Search results for: disease prediction

Authors: Nuruddin Mohammod Zahangir, Syed Tanvir Ahmady, Firoz Ahmed, Mainul Kabir, Tamjid Mohammad Najmus Sakib Khan, Nazmul Hossain, Niaz Ahmed, Madhava Janardhan Naik

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The management of combined Coronary Artery Disease and Peripheral Vascular Disease is a challenge and brings with it numerous clinical dilemmas.The 56 year old gentleman presented to our department with significant triple vessel disease with occluded lower end of aorta just before bifurcation and bilateral superficial femoral arteries. Operation was done on 11.03.14. The The Left Internal Mammary Artery (LIMA) and the Right Internal Mammary Artery (RIMA) were harvested in skeletonized manner. The free RIMA was then anastomosed with LIMA to make LIMA-RIMA Y. Cardio Pulmonary Bypass was then established and coronary artery bypass grafts performed. LIMA was anastomosed to the Left Anterior Descending artery. RIMA was anastomosed to Posterior Descending Artery, 1st and 2nd Obtuse Marginal arteries in a sequential manner. Abdomen was opened by midline incision. The infrarenal aorta exposed and was found to be severely diseased. A Vascular Clamp was applied infrarenally, aortotomy done and limited endarterectomy performed. An end-to-side anastomosis was done with upper end of PTFE synthetic Y-graft (14/7 mm) to the infarenal Aorta and the Clamp released. Good flow noted in both limbs of the graft. Patient was then slowly weaned off from Cardio Pulmonary Bypass without difficulty. The distal two limbs of the Y graft were passed to the groin through retroperitoneal tunnels and anastomosed end-to-side with the common femoral arteries. Saphenous vein was interposed between common femoral and popliteal arteries bilaterally through subfascial tunnels in both thigh. On 12th postoperative day he was discharged from hospital in good general condition. Follow up after 3 months of operation the patient is doing good and free of chest pain and claudication pain.

Keywords: total arterial, coronary revascularization, aorto-bifemoral bypass, bifemoro-bipopliteal bypass

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Authors: Paul Shize Li, Frank Alber

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A fundamental task of clinical genomics is to unravel the functions of genes and their associations with disorders. Although experimental biology has made efforts to discover and elucidate the molecular mechanisms of individual genes in the past decades, still about 40% of human genes have unknown functions, not to mention the diseases they may be related to. For those biologists who are interested in a particular gene with unknown functions, a powerful computational method tailored for inferring the functions and disease relevance of uncharacterized genes is strongly needed. Studies have shown that genes strongly linked to each other in multiple biological networks are more likely to have similar functions. This indicates that the densely connected subgraphs in multiple biological networks are useful in the functional and phenotypic annotation of uncharacterized genes. Therefore, in this work, we have developed an integrative network approach to identify the frequent local clusters, which are defined as those densely connected subgraphs that frequently occur in multiple biological networks and consist of the query gene that has few or no disease or function annotations. This is a local clustering algorithm that models multiple biological networks sharing the same gene set as a three-dimensional matrix, the so-called tensor, and employs the tensor-based optimization method to efficiently find the frequent local clusters. Specifically, massive public gene expression data sets that comprehensively cover dynamic, physiological, and environmental conditions are used to generate hundreds of gene co-expression networks. By integrating these gene co-expression networks, for a given uncharacterized gene that is of biologist’s interest, the proposed method can be applied to identify the frequent local clusters that consist of this uncharacterized gene. Finally, those frequent local clusters are used for function and disease annotation of this uncharacterized gene. This local tensor clustering algorithm outperformed the competing tensor-based algorithm in both module discovery and running time. We also demonstrated the use of the proposed method on real data of hundreds of gene co-expression data and showed that it can comprehensively characterize the query gene. Therefore, this study provides a new tool for annotating the uncharacterized genes and has great potential to assist clinical genomic diagnostics.

Keywords: local tensor clustering, query gene, gene co-expression network, gene annotation

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Authors: Afolabi Joseph Fasoranti

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Tuberculosis (TB) is an infectious disease caused by mycobacterium tuberculosis. Tuberculosis is a major public health problem in Nigeria, being one of the ten leading causes of hospital admissions and a leading cause of death in adults, especially among the economically productive age group. This paper critically examined the importance of health education towards the eradication and prevention of tuberculosis in Nigeria. It was reviewed and discussed under the following subheadings; Global burden of tuberculosis in Nigeria, concept, definition and etiology of tuberculosis, Signs and symptoms of tuberculosis, diagnosis of tuberculosis, causative agent, modes of infection and incubation period, risk factors of pulmonary tuberculosis Dots and stop TB programmes in Nigeria Treatment and prevention of tuberculosis TB treatment strategies, Dealing with treatment problems in Nigeria Stigmatization against Tuberculosis Patients Health education as a tool for achieving free tuberculosis country. Emphasis for Tb control has been placed on the development of improved vaccines, diagnostic and treatment courses but less on health education and awareness. Although the need for these tools is indisputable, the obstacle facing the spread of TB go beyond technological. The findings of this study may stimulate health system policy makers, Government and non- governmental organizations, donor agencies and other stakeholders in planning and designing health education intervention programs on the control and eradication of tuberculosis. It therefore recommended that Government should implement health education as part of the DOTs, this will thus empower the tuberculosis patients on ways to live healthy, lifestyle, in doing this, they will recover fast and prevent them from spreading the disease.

