Toward a Multi-Column Knowledge-Oriented Neural Network for Web Corpus Causality Mining

In the digital age, many sources of textual content are devoted to studying and expressing many sorts of relationships, including employer–employee, if–then, part–whole, product–producer, and cause–effect relations/causality. Mining cause–effect relations are a key topic in many NLP (natural language processing) applications, such as future event prediction, information retrieval, healthcare, scenario generation, decision making, commerce risk management, question answering, and adverse drug reaction. Many statistical and non-statistical methods have been developed in the past to address this topic. Most of them frequently used feature-driven supervised approaches and hand-crafted linguistic patterns. However, the implicit and ambiguous statement of causation prevented these methods from achieving great recall and precision. They cover a limited set of implicit causality and are difficult to extend. In this work, a novel MCKN (multi-column knowledge-oriented network) is introduced. This model includes various knowledge-oriented channels/columns (KCs), where each channel integrates prior human knowledge to capture language cues of causation. MCKN uses unique convolutional word filters (wf) generated automatically using WordNet and FrameNet. To reduce MCKN's dimensionality, we use filter selection and clustering approaches. Our model delivers superior performance on the Alternative Lexicalization (AltLexes) dataset, proving that MCKN is a simpler and distinctive approach for informal datasets.

Increased Levels of Autoantibodies against ROS-Modified Proteins in Depressed Individuals with Decrease in Antibodies against SARS-CoV-2 Antigen (S1-RBD).

Coronavirus 2019 (COVID-19) disease management is highly dependent on the immune status of the infected individual. An increase in the incidence of depression has been observed during the ongoing COVID-19 pandemic. Autoantibodies against in vitro reactive oxygen species (ROS) modified BSA and Lys as well as antibodies against receptor binding domain subunit S1 (S1-RBD) (S1-RBD-Abs) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were estimated using direct binding and competition ELISA. Serum samples were also tested for fasting blood glucose (FBG), malondialdehyde (MDA), carbonyl content (CC), interferon-gamma (IFN-γ) and tumor necrosis factor-alpha (TNF-α). Significant structural changes were observed in ROS modified BSA and Lys. Female depressed subjects who were also smokers (F-D-S) showed the highest levels of oxidative stress (MDA and CC levels). Similarly, increased levels of autoantibodies against ROS modified proteins were detected in F-D-S subjects, in males who were depressed and in smokers (M-D-S) compared to the other subjects from the rest of the groups. However, contrary to this observation, levels of S1-RBD-Abs were found to be lowest in the F-D-S and M-D-S groups. During the pandemic, large numbers of individuals have experienced depression, which may induce excessive oxidative stress, causing modifications in circulatory proteins. Thus, the formation of neo-antigens is induced, which lead to the generation of autoantibodies. The concomitant effect of increased autoantibodies with elevated levels of IFN-γ and TNF-α possibly tilt the immune balance toward autoantibody generation rather than the formation of S1-RBD-Abs. Thus, it is important to identify individuals who are at risk of depression to determine immune status and facilitate the better management of COVID-19.

Seroprevalence of Anti-S1-RBD Antibodies in Pre-pandemic and Pandemic Subjects From Hail Region, KSA.

Background: Two years into the pandemic, yet the threat of new SARS-CoV-2 variants continues to loom large. Sustained efforts are required to fully understand the infection in asymptomatic individuals and those with complications. Identification, containment, care, and preventative strategies rely on understanding the varied humoral immune responses. Methods: An in-house ELISA was developed and standardized to screen for serum IgG antibodies against the SARS-CoV-2 S1-RBD protein as an antigen. This study aims to investigate the seroprevalence of serum antibodies against S1-RBD antigen in pre-pandemic (n = 120) and during the early pandemic period (n = 120) in subjects from the Hail region, KSA and to correlate it with clinical and demographic factors. Results: Samples collected from both male (n = 60) and female (n = 60) subjects during the pandemic in the age groups of 20-40 (0.31 ± 0.029 and 0.29 ± 0.024, respectively) and 41-60 years (0.35 ± 0.026 and 0.30 ± 0.025, respectively) showed significantly higher levels of serum antibodies against S-RBD antigen than the age-matched pre-pandemic samples [male (n = 60) and female (n = 60)]. Pandemic subjects exhibited significantly (p < 0.01) higher inhibition (80-88%) than age-matched pre-pandemic subjects (32-39%). Antibodies against S1-RBD antigen were detected in approximately 10% of the total pre-pandemic population (males and females). However, subjects > 60 years did not show antibodies. Conclusion: Antibody levels increased in samples collected during the pandemic, even though these subjects were not clinically COVID-19 positive. A small number of pre-pandemic subjects showed serum antibodies, suggesting prior exposure to other coronaviruses in the region. With dwindling neutralizing antibody levels and reduced vaccine efficacy against newer variants, it remains crucial to develop better assays for surveillance, management, and future research.

