OBJECTIVES: Renal cell carcinoma (RCC) is a malignant renal tumor that poses a significant threat to patient health. Accurate preoperative pathological grading plays a crucial role in determining the appropriate treatment for this disease. Currently, deep learning technology has become an important method for pathological grading of RCC. However, existing methods primarily rely on single-phase computed tomography (CT) imaging for analysis and prediction, which has limitations such as missing small lesions, one-sided evaluation, and local focusing issues. Therefore, this study proposes a multi-modal deep learning algorithm that integrates multi-phase enhanced CT images with clinical variable data, aiming to provide a basis for predicting the pathological grading of RCC. METHODS: First, the algorithm took four-phase enhanced CT images from the plain scan, arterial phase, venous phase, and delayed phase, along with clinical variables, as inputs. Then, an embedding encoding module was used to extract heterogeneous information from the clinical variables, and a 3-dimensional (3D) ResNet50 model was employed to capture spatial information from the multi-phase enhanced CT image data. Finally, a Fusion module deeply integrated the feature information from clinical variables and each phase's CT image features, further utilizing a cross-self-attention mechanism to achieve multi-phase feature fusion. This approach comprehensively captures the deep semantic information from the patient data, fully leveraging the complementary advantages of multi-modal and multi-phase data. To validate the effectiveness of the proposed method, a total of 1 229 RCC patients were approved by ethics review were included to train the model. RESULTS: Experimental results demonstrated superior performance compared to traditional radiomics and state-of-the-art deep learning methods, achieving an accuracy of 83.87%, a recall rate of 95.04%, and an F1-score of 82.23%. CONCLUSIONS The proposed algorithm exhibits strong stability and sensitivity, significantly enhancing the predictive performance of RCC pathological grading. It offers a novel approach for accurate RCC diagnosis and personalized treatment planning.
Humans ; Carcinoma, Renal Cell/pathology* ; Deep Learning ; Kidney Neoplasms/diagnostic imaging* ; Tomography, X-Ray Computed/methods* ; Algorithms ; Neoplasm Grading ; Male ; Female ; Middle Aged

OBJECTIVE: Baicalein has been reported to have wide therapeutic effects that act through its anti-inflammatory activity. This study examines the effect and mechanism of baicalein on sepsis-induced cardiomyopathy (SIC). METHODS: A thorough screening of a small library of natural products, comprising 100 diverse compounds, was conducted to identify the most effective drug against lipopolysaccharide (LPS)-treated H9C2 cardiomyocytes. The core target proteins and their associated signaling pathways involved in baicalein's efficacy against LPS-induced myocardial injury were predicted by network pharmacology. RESULTS: Baicalein was identified as the most potent protective agent in LPS-exposed H9C2 cardiomyocytes. It exhibited a dose-dependent inhibitory effect on cell injury and inflammation. In the LPS-induced septic mouse model, baicalein demonstrated a significant capacity to mitigate LPS-triggered myocardial deficits, inflammatory responses, and ferroptosis. Network pharmacological analysis and experimental confirmation suggested that hypoxia-inducible factor 1 subunit α (HIF1-α) is likely to be the crucial factor in mediating the impact of baicalein against LPS-induced myocardial ferroptosis and injury. By combining microRNA (miRNA) screening in LPS-treated myocardium with miRNA prediction targeting HIF1-α, we found that miR-299b-5p may serve as a regulator of HIF1-α. The reduction in miR-299b-5p levels in LPS-treated myocardium, compared to the control group, was reversed by baicalein treatment. The reverse transcription quantitative polymerase chain reaction, Western blotting, and dual-luciferase reporter gene analyses together identified HIF1-α as the target of miR-299b-5p in cardiomyocytes. CONCLUSION Baicalein mitigates SIC at the miRNA level, suggesting the therapeutic potential of it in treating SIC through the regulation of miR-299b-5p/HIF1-α/ferroptosis pathway. Please cite this article as: Zhou WY, Du JK, Liu HH, Deng L, Ma K, Xiao J, Zhang S, Wang CN. Baicalein attenuates lipopolysaccharide-induced myocardial injury by inhibiting ferroptosis via miR-299b-5p/HIF1-α pathway. J Integr Med. 2025; 23(5):560-575.
Flavanones/pharmacology* ; Animals ; MicroRNAs/genetics* ; Lipopolysaccharides ; Hypoxia-Inducible Factor 1, alpha Subunit/genetics* ; Ferroptosis/drug effects* ; Mice ; Myocytes, Cardiac/metabolism* ; Signal Transduction/drug effects* ; Rats ; Male ; Mice, Inbred C57BL ; Cardiomyopathies/etiology* ; Cell Line ; Sepsis/complications*

