Search results for: disease specific genes

Authors: Abdirahman Barre, Abdihamid Salad Hassan, Iftin Abdi Mohamud, Abdirahman Mohamed Mohamud, Ahmed Adan Mohamed, Mukhtaar Mohamed Idow

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Pasteurellosis (Hemorrhagic septicemia) is a common respiratory disease of camel that is an acutely fatal disease caused by Pasteurella multocida type A or several serotypes of Mannheimia hemolytic, which also affect other animals. The disease had shown to spread between animals, across herds and to humans. Meaning that the disease is Zoonosis. The study aimed at establishment of sero-prevalence of Pasteurellosis in some selected Districts of camel rearing in the Benadir Region. It was a cross-sectional study, where the study population was purposively chosen to consist of animals taken within three sub-Districts of Benadir Region, namely Sub-District (Daynile Township), Sub-District (Yaaqshid) Sub-District (kaxda). This was because they normally handle many camels in a day, thus making it easy for the investigator to access the required number conveniently; it was also assumed that data collected from these for-slaughter camels was representative of the situation in the sub-District/county. A total of one hundred and sixty camels were tested using four serological tests: Rose Bengal Plate Test (RBPT),) and Complex Fixation Test (CFT). The serological tests were purposively chosen to increase the chances of picking positive cases and also to compare their sensitivities with respect to camel serum since they were originally meant for use on bovine serum. Blood samples (15 ml) were collected for serum harvesting from the jugular veins of the animals as they were waiting to be examined. Rose Bengal plate test and CFT were run at a laboratory within the Department of Veterinary Medicine, University of Horsed, 21 October campus; serum samples having been transported in a cool box. On average, out of an overall total of 300 serum samples tested, 180 samples were selected as sample procedures and were given eleven (11) positive results, amounting to a prevalence of 6.67%. For the three Districts, respective prevalence (averaged from the two (2) serological tests run) were: 7% (3/50) for Yaqshiid; 8% (3/60) for Deyniile and 10% (3/70) for Kaxda. When sensitivities of the two (2) serological tests were compared, there was no significant difference between them with respect to the picking of positive cases (p=0.05). The study has demonstrated presence of Pasterolosis in camels in Benadir Region and the authors are recommending the usage of RBPT and CFT as screening tests, since they are cheap, quick, and easy to carry out. Any of the other three involving tests can then be used if one wants to establish respective titers. Therefore, further detailed investigation needs to be conducted so as to understand specific etiological agents causing pasteurollosis in camel and can be instituted to optimize the benefit obtained from the camel sector.

Keywords: hemorrhagic septicemia, camel, prevalence, Benadir region, Somalia

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Authors: Mina Jafari, Kobra Hamraee, Saied Hossein Hosseini

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The prediction of breast cancer disease is one of the challenges in medicine. In this paper we collected 528 records of women’s information who live in Kabul including demographic, life style, diet and pregnancy data. There are many classification algorithm in breast cancer prediction and tried to find the best model with most accurate result and lowest error rate. We evaluated some other common supervised algorithms in data mining to find the best model in prediction of breast cancer disease among afghan women living in Kabul regarding to momography result as target variable. For evaluating these algorithms we used Cross Validation which is an assured method for measuring the performance of models. After comparing error rate and accuracy of three models: Decision Tree, Naive Bays and Rule Induction, Decision Tree with accuracy of 94.06% and error rate of %15 is found the best model to predicting breast cancer disease based on the health care records.

Keywords: decision tree, breast cancer, probability, data mining

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Authors: Dwarika P. Shrestha, Dipendra Gurung, Rushma Shrestha, Inger Rosdahl

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Introduction: Skin diseases are one of the most common health problems in Nepal. The objectives of this study are to determine the prevalence of skin diseases and impact on quality of life in rural areas in Nepal. Materials and methods: A house-to-house survey was conducted, to obtain socio-demographic data and identify individuals with skin diseases, followed by health camps, where the villagers were examined. A pilot study was conducted in one village, which was then extended to 10 villages in 4 districts. To assess the impact on quality of life, the villagers were interviewed with Skin Disease Disability Index. This is a questionnaire developed and validated by the authors for use in Nepal. Results: In the pilot study, the overall prevalence of skin diseases was 20.1% (645/3207). In the additional 10 villages with 7348 (3651/3787 m/f) inhabitants, 1862 (721/1141 m/f, mean age 31.4 years) had one or more skin diseases. The overall prevalence of skin diseases was 25%. The most common skin disease categories were eczemas (13.7%, percentage among all inhabitants) pigment disorders (6.8%), fungal infections (4.9%), nevi (3.7%) and urticaria (2.9%). These five most common skin disease categories comprise 71% of all skin diseases seen in the study. The mean skin disease disability index score was 13.7, indicating very large impact on the quality of life. Conclusions: This population-based study shows that skin diseases are very common in the rural areas of Nepal and have significant impact on quality of life. Targeted intervention at the primary health care level should help to reduce the health burden due to skin diseases.

Keywords: prevalence and pattern of skin diseases, impact on quality of life, rural Nepal, interventions

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Authors: Berengere Vire, Nicolas Salvetat, Yoann Lannay, Guillaume Marcellin, Siem Van Der Laan, Franck Molina, Dinah Weissmann

