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.

Objective To investigate the mechanism by which angiotensin Ⅱ type 1 receptor autoantibody(AT1-AA)promotes phenotypic switch of vascular smooth muscle cells(VSMCs)and vascular fibrosis through abnormal expression of circadian clock protein BMAL1.Methods Twelve male SD rats(6～8 weeks old,weighing 180～220 g)were randomly divided into(n=6)a control group and an AT1-AA-positive group[established by active immunization of SD rats with AT1R extracellular loop Ⅱ peptide(AT1R-ECLⅡ)].HE and Masson stainings were used to observe structural changes and fibrosis in the thoracic aorta(n=3).Western blotting was performed to detect the expression of Collagen I,phenotypic switch-related proteins(SM22,α-SMA,OPN and MMP2)in vascular tissues and primary VSMCs(n=4),as well as the expression of BMAL1 at CT0,CT4,CT8,CT12,CT16,and CT20.Transwell and scratch assays were used to assess the proliferation and migration of VSMCs(n=3).si-RNA was employed to knock down Bmal1,followed by detection of BMAL1,Collagen I,and phenotypic conversion-related protein expression(n=3).Additionally,AT1-AA-positive AT1R-knockout(AT1R-KO)rats were constructed to measure BMAL1 expression in thoracic aortic tissues(n=4).Results The AT1-AA-positive rats had significantly thickened thoracic aortic vessel wall[(140±9)%vs(120±5)%,P<0.05],badly arranged VSMCs,obvious blue Masson staining,and up-regulated Collagen I expression(P<0.05).In the thoracic aorta of AT1-AA-positive rats and AT1-AA-treated VSMCs,the expression of contractile phenotype-related proteins(α-SMA,SM22)was decreased(P<0.05),while the expression of synthetic phenotype-related proteins(OPN,MMP2)was increased(P<0.05).AT1-AA enhanced the scratch healing ability and migration ability of VSMCs.Furthermore,both mRNA and protein levels of Bmal1 were significantly up-regulated at CT12(P<0.05),and the rhythmicity of Bmal1 was lost.Knockdown of Bmal1 partially ameliorated AT1-AA-induced phenotypic switch of VSMCs.Compared with AT1-AA-positive WT rats,AT1-AA-positive AT1R-KO rats showed significantly reduced BMAL1 expression in the thoracic aorta(1.35±0.06 vs 0.86±0.07,P<0.001).At the cellular level,AT1-AA-induced phenotypic switch and high Collagen I expression in VSMCs were partially improved in AT1R-KO VSMCs.Conclusion AT1-AA promotes VSMCs phenotypic conversion and vascular fibrosis through the AT1R-Bmal1 axis.

Objective To investigate the protective effects of Qiji Special Dietary Food on exercise-induced myocardial injury in mice.Methods An exercise-induced myocardial injury model was established using a treadmill running protocol,and at the same time,the modeled mice were administered Qiji Special Dietary Food via oral gavage,followed by a 4-week treadmill exhaustion test.Serum levels of cardiac troponin T(cTnT),creatine kinase(CK),and lactate dehydrogenase(LDH)were measured.Myocardial tissues were analyzed for superoxide dismutase(SOD)activity and malondialdehyde(MDA)content.Histopathological alterations and ultrastructural changes in myocardial tissue were evaluated using light microscopy and transmission electron microscopy(TEM).Results After 4 weeks of exhaustive training,compared to the control group,the model group exhibited significantly elevated serum cTnT,CK,and myocardial MDA levels(P<0.01),along with reduced myocardial SOD activity(P<0.01).Compared to the model group,high-,medium-,and low-dose treatment significantly attenuated the exhaustive exercise-induced increases in serum cTnT level and myocardial MDA content(P<0.01),restoring these indicators to the levels comparable to those of the normal control group(P<0.05).Additionally,all treatment groups had markedly increased myocardial SOD activity,with no significant difference from the normal group.Histopathological and ultrastructural analyses revealed markedly alleviated myocardial damage in the treatment groups,with the medium-dose group exhibiting the most pronounced protective effects.Conclusion Qiji Special Dietary Food demonstrates significant protective effects against exercise-induced myocardial injury in mice,which maybe associated with its antioxidant activity and mitigation of oxidative stress.

Current ambient mass spectrometry ionization often requires external auxiliary equipment such as high-voltage power supply,gas cylinder,and syringe pump.Moreover,the process of sample preparation is cumbersome,and the experimental operations are complex,which makes it difficult to adapt to real-time on-site detection.In this work,a novel method was proposed,in which direct sampling of raw samples,online extraction of interest analytes,and ionization of target molecules were integrated into a single unit.With the developed method,the in-situ extraction and nano-electrospray ionization for both liquid and solid raw samples were achieved.Also,a handheld ion source and its pose adjustment device were developed,and the position and angle parameters were subsequently optimized.The performance of the ionization device was tested using standard solutions of caffeine and reserpine.The limits of detection(LODs)were 0.08 μg/L and 0.14 μg/L,with relative standard deviations(RSDs)≤3.7% and≤5.6%,respectively,indicating that the device possessed high sensitivity and stability.Using this device,three different concentrations of reserpine standard solutions were continuously tested for five days.The intra-day RSDs were consistently≤4.7% and the inter-day RSDs were all≤10.3%,showing the good working stability of the device.Without any pretreatment,a rapid qualitative detection of medicinal components including astragaloside II and cycloastragenol in five traditional Chinese medicines was carried out,with RSDs≤8.0% and≤7.1%,respectively.Additionally,rapid qualitative detection of gallic acid,a medicinal component,in white peony roots,and hypaphorine as well as quercetin in cowherb seeds were carried out,with RSDs≤7.0%,≤6.4% and≤6.1%,respectively.These results demonstrated that the ionization technology and device exhibited good stability during qualitative detection of raw samples.

The hydroxyl value and conjugated linoleic acid content of dehydrated castor oils are two important indicators that reflect its properties.Thus,monitoring the two indicators can better realize the industrial production of high-quality dehydrated castor oils.However,traditional chemical measurement methods have many disadvantages in determination of the two indictors,including large reagent consumption,long determination time,and cannot achieve rapid monitoring.Fourier transform infrared spectrometry(FTIR)is a new and non-destructive detection method that is low-cost and can achieve rapid detection.In this work,FTIR technique was employed to collect spectral information of dehydrated castor oils and analyze the relationship between FTIR spectral information and hydroxyl value and conjugated linoleic acid content,and a rapid detection method for detecting the property indicators of dehydrated castor oils was thus established.FTIR scanning was performed on dehydrated castor oils with a hydroxyl value of 21.9-161.4 mg KOH/g and a conjugated linoleic acid content of less than 37.5%.Among different preprocessing methods,orthogonal scatter correction(OSC)could improve the prediction accuracy of the resulting model,by which the optimal modeling data segments for hydroxyl value and conjugated linoleic acid content were 3200-3800 cm-1 and 800-1200 cm-1,respectively,and the optimal modeling method was partial least squares(PLS).The coefficients of determination of the optimal models for hydroxyl value and conjugated linoleic acid content were all above 0.99.

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.