Keywords: tuberculosis, health education, panacea, Nigeria, prevention

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Authors: Surachart Koyadun

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Introduction: Plasmodium knowlesi (P. knowlesi) malaria is a zoonotic disease that is classified as type 5 of human malaria. Commonly found in macaques (Macaca fascicularis) and (Macaca nemestrina), P. knowlesi is capable of resulting in both uncomplicated and severe malaria in humans. Situation of P. knowlesi malaria in Phang-Nga province for the past 3 years from 2020 – 2022 revealed no case report in 2020, however, a total of 14 cases had been reported in 2021 - 2022. This research aimed to 1) study the epidemiology of P. knowlesi, 2) examine the clinical manifestations of P. knowlesi patients, 3) analyze the ecology and entomology of P. knowlesi, and 4) analyze the diagnosis and treatment of P. knowlesi. Method: This research was a retrospective descriptive study/case report. The study was conducted in 14 patients with P. knowlesi malaria between 2021 and 2022 in 4 districts of Phang-Nga Province, Thailand including Thapput, Kapong, Takuapa and Khuraburi. Results: The study subjects of P. knowlesi malaria were all males. Most of them were working age groups as farmers and worked in forest or plantation areas. All had no history of blood transfusions. Most of the patients did not use mosquito nets and had a history of camping in the forest prior to the onset of fever. An analysis of all 14 sources of infection unveiled the area is home to macaques, and that area has detected Anopheles mosquito, which is the carrier of the disease. Majority of them got sick in the dry season of Thailand (December-April). The main symptoms brought to the hospital were fever, chills, headache, body aches. Laboratory findings on the first day of diagnosis were as follows: The white blood cell count was found within the normal range. In the proportion of white blood cells, eosinophils were found to be slightly higher than normal. Slight anemia was found on early examination. The platelet count was found to be below normal in all cases. Severely low platelet count (2,000 cells/mm3) was found in severe cases with multiple complications. No patient was found dead but 85.7% of complications were found, with acute renal failure being the most common. Patients with delayed diagnosis and treatment of malaria (inaccurate diagnosis or late access to the hospital) had the highest severity and complications than those who had seen the doctor since the first 3-4 days of illness or the screening of symptoms and risk history by the malaria clinic staff at vector-borne disease control unit. Conclusion and Recommendation: P. knowlesi malaria is an emerging infectious disease transmitted from animals to humans. There are challenges in epidemiology, entomology, ecology for effective surveillance, prevention and control. Early diagnosis and treatment would reduce complications and prevent death.

Keywords: malaria, plasmodium knowlesi, epidemiology, ecology, entomology, diagnosis, treatment

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Authors: Adel Khorramrouz, Monireh Ahmadi Bani, Ehsan Norouzi, Morvarid Lalenoor

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Background: Plantar pressure distribution measurement has been used for a long time to assess foot disorders. Plantar pressure is an important component affecting the foot and ankle function and Changes in plantar pressure distribution could indicate various foot and ankle disorders. Morphologic and mechanical properties of the foot may be important factors affecting the plantar pressure distribution. Accurate and early measurement may help to reduce the prevalence of pes planus. With recent developments in technology, new techniques such as machine learning have been used to assist clinicians in predicting patients with foot disorders. Significance of the study: This study proposes a neural network learning-based flat foot classification methodology using static foot pressure distribution. Methodologies: Data were collected from 895 patients who were referred to a foot clinic due to foot disorders. Patients with pes planus were labeled by an experienced physician based on clinical examination. Then all subjects (with and without pes planus) were evaluated for static plantar pressures distribution. Patients who were diagnosed with the flat foot in both feet were included in the study. In the next step, the leg length was normalized and the network was trained for plantar pressure mapping images. Findings: From a total of 895 image data, 581 were labeled as pes planus. A computational neural network (CNN) ran to evaluate the performance of the proposed model. The prediction accuracy of the basic CNN-based model was performed and the prediction model was derived through the proposed methodology. In the basic CNN model, the training accuracy was 79.14%, and the test accuracy was 72.09%. Conclusion: This model can be easily and simply used by patients with pes planus and doctors to predict the classification of pes planus and prescreen for possible musculoskeletal disorders related to this condition. However, more models need to be considered and compared for higher accuracy.

Keywords: foot disorder, machine learning, neural network, pes planus

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Authors: Ian Walsh, Terry Nguyen-Khuong, Christopher H. Taron, Pauline M. Rudd

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Glycoproteins and their covalently bonded glycans play critical roles in the immune system, cell communication, disease and disease prognosis. Ultra performance liquid chromatography (UPLC) coupled with mass spectrometry is conventionally used to qualitatively and quantitatively characterise glycan structures in a given sample. Exoglycosidases are enzymes that catalyze sequential removal of monosaccharides from the non-reducing end of glycans. They naturally have specificity for a particular type of sugar, its stereochemistry (α or β anomer) and its position of attachment to an adjacent sugar on the glycan. Thus, monitoring the peak movements (both in the UPLC and MS1) after application of exoglycosidases provides a unique and effective way to annotate sugars with high detail - i.e. differentiating positional and linkage isomers. Manual annotation of an exoglycosidase experiment is difficult and time consuming. As such, with increasing sample complexity and the number of exoglycosidases, the analysis could result in manually interpreting hundreds of peak movements. Recently, we have implemented pattern recognition software for automated interpretation of UPLC-MS1 exoglycosidase digestions. In this work, we explain the software, indicate how much time it will save and provide example usage showing the annotation of positional and linkage isomers in Immunoglobulin G, apolipoprotein J, and simple glycan standards.

Keywords: bioinformatics, automated glycan assignment, liquid chromatography, mass spectrometry

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Authors: M. Suwaibah, S. W. Tan, I. Aiini, K. Yusoff, A. R. Omar

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Respiratory diseases are the most important infectious diseases affecting poultry worldwide. One of the avian respiratory virus of global importance causing significant economic losses is Infectious Bronchitis Virus (IBV). The virus causes a wide spectrum disease known as Infectious Bronchitis (IB), affecting not only the respiratory system but also the kidney and the reproductive system, depending on its strain. IB and Newcastle disease are two of the most prevalent diseases affecting poultry in Malaysia. However, a study on the molecular characterization of Malaysian IBV is lacking. In this study, an IBV strain IBS130 which was isolated in 2015 was fully sequenced using next-gene sequencing approach. Sequence analysis of IBS130 based on the complete genome, polyprotein 1ab and S1 genes were compared with other IBV sequences available in Genbank, National Center for Biotechnology Information (NCBI). IBV strain IBS130 is characterised as QX-like strain based on whole genome and S1 gene sequence analysis. Comparisons of the virus with other IBV strains showed that the nucleotide identity ranged from 67% to 99.2%, depending on the region analysed. The similarity in whole genome nucleotide ranging from 84.9% to 90.7% with the least similar was from Singapore strains (84.9%) and highly similar with China QX-like strains. Meanwhile, the similarity in polyprotein 1ab ranging from 85.3% to 89.9% with the least similar to Singapore strains (85.3%) and highly similar with Mass strains from USA.

