Obstructive sleep apnea (OSA) is an increasingly widespread sleep-breathing disordered disease, and is an independent risk factor for many high-risk chronic diseases such as hypertension, coronary heart disease, stroke, arrhythmias and diabetes, which is potentially fatal. The key to the prevention and treatment of OSA is early diagnosis and treatment, so the assessment and diagnostic technologies of OSA have become a research hotspot. This paper reviews the research progresses of severity assessment parameters and diagnostic technologies of OSA, and discusses their future development trends. In terms of severity assessment parameters of OSA, apnea hypopnea index (AHI), as the gold standard, together with the percentage of duration of apnea hypopnea (AH%), lowest oxygen saturation (LSpO₂), heart rate variability (HRV), oxygen desaturation index (ODI) and the emerging biomarkers, constitute a multi-dimensional evaluation system. Specifically, the AHI, which measures the frequency of sleep respiratory events per hour, does not fully reflect the patients’ overall sleep quality or the extent of their daytime functional impairments. To address this limitation, the AH%, which measures the proportion of the entire sleep cycle affected by apneas and hypopneas, deepens our understanding of the impact on sleep quality. The LSpO₂ plays a critical role in highlighting the potential severe hypoxic episodes during sleep, while the HRV offers a different perspective by analyzing the fluctuations in heart rate thereby revealing the activity of the autonomic nervous system. The ODI provides a direct and objective measure of patients’ nocturnal oxygenation stability by calculating the number of desaturation events per hour, and the biomarkers offers novel insights into the diagnosis and management of OSA, and fosters the development of more precise and tailored OSA therapeutic strategies. In terms of diagnostic techniques of OSA, the standardized questionnaire and Epworth sleepiness scale (ESS) is a simple and effective method for preliminary screening of OSA, and the polysomnography (PSG) which is based on recording multiple physiological signals stands for gold standard, but it has limitations of complex operations, high costs and inconvenience. As a convenient alternative, the home sleep apnea testing (HSAT) allows patients to monitor their sleep with simplified equipment in the comfort of their own homes, and the cardiopulmonary coupling (CPC) offers a minimal version that simply analyzes the electrocardiogram (ECG) signals. As an emerging diagnostic technology of OSA, machine learning (ML) and artificial intelligence (AI) adeptly pinpoint respiratory incidents and expose delicate physiological changes, thus casting new light on the diagnostic approach to OSA. In addition, imaging examination utilizes detailed visual representations of the airway’s structure and assists in recognizing structural abnormalities that may result in obstructed airways, while sound monitoring technology records and analyzes snoring and breathing sounds to detect the condition subtly, and thus further expands our medical diagnostic toolkit. As for the future development directions, it can be predicted that interdisciplinary integrated researches, the construction of personalized diagnosis and treatment models, and the popularization of high-tech in clinical applications will become the development trends in the field of OSA evaluation and diagnosis.

Ankylosing spondylitis (AS) combined with lower cervical fracture is often categorized into unstable fracture, with a high incidence of neurological injury and a high rate of disability and morbidity. As factors such as shoulder occlusion may affect the accuracy of X-ray imaging diagnosis, it is often easily misdiagnosed at the primary diagnosis. Non-operative treatment has complications such as bone nonunion and the possibility of secondary neurological damage, while the timing, access and choice of surgical treatment are still controversial. Currently, there are no clinical practice guidelines for the treatment of AS combined with lower cervical fracture with or without dislocation. To this end, the Spinal Trauma Group of Orthopedics Branch of Chinese Medical Doctor Association organized experts to formulate Clinical guidelines for the treatment of ankylosing spondylitis combined with lower cervical fracture in adults ( version 2024) in accordance with the principles of evidence-based medicine, scientificity and practicality, in which 11 recommendations were put forward in terms of the diagnosis, imaging evaluation, typing and treatment, etc, to provide guidance for the diagnosis and treatment of AS combined with lower cervical fracture.

