Diseased Cases Research Articles

Clinical study on Moraxella-associated infectious keratoconjunctivitis (IKC) of small ruminants

Infectious keratoconjunctivitis (IKC) represents an important health problem in semi-desert and desert areas. The present study tries to investigate the possible role of Moraxella as a causative agent of IKC. A total number of 140 sterile conjunctival swabs from the diseased animals (93 sheep and 47 goats) of different ages showed signs of IKC were subsequently collected, bacteriologically examined to isolate Moraxella spp, which was successively isolated from 19 animals (11 sheep and 8 goats) with infection rate about 13.6%. In relation to age, a higher infection rate (19.2%) was recorded among sheep in the age group ≥ 12 to < 24 months and among goats in the age group ≥ 3 to < 6 months. Antimicrobial sensitivity test of obtained isolates revealed that Moraxella was 100% sensitive to Ciprofloxacin, Gentamicin, and Tylosin, and 79% to Oxytetracycline. All tested isolates were resistant to Vancomycin, Ampicillin plus Sulbactam, and Sulfamethoxazole plus Trimethoprim. Therapeutically, two therapeutic regimens were carried out to treat the diseased cases under field conditions and the results were illustrated in detail.

Automated detection of orofacial pain from thermograms using machine learning and deep learning approaches

AbstractThe main objectives of this study are (i) to perform automated segmentation of facial regions from thermograms using k‐means clustering algorithm and to classify the data into normal and orofacial pain (OFP) categories using various machine learning classifiers (ii) to implement the convolutional neural network (CNN) for classification of normal and OFP subjects which involves automated feature extraction and feature selection process. Fifty normal and 50 diseased cases suffering from orofacial pain were included in the study. Facial thermograms were segmented using k‐means algorithm, then statistical features were extracted and classified into normal and OFP using various machine learning classifier. Further, the deep learning networks such as VGG‐16 and DenseNet‐121 were used for automated feature extraction and classification of facial thermograms. The facial temperature variations of 3.46%, 3.4%, and 3.27% were observed in the front, right and left side facial regions respectively between the normal and the OFP subjects. Machine learning classifiers such as support vector machine (SVM) and random forest (RF) classifier provided the highest accuracy of 99%. On the other hand, deep learning models such as modified VGG‐16 achieved an average accuracy of 97% compared to modified DenseNet‐121 which produced an average accuracy of 68% in classification of normal and OFP thermograms. Thus, computer aided diagnosis of facial thermography could be used as a viable screening device for a reliable identification of tooth pathology before the occurrence of structural changes and complications.

Correlation of Status of Mastoid with Outcomes of Myringoplasty with Cortical Mastoidectomy in Mucosal Otitis Media with High Risk Perforation

Introduction: Chronic mucosal otitis media is one of the common disease prevalent in our society. This study was done to correlate the status of mastoid with outcomes of myringoplasty with cortical mastoidectomy in mucosal otitis media with high risk perforation. Methods: This prospective, observational study was done at Department of Otorhinolaryngology and Head and Neck Surgery, Tribhuvan University Teaching Hospital. Thirty-four patients of ag|e 15 and above with chronic mucosal otitis media having high-risk perforation undergoing cortical mastoidectomy with myringoplasty were included. The status of middle ear, aditus, and mastoid air cells were assessed. Post-operatively, patients were assessed for graft uptake and hearing after three months. The post-operative graft uptake and hearing results were correlated with the peroperative status. Four patients who had preoperative sensorineural hearing loss were studied in terms of graft uptake only. Results: The graft success rate in patients with normal mastoid air cells was 90% whereas in diseased cases was 71.4% which was statistically not significant with p value 0.20. The success rate in terms of hearing was 68.8% in normal mastoid whereas it was 64.3% in diseased mastoid which was statistically not significant with p-value of 1. Conclusion: In correlation with the status of mastoid air cells with graft uptake and hearing result, the observed differences were not statistically significant. However, averages of post-operative air conduction threshold and air-bone gap of all cases were better as compared to preoperative levels.

