A novel deep learning technique for medical image analysis using improved optimizer.

Application of Convolutional neural network in spectrum of Medical image analysis are providing benchmark outputs which converges the interest of many researchers to explore it in depth. Latest preprocessing technique Real ESRGAN (Enhanced super resolution generative adversarial network) and GFPGAN (Generative facial prior GAN) are proving their efficacy in providing high resolution dataset. Objective: Optimizer plays a vital role in upgrading the functioning of CNN model. Different optimizers like Gradient descent, Stochastic Gradient descent, Adagrad, Adadelta and Adam etc. are used for classification and segmentation of Medical image but they suffer from slow processing due to their large memory requirement. Stochastic Gradient descent suffers from high variance and is computationally expensive. Dead neuron problem also proves to detrimental to the performance of most of the optimizers. A new optimization technique Gradient Centralization is providing the unparalleled result in terms of generalization and execution time. Method: Our paper explores the next factor which is the employment of new optimization technique, Gradient centralization (GC) to our integrated framework (Model with advanced preprocessing technique). Result and conclusion: Integrated Framework of Real ESRGAN and GFPGAN with Gradient centralization provides an optimal solution for deep learning models in terms of Execution time and Loss factor improvement.

Chlorhexidine and doxycycline gel versus chip as adjuncts in oral hygiene among Indians.

The effectiveness of newly released medications such as Chlorhexidine (CHX) chip, Doxycycline hyclate (DH) chip, CHX gel, DH chip as adjunct to scaling and root planing in the treatment of chronic periodontitis is important. 90 adult Indian patients with moderate chronic periodontitis were enlisted. It was observed that reduction in periodontal pocket depth (PPD) and increase in clinical attachment level (CAL) was seen in patients in CHX group as compared to DH treated study participants. It was observed that CHX and DH in gel form were more effective in improving periodontal health as compared to CHX and DH in chip form in this group of subjects.

Discovery of anti-SARS-CoV-2 molecules using structure-assisted repurposing approach targeting N-protein

SARS-CoV-2 nucleocapsid protein (N-protein) is a virus specific multitasking protein, responsible for recognition and encapsidation of the viral genome. The N-terminal domain (NTD) of N-protein has a major role of packaging viral RNA genome into a long helical nucleocapsid structure. In this study, using structure-based drug repurposing strategy, small molecules from a FDA approved, natural product, and LOPAC1280 libraries have been virtually screened against the RNA binding pocket of SARS-CoV-2 NTD and twelve candidate molecules with high binding affinity were identified. Highly sensitive isothermal titration calorimetry (ITC) method was utilized to confirm binding of these molecules to purified NTD protein. In vitro cell-based SARS-CoV-2 antiviral assays demonstrate that nine of these identified molecules are highly efficacious in inhibiting virus replication with half maximal effective concentration (EC50) ranging from 0.98 M-10 M. FDA approved drugs: Telmisartan, an angiotensin II type 1 (AT1) receptor antagonist used in the management of hypertension and Bictegravir, an HIV-1 integrase inhibitor showed significant inhibitory activity against SARS-CoV-2 with a EC50 values of 1.02 M and 8.11 M respectively. Additionally, Bisdemethoxycurcumin, a natural analogue of curcumin and MCC-555, an anti-diabetic drug exerted antiviral activity with EC50 values of 1.64 M and 4.26 M, respectively. Taken together, this is the first report of drug molecules targeting the NTD of SARS-CoV-2 N-protein and the data presented in this study exhibit high potential for development of COVID-19 therapy based on drug repurposing.

One-Stop Serum Assay Identifies COVID-19 Disease Severity and Vaccination Responses.

