OBJECTIVE To establish a “BRAND” pharmaceutical care model for advanced non-small cell lung cancer （NSCLC） patients with positive driver genes， providing theoretical and practical references for the clinical implementation of precise and individualized oncology pharmaceutical care. METHODS One hundred patients admitted to the department of pulmonary and critical care medicine in our hospital from January 2023 to May 2024 were collected meeting the inclusion and exclusion criteria. Patients were randomly divided into control group and intervention group， with 50 patients in each group. The control group received routine pharmaceutical care， while the intervention group received pharmaceutical care under the “BRAND” model （collecting patients’ basic information， reviewing disease treatment-related information， conducting precise medication assessments， formulating individualized pharmaceutical care plans for the next steps， and implementing medication guidance and follow-up management）. The study was conducted in a 3-week cycle for a total of 4 cycles. The medication compliance， quality of life， laboratory test indicators， incidence of drug-related adverse events and satisfaction of patients in both groups were compared before and after the intervention to evaluate the effects. RESULTS After 12 weeks of intervention， compared with the control group， the medication compliance， cognitive function， social function and satisfaction of patients in the intervention group were improved significantly （ P ＜0.05）； the severity of fatigue and constipation and the incidence of drug-related adverse events were significantly reduced （ P ＜0.05）， and there was no statistically significant difference in laboratory test indicators （ P ＞0.05）. CONCLUSIONS The “BRAND” pharmaceutical care model can effectively improve the medication compliance of patients with advanced NSCLC with positive driver genes and improve their quality of life. This study can provide a feasible path for clinical pharmacists to carry out standardized and high-quality pharmaceutical care.

Neurological disorders such as post-stroke hemiplegia, spinal cord injury, and Parkinson disease represent a major global health burden. Brain-computer interface (BCI), which creates direct communication pathways between the nervous system and external devices, offers a promising strategy for functional restoration. The long-term efficacy of such BCI fundamentally depends on the performance of biomaterials at the neural interface. Ideal materials must concurrently satisfy biocompatibility, electrical conductivity, enduring chemical stability, and mechanical compatibility with brain tissue. This review systematically outlines the application of conductive polymers, inorganic nanomaterials, natural biomaterials, and composites in BCI, with a focus on how advanced designs, such as bionic and encapsulated electrodes, improve signal fidelity and surgical feasibility through structural innovation. It further summarizes key material-modification techniques and analyzes the complex foreign-body response orchestrated by microglia, astrocytes, and peripheral immune cells. Finally, it provides insights into future research directions and clinical translation of BCI-based neurorehabilitation, while highlighting critical challenges including long-term biosafety and the establishment of standardized evaluation frameworks, aiming to bridge the gap between laboratory innovation and effective clinical deployment.

Objective: To understand the incidence risk and risk factors of tuberculosis (TB) among middle school students in Chongqing, so as to provide a basis for formulating TB prevention and control strategies. Methods: From September to December 2022, 32 181 middle school students were selected as the study cohort from 15 administrative districts in Chongqing by using the stratified cluster random sampling method. All cohort members were screened with the tuberculin skin test (TST), and relevant information was collected from January 1, 2023 to December 31, 2024. On the basis of active screening, the follow up data of the participants were compared with the National Tuberculosis Management Information System to obtain the incidence status of the study subjects. The Log rank test was used to compare the TB incidence rates among students with different characteristics, and a Cox proportional hazards model was established to analyze the incidence risk and risk factors of TB. Results: The TST screening rate of the cohort members was 93.0%. During the 2 year follow up period, a total of 36 TB cases occurred, with a cumulative incidence rate of 111.87/100 000 and an incidence density of 55.95/100 000. Among them, the cumulative incidence rate of students from public schools (170.44/ 100 000 ) was higher than that of students from private schools (41.16/100 000), the cumulative incidence rate of students in schools located in high epidemic areas (153.95/100 000) was higher than that in medium epidemic areas (69.00/100 000), and the difference was statistically significant ( χ 2=11.49, 4.73, both P <0.05). The Log-rank test for different TST results showed that the difference in TB comulative incidence rate between students with strongly positive TST results (216.55/ 100 000 ) and those with negative TST results (81.40/100 000) was statistically significant ( χ 2=5.85, P <0.05). Univariate analysis using the Cox proportional hazards model revealed that the risk of TB was lower in students from private schools ( HR=0.25, 95% CI = 0.10-0.59) and students in medium epidemic areas ( HR=0.46, 95%CI =0.23-0.94); whereas the risk of TB was increased in students with strongly positive TST results ( HR=1.39, 95%CI =1.05-1.84) (all P <0.05). Multivariate Cox regression analysis showed that the risk of TB in students from private schools was lower than that of students from public schools ( HR=0.23, 95%CI=0.08-0.62, P <0.05). Conclusions The annual average incidence rate of TB among middle school students in Chongqing is at a relatively high level. It is necessary to strengthen the management and intervention for student groups, including those in public schools, those in schools located in high epidemic areas, and those with strongly positive TST results, so as to reduce the incidence rate of TB.

Objective To investigate the association of digit ratio with single nucleotide polymorphism(SNP)at three loci(rs17576,rs3918249,rs9509)of matrix metallopeptidase 9(MMP-9)gene.Methods A total of 804 Ningxia Han youths(399 males and 405 females)were used as the study subjects.A digital camera was used to take frontal photographs of the hands,and image analysis software was used to mark the anatomical points and measure the lengths of each finger of both hands(2D,3D,4D,5D);Multiplexed PCR was used to detect the three polymorphic sites of the MMP-9 gene,SPSS 25.0 and R Studio software were used for data analysis and plotting.Results The 2D/3D(P＜0.05)and 2D/4D(left,P＜0.01,right,P＜0.05)of both hands,2D/5D(P＜0.01),3D/5D,4D/5D(P＜0.05)of the right hand,and 3D/4D(P＜0.05)of the left hand in female youths of Ningxia Han were significantly higher than those in males,Differences in genotypes and allele frequencies at all 3 loci of the MMP-9 gene were not statistically significant between genders(P＞0.05).Right hand 2D/4D was significantly associated with genotypes at the rs17576 and rs3918249 loci in male youths(P＜0.05).Conclusion MMP-9 gene SNPs(rs17576 and rs3918249)may be associated with the formation of 2D/4D of Ningxia Han male youths.

Objective: To explore the therapeutic mechanism of puerarin in treating rheumatoid arthritis (RA) rats based on the serine/tyrosine protein kinase B (AKT)-phosphorylated forkhead box protein O1 (FOXO1)-interleukin-9 (AKT-FOXO1-IL-9) signaling pathway. Methods : 36 rats were randomly divided into a blank group , a model group , a positive control group , and low , medium , and high dose groups of puerarin. Except for the blank group , the other groups were induced with type Ⅱ collagen to establish a RA rat model. After successful modeling , different doses of puerarin and methotrexate were given to treat the rats. The body mass and toe thickness of the rats were measured , and biochemical indicators of rat blood rheology were detected. X-ray was used to observe changes in rat joint morphology. Safranin green staining were used to observe the pathology of rat joint tissue. ELISA was used to detect the levels of IL-9 and rheumatoid factors in rat serum , and Western blot was used to detect changes in levels of AKT and FOXO1 . 36 rats were randomly divided into a blank group , a model group , a positive control group , and low , medium , and high dose groups of puerarin. Except for the blank group , the other groups were induced with type Ⅱ collagen to establish a RA rat model. After successful modeling , different doses of puerarin and methotrexate were given to treat the rats. The body mass and toe thickness of the rats were measured , and biochemical indicators of rat blood rheology were detected. X-ray was used to observe changes in rat joint morphology. Safranin green staining were used to observe the pathology of rat joint tissue. ELISA was used to detect the levels of IL-9 and rheumatoid factors in rat serum , and Western blot was used to detect changes in levels of AKT and FOXO1 . Results: Compared with the blank group , the model group had the lowest toe thickness , and X-ray images showed more obvious segmental stenosis and more severe marginal bone invasion ; scaly like changes appeared at the edges of joints stained with safranin green , accompanied by the exudation of inflammatory cells and increased proliferation and secretion of chondrocytes ; the expression levels of inflammatory factors IL-9 and rheumatoid factors were the highest , and the expression levels of AKT and FOXO1 proteins were the highest (P < 0. 05) . Compared with the model group , the toe thickness of rats treated with different doses of puerarin decreased ; X-ray images showed that the puerarin treatment group of rats showed improvement in plantar joint stenosis and marginal bone invasion ; the results of safranin green staining showed that after treatment with different doses of puerarin , the infiltration of inflammatory cells decreased , and the expression levels of inflammatory factor IL-9 , rheumatoid factors , AKT , and FOXO1 proteins decreased significantly ( P < 0. 05 ) , with the high-dose puerarin group showing the most significant difference. Compared with the high-dose puerarin group , the positive control group showed a significant decrease in the above results and statistical differences (P < 0. 05) . Conclusion Puerarin has a good therapeutic effect on rats with RA by inhibiting the AKT-FOXO1-IL-9 pathway. The high-dose puerarin group (60 mg/kg) has the best therapeutic effect and the results show a dose-response relationship.

This paper aimed to systematically evaluate the effects of hypoxic training at different fraction of inspired oxygen (FiO₂) on body composition, glucose metabolism, and lipid metabolism in obese individuals, and to determine the optimal oxygen concentration range to provide scientific evidence for personalized and precise hypoxic exercise prescriptions. A systematic search was conducted in the Cochrane Library, PubMed, Web of Science, Embase, and CNKI databases for randomized controlled trials and pre-post intervention studies published up to March 31, 2025, involving hypoxic training interventions in obese populations. Meta-analysis was performed using RevMan 5.4 software to assess the effects of different fraction of inspired oxygen (FiO₂≤14% vs. FiO₂>14%) on BMI, body fat percentage, waist circumference, fasting blood glucose, insulin, HOMA-IR, triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C), with subgroup analyses based on oxygen concentration. A total of 22 studies involving 292 participants were included. Meta-analysis showed that hypoxic training significantly reduced BMI (mean difference (MD)=-2.29,95%CI: -3.42 to -1.17, P<0.000 1), body fat percentage (MD=-2.32, 95%CI: -3.16 to -1.47, P<0.001), waist circumference (MD=-3.79, 95%CI: -6.73 to -0.85, P=0.01), fasting blood glucose (MD=-3.58, 95%CI: -6.23 to -0.93, P=0.008), insulin (MD=-1.60, 95%CI: -2.98 to -0.22, P=0.02), TG (MD=-0.18, 95%CI: -0.25 to -0.12, P<0.001), and LDL-C (MD=-0.25, 95%CI: -0.39 to -0.11, P=0.000 3). Greater improvements were observed under moderate hypoxic conditions with FiO₂>14%. Changes in HOMA-IR (MD=-0.74, 95%CI: -1.52 to 0.04,P=0.06) and HDL-C (MD=-0.09, 95%CI: -0.21 to 0.02, P=0.11) were not statistically significant. Hypoxic training can significantly improve body composition, glucose metabolism, and lipid metabolism indicators in obese individuals, with greater benefits observed under moderate hypoxia (FiO>14%). As a key parameter in hypoxic exercise interventions, the precise setting of oxygen concentration is crucial for optimizing intervention outcomes.

Objective To explore the application of plasma 7 microRNA (miR7) testing in the differential diagnosis of very early-stage hepatocellular carcinoma (HCC). Methods This study is a multicenter real-world study. Patients with single hepatic lesion (maximum diameter≤2 cm) who underwent plasma miR7 testing at Zhongshan Hospital, Fudan University, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Anhui Provincial Hospital, and Peking University People’s Hospital between January 2019 and December 2024 were retrospectively enrolled. Patients were divided into very early-stage HCC group and non-HCC group, and the clinical pathological characteristics of the two groups were compared. The value of plasma miR7 levels, alpha-fetoprotein (AFP), and des-gamma-carboxy prothrombin (DCP) in the differential diagnosis of very early-stage HCC was evaluated using receiver operating characteristic (ROC) curves and area under the curve (AUC). In patients with both negative AFP and DCP (AFP＜20 ng/mL, DCP＜40 mAU/mL), the diagnostic value of plasma miR7 for very early-stage HCC was analyzed. Results A total of 64 528 patients from 4 hospitals underwent miR7 testing, and 1 682 were finally included, of which 1 073 were diagnosed with very early-stage HCC and 609 were diagnosed with non-HCC. The positive rate of miR7 in HCC patients was significantly higher than that in non-HCC patients (67.9% vs 24.3%, P＜0.001). ROC curves showed that the AUCs for miR7, AFP, and DCP in distinguishing HCC patients from the non-HCC individuals were 0.718, 0.682, and 0.642, respectively. The sensitivities were 67.85%, 43.71%, and 44.45%, and the specificities were 75.70%, 92.78%, and 83.91%, respectively. The pairwise comparison of AUCs showed that the diagnostic efficacy of plasma miR7 detection was significantly better than that of AFP or DCP (P＜0.05). Although its specificity was slightly lower than AFP and DCP, the sensitivity was significantly higher. Among patients negative for both AFP and DCP, miR7 maintained an AUC of 0.728 for diagnosing very early-stage HCC, with 67.82% sensitivity and 77.73% specificity. Conclusions Plasma miR7 testing is a potential molecular marker with high sensitivity and specificity for the differential diagnosis of small hepatic nodules. In patients with very early-stage HCC lacking effective molecular markers (negative for both AFP and DCP), miR7 can serve as a novel and effective molecular marker to assist diagnosis.

In recent years, growing evidence indicates that the nervous system plays an indispensable role in tumor development and metastasis. Elucidating crosstalk between the nervous system and tumor progression has thrived as a hot topic and a new direction for understanding cancer pathogenesis. Notably, many novel discoveries have suggested that neurotransmitter receptors (NRs) are not only widely expressed in cancer cells, but also play key roles in regulating cancer initiation and progression by diverse approaches. In this review, we summarized the latest advance in cancer neuroscience, especially emphasizing the important roles of different NRs in cancer development and prevention. The exemplary studies presented herein illustrate the emerging view that NRs are profoundly influential, manifested in tumor growth, apoptosis, angiogenesis, metastasis, resistance to drugs, and participate in the formation of neural-cancer interactions. In addition, NRs also regulate cellular metabolic processes and tumor microenvironment (TME) remodeling. More importantly, numerous basic and clinical studies have suggested that NRs may be potential targets for cancer treatments, and corresponding agonists or antagonists have been identified effectively in controlling tumor growth and metastasis. In conclusion, NRs are emerging as novel targets for anti-cancer drug exploration and clinical cancer treatments, while trying to uncover deeper mechanisms and connections between NRs and cancer is of high clinical significance and translational value.
Humans ; Neoplasms/metabolism* ; Receptors, Neurotransmitter/physiology* ; Animals ; Tumor Microenvironment/physiology*

BACKGROUND: Pancreatic cancer is a lethal malignancy prone to gemcitabine resistance. The single-strand selective monofunctional uracil DNA glycosylase (SMUG1), which is responsible for initiating base excision repair, has been reported to predict the outcomes of different cancer types. However, the function of SMUG1 in pancreatic cancer is still unclear. METHODS: Gene and protein expression of SMUG1 as well as survival outcomes were assessed by bioinformatic analysis and verified in a cohort from Fudan University Shanghai Cancer Center. Subsequently, the effect of SMUG1 on proliferation, cell cycle, and migration abilities of SMUG1 cells were detected in vitro . DNA damage repair, apoptosis, and gemcitabine resistance were also tested. RNA sequencing was performed to determine the differentially expressed genes and signaling pathways, followed by quantitative real-time polymerase chain reaction and Western blotting verification. The cancer-promoting effect of forkhead box Q1 (FOXQ1) and SMUG1 on the ubiquitylation of myelocytomatosis oncogene (c-Myc) was also evaluated. Finally, a xenograft model was established to verify the results. RESULTS: SMUG1 was highly expressed in pancreatic tumor tissues and cells, which also predicted a poor prognosis. Downregulation of SMUG1 inhibited the proliferation, G1 to S transition, migration, and DNA damage repair ability against gemcitabine in pancreatic cancer cells. SMUG1 exerted its function by binding with FOXQ1 to activate the Protein Kinase B (AKT)/p21 and p27 pathway. Moreover, SMUG1 also stabilized the c-Myc protein via AKT signaling in pancreatic cancer cells. CONCLUSIONS SMUG1 promotes proliferation, migration, gemcitabine resistance, and c-Myc protein stability in pancreatic cancer via protein kinase B signaling through binding with FOXQ1. Furthermore, SMUG1 may be a new potential prognostic and gemcitabine resistance predictor in pancreatic ductal adenocarcinoma.
Humans ; Pancreatic Neoplasms/pathology* ; Forkhead Transcription Factors/genetics* ; Signal Transduction/genetics* ; Animals ; Cell Line, Tumor ; Proto-Oncogene Proteins c-akt/metabolism* ; Cell Proliferation/physiology* ; Mice ; Uracil-DNA Glycosidase/genetics* ; Female ; Male ; Gemcitabine ; Mice, Nude ; Apoptosis/physiology* ; Deoxycytidine/analogs & derivatives* ; Cell Movement/genetics*

Accurate prediction of drug responses in cancer cell lines (CCLs) and transferable prediction of clinical drug responses using CCLs are two major tasks in personalized medicine. Despite the rapid advancements in existing computational methods for preclinical and clinical cancer drug response (CDR) prediction, challenges remain regarding the generalization of new drugs that are unseen in the training set. Herein, we propose a multimodal fusion deep learning (DL) model called drug-target and single-cell language based CDR (DTLCDR) to predict preclinical and clinical CDRs. The model integrates chemical descriptors, molecular graph representations, predicted protein target profiles of drugs, and cell line expression profiles with general knowledge from single cells. Among these features, a well-trained drug-target interaction (DTI) prediction model is used to generate target profiles of drugs, and a pretrained single-cell language model is integrated to provide general genomic knowledge. Comparison experiments on the cell line drug sensitivity dataset demonstrated that DTLCDR exhibited improved generalizability and robustness in predicting unseen drugs compared with previous state-of-the-art baseline methods. Further ablation studies verified the effectiveness of each component of our model, highlighting the significant contribution of target information to generalizability. Subsequently, the ability of DTLCDR to predict novel molecules was validated through in vitro cell experiments, demonstrating its potential for real-world applications. Moreover, DTLCDR was transferred to the clinical datasets, demonstrating satisfactory performance in the clinical data, regardless of whether the drugs were included in the cell line dataset. Overall, our results suggest that the DTLCDR is a promising tool for personalized drug discovery.