Objective To construct a lung cancer surgery-oriented disease-specific database covering the entire perioperative care pathway, thereby improving the quality and usability of key surgical data elements. Methods Real-world clinical data were extracted from a single-center thoracic surgery department. A standardized data model was established based on the open electronic health record (openEHR) standard. Large language model (LLM), optical character recognition (OCR), and artificial intelligence (AI)-driven techniques were employed to extract, structure, and perform quality control on unstructured clinical narratives, imaging reports, and radiological data, with a focus on capturing surgically relevant perioperative indicator. Results A multimodal database comprising 19 917 patients was established, including 7 930 males and 11 987 females, with ages ranging from 15 to 97 (61.7±9.7) years. The database includes 582 structured data variables, textual report data corresponding to 69 clinical indicators, 13 000 pulmonary function test PDF reports, and chest CT imaging data from 16 884 patients. This database comprehensively covers major information relevant to surgical diagnosis and treatment of lung cancer, significantly improving the completeness and granularity of surgical detail data. Large language models (LLMs) and optical character recognition (OCR) technologies enhanced the efficiency of converting unstructured data into structured formats, while a multi-level manual verification process ensured data accuracy and traceability. The database supports real-world research including comparisons of surgical procedures, prediction of postoperative complications, prognosis assessment, and multimodal data association analyses.

Objective:To construct and validate a predictive model for pathological complete response (pCR) in patients with locally advanced rectal cancer (LARC) after neoadjuvant chemoradiotherapy.Methods:This retrospective observational study included 595 patients with stage T2-4 and (or) N+M0 LARC diagnosed in the Cancer Hospital of Chinese Academy of Medical Sciences and the Fourth Hospital of Hebei Medical University who had no metastases, tolerated neoadjuvant therapy, completed neoadjuvant therapy, and had undergone radical surgery after neoadjuvant therapy. The training set comprised 299 patients admitted to the Cancer Hospital of Chinese Academy of Medical Sciences from 2013 to 2018, the internal validation set 155 patients admitted from 2019 to 2023, and the external validation set 141 patients admitted to the Fourth Hospital of Hebei Medical University from 2013 to 2021. They were divided into pCR group and non-pCR groups according to postoperative pathology. Among the 299 patients in the training set, 247 were in the non-PCR and 52 in the pCR group; among the 155 patients verified internally, 113 were in the non-PCR and 42 in the pCR group; and among the 141 patients validated externally, 132 were in the non-pCR and nine in the pCR group. Logistic regression was used for univariate and multifactorial analysis to explore the factors associated with pCR and construct a nomogram prediction model. Receiver operating characteristic curves, calibration curves, and decision curve analysis (DCA) were used to validate the performance of the predictive model.Results:Univariate and multivariate logistic regression analysis showed that carbohydrate antigen 19-9 ( P=0.040, OR=0.97, 95%CI: 0.93-0.99), neutrophil count ( P<0.001, OR=0.66, 95%CI: 0.52-0.84), tumor T stage: Stage IV ( P=0.011, OR=0.22, 95%CI: 0.07-0.70), tumor N stage: Stage I ( P=0.003, OR=0.22,95%CI:0.08-0.60), Stage II ( P<0.001, OR=0.03, 95%CI: 0.01-0.09) and involvement of mesorectal fascia ( P=0.004, OR=0.09, 95%CI: 0.02-0.47) were independent predictors of pCR. In the training set, the area under the receiver operating characteristic curve of the model was 0.92 (95%CI: 0.87-0.96), whereas in the internal and external validation sets, the AUCs were 0.78 and 0.81, respectively. The calibration curve showed that the prediction model had good prediction efficiency in both the training and verification sets. Decision curve analysis showed that the net benefit of the model was largest when the threshold probability was in the range of 5.2% to 89.7% (in the internal and external validation sets, the threshold probabilities were in the range of 15.7% to 92.3% and 2.2% to 84.1%, respectively). Conclusion:The nomogram model constructed in this study showed efficacy in predicting whether patients with LARC will achieve pCR after receiving neoadjuvant chemoradiotherapy.

Protective ileostomy is an important bridging procedure in low anterior resection for rectal cancer, aimed at preventing severe anastomotic complications. It has been shown to significantly reduce the risk of pelvic infections resulting from anastomotic leakage. However, whether ileostomy plays a positive clinical role in preventing anastomotic leaks remains a subject of considerable debate. The procedure for creating a protective ileostomy is relatively simple and convenient, making it a commonly used approach in clinical practice. Nevertheless, as a traumatic surgical procedure, ileostomy itself may lead to a range of complications. Therefore, it is crucial to comprehensively understand the potential complications associated with ileostomy, develop optimized management strategies, and carefully select appropriate patients for preventive ileostomy, as these steps hold significant clinical value. This article provides a systematic review of the types, development, and application of preventive ileostomy, as well as the management and prevention strategies for common complications. The aim is to offer valuable guidance to clinical surgeons in optimizing stoma management and minimizing complications in rectal cancer sphincter-preserving surgery.