SARS-CoV-2 has caused over 100,000,000 cases and almost 2,500,000 deaths globally. Comprehensive assessment of the multifaceted antiviral Ab response is critical for diagnosis, differentiation of severity, and characterization of long-term immunity, especially as COVID-19 vaccines become available. Severe disease is associated with early, massive plasmablast responses. We developed a multiplex immunoassay from serum/plasma of acutely infected and convalescent COVID-19 patients and prepandemic and postpandemic healthy adults. We measured IgA, IgG, and/or IgM against SARS-CoV-2 nucleocapsid (N), spike domain 1 (S1), S1-receptor binding domain (RBD) and S1-N-terminal domain. For diagnosis, the combined [IgA + IgG + IgM] or IgG levels measured for N, S1, and S1-RBD yielded area under the curve values ≥0.90. Virus-specific Ig levels were higher in patients with severe/critical compared with mild/moderate infections. A strong prozone effect was observed in sera from severe/critical patients-a possible source of underestimated Ab concentrations in previous studies. Mild/moderate patients displayed a slower rise and lower peak in anti-N and anti-S1 IgG levels compared with severe/critical patients, but anti-RBD IgG and neutralization responses reached similar levels at 2-4 mo after symptom onset. Measurement of the Ab responses in sera from 18 COVID-19-vaccinated patients revealed specific responses for the S1-RBD Ag and none against the N protein. This highly sensitive, SARS-CoV-2-specific, multiplex immunoassay measures the magnitude, complexity, and kinetics of the Ab response and can distinguish serum Ab responses from natural SARS-CoV-2 infections (mild or severe) and mRNA COVID-19 vaccines.

Triage of potential COVID-19 patients from chest X-ray images using hierarchical convolutional networks.

The current COVID-19 pandemic has motivated the researchers to use artificial intelligence techniques for a potential alternative to reverse transcription-polymerase chain reaction due to the limited scale of testing. The chest X-ray (CXR) is one of the alternatives to achieve fast diagnosis, but the unavailability of large-scale annotated data makes the clinical implementation of machine learning-based COVID detection difficult. Another issue is the usage of ImageNet pre-trained networks which does not extract reliable feature representations from medical images. In this paper, we propose the use of hierarchical convolutional network (HCN) architecture to naturally augment the data along with diversified features. The HCN uses the first convolution layer from COVIDNet followed by the convolutional layers from well-known pre-trained networks to extract the features. The use of the convolution layer from COVIDNet ensures the extraction of representations relevant to the CXR modality. We also propose the use of ECOC for encoding multiclass problems to binary classification for improving the recognition performance. Experimental results show that HCN architecture is capable of achieving better results in comparison with the existing studies. The proposed method can accurately triage potential COVID-19 patients through CXR images for sharing the testing load and increasing the testing capacity.

Predictors of COVID-19 Vaccine Confidence: Findings from Slums of Four Major Metro Cities of India.

There are limited studies on COVID vaccine confidence at the household level in urban slums, which are at high risk of COVID-19 transmission due to overcrowding and poor living conditions. The objective was to understand the reasons influencing COVID-19 vaccine confidence, in terms of barriers and enablers faced by communities in urban slums and informal settlements in four major metro cities in India. A mixed method approach was adopted, where in field studies were conducted during April-May 2021. First, a survey of at least 50 subjects was conducted among residents of informal urban settlements who had not taken any dose of the COVID-19 vaccine in Mumbai, Bengaluru, Kolkata and Delhi; second, a short interview with five subjects who had taken at least one dose of the vaccine in each of the four cities to understand the factors that contributed to positive behaviour and, finally, an in-depth interview of at least 3 key informants in each city to ascertain the vaccination pattern in the communities. The reasons were grouped under contextual, individual/group and vaccine/vaccination specific issues. The most frequent reason (27.7%) was the uncertainty of getting the vaccine. The findings show the need for increasing effectiveness of awareness campaigns, accessibility and the convenience of vaccination, especially among vulnerable groups, to increase the uptake.

Relaxed peripheral tolerance drives broad de novo autoreactivity in severe COVID-19.

An emerging feature of COVID-19 is the identification of autoreactivity in patients with severe disease that may contribute to disease pathology, however the origin and resolution of these responses remain unclear. Previously, we identified strong extrafollicular B cell activation as a shared immune response feature between both severe COVID-19 and patients with advanced rheumatic disease. In autoimmune settings, this pathway is associated with relaxed peripheral tolerance in the antibody secreting cell compartment and the generation of de novo autoreactive responses. Investigating these responses in COVID-19, we performed single-cell repertoire analysis on 7 patients with severe disease. In these patients, we identify the expansion of a low-mutation IgG1 fraction of the antibody secreting cell compartment that are not memory derived, display low levels of selective pressure, and are enriched for autoreactivity-prone IGHV4-34 expression. Within this compartment, we identify B cell lineages that display specificity to both SARS-CoV-2 and autoantigens, including pathogenic autoantibodies against glomerular basement membrane, and describe progressive, broad, clinically relevant autoreactivity within these patients correlated with disease severity. Importantly, we identify anti-carbamylated protein responses as a common hallmark and candidate biomarker of broken peripheral tolerance in severe COVID-19. Finally, we identify the contraction of this pathway upon recovery, and re-establishment of tolerance standards coupled with a concomitant loss of acute-derived ASCs irrespective of antigen specificity. In total, this study reveals the origins, breadth, and resolution of acute-phase autoreactivity in severe COVID-19, with significant implications in both early interventions and potential treatment of patients with post-COVID sequelae.

