Diabetic retinopathy (DR) is one of the most prevalent and vision-threatening microvascular complications of diabetes mellitus, yet its pathogenesis extends far beyond vascular injury alone. As the retina is among the most energy-demanding tissues in the body, its neurons, glial cells, pigment epithelial cells, pericytes, and endothelial cells are highly dependent on mitochondrial oxidative phosphorylation to maintain visual signal transduction, ionic homeostasis, and neurovascular integrity. This review summarizes current evidence indicating that mitochondrial dysfunction is not merely a downstream consequence of chronic hyperglycemia, but a central pathogenic hub that initiates, amplifies, and perpetuates retinal neurovascular degeneration in DR. Persistent hyperglycemia activates multiple abnormal metabolic pathways, including the polyol pathway, hexosamine pathway, protein kinase C signaling, advanced glycation end-product formation, and angiotensin II-related responses. Although these pathways differ mechanistically, they converge on excessive reactive oxygen species (ROS) generation, antioxidant depletion, and mitochondrial injury. Under diabetic stress, electron transport chain overload promotes mitochondrial ROS leakage, damages mitochondrial DNA, disrupts membrane potential, and impairs the transcription of key respiratory chain components. In parallel, mitochondrial quality-control systems become progressively compromised. The balance between fusion and fission shifts toward pathological fragmentation through reduced MFN1/2 and OPA1 activity and enhanced DRP1-mediated fission. Mitochondrial biogenesis is suppressed through inhibition of the AMPK/SIRT1/PGC-1α/NRF1/TFAM axis, while mitophagy changes from an early compensatory response to a later state of autophagic flux blockade and accumulation of dysfunctional mitochondria. Importantly, damaged mitochondria serve as signal amplifiers linking metabolic stress to inflammation and programmed cell death. Mitochondrial ROS, oxidized mitochondrial DNA, calcium overload, cardiolipin exposure, and membrane permeabilization activate interrelated death pathways, including intrinsic apoptosis, ferroptosis, and pyroptosis. Cytochrome C and apoptosis-inducing factor promote caspase-dependent and caspase-independent apoptosis; iron dyshomeostasis, glutathione depletion, GPX4 dysfunction, and lipid peroxidation drive ferroptosis; and mitochondrial danger signals activate the NLRP3 inflammasome and gasdermin-dependent pyroptosis. These pathways jointly damage the retinal neurovascular unit and contribute to pericyte loss, endothelial barrier breakdown, Müller cell dysfunction, retinal ganglion cell apoptosis, retinal pigment epithelial injury, and photoreceptor degeneration. This review also emphasizes the role of epigenetic regulation in stabilizing mitochondrial pathology. DNA methylation, histone modifications, and non-coding RNAs interact to silence mitochondrial protective genes, alter antioxidant responses, and maintain the “metabolic memory” of DR even after glycemic normalization. Therefore, mitochondrial dysfunction should be understood as a dynamic, multidimensional network rather than a single pathological event. Current clinical approaches, such as laser photocoagulation, intravitreal anti-VEGF therapy, and vitrectomy, mainly target advanced vascular lesions and are limited by invasiveness, incomplete responsiveness, recurrence, and potential adverse effects. Therapeutically, strategies targeting mitochondrial ROS, restoring mitochondrial dynamics, enhancing biogenesis, regulating mitophagy, inhibiting inflammasome activation, correcting epigenetic abnormalities, and improving targeted delivery systems show promising potential. However, major translational barriers remain, including retinal cell heterogeneity, stage-specific mitochondrial responses, insufficient organelle-specific drug delivery, and long-term safety concerns. A deeper understanding of mitochondrial regulatory networks may support earlier, more precise, and multi-target interventions for preventing or slowing DR progression.

