PURPOSE: Deep vein thrombosis (DVT) of the left and right lower extremities was treated in the same way, but the left and right extremities received different levels of attention. This study aimed to investigate the differences between the right and left lower extremity deep vein thrombosis (LEDVT). METHODS: Clinical characteristics of LEDVT patients from July 2020 to June 2022 were retrospectively analyzed to compare the incidence of LEDVT on different limbs, demographics, predisposing factors, and anatomical characteristics. The exclusion criteria were bilateral LEDVT and recurrent thrombosis. Measured data was analyzed using independent samples t-test or Mann-Whitney test. Count data were analyzed by Chi-square test. A p < 0.05 was considered a statistically significant difference. RESULTS: There were 478 patients included in this study and the ratio of left to right LEDVT on the left and right limbs was 3.16:1 (363:115). Left LEDVT predominantly affected female, with the major aged > 50 years (50 - 60 years: 16.80%; > 60 years: 57.30%). The primary predisposing factor was iliac vein compression syndrome, with iliofemoral thrombosis being the main type. Male patients with LEDVT on the right limb were predominant and the age of onset was usually ≤ 60 years (52.17%). The main predisposing factor was recent surgery or trauma (< 30 days) and femoropopliteal thrombosis was the main type. In more detail, the left iliac vein was compressed mainly in the proximal segment, and the right iliac vein was compressed mainly in the intermediate and distal segments. Recent surgery or trauma to the locomotor system and genitourinary system often induced LEDVT. CONCLUSION The incidence of LEDVT on the left is significantly higher than that on the right. LEDVT on different sides has different characteristics, which is crucial for prevention and diagnosis in the relevant population so there are also differences in treatment of the affected limbs.
Humans ; Venous Thrombosis/etiology* ; Male ; Female ; Middle Aged ; Lower Extremity/blood supply* ; Retrospective Studies ; Adult ; Aged ; Age Factors ; Sex Factors ; Risk Factors ; Acute Disease ; Incidence ; Aged, 80 and over ; Young Adult ; Adolescent

In this study, ultra-performance liquid chromatography-quadrupole-time-of-flight tandem mass spectrometry(UPLC-Q-TOF-MS~E) was used to analyze the plasma components of Danzhi Xiaoyao Formula after oral administration. Forty-nine plasma components were found in the serum of rats by comparing the compound extract, drug-containing serum, and blank serum. Components, such as 6-hydroxycoumarin, poricoic acid F, deoxoglabrolide, 30-norhederagenin, kanzonol R, 3',6'-di-O-galloylpaeoniflorin, 16α-hydroxytrametenolic acid, 16-deoxyporicoic acid B, 3-O-acetyl-16α-hydroxytrametenolic acid, and 16α,25-dihydroxydehydroeburiconic acid, were first found in rat serum. Behavioral tests, including the tail suspension test, novel object recognition test, and novelty-suppressed feeding test, were conducted for behavioral analysis. It was confirmed that this formula had therapeutic effects on perimenopausal depression. Furthermore, in combination with the network pharmacology method, 53 core targets including MAPK1, HRAS, AKT1, EGFR, and ESR1 were screened, and these targets participated in 165 signaling pathways, including PI3K-AKT, AMPK, VEGFA, MAPK, and HIF-1. In summary, the potential effects of Danzhi Xiaoyao Formula in treating perimenopausal depression are associated with mechanisms in accelerating inflammation repair, improving neuroplasticity, affecting neurotransmitters, regulating estrogen levels, and promoting new blood vessel formation.
Animals ; Rats ; Chromatography, High Pressure Liquid ; Depression/drug therapy* ; Network Pharmacology ; Perimenopause ; Phosphatidylinositol 3-Kinases ; Drugs, Chinese Herbal/pharmacology* ; Molecular Docking Simulation

