ObjectiveTo analyze the infection characteristics of human respiratory syncytial virus (HRSV) among children hospitalized with acute lower respiratory tract infection (ALRTI) in a specialized pediatric hospital in Shanghai, so as to provide evidence-based support for optimizing the prevention and control strategies and clinical diagnosis and treatment of respiratory tract infections in children in this region. MethodsA retrospective analysis was performed to the clinical and etiological data of 29 260 children hospitalized for ALRTI in Shanghai Children’s Hospital from January 2021 to December 2024. HRSV and 12 other common respiratory pathogens were detected with multiplex polymerase chain reaction (PCR) and capillary electrophoresis. Demographic and clinical data were collected for statistical analyses. A total of2 412 cases with positive HRSV were divided into the severe group and the non-severe group. Clinical characteristics between the two groups were compared using the Mann-Whitney U test and the chi- square (χ²) test. Additionally, the related influencing factors of severe HRSV infection were explored. ResultsThe overall positivity rate of HRSV from 2021 to 2024 was 8.24% (2 412/29 260), with statistically significant differences observed across the four years (χ²=389.42, P<0.001). The highest positivity rate was in 2021 (14.76%), with a high prevalence throughout the year. In 2022, when non-pharmaceutical interventions (NPIs) were implemented, the HRSV positivity rate was the lowest (4.93%), with a winter-dominant epidemic pattern. In 2023, after the NPIs were lifted, the HRSV positivity rate showed a slight rebound (8.14%), presenting a double-peak pattern. In 2024, the HRSV positivity rate slightly decreased compared to that in 2023 (6.29%), exhibiting a winter and spring-dominant epidemic pattern. Among the hospitalized children with ALRTI, the HRSV positivity rate in males (8.85%) was higher than that in females (7.51%), and the difference was statistically significant (χ²=17.33, P<0.001). Age distribution showed that 82.26% (1 984/2 412) of HRSV infections occurred in children aged 3 years old and below. Besides, as age increased, the infection rate of HRSV showed a gradually decreasing trend (P<0.001). Among the 2 412 children with HRSV infection, the proportion of severe cases was 22.31% (538/2 412), while the non-severe cases accounted for 77.69% (1 874/2 412). Compared with non-severe cases, severe cases were more frequently presented with high fever, longer duration of wheezing, as well as higher rates of underlying diseases or co-infection with Mycoplasma pneumoniae (P<0.001). ConclusionThe prevalence intensity of HRSV varied yearly from 2021 to 2024. After the removal of NPIs in 2023, a slight rebound with a double-peak epidemic pattern was observed. HRSV remained a common pathogen in children hospitalized for ARLTI, and children aged 3 years old and below constituted the highest proportion for infection. Compared with non-severe cases, those with severe HRSV infections were more prone to presenting with high fever and a longer duration of wheezing. Children with positive HRSV who had underlying diseases or co-infection with Mycoplasma pneumonia were more likely to develop severe conditions.

In recent years， repetitive transcranial magnetic stimulation （rTMS） has garnered significant attention as a therapeutic approach for sleep disorders in the elderly. However， the prevailing rTMS protocols are predominantly developed based on normative neurophysiological data derived from young adults and fail to incorporate individualized parameters tailored to the brain characteristics of the elderly. To address this gap， the consensus development group synthesized the latest evidence from 2010 to 2025 and established a standardized rTMS protocol specifically for elderly patients with sleep disorders. Adhering to the Appraisal of Guidelines for Research and Evaluation II （AGREE II） framework， systematically screened randomized controlled trials （RCTs） and systematic reviews regarding rTMS in the treatment of sleep disorders across various conditions. Meanwhile， the Grading of Recommendations Assessment， Development and Evaluation （GRADE） system was employed to rigorously grade the quality of evidence and the strength of recommendations. This consensus guideline delineates precise rTMS protocols for the management of sleep disorders in the elderly， highlights the adjustment of stimulation intensity according to scalp-cortex distance recommends either MRI‑guided neuronavigation or the Beam F3/F4 heuristic approach for accurate target localization， thereby providing precise rTMS intervention protocol for sleep disorders in the elderly， aiming to enhance clinical efficacy while ensuring treatment safety. ［Funded by National Key Research and Development Program （number， 2023YFC3603200）； General Program of Shenzhen Science and Technology Innovation Commission （number， JCYJ20240813112859008， JCYJ20240813112900002）； Youth Program of Shenzhen Kangning Hospital （number， KN2023A004）； www.guidelines-registry.cn number， PREPARE-2026CN530］