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Predicting suicidal behaviors is one of the most complex challenges of daily psychiatric practices. Today, suicide risk prediction using biological tools is not validated and is only based on subjective clinical reports of the at-risk individual. Therefore, there is a great need to identify biomarkers that would allow early identification of individuals at risk of suicide. Alterations of adenosine-to-inosine (A-to-I) RNA editing of neurotransmitter receptors and other proteins have been shown to be involved in etiology of different psychiatric disorders and linked to suicidal behavior. RNA editing is a co- or post-transcriptional process leading to a site-specific alteration in RNA sequences. It plays an important role in the epi transcriptomic regulation of RNA metabolism. On postmortem human brain tissue (prefrontal cortex) of depressed suicide victims, Alcediag found specific alterations of RNA editing activity on the mRNA coding for the serotonin 2C receptor (5-HT2cR). Additionally, an increase in expression levels of ADARs, the RNA editing enzymes, and modifications of RNA editing profiles of prime targets, such as phosphodiesterase 8A (PDE8A) mRNA, have also been observed. Interestingly, the PDE8A gene is located on chromosome 15q25.3, a genomic region that has recurrently been associated with the early-onset major depressive disorder (MDD). In the current study, we examined whether modifications in RNA editing profile of prime targets allow identifying disease-relevant blood biomarkers and evaluating suicide risk in patients. To address this question, we performed a clinical study to identify an RNA editing signature in blood of depressed patients with and without the history of suicide attempts. Patient’s samples were drawn in PAXgene tubes and analyzed on Alcediag’s proprietary RNA editing platform using next generation sequencing technology. In addition, gene expression analysis by quantitative PCR was performed. We generated a multivariate algorithm comprising various selected biomarkers to detect patients with a high risk to attempt suicide. We evaluated the diagnostic performance using the relative proportion of PDE8A mRNA editing at different sites and/or isoforms as well as the expression of PDE8A and the ADARs. The significance of these biomarkers for suicidality was evaluated using the area under the receiver-operating characteristic curve (AUC). The generated algorithm comprising the biomarkers was found to have strong diagnostic performances with high specificity and sensitivity. In conclusion, we developed tools to measure disease-specific biomarkers in blood samples of patients for identifying individuals at the greatest risk for future suicide attempts. This technology not only fosters patient management but is also suitable to predict the risk of drug-induced psychiatric side effects such as iatrogenic increase of suicidal ideas/behaviors.

Keywords: blood biomarker, next-generation-sequencing, RNA editing, suicide

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Authors: Usama Ahmed

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Data mining is the process of analyze data which are used to predict helpful information. It is the field of research which solve various type of problem. In data mining, classification is an important technique to classify different kind of data. Diabetes is most common disease. This paper implements different classification technique using Waikato Environment for Knowledge Analysis (WEKA) on diabetes dataset and find which algorithm is suitable for working. The best classification algorithm based on diabetic data is Naïve Bayes. The accuracy of Naïve Bayes is 76.31% and take 0.06 seconds to build the model.

Keywords: data mining, classification, diabetes, WEKA

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Authors: Kayode Ilesanmi Ebenezer Bowale, Dominic Azuh, Busayo Aderounmu, Alfred Ilesanmi

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There has been a debate among scholars and policymakers about the effects of oil exploration and production on industrial development. In Nigeria, there were many reforms resulting in an increase in crude oil production in the recent past. There is a controversy on the importance of oil production in the development of the manufacturing sector in Nigeria. Some scholars claim that oil has been a blessing to the development of the manufacturing sector, while others regard it as a curse. The objective of the study is to determine if empirical analysis supports the presence of Dutch Disease and de-industrialisation in the Nigerian manufacturing sector between 2019- 2022. The study employed data that were sourced from World Development Indicators, Nigeria Bureau of Statistics, and the Central Bank of Nigeria Statistical Bulletin on manufactured exports, manufacturing employment, agricultural employment, and service employment in line with the theory of Dutch Disease using the unit root test to establish their level of stationarity, Engel and Granger cointegration test to check their long-run relationship. Autoregressive. Distributed Lagged bound test was also used. The Vector Error Correction Model will be carried out to determine the speed of adjustment of the manufacturing export and resource movement effect. The results showed that the Nigerian manufacturing industry suffered from both direct and indirect de-industrialisation over the period. The findings also revealed that there was resource movement as labour moved away from the manufacturing sector to both the oil sector and the services sector. The study concluded that there was the presence of Dutch Disease in the manufacturing industry, and the problem of de-industrialisation led to the crowding out of manufacturing output. The study recommends that efforts should be made to diversify the Nigerian economy. Furthermore, a conducive business environment should be provided to encourage more involvement of the private sector in the agriculture and manufacturing sectors of the economy.

Keywords: Dutch disease, resource movement, manufacturing sector performance, Nigeria

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Authors: Pejman Taghibeikzadehbadr

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Muscle contraction stimulates a transient change of myogenic factors, partly related to the mode of contractions. Here, we assessed the response of Insulin-like growth factor 1Ea (IGF-1Ea), Insulin-like growth factor 1Eb (IGF-1Eb), Insulin-like growth factor 1Ec (IGF-1Ec), Peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC1α-1), Peroxisome proliferator-activated receptor gamma coactivator 4-alpha (PGC1α-4), and myostatin to the eccentric Vs the concentric contraction in human skeletal muscle. Ten healthy males were performed an acute eccentric and concentric exercise bout (n = 5 per group). For each contraction type, participants performed 12 sets of 10 repetitions knee extension by the dominant leg. Baseline and post-exercise muscle biopsy were taken 4 weeks before and immediately after experimental sessions from Vastus Lateralis muscle. Genes expression was measured by real-time PCR technique. There was a significant increase in PGC1α-1, PGC1α-4, IGF-1Ea and, IGF-1Eb mRNA after concentric contraction (p ≤ 0.05), while the PGC1α-4 and IGF-1Ec significantly increased after eccentric contraction (p ≤ 0.05). It is intriguing to highlight that; no significant differences between groups were evident for changes in any variables following exercise bouts (p ≥ 0.05). Our results found that concentric and eccentric contractions presented different responses in PGC1α-1, IGF-1Ea, IGF-1Eb, and IGF-1Ec mRNA. However, a similar significant increase in mRNA content was observed in PGC1α-4. Further, no apparent differences could be found between the response of genes to eccentric and concentric contraction.

