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*

This paper applied gas chromatography-mass spectrometry (GC-MS), network pharmacology and nuclear magnetic resonance hydrogen spectroscopy (¹H NMR) metabolomics techniques to study the material basis and mechanism of action of Ning Shen Essential Oil in anti-insomnia. The main volatile components of Ning Shen Essential Oil were analyzed by gas chromatography-mass spectrometry (GC-MS), and the insomnia-related targets were predicted using the Traditional Chinese Medicine Systematic Pharmacology Database and Analytical Platform (TCMSP) and the databases of GeneCards, OMIM and Drugbank. The insomnia model of rats was replicated by intraperitoneal injection of 4-chloro-DL-phenylalanine (PCPA). Animal experiments were approved by the Animal Ethics Committee of Shandong University of Traditional Chinese Medicine (Ethics No.: SDUTCM20221025010). The modulating effect of Compound Ning Shen Essential Oil on anxiety behavior of rats was evaluated by behavioral related indexes. The serum levels of corticotropin-releasing hormone (CRH), adrenotropic corticotropic hormone (ACTH) and melatonin (MT) were measured by enzyme-linked immunoassay (ELISA). Rat serum and hippocampus were taken for nuclear magnetic resonance (¹H NMR) metabolomics to detect the changes of endogenous metabolites in rat serum hippocampus, to designate the differential metabolites and to construct metabolic pathways. The results showed that the exercise distance in the open field experiment and the number of times and time to enter the open arm in the elevated cross maze experiment of the rats in the model group were significantly reduced (P < 0.05, P < 0.01). The behavioral indexes of rats improved to different degrees after the administration of Ning Shen Essential Oil. The serum CRH and ACTH levels of rats in the model group increased significantly (P < 0.05, P < 0.01), and the MT level decreased significantly (P < 0.01); After the intervention, serum CRH and ACTH levels were reduced to different degrees, and MT levels could be regressed. ¹H NMR metabolomics screened 10 potential biomarkers related to insomnia, which involved in 6 potential metabolic pathways. A total of 35 components of Ning Shen Essential Oil were detected by GC-MS, the main component targets of Ning Shen Essential Oil and insomnia disease targets were intersected, a total of 172 intersecting genes were screened, and 26 core targets were identified. The study demonstrated that Ning Shen Essential Oil had protective effects against PCPA-induced insomnia in rats, which was probably correlated with regulation of the hypothalamic-pituitary-adrenal axis (HPA) related hormones and metabolism of amino acids, lipids and choline.

Objective To analyze the literature related to diphenidol tablets poisoning,the characteristics of poisoning were summarized to provide reference for controlling the suicidal abuse risk of diphenidol tablets.Methods The global literature on suicide,overdose,poisoning,shock,and death related to difenidol published from January 1,2011 to December 31,2022 was analyzed,including gender,age,dosage,cardiac(blood)concentration,poisoning symptoms,etc.Results Young women were the majority of people with poisoning.The highest proportion of the age group is 11 to 30 years group.Patients who take medication doses greater than 3 000 mg may have a higher risk of death;patients with a heart(blood)concentration greater than 6 μg·mL-1 may have a higher risk of death.Malignant arrhythmia,consciousness disorders,coma,and apnea are common serious adverse events during poisoning.Conclusion It is recommended that the drug regulatory authorities should require the Listing permit holder of difenidol tablets to add the risk and symptoms of poisoning into the instructions.It is suggested that restricting individual consumers from purchasing large amounts of difenidol tablets in the short term.It is recommended that canceling the high-dose sales packaging of difenidol tablets.It is suggested that converting difenidol tablets into prescription drugs,even consider canceling the registration certificate of difenidol tablets.