With the accelerating trend of population aging, the number of elderly patients with lung cancer continues to rise, and the disease burden is becoming increasingly heavy. The clinical management of these patients faces severe challenges due to their decreased physiological reserve, complex comorbidities, and significant individual heterogeneity. Consequently, under traditional diagnosis and treatment models, doctors often struggle to identify the individualized risks of elderly patients in a timely and comprehensive manner, which can easily lead to decision biases such as undertreatment or overtreatment. In view of this, this study advocates for the establishment of an umbrella decision-making model specifically tailored for elderly lung cancer patients. Grounded in a multidisciplinary team (MDT) platform, this model deeply integrates oncological indicators with the comprehensive geriatric assessment (CGA) system. By holistically considering multidimensional variables including tumor burden, organ function, frailty index, cognitive status, and social support, the model establishes an operational mechanism characterized by "single entry, precise stratification, and targeted selection". Accordingly, patients can be scientifically triaged into distinct intervention tiers, such as active surveillance, minimally invasive surgery, drug therapy, radiotherapy, and best supportive care, thereby achieving real-time alignment between treatment intensity and patient fitness. This article elaborates on the construction logic and key operational procedures of this novel decision-making framework, aiming to guide clinical practice beyond the limitations of a tumor-centric perspective toward a holistic, dynamic, whole-course management strategy. This transition seeks to ensure optimal quality of life and clinical net benefit for elderly patients alongside survival prolongation.

Objective To investigate the anti-intrahepatic cholangiocarcinoma （ICC） activity and mechanism of 2-heptyl-3-hydroxy-4（1H）-quinolone （PQS）, a secondary metabolite of polar marine microorganisms. Methods Patient-derived organoid （PDO） models were established using intrahepatic cholangiocarcinoma （ICC） tumor tissues obtained from Renji Hospital, Shanghai Jiao Tong University School of Medicine. Hematoxylin and eosin （HE） staining was performed to assess the histomorphological characteristics of both patient ICC tissues and corresponding PDOs. Immunohistochemistry （IHC） was employed to evaluate CYP3a expression in patient ICC tissues and PDOs. The antiproliferative activity of PQS against stably passaged PDOs was determined using an adenosine triphosphate （ATP）-based bioluminescence assay, and dose-response curves were fitted to calculate the half-maximal inhibitory concentration （IC₅₀） for assessing the anti-ICC efficacy of PQS. In the human intrahepatic cholangiocarcinoma RBE cell model, the effects of PQS on RBE cell proliferation were evaluated by the cell counting kit-8 （CCK-8） assay; colony formation capacity was assessed by the plate colony formation assay; cell cycle distribution and apoptosis were analyzed by flow cytometry; and the protein expression levels of cyclin-dependent kinase 2（CDK2）, CDK4, RelA（p65）, and nuclear factor-κB1（p50） were detected by Western blotting. Results Two ICC PDO models were successfully established. Histomorphological observation revealed that the PDO tissues after serial passaging exhibited morphological features essentially consistent with the corresponding patient ICC tissues, both presenting as cystic vesicle-like structures. Immunohistochemical analysis demonstrated that CYP3a was expressed in both PDO tissues and patient ICC tissues. ATP-based bioluminescence assay results indicated that PQS effectively suppressed ATP content in PDO tissues, with a fitted dose-response curve yielding an IC₅₀ value of 2.49 µmol/L. In the RBE cell model, PQS inhibited RBE cell viability in a concentration-dependent manner, and the fitted dose-response curve yielded an IC₅₀ value of 1.05 µmol/L. Furthermore, PQS at concentrations of 1, 2, and 4 µmol/L significantly suppressed colony formation of RBE cells, arrested the cell cycle at the S phase, induced apoptosis, and downregulated the expression of proteins associated with the NF-κB signaling pathway. Conclusion ICC PDO models were successfully established, confirming the anti-ICC activity of PQS. PQS inhibited RBE cell proliferation, potentially via the NF-κB signaling pathway, by arresting the cell cycle at the S phase and inducing apoptosis of RBE cells

