A prominent β-hairpin structure in the winged-helix domain of RECQ1 is required for DNA unwinding and oligomer formation

RecQ helicases have attracted considerable interest in recent years due to their role in the suppression of genome instability and human diseases. These atypical helicases exert their function by resolving a number of highly specific DNA structures. The crystal structure of a truncated catalytic core of the human RECQ1 helicase (RECQ149–616) shows a prominent β-hairpin, with an aromatic residue (Y564) at the tip, located in the C-terminal winged-helix domain. Here, we show that the β-hairpin is required for the DNA unwinding and Holliday junction (HJ) resolution activity of full-length RECQ1, confirming that it represents an important determinant for the distinct substrate specificity of the five human RecQ helicases. In addition, we found that the β-hairpin is required for dimer formation in RECQ149–616 and tetramer formation in full-length RECQ1. We confirmed the presence of stable RECQ149–616 dimers in solution and demonstrated that dimer formation favours DNA unwinding; even though RECQ1 monomers are still active. Tetramers are instead necessary for more specialized activities such as HJ resolution and strand annealing. Interestingly, two independent protein–protein contacts are required for tetramer formation, one involves the β-hairpin and the other the N-terminus of RECQ1, suggesting a non-hierarchical mechanism of tetramer assembly

Protective Policy Index (PPI) global dataset of origins and stringency of COVID 19 mitigation policies

This the final version. Available on open access from Nature Research via the DOI in this recordData Records: We have created a Github repository (https://github.com/COVID-policy-response-lab/PPI-data) to store the datasets with the Public Health Protective Policy Index and its components. A copy of the included datafiles, as described below, was deposited with openICPSR15. It presently requires creating an account with the depository. Data access is free. Data location is at https://www.openicpsr.org/openicpsr/project/123401. The datasets are stored as csv files with five types of layouts. “PPI_country_m1.csv” is a file with country-level aggregates of region-level PPIs, computed using method 1, and their components. Each row corresponds to a country-date. The rows are identified using the country name (cname), numeric and 2-letter ISO 3166-1 codes (isocode and isoabbr respectively), as well as a date variable. The names of the policy variables contain four components: the name of the broader category, the name of the category, the level of issuing government (“nat” refers to the national policies, “reg” refers to the subnational policies, and “tot” refers to the combination of national and subnational policies), as well as suffix “ave”. For example, the average Total PPI is denoted as “ppi.all.tot.ave”, and the average stringency of the closures of air borders by the national government is denoted as “borders.air_bord.nat.ave”. See the codebook for the complete list of variables. “PPI_country_m2.csv” is a file with country-level aggregates of region-level PPIs, computed using method 2, and their components. The identifying variables and the naming convention for the policy variables is the same as in “PPI_country_m1.csv”, with the addition of suffix “0.2” at the end of the policy variable names. “PPI_regions_XX_m1.csv” (replace XX with the 2-letter ISO 3166-1 country codes) are country-specific files with region-specific PPIs, computed using method 1, and their components. The identifying variables include the numeric and 2-letter ISO 3166-1 codes of the country (isocode and isoabbr respectively), the name of the region (state_province), its ISO 3166-2 code (iso_state), as well as a date variable. The names of the policy variables contain three components: the name of the broader category, the name of the category, and the level of issuing government (“nat” refers to the national policies, “reg” refers to the subnational policies, and “tot” refers to the combination of national and subnational policies). For example, the average Total PPI is denoted as “ppi.all.tot”, and the stringency of the closures of air borders by the national government is denoted as “borders.air_bord.nat”. “PPI_regions_XX_m2.csv” (replace XX with the 2-letter ISO 3166-1 country codes are country-specific files with region-specific PPIs, computed using method 2, and their components. The identifying variables and the naming convention for the policy variables is the same as in “PPI_regions_XX_m1.csv”, with the addition of the suffix “0.2” at the end of the policy variable names. “changes_regions_m1.csv” is an auxiliary file that describes the changes in the policy states, as recorded in the “PPI_regions_XX_m1.csv” files. Each row in this file corresponds to a change in a value of a policy state variable in a region and of a specific government level. The case identifying variables include the name of the country (cname), the numeric and 2-letter ISO 3166-1 code of the country (isocode and isoabbr, respectively), the name of the region (state_province) and its ISO 3166-2 code, date, policy dimension, and a marker of policies issued by a regional government (subnational). Among others, the attributes included in this file include the branch of the government (branch) and the date when the change was announced (report_date).Code availability; The code used to produce our calculations is available at https://github.com/COVID-policy-response-lab/PPI-dataWe have developed and made accessible for multidisciplinary audience a unique global dataset of the behavior of political actors during the COVID-19 pandemic as measured by their policy-making efforts to protect their publics. The dataset presents consistently coded cross-national data at subnational and national levels on the daily level of stringency of public health policies by level of government overall and within specific policy categories, and reports branches of government that adopted these policies. The data on these public mandates of protective behaviors is collected from media announcements and government publications. The dataset allows comparisons of governments’ policy efforts and timing across the world and can serve as a source of information on policy determinants of pandemic outcomes–both societal and possibly medical

