Oscar N Whitney; Basem Al-Shayeb; Alex Crits-Cristoph; Mira Chaplin; Vinson Fan; Hannah Greenwald; Adrian Hinkle; Rose Kantor; Lauren Kennedy; Anna Maurer; +3 more
Oscar N Whitney; Basem Al-Shayeb; Alex Crits-Cristoph; Mira Chaplin; Vinson Fan; Hannah Greenwald; Adrian Hinkle; Rose Kantor; Lauren Kennedy; Anna Maurer; Robert Tjian; UC Berkeley Wastewater-based epidemiology consortium; Kara L Nelson;
This protocol describes the procedure of the "4S" (Sewage, Salt, Silica and SARS-CoV-2) method for SARS-CoV-2 RNA extraction from wastewater. Offering a highly efficient, modular and economical alternative to existing wastewater RNA purification methods, this procedure lowers the barrier to entry for SARS-CoV-2 wastewater-based epidemiology. This procedure is intended to be carried out in a BSL2+ laboratory space, with precautions when handling raw wastewater samples.
ABSTRACTThere is an urgent need for animal models of COVID-19 to study immunopathogenesis and test therapeutic intervenes. In this study we showed that NSG mice engrafted with human lung (HL) tissue (NSG-L mice) could be infected efficiently by SARS-CoV-2, and that live virus capable of infecting Vero cells was found in the HL grafts and multiple organs from infected NSG-L mice. RNA-seq examination identified a series of differentially expressed genes, which are enriched in viral defense responses, chemotaxis, interferon stimulation, and pulmonary fibrosis between HL grafts from infected and control NSG-L mice. Furthermore, when infecting humanized mice with human immune system (HIS) and autologous HL grafts (HISL mice), the mice had bodyweight loss and hemorrhage and immune cell infiltration in HL grafts, which were not observed in immunodeficient NSG-L mice, indicating the development of anti-viral immune responses in these mice. In support of this possibility, the infected HISL mice showed bodyweight recovery and lack of detectable live virus at the later time. These results demonstrate that NSG-L and HISL mice are susceptible to SARS-CoV-2 infection, offering a useful in vivo model for studying SARS-CoV-2 infection and the associated immune response and immunopathology, and testing anti-SARS-CoV-2 therapies.
Abstract Background: The nature of COVID-19 pandemic measures has altered the clinical management of migraine, and has also created barriers to evaluate the impact of such measures of migraine patients. Using the Migraine Buddy smartphone application, we assessed the impact of the COVID-19 pandemic on migraine in users residing in the United States.Methods: Migraine Buddy is a smartphone application by individuals to record their migraine headache episodes, characteristics, and coping mechanisms. For this study, anonymized self-reported data from 163,176 adult Migraine Buddy users in the United States between January 2020 and May 2020, were analyzed for migraines associated with stress. A stress-related migraine is defined as one in which stress or anxiety was reported as a trigger or symptom. A questionnaire on the impact of COVID-19 on migraine and its management was also completed by 1,322 users in the app between April 2020 and May 2020. Results: 88% of the Migraine Buddy database extract and 83% of the respondents are female, with a mean age of 36.2 years. The proportion of stress-related migraine attacks peaked at 50% on March 17, although the number of migraine attacks decreased. This followed the declaration of the COVID-19 national emergency on March 13 and a spike in the number of COVID-19 cases in the United States. Questionnaire respondents felt that the following added more stress: social isolation (22.6%), information overdose (21.2%), access to essentials (food, medication, etc.) (18.7%), and financial concerns (17.8%). To help manage migraine during COVID-19, respondents suggested stress and diet coaching programs and resources (medical articles, etc.) (34.0%), having the option for home delivery of medication (30.6%) and tele-consulting (25.5%).Conclusion: Here, we report the change in the proportion of self-reported stress-related migraine in relation to evolution of the COVID-19 pandemic, as well as its impact of migraine management. Our data will help increase the understanding of patients' needs and help with planning and execution of mitigating strategies.
Abstract Grayscale image attributes from 456 images extracted from CT scan slices of 53 patients (49 with COVID-19 and 4 without) are used to establish a visual scale of severity of lung abnormalities (five classes: 0 to 4). The complex trends of these easy-to-derive image attributes can be used graphically to discern the visual scale of lung abnormalities in broad terms. With the aid of machine learning algorithms, the visual classes can be distinguished with close to 95% accuracy using combinations of selected grayscale attributes. Confusion matrices reveal that the best-performing machine learning models are able to distinguish more accurately between certain classes than visual inspection of CT images by experts. The adaboost, decision tree and random forest models confused on average less than 25 of the 456 CT-scan image extracts evaluated between the visual classes of lung abnormalities.
