Enhance-Net: An Approach to Boost the Performance of Deep Learning Model Based on Real-Time Medical Images

Real-time medical image classification is a complex problem in the world. Using IoT technology in medical applications assures that the healthcare sectors improve the quality of treatment while lowering costs via automation and resource optimization. Deep learning is critical in categorizing medical images, which is accomplished by artificial intelligence. Deep learning algorithms allow radiologists and orthopaedic surgeons to make their life easier by providing them with quicker and more accurate findings in real time. Despite this, the classic deep learning technique has hit its performance limits. For these reasons, in this research, we examine alternative enhancement strategies to raise the performance of deep neural networks to provide an optimal solution known as Enhance-Net. It is possible to classify the experiment into six distinct stages. Champion-Net was chosen as a deep learning model from a pool of benchmark deep learning models (EfficientNet: B0, MobileNet, ResNet-18, and VGG-19). This stage helps choose the optimal model. In the second step, Champion-Net was tested with various resolutions. This stage helps conclude dataset resolution and improves Champion-Net performance. The next stage extracts green channel data. In the fourth step, Champion-Net combines with image enhancement algorithms CLAHE, HEF, and UM. This phase serves to improve Enhance-performance. The next stage compares the Enhance-Net findings to the lightness order error (LoE). In Enhance-Net models, the current study combines image enhancement and green channel with Champion-Net. In the final step, radiologists and orthopaedic surgeons use the trained model for real-time medical image prediction. The study effort uses the musculoskeletal radiograph-bone classification (MURA-BC) dataset. Classification accuracy of Enhance-Net was determined for the train and test datasets. These models obtained 98.02 percent, 94.79 percent, and 94.61 percent accuracy, respectively. The 96.74% accuracy was achieved during real-time testing with the unseen dataset.

Surveillance of omicron variant in Kangra District of Himachal Pradesh, India during the 3rd disease wave of COVID-19.

INTRODUCTION: The coronavirus disease 2019 (COVID-19) wave has fluctuated erratically around the globe over the past three years of the pandemic, sometimes declining and at other times surging. The cases of infection in India have remained low, despite the continued surge of Omicron sub-lineages reported in a few countries. In this study, we determined the presence of the circulating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strains in the population of Kangra District, Himachal Pradesh, India. METHODOLOGY: In vitro diagnostic real-time reverse transcriptase polymerase chain reaction (RT-qPCR) was performed using Tata MD CHECK RT-PCR Omisure kit (Tata Medical and Diagnostics Limited, Maharashtra, India), to detect the presence of Omicron in target samples. A total of 400 samples were analyzed in this study; 200 each for the second and third waves, respectively. The S gene target failure (SG-TF) and S gene mutation amplification (SG-MA) primer-probe sets were used. RESULTS: Our results corroborated that during the third wave, SG-MA amplification was noted, while amplification of SG-TF was not, and vice versa in the case of the second wave, indicating that all the tested patients were infected with the Omicron variant during the third wave, while Omicron was absent during the second wave. CONCLUSIONS: This study added more information about the prevalence of Omicron variants during the third wave in the chosen area, and it projected a use of in vitro RT-qPCR method for rapid prospective determination of the prevalence of the variant of concern (VOC) in developing countries with limited sequencing facility.

Using immersive technology and architectural design to assist head and neck cancer patients' recovery from treatment: A focus group and technology acceptance study.

PURPOSE: Head and neck cancer patients can face debilitating treatment related side-effects, resulting in requirement for support and negatively impacting on care outcomes. This study aimed to develop a digital recovery support package and assess its acceptability with head and neck cancer patients to support their information needs and assist with their self-management. It provided additional support through development of a WebXR platform 'recovery' package, which allowed patients to live a 'virtual reality' experience, entering and moving inside a 'virtual room', accessing targeted resources and specific learning materials related to their cancer. METHOD: A qualitative intervention development study consisting of three phases. This study followed the COREQ checklist for qualitative research. Phase 1- Focus groups with seven head and neck cancer patients and six healthcare professionals. Phase 2- Development of 'recovery' package based on the focus group data which informed the content and design of the WebXR recovery platform. Phase 3- Technology acceptance study. Once developed, the platform's acceptability of the experience lived inside the virtual room was assessed via qualitative interviews with six different patient participants. RESULTS: Most participants felt comfortable using the virtual reality platform, finding it a realistic and useful support for identifying resources and signposting to relevant materials. Participants agreed the WebXR platform was a feasible tool for the head and neck cancer setting and helped reduce anxiety. CONCLUSIONS: Head and neck cancer patients welcome specific targeted, information and advice to support their ability to self-manage their rehabilitation and thus focus their nursing care. The platform was implemented during the Covid-19 pandemic, demonstrating its versatility and accessibility in providing complementary support to head and neck cancer patients, to empower them to adjust to their 'new' normal as part of their ongoing cancer journeys.

