Development of a cost-effective ex vivo lung perfusion system for lung transplantation in India.

Background & objectives: Standard donor lung preservation with cold flush and storage allows up to six hours between retrieval of lungs from the donor and transplantation in the recipient. Ex vivo lung perfusion (EVLP) systems mimic physiological ventilation and perfusion in the donor lungs with potential for prolonged lung preservation and donor lung reconditioning. In this study, it was aimed to perform EVLP on discarded donor lungs using a locally developed EVLP system. Methods: Equipment that are routinely used for cardiac surgeries were collected and a functional EVLP system was assembled. This system was used on five pairs of lungs retrieved from brain-dead organ donors. The lungs were ventilated and pulmonary circulation was continuously perfused with a solution containing oxygen and nutrients for four hours. The system was tested without red blood cells (RBCs) added to the solution (acellular group; n=3; A1, A2 and A3) and also with RBCs added to the solution (cellular group; n=2; C1 and C2). Results: The EVLP system was successfully used in four (A1, A2, A3 and C2) of the five lung pairs. Mechanical and gas exchange functions of the lungs were preserved in these lung pairs. One lung pair (C1) worsened and developed pulmonary oedema. Histopathological examination of all five lung pairs was satisfactory at the end of the procedure. Major challenges faced were leakage of solution from the system and obstruction to drainage of RBCs containing solution from the lungs. Interpretation & conclusions: The results of the present study suggest that, it is possible to maintain the lungs retrieved for transplantation in a physiological condition using a locally prepared EVLP system and a solution without RBCs.

Video-Assisted Thoracoscopic Surgery (VATS) for Spontaneous Pneumothorax and Emphysematous Bullous Lung Disease: A Study From Northern India.

INTRODUCTION: Bullous lung disease is the most common cause of spontaneous pneumothorax. The management of the same is primarily surgical, aiming at the bullectomy, which was earlier performed by standard postero-lateral thoracotomy. The last two decades have seen more frequent use of video-assisted thoracoscopic surgery (VATS) for the same and has been shown to be a low morbidity, efficacious, and cost-effective method. In this study we assess the role of VATS in the spectrum of bullous lung disease. METHOD: The study was conducted in the Department of Surgery, Dayanand Medical College and Hospital, Ludhiana, for a period of three years from January 1, 2016 to December 31, 2019 in which patients with bullous lung diseases were enrolled and the role of video-assisted thoracoscopic surgery was assessed in them. RESULTS: The study included a total of 75 patients who were managed operatively either by VATS or open thoracotomy. In the study group, the average age of patients was 35.6 years (range 16-68 years). The most common presentation was only bullous lung disease (BLD) in 40% of patients followed by 32% of patients having both BLD and broncho-pleural fistula (BPF). Apical segmentectomy/non-anatomical wedge resection was done in 36% of patients whereas VATS bullectomy was done in 36% of patients. Elective conversion to thoracotomy was planned in six patients because of dense adhesions and thick pleural peel. We performed pleurodesis in almost all cases (96%). Mean blood loss in the VATS procedure was 48.7 ml and mean operative time was 67.2 minutes. Mean duration of hospital stay was 4.8 days. Forced expiratory volume (FEV1) increased significantly from a mean of 65.80% to 77.60%. There was significant increase in forced vital capacity (FVC) mean from 70.30% to 79.50%. CONCLUSION: VATS can be used as a safe, feasible and effective procedure in patients presenting with spontaneous pneumothorax and bullous lung disease with or without a broncho-pleural fistula or parenchymal leak. It should be preferred over the traditional open thoracotomy procedure, whenever feasible to do so, in view of decreased perioperative morbidity and better functional outcome.

Extractive single document summarization using binary differential evolution: Optimization of different sentence quality measures.

With the increase in the amount of text information in different real-life applications, automatic text-summarization systems become more predominant in extracting relevant information. In the current study, we formulated the problem of extractive text-summarization as a binary optimization problem, and multi-objective binary differential evolution (DE) based optimization strategy is employed to solve this. The solutions of DE encode a possible subset of sentences to be present in the summary which is then evaluated based on some statistical features (objective functions) namely, the position of the sentence in the document, the similarity of a sentence with the title, length of the sentence, cohesion, readability, and coverage. These objective functions, measuring different aspects of summary, are optimized simultaneously using the search capability of DE. Some newly designed self-organizing map (SOM) based genetic operators are incorporated in the optimization process to improve the convergence. SOM generates a mating pool containing solutions and their neighborhoods. This mating pool takes part in the genetic operation (crossover and mutation) to create new solutions. To measure the similarity or dissimilarity between sentences, different existing measures like normalized Google distance, word mover distance, and cosine similarity are explored. For the purpose of evaluation, two standard summarization datasets namely, DUC2001, and DUC2002 are utilized, and the obtained results are compared with various supervised, unsupervised and optimization strategy based existing summarization techniques using ROUGE measures. Results illustrate the superiority of our approach in terms of convergence rate and ROUGE scores as compared to state-of-the-art methods. We have obtained 45% and 5% improvements over two recent state-of-the-art methods considering ROUGE-2 and ROUGE-1 scores, respectively, for the DUC2001 dataset. While for the DUC2002 dataset, improvements obtained by our approach are 20% and 5%, considering ROUGE-2 and ROUGE-1 scores, respectively. In addition to these standard datasets, CNN news dataset is also utilized to evaluate the efficacy of our proposed approach. It was also shown that the best performance not only depends on the objective functions used but also on the correct choice of similarity/dissimilarity measure between sentences.