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).

Functional disorders of the Golgi apparatus are harmful to the health of organisms, leading to various diseases. Removing damaged Golgi apparatus is crucial for maintaining cellular homeostasis, therefore, autophagy of Golgi apparatus has gradually attracted attention. This article summarizes Golgi autophagy, briefly describes its structure and functions, Golgi autophagy receptors, and the role of Golgi autophagy in disease treatment. It also proposes the new concept of Golgimedicine, which looks forward to the role of Golgi in disease diagnosis, treatment, prognosis, genetic diseases, and rare diseases. This article aims to explore the scientific connotations of Golgi autophagy, Golgi structure and function from the perspective of Golgimedicine, providing theoretical references for drug target research, new drug development, and the healthy development of humanity.

Objective To analyze the pollution characteristics of 16 polycyclic aromatic hydrocarbons (PAHs) in atmospheric PM_2.5 in Yanta District and Lianhu District of Xi'an City, and assess their health risks to exposed populations through inhalation pathways. Methods From 2020 to 2022, monitoring sites were set up in Yanta District and Lianhu District of Xi'an City, and PM_2.5 samples were collected regularly every month. The mass concentrations of PAHs were determined. The analysis and evaluation were carried out according to different years, regions, and seasons. The sources of PAHs in the atmosphere were identified by calculating characteristic ratios. Health risk assessments through inhalation routes were conducted for certain polycyclic aromatic hydrocarbons and their total carcinogenic equivalent concentrations. Results The average mass concentrations of PAHs in Yanta District and Lianhu District were 6.38 ng/m³ and 6.06 ng/m³, respectively, with no statistically significant difference (P>0.05). Except for fluoranthene, there was no statistically significant difference in other PAHs between regions (P>0.05). Except for acenaphthylene and anthracene, the concentrations of other PAHs showed a decreasing trend year by year (P<0.05). The total mass concentration of PAHs in both urban areas showed a trend of winter>spring>autumn>summer (P<0.05), and all categories of PAHs showed the highest levels in winter and the lowest levels in summer (P<0.05). The proportion of 5-ring PAHs was the highest in summer, while the proportion of 4-ring PAHs was the highest in winter. The main sources of atmospheric PAHs in the two districts were a mixture of coal combustion, motor vehicle emissions, and biomass burning. The HQ values of benzo[a]pyrene and TEQs in both districts were less than 1. The carcinogenic risk through inhalation pathways for TEQs was 1.15×10^-6, exceeding the acceptable level (1×10^-6). Conclusion The pollution of PAHs in Yanta District and Lianhu District of Xi'an City continues to decrease, with seasonal differences. The main sources are mixed sources of coal combustion, motor vehicle emissions, and biomass burning, and overall PAHs pose a potential carcinogenic risk to residents.

ObjectiveTo explore the main mechanism of self-precipitation formed during the decoction of Sinitang（SNT）， and to provide a research basis for exploring the differences in the toxic and effective components of this compound. MethodsThe average precipitation yields of SNT， Glycyrrhizae Radix et Rhizoma（GRR）-Aconiti Lateralis Radix Praeparata（ALRP） decoction（GF）， ALRP-Zingiberis Rhizoma（ZR） decoction（FJ）， GRR-ZR decoction（GJD）， ALRP decoction（FZ）， ZR decoction（GJ） and GRR decoction（GC） were determined. The four main self-precipitation samples of SNT， GF， FZ and GC were physically characterized by particle size， scanning electron microscopy（SEM）， pH， total dissolved solids（TDS）， conductivity， and Fourier transform infrared spectroscopy（FT-IR） analysis. The chemical compositions of SNT decoction and its different phases was identified by ultra-performance liquid chromatography-quadrupole-electrostatic field orbitrap high-resolution mass spectrometry（UPLC-Q-Exactive Orbitrap-MS） for SNT， SNT self-precipitation and SNT supernatant， and the contents of its main toxic and effective components were determined by high performance liquid chromatography（HPLC）. ResultsPrecipitation yield results of the 7 samples of SNT decoction and single decoction showed that SNT had the highest self-precipitation yield. The formation of SNT self-precipitation was mainly related to the reaction between ALRP and GRR components to form complexes， and FT-IR showed that GRR had the greatest influence on the formation of self-precipitation. A total of 110 components were identified in the SNT decoction， including 100 components in the SNT self-precipitation and 106 components in the SNT supernatant. And quantitative results of the main toxic and effective components revealed that the reaction between ALRP and GRR components formed complexes， resulting in the following content hierarchy for free components：SNT decoctionsupernatantself-precipitation， these components included free liquiritin， benzoylmesaconine， benzoylaconitine， benzoylhypacoitine， liquiritigenin， aconitine， hypoaconitine， isoliquiritigenin and ammonium glycyrrhizinate. ConclusionSNT exhibits spontaneous precipitation during compound decoction， with GRR exerting the greatest influence on its formation. This suggests GRR plays a significant role in the detoxification of SNT. The differences in the self-precipitated toxic-effective components of SNT compound decoction primarily manifest as changes in component content， reflecting the characteristics of SNT "deposition in vitro and sustained release in vivo" and the importance of "administered at draught" in the clinical application of SNT.

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.

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.

ObjectiveTemporal heterogeneity in lung cancer presents as fluctuations in the biological characteristics, genomic mutations, proliferation rates, and chemotherapeutic responses of tumor cells over time, posing a significant barrier to effective treatment. The complexity of this temporal variance, coupled with the spatial diversity of lung cancer, presents formidable challenges for research. This article will pave the way for new avenues in lung cancer research, aiding in a deeper understanding of the temporal heterogeneity of lung cancer, thereby enhancing the cure rate for lung cancer. MethodsRaman spectroscopy emerges as a powerful tool for real-time surveillance of biomolecular composition changes in lung cancer at the cellular scale, thus shedding light on the disease’s temporal heterogeneity. In our investigation, we harnessed Raman spectroscopic microscopy alongside multivariate statistical analysis to scrutinize the biomolecular alterations in human lung epithelial cells across various timeframes after benzo(a)pyrene exposure. ResultsOur findings indicated a temporal reduction in nucleic acids, lipids, proteins, and carotenoids, coinciding with a rise in glucose concentration. These patterns suggest that benzo(a)pyrene induces structural damage to the genetic material, accelerates lipid peroxidation, disrupts protein metabolism, curtails carotenoid production, and alters glucose metabolic pathways. Employing Raman spectroscopy enabled us to monitor the biomolecular dynamics within lung cancer cells in a real-time, non-invasive, and non-destructive manner, facilitating the elucidation of pivotal molecular features. ConclusionThis research enhances the comprehension of lung cancer progression and supports the development of personalized therapeutic approaches, which may improve the clinical outcomes for patients.

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.