Tumor drug resistance is an important problem in the failure of chemotherapy and targeted drug therapy, which is a complex process involving chromatin remodeling. SWI/SNF is one of the most studied ATP-dependent chromatin remodeling complexes in tumorigenesis, which plays an important role in the coordination of chromatin structural stability, gene expression, and post-translation modification. However, its mechanism in tumor drug resistance has not been systematically combed. SWI/SNF can be divided into 3 types according to its subunit composition: BAF, PBAF, and ncBAF. These 3 subtypes all contain two mutually exclusive ATPase catalytic subunits (SMARCA2 or SMARCA4), core subunits (SMARCC1 and SMARCD1), and regulatory subunits (ARID1A, PBRM1, and ACTB, etc.), which can control gene expression by regulating chromatin structure. The change of SWI/SNF complex subunits is one of the important factors of tumor drug resistance and progress. SMARCA4 and ARID1A are the most widely studied subunits in tumor drug resistance. Low expression of SMARCA4 can lead to the deletion of the transcription inhibitor of the BCL2L1 gene in mantle cell lymphoma, which will result in transcription up-regulation and significant resistance to the combination therapy of ibrutinib and venetoclax. Low expression of SMARCA4 and high expression of SMARCA2 can activate the FGFR1-pERK1/2 signaling pathway in ovarian high-grade serous carcinoma cells, which induces the overexpression of anti-apoptosis gene BCL2 and results in carboplatin resistance. SMARCA4 deletion can up-regulate epithelial-mesenchymal transition (EMT) by activating YAP1 gene expression in triple-negative breast cancer. It can also reduce the expression of Ca²⁺ channel IP3R3 in ovarian and lung cancer, resulting in the transfer of Ca²⁺ needed to induce apoptosis from endoplasmic reticulum to mitochondria damage. Thus, these two tumors are resistant to cisplatin. It has been found that verteporfin can overcome the drug resistance induced by SMARCA4 deletion. However, this inhibitor has not been applied in clinical practice. Therefore, it is a promising research direction to develop SWI/SNF ATPase targeted drugs with high oral bioavailability to treat patients with tumor resistance induced by low expression or deletion of SMARCA4. ARID1A deletion can activate the expression of ANXA1 protein in HER2+ breast cancer cells or down-regulate the expression of progesterone receptor B protein in endometrial cancer cells. The drug resistance of these two tumor cells to trastuzumab or progesterone is induced by activating AKT pathway. ARID1A deletion in ovarian cancer can increase the expression of MRP2 protein and make it resistant to carboplatin and paclitaxel. ARID1A deletion also can up-regulate the phosphorylation levels of EGFR, ErbB2, and RAF1 oncogene proteins.The ErbB and VEGF pathway are activated and EMT is increased. As a result, lung adenocarcinoma is resistant to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs). Although great progress has been made in the research on the mechanism of SWI/SNF complex inducing tumor drug resistance, most of the research is still at the protein level. It is necessary to comprehensively and deeply explore the detailed mechanism of drug resistance from gene, transcription, protein, and metabolite levels by using multi-omics techniques, which can provide sufficient theoretical basis for the diagnosis and treatment of poor tumor prognosis caused by mutation or abnormal expression of SWI/SNF subunits in clinical practice.

