Abstract: Measuring the inequality of leaf area distribution per plant (ILAD) can provide a useful tool for quantifying the influences of intra- and interspecific competition, foraging behavior of herbivores, and environmental stress on plants’ above-ground architectural structures and survival strategies. Despite its importance, there has been limited research on this issue. This paper aims to fill this gap by comparing four inequality indices to measure ILAD, using indices for quantifying household income that are commonly used in economics, including the Gini index (which is based on the Lorenz curve), the coefficient of variation, the Theil index, and the mean log deviation index. We measured the area of all leaves for 240 individual plants of the species Shibataea chinensis Nakai, a drought-tolerant landscape plant found in southern China. A three-parameter performance equation was fitted to observations of the cumulative proportion of leaf area vs. the cumulative proportion of leaves per plant to calculate the Gini index for each individual specimen of S. chinensis. The performance equation was demonstrated to be valid in describing the rotated and right shifted Lorenz curve, given that >96% of root-mean-square error values were smaller than 0.004 for 240 individual plants. By examining the correlation between any of the six possible pairs of indices among the Gini index, the coefficient of variation, the Theil index, and the mean log deviation index, the data show that these indices are closely related and can be used interchangeably to quantify ILAD.

Abstract: Stimuli-responsive metal-organic frameworks (MOFs) are highly versatile porous materials with the ability to respond to different external stimuli, including temperature, pressure, pH, and light. The MOF properties can switch reversibly under specific light irradiation, opening the doors to various applications. This review focuses on design strategies to obtain photo-responsive MOFs, namely (i) encapsulation of photo-switchable molecules as guests in MOF porous structures, (ii) fabrication of MOF composites, (iii) post-synthesis modification, and (iv) synthesis of MOFs with photo-responsive ligands. The most recent reports from the literature are herein reviewed and analyzed in terms of material chemistry and performance. Comparisons between the different strategies are performed and future challenges are discussed. The critical aspect of the fatigue of photo-responsive MOFs applied for prolonged cycling of irradiation is also discussed.

Abstract: Resource-efficient nitrogen management is of high environmental and economic interest, and manure represents the major nutrient flow in livestock-intensive regions. Ammonia stripping/scrubbing (SS) is an appealing nitrogen recovery route from manure, yet its real-life implementation has been limited thus far. In nutrient surplus regions like Flanders, treatment of the liquid fraction (LF) of (co–)digested manure typically consists of nitrification/denitrification (NDN) removing most N as nitrogen gas. Integrating SS before NDN in existing plants would expand treatment capacity and recover N while maintaining low N effluent values, yet cost estimations of this novel approach after process optimisation are not yet available. A programming model was developed and calibrated to minimise the treatment costs of this approach and find the balance between N recovery versus N removal. Four crucial operational parameters (CO2 stripping time, NH3 stripping time, temperature and NaOH addition) were optimised for 18 scenarios which were different in terms of technical set-up, influent characteristics and scrubber acid. The model shows that SS before NDN can decrease the costs by 1 to 56% under optimal conditions compared to treatment with NDN only, with 1 to 8% reduction for the LF of manure (22–29% recovered of N treated), and 11 to 56% reduction for the LF of co-digested manure (42–67% recovered of N treated), primarily dependent on resource pricing. This study shows the power of modelling for minimum-cost design and operation of manure treatment yielding savings while producing useful N recovery products with SS followed by NDN.

