Search results for: clinical predictions

Authors: Sultan Ayoub Meo

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Environmental pollution is a highly challenging global concern of the 21st century and is a major cause of various communicable and non-communicable diseases. We investigate the impact of air pollution on "lung function, fractional exhaled nitric oxide, and cognitive function"in a group of one hundred young students studying in a traffic-polluted school. The students wereselected based on their age, gender, height, weight, and ethnicity. After the clinical history, one hundred students were recruited from the schoolnear and away from the polluted areas. The lung and cognitive functions were recorded. The results revealed that lung and cognitive function parameters were reduced in groups of students studying in a school located in a traffic-polluted area compared to thosestudying in a schoolsituated away from the traffic-polluted area. Environmental pollution impairs students' lung and cognitive functions studying in schools located within traffic-polluted areas. The health officials and policymakers establish strategies to minimize environmental pollution and its allied health hazards. Prof. Sultan Ayoub Meo, MD, Ph.D Professor, Department of Physiology, College of Medicine, King Saud University, Saudi Arabia Email. [email protected] / [email protected]

Keywords: environmental pOllution, lung physiology, cognitive functions, air pollution

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Authors: Benjamin J. Kuo, Silvia D. Vaca, Joao Ricardo Nickenig Vissoci, Catherine A. Staton, Linda Xu, Michael Muhumuza, Hussein Ssenyonjo, John Mukasa, Joel Kiryabwire, Lydia Nanjula, Christine Muhumuza, Henry E. Rice, Gerald A. Grant, Michael M. Haglund

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Background: Traumatic Brain Injury (TBI) is disproportionally concentrated in low- and middle-income countries (LMICs), with the odds of dying from TBI in Uganda more than 4 times higher than in high income countries (HICs). The disparities in the injury incidence and outcome between LMICs and resource-rich settings have led to increased health outcomes research for TBIs and their associated risk factors in LMICs. While there have been increasing TBI studies in LMICs over the last decade, there is still a need for more robust prospective registries. In Uganda, a trauma registry implemented in 2004 at the Mulago National Referral Hospital (MNRH) showed that RTI is the major contributor (60%) of overall mortality in the casualty department. While the prior registry provides information on injury incidence and burden, it’s limited in scope and doesn’t follow patients longitudinally throughout their hospital stay nor does it focus specifically on TBIs. And although these retrospective analyses are helpful for benchmarking TBI outcomes, they make it hard to identify specific quality improvement initiatives. The relationship among epidemiology, patient risk factors, clinical care, and TBI outcomes are still relatively unknown at MNRH. Objective: The objectives of this study are to describe the processes of care and determine risk factors predictive of poor outcomes for TBI patients presenting to a single tertiary hospital in Uganda. Methods: Prospective data were collected for 563 TBI patients presenting to a tertiary hospital in Kampala from 1 June – 30 November 2016. Research Electronic Data Capture (REDCap) was used to systematically collect variables spanning 8 categories. Univariate and multivariate analysis were conducted to determine significant predictors of mortality. Results: 563 TBI patients were enrolled from 1 June – 30 November 2016. 102 patients (18%) received surgery, 29 patients (5.1%) intended for surgery failed to receive it, and 251 patients (45%) received non-operative management. Overall mortality was 9.6%, which ranged from 4.7% for mild and moderate TBI to 55% for severe TBI patients with GCS 3-5. Within each TBI severity category, mortality differed by management pathway. Variables predictive of mortality were TBI severity, more than one intracranial bleed, failure to receive surgery, high dependency unit admission, ventilator support outside of surgery, and hospital arrival delayed by more than 4 hours. Conclusions: The overall mortality rate of 9.6% in Uganda for TBI is high, and likely underestimates the true TBI mortality. Furthermore, the wide-ranging mortality (3-82%), high ICU fatality, and negative impact of care delays suggest shortcomings with the current triaging practices. Lack of surgical intervention when needed was highly predictive of mortality in TBI patients. Further research into the determinants of surgical interventions, quality of step-up care, and prolonged care delays are needed to better understand the complex interplay of variables that affect patient outcome. These insights guide the development of future interventions and resource allocation to improve patient outcomes.

Keywords: care continuum, global neurosurgery, Kampala Uganda, LMIC, Mulago, prospective registry, traumatic brain injury

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Authors: H. Merhni, A. Sbiti, I. Ratbi, A. Sefiani

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The proximal spinal muscular atrophy (SMA) is a group of neuromuscular disorders characterized by progressive muscle weakness due to the degeneration and loss of anterior motor neurons of the spinal cord. Depending on the age of onset of symptoms and their evolution, four types of SMA, varying in severity, result in a mutations of the SMN gene (survival of Motor neuron). We have analyzed the DNA of 295 patients referred to our genetic counseling; since January 1996 until October 2014; for suspected SMA. The homozygous deletion of exon 7 of the SMN gene was found in 133 patients; of which, 40.6% were born to consanguineous parents. In countries like Morocco, where the frequency of heterozygotes for SMA is high, genetic testing should be offered as first-line and, after careful clinical assessment, especially in newborns and infants with congenital hypotonia unexplained and prognosis compromise. The molecular diagnosis of SMA allows a quick and certainly diagnosis, provide adequate genetic counseling for families at risk and suggest, for couples who want prenatal diagnosis. The analysis of the SMN gene is a perfect example of genetic testing with an excellent cost/benefit ratio that can be of great interest in public health, especially in low-income countries. We emphasize in this work for the benefit of the generalization of molecular diagnosis of SMA by the technique of PCR-enzymatic digestion in other centers in Morocco.

