ObjectiveThe controllability changes of structural brain network were explored based on the control and brain network theory in young smokers, this may reveal that the controllability indicators can serve as a powerful factor to predict the sleep status in young smokers. MethodsFifty young smokers and 51 healthy controls from Inner Mongolia University of Science and Technology were enrolled. Diffusion tensor imaging (DTI) was used to construct structural brain network based on fractional anisotropy (FA) weight matrix. According to the control and brain network theory, the average controllability and the modal controllability were calculated. Two-sample t-test was used to compare the differences between the groups and Pearson correlation analysis to examine the correlation between significant average controllability and modal controllability with Fagerström Test of Nicotine Dependence (FTND) in young smokers. The nodes with the controllability score in the top 10% were selected as the super-controllers. Finally, we used BP neural network to predict the Pittsburgh Sleep Quality Index (PSQI) in young smokers. ResultsThe average controllability of dorsolateral superior frontal gyrus, supplementary motor area, lenticular nucleus putamen, and lenticular nucleus pallidum, and the modal controllability of orbital inferior frontal gyrus, supplementary motor area, gyrus rectus, and posterior cingulate gyrus in the young smokers’ group, were all significantly different from those of the healthy controls group (P<0.05). The average controllability of the right supplementary motor area (SMA.R) in the young smokers group was positively correlated with FTND (r=0.393 0, P=0.004 8), while modal controllability was negatively correlated with FTND (r=-0.330 1, P=0.019 2). ConclusionThe controllability of structural brain network in young smokers is abnormal. which may serve as an indicator to predict sleep condition. It may provide the imaging evidence for evaluating the cognitive function impairment in young smokers.

ObjectiveTo investigate the effects of modified Ditan tang on genes related to the transcription-translation feedback loop （TTFL） of biorhythm in the rat model of non-alcoholic fatty liver disease （NAFLD） and its mechanism for prevention and treatment of NAFLD. MethodsSixty-five healthy SPF male SD rats were randomly assigned into blank （n=20）， model （n=15）， and low-， medium-， and high-dose （2.68， 5.36， and 10.72 g·kg^-1·d^-1， respectively） modified Ditan tang （n=10） groups. Other groups except the blank group were fed a high-fat diet for 12 weeks. The modified Ditan tang groups were treated with the decoction at corresponding doses by gavage， and the blank and model groups were treated with an equal volume of normal saline from the 9th week for 4 weeks. The levels of triglyceride （TG）， total cholesterol （TC）， low-density lipoprotein cholesterol （LDL-C）， high-density lipoprotein cholesterol （HDL-C）， aspartate aminotransferase （AST）， and alanine aminotransferase （ALT） in the serum were measured by an automatic biochemical analyzer. TG and non-esterified fatty acid （NEFA） assay kits were used to measure the levels of TG and NEFA in the liver. The pathological changes in the hypothalamus and liver were observed by hematoxylin-eosin staining， and the lipid deposition in the liver was observed by oil red O staining. The levels of brain-muscle ARNT-like protein 1 （BMAL1/ARNTL） in the hypothalamus and liver were determined by immunohistochemical staining. The mRNA and protein levels of BMAL1， circadian locomotor output cycles kaput （CLOCK）， period circadian clock 2 （PER2）， and cryptochrome1 （Cry1） in the hypothalamus and liver were determined by Real-time PCR and Western blot， respectively. ResultsCompared with the blank group， the model group showed elevated levels of TG， TC， LDL-C， AST， and ALT （P<0.01） and a lowered level of HDL-C （P<0.05） in the serum， elevated levels of TG and NEFA in the liver （P<0.01）， pyknosis and deep staining of hypothalamic neuron cells， and a large number of vacuoles in the brain area. In addition， the model group showed lipid deposition in the liver， up-regulated mRNA and protein levels of CLOCK and BMAL1 （P<0.01）， and down-regulated mRNA and protein levels of Cry1 and PER2 （P<0.01） in the hypothalamus and liver. Compared with the model group， all the three modified Ditan tang groups showed lowered levels of TG， TC， LDL-C， ALT， and AST （P<0.05， P<0.01） and an elevated level of HDL-C （P<0.05） in the serum， and lowered levels of TG and NEFA （P<0.05， P<0.01） in the liver. Furthermore， the three groups showed alleviated pyknosis and deep staining of hypothalamic neuron cells， reduced lipid deposition in the liver， down-regulated mRNA and protein levels of CLOCK and BMAL1 （P<0.05， P<0.01）， and up-regulated mRNA and protein levels of Cry1 and PER2 （P<0.05， P<0.01） in the hypothalamus and liver. ConclusionModified Ditan tang can reduce lipid deposition in the liver and regulate the expression of CLOCK， BMAL1， Cry1， and PER2 in the TTFL of NAFLD rats.

