In-silico analysis of SARS-CoV-2 N protein host interactors involved in Parkinson’s Disease and Dementia (preprint)

Severe-acute-respiratory-syndrome-coronavirus-2 (SARS-CoV-2) is a highly pathogenic and contagious coronavirus that first surfaced in late 2019. The genome encodes four major structural proteins, non-structural proteins and accessory proteins. The nucleocapsid (N) protein of SARS-CoV-2 is an evolutionarily conserved RNA-binding protein that is abundant and plays a critical role in packaging the viral genome. Researchers have explored its potential as a target for therapeutic purposes. People with pre-existing neurological conditions like Parkinson’s disease (PD) and dementia have been recognised as a high-risk population for severe COVID-19 illness as SARS-CoV-2 has been reported to cause deterioration of the symptoms of these diseases. This study aims to identify the shared human interactors of SARS-CoV-2 N protein, PD and dementia. Proteins involved were retrieved from databases, and protein-protein interaction networks were created and visualized in Cytoscape. Individual intersection networks of SARS-CoV-2 N protein with PD and dementia resulted in 46 and 26 proteins, respectively, while intersection networks of SARS-CoV-2 N protein, PD and dementia resulted in 15 common proteins. Seed proteins were identified from network clusters and their Gene Ontology (GO) analysis revealed their involvement in several biological processes. Valosin-containing-protein (VCP) was found to be the only seed protein involved during the co-occurrence of SARS-CoV-2 N protein infection, PD and dementia and is mainly concerned with the regulation of the ubiquitin-proteasome system (UPS). Further, gene enrichment analysis of the identified 15 common proteins was conducted using the DAVID tool, followed by the identification of 7 druggable targets using the Therapeutic Target Database (TTD) and DrugBank. Studying the biological functions of the identified host-protein interactors is crucial for understanding the progression of the disease at a molecular level. Moreover, approved therapeutic compounds against the potential drug target proteins can also be utilized to develop effective treatments.

Creutzfeldt-Jakob Disease with Initial Typical Parkinsonism Precipitated by COVID-19? A Case Report (preprint)

Background Creutzfeldt-Jakob disease (CJD) is a rare and fatal neurodegenerative disease caused by the accumulation of PrPSc. While COVID-19-induced sporadic CJD (sCJD) with parkinsonism as the initial symptom is extremely uncommon, this report aims to raise awareness of sCJD cases that present with parkinsonism that are not associated with genetic mutations or pathological α-synuclein (α-Syn) accumulation. Case presentation This report presents the case of a 72-year-old man with probable sporadic Creutzfeldt-Jakob disease (sCJD) who initially showed symptoms of parkinsonism, which worsened rapidly after contracting COVID-19. Despite a history of responsive tremor and bradykinesia, his condition deteriorated following the viral infection, leading to rapid consciousness decline and diffuse myoclonus. Diagnostic tests, including brain MRI, cerebrospinal fluid analysis, and EEG, pointed towards prion disease. PrPSc, a marker for CJD, was detected in both the cerebrospinal fluid and skin samples using RT-QuIC, further confirming the diagnosis. Notably, skin analysis revealed PrPSc but no pathological α-synuclein deposits, ruling out typical Parkinson's disease.  Conclussion This case underscores the importance of considering sCJD in patients with parkinsonism, especially if they experience sudden neuropsychiatric symptoms, especially if they do not exhibit pathological α-Syn accumulation or have genetic mutations.

Perceptions of Disrespect in the Hospital Workforce During the COVID-19 Pandemic: Analysis and Implications for the Future (preprint)

