Construction of air filter membranes bearing prominent collecting and transferring capability is highly desirable for detecting airborne pathogens but remains challenging. Here, a hyaluronic acid air filter membrane (HAFM) with tunable heterogeneous micro-nano porous structures is straightforwardly constructed through the ethanol-induced phase separation strategy. Airborne pathogens can be trapped and collected by HAFM with high performance due to the ideal trade-off between removal efficiency and pressure drop. By exempting the sample elution and extraction processes, the HAFM after filtration sampling can not only directly disperse on the agar plate for colony culture but also turn to an aqueous solution for centrifugal enrichment, which significantly reduces the damage and losses of the captured microorganisms. The following combination with ATP bioluminescence endows the HAFM with a real-time quantitative detection function for the captured airborne pathogens. Benefiting from high-efficiency sampling and non-traumatic transfer of airborne pathogens, the real-world bioaerosol concentration can be facilely evaluated by the HAFM-based ATP assay. This work thus not only provides a feasible strategy to fabricate air filter membranes for efficient microbial collection and enrichment but also sheds light on designing advanced protocols for real-time detection of bioaerosols in the field.

Molecular tools are an indispensable part of ecology and biodiversity sciences and implemented across all biomes. About a decade ago, the use and implementation of environmental DNA (eDNA) to detect biodiversity signals extracted from environmental samples opened new avenues of research. Initial eDNA research focused on understanding population dynamics of target species. Its scope thereafter broadened, uncovering previously unrecorded biodiversity via metabarcoding in both well-studied and understudied ecosystems across all taxonomic groups. The application of eDNA rapidly became an established part of biodiversity research, and a research field by its own. Here, we revisit key expectations made in a land-mark special issue on eDNA in Molecular Ecology in 2012 to frame the development in six key areas: (1) sample collection, (2) primer development, (3) biomonitoring, (4) quantification, (5) behaviour of DNA in the environment and (6) reference database development. We pinpoint the success of eDNA, yet also discuss shortfalls and expectations not met, highlighting areas of research priority and identify the unexpected developments. In parallel, our retrospective couples a screening of the peer-reviewed literature with a survey of eDNA users including academics, end-users and commercial providers, in which we address the priority areas to focus research efforts to advance the field of eDNA. With the rapid and ever-increasing pace of new technical advances, the future of eDNA looks bright, yet successful applications and best practices must become more interdisciplinary to reach its full potential. Our retrospect gives the tools and expectations towards concretely moving the field forward.

Bioaerosol is a concept that is used to describe all biological materials suspended in the air, including bacteria, fungi, viruses, pollen, and their derivatives such as allergens, endotoxin, mycotoxins and etc. In some studies, primary biological aerosol particle (PBAP) is also coined to refer to intact microbes in the air. Bioaerosol is a multidisciplinary research subject, involving many different fields such as microbiology, mechanical engineering, air pollution, medical science, epidemiology, immunological science, biochemistry, physics, nanotechnologies and etc. The bioaerosol field has undergone about 200 years\' research history since 1833 when mold spores were first detected in the air by Charles Darwin on the Cape Verde Islands. In recent decades, there has been a research boom in bioaerosol field, thus triggering many outstanding research opportunities. Visible progress has already been made in understanding bioaerosol roles in human health, atmospheric and ecological impacts as well as their respective technologies: bioaerosol capture, monitoring and also inactivation. Most recently, researchers from different fields start to bridge together for solving bioaerosol challenges and addressing key scientific problems, e.g., bioaerosol spread, real-time detection, indoor microbes, human bioaerosol emissions, and bio-defense. Toward this effort, a \"Bioaerosol Xiangshan Science Conference-the 600th\" has been successfully held in the summer in Beijing, China. A total of 47 scientists and funding agency officials including leading bioaerosol experts from overseas were invited and two-day long extensive discussions on bioaerosol progress and problems were carried out. Future bioaerosol directions have been outlined by the attendees during the conference. Some of the participants have also contributed to this bioaerosol special issue. This special issue consists of a total of 20 bioaerosol articles from eight countries including one review, and contributes to the advances in bioaerosol emission, transmission, health effects, ambient bioaerosols, method development and instrumentation, and control. Through this special issue, the bioaerosol community has obtained a better understanding of bioaerosol health risks and developed the corresponding strategies to confront the threats. This special issue might serve as a starting point to not only link bioaerosol scientists from different continents, but also bring together people from various fields yet with an interest in bioaerosol to collectively advance the field further.

