ABSTRACT
Melanoma is an abnormal proliferation of skin cells that arises and develops in most of the cases on surface of skin that is exposed to copious amounts of sunlight. This common type of cancer may develop in areas of the skin that are not exposed to a much abundant sunlight. The research addresses the problem of Segmentation and Classification of Melanoma Skin Cancer. Melanoma is the fifth most common skin cancer lesion. Bio-medical Imaging and Analysis has become more promising, interesting, and beneficial in recent years to address the eventual problems of Melanoma Skin Cancerous Tissues that may develop on Skin Surfaces. The evolved research finds that Attributes Selected for Classification with Color Layout Filter model. The research has produced an optimal result in terms of certain performance metrics accuracy, precision, recall, PRC (what is PRC? Expansion is needed in Abstract), The proposed method has yielded 90.96% of accuracy and 91% percent of precise and 0.91 of recall out of 1.0, 0.95 of ROC AUC, 0.87 of Kappa Statistic, 0.91 of F-Measure. It has been noticed a lowest error with reference to proposed method on certain dataset. Finally, this research recommends that the Attribute Selected Classifier by implementing one of the image enhancement techniques like Color Layout Filter is showing an efficient outcome.
ABSTRACT
SARS-nCoV was identified as corona virus had spread worldwide very quickly and affected more than million people worldwide. To halt this acceleration and for efficient control the knowledge on genomic information is of utmost importance. We attempted to determine the nature of variation i.e., insertion, deletion, substitution, among structural sequences required to code for membrane, spike, nucleocapsid, envelope protein and glycosylation variation between SARS CoV and SARS nCoV spike glycoproteins, respectively. Comparative sequence analysis was performed by using retrieved sequences from the NCBI database. The analyzed sequences revealed, that the sequences coding for envelope protein show minor substituting amino acids. SARS CoV showed 94.74 percent amino acid identities with SARS nCoV amino acid sequences coding for envelope protein. In comparison to SARS nCoV, distinct amino acid residues vary in SARS CoV sequences coding for membrane, nucleocapsid, and spike proteins, respectively. S protein coding sequences of SARS CoV exhibited one deletion, six insertion and six hundred three substitutions in SARS nCoV sequence. Insertion of valine was found in receptor binding domain of SARS nCoV at position 487, and NSPR amino acid residues at position 683-686. Deletions and substitutions were also found in nucleotide sequences of strain B.1.617.2 of SARS nCoV. Additionally, binding interaction pattern of ACE2 receptor protein with original wild-type SARS-CoV-2 strain with the recently evolved Omicron variant was also evaluated. The docking results substantiated that the specific variation in binding residues is likely to impact virulence pattern of both variants.
ABSTRACT
Environmental monitoring and impact assessment reports are created by compiling and analyzing data. Ensuring that an organization's operations do not harm human health or the natural environment is the primary goal of environmental monitoring. To conserve the earth, safeguard public health, and minimize expenses, environmental monitoring systems are becoming increasingly important. When discussing IoT-enabled environmental monitoring, waste management, air pollution, and extreme weather typically come up. Infectious illness is induced by a newly discovered coronavirus (COVID-19). A mild to severe respiratory sickness is the most common symptom of infection with COVID-19 and does not necessitate any special treatment for most patients. An increased risk of serious sickness is seen in the elderly, as well as individuals who have pre-existing medical conditions. COVID-19, the virus that causes and transmits the disease, can be prevented and slowed down by being educated about it. Using an alcohol-based hand sanitizer or washing your hands often is a good way to keep yourself and others safe from infection. Different people are affected by COVID-19 in various ways. A viral infection usually results in mild to moderate symptoms, and the majority of individuals will be able to heal at home without the need for medical attention. Sensors are used to monitor and record every aspect of the environment in their respective settings. The most commonly utilized sensors include proximity sensors, temperature sensors, smoke sensors, etc. With an ever-increasing population, increasing industrial activity, and rising energy consumption, it is imperative that the environmental monitoring process be made more accurate and efficient by using cuttingedge, automated monitoring applications and devices. It will be a useful tool for monitoring climate change. People, energy, goods, and information will move more efficiently as a result. In addition, it will continue to adapt as scientists and leaders come to new agreements on the actions, we must take to safeguard ourselves from rising temperatures and hazardous climate circumstances. © 2022 Nova Science Publishers, Inc..
