Aural vertigo frequently encountered in the otolaryngology department of traditional Chinese medicine （TCM） mainly involves peripheral vestibular diseases of Western medicine， such as Meniere's disease， benign paroxysmal positional vertigo， vestibular neuritis， and vestibular migraine， being a hot research topic in both TCM and Western medicine. Western medical therapies alone have unsatisfactory effects on recurrent aural vertigo， aural vertigo affecting the quality of life， aural vertigo not relieved after surgery， aural vertigo with complex causes， and children's aural vertigo. The literature records and clinical practice have proven that TCM demonstrates unique advantages in the treatment of aural vertigo. The China Association of Chinese medicine sponsored the "17th youth salon on the diseases responding specifically to TCM： Aural vertigo" and invited vertigo experts of TCM and Western medicine to discuss the difficulties and advantages of TCM diagnosis and treatment of aural vertigo. The experts deeply discussed the achievements and contributions of TCM and Western medicine in the diagnosis and treatment of aural vertigo， the control and mitigation of the symptoms， and the solutions to disease recurrence. The discussion clarified the positioning and advantages of TCM treatment and provided guidance for clinical and basic research on aural vertigo.

BACKGROUND:Hypoxia is strongly associated with the development and progression of osteoarthritic chondrocyte injury,but the specific targets and regulatory mechanisms are unclear. OBJECTIVE:A machine learning approach was used to identify KDEL(Lys-Asp-Glu-Leu)receptor 3(KDELR3)as a characteristic gene for osteoarthritis hypoxia and immune infiltration analysis,to provide new ideas and methods for the treatment of osteoarthritis. METHODS:The osteoarthritis-related datasets were downloaded from the GEO database and the GSEA website to obtain hypoxia-related genes.The osteoarthritis datasets were batch-corrected and immune infiltration analyzed using R language,and osteoarthritis hypoxia genes were extracted for differential analysis.Differentially expressed genes were analyzed for GO function and KEGG signaling pathway.Weighted correlation network analysis(WGCNA)and machine learning were also used to screen osteoarthritis hypoxia signature genes,and in vitro cellular experiments were performed to validate expression and correlate immune infiltration analysis using the datasets and qPCR. RESULTS AND CONCLUSION:(1)8492 osteoarthritis genes were obtained by batch correction and principal component analysis,mainly strongly associated with immune cells such as Macrophages M2 and Mast cells resting;200 hypoxia genes were also obtained,resulting in 41 osteoarthritis hypoxia differentially expressed genes.(2)GO analysis involved mainly biological processes such as response to nutrient levels and glucocorticoids;cellular components such as lysosomal lumen and Golgi lumen;and molecular functions such as 14-3-3 protein binding and DNA-binding transcriptional activator activity.(3)KEGG analysis of osteoarthritis hypoxia differentially expressed genes was associated with signaling pathways such as PI3K-Akt,FoxO,and microRNAs in cancer.(4)The characteristic gene KDELR3 was obtained after using WGCNA analysis and machine learning screening.(5)The gene expression of KDELR3 was found to be higher in the test group than in the control group in the synovium(P=0.014)but lower in the meniscus(P=0.024)after validation by gene microarray.(6)In vitro chondrocyte assay showed that the expression of KDELR3 was higher in cartilage than in the control group(P=0.005),while KDELR3 was closely associated with Macrophages M0(P=0.014)and T cells follicular helper(P=0.014).Using a machine learning approach,we confirmed that KDELR3 can be used as a hypoxic signature gene for osteoarthritis and may intervene in osteoarthritis pathogenesis by improving hypoxia,expecting to provide a new direction for better treatment of osteoarthritis.

