Mask-up: Investigating Biases in Face Re-identification for Masked Faces (preprint)

AI based Face Recognition Systems (FRSs) are now widely distributed and deployed as MLaaS solutions all over the world, moreso since the COVID-19 pandemic for tasks ranging from validating individuals' faces while buying SIM cards to surveillance of citizens. Extensive biases have been reported against marginalized groups in these systems and have led to highly discriminatory outcomes. The post-pandemic world has normalized wearing face masks but FRSs have not kept up with the changing times. As a result, these systems are susceptible to mask based face occlusion. In this study, we audit four commercial and nine open-source FRSs for the task of face re-identification between different varieties of masked and unmasked images across five benchmark datasets (total 14,722 images). These simulate a realistic validation/surveillance task as deployed in all major countries around the world. Three of the commercial and five of the open-source FRSs are highly inaccurate; they further perpetuate biases against non-White individuals, with the lowest accuracy being 0%. A survey for the same task with 85 human participants also results in a low accuracy of 40%. Thus a human-in-the-loop moderation in the pipeline does not alleviate the concerns, as has been frequently hypothesized in literature. Our large-scale study shows that developers, lawmakers and users of such services need to rethink the design principles behind FRSs, especially for the task of face re-identification, taking cognizance of observed biases.

COVID-19 VACCINATION-INFECTION STATUS AND IMMUNOLOGICAL PROFILE: IDENTIFICATION OF HIGH RISK POPULATION FOR TARGETED BOOSTER IMMUNIZATION IN INDIA (preprint)

Background: The COVID-19 pandemic's global impact was mitigated through rapid vaccine development, leading to a mix of natural and vaccination-derived immunity. Immunological profile in hybrid immunity remains less studies, especially in regions where non-mRNA vaccines were used. This study focuses on the immunological profiles and predictors of immune response in one such population. Methods: This was a cross-sectional study to assess their humoral and cellular immune responses based on vaccination and infection history. Immunological assays were performed to measure anti-spike protein and neutralizing antibodies as well as interferon-γ release assay. Multivariable linear regression model was used to estimate predictors of immune response. Results: The study revealed significant differences in immune response among participants based on their hybrid immunity status, vaccination, and infection history. Higher antibody titres and cellular responses were observed in individuals with hybrid immunity, especially those with dual pre-Omicron and Omicron infections (3326 BAU/ml, IQR: 770.25-5678.25 and 4.92 IU of IFN-γ/mL, IQR:3.74-16.98 respectively, p <0.001). Age and comorbidities such as diabetes and hypertension were associated with lower antibody levels and cellular response, while vaccination and hybrid immunity correlated with higher immune responses. Conclusion: The prevalence of hybrid immunity was high, yet a substantial portion of the population lacks it, indicating the necessity for targeted immunization strategies. The findings underscore the importance of prioritizing high-risk individuals, such as elderly and individuals with comorbidities, for booster vaccinations to enhance community-level protection against COVID-19.

RACER: An LLM-powered Methodology for Scalable Analysis of Semi-structured Mental Health Interviews (preprint)

Semi-structured interviews (SSIs) are a commonly employed data-collection method in healthcare research, offering in-depth qualitative insights into subject experiences. Despite their value, the manual analysis of SSIs is notoriously time-consuming and labor-intensive, in part due to the difficulty of extracting and categorizing emotional responses, and challenges in scaling human evaluation for large populations. In this study, we develop RACER, a Large Language Model (LLM) based expert-guided automated pipeline that efficiently converts raw interview transcripts into insightful domain-relevant themes and sub-themes. We used RACER to analyze SSIs conducted with 93 healthcare professionals and trainees to assess the broad personal and professional mental health impacts of the COVID-19 crisis. RACER achieves moderately high agreement with two human evaluators (72%), which approaches the human inter-rater agreement (77%). Interestingly, LLMs and humans struggle with similar content involving nuanced emotional, ambivalent/dialectical, and psychological statements. Our study highlights the opportunities and challenges in using LLMs to improve research efficiency and opens new avenues for scalable analysis of SSIs in healthcare research.

