Search results for: infectious diseases dissemination

Authors: Niamh Higgins, Dawn Howard

Abstract:

The Irish agri-food sector is of major importance to Ireland’s manufacturing sector and to the Irish economy through employment and the exporting of animal products worldwide. Infectious diseases and parasites have an impact on farm animal health causing profitability and productivity to be affected. For the sustainability of Irish dairy farming, there must be the highest standard of animal health. There can be a lack of information in accounting for > 1% of complete microbial diversity in an environment. There is the tendency of culture-based methods of microbial identification to overestimate the prevalence of species which grow easily on an agar surface. There is a need for new technologies to address these issues to assist with animal health. Metagenomic approaches provide information on both the whole genome and transcriptome present through DNA sequencing of total DNA from environmental samples producing high determination of functional and taxonomic information. Nanopore Next Generation Technologies have the ability to be powerful sequencing technologies. They provide high throughput, low material requirements and produce ultra-long reads, simplifying the experimental process. The aim of this study is to use a metagenomics approach to analyze dairy cattle faecal samples using the Oxford Nanopore MinION Next Generation Sequencer and to establish an in-house pipeline for metagenomic characterization of complex samples. Faecal samples will be obtained from Irish dairy farms, DNA extracted and the MinION will be used for sequencing, followed by bioinformatics analysis. Of particular interest, will be the parasite Buxtonella sulcata, which there has been little research on and which there is no research on its presence on Irish dairy farms. Preliminary results have shown the ability of the MinION to produce hundreds of reads in a relatively short time frame of eight hours. The faecal samples were obtained from 90 dairy cows on a Galway farm. The results from Oxford Nanopore ‘What’s in my pot’ (WIMP) using the Epi2me workflow, show that from a total of 926 classified reads, 87% were from the Kingdom Bacteria, 10% were from the Kingdom Eukaryota, 3% were from the Kingdom Archaea and < 1% were from the Kingdom Viruses. The most prevalent bacteria were those from the Genus Acholeplasma (71 reads), Bacteroides (35 reads), Clostridium (33 reads), Acinetobacter (20 reads). The most prevalent species present were those from the Genus Acholeplasma and included Acholeplasma laidlawii (39 reads) and Acholeplasma brassicae (26 reads). The preliminary results show the ability of the MinION for the identification of microorganisms to species level coming from a complex sample. With ongoing optimization of the pipe-line, the number of classified reads are likely to increase. Metagenomics has the potential in animal health for diagnostics of microorganisms present on farms. This would support wprevention rather than a cure approach as is outlined in the DAFMs National Farmed Animal Health Strategy 2017-2022.

Keywords: animal health, buxtonella sulcata, infectious disease, irish dairy cattle, metagenomics, minION, next generation sequencing

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Authors: G. Anjan Babu, G. Sumana, M. Rajasekhar

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Many inherited diseases and non-hereditary disorders are common in the development of renal cystic diseases. Polycystic kidney disease (PKD) is a disorder developed within the kidneys in which grouping of cysts filled with water like fluid. PKD is responsible for 5-10% of end-stage renal failure treated by dialysis or transplantation. New experimental models, application of molecular biology techniques have provided new insights into the pathogenesis of PKD. Researchers are showing keen interest for developing an automated system by applying computer aided techniques for the diagnosis of diseases. In this paper a multi-layered feed forward neural network with one hidden layer is constructed, trained and tested by applying back propagation learning rule for the diagnosis of PKD based on physical symptoms and test results of urinanalysis collected from the individual patients. The data collected from 50 patients are used to train and test the network. Among these samples, 75% of the data used for training and remaining 25% of the data are used for testing purpose. Furthermore, this trained network is used to implement for new samples. The output results in normality and abnormality of the patient.

Keywords: dialysis, hereditary, transplantation, polycystic, pathogenesis

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Authors: A. A. M. A. S. S. Perera, L. A. Ranasinghe, T. K. H. Nimeshika, D. M. Dhanushka Dissanayake, Namalie Walgampaya

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Nowadays, skin fungal diseases are mostly found in people of tropical countries like Sri Lanka. A skin fungal disease is a particular kind of illness caused by fungus. These diseases have various dangerous effects on the skin and keep on spreading over time. It becomes important to identify these diseases at their initial stage to control it from spreading. This paper presents an automated skin fungal disease identification system implemented to speed up the diagnosis process by identifying skin fungal infections in digital images. An image of the diseased skin lesion is acquired and a comprehensive computer vision and image processing scheme is used to process the image for the disease identification. This includes colour analysis using RGB and HSV colour models, texture classification using Grey Level Run Length Matrix, Grey Level Co-Occurrence Matrix and Local Binary Pattern, Object detection, Shape Identification and many more. This paper presents the approach and its outcome for identification of four most common skin fungal infections, namely, Tinea Corporis, Sporotrichosis, Malassezia and Onychomycosis. The main intention of this research is to provide an automated skin fungal disease identification system that increase the diagnostic quality, shorten the time-to-diagnosis and improve the efficiency of detection and successful treatment for skin fungal diseases.

Keywords: Circularity Index, Grey Level Run Length Matrix, Grey Level Co-Occurrence Matrix, Local Binary Pattern, Object detection, Ring Detection, Shape Identification

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Authors: Peter Fedichev

Abstract:

We studied fundamental aspects of aging to develop a mathematical model of gene regulatory network. We show that aging manifests itself as an inherent instability of gene network leading to exponential accumulation of regulatory errors with age. To validate our approach we studied age-dependent omic data such as transcriptomes, metabolomes etc. of different model organisms and humans. We build a computational platform based on our model to identify the targets and biomarkers of aging to design new drugs against aging and age-related diseases. As biomarkers of aging, we choose the rate of aging and the biological age since they completely determine the state of the organism. Since rate of aging rapidly changes in response to an external stress, this kind of biomarker can be useful as a tool for quantitative efficacy assessment of drugs, their combinations, dose optimization, chronic toxicity estimate, personalized therapies selection, clinical endpoints achievement (within clinical research), and death risk assessments. According to our model, we propose a method for targets identification for further interventions against aging and age-related diseases. Being a biotech company, we offer a complete pipeline to develop an anti-aging drug-candidate.

