OBJECTIVE To investigate the effects of subanesthetic dose of esketamine on postoperative anxiety and recovery in patients undergoing laparoscopic cholecystectomy. METHODS A total of 200 patients scheduled for laparoscopic cholecystectomy at Suzhou Ninth Hospital Affiliated to Soochow University from January 2023 to December 2024 were randomly assigned to control group （n＝100） and observation group （n＝100）. One minute before the initiation of anesthesia， patients in the control group received intravenous injections of Propofol emulsion injection， Sufentanil citrate injection， and Succinylcholine chloride injection. On this basis， patients in the observation group received an intravenous injection of Esketamine hydrochloride injection. The anxiety status of patients in both groups was compared， along with their general intraoperative conditions （including sufentanil dosage， duration of pneumoperitoneum， operative time， anesthesia time， and extubation time）， postoperative recovery， incidence of adverse reactions， and the need for dezocine rescue analgesia. Heart rate and mean arterial pressure， entropy index （state entropy and response entropy）， inflammatory marker levels [interleukin-6 （IL-6） and C-reactive protein （CRP）]， numerical rating scale （NRS） for pain intensity were compared between the two groups at different time points. RESULTS No significant differences were found between the two groups in pneumoperitoneum duration， operative time， anesthesia time，extubation time， incidence of postoperative dry mouth， entropy index or length of stay in the post-anesthesia care unit （P＞0.05）. Compared with the control group， the observation group showed significantly lower postoperative STAI-S scores， reduced intraoperative sufentanil consumption， decreased incidence of postoperative nausea， vomiting， and shivering， the need for dezocine rescue analgesia， as well as lower plasma IL-6 and CRP levels at 24 h after surgery， and NRS （P＜0.05）. The heart rate and mean arterial pressure of patients in the observation group at the start of surgery， end of surgery， and during extubation were all significantly higher than those in the control group （P＜0.05）. CONCLUSIONS Subanesthetic dose of esketamine can effectively alleviate postoperative anxiety， reduce intraoperative opioid consumption， suppress postoperative inflammatory response， relieve postoperative pain， and promote recovery in patients undergoing laparoscopic cholecystectomy.

Animal experimentation constitutes a critical link between basic research and clinical application, making its research quality and translational efficiency paramount. Although considerable progress has been made in standardizing operational procedures and ethical guidelines, the standardization of outcome evaluation systems has significantly lagged, creating a key bottleneck that constrains the quality of biomedical research and evidence synthesis. This deficiency is manifested by pronounced heterogeneity in outcome selection across similar studies, incomplete methodological reporting, and disparate criteria for result interpretation, which severely impairs the comparability of findings and the evidence integration. To cope with this challenge, this paper systematically introduces a mature methodological tool from clinical research–the core outcome set (COS)–and explores its construction strategies and application potential in the field of animal experimentation. Given the extensive diversity of animal experiments, a pragmatic strategy of "focusing on key areas, implementing phased pilots, and promoting gradual expansion" should be adopted. This approach prioritizes the development of domain-specific COS for disease areas characterized by high research volume, urgent translational needs, and well-established animal models. A multi-source integration pathway for COS development is detailed, comprising systematic literature searches, methodological appraisals, and expert consensus, with the feasibility of leveraging artificial intelligence (AI) to enhance efficiency also being examined. The development and promotion of such COS are not intended to restrict scientific exploration; rather, they aim to establish a new, tiered evaluation paradigm consisting of "core outcomes" (mandatory), "recommended outcomes" (encouraged), and "exploratory outcomes" (optional). This framework is expected not only to enhance research quality through standardization and to adhere to the "3R" principles but also to accelerate the accumulation of high-quality evidence. This, in turn, provides a solid foundation for higher-level evidence synthesis, ultimately facilitating the effective translation of basic research findings into clinical practice and providing an essential methodological framework for scientific advancement in relevant disciplines.

