Search results for: Invasive Disease

Authors: M. S. Deshpande, Snehal D. Bomble

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Tuberculosis (TB) is a deadly contagious disease that is caused by a bacterium called Mycobacterium tuberculosis. More than sixty years ago, the introduction of the first anti-TB drugs for the treatment of TB (streptomycin (STR), p-aminosalcylic acid (PAS), isoniazid (INH), and then later ethambutol (EMB) and rifampicin (RIF)) gave optimism to the medical community, and it was believed that the disease would be completely eradicated soon. Worldwide, the number of TB cases has continued to increase, but the incidence rate has decreased since 2003. Recently, highly drug-resistant forms of TB have emerged worldwide. The prolonged use of classical drugs developed a growing resistance and these drugs have gradually become less effective and incapable to meet the challenges, especially those of multi drug resistant (MDR)-TB, extensively drug resistant (XDR)-TB, and HIV-TB co-infections. There is an unmet medical need to discover newer synthetic molecules and new generation of potent drugs for the treatment of tuberculosis which will shorten the time of treatment, be potent and safe while effective facing resistant strains and non-replicative, latent forms, reduce adverse side effect and not interfere in the antiretroviral therapy. This paper attempts to bring out the review of anti-TB drugs, and presents a novel method of synthesizing new anti-tuberculosis drugs and potential compounds to overcome the bacterial resistance and combat the re-emergence of tuberculosis.

Keywords: tuberculosis, mycobacterium, multi-drug resistant (MDR)-TB, extensively drug resistant (XDR)-TB

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Authors: Daniel C. Bonzo

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Practical considerations lead to the use of unit of analysis within subjects, e.g., bleeding episodes or treatment-related adverse events, in rare disease settings. This is coupled with data augmentation techniques such as extrapolation to enlarge the subject base. In general, one can think about extrapolation of data as extending information and conclusions from one estimand to another estimand. This approach induces hierarchichal clustered data with varying cluster sizes. Extrapolation of clinical trial data is being accepted increasingly by regulatory agencies as a means of generating data in diverse situations during drug development process. Under certain circumstances, data can be extrapolated to a different population, a different but related indication, and different but similar product. We consider here the problem of estimation (point and interval) using a mixed-models approach under an extrapolation. It is proposed that estimators (point and interval) be constructed using weighting schemes for the clusters, e.g., equally weighted and with weights proportional to cluster size. Simulated data generated under varying scenarios are then used to evaluate the performance of this approach. In conclusion, the evaluation result showed that the approach is a useful means for improving statistical inference in rare disease settings and thus aids not only signal detection but risk-benefit evaluation as well.

Keywords: clustered data, estimand, extrapolation, mixed model

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Authors: Alaa A. Youssef, Mohamed A. El-Emam, Momeana B. Mahmoud, Mona Ragheb

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Schistosomiasis, also known as bilharzia, is a disease caused by a parasitic trematode worm called Schistosoma. Biological control of the snail intermediate hosts of Schistosoma is one of the promising methods for eliminating this disease in Egypt. The molluscicidal activity of exotoxins secreted from Bacillus subtilis bacteria was studied. The effect of these exotoxins was studied on the fecundity of Biomphalaria alexandrina snails the intermediate host of Schistosoma mansoni; the fecundity includes the reproductive rate (R0) of B. alexandrina snails and levels of sex hormones (progesterone, testosterone, and estradiol). Moreover, the cercarial production of S. mansoni was determined. The results showed a significant reduction in the egg-laying capacity of the treated snails after exposure to sublethal concentrations ( LC10 and LC25) of B. Subtilis exotoxins; this reduction reached 70% at LC25. Moreover, B. Subtilis exotoxins' significantly suppressed the cercarial production of B. alexandrina snails. It is concluded that the exotoxins of Bacillus subtilis bacteria play an important role in the interference of the Schistosomiasis transmission, hence should be applied in the strategy of schistosomiasis control.

Keywords: schistosomiasis, Biomphalaria alexandrina snails, Bacillus subtilis bacteria, fecundity, sex hormones

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Authors: Srijoni Banerjee

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Sequences of some of the candidate genes (e.g., CPE, CDKAL1, GCKR, HSD11B1, IGF2BP2, IRS1, LPIN1, PKLR, TNF, PPARG) implicated in some of the complex disease, e.g. Type II diabetes in man has been compared with other species to investigate phylogenetic affinity. Based on mRNA sequence of these genes of 7 to 8 species, using bioinformatics tools Mega 5, Bioedit, Clustal W, distance matrix was obtained. Phylogenetic trees were obtained by NJ and UPGMA clustering methods. The results of the phylogenetic analyses show that of the species compared: Xenopus l., Danio r., Macaca m., Homo sapiens s., Rattus n., Mus m. and Gallus g., Bos taurus, both NJ and UPGMA clustering show close affinity between clustering of Homo sapiens s. (Man) with Rattus n. (Rat), Mus m. species for the candidate genes, except in case of Lipin1 gene. The results support the functional similarity of these genes in physiological and biochemical process involving man and mouse/rat. Therefore, in understanding the complex etiology and treatment of the complex disease mouse/rate model is the best laboratory choice for experimentation.

Keywords: phylogeny, candidate gene of type-2 diabetes, CPE, CDKAL1, GCKR, HSD11B1, IGF2BP2, IRS1, LPIN1, PKLR, TNF, PPARG

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Authors: Charalabos Antonatos, Mariza Panoutsopoulou, Georgios K. Georgakilas, Evangelos Evangelou, Yiannis Vasilopoulos

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The extended tissue damage and severe clinical outcomes of autoimmune diseases, accompanied by the high annual costs to the overall health care system, highlight the need for an efficient therapy. Increasing knowledge over the pathophysiology of specific chronic inflammatory diseases, namely Psoriasis (PsO), Inflammatory Bowel Diseases (IBD) consisting of Crohn’s disease (CD) and Ulcerative colitis (UC), and Rheumatoid Arthritis (RA), has provided insights into the underlying mechanisms that lead to the maintenance of the inflammation, such as Tumor Necrosis Factor alpha (TNF-α). Hence, the anti-TNFα biological agents pose as an ideal therapeutic approach. Despite the efficacy of anti-TNFα agents, several clinical trials have shown that 20-40% of patients do not respond to treatment. Nowadays, high-throughput technologies have been recruited in order to elucidate the complex interactions in multifactorial phenotypes, with the most ubiquitous ones referring to transcriptome quantification analyses. In this context, a random effects meta-analysis of available gene expression cDNA microarray datasets was performed between responders and non-responders to anti-TNFα therapy in patients with IBD, PsO, and RA. Publicly available datasets were systematically searched from inception to 10th of November 2020 and selected for further analysis if they assessed the response to anti-TNFα therapy with clinical score indexes from inflamed biopsies. Specifically, 4 IBD (79 responders/72 non-responders), 3 PsO (40 responders/11 non-responders) and 2 RA (16 responders/6 non-responders) datasetswere selected. After the separate pre-processing of each dataset, 4 separate meta-analyses were conducted; three disease-specific and a single combined meta-analysis on the disease-specific results. The MetaVolcano R package (v.1.8.0) was utilized for a random-effects meta-analysis through theRestricted Maximum Likelihood (RELM) method. The top 1% of the most consistently perturbed genes in the included datasets was highlighted through the TopConfects approach while maintaining a 5% False Discovery Rate (FDR). Genes were considered as Differentialy Expressed (DEGs) as those with P ≤ 0.05, |log2(FC)| ≥ log2(1.25) and perturbed in at least 75% of the included datasets. Over-representation analysis was performed using Gene Ontology and Reactome Pathways for both up- and down-regulated genes in all 4 performed meta-analyses. Protein-Protein interaction networks were also incorporated in the subsequentanalyses with STRING v11.5 and Cytoscape v3.9. Disease-specific meta-analyses detected multiple distinct pro-inflammatory and immune-related down-regulated genes for each disease, such asNFKBIA, IL36, and IRAK1, respectively. Pathway analyses revealed unique and shared pathways between each disease, such as Neutrophil Degranulation and Signaling by Interleukins. The combined meta-analysis unveiled 436 DEGs, 86 out of which were up- and 350 down-regulated, confirming the aforementioned shared pathways and genes, as well as uncovering genes that participate in anti-inflammatory pathways, namely IL-10 signaling. The identification of key biological pathways and regulatory elements is imperative for the accurate prediction of the patient’s response to biological drugs. Meta-analysis of such gene expression data could aid the challenging approach to unravel the complex interactions implicated in the response to anti-TNFα therapy in patients with PsO, IBD, and RA, as well as distinguish gene clusters and pathways that are altered through this heterogeneous phenotype.

Keywords: anti-TNFα, autoimmune, meta-analysis, microarrays

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Authors: Reza Safdari, Goli Arji, Robab Abdolkhani Maryam zahmatkeshan

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Background and purpose: Cardiovascular diseases are among the most common diseases in all societies. The most important step in minimizing myocardial infarction and its complications is to minimize its risk factors. The amount of medical data is increasingly growing. Medical data mining has a great potential for transforming these data into information. Using data mining techniques to generate predictive models for identifying those at risk for reducing the effects of the disease is very helpful. The present study aimed to collect data related to risk factors of heart infarction from patients’ medical record and developed predicting models using data mining algorithm. Methods: The present work was an analytical study conducted on a database containing 350 records. Data were related to patients admitted to Shahid Rajaei specialized cardiovascular hospital, Iran, in 2011. Data were collected using a four-sectioned data collection form. Data analysis was performed using SPSS and Clementine version 12. Seven predictive algorithms and one algorithm-based model for predicting association rules were applied to the data. Accuracy, precision, sensitivity, specificity, as well as positive and negative predictive values were determined and the final model was obtained. Results: five parameters, including hypertension, DLP, tobacco smoking, diabetes, and A+ blood group, were the most critical risk factors of myocardial infarction. Among the models, the neural network model was found to have the highest sensitivity, indicating its ability to successfully diagnose the disease. Conclusion: Risk prediction models have great potentials in facilitating the management of a patient with a specific disease. Therefore, health interventions or change in their life style can be conducted based on these models for improving the health conditions of the individuals at risk.

Keywords: decision trees, neural network, myocardial infarction, Data Mining

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Authors: Nathenal Thomas

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In the food chain and in many other agricultural products, corn, also known as maize, which goes by the scientific name Zea mays subsp, is a widely produced agricultural product. Corn has the highest adaptability. It comes in many different types, is employed in many different industrial processes, and is more adaptable to different agro-climatic situations. In Ethiopia, maize is among the most widely grown crop. Small-scale corn farming may be a household's only source of food in developing nations like Ethiopia. The aforementioned data demonstrates that the country's requirement for this crop is excessively high, and conversely, the crop's productivity is very low for a variety of reasons. The most damaging disease that greatly contributes to this imbalance between the crop's supply and demand is the corn disease. The failure to diagnose diseases in maize plant until they are too late is one of the most important factors influencing crop output in Ethiopia. This study will aid in the early detection of such diseases and support farmers during the cultivation process, directly affecting the amount of maize produced. The diseases in maize plants, such as northern leaf blight and cercospora leaf spot, have distinct symptoms that are visible. This study aims to detect the most frequent and degrading maize diseases using the most efficiently used subset of machine learning technology, deep learning so, called Image Processing. Deep learning uses networks that can be trained from unlabeled data without supervision (unsupervised). It is a feature that simulates the exercises the human brain goes through when digesting data. Its applications include speech recognition, language translation, object classification, and decision-making. Convolutional Neural Network (CNN) for Image Processing, also known as convent, is a deep learning class that is widely used for image classification, image detection, face recognition, and other problems. it will also use this algorithm as the state-of-the-art for my research to detect maize diseases by photographing maize leaves using a mobile phone.