ObjectiveTo determine the value of MRI blooming sign in differentiating benign and malignant small breast masses and investigate its radiologic-pathologic correlation. MethodsThis retrospective study included 554 small breast masses （291 malignant and 263 benign） which were ≤ 2 cm and validated by pathology analysis between June 2016 and September 2020. All 554 patients underwent breast MRI. The clinical characteristics and MR features were analyzed. Univariate and multivariate regression analysis were performed to identify the independent risk factors of breast cancer. Two diagnostic models were constructed based on independent risk factors （model 1 included blooming sign and model 2 didn’t）. ROC curve was used to evaluate the diagnostic performances of the two models. The histological changes of peritumoral tissues in all small masses were analyzed. ResultsThe blooming sign was positive in 199 cases （68.4%） of the malignant masses and 25 cases （9.5%） of the benign ones （P＜0.05）. Univariate and multivariate regression analysis showed that age， lesion diameter， margin， ADC value， time signal intensity curve type and blooming sign were independent risk factors for breast cancer. Odds ratio were 1.065， 4.515， 2.811， 0.013， 3.487 and 13.894， respectively. Their corresponding 95%CI were （1.034， 1.097）， （2.368， 8.608）， （1.954， 4.045）， （0.004， 0.049）， （2.087， 5.826） and （7.026， 27.477）， respectively. The diagnostic performance of model 1 （blooming sign included） was better than that of model 2 （blooming sign not included； AUC： 0.938 vs 0.897， P < 0.05）. Histopathological analysis showed that the blooming sign was related to peritumoral lymphocyte infiltration and vascular proliferation. ConclusionsMRI blooming sign is helpful for distinguishing breast cancer from benign masses. The correlated histopathological basis may be peritumoral lymphocyte infiltration and neovascularization.

This study aimed to assess the role of prostate-specific antigen density (PSAD) and negative multiparametric magnetic resonance imaging (mpMRI) in predicting prostate cancer for biopsy-naïve men based on a large cohort of the Chinese population. From a prostate biopsy database between March 2017 and July 2021, we retrospectively identified 240 biopsy-naïve patients with negative prebiopsy mpMRI (Prostate Imaging Reporting and Data System version 2 [PI-RADS v2] score <3). Logistic regression analysis was performed to select the potential predictors for clinically significant prostate cancer (csPCa). Receiver operating characteristic (ROC) curve analysis and area under the ROC curve (AUC) were performed to assess the diagnostic accuracy. The negative predictive values of mpMRI in excluding any cancer and csPCa were 83.8% (201/240) and 90.8% (218/240), respectively. ROC curve analysis indicated that PSAD was the most promising predictor, with an AUC value of 0.786 (95% confidence interval [CI]: 0.699-0.874), and multiparametric logistic regression analysis confirmed that higher PSAD remained a significant marker for predicting csPCa (odds ratio [OR]: 10.99, 95% CI: 2.75-44.02, P < 0.001). Combining negative mpMRI and PSAD below 0.20 ng ml^-2 obviously increased the predictive value in excluding PCa (91.0%, 101/111) or csPCa (100.0%, 111/111). If a PSAD below 0.20 ng ml^-2 was set as the criterion to omit biopsy, nearly 46.3% of patients (463 per 1000) with negative mpMRI could safely avoid unnecessary biopsy, with approximately 4.2% of patients (42 per 1000) at risk of missed diagnosis of PCa and no patients with csPCa missed. A PI-RADS v2 score <3 and a PSAD <0.20 ng ml^-2 could be potential criteria for the Chinese population to omit prompt biopsy safely.
Male ; Humans ; Prostatic Neoplasms/pathology* ; Prostate-Specific Antigen ; Multiparametric Magnetic Resonance Imaging ; Magnetic Resonance Imaging/methods* ; Retrospective Studies ; Biopsy ; Image-Guided Biopsy/methods*

Objective: To analyze the prevalence of dry and wet age-related macular degeneration (AMD) in patients with diabetes, hypertension and hyperlipidemia, and to analyze the risk factors for AMD. Methods: A population-based cross-sectional epidemiologic study was conducted involving 14,440 individuals. We assessed the prevalence of dry and wet AMD in diabetic and non-diabetic subjects and analyzed the risk factors for AMD. Results: The prevalence of wet AMD in diabetic and non-diabetic patients was 0.3% and 0.5%, respectively, and the prevalence of dry AMD was 17% and 16.4%, respectively. The prevalence of wet AMD in healthy, hypertensive, hyperlipidemic, and hypertensive/hyperlipidemic populations was 0.5%, 0.3%, 0.2%, and 0.7%, respectively. The prevalence of dry AMD in healthy, hypertensive, hyperlipidemic, and hypertensive/hyperlipidemic populations was 16.6%, 16.2%, 15.2%, and 17.2%, respectively. Age, sex, body mass index, and use of hypoglycemic drugs or lowering blood pressure drugs were corrected in the risk factor analysis of AMD. Diabetes, diabetes/hypertension, diabetes/hyperlipidemia, and diabetes/hypertension/hyperlipidemia were analyzed. None of the factors analyzed in the current study increased the risk for the onset of AMD. Conclusion There was no significant difference in the prevalence of wet and dry AMD among diabetic and non-diabetic subjects. Similarly, there was no significant difference in the prevalence of wet and dry AMD among subjects with hypertension and hyperlipidemia. Diabetes co-existing with hypertension and hyperlipidemia were not shown to be risk factors for the onset of dry AMD.
Cross-Sectional Studies ; Diabetes Mellitus/epidemiology* ; Humans ; Hyperlipidemias/epidemiology* ; Hypertension/epidemiology* ; Macular Degeneration/etiology* ; Risk Factors

