Online ISSN: 2515-8260

Volume 4, Issue 1

Volume 4, Issue 1, Winter 2017

PSO-ANN based diagnostic model for the early detection of dengue disease

Shalini Gambhira; Sanjay Kumar Malika; Yugal Kumarb

European Journal of Molecular & Clinical Medicine, 2017, Volume 4, Issue 1, Pages 1-8

Large numbers of machine learning approaches have been developed for analysis of medical data in recent years. These approaches have also proved their significance through accurate and earlier diagnosis of diseases. The objective of this work is to develop a diagnostic model for earlier diagnosis of dengue disease. Dengue fever is spread through the bite of the female mosquito (Aedes aegypti). The symptoms of this fever are similar to other fever such as that of Viral influenza, Chikungunya, Zika fever, and so on. However, in this fever, human life can be at risk due to severe depletion of blood platelets. Therefore, early diagnosis of dengue disease can help in protecting human lives by making a preventive move before it turns into an infectious disease. In this work, an effort is made to develop a PSO-ANN based diagnostic model for earlier diagnosis of dengue fever. In the proposed model, PSO technique is applied to optimize the weight and bias parameters of ANN method. Further, PSO optimized ANN approach is used to detect dengue patients. The effectiveness of the proposed model is evaluated based on accuracy, sensitivity, specificity, error rate and AUC parameters. The results of the proposed model have been compared with other existing approaches like ANN, DT, NB, and PSO. It is observed that the proposed diagnostic model is a proficient and powerful model for more accurate and earlier detection of dengue fever

Pros, cons and future of antibiotics

Elroy P. Weledji; Elizabeth K Weledji; Jules C. Assob; Dickson S. Nsagha

European Journal of Molecular & Clinical Medicine, 2017, Volume 4, Issue 1, Pages 9-14

The advantages of antibiotics have been most clearly seen in those acute bacterial infections which had a high mortality before the introduction of antibiotics. The reality of the potential harmful effects of antibiotics, both short term in individual patients and long term in favoring emergent resistance and opportunistic pathogens are discussed. Bacterial resistance makes the standard treatments ineffective, and increases the risk of infection spreading. The shortage of novel antibiotics has strengthened the efforts of genome sequencing to control bacterial resistance. The future would include novel approaches, based on a re-conceptualization of the nature of resistance, disease and prevention.

Safety study of autologous adult bone marrow derived mesenchymal stromal cells in idiopathic pulmonary fibrosis - Pilot data

Lakshmi Kiran Chelluria; Upasna Upadhyaya; Ravindra Nallagondab; Sudhir Prasadb; Mohammad Samiuddinb; Rajat Mohantyb; Chandrashekar Mallarpua; Meenakshi Ponnanaa; Sindhoora Rawulc; Eswara Prasad Chelluric

European Journal of Molecular & Clinical Medicine, 2017, Volume 4, Issue 1, Pages 15-22

Background: Lung transplantation is the choice of therapy in severe cases of idiopathic pulmonary fibrosis (IPF) but is compounded with post-transplant complications. The paucity of deceased organ donations underlines the need for alternate approaches that improves the quality of life. Herein, we attempted to develop an autologous adult bone marrow derived mesenchymal stromal cell (BMSC) therapy via central line access, and evaluated the safety of a single dose (~13 × 106 cells/mL), in treating “no option” IPF. Method: The study included severe IPF subjects (n = 6) both male and female, aged 40–70 years of age with a forced vital capacity < 50%, diffusing capacity of lung for carbon monoxide (DLco) < 35% of predicted, and/or oxygen (SpO2) saturation < 88% on 6 min walk distance (6 MWD). BMSCs at passage 2 were suspended in 30.0 mL normal saline and dispensed through the central line route in a respiratory intensive care unit of Gleneagles Global Hospitals. The subjects were monitored for the first 24 h for serious adverse events and hemodynamic parameters. They were followed up periodically at intervals of 1, 4, and 9 months for safety and monitoring of adverse events, including secondary objectives of changes in pulmonary function test, DLco, 6 MWD, and quality of life as per the study protocol. Results: It was observed that central line infusions were well tolerated by all subjects. Furthermore, there was an improved quality of life. Conclusions: BMSC central line infusion in “no option” IPF cases provided an insight into the strategies in improving the quality of life for patient and thereby increasing the therapeutic window period for lung transplantation.