Keywords: eccentric contraction, concentric contraction, gene expression, PGC-1 alpha, IGF-1 Myostatin

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Authors: John Hawkins, Graham Burton

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Contextual targeting is a common strategy for advertising that places marketing messages in media locations that are expected to be aligned with the target audience. There are multiple major challenges to contextual targeting: the ideal categorisation scheme needs to be known, as well as the most appropriate subsections of that scheme for a given campaign or creative. In addition, the campaign reach is typically limited when targeting becomes narrow, so a balance must be struck between requirements. Finally, refinement of the process is limited by the use of evaluation methods that are either rapid but non-specific (click through rates), or reliable but slow and costly (conversions or brand recall studies). In this study we evaluate the use of attention measurement as a technique for understanding the performance of targeting on the basis of specific contextual topics. We perform the analysis using a large scale dataset of impressions categorised using the iAB V2.0 taxonomy. We evaluate multiple levels of the categorisation hierarchy, using categories at different positions within an initial creative specific ranking. The results illustrate that measuring attention time is an affective signal for the performance of a specific creative within a specific context. Performance is sustained across a ranking of categories from one period to another.

Keywords: contextual targeting, digital advertising, attention measurement, marketing performance

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Authors: Thota Sai Prakash, B. Yaswanth, Jhade Bhuvaneswar, Marreddy Divakar Reddy, Shyam Ji Gupta

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Across the globe, there are a lot of chronic diseases, and heart disease stands out as one of the most perilous. Sadly, many lives are lost to this condition, even though early intervention could prevent such tragedies. However, identifying heart disease in its initial stages is not easy. To address this challenge, we propose an automated system aimed at predicting the presence of heart disease using advanced techniques. By doing so, we hope to empower individuals with the knowledge needed to take proactive measures against this potentially fatal illness. Our approach towards this problem involves meticulous data preprocessing and the development of predictive models utilizing classification algorithms such as Support Vector Machines (SVM), Decision Tree, and Random Forest. We assess the efficiency of every model based on metrics like accuracy, ensuring that we select the most reliable option. Additionally, we conduct thorough data analysis to reveal the importance of different attributes. Among the models considered, Random Forest emerges as the standout performer with an accuracy rate of 96.04% in our study.

Keywords: support vector machines, decision tree, random forest

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Authors: Tomas Premoli, Sareh Rowlands

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In this study, we investigate the impact of various convolutional neural network (CNN) architectures on the accuracy of diagnosing Alzheimer’s disease (AD) using patient MRI scans. Alzheimer’s disease is a debilitating neurodegenerative disorder that affects millions worldwide. Early, accurate, and non-invasive diagnostic methods are required for providing optimal care and symptom management. Deep learning techniques, particularly CNNs, have shown great promise in enhancing this diagnostic process. We aim to contribute to the ongoing research in this field by comparing the effectiveness of different CNN architectures and providing insights for future studies. Our methodology involved preprocessing MRI data, implementing multiple CNN architectures, and evaluating the performance of each model. We employed intensity normalization, linear registration, and skull stripping for our preprocessing. The selected architectures included VGG, ResNet, and DenseNet models, all implemented using the Keras library. We employed transfer learning and trained models from scratch to compare their effectiveness. Our findings demonstrated significant differences in performance among the tested architectures, with DenseNet201 achieving the highest accuracy of 86.4%. Transfer learning proved to be helpful in improving model performance. We also identified potential areas for future research, such as experimenting with other architectures, optimizing hyperparameters, and employing fine-tuning strategies. By providing a comprehensive analysis of the selected CNN architectures, we offer a solid foundation for future research in Alzheimer’s disease diagnosis using deep learning techniques. Our study highlights the potential of CNNs as a valuable diagnostic tool and emphasizes the importance of ongoing research to develop more accurate and effective models.

Keywords: Alzheimer’s disease, convolutional neural networks, deep learning, medical imaging, MRI

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Authors: Tatiana Butkova, Nikolai Kibrik, Kristina Malsagova, Alexander Izotov, Alexander Stepanov, Anna Kaysheva

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Relevance. The genetic risk of developing schizophrenia is determined by two factors: single nucleotide polymorphisms and gene copy number variations. The search for serological markers for early diagnosis of schizophrenia is driven by the fact that the first five years of the disease are accompanied by significant biological, psychological, and social changes. It is during this period that pathological processes are most amenable to correction. The aim of this study was to analyze single nucleotide polymorphisms (SNPs) that are hypothesized to potentially influence the onset and development of the endogenous process. Materials and Methods It was analyzed 73 single nucleotide polymorphism variants. The study included 48 patients undergoing inpatient treatment at "Psychiatric Clinical Hospital No. 1" in Moscow, comprising 23 females and 25 males. Inclusion criteria: - Patients aged 18 and above. - Diagnosis according to ICD-10: F20.0, F20.2, F20.8, F21.8, F25.1, F25.2. - Voluntary informed consent from patients. Exclusion criteria included: - The presence of concurrent somatic or neurological pathology, neuroinfections, epilepsy, organic central nervous system damage of any etiology, and regular use of medication. - Substance abuse and alcohol dependence. - Women who were pregnant or breastfeeding. Clinical and psychopathological assessment was complemented by psychometric evaluation using the PANSS scale at the beginning and end of treatment. The duration of observation during therapy was 4-6 weeks. Total DNA extraction was performed using QIAamp DNA. Blood samples were processed on Illumina HiScan and genotyped for 652,297 markers on the Infinium Global Chips Screening Array-24v2.0 using the IMPUTE2 program with parameters Ne=20,000 and k=90. Additional filtration was performed based on INFO>0.5 and genotype probability>0.5. Quality control of the obtained DNA was conducted using agarose gel electrophoresis, with each tested sample having a volume of 100 µL. Results. It was observed that several SNPs exhibited gender dependence. We identified groups of single nucleotide polymorphisms with a membership of 80% or more in either the female or male gender. These SNPs included rs2661319, rs2842030, rs4606, rs11868035, rs518147, rs5993883, and rs6269.Another noteworthy finding was the limited combination of SNPs sufficient to manifest clinical symptoms leading to hospitalization. Among all 48 patients, each of whom was analyzed for deviations in 73 SNPs, it was discovered that the combination of involved SNPs in the manifestation of pronounced clinical symptoms of schizophrenia was 19±3 out of 73 possible. In study, the frequency of occurrence of single nucleotide polymorphisms also varied. The most frequently observed SNPs were rs4849127 (in 90% of cases), rs1150226 (86%), rs1414334 (75%), rs10170310 (73%), rs2857657, and rs4436578 (71%). Conclusion. Thus, the results of this study provide additional evidence that these genes may be associated with the development of schizophrenia spectrum disorders. However, it's impossible cannot rule out the hypothesis that these polymorphisms may be in linkage disequilibrium with other functionally significant polymorphisms that may actually be involved in schizophrenia spectrum disorders. It has been shown that missense SNPs by themselves are likely not causative of the disease but are in strong linkage disequilibrium with non-functional SNPs that may indeed contribute to disease predisposition.

