Comparative proteome analysis of human esophageal cancer and adjacent normal tissues

Objective(s): Ranking as the sixth commonest cancer, esophageal squamous cell carcinoma (ESCC) represents one of the leading causes of cancer death worldwide. One of the main reasons for the low survival of patients with esophageal cancer is its late diagnosis. Materials and Methods: We used proteomics approach to analyze ESCC tissues with the aim of a better understanding of the malignant mechanism and searching candidate protein biomarkers for early diagnosis of esophageal cancer. The differential protein expression between cancerous               and normal esophageal tissues was investigated by two-dimensional polyacrylamide gel electrophoresis (2D-PAGE). Then proteins were identified by matrix-assisted laser desorption/ ionization tandem time-of-flight mass spectrometry (MALDI-TOF/TOF-MS) and MASCOT web based search engine. Results:We reported 4 differentially expressed proteins involved in the pathological process of esophageal cancer, such as annexinA1 (ANXA1), peroxiredoxin-2 (PRDX2), transgelin (TAGLN) andactin-aortic smooth muscle (ACTA2). Conclusion: In this report we have introduced new potential biomarker (ACTA2). Moreover, our data confirmed some already known markers for EC in our region

Applying the new multi-objective algorithms for the operation of a multi-reservoir system in hydropower plants

Abstract The optimal operation of the multi-purpose reservoir system is a difficult, and, sometimes, non-linear problem in multi-objective optimization. By simulating biological behavior, meta-heuristic algorithms scan the decision space and can offer a set of points as a group of solutions to a problem. Because it is essential to simultaneously optimize several competing objectives and consider relevant constraints as the main problem in many optimization problems, researchers have improved their ability to solve multi-objective problems by developing complementary multi-objective algorithms. Because the AHA algorithm is new, its multi-objective version, MOAHA (multi-objective artificial hummingbird algorithm), was used in this study and compared with two novel multi-objective algorithms, MOMSA and MOMGA. Schaffer and MMF1 were used as two standard multi-objective benchmark functions to gauge the effectiveness of the proposed method. Then, for 180 months, the best way to operate the reservoir system of the Karun River basin, which includes Karun 4, Karun 3, Karun 1, Masjed-e-Soleyman, and Gotvand Olia dams to generate hydropower energy, supply downstream demands (drinking, agriculture, industry, environmental), and control flooding was examined from September 2000 to August 2015. Four performance appraisal criteria (GD, S, Δ, and MS) and four evaluation indices (reliability, resiliency, vulnerability, and sustainability) were used in Karun's multi-objective multi-reservoir problem to evaluate the performance of the multi-objective algorithm. All three algorithms demonstrated strong capability in criterion problems by using multi-objective algorithms’ criteria and performance indicators. The large-scale (1800 dimensions) of the multi-objective operation of the Karun Basin reservoir system was another problem. With a minimum of 1441.71 objectives and an average annual hydropower energy manufacturing of 17,166.47 GW, the MOAHA algorithm demonstrated considerable ability compared to the other two. The final results demonstrated the MOAHA algorithm’s excellent performance, particularly in difficult and significant problems such as multi-reservoir systems' optimal operation under various objectives

Conjunctive management of groundwater and surface water resources using a hybrid simulation–optimization method

This study aimed to determine the optimal conjunctive utilization of groundwater and surface water resources in the Halil River basin, one of the most significant study regions in Kerman Province (Iran). Multi-verse optimizer (MVO) and the ANFIS (adaptive neuro-fuzzy inference systems) simulation model, known as the MVO–ANFIS simulation–optimization model, were used for this purpose. Moreover, the optimal exploitation policy for the studied basin was presented. The ANFIS model yielded a coefficient of determination greater than 0.99 in Baft, Rabor, and Jiroft. This model had a high capability to simulate groundwater levels in these three regions. Therefore, the ANFIS model was adopted as the simulation model to predict the aquifer water table in these regions. Regarding the conjunctive utilization of groundwater and surface water resources, the exploitation policy resulting from the MVO–ANFIS simulation–optimization model had a desirable performance by supplying 91.70, 87.75, and 97.58% of the total demands of Baft, Rabor, and Jiroft, respectively. Moreover, results of water system performance indicators, including reliability (82.96, 72.65, 95.07), resiliency (70, 53.47, 80), vulnerability (29.54, 25.64, 17.02), and sustainability (74.24%, 66.10%, 85.78%) in the mentioned regions, respectively, showed the appropriate performance of the proposed model for the simulation–optimization problem. HIGHLIGHTS An ANFIS model was used to simulate the underground water level.; The MVO–ANFIS model was developed for the purpose of conjunctive exploitation of surface and underground water resources.; The developed model had favorable results.

Clinical and microbiological patterns in critically ill patients with catheter-associated UTI : a report from Iran

Introduction: Catheter-associated urinary tract infections (CAUTIs) are among the most common nosocomial infections with different clinical and microbiological characteristics. We studied these characteristics in critically ill patients. Methodology: This research was a cross-sectional study conducted on intensive care unit (ICU) patients with CAUTI. Patients’ demographic and clinical information and laboratory data, including causative microorganisms and antibiotic susceptibility tests, were recorded and analyzed. Finally, the differences between the patients who survived and died were compared.Results: After reviewing 353 ICU cases, 80 patients with CAUTI were finally included in the study. The mean age was 55.9 ± 19.1 years, 43.7% were male and 56.3% were female. The mean length of infection development since hospitalisation and hospital stay were 14.7 (3-90) and 27.8 (5-98) days, respectively. The most common symptom was fever (80%). The microbiological identification showed that the most isolated microorganisms were Multidrug-resistant (MDR) Enterobacteriaceae (75%), Pseudomonas aeruginosa (8.8%), Gram-positive uropathogens (8.8%) and Acinetobacter baumannii (5%). Fifteen patients (18.8%) died among whom infections with A. baumannii (75%) and P. aeruginosa (57.1%) were associated with more death (p = 0.005). Conclusions: Although A. baumannii and P. aeruginosa can be the most important pathogens for death, MDR Enterobacteriaceae are still a serious concern as causes of CAUTIs