In recent years, nucleic acid therapy, as a revolutionary therapeutic tool, has shown great potential in the treatment of genetic diseases, infectious diseases and cancer. Lipid nanoparticles (LNPs) are currently the most advanced mRNA delivery carriers, and their emergence is an important reason for the rapid approval and use of COVID-19 mRNA vaccines and the development of mRNA therapy. Currently, mRNA therapeutics using LNP as a carrier have been widely used in protein replacement therapy, vaccines and gene editing. Conventional LNP is composed of four components: ionizable lipids, phospholipids, cholesterol, and polyethylene glycol (PEG) lipids, which can effectively load mRNA to improve the stability of mRNA and promote the delivery of mRNA to the cytoplasm. However, in the face of the complexity and diversity of clinical diseases, the structure, properties and functions of existing LNPs are too homogeneous, and the lack of targeted delivery capability may result in the risk of off-targeting. LNPs are flexibly designed and structurally stable vectors, and the adjustment of the types or proportions of their components can give them additional functions without affecting the ability of LNPs to deliver mRNAs. For example, by replacing and optimizing the basic components of LNP, introducing a fifth component, and modifying its surface, LNP can be made to have more precise targeting ability to reduce the side effects caused by treatment, or be given additional functions to synergistically enhance the efficacy of mRNA therapy to respond to the clinical demand for nucleic acid therapy. It is also possible to further improve the efficiency of LNP delivery of mRNA through machine learning-assisted LNP iteration. This review can provide a reference method for the rational design of engineered lipid nanoparticles delivering mRNA to treat diseases.

As a microbial therapy method, fecal microbiota transplantation (FMT) has attracted the attention of researchers in recent years. As one of the most direct and effective methods to improve gut microbiota, FMT achieves therapeutic benefits by transplanting functional gut microbiota from healthy human feces into the intestines of patients to reconstruct new gut microbiota. FMT has been proven to be an effective treatment for gastrointestinal diseases such as Clostridium difficile infection, irritable bowel syndrome, and inflammatory bowel disease. In addition, the clinical and basic research of FMT outside the gastrointestinal system is also emerging. It is worth noting that there is bidirectional communication between the gut microbial community and the central nervous system (CNS) through the gut-brain axis. Some gut bacteria can synthesize and release neurotransmitters such as glutamate, gamma-aminobutyric acid (GABA) and dopamine. Imbalanced gut microbiota may interfere with the normal levels of these neurotransmitters, thereby affecting brain function. Gut microbiota can also produce metabolites that may cross the blood-brain barrier and affect CNS function. FMT may affect the occurrence and development of CNS and its related diseases by reshaping the gut microbiota of patients through a variety of pathways such as nerves, immunity, and metabolites. This article introduces the development of FMT and the research status of FMT in China, and reviews the basic and clinical research of FMT in neurodegenerative diseases (Alzheimer’s disease, Parkinson’s disease), neurotraumatic diseases (spinal cord injury, traumatic brain injury) and stroke from the characteristics of three types of nervous system diseases, the characteristics of intestinal flora, and the therapeutic effect and mechanism of fecal microbiota transplantation, summarize the common mechanism of fecal microbiota transplantation in the treatment of CNS diseases and the therapeutic targets. We found that the common mechanisms of FMT in the treatment of nervous system diseases may include the following 3 categories through summary and analysis. (1) Gut microbiota metabolites, such as SCFAs, TMAO and LPS. (2) Inflammatory factors and immune inflammatory pathways such as TLR-MyD88 and NF-κB. (3) Neurotransmitter 5-HT. In the process of reviewing the studies, we found the following problems. (1) In basic researches on the relationship between FMT and CNS diseases, there are relatively few studies involving the autonomic nervous system pathway. (2) Clinical trial studies have shown that FMT improves the severity of patients’ symptoms and may be a promising treatment for a variety of neurological diseases. (3) The improvement of clinical efficacy is closely related to the choice of donor, especially emphasizing that FMT from healthy and young donors may be the key to the improvement of neurological diseases. However, there are common challenges in current research on FMT, such as the scientific and rigorous design of FMT clinical trials, including whether antibiotics are used before transplantation or different antibiotics are used, as well as different FMT processes, different donors, different functional analysis methods of gut microbiota, and the duration of FMT effect. Besides, the safety of FMT should be better elucidated, especially weighing the relationship between the therapeutic benefits and potential risks of FMT carefully. It is worth mentioning that the clinical development of FMT even exceeds its basic research. Science and TIME rated FMT as one of the top 10 breakthroughs in the field of biomedicine in 2013. FMT therapy has great potential in the treatment of nervous system diseases, is expected to open up a new situation in the medical field, and may become an innovative weapon in the medical field.

