Evidences have shown that dysbiosis could promote the progression of colorectal cancer (CRC). However, the association of dysbiosis and prognosis of CRC is barely investigated. Therefore, we used 16S rRNA gene sequencing approach to determine differences in microbiota among tumor tissues of different prognosis and found that Fusobacterium nucleatum and Bacteroides fragilis were more abundant in worse prognosis groups, while Faecalibacterium prausnitzii displayed higher abundance in survival group. To further explore the prognostic value of the found bacteria, Kaplan–Meier and Cox proportional regression analyses were used and the results exhibited that high abundance of F. nucleatum and B. fragilis were independent indicators of poor patient's survival. Besides, the expression of major inflammatory mediator were analyzed using PCR and western blot methods, and it turned out that high abundance of F. nucleatum was associated with increased expression of TNF-α, β-catenin and NF-κB, while COX-2, MMP-9 and NF-κB were positively related with high B. fragilis level, and high level of F. prausnitzii showed lower expression of β-catenin, MMP-9 and NF-κB. Moreover, immunohistochemical analysis indicated that KRAS and BRAF expression were prominent in F. nucleatum and B. fragilis high abundance group, while MLH1 showed lower expression. In conclusion, F. nucleatum, B. fragilis and F. prausnitzii can be identified as useful prognostic biomarkers for CRC, and dysbiosis might worsen the patients' prognosis by up-regulating gut inflammation level.

SPDP was a safe procedure associated with better short-term outcomes than DPS. SVP could provide more sufficient blood perfusion for the conserved spleen than WT. However, the evidence is limited, and more randomized controlled trials are warranted.

Background: Early diagnosis and accurate staging are important to improve the cure rate and prognosis for pancreatic cancer. This study was performed to develop an automatic and accurate imaging processing technique system, allowing this system to read computed tomography (CT) images correctly and make diagnosis of pancreatic cancer faster. Methods: The establishment of the artificial intelligence (AI) system for pancreatic cancer diagnosis based on sequential contrast-enhanced CT images were composed of two processes: training and verification. During training process, our study used all 4385 CT images from 238 pancreatic cancer patients in the database as the training data set. Additionally, we used VGG16, which was pre-trained in ImageNet and contained 13 convolutional layers and three fully connected layers, to initialize the feature extraction network. In the verification experiment, we used sequential clinical CT images from 238 pancreatic cancer patients as our experimental data and input these data into the faster region-based convolution network (Faster R-CNN) model that had completed training. Totally, 1699 images from 100 pancreatic cancer patients were included for clinical verification. Results: A total of 338 patients with pancreatic cancer were included in the study. The clinical characteristics (sex, age, tumor location, differentiation grade, and tumor-node-metastasis stage) between the two training and verification groups were insignificant. The mean average precision was 0.7664, indicating a good training effect of the Faster R-CNN. Sequential contrast-enhanced CT images of 100 pancreatic cancer patients were used for clinical verification. The area under the receiver operating characteristic curve calculated according to the trapezoidal rule was 0.9632. It took approximately 0.2 s for the Faster R-CNN AI to automatically process one CT image, which is much faster than the time required for diagnosis by an imaging specialist. Conclusions: Faster R-CNN AI is an effective and objective method with high accuracy for the diagnosis of pancreatic cancer. Trial Registration: ChiCTR1800017542; http://www.chictr.org.cn.

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ObjectiveTo describe the quality of life and related factors in HIV-positive spouses undergoing ART from discordant couples.MethodsA cross-sectional study was conducted among 1,009 HIV-positive spouses from serodiscordant couples in Zhumadian, Henan Province, between October 1, 2008 and March 31, 2009. HIV-positive spouses were interviewed by local health professionals. Quality of life was evaluated by WHOQOL (Chinese Version). A multiple linear regression model was used to analyze the related factors.ResultsThe majority of subjects were female (56.39%), had received a high school education (44%), were of Han ethnicity (98.41%), and were farmers (90.09%); the median time period of receiving ART was 3.92 years. The physical, psychological, social, and environmental QOL scores of the subjects were 12.91±1.95, 12.35±1.80, 13.96±2.43, and 12.45±1.91 respectively. The multiple linear regression model identified the physical domain related factors to be CD4 count, educational level, and occupation; psychological domain related factors include age, educational level, and reported STD symptom; social domain related factors included education level; and environmental domain related factors included education level, reported STD symptoms, and occupation.ConclusionBeing younger, a farmer, having a lower level of education, a reported STD symptom, or lower CD4 count, could decrease one's quality of life, suggesting that the use of blanket ART programs alone may not necessarily improve quality of life. Subjects received lower scores in the psychological domain, suggesting that psychological intervention may also need to be strengthened.