Construction and Evaluation of a Nomogram to Predict Gallstone Disease Based on Body Composition.

Purpose: We aimed to analyze the body composition characteristics of gallstone disease (GD) patients with bioelectrical impedance analysis (BIA) and to construct a nomogram to predict GD based on body composition. Methods: Patients with or without symptomatic cholecystolithiasis or choledocholithiasis diagnosed in Inner Mongolia People's Hospital from July 2020 to December 2021 were selected as the case group, and healthy subjects during the same period were selected as the control group. The body composition of the two groups was determined by BIA. The risk predictors for GD were extracted to construct a nomogram based on regression analysis. ROC curves were used to evaluate the predictive power of the nomogram, and calibration curves were drawn to evaluate the consistency of the model. The bootstrap method was used to verify the model and evaluate the generalizability of the model. Results: A total of 1000 individuals were recruited for the study, including 500 GD cases and 500 controls, to evaluate body composition. Multivariate logistic regression analysis showed that sex (OR = 2.292, 95% CI: 1.436-3.660), BMI (OR = 1.828, 95% CI: 1.738-1.929), body fat percentage (BFP) (OR = 1.904, 95% CI: 1.811-2.205) and waist circumference (WC) (OR = 1.934, 95% CI: 1.899-1.972) were risk predictors of GD. The AUC was 0.770 (95% CI: 0.741-0.799). The calibration curve showed that the C-index was 0.767. The prediction model was validated internally with 1000 bootstrap resamples. The accurate value was 0.72, and the kappa value was 0.43. All of the indices indicated that the model was well constructed and could be used to predict the incidence of GD. Conclusion: A nomogram model of gallstone disease based on sex, BMI, BFP and WC was constructed with good discrimination, calibration and generalizability and can be used for the noninvasive and convenient prediction of gallstone disease in the general population.

Minor allele of rs55763075 located in MTHFR is associated with the risk of cognitive impairment after anesthesia via modulating miR-34b.

This study aimed to investigate the association between cognitive impairment after general anesthesia and rs55763075 polymorphisms. We enrolled and grouped patients undergoing general anesthesia according to their genotypes of rs55763075 polymorphism. Mini-Mental State Examination (MMSE) scoring was performed to evaluate the cognitive status of patients. Quantitative real-time PCR was carried out to analyze the expression of methylenetetrahydrofolate reductase (MTHFR) mRNA and miR-34b while Western blot was performed to evaluate the expression of MTHFR protein. Furthermore, we studied the effect of rs55763075 polymorphism on the expression of MEHFR via luciferase assay. Accordingly, we found that the MMSE score in GG/GA groups was significantly higher than that in AA group. And a significant reduction of MTHFR mRNA expression was observed in the serum and peripheral blood mononuclear cells (PBMCs) of patients carrying AA genotype compared with the patients carrying GG/GA genotypes. Moreover, the MTHFR expression was much lower in the cultured AA-genotyped cells transfected with miR-34b. Luciferase assay results also showed that miR-34b transfection reduced luciferase activity in the cells carrying A allele but not in cells carrying G allele. In summary, the data of this study showed that minor allele (A) of rs55763075 polymorphisms in the 3'-untranslated region of MTHFR mRNA generated a potential binding site for miR-34b, which led to reduced level of folic acid in the patients carrying the AA genotype. Furthermore, we found that the MMSE score of AA-genotyped patients was lower than that of patients carrying GG/GA genotypes.

[Application of near infrared spectroscopy in screening Cordyceps militaris mutation strains and optimizing their fermentation process].

To fast screen high-yield Cordyceps militaris mutations strains and optimize their fermentation process, near infrared (NIR) spectroscopy technology combined with chemometrics has been applied to establishing models for simultaneous determination of adenosine, protein, polysaccharide and Cordyceps militaris acid contents in Cordyceps militaris powder samples. Fermentations were implemented in Erlenmeyer flask with 468 Cordyceps militaris mutations strains under various fermentation conditions and Cordyceps militaris powder samples were collected. Then their NIR spectra were obtained using UV-VIS-NIR spectrometer and their adenosine, protein, polysaccharide and Cordyceps militaris acid contents were determined using reference methods. Partial least squares (PLS) method was employed to model the relationships between NIR spectra and the above mentioned components' contents in Cordyceps militaris powder samples. Monte Carlo partial least square (MCPLS) was applied to identify the outliers and select suitable number of calibration samples. Moving window partial least square (MWPLS) was applied to select the characteristic wavelength of the components. The degree of the approaching (Da) was employed as criterion for selecting effective pretreatment methods investigated. The optimum models for determination of adenosine, protein, polysaccharide and Cordyceps militaris acid contents in Cordyceps militaris powder samples were obtained with the above mentioned optimization. Their correlation between actual and predictive values of calibration samples (Re) was 0.92943, 0.98479, 0.90785, and 0.85131, respectively. Their root mean square error of prediction set (RMSEP) was 0.66714, 0.02065, 0.01131, and 0.01159, respectively. The obtained results demonstrated that the fitting and the predictive accuracy were satisfactory. It is feasible to apply this method to screen the high yield Cordyceps militaris mutation strains and optimize their fermentation process.