Correlation of Status of Mastoid with Outcomes of Myringoplasty with Cortical Mastoidectomy in Mucosal Otitis Media with High Risk Perforation

Introduction Chronic mucosal otitis media is one of the common disease prevalent in our society. This study was done to correlate the status of mastoid with outcomes of myringoplasty with cortical mastoidectomy in mucosal otitis media with high risk perforation.&#x0D; MethodsThis prospective, observational study was done at Department of Otorhinolaryngology and Head and Neck Surgery, Tribhuvan University Teaching Hospital. Thirty-four patients of ag|e 15 and above with chronic mucosal otitis media having high-risk perforation undergoing cortical mastoidectomy with myringoplasty were included. The status of middle ear, aditus, and mastoid air cells were assessed. Post-operatively, patients were assessed for graft uptake and hearing after three months. The post-operative graft uptake and hearing results were correlated with the peroperative status. Four patients who had preoperative sensorineural hearing loss were studied in terms of graft uptake only.&#x0D; ResultsThe graft success rate in patients with normal mastoid air cells was 90% whereas in diseased cases was 71.4% which was statistically not significant with p value 0.20. The success rate in terms of hearing was 68.8% in normal mastoid whereas it was 64.3% in diseased mastoid which was statistically not significant with p-value of 1.&#x0D; ConclusionIn correlation with the status of mastoid air cells with graft uptake and hearing result, the observed differences were not statistically significant. However, averages of post-operative air conduction threshold and air-bone gap of all cases were better as compared to preoperative levels.

Cross infection control awareness of dentists of Northern India for Covid-19 pandemic

Pandemic of COVID-19 is globally on the rise. Routes of transmission include human to human contact. Dentists are at highest risk of coronavirus infection contraction and dissemination. Due to recent outbreak of this disease, definitive guidelines on this subject are not sufficient for various procedures. Awareness of protective measures for dental practices may reduce the number of new cases within the country. The aim of this study was to evaluate the awareness of cross infection control measures during stage I of pandemic of COVID-19 within dental practices of Lucknow &amp; Barabanki district Uttar Pradesh, India. A cross sectional study based on evidence provided by Department of Periodontics, Chandra Dental College &amp; Hospital, Safedabad, Barabanki was conducted during the stage I of spread of coronavirus amongst general dental practitioners of Lucknow &amp; Barabanki district Uttar Pradesh, India. A questionnaire comprising of 10 questions pertinent to the cross-infection protocol for COVID-19 in a dental setting was constructed. Sample size was calculated for registered general dental practitioners of Lucknow &amp; Barabanki district Uttar Pradesh, India. The form was communicated to 200 general dental practitioners all over Lucknow &amp; Barabanki district Uttar Pradesh, India. Out of these, 143 (71.5%) responded. Majority participants showed adequate level of awareness (more than 66%), for protection measures against corona virus COVID-19 in a dental practice. However, few aspects need more emphasis. such as during initial patient interview, temperature evaluation, radiographic records, pre-operative rinses, nature of permissible procedures, surface disinfection, irrigation and drainage methods, to control the chain the infection transmission. Earlier awareness of COVID-19 specific protection measures to health professionals may reduce the number of new diseased cases. Strict adherence to social distancing generally and COVID-19 specific cross infection control measures in a dental setting might help in timely control of this potentially deadly disease.

Bacteriological and Molecular Comparative Study between Staphylococcus aureus Isolated from Animals and Human

