Punicalagin and Catechins Contain Polyphenolic Substructures That Influence Cell Viability and Can Be Monitored by Radical Chemosensors Sensitive to Electron Transfer

Plant polyphenols may be free radical scavengers or generators, depending on their nature and concentration. This dual effect, mediated by electron transfer reactions, may contribute to their influence on cell viability. This study used two stable radicals (tris­(2,3,5,6-tetrachloro-4-nitrophenyl)­methyl (TNPTM) and tris­(2,4,6-trichloro-3,5-dinitrophenyl)­methyl (HNTTM)) sensitive only to electron transfer reduction reactions to monitor the redox properties of polyphenols (punicalagin and catechins) that contain phenolic hydroxyls with different reducing capacities. The use of the two radicals reveals that punicalagin’s substructures consisting of gallate esters linked together by carbon–carbon (C–C) bonds are more reactive than simple gallates and less reactive than the pyrogallol moiety of green tea catechins. The most reactive hydroxyls, detected by TNPTM, are present in the compounds that affect HT-29 cell viability the most. TNPTM reacts with C–C-linked gallates and pyrogallol and provides a convenient way to detect potentially beneficial polyphenols from natural sources

Additional file 1 of Specific-cytokine associations with outcomes in knee osteoarthritis subgroups: breaking down disease heterogeneity with phenotyping

Additional file 1

Additional file 1 of SARS-CoV-2 infection, vaccination, and antibody response trajectories in adults: a cohort study in Catalonia

Additional file 1: Table S1. Characteristics of participants with breakthrough infections, post-vaccination. Table S2. Allocation of vaccinated and non-vaccinated participants with evidence of infection according to the criterion of infection fulfilled. Table S3. Fold change (FC) (95% CI) in antibody levels within one year after infection estimated using two repeated samples among decayers. Estimates are based on linear mixed-effects models. Table S4. Spearman correlations for RBD antigen. All participants, n=1,076. Darker red=stronger association. Table S5. Cross tabulation between serostatus to RBD of Wuhan variant with the RBD of Alpha, Beta Gamma and Delta variants. Table S6. Characteristics of non-responders (seronagetive or with an undetermined status) to vaccination. Table S7. Association (fold change FC and 95% CI and p-values) between each determinant with log10 antibody leves in vaccinated people after adjusting each model for time since last vaccination and number of doses. Participants with any vaccination excluding Janssen (n=923). Table S8. P-values for comparisons related to Figs. 3 and 5 and Figure S6. Figure S1. Dates and density of positive viral detection tests, sampling in 2020 (1st serological assessment) and 2021 (2nd serological assessment) and receipt of 1st vaccine dose in the study population (n=1,076). Figure S2. Venn diagram illustrating overlap between sustainer groups of IgA or IgG antibodies against nucleoprotein and spike antigens, among all infected unvaccinated participants (n=64). Figure S3. Differences in IgG antibody responses against RBD between Wuhan, Alpha, Beta, Gamma and Delta variant among vaccinated people. All differences were statistically significant apart from Delta vs Wuhan (p=0.861) and Alpha vs Wuhan (p=0.051). Figure S4. Generalized additive models for associations of days since vaccination with antibody responses to the six isotype-antigen combinations in infected (red) and naïve (blue) participants after first or second dose in people vaccinated by Vaxzevria (a), Comirnaty (b) or Spikevax (c). Fitted lines after adjustment for participant’s age. Plus symbols (+) represent measured responses for a specific participant. Figure S5. Differences in antibody responses by infection and/or vaccination and number of doses in people vaccinated with Comirnaty (a), Spikevarx (b), Vaxzevria (c) of Janssen COVID-19 vaccine (d). Figure S6. Differences in IgM responses by infection and/or vaccination and number of doses. Table S8 presents corresponding p-values

COVID-19 Host Genetics Initiative. A first update on mapping the human genetic architecture of COVID-19

The COVID-19 pandemic continues to pose a major public health threat, especially in countries with low vaccination rates. To better understand the biological underpinnings of SARS-CoV-2 infection and COVID-19 severity, we formed the COVID-19 Host Genetics Initiative1. Here we present a genome-wide association study meta-analysis of up to 125,584 cases and over 2.5 million control individuals across 60 studies from 25 countries, adding 11 genome-wide significant loci compared with those previously identified2. Genes at new loci, including SFTPD, MUC5B and ACE2, reveal compelling insights regarding disease susceptibility and severity.</p