In recent years， repetitive transcranial magnetic stimulation （rTMS） has garnered significant attention as a therapeutic approach for sleep disorders in the elderly. However， the prevailing rTMS protocols are predominantly developed based on normative neurophysiological data derived from young adults and fail to incorporate individualized parameters tailored to the brain characteristics of the elderly. To address this gap， the consensus development group synthesized the latest evidence from 2010 to 2025 and established a standardized rTMS protocol specifically for elderly patients with sleep disorders. Adhering to the Appraisal of Guidelines for Research and Evaluation II （AGREE II） framework， systematically screened randomized controlled trials （RCTs） and systematic reviews regarding rTMS in the treatment of sleep disorders across various conditions. Meanwhile， the Grading of Recommendations Assessment， Development and Evaluation （GRADE） system was employed to rigorously grade the quality of evidence and the strength of recommendations. This consensus guideline delineates precise rTMS protocols for the management of sleep disorders in the elderly， highlights the adjustment of stimulation intensity according to scalp-cortex distance recommends either MRI‑guided neuronavigation or the Beam F3/F4 heuristic approach for accurate target localization， thereby providing precise rTMS intervention protocol for sleep disorders in the elderly， aiming to enhance clinical efficacy while ensuring treatment safety. ［Funded by National Key Research and Development Program （number， 2023YFC3603200）； General Program of Shenzhen Science and Technology Innovation Commission （number， JCYJ20240813112859008， JCYJ20240813112900002）； Youth Program of Shenzhen Kangning Hospital （number， KN2023A004）； www.guidelines-registry.cn number， PREPARE-2026CN530］

Owing to its inherent advantages—such as being non-destructive, rapid, highly molecule-specific, and minimally interfered with by moisture—Raman spectroscopy has been widely adopted in the fields of skin barrier function assessment, monitoring the transdermal penetration of active cosmetic ingredients, and the identification and quality control of cosmetic products. Despite these strengths, the practical application of this technique faces a significant bottleneck: the strong fluorescence background generated by endogenous skin components and exogenous cosmetic additives. Endogenous skin substances, such as structural proteins (e.g., collagen and elastin), metabolic coenzymes (e.g., nicotinamide adenine dinucleotide), and pigments (e.g., melanin), together with exogenous cosmetic constituents like organic colorants, chemical sunscreens, and fragrances, often possess strong absorption and emission characteristics. When excited by lasers, these components produce a fluorescence background that can be 10⁶ to 10⁸ times stronger than the Raman scattering signals, effectively masking the inherently weak vibrational fingerprint information. In recent years, driven by the rapid development of optoelectronic hardware and artificial intelligence algorithms, fluorescence suppression strategies have evolved from isolated, single-method approaches into comprehensive, multi-level synergistic systems. These systems are categorized into three distinct tiers: sample preparation, signal acquisition, and data processing. At the sample preparation level, techniques such as photobleaching and surface-enhanced Raman spectroscopy (SERS) are employed to eliminate or bypass the generation of fluorescence at the source. At the signal acquisition level, instrumental improvements—including the use of long-wavelength near-infrared excitation (typically 785 nm or 1 064 nm), confocal spatial filtering, and shifted excitation Raman difference spectroscopy (SERDS)— are utilized to physically isolate Raman signals from the fluorescence background. Furthermore, at the data processing level, numerical baseline correction methods such as polynomial fitting, penalized least squares (e.g., airPLS, arPLS), wavelet transform, and derivative algorithms are increasingly integrated into the analytical pipeline to extract Raman spectral features from mixed signals without increasing hardware costs or acquisition time. This review provides a systematic categorization and critical evaluation of these fluorescence suppression methods, detailing their underlying principles, technical advantages, and inherent limitations in diverse experimental setups. By focusing on critical application scenarios—including skin barrier assessment, percutaneous absorption monitoring, the routine quality control of cosmetics, and the emerging field of portable on-site detection—this paper explores the current state of technique selection and optimization. Finally, the article discusses future development trends, emphasizing the necessity of constructing adaptive, tiered suppression strategies, developing intelligent and automated data processing algorithms, and promoting the integration of portable, multi-modal diagnostic devices. The objective of this review is to provide a comprehensive technical reference to facilitate the transition of Raman spectroscopy from a specialized laboratory tool into a routine, robust analytical platform for advancements in skin science and cosmetic research.

