The impact of metabolic diseases and their comorbidities for stroke in a middle-income area of China: a case-control study.

BACKGROUND: There are few studies on the comorbidity of hypertension (HTN), diabetes mellitus (DM) and dyslipidemia (DLP) associated with stroke. We aimed to explore the relationship between the number of metabolic diseases and stroke and its different subtypes, and to reveal whether metabolic diseases alone or coexist can significantly increase the risk of stroke. METHODS: We completed a multi-center case-control study in Jiangxi Province, China. Neuroimaging examination was done in all cases. Controls were stroke-free adults recruited from the community in the case concentration area and matched with the cases in 1:1 ratio by age and sex. Odds ratios (OR) were calculated by conditional logistic regression. RESULTS: We enrolled 11,729 case-control pairs. The estimated ORs among patients with 1, 2 and 3 metabolic diseases were 3.16 (2.78-3.60), 7.11 (6.16-8.20), 12.22 (9.73-15.36), respectively after adjusting age, body mass index, urban-rural areas, cardiac disease, smoking, alcohol intake, physically active, high intake of salt, meat-biased diet, high homocysteine. The coexistence of HTN and DM (OR: 7.67), the coexistence of HTN and DLP (OR:7.58), and the coexistence of DM and DLP (OR:3.64) can all significantly increase the risk of stroke. HTN alone or combined other metabolic diseases were significantly more strongly associated with intracerebral haemorrhage than ischemic stroke. CONCLUSIONS: The risk of stroke increased with the number of chronic metabolic diseases. It is necessary to regularly monitor blood pressure, blood sugar and blood lipids and strengthen lifestyle management and take appropriate drug interventions to prevent exposure to multiple metabolic diseases based on existing conditions.

Construction and validation of a 6-gene nomogram discriminating lung metastasis risk of breast cancer patients.

Breast cancer is the most common malignant disease in women. Metastasis is the foremost cause of death. Breast tumor cells have a proclivity to metastasize to specific organs. The lung is one of the most common sites of breast cancer metastasis. Therefore, we aimed to build a useful and convenient prediction tool based on several genes that may affect lung metastasis-free survival (LMFS). We preliminarily identified 319 genes associated with lung metastasis in the training set GSE5327 (n = 58). Enrichment analysis of GO functions and KEGG pathways was conducted based on these genes. The best genes for modeling were selected using a robust likelihood-based survival modeling approach: GOLGB1, TMEM158, CXCL8, MCM5, HIF1AN, and TSPAN31. A prognostic nomogram for predicting lung metastasis in breast cancer was developed based on these six genes. The effectiveness of the nomogram was evaluated in the training set GSE5327 and the validation set GSE2603. Both the internal validation and the external validation manifested the effectiveness of our 6-gene prognostic nomogram in predicting the lung metastasis risk of breast cancer patients. On the other hand, in the validation set GSE2603, we found that neither the six genes in the nomogram nor the risk predicted by the nomogram were associated with bone metastasis of breast cancer, preliminarily suggesting that these genes and nomogram were specifically associated with lung metastasis of breast cancer. What's more, five genes in the nomogram were significantly differentially expressed between breast cancer and normal breast tissues in the TIMER database. In conclusion, we constructed a new and convenient prediction model based on 6 genes that showed practical value in predicting the lung metastasis risk for clinical breast cancer patients. In addition, some of these genes could be treated as potential metastasis biomarkers for antimetastatic therapy in breast cancer. The evolution of this nomogram will provide a good reference for the prediction of tumor metastasis to other specific organs.

Comparative Study of Two Methods of Enteric Virus Detection and Enteric Virus Relationship with Bacterial Indicator in Poyang Lake, Jiangxi, China.

Currently, water contaminated with fecal matter poses a threat to public health and safety. Thus, enteric viruses are tested for as a part of water quality indicator assays; however, enteric viruses have not yet been listed in the criteria. Effective and sensitive methods for detecting enteric viruses are required in order to increase water safety. This study utilized enteric viruses as possible alternative indicators of water quality to examine fresh water in six sites in Poyang Lake, Nanchang, Jiangxi Province. The presence of norovirus geno-groups II (NoV GII), enteroviruses (EoV) and adenoviruses (AdV) were determined using Tianjin's protocol and Hawaii's protocol during a six month period from 2016-2017. The former used an electropositive material method for viral concentration and Taqman-q reverse transcription polymerase chain reaction (RT-PCR) to detect enteric viruses; while the latter used a filtration-based method for viral concentration and RT-PCR for enteric virus detection. There is a statistically significant difference between Tianjin's method and Hawaii's method for the detection of enteric viruses, such as NoV GII, EoV, and AdV (n = 36, p < 0.001). The enteric viruses showed no significant positive correlation with bacteria indicators (n = 36, p > 0.05). These data stress the need for additional indicators when establishing water quality systems, and the possibility of using enteric viruses as water quality indicators. It has become essential to improve shortcomings in order to search for an adequate method to detect enteric viruses in water and to implement such method in water quality monitoring.

XRCC1 polymorphisms and lung cancer risk in Chinese populations: a meta-analysis.

X-ray repair cross-complementing group 1 (XRCC1), one of the >20 genes that participate in the base excision repair (BER) pathway, is thought to account for differences in lung cancer susceptibility. Our meta-analysis on 2861 cases (lung cancer patients) and 2783 controls from eight eligible studies in Chinese populations showed that for the XRCC1 Arg194Trp polymorphism, compared with the Arg/Arg homozygous genotype, the variant Arg/Trp and Trp/Trp genotypes combined was not associated with lung cancer risk (OR=1.06, 95% confidence interval [CI]=0.89-1.27) (Z=0.70, P=0.48), nor was Arg280His (OR=0.63, 95% CI=0.28-1.41) (Z=1.12, P=0.26); however, for the XRCC1 Arg399Gln polymorphism, the combination of variant Arg/Gln and Gln/Gln genotypes was borderline significantly associated with lung cancer risk (OR=1.16, 95% CI=1.00-1.36) (Z=1.90, P=0.06), compared with the Arg/Arg homozygous genotype. Therefore, in the eight published studies in Chinese populations, we found little evidence of an association between the combined variant genotypes of the XRCC1Arg399Gln polymorphism and the increased risk of lung cancer.