Combating the progression of novel coronavirus SARS-CoV-2 infectious Disease: Current state and future prospects in molecular diagnostic and drug discovery.

A highly infectious and life-threatening virus originated from Wuhan, China in late 2019 and rapidly spread all over the world. This novel virus belongs to coronavirus family and is associated with severe acute respiratory syndrome (SARS), causing respiratory disease known as COVID-19. In March 2020, WHO has declared COVID-19 outbreak a global pandemic. Morbidity and mortality are swiftly rising day by day with the situation more severe and fatal for the co-morbid population. Many COVID-19 patients are asymptomatic, but they are silently spreading the infection. There is a need for proper screening of infected patients to prevent the epidemic transmission of disease and also for the early curative interventions to reduce the risk of developing serious complications from COVID-19 illness. To date, the diagnostic assays fall under two categories, molecular detection of viral genetic material by realtime RT-polymerase chain reaction and serological test, which rely on detecting antiviral antibodies. Unfortunately, there are no effective prophylactics and therapeutics available against COVID-19. However, few drugs are showing promising antiviral activity against it and presently are referred for the clinical trials, albeit FDA issued an Emergency Use Authorization (EUA) for emergency use of few drugs in the manifestation of SARS-CoV-2 infection. This review gives an insight into current progress, challenges and future prospects of laboratory detection methods of COVID-19 and also highlights the clinical stage of the major proposed or evidence based drugs/vaccines recommended against the novel SARS-CoV-2 pandemic virus.

Needle-free injection system delivery of ZyCoV-D DNA vaccine demonstrated improved immunogenicity and protective efficacy in rhesus macaques against SARS-CoV-2.

The apprehension of needles related to injection site pain, risk of transmitting bloodborne pathogens, and effective mass immunization have led to the development of a needle-free injection system (NFIS). Here, we evaluated the efficacy of the NFIS and needle injection system (NIS) for the delivery and immunogenicity of DNA vaccine candidate ZyCoV-D in rhesus macaques against SARS-CoV-2 infection. Briefly, 20 rhesus macaques were divided into 5 groups (4 animals each), that is, I (1 mg dose by NIS), II (2 mg dose by NIS), III (1 mg dose by NFIS), IV (2 mg dose by NFIS) and V (phosphate-buffer saline [PBS]). The macaques were immunized with the vaccine candidates/PBS intradermally on Days 0, 28, and 56. Subsequently, the animals were challenged with live SARS-CoV-2 after 15 weeks of the first immunization. Blood, nasal swab, throat swab, and bronchoalveolar lavage fluid specimens were collected on 0, 1, 3, 5, and 7 days post infection from each animal to determine immune response and viral clearance. Among all the five groups, 2 mg dose by NFIS elicited significant titers of IgG and neutralizing antibody after immunization with enhancement in their titers postvirus challenge. Besides this, it also induced increased lymphocyte proliferation and cytokine response. The minimal viral load post-SARS-CoV-2 challenge and significant immune response in the immunized animals demonstrated the efficiency of NFIS in delivering 2 mg ZyCoV-D vaccine candidate.