Keywords: Exon7, PCR-digestion, SMA, SMN gene

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Authors: Marina Sofia, Alexios Giannakopoulos, Antonia Touloudi, Dimitris C Chatzopoulos, Zoi Athanasakopoulou, Vassiliki Spyrou, Charalambos Billinis

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Fertility of dairy cattle can be affected by heat stress when the ambient temperature increases above 30°C and the relative humidity ranges from 35% to 50%. The present study was conducted on dairy cattle farms during summer months in Greece and aimed to identify the serological profile against pathogens that could affect fertility and to associate the positive serological results at herd level with temperature factors. A total of 323 serum samples were collected from clinically healthy dairy cows of 8 herds, located in Central and Northern Greece. ELISA tests were performed to detect antibodies against selected pathogens that affect fertility, namely Chlamydophila abortus, Coxiella burnetii, Neospora caninum, Toxoplasma gondii and Infectious Bovine Rhinotracheitis Virus (IBRV). Eleven climatic variables were derived from the WorldClim version 1.4. and ArcGIS V.10.1 software was used for analysis of the spatial information. Five different MaxEnt models were applied to associate the temperature variables with the locations of seropositive Chl. abortus, C. burnetii, N. caninum, T. gondii and IBRV herds (one for each pathogen). The logistic outputs were used for the interpretation of the results. ROC analyses were performed to evaluate the goodness of fit of the models’ predictions. Jackknife tests were used to identify the variables with a substantial contribution to each model. The seropositivity rates of pathogens varied among the 8 herds (0.85-4.76% for Chl. abortus, 4.76-62.71% for N. caninum, 3.8-43.47% for C. burnetii, 4.76-39.28% for T. gondii and 47.83-78.57% for IBRV). The variables of annual temperature range, mean diurnal range and maximum temperature of the warmest month gave a contribution to all five models. The regularized training gains, the training AUCs and the unregularized training gains were estimated. The mean diurnal range gave the highest gain when used in isolation and decreased the gain the most when it was omitted in the two models for seropositive Chl.abortus and IBRV herds. The annual temperature range increased the gain when used alone and decreased the gain the most when it was omitted in the models for seropositive C. burnetii, N. caninum and T. gondii herds. In conclusion, antibodies against Chl. abortus, C. burnetii, N. caninum, T. gondii and IBRV were detected in most herds suggesting circulation of pathogens that could cause infertility. The results of the spatial analyses demonstrated that the annual temperature range, mean diurnal range and maximum temperature of the warmest month could affect positively the possible pathogens’ presence. Acknowledgment: This research has been co‐financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH–CREATE–INNOVATE (project code: T1EDK-01078).

Keywords: dairy cows, seropositivity, spatial analysis, temperature factors

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Authors: Adrian Sebastian, Chris Gillespie

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We describe a case of diffuse rectal involvement with cap polyposis, manifesting with a protein-losing colopathy and occurring in the setting of advanced mechanical pelvic floor dysfunction. A 59-year-old male with a 5-year history of persistent excessive flatulence, defecatory difficulties, and diarrhea. He had extensive cap polyposis of the entire rectum endoscopically. His symptoms progressed to severe fecal incontinence with mucus leakage, pelvic pain, weight loss, and hypoalbuminemia. Clinical examination exhibited severe perineal descent, a large rectocele, poor anal squeeze, and a poor defecatory technique. After a trial of nonoperative therapies addressing his defecatory dysfunction, and Helicobacter pylori eradication, surgical resection was offered due to severe symptoms with ongoing incontinence and protein loss with no other reasonable options. A robotic abdominoperineal resection with a permanent colostomy was performed, followed by an uncomplicated recovery. Our observation of coexisting mechanical pelvic floor changes in this patient lends weight to the concept of a prolapse-related phenomenon in the pathophysiology of this rare condition.

Keywords: cap polyposis, pelvic dysfunction, fecal incontinence, case report

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Authors: Farhood Rismanchian, Seong Hyeon Park, Young Hoon Lee

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During the recent years, demand for healthcare services has dramatically increased. As the demand for healthcare services increases, so does the necessity of constructing new healthcare buildings and redesigning and renovating existing ones. Increasing demands necessitate the use of optimization techniques to improve the overall service efficiency in healthcare settings. However, high complexity of care processes remains the major challenge to accomplish this goal. This study proposes a method based on process mining results to address the high complexity of care processes and to find the optimal layout of the various medical centers in an emergency department. ProM framework is used to discover clinical pathway patterns and relationship between activities. Sequence clustering plug-in is used to remove infrequent events and to derive the process model in the form of Markov chain. The process mining results served as an input for the next phase which consists of the development of the optimization model. Comparison of the current ED design with the one obtained from the proposed method indicated that a carefully designed layout can significantly decrease the distances that patients must travel.

Keywords: Mixed Integer programming, Facility layout problem, Process Mining, Healthcare Operation Management

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Authors: Kostas Kouvaris, Anastasia Eleftheriou, Georgios A. Sarantitis, Apostolos Chondronasios

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To achieve the objective of almost zero carbon energy solutions by 2050, the EU needs to accelerate the development of integrated, highly efficient and environmentally friendly solutions. In this direction, district heating and cooling (DHC) emerges as a viable and more efficient alternative to conventional, decentralized heating and cooling systems, enabling a combination of more efficient renewable and competitive energy supplies. In this paper, we develop a forecasting tool for near real-time local weather and thermal energy demand predictions for an entire DHC network. In this fashion, we are able to extend the functionality and to improve the energy efficiency of the DHC network by predicting and adjusting the heat load that is distributed from the heat generation plant to the connected buildings by the heat pipe network. Two case-studies are considered; one for Vransko, Slovenia and one for Montpellier, France. The data consists of i) local weather data, such as humidity, temperature, and precipitation, ii) weather forecast data, such as the outdoor temperature and iii) DHC operational parameters, such as the mass flow rate, supply and return temperature. The external temperature is found to be the most important energy-related variable for space conditioning, and thus it is used as an external parameter for the energy demand models. For the development of the forecasting tool, we use state-of-the-art deep neural networks and more specifically, recurrent networks with long-short-term memory cells, which are able to capture complex non-linear relations among temporal variables. Firstly, we develop models to forecast outdoor temperatures for the next 24 hours using local weather data for each case-study. Subsequently, we develop models to forecast thermal demand for the same period, taking under consideration past energy demand values as well as the predicted temperature values from the weather forecasting models. The contributions to the scientific and industrial community are three-fold, and the empirical results are highly encouraging. First, we are able to predict future thermal demand levels for the two locations under consideration with minimal errors. Second, we examine the impact of the outdoor temperature on the predictive ability of the models and how the accuracy of the energy demand forecasts decreases with the forecast horizon. Third, we extend the relevant literature with a new dataset of thermal demand and examine the performance and applicability of machine learning techniques to solve real-world problems. Overall, the solution proposed in this paper is in accordance with EU targets, providing an automated smart energy management system, decreasing human errors and reducing excessive energy production.

