ObjectiveTo explore the complex network relationships among pain, kinesiophobia, social participation and knee function in patients after total knee arthroplasty (TKA), and to analyze the moderating effects of different socio-structural factors on the rehabilitation network from an ethical equity perspective. MethodsA convenience sampling method was used to select 291 patients who underwent TKA in Qilu Hospital of Shandong University from May to July, 2023. Pain was assessed using Numerical Rating Scale, kinesiophobia with Chinese short version of the Tampa Scale for Kinesiophobia, social participation with Impact on Participation and Autonomy Questionnaire, and knee function with Hospital for Special Surgery Knee Score. A partial correlation network among pain, kinesiophobia, social participation and knee function was constructed using Graphical Least Absolute Shrinkage and Selection Operator. Key variables were identified through node centrality and bridge centrality analysis. Network Comparison Tests (NCT) were used to analyze network differences among subgroups based on different socio-structural characteristics. ResultsIn the network model, the nodes with the highest strength centrality were indoor participation, activity behavior and activity pain. Bridge centrality analysis indicated that activity pain, knee function, indoor participation and activity cognition were key bridge nodes. NCT revealed no significant differences in overall network structure or global strength among subgroups based on residence, education level or payment method (P > 0.05). However, significant differences in edge weights were found for specific edges such as activity cognition-activity behavior and knee function-indoor participation (P < 0.05). ConclusionThere is a network of interactions among pain, kinesiophobia, social participation and knee function in patients after TKA, with nodes such as indoor participation and activity pain playing key roles in the rehabilitation process. Although the overall rehabilitation network is similar across different socio-structural groups, variations exist in specific relational pathways among patients from rural areas, those with lower education levels, and those with out-of-pocket payment. This suggests that clinical rehabilitation interventions should focus on these core nodes and implement targeted support strategies for socio-structurally disadvantaged groups to promote rehabilitation equity.

ObjectiveTo explore the complex network relationships among pain, kinesiophobia, social participation and knee function in patients after total knee arthroplasty (TKA), and to analyze the moderating effects of different socio-structural factors on the rehabilitation network from an ethical equity perspective. MethodsA convenience sampling method was used to select 291 patients who underwent TKA in Qilu Hospital of Shandong University from May to July, 2023. Pain was assessed using Numerical Rating Scale, kinesiophobia with Chinese short version of the Tampa Scale for Kinesiophobia, social participation with Impact on Participation and Autonomy Questionnaire, and knee function with Hospital for Special Surgery Knee Score. A partial correlation network among pain, kinesiophobia, social participation and knee function was constructed using Graphical Least Absolute Shrinkage and Selection Operator. Key variables were identified through node centrality and bridge centrality analysis. Network Comparison Tests (NCT) were used to analyze network differences among subgroups based on different socio-structural characteristics. ResultsIn the network model, the nodes with the highest strength centrality were indoor participation, activity behavior and activity pain. Bridge centrality analysis indicated that activity pain, knee function, indoor participation and activity cognition were key bridge nodes. NCT revealed no significant differences in overall network structure or global strength among subgroups based on residence, education level or payment method (P > 0.05). However, significant differences in edge weights were found for specific edges such as activity cognition-activity behavior and knee function-indoor participation (P < 0.05). ConclusionThere is a network of interactions among pain, kinesiophobia, social participation and knee function in patients after TKA, with nodes such as indoor participation and activity pain playing key roles in the rehabilitation process. Although the overall rehabilitation network is similar across different socio-structural groups, variations exist in specific relational pathways among patients from rural areas, those with lower education levels, and those with out-of-pocket payment. This suggests that clinical rehabilitation interventions should focus on these core nodes and implement targeted support strategies for socio-structurally disadvantaged groups to promote rehabilitation equity.