Electroencephalogram (EEG) is a non-invasive, high temporal-resolution technique for monitoring brain activity. However, affected by the volume conduction effect, EEG has a low spatial resolution and is difficult to locate brain neuronal activity precisely. The surface Laplacian (SL) technique obtains the Laplacian EEG (LEEG) by estimating the second-order spatial derivative of the scalp potential. LEEG can reflect the radial current activity under the scalp, with positive values indicating current flow from the brain to the scalp (“source”) and negative values indicating current flow from the scalp to the brain (“sink”). It attenuates signals from volume conduction, effectively improving the spatial resolution of EEG, and is expected to contribute to breakthroughs in neural engineering. This paper provides a systematic overview of the principles and development of SL technology. Currently, there are two implementation paths for SL technology: current source density algorithms (CSD) and concentric ring electrodes (CRE). CSD performs the Laplace transform of the EEG signals acquired by conventional disc electrodes to indirectly estimate the LEEG. It can be mainly classified into local methods, global methods, and realistic Laplacian methods. The global method is the most commonly used approach in CSD, which can achieve more accurate estimation compared with the local method, and it does not require additional imaging equipment compared with the realistic Laplacian method. CRE employs new concentric ring electrodes instead of the traditional disc electrodes, and measures the LEEG directly by differential acquisition of the multi-ring signals. Depending on the structure, it can be divided into bipolar CRE, quasi-bipolar CRE, tripolar CRE, and multi-pole CRE. The tripolar CRE is widely used due to its optimal detection performance. While ensuring the quality of signal acquisition, the complexity of its preamplifier is relatively acceptable. Here, this paper introduces the study of the SL technique in resting rhythms, visual-related potentials, movement-related potentials, and sensorimotor rhythms. These studies demonstrate that SL technology can improve signal quality and enhance signal characteristics, confirming its potential applications in neuroscientific research, disease diagnosis, visual pathway detection, and brain-computer interfaces. CSD is frequently utilized in applications such as neuroscientific research and disease detection, where high-precision estimation of LEEG is required. And CRE tends to be used in brain-computer interfaces, that have stringent requirements for real-time data processing. Finally, this paper summarizes the strengths and weaknesses of SL technology and envisages its future development. SL technology boasts advantages such as reference independence, high spatial resolution, high temporal resolution, enhanced source connectivity analysis, and noise suppression. However, it also has shortcomings that can be further improved. Theoretically, simulation experiments should be conducted to investigate the theoretical characteristics of SL technology. For CSD methods, the algorithm needs to be optimized to improve the precision of LEEG estimation, reduce dependence on the number of channels, and decrease computational complexity and time consumption. For CRE methods, the electrodes need to be designed with appropriate structures and sizes, and the low-noise, high common-mode rejection ratio preamplifier should be developed. We hope that this paper can promote the in-depth research and wide application of SL technology.

Objective To optimize the process conditions and analyze the components of alkaloids from Zanthoxylum bungeanum Maxim（Z. bungeanum）using macroporous resin. Methods Combining single factor tests and orthogonal tests, the content of hydroxy-α-sanshool（HAS）and hydroxy-β-sanshool（HBS）were considered as indexes to determine the best process parameters. Ultra-performance liquid chromatography-quadrupole tandem time-of-flight mass spectrometry（UPLC-Q-TOF-MS^E）was used to identify the structures of alkaloids. Results The optimal conditions were Mitsubishi HP-20 macroporous resin, the loading solution concentration was 0.2 g crude drug/ml, the ratio of crude drug to resin volume was 1 g∶2.5 ml, the diameter/height ratio of resin column was 1∶7, the dynamic adsorption flow rate was 4 times of bed volume（BV）per hour, and the adsorption time was 1 h. Impurities were removed by using 2 BV of 20% ethanol, 5 BV of 80% ethanol was used to elution, and the content of HAS and HBS was 4.71% and 1.02%, respectively. A total of 20 alkaloids were identified from Z. bungeanum. Conclusion This method was stable and feasible, obtaining high purity and various kinds of alkaloids, which could be used for the enrichment and purification of alkaloids from Z. bungeanum.

