Objective To study the five-year survival status and influencing factors of elderly patients with lung cancer complicated with chronic obstructive pulmonary disease (COPD). Methods A cohort study was conducted to follow up 450 patients with lung cancer and chronic obstructive pulmonary disease who were hospitalized in our hospital from January 2018 to December 2023. The endpoint of the follow-up was the end of a five-year period or death. The Life Tables method was used to calculate survival rates and plot survival curves. The Cox proportional hazards model was used to analyze the influencing factors of five-year survival. Results The results indicated that the overall five-year survival rate of patients was 4.89%, and it decreased year by year. Cox regression analysis showed that age, gender, family functioning, and psychological status significantly influenced patient survival rate (all P<0.05). Stratified analysis found that the smoking status, family functioning, and psychological status of male patients all had an impact on survival rate (all P<0.05), while the psychological status of female patients had a more significant impact on survival (P=0.008). Conclusion This study provides a scientific basis for comprehensive intervention of elderly lung cancer patients with COPD. It is recommended that clinical attention should be paid to psychological and family factors to improve patient prognosis.

Diabetic nephropathy （DKD）， as a common microvascular complication of diabetes mellitus （DM）， is a major cause of end-stage renal disease （ESRD）. Its clinical manifestations include increased urinary protein excretion， thickening of the glomerular basement membrane， and renal tubulointerstitial fibrosis. The pathogenesis of DKD is complex and involves multiple factors， including disordered glucose metabolism， hemodynamic alterations， and oxidative stress. Although modern medical approaches can alleviate certain symptoms， they still have limitations such as insufficient therapeutic targeting and prominent adverse effects. The transforming growth factor-β/Smad （TGF-β/Smad） signaling pathway is not only a tissue fibrosis pathway that has attracted considerable attention in recent years， but also regulates multiple protein molecules， including the glomerular podocyte slit diaphragm protein Podocin， interleukin-1β （IL-1β）， and superoxide dismutase （SOD）， thereby participating in various pathological processes and ultimately mediating renal injury. Flavonoid compounds， owing to their sustained pharmacological effects， broad spectrum of action， and high safety profile， have become ideal candidates for targeted therapy research in DKD. Existing studies have shown that these compounds can exert inhibitory effects on renal fibrosis， alleviate inflammatory responses， protect podocytes， and reduce oxidative stress by regulating the interactions between the TGF-β/Smad signaling pathway and the aforementioned protein molecules， thereby maintaining renal structure and function， reducing proteinuria， and significantly improving DKD lesions. This review briefly outlines the composition and functions of the TGF-β/Smad signaling pathway， elucidates the mechanisms by which this pathway regulates DKD， and focuses on summarizing major studies from the past decade on flavonoid-based interventions in DKD through targeted inhibition of the TGF-β/Smad signaling pathway. Furthermore， it discusses the considerable therapeutic potential of flavonoids in the treatment of this disease， aiming to provide a scientific basis for future clinical prevention and treatment of DKD and to promote the development of targeted drugs.

Objective To study the photodynamic performance and the killing effect of photodynamic therapy on lung cancer of novel chlorin compounds 2-（4-（5,15,20-triphenyl-7H,8H-porphyrin-10-yl） phenoxy） acetic acid（D1）and 4-（4-（5,15,20-triphenyl-7H,8H-porphyrin-10-yl） phenoxy） butanoic acid （D2）. Methods The ultraviolet visible absorption spectrum and fluorescence spectrum of D1 and D2 were determined. The singlet oxygen generation capacity of D1 and D2 was measured by using DPBF as singlet oxygen capture agent. Fluorescence assay was used to detect the cellular phagocytosis rate of the compounds in A549 cells, and MTT assay was used to detect their dark toxicity and phototoxicity. A nude mouse model of lung cancer was established to investigate the antitumor activity of the compounds mediated photodynamic action in vivo, and the blood concentration of D2 in nude mice, its distribution in tumor tissue and skin tissue were further detected. Results D1 and D2 had strong absorption at 652 nm with the best excitation wavelength at 429 nm and 427 nm, and the optimal emission wavelength was at about 659 nm. They also had a higher singlet oxygen generation rate than the control drug m-THPC. D1 and D2 had no dark toxicity at concentrations below 10 μmol/L, and could be ingested by A549 cells, basically reaching saturation in 18~24 hours. After laser irradiation at 650 nm wavelength, D1 and D2 showed significant antitumor activity in vivo and in vitro （P<0.01）. However, D2 could selectively accumulate in tumor tissues after administration, and the optimal treatment time was less than 30 min after administration. Conclusion D2 had excellent photodynamic antitumor activity and could selectively aggregate in tumor tissues, which had the potential to be a candidate drug for photosensitizer and treatment of lung cancer with independent intellectual property rights, and was worth further research.