Keywords: infectious bronchitis virus, phylogenetic analysis, chicken, Malaysia

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Authors: Jihene Bettaieb, Ghassen kharroubi, Rym mallekh, Ines Cherif, Taoufik Atawa, Kaouther Harrabech

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Brucellosis is a major worldwide zoonosis. It is a reportable condition in Tunisia where the disease remains endemic, especially in rural areas. The aim of this study was to describe the epidemiological, clinical, and bacteriological profile of human brucellosis cases notified in the district of Tunis. It was a retrospective descriptive study of cases reported in the district of Tunis through the national surveillance system between the 1st January and 31th December 2017. During the study period, 133 brucellosis confirmed cases were notified. The mean age was 37.5 ± 18.0 years, and 54.9% of cases were males. More than four-fifths (82.7%) of cases were reported in spring and summer with a peak in the month of May (36 cases). Fever and sweats were the most common symptoms; they occurred in 95% and 72% of cases, respectively. Osteoarticular complications occurred in 10 cases, meningitis in one case and endocarditis in one other case. Wright agglutination test and Rose Bengale test were positive in 100% and 91% of cases, respectively. While blood culture was positive in 9 cases and PCR in 2 cases. Brucella melitensis was the only identified specie (9 cases). Almost all cases (99.2%) reported the habit of consuming raw dairy products. Only 5 cases had a suspect contact with animals; among them, 3 persons were livestock breeders. The transmission was essentially due to raw dairy product consumption. It is important to enhance preventive measures to control animal Brucellosis and to educate the population regarding the risk factors of the disease.

Keywords: brucellosis, risk factors, surveillance system, Tunisia

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Authors: En-Tzu Wang, Ting-Ann Wang, Yi-Hui Shen, Yu-Min Chou, Chi-Tai Fang, Chin-Hui Yang

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Background and purpose: A mass varicella immunization program was established to provide free 1-dose vaccination for all 1-year-old children throughout Taiwan since 2004. The epidemiological characteristics and disease burden of varicella from 2000 to 2012 was investigated and the results will be essential to refine the national immunization policy. Method: We included patients (n = 17,838–164,245) with ICD-9-CM codes 052 (chickenpox) from the 2000 to 2012 National Health Insurance Database. The age, period, and cohort-specific incidence of varicella were calculated. The hospital admission rate, medical costs and indirect costs from the societal perspective of varicella including travel costs to the medical facility, registration fee, productivity losses of the patients and caregivers were also estimated. Result: There were 979,252 patients for medical treatment due to varicella from 2000 to 2012 in Taiwan. The implementation of a routine childhood varicella vaccination program has resulted in 87% decline in morbidity (881.49 to 115.17 per 100,000). The average age of patients increased from 7.9 years to 16.3 years. The overall varicella-related hospital admission rate was 15.5 per 1000 patients, and peaked in the groups of infants younger than 1 year, adults aged from 20 to 39 years and elders over 70 years. Among patients admitted to hospital, 33.5% of them had one or more complications. Patients with underlying diseases had higher admission rate (241.6 per 1,000) and longer duration of hospital stay (6.61 days vs. 4.76 days). The annual varicella-related medical expense declined after 2002 and the proportion of medical costs for admission has increased to 42%. The annual indirect costs from the societal perspective of varicella were 5.29 to 9.63 times higher than varicella-related medical costs. Every one dollar invested in the varicella immunization program, 2.97 dollars of medical and social costs were saved on average. Conclusion: The dramatic decline in morbidity, hospitalization, medical and social costs of varicella can be directly attributed to the implementation of the mass immunization program. Two-dose vaccination is recommended for both children with underlying diseases and susceptible adults to prevent serious complications and hospitalizations.

Keywords: disease burden, epidemiology, medical and social costs, varicella, varicella vaccine

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Authors: Junfeng Yan, Wenkui Hou

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Prognostics and Health Management (PHM) is a technology to monitor the equipment status and predict impending faults. It is used to predict the potential fault and provide fault information and track trends of system degradation by capturing characteristics signals. So how to detect characteristics signals is very important. The select of test point plays a very important role in detecting characteristics signal. Traditionally, we use dependency model to select the test point containing the most detecting information. But, facing the large complicated system, the dependency model is not built so easily sometimes and the greater trouble is how to calculate the matrix. Rely on this premise, the paper provide a highly effective method to select test point without dependency model. Because signal flow model is a diagnosis model based on failure mode, which focuses on system’s failure mode and the dependency relationship between the test points and faults. In the signal flow model, a fault information can flow from the beginning to the end. According to the signal flow model, we can find out location and structure information of every test point and module. We break the signal flow model up into serial and parallel parts to obtain the final relationship function between the system’s testability or prediction metrics and test points. Further, through the partial derivatives operation, we can obtain every test point’s importance degree in determining the testability metrics, such as undetected rate, false alarm rate, untrusted rate. This contributes to installing the test point according to the real requirement and also provides a solid foundation for the Prognostics and Health Management. According to the real effect of the practical engineering application, the method is very efficient.

Keywords: false alarm rate, importance degree, signal flow model, undetected rate, untrusted rate

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Authors: N. Hadthamard, P. Chaumpluk, M. Buanong, P. Boonyaritthongchai, C. Wongs-Aree

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Ripe ‘Nam Dok Mai’ mango (Mangifera indica L.) is an important exported fruit of Thailand, but rapidly declined in the quality attributes mainly by infection of anthracnose and stem end rot diseases. Multilayer coating is considered as a developed technique to maintain the postharvest quality of mangoes. The utilization of alternated coating by matching oppositely electrostatic charges between 0.1% chitosan and 0.1% polystyrene sulfonate (PSS) was studied. A number of the coating layers (layer by layer) were applied on mature green ‘Nam Dok Mai No.4’ mangoes prior to storage at 25 ^oC, 65-70% relative humidity (RH). There were significant differences in some quality attributes of mangoes coated by 3½ layers, 4½ layers and 5½ layers. In comparison to coated mangoes, uncoated fruits were higher in weight loss, total soluble solids, respiration rate, ethylene production and disease incidence except the titratable acidity. Coating fruit at 3½ layers exhibited the ripening delay and reducing disease infection without off flavour. On the other hand, fruit coated with 5½ layers comprised the lowest acceptable score, caused by exhibiting disorders from fermentation at the end of storage. As a result, multilayer coating between chitosan and PSS could effectively maintain the postharvest quality of mango, but number of coating layers should be thoroughly considered.

