Aldehyde oxidase (AOX) is a molybdoenzyme that is primarily expressed in the liver and is involved in the metabolism of drugs and other xenobiotics. AOX-mediated metabolism can result in unexpected outcomes, such as the production of toxic metabolites and high metabolic clearance, which can lead to the clinical failure of novel therapeutic agents. Computational models can assist medicinal chemists in rapidly evaluating the AOX metabolic risk of compounds during the early phases of drug discovery and provide valuable clues for manipulating AOX-mediated metabolism liability. In this study, we developed a novel graph neural network called AOMP for predicting AOX-mediated metabolism. AOMP integrated the tasks of metabolic substrate/non-substrate classification and metabolic site prediction, while utilizing transfer learning from ¹³C nuclear magnetic resonance data to enhance its performance on both tasks. AOMP significantly outperformed the benchmark methods in both cross-validation and external testing. Using AOMP, we systematically assessed the AOX-mediated metabolism of common fragments in kinase inhibitors and successfully identified four new scaffolds with AOX metabolism liability, which were validated through in vitro experiments. Furthermore, for the convenience of the community, we established the first online service for AOX metabolism prediction based on AOMP, which is freely available at https://aomp.alphama.com.cn.

Colorectal cancer is the most common malignant tumor of digestive tract, and the incidence of colorectal cancer in China is especially characterized by middle and low rectal cancer. In recent years, with the progress of computer science, artificial intelligence technology has developed rapidly, and has achieved a lot of application results in the medical field. At present, artificial intelligence technology has covered various stages of colorectal cancer, including screening, individualized assessment, auxiliary diagnosis and treatment decision-making, refined surgery and prognosis judgment, providing help for the accurate and individualized treatment of rectal cancer. However, the lack of standardized, systematic, and scalable AI models remains a major pain point for the field. Therefore, it is necessary to carry out large-scale prospective clinical studies on artificial intelligence model to further confirm its application value in the clinical diagnosis and treatment of rectal cancer.

Colorectal cancer is the most common malignant tumor of digestive tract, and the incidence of colorectal cancer in China is especially characterized by middle and low rectal cancer. In recent years, with the progress of computer science, artificial intelligence technology has developed rapidly, and has achieved a lot of application results in the medical field. At present, artificial intelligence technology has covered various stages of colorectal cancer, including screening, individualized assessment, auxiliary diagnosis and treatment decision-making, refined surgery and prognosis judgment, providing help for the accurate and individualized treatment of rectal cancer. However, the lack of standardized, systematic, and scalable AI models remains a major pain point for the field. Therefore, it is necessary to carry out large-scale prospective clinical studies on artificial intelligence model to further confirm its application value in the clinical diagnosis and treatment of rectal cancer.

Objective:To explore the effect and possible mechanism of Zexie Tang(ZXT)regulate the balance of M1/M2 polarization in macrophage cells.Methods:Lipid metabolism disorder mouse model was induced by Western diet(WD)in vivo,RAW264.7 cell M1/M2 macrophage model was induced by LPS/IL-4 in vitro,set up blank group,model group and ZXT group.The flu-orescence intensity of M1 and M2 macrophage markers in adipose tissue and RAW264.7 cells was observed by immunofluorescence staining;protein levels of p-AKT,AKT and COX-2 were measured by Western blot;levels of macrophage marker gene mRNAs of M1 and M2 were analysed by qPCR;IL-1β and IL-10 were measured by ELISA;content of NO was detected by Griess;binding of active components of Alismatis Rhizoma and Atractylodes Macrocephala with PI3K protein was analyzed by Docking.Results:Compared with WD group,expression of CD11c was significantly decreased in ZXT group,while expression of CD206 was significantly up-regulated;ZXT reversed LPS-induced increased in CD80 expression,down-regulated mRNA levels of M1 macrophage marker gene iNOS,etc,decreased the expression of COX-2 protein,and inhibited the secretion of IL-1β(P<0.001);ZXT promoted IL-4-induced CD206 expression,up-regulation of M2 macrophage marker gene Arg-1 and other mRNAs levels and secretion of IL-10;ZXT reversed the LPS-induced increased in NO release;p-AKT/AKT protein level increased in vivo and in vitro after ZXT administration;Docking re-sults show that many active ingredients in Alismatis Rhizoma and Atractylodes Macrocephala could form hydrogen bonds stably with PI3K protein.Conclusion:ZXT regulates the M1/M2 polarization balance of macrophages,and its mechanism may be related to the regulation of PI3K/AKT pathway.

