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.

BACKGROUND:Studies have shown that mitochondrial oxidative stress has an important role in the development of knee osteoarthritis,and Hemin can regulate the expression of mitochondria-related proteins. OBJECTIVE:To study the regulatory effect of Hemin on oxidative stress in mouse chondrocytes and its interventional effect and mechanism in knee osteoarthritis. METHODS:(1)In vitro cell experiment:Primary chondrocytes from C57BL/6 mice were extracted and induced with 10 ng/mL interleukin-1β to construct an in vitro chondrocyte model of osteoarthritis.The optimal concentration of Hemin(0,1,10,20,40,80,and 160 μmol/L)for the intervention in mouse chondrocytes was determined by cell counting kit-8 method.Chondrocytes were randomly divided into control group,model group(interleukin-1β)and Hemin group(interleukin-1β+Hemin).Reactive oxygen species,mitochondrial membrane potential and apoptosis of chondrocytes in each group were detected.(2)In vivo experiment:Adult C57BL/6 mice were randomly divided into normal group,model group(osteoarthritis)and Hemin group(osteoarthritis+Hemin),with eight mice in each group.After 4 weeks of Hemin treatment,the behavioral test and histopathological observation of the knee joint were performed in each group.Changes in extracellular matrix-related protein expression and apoptosis in chondrocytes and the expression level of Nrf2/HO-1 protein in cartilage tissue were detected. RESULTS AND CONCLUSION:In vitro experiment:the optimal concentration of Hemin on primary chondrocytes was 40 μmol/L.Compared with the model group,the level of reactive oxygen species was significantly reduced,the mitochondrial membrane potential was significantly improved,and the apoptosis of chondrocytes was reduced in the hemin-treated interleukin-1β-induced chondrocytes.In vivo experiment:After 4 weeks of treatment,compared with the model group,the lower limb function of mice in the Hemin group was significantly improved,the histopathological score was significantly improved,and the apoptosis of knee chondrocytes was significantly reduced.All these findings indicate that Hemin can alleviate oxidative stress,restore mitochondrial function and reduce apoptosis in mouse chondrocytes induced by interleukin-1β.Hemin can improve extracellular matrix degradation,promote chondrocyte anabolism,reduce catabolism and reduce chondrocyte apoptosis in knee osteoarthritis.It may act by activating the chondrocyte Nrf2/HO-1 signaling pathway in the inflammatory environment.

OBJECTIVE: To explore the therapeutic effects and underlying mechanisms of Dendrobium officinale (Tiepi Shihu) extract (DOE) on insomnia. METHODS: Forty-two male Sprague-Dawley rats were randomly divided into 6 groups (n=7 per group): normal control, model control, melatonin (MT, 40 mg/kg), and 3-dose DOE (0.25, 0.50, and 1.00 g/kg) groups. Rats were raised in a strong-light (10,000 LUX) and -noise (>80 db) environment (12 h/d) for 16 weeks to induce insomnia, and from week 10 to week 16, MT and DOE were correspondingly administered to rats. The behavior tests including sodium pentobarbital-induced sleep experiment, sucrose preference test, and autonomous activity test were used to evaluate changes in sleep and emotions of rats. The metabolic-related indicators such as blood pressure, blood viscosity, blood glucose, and uric acid in rats were measured. The pathological changes in the cornu ammonis 1 (CA1) region of rat brain were evaluated using hematoxylin and eosin staining and Nissl staining. Additionally, the sleep-related factors gamma-aminobutyric acid (GABA), glutamate (GA), 5-hydroxytryptamine (5-HT), and interleukin-6 (IL-6) were measured using enzyme linked immunosorbent assay. Finally, we screened potential sleep-improving receptors of DOE using polymerase chain reaction (PCR) array and validated the results with quantitative PCR and immunohistochemistry. RESULTS: DOE significantly improved rats' sleep and mood, increased the sodium pentobarbital-induced sleep time and sucrose preference index, and reduced autonomic activity times (P<0.05 or P<0.01). DOE also had a good effect on metabolic abnormalities, significantly reducing triglyceride, blood glucose, blood pressure, and blood viscosity indicators (P<0.05 or P<0.01). DOE significantly increased the GABA content in hippocampus and reduced the GA/GABA ratio and IL-6 level (P<0.05 or P<0.01). In addition, DOE improved the pathological changes such as the disorder of cell arrangement in the hippocampus and the decrease of Nissel bodies. Seven differential genes were screened by PCR array, and the GABA_A receptors (Gabra5, Gabra6, Gabrq) were selected for verification. The results showed that DOE could up-regulate their expressions (P<0.05 or P<0.01). CONCLUSION DOE demonstrated remarkable potential for improving insomnia, which may be through regulating GABA_A receptors expressions and GA/GABA ratio.
Animals ; Dendrobium/chemistry* ; Rats, Sprague-Dawley ; Male ; Sleep Initiation and Maintenance Disorders/blood* ; Plant Extracts/therapeutic use* ; Receptors, GABA-A/metabolism* ; Noise/adverse effects* ; Light/adverse effects* ; gamma-Aminobutyric Acid/metabolism* ; Sleep/drug effects* ; Rats ; Receptors, GABA/metabolism*