Keywords: multilayer, chitosan, polystyrene sulfonate, Nam Dok Mai No.4

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Authors: Shahrzad Zolfagharnassab, Abdul Rashid Mohamed Shariff, Siti Khairunniza Bejo

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Conventional methods for nutrient soil mapping are based on laboratory tests of samples that are obtained from surveys. The time and cost involved in gathering and analyzing soil samples are the reasons that researchers use Predictive Soil Mapping (PSM). PSM can be defined as the development of a numerical or statistical model of the relationship among environmental variables and soil properties, which is then applied to a geographic database to create a predictive map. Kriging is a group of geostatistical techniques to spatially interpolate point values at an unobserved location from observations of values at nearby locations. The main problem with using kriging as an interpolator is that it is excessively data-dependent and requires a large number of closely spaced data points. Hence, there is a need to minimize the number of data points without sacrificing the accuracy of the results. In this paper, an Artificial Neural Networks (ANN) scheme was used to predict macronutrient values at un-sampled points. ANN has become a popular tool for prediction as it eliminates certain difficulties in soil property prediction, such as non-linear relationships and non-normality. Back-propagation multilayer feed-forward network structures were used to predict nitrogen, phosphorous and potassium values in the soil of the study area. A limited number of samples were used in the training, validation and testing phases of ANN (pattern reconstruction structures) to classify soil properties and the trained network was used for prediction. The soil analysis results of samples collected from the soil survey of block C of Sawah Sempadan, Tanjung Karang rice irrigation project at Selangor of Malaysia were used. Soil maps were produced by the Kriging method using 236 samples (or values) that were a combination of actual values (obtained from real samples) and virtual values (neural network predicted values). For each macronutrient element, three types of maps were generated with 118 actual and 118 virtual values, 59 actual and 177 virtual values, and 30 actual and 206 virtual values, respectively. To evaluate the performance of the proposed method, for each macronutrient element, a base map using 236 actual samples and test maps using 118, 59 and 30 actual samples respectively produced by the Kriging method. A set of parameters was defined to measure the similarity of the maps that were generated with the proposed method, termed the sample reduction method. The results show that the maps that were generated through the sample reduction method were more accurate than the corresponding base maps produced through a smaller number of real samples. For example, nitrogen maps that were produced from 118, 59 and 30 real samples have 78%, 62%, 41% similarity, respectively with the base map (236 samples) and the sample reduction method increased similarity to 87%, 77%, 71%, respectively. Hence, this method can reduce the number of real samples and substitute ANN predictive samples to achieve the specified level of accuracy.

Keywords: artificial neural network, kriging, macro nutrient, pattern recognition, precision farming, soil mapping

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Authors: K. Iu. Hrizhymalska, O. Ol. Andrushkova, I. Iu. Pshenychna

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Aim. To study and copare the side effects of myopia contact correction by soft lenses and orthokeratology lenses among medical students. Patients and methods: 34 students (68 eyes) with moderate and severe myopia, who used contact correction of myopia for 2-4 years, were examined. Some of them used soft lenses, while others - orthokeratology lenses. Methods were used: biomicroscopy of the eye surface, Schirmer's test, Norn's test, survey regarding satisfaction with use. Results. Corneal vascularization along the limbus was noted in 4 (5%) eyes of the examined students. In 8 (11%) eyes, symptoms of mild dry eye disease were detected. 2 (3%) eyes showed signs of meibomitis. Allergic conjunctivitis was observed in 4 (5%) eyes, and a purulent corneal ulcer was present in 1 eye. Surveys have shown that orthokeratology lenses unlike soft lenses don't limit everyday activity (in sports, tourism, swimming etc.), they also don't cause discomfort during temperature changes and reduce existing symptoms of dry eye disease. Conclusion. Thus, myopia contact correction is one of the optimal options among students, which allows to expand physical and mental activity. However, taking into account the frequency of side effects in users of soft contact lenses, it is necessary to carry out prevention and treatment of myopia in medical students, follow the recommendations for use, instill preservative-free tear substitutes with trehalose when symptoms of dry eye appear. Also when side reactions occur, contact correction with soft lenses should be changed to orthokeratology lenses.

Keywords: correction, myopia, soft lenses, orthokeratology, specracles, cornea, dry eye, side effects, refractive errors

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Authors: Wenjun Zhang, Yunqing Du, Steven W. Cranford, Ming L. Wang

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The beginning of 21st century has witnessed new advancements in the design and use of new materials for biosensing applications, from nano to macro, protein to tissue. Traditional analytical methods lack a complete toolset to describe the complexities introduced by living systems, pathological relations, discrete hierarchical materials, cross-phase interactions, and structure-property dependencies. Materiomics – via systematic molecular dynamics (MD) simulation – can provide structure-process-property relations by using a materials science approach linking mechanisms across scales and enables oriented biosensor design. With this approach, DNA biosensors can be utilized to detect disease biomarkers present in individuals’ breath such as acetone for diabetes. Our wireless sensor array based on single-stranded DNA (ssDNA)-decorated single-walled carbon nanotubes (SWNT) has successfully detected trace amount of various chemicals in vapor differentiated by pattern recognition. Here, we present how MD simulation can revolutionize the way of design and screening of DNA aptamers for targeting biomarkers related to oral diseases and oral health monitoring. It demonstrates great potential to be utilized to build a library of DNDA sequences for reliable detection of several biomarkers of one specific disease, and as well provides a new methodology of creating, designing, and applying of biosensors.

Keywords: biosensor, DNA, biomarker, molecular dynamics simulation

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Authors: Zahow Muoftah

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Traditional manual visual grading of fruits has been one of the agricultural industry’s major challenges due to its laborious nature as well as inconsistency in the inspection and classification process. The main requirements for computer vision and visual processing are some effective techniques for identifying defects and estimating defect areas. Automated defect detection using computer vision and machine learning has emerged as a promising area of research with a high and direct impact on the visual inspection domain. Grading, sorting, and disease detection are important factors in determining the quality of fruits after harvest. Many studies have used computer vision to evaluate the quality level of fruits during post-harvest. Many studies have used computer vision to evaluate the quality level of fruits during post-harvest. Many studies have been conducted to identify diseases and pests that affect the fruits of agricultural crops. However, most previous studies concentrated solely on the diagnosis of a lesion or disease. This study focused on a comprehensive study to identify pests and diseases of apple and banana fruits using detection and classification defects on Banana and Apples by Computer Vision. As a result, the current article includes research from these domains as well. Finally, various pattern recognition techniques for detecting apple and banana defects are discussed.

