Childhood obesity has become a global public health issue. Current research indicates that early life obesogen exposure has emerged as a significant risk factor for childhood obesity. While obesogens have been confirmed to influence the development and progression of childhood obesity through mechanisms such as endocrine disruption and epigenetic programming, controversies remain regarding the establishment of causal relationships, assessment of combined exposures, and validation of transgenerational effects in humans. In recent years, novel approaches including multi-omics technologies, exposome-based analysis, and multigenerational cohort studies have integrated dynamic biomarker monitoring with analyses of social-environmental interactions, offering new perspectives and methodologies for constructing a systematic "exposure-mechanism-outcome" research framework. This article reviews literature from PubMed and Web of Science up to August 2025 on the association between early life obesogen exposure and childhood obesity, summarizing evidence on the health effects of early life obesogen exposure, major exposure pathways and internal exposure assessment, interactions and amplifying effects of social and environmental factors, as well as the biological mechanisms underlying obesogen action. It further examines current research frontiers and challenges, aiming to provide a theoretical foundation for early prevention and precision intervention of childhood obesity.

ObjectiveTo investigate the mechanisms by which Renshentang treats atherosclerosis （AS） in mice， focusing on the regulation of endothelial inflammatory responses mediated by transient receptor potential vanilloid subtype 1 （TRPV1）. MethodsAn AS model was established in apolipoprotein E knockout （ApoE^-/-） mice fed a high-fat diet. The mice were randomly divided into a simvastatin group （0.02 g·kg^-1·d^-1） and low-， medium-， and high-dose Renshentang groups （1.77， 3.54， 7.08 g·kg^-1·d^-1）， with 12 mice in each group. ApoE^-/- mice were fed a high-fat diet and treated simultaneously. C57BL/6J mice fed a normal diet served as the normal group （n=9）. After continuous administration for 12 weeks， mice were anesthetized and the aortas were collected. Oil Red O staining was used to observe lipid plaque formation in the aorta. Hematoxylin-eosin （HE） staining was performed to examine pathological changes in the aortic root. Immunohistochemistry was used to analyze the levels of pro-inflammatory factors tumor necrosis factor-α （TNF-α） and interleukin-1β （IL-1β）， as well as the expression of TRPV1， phosphorylated phosphoinositide 3-kinase （p-PI3K）， and phosphorylated protein kinase B （p-Akt） in the aortic root. Real-time quantitative polymerase chain reaction （Real-time PCR） was used to detect endothelial nitric oxide synthase （eNOS） mRNA expression in the aorta， and Western blot was used to detect TRPV1 protein expression. ResultsCompared with the normal group， the model group showed a significant increase in aortic plaque formation （P<0.01） and significantly elevated levels of TNF-α and IL-1β in the aortic root （P<0.01）. The expression levels of TRPV1， p-PI3K， and p-Akt were decreased （P<0.05， P<0.01）， and eNOS mRNA expression was reduced （P<0.05， P<0.01）. Compared with the model group， all Renshentang groups significantly reduced aortic plaque formation （P<0.01）， significantly decreased TNF-α and IL-1β levels （P<0.01）， and markedly increased the expression levels of TRPV1， p-PI3K， p-Akt， and eNOS mRNA （P<0.05， P<0.01）. ConclusionRenshentang may inhibit endothelial inflammation and suppress the formation of AS by increasing TRPV1 protein expression and up-regulating the PI3K/Akt/eNOS signaling pathway， which may be one of the molecular mechanisms underlying its therapeutic effect against AS.

