Autoimmune pancreatitis is a special type of chronic pancreatitis that can lead to abnormal pancreatic exocrine function in patients. Autoimmune pancreatitis comorbid with pancreatic exocrine insufficiency has a complex pathogenesis， and there is limited research on this topic， leading to the lack of understanding of such patients in clinical practice. This article introduces the epidemiology of autoimmune pancreatitis， briefly describes the pathogenesis of pancreatic exocrine insufficiency caused by autoimmune pancreatitis， and summarizes the various detection methods for pancreatic exocrine function， nutritional assessments， lifestyle management， and drug therapy， in order to strengthen the understanding of autoimmune pancreatitis comorbid with pancreatic exocrine insufficiency and improve the clinical diagnosis and treatment of pancreatic exocrine insufficiency.

The p21-activated kinase 4 (PAK4), a key regulator of malignancy, is negatively correlated with immune infiltration and has become an emergent drug target of cancer therapy. Given the lack of high efficacy PAK4 inhibitors, we herein reported the identification of a novel inhibitor 13 bearing a tetrahydrobenzofuro[2,3-c]pyridine tricyclic core and possessing high potency against MIA PaCa-2 and Pan02 cell lines with IC₅₀ values of 0.38 and 0.50 μmol/L, respectively. This compound directly binds to PAK4 in a non-ATP competitive manner. In the mouse Pan02 model, compound 13 exhibited significant tumor growth inhibition at a dose of 100 mg/kg, accompanied by reduced levels of PAK4 and its phosphorylation together with immune infiltration in mice tumor tissue. Overall, compound 13 is a novel allosteric PAK4 inhibitor with a unique tricyclic structural feature and high potency both in vitro and in vivo, thus making it worthy of further exploration.

Objective To construct 5 machine-learning models and compare their performance in predicting the associations between pre-pregnancy socio-psycho-behavioral exposures of both spouses and preconception outcomes.Methods Based on Chongqing Preconception Reproductive Health and Birth Outcome Cohort of volunteers recruited from Chongqing Health Center for Women and Children during January 2019 and March 2022,5 447 couples were recruited and surveyed through interviewer-interview for the demographic and social-psychological-behavioral data of both spouses(221 variables).According to the inclusion and exclusion criteria,4 097 couples were finally included,and randomly assigned into a training set(n=2 867 spouses)and a validation set(n=1 230 spouses)at a ratio of 7∶3.Feature analysis and collinear screening were applied to select the potential exposure factors.In consideration of difficulty to carry out semen parameters analysis in primary healthcare institutions,feature Set 1 including sperm parameters and feature Set 2 excluding semen parameters were constructed by including or excluding sperm quality simultaneously in the training set and the validation set.Five algorithms,that is,Logistic Regression,Naive Bayes,Random Forest,Gradient Boosting Machine,and Support Vector Machine,were used to construct preconception outcome prediction models,and the parameters of each model were optimized using random search combined with grid search.The predictive performance of each model was compared using precision,recall,F1 score,area under the receiver operating characteristic curve(AUC),and calibration curve.The optimal model was then selected by comparing the changes in the predictive ability of the questionnaire data for fertility outcomes with or without semen parameters.Results There were 24 variables screened out in feature Set 1,and 16 variables in feature Set 2.In feature Set 1,the gradient boosting machine performed better,with a relatively higher AUC value(0.651)and better F1 score(0.61).The logistic regression model performed stably(AUC value=0.647)and was suitable as the reference model.The random forest(AUC value=0.641),Naive Bayes(AUC value=0.641),and support vector machine(AUC value=0.634)performed second-best.By utilizing the gradient boosting machine,comparable results were found between the predictions from feature sets with or without semen parameters,as in feature Set 1,the AUC value of its validation set was 0.651(95%CI:0.629～0.681),the prediction accuracy was 0.63,the recall rate was 0.65,and the average precision value F1 was 0.61;and in feature Set 2,the AUC value of its validation set was 0.649(95%CI:0.624～0.663),and both the calibration curves were close to the ideal curve.The prediction results indicated that in feature Set 1,the features highly negatively correlated with preconception outcomes were female age,male age,and no pregnancy within 1 year without contraception,while the features highly positively correlated with preconception outcomes were female pregnancy history,total sperm vitality,and use of contraceptive measures before enrollment.Conclusion Among the 5 machine-learning algorithms performed in this cohort data,the gradient boosting machine shows slightly better performance.There are 24 factors being associated with preconception outcomes in both spouses,and the performance of the simplified model excluding semen parameters is not significantly declined.It is feasible to use machine-learning methods to predict human preconception outcomes through social-psychological-behavioral questionnaires.

