Polypoidal choroidal vasculopathy(PCV)is one of the important subtypes of neovascular age-related macular degeneration(nARMD), which causes severe vision loss. It is necessary to distinguish PCV from other nARMD subtypes to guide the clinical treatment plans and predict disease outcomes. In recent years, artificial intelligence(AI)has been widely used in the diagnosis and research of ophthalmic diseases. By utilizing machine learning or deep learning combined with examination images in disease classification, lesion segmentation, and quantitative assessment, etc. This article reviews the recent applications of AI in the differential diagnosis of PCV through various examination images, the segmentation and quantification of biomarkers, as well as the prediction of genotype, response to anti-vascular endothelial growth factor(VEGF)therapy, and the short-term risk of vitreous hemorrhage. It summarizes the difficulties and challenges in clinical practice of AI and looks forward to the advantages and development trends of AI in PCV applications in the future. The article aims to provide more information for further research and application, thereby improving the diagnostic rate of PCV, optimizing treatment plans, and improving patients' visual prognosis.

Polypoidal choroidal vasculopathy(PCV)is one of the important subtypes of neovascular age-related macular degeneration(nARMD), which causes severe vision loss. It is necessary to distinguish PCV from other nARMD subtypes to guide the clinical treatment plans and predict disease outcomes. In recent years, artificial intelligence(AI)has been widely used in the diagnosis and research of ophthalmic diseases. By utilizing machine learning or deep learning combined with examination images in disease classification, lesion segmentation, and quantitative assessment, etc. This article reviews the recent applications of AI in the differential diagnosis of PCV through various examination images, the segmentation and quantification of biomarkers, as well as the prediction of genotype, response to anti-vascular endothelial growth factor(VEGF)therapy, and the short-term risk of vitreous hemorrhage. It summarizes the difficulties and challenges in clinical practice of AI and looks forward to the advantages and development trends of AI in PCV applications in the future. The article aims to provide more information for further research and application, thereby improving the diagnostic rate of PCV, optimizing treatment plans, and improving patients' visual prognosis.

The Mofeng Ointment Formulation （MOF， 摩风膏方） is recorded in the Dunhuang manuscript Unnamed Treatise on the Pulse （《亡名氏脉经》） and stands as a representative ancient external therapeutic formula in traditional Chinese medicine （TCM）. Known for dispelling wind， activating blood circulation， warming the meridians， and relieving pain， it is particularly effective in treating rheumatic arthralgia. Through literature research， this paper systematically reviews the composition， preparation techniques， and clinical application characteristics of MOF. In recent years， advancements in modern pharmaceutical technology have led to the development of various innovative ointment-based formulations derived from the traditional recipe， such as Dunhuang Xiaoding Ointment （敦煌消定膏）， Dunhuang Xiaozhong and Zhentong Ointment （Patch） （敦煌消肿镇痛膏/贴）， Xiaoding Ointment （消定膏） gel patch， and Xiaoding Ointment （消定膏） cataplasm. These innovations explore pathways for transforming classical prescriptions into modern applications， providing a theoretical basis for the external TCM treatment of pain-related and orthopedic conditions.

Objective To analyze the nonlinear relationship between hypothermic machine perfusion (HMP) parameters and delayed graft function (DGF) and optimize the construction of a predictive model for DGF. Methods The data of 923 recipients who underwent kidney transplantation from deceased donors were retrospectively analyzed. According to the occurrence of DGF, the recipients were divided into DGF group (n=823) and non-DGF group (n=100). Donor data, HMP parameters and recipient data were analyzed for both groups. The nonlinear relationship between HMP parameters and the occurrence of DGF was explored based on restricted cubic splines (RCS). Over-sampling, under-sampling and balanced sampling were used to address the imbalance in the proportion of DGF to construct logistic regression predictive models. The area under the curve (AUC) of each model was compared in the validation set, and a nomogram model was constructed. Results Donor BMI, cold ischemia time of the donor kidney, and HMP parameters (initial and final pressures, resistance, and perfusion time) were significantly different between the DGF and non-DGF groups (all P<0.05). The RCS analysis revealed a threshold-like nonlinear relationship between HMP parameters and the risk of DGF. Among the models constructed using different sampling methods, the balanced sampling model had the highest AUC. Using this model, a nomogram was constructed to stratify recipients based on risk scores. Recipients in the high-risk group had higher serum creatinine levels at 1, 6, and 12 months after kidney transplantation compared to those in the low-risk group (all P<0.05). Conclusions There is a nonlinear relationship between HMP parameters and the risk of DGF, and the threshold is helpful for organ quality assessment and monitoring of graft function after transplantation. The predictive model for DGF constructed on the base of balanced sampling algorithms helps perioperative decision-making and postoperative graft function monitoring of kidney transplantation.

