Chung-Tay Yao

Blunt abdominal injury with pelvic fracture is common in polytrauma cases and is a major challenge for emergency physicians. Fluid resuscitation and massive transfusion protocol should be activated when pelvic fracture patients are found in hypovolemic shock. At the emergency department, resuscitative endovascular balloon occlusion of the aorta may be performed to temporarily control bleeding. Finally, a damage control operation or trans-arterial embolization may be performed in the hybrid operating room.

Background: Symptom distress often occurs in lung cancer patients undergoing chemotherapy. However, a biomarker has not been identified to reflect the severity of their symptom distress.Objective: The aim of this study was to investigate the relationship between symptom distress and serum inflammatory biomarkers in lung cancer patients undergoing chemotherapy.Methods: A longitudinal, repeated-measures design was used to assess subjective symptoms (fatigue, sleep disturbance, pain, depression, and confusion), serum biomarkers (tartrate-resistant acid phosphatase 5a [TRACP5a], interleukin 6 [IL-6], IL-8, and C-reactive protein), and white blood cells in 62 lung cancer patients recruited from a single medical center at 3 time points: T1 was the baseline, T2 was the eighth day after the first chemotherapy cycle, and T3 was prior to the second cycle. Symptom distress was measured individually by 5 questionnaires (General Fatigue Scale, Pittsburgh Sleep Quality Index, Brief Pain Inventory, Profile of Mood States–Depressive, and Confusion).Results: The trend of TRACP5a was positively correlated to the trend of the patients’ symptom distress. However, the trends of IL-6 and IL-8 did not correlate.Conclusions: Serum TRACP5a was associated with symptom distress in lung cancer patients. Therefore, TRACP5a might be a potential biomarker to assess symptom distress of lung cancer patients undergoing chemotherapy.Implications for Practice: Oncology nurses may be able to apply TRACP5a expression to predict or monitor multiple distress symptoms in lung cancer patients undergoing chemotherapy. Furthermore, nurses can use these study findings to better understand the patients who need more attention to improve their quality of life.

Alcohol dehydrogenase (ADH) and aldehyde dehydrogenase (ALDH) are principal enzymes responsible for metabolism of ethanol in mammals. The steady-state metabolic flux of ethanol has been poorly understood.We investigated flux rates of the individual steps of ethanol metabolism in perfused rat livers treated with ALDH inactivator cyanamide as an attempt to mimic human ALDH2 deficiency commonly seen in East Asians. The net rates of ethanol oxidation, acetaldehyde oxidation, and acetate activation were determined with a set of defined equations, based on the set influx rates of ethanol and the measured efflux rates of ethanol, acetaldehyde, and acetate.After intraperitoneal injections of 0.2 and 1.5 mg/kg cyanamide, hepatic activities of mitochondrial ALDH2 and cytoplasmic ALDH1A1 decreased to a similar degree, that is, 51 to 57% and 69 to 74%, compared with the corresponding controls, respectively, whereas cytoplasmic ADH1 activity remained unchanged. At infusing 2 mM ethanol, acetaldehyde oxidation rate well matched (99%) the net ethanol oxidation rate in control liver. Both the ethanol and acetaldehyde oxidation rates were significantly decreased after cyanamide treatments. At 10 mM ethanol, the efflux acetaldehyde was significantly higher than that infusing 2 mM ethanol in both control and cyanamide groups. Seventy-eight percent of the oxidized ethanol released as efflux acetate. At 2 mM ethanol, the apparent flux control coefficients of ADH1 were assessed to be 0.78, 0.54, and 0.39, respectively, in control, low, and high cyanamide-treated livers. Kinetic simulations revealed that inhibition by acetaldehyde may largely account for the observed reduction of ADH1 oxidation rates after cyanamide treatment.Our results provide the first flux evidence that ADH and ALDH are steps influencing steady-state metabolism of ethanol in rat livers with inactivated ALDHs.

Background: Microarray technology can acquire information about thousands of genes simultaneously. We analyzed published breast cancer microarray databases to predict five-year recurrence and compared the performance of three data mining algorithms of artificial neural networks (ANN), decision trees (DT) and logistic regression (LR) and two composite models of DT-ANN and DT-LR. The collection of microarray datasets from the Gene Expression Omnibus, four breast cancer datasets were pooled for predicting five-year breast cancer relapse. After data compilation, 757 subjects, 5 clinical variables and 13,452 genetic variables were aggregated. The bootstrap method, Mann-Whitney U test and 20-fold cross-validation were performed to investigate candidate genes with 100 most-significant p-values. The predictive powers of DT, LR and ANN models were assessed using accuracy and the area under ROC curve. The associated genes were evaluated using Cox regression. Results: The DT models exhibited the lowest predictive power and the poorest extrapolation when applied to the test samples. The ANN models displayed the best predictive power and showed the best extrapolation. The 21 most-associated genes, as determined by integration of each model, were analyzed using Cox regression with a 3.53-fold (95% CI: 2.24-5.58) increased risk of breast cancer five-year recurrence… Conclusions: The 21 selected genes can predict breast cancer recurrence. Among these genes, CCNB1, PLK1 and TOP2A are in the cell cycle G2/M DNA damage checkpoint pathway. Oncologists can offer the genetic information for patients when understanding the gene expression profiles on breast cancer recurrence.