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.

Oral solid dosage forms require processes such as disintegration and dissolution to release the drug before it can be absorbed and utilized by the body. In this manuscript, imaging technology was used to continuously visualize and characterize the in vitro static drug release process of gliclazide modified release tablets from 15 manufacturers, combined with the traditional method of in vitro dissolution testing, to determine the release profile of gliclazide modified release tablets, to evaluate the similarity of the release profiles by using the similarity factor (f₂) method and based on the analysis of the release profiles fitted with a variety of mathematical models. The results indicate that the gliclazide modified release tablets produced by 14 companies are hydrophilic gel matrix tablets. Compared to the reference listed drug, the release profiles of formulations from 11 companies show high similarity (f₂ > 50) to the reference. Among these, formulations with visual characteristics similar to the reference exhibit similar release curves. This study provides an alternative method for the in vitro consistency evaluation of gliclazide modified release tablets, aiming to assess the in vitro release behaviour of generic formulations more accurately and comprehensively.

The present study employed UPLC-MS/MS to analyze and identify compounds in the raw powder of Tongluo Shenggu capsules. An HPLC method for the determination of vitexin content was established. The analysis of this drug was performed on a 30 ℃ thermostatic Acquity UPLC® BEH C18 (2.1 mm×100 mm,1.7 μm) column, with the mobile phase comprising 0.2% formic acid-methanol flowing at 0.3 mL /min in a gradient elution manner. Mass spectrometry was detected by ESI sources in both positive and negative ion modes for qualitative identification of chemical constituents. 12 flavonoid and 3 stilbenes compounds in the raw powder of Tongluo Shenggu capsules were successfully identified. Additionally, an HPLC method for the determination of vitexin content was established using a XBridge C18 column (4.6 mm × 250 mm, 5 µm) with a mobile phase of 0.05% glacial acetic acid in methanol for gradient elution, at a column temperature of 30 °C, a flow rate of 1.0 mL/min, and an injection volume of 20 μL. The method demonstrated good linearity in the concentration range of 10 µg/mL to 40 µg/mL (R=1.000) with an average recovery rate of 96.7%. The establishment of these methods provides a scientific basis for the quality control and development of the raw powder of Tongluo Shenggu capsules.

The traditional Chinese medicine(TCM) industry is a crucial part of China's pharmaceutical sector and plays a strategic role in ensuring public health and promoting economic and social development. In response to the practical demand for high-quality development of the TCM industry, this paper focused on the bottlenecks encountered during the digital and intelligent transformation of TCM production systems. Specifically, it explored technical strategies and methodologies for constructing the best TCM production mode. An innovative artificial intelligence(AI)-centered technical architecture for TCM production was proposed, focusing on key aspects of production management including process modeling, state evaluation, and decision optimization. Furthermore, a series of critical technologies were developed to realize the best TCM production mode. Finally, a novel AI-driven TCM production mode characterized by a closed-loop system of "measurement-modeling-decision-execution" was presented through engineering case studies. This study is expected to provide a technological pathway for developing new quality productive forces within the TCM industry.
Artificial Intelligence ; Drugs, Chinese Herbal ; Medicine, Chinese Traditional/methods* ; Humans

OBJECTIVE: To evaluate the efficacy and safety of Shexiang Tongxin Dropping Pill (STDP) in treating stable angina patients with phlegm-heat and blood-stasis syndrome by exercise duration and metabolic equivalents. METHODS: This multicenter, randomized, double-blind, placebo-controlled clinical trial enrolled stable angina patients with phlegm-heat and blood-stasis syndrome from 22 hospitals. They were randomized 1:1 to STDP (35 mg/pill, 6 pills per day) or placebo for 56 days. The primary outcome was the exercise duration and metabolic equivalents (METs) assessed by the standard Bruce exercise treadmill test after 56 days of treatment. The secondary outcomes included the total angina symptom score, Chinese medicine (CM) symptom scores, Seattle Angina Questionnaire (SAQ) scores, changes in ST-T on electrocardiogram and adverse events (AEs). RESULTS: This trial enrolled 309 patients, including 155 and 154 in the STDP and placebo groups, respectively. STDP significantly prolonged exercise duration with an increase of 51.0 s, compared to a decrease of 12.0 s with placebo (change rate: -11.1% vs. 3.2%, P<0.01). The increase in METs was significantly greater in the STDP group than in the placebo group (change: -0.4 vs. 0.0, change rate: -5.0% vs. 0.0%, P<0.01). The improvement of total angina symptom scores (25.0% vs. 0.0%), CM symptom scores (38.7% vs. 11.8%), reduction of nitroglycerin consumption (100.0% vs. 11.3%), and all domains of SAQ, were significantly greater with STDP than placebo (all P<0.01). The changes in Q-T intervals at 28 and 56 days from baseline were similar between the two groups (both P>0.05). Twenty-five participants (16.3%) with STDP and 16 (10.5%) with placebo experienced AEs (P=0.131), with no serious AEs observed. CONCLUSION STDP could improve exercise tolerance in patients with stable angina and phlegm-heat and blood stasis syndrome, with a favorable safety profile. (Registration No. ChiCTR-IPR-15006020).
Humans ; Double-Blind Method ; Drugs, Chinese Herbal/adverse effects* ; Male ; Female ; Middle Aged ; Angina, Stable/physiopathology* ; Aged ; Syndrome ; Treatment Outcome ; Placebos ; Tablets