Keywords: CNN, zea mays subsp, leaf blight, cercospora leaf spot

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Authors: Thi Thanh Nga Pham, Damien Philippon, Alexis Drogoul, Thi Thu Thuy Nguyen, Tien Cong Nguyen

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Mekong River Delta region of Vietnam is recognized as one of the most vulnerable to climate change due to flooding and seawater rise and therefore an increased burden of climate change-related diseases. Changes in temperature and precipitation are likely to alter the incidence and distribution of vector-borne diseases such as dengue fever. In this region, the peak of the dengue epidemic period is around July to September during the rainy season. It is believed that climate is an important factor for dengue transmission. This study aims to enhance the capacity of dengue prediction by the relationship of dengue incidences with climate and environmental variables for Mekong River Delta of Vietnam during 2005-2015. Mathematical models for vector-host infectious disease, including larva, mosquito, and human being were used to calculate the impacts of climate to the dengue transmission with incorporating geospatial data for model input. Monthly dengue incidence data were collected at provincial level. Precipitation data were extracted from satellite observations of GSMaP (Global Satellite Mapping of Precipitation), land surface temperature and land cover data were from MODIS. The value of seasonal reproduction number was estimated to evaluate the potential, severity and persistence of dengue infection, while the final infected number was derived to check the outbreak of dengue. The result shows that the dengue infection depends on the seasonal variation of climate variables with the peak during the rainy season and predicted dengue incidence follows well with this dynamic for the whole studied region. However, the highest outbreak of 2007 dengue was not captured by the model reflecting nonlinear dependences of transmission on climate. Other possible effects will be discussed to address the limitation of the model. This suggested the need of considering of both climate variables and another variability across temporal and spatial scales.

Keywords: infectious disease, dengue, geospatial data, climate

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Authors: M.Younus, M. Athar Khan, Asif Adrees

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The present research endeavour was made to investigate the Public Health impact of Salmonellosis through consuming the meat and eggs of the carrier’s birds and to see the prevalence of Salmonella enteritidis and Salmonella typhimurium from poultry feed, poultry meat, and poultry eggs and their role in the chain of transmission of salmonellae to human beings and causing food poisoning. The ultimate objective was to generate data to improve the quality of poultry products and human health awareness. Salmonellosis is one of the most wide spread food borne zoonoses in all the continents of the world. The etiological agents Salmonella enteritidis and Salmonella typhimurium not only produce the disease but during the convalescent phase (after the recovery of disease) remain carriers for indefinite period of time. The carrier state was not only the source of spread of disease with in the poultry but also caused typhoid fever in humans. The chain of transmission started from poultry feed to poultry meat and ultimately to humans as dead end hosts. In this experiment a total number of 200 samples of human stool and blood were collected randomly (100 samples of human stool and 100 samples of human blood) of 100 patients suspected from food poisoning patients from different hospitals of Lahore area for the identification of Salmonella enteritidis and Salmonella typhimurium through PCR method in order to see the public health impact of Salmonellosis through consuming the meat and eggs of the carrier birds. On the average 14 and 10 stool samples were found positive against Salmonella enteritidis and Salmonella typhimurium from each of the 25 patients from each hospital respectively in case of suspected food poisoning patients. Similarly on an average 5% and 6% blood samples were found positive from 25 patients of each hospital respectively. There was a significant difference (P< 0.05) in the sero positivity of stool and blood samples of suspected food poisoning patients as far as Salmonella enteritidis and Salmonella typhimurium was concerned. However there was no significant difference (P<0.05) between the hospitals.

Keywords: salmonella, zoonosis, food, transmission, eggs

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Authors: Sakeh N. Mohd, Bahari M. N. Abdul, Abdullah S. N. Akmar

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Oil palm production generates high export earnings to many countries especially in Southeast Asian region. Infection by necrotrophic fungus, Ganoderma boninense on oil palm results in basal stem rot which compromises oil palm production leading to significant economic loss. There are no reliable disease treatments nor promising resistant oil palm variety has been cultivated to eradicate the disease up to date. Thus, understanding molecular mechanisms underlying early interactions of oil palm with Ganoderma boninense may be vital to promote preventive or control measure of the disease. In the present study, four months old oil palm seedlings were infected via artificial inoculation of Ganoderma boninense on rubber wood blocks. Roots of six biological replicates of treated and untreated oil palm seedlings were harvested at 0, 3, 7 and 11 days post inoculation. Next-generation sequencing was performed to generate high-throughput RNA-Seq data and identify differentially expressed genes (DEGs) during early oil palm-Ganoderma boninense interaction. Based on de novo transcriptome assembly, a total of 427,122,605 paired-end clean reads were assembled into 30,654 unigenes. DEGs analysis revealed upregulation of 173 transcription factors on Ganoderma boninense-treated oil palm seedlings. Sixty-one transcription factors were categorized as DEGs according to stringent cut-off values of genes with log2 ratio [Number of treated oil palm seedlings/ Number of untreated oil palm seedlings] ≥ |1.0| (corresponding to 2-fold or more upregulation) and P-value ≤ 0.01. Transcription factors in response to biotic stress will be screened out from abiotic stress using reverse transcriptase polymerase chain reaction. Transcription factors unique to biotic stress will be verified using real-time polymerase chain reaction. The findings will help researchers to pinpoint defense response mechanism specific against Ganoderma boninense.

Keywords: Ganoderma boninense, necrotrophic, next-generation sequencing, transcription factors

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Authors: Kohkan Shamsi

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Background: MRI and PET are now extensively utilized in Alzheimer's disease (AD) trials for patient eligibility, efficacy assessment, and safety evaluations but including imaging in AD trials impacts site selection process, patient recruitment, and patient retention. Methods: PET/MRI are performed at baseline and at multiple follow-up timepoints. This requires prospective site imaging qualification, evaluation of phantom data, training and continuous monitoring of machines for acquisition of standardized and consistent data. This also requires prospective patient/caregiver training as patients must go to multiple facilities for imaging examinations. We will share our experience form one of the largest AD programs. Lesson learned: Many neurological diseases have a similar presentation as AD or could confound the assessment of drug therapy. The inclusion of wrong patients has ethical and legal issues, and data could be excluded from the analysis. Centralized eligibility evaluation read process will be discussed. Amyloid related imaging abnormalities (ARIA) were observed in amyloid-β trials. FDA recommended regular monitoring of ARIA. Our experience in ARIA evaluations in large phase III study at > 350 sites will be presented. Efficacy evaluation: MRI is utilized to evaluate various volumes of the brain. FDG PET or amyloid PET agents has been used in AD trials. We will share our experience about site and central independent reads. Imaging logistic issues that need to be handled in the planning phase will also be discussed as it can impact patient compliance thereby increasing missing data and affecting study results. Conclusion: imaging must be prospectively planned to include standardizing imaging methodologies, site selection process and selecting assessment criteria. Training should be transparently conducted and documented. Prospective patient/caregiver awareness of imaging requirement is essential for patient compliance and reduction in missing imaging data.