Background The COVID-19 pandemic brought disruption and uncertainties to hospital settings. The objective of the study is to expand our understanding of how the intensity and stressors of the pandemic impacted perceptions of disrespect among the United States (US) hospital workforce. This investigation focuses on three core dimensions. First, the study seeks to shed light on how perceptions of disrespect during the pandemic varied by job category, including physicians, nurses, clinical specialists, supervisors, and non-clinical support staff. Second, this analysis looks at the effect of having direct patient interaction on the likelihood that hospital workers perceived disrespect. And, lastly, this research compares worker perceptions of disrespect during the early versus later pandemic timeframes.Methods This study uses logistic regression and bivariate comparative analysis of publicly available data from the US Agency for Healthcare Research and Quality’s (AHRQ) 2021 and 2022 Hospital Surveys on Patient Safety Culture 2.0, spanning survey years of 2020–2022.Results Perceptions of workplace disrespect during the COVID-19 pandemic varied across job categories. Nurses and support staff are found to perceive the most disrespect, and physicians are much less likely than nurses to perceive disrespect (-.53 OR, p < 0.01). For both nursing and support workers, direct patient interaction did not play a role in the likelihood of perceiving disrespect. By contrast, for physicians, clinical specialists, and supervisors, directly interacting with patients is found to significantly impact the likelihood of perceiving disrespect. Physicians are also the job category with the greatest percentage shift (20–25%) in increased perceptions of disrespect from early to later stages of the COVID-19 pandemic.Conclusions Removing blind spots to experiences of disrespect within the workforce is essential to reducing it. Equipping workers with multiple pathways to safely report perceived disrespect without fear of retribution is the first step that can enable healthcare institutions to address it. Heightened accountability at all levels of an organization, conflict management and communication training, and team and individual interventions such as one-on-one coaching and peer support programs may all be useful strategies for improving cultures of respect.

Prevalence of Burnout in Health Professionals during the COVID-19 Pandemic: A Review of Reviews (preprint)

(1) Background: Burnout syndrome results from chronic stress in the work-place. The COVID-19 pandemic has imposed a heavy workload on health professionals, doctors and nurses to respond to first-line health care during the first two years of an emergency caused by this virus. The aim of this study was to evaluate the prevalence of burnout in healthcare personnel, doctors and nurses during the COVID-19 pandemic. (2) Methods: This was a review of reviews on the prevalence of professional burnout syndrome in healthcare personnel, doctors and nurses before or during the COVID-19 pandemic, without language restrictions or missing data from the Cochrane Library electronic databases. In total, 48,657 articles were obtained from Pub-Med/MEDLINE and the Web of Science. (3) Results: After completing the examination, 20 articles were included in the review. Of these articles, 7% included nurses in their study population, 72% interviewed doctors from different specialties, and the remaining 21% reported personnel data. Healthcare as a whole: In total, 624 articles with 233,087 participants were included. Regarding the prevalence by subscale, a PD of 33% (95% CI; 33%- 34%), an AE of 37% (95% CI; 37%- 37%) and a PR of 29% (95% CI) were found. %; 29% and 29%). ; (4) Conclusions: The incidences of DP and AE are high, and that of RP is low. These findings demonstrate the high prevalence of burnout according to subscale. Burnout is a problem of great magnitude, and as such, interventions must be implemented immediately at the individual and group levels by institutions and health systems.

Understanding Parkinson's Disease Conversations on Chinese Social Media: Themes, Trends, and Connections (preprint)

Parkinson's disease profoundly impacts patients' quality of life, yet public awareness is limited. As social networks reach broad audiences, they are vital platforms for health communication. This study analyzed Parkinson's disease (PD) topics on China's major social network, Weibo, to reveal public awareness and concerns. We found Parkinson's became a popular keyword due to its association with hand tremors, though this trend may impede public comprehensive understanding of this disease. Through time series analysis, marketing accounts were found to publish misinformation through concentrated posts during specific periods, but this false information had limited impact. Further analysis of communication network structures showed people focused more on mutual aid than acquiring Parkinson's disease knowledge. This indicates advanced technique should be develop to promote accurate Parkinson's knowledge through social media. Additionally, the COVID-19 pandemic over the past three years led people to pay more attention to Parkinson's, demonstrating social media's role in responding to health crises. Overall, this study details how people discuss diseases on social media, providing a basis for developing communication strategies to promote Parkinson's and other diseases, while also informing patient mutual aid systems. To our best knowledge, this is the first study revealing the communications characteristics of PD related contents on social network. The findings may also empower more effective health promotion and patient support worldwide through social networks.

