Oral squamous cell carcinoma (OSCC) is a common head and neck malignancy. Approximately 50% to 60% of patients with OSCC are diagnosed at a locally advanced stage (clinical staging III-IVa). Even with comprehensive and sequential treatment primarily based on surgery, the 5-year overall survival rate remains below 50%, and patients often suffer from postoperative functional impairments such as difficulties with speaking and swallowing. Programmed death receptor-1 (PD-1) inhibitors are increasingly used in the neoadjuvant treatment of locally advanced OSCC and have shown encouraging efficacy. However, clinical practice still faces key challenges, including the definition of indications, optimization of combination regimens, and standards for efficacy evaluation. Based on the latest research advances worldwide and the clinical experience of the expert group, this expert consensus systematically evaluates the application of PD-1 inhibitors in the neoadjuvant treatment of locally advanced OSCC, covering combination strategies, treatment cycles and surgical timing, efficacy assessment, use of biomarkers, management of special populations and immune related adverse events, principles for immunotherapy rechallenge, and function preservation strategies. After multiple rounds of panel discussion and through anonymous voting using the Delphi method, the following consensus statements have been formulated: 1) Neoadjuvant therapy with PD-1 inhibitors can be used preoperatively in patients with locally advanced OSCC. The preferred regimen is a PD-1 inhibitor combined with platinum based chemotherapy, administered for 2-3 cycles. 2) During the efficacy evaluation of neoadjuvant therapy, radiographic assessment should follow the dual criteria of Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 and immune RECIST (iRECIST). After surgery, systematic pathological evaluation of both the primary lesion and regional lymph nodes is required. For combination chemotherapy regimens, PD-L1 expression and combined positive score need not be used as mandatory inclusion or exclusion criteria. 3) For special populations such as the elderly (≥ 70 years), individuals with stable HIV viral load, and carriers of chronic HBV/HCV, PD-1 inhibitors may be used cautiously under the guidance of a multidisciplinary team (MDT), with close monitoring for adverse events. 4) For patients with a poor response to neoadjuvant therapy, continuation of the original treatment regimen is not recommended; the subsequent treatment plan should be adjusted promptly after MDT assessment. Organ transplant recipients and patients with active autoimmune diseases are not recommended to receive neoadjuvant PD-1 inhibitor therapy due to the high risk of immune related activation. Rechallenge is generally not advised for patients who have experienced high risk immune related adverse events such as immune mediated myocarditis, neurotoxicity, or pneumonitis. 5) For patients with a good pathological response, individualized de escalation surgery and function preservation strategies can be explored. This consensus aims to promote the standardized, safe, and precise application of neoadjuvant PD-1 inhibitor strategies in the management of locally advanced OSCC patients.

BACKGROUND:Osteoporotic fracture is the most serious complication of osteoporosis.Previous studies have demonstrated that gut microbiota has a regulatory effect on skeletal tissue and that gut microbiota has an important relationship with osteoporotic fracture,but the causal relationship between the two is unclear. OBJECTIVE:To explore the causal relationship between gut microbiota and osteoporotic fractures using Mendelian randomization method. METHODS:The genome-wide association study(GWAS)datasets of gut microbiota and osteoporotic fracture were obtained from the IEU Open GWAS database and the Finnish database R9,respectively.Using gut microbiota as the exposure factor and osteoporotic fracture as the outcome variable,Mendelian randomization analyses with random-effects inverse variance weighted,MR-Egger regression,weighted median,simple model,and weighted model methods were performed to assess whether there is a causal relationship between gut microbiota and osteoporotic fracture.Sensitivity analyses were performed to test the reliability and robustness of the results.Reverse Mendelian randomization analyses were performed to further validate the causal relationship identified in the forward Mendelian randomization analyses. RESULTS AND CONCLUSION:The results of this Mendelian randomization analysis indicated a causal relationship between gut microbiota and osteoporotic fracture.Elevated abundance of Actinomycetales[odds ratio(OR)=1.562,95%confidence interval(CI):1.027-2.375,P=0.037),Actinomycetaceae(OR=1.561,95%CI:1.027-2.374,P=0.037),Actinomyces(OR=1.544,95%CI:1.130-2.110,P=0.006),Butyricicoccus(OR=1.781,95%CI:1.194-2.657,P=0.005),Coprococcus 2(OR=1.550,95%CI:1.068-2.251,P=0.021),Family ⅩⅢ UCG-001(OR=1.473,95%CI:1.001-2.168,P=0.049),Methanobrevibacter(OR=1.274,95%CI:1.001-1.621,P=0.049),and Roseburia(OR=1.429,95%CI:1.015-2.013,P=0.041)would increase the risk of osteoporotic fractures in patients.Elevated abundance of Bacteroidia(OR=0.660,95%CI:0.455-0.959,P=0.029),Bacteroidales(OR=0.660,95%CI:0.455-0.959,P=0.029),Christensenellacea(OR=0.725,95%CI:0.529-0.995,P=0.047),Ruminococcaceae(OR=0.643,95%CI:0.443-0.933,P=0.020),Enterorhabdus(OR=0.558,95%CI:0.395-0.788,P=0.001),Eubacterium rectale group(OR=0.631,95%CI:0.435-0.916,P=0.016),Lachnospiraceae UCG008(OR=0.738,95%CI:0.546-0.998,P=0.048),and Ruminiclostridium 9(OR=0.492,95%CI:0.324-0.746,P=0.001)would reduce the risk of osteoporotic fractures in patients.We identified 16 gut microbiota associated with osteoporotic fracture by the Mendelian randomization method.That is,using gut microbiota as the exposure factor and osteoporotic fracture as the outcome variable,eight gut microbiota showed positive causal associations with osteoporotic fracture and another eight gut microbiota showed negative causal associations with osteoporotic fracture.The results of this study not only identify new biomarkers for the early prediction of osteoporotic fracture and potential therapeutic targets in clinical practice,but also provide an experimental basis and theoretical basis for the study of improving the occurrence and prognosis of osteoporotic fracture through gut microbiota in bone tissue engineering.

