Ultrasound-Guided Lateral Femoral Cutaneous Nerve Cryoneurolysis for Analgesia in Patients With Burns.

Autologous skin grafting from the thigh is frequently required for treatment of burns and is associated with intense pain at the donor site. Local anesthetic-based (LA) nerve blocks of the lateral femoral cutaneous nerve (LFCN) have been demonstrated to provide analgesia when the graft is taken from the lateral thigh. However, the duration of these single injection blocks has been reported to average only 9 hours, whereas the pain from the procedure lasts days or weeks. Continuous LA nerve blocks can also be used to provide analgesia during serial debridement of burns, although this requires placement of a perineural catheter which may increase infection risk in a population with an increased susceptibility to infection. Cryoneurolysis of the LFCN can potentially provide analgesia of the lateral thigh for skin graft harvesting or serial burn debridement that lasts far longer than conventional LA nerve blocks. Here, we present a series of three patients who received a combination of a LA nerve block and cryoneurolysis nerve block of the LFCN for analgesia of the lateral thigh. Two of these patients had the blocks placed before harvesting a split thickness skin graft. The third received the blocks for outpatient wound care of a burn to the lateral thigh. In all cases, the resulting analgesia lasted more than 1 week. A single cryoneurolysis block of the LFCN successfully provided extended duration analgesia of the lateral thigh for autologous skin graft donor site or wound care of a burn in three patients

Suture-method versus Through-the-needle Catheters for Continuous Popliteal-sciatic Nerve Blocks: A Randomized Clinical Trial.

BACKGROUND:The basic perineural catheter design has changed minimally since inception, with the catheter introduced through or over a straight needle. The U.S. Food and Drug Administration recently cleared a novel perineural catheter design comprising a catheter attached to the back of a suture-shaped needle that is inserted, advanced along the arc of its curvature pulling the catheter past the target nerve, and then exited through the skin in a second location. The authors hypothesized that analgesia would be noninferior using the new versus traditional catheter design in the first two days after painful foot/ankle surgery with a primary outcome of average pain measured with the Numeric Rating Scale. METHODS:Subjects undergoing painful foot or ankle surgery with a continuous supraparaneural popliteal-sciatic nerve block 5 cm proximal to the bifurcation were randomized to either a suture-type or through-the-needle catheter and subsequent 3-day 0.2% ropivacaine infusion (basal 6 ml/h, bolus 4 ml, lockout 30 min). Subjects received daily follow-up for the first four days after surgery, including assessment for evidence of malfunction or dislodgement of the catheters. RESULTS:During the first two postoperative days the mean ± SD average pain scores were lower in subjects with the suture-catheter (n = 35) compared with the through-the-needle (n = 35) group (2.7 ± 2.4 vs. 3.4 ± 2.4) and found to be statistically noninferior (95% CI, -1.9 to 0.6; P < 0.001). No suture-style catheter was completely dislodged (0%), whereas the tips of three (9%) traditional catheters were found outside of the skin before purposeful removal on postoperative day 3 (P = 0.239). CONCLUSIONS:Suture-type perineural catheters provided noninferior analgesia compared with traditional catheters for continuous popliteal-sciatic blocks after painful foot and ankle surgery. The new catheter design appears to be a viable alternative to traditional designs used for the past seven decades

A comparison of machine learning classifiers for pediatric epilepsy using resting-state functional MRI latency data

Epilepsy affects 1 in 150 children under the age of 10 and is the most common chronic pediatric neurological condition; poor seizure control can irreversibly disrupt normal brain development. The present study compared the ability of different machine learning algorithms trained with resting-state functional MRI (rfMRI) latency data to detect epilepsy. Preoperative rfMRI and anatomical MRI scans were obtained for 63 patients with epilepsy and 259 healthy controls. The normal distribution of latency z-scores from the epilepsy and healthy control cohorts were analyzed for overlap in 36 seed regions. In these seed regions, overlap between the study cohorts ranged from 0.44-0.58. Machine learning features were extracted from latency z-score maps using principal component analysis. Extreme Gradient Boosting (XGBoost), Support Vector Machines (SVM), and Random Forest algorithms were trained with these features. Area under the receiver operating characteristics curve (AUC), accuracy, sensitivity, specificity and F1-scores were used to evaluate model performance. The XGBoost model outperformed all other models with a test AUC of 0.79, accuracy of 74%, specificity of 73%, and a sensitivity of 77%. The Random Forest model performed comparably to XGBoost across multiple metrics, but it had a test sensitivity of 31%. The SVM model did not perform \u3e70% in any of the test metrics. The XGBoost model had the highest sensitivity and accuracy for the detection of epilepsy. Development of machine learning algorithms trained with rfMRI latency data could provide an adjunctive method for the diagnosis and evaluation of epilepsy with the goal of enabling timely and appropriate care for patients

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

High Prevalence of Respiratory Ciliary Dysfunction in Congenital Heart Disease Patients With Heterotaxy

Patients with congenital heart disease (CHD) and heterotaxy show high postsurgical morbidity/mortality, with some developing respiratory complications. Although this finding is often attributed to the CHD, airway clearance and left-right patterning both require motile cilia function. Thus, airway ciliary dysfunction (CD) similar to that of primary ciliary dyskinesia (PCD) may contribute to increased respiratory complications in heterotaxy patients

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Protein ubiquitination is a dynamic and reversibleprocess of adding single ubiquitin molecules orvarious ubiquitin chains to target proteins. Here,using multidimensional omic data of 9,125 tumorsamples across 33 cancer types from The CancerGenome Atlas, we perform comprehensive molecu-lar characterization of 929 ubiquitin-related genesand 95 deubiquitinase genes. Among them, we sys-tematically identify top somatic driver candidates,including mutatedFBXW7with cancer-type-specificpatterns and amplifiedMDM2showing a mutuallyexclusive pattern withBRAFmutations. Ubiquitinpathway genes tend to be upregulated in cancermediated by diverse mechanisms. By integratingpan-cancer multiomic data, we identify a group oftumor samples that exhibit worse prognosis. Thesesamples are consistently associated with the upre-gulation of cell-cycle and DNA repair pathways, char-acterized by mutatedTP53,MYC/TERTamplifica-tion, andAPC/PTENdeletion. Our analysishighlights the importance of the ubiquitin pathwayin cancer development and lays a foundation fordeveloping relevant therapeutic strategies