[Association between resting heart rate and metabolic syndrome: a cohort study].

Objective: To investigate the association between resting heart rate (RHR) and subsequent metabolic syndrome (MS). Methods: Under a cluster design, participants age ≥18 years old were selected from a rural area of Henan province in China. Interview through questionnaire, physical examination, fasting blood glucose, and lipid profile measurements were done from July to August of 2007 and July to August of 2008. Same methods were implemented in the follow-up examination, during July to August of 2013 and July to October of 2014. Results: During the 6-year follow-up period, cumulative incidence rates of MS for overall, male, and female participants appeared as 21.89%(1 933/8 829), 16.78%(664/3 957) and 26.05%(1 269/4 872), respectively. After controlling for potential confounders and compared with the groups of RHR<60 bpm, 60-69, 70-79, 80-89 and ≥90 bpm, the ORs (95%CIs) of MS for overall, male, and female participants became 1.24(0.95-1.60), 1.42(1.10-1.84), 1.63(1.24-2.15) and 1.62(1.16-2.27); 1.12(0.81-1.55), 1.23(0.88-1.71), 1.42 (0.97-2.07) and 1.84(1.09-3.11); 1.46(0.93-2.29), 1.70(1.09-2.65), 1.99(1.25-3.16) and 1.78(1.06-2.98); respectively. Conclusions: The risk on MS appeared higher in females than in males while the risk for MS increased with the elevation of RHR. Intensive intervention programs that targeted adult participants with elevated RHR, especially in females, should be formulated and implemented.

[Prevalence and risk factors of dyslipidemia in a rural population of Henan Province, China].

Objective: The purpose of this study was to investigate the prevalence and risk factors of dyslipidemia in a rural population of Henan Province, China. Methods: A total of 20 194 participants aged ≥18 years were selected randomly by cluster sampling from two townships(towns)in Henan Province from July to August 2007 and July to August 2008. Investigations included questionnaires, anthropometric measurements, fasting plasma glucose, and lipid profile examination at baseline. A total of 16 155 participants were followed up from July to August 2013 and July to October 2014. Overall, 13 869 participants were included in the study, after excluding 2 286 participants with incomplete dyslipidemia follow-up data. Distributions of the characteristics of dyslipidemia were determined, and prevalence was standardized by age according to data of the 2010 Sixth National Population Census. Risk factors for dyslipidemia were analyzed using a logistic regression model after adjusting for sex, age, education level, marital status, and income status. Results: The prevalence of dyslipidemia was 53.72%(7 450/13 869)for residents aged ≥22 years living in rural areas of Henan Province(59.32%(3 069/5 174)for men and 50.39%(4 381/8 695)for women). The adjusted prevalence of dyslipidemia was 50.50%(59.27% for men and 45.53% for women). The prevalence of hypercholesterolemia, hypertriglyceridemia, low HDL-C, and high LDL-C was 4.34%(602/13 868), 20.42%(2 826/13 837), 42.75%(5 927/13 865), and 3.14%(420/13 375), respectively, and the adjusted prevalence was 2.44%, 18.84%, 41.42%, and 1.86%, respectively. Logistic regression analyses showed that alcohol consumption(OR=1.27, 95% CI: 1.05-1.53), family history of hyperlipidemia(OR=1.29, 95% CI: 1.17-1.43), overweight(OR=1.40, 95% CI: 1.22-1.61), obesity(OR= 1.65, 95% CI: 1.39- 1.96), abnormal waist circumference(OR=1.22, 95% CI: 1.04- 1.43), and abnormal waist-height ratio(OR=1.21, 95% CI: 1.01-1.45)were significant independent risk factors, and high levels of physical activity(OR=0.85, 95% CI: 0.77- 0.95)and underweight(OR=0.52, 95% CI: 0.36- 0.75)were protective factors for dyslipidemia after adjusting for sex, age, education level, marital status, and income status. Conclusion: The prevalence of dyslipidemia was very high for this rural population. Alcohol consumption, family history of hyperlipidemia, overweight, obesity, abnormal waist circumference, and abnormal waist-height ratio were significant independent risk factors for dyslipidemia.

[Establishing a noninvasive prediction model for type 2 diabetes mellitus based on a rural Chinese population].