Keywords: aging, longevity, biomarkers, senescence

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Authors: S. Rostampour Yasouri, M. Ghane, M. Doudi

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Leptospirosis is one of the most significant infectious and zoonotic diseases along with global spreading. This disease is causative agent of economoic losses and human fatalities in various countries, including Northern provinces of Iran. The aim of this research is to identify and compare the rapid diagnostic techniques of pathogenic leptospiras, considering the multifacetedness of the disease from a clinical manifestation and premature death of patients. In the spring and summer of 2020-2022, 25 fecal samples were collected from suspected leptospirosis patients and 25 Fecal samples from mice residing in the rice fields and factories in Tonekabon city. Samples were prepared by centrifugation and passing through membrane filters. Culture technique was used in liquid and solid EMJH media during one month of incubation at 30°C. Then, the media were examined microscopically. DNA extraction was conducted by extraction Kit. Diagnosis of leptospiras was enforced by PCR and Real time PCR (SYBR Green) techniques using lipL32 specific primer. Out of the patients, 11 samples (44%) and 8 samples (32%) were determined to be pathogenic Leptospira by Real time PCR and PCR technique, respectively. Out of the mice, 9 Samples (36%) and 3 samples (12%) were determined to be pathogenic Leptospira by the mentioned techniques, respectively. Although the culture technique is considered to be the gold standard technique, but due to the slow growth of pathogenic Leptospira and lack of colony formation of some species, it is not a fast technique. Real time PCR allowed rapid diagnosis with much higher accuracy compared to PCR because PCR could not completely identify samples with lower microbial load.

Keywords: culture, pathogenic leptospiras, PCR, real time PCR

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Authors: Warren Jared, Bekker Jeremy, Salazar Guy, Jackman Katelyn, Linford Lauren

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Introduction: Positive Psychology research has burgeoned in the past 20 years; however, relatively few evidence-based resources to cultivate positive psychology skills are widely available to the general public. The positive psychology resources at www.mybestself101.org were developed to assist individuals in cultivating well-being using a variety of techniques, including gratitude, purpose, mindfulness, self-compassion, savoring, personal growth, and supportive relationships. These resources are empirically based and are built to be accessible to a broad audience. Key Objectives: This presentation highlights results from two recent randomized intervention studies of specific MBS101 learning modules. A key objective of this research is to empirically assess the efficacy and usability of these online resources. Another objective of this research is to encourage the broad dissemination of online positive psychology resources; thus, recommendations for further research and dissemination will be discussed. Methods: In both interventions, we recruited adult participants using social media advertisements. The participants completed several well-being and positive psychology construct-specific measures (savoring and self-compassion measures) at baseline and post-intervention. Participants in the experimental condition were also given a feedback questionnaire to gather qualitative data on how participants viewed the modules. Participants in the self-compassion study were randomly split between an experimental group, who received the treatment, and a control group, who were placed on a waitlist. There was no control group for the savoring study. Participants were instructed to read content on the module and practice savoring or self-compassion strategies listed in the module for a minimum of twenty minutes a day for 21 days. The intervention was semi-structured, as participants were free to choose which module activities they would complete from a menu of research-based strategies. Participants tracked which activities they completed and how long they spent on the modules each day. Results: In the savoring study, participants increased in savoring ability as indicated by multiple measures. In addition, participants increased in well-being from pre- to post-treatment. In the self-compassion study, repeated measures mixed model analyses revealed that compared to waitlist controls, participants who used the MBS101 self-compassion module experienced significant improvements in self-compassion, well-being, and body image with effect sizes ranging from medium to large. Attrition was 10.5% for the self-compassion study and 71% for the savoring study. Overall, participants indicated that the modules were generally helpful, and they particularly appreciated the specific strategy menus. Participants requested more structured course activities, more interactive content, and more practice activities overall. Recommendations: Mybestself101.org is an applied positive psychology research program that shows promise as a model for effectively disseminating evidence-based positive psychology resources that are both engaging and easily accessible. Considerable research is still needed, both to test the efficacy and usability of the modules currently available and to improve them based on participant feedback. Feedback received from participants in the randomized controlled trial led to the development of an expanded, 30-day online course called The Gift of Self-Compassion and an online mindfulness course currently in development called Mindfulness For Humans.

Keywords: positive psychology, intervention, online resources, self-compassion, dissemination, online curriculum

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Authors: Mohadese Oghbaee, Borna Firouzi

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The emergence of the Internet and more specifically the formation of social media has provided the ground for paying attention to new types of content dissemination. In recent years, Social media users share information, communicate with others, and exchange opinions on social events in this space. Many of the information published in this space are suspicious and produced with the intention of deceiving others. These contents are often called "fake news". Fake news, by disrupting the circulation of the concept and similar concepts such as fake news with correct information and misleading public opinion, has the ability to endanger the security of countries and deprive the audience of the basic right of free access to real information; Competing governments, opposition elements, profit-seeking individuals and even competing organizations, knowing about this capacity, act to distort and overturn the facts in the virtual space of the target countries and communities on a large scale and influence public opinion towards their goals. This process of extensive de-truthing of the information space of the societies has created a wave of harm and worries all over the world. The formation of these concerns has led to the opening of a new path of research for the timely containment and reduction of the destructive effects of fake news on public opinion. In addition, the expansion of this phenomenon has the potential to create serious and important problems for societies, and its impact on events such as the 2016 American elections, Brexit, 2017 French elections, 2019 Indian elections, etc., has caused concerns and led to the adoption of approaches It has been dealt with. In recent years, a simple look at the growth trend of research in "Scopus" shows an increasing increase in research with the keyword "false information", which reached its peak in 2020, namely 524 cases, reached, while in 2015, only 30 scientific-research contents were published in this field. Considering that one of the capabilities of social media is to create a context for the dissemination of news and information, both true and false, in this article, the classification of strategies for spreading fake news in social networks was investigated in social events. To achieve this goal, thematic analysis research method was chosen. In this way, an extensive library study was first conducted in global sources. Then, an in-depth interview was conducted with 18 well-known specialists and experts in the field of news and media in Iran. These experts were selected by purposeful sampling. Then by analyzing the data using the theme analysis method, strategies were obtained; The strategies achieved so far (research is in progress) include unrealistically strengthening/weakening the speed and content of the event, stimulating psycho-media movements, targeting emotional audiences such as women, teenagers and young people, strengthening public hatred, calling the reaction legitimate/illegitimate. events, incitement to physical conflict, simplification of violent protests and targeted publication of images and interviews were introduced.

