[This corrects the article DOI: 10.1016/j.apsb.2022.03.002.].

Metformin has been demonstrated to attenuate hyperglycaemia by modulating the gut microbiota. However, the mechanisms through which the microbiome mediates metformin monotherapy failure (MMF) are unclear. Herein, in a prospective clinical cohort study of newly diagnosed type 2 diabetes mellitus (T2DM) patients treated with metformin monotherapy, metagenomic sequencing of faecal samples revealed that Phocaeicola vulgatus abundance was approximately 12 times higher in nonresponders than in responders. P. vulgatus rapidly hydrolysed taurine-conjugated bile acids, leading to ceramide accumulation and reversing the improvements in glucose intolerance conferred by metformin in high-fat diet-fed mice. Interestingly, C22:0 ceramide bound to mitochondrial fission factor to induce mitochondrial fragmentation and impair hepatic oxidative phosphorylation in P. vulgatus-colonized hyperglycaemic mice, which could be exacerbated by metformin. This work suggests that metformin may be unsuitable for P. vulgatus-rich T2DM patients and that clinicians should be aware of metformin toxicity to mitochondria. Suppressing P. vulgatus growth with cefaclor or improving mitochondrial function using adenosylcobalamin may represent simple, safe, effective therapeutic strategies for addressing MMF.

Objective To explore the differences in gut microbiota among patients with Parkinson disease(PD),major depressive disorder(MDD)and PD with depression(dPD),as well as their correlation with psychological factors.Methods A cross-sectional control design was used for the study.Fecal samples were collected from 30 PD patients,21 dPD patients,and 20 MDD patients for high-throughput 16S rRNA sequencing analysis.The Snaith-Hamilton pleasure scale(SHAPS),ruminative responses scale(RRS),Connor-Davidson resilience scale(CD-RISC)and self-compassion scale short form(SCS-SF)were used for psychological assessments.Results The relative abundance of Megamonas was higher in the MDD group than in the dPD and PD groups,while Prevotella was lower in the MDD group than in the dPD and PD groups.The relative abundance of Escherichia-Shigella in PD was higher than that in the dPD and MDD groups,and the difference was significant(P<0.05).The score of the CD-RISC was positively correlated with the abundance of microbiota at Vibrio(r=0.598,P<0.001)and Shewanella(r=0.569,P<0.001),while the score of ruminative responses scale was positively correlated with the abundance of microbiota at Hydrogenophaga(r=0.625,P<0.001),Rhodococcus(r=0.510,P<0.001).Conclusion There are some differences in gut microbiota among patients with Parkinson disease,Parkinson disease with depression and major depression disorder.The specific microbiota such as Vibrio and Rhodococcus may be related to the psychological factors and depressive symptoms of dPD patients.

Objective:To establish a model based on the characteristics of breast cancer ultrasound images through deep learning methods to predict the risk of axillary lymph node metastasis（ALNM）in patients with breast cancer（maximum diameter ≤2.5 cm）before surgery.Methods:A total of 419 patients（3 433 breast tumor ultrasound images）with breast cancer（maximum diameter ≤2.5 cm）who underwent axillary lymph node dissection at Beijing Tiantan Hospital，Capital Medical University from January 2019 to December 2024 were retrospectively included. According to the pathological results of axillary lymph nodes，they were divided into 220 cases in the ALNM occurrence group（positive group）and 199 cases in the non-ALNM occurrence group（negative group）. The breast cancer ultrasound images of the two groups of cases were randomly classified into the training set（2 404 images），the validation set（687 images）and the test set（342 images）according to a ratio of 7∶2∶1. YOLOv8 was used as the basic model of You Only Look Once（YOLO）and optimized. The optimized model was applied to locate and capture the potential ultrasound features of breast cancer cases in the training set. A prediction model was constructed based on the captured ultrasound features. The model was adjusted and optimized through the validation set，and then matched with the case images in the test set. The confusion classification matrix graph and the curve graph for measuring the model performance were used to evaluate the model prediction performance and interpret the model，and the efficacy of this model in identifying breast cancer patients at risk of ALNM was analyzed.Results:There were statistically significant differences between the positive and negative groups in terms of the pathological maximum diameter of breast tumors，pathological T staging，the differentiation degree，the presence of distant metastasis，the maximum diameter measured by ultrasound，the quadrant of breast tumor occurrence，the Breast Imaging - Reporting and Data System（BI-RADS）classification of breast tumors，and the presence of abnormal ultrasound features of lymph node（all P<0.05）. The established deep learning model could automatically perform bounding box localization for the breast cancer of patients.The breast tumors in the positive group had potential ultrasound features that could be captured by the model compared with those in the negative group. The mean average precision（mAP）50 was 0.883，mAP 50-95 was 0.636，PR-AUC was 0.884 5，strict PR-AUC was 0.636 4，the sensitivity was 90.5%，and the specificity was 91.2%，and it had a good predictive efficacy. Conclusions:This prediction model based on the ultrasound characteristics of breast cancer through deep learning can effectively predict breast cancer（maximum diameter ≤ 2.5 cm）with the risk of ALNM，providing an effective basis for the clinical management of axillary lymph nodes in breast cancer patients.