Staphylococcus aureus represents a serious health hazard on both animals and humans. The main goal of the present work was to compare between S. aureus isolated from animal and human origin. This was achieved through studying the virulence, phenotypic characterization, genotypic testing of mecA gene, analysis the antibiotic resistance profile of the recovered S. aureus isolates. A total number of 165 samples were collected from clinical mastitic cows and sheep, pus from abscesses collected from septic wounds of infected animals, respectively. Moreover, blood, pus swabs from abscesses and septic wounds, and sputum samples were collected from diseased humans from Assiut Governorate, Egypt. The results revealed that incidence of S. aureus isolates recovered from the examined animal samples were 8.33%, 100% and 20%, per, while from human cases (blood, pus and sputum) were 16.67%, 53.49% and 75%, independently. Using Staphaurex kits, the prevalence of coagulase positive S. aureus from animal samples reached 8.33%, 100% and 20%, but from the diseased human cases were 16.67%, 53.49% and 75%, respectively. Antimicrobial Sensitivity Testing of the animal isolateswere resistant to cefoxitin (15.79%), tetracycline (10.53%), clindamycin and erythromycin (10.53%), while the isolates weresensitive to gentamicin (100%), trimethoprim + sulfamethoxazole and vancomycin (94.74% for each). However, S. aureus human isolateswere resistant to cefoxitin (75%) and tetracycline (78.57%) and sensitive to vancomycin (100%), ciprofloxacin (89.29%) and trimethoprim+ sulfamethoxazole (82.14%). Out of 47 identified S. aureus strains, 3 from animal isolates (15.79%) and 21 from human isolates (75%) proved to be methicillin-resistant (MRSA). Furthermore, one animal isolate (5.26%) and 12 human isolates (42.86%) were multi-drug resistant (MDR). S. aureus isolates from animal and humans were subjected to genotypic characterization of mecA gene using PCR. All the animal and human isolates were positive for mecA gene with a percentage of 100%. The results of this study provide that from both animals and human samples; the isolation rate of S. aureus was greater than that of MRSA followed by MDR.

Virological, Molecular And Immuno-Biochemical Studies Of Lumpy Skin Disease In Naturally Infected Cattle

This study aimed to diagnose Lumpy skin desease by isolation and identification of LSD from suspected naturally infected cattle and to study its effect on immuno-biochemical parameters, inflammatory and oxidative stress markers. The study was conducted on 25 cattle, 1-3 years age from two cities in the Sharkia governorate. Ten clinically healthy cattle represented the control group and fifteen suspected diseased cases by LSD represented the infected group. The clinical signs of suspected cases showed anorexia, skin nodules all over the body, fever above 40˚C, edema in forelimbs and dewlap, enlarged superficial lymph nodes, retarded milk production, and abortion in some cases. The virological examination of LSDV from the samples of skin nodules was done. Isolation from skin nodules was done on MDBK cell line and embryonated chiken egg through chorioallantoic membrane route followed by identification using fluorescence technique . Molecular studies including phylogenetic analysis for three positive isolates showed similarity to previously locally isolated strains in Egypt and close relation to strains of SPPV. Immuno-biochemical results revealed a significant increase in aspartate aminotransferase , alanine aminotransferase , alkaline phosphatase , Malondialdehyde , Tumor necrosis factor , Interleukin4,immunoglobulin M and immunoglobulin G . Meanwhile, a significant decrease in total protein, albumin, globulin, Glutathione peroxidase, phagocytic assay, calcium, inorganic phosphorous, sodium, and potassium with a non-significant change in magnesium was seen when compared to control ones. It could be concluded that the infection with LSD in cattle induce severe effects on immuno-biochemical, antioxidant parameters, and inflammatory markers causing great economic loss

WITHDRAWN: The impact of various policy factors implemented for controlling the spread of COVID-19

More than sixty million cases were affected by the novel corona virus around the world till date. The virus has reached more than 200 countries and more than seven lakh people have lost their lives globally so far. To control the spread of this virus many countries have taken extreme measures but still couldn’t control the spread. The primary objective of this analysis is to classify the various policy factors adopted by the countries to manage the spread of Covid-19. Our study uses Oxford Covid-19 Government Response Tracker (OxCGRT) dataset and Autoregressive Integrated Moving Average (ARIMA) model as the model for forecasting. The representation is trained using day wise number of infected cases reported in each country from August’2020 to October’2020 and then forecasts the number of infections for five days from 15th November’ 2020 to 19th November’2020. We have included 15 countries in our study and analysed 13 factors which includes 8 factors in Containment and Closure policies category, 2 factors in Economic policies category and 3 factors in Health System policies category. We analysed the impact of above factors by comparing the forecasted number of affected people with the actual total diseased cases reported in those five days. The study discovers the fact that out of thirteen policy factors, the countries which concentrated more on policies in economic category during the pandemic have helped in controlling the dissemination of covid-19.

