Objective To understand the driver gene mutation status in patients with non-small cell lung cancer (NSCLC) in Xi'an City, and to analyze the association with environmental exposure factors. Methods A total of 305 NSCLC patients admitted to the First Affiliated Hospital of the Air Force Medical University from January 2019 to December 2023 were included. The driver gene mutation status was observed, and the relationship with environmental exposure factors was analyzed. Results The driver gene mutation rate of 305 patients was 46.89%, with EGFR gene mutation accounting for the highest proportion, and 4 cases of gene co-mutations were detected. There was a difference in gender among patients with different single drive gene mutations (P<0.05), and the proportion of EGFR in women was significantly higher (P<0.05). Univariate analysis showed that there were statistical differences in family history, smoking history, long-term cooking history, and fried smoked food intake between patients with driver gene mutation and patients without driver gene mutation (P<0.05). Logistic regression analysis suggested that long-term cooking history (OR=2.392), and fried smoked food intake (OR=2.849) were the environmental exposure factors affecting EGFR gene mutation (P<0.05), and smoking history (OR=1.377) was an environmental exposure factor of KRAS gene mutation (P<0.05). Conclusion EGFR gene mutation accounts for the highest proportion of NSCLC patients in Xi'an City, and is mainly female. Long-term cooking history, and fried smoked food intake are related to EGFR gene mutation. There is a certain association between smoking history and KRAS gene mutation.

The innate immune system can be boosted in response to subsequent triggers by pre-exposure to microbes or microbial products, known as “trained immunity”. Compared to classical immune memory, innate trained immunity has several different features. Firstly, the molecules involved in trained immunity differ from those involved in classical immune memory. Innate trained immunity mainly involves innate immune cells (e.g., myeloid immune cells, natural killer cells, innate lymphoid cells) and their effector molecules (e.g., pattern recognition receptor (PRR), various cytokines), as well as some kinds of non-immune cells (e.g., microglial cells). Secondly, the increased responsiveness to secondary stimuli during innate trained immunity is not specific to a particular pathogen, but influences epigenetic reprogramming in the cell through signaling pathways, leading to the sustained changes in genes transcriptional process, which ultimately affects cellular physiology without permanent genetic changes (e.g., mutations or recombination). Finally, innate trained immunity relies on an altered functional state of innate immune cells that could persist for weeks to months after initial stimulus removal. An appropriate inducer could induce trained immunity in innate lymphocytes, such as exogenous stimulants (including vaccines) and endogenous stimulants, which was firstly discovered in bone marrow derived immune cells. However, mature bone marrow derived immune cells are short-lived cells, that may not be able to transmit memory phenotypes to their offspring and provide long-term protection. Therefore, trained immunity is more likely to be relied on long-lived cells, such as epithelial stem cells, mesenchymal stromal cells and non-immune cells such as fibroblasts. Epigenetic reprogramming is one of the key molecular mechanisms that induces trained immunity, including DNA modifications, non-coding RNAs, histone modifications and chromatin remodeling. In addition to epigenetic reprogramming, different cellular metabolic pathways are involved in the regulation of innate trained immunity, including aerobic glycolysis, glutamine catabolism, cholesterol metabolism and fatty acid synthesis, through a series of intracellular cascade responses triggered by the recognition of PRR specific ligands. In the view of evolutionary, trained immunity is beneficial in enhancing protection against secondary infections with an induction in the evolutionary protective process against infections. Therefore, innate trained immunity plays an important role in therapy against diseases such as tumors and infections, which has signature therapeutic effects in these diseases. In organ transplantation, trained immunity has been associated with acute rejection, which prolongs the survival of allografts. However, trained immunity is not always protective but pathological in some cases, and dysregulated trained immunity contributes to the development of inflammatory and autoimmune diseases. Trained immunity provides a novel form of immune memory, but when inappropriately activated, may lead to an attack on tissues, causing autoinflammation. In autoimmune diseases such as rheumatoid arthritis and atherosclerosis, trained immunity may lead to enhance inflammation and tissue lesion in diseased regions. In Alzheimer’s disease and Parkinson’s disease, trained immunity may lead to over-activation of microglial cells, triggering neuroinflammation even nerve injury. This paper summarizes the basis and mechanisms of innate trained immunity, including the different cell types involved, the impacts on diseases and the effects as a therapeutic strategy to provide novel ideas for different diseases.