To Investigate The Importance Of The CBC, Derived Parameters, And Morphology Of Peripheral Blood Cells In Covid-19 Patients

Aim: To investigate the importance of the CBC, derived parameters, and morphology of peripheral blood cells in Covid-19 patients. Material and methods: According to their symptoms, patients were classified as asymptomatic, mild, or moderate-severe. This research included all paediatric and adult patients who had two CBC samples available (one at admission and another during discharge) throughout their hospital stay. Those who were already undergoing therapy for their cancer, haematological illness, liver disease, or chronic lung disease were not allowed to participate. Results: Patients' ages varied from 8 to 71. The patients' average age was 36.15±14.58 years. Sixty percent of research participants were male, making up a sex ratio of 1.5:1. (M: F). The average white blood cell count was 6.87±3.51 x109/L, the average red blood cell count was 4.61±0.88 x106/microL, and the average haemoglobin level was 12.80±2.15 g/dl upon admission. The average absolute neutrophil count was 3.81±3.46x109/L, the average absolute lymphocyte count was 2.31±1.40x109/L, the average absolute monocyte count was 0.38±0.31x109/L, and the average absolute eosinophil count was 0.15±0.18x109/L. Overall, the average number of platelets per microliter of blood was 149.21± 80.25. Neutrophil to lymphocyte ratio (NLR) at admission was 3.806;platelet to lymphocyte ratio (PLR) was 116.32±13.1;lymphocyte to monocyte ratio (LMR) was 8.91±5.25, and derivative neutrophil to lymphocyte ratio (d-NLR) was 2.61±1.36. Twenty (40%) of the patients were asymptomatic at admission, while 44% had mild symptoms, and 16% required oxygen and ventilator support due to moderate to severe symptoms. The RT-PCR test was positive for all of the patients examined. There was a noteworthy shift in both the mean WBC and mean platelet counts after the follow-up evaluation. No correlation was seen between clinical state on admission and any of the other CBC measures (p>0.05). Conclusion: The significance of CBC values and morphological inspection of the peripheral blood smear at baseline and subsequent assessment is highlighted in the research. [ FROM AUTHOR]

COVID-19 Detection from Chest X-rays Using Trained Output Based Transfer Learning Approach

The recent Coronavirus disease (COVID-19), which started in 2019, has spread across the globe and become a global pandemic. The efficient and effective COVID-19 detection using chest X-rays helps in early detection and curtailing the spread of the disease. In this paper, we propose a novel Trained Output-based Transfer Learning (TOTL) approach for COVID-19 detection from chest X-rays. We start by preprocessing the Chest X-rays of the patients with techniques like denoising, contrasting, segmentation. These processed images are then fed to several pre-trained transfer learning models like InceptionV3, InceptionResNetV2, Xception, MobileNet, ResNet50, ResNet50V2, VGG16, and VGG19. We fine-tune these models on the processed chest X-rays. Then we further train the outputs of these models using a deep neural network architecture to achieve enhanced performance and aggregate the capabilities of each of them. The proposed model has been tested on four recent COVID-19 chest X-rays datasets by computing several popular evaluation metrics. The performance of our model has also been compared with various deep transfer learning models and several contemporary COVID-19 detection methods. The obtained results demonstrate the efficiency and efficacy of our proposed model.

Current scenario of COVID-19 and impact of preventive strategies in curtailing its spread in a district of Gujarat

COVID-19 outbreak has been declared pandemic by World Health Organization (WHO). This study was planned to know the current COVID-19 situation in district and to know the impact of data driven preventive strategy to curtail the cases (Between 3rd August and 2nd September 2020). This is a cross sectional study done in tribal district of Gujarat. Total registered patients upto 2nd September 2020 were included in the study. Out of total 1189 patients, 34.4% were female. Recovery rate on 3rd August 2020 was 44.8% which is increased to 82.09% on 2nd September 2020. Positivity rate declined from 5.2% to 2.3% despite increase in test per million from 5042 to 51606 between 3rd August and 2nd September 2020. This decrease in test positivity rate attributed to preventive strategy followed by district. Over a period of one month (3rd August to 2nd September) district observed gradual decrease in Compound daily growth rate (CDGR) and increase in doubling time. Over a period of time, downward trend in cases detection and increase in recovery rate observed due to preventive strategies followed by district. To curtail the COVID-19 it is required to keep constant watch on spread, as few cases leftundiagnosed can make big spike in district.

A ricin-based peptide BRIP from Hordeum vulgare inhibits Mpro of SARS-CoV-2.

