ObjectiveTo establish steroid-induced osteonecrosis of the femoral head （SANFH） cell model by using dexamethasone （DEX）-induced bone marrow mesenchymal stem cells （BMSCs） and demonstrate that Gushing Granules （GSNs） exert an improving effect by activating the phosphatidylinositol-3-kinase/protein kinase B/B-lymphoma-2 gene related promoter （PI3K/Akt/Bad） signalling pathway. MethodsFirstly， SD rats were orally administered with drugs at a dose of 0.9 g·kg^-1 to prepare GSN-containing serum， and CCK-8 screening was used to determine the optimal dosage and duration of action. Then， BMSCs were cultured and treated with 1×10^-6 mol·L^-1 DEX， 10% GSN-containing serum， and inhibitor LY294002 of PI3K/Akt signalling pathway for 24 hours to model and group SANFH cells. Cell viability and proliferation were detected by using CCK-8 assay kit and EdU staining kit. Flow cytometry was used to detect cell apoptosis. An alkaline phosphatase （ALP） assay kit was employed to detect ALP expression. In order to detect the PI3K/Akt/Bad signalling pathway and protein and mRNA expression of apoptosis-related proteins such as apoptosis regulatory factors B-cell lymphoma-2 gene （Bcl-2）， and Bcl-2-associated X protein （Bax）， osteocalcin （OCN）， and Collagen Ⅰ， we used Western blot and Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）. ResultsThe CCK-8 assay kit determined that the optimal dosage for GSN-containing serum is 10%， and the duration of action is 48 hours. After modelling and grouping the cells in each group， the detection results showed that the SANFH model group had significantly lower cell viability， cell proliferation， and ALP expression， as well as protein and mRNA expressions of PI3K， Akt， Bad， Bcl-2， OCN， and Collagen I compared to the blank group. The nucleic acid and protein levels of the Bax index and the cell apoptosis rate detected by flow cytometry significantly increased （P<0.05，P<0.01）. After treatment with GSN-containing serum， cell viability， cell proliferation， and ALP expression， as well as expressions of PI3K， Akt， Bad， Bcl-2， OCN， and Collagen Ⅰ nucleic acids and proteins were significantly increased， while the nucleic acid and protein levels of the Bax index and the cell apoptosis rate detected by flow cytometry significantly decreased（P<0.05，P<0.01）. Compared with the GSN drug-containing serum group， the simultaneous treatment with the inhibitor LY294002 and GSN drug-containing serum reversed the improvement effect of GSN. Specifically， the cell viability， cell proliferation， ALP expression， and the nucleic acid and protein levels of PI3K， Akt， Bad， Bcl-2， OCN， and Collagen Ⅰ were all significantly decreased， while the nucleic acid and protein levels of the Bax index and the cell apoptosis rate detected by flow cytometry were significantly increased （P<0.05， P<0.01）. ConclusionGSNs antagonize DEX-induced apoptosis of BMSCs by activating the PI3K/Akt/Bad signalling pathway， providing a scientific theoretical basis for the clinical treatment of SANFH with GSNs.

Clinical practice guidelines represent the best recommendations for patient care. They are developed through systematically reviewing currently available clinical evidence and weighing the relative benefits and risks of various interventions. However, clinical practice guidelines have to go through a long translation cycle from development and revision to clinical promotion and application, facing problems such as scattered distribution, high duplication rate, and low actual utilization. At present, the clinical practice guideline information platform can directly or indirectly solve the problems related to the lengthy revision cycles, decentralized dissemination and limited application of clinical practice guidelines. Therefore, this paper systematically examines different types of clinical practice guideline information platforms and investigates their corresponding challenges and emerging trends in platform design, data integration, and practical implementation, with the aim of clarifying the current status of this field and providing valuable reference for future research on clinical practice guideline information platforms.

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.

Biomolecular condensates are formed through phase separation of biomacromolecules such as proteins and RNAs. These condensates exhibit liquid-like properties that can futher transition into more stable material states. They form complex internal structures via multivalent weak interactions, enabling precise spatiotemporal regulations. However, the use of inconsistent and non-standardized terminology has become increasingly problematic, hindering academic exchange and the dissemination of scientific knowledge. Therefore, it is necessary to discuss the terminology related to biomolecular condensates in order to clarify concepts, promote interdisciplinary cooperation, enhance research efficiency, and support the healthy development of this field.