Physiologically-based pharmacokinetic and pharmacodynamic (PBPK/PD) modeling as a tool for antiviral drug dose regimens for COVID-19 (preprint)

Background: and Purpose: Ritonavir-boosted lopinavir and chloroquine were withdrawn for COVID-19 treatment according to WHO recommendation. However, lopinavir is still being used for COVID-19 treatment in a clinical practice guideline without supportive evidence. We demonstrated the utility of physiologically-based pharmacokinetic (PBPK)/pharmacodynamic (PD) models to support clinical use of lopinavir and the withdrawal of chloroquine for COVID-19 treatment. Experimental approach: The developed whole-body PBPK models were validated against clinical data. Model validation was performed using acceptable methods. The inhibitory effect (%E) was calculated to demonstrate drug efficacy. The recommended drug regimen for COVID-19 was the combination of 400/100 mg lopinavir/ritonavir given twice daily and 300 mg base chloroquine given twice daily for 14 days. Key Results: This study successfully developed whole-body PBPK models (AAFEs of 1.2-fold). For patients with a 70 kg body weight, %E for chloroquine in epithelial lining fluid (ELF) and bronchial epithelial cells (BEC) were about 2% and 12%, respectively. The corresponding values for lopinavir were 66% and 87.4%, respectively. With the increased body weight to 90 kg, %E for lopinavir in BEC dramatically dropped to lower than 60%, while that in ELF was slightly decreased (86.87%). Conclusion and Implications: The results support the decision of withdrawing chloroquine and using lopinavir in asymptomatic (with positive antigen kit test) or mild COVID-19 cases. In addition, results support the administration of antiviral drugs within the ten days of infection to prevent treatment failure.

COVID-19 and Parkinson’s disease: a single-centered study and Mendelian randomization study (preprint)

Objective To investigate the effects of the release of COVID-19 restrictions on patients with PD, and the association between COVID-19 and PD.Methods A single-center survey was performed among patients with PD through a questionnaire from December 7, 2022, to March 10, 2023. Logistic regression was performed to analyze the infection-related risk factors. Then, a bidirectional two-sample Mendelian randomization was utilized to investigate the association between COVID-19 and PD.Results In cross-sectional analysis, the COVID-19 infection rate of PD was 65.7%. Forty-eight (35.3%) patients with PD experienced worsening of motor symptoms. Long PD course (OR: 3.296, P = 0.047) and duration of the last dose of COVID-19 vaccine (OR: 4.967, P = 0.034) were the infection-related risk factors. The MR analysis results supported that PD causally increases the risk of COVID-19 susceptibility (β = 0.081, OR = 1.084, P = 0.006). However, MR analysis showed that PD did not increases the risk of COVID-19 severity and hospitalization. In addition, no causal linkage of COVID-19 on PD was observed.Conclusion Our findings suggest that COVID-19 infection leads to worsened PD motor symptoms. Long PD course is the infection-related risk factors, and PD causally increases the risk of COVID-19 susceptibility. However, we found no evidence that COVID-19 contributes to PD.

Austria's KlimaTicket: Assessing the short-term impact of a cheap nationwide travel pass on demand (preprint)

Measures to reduce transport-related greenhouse gas emissions are of great importance to policy-makers. A recent example is the nationwide KlimaTicket in Austria, a country with a relatively high share of transport-related emissions. The cheap yearly season ticket introduced in October 2021 allows unlimited access to Austria's public transport network. Using the synthetic control and synthetic difference-in-differences methods, I assess the causal effect of this policy on public transport demand by constructing a data-driven counterfactual out of European railway companies to mimic the number of passengers of the Austrian Federal Railways without the KlimaTicket. The results indicate public transport demand grew slightly faster in Austria, i.e., 3.3 or 6.8 percentage points, depending on the method, than it would have in the absence of the KlimaTicket. However, the growth effect after the COVID-19 pandemic appears only statistically significant when applying the synthetic control method, and the positive effect on public transport demand growth disappears in 2022.

Neuropathological assessment of the olfactory bulb and tract in individuals with COVID-19 (preprint)