Keywords: fake news, social network, social events, thematic analysis

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Authors: Y. V. S. Annapurna, V. V. Lakshmi

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Urinary tract infection (UTI) is one of the most common infectious diseases at the community level with a high rate of morbidity . This is further augmented by increase in the number of resistant and multi resistant strains of bacteria particularly by those producing Extended spectrum of beta lactamases. The present study was aimed at analysis of antibiograms of E.coli and Klebsiella sp causing urinary tract infections. Between November 2011 and April 2013, a total of 1120 urine samples were analyzed,. Antibiotic sensitivity testing was done with 542(48%) isolates of E.coli and 446(39%) of Klebsiella sp using the standard disc diffusion method against eleven commonly used antibiotics .Organisms showed high susceptibility to Amikacin and Netilimicin and low susceptibility to Cephalosporins. MAR index was calculated for the multidrug resistant strains. Maximum MAR index detected among the isolates was 0.9. Phenotypic identification for ESBL production was confirmed by double disk synergy test (DDST) according to CLSI guidelines. Plasmid profile of the isolates was carried out using alkaline hydrolysis method. Agarose-gel electrophoresis showed presence of high-molecular weight plasmid DNA among the ESBL strains. This study emphasizes the importance of indiscriminate use of antibiotics which if discontinued, in turn would prevent further development of bacterial drug resistance. For this, a proper knowledge of susceptibility pattern of uropathogens is necessary before prescribing empirical antibiotic therapy and it should be made mandatory.

Keywords: escherichia coli, extended spectrum of beta lactamase, Klebsiella spp, Uropathogens

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Authors: V. V. Lakshmi, Y. V. S. Annapurna

Abstract:

Urinary tract infection (UTI) is one of the most common infectious diseases seen in the community. Susceptible individuals experience multiple episodes, and progress to acute pyelonephritis or uro-sepsis or develop asymptomatic bacteriuria (ABU). Ability to cause extraintestinal infections depends on several virulence factors required for survival at extraintestinal sites. Presence of virulence phenotypes enhances the pathogenicity of these otherwise commensal organisms and thus augments its ability to cause extraintestinal infections, the most frequent in urinary tract infections(UTI). The present study focuses on detection of the virulence characters exhibited by the uropathogenic organism and most common factors exhibited in the local pathogens. A total of 700 isolates of E.coli and Klebsiella spp were included in the study. These were isolated from patients from local hospitals reported to be suffering with UTI over a period of three years. Isolation and identification was done based on Gram character and IMVIC reactions. Antibiotic sensitivity profile was carried out by disc diffusion method and multi drug resistant strains with MAR index of 0.7 were further selected.. Virulence features examined included their ability to produce exopolysaccharides, protease- gelatinase production, hemolysin production, haemagglutination and hydrophobicity test. Exopolysaccharide production was most predominant virulence feature among the isolates when checked by congo red method. The biofilms production examined by microtitre plates using ELISA reader confirmed that this is the major factor contributing to virulencity of the pathogens followed by hemolysin production

Keywords: Escherichia coli, Klebsiella sp, Uropathogens, Virulence features.

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Authors: Recep Kesli, Onur Turkyilmaz, Cengiz Demir

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Objective: Autoimmune collagen diseases occur with the immune reactions against the body’s own cell or tissues which cause inflammation and damage the tissues and organs. In this study, it was aimed to compare seropositivity rates and patterns of the anti-nuclear antibodies (ANA) in the diagnosis of four different autoimmune collagen tissue diseases (Rheumatoid Arthritis-RA, Systemic Lupus Erythematous-SLE, Scleroderma-SSc and Sjogren Syndrome-SS) with each other. Methods: One hundred eighty-eight patients applied to different clinics in Afyon Kocatepe University ANS Practice and Research Hospital between 11.07.2014 and 14.07.2015 that thought the different collagen disease such as RA, SLE, SSc and SS have participated in the study retrospectively. All the data obtained from the patients participated in the study were evaluated according to the included criteria. The historical archives belonging to the patients have been screened, assessed in terms of ANA positivity. The obtained data was analysed by using the descriptive statistics; chi-squared, Fischer's exact test. The evaluations were performed by SPSS 20.0 version and p < 0.05 level was considered as significant. Results: Distribution rates of the totally one hundred eighty-eight patients according to the diagnosis were found as follows: 82 (43.6%) were RA, 38 (20.2%) were SLE, 22 (11.7%) were SSc, and 46 (24.5%) were SS. Distribution of ANA positivity rates according to the collagen tissue diseases were found as follows; for RA were 54 (65,9 %), for SLE were 36 (94,7 %), for SSc were 18 (81,8 %), and for SS were 43 (93,5 %). Rheumatoid arthritis should be evaluated and classified as a different class among all the other investigated three autoimmune illnesses. ANA positivity rates were found as differently higher (91.5 %) in the SLE, SSc, and SS, from the RA (65.9 %). Differences at ANA positivity rates for RA and the other three diseases were found as statistically significant (p=0.015). Conclusions: Systemic autoimmune illnesses show broad spectrum. ANA positivity was found as an important predictor marker in the diagnosis of the rheumatologic illnesses. ANA positivity should be evaluated as more valuable and sensitive a predictor diagnostic marker in the laboratory findings of the SLE, SSc, and SS according to RA.