Elevated SARS-CoV-2 Antibodies Distinguish Severe Disease in Early COVID-19 Infection.

BACKGROUND: SARS-CoV-2 has caused over 36,000,000 cases and 1,000,000 deaths globally. Comprehensive assessment of the multifaceted anti-viral antibody response is critical for diagnosis, differentiation of severe disease, and characterization of long-term immunity. Initial observations suggest that severe disease is associated with higher antibody levels and greater B cell/plasmablast responses. A multi-antigen immunoassay to define the complex serological landscape and clinical associations is essential. METHODS: We developed a multiplex immunoassay and evaluated serum/plasma from adults with RT-PCR-confirmed SARS-CoV-2 infections during acute illness (N=52) and convalescence (N=69); and pre-pandemic (N=106) and post-pandemic (N=137) healthy adults. We measured IgA, IgG, and/or IgM against SARS-CoV-2 Nucleocapsid (N), Spike domain 1 (S1), receptor binding domain (S1-RBD) and S1-N-terminal domain (S1-NTD). RESULTS: To diagnose infection, the combined [IgA+IgG+IgM] or IgG for N, S1, and S1-RBD yielded AUC values -0.90 by ROC curves. From days 6-30 post-symptom onset, the levels of antigen-specific IgG, IgA or [IgA+IgG+IgM] were higher in patients with severe/critical compared to mild/moderate infections. Consistent with excessive concentrations of antibodies, a strong prozone effect was observed in sera from severe/critical patients. Notably, mild/moderate patients displayed a slower rise and lower peak in anti-N and anti-S1 IgG levels compared to severe/critical patients, but anti-RBD IgG and neutralization responses reached similar levels at 2-4 months. CONCLUSION: This SARS-CoV-2 multiplex immunoassay measures the magnitude, complexity and kinetics of the antibody response against multiple viral antigens. The IgG and combined-isotype SARS-CoV-2 multiplex assay is highly diagnostic of acute and convalescent disease and may prognosticate severity early in illness. ONE SENTENCE SUMMARY: In contrast to patients with moderate infections, those with severe COVID-19 develop prominent, early antibody responses to S1 and N proteins.

Elevated SARS-CoV-2 Antibodies Distinguish Severe Disease in Early COVID-19 Infection

BackgroundSARS-CoV-2 has caused over 36,000,000 cases and 1,000,000 deaths globally. Comprehensive assessment of the multifaceted anti-viral antibody response is critical for diagnosis, differentiation of severe disease, and characterization of long-term immunity. Initial observations suggest that severe disease is associated with higher antibody levels and greater B cell/plasmablast responses. A multi-antigen immunoassay to define the complex serological landscape and clinical associations is essential. MethodsWe developed a multiplex immunoassay and evaluated serum/plasma from adults with RT-PCR-confirmed SARS-CoV-2 infections during acute illness (N=52) and convalescence (N=69); and pre-pandemic (N=106) and post-pandemic (N=137) healthy adults. We measured IgA, IgG, and/or IgM against SARS-CoV-2 Nucleocapsid (N), Spike domain 1 (S1), receptor binding domain (S1-RBD) and S1-N-terminal domain (S1-NTD). ResultsTo diagnose infection, the combined [IgA+IgG+IgM] or IgG for N, S1, and S1-RBD yielded AUC values -0.90 by ROC curves. From days 6-30 post-symptom onset, the levels of antigen-specific IgG, IgA or [IgA+IgG+IgM] were higher in patients with severe/critical compared to mild/moderate infections. Consistent with excessive concentrations of antibodies, a strong prozone effect was observed in sera from severe/critical patients. Notably, mild/moderate patients displayed a slower rise and lower peak in anti-N and anti-S1 IgG levels compared to severe/critical patients, but anti-RBD IgG and neutralization responses reached similar levels at 2-4 months. ConclusionThis SARS-CoV-2 multiplex immunoassay measures the magnitude, complexity and kinetics of the antibody response against multiple viral antigens. The IgG and combined-isotype SARS-CoV-2 multiplex assay is highly diagnostic of acute and convalescent disease and may prognosticate severity early in illness. One Sentence SummaryIn contrast to patients with moderate infections, those with severe COVID-19 develop prominent, early antibody responses to S1 and N proteins.

