By retrospectively reviewing the current status of traditional Chinese medicine (TCM) and Western medicine treatments of chronic nonbacterial prostatitis (CNP), the TCM understanding of its etiologies and pathogenesis, the therapeutic principles and the mechanisms of acupuncture treatment of CNP, the clinical study strategies of acupuncture treatment for CNP were further proposed, which could provide more scientific basis and support for the definite longer-term therapeutic efficacy of acupuncture treatment of CNP. Breakthrough in the treatment of CNP will be achieved with the application of acupuncture therapy both in clinical practice and experimental research.

Cerebral ischemia is one of the most common diseases treated by acupuncture therapeutics. Recent studies indicated that acupuncture treatment by needling the conception and governor vessels had positive effects in promoting neural regeneration in patients after cerebral ischemia injury. Acupuncture intervention could continuously promote the proliferation and differentiation of the neural stem cells in the brain, obviously up-regulate expression of growth factors, accelerate angiogenesis and inhibit apoptosis. Hence, it is necessary to present an exhaustive review on the mechanisms. The present review gives a detailed description of pathological changes of cerebral ischemia and acupuncture intervention applied to the conception and governor vessels, and proposes research prospects in the future.

OBJECTIVETo investigate the combined effects of alcohol consumption and obesity hypertension risk.

METHODSBased on data from program "Prevention of multiple metabolic disorders and metabolic syndrome in Jiangsu province", Baseline data were obtained in April 1999 to Jun 2004, we conducted the follow up investigation from March 2006 to October 2007 for subjects, those follow up time meet 5 years. A total of 4 083 participants completed the follow-up survey, and 2 778 eligible participants for final analysis. In the baseline and follow up survey, participants returned a completed questionnaire with information on diet, education, occupation, lifestyle factors, and medical history. Data on demographic characteristics, physical examination and laboratory tests were also obtained. Cox proportional hazards regression model was used to investigate the association between body mass index (BMI), waist circumference (WC) and waist to height ratio (WHtR). Logistic regression model was used to examine the interaction of alcohol consumption with WC, BMI and WHtR on risk of hypertension and the relative excess risk due to interaction (RERI), the attributable proportion due to interaction (AP), and the synergy index (SI) were calculated. If the 95% CI of SI do not include 1, the 95% CI of RERI and AP do not include 0, the interactions are statistically significant.

RESULTSIn the study subjects, 660 patients (254 males and 406 females) were new cases, who developed hypertension by the follow-up investigation. The mean of WC, BMI and WHtR were (23.3 ± 3.2) kg/m(2), (77.7 ± 9.0) cm and 0.49 ± 0.06, were higher than that in normal subjects ((22.4 ± 3.0) kg/m², (74.8 ± 8.5) cm and 0.47 ± 0.05, all P values < 0.001). After adjustment for age, sex, smoking status, family history of hypertension, the hazard ratio of EH for participants with obesity, high WC, high WHtR and alcohol consumption were higher, the HR (95% CI) were 2.12 (1.46-3.10), 1.64 (1.32-2.03), 2.80 (1.73-4.59) and 1.65 (1.29-2.12). HR (95% CI) of subjects with both abnormal BMI and current alcohol consumption was 2.76 (2.45-3.17), SI (95% CI) was 1.60 (0.48-5.28), RERI(95%CI) was 0.66 (-0.47-1.79) and AP was 0.24 (-0.22-0.69), HR (95% CI) of subjects with both high WC and current alcohol consumption was 4.93 (2.87-8.49), SI(95% CI) was 4.49(1.97-10.22), RERI (95%CI) was 3.06 (0.48-5.64) and AP(95% CI) was 0.62 (0.41-0.83), HR (95% CI) of subjects with both high WHtR and current alcohol consumption was 2.80 (1.73-4.59), SI (95% CI) was 2.14 (0.88-5.17), RERI was 0.96 (0.48-5.64) and AP (95% CI) was 0.34 (0.03-0.68).

CONCLUSIONBoth obesity, high WC, high WHtR, and alcohol consumption were strong risk factors of EH, and impact of an additive interaction of alcohol consumption and high WC on EH risk existed.

Alcohol Drinking ; epidemiology ; Body Mass Index ; Female ; Humans ; Hypertension ; epidemiology ; Incidence ; Logistic Models ; Male ; Obesity ; epidemiology ; Proportional Hazards Models ; Risk Factors ; Waist Circumference ; Waist-Height Ratio

OBJECTIVETo investigate the impact of dynamic change of waist circumference or body mass index (BMI) on type 2 diabetes mellitus (T2DM) populations in a cohort study.

METHODSWe not only obtained the baseline survey data from program 'Prevention of Multiple Metabolic Disorders and metabolic syndrome (MS) in Jiangsu Province'(PMMJS) which started in 1994, and we conducted twice follow-ups from January 2002 to August 2003, and March 2006 to November 2007. After excluding subjects who were found to have T2DM at baseline, cardiovascular disease(CVD), and BMI<18.5 kg/m(2) , and loss to follow up because of relocation, death or other reasons, a total of 3 461 subjects were included in this analysis. They received investigation including questionnaires investigation, measurement and laboratory examination. The differences of gender, smoking, alcohol drinking and T2DM family history in different groups were examined using χ(2)-test, median and inter-quartile range were calculated for TG, and they were examined by rank test. Four equal parts of the differences of waist circumference and BMI were carried out in the COX regression model, to investigate the association between 2 years change of waist circumference or BMI and incidence of T2DM. We also examined the association between BMI and waist circumference modification and incident risk of T2DM in subjects with normal baseline BMI, baseline obese subjects, subjects with normal baseline waist circumference and baseline abdominal obese subjects.