Keywords: gene polymorphisms, genotyping, single nucleotide polymorphisms, schizophrenia.

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Authors: Micheale Yifter Weldemichael

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Sesame (Sesamum indicum L.) is among the most important oilseed crops for its high edible oil quality and quantity. Sesame is grown for food, medicinal, pharmaceutical, and industrial uses. Sesame is also cultivated as a main cash crop in Asia and Africa by smallholder farmers. Despite the global exponential increase in sesame cultivation area, its production and productivity remain low, mainly due to biotic and abiotic constraints. Notwithstanding the efforts to solve these problems, a low level of genetic variation and inadequate genomic resources hinder the progress of sesame improvement. The objective of this paper is, therefore, to review recent advances in the area of molecular breeding and transformation to overcome major production constraints and could result in enhanced and sustained sesame production. This paper reviews various researches conducted to date on molecular breeding and genetic transformation in sesame focusing on molecular markers used in assessing the available online database resources, genes responsible for key agronomic traits as well as transgenic technology and genome editing. The review concentrates on quantitative and semi-quantitative studies on molecular breeding for key agronomic traits such as improvement of yield components, oil and oil-related traits, disease and insect/pest resistance, and drought, waterlogging and salt tolerance, as well as sesame genetic transformation and genome editing techniques. Pitfalls and limitations of existing studies and methodologies used so far are identified and some priorities for future research directions in sesame genetic improvement are identified in this review.

Keywords: abiotic stress, biotic stress, improvement, molecular breeding, oil, sesame, shattering

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Authors: Abdollah Sobhani, Hossein Vaseghi-Dodaran

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Proteomics is defined as the study of the component of a cell, tissue and biological fluid. This technique has the potential to identify protein biomarkers of a disease states. In this study which was performed on bovine ovarian follicular cysts (BOFC), eight proteins are over expressed in BOFC that these proteins could be useful biomarkers for BOFC. The difference between serum proteome pattern cows affected by postpartum endometritis with healthy cows revealed that concentrations orosomucoid was decreased in endometritis. The comparison proteome of brucella abortus between laboratory adapted strains and clinical isolates could be useful to better understand this disease and vaccine development. Proteomics experiments identified new proteins and pathways that may be important in future hypothesis-driven studies of glucocorticoid-induced immunosuppression. Understanding the molecular mechanisms of effective parameters on male fertility is essential for obtaining high reproductive efficiency by decreasing cost and time. The investigations on proteome of high fertility spermatozoa indicated that expression of some proteins such as casein kinase 2 (CKII) prime poly peptide and tyrosine kinase in high fertility spermatozoa was higher compared to low fertility spermatozoa. Also, some evidence has indicated that variation in protein types and amounts in seminal fluid regulates fertility indexes in dairy bull. In conclusion, proteomics is a useful technique for discovering drugs, vaccine development, and diagnosis disease by biomarkers and improvement of reproduction efficiency.

Keywords: proteomics, reproduction, biomarker, immunity

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Authors: Kanika Gupta, Ashok Kumar

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Biofilms are dense, highly hydrated cell clusters that are irreversibly attached to a substratum, to an interface or to each other, and are embedded in a self-produced gelatinous matrix composed of extracellular polymeric substances. Research in biofilm field has become very significant, as biofilm has shown high mechanical resilience and resistance to antibiotic treatment and constituted as a significant problem in both healthcare and other industry related to microorganisms. The massive information both stated and hidden in the biofilm literature are growing exponentially therefore it is not possible for researchers and practitioners to automatically extract and relate information from different written resources. So, the current work proposes and discusses the use of text mining techniques for the extraction of information from biofilm literature corpora containing 34306 documents. It is very difficult and expensive to obtain annotated material for biomedical literature as the literature is unstructured i.e. free-text. Therefore, we considered unsupervised approach, where no annotated training is necessary and using this approach we developed a system that will classify the text on the basis of growth and development, drug effects, radiation effects, classification and physiology of biofilms. For this, a two-step structure was used where the first step is to extract keywords from the biofilm literature using a metathesaurus and standard natural language processing tools like Rapid Miner_v5.3 and the second step is to discover relations between the genes extracted from the whole set of biofilm literature using pubmed.mineR_v1.0.11. We used unsupervised approach, which is the machine learning task of inferring a function to describe hidden structure from 'unlabeled' data, in the above-extracted datasets to develop classifiers using WinPython-64 bit_v3.5.4.0Qt5 and R studio_v0.99.467 packages which will automatically classify the text by using the mentioned sets. The developed classifiers were tested on a large data set of biofilm literature which showed that the unsupervised approach proposed is promising as well as suited for a semi-automatic labeling of the extracted relations. The entire information was stored in the relational database which was hosted locally on the server. The generated biofilm vocabulary and genes relations will be significant for researchers dealing with biofilm research, making their search easy and efficient as the keywords and genes could be directly mapped with the documents used for database development.