Objective:To construct and validate a predictive model for pathological complete response (pCR) in patients with locally advanced rectal cancer (LARC) after neoadjuvant chemoradiotherapy.Methods:This retrospective observational study included 595 patients with stage T2-4 and (or) N+M0 LARC diagnosed in the Cancer Hospital of Chinese Academy of Medical Sciences and the Fourth Hospital of Hebei Medical University who had no metastases, tolerated neoadjuvant therapy, completed neoadjuvant therapy, and had undergone radical surgery after neoadjuvant therapy. The training set comprised 299 patients admitted to the Cancer Hospital of Chinese Academy of Medical Sciences from 2013 to 2018, the internal validation set 155 patients admitted from 2019 to 2023, and the external validation set 141 patients admitted to the Fourth Hospital of Hebei Medical University from 2013 to 2021. They were divided into pCR group and non-pCR groups according to postoperative pathology. Among the 299 patients in the training set, 247 were in the non-PCR and 52 in the pCR group; among the 155 patients verified internally, 113 were in the non-PCR and 42 in the pCR group; and among the 141 patients validated externally, 132 were in the non-pCR and nine in the pCR group. Logistic regression was used for univariate and multifactorial analysis to explore the factors associated with pCR and construct a nomogram prediction model. Receiver operating characteristic curves, calibration curves, and decision curve analysis (DCA) were used to validate the performance of the predictive model.Results:Univariate and multivariate logistic regression analysis showed that carbohydrate antigen 19-9 ( P=0.040, OR=0.97, 95%CI: 0.93-0.99), neutrophil count ( P<0.001, OR=0.66, 95%CI: 0.52-0.84), tumor T stage: Stage IV ( P=0.011, OR=0.22, 95%CI: 0.07-0.70), tumor N stage: Stage I ( P=0.003, OR=0.22,95%CI:0.08-0.60), Stage II ( P<0.001, OR=0.03, 95%CI: 0.01-0.09) and involvement of mesorectal fascia ( P=0.004, OR=0.09, 95%CI: 0.02-0.47) were independent predictors of pCR. In the training set, the area under the receiver operating characteristic curve of the model was 0.92 (95%CI: 0.87-0.96), whereas in the internal and external validation sets, the AUCs were 0.78 and 0.81, respectively. The calibration curve showed that the prediction model had good prediction efficiency in both the training and verification sets. Decision curve analysis showed that the net benefit of the model was largest when the threshold probability was in the range of 5.2% to 89.7% (in the internal and external validation sets, the threshold probabilities were in the range of 15.7% to 92.3% and 2.2% to 84.1%, respectively). Conclusion:The nomogram model constructed in this study showed efficacy in predicting whether patients with LARC will achieve pCR after receiving neoadjuvant chemoradiotherapy.

Protective ileostomy is an important bridging procedure in low anterior resection for rectal cancer, aimed at preventing severe anastomotic complications. It has been shown to significantly reduce the risk of pelvic infections resulting from anastomotic leakage. However, whether ileostomy plays a positive clinical role in preventing anastomotic leaks remains a subject of considerable debate. The procedure for creating a protective ileostomy is relatively simple and convenient, making it a commonly used approach in clinical practice. Nevertheless, as a traumatic surgical procedure, ileostomy itself may lead to a range of complications. Therefore, it is crucial to comprehensively understand the potential complications associated with ileostomy, develop optimized management strategies, and carefully select appropriate patients for preventive ileostomy, as these steps hold significant clinical value. This article provides a systematic review of the types, development, and application of preventive ileostomy, as well as the management and prevention strategies for common complications. The aim is to offer valuable guidance to clinical surgeons in optimizing stoma management and minimizing complications in rectal cancer sphincter-preserving surgery.