The majority of patients with Parkinson disease (PD) experience a loss in their sense of smell and accumulate insoluble alpha-synuclein aggregates in their olfactory bulbs (OB). Subjects affected by a SARS-CoV-2-linked illness (COVID-19) frequently experience hyposmia. We previously hypothesized that alpha-synuclein and tau misprocessing could occur following host responses to microbial triggers. Using semiquantitative measurements of immunohistochemical signals, we examined OB and olfactory tract specimens collected serially at autopsies between 2020 and 2023. Deceased subjects comprised 50 adults, which included COVID19+ patients (n=22), individuals with Lewy body disease (e.g., PD and dementia with Lewy bodies (DLB; n=6)), Alzheimer disease (AD; n=3), other non-synucleinopathy-linked degenerative diseases (e.g., progressive supranuclear palsy (PSP; n=2) and multisystem atrophy (MSA; n=1)). Further, we included neurologically healthy controls (HCO; n=9) and those with an inflammation-rich brain disorder as neurological controls (NCO; n=7). When probing for inflammatory changes focusing on anterior olfactory nuclei (AON) using anti-CD68 immunostaining, scores were consistently elevated in NCO and AD cases. In contrast, inflammation on average was not significantly altered in COVID19+ patients relative to controls, although anti-CD68 reactivity in their OB and tracts declined with progression in age. Mild-to-moderate increases in phospho-alpha-Syn and phospho-tau signals were detected in the AON of tauopathy- and synucleinopathy-afflicted brains, respectively, consistent with mixed pathology, as described by others. Lastly, when both sides were available for comparison in our case series, we saw no asymmetry in the degree of pathology of the left versus right OB and tracts. We concluded from our autopsy series that after a fatal course of COVID-19, microscopic changes, when present, in the rostral, intracranial portion of the olfactory circuitry generally reflected neurodegenerative processes seen elsewhere in the brain. In general, inflammation correlated best with the degree of Alzheimer's-linked tauopathy and declined with progression of age in COVID19+ patients.

A Four Years Longitudinal Study of Childhood Vaccination Trends and Supply Chain Resilience in Tanzania amid COVID-19 Pandemic (preprint)

Background The COVID-19 pandemic has significantly disrupted healthcare systems at all levels globally, notably affecting routine healthcare services such as childhood immunisations. This study delves into the impact of these disruptions on routine childhood vaccination programs in Tanzania. Methodology We conducted a longitudinal study over four years in five Tanzanian regions: Mwanza, Dar es Salaam, Mtwara, Arusha, and Dodoma. The study analysed trends in the usage of six key vaccines: Bacille Calmette-Guérin (BCG), Bivalent Oral Polio Vaccine (bOPV), Diphtheria Tetanus Pertussis, Hepatitis-B and Hib vaccine (DTP-HepB-Hib), measles-rubella (MR), Pneumococcal Conjugate Vaccine (PCV), and Rota vaccines. We evaluated annual and monthly vaccination trends using time series and regression analyses. Predictive modelling was performed using an Autoregressive Integrated Moving Average (ARIMA) model. Results The study recorded a total of 32,602,734 vaccination events across the regions from 2019 to 2022. Despite declining vaccination rates in 2020, there was a notable rebound in 2021, indicating the resilience of Tanzania's immunisation program. The analysis also highlighted regional differences in varying vaccination rates when standardised per 1000 population. Seasonal fluctuations were observed in the monthly vaccination rates, with BCG showing the most stable trend. Predictive modelling of BCG indicated stable and increasing vaccination coverage through 2023. Conclusion The findings underscore the robustness of Tanzania's childhood immunisation infrastructure in overcoming the challenges posed by the COVID-19 pandemic, marked by a strong recovery in vaccination rates post-2020. We provide valuable insights into the dynamics of vaccinations during a global health crisis and highlight the importance of sustained immunisation efforts in maintaining public health.

Olfactory and Cognitive Decrements in 1991 Gulf War Veterans (preprint)