AIM To investigate the mechanism of Shaoyao Gancao Decoction in preventing meglumine diatrizoate-induced post-ERCP pancreatitis in rats through autophagy regulation.METHODS The rats were randomized into the normal group,the model group,the low-dose and high-dose Shaoyao Gancao Decoction(1.5,3.0 g/kg),and the indomethacin suppository group.A rat model of post-ERCP pancreatitis was induced by meglumine diatrizoate injection into the pancreatic duct under continuous pressure.The rats had their pancreatic tissues stained with HE to observe the pathological alterations,inflammatory cell infiltration,hemorrhage and necrosis;their serum levels of IL-1β,IL-6,IL-8,TNF-α,AMS,and IL-10 identified by ELISA;their autophagic vacuoles in pancreatic acinar cells observed by transmission electron microscopy;their pancreatic protein expressions of Beclin1,LC3B,p62,TRAF2 and p-JNK detected by IHC and Western blot;and their pancreatic mRNA expressions of Beclin1 and TRAF2 detected by RT-qPCR.RESULTS Compared with the model group,the high-dose Shaoyao Gancao Decoction group displayed no obvious hemorrhage;improvement in edema of acinar and interstitial cells;obviously less cellular inflammatory infiltration;substantially decreased serum levels of IL-1β,IL-6,TNF-α and AMS(P＜0.05,P＜0.01);drastically reduced amount of autophagosomes in acinar cells;and down-regulated expressions of autophagy-related proteins Beclin1,LC3,p62,TRAF2 and p-JNK(P＜0.05,P＜0.01).CONCLUSION Shaoyao Gancao Decoction can prevent post-ERCP pancreatitis by ameliorating pancreatic tissue injury,decreasing serum inflammatory response level,and interfering with abnormal autophagy of pancreatic acinar cells.Its molecular mechanism may involve inhibition of TRAF2 protein expression and modulation of p-JNK activation.

Objective:To investigate the effect of Qinggan Bupi Jiangtang Decoction combined with acupuncture on glucose and lipid metabolism and cytokines in patients with overweight/obese T2DM.Methods:Randomized controlled trial. A total of 104 patient with overweight/obese T2DM who were admitted to the Shanghai Municipal Hospital of Traditional Chinese Medicine of Shanghai University of Traditional Chinese Medicine from September 2022 to March 2023 were selected as the research subjects. They were randomly divided into the control group (52 cases) and the combination group (52 cases). The control group was given conventional symptomatic treatment and treated with acupuncture. On this basis, the combination group was treated with Qinggan Bupi Jiangtang Decoction. The two groups were compared in terms of efficacy, TCM syndrome scores, glucose metabolism indicators, islet function indicators, lipid metabolism indicators, cytokines, and blood glucose control. Results:The total effective rate was 90.38% (47/52) in the combined group and 73.08% (38/52) in the control group, and the difference between the two groups was statistically significant ( χ2=5.22, P=0.022). After treatment, the TCM syndrome score (13.21±1.48 vs. 18.54±2.01, t=15.40) of the combination group was lower than that of the control group ( P<0.001). After treatment, the combination group FPG [(6.05 ± 1.01) mmol/L vs. (7.26 ± 1.13) mmol/L, t=5.73], 2 hPG [(8.23 ± 1.12) mmol/L vs. (10.41 ± 1.26) mmol/L, t=9.54], HbAlc [(5.84 ± 0.84) % vs. (6.31 ± 0.93) %, t=2.84] and HOMA-IR (2.57 ± 0.26 vs. 2.86 ± 0.30, t=3.75) were lower than those in the control group ( P<0.05), and HOMA-β (61.34 ± 6.75 vs. 56.69 ± 5.72, t=5.87) was higher than that of the control group ( P<0.05). After treatment, the combination group TC, TG and LDL-C were lower than those in the control group ( t values were 10.25, 5.35, 3.51, respectively, P<0.01), HDL-C was higher than that of the control group ( t=11.59, P<0.01). After treatment, the combination group CTRP12 [(296.05 ± 30.11) ng/L vs. (280.23 ± 28.44) ng/L, t=2.76], FGF-21 [(184.12 ± 19.05) μg/L vs. (170.04 ± 17.03) μg/L, t=2.77], Nesfatin1 [(0.92 ± 0.10) μg/L vs. (0.77±0.08) μg/L, t=5.99] and lipidin levels [(4.89±0.51) mg/L vs. (4.12±0.48) mg/L, t=8.58] were higher than those in the control group ( P<0.01). The combined group composite endpoint achievement rate was 53.85% (28/52), the 12-week HbA1c achievement rate was 80.77% (42/52), and the rate of no weight increase was 84.62% (44/52). The control group's composite endpoint achievement rate was 34.62% (18/52), the 12-week HbA1c achievement rate was 61.54% (32/52), and the rate of no weight increase was 67.31% (35/52). The differences between the two groups were statistically significant ( χ2 values were 3.90, 4.69, 4.27, respectively, and the P values were 0.048, 0.030, 0.039, respectively). The adverse reactions of the two groups were mainly mild nausea, skin rash and pruritus, the incidence of which was 15.38% (8/52) in the combination group and 9.62% (5/52) in the control group, and there was no significant difference between the two groups ( χ2=0.79, P=0.374). Conclusion:The therapeutic effect of Qinggan Bupi Jiangtang Decoction combined with acupuncture on overweight/obese T2DM patients is relatively clear, and it can regulate the glucose and lipid metabolism and cytokines of patients.