Peripheral Transcriptomics in Acute and Long-Term Kidney Dysfunction in SARS-CoV2 Infection (preprint)

Background. Acute kidney injury (AKI) is common in hospitalized patients with SARS-CoV2 infection despite vaccination and leads to long-term kidney dysfunction. However, peripheral blood molecular signatures in AKI from COVID-19 and their association with long-term kidney dysfunction are yet unexplored. Methods. In patients hospitalized with SARS-CoV2, we performed bulk RNA sequencing using peripheral blood mononuclear cells (PBMCs). We applied linear models accounting for technical and biological variability on RNA-Seq data accounting for false discovery rate (FDR) and compared the functional enrichment and pathway results to a historical sepsis-AKI cohort. Finally, we evaluated the association of these signatures with long-term trends in kidney function. Results. Of 283 patients, 106 had AKI. After adjustment for sex, age, mechanical ventilation, and chronic kidney disease (CKD), we identified 2635 significant differential gene expressions at FDR<0.05. Top canonical pathways were EIF2 signaling, oxidative phosphorylation, mTOR signaling, and Th17 signaling, indicating mitochondrial dysfunction and endoplasmic reticulum (ER) stress. Comparison with sepsis associated AKI showed considerable overlap of key pathways (48.14%). Using follow-up estimated glomerular filtration rate (eGFR) measurements from 115 patients, we found that 164/2635 (6.2%) of the significantly differentiated genes were associated with overall decrease in long-term kidney function. The strongest associations were autophagy, renal impairment via fibrosis and cardiac structure/function. Conclusions. We show that AKI in SARS-CoV2 is a multifactorial process with mitochondrial dysfunction driven by ER stress whereas long-term kidney function decline is associated with cardiac structure and function, and immune dysregulation. Functional overlap with sepsis-AKI also highlights common signatures indicating generalizability in therapeutic approaches.

Expansion of profibrotic monocyte-derived alveolar macrophages in patients with persistent respiratory symptoms and radiographic abnormalities after COVID-19 (preprint)

As many as 10-30% of the over 760 million survivors of COVID-19 develop persistent symptoms, of which respiratory symptoms are among the most common. To understand the cellular and molecular basis for respiratory PASC, we combined a machine learning-based analysis of lung computed tomography (CT) with flow cytometry, single-cell RNA-sequencing analysis of bronchoalveolar lavage fluid and nasal curettage samples, and alveolar cytokine profiling in a cohort of thirty-five patients with respiratory symptoms and radiographic abnormalities more than 90 days after infection with COVID-19. CT images from patients with PASC revealed abnormalities involving 73% of the lung, which improved on subsequent imaging. Interstitial abnormalities suggestive of fibrosis on CT were associated with the increased numbers of neutrophils and presence of profibrotic monocyte-derived alveolar macrophages in BAL fluid, reflecting unresolved epithelial injury. Persistent infection with SARS-CoV-2 was identified in six patients and secondary bacterial or viral infections in two others. These findings suggest that despite its heterogenous clinical presentations, respiratory PASC with radiographic abnormalities results from a common pathobiology characterized by the ongoing recruitment of neutrophils and profibrotic monocyte-derived alveolar macrophages driving lung fibrosis with implications for diagnosis and therapy.

Intracardiac Thrombus in COVID-19 Inpatients: A Nationwide Study of Incidence, Predictors and Outcomes (preprint)