On the Role of Ionic Modeling on the Signature of Cardiac Arrhythmias for Healthy and Diseased Hearts

Computational cardiology is rapidly becoming the gold standard for innovative medical treatments and device development. Despite a worldwide effort in mathematical and computational modeling research, the complexity and intrinsic multiscale nature of the heart still limit our predictability power raising the question of the optimal modeling choice for large-scale whole-heart numerical investigations. We propose an extended numerical analysis among two different electrophysiological modeling approaches: a simplified phenomenological one and a detailed biophysical one. To achieve this, we considered three-dimensional healthy and infarcted swine heart geometries. Heterogeneous electrophysiological properties, fine-tuned DT-MRI -based anisotropy features, and non-conductive ischemic regions were included in a custom-built finite element code. We provide a quantitative comparison of the electrical behaviors during steady pacing and sustained ventricular fibrillation for healthy and diseased cases analyzing cardiac arrhythmias dynamics. Action potential duration (APD) restitution distributions, vortex filament counting, and pseudo-electrocardiography (ECG) signals were numerically quantified, introducing a novel statistical description of restitution patterns and ventricular fibrillation sustainability. Computational cost and scalability associated with the two modeling choices suggests that ventricular fibrillation signatures are mainly controlled by anatomy and structural parameters, rather than by regional restitution properties. Finally, we discuss limitations and translational perspectives of the different modeling approaches in view of large-scale whole-heart in silico studies.

Gross and Histopathological Study of the Genitalia in Goats: 2. Tubular Genital Organs (Uterine tubes and Uterus)

The aim of this study was to detect the microscopic and macroscopic lesions in uterine tubes and uterus in Sluaimani abattoir, Kurdistan region/Iraq. The total samples collected were 340 genitalia of does of pregnant and non-pregnant. 37.05% (126/340) of the samples were pregnant and 37.35% (127/340) of the samples were observed without gross lesions and 2.23% (10/340) were noticed with uterine tube gross abnormalities and the remaining 34 (12.941%) samples were recorded as anatomical lesions and pathological lesions of uterus. The a numbers of uterine tubes abnormalities were 11 out of 340 specimens (3.235%), and the most common lesions were; salpingitis 6 cases (7.64%); 1 case from each of hydrosalpinx and Pyosalpinx, respectively (0.294%). Microscopically, the lesions of salpingitis were sloughing off the part of the epithelium and infiltration of inflammatory cells. Three specimens of cyst on uterine tubes (0.882%). The numbers of uterine lesions were 44 specimens which shared 12.941% of abnormalities out of the 340 collected specimens. The most common diseased genital cases were; endometritis and metritis which 21 cases (6.176%), which were histopathologically characterized by a significant increase in the endometrial thickness due to diffuse infiltration of inflammatory cells mainly lymphocytes, the proliferation of fibroblasts with deposition of extracellular matrix. Five pyometra (1.470%), which was histolopatholgically characterized by definite increase in the uterine wall thickness, especially in the endometrium due to infiltration of light pinkish fibrinous inflammatory exudates with mild inflammatory cell proliferation. Three Hydrometra specimens (0.882%), and five endometrial cystic hyperplasia (1.470%). The microscopic lesions for them include massive cystic dilatation of the uterine gland that contains pinkish granular secretion, infiltration of light pinkish edematous fluid in the endometrial stroma associated with inflammatory cells. Two specimens of uterine wall with cysticercus tenuicolis (0.588%), and one uterine melanoma (0.294%), The histopathological features for the uterine melanoma include; deposition of the dark black melanin pigment within the phagocytic cells. Uterine leiomyosarcoma was one specimens (0.294%), which histologically, appear as pleomorphic cells variable in shape and size with different nuclear size randomly oriented in different directions, some of these cells were hyperchromatic with an abnormal mitotic figure. One case of cyst on the uterine wall was found (0.294%), and five cervicitis (1.470%). Finally, it could be concluded that uterine tubes, and uterus abnormalities constitute a percentage (3.235%, and 12.941%), respectively. In this study, uterine melanoma, and uterine leiomyosarcoma were firstly recorded in this study in Iraq and Kurdistan region.