OBJECTIVE: Paridis Rhizoma (Chonglou in Chinese), a traditional Chinese herbal medicine, has been shown have strong anti-tumor effects. Paris saponin VII (PSVII), an active constituent isolated from Paridis Rhizoma, was demonstrated to significantly suppress the proliferation of BxPC-3 cells in our previous study. Here, we aimed to elucidate the anti-pancreatic ductal adenocarcinoma (PDAC) effect of PSVII and the underlying mechanism. METHODS: Cell viability was determined by CCK-8, colony formation, and cell migration assays. Cell apoptosis and reactive oxygen species (ROS) production were measured by flow cytometry with annexin V/propidine iodide (Annexin V/PI) and 2',7'-dichlorodihydrofluorescein diacetate (DCFH-DA), respectively. Pyroptosis was evaluated by morphological features, Hoechst 33342/PI staining assay, and release of lactate dehydrogenase (LDH). JC-1 fluorescent dye was employed to measure mitochondrial membrane potential. Western blotting and reverse transcription-quantitative polymerase chain reaction (RT-qPCR) were used to determine the levels of proteins or mRNAs. The effect in vivo was assessed by a xenograft tumor model. RESULTS: PSVII inhibited the viability of PDAC cells (BxPC-3, PANC-1, and Capan-2 cells) and induced gasdermin E (GSDME) cleavage, as well as the simultaneous cleavage of Caspase-3 and poly (ADP-ribose) polymerase 1 (PARP). Knockdown of GSDME shifted PSVII-induced pyroptosis to apoptosis. Additionally, the effect of PSVII was significantly attenuated by Z-Asp(OMe)-Glu(OMe)-Val-Asp(OMe)-fluoromethylketone (Z-DEVD-FMK), on the induction of GSDME-dependent pyroptosis. PSVII also elevated intracellular ROS accumulation and stimulated Bax and Caspase-3/GSDME to conduct pyroptosis in PDAC cells. The ROS scavenger N-acetyl cysteine (NAC) suppressed the release of LDH and inhibited Caspase-9, Caspase-3, and GSDME cleavage in PDAC cells, ultimately reversing PSVII-induced pyroptosis. Furthermore, in a xenograft tumor model, PSVII markedly suppressed the growth of PDAC tumors and induced pyroptosis. CONCLUSION These results demonstrated that PSVII exerts therapeutic effects through Caspase-3/GSDME-dependent pyroptosis and may constitute a novel strategy for preventing chemotherapeutic resistance in patients with PDAC in the future.

