This study investigates the pharmacokinetics and metabolic characteristics of three marine-derived piericidins as potential drug leads for kidney disease: piericidin A (PA) and its two glycosides (GPAs), glucopiericidin A (GPA) and 13-hydroxyglucopiericidin A (13-OH-GPA). The research aims to facilitate lead selection and optimization for developing a viable preclinical candidate. Rapid absorption of PA and GPAs in mice was observed, characterized by short half-lives and low bioavailability. Glycosides and hydroxyl groups significantly enhanced the absorption rate (13-OH-GPA > GPA > PA). PA and GPAs exhibited metabolic instability in liver microsomes due to Cytochrome P450 enzymes (CYPs) and uridine diphosphoglucuronosyl transferases (UGTs). Glucuronidation emerged as the primary metabolic pathway, with UGT1A7, UGT1A8, UGT1A9, and UGT1A10 demonstrating high elimination rates (30%-70%) for PA and GPAs. This rapid glucuronidation may contribute to the low bioavailability of GPAs. Despite its low bioavailability (2.69%), 13-OH-GPA showed higher kidney distribution (19.8%) compared to PA (10.0%) and GPA (7.3%), suggesting enhanced biological efficacy in kidney diseases. Modifying the C-13 hydroxyl group appears to be a promising approach to improve bioavailability. In conclusion, this study provides valuable metabolic insights for the development and optimization of marine-derived piericidins as potential drug leads for kidney disease.
Animals ; Male ; Mice ; Aquatic Organisms/chemistry* ; Biological Availability ; Cytochrome P-450 Enzyme System/metabolism* ; Glucuronosyltransferase/metabolism* ; Microsomes, Liver/metabolism* ; Molecular Structure ; Biological Products/pharmacokinetics* ; Pyridines/pharmacokinetics*

This article reviews the current status, advantages, and limitations of the application of Internet of Things (IoT) technology in mental health services. It explores the prospects of IoT technology in this field. IoT technology has been successfully applied in smart hospitals, telemedicine, smart devices, and health management. However, there are few reports on IoT technology application in our country′s mental health services. In the field of mental health services, IoT technology can help improve the quality of life of patients with mental disorders and the effectiveness of medical services. Still, it also faces challenges brought about by patient privacy and security.

Objective:To investigate the correlation between fat distribution and the composite indices of femoral neck strength in obese postmenopausal women.Methods:A total of 293 postmenopausal women with non-low body weight were selected, laboratory tests, body composition analyzer test and double-energy X-ray absorptiometry scan were performed. Based on the body mass index(BMI), they were divided into three groups, the normal BMI group(18.5 kg/m 2≤BMI<24.0 kg/m 2, n=91), the overweight group(24.0 kg/m 2≤BMI<28.0 kg/m 2, n=115), and the obese group(BMI≥28.0 kg/m 2, n=87). The measurement results were analyzed. Results:In the obese group, bone mineral density(BMD) of all sites was higher than that in the normal BMI group and overweight group( P<0.005), compression strength index(CSI), bending strength index(BSI), and impact strength index(ISI) were significantly lower than those in the normal BMI group( P<0.001, P=0.008, P=0.001). In the obese group, waist circumference, waist-hip ratio, total fat mass, appendicular fat mass, and trunk fat mass were risk factors for CSI, BSI and ISI independent of age, fasting blood glucose, and BMI( P<0.05). Visceral fat grade and Chinese visceral adiposity fat index were the risk factors for CSI, BSI, and ISI( P<0.05). Conclusion:The composite indices of femoral neck strength decreased in obese postmenopausal women, and both subcutaneous fat and visceral fat were negatively associated with the composite indices of femoral neck strength.

This article reviews the current status, advantages, and limitations of the application of Internet of Things (IoT) technology in mental health services. It explores the prospects of IoT technology in this field. IoT technology has been successfully applied in smart hospitals, telemedicine, smart devices, and health management. However, there are few reports on IoT technology application in our country′s mental health services. In the field of mental health services, IoT technology can help improve the quality of life of patients with mental disorders and the effectiveness of medical services. Still, it also faces challenges brought about by patient privacy and security.