Objective:To construct and validate a predictive model and application program for stone recurrence after endoscopic retrograde cholangiopancreatography (ERCP) based on machine learning algorithms in patients with common bile duct stones (CBDS).Methods:A multicenter retrospective cohort study was conducted, 862 CBDS patients underwent ERCP from June 2020 to September 2023 in Changshu First People′s Hospital (data set 1, 759 cases, including a training set of 588 cases and a validation set of 171 cases) and Changshu Hospital of Traditional Chinese Medicine (data set 2, 103 cases, used as a test set). The demographics, medical history, ERCP procedural records and laboratory indices were collected. All patients were followed up for 1 year, and the stone recurrence was recorded. In training set, the feature selection was conducted by the least absolute shrinkage and selection operator (LASSO) algorithm, and a conventional Logistic regression model was constructed based on selected features. The 3 machine learning algorithms (gradient boosting machine model, extreme gradient boosting model and random forest model) and a conventional Logistic regression model (LASSO model) were trained to fit predictive models. The model performance was assessed by area under curve (AUC) of receiver operating characteristic curve. The model interpretability was analyzed by feature importance evaluation, Shapley additive explanations (SHAP) and force plots. The best-performing model was deployed as an online application by Streamlit framework (V1.36.0).Results:Among the 862 patients, 158 patients (18.33%) developed stone recurrence after ERCP. There were no statistical difference in demographics, medical history, ERCP procedural records and laboratory indices between training set and a validation set ( P>0.05). LASSO regression analysis result showed that 6 key variables (in descending order of significance: endoscopic sphincterotomy, common bile duct angulation, stone diameter, stone count, common bile duct diameter, and periampullary diverticulum) influencing stone recurrence. ROC curve analysis result showed that the random forest model exhibited the highest predictive performance (it had the largest AUC of 0.900). SHAP analysis result showed that common bile duct angulation, common bile duct diameter, stone diameter, endoscopic sphincterotomy and stone count were the top 5 contributing factors in the random forest model. Using Python, the random forest model was implemented into a Streamlit-based application with a user-friendly visual interface, providing predictive outcomes, confidence levels, SHAP force diagram and health recommendations. In the test set, the application program achieved an accuracy of 84.5% (87/103), sensitivity of 82.6% (19/23), and specificity of 85.0% (68/80). SHAP plots and force diagram intuitively illustrated the impact of key features on stone recurrence prediction, offering a clear visualization of each variable′s role within the model. Conclusions:The predictive model and application program based on the random forest machine learning algorithms demonstrate excellent predictive performance and practical usability in predicting stone recurrence after ERCP in patients with CBDS.

Objective To compare the effects of dexmedetomidine and midazolam on intraoperative blood pressure and postoperative 90-day outcome of endovascular treatment(EVT)in patients with acute anterior circulation large vessel occlusive stroke.Methods Retrospective consecutive patients with acute anterior circulation large vessel occlusion stroke who received EVT within 24 hours of onset,admitted to the Department of Neurology at the Second People's Hospital of Hefei from January 2024 to February 2025 were included.Patients were divided into the dexmedetomidine group and the midazolam group based on the choice of sedative in EVT.Baseline and clinical data were collected from patients,including sex,age,medical history(hypertension,diabetes,atrial fibrillation,stroke history),smoking history,blood pressure at admission(systolic,diastolic,mean arterial pressure),National Institutes of Health stroke scale(NIHSS)score at admission,trial of Org 10172 in acute stroke treatment(TOAST)classification,and site of vascular occlusion(internal carotid artery,M1 segment of the middle cerebral artery).Procedure related parameters,including intravenous thrombolysis before EVT,intraoperative use of