Keywords: biofilms literature, classifiers development, text mining, unsupervised learning approach, unstructured data, relational database

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Authors: I. Ahmad, A. Hannan, S. Ahmad, M. Asif, M. F. Nawaz, M. A. Tanvir, M. F. Azhar

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During this research, a comprehensive survey of tree growing areas of Faisalabad district of Pakistan was conducted to observe the symptoms, spectrum, occurrence and severity of A. nilotica and E. camaldulensis decline. Objective of current research was to investigate specific fungal pathogens involved in decline of A. nilotica and E. camaldulensis. For this purpose, infected roots, bark, neck portion, stem, branches, leaves and infected soils were collected to identify associated fungi. Potato dextrose agar (PDA) and Czepak dox agar media were used for isolations. Identification of isolated fungi was done microscopically and different fungi were identified. During survey of urban locations of Faisalabad, disease incidence on Kikar and Eucalyptus was recorded as 3.9-7.9% and 2.6-7.1% respectively. Survey of Agroforest zones of Faisalabad revealed decline incidence on kikar 7.5% from Sargodha road while on Satiana and Jhang road it was not planted. In eucalyptus trees, 4%, 8% and 0% disease incidence was observed on Jhang road, Sargodha road and Satiana road respectively. The maximum fungus isolated from the kikar tree was Drechslera australiensis (5.00%) from the stem part. Aspergillus flavus also gave the maximum value of (3.05%) from the bark. Alternaria alternata gave the maximum value of (2.05%) from leaves. Rhizopus and Mucor spp. were recorded minimum as compared to the Drechslera, Alternaria and Aspergillus. The maximum fungus isolated from the Eucalyptus tree was Armillaria luteobubalina (5.00%) from the stem part. The other fungi isolated were Macrophamina phaseolina and A. niger.

Keywords: decline, frequency of mycoflora, A. nilotica and E. camaldulensis, Drechslera australiensis, Armillaria luteobubalina

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Authors: Hamdy Khamis Korayem, Manal Yehia Tayel, Abeer Shawky El Hadedy, Emmanuel Kamal Aziz Saba, Shimaa Badr Abdelnaby Badr

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The aim of the current study was to demonstrate whether serum Interleukin-18 (IL-18) is increased in rheumatoid arthritis (RA) and its correlation with disease activity, functional disability and quality of life in RA patients. The study included 30 RA patients and 20 healthy normal control subjects. The RA patients were diagnosed according to the 2010 ACR/EULAR classification criteria for RA with the exclusion of those who had diabetes mellitus, endocrine disorders, associated rheumatologic diseases, viral hepatitis B or C and other diseases with increased serum IL-18 level. All patients were subjected to clinical evaluation of the musculoskeletal system. Disease activity was assessed by disease activity score 28 with 4 variables (DAS 28). Functional disability was assessed by health assessment questionnaire disability index (HAQ-DI). The quality of life was assessed by Short form-36 (SF-36) questionnaire. Radiological assessment of both hands and feet by Sharp/van der Heijde (SvH) scoring method. Laboratory parameters including erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), rheumatoid factor (RF) and anti-cyclic citrullinated peptide antibody (ACPA) were assessed in patients and serum level of IL-18 in both patients and control subjects. There was no statistically significant difference between patient and control group as regards age and sex. Among patients, 29 % were females and the age range was between 25 to 55 years. Extra-articular manifestations were presented in 56.7% of the patients. The mean of DAS 28 score was 5.73±1.46 and that of HAQ-DI was 1.22±0.72 while that of SF-36 was 40.03±13.96. The level of serum IL-18 was significantly higher in patients than in the control subjects (P= 0.030). Serum IL-18 was correlated with ACPA among the patient group. There were no statistically significant correlations between serum IL-18 and DAS28, HAQ-DI, SF-36, total SvH score and the other laboratory results. In conclusion, IL-18 is significantly higher in RA patient than in healthy control subjects and positively correlated with ACPA level. IL-18 is associated with extra-articular manifestations. However, it is not correlated with other laboratory parameters, disease activity, functional disability, quality of life nor radiological severity.

Keywords: disease activity score, Interleukin-18, quality of life assessment, rheumatoid arthritis

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Authors: E. N. Hasanov, K. Y. Yusifova, M. A. Ali

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Rabies is a zoonotic disease that causes acute encephalitis in domestic and wild carnivores. The goal of our investigation was to analyze the data on oral vaccination of wild canids and stray dogs in Azerbaijan. Before the start of the vaccination campaign conducted by the International Dialogue for Environmental Action (IDEA) Animal Care Center (IACC), all rabies cases in Azerbaijan for the period of 2017-2020 were analyzed. So, 30 regions for oral immunization with the Rabadrop vaccine were selected. In total, 95.9 thousand doses of baits were scattered in 30 regions, 970 (0.97%) remained intact. In addition, a campaign to sterilize and vaccinate stray dogs and cats undoubtedly had a positive impact on reducing the dynamics of rabies incidence. During the period 2017-2020, 2339 dogs and 2962 cats were sterilized and vaccinated under this program. It can be noted that the risk of rabies infection can be reduced through special preventive measures against disease reservoirs, which include oral immunization of wild and stray animals.

Keywords: rabies, vaccination, oral immunization, wild canids, stray dogs, baits, disease reservoirs

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Authors: C. Andreu Sabater, D. Drago, C. Key-aberg, W. Moukrim, B. Naccache

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Present study concerns the optimization of a new vertical axis wind turbine system associated to a dynamoelectric motor. The system is composed by three Savonius wind turbines, arranged in an equilateral triangle. The idea is to propose a new concept of wind turbines through a technical approach allowing find a specific power never obtained before and therefore, a significant reduction of installation costs. In this work different wind flows across the system have been simulated, as well as precise definition of parameters and relations established between them. It will allow define the optimal rotor specific power for a given volume. Calculations have been developed with classical Savonius dimensions.

