To address the growing challenge of an increasing number of elderly lung cancer patients amidst China's aging population and to fill the gap in quality control standards for surgical treatment in this special population, this study aimed to develop a standardized surgical evaluation system for elderly lung cancer patients tailored to China's national conditions. The system was established through a literature review, integrated the pathophysiological characteristics of elderly patients, and was constructed following review, feedback, and revision by experts from multiple thoracic surgery centers. Employing a 100-point scoring system, it comprises three primary domains: physical infrastructure and geriatric adaptability foundational conditions (10 points); management level and perioperative care models (20 points); and technical proficiency and clinical outcomes (70 points). The system places a strong emphasis on geriatric adaptability, proposing specific, quantifiable indicators for age-friendly facility modifications, control of elderly-specific complications, multidisciplinary collaboration, and standardized perioperative management. It provides a convenient and measurable assessment tool for quality control in the surgical treatment of elderly lung cancer in China, which is expected to promote the standardization and homogenization of diagnosis and treatment.

Objective:To investigate the effect of insulin-like growth factor 1 (IGF-1) on acute lung injury in septic mice and its underlying molecular mechanism.Methods:Twenty SPF male C57BL/6J mice aged 6-8 weeks were randomly (random number) divided into the sham-operated group, sham-operated + IGF-1 group, sepsis group and sepsis + IGF-1 group, with 5 mice in each group. IGF-1 [60 μg/(kg·d)] was injected via the tail vein for 3 consecutive days in the sham-operated + IGF-1 group and sepsis + IGF-1 group, and mice in the sham-operated group and sepsis group were injected with an equal volume of saline. The tissue of the upper lobe of the right lung was taken to calculate the wet-to-dry ratio, and the upper lobe of the left lung was subjected to HE staining to analyze pathological changes and evaluate lung injury. The levels of interleukin (IL)-6 and IL-1β in the bronchoalveolar lavage fluid (BALF) and serum of mice were detected by ELISA. The expression of p-PI3K, PI3K, p-AKT and AKT in lung tissues was determined via Western blotting. The quantitative data with a normal distribution and homogeneity of variance were compared between the two groups by two independent sample t test. Results:Lung volume was reduced in the sepsis group than in the sham-operated group, obvious surface congestion, dark red color, large bruises and hemorrhagic foci were observed under the pericardium, and the wet-to-dry ratio was significantly elevated ( P<0.05). Compared with the sepsis group, the sepsis + IGF-1 group had slightly increased lung volume, less congestion, darker red color, fewer bruises and hemorrhagic foci, and a lower wet-to-dry ratio ( P<0.05). There was no significant change in lung tissue morphology in the sham-operated + IGF-1 group compared with the sham-operated group. HE staining and lung histopathological scores showed that lung tissue was significantly damaged in the sepsis group than the sham-operated group ( P<0.001), and the pathological score of lung tissue was less damaged in the sepsis + IGF-1 group compared with the sepsis group ( P<0.01). The ELISA results demonstrated that the serum levels of IL-6 and IL-1β were markedly decreased in the sepsis + IGF-1 group than in the sepsis group [(26.22±1.60) pg/mL vs. (45.61±7.85) pg/mL, P<0.05; (87.99±11.80) pg/mL vs. (181.26±10.11) pg/mL, P<0.001]. Moreover, the IL-6 and IL-1β contents in the BALF of the sepsis + IGF-1 group were notably lower than those in the BALF of the sepsis group [(7.67±0.42) pg/mL vs. (20.25±0.43) pg/mL, P<0.001; (17.00±6.08) pg/mL vs. (108.61±5.18), pg/mL P <0.001]. Western blot analysis revealed that the expression of p-PI3K, PI3K, p-AKT and AKT in the lung tissues of mice in the sepsis+IGF-1 group were markedly lower than that in the sepsis group [(0.71±0.05) vs. (1.21±0.09), P<0.05; (0.57±0.08) vs. (1.24±0.22), P<0.01; (0.29±0.07) vs. (1.10±0.04), P<0.001; (0.65±0.17) vs. (1.19±0.07), P<0.01]. Conclusion:IGF-1 ameliorates sepsis-induced acute lung injury in mice, and its protective effect may be achieved by inhibiting the PI3K/AKT pathway.

