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Background Machine learning is a broad term encompassing a number of methods that allow the investigator to learn from the data. These methods may permit large real-world databases to be more rapidly translated to applications to inform patient-provider decision making. Methods This systematic literature review was conducted to identify published observational research of employed machine learning to inform decision making at the patient-provider level. The search strategy was implemented and studies meeting eligibility criteria were evaluated by two independent reviewers. Relevant data related to study design, statistical methods and strengths and limitations were identified; study quality was assessed using a modified version of the Luo checklist. Results A total of 34 publications from January 2014 to September 2020 were identified and evaluated for this review. There were diverse methods, statistical packages and approaches used across identified studies. The most common methods included decision tree and random forest approaches. Most studies applied internal validation but only two conducted external validation. Most studies utilized one algorithm, and only eight studies applied multiple machine learning algorithms to the data. Seven items on the Luo checklist failed to be met by more than 50% of published studies. Conclusions A wide variety of approaches, algorithms, statistical software, and validation strategies were employed in the application of machine learning methods to inform patient-provider decision making. There is a need to ensure that multiple machine learning approaches are used, the model selection strategy is clearly defined, and both internal and external validation are necessary to be sure that decisions for patient care are being made with the highest quality evidence. Future work should routinely employ ensemble methods incorporating multiple machine learning algorithms.

Somatic cells can accumulate mutations over the course of an individual's lifetime. This generates cells that differ genetically at specific loci within the genome. To explore how this genetic diversity in individuals contributes to disease, Yizhak et al. developed a method to detect mutations from RNA sequencing data (see the Perspective by Tomasetti). Applying this method to Cancer Genome Atlas samples and normal samples from the Genotype-Tissue Expression (GTEx) project generated a tissue-specific study of mutation accumulation. Somatic mutations were detected in nearly all individuals and across many normal human tissues in genomic regions called cancer hotspots and in genes that play a role in cancer. Interestingly, the skin, lung, and esophagus exhibited the most mutations, suggesting that the environment generates many human mutations. Science , this issue p. eaaw0726 ; see also p. 938 “Normal” skin and other human tissues include macroscopic clonal expansions that contain genes associated with cancer risk. How somatic mutations accumulate in normal cells is poorly understood. A comprehensive analysis of RNA sequencing data from ~6700 samples across 29 normal tissues revealed multiple somatic variants, demonstrating that macroscopic clones can be found in many normal tissues. We found that sun-exposed skin, esophagus, and lung have a higher mutation burden than other tested tissues, which suggests that environmental factors can promote somatic mosaicism. Mutation burden was associated with both age and tissue-specific cell proliferation rate, highlighting that mutations accumulate over both time and number of cell divisions. Finally, normal tissues were found to harbor mutations in known cancer genes and hotspots. This study provides a broad view of macroscopic clonal expansion in human tissues, thus serving as a foundation for associating clonal expansion with environmental factors, aging, and risk of disease.

Fast radio bursts (FRBs) are extragalactic astrophysical transients 1 whose brightness requires emitters that are highly energetic yet compact enough to produce the short, millisecond-duration bursts. FRBs have thus far been detected at frequencies from 8 gigahertz (ref. 2 ) down to 300 megahertz (ref. 3 ), but lower-frequency emission has remained elusive. Some FRBs repeat 4 – 6 , and one of the most frequently detected, FRB 20180916B 7 , has a periodicity cycle of 16.35 days (ref. 8 ). Using simultaneous radio data spanning a wide range of wavelengths (a factor of more than 10), here we show that FRB 20180916B emits down to 120 megahertz, and that its activity window is frequency dependent (that is, chromatic). The window is both narrower and earlier at higher frequencies. Binary wind interaction models predict a wider window at higher frequencies, the opposite of our observations. Our full-cycle coverage shows that the 16.3-day periodicity is not aliased. We establish that low-frequency FRB emission can escape the local medium. For bursts of the same fluence, FRB 20180916B is more active below 200 megahertz than at 1.4 gigahertz. Combining our results with previous upper limits on the all-sky FRB rate at 150 megahertz, we find there are 3–450 FRBs in the sky per day above 50 Jy ms. Our chromatic results strongly disfavour scenarios in which absorption from strong stellar winds causes FRB periodicity. We demonstrate that some FRBs are found in ‘clean’ environments that do not absorb or scatter low-frequency radiation. The fast radio burst FRB 20180916B repeats with a periodicity of 16 days, and is now found to emit down to a frequency of 120 MHz, much lower than previously observed.