Keywords: Alzheimer's disease, ARIA, MRI, PET, patient recruitment, retention

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Authors: Sai Maniveer Adapa, Sai Guptha Perla, Adithya Reddy P.

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Thyroid nodules can often be diagnosed with ultrasound imaging, although differentiating between benign and malignant nodules can be challenging for medical professionals. This work suggests a novel approach to increase the precision of thyroid nodule identification by combining machine learning and deep learning. The new approach first extracts information from the ultrasound pictures using a deep learning method known as a convolutional autoencoder. A support vector machine, a type of machine learning model, is then trained using these features. With an accuracy of 92.52%, the support vector machine can differentiate between benign and malignant nodules. This innovative technique may decrease the need for pointless biopsies and increase the accuracy of thyroid nodule detection.

Keywords: thyroid tumor diagnosis, ultrasound images, deep learning, machine learning, convolutional auto-encoder, support vector machine

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Authors: Yu-Jia Jian, Emily Chia-Yu Su, Hui-Ling Hsu, Jian-Jhih Chen

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Coronary artery is the major supplier of myocardial blood flow. When fat and cholesterol are deposit in the coronary arterial wall, narrowing and stenosis of the artery occurs, which may lead to myocardial ischemia and eventually infarction. According to the World Health Organization (WHO), estimated 740 million people have died of coronary heart disease in 2015. According to Statistics from Ministry of Health and Welfare in Taiwan, heart disease (except for hypertensive diseases) ranked the second among the top 10 causes of death from 2013 to 2016, and it still shows a growing trend. According to American Heart Association (AHA), the risk factors for coronary heart disease including: age (> 65 years), sex (men to women with 2:1 ratio), obesity, diabetes, hypertension, hyperlipidemia, smoking, family history, lack of exercise and more. We have collected a dataset of 421 patients from a hospital located in northern Taiwan who received coronary computed tomography (CT) angiography. There were 300 males (71.26%) and 121 females (28.74%), with age ranging from 24 to 92 years, and a mean age of 56.3 years. Prior to coronary CT angiography, basic data of the patients, including age, gender, obesity index (BMI), diastolic blood pressure, systolic blood pressure, diabetes, hypertension, hyperlipidemia, smoking, family history of coronary heart disease and exercise habits, were collected and used as input variables. The output variable of the prediction module is the degree of coronary artery stenosis. The output variable of the prediction module is the narrow constriction of the coronary artery. In this study, the dataset was randomly divided into 80% as training set and 20% as test set. Four machine learning algorithms, including logistic regression, stepwise regression, neural network and decision tree, were incorporated to generate prediction results. We used area under curve (AUC) / accuracy (Acc.) to compare the four models, the best model is neural network, followed by stepwise logistic regression, decision tree, and logistic regression, with 0.68 / 79 %, 0.68 / 74%, 0.65 / 78%, and 0.65 / 74%, respectively. Sensitivity of neural network was 27.3%, specificity was 90.8%, stepwise Logistic regression sensitivity was 18.2%, specificity was 92.3%, decision tree sensitivity was 13.6%, specificity was 100%, logistic regression sensitivity was 27.3%, specificity 89.2%. From the result of this study, we hope to improve the accuracy by improving the module parameters or other methods in the future and we hope to solve the problem of low sensitivity by adjusting the imbalanced proportion of positive and negative data.

Keywords: decision support, computed tomography, coronary artery, machine learning

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Authors: Nermin Isik, Ozlem Derinbay Ekici

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Bovine coccidiosis is a protozoan disease caused by various species of Eimeria and most signs of disease are chronic or subclinical. The aim of this study was to determine the prevalence of Eimeria spp. in calves in Konya, in Turkey. The study, conducted from January- February 2015, involved 240 faecal samples of calves in the age groups of <1 month, 1-3 months and >3 months in Konya city centre, in Turkey. In a retrospective study from these faecal samples of calves submitted to the University of Selcuk, Faculty of Veterinary Medicine, Laboratory of Parasitology were evaluated regarding the prevalence of Eimeria spp. Faecal samples were examined by Fulleborn saturated salt floatation technique. Eimeria oocysts were found in 8.33% of all samples. The positivity rates in each of the age groups were different. According to the age groups (<1 month, 1-3 months and >3 months), the Eimeria spp. were determined as 0.83, 22.73 and 7.41%, respectively. After examination of stool, detected oocysts were sporulated in 2.5% potassium dichromate at 22º C and species were identified as E. cylindrica, E. zuernii, E. ellipsoidalis, E. subspherica, E. bovis, E. auburnensis, E. canadensis, E. illinoisensis and E. brasiliensis in infected calves. In conclusion, the highest prevalence was observed in the age group of 1-3 months. The presence of Eimeria species in calves demonstrated for the first time in the Konya region in Turkey. Other etiologic agents should also be investigated in calves more seriously. Further molecular epidemiological studies should be performed in this community.

Keywords: Eimeria spp., calves, diarrhea, bovine coccidiosis

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Authors: Afolakemi Helen Olaleye, Ogunjobi A. O

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Since coronavirus disease 2019 (COVID-19) was first reported in Nigeria, the virus has spread to virtually all sub-Saharan Africa (SSA) countries. In Nigeria, government agencies came together to create a goal-driven taskforce in improving our response against the virus. As COVID-19 international spread has been curtailed, community spread became rampant locally, leading to many health authorities raising concerns over the scarcity of medical consumables and supplies. Here at Lagos university teaching Hospital (LUTH), we present data analysis of COVID-19 infections offered at our Hospital (LUTH) and the surrounding communities. In addition, the adopted innovative solution to control the spread of infection, methods used in filling shortages of consumables, personal protective equipment (PPE), and use of mobile video technology in patient’s consultation. The management style and strategy adopted has led to a decline in infection rates in our community and among our front line staff. The current COVID -19 crisis has created an opportunity to test and demonstrate our pandemic response and control of infectious disease along with the revealed unknown potential in our community.

