OBJECTIVE To explore the transformation of the dispensing and drug pickup process in traditional Chinese medicine pharmacy （TCM Pharmacy） in our hospital based on data-intelligence-driven， aiming to improve pharmacists’ work efficiency and patients’ drug pickup experience. METHODS Value stream mapping and journey mapping were used to systematically identify non-value-added links in pharmacists’ dispensing process and key pain points in patients’ drug pickup under the traditional process. An intelligent dispensing and drug pickup system for the TCM Pharmacy was developed based on the C# and Android television platforms， and a machine-learning model was adopted to predict patients’ drug pickup waiting time. A comprehensive evaluation was performed from three perspectives： system performance， prediction accuracy， and satisfaction of pharmacists and patients. RESULTS The system successfully streamlined non-value-added links such as “waiting for writing on the board” and “searching for drugs”， and realized multimodal dynamic prompts of dispensing status through auditory （number calling） and visual （television terminal） channels. The constructed model for predicting drug pickup waiting time exhibited good fitting degree and generalization ability （mean absolute error＝4.28 min， R 2 ＝0.882）. The comprehensive satisfaction scores of pharmacists and patients in the traditional mode were significantly increased from （70.99±1.74） and （73.58±1.98） to （90.02±1.30） and （88.61±2.08） in the new system， respectively （ P ＜0.01）. CONCLUSIONS The transformation of the intelligent drug dispensing and pickup system for TCM pharmacy based on data-intelligence-driven effectively improves the efficiency of pharmacists’ dispensing work， realizes process transparency and waiting time predictability， and significantly enhances patients’ drug pickup experience.

[Objective] To analyze the prognostic value of prostate cancer (PCa) pyroptosis-related genes (PRGs) using gene expression databases and to explore the regulatory mechanism of nucleotidebinding oligomerization domain-like receptor containing pyrin domain 1 (NLRP1) in the pyroptosis of PCa cells. [Methods] Fragments per kilobase of exon model per million reads mapped (FPKM) data and clinical information from PCa and adjacent tissues from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were obtained. Differentially expressed PRGs between PCa and adjacent tissues, classified subtypes and plotted survival curves were analyzed. Univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) regression analysis were conducted to screen prognosis-related PRGs, risk scores were calculated, and a prognostic risk model was constructed and validated. Patients were divided into high and low risk groups based on the median risk scores from the training and validation sets, and gene ontology (GO) enrichment and kyoto encyclopedia of genes and genomes (KEGG) analysis were conducted on differentially expressed PRGs. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to detect the expression level of NLRP1 in PCa cell lines, and pyroptosis was induced in DU145 and LNCaP cells while morphological changes were observed. Western blot (WB) was performed to detect the expression of pyroptosis-related molecules. [Results] A total of 6 prognostic-related PRGs were obtained, including CHMP4C, CYCS, GPX4, GSDMB, NLRP1, and PLCG1. The risk score was positively correlated with the risk of recurrence but negatively correlated with the progression-free survival (P<0.001). The area under the receiver operating characteristic curves (AUCs) for the training set at 1, 3, and 5 years were 0.769 (95%CI: 0.652-0.878), 0.804 (95%CI: 0.736-0.882), and 0.772 (95%CI: 0.631-0.905), respectively, while those for the validation set were 0.731 (95%CI: 0.647-0.826), 0.753 (95%CI: 0.674-0.818), and 0.763 (95%CI: 0.626-0.849), respectively. Differences in expression levels of the 6 PRGs were observed between the high and low risk groups in both the training and validation sets (P<0.05). Cox regression analysis showed that T stage, prostate specific antigen (PSA), Gleason grade, and risk score were independent predictors of PCa prognosis (P<0.05). Differences in risk scores were observed among patients of different ages, T stages, and Gleason grades (P<0.05). NLRP1 was found to be lowly expressed in PCa cell lines and was involved in the regulation of pyroptosis in DU145 and LNCaP cells. [Conclusion] The prognostic risk model constructed based on PRGs has a certain predictability for the prognosis of PCa patients, and NLRP1 may be involved in the regulation of pyroptosis in PCa cells.