Mineral particles, in general, are not spheres and so the assumption of spherical particles, instead of more realistic shapes, has significant effects on modeled optical properties and therefore on remote-sensing procedures for desert aerosol and the derived radiative forcing. Thus, in a new version of the database OPAC (Optical Properties of Aerosols and Clouds; Hess et al., 1998), the optical properties of the mineral particles are modeled describing the particles as spheroids with size dependent aspect ratio distributions, but with the size distributions and the spectral refractive indices not changed against the previous version of OPAC. The spheroid assumption is known to substantially improve the scattering functions but pays regard to the limited knowledge on particle shapes in an actual case. The relative deviations of the optical properties of non-spherical mineral particles from those of spherical particles are for the phase function in the solar spectral range up to +60% at scattering angles of about 130° and up to −60% in the backscatter region, but less than 2% for the asymmetry parameter. The deviations are generally small in the thermal infrared and for optical properties that are independent of the scattering angle. The improved version of OPAC (4.0) is freely available at www.rascin.net.

Following the dynamic capabilities perspective, we suggest that antecedents to innovation can be found at the individual, firm, and network levels. Thus, we challenge two assumptions common in prior research: (1) that significant variance exists at the focal level of analysis, whereas other levels of analysis are assumed to be homogeneous, and (2) that the focal level of analysis is independent from other levels of analysis. Accordingly, we advance a set of hypotheses to simultaneously assess the direct effects of antecedents at the individual, firm, and network levels on innovation output. We then investigate whether a firm's antecedents to innovation lie across different levels. To accomplish this, we propose two competing interaction hypotheses. We juxtapose the hypothesis that the individual-, firm-, and network-level antecedents to innovation are substitutes versus the proposition that these innovation mechanisms are complements. We test our multilevel theoretical model using an unusually comprehensive and detailed panel data set that documents the innovation attempts of global pharmaceutical companies within biotechnology over a 22-year time period (1980-2001). We find evidence that the antecedents to innovation lie across different levels of analysis and can have compensating or reinforcing effects on firm-level innovative output.

Diversification of biocrystal arrangements, incorporation of biopolymers at many scale levels and hierarchical architectures are keys for biomaterial optimization. The planktonic rotaliid foraminifer Pulleniatina obliquiloculata displays in its shell a new kind of mesocrystal architecture. Shell formation starts with crystallization of a rhizopodial network, the primary organic sheet (POS). On one side of the POS, crystals consist of blocky domains of 1 μm. On the other side of the POS crystals have dendritic-fractal morphologies, interdigitate and reach sizes of tens of micrometers. The dendritic-fractal crystals are twinned. At the site of nucleation, twinned crystals consist of minute fibrils. With distance away from the nucleation-site, fibrils evolve to bundles of crystallographically well co-oriented nanofibrils and to, twinned, platy-blade-shaped crystals that seam outer shell surfaces. The morphological nanofibril axis is the crystallographic c-axis, both are perpendicular to shell vault. The nanofibrillar calcite is polysynthetically twinned according to the 60°/[100] (= m/{001}) twin law. We demonstrate for the twinned, fractal-dendritic, crystals formation at high supersaturation and growth through crystal competition. We show also that c-axis-alignment is already induced by biopolymers of the POS and is not simply a consequence of growth competition. We discuss determinants that lead to rotaliid calcite formation.