Keywords: VAWT, savonius, specific power, optimization, weibull

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Authors: A. K. Putri, A.Fitri, C. A. Batubara

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Diabetes Mellitus (DM) is a chronic disease that could cause complications. The complication can be Peripheral Arterial Disease (PAD) or Diabetic Neuropathy (DN). Peripheral Arterial Disease is checked by Ankle Brachial Index (ABI), DN is checked by Diabetic Neuropathy Examination (DNE) score. To determine the association of ABI and DNE score in DM type 2. This study uses a cross-sectional design. The subjects were DM patients at the neurology and endocrinology polyclinic at Haji Adam Malik Hospital Medan and its network hospital and this study subjects were examined for ABI and DNE scores. The data were analysed using the Fisher Exact statistics test. Demographics characteristic showed most of subject are female (51,6%), age range ≥ 60 (45.2% ; average 57,6 ± 9,8 years ), and history of DM 5-10 years (45,2%). The most patient ABI characteristics were mild PAD (42%) and moderate PAD (29%). The most patient DNE Score characteristics were≥ 3 (51,6%). There’s a significant relationship between ABI and DNE score in DM type 2 (p =0.016). Conclusion: There is a significant association between ABI and DNE scores in DM type 2 patients

Keywords: diabetic neuropathy, diabetes mellitus, ankle-brachial index, diabetic neuropathy examination

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Authors: Peter Burggräf, Moritz Krunke, Hanno Voet

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Due to shortening product and technology lifecycles, many companies use standardization approaches in product development and factory planning to reduce costs and time to market. Unlike large companies, where modular systems are already widely used, small and medium-sized companies often show a much lower degree of standardization due to lower scale effects and missing capacities for the development of these standards. To overcome these challenges, the development of industry sector specific standards in cooperations or by third parties is an interesting approach. This paper analyzes which branches that are mainly dominated by small or medium-sized companies might be especially interesting for the development of factory standards using the example of the German industry. For this, a key performance indicator based approach was developed that will be presented in detail with its specific results for the German industry structure.

Keywords: factory planning, factory standards, industry sector specific standardization, production planning

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Authors: Henry Kuppen

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In the last decade, tree managers have faced many threats of pests and diseases and the effects of climate change. Managers will recognize that they have to put more energy and more money into tree management. By recognizing the cause behind this, the opportunity will arise to build sustainable tree populations for the future. More and more, unwanted larvae are sprayed, ash dieback infected trees are pruned or felled, and emerald ash borer is knocking at the door of West Europe. A lot of specific knowledge is needed to produce management plans and best practices. If pest and disease have a large impact, society loses complete tree species and need to start all over again building urban forest. But looking at the cause behind it, landscape design, and tree species selection, the sustainable solution does not present itself in managing these threats. Every pest or disease needs two important basic ingredients to be successful: climate and food. The changing climate is helping several invasive pathogens to survive. Food is often designed by the landscapers and managers of the urban forest. Monocultures promote the success of pathogens. By looking more closely at the basics, tree managers will realise very soon that the solution will not be the management of pathogens. The long-term solution for sustainable tree populations is a different design of our urban landscape. The use of tree species diversity can help to reduce the impact of climate change and pathogens. Therefore landscapers need to be supported. They are the specialists in designing the landscape using design values like canopy volume, ecosystem services, and seasonal experience. It’s up to the species specialist to show what the opportunities are for different species that meet the desired interpretation of the landscape. Based on landscapers' criteria, selections can be made, including tree species related requirements. Through this collaboration and formation of integral teams, sustainable plant design will be possible.

Keywords: climate change, landscape design, resilient landscape, tree species selection

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Authors: Abobaker Mohammed Qasem Farhan, Shangming Yang, Mohammed Al-Nehari

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Pneumonia is a kind of lung disease that creates congestion in the chest. Such pneumonic conditions lead to loss of life of the severity of high congestion. Pneumonic lung disease is caused by viral pneumonia, bacterial pneumonia, or Covidi-19 induced pneumonia. The early prediction and classification of such lung diseases help to reduce the mortality rate. We propose the automatic Computer-Aided Diagnosis (CAD) system in this paper using the deep learning approach. The proposed CAD system takes input from raw computerized tomography (CT) scans of the patient's chest and automatically predicts disease classification. We designed the Hybrid Deep Learning Algorithm (HDLA) to improve accuracy and reduce processing requirements. The raw CT scans have pre-processed first to enhance their quality for further analysis. We then applied a hybrid model that consists of automatic feature extraction and classification. We propose the robust 2D Convolutional Neural Network (CNN) model to extract the automatic features from the pre-processed CT image. This CNN model assures feature learning with extremely effective 1D feature extraction for each input CT image. The outcome of the 2D CNN model is then normalized using the Min-Max technique. The second step of the proposed hybrid model is related to training and classification using different classifiers. The simulation outcomes using the publically available dataset prove the robustness and efficiency of the proposed model compared to state-of-art algorithms.

Keywords: CT scan, Covid-19, deep learning, image processing, lung disease classification

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Authors: Ghibeche Abderrahmane

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To examine whether genes associated with cellular defense against oxidative stress are associated with insulin sensitivity, patients with type 2 diabetes (n=7) and age-matched (n=5) and young (n=9) control subjects underwent a euglycemic-hyperinsulinemic clamp for 120 min. Muscle samples were obtained before and after the clamp and analyzed for heat shock protein (HSP)72 and heme oxygenase (HO)-1 mRNA, intramuscular triglyceride content, and the maximal activities of β-hyroxyacyl-CoA dehydrogenase (β-HAD) and citrate synthase (CS). Basal expression of both HSP72 and HO-1 mRNA were lower (P < 0.05) by 33 and 55%, respectively, when comparing diabetic patients with age-matched and young control subjects, with no differences between the latter groups. Both basal HSP72 (r = 0.75, P < 0.001) and HO-1 (r = 0.50,P < 0.05) mRNA expression correlated with the glucose infusion rate during the clamp. Significant correlations were also observed between HSP72 mRNA and both β-HAD (r = 0.61, P < 0.01) and CS (r = 0.65, P < 0.01). HSP72 mRNA was induced (P < 0.05) by the clamp in all groups. Although HO-1 mRNA was unaffected by the clamp in both the young and age-matched control subjects, it was increased (P < 0.05) ∼70-fold in the diabetic patients after the clamp. These data demonstrate that genes involved in providing cellular protection against oxidative stress are defective in patients with type 2 diabetes and correlate with insulin-stimulated glucose disposal and markers of muscle oxidative capacity. The data provide new evidence that the pathogenesis of type 2 diabetes involves perturbations to the antioxidant defense mechanism within skeletal muscle.

