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.

ObjectivePhotoacoustic pump-probe imaging can effectively eliminate the interference of blood background signal in traditional photoacoustic imaging, and realize the imaging of weak phosphorescence molecules and their triplet lifetimes in deep tissues. However, background differential noise in photoacoustic pump-probe imaging often leads to large fitting results of phosphorescent molecule concentration and triplet lifetime. Therefore, this paper proposes a novel triplet lifetime fitting method for photoacoustic pump-probe imaging. By extracting the phase of the triplet differential signal and the background noise, the fitting bias caused by the background noise can be effectively corrected. MethodsThe advantages and feasibility of the proposed algorithm are verified by numerical simulation, phantom and in vivo experiments, respectively. ResultsIn the numerical simulation, under the condition of noise intensity being 10% of the signal amplitude, the new method can optimize the fitting deviation from 48.5% to about 5%, and has a higher exclusion coefficient (0.88>0.79), which greatly improves the fitting accuracy. The high specificity imaging ability of photoacoustic pump imaging for phosphorescent molecules has been demonstrated by phantom experiments. In vivo experiments have verified the feasibility of the new fitting method proposed in this paper for fitting phosphoometric lifetime to monitor oxygen partial pressure content during photodynamic therapy of tumors in nude mice. ConclusionThis work will play an important role in promoting the application of photoacoustic pump-probe imaging in biomedicine.

The mechanism of L-perilla alcohol(L-POH) in intervening hypoxic pulmonary hypertension(HPAH) was discussed based on network pharmacology, and experimental verification. The active components and potential targets of the volatile oil of Rhodiola tangutica(VORA) in the intervention of HPAH were screened by network pharmacology. The biological process of Gene Ontology(GO) and the signaling pathway enrichment of Kyoto Encyclopedia of Genes and Genomes(KEGG) were analyzed for the core targets, and a "component-common target-disease" network was constructed. Four active components were screened from VORA: L-POH, linalool, geraniol, and(-)-myrtenol. The core targets for treating HPAH were HSP90AA1, AKT1, ESR1, PIK3CA, EP300, EGFR, and JAK2. GO enrichment analysis mainly involved biological processes such as reaction to hypoxia, heme binding, and steroid binding. KEGG enrichment analysis mainly involved hypoxia-inducing factor 1(HIF-1) signaling pathway, phosphatidylinositol 3-kinase/protein kinase B(PI3K/AKT) signaling pathway, and Janus kinase/activator of signal transduction and transcription(JAK/STAT) signaling pathway. The vasodilation effects of the four active components were screened by perfusion experiment of extracorporeal vascular rings, and the mechanism of the main active component L-POH was studied by channel blockers. The inhibitory effects of the four active components on the proliferation of pulmonary artery smooth muscle cells(PASMCs) induced by hypoxia were screened by cell proliferation experiment, and the mechanism of the main active component L-POH was studied by flow cytometry, cell cycle experiment, and Western blot. The results showed that L-POH could directly act on vascular smooth muscle to relax pulmonary arterioles, induce ATP-sensitive potassium channels to open, and inhibit extracellular Ca~(2+) influx through voltage-gated calcium channels to relax blood vessels. In addition, L-POH could inhibit the abnormal proliferation of PASMCs induced by hypoxia and promote its apoptosis, and its mechanism may be related to the increase in Bax protein expression and the decrease in p-JAK2, p-STAT3, Bcl-2, and cyclinA2 protein expression. In summary, L-POH can interfere with HPAH by relaxing pulmonary arterioles and inhibiting the proliferation of smooth muscle cells.
Network Pharmacology ; Animals ; Hypertension, Pulmonary/physiopathology* ; Drugs, Chinese Herbal/administration & dosage* ; Rats ; Hypoxia/metabolism* ; Rhodiola/chemistry* ; Signal Transduction/drug effects* ; Humans ; Monoterpenes/chemistry* ; Male ; Cell Proliferation/drug effects* ; Rats, Sprague-Dawley