Allergic asthma is a complex，polygenic disease characterized by chronic inflammation and airway hyperresponsiveness. Fungus and dust mites are the most important inhaled allergens of allergic asthma，and often exist in the form of mixed allergens. In recent years，genetic studies have shown that several genes are associated with allergic asthma attacks. This article reviews the studies on the genes related to allergic asthma caused by dust mites and fungus，such as a disintegrin and metalloproteinase 33（ADAM33），interleukin-4（IL-4），glycoprotein A repetitions predominant（GARP），toll like receptor 3（TLR3），mannose-binding lectin 2（MBL2），chemokine（C-C motif）ligand 17（CCL17）and other genes .

In recent years， the research data on the combination model of insomnia of liver depression and qi stagnation syndrome in traditional Chinese medicine （TCM） were sorted out and summarized in terms of the selection of experimental animals， modelling methods， and model evaluation， with a view to providing references for the standardized preparation of the experimental model of insomnia of liver depression and qi stagnation syndrome and the study of the intervention mechanism. As for the selection of experimental animals， rats and mice are commonly used for the study of sleep patterns in the insomnia model of liver depression and qi stagnation syndrome because their sleep patterns are similar to those of human beings； zebrafish is suitable for the study of sleep patterns in early development because of its high genetic homology； and rhesus macaques， common marmosets， and crab-eating monkeys are used for the study of highly complex sleep disorders because their physiological and behavioural characteristics are closer to those of human beings. In terms of modelling methods， electrical stimulation， chronic restraint， chronic emotional stress and impact psychological stress each have their own characteristics and application scenarios， while chronic tail-clamping stimulation combined with intraperitoneal injection of p-chlorophenylalanine （PCPA） combines physical and chemical stimuli， in order to simulate the complex mechanism of insomnia in human beings， and to more comprehensively simulate the pathology of insomnia with liver depression and qi stagnation syndrome. In terms of evaluation indexes， electroencephalography （EEG） and electromyography （EMG） monitoring and barbiturate synergistic sleep test are the most commonly used and scientific methods for evaluating insomnia animal models with liver depression and qi stagnation syndrome， which can provide intuitive and continuous sleep state monitoring； barbiturate synergistic sleep test can reflect the sensitivity and responsiveness of the model animals to the sleep-regulating medications； and the introduction of the method of using formulas to measure syndromes for the evaluating the model can combine the treatment and diagnostic principles of TCM with modern scientific research.

Objective To analyze the values of renal resistance index(RRI),cystatin C(CysC),blood β2-microglobulin(β2-MG)and urinary N-acetyl-β-glucosamine glycosidase(NAG)in early prediction of contrast-induced acute kidney injury(CI-AKI).Methods A retrospective cohort analysis on 207 postoperative patients after intervention therapy was conducted.The patients were divided into AKI group(18 patients)and non-AKI group(189 patients)based on whether CI-AKI occurred.General and clinical data were collected and compared.Accord-ing to the time of diagnosis of AKI(D0 on the day of surgery or D1 on the first day after surgery),the AKI group was divided into AKI(D0)group and AKI(D1)group.Indicators RRI,CysC,and blood β2-MG,serum creatinine(sCr),and urinary NAG were compared between the two groups.The risk factors of CI-AKI were explored using logistic regression and linear regression.Results In the AKI group,males,preoperative sCr,acute physiological and chronic health(APACHⅡ)score and sequential organ failure(SOFA)score,surgical duratrion,sCr,CysC,blood β2-MG,urinary NAG on the day of surgery and the first day after surgery,and RRI were higher than those in the non-AKI group;Higher APACHEⅡ and SOFA scores and higher CysC level on D1 were independent risk factors for the occurrence of CI-AKI(P<0.05).Levels of CysC and urinay NAG on D0 were higher in the AKI(D0)group than in the AKI(D1)group(P<0.05).RRI,urinary NAG and blood β2-MG were not independent risk factors for CI-AKI.Conclusions CysC and urinary NAG are powerful predictors for the prediction of CI-AKI,and RRI and blood β2-MG cannot predict the occurrence of CI-AKI early.