Keywords: machine learning, LSTMs, district heating and cooling system, thermal demand

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Authors: Jay L. Fu

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Patients with Alzheimer's disease progressively lose their memory and thinking skills and, eventually, the ability to carry out simple daily tasks. The disease is irreversible, but early detection and treatment can slow down the disease progression. In this research, publicly available MRI data and demographic data from 373 MRI imaging sessions were utilized to build models to predict dementia. Various machine learning models, including logistic regression, k-nearest neighbor, support vector machine, random forest, and neural network, were developed. Data were divided into training and testing sets, where training sets were used to build the predictive model, and testing sets were used to assess the accuracy of prediction. Key risk factors were identified, and various models were compared to come forward with the best prediction model. Among these models, the random forest model appeared to be the best model with an accuracy of 90.34%. MMSE, nWBV, and gender were the three most important contributing factors to the detection of Alzheimer’s. Among all the models used, the percent in which at least 4 of the 5 models shared the same diagnosis for a testing input was 90.42%. These machine learning models allow early detection of Alzheimer’s with good accuracy, which ultimately leads to early treatment of these patients.

Keywords: Alzheimer's disease, clinical diagnosis, magnetic resonance imaging, machine learning prediction

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Authors: Khaled Soliman, Abdullah Alrushoud, Abdulrahman Alkhalifah, Raed Albathi, Salman Altymiat

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Radiation dose received by patients undergoing Computed Tomography (CT) examination of the cervical spine was evaluated using Gafchromic XR-QA2 films and CT-EXPO software (ver. 2.3), in order to document our clinical dose values and to compare our results with other benchmarks reported in the current literature. Radiochromic films were recently used as practical dosimetry tool that provides dose profile information not available using the standard ionisation chamber routinely used in CT dosimetry. We have developed an in-house program to use the films in order to calculate the Entrance Dose Length Product (EDLP) in (mGy.cm) and to relate the EDLP to various organ doses calculated using the CT-EXPO software. We also calculated conversion factor in (mSv/mGy.cm) relating the EDLP to the effective dose (ED) from the examination using CT-EXPO software. Variability among different types of CT scanners and dose modulation methods are reported from at least three major CT brands available at our medical institution. Our work describes the dosimetry method and results are reported. The method can be used as in-vivo dosimetry method. But this work only reports results obtained from adult female anthropomorphic Phantom studies.

Keywords: CT dosimetry, gafchromic films, XR-QA2, CT-Expo software

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Authors: Mohammad Javad Zehtab, S. Alireza Mirghasemi, Ali Majlesara, Parvin Tajik, Babak Siavashi

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Objective: There are different modalities proposed for tennis elbow treatment with few randomized trials comparing them. We designed a study to compare the effectiveness of five different modalities and determine the usefulness of recently proposed extensor grip test (EGT) in predicting the response to treatment. Methods: In a randomized controlled clinical trial 92 of 98 tennis elbow patients in Sina hospital of Tehran, Iran between 2006 and 2007 fulfill trial entry criteria, among these patients 56 (60.9%) had positive EGT result. Stratified on EGT result, patients allocated randomly to 5 treatment groups: Brace (B) group, physiotherapy (P), brace + physiotherapy (BP), injection (I) and injection + physiotherapy (IP). Results: Patients who had positive result of EGT had better response to treatments: less SOC (p = 0.06), less PFFQ and patients’ satisfaction scores (p < 0.001). Among the treatment IP was the most successful, then BP, P and B, respectively; injection was the worst treatment modality. Response to treatment was comparable in all groups between EGT positive and negative patients except bracing; in which positive EGT was correlated with a dramatic response to treatment. Conclusion: In all patients IP and then BP is recommended but in EGT negatives, bracing seems to be of no use. Injection alone is not recommended in either group.

Keywords: tennis elbow, extensor grip test, physiotherapy, tennis elbow treatment

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Authors: Aiche Mohamed Amine, Mallem Leila, Yahia El Khansa, Boulakoud Mohamed Salah

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Until recently, toxicological studies focused on the effects of individual chemicals. However, humans and wildlife are exposed to a complex milieu of chemicals from different sources including food and water, personal care products and the environment. The aim of this study is to detect the toxicity of two fungicides and their mixtures in the fertility and oxidative damge induced in the rat. The male of rats (28) were used, they were divided in four groups (7 rats of each group) and one group was used as control. Rats were dosed orally with Propiconazole 60mg/Kg/day, Propinebe 100mg/Kg/day and their mixture 30mg Propiconazole/kg/day + 50mg Propineb/kg/day for 4 weeks. Animals were observed for clinical toxicity. At the end of treatment period, animals of all groups were scarified, blood was collected for hematological and biochemical’s analysis and desired organs were removed and weighted. The results indicated that the fungicide and their mixture were toxic in the treated animals. The semen study showed a decrease in the count and mobility of spermatozoa in all treated group, it was also a decrease in the weight of the testis and epidydimis in the treated group as compared with control. Reduced glutathione (GSH), Glutathione peroxidase (GPx) level was decreased in all treated groups.