Nowcasting the COVID-19 pandemic in Bavaria.

To assess the current dynamics of an epidemic, it is central to collect information on the daily number of newly diseased cases. This is especially important in real‐time surveillance, where the aim is to gain situational awareness, for example, if cases are currently increasing or decreasing. Reporting delays between disease onset and case reporting hamper our ability to understand the dynamics of an epidemic close to now when looking at the number of daily reported cases only. Nowcasting can be used to adjust daily case counts for occurred‐but‐not‐yet‐reported events. Here, we present a novel application of nowcasting to data on the current COVID‐19 pandemic in Bavaria. It is based on a hierarchical Bayesian model that considers changes in the reporting delay distribution over time and associated with the weekday of reporting. Furthermore, we present a way to estimate the effective time‐varying case reproduction number Re(t) based on predictions of the nowcast. The approaches are based on previously published work, that we considerably extended and adapted to the current task of nowcasting COVID‐19 cases. We provide methodological details of the developed approach, illustrate results based on data of the current pandemic, and evaluate the model based on synthetic and retrospective data on COVID‐19 in Bavaria. Results of our nowcasting are reported to the Bavarian health authority and published on a webpage on a daily basis (https://corona.stat.uni-muenchen.de/). Code and synthetic data for the analysis are available from https://github.com/FelixGuenther/nc_covid19_bavaria and can be used for adaption of our approach to different data.

Delivering Systemic Anti-Cancer Treatment Via Another Route of Administration As an Option to Reduce Exposure to COVID-19 in Patients with Multiple Myeloma in the UK

Introduction:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a strain of coronavirus that causes a respiratory illness known as COVID-19. COVID-19 is a pandemic affecting many countries globally.(1) As of 23rd July 2020, there have been 297,146 lab-confirmed cases of COVID-19 in the UK and 45,554 people who tested positive for the virus have died.(2) Patients with multiple myeloma (MM) are at a higher risk of contracting the virus and experiencing more severe outcomes.(3-6) The higher risk is driven by a compromised immune system, the use of immunosuppressive agents and patient characteristics aligning with key risk factors - patients with MM are often elderly and have multiple co-morbidities.(7) In light of the COVID-19 outbreak, NHS England and NICE have issued guidance to modify usual care to reduce patient exposure to COVID-19. For patients with cancer, NICE recommend delivering systemic anti-cancer treatment in different and less immunosuppressive regimens, different locations (ideally at home) or via another (less invasive and/or less resource intensive) route of administration where possible.(8)(9)The objective of this analysis is to explore the impact of switching patients from intravenous (IV) treatments requiring hospital administrations to subcutaneous (SC) or oral alternatives which can be administered at home or in an outpatient setting which reduces the patient's potential exposure to COVID-19.Methods:A decision tree model was developed in Microsoft Excel® (Figure 1). Patients enter the model and are assigned a probability of being treated; those that are treated are then assigned a probability of IV, SC or oral-based therapy. Based on the route of administration, patients are assigned a probability of contracting COVID-19 and, for those patients that do contract the virus, a probability of death from the virus is estimated. The model compares the outcomes from two identical decision trees: one informed by the pre-COVID-19 treatment pathway and one informed by the post-COVID-19 pathway. Model inputs, including COVID-19 inputs (e.g., number of active and diseased COVID-19 cases among patients with MM), have been informed by the literature and clinical opinion. Costs reflected in the model include: treatment of COVID-19, treatment for MM and administration of MM treatments. Scenario analyses explore lower and upper bounds for key inputs. Results are presented from a UK perspective and a 1-year time horizon (from model entry) is considered.Results:Per the model, treating patients with oral therapies is shown to reduce the number of COVID-19 cases and the number of COVID-19 deaths in patients with MM compared with IV- and SC-delivered therapies. These outcomes translate into cost savings driven by costs avoided in treating COVID-19. There was a limited difference in the costs of treating the underlying MM despite the switch. However, there were additional cost savings demonstrated through avoiding expensive and resource intensive administration appointments associated with IV therapies, and to a lesser extent SC therapies. The use of oral therapies has also aided the increase in telemedicine for routine appointments - scenarios exploring this demonstrate further savings. These results are driven by the perceived risk attached to each of the different routes of administration - scenario analyses demonstrated that assuming even the lower bound risk (an assumed additional risk of 10%) for IV therapies vs. oral therapies, a significant number of COVID-19 cases and deaths were avoided, and costs reduced.Conclusions:Changes to the treatment pathway for patients with MM in light of the COVID-19 pandemic aim to reduce the exposure to the virus for these patients. The model demonstrates that simply switching the route of administration can reduce the number of COVID-19 cases and deaths . This has important implications in avoiding severe outcomes, decreasing the spread of the virus and reducing the cost and resource use burden to the healthcare system. In addition, the model reflects potential efficiencies which may extend beyond the COVID-19 pandemic (e.g. telemedicine) to optimize clinical practice for patients with MM in the longer-term.DisclosuresCranmer:Takeda: Current Employment. Podkonjak:Takeda: Current Employment. Benson:Takeda: Current Employment. Dabora:Takeda: Current Employment. Jackson:Merck Sharp and Dohme: Honoraria; Chugai: Honoraria; Amgen: Honoraria; Janssen: Honoraria; Celgene: Honoraria; Takeda: Honoraria; Roche: Honoraria.