Keywords: antinuclear antibody (ANA), rheumatoid arthritis, scleroderma, Sjogren syndrome, systemic lupus Erythemotosus

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Authors: Dmitriy Yu. Korulkin, Raissa A. Muzychkina

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The last decade the growth of severe and disseminated forms of inflammatory diseases is observed in Kazakhstan, in particular, septic shock, which progresses on 3-15% of patients with infectious complications of postnatal period. In terms of the rate of occurrence septic shock takes third place after hemorrhagic and cardiovascular shock, in terms of lethality it takes first place. The structure of obstetric sepsis has significantly changed. Currently the first place is taken by postabortive sepsis (40%) that is connected with usage of imperfect methods of artificial termination of pregnancy in late periods (intraamnial injection of sodium chloride, glucose). The second place is taken by postnatal sepsis (32%); the last place is taken by septic complications of caesarean section (28%). In this connection, search for and assessment of effectiveness of new medicines for treatment of postoperative infectious complications, having biostimulating effect and speeding up regeneration processes, is very promising and topical. Essential oil was obtained by the method hydrodistillation air-dry aerial part of Sedum L. plants using Clevenger apparatus. Pilot batch of plant medicinal product based on Sedum essential oils was produced by Chimpharm JSC, Santo Member of Polpharma Group (Kazakhstan). During clinical test of the plant medicinal product based on Sedum L. essential oils 37 female patients at the age from 35 to 57 with clinical signs of complicated postoperative processes and 12 new mothers with clinical signs of inflammatory process on sutures on anterior abdominal wall after caesarean section and partial disruption of surgical suture line on perineum were examined. Medicine usage methods - surgical wound treatment 2 times a day, treatment with other medicines of local action was not performed. Before and after treatment general clinical test, determination of immune status, bacterioscopic test of wound fluid was performed to all women, medical history data was taken into account, wound cleansing and healing time, full granulations, side effects and complications, satisfaction with the used medicine was assessed. On female patients with inflammatory infiltration and partial disruption of surgical suture line anesthetic wound healing effect of plant medicinal product based on Sedum L. essential oils was observed as early as on the second day after beginning of using it, wound cleansing took place, as a rule, within the first row days. Hyperemia in the area of suture line also was not observed for 2-3-d day of usage of medicine, good constant course was observed. The absence of clinical effect on this group of patients was not registered. The represented data give evidence of that clinical effect was accompanied with normalization of changed laboratory findings. No allergic responses or side effects were observed during usage of the plant medicinal products based on Sedum L. essential oils.

Keywords: antiinflammatory, bioactive substances, essential oils, isolation, sedum L., wound healing

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Authors: Tivani Phosa Mashamba-Thompson, Mahmoud E. S. Soliman

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To date, the cause of neurodegeneration is not well understood and diseases that stem from neurodegeneration currently have no known cures. Cathepsin B (CB) enzyme is known to be involved in the production of peptide neurotransmitters and toxic peptides in neurodegenerative diseases (NDs). CA-074Me is a membrane-permeable irreversible selective cathepsin B (CB) inhibitor as confirmed by in vivo studies. Due to the lack of the crystal structure, the binding mode of CA-074Me with the human CB at molecular level has not been previously reported. The main aim of this study is to gain an insight into the binding mode of CB CA-074Me to human CB using various computational tools. Herein, molecular dynamics simulations, binding free energy calculations and per-residue energy decomposition analysis were employed to accomplish the aim of the study. Another objective was to identify novel CB inhibitors based on the structure of CA-074Me using fragment based drug design using scaffold hoping drug design approach. Results showed that two of the designed ligands (hit 1 and hit 2) were found to have better binding affinities than the prototype inhibitor, CA-074Me, by ~2-3 kcal/mol. Per-residue energy decomposition showed that amino acid residues Cys29, Gly196, His197 and Val174 contributed the most towards the binding. The Van der Waals binding forces were found to be the major component of the binding interactions. The findings of this study should assist medicinal chemist towards the design of potential irreversible CB inhibitors.

Keywords: cathepsin B, scaffold hopping, docking, molecular dynamics, binding-free energy, neurodegerative diseases

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Authors: Suthida Panwong, Jeeraporn Pekkoh, Yingmanee Tragoolpua, Aussara Panya

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Dengue virus (DENV) infection is a major public health problem in many countries, especially in tropical and subtropical countries. DENV infection causes dengue fever that can progress to serious conditions of dengue hemorrhagic fever (DHF) or dengue shock syndrome (DSS), relevant to a high risk of mortality. However, there are no effective treatments available against the manifestation and fatalities. Currently, natural extracts have been widely used for the treatment of infectious diseases due to their safety, non-accumulation in the body, or lower side effects. Chlorella spp. is a microalgae with anti-viral activity, but there is not much report to support its ability to inhibit DENV infection. Thus, this study aimed to investigate the inhibitory effect of ethanolic extract from Chlorella sp. AARL G049, which was explored in Thailand on inhibition of DENV-2 infection. The inhibitory effect on viral infection was assessed using a foci-forming assay (FFA), which revealed that a concentration of 125 µg/mL could inhibit viral infection in Vero cells by 75.45±8.06% when treated at the same time as DENV-2 infection. Moreover, the extract at an equal concentration effectively reduced viral protein synthesis by 90.51±5.48% when assessed in human cell lines using enzyme-linked immunosorbent assay (ELISA). Concordantly, the number of infected cells after treatment was reduced as measured by immunofluorescent assay (IFA). Therefore, the finding of this study supports the potential use of Chlorella sp. extract to suppress DENV infection.

Keywords: viral infection, flavivirus, treatment, natural extract

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Authors: V. V. Lakshmi, Y. V. S. Annapurna

Abstract:

Urinary tract infection (UTI) is one of the most common infectious diseases seen in the community. Susceptible individuals experience multiple episodes, and progress to acute pyelonephritis or uro-sepsis or develop asymptomatic bacteriuria (ABU). Ability to cause extraintestinal infections depends on several virulence factors required for survival at extraintestinal sites. Presence of virulence phenotypes enhances the pathogenicity of these otherwise commensal organisms and thus augments its ability to cause extraintestinal infections, the most frequent in urinary tract infections(UTI). The present study focuses on detection of the virulence characters exhibited by the uropathogenic organism and most common factors exhibited in the local pathogens. A total of 700 isolates of E.coli and Klebsiella spp were included in the study.These were isolated from patients from local hospitals reported to be suffering with UTI over a period of three years. Isolation and identification was done based on Gram character and IMVIC reactions. Antibiotic sensitivity profile was carried out by disc diffusion method and multi drug resistant strains with MAR index of 0.7 were further selected. Virulence features examined included their ability to produce exopolysaccharides, protease- gelatinase production, hemolysin production, haemagglutination and hydrophobicity test. Exopolysaccharide production was most predominant virulence feature among the isolates when checked by congo red method. The biofilms production examined by microtitre plates using ELISA reader confirmed that this is the major factor contributing to virulencity of the pathogens followed by hemolysin production.