Farhan S. Cyprian; Muhammad Suleman; Ibrahim Abdelhafez; Asmma Doudin; Ibn Mohammed Masud Danjuma; Fayaz Mir; Aijaz Parray; Zohaib Yousaf; Mohammed Yassin Ahmed Siddiqui; Ala Eldin; +8 more
Farhan S. Cyprian; Muhammad Suleman; Ibrahim Abdelhafez; Asmma Doudin; Ibn Mohammed Masud Danjuma; Fayaz Mir; Aijaz Parray; Zohaib Yousaf; Mohammed Yassin Ahmed Siddiqui; Ala Eldin; Mohammad Mulhim; Shaikha D. Al-Shokri; Mohammad Abukhattab; Ranad Shaheen; Eyad Elkord; Abdul Latif Al-khal; Abdel Naser Al Zouki; Guillermina Girardi;
Abstract Coronavirus disease-2019 (COVID-19) was declared as a pandemic by WHO in March 2020. SARS-CoV-2 causes a wide range of illness from asymptomatic to life-threatening. There is an essential need to identify biomarkers to predict disease severity and mortality during the earlier stages of the disease, aiding treatment and allocation of resources to improve survival. The aim of this study was to identify at the time of SARS-COV-2 infection patients at high risk of developing severe disease associated with low survival using blood parameters, including inflammation and coagulation mediators, vital signs, and pre-existing comorbidities. This cohort included 89 multi-ethnic COVID-19 patients recruited between July 14th and October 20th 2020 in Doha, Qatar. According to clinical severity, patients were grouped into severe (n = 33), mild (n = 33) and asymptomatic (n = 23). Common routine tests such as complete blood count (CBC), glucose, electrolytes, liver and kidney function parameters and markers of inflammation, thrombosis and endothelial dysfunction including complement component split product C5a, Interleukin-6, ferritin and C-reactive protein were measured at the time COVID-19 infection was confirmed. Correlation tests suggest that C5a is a novel predictive marker of disease severity and mortality, in addition to 40 biological and physiological parameters that were found statistically significant between survivors and non-survivors. Survival analysis showed that. high C5a levels, hypoalbuminemia, lymphopenia, elevated procalcitonin, neutrophilic leukocytosis, acute anemia along with increased acute kidney and hepatocellular injury markers were associated with a higher risk of death in COVID-19 patients. Altogether, we created a prognostic classification model, the CAL model (C5a, Albumin, and Lymphocyte count) to predict severity with significant accuracy. Stratification of patients using the CAL model could help the identification of patients likely to develop severe symptoms in advance so that treatments can be targeted accordingly.
Nicholas D. Weber; Goni-Salaverri A; Jose A. Rodriguez; Unfried Jp; Daniel Alameda; Mirian Fernández-Alonso; Saez E; Maestro-Galilea S; Félix Alegre; Francisco Carmona-Torre; +8 more
Nicholas D. Weber; Goni-Salaverri A; Jose A. Rodriguez; Unfried Jp; Daniel Alameda; Mirian Fernández-Alonso; Saez E; Maestro-Galilea S; Félix Alegre; Francisco Carmona-Torre; Marta Marin-Oto; Cristina Olagüe; Odriozola L; Navarro-Alonso M; Sanchez-Ostiz R; Josepmaria Argemi; del Pozo Jl; David Lara-Astiaso;
AbstractBackgroundSpain is one of the countries most heavily affected by the COVID-19 pandemic. As in other countries such as UK and USA, nursing homes have been an important human reservoir for the virus and the population with the highest mortality worldwide. The presence of asymptomatic carriers within nursing homes is one of the factors that could provoke new outbreaks during the relaxing of lockdown measures.MethodsWe developed a high-throughput protocol for RNA extraction of patient samples based on silane magnetic beads in multi-well plates. The sensitivity, specificity and reproducibility rates were assessed using positive and negative clinical samples from the Clinica Universidad de Navarra, Spain. We utilized the protocol to test a pilot cohort of 138 residents and 87 staff from a nursing home in Northern Navarre, Spain.FindingsOur protocol showed high sensitivity (100%), specificity (96·0%) and linear correlation with PCR cycle threshold values obtained with a standard testing kit (R2 = 0·807, p=3E-05). Testing of 225 individuals from the nursing home revealed 63 residents (46%) and 14 staff (16%) positive for SARS-CoV-2. Only 18 of the positive residents (28·6%) were symptomatic at time of testing. During follow-up, 6 PCR-negative symptomatic residents were retested and resulted positive. One-month mortality among positive residents was higher than in negative residents (15·9% vs 1·3%), regardless of age or comorbidities.InterpretationRapid silane bead-based RNA extraction expanded the testing capabilities and COVID-19 patients were promptly identified. Personal and public health measures were enacted to avoid spreading and tighten clinical surveillance. The ability to easily adapt the technical capabilities of academic research centers to large-scale testing for SARS-CoV-2 could provide an invaluable tool for ensuring a safe lifting of lockdown in countries with high numbers of cases.FundingEuropean Molecular Biology Organization and Genomics Unit, Cima Universidad de Navarra.