Objective: To explore the effects of Cldn14 gene knockout on renal metabolism and stone formation in rats，so as to provide reference for research in the field of urinary calium metabolism and stone formation. Methods: Cldn14 gene knockout homozygous rats and wild-type rats of the same age were randomly divided into 4 groups：wild-type control (WC) group，wild-type ethylene glycol (WE) group，gene knockout control (KC) group and gene knockout ethylene glycol (KE) group，with 10 rats in each group.The WE and KE groups were induced with ethylene glycol + ammonium chloride to form kidney stones，while the WC and KC groups received normal saline gavage.After 4 weeks of standard maintenance feeding，the urine samples were collected to detect the venous blood.The kidneys were collected for HE，Pizzolatto's staining and transmission electron microscopy.The protein in renal tissues was extracted to detect the expressions of Claudin16 and Claudin19. Results: Crystal deposition was observed in the renal tubular lumen of the WE and the KE groups，and more crystals were detected in the KE group.The WE group had a large number of intracytoplasmic black crystalline inclusions observed in renal tubular epithelial cells under transmission electron microscope，followed by the KE and KC groups.Compared with WC and WE groups，KC and KE groups had significantly decreased serum calcium and magnesium levels but significantly increased urinary calcium level.In addition，the urinary calcium level was higher in the WE group than in the WC group and higher in the KE group than in the KC group.The KE group had lower level of Claudin16，but there was no significant difference in the level of Claudin19 among the 4 groups(P>0.05). Conclusion: Knockout of Cldn14 gene alone cannot effectively reduce urinary calcium excretion or reduce the risk of stone formation in rats，which may be related to the decrease of Claudin16 level.

AIM To investigate the mechanism of Shaoyao Gancao Decoction in preventing meglumine diatrizoate-induced post-ERCP pancreatitis in rats through autophagy regulation.METHODS The rats were randomized into the normal group,the model group,the low-dose and high-dose Shaoyao Gancao Decoction(1.5,3.0 g/kg),and the indomethacin suppository group.A rat model of post-ERCP pancreatitis was induced by meglumine diatrizoate injection into the pancreatic duct under continuous pressure.The rats had their pancreatic tissues stained with HE to observe the pathological alterations,inflammatory cell infiltration,hemorrhage and necrosis;their serum levels of IL-1β,IL-6,IL-8,TNF-α,AMS,and IL-10 identified by ELISA;their autophagic vacuoles in pancreatic acinar cells observed by transmission electron microscopy;their pancreatic protein expressions of Beclin1,LC3B,p62,TRAF2 and p-JNK detected by IHC and Western blot;and their pancreatic mRNA expressions of Beclin1 and TRAF2 detected by RT-qPCR.RESULTS Compared with the model group,the high-dose Shaoyao Gancao Decoction group displayed no obvious hemorrhage;improvement in edema of acinar and interstitial cells;obviously less cellular inflammatory infiltration;substantially decreased serum levels of IL-1β,IL-6,TNF-α and AMS(P＜0.05,P＜0.01);drastically reduced amount of autophagosomes in acinar cells;and down-regulated expressions of autophagy-related proteins Beclin1,LC3,p62,TRAF2 and p-JNK(P＜0.05,P＜0.01).CONCLUSION Shaoyao Gancao Decoction can prevent post-ERCP pancreatitis by ameliorating pancreatic tissue injury,decreasing serum inflammatory response level,and interfering with abnormal autophagy of pancreatic acinar cells.Its molecular mechanism may involve inhibition of TRAF2 protein expression and modulation of p-JNK activation.