ObjectiveTo investigate the value of predictive models established based on machine learning methods in predicting the risk of metabolic associated fatty liver disease （MAFLD）， and to analyze its key risk factors. MethodsA retrospective analysis was performed for the 50 variables of 2 168 healthy individuals who underwent physical examination in Department of Health Assessment， Xiyuan Hospital， China Academy of Chinese Medical Sciences， from January 2021 to December 2024， including body composition， past history， and laboratory tests， and according to whether they were diagnosed with MAFLD or not， they were divided into MAFLD group with 265 individuals and non-MAFLD group with 1 903 individuals. The Mann-Whitney U test was used for comparison of continuous data between two groups， and the chi-square test was used for comparison of categorical data between two groups. Randomly split the research data into a training set and a validation set in a 70% to 30% ratio. Predictive factors were screened from the training set data using univariate analysis， LASSO regression， and multivariate Logistic regression analysis. Predictive models were then constructed using seven machine learning methods： Logistic regression， decision tree， random forest （RF）， eXtreme gradient boosting， light gradient boosting machine， support vector machine， and artificial neural network. Model performance was evaluated by plotting receiver operating characteristic curve for the validation set and calculating the area under the curve （AUC）， sensitivity， specificity， and Youden index for each model. Furthermore， the SHapley Additive exPlanation （SHAP） method was used to analyze the contribution of variables in the optimal model. ResultsThe prevalence rate of MAFLD among the 2 168 subjects was 12.22% （265/2 168）. Smoking， diastolic blood pressure， phase angle， visceral fat area， muscle fat ratio， waist-to-hip ratio， aspartate aminotransferase， non-HDL-C/HDL-C ratio， triglyceride-glucose index， and gallstones were independent risk factors for MAFLD （all P<0.05）. The seven predictive models of support vector machine， eXtreme gradient boosting， decision tree， light gradient boosting machine， artificial neural network， RF， and Logistic regression had an AUC of 0.738， 0.754， 0.757， 0.786， 0.795， 0.796， and 0.815， respectively， in the validation set， among which the RF model had the best discriminatory ability （AUC=0.796， 95% confidence interval： 0.754 — 0.839）， with a sensitivity of 81.01%， a specificity of 63.16%， and a Youden index of 44.17%. The SHAP analysis showed that visceral fat area， waist-to-hip ratio， and diastolic blood pressure were the top three predictive factors in terms of importance. ConclusionThe RF model， constructed based on body composition and clinical indicators， has a good performance in predicting the risk of MAFLD， and its interpretability can help to identify high-risk individuals in the early stage in clinical practice.

Numerous techniques for C2 screw fixation have been recently reported. However, concerns remain regarding the risk of spinal cord or vertebral artery injury and inadequate biomechanical stability. To our knowledge, the specific transforaminal “in-out-in” screw fixation technique has not been previously reported. This study aimed to investigate the feasibility and preliminary clinical outcomes of a transforaminal “in-out-in” multi-cortical purchase screw for posterior C2 screw fixation. Between October 2022 and March 2023, 10 patients underwent posterior atlantoaxial internal fixation. All patients had severe hypoplasia of the C2 pedicle on at least one side, precluding the use of standard C2 pedicle screws. A transforaminal “in-out-in” screw was used as an alternative. No spinal cord injury, vascular injury, or other major complications were observed. No implant failure was noted at the final follow-up. In conclusion, the transforaminal “in-out-in” screw may achieve rigid three-column fixation with multiple cortical purchases. It represents a safe and effective alternative for posterior C2 fixation in patients with severely narrow C2 pedicles where traditional pedicle screw placement is not feasible.