PI3Kγ and PI3Kδ have important regulatory roles in the immune system, and targeting these two subtypes helps to reshape the tumor microenvironment. PI3Kγ and PI3Kδ are potential targets for tumor immunotherapy. In this study, a series of new pyrazolopyrimidine derivatives were designed and synthesized on the basis of our previously reported PI3K inhibitors, resulting in the discovery of compound 16l as a potent and selective PI3Kγ/δ dual inhibitor. Compound 16l demonstrated strong biochemical potencies against PI3Kγ and PI3Kδ with IC₅₀ values of 0.11 and 0.79 nmol·L^-1. In cell-based assays, it potently inhibited the PI3Kγ and PI3Kδ mediated Akt S473 phosphorylation with EC₅₀ values of 3 and 7 nmol·L^-1. In vivo, compound 16l exhibited acceptable pharmacokinetic properties in Sprague-Dawley (SD) rats and suppressed the tumor growth in a MC38 syngeneic mouse model. The animal experiments were approved by the Animal Ethics Committee of Hefei Institutes of Physical Science, Chinese Academy of Sciences (approval number: DWLL-2000-06). In addition, no appreciable human ether-a-go-go-related gene (hERG) inhibition was observed for compound 16l even at 30 μmol·L^-1. These results suggested that compound 16l might be a potential research tool for studying the PI3Kγ/δ mediated signaling pathways.

Objective To understand the prevalence characteristics of influenza and changes of influenza virus strains,and provide reference for the prevention and control of influenza in the province.Methods Surveillance da-ta about influenza in Hunan Province from 2014 to 2023 were exported from China Influenza Surveillance Informa-tion System.Differences in the percentage of influenza-like illness(ILI)cases(percentage of influenza-like cases[ILI％]in outpatient and emergency department visits)among different years and different populations,as well as the positive rate of influenza virus in ILI specimens were compared.Results From 2014 to 2023,over 2.65 million cases of ILI were reported,with an ILI％of 4.70％.ILI％among different years presented statistically significant differences(P＜0.001).People aged 0-14 years old were the main population with ILI,accounting for 82.90％.The positive rate of influenza virus in ILI specimens was 14.14％,the positive rate of influenza virus among diffe-rent years and age groups were both significantly different(both P＜0.001).The main prevalent influenza strains from 2014 to 2023 included types A(H1N1),A(H3N2),B(Victoria),and B(Yamagata),alternating among di-fferent years.However,type B(Yamagata)strains were not detected from 2020 to 2023.There were basically two influenza prevalence seasons every year,namely winter-spring and summer.Conclusion People＜15 years old are the main population of influenza,and the prevalence peaks are in winter-spring and summer.From 2021 to 2023,the prevalence alternates mainly among 3 types:A(H1N1),A(H3N2),and B(Victoria).

Objective:To construct a machine-learning model for predicting the progression of pancreatic cystic lesions (PCLs) based on clinical and CT features, and to evaluate its predictive performance in internal/external testing cohorts.Methods:Baseline clinical and radiological data of 200 PCLs in 177 patients undergoing abdominal thin slice enhanced CT examination at Peking Union Medical College Hospital from July 2014 to December 2022 were retrospectively collected. PCLs were divided into progressive and non-progressive groups according to whether the signs indicated for surgery by the guidelines of the European study group on PCLs were present during three-year follow-up. 200 PCLs were randomly divided into training (150 PCLs) and internal testing cohorts (50 PCLs) at the ratio of 1∶3. 15 PCLs in 14 patients at Jinling Affiliated Hospital of Medical School of Nanjing University from October 2011 to May 2020 were enrolled as external testing cohort. The clinical and CT radiological features were recorded. Multiple feature selection methods and machine-learning models were implemented and combined to identify the optimal machine-learning model based on the 10-fold cross-validation method. Receiver operating characteristics (ROC) curve was drawn and area under curve (AUC) was calculated. The model with the highest AUC was determined as the optimal model. The optimal model's predictive performance was evaluated on testing cohort by calculating AUC, sensitivity, specificity and accuracy. Permutation importance was used to assess the importance of optimal model features. Calibration curves of the optimal model were established to evaluate the model's clinical applicability by Hosmer-Lemeshow test.Results:In training and internal testing cohorts, the progressive and non-progressive groups were significantly different on history of pancreatitis, lesions size, main pancreatic duct diameter and dilation, thick cyst wall, presence of septation and thick septation (all P value <0.05) In internal testing cohort, the two groups were significantly different on gender, lesion calcification and pancreatic atrophy (all P value <0.05). In external testing cohort, the two groups were significantly different on lesions size and pancreatic duct dilation (both P<0.05). The support vector machine (SVM) model based on five features selected by F test (lesion size, thick cyst wall, history of pancreatitis, main pancreatic duct diameter and dilation) achieved the highest AUC of 0.899 during cross-validation. SVM model for predicting the progression of PCLs demonstrated an AUC of 0.909, sensitivity of 82.4%, specificity of 72.7%, and accuracy of 76.0% in the internal testing cohort, and 0.944, 100%, 77.8%, and 86.7% in the external testing cohort. Calibration curved showed that the predicted probability by the model was comparable to the real progression of PCLs. Hosmer-Lemeshow goodness-of-fit test affirmed the model's consistency with actual PCLs progression in testing cohorts. Conclusions:The SVM model based on clinical and CT features can help doctors predict the PCLs progression within three-year follow-up, thus achieving efficient patient management and rational allocation of medical resource.

