Search results for: Aleutian mink disease virus
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4228

Search results for: Aleutian mink disease virus

2968 Literature Review on the Controversies and Changes in the Insanity Defense since the Wild Beast Standard in 1723 until the Federal Insanity Defense Reform Act of 1984

Authors: Jane E. Hill

Abstract:

Many variables led to the changes in the insanity defense since the Wild Beast Standard of 1723 until the Federal Insanity Defense Reform Act of 1984. The insanity defense is used in criminal trials and argued that the defendant is ‘not guilty by reason of insanity’ because the individual was unable to distinguish right from wrong during the time they were breaking the law. The issue that surrounds whether or not to use the insanity defense in the criminal court depends on the mental state of the defendant at the time the criminal act was committed. This leads us to the question of did the defendant know right from wrong when they broke the law? In 1723, The Wild Beast Test stated that to be exempted from punishment the individual is totally deprived of their understanding and memory and doth not know what they are doing. The Wild Beast Test became the standard in England for over seventy-five years. In 1800, James Hadfield attempted to assassinate King George III. He only made the attempt because he was having delusional beliefs. The jury and the judge gave a verdict of not guilty. However, to legal confine him; the Criminal Lunatics Act was enacted. Individuals that were deemed as ‘criminal lunatics’ and were given a verdict of not guilty would be taken into custody and not be freed into society. In 1843, the M'Naghten test required that the individual did not know the quality or the wrongfulness of the offense at the time they committed the criminal act(s). Daniel M'Naghten was acquitted on grounds of insanity. The M'Naghten Test is still a modern concept of the insanity defense used in many courts today. The Irresistible Impulse Test was enacted in the United States in 1887. The Irresistible Impulse Test suggested that offenders that could not control their behavior while they were committing a criminal act were not deterrable by the criminal sanctions in place; therefore no purpose would be served by convicting the offender. Due to the criticisms of the latter two contentions, the federal District of Columbia Court of Appeals ruled in 1954 to adopt the ‘product test’ by Sir Isaac Ray for insanity. The Durham Rule also known as the ‘product test’, stated an individual is not criminally responsible if the unlawful act was the product of mental disease or defect. Therefore, the two questions that need to be asked and answered are (1) did the individual have a mental disease or defect at the time they broke the law? and (2) was the criminal act the product of their disease or defect? The Durham courts failed to clearly define ‘mental disease’ or ‘product.’ Therefore, trial courts had difficulty defining the meaning of the terms and the controversy continued until 1972 when the Durham rule was overturned in most places. Therefore, the American Law Institute combined the M'Naghten test with the irresistible impulse test and The United States Congress adopted an insanity test for the federal courts in 1984.

Keywords: insanity defense, psychology law, The Federal Insanity Defense Reform Act of 1984, The Wild Beast Standard in 1723

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2967 Analysis of Post-vaccination Immunity in Children with Severe Chronic Diseases Receiving Immunosuppressive Therapy by Specific IgG Antibodies Definition Method

Authors: Marina G. Galitskaya, Svetlana G. Makarova, Andrey P. Fisenko.

Abstract:

Children on medication-induced immunosuppression are at high risk of developing severe course infectious diseases. Therefore, preventive vaccination is especially important for these children. However, due to the immunosuppressive effects of treatment for the underlying disease, the effectiveness of vaccination may decrease below the protective level. In a multidisciplinary children's medical center, post-vaccination immunity was studied in 79 children aged 4-17 years. The children were divided into 2 groups: Group 1 (38 children) with kidney pathology (Nephrotic Syndrome) and Group 2 (41 children) with inflammatory bowel diseases (Ulcerative Colitis, Crohn's Disease). Both groups of children were vaccinated according to the national vaccination calendar and received immunosuppressive therapy (prednisolone, methotrexate, cyclosporine, and other drugs) for at least 1 year. Using the enzyme-linked immunosorbent assay method, specific IgG antibodies to vaccine-preventable infections were determined: measles, rubella, mumps, diphtheria, pertussis, tetanus, and hepatitis B. The study showed the percentage of children with positive IgG values for vaccine-preventable infections. The highest percentage of children had protective antibody levels to measles (84.2% in children with nephrotic syndrome and 92.6% in those with inflammatory bowel disease) and rubella (71% and 80.4%, respectively). The lowest percentage of children with protective antibodies was for hepatitis B (5.2% and 29.2% respectively). Antibodies to mumps, diphtheria, pertussis, and tetanus were found not in all children (from 39,4% to 82,9%). The remaining percentage of children did not have detectable IgG antibodies to vaccine-preventable infections. Not all children, despite the previous vaccination, preserved antibodies to vaccine-controlled infections and remained unprotected by specific IgG antibodies. The issue of a booster vaccine dose should be considered in children without contraindications to vaccination. Children receiving long-term immunosuppressive therapy require an individual vaccination approach, including a specific definition of the performed vaccination.