Keywords: Escherichia coli, Klebsiella spp, Uropathogens, virulence features

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Authors: Santanu Chattopadhyay, Gautam Sarkar, Arabinda Das

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This paper presents wavelet based classification of various heart diseases. Electrocardiogram signals of different heart patients have been studied. Statistical natures of electrocardiogram signals for different heart diseases have been compared with the statistical nature of electrocardiograms for normal persons. Under this study four different heart diseases have been considered as follows: Myocardial Ischemia (MI), Congestive Heart Failure (CHF), Arrhythmia and Sleep Apnea. Statistical nature of electrocardiograms for each case has been considered in terms of kurtosis values of two types of wavelet coefficients: approximate and detail. Nine wavelet decomposition levels have been considered in each case. Kurtosis corresponding to both approximate and detail coefficients has been considered for decomposition level one to decomposition level nine. Based on significant difference, few decomposition levels have been chosen and then used for classification.

Keywords: arrhythmia, congestive heart failure, discrete wavelet transform, electrocardiogram, myocardial ischemia, sleep apnea

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Authors: Miral Sabry AlAshry

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The main objective of the study is to investigate the effectiveness of Egyptian Journalists through the Anti-Cyber and Information Technology Crimes Law, as well as its implications for journalistic practice and the implications for press freedom in Egypt. Questionnaires were undertaken with 192 journalists representing four official newspapers, and in-depth interviews were held with 15 journalists. The study used an Authoritarian theory as a theoretical framework. The study revealed that the government placed restrictions on journalists by using the law to oppress them.

Keywords: anti-cyber and information technology crimes law, media legislation, personal information, Egyptian constitution

Procedia PDF Downloads 359

Authors: Aziz Rezapour, Abdosaleh Jafari, Marziye Hadian, Elaheh Mazaheri

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Introduction: Cardiac rehabilitation is an accurate educational and sporting program designed to help heart patients to increase their physical activities and reduce the risk factors that make their health worse and help to a healthier lifestyle so that they can return to their families and society with a better spirit. The aim of this study was to examine the cost-effectiveness and cost-utility of cardiac rehabilitation programs for patients with cardiovascular diseases. Methods: In the present review study, published articles related to cost-effectiveness and cost-utility of cardiac rehabilitation programs for patients with cardiovascular diseases within the time interval between 2004 and 2019 were searched using electronic databases. The methodological quality of the structure of articles was examined by Drummond’s standard checklist. Results: The results of reviewing studies showed that most of the studies related to the economic evaluation of cardiac rehabilitation programs in patients with cardiovascular disease were flawed in Drummond’s criteria, and only one study adhered to Drummond’s criteria. The results of the present study indicated use of cardiac rehabilitation programs in patients with cardiovascular disease was cost-effective. Conclusion: The results of this review study showed that although the results of the studies were different in terms of a number of aspects, such as the study perspective, the time horizons, and the costs of rehabilitation programs, they achieved a similar conclusion, they concluded that the use of cardiac rehabilitation programs in patients with cardiovascular diseases, leading to higher quality-adjusted life years (QALYs) and lower costs.

Keywords: economic evaluation, systematic review, cardiac rehabilitation, Drummond’s checklist

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Authors: Zhijun Wu

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While social living is considered to be an indispensable part of human life in today's ever-connected world, social distancing has recently received much public attention on its importance since the outbreak of the coronavirus pandemic. In fact, social distancing has long been practiced in nature among solitary species and has been taken by humans as an effective way of stopping or slowing down the spread of infectious diseases. A social distancing problem is considered for how a population, when in the world with a network of social sites, decides to visit or stay at some sites while avoiding or closing down some others so that the social contacts across the network can be minimized. The problem is modeled as a population game, where every individual tries to find some network sites to visit or stay so that he/she can minimize all his/her social contacts. In the end, an optimal strategy can be found for everyone when the game reaches an equilibrium. The paper shows that a large class of equilibrium strategies can be obtained by selecting a set of social sites that forms a so-called maximal r-regular subnetwork. The latter includes many well-studied network types, which are easy to identify or construct and can be completely disconnected (with r = 0) for the most-strict isolation or allow certain degrees of connectivity (with r > 0) for more flexible distancing. The equilibrium conditions of these strategies are derived. Their rigidity and flexibility are analyzed on different types of r-regular subnetworks. It is proved that the strategies supported by maximal 0-regular subnetworks are strictly rigid, while those by general maximal r-regular subnetworks with r > 0 are flexible, though some can be weakly rigid. The proposed model can also be extended to weighted networks when different contact values are assigned to different network sites.

Keywords: social distancing, mitigation of spread of epidemics, populations games, networked social environments

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Authors: Fazal-e-Amin, Abdullah S. Alghamdi, Iftikhar Ahmad

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Software ecosystems’ concept is an inspiration from the natural ecosystem. Software ecosystems refer to large systems developed on top of a platform composed of different components developed by different entities of that ecosystem. Ecosystems improve information access, dissemination and coordination considerably. The ability to evolve and accommodate new subsystems gives a boost to the software ecosystems. In this paper, Saudi education software ecosystem is discussed and its need and potential benefits are highlighted. This work will provide a basis for further research in this area and foundation in development of Saudi education ecosystem.

