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No abstract

Background: Talus avascular necrosis (AVN) is a challenging entity to treat. Management options depend on disease severity and functional goals. Total talus replacement (TTR) is a treatment option that maintains joint range of motion. The literature on TTR is limited with variability in implant design and material. The purpose of this study was to evaluate outcomes following TTR with a custom 3D printed metal implant. Methods: Patients who underwent TTR were retrospectively reviewed over a 3-year period. Basic demographic data and comorbidities were collected. Medical records were reviewed to obtain postoperative and preoperative visual analog scale (VAS) scores, Foot and Ankle Outcome Scores (FAOSs), ankle range of motion, and postoperative complications. Statistical analysis was conducted to compare clinical and patient-reported outcomes pre- and postoperatively. Twenty-seven patients underwent TTR for talar AVN with a mean follow-up of 22.2 months. Results: Ankle range of motion remained unchanged postoperatively. VAS pain scores improved postoperatively from 7.1 to 3.9 ( P < .001). FAOSs improved postoperatively with regard to pain ( P < .001), symptoms ( P = .001), quality of life ( P < .001), and activities of daily living ( P < .001). There were 3 complications requiring reoperation in this cohort. Discussion: 3D printed TTRs represent a unique surgical option for patients with severe talar AVN. Patients in this cohort demonstrated significant improvements in pain scores and patient-reported outcomes. TTR allows for symptomatic improvement with the preservation of motion in individuals with talar collapse and AVN. Level of Evidence: Level IV, retrospective case series.

The block copolymer VIPER (virus-inspired polymer for endosomal release) has been reported to be a promising novel delivery system of DNA plasmids both in vitro and in vivo. VIPER is comprised of a polycation segment for condensation of nucleic acids as well as a pH-sensitive segment that exposes the membrane lytic peptide melittin in acidic environments to facilitate endosomal escape. The objective of this study was to investigate VIPER/siRNA polyplex characteristics, and compare their in vitro and in vivo performance with commercially available transfection reagents and a control version of VIPER lacking melittin. VIPER/siRNA polyplexes were formulated and characterized at various charge ratios and shown to be efficiently internalized in cultured cells. Target mRNA knockdown was confirmed by both flow cytometry and qRT-PCR and the kinetics of knockdown was monitored by live cell spinning disk microscopy, revealing knockdown starting by 4 hours post-delivery. Intratracheal instillation of VIPER particles formulated with sequence specific siRNA to the lung of mice resulted in a significantly more efficient knockdown of GAPDH compared to treatment with VIPER particles formulated with scrambled sequence siRNA. We also demonstrated using pH-sensitive labels that VIPER particles experience less acidic environments compared to control polyplexes. In summary, VIPER/siRNA polyplexes efficiently deliver siRNA in vivo resulting in robust gene silencing (>75% knockdown) within the lung.

ATAC-seq is widely used to measure chromatin accessibility and identify open chromatin regions (OCRs). OCRs usually indicate active regulatory elements in the genome and are directly associated with the gene regulatory network. The identification of differential accessibility regions (DARs) between different biological conditions is critical in determining the differential activity of regulatory elements. Differential analysis of ATAC-seq shares many similarities with differential expression analysis of RNAseq data. However, the distribution of ATAC-seq signal intensity is different from that of RNA-seq data, and higher sensitivity is required for DARs identification. Many different tools can be used to perform differential analysis of ATAC-seq data, but a comprehensive comparison and benchmarking of these methods is still lacking. Here, we used simulated datasets to systematically measure the sensitivity and specificity of six different methods. We further discussed the statistical and signal density cutoffs in the differential analysis of ATAC-seq by applying them to real data. Batch effects are very common in high-throughput sequencing experiments. We illustrated that batch-effect correction can dramatically improve sensitivity in the differential analysis of ATAC-seq data. Finally, we developed a user-friendly package, BeCorrect, to perform batch effect correction and visualization of corrected ATAC-seq signals in a genome browser. Gene regulation in the mammalian genome involves different types of regulatory elements, such as promoters, enhancers, and insulators. It was estimated that there are over two million regulatory elements in the human and mouse genomes 1,2 , and these regulatory elements recruit different epigenetic modifications to regulate the expression of genes in cell type-specific and developmental stage-specific manners 3-5. Active regulatory elements must remain in an accessible state to allow the binding of different transcription factors to activate or silence target genes. ATAC-seq (assay for transposase-accessible chromatin followed by sequencing) is a recently developed technique to measure genome-wide chromatin accessibility (or open chromatin) 6,7. Compared with other techniques, such as DNase-seq, Mnase-seq, and FAIRE-seq, ATAC-seq experiments are relatively easier to perform across different tissues and cell types. Furthermore, ATAC-seq experiments allow ultra-low input cell numbers, even down to the single-cell level 8. These advantages propelled ATAC-seq to be the most widely used technology to define open chromatin by many large genomics consortiums, including ENCODE 9 , TCGA 10 , PsychENCODE 11 , IHEC 12 , and TaRGET II 13. The peak-calling analysis used to identify open chromatin regions (OCRs) by using ATAC-seq is generally adapted from ChIP-seq data analysis. However, there are fundamental differences between ATAC-seq and ChIP-seq-most notably that ATAC-seq is performed without control or input samples. Nonetheless, peak callers, such as macs2 14 , can identify OCRs by evalua...