Stentian structural plasticity in the developing visual system.

In a small fraction of Xenopus tadpoles, a single retinal ganglion cell (RGC) axon misprojects to the ipsilateral optic tectum. Presenting flashes of light to the ipsilateral eye causes that ipsilateral axon to fire, whereas stimulating the contralateral eye excites all other RGC inputs to the tectum. We performed time-lapse imaging of individual ipsilaterally projecting axons while stimulating either the ipsilateral or contralateral eye. Stimulating either eye alone reduced axon elaboration by increasing branch loss. New branch additions in the ipsi axon were exclusively increased by contralateral eye stimulation, which was enhanced by expressing tetanus neurotoxin (TeNT) in the ipsilateral axon, to prevent Hebbian stabilization. Together, our results reveal the existence of a non-cell-autonomous "Stentian" signal, engaged by activation of neighboring RGCs, that promotes exploratory axon branching in response to noncorrelated firing.

16-year outcomes of blunt thoracic aortic injury treated with thoracic endovascular aortic repair: A single-institution experience.

BACKGROUND: Blunt thoracic aortic injury (BTAI) is associated with considerable mortality and morbidity. Thoracic endovascular aortic repair (TEVAR) has essentially replaced open aortic repair (OAR) with superior outcome. The objective of this study was to evaluate the early and intermediate-term outcomes in patients sustaining BTAI treated with TEVAR, and to evaluate the prevalence and impact of left subclavian artery (LSA) coverage. METHODS: This retrospective analysis includes patients undergoing TEVAR for BTAI between February 2006 and December 2022 at the Helsinki University Hospital, Finland. The primary endpoints were 30-day and 2-year mortality, technical success of stent-graft system deployment, and procedural and device-related complications. The secondary endpoints pertained to reintervention events: conversion to OAR, re-TEVAR, any endovascular/surgical reinterventions for optimal stent-graft function, or any reinterventions during follow-up. RESULTS: A total of 38 consecutive BTAI patients treated with TEVAR were included in the analyses. Median patient age was 45.5 years (range, 15-79) and 66% were male. The median follow-up period was 39 months. Technical success was 100%, 30-day mortality was 0%, and 2-year mortality was 11% in the study cohort. Coverage of LSA without revascularization (13/18) resulted in one postoperative nondisabling stroke (1/13), no paraplegia, and one had ischemic left arm findings (1/13). Only one patient required reintervention (LSA embolization; 1/38). CONCLUSION: In this institutional series, we provide further evidence in favor of TEVAR for BTAI treatment. We demonstrated that TEVAR is linked to highly favorable outcomes in the short and intermediate term, and coverage of LSA without revascularization was quite well tolerated.

Ultrasound-guided closure of the femoral artery during venoarterial decannulation using a large-bore closure device.

BACKGROUND: Peripheral femoro-femoral venoarterial extracorporeal membrane oxygenation (VA-ECMO) is viable for fast hemodynamic assistance during cardiogenic shock. Ultrasound-guided closure with a large-bore device (MANTA®) is a feasible option potentially replacing surgical arteriotomy closure in peripheral VA-ECMO decannulation. METHODS: This retrospective study included patients weaning from percutaneously inserted femoro-femoral VA-ECMO at the Helsinki University Hospital, Finland in 2012-2020. The primary endpoints were access-site complications, a composite of hematomas/seromas/surgical site infections (SSIs), and the safety endpoint of vascular complications (VCs). RESULTS: A total of 100 consecutive percutaneously implanted and weaned VA-ECMO patients were stratified into two groups by decannulation strategy: percutaneous ultrasound-guided MANTA device (n = 21, 21.0%) or surgical approach (n = 79, 79.0%). The mean age of the cohort was 51 ± 13 years and females represented 25.0%. The technical success rate of the percutaneous ultrasound-guided MANTA technique was 95.2%. In multivariate analysis, surgical closure was associated with a higher incidence of combined access site hematomas/seromas/SSIs compared to percutaneous ultrasound-guided deployment of MANTA device (44.3% versus 9.5%, odds ratio (OR): 7.162, 95% confidence interval (CI): 1.544-33.222; p = 0.012). Similarly, access-site complications necessitating interventions were more frequent in the surgical closure group compared to US-MANTA (ultrasound-guided MANTA) group (26.6% versus 0.0%, p = 0.005). VCs were infrequent in both groups without any significant intergroup difference (p > 0.99). CONCLUSIONS: Percutaneous ultrasound-guided MANTA closure of the femoral artery after VA-ECMO decannulation was associated with high technical success rate and low incidence of VCs. Compared to surgical closure, access-site complications were significantly less frequent, along with access-site complications necessitating interventions.

Early-Stage Detection of Ovarian Cancer Based on Clinical Data Using Machine Learning Approaches.

One of the common types of cancer for women is ovarian cancer. Still, at present, there are no drug therapies that can properly cure this deadly disease. However, early-stage detection could boost the life expectancy of the patients. The main aim of this work is to apply machine learning models along with statistical methods to the clinical data obtained from 349 patient individuals to conduct predictive analytics for early diagnosis. In statistical analysis, Student's t-test as well as log fold changes of two groups are used to find the significant blood biomarkers. Furthermore, a set of machine learning models including Random Forest (RF), Support Vector Machine (SVM), Decision Tree (DT), Extreme Gradient Boosting Machine (XGBoost), Logistic Regression (LR), Gradient Boosting Machine (GBM) and Light Gradient Boosting Machine (LGBM) are used to build classification models to stratify benign-vs.-malignant ovarian cancer patients. Both of the analysis techniques recognized that the serumsamples carbohydrate antigen 125, carbohydrate antigen 19-9, carcinoembryonic antigen and human epididymis protein 4 are the top-most significant biomarkers as well as neutrophil ratio, thrombocytocrit, hematocrit blood samples, alanine aminotransferase, calcium, indirect bilirubin, uric acid, natriumas as general chemistry tests. Moreover, the results from predictive analysis suggest that the machine learning models can classify malignant patients from benign patients with accuracy as good as 91%. Since generally, early-stage detection is not available, machine learning detection could play a significant role in cancer diagnosis.