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.

OBJECTIVE To explore the mechanism of Huayu jiedu formula in regulating inflammatory injury in chronic kidney disease （CKD）. METHODS Fifty male SD rats were randomly divided into a sham surgery group （10 rats） and a modeling group （40 rats）. The CKD model was replicated in the modeling group by unilateral ureteral obstruction surgery. After successful modeling， the rats were randomly divided into model group， esaxerenone group （positive control）， and TCM low- and high-dose groups， with 10 rats in each group. The Esaxerenone group was given 1 mg/kg of esaxerenone， while the TCM low- and high-dose groups were given 13.7 and 27.4 g/kg of Huayu jiedu formula respectively， the sham surgery group and model group were given an equal volume of physiological saline， all groups were intervened continuously for 14 days. Hematoxylin eosin and Masson staining were used to observe the pathological changes in rat kidney tissue. Conventional biochemical methods were used to detect serum urea （SUr）， serum creatinine （SCr）， malondialdehyde （MDA）， and superoxide dismutase （SOD） levels； enzyme-linked immunosorbent assay was used to detect the levels of serum interleukin-1β （IL-1β）， IL-6， and tumor necrosis factor-α（TNF-α）； immunohistochemistry and Western blot were used to detect the protein expression of peroxisome proliferator-activated receptor γ coactivator-1α（PGC-1α） ， mitochondrial transcription factor A （TFAM）， absent in melanoma 2（AIM2）， caspase-1， gasdermin D （GSDMD）， IL-1β and IL-18 in renal tissue； real-time fluorescence quantitative PCR was used to detect the mRNA expression of AIM2. RESULTS Compared with the sham surgery group， the renal tissue of the model group showed pathological changes such as glomerular deformation and destruction， severe tubular dilation， and increased deposition of blue fibrin； the levels of SUr， SCr， MDA， IL-1β， IL-6， TNF-α，the protein expression of AIM2， GSDMD， caspase-1， IL-1β， IL-18 ， and the mRNA expression of AIM2 were significantly increased or up-regulated （P＜0.01）； the levels of SOD， the protein expression of PGC-1α， TFAM were significantly reduced or down-regulated （P＜0.01）. Compared with the model group， all treatment groups showed improvement in the above symptoms and most indicators in rats. CONCLUSIONS Huayu jiedu formula may improve renal function， alleviate renal inflammatory damage and pyroptosis， and exert renal protective effects by regulating the AIM2 pyroptosis pathway.

Objective To investigate the knowledge-attitude-practice(KAP)of drug application among university students in Karamay,to analyze potential risk factors of medication risk.Methods Using the convenience sampling method,the basic information,current status of the KAP of medication of university students in Karamay were collected through online and offline questionnaire.Multiple linear regression was performed to analyze the influence of different characteristics of the research objects on KAP concerning medication risk.Results A total of 948 valid questionnaires were retrieved,the interviewees were mostly aged between 18 and 20 years old(55.06％),females(63.92％)were more than males(36.08％).The mean scores of knowledge,behavior,education and attitude towards medication among university students were(36.17±11.82),(31.04±9.17),(11.66±4.66)and(11.50±3.53)respectively.Most university students had good drug use habits and considered it necessary to acquire knowledge about safe drug use through different ways and forms,but they lacked awareness on safe drug use in terms of purchasing drugs,storing drugs,drug use behavior and drug use education.Multiple linear regression analysis showed that the major of study was an influential factor in medication knowledge(P＜0.01),with pharmacy majors demonstrating better mastery.It also in medication behavior(P＜0.01),with pharmacy majors exhibiting more standardized practices.Gender was an influential factor in attitudes toward medication education(P＜0.05),with females showing more positive attitude.Conclusion The knowledge of drug application among university students in the city is relatively good,and they have good medication habits.However,there are shortcomings in their medication behavior and education.It is necessary to actively carry out targeted medication education activities to promote safe and rational medication among university students.