ObjectiveGastrodia elata has evolved ecological types with shortened rhizome internodes and diversified flower and fruit coloration in response to different altitudes. Studying the genetic mechanisms of different ecotype germplasm is significant for guiding variety breeding in different cultivation areas. MethodsThe bHLH gene family was identified based on the whole-genome datasets of G. elata f. elata and G. elata f. glauca. Subsequently， the gene family members were subject to analysis， including gene structure， chromosomal localization， cis-acting elements， gene synteny， and phylogeny. Combined with transcriptome data and quantitative Real-time PCR， the expression patterns of bHLH genes in the stems of the different G. elata ecotype germplasm were analyzed. Finally， correlation analysis was conducted between gene expression patterns and color to obtain the key bHLH genes regulating the color formation of stem. ResultsA total of 63 bHLH genes were identified in both G elata f. elata and G. elata f. glauca， unevenly distributed across 17 chromosomes and clustered into 16 subfamilies， with significant expansion in some family members. Obvious inversions of bHLH genes on the same chromosome and interchromosomal translocations were detected in the two ecotype germplasm. Among these genes， 12 bHLH genes （such as bHLH62-3 and bHLH74） were associated with the bright yellow color of G elata f. elata stem， while 9 bHLH genes （such as PIL13， UNE12， and bHLH130） were correlated with the red color of G. elata f. glauca stem. Compared to G. elata f. glauca， the bHLH48 expression level was significantly higher in flowers and scale leaves of G elata f. elata， and the bHLH62-3 expression level was significantly higher in all organs of G elata f. elata. ConclusionsFunctional pathway divergence of the bHLH family members has occurred across different chromosomes in G elata f. elata and G. elata f. glauca. Through synergism or antagonism with other genes， 21 bHLH genes participate in the coloration metabolic pathway regulation of stems， flowers， and fruits. Specifically， bHLH62-3 is involved in regulating stem color differentiation in the anthocyanin biosynthesis pathway of G. elata， thus relevant to the color formation of stem. Additionally， GebHLH48 positively regulates flowering-related pathways to promote the early-flowering phenotype of G. elata f. elata. These findings have laid the foundation for analyzing the genetic regulatory mechanisms underlying the color formation of the G. elata stem.

ObjectiveGastrodia elata has evolved ecological types with shortened rhizome internodes and diversified flower and fruit coloration in response to different altitudes. Studying the genetic mechanisms of different ecotype germplasm is significant for guiding variety breeding in different cultivation areas. MethodsThe bHLH gene family was identified based on the whole-genome datasets of G. elata f. elata and G. elata f. glauca. Subsequently， the gene family members were subject to analysis， including gene structure， chromosomal localization， cis-acting elements， gene synteny， and phylogeny. Combined with transcriptome data and quantitative Real-time PCR， the expression patterns of bHLH genes in the stems of the different G. elata ecotype germplasm were analyzed. Finally， correlation analysis was conducted between gene expression patterns and color to obtain the key bHLH genes regulating the color formation of stem. ResultsA total of 63 bHLH genes were identified in both G elata f. elata and G. elata f. glauca， unevenly distributed across 17 chromosomes and clustered into 16 subfamilies， with significant expansion in some family members. Obvious inversions of bHLH genes on the same chromosome and interchromosomal translocations were detected in the two ecotype germplasm. Among these genes， 12 bHLH genes （such as bHLH62-3 and bHLH74） were associated with the bright yellow color of G elata f. elata stem， while 9 bHLH genes （such as PIL13， UNE12， and bHLH130） were correlated with the red color of G. elata f. glauca stem. Compared to G. elata f. glauca， the bHLH48 expression level was significantly higher in flowers and scale leaves of G elata f. elata， and the bHLH62-3 expression level was significantly higher in all organs of G elata f. elata. ConclusionsFunctional pathway divergence of the bHLH family members has occurred across different chromosomes in G elata f. elata and G. elata f. glauca. Through synergism or antagonism with other genes， 21 bHLH genes participate in the coloration metabolic pathway regulation of stems， flowers， and fruits. Specifically， bHLH62-3 is involved in regulating stem color differentiation in the anthocyanin biosynthesis pathway of G. elata， thus relevant to the color formation of stem. Additionally， GebHLH48 positively regulates flowering-related pathways to promote the early-flowering phenotype of G. elata f. elata. These findings have laid the foundation for analyzing the genetic regulatory mechanisms underlying the color formation of the G. elata stem.

Objective: To investigate the safety and feasibility of transurethral blue laser vaporization of the prostate (BVP) under intravenous anesthesia without intubation. Methods: Clinical data of 30 benign prostatic hyperplasia (BPH) (prostate volume <40 mL) patients undergoing BVP under intravenous anesthesia without intubation in our hospital during Jul.and Nov.2024 were retrospectively analyzed.Preoperative and 1-month postoperative international prostate symptom score (IPSS), quality of life score (QoL), maximum urinary flow rate (Qmax), and postvoid residual volume (PVR) were compared.The operation time, cumulative blue laser activation time, recovery time, postoperative bladder irrigation time, postoperative catheter indwelling time, postoperative 2-hour visual analog scale (VAS) score and incidence of surgical and anesthetic complications were recorded. Results: All 30 patients successfully completed BVP under intravenous anesthesia without intubation.The operation time was (12.5±5.0) min, cumulative laser activation time (9.8±4.1) min, recovery time (6.8±1.2) min, postoperative bladder irrigation time (11.0±4.6) h, postoperative catheter indwelling time (2.7±1.1) days and postoperative 2-hour VAS score was (3.0±1.3).No cases required conversion to intubated general anesthesia, and no severe perioperative surgical or anesthetic complications occurred.Significant improvements in IPSS, QoL, Qmax, and PVR were observed 1 month postoperatively (P＜0.001). Conclusion: BVP under intravenous anesthesia without intubation in the treatment of prostate volume <40 mL BPH is clinically feasible, significantly improving lower urinary tract symptoms without significant surgical or anesthetic complications.