The incidence of osteoporotic thoracolumbar vertebral fracture (OTLVF) in the elderly is gradually increasing. The kyphotic deformity caused by various factors has become an important characteristic of OTLVF and has received increasing attention. Its clinical manifestations include pain, delayed nerve damage, sagittal imbalance, etc. Currently, the definition and diagnosis of OTLVF with kyphotic deformity in the elderly are still unclear. Although there are many treatment options, they are controversial. Existing guidelines or consensuses pay little attention to this type of fracture with kyphotic deformity. To this end, the Lumbar Education Working Group of the Spine Branch of the Chinese Medicine Education Association and Editorial Committee of Chinese Journal of Trauma organized the experts in the relevant fields to jointly develop Clinical guidelines for the diagnosis and treatment of osteoporotic thoracolumbar vertebral fractures with kyphotic deformity in the elderly ( version 2024), based on evidence-based medical advancements and the principles of scientificity, practicality, and advanced nature, which provided 18 recommendations to standardize the clinical diagnosis and treatment.

Objective To investigate clinical effect of tendons pulling,poking and kneading for the treatment of external humeral epicondylitis.Metods From January 2018 to December 2021,a multicenter randomized controlled study was per-formed to collect 192 patients with external humeral epicondylitis in Wangjing Hospital,Beijing Dianli Hospital,and Beijing Fengsheng Osteotraumatology Hospital,respectively,and they were divided into treatment group and control group by random number table method.There were 96 patients in treatment group,including 36 males and 60 females,aged from 28 to 60 years old with an average of(41.20±5.50)years old;the course of disease ranged from 1 to 14 days with an average of(5.24±1.35)days;they were treated once every other day for 2 weeks.There were 96 patients in control group,including 33 males and 63 females,aged from 26 to 60 years old with an average of(43.35±7.75)years old;the course of disease ranged from 1 to 14 days with an average of(5.86±1.48)days;they were treated with topical voltaalin combined with elbow joint fixation for 2 weeks.Visual analogue scale(VAS)and Hospital for Surgery Scoring System(HSS)elbow pronation and supination angles,wrist metacarpal flexion and dorsal extension angles,elbow tenderness between two groups were compared before treatment and at 1,3,5,7,11 and 13 days after treatment;Hospital for Surgery Scoring System 2(HSS2)was compared before treatment and the final treatment.Results All patients were followed up for 10 to 14 days with an average of(12±1.6)days.VAS between treatment group and control group before treatment were 6.83±1.36 and 6.79±1.58,respectively,and decreased to 1.49±1.09 and 2.11±1.81 after the final treatment.VAS of treatment group were significantly lower than those of control group at 1,3,5,7,9,11 and 13 days after treatment(P＜0.05).HSS between two groups were 61.73±11.00 and 36.47±12.45 before treatment,respectively,and increased to 94.42±5.9 and 91.44±9.11 at the final treatment.HSS of treatment group were signifi-cantly higher than those of control group at 1,3,5,7,9,11 and 13 days after treatment(P＜0.05).On the 5th day after treat-ment,the external and internal rotation angles of elbow in treatment group were(66.41±12.69)° and(66.35±13.54)°,while those in control group were(62.08±16.03)° and(61.77±16.35)°.On the 7th day after treatment,the external and internal ro-tation angles of elbow were(69.79±12.64)° and(70.02±13.55)° in treatment group,and(65.28±15.86)° and(65.09± 16.67)° in control group.Elbow joint motion in treatment group was higher than that in control group(P＜0.05).On the 5th day after treatment,angles of wrist dorsiflexion and palm flexion were(39.43±15.94)°and(46.68±11.10)° in treatment group,and(38.51±18.49)° and(44.27±13.58)° in control group.On the 7th day after treatment,angles of wrist dorsiflexion and palm flexion were(42.52±16.50)° and(49.23±10.96)° in treatment group,and(41.18±20.09)° and(46.64±14.63)° in control group.The motion of wrist joint in treatment group was higher than that in control group(P＜0.05).On the 13th day after treatment,HSS2 in treatment group 93.61±6.32 were higher than those in control group 92.06±7.94(P＜0.05).There was no significant difference in elbow tenderness between two groups at each time point(P＞0.05).Conclusion Voltaren external treatment combined with elbow fixation and tendons pulling,poking and kneading could effectively improve symptoms of exter-nal humeral epicondylitis.Compared with voltaren external treatment,tendons pulling,poking and kneading has advantages of longer analgesic time and better elbow function recovery.

