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.

Objective To establish an indirect enzyme-linked immunosorbent assay(ELISA)method for testing the concentration of a monoclonal antibody target tumor necrosis factor-α(TNF-α)in animal serum.Methods The critical parameters of the method including coating concentration of human TNF-α,source,concentration and stability of HRP-labeled goat anti-human immunoglobulin G(IgG)were investigated.The specificity,accuracy,precision,linearity and Limited of Determination of the method were investigated.Results The critical parameters of the method were confirmed as below:TNF-α was coated at 400 ng·mL-1;HRP labeled goat anti-human IgG antibody was diluted at 1:3.0 ×105;the diluted horseradish peroxidase labeled goat anti-human IgG antibody is well stored at 4 ℃ for 3 days.Meanwhile the method was confirmed to have good specificity,the recovery rate ranged from 84.00％to 106.82％,the coefficient of variation of different antibody concentration levels were no more than 10％;the method had a good linearity and the standard curve was y=(-8.37×103-2.37 × 106)/[1+(x/29.80)106]+2.37 × 106(R2=0.999);the limit of quantification was 1 ng·mL-1,all of which met the requirements.Conclusion A accurate and robust ELISA method was developed to test the concentration of anti-TNF-α monoclonal antibody in serum.

Alzheimer's disease(AD)is one kind of disruptive neurodegenerative disease which can lead to severe cognitive dysfunction.Sinomenine can inhibit the activation of astrocytes,increase of oxidative stress and levels of inflammatory factors,protect neurons from indirect toxicity of astrocytes,inhibit microglial-mediated neuroinflammation,inhibit acetyl cholinesterase and β-site amyloid precursor protein cleaving enzyme-1 activities in AD,thus exert anti AD effects.According to review the molecular mechanisms of sinomenine in treatment of AD,we aim to provide a basis for the development of new drugs for treatment of AD.

In the past few decades, microbubbles were widely used as ultrasound contrast agents in the field of tumor imaging. With the development of research, ultrasound targeted microbubble destruction technology combined with drug-loaded microbubbles can achieve precise drug release and play a therapeutic role. As a micron-scale carrier, microbubbles are difficult to penetrate the endothelial cell space of tumors, and nano-scale drug delivery system—nanobubbles came into being. The structure of the two is similar, but the difference in size highlights the unique advantages of nanobubbles in drug delivery. Based on the classification principle of shell materials, this review summarized micro/nanobubbles used for ultrasound diagnosis or treatment and discussed the possible development directions, providing references for the subsequent development.

Objective To investigate the implementation of surveillance,prevention and control measures for healthcare-associated infection(HAI)in maternal and child healthcare(MCH)institutions,and provide policy evi-dence for optimizing HAI prevention and control in MCH institutions.Methods Stratified sampling was conducted among the MCH institutions at provincial,municipal and county levels in 8 provinces/autonomous regions.A uni-fied questionnaire was designed and the online survey was conducted through"Questionnaire Star".Results The data from 123 MCH institutions were included in the analysis.90.24％of the MCH institutions carried out compre-hensive surveillance on HAI.The ratios of MCH institutions which implemented targeted surveillance on HAI in neonatal intensive care unit(NICU),surgical site infection,multidrug-resistant organisms(MDROs)and HAI in intensive care units(non-NICU excluded)were 89.66％,85.96％,80.77％,and 74.19％,respectively.51.22％MCH institutions adopted information surveillance system on HAI cases.94.31％MCH institutions carried out surveillance on hand hygiene compliance.Over 90％MCH institutions carried out surveillance on environment hy-giene in high-risk departments.71.54％MCH institutions conducted centralized cleaning,disinfection,sterilization and supply for reusable medical instruments in the central sterile supply department(CSSD).Over 90％MCH insti-tutions established three-level pre-examination triage systems.86.18％set up transitional wards.MCH institutions generally adopted a management model with established effective communication,full appointment visits,and sepa-rate visits for special medical groups,such as registered pregnant women,high-risk newborns,healthcare groups,and long-term rehabilitation patients.However,the ratio of institutions conducting on-line follow-up visits was less than 50％.Conclusion MCH institutions have generally carried out comprehensive and targeted surveillance on HAI.Information surveillance need to be facilitated.Hand hygiene and environmental hygiene surveillance has been popularized to a certain extent at all levels of MCH institutions.The cleaning,disinfection,sterilization,and supply processes of reusable medical devices in a few MCH institutions are not standardized.Special medical populations get effective management.On-line healthcare is to be further promoted.

Surgery is an important treatment for the anterior mediastinal disease. With the rapid development of minimally invasive techniques, complete resection of the lesion in most patients with thymic disease can be achieved through thoracoscopic surgery. Practice has proved that the three-port resection of anterior mediastinal thymus disease via the subxiphoid approach is an ideal surgical method for the treatment of anterior mediastinal thymic tumors at present, which has strong popularization and popularity and can benefit the patients. The procedure focuses primarily on the anterior and upper mediastinum and can thoroughly expose the anatomy of the mediastinum and both sides, with minimal intraoperative bleeding, high safety, minimal trauma and postoperative pain, and a short hospital stay. It has clear advantages over conventional thoracic open-heart surgery and transversal resection. However, the surgical approach and field of view, and intraoperative precautions of this procedure are completely different from those of previous thoracoscopic procedures, and from the subxiphoid single-port approach adopted by other centers. Based on 10 years of surgical experience at our center, a modular mode of surgical operation has been developed and its procedure has been standardized. This paper will share and discuss relevant operational points and experiences.

