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.

Chagas disease(American trypanosomiasis)is a zoonosis caused by Trypanosoma cruzi,which severely affects public health.Recently,with changes in economic globalization and increased population mobility,this disease has gradually spread from the original Latin American epidemic areas to non-epidemic areas,such as Europe,thus showing a trend of globalization.The main trans-mission routes have changed from transmission via the Triatomine vector to blood transfusion transmission,mother-to-child transmis-sion,oral transmission,and other routes.Consequently,Chagas disease is spreading globally,and more people are increasingly vul-nerable to infection.This article retrospectively reviews research on the transmission routes of Chagas disease,analyzes the changing trends in transmission routes,and provides a scientific basis for the formulation and optimization of Chagas disease prevention and con-trol strategies from a One Health perspective.

This study was aimed at establishing a method of ultra-fast quantitative PCR for Brucella detection.We used an exogenous recombinant plasmid as the internal reference and targeted the T4SS secretion system,an important Brucella viru-lence factor,to design specific primers and probes.The sensitivity,specificity,and repeatability of this method were evaluated,and a standard curve was constructed.The coincidence rate of detection findings with this method versus quantitative PCR was determined.This method markedly decreased the detection time to only 10 minutes.The standard curve demonstrated a good linear relationship(Y=-3.410 7x+38.357,R2=0.998 5)with a low minimum detection limit of 10 copies/μL.The method exhibited good specificity and did not specifically amplify several common clinical bacteria other than Brucella.The de-tection of three concentrations of positive plasmids yielded coefficients of variation(CVs)of 0.20％to 0.91％,thus demonstra-ting the method's excellent repeatability.Furthermore,140 clinical samples were analyzed concurrently with the fluorescence PCR method,which yielded a 100％compliance rate and consistent results.Our findings indicated that the Brucella ultra-fast quantitative PCR was ultrafast;had high sensitivity,high specificity,and good specificity;and can be used for the clinical de-tection of Brucella and emergency investigation of epidemics.Therefore,this method is valuable for the early diagnosis of Bru-cella.

Hepatocellular carcinoma(HCC),which is essentially primary liver cancer,is closely related to CD8+T cell immune infiltration and immune suppression.We constructed a CD8+T cells related risk score model to pre-dict the prognosis of HCC patients and provided therapeutic guidance based on the risk score.Using integrated bulk RNA sequencing(RNA-seq)and single-cell RNA sequencing(scRNA-seq)datasets,we identified stable CD8+T cell signatures.Based on these signatures,a 3-gene risk score model,comprised of KLRB1,RGS2,and TN-FRSF1B was constructed.The risk score model was well validated through an independent external validation co-hort.We divided patients into high-risk and low-risk groups according to the risk score and compared the differ-ences in immune microenvironment between these two groups.Compared with low-risk patients,high-risk patients have higher M2-type macrophage content(P＜0.0001)and lower CD8+T cells infiltration(P＜0.0001).High-risk patients predict worse response to immunotherapy treatment than low-risk patients(P＜0.01).Drug sensitivity a-nalysis shows that PI3K-β inhibitor AZD6482 and TGFβRII inhibitor SB505124 may be suitable therapies for high-risk patients,while the IGF-1R inhibitor BMS-754807 or the novel pyrimidine-based anti-tumor metabolic drug Gemcitabine could be potential therapeutic choices for low-risk patients.Moreover,expression of these 3-gene mod-el was verified by immunohistochemistry.In summary,the establishment and validation of a CD8+T cell-derived risk model can more accurately predict the prognosis of HCC patients and guide the construction of personalized treatment plans.

