Objective: To evaluate the current situation of thermal environment in primary and secondary school classrooms during winter, and to analyze students thermal comfort needs, so as to provide a basis for improving classroom thermal environment. Methods: From December 16 to 26, 2024, a stratified cluster random sampling method was used to select 90 classrooms from 15 primary and secondary schools in centralized/air conditioned heating areas(Liaoning Province, Tianjin City, Shanghai City) and naturally ventilated areas(Anhui Province and Jiangxi Province)for on site environmental measurement. A questionnaire survey was conducted among 743 students. The differences between groups using the χ 2 test were compared. Based on actual measurement data, a predicted mean vote prepared percentage of dissatisfied (PMV-PPD) model for centralized/air conditioned classrooms and an adaptive model for naturally ventilated classrooms were established, and the thermal neutral temperature and comfort interval were calculated. Results: The average outdoor temperature during on site measurement was 4.00(0.20，7.00)℃. In classrooms with centralized or air conditioned heating systems, the measured average temperature was (19.33±2.59)℃, with a thermal comfort range of 20.35-25.35 ℃ and a thermal neutral temperature of 22.85 ℃. And 13.92% of students reported feeling cold, while 80.80% felt comfortable. In classrooms with natural ventilation, the measured average temperature was (12.26±1.83)℃, with a thermal neutral temperature of 19.67 ℃ and a thermal comfort range of 16.17-23.17 ℃. About 48.33% of students reported feeling cold, and 49.81 % felt comfortable.The results of univariate analysis showed that there were statistically significant differences in shoe thickness, temperature sensation, relative humidity sensation and wind speed sensation between centralized/air conditioned heating areas ( χ 2= 7.01 , 31.47, 13.57, 13.80,all P <0.05). There were also statistically significant differences in school stage for primary and secondary school students, body mass index, classroom location for seat, temperature sensation, relative humidity sensation and wind speed sensation between naturally ventilated areas ( χ 2=42.13, 11.13, 11.04, 60.39, 29.27, 38.46,all P <0.05). Conclusions There are differences in thermal environment and students subjective thermal comfort in primary and secondary schools under different ventilation modes in winter. The temperature standards for heated classrooms should be revised, and differentiated environmental regulation strategies should be adopted based on different ventilation methods to improve students health and comfort levels.

To explore the advantages of traditional Chinese medicine （TCM） and integrative TCM-Western medicine approaches in the treatment of diabetic microvascular complications （DMC）， refine key pathophysiological insights and treatment principles， and promote academic innovation and strategic research planning in the prevention and treatment of DMC. The 38th session of the Expert Salon on Diseases Responding Specifically to Traditional Chinese Medicine， hosted by the China Association of Chinese Medicine， was held in Beijing， 2024. Experts in TCM， Western medicine， and interdisciplinary fields convened to conduct a systematic discussion on the pathogenesis， diagnostic and treatment challenges， and mechanism research related to DMC， ultimately forming a consensus on key directions. Four major research recommendations were proposed. The first is addressing clinical bottlenecks in the prevention and control of DMC by optimizing TCM-based evidence evaluation systems. The second is refining TCM core pathogenesis across DMC stages and establishing corresponding "disease-pattern-time" framework. The third is innovating mechanism research strategies to facilitate a shift from holistic regulation to targeted intervention in TCM. The fourth is advancing interdisciplinary collaboration to enhance the role of TCM in new drug development， research prioritization， and guideline formulation. TCM and integrative approaches offer distinct advantages in managing DMC. With a focus on the diseases responding specifically to TCM， strengthening evidence-based support and mechanism interpretation and promoting the integration of clinical care and research innovation will provide strong momentum for the modernization of TCM and the advancement of national health strategies.

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 This study aimed to investigate the genetic diversity, differentiation, and population structure of Aedes albopictus across different geographical regions in Shandong Province, and to explore the relationship between genetic diversity and geographical distribution. Methods Between July and August 2024, ten Ae. albopictus populations were sampled from seven cities in Shandong Province. Genomic DNA was extracted from individual mosquitoes, and the mitochondrial cytochrome c oxidase subunit I(COⅠ)gene was amplified using PCR and sequenced. The obtained sequences were verified using BLAST and analyzed with MAFFT, MEGA 11, DnaSP v6.12, Arlequin 3.5, PopART 1.7, STRUCTURE 2.3.4 and the R packages adegenet and vegan to assess genetic diversity and population structure. Results A total of 229 COⅠ sequences(662 bp) was obtained, revealing ten variable sites with no insertions or deletions. The overall base composition showed an AT bias of 67.7%. Haplotype analysis identified 11 haplotypes, with Hap2 being the dominant and most widely distributed haplotype across all populations. Neutrality tests showed significant population expansion only in the Rizhao population. Mantel testing result revealed that geographical distance does not significantly impede gene flow. Overall, genetic differentiation among populations was low, indicating frequent gene flow. When combined with additional samples from Shanghai, Fujian, Guangdong, Yunnan, Hainan and Guangxi, STRUCTURE, UPGMA and DAPC analyses revealed two primary genetic clusters of Ae. albopictus. Conclusions Ae. albopictus populations in Shandong Province exhibit frequent gene flow, low genetic differentiation, and relatively low overall genetic diversity. However, the Rizhao population showed signs of recent expansion, highlighting the need for enhanced surveillance and targeted control measures in this area.