The Pharmacopeia of the People’s Republic of China 2025 Edition (referred to as the Chinese Pharmacopoeia 2025 Edition, ChP 2025) will be promulgated and implemented. This article introduces the process of development of ChP 2025 Edition (Volume Ⅱ), including the selection, the revision of general notices,the addition and revision of drug monographs, etc., and provides some analysis and examples to illustrate,which can facilitate the readers to understand and implement the ChP 2025 Edition (Volume Ⅱ).

Multiple sclerosis (MS) is a neuroinflammatory demyelinating disease, mediated by pathogenic T helper 17 (Th17) cells. However, the therapeutic effect is accompanied by the fluctuation of the proportion and function of Th17 cells, which prompted us to find the key regulator of Th17 differentiation in MS. Here, we demonstrated that the triggering receptor expressed on myeloid cells 2 (TREM-2), a modulator of pattern recognition receptors on innate immune cells, was highly expressed on pathogenic CD4-positive T lymphocyte (CD4⁺ T) cells in both patients with MS and experimental autoimmune encephalomyelitis (EAE) mouse models. Conditional knockout of Trem-2 in CD4⁺ T cells significantly alleviated the disease activity and reduced Th17 cell infiltration, activation, differentiation, and inflammatory cytokine production and secretion in EAE mice. Furthermore, with Trem-2 knockout in vivo experiments and in vitro inhibitor assays, the TREM-2/zeta-chain associated protein kinase 70 (ZAP70)/signal transducer and activator of transcription 3 (STAT3) signal axis was essential for Th17 activation and differentiation in EAE progression. In conclusion, TREM-2 is a key regulator of pathogenic Th17 in EAE mice, and this sheds new light on the potential of this therapeutic target for MS.
Animals ; Humans ; Mice ; CD4-Positive T-Lymphocytes/pathology* ; Cell Differentiation ; Encephalomyelitis, Autoimmune, Experimental/metabolism* ; Mice, Inbred C57BL ; Multiple Sclerosis ; Th1 Cells/pathology*

Aim To investigate the effect of benzyl iso-thiocyanate (BITC) on the proliferation of mouse U14 cervical cancer cells and to explore the mechanism of cytotoxicity based on transcriptomic data analysis. Methods The effect of BITC on U14 cell activity was detected by MTT, nuclear morphological changes were observed by Hochest 33258 and fluorescent inverted microscope, cell cycle and apoptosis were determined by flow cytometry, and the transcriptome database of U14 cells before and after BITC (20 μmol · L

Objective To investigate the mechanism and protective effect of Humanin(HN)on rotenone(Rot)-induced toxic damage for dopamine neurons.Methods The Rot-poisened PC12 cell model was constructed,and the control group,the Rot poisening group,the HN pretreated Rot poisening group,and the HN treatment group were set up.ELISA was used to detect the content of HN inside and outside of Rot-infected cells,CCK-8 assay was used to detect cell viability,and ATP detection kit was used to detect the intracellular ATP content.Dichloro-dihydro-fluorescein diacetate(DCFH-DA)assay was used to detect the level of reactive oxygen species(ROS)in cells.Western blotting was performed to detect the expression level of mitochondrial autophagy regulatory proteins Pink1,Parkin,p62,LC3,mitochondrial biogenesis regulatory protein PGC1α,division/fusion regulatory proteins OPA1,MFN2,DRP1,p-DRP1 and antioxidant stress regulatory proteins Keap1 and Nrf2.HBAD-mcherry-EGFP-LC3 adenovirus transfected cells was used to observed the number of autophagosomes and autophagolysosomes.Results The results showed that the intracellular concentration of HN in PC12 in the Rot poisening group was significantly higher than that in the control group(P＜0.05);Compared with the control group,the Rot poisening group had significantly decreased activity of PC12 cells,decreased ATP content and increased production of ROS.After the poisen of Rot in PC12 cells,the expression of Pink1 and p-Parkin,the ratio of LC3Ⅱ/LC3Ⅰ and the expression of p-DRP1 in mitochondrial fusion protein was increased,while the expression of p62,the expression of mitochondrial biogenesis protein PGC1 α,mitochondrial fusion proteins MFN2 and OPA1,and antioxidant stress proteins Keap1 and Nrf2 were decreased(all P＜0.05).The number of autophagosomes and autophagolysosomes in PC12 cells in the Rot poisening group was higher than that in the control group(P＜0.05),and HN pretreatment(20 μmol/L)could significantly improve the changes mentioned above caused by Rot poisening(P＜0.05).Conclusion HN ameliorates Rot-induced toxic damage for dopamine neurons by inhibiting mitophagy and mitochondrial division and promoting mitochondrial biogenesis and fusion,and anti-oxidative stress.