Objective: To investigate the effects of Zuogui Jiangtang Yishen Formula (左归降糖益肾方, ZGJTYSF) in regulating the nucleotide-binding oligomerization domain-like receptor protein 3 (NLRP3)/caspase-1/gasdermin D (GSDMD) signaling axis on pyroptosis in rats with diabetic kidney disease (DKD). Methods: Fifty male specific pathogen-free (SPF) grade Goto-Kakizaki (GK) rats (12 weeks old) were fed a high-fat diet for one month to establish an early DKD model. Model establishment was confirmed when fasting blood glucose (FBG) ≥ 11.1 mmol/L and urinary albumin-to-creatinine ratio (uACR) ≥ 30 mg/g. The successfully modeled early DKD rats were randomly divided by random number table into five groups (n = 10 per group): model group; dapagliflozin group (1.0 mg/kg, by gavage, served as positive control); and low-, medium-, and high-dose of ZGJTYSF groups (4.9, 9.9, and 19.9 g/kg, respectively, by gavage). Age-matched male SPF Wistar rats (n = 10) served as control group. Rats in control and model groups were gavaged with equivalent volumes of distilled water. Treatment lasted 12 weeks. Changes in uACR, FBG, and renal function were observed in all groups. Hematoxylin-eosin (HE), periodic acid-Schiff (PAS), and Masson staining were used to observe renal histopathological changes. Immunohistochemistry was performed to detect the localization and expression of caspase-1, GSDMD, and NLRP3 in rat renal tissues. Terminal deoxynucleotidyl transferase deoxyuridine triphosphate (dUTP) nick end labeling (TUNEL) was utilized to detect pyroptosis in renal tissues. Quantitative real-time polymerase chain reaction (qPCR) and Western blot were applied to detect mRNA and protein expression levels of NLRP3, caspase-1, GSDMD, interleukin (IL)-1β, and IL-18. Results: Compared with model group, all doses of ZGJTYSF showed reductions in FBG, with medium- and high-dose of ZGJTYSF groups demonstrating significant decreases at week 8 and 12 (P < 0.05). For uACR, all doses of ZGJTYSF groups exhibited a decreasing trend, with high-dose of ZGJTYSF group being significantly lower than low- and medium-dose of ZGJTYSF groups at week 12 (P < 0.05) and showing no significant difference from dapagliflozin group (P > 0.05). No significant differences in renal function parameters (serum creatinine, blood urea nitrogen, and uric acid) were observed among groups (P > 0.05). Histopathological examination revealed milder glomerular and tubular lesions in both ZGJTYSF groups and dapagliflozin group, with renal pathological changes in high-dose of ZGJTYSF group resembling those in dapagliflozin group. Immunohistochemistry demonstrated significantly reduced expression of caspase-1, GSDMD, and NLRP3 in renal tissues of dapagliflozin group and high-dose of ZGJTYSF group compared with model group (P < 0.05 or P < 0.01), while the differences in low- and medium-dose of ZGJTYSF groups were not statistically significant (P > 0.05). TUNEL assay showed significantly fewer TUNEL-positive cells in renal tissues of dapagliflozin and high-dose of ZGJTYSF groups (P < 0.01), indicating a marked reduction in pyroptotic cells. Molecular analysis revealed that compared with model group, both dapagliflozin and high-dose of ZGJTYSF groups showed significantly downregulated mRNA and protein expression levels of NLRP3, caspase-1, GSDMD, IL-1β, and IL-18 in renal tissues (P < 0.01), while low- and medium-dose of ZGJTYSF groups showed downward trends without statistical significance (P > 0.05). Conclusion ZGJTYSF may inhibit renal pyroptosis by regulating the NLRP3/caspase-1/GSDMD signaling axis, thereby preventing and treating early renal injury in DKD and delaying the onset and progression of DKD.

BACKGROUND: Neoadjuvant chemoradiotherapy followed by radical surgery has been a common practice for patients with locally advanced rectal cancer, but the response rate varies among patients. This study aimed to develop a ResNet-Vision Transformer based magnetic resonance imaging (MRI)-endoscopy fusion model to precisely predict treatment response and provide personalized treatment. METHODS: In this multicenter study, 366 eligible patients who had undergone neoadjuvant chemoradiotherapy followed by radical surgery at eight Chinese tertiary hospitals between January 2017 and June 2024 were recruited, with 2928 pretreatment colonic endoscopic images and 366 pelvic MRI images. An MRI-endoscopy fusion model was constructed based on the ResNet backbone and Transformer network using pretreatment MRI and endoscopic images. Treatment response was defined as good response or non-good response based on the tumor regression grade. The Delong test and the Hanley-McNeil test were utilized to compare prediction performance among different models and different subgroups, respectively. The predictive performance of the MRI-endoscopy fusion model was comprehensively validated in the test sets and was further compared to that of the single-modal MRI model and single-modal endoscopy model. RESULTS: The MRI-endoscopy fusion model demonstrated favorable prediction performance. In the internal validation set, the area under the curve (AUC) and accuracy were 0.852 (95% confidence interval [CI]: 0.744-0.940) and 0.737 (95% CI: 0.712-0.844), respectively. Moreover, the AUC and accuracy reached 0.769 (95% CI: 0.678-0.861) and 0.729 (95% CI: 0.628-0.821), respectively, in the external test set. In addition, the MRI-endoscopy fusion model outperformed the single-modal MRI model (AUC: 0.692 [95% CI: 0.609-0.783], accuracy: 0.659 [95% CI: 0.565-0.775]) and the single-modal endoscopy model (AUC: 0.720 [95% CI: 0.617-0.823], accuracy: 0.713 [95% CI: 0.612-0.809]) in the external test set. CONCLUSION The MRI-endoscopy fusion model based on ResNet-Vision Transformer achieved favorable performance in predicting treatment response to neoadjuvant chemoradiotherapy and holds tremendous potential for enabling personalized treatment regimens for locally advanced rectal cancer patients.
Humans ; Rectal Neoplasms/diagnostic imaging* ; Magnetic Resonance Imaging/methods* ; Male ; Female ; Middle Aged ; Neoadjuvant Therapy/methods* ; Aged ; Adult ; Chemoradiotherapy/methods* ; Endoscopy/methods* ; Treatment Outcome