Objective To preliminarily investigate the safety and efficacy of donor pancreas needle biopsy in simultaneous pancreas-kidney transplantation. Methods Clinical data of 7 cases undergoing donor pancreas biopsy were collected retrospectively. All cases underwent donor pancreas biopsy before or during simultaneous pancreas-kidney transplantation. Frozen section or paraffin sectioning techniques were used for tissue preparation, and hematoxylin-eosin and Masson staining were performed to histologically evaluate the donor pancreas. The quality of donor pancreas was comprehensively assessed by combining histological findings with the donor's clinical data. Postoperative follow-up data of 5 simultaneous pancreas-kidney transplant recipients were collected to summarize the safety of donor pancreas biopsy and the prognosis of transplant recipients. Results The 7 pancreas donors were aged 28 to 62 years, with a body mass index ranging from 20.76 to 27.68 kg/m². Liver ultrasound indicated fatty liver in 3 cases, while pancreatic ultrasound did not reveal any significant abnormalities. Among them, biopsy was performed on 2 donors after completion of pancreatic procurement and processing, and the frozen section histology showed moderate acute pancreatitis changes (edema of acinar cells, necrosis and inflammatory cell infiltration). Combined with a serum amylase level elevated more than 3 times the upper limit of normal value, these two donor pancreases were finally discarded. The remaining 5 cases underwent biopsy immediately after pancreatic vascular anastomosis during simultaneous pancreas-kidney transplantation, and histological evaluation was performed on paraffin-embedded sections. No biopsy-related complications (such as bleeding, pancreatic fistula, etc.) occurred after transplantation. One recipient died of severe infection 2 months after transplantation, while the other 4 recipients were followed up for more than 5 years, with well-functioning transplant kidneys and pancreases. Conclusions Donor pancreas biopsy is relatively safe, and the risk of biopsy-related complications after transplantation is controllable. Comprehensive assessment of donor pancreas quality by combining histological evaluation with the donor's clinical indicators is conducive to improving the accuracy of donor pancreas selection and organ utilization.

ObjectiveTo evaluate the therapeutic effects of modified Banxia Xiexintang（MBXT） on polycystic ovary syndrome with insulin resistance（PCOS-IR） rats and reveal its potential mechanisms based on the integrated analysis of transcriptomics and metabolomics. MethodsFemale SD rats were selected， and a PCOS-IR model was established by intragastric administration of letrozole combined with a high-fat diet for 21 days. The modeled rats were randomly divided into the model group， MBXT low-， medium-， and high-dose groups（6.62， 13.23， 26.46 g·kg^-1）， and metformin group（0.158 g·kg^-1）， with a normal group set up separately. After 14 days of administration， the estrous cycle was observed， ovarian morphology was examined by hematoxylin-eosin（HE） staining， and the levels of testosterone（T）， estradiol（E₂）， follicle-stimulating hormone（FSH）， and luteinizing hormone（LH） in serum were detected by enzyme-linked immunosorbent assay（ELISA）. Serum metabolites and ovarian tissue gene expression were detected using ultra-performance liquid chromatography-quadrupole-electrostatic orbitrap mass spectrometry（UPLC-Q-Orbitrap-MS） and RNA-Seq technology， respectively， followed by multi-omics integrated analysis. ResultsPharmacodynamic findings revealed that all MBXT dose groups could reversed abnormal estrous cycles in PCOS-IR rats， improve polycystic ovarian lesions， and normalize dysregulated serum hormone levels（T， LH， E₂， FS， P<0.05， P<0.01）. Metabolomic analysis revealed that compared with the model group， MBXT reversed 278 differential metabolites such as estrone and S-formylglutathione， mainly involving pathways such as steroid hormone biosynthesis， glutathione metabolism， and lipid peroxidation regulation. Transcriptomic analysis identified 434 differentially expressed genes， and enrichment analysis revealed that MBXT significantly regulated lipid peroxidation defense systems， including glutathione metabolism， peroxisome function， and fatty acid metabolism， thereby intervening in ferroptosis processes. It also engaged in inflammation-related pathways such as the chemokine signaling pathway. Integrated analysis revealed that both metabolomics and transcriptomics co-enriched metabolic pathways associated with ferroptosis and fatty acid metabolism. And key Hub genes［such as Ras-related C3 botulinum toxin substrate 2 gene（Rac2） and Fas ligand gene（Faslg）］ showed significant correlations with differential metabolites. ConclusionMBXT can effectively ameliorate reproductive dysfunction and metabolic disorders in PCOS-IR rats. Its mechanism may be related to remodeling the immune-metabolism network， particularly by regulating MHC-mediated immune responses， inhibiting local ovarian ferroptosis， and enhancing steroid hormone synthesis pathways.