ObjectiveTo explore the complex network relationships among pain, kinesiophobia, social participation and knee function in patients after total knee arthroplasty (TKA), and to analyze the moderating effects of different socio-structural factors on the rehabilitation network from an ethical equity perspective. MethodsA convenience sampling method was used to select 291 patients who underwent TKA in Qilu Hospital of Shandong University from May to July, 2023. Pain was assessed using Numerical Rating Scale, kinesiophobia with Chinese short version of the Tampa Scale for Kinesiophobia, social participation with Impact on Participation and Autonomy Questionnaire, and knee function with Hospital for Special Surgery Knee Score. A partial correlation network among pain, kinesiophobia, social participation and knee function was constructed using Graphical Least Absolute Shrinkage and Selection Operator. Key variables were identified through node centrality and bridge centrality analysis. Network Comparison Tests (NCT) were used to analyze network differences among subgroups based on different socio-structural characteristics. ResultsIn the network model, the nodes with the highest strength centrality were indoor participation, activity behavior and activity pain. Bridge centrality analysis indicated that activity pain, knee function, indoor participation and activity cognition were key bridge nodes. NCT revealed no significant differences in overall network structure or global strength among subgroups based on residence, education level or payment method (P > 0.05). However, significant differences in edge weights were found for specific edges such as activity cognition-activity behavior and knee function-indoor participation (P < 0.05). ConclusionThere is a network of interactions among pain, kinesiophobia, social participation and knee function in patients after TKA, with nodes such as indoor participation and activity pain playing key roles in the rehabilitation process. Although the overall rehabilitation network is similar across different socio-structural groups, variations exist in specific relational pathways among patients from rural areas, those with lower education levels, and those with out-of-pocket payment. This suggests that clinical rehabilitation interventions should focus on these core nodes and implement targeted support strategies for socio-structurally disadvantaged groups to promote rehabilitation equity.

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.

Objective To gain insights into the biological characteristics of different populations of Culex tritaeniorhynchus within and around the Yellow Sea wetland from the perspective of the occurrence of resistance, we investigated the levels of resistance to deltamethrin and kdr gene mutation in the wetland and its peripheral areas. Methods Specimens were collected from Cx. tritaeniorhynchus populations at two monitoring sites in the Rare Bird National Nature Reserve and Tiaozi Ni Wetland Scenic Area, and also from two populations in Yancheng City and the Liuhe District of Nanjing, and the resistance of these mosquitoes to deltamethrin was determined using the CDC biotest bottle method. For each concentration of deltamethrin assessed, a random subset of exposed specimens was selected for amplification of the kdr gene fragment, followed by Sanger sequencing to identify and analyze resistance-associated mutations. Results The LC50 levels of deltamethrin among mosquitoes from the four populations in Luhe, Yancheng, the Rare Bird National Nature Reserve and the Tiaozi Ni Wetland Scenic Area were 2.048 5, 7.798 2, 3.473 3, and 17.695 5 mg/mL, respectively, with corresponding concentrations of deltamethrin ranging from 0.005 to 5.000,0.050 to 50.000,0.050 to 25.000 and 0.050 to 50.000 mg/mL, respectively. Furthermore, the ranges of the KT50 values were 11.76-107.43, 67.05-216.30,29.77-107.43 and 28.40-329.51 min; the 1-h knockdown rates were 34.58%-99.15%, 9.52%-43.80%, 55.09%-73.01%, and 10.09%-68.07%; and the 24-h mortality rates were 12.15%-67.52%,9.52%-79.56%,13.17%-82.21%, and 11.01%-78.99%, respectively. With respect to kdr gene mutation, we assayed a total of 63,70,59, and 57 mosquitoes for the four populations, for which we detected L1014F mutation frequencies of 14.29%, 35.00%, 20.34%, and 31.58%, respectively, with a majority of these mutations being heterozygous for resistance. In addition, five adult mosquitoes were identified has having synonymous mutations at site 1011[i. e. , AAT(asparagine)mutation to AAC(asparagine)]. Conclusions Our findings revealed the clear resistance of Cx. tritaeniorhynchus to deltamethrin in the Yancheng region of the Yellow Sea wetland, and the resistance phenotype and kdr frequency of Cx. tritaeniorhynchus in the wetland environment were comparable to those of Cx. tritaeniorhynchus in the wetland environment, thereby indicating that the resistance of different populations of Cx. tritaeniorhynchus was homogeneous under the pressure of different insecticide selection within and around the wetland. However, the underlying mechanisms need to be further studied.

Objective To examine the potential causal associations between different dietary taste preferences and the risk of prostatitis, so as to provide reference for the primary prevention of this disease. Methods Summary-level genome-wide association study(GWAS)data on five taste preferences-sweet, sour, salty, bitter and spicy—were obtained from the GWAS, and GWAS data for prostatitis were sourced from the FinnGen database. The potential causal associations between the dietary taste preferences and risk of prostatitis were analyzed with MR. The inverse variance weighted(IVW)method served as the primary analytical approach. Heterogeneity was assessed using Cochran's Q test. Horizontal pleiotropy was evaluated via the MR-Egger intercept and Mendelian randomization pleiotropy residual sum and outlier(MR-PRESSO)tests. Leave-one-out analysis was performed to evaluate the influence of individual single nucleotide polymorphisms(SNPs)on the causal estimates. Results Preferences for sweet(OR=1.338, 95%CI:1.024-1.748, P=0.033)and salty(OR=1.356, 95%CI:1.092-1.684, P=0.006)tastes showed positive causal associations with the risk of prostatitis, whereas a preference for bitter taste was negatively associated(OR=0.638, 95%CI:0.416-0.978, P=0.039). No significant causal links were observed for sour or spicy taste preferences(P＞0.05). Sensitivity analyses and reverse MR analyses further supported the robustness of the findings.Conclusion Sweet and salty taste preferences may be potential dietary risk factors for prostatitis, while bitter taste preference could play a protective role. Further research is needed to elucidate these causal relationships, which may contribute to developing tailored dietary intervention strategies for prostatitis prevention.