Background Prominent symptoms of Gulf War illness (GWI), the disorder related to military service in the 1991 Gulf War (GW), include fatigue, pain, and cognitive dysfunction. Although anosmia is not a typical GWI symptom, anecdotally some veterans reported losing their sense smell shortly after the war. Because olfactory deficit is a prodromal symptom of neurodegenerative diseases like Parkinson’s and Alzheimer’s disease, and because we previously reported suggestive evidence that deployed GW veterans may be at increased risk for Mild Cognitive Impairment (MCI) and dementia, the current study examined the relationship between olfactory and cognitive function in deployed GW veterans.Methods Eighty deployed GW veterans (mean age: 59.9 ± 7.0; 4 female) were tested remotely with the University of Pennsylvania Smell Identification Test (UPSIT) and the Montreal Cognitive Assessment (MoCA). Veterans also completed self-report questionnaires about their health and deployment-related exposures and experiences. UPSIT and MoCA data from age-matched healthy controls (HC) were downloaded from the Parkinson’s Progression Markers Initiative (PPMI) study for comparison.Results GW veterans had a mean UPSIT score of 27.8 ± 6.3 (range 9–37) and a mean MoCA score of 25.3 ± 2.8 (range 19–30). According to age- and sex-specific normative data, 31% of GW veterans (vs. 8% PPMI HCs) had UPSIT scores below the 10th percentile. Nearly half (45%) of GW veterans (vs. 8% PPMI HCs) had MoCA scores below the cut-off for identifying MCI. Among GW veterans, but not PPMI HCs, there was a positive correlation between UPSIT and MoCA scores (Spearman’s ρ = 0.39, p < 0.001). There was no significant difference in UPSIT or MoCA scores between GW veterans with and without history of COVID and with and without Kansas GWI exclusionary conditions.Conclusions We found evidence of olfactory and cognitive deficits and a significant correlation between UPSIT and MoCA scores in a cohort of 80 deployed GW veterans. Because impaired olfactory function has been associated with increased risk for MCI and dementia, it may be prudent to screen aging, deployed GW veterans with smell identification tests so that hypo- and anosmic veterans can be followed longitudinally and offered targeted neuroprotective therapies as they become available.

Meta-Analysis of the Mechanisms Underlying COVID-19 Modulation of Parkinson’s Disease (preprint)

Coronavirus Disease-19 (COVID-19) is caused by the infection of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). The virus enters host cells through receptor-mediated endocytosis of angiotensin-converting enzyme-2 (ACE2), leading to systemic inflammation, also known as a “cytokine storm,” and neuroinflammation. COVID-19’s upstream regulator, interferon-gamma (IFNG), is downregulated upon the infection of SARS-CoV-2, which leads to the downregulation of ACE2. The neuroinflammation signaling pathway (NISP) can lead to neurodegenerative diseases, such as Parkinson's disease (PD), which is characterized by the formation of Lewy Bodies made of α-Synuclein protein encoded by synuclein alpha (SNCA). This study presents the pathways involved in the downregulation of ACE2 following SARS-CoV-2 infection and its effect on PD progression. Through QIAGEN’s Ingenuity Pathway Analysis, the study identifies the NISP as a top-five canonical pathway/signaling pathway and SNCA as a top-five upstream regulator. Core Analysis was also conducted on the associated molecules between COVID-19 and SNCA to construct a network connectivity map. The Molecule Activity Predictor tool was used to simulate the infection of SARS-CoV-2 by downregulating IFNG, which leads to the predicted activation of SNCA, and subsequently PD, through a dataset of intermediary molecules. Downstream Effect analysis was further used to quantify the downregulation of ACE2 on SNCA activation.

A Systematic Review of Diffusion Microstructure Imaging (Dmi): Current and Future Applications in Neurology Research (preprint)

Background: Diffusion microstructure imaging (DMI) is a novel diffusion magnetic resonance imaging (MRI) technique that provides rich estimates of microscopic tissue properties, such as axon morphologies and fiber configurations. DMI has potential applications in neurology, where various diseases and disorders affect the brain tissue's microstructure and connectivity.Objectives: To investigate the current and future applications of DMI in neurology, covering various diseases and disorders such as brain tumors and metastases, Parkinson's syndromes, COVID-19-related neurological symptoms, temporal lobe epilepsy, and acute ischemic stroke.Methods: The PRISMA 2020 statement was followed. Four electronic databases were searched from inception to May the 5th 2023. Two reviewers independently screened, selected, and extracted data from the eligible studies.Results: Seven studies were included in the review. The studies showed that DMI can differentiate between various neurological diseases or disorders based on alterations in brain tissue microstructure and connectivity. The studies also showed that DMI can be superior to conventional diffusion imaging techniques, such as diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI), in detecting subtle differences between pathological conditions.Conclusions: DMI is a powerful diffusion imaging technique that can provide rich estimates of microscopic tissue properties and differentiate between various neurological diseases or disorders. However, more research is needed to compare DMI with other imaging modalities or clinical measures and to evaluate longitudinal changes or treatment effects using DMI in neurological diseases or disorders.