OBJECTIVE: To describe survival trends and global patterns of esophageal cancer (EC) using survival data from population-based cancer registries. METHODS: We systematically searched PubMed, EMBASE, Web of Science, SEER, and SinoMed databases for articles published up to 31 December 2023. Eligible EC survival estimates were evaluated according to country or region, period, sex, age group, pathology, and disease stage. RESULTS: After 2010, Jordan exhibited the highest age-standardized 5-year relative survival rates (RSRs)/net survival rates (NSRs) at 41.1% between 2010 and 2014, while India had the lowest, at 4.1%. Survival rates generally improved with diagnostic age across most countries, with significant increases in South Korea and China, of 12.7% and 10.5% between 2000 and 2017, respectively. Survival was higher among women compared to men, ranging from 0.4%-10.9%. Survival rates for adenocarcinoma and squamous cell carcinoma were similar, differing by about 4%. In China, the highest age-standardized RSRs/NSRs was 33.4% between 2015 and 2017. Meanwhile, the lowest was 5.3%, in Qidong (Jiangsu province) between 1992-1996. CONCLUSION Global EC survival rates have improved significantly in recent decades, but substantial geographical, sex, and age disparities still exist. In Asia, squamous cell carcinoma demonstrated superior survival rates compared to adenocarcinoma, while the opposite trend was observed in Western countries. Future research should clarify the prognostic factors influencing EC survival and tailor prevention and screening strategies to the changing EC survival patterns.
Humans ; Esophageal Neoplasms/mortality* ; Registries ; Male ; Female ; Survival Analysis ; Middle Aged ; Survival Rate ; Aged ; Global Health

There is significant inter-individual variation of pharmacokinetics and pharmacody-namics in patients receiving tacrolimus(TAC)for an-ti-rejection therapy,which cause the rejection or toxic action.Based on results of therapeutic drug monitoring and pathophysiological index of trans-plant patients,the individualized dosing regimen can be designed and adjusted by using model in-formed precision dosing(MIPD).The patients'clini-cal outcome can be improved.In the consensus,the different methods of MIPD used for patients re-ceived TAC for anti-rejection therapy were intro-duced,which can be used for the designing and ad-justing doing regimen,predicting adverse drug reac-tion,improving medication adherence and econom-ics during therapy.

Objective:This study aims to construct a colorectal cancer(CRC)prognosis prediction model based on disulfide death associated long-chain non coding ribonucleic acids(DRLncRNAs),and to explore its potential application in predicting prognosis and guiding personalized treatment.Methods:The data for this study was sourced from the Cancer Genome Atlas(TCGA)database,which includes RNA sequencing data and detailed clinical information of CRC patients.Using co expression network analysis to screen DRLncRNAs.Preliminary screening of DRLncRNAs related to prognosis was conducted through univariate Cox regression analysis,followed by variable screening and dimensionality reduction using LASSO Cox regression analysis.Finally,key DRLncRNAs for constructing a prognostic risk model were identified through multivariate Cox regression analysis.Evaluate the predictive ability of prognostic risk models for survival in CRC patients through Kaplan Meier survival curve analysis.The accuracy of the model was analyzed using receiver operating characteristic(ROC)curves,and the ability of different gene expression profiles to distinguish risk stratification was evaluated using principal component analysis(PCA).Gene ontology(GO)and KEGG enrichment analysis were used to evaluate the enrichment of high and low expression gene sets in different risk groups.Results:Five key DRLncRNAs(AC068580.3,AL161729.4,ZEB1-AS1,AC073896.3,and SNHG16)were successfully screened.In the overall concentration,the area under the curve(AUC)of the model's 1-year,3-year,and 5-year survival predictions are 0.674,0.746,and 0.727,respectively;In the training set,the predicted AUC for 1-year,3-year,and 5-year survival were 0.669,0.762,and 0.756,respectively;In the test set,the predicted AUC for 1-year,3-year,and 5-year survival were 0.666,0.725,and 0.697,respectively.SNHG16 and AC073896.3 are protective factors,and high expression was associated with better prognosis;ZEB1-AS1,AC068580.3,and AL161729.4 were risk factors,and high expression indicates poor prognosis.The Kaplan Meier survival analysis results showed that there was a significant difference in survival between the high-risk and low-risk groups(P＜0.05),and the overall survival rate of the high-risk group was significantly lower(P＜0.05).The enrichment analysis results showed that the phosphatidylinositol mediated signal transduction,mitochondrial gene expression,and other biological processes related to 5 DRLncRNAs may be involved in the occurrence,development,and poor prognosis of CRC.The results of this study showed that a prognostic risk model based on five DRLncRNAs(AC068580.3,AL161729.4,ZEB1-AS1,AC073896.3,and SNHG16)was successfully established,which showed independent correlation with the overall survival status of CRC patients.In addition,the prognostic risk model constructed based on these 5 DRLncRNAs can effectively predict the prognosis of CRC patients.Conclusion:This study identified five DRLncRNAs,including AC068580.3,AL161729.4,ZEB1-AS1,AC073896.3,and SNHG16,that are associated with the prognosis of CRC patients.The prognostic risk model constructed based on these five DRLncRNAs has a high evaluation efficiency for the prognosis of CRC patients.

