Objective To study the photodynamic performance and the killing effect of photodynamic therapy on lung cancer of novel chlorin compounds 2-（4-（5,15,20-triphenyl-7H,8H-porphyrin-10-yl） phenoxy） acetic acid（D1）and 4-（4-（5,15,20-triphenyl-7H,8H-porphyrin-10-yl） phenoxy） butanoic acid （D2）. Methods The ultraviolet visible absorption spectrum and fluorescence spectrum of D1 and D2 were determined. The singlet oxygen generation capacity of D1 and D2 was measured by using DPBF as singlet oxygen capture agent. Fluorescence assay was used to detect the cellular phagocytosis rate of the compounds in A549 cells, and MTT assay was used to detect their dark toxicity and phototoxicity. A nude mouse model of lung cancer was established to investigate the antitumor activity of the compounds mediated photodynamic action in vivo, and the blood concentration of D2 in nude mice, its distribution in tumor tissue and skin tissue were further detected. Results D1 and D2 had strong absorption at 652 nm with the best excitation wavelength at 429 nm and 427 nm, and the optimal emission wavelength was at about 659 nm. They also had a higher singlet oxygen generation rate than the control drug m-THPC. D1 and D2 had no dark toxicity at concentrations below 10 μmol/L, and could be ingested by A549 cells, basically reaching saturation in 18~24 hours. After laser irradiation at 650 nm wavelength, D1 and D2 showed significant antitumor activity in vivo and in vitro （P<0.01）. However, D2 could selectively accumulate in tumor tissues after administration, and the optimal treatment time was less than 30 min after administration. Conclusion D2 had excellent photodynamic antitumor activity and could selectively aggregate in tumor tissues, which had the potential to be a candidate drug for photosensitizer and treatment of lung cancer with independent intellectual property rights, and was worth further research.

ObjectiveTo investigate the value of predictive models established based on machine learning methods in predicting the risk of metabolic associated fatty liver disease （MAFLD）， and to analyze its key risk factors. MethodsA retrospective analysis was performed for the 50 variables of 2 168 healthy individuals who underwent physical examination in Department of Health Assessment， Xiyuan Hospital， China Academy of Chinese Medical Sciences， from January 2021 to December 2024， including body composition， past history， and laboratory tests， and according to whether they were diagnosed with MAFLD or not， they were divided into MAFLD group with 265 individuals and non-MAFLD group with 1 903 individuals. The Mann-Whitney U test was used for comparison of continuous data between two groups， and the chi-square test was used for comparison of categorical data between two groups. Randomly split the research data into a training set and a validation set in a 70% to 30% ratio. Predictive factors were screened from the training set data using univariate analysis， LASSO regression， and multivariate Logistic regression analysis. Predictive models were then constructed using seven machine learning methods： Logistic regression， decision tree， random forest （RF）， eXtreme gradient boosting， light gradient boosting machine， support vector machine， and artificial neural network. Model performance was evaluated by plotting receiver operating characteristic curve for the validation set and calculating the area under the curve （AUC）， sensitivity， specificity， and Youden index for each model. Furthermore， the SHapley Additive exPlanation （SHAP） method was used to analyze the contribution of variables in the optimal model. ResultsThe prevalence rate of MAFLD among the 2 168 subjects was 12.22% （265/2 168）. Smoking， diastolic blood pressure， phase angle， visceral fat area， muscle fat ratio， waist-to-hip ratio， aspartate aminotransferase， non-HDL-C/HDL-C ratio， triglyceride-glucose index， and gallstones were independent risk factors for MAFLD （all P<0.05）. The seven predictive models of support vector machine， eXtreme gradient boosting， decision tree， light gradient boosting machine， artificial neural network， RF， and Logistic regression had an AUC of 0.738， 0.754， 0.757， 0.786， 0.795， 0.796， and 0.815， respectively， in the validation set， among which the RF model had the best discriminatory ability （AUC=0.796， 95% confidence interval： 0.754 — 0.839）， with a sensitivity of 81.01%， a specificity of 63.16%， and a Youden index of 44.17%. The SHAP analysis showed that visceral fat area， waist-to-hip ratio， and diastolic blood pressure were the top three predictive factors in terms of importance. ConclusionThe RF model， constructed based on body composition and clinical indicators， has a good performance in predicting the risk of MAFLD， and its interpretability can help to identify high-risk individuals in the early stage in clinical practice.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Dental implantology has developed rapidly for over half a century,since pure titanium(99.7％)dental cylindrical threaded implants were exploited and osseointegration was introduced in 1960s by Prof.Br?nemark.The long term retention rates of 10 years or more are over 95％.However,the biological complications jeopardize the long term effects of dental implant treatment seriously.The prevalence of dental implant biological complications varies greatly among different reports resulting from the disparities on the defini-tions of dental implant biological complications.After analyzing and summarizing the major opinions proposed internationally in recent years,the consensus for the definition of dental implant biological complications has been reached.Generally the dental implant biologi-cal implications can be classified into early stage(before restoration)biological complications and late stage(after restoration)biological complications.The early stage biological complications include acute and chronic infections,pain,soft tissue deficiency,and osseointegration failure,etc.The late stage complications include peri-implant diseases(peri-implant mucositis and peri-implantitis),soft tissue deficiency around implant,implant loosening and dropping off,etc.The various risk factors related to different dental implant biological complications,the strategies of the prevention and treatment for the dental implant biological complications have been discussed comprehensively,and the consensus has been reached.It is aimed to advocate the dentist to pay more attention to the early prevention of the biological implant complications,to promote more researches on the implant biological complications,and to help elevate the level of dental implantology in our country.

Objective:To observe the effects of Maxing Loushi decoction on the inflammatory response and inflammatory indicators in mice with chronic obstructive pulmonary disease (COPD) models.Methods:Thirty-six BALB/C mice were randomly divided into 4 groups by random number table method: 10 mice in the COPD model group (referred to as the model group), 10 mice in the Maxing Loushi decoction group (referred to as the traditional Chinese medicine group), 10 mice in the programmed death receptor-1 (PD-1) inhibitor group (referred to as the control group), and 6 mice in the normal group. The COPD models of mice in the model group, the traditional Chinese medicine group and the control group were prepared by cigarette smoking combined with lipopolysaccharide (LPS) induction method. During the modeling process, the model group and the traditional Chinese medicine group were respectively given normal saline and Maxing Loushi decoction by gavage. The control group was given intraperitoneal injection of PD-1 inhibitor, while the normal group was given intragastric administration of normal saline. Pathological changes of lung tissues in each group of mice were detected by HE staining. The levels of inflammatory factors [monocyte chemotactic protein-1 (MCP-1), macrophage inflammatory protein-1α (MIP-1α), interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α)] in the plasma and alveolar lavage fluid (BALF) of mice in each group were determined by enzyme-linked immunosorbent assay (ELISA). The effects of Maxing Loushi decoction intervention on inflammatory responses and inflammatory factors were evaluated.Results:The lung tissue structure in the normal group was basically normal. There was no thickening of the alveolar walls, no infiltration of neutrophils in the tissues, and no obvious inflammatory infiltration. In the model group, the lung tissue structure was slightly abnormal. A small amount of alveolar atrophy could be observed, the alveolar walls were slightly thickened, and inflammatory infiltration could be seen. In the traditional Chinese medicine group, the lung tissue structure was slightly abnormal. A small amount of alveolar atrophy and collapse could be observed, the alveolar walls were not thickened, and individual neutrophil infiltration could be seen in the tissue. In the control group, the lung tissue structure was slightly abnormal, some alveoli atrophied, and a small amount of neutrophil infiltration could be seen in the tissue. The levels of MCP-1 and MIP-1α in plasma and lavage fluid of the model group were significantly higher than those of the normal group (all P<0.05), while the levels of MCP-1 and MIP-1α in plasma and lavage fluid of the traditional Chinese medicine group and the control group were significantly lower than those of the model group (all P<0.05). Moreover, the levels of plasma MCP-1 and MIP-1α in the traditional Chinese medicine group were significantly lower than those in the control group (all P<0.05), while there was no statistically significant difference in the levels of MCP-1 and MIP-1α in alveolar lavage fluid between the traditional Chinese medicine group and the control group (all P>0.05). The levels of IL-6 and TNF-α in plasma and alveolar lavage fluid of the model group were significantly higher than those of the normal group (all P<0.05), while the levels of IL-6 and TNF-α in plasma and alveolar lavage fluid of the traditional Chinese medicine group and the control group were significantly lower than those of the model group (all P<0.05). Moreover, the levels of IL-6 and TNF-α in plasma and alveolar lavage fluid of the traditional Chinese medicine group were significantly lower than those of the control group (all P<0.05). Conclusions:The intervention of Maxing Loushi decoction has a significant improvement effect on the inflammatory response of COPD model mice. Inflammatory factors such as MCP-1, MIP-1α, IL-6, and TNF-α can be used as indicators to determine the degree of COPD inflammation.