ObjectiveTo investigate the mechanism of modified Banxia Xiexintang（MBXT） in improving ovarian dysfunction in polycystic ovary syndrome with insulin resistance（PCOS-IR） rats by inhibiting ferroptosis through the adenosine monophosphate（AMP）-activated protein kinase（AMPK）/fatty acid synthase（FASN）/glutathione peroxidase 4（GPX4） signaling pathway. MethodsSeventy-six female SD rats were randomly divided into a normal group（n=13） and a modeling group（n=63）. The modeling group established a PCOS-IR model by intragastric administration of letrozole combined with a high-fat diet for 21 days. After successful modeling， these rats were randomly divided into the model group， MBXT low-， medium-， and high-dose groups（6.62， 13.23， 26.46 g·kg^-1）， metformin group（0.158 g·kg^-1）， and high-dose of MBXT combined with ferroptosis inducer Erastin group（15 mg·kg^-1）， with 10 rats in each group. After 14 days of intervention， ovarian pathological morphology was observed by hematoxylin-eosin（HE） staining， the mitochondrial ultrastructure of granulosa cells was observed by transmission electron microscopy（TEM）， ovarian reactive oxygen species（ROS） levels were detected by dihydroethidium（DHE） probe， biochemical methods were used to detect Fe²⁺， malondialdehyde（MDA）， glutathione（GSH） and other indicators in ovarian tissues， serum sex hormone and insulin levels were measured by enzyme-linked immunosorbent assay（ELISA）， and the protein expressions of AMPK， FASN， acyl-CoA synthetase long-chain family member 4（ACSL4）， GPX4， and solute carrier family 7 member 11（SLC7A11） in ovarian tissues were detected by Western blot. ResultsCompared with the normal group， the model group showed polycystic changes in the ovaries， with atrophy of mitochondria in granulosa cells and increased membrane density. Serum levels of testosterone（T）， luteinizing hormone（LH）， and insulin were significantly increased（P<0.01）. The levels of ROS， MDA， 4-hydroxynonenal（4-HNE）， and Fe²⁺ in ovarian tissues were significantly elevated（P<0.01）， while adenosine triphosphate（ATP）， GSH， and reduced nicotinamide adenine dinucleotide phosphate （NADPH） levels were significantly decreased（P<0.01）. The phosphorylation levels of AMPK and acetyl-CoA carboxylase （ACC）， as well as the protein expressions of SLC7A11， GPX4， and ferroptosis suppressor protein 1（FSP1） were significantly downregulated（P<0.01）， whereas the expressions of FASN， ACSL4， and nuclear receptor coactivator 4（NCOA4） were significantly upregulated（P<0.01）. Compared with the model group， MBXT intervention at various doses improved the above pathological changes and biochemical indicators in a dose-dependent manner， with the high-dose group showing the most significant effect（P<0.01）. Compared with the MBXT high-dose group， the high-dose of MBXT combined with ferroptosis inducer Erastin group restored ovarian ferroptosis characteristics in rats， with increased ROS and lipid peroxidation products， and altered expressions of key proteins（P<0.05， P<0.01）. ConclusionMBXT can effectively improve ovarian function and metabolic disorders in PCOS-IR rats. Its mechanism may be related to activating the AMPK/ACC signaling pathway， downregulating FASN and ACSL4 to reduce lipid peroxidation substrates， and restoring glucose-6-phosphate dehydrogenase/phosphoglycerate dehydrogenase（G6PD/PHGDH） metabolic flux to enhance the GPX4/FSP1 antioxidant defense system， thereby inhibiting ferroptosis in ovarian granulosa cells.

