ObjectiveTo study the pharmacological substances and mechanisms through which sesquiterpene ZH-13 from Aquilariae Lignum Resinatum improves neuroinflammation. MethodsBV-2 microglial cells were stimulated with lipopolysaccharide （LPS） to induce neuroinflammation. The cells were divided into the normal group， the model group， and the ZH-13 low- and high-dose treatment groups （10， 20 μmol·L^-1）. The model group was treated with 1 μmol·L^-1 LPS. Cell viability was assessed using the cell proliferation and activity assay （CCK-8 kit）. Nitric oxide （NO） release in the cell supernatant was measured using a nitric oxide kit （Griess method）. The mRNA expression levels of interleukin-1β （IL-1β）， tumor necrosis factor-α （TNF-α）， inducible nitric oxide synthase （iNOS）， and interleukin-6 （IL-6） were detected by real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）. The phosphorylation of mitogen-activated protein kinase （MAPK） pathway proteins was assessed by Western blot. ResultsCompared with the model group， ZH-13 dose-dependently reduced NO release from BV-2 cells under LPS stimulation （P<0.05， P<0.01）. In the 20 μmol·L^-1 ZH-13 treatment group， the mRNA expression levels of IL-1β， TNF-α， iNOS， and IL-6 were significantly reduced compared to the model group （P<0.05， P<0.01）. In both the low- and high-dose ZH-13 groups， the expression of the inflammatory factor TNF-α and the phosphorylation of c-Jun N-terminal kinase （JNK） in the upstream MAPK pathway were significantly reduced （P<0.05）. After stimulation with the JNK agonist anisomycin （Ani）， both low- and high-dose ZH-13 treatment groups showed reduced phosphorylation of JNK proteins compared to the Ani-treated group （P<0.01）. ConclusionThe sesquiterpene compound ZH-13 from Aquilariae Lignum Resinatum significantly ameliorates LPS-induced neuroinflammatory responses in BV-2 cells by inhibiting excessive JNK phosphorylation and reducing TNF-α expression. These findings elucidate the pharmacological substances and mechanisms underlying the sedative and calming effects of Aquilariae Lignum Resinatum.

Objective To analyze the structural and phylogenetic characteristics of the mitochondrial genome from Bulinus globosus, so as to provide a theoretical basis for classification and identification of species within the Bulinus genus, and to provide insights into understanding of Bulinus-schistosomes interactions and the mechanisms of parasite transmission. Methods B. globosus samples were collected from the Ruya River basin in Zimbabwe. Mitochondrial DNA was extracted from B. globosus samples and the corresponding libraries were constructed for high-throughput sequencing on the Illumina NovaSeq 6000 platform. After raw sequencing data were subjected to quality control using the fastp software, genome assembly was performed using the A5-miseq and SPAdes tools, and genome annotation was conducted using the MITOS online server. Circular maps and sequence plots of the mitochondrial genome were generated using the CGView and OGDRAW software, and the protein conservation motifs and structures were analyzed using the TBtools software. Base composition and codon usage bias were analyzed and visualized using the software MEGA X and the ggplot2 package in the R software. In addition, a phylogenetic tree was created in the software MEGA X after sequence alignment with the software MAFFT 7, and visualized using the software iTOL. Results The mitochondrial genome of B. globosus was a 13 730 bp double-stranded circular molecule, containing 2 ribosomal RNA (rRNA) genes, 22 transfer RNA (tRNA) genes, and 13 protein-coding genes, with a marked AT preference. The mitochondrial genome composition of B. globosus was similar to that of other species within the Bulinus genus. Phylogenetic analysis revealed that the complete mitochondrial genome sequence of B. globosus was clustered with B. truncatus, B. nasutus, and B. ugandae into the same evolutionary clade, and gene superfamily analysis showed that the metabolism-related proteins of B. globosus were highly conserved, notably the cytochrome c oxidase family, which showed a significant consistency. Conclusions This is the first whole mitochondrial genome sequencing to decode the compositional features of the mitochondrial genome of B. globosus from Zimbabwe and its evolutionary relationship within the Bulinus genus, which provides important insights for further understanding of the phylogeny and mitochondrial genome characteristics of the Bulinus genus.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

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.