Keywords: fungicides, mixtures, fertility, oxidative stress

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Authors: Qasem Qananwah, Ahmad Dagamseh, Hiam AlQuran, Khalid Shaker Ibrahim

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Blood pressure helps the physicians greatly to have a deep insight into the cardiovascular system. The determination of individual blood pressure is a standard clinical procedure considered for cardiovascular system problems. The conventional techniques to measure blood pressure (e.g. cuff method) allows a limited number of readings for a certain period (e.g. every 5-10 minutes). Additionally, these systems cause turbulence to blood flow; impeding continuous blood pressure monitoring, especially in emergency cases or critically ill persons. In this paper, the most important statistical features in the photoplethysmogram (PPG) signals were extracted to estimate the blood pressure noninvasively. PPG signals from more than 40 subjects were measured and analyzed and 12 features were extracted. The features were fed to principal component analysis (PCA) to find the most important independent features that have the highest correlation with blood pressure. The results show that the stiffness index means and standard deviation for the beat-to-beat heart rate were the most important features. A model representing both features for Systolic Blood Pressure (SBP) and Diastolic Blood Pressure (DBP) was obtained using a statistical regression technique. Surface fitting is used to best fit the series of data and the results show that the error value in estimating the SBP is 4.95% and in estimating the DBP is 3.99%.

Keywords: blood pressure, noninvasive optical system, principal component analysis, PCA, continuous monitoring

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Authors: Raneem O. Salem, Najwa Al-Mously, Nihal Mohamed Nabil, Abdulmohsen H. Al-Zalabani, Abeer F. Al-Dhawi, Nasser Al-Hamdan

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Objective: There are various demographic and educational factors that affect the academic performance of undergraduate medical students. The objective of this study is to identify these factors and correlate them to the GPA of the students. Methods: A cross-sectional study design utilizing grade point averages (GPAs) of two cohorts of students in both levels of the pre-clinical phase. In addition, self-administered questionnaire was used to evaluate the effect of these factors on students with poor and good cumulative GPA. Results: Among the various factors studied, gender, marital status, and the transportation used to reach the faculty significantly affected academic performance of students. Students with a cumulative GPA of 3.0 or greater significantly differed than those with a GPA of less than 3.0 being higher in female students, in married students, and type of transportation used to reach the college. Factors including age, educational factors, and type of transportation used have shown to create a significant difference in GPA between male and females. Conclusion: Factors such as age, gender, marital status, learning resources, study time, and the transportation used have been shown to significantly affect medical student GPA as a whole batch as well as when they are tested for gender.

Keywords: academic performance, educational factors, learning resources, study time, gender, socio-demographic factors

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Authors: Georges Ghazi, Magali Gelhaye, Ruxandra Botez

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Over the years, the Flight Management System (FMS) has experienced a continuous improvement of its many features, to the point of becoming the pilot’s primary interface for flight planning operation on the airplane. With the assistance of the FMS, the concept of distance and time has been completely revolutionized, providing the crew members with the determination of the optimized route (or flight plan) from the departure airport to the arrival airport. To accomplish this function, the FMS needs an accurate Aircraft Performance Model (APM) of the aircraft. In general, APMs that equipped most modern FMSs are established before the entry into service of an individual aircraft, and results from the combination of a set of ordinary differential equations and a set of performance databases. Unfortunately, an aircraft in service is constantly exposed to dynamic loads that degrade its flight characteristics. These degradations endow two main origins: airframe deterioration (control surfaces rigging, seals missing or damaged, etc.) and engine performance degradation (fuel consumption increase for a given thrust). Thus, after several years of service, the performance databases and the APM associated to a specific aircraft are no longer representative enough of the actual aircraft performance. It is important to monitor the trend of the performance deterioration and correct the uncertainties of the aircraft model in order to improve the accuracy the flight management system predictions. The basis of this research lies in the new ability to continuously update an Aircraft Performance Model (APM) during flight using an adaptive lookup table technique. This methodology was developed and applied to the well-known Cessna Citation X business aircraft. For the purpose of this study, a level D Research Aircraft Flight Simulator (RAFS) was used as a test aircraft. According to Federal Aviation Administration the level D is the highest certification level for the flight dynamics modeling. Basically, using data available in the Flight Crew Operating Manual (FCOM), a first APM describing the variation of the engine fan speed and aircraft fuel flow w.r.t flight conditions was derived. This model was next improved using the proposed methodology. To do that, several cruise flights were performed using the RAFS. An algorithm was developed to frequently sample the aircraft sensors measurements during the flight and compare the model prediction with the actual measurements. Based on these comparisons, a correction was performed on the actual APM in order to minimize the error between the predicted data and the measured data. In this way, as the aircraft flies, the APM will be continuously enhanced, making the FMS more and more precise and the prediction of trajectories more realistic and more reliable. The results obtained are very encouraging. Indeed, using the tables initialized with the FCOM data, only a few iterations were needed to reduce the fuel flow prediction error from an average relative error of 12% to 0.3%. Similarly, the FCOM prediction regarding the engine fan speed was reduced from a maximum error deviation of 5.0% to 0.2% after only ten flights.

Keywords: aircraft performance, cruise, trajectory optimization, adaptive lookup tables, Cessna Citation X

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Authors: Awol Seid Ebrie

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HIV results as an incurable disease, AIDS. After a person is infected with virus, the virus gradually destroys all the infection fighting cells called CD4 cells and makes the individual susceptible to opportunistic infections which cause severe or fatal health problems. Several studies show that the CD4 cells count is the most determinant indicator of the effectiveness of the treatment or progression of the disease. The objective of this paper is to investigate the progression of the disease over time among patient under HAART treatment. Two main approaches of the generalized multilevel ordinal models; namely the proportional odds model and the nonproportional odds model have been applied to the HAART data. Also, the multilevel part of both models includes random intercepts and random coefficients. In general, four models are explored in the analysis and then the models are compared using the deviance information criteria. Of these models, the random coefficients nonproportional odds model is selected as the best model for the HAART data used as it has the smallest DIC value. The selected model shows that the progression of the disease increases as the time under the treatment increases. In addition, it reveals that gender, baseline clinical stage and functional status of the patient have a significant association with the progression of the disease.

