Brodersenhumphrey5116

Determine the effectiveness of intraosseous basivertebral nerve radiofrequency neurotomy for the treatment of chronic low back pain with type 1 or 2 Modic changes.

Systematic review.

Persons aged ≥18 years with chronic low back pain with type 1 or 2 Modic changes.

Intraosseous basivertebral nerve radiofrequency neurotomy.

Sham, placebo procedure, active standard care treatment, or none.

The primary outcome of interest was the proportion of individuals with ≥50% pain reduction. Secondary outcomes included ≥10-point improvement in function as measured by Oswestry Disability Index as well as ≥2-point reduction in pain score on the Visual Analog Scale or Numeric Rating Scale, and decreased use of pain medication.

Three reviewers independently assessed publications before May 15, 2020, in MEDLINE and Embase and the quality of evidence was evaluated using the Grades of Recommendation, Assessment, Development, and Evaluation framework.

Of the 725 publications screened, seven publications with 321 par of the procedure appears to be dependent on effective targeting of the BVN. Non-industry funded high-quality, large prospective studies are needed to confirm these findings.

There is moderate-quality evidence that suggests this procedure is effective in reducing pain and disability in patients with chronic low back pain who are selected based on type 1 or 2 Modic changes, among other inclusion and exclusion criteria used in the published literature to date. Success of the procedure appears to be dependent on effective targeting of the BVN. Non-industry funded high-quality, large prospective studies are needed to confirm these findings.

Aedes aegypti is a highly competent vector in the transmission of arboviruses, such as chikungunya, dengue, Zika and yellow fever, and causes single and coinfections in the populations of tropical countries.

The infection rate, viral abundance, vector competence, disseminated infection and survival rate were recorded after single and multiple infections of the vector with 15 combinations of chikungunya, dengue, Zika and yellow fever arboviruses.

Infection rates were 100% in all single and multiple infection experiments, except in one triple coinfection that presented a rate of 50%. The vector competence and disseminated infection rate varied from 100% (in single and quadruple infections) to 40% (in dual and triple infections). The dual and triple coinfections altered the vector competence and/or viral abundance of at least one of the arboviruses. The highest viral abundances were detected for a single infection with chikungunya. The viral abundances in quadruple infections were similar when compared to each respective single infection. A decrease in survival rates was observed in a few combinations.

Ae. aegypti was able to host all single and multiple arboviral coinfections. The interference of the chikungunya virus suggests that distinct arbovirus families may have a significant role in complex coinfections.

Ae. aegypti was able to host all single and multiple arboviral coinfections. The interference of the chikungunya virus suggests that distinct arbovirus families may have a significant role in complex coinfections.We recently showed that site-specific incorporation of 2'-modifications or neutral linkages in the oligo-deoxynucleotide gap region of toxic phosphorothioate (PS) gapmer ASOs can enhance therapeutic index and safety. In this manuscript, we determined if introducing substitution at the 5'-position of deoxynucleotide monomers in the gap can also enhance therapeutic index. Introducing R- or S-configured 5'-Me DNA at positions 3 and 4 in the oligodeoxynucleotide gap enhanced the therapeutic profile of the modified ASOs suggesting a different positional preference as compared to the 2'-OMe gap modification strategy. The generality of these observations was demonstrated by evaluating R-5'-Me and R-5'-Ethyl DNA modifications in multiple ASOs targeting HDAC2, FXI and Dynamin2 mRNA in the liver. The current work adds to a growing body of evidence that small structural changes can modulate the therapeutic properties of PS ASOs and ushers a new era of chemical optimization with a focus on enhancing the therapeutic profile as opposed to nuclease stability, RNA-affinity and pharmacokinetic properties. The 5'-methyl DNA modified ASOs exhibited excellent safety and antisense activity in mice highlighting the therapeutic potential of this class of nucleic acid analogs for next generation ASO designs.

Drug-drug interactions (DDIs) can result in adverse and potentially life-threatening health consequences; however, it is challenging to predict potential DDIs in advance. IBRD9 We introduce a new computational approach to comprehensively assess the drug pairs which may be involved in specific DDI types by combining information from large-scale gene expression (984 transcriptomic datasets), molecular structure (2159 drugs), and medical claims (150 million patients).

Features were integrated using ensemble machine learning techniques, and we evaluated the DDIs predicted with a large hospital-based medical records dataset. Our pipeline integrates information from >30 different resources, including >10000 drugs and >1.7 million drug-gene pairs. We applied our technique to predict interactions between 37611 drug pairs used to treat psoriasis and its comorbidities.

Our approach achieves >0.9 area under the receiver operator curve (AUROC) for differentiating 11861 known DDIs from 25750 non-DDI drug pairs. Significantly, we demonstrate that the novel DDIs we predict can be confirmed through independent data sources and supported using clinical medical records.

By applying machine learning and taking advantage of molecular, genomic, and health record data, we are able to accurately predict potential new DDIs that can have an impact on public health.

By applying machine learning and taking advantage of molecular, genomic, and health record data, we are able to accurately predict potential new DDIs that can have an impact on public health.Spatially resolved gene expression profiles are key to understand tissue organization and function. However, spatial transcriptomics (ST) profiling techniques lack single-cell resolution and require a combination with single-cell RNA sequencing (scRNA-seq) information to deconvolute the spatially indexed datasets. Leveraging the strengths of both data types, we developed SPOTlight, a computational tool that enables the integration of ST with scRNA-seq data to infer the location of cell types and states within a complex tissue. SPOTlight is centered around a seeded non-negative matrix factorization (NMF) regression, initialized using cell-type marker genes and non-negative least squares (NNLS) to subsequently deconvolute ST capture locations (spots). Simulating varying reference quantities and qualities, we confirmed high prediction accuracy also with shallowly sequenced or small-sized scRNA-seq reference datasets. SPOTlight deconvolution of the mouse brain correctly mapped subtle neuronal cell states of the cortical layers and the defined architecture of the hippocampus.