COVID-19 pandemic caused by SARS-CoV-2 led to the research aiming to find the inhibitors of this virus. Towards this world problem, an attempt was made to identify SARS-CoV-2 main protease (Mpro) inhibitory peptides from ricin domains. The ricin-based peptide from barley (BRIP) was able to inhibit Mpro in vitro with an IC50 of 0.52 nM. Its low and no cytotoxicity upto 50 µM suggested its therapeutic potential against SARS-CoV-2. The most favorable binding site on Mpro was identified by molecular docking and steered molecular dynamics (MD) simulations. The Mpro-BRIP interactions were further investigated by evaluating the trajectories for microsecond timescale MD simulations. The structural parameters of Mpro-BRIP complex were stable, and the presence of oppositely charged surfaces on the binding interface of BRIP and Mpro complex further contributed to the overall stability of the protein-peptide complex. Among the components of thermodynamic binding free energy, Van der Waals and electrostatic contributions were most favorable for complex formation. Our findings provide novel insight into the area of inhibitor development against COVID-19.

Plant-derived immuno-adjuvants in vaccines formulation: a promising avenue for improving vaccines efficacy against SARS-CoV-2 virus.

The SARS-CoV-2 outbreak has posed a plethora of problems for the global healthcare system and socioeconomic burden. Despite valiant efforts to contain the COVID-19 outbreak, the situation has deteriorated to the point that there are no viable preventive therapies to treat this disease. The case count has skyrocketed globally due to the newly evolved variants. Despite vaccination drives, the re-occurrence of recent pandemic waves has reinforced the importance of innovation/utilization of immune-booster to achieve appropriate long-term vaccine protection. Plant-derived immuno-adjuvants, which have multifaceted functions, can impede infections by boosting the immune system. Many previous studies have shown that formulation of vaccines using plant-derived adjuvant results in long-lasting immunity may overcome the natural tendency of coronavirus immunity to wane quickly. Plant polysaccharides, glycosides, and glycoprotein extracts have reportedly been utilized as enticing adjuvants in experimental vaccines, such as Advax, Matrix-M, and Mistletoe lectin, which have been shown to be highly immunogenic and safe. When employed in vaccine formulation, Advax and Matrix-M generate long-lasting antibodies, a balanced robust Th1/Th2 cytokine profile, and the stimulation of cytotoxic T cells. Thus, the use of adjuvants derived from plants may increase the effectiveness of vaccines, resulting in the proper immunological response required to combat COVID-19. A few have been widely used in epidemic outbreaks, including SARS and H1N1 influenza, and their use could also improve the efficacy of COVID-19 vaccines. In this review, the immunological adjuvant properties of plant compounds as well as their potential application in anti-COVID-19 therapy are thoroughly discussed.

An approach for DoS attack detection in cloud computing using sine cosine anti coronavirus optimized deep maxout network

Purpose The Denial of Service (DoS) attack is a category of intrusion that devours various services and resources of the organization by the dispersal of unusable traffic, so that reliable users are not capable of getting benefit from the services. In general, the DoS attackers preserve their independence by collaborating several victim machines and following authentic network traffic, which makes it more complex to detect the attack. Thus, these issues and demerits faced by existing DoS attack recognition schemes in cloud are specified as a major challenge to inventing a new attack recognition method. Design/methodology/approach This paper aims to detect DoS attack detection scheme, termed as sine cosine anti coronavirus optimization (SCACVO)-driven deep maxout network (DMN). The recorded log file is considered in this method for the attack detection process. Significant features are chosen based on Pearson correlation in the feature selection phase. The over sampling scheme is applied in the data augmentation phase, and then the attack detection is done using DMN. The DMN is trained by the SCACVO algorithm, which is formed by combining sine cosine optimization and anti-corona virus optimization techniques. Findings The SCACVO-based DMN offers maximum testing accuracy, true positive rate and true negative rate of 0.9412, 0.9541 and 0.9178, respectively. Originality/value The DoS attack detection using the proposed model is accurate and improves the effectiveness of the detection.

Theaflavin 3-gallate inhibits the main protease (Mpro) of SARS-CoV-2 and reduces its count in vitro.