BACKGROUND:The causal relationship between modifiable factors such as lifestyle,metabolic characteristics,and nutritional intake and joint sports injuries has been increasingly recognized in clinical studies.However,the exact causal relationship between these modifiable factors and joint sports injuries remains unclear. OBJECTIVE:To investigate the causal relationship between modifiable factors and joint sports injuries using Mendelian randomization to provide a basis for sports injury prevention. METHODS:The GWAS dataset of intervening factors and joint sports injuries was obtained from publicly available data.The causal relationships between lifestyle,metabolic characteristics,nutritional intake,and joint sports injuries were explored using the inverse variance weighting method,the MR-Egger method,and the weighted median method.For sensitivity analyses,Cochran's Q test,MR-Egger regression,leave-one-out method,and MR-PRESSO were used to verify the stability and reliability of the results. RESULTS AND CONCLUSION:(1)In terms of lifestyle,coffee(OR=0.29,95%CI:0.10-0.79,P=0.016),and tea consumption(OR=0.41,95%CI=0.19-0.85,P=0.017)were associated with a decreased risk of ankle and foot joint sports injuries,and coffee consumption(OR=3.31,95%CI=1.02-10.73,P=0.046)was potentially causally associated with an increased risk of shoulder joint sports injuries;and never smoking(OR=0.78,95%CI=0.70-0.87,P=1.49×10-5)was significantly causally associated with a decreased risk of ankle and foot joint sports injuries.(2)In terms of metabolic characteristics,calcium levels(OR=0.88,95%CI=0.79-0.98,P=0.017)were potentially causally associated with a decreased risk of wrist and hand joint sports injuries.(3)In terms of nutritional intake,vitamin A intake(OR=1.08,95%CI:1.02-1.13,P=0.007)was potentially causally associated with increased risk of knee joint sports injury.(4)For the sensitivity analysis,Cochran's Q test showed the existence of heterogeneity(P<0.05),so the random effect model was used for the analysis.MR-Egger regression and MR-PRESSO test did not find evidence of pleiotropy(P>0.05),and the leave-one-out method showed that the results were stable after eliminating single nucleotide polymorphisms one by one.(5)This study preliminarily reveals the effects of modifiable factors,such as lifestyle,metabolic characteristics,and nutritional intake,on the risk of joint sports injuries.It provides valuable research evidence and guidance for the prevention of joint sports injuries.