Objective:The research group had previously developed an artificial intelligence algorithm to predict sepsis within 24 hours at the triage stage in emergency departments. This research studied the doctors’ response to algorithm-generated risk alerts and designs appropriate physician-algorithm collaboration strategies to further enhance sepsis risk identification capabilities.Methods:The research collected 40 cases of sepsis in the emergency departments from the open medical database MIMIC-IV (Medical Information Mart for Intensive Care) for a collaboration test. The cases were selected according to their typicality and classified according to the model’s confidence in its prediction. A total of 165 emergency doctors from 58 hospitals in China, stratified by professional rank, participated in the study. Four collaboration modes were designed with different information volumes and reading costs using the information offered by the algorithm. During the test, before and after the model presented its results and interpretive information according to the collaboration mode, the doctors were asked to rate the sepsis risk for each sample and record their confidence.Results:Analysis of the 4 704 valid evaluations done by 147 doctors showed that different collaboration modes caused no significant difference on doctors’ detection of sepsis risk. For cases with high model confidence, physicians’ diagnostic accuracy improved by 2.6%±0.6% ( P=0.02) post-algorithm input, with increased confidence in correct judgments. Conversely, for low-confidence model predictions, diagnostic accuracy decreased by 2.6%±1.4% ( P=0.06), accompanied by reduced clinician confidence in accurate assessments. Conclusions:The collaboration effect is mostly determined by the model’s confidence in its prediction. Different collaboration modes cause no significant difference, and doctors of different titles are influenced consistently with the same model confidence. Suggestions for collaboration design are as follow. When the model has low confidence in its own assessment of a patient’s sepsis risk, it should not directly demonstrate its assessment. When the model has high confidence, its assessment can be offered to the doctors as a reference. When predicting sepsis at the triage stage in the emergency departments, no extra interpretive information is needed.

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging tick-borne infectious disease with a high mortality rate. Many countries worldwide have already reported local transmission, and the number of reported cases has been increasing yearly, with an ever-expanding region. No specific treatment drugs or vaccines have seriously threatened public health safety in epidemic regions. This article reviews the epidemiological characteristics, transmission routes, and control measures of SFTS.

[This corrects the article DOI: 10.1016/j.apsb.2019.01.013.].

Azvudine and nirmatrelvir/ritonavir (Paxlovid) are recommended for COVID-19 treatment in China, but their safety and efficacy in the elderly population are not fully known. In this multicenter, retrospective, cohort study, we identified 5131 elderly hospitalized COVID-19 patients from 32,864 COVID-19 patients admitted to nine hospitals in Henan Province, China, from December 5, 2022, to January 31, 2023. The primary outcome was all-cause death, and the secondary outcome was composite disease progression. Propensity score matching (PSM) was performed to control for confounding factors, including demographics, vaccination status, comorbidities, and laboratory tests. After 2:1 PSM, 1786 elderly patients receiving azvudine and 893 elderly patients receiving Paxlovid were included. Kaplan-Meier and Cox regression analyses revealed that compared with Paxlovid group, azvudine could significantly reduce the risk of all-cause death (log-rank P = 0.002; HR: 0.71, 95% CI: 0.573-0.883, P = 0.002), but there was no difference in composite disease progression (log-rank P = 0.52; HR: 1.05, 95% CI: 0.877-1.260, P = 0.588). Four sensitivity analyses verified the robustness of above results. Subgroup analysis suggested that a greater benefit of azvudine over Paxlovid was observed in elderly patients with primary malignant tumors (P for interaction = 0.005, HR: 0.32, 95% CI: 0.18-0.57) compared to patients without primary malignant tumors. Safety analysis revealed that azvudine treatment had a lower incidence of adverse events and higher lymphocyte levels than Paxlovid treatment. In conclusion, azvudine treatment is not inferior to Paxlovid treatment in terms of all-cause death, composite disease progression and adverse events in elderly hospitalized COVID-19 patients.

Human respiratory syncytial virus (RSV) is a major cause of lower respiratory tract infections in infants and young children, as well as an important cause of respiratory tract infections in immunocompromised patients and the elderly, which poses a significant economic and social burden worldwide. In recent years, substantial progress has been made in understanding the structure and function of RSV proteins and the interactions between RSV with host factors which is helpful to the discovery of new therapeutic targets and the development of novel interventions. Although two vaccines and two monoclonal antibodies for RSV prevention have been approved, the antiviral treatment remains an unmet clinical need. In this review, we summarize the structure, protein functional properties, and pathological mechanisms of RSV and the current status of RSV drug development. In addition, remaining challenges and innovative ideas for RSV prevention and treatment have also been highlighted.