OBJECTIVE: To explore whether casticin (CAS) suppresses stemness in cancer stem-like cells (CSLCs) obtained from human cervical cancer (CCSLCs) and the underlying mechanism. METHODS: Spheres from HeLa and CaSki cells were used as CCSLCs. DNA methyltransferase 1 (DNMT1) activity and mRNA levels, self-renewal capability (Nanog and Sox2), and cancer stem cell markers (CD133 and CD44), were detected by a colorimetric DNMT activity/inhibition assay kit, quantitative real-time reverse transcription-polymerase chain reaction, sphere and colony formation assays, and immunoblot, respectively. Knockdown and overexpression of DNMT1 by transfection with shRNA and cDNA, respectively, were performed to explore the mechanism for action of CAS (0, 10, 30, and 100 nmol/L). RESULTS: DNMT1 activity was increased in CCSLCs compared with HeLa and CaSki cells (P<0.05). In addition, HeLa-derived CCSLCs transfected with DNMT1 shRNA showed reduced sphere and colony formation abilities, and lower CD133, CD44, Nanog and Sox2 protein expressions (P<0.05). Conversely, overexpression of DNMT1 in HeLa cells exhibited the oppositive effects. Furthermore, CAS significantly reduced DNMT1 activity and transcription levels as well as stemness in HeLa-derived CCSLCs (P<0.05). Interestingly, DNMT1 knockdown enhanced the inhibitory effect of CAS on stemness. As expected, DNMT1 overexpression reversed the inhibitory effect of CAS on stemness in HeLa cells. CONCLUSION CAS effectively inhibits stemness in CCSLCs through suppression of DNMT1 activation, suggesting that CAS acts as a promising preventive and therapeutic candidate in cervical cancer.
Female ; Humans ; Cell Line, Tumor ; HeLa Cells ; Neoplastic Stem Cells/metabolism* ; RNA, Small Interfering/metabolism* ; Uterine Cervical Neoplasms/metabolism*

Objective: To introduce a classification of alar retraction, and to discuss the therapeutic strategy of alar retraction with cartilage graft and the satisfaction evaluation of patients after operation. Methods: A retrospective analysis was performed on 88 patients with alar retraction admitted to the Department of Plastic and Aesthetic (Burn) Surgery, the Second Xiangya Hospital of Central South University from January 2015 to December 2020, including 20 males and 68 females, aged 20 to 48 years, with an average age of 28.98 years. All patients underwent external rhinoplasty according to a series of treatment plans determined by the classification of alar retraction based on nostril exposure. Visual Analogue Scale (VAS) and Rhinoplasty Outcomes Evaluation (ROE) were used to conduct satisfaction survey before and 12 months after operation. Wilcoxon signed-rank test was used to analyze patient satisfaction. Results: A total of 88 patients were included in this study. According to the classification of alar retraction based on nostril exposure, 45 cases were mild, 23 cases were moderate, and 20 cases were severe. There were 16 cases of unilateral and 72 cases of bilateral alar retraction. The patients were followed up for 12 to 18 months, with an average of 13.37 months. The VAS score and ROE score after each type of surgery were higher than those before surgery, with statistically significant (all P<0.05). Among them, the difference in VAS score (6.75±1.29) and in ROE satisfaction (67.70±7.38) of patients with severe alar retraction were the most significant improvement. Conclusion: The classification of alar retraction based on nostril exposure in the frontal view can comprehensively evaluate the severity of alar retraction, and makes the treatment algorithms systematic and comprehensive. The satisfaction of patients is relatively high.
Male ; Female ; Humans ; Adult ; Rhinoplasty ; Retrospective Studies ; Patient Satisfaction ; Treatment Outcome ; Esthetics ; Nose/surgery*