Gender Effect on Political Leaders' Nonverbal Communicative Structure during the COVID-19 Crisis.

During the COVID-19 pandemic, there has been intense interest in political leaders’ nonverbal communicative structures (NCS) during televised appearances. This study analyzes the effect of gender on leaders’ NCS and presents theoretical and analytical frameworks of gendered NCS. We analyzed 20 televised appearances by 10 heads of state (five males and five females) from democratic Western countries during the COVID-19 pandemic. The findings revealed that gender had a significant effect on leaders’ NCS, indicating that leaders presented NCS that corresponded to their gender. Male leaders’ masculine NCS included competition, warning, threatening, and scaring behavior, broad proxemics, tension leakage, and illustrative gestures, while female leaders presented feminine NCS of cooperativeness, emotional communication, empathy, optimism, eye contact, and flexible expressions. Furthermore, the effect of gender on leaders’ NCS had an interaction effect with the situation of the pandemic, indicating that countries with a female leader had fewer diseased and severe cases and more calmness and healing NCS. The conclusions present theoretical and analytical frameworks that explain the central effect of gender on contemporary leaders’ NCS. This study develops advanced distinctive profiles for male versus female leaders’ NCS of emotions, cognition, and behavior during a crisis.

Ultrasonography of the Kidneys in Healthy and Diseased Camels (Camelus dromedarius).

This review article is written to describe the results of ultrasonography of the kidneys in healthy camels as well as camels with some renal disorders. In the dromedary camel, the physiology of the kidney is of interest in view of the specialization of the camel to hot dry deserts and to prolonged periods without water. It plays an important role in water conservation through the production of highly concentrated urine that may predispose animal to varieties of renal disorders. Examples of kidney affections in dromedary camels are renal capsular pigmentation, medullary hyperemia, subcapsular calcification, cortical and medullar discoloration, hemorrhage in renal pelvis, nephrolithiasis, and hydatidosis. Congestion, hemorrhage, hydronephrosis, acute glomerulonephritis, subacute glomerulonephritis, chronic glomerulonephritis, diffuse interstitial nephritis, focal interstitial nephritis, renal cyst, hyaline degeneration, renal amyloidosis, tubular nephrosis, pyelonephritis, hemosiderosis, and renal toxicity. When the kidney is examined by ultrasonography, the clinician can get sufficient information about the size, position, and echo patterns of the renal cortex and medulla and renal pelvis and outlines of the renal blood vessels. In recent years, ultrasonography has been used in camels for scanning of the healthy status as well as evaluation and determining the diagnosis and prognosis of diseased cases. Examples of diseases evaluated by ultrasonography are paratuberculosis, trypanosomiasis, pneumonia, pleurisy, gastrointestinal neoplasms, chronic peritonitis, splenic abscessation, and hepatic disorders. Of the renal disorders assessed by ultrasonography are nephrolithiasis, hydronephrosis, pyelonephritis, renal abscessation, and renal neoplasms. Ultrasound guidance in biopsy of renal specimens has also been reported in dromedary camels.