BACKGROUND:Currently,spinal endoscopic technology has become the mainstream technology in minimally invasive spinal surgery.The specifications of the instruments for different operating systems are different,and the choice of specific surgical protocols needs to be combined with the actual situation of the patient and the choice of the clinical surgeon. OBJECTIVE:To compare the early efficacy of percutaneous endoscopic interlaminar discectomy for L5-S1 disc herniation under the iLESSYS Delta System and Endo-Surgi Plus System. METHODS:Totally 80 patients with L5-S1 disc herniation were treated with percutaneous endoscopic interlaminar discectomy.Patients were divided into two groups based on the endoscopic system used.Among them,37 cases received the iLESSYS Delta System(Delta group)and 43 cases received the Endo-Surgi Plus System(Plus group).Patient demographic characteristics,perioperative indicators,and complications were analyzed between the two groups.Clinical outcomes were quantified using back and leg visual analog scale scores,Oswestry Disability Index,and Japanese Orthopaedic Association scores at 1 day,1,3,and 6 months after surgery.Patient satisfaction was assessed according to modified MacNab criteria at final follow-up. RESULTS AND CONCLUSION:(1)The operative time and number of arthroplasties in the Plus group were less than those in the Delta group,and the differences were statistically significant(P<0.05).(2)Compared with the preoperative period,the visual analog scale scores,Oswestry Disability Index,and Japanese Orthopaedic Association scores of patients in both groups improved at all follow-up time points,and the difference was statistically significant(P<0.001).(3)There was no statistically significant difference in the comparison of pain visual analog scale scores,Oswestry Disability Index,and Japanese Orthopaedic Association scores of patients in the two groups(P>0.05).(4)At 6-month follow-up after surgery,the MacNab standard excellent and good rates in the Delta group and Plus group were 81%and 79%,respectively,with no significant difference(P=0.823).(5)The incidence of complications was 3%in the Delta group and 2%in the Plus group,but there was no significant difference between the two groups(P=0.914).(6)It is concluded that both iLESSYS Delta and Endo-Surgi Plus surgical systems achieved satisfactory early clinical results in the treatment of lumbar disc herniation,with Endo-Surgi Plus surgical moulding being more efficient and safer.

Adipose tissue is a critical energy reservoir in animals and humans, with multifaceted roles in endocrine regulation, immune response, and providing mechanical protection. Based on anatomical location and functional characteristics, adipose tissue can be categorized into distinct types, including white adipose tissue (WAT), brown adipose tissue (BAT), beige adipose tissue, and pink adipose tissue. Traditionally, adipose tissue research has centered on its morphological and functional properties as a whole. However, with the advent of single-cell transcriptomics, a new level of complexity in adipose tissue has been unveiled, showing that even under identical conditions, cells of the same type may exhibit significant variation in morphology, structure, function, and gene expression——phenomena collectively referred to as cellular heterogeneity. Single-cell transcriptomics, including techniques like single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq), enables in-depth analysis of the diversity and heterogeneity of adipocytes at the single-cell level. This high-resolution approach has not only deepened our understanding of adipocyte functionality but also facilitated the discovery of previously unidentified cell types and gene expression patterns that may play key roles in adipose tissue function. This review delves into the latest advances in the application of single-cell transcriptomics in elucidating the heterogeneity and diversity within adipose tissue, highlighting how these findings have redefined the understanding of cell subpopulations within different adipose depots. Moreover, the review explores how single-cell transcriptomic technologies have enabled the study of cellular communication pathways and differentiation trajectories among adipose cell subgroups. By mapping these interactions and differentiation processes, researchers gain insights into how distinct cellular subpopulations coordinate within adipose tissues, which is crucial for maintaining tissue homeostasis and function. Understanding these mechanisms is essential, as dysregulation in adipose cell interactions and differentiation underlies a range of metabolic disorders, including obesity and diabetes mellitus type 2. Furthermore, single-cell transcriptomics holds promising implications for identifying therapeutic targets; by pinpointing specific cell types and gene pathways involved in adipose tissue dysfunction, these technologies pave the way for developing targeted interventions aimed at modulating specific adipose subpopulations. In summary, this review provides a comprehensive analysis of the role of single-cell transcriptomic technologies in uncovering the heterogeneity and functional diversity of adipose tissues.

OBJECTIVE To evaluate the influence of pharmaceutical quality control on the efficiency and outcomes of standardized medication therapy management （MTM） services for patients with coronary heart disease by using Economic， Clinical and Humanistic Outcomes （ECHO） model. METHODS This study collected case data of coronary heart disease patients who received MTM services during January-March 2023 （pre-quality control implementation group， n＝96） and June-August 2023 （post-quality control implementation group， n＝164）. Using propensity score matching analysis， 80 patients were selected from each group. The study subsequently compared the economic， clinical， and humanistic outcome indicators of pharmaceutical services between the two matched groups. RESULTS There were no statistically significant differences in baseline data between the two groups after matching （P＞0.05）. Compared with pre-quality control implementation group， the daily treatment cost （16.26 yuan vs. 24.40 yuan， P＜0.001）， cost-effectiveness ratio [23.12 yuan/quality-adjusted life year （QALY） vs. 32.32 yuan/QALY， P＜0.001]， and the incidence of general adverse drug reactions （2.50% vs. 10.00%， P＝0.049） of post-quality control implementation group were decreased significantly； the utility value of the EuroQol Five-Dimensional Questionnaire （0.74± 0.06 vs. 0.71±0.07， P＝0.003）， the reduction in the number of medication related problems （1.0 vs. 0.5， P＜0.001）， the medication adherence score （[ 6.32±0.48） points vs. （6.10±0.37） points， P＝0.001]， and the satisfaction score （[ 92.56±1.52） points vs. （91.95±1.56） points， P＝0.013] all showed significant improvements. Neither group experienced serious adverse drug reactions. There was no statistically significant difference in the incidence of new adverse reactions between the two groups （1.25% vs. 3.75%， P＝0.310）. CONCLUSIONS Pharmaceutical quality control can improve the quality of pharmaceutical care， and the ECHO model can quantitatively evaluate the effect of MTM services， making pharmaceutical care better priced and more adaptable to social needs， thus being worthy of promotion.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.