Objective:To investigate the clinical value of magnetic resonance imaging (MRI) based integrated deep learning model for predicting the times of linear staplers used in double stapling technique for middle-low rectal cancer resection.Methods:The retrospective cohort study was conducted. The clinicopathological data of 263 patients who underwent low anterior resection (LAR) for middle-low rectal cancer in Ruijin Hospital of Shanghai Jiaotong University School of Medicine from January 2018 to December 2022 were collected as training dataset. There were 183 males and 80 females, aged 63(55,68)years. The clinicopathological data of 128 patients with middle-low rectal cancer were collected as validation dataset, including 83 males and 45 females, with age as 65(57,70)years. The training dataset was used to construct the prediction model, and the validation dataset was used to validate the prediction model. Observation indicators: (1) clinicopathological features of patients in the training dataset; (2) influencing factors for ≥3 times using of linear staplers in the operation; (3) prediction model construction; (4) efficiency evaluation of prediction model; (5) validation of prediction model. Measurement data with skewed distribution were represented as M( Q1, Q3), and Mann-Whitney U test was used for comparison between groups. Count data were expressed as absolute numbers, and comparison between groups was conducted using the chi-square test. Wilcoxon rank sum test was used for non-parametric data analysis. Univariate analysis was conducted using the Logistic regression model, and multivariate analysis was conducted using the Logistic stepwise regression model. The receiver operating characteristic (ROC) curve was draw and the area under the curve (AUC) was calculated. The AUC of the ROC curve >0.75 indicated the prediction model as acceptable. Comparison of AUC was conducted using the Delong test. Results:(1) Clinicopathological features of patients in the training dataset. Of the 263 patients, there were 48 cases with linear staplers used in the operation ≥3 times and 215 cases with linear staplers used in the operation ≤2 times. Cases with preoperative serum carcinoembryonic antigen (CEA) >5 μg/L, cases with anastomotic leakage, cases with tumor diameter ≥5 cm were 20, 12, 13 in the 48 cases with linear staplers used ≥3 times in the operation, versus 56, 26, 21 in the 215 cases with linear staplers used ≤2 times in the operation, showing significant differences in the above indicators between them ( χ2=4.66, 5.29, 10.45, P<0.05). (2) Influencing factors for ≥3 times using of linear staplers in the operation. Results of multivariate analysis showed that preoperative serum CEA >5 μg/L and tumor diameter ≥5 cm were independent risk factors for ≥3 times using of linear staplers in the operation ( odds ratio=2.26, 3.39, 95% confidence interval as 1.15-4.43, 1.50-7.65, P<0.05). (3) Prediction model construction. According to the results of multivariate analysis, the clinical prediction model was established as Logit(P)=-2.018+0.814×preoperative serum CEA (>5 μg/L as 1, ≤5 μg/L as 0)+ 1.222×tumor diameter (≥5 cm as 1, <5 cm as 0). The image data segmented by the Mask region convolutional neural network (MASK R-CNN) was input into the three-dimensional convolutional neural network (C3D), and the image prediction model was constructed by training. The image data segmented by the MASK R-CNN and the clinical independent risk factors were input into the C3D, and the integrated prediction model was constructed by training. (4) Efficiency evaluation of prediction model. The sensitivity, specificity and accuracy of the clinical prediction model was 70.0%, 81.0% and 79.4%, respectively, with the Yoden index as 0.51. The sensitivity, specificity and accuracy of the image prediction model was 50.0%, 98.3% and 91.2%, respectively, with the Yoden index as 0.48. The sensitivity, specificity and accuracy of the integrated prediction model was 70.0%, 98.3% and 94.1%, respectively, with the Yoden index as 0.68. The AUC of clinical prediction model, image prediction model and integrated prediction model was 0.72(95% confidence interval as 0.61-0.83), 0.81(95% confidence interval as 0.71-0.91) and 0.88(95% confidence interval as 0.81-0.95), respectively. There were significant differences in the efficacy between the integrated prediction model and the image prediction model or the clinical prediction model ( Z=2.98, 2.48, P<0.05). (5) Validation of prediction model. The three prediction models were externally validated by validation dataset. The sensitivity, specificity and accuracy of the clinical prediction model was 62.5%, 66.1% and 65.6%, respectively, with the Yoden index as 0.29. The sensitivity, specificity and accuracy of the image prediction model was 58.8%, 95.5% and 92.1%, respectively, with the Yoden index as 0.64. The sensitivity, specificity and accuracy of the integrated prediction model was 68.8%, 97.3% and 93.8%, respectively, with the Yoden index as 0.66. The AUC of clinical prediction model, image prediction model and integrated prediction model was 0.65(95% confidence interval as 0.55-0.75), 0.75(95% confidence interval as 0.66-0.84) and 0.84(95% confidence interval as 0.74-0.93), respec-tively. There was significant differences in the efficacy between the clinical prediction model and the integrated prediction model ( Z=3.24, P<0.05). Conclusion:The MRI-based deep-learning model can help predicting the high-risk population with ≥3 times using of linear staplers in resection of middle-low rectal cancer with double stapling technique.

