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Site-Selective Copper(I)-Catalyzed Hydrogenation of Amides
Prevalence and features of allergic bronchopulmonary aspergillosis, United States, 2016–2022
The epidemiology of allergic bronchopulmonary aspergillosis (ABPA) in the United States is not well-described. To estimate national ABPA prevalence among patients with asthma or cystic fibrosis, characterize ABPA testing practices, and describe ABPA clinical features, treatment, and 6-month outcomes. We used the 2016–2022 Merative™ MarketScan® Commercial/Medicare and Multi-State Medicaid Databases to identify cohorts of patients with 1) asthma, 2) cystic fibrosis (CF), and 3) ABPA. We calculated ABPA prevalence per 10,000 patients with asthma or CF, assessed diagnostic testing for ABPA among patients with severe asthma, and described features of patients with ABPA using diagnosis and procedure codes. The overall ABPA prevalence among patients with asthma was 2.8/10,000 (Commercial/Medicare) and 1.0/10,000 (Medicaid). ABPA prevalence increased with asthma severity (Commercial/Medicare: mild 1.3, moderate 9.3, severe 70.6, Medicaid: mild 0.3, moderate 2.4, severe 32.4). Among patients with CF, ABPA prevalence was 183.7/10,000 (Commercial/Medicare) and 134.6/10,000 (Medicaid). Among patients with severe asthma, 10.3% (Commercial/Medicare) and 7.4% (Medicaid) received total immunoglobulin E testing, which is recommended for ABPA diagnosis. Among all patients with ABPA (Commercial/Medicare: n = 1,564, Medicaid: n = 410), ABPA treatments included inhaled corticosteroids (>70%), systemic corticosteroids (>62%), and antifungals (>18%). Patients with ABPA and Medicaid were more likely to experience hospitalization (45.1% vs. 22.5% of patients with Commercial/Medicare insurance) and respiratory failure (18.5% vs. 10.9%). This analysis provides initial estimates of national ABPA prevalence. Further studies could identify potential barriers to ABPA testing and investigate potential factors affecting payer-related differences in ABPA burden.
Controlling the Spatiotemporal Self-Organization of Stimuli-Responsive Nanocrystals under Out-of-Equilibrium Conditions
Assessing changing baleen whale distributions and reported incidents relative to vessel activity in the Northwest Atlantic
Baleen whales are among the largest marine megafauna, and while mostly well-protected from direct exploitation, they are increasingly affected by vessel traffic, interactions with fisheries, and climate change. Adverse interactions, notably vessel strikes and fishing gear entanglement, often result in distress, injury, or death for these animals. In Atlantic Canadian waters, such negative interactions or ‘incidents’ are consistently reported to marine animal response organizations but have not yet been analyzed relative to the spatial distribution of whales and vessels. Using a database of 483,003 whale sightings, 1,110 incident reports, and 82 million hours of maritime vessel activity, we conducted a spatiotemporal vulnerability analysis for all six baleen whale species occurring in the Northwest Atlantic Ocean by developing an ensemble of habitat-suitability models. The relative spatial risk of vessel-induced incidents was assessed for present (1985–2015) and projected near-future (2035–2055) distributions of baleen whales. Areas of high habitat suitability for multiple baleen whale species were intrinsically linked to sea surface temperature and salinity, with multispecies hotspots identified in the Bay of Fundy, Scotian Shelf, Laurentian Channel, Flemish Cap, and Gulf of St. Lawrence. Present-day model projections were independently evaluated using a separate database of acoustic detections and found to align well. Regions of high relative incident risk were projected close to densely inhabited regions, principal maritime routes, and major fishing grounds, in general coinciding with reported incident hotspots. While some high-risk regions already benefit from mitigation strategies aimed at protecting North Atlantic Right Whales, our analysis highlights the importance of considering risks to multiple species, both in the present day and under continued environmental change.