Background: COronaVIrus Disease 2019 (COVID-19) has been observed to be associated with a hypercoagulable state. Intracardiac thrombosis is a serious complication but has seldom been evaluated in COVID-19 patients. We assessed the incidence, associated factors, and outcomes of COVID-19 patients with intracardiac thrombosis. Methods: COVID-19 inpatients during 2020 were retrospectively identified from the national inpatient sample (NIS) database, and data retrieved regarding clinical characteristics, intracardiac thrombosis, and adverse outcomes. Multivariable logistic regression was performed to identify the clinical factors associated with intracardiac thrombosis and in-hospital mortality and morbidities. Results: A total of 1,683,785 COVID-19 inpatients were identified in 2020 from NIS, with a mean age of 63.8 {+/-} 1.6 years, and 32.2% females. Intracardiac thrombosis was present in 0.001% (1,830) patients. Overall, in-hospital outcomes include all-cause mortality 13.2% (222,695/1,683,785), cardiovascular mortality 3.5%, cardiac arrest 2.6%, acute coronary syndrome (ACS) 4.4%, heart failure 16.1%, stroke 1.3% and acute kidney injury (AKI) 28.3%. The main factors associated with intracardiac thrombosis were a history of congestive heart failure and coagulopathy. Intracardiac thrombosis was independently associated with a higher risk of in-hospital all-cause mortality (OR: 3.32, 95% CI: 2.42-4.54, p<0.001), cardiovascular mortality (OR: 2.95, 95% CI: 1.96-4.44, p<0.001), cardiac arrest (OR: 2.04, 95% CI: 1.22-3.43, p=0.006), ACS (OR: 1.62, 95% CI: 1.17-2.22, p=0.003), stroke (OR: 3.10, 95% CI: 2.11-4.56, p<0.001), and AKI (OR: 2.13 95% CI: 1.68-2.69, p<0.001), but not incident heart failure (p=0.27). Conclusion: Although intracardiac thrombosis is rare in COVID-19 inpatients, its presence was independently associated with higher risks of in-hospital mortality and most morbidities. Prompt investigations and treatments for intracardiac thrombosis are warranted when there is a high index of suspicion and a confirmed diagnosis respectively.

Metaverse Skills for Executives and Senior Managers: The Pros and Cons

The COVID-19 pandemic has accelerated the shift from traditional office setups to remote working, driven by information and communication technology advancements. As a result, the metaverse concept is gaining popularity in modern organizations, allowing users to create avatars for virtual work, socializing, and other activities. While its corporate adoption is rising, managers must acquire the necessary skills to integrate and utilize the technology successfully. However, technological progress can be disruptive, making it essential to weigh the benefits and drawbacks.Methodology: This proposal aims to investigate metaverse skills that managers require for remote working using virtual realities, assessing the positive and negative risks for employees and management within business organizations. Using secondary data from reliable online databases, a qualitative research approach was used to understand the pros and cons of the metaverse and remote work.Purpose: The study examines the essential skills managers need to adopt metaverse virtual realities for remote working and how employees and organizations can implement it while maintaining a positive work environment. Keywords such as metaverse, remote working, virtual reality, and information and communication technology are critical. As technology evolves, managers and organizations must consider the metaverse's inherent advantages and disadvantages to ensure a successful transition to remote.Research Questions: What are the necessary skills needed by managers towards the adoption of metaverse virtual realities for remote working? How can employees and organizations adapt to implementing metaverse for remote work and sustain a positive work environment? © 2023 IEEE.

Consumer buying behaviour post and pre COVID analysis- specific reference to South Africa

This research focused on examining the motivational factors that determine the behaviour of consumers in pre and post pandemic times in South Africa by conducting a secondary literature study in the selected universe, with the aim of exploring the key factors in the changes of consumption in men and women, due to the situation of isolation caused by COVID 19. The economic factor referring to the consumption of basic necessities in consumer behaviour is a benchmark for marketing sanitary. Because cleaning, sanitizing and medicinal products have become part of the basic (emerging) consumption of men and women in South Africa. Likewise, the psychological factor, from an exercise and health perspective, is another important factor in times of pandemic. The present study conducted in two phases, pre and post COVID-19 in South Africa. During those period consumers used to buy in a hybrid mode of shopping. Twelve variables (items) are used for the scale development of buying behaviour and taken from the literature and further improved through EFA (Exploratory Factor Analysis) in the study. The questionnaire was developed using the five-point Likert scale. The survey tool consisted of 30 items. There are 258 respondents were replied through online questionnaire. Two set of questions were asked, and responses were analysed.

COVID-19 Detection using adopted convolutional neural networks and high-performance computing.