Extrafollicular B cell responses correlate with neutralizing antibodies and morbidity in COVID-19.

A wide spectrum of clinical manifestations has become a hallmark of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) COVID-19 pandemic, although the immunological underpinnings of diverse disease outcomes remain to be defined. We performed detailed characterization of B cell responses through high-dimensional flow cytometry to reveal substantial heterogeneity in both effector and immature populations. More notably, critically ill patients displayed hallmarks of extrafollicular B cell activation and shared B cell repertoire features previously described in autoimmune settings. Extrafollicular activation correlated strongly with large antibody-secreting cell expansion and early production of high concentrations of SARS-CoV-2-specific neutralizing antibodies. Yet, these patients had severe disease with elevated inflammatory biomarkers, multiorgan failure and death. Overall, these findings strongly suggest a pathogenic role for immune activation in subsets of patients with COVID-19. Our study provides further evidence that targeted immunomodulatory therapy may be beneficial in specific patient subpopulations and can be informed by careful immune profiling.

Broadly-targeted autoreactivity is common in severe SARS-CoV-2 Infection

An emerging feature of COVID-19 is the identification of autoreactivity in patients with severe disease that may contribute to disease pathology, however the origin and resolution of these responses remain unclear. Previously, we identified strong extrafollicular B cell activation as a shared immune response feature between both severe COVID-19 and patients with advanced rheumatic disease. In autoimmune settings, this pathway is associated with relaxed peripheral tolerance in the antibody secreting cell compartment and the generation of de novo autoreactive responses. Investigating these responses in COVID-19, we performed single-cell repertoire analysis on 7 patients with severe disease. In these patients, we identify the expansion of a low-mutation IgG1 fraction of the antibody secreting cell compartment that are not memory derived, display low levels of selective pressure, and are enriched for autoreactivity-prone IGHV4-34 expression. Within this compartment, we identify B cell lineages that display specificity to both SARS-CoV-2 and autoantigens, including pathogenic autoantibodies against glomerular basement membrane, and describe progressive, broad, clinically relevant autoreactivity within these patients correlated with disease severity. Importantly, we identify anti-carbamylated protein responses as a common hallmark and candidate biomarker of broken peripheral tolerance in severe COVID-19. Finally, we identify the contraction of this pathway upon recovery, and re-establishment of tolerance standards coupled with a concomitant loss of acute-derived ASCs irrespective of antigen specificity. In total, this study reveals the origins, breadth, and resolution of acute-phase autoreactivity in severe COVID-19, with significant implications in both early interventions and potential treatment of patients with post-COVID sequelae.

Comparison of FNAC smears, cytospin smears, and cellblocks of transthoracic guided FNAC of suspected lung tumor: A study of 100 cases.

INTRODUCTION: Transthoracic guided fine needle aspiration cytology (FNAC) of clinically suspected lung tumors is an increasingly common procedure in diagnosis. Cytospin Smear and Cellblock preparations of available material are helpful in subtyping and confirming the diagnosis, and they can also be used for further studies, i.e., special stain and immunohistochemistry, etc. AIMS AND OBJECTIVES: This research was undertaken to study the technique of guided transthoracic lung FNAC of clinically suspected lung tumors and the establish role of FNAC smears, cytospin smears, and cellblocks in the detection and typing of neoplastic lung lesions and correlation. MATERIALS AND METHODS: Guided FNAC was taken from 100 cases of clinically suspected lung tumor and FNAC smears, cytospin smears, and cellblocks of aspirated material were studied over a period of 2 years from September 2011 to September 2013. RESULTS: The material adequacies were 80% in FNAC smears, 83% in cytospin smears, and 89% in cellblocks. Additional information supported by cytospin smear and cellblock was 3% and 9%, respectively. Architectural preservation was better in FNAC smears (85%) and cellblocks (73.03%) than that in cytospin smears (31.33%). Morphological preservation was better in FNAC smears (90%) and cellblocks (75.28%) than that in cytospin smears (14.46%). Diagnostic accuracy was increased in the cellblocks and cytospin smears. CONCLUSION: Cytospin smear was helpful when low cellular material was obtained, and the concomitant examination of cellblocks not only confirmed the diagnosis of malignancy but also helped in classifying the obtained material and allowed further study on the same.