OBJECTIVE: To provide a noninvasive type 2 diabetes mellitus (T2DM) prediction model for a rural Chinese population. METHODS: From July to August, 2007 and July to August, 2008, a total of 20 194 participants aged ≥18 years were selected by cluster sampling technique from a rural population in two townships of Henan province, China. Data were collected by questionnaire interview, anthropometric measurement, and fasting plasma glucose and lipid profile examination. A total 17 265 participants were followed up from July to August, 2013 and July to October, 2014. Finally, 12 285 participants were selected for analysis. Data for these participants were randomly divided into a derivation group (derivation dataset, n= 6 143) and validation group (validation dataset, n=6 142) by 1∶1, respectively. Randomization was carried out by the use of computer-generated random numbers. A Cox regression model was used to analyze risk factors of T2DM in the derivation dataset. A T2DM prediction model was established by multiplying ß by 10 for each significant variable. After the total score was calculated by the model, analysis of the receiver operating characteristic (ROC) curve was performed. The area under the ROC curve (AUC) was used for evaluating model predictability. Furthermore, the model's predictability was validated in the validation dataset and compared with the Finnish Diabetes Risk Score (FINDRISC) model. RESULTS: A total 779 of 12 285 participants developed T2DM during the 6-year study period. The incidence rate was 6.12% in the derivation dataset (n=376) and 6.56% in the validation dataset (n=403). The difference was not statistically significant (χ(2)=1.00, P=0.316). A total of four noninvasive T2DM prediction models were established using the Cox regression model. The ROCs of the risk score calculated by the prediction models indicated that the AUCs of these models were similar (0.67-0.70). The AUC and Youden index of model 4 was the highest. The optimal cut-off value, sensitivity, specificity, and Youden index were scores of 25, 65.96%, 66.47%, and 0.32, respectively. Age, sleep time, BMI, waist circumference, and hypertension were selected as predictive variables. Using age<30 years as reference, ß values were 1.07, 1.58, and 1.67 and assigned scores were 11, 16, and 17 for age groups 30-44, 45-59, and ≥60 years, respectively. Using sleep time<8.0 h/d as reference, the ß value and assigned score were 0.27 and 3, respectively, for sleep time ≥10.0 h/d. Using BMI 18.5-23.9 kg/m(2) as reference, ß values were 0.53 and 1.00 and assigned scores 5 and 10, respectively, for BMI 24.0-27.9 kg/m(2), and ≥28.0 kg/m(2). Using waist circumference <85 cm for males/< 80 cm for females as reference, ß values were 0.44 and 0.65 and assigned scores 4 and 7, respectively, for 85 cm ≤ waist circumference <90 cm for males/80 cm≤ waist circumference <85 cm for females, and waist circumference ≥90 cm for males/≥85 cm for females. Using nonhypertension as reference, the respective ß value and assigned score were 0.34 and 3 for hypertension. The AUC performance of this model and the FINDRISC model was 0.66 and 0.64 (P=0.135), respectively, in the validation dataset. CONCLUSION: Based on this cohort study, a noninvasive prediction model that included age, sleep time, BMI, waist circumference, and hypertension was established, which is equivalent to the FINDRISC model and applicable to a rural Chinese population.

[Body mass index, waist circumference and waist-to-height ratio associated with the incidence of type 2 diabetes mellitus: a cohort study].

OBJECTIVE: To investigate the association between body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), and the incidence risk of type 2 diabetes mellitus (T2DM). METHODS: In total, 20 194 participants ≥18 years old were selected randomly by cluster sampling from two township (town) of the county in Henan province from July to August of 2007 and July to August of 2008 and the investigation included questionnaires, anthropometric measurements, fasting plasma glucose, and lipid profile examination were performed at baseline; 17 236 participants were enrolled in this cohort study. 14 720 (85.4%) were followed up from July to August 2013 and July to October 2014. Finally, 11 643 participants (4 301 males and 7 342 females) were included in this study. Incidence density and Cox proportional hazards regression models were used to evaluate the risk of T2DM associated with baseline BMI, WC, WHtR, and their dynamic changes. RESULTS: After average of 6.01 years following up for 11 643 participants, 613 developed T2DM and the incidence density was 0.89 per 100 person-years. After adjusted for baseline sex, age, smoking, drinking, family history of diabetes, as well as the difference of fasting plasma-glucose (FPG), total cholesterol (TC), triglyceride (TG), high density lipoprotein cholesterol (HDL-C), systolic blood pressure (SBP), diastolic blood pressure (DBP) between baseline and follow-up, Cox Proportional-Hazards regression analysis indicated that T2DM risk of baseline BMI overweight group, BMI obesity group, abnormal WC group and abnormal WHtR group were significantly higher than that of the corresponding baseline normal groups , and the incidence risk of T2DM reached the highest for those whose baseline BMI, WC and WHtR were all abnormal, the corresponding HR (95%CI) were 2.05 (1.62-2.59), 3.01 (2.33-3.90), 2.34 (1.89-2.90), 2.88 (2.21-3.74), 3.32 (2.50-4.40), respectively. Whether baseline BMI/WC was normal or not, T2DM risk increased if baseline WHtR was abnormal, and the HR (95%CI) of baseline normal BMI/abnormal WHtR group, baseline abnormal BMI/abnormal WHtR group, baseline normal WC/abnormal WHtR group, baseline abnormal WC/abnormal WHtR group were 1.88 (1.29-2.74), 3.08 (2.34-4.05), 2.15(1.53-3.00), 3.22 (2.45-4.23), respectively. The analysis for dynamic changes of BMI, WC, and WHtR indicated that in baseline normal WC or WHtR group, T2DM risk increased when baseline normal WC or WHtR developed abnormal at follow-up, and the corresponding HR (95%CI) were 1.79 (1.26-2.55), 2.12(1.32-3.39), respectively. In baseline abnormal WC or WHtR group, T2DM risk decresed when baseline abnormal WC or WHtR reversed to normal at follow-up, and the corresponding HR (95%CI) were 2.16 (1.42-3.29), 2.62 (1.63-4.20), respectively. CONCLUSION: BMI, WC, and WHtR were associated with increased T2DM risk. The more abnormal aggregation of BMI, WC, and WHtR presents, the higher T2DM risk was. T2DM risk could be decreased when abnormal WC or WHtR reversed to normal.