Hematologic malignancies,such as lymphoma,myeloma,and myeloid neoplasms,can occur in extramedullary tissues.Traditional histopathological morphology and immunohistochemical staining have lim-itations,including time-consuming specimen processing,prolonged reporting cycles,and relatively low sensi-tivity in cases of limited cell numbers.Flow cytometry offers significant advantages in detecting tissue sam-ples,such as rapid processing,shorter reporting cycles,and high accuracy and sensitivity,making it an effective complement to histopathological and immunohistochemical methods.However,the application of flow cytome-try in tissue sample detection currently lacks standardized protocols for sample collection and preservation,single-cell suspension preparation,antibody panel design for limited samples,data analysis,and result repor-ting.To promote the standardized application of flow cytometry in detecting hematologic tumor cells in tissue samples,the Cell Analysis Professional Committee of the Chinese Society of Biotechnology organized experts to develop the Chinese Expert Consensus on Flow Cytometry for Detecting Hematologic Tumor Cells in Tis-sue Samples(hereinafter referred to as the Consensus).This Consensus elaborates on the technical aspects of flow cytometry for tissue sample detection,covering sample processing,antibody panel design,data analysis,reporting content,and quality management.It particularly emphasizes recommended antibody panels and data analysis methods for flow cytometry when tissue sample cell counts are low.This article aims to interpret the key points of the Consensus to facilitate its better application in clinical practice.

Objective To propose a multiple regression-variational auto-encoders(MR-VAE)model to realize precise and non-invasive prediction of intra-abdominal pressure(IAP)in critically ill patients.Methods At first,a dataset was constructed by retrospectively analysing baseline characteristics and clinical indicators of 100 critically ill patients admitted to the Intensive Care Unit of Daping Hospital of Army Medical University between 30 August 2019 and 30 March 2021.Then,a MR-VAE prediction model was developed by integrating a feedforward neural network for supervised regression onto a variational autoencoder(VAE)framework and incorporating multiple regression strategies to mitigate feature interference.Finally,the MR-VAE model had its performance evaluated by its comparison with five classical models including support vector machines(SVM),convolutional neural networks(CNN),Scikit-learn integrated model(SIM),multi-layer perceptron(MLP)and K-nearest neighbors(KNN),and its prediction accuracy verified by testing the data of 10 randomly selected patients.Results The MR-VAE model behaved the best when compared with the five classical models,with a mean squared error(MSE)of 0.207,a root mean square error(RMSE)of 0.454,a mean absolute error(MAE)of 0.361,a median absolute deviation(MAD)of 0.243,an explained variance score(EVS)of 0.814 and a R2of 0.823,which also outperformed the five models in fitting performance,convergence and final loss.In random sample testing,the MR-VAE model exhibited high consistency between predicted and actual values.Conclusion The MR-VAE model proposed can accurately predict IAP,which has great potential in reducing the repeated measurements of IAP in critically ill patients and providing new ideas for the early diagnosis and treatment of IAH.

Objective Prepubertal mice are administered subcutaneously with letrozole sustained-release pellets behind the neck and treated with a high-fat diet to establish a mouse model of polycystic ovary syndrome(PCOS).The liver transcriptomes of the model mice are compared with those of the placebo control mice to investigate the underlying mechanisms of liver involvement in the pathogenesis of PCOS.Methods A customized 2 mg dose of letrozole sustained-release pellets with a 40-day release period was used.The control placebo and letrozole pellets were implanted subcutaneously in the dorsal cervical region of 3-4-week-old C57BL/6J mice(8 mice per group)to establish the control group and letrozole-induced PCOS model group.Both groups were treated with a high-fat diet starting the day after administration.The modeling period lasted for 5 weeks,during which body weight and 24-hour food intake were monitored in each group every week.When samples were collected,liver weight was recorded.Pathological changes in ovarian and hepatic tissues were examined by hematoxylin-eosin(HE)staining,while hepatic lipid deposition was observed by Oil Red O staining.The extent of macrophage infiltration in the liver was evaluated via F4/80 immunohistochemical staining,and hepatic fibrosis levels were observed by Masson's trichrome staining.Transcriptomic sequencing was performed to analyze differentially expressed genes(DEGs)in liver tissues between the control and model groups,followed by enrichment analysis of significant DEGs.Quantitative real-time fluorescent quantitative PCR(qPCR)was subsequently used to validate the expression of significant DEGs in liver tissues of both groups.Results Compared with the control group,the model group which received subcutaneous letrozole sustained-release pellets combined with a high-fat diet exhibited significantly increased body weight(P＜0.001),prominent polycystic ovarian morphology,and significantly decreased liver-to-body weight ratio(P＜0.05).However,no significant changes were observed in absolute liver weight(P＞0.05),hepatic histomorphology,or lipid deposition.Transcriptome sequencing identified 119 upregulated and 217 downregulated DEGs in the liver tissues of letrozole-treated mice,which were predominantly enriched in pathways related to cholesterol and steroid biosynthesis,steroid hormone metabolism,and inflammatory responses.qPCR validation demonstrated that mRNA expression of HSD3B2 and HMGCR was significantly upregulated in liver(P＜0.01),while mRNA expression of IL4,CCL2 and COL1A1 was downregulated(P＜0.05)in the model group compared with the control group.However,Masson's trichrome staining and F4/80 immunohistochemical analysis showed no significant changes in hepatic fibrosis or macrophage infiltration.Conclusion Subcutaneous administration of letrozole sustained-release pellets combined with a high-fat diet successfully establishes a mouse model of PCOS.The model mice exhibited significant changes in hepatic gene expression.Liver may contribute to PCOS pathogenesis through regulating cholesterol and steroid metabolism.