Eight compounds were isolated and purified from the ethyl acetate part of 70% acetone extract of Rehmannia glutinosa by various chromatographic techniques such as silica gel, MCI gel CHP-20, ODS, Toyopearl HW-40C, combined with TLC and semi-preparative HPLC. Their structures were elucidated by modern spectroscopy techniques (NMR, MS, UV, IR), and identified as neomartynoside A (1), osmanthuside B₆ (2), martynoside (3), isomartynoside (4), (E)-p-hydroxycinnamic acid (5), caffeic acid (6), ferulic acid (7), and methyl caffeate (8). Compound 1 is a new phenylethanol glycoside, which was identified as neomartynoside A. Compound 2 was isolated from Rehmannia glutinosa for the first time. In addition, compounds 2, 6 and 7 significantly increased relative glucose consumption, showing potential hypoglycemic activity.

Exercise fatigue is a complex physiological and psychological phenomenon that includes peripheral fatigue in the muscles and central fatigue in the brain. Peripheral fatigue refers to the loss of force caused at the distal end of the neuromuscular junction, whereas central fatigue involves decreased motor output from the primary motor cortex, which is associated with modulations at anatomical sites proximal to nerves that innervate skeletal muscle. The central regulatory failure reflects a progressive decline in the central nervous system’s capacity to recruit motor units during sustained physical activity. Emerging evidence highlights the critical involvement of central neurochemical regulation in fatigue development, particularly through neurotransmitter-mediated modulation. Alterations in neurotransmitter release and receptor activity could influence excitatory and inhibitory signal pathways, thus modulating the perception of fatigue and exercise performance. Increased serotonin (5-HT) could increase perception of effort and lethargy, reduce motor drive to continue exercising, and contribute to exercise fatigue. Decreased dopamine (DA) and noradrenaline (NE) neurotransmission can negatively impact arousal, mood, motivation, and reward mechanisms and impair exercise performance. Furthermore, the serotonergic and dopaminergic systems interact with each other; a low 5-HT/DA ratio enhances motor motivation and improves performance, and a high 5-HT/DA ratio heightens fatigue perception and leads to decreased performance. The expression and activity of neurotransmitter receptors would be changed during prolonged exercise to fatigue, affecting the transmission of nerve signals. Prolonged high-intensity exercise causes excess 5-HT to overflow from the synaptic cleft to the axonal initial segment and activates the 5-HT1A receptor, thereby inhibiting the action potential of motor neurons and affecting the recruitment of motor units. During exercise to fatigue, the DA secretion is decreased, which blocks the binding of DA to D1 receptor in the caudate putamen and inhibits the activation of the direct pathway of the basal ganglia to suppress movement, meanwhile the binding of DA to D2 receptor is restrained in the caudate putamen, which activates the indirect pathway of the basal ganglia to influence motivation. Furthermore, other neurotransmitters and their receptors, such as adenosine (ADO), glutamic acid (Glu), and γ‑aminobutyric acid (GABA) also play important roles in regulating neurotransmitter balance and fatigue. The occurrence of central fatigue is not the result of the action of a single neurotransmitter system, but a comprehensive manifestation of the interaction between multiple neurotransmitters. This review explores the important role of neurotransmitters and their receptors in central motor fatigue, reveals the dynamic changes of different neurotransmitters such as 5-HT, DA, NE, and ADO during exercise, and summarizes the mechanisms by which these neurotransmitters and their receptors regulate fatigue perception and exercise performance through complex interactions. Besides, this study presents pharmacological evidence that drugs such as agonists, antagonists, and reuptake inhibitors could affect exercise performance by regulating the metabolic changes of neurotransmitters. Recently, emerging interventions such as dietary bioactive components intake and transcranial electrical stimulation may provide new ideas and strategies for the prevention and alleviation of exercise fatigue by regulating neurotransmitter levels and receptor activity. Overall, this work offers new theoretical insights into the understanding of exercise central fatigue, and future research should further investigate the relationship between neurotransmitters and their receptors and exercise fatigue.