Keywords: nonproportional odds model, proportional odds model, random coefficients model, random intercepts model

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Authors: A. Lubis, L. Setiawati, A. R. Setyoningrum, A. Suryawan, Irwanto

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Asthma is a condition that causing chronic health problems in children. In addition to basic therapy against disease, we must try to reduce the impact of chronic health problems and also optimize their medical aspect of growth and development. A boy with mild asthma attack frequent episode did not showed any improvement with medical treatment and his asthma control test was 11. From radiologic examination he got hyperaerated lung and billateral sinusitis maxillaris; skin test results were house dust, food and pet allergy; an overweight body; bad school grades; psychological and environmental problem. We followed and evaluated this boy in 6 months, treated holistically. Even we could not do much on environmental but no more psychological and school problems, his on a good bodyweight and his asthma control test was 22. A case of a child with mild asthma attack frequent episode was reported. Asthma clinical course show no significant improvement when other predisposing factor is not well-controlled and a child’s growth and development may be affected. Improving condition of the patient can be created with the help of loving and caring way of nurturing from the parents and supportive peer group. Therefore, continuous and consistent monitoring is required because prognosis of asthma is generally good when regularly and properly controlled.

Keywords: asthma, chronic health problems, growth, development

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Authors: Reem Al-Shidhani, Isabelle S. R. Storer, Michael J. Bromley, Lydia Tabernero

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Invasive fungal diseases are an increasing global health concern that contributes to the high mortality rates in immunocompromised patients. The rising of antifungal resistance severely lowers the efficacy of the limited antifungal agents available. New antifungal drugs that target new mechanisms are necessary to tackle the current shortfalls. Amongst post- modifications, phosphorylation is a predominant and an outstanding protein alteration in all eukaryotes. In fungi, protein phosphorylation plays a vital role in many signal transduction pathways, including cell cycle, cell growth, metabolism, transcription, differentiation, proliferation, and virulence. The investigation of Aspergillus fumigatus phosphatases revealed seven genes essential for viability. Inhibiting one of these phosphatases is a new interesting route to develop novel antifungal drugs. In this study, we carried out an early drug discovery process targeting oneessential phosphatase, GlcA. Here, we report the identification of new GlcA inhibitors that show antifungal activity. These important finding open a new avenue to the development of novel antifungals to expand the current narrow arsenal of clinical candidates.

Keywords: invasive fungal diseases, phosphatases, GlcA, competitive inhibitors

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Authors: S. Chami, J. Chauvin, T. Demarest, Stan Ng, M. Straus, W. Jahner

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Biometrics tools such as fingerprint and iris are widely used in industry to protect critical assets. However, their vulnerability and lack of robustness raise several worries about the protection of highly critical assets. Biometrics based on Electrocardiographic (ECG) signals is a robust identification tool. However, most of the state-of-the-art techniques have worked on clinical signals, which are of high quality and less noisy, extracted from wearable devices like a smartwatch. In this paper, we are presenting a complete machine learning pipeline that identifies people using ECG extracted from an off-person device. An off-person device is a wearable device that is not used in a medical context such as a smartwatch. In addition, one of the main challenges of ECG biometrics is the variability of the ECG of different persons and different situations. To solve this issue, we proposed two different approaches: per person classifier, and one-for-all classifier. The first approach suggests making binary classifier to distinguish one person from others. The second approach suggests a multi-classifier that distinguishes the selected set of individuals from non-selected individuals (others). The preliminary results, the binary classifier obtained a performance 90% in terms of accuracy within a balanced data. The second approach has reported a log loss of 0.05 as a multi-class score.

Keywords: biometrics, electrocardiographic, machine learning, signals processing

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Authors: Darma Putra Sitepu, Dewi Larasati, Yohanes Wolter Hendrik George

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Sepsis is a life-threatening medical emergency frequently observed in intensive care unit (ICU). Surviving Sepsis Campaign in 2018 has recommended the administration of early vasopressor in the first hour of sepsis or septic shock but has not yet included de-resuscitation protocol. De-resuscitation in acute management of septic shock is where patient received active removal of accumulated fluid. It has been proposed by some studies and ongoing clinical trials. Here we present a case with early vasopressor and de-resuscitation. Male, 27 years old presenting to the emergency room with shortness of breath, altered mental status, and widespread blisters on his body and lips started a few hours prior, after receiving non-steroidal anti-inflammatory drug through intravenous injection. Patient was hypotensive, tachycardic, and tachypneic at admission, diagnosed with Steven Johnson Syndrome with Septic Shock. Patient received fluid resuscitation, early vasopressor, and diuresis agent aimed to actively remove fluid after the initial phase of resuscitation. Patient was admitted to ICU and progressively recovering. At day-10, patient was stabilized and was transferred to general ward. Early vasopressor and de-resuscitation are beneficial for the patient.

Keywords: sepsis, shock, de-resuscitation, vasopressor, fluid, case report

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Authors: Pallab Datta, Jyotirmoy Chatterjee, Santanu Dhara