ObjectiveGastric cancer (GC) seriously affects human health and life, and research has shown that it is closely related to the serine/glycine metabolism. The proliferation ability of tumor cells is greatly influenced by the metabolism of serine and glycine. The aim of this study was to investigate the molecular mechanism of serine/glycine metabolism can affect the proliferation of gastric cancer cells. MethodsIn this work, a stable metabolic dynamic model of gastric cancer cells was established via a large-scale metabolic network dynamic modeling method in terms of a potential landscape description of stochastic and non-gradient systems. Based on the regulation of the model, a quantitative analysis was conducted to investigate the dynamic mechanism of serine/glycine metabolism affecting the proliferation of gastric cancer cells. We introduced random noise to the kinetic equations of the general metabolic network, and applied stochastic kinetic decomposition to obtain the Lyapunov function of the metabolic network parameter space. A stable metabolic network was achieved by further reducing the change in the Lyapunov function tied to the stochastic fluctuations. ResultsDespite the unavailability of a large number of dynamic parameters, we were able to successfully construct a dynamic model for the metabolic network in gastric cancer cells. When extracellular serine is available, the model preferentially consumes serine. In addition, when the conversion rate of glycine to serine increases, the model significantly upregulates the steady-state fluxes of S-adenosylmethionine (SAM) and S-adenosyl homocysteine (SAH). ConclusionIn this paper, we provide evidence supporting the preferential uptake of serine by gastric cancer cells and the important role of serine/glycine conversion rate in SAM generation, which may affect the proliferation ability of gastric cancer cells by regulating the cellular methylation process. This provides a new idea and direction for targeted cancer therapy based on serine/glycine metabolism.

ObjectiveGlutathione (γ-glutamyl-L-cysteinylglycine, GSH) is the most abundant non-protein compound containing sulfhydryl (―SH) groups in cells. It serves as a source of reducing equivalents, effectively neutralizing harmful reactive substances, and playing a crucial role in maintaining cellular redox balance. Therefore, sensitive detection and accurate measurement of GSH levels in tissues are of great importance. In this work, we presents a novel method for GSH detection utilizing electron paramagnetic resonance (EPR) spectroscopy. MethodsInitially, ABTS (2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonate acid)) solution was mixed with K₂S₂O₈ solution and reacted in the dark for 12 to 16 h to prepare ABTS·⁺ solution, which was then quantified using UV-Vis spectroscopy. Subsequently, the concentration of glutathione (GSH) was determined based on the changes in the EPR signal of ABTS·⁺. On this basis, the optimal reaction time and temperature were explored to establish a standard equation correlating the EPR signal intensity of ABTS·⁺ with GSH concentration. Finally, the derived standard curve was employed to quantitatively analyze the GSH concentration in whole blood from C57BL/6J mice, and the results were compared with those reported in the literature to verify the accuracy of the method. ResultsThe experimental results demonstrate that this method has a linear detection range from50 nmol/L to 15 μmol/L for GSH, spanning two orders of magnitude, with a limit of detection (LOD) at0.50 nmol/L. The measured GSH content in mouse whole blood is (10 660±706) nmol/g Hb, which agrees with the value of (11 200±237) nmol/g Hb as previously reported. Furthermore, a similar method was developed for detection of glutathione disulfide (GSSG) at higher reaction temperature. ConclusionThis article presents a novel assay for the rapid detection of GSH using the intensity of EPR signal from ABTS·⁺ as indicator. This method demonstrates enhanced detection sensitivity and a broader linear range compared to conventional colorimetric methods. Furthermore, we have extended the application of this method to detect GSH content in blood samples efficiently and accurately, offering valuable information for assessing tissue redox balance, thus holding significant potentials.

