Outcome of neoadjuvant chemotherapy in “locally advanced/borderline resectable” gallbladder cancer: the need to define indications

Studies evaluating neo-adjuvant chemotherapy (NACT) exclusively in gallbladder cancer (GBC) are few and there are no randomized trials on the subject. Locally advanced GBC and indications for NACT in GBC are not yet clearly defined.

A method for bidirectional active vibration control of structure using discrete-time sliding mode

Pneumopericardium during BMV: A rare complication

Multiobjective optimization for improving machinability of Ti-6Al-4V using RSM and advanced algorithms

This paper explores use of Teaching Learning Based Optimization (TLBO), ‘JAYA’ (Sanskrit word means Victory) and Genetic Algorithm (GA) for the combined minimization of roughness of machined surface and forces generated in cutting in turning of Ti-6Al-4V. Experimentation was carried out with Response Surface Methodology (RSM) and the Central Composite Design (CCD). Speed of cutting (m/min), feed rate (mm/min) and depth of cut (mm) were the design variables for optimization. Two responses (roughness of machined surface and force of cutting) were independently minimized. RSM was useful in finding empirical relations and the effect of each parameter and their interactions on the responses considered. Analysis of variance (ANOVA) was used to find out the effective and non-effective factors and correctness of the models. Later on, a multi-objective optimization function was developed for minimizing both – roughness in machined surface and force generated in cutting using weights method and the correctness of weights were confirmed by Analytical Hierarchy Process (AHP). After formulating the combined objective function, TLBO, ‘JAYA’ and GA methods were used for further parameter optimization of the turning process. Performance of TLBO and ‘JAYA’ algorithm was compared with that of Genetic Algorithm (GA). It is found that TLBO and ‘JAYA’ performed better than GA in the combined minimization of roughness and forces in while turning Ti-6Al-4V. It is also found from the results that higher cutting speed (171.4 m/min) and lower feed rate (55.6 mm/min) can produce better surface roughness and minimum cutting forces in machining of Ti-6Al-4V.

Rupture of Hepatocellular Carcinoma: A Review of Literature

Approximately 700,000 people die of Hepatocellular Carcinoma (HCC) each year worldwide, making it the third leading cause of cancer related deaths. Rupture is a potentially life-threatening complication of HCC. The incidence of HCC rupture is higher in Asia and Africa than in Europe. In Asia approximately 10% of patients with a diagnosis of HCC die due to rupture each year. Spontaneous rupture is the third most common cause of death due to HCC after tumor progression and liver failure. The diagnosis of rupture in patients without history of cirrhosis or HCC may be difficult. The most common symptom of ruptured HCC is abdominal pain (66-100%). Shock at presentation can be seen in 33-90% of cases; abdominal distension is reported in 33%. Abdominal paracentesis documenting hemoperitoneum is a reliable test to provisionally diagnose rupture of HCC, it can be seen in up to 86% of clinically suspected cases. The diagnoses can be confirmed by computed tomography scan or ultrasonography, or both in 75% of cases. Careful pre-treatment evaluation is essential to decide the best treatment option. Management of ruptured HCC involves multi-disciplinary care where hemostasis remains a primary concern. Earlier studies have reported a mortality rate of 25-75% in the acute phase of ruptured HCC. However, recent studies have reported a significant decrease in the incidence of mortality. There is also a decrease in the incidence of ruptured HCC due to improved surveillance and early detection of HCC. Transarterial Embolization is the least invasive method to effectively induce hemostasis in the acute stage with a success rate of 53-100%. Hepatic resection in the other hand has the advantage of achieving hemostasis and in the same go offers a potentially curative resection in selected patients.

Physical Activity, Fitness, and Obesity in Heart Failure With Preserved Ejection Fraction

Heart failure with preserved ejection fraction (HFpEF) is common, increasing in prevalence, and refractory to available pharmacotherapies. Our understanding of HFpEF has evolved from a disorder of diastolic dysfunction to a constellation of physiologic impairments that lead to elevated left ventricular filling pressures and exercise intolerance. Accordingly, the therapeutic and preventive focus has shifted to identifying lifestyle factors that may have more pleotropic effects on the pathophysiologic mechanisms that define HFpEF. Recent studies have demonstrated that physical inactivity, low fitness, and obesity are potential modifiable targets for prevention as well as management of HFpEF. In this review, we have discussed the emerging epidemiological, mechanistic, and clinical evidence that support the role of these lifestyle factors as key determinants of development and progression of HFpEF. We also summarize the available evidence and major knowledge gaps with regard to developing exercise training and weight loss as unique and effective therapeutic strategies for management of HFpEF.

Three-Dimensional Organoids Reveal Therapy Resistance of Esophageal and Oropharyngeal Squamous Cell Carcinoma Cells

Oropharyngeal and esophageal squamous cell carcinomas, especially the latter, are a lethal disease, featuring intratumoral cancer cell heterogeneity and therapy resistance. To facilitate cancer therapy in personalized medicine, three-dimensional (3D) organoids may be useful for functional characterization of cancer cells ex vivo . We investigated the feasibility and the utility of patient-derived 3D organoids of esophageal and oropharyngeal squamous cell carcinomas.

Modeling and optimization by particle swarm embedded neural network for adsorption of zinc (II) by palm kernel shell based activated carbon from aqueous environment

Zn (II) is one the common pollutant among heavy metals found in industrial effluents. Removal of pollutant from industrial effluents can be accomplished by various techniques, out of which adsorption was found to be an efficient method. Applications of adsorption limits itself due to high cost of adsorbent. In this regard, a low cost adsorbent produced from palm oil kernel shell based agricultural waste is examined for its efficiency to remove Zn (II) from waste water and aqueous solution. The influence of independent process variables like initial concentration, pH, residence time, activated carbon (AC) dosage and process temperature on the removal of Zn (II) by palm kernel shell based AC from batch adsorption process are studied systematically. Based on the design of experimental matrix, 50 experimental runs are performed with each process variable in the experimental range. The optimal values of process variables to achieve maximum removal efficiency is studied using response surface methodology (RSM) and artificial neural network (ANN) approaches. A quadratic model, which consists of first order and second order degree regressive model is developed using the analysis of variance and RSM - CCD framework. The particle swarm optimization which is a meta-heuristic optimization is embedded on the ANN architecture to optimize the search space of neural network. The optimized trained neural network well depicts the testing data and validation data with R 2 equal to 0.9106 and 0.9279 respectively. The outcomes indicates that the superiority of ANN-PSO based model predictions over the quadratic model predictions provided by RSM.

Power system stability enhancement by fractional order multi input SSSC based controller employing whale optimization algorithm

Friction stir welding of polypropylene sheet