Objective:To explore the changes of bone turnover markers and geometric parameters of hip bone in overweight postmenopausal women with metabolic syndrome(MS), as well as the influence of MS components. To analyze the association of these factors with the risk of fracture.Methods:A total of 505 overweight postmenopausal female patients who underwent health check-up in Lianhu Community Service Center, Danyang City, Jiangsu Province from January to December 2017 were selected. According to the MS diagnostic criteria of the International Diabetes Federation(2009), the patients were divided into MS group( n=331)and non-MS group( n=174). Blood samples were collected to determine the level of procollagen type 1 N-terminal propeptide(P1NP)and carboxy-terminal cross-linked telopeptide of type 1 collagen(CTX). Bone mineral density and hip bone geometry parameters were tested with dual-energy X-ray absorptiometry and hip structural analysis software. Results:The incidence of osteoporotic fracture and hip fracture in MS group was significantly higher than that in non-MS group(21.1% vs 13.8%, 4.8% vs 1. 1%, P<0.05). However, the bone mineral density of lumbar vertebra 1-4, femoral neck, and total hip in MS group was significantly higher than that in non-MS group, which remained after adjusting for age( P<0.05), but the difference disappeared after further adjustment for body mass index( P>0.05). The P1NP, CTX, femur strength index(FSI), section modulus(SM), and cross-sectional area(CSA)of MS group were significantly lower than those of non-MS group, the buckling ration(BR)was significantly higher than that in non-MS group, and the differences were still statistically significant after adjusting for age and body mass index( P<0.05). There was no significant difference in bone mineral density of lumbar vertebra 1-4, femoral neck, total hip, P1NP, and CTX between fracture group and non-fracture group in patients with MS. But FSI, SM, cross-sectional moment of inertia(CSMI), and CSA were significantly lower, BR was significantly higher( P<0.05) and femur strength decreased in patients with fracture. Regression analysis showed that high BR was an independent risk factor for fracture risk, while high FSI, SM, CSMI, and CSA were protective factors. Multivariate linear regression analysis showed that wasit circumference, diastolic blood pressure, and fasting plasma glucose were the main MS components affecting bone mineral density, bone turnover indexes, and hip bone geometry parameters. Conclusions:Overweight postmenopausal MS patients had decreased bone turnover rate, femoral strength, and relatively poor bone quality. Hip bone geometry parameters can be used as one of the methods to assess fracture risk in MS patients. Waist circumference, diastolic blood pressure, and fasting blood glucose are the important MS components affecting bone mass and bone quality.

Objective:To explore the risk of hip fracture, changes of composite indices of femoral neck strength and its influential factors in non-low-weight postmenopausal women with type 2 diabetes mellitus(T2DM).Methods:A total of 626 non-low-weight postmenopausal women were selected and divided into type 2 diabetes group, pre-diabetic group, and non-diabetic group according to the diagnostic criteria of the American Diabetes Association in 2010. Each participant completed the questionnaire, physical examination, laboratory examination, and Dual-energy X-ray absorptiometry(DXA) examination.Results:Hip fracture rate in T2DM group was significantly higher than that in non-diabetic group(3.4% vs 0.7%, P<0.05), while no significant difference was observed between pre-diabetic group and non-diabetic group(1.1% vs 0.7%, P>0.05). Bone mineral density(BMD) of lumbar spine 1-4, femoral neck, and total hip was comparable between T2DM group and non-diabetic group or pre-diabetic group and non-diabetic group, respectively( P>0.05). The composite indices of femoral neck strength in T2DM group was significantly lower than that in non-diabetic group( P<0.05), but there was no significant difference between pre-diabetic group and non-diabetic group( P>0.05). Regression analysis showed that age and body mass index were the main influential factors of the femoral neck bone mineral density and the composite indices of femoral neck strength( P<0.05). Conclusion:The composite indices of femoral neck strength could be used as one of the markers to evaluate the risk of hip fracture in type 2 diabetic patients.

Objective To assess the reliability and validity of the Chinese version of the neuropsychiatric inventory (CNPI). Methods The CNPI was administered to 219 caregivers of patients with Alzheimer's disease (AD). Each caregiver was retested 4 weeks after initial testing. Results The Cronbach a coefficient of the total symptom scale was 0.69. The Cronbach α coefficient of the total caregiver distress subscale was 0.72. The Cronbach α coefficient of the entire inventory was 0. 82. The test-retest coefficients ranged from 0.66 to 0.98 (P < 0.01). Principal axis factoring analysis of the symptom subscale yielded a five-factor solution which contributed to 67.0% of the cumulative variance. Factor 1, which included aberrant motor behavior, hallucinations, delusion and irritability had the most significant contribution to the cumulative variance. Principal axis factoring analysis of the caregiver distress subscale also yielded a five-factor solution which contributed to 70.2% of the cumulative variance. Factor 1, which included depression, delusion, sleep/night behavior, aberrant motor behavior, and irritability had the most significant contribution to the cumulative variance. Conclusion This Chinese version of NPI is a reliable and valid tool for measuring neuropsychiatric disturbances in patients with AD.

The paper analyzed the challenges for community-based rehabilitation of schizophrenic patients in China' s rural areas,from such six aspects as culture, prevention and control system for mental health, fairness of health resources allocation, shortage of specialists, confidence in treatment,and delay in rehabilitation. These studies aim at providing the government with decision making evidence for enacting rural mental health policies and taking effective intervention measures.