Bio-medical imaging (X-ray, CT, ultrasound, ECG), genome sequences applications of deep neural network and machine learning in diagnosis, detection, classification, and segmentation of COVID-19: a Meta-analysis & systematic review.

This review investigates how Deep Machine Learning (DML) has dealt with the Covid-19 epidemic and provides recommendations for future Covid-19 research. Despite the fact that vaccines for this epidemic have been developed, DL methods have proven to be a valuable asset in radiologists' arsenals for the automated assessment of Covid-19. This detailed review debates the techniques and applications developed for Covid-19 findings using DL systems. It also provides insights into notable datasets used to train neural networks, data partitioning, and various performance measurement metrics. The PRISMA taxonomy has been formed based on pretrained(45 systems) and hybrid/custom(17 systems) models with radiography modalities. A total of 62 systems with respect to X-ray(32), CT(19), ultrasound(7), ECG(2), and genome sequence(2) based modalities as taxonomy are selected from the studied articles. We originate by valuing the present phase of DL and conclude with significant limitations. The restrictions contain incomprehensibility, simplification measures, learning from incomplete labeled data, and data secrecy. Moreover, DML can be utilized to detect and classify Covid-19 from other COPD illnesses. The proposed literature review has found many DL-based systems to fight against Covid19. We expect this article will assist in speeding up the procedure of DL for Covid-19 researchers, including medical, radiology technicians, and data engineers.

PulDi-COVID: Chronic obstructive pulmonary (lung) diseases with COVID-19 classification using ensemble deep convolutional neural network from chest X-ray images to minimize severity and mortality rates.

Background and Objective: In the current COVID-19 outbreak, efficient testing of COVID-19 individuals has proven vital to limiting and arresting the disease's accelerated spread globally. It has been observed that the severity and mortality ratio of COVID-19 affected patients is at greater risk because of chronic pulmonary diseases. This study looks at radiographic examinations exploiting chest X-ray images (CXI), which have become one of the utmost feasible assessment approaches for pulmonary disorders, including COVID-19. Deep Learning(DL) remains an excellent image classification method and framework; research has been conducted to predict pulmonary diseases with COVID-19 instances by developing DL classifiers with nine class CXI. However, a few claim to have strong prediction results; because of noisy and small data, their recommended DL strategies may suffer from significant deviation and generality failures. Methods: Therefore, a unique CNN model(PulDi-COVID) for detecting nine diseases (atelectasis, bacterial-pneumonia, cardiomegaly, covid19, effusion, infiltration, no-finding, pneumothorax, viral-Pneumonia) using CXI has been proposed using the SSE algorithm. Several transfer-learning models: VGG16, ResNet50, VGG19, DenseNet201, MobileNetV2, NASNetMobile, ResNet152V2, DenseNet169 are trained on CXI of chronic lung diseases and COVID-19 instances. Given that the proposed thirteen SSE ensemble models solved DL's constraints by making predictions with different classifiers rather than a single, we present PulDi-COVID, an ensemble DL model that combines DL with ensemble learning. The PulDi-COVID framework is created by incorporating various snapshots of DL models, which have spearheaded chronic lung diseases with COVID-19 cases identification process with a deep neural network produced CXI by applying a suggested SSE method. That is familiar with the idea of various DL perceptions on different classes. Results: PulDi-COVID findings were compared to thirteen existing studies for nine-class classification using COVID-19. Test results reveal that PulDi-COVID offers impressive outcomes for chronic diseases with COVID-19 identification with a 99.70% accuracy, 98.68% precision, 98.67% recall, 98.67% F1 score, lowest 12 CXIs zero-one loss, 99.24% AUC-ROC score, and lowest 1.33% error rate. Overall test results are superior to the existing Convolutional Neural Network(CNN). To the best of our knowledge, the observed results for nine-class classification are significantly superior to the state-of-the-art approaches employed for COVID-19 detection. Furthermore, the CXI that we used to assess our algorithm is one of the larger datasets for COVID detection with pulmonary diseases. Conclusion: The empirical findings of our suggested approach PulDi-COVID show that it outperforms previously developed methods. The suggested SSE method with PulDi-COVID can effectively fulfill the COVID-19 speedy detection needs with different lung diseases for physicians to minimize patient severity and mortality.

Application of Deep Learning Techniques in Diagnosis of Covid-19 (Coronavirus): A Systematic Review.