Objective: To analyze the changes in homologous immunity after RhCE-matched transfusion in positive patients with RhCE blood group antibodies, and to provide precise transfusion strategies for chronic anemia patients. Methods: Patients with chronic anemia in our hospital from January 2020 to March 2024 (continuously receiving blood transfusions for more than 6 months) were enrolled, and 63 cases of unexpected antibody screening positive and identified as RhCE blood group antibodies were selected as the research subjects. The changes in unexpected antibody yield rate after ABO and RhCcDEe isotype blood transfusion were observed. Patients with MNS, Kidd, or Lewis blood group antibodies were screened for corresponding negative donors using monoclonal antibodies for extended typing transfusion based on RhCcEe typing, and the changes in unexpected antibody yield rate after transfusion were observed. Blood group genotyping was performed when serological techniques failed to resolve discrepancies or detect abnormal antigen expression. Results: After RhCcDEe-matched transfusions, RhCE antibodies disappeared in 62 patients, while 1 patient developed anti-Ce. The latter did not develop blood type isotype immunity after receiving RhccEE donor blood. Among the 62 patients, 9 developed unexpected antibodies against other systems: anti-M (4 cases), anti-Mur (2), anti-S (1), anti-Jka (1), and anti-Lea (1). No additional alloimmunization occurred after extended antigen-matched transfusions. A patient with serologically weak e phenotype was genotyped as DCe/DcE, with gene sequencing revealing an 827C>A mutation in exon 6 of the RHCE gene, forming the RHCE 01.31 allele. Conclusion: Precise transfusion strategies incorporating RhCE, MNS, Kidd, and Lewis blood group antigen typing can reduce the probability of blood group homologous immunity. RhCE complex antibodies and RhCE variants pose difficulties for clinical RhCE typing transfusion, which can be addressed through cross-matching and genetic analysis.

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.

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 investigate the completion rate of tumor evaluation at initial assessment and after neoadjuvant therapy for mid and low rectal cancer patients in the national multicenter real-world database.Methods:The prospective real-world study was conducted. The clinicopathological data of 1 074 patients who underwent surgical treatment for mid and low rectal cancer in 47 national medical institutions, including Peking Union Medical College Hospital et al, from May 12,2023 to May 11,2024 were collected. Observation indicators: (1) clinical characteristics of patients with mid and low rectal cancer; (2) initial colonoscopy and pathologic evaluation of tumors in patients with mid and low rectal cancer; (3) initial imaging evaluation of patients with mid and low rectal cancer; (4) imaging evaluation after neoadjuvant therapy for patients with mid and low rectal cancer. Measurement data with normal distribution were represented as Mean± SD, and measurement data with skewed distribution were represented as M( Q1, Q3). Count data were described as absoluter numbers and/or percentages. Results:(1) Clinical characteristics of patients with mid and low rectal cancer. Of the 1 074 patients, there were 713 males and 361 females, aged 63(56,70)years. The body mass index of 1 074 patients was 24(21,26)kg/m 2.For American Society of Anesthesiologists classification, there were 147 cases of stage Ⅰ, 641 cases of stage Ⅱ, 157 cases of stage Ⅲ, 2 cases of stage Ⅳ, and there were 127 cases missing data. (2) Initial colonoscopy and pathologic evaluation of tumors in patients with mid and low rectal cancer. Of the 1 074 patients, there were 787 cases (73.28%) undergoing complete colonoscopy, and there were only 197 cases (18.34%) undergoing immunohistochemical evaluation of all four mismatch repair proteins. (3) Initial imaging evaluation of patients with mid and low rectal cancer. Of the 1 074 patients, there were 842(78.40%) patients completing magnetic resonance imaging (MRI) or ultrasound evaluation, and there were 914(85.10%) patients completing chest, abdomen, and pelvis enhanced computed tomography (CT) evaluation. In the 149 patients completing rectal ultrasound evaluation, there were 122 cases (81.88%) comple-ting T staging evaluation, and there were 81 cases (54.36%) completing N staging evaluation. In the 808 patients completing rectal MRI evaluation, there were 708 cases (87.62%) completing T staging evaluation, and there were 590 cases (73.02%) completing N staging evaluation. (4) Imaging evalua-tion after neoadjuvant therapy for patients with mid and low rectal cancer. Of the 388 patients with neoadjuvant therapy, there were 332 patients (85.57%) completing MRI or ultrasound evaluation, and there were 327 patients (84.28%) completing chest, abdomen, and pelvis enhanced CT evalua-tion. In the 70 patients completing rectal ultrasound evaluation, there were 65 cases (92.86%) com-pleting T staging evaluation, and there were 49 cases (70.00%) completing N staging evaluation. In the 327 patients completing rectal MRI evaluation, there were 246 cases (75.23%) completing T staging, and there were 228 cases (69.72%) completing N staging evaluation. Conclusion:The com-pletion rate of tumor imaging evaluation at initial assessment and after neoadjuvant therapy for mid and low rectal cancer patients on a national scale is relatively good.