Objective To investigate the human papillomavirus(HPV)infection and genotype distribution characteristics among male reproductive health outpatients,and to compare the differences among different age groups of outpatients.Methods A total of 1 658 males,visited in the Affiliated Hospital of Shanghai Institute of Planned Parenthood Research from 2018 to 2022,were selected and 23 HPV genotypes were detected by PCR-reverse dot hybridization.Results Among the 1 658 subjects,the overall HPV infection rate was 22.50%.Single infection accounted for 66.76%,which was the main infection type.HPV infection among different age groups were statistically significant(P<0.001),with HPV infection of 16.83%,22.87%,34.63%,and 29.35%for 18-30,31-40,41-50,and≥51 years,respectively.The top 5 high risk HPV genotypes were HPV52(3.56%),HPV16(3.26%),HPV39(2.41%),HPV51(2.17%),HPV58(2.17%),and the top 1 low risk HPV genotype was HPV81(2.90%).The proportions of infected individuals in this study that could be completely covered by bivalent,quadrivalent,and nine-valent HPV vaccines were 7.77%,12.33%,and 26.27%,respectively.Conclusion The predominant infection type among male reproductive health outpatients was single infection type.HPV 52,16,39,51 and 58 were the most common high risk genotypes,while HPV 81 was the most common low risk genotype.Individuals aged 41-50 years had the highest HPV infection rate.

There are huge differences between tumor cells and normal cells in material metabolism, and tumor cells mainly show increased anabolism, decreased catabolism, and imbalance in substance metabolism. These differences provide the necessary material basis for the growth and reproduction of tumor cells, and also provide important targets for the treatment of tumors. Ferroptosis is an iron-dependent form of cell death characterized by an imbalance of iron-dependent lipid peroxidation and lipid membrane antioxidant systems in cells, resulting in excessive accumulation of lipid peroxide, causing damage to lipid membrane structure and loss of function, and ultimately cell death. The regulation of ferroptosis involves a variety of metabolic pathways, including glucose metabolism, lipid metabolism, amino acid metabolism, nucleotide metabolism and iron metabolism. In order for tumor cells to grow rapidly, their metabolic needs are more vigorous than those of normal cells. Tumor cells are metabolically reprogrammed to meet their rapidly proliferating material and energy needs. Metabolic reprogramming is mainly manifested in glycolysis and enhancement of pentose phosphate pathway, enhanced glutamine metabolism, increased nucleic acid synthesis, and iron metabolism tends to retain more intracellular iron. Metabolic reprogramming is accompanied by the production of reactive oxygen species and the activation of the antioxidant system. The state of high oxidative stress makes tumor cells more susceptible to redox imbalances, causing intracellular lipid peroxidation, which ultimately leads to ferroptosis. Therefore, in-depth study of the molecular mechanism and metabolic basis of ferroptosis is conducive to the development of new therapies to induce ferroptosis in cancer treatment. Ferroptosis, as a regulated form of cell death, can induce ferroptosis in tumor cells by pharmacologically or genetically targeting the metabolism of substances in tumor cells, which has great potential value in tumor treatment. This article summarizes the effects of cellular metabolism on ferroptosis in order to find new targets for tumor treatment and provide new ideas for clinical treatment.