Keywords: computer vision, banana, apple, detection, classification

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Authors: S. Mousavian, F. Mousavian, V. Nikkhah Rashidabad

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Cubic equations of state like Redlich–Kwong (RK) EOS have been proved to be very reliable tools in the prediction of phase behavior. Despite their good performance in compositional calculations, they usually suffer from weaknesses in the predictions of saturated liquid density. In this research, RK equation was modified. The result of this study shows that modified equation has good agreement with experimental data.

Keywords: equation of state, modification, ammonia, genetic algorithm

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Authors: Jiri Kysucan, Dusan Klos, Katherine Vomackova, Pavel Koranda, Martin Lovecek, Cestmir Neoral, Roman Havlik

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Aim: The prognosis of patients with pancreatic cancer is poor. The median of survival after establishing diagnosis is 3-11 months without surgical treatment, 13-20 months with surgical treatment depending on the disease stage, 5-year survival is less than 5%. Radical surgical resection remains the only hope of curing the disease. Early diagnosis with valid establishment of tumor resectability is, therefore, the most important aim for patients with pancreatic cancer. The aim of the work is to evaluate the contribution and define the role of 18F-FDG PET/CT in preoperative staging. Material and Methods: In 195 patients (103 males, 92 females, median age 66,7 years, 32-88 years) with a suspect pancreatic lesion, as part of the standard preoperative staging, in addition to standard examination methods (ultrasonography, contrast spiral CT, endoscopic ultrasonography, endoscopic ultrasonographic biopsy), a hybrid 18F-FDG PET/CT was performed. All PET/CT findings were subsequently compared with standard staging (CT, EUS, EUS FNA), with peroperative findings and definitive histology in the operated patients as reference standards. Interpretation defined the extent of the tumor according to TNM classification. Limitations of resectability were local advancement (T4) and presence of distant metastases (M1). Results: PET/CT was performed in a total of 195 patients with a suspect pancreatic lesion. In 153 patients, pancreatic carcinoma was confirmed and of these patients, 72 were not indicated for radical surgical procedure due to local inoperability or generalization of the disease. The sensitivity of PET/CT in detecting the primary lesion was 92.2%, specificity was 90.5%. A false negative finding in 12 patients, a false positive finding was seen in 4 cases, positive predictive value (PPV) 97.2%, negative predictive value (NPV) 76,0%. In evaluating regional lymph nodes, sensitivity was 51.9%, specificity 58.3%, PPV 58,3%, NPV 51.9%. In detecting distant metastases, PET/CT reached a sensitivity of 82.8%, specificity was 97.8%, PPV 96.9%, NPV 87.0%. PET/CT found distant metastases in 12 patients, which were not detected by standard methods. In 15 patients (15.6%) with potentially radically resectable findings, the procedure was contraindicated based on PET/CT findings and the treatment strategy was changed. Conclusion: PET/CT is a highly sensitive and specific method useful in preoperative staging of pancreatic cancer. It improves the selection of patients for radical surgical procedures, who can benefit from it and decreases the number of incorrectly indicated operations.

Keywords: cancer, PET/CT, staging, surgery

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Authors: Selim M. Khan, Aaron A. Goodarzi, Joshua M. Taron, Tryggve Rönnqvist

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Indoor air quality, a prime determinant of health, is strongly influenced by the presence of hazardous radon gas within the built environment. As a health issue, dangerously high indoor radon arose within the 20th century to become the 2nd leading cause of lung cancer. While the 21st century building metrics and human behaviors have captured, contained, and concentrated radon to yet higher and more hazardous levels, the issue is rapidly worsening in Canada. It is established that Canadians in the Prairies are the 2nd highest radon-exposed population in the world, with 1 in 6 residences experiencing 0.2-6.5 millisieverts (mSv) radiation per week, whereas the Canadian Nuclear Safety Commission sets maximum 5-year occupational limits for atomic workplace exposure at only 20 mSv. This situation is also deteriorating over time within newer housing stocks containing higher levels of radon. Deep machine learning (LSTM) algorithms were applied to analyze multiple quantitative and qualitative features, determine the most important contributory factors, and predicted radon levels in the known past (1990-2020) and projected future (2021-2050). The findings showed gradual downwards patterns in Sweden, whereas it would continue to go from high to higher levels in Canada over time. The contributory factors found to be the basement porosity, roof insulation depthness, R-factor, and air dynamics of the indoor environment related to human window opening behaviour. Building codes must consider including these factors to ensure adequate indoor ventilation and healthy living that can prevent lung cancer in non-smokers.

Keywords: radon, building metrics, deep learning, LSTM prediction model, lung cancer, canada, sweden

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Authors: Muhamad Aris Burhanudin, Angga Firmansyas, Bagus Jaya Santosa

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Earthquakes are natural hazard that can trigger the most dangerous hazard, tsunami. 26 December 2004, a giant earthquake occurred in north-west Andalas Island. It made giant tsunami which crushed Sumatra, Bangladesh, India, Sri Lanka, Malaysia and Singapore. More than twenty thousand people dead. The occurrence of earthquake and tsunami can not be avoided. But this hazard can be mitigated by earthquake forecasting. Early preparation is the key factor to reduce its damages and consequences. We aim to investigate quantitatively on pattern of earthquake. Then, we can know the trend. We study about earthquake which has happened in Andalas island, Indonesia one last decade. Andalas is island which has high seismicity, more than a thousand event occur in a year. It is because Andalas island is in tectonic subduction zone of Hindia sea plate and Eurasia plate. A tsunami forecasting is needed to mitigation action. Thus, a Tsunami Forecasting Method is presented in this work. Neutral Network has used widely in many research to estimate earthquake and it is convinced that by using Backpropagation Method, earthquake can be predicted. At first, ANN is trained to predict Tsunami 26 December 2004 by using earthquake data before it. Then after we get trained ANN, we apply to predict the next earthquake. Not all earthquake will trigger Tsunami, there are some characteristics of earthquake that can cause Tsunami. Wrong decision can cause other problem in the society. Then, we need a method to reduce possibility of wrong decision. Fuzzy TOPSIS is a statistical method that is widely used to be decision seconder referring to given parameters. Fuzzy TOPSIS method can make the best decision whether it cause Tsunami or not. This work combines earthquake prediction using neural network method and using Fuzzy TOPSIS to determine the decision that the earthquake triggers Tsunami wave or not. Neural Network model is capable to capture non-linear relationship and Fuzzy TOPSIS is capable to determine the best decision better than other statistical method in tsunami prediction.

