This study is to investigate the effect of ZL-004 on normal mouse and mice with leukopenia induced by chemotherapeutic agents. 5-Fluorouracil were administered intraperitoneally to mice to develop leucopenia, and the mice were treated with ZL-004. The number of peripheral leukocytes and the percentage of granulocyte in total WBC were examined. The results are that ZL-004 markedly raise peripheral blood leukocytes in the normal mice and the mice model of leukopenia. So, ZL-004 could protect mice against 5-fluorouracil damage and raise peripheral blood leukocyte. Features of bone marrow smears is myeloproliferative hyperactivity in the mice, particularly the matured granulocytic series were observed. The mechanism of ZL-004 is to act on the mouse bone marrow causing proliferation and differentiation.

Objective In problem-based learning, students are often found difficult to con-struct medical knowledge systematically and transfer knowledge to solve new problems. In face of this challenge, this study aims to investigate the effect of visualization tool-supported online problem-based learning on medical students' clinical diagnostic expertise development. Methods A controlled study was conducted and 52 medical students were randomly assigned into experimental group (using visual-ization tool-supported online PBL environment for learning) and control group (using online PBL envi-ronment for learning without visualization tool support). Participants were asked to complete the diag-nostic analysis of three kidney problems according to the requirements of the learning environments and to provide feedback of online learning experience afterwards. Paired-sample t test and one-way analysis of vonriance were used to analyze both group's case 1 and case 3 on line learing scores. Results The results revealed that the experimental group had significant improvement in online learning performance [case 1: (1.47 ±0.54), case 3: (2.14 ±0.55), P=0.015], while the control group had no significant improvement [case 1:(1.57±0.67), case 3:(1.66±0.49), P=0.234]. Early performance of online learning and group factor had interative effects (F=7.266, P=0.013). Conclusions The findings suggest that visualization tool-supported online PBL environment can facilitate medical student clinical diagnostic expertise development effectively.

Objective To observe influence of atorvastatin combining with berberine on blood cholesterol level and carotid atherosclerotic plaques in patients with acute artery atherosclerosis cerebral infarction disease. Methods Fif-ty-five cases of acute cerebral infarction patients were randomized into 3 groups: group A (n=28), group B (n=11) and group C (n=16). Group A, B or C received atorvastatin 20 mg (qn), atorvastatin 40 mg (qn) or atorvastatin 20 mg (qn) +berberine 0.4 g (tid), respectively. All groups were then followed up for 3 months. The total cholesterol(TC), triglyceride (TG), low-density lipoprotein-cholesterol (LDL-C),high-density lipoprotein-cholesterol(HDL-C and the changes of carotid atherosclerotic plaques including total plaque area (TPA), crouse score,carotid intima-media thickness (IMT) and the stability of carotid plaques as well as the serum levels of creatinine(Scr), alanine aminotransferase(ALT), aspartate aminotransferase(AST), were compared among three groups. Results After 3 months, the TC, TG and LDL-C were de-creased in all three groups. There were statistically significant differences in the TC and LDL-C among these three groups (P=0.011,P=0.033) after treatment. The compliance rate of group C (75.0%) was significantly higher than group A ( 32.1% ) and group B (45.5%) in LDL-C (P=0.026). Both berberine combining with atorvastatin and atorvastatin monotherapy(20mg could significantly reduce crouse score. Conclusions Berberine can significantly enhance the benefi-cial effects of atorvastatin on LDL-C and the crouse score in patients with acute artery atherosclerosis cerebral infarction patients.

Objective To identity the characteristic metabolites of platelets activation by Plasma metabolic Profiling in acute myocardium infarction ( AMI ) patients.Methods From August 2012 to February 2013, samples in three groups were collected at Tianjin Third Central hospital, including AMI group (25 clinically diagnosis myocardial infarction, 14 male, 11 female, average age 67 ±13 ) , control group(A) and simulation platelet activation group(B) (A and B group composed of 29 health volunteers, 11 male 18 female, average age 65 ±12 ) .After collagen platelet activation on B group, HPLC-LTQ Orbitrap XL MS platform was used to analyze the serum metabolic profiling in three groups respectively.Principal component analysis ( PCA) model and partial least squares-discriiminate analysis ( OPLS-DA) model were established to select characteristic metabolites in A and B group, and then tested in X group to find common ions.Results 20 characteristic metabolites were selected in A and B group.3 different lysophosphatidyl choline, sphingosine 1-phosphate, ethanol amine amides, sphingosine choline phosphate, thromboxane, 14-methyl hexadecanoic acid showed the same changing trend and were significant different between B group and AMI group.Conclusions Characteristic ions selected by metabolic profiling technology had significant distinguishing ability for AMI patients and health control.They may provide early diagnosis for AMI.