The COVID 19 pandemic is highly contagious disease is wreaking havoc on people's health and well-being around the world. Radiological imaging with chest radiography is one among the key screening procedure. This disease contaminates the respiratory system and impacts the alveoli, which are small air sacs in the lungs. Several artificial intelligence (AI)-based method to detect COVID-19 have been introduced. The recognition of disease patients using features and variation in chest radiography images was demonstrated using this model. In proposed paper presents a model, a deep convolutional neural network (CNN) with ResNet50 configuration, that really is freely-available and accessible to the common people for detecting this infection from chest radiography scans. The introduced model is capable of recognizing coronavirus diseases from CT scan images that identifies the real time condition of covid-19 patients. Furthermore, the database is capable of tracking detected patients and maintaining their database for increasing accuracy of the training model. The proposed model gives approximately 97% accuracy in determining the above-mentioned results related to covid-19 disease by employing the combination of adopted-CNN and ResNet50 algorithms.

Exploring the Perceived Educational Impact of COVID-19 on Postgraduate Training in Oncology.

This study sought to report the degree to which postgraduate trainees in radiation oncology perceive their education has been impacted by the COVID-19 pandemic. A cross-sectional online survey was administered from June to July 2020 to trainee members of the Canadian Association of Radiation Oncology (CARO) (n = 203). Thirty-four trainees responded with a 17% response rate. Just under half of participants indicated that COVID-19 had a negative/very negative impact on training (n = 15; 46%). The majority agreed/strongly agreed that they feared family/loved ones would contract COVID-19 (n = 29, 88%), felt socially isolated from friends and family because of COVID-19 (n = 23, 70%), and had difficulty concentrating on tasks because of concerns about COVID-19 (n = 17, 52%). Changes that had a negative/very negative impact on learning included limitations to travel and networking (n = 31; 91%) and limited patient contact (n = 19; 58%). Virtual follow-ups (n = 25: 76%) and in-patient care activities (n = 12; 36%) increased. Electives were cancelled in province (n = 10; 30%), out-of-province (n = 16; 49%), and internationally (n = 15; 46%). Teaching from staff was moderately reduced to completely suppressed (n = 23, 70%) and teaching to medical students was moderately reduced to completely suppressed (n = 27, 82%). Significant changes to radiation oncology training were wrought by the pandemic, and roughly half of trainees perceive that these changes had a negative impact on training. Innovations in training delivery are needed to adapt to these new changes.

Recurrent/Subsequent Stroke and Associated Outcomes in Geriatric Patients with OSA and Prior Stroke Events: A Retrospective Study Using the 2019 National Inpatient Sample.

Background: Obstructive sleep apnea (OSA) increases the risk of stroke and cardiovascular diseases. However, its impact on geriatric patients with a prior history of stroke/transient ischemic attack (TIA) has not been adequately studied. Methods: We utilized the 2019 National Inpatient Sample in the US to identify geriatric patients with OSA (G-OSA) who had a prior history of stroke/TIA. We then compared subsequent stroke (SS) rates among sex and race subgroups. We also compared the demographics and comorbidities of SS+ and SS- groups and utilized logistic regression models to assess outcomes. Results: Out of 133,545 G-OSA patients admitted with a prior history of stroke/TIA, 4.9% (6520) had SS. Males had a higher prevalence of SS, while Asian-Pacific Islanders and Native Americans had the highest prevalence of SS, followed by Whites, Blacks, and Hispanics. The SS+ group had higher all-cause in-hospital mortality rates, with Hispanics showing the highest rate compared to Whites and Blacks (10.6% vs. 4.9% vs. 4.4%, p < 0.001), respectively. Adjusted analysis for covariates showed that complicated and uncomplicated hypertension (aOR 2.17 [95% CI 1.78-2.64]; 3.18 [95% CI 2.58-3.92]), diabetes with chronic complications (aOR 1.28 [95% CI 1.08-1.51]), hyperlipidemia (aOR 1.24 [95% CI 1.08-1.43]), and thyroid disorders (aOR 1.69 [95% CI 1.14-2.49]) were independent predictors of SS. The SS+ group had fewer routine discharges and higher healthcare costs. Conclusions: Our study shows that about 5% of G-OSA patients with a prior history of stroke/TIA are at risk of hospitalization due to SS, which is associated with higher mortality and healthcare utilization. Complicated and uncomplicated hypertension, diabetes with chronic complications, hyperlipidemia, thyroid disorders, and admission to rural hospitals predict subsequent stroke.

A robust NIfTI image authentication framework to ensure reliable and safe diagnosis.

Advancements in digital medical imaging technologies have significantly impacted the healthcare system. It enables the diagnosis of various diseases through the interpretation of medical images. In addition, telemedicine, including teleradiology, has been a crucial impact on remote medical consultation, especially during the COVID-19 pandemic. However, with the increasing reliance on digital medical images comes the risk of digital media attacks that can compromise the authenticity and ownership of these images. Therefore, it is crucial to develop reliable and secure methods to authenticate these images that are in NIfTI image format. The proposed method in this research involves meticulously integrating a watermark into the slice of the NIfTI image. The Slantlet transform allows modification during insertion, while the Hessenberg matrix decomposition is applied to the LL subband, which retains the most energy of the image. The Affine transform scrambles the watermark before embedding it in the slice. The hybrid combination of these functions has outperformed previous methods, with good trade-offs between security, imperceptibility, and robustness. The performance measures used, such as NC, PSNR, SNR, and SSIM, indicate good results, with PSNR ranging from 60 to 61 dB, image quality index, and NC all close to one. Furthermore, the simulation results have been tested against image processing threats, demonstrating the effectiveness of this method in ensuring the authenticity and ownership of NIfTI images. Thus, the proposed method in this research provides a reliable and secure solution for the authentication of NIfTI images, which can have significant implications in the healthcare industry.

Recent advancements in coordination compounds and their potential clinical application in the management of diseases: An up-to-date review

Coordination compounds-based drugs are crucial in targeting various diseases due to their distinct structural order. They also show a significant role in biological systems, including human beings. For example, hemoglobin, a carrier of oxygen transportation in the blood, is a metal complex of Fe (II) ions and is vital for human life. In addition, they have been utilized for treating various diseases associated with human beings due to their excellent anti-bacterial, anti-cancer, and anti-viral potential. The coordination compounds of different metal ions such as platinum (Pt), palladium (Pd), ruthenium (Ru), nickel (Ni), chromium (Cr), silver (Ag), and gold (Au) have been used as anti-cancer drugs. Moreover, the metal complex of chromium, gold, and copper ions exhibited excellent anti-bacterial activity. Additionally, many coordination compounds revealed promising applications against malaria and neurodegenerative conditions like Alzheimer's. Recently, coordination compounds have been utilized as anti-viral drugs to treat coronavirus. In the present review, we have spotlighted the advanced and most significant coordination compounds that exhibit an essential role in medicine.

To evaluate the diagnostic accuracy of Modified Alvarado and Tzanakis scores in diagnosing Acute Appendicitis

Background: Evaluation of the diagnostic accuracy of Modified Alvarado and Tzanakis scores in diagnosing Acute Appendicitis. Materials & methods: Due to COVID-19 pandemic the sample size was selected to be 51. CECT abdomen was done. Postoperatively, the Modified Alvarado and Tzanakis scoring systems were applied on all these patients using scoring sheets keeping a cut off of 7 for the Modified Alvarado score, and 8 for the Tzanakis score followed by which, histopathological diagnosis of the removed appendix was obtained. Subsequently, comparison was made between the histopathological findings and the above calculated scores. Data were analysed using SPSS version 23. Qualitative data was compared using Chi-square test or Fischer exact test as applicable. Results: The reported sensitivity and specificity for modified Alvarado score was 97.6% and 66.7% respectively while for Tzanakis scoring was reported as 92.9% and 100% respectively. Positive predictive value for modified Alvarado score was 93.2 with a negative predictive value of 85.6% and a diagnostic accuracy of 92.1%. Positive predictive value for Tzanakis score was 100% with a negative predictive value of 75.1% and a diagnostic accuracy of 94.2%. Conclusion: Tzanakis scoring system is an effective modality to establish the accurate diagnosis of acute appendicitis which requires surgery especially in low resource areas and helps in reducing the rates of negative appendicectomy. Though acute appendicitis is a clinical diagnosis the scoring system can complement the clinical diagnosis. [ FROM AUTHOR] Copyright of Journal of Cardiovascular Disease Research (Journal of Cardiovascular Disease Research) is the property of Journal of Cardiovascular Disease Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Rationalizing the Use of COVID-19 Questionable Efficacy Drugs in a Low Middle-income Country: A Hospital Tocilizumab Committee Experience.

