection operator logistic regression model. The Canny edge detector was used to define tumor borders (border index). The diagnostic performance of rad-score and border index before and after PSM was evaluated with area under the receiver operating characteristic curve analysis.

For differentiation of pleomorphic adenomas and Warthin tumors, rad-score and border index areas under the curve for MRI after PSM were 0.911 (95% confidence interval [CI], 0.871-0.951) and 0.716 (95% CI, 0.646-0.