Objective: To investigate the status of latent tuberculosis infection（LTBI）among freshmen in middle schools and their willingness of preventive treatment in Yunyan District of Guiyang, so as to provide a reference for the prevention and control of tuberculosis in schools. Methods: The tuberculin skin test (TST) and X-ray scans were used to screen the TB infection of 13 915 freshmen in middle schools in Yunyan District of Guiyang in 2023, and a questionnaire survey on the willingness of accepting tuberculosis preventive treatment was conducted to LTBI patients. The χ 2 test and Fisher exact probability was conducted for the comparison of the rates among the groups. Results: Among the freshmen screened, the detection rate of LTBI was 3.29%. There were statistically significant difference in LTBI rates among freshmen of different genders (boys:2.87%, girls:3.81%), age groups (12-15 years old:3.31%, 16-17 years old:3.92%, 18-20 years old:1.91%), and school stages (junior high school:3.52%, ordinary high school:5.96%, vocational high school:2.29%)（ χ 2=9.59, 13.08, 54.30, P ＜0.01). A total of 356 LTBI freshmen completed questionnaire survey,and 299(83.99%) were willing to accept tuberculosis preventive treatment, but the actual number of LIBI freshman who underwent preventive treatment was zero. Those LTBI who had received Bacille Calmette Guérin(BCG) vaccine(86.97%) was higher in the reporting rates of being willing to accept preventive treatment than that of LTBI who had not received BCG vaccine( 75.79 %),the differences were statistically significant( χ 2=6.48， P <0.05). The main reasons for refusing preventive treatment was worry about adverse drug reactions(80.70%), social acceptance and the support of social institutions were needed most(85.96%). Conclusions The LTBI rate among freshmen in Yunyan District of GuiYang is higher. Although the freshmen with LTBI have a higher willingness to accept preventive treatment, however, no one has undergone preventive treatment. Corresponding measures need to be taken for improving the preventive treatment rate of LIBI freshmen.

Objective: To investigate the characteristics of influenza A virus (FluA), influenza B virus (FluB), human rhinovirus (HRV), respiratory syncytial virus (RSV), human adenovirus (ADV) and Mycoplasma pneumoniae (MP) among acute respiratory infection (ARI) cases in the First People's Hospital of Huzhou, so as to provide the basis for formulating prevention and treatment measures for ARI. Methods: Gender, age, testing time, and pathogen testing data of ARI cases in the First People's Hospital of Huzhou from April 2023 to March 2024 were collected. The detection rates of FluA, FluB, HRV, RSV, ADV and MP were analyzed across different genders, age groups and seasons. Results: A total of 15 788 ARI cases were included, and 8 617 cases were tested positive for at least one pathogen, with a detection rate of 54.58%. Single-pathogen detection was found in 7 913 cases (50.12%), with the detection rates of 14.61% for FluA, 11.86% for MP, 8.46% for FluB, 8.41% for RSV, 4.35% for HRV, and 2.44% for ADV. Mixed-pathogen detection was found in 704 cases (4.46%). MP mixed with other pathogens was the most common, with 335 cases accounting for 47.59% of mixed detections. The single-pathogen detection rate for RSV was higher in males than in females (9.13% vs. 7.64%, P<0.05). The detection rate was higher in the cases aged 5 to <18 years (67.32%) than in the other age groups (all P<0.008). The detection rates were higher in autumn and winter, with 56.99% and 61.59%, respectively (all P<0.008). Conclusions The pathogen detection rate among ARI cases in the First People's Hospital of Huzhou from 2023 to 2024 was relatively high, with FluA and MP being the predominant pathogens. Children and adolescents aged 5 to <18 years were the susceptible population, and autumn and winter were the peak seasons for infection.

OBJECTIVE To explore the association between the use of oral progesterone drugs in early pregnancy and gestational diabetes mellitus （GDM）. METHODS Through real-world retrospective cohort research method， pregnant women who underwent the oral glucose tolerance test （OGTT） at the Affiliated Maternal and Child Health Hospital of Nantong University between January 2022 and January 2023 were enrolled. Based on whether oral progesterone drugs were used in early pregnancy， they were divided into treatment group and control group； propensity score matching （PSM） with a 1∶1 ratio was employed to control for confounding factors； Logistic regression and linear regression were employed to analyze the association between drug factors （whether use of oral progesterone drug， duration of medication， dosage， and drug type） and outcome indicators （occurrence of GDM， fasting blood glucose levels， and OGTT 1 and 2 h blood glucose levels in late pregnancy）. RESULTS A total of 709 pregnant women were enrolled in the two groups before PSM； after PSM， 256 cases were included in both the treatment group and the control group. The results of association analysis indicated that there was no significant association between the use of oral progesterone drugs and GDM （P＞0.05）； but a significant correlation was found with OGTT 1 h blood glucose levels [β＝0.965， 95%CI （0.007，1.922）， P＜0.05]， specifically with Dydrogesterone tablets [β＝0.977， 95%CI （0.009， 1.944）， P＜0.05] and Progesterone soft capsules [β ＝1.089， 95%CI （0.077， 2.102）， P＜0.05]. There was no significant correlation between other drug factors and outcome indicators （P＞0.05）. CONCLUSIONS The use of oral progestogen drugs in early pregnancy is not significantly associated with GDM. The blood glucose levels in late pregnancy， especially OGTT 1 h blood glucose levels， have a certain correlation with Progesterone soft capsules and Dydrogesterone tablets.