AbstractBackgroundSeveral studies have reported that the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can directly infect endothelial cells, and endothelial dysfunction is often found in severe cases of coronavirus disease 2019 (COVID-19). To better understand the pathological mechanisms underlying endothelial dysfunction in COVID-19-associated coagulopathy, we conducted a systematic review and meta-analysis to assess biomarkers of endothelial cells in patients with COVID-19.MethodsA literature search was conducted on online databases for observational studies evaluating biomarkers of endothelial dysfunction and composite poor outcomes in COVID-19 patients.ResultsA total of 1187 patients from 17 studies were included in this analysis. The estimated pooled means for von Willebrand Factor (VWF) antigen levels in COVID-19 patients was higher compared to healthy control (306.42 [95% confidence interval (CI) 291.37-321.48], p<0.001; I2:86%), with the highest VWF antigen levels was found in deceased COVID-19 patients (448.57 [95% CI 407.20-489.93], p<0.001; I2:0%). Meta-analysis showed that higher plasma levels of VWF antigen, tissue-type plasminogen activator (t-PA), plasminogen activator inhibitor-1 antigen (PAI-1) antigen, and soluble thrombomodulin (sTM) were associated with composite poor outcome in COVID-19 patients ([standardized mean difference (SMD) 0.74 [0.33-1.16], p<0.001; I2:80.4%], [SMD 0.55 [0.19-0.92], p=0.003; I2:6.4%], [SMD 0.33 [0.04-0.62], p=0.025; I2:7.9%], and [SMD 0.55 [0.10-0.99], p=0.015; I2:23.6%], respectively).ConclusionThe estimated pooled means shows increased levels of VWF antigen in COVID-19 patients. Several biomarkers of endothelial dysfunction, including VFW antigen, t-PA, PAI-1, and sTM, are significantly associated with increased composite poor outcome in patients with COVID-19.PROSPERO registration numberCRD42021228821
In this study a computer-aided approach to de novo design of chemical entities with drug-like properties against the SARS-CoV-2 Spike protein bound to ACE2 is presented. A structure-based de novo drug design tool LIGANN was used to produce complementary ligand shapes to the SARS-CoV-2 Spike protein (6M0J). The obtained ligand structures - potential drug candidates – were optimized and virtually screened. Hit ligands were considered all that showed initial binding energy scores ≤ -9.0 kcal.mol-1 for the protein. These compounds were tested for drug-likeness (Lipinski’s rule and BOILED Permeation Predictive Model). All satisfying the criteria were re-optimized (geometry & frequencies) at the HF-3c33 level of theory and virtually screened against 6M0J. Molecular dynamics (MD) simulations were used to assess the structural stability of selected 6M0J/novel compound complexes. Synthetic pathways for selected compounds from commercially available starting materials are proposed.
In this paper, we present a new approach based on dynamic factor models (DFMs) to perform nowcasts for the percentage annual variation of the Mexican Global Economic Activity Indicator (IGAE in Spanish). The procedure consists of the following steps: i) build a timely and correlated database by using economic and financial time series and real-time variables such as social mobility and significant topics extracted by Google Trends; ii) estimate the common factors using the two-step methodology of Doz et al. (2011); iii) use the common factors in univariate time-series models for test data; and iv) according to the best results obtained in the previous step, combine the statistically equal better nowcasts (Diebold-Mariano test) to generate the current nowcasts. We obtain timely and accurate nowcasts for the IGAE, including those for the current phase of drastic drops in the economy related to COVID-19 sanitary measures. Additionally, the approach allows us to disentangle the key variables in the DFM by estimating the confidence interval for both the factor loadings and the factor estimates. This approach can be used in official statistics to obtain preliminary estimates for IGAE up to 50 days before the official results. 29 pages, 8 figures, 1 table and 1 annex