Transformer models have emerged as pivotal tools within the realm of drug discovery, distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes. Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data, these models showcase remarkable efficacy across various tasks, including new drug design and drug target identification. The adaptability of pre-trained transformer-based models renders them indispensable assets for driving data-centric advancements in drug discovery, chemistry, and biology, furnishing a robust framework that expedites innovation and discovery within these domains. Beyond their technical prowess, the success of transformer-based models in drug discovery, chemistry, and biology extends to their interdisciplinary potential, seamlessly combining biological, physical, chemical, and pharmacological insights to bridge gaps across diverse disciplines. This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields. In our review, we elucidate the myriad applications of transformers in drug discovery, as well as chemistry and biology, spanning from protein design and protein engineering, to molecular dynamics (MD), drug target identification, transformer-enabled drug virtual screening (VS), drug lead optimization, drug addiction, small data set challenges, chemical and biological image analysis, chemical language understanding, and single cell data. Finally, we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.

Objective To investigate the related mechanism which metformin inhibited the proliferation of HCT116 colorectal cancer cells via down-regulating the expression of up-frameshift protein 1(UPF1).Methods TCGA and UALCAN databases were utilized to analyze the expression level of UPF1,while Western blotting and Real-time PCR were performed to validate the differences of UPF1 expressions in colon cancer tissues and adjacent normal tissues.Clone formation assay,CCK-8 assay,wound healing assay and Transwell invasion assay were used to examine the effects of knockdown UPF1 on the proliferation,migration and invasion of HCT116 cells respectively.The HCT116 cell dataset with UPF1 knockdown was screened from GEO database for Kyoto Encydopedia of Genes and Genomes(KEGG)pathway analysis,the expression level of differential genes that enriched in Hippo pathway were verified by Real-time PCR.The HCT116 cells were treated with metformin,Western blotting and Real-time PCR were employed to detect the UPF1 expression.Mendelian randomization analysis was performed to explore the causal association between metformin treatment and colorectal cancer.Results Analysis of TCGA and UALCAN databases showed that both UPF1 mRNA and protein were highly expressed in colon cancer tissues and the expression level of UPF1 was closely correlated with clinicopathologic stage and lymph node metastasis.Compared with adjacent normal tissues,the UPF1 protein and mRNA were highly expressed in colon cancer tissues.Knockdown UPF1 expression could inhibit the proliferation,migration and invasive ability of HCT116 cells.There were 8 differential genes affect the Hippo pathway by KEGG enrichment analysis,Real-time PCR experiments confirmed that CTNNB1,BMP4,TEAD2,PARD6G and FZD1 mRNA decreased in HCT116 cells with UPF1 knockdown.Both UPF1 protein and mRNA expressions decreased after metformin treatment in HCT116 cells.Mendelian randomization analysis showed a negative causal association between metformin treatment and colorectal cancer.Conclusion Knockdown of UPF1 expression inhibits the proliferation of HCT116 cells through regulating Hippo pathway.Metformin can reduce the UPF1 expression for further inhibiting the proliferation of colorectal cancer cells.