Covid-19 is now one of the most incredibly intense and severe illnesses of the twentieth century. Covid-19 has already endangered the lives of millions of people worldwide due to its acute pulmonary effects. Image-based diagnostic techniques like X-ray, CT, and ultrasound are commonly employed to get a quick and reliable clinical condition. Covid-19 identification out of such clinical scans is exceedingly time-consuming, labor-intensive, and susceptible to silly intervention. As a result, radiography imaging approaches using Deep Learning (DL) are consistently employed to achieve great results. Various artificial intelligence-based systems have been developed for the early prediction of coronavirus using radiography pictures. Specific DL methods such as CNN and RNN noticeably extract extremely critical characteristics, primarily in diagnostic imaging. Recent coronavirus studies have used these techniques to utilize radiography image scans significantly. The disease, as well as the present pandemic, was studied using public and private data. A total of 64 pre-trained and custom DL models concerning imaging modality as taxonomies are selected from the studied articles. The constraints relevant to DL-based techniques are the sample selection, network architecture, training with minimal annotated database, and security issues. This includes evaluating causal agents, pathophysiology, immunological reactions, and epidemiological illness. DL-based Covid-19 detection systems are the key focus of this review article. Covid-19 work is intended to be accelerated as a result of this study.

Bacterial endocarditis due to Eikenella corrodens: a case report.

Of all the causes of bacterial endocarditis, HACEK group consisting of Haemophilus, Actinobacillus actinomycetemcomitans, Cardiobacterium hominis, Eikenella corrodens, and Kingella Kingae are rare causative agents. We report a case of bacterial endocarditis by E. corrodens, which is one of the members of the HACEK group.

Water pollution from major industries in Paradip area--a case study.

This paper reveals the present status of water pollution generated from major industries in Paradip area. The source of water pollution and the existing pollution control measures are outlined. The quality of the surface water and ground water have been studied thoroughly and in consequence to this, further pollution control measures are recommended.

Epidemic of Vibrio cholerae serogroup O139 in Berhampur, Orissa.

During the months of May-June 2000, 194 patients with watery diarrhoea were admitted to the Infectious Diseases Ward of the M.K.C.G. Medical College, Berhampur. Ninety four rectal swabs were collected and processed according to the standard procedures. Vibrio cholerae strains were isolated from 20 samples. Of these 20 isolates, two were found to be V. cholerae O1 EITor Ogawa strain and 18 were confirmed to be V. cholerae serotype O139. All V. cholerae O139 isolates were of a single phage type (phage type 1) and the two O1 strains were of phage type 3 and phage type 27 respectively. All 20 V. cholerae isolates were positive for CAMP test, and showed uniform resistance to furazolidone and sensitivity to co-trimoxazole, amoxycillin, norfloxacin, tetracycline and gentamycin. V. cholerae O139 serotype has not been reported earlier in south Orissa. This is probably the first report of its isolation from this area.

A study on the venues of suicide.

This study was aimed to assess the venues of suicide and the related factors. One hundred and forty four (M-89. F-55) suicide cases undertaken for autopsy at the department of Forensic Medicine, Madras Medical College formed the study material. 33.71% of males and 3.64% of females had chosen the venues other than their houses. Most of the males suffering from mental illness (80%) had preferred places outside their house for this fatal act. Among the males, 71.74% of those who consumed insecticides and 87.5% who adopted self immolation, did so inside their houses. Comparatively lesser (53.33%) proportion of males resorted to hanging inside their houses.

Rhinosporidiosis presenting as urethral polyp.

Rhinosporidiosis is a very common disease endemic in India, Ceylon, East Africa and part of America. Extremely rare in Europe. Nose, naso-pharynx, nasal sinuses, larynx are the common sites of affection, but urethral lesion is very rare. Reports from India so far as our knowledge goes are not available. Symmers may be the only case report available so far. For the rarity of site of affection, the case is reported.

Farm-grade chlorpyrifos (Durmet) is genotoxic in somatic and germ-line cells of Drosophila.

The mutagenic potential of Durmet, a farm-grade formulation of chlorpyrifos, was studied in the Drosophila wing mosaic and sex-linked recessive lethal tests. Larvae of the 2nd or 3rd instar carrying suitable recessive genetic markers on chromosome 3 were exposed to different concentrations of the insecticide and the frequency of induction of mutant mosaic spots on the wings was noted. The Basc technique was followed to study the induction of sex-linked recessive lethals. On the basis of the frequency of induction of mosaic wing spots and sex-linked recessive lethals, it is concluded that Durmet is genotoxic in somatic cells as well as germ cells of Drosophila.

