Oropharyngeal squamous cell carcinoma(OPSCC)is a malignant tumor originating from the squamous epithelium of the oro-pharyngeal mucosa,accounting for more than 90％of oropharyngeal malignancies.In recent years,human papillomavirus(HPV)infec-tion has become one of the primary etiological factors of oropharyngeal squamous carcinoma.The incidence of HPV-associated oropharyn-geal squamous carcinoma has been rising annually,with a noticeable trend toward younger populations,posing a significant threat to hu-man health.Due to the distinct biological behavior and clinical characteristics of HPV-associated oropharyngeal squamous carcinoma com-pared to its non-HPV-related counterpart,the diagnostic and treatment strategies for oropharyngeal squamous carcinoma have undergone substantial changes.Prevention and screening for oropharyngeal squamous carcinoma are of critical importance.The diagnostic and treat-ment process involves multi-disciplinary collaboration,including oral and maxillofacial surgery,otolaryngology,head and neck surgery,oncology,radiology and pathology.Based on evidence from clinical practice,a comprehensive,integrated diagnostic and therapeutic ap-proach has been established,centered around the concept of"prevention,screening,diagnosis,treatment,and rehabilitation",covering the entire patient lifecycle and providing a valuable reference for clinical practice.

Objective:To establish a rapid quantitative model of sodium chloride content in Halitum of traditional Chinese medicine by using X-ray diffraction technology and machine learning algorithm.Methods:The data of X-ray diffraction patterns of 90 batches of Halitum samples were collected,and the rapid prediction models of X-ray diffraction were constructed by using partial least squares(PLS),support vector regression(SVR)long short-term memory(LSTM)according to the reference values determined by the content determination method of Halitum in the Chinese Pharmacopoeia 2020 edition.Results:The data preprocessed by multivariate scatter correction(MSC)and selected by competitive adaptive reweighted sampling(CARS)were better in PLS model and LSTM model.The data pretreated by standard normal transformation(SNV)and selected by CARS feature variable perform well in SVR.Conclusion:The three models show good prediction potential,which shows that the combination of X-ray diffraction technology and machine learning algorithm is feasible for accurate prediction of the content of Halitum in traditional Chinese medicine.

Objective:To establish a rapid quantitative model for the determination of moisture,extractives,and content in Pollen Typhae.Methods:Near-infrared spectra of 91 batches of Pollen Typhae samples were collected.Spectral preprocessing was performed using S-G,MSC,SNV,and CWT methods.Variable selection was conducted using CARS,SPA,and VIP methods,and compared with full-spectrum modeling.Partial least squares(PLS)mod-els were established for the quantitative determination of moisture,total ash,extractives,and content.The model performance was evaluated by calculating the coefficient of determination for the calibration set and validation set(R2 c,R2v),root mean square error of calibration and validation(RMSEc,RMSEv),and residual prediction devia-tion(RPD).Results:The PLS models for moisture,extractives,and content in Pollen Typhae showed R2c and R2v values greater than 0.9,RMSEc and RMSEv values approaching 0,and RPD values greater than 3.Conclusion:In this study,near-infrared spectroscopy was used to construct quantitative prediction models for moisture,extractives,typhaneoside,and isorhamnetin-3-O-neohesperidoside content in Pollen Typhae.This method enables rapid detection of the main quality control indicators of Pollen Typhae,providing strong technical support for its quality supervision.