Objective:To observe the diuretic effects of Zhuling Decoction on mice with adriamycin nephropathy (ADRN); To explore its mechanism.Methods:Totally 32 SPF male C57BL/6 mice were divided into a blank group of 7 mice and a model group of 25 mice using a random number table method. ADRN model was prepared by single tail vein injection of 0.01 g/kg of amphotericin. Two weeks later, the successfully modeled mice were divided into a model group (7 mice), a furosemide group (8 mice), and a Zhuling Decoction group (8 mice). The blank group and model group mice were given equal volumes of injection water by gavage. The furosemide group was given 2.6 mg/kg of furosemide by gavage, and the Zhuling Decoction group was given 6.5 g/kg of Zhuling Decoction by gavage, once a day, for 8 consecutive weeks. Changes in body weight and urine output of mice were observed. A biochemical analyzer was used to detect 24-hour urinary protein quantification and blood potassium and SCr levels in mice. HE staining was used to observe pathological changes in mouse kidneys, and immunohistochemistry and Western blot were used to detect the homology of cyclin dependent kinase 18 (CDK18), STIP1, and the expressions of U-box protein 1 (STUB1) and aquaporin 2 (AQP2) in mouse kidney tissue cells.Results:Compared with the model group, both the furosemide and Zhuling Decoction groups exhibited increased 24-hour urine output ( P<0.05); compared with the model group and furosemide group, Zhuling Decoction group showed reduced average optical density values and protein expressions of CDK18 and AQP2 ( P<0.05) and increased STUB1 average optical density value and protein expression ( P<0.05). Conclusion:Zhuling Decoction can increase 24-hour urine output in ADRN mice, and the mechanism may be related to down-regulation of CDK18 and AQP2 protein expressions and up-regulation of STUB1 protein expression, thereby modulating the CDK18/STUB1/AQP2 pathway and reducing water reabsorption.

Approximately 60% of colorectal cancer (CRC) patients exhibit TP53 mutations, which are strongly associated with tumor progression, chemotherapy resistance, and an unfavorable prognosis. However, targeting p53 has historically been challenging, and currently, there are no approved p53-based therapeutics for clinical use worldwide. In this study, we discovered that ubiquitin carboxyl terminal hydrolase L3 (UCHL3) plays a crucial role in high-level glycolysis, enhanced stem-like properties, and 5-fluorouracil (5-FU) chemoresistance in TP53-mutant CRC by exerting its deubiquitinating enzyme activity to stabilize α-enolase (ENO1) protein. Notably, we identified a newly Food and Drug Administration (FDA)-approved drug, pacritinib, that potently suppresses UCHL3 expression by blocking the janus kinase 2 (JAK2)-signal transducer and activator of transcription 3 (STAT3) pathway in TP53-mutant CRC. Furthermore, Pacritinib was demonstrated to effectively inhibit glycolysis and improve the sensitivity to 5-FU chemotherapy in TP53-mutant CRC. Our findings suggest that targeting the JAK2-STAT3-UCHL3-ENO1 axis is a promising strategy to suppress glycolysis and enhance the efficacy of 5-FU chemotherapy in TP53-mutant CRC. Pacritinib shows potential for clinical application in the treatment of TP53-mutant CRC.

The incidence of osteoporotic thoracolumbar vertebral fracture (OTLVF) in the elderly is gradually increasing. The kyphotic deformity caused by various factors has become an important characteristic of OTLVF and has received increasing attention. Its clinical manifestations include pain, delayed nerve damage, sagittal imbalance, etc. Currently, the definition and diagnosis of OTLVF with kyphotic deformity in the elderly are still unclear. Although there are many treatment options, they are controversial. Existing guidelines or consensuses pay little attention to this type of fracture with kyphotic deformity. To this end, the Lumbar Education Working Group of the Spine Branch of the Chinese Medicine Education Association and Editorial Committee of Chinese Journal of Trauma organized the experts in the relevant fields to jointly develop Clinical guidelines for the diagnosis and treatment of osteoporotic thoracolumbar vertebral fractures with kyphotic deformity in the elderly ( version 2024), based on evidence-based medical advancements and the principles of scientificity, practicality, and advanced nature, which provided 18 recommendations to standardize the clinical diagnosis and treatment.