Keywords: software ecosystem, education software, framework, software engineering

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Authors: Atmaja Patel

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Since the development of lasers in 1951, the first medical application was reported by Goldman in 1962. In 1960, T.H. Maiman produced the first Ruby laser and was used in cardiovascular surgery by McGuff in 1963. After a long time of investigations and new developments in laser technology first clinical applications were performed by Choy and Ginsburg in 1983. Introduction of the first true dental laser was in 1989. This paper is to highlight the various treatments and prevention of periodontal diseases. Lasers have become more predictable and effective form of treatment for periodontal diseases. The advantages of lasers include reduced use of anaesthesia, coagulation that yields a dry surgical field and hence better visibility, reduced need of sutures, minimal swelling and scarring, less pain and medication, faster healing and increased patient acceptance.

Keywords: lasers, periodontal surgery, diode laser, healing

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Authors: Ravija Gunawardana, Banuka Athuraliya

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Machine learning has emerged as a powerful tool for disease diagnosis and prediction. The use of machine learning algorithms has the potential to improve the accuracy of disease prediction, thereby enabling medical professionals to provide more effective and personalized treatments. This study focuses on developing a machine-learning model for disease prediction using symptoms and X-ray images. The importance of this study lies in its potential to assist medical professionals in accurately diagnosing diseases, thereby improving patient outcomes. Respiratory diseases are a significant cause of morbidity and mortality worldwide, and chest X-rays are commonly used in the diagnosis of these diseases. However, accurately interpreting X-ray images requires significant expertise and can be time-consuming, making it difficult to diagnose respiratory diseases in a timely manner. By incorporating machine learning algorithms, we can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The study utilized the Mask R-CNN algorithm, which is a state-of-the-art method for object detection and segmentation in images, to process chest X-ray images. The model was trained and tested on a large dataset of patient information, which included both symptom data and X-ray images. The performance of the model was evaluated using a range of metrics, including accuracy, precision, recall, and F1-score. The results showed that the model achieved an accuracy rate of over 90%, indicating that it was able to accurately detect and segment regions of interest in the X-ray images. In addition to X-ray images, the study also incorporated symptoms as input data for disease prediction. The study used three different classifiers, namely Random Forest, K-Nearest Neighbor and Support Vector Machine, to predict diseases based on symptoms. These classifiers were trained and tested using the same dataset of patient information as the X-ray model. The results showed promising accuracy rates for predicting diseases using symptoms, with the ensemble learning techniques significantly improving the accuracy of disease prediction. The study's findings indicate that the use of machine learning algorithms can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The model developed in this study has the potential to assist medical professionals in diagnosing respiratory diseases more accurately and efficiently. However, it is important to note that the accuracy of the model can be affected by several factors, including the quality of the X-ray images, the size of the dataset used for training, and the complexity of the disease being diagnosed. In conclusion, the study demonstrated the potential of machine learning algorithms for disease prediction using symptoms and X-ray images. The use of these algorithms can improve the accuracy of disease diagnosis, ultimately leading to better patient care. Further research is needed to validate the model's accuracy and effectiveness in a clinical setting and to expand its application to other diseases.

Keywords: K-nearest neighbor, mask R-CNN, random forest, support vector machine

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Authors: Maitri Dave

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Coronaviruses (CoV) is such infectious virus which has impacted globally in a more dangerous manner causing severe lung problems and leaving behind more serious diseases among the people. This pandemic has affected globally and created severe respiratory problems, and damaged the lungs. India has reported the first case of COVID-19 in January 2020. The first wave of COVID-19 took place from April to September of 2020. Soon after, a second peak is also noticed in the month of March 2021, which in turn becomes more dangerous due to a lack of supply of medical equipment. It created resource deficiency globally, specifically in India, where some necessary life-saving equipment like ventilators and oxygenators were not sufficient to cater to the demand-supply ratio effectively. Through carefully examining such a situation, India began to execute the process of vaccination in the month of January 2021 and successfully administered 25,46,71,259 doses of vaccines till now, which is only 15.5% of the total population while only 3.6% of the total population is fully vaccinated. India has authorized the British Oxford–AstraZeneca vaccine (Covishield), the Indian BBV152 (Covaxin) vaccine, and the Russian Sputnik V vaccine for emergency use. In the present study, we have collected all the data state wisely of both first and second wave and analyzed them using MS Excel Version 2019 and SPSS Statistics Version 26. Following the trends, we have predicted the characteristics of the upcoming third wave of COVID-19 and recommended some strategies, early actions, and measures that can be taken by the public health system in India to combat the third wave more effectively.

Keywords: COVID-19, vaccination, Covishiled, Coronavirus

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Authors: Payel Saha

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Social media is playing an important role for dissemination of information in society. In 21st century most people have a smart phone and used different social media tools like Facebook, Twitter, Instagram, WhatsApp, Skype etc. in day to day life. It is rapidly growing web-based tool for everyone to share thoughts, ideas and knowledge globally using internet. The study highlights the current use of social media tools for promoting library and information services of Library and Information Professionals of India, which are working in Library. The study was conducted during November, 2017. A structured questionnaire was prepared using google docs and shared using different mailing list, sent to individual email IDs and sharing with other social media tools. Only 90 responses received from the different states of India and analyzed via MS-Excel. The data receive from 17 states and 3 union territories of India; however most of the respondents has come from the states Odisha 23, Himachal Pradesh 14 and Assam 10. The results revealed that out 90 respondents 37 Female and 53 male categories and also majority of respondents 71 have come from academic library followed by special library 15, Public library 3 and corporate library 1 respondent. The study indicates that, out of 90 respondent’s majority of 53 of respondents said that their Library have a social media account while 39 of respondents have not their Library social media account. The study also inform that Facebook, YouTube, Google+, LinkedIn, Twitter and Instagram are using by the LIS professional of India and Facebook 86 was popular social media tool among the other social media tools. Furthermore, respondent reported that they are using social media tools for sharing photos of events and programs of library 72, followed by tips for using different services 64, posting of new arrivals 56, tutorials of database 35 and send brief updates to patrons 32, announcement of library holidays 22. It was also reported by respondents that they are sharing information about scholarships training programs and marketing of library events etc. The study furthermore identify that lack of time is the major problem while using social media with 53 of respondents followed by low speed of internet 35, too many social media tools to learn 17 and some 3 respondents reported that there is no problem while using social media tools. The results also revealed that, majority of the respondents reported that they are using social media tools in daily basis 71 followed by weekly basis 16. It was followed by monthly 1 respondent and other 2 of the respondents. In summary, this study is expected to be useful in further promoting the social media for dissemination of library and information services to the general public.