Synthesis of a series of new 6-nitrobenzofuran-2-carbohydrazide derivatives with cytotoxic and antioxidant activity

Muhammad Taha; Sadia Sultan; Mohamad Azlan; Syed Adnan Ali Shah; Waqas Jamil; Swee Keong Yeap; Syahrul Imranb; Muhammad Nadeem Akhtar; Seema Zareenf; Nor Hadiani Ismailb; Muhammad Alih

European Journal of Molecular & Clinical Medicine, 2017, Volume 4, Issue 1, Pages 23-30

6-nitrobenzofuran-2-carbohydrazide Schiff base derivatives have been synthesized and their structure has been confirmed via H1NMR, Mass spectrometry and elemental (CHN/S) analysis. These synthesized analogs showed significant cytotoxic and antioxidant activity. Doxorubicin (IC50 = 0.94 ± 0.20 μM) and n-propyl gallate (IC50 = 30.30 ± 0.40 μM) were used as standard in cytotoxic and antioxidant activities, respectively. Compound 1 (IC50 = 3.30 ± 0.90 μM), 2 (IC50 = 2.70 ± 0.25 μM), 3 (IC50 = 2.70 ± 0.25 μM), 10 (IC50 = 2.70 ± 1.10 μM), 11 (IC50 = 1.00 ± 1.20 μM), and 17 (IC50 = 3.75 ± 0.90 μM) showed excellent while 21 (IC50 = 7.50 ± 0.60 μM) and 28 (IC50 = 7.50 ± 0.66 μM) showed moderate anti cancer activity. Furthermore, compound 10 (IC50 = 17.50 ± 0.85 μM), 11 (IC50 = 24.20 ± 0.55 μM), 12 (IC50 = 21.10 ± 1.58 μM), 13 (IC50 = 14.60 ± 0.32 μM), 14 (IC50 = 29.20 ± 0.75 μM) and 15 (IC50 = 9.26 ± 0.15 μM) showed better antioxidant activity than the standard n-propyl gallate. This study will be useful to develop potential lead molecules with cytotoxic and antioxidant potential.

Improving disease diagnosis by a new hybrid model

Bikash Kanti Sarkar

European Journal of Molecular & Clinical Medicine, 2017, Volume 4, Issue 1, Pages 31-47

Knowledge extraction is an important part of e-Health system. However, datasets in health domain are highly imbalanced, voluminous, conflicting and complex in nature, and these can lead to erroneous diagnosis of diseases. So, designing accurate and robust clinical diagnosis models for such datasets is a challenging task in data mining. In literature, numerous standard intelligent models have been proposed for this purpose but they usually suffer from several drawbacks like lack of understandability, incapability of operating rare cases, inefficiency in making quick and correct decision, etc. In fact, specific health application using standard intelligent methods may not satisfy multiple criteria. However, recent research indicates that hybrid intelligent methods (integrating several standard ones, can achieve better performance for health applications. Addressing the limitations of the existing approaches, the present research introduces a new hybrid predictive model (integrating C4.5 and PRISM learners) for diagnosing effectively the diseases (instead of any specific disease) in comprehensible way by the practitioners with better prediction results in comparison to the traditional approaches. The empirical results (in terms of accuracy, sensitivity and false positive rate) obtained over fourteen benchmark datasets demonstrate that the model outperforms the base learners in almost all cases. The performance of the model also claims that it can be good alternative to the specialized learners (each designed for specific disease) published in the literature. After all, the presented intelligent system is effective in undertaking medical data classification task.

Abstracts: 5th Annual Congress of the European Society for Translational Medicine (EUSTM-2017), 20–22 October 2017, Berlin, Germany

Aamir Shahzad; Randall J. Cohrs

European Journal of Molecular & Clinical Medicine, 2017, Volume 4, Issue 1, Pages 48-98

Regenerative medicine is a promising field with the potential to overcome the increasing need for donor organs either by stopping disease progression (e.g. with cells, genes or biologics) or by providing novel organ options. Furthermore, regenerative medicine strategies are unlike other treatments in that they are meant to persevere and treat the underlying injury rather than symptoms. This requires a level of persistence and safety and long term efficacy not always previously required for new therapies. In the past decade, clinicians have been able to utilize cell and gene therapies in unprecedented numbers, but with mixed results. At the same time, scientists have engineered organs (bladder, esophagus and blood vessels) that are considered simple structurally and functionally. However, regenerative medicine is yet to fully succeed with cells or genes or to fabricate fully functional solid organs such as kidneys, livers, lungs, and hearts. Yet, development of organs in the laboratory is proceeding both via 3D printing and use of decellularized scaffolds