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 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 map the super-enhancers remodeling of intestinal gastric cancer and reveal the tumor biological functions of the super-enhancers and the downstream target genes that may be activated.Methods A total of 31 normal gastric mucosal tissues,23 intestinal gastric cancer tissues and 9 intestinal gastric cancer organoids were collected from the Department of Gastroenterology of Army Medical Center of PLA from January to December 2022.Chromatin targeting histone H3K27ac modified chromatin targeting cleavage under targets and tagmentation(CUT&Tag)sequencing was conducted on above tissues.The remodeling profiles of super-enhancers in intestinal gastric cancer were analyzed and the key target genes were identified based on bioinformation tools.CRISPRi technology was used to intervene with the super-enhancers,the expression of target genes was detected with Western blotting,and the proliferation,migration and invasion abilities were detected by CCK-8 assay and Transwell chambers in the control group and the intervention group.Results There was a significant difference in the signal of super-enhancers between intestinal gastric cancer tissues and normal gastric mucosal tissues(P<0.05),and the active super-enhancers in cancer tissues may be involved in biological processes such as negative regulation of the immune system and cell adhesion.The expression of up-regulated cell migration-inducing protein(CEMIP)in tumor cells was regulated by the super-enhancers,and intervening the super-enhancers down-regulated the expression of CEMIP(P<0.05),and inhibited the cell proliferation,invasion and migration abilities of tumor cells(P<0.05).Conclusion Super-enhancer remodeling is observed in intestinal gastric cancer,and they can up-regulate the expression of CEMIP gene and promote the growth,migration and invasion of cancer cells.

Objective To explore the role of SLIT-ROBO Rho GTPase-activating protein 2(srGAP2)in spinal motor neuron degeneration in amyotrophic lateral sclerosis(ALS).Methods Applied bioinformatics analysis to investigate the expression changes of srGAP2 in the spinal cord of human superoxide dismutase 1(hSOD1)mutant ALS transgenic mice.hSOD1 G93A mutant ALS transgenic mice were selected for animal experimental validation,with littermate wild type(WT)mice serving as the control group.A total of 36 pairs were divided into four groups,namely the pre-onset stage,early-onset stage,mid-onset stage,and late-onset stage.The expression changes and cellular localization of srGAP2 in the spinal cord of ALS mice were detected by Real-time PCR,Western blotting and immunofluorescent double-label staining.The hSOD1G93A mutant NSC34 motor neuron-like cell model was established,and in vitro experiments were carried out to detect the changes in srGAP2 expression,and the effects of srGAP2 over-expression on the viability of hSOD1G93A mutant NSC34 cells and the growth of cell protrusions.Results Bioinformatics analysis revealed abnormally low expression of srGAP2 in the spinal cord of hSOD1 mutant ALS mice.Animal experiments verified that compared with the WT mice,the expression of srGAP2 was reduced at both mRNA level and protein level in the spinal cord of hSOD1G93A mutant ALS transgenic mice at early-onset,mid-onset and late-onset stages.Compared with the WT mice,srGAP2 integral absorbance(IA)values in srGAP2+/NeuN+double-positive cells in the anterior horn of the spinal cord of hSOD1G93A mutant ALS transgenic mice were lower,srGAP2 IA values in srGAP2+/GFAP+double-positive cells were higher;Compared with the hSOD1WT NSC34 cells,the expression of srGAP2 was reduced at both mRNA level and protein level in hSOD1G93A mutant NSC34 cells.Over-expression of srGAP2 elevated the viability of hSOD1G93A mutant NSC34 cells,and up-regulated the expression level of synapse-related protein β Ⅲ-tubulin and growth associated protein 43(GAP43).Conclusion Low expression of srGAP2 is closely associated with the progression of ALS,while over-expression of srGAP2 can promote outgrowth of cell protrusions and exert a protective effect on spinal motor neurons in ALS.

Nipah virus (NiV) and related viruses form a distinct henipavirus genus within the Paramyxoviridae family. NiV continues to spillover into the humans causing deadly outbreaks with increasing human-bat interaction. NiV encodes the large protein (L) and phosphoprotein (P) to form the viral RNA polymerase machinery. Their sequences show limited homologies to those of non-henipavirus paramyxoviruses. We report two cryo-electron microscopy (cryo-EM) structures of the Nipah virus (NiV) polymerase L-P complex, expressed and purified in either its full-length or truncated form. The structures resolve the RNA-dependent RNA polymerase (RdRp) and polyribonucleotidyl transferase (PRNTase) domains of the L protein, as well as a tetrameric P protein bundle bound to the L-RdRp domain. L-protein C-terminal regions are unresolved, indicating flexibility. Two PRNTase domain zinc-binding sites, conserved in most Mononegavirales, are confirmed essential for NiV polymerase activity. The structures further reveal anchoring of the P protein bundle and P protein X domain (XD) linkers on L, via an interaction pattern distinct among Paramyxoviridae. These interactions facilitate binding of a P protein XD linker in the nucleotide entry channel and distinct positioning of other XD linkers. We show that the disruption of the L-P interactions reduces NiV polymerase activity. The reported structures should facilitate rational antiviral-drug discovery and provide a guide for the functional study of NiV polymerase.
Nipah Virus/chemistry* ; Cryoelectron Microscopy ; Viral Proteins/genetics* ; RNA-Dependent RNA Polymerase/genetics* ; Phosphoproteins/genetics* ; Humans ; Models, Molecular ; Protein Binding

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.

The existing relevant standards and registration of disposable sterile surgical drapes were introduced,and four times of national supervision and sample inspection of disposable sterile surgical drapes from 2017 to 2023 were described.The unqualified items found in the supervision and sample inspection were analyzed,the exploratory research projects carried out were summarized and other problems encountered during the sample inspection were pointed out.Relevant enterprises were suggested to strengthen the implementation of industry standards,take seriously the product material identification information,clearly limit the raw materials used and standardize the product registration name.References were provided for the industrial supervision and development of disposable sterile surgical drapes.[Chinese Medical Equipment Journal,2025,46(5):66-72]

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.