Objective To propose a multiple regression-variational auto-encoders(MR-VAE)model to realize precise and non-invasive prediction of intra-abdominal pressure(IAP)in critically ill patients.Methods At first,a dataset was constructed by retrospectively analysing baseline characteristics and clinical indicators of 100 critically ill patients admitted to the Intensive Care Unit of Daping Hospital of Army Medical University between 30 August 2019 and 30 March 2021.Then,a MR-VAE prediction model was developed by integrating a feedforward neural network for supervised regression onto a variational autoencoder(VAE)framework and incorporating multiple regression strategies to mitigate feature interference.Finally,the MR-VAE model had its performance evaluated by its comparison with five classical models including support vector machines(SVM),convolutional neural networks(CNN),Scikit-learn integrated model(SIM),multi-layer perceptron(MLP)and K-nearest neighbors(KNN),and its prediction accuracy verified by testing the data of 10 randomly selected patients.Results The MR-VAE model behaved the best when compared with the five classical models,with a mean squared error(MSE)of 0.207,a root mean square error(RMSE)of 0.454,a mean absolute error(MAE)of 0.361,a median absolute deviation(MAD)of 0.243,an explained variance score(EVS)of 0.814 and a R2of 0.823,which also outperformed the five models in fitting performance,convergence and final loss.In random sample testing,the MR-VAE model exhibited high consistency between predicted and actual values.Conclusion The MR-VAE model proposed can accurately predict IAP,which has great potential in reducing the repeated measurements of IAP in critically ill patients and providing new ideas for the early diagnosis and treatment of IAH.

Objective Prepubertal mice are administered subcutaneously with letrozole sustained-release pellets behind the neck and treated with a high-fat diet to establish a mouse model of polycystic ovary syndrome(PCOS).The liver transcriptomes of the model mice are compared with those of the placebo control mice to investigate the underlying mechanisms of liver involvement in the pathogenesis of PCOS.Methods A customized 2 mg dose of letrozole sustained-release pellets with a 40-day release period was used.The control placebo and letrozole pellets were implanted subcutaneously in the dorsal cervical region of 3-4-week-old C57BL/6J mice(8 mice per group)to establish the control group and letrozole-induced PCOS model group.Both groups were treated with a high-fat diet starting the day after administration.The modeling period lasted for 5 weeks,during which body weight and 24-hour food intake were monitored in each group every week.When samples were collected,liver weight was recorded.Pathological changes in ovarian and hepatic tissues were examined by hematoxylin-eosin(HE)staining,while hepatic lipid deposition was observed by Oil Red O staining.The extent of macrophage infiltration in the liver was evaluated via F4/80 immunohistochemical staining,and hepatic fibrosis levels were observed by Masson's trichrome staining.Transcriptomic sequencing was performed to analyze differentially expressed genes(DEGs)in liver tissues between the control and model groups,followed by enrichment analysis of significant DEGs.Quantitative real-time fluorescent quantitative PCR(qPCR)was subsequently used to validate the expression of significant DEGs in liver tissues of both groups.Results Compared with the control group,the model group which received subcutaneous letrozole sustained-release pellets combined with a high-fat diet exhibited significantly increased body weight(P＜0.001),prominent polycystic ovarian morphology,and significantly decreased liver-to-body weight ratio(P＜0.05).However,no significant changes were observed in absolute liver weight(P＞0.05),hepatic histomorphology,or lipid deposition.Transcriptome sequencing identified 119 upregulated and 217 downregulated DEGs in the liver tissues of letrozole-treated mice,which were predominantly enriched in pathways related to cholesterol and steroid biosynthesis,steroid hormone metabolism,and inflammatory responses.qPCR validation demonstrated that mRNA expression of HSD3B2 and HMGCR was significantly upregulated in liver(P＜0.01),while mRNA expression of IL4,CCL2 and COL1A1 was downregulated(P＜0.05)in the model group compared with the control group.However,Masson's trichrome staining and F4/80 immunohistochemical analysis showed no significant changes in hepatic fibrosis or macrophage infiltration.Conclusion Subcutaneous administration of letrozole sustained-release pellets combined with a high-fat diet successfully establishes a mouse model of PCOS.The model mice exhibited significant changes in hepatic gene expression.Liver may contribute to PCOS pathogenesis through regulating cholesterol and steroid metabolism.