Post-stroke depression (PSD) is a serious and common complication of stroke, which seriously affects the rehabilitation of stroke patients. To date, the pathogenesis of PSD is unclear and effective treatments remain unavailable. Here, we established a mouse model of PSD through photothrombosis-induced focal ischemia. By using a combination of brain imaging, transcriptome sequencing, and bioinformatics analysis, we found that the hippocampus of PSD mice had a significantly lower metabolic level than other brain regions. RNA sequencing revealed a significant reduction of miR34b-3p, which was expressed in hippocampal neurons and inhibited the translation of eukaryotic translation initiation factor 4E (eIF4E). Furthermore, silencing eIF4E inactivated microglia, inhibited neuroinflammation, and abolished the depression-like behaviors in PSD mice. Together, our data demonstrated that insufficient miR34b-3p after stroke cannot inhibit eIF4E translation, which causes PSD by the activation of microglia in the hippocampus. Therefore, miR34b-3p and eIF4E may serve as potential therapeutic targets for the treatment of PSD.
Animals ; Mice ; Depression ; Eukaryotic Initiation Factor-4E/metabolism* ; MicroRNAs/metabolism* ; Neurons/metabolism* ; Stroke/metabolism*

Objective: To explore the utility of stool-based DNA test of methylated SDC2 (mSDC2) for colorectal cancer (CRC) screening in residents of Shipai Town, Dongguan City. Methods: This was a cross-sectional study. Using a cluster sampling method, residents of 18 villages in Shipai Town, Dongguan City were screened for CRC from May 2021 to February 2022. In this study, mSDC2 testing was employed as a preliminary screening method. Colonoscopy examination was recommended for individuals identified as high-risk based on the positive mSDC2 tests. The final screening results, including the rate of positive mSDC2 tests, the rate of colonoscopy compliance, the rate of lesions detection, and the cost-effectiveness of screening, were analyzed to explore the benefits of this screening strategy. Results: A total of 10 708 residents were enrolled and completed mSDC2 testing, giving a participation rate of 54.99% (10 708/19 474) and a pass rate of 97.87% (10 708/10 941). These individuals included 4 713 men (44.01%) and 5 995 women (55.99%) with a mean age of (54.52±9.64) years. The participants were allocated to four age groups (40-49, 50-59, 60-69, and 70-74 years), comprising 35.21%(3770/10 708), 36.25% (3882/10 708), 18.84% (2017/10 708), and 9.70% (1039/10 708) of all participants, respectively. mSDC2 testing was positive in 821/10 708 (7.67%) participants, 521 of whom underwent colonoscopy, resulting in a compliance rate of 63.46% (521/821). After eliminating of 8 individuals without pathology results, data from 513 individuals were finally analyzed. Colonoscopy detection rate differed significantly between age groups (χ²=23.155, P<0.001),ranging from a low of 60.74% in the 40-49 year age group to a high of 86.11% in the 70-74 year age group. Colonoscopies resulted in the diagnosis of 25 (4.87%) CRCs, 192 (37.43%) advanced adenomas, 67 (13.06%) early adenomas, 15 (2.92%) serrated polyps, and 86 (16.76%) non- adenomatous polyps. The 25 CRCs were Stage 0 in 14 (56.0%) individuals, stage I in 4 (16.0%), and Stage II in 7(28.0%). Thus, 18 of the detected CRCs were at an early stage. The early detection rate of CRCs and advanced adenomas was 96.77% (210/217). The rate of mSDC2 testing for all intestinal lesions was 75.05% (385/513). In particular, the financial benefit of this screening was 32.64 million yuan, and the benefit-cost ratio was 6.0. Conclusion: Screening for CRCs using stool-based mSDC2 testing combined with colonoscopy has a high lesion detection rate and a high cost-effectiveness ratio. This is a CRC screening strategy that deserves to be promoted in China.
Male ; Humans ; Female ; Adult ; Middle Aged ; Cross-Sectional Studies ; Early Detection of Cancer/methods* ; Colorectal Neoplasms/pathology* ; Colonoscopy/methods* ; Mass Screening/methods* ; Adenoma/diagnosis* ; DNA ; Syndecan-2/genetics*

The ethanol precipitation process of Nauclea officinalis extract was optimized based on the concept of quality by design(QbD). Single factor tests were carried out to determine the levels of test factors. The ethanol volume fraction, pre-ethanol precipitation drug concentration, and ethanol precipitation time were taken as critical process parameters(CPPs). With the comprehensive scores of strictosamide transfer rate and solid removal rate as the critical quality attributes(CQAs), Box-Behnken design was employed to establish the mathematical models and space design between CPPs and CQAs, and the obtained optimal operating space was validated. The optimal operating space included ethanol volume fraction of 65%-70%, pre-ethanol precipitation drug concentration of 22-27 mg·mL~(-1), and ethanol precipitation time of 12 h. Based on the concept of QbD, this study adopted the design space to optimize the ethanol precipitation process of N. officinalis extract, which provided a reliable theoretical basis for the quality control in the production process of N. officinalis preparations. Moroever, this study provided a reference value for guiding the research and industrial production of traditional Chinese medicines.
Drugs, Chinese Herbal ; Ethanol ; Medicine, Chinese Traditional ; Quality Control ; Models, Theoretical