Understanding and conceptualizing the complexities of the contemporary global economy is a challenging but vitally important task. In this article, we critically evaluate the potential of one interpretive framework—the global production networks (GPN) perspective—for analysing the global economy and its impacts on territorial development. After situating the approach in relation to other cognate chain/network approaches, the article proceeds to review and evaluate a number of underdeveloped areas that need to be understood and incorporated more fully if the framework is to deliver on its early potential. The article concludes with a consideration of the key research issues facing work in this area.

Unlimited access to calorie-dense, palatable food is a hallmark of Western societies and substantially contributes to the worldwide rise of metabolic disorders. In addition to promoting overconsumption, palatable diets dampen daily intake patterns, further augmenting metabolic disruption. We developed a paradigm to reveal differential timing in the regulation of food intake behavior in mice. While homeostatic intake peaks in the active phase, conditioned place preference and choice experiments show an increased sensitivity to overeating on palatable food during the rest phase. This hedonic appetite rhythm is driven by endogenous circadian clocks in dopaminergic neurons of the ventral tegmental area (VTA). Mice with disrupted clock function in the VTA lose their hedonic overconsumption rhythms without affecting homeostatic intake. These findings assign a functional role of VTA clocks in modulating palatable feeding behaviors and identify a potential therapeutic route to counteract hyperphagy in an obesogenic environment. In addition to promoting overconsumption, palatable diets dampen daily intake patterns, which further augments metabolic dysfunction. Here, the authors find that in mice, circadian clocks in dopaminergic neurons in the ventral tegmental area drive hedonic appetite rhythms.

This contribution focuses on the utilization of very-high-resolution (VHR) images to identify construction areas and their temporal changes aiming to estimate the investment in construction as a basis for economic forecasts. Triggered by the need to improve macroeconomic forecasts and reduce their time intervals, the idea arose to use frequently available information derived from satellite imagery. For the improvement of macroeconomic forecasts, the period to detect changes between two points in time needs to be rather short because early identification of such investments is beneficial. Therefore, in this study, it is of interest to identify and quantify new construction areas, which will turn into build-up areas later. A multiresolution segmentation followed by a kNN classification is applied to WorldView images from an area around the southern part of Berlin, Germany. Specific material compositions of construction areas result in typical classification patterns different from other land cover classes. A GIS-based analysis follows to extract specific temporal “patterns of life” in construction areas. With the early identification of such patterns of life, it is possible to predict construction areas that will turn into real estate later. This information serves as an input for macroeconomic forecasts to support quicker forecasts in future.

Stent thrombosis is a safety concern associated with use of drug-eluting stents. Little is known about occurrence of stent thrombosis more than 1 year after implantation of such stents. Between April, 2002, and Dec, 2005, 8146 patients underwent percutaneous coronary intervention with sirolimus-eluting stents (SES; n=3823) or paclitaxel-eluting stents (PES; n=4323) at two academic hospitals. We assessed data from this group to ascertain the incidence, time course, and correlates of stent thrombosis, and the differences between early (0–30 days) and late (>30 days) stent thrombosis and between SES and PES. Angiographically documented stent thrombosis occurred in 152 patients (incidence density 1·3 per 100 person-years; cumulative incidence at 3 years 2·9%). Early stent thrombosis was noted in 91 (60%) patients, and late stent thrombosis in 61 (40%) patients. Late stent thrombosis occurred steadily at a constant rate of 0·6% per year up to 3 years after stent implantation. Incidence of early stent thrombosis was similar for SES (1·1%) and PES (1·3%), but late stent thrombosis was more frequent with PES (1·8%) than with SES (1·4%; p=0·031). At the time of stent thrombosis, dual antiplatelet therapy was being taken by 87% (early) and 23% (late) of patients (p<0·0001). Independent predictors of overall stent thrombosis were acute coronary syndrome at presentation (hazard ratio 2·28, 95% CI 1·29–4·03) and diabetes (2·03, 1·07–3·83). Late stent thrombosis was encountered steadily with no evidence of diminution up to 3 years of follow-up. Early and late stent thrombosis were observed with SES and with PES. Acute coronary syndrome at presentation and diabetes were independent predictors of stent thrombosis.