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.

The clinical practice guidelines of traditional Chinese medicine （TCM） have problems such as limited clinical application and unclear implementation effects， which may be related to the lack of clinical practice evidence. To provide reliable and precise evidence for clinical practice， this article proposes a model of combining TCM guidelines with real-world study， which includes 4 steps. Firstly， during the implementation process of the guidelines， a high-quality research database is established. Secondly， the recommendations in the guidelines are evaluated based on the established database in multiple dimensions， including applicability， effectiveness， safety， and cost-effectiveness， and thus their effectiveness in practical applications can be determined. Thirdly， based on the established database， core prescriptions are identified， and the targeted populations and medication plans are determined. That is， the best treatment regimen is established based on the analysis of abundant clinical data regarding the effects of different medication frequencies， dosages， and duration on efficacy. Fourthly， the guidelines are updated according to the real-world evidence. The research based on this model can provide real-world evidence for ancient and empirical prescriptions， improving their application in clinical practice. Moreover， this model can reduce research costs and improve research efficiency. When applying this model， researchers need to pay attention to the quality of real-world evidence， ensuring that it can truly reflect the situation in clinical practice. In addition， importance should be attached to the clinical application of guideline recommendations， ensuring that doctors can conduct standardized diagnosis and treatment according to the guidelines. Finally， full-process participation of multidisciplinary experts is encouraged to ensure the comprehensiveness and scientificity of the study. In conclusion， the application of this model will contribute to the development of TCM guidelines responsive to the needs of clinical practice and achieve the goal of promoting the homogenization of TCM clinical diagnosis and treatment.

ObjectiveTo explore and analyze the influencing factors of myopia among the primary and middle school students, and to provide an evidence for the prevention and control of myopia in students through the combination of scientific use in electronic products and adherence improvement to outdoor activities. MethodsStratified cluster sampling method was used to select 4 schools in Jiading District, in which all the students in grades 3‒5 of primary school and grades 7‒9 of middle school were enrolled into the study for a questionnaire survey and refraction examination. The χ² test was used to compare the data between the myopic and non-myopic group. Logistic regression analysis was used to analyze the influencing factors of myopia. ResultsThe total myopia detection rate among the primary and middle school students in the industrial zone of Jiading District was 62.8%, with a detection rate of 46.9% for primary school students and 75.6% for middle school students, respectively. Logistic regression analysis showed that middle school (OR=3.639, 95%CI=3.045‒4.349, P<0.001), female students (OR=1.278, 95%CI=1.081‒1.510, P=0.004), the frequency of school desks and chairs was adjusted>1 semester (OR=1.227, 95%CI=1.031‒1.461, P=0.021), the length of time spent on extracurricular tutorial classes for main courses ≥1 hour in a week (OR=1.205,95%CI=1.009‒1.440, P=0.040), parents reduced the length of time that their children spent on exercise (OR=1.205, 95%CI=1.009‒1.440, P=0.040), and parental myopia (OR=2.611, 95%CI=2.157‒3.160, P<0.001) were associated with myopia among the primary and middle school students in the industrial zone of Jiading District. ConclusionThe detection rate of myopia among students in Jiading District was relatively high. More attention should be paid to the effect of school desks and chairs’ adjustment frequency, the length of time spent on extracurricular tutorial classes for main courses, electronic screen exposure time on students’ vision, so as to prevent and slow down the occurrence and development of myopia.