Objective To understand the current situation and dynamic changing trends of healthcare-associated infection(HAI)in a tertiary first-class hospital in the northwest of Hunan Province from 2015 to 2024,and provide scientific basis for optimizing infection control strategies.Methods A single-day cross-sectional survey method was employed to investigate the HAI prevalence rates of hospitalized patients on the given survey day each year from 2015 to 2024.The standardized survey protocol on prevalence rate issued by the National Medical Institution Infec-tion Surveillance Network was strictly adhered,lanqingting real-time HAI monitoring management platform was adopted to retrieve cases from the hospital information system,and R4.2.2 was applied for statistical analysis.Results From 2015 to 2024,the prevalence rate of HAI decreased from 3.03％in 2015 to 1.76％in 2024(Z=-3.37,P＜0.001),and the HAI case prevalence rate decreased from 3.55％in 2015 to 2.20％in 2024(Z=-2.81,P=0.005).Department of critical care medicine continuously had the highest HAI case prevalence rate,which presented a downward trend over time(Z=-2.84,P=0.004).The main site of HAI was lower respiratory tract,accounting for 39.36％to 48.15％,bloodstream infection increased from 3.57％in 2015-2016 to 10.60％in 2023-2024(Z=2.41,P=0.016).A total of 302 strains of HAI pathogens were detected,including 212 strains(70.20％)of Gram-negative bacteria,mainly Pseudomonas aeruginosa(n=55,18.21％),Escherichia coli(n=45,14.90％),Acinetobacter baumannii(n=33,10.93％),and Klebsiella pneumoniae(n=31i,10.26％).65 strains(21.52％)of Gram-positive bacteria were identified,with Enterococcus faecium(n=19,6.29％)and Staphylococcus aureus(n=18,5.96％)accounting for the highest proportions.25 fungal strains(8.28％)were detected,mainly Candi-da albicans(n=11,3.64％).The use rate of antimicrobial agents showed a downward trend over the past decade(Z=-4.01,P＜0.001).Therapeutic antimicrobial use accounting for 82.42％,and its proportion increased over time(Z=6.02,P＜0.001).Prophylactic antimicrobial use accounted for 16.42％,showing a decreasing trend(Z=-2.75,P＜0.001).The pathogen detection rate presented an upward trend over the past decade(Z=13.01,P＜0.001).Conclusion The prevalence rate and case prevalence rate of HAI present a downward trend in this hospi-tal.In the future,it is necessary to establish a monitoring data-based dynamic analysis mechanism,achieve timely feedback and intervention in data monitoring,pay attention to high-risk links in department of critical care medicine,implement precise prevention and control mearsures,perform targeted prevention and control for lower respiratory tract,urinary tract,and bloodstream infection,optimize diagnosis and treatment processes,use antimicrobial agents rationally,and pay attention to the prevalence trend of Gram-negative bacteria.

In recent decades,the incidence of human papillomavirus(HPV)-associated oropharyngeal squamous cell carcinoma(OPSCC)has shown a marked increase.Significant changes have also occurred in the OPSCC diagnosis and treatment paradigm.Deter-mining HPV status prior to treatment is now essential,and radiotherapy/chemotherapy,immunotherapy,and minimally invasive surgical techniques have progressively emerged as key modalities for managing OPSCC.However,alongside these paradigm shifts,a comprehen-sive technical consensus guiding the entire diagnostic and therapeutic process for OPSCC patients is currently lacking.Given China's large population base and the rising incidence of OPSCC,an expert panel convened to develop a clinical technical consensus on OPSCC diagno-sis and management tailored to China's specific context.This consensus aims to further enhance and standardize understanding of OPSCC management techniques among relevant healthcare professionals.

Oral squamous cell carcinoma(OSCC)is a malignant lesion originating from the oral mucosal squamous epithelium,account-ing for over 80％of oral and maxillofacial malignancies.Key etiological factors include tobacco,alcohol abuse,and betel quid chewing.In China,its incidence has shown an overall upward trend,posing a significant threat to public health.OSCC exhibits high local invasive-ness,making early diagnosis critical for improving prognosis.Its clinical management requires close multidisciplinary collaboration among oral and maxillofacial surgery,head and neck surgery,radiation oncology,medical oncology,reconstructive surgery,radiology,patholo-gy,and nutritional support teams.Given the increasing disease burden of OSCC and rapid development of multidisciplinary collaborative models,an expert panel has formulated this integrated management consensus based on evidence-based medicine and extensive deliber-ation.Centered on the'Prevention-Screening-Diagnosis-Treatment-Rehabilitation'framework,the consensus provides comprehensive guidance for the entire disease course of OSCC patients,aiming to standardize clinical practice.

