Effect of Interlaminar Epidural Steroid Injection in Acute and Subacute Pain Due to Lumbar Disk Herniation: A Randomized Comparison of 2 Different Protocols

In order to assess the efficacy of epidural steroid injections (ESI) in acute and subacute pain due to lumbar spine disk herniation, we conducted a randomized trial, comparing 2 different protocols. Fourty patients with radicular pain due to L4-L5 and L5-S1 disc herniation were assigned to receive either 3 consecutive ESI every 24 hours through a spinal catheter (group A) or 3 consecutive ESI every 10 days with an epidural needle (group B). All patients had improved Oswestry Disabilty Index (ODI) and the Visual Analog Scale (VAS) for pain scores at 1 month of follow-up compared to baseline, while no significant differences were observed between the 2 groups. The scores for group B were statistically significant lower at 2 months of follow-up compared to those of group A. The improvement in the scores of group B was continuous since the mean scores at 2 months of follow up were lower compared to the respective scores at 1 month. Protocol B (3 consecutive ESI every 10 days) was found more effective in the treatment of subacute pain compared to Protocol A (3 consecutive ESI every 24 hours) with statistically significant differences in the ODI and VAS scores at 2 months of follow-up

The Effect of Agronomic Factors on the Yield of Winter Wheat in Crop Rotation with Livestock Production

The aim of the study was to evaluate the influence not only of the year, but also of the three agronomic factors, namely pre-crops, soil tillage, and application of fungicides on the subsequent grain yield of winter wheat. The field trial was carried out at the Field Trial Station in Žabčice (South Moravia, Czech Republic), between 2014 and 2016, as part of a long-term field experiment focused on management of soil with livestock production. Winter wheat was grown after two pre-crops, namely alfalfa and silage maize. The soil was treated using three technologies, namely conventional tillage (CT) – ploughing to a depth of 0.24 m, minimum tillage (MT) – shallow loosening to a depth of 0.15 m, and no-tillage (NT) – direct sowing. In terms of fungicide treatment, two treatments were used and compared to a non-treatment variant. The obtained results suggest that the statistical significance was not found in the influence of the pre-crop. On the contrary, the influence of not only the year but also of the soil tillage technology and fungicide treatment was confirmed. Higher yields by 0.59 t/ha were achieved after shallow loosening and direct sowing as compared with after traditional ploughing and after application of fungicides. In addition, inconclusive influence of interaction between pre-crop and soil tillage as well as between soil tillage and fungicide treatment was also found

Genetic analyses of the electrocardiographic QT interval and its components identify additional loci and pathways

The QT interval is an electrocardiographic measure representing the sum of ventricular depolarization and repolarization, estimated by QRS duration and JT interval, respectively. QT interval abnormalities are associated with potentially fatal ventricular arrhythmia. Using genome-wide multi-ancestry analyses (>250,000 individuals) we identify 177, 156 and 121 independent loci for QT, JT and QRS, respectively, including a male-specific X-chromosome locus. Using gene-based rare-variant methods, we identify associations with Mendelian disease genes. Enrichments are observed in established pathways for QT and JT, and previously unreported genes indicated in insulin-receptor signalling and cardiac energy metabolism. In contrast for QRS, connective tissue components and processes for cell growth and extracellular matrix interactions are significantly enriched. We demonstrate polygenic risk score associations with atrial fibrillation, conduction disease and sudden cardiac death. Prioritization of druggable genes highlight potential therapeutic targets for arrhythmia. Together, these results substantially advance our understanding of the genetic architecture of ventricular depolarization and repolarization

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease