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.

This article investigated the effect and mechanism of salidroside(SAL) on the expression of adhesion molecules in oxidized low-density lipoprotein(oxLDL)-induced mouse aortic endothelial cell(MAEC). The oxLDL-induced endothelial cell injury model was constructed, and the safe concentration and action time of SAL were screened. The cells were divided into control group, oxLDL group, low and high concentration groups of SAL, and ferrostatin-1(Fer-1) group. The cell viability was detected by CCK-8 assay; lactate dehydrogenase(LDH) leakage was measured by colorimetry; the expression of intercellular adhesion molecule 1(ICAM-1) and recombinant vascular cell adhesion molecule 1(VCAM-1) were detected by immunofluorescence; Fe~(2+),glutathione(GSH),malondialdehyde(MDA),and 4-hydroxynonenal(4-HNE) levels were detected by kit method; reactive oxygen species(ROS) was detected by DCFH-DA probe; the levels of glutathione peroxidase 4(GPX4),silent mating type information regulation 2 homolog 1(SIRT1), and nuclear factor erythroid 2-related factor 2(Nrf2) were determined by using Western blot. The inhibitors of Nrf2 and SIRT1 were used, and endothelial cell were divided into control group, oxLDL group, SAL group, ML385 group(Nrf2 inhibitor), and EX527 group(SIRT1 inhibitor). The ultrastructure of mitochondria was observed by electron microscope; mitochondrial membrane potential(MMP) was detected by flowcytometry; the expressions of SIRT1,Nrf2,solute carrier family 7 member 11(SLC7A11),GPX4,ferroportin 1(FPN1),ferritin heavy chain 1(FTH1),ICAM-1, and VCAM-1 were detected by Western blot. The results showed that similar to Fer-1,low and high concentrations of SAL could improve cell viability, inhibit LDH release and the expression of ICAM-1 and VCAM-1 in oxLDL-induced endothelial cells(P<0.05 or P<0.01). It was related to increase in GSH level, decrease in Fe~(2+),ROS,MDA, and 4-HNE level, and up-regulation of SIRT1,Nrf2, and GPX4 expression to inhibit ferroptosis(P<0.05 or P<0.01). The intervention effect of high concentration SAL was the most significant. ML385 and EX527 could partially offset the protection of SAL on mitochondrial structure and MMP and reverse the ability of SAL to up-regulate the expression of SIRT1,Nrf2,SLC7A11,GPX4,FPN1, and FTH1 and down-regulate the expression of ICAM-1 and VCAM-1(P<0.05 or P<0.01).To sum up, SAL could reduce the expression of ICAM-1 and VCAM-1 in oxLDL-induced endothelial cell, which may relate to activation of SLC7A11/GPX4 antioxidant signaling pathway mediated by SITR1/Nrf2, up-regulation of FPN1 and FTH1 expression, and inhibition of ferroptosis.
Sirtuin 1/genetics* ; Animals ; Ferroptosis/drug effects* ; Lipoproteins, LDL/metabolism* ; NF-E2-Related Factor 2/genetics* ; Mice ; Endothelial Cells/cytology* ; Glucosides/pharmacology* ; Phenols/pharmacology* ; Cell Adhesion Molecules/genetics* ; Reactive Oxygen Species/metabolism* ; Intercellular Adhesion Molecule-1/genetics* ; Vascular Cell Adhesion Molecule-1/genetics* ; Cell Survival/drug effects*

Instrument separation is a critical complication during root canal therapy, impacting treatment success and long-term tooth preservation. The etiology of instrument separation is multifactorial, involving the intricate anatomy of the root canal system, instrument-related factors, and instrumentation techniques. Instrument separation can hinder thorough cleaning, shaping, and obturation of the root canal, posing challenges to successful treatment outcomes. Although retrieval of separated instrument is often feasible, it carries risks including perforation, excessive removal of tooth structure and root fractures. Effective management of separated instruments requires a comprehensive understanding of the contributing factors, meticulous preoperative assessment, and precise evaluation of the retrieval difficulty. The application of appropriate retrieval techniques is essential to minimize complications and optimize clinical outcomes. The current manuscript provides a framework for understanding the causes, risk factors, and clinical management principles of instrument separation. By integrating effective strategies, endodontists can enhance decision-making, improve endodontic treatment success and ensure the preservation of natural dentition.
Humans ; Root Canal Therapy/adverse effects* ; Consensus ; Root Canal Preparation/adverse effects*

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.