OBJECTIVE To summarize the current situation of pharmaceutical clinic service in our hospital over the past five years， and explore sustainable development strategies for service models of pharmaceutical clinics. METHODS A retrospective analysis was conducted on the consultation records of patients who registered and established files at the pharmaceutical clinic in our hospital from January 2019 to December 2023. Statistical analysis was performed on patients’ general information， medication- related problems， and types of pharmaceutical services provided by pharmacists. RESULTS A total of 963 consultation records were included， among which females aged 20-39 years accounted for the highest proportion （66.04%）； obstetrics and gynecology- related consultations accounted for the largest number of cases. Additionally， 80 patients attended follow-up visits at our hospital’s pharmaceutical clinic. A total of 1 029 medication-related issues were resolved， including 538 cases of drug consultations （52.28%）， 453 medication recommendations （44.02%）， 22 medication restructuring（2.14%）， and 16 medication education （1.55%）； the most common types of medication-related problems identified were adverse drug events（70.07%）. CONCLUSIONS Although the pharmaceutical clinic has achieved recognition from clinicians and patients， challenges such as low awareness among healthcare providers and the public persist. Future efforts should focus on strengthening information technology construction， enhancing pharmacist training， and establishing various forms of outpatient pharmaceutical service models.

Osteoporosis （OP） is a systemic metabolic disease with a strong correlation with age. The prevalence of osteoporosis is rising annually as a consequence of the growing issue of population ageing. The current treatments for OP have numerous shortcomings. In contrast， traditional Chinese medicine has a long history and a rich species diversity. Furthermore， recent years have seen an increase in the number of studies examining the anti-OP properties of traditional Chinese medicine. This may provide a safe and effective alternative strategy for the treatment of OP. The zebrafish， due to its favourable optical transparency and high homology with human genes， has been extensively employed as an animal research model in the investigation of human skeletal-related disease mechanisms and drug screening. This paper presents a review of anti-osteoporosis studies of traditional Chinese medicine using zebrafish as a model for osteoporosis. It also provides a summary of the experimental evaluation methods involved in such studies， an analysis of the current status of traditional Chinese medicine in the treatment of osteoporosis using zebrafish as a model， and a summary of the mechanism of action and the signalling pathways involved in traditional Chinese medicine in the anti-osteoporosis treatment of zebrafish. The current research status of Chinese medicine in the treatment of OP was analysed， as well as the mechanism of action of Chinese medicine against OP and the signalling pathways involved. Furthermore， the advantages and disadvantages of various zebrafish modelling methods of OP were compared with those of traditional animal models. The objective of this study is to provide a reference for the evaluation method of the zebrafish model in the study of bone-related diseases， as well as for the study of the mechanism of action of traditional Chinese medicine against OP and for the reference of the research and development of new drugs.