Objective To develop a multivariate modeling and prediction approach using the data of influenza incidence, meteorological factors and PM_2.5 variables in Hefei City, and to provide new insights into multivariate modeling and prediction methods. Methods PM_2.5 data were transformed into fractal dimension data and, along with meteorological data, were incorporated into a ConvLSTM model. The performance of this model was compared with traditional ARIMAX and multivariate LSTM models. Results The ARIMAX model's testing set Mean Absolute Error (MAE) was 95.75, Root Mean Square Error (RMSE) was 176.72, and Index of Agreement (IA) was 0.396642. The multivariate LSTM model's testing set MAE was 22.18, RMSE was 43.06, and IA was 0.974611. For the fractal dimension-based ConvLSTM model, the testing set MAE was 17.37, RMSE was 32.25, and IA was 0.988149. Conclusion The fractal dimension effectively captures the complexity and self-similarity of PM_2.5 concentration, providing the model with richer feature information. The fractal dimension-based ConvLSTM model significantly outperforms the traditional ARIMAX model and the multivariate LSTM model in prediction accuracy and can be used for predicting the number of influenza cases.

Objective To investigate the epidemiology of elderly respiratory tract infection (RTI) cases in a hospital in Xuzhou region from 2020 to 2022. Methods The cases of RTI patients in a hospital were screened from May 2020 to December 2022, and 548 cases that met the criteria were included in the study. Patient case data were analyzed for symptoms, pathogen distribution, and differences in patient distribution under different screening conditions (age, disease, and season). Results More than 90.00% of the included RTI patients presented with symptoms of cough, sputum, wet rales and pleural effusion was less common. The top three comorbidities were cardiovascular disease (153 patients, 27.92%), cerebrovascular disease (133 patients, 24.27%), and gastrointestinal disease (105 patients, 19.16%).All 548 elderly patients tested positive for respiratory pathogens (100.00%). There were 540 cases of single pathogen infection (98.54%) and 8 cases of mixed infection (1.46%). The top five single pathogen infections were Pseudomonas aeruginosa (92 cases, 16.76%), Escherichia coli (78 cases, 14.21%), drug-resistant Staphylococcus aureus (69 cases, 12.57%), Klebsiella pneumoniae (65 cases, 11.84%), and Mycoplasma pneumoniae (46 cases, 8.38%). The highest detection rate of respiratory pathogens was found in patients >90 years old, whose main pathogens were Pseudomonas aeruginosa, Klebsiella pneumoniae and drug-resistant Staphylococcus aureus. The next highest rates of pathogen detection were found in patients aged 86-91 and 81-85 years, unlike patients >90 years, who had a higher rate of Escherichia coli detection. Unlike other age groups, patients <75 years old had a higher percentage of influenza B virus detection. The highest incidence of pneumonia was found in 45.62% (250 cases). Escherichia coli had the highest detection rate in acute bronchitis/episodes and pneumonia, respiratory syncytial virus had the highest detection rate in wheezing bronchitis, Klebsiella pneumoniae had the highest detection rate in bronchopneumonia, and Pseudomonas aeruginosa had the highest detection rate in fever. The highest detection rate of pathogens was found in fall (36.50%), followed by spring (27.01%). The distribution of pathogen infections in all seasons was matched with the results of pathogenicity testing. Streptococcus oxysporus had the highest number of infections in the fall (χ²=20.33, P<0.001). Conclusion Elderly respiratory tract infections in this region are most common in patients over 90 years old, with the highest incidence of pneumonia and high incidence in fall, and the pathogens are mainly Pseudomonas aeruginosa, Escherichia coli and drug-resistant Staphylococcus aureus. Attention to distinguish the above characteristics can provide some support for early diagnosis and treatment of respiratory infections in the elderly in this region.