Objective:To study the feasibility of magnetic resonance imaging(MRI)technique with amide proton transfer(APT)in predicting the prognosis of cerebral stroke.Methods:A total of 71 patients with acute cerebral stroke who admitted to the Nanjing First Hospital,Nanjing Medical University from September 2022 to May 2023 were selected.All of them underwent the test of National Institute of Health Stroke Scale(NIHSS),and received the MRI examination with chemical exchange saturation transfer(CEST).According to the modified Rankin scale(mRS)values of 1-month follow-up,they were divided into favorable recovery group(mRS<2,44 cases)and poor group(mRS≥2,27 cases).The asymmetric magnetization transfer ratio(MTRasym)image(APT)was obtained by analyzing data with special software.And then,the difference(△APTw)of APT values between ischemic zone and contralateral normal tissue was further calculated.The △APTw values of two groups were compared and analyzed,and the Pearson correlation analysis was adopted to analyze the correlation among △APTw,NIHSS and mRS.The receiver operating characteristics(ROC)curve was drawn,and the area under curve(AUC)of ROC curve was calculated.Results:There were significant positive correlations among △APTw,NIHSS and mRS scores(R2=0.659,0.522,P<0.001),and the differences of △APTW,NIHSS and mRS scores between the favorable recovery group and poor group were significant(t=5.73,6.36,13.92,P<0.05),respectively.The AUC value was 0.886,and the sensitivity and specificity of prediction were respectively 77.8%and 95.5%.The positive and negative predictive values were respectively 91.3%and 87.5%.Conclusion:APT imaging technique has feasibility in predicting the prognosis of acute cerebral ischemic stroke.

Objective To propose a method for classifying small bowel capsule endoscopy images by combining the Swin Transformer network with an improved Adapt-RandAugment data augmentation approach,aiming to enhance the accuracy and efficiency of small bowel lesion classification and recognition.Methods An Adapt-RandAugment data augmentation approach was formulated based on the RandAugment data enhancement sub-strategy and the principles of no feature loss and no distortion when enhancing small bowel capsule endoscopy images.In the publicly available Kvasir-Capsule dataset of small bowel capsule endoscopic images,the Adapt-RandAugment data augmentation approach was trained based on the Swin Transformer network,and the convolutional neural networks ResNet152 and DenseNet161 were used as the benchmarks to validate the combined Swin Transformer network and Adapt-RandAugment data augmentation approach for small bowel capsule endoscopy image classification.Results The proposed algorithm gained advantages over ResNet152 and DenseNet161 networks in the indicators,which had the macro average precision(MAC-PRE),macro average recall(MAC-REC),macro average F1 score(MAC-Fi-S)being 0.383 2,0.314 8 and 0.290 5 respectively,the micro average precision(MIC-PRE),micro average recall(MIC-REC)and micro average F1 score(MIC-Fi-S)all being 0.755 3,and the Matthews correlation coe-fficient(MCC)being 0.452 3.Conclusion The proposed small bowel capsule endoscopy image classification method based on Swin Transformer network and Adapt-RandAugment data augmentation approach behaves well in classified recognition efficiency and accuracy.[Chinese Medical Equipment Journal,2024,45(6):9-16]

In this study,a method for detecting heavy metal ions using potentiometric sensor and voltammetric sensor was proposed.By exploiting the complementary advantages of potentiometric and voltammetric electrochemical sensor,the traditional electrochemical electrode without special material preparation and modification could be used for the wide range and accurate detection of heavy metal ions in actual water samples.During detection,the concentration of target ion was measured by a potentiometric electrochemical sensor to determine the concentration range.The amperometric electrochemical sensor was then used for calibration and accurate measurement in the appropriate concentration range.Taking copper ion(Cu2+)as an example,the prepared Cu2+water sample and the actual water sample were tested.First,the copper ion selective electrode was used to determine the concentration range of Cu2+in the sample.Then,based on the gold electrode in different concentration range(0.86-100 μg/L and 100-300 μg/L)using two different optimization parameter settings to calibrate the electrochemical sensor and measure,the test results had a good correlation with those by professional water quality testing institutions.The recoveries ranged from 86.7%to 103.0%.The experimental results showed that the combination of potential sensor and current sensor could improve the accuracy of detection of heavy metal ions in water samples by electrochemical sensor.

