XANES Study of Structural Disorder in Amorphous Silicon

An investigation of the structure of several amorphous silicon (a-Si) films is presented. Samples were prepared by using the ion beam sputtering technique at different substrate deposition temperatures. X-ray absorption spectroscopy and multiple scattering formalism have been used to detect structural variations of the a-Si films. The analysis of the XANES (X-ray absorption near-edge structure) spectra shows that increasing the substrate deposition temperature leads to a structural change toward a higher-level short-range order.

Magneto-transport in periodic and quasiperiodic arrays of mesoscopic rings

We study theoretically the transmission properties of serially connected mesoscopic rings threaded by a magnetic flux. Within a tight-binding formalism we derive exact analytical results for the transmission through periodic and quasiperiodic Fibonacci arrays of rings of two different sizes. The role played by the number of scatterers in each arm of the ring is analyzed in some detail. The behavior of the transmission coefficient at a particular value of the energy of the incident electron is studied as a function of the magnetic flux (and vice versa) for both the periodic and quasiperiodic arrays of rings having different number of atoms in the arms. We find interesting resonance properties at specific values of the flux, as well as a power-law decay in the transmission coefficient as the number of rings increases, when the magnetic field is switched off. For the quasiperiodic Fibonacci sequence we discuss various features of the transmission characteristics as functions of energy and flux, including one special case where, at a special value of the energy and in the absence of any magnetic field, the transmittivity changes periodically as a function of the system size.Comment: 9 pages with 7 .eps figures included, submitted to PR

The EORTC-DeCOG nomogram adequately predicts outcomes of patients with sentinel node–positive melanoma without the need for completion lymph node dissection

Purpose: Based on recent advances in the management of patients with sentinel node (SN)–positive melanoma, we aimed to develop prediction models for recurrence, distant metastasis (DM) and overall mortality (OM). Methods: The derivation cohort consisted of 1080 patients with SN-positive melanoma from nine European Organization for Research and Treatment of Cancer (EORTC) centres. Prognostic factors for recurrence, DM and OM were studied with Cox regression analysis. Significant factors were incorporated in the models. Performance was assessed by discrimination (c-index) and calibration in cross-validation across centres. The models were externally validated using a prospective cohort consisting of 705 German patients with SN-positive: 473 trial participants of the German Dermatologic Cooperative Oncology Group study (DeCOG-SLT) and 232 screened patients. A nomogram was developed for graphical presentation. Results: The final model for recurrence and the calibrated models for DM and OM included ulceration, age, SN tumour burden and Breslow thickness. The models showed reasonable calibration. The c-index for the recurrence, DM and OM model was 0.68, 0.70 and 0.70, respectively, and 0.70, 0.72 and 0.74, respectively, in external validation. The EORTC-DeCOG model identified a robust low-risk group, with all identified low-risk patients (approximately 4% of the entire population) having a 5-year recurrence probability of <25% and an overall 5-year recurrence rate of 13%. A model including information on completion lymph node dissection (CLND) showed only marginal improvement in model performance. Conclusions: The EORTC-DeCOG nomogram provides an adequate prognostic tool for patients with SN-positive melanoma, without the need for CLND. It showed consistent results across validation. The nomogram could be used for patient counselling and might aid in adjuvant therapy decision-making

Long-term reliability of the phospholamban (PLN) p.(Arg14del) risk model in predicting major ventricular arrhythmia:a landmark study

Aims:Recently, a genetic variant-specific prediction model for phospholamban (PLN) p.(Arg14del)-positive individuals was developed to predict individual major ventricular arrhythmia (VA) risk to support decision-making for primary prevention implantable cardioverter defibrillator (ICD) implantation. This model predicts major VA risk from baseline data, but iterative evaluation of major VA risk may be warranted considering that the risk factors for major VA are progressive. Our aim is to evaluate the diagnostic performance of the PLN p.(Arg14del) risk model at 3-year follow-up. Methods:We performed a landmark analysis 3 years after presentation and selected only patients with no prior major VA. Data were and results collected of 268 PLN p.(Arg14del)-positive subjects, aged 43.5 ± 16.3 years, 38.9% male. After the 3 years landmark, subjects had a mean follow-up of 4.0 years (± 3.5 years) and 28 (10%) subjects experienced major VA with an annual event rate of 2.6% [95% confidence interval (CI) 1.6–3.6], defined as sustained VA, appropriate ICD intervention, or (aborted) sudden cardiac death. The PLN p.(Arg14del) risk score yielded good discrimination in the 3 years landmark cohort with a C-statistic of 0.83 (95% CI 0.79–0.87) and calibration slope of 0.97. Conclusion:The PLN p.(Arg14del) risk model has sustained good model performance up to 3 years follow-up in PLN p.(Arg14del)positive subjects with no history of major VA. It may therefore be used to support decision-making for primary prevention ICD implantation not merely at presentation but also up to at least 3 years of follow-up.</p