Keywords: earthquake, fuzzy TOPSIS, neural network, tsunami

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Authors: Sanela Slavkovic, Congor Nad, Spela Golubovic

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Background: The diagnosis of multiple sclerosis (MS) is a major life challenge and has repercussions on all aspects of the daily functioning of those attained by it – personal activities, social participation, and quality of life. Regular follow-up of only the neurological status is not informative enough so that it could provide data on the sort of support and rehabilitation that is required. Objective: The aim of this study was to establish the current level of functioning of persons attained by MS and the factors that influence it. Methods: The study was conducted in Serbia, on a sample of 108 persons with relapse-remitting form of MS, aged 20 to 53 (mean 39.86 years; SD 8.20 years). All participants were fully ambulatory. Methods applied in the study include Expanded Disability Status Scale-EDSS and World Health Organization Disability Assessment Schedule, WHODAS 2.0 (36-item version, self-administered). Results: Participants were found to experience the most problems in the domains of Participation, Mobility, Life activities and Cognition. The least difficulties were found in the domain of Self-care. Symptom duration was the only control variable with a significant partial contribution to the prediction of the WHODAS scale score (β=0.30, p < 0.05). The total EDSS score correlated with the total WHODAS 2.0 score (r=0.34, p=0.00). Statistically significant differences in the domain of EDSS 0-5.5 were found within categories (0-1.5; 2-3.5; 4-5.5). The more pronounced a participant’s EDSS score was, although not indicative of large changes in the neurological status, the more apparent the changes in the functional domain, i.e. in all areas covered by WHODAS 2.0. Pyramidal (β=0.34, p < 0.05) and Bowel and bladder (β=0.24, p < 0.05) functional systems were found to have a significant partial contribution to the prediction of the WHODAS score. Conclusion: Measuring functioning and disability is important in the follow-up of persons suffering from MS in order to plan rehabilitation and define areas in which additional support is needed.

Keywords: disability, functionality, multiple sclerosis, rehabilitation

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Authors: Gabriel Cucato, Marilia Correia, Wagner Domingues, Aline Palmeira, Paulo Longano, Nelson Wolosker, Raphael Ritti-Dias

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Women with peripheral arterial disease (PAD) present lower walking capacity in comparison with men. However, whether cardiovascular regulation is also different between genders is unknown. Thus, the aim of this study was to compare walking capacity and cardiovascular regulation between men and women with PAD. A total of 23 women (66±7 yrs) and 31 men (64±9 yrs) were recruited. Patients performed a 6-minute test and the onset claudication distance and total walking distance were measured. Additionally, cardiovascular regulation was assessed by arterial stiffness (pulse wave velocity and augmentation index) and heart rate variability (frequency domain). Independent T test or Mann-Whitney U test were performed. In comparison with men, women present lower onset claudication distance (108±66m vs. 143±50m; P=0.032) and total walking distance (286±83m vs. 361±91 m, P=0.007). Regarding cardiovascular regulation, there were no differences in heart rate variability SDNN (72±160ms vs. 32±22ms, P=0.587); RMSSD (75±209 vs. 25±22ms, P=0.726); pNN50 (11±17ms vs. 8±14ms, P=0.836) in women and men, respectively. Moreover, there were no difference in augmentation index (39±10% vs. 34±11%, P=0.103); pulse pressure (59±17mmHg vs. 56±19mmHg, P=0.593) and pulse wave velocity (8.6±2.6m\s vs. 9.0±2.7m/s, P=0.580). In conclusion, women have impaired walking capacity compared to men. However, sex differences were not observed on cardiovascular regulation in patients with PAD.

Keywords: exercise, intermittent claudication, cardiovascular load, arterial stiffness

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Authors: Asghar Motea Noparvar

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According to the World Health Organization (WHO), the coronavirus disease (COVID-19), which has been characterized as a pandemic since December 2019, is attacking societies in terms of different ways. It means that this is much more than a crisis that is related to human health. It is a human, economic and social crisis. Since December 2019, not only some significant transformations have happened in human life, but also there has been some mental health, daily life activities, and even urban space changes. The purpose of this study is to mention some tangible transformations in society by applying two main restrictions such as “lock down” and “social distancing,” and how people took refuge in their homes and fit every activity there. How this pandemic has been transforming human life and social activities is the main issue of this study. In order to gather the information, review the impacts of COVID-19 on social life by revising the literature and considering the “Risk Society” theory, which is gotten credited by a German sociologist, Ulrich Beck. Additionally, COVID-19 not only had a direct impact on health but also had significant impacts on the economy, education, tourism, the environment, and the construction industry. Therefore, the pandemic caused a disruption in the whole urban system. In this study, the main focused point is the transformation of activities and residential areas. In order to achieve this finding, the literature review is analyzed in the case of COVID-19 and its impacts on social life. To sum up, it can be concluded that a pandemic can change social life along with other transformations that it is able to do.

Keywords: infectious disease, COVID-19, social activities, residential areas, transformation

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Authors: Yalda Zarnegarnia, Shari Messinger

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Receiver operating characteristic (ROC) curves have been widely used in medical research to illustrate the performance of the biomarker in correctly distinguishing the diseased and non-diseased groups. Correlated biomarker data arises in study designs that include subjects that contain same genetic or environmental factors. The information about correlation might help to identify family members at increased risk of disease development, and may lead to initiating treatment to slow or stop the progression to disease. Approaches appropriate to a case-control design matched by family identification, must be able to accommodate both the correlation inherent in the design in correctly estimating the biomarker’s ability to differentiate between cases and controls, as well as to handle estimation from a matched case control design. This talk will review some developed methods for ROC curve estimation in settings with correlated data from case control design and will discuss the limitations of current methods for analyzing correlated familial paired data. An alternative approach using Conditional ROC curves will be demonstrated, to provide appropriate ROC curves for correlated paired data. The proposed approach will use the information about the correlation among biomarker values, producing conditional ROC curves that evaluate the ability of a biomarker to discriminate between diseased and non-diseased subjects in a familial paired design.