Objective To investigate the anti-intrahepatic cholangiocarcinoma （ICC） activity and mechanism of 2-heptyl-3-hydroxy-4（1H）-quinolone （PQS）, a secondary metabolite of polar marine microorganisms. Methods Patient-derived organoid （PDO） models were established using intrahepatic cholangiocarcinoma （ICC） tumor tissues obtained from Renji Hospital, Shanghai Jiao Tong University School of Medicine. Hematoxylin and eosin （HE） staining was performed to assess the histomorphological characteristics of both patient ICC tissues and corresponding PDOs. Immunohistochemistry （IHC） was employed to evaluate CYP3a expression in patient ICC tissues and PDOs. The antiproliferative activity of PQS against stably passaged PDOs was determined using an adenosine triphosphate （ATP）-based bioluminescence assay, and dose-response curves were fitted to calculate the half-maximal inhibitory concentration （IC₅₀） for assessing the anti-ICC efficacy of PQS. In the human intrahepatic cholangiocarcinoma RBE cell model, the effects of PQS on RBE cell proliferation were evaluated by the cell counting kit-8 （CCK-8） assay; colony formation capacity was assessed by the plate colony formation assay; cell cycle distribution and apoptosis were analyzed by flow cytometry; and the protein expression levels of cyclin-dependent kinase 2（CDK2）, CDK4, RelA（p65）, and nuclear factor-κB1（p50） were detected by Western blotting. Results Two ICC PDO models were successfully established. Histomorphological observation revealed that the PDO tissues after serial passaging exhibited morphological features essentially consistent with the corresponding patient ICC tissues, both presenting as cystic vesicle-like structures. Immunohistochemical analysis demonstrated that CYP3a was expressed in both PDO tissues and patient ICC tissues. ATP-based bioluminescence assay results indicated that PQS effectively suppressed ATP content in PDO tissues, with a fitted dose-response curve yielding an IC₅₀ value of 2.49 µmol/L. In the RBE cell model, PQS inhibited RBE cell viability in a concentration-dependent manner, and the fitted dose-response curve yielded an IC₅₀ value of 1.05 µmol/L. Furthermore, PQS at concentrations of 1, 2, and 4 µmol/L significantly suppressed colony formation of RBE cells, arrested the cell cycle at the S phase, induced apoptosis, and downregulated the expression of proteins associated with the NF-κB signaling pathway. Conclusion ICC PDO models were successfully established, confirming the anti-ICC activity of PQS. PQS inhibited RBE cell proliferation, potentially via the NF-κB signaling pathway, by arresting the cell cycle at the S phase and inducing apoptosis of RBE cells

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.

As a neglected tropical disease, schistosomiasis remains a major public health challenge in underdeveloped areas, notably Africa. Currently, the national schistosomiasis control programmes in Africa mainly depend on foreign aids; however, conventional international aid models have multiple limitations. To enhance the effectiveness and sustainability of global schistosomiasis control programmes, this article proposes a trinity collaboration model based on international rules, China’s experiences and local needs, which is explained with China aid project of schistosomiasis control in Zanzibar as an example. Based on the successful experiences from the national schistosomiasis control programme in China, this model emphasizes the compliance with World Health Organization guidelines and fully considers local actual needs to promote the effectiveness and sustainability of the schistosomiasis control programme through integrating international resources and promoting China’s experience to meet local needs. The successful practice of the China aid project of schistosomiasis control in Zanzibar provides strong evidence that the model is of great theoretical significance and practical value to improve the efficiency of multilateral collaboration and promote global health governance.

Surgical treatment is one of the key approaches for non-small cell lung cancer (NSCLC). Regular postoperative follow-up is crucial for early detection and timely management of tumor recurrence, metastasis, or second primary tumors. A scientifically sound and reasonable follow-up strategy not only extends patient survival but also significantly improves quality of life, thereby enhancing overall prognosis. This consensus aims to build upon the previous version by incorporating the latest clinical research advancements and refining postoperative follow-up protocols for early-stage NSCLC patients based on different treatment modalities. It provides a scientific and practical reference for clinicians involved in the postoperative follow-up management of NSCLC. By optimizing follow-up strategies, this consensus seeks to promote the standardization and normalization of lung cancer diagnosis and treatment in China, helping more patients receive high-quality care and long-term management. Additionally, the release of this consensus is expected to provide insights for related research and clinical practice both domestically and internationally, driving continuous development and innovation in the field of postoperative management for NSCLC.

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.