Foreign Bodies ; Humans ; Male ; Maxillary Sinus ; Middle Aged

To provide new ideas for clinical diagnosis and treatment of coronavirus disease 2019 (COVID-19), this study explore the expression level and prognostic value of platelet parameters in mild, moderate and severe COVID-19. This is a retrospective analysis. From January to May 2020, a total of 69 patients who were diagnosed with COVID-19 in the Third Central Hospital and the Jinnan Hospital (both situated in Tianjin) were enrolled in the disease group. According to the severity, these patients were divided into mild group (15 cases), moderate group (46 cases), and severe group (8 cases). In the same period, 70 non-infected patients were enrolled in control group. The level of white blood cell count (WBC), absolute neutrophil count (NEU#), absolute lymphocyte count (LY#), neutrophil-lymphocyte ratio (NLR), red blood cell count (RBC), hemoglobin (Hb), platelet count (PLT), mean platelet volume (MPV), platelet distribution width (PDW), and platelet-large contrast ratio (P-LCR) before and after treatment were analyzed. Binary logistic regression analysis is used to establish a mathematical model of the relationship between these indexes and the outcome of severe COVID-19 patients. The receiver operating characteristic(ROC) curve is used to further explore the prognosis value of MPV, P-LCR, NLR separately and jointly in COVID-19 patients. Compare to the control group, WBC and NE# increase ( Z=-5.63, P<0.01; Z=-9.19, P<0.01) and LY# decrease ( Z=-9.34, P<0.01) in the severe group; NLR increase with the aggravation of the disease, there is significant difference between groups ( Z=17.61, P<0.01); PLT, PDW, MPV and P-LCR decrease with the aggravation of the disease, there is significant difference between groups ( Z=9.47, P<0.01; Z=11.41, P<0.01; Z =16.76, P<0.01; Z=13.97, P<0.01). Binary logistic regression analysis shows MPV, P-LCR and NLR have predictive value for severe COVID-19 patients. There is a negative correlation between MPV, P-LCR and severe COVID-19 patients ( OR=1.004, P=0.034; OR=1.097, P=0.046). There is a positive correlation between NLR and severe COVID-19 patients ( OR=1.052, P=0.016). MPV and P-LCR of patients with good prognosis after treatment were significantly higher than those before treatment ( Z=-6.47, P<0.01; Z=-5.36, P<0.01). NLR was significantly lower than that before treatment ( Z=-8.13, P<0.01). MPV and P-LCR in poor prognosis group were significantly lower than those before treatment ( Z=-9.46, P<0.01; Z=-6.81, P<0.01). NLR was significantly higher than that before treatment ( Z=-3.24, P<0.01). There were significant differences between good and poor prognosis groups before and after treatment in MPV, P-LCR and NLR ( P<0.01). Combination of these three indexes, ROC shows the AUC is 0.931, the sensitivity is 91.5%, the specificity is 94.1%, the positive predictive value is 88.9%, and the negative predictive value is 87.4%, which is better than any of these indexes separately. Changes in these parameters are closely related to clinical stage of COVID-19 patients. MPV, P-LCR and NLR are of great value in the prediction and prognosis of severe COVID-19 patients.

This study was aimed to investigate the effect of Forkhead Box G1 (FOXG1) on the epithelial-mesenchymal transition (EMT) of colorectal cancer (CRC) cells and the underlying mechanism. For this purpose, FOXG1 lentiviral interference (shRNA) plasmid and expression plasmid were constructed. Western blotting was used to analyze the expression of FOXG1 protein in five CRC cells, namely RKO, SW480, SW620, LoVo and DLD-1. The shRNA fragment of FOXG1 (shFOXG1) was designed and synthesized. Recombinant plasmids were obtained with the aid of DNA recombination technique. Double digestion and sequencing were used to identify the recombinant plasmids, and then lentivirus packaging, purification and stable transfection were carried out. Additionally, stable CRC cell lines were screened out. The changes of FOXG1 knockdown and overexpression efficiency, E-cadherin, Vimentin, Fibronectin, Snail, Twist mRNA and protein were investigated respectively by Western blotting and qRT-PCR analysis. Furthermore, the changes of cell morphology after knockdown and cell migration ability were evaluated respectively with optical microscopy, scratch test and Transwell assay. FOXG1 had the highest protein expression in RKO and the lowest in DLD-1 among the five CRC cells. Compared with those of the control group, the cell morphology in FOXG1 knockdown RKO group was changed from spindle into round or polygonal shape, cell polarization was enhanced and tight junction assembly was acclerated while cell migration distance was noticeably decreased. Moreover, the number of cells invaded and migrated through chambers was significantly reduced. Among these key factors of EMT, the expression of E-cadherin was increased while the expressions of Vimentin, Fibronectin, Snail and Twist were decreased. The opposite was the case in the overexpressed FOXG1 group. The overexpression of FOXG1 in CRC promoted the invasion and metastasis of CRC cells and played a crucial role in regulating the EMT. Thus, FOXG1 might be a novel therapeutic target in CRC treatment.