Hypertension-specific association of cardio-ankle vascular index with subclinical left ventricular function in a Chinese population: Danyang study.

The association of cardio-ankle vascular index (CAVI), with subclinical cardiac dysfunction in hypertensive patients is unclear. We aim to examine their relationship in hypertensive patients compared with that in normotensive subjects. Our study included 1887 subjects enrolled from Danyang between 2018 and 2019. CAVI was measured using VaSera VS-1500A device. We performed conventional echocardiography to measure ejection fraction (EF) and E/A, tissue Doppler to measure mitral annular early diastolic velocities (e'), and speckle-tracking to estimate left ventricular (LV) global longitudinal strain (GLS). LV mass index (76.3, 80.0, and 84.0 g/m2), and E/e' (7.6, 8.2, and 8.8) were increased and GLS (21.1, 21.0, and 20.4%), E/A (1.2, 1.0, and 0.8) and e' velocity (11.2, 9.4, and 8.2 cm/s) was decreased from tertiles 1-3 of CAVI on unadjusted analyses (P < .001). After adjustment for covariates, GLS, E/A, and e' were still significantly decreased from tertiles 1-3 of CAVI (P ≤ .04). Further sensitive analyses revealed a similar association pattern for diastolic function but not systolic function. Compared with the lowest tertile, subjects with a top tertile of CAVI were at higher risk of subclinical LV systolic dysfunction in hypertensive patients (OR = 2.61; P = .005). Increased CAVI is associated with worse subclinical diastolic function. However, this relationship of CAVI to subclinical systolic function was more prominent in hypertensive patients.

Association of epicardial and visceral adipose tissue in relation to subclinical cardiac dysfunction in Chinese: Danyang study.

OBJECTIVE: Our study aims to examine the associations of visceral adipose tissue (VAT) and epicardial adipose tissue (EAT) with subclinical cardiac dysfunction in a Chinese population. DESIGN: Cross-sectional. BACKGROUND: EAT and VAT are the most important ectopic fat pools which were previously shown to be associated with subclinical cardiac dysfunction. However, few studies simultaneously measured both EAT thickness and VAT area, and explored their associations with cardiac dysfunction. Our study aims to examine the associations of VAT and EAT with subclinical cardiac dysfunction in a Chinese population. METHODS: The study subjects were recruited from Danyang County from 2018 to 2019. Using Philips CX50, we recorded EAT thickness at the end-systole in a long-axis view. The subclinical systolic and diastolic function were assessed by two-dimensional speckle tracking, and transmitral and tissue Doppler imaging, respectively. Using Omron HDS-2000, we measured VAT area by dual bioelectrical impedance analysis. RESULTS: The 1558 participants (age, 52.3±12.8 years) included 930 (59.7%) women. Compared with women, men had higher VAT area (99.4 vs 70.1 cm2; p<0.0001) but lower EAT thickness (4.02 vs 4.46 mm; p<0.0001). In simple correlation analyses, EAT thickness and VAT area were positively associated with E/e' ratio (r=0.16 to 0.20; all p<0.0001) and negatively with global longitudinal strain (GLS) and e' (r=-0.12 to -0.37; all p<0.0001). Furthermore, VAT area was associated with left ventricular ejection fraction (LVEF) (r=-0.14; p<0.0001). After adjustment for confounding factors, the association of EAT with GLS and that of VAT with e' and E/e' ratio remained significant (all p≤0.001), whereas the associations of EAT with subclinical diastolic dysfunction and that of VAT with systolic function became non-significant (all p≥0.11). Analyses on further adjustment for LVEF showed similar results. CONCLUSIONS: Increased EAT thickness was associated with worse subclinical systolic dysfunction, while greater VAT area was associated with early diastolic dysfunction.

The characteristics and risk factors of e-cigarette use among adolescents in Shanghai: A case-control study.

INTRODUCTION: This study was conducted to explore the characteristics and risk factors of e-cigarette use in adolescents, aiming for tobacco control and reducing e-cigarette use in this population. METHODS: Using 1:1 matching, 88 students from three vocational high schools in Shanghai were recruited to conduct a case (using e-cigarettes) - control (not using e-cigarettes) study. Group interviews and questionnaire surveys were used for this qualitative and quantitative mixed-methods study. The keywords were extracted from the interview data and analyzed by the Colaizzi seven-step method. RESULTS: The characteristics of adolescents' use of e-cigarettes include young age at first use, consumption of a large amount, as well as smoking in discrete locations in order to hide from adults. The reasons for using e-cigarettes include curiosity and wanting to replace traditional cigarettes. The risk factors of using e-cigarettes include insufficient understanding of the harm of e-cigarettes at the individual level (The positive outcome expectancy points: Z= -3.746, p<0.001; The negative outcome expectancy points: Z= -3.882, p<0.001), peer influence at the interpersonal level (χ2=6.510, p<0.01), and the influence of social and environmental factors such as e-cigarette sales in the stores and WeChat Moments (p<0.05 for all associations). CONCLUSIONS: Having friends who use e-cigarettes, curiosity and sales exposure about e-cigarettes are important factors affecting the use of e-cigarettes by adolescents. It is necessary to strengthen the publicity of the potential hazards of e-cigarettes and to reduce overall usage by improving relevant laws and regulations.

