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 analyze the antiviral effect of molnupiravir against influenza virus in vitro and in vivo.Methods The antiviral ability of molnupiravir against influenza virus strain H1N1 PR8 was detected in vitro and in vivo.H uman non-small cell lung cancer cell line(A549 cells)was used as an in vitro model of PR8 infection.The antiviral effects of molnupiravir on virus replication,protein synthesis,and viral particle formation were analyzed using real-time fluorescence quantitative polymerase chain reaction(qRT-PCR),Western blot(WB)assay,and plaque assay.PR8 nose-dripping infected C57BL/6 female mice were used as an in vivo infection model.The antivi-ral ability of molnupiravir was evaluated by detecting viral load,pathological changes,and immunohistochemistry in the control group,administration group,inoculation group,and inoculation-administration group.Results In vitro test results showed that molnupiravir had no significant inhibitory effect on influenza virus replication,protein syn-thesis,and virus particle formation(all P＞0.05).In vivo test results showed that compared with mice infected with H1N1 alone,the viral load in the lung tissue of mice treated with molnupiravir declined significantly,and the extent of pathological changes was milder.Immunohistochemical detection showed a significant weakening in nuclear protein(NP)antigen signal,and the expression levels of interferon(IFN)-α,interleukin(IL)-4,and IL-6 in the lungs were lower(all P＜0.01).Conclusion As a precursor with antiviral activity,molnupiravir can not exert anti-viral activity in lung-derived cells cultured in vitro,but can be transformed into an active form in the host,which significantly decreases the ability of H1N1 influenza virus to proliferate in the lungs and thereby alleviates the da-mage of virus to lung tissue.

This consensus was developed by the Orthodontic Society of the Chinese Stomatological Association to provide a systematic, scientific, and practical guideline for informed consent in orthodontic care. Orthodontic treatment is typically lengthy, highly individualized, and involves multiple factors such as growth and development, occlusal function, and facial esthetics. Rapid technological advances and diverse risk profiles make the traditional reliance on orthodontist experience or institutional templates insufficient to ensure patients′ full understanding and autonomous decision-making. To address this, the expert panel conducted extensive reviews of domestic and international guidelines, analyzed representative dispute cases, and performed multicenter patient-clinician surveys. Using a multi-round Delphi method, the group established a standardized informed consent framework covering the initial consultation, treatment, and retention phases. The consensus emphasizes that informed consent is not only a fundamental legal and ethical requirement but also a key step in building trust, improving patient compliance, and enhancing treatment satisfaction. Orthodontists should clearly and comprehensively explain treatment plans, potential risks, uncertainties, and associated costs, while respecting the autonomy of patients or guardians, and maintain continuous communication and dynamic evaluation throughout the treatment process. The release of this consensus provides unified and authoritative guidance for clinical orthodontics, helping to standardize informed consent, enhance its transparency, safeguard patient rights, reduce medical risks, and promote high-quality, sustainable development of orthodontic practice.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Objective To analyze the antiviral effect of molnupiravir against influenza virus in vitro and in vivo.Methods The antiviral ability of molnupiravir against influenza virus strain H1N1 PR8 was detected in vitro and in vivo.H uman non-small cell lung cancer cell line(A549 cells)was used as an in vitro model of PR8 infection.The antiviral effects of molnupiravir on virus replication,protein synthesis,and viral particle formation were analyzed using real-time fluorescence quantitative polymerase chain reaction(qRT-PCR),Western blot(WB)assay,and plaque assay.PR8 nose-dripping infected C57BL/6 female mice were used as an in vivo infection model.The antivi-ral ability of molnupiravir was evaluated by detecting viral load,pathological changes,and immunohistochemistry in the control group,administration group,inoculation group,and inoculation-administration group.Results In vitro test results showed that molnupiravir had no significant inhibitory effect on influenza virus replication,protein syn-thesis,and virus particle formation(all P＞0.05).In vivo test results showed that compared with mice infected with H1N1 alone,the viral load in the lung tissue of mice treated with molnupiravir declined significantly,and the extent of pathological changes was milder.Immunohistochemical detection showed a significant weakening in nuclear protein(NP)antigen signal,and the expression levels of interferon(IFN)-α,interleukin(IL)-4,and IL-6 in the lungs were lower(all P＜0.01).Conclusion As a precursor with antiviral activity,molnupiravir can not exert anti-viral activity in lung-derived cells cultured in vitro,but can be transformed into an active form in the host,which significantly decreases the ability of H1N1 influenza virus to proliferate in the lungs and thereby alleviates the da-mage of virus to lung tissue.

To investigate the awareness of cognitive impairment disorders among residents of the Xizang Autonomous Region and its influencing factors, thereby providing a basis for targeted prevention and treatment efforts.

Objective To explore the efficacy of bilateral facial muscle training combined with visual electromyography biofeedback on facial nerve function recovery in patients with idiopathic facial nerve palsy. Methods Patients with idiopathic facial nerve palsy admitted to Shanghai Fifth People’s Hospital, Fudan University from July 2022 to July 2024 were selected and randomly divided into a control group and an intervention group. The control group received conventional physical factor therapy, while the intervention group received bilateral facial muscle training combined with visual electromyography biofeedback therapy based on the control group’s regimen. After 20 treatment sessions, the total effective rate, the House-Brackmann (H-B) facial nerve grading system, the Sunnybrook Facial Grading System (SFGS) score, and the average value ratio of maximal amplitudes of bilateral frontalis and zygomaticus muscles were compared between the two groups. Results A total of 90 patients were included, 45 in each group. After 20 treatment sessions, the total effective rate was significantly higher in the intervention group than in the control group (84.4% vs 75.6%, P＝0.003). Compared with the control group, the intervention group demonstrated a significantly lower H-B grade (P＝0.003) and a higher SFGS score (P＝0.001). The average value ratios of maximal amplitudes of the affected versus healthy side frontalis (P＝0.013) and zygomatic (P＝0.022) muscles were higher in the intervention group than in the control group. Conclusions Bilateral facial muscle training combined with visual electromyography biofeedback is an effective approach for treating idiopathic facial nerve palsy, effectively promoting the recovery of facial nerve function, and improving facial symmetry and facial muscle function.

This consensus was developed by the Orthodontic Society of the Chinese Stomatological Association to provide a systematic, scientific, and practical guideline for informed consent in orthodontic care. Orthodontic treatment is typically lengthy, highly individualized, and involves multiple factors such as growth and development, occlusal function, and facial esthetics. Rapid technological advances and diverse risk profiles make the traditional reliance on orthodontist experience or institutional templates insufficient to ensure patients′ full understanding and autonomous decision-making. To address this, the expert panel conducted extensive reviews of domestic and international guidelines, analyzed representative dispute cases, and performed multicenter patient-clinician surveys. Using a multi-round Delphi method, the group established a standardized informed consent framework covering the initial consultation, treatment, and retention phases. The consensus emphasizes that informed consent is not only a fundamental legal and ethical requirement but also a key step in building trust, improving patient compliance, and enhancing treatment satisfaction. Orthodontists should clearly and comprehensively explain treatment plans, potential risks, uncertainties, and associated costs, while respecting the autonomy of patients or guardians, and maintain continuous communication and dynamic evaluation throughout the treatment process. The release of this consensus provides unified and authoritative guidance for clinical orthodontics, helping to standardize informed consent, enhance its transparency, safeguard patient rights, reduce medical risks, and promote high-quality, sustainable development of orthodontic practice.