Cascaded deep learning classifiers for computer-aided diagnosis of COVID-19 and pneumonia diseases in X-ray scans

Computer-aided diagnosis (CAD) systems are considered a powerful tool for physicians to support identification of the novel Coronavirus Disease 2019 (COVID-19) using medical imaging modalities. Therefore, this article proposes a new framework of cascaded deep learning classifiers to enhance the performance of these CAD systems for highly suspected COVID-19 and pneumonia diseases in X-ray images. Our proposed deep learning framework constitutes two major advancements as follows. First, complicated multi-label classification of X-ray images have been simplified using a series of binary classifiers for each tested case of the health status. That mimics the clinical situation to diagnose potential diseases for a patient. Second, the cascaded architecture of COVID-19 and pneumonia classifiers is flexible to use different fine-tuned deep learning models simultaneously, achieving the best performance of confirming infected cases. This study includes eleven pre-trained convolutional neural network models, such as Visual Geometry Group Network (VGG) and Residual Neural Network (ResNet). They have been successfully tested and evaluated on public X-ray image dataset for normal and three diseased cases. The results of proposed cascaded classifiers showed that VGG16, ResNet50V2, and Dense Neural Network (DenseNet169) models achieved the best detection accuracy of COVID-19, viral (Non-COVID-19) pneumonia, and bacterial pneumonia images, respectively. Furthermore, the performance of our cascaded deep learning classifiers is superior to other multi-label classification methods of COVID-19 and pneumonia diseases in previous studies. Therefore, the proposed deep learning framework presents a good option to be applied in the clinical routine to assist the diagnostic procedures of COVID-19 infection.

Disinfection and outcome of root canal treatment using single-file or multifile systems and Ca(OH)2 medication.

This clinical study reports on the antibacterial effects and outcome of endodontic treatment using either a single-file or a multifile system, associated with calcium hydroxide interappointment medication. The root canals of single-rooted teeth with apical periodontitis were treated by using either Reciproc or BioRaCe instrument systems, 2.5% NaOCl irrigation, and calcium hydroxide medication. Bacteriological samples taken before preparation and immediately before obturation were evaluated for total bacterial counts by quantitative real-time polymerase chain reaction (qPCR). Patients were followed up and the treatment outcome was assessed by clinical and radiographic criteria. Decreasing lesions were classified as success in a lenient criterion or failure in a rigid one. Bacteria were detected in all initial samples (47 cases) and were significantly reduced after treatment in both groups (p<0.001). In the Reciproc and BioRaCe groups, 7/25 (28%) and 11/22 (50%) root canals yielded negative qPCR results before obturation, respectively (p>0.05). Quantitative bacterial reduction was similar between groups (p>0.05). The success rate in the BioRaCe group was 95.5% and 77% in the loose and rigid criterion, respectively. In the Reciproc group, corresponding figures were 88% and 76%. Differences in outcome were not significant (p>0.05). No diseased case showed negative qPCR results for bacteria. A difference of >1 Log10 counts was observed between healed and diseased cases. Root canal treatments of teeth with apical periodontitis using a single-file or a multifile system for preparation, associated with NaOCl irrigation and calcium hydroxide interappointment medication, showed similar antibacterial effectiveness and success rate.

Digital resolution enhancement in low transverse sampling optical coherence tomography angiography using deep learning

Optical coherence tomography angiography (OCTA) requires high transverse sampling density for visualizing retinal and choroidal capillaries. Low transverse sampling causes digital resolution degradation, such as the angiograms in wide-field OCTA. In this paper, we propose to address this problem using deep learning. We conducted extensive experiments on converting the centrally cropped 3 × 3 mm2 field of view (FOV) of the 8 × 8 mm2 foveal OCTA images (a sampling density of 22.9 µm) to the native 3 × 3 mm2 en face OCTA images (a sampling density of 12.2 µm). We employed a cycle-consistent adversarial network architecture in this conversion. The quantitative analysis using the perceptual similarity measures shows the generated OCTA images are closer to the native 3 × 3 mm2 scans. Besides, the results show the proposed method could also enhance the signal-to-noise ratio. We further applied our method to enhance diseased cases and calculate vascular biomarkers, which demonstrates its generalization performance and clinical perspective.