BACKGROUND: Only corticosteroids have confirmed mortality benefits in coronavirus disease of 2019 (COVID-19). Rational use of costlier drugs with questionable benefits poses a great concern to hospital pharmacies in low middle-income countriesAim: The present study aimed to assess the rational utilization of hospital supply tocilizumab and understand its clinical benefits in hospitalized COVID-19 pneumonia patientsMethods: The Hospital Tocilizumab Committee (HTC) decision support system framework was developed to make patients eligible or ineligible for tocilizumab procurement from the hospital pharmacy. A total of 33 consecutive patients receiving tocilizumab were analyzed retrospectively in the 3-month study period. The records of the inpatient stay of the patients were observed for pulse, blood pressure, respiratory rate (RR), oxygen saturation (SpO2), fraction of inspired oxygen (FiO2) laboratory work-up, hospital stay duration, and mortality benefit, if any. Patients were analyzed as "died," "survived," and "composite" subgroupsResults: The study observed death as a final outcome in 48% of patients. The study observed a significant effect of tocilizumab on C-reactive protein (CRP) (p = 0.02) and ferritin (p = 0.018) levels on a 10-day follow-up when all patients were analyzed together. Rising and declining trends of RR and FiO2 were observed among the "died" (RR, p = 0.02; FiO2, p = 0.03) and survived (RR, p = 0.03; FiO2, p = 0.05) subgroups. The second dose of tocilizumab was received by 88% of survivors as against 50% of patients who died (p = 0.04)Conclusion: Hospital Tocilizumab Committee (HTC) was successfully established to continue the assessment of the costlier drug with uncertain treatment benefits. A repeat dose of tocilizumab may provide a mortality benefit in Asian Indians.

Stage Migration in Renal Malignancies in COVID Era: A Single-Center Analysis.

The COVID-19 disease, caused by SARS-CoV-2 virus, attained the status of a pandemic by March 2020. There was apprehension among patients suffering from renal malignancies about balancing cancer treatment and preventing COVID-19 infection transmission. We analyzed 184 patients with renal malignancies retrospectively, who presented to our institute over 2 years: 91 patients of renal malignancies in pre-COVID era (March 2019-Feb 2020) and 93 patients in COVID era (March 2020-Feb 2021). The parameters analyzed were age, tumor size, clinical presentation, clinical stage, pathological stage, nuclear grade, and presence of metastasis. Level of significance was kept at 95%, and p value <0.05 was considered significant. The age of patients was comparable in both groups (p: 0.381). Clinical presentation was also similar in both groups whereas there were more cases diagnosed during routine evaluation in pre-COVID era (p: 0.022). Tumor size was 5.84 ± 3.03cm vs. 7.10±3.83cm (p: 0.017) in pre-COVID vs. COVID era, respectively. Patients in COVID era had significantly higher clinical stage (p = 0.041), pathological stage (p =0.027), nuclear grade (p = 0.007), and presence of metastasis (p = 0.005) as compared to pre-COVID era. Patients, who underwent Nephron-sparing surgery, also had higher pathological stage in COVID era. COVID overshadowed the management of renal malignancies. There was a clear shift and stage migration in patients of renal malignancies in COVID era as compared to pre-COVID era, probably because of less routine health check-ups and patients deferring hospital visits due to fear of contracting COVID infection.