OBJECTIVE To establish the method for determining the contents of five active components in raw and charred herb pairs of Gardenia jasminoides-Scutellaria baicalensis ， construct their fingerprints， and investigate the effects of G. jasminoides processing on chemical constituents in the h erb pairs. METHODS The HPLC method was used to determine the contents of genipin 1- β -D-gentiobioside， geniposide， crocin Ⅰ， crocin Ⅱ and baicalin in ten batches of raw G. jasminoides-S. baicalensis herb pairs and ten batches of charred G. jasminoides-S. baicalensis herb pairs. Using the same HPLC method， chromatographic fingerprints for the ten batches of raw herb pairs and ten batches of processed herb pairs were established with the Similarity Evaluation System for Chromatographic Fingerprints of Traditional Chinese Medicine （2012 edition）. Principal component analysis and orthogonal partial least squares-discriminant analysis were performed. RESULTS Compared with the raw G. jasminoides-S. baicalensis herb pair， the average content of genipin 1- β -D-gentiobioside in the charred G. jasminoides-S. baicalensis herb pair increased by 12.65%； while the average contents of geniposide， crocin Ⅰ， crocin Ⅱ and baicalin decreased by 7.86%， 60.62%， 62.07% and 0.15%， respectively. Chromatographic fingerprints of ten batches of raw herb pairs and ten batches of processed herb pairs shared 18 common peaks with similarities ranging from 0.997 to 1.000 and 0.988 to 1.000， respectively. Five common peaks were identified： genipin 1- β -D-gentiobioside （peak 2）， geniposide （peak 3）， crocin Ⅰ （peak 6）， crocin Ⅱ （peak 9） and baicalin （peak 10）. Principal component analysis and orthogonal partial least squares-discriminant analysis results showed that the raw G. jasminoides-S. baicalensis herb pair and the charred G. jasminoides-S. baicalensis herb pair could be clearly distinguished. Variable importance in the projection （VIP） values for crocin Ⅰ and crocin Ⅱ were both greater than one. CONCLUSIONS A method has been successfully developed for the determination of five active c omponents， including genipin 1- β -D-gentiobioside， in the G. jasminoides-S. baicalensis herb pair， and its fingerprint has been drawn. Processing is found to increase the content of genipin 1- β -D-gentiobioside， while decreasing the levels of geniposide， crocin Ⅰ， crocin Ⅱ and baicalin in the herb pair. Furthermore， crocin Ⅰ and crocin Ⅱ could serve as potential quality markers for the quality control of this herb pair.

BACKGROUND:Prolyl hydroxylase domain 2(PHD2)inhibitors can regulate bone metabolism and relieve osteoporosis in ovariectomized rats.cpd17 is a small molecule oral PHD2 inhibitor newly developed by China Pharmaceutical University.It is effective in the treatment of renal anemia with few side effects,but its effect on bone formation and bone resorption is still unclear. OBJECTIVE:To investigate the effects of cpd17 on mouse osteogenic precursor cells. METHODS:Osteogenic precursor cells were treated with cpd17.Alkaline phosphatase activity and extracellular matrix mineralization were measured,and the expression levels of osteogenesis-and osteoclastogenesis-related markers,as well as PHD2 and hypoxia-inducible factor 1α,were detected.After inhibition of the hypoxia-inducible factor 1α pathway using LW6(a hypoxia-inducible factor 1α pathway inhibitor),alkaline phosphatase activity and extracellular matrix mineralization were detected again,as well as the expression levels of osteogenesis-and osteoclastogenesis-related markers,PHD2 and hypoxia-inducible factor 1α. RESULTS AND CONCLUSION:cpd17 significantly enhanced alkaline phosphatase activity and extracellular matrix mineralization,up-regulated the expression of osteogenesis-related markers,down-regulated the expression of osteoclastogenesis-related markers,up-regulated the expression of hypoxia-inducible factor 1α,down-regulate the expression of PHD2.However,cpd17's effects were significantly attenuated by LW6.To conclude,the PHD2 inhibitor cpd17 promotes osteogenic differentiation and inhibits osteoclastic differentiation through activation of the hypoxia-inducible factor 1α signaling pathway.

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.