Objective To evaluate the predictive ability and clinical application value of artificial intelligence (AI) systems in the benign and malignant differentiation and pathological type of pulmonary nodules, and to summarize clinical application experience. Methods A retrospective analysis was conducted on the clinical data of patients with pulmonary nodules admitted to the Department of Thoracic Surgery, Second Hospital of Lanzhou University, from February 2016 to February 2025. Firstly, pulmonary nodules were divided into benign and non-benign groups, and the discriminative abilities of AI systems and clinicians were compared. Subsequently, lung nodules reported as precursor glandular lesions (PGL), microinvasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) in postoperative pathological results were analyzed, comparing the efficacy of AI systems and clinicians in predicting the pathological type of pulmonary nodules. Results In the analysis of benign/non-benign pulmonary nodules, clinical data from a total of 638 patients with pulmonary nodules were included, of which there were 257 males (10 patients and 1 patient of double and triple primary lesions, respectively) and 381 females (18 patients and 1 patient of double and triple primary lesions, respectively), with a median age of 55.0 (47.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis of the two groups of variables showed that, except for nodule location, the differences in the remaining variables were statistically significant (P<0.05). Multivariate logistic regression analysis showed that age, nodule type (subsolid pulmonary nodule), average density, spicule sign, and vascular convergence sign were independent influencing factors for non-benign pulmonary nodules, among which age, nodule type (subsolid pulmonary nodule), spicule sign, and vascular convergence sign were positively correlated with non-benign pulmonary nodules, while average density was negatively correlated with the occurrence of non-benign pulmonary nodules. The area under the receiver operating characteristic curve (AUC) of the malignancy risk value given by the AI system in predicting non-benign pulmonary nodules was 0.811, slightly lower than the 0.898 predicted by clinicians. In the PGL/MIA/IAC analysis, clinical data from a total of 411 patients with pulmonary nodules were included, of which there were 149 males (8 patients of double primary lesions) and 262 females (17 patients of double primary lesions), with a median age of 56.0 (50.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis results showed that, except for gender, nodule location, and vascular convergence sign, the differences in the remaining variables among the three groups of PGL, MIA, and IAC patients were statistically significant (P<0.05). Multinomial multivariate logistic regression analysis showed that the differences between the parameters in the PGL group and the MIA group were not statistically significant (P>0.05), and the maximum diameter and average density of the nodules were statistically different between the PGL and IAC groups (P<0.05), and were positively correlated with the occurrence of IAC as independent risk factors. The average AUC value, accuracy, recall rate, and F1 score of the AI system in predicting lung nodule pathological type were 0.807, 74.3%, 73.2%, and 68.5%, respectively, all better than the clinical physicians’ prediction of lung nodule pathological type indicators (0.782, 70.9%, 66.2%, and 63.7% respectively). The AUC value of the AI system in predicting IAC was 0.853, and the sensitivity, specificity, and optimal cutoff value were 0.643, 0.943, and 50.0%, respectively. Conclusion This AI system has demonstrated high clinical value in predicting the benign and malignant nature and pathological type of lung nodules, especially in predicting lung nodule pathological type, its ability has surpassed that of clinical physicians. With the optimization of algorithms and the adequate integration of multimodal data, it can better assist clinical physicians in formulating individualized diagnostic and treatment plans for patients with lung nodules.