ABSTRACT
Mucormycosis is a lethal human disease caused by fungi of the order Mucorales. Mucormycosis is caused by fungi mainly belonging to the genera Mucor, Rhizopus, and Lichtheimia, all of which belong to the order Mucorales. The number of individuals with mucormycosis-causing disorders has increased in recent years, hence, leading to the spread of mucormycosis. Throughout the coronavirus disease 2019 (COVID-19) pandemic, numerous cases of mucormycosis in COVID-19-infected patients have been reported worldwide, and the illness is now recognized as COVID-19-associated mucormycosis, with most of the cases being reported from India. Immunocompromised patients such as those with bone marrow sickness and uncontrolled diabetes are at a greater risk of developing mucormycosis. Genes, pathways, and other mechanisms have been studied in Mucorales, demonstrating a direct link between virulence and prospective therapeutic and diagnostic targets. This review discusses several proteins such as high-affinity iron permease (FTR1), calcineurin, spore coat protein (CotH), and ADP-ribosylation factors involved in the pathogenesis of mucormycosis that might prove to be viable target(s) for the development of novel diagnostic and therapeutic methods. Copyright © 2022 The Chinese Medical Association, Published by Wolters Kluwer Health, Inc.
ABSTRACT
MXenes have gained significant importance in many applications in the fields of energy, environment and healthcare. The versatile features of MXenes enable them as a wonder material for their wide category of applications. Tunable surface chemistry and nano-dimensional layered features of MXenes are accounted for their improved multifunctional properties among the other two-dimensional materials. Of various applications, MXenes show the relevant properties toward antimicrobial disinfection of bacteria, fungi and viruses including the SARS responsible for COVID-19. Therefore, the development, characterizations and mechanism of MXenes-based materials are important to bring these advanced materials for their real-time antimicrobial applications. In this context, this review presents a glimpse of MXenes in terms of their synthesis processes, characterizations, antimicrobial properties, and elucidate their mechanism of actions toward antibacterial, antifungal and antiviral activities. Finally, it concludes with a future perspective of MXenes towards their biomedical applications.
ABSTRACT
Background: The recent coronavirus disease 2019 lockdowns forced people to stay indoors, resulting in lower physical activity, and change in dietary patterns, impacting glycemic control in the diabetic population. We aimed to assess the impact of the 3-month lockdown on glycemic control among outpatients with type 2 diabetes (T2DM) being treated at our hospital. Study Design: This retrospective study included data of outpatients aged & GE;30 years with preexisting T2DM, regularly attending the clinic during the prelockdown period and who came for follow-up postlockdown. The primary outcome measures were change in glycated hemoglobin (HbA1c), fasting blood glucose sugar (FBG), and postprandial blood sugar (PPBG) compared to the last value before the lockdown. Results: A total of 200 (male: female - 83:117) patients with a mean (standard deviation [SD]) age of 58.0 (10.8) years were included. The mean (SD) interval between the pre- and post-lockdown visit was 3.9 (0.9) months, and 58.5% of the patients were compliant with the medication. The mean HbA1c levels increased significantly by 1.1 (P = 0.000), FBG by 21.9 mg/dL (P = 0.000), PPBG by 28.0 mg/dL (P = 0.000), and weight by 1.6 kg (P = 0.000), from pre- to post-lockdown visit. The patients noncompliant to therapy had a significantly higher increase in glycemic parameters. The results showed a significant correlation between the interval of follow-up and treatment compliance with increase in glycemic parameters and weight. Conclusion: The results of this study revealed that there was a negative impact of lockdown on glycemic control in T2DM patients, highlighting the need for telehealth strategies to ensure the well-being of diabetic patients during such calamities.