Keywords: immunosuppressive therapy, inflammatory bowel diseases, nephrotic syndrome, post-vaccination immunity, specific antibodies, vaccine-preventable infections.

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2966 Characteristics of Phytophthora infestans: The Causal Fungus of Potato Late Blight Disease

Authors: A. E. Elkorany, Eman Elsrgawy

Abstract:

Eighty six isolates of Phytophthora infestans dating back to 2006 were recovered from potato tubers that were on sale in Alexandria markets, Egypt. The isolates were characterized for mating type and colony morphology. Both A1 and A2 mating types were detected in the isolate collection, however, the A2 constituted 5.8% of the total isolates made while the A1 mating type isolates constituted 91.9%. The self-fertile phenotype was also detected but at a lower percentage of 2.3% of the total isolates. This indicated that Mexico, the probable origin of the disease, is no longer the only place where A2 mating type ever exists. The lumpy phenotype was the only trait observed linked to the A2 mating type isolates on rye A agar medium. The self-fertile isolates, however, exhibited colonies of a waxy appearance with little aerial hyphae and the culture were backed full with oospores. The A1 mating colonies were of smooth white abundant aerial hyphae. The metalaxyl resistant isolates were also detected among the analyzed isolates and constituted 4.6% of the total (86) isolates investigated. The appearance of the A2 mating type outside Mexico and the variation revealed in the population of Phytophthora infestans investigated supported the hypothesis of a second worldwide migration of the fungus from its origin which could constitute a threat to potato cultivation around the world.

Keywords: Phytophthora infestans, potato, Egypt, fungus

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2965 Synthesis of New Anti-Tuberculosis Drugs

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

Abstract:

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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2964 An Approach for Estimation in Hierarchical Clustered Data Applicable to Rare Diseases

Authors: Daniel C. Bonzo

Abstract:

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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2963 Impact of Bacillus subtilis Exotoxins on Fecundity, Sex Hormones and Release of Schistosoma mansoni cercariae in Biomphalaria alexandrina Snails

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

Abstract:

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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2962 The Phylogenetic Investigation of Candidate Genes Related to Type II Diabetes in Man and Other Species

Authors: Srijoni Banerjee

Abstract:

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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2961 Gene Expression Meta-Analysis of Potential Shared and Unique Pathways Between Autoimmune Diseases Under anti-TNFα Therapy

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

Abstract:

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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2960 Comparing Performance of Neural Network and Decision Tree in Prediction of Myocardial Infarction

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

Abstract:

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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2959 Image Processing-Based Maize Disease Detection Using Mobile Application

Authors: Nathenal Thomas

Abstract:

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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2958 Modelling Dengue Disease With Climate Variables Using Geospatial Data For Mekong River Delta Region of Vietnam

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

Abstract:

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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2957 Blackcurrant-Associated Rhabdovirus: New Pathogen for Blackcurrants in the Baltic Sea Region

Authors: Gunta Resevica, Nikita Zrelovs, Ivars Silamikelis, Ieva Kalnciema, Helvijs Niedra, Gunārs Lācis, Toms Bartulsons, Inga Moročko-Bičevska, Arturs Stalažs, Kristīne Drevinska, Andris Zeltins, Ina Balke

Abstract:

Newly discovered viruses provide novel knowledge for basic phytovirus research, serve as tools for biotechnology and can be helpful in identification of epidemic outbreaks. Blackcurrant-associated rhabdovirus (BCaRV) have been discovered in USA germplasm collection samples from Russia and France. As it was reported in one accession originating from France it is unclear whether the material was already infected when it entered in the USA or it became infected while in collection in the USA. Due to that BCaRV was definite as non-EU viruses. According to ICTV classification BCaRV is representative of Blackcurrant betanucleorhabdovirus specie in genus Betanucleorhabdovirus (family Rhabdoviridae). Nevertheless, BCaRV impact on the host, transmission mechanisms and vectors are still unknown. In RNA-seq data pool from Ribes plants resistance gene study by high throughput sequencing (HTS) we observed differences between sample group gene transcript heat maps. Additional analysis of the whole data pool (total 393660492 of 150 bp long read pairs) by rnaSPAdes v 3.13.1 resulted into 14424 bases long contig with an average coverage of 684x with shared 99.5% identity to the previously reported first complete genome of BCaRV (MF543022.1) using EMBOSS Needle. This finding proved BCaRV presence in EU and indicated that it might be relevant pathogen. In this study leaf tissue from twelve asymptomatic blackcurrant cv. Mara Eglite plants (negatively tested for blackcurrant reversion virus (BRV)) from Dobele, Latvia (56°36'31.9"N, 23°18'13.6"E) was collected and used for total RNA isolation with RNeasy Plant Mini Kit with minor modifications, followed by plant rRNA removal by a RiboMinus Plant Kit for RNA-Seq. HTS libraries were prepared using MGI Easy RNA Directional Library Prep Set for 16 reactions to obtain 150 bp pair-end reads. Libraries were pooled, circularized and cleaned and sequenced on DNBSEQ-G400 using PE150 flow cell. Additionally, all samples were tested by RT-PCR, and amplicons were directly sequenced by Sanger-based method. The contig representing the genome of BCaRV isolate Mara Eglite was deposited at European Nucleotide Archive under accession number OU015520. Those findings indicate a second evidence on the presence of this particular virus in the EU and further research on BCaRV prevalence in Ribes from other geographical areas should be performed. As there are no information on BCaRV impact on the host this should be investigated, regarding the fact that mixed infections with BRV and nucleorhabdoviruses are reported.

Keywords: BCaRV, Betanucleorhabdovirus, Ribes, RNA-seq

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2956 Food Poisoning (Salmonellosis) as a Public Health Problem Through Consuming the Meat and Eggs of the Carrier Birds

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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2955 Characterization of Transcription Factors Involved in Early Defense Response during Interaction of Oil Palm Elaeis guineensis Jacq. with Ganoderma boninense

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

Abstract:

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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2954 Role of Imaging in Alzheimer's Disease Trials: Impact on Trial Planning, Patient Recruitment and Retention

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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2953 Prediction of Coronary Artery Stenosis Severity Based on Machine Learning Algorithms

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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2952 Human Immuno-Deficiency Virus Co-Infection with Hepatitis B Virus and Baseline Cd4+ T Cell Count among Patients Attending a Tertiary Care Hospital, Nepal

Authors: Soma Kanta Baral

Abstract:

Background: Since 1981, when the first AIDS case was reported, worldwide, more than 34 million people have been infected with HIV. Almost 95 percent of the people infected with HIV live in developing countries. As HBV & HIV share similar routes of transmission by sexual intercourse or drug use by parenteral injection, co-infection is common. Because of the limited access to healthcare & HIV treatment in developing countries, HIV-infected individuals are present late for care. Enumeration of CD4+ T cell count at the time of diagnosis has been useful to initiate the therapy in HIV infected individuals. The baseline CD4+ T cell count shows high immunological variability among patients. Methods: This prospective study was done in the serology section of the Department of Microbiology over a period of one year from august 2012 to July 2013. A total of 13037 individuals subjected for HIV test were included in the study comprising of 4982 males & 8055 females. Blood sample was collected by vein puncture aseptically with standard operational procedure in clean & dry test-tube. All blood samples were screened for HIV as described by WHO algorithm by Immuno-chromatography rapid kits. Further confirmation was done by biokit ELISA method as per the manufacturer’s guidelines. After informed consent, HIV positive individuals were screened for HBsAg by Immuno-chromatography rapid kits (Hepacard). Further confirmation was done by biokit ELISA method as per the manufacturer’s guidelines. EDTA blood samples were collected from the HIV sero-positive individuals for baseline CD4+ T count. Then, CD4+ T cells count was determined by using FACS Calibur Flow Cytometer (BD). Results: Among 13037 individuals screened for HIV, 104 (0.8%) were found to be infected comprising of 69(66.34%) males & 35 (33.65%) females. The study showed that the high infection was noted in housewives (28.7%), active age group (30.76%), rural area (56.7%) & in heterosexual route (80.9%) of transmission. Out of total HIV infected individuals, distribution of HBV co-infection was found to be 6(5.7%). All co- infected individuals were married, male, above the age of 25 years & heterosexual route of transmission. Baseline CD4+ T cell count of HIV infected patient was found higher (mean CD4+ T cell count; 283cells/cu.mm) than HBV co-infected patients (mean CD4+ T cell count; 91 cells/cu.mm). Majority (77.2%) of HIV infected & all co-infected individuals were presented in our center late (CD4+ T cell count;< 350/cu. mm) for diagnosis and care. Majority of co- infected 4 (80%) were late presented with advanced AIDS stage (CD4+ count; <200/cu.mm). Conclusions: The study showed a high percentage of HIV sero-positive & co- infected individuals. Baseline CD4+ T cell count of majority of HIV infected individuals was found to be low. Hence, more sustained and vigorous awareness campaigns & counseling still need to be done in order to promote early diagnosis and management.