Long-term reliability of the phospholamban (PLN) p.(Arg14del) risk model in predicting major ventricular arrhythmia:a landmark study

Aims:Recently, a genetic variant-specific prediction model for phospholamban (PLN) p.(Arg14del)-positive individuals was developed to predict individual major ventricular arrhythmia (VA) risk to support decision-making for primary prevention implantable cardioverter defibrillator (ICD) implantation. This model predicts major VA risk from baseline data, but iterative evaluation of major VA risk may be warranted considering that the risk factors for major VA are progressive. Our aim is to evaluate the diagnostic performance of the PLN p.(Arg14del) risk model at 3-year follow-up. Methods:We performed a landmark analysis 3 years after presentation and selected only patients with no prior major VA. Data were and results collected of 268 PLN p.(Arg14del)-positive subjects, aged 43.5 ± 16.3 years, 38.9% male. After the 3 years landmark, subjects had a mean follow-up of 4.0 years (± 3.5 years) and 28 (10%) subjects experienced major VA with an annual event rate of 2.6% [95% confidence interval (CI) 1.6–3.6], defined as sustained VA, appropriate ICD intervention, or (aborted) sudden cardiac death. The PLN p.(Arg14del) risk score yielded good discrimination in the 3 years landmark cohort with a C-statistic of 0.83 (95% CI 0.79–0.87) and calibration slope of 0.97. Conclusion:The PLN p.(Arg14del) risk model has sustained good model performance up to 3 years follow-up in PLN p.(Arg14del)positive subjects with no history of major VA. It may therefore be used to support decision-making for primary prevention ICD implantation not merely at presentation but also up to at least 3 years of follow-up.</p

ECG-only explainable deep learning algorithm predicts the risk for malignant ventricular arrhythmia in phospholamban cardiomyopathy

Background: Phospholamban (PLN) p.(Arg14del) variant carriers are at risk for development of malignant ventricular arrhythmia (MVA). Accurate risk stratification allows timely implantation of intracardiac defibrillators and is currently performed with a multimodality prediction model. Objective: This study aimed to investigate whether an explainable deep learning–based approach allows risk prediction with only electrocardiogram (ECG) data. Methods: A total of 679 PLN p.(Arg14del) carriers without MVA at baseline were identified. A deep learning–based variational auto-encoder, trained on 1.1 million ECGs, was used to convert the 12-lead baseline ECG into its FactorECG, a compressed version of the ECG that summarizes it into 32 explainable factors. Prediction models were developed by Cox regression. Results: The deep learning–based ECG-only approach was able to predict MVA with a C statistic of 0.79 (95% CI, 0.76–0.83), comparable to the current prediction model (C statistic, 0.83 [95% CI, 0.79–0.88]; P = .054) and outperforming a model based on conventional ECG parameters (low-voltage ECG and negative T waves; C statistic, 0.65 [95% CI, 0.58–0.73]; P &lt; .001). Clinical simulations showed that a 2-step approach, with ECG-only screening followed by a full workup, resulted in 60% less additional diagnostics while outperforming the multimodal prediction model in all patients. A visualization tool was created to provide interactive visualizations (https://pln.ecgx.ai). Conclusion: Our deep learning–based algorithm based on ECG data only accurately predicts the occurrence of MVA in PLN p.(Arg14del) carriers, enabling more efficient stratification of patients who need additional diagnostic testing and follow-up.</p

A randomized controlled trial of eplerenone in asymptomatic phospholamban p.Arg14del carriers

Phospholamban (PLN; p.Arg14del) cardiomyopathy is an inherited disease caused by the pathogenic p.Arg14del variant in the PLN gene. Clinically, it is characterized by malignant ventricular arrhythmias and progressive heart failure.1,2 Cardiac fibrotic tissue remodelling occurs early on in PLN p.Arg14del carriers.3,4 Eplerenone was deemed a treatment candidate because of its beneficial effects on ventricular remodelling and antifibrotic properties.5,6 We conducted the multicentre randomized trial ‘intervention in PHOspholamban RElated CArdiomyopathy STudy’ (i-PHORECAST) to assess whether treatment with eplerenone of asymptomatic PLN p.Arg14del carriers attenuates disease onset and progression

Agricultura orgânica em áreas urbanas e periurbanas com base na agroecologia.

A agricultura orgânica com base na agroecologia é o mote tecnológico adequado à realidade dos agroecossistemas urbanos. Este artigo ressalta a necessidade de se desenvolver tecnologias e insumos específicos. A partir de experiências com agricultura urbana em diferentes países em desenvolvimento, evidencia-se a necessidade de se buscar capacidades locais e apoio do poder público, especialmente nas iniciativas da sociedade organizada e mobilizada para a produção agrícola urbana