Exposure to bioaerosol contamination has detrimental effects on human health. Recent advances in ATP bioluminescence provide more opportunities for the quantitative detection of bioaerosols. Since almost all active organisms can produce ATP, the amount of airborne microbes can be easily measured by detecting ATP-driven bioluminescence. The accurate evaluation of microorganisms mainly relies on following the four key steps: sampling and enrichment of airborne microbes, lysis for ATP extraction, enzymatic reaction, and measurement of luminescence intensity. To enhance the effectiveness of ATP bioluminescence, each step requires innovative strategies and continuous improvement. In this review, we summarized the recent advances in the quantitative detection of airborne microbes based on ATP bioluminescence, which focuses on the advanced strategies for improving sampling devices combined with ATP bioluminescence. Meanwhile, the optimized and innovative strategies for the remaining three key steps of the ATP bioluminescence assay are highlighted. The aim is to reawaken the prosperity of ATP bioluminescence and promote its wider utilization for efficient, real-time, and accurate detection of airborne microbes.

Intra-tissue genetic heterogeneity is universal to both healthy and cancerous tissues. It emerges from the stochastic accumulation of somatic mutations throughout development and homeostasis. By combining population genetics theory and genomic information, genetic heterogeneity can be exploited to infer tissue organization and dynamics in vivo. However, many basic quantities, for example the dynamics of tissue-specific stem cells remain difficult to quantify precisely. Here, we show that single-cell and bulk sequencing data inform on different aspects of the underlying stochastic processes. Bulk-derived variant allele frequency spectra (VAF) show transitions from growing to constant stem cell populations with age in samples of healthy esophagus epithelium. Single-cell mutational burden distributions allow a sample size independent measure of mutation and proliferation rates. Mutation rates in adult hematopietic stem cells are higher compared to inferences during development, suggesting additional proliferation-independent effects. Furthermore, single-cell derived VAF spectra contain information on the number of tissue-specific stem cells. In hematopiesis, we find approximately 2 × 105 HSCs, if all stem cells divide symmetrically. However, the single-cell mutational burden distribution is over-dispersed compared to a model of Poisson distributed random mutations. A time-associated model of mutation accumulation with a constant rate alone cannot generate such a pattern. At least one additional source of stochasticity would be needed. Possible candidates for these processes may be occasional bursts of stem cell divisions, potentially in response to injury, or non-constant mutation rates either through environmental exposures or cell-intrinsic variation.

Natural compounds in plants are often unevenly distributed, and determining the best sampling locations to obtain the most representative results is technically challenging. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) can provide the basis for formulating sampling guideline. For a succulent plant sample, ensuring the authenticity and in situ nature of the spatial distribution analysis results during MSI analysis also needs to be thoroughly considered. In this study, we developed a well-established and reliable MALDI-MSI method based on preservation methods, slice conditions, auxiliary matrices, and MALDI parameters to detect and visualize the spatial distribution of mescaline in situ in Lophophora williamsii. The MALDI-MSI results were validated using liquid chromatography-tandem mass spectrometry. Low-temperature storage at -80°C and drying of \"bookmarks\" were the appropriate storage methods for succulent plant samples and their flower samples, and cutting into 40 μm thick sections at -20°C using gelatin as the embedding medium is the appropriate sectioning method. The use of DCTB (trans-2-[3-(4-tert-butylphenyl)-2-methyl-2-propenylidene]malononitrile) as an auxiliary matrix and a laser intensity of 45 are favourable MALDI parameter conditions for mescaline analysis. The region of interest semi-quantitative analysis revealed that mescaline is concentrated in the epidermal tissues of L. williamsii as well as in the meristematic tissues of the crown. The study findings not only help to provide a basis for determining the best sampling locations for mescaline in L. williamsii, but they also provide a reference for the optimization of storage and preparation conditions for raw plant organs before MALDI detection.
UNASSIGNED: An accurate in situ MSI method for fresh water-rich succulent plants was obtained based on multi-parameter comparative experiments.Spatial imaging analysis of mescaline in Lophophora williamsii was performed using the above method.Based on the above results and previous results, a sampling proposal for forensic medicine practice is tentatively proposed.