Objective To investigate the potential therapeutic effects,targets,and pathways of wogonoside in hypertension-induced renal injury using the Gene Expression Omnibus(GEO)database and network pharmacology,and to validate the effects of wogonoside intervention on the renal tissues of spontaneously hypertensive rats(SHR),angiotensin Ⅱ(Ang Ⅱ)-stimulated NRK-52E cell apoptosis,and the regulation of relevant pathways through in vivo and in vitro experiments.Methods GEO dataset and network pharmacology analyses were performed to investigate the key therapeutic targets of wogonoside for hypertensive nephropathy.The STRING database was used to analyze protein-protein interactions.Biological functions were annotated via Gene Ontology(GO),and the potential signaling pathways were enriched using the Kyoto Encyclopedia of Genes and Genomes(KEGG).SHR were randomly divided into groups and given low,medium,or high doses of wogonoside(0.075,0.75,and 7.5 mg/kg)via gastric gavage for 10 weeks.Morphological changes in the kidney tissue were assessed by hematoxylin-eosin(HE)staining.Serum levels of inflammatory cytokines,including tumor necrosis factor α(TNF-α),interleukin(IL)-1 β,and IL-6,were measured using ELISA.Apoptosis rates were evaluated by TUNEL staining,and Western blot was performed to determine the expression of Bax,Bcl-2,cleaved caspase-3,and caspase-3,and the expression of phosphorylated and total extracellular signal-regulated kinases(ERK)and p38 mitogen-activated protein kinase(MAPK)proteins.An in vitro model of Ang Ⅱ-stimulated NRK-52E cells was constructed and was treated with wogonoside at different concentrations(25,50,or 100 μmol/L)for 24 h.The apoptosis rates were then assessed by Annexin V staining,and Western blot was performed to validate the expression of apoptosis-related and pathway-associated proteins.Results Analysis of dataset GSE41453 revealed 11673 upregulated and 5902 downregulated genes in the renal tissues of SHR compared to the Wistar Kyoto(WKY)rats,or the WKY control group.Through the analysis of multiple databases,371 potential targets of wogonoside were identified,resulting in 98 overlapping targets.From these,45 core therapeutic targets were identified through further analysis,including TNF,CASP3,etc.GO analysis significantly enriched processes such as the negative regulation of apoptosis.KEGG pathway enrichment analysis highlighted the apoptosis pathway,IL-17 signaling pathway,and MAPK signaling pathway as being significantly enriched.Wogonoside treatment effectively mitigated pathological damage in SHR kidney tissues and significantly inhibited the expression of inflammatory cytokines,including TNF-α,IL-1 β,and IL-6(P＜0.05).It also decreased cell apoptosis rates in SHR kidney tissues and Ang Ⅱ-stimulated NRK-52E cells,downregulated the expression of Bax and cleaved caspase-3,and upregulated Bcl-2 expression(P＜0.05).Furthermore,wogonoside treatment inhibited the phosphorylation of ERK and p38 MAPK in SHR kidney tissues and Ang Ⅱ-stimulated NRK-52E cells(P＜0.05).Conclusion Wogonoside may exert its protective effects against hypertension-induced renal injury by suppressing the inflammatory response and cell apoptosis,potentially through the regulation of the MAPK signaling pathway.

Objective To investigate the potential therapeutic effects of trifolin on hypertension-induced renal injury,as well as the key targets and pathways involved.Methods The mRNA transcriptional profiles of peripheral blood clinical samples from hypertensive patients were analyzed using Gene Expression Omnibus(GEO),a high-throughput gene expression database.The network pharmacology method was employed to screen key targets of trifolin in treating hypertension-induced renal injury.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analyses were conducted.NRK-52E cells,a rat renal proximal tubular cell line,were used to construct an angiotensin Ⅱ(Ang Ⅱ)-stimulated cell model.Flow cytometry was performed to assess cell apoptosis rates and Western blotting was performed to determine the expression levels of apoptosis-related proteins,including Bax,Bcl-2,cleaved caspase-3,and caspase-3,and the phosphorylation and total protein levels of the key MAPK pathway proteins,including ERK,p38 MAPK,and JNK.Results Analysis of the dataset GSE75360 revealed that,compared with healthy controls,3 331 genes were upregulated and 3 197 genes were downregulated in peripheral blood mononuclear cells of hypertensive patients.According to network pharmacology analysis,472 potential targets of trifolin were identified,including CASP3 and MAPK1.Protein-protein interaction network analysis showed that these targets were closely associated with apoptosis regulatory signaling pathways.GO and KEGG pathway enrichment analyses indicated that trifolin was significantly enriched in pathways associated with negative regulation of apoptosis,apoptotic signaling pathways,and the MAPK signaling pathway.The in vitro experiments confirmed that,compared with the Ang Ⅱ group,trifolin intervention inhibited apoptosis in Ang Ⅱ-stimulated NRK-52E cells,suppressed the expression of Bax and cleaved caspase-3,promoted Bcl-2 expression,and inhibited the phosphorylation of p38 MAPK,ERK,and JNK(P<0.05).Conclusion Trifolin may exert its protective effect against hypertension-induced renal injury by inhibiting Ang Ⅱ-induced NRK-52E cell apoptosis and regulating the MAPK signaling pathway,representing an important mechanism underlying its therapeutic action.

Objective This study aimed to provide an effective scientific basis for prevention and control of cockroaches on aircrafts by identifying cockroach-carried pathogens,and assess the insecticidal efficacy of gel bait mediated cockroach control on aircrafts,to provide technical guidance for aircraft disinsection.Methods Cassette-trapping was used to trap cockroaches,and the carried pathogens were detected using bacterial cultivation techniques.The gel bait mediated killing rate was calculated after 1,7,and 30 d by field application of gel bait.Results A total of 411 cockroaches were captured,and all were identified as Blattella germanica.26 strains of pathogenic bacteria were isolated from the trapped cockroaches.The killing rates of cockroaches were 58.8％-96.3％with 1-30 day application of gel bait.Statistically significant differences were observed in cockroach killing rates on different days(χ2=58.95,P<0.01).Conclusions B.germanica carry a large variety of pathogenic bacteria and opportunistic pathogens and are thus important infectious disease carriers.Gel bait agents have proven to be very effective against cockroaches on aircrafts.