ObjectiveMicrotube associated protein-2 （MAP-2）， alpha-tubulin （α-tubulin）， and synaptophysin （SYP） are important proteins in neuronal signal communication. This paper observed the effects of modified Zhigancao Tang on the expression of serum α-Synuclein （α-Syn） and its oligomers， MAP-2， α-tubulin， and SYP of patients with liver and kidney deficiency of Parkinson's disease （PD）， analyzed their correlation， and evaluated the therapeutic effect of modified Zhigancao Tang in patients with liver and kidney deficiency of PD based on α-Syn transmission pathway mediated by neuronal communication in vivo. MethodsA total of 60 patients with PD who met the inclusion criteria were randomly divided into a treatment group （30 cases） and a control group （30 cases）. Both groups were treated on the basis of PD medicine， and the treatment group was treated with modified Zhigancao Tang. Both groups were treated for 12 weeks. The changes in UPDRS score， TCM syndrome score， and expression of serum α-Syn and its oligomers， MAP-2， α-tubulin， and SYP were observed before and after 12 weeks of treatment in each group. The correlation between the above-mentioned serum biological indexes and the levels of serum α-Syn and its oligomers was analyzed. ResultsAfter treatment， the TCM syndrome score， UPDRS score， UPDRS-Ⅱ score， and UPDRS-Ⅲ score of the treatment group were significantly decreased （P<0.05， P<0.01）. The UPDRS score， UPDRS-Ⅱ score， and UPDRS-Ⅲ scores in the treatment group were significantly decreased compared with those in the control group after treatment （P<0.05）. After treatment， the total effective rate of the control group was 63.3% （19/30）， and that of the treatment group was 86.7% （26/30）. The clinical effect of the observation group was better than the control group （Z=-2.03， P<0.05）. The total effective rate of the observation group was better than that of the control group， and the difference was statistically significant （χ²=5.136， P<0.05）. After treatment， the oligomer level of serum α-Syn and MAP-2 level in the treatment group were significantly decreased （P<0.05， P<0.01）. The levels of serum α-Syn and its oligomers， as well as α-tubulin in the treatment group， were significantly decreased compared with those in the control group after treatment （P<0.05， P<0.01）. Serum α-Syn was correlated with serum MAP-2 and α-Syn oligomer in patients with PD （P<0.05， P<0.01） but not correlated with serum SYP . Serum α-Syn oligomers of patients with PD were correlated with serum MAP-2 and α-tubulin （P<0.05， P<0.01） but not correlated with serum SYP level. Serum SYP of patients with PD was correlated with serum MAP-2 （P<0.05）. ConclusionModified Zhigancao Tang has a therapeutic effect on patients with liver and kidney deficiency of PD by inhibiting the production of α-Syn oligomers and intervening α-Syn microtubule transport pathway in vivo.

Objective: To investigate the effects of Zuogui Jiangtang Jieyu Formula (ZGJTJYF) on histone H3 lysine 18 lactylation (H3K18la) in the hippocampus of rats with diabetes mellitus complicated with depression (DD) and predict the regulatory genes of H3K18la. Methods: Male Sprague-Dawley rats were divided into control, model, and positive drug (metformin [0.18 g/kg] and fluoxetine [1.8 mg/kg]) groups, and the three groups were treated with high, medium, and low ZGJTJYF doses (20.52, 10.26, and 5.13 g/kg, respectively), with 10 rats per group. After treatment, the forced swimming and water maze tests were performed to assess depressive-like behaviors and cognitive function. An enzyme-linked immunosorbent assay was used to measure blood insulin, glycosylated hemoglobin, lactate levels, and lactate content in the hippocampus. Western blotting was used to detect H3K18la expression in the hippocampus. Cleavage Under Targets and lagmentation(CUT&Tag) experiments targeted hippocampal H3K18la epigenetic modification regions to analyze the transcription factors bound by H3K18la. Kyoto Encyclopedia of Genes and Genomes and Protein-Protein Interaction networks were constructed to identify key pathways and target genes regulated by H3K18la. Results: Compared with the normal group, the model group rats showed prolonged immobility time in the forced swim test, increased escape latency in the water maze experiment, decreased target quadrant distance ratio (P<0.01), increased serum lactate content, and decreased lactate content in hippocampal homogenate (P<0.01), as well as decreased H3K18la protein expression in the hippocampus (P<0.01). Compared with the model group, ZGJTJYF reduced the immobility time in the forced swim test and the escape latency in the water maze test (P<0.01), while the distance ratio in the target quadrant increased (P<0.01) in model rats. Lowered fasting blood glucose, insulin, and glycosylated hemoglobin levels (P<0.05, P<0.01) were also observed. ZGJTJYF also increased the lactate content and H3K18la protein expression in hippocampal homogenate (P<0.05, P<0.01). The DNA sequences bound by H3K18la were predominantly enriched at the transcription start sites. ZGJTJYF modulated H3K18la-associated pathways, including cell adhesion junctions, tumor growth factor-beta (TGF-β) signaling, stem cell pluripotency regulation, mitogen-activated protein kinase(MAPK) signaling pathway, and insulin resistance, leading to the identification of 12 target genes. Conclusion ZGJTJYF enhances hippocampal lactate levels and H3K18la modification in DD rats, which may regulate neural cell interactions, neurogenic stem cell function, TGF-β signaling, MAPK signaling, and insulin resistance pathways.