Keywords: COVID-19, preparedness, response, Lagos university teaching hospital

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Authors: Manju Lata Sharma

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Damage to cells caused by free radicals is believed to play a central role in the ageing process and in disease progression. Withania somnifera is widely used in ayurvedic medicine, and it is one of the ingredients in many formulations to increase energy, improve overall health and longevity and prevent disease. Withania somnifera possesses antioxidative properties. The antioxdant activity of Withania somnifera consisting of an equimolar concentration of active principles of sitoindoside VII-X and withaferin A. The antioxidant effect of Withania somnifera extract was investigated on lipid peroxidation (LPO), superoxide dismutase (SOD) and catalase (CAT) activity in mice. Aim: To study the antioxidant activity of an extract of Withania somnifera leaf against a mice model of chronic stress. Healthy swiss albino mice (3-4 months old) selected from an inbred colony were divided in to 6 groups. Biochemical estimation revealed that stress induced a significant change in SOD, LPO, CAT AND GPX. These stress induced perturbations were attenuated Withania somnifera (50 and 100 mg/kg BW). Result: Withania somnifera tended to normalize the augmented SOD and LPO activities and enhanced the activities of CAT and GPX. The result indicates that treatment with an alcoholic extract of Withania somnifera produced a significant decrease in LPO ,and an increase in both SOD and CAT in brain mice. This indicates that Withania somnifera extract possesses free radical scavenging activity .

Keywords: Withania somnifera, antioxidant, lipid peroxidation, brain

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Authors: Ghorbanali Mohammadi

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Background: Due to the widespread outbreak of the COVID-19 virus, a large number of people become infected with the disease every day and go to hospitals. The acute condition of this disease has caused the death of many people. Since all the stages of treatment for these people happen in the hospitals, nurses are at the forefront of the fight against this virus. This causes nurses to suffer from physical and mental health problems. Methods: Physical and mental problems in nurses were assessed using the Depression, Anxiety and Stress Scale (DASS-42) of Lovibond (1995) and the Nordic Questionnaire. Results: 90 nurses from emergency, intensive care, and coronary care units were examined, and a total of 180 questionnaires were collected and evaluated. It was found that 37.78%, 47.78%, and 21.11% of nurses have symptoms of depression, anxiety, and stress, respectively. 40% of the nurses had physical problems. In total, 65.17% of them were involved in one or more mental or physical illnesses. Conclusions: Of the three units surveyed, the nurses in intensive care, emergency room, and coronary care units worked more than ten hours a day. Examining the interaction of physical and mental health problems indicated that physical problems can aggravate mental problems.

Keywords: depression anxiety and stress scale of Lovibond, nordic questionnaire, mental health of nurses, physical health problems in nurses

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Authors: Guy Rubin, Ravit Shay, Nimrod Rozen

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The accuracy of a diagnostic test used to classify a patient as having disease or being disease-free is a valuable piece of information to be used by the physician when making treatment decisions. Finger laceration, suspected to have nerve injury is a challenging decision for the treating surgeon. The purpose of this study was to evaluate the sensitivity, specificity and predictive values of six clinical tests in the diagnosis of digital nerve injury. The six clinical tests included light touch, pin prick, static and dynamic 2-point discrimination, Semmes Weinstein monofilament and wrinkle test. Data comparing pre-surgery examination with post-surgery results of 42 patients with 52 digital nerve injury was evaluated. The subjective examinations, light touch, pin prick, static and dynamic 2-point discrimination and Semmes-Weinstein monofilament were not sensitive (57.6, 69.7, 42.4, 40 and 66.8% respectively) and specific (36.8, 36.8, 47.4, 42.1 and 31.6% respectively). Wrinkle test, the only objective examination, was the most sensitive (78.1%) and specific (55.6%). This result gives no pre-operative examination the ability to predict the result of explorative surgery.

Keywords: digital nerve, injury, nerve examination, Semmes-Weinstein monofilamen, sensitivity, specificity, two point discrimination, wrinkle test

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Authors: Y. Ruchi, A. Prerna, S. Deepshikha

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Amyotrophic lateral sclerosis (ALS), also known as “Lou Gehrig’s disease”. It is a neurodegenerative disease associated with degeneration of motor neurons in the cerebral cortex, brain stem, and spinal cord characterized by distal muscle weakness, atrophy, normal sensation, pyramidal signs and progressive muscular paralysis reflecting. ALS2 is a juvenile autosomal recessive disorder, slowly progressive, that maps to chromosome 2q33 and is associated with mutations in the alsin gene, a putative GTPase regulator. In this paper we have done homology modeling of alsin2 protein using multiple templates (3KCI_A, 4LIM_A, 402W_A, 4D9S_A, and 4DNV_A) designed using the Prime program in Schrödinger software. Further modeled structure is used to identify effective binding sites on the basis of structural and physical properties using sitemap program in Schrödinger software, structural and function analysis is done by using Prosite and ExPASy server that gives insight into conserved domains and motifs that can be used for protein classification. This paper summarizes the structural, functional and binding site property of alsin2 protein. These binding sites can be potential drug target sites and can be used for docking studies.

Keywords: ALS, binding site, homology modeling, neuronal degeneration

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Authors: Faith-Michael E. Uzoka, Boluwaji A. Akinnuwesi, Taiwo Amoo, Flora Aladi, Stephen Fashoto, Moses Olaniyan, Joseph Osuji

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The overarching aim of this study is to develop a soft-computing system for the differential diagnosis of tropical diseases. These conditions are of concern to health bodies, physicians, and the community at large because of their mortality rates, and difficulties in early diagnosis due to the fact that they present with symptoms that overlap, and thus become ‘confusable’. We report on the first phase of our study, which focuses on the development of a fuzzy cognitive map model for early differential diagnosis of tropical diseases. We used malaria as a case disease to show the effectiveness of the FCM technology as an aid to the medical practitioner in the diagnosis of tropical diseases. Our model takes cognizance of manifested symptoms and other non-clinical factors that could contribute to symptoms manifestations. Our model showed 85% accuracy in diagnosis, as against the physicians’ initial hypothesis, which stood at 55% accuracy. It is expected that the next stage of our study will provide a multi-disease, multi-symptom model that also improves efficiency by utilizing a decision support filter that works on an algorithm, which mimics the physician’s diagnosis process.