Keywords: biomarker, correlation, familial paired design, ROC curve

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Authors: Bharti Arora, Michael Chen, Steven Lun

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Plasmacytoid urothelial carcinoma (PUC) of the bladder is a rare and aggressive subtype of urothelial carcinoma that usually presents at an advanced clinical stage, has a predilection for early metastatic potential and is associated with poor prognosis. The first reported case of PUC was in 1991 and approximately 100 cases were reported in the literature worldwide. We present a case of a 43 year old female presenting with a 3-month history of urgency and frequency. Failing medical management of her urinary symptoms with anticholinergic medication, she underwent a diagnostic cystoscopy which revealed an erythematous and indurated bladder. Bladder biopsies of these regions revealed plasmacytoid urothelial carcinoma. Pre-operative staging scans were clear of any metastatic disease and the patient subsequently underwent a radical cystectomy and pelvic clearance with the formation of ileal conduit for urinary diversion. Histology confirmed plasmacytoid urothelial carcinoma with involvement of right upper vagina and focally positive margins in soft tissue at right and left sides of bladder. She received adjuvant chemotherapy but passed away within a year from disease progression. PUC can present atypically and our case highlights the role of cystoscopy in patients with persistent urinary symptoms. By reviewing the literature on PUC, we aim to raise awareness and improve understanding of this rare bladder cancer subtype amongst urologists.

Keywords: urology, bladder cancer, plasmacytoid urothelial cancer, literature review

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Authors: Thomas Geninatti, Bruno Giacomo, Alessandro Grattoni

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Nanofluidic devices have been investigated for over a decade as promising platforms for the controlled release of therapeutics. The nanochannel drug delivery system (nDS), a membrane fabricated with high precision silicon techniques, capable of zero-order release of drugs by exploiting diffusion transport at the nanoscale originated from the interactions between molecules with nanochannel surfaces, showed the flexibility of the sustained release in vitro and in vivo, over periods of time ranging from weeks to months. To improve the implantable bio nanotechnology, in order to create a system that possesses the key features for achieve the suitable release of therapeutics, the next generation of nDS has been created. Platinum electrodes are integrated by e-beam deposition onto both surfaces of the membrane allowing low voltage (<2 V) and active temporal control of drug release through modulation of electrostatic potentials at the inlet and outlet of the membrane’s fluidic channels. Hence, a tunable administration of drugs is ensured from the nanochannel drug delivery system. The membrane will be incorporated into a peek implantable capsule, which will include drug reservoir, control hardware and RF system to allow suitable therapeutic regimens in real-time. Therefore, this new nanotechnology offers tremendous potential solutions to manage chronic disease such as cancer, heart disease, circadian dysfunction, pain and stress.

Keywords: nanochannel membrane, drug delivery, tunable release, personalized administration, nanoscale transport, biomems

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Authors: Junie B. Billones, Maria Constancia O. Carrillo, Voltaire G. Organo, Stephani Joy Y. Macalino, Inno A. Emnacen, Jamie Bernadette A. Sy

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The drug discovery and development process is generally known to be a very lengthy and labor-intensive process. Therefore, in order to be able to deliver prompt and effective responses to cure certain diseases, there is an urgent need to reduce the time and resources needed to design, develop, and optimize potential drugs. Computer-aided drug design (CADD) is able to alleviate this issue by applying computational power in order to streamline the whole drug discovery process, starting from target identification to lead optimization. This drug design approach can be predominantly applied to diseases that cause major public health concerns, such as tuberculosis. Hitherto, there has been no concrete cure for this disease, especially with the continuing emergence of drug resistant strains. In this study, CADD is employed for tuberculosis by first identifying a key enzyme in the mycobacterium’s metabolic pathway that would make a good drug target. One such potential target is the lipoate protein ligase B enzyme (LipB), which is a key enzyme in the M. tuberculosis metabolic pathway involved in the biosynthesis of the lipoic acid cofactor. Its expression is considerably up-regulated in patients with multi-drug resistant tuberculosis (MDR-TB) and it has no known back-up mechanism that can take over its function when inhibited, making it an extremely attractive target. Using cutting-edge computational methods, compounds from AnalytiCon Discovery Natural Derivatives database were screened and docked against the LipB enzyme in order to rank them based on their binding affinities. Compounds which have better binding affinities than LipB’s known inhibitor, decanoic acid, were subjected to in silico toxicity evaluation using the ADMET and TOPKAT protocols. Out of the 31,692 compounds in the database, 112 of these showed better binding energies than decanoic acid. Furthermore, 12 out of the 112 compounds showed highly promising ADMET and TOPKAT properties. Future studies involving in vitro or in vivo bioassays may be done to further confirm the therapeutic efficacy of these 12 compounds, which eventually may then lead to a novel class of anti-tuberculosis drugs.

Keywords: pharmacophore, molecular docking, lipoate protein ligase B (LipB), ADMET, TOPKAT

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Authors: Etienne Gaborit, Dorothy Durnford, Daniel Deacu, Marco Carrera, Nathalie Gauthier, Camille Garnaud, Vincent Fortin

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A new experimental streamflow forecasting system was recently implemented at the Environment and Climate Change Canada’s (ECCC) Canadian Centre for Meteorological and Environmental Prediction (CCMEP). It relies on CaLDAS (Canadian Land Data Assimilation System) for the assimilation of surface variables, and on a surface prediction system that feeds a routing component. The surface energy and water budgets are simulated with the SVS (Soil, Vegetation, and Snow) Land-Surface Scheme (LSS) at 2.5-km grid spacing over Canada. The routing component is based on the Watroute routing scheme at 1-km grid spacing for the Great Lakes and Nelson River watersheds. The system is run in two distinct phases: an analysis part and a forecast part. During the analysis part, CaLDAS outputs are used to force the routing system, which performs streamflow assimilation. In forecast mode, the surface component is forced with the Canadian GEM atmospheric forecasts and is initialized with a CaLDAS analysis. Streamflow performances of this new system are presented over 2019. Performances are compared to the current ECCC’s operational streamflow forecasting system, which is different from the new experimental system in many aspects. These new streamflow forecasts are also compared to persistence. Overall, the new streamflow forecasting system presents promising results, highlighting the need for an elaborated assimilation phase before performing the forecasts. However, the system is still experimental and is continuously being improved. Some major recent improvements are presented here and include, for example, the assimilation of snow cover data from remote sensing, a backward propagation of assimilated flow observations, a new numerical scheme for the routing component, and a new reservoir model.