Objective: To explore the association of latent profiles of mobile phone dependence and self control with physical exercise among junior high school students, so as to provide references for the prevention of mobile phone dependence and the improvement of self control among junior high school students. Methods: From April to May 2024, a stratified random cluster sampling method was used to select a total of 2 311 students from grade 7 to grade 9 in three public junior high schools in Xiangxi Autonomous Prefecture, Hunan Province. Latent profile analysis was conducted to identify the latent profiles of mobile phone dependence and self control among junior high school students. Pearson correlation analysis was used to examine the correlation between mobile phone dependence and self control, and Chi square test was used to analyze the distribution differences of latent profiles of adolescents across different demographic characteristics. Multiple Logistic regression analysis was applied to explore the association between mobile phone dependence, self control, and physical exercise. Results: Four latent profiles of mobile phone dependence and self control were identified: low dependence-moderate self control group ( n =885, 38.3%), moderate dependence-low self control group ( n =910, 39.4%), high dependence-no self control group ( n =232, 10.0%), and no dependence-high self control group ( n =284, 12.3%). Significant differences were observed in the distribution of latent profiles across gender, grade and only child status ( χ 2=10.85, 35.72, 13.85， P <0.05). Logistic regression analysis showed that, after controlling for demographic variables, compared with the low dependence-moderate self control group, physical exercise was negatively associated with the moderate dependence-low self control group ( OR =0.79) and the high dependence-no self control group ( OR =0.81), while positively associated with the no dependence-high self control group ( OR =1.58) ( P <0.01). Conclusions The influence of physical exercise on junior high school students different potential profile types of mobile phone dependence and self control is different. Schools and families should adopt targeted physical exercise interventions based on the characteristics of different profiles to promote the physical and mental health of junior high school students.

Cell models can simulate a variety of life states and disease developments, including single cells, two-dimensional (2D) cell cultures, three-dimensional (3D) multicellular spheroids, and organoids. They are essential tools for addressing complex biochemical questions. With continuous advancements in biological and cellular analysis technologies, in vitro cellular models designed to answer scientific questions have evolved rapidly. Early in vitro models primarily relied on 2D systems, which failed to accurately replicate the complex cellular compositions and microenvironmental interactions observed in vivo, let alone support sophisticated investigations into cellular biological functions. Subsequent improvements in cell culture techniques led to the development of 3D culture-based models, such as cellular spheroids. The advent of pluripotent stem cell technology further advanced the development of organoid systems, which closely mimic human organ development. Compared to traditional 2D models, both 3D cellular models and organoids offer significant advantages, including personalization and enhanced physiological relevance, making them particularly suitable for exploring molecular mechanisms of disease progression, discovering novel cellular and biomolecular functions, and conducting related studies. The imaging analysis of common cellular models primarily employs labeling-based methods for in situ imaging of targeted genes, proteins, and small-molecule metabolites, enabling further research on cell types, states, metabolism, and drug efficacy. However, these approaches have drawbacks such as poor labeling specificity and complex experimental procedures. By using cells as experimental models, mass spectrometry technology combined with morphological analysis can reveal quantitative changes and spatial distributions of various biological substances at the spatiotemporal level, including metabolites, proteins, lipids, peptides, drugs, environmental pollutants, and metals. This allows for the investigation of cell-cell interactions, tumor microenvironments, and cellular bioinformational heterogeneity. The application of these cutting-edge imaging technologies generates vast amounts of cellular data, necessitating the development of rapid, efficient, and highly accurate image data algorithms for precise segmentation and identification of single cells, multi-organelle structures, rare cell subpopulations, and complex cellular morphologies. A critical focus lies in creating deep learning models and algorithms that enhance the accuracy of cellular visualization. At the same time, establishing more robust data integration tools is essential not only for analyzing and interpreting outputs but also for effectively uncovering the biological significance of spatially resolved mass spectrometry data. Developing a cell imaging platform with high versatility, operational stability, and specificity to enable data interoperability will significantly enhance its utility in clinical research, thereby advancing investigations into disease molecular mechanisms and supporting precision diagnostics and therapeutics. In contrast to genomic, transcriptomic, and proteomic information, the metabolome can rapidly respond to external stimuli and cellular physiological changes within a short timeframe. This rapid and precise reflection of ongoing cellular state alterations has positioned spatial metabolomics as a pivotal approach for exploring the molecular mechanisms underlying physiological and pathological processes in cells, tissues, and organisms. In this review, we summarize research on cell imaging based on mass spectrometry technologies, including the selection and preparation of cell models, morphological analysis of cell models, spatial omics techniques based on mass spectrometry, mass cytometry, and their applications. We also discuss the current challenges and propose future directions for development in this field.