Systematic Analysis of Clinical Outcomes Following Stereotactic Radiosurgery for Central Neurocytoma.

Central neurocytoma (CN) typically presents as an intraventricular mass causing obstructive hydrocephalus. The first line of treatment is surgical resection with adjuvant conventional radiotherapy. Stereotactic radiosurgery (SRS) was proposed as an alternative therapy for CN because of its lower risk profile. The objective of this systematic analysis is to assess the efficacy of SRS for CN. A systematic analysis for CN treated with SRS was conducted in PubMed. Baseline patient characteristics and outcomes data were extracted. Heterogeneity and publication bias were also assessed. Univariate and multivariate linear regressions were used to test for correlations to the primary outcome: local control (LC). The estimated cumulative rate of LC was 92.2% (95% confidence interval: 86.5-95.7%, p<0.001). Mean follow-up time was 62.4 months (range 3-149 months). Heterogeneity and publication bias were insignificant. The univariate linear regression models for both mean tumor volume and mean dose were significantly correlated with improved LC (p<0.001). Our data suggests that SRS may be an effective and safe therapy for CN. However, the rarity of CN still limits the efficacy of a quantitative analysis. Future multi-institutional, randomized trials of CN patients should be considered to further elucidate this therapy

Using machine learning to predict the complete degradation of accelerated damp heat testing in just 10% of the time

The ability to accurately predict the long-term performance of photovoltaic modules would have substantial benefits for the photovoltaic market. If we can precisely determine how new modules will perform after 25–30 years in the field, the reliability and bankability of photovoltaic systems will significantly increase. Keeping this target in mind, this study presents the first step towards achieving more cost-effective degradation monitoring. We develop machine learning models to predict the performance of photovoltaic modules at the end of 1,000 hours of damp heat tests after modules have only spent less than 10% of that time in damp heat conditions. Hence, we investigate the ability of unsupervised neural ordinary differential networks to model the entire dynamics of the degradation during a damp heat test using only the data that is collected in the first 10% of the process. The developed algorithms can significantly reduce the required time for damp heat tests and pave the way to transform the photovoltaic market

Tc-99m pyrophosphate imaging of poloxamer-treated electroporated skeletal muscle in an in vivo rat model

Objective: This study investigates whether 99mTc pyrophosphate (PYP) imaging provides a quantitative non-invasive assessment of the extent of electroporation injury, and of the effect of poloxamer in vivo on electroporated skeletal muscle. Methods: High-voltage electrical shock was used to produce electroporation injury in an anesthetized rat\u27s hind limb. In each experiment, the injured limb was treated intravenously by either poloxamer-188, dextran, or saline, and subsequently imaged with 99mTc PYP. The radiotracer\u27s temporal behavior among the experimental groups was compared using curve fitting of time-activity curves from the dynamic image data. Results: The washout kinetics of 99mTc PYP changed in proportion to the electric current magnitude that produced electroporation. Also, 99mTc PYP washout from electroporated muscle differed between poloxamer-188 treatment and saline treatment. Finally, 10-kDa dextran treatment of electroporated muscle altered 99mTc PYP washout less than poloxamer-188 treatment. Conclusions: Behavior of 99mTc PYP in electroporated muscle appears to be an indicator of the amount of electroporation injury. Compared to saline, intravenous polaxamer-188 treatment reduced the amount of 99mTc PYP uptake. Coupled to results showing poloxamer-188 seals ruptured cellular membranes, lessens the extent of electroporation injury and improves cell viability, 99mTc PYP imaging appears to be a useful in vivo monitoring tool for the extent of electroporation injury. © 2006 Elsevier Ltd and ISBI

Decoupling Bimolecular Recombination Mechanisms in Perovskite Thin Films Using Photoluminescence Quantum Yield

We present a novel analytical model for analysing the spectral photoluminescence quantum yield of non-planar semiconductor thin films. This model considers the escape probability of luminescence and is applied to triple-cation perovskite thin films with a 1-Sun photoluminescence quantum yield approaching 25%. By using our model, we can decouple the internal radiative, external radiative, and non-radiative bi-molecular recombination coefficients. Unlike other techniques that measure these coefficients separately, our proposed method circumvents experimental uncertainties by avoiding the need for multiple photoluminescence measurement techniques. We validate our model by comparing the extracted implied open-circuit voltage, effective luminescence escape probabilities, absorptivity, and absorption coefficient with values obtained using established methods and found that our results are consistent with previous findings. Next, we compare the implied 1-Sun radiative open-circuit voltage and radiative recombination current obtained from our method with literature values. We then convert the implied open-circuit voltage and implied radiative open-circuit voltage to the injection-dependent apparent-effective and apparent-radiative carrier lifetimes, which allow us to decouple the different recombination coefficients. Using this lifetime analysis, we predict the efficiency losses due to each recombination mechanism. Our proposed analytical model provides a reliable method for analysing the spectral photoluminescence quantum yield of semiconductor thin films, which will facilitate further research into the photovoltaic properties of these materials