The auxin/indole-3-acetic acid (Aux/IAA) gene family is an important regulator for plant growth hormone signaling, involved in plant growth, development, as well as response to environmental stresses. In the present study, we identified SmIAA7 which is potentially associated with Salvia miltiorrhiza leaf development through comparatively analyzed the transcriptome data from different pinnate leaves. SmIAA7 was successfully isolated from S. miltiorrhiza using the specific primers. Then subsequent bioinformatic analysis, prokaryotic expression and purification, subcellular localization, and induction expression analysis under auxin and abiotic stress were performed. The full-length of SmIAA7 contained an ORF of 684 bp encoding a protein of 227 amino acid with a molecular weight of 25.3 kD. Conserved domain analysis showed that SmIAA7 contains the conserved Aux_IAA domain (pfam02309). Sequence analysis and phylogenetic tree analysis results indicated SmIAA7 was phylogenetically close to IAA7 and IAA14 from other plants, suggesting SmIAA7 involved in plant growth and development as well as response to environmental stresses. The prokaryotic expression vector pET28a-SmIAA7 was constructed and SmIAA7 recombinant protein was successfully expressed in E. coli Rosetta (DE3) strain. Subcellular localization experiment demonstrated that SmIAA7 localized in the nucleus of plant cells. Real-time fluorescence quantitative PCR results showed that the expression level of SmIAA7 was upregulated in response to auxin. Drought, low temperature, and salt stress significantly increased the transcript level of SmIAA7 gene. This study lays a foundation for further elucidating the role of SmIAA7 in leaf development, signal transduction, and stress defense in S. miltiorrhiza.

Lung adenocarcinoma (LUAD) is a global malignancy with significant chemoresistance impacting patient prognosis. The pro-tumorigenic role of hyaluronan-mediated motility receptor (HMMR) in LUAD is recognized. This study was designed to investigate the underlying mechanisms by which HMMR affects chemoresistance in LUAD. Bioinformatics presented the expression patterns of HMMR in LUAD patients and the association between HMMR levels and patient survival, followed by qRT-PCR to verify HMMR expression in LUAD tissues and cells. Further, bioinformatics was leveraged to identify the signaling pathways enriched by HMMR and its relevance to glycolytic genes, we also analyzed changes in the glycolytic activity of LUAD cells by manipulating HMMR expression. Stemness was evaluated through cell aggregation assays and Western blot, and drug responsiveness was gauged using CCK-8 assays, alongside flow cytometry for apoptosis analysis. HMMR was highly expressed in LUAD tissues and cells, and this overexpression correlated with poorer prognoses in patients. GSEA showed that HMMR was notably enriched in the glycolysis and gluconeogenesis pathways, correlating positively with the expression of key glycolytic genes. Cellular experiments confirmed that HMMR knockdown notably suppressed aerobic glycolysis in LUAD cells. Moreover, overexpression of HMMR could further enhance the stemness and cisplatin resistance of LUAD cells by stimulating glycolysis. In brief, this study has validated that high levels of HMMR in LUAD are predictive of poor patient prognosis, and that overexpression of HMMR can catalyze aerobic glycolysis, thus promoting stemness and chemoresistance in LUAD cells. Thus, HMMR could be a target for improving chemosensitivity in LUAD.

Lung adenocarcinoma (LUAD) is a global malignancy with significant chemoresistance impacting patient prognosis. The pro-tumorigenic role of hyaluronan-mediated motility receptor (HMMR) in LUAD is recognized. This study was designed to investigate the underlying mechanisms by which HMMR affects chemoresistance in LUAD. Bioinformatics presented the expression patterns of HMMR in LUAD patients and the association between HMMR levels and patient survival, followed by qRT-PCR to verify HMMR expression in LUAD tissues and cells. Further, bioinformatics was leveraged to identify the signaling pathways enriched by HMMR and its relevance to glycolytic genes, we also analyzed changes in the glycolytic activity of LUAD cells by manipulating HMMR expression. Stemness was evaluated through cell aggregation assays and Western blot, and drug responsiveness was gauged using CCK-8 assays, alongside flow cytometry for apoptosis analysis. HMMR was highly expressed in LUAD tissues and cells, and this overexpression correlated with poorer prognoses in patients. GSEA showed that HMMR was notably enriched in the glycolysis and gluconeogenesis pathways, correlating positively with the expression of key glycolytic genes. Cellular experiments confirmed that HMMR knockdown notably suppressed aerobic glycolysis in LUAD cells. Moreover, overexpression of HMMR could further enhance the stemness and cisplatin resistance of LUAD cells by stimulating glycolysis. In brief, this study has validated that high levels of HMMR in LUAD are predictive of poor patient prognosis, and that overexpression of HMMR can catalyze aerobic glycolysis, thus promoting stemness and chemoresistance in LUAD cells. Thus, HMMR could be a target for improving chemosensitivity in LUAD.

