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 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.

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.

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.

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.

Robotics ; Robotic Surgical Procedures ; Kidney Transplantation

This study aimed to explore the mechanism of albiflorin in the treatment of Alzheimer's disease(AD) based on network pharmacology, molecular docking, and in vitro experiments. Network pharmacology was used to predict the potential targets and pathways of albiflorin against AD, and molecular docking technology was used to verify the binding affinity of albiflorin to key target proteins. Finally, the AD cell model was induced by Aβ_(25-35) in rat pheochromocytoma(PC12) cells and intervened by albiflorin to validate core targets and pathways. The results of network pharmacological analysis showed that albiflorin acted on key targets such as mitogen-activated protein kinase-1(MAPK1 or ERK2), albumin(ALB), epidermal growth factor receptor(EGFR), caspase-3(CASP3), and sodium-dependent serotonin transporter(SLC6A4), and signaling pathways such as MAPK, cAMP, and cGMP-PKG. The results of molecular docking showed that albiflorin had strong binding affinity to MAPK1(ERK2). In vitro experiments showed that compared with the blank group, the model group showed decreased cell viability, decreased expression level of B-cell lymphoma 2(Bcl-2), increased Bcl-2-associated X protein(Bax), and reduced phosphorylation level of extracellular signal-regulated kinase 1/2(ERK1/2) and the relative expression ratio of p-ERK1/2 to ERK1/2. Compared with the model group, the albiflorin group showed potentiated cell viability, up-regulated expression of Bcl-2, down-regulated Bax, and increased phosphorylation level of ERK1/2 and the relative expression ratio of p-ERK1/2 to ERK1/2. These results suggest that the mechanism of albiflorin against AD may be related to its activation of the MAPK/ERK signaling pathway and its inhibition of neuronal apoptosis.
Animals ; Rats ; Alzheimer Disease/drug therapy* ; bcl-2-Associated X Protein ; Network Pharmacology ; Molecular Docking Simulation

Objective:To investigate the risk factors of bronchopulmonary dysplasia (BPD) in very low birth weight (VLBW) infants with gestational age ≤32 weeks within 28 days after birth and to establish and validate the nomogram model for BPD prediction.Methods:We retrospectively chose VLBW infants with gestational age ≤32 weeks who survived to postmenstrual age (PMA) 36 weeks and were admitted to the neonatal intensive care unit of Peking University Third Hospital from January 2016 to April 2020 as the training cohort. BPD was diagnosed in accordance with the 2018 criteria. The clinical data of these infants were collected, and the risk factors of BPD were analyzed by Chi-square test, Mann-Whitney U test, and multivariate logistic regression, and a nomogram model was established. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to assess the predictive performance. Decision curve analysis (DCA) was constructed for differentiation evaluation, and the calibration chart and Hosmer-Lemeshow goodness of fit test were used for the calibration evaluation. Bootstrap was used for internal validation. VLBW infants with gestational age ≤32 weeks survived to PMA 36 weeks and admitted to Hebei Chengde Maternal and Child Health Hospital from October 2017 to February 2022 were included as the validation cohort. ROC curve and calibration plot were conducted in the validation cohort for external validation. Results:Of the 467 premature infants included in the training cohort, 104 were in the BPD group; of the 101 patients in the external validation cohort, 16 were in the BPD group. Multivariate logistic regression analysis showed that low birth weight ( OR=0.03, 95% CI: 0.01-0.13), nosocomial pneumonia ( OR=2.40, 95% CI: 1.41-4.09), late-onset sepsis ( OR=2.18, 95% CI: 1.18-4.02), and prolonged duration of endotracheal intubation ( OR=1.61, 95% CI: 1.26-2.04) were risk factors for BPD in these groups of infants (all P<0.05). According to the multivariate logistic regression analysis results, a nomogram model for predicting BPD risk was established. The AUC of the training cohort was 0.827 (95% CI: 0.783-0.872), and the ideal cut-off value for predicted probability was 0.206, with a sensitivity of 0.788 (95% CI: 0.697-0.862) and specificity of 0.744 (95% CI: 0.696-0.788). The AUC of the validation cohort was 0.951 (95% CI:0.904-0.999). Taking the prediction probability of 0.206 as the high-risk threshold, the sensitivity and specificity corresponding to this value were 0.812 (95% CI: 0.537-0.950) and 0.882 (95% CI: 0.790-0.939). The Hosmer-Lemeshow goodness-of-fit test in the training and validation cohort showed a good fit ( P>0.05). DCA results showed a high net benefit of clinical intervention in very preterm infants when the threshold probability was 5%~80% for the training cohort. Conclusion:Low birth weight, nosocomial pneumonia, late-onset sepsis, and prolonged tracheal intubation duration are risk factors for BPD. The established nomogram model has a certain value in predicting the risk of BPD in VLBW less than 32 weeks.