ABSTRACT
Since chest illnesses are so frequent these days, it is critical to identify and diagnose them effectively. As such, this study proposes a model designed to accurately predict chest disorders by analyzing multiple chest x-ray pictures obtained from a dataset, consisting of 112,120 chest X-ray images, obtained the National Institute of Health (NIH) X-ray. The study used photos from 30,805 individuals with a total of 14 different types of chest disorder, including atelectasis, consolidation, infiltration, and pneumothorax, as well as a class called "No findings" for cases in which the ailment was undiagnosed. Six distinct transfer-learning approaches, namely, VGG-16, MobileNet V2, ResNet-50, DenseNet-161, Inception V3, and VGG-19, were used in the deep learning and federated learning environment to predict the accuracy rate of detecting chest disorders. The VGG-16 model showed the best accuracy at 0.81, with a recall rate of 0.90. As a result, the Fl score of VGG-16 is 0.85, which was higher than the Fl scores computed by other transfer learning approaches. VGG-19 obtained a maximum rate of accuracy of 97.71% via federated transfer learning. According to the classification report, the VGG-16 model is the best transfer-learning model for correctly detecting chest illness.
ABSTRACT
We report a telemedicine-based case-series of 30 mild/moderate (classification based on guidelines by Ministry of Health and Family Welfare, Government of India) COVID-19 patients, treated using Integrative Therapy based on Ayurveda, Yoga and Modern Western Medicine, i.e., MWM (allopathy). Cases were high-risk owing to comorbidities like Diabetes Mellitus, Hypertension, Coronary Artery Disease, Ulcerative colitis, Chronic Kidney Disease and/or age above 60. The cases have been categorized into YAS (Yoga-Ayurveda based treatment, with possibly allopathic Supplements: 4 patients), YASP (Yoga-Ayurveda based treatment, with possibly allopathic Supplements and Paracetamol: 6 patients), YAM (Yoga-Ayurveda based treatment, and MWM as adjunct: 6 patients), MYA (first tried MWM, later switched to Yoga-Ayurveda: 14 patients). Based on each patient’s symptoms and co-morbidities, a personalized treatment plan including Ayurvedic medicines, Yoga protocol, dietary recommendations and lifestyle modifications was prescribed by a registered Ayurveda doctor and a Yoga consultant. More than half of symptomatic patients started improving within 5 days (90% within 9 days);more than 60% reported at least 90% recovery within 10 days. Six patients with oxygen saturation (SpO2) below 95%, benefited through Makarasana and Shithilasana;none progressed to composite endpoints (consisting of admission to Intensive Care Unit, invasive ventilation or death). Considering that approximately 19.3% of the patients with these comorbidities progress to composite end points, the p-value is 7.21 x 10−3. The Integrative Therapy, incorporating Yoga and Ayurveda with MWM, may offer an economical, scalable treatment option for COVID-19 by reducing burden on healthcare facilities and preventing risk-exposure of healthcare workers. © 2022, National Institute of Science Communication and Information Resources. All rights reserved.
ABSTRACT
Aim and objective: To report a case of surgical management and postsurgical rehabilitation COVID-19-related mucormycotic osteomyelitis of the maxilla. Background: Patients with the SARS-CoV-2 infection, also termed the COVID-19 illness, have been found to be afflicted with other associated bacterial and fungal diseases which have been termed as co-infections. In this regard, mucormycosis, a fungal infection, has been found to occur in these patients especially with a lowered immune response and has been found to cause osteomyelitis of the jaw bones. Case description: We present a case of mucormycosis in a COVID-19-affected patient that occurred in August 2020 denoted the first wave of disease in India, causing extensive osteomyelitis of the left maxilla. The patient presented clinically with odontalgia and tooth mobility in the upper anterior region. Clinical examination revealed the presence of abscesses in the attached gingiva in relation to tooth numbers 13,12, 11, 22, 23,24 and 25. A deep horizontal cleft was observed in the mucogingival junction in relation to 23 discharging pus. Computed tomography (CT) imaging revealed a diffuse radiolucency extending from the alveolar ridge of the upper anterior teeth to the left maxillary sinus, breaking the floor of the sinus. We have performed extensive medical and surgical management of this patient including postoperative prosthetic rehabilitation which is documented in the present case report. Clinical significance: Our observation of maxillary osteomyelitis secondary to mucormycosis in the first COVID wave in India makes our case extremely rare and important as this highlights that COVID-19 complications were significant but under-evaluated in the first wave of the disease. © Jaypee Brothers Medical Publishers. 2021.
