Lung adenocarcinoma (LUAD) is one of the most universal types of cancer all over the world and its morbidity continues to rise year by year. Growing evidence has demonstrated that endoplasmic reticulum stress is highly activated in cancer cells and plays a key role in regulating the fate of cancer cells. However, the role and mechanism of endoplasmic reticulum stress in lung adenocarcinoma genesis and development remains unclear. In this research, we developed a prognostic model to predict the overall survival of patients with LUAD utilizing endoplasmic reticulum stress-related genes and screened out potential small molecular compounds, which could assist the clinician in making accurate decisions and better treat LUAD patients. Firstly, we downloaded 419 endoplasmic reticulum stress-related genes (ERSRGs) from Molecular Signatures Database (MSigDB). Secondly, we obtained information about the transcriptome profiling and corresponding clinical data of 59 normal samples and 535 lung adenocarcinoma samples from The Cancer Genome Atlas (TCGA) database. Next, we used the DESeq2 package to identify differentially expressed genes related to endoplasmic reticulum stress. We performed univariate Cox, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis to establish a prognostic model for LUAD patients based on ERSRGs. Then, we carried out univariate and multivariate independent prognostic analysis of endoplasmic reticulum stress-related gene (ERSRG) score and some clinical traits of lung adenocarcinoma. Additionally, we developed a clinically applicable nomogram for predicting survival for LUAD patients over one, three, and five years. Moreover, we carried out a drug sensitivity analysis to identify novel small molecule compounds for LUAD treatment. Finally, we examined the tumor microenvironment (TME) and immune cell infiltrating analysis to explore the interactions between immune and cancer cells. 142 differentially expressed ERSRGs were identified by using the DESeq2 package. A prognostic model was built based on 7 differentially expressed ERSRGs after performing univariate Cox regression, LASSO regression, and multivariate Cox regression analysis. According to the results of univariate and multivariate independent prognostic analysis, we found ERSRG score can be used as an independent prognostic maker. Using the Kaplan–Meier curves, we found low-risk patients had higher survival probability than high-risk patients in both training set and test set. A nomogram was drawn to predict 1-, 3-, and 5-year survival probability. The calibration curves explained good performance of the model for the prediction of survival. Phenformin, OSU-03012, GSK-650394 and KIN001-135 were identified as the drugs most likely to provide important information to clinicians about the treatment of LUAD patients. A prognostic prediction model was established based on 7 differentially expressed ERSRGs (PDX1, IGFBP1, DDIT4, PPP1R3G, CFTR, DERL3 and NUPR1), which could effectively predict the prognosis of LUAD patients and give a reference for clinical doctors to help LUAD patients to make better treatment tactics. Based on the 4 small molecule compounds (Phenformin, OSU-03012, GSK-650394 and KIN001-135) we discovered, targeting endoplasmic reticulum stress-related genes may also be a therapeutic approach for LUAD patients.

Substrate-controlled diversity-oriented synthesis of polycyclic frameworks via [4 + 2] and [3 + 2] annulations between ninhydrin-derived Morita–Baylis–Hillman (MBH) adducts and 3,4-dihydroisoquinolines under similar reaction conditions have been developed. The reaction provides diversity-oriented synthesis of a series of novel and structurally complex spiro multi heterocyclic skeletons in good yields (up to 87% and 90%, respectively) with excellent diastereoselectivities (up to >25:1 dr). In particular, the switchable [4 + 2] and [3 + 2] annulation reactions are controlled by tuning the hydroxyl protecting group on the ninhydrin-derived MBH adduct to deliver structural diverse spiro[indene-2,2′-[1,3]oxazino[2,3-a]isoquinoline] and spiro[indene-2,1′-pyrrolo[2,1-a]isoquinoline], respectively. Furthermore, the relative configuration and chemical structure of two kinds of cycloadducts were confirmed through X-ray diffraction analysis.

Due to their facile synthesis and friendly functionalization, gold nanoparticles (AuNPs) have been applied in all kinds of biosensors. More importantly, these biosensors, with the combination of AuNPs and immunoassay, are expected to be used for the detection of different compounds with low concentrations in complex samples. In this study, a AuNPs-labeled antibody immunoprobe was prepared and combined with a fluorescence-quenching principle and a background fluorescence-quenching immunochromatographic assay (bFQICA), achieving rapid on-site detection. By using a portable fluorescence immunoquantitative analyzer and a QR code with a built-in standard curve, the rapid quantitative determination for nitrofurazone metabolite of semicarbazide (SEM) in animal-derived foods was realized. The limits of detection (LODs) for bFQICA in egg, chicken, fish, and shrimp were 0.09, 0.10, 0.12, and 0.15 μg kg⁻¹ for SEM, respectively, with the linear range of 0.08–0.41 μg L⁻¹, the recoveries ranging from 73.5% to 109.2%, and the coefficient of variation <15%, only taking 13 min for the SEM detection. The analysis of animal-derived foods by bFQICA complied with that of liquid chromatography-tandem mass spectrometry (LC-MS/MS).

Objective The aim of this study was to explore the action mechanism of Sanhua decoction in treating ischemic stroke through network pharmacology and molecular docking technology. Methods Active components and related targets of Sanhua decoction were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. A “drug-active component-target” network was constructed, and core components were selected through topological analysis. Disease targets related to ischemic stroke were screened based on the Online Mendelian Inheritance in Man (OMIM), Therapeutic Target Database (TTD), GeneCards, DrugBank, and PharmGKB databases. The intersection of active component–related targets and ischemic stroke disease targets was identified to obtain potential targets of Sanhua decoction for treating ischemic stroke, represented using a Venn diagram. The STRING database was used to construct a protein–protein interaction (PPI) network of potential targets and filter for core targets. Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of core targets were performed using the DAVID database and Metascape platform. Molecular docking verification of core targets and core components was conducted using AutoDock. Results A total of 52 active components and 142 related targets were screened from Sanhua decoction, with core active components including luteolin, nobiletin, β-sitosterol, eucalyptol, and aloe-emodin. There were 2,991 ischemic stroke–related targets, with 98 potential targets identified in the intersection with active component–related targets. An analysis of the PPI network analysis revealed 23 core targets, including serine/threonine-protein kinase 1 (AKT1), tumor protein p53 (TP53), and mitogen-activated protein kinase 3 (MAPK3). Enrichment analysis obtained 35 GO results and 41 signaling pathways. Molecular docking results indicated good binding between core components and core targets. Conclusion Multiple components in the classic formula Sanhua decoction, such as luteolin and nobiletin, may play a role in treating ischemic stroke by regulating core targets like AKT1, TP53, and MAPK3, and participating in multiple signaling pathways.