3ʹ-Hydroxy-4ʹ-methoxy-2-hydroxy-5-bromochalcone (hereinafter referred to as C13) is a novel chalcone derivative obtained in the process of structural modification of DHMMF, the antitumor active compound of Resina Draconis, in our laboratory. In this study, we investigated the effects of C13 on the proliferation and apoptosis of human gastric cancer HGC-27 and AGS cells and its potential mechanism of action. Firstly, through methyl thiazolyl tetrazolium (MTT), colony formation assay, and 5-ethynyl-2'-deoxyuridine (EdU) staining, we found that C13 inhibited the proliferation ability of human gastric cancer HGC-27 and AGS cells. Using flow cytometry and Western blot, it was found that C13 induced apoptosis in human gastric cancer HGC-27 and AGS cells, and up-regulated the protein level of cleaved poly ADP-ribose polymerase (cleaved-PARP). The results of RNA sequencing analysis showed that the Erb-b2 receptor tyrosine kinase 4/phosphoinositide 3-kinases/AKT (ErbB4/PI3K/AKT) signaling pathway may be involved in anti-gastric cancer activity of C13. Finally, the results of immunoblotting assay showed that C13 treatment down-regulated the protein levels of ErbB4 and phospho-ErbB4, as well as down-regulated the phosphorylation levels of PI3K and AKT in human gastric cancer HGC-27 and AGS cells, which verified the results from RNA-seq analysis. In conclusion, C13 inhibited the proliferation and induced apoptosis of human gastric cancer cells, which may be related to the down-regulation of ErbB4/PI3K/AKT signaling pathway. This study may provide a candidate drug for the treatment of gastric cancer.

Exploring the risk "time interval window" of sequential medication of Reduning injection (RDN) and penicillin G injection (PG) by detecting the correlation between serum biochemical indexes and plasma metabonomic characteristics, in order to reduce the risk of adverse reactions caused by the combination of RDN and PG. All animal experiments and welfare are in accordance with the requirements of the First Affiliated Experimental Animal Ethics and Animal Welfare Committee of Henan University of Chinese Medicine (approval number: YFYDW2020002). The changes of biochemical indexes in serum of rats were detected by enzyme-linked immunosorbent assay. It was determined that RDN combined with PG could cause pseudo-allergic reactions (PARs) activated by complement pathway. Further investigation was carried out at different time intervals (1.5, 2, 3.5, 4, 6, and 8 h PG+RDN). It was found that sequential administration within 3.5 h could cause significant PARs. However, PARs were significantly reduced after administration interval of more than 4 h. LC-MS was used for plasma metabolomics analysis, and the levels of serum biochemical indicators and plasma metabolic profile characteristics were compared in parallel. 22 differential metabolites showed similar or opposite trends to biochemical indicators before and after 3.5 h. And enriched to 10 PARs-related pathways such as arachidonic acid metabolism, steroid hormone biosynthesis, linoleic acid metabolism, glycerophospholipid metabolism, and tryptophan metabolism. In conclusion, there is a risk "time interval window" phenomenon in the adverse drug reactions caused by the sequential use of RDN and PG, and the interval medication after the "time interval window" can significantly reduce the risk of adverse reactions.

PI3Kγ and PI3Kδ have important regulatory roles in the immune system, and targeting these two subtypes helps to reshape the tumor microenvironment. PI3Kγ and PI3Kδ are potential targets for tumor immunotherapy. In this study, a series of new pyrazolopyrimidine derivatives were designed and synthesized on the basis of our previously reported PI3K inhibitors, resulting in the discovery of compound 16l as a potent and selective PI3Kγ/δ dual inhibitor. Compound 16l demonstrated strong biochemical potencies against PI3Kγ and PI3Kδ with IC₅₀ values of 0.11 and 0.79 nmol·L^-1. In cell-based assays, it potently inhibited the PI3Kγ and PI3Kδ mediated Akt S473 phosphorylation with EC₅₀ values of 3 and 7 nmol·L^-1. In vivo, compound 16l exhibited acceptable pharmacokinetic properties in Sprague-Dawley (SD) rats and suppressed the tumor growth in a MC38 syngeneic mouse model. The animal experiments were approved by the Animal Ethics Committee of Hefei Institutes of Physical Science, Chinese Academy of Sciences (approval number: DWLL-2000-06). In addition, no appreciable human ether-a-go-go-related gene (hERG) inhibition was observed for compound 16l even at 30 μmol·L^-1. These results suggested that compound 16l might be a potential research tool for studying the PI3Kγ/δ mediated signaling pathways.