Inteins are unique protein insertion sequences capable of self-excision, enabling the covalent ligation of flanking extein peptides via amide bond formation. This process proceeds spontaneously without requiring external enzymes, cofactors, or chemical reagents, granting inteins exceptional biocompatibility and traceless performance in protein engineering applications. Split inteins represent a specialized and versatile subclass whose splicing domains are encoded by two separate gene fragments rather than a single continuous open reading frame. These fragments, known as the N-terminal (IntN) and C-terminal (IntC) split inteins, associate through non-covalent interactions including hydrophobic forces, hydrogen bonds, and van der Waals forces to assemble into an active three-dimensional structure, which then drives efficient extein ligation and enables protein trans-splicing. Protein trans-splicing mediated by split inteins has become a cornerstone for traceless protein ligation owing to its high specificity and irreversibility, fundamentally reshaping strategies for protein modification, assembly, and functional regulation. Compared with traditional chemical ligation methods, split intein systems require no complex chemical derivatization of peptide fragments and can operate efficiently at micromolar concentrations under physiological conditions, thus avoiding structural and functional damage caused by organic reagents. In contrast to enzymatic ligation tools such as sortase, split inteins eliminate the need for additional enzymes or cofactors, simplifying reaction systems, reducing costs, and minimizing non-specific side products. These distinctive advantages render split inteins highly promising for applications in chemical biology, synthetic biology, and biopharmaceutical development. In recent years, deepened mechanistic understanding has established structure-guided rational design as the primary approach to overcoming key limitations of split inteins, including intrinsic aggregation propensity, strict extein sequence dependence, and limited splicing efficiency. Bioinformatic tools have been used to identify aggregation-prone regions in the IntN fragment, and site-directed mutagenesis of hydrophobic residues, relocation of split sites, or removal of misfolding-prone sequences has substantially reduced in vitro aggregation and improved soluble expression and assembly activity. Rational engineering of catalytic residues and adjacent flexible loops has relaxed strict amino acid preferences at extein junctions, enhancing sequence tolerance and reducing the risk of functional impairment in target proteins. Consensus design based on multiple sequence alignments has yielded ultra-fast splicing variants such as Cfa DnaE and Cat-TerL, which exhibit significantly accelerated kinetics and improved tolerance to denaturing conditions. Meanwhile, advances in structural biology have further clarified the conformational dynamics and catalytic mechanisms of splicing, supporting the precise design of high-performance intein modules. On this basis, electrostatic interaction tuning and metagenomic screening have yielded multiple mutually orthogonal split intein pairs, enabling selective multi-fragment protein ligation and providing new routes for the efficient synthesis of large multi-domain functional proteins. With these engineered split inteins offering continuously improved performance and expanded applicability, protein trans-splicing has been widely applied in numerous cutting-edge areas of protein research and biomedicine. In gene delivery, split intein-based systems overcome the packaging limit of adeno-associated viral vectors, enabling the accurate reconstitution of large therapeutic proteins and base editors in target cells, thereby enhancing the efficacy and scope of gene therapy for genetic diseases. In internal protein sequence editing, split inteins mediate precise sequence replacement and modification in flexible regions or loops of target proteins, without the need for complex multi-step ligation and protein refolding involved in traditional protein semisynthesis. In protein-protein interaction studies, intein-mediated splicing covalently captures transient and weak intracellular complexes, enabling sensitive, high-throughput interaction detection and drug screening. In synthetic biology, conditionally controllable splicing systems support the construction of diverse intracellular and cell-surface biological logic gates for the precise regulation of cellular behavior. In mechanistic biochemical research, split inteins enable photocatalytic proximity labeling and site-specific tagging, allowing the preparation of homogeneous protein samples carrying precise post-translational modifications such as ubiquitination and polyglutamylation for chromatin interactome analysis and epigenetic studies. Moreover, covalent trapping strategies using split inteins stabilize transient enzymatic intermediates, providing unprecedented insights into molecular mechanisms such as nucleosome ubiquitination that are difficult to elucidate using conventional methods. This review systematically summarizes key technological advances in split inteins over the past decade, highlighting engineering strategies, mechanistic insights, and the development of orthogonal components. It comprehensively surveys emerging applications at the frontiers of protein research, analyzes current core challenges, and proposes future directions, particularly emphasizing artificial intelligence-driven de novo design and novel splicing pathways to break existing technical bottlenecks. By enabling traceless, efficient, and versatile protein manipulation, split inteins continue to serve as indispensable tools that drive innovation in protein engineering and fundamental life science research.