Objective:To explore the effect of ginsenoside Rg1 on spermatogenic dysfunction in mice caused by diabetes and its mechanism of action.Methods:Eighteen male C57BL mice were randomly divided into control group, the model group and the ginsenoside Rg1 group by completely random method, with 6 mice in each group. Type 2 diabetes models were established in the model group and the ginsenoside Rg1 group by a high-fat diet combined with intraperitoneal injection of streptozotocin, while control group was injected with the same amount of normal saline. After successful modeling, control group was given a regular diet for 8 weeks, while the model group and ginsenoside Rg1 group were given a high-fat diet for 8 weeks. The ginsenoside Rg1 group was also treated with ginsenoside Rg1 medication. Reproductive hormone levels were detected by enzyme-linked immunosorbent assay test kits, and Western blotting was used to detect the expressions of apoptosis-related proteins (Bcl2 protein, Caspase-3 protein, Bax protein), autophagy-related proteins (P62, LC3Ⅰ, LC3Ⅱ, Beclin1), β-Catenin protein, mTOR protein, LAMP1 protein and transcription factor EB. The body weight, blood glucose levels, testicular index of mice in each group were compared, as well as the testicular injury status.Results:The body weight [(18.77±1.14) g], testosterone level [(141.07±8.47) ng/L], follicle-stimulating hormone level [(9.19±0.74) U/L], and luteinizing hormone level [(1 497.91±99.57) pg/L] of mice in the model group were significantly lower than those in the control [(31.57±2.35) g, P<0.001; (171.50±11.76) ng/L, P<0.001; (12.46±1.54) U/L, P<0.001; (1 807.29±92.76) pg/L, P<0.001]; fasting blood glucose level [(20.82±1.11) mmol/L], glycosylated hemoglobin (12.67%±1.03%), the testis index (0.65%±0.03%) were significantly higher than those in the control [(6.40±1.34) mmol/L, P<0.001; 5.17%±1.17%, P<0.001; 0.48%±0.04%, P<0.001]. Compared with the model group, the body weight [(22.62±0.92) g, P=0.023], testosterone level [(172.63±9.20) ng/L, P<0.001], follicle-stimulating hormone level [(12.37±1.15) U/L, P<0.001], and luteinizing hormone level [(1 847.80±108.80) pg/L, P<0.001] of mice in the ginsenoside Rg1 group increased significantly, fasting blood glucose level [(18.63±1.14) mmol/L, P=0.017], glycosylated hemoglobin (8.50%±1.05%, P<0.001) and testicular index (0.54%±0.02%, P<0.001) decreased significantly. Compared with the control, the expressions of P62 ( P=0.039), LC3Ⅱ/LC3Ⅰ( P<0.001), Beclin1 ( P=0.002) and mTOR ( P=0.036) in the testicular tissue of mice in the model group all increased, the expression of β-Catenin ( P<0.001), LAMP1 ( P=0.005), transcription factor EB ( P<0.001) all decreased. Compared with the model group, the expressions of autophagy-related proteins P62 ( P=0.048), LC3Ⅱ/LC3Ⅰ( P<0.001) , Beclin1 ( P=0.023) and mTOR ( P=0.005) in the ginsenoside Rg1 group all decreased, while the expression of β-Catenin ( P=0.001), LAMP1 ( P=0.011) and transcription factor EB ( P=0.022) all increased. Transmission electron microscopy detected a decrease in the number of autophagosomes in the testicles of mice in the model group, and it improved after drug intervention. The HE staining showed that the testes of mice in the model group exhibited phenotypes such as the shedding and disorganization of spermatogenic cells, while ginsenoside Rg1 was able to improve these phenotypes. Conclusion:Ginsenoside Rg1 can improve testicular injury caused by diabetes in mice by regulating autophagy.