Therapeutic Effect of Lactobacillus-based Probiotic on Canine Acute Diarrhea

The present study was conducted to evaluate therapeutic effect of commercial lactobacillus-based probiotic as a single therapeutic agent against acute diarrhea in dogs. About 47 dogs were studied in the present work, included 20 apparent healthy dogs and 27 diseased dogs suffered from acute diarrhea. About 17 diarrheic dogs were treated with probiotic for 5 days. Physical and clinical examinations were performed for all dogs. Blood and serum samples were collected to evaluate hemato-biochemical status at Day 0 and Day 5 after treatment. Stool was observed and scrutinized for its consistency during treatment. Results showed a decreased recovery time of diseased cases at 2.4±0.02 days. Significant decrease of PCV and WBCs count, significant increase total protein, albumin, A/G ratio and significant decrease of elevated ALT, AST and bilirubin at Day 5 was recorded compared to diarrheic dogs at day 0. Conclusion: the data indicates an efficient treatment with lactobacillus-based probiotic as solo therapeutic agent against canine acute diarrhea, not only reduce the recovery time, but also, enhance liver functions and improve the fecal consistency.

The sensitivity and specificity analyses of ambient temperature and population size on the transmission rate of the novel coronavirus (COVID-19) in different provinces of Iran

On 10 April 2020, Iran reported 68,192 COVID-19 cumulative cases including 4232 death and 35,465 recovery cases. Numerous factors could influence the transmission rate and survival of coronavirus. On this basis and according to the latest epidemiological researches, both ambient temperature (AT) and population size (PS) can be considered as significant transmissibility factors for coronavirus. The analysis of receiver operating characteristics (ROC) allows measuring the performance of a classification model using the confusion matrix. This study intends to investigate the sensitivity of AT and PS on the transmission rate of the novel coronavirus in different provinces of Iran. For this purpose, the information of each province of Iran including the annual average of AT and the number of healthy and diseased cases are categorized. Subsequently, the sensitivity and specificity analyses of both AT and PS factors are performed. The obtained results confirm that AT and PS have low sensibility and high sensitivity, respectively. Thus, there is no scientific reason to confirm that the number of COVID-19 cases in warmer climates is less than that of moderate or cold climates. Therefore, it is recommended that the cities/provinces with a population of over 1.7 million people have stricter inspections and more precise controls as their management policy.

Hybrid Multi Cloud based Disease Prediction Model for Type II Diabetes

Advancements in health informatics pave the way to explore new medical decision making systems which are characterized by an exponential evolution of knowledge. In the medical domain, disease prediction has become the centre of research with the increasing trend of healthcare applications. The predictive knowledge for the diagnosis of disease highly depends on the subjective knowledge of the experts. So the development of a disease prediction model in time is essential for patients and physicians to overcome the problem of medical distress. This paper explores a hybrid approach (Cooperative Ant Miner Genetic Algorithm) for classifying the medical data. Three benchmarked Type II diabetic datasets (US, PIMA, German) from the UCI machine learning repository were used to analyze the effectiveness of the disease prediction model. The devised classification algorithm with a Soft-Set approach was deployed in a Multi-Cloud environment for enhancing the storage and retrieval of data with reduced response and computation time. The cooperative classification algorithm in the cloud database distinguishes the diseased cases from the normal ones .The soft set theory analyzes the severity of the diseased cases by calculating the percentage of diabetic risk using soft intelligent rules and stores them in a separate knowledge base. Thus the proposed model serves as a suitable tool for eliciting and representing the expert’s decision which aids in prediction of Type II diabetic risk percentage leading to the timely treatment of patients.