Nicotine Reduces Reactive Oxygen Species and Enhances Cell Proliferation via the α4 Nicotinic Acetylcholine Receptor Subunit in Human Induced Pluripotent Stem Cells.

The effects of smoking on fetal development and stem cell differentiation are not fully understood. Although nicotinic acetylcholine receptors (nAChRs) are expressed in many organs of the human body, their significance in human induced pluripotent stem cells (hiPSCs) remains unclear. After expression levels of nAChR subunits in hiPSCs were determined, the effects of the nAChR agonist, nicotine, on undifferentiated hiPSCs were evaluated using a Clariom S Array. We also determined the effect of nicotine alone and with a nAChR subunit antagonist on hiPSCs. nAChR α4, α7, and ß4 subunits were strongly expressed in hiPSCs. cDNA microarray, gene ontology, and enrichment analyses showed that exposing hiPSCs to nicotine altered expression of genes associated with immune responses, neurological system, carcinogenesis, cell differentiation, and cell proliferation. Particularly affected was metallothionein, which acts to decrease reactive oxygen species (ROS). The nicotine-induced reduction of ROS in hiPSCs was canceled by an α4 subunit or nonselective nAChR antagonist. HiPSC proliferation was increased by nicotine, and this effect, too, was canceled by an α4 antagonist. In conclusion, nicotine reduces ROS and enhances cell proliferation through the α4 nAChR subunit in hiPSCs. These findings provide new insight into the significance of nAChRs on human stem cells and fertilized human ova.

Developing a Stroke Risk Prediction Model Using Cardiovascular Risk Factors: The Suita Study.

INTRODUCTION: Stroke remains a major cause of death and disability in Japan and worldwide. Detecting individuals at high risk for stroke to apply preventive approaches is recommended. This study aimed to develop a stroke risk prediction model among urban Japanese using cardiovascular risk factors. METHODS: We followed 6,641 participants aged 30-79 years with neither a history of stroke nor coronary heart disease. The Cox proportional hazard model estimated the risk of stroke incidence adjusted for potential confounders at the baseline survey. The model's performance was assessed using the receiver operating characteristic curve and the Hosmer-Lemeshow statistics. The internal validity of the risk model was tested using derivation and validation samples. Regression coefficients were used for score calculation. RESULTS: During a median follow-up duration of 17.1 years, 372 participants developed stroke. A risk model including older age, current smoking, increased blood pressure, impaired fasting blood glucose and diabetes, chronic kidney disease, and atrial fibrillation predicted stroke incidence with an area under the curve = 0.76 and p value of the goodness of fit = 0.21. This risk model was shown to be internally valid (p value of the goodness of fit in the validation sample = 0.64). On a risk score from 0 to 26, the incidence of stroke for the categories 0-5, 6-7, 8-9, 10-11, 12-13, 14-15, and 16-26 was 1.1%, 2.1%, 5.4%, 8.2%, 9.0%, 13.5%, and 18.6%, respectively. CONCLUSION: We developed a new stroke risk model for the urban general population in Japan. Further research to determine the clinical practicality of this model is required.

Perfluoroalkyl substances are inversely associated with coronary heart disease in adults with diabetes.

AIMS: Perfluoroalkyl substances (PFAS) are environmentally and biologically persistent synthetic environmental contaminants linked to adverse health outcomes. Though null to modest inverse relationships between PFAS and coronary heart disease (CHD) have been reported, studies regarding relationships in high risk populations such as those with diabetes are sparse. We investigated the relationship of PFAS with CHD in persons with diabetes. METHODS: Data on 5270 adults, aged ≥20 years, with diabetes were obtained from the C8 Health Project. Four PFAS were investigated separately: perfluorohexane sulfonate (PFHxS), perfluorooctanoic acid (PFOA), perfluorooctane sulfonate (PFOS), and perfluorononanoic acid (PFNA). RESULTS: In logistic regression analyses adjusting for age, sex, diabetes duration, BMI, smoking, lipids, WBC, CRP, eGFR, uric acid, hemoglobin and iron, all PFAS were inversely associated with CHD, ORs (95% CIs): PFHxS; 0.72 (0.65-0.79), PFOA; 0.90 (0.81-0.96), PFOS; 0.90 (0.81-0.99), PFNA; 0.88 (0.76-1.02). Stratification by chronic kidney disease status revealed similar inverse relationships for those with and without chronic kidney disease. CONCLUSIONS: In this cross-sectional study of over 5000 adults with diabetes, PFAS showed inverse associations with CHD. These findings may, if confirmed in future studies, provide new physiologic understanding of CHD prevention strategies.

Evaluation of quantitative parameters for distinguishing pheochromocytoma from other adrenal tumors.

Adrenal tumors are increasingly found incidentally during imaging examinations. It is important to distinguish pheochromocytomas from other adrenal tumors because of the risk of hypertensive crisis. Although catecholamines and their metabolites are generally used to diagnose pheochromocytoma, false-positive test results are common. An effective screening method to distinguish pheochromocytoma from adrenal incidentalomas is needed. We analyzed 297 consecutive patients with adrenal incidentalomas. Our findings included 162 non-functioning tumors, 47 aldosterone-producing adenomas, 26 metastases, 22 cases of subclinical Cushing's syndrome, 21 pheochromocytomas, 12 cases of Cushing's syndrome, and 7 adrenocortical cancers. We checked quantitative parameters such as age, blood, and urine catecholamines and their metabolites, neuron-specific enolase, size and computed tomography (CT) attenuation values. Among catecholamine-related parameters, the sum of urine metanephrine and normetanephrine (urineMNM) levels produced the highest area under the receiver operating characteristic curve regarding discrimination of pheochromocytoma from other lesions. Size and CT attenuation values also differed significantly. However, size was correlated with catecholamine levels. CT attenuation was not correlated with other factors. The optimal thresholds were 19 Hounsfield units (HU) for CT attenuation (sensitivity, 100%; specificity, 60%) and 0.43 mg/24 h for urineMNM (sensitivity, 89%; specificity, 96%). No pheochromocytomas were evident when CT attenuation values were under 19 HU. Even in adrenal tumors with CT attenuation values ≥ 19 HU, when urineMNM was < 0.43 mg/24 h, the frequency of pheochromocytoma was only 4.3%, when urineMNM was ≥ 0.43 mg/24 h, the frequency of pheochromocytoma was 93% and when urineMNM was > 0.77 mg/24 h the frequency of pheochromocytoma was 100%. CT attenuation value and urineMNM represented the most useful combination for diagnosis of pheochromocytoma.