Hepatocellular carcinoma(HCC),which is essentially primary liver cancer,is closely related to CD8+T cell immune infiltration and immune suppression.We constructed a CD8+T cells related risk score model to pre-dict the prognosis of HCC patients and provided therapeutic guidance based on the risk score.Using integrated bulk RNA sequencing(RNA-seq)and single-cell RNA sequencing(scRNA-seq)datasets,we identified stable CD8+T cell signatures.Based on these signatures,a 3-gene risk score model,comprised of KLRB1,RGS2,and TN-FRSF1B was constructed.The risk score model was well validated through an independent external validation co-hort.We divided patients into high-risk and low-risk groups according to the risk score and compared the differ-ences in immune microenvironment between these two groups.Compared with low-risk patients,high-risk patients have higher M2-type macrophage content(P＜0.0001)and lower CD8+T cells infiltration(P＜0.0001).High-risk patients predict worse response to immunotherapy treatment than low-risk patients(P＜0.01).Drug sensitivity a-nalysis shows that PI3K-β inhibitor AZD6482 and TGFβRII inhibitor SB505124 may be suitable therapies for high-risk patients,while the IGF-1R inhibitor BMS-754807 or the novel pyrimidine-based anti-tumor metabolic drug Gemcitabine could be potential therapeutic choices for low-risk patients.Moreover,expression of these 3-gene mod-el was verified by immunohistochemistry.In summary,the establishment and validation of a CD8+T cell-derived risk model can more accurately predict the prognosis of HCC patients and guide the construction of personalized treatment plans.

The engineering application of microbially induced carbonate precipitation(MICP)is limited by pH-dependent conformational dynamics of urease.Focusing on the α-subunit urease from Sporosarcina pasteurii,this study integrated conductivity experiments and constant-pH molecular dynamics simulations to analyze active site conformational dynamics and catalytic function across pH 3-11.Results showed that under neutral conditions(pH 7-8),key histidine residues(HIS139/HIS249)exhibited minimal dis-placement(＜0.5 ?),the longest hydrogen bond lifetime(＞8 ps),highest conformational stability(root mean square deviation,RMSD:0.15-0.18 nm),and optimal catalytic activity(conductivity change rate:0.03 mS/cm·min-1,CaCO3 precipitation:3.84 g).Extreme pH(pH 3/11)induced structural collapse(displacement up to 1.8 ?)and complete activity loss.Simulations revealed that neutral pH sta-bilizes a protonation-dependent cooperative allosteric network by maintaining active site cavity volume(～120 ?3)and moderate conformational coherence(correlation coefficient～0.8).This work deciphers the molecular mechanism of pH-regulated urease dynamics through protonation states,providing theoreti-cal support for MICP applications in acidic mine tailing remediation and alkaline soil stabilization.

Objective To propose a lightweight deep learning network-based segmentation method for automatic segmenta-tion of the skeletal muscle at the third cervical spine(C3)level.Methods Firstly,121 patients with head and neck tumors admitted to the Department of Oncology of Zigong First People's Hospital from January 2019 to December 2022 were selected and randomly divided into a training set,a validation set and a test set in the ratio of 7∶1∶2.Secondly,a lightweight Mamba architecture was introduced into the UNet network and an attention gate(AG)mechanism was added to the skip connection path to construct a MB-UNet network model.Finally,the trained network models were evaluated for segmentation performance on the test set,the MB-UNet network model was compared with manual segmentation over the results of determination of skeletal muscle area(SMA),and with classical network models in terms of parameter scale and computation effort including UNet,Deeplab V3+,U2Net,VMUNet and UltraLight-VMUNet models.The time required by the MB-UNet network model for predicting SMA and that by the physician with the assistance of the model was summarized.Results When used for segmenting the skeletal muscle at C3 level the constructued MB-UNet network model gained advantages over the classical models,with a Dice similarity coefficient of 88.23%,an intersection over union(IoU)ratio of 78.94%,a sensitivity of 91.27%and a 95%Hausdorff distance of 7.13 mm;the SMA determined by manual segementation was basically close to that by the MB-UNet network model;the MB-UNet network model behaved generally better than the classical network models,with the computation effort being 1.88 GFLOPS and the parameter scale being 0.77M;it took the MB-UNet network model 1.93 s for the prediction on the test set,and only 2 min for the physician to obtain satisfactory results with the assistance of the MB-UNet network model,which was significantly shorter than that by munual segmentation(20 min).Conclusion The proposed method contributes to segmenting the skeletal muscle at C3 level precisely and rapidly and calculating SMA accurately,which helps clinicians to quickly diagnose sarcopenia in patients with head and neck tumors and improves the diagnostic efficiency.[Chinese Medical Equipment Journal,2025,46(8):11-17]