ObjectiveTo investigate the relationship between mitochondrial DNA copy number (mtDNAcn) and cognitive dysfunction, and its mediating role between type 2 diabetes mellitus (T2DM) and cognitive dysfunction. MethodsA case-control study was conducted from May 2019 to April 2021 at the Shanghai Yangpu District Central Hospital, China. A total of 193 subjects were recruited and divided into two groups based on the Montreal Cognitive Assessment (MoCA): normal control (NC) group (n=95) and cognitive impairment group (n=98). The prevalence of T2DM was determined on the basis of medical history, while mtDNAcn in peripheral blood samples was quantified using realtime fluorescent quantitative polymerase chain reaction. ResultsUnivariate analyses revealed that the mean mtDNAcn in the cognitive impairment group was 0.76±0.37, significantly lower than that in the NC group (1.06±0.45) (P<0.05). Logistic regression analyses showed that higher mtDNAcn was associated with a reduced risk of cognitive impairment (OR=0.315, 95%CI: 0.125‒0.795). Additionaly, a statistically significant positive correlation was observed between mtDNAcn and the total MoCA score (r=0.381, P<0.01). Morever, T2DM history (OR=2.741, 95%CI: 1.002‒7.497) and elevated glycosylated hemoglobin (HbA1c) levels (OR=1.796, 95%CI: 1.190‒2.711) were identified as risk factors for cognitive impairment. Mediation analyses indicated that mtDNAcn served as a mediator between T2DM/HbA1c and the risk of cognitive impairment, with proportions of mediating effect of 9.04% and 9.18%, respectively. ConclusionPatients with mild and moderate cognitive impairment have significantly lower mtDNAcn than those with normal cognitive function. Reduced mtDNAcn is an influencing factor for cognitive dysfunction and may play a mediating role in the association between T2DM and mild to moderate cognitive impairment.

Dormant tumor cells constitute a population of cancer cells that reside in a non-proliferative or low-proliferative state, typically arrested in the G0/G1 phase and exhibiting minimal mitotic activity. These cells are commonly observed across multiple cancer types, including breast, lung, and ovarian cancers, and represent a central cellular component of minimal residual disease (MRD) following surgical resection of the primary tumor. Dormant cells are closely associated with long-term clinical latency and late-stage relapse. Due to their quiescent nature, dormant cells are intrinsically resistant to conventional therapies—such as chemotherapy and radiotherapy—that preferentially target rapidly dividing cells. In addition, they display enhanced anti-apoptotic capacity and immune evasion, rendering them particularly difficult to eradicate. More critically, in response to microenvironmental changes or activation of specific signaling pathways, dormant cells can re-enter the cell cycle and initiate metastatic outgrowth or tumor recurrence. This ability to escape dormancy underscores their clinical threat and positions their effective detection and elimination as a major challenge in contemporary cancer treatment. Hypoxia, a hallmark of the solid tumor microenvironment, has been widely recognized as a potent inducer of tumor cell dormancy. However, the molecular mechanisms by which tumor cells sense and respond to hypoxic stress—initiating the transition into dormancy—remain poorly defined. In particular, the lack of a systems-level understanding of the dynamic and multifactorial regulatory landscape has impeded the identification of actionable targets and constrained the development of effective therapeutic strategies. Accumulating evidence indicates that hypoxia-induced dormancy tumor cells are accompanied by a suite of adaptive phenotypes, including cell cycle arrest, global suppression of protein synthesis, metabolic reprogramming, autophagy activation, resistance to apoptosis, immune evasion, and therapy tolerance. These changes are orchestrated by multiple converging signaling pathways—such as PI3K-AKT-mTOR, Ras-Raf-MEK-ERK, and AMPK—that together constitute a highly dynamic and interconnected regulatory network. While individual pathways have been studied in depth, most investigations remain reductionist and fail to capture the temporal progression and network-level coordination underlying dormancy transitions. Systems biology offers a powerful framework to address this complexity. By integrating high-throughput multi-omics data—such as transcriptomics and proteomics—researchers can reconstruct global regulatory networks encompassing the key signaling axes involved in dormancy regulation. These networks facilitate the identification of core regulatory modules and elucidate functional interactions among key effectors. When combined with dynamic modeling approaches—such as ordinary differential equations—these frameworks enable the simulation of temporal behaviors of critical signaling nodes, including phosphorylated AMPK (p-AMPK), phosphorylated S6 (p-S6), and the p38/ERK activity ratio, providing insights into how their dynamic changes govern transitions between proliferation and dormancy. Beyond mapping trajectories from proliferation to dormancy and from shallow to deep dormancy, such dynamic regulatory models support topological analyses to identify central hubs and molecular switches. Key factors—such as NR2F1, mTORC1, ULK1, HIF-1α, and DYRK1A—have emerged as pivotal nodes within these networks and represent promising therapeutic targets. Constructing an integrative, systems-level regulatory framework—anchored in multi-pathway coordination, omics-layer integration, and dynamic modeling—is thus essential for decoding the architecture and progression of tumor dormancy. Such a framework not only advances mechanistic understanding but also lays the foundation for precision therapies targeting dormant tumor cells during the MRD phase, addressing a critical unmet need in cancer management.