tirofiban,modified thrombolysis in cerebral infarction(mTICI)grade,thrombectomy techniques(stent-retriever thrombectomy,aspiration thrombectomy,combined stent-retriever and aspiration thrombectomy,and other salvage measures),number of thrombectomy,time from onset to revascularization,time from puncture to revascularization,blood pressure during EVT(minimum systolic,minimum diastolic,and minimum mean arterial pressure),and blood pressure at the end of EVT(systolic,diastolic,and mean arterial pressure).The primary outcome was good prognosis at 90 days after EVT(modified Rankin scale score of 0-2 at 90 days),while secondary outcome was＞20％decrease in mean arterial pressure during EVT,early neurological improvement(ENI;a decrease on NIHSS score no less than 8 or a reduction of NIHSS score to 0-1 at 24 hours after EVT),and early neurological deterioration(END;an increase of more than 2 points on the NIHSS at 24 hours after procedure).Safety outcomes included any intracranial hemorrhage within 48 hours after EVT,symptomatic intracranial hemorrhage within 48 hours after EVT(sICH;intracranial hemorrhage confirmed by head CT leading to neurological deterioration,with an increase in NIHSS score of at least 4 points,or the presence of potentially fatal intracranial hemorrhage on head CT),pneumonia within 2 weeks after EVT,and the 90-day mortality after EVT.The baseline and clinical data,EVT conditions,primary outcome,secondary outcome,and safety indicators were compared between the two groups.Univariate Logistic regression analysis was used to screen the variables associated with a decrease in mean arterial pressure＞20％during EVT in patients with acute anterior circulation large vessel occlusive stroke.Variables with P＜0.15 and those considered potentially influential based on clinical experience were included in multivariate Logistic regression analysis to identify predictors of a＞20％decrease in mean arterial pressure during EVT in patients with acute anterior circulation large vessel occlusive stroke.Results A total of 93 patients with acute anterior circulation large vessel occlusive stroke who underwent EVT were included,comprising 51 males and 42 females,aged 34 to 99 years,with an average of(71±13)years old.Among them,63 patients were in the dexmedetomidine group,and 30 patients were in the midazolam group.33 patients showed＞20％decreases in mean arterial pressure during EVT,while 60 patients had ≤20％decreases.(1)Compare with the midazolam group,the proportion of female patients in the dexmedetomidine group was lower(36.5％[23/63]vs.63.3％[19/30],P=0.015),and the age was younger([69±13]years vs.[77±13]years,P=0.005).There were no statistically significant differences in other baseline and clinical data(all P＞0.05).(2)In comparison with the midazolam group,the dexmedetomidine group had a higher proportion of patients with more thrombectomy procedures(1.00[1.00,2.00]times vs.1.00[1.00,1.25]times,P=0.011),END(27.0％[17/63]vs.6.7％[2/30],P=0.023),sICH within 48 hours(19.0％[12/63]vs.3.3％[1/30],P=0.041),and a decrease in mean arterial pressure＞20％during EVT(42.9％[27/63]vs.20.0％[6/30],P=0.031).There were no statistically significant differences in the remaining EVT conditions,primary outcome,secondary outcome,and safety indicators(all P＞0.05).(3)The results of univariate Logistic regression analysis showed that diastolic blood pressure at admission(P=0.002),mean arterial pressure at admission(P=0.009),and dexmedetomidine sedation(P=0.036)were the influencing factors of a decrease＞20％in mean arterial pressure during EVT in patients with acute anterior circulation large vessel occlusion stroke.(4)The results of multivariate Logistic regression analysis showed that dexmedetomidine sedation(OR,3.271,95％CI 1.057-10.126,P=0.040)and higher diastolic blood pressure on admission(OR,1.105,95％CI 1.006-1.213,P=0.037)were independent predictors of a decrease over 20％in mean arterial pressure during EVT in patients with acute anterior circulation large vessel occlusive stroke.Conclusions Dexmedetomidine is an independent predictor of an over 20％decrease in mean arterial pressure during EVT in patients with acute anterior circulation large vessel occlusive stroke,but there is no statistically significant differences in the rate of good neurological function at 90 days and 90-day mortality postoperatively between the two groups.Further prospective randomized controlled studies are needed.