The main protease (Mpro) of SARS-CoV-2 has been recognized as an attractive drug target because of its central role in viral replication. Our previous preliminary molecular docking studies showed that theaflavin 3-gallate (a natural bioactive molecule derived from theaflavin and found in high abundance in black tea) exhibited better docking scores than repurposed drugs (Atazanavir, Darunavir, Lopinavir). In this study, conventional and steered MD-simulations analyses revealed stronger interactions of theaflavin 3-gallate with the active site residues of Mpro than theaflavin and a standard molecule GC373 (a known inhibitor of Mpro and novel broad-spectrum anti-viral agent). Theaflavin 3-gallate inhibited Mpro protein of SARS-CoV-2 with an IC50 value of 18.48 ± 1.29 µM. Treatment of SARS-CoV-2 (Indian/a3i clade/2020 isolate) with 200 µM of theaflavin 3-gallate in vitro using Vero cells and quantifying viral transcripts demonstrated reduction of viral count by 75% (viral particles reduced from Log106.7 to Log106.1). Overall, our findings suggest that theaflavin 3-gallate effectively targets the Mpro thus limiting the replication of the SARS-CoV-2 virus in vitro.

Clinical profile of COVID-19 patients and their length of stay: Tertiary care hospital experience.

Background: SARSCoV-2, a coronavirus that causes COVID-19, is spreading rapidly. By the middle of August-2021, it has affected over 3 million confirmed cases in India. The main aim of this study was to examine the clinical profile of COVID-19 patients and their length of stay during treatment in a hospital. Materials and Methods: It was a hospital-based retrospective study conducted by using a total enumeration technique in July-August 2021 at Nehru Hospital, Postgraduate Institute of Medical Education and Research (PGIMER) in India. The present study was conducted on 72 COVID-19 patients who took treatment in 4C and 5C wards. Structured questionnaires were used to collect data, which included bio-demographic factors and questions about their treatment and length of stay. Results: The majority of the 72 COVID-19 positive patients were men (62%), belonged to the age group of 41-60 years (35%), had SpO2 levels ranging from 91%-95% (45%), and received room air O2 therapy (63%) during their treatment in the hospital. Female patients had a longer length of stay (7.33 days), patients under the age of 20 years had the longest hospital stay (11.5 days), patients with SpO2 less than 70% had the longest hospital stay (8 days), and patients who received oxygen using a non-rebreathing mask had the longest hospital stay (11 days). Conclusion: To avoid panic situations, regular admission and discharge of patients was essential due to the considerable increase in cases during the second wave. Patient length of stay was reduced as a consequence of collaboration and cooperation among all physicians, residents, staff nurses, and paramedics, with the goal of discharging the patient after a room air trial and follow up if needed.

Assessment of in-cabin noise of wide-body aircrafts.

The aviation industry has seen dramatic growth over the decades till the recent disruption due to the COVID-19 pandemic. Moreover, long-haul routes with a distance of more than 4000 km are common for major airlines worldwide. Therefore, aircraft cabin noise assessment is essential, especially in long-haul flights, for passenger and flight crew health wellness. In this paper, the cabin noise of five wide-body aircraft, namely Airbus A330-300ER, A350-900, A380-800, and Boeing B777-200ER and B787-900, was recorded using a calibrated in-house developed smartphone application. The sound pressure levels of in-cabin noise have been measured on two different decibel scales, namely, A-weighted [dB(A)] and C-weighted scales [dB(C)]. The sound pressure levels of Airbus A380-800 were lowest among selected models, while the in-cabin pressure level values of Airbus A350-900 were maximum. However, the difference in decibel levels between the aircraft is minimal as it is within 3 dB.

In-silico evaluation of bioactive compounds from tea as potential SARS-CoV-2 nonstructural protein 16 inhibitors.

BACKGROUND AND AIM: A novel coronavirus, called the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been found to cause COVID-19 in humans and some other mammals. The nonstructural protein 16 (NSP16) of SARS-CoV-2 plays a significant part in the replication of viruses and suppresses the ability of innate immune system to detect the virus. Therefore, inhibiting NSP16 can be a secure path towards identifying a potent medication against SARS-CoV-2. Tea (Camellia sinensis) polyphenols have been reported to exhibit potential treatment options against various viral diseases. METHODS: We conducted molecular docking and structural dynamics studies with a set of 65 Tea bioactive compounds to illustrate their ability to inhibit NSP16 of SARS-CoV-2. Moreover, post-simulations end state thermodynamic free energy calculations were estimated to strengthen our results. RESULTS AND CONCLUSION: Six bioactive tea molecules showed better docking scores than the standard molecule sinefungin. These results were further validated by MD simulations, where Theaflavin compound demonstrated lower binding free energy in comparison to the standard molecule sinefungin. The compound theaflavin could be considered as a novel lead compound for further evaluation by in-vitro and in-vivo studies.