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Over the past few years, phosphorous containing polymers have received widespread attention for applications such as high performance optical fibers, flame retardant materials, drug delivery and tissue engineering. Being pentavalent, phosphorous can exist in different chemical environments in these polymers which increase their versatility. In human biochemistry, phosphorous based compounds exert their functions both in soluble and insoluble form occurring as inorganic or as organophosphorous compounds. Specifically in case of biomacromolecules, phosphates are critical for functions of DNA, ATP, phosphoproteins, phospholipids, phosphoglycans and several coenzymes. Inspired by the role of phosphorous in functional biomacromolecules, design and synthesis of biomimetic materials are thus carried out by several authors to study macromolecular function or as substitutes in clinical tissue regeneration conditions. In addition, many regulatory signals of the body are controlled by phoshphorylation of key proteins present either in form of growth factors or matrix-bound scaffold proteins. This inspires works on synthesis of phospho-peptidomimetic amino acids for understanding key signaling pathways and this is extended to obtain molecules with potentially useful biological properties. Apart from above applications, phosphate groups bound to polymer backbones have also been demonstrated to improve function of osteoblast cells and augment performance of bone grafts. Despite the advantages of phosphate grafting, however, there is limited understanding on effect of degree of phosphorylation on macromolecular physicochemical and/or biological properties. Such investigations are necessary to effectively translate knowledge of macromolecular biochemistry into relevant clinical products since they directly influence processability of these polymers into suitable scaffold structures and control subsequent biological response. Amongst various techniques for fabrication of biomimetic scaffolds, nanofibrous scaffolds fabricated by electrospinning technique offer some special advantages in resembling the attributes of natural extracellular matrix. Understanding changes in physico-chemical properties of polymers as function of phosphorylation is therefore going to be crucial in development of nanofiber scaffolds based on phosphorylated polymers. The aim of the present work is to investigate the effect of phosphorous grafting on the electrospinning behavior of polymers with aim to obtain biomaterials for bone regeneration applications. For this purpose, phosphorylated derivatives of two polymers of widely different electrospinning behaviors were selected as starting materials. Poly(vinyl alcohol) is a conveniently electrospinnable polymer at different conditions and concentrations. On the other hand, electrospinning of chitosan backbone based polymers have been viewed as a critical challenge. The phosphorylated derivatives of these polymers were synthesized, characterized and electrospinning behavior of various solutions containing these derivatives was compared with electrospinning of pure poly (vinyl alcohol). In PVA, phosphorylation adversely impacted electrospinnability while in NMPC, higher phosphate content widened concentration range for nanofiber formation. Culture of MG-63 cells on electrospun nanofibers, revealed that degree of phosphate modification of a polymer significantly improves cell adhesion or osteoblast function of cultured cells. It is concluded that improvement of cell response parameters of nanofiber scaffolds can be attained as a function of controlled degree of phosphate grafting in polymeric biomaterials with implications for bone tissue engineering applications.

Keywords: bone regeneration, chitosan, electrospinning, phosphorylation

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Authors: Keshari Shrestha, Philip Vatterott

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Introduction: Drug reaction with eosinophilia and systemic symptoms (DRESS) syndrome is a rare and potentially fatal drug-related syndrome. DRESS classically presents with a diffuse maculopapular rash, fevers, and eosinophilia more than three weeks after drug exposure. DRESS can present with multi-organ involvement, with liver damage being the most common and severe. Pulmonary involvement is a less common manifestation and is associated with poor clinical outcomes. Chest imaging is often nonspecific, and symptoms can range from mild cough to acute respiratory distress syndrome (ARDS) . This is a case of a 49-year-old female with a history of recent clostridium difficile colitis status post treatment with oral vancomycin who presented with rash, acute liver and kidney failure, as well as diffuse nodular alveolar lung opacities concerning for DRESS syndrome with multi-organ involvement. Clinical Course: This patient initially presented to an outside hospital with clostridium difficile colitis, acute liver injury, and acute kidney injury. She developed a desquamating maculopapular rash in the setting of recent oral vancomycin, meloxicam, and furosemide initiation. She was hospitalized on two additional occasions with worsening altered mental status, liver injury, and acute kidney injury and was initiated on intermittent hemodialysis. Notably, she was found to have systemic eosinophilia (4100 cells/microliter) several weeks prior. She was transferred to this institution for further management where she was found to have encephalopathy, jaundice, lower extremity edema, and diffuse bilateral rhonchorous breath sounds on pulmonary examination. The patient was started on methylprednisolone for suspected DRESS syndrome. She underwent an evaluation for alternative causes of her organ failure. Her workup included a negative infectious, autoimmune, metabolic, toxic, and malignant work-up. Abdominal computed tomography (CT) and ultrasound were remarkable for evidence of hepatic steatosis and possible cirrhotic morphology. Additionally, a chest CT demonstrated diffuse and symmetric nodular alveolar lung opacities with peripheral sparing not consistent with acute respiratory distress syndrome or edema. Ultimately, her condition continued to decline, and she required intubation on several occasions. On hospital day 25 she succumbed to distributive shock in the setting of probable sepsis and multi-organ failure. Discussion: DRESS syndrome occurs in 1 in 1,000 to 10,000 patients with a mortality rate of around 10%. Anti-convulsant, anti-bacterial, anti-viral, and sulfonamide drugs are the most common drugs implicated in the development of DRESS syndrome; however, the list of offending agents is extensive . The diagnosis of DRESS syndrome is made after excluding other causes of disease such as infectious and autoimmune etiologies. The RegiSCAR scoring system is used to diagnose DRESS syndrome with 2-3 points indicating possible disease, 4-5 probable disease, and >5 definite disease. This patient scored a 7 on the RegiSCAR scale for eosinophilia, rash, organ involvement, and exclusion of other causes (infectious and autoimmune). While the pharmacologic trigger in this case is unknown, it is speculated to be caused by vancomycin, meloxicam, or furosemide due to the favorable timeline of initiation. Despite aggressive treatment, DRESS syndrome can often be fatal. Because of this, early diagnosis and treatment of patients with suspected DRESS syndrome is imperative.

Keywords: drug reaction with eosinophilia and systemic symptoms, multi-organ failure, pulmonary involvement, renal failure

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Authors: Stela Papa, Klementina Puto, Migena Pllaha

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HCV is a hepatotropic RNA virus, transmitted primarily via the blood route, which causes progressive disease such as chronic hepatitis, liver cirrhosis, or hepatocellular carcinoma. HCV nowadays is a global healthcare problem. A variety of immunoassays including old and new technologies are being applied to detect HCV in our country. These methods include Immunochromatography assays (ICA), Fluorescence immunoassay (FIA), Enzyme linked fluorescent assay (ELFA), and Enzyme linked immunosorbent assay (ELISA) to detect HCV antibodies in blood serum, which lately is being slowly replaced by more sensitive methods such as rapid automated analyzer chemiluminescence immunoassay (CLIA). The aim of this study is to estimate HCV infection in carriers and chronic acute patients and to evaluate the use of new diagnostic methods. This study was realized from September 2016 to May 2018. During this study period, 2913 patients were analyzed for the presence of HCV by taking samples from their blood serum. The immunoassays performed were ICA, FIA, ELFA, ELISA, and CLIA assays. Concluding, 82% of patients taken in this study, resulted infected with HCV. Diagnostic methods in clinical laboratories are crucial in the early stages of infection, in the management of chronic hepatitis and in the treatment of patients during their disease.