Objective To explore the efficiency of artificial intelligence and radiomics-assisted X-ray in diagnosis of lumbar osteoporotic vertebral compression fractures(OVCF).Methods The clinical data of 455 patients diagnosed as lumbar OVCF by MRI in our hospital were selected.The patients were divided into the training group(n=364)and the validation group(n=91),X-ray films were extracted,the image delineation,feature extraction and data analysis were carried out,and the artificial intelligence radiomics deep learning was applied to establish a diagnostic model for OVCF.After verifying the effectiveness of the model by receiver operating characteristic(ROC)curve,area under the curve(AUC),calibration curve,and decision curve analysis(DCA),the efficiencies of manual reading,model reading,and model-assisted manual reading of X-ray in the early diagnosis of OVCF were compared.Results The ROC curve,AUC and calibration curve proved that the model had good discrimination and calibration,and excellent diagnostic performance.DCA demonstrated that the model had a higher clinical net benefit.The diagnostic efficiency of the manual reading group:the accuracy rate was 0.89,the recall rate was 0.62.The diagnostic efficiency of the model reading group:the accuracy rate was 0.93,the recall rate was 0.86,the model diagnosis showed good predictive performance,which was significantly better than the manual reading group.The diagnostic efficiency of the model-assisted manual reading group:the accuracy rate was 0.92,the recall rate was 0.72,and the recall rate of the model-assisted manual reading group was higher than that of the manual reading group,but lower than that of the model reading group,indicating the superiority of the model diagnosis.Conclusion The diagnostic model established based on artificial intelligence and radiomics in this study has reached an ideal level of efficacy,with better diagnostic efficacy compared with manual reading,and can be used to assist X-ray in the early diagnosis of OVCF.

Objective To develop a clinical prediction model for predicting risk factors for prolonged hospital stay after anterior cervical discectomy and fusion(ACDF).Methods The clinical data of 914 patients underwent ACDF treatment for cervical spondylotic myelopathy(CSM)were retrospectively analyzed.According to the screening criteria,800 eligible patients were eventually included,and the patients were divided into the development cohort(n=560)and the validation cohort(n=240).LASSO regression was used to screen variables,and multivariate Logistic regression analysis was used to establish a prediction model.The prediction model was evaluated from three aspects:differentiation,calibration and clinical effectiveness.The performance of the model was evaluated by area under the curve(AUC)and Hosmer-Lemeshow test.Decision curve analysis(DCA)was used to evaluate the clinical effectiveness of the model.Results In this study,the five factors that were significantly associated with prolonged hospital stay were male,abnormal BMI,mild-to-moderate anemia,stage of surgery(morning,afternoon,evening),and alcohol consumption history.The AUC of the development cohort was 0.778(95%CI:0.740 to 0.816),with a cutoff value of 0.337,and that of the validation cohort was 0.748(95%CI:0.687 to 0.809),with a cutoff value of 0.169,indicating that the prediction model had good differentiation.At the same time,the Hosmer-Lemeshow test showed that the model had a good calibration degree,and the DCA proved that it was effective in clinical application.Conclusion The prediction model established in this study has excellent comprehensive performance,which can better predict the risk of prolonged hospital stay,and can guide clinical intervention as soon as possible,so as to minimize the postoperative hospital stay and reduce the cost of hospitalization.