ObjectiveTo explore the effects of Renshentang on atherosclerosis （AS） in mice based on the role of transient receptor potential vanilloid1 （TRPV1） in regulating cholesterol metabolism in foam cells. MethodsNine SPF-grade 8-week-old C57BL/6J mice were set as a normal group， and 60 ApoE^-/- mice were randomized into model， positive drug （simvastatin， 0.02 g·kg^-1·d^-1）， and low-， medium-， and high-dose （1.77， 3.54， 7.08 g·kg^-1·d^-1， respectively） Renshentang groups （n=12） according to body weight. The normal group was fed with a normal diet， and the other groups were fed with a high-fat diet and given corresponding drugs by oral gavage for the modeling of AS. The mice were administrated with corresponding drugs once a day for 12 weeks. After the last administration and fasting for 12 h， the aorta was collected. Plaque conditions， pathological changes， levels of total cholesterol （TC）， triglcerides （TG）， low-density lipoprotein-cholesterol （LDL-C）， and high-density lipoprotein-cholesterol （HDL-C）， and the expression of TRPV1， liver X receptor （LXR）， inducible degrader of the low-density lipoprotein receptor （IDOL）， and low-density lipoprotein receptor （LDLR） in the aortic tissue were observed and detected by gross oil red O staining， HE staining， Western blot， immunohistochemistry， and real-time PCR. ResultsCompared with the normal group， the model group presented obvious plaque deposition in the aorta， raised levels of TC， TG， and LDL-C in the serum （P<0.01）， up-regulated expression level of LDLR in the aorta （P<0.01）， lowered level of HDL-C in the serum， and down-regulated expression levels of TRPV1， LXR， and IDOL in the aorta （P<0.05， P<0.01）. Compared with the model group， the positive drug and Renshentang at different doses alleviated AS， elevated the levels of HDL-C， TRPV1， LXR， and IDOL （P<0.05， P<0.01）， while lowering the levels of TC， TG， LDL-C， and LDLR （P<0.05， P<0.01）. ConclusionRenshentang has a lipid-lowering effect on AS mice. It can effectively reduce lipid deposition， lipid levels， and plaque area of AS mice by activating TRPV1 expression and regulating the LXR/IDOL/LDLR pathway.

Heart and spleen deficiency syndrome is the most common syndrome type in patients with insomnia. Based on the theory of disease syndrome-combined animal model， this paper used multiple databases to search for the keywords "heart and spleen deficiency"， "insomnia"， "sleepless"， "disease syndrome-combined animal model"， "model evaluation"， etc. It selected the literature related to the animal model of insomnia with heart and spleen deficiency in the past 20 years to evaluate from the aspects of model establishment， modeling factors， syndrome model， disease model， macro characterization & macro characterization evaluation scale， micro indicators， etc. It is found that the existing animal model of insomnia with heart and spleen deficiency is not completely constructed by the method of disease syndrome combination of disease modeling factors and syndrome modeling factors. In the model using this method， the single establishment factor of heart and spleen deficiency does not conform to the clinical reality of disease， and the selection of the factors for the insomnia model is not closely related to or even separated from the syndrome performance. There is a problem of insufficient quantification of macro representation when the macro representation of the model replaces the symptoms related to heart and spleen deficiency syndrome and insomnia in an equivalent manner for macro representation evaluation， which can be improved according to the quantitative ideas and examples of the existing macro representation and macro representation evaluation scale. There are few specific indicators of heart and spleen deficiency syndrome in micro indicators. The micro research of heart and spleen deficiency syndrome and the essence of other traditional Chinese medicine （TCM） syndromes can be carried out by metabonomics and other technologies combined with the theory of corresponding prescription and syndrome， along the specific related ideas of "prescription and syndrome， treatment principle and selection of prescription， treatment principle and selection of acupoints， as well as therapeutic mechanism and syndrome essence". The future users and researchers of animal models of insomnia with heart and spleen deficiency can get improved methods and ideas through the shortcomings of animal models of heart and spleen deficiency listed in this paper and construct animal models of insomnia with heart and spleen deficiency that are more suitable for clinical practice， so as to establish a more perfect modeling method and evaluation system of disease syndrome-combined animal model.