Keywords: CLIA, ELISA, Hepatitis C virus, immunoassay

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Authors: A. Nazilah

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Floods are classified among sudden onset phenomenon and the highest natural disasters happen in Malaysia. Floods have a negative impact on mental health. Measuring the psychopathology symptoms among flood victims is an important step for intervention and treatment. However, there is a gap of a valid, reliable and an efficient instrument to measure flood victims' mental health, especially in Malaysia. This study aims to replicate the earlier studies of developing e-Psychological Instrument for Flood Victims (e-PIFV). The e-PIFV is a digital self-report inventory that has 84 items with 4 dimension scales namely stress, anxiety, depression, and trauma. Two replicated studies have been done to validate the instrument using expert judgment method. Results showed that content coefficient validity for each sub-scale of the instrument ranging from moderate to very strong validity. In study I, coefficient values of stress was 0.7, anxiety was 0.9, depression was 1.0, trauma was 0.6 and overall was 0.8. In study II, the coefficient values for two subscales and overall scale were increased. The coefficient value of stress was 0.8, anxiety was 0.9, depression was 1.0, trauma was 0.8 and overall was 0.9. This study supports the theoretical framework and provides practical implication in the field of clinical psychology and flood management.

Keywords: developing e-psychological instrument, content validity, instrument, mental health management, flood victims, psychopathology, validity

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Authors: Minakshi Jain, I. P. Singh

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Due to the era of outstanding technology and modern lifestyle, human beings are debasing their physical, psychological, and mental well-being. The effect of this leads to a trail of chronic diseases like anxiety, loneliness, and depression, especially in children and young adults. This is visible in individuals who suffer from clinical depression, which leads to impaired mood and distortion of cognition, particularly in children. The Members of the WHO European Region made a declaration to provisioning each child with access to healthy and safe environments by 2020, and the decision was taken at the Conference on Environment and Health in 2010 as an initiative to improve access to green spaces in cities which provides universal access for quality spaces for both social interaction and human well-being. In line with this, the paper aims to establish a prospective study on linking green spaces and CBT (Cognitive behavior therapy) in order to treat disorders with reference to children and young adults. A questionnaire was adopted to explore the possibility of green spaces as additive measures for the existing modes of therapy. The results adapted from the questionnaire show that certain species of vegetation have a significant effect in enhancing effective mental well-being.

Keywords: CBT, therapeutic gardens UCLA loneliness scale, anxiety, depression, green spaces, biophilia, environmental psychology

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Authors: Shalitha Jayasekara, Saluk Bawantha, Dinithi Anupama, Isuru Gunarathne, Pradeepa Bandara, Hansi De Silva

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Dogs have been known as "man's best friend" for generations, providing friendship and loyalty to their human counterparts. However, due to people's busy lives, they are unaware of the ailments that can affect their pets. However, in recent years, mobile technologies have had a significant impact on our lives, and with technological improvements, a rule-based expert system allows the end-user to enable new types of healthcare systems. The advent of Android OS-based smartphones with more user-friendly interfaces and lower pricing opens new possibilities for continuous monitoring of pets' health conditions, such as healthy dogs, dangerous ingestions, and swallowed objects. The proposed ‘Best Bark’ Dog care and owner consultation system is a mobile application for dog owners. Four main components for dog owners were implemented after a questionnaire was distributed to the target group of audience and the findings were evaluated. The proposed applications are widely used to provide health and clinical support to dog owners, including suggesting exercise and diet plans and answering queries about their dogs. Additionally, after the owner uploads a photo of the dog, the application provides immediate feedback and a description of the dog's skin disease.

Keywords: Convolution Neural Networks, Artificial Neural Networks, Knowledgebase, Sentimental Analysis.

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Authors: Masaki Yamaguchi, Daimei Sasayama, Shinsuke Washizuka

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The goal of this study was to examine the possibility of salivary cytokines for the screening of attention deficit hyperactivity disorder (ADHD) in children. We carried out a case-control study, including 19 children with ADHD and 17 healthy children (controls). A multiplex bead array immunoassay was used to conduct a multi-analysis of 27 different salivary cytokines. Six salivary cytokines (interleukin (IL)-1β, IL-8, IL12p70, granulocyte colony-stimulating factor (G-CSF), interferon gamma (IFN-γ), and vascular endothelial growth factor (VEGF)) were significantly associated with the presence of ADHD (p < 0.05). An informative salivary cytokine panel was developed using VEGF by logistic regression analysis (odds ratio: 0.251). Receiver operating characteristic analysis revealed that assessment of a panel using VEGF showed “good” capability for discriminating between ADHD patients and controls (area under the curve: 0.778). ADHD has been hypothesized to be associated with reduced cerebral blood flow in the frontal cortex, due to reduced VEGF levels. Our study highlights the possibility of utilizing differential salivary cytokine levels for point-of-care testing (POCT) of biomarkers in children with ADHD.