Objective:To establish a rapid quantitative model of sodium chloride content in Halitum of traditional Chinese medicine by using X-ray diffraction technology and machine learning algorithm.Methods:The data of X-ray diffraction patterns of 90 batches of Halitum samples were collected,and the rapid prediction models of X-ray diffraction were constructed by using partial least squares(PLS),support vector regression(SVR)long short-term memory(LSTM)according to the reference values determined by the content determination method of Halitum in the Chinese Pharmacopoeia 2020 edition.Results:The data preprocessed by multivariate scatter correction(MSC)and selected by competitive adaptive reweighted sampling(CARS)were better in PLS model and LSTM model.The data pretreated by standard normal transformation(SNV)and selected by CARS feature variable perform well in SVR.Conclusion:The three models show good prediction potential,which shows that the combination of X-ray diffraction technology and machine learning algorithm is feasible for accurate prediction of the content of Halitum in traditional Chinese medicine.

Objective:To establish a rapid quantitative model for the determination of moisture,extractives,and content in Pollen Typhae.Methods:Near-infrared spectra of 91 batches of Pollen Typhae samples were collected.Spectral preprocessing was performed using S-G,MSC,SNV,and CWT methods.Variable selection was conducted using CARS,SPA,and VIP methods,and compared with full-spectrum modeling.Partial least squares(PLS)mod-els were established for the quantitative determination of moisture,total ash,extractives,and content.The model performance was evaluated by calculating the coefficient of determination for the calibration set and validation set(R2 c,R2v),root mean square error of calibration and validation(RMSEc,RMSEv),and residual prediction devia-tion(RPD).Results:The PLS models for moisture,extractives,and content in Pollen Typhae showed R2c and R2v values greater than 0.9,RMSEc and RMSEv values approaching 0,and RPD values greater than 3.Conclusion:In this study,near-infrared spectroscopy was used to construct quantitative prediction models for moisture,extractives,typhaneoside,and isorhamnetin-3-O-neohesperidoside content in Pollen Typhae.This method enables rapid detection of the main quality control indicators of Pollen Typhae,providing strong technical support for its quality supervision.

Oral squamous cell carcinoma(OSCC)is a malignant lesion originating from the oral mucosal squamous epithelium,account-ing for over 80％of oral and maxillofacial malignancies.Key etiological factors include tobacco,alcohol abuse,and betel quid chewing.In China,its incidence has shown an overall upward trend,posing a significant threat to public health.OSCC exhibits high local invasive-ness,making early diagnosis critical for improving prognosis.Its clinical management requires close multidisciplinary collaboration among oral and maxillofacial surgery,head and neck surgery,radiation oncology,medical oncology,reconstructive surgery,radiology,patholo-gy,and nutritional support teams.Given the increasing disease burden of OSCC and rapid development of multidisciplinary collaborative models,an expert panel has formulated this integrated management consensus based on evidence-based medicine and extensive deliber-ation.Centered on the'Prevention-Screening-Diagnosis-Treatment-Rehabilitation'framework,the consensus provides comprehensive guidance for the entire disease course of OSCC patients,aiming to standardize clinical practice.

Objective:To estimate the burden of influenza-associated outpatient consultations in China from 2011 to 2021 surveillance years to provide a reference for developing influenza prevention, control strategies, and vaccination policies.Methods:Data on influenza-like illness (ILI) and virological confirmation of sentinel specimens from 2011 to 2021 surveillance years were extracted from China's national sentinel surveillance system. Generalized additive models were fitted to estimate influenza-associated excess ILI outpatient burden, accounting for seasonal baselines and meteorological factors.Results:Influenza was associated with an average of 1.66 (95% CI: 1.51-1.80) excess ILI consultations per 1 000 person-years (py) in China each year from 2011 to 2021 surveillance years. The influenza-associated outpatient burden was similar across different virus types/subtypes. Influenza A(H1N1)pdm09 led to a higher rate of influenza- associated ILI consultations [0.65 (95% CI: 0.53-0.76) per 1 000 py] compared to other types/subtypes. The age groups with the highest burdens were children aged 0-4 years and 5-14 years, with excess outpatient consultation rates of 15.23 (95% CI: 13.73-16.73) per 1 000 py and 13.53 (95% CI: 12.49-14.52) per 1 000 py, respectively. Conclusions:Influenza caused many outpatient consultations in China, particularly among children aged 0-14. Continuous influenza monitoring and disease burden assessment should be conducted, and close attention should be paid to the changing trends of various influenza virus types/subtypes. When formulating vaccination strategies, priority should be given to recommending vaccination for high-risk populations, such as children.