Objective:To summarize the ideal strategy for the treatment of female hypospadias.Methods:The data of 12 female patients with hypospadias admitted to the Sixth People's Hospital Affiliated to Shanghai Jiaotong University School of Medicine from December 2011 to December 2019 were retrospectively analyzed. The patients was (31.0±16.6) years old (7-67 years old). Among them, 3 cases had a history of pelvic fracture trauma, 3 cases had a history of birth trauma, and the remaining 6 cases had no history of trauma and surgery. Among them, there were 6 cases of congenital hypospadias and 6 cases of acquired hypospadias. The clinical manifestations were urinary incontinence in 6 cases and dysuria in 6 cases. Examination of the normal position of the external opening of the genital urethra did not show the opening of the urethra, but moved down to different parts of the anterior wall of the vagina. All patients underwent urethral lengthening. For congenital hypospadias, the urethral plate is used to cut the coiled tube during the operation to prolong the urethra. For acquired hypospadias, the stenotic urethra was enlarged and lengthened with a labial pedicled flap coil. The subcutaneous fat pad of the labia majora was mobilized and transferred to the outside of the newly constructed urethra to prevent the occurrence of urethro-vaginal fistula and increase the pressure of the urethra. Five patients with significant urinary incontinence underwent bladder neck reconstruction at the same time. Anatomical success of the procedure was defined as the appearance of a normal-shaped external urethral opening beneath the clitoris. Functional success was defined as the absence of moderate to severe urinary incontinence after surgery, and the maximum urinary flow rate was >15ml/s during the 12-month follow-up period.Results:All operations were successfully completed. All patients had no perioperative complications, and were followed up for 18-96 months, with an average of 57.3±32.5 months. All patients were able to urinate spontaneously after operation, 4 cases of urinary incontinence disappeared, and 2 cases improved significantly; 4 cases of patients with strenuous urination urinated smoothly. The remaining 2 cases still complained of dysuria after operation, which was solved by subsequent urethral dilatation. The anatomical repair success rate was 100.0%(12/12) and the functional success rate was 83.3% (10/12).Conclusions:Urethral lengthening is an effective method for female hypospadias. The pedicled fat pad helps to increase urethral pressure and prevent fistulas. For female patients with hypospadias and severe urinary incontinence, bladder neck reconstruction is an ideal method. of the technique.

The main protease (Mpro) of SARS-CoV-2 is a highly conserved and mutation-resistant coronaviral enzyme, which plays a pivotal role in viral replication, making it an ideal target for the development of novel broad-spectrum anti-coronaviral drugs. In this study, a codon-optimized Mpro gene was cloned into pET-21a and pET-28a expression vectors. The recombinant plasmids were transformed into E. coli Rosetta(DE3) competent cells and the expression conditions were optimized. The highly expressed recombinant proteins, Mpro and Mpro-28, were purified by HisTrapTM chelating column and its proteolytic activity was determined by a fluorescence resonance energy transfer (FRET) assay. The FRET assay showed that Mpro exhibits a desirable proteolytic activity (25 000 U/mg), with Km and kcat values of 11.68 μmol/L and 0.037/s, respectively. The specific activity of Mpro is 25 times that of Mpro-28, a fusion protein carrying a polyhistidine tag at the N and C termini, indicating additional residues at the N terminus of Mpro, but not at the C terminus, are detrimental to its proteolytic activity. The preparation of active SARS-CoV-2 Mpro through codon-optimization strategy might facilitate the development of the rapid screening assays for the discovery of broad-spectrum anti-coronaviral drugs targeting Mpro.
COVID-19 ; Codon/genetics* ; Cysteine Endopeptidases/genetics* ; Escherichia coli/genetics* ; Humans ; Peptide Hydrolases ; SARS-CoV-2 ; Viral Nonstructural Proteins/genetics*