Objective To investigate the current symptom status of maintenance hemodialysis(MHD)patients,analyze the influencing factors from the perspective of multidimensional symptom burden,extract symptom groups,and construct a symptom network.Methods A total of 490 patients who received MHD at the blood purification center of a tertiary hospital in Shanghai from March to April 2025 were selected using a convenience sampling method.30 symptoms of MHD patients were investigated using a modified dialysis symptom index table.SPSS and R software were utilized to analyze the influencing factors,extract symptom groups,and construct a multidimensional symptom network.Results A total of 488 valid questionnaires were collected,with a valid questionnaire recovery rate of 99.59％.The median number of symptoms experienced by patients was 6(interquartile range:4,8),with the top 5 symptoms being dry skin(69.88％),fatigue or tiredness(56.97％),itching(56.97％),worry(50.20％),and dry mouth(46.31％).Multidimensional analysis indicated that age,duration of dialysis,education level,and complications were influencing factors of symptom burden scores across different dimensions.6 stable symptom groups were extracted,namely skin discomfort,fatigue and pain,gastrointestinal tract,sleep disorders,water-electrolyte imbalance,and uremia.The results of the symptom network analysis revealed that difficulty of falling asleep had the highest intensity centrality(rs=2.18,2.25,2.12).Conclusion The symptom association is relatively stable,and difficulty of falling asleep is the core symptom.This finding can assist clinical medical staff in achieving efficiency and precision in symptom group management.

Objective:To observe the effects of Maxing Loushi decoction on the inflammatory response and inflammatory indicators in mice with chronic obstructive pulmonary disease (COPD) models.Methods:Thirty-six BALB/C mice were randomly divided into 4 groups by random number table method: 10 mice in the COPD model group (referred to as the model group), 10 mice in the Maxing Loushi decoction group (referred to as the traditional Chinese medicine group), 10 mice in the programmed death receptor-1 (PD-1) inhibitor group (referred to as the control group), and 6 mice in the normal group. The COPD models of mice in the model group, the traditional Chinese medicine group and the control group were prepared by cigarette smoking combined with lipopolysaccharide (LPS) induction method. During the modeling process, the model group and the traditional Chinese medicine group were respectively given normal saline and Maxing Loushi decoction by gavage. The control group was given intraperitoneal injection of PD-1 inhibitor, while the normal group was given intragastric administration of normal saline. Pathological changes of lung tissues in each group of mice were detected by HE staining. The levels of inflammatory factors [monocyte chemotactic protein-1 (MCP-1), macrophage inflammatory protein-1α (MIP-1α), interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α)] in the plasma and alveolar lavage fluid (BALF) of mice in each group were determined by enzyme-linked immunosorbent assay (ELISA). The effects of Maxing Loushi decoction intervention on inflammatory responses and inflammatory factors were evaluated.Results:The lung tissue structure in the normal group was basically normal. There was no thickening of the alveolar walls, no infiltration of neutrophils in the tissues, and no obvious inflammatory infiltration. In the model group, the lung tissue structure was slightly abnormal. A small amount of alveolar atrophy could be observed, the alveolar walls were slightly thickened, and inflammatory infiltration could be seen. In the traditional Chinese medicine group, the lung tissue structure was slightly abnormal. A small amount of alveolar atrophy and collapse could be observed, the alveolar walls were not thickened, and individual neutrophil infiltration could be seen in the tissue. In the control group, the lung tissue structure was slightly abnormal, some alveoli atrophied, and a small amount of neutrophil infiltration could be seen in the tissue. The levels of MCP-1 and MIP-1α in plasma and lavage fluid of the model group were significantly higher than those of the normal group (all P<0.05), while the levels of MCP-1 and MIP-1α in plasma and lavage fluid of the traditional Chinese medicine group and the control group were significantly lower than those of the model group (all P<0.05). Moreover, the levels of plasma MCP-1 and MIP-1α in the traditional Chinese medicine group were significantly lower than those in the control group (all P<0.05), while there was no statistically significant difference in the levels of MCP-1 and MIP-1α in alveolar lavage fluid between the traditional Chinese medicine group and the control group (all P>0.05). The levels of IL-6 and TNF-α in plasma and alveolar lavage fluid of the model group were significantly higher than those of the normal group (all P<0.05), while the levels of IL-6 and TNF-α in plasma and alveolar lavage fluid of the traditional Chinese medicine group and the control group were significantly lower than those of the model group (all P<0.05). Moreover, the levels of IL-6 and TNF-α in plasma and alveolar lavage fluid of the traditional Chinese medicine group were significantly lower than those of the control group (all P<0.05). Conclusions:The intervention of Maxing Loushi decoction has a significant improvement effect on the inflammatory response of COPD model mice. Inflammatory factors such as MCP-1, MIP-1α, IL-6, and TNF-α can be used as indicators to determine the degree of COPD inflammation.

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.