Keywords: medical diagnosis, tropical diseases, fuzzy cognitive map, decision support filters, malaria differential diagnosis

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Authors: Esra Yuksel, Dilek Duman, Levent Yeniay, Sezgin Ulukaya

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Sentinel lymph node biopsy (SLNB) is a minimal invasive technique with lower morbidity in axillary staging of breast cancer. Isosulfan blue stain is frequently used in SLNB and regarded as safe. The present case report aimed to report severe decrement in SpO2 following isosulfan blue administration, as well as skin and urine signs and inconsistency with clinical picture in a 67-year-old ,77 kg, ASA II female case that underwent SLNB under general anesthesia. Ten minutes after subcutaneous administration of 10 ml 1% isosulfan blue by the surgeons into the patient, who were hemodynamically stable, SpO2 first reduced to 87% from 99%, and then to 75% in minutes despite 100% oxygen support. Meanwhile, blood pressure and EtCO2 monitoring was unremarkable. After specifying that anesthesia device worked normally, airway pressure did not increase and the endotracheal tube has been placed accurately, the blood sample was taken from the patient for arterial gas analysis. A severe increase was thought in MetHb concentration since SpO2 persisted to be 75% although the concentration of inspired oxygen was 100%, and solution of 2500 mg ascorbic acid in 500 ml 5% Dextrose was given to the patient via intravenous route until the results of arterial blood gas were obtained. However, arterial blood gas results were as follows: pH: 7.54, PaCO2: 23.3 mmHg, PaO2: 281 mmHg, SaO2: %99, and MetHb: %2.7. Biochemical analysis revealed a blood MetHb concentration of 2%.However, since arterial blood gas parameters were good, hemodynamics of the patient was stable and methemoglobin concentration was not so high, the patient was extubated after surgery when she was relaxed, cooperated and had adequate respiration. Despite the absence of respiratory or neurological distress, SpO2 value was increased only up to 85% within 2 hours with 5 L/min oxygen support via face mask in the surgery room as the patient was extubated. At that time, the skin of particularly the upper part of her body has turned into blue, more remarkable on the face. The color of plasma of the blood taken from the patient for biochemical analysis was blue. The color of urine coming throughout the urinary catheter placed in intensive care unit was also blue. Twelve hours after 5 L/min. oxygen inhalation via a mask, the SpO2 reached to 90%. During monitoring in intensive care unit on the postoperative 1st day, facial color and urine color of the patient was still blue, SpO2 was 92%, and arterial blood gas levels were as follows: pH: 7.44, PaO2: 76.1 mmHg, PaCO2: 38.2 mmHg, SaO2: 99%, and MetHb 1%. During monitoring in clinic on the postoperative 2nd day, SpO2 was 95% without oxygen support and her facial and urine color turned into normal. The patient was discharged on the 3rd day without any problem.In conclusion, SLNB is a less invasive alternative to axillary dissection. However, false pulse oximeter reading due to pigment interference is a rare complication of this procedure. Arterial blood gas analysis should be used to confirm any fall in SpO2 reading during monitoring.

Keywords: isosulfan blue, pulse oximetry, SLNB, methemoglobinemia

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Authors: Ashish Jain, Shivam Tayal

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There has been great interest in the field of Iontophoresis since few years due to its great applications in the field of controlled transdermal drug delivery system. It is an technique which is used to enhance the transdermal permeation of ionized high molecular weight molecules across the skin membrane especially Peptides & Proteins by the application of direct current of 1-4 mA for 20-40 minutes whereas chemical must be placed on electrodes with same charge. Iontophoresis enhanced the delivery of drug into the skin via pores like hair follicles, sweat gland ducts etc. rather than through stratum corneum. It has wide applications in the field of experimental, Therapeutic, Diagnostic, Dentistry etc. Medical science is using it to treat Hyperhidrosis (Excessive sweating) in hands and feet and to treat other ailments like hypertension, Migraine etc. Nowadays commercial transdermal iontophoretic patches are available in the market to treat different ailments. Researchers are keen to research in this field due to its vast applications and advantages.

Keywords: iontophoresis, novel drug delivery, transdermal, permeation enhancer

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Authors: Amardass Dhami, Clare Samuelson

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Background: Sickle cell disease (SCD) is a complex, multisystem condition that significantly impacts patients' quality of life, characterized by acute illness episodes, progressive organ damage, and reduced life expectancy. In the UK, over 13,000 individuals are affected, with South Yorkshire having the fifth highest prevalence, including approximately 800 patients. Retinal complications in SCD can manifest as either proliferative or non-proliferative disease, with proliferative changes being more prevalent. These retinal issues can cause significant morbidity, including visual loss and increased care requirements, underscoring the need for regular monitoring. An integrated approach was applied to ensure timely interventions, ultimately enhancing patient outcomes and reduce ‘did not attend’ rates. Aim: To assess the factors which may influence attendance to Haematology and Ophthalmology Clinics with attention towards levels of deprivation towards non-attendance. Method : A retrospective study on 84 eligible patients, from the regional tertiary Centre for Sickle Cell Care (Sheffield Teaching Hospital) from 2017 to 2023. The study focused on the incidence of sickle cell eye disease, specifically examining the outcomes of patients who attended the combined haematology and ophthalmology clinics. Patients who did not attend either clinic were excluded from the analysis to ensure a clear understanding of the combined clinic's impact. This data was then compared with the United Kingdom’s Index of Multiple Deprivation (IMD) datasets to assess if inequalities of care affected this population. Results: The study concluded that the effectiveness of combining haematology and ophthalmology clinics was reduced following the intervention. The DNA rates increased to 40% for the haematology clinic. Additionally, a significant proportion of the cohort was classified as residing in areas of deprivation, suggesting a possible link between socioeconomic factors and non-attendance rates Conclusion: These findings underscore the challenges of integrating care for SCD patients, particularly in relation to socioeconomic barriers. Despite the intent to streamline care and improve patient outcomes, the increase in DNA rates points to the need for further investigation into the underlying causes of non-attendance. Addressing these issues, especially in deprived areas, could enhance the effectiveness of combined clinics and ensure that patients receive the necessary monitoring and interventions for their eye health and overall well-being. Future strategies may need to focus on improving accessibility, outreach, and support for patients to mitigate the impact of socioeconomic factors on healthcare attendance.