Objective To analyze the relationships of serum soluble triggering receptor ex-pressed on myeloid cells-2(sTREM2),P-selectin and the length of hyperdense middle cerebral arter-y sign(HMCAS)with the effect of thrombolysis and short-term prognosis in patients with acute cere-bral infarction(ACI).Methods A total of 109 ACI patients with thrombolytic therapy were divided into ineffective group(n=27)and effective group(n=82)based on thrombolysis outcomes.Ninety days after treatment,the 109 patients were further divided into good prognosis group(n=78)and poor prognosis group(n=31)according to the modified Rankin Scale(mRS).General information,the National Institutes of Health Stroke Scale(NIHSS)score,serum sTREM2 level,P-selectin levels,and HMCAS length were compared between the two groups.Binary Logistic regression model was used to analyze the influencing factors of thrombolysis outcomes in ACI patients.Pearson correlation coef-ficient was calculated to analyze the correlation between laboratory indicators and mRS in ACI pa-tients.Receiver operating characteristic(ROC)curve was plotted to analyze the predictive values of serum sTREM2,P-selectin and HMCAS length for prognosis of patients.Results The NIHSS score at admission in the effective group was significantly lower than that in the ineffective group(P＜0.01).The serum sTREM2 and P-selectin levels as well as the HMCAS length in the effective group were significantly lower or shorter than those in the ineffective group(P＜0.01).The results of bina-ry Logistic regression analysis showed that NIHSS score＞15(OR=2.649,95％CI,1.357 to 5.167),serum sTREM2 above the mean level(OR=2.686,95％CI,1.860 to 8.786),P-selectin a-bove the mean level(OR=4.043,95％CI,1.860 to 8.786),and HMCAS length＞1 mm(OR=3.827,95％CI,1.740 to 8.414)were all risk factors for poor thrombolysis outcomes in ACI pa-tients(P＜0.01).The serum sTREM2 and P-selectin levels as well as the HMCAS length in the good prognosis group were significantly lower or shorter than those in the poor prognosis group(P＜0.01).Serum sTREM2,P-selectin and HMCAS length were all positively correlated with mRS in ACI patients after thrombolytic therapy(r=0.686,0.597,0.662,P＜0.001).Areas under the curve(AUCs)for predicting the prognosis of ACI patients after thrombolytic therapy by serum sTREM2,P-selectin,HMCAS length,and the combination of the three indicators were 0.833,0.862,0.889 and 0.914 respectively,with sensitivities of 0.806,0.742,0.806 and 0.742 re-spectively,and specificities of 0.923,0.897,0.936 and 0.949,respectively.Conclusion The effect of thrombolysis in ACI patients is related to NIHSS score at admission,serum sTREM2 level,P-selectin level,and HMCAS length.High levels of serum sTREM2 and P-selectin and a long HMCAS may increase the risk of poor thrombolysis outcomes in ACI patients.

Medical device related infections caused by bacteria are common complications in clinical practice,and preventing bacterial colonization on the surface of medical materials is one of the important challenges in the medical field.Therefore,there is an urgent need to construct medical coatings that combine antibacterial properties and biocompatibility.In this study,a γ-polyglutamic acid(γ-PGA)complex with long-chain alkyl quaternary ammonium salts formed by electrostatic and hydrophobic interactions was prepared,which was insoluble in water but soluble in organic solvents(e.g.,ethanol),and was capable of constructing antimicrobial coatings on the surfaces of medical materials in a simple and efficient manner.The bactericidal effect of the coating was verified using viable bacteria counting experiments,and the results showed that the bactericidal rate of the coated thermoplastic polyurethane(TPU)membrane against Staphylococcus aureus was greater than 99.9%compared with that of the uncoated TPU membrane.In addition,a cytotoxicity assay was performed using the L929 fibroblast and cell proliferation detection kit(CCK-8),which showed that the survival rate of L929 fibroblasts on coated TPU was greater than 90%.Meanwhile,the hemolysis rate of coated erythrocytes was tested using fresh rabbit red blood cells(RBCs),and the hemolysis rate on the coated TPU surface was 1.5%.The above results indicated that the coating had good biocompatibility.The preparation method of medical antibacterial coating reported in this study provided a new idea for preventing bacterial infections related to implantable/interventional medical devices.

Transformer models have emerged as pivotal tools within the realm of drug discovery,distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes.Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data,these models showcase remarkable efficacy across various tasks,including new drug design and drug target identification.The adaptability of pre-trained trans-former-based models renders them indispensable assets for driving data-centric advancements in drug discovery,chemistry,and biology,furnishing a robust framework that expedites innovation and dis-covery within these domains.Beyond their technical prowess,the success of transformer-based models in drug discovery,chemistry,and biology extends to their interdisciplinary potential,seamlessly combining biological,physical,chemical,and pharmacological insights to bridge gaps across diverse disciplines.This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields.In our review,we elucidate the myriad applications of transformers in drug discovery,as well as chemistry and biology,spanning from protein design and protein engineering,to molecular dynamics(MD),drug target iden-tification,transformer-enabled drug virtual screening(VS),drug lead optimization,drug addiction,small data set challenges,chemical and biological image analysis,chemical language understanding,and single cell data.Finally,we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.