Dendritic cells (DCs), a type of antigen-presenting cells (APC), are recognized as an important regulator of immune response and immune tolerance, and play a critical role in the host innate immunity and adaptive immunity. Previous studies have shown that the long-term parasization of Echinococcus in the host is strongly associated with the host immune tolerance induced by DCs. This review summarizes the research progress of the role of DCs in host immune tolerance caused Echinococcus infection, aiming to provide the theoretical basis and insights into the management and immunotherapy of Echinococcus infections.

BACKGROUND: The current deep learning diagnosis of breast masses is mainly reflected by the diagnosis of benign and malignant lesions. In China, breast masses are divided into four categories according to the treatment method: inflammatory masses, adenosis, benign tumors, and malignant tumors. These categorizations are important for guiding clinical treatment. In this study, we aimed to develop a convolutional neural network (CNN) for classification of these four breast mass types using ultrasound (US) images. METHODS: Taking breast biopsy or pathological examinations as the reference standard, CNNs were used to establish models for the four-way classification of 3623 breast cancer patients from 13 centers. The patients were randomly divided into training and test groups (n = 1810 vs. n = 1813). Separate models were created for two-dimensional (2D) images only, 2D and color Doppler flow imaging (2D-CDFI), and 2D-CDFI and pulsed wave Doppler (2D-CDFI-PW) images. The performance of these three models was compared using sensitivity, specificity, area under receiver operating characteristic curve (AUC), positive (PPV) and negative predictive values (NPV), positive (LR+) and negative likelihood ratios (LR-), and the performance of the 2D model was further compared between masses of different sizes with above statistical indicators, between images from different hospitals with AUC, and with the performance of 37 radiologists. RESULTS: The accuracies of the 2D, 2D-CDFI, and 2D-CDFI-PW models on the test set were 87.9%, 89.2%, and 88.7%, respectively. The AUCs for classification of benign tumors, malignant tumors, inflammatory masses, and adenosis were 0.90, 0.91, 0.90, and 0.89, respectively (95% confidence intervals [CIs], 0.87-0.91, 0.89-0.92, 0.87-0.91, and 0.86-0.90). The 2D-CDFI model showed better accuracy (89.2%) on the test set than the 2D (87.9%) and 2D-CDFI-PW (88.7%) models. The 2D model showed accuracy of 81.7% on breast masses ≤1 cm and 82.3% on breast masses >1 cm; there was a significant difference between the two groups (P < 0.001). The accuracy of the CNN classifications for the test set (89.2%) was significantly higher than that of all the radiologists (30%). CONCLUSIONS: The CNN may have high accuracy for classification of US images of breast masses and perform significantly better than human radiologists. TRIAL REGISTRATION Chictr.org, ChiCTR1900021375; http://www.chictr.org.cn/showproj.aspx?proj=33139.
Area Under Curve ; Breast/diagnostic imaging* ; Breast Neoplasms/diagnostic imaging* ; China ; Deep Learning ; Humans ; ROC Curve ; Sensitivity and Specificity

The study explores the application of Tanreqing Injection into brain components in brain diseases. The components of Tanreqing Injection and its existing components in rat cerebrospinal fluid were qualitatively analyzed by liquid chromatography-mass spectrometry(LC-MS). The possible mechanism of action of Tanreqing Injection into brain on brain diseases was predicted by network pharmacological theory. In this study, 17 brain-entry components of Tanreqing Injection were founded, and 222 core targets were obtained from network pharmacological results. The biological processes include 31 items such as negative regulation of apoptotic process, MAPK cascade, Ras protein signal transduction, and 22 items such as PI3 K-Akt signal transduction, MAPK signal transduction and neurotrophic factor signal transduction. Nine brain diseases including stroke, migraine and meningioma were screened out by predicting the effect of Tanreqing Injection on brain components, which provide ideas and directions for further study of a certain encephalopathy and lay a theoretical foundation for further revealing its molecular mechanism.
Animals ; Apoptosis ; Brain Diseases/drug therapy* ; Cerebrospinal Fluid/chemistry* ; Chromatography, Liquid ; Drugs, Chinese Herbal/analysis* ; Injections ; Mass Spectrometry ; Rats ; Signal Transduction