Pharmacological Profile of Nigella sativa Seeds in Combating COVID-19 through In-Vitro and Molecular Docking Studies

COVID-19 infection is associated with elevated oxidative stress, systemic hyper-inflammatory responses, endothelial dysfunction, and red blood cell membrane deformability. Nigella sativa extract is widely used in alternative and complementary medicine systems in a large population, due to its highly therapeutic, economic, natural, and safe nature. The aim of this study was to evaluate the effect of N. sativa extract on oxidative stress, hemolysis, proteolysis, and glycation through in vitro studies, as well as to find out its anti-viral potential against severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) using in silico studies. N. sativa seed extract (at 600 µg/mL) displayed 67.33% scavenging activity in the 2,2-diphenyl-1-picrylhydrazyl (DPPH) test, and 70.28% hydrogen peroxide reducing activity. N. sativa exhibited anti-proteolytic activity by decreasing heat-induced denaturation of bovine serum albumin (BSA) and egg albumin by 63.14% and 57.95%, respectively, and exhibited anti-proteinase potential of 66.28% at 600 μg/mL. In addition, heat-induced hemolysis and hypersalinity-induced hemolysis were inhibited by 57.86% and 61.7%, respectively, by the N. sativa seeds. N. sativa also inhibited browning intensity by 56.38%, and percent aggregation index by 51.38%, amyloid structure by 48.28%, and AGE-specific fluorescence by 52.18%, thereby protecting the native structure of BSA from glycation. The binding interactions between bioactive molecules of N. sativa seed with SARS-CoV-2 spike glycoprotein were proven by using in silico molecular docking tools. The functional amino acids involved in the interactions are Asp467, Thr108, Thr114, Ile468, Asn234, Gln155, Glu465, Arg466, Gly232, and Ile233, indicating the inhibiting property of N. sativa on SARS-CoV-2. Finally, we may infer that phytoconstituents of N. sativa seeds have the potential to protect against the spike protein of SARS-CoV-2. Studies on N. sativa seeds might act as a path to develop a potent alternative therapy against viral infections, especially COVID-19 infection, in the future. However, the limitations linked with the use of natural products are also needed to be considered in this regard.

Analytical methods for Ebola virus detection

Ebola virus (EBOV) outbreaks have been reported to be the most severe mortally recurrent illness due to a lack of timely diagnosis and medication. EBOV disease is a severe syndrome of hemorrhagic viral fever caused by the EBOV, is spread directly in contact with infected body fluids and virus-contaminated or animal-affected objects. Individuals typically die before antibody response at the point of fatal EBOV infection. Currently, prognosis includes a combination of case identification and lab tests, typically real-time PCR or reverse transcription to diagnose viral RNA or rapid immunoassay-based detection methods to identify EBOV antigens. Moreover, few nanotech-based ways have lately been identified to diagnose the Ebola virus. Optical monitoring, in particular, permits fluorescence molecules to be recognized with the naked eye or fluorometers. Also, electrochemical identification methods (either amperometry, potentiometric, or impedimetric) could provide a susceptible system utilizing disposable lab on chips. Furthermore, the electrochemical devices may be easily miniaturized using a hand-held potentiostat, eliminating the need for complicated diagnostic tools. Advances in technology have also been coupled with growing attempts to improve the capacity for decentralized diagnostic identification that can be used near the patient care level. Infectious illness outbreaks can be contained more easily with timely identification and treatment optimization. Currently, technical advancements in artificial intelligence (AI) and the internet of medical things(IoMT) are being used to assist such POCT. Therefore, IoMT provides wireless-based operation & interconnection of POCT devices to health experts & medical care centers. POCT systems with IoMT can bridge the gap between bioinformatics generation, quick analysis & clinical validation. An optimal IoMT-POCT will aid in determining the development of the disease, making treatment recommendations, and assessing prescribed therapy's efficiency. This review illustrates some conventional strategies for diagnosing Ebola & advocates for a fast, accurate, and responsive point of care identification of EBOV for massive health care.