Objective To construct machine learning models that can be used to predict AUC fold change(FC)using a database of existing pharmacokinetic(PK)and drug-drug interaction(DDI)information,which can be used to explore the possibility of predicting existing drug interactions and to provide certain rational recommendations for clinical drug use.Methods PK data of DDIs and AUC fold change data were extracted from FDA-approved drug labels.Peptide and pharmacodynamic(PD)information related to drug interactions were retrieved through DrugBank,and PPDT identification of relevant peptide IDs was performed using Protein Resource(UniProt),and a matrix normalization code was used to generate multidimensional vector data that were easy to analysis.The effect of PPDT on the AUC,and the resulting multiplicity change was used as the dependent variable for machine learning model construction.The model with the smallest root mean square error(RMES)value was used for model construction to train a bagged decision tree(Bagged)prediction model.The models were tested using the trained models for some of the drug tests.The models were evaluated by reviewing the available literature findings on detection of drug interaction pairs and analyzing and comparing the predicted values.Results A total of 16 pairs of model drug pairs were tested for the effects of 16 drugs on tacrolimus,and it was found that the accuracy of the prediction of the presence or absence of drug interactions was 81.25％;the prediction results were classified according to the FDA standard classification of the strong and weak for the strength of drug interactions,and the results showed that the prediction of the strength of drug interactions,with a large deviation from the larger prediction was less.Conclusion The evaluation of the model to predict the presence or absence of drug interactions was general;however,after classifying the strengths and weaknesses of drug interactions,the prediction of drug interactions was better,and the prediction results indicated that the model prediction performance has a certain reference value for potential DDI assessment before clinical trials.

Highly sensitive multiple detection and accurate identification of gases are of great importance in the fields of public safety,environmental protection,health diagnosis and industrial production.However,the traditional means of gas detection have many shortcomings such as low sensitivity,long time-consuming,bulky equipment,cumbersome processes and expensive costs.In recent years,Raman spectroscopy has become a hotspot in the field of gas detection because of its fast,sensitive and non-destructive characteristics,and has been more and more closely combined with artificial intelligence.This paper reviews the progress of Raman spectroscopy in gas detection in recent years,including conventional Raman spectroscopy and enhanced Raman spectroscopy,and also introduces the integration of artificial intelligence algorithms in gas Raman detection technology,and discusses the future development of gas Raman detection.

Objective To develop an intelligent horizontal rotating cell culture device with high modularity,easy operation,easy disinfection,low cost and high stability.Methods The cell culture device consisted of a rotating culture module,a dirve module,a control module and control software,with the shells of all the modules being manufactured by 3D printing.The rotating culture module was composed of a tubular electrospun scaffold,a cell culture chamber,a magnetic coupling rotor and polypropylene pipeline;the drive module was made up of a N20 reduction motor and a magnetic coupling rotor;the control module included an ESP-8266 chip and a printed circuit board;the control software was developed with Blinker IoT platform and C++language.The device was used to culture human intrahepatic bile duct epithelial cells to verify its effects.Results Light microscopy and scanning electron microscopy images showed that a uniform and continuous cell layer was formed on the surface of the tubular electrospun scaffold.Conclusion The intelligent horizontal rotating cell culture device achieves uniform growth of cells on the inner surface of tubular electrospun scaffolds,and can be used as an effective platform for cell culture on tubular scaffolds.[Chinese Medical Equipment Journal,2024,45(9):41-45]

Objective To investigate the clinical effect of anterior cervical discectomy and fusion(ACDF)in the treatment of cervical spondylosis of vertebral artery type(CSA).Methods The clinical data of 42 patients with CSA from January 2020 to January 2022 were retrospectively analyzed.There were 25 males and 17 females,aged from 30 to 74 years old with an average of(53.9±11.0)years old.There were 18 cases with single-segment lesions,17 cases with two-segment lesions,and 7 cases with three-segment lesions.The American Academy of Otolaryngology-Head and Neck Surgery's Hearing and Balance Committee score(CHE),the Neck Disability Index(NDI)and the cervical curvature Cobb angle were recorded before surgery and after surgery at 6 months.Results All 42 ACDF patients were followed up for 6 to 30 months with an average of(14.0±5.2)months.The operative time ranged from 95 to 220 min with an average of(160.38±36.77)min,the intraoperative blood loss ranged from 30 to 85 ml with an average of(53.60±18.98)ml.Tow patients had mild postoperative dysphagia,which improved with symptomatic treatment such as nebulized inhalation.CHE score decreased from(4.05±0.96)preoperatively to(2.40±0.70)at 6 months postoperatively(t=12.97,P＜0.05).The number of improved vertigo at 6 months postoperatively was 38,with an im-provement rate of 90.5％.NDI score was reduced from(34.43±8.04)preoperatively to(20.76±3.91)at 6 months postopera-tively(t=1 1.83,P＜0.05).The cervical curvature Cobb angle improved from(8.04±6.70)° preoperatively to(12.42±5.23)° at 6 months postoperatively(t=-15.96,P＜0.05).Conclusion The ACDF procedure has outstanding clinical efficacy in treating CSA.The operation can rapidly relieve patients'episodic vertigo symptoms by relieving bony compression and reconstructing cervical curvature.However,it is necessary to strictly grasp the indications for surgery and clarify the causes of vertigo in pa-tients,and ACDF surgery is recommended for CSA patients for whom conservative treatment is ineffective.