Synergy study on charge transport dynamics in hybrid organic solar cell: photocurrent mapping and performance analysis under local spectrum

Charge transport dynamics in ZnO based inverted organic solar cell (IOSC) has been characterized with transient photocurrent spectroscopy and localised photocurrent mapping-atomic force microscopy. The value of maximum exciton generation rate was found to vary from 2.6 × 1027 m−3s−1 (Jsat = 79.7 A m−2) to 2.9 × 1027 m−3s−1 (Jsat = 90.8 A m−2) for devices with power conversion efficiency ranging from 2.03 to 2.51%. These results suggest that nanorods served as an excellent electron transporting layer that provides efficient charge transport and enhances IOSC device performance. The photovoltaic performance of OSCs with various growth times of ZnO nanorods have been analysed for a comparison between AM1.5G spectrum and local solar spectrum. The simulated PCE of all devices operating under local spectrum exhibited extensive improvement with the gain of 13.3–13.7% in which the ZnO nanorods grown at 15 min possess the highest PCE under local solar with the value of 2.82%

Silver nanowires as flexible transparent electrode: role of PVP chain length

In this project, crystalline silver nanowires (AgNWs) are successfully grown using a continuous segmented flow process. The robust relationship among the structural, electrical and optical properties of the AgNWs in the function of the polyvinylpyrrolidone (PVP) chain length is elaborated. A concise carrier transport and a density mechanism are also discussed using a localized conductive atomic force microscopy analysis. The obtained results proved that the AgNWs synthesized using PVP with a chain length of 1.3 M exhibit excellent electrical and optical properties in the form of flexible transparent film with a sheet resistance of 90% at various bending angles. These findings present an alternative approach for production of AgNWs and fabrication of a high flexible transparent electrode

<i>Neisseria</i> species as pathobionts in bronchiectasis

Neisseria species are frequently identified in the bronchiectasis microbiome, but they are regarded as respiratory commensals. Using a combination of human cohorts, next-generation sequencing, systems biology, and animal models, we show that bronchiectasis bacteriomes defined by the presence of Neisseria spp. associate with poor clinical outcomes, including exacerbations. Neisseria subflava cultivated from bronchiectasis patients promotes the loss of epithelial integrity and inflammation in primary epithelial cells. In vivo animal models of Neisseria subflava infection and metabolipidome analysis highlight immunoinflammatory functional gene clusters and provide evidence for pulmonary inflammation. The murine metabolipidomic data were validated with human Neisseria-dominant bronchiectasis samples and compared with disease in which Pseudomonas-, an established bronchiectasis pathogen, is dominant. Metagenomic surveillance of Neisseria across various respiratory disorders reveals broader importance, and the assessment of the home environment in bronchiectasis implies potential environmental sources of exposure. Thus, we identify Neisseria species as pathobionts in bronchiectasis, allowing for improved risk stratification in this high-risk group.Published versio

Myosin Light-Chain Kinase Is Necessary for Membrane Homeostasis in Cochlear Inner Hair Cells

The structural homeostasis of the cochlear hair cell membrane is critical for all aspects of sensory transduction, but the regulation of its maintenance is not well understood. In this report, we analyzed the cochlear hair cells of mice with specific deletion of myosin light chain kinase (MLCK) in inner hair cells. MLCK-deficient mice showed impaired hearing, with a 5- to 14-dB rise in the auditory brainstem response (ABR) thresholds to clicks and tones of different frequencies and a significant decrease in the amplitude of the ABR waves. The mutant inner hair cells produced several ball-like structures around the hair bundles in vivo, indicating impaired membrane stability. Inner hair cells isolated from the knockout mice consistently displayed less resistance to hypoosmotic solution and less membrane F-actin. Myosin light-chain phosphorylation was also reduced in the mutated inner hair cells. Our results suggest that MLCK is necessary for maintaining the membrane stability of inner hair cells

Prediction of overall survival for patients with metastatic castration-resistant prostate cancer : development of a prognostic model through a crowdsourced challenge with open clinical trial data

Background Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. Methods Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interest-namely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a fifth trial-ENTHUSE M1-in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone. Findings 50 independent methods were developed to predict overall survival and were evaluated through the DREAM challenge. The top performer was based on an ensemble of penalised Cox regression models (ePCR), which uniquely identified predictive interaction effects with immune biomarkers and markers of hepatic and renal function. Overall, ePCR outperformed all other methods (iAUC 0.791; Bayes factor >5) and surpassed the reference model (iAUC 0.743; Bayes factor >20). Both the ePCR model and reference models stratified patients in the ENTHUSE 33 trial into high-risk and low-risk groups with significantly different overall survival (ePCR: hazard ratio 3.32, 95% CI 2.39-4.62, p Interpretation Novel prognostic factors were delineated, and the assessment of 50 methods developed by independent international teams establishes a benchmark for development of methods in the future. The results of this effort show that data-sharing, when combined with a crowdsourced challenge, is a robust and powerful framework to develop new prognostic models in advanced prostate cancer.Peer reviewe

On the dynamics of the adenylate energy system: homeorhesis vs homeostasis.

Biochemical energy is the fundamental element that maintains both the adequate turnover of the biomolecular structures and the functional metabolic viability of unicellular organisms. The levels of ATP, ADP and AMP reflect roughly the energetic status of the cell, and a precise ratio relating them was proposed by Atkinson as the adenylate energy charge (AEC). Under growth-phase conditions, cells maintain the AEC within narrow physiological values, despite extremely large fluctuations in the adenine nucleotides concentration. Intensive experimental studies have shown that these AEC values are preserved in a wide variety of organisms, both eukaryotes and prokaryotes. Here, to understand some of the functional elements involved in the cellular energy status, we present a computational model conformed by some key essential parts of the adenylate energy system. Specifically, we have considered (I) the main synthesis process of ATP from ADP, (II) the main catalyzed phosphotransfer reaction for interconversion of ATP, ADP and AMP, (III) the enzymatic hydrolysis of ATP yielding ADP, and (IV) the enzymatic hydrolysis of ATP providing AMP. This leads to a dynamic metabolic model (with the form of a delayed differential system) in which the enzymatic rate equations and all the physiological kinetic parameters have been explicitly considered and experimentally tested in vitro. Our central hypothesis is that cells are characterized by changing energy dynamics (homeorhesis). The results show that the AEC presents stable transitions between steady states and periodic oscillations and, in agreement with experimental data these oscillations range within the narrow AEC window. Furthermore, the model shows sustained oscillations in the Gibbs free energy and in the total nucleotide pool. The present study provides a step forward towards the understanding of the fundamental principles and quantitative laws governing the adenylate energy system, which is a fundamental element for unveiling the dynamics of cellular life

Analyst information precision and small earnings surprises

This study proposes and tests an alternative to the extant earnings management explanation for zero and small positive earnings surprises (i.e., analyst forecast errors). We argue that analysts’ ability to strategically induce slight pessimism in earnings forecasts varies with the precision of their information. Accordingly, we predict that the probability that a firm reports a small positive instead of a small negative earnings surprise is negatively related to earnings forecast uncertainty, and we present evidence consistent with this prediction. Our findings have important implications for the earnings management interpretation of the asymmetry around zero in the frequency distribution of earnings surprises. We demonstrate how empirically controlling for earnings forecast uncertainty can materially change inferences in studies that employ the incidence of zero and small positive earnings surprises to categorize firms as suspected of managing earnings