Objective:To observe effect of ginsenoside Rh₂ (GRh₂) on the invasion and migration of colon cancer resistant cells HCT116/L-OHP and its specific mechanism. Method:Cell counting kit-8 (CCK-8) assay was used to detect the inhibitory effect of different concentrations of GRh₂ (0, 2.5, 5, 10, 20, 40 mg·L^-1) on HCT116/L-OHP cell proliferation, scratch assay, Transwell assay and adhesion assay were used to detect the effects of GRh₂ (0, 2.5, 5, 10 mg·L^-1) on cell migration, invasion and adhesion. The protein expression levels of E-cadherin and matrix metalloproteinase-9(MMP-9) were examined by Western blot. Result:Compared with control group, GRh₂(5, 10, 20, 40 mg·L^-1) significantly inhibited the proliferation of HCT116/L-OHP cells in a dose-dependent manner(P<0.05, P<0.01); Compared with the control group, the scratch healing rate of GRh₂ group (5, 10 mg·L^-1) was significantly decreased (P<0.05, P<0.01), the number of cells passing through the chamber of GRh₂ group was significantly decreased (P<0.05, P<0.01), cell migration and invasive ability were significantly inhibited in a dose-dependent manner. The number of adherent cells in GRh₂ group was significantly reduced (P<0.05, P<0.01), and the cell adhesion ability was significantly inhibited. Compared with the control group, GRh₂ (10, 20, 30 mg·L^-1) promoted E-cadherin protein expression (P<0.05, P<0.01), while protein expression of MMP-9 was inhibited (P<0.01). Conclusion:GRh₂ can significantly inhibit the invasion and migration of HCT116/L-OHP in colon cancer cells, and its potential mechanism may be related to the promotion of E-cadherin and the inhibition of MMP-9 expression in a dose-dependent manner.

We evaluated the role of IL-10- in IL-33-mediated cholesterol reduction in macrophage-derived foam cells (MFCs) and the mechanism by which IL-33 upregulates IL-10. Serum IL-33 and IL-10 levels in coronary artery disease patients were measured. The effects of IL-33 on intra-MFC cholesterol level, IL-10, ABCA1 and CD36 expression, ERK 1/2, Sp1, STAT3 and STAT4 activation, and IL-10 promoter activity were determined. Core sequences were identified using bioinformatic analysis and site-specific mutagenesis. The serum IL-33 levels positively correlated with those of IL-10. IL-33 decreased cellular cholesterol level and upregulated IL-10 and ABCA1 but had no effect on CD36 expression. siRNA-IL-10 partially abolished cellular cholesterol reduction and ABCA1 elevation by IL-33 but did not reverse the decreased CD36 levels. IL-33 increased IL-10 mRNA production but had little effect on its stability. IL-33 induced ERK 1/2 phosphorylation and increased the luciferase expression driven by the IL-10 promoter, with the highest extent within the −2000 to −1752 bp segment of the 5′-flank of the transcription start site; these effects were counteracted by U0126. IL-33 activated Sp1, STAT3 and STAT4, but only the STAT3 binding site was predicted in the above segment. Site-directed mutagenesis of the predicted STAT3-binding sites (CTGCTTCCTGGCAGCAGAA→CTGCCTGGCAGCAGAA) reduced luciferase activity, and a STAT3 inhibitor blocked the regulatory effects of IL-33 on IL-10 expression. Chromatin immunoprecipitation (CHIP) confirmed the STAT3-binding sequences within the −1997 to −1700 and −1091 to −811 bp locus regions. IL-33 increased IL-10 expression in MFCs via activating ERK 1/2 and STAT3, which subsequently promoted IL-10 transcription and thus contributed to the beneficial effects of IL-33 on MFCs.
Binding Sites ; Cholesterol ; Chromatin Immunoprecipitation ; Computational Biology ; Coronary Artery Disease ; Foam Cells* ; Humans ; Interleukin-10* ; Interleukin-33* ; Luciferases ; Macrophages* ; Mutagenesis, Site-Directed ; Phosphorylation ; RNA, Messenger ; Transcription Initiation Site