Improving early prediction of crop yield in Spanish olive groves using satellite imagery and machine learning
In the production sector, the usefulness of predictive systems as a tool for management and decision-making is well known. In the agricultural sector, a correct economic balance of the farm depends on making the right decisions. For this purpose, having information in advance on crop yields is an extraordinary help. Numerous predictive models infer accurate crop yield data from aerobiological variables and pollen analysis; this is around spring, in the middle stage of the crop year, when planning and investments are already done. The aim of this study is to anticipate accurate crop yield data at an early stage of the cropping season. In the case of olive groves in Spain, this period is in February. This work is developed for an entire province, Jaen, belonging to the region of Andalusia, in Southern Spain. The methodology uses Machine Learning algorithms together with an exhaustive analysis of predictor variables. Temporal data come from public web services, such as spatial data infrastructures of some state agencies. The processing of the satellite imagery is carried out by the geospatial processing service Google Earth Engine. The result is the early prediction of kilograms of both olive crop and olive oil, eight months prior to the beginning of the first harvesting campaigns of the year, with an average absolute error of prediction better than 26%. The relevance of this work is the early availability of predicted crop yield data together with the multi-scale applicability of the predictive models. This makes this model a useful tool for all the agents involved in olive grove management. From farmers, to agricultural technicians, researchers and scientists dedicated to the study of the olive tree, to governmental institutions and agricultural associations that provide technical support, advice and regulation to ensure responsible practices and the long-term viability of the olive industry.
Unlocking Chiral Sulfinimidoyl Electrophiles: Asymmetric Synthesis of Sulfinamides Catalyzed by Anionic Stereogenic-at-Cobalt(III) Complexes
Analyzing robust dividend payout policy with dynamic panel regression: Application of speed of adjustment to half-life
This study aims to observe the effects of financial metrics, free float shareholders, GDP growth and firm age on dividend payout policy in both the short- and long-term scenarios. The study introduces the dynamic panel regression models, i.e. Autoregressive Integrated Moving Average (ARIMA) for time series data and Weighted Least Squares (WLS) to account for autocorrelation and heteroscedasticity limitation. The dataset includes all companies listed on the Stock Exchange of Thailand during the years 2013–2023. The study finds that in the long-term, GDP growth negatively relates to dividend payout policy in all industrial sectors. Financial metrics, free float shareholders, GDP growth and firm age affect a mixed picture of industrial sectors on dividend payout policy. In the short-term, previous dividend payments significantly influence dividend payment policy. Furthermore, a higher debt-to-equity ratio, firm age, and free cashflows influence dividend payout policy in various industrial sectors. Also shown by the analysis is that factors influence short-run adjustment to half-life analysis.
Colloidal Germanium Quantum Dots with Broadly Tunable Size and Light Emission
The value co-creation mechanism of Public Cultural Services ecosystem in China based on "public value" theory
The establishment of China’s public cultural service system has been explored for nearly two decades, but there is still a significant gap in achieving the goal of equalising and eliminating differences in public value, and it is urgent to systematically explore the public value governance issues contained in it. This paper presents a localised theoretical analysis framework based on the strategic triangle model of public value, with the objective of exploring the endogenous mechanism of China’s public cultural services ecosystem (PCSE). Furthermore, it constructs a panel vector autoregression (PVAR) model from a dynamic endogenous perspective, employing the STATA 16.0 software package to conduct empirical tests. The empirical testing of the interactions between government attention (GA), cultural needs (CN) and public cultural services (PCS), as well as the regional heterogeneity, is based on data from 31 provinces and municipalities in mainland China for the period of 2008–2022. The findings are as follows: (1) The unified analysis framework reveals a significant positive mutual promotion relationship between GA and PCS. In contrast, the two-way promotion relationship between CN and PCS is weak, while the relationship between GA and PCS is unstable. (2) The results of the dynamic response analysis demonstrate significant regional disparities in the value co-creation path of public cultural services. The circular transfer of CN and PCS is more pronounced in the eastern region, while the central-western regions rely more on the circular transfer of GA and PCS. This study offers insights for central and local governments to reinforce the value co-creation foundation of a service-oriented government, explore a value co-creation pathway tailored to local conditions, and construct a contemporary public cultural services ecosystem guided by the value of common prosperity in spiritual life.
Author Correction: Increasing extreme hourly precipitation risk for New York City after Hurricane Ida
An Emerging Toolkit of Ho<sup>3+</sup> Sensitized Lanthanide Nanocrystals with NIR-II Excitation and Emission for <i>in Vivo</i> Bioimaging
MESS to live with schizophrenic parental history: A systematic review of developmental checkpoints
Parental history of schizophrenia, a complex and multifaceted psychological disorder, is recognized as a well-established risk factor in the development of the disorder among offspring. However, the developmental patterns of such children and adolescents before the onset of the problem have not yet been systematically documented. We present a comprehensive account of developmental checkpoints essential for preventing it from occurring. This review embarks on a detailed explanation of the domains requiring serious attention during the development of an individual with such a familial history. We examined a diversified set of studies comparing the developmental patterns of children with or without (a comparative) a parental history of schizophrenia and highlighted the areas of concern for the later development of the problem among the first group. We included the peer-reviewed articles, published in English based on children and adolescents, found in Web of Science, PubMed, and PsychInfo databases and separate citation searches. We summarized our findings under MESS typology covering motor development, emotional and behavioral issues, speech and hearing impairments, and socio-cognitive aspects as essential features of a child’s development serving as a guide to prevent the onset of psychological complications.