Keywords: assimilation system, distributed physical model, offline hydro-meteorological chain, short-term streamflow forecasts

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Authors: Xiaomin Zhong, Alexander Pate, Ya-Ting Yang, Ali Fahmi, Darren M. Ashcroft, Ben Goldacre, Brian Mackenna, Amir Mehrkar, Sebastian C. J. Bacon, Jon Massey, Louis Fisher, Peter Inglesby, Kieran Hand, Tjeerd van Staa, Victoria Palin

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Background: This study aimed to predict risks of potentially inappropriate antibiotic type and repeat prescribing and assess changes during COVID-19. Methods: With the approval of NHS England, we used the OpenSAFELY platform to access the TPP SystmOne electronic health record (EHR) system and selected patients prescribed antibiotics from 2019 to 2021. Multinomial logistic regression models predicted the patient’s probability of receiving an inappropriate antibiotic type or repeating the antibiotic course for each common infection. Findings: The population included 9.1 million patients with 29.2 million antibiotic prescriptions. 29.1% of prescriptions were identified as repeat prescribing. Those with same-day incident infection coded in the EHR had considerably lower rates of repeat prescribing (18.0%), and 8.6% had a potentially inappropriate type. No major changes in the rates of repeat antibiotic prescribing during COVID-19 were found. In the ten risk prediction models, good levels of calibration and moderate levels of discrimination were found. Important predictors included age, prior antibiotic prescribing, and region. Patients varied in their predicted risks. For sore throat, the range from 2.5 to 97.5th percentile was 2.7 to 23.5% (inappropriate type) and 6.0 to 27.2% (repeat prescription). For otitis externa, these numbers were 25.9 to 63.9% and 8.5 to 37.1%, respectively. Interpretation: Our study found no evidence of changes in the level of inappropriate or repeat antibiotic prescribing after the start of COVID-19. Repeat antibiotic prescribing was frequent and varied according to regional and patient characteristics. There is a need for treatment guidelines to be developed around antibiotic failure and clinicians provided with individualised patient information.

Keywords: antibiotics, infection, COVID-19 pandemic, antibiotic stewardship, primary care

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Authors: Patricia Shirley Almeida Prado, Selma Paixão Argollo, Maria De Fátima Teixeira Guimarães, Leticia Matos Sobrinho

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Skeletal differential diagnosis is essential in forensic anthropology in order to differentiate skeletal trauma from normal osseous variation and pathological processes. Thus, part of forensic anthropological field is differentiate skeletal criminal injuries from the normal skeletal variation (bone fusion or nonunion, transitional vertebrae and other non-metric traits), non-traumatic skeletal pathology (myositis ossificans, arthritis, bone metastasis, osteomyelitis) from traumatic skeletal pathology (myositis ossificans traumatic) avoiding misdiagnosis. This case shows the importance of effective pathological diagnosis in order to accelerate the identification process of skeletonized human remains. THE CASE: An unidentified skeletal remains at the medico legal institute Nina Rodrigues-Salvador, of a male young adult (29 to 40 years estimated) showing a massive heterotopic ossification on its right tibia at upper epiphysis and adjacent articular femur surface; an extensive ossification on the right clavicle (at the sternal extremity) also presenting an heterotopic ossification at right scapulae (upper third of scapulae lateral margin and infraglenoid tubercule) and at the head of right humerus at the shoulder joint area. Curiously, this case also shows an unusual porosity in certain vertebrae´s body and in some tarsal and carpal bones. Likewise, his left fifth metacarpal bones (right and left) showed a healed fracture which led both bones distorted. Based on identification, of pathological conditions in human skeletal remains literature and protocols these alterations can be misdiagnosed and this skeleton may present more than one pathological process. The anthropological forensic lab at Medico-legal Institute Nina Rodrigues in Salvador (Brazil) adopts international protocols to ancestry, sex, age and stature estimations, also implemented well-established conventions to identify pathological disease and skeletal alterations. The most compatible diagnosis for this case is hematogenous osteomyelitis due to following findings: 1: the healed fracture pattern at the clavicle showing a cloaca which is a pathognomonic for osteomyelitis; 2: the metacarpals healed fracture does not present cloaca although they developed a periosteal formation. 3: the superior articular surface of the right tibia shows an extensive inflammatory healing process that extends to adjacent femur articular surface showing some cloaca at tibia bone disease. 4: the uncommon porosities may result from hematogenous infectious process. The fractures probably have occurred in a different moments based on the healing process; the tibia injury is more extensive and has not been reorganized, while metacarpals and clavicle fracture is properly healed. We suggest that the clavicle and tibia´s fractures were infected by an existing infectious disease (syphilis, tuberculosis, brucellosis) or an existing syndrome (Gorham’s disease), which led to the development of osteomyelitis. This hypothesis is supported by the fact that different bones are affected in diverse levels. Like the metacarpals that do not show the cloaca, but then a periosteal new bone formation; then the unusual porosities do not show a classical osteoarthritic processes findings as the marginal osteophyte, pitting and new bone formation, they just show an erosive process without bone formation or osteophyte. To confirm and prove our hypothesis we are working on different clinical approaches like DNA, histopathology and other image exams to find the correct diagnostic.

Keywords: bone disease, forensic anthropology, hematogenous osteomyelitis, human identification, human remains

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Authors: Chia-Feng Lu, Yuh-Jen Wang, Shin Teng, Yu-Te Wu, Sui-Hing Yan

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Brain functional networks based on resting-state EEG data were compared between patients with mild Alzheimer’s disease (mAD) and matched patients with amnestic subtype of mild cognitive impairment (aMCI). We integrated the time–frequency cross mutual information (TFCMI) method to estimate the EEG functional connectivity between cortical regions and the network analysis based on graph theory to further investigate the alterations of functional networks in mAD compared with aMCI group. We aimed at investigating the changes of network integrity, local clustering, information processing efficiency, and fault tolerance in mAD brain networks for different frequency bands based on several topological properties, including degree, strength, clustering coefficient, shortest path length, and efficiency. Results showed that the disruptions of network integrity and reductions of network efficiency in mAD characterized by lower degree, decreased clustering coefficient, higher shortest path length, and reduced global and local efficiencies in the delta, theta, beta2, and gamma bands were evident. The significant changes in network organization can be used in assisting discrimination of mAD from aMCI in clinical.

Keywords: EEG, functional connectivity, graph theory, TFCMI

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