Objective To isolate pathogenic bacteria from the skin of a nude mouse exhibiting squamous skin scurfs, and perform bacterial identification, traceability analysis, and pathogenicity studies to provide a new approach for the diagnosis of pathogens in nude mice with squamous skin scurfs. MethodsSkin swab samples were collected from a nude mouse exhibiting squamous skin scurfs for nucleic acid testing, bacterial isolation and culture, biochemical identification, 16S rDNA gene amplification and sequencing, and whole genome sequencing to construct a phylogenetic tree. Fifteen BALB/c nude mice were randomized into a saline-treated control group, a high-concentration group treated with 1.8×10⁸ CFU/mL of the isolated bacterial suspension, and a low-concentration group treated with 1.8×10⁷ CFU/mL of the isolated bacterial suspension. Pathogenicity was assessed by animal infection experiments and observation of histopathological changes in skin tissue using HE staining. Results The nucleic acid test for Corynebacterium bovis was negative, excluding infection by this organism. The pathogen isolated on mannitol salt agar and blood agar, combined with Gram staining, suggested a Gram-positive Staphylococcus species. The isolated strain was identified by 16S rDNA sequencing and a fully automated microbial identification system as Staphylococcus xylosus. Phylogenetic tree analysis based on whole genome sequencing showed that the strain was most closely related to an isolate from leafy vegetables in South Korea (GenBank GCA_00207825.1). In the high-concentration group, squamous skin scurfs appeared on the head, neck, and back of nude mice on the 17th day post-infection, while in the low concentration group, similar symptoms appeared on the 20th day post-infection and gradually spread to other areas. The scaling symptoms were transient, lasting for 7 days in the high-concentration group and 3 days in the low-concentration group, after which the skin returned to normal. The infection rate was 33.33% in both the high- and low-concentration groups. No significant pathological changes were observed in the skin tissues of infected mice compared to the control group, indicating marked individual differences in the pathogenicity of the strain in nude mice. Conclusion A strain of Staphylococcus xylosus was isolated from the skin of a nude mouse exhibiting squamous skin scurfs. The strain is an opportunistic pathogen that causes transient squamous skin scurfs without significant histopathological changes, and there are individual differences in the sensitivity of nude mice to this strain. These findings can provide valuable data for pathogen identification in immunodeficient or gene knockout mice.

Objective To isolate pathogenic bacteria from the skin of a nude mouse exhibiting squamous skin scurfs, and perform bacterial identification, traceability analysis, and pathogenicity studies to provide a new approach for the diagnosis of pathogens in nude mice with squamous skin scurfs. MethodsSkin swab samples were collected from a nude mouse exhibiting squamous skin scurfs for nucleic acid testing, bacterial isolation and culture, biochemical identification, 16S rDNA gene amplification and sequencing, and whole genome sequencing to construct a phylogenetic tree. Fifteen BALB/c nude mice were randomized into a saline-treated control group, a high-concentration group treated with 1.8×10⁸ CFU/mL of the isolated bacterial suspension, and a low-concentration group treated with 1.8×10⁷ CFU/mL of the isolated bacterial suspension. Pathogenicity was assessed by animal infection experiments and observation of histopathological changes in skin tissue using HE staining. Results The nucleic acid test for Corynebacterium bovis was negative, excluding infection by this organism. The pathogen isolated on mannitol salt agar and blood agar, combined with Gram staining, suggested a Gram-positive Staphylococcus species. The isolated strain was identified by 16S rDNA sequencing and a fully automated microbial identification system as Staphylococcus xylosus. Phylogenetic tree analysis based on whole genome sequencing showed that the strain was most closely related to an isolate from leafy vegetables in South Korea (GenBank GCA_00207825.1). In the high-concentration group, squamous skin scurfs appeared on the head, neck, and back of nude mice on the 17th day post-infection, while in the low concentration group, similar symptoms appeared on the 20th day post-infection and gradually spread to other areas. The scaling symptoms were transient, lasting for 7 days in the high-concentration group and 3 days in the low-concentration group, after which the skin returned to normal. The infection rate was 33.33% in both the high- and low-concentration groups. No significant pathological changes were observed in the skin tissues of infected mice compared to the control group, indicating marked individual differences in the pathogenicity of the strain in nude mice. Conclusion A strain of Staphylococcus xylosus was isolated from the skin of a nude mouse exhibiting squamous skin scurfs. The strain is an opportunistic pathogen that causes transient squamous skin scurfs without significant histopathological changes, and there are individual differences in the sensitivity of nude mice to this strain. These findings can provide valuable data for pathogen identification in immunodeficient or gene knockout mice.