Objective To explore the risk factors for surgical site infection(SSI)after transforaminal lumbar interbody fusion(TLIF)for the treatment of lumbar degenerative diseases.Methods A total of 1 000 patients who underwent TLIF for lumbar degenerative diseases in our hospital were included and divided into the infection group(n=23)and the non-infection group(n=977)according to whether the surgical incision was infected.General data,surgical and laboratory indicators of patients were collected,and potential risk factors of SSI were screened by univariate analysis and multivariate regression analysis,a nomogram model was established,and its predictive efficiency was validated by the receive operating characteristic(ROC)curve.Results The incidence of SSI in patients after TLIF was 2.3％.The results of univariate analysis showed that age,operative time,intraoperative blood loss,preoperative C-reactive protein(CRP),smoking,and diabetes mellitus were the significant risk factors for the occurrence of SSI.Multivariate regression analysis showed that older age,longer operation time,more intraoperative blood loss,smoking and diabetes mellitus were the independent risk factors for postoperative SSI.ROC curve showed that the nomogram model established in this study has good predictive efficiency.Conclusion Older age,longer operation time,more intraoperative blood loss,smoking,and diabetes mellitus were independent risk factors for postoperative SSI.For patients with these high risk factors,corresponding intervention measures should be taken before operation to reduce the incidence of SSI.

Objective To explore the core drugs and antidepressant molecular mechanisms of Chinese herbal compound in the clinical treatment of depression.Methods Relevant literature was searched through CNKI,Wanfang and VIP to screen and sort out the Chinese Herbal compounds used in clinical practice.By analyzing the frequency of medication and the association rules of Chinese medicines,Bupleuri Radix,Paeoniae Radix Alba,Curcumae Radix were determined as the core Chinese medicinals for the treatment of depression.The active components and target proteins of these drugs were screened by TCMSP database,and depression-related targets were obtained from TTD,OMIM,DrugBank and GeneCards.Protein-protein interaction(PPI)network and'core drug-active ingredient-intersection target'network were constructed by STRING and Cytoscape.Gene Ontology(GO)enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis were performed by Metascape.Molecular docking analysis used RCSB database,AutoDockTools and PyMOL to verify the binding activity of key active components with core targets.Results The drugs for the treatment of depression in clinical Chinese herbal compound prescriptions were mainly cold,sweet,bitter and pungent,and the liver meridian was the first.Bupleuri Radix,Paeoniae Radix Alba,Curcumae Radix had the highest frequency of medication,and the combination of"Paeoniae Radix Alba-Bupleuri Radix"and"Curcumae Radix-Paeoniae Radix Alba-Bupleuri Radix"had the highest support.In the PPI network,SLC6A4,AKT1 and CHRNA4 were the key targets.GO enrichment analysis results showed that core drugs play a role in synaptic membranes and other parts through biological processes such as chemical synaptic transmission,as well as molecular functions such as G protein-coupled receptor activity.KEGG pathway enrichment analysis results showed that core drugs may treat depression through neuroactive ligand-receptor interaction,calcium signaling pathway and other pathways.Molecular docking confirmed that there was a strong binding activity between the key active ingredients and the core target.Conclusion Bupleuri Radix,Paeoniae Radix Alba,Curcumae Radix are the core drugs for clinical treatment of depression,which can treat depression through multi-component,multi-target and multi-pathway.