Lung adenocarcinoma (LUAD) is a global malignancy with significant chemoresistance impacting patient prognosis. The pro-tumorigenic role of hyaluronan-mediated motility receptor (HMMR) in LUAD is recognized. This study was designed to investigate the underlying mechanisms by which HMMR affects chemoresistance in LUAD. Bioinformatics presented the expression patterns of HMMR in LUAD patients and the association between HMMR levels and patient survival, followed by qRT-PCR to verify HMMR expression in LUAD tissues and cells. Further, bioinformatics was leveraged to identify the signaling pathways enriched by HMMR and its relevance to glycolytic genes, we also analyzed changes in the glycolytic activity of LUAD cells by manipulating HMMR expression. Stemness was evaluated through cell aggregation assays and Western blot, and drug responsiveness was gauged using CCK-8 assays, alongside flow cytometry for apoptosis analysis. HMMR was highly expressed in LUAD tissues and cells, and this overexpression correlated with poorer prognoses in patients. GSEA showed that HMMR was notably enriched in the glycolysis and gluconeogenesis pathways, correlating positively with the expression of key glycolytic genes. Cellular experiments confirmed that HMMR knockdown notably suppressed aerobic glycolysis in LUAD cells. Moreover, overexpression of HMMR could further enhance the stemness and cisplatin resistance of LUAD cells by stimulating glycolysis. In brief, this study has validated that high levels of HMMR in LUAD are predictive of poor patient prognosis, and that overexpression of HMMR can catalyze aerobic glycolysis, thus promoting stemness and chemoresistance in LUAD cells. Thus, HMMR could be a target for improving chemosensitivity in LUAD.

Lung adenocarcinoma (LUAD) is a global malignancy with significant chemoresistance impacting patient prognosis. The pro-tumorigenic role of hyaluronan-mediated motility receptor (HMMR) in LUAD is recognized. This study was designed to investigate the underlying mechanisms by which HMMR affects chemoresistance in LUAD. Bioinformatics presented the expression patterns of HMMR in LUAD patients and the association between HMMR levels and patient survival, followed by qRT-PCR to verify HMMR expression in LUAD tissues and cells. Further, bioinformatics was leveraged to identify the signaling pathways enriched by HMMR and its relevance to glycolytic genes, we also analyzed changes in the glycolytic activity of LUAD cells by manipulating HMMR expression. Stemness was evaluated through cell aggregation assays and Western blot, and drug responsiveness was gauged using CCK-8 assays, alongside flow cytometry for apoptosis analysis. HMMR was highly expressed in LUAD tissues and cells, and this overexpression correlated with poorer prognoses in patients. GSEA showed that HMMR was notably enriched in the glycolysis and gluconeogenesis pathways, correlating positively with the expression of key glycolytic genes. Cellular experiments confirmed that HMMR knockdown notably suppressed aerobic glycolysis in LUAD cells. Moreover, overexpression of HMMR could further enhance the stemness and cisplatin resistance of LUAD cells by stimulating glycolysis. In brief, this study has validated that high levels of HMMR in LUAD are predictive of poor patient prognosis, and that overexpression of HMMR can catalyze aerobic glycolysis, thus promoting stemness and chemoresistance in LUAD cells. Thus, HMMR could be a target for improving chemosensitivity in LUAD.

Lung adenocarcinoma (LUAD) is a global malignancy with significant chemoresistance impacting patient prognosis. The pro-tumorigenic role of hyaluronan-mediated motility receptor (HMMR) in LUAD is recognized. This study was designed to investigate the underlying mechanisms by which HMMR affects chemoresistance in LUAD. Bioinformatics presented the expression patterns of HMMR in LUAD patients and the association between HMMR levels and patient survival, followed by qRT-PCR to verify HMMR expression in LUAD tissues and cells. Further, bioinformatics was leveraged to identify the signaling pathways enriched by HMMR and its relevance to glycolytic genes, we also analyzed changes in the glycolytic activity of LUAD cells by manipulating HMMR expression. Stemness was evaluated through cell aggregation assays and Western blot, and drug responsiveness was gauged using CCK-8 assays, alongside flow cytometry for apoptosis analysis. HMMR was highly expressed in LUAD tissues and cells, and this overexpression correlated with poorer prognoses in patients. GSEA showed that HMMR was notably enriched in the glycolysis and gluconeogenesis pathways, correlating positively with the expression of key glycolytic genes. Cellular experiments confirmed that HMMR knockdown notably suppressed aerobic glycolysis in LUAD cells. Moreover, overexpression of HMMR could further enhance the stemness and cisplatin resistance of LUAD cells by stimulating glycolysis. In brief, this study has validated that high levels of HMMR in LUAD are predictive of poor patient prognosis, and that overexpression of HMMR can catalyze aerobic glycolysis, thus promoting stemness and chemoresistance in LUAD cells. Thus, HMMR could be a target for improving chemosensitivity in LUAD.

In the context of exploring the specialization of medical social work， this paper explored the current situation， problems， and future development directions of medical social work supervision based on the perspective of four basic systems of social work practice. It has ethical significance and professional value for improving the professional ability and service quality of medical social workers. Currently， medical social work supervision is developing at a slow pace， while its overall construction remains behind. Taking the Beijing municipal medical social work supervision project as a case study， from the specific to the general， it was found that there were practical dilemmas in medical social work supervision， such as the lack of system， standards， and talents. Based on these， suggestions for improvement were proposed by focusing on the change of promoter system， action system， and goal system.

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.