ObjectiveTo explore the effects of Renshentang on atherosclerosis （AS） in mice based on the role of transient receptor potential vanilloid1 （TRPV1） in regulating cholesterol metabolism in foam cells. MethodsNine SPF-grade 8-week-old C57BL/6J mice were set as a normal group， and 60 ApoE^-/- mice were randomized into model， positive drug （simvastatin， 0.02 g·kg^-1·d^-1）， and low-， medium-， and high-dose （1.77， 3.54， 7.08 g·kg^-1·d^-1， respectively） Renshentang groups （n=12） according to body weight. The normal group was fed with a normal diet， and the other groups were fed with a high-fat diet and given corresponding drugs by oral gavage for the modeling of AS. The mice were administrated with corresponding drugs once a day for 12 weeks. After the last administration and fasting for 12 h， the aorta was collected. Plaque conditions， pathological changes， levels of total cholesterol （TC）， triglcerides （TG）， low-density lipoprotein-cholesterol （LDL-C）， and high-density lipoprotein-cholesterol （HDL-C）， and the expression of TRPV1， liver X receptor （LXR）， inducible degrader of the low-density lipoprotein receptor （IDOL）， and low-density lipoprotein receptor （LDLR） in the aortic tissue were observed and detected by gross oil red O staining， HE staining， Western blot， immunohistochemistry， and real-time PCR. ResultsCompared with the normal group， the model group presented obvious plaque deposition in the aorta， raised levels of TC， TG， and LDL-C in the serum （P<0.01）， up-regulated expression level of LDLR in the aorta （P<0.01）， lowered level of HDL-C in the serum， and down-regulated expression levels of TRPV1， LXR， and IDOL in the aorta （P<0.05， P<0.01）. Compared with the model group， the positive drug and Renshentang at different doses alleviated AS， elevated the levels of HDL-C， TRPV1， LXR， and IDOL （P<0.05， P<0.01）， while lowering the levels of TC， TG， LDL-C， and LDLR （P<0.05， P<0.01）. ConclusionRenshentang has a lipid-lowering effect on AS mice. It can effectively reduce lipid deposition， lipid levels， and plaque area of AS mice by activating TRPV1 expression and regulating the LXR/IDOL/LDLR pathway.

Heart and spleen deficiency syndrome is the most common syndrome type in patients with insomnia. Based on the theory of disease syndrome-combined animal model， this paper used multiple databases to search for the keywords "heart and spleen deficiency"， "insomnia"， "sleepless"， "disease syndrome-combined animal model"， "model evaluation"， etc. It selected the literature related to the animal model of insomnia with heart and spleen deficiency in the past 20 years to evaluate from the aspects of model establishment， modeling factors， syndrome model， disease model， macro characterization & macro characterization evaluation scale， micro indicators， etc. It is found that the existing animal model of insomnia with heart and spleen deficiency is not completely constructed by the method of disease syndrome combination of disease modeling factors and syndrome modeling factors. In the model using this method， the single establishment factor of heart and spleen deficiency does not conform to the clinical reality of disease， and the selection of the factors for the insomnia model is not closely related to or even separated from the syndrome performance. There is a problem of insufficient quantification of macro representation when the macro representation of the model replaces the symptoms related to heart and spleen deficiency syndrome and insomnia in an equivalent manner for macro representation evaluation， which can be improved according to the quantitative ideas and examples of the existing macro representation and macro representation evaluation scale. There are few specific indicators of heart and spleen deficiency syndrome in micro indicators. The micro research of heart and spleen deficiency syndrome and the essence of other traditional Chinese medicine （TCM） syndromes can be carried out by metabonomics and other technologies combined with the theory of corresponding prescription and syndrome， along the specific related ideas of "prescription and syndrome， treatment principle and selection of prescription， treatment principle and selection of acupoints， as well as therapeutic mechanism and syndrome essence". The future users and researchers of animal models of insomnia with heart and spleen deficiency can get improved methods and ideas through the shortcomings of animal models of heart and spleen deficiency listed in this paper and construct animal models of insomnia with heart and spleen deficiency that are more suitable for clinical practice， so as to establish a more perfect modeling method and evaluation system of disease syndrome-combined animal model.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.