OBJECTIVE: To evaluate the dynamic changes of glucocorticoid (GC) dose and the feasibility of GC discontinuation in rheumatoid arthritis (RA) patients under the background of Chinese medicine (CM). METHODS: This multicenter retrospective cohort study included 1,196 RA patients enrolled in the China Rheumatoid Arthritis Registry of Patients with Chinese Medicine (CERTAIN) from September 1, 2019 to December 4, 2023, who initiated GC therapy. Participants were divided into the Western medicine (WM) and integrative medicine (IM, combination of CM and WM) groups based on medication regimen. Follow-up was performed at least every 3 months to assess dynamic changes in GC dose. Changes in GC dose were analyzed by generalized estimator equation, the probability of GC discontinuation was assessed using Kaplan-Meier curve, and predictors of GC discontinuation were analyzed by Cox regression. Patients with <12 months of follow-up were excluded for the sensitivity analysis. RESULTS: Among 1,196 patients (85.4% female; median age 56.4 years), 880 (73.6%) received IM. Over a median 12-month follow-up, 34.3% (410 cases) discontinued GC, with significantly higher rates in the IM group (40.8% vs. 16.1% in WM; P<0.05). GC dose declined progressively, with IM patients demonstrating faster reductions (median 3.75 mg vs. 5.00 mg in WM at 12 months; P<0.05). Multivariate Cox analysis identified age <60 years [P<0.001, hazard ratios (HR)=2.142, 95% confidence interval (CI): 1.523-3.012], IM therapy (P=0.001, HR=2.175, 95% CI: 1.369-3.456), baseline GC dose ⩽7.5 mg (P=0.003, HR=1.637, 95% CI: 1.177-2.275), and absence of non-steroidal anti-inflammatory drugs use (P=0.001, HR=2.546, 95% CI: 1.432-4.527) as significant predictors of GC discontinuation. Sensitivity analysis (545 cases) confirmed these findings. CONCLUSIONS RA patients receiving CM face difficulties in following guideline-recommended GC discontinuation protocols. IM can promote GC discontinuation and is a promising strategy to reduce GC dependency in RA management. (Trial registration: ClinicalTrials.gov, No. NCT05219214).
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Arthritis, Rheumatoid/drug therapy* ; Glucocorticoids/therapeutic use* ; Medicine, Chinese Traditional ; Retrospective Studies

Risks of food safety induced by small molecule drug residues in animal food and environment have become an increasing public concern,so it is necessary to develop highly sensitive and easy-to-operate techniques to detect small molecules.Herein,a metasurface plasma resonance(MetaSPR)sensor chip coupled with gold nanoparticles(AuNPs)was developed for detection of enrofloxacin(ENR)based on competitive immunoassay.The detection range of the sensor for ENR was 0.025-3.2 ng/mL,and the detection limit(3σ)was 20 pg/mL.The biosensor showed excellent performance including high selectivity,good stability,ease to operate and high throughput,etc.The developed method was applied to detection of ENR residues in real samples,with recoveies of 96.0% -105.0%.The proposed sensing strategy provided new technique reference for detection of other small molecules in the field of residue analysis in food safety and environment monitoring.

Chest low-dose computed tomography (LDCT) is a widely utilized modality for lung cancer screening and follow-up in high-risk populations, owing to its low radiation dose. However, the diagnostic accuracy of LDCT is significantly constrained by inherent limitations, including elevated image noise and reduced contrast resolution. The potential for deep learning technologies to address these challenges through data-driven LDCT image denoising approaches has been demonstrated. In this review, the advantages and limitations of deep learning models were introduced, including supervised, unsupervised, and self-supervised learning. The potential and challenges of these models in clinical applications were analyzed, thereby providing a reference for subsequent research and clinical practice.