Objective To investigate the risk factors of overt hepatic encephalopathy(OHE)and death in cirrhotic portal hyperten-sion patients after transjugular intrahepatic portosystemic shunt(TIPS).Methods A retrospective selection was conducted on 40 patients with cirrhotic portal hypertension who underwent TIPS.The follow-up time was 3-41 months,median follow-up time was 20.36 months.The postoperative hepatic encephalopathy(HE)were divided into OHE group(20 cases)and non-OHE group(20 cases)and were further divided into death group(11 cases)and survival group(29 cases)according to their postoperative survival status.Gender,age,preoperative height,weight,total bilirubin,albumin,alanine aminotransferase,aspartate aminotransferase,creatinine,international normalized ratio(INR),prothrombin time,blood glucose,white blood cells,hemoglobin and platelet of all patients were recorded in detail,as well as whether they had diabetes and portal thrombosis before surgery.Child score and model for end-stage liver disease(MELD)score were also performed.The related risk factors of HE and death were obtained by statistical analysis of the two groups.Results The incidence rate of OHE after TIPS was 50%.The analysis revealed that age[hazard ratio(HR)1.115,95%confidence interval(CI)1.007-1.234,P=0.036]and albumin(HR 0.776,95%CI 0.627-0.960,P=0.020)were independent risk factors for OHE after TIPS.The receiver operating characteristic(ROC)curves were drawn with area under the curve(AUC)of 0.733 for age and AUC of 0.784 for albumin.The mortality rate after TIPS was 27.5%,and the analysis indicated that albumin(HR 0.660,95%CI 0.453-0.961,P=0.030),creatinine(HR 1.031,95%CI 1.001-1.062,P=0.044),and aspartate aminotransferase(HR 1.074,95%CI 1.013-1.139,P=0.018)were independent risk factors for death after TIPS.The ROC curves were drawn with AUC of 0.716 for albumin,AUC of 0.762 for creatinine,and AUC of 0.710 for aspartate aminotransferase.Conclusion Postoperative OHE is posi-tively correlated with age and negatively correlated with albumin.Furthermore,the risk of postoperative death is positively correlated with creatinine and aspartate aminotransferase and negatively correlated with albumin.

Aim To investigate the effect of interdialytic serum potassium levels on thrombosis of autologous ar-teriovenous fistula(AVF)in patients with chronic kidney disease(CKD)on maintenance haemodialysis(MHD).Methods 159 CKD patients who underwent MHD in our hospital from October 2021 to October 2022 were retrospectively analyzed.They were divided into hyperkalemia group(n=53),normal serum potassium group(n=61)and hypokalemia group(n=45)according to the mean serum potassium level of patients with different dialysis intervals,and all patients were followed up for 1 year or followed up until AVF thrombosis.General datas were collected and the following indicators were detected at the time of patient enrolment,including biochemical indicators,inflammatory factors,ultrasound indicators of AVF and oxidative stress factors levels.Multifactorial Logistic regression equations were used to analyze the effects of clinical indicators on AVF thrombosis in MHD patients,receiver operating characteristic(ROC)curve was used to assess the predictive efficacy of clinical indicators on AVF thrombosis;And interval likelihood ratio was used to stratify interdialyt-ic serum potassium levels,and further observe whether the relationship was stability between AVF thrombosis and interdia-lytic serum potassium levels in MHD patients.Results Compared with the normal serum potassium group,the levels of C-reactive protein(CRP),intact parathyroid hormone(iPTH),procalcitonin(PCT),triglyceride(TG),malondial-dehyde(MDA),myeloperoxidase(MPO),brachial artery resistance index(RI),brachial artery pulsatility index(PI)and radial artery PI were significantly elevated in hyperkalemia group and hypokalemia group,while the levels of albumin(Alb),total cholesterol(TC),superoxide dismutase(SOD)and fistula blood flow were significantly reduced(P＜0.05).Systolic blood pressure,diastolic blood pressure,fistula blood flow,Alb and SOD levels were significantly lower in patients with AVF thrombosis than those in patients with AVF unthrombosis(P＜0.05);Interdialytic mean serum potassium level,CRP,iPTH,PCT,brachial artery RI,brachial artery PI,radial artery PI,radial artery RI,MDA and MPO levels were significantly higher in patients with AVF thrombosis(P＜0.05).The ROC curve was used to analyse the model estab-lished by the multifactorial Logistic regression equation,and it was found that model 1 and model 2 had good predictive effi-cacy,and model 2 had the best predictive efficacy.The results of the interval likelihood ratio showed that:when the patient's interdialytic serum potassium level was 3.5～4.5 mmol/L,the possibility of the patient's AVF thrombosis was the lowest,and when the patient's interdialytic serum potassium level was＞5.5 mmol/L or＜3.5 mmol/L,the possibility of the patient's AVF thrombosis was higher,and when the patient's serum potassium level was＞5.5 mmol/L,the probability of AVF thrombosis was the highest in patients,which was 3.925 times higher than that of patients without AVF thrombosis.Conclusion Abnormal interdialytic serum potassium levels may induce AVF thrombosis in CKD patients.Serum potassium levels can be monitored during MHD treatment to enable timely intervention and improve clinical treatment outcomes for patients.