Objective To investigate the impact of different application methods of tissue compensators(bolus)on the skin dose delivered to the chest wall following radical mastectomy for breast cancer.Methods A retrospective analysis was conducted on 60 female patients who underwent radical mastectomy and required chest wall radiotherapy at the hospital between January 2023 and March 2025.The Pinnacle3 9.10 radiotherapy planning system(TPS)was utilized to design two VMAT dual semi-arc radiotherapy plans for each patient,with a prescribed target dose of 50 Gy delivered in 2 Gy fractions over 25 sessions.In Plan 1,a Bolus was applied and optimized during the first 15 fractions,and subsequently removed for the remaining 10 fractions without re-optimization.The sub-field configuration and dose weighting from the initial optimization were retained,and only dose recalculations were performed.The final treatment plan combined both the Bolus-included and Bolus-excluded phases.In contrast,Plan 2 involved the application and optimization of Bolus during the first 15 fractions,followed by its removal and re-optimization of the plan for the last 10 fractions.The two optimized plans were then combined for the overall treatment delivery.Data from the two plan groups were analyzed using a paired sample t-test with SPSS 29.0 software.Results There was a statistically significant difference(P＜0.05)in skin Dmean,V52.5,and V55;heart Dmean,V5,V30,and V40;affected lung Dmean,V5,and V20;PRVcord Dmean and Dmax;healthy breast Dmean,V5,and V10;affected humeral head Dmean and V30;as well as PTV Dmean,V50,V55,D2％,D98％,CI,and MU.Moreover,the dose distribution on the target layer and the DVH curves showed marked differences.However,no statistically significant difference was observed in PTV HI(P=0.125).Conclusion The combination of the two optimized plans,consisting of 15 fractions with bolus and 10 fractions without bolus,more accurately reflects the dose distri-bution within the planned target area and organs at risk,thereby providing enhanced protection for the patient's chest wall skin.

Objective:To analyze the epidemiological characteristics and natural focus distribution of marburg virus disease (MVD), and provide evidence for the prevention and control of MVD.Methods:A systematic literature retrieval was conducted, and descriptive epidemiological method was used to analyze the temporal, spatial, and population distributions of MVD as well as its natural hosts. The case fatality rate of MVD was evaluated through Meta-analysis, and the phylogenetic analysis of viral genomes was done by using software IQ-TREE 2.3.6.Results:Marburg virus has endemic spread in Africa and can be detected in various animals such as primates and bats. The positive rate is higher in Egyptian fruit bats, and the disease epidemic areas continue to expand. The human infections occur frequently. As of December 20, 2024, a total of 18 MVD outbreaks had been reported worldwide, resulting in 722 reported cases and 548 deaths. Meta- analysis showed a case fatality rate of about 65.19% (95% CI: 48.07%-80.50%). Populations are generally susceptible, with a higher proportion of the cases in miners and medical workers. Marburg virus specific antibody can be detected in populations and animals in some countries and regions where no cases have been reported in Africa, indicating the potential of virus transmission. Conclusion:The transmission capacity of Marburg virus shows no significant changes, but the areas affected by the virus transmission expands, indicating increased risk for MVD outbreak.

Objective To explore the efficiency improvement in segmenting neural network with the application of Transformer + U-Net artificial intelligence (AI) and modeling with the application of Python scripts in three-dimensional (3D) printing brachytherapy. Methods A Transformer + U-Net AI neural network model was constructed, and Adam optimizer was used to ensure rapid gradient descent. Computed tomography or magnetic resonance imaging data of patients were standardized and processed as self-made data sets. The training set was used to train AI and the optimal result weight parameters were saved. The test set was used to evaluate the AI ability. Python programming language was used to write an automated script to obtain the output segmentation image and convert it to the STL file for import. The source applicator and needle could be automatically modeled. The time of automatic segmentation and modeling and the time of manual segmentation and modeling were entered by two people, and the difference was verified by paired t-test. Results Dice similarity coefficient (DSC), mean intersection over union (MIOU), and Hausdorff distance (HD95) were used for evaluation. DSC was 0.9341, MIOU was 0.8762, and mean HD95 was 2.516. The mean time of manual segmentation was 1187 s, and the mean time of AI segmentation was 145 s (P < 0.01). The mean time of manual modeling was 321 s, and the mean time of modeling with Python automated scripts was 18 s (P < 0.01). Conclusion The application of Transformer + U-Net automatic segmentation and Python automated scripts can effectively improve work efficiency in the 3D printing brachytherapy for cervical cancer.