BACKGROUND:Ferroptosis is strongly associated with the occurrence and progression of osteoarthritis,but the specific characteristic genes and regulatory mechanisms are not known. OBJECTIVE:To identify osteoarthritis ferroptosis signature genes and immune infiltration analysis using the WGCNA and various machine learning methods. METHODS:The osteoarthritis dataset was downloaded from the GEO database and ferroptosis-related genes were obtained from the FerrDb website.R language was used to batch correct the osteoarthritis dataset,extract osteoarthritis ferroptosis genes and perform differential analysis,analyze differentially expressed genes for GO function and KEGG signaling pathway.WGCNA analysis and machine learning(random forest,LASSO regression,and SVM-RFE analysis)were also used to screen osteoarthritis ferroptosis signature genes.The in vitro cell experiments were performed to divide chondrocytes into normal and osteoarthritis model groups.The dataset and qPCR were used to verify expression and correlate immune infiltration analysis. RESULTS AND CONCLUSION:(1)12 548 osteoarthritis genes were obtained by batch correction and PCA analysis,while 484 ferroptosis genes were obtained,resulting in 24 differentially expressed genes of osteoarthritis ferroptosis.(2)GO analysis mainly involved biological processes such as response to oxidative stress and response to organophosphorus,cellular components such as apical and apical plasma membranes,and molecular functions such as heme binding and tetrapyrrole binding.(3)KEGG analysis exhibited that differentially expressed genes of osteoarthritis ferroptosis were related to signaling pathways such as the interleukin 17 signaling pathway and tumor necrosis factor signaling pathway.(4)After using WGCNA analysis and machine learning screening,we obtained the characteristic gene KLF2.After validation by gene microarray,we found that the gene expression of KLF2 was higher in the test group than in the control group in the meniscus(P=0.000 14).(5)In vitro chondrocyte assay showed that type Ⅱ collagen and KLF2 expression was lower in the osteoarthritis group than in the control group in chondrocytes(P<0.05),while in osteoarthritis ferroptosis,mast cells activated was closely correlated with dendritic cells(r=0.99);KLF2 was closely correlated with natural killer cells(r=-1,P=0.017)and T cells follicular helper(r=-1,P=0.017).(6)The findings indicate that using WGCNA analysis and machine learning methods confirmed that KLF2 can be a characteristic gene for osteoarthritis ferroptosis and may improve osteoarthritis ferroptosis by interfering with KLF2.

When skin injuries are healing, complex wound environments can be easily created, which can result in wound infection, excessive inflammation caused by neutrophil accumulation and inflammatory factors, and excessive reactive oxygen species, resulting in high levels of oxidative stress. As a result of these factors, cell membranes, proteins, DNA, etc. may become damaged, which adversely affects the repair function of normal cells around the wound, resulting in the formation of chronic wounds. The effectiveness of wound dressings as a treatment is well known. They can offer temporary skin damage protection, prevent or control wound infection, create an environment that is conducive to mending skin damage, and speed wound healing. Traditional dressings like gauze, cotton balls, and bandages, however, have the drawbacks of having no antimicrobial properties, having weak adhesive properties, having poor mechanical properties, being susceptible to inflammation, obstructing angiogenesis, needing frequent replacement, and being unable to create an environment that is conducive to wound healing. As an innovative bandage, self-assembled hydrogel has great water absorption, high water retention, superior biocompatibility, biodegradability and three-dimensional (3D) structure. With properties including hemostasis, antibacterial, anti-inflammatory, and antioxidant, the synthesized raw material itself and the loaded active compounds have a wide range of potential applications in the treatment of skin injuries and wound healing. This research begins by examining and discussing the mechanism of cross-linking in self-assembled hydrogels. The cross-linking modes include non-covalent consisting of physical interaction forces such as electrostatic interactions, π-stacking, van der Waals forces, hydrophobic interactions, and metal-ligand bonds, covalent cross-linking formed by dynamic covalent bonding such as disulfide bonding and Schiff bases. And hybrid cross-linking with mixed physical forces and dynamic covalent bonding. The next part describes the special structure and excellent functions of self-assembled hydrogels, which include an extracellular matrix-like structure, the removal of exogenous microorganisms, and the mitigation of inflammation and oxidative stress. It goes on to explain the benefits of using self-assembled hydrogels as dressings for skin injuries. These dressings are capable of controlling cell proliferation, loading active ingredients, achieving hemostasis and coagulation, hastening wound healing, and controlling the regeneration of the injured area. The development of self-assembly hydrogels as dressings is summarized in the last section. The transition from purely non-covalent or covalent cross-linking to hybrid cross-linking with multiple networks, from one-strategy action to multi-strategy synergy in exerting antimicrobial, anti-inflammatory, and antioxidant effects and from single-function to multi-functioning in a single product. Additionally, it is predicted that future developments in self-assembled hydrogels will focus on creating biomimetic gels with multi-strategy associations linkage from naturally self-assembling biomolecules peptides, lipids, proteins and polysaccharides; improving the properties and cross-linking of raw materials to enhance the storage capabilities of hydrogels and cross-linking techniques, realizing the recycling of hydrogels; conducting additional research and exploration into the cross-linking process of hydrogels; and realizing the gel’s controllable rate of degradation. Furthermore, combining 3D printing and 3D microscopic imaging technology to design and build one-to-one specialized gel dressings; using computer simulation and virtual reality to eliminate the time factor, resulting in self-assembled hydrogels that perfectly fit the ideal dressing.