Machine learning,as a core branch of artificial intelligence,has gradually demonstrated significant potential in the field of dentition defect repair in recent years.By employing techniques such as data mining and pattern recognition,machine learning has been applied in various aspects including oral implant restoration,fixed bridge design,and fabrication of removable partial dentures.This paper seeks to provide a comprehensive review of machine learning applications within the aforementioned three aspects.It endeavors to assess the current developmental landscape and chart a course for future investigative endeavors,in hopes of offering a reference for re-search on machine learning in prosthodontics.

Objective To explore the value of analysis on the incidence of healthcare-associated infection(HAI)based on disease diagnosis-related grouping(DRG),case mix index(CMI),and relative weight(RW).Methods All discharged cases,DRG and HAI status in a tertiary first-class general hospital from January 1 to December 31,2023 were analyzed retrospectively.Incidences of HAI in different departments were adjusted and compared by CMI.Incidences of HAI in different DRG groups were adjusted by RW.Results Among the 47 695 cases included in the analysis,757 were HAI cases,including 225 DRG groups.The department of critical care medicine had the highest incidence of HAI(11.98％).After CMI adjustment,departments with higher incidence of HAI were main-ly the department of respiratory and critical care medicine(3.96％),department of critical care medicine(3.04％),and department of neurology(2.85％),et al.DRG groups with the top five high incidence of HAI were AH11(tracheotomy and with ventilator support ≥96 hours or extracorporeal membrane oxygenation[ECMO],accompa-nied by major complications and comorbidity[MCC],50.00％),BC29(ventricular shunt and revision surgery,31.43％),BB21(craniotomy other than trauma,accompanied by MCC,27.56％),BB11(craniotomy of brain trauma,accompanied by MCC,26.32％),and GB1A(major surgery of esophagus,stomach,and duodenum,accompanied by major or moderate complications and comorbidity,16.00％).After RW adjustment,the DRG groups with the top five high incidence of HAI were ES21(respiratory system infection/inflammation,accompanied by MCC,5.89％),BR21(cerebral ischemic disease,accompanied by MCC,5.17％),FR11(heart failure,shock,accompanied by MCC,4.80％),BC29(4.57％)and AH11(3.57％).Conclusion Analyzing the incidence of HAI based on CMI and RW can help to identify key departments and disease groups for infection prevention and control,and provide reference for precise prevention and control of HAI in the new era.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective To explore the brain damage of SD rats under different time points of hypobaric hypoxia exposure.Methods A rat high-altitube cerebral edema(HACE)model was constructed by simulating an altitude of 6 000 m in a hypobaric hypoxia animal experimental chamber.Thirty-six SD male rats were randomly divided into the control group and the hypobaric hypoxia exposure 3,7 and 14 d groups,with 9 rats in each group.Except for the control group,the rats in each group were continuously exposed to hypobaric hypoxia for 3,7,and 14 d.At the end of the modeling period,serum was collected by blood sampling via the abdominal aorta,and brain tissue samples were taken.The wet-to-dry ratio(W/D)of brain tissue was calculated,and the levels of relevant oxidative enzymes in serum and brain tissue were measured.The expression levels of hypoxia-inducible factor-1α(HIF-1α)and aquaporin 4(AQP4)mRNAs in brain tissue were detected by real-time fluorescence quantitative polymerase chain reaction.Results The W/D of brain tissues in the control group and the group exposed to hypobaric hypoxia for 3,7 and 14 d were 4.46±0.12,4.98±0.16,5.07±0.18 and 4.95±0.07;the superoxide dismutase contents were(111.86±2.45),(90.73±1.48),(79.64±2.56)and(55.33±1.45)U·g-1;the glutathione contents were(126.91±5.18),(125.26±1.53),(56.20±2.17)and(122.73±1.78)μg·mL-1;the malondialdehyde contents were(230.94±2.00),(362.65±3.28),(407.34±3.47)and(237.50±1.59)nmol·g-1;the relative expression levels of HIF-1 α mRNA were 1.00±0,2.99±0.49,4.72±0.49 and 1.91±0.28;the relative expression levels of AQP4 mRNA were 1.00±0,2.62±0.34,8.38±0.84 and 5.27±0.42,respectively.Statistically significant differences were found between the above indexes in the 3,7 and 14 d of hypobaric hypoxia exposure group compared with the control group(P＜0.05,P＜0.01).Conclusion Different time of hypobaric hypoxia exposure can up-regulate the expression of AQPs proteins in HACE rats and cause the disruption of the blood-brain barrier,and the HACE model constructed in the hypobaric hypoxia chamber with 6 000 m intervention for 7 d was more stable.