Keywords: cytokine, saliva, attention deficit hyperactivity disorder, child

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Authors: Elia Caldini, Cláudia N. Battlehner, Marcelo A. Ferreira, Rolf Gemperli, Nivaldo Alonso, Luiz P. Vana

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The advent of dermal regenerate templates has fostered major advances in the treatment of acute burns and their sequelae, in the last two decades. Both data on morphological aspects of the newly-formed tissue, and clinical trials comparing different templates, are still lacking. The goal of this study was to prospectively analyze the outcome of patients treated with two of the existing templates, followed by thin skin autograft. They are both made of bovine collagen, one includes a superficial silicone layer. Surgery was performed on patients with impaired mobility resulting from burn sequelae (n = 12 per template). Negative pressure therapy was applied post-surgically; patients were monitored for 12 months. Data on scar skin quality (Vancouver and POSAS evaluation scales), rate of joint mobility recovery, and graft contraction were recorded. Improvement in mobility and skin quality were demonstrated along with graft contraction, in all patients. The silicone-coupled template showed the best performance in all aspects.

Keywords: dermal regeneration template, artificial skin, skin quality, scar contracture

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Authors: Bashar Mahmoud, Lee Mortimer, Michael Fairweather

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New methods have recently been introduced to improve the thermal property values of molten nitrate salts (a binary mixture of NaNO3:KNO3in 60:40 wt. %), by doping them with minute concentration of nanoparticles in the range of 0.5 to 1.5 wt. % to form the so-called: Nano-heat-transfer-fluid, apt for thermal energy transfer and storage applications. The present study aims to assess the stability of these nanofluids using the advanced computational modelling technique, Lagrangian particle tracking. A multi-phase solid-liquid model is used, where the motion of embedded nanoparticles in the suspended fluid is treated by an Euler-Lagrange hybrid scheme with fixed time stepping. This technique enables measurements of various multi-scale forces whose characteristic (length and timescales) are quite different. Two systems are considered, both consisting of 50 nm Al2O3 ceramic nanoparticles suspended in fluids of different density ratios. This includes both water (5 to 95 °C) and molten nitrate salt (220 to 500 °C) at various volume fractions ranging between 1% to 5%. Dynamic properties of both phases are coupled to the ambient temperature of the fluid suspension. The three-dimensional computational region consists of a 1μm cube and particles are homogeneously distributed across the domain. Periodic boundary conditions are enforced. The particle equations of motion are integrated using the fourth order Runge-Kutta algorithm with a very small time-step, Δts, set at 10-11 s. The implemented technique demonstrates the key dynamics of aggregated nanoparticles and this involves: Brownian motion, soft-sphere particle-particle collisions, and Derjaguin, Landau, Vervey, and Overbeek (DLVO) forces. These mechanisms are responsible for the predictive model of aggregation of nano-suspensions. An energy transport-based method of predicting the thermal conductivity of the nanofluids is also used to determine thermal properties of the suspension. The simulation results confirms the effectiveness of the technique. The values are in excellent agreement with the theoretical and experimental data obtained from similar studies. The predictions indicates the role of Brownian motion and DLVO force (represented by both the repulsive electric double layer and an attractive Van der Waals) and its influence in the level of nanoparticles agglomeration. As to the nano-aggregates formed that was found to play a key role in governing the thermal behavior of nanofluids at various particle concentration. The presentation will include a quantitative assessment of these forces and mechanisms, which would lead to conclusions about nanofluids, heat transfer performance and thermal characteristics and its potential application in solar thermal energy plants.

Keywords: thermal energy storage, molten salt, nano-fluids, multi-scale computational modelling

Procedia PDF Downloads 191

Authors: I. L. Ibrahim, A. Mann, A. Ndanaimi

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The research involved phytochemical screening, antibacterial activities and mineral determination by flame photometry of the crude extract of Brysocarpus coccineus schum indeed were carried out. The result of Phytochemical screening reveal tha saponins, alkaloids, cardiac glycosides, and anthraquinones were present. This suggests that the plant extract could be used as anti-inflammatory and anti-bleeding agents. Estimation of mineral content shows that the crude extract of B. coccineus contains 0.73 (Na+), 1.06 (K+) and 1.98 (Ca+) which justifies its use to be safe for hypertensive patients and could be used to lower blood pressure. The antibacterial properties of aqueous and ethanol extract were studied against some bacteria; pseudomonas aeruginosa, Escherichia coli, Bacilus subtilis, Klebsilla penmuoniae by disc diffusion method. The aqueous extract showed significant activity against the organisms while the ethanol at concentrations 5-10mg/ml ethanol extract showed significant zone of inhibition against the organisms, E. coli, (19 mm), B. cereus (12 mm), P. aeruginosa (11 mm), K. pnemuoniae (11 mm). Minimum inhibitory concentration (MIC) was carried with considerable effect of inhibition on the organisms. The MIC values observed were 1, 24, 16 and 19 mm against E. coli, B. cereus, P. aeruginosa and K. pnemuoniae respectively. Therefore, the plant could be a potential source of antibacterial agent although more pharmacological and clinical study may be recommended.

Keywords: phytochemicals, microorganisms, screenings, mineral ions

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Authors: Jeong Hong Kim, Ju Wan Kang

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Objective: Histamine skin prick testing is most commonly used to diagnose immunoglobulin E (IgE)-mediated allergic diseases, and histamine reactivity is used as a standardized positive control in the interpretation of a skin prick test. However, reactivity to histamine differs among individuals for reasons that are poorly understood. The present study aimed to evaluate the potential association between body mass index (BMI) and histamine skin reactivity in children. Methods: A total of 451 children (246 boys, 205 girls) aged 7–8 years were enrolled in this study. The skin prick test was performed with 26 aeroallergens commonly found in Korea. Other information was collected, including sex, age, BMI, parental allergy history, and parental smoking status. Multivariate analysis was used to confirm the association between histamine skin reactivity and BMI. Results: The histamine wheal size was revealed to be associated with BMI (Spearman's Rho 0.161, p < 0.001). This association was confirmed by multivariate analysis, after adjusting for sex, age, parental allergy history, parental smoking status, and allergic sensitization (coefficient B 0.071, 95% confidence interval 0.030–0.112). Conclusions: Skin responses to histamine were primarily correlated with increased BMI. Further studies are needed to understand the clinical implication of BMI when interpreting the results of skin prick test.

Keywords: allergy, body mass index, histamine, skin prick test

Procedia PDF Downloads 363