Objective To investigate the role of long non-coding RNA(lnc RNA)ZFAS1 in glioma cells'sensitivity to cisplatin and its underlying mechanisms.Methods By analyzing the knockdown of ZFAS1 on the sensitivity of glioma cells to cisplatin using real-time fluorescence quantitative polymerase chain reaction(qRT-PCR)experiments,and the cells were divided into sh-NC group(transfected with sh-NC lentiviral plasmid),sh#1 group(transfected with sh-ZFAS1-1 lentiviral plasmid)and sh#2 group(transfected with sh-ZFAS1-2 lentiviral plasmid).Dual luciferase experiments verified the interaction between ZFAS1 and miR-193b-3p,and the cells were divided into ZFAS1-WT+NC inhibitor group(transfected with ZFAS1 wild-type plasmid and NC inhibitor),ZFAS1-WT+miR-193b-3p inhibitor group(transfected with ZFAS1 wild-type plasmid and miR-193b-3p inhibitor),ZFAS1-Mut+NC inhibitor group(transfected with ZFAS1 mutant plasmid and NC inhibitor)and ZFAS1-Mut+miR-193b-3p inhibitor group(transfected with ZFAS1 mutant plasmid and miR-193b-3p inhibitor).Cell counting kit-8(CCK-8)and terminal deoxynucleotidly transferase mediated labeling(TUNEL)experiments were used to analyze the effect of ZFAS1/miR-193b-3p on the sensitivity of glioma cells to cisplatin,and the cells were divided into blank control group(0 μg·mL-1 cisplatin treatment of U251 cells),0.5 μg·mL-1 cisplatin+sh-NC+NC inhibitor group(0.5 μg·mL-1 cisplatin treatment of U251 cells co-transfected with sh-NC lentiviral plasmid and NC inhibitor),0.5 μg·mL-1 cisplatin+sh#1+NC inhibitor group(0.5 μg·mL-1cisplatin treatment of U251 cells co-transfected with sh-NC lentiviral plasmid and NC inhibitor),and 0.5 μg·mL-1 cisplatin+sh#1+miR-193b-3p inhibitor group(0.5 μg·mL-1 cisplatin treatment of U251 cells co-transfected with sh-ZFAS1-1 lentiviral plasmid and miR-193b-3p inhibitor).Results The results of the experiment showed that the expression levels of ZFAS1 in the sh-NC group,sh#1 group and sh#2 group were 1.00±0.17,0.48±0.06 and 0.68±0.08.The fluorescence activities of ZFAS 1-WT+NC inhibitor group,ZFAS1-WT+miR-193b-3p inhibitor group,ZFAS1-Mut+NC inhibitor group and ZFAS1-Mut+miR-193b-3p inhibitor group were 1.00±0.10,1.45±0.11,1.02±0.09 and 0.97±0.13.The proliferation rates at 72 h for the blank control group,0.5 μg·mL-1 cisplatin+sh-NC+NC inhibitor group,0.5 μg·mL-1 cisplatin+sh#1+NC inhibitor group and 0.5 μg·mL-1cisplatin+sh# 1+miR-193b-3p inhibitor group were(100.00±14.13)％,(96.62±9.82)％,(60.56±6.08)％and(78.64±7.22)％;while the apoptosis rates at 72 h were(9.52±1.11)％,(10.12±1.34)％,(16.08±1.52)％and(12.22±1.19)％.Comparied between blank control group and 0.5 μg·mL-1 cisplatin+sh-NC+NC inhibitor group,0.5 μg·mL-1 cisplatin+sh#1+NC inhibitor group and 0.5 μg·mL-1 cisplatin+sh # 1+miR-193b-3p inhibitor group,the differences were statistically significant(all P＜0.05).Conclusion This study reveals the important role of ZFAS1 in cisplatin sensitivity in glioma and elucidates its mechanism of influencing drug sensitivity through the regulation of miR-193b-3p.

The syndrome/pattern of defensive qi deficiency is a common basic syndrome of traditional Chinese medicine in clinical practice. However,there is a lack of standardized and operable diagnostic specifications in practical applications. Based on the previous literature,this study proposed the idea of starting from the elements of the syndrome,qualitative diagnostic criteria for the syndrome/pattern of defensive qi deficiency oriented to the entire region of the disease were constructed based on the two dimensions of " deficient defensive qi failing to consolidate the exterior" and " qi deficiency" and constructing a set of quantitative evaluation criteria as the supporting content for the diagnostic items. The core members of the research group attempted to formulate the draft standard,then reached a consensus through the Delphi method expert questionnaire consultation and the Nominal group technique,and finally evaluated the reliability and validity of the standard through clinical verification to provide ideas for the standardization and normalization of research on syndromes.