RESULTSA total of 3 461 participants (1 406 males, 2 055 females) were investigated, including 160 new T2DM cases (60 males, 100 females) who were from between baseline and the second following up. The accumulative incidence was 4.6% (60/3 461). Multivariate COX regression model analysis results showed that the T2DM risk was relatively high in the highest quartile of waist circumference D-value group(HR=2.06, 95% CI: 1.27-3.16), the T2DM risk was also high in the highest quartile of BMI D-value group (HR=1.30, 95% CI: 0.86-1.95). In subjects with abdominal obesity and normal waist circumference at baseline, the incidence rate of T2DM in non-control group was 7.1% (40/565) , 6.3% (45/645), higher than that in control group (3.4%(71/2 096), 4.5%(4/155)) (χ(2) values were 3.98 and 15.18, P values were 0.043 and <0.001). In subjects with normal waist circumference, T2DM risk was higher in non-control group than that in control group (HR=2.12, 95% CI: 1.40-3.22). In abdominal obese subjects, T2DM risk was also higher in non-control group than that in control group (HR=1.14, 95% CI: 1.04-1.92). If waist circumference was not controlled, T2DM risk was high, no matter BMI controlled or not (HR(95% CI) were 1.73(1.17-2.54), 2.45(1.63-3.69) respectively).

CONCLUSIONControlling the waistline could reduce the risk of diabetes, and once waist circumference was not controlled, T2DM risk would be increased no matter BMI was controlled or not.

Alcohol Drinking ; Body Mass Index ; Cardiovascular Diseases ; Cohort Studies ; Diabetes Mellitus, Type 2 ; epidemiology ; Female ; Humans ; Incidence ; Male ; Multivariate Analysis ; Obesity ; epidemiology ; Obesity, Abdominal ; epidemiology ; Risk Factors ; Smoking ; Waist Circumference

The Assistive Devices Program was funded and supported sufficiently, and improved the qulity of life of the disabled persons significantly (scores of SF-36). Most disabled users were satisfied with the Program. Some problems, such as inefficient way of working,undefined screening standards, lack of integrity of the assessment content, limited categories of assistive devices and home modifications,unavailable follow-up services, needed to be improved.

OBJECTIVETo examine the main effect of 10 Peroxisome proliferators-activated receptor (PPAR) SNP in contribution to non-HDL-C and study whether there is an interaction in the 10 SNPs.

METHODSParticipants were recruited within the framework of the PMMJS (Prevention of Multiple Metabolic Disorders and Metabolic Syndrome in Jiangsu province) cohort-population-survey, which was initiated from April 1999 to June 2004, and 5-year follow-up data from total 4 582 subjects were obtained between March 2006 and October 2007. A total of 4 083 participants received follow-up examination. After excluding subjects who had experienced stroke or exhibited cardiovascular disease, type 2 diabetes or a BMI <18.5 kg/m(2), a total of 820 unrelated individual subjects were selected from 3 731 subjects on October of 2009. Blood samples which were collected at the baseline were subjected to PPARα, PPARδ and PPARγ 10 SNPs genotype analysis. Logistic regression model was used to examine the association between 10 SNPs in the PPARs and non-HDL-C. Interactions within the 10 SNP were explored by using the Generalized Multifactor Dimensionality Reduction (GMDR).

RESULTSA total of 820 participants (mean age was 50.05±9.41) were included in the study and 270 were males and 550 were females. Single-locus analysis showed that after adjusting gender, age, smoking, alcohol consumption, physical activity, high-fat diet and low-fiber diet factors, rs1800206-V and rs3856806-T were significantly associated with higher non-HDL-C levels. V allele (LV + VV genotype) carriers of rs1800206 have a average non-HDL-C levels on (3.15 ± 0.89)mg/L (F = 15.01, P = 0.002); T allele (CT+TT genotype) carriers of rs3856806 have a average non-HDL-C levels on (3.03±1.01) mg/L (F = 9.87, P = 0.005). GMDR model analysis showed that after adjusting the same factors, two-locus model, five-locus model, six-locus model and seven-order interaction models were all statistically significant (P<0.05), and the seven-locus model (rs1800206, rs3856806, rs135539, rs4253778, rs2016520, rs1805192, rs709158) was the best model (P = 0.001), the cross-validation consistency was 10/10 and testing accuracy was 0.656.

CONCLUSIONRs1800206 and rs3856806 were significantly associated with non-HDL-C. And there was an gene-gene interaction among rs1800206, rs3856806, rs1800206, rs135539, rs4253778, rs2016520, rs1805192, rs3856806 and rs709158 which could influence the non-HDL-C levels.

Alleles ; Cardiovascular Diseases ; Cholesterol ; Diabetes Mellitus, Type 2 ; Female ; Genetic Phenomena ; Genotype ; Humans ; Logistic Models ; Male ; Middle Aged ; Overweight ; PPAR alpha ; PPAR delta ; PPAR gamma ; Peroxisome Proliferator-Activated Receptors ; Polymorphism, Single Nucleotide ; Stroke