This study employed bioinformatics to screen the feature genes related to efferocytosis in diabetic kidney disease(DKD) and explores traditional Chinese medicine(TCM) regulating these feature genes. The GSE96804 and GSE30528 datasets were integrated as the training set, and the intersection of differentially expressed genes and efferocytosis-related genes(ERGs) was identified as DKD-ERGs. Subsequently, correlation analysis, protein-protein interaction(PPI) network construction, enrichment analysis, and immune infiltration analysis were performed. Consensus clustering was conducted on DKD patients based on the expression levels of DKD-ERGs, and the expression levels, immune infiltration characteristics, and gene set variations between different subtypes were explored. Eight machine learning models were constructed and their prediction performance was evaluated. The best-performing model was evaluated by nomograms, calibration curves, and external datasets, followed by the identification of efferocytosis-related feature genes associated with DKD. Finally, potential TCMs that can regulate these feature genes were predicted. The results showed that the training set contained 640 differentially expressed genes, and after intersecting with ERGs, 12 DKD-ERGs were obtained, which demonstrated mutual regulation and immune modulation effects. Consensus clustering divided DKD into two subtypes, C1 and C2. The support vector machine(SVM) model had the best performance, predicting that growth arrest-specific protein 6(GAS6), S100 calcium-binding protein A9(S100A9), C-X3-C motif chemokine ligand 1(CX3CL1), 5'-nucleotidase(NT5E), and interleukin 33(IL33) were the feature genes of DKD. Potential TCMs with therapeutic effects included Astragali Radix, Trionycis Carapax, Sargassum, Rhei Radix et Rhizoma, Curcumae Radix, and Alismatis Rhizoma, which mainly function to clear heat, replenish deficiency, activate blood, resolve stasis, and promote urination and drain dampness. Molecular docking revealed that the key components of these TCMs, including β-sitosterol, quercetin, and sitosterol, exhibited good binding activity with the five target genes. These results indicated that efferocytosis played a crucial role in the development and progression of DKD. The feature genes closely related to both DKD and efferocytosis, such as GAS6, S100A9, CX3CL1, NT5E, and IL33, were identified. TCMs such as Astragali Radix, Trionycis Carapa, Sargassum, Rhei Radix et Rhizoma, Curcumae Radix, and Alismatis Rhizoma may provide a new therapeutic strategy for DKD by regulating efferocytosis.
Humans ; Computational Biology ; Diabetic Nephropathies/physiopathology* ; Protein Interaction Maps ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal ; Phagocytosis/genetics* ; Efferocytosis

OBJECTIVE: As an age-related neurodegenerative disease, the prevalence of mild cognitive impairment (MCI) increases with age. Within the framework of traditional Chinese medicine, spleen-kidney deficiency syndrome (SKDS) is recognized as the most frequent MCI subtype. Due to the covert and gradual onset of MCI, in community settings it poses a significant challenge for patients and their families to discern between typical aging and pathological changes. There exists an urgent need to devise a preliminary diagnostic tool designed for community-residing older adults with MCI attributed to SKDS (MCI-SKDS). METHODS: This investigation enrolled 312 elderly individuals diagnosed with MCI, who were randomly distributed into training and test datasets at a 3:1 ratio. Five machine learning methods, including logistic regression (LR), decision tree (DT), naive Bayes (NB), support vector machine (SVM), and gradient boosting (GB), were used to build a diagnostic prediction model for MCI-SKDS. Accuracy, sensitivity, specificity, precision, F1 score, and area under the curve were used to evaluate model performance. Furthermore, the clinical applicability of the model was evaluated through decision curve analysis (DCA). RESULTS: The accuracy, precision, specificity and F1 score of the DT model performed best in the training set (test set), with scores of 0.904 (0.845), 0.875 (0.795), 0.973 (0.875) and 0.973 (0.875). The sensitivity of the training set (test set) of the SVM model performed best among the five models with a score of 0.865 (0.821). The area under the curve of all five models was greater than 0.9 for the training dataset and greater than 0.8 for the test dataset. The DCA of all models showed good clinical application value. The study identified ten indicators that were significant predictors of MCI-SKDS. CONCLUSION The risk prediction index derived from machine learning for the MCI-SKDS prediction model is simple and practical; the model demonstrates good predictive value and clinical applicability, and the DT model had the best performance. Please cite this article as: Ai YT, Zhou S, Wang M, Zheng TY, Hu H, Wang YC, Li YC, Wang XT, Zhou PJ. Development of a machine learning-based risk prediction model for mild cognitive impairment with spleen-kidney deficiency syndrome in the elderly. J Integr Med. 2025; 23(4): 390-397.
Humans ; Cognitive Dysfunction/diagnosis* ; Aged ; Male ; Female ; Machine Learning ; Spleen ; Aged, 80 and over ; Kidney ; Medicine, Chinese Traditional