Erythrocyte modified controlling nutritional status as a biomarker for predicting poor prognosis in post-surgery breast cancer patients
Precise Preparation of Size-Uniform Two-Dimensional Platelet Micelles Through Crystallization-Assisted Rapid Microphase Separation Using All-Bottlebrush-Type Block Copolymers with Crystalline Side Chains
Identification of novel cyclin-dependent kinase 4/6 inhibitors from marine natural products
Cyclin-dependent kinases 4 and 6 (CDK4/6) are crucial regulators of cell cycle progression and represent important therapeutic targets in breast cancer. This study employs a comprehensive computational approach to identify novel CDK4/6 inhibitors from marine natural products. We utilized structure-based virtual screening of the CMNPD database and MNP library, followed by rigorous filtering based on drug-likeness criteria, PAINS filter, ADME properties, and toxicity profiles. From an initial hit of 9,497 compounds, 2,344 passed drug-likeness and PAINS filters. Further ADME filtering yielded 50 compounds, of which 25 exhibited non-toxic profiles. These 25 candidates underwent consensus molecular docking using seven distinct algorithms: AutoDockTools 4.2, idock, LeDock, Qvina 2, Smina, AutoDock Vina 1.2.0, PLANTS, and rDock. Based on these results, six top-scoring compounds were selected for comprehensive 500 nanosecond all-atom molecular dynamics simulations to evaluate their structural stability and interactions with CDK4/6. Our analysis revealed that compounds CMNPD11585 and CMNPD2744 demonstrated superior stability in their interactions with CDK4/6, exhibiting lower RMSD and RMSF values, more favorable binding free energies, and persistent hydrogen bonding patterns. These compounds also showed lower Solvent Accessible Surface Area values, indicating better compatibility with the CDK4/6 active site. Subsequent in-vitro studies using MTT assays on MCF-7 breast cancer cells confirmed the cytotoxic effects of these compounds, with CMNPD11585 showing the highest potency, followed by CMNPD2744.
Bioinformatic analysis of ferroptosis related biomarkers and potential therapeutic targets in vitiligo
An Automated Workflow to Discover the Structure–Stability Relations for Radiation Hard Molecular Semiconductors
State of the art modelling for the Black Sea ecosystem to support European policies
The Black Sea is affected by numerous anthropogenic pressures, such as eutrophication and pollution through coastal and river discharges, fisheries overexploitation, species invasions, and the impacts of climate change. Growing concerns regarding the cumulative effects of these pressures have necessitated the need for an ecosystem approach to assessing the state of this basin. In recent years, the European Commission-JRC has developed a scientific and modelling tool, the Blue2 Modelling Framework with the aim of exploring the consequences of EU management and policy options on marine ecosystems. This framework has been designed to provide information on specific ecological indicators set out in EU legislation. Here, we present the Blue2 framework for the Black Sea ecosystem. The model represented the mid-1990s’ conditions in the Black Sea ecosystem including trophic levels from primary producers to marine mammals and sea birds. The model simulations covered a period from 1995–2021. The results showed that gulls & cormorant seabirds, sprat, horse mackerel and mugilidae had structuring role in the food web. Fishing fleets had indirect negative impacts on marine mammals in addition to commercially exploited species. Analysis of the ecosystem indicators confirmed the overall temporal degradation of the Black Sea when comparing results with other Black Sea models, whilst the comparison with the Mediterranean Sea allowed us to identify comparable indicators between similar model structures. The spatial/temporal model successfully simulated the overall ongoing declining dynamics of the Black Sea ecosystem as the biomasses of the majority of the functional groups had significant observed decreasing trends during the simulation period. This model is the first attempt to represent the historical and current state of the Black Sea ecosystem spatially and temporally, serving as a reference baseline for evaluating policy scenarios and assisting policy makers in the evaluation of potential environmental impacts of management options.