Objective To investigate the effect of chronic psychological stress on testicular cell senescence in rats and the role of glucocorticoid receptor(GR)in the process.Methods Thirty-two male SD rats(4～6 weeks old,weighing 120～140 g)were randomly assigned into dimethyl sulfoxide(DMSO)group,mifepristone(RU486)group,chronic unpredictable mild stress(CUMS)group,and CUMS+RU486 group.DMSO of 0.5 ml/(kg·d)was injected subcutaneously into the rats of DMSO group.After the rats of the CUMS group were exposed to CUMS,mifepristone of 1 mg/(kg·d)was given to the rats of the RU486 group and CUMS+RU486 group.All the above 4 groups were inflicted for 42 consecutive days.After modeling,the psychological stress status of rats was evaluated with animal behavioral experiments.Computer-aided sperm analysis(CASA)system was used to detect sperm density.ELISA was employed to measure the serum levels of corticosterone(CORT),sex hormones and inflammation factors.The contents of malondialdehyde(MDA),H2O2,NAD+/NADH and ATP in the testicular tissues were tested with corresponding reagent kits.Western blotting was utilized to detect protein levels of[3-gal,p16,and GR in testicular tissue,and transmission electron microscopy was used to observe mitochondrial structure of spermatogenic cells.Results Compared with the DMSO group,the sperm density,serum levels of testosterone(T),luteinizing hormone(LH)and follicle stimulating hormone(FSH)were decreased while those of CORT and estradiol(E2)were increased in the CUMS group(all P＜0.001).Serum pro-inflammatory factors IL-6 and TNF-α concentrations were increased while anti-inflammatory factor IL-10 concentration was decreased in the CUMS group than the DMSO group(all P＜0.05).And,ATP content and NAD+/NADH ratio were decreased while MDA and H2O2 levels were elevated in testicular tissues in the CUMS group(all P＜0.05).Moreover,the protein levels of testicular cell aging markers β-gal,p16 and GR were significantly enhanced in the CUMS group(all P＜0.01),accompanied by swelling and vacuolization of mitochondrial structures in spermatogenic cells.RU486 treatment effectively improved sperm density and increased CORT level and down-regulated the testicularβ-gal,p16 and GR protein level(all P＜0.05).Conclusion Chronic psychological stress induces testicular damage in rats,presenting declines in sperm density and CORT level,which is possibly associated with GR-mediated cell senescence.

Juvenile zebrafish were used to screen the active components of Lycii Fructus for improving osteoporosis. The screening results were further verified by zebrafish adult osteoporosis model and the action mechanism was explored. Prednisolone was used as the inducer to build osteoporosis models of juvenile and adult zebrafish, and 9 groups of samples of different extracts and chemical parts of Lycii Fructus were given. Alizarin red staining was applied for observing the scale matrix mineralization and bone resorption. The activities of osteoblasts and osteoclasts were detected using alkaline phosphatase (ALP) and tartrate resistant acid phosphatase (TRAP/TRACP) staining. The expressions of bone metabolism-related genes alp, osteoprotectin (opn), osteoblast specific transcription factor (sp7), cathepsin K (ctsk), tracp, and Runt family transcription factor 2b (runx2b) in each group were determined using quantitative polymerase chain reaction. The results showed that all components of Lycii Fructus improved the formation area of the first vertebrae, the staining light density value, and the number of vertebrae joints in juvenile zebrafish and the Lycium barbarum polysaccharide (LBP) treatment group exerted the best effect. In addition, LBP prevented the formation of bone resorption lacunae in zebrafish scales, increased ALP activity, decreased TRAP activity, up-regulated the alp, sp7, and opn genes, and lowered the expressions of ctsk and tracp genes. In conclusion, LBP regulated the activity of osteoblasts and osteoclasts, reduced bone resorption, promoted bone formation and enhanced bone density, which might be the main anti-osteoporosis active fraction of Lycii Fructus. This study provided modern scientific evidence for the scientific connotation of the traditional effect of "strengthening bones and muscles" of Lycii Fructus, provided the reference for the evaluation of the anti-osteoporosis activity of traditional Chinese medicine based on zebrafish adult model, and provided beneficial enlightenment for the bone health needs of the aging society population.