Expression of cell cycle regulator p57^(kip2), cyclinE protein and proliferating cell nuclear antigen in human pancreatic cancer: An immunohistochemical study

AIM： To investigate the effects of p57^kip2, cyclinE protein and proliferating cell nuclear antigen （PCNA） on occurrence and progression of human pancreatic cancer. METHODS： The expression of p57^kip2, cyclinE protein and PCNA in tumor tissues and adjacent tissues from 32 patients with pancreatic cancer was detected by SP immunohistochemical technique. RESULTS： The positive expression rate of p57^kip2 protein in tumor tissues was 46.9%, which was lower than that in adjacent pancreatic tissues （χ^2 = 5.317, P〈0.05）. p57^kip2 protein positive expression remarkably correlated with tumor cell differentiation （P〈0.05）, but not with lymph node metastasis （P〉0.05）. The positive expression rate of cyclinE protein in tumor tissues was 68.8%, which was higher than that in adjacent pancreatic tissues （χ^2 = 4.063, P〈0.05）. CyclinE protein positive expression significantly correlated with tumor cell differentiation and lymph node metastasis （P〈0.05）. The positive expression rate of PCNA in the tumor tissues was 71.9%, which was higher than that in adjacent pancreatic tissues （χ^2 = 5.189, P〈0.05）. PCNA positive expression remarkably correlated with tumor cell differentiation and lymph node metastasis （P〈0.05）. CONCLUSION： The decreased expression of p57^kip2 and/or overexpression of cyclinE protein and PCNA may contribute to the occurrence and progression of pancreatic cancer. p57^kip2, cyclinE protein, and PCNA play an important role in occurrence and progression of pancreatic cancer.

Effects of environmental hypothermia on hemodynamics and oxygen dynamics in a conscious swine model of hemorrhagic shock

BACKGROUND:Hypothermia is associated with poor outcome in trauma patients;however,hemorrhagic shock(HS)model with anesthetized swine was different from that of clinical reality.To identify the effects of environmental hypothermia on HS,we investigated hemodynamics and oxygen dynamics in an unanesthetized swine model of HS under simulating hypothermia environment.METHODS:Totally 16 Bama pigs were randomly divided into ambient temperature group(group A)and low temperature group(group B),8 pigs in each group.Venous blood(30 mL/kg)was continuously withdrawn for more than 15 minutes in conscious swine to establish a hemorrhagic shock model.Pulmonary arterial temperature(Tp),heart rate(HR),mean arterial pressure(MAP),pulmonary arterial pressure(PAP),pulmonary arterial wedge pressure(PAWP),central venous pressure(CVP),cardiac output(CO),hemoglobin(Hb),saturation of mixed venous blood(SvO_2)and blood gas analysis were recorded at the baseline and different hemorrhagic shock time(HST).The whole body oxygen delivery indices,DO_2l and VO_2l,and the O_2 extraction ratio(O_2ER)were calculated.RESULTS:Core body temperature in group A decreased slightly after the hemorrhagic shock model was established,and environmental hypothermia decreased in core body temperature.The mortality rate was significantly higher in group B(50%)than in group A(0%).DO_2l and VO_2l decreased significantly after hemorrhage.No difference was found in hemodynamics,DO_2l and VO_2l between group A and group B,but the difference in pH,lactic acid and O_2ER was significant between the two groups.CONCLUSION:Environmental hypothermia aggravated the disorder of oxygen metabolism after hemorrhagic shock,which was associated with poor prognosis.

Construction and analysis of tree models for chromosomal classification of diffuse large B-cell lymphomas

AIM: To construct tree models for classification of diffuse large B-cell lymphomas (DLBCL) by chromosome copy numbers, to compare them with cDNA microarray classification, and to explore models of multi-gene, multi-step and multi-pathway processes of DLBCL tumorigenesis. METHODS: Maximum-weight branching and distancebased models were constructed based on the comparative genomic hybridization (CGH) data of 123 DLBCL samples using the established methods and software of Desper et al . A maximum likelihood tree model was also used to analyze the data. By comparing with the results reported in literature, values of tree models in the classification of DLBCL were elucidated. RESULTS: Both the branching and the distance-based trees classified DLBCL into three groups. We combined the classification methods of the two models and classified DLBCL into three categories according to their characteristics. The first group was marked by +Xq, +Xp, -17p and +13q; the second group by +3q, +18q and +18p; and the third group was marked by -6q and +6p. This chromosomal classification was consistent with cDNA classification. It indicated that -6q and +3q were two main events in the tumorigenesis of lymphoma. CONCLUSION: Tree models of lymphoma established from CGH data can be used in the classification of DLBCL. These models can suggest multi-gene, multistep and multi-pathway processes of tumorigenesis. Two pathways, -6q preceding +6q and +3q preceding+18q, may be important in understanding tumorigenesis of DLBCL. The pathway, -6q preceding +6q, may have a close relationship with the tumorigenesis of non-GCB DLBCL.

Interactions Between Gut Microbiota and Hosts and Their Role in Infectious Diseases

Major infectious diseases,such as viral hepatitis,acquired immune deficiency syndrome,and tuberculosis,are difficult to eliminate within a short period.Dengue fever,global influenza pandemic,and ebola and other high-threat pathogens are now the main threats to human health as well.Therefore,it is particularly important to find new strategies for the prevention and treatment of infectious diseases.The human gut tract contains trillions of microbial cells,including bacteria,archaea,fungi and viruses.These microbes are defined as gut microbiota and play an important role in human development,immunity,metabolism and diseases.In this review,we analyzed the mechanisms by which alterations in gut microbiota affect infectious diseases and how infectious diseases regulate the structure and function of gut microbiota.Finally,we summarized and discussed methods used for the diagnosis,prevention and treatment of infectious diseases based on the alteration of gut microbiota.