Background Bacteria are the most diverse and widely sourced microorganisms in the indoor air of subway stations, where pathogenic bacteria can spread through the air, leading to increased health risks. Objective To understand the status and distribution characteristics of indoor air bacterial pollution in subway stations and compartments in a city of Central South China, and to provide a scientific basis for formulating intervention measures to address indoor air bacteria pollution in subways. Methods Three subway stations and the compartments of trains parking there in a city in Central South China were selected according to passenger flow for synchronous air sampling and monitoring. Temperature, humidity, wind speed, carbon dioxide (CO₂), fine particulate matter (PM_2.5), and inhalable particulate matter (PM₁₀) were measured by direct reading method. In accordance with the requirements of Examination methods for public places-Part 3: Airborne microorganisms (GB/T 18204.3-2013), air samples were collected at a flow rate of 28.3 L·min⁻¹, and total bacterial count was estimated. Bacterial microbial species were identified with a mass spectrometer and pathogenic bacteria were distinguished from non-pathogenic bacteria according to the Catalogue of pathogenic microorganisms transmitted to human beings issued by National Health Commission. Kruskal-Wallis H test was used to compare the subway hygiene indicators in different regions and time periods, and Bonferroni test was used for pairwise comparison. Spearman correlation test was used to evaluate the correlation between CO₂ concentration and total bacterial count. Results The pass rates were 100.0% for airborne total bacteria count, PM_2.5, and PM₁₀ in the subway stations and train compartments, 94.4% for temperature and wind speed, 98.6% for CO₂, but 0% for humidity. The overall median (P₂₅, P₇₅) total bacteria count was 177 (138,262) CFU·m⁻³. Specifically, the total bacteria count was higher in station halls than in platforms, and higher during morning peak hours than during evening peak hours (P<0.05). A total of 874 strains and 82 species were identified by automatic microbial mass spectrometry. The results of identification were all over 9 points, and the predominant bacteria in the air were Micrococcus luteus (52.2%) and Staphylococcus hominis (9.8%). Three pathogens, Acinetobacter baumannii (0.3%), Corynebacterium striatum (0.1%), and Staphylococcus epidermidis bacilli (2.2%) were detected in 23 samples (2.6%), and the associated locations were mainly distributed in train compartments during evening rush hours. Conclusion The total bacteria count in indoor air varies by monitoring sites of subway stations and time periods, and there is a risk of opportunistic bacterial infection. Attention should be paid to cleaning and disinfection during peak passenger flow hours in all areas.

Objective To study the pharmacokinetic characteristics of the test formulation of compound lidocaine cream and reference formulation of lidocaine and prilocaine cream in Chinese healthy subjects and to evaluate whether there is bioequivalence between the two formulations.Methods A single-center,single-dose,randomized,open-label,two-period,two-sequence,crossover design was used.This study included 40 healthy subjects,and in each period,test formulation or reference formulation 60 g was applied to the skin in front of both thighs(200 cm2 each side,a total of 400 cm2)under fasting conditions,and the drug was left on for at least 5 h after application.The concentrations of lidocaine and prilocaine in plasma were determined using liquid chromatography-tandem mass spectrometry(LC-MS/MS)method.Pharmacokinetic parameters were calculated using WinNonlin 8.0 software to evaluate the bioequivalence of the two formulations.Results After the application of the test formulation compound lidocaine cream and the reference formulation lidocaine and prilocaine cream on both thighs of the subjects,the pharmacokinetic parameters of lidocaine in plasma were as follows:Cmax were(167.27±91.33)and(156.13±66.86)ng·mL-1,AUC0-t were(1 651.78±685.09)and(1 636.69±617.23)ng·mL-1·h,AUC0-∞ were(1 669.85±684.65)and(1 654.37±618.30)ng·mL-1·h,the adjusted geometric mean ratios were 104.49％,101.88％and 101.89％,respectively,with 90％confidence intervals of 98.18％-111.20％,97.80％-106.13％and 97.87％-106.07％,all within the range of 80.00％-125.00％.The pharmacokinetic parameters of prilocaine in plasma were as follows:Cmax were(95.66±48.84)and(87.52±39.16)ng·mL-1,AUC0-t were(790.86±263.99)and(774.14±256.42)ng·mL-1·h,AUC0_m were(807.27±264.67)and(792.84±254.06)ng·mL-1 h,the adjusted geometric mean ratios were 107.34％,103.55％and 102.98％,respectively with 90％confidence intervals of 101.69％-113.31％,99.94％-107.30％and 99.65％-106.43％,all within the range of 80.00％-125.00％.Conclusion The test formulation compound lidocaine cream and the reference formulation lidocaine and prilocaine cream are bioequivalent.