Objective To propose a residual convolutional feedforward network-based high-resolution medical image generation model to enhance the quality for generating high-resolution medical images.Methods Firstly,a vector quantized generative adversarial network(VQGAN)was selected as the benchmark model;secondly,a residual convolutional feedfor-ward network composed of a residual module and a multi-scale convolutional feedforward module was integrated into the the encoder and decoder of VQGAN to form a new architecture;finally,the model propsed was compared with denoising diffusion model(DDM),StyleSwin model,VQGAN moel and SinGAN model to verify its performance,and the ablation experiment was carried out.Results The quantitative evaluation comparison showed that the model proposed behaved well generally with the lowest frechet inception distance(FID)(145.64),the lowest learned perceptual image patch similarity(LPIPS)(0.46)and the peak signal-to-noise ratio(PSNR)(62.63)only lower than that of DDM.Visualized comparison indicated the model proposed had the image generated gaining advantages over the other models in the texture,edges and sharpness of kidney stones and similarity to the real lesion images.The ablation experiment proved that the model proposed behaved better than the VQGAN benchmark model in convergence rate and training stability.Conclusion The proposed model has significant advantages in learning multi-scale texture features and retaining the information on low-dimensional anatomical structures,which can be used for generating high-quality high-resolution medical images.[Chinese Medical Equipment Journal,2025,46(9):1-8]

Objective:To investigate the association between anti-rituximab antibodies (ARA) and relapse after rituximab (RTX) therapy in children with frequently relapsing or steroid-dependent nephrotic syndrome (FRNS or SDNS).Methods:A retrospective cohort study was conducted. Clinical and laboratory data were collected from 48 FRNS or SDNS children treated with RTX in the Department of Pediatrics, General Hospital of Eastern Theater Command, between April 2024 and October 2024. Data included RTX dosing frequency, relapse events, peripheral CD20? B-cell counts, and ARA levels. With a 6-month observation period after the last RTX therapy, the children were divided into an ARA-positive group and an ARA-negative group based on ARA test results. Chi-square test, independent sample t-test, or Mann-Whitney U test were used to compare relapse rates and laboratory indicators between the two groups. The predictive value of ARA levels for relapse was evaluated using univariate receiver operating characteristic (ROC) curve analysis. Results:Among the 48 children (36 males, 12 females), the age of disease onset was 3.5 (2.0, 6.0) years, the ages at the first and last RTX treatments were 7.0 (5.0, 12.0) years and 9.5 (7.0, 13.0) years, respectively. The overall ARA positive rate was 29% (14/48). The relapse rate in the ARA-positive group was significantly higher than that in the negative group ( P<0.05). The ARA level was 0.01 (0.01, 5.88) μg/L, and all 12 children with ARA levels >5.88 μg/L relapsed. ROC curve analysis showed that ARA levels predicted relapse after RTX treatment in FRNS or SDNS children with an area under the curve (AUC) of 0.73, sensitivity of 0.50, specificity of 1.00, and an optimal cut-off value of 5.02 μg/L. All children received single-dose RTX therapy, with no significant difference in treatment frequency between the two groups ( P>0.05). At 3 months after the last rituximab therapy, CD20? B cell counts were significantly higher in the ARA-positive group ( P<0.05). During follow-up, 15% (7/48) of the children experienced infusion-related adverse reactions, with no significant difference in incidence between the two groups ( P>0.05). Conclusion:ARA is significantly associated with relapse in FRNS or SDNS children after RTX therapy.