Invariant Scattering Transform for Medical Imaging (preprint)

Invariant scattering transform introduces new area of research that merges the signal processing with deep learning for computer vision. Nowadays, Deep Learning algorithms are able to solve a variety of problems in medical sector. Medical images are used to detect diseases brain cancer or tumor, Alzheimer's disease, breast cancer, Parkinson's disease and many others. During pandemic back in 2020, machine learning and deep learning has played a critical role to detect COVID-19 which included mutation analysis, prediction, diagnosis and decision making. Medical images like X-ray, MRI known as magnetic resonance imaging, CT scans are used for detecting diseases. There is another method in deep learning for medical imaging which is scattering transform. It builds useful signal representation for image classification. It is a wavelet technique; which is impactful for medical image classification problems. This research article discusses scattering transform as the efficient system for medical image analysis where it's figured by scattering the signal information implemented in a deep convolutional network. A step by step case study is manifested at this research work.

An in silico investigation of the phytomolecules present in Piper longum roots as a potential treatment for SARS-CoV-2 (preprint)

The epidemic of COVID-19 brought on by SARS-CoV-2 (coronavirus related to SARS) as well as its variants is still a life-threatening and critical risk to public health around the world. Due to the COVID-19 virus's propensity for mutation, the pandemic is still spreading havoc compared to SARS-CoV-2. Several phytochemicals are now undergoing in silico analysis for their anti-SARS-CoV-2 efficacy. Scientists all over the world are on the lookout for novel lead phytochemicals that can effectively block SARS-CoV-2 entrance and infection in host cells. Piper longum phytomolecules suggest that it may be more effective to use natural remedies and herbal extracts to improve immunity and fight the infection. In this current in silico study of different Piper longum phytochemicals like sesamin, piperine, gamma-sitosterol, and epizonarene, Utilizing Lipinski's rule, study the drugability guidelines and oral bioavailability of these compounds. Four putative SARS-CoV-2 therapeutic targets were explored using the top four ligands in a comparative study. Our finding shows that sesamin, piperine, gamma-sitostenone, and epizonarene all displayed binding affinity values of -8.9, -7.8, -7.4, and − 7.2 kcal/mol, respectively. Sesamin was found to have a greater negative binding energy toward the SARS-CoV-2 targets, which is a significant finding. We concluded that sesamin may be effective as a treatment for SARS-CoV-2.

How Toll-like receptors influence Parkinson's disease in the microbiome-gut-brain axis.

Recently, a large number of experimenters have found that the pathogenesis of Parkinson's disease may be related to the gut microbiome and proposed the microbiome-gut-brain axis. Studies have shown that Toll-like receptors, especially Toll-like receptor 2 (TLR2) and Toll-like receptor 4 (TLR4), are key mediators of gut homeostasis. In addition to their established role in innate immunity throughout the body, research is increasingly showing that the Toll-like receptor 2 and Toll-like receptor 4 signaling pathways shape the development and function of the gut and enteric nervous system. Notably, Toll-like receptor 2 and Toll-like receptor 4 are dysregulated in Parkinson's disease patients and may therefore be identified as the core of early gut dysfunction in Parkinson's disease. To better understand the contribution of Toll-like receptor 2 and Toll-like receptor 4 dysfunction in the gut to early α-synuclein aggregation, we discussed the structural function of Toll-like receptor 2 and Toll-like receptor 4 and signal transduction of Toll-like receptor 2 and Toll-like receptor 4 in Parkinson's disease by reviewing clinical, animal models, and in vitro studies. We also present a conceptual model of the pathogenesis of Parkinson's disease, in which microbial dysbiosis alters the gut barrier as well as the Toll-like receptor 2 and Toll-like receptor 4 signaling pathways, ultimately leading to a positive feedback loop for chronic gut dysfunction, promoting α-synuclein aggregation in the gut and vagus nerve.

Feasibility and Efficacy of Online Neuropsychological Assessment.

Neuropsychological testing has intrinsic challenges, including the recruitment of patients and their participation in research projects. To create a method capable of collecting multiple datapoints (across domains and participants) while imposing low demands on the patients, we have developed PONT (Protocol for Online Neuropsychological Testing). Using this platform, we recruited neurotypical controls, individuals with Parkinson's disease, and individuals with cerebellar ataxia and tested their cognitive status, motor symptoms, emotional well-being, social support, and personality traits. For each domain, we compared each group to previously published values from studies using more traditional methods. The results show that online testing using PONT is feasible, efficient, and produces results that are in line with results obtained from in-person testing. As such, we envision PONT as a promising bridge to more comprehensive, generalizable, and valid neuropsychological testing.