Traditional Chinese medicine can regulate the hypoxia-inducible factor-1α(HIF-1α)signalling pathway and slow down tumour progression mainly by inhibiting tumour angiogenesis,glycolysis,epithelial mesenchymal transition and other pathological processes.This paper,starting from HIF-1α and related factors,reviews its pathological mechanism in tumours and the research of traditional Chinese medicine interventions with the aim of providing theoretical references for the treatment of tumours with traditional Chinese medicine.

Objective:The aim of this study is to analyze the development of speech ability in Mandarin-speaking infants and children with normal hearing using MUSS and to provide a normal value control for the evaluation of speech ability in children with hearing loss.Methods:From September 2012 to January 2023, a total of 256 infants and children aged 1-60 months in Mandarin language environment participated in this study. 200 infants and children aged from 1 to 60 months were finally included, whose hearing was considered normal according to the history collection, high-risk registers for hearing loss and hearing screening. All infants and children were divided into 10 groups with 20 infants or children in each group. They were: 1 month, 2-3 months, 4-6 months, 7-9 months, 10-12 months, 13-18 months, 19-24 months, 25-36 months, 37-48 months, and 49-60 months. Using SPSS 19.0 software for data analysis, we calculated regression equations based on fitting curves.Results:The language ability of infants and children with normal hearing increased with age and reached ceiling at 56.5months.The regression equation was: score=-0.009 3×(age) 2+2.179×(age)+6.718 6, r2=0.85; age=0.003 9×(score) 2+0.148 4×(score)+2.708, r2=0.85. Conclusions:The speech ability of infants and children with normal hearing shows an increasing trend with age. Scores of different speech skills can be predicted according to their age. Age can also be predicted according to their scores of different speech skills.

Objective Viral encephalitis is an infectious disease severely affecting human health.It is caused by a wide variety of viral pathogens,including herpes viruses,flaviviruses,enteroviruses,and other viruses.The laboratory diagnosis of viral encephalitis is a worldwide challenge.Recently,high-throughput sequencing technology has provided new tools for diagnosing central nervous system infections.Thus,In this study,we established a multipathogen detection platform for viral encephalitis based on amplicon sequencing. Methods We designed nine pairs of specific polymerase chain reaction(PCR)primers for the 12 viruses by reviewing the relevant literature.The detection ability of the primers was verified by software simulation and the detection of known positive samples.Amplicon sequencing was used to validate the samples,and consistency was compared with Sanger sequencing. Results The results showed that the target sequences of various pathogens were obtained at a coverage depth level greater than 20×,and the sequence lengths were consistent with the sizes of the predicted amplicons.The sequences were verified using the National Center for Biotechnology Information BLAST,and all results were consistent with the results of Sanger sequencing. Conclusion Amplicon-based high-throughput sequencing technology is feasible as a supplementary method for the pathogenic detection of viral encephalitis.It is also a useful tool for the high-volume screening of clinical samples.

