BackgroundThe exact pathogenic mechanism of knee osteoarthritis (OA) is still unknown. With the exception of clinical treatment to alleviate symptoms, or total knee replacement, there is currently no effective treatment method. Consequently, an in-depth etiological and epidemiological study of knee OA can provide clues for diagnosis, treatment and scientific research, and will ultimately have a beneficial effect on public health.MethodsA cross-sectional community study in the rural village of Gaoyou was conducted in 3428 Chinese adults (aged ≥ 40 years). Subjects completed an interviewer-administered questionnaire, evaluating knee pain and associated disability, analgesia, use of health services, past medical history, walking, income, smoking, and use of oral contraceptives, and standardized weight-bearing knee radiographs were obtained. Patient demographic characteristics and biochemical parameters were recorded.ResultsSingle-factor regression analysis indicated that age, overweight, central adiposity, high low-density lipoprotein cholesterol (LDLC), high total cholesterol (TC), high triglycerides (TG), dyslipidemia, hypertension and low income were the associated factors for knee OA in females; age, high LDLC, hypertension, low income and frequent walking were the associated factors for knee OA in males. Interestingly, male heavy smokers were less likely to develop severe knee OA compared with non-smokers. Stepwise logistic regression analysis indicated that age and overweight were the associated factors for knee OA for all individuals. Although central adiposity, high LDLC, high TC, high TG, dyslipidemia, hypertension and low income appeared to be related to knee OA in females according to univariate analysis, these factors were not identified in stepwise logistic regression analysis. In addition although age, high LDLC, hypertension and frequent walking were also the associated factors for knee OA in males by stepwise logistic regression analysis, smoking as a protective factor was not identified in this analysis.ConclusionsIn this study, aging, obesity, frequent walking, low income and relevant multiple metabolic disorders were the associated factors for knee OA. Smoking might be associated with a lower prevalence of OA in male smokers according to univariate analysis. A retrospective association of smoking with OA may constitute an important etiologic clue, but further well-designed, large-scale prospective controlled trials are required to confirm these findings.

The aim of this study was to investigate the prognostic value of the lymphocyte-to-monocyte ratio (LMR) in patients undergoing hepatectomy and to compare it to established biomarkers including the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR). Medical records were retrospectively analyzed for 652 HCC patients undergoing hepatectomy at the Affiliated Tumor Hospital of Guangxi Medical University and the First People’s Hospital of Changde between April 2004 to April 2012. The correlation between the LMR and clinical variables were analyzed in Kaplan-Meier log-rank survival analysis and then multivariate Cox regression models trying to find relation with disease-free survival (DFS) and overall survival (OS). The area under the ROC curve (AUC) of the LMR(AUC:0.627) for predicting long-term survival was greater than that of the NLR(AUC:0.600) and the PLR(AUC:0.520).Multivariate analysis showed LMR to be an independent risk factor for OS (P = 0.002), and the NLR and PLR were not independently significant. Subgroup analysis also showed that LMR was significantly associated with poor DFS and OS in patients positive for HBsAg or with cirrhosis (both P < 0.001).Elevated preoperative LMR is an independently associated with poor OS and DFS in HCC patients following curative resection and appears to be superior to NLR and PLR.

It is critical for patients who cannot undergo eradicable surgery to predict the risk of lung cancer recurrence and metastasis; therefore, the physicians can design the appropriate adjuvant therapy plan. However, traditional circulating tumor cell (CTC) detection or next-generation sequencing (NGS)-based methods are usually expensive and timeinefficient, which urge the need for more efficient computational models. In this study, we have established a convolutional neural network (CNN) framework called DeepLRHE to predict the recurrence risk of lung cancer by analyzing histopathological images of patients. The steps for using DeepLRHE include automatic tumor region identification, image normalization, biomarker identification, and sample classification. In practice, we used 110 lung cancer samples downloaded from The Cancer Genome Atlas (TCGA) database to train and validate our CNN model and 101 samples as independent test dataset. The area under the receiver operating characteristic (ROC) curve (AUC) for test dataset was 0.79, suggesting a relatively good prediction performance. Our study demonstrates that the features extracted from histopathological images could be well used to predict lung cancer recurrence after surgical resection and help classify patients who should receive additional adjuvant therapy.

In this study, the expression of neural precursor cell expressed developmentally downregulated 9 (NEDD9) in benign and malignant gastric tissues was investigated, and the significance of NEDD9 in gastric cancer prognosis was explored. Immunohistochemistry was used to detect NEDD9 expression in gastric cancer, nontumor gastric, and normal gastric tissues. The relationship between NEDD9 expression in gastric cancer tissues and the clinicopathologic factors was examined using the Mann-Whitney U test. The two factors between NEDD9 expression and tumor node metastasis (TNM) stage in gastric cancer patients were analyzed by Spearman rank correlation analysis. The Kaplan-Meier method and log-rank test were used to compare the overall survival of NEDD9 negative, weak positive expression, and strong positive expression group. NEDD9 expression rates were significantly higher (P < 0.001) in gastric cancer tissues (162 out of 187, 86.6 %) compared with normal (2 out of 11, 18.2 %) and nontumor (11 out of 58, 19.0 %) gastric tissues. The upregulated NEDD9 expression in gastric cancer tissue was significantly correlated with high preoperative CEA level (P = 0.044), poor differentiation (P = 0.007), tissue invasion (P = 0.015), present lymph node metastasis (P < 0.001), and high TNM stage (P < 0.001). NEDD9 expression was positively correlated with clinical TNM stage. Advancing clinical TNM stage corresponded with higher NEDD9 expression (r s = 0.289, P < 0.001). The overall 5-year survival of gastric cancer patients with strong positive NEDD9 expression was significantly shorter compared with the survival of NEDD9 negative and weakly positive expression group. NEDD9 may be used as a biomarker in the clinical setting to predict the prognosis of gastric cancer patients.