Identification of Novel Umami Peptides in Chicken Breast Soup through a Sensory-Guided Approach and Molecular Docking to the T1R1/T1R3 Taste Receptor.

Ultrafiltration combined with nanoliquid chromatography quadrupole time-of-flight mass spectrometry (nano-LC-QTOF-MS) and sensory evaluation was used to separate and identify umami peptides in chicken breast soup. Fifteen peptides with umami propensity scores of >588 were identified from the fraction (molecular weight ≤1 kDa) using nano-LC-QTOF-MS, and their concentrations ranged from 0.02 ± 0.01 to 6.94 ± 0.41 µg/L in chicken breast soup. AEEHVEAVN, PKESEKPN, VGNEFVTKG, GIQKELQF, FTERVQ, and AEINKILGN were considered as umami peptides according to sensory analysis results (detection threshold: 0.18-0.91 mmol/L). The measurement of point of subjective equality showed that these six umami peptides (2.00 g/L) were equivalent to 0.53-0.66 g/L of monosodium glutamate (MSG) in terms of umami intensity. Notably, the sensory evaluation results showed that the peptide of AEEHVEAVN significantly enhanced the umami intensity of the MSG solution and chicken soup models. The molecular docking results showed that the serine residues were the most frequently observed binding sites in T1R1/T1R3. The binding site Ser276 particularly contributed to the formation of the umami peptide-T1R1 complexes. The acidic glutamate residues observed in the umami peptides were also involved in their binding to the T1R1 and T1R3 subunits.

A new cross-domain prediction model of air pollutant concentration based on secure federated learning and optimized LSTM neural network.

As air pollution worsens, the fast prediction of air pollutant concentration becomes increasingly important for public health. This paper proposes a new cross-domain prediction model of air pollutant concentration based on federated learning (FL), differential privacy laplace mechanism (DPLA) and long and short-term memory network optimized by sparrow search algorithm (SSA-LSTM), named FL-DPLA-SSA-LSTM. Firstly, with FL, SSA-LSTM is used as local training model for each city and predicts air pollutant concentration. Secondly, DPLA is used to add noise to the local model parameters, which can protect local data security. Then, the global model is updated by using the federated averaging algorithm (FedAvg). Lastly, FL is used to share global model for all cities, which can safely and quickly cross-domain predict air pollutant concentration. For data set, it is taken from hourly air pollutants and meteorological data from 12 cities in the Fenhe River and Weihe River Plains in China in 2020. The experimental results show that the prediction performance of the proposed model is significantly better than all comparison models. FedAvg updating with local model parameters with DPLA noise has little effect on the performance of the global model and even exceeds that of the global model. The calculation time of FL-DPLA-SSA-LSTM model is reduced by 99.95% compared with that of not using FL-DPLA machine learning model. It is proved that the model is high sharing and high safety, which greatly improves the training efficiency and has better generalization ability. It is significant for joint air pollution prevention and control and environmental protection.

Speckle Tracking Echocardiography Verified the Efficacy of Qianyangyuyin Granules in Alleviating Left Ventricular Remodeling in a Hypertensive Rat Model.

BACKGROUND: Global longitudinal strain (GLS) can be assessed by speckle tracking echocardiography (STE) to express the degree of cardiac fibrosis. Qianyangyuyin (QYYY) granules can effectively improve GLS in hypertensive patients. Using a hypertensive rat model, we carried out speckle tracking echocardiography to validate the effect of QYYY in diminishing LV remodeling. METHODS: We randomly divided 16 spontaneously hypertensive rats (SHRs) into SHR, SHR + valsartan (SHR + V), SHR + low-dose QYYY (SHR + QL), and SHR + high-dose QYYY (SHR + QH) groups, with four rats in each group. Another group of 4 Wistar-Kyoto (WKY) rats were selected into a normal control (WKY) group. At the 8th week, conventional echocardiographic parameters were measured by GE Vivid E95 ultrasound (12S probe, 10-12 MHz) and GLS by speckle tracking echocardiography with EchoPAC (version 203) software. HE and Masson's trichrome staining were performed to detect the cardiomyocyte width and collagen volume fraction after rat sacrifice. Collagen I, α-SMA, S100A4, TGF-ß, Smad 3, MYH6, and MYH7 were further analyzed by Western blot. RESULTS: The absolute values of GLS significantly increased in the SHR + QH group compared to the SHR group, while the CVF and CW values significantly decreased. In addition, Collagen I, α-SMA, S100A4, TGF-ß, Smad3, MYH7, and MYH7/MYH6 ratio remarkably reduced in the SHR + QH group. The value of GLS could be repetitively measured and positively correlated with the collagen volume fraction of the myocardium and the cardiomyocyte width of the left ventricular free wall. CONCLUSIONS: GLS is a reliable indicator to evaluate the therapeutic effect on left ventricular remodeling in hypertension. QYYY granules can inhibit the development of cardiac fibrosis in the hypertensive rat model.