Exposure to acceleration can have Various effects on the physiology,psychology,and performance of human.With the increasing density and complexity of China's space mission,and the significant differences between deep space exploration and near Earth orbit flight,unprecedented challenges have been posed to the emotions of astronauts and the ability of human-machine collaboration to complete complex operational tasks in special environments.Similarly,with the continuous development of high-performance fighter jets,air combat operation are becoming increasingly complex,and the payload generated by the aircraft is also increasing.The requirements for the anti-overload ability of fighter pilots are also becoming higher and higher.A review of recent studies on physiological and cognitive load of acceleration exposure on humans.The research on human physiology is relatively systematic,but there is limited research on cognitive load.The corresponding evaluation methods,assessment methods,and assessment systems are not comprehensive enough,and there is a lack of mechanistic analysis.Multimodal analysis and modeling are even rarer.Further in-depth research is needed on the cognitive load and evaluation techniques of overweight environment in the future.This article provides reference for the selection,adaptive training,and related experimental research of overweight endurance for astronauts and pilots in the future.

ObjectiveTo systematically explore the underlying mechanisms of Huashi Baidu prescription （HBP） against myocardial injury through a multidimensional network analysis of "transcriptome-putative target-phenotype gene". MethodPutative targets of compounds in HBP were predicted using the Encyclopedia of Traditional Chinese Medicine （ETCM 2.0，http：//www.tcmip.cn/ETCM2/front/） and the Integrative Pharmacology-based Research Platform of Traditional Chinese Medicine （TCMIP v2.0，http：//www.tcmip.cn/TCMIP/index.php/Home/Login/login.html）. Clinical predominant symptom phenotypes for HBP against coronavirus disease 2019 （COVID-19） were collected from CNKI and PubMed databases， while clinical side effects of doxorubicin were gathered from the CTD database. Phenotype-related genes were collected from the HPO database and SoFDA data platform （http：//www.tcmip.cn/Syndrome/front/#/）. An interaction network of "transcriptome-putative target-phenotype gene" was constructed. Key nodes were identified through topological feature calculations， and functional enrichment analysis was conducted to explain the underlying mechanism. Pharmacodynamic evaluation and mechanism verification were performed using a doxorubicin-induced myocardial injury mouse model. Sixty-five SPF-grade C57BL/6J male mice were randomly divided into a control group， a doxorubicin model group， and low-， medium-， and high-dose HBP groups （HBP-L/M/H）， with 13 mice per group. Histopathological severity was assessed using hematoxylin-eosin （HE） and Masson staining. Fibrosis markers were measured by Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）， and protein expression was detected by Western blot. ResultA total of 1 044 putative targets for HBP were obtained from ETCM 2.0 and TCMIP v2.0. From the CTD， HPO， and SoFDA databases， 1 223 potential effect-related targets were identified. Cardiac transcriptome sequencing （RNA-seq） yielded 214 genes related to doxorubicin-induced myocardial injury and 58 genes associated with the effects of HBP， using criteria of P-value<0.05 and FC > 1.5/< 0.667. Analysis of the multidimensional molecular network revealed that the mechanisms of HBP on myocardial injury were mainly related to immune-inflammation imbalance， cellular metabolism， myocardial cell function and fibrosis， angiogenesis， contraction and platelet activation， DNA synthesis， metabolism and repair， as well as cell death and oxidative stress. HBP improved cardiovascular abnormalities such as reduced ejection fraction， myocardial fibrosis， myocarditis， hypertriglyceridemia， and arterial/venous thrombosis. Animal experiments demonstrated that HBP reduced the abnormal high expression of Nod-like receptor heat protein domain Protein 3 （NLRP3）， Caspase-1， apoptosis-associated speck-like protein （ASC）， and Gasdermin D （GSDMD） in myocardial tissue induced by doxorubicin （P<0.05）， and improved the elevated mRNA levels of fibrosis markers transforming growth factor-β₁ （TGF-β₁）， Smad3， and α-smooth muscle actin （α-SMA） （P<0.05）. ConclusionHBP can improve myocardial injury through multiple components， targets， and effects， with the inhibition of the NLRP3 inflammasome activation pathway being a key pharmacodynamic mechanism. This study is expected to provide new insights for the development of targeted therapeutic drugs.