In canonical Wnt/β-catenin signaling pathway, β-catenin/TCF4 (T-cell factor 4) interaction plays an important role in the pathogenesis and development of non-small cell lung cancer (NSCLC), and it is tightly associated with the proliferation, chemoresistance, recurrence and metastasis of NSCLC. Therefore, suppressing β-catenin/TCF4 interaction in Wnt/β-catenin signaling pathway would be a new therapeutic avenue against NSCLC metastasis. In this study, considering the principle of enzyme-linked immunosorbent assay (ELISA), an optimized high-throughput screening (HTS) assay was developed for the discovery of β-catenin/TCF4 interaction antagonists. Subsequently, this ELISA-like screening assay was performed using 2 μg/mL GST-TCF4 βBD and 0.5 μg/mL β-catenin, then a high Z' factor of 0.83 was achieved. A pilot screening of a natural product library using this ELISA-like screening assay identified plumbagin as a potential β-catenin/TCF4 interaction antagonist. Plumbagin remarkably inhibited the proliferation of A549, H1299, MCF7 and SW480 cell lines. More importantly, plumbagin significantly suppressed the β-catenin-responsive transcription in TOPFlash assay. In short, this newly developed ELISA-like screening assay will be vital for the rapid screening of novel Wnt inhibitors targeting β-catenin/TCF4 interaction, and this interaction is a potential anticancer target of plumbagin in vitro.
Carcinoma, Non-Small-Cell Lung ; Cell Line, Tumor ; Enzyme-Linked Immunosorbent Assay ; High-Throughput Screening Assays ; Humans ; Lung Neoplasms ; Transcription Factor 4/genetics* ; beta Catenin/genetics*

Objective:To explore the selection of surgical methods for different sites of symptomatic Rathke's cleft cyst (RCC) and the clinical efficacies of these patients.Methods:Forty-seven patients with symptomatic RCC, admitted to our hospital from January 2016 to December 2019, were chosen in our study; 21 patients with intrasellar symptomatic RCC accepted surgery via unilateral nasal approach at the right side, 19 patients with intra-suprasellar symptomatic RCC accepted surgery via bilateral nasal approach, 3 patients with suprasellar symptomatic RCC accepted endonasal transsphenoidal surgery under endoscope, and 4 patients with suprasellar symptomatic RCC accepted craniotomy via pterion approach. The clinical efficacies and complications of patients accepted different surgical methods were compared. All patients were followed up for 3-36 months to observe the recurrence.Results:The postoperative symptoms of the patients were effectively improved, including headache relief ratio of 27/31, vision loss improvement ratio of 5/5, high prolactin relief ratio of 11/13, pituitary function improvement ratio of 9/18. Complications occurred in 6 patients, presenting as diabetes insipidus. Four patients recurred during follow-up.Conclusion:Intrasellar and intra-suprasellar symptomatic RCC accepted surgery via endoscopic transnasal transsphenoidal approach are safe and effective; selection of surgical methods for suprasellar symptomatic RCC should be determined according to the sizes and growth directions of cysts.

Polo-like kinase 1 (Plk1) is widely regarded as one of the most promising targets for cancer therapy due to its essential role in cell division and tumor cell survival. At present, most Plk1 inhibitors have been developed based on kinase domain, some of which are in clinical trial. However, inhibitors targeting kinase domain face off-target effect and drug resistance owing to the conserved nature and the frequent mutations in the ATP-binding pocket. In addition to a highly conserved kinase domain, Plk1 also contains a unique Polo-Box domain (PBD), which is essential for Plk1's subcellular localization and mitotic functions. Inhibitors targeting Plk1 PBD show stronger selectivity and less drug resistance for cancer therapy. Therefore, Plk1 PBD is an attractive target for the development of anti-cancer agents. In this review, we will summarize the up-to date drug discovery for targeting Plk1 PBD, including the molecular structure and cellular functions of Plk1 PBD. Small-molecule inhibitors targeting Plk1 PBD not only provide an opportunity to specifically inhibit Plk1 activity for cancer treatment, but also unveil novel biological basis regarding the molecular recognition of Plk1 and its substrates.
Cell Cycle Proteins/genetics* ; Neoplasms/drug therapy* ; Protein Kinase Inhibitors/pharmacology* ; Protein-Serine-Threonine Kinases/genetics* ; Proto-Oncogene Proteins/genetics*