Electromagnetic fields can regulate the fundamental biological processes involved in bone remodeling. As a non-invasive physical therapy, electromagnetic fields with specific parameters have demonstrated therapeutic effects on bone remodeling diseases, such as fractures and osteoporosis. Electromagnetic fields can be generated by the movement of charged particles or induced by varying currents. Based on whether the strength and direction of the electric field change over time, electromagnetic fields can be classified into static and time-varying fields. The treatment of bone remodeling diseases with static magnetic fields primarily focuses on fractures, often using magnetic splints to immobilize the fracture site while studying the effects of static magnetic fields on bone healing. However, there has been relatively little research on the prevention and treatment of osteoporosis using static magnetic fields. Pulsed electromagnetic fields, a type of time-varying field, have been widely used in clinical studies for treating fractures, osteoporosis, and non-union. However, current clinical applications are limited to low-frequency, and research on the relationship between frequency and biological effects remains insufficient. We believe that different types of electromagnetic fields acting on bone can induce various “secondary physical quantities”, such as magnetism, force, electricity, acoustics, and thermal energy, which can stimulate bone cells either individually or simultaneously. Bone cells possess specific electromagnetic properties, and in a static magnetic field, the presence of a magnetic field gradient can exert a certain magnetism on the bone tissue, leading to observable effects. In a time-varying magnetic field, the charged particles within the bone experience varying Lorentz forces, causing vibrations and generating acoustic effects. Additionally, as the frequency of the time-varying field increases, induced currents or potentials can be generated within the bone, leading to electrical effects. When the frequency and power exceed a certain threshold, electromagnetic energy can be converted into thermal energy, producing thermal effects. In summary, external electromagnetic fields with different characteristics can generate multiple physical quantities within biological tissues, such as magnetic, electric, mechanical, acoustic, and thermal effects. These physical quantities may also interact and couple with each other, stimulating the biological tissues in a combined or composite manner, thereby producing biological effects. This understanding is key to elucidating the electromagnetic mechanisms of how electromagnetic fields influence biological tissues. In the study of electromagnetic fields for bone remodeling diseases, attention should be paid to the biological effects of bone remodeling under different electromagnetic wave characteristics. This includes exploring innovative electromagnetic source technologies applicable to bone remodeling, identifying safe and effective electromagnetic field parameters, and combining basic research with technological invention to develop scientifically grounded, advanced key technologies for innovative electromagnetic treatment devices targeting bone remodeling diseases. In conclusion, electromagnetic fields and multiple physical factors have the potential to prevent and treat bone remodeling diseases, and have significant application prospects.

ObjectiveTo observe the clinical efficacy and possible mechanisms of Xianglian Huazhuo Granules （香连化浊颗粒， XHG） in the treatment of chronic atrophic gastritis with intestinal metaplasia. MethodsA total of 140 patients with chronic atrophic gastritis and intestinal metaplasia were randomly divided into a treatment group and a control group， with 70 cases in each group. The treatment group received 12.5 g of XHG orally， twice daily. The control group received 12.5 g of placebo orally， twice daily. Both groups were treated for 6 months. The traditional Chinese medicine （TCM） symptom scores， pathological types， serum tumor markers of the digestive system， and serum bile acids （TBA）， interleukin-23 （IL-23）， and Dickkopf-related protein 1 （DKK-1） levels were observed before and after treatment. Safety indicators and adverse events were recorded. After treatment， TCM syndrome efficacy and pathological types were evaluated， and patients were followed up for 18 months with gastric endoscopy and pathological results， which were compared with the results after treatment finished. ResultsTwo patients dropped out in the control group， and a total of 168 cases were included in the final analysis， 70 in the treatment group and 68 in the control group. The treatment group showed a significant reduction in TCM symptom scores， serum TBA， IL-23， and DKK-1 levels， and a significant increase in alpha-fetoprotein （AFP）， carbohydrate antigen 125 （CA125）， carbohydrate antigen 199 （CA199） levels； in the control group， carcinoembryonic antigen （CEA）， CA125， CA199 levels significantly increased （P＜0.05 or P＜0.01）； and carbohydrate antigen 242 （CA242） level in both the treatment group and the control group decreased significantly （P＜0.01）. The treatment group had lower TCM symptom scores and lower levels of serum TBA， IL-23， and DKK-1 compared to the control group （P＜0.05）. The effective rate for TCM syndrome efficacy in the treatment group was 80.00% （56/70）， significantly higher than the 20.59% （14/68） in the control group （P < 0.05）. The effective rate for pathological classification in the treatment group was 72.73% （8/11） for mixed intestinal metaplasia， significantly better than 46.15% （6/13） in the control group （P＜0.05）. No adverse events were reported in either group. Among 40 patients who had a follow-up endoscopy after one year， 21 were from the treatment group， of whom 11 showed reduced intestinal metaplasia， 9 showed no significant changes， and 1 had worsened； while 19 patients in the control group had 4 with reduced intestinal metaplasia， 13 with no significant changes， and 2 with worsened conditions. No cancer was detected in either group. The treatment group showed significantly better improvement in intestinal metaplasia on follow-up gastric endoscopy pathology than the control group （P＜0.05）. ConclusionXHG can significantly improve the clinical symptoms in patients with chronic atrophic gastritis and intestinal metaplasia and reduce the degree of mixed intestinal metaplasia. The mechanism may involve lowering serum TBA， DKK-1， and IL-23 levles， thus delaying the progression from inflammation to cancer.