Studies on the genotoxicity of monocrotophos in somatic and germ-like cells of Drosophila.

Parryfos, a farm-grade formulation of monocrotophos, was tested for genotoxicity in the wing primordial cells and the male germ-line cells of Drosophila melanogaster. Larvae of the 2nd or 3rd instar, heterozygous for the wing-cell marker mutations mwh and flr3, were exposed to different concentrations of the insecticide in the food. The wings of the hatched flies were screened for the presence of mutant mosaic spots exhibiting the marker phenotypes. The frequency of induction of sex-linked recessive lethal mutations was used to assess genotoxic effects in male germ-line cells. The tested compound was genotoxic in both the somatic and the germ-line cells of Drosophila.

Mutagenicity of sumithion tested in Drosophila somatic and germ cells.

Sumithion, a broad-spectrum insecticide, was tested for its mutagenicity in the Drosophila wing-spot test and sex-linked recessive lethal test. Strains carrying the recessive mutant markers mwh and flr3 in their third chromosomes, expressed phenotypically as multiple trichomes or thickened and misshapen wing hairs in the adult wings, were used in the wing-spot test. Larvae transheterozygous for these markers were exposed to the insecticide in instant food and the sex-linked recessive lethal test was performed by the standard technique using the Basc strain. The compound is mutagenic in the wing primordial cells and induces recombination at high doses. Further, the frequency of induction of sex-linked recessive lethals is significant only at high treatment doses.

Acrylamide is genotoxic to the somatic and germ cells of Drosophila melanogaster.

The genotoxic effects of acrylamide, a recently detected carcinogen, have been studied in the somatic (wing primordia) and germ cells of Drosophila melanogaster by the wing mosaic assay and the sex-linked recessive lethal test respectively. Larvae, 72 +/- 4 h old, were exposed to 6 different concentrations of acrylamide ranging between 0.25 mM and 5.0 mM in instant medium for 48 h. It is observed that acrylamide is both mutagenic and recombinogenic in the wing disc cells and induces sex-linked recessive lethals.

Degradation of Alpha-, Beta-, and Gamma-Hexachlorocyclohexane by a Soil Bacterium under Aerobic Conditions.

A Pseudomonas sp., isolated from sugarcane rhizosphere soil, readily metabolized not only alpha and gamma isomers of hexachlorocyclohexane, but also the thermodynamically more stable beta isomer, under aerobic conditions. Bacterial degradation of the three isomers led to the accumulation of a transitory metabolite and eventual release of covalently linked chlorine as chloride in stoichiometric amounts.

Construction of growth reference standards for urban slum children in developing countries.

A cross-sectional sample of 2987 children in the age group of 1 to 10 years were selected from urban slums of Delhi for measurement of weight and height. Males and females were 53 and 47% respectively. Mean weight and height were calculated for both the sexes. Comparison of percentiles of weight and height with NCHS and ICMR standards showed that the 75th percentiles weight and height of the present study were comparable with 80 and 90% of 50th percentile of NCHS respectively. Hence, upper 25% of the sample arranged in ascending order of magnitude were used for the construction of reference standards of weight and height. Comparison of percentiles drawn from the top 25% of the sample demonstrated that 50th percentile of the present study corresponded to 80% of 50th percentile of the NCHS for weight and 90% of 50th percentile of NCHS of the height for both boys and girls. Also the 50th percentile of ICMR for weight and height for both the sexes. Standards constructed from such sample would be better suited for two important uses: (i) monitoring of Nutrition Programme, and (ii) to detect a child with abnormal growth at the earliest.

Mutagenicity of dimecron studied in 3 mosaic assays and the sex-linked recessive lethal test in Drosophila melanogaster.

The genotoxicity of dimecron, a systemic organophosphate pesticide, has been tested in the wing, eye and germ line mosaic assays and the sex-linked recessive lethal test in Drosophila melanogaster. Larvae heterozygous for recessive marker mutations were fed the compound for various periods of time. On emergence, the wings and eyes of the adults were screened for mosaic spots and the eggs laid by the females were checked for induction of female germ line mosaicism. Dimecron is mutagenic to the somatic and germ line cells of Drosophila and induces a high frequency of sex-linked recessive lethals.