Keywords: south yorkshire, sickle cell anemia, deprivation, factors, haematology

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Authors: Karina Zaccari, Ernesto Cordeiro Marujo

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This paper presents a Machine Learning (ML) approach to support Meningitis diagnosis in patients at a children’s hospital in Sao Paulo, Brazil. The aim is to use ML techniques to reduce the use of invasive procedures, such as cerebrospinal fluid (CSF) collection, as much as possible. In this study, we focus on predicting the probability of Meningitis given the results of a blood and urine laboratory tests, together with the analysis of pain or other complaints from the patient. We tested a number of different ML algorithms, including: Adaptative Boosting (AdaBoost), Decision Tree, Gradient Boosting, K-Nearest Neighbors (KNN), Logistic Regression, Random Forest and Support Vector Machines (SVM). Decision Tree algorithm performed best, with 94.56% and 96.18% accuracy for training and testing data, respectively. These results represent a significant aid to doctors in diagnosing Meningitis as early as possible and in preventing expensive and painful procedures on some children.

Keywords: machine learning, medical diagnosis, meningitis detection, pediatric research

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Authors: Ali Berkan Ural

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This paper presents the analysis, evaluation, and pre-diagnosis of early stage breast based diagnostic problems (breast cancer, nodulesorlumps) by Computer Aided Diagnosing (CAD) system from mammogram radiological images. According to the statistics, the time factor is crucial to discover the disease in the patient (especially in women) as possible as early and fast. In the study, a new algorithm is developed using advanced image processing and deep learning method to detect and classify the problem at earlystagewithmoreaccuracy. This system first works with image processing methods (Image acquisition, Noiseremoval, Region Growing Segmentation, Morphological Operations, Breast BorderExtraction, Advanced Segmentation, ObtainingRegion Of Interests (ROIs), etc.) and segments the area of interest of the breast and then analyzes these partly obtained area for cancer detection/lumps in order to diagnosis the disease. After segmentation, with using the Spectrogramimages, 5 different deep learning based methods (specified Convolutional Neural Network (CNN) basedAlexNet, ResNet50, VGG16, DenseNet, Xception) are applied to classify the breast based problems.

Keywords: computer aided diagnosis, breast cancer, region growing, segmentation, deep learning

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Authors: N. Chikhi-Chorfi, L. Arbia, S. Zenia, H.Lounici

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Opuntia ficus-indica belongs to the Cactaceae family. The cactus is mainly cultivated for its fruit (prickly pear) that, eaten after pealing, is sweet and juicy, and rich in nutritional compounds, such as ascorbic acid and polyphenols. Different parts of O. ficus-indica are used in the traditional medicine of several countries: the cladodes are utilized to reduce serum cholesterol level and blood pressure, for treatment of ulcers, rheumatic pain, wounds, fatigue, capillary fragility, and liver conditions. This original study, investigate the effect of polyphenols of O. ficus indica (cactus) cladodes against periodontal bacteria collected from patients with periodontitis. The quantitative analysis of total polyphenols (TPP) was determined with Follin-Ciocalteu method. Different concentrations of extracts of O. ficus indica were tested by the disk method on two bacterial strains: Porphyromonas gingivalis and Prevotella intermedia responsible for periodontal disease. The results showed a good correlation between the concentration of total polyphenols and the antibacterial activity of the extracts of Opuntia ficus indica against P. gingivalis and P. intermedia with R² = 0.94 and R² = 0.90 respectively. This observation suggests that these extracts could be used in the treatment and prevention of periodontitis.

Keywords: periodontal disease, P. gingivalis, P. intermedia, polyphenols, Opuntia ficus indica

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Authors: Kalbiye Konanc, Ergin Ozturk

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To examine the effects of an ethanol liquid extract obtained from raw bee propolis (PE) on fattening performance and physiology such as vaccine-antibody relationship, microbial profile, immune status and some blood parameters of broiler chickens were used a total of 600 broiler (Ross 308) chicks, obtained from eggs of 288, 38-weeks-old broiler breeding. There were 6 groups: CC (Parent-Control and Offspring-Control, CP (Parent-Control and Offspring-propolis extract, Cip (Parent-Control and Offspring-in-ovo propolis extract), Cis (Parent-Control and Chickens-in-ovo saline), PeC (Parent-propolis extract and Offspring-Control), PeP (Parent-Propolis extract and Offspring-Propolis extract). Each group was consisted of 10 replications with 10 broiler offspring, and the experiment was lasted for 6 weeks with ethanol-extracted propolis concentration is 400 ppm/kg diet. While the highest feed consumptions at 0-21 days and 0-42 days were found in PeC, the best feed conversion ratio at 0-42 days was found in CP group. The live weight gains were found not to be different among the groups. The highest alanine aminotransferase activities were found in CC and CP and aspartate aminotransferase activities in PeP and PeC groups. The highest triglyceride and total antioxidant levels were found highest in CC and the highest total oxidant level in Cip group. IgA level in hatched eggs and IgM value after slaughtering were highest in Cip group. The best immune response was obtained for 21st day Newcastle Disease vaccine in CC and Cis groups and for 28th day Infectious Bursal Disease vaccine in CP group. The highest total aerobic microorganism and the lowest total fungi count were found in PeP group. In conclusion, it was determined that in-ovo propolis ethanol extract (Cip) increased the maternal antibody levels, that had not consistent effects on blood biochemical parameters except for triglyceride, that led to decrease in E. coli counts and that it can provide strong immune response against Infectious Bursal Disease.