Information-driven mission abort is an effective way to control the failure risk of safety-critical systems during mission executions. We investigate the optimal sampling and mission abort decisions of partially observable safety-critical systems, where the underlying system health state can only be revealed by sampling. In contrast to previous studies, we employ partial health information to jointly determine: (a) whether to execute sampling, and (b) when to abort the mission in a dynamic manner, so as to minimize the expected total cost incurred by sampling, mission failure, and system malfunction. Dynamic sampling and mission abort policies are devised following the belief state, whose optimization model is cast into the framework of a partially observable Markov decision process. Some structural insights with regard to the value function, control limit selection, and optimality existence are presented. The performance of the proposed sampling and abort policy is tested by numerical experiments, which are proved to outperform other heuristic abort policies in mission loss control.

Chemical analysis of atmospheric aerosols by conventional analytical methods is usually required to perform complicated and time-consuming sample preparation processes. In recent decades, ambient ionization mass spectrometry (AI-MS) methods have been proven to be simple, rapid, and effective analytical tools for direct analysis of various complex samples. In this work, we applied porous paper filters for direct adsorptive sampling of tobacco smoke, and then the sampled paper filters were performed the emitters of the paper spray ionization (PSI) device. An auto-sampling device was made to control the generation and collection of tobacco smoke. Nicotine, the typical compound of tobacco smoke, was used to optimize the key conditions of auto-sampling. Moreover, different types of tobacco smoke were also compared with multivariate variable analysis, and the makers of tobacco smoke from different sources of tobacco smoke were investigated. By using this method, direct sampling and analysis of a single tobacco sample can be completed within minutes. Overall, our results show that PSI-MS is a powerful tool that integrates collection, extraction, ionization, and identification analytes in smoke.

More and more studies have proved that microRNAs (miRNAs) play a critical role in gene expression regulation, and the irregular expression of miRNAs tends to be associated with a variety of complex human diseases. Because of the high cost and low efficiency of identifying disease-associated miRNAs through biological experiments, scholars have focused on predicting potential disease-associated miRNAs by computational methods. Considering that the existing methods are flawed in constructing negative sample set, we proposed a clustering-based sampling method for miRNA-disease association prediction (CSMDA). Firstly, we integrated multiple similarity information of miRNA and disease to represent miRNA-disease pairs. Secondly, we performed a clustering-based sampling method to avoid introducing potential positive samples when constructing negative sample set. Thirdly, we employed a random forest-based feature selection method to reduce noise and redundant information in the high-dimensional feature space. Finally, we implemented an ensemble learning framework for predicting miRNA-disease associations by soft voting. The Precision, Recall, F1-score, AUROC and AUPR of the CSMDA achieved 0.9676, 0.9545, 0.9610, 0.9928, and 0.9940, respectively, under five-fold cross-validation. Besides, case study on three cancers showed that the top 20 potentially associated miRNAs predicted by the CSMDA were confirmed by the dbDEMC database or literatures. The above results demonstrate that the CSMDA can predict potential disease-associated miRNAs more accurately.

Direct sampling of lipids from tissues for direct mass spectrometry (MS) analysis allows a quick profiling of lipidome, which is important for biomedical applications. In this work, we developed a polyporous polymeric membrane (PPM) microprobe for highly efficient sampling of lipids directly from tissue samples. The PPM was prepared by polypropylene with pores as large of 10 ​μm, facilitating the permeation of lipids from tissue surfaces. The PPM was coated onto a stainless steel wire with a thickness of ∼100 ​μm. The entire analysis procedure includes sampling of the lipids in tissue, washing the probe, and extraction spray ionization for MS analysis. The effectiveness was validated by analyzing mouse brain tissue samples. It showed high recoveries for a series of lipid classes in comparison with total lipid extraction method. Further demonstration was carried out with analysis of tissue samples from mouse liver, stomach, kidney and legs. With high physical strength and good chemical stability, the microprobe was also demonstrated for sampling lipids inside mouse kidney tissue samples. By incorporating a photochemical derivatization, a workflow was also developed for fast detection of lipid C[bond, double bond]C isomers in tissue samples. Finally, a microprobe array was also developed for simultaneous sampling of lipids from multiple sites on tissue surfaces.