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: To investigate the trends in incidence and mortality of lung cancer in Huangpu District, Shanghai Municipality from 2002 to 2019, so as to provide the evidence for formulating lung cancer prevention and control measures. Methods: Data of lung cancer incidence and mortality among residents in Huangpu District from 2002 to 2019 were collected through the Shanghai Cancer Registration and Reporting Management System. The crude incidence and mortality of lung cancer was calculated, and standardized by the data from the Chinese Fifth National Population Census in 2000 (Chinese-standardized rate) and the Segi's world standard population in 1960 (world-standardized rate). The trends in incidence and mortality of lung cancer among residents by age and gender were evaluated using annual percent change (APC). Results: A total of 12 965 cases of lung cancer were reported in Huangpu District from 2002 to 2019, and the crude incidence rate was 80.66/105, the Chinese-standardized incidence rate was 34.54/105, and the world-standardized incidence rate was 31.30/105, all showing upward trends (APC=4.588%, 2.933% and 3.247%, all P<0.05). A total of 10 102 deaths of lung cancer were reported, and the crude mortality rate was 62.30/105, showing an upward trend (APC=0.959%, P<0.05); the Chinese-standardized mortality was 25.93/105, and the world-standardized mortality was 22.05/105, both showing downward trends (APC=-1.282% and -1.263%, both P<0.05). The crude incidence and mortality rates of lung cancer in males were higher than those in females (101.39/105 vs. 60.52/105, 85.45/105 vs. 39.87/105, both P<0.05). The crude incidence and mortality rates of lung cancer showed upward trends with age (both P<0.05), reaching their peaks in the age groups of 80-<85 years (341.37/105) and 85 years or above (355.97/105), respectively. Conclusions The incidence of lung cancer showed an upward trend, while the mortality showed a downward trend in Huangpu District from 2002 to 2019. Elderly men were the high-risk group for lung cancer incidence and mortality.

Monkeypox is a viral zoonotic disease,and there is currently a lack of safe and effective vac-cines against the monkeypox virus.Therefore,screening and developing vaccine candidates is of signifi-cant practical importance.With the rapid advancement of molecular biology and plant genetic engineer-ing,plant bioreactors offer promising potential for producing vaccine proteins due to their advantages,in-cluding safety,cost-effectiveness,and scalability.In this study,we focused on the monkeypox protein B6R.The recombinant expression plasmid pFolia40108-B6R-Fer was successfully constructed using am-plification,enzyme digestion,and flexible linker tandem ferritin technology.A complete transient expres-sion system in Nicotiana benthamiana and a purification system for the recombinant monkeypox protein were established.The optimal expression time was determined to be 12-14 days,with a final purified pro-tein concentration of approximately 1 mg/mL and a yield of 0.85 mg/kg fresh weight.The purified B6R-Fer recombinant protein self-assembled into spherical virus-like particles(VLPs)with an average particle size of 24 nm.The B6R-Fer recombinant protein from this study shows promising potential for use in the development and screening of plant-derived monkeypox vaccine candidates.

Objective To investigate the feasibility of magnetic tracer technique for locating pulmonary nodules.Methods A tracer magnet and a matching puncture instrument were designed by ourselves for locating pulmonary nodules.After preliminarily verifying the feasibility of the operation in the isolated lung,four beagle dogs were used as animal models to perform puncture localization of the assumed lesions in the upper lobe of the right lung under the guidance of X-ray by using self-designed tracer magnets and puncture instruments,and the positioning effect was observed and evaluated after thorax opening.The operation time required for the tracer magnet implantation,whether there is bleeding at the puncture site,whether the tracer magnet is displaced,and the positioning time of pulmonary nodules after thorax opening were recorded.Results Two tracer magnets were successfully inserted into the upper lobe of the right lung under X-ray guidance in four beagle dogs,and the magnets were successfully attracted and fixed.The median insertion time of the tracer magnet was 5 minutes(4 to 7 minutes),and the insertion process was smooth without bleeding at the puncture site.After thorax opening,oval forceps were used to conveniently locate the location of the tracer magnet,achieving accurate positioning of pulmonary nodules with a median positioning time of 13 seconds(10 to 17 seconds),and the tracer magnet did not shift during the whole process.Conclusion The magnetic tracer technique is simple to operate and pricise for localization of pulmonary nodules.With further optimization of the operation process,this technique is expected to be applied in clinic.