Keywords: bee propolis, in-ovo feeding, immune parameters, poultry, maternal antibody, microorganisms

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Authors: Hsiang-Yu Yuan, Marc Baguelin, Kin O. Kwok, Nimalan Arinaminpathy, Edwin Leeuwen, Steven Riley

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Traditional syndromic surveillance for influenza has substantial public health value in characterizing epidemics. Because the relationship between syndromic incidence and the true infection events can vary from one population to another and from one year to another, recent studies rely on combining serological test results with syndromic data from traditional surveillance into epidemic models to make inference on epidemiological processes of influenza. However, despite the widespread availability of serological data, epidemic models have thus far not explicitly represented antibody titre levels and their correspondence with immunity. Most studies use dichotomized data with a threshold (Typically, a titre of 1:40 was used) to define individuals as likely recently infected and likely immune and further estimate the cumulative incidence. Underestimation of Influenza attack rate could be resulted from the dichotomized data. In order to improve the use of serosurveillance data, here, a refinement of the concept of the stratified immunity within an epidemic model for influenza transmission was proposed, such that all individual antibody titre levels were enumerated explicitly and mapped onto a variable scale of susceptibility in different age groups. Haemagglutination inhibition titres from 523 individuals and 465 individuals during pre- and post-pandemic phase of the 2009 pandemic in Hong Kong were collected. The model was fitted to serological data in age-structured population using Bayesian framework and was able to reproduce key features of the epidemics. The effects of age-specific antibody boosting and protection were explored in greater detail. RB was defined to be the effective reproductive number in the presence of stratified immunity and its temporal dynamics was compared to the traditional epidemic model using use dichotomized seropositivity data. Deviance Information Criterion (DIC) was used to measure the fitness of the model to serological data with different mechanisms of the serological response. The results demonstrated that the differential antibody response with age was present (ΔDIC = -7.0). The age-specific mixing patterns with children specific transmissibility, rather than pre-existing immunity, was most likely to explain the high serological attack rates in children and low serological attack rates in elderly (ΔDIC = -38.5). Our results suggested that the disease dynamics and herd immunity of a population could be described more accurately for influenza when the distribution of immunity was explicitly represented, rather than relying only on the dichotomous states 'susceptible' and 'immune' defined by the threshold titre (1:40) (ΔDIC = -11.5). During the outbreak, RB declined slowly from 1.22[1.16-1.28] in the first four months after 1st May. RB dropped rapidly below to 1 during September and October, which was consistent to the observed epidemic peak time in the late September. One of the most important challenges for infectious disease control is to monitor disease transmissibility in real time with statistics such as the effective reproduction number. Once early estimates of antibody boosting and protection are obtained, disease dynamics can be reconstructed, which are valuable for infectious disease prevention and control.

Keywords: effective reproductive number, epidemic model, influenza epidemic dynamics, stratified immunity

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Authors: Sandra Soca Lozano, Teresa Isabel Lozano Pérez, Germain Weber

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Cancer is a chronic disease of high prevalence in children and adolescents. Medical care in Cuba is carried out by a multidisciplinary team and family is the mediator between this team and the patient. Around this disease, there are interwoven many stereotypes and taboos by its relation to death. In this research report, we describe the work paradigm of psychological care to patients suffering from these diseases in the University Pediatric Hospital Juan Manuel Márquez of Havana, Cuba. We present the psychosocial factors that must be taken into account to provide comprehensive care and ensuring the quality of life of patients and their families. We also present the factors related to the health team and the management of information done with the patient. This is a descriptive proposal from the working experience accumulated in the named institution and in the review of the literature. As a result of this report we make a proposal of teamwork and the aspects in which psychological intervention should be continue performing in terms of increasing the quality of the care made by the health team. We conclude that it is necessary to continue improving the information management of children and adolescents with theses health problems and took into account their right to autonomy.

Keywords: comprehensive care, management of information, psychosocial factors, right to autonomy

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Authors: Ali Kassem, Yhea Kishik, Ali Hassan, Mohamed Abdelwahab

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Introduction: Accelerated coronary and peripheral vascular atherosclerosis is one of the most common and chronic complications of diabetes mellitus. A recent aspect of coronary artery disease in this condition is its silent nature. The aim of the work: Detection of the prevalence of silent myocardial ischemia (SMI) in Upper Egypt type 2 diabetic males and to select male diabetic population who should be screened for SMI. Patients and methods: 100 type 2 diabetic male patients with a negative history of angina or anginal equivalent symptoms and 30 healthy control were included. Full medical history and thorough clinical examination were done for all participants. Fasting and post prandial blood glucose level, lipid profile, (HbA1c), microalbuminuria, and C-reactive protein were done for all participants Resting ECG, trans-thoracic echocardiography, treadmill exercise ECG, myocardial perfusion imaging were done for all participants and patients positive for one or more NITs were subjected for coronary angiography. Results Twenty nine patients (29%) were positive for one or more NITs in the patients group compared to only one case (3.3%) in the controls. After coronary angiography, 20 patients were positive for significant coronary artery stenosis in the patients group, while it was refused to be done by the patient in the controls. There were statistical significant difference between the two groups regarding, hypertension, dyslipidemia and obesity, family history of DM and IHD with higher levels of microalbuminuria, C-reactive protein, total lipids in patient group versus controls According to coronary angiography, patients were subdivided into two subgroups, 20 positive for SMI (positive for coronary angiography) and 80 negative for SMI (negative for coronary angiography). No statistical difference regarding family history of DM and type of diabetic therapy was found between the two subgroups. Yet, smoking, hypertension, obesity, dyslipidemia and family history of IHD were significantly higher in diabetics positive versus those negative for SMI. 90% of patients in subgroup positive for SMI had two or more cardiac risk factors while only two patients had one cardiac risk factor (10%). Uncontrolled DM was detected more in patients positive for SMI. Diabetic complications were more prevalent in patients positive for SMI versus those negative for SMI. Most of the patients positive for SMI have DM more than 5 years duration. Resting ECG and resting Echo detected only 6 and 11 cases, respectively, of the 20 positive cases in group positive for SMI compared to treadmill exercise ECG and myocardial perfusion imaging that detected 16 and 18 cases respectively, Conclusion: Type 2 diabetic male patients should be screened for detection of SMI when aged above 50 years old, diabetes duration is more than 5 years, presence of two or more cardiac risk factors and/or patients suffering from one or more of the chronic diabetic complications. CRP, is an important parameter for selection of type 2 diabetic male patients who should be screened for SMI. Non invasive cardiac tests are reliable for screening of SMI in these patients in our locality.

Keywords: C-reactive protein, Silent myocardial ischemia, Stress tests, type 2 DM

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