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Abstract Background and aims Preoperative prediction of microvascular invasion (MVI) using a noninvasive method remain unresolved, especially in HBV-related in intrahepatic cholangiocarcinoma (ICC). This study aimed to build and validate a preoperative prediction model for MVI in HBV-related ICC. Methods Patients with HBV-associated ICC undergoing curative surgical resection were identified. Univariate and multivariate logistic regression analyses were performed to determine the independent risk factors of MVI in the training cohort. Then, a prediction model was built by enrolling the independent risk factors. The predictive performance was validated by receiver operator characteristic curve (ROC) and calibration in the validation cohort. Results Consecutive 626 patients were identified and randomly divided into the training (418, 67%) and validation (208, 33%) cohorts. Multivariate analysis showed that TBIL, CA19-9, tumor size, tumor number, and preoperative image lymph node metastasis were independently associated with MVI. Then, a model was built by enrolling former fiver risk factors. In the validation cohort, the performance of this model showed good calibration. The area under the curve was 0.874 (95% CI: 0.765–0.894) and 0.729 (95%CI: 0.706–0.751) in the training and validation cohort, respectively. Decision curve analysis showed an obvious net benefit from the model. Conclusion Based on clinical data, an easy model was built for the preoperative prediction of MVI, which can assist clinicians in surgical decision-making and adjuvant therapy.

Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by progressive joint erosion. Tumor necrosis factor (TNF) antagonists are the most widely used biological disease-modifying anti-rheumatic drug in RA. However, there continue to be one third of RA patients who have poor or no response to TNF antagonists. Following consideration of the uncertainty of therapeutic effects and the high price of TNF antagonists, it is worthy to predict the treatment responses before anti-TNF therapy. According to the comparisons between the responders and non-responders to TNF antagonists by omic technologies, such as genomics, transcriptomics, proteomics, and metabolomics, rheumatologists are eager to find significant biomarkers to predict the effect of TNF antagonists in order to optimize the personalized treatment in RA. [ABSTRACT FROM AUTHOR]

Flexible polyethylene terephthalate (PET) electrodes based on pristine single-walled carbon nanotubes (SWCNTs) and acid-treated single-walled carbon nanotubes (A-SWCNTs) were prepared by spray coating technique. Flexible A-SWCNTs electrodes showed enhanced electrochemical properties compared to the pristine SWCNTs electrodes. The electrochemical properties of the flexible A-SWCNTs electrodes were optimized with various types of aqueous electrolytes including sulfuric acid (H2SO4), sodium sulfate (Na2SO4), potassium chloride (KCl), sodium hydroxide (NaOH), and potassium hydroxide (KOH). The electrochemical performance of the A-SWCNTs electrodes as a function of bending to 30° were evaluated using cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and galvanostatic charge/discharge (GCD) measurements in 1 M H2SO4. The specific capacitance value of the unbent A-SWCNTs electrode was 67 F g−1, which decreased to 63 F g−1(94% retention) after 1000 GCD cycles. Interestingly, the specific capacitance of the unbent A-SWCNTs electrode with application of the 1000 GCD cycles was retained even after 500 bending to 30° with 6000 GCD cycles. [ABSTRACT FROM AUTHOR]

Objective: To investigate the risk factors for the occurrence of patent ductus arteriosus (PDA) and to provide a clinical basis for reducing the occurrence of PDA in early preterm infants., Methods: A total of 136 early preterm infants (gestational age≤32 weeks) who were hospitalized between January 2013 and December 2014 and diagnosed with hemodynamicalhy significant PDA (hs-PDA) were enrolled as the case group. Based on the matched case-control principle, 136 early preterm infants without hs-PDA were selected among those who were hospitalized within the same period at a ratio of 1:1 and enrolled as the control group. The two groups were matched for sex and gestational age. The basic information of neonates and maternal conditions during the pregnancy and perinatal periods were collected. Logistic regression analysis was performed to identify the risk factors for the development of PDA., Results: Univariate analysis showed that neonatal infectious diseases, neonatal respiratory distress syndrome, decreased platelet count within 24 hours after birth, and low birth weight were associated with the development of hs-PDA (P<0.05). Multivariate conditional logistic regression analysis revealed that neonatal infectious diseases (OR=2.368) and decreased platelet count within 24 hours after birth (OR=0.996) were independent risk factors for hs-PDA., Conclusions: Neonatal infectious diseases and decreased platelet count within 24 hours after birth increase the risk of hs-PDA in early preterm infants.