Objective: To investigate the abnormal fluctuation of coagulation function indicators in pediatric Burkitt lymphoma patients, and to analyze its correlation with disease progression and prognosis. Methods: The data of 172 children with Burkitt lymphoma in Children's Medical Center, Shanghai Jiao Tong University School of Medicine from January 2020 to December 2023 were retrospectively analyzed, and 120 healthy children were used as control group. Plasma prothrombin time (PT), activated partial thromboplastin time (APTT), thrombin time (TT), fibrinogen (Fib), International standardized ratio (INR), D-dimer (D-D), fibrinogen degradation products (FDP), and antithrombin (AT) were measured. Appropriate statistical methods were used to compare the data between two groups, and the Cox regression model was employed to analyze the influencing factors. A P-value <0.05 was considered statistically significant. Results: Levels of D-D, FDP, INR, and PT were significantly higher in children with Burkitt lymphoma than in the healthy controls [median (P25, P75) for the case group: 0.35 (0.13, 1.22), 3.10 (1.30, 10.20), 1.16 (1.06, 1.24), 12.60 (11.43, 13.50); median (P25, P75) for the healthy control group: 0.10 (0.07, 0.15), 0.60 (0.20, 1.08), 1.06 (1.02, 1.13), 11.50 (11.00, 12.30)](P<0.05). Levels of D-D, FDP, INR, PT, and TT were significantly elevated in children with recurrence compared to those without recurrence [median (P25, P75) for the recurrent group: 0.44 (0.16, 1.42), 3.85 (1.50, 12.25), 1.17 (1.08, 1.24), 12.70 (11.73, 13.50), 16.20 (14.80, 17.80); median (P25, P75) for the non-recurrent group: 0.21 (0.11, 0.69), 2.00 (1.00, 6.85), 1.11 (1.03, 1.24), 11.90 (11.10, 13.43), 15.20 (14.50, 16.40)](P<0.05). Levels of D-D, FDP in children with metastasis were significantly higher than those without metastasis [median (P25, P75) for the metastatic group: 0.51 (0.17, 1.84), 4.38 (1.70, 13.45); median (P25, P75) for the non-metastatic group: 0.20 (0.11, 0.39), 1.50 (1.00, 3.10)] (P<0.05). Levels of D-D and FDP were significantly higher in children with advanced stage than in those with early stage [median (P25, P75) for the high-stage group: 0.33 (0.14, 1.20), 3.10 (1.40, 10.23); median (P25, P75) for the low-stage group: 0.12 (0.08, 0.24), 0.90 (0.50, 2.50)] (P<0.05). Levels of D-D and FDP in high-risk children were significantly higher than those of low-risk [median (P25, P75) for the high-risk group: 0.28 (0.13, 1.01), 2.90 (1.15, 9.65); median (P25, P75) for the low-risk group: 0.12 (0.08, 0.17), 0.80 (0.43, 1.98)] (P<0.05). Levels of D-D, FDP, INR, and PT were significantly higher in children with poor prognosis than in those with favorable prognosis [median (P25, P75) for the poor prognosis group: 1.76 (0.80, 2.72), 13.45 (7.20, 25.30), 1.19 (1.12, 1.32), 12.85 (12.10, 14.35); median (P25, P75) for the favorable prognosis group: 0.23 (0.12, 0.52), 2.00 (1.00, 4.80), 1.14 (1.05, 1.23), 12.30 (11.40, 13.40)] (P<0.05). INR levels significantly increased with accumulating chemotherapy cycles [median (P25, P75) for one session: 1.09 (1.02, 1.20); two sessions: 1.31 (1.23, 1.38); three sessions: 1.79 (1.52, 2.41)] (P<0.05). Age, APTT, D-D, FDP, INR, PT, recurrence and metastasis had a significant effect on the survival of children with Burkitt lymphoma (P<0.05). Conclusion: Patients with Burkitt lymphoma exhibit coagulation disorders, which are influenced by recurrence, metastasis, clinical stage, risk stratification, and prognosis. In clinical practice, it is crucial to prioritize the monitoring of coagulation indicators to facilitate timely detection of coagulation dysfunction.