Objective To explore the effects of different nerve blocks under ultrasound guidance on the expression of inflammatory factors after total hip replacement in the elderly,and its correlation with postoperative cognitive dysfunction(POCD).Methods A total of 100 elderly patients who underwent total hip replacement in our hospital from February to November 2023 were selected as the research objects,and they were divided into the femoral nerve block(FNB)group and the pericapsule nerve group block(PNGB)group according to different nerve block methods during the operation.The expression of inflammatory factors such as serum interleukin-1β(IL-1β),interleukin-6(IL-6),interleukin-10(IL-10),tumor necrosis factor-α(TNF-α)and tumor necrosis factor-β(TNF-β)1 day before surgery,6 hours after anesthesia,1 day after surgery,and 3 days after surgery of patients in the two groups were compared.The cognitive function of patients was evaluated by the mini-mental state examination(MMSE)score,and the pain of patients was evaluated by visual analogue scale(VAS)score.GEE model was used to evaluate the effects of two kinds of nerve block on the expression of inflammatory factors.Logistic regression was used to analyzed the correlation between postoperative inflammatory factors and POCD in patients.Results The levels of IL-1β,IL-6,IL-10,TNF-α and TNF-β 1 day after operation in the PNGB group were higher than those in the FNB group,and the differences were statistically significant(P<0.05).The MMSE score 1 day after surgery in the PNGB group was significantly higher than that in the FNB group(P<0.05),and the VAS score 3 days after surgery was significantly lower than that in the FNB group(P<0.05).GEE model showed that PNGB has a greater impact on IL-1β,IL-6,IL-10,TNF-α,and TNF-β.IL-1β,IL-6,IL-10,TNF-α,and TNF-β were all independently related to POCD induced by two different nerve blocks(P<0.05).Conclusion PNGB can effectively inhibit pro-inflammatory factors,reduce inflammatory stress responses,and maintain the balance of inflammatory factors.Inflammatory factors are independently related to POCD induced by different nerve blocks.With the occurrence of inflammatory stress response,the risk of POCD in patients increases.

Objective To design an 8-channel gene analyzer to take the place of the widely used gene analyzer with problems in inconvenient consumable replacement and short storage time of electrophoresis polymer.Methods The 8-channel gene analyzer had its mechanical components composed of an automatic sample loading table,a polymer injection module,a high-voltage temperature control module,an optical module and an integrated U box,its electrical control system made up of a host computer(an embedded computer)and three slave computers(a sampling control board,a polymer injection control board and a high-voltage temperature control board).The automatic sample loading table involved in four motors and transmission systems for x,y,z directions and optical alignment,the transmission systems adopted mainly belt drive mode and the optical alignment motor had its threads with an anti-backlash structure;the polymer injuection module was manipulated by the polymer injection control board,and the polymer block was made of highly transparent acrylic material;the high-voltage temperature control module realized the regulation of electrophoresis voltage and the detection of electrophoresis current by the low-ripple precision high-voltage power supply,and controlled the temperature of the heating furnace by the proportional-integral-differential(PID)algorithm;the optical module consisted of an excitation module and a light-receiving module,which had the base of the reflector made of low expansion coefficient alloy material;the integrated U box had the electrophoresis polymer,capillary array,polymer block and anode buffer in a plastic housing;the host computer had the data acquisition software programmed with C# and C++,and the slave computers were controlled by STM32 SCM.Results The 8-channel gene analyzer had no significant differences with the widely used ABI3500 gene analyzer in resolution,precision accuracy and clinical results.Conclusion The 8-channel gene analyzer gains advantages in consumable replacement and storage time of electrophoresis polymer,and can meet the requirements for gene sequencing.[Chinese Medical Equipment Journal,2025,46(2):24-30]