Combined associations of obesity and metabolic health with subclinical left ventricular dysfunctions: Danyang study.

AIMS: The association of strictly defined metabolic healthy obese (MHO) with subclinical cardiac function was unclear. Our study aims to examine the role of MHO in subclinical cardiac dysfunction in a Chinese population. METHODS AND RESULTS: The study subjects were recruited from Danyang from 2017 to 2019. Obesity was defined by body mass index (BMI) categories (normal weight, overweight and obesity). Metabolic health was strictly defined as having neither any of the guidelines recommended metabolic syndrome components nor insulin resistance. Thus, subjects were grouped by BMI categories and metabolic health status as six groups. Preclinical systolic (global longitudinal strain [GLS]) and diastolic function were assessed by 2D speckle tracking, and transmitral and tissue Doppler imaging, respectively. The 2757 participants (mean age ± standard deviation, 52.7 ± 11.7 years) included 1613 (58.5%) women, 999 (36.2%) obese, 2080 (75.4%) metabolically unhealthy and 93 (3.4%) MHO participants. After adjustment for covariates, the trend was similar for left ventricular (LV) ejection fraction (Ptrend  ≥ 0.07) but significantly worse for GLS, e' and E/e' (Ptrend  ≤ 0.02) across the six groups or passing from normal weight to obese individuals irrespective of metabolic status. MHO participants had lower GLS (20.4 vs. 21.4%) and e' (9.6 vs. 10.6 cm/s) compared with controls (P < 0.0001) but had similar GLS (P = 0.47) compared with metabolically unhealthy obese (MUO). Regardless of obesity status, metabolically unhealthy participants had worse diastolic function compared with their metabolically healthy counterparts (P ≤ 0.0004). Compared with controls, MHO individuals were at higher risk of subclinical LV systolic dysfunction (OR = 3.44, 95% CI = 1.25-9.49, P = 0.02). These results were robust to sensitivity analysis. CONCLUSIONS: MHO was substantially associated with worse subclinical systolic function although early diastolic dysfunction seemed to be more accentuated in MUO.

Association of urine albumin-to-creatinine ratio with subclinical systolic dysfunction in hypertensive patients but not normotensive subjects: Danyang study.

The association of albuminuria, as measured by urine albumin-to-creatinine ratio (UACR) concentration, with subclinical cardiac dysfunction in hypertensive patients is unclear. Our study aimed to examine its relationship in hypertensive patients compared with that in normotensive patients. The study participants were recruited from Danyang, a city of Jiangsu Province from 2017 to 2019. Categorical and continuous analyses were performed with sex-specific UACR tertiles and natural logarithmically transformed UACR, respectively. Comprehensive echocardiography including conventional imaging, tissue Doppler imaging, and 2D speckle tracking was performed using Philips CX50 device. The 2857 participants (mean age = 52.7 ± 11.8 years) included 1673 (58.6%) women, 1125 (39.4%) hypertensive patients, 546 (19.1%) patients with microalbuminuria, and 38 (1.3%) patients with macroalbuminuria. Comorbidities were increasingly prevalent across the tertiles of UACR. Increased left ventricular (LV) mass index, decreased global longitudinal strain (GLS) and LV ejection fraction, lower E/A ratio and e' velocity, and higher E/e' ratio were significantly associated with higher UACR on unadjusted analyses (p ≤ .01). After adjustment for covariates, UACR was only independently associated with lower GLS (tertile 3 = 20.7% vs. tertile 1 = 20.9%; p = .04). The results of hypertensive patients (p ≤ .04) but not normotensive patients (p ≥ .16) were similar to those of the total cohort. Subgroup analyses revealed similar results in patients without coronary artery disease, or without LV hypertrophy, or without diabetes. In conclusion, increased UACR is associated with worse subclinical systolic function in Chinese hypertensive patients but not in normotensive participants.

Fine-grained diabetic wound depth and granulation tissue amount assessment using bilinear convolutional neural network.

Diabetes mellitus is a serious chronic disease that affects millions of people worldwide. In patients with diabetes, ulcers occur frequently and heal slowly. Grading and staging of diabetic ulcers is the first step of effective treatment and wound depth and granulation tissue amount are two important indicators of wound healing progress. However, wound depths and granulation tissue amount of different severities can visually appear quite similar, making accurate machine learning classification challenging. In this paper, we innovatively adopted the fine-grained classification idea for diabetic wound grading by using a Bilinear CNN (Bi-CNN) architecture to deal with highly similar images of five grades. Wound area extraction, sharpening, resizing and augmentation were used to pre-process images before being input to the Bi-CNN. Innovative modifications of the generic Bi-CNN network architecture are explored to improve its performance. Our research generated a valuable wound dataset. In collaboration with wound experts from University of Massachusetts Medical School, we collected a diabetic wound dataset of 1639 images and annotated them with wound depth and granulation tissue grades as labels for classification. Deep learning experiments were conducted using holdout validation on this diabetic wound dataset. Comparisons with widely used CNN classification architectures demonstrated that our Bi-CNN fine-grained classification approach outperformed prior work for the task of grading diabetic wounds.