Objective To establish an artificial intelligence (AI)-assisted platform for detection of parasite eggs, and to evaluate its detection efficiency and accuracy, so as to provide technical supports for elimination of parasitic diseases. Methods A total of 1 003 slides of Enterobius vermicularis, horkworm, Trichuris trichiura, Clonorchis sinensis, Taenia, Ascaris lumbricoides, Schistosoma japonicum, Paragonimus westermani and Fasciolopsis buski eggs were collected, and converted into digital images with an automatated scanning microscope to create a dataset. Based on the Object Detection platform on the Baidu Easy DL model, an AI-assisted platform for detection of parasite eggs was created through procedures of uploading, labeling, training, evaluation and optimization. Then, 70% of the datasets were randomly selected for model training, and the precision, recall and average accuracy were calculated to evaluate the effectiveness of platform for recognition of parasite eggs. In addition, the platform was deployed on the computer and smart phone terminals for use. Results An AI-assisted platform for detection of parasite eggs was successfully created. If the platform was deployed using the public cloud application programming interface (API), the average accuracy, precision and recall of the platform were 93.42%, 92.55% and 89.32% for recognition of parasite eggs. If the platform was deployed using the offline software development kit (SDK), the average accuracy, precision and recall of the platform were 92.97%, 94.78% and 87.63% for recognition of parasite eggs. In addition, the precision of the platform was 97.00% and 96.23% for identification of Taenia and C. sinensis eggs, respectively. Conclusions The AI-assisted platform for detection of parasite eggs has been successfully created, which is high in the accuracy for recognition of parasite eggs and convenient in use. This platform may provide a powerful technical support for parasitic disease diagnosis.

Objective:To analyze the incidence and progression of overactive bladder(OAB)symp-toms following radical prostatectomy for prostate cancer patients and to identify related risk factors.Methods:A retrospective study was conducted on 263 local stage prostate cancer patients who underwent radical prostatectomy at Peking University Third Hospital from January 2013 to May 2017.Clinical base-line information,comprehensive imaging features,perioperative parameters,preoperative urinary control status,pathological diagnosis,and the incidence of OAB within one year postoperatively were collected and analyzed.In the imaging features,two parameters were defined:Bladder wall thickness(BWT)and bladder mucosal smoothness(BMS),which were used to predict the occurrence of OAB.Patients were evaluated based on their clinical baseline characteristics,including age,body mass index(BMI),co-morbidities,and prostate-specific antigen(PSA)levels.The imaging characteristics were assessed using preoperative MRI,focusing on BWT and BMS.Perioperative parameters included operative time,blood loss,and length of hospital stay.The OAB symptoms were assessed using the overactive bladder symptom score(OABSS)and the international prostate symptom score(IPSS).These scores were correlated with the postoperative incidence of OAB.Results:Among the 263 patients who underwent radical prostatecto-my,52(19.8％)exhibited OAB within one year postoperatively.Of the 40 patients with preoperative OAB symptoms,17(42.5％)showed remission postoperatively,while 23(57.5％)had persistent symptoms.Additionally,29 patients developed new-onset OAB,accounting for 55.77％of all postopera-tive OAB cases.Univariate analysis indicated that BWT,BMS,OABSS,and IPSS score were all associ-ated with the occurrence of postoperative OAB.Further multivariate analysis identified BMS as an inde-pendent risk factor for long-term OAB(P＜0.001).Conclusion:Long-term postoperative overactive bladder is a common complication following radical prostatectomy.The findings suggest that preoperative MRI measurements of bladder wall thickness and bladder mucosal smoothness during bladder filling phase can predict the risk of OAB occurrence postoperatively.Identifying these risk factors preoperatively can help in counseling patients about potential complications and in developing strategies to mitigate the risk of developing OAB after surgery.Early detection and management of these parameters might improve the quality of life for patients undergoing radical prostatectomy.

With advancements in radiology,endoscopic techniques,surgical treatments,cell biology and molecular biology,the un-derstanding of temporomandibular disorders(TMD)has increased.The temporomandibular joint(TMJ)is a complex structure comprising both soft and hard tissues.Within the TMJ,the temporomandibular disc is a soft tissue structure that connects the mandible to the skull,providing cushioning and stability during joint movement.Different imaging techniques have their own advantages and limi-tations in the diagnosis and treatment of TMD.Therefore,using image registration technology to assess the condition and position of the articular disc provides new research perspectives for evaluating TMD,which may contribute to the diagnosis and treatment.This article reviews the latest advancements in TMJ imaging,explores the applications of various image registration techniques,particularly in the context of TMD diagnosis and treatment,and discusses future prospects.Combining the research results of some scholars at home and a-broad with the author’s clinical experience,the article aims to provide valuable insights for clinicians.