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.

A high performance liquid chromatography-tandem mass spectrometry(HPLC-MS/MS) method was established for the simultaneous determination of 498 farm chemical residues in Atractylodis Macrocephalae Rhizoma. Furthermore, the established method was used to determine the residues in 30 batches of Atractylodis Macrocephalae Rhizoma samples from different habitats. The samples were extracted with acetonitrile containing 1% glacial acetic acid, and the extract was purified by dispersive solid-phase extraction with sorbents of magnesium sulfate, primary secondary amine(PSA), C_(18), silica gel, and graphitized carbon black(GCB). The prepared samples were then analyzed by HPLC-MS/MS, and the internal standard method was used to quantify the residues. The experimental results showed that the 498 farm chemicals presented good linear relationship within the range of 5-400 ng·mL~(-1), with correction coefficients greater than 0.990. Within the linear ranges, the recovery of 495 farm chemicals(except daimuron, chinomethionat, and emamectin benzoate) at three spiked levels(0.05, 0.10, and 0.20 mg·kg~(-1)) was in the range of 61.18%-132.1%, with the RSD of 0.24%-15%. A total of 16 farm chemicals were detected in 30 batches of samples. Among them, difenoconazole and tebuconazole showed higher detection rates, and the detection rate of difenoconazole was 76.7%. The residues of 4 batches of samples exceeded the limits of quantitation of 33 banned farm chemicals stipulated in the Chinese Pharmacopoeia. The theoretical maximum residue limits of the farm chemicals except banned farm cheimicals were used as the judgment standard of safety risks, under which the detected residues of clothianidin, difenoconazole, and pirimiphos-methyl exceeded the theoretical maximum residue limits. The new method established in this paper is simple and reliable, and it can thus be used for qualitative and quantitative analyses of farm chemical residues in Atractylodis Macrocephalae Rhizoma.
Tandem Mass Spectrometry/methods* ; Chromatography, High Pressure Liquid/methods* ; Atractylodes/chemistry* ; Rhizome/chemistry* ; Drugs, Chinese Herbal/analysis* ; Pesticide Residues/analysis* ; Liquid Chromatography-Mass Spectrometry

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

Inflammatory skin diseases(ISD)are characterized by persistent inflammatory cell infiltration and lingering and intractable skin lesions.At present,corticosteroids are the main drugs used in the treatment of ISD.However,due to the characteristics of recurrent and intractable ISD,long-term use of these hormone drugs may cause serious side effects in patients.In recent years,increasingly more studies are confirming that bee venom has significant anti-inflammatory,anti-apoptosis,anti-fibrosis,antibacterial,and other effects and could effectively treat ISD.In this paper,the main active components and anti-inflammatory mechanisms of bee venom are reviewed.The latest attempts to use bee venom for acne,atopic dermatitis,psoriasis,urticaria,and systemic lupus erythematosus are discussed,providing a reference for basic research and the clinical treatment of ISD.

Objective:To explore whether thiotert treatment can inhibit proliferation and induce apoptosis in myelodysplastic syndromes(MDS)cells.Methods:CCK-8 assay was used for determining the cytotoxicity of thiotert to MDS cell line SKM-1 and the reversal effect of GSH,NAC,and Z-VAD-FMK on thiotert-induced inhibition of cell viability.EdU assay was deployed to detect the cell proliferation ability.Intracellular reactive oxygen species(ROS)was measured by flow cytometry after DCFH-DA staining.The expression of DNA damage-and apoptosis-related proteins was detected by Western blot.Results:Thiotert treatment significantly suppressed the cell viability and proliferation ability in SKM-1 cells.A large amount of ROS generation and markedly elevated C-PARP,C-Caspase 3,and γ-H2AX were observed after thiotert administration,while BCL-2 was significantly decreased.In addition,GSH,NAC,and Z-VAD-FMK were able to mitigate the cytotoxicity of thiotert on SKM-1 cells.Conclusion:Thiotert can promote MDS cell apoptosis by mediating ROS production and pro-apoptotic proteins expression.