Objective To explore the effect of plasma-activated gas(PAG)in promoting wound healing.Methods The pro-healing effect of PAG was explored by testing the effectiveness of PAG in promoting cell proliferation and healing of infected wounds.Cell proliferation assay:five different cells(i.e.,HSF,IHSMC,WPMY-1,HaCaT,and HFF)in logarithmic growth phase were inoculated into culture plates.After the cells grew adherently to the wall,the different cells were each grouped experimentally using a suitable time gradient.After the cells were treated with PAG for different time,their activity was detected by CCK-8 method.Animal infected wound healing assay:a wound of about 1.5 cm × 1.5 cm in size was created on the back of SD rats with sterile tweezers and scissors,and then the wound was infected with P.Aeruginosa with A600nm=6.5.After the infection was completed,the wounds were treated with PAG at regular intervals,and the experiment groups were subdivided according to the different treatment durations.Wound healing photographs and changes in relative wound area were used as indicators of healing performance.Results Cell proliferation assay:PAG treatment was effective in promoting cell proliferation for a reasonable period of time,while overdose led to cell death.Therefore,the dose of cells treated with plasma activation gas was defined as=W/N(J/cell),where W is the work consumed by the activation gas device during the treatment process and N is the number of cells.The three indexes(starting dose,optimal dose and safe dose range)were used to characterize the proliferative effect of PAG.Animal infected wound healing assay:the experimental groups all showed accelerated wound healing,so the optimal treatment time was used to characterize the pro-healing effect of PAG.The sterilization mode played a primary role,with an optimal treatment time of 2 min,and the pro-healing mode played a secondary role.The treatment conditions with the best overall healing effect were 2 min for the sterilization mode and 1 min for the pro-healing mode.Conclusion PAG has the effect of promoting cell proliferation and infected wound healing,and indicators can be summarized to quantitatively describe its effect,which is conducive to further standardization of PAG research and clinical utility.

Objective:To investigate the effect of age factor on glymphatic function in patients with Parkinson′s disease (PD) and its potential correlation with overall cognitive performance based on diffusion tensor imaging analysis along the perivascular space(DTI-ALPS) index.Methods:The study was cross-sectional. Clinical and imaging data of 77 PD patients (PD group) who attended the Provincial Hospital of Shandong First Medical University from October 2021 to June 2024 were retrospectively analyzed. In the same period, 30 healthy volunteers matched by age and gender were collected as the normal control (NC) group. All subjects underwent MRI scanning and DTI-ALPS index was calculated based on diffusion tensor imaging. Cognitive functions of 46 patients in the PD group were assessed using the mini-mental state examination (MMSE) and montreal cognitive assessment (MoCA) scores. Independent samples t-tests were used to compare the differences in DTI-ALPS index between the PD and NC groups. After adjusting for confounders, the relationship between DTI-ALPS and age was explored using partial correlation analyses, multiple linear regression models. A mediation model was further developed to explore the mediating effect of DTI-ALPS index between age and cognitive function scores. Results:The DTI-ALPS indices of PD and NC groups were 1.66±0.20 and 1.44±0.17, respectively, and the differences were statistically significant ( t=5.27, P<0.001). The age of patients in the PD group was negatively correlated with the DTI-ALPS index ( r=-0.54, P<0.001), and age (β=-0.467, P<0.001) was an independent influencer of DTI-ALPS index. The DTI-ALPS index was positively correlated with MMSE scores ( r=0.53, P<0.001) and positively correlated with MoCA scores ( r=0.56, P<0.001). The mediation model showed that the DTI-ALPS index fully mediated between age and MMSE scores and partially mediated between age and MoCA scores, with an effect share of 33.25%. Conclusion:Age is an independent risk factor for impaired glymphatic pathway in PD patients, and it may induce cognitive decline in PD patients by exacerbating glymphatic pathway impairment.