Keywords: application of social media, India, promoting library services, library professionals

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Authors: Sheng Yu Chen, Shi-Heng Wang

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Aim: Based on human, animal experiments, and genetic studies, cysteinyl leukotrienes, LTC4, LTD4, and LTE4, are inflammatory substances that are metabolized by 5-lipooxygenase from arachidonic acid, and these substances trigger asthma. In addition, the synthetic pathway of cysteinyl leukotriene is relevant to the increase in cardiovascular diseases such as myocardial ischemia and stroke. Given the situation, we aim to investigate whether cysteinyl leukotrienes receptor antagonist (LTRA), montelukast which cures those who have asthma has potential protective effects on cardiovascular diseases. Method: We conducted a cohort study, and enrolled participants which are newly diagnosed with asthma (ICD-9 CM code 493. X) between 2002 to 2011. The data source is from Taiwan National Health Insurance Research Database Patients with a previous history of myocardial infarction or ischemic stroke were excluded. Among the remaining participants, every montelukast user was matched with two randomly non-users by sex, and age. The incident cardiovascular diseases, including myocardial infarction and ischemic stroke, were regarded as outcomes. We followed the participants until outcomes come first or the end of the following period. To explore the protective effect of montelukast on the risk of cardiovascular disease, we use multivariable Cox regression to estimate the hazard ratio with adjustment for potential confounding factors. Result: There are 55876 newly diagnosed asthma patients who had at least one claim of inpatient admission or at least three claims of outpatient records. We enrolled 5350 montelukast users and 10700 non-users in this cohort study. The following mean (±SD) time of the Montelukast group is 5 (±2.19 )years, and the non-users group is 6.2 5.47 (± 2.641) years. By using multivariable Cox regression, our analysis indicated that the risk of incident cardiovascular diseases between montelukast users (n=43, 0.8%) and non-users (n=111, 1.04%) is approximately equal. [adjusted hazard ratio 0.992; P-value:0.9643] Conclusion: In this population-based study, we found that the use of montelukast is not associated with a decrease in incident MI or IS.

Keywords: asthma, inflammation, montelukast, insurance research database, cardiovascular diseases

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Authors: Siveshnee Devar

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Background: The rate of absenteeism and prevalence of NCDs in South Africa is extremely high. This is consistent with other educational institutions and workplaces around the globe. In most cases the absence of health and the presence of one or more non communicable diseases coupled with the lack of physical exercise is a major factor in absenteeism. Absenteeism at the workplace comes at a huge cost to the employer and the country as a whole. Aim: Findings from this study was to develop a suitable nutritional wellness program for the workplace. Methodology: A needs analysis in the form of 24-hour recall, food frequency, health and socio demographic questionnaires was undertaken to determine the need for a wellness program for the institution. Anthropometric indices such as BMI, waist circumference and blood pressure were also undertaken to determine the state of health of the staff. Results: This study has found that obesity, central obesity, hypertension as well as deficiencies in nutrients and minerals were prevalent in this group. Fruit and vegetable consumption was also below the WHO recommendation. This study showed a link between diet, physical activity and diseases of lifestyle. There were positive correlations between age and systolic blood pressure, waist circumference and systolic blood pressure, waist circumference and diastolic blood pressure and waist-to-height ratio and BMI. Conclusion: The results indicated the need for immediate intervention in the form of a wellness program. Nutrition education is important for both the workplace and out. Education and knowledge are important factors for lifestyle changes. The proposed intervention is aimed at improving presenteeism and decreasing the incidence of non- communicable diseases. Presenteeism and good health are important factors for quality education at all educational institutions.

Keywords: absenteeism, non-communicable diseases, nutrition, wellness

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Authors: Arunporn Itharat, Kamonmas Srikwan, Srisopa Ruangnoo, Pakakrong Thongdeeying

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Background: The rhizomes of Smilax glabra (SG) has long been used in Traditional Chinese and Thai herbal medicine to treat a variety of infectious diseases and immunological disorders. Objective: To investigate the in vitro anti-allergic activities of crude extracts and pure isolated flavonoid compounds from SG by determination of inhibitory effects on antigen-induced release of β-hexosaminidase from RBL-2H3 cells. Methods: The in vitro inhibitory effects of crude aqueous and organic extracts on beta-hexosaminidase release in RBL-2H3 cells were evaluated as an in vitro indication of possible anti-allergic activity in vivo. Bioassay-guided fractionation of extracts was used to isolate flavonoid compounds from the ethanolic extracts. Results: The 95% and 50% ethanolic extracts of SG showed remarkably high anti-allergic activity, with IC50 values of 5.74 ± 2.44 and 23.54 ± 4.75 μg/ml, much higher activity than that for Ketotifen (IC50 58.90 μM). The water extract had negligible activity (IC50 > 100 μg/ml). The two isolated flavonols, Engeletin and Astilbin, showed weak anti-allergic activity, IC50 values 97.46 ± 2.04 and > 100 μg/ml, respectively. Conclusions: The 95% and 50% ethanolic extracts of SG showed strong anti-allergic activity but two flavonol constituents did not show any significant anti-allergic activity. These findings suggest that a combination of effects of various phytochemicals in crude extracts used in traditional medicine are responsible for the purported anti-allergic activity of SG herbal preparations. The plethora of constituents in crude extracts, as yet unidentified, are likely to be acting synergistically to account for the strong observed anti-allergic in vitro activity.