The Expert Consensus on Clinical Application of Qinbaohong Zhike Oral Liquid in Treatment of Acute Bronchitis and Acute Attack of Chronic Bronchitis （GS/CACM 337-2023） was released by the China Association of Chinese Medicine on December 13^th， 2023. This expert consensus was developed by experts in methodology， pharmacy， and Chinese medicine in strict accordance with the development requirements of the China Association of Chinese Medicine （CACM） and based on the latest medical evidence and the clinical medication experience of well-known experts in the fields of respiratory medicine （pulmonary diseases） and pediatrics. This expert consensus defines the application of Qinbaohong Zhike oral liquid in the treatment of cough and excessive sputum caused by phlegm-heat obstructing lung， acute bronchitis， and acute attack of chronic bronchitis from the aspects of applicable populations， efficacy evaluation， usage， dosage， drug combination， and safety. It is expected to guide the rational drug use in medical and health institutions， give full play to the unique value of Qinbaohong Zhike oral liquid， and vigorously promote the inheritance and innovation of Chinese patent medicines.

Subarachnoid hemorrhage (SAH) is a serious intracranial hemorrhage characterized by acute bleeding into the subarachnoid space. The effects of shikonin, a natural compound from the roots of Lithospermum erythrorhizon, on oxidative stress and blood–brain barrier (BBB) injury in SAH was evaluated in this study. A rat model of SAH was established by endovascular perforation to mimic the rupture of intracranial aneurysms. Rats were then administered 25 mg/kg of shikonin or dimethylsulfoxide after surgery. Brain edema, SAH grade, and neurobehavioral scores were measured after 24 h of SAH to evaluate neurological impairment. Concentrations of the oxidative stress markers superoxide dismutase (SOD), glutathione (GSH), and malondialdehyde (MDA) in the brain cortex were determined using the corresponding commercially available assay kits. Evans blue staining was used to determine BBB permeability. Western blotting was used to quantify protein levels of tight junction proteins zonula occludens-1, Occludin, and Claudin-5. After modeling, the brain water content increased significantly whereas the neurobehavioral scores of rats with SAH decreased prominently. MDA levels increased and the levels of the antioxidant enzymes GSH and SOD decreased after SAH. These changes were reversed after shikonin administration. Shikonin treatment also inhibited Evans blue extravasation after SAH. Furthermore, reduction in the levels of tight junction proteins after SAH modeling was rescued after shikonin treatment. In conclusion, shikonin exerts a neuroprotective effect after SAH by mitigating BBB injury and inhibiting oxidative stress in the cerebral cortex.

Objective To identify and analyze risk factors for acute renal failure (ARF) following lung transplantation and to develop a predictive model. Methods Data for this study were obtained from the United Network for Organ Sharing (UNOS) database, encompassing patients who underwent unilateral or bilateral lung transplantation between 2015 and 2022. We analyzed both preoperative and postoperative clinical characteristics of the patients. A combined approach utilizing random forest and least absolute shrinkage and selection operator (LASSO) regression was employed to identify key factors associated with the incidence of ARF post-transplantation, based on which a nomogram model was developed. The predictive performance of the constructed model was evaluated in both training and validation sets, using receiver operating characteristic (ROC) curves and area under the curve (AUC) metrics to verify and compare model effectiveness. Results A total of 15 110 lung transplantation patients were included in the study, consisting of6 041 males and 9 069 females, with a median age of 62.00 years (interquartile range: 54.00 to 67.00). The analysis revealed statistically significant differences between postoperative renal dialysis and non-dialysis patients regarding preoperative lung diagnosis, estimated glomerular filtration rate (eGFR), mechanical ventilation, preoperative ICU treatment, extracorporeal membrane oxygenation (ECMO) support, infections occurring within two weeks prior to transplantation, Karnofsky Performance Status (KPS) score, waitlist duration, double-lung transplantation, and ischemia time (P<0.05). Five key variables associated with ARF after lung transplantation were identified through random forest and LASSO regression: recipients’ eGFR, preoperative ICU treatment, ECMO support, bilateral lung transplantation, and ischemia time. A nomogram model was subsequently established. Model evaluation demonstrated that the constructed predictive model achieved high accuracy in both training and validation sets, with favorable AUC values, confirming its validity and reliability. Conclusion This study identifies common risk factors for ARF following lung transplantation and introduces an effective predictive model with potential clinical applications.