Keywords: HIV/AIDS, HBsAg, co-infection, CD4+

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2951 Eimeria spp. in Naturally Infected Calves

Authors: Nermin Isik, Ozlem Derinbay Ekici

Abstract:

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

Procedia PDF Downloads 536
2950 Representation of the Iranian Community in the Videos of the Instagram Page of the World Health Organization Representative in Iran

Authors: Naeemeh Silvari

Abstract:

The phenomenon of the spread and epidemic of the corona virus caused many aspects of the social life of the people of the world to face various challenges. In this regard, and in order to improve the living conditions of the people, the World Health Organization has tried to publish the necessary instructions for its contacts in the world in the form of its media capacities. Considering the importance of cultural differences in the discussion of health communication and the distinct needs of people in different societies, some production contents were produced and published exclusively. This research has studied six videos published on the official page of the World Health Organization in Iran as a case study. The published content has the least semantic affinity with Iranian culture, and it has been tried to show a uniform image of the Middle East with the predominance of the image of the culture of the developing Arab countries.

Keywords: corona, representation, semiotics, instagram, health communication

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2949 Antioxidant Effects of Withania Somnifera (Ashwagandha) on Brain

Authors: Manju Lata Sharma

Abstract:

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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2948 Sensitivity and Specificity of Clinical Testing for Digital Nerve Injury

Authors: Guy Rubin, Ravit Shay, Nimrod Rozen

Abstract:

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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2947 On the Homology Modeling, Structural Function Relationship and Binding Site Prediction of Human Alsin Protein

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

Abstract:

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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2946 A Framework for Early Differential Diagnosis of Tropical Confusable Diseases Using the Fuzzy Cognitive Map Engine

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

Abstract:

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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2945 Feature Extraction Technique for Prediction the Antigenic Variants of the Influenza Virus

Authors: Majid Forghani, Michael Khachay

Abstract:

In genetics, the impact of neighboring amino acids on a target site is referred as the nearest-neighbor effect or simply neighbor effect. In this paper, a new method called wavelet particle decomposition representing the one-dimensional neighbor effect using wavelet packet decomposition is proposed. The main idea lies in known dependence of wavelet packet sub-bands on location and order of neighboring samples. The method decomposes the value of a signal sample into small values called particles that represent a part of the neighbor effect information. The results have shown that the information obtained from the particle decomposition can be used to create better model variables or features. As an example, the approach has been applied to improve the correlation of test and reference sequence distance with titer in the hemagglutination inhibition assay.

Keywords: antigenic variants, neighbor effect, wavelet packet, wavelet particle decomposition

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2944 Poster for Sickle Cell Disease and Barriers to Care in South Yorkshire from 2017 to 2023

Authors: Amardass Dhami, Clare Samuelson

Abstract:

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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2943 Computer Aided Analysis of Breast Based Diagnostic Problems from Mammograms Using Image Processing and Deep Learning Methods

Authors: Ali Berkan Ural

Abstract:

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

Procedia PDF Downloads 93
2942 Correlation between Total Polyphenol Content and Antimicrobial Activity of Opuntia ficus indica Extracts against Periodontopathogenic Bacteria

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

Abstract:

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

Procedia PDF Downloads 142
2941 Performance and Physiological Responses of Broiler Chickens to Diets Supplemented with Propolis in Breeding, to in Ovo Propolis Feeding or to Propolis Supplementation of Diets for Their Chicks

Authors: Kalbiye Konanc, Ergin Ozturk

Abstract:

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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2940 Inferring Influenza Epidemics in the Presence of Stratified Immunity

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

Abstract:

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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2939 Comprehensive Care and the Right to Autonomy of Children and Adolescents with Cancer

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

Abstract:

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

Procedia PDF Downloads 333