Block of induction and maintenance of calcium-induced LTP by inhibition of protein kinase C in postsynaptic neuron in hippocampal CA1 region.

Calcium-induced LTP (Ca-LTP) refers to the long-lasting potentiation of synaptic transmission in hippocampal synapses that can be induced by a transient (7-10 min) and small increase (from 2 mM to 4 mM) in extracellular calcium concentration. In this paper the effects of protein kinase C (PKC) inhibitors, polymyxin B (PMB) and PKC(19-31), given intracellularly to the postsynaptic neuron in the CA1 region, on the induction and maintenance of Ca-LTP were studied and compared with those found in a similar study earlier made in this laboratory on tetanic stimulation-induced LTP (TS-LTP) [18]. When the intracellular delivery of the inhibitor(s) was made to begin 30 min before the exposure to increased [Ca2+]0, the development of Ca-LTP was completely blocked, leaving only a brief enhancement of EPSPs directly attributable to the brief increase in [Ca2+]0. When the intracellular delivery of either PKC(19-31) alone or PMB+PKC(19-31) was made to begin after the full establishment of Ca-LTP, it soon made the maintained potentiation begin to decline, the EPSP amplitude gradually returning to the control value before the exposure to increased calcium. Thus postsynaptic PKC inhibition blocks both the induction and the maintenance of Ca-LTP, just as it has been shown to do to TS-LTP. But quantitative differences exist: both the induction and the maintenance of Ca-LTP appeared to be more susceptible to block by postsynaptic PKC inhibition than those of TS-LTP.

The neuromuscular junction revisited: Ca2+ channels and transmitter release in cholinergic neurones in Xenopus nerve and muscle cell culture.

Although the entry of calcium ions into the presynaptic nerve terminals though voltage-gated Ca2+ channels is now universally recognized as playing an essential role in evoked transmitter release at the neuromuscular junction (NMJ), and indeed in chemical synapses generally, we have as yet very little direct knowledge of the Ca2+ channels of the presynaptic terminals. In this work, making use of co-cultured nerve and muscle cells from Xenopus embryos, we studied the NMJ formed between the soma of identified cholinergic neurones and myoball, which allowed the use of patch-clamps on both the pre- and postsynaptic components. Both whole-cell and single-channel recordings of Ca2+ channels in the presynaptic cell were made. We found only one type of voltage-gated Ca2+ channel with high-voltage activation and slow inactivation characteristics, allowing its classification either as the L or the N type. The channels were susceptible to block by metenkephalin but not to block by nifedipine or to enhancement by Bay K 8644. This combination of pharmacological properties favours their classificaiton as the N type. Preliminary observations on the correlation between calcium currents and transmitter release disclosed a strikingly rapid run-down of the evoked release with unchanged calcium currents and spontaneous release during whole-cell recording, indicating a specific wash-out effect on some link between calcium entry and evoked transmitter release.

Of post-denervation hypertrophy in chick slow muscle fibres after complete elimination of stretch and tension.

For the slow muscle fibres in the pure slow muscle ALD as well as in two mixed muscles, flexor metacarpi ulnaris and sartorius, it is demonstrated that the phenomenon of post-denervation hypertrophy still occurs under conditions preventing stretch of muscle after denervation or even in tenotomized muscles in shortened state relieved of tension. Striking differences between the slow fibres of the ALD and those of the mixed muscles are seen, both with respect to their histochemical property and to the degree of development of post-denervation hypertrophy. The slow fibres in mixed muscles show the phenomenon of post-denervation hypertrophy in a much more striking form than do the ALD fibres, and should be used in further studies of the phenomenon.