Objective To investigate whether successful percutaneous coronary intervention(PCI)could improve symptoms and quality of life(QOL)in left main disease and/or 3-vessel disease patients with diabetes.Methods Patients with left main disease and/or 3-vessel disease who underwent PCI in the First Affiliated Hospital of Air Force Medical University from April 2018 to May 2021 were consecutively enrolled and subdivided into 2 groups:diabetes and no diabetes.Detailed baseline characteristics,symptoms,including dyspnea and angina,assessed with the Rose dyspnea scale(RDS),Seattle angina questionnaire(SAQ),the European quality of life-5 dimensions(EQ-5D)and 12-item short-form health survey(SF-12)questionnaire respectively,procedural details,and 1 month and 1 year follow-up data were collected.Results Among 440 left main disease and/or 3-vessel disease patients,disease was present in 176(40.00％),who had more hypertension,peripheral artery disease,and LCX lesion(all P＜0.05).The incidence of major adverse cardiovascular events(MACE)and all-cause mortality were similar between the two groups(both P＞0.05)at 1 month follow-up,while all-cause mortality in diabetes patients was significantly higher than those without diabetes at 1 year follow-up(P=0.013).Low left ventricular ejection fraction was an independent risk factor for MACE and all-cause mortality at 1 month and 1 year follow-up after successful revascularization(all P＜0.05).Most importantly,symptoms,including dyspnea and angina,and QOL were markedly improved regardless of diabetes both at 1 month and 1 year follow-up(all P＜0.05).Diabetes patients showed improved dyspnea and QOL at similar degree to the non-diabetes patients(all P＞0.05)and a more significantly relieved angina(P=0.013).Additionally,the number of chronic total occlusion(CTO)per patient was identified as an independent risk factor of dyspnea(OR 0.723,95％CI 0.525～0.997,P=0.048)and angina relief(OR 0.686,95％CI 0.473～0.995,P=0.047),and the contrast volume(OR 0.995,95％CI 0.992～0.999,P=0.008)as an independent risk factor of QOL improvement in diabetic patients.Conclusions Successful PCI is beneficial for relieving symptoms and improving quality of life in patients with diabetes who have left main disease and/or 3-vessel disease.

Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.

Neonatal sepsis is a global health problem that seriously affects the body health and life safety of newborns. It has a higher incidence in preterm infants,especially for early-onset sepsis (EOS) within 72 hours of birth. The diagnosis of neonatal EOS requires a series of examinations,and early and accurate diagnosis can improve clinical outcomes and reduce antibiotic overuse in a timely manner. At present,the commonly used biomarkers and traditional blood culture methods for EOS diagnosis have certain shortcomings,so it is urgent to find new molecular diagnostic methods. This article summarizes and compares the early and novel diagnostic methods of neonatal EOS,in order to provide a reference for clinical practice.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.