Objective:To compare the perioperative conditions of open pancreaticoduodenectomy (OPD), laparoscopic pancreaticoduodenectomy (LPD) and LPD conversion OPD, and analyze the short-term prognosis and risk factors for LPD conversion OPD.Methods:The clinical data of 167 patients undergoing pancreaticoduodenectomy (PD) in the Beijing Friendship Hospital, Capital Medical University from February 2020 to March 2023 were retrospectively analyzed. Of 167 patients, 63 patients underwent OPD surgery (OPD group), 91 patients underwent LPD surgery (LPD group), and 13 patients were converted to OPD during LPD surgery (LPD conversion OPD group). The measurement data with non-normal distribution were expressed as median (interquartile range) [ M( Q1, Q3)], and comparison between groups was analyzed using the Kruskal-Wallis H test. The count data were expressed as the number of cases and percentage, and the Chi-square test was used for ordered categorical variable, Kruskal-Wallis H test was used for un-ordered categorical variable. The risk factors of LPD conversion OPD were analyzed by multivariate Logistic regression. Results:The intraoperative blood loss [600(350, 1 000) mL], bilio-intestinal drainage stay time [10(8, 15) d] and bilio-intestinal drainage volume [995(505, 1 502) mL] in the LPD conversion OPD group were significantly higher than those in the LPD group [200(100, 300) mL, 7(6, 6) 10) d, 450(175, 874) mL], the differences were statistically significant ( P<0.05). The operation time of the LPD conversion OPD group [335(293, 385) d] was significantly longer than that of the OPD group [230 (195, 290)d], and the difference was statistically significant ( P<0.05). Multivariate Logistic regression analysis revealed that preoperative complications of chronic pancreatitis ( OR=19.714) and maximum diameter of the lesion ( OR=5.583) has a significant impact on the LPD conversion OPD ( P<0.05). Conclusions:Patients who plan to undergo PD should prefer LPD if the technology and physical condition permit. Preoperative complication of chronic pancreatitis, maximum diameter of lesion > 3.5 cm are the risk factors for LPD conversion OPD, which may significantly increase intraoperative blood loss, prolong the indwelling time of biliary drainage tube, and increase the drainage volume of biliary drainage tube. Therefore, the surgical method should be carefully selected.

Objective To construct an artificial intelligence assisted diagnosis model based on deep learning for dynamically recognizing gastric lesions and their locations under gastroscopy in real time,and to evaluate its ability to detect and recognize gastric lesions and their locations.Methods The gastroscopy videos of 104 patients in our hospital was retrospectively analyzed,and the video frames were manually annotated.The annotated picture frames of lesion category were divided into the training set and the validation set according to the ratio of 8∶2,and the annotated picture frames of location category were divided into the training set and the validation set according to the patient sources at the ratio of 8∶2.These sets were utilized for training and validating the respective models.YoloV4 model was used for the training of lesion recognition,and ResNet152 model was used for the training of location recognition.The accuracy,sensitivity,specificity,positive predictive value,negative predictive value and location recognition accuracy of the auxiliary diagnostic model were evaluated.Results A total of 68 351 image frames were annotated,with 54 872 frames used as the training set,including 41 692 frames for lesion categories and 13 180 frames for location categories.The validation set consisted of 13 479 frames,comprising 10 422 frames for lesion categories and 3 057 frames for location categories.The lesion recognition model achieved an overall accuracy of 98.8%,with a sensitivity of 96.6%,specificity of 99.3%,positive predictive value of 96.3%,and negative predictive value of 99.3% in validation set.Meanwhile,the location recognition model demonstrated an top-5 accuracy of 87.1% .Conclusion The artificial intelligence assisted diagnosis model based on deep learning for real-time dynamic recognition of gastric lesions and their locations under gastroscopy has good ability in lesion detection and location recognition,and has great clinical application prospects.

For the past 30 years,percutaneous balloon mitral valve dilatation has been performed under the guidance of X-rays and bedside ultrasound.However,there are still some cases of mitral valve stenosis in the large atrium where balloon dilation failed.Intraperitoneal ultrasound-guided percutaneous balloon mitral valve plasty is accurate and feasible,which can reduce the occurrence of complications and improve the success rate of such elderly complex cases.Two patients with severe mitral stenosis underwent percutaneous balloon mitral valve plasty guided by intracardiac ultrasound.The operations were successful without any complications,which can provide reference for clinical treatment of mitral stenosis.