Keywords: Smilax glabra, anti-allergic activity, RBL-2H3 cells, flavonoid compounds

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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: Jane Oliver, Angeline Ferdinand, Jessica Kaufman, Peta Edler, Nicole Allard, Margie Danchin, Katherine B. Gibney

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Background: The cohealth Health Concierge program operated in Melbourne, Australia, from July 2020 to 30 June 2022. The program was designed to provide place-based peer-to-peer COVID-19 education and support to culturally and linguistically diverse residents of high-rise public housing estates. During this time, the COVID-19 public health response changed frequently. We conducted a mixed-methods evaluation to determine the program’s impact on residents’ trust, engagement and communication with health services and public health activities. Methods: The RE-AIM model was used to assess program reach, effectiveness, adoption, implementation and maintenance and the evaluation was informed by a Project Reference Group including end-users. Data were collected between March and May 2022 in four estates where the program operated. We surveyed 301 residents, conducted qualitative interviews with 32 stakeholders and analyzed data from 20,901 forms reporting interactions between Health Concierges and residents collected from August 2021 to May 2022. These forms outlined the support provided by Health Concierges during each interaction. Results: Overall, the program was effective in guiding residents to testing and vaccination services and facilitating COVID-19 safe practices. Nearly two-thirds (191; 63.5%) of the 301 surveyed participants reported speaking with a Health Concierge in the previous six months, and some described having meaningful conversations with them. Despite this, many of the interactions residents described having with Health Concierges were superficial. When considering surveyed participants’ responses to the adapted Public Health Disaster Trust Scale, the mean score across all estates was 2.3 (or slightly more than ‘somewhat confident’) in public health authorities’ ability to respond to a localized infectious disease outbreak. While the program was valued during the rapidly changing public health response, many felt it had failed to evolve in the ‘living with COVID’ phase. Some residents expressed frustration with Health Concierges’ having perceived inactive, passive roles - although other residents felt Health Concierges were helpful and appreciated them. A perception that the true impact of Health Concierges’ work was underrecognized was widely voiced by health staff. All 20,901 Interaction Forms identified COVID-19-related supports provided to residents; almost all included provision of facemasks and/or hand sanitiser and 78% identified additional supports that were also provided, most frequently provision of other health information. Conclusions: The program disseminated up-to-date information to a diverse population within a rapidly changing public health setting. Health Concierges were able promote COVID-19-safe behaviours, including vaccine uptake, and link residents with support services. We recommend the program be revised and continued. New programs that draw on the Health Concierge model may be valuable in supporting future pandemic responses and should be considered in preparedness planning.

Keywords: community health, COVID-19 pandemic, infectious diseases, public health, community health workers

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Authors: Kunal Garg, Louise Theusen Hermansan, Kanoktip Puttaraska, Oliver Hendricks, Heidi Pirttinen, Leona Gilbert

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The Germ Theory (one infectious determinant is equal to one disease) has unarguably evolved our capability to diagnose and treat infectious diseases over the years. Nevertheless, the advent of technology, climate change, and volatile human behavior has brought about drastic changes in our environment, leading us to question the relevance of the Germ Theory in our day, i.e. will vector-borne disease (VBD) sufferers produce multiple immune responses when tested for multiple microbes? Vector diseased patients producing multiple immune responses to different microbes would evidently suggest human polymicrobial infections (HPI). Ongoing diagnostic tools are exceedingly unequipped with the current research findings that would aid in diagnosing patients for polymicrobial infections. This shortcoming has caused misdiagnosis at very high rates, consequently diminishing the patient’s quality of life due to inadequate treatment. Equipped with the state-of-art scientific knowledge, PolyScan intends to address the pitfalls in current VBD diagnostics. PolyScan is a multiplex and multifunctional enzyme linked Immunosorbent assay (ELISA) platform that can test for numerous VBD microbes and allow simultaneous screening for multiple types of antibodies. To validate PolyScan, Lyme Borreliosis (LB) and spondyloarthritis (SpA) patient groups (n = 54 each) were tested for Borrelia burgdorferi, Borrelia burgdorferi Round Body (RB), Borrelia afzelii, Borrelia garinii, and Ehrlichia chaffeensis against IgM and IgG antibodies. LB serum samples were obtained from Germany and SpA serum samples were obtained from Denmark under relevant ethical approvals. The SpA group represented chronic LB stage because reactive arthritis (SpA subtype) in the form of Lyme arthritis links to LB. It was hypothesized that patients from both the groups will produce multiple immune responses that as a consequence would evidently suggest HPI. It was also hypothesized that the multiple immune response proportion in SpA patient group would be significantly larger when compared to the LB patient group across both antibodies. It was observed that 26% LB patients and 57% SpA patients produced multiple immune responses in contrast to 33% LB patients and 30% SpA patients that produced solitary immune responses when tested against IgM. Similarly, 52% LB patients and an astounding 73% SpA patients produced multiple immune responses in contrast to 30% LB patients and 8% SpA patients that produced solitary immune responses when tested against IgG. Interestingly, IgM immune dysfunction in both the patient groups was also recorded. Atypically, 6% of the unresponsive 18% LB with IgG antibody was recorded producing multiple immune responses with the IgM antibody. Similarly, 12% of the unresponsive 19% SpA with IgG antibody was recorded producing multiple immune responses with the IgM antibody. Thus, results not only supported hypothesis but also suggested that IgM may atypically prevail longer than IgG. The PolyScan concept will aid clinicians to detect patients for early, persistent, late, polymicrobial, & immune dysfunction conditions linked to different VBD. PolyScan provides a paradigm shift for the VBD diagnostic industry to follow that will drastically shorten patient’s time to receive adequate treatment.

Keywords: diagnostics, immune dysfunction, polymicrobial, TICK-TAG

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Authors: Janneth González, George Barreto, Ludis Morales, Angélica Sabogal

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Sea anemone neurotoxins are peptides that interact with Na+ and K+ channels, resulting in specific alterations on their functions. Some of these neurotoxins (1ROO, 1BGK, 2K9E, 1BEI) are important for the treatment of nearly eighty autoimmune disorders due to their specificity for Kv1.3 channel. The aim of this study was to identify the common residues among these neurotoxins by computational methods, and establish whether there is a pattern useful for the future generation of a treatment for autoimmune diseases. Our results showed eight new key common residues between the studied neurotoxins interacting with a histidine ring and the selectivity filter of the receptor, thus showing a possible pattern of interaction. This knowledge may serve as an input for the design of more promising drugs for autoimmune treatments.

Keywords: neurotoxins, potassium channel, Kv1.3, computational methods, autoimmune diseases

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