Alternaria alternata is a ubiquitous fungus and a major allergen associated with the development of asthma. Inhalation of intact spores is the primary cause of human exposure to fungal allergen. However, allergen-rich cultured fungal filtrates are oftentimes used in the current models of fungal sensitization that do not fully reflect real-life exposures. Thus, establishing novel spore exposure models is imperative. In this study, we established novel fungal exposure models of both adult and neonate to live spores. We examined pathophysiological changes in the spore models as compared to the non-exposure controls and also to the conventional filtrate models. While both Alternaria filtrate- and spore-exposed adult BALB/c mice developed elevated airway hyperresponsiveness (AHR), filtrates induced a greater IgE mediated response and higher broncholavage eosinophils than spores. In contrast, the mice exposed to Alternaria spores had higher numbers of neutrophils. Both exposures induced comparable levels of lung tissue inflammation and mucous cell metaplasia (MCM). In the neonatal model, exposure to Alternaria spores resulted in a significant increase of AHR in both adult and neonatal mice. Increased levels of IgE in both neonatal and adult mice exposed to spores was associated with increased eosinophilia in the treatment groups. Adult demonstrated increased numbers of lymphocytes that was paralleled by increased IgG1 production. Both adults and neonates demonstrated similarly increased eosinophilia, IgE, tissue inflammation and MCM.

This work studies moisture and heat budgets within two atmospheric rivers (ARs) that made landfall on the west coast of North America during January 2009. Three-dimensional kinematic and thermodynamic fields were constructed using ECMWF Year of Tropical Convection data and global gridded precipitation datasets. Differences between the two ARs are observed, even though both had embedded precipitating convective organizations of the same spatial scale. AR1 extended from 20° to 50°N in an almost west–east orientation. It had excessive warm and moist near-surface conditions. Its precipitating systems were mainly distributed on the southwest and northeast sides of the AR, and tended to exhibit stratiform-type vertical heat and moisture transports. In contrast, AR2 spanned latitudes between 20° and 60°N in a north–south orientation. It was narrower and shorter than AR1, and was mostly covered by pronounced precipitating systems, dominated by a deep convection type of heating throughout the troposphere. In association with these distinctions, the atmosphere over the northeastern Pacific on average experienced episodic cooling and drying despite the occurrence of AR1, yet underwent heating and drying during AR2, when latent heating was strong. Downward sensible heat flux and weak upward surface latent heat flux were observed particularly in AR1. In addition, cloud radiative forcing (CRF) was very weak in AR1, whereas it was strongly negative in AR2. In short, it is found that the oceanic convection in ARs both impacts the moisture transport of ARs, as well as modifies the heat balance in the midlatitudes through latent heat release, convective heat transport, surface heat fluxes, and CRF.

Microbial source-tracking is a useful tool for trace evidence analysis in Forensics. Community-wide massively parallel sequencing profiles can bypass the need for satellite microbes or marker sets, which are unreliable when handling unstable samples. We propose a novel method utilizing Aitchison distance to select important suspects/sources, and then integrate it with existing algorithms in source tracking to estimate the proportions of microbial sample coming from important suspects/sources. A series of comprehensive simulation studies show that the proposed method is capable of accurate selection and therefore improves the performance of current methods such as Bayesian SourceTracker and FEAST in the presence of noise microbial sources.

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Enterprise digital transformation has always been a hot issue in Chinese industries. To grasp the hot topics and development trends of enterprise digital transformation research, this paper uses the visual analysis software CiteSpace to analyze the distribution and trend of research on enterprise digital transformation in CNKI journal papers and draws the following conclusions. The research on the digital transformation of Chinese enterprises first started in 2011, and the period of 2011–2019 belongs to the initial stage and has entered the rapid growth stage since 2020. Most of the authors and research institutions in this field in China are independent researchers and have not yet formed a complex cooperative network. Research on the digital transformation of Chinese enterprises initially started in the publishing industry and gradually extended to various sectors. Future research on the digital transformation of Chinese enterprises will develop in the “digital transformation of state-owned enterprises” and “digital transformation of agricultural enterprises.”