Suicide, self-harm and suicidal ideation during COVID-19: A systematic review.

We aimed to do a systematic review and meta-analysis of studies describing suicidal ideation, suicide attempts and suicide and associated risk factors during COVID-19 pandemic. We searched following electronic databases using relevant search terms: Medline, Embase, PsycInfo and CINAHL and systematically reviewed the evidence following PRISMA guidelines. The meta-analysis of prevalence of suicidal ideation was done using random effect model. The search returned 972 records, we examined 106 in full text and included 38 studies describing 120,076 participants. Nineteen studies described suicide or attempted self-harm, mostly in case reports. Out of 19 studies describing suicidal ideations, 12 provided appropriate data for meta-analysis. The pooled prevalence of suicidal ideation in these studies was 12.1% (CI 9.3-15.2). Main risk factors for suicidal ideations were: low social support, high physical and mental exhaustion and poorer self-reported physical health in frontline medical workers, sleep disturbances, quarantine and exhaustion, loneliness, and mental health difficulties. We provide first meta-analytic estimate of suicidal ideation based on large sample from different countries and populations. The rate of suicidal ideations during COVID pandemic is higher than that reported in studies on general population prior to pandemic and may result in higher suicide rates in future.

Utility of teleconsultation in accessing eye care in a developing country during COVID-19 pandemic.

OBJECTIVE: To evaluate the utility of teleconsultation in the provision of eye care services during the COVID-19 lockdown. Disparities in the consultation burden of sub-specialities and socio-demographic differences in teleconsultation utilization were also assessed. METHODS: Al-Shifa Trust Eye Hospital Rawalpindi began audio and video teleconsultation using broadband telecommunication services during the lockdown. Patients' and consultations' data gathered during the first three weeks after the commencement of this programme were compared with data from the four weeks prior to lockdown. The weekly consultation ratio and overall consultation burden of sub-specialities were measured. Chi-Square tests of association determined the relationship between different variables (socioeconomic status and consultation characteristics) and consultation modality (on-site vs online). RESULTS: In total, 17507 on-site consultations (4377/week) were conducted compared to 1431 teleconsultations (477/week), which maintained 10.89% of the weekly pre-lockdown eye care services. The post-lockdown teleconsultation programme saw a relatively higher percentage of service utility among female (47.09% vs 44.71%), younger-age (31.33±19.45 vs 41.25±23.32 years) and higher-socioeconomic-status (32.21% vs 0.30%) patients compared to pre-lockdown on-site consultations. The most common indication for teleconsultation was red-eye (16.70%). While cornea and glaucoma clinics maintained most of the pre-lockdown services (30.42% and 29% respectively), the highest dropout was seen in optometric and vitreoretinal services supporting only 5.54% and 8.28% of pre-lockdown services, respectively. CONCLUSION: Digital initiatives could partially maintain eye care services during the lockdown. Focused strategies to improve teleconsultation utilization are required during the pandemic and beyond.

Cytokine Response in SARS-CoV-2 Infection in the Elderly.

The last few months of 2019 witnessed the emergence, rise and rapid spread of a novel coronavirus known as severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), causing an acute respiratory disease called coronavirus disease 2019 or Covid-19. Severe pathological manifestations of the disease in the infected population with comorbidities are linked to acute respiratory distress syndrome (ARDS), associated with an exaggerated synthesis and expression of cytokines, leading to a systemic inflammatory response also known as a cytokine storm (CS). Elderly patients (>60 years of age) showed more deaths in Covid-19 infection. Age-related immune imbalance increases patient susceptibility to CS. In acute Covid-19 infection, it is difficult to minimize or control the overproduction of cytokines; hence, limited medical treatments are effective. This review aims to provide an overview of the current knowledge of involvement of cytokines in SARS-CoV-2 infection, susceptibility factors for the accompanying cytokine storm in severe Covid-19 cases and possible treatment strategies.