Keywords: euglycemic-hyperinsulinemic, HSP72, mRNA, diabete

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Authors: M. Klimova, O. Semyachkina-Glushkovskaya, J. Kurts, E. Zinchenko, N. Navolokin, A. Shirokov, A. Dubrovsky, A. Abdurashitov, A. Terskov, A. Mamedova, I. Agranovich, T. Antonova, I. Blokhina

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The direction for research of Alzheimer's disease is to find an effective non-invasive and non-pharmacological way of treatment. Here we tested our hypothesis that the opening of the blood-brain barrier (BBB) induces activation of lymphatic drainage and clearing functions that can be used as a method for non-invasive stimulation of clearance of beta-amyloid and therapy of Alzheimer’s disease (AD). To test our hypothesis, in this study on healthy male mice we analyzed the interaction between BBB opening by repeated loud music (100-10000 Hz, 100 dB, duration 2 h: 60 sec – sound; 60 sec - pause) and functional changes in the meningeal lymphatic vessels (MLVs). We demonstrate clearance of dextran 70 kDa (i.v. injection), fluorescent beta-amyloid (intrahippocampal injection) and gold nanorods (intracortical injection) via MLV that significantly increased after the opening of BBB. Our studies also demonstrate that the BBB opening was associated with the improvement of neurocognitive status in mice with AD. Thus, we uncover therapeutic effects of BBB opening by loud music, such as non-invasive stimulation of lymphatic clearance of beta-amyloid in mice with AD, accompanied by improvement of their neurocognitive status. Our data are consistent with other results suggesting the therapeutic effect of BBB opening by focused ultrasound without drugs for patients with AD. This research was supported by a grant from RSF 18-75-10033

Keywords: Alzheimer's disease, beta-amyloid, blood-brain barrier, meningeal lymphatic vessels, repeated loud music

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Authors: Hushyar Azari

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Aim and background: Deep brain stimulation (DBS) is regarded as an important therapeutic choice for Parkinson's disease (PD). The two most common targets for DBS are the subthalamic nucleus (STN) and globus pallidus (GPi). This review was conducted to compare the clinical effectiveness of these two targets. Methods: A systematic literature search in electronic databases: Embase, Cochrane Library and PubMed were restricted to English language publications 2010 to 2021. Specified MeSH terms were searched in all databases. Studies which evaluated the Unified Parkinson's Disease Rating Scale (UPDRS) III were selected by meeting the following criteria: (1) compared both GPi and STN DBS; (2) had at least three months follow-up period; (3)at least five participants in each group; (4)conducted after 2010. Study quality assessment was performed using the Modified Jadad Scale. Results: 3577 potentially relevant articles were identified, of these, 3569 were excluded based on title and abstract, duplicate and unsuitable article removal. Eight articles satisfied the inclusion criteria and were scrutinized (458 PD patients). According to Modified Jadad Scale, the majority of included studies had low evidence quality which was a limitation of this review. 5 studies reported no statistically significant between-group difference for improvements in UPDRS ш scores. At the same time, there were some results in terms of pain, action tremor, rigidity, and urinary symptoms, which indicated that STN DBS might be a better choice. Regarding the adverse effects, GPi was superior. Conclusion: It is clear that other larger randomized clinical trials with longer follow-up periods and control groups are needed to decide which target is more efficient for deep brain stimulation in Parkinson’s disease and imposes fewer adverse effects on the patients. Meanwhile, STN seems more reasonable according to the results of this systematic review.

Keywords: brain stimulation, globus pallidus, Parkinson's disease, subthalamic nucleus

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Authors: Mohammad Al-Mousawi

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This academic article explores the indispensable role of critical thinking in the process of diagnosing diseases. Employing a multidisciplinary approach, we delve into the cognitive skills and analytical mindset that clinicians, researchers, and healthcare professionals must employ to navigate the complexities of disease identification. By examining the integration of critical thinking within the realms of medical education, diagnostic decision-making, and technological advancements, this article aims to underscore the significance of cultivating and applying critical thinking skills in the ever-evolving landscape of healthcare.

Keywords: critical thinking, medical education, diagnostic decision-making, fostering critical thinking

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Authors: A. Reum Son, Jin Seon Kwon, Seung Hun Park, Hai Bang Lee, Moon Suk Kim

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These days, stem cell therapy is focused on for promising source of treatment in clinical human disease. As a supporter of stem cells, in situ-forming hydrogels with growth factors and cells appear to be a promising approach in tissue engineering. To examine osteogenic differentiation of hTMSCs which is one of mesenchymal stem cells in vivo in an injectable hydrogel, we use a methoxy polyethylene glycol-polycaprolactone blockcopolymer (MPEG-PCL) solution with osteogenic factors. We synthesized MPEG-PCL hydrogel and measured viscosity to check sol-gel transition. In order to demonstrate osteogenic ability of hTMSCs, we conducted in vitro osteogenesis experiment. Then, to confirm the cell cytotoxicity, we performed WST-1 with hTMSCs and MPEG-PCL. As the result of in vitro experiment, we implanted cell and hydrogel mixture into animal model and checked degree of osteogenesis with histological analysis and amount of expression genes. Through these experimental data, MPEG-PCL hydrogel has sol-gel transition in temperature change and is biocompatible with stem cells. In histological analysis and gene expression, hTMSCs are very good source of osteogenesis with hydrogel and will use it to tissue engineering as important treatment method. hTMSCs could be a good adult stem cell source for usability of isolation and high proliferation. When hTMSCs are used as cell therapy method with in situ-formed hydrogel, they may provide various benefits like a noninvasive alternative for bone tissue engineering applications.