Detection of subclinical keratoconus using biometric parameters

The validation of innovative methodologies for diagnosing keratoconus in its earliest stages is of major interest in ophthalmology. So far, subclinical keratoconus diagnosis has been made by combining several clinical criteria that allowed the definition of indices and decision trees, which proved to be valuable diagnostic tools. However, further improvements need to be made in order to reduce the risk of ectasia in patients who undergo corneal refractive surgery. The purpose of this work is to report a new subclinical keratoconus detection method based in the analysis of certain biometric parameters extracted from a custom 3D corneal model. This retrospective study includes two groups: the first composed of 67 patients with healthy eyes and normal vision, and the second composed of 24 patients with subclinical keratoconus and normal vision as well. The proposed detection method generates a 3D custom corneal model using computer-aided graphic design (CAGD) tools and corneal surfaces’ data provided by a corneal tomographer. Defined bio-geometric parameters are then derived from the model, and statistically analysed to detect any minimal corneal deformation. The metric which showed the highest area under the receiver-operator curve (ROC) was the posterior apex deviation. This new method detected differences between healthy and sub-clinical keratoconus corneas by using abnormal corneal topography and normal spectacle corrected vision, enabling an integrated tool that facilitates an easier diagnosis and follow-up of keratoconus.This publication has been carried out in the framework of the Thematic Network for Co-Operative Research in Health (RETICS) reference number RD16/0008/0012 financed by the Carlos III Health Institute-General Subdirection of Networks and Cooperative Investigation Centers (R&D&I National Plan 2013–2016) and the European Regional Development Fund (FEDER)

Acetylation Regulates WRN Catalytic Activities and Affects Base Excision DNA Repair

Background: The Werner protein (WRN), defective in the premature aging disorder Werner syndrome, participates in a number of DNA metabolic processes, and we have been interested in the possible regulation of its function in DNA repair by post-translational modifications. Acetylation mediated by histone acetyltransferases is of key interest because of its potential importance in aging, DNA repair and transcription. Methodology/Principal Findings: Here, we have investigated the p300 acetylation mediated changes on the function of WRN in base excision DNA repair (BER). We show that acetylation of WRN increases in cells treated with methyl methanesulfonate (MMS), suggesting that acetylation of WRN may play a role in response to DNA damage. This hypothesis is consistent with our findings that acetylation of WRN stimulates its catalytic activities in vitro and in vivo, and that acetylated WRN enhances pol b-mediated strand displacement DNA synthesis more than unacetylated WRN. Furthermore, we show that cellular exposure to the histone deacetylase inhibitor sodium butyrate stimulates long patch BER in wild type cells but not in WRN depleted cells, suggesting that acetylated WRN participates significantly in this process. Conclusion/Significance: Collectively, these results provide the first evidence for a specific role of p300 mediated WRN acetylation in regulating its function during BER

Effect of Fibrin Glue on the Biomechanical Properties of Human Descemet's Membrane

10.1371/journal.pone.0037456PLoS ONE75