ABSTRACT
“Mad March – 2020, witnessed dramatic down-slide in the world‟s top stock exchanges due to COVID-19 pandemic with worrying volatility which resulted in traders panic sold off their holdings out of fear”.2020‟s first quarter witnessed substantial losses in the several well-recognized stock indices, especially between March 6 to 18, more than 20% that were triggered downward by the outbreak of COVID-19. Dow Jones Industrial Average and S&P 500 experienced the worst first quarter ever in the history during the year 2020 reducing its value by 23.2%. The year 2020 witnessed several historical landmark changes in the Indian share market movements along with other prominent stock exchanges of the globe. On March 23rd, 2020, Benchmark index SENSEX touched intraday lowest value of 25880 and NIFTY fell to the lowest value of 7583. Throughout the globe, including Indian investors, started to rush for clearing their holdings ahead of dark lines created by the pandemic in spite of most of the financial analysts‟ suggestion for fresh buy and/or to hold previous purchase for long. Supporting financial experts‟ views, within the next nine months SENSEX has gained around 100% and stood at 48834.34 on 8th Jan 2021. There are many studies both in India and outside the country that have provided evidence for the role of behavioral factors on investment decision-making at respective stock markets. Here authors attempted to verify, „weather market factor and herding effect of behavioral variables do influences on investment decision making of Indian share market investors?‟ © 2021 Karadeniz Technical University. All rights reserved.
ABSTRACT
During the period of COVID-19 Lock-down the e-learning became very popular by dependency of both teachers as well as the learners to avoid interruptions in their academic progress. In a view to assess the effectiveness and evaluate the adaptation of the students towards e-learning, a survey was conducted among the nursing students in the form of feedback. The feedback was mainly focused on the student’s interest, and the efforts taken by teachers in regard to class time and pace, organization and preparations of class, and fair assessment opportunities provided by teachers etc. The survey results were computed through Microsoft excel analysis based on the central tendencies, reveals that the Most of students “Agree”, maximum have “Strongly Agree” and very few students have “Disagree” to the approaches and efforts of the teachers taken during e-learning. It was concluded from study that majority of the students had strongly agree that faculty organized and prepared well for every class and faculty were encouraged in discussions and responded to questions. © 2020, Institute of Medico-Legal Publications. All rights reserved.
ABSTRACT
Since December 2019, a novel coronavirus disease (COVID-19) creates a global threat. Medical students are more susceptible to be infected by the virus. This study aimed to assess COVID-19 related knowledge, attitude towards COVID-19, and preventive behaviours against COVID-19 among medical students within the first month of the onset of the outbreak in Malaysia. We collect data from medical students using an online Google survey form. Out of 696 students, 467 responded to the questionnaire. The analysis revealed that the mean percentage of knowledge was (85.04), attitude (84.12), and preventive practice (77.75) respectively. Hierarchical multiple linear regression analysis revealed that living with family (p<0.01) and knowledge of COVID-19 (p<0.001) appeared to be important predictors of attitude toward COVID-19. However, gender (p<0.001), living status (p<0.001), frequency of travel during movement control order (p<0.01), attitude towards COVID-19 (p<0.001) have appeared significant predictors for preventive practice against COVID-19. But knowledge of COVID-19 had no impact on preventive practice against COVID-19 (p>0.05). We found a high level of COVID-19 related knowledge, attitude, and preventive practice against COVID-19 among medical students. A sustained knowledge, attitude, and preventive behavioural strategy could play an ingredient in upholding the student’s learning and practice against any disease like COVID-19. © 2020