The accumulation of uremic toxins such as urea nitrogen, blood creatinine, and uric acid of patients with renal failure in vivo would lead to aggravated kidney damage. In this study, coated aldehyde oxy-starch (CAO) was used as an adsorbent to investigate its in vitro adsorption performance on renal failure indexes for urea, indoxyl sulfate (INS), monomethylamine (MMA), dimethylamine (DMA), uric acid (UA), and creatinine (Cr). The effects of variables such as pH, temperature, concentration, dosage, and time on the adsorption capacity of CAO were systematically investigated, employing analytical techniques of high-performance liquid chromatography (HPLC) and gas chromatography (GC). The results revealed that CAO exhibited a strong adsorption capacity for urea, INS, and MMA, alongside a moderate adsorption capacity for DMA, UA, and Cr. The adsorption kinetics and thermodynamic studies indicated that the adsorption of urea and UA by CAO were fitted in pseudo-first-order kinetics, and the adsorption isotherm aligned with the Freundlich adsorption model. The enthalpy change ΔH of urea in adsorption was in the range of 40 to 60 kJ·mol^-1, which demonstrated the presence of strong adsorption force due to the interactions of coordinating groups. The ΔH of UA was greater than 80 kJ·mol^-1, indicating the generation of chemical bonds during the adsorption. Both of them, Gibbs free energy ΔG was less than 0, within the range of -20 to 0 kJ·mol^-1, suggested that the adsorption of urea and UA by CAO occurred spontaneously as physical adsorption process. The adsorption entropy ΔS of urea and UA was > 0, which indicated an increase in entropy throughout the adsorption. The infrared spectroscopygram showed the formation of a chemical bond, specifically the imine bond, following the adsorption of urea by CAO, thereby indicating a chemical reaction during the adsorption. This study elucidates the adsorption mechanism of CAO on various indexes of renal failure, providing a scientific basis for its clinical usage.

ObjectiveTo explore the clinical safety of Feilike Mixture （FLK） in the real world. MethodsThe safety of all children who received FLK from 29 institutions in 12 provinces between January 21，2021 and December 25，2021 was evaluated through prospective centralized surveillance and a nested case control study. ResultsA total of 3 035 juveniles were included. There were 29 research centers involved，which are distributed across 12 provinces，including one traditional Chinese medicine （TCM） hospital and 28 general hospitals. The average age among the juveniles was （4.77±3.56） years old，and the average weight was （21.81±12.97） kg. Among them，119 cases （3.92%） of juveniles had a history of allergies. Acute bronchitis was the main diagnosis for juveniles，with 1 656 cases （54.46%）. FLK was first used in 2 016 cases （66.43%），and 142 juvenile patients had special dosages，accounting for 4.68%. Among them，92 adverse drug reactions （ADRs） occurred，including 73 cases of gastrointestinal system disorders，10 cases of metabolic and nutritional disorders，eight cases of skin and subcutaneous tissue diseases，two cases of vascular and lymphatic disorders，and one case of systemic diseases and various reactions at the administration site. The manifestations of ADRs were mainly diarrhea，stool discoloration，and vomiting，and no serious ADRs occurred. The results of multi-factor analysis indicated that special dosages （the use of FLK）［odds ratio （OR） of 2.642， 95% confidence interval （CI） of 1.105-6.323］，combined administration： spleen aminopeptide （OR of 4.978， 95%CI of 1.200-20.655），and reason for combined administration： anti-infection （OR of 1.814， 95%CI of 1.071-3.075） were the risk factors for ADRs caused by FLK. Conclusion92 ADRs occurred among 3 035 juveniles using FLK. The incidence of ADRs caused by FLK was 3.03%，and the severity was mainly mild or moderate. Generally，the prognosis was favorable after symptomatic treatment such as drug withdrawal or dosage reduction，suggesting that FLK has good clinical safety.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.