Proteomic landscape of astrocytes and pericytes infected with HIV/SARS-CoV-2 mono/co-infection, impacting on neurological complications (preprint)

Background Although most individuals recover from coronavirus disease 2019 (COVID-19) within a few weeks, some people continue to experience a wide range of symptoms known as post-acute sequelae of SARS-CoV-2 (PASC) or long COVID. Majority of patients with PASC develop neurological disorders like brain fog, fatigue, mood swings, sleep disorders, loss of smell and test among others collectively called neuro-PASC. While the people living with HIV (PWH) do not have a higher risk of developing severe disease and mortality/morbidity due to COVID-19. As a large section of PWH suffered from HIV-associated neurocognitive disorders (HAND), it is essential to understand the impact of neuro-PASC on people with HAND. In pursuit of this, we infected HIV/SARS-CoV-2 alone or together in primary human astrocytes and pericytes and performed proteomics to understand the impact of co-infection in the central nervous system.Methods Primary human astrocytes and pericytes were infected with SARS-CoV-2 or HIV or HIV + SARS-CoV-2. The concentration of HIV and SARS-CoV-2 genomic RNA in the culture supernatant was quantified using reverse transcriptase quantitative real time polymerase chain reaction (RT-qPCR). This was followed by a quantitative proteomics analysis of mock, HIV, SARS-CoV-2, and HIV + SARS-CoV-2 infected astrocytes and pericytes to understand the impact of the virus in CNS cell types.Results Both healthy and HIV-infected astrocytes and pericytes support abortive/low level of SARS-CoV-2 replication. In both mono-infected and co-infected cells, we observe a modest increase in the expression of SARS-CoV-2 host cell entry factors (ACE2, TMPRSS2, NRP1, and TRIM28) and inflammatory mediators (IL-6, TNF-α, IL-1β and IL-18). Quantitative proteomic analysis has identified uniquely regulated pathways in mock vs SARS-CoV-2, mock vs HIV + SARS-CoV-2, and HIV vs HIV + SARS-CoV-2 infected astrocytes and pericytes. The gene set enrichment analysis revealed that the top ten enriched pathways are linked to several neurodegenerative disorders, including Alzheimer's disease, Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis.Conclusions Our study emphasizes the significance of long-term monitoring of patients co-infected with HIV and SARS-CoV-2 to detect and understand the development of neurological abnormalities. By unraveling the molecular mechanisms involved, we can identify potential targets for future therapeutic interventions.

Development of Multi-Target Pharmacophore-Based Virtual Screening Agent Against COVID-19 (preprint)

The worldwide outbreak of the COVID-19 pandemic compelled scientists to develop new, highly effective therapeutic approaches to fight it. Multitarget drugs have been proven to be effective in managing complex disorders. But designing multitarget drugs is a great challenge. In this study, to prevent lack of efficacy due to viral mutation escape, a multi-target agent against the COVID-19 virus was discovered. As crucial targets, RNA-dependent RNA polymerase (RdRp), COVID-19 main protease (Mpro), and SARS-CoV-2 Nsp15 were selected. A pharmacophore model was developed using the native ligands of the chosen targets. This model was used to screen the ZINC Drug Database for commercially available compounds having similar features to the experimentally tested drugs. Pharmacophore-based virtual screening yielded 1331 hits, which were further docked into the binding sites of selected proteins using PyRx AutoDock Vina. Evaluation of docking results revealed that glisoxepide (Zn 00537804) has the highest binding scores for the three target proteins. It showed binding free energies of -6.8, -6.2, and -7.8 kcal/mol towards SARS-CoV-2 Mpro, Nsp15, and RdRp, respectively. According to an in silicoADME study, glisoxepide follows Lipinski's rule. The results of a molecular dynamics simulation study and subsequent investigations showed that glisoxepide had good dynamics and stability within the active sites of selected targets. The promise of glisoxepide as a potential treatment for SARS-CoV-2 still needs to be further evaluated through experimental research.