Objective To explore the differences in gut microbiota among patients with Parkinson disease(PD),major depressive disorder(MDD)and PD with depression(dPD),as well as their correlation with psychological factors.Methods A cross-sectional control design was used for the study.Fecal samples were collected from 30 PD patients,21 dPD patients,and 20 MDD patients for high-throughput 16S rRNA sequencing analysis.The Snaith-Hamilton pleasure scale(SHAPS),ruminative responses scale(RRS),Connor-Davidson resilience scale(CD-RISC)and self-compassion scale short form(SCS-SF)were used for psychological assessments.Results The relative abundance of Megamonas was higher in the MDD group than in the dPD and PD groups,while Prevotella was lower in the MDD group than in the dPD and PD groups.The relative abundance of Escherichia-Shigella in PD was higher than that in the dPD and MDD groups,and the difference was significant(P<0.05).The score of the CD-RISC was positively correlated with the abundance of microbiota at Vibrio(r=0.598,P<0.001)and Shewanella(r=0.569,P<0.001),while the score of ruminative responses scale was positively correlated with the abundance of microbiota at Hydrogenophaga(r=0.625,P<0.001),Rhodococcus(r=0.510,P<0.001).Conclusion There are some differences in gut microbiota among patients with Parkinson disease,Parkinson disease with depression and major depression disorder.The specific microbiota such as Vibrio and Rhodococcus may be related to the psychological factors and depressive symptoms of dPD patients.

Objective:To establish a model based on the characteristics of breast cancer ultrasound images through deep learning methods to predict the risk of axillary lymph node metastasis（ALNM）in patients with breast cancer（maximum diameter ≤2.5 cm）before surgery.Methods:A total of 419 patients（3 433 breast tumor ultrasound images）with breast cancer（maximum diameter ≤2.5 cm）who underwent axillary lymph node dissection at Beijing Tiantan Hospital，Capital Medical University from January 2019 to December 2024 were retrospectively included. According to the pathological results of axillary lymph nodes，they were divided into 220 cases in the ALNM occurrence group（positive group）and 199 cases in the non-ALNM occurrence group（negative group）. The breast cancer ultrasound images of the two groups of cases were randomly classified into the training set（2 404 images），the validation set（687 images）and the test set（342 images）according to a ratio of 7∶2∶1. YOLOv8 was used as the basic model of You Only Look Once（YOLO）and optimized. The optimized model was applied to locate and capture the potential ultrasound features of breast cancer cases in the training set. A prediction model was constructed based on the captured ultrasound features. The model was adjusted and optimized through the validation set，and then matched with the case images in the test set. The confusion classification matrix graph and the curve graph for measuring the model performance were used to evaluate the model prediction performance and interpret the model，and the efficacy of this model in identifying breast cancer patients at risk of ALNM was analyzed.Results:There were statistically significant differences between the positive and negative groups in terms of the pathological maximum diameter of breast tumors，pathological T staging，the differentiation degree，the presence of distant metastasis，the maximum diameter measured by ultrasound，the quadrant of breast tumor occurrence，the Breast Imaging - Reporting and Data System（BI-RADS）classification of breast tumors，and the presence of abnormal ultrasound features of lymph node（all P<0.05）. The established deep learning model could automatically perform bounding box localization for the breast cancer of patients.The breast tumors in the positive group had potential ultrasound features that could be captured by the model compared with those in the negative group. The mean average precision（mAP）50 was 0.883，mAP 50-95 was 0.636，PR-AUC was 0.884 5，strict PR-AUC was 0.636 4，the sensitivity was 90.5%，and the specificity was 91.2%，and it had a good predictive efficacy. Conclusions:This prediction model based on the ultrasound characteristics of breast cancer through deep learning can effectively predict breast cancer（maximum diameter ≤ 2.5 cm）with the risk of ALNM，providing an effective basis for the clinical management of axillary lymph nodes in breast cancer patients.