OBJECTIVE To evaluate the mechanisms underlying the antidepressant effect of ZBH2012001,a novel serotonin and norepinephrine reuptake inhibitor(SNRI),in general and its ability to enhance monoaminergic transmission and suppress neuroinflammation in particular.METHODS① Male ICR mice were divided into vehicle(distilled water),duloxetine(DLX,10 or 20 mg·kg-1)and ZBH2012001(5,10 and 20 mg·kg-1)groups.One hour following ig administration,the antidepressant effect of ZBH2012001 was evaluated using the tail suspension test(TST)and forced swimming test(FST).② Radioligand binding assay was conducted to evaluate the affinity of ZBH2012001 for human serotonin transporters(hSERTs)and human norepinephrine transporters(hNETs).③ Mice were divided into vehicle(distilled water),DLX(10 or 20 mg·kg-1)and ZBH2012001(5,10 and 20 mg·kg-1)groups.One hour following drug administration,the 5-hydroxytryptophan(5-HTP)-induced head-twitch test or yohimbine-induced lethality test were performed to evaluate the effect of ZBH2012001 on the function of the 5-hydroxytryptamine(5-HT)and norepinephrine(NE)systems.④ Mice were divided into vehicle(distilled water+0.1%acetic acid),reserpine model(distilled water+reserpine 5 mg·kg-1),DLX(DLX 20 mg·kg-1+reserpine 5 mg·kg-1)and ZBH2012001(ZBH2012001 5,10 and 20 mg·kg-1+reserpine 5 mg·kg-1)groups.One hour following drug administration,reserpine was injected intraperitoneally to establish a monoamine-depletion model.The ptosis,akinesia,and hypothermia assays were performed to evaluate the effect of ZBH2012001 on the down-regulation of the reserpine-induced monoamine system.The TST in mice was used to evaluate the effect of ZBH2012001 on reserpine-induced depressive-like behavior while high-performance liquid chromatography with electrochemical detection(HPLC-ECD)was used to measure the levels of monoamines and their metabolites in the hippocampal tissue of reserpine-induced monoamine-depletion mice.ELISA was employed to detect the contents of tumor necrosis factor-alpha(TNF-α)and interleukin-6(IL-6)in the hippocampal tissue of reserpine-induced monoamine-depletion mice.Western blotting was used to assess the expressions of ionized calcium-binding adapter molecule-1(Iba-1)and nuclear factor-kappa B(NF-κB)in the hippocampal tissue of reserpine-induced monoamine-depletion mice.RESULTS ① Compared with the vehicle group,ZBH2012001(5,10 and 20 mg·kg-1)significantly reduced the immobility time both in the TST in mice(P<0.01,respectively),and ZBH2012001(20 mg·kg-1)and in the FST in mice(P<0.05).② ZBH2012001 competitively inhibited the binding of[3H]-imipramine to hSERTs and[3H]-nisoxetine to hNETs,with the half maximal inhibitory concentration(IC50)values of 84.95 and 712.90 nmol·L-1,respectively.③Com-pared with the vehicle group,ZBH2012001(10 and 20 mg·kg-1)significantly increased the head twitches induced by 5-HTP in mice(P<0.01,respectively)and increased the mortality rate in mice induced by yohimbine(P<0.05,P<0.01).④ In the reserpine-induced monoamine-depletion model in mice,compared with the vehicle group,mice in the reserpine model group exhibited ptosis,akinesia and hypothermia feature(P<0.01,respectively),significantly prolonged immobility time in the TST(P<0.01),significantly decreased the levels of NE,5-HT and dopamine(DA)(P<0.05,P<0.01),significantly increased the metabolic conversion rate of 5-HT and DA(P<0.01,respectively),significantly elevated levels of TNF-α and IL-6(P<0.05,respectively),and significantly increased expressions of Iba-1 and NF-κB(P<0.05,respectively)in the hippocampus.Compared with the model group,ZBH2012001(5,10 and 20 mg·kg-1)significantly antagonized ptosis and hypothermia behaviors induced by reserpine(P<0.01,respectively),ZBH2012001(10 and 20 mg·kg-1)significantly shortened the immobility time in reserpine-treated mice(P<0.05,P<0.01),ZBH2012001(20 mg·kg-1)significantly increased the levels of NE and 5-HT in the hippocampus of reserpine-treated mice(P<0.05,respectively),decreased the metabolic conversion rate of 5-HT(P<0.05),significantly reduced the contents of TNF-α and IL-6 in the hippocampus of reserpine-treated mice(P<0.05,respectively),ZBH2012001(5,10 and 20 mg·kg-1)significantly reduced the expression of Iba-1 protein in the hippocampus of reserpine-treated mice(P<0.01,respec-tively),and ZBH2012001(20 mg·kg-1)significantly reduced the expression of NF-κB protein in the hippocampus of reserpine-treated mice(P<0.05).CONCLUSION ZBH2012001 exerts its antidepres-sant effect through a dual mechanism involving monoamine enhancement and inflammation suppres-sion.

Objective To construct an artificial intelligence assisted diagnosis model based on deep learning for dynamically recognizing gastric lesions and their locations under gastroscopy in real time,and to evaluate its ability to detect and recognize gastric lesions and their locations.Methods The gastroscopy videos of 104 patients in our hospital was retrospectively analyzed,and the video frames were manually annotated.The annotated picture frames of lesion category were divided into the training set and the validation set according to the ratio of 8∶2,and the annotated picture frames of location category were divided into the training set and the validation set according to the patient sources at the ratio of 8∶2.These sets were utilized for training and validating the respective models.YoloV4 model was used for the training of lesion recognition,and ResNet152 model was used for the training of location recognition.The accuracy,sensitivity,specificity,positive predictive value,negative predictive value and location recognition accuracy of the auxiliary diagnostic model were evaluated.Results A total of 68 351 image frames were annotated,with 54 872 frames used as the training set,including 41 692 frames for lesion categories and 13 180 frames for location categories.The validation set consisted of 13 479 frames,comprising 10 422 frames for lesion categories and 3 057 frames for location categories.The lesion recognition model achieved an overall accuracy of 98.8%,with a sensitivity of 96.6%,specificity of 99.3%,positive predictive value of 96.3%,and negative predictive value of 99.3% in validation set.Meanwhile,the location recognition model demonstrated an top-5 accuracy of 87.1% .Conclusion The artificial intelligence assisted diagnosis model based on deep learning for real-time dynamic recognition of gastric lesions and their locations under gastroscopy has good ability in lesion detection and location recognition,and has great clinical application prospects.

Clinicians need to focus on various points in the diagnosis and treatment of insomnia.This article prescribed the treatment protocol based on the unique features,such as insomnia in the elderly,women experiencing specific physiologi-cal periods,children insomnia,insomnia in sleep-breathing disorder patients,insomnia in patients with chronic liver and kidney dysfunction.It pro-vides some reference for clinicians while they make decision on diagnosis,differentiation and treat-ment methods.