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Background: Suppressing acid secretion is thought to reduce the risk of ulcers associated with regular use of nonsteroidal antiinflammatory drugs (NSAIDs), but the best means of accomplishing this is uncertain. Methods: We studied 541 patients who required continuous treatment with NSAIDs and who had ulcers or more than 10 erosions in either the stomach or duodenum. Patients were randomly assigned to double-blind treatment with omeprazole, 20 mg or 40 mg orally per day, or ranitidine, 150 mg orally twice a day, for four or eight weeks, depending on when treatment was successful (defined as the resolution of ulcer and the presence of fewer than five erosions in the stomach and fewer than five erosions in the duodenum, and not more than mild dyspepsia). We randomly assigned 432 patients in whom treatment was successful to maintenance treatment with either 20 mg of omeprazole per day or 150 mg of ranitidine twice a day for six months. Results: At eight weeks, treatment was successful in 80 percent (140 of 174) of the patients in the group given 20 mg of omeprazole per day, 79 percent (148 of 187) of those given 40 mg of omeprazole per day, and 63 percent (110 of 174) of those given ranitidine (P<0.001 for the comparison with 20 mg of omeprazole and P = 0.001 for the comparison with 40 mg of omeprazole). The rates of healing of all types of lesions were higher with omeprazole than with ranitidine. During maintenance therapy, the estimated proportion of patients in remission at the end of six months was 72 percent in the omeprazole group and 59 percent in the ranitidine group. The rates of adverse events were similar between groups during both phases. Both medications were well tolerated. Conclusions: In patients who use NSAIDs regularly, omeprazole healed and prevented ulcers more effectively than did ranitidine. (N Engl J Med 1998;338:719-26.) [ABSTRACT FROM AUTHOR]

Metal halide perovskite (MHP) photovoltaics may become a viable alternative to standard Si-based technologies, but the current lack of long-term stability precludes their commercial adoption. Exposure to standard operational stressors (light, temperature, bias, oxygen, and water) often instigate optical and electronic dynamics, calling for a systematic investigation into MHP photophysical processes and the development of quantitative models for their prediction. We resolve the moisture-driven light emission dynamics for both methylammonium lead tribromide and triiodide thin films as a function of relative humidity (rH). With the humidity and photoluminescence time series, we train recurrent neural networks and establish their ability to quantitatively predict the path of future light emission with 18% error over 4 h. Together, our in situ rH-PL measurements and machine learning forecasting models provide a framework for the rational design of future stable perovskite devices and, thus, a faster transition toward commercial applications.

Perovskite solar cells (PSC) are a favorable candidate for next-generation solar systems with efficiencies comparable to Si photovoltaics, but their long-term stability must be proven prior to commercialization. However, traditional trial-and-error approaches to PSC screening, development, and stability testing are slow and labor-intensive. In this Perspective, we present a survey of how machine learning (ML) and autonomous experimentation provide additional toolkits to gain physical understanding while accelerating practical device advancement. We propose a roadmap for applying ML to PSC research at all stages of design (compositional selection, perovskite material synthesis and testing, and full device evaluation). We also provide an overview of relevant concepts and baseline models that apply ML to diverse materials problems, demonstrating its broad relevance while highlighting promising research directions and associated challenges. Finally, we discuss our outlook for an integrated pipeline that encompasses all design stages and presents a path to commercialization.

Hybrid organic-inorganic perovskites containing Cs are a promising new material for light-absorbing and light-emitting optoelectronics. However, the impact of environmental conditions on their optical properties is not fully understood. Here, we elucidate and quantify the influence of distinct humidity levels on the charge carrier recombination in Cs x FA 1- x Pb(I y Br 1- y ) 3 perovskites. Using in situ environmental photoluminescence (PL), we temporally and spectrally resolve light emission within a loop of critical relative humidity (rH) levels. Our measurements show that exposure up to 35% rH increases the PL emission for all Cs (10-17%) and Br (17-38%) concentrations investigated here. Spectrally, samples with larger Br concentrations exhibit PL redshift at higher humidity levels, revealing water-driven halide segregation. The compositions considered present hysteresis in their PL intensity upon returning to a low-moisture environment due to partially reversible hydration of the perovskites. Our findings demonstrate that the Cs/Br ratio strongly influences both the spectral stability and extent of light emission hysteresis. We expect our method to become standard when testing the stability of emerging perovskites, including lead-free options, and to be combined with other parameters known for affecting material degradation, e.g., oxygen and temperature.

In this article, Professor John Howard shares with our readers his life experiences as a pancreatic surgeon-researcher and gives advice to junior pancreatologists starting a career in pancreatic research. Professor Howard made an outstanding contribution to the understanding of acute pacreatitis and he is a pioneer in the development of management approaches for pancreatic diseases., (Copyright 2009 S. Karger AG, Basel.)