Keywords: injectable hydrogel, stem cell, osteogenic differentiation, tissue engineering

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Authors: Debit Datta, Jeffrey J. Coleman, Scott A. Enebak, Lori G. Eckhardt

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Loblolly pine (Pinus taeda) is a leading productive timber species in the southeastern USA. Over the past three years, an emerging threat is expressed by successive needle defoliation followed by stunted growth and tree mortality in loblolly pine plantations. Considering economic significance, it has now become a rising concern among landowners, forest managers, and forest health state cooperators. However, the symptoms of the disease were perplexed somewhat with root disease(s) and recurrently attributed to invasive Phytophthora species due to the similarity of disease nature and devastation. Therefore, the study investigated the potential causal agent of this disease and characterized the fungi associated with loblolly pine needle defoliation in the southeastern USA. Besides, 70 trees were selected at seven long-term monitoring plots at Chatom, Alabama, to monitor and record the annual disease incidence and severity. Based on colony morphology and ITS-rDNA sequence data, a total of 28 species of fungi representing 17 families have been recovered from diseased loblolly pine needles. The native brown-spot pathogen, Lecanosticta acicola, was the species most frequently recovered from unhealthy loblolly pine needles in combination with some other common needle cast and rust pathogen(s). Identification was confirmed using morphological similarity and amplification of translation elongation factor 1-alpha gene region of interest. Tagged trees were consistently found chlorotic and defoliated from 2019 to 2020. The current emergence of the brown-spot pathogen causing loblolly pine mortality necessitates the investigation of the role of changing climatic conditions, which might be associated with increased pathogen pressure to loblolly pines in the southeastern USA.

Keywords: brown-spot needle blight, loblolly pine, needle defoliation, plantation forestry

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Authors: Jakub Młoźniak, Adam Szymański, Gabriela Stondzik, Dagny Krankowska, Tomasz Mikuła

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Nontuberculous mycobacteria (NTM) are bacterial species that cause diversely manifesting diseases mainly in immunocompromised patients. In people with HIV, NTM infection is an AIDS-defining disease and usually appears when the lymphocyte T CD4 count is below 50 cells/μl. The usage of antiretroviral therapy has decreased the prevalence of NTM among people with HIV, but the disease can still be observed especially among patients with late HIV diagnosis. Common presence in environment, human colonization, clinical similarity with tuberculosis and slow growth on culture makes NTM especially hard to diagnose. The study aimed to analyze the epidemiology and clinical course of NTM among patients with HIV. This study included patients with NTM and HIV admitted to our department between 2017 and 2023. Medical records of patients were analyzed and data on age, sex, median time from HIV diagnosis to identification of NTM infection, median CD4 count at NTM diagnosis, methods of determining NTM infection, type of species of mycobacteria identified, clinical symptoms and treatment course were gathered. Twenty-four patients (20 men, 4 women) with identified NTM were included in this study. Among them, 20 were HIV late presenters. The patients' median age was 40. The main symptoms which patients presented were fever, weight loss and cough. Pulmonary disease confirmed with positive cultures from sputum/bronchoalveolar lavage was present in 18 patients. M. avium was the most common species identified. M. marinum caused disseminated skin lesions in 1 patient. Out of all, 5 people were not treated for NTM caused by lack of symptoms and suspicion of colonization with mycobacterium. Concomitant tuberculosis was present in 6 patients. The median diagnostic time from HIV to NTM infections was 3.5 months. The median CD4 count at NTM identification was 69.5 cells/μl. Median NTM treatment time was 16 months but 7 patients haven’t finished their treatment yet. The most commonly used medications were ethambutol and clarithromycin. Among analyzed patients, 4 of them have died. NTM infections are still an important disease among patients who are HIV late presenters. This disease should be taken into consideration during the differential diagnosis of fever, weight loss and cough in people with HIV with lymphocyte T CD4 count <100 cells/μl. Presence of tuberculosis does not exclude nontuberculous mycobacterium coinfection.

Keywords: mycobacteriosis, HIV, late presenter, epidemiology

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Authors: Vaishali Patil, Neeraj Masand

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In older people, Alzheimer’s disease (AD) is turning out to be a lethal disease. According to the amyloid hypothesis, aggregation of the amyloid β–protein (Aβ), particularly its 42-residue variant (Aβ42), plays direct role in the pathogenesis of AD. Aβ is generated through sequential cleavage of amyloid precursor protein (APP) by β–secretase (BACE) and γ–secretase (GS). Thus in the treatment of AD, γ-secretase modulators (GSMs) are potential disease-modifying as they selectively lower pathogenic Aβ42 levels by shifting the enzyme cleavage sites without inhibiting γ–secretase activity. This possibly avoids known adverse effects observed with complete inhibition of the enzyme complex. Virtual screening, via drug-like ADMET filter, QSAR and molecular docking analyses, has been utilized to identify novel γ–secretase modulators with sulphonamide nucleus. Based on QSAR analyses and docking score, some novel analogs have been synthesized. The results obtained by in silico studies have been validated by performing in vivo analysis. In the first step, behavioral assessment has been carried out using Scopolamine induced amnesia methodology. Later the same series has been evaluated for neuroprotective potential against the oxidative stress induced by Scopolamine. Biochemical estimation was performed to evaluate the changes in biochemical markers of Alzheimer’s disease such as lipid peroxidation (LPO), Glutathione reductase (GSH), and Catalase. The Scopolamine induced amnesia model has shown increased Acetylcholinesterase (AChE) levels and the inhibitory effect of test compounds in the brain AChE levels have been evaluated. In all the studies Donapezil (Dose: 50µg/kg) has been used as reference drug. The reduced AChE activity is shown by compounds 3f, 3c, and 3e. In the later stage, the most potent compounds have been evaluated for Aβ42 inhibitory profile. It can be hypothesized that this series of alkyl-aryl sulphonamides exhibit anti-AD activity by inhibition of Acetylcholinesterase (AChE) enzyme as well as inhibition of plaque formation on prolong dosage along with neuroprotection from oxidative stress.

Keywords: gamma-secretase inhibitors, Alzzheimer's disease, sulphonamides, QSAR

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