Abstract: Dry deposition is an important process determining pollutant concentrations, especially when studying the influence of urban green infrastructure on particulate matter (PM) levels in cities. Computational fluid dynamics (CFD) models of PM capture by vegetation are useful tools to increase their applicability. The meso-scale models of Zhang et al. (Atmos Environ 35:549-560, 2001) and Petroff and Zhang (Geosci Model Dev 3(2):753-769, 2010) have often been adopted in CFD models, however a comparison of these models with measurements including all PM particle sizes detrimental to health has been rarely reported and certainly not for green wall species. This study presents dry deposition experiments on real grown Hedera helix in a wind tunnel setup with wind speeds from 1 to 4 m s(-1) and PM consisting of a mixture of soot (0.02 – 0.2 mu mu m) and dust particles (0.3 – 10 mu mu m). Significant factors determining the collection efficiency (%) were particle diameter and wind speed, but relative air humidity and the type of PM (soot or dust) did not have a significant influence. Zhang's model outperformed Petroff's model for particles < 0.3 mu mu m, however the inclusion of turbulent impaction in Petroff's model resulted in better agreement with the measurements for particles > 2 – 3 mu mu m. The optimised model had an overall root-mean-square-error of similar to 4% for collection efficiency (CE) and 0.4 cm s-1 for deposition velocity (nu d), which was shown to be highly competitive against previously described models. It can thus be used to model PM deposition on other plant species, provided the correct parameterisation of the drag by this species. A detailed description of the spatial distribution of the vegetation could solve the underestimation for particle sizes of 0.3 – 2 mu mu m.

Abstract: One of the most basic criteria in documenting rangeland use prospects is the recognition of byproducts and their economic appraisal. The current study was conducted to assess the economic indices of exploiting byproduct production in Shahindej, Northwest Iran. For this purpose, 24 by-product-generating species were selected in 114 locations that belong to 49 rangeland units. The total expected value of 24 by-product generating species yield and forage production was calculated at 44.22 USD ha(-1). The results of this study showed that the sustainability of natural resources depends on the effective participation and empowerment of local communities. Furthermore, by-product exploitation contributes significantly to the local economy and employment while also reducing grazing intensity. Overall, the findings of this study show that by-product earnings should be considered in range management schemes and comprehensive natural-area management.

Abstract: Natural deep eutectic solvents (NADES) represent a green alternative to common organic solvents in the biochemical industry due to their benign behavior and tailorable properties, in particular as media for enzymatic reactions. However, to fully exploit their potential in enzymatic reactions, there is a need for a more fundamental understanding of how these neoteric solvents influence the course of these reac-tions. Thus, the aim of this study is to investigate the influence of NADES with various molar composi-tions on the stability and structure of enzymes, applying molecular dynamics simulations. This can help to better understand the effect of individual compounds of NADES, in addition to eutectic mixtures. More specifically, we simulate the behavior of Candida antarctica lipase B (CALB) enzyme in NADES com-posed of choline chloride with either urea, ethylene glycol or glycerol. Hereto, we monitor the NADES microstructure, the general stability of the enzyme and changes in the structure of its active sites and sur-face residues. Our simulations show that none of the studied NADES systems significantly disrupt the microstructure of the solvent or the stability of the CALB enzyme within the time scales of the simula-tions. The enzyme preserves its initial structure, size and intra-chain hydrogen bonds in all investigated compositions and, for the first time reported, also in NADES with increased hydrogen bond donating com-pound ratios. As the main novelty, our results indicate that, in addition to the composition, the molar ratio can be an additional variable to fine-tune the physicochemical properties of NADES without altering the enzyme characteristics. These findings could facilitate the development and application of task -tailored NADES media for biocatalytic processes. (c) 2022 Elsevier B.V. All rights reserved.

Abstract: Background Patient-derived organoids are invaluable for fundamental and translational cancer research and holds great promise for personalized medicine. However, the shortage of available analysis methods, which are often single-time point, severely impede the potential and routine use of organoids for basic research, clinical practise, and pharmaceutical and industrial applications. Methods Here, we developed a high-throughput compatible and automated live-cell image analysis software that allows for kinetic monitoring of organoids, named Organoid Brightfield Identification-based Therapy Screening (OrBITS), by combining computer vision with a convolutional network machine learning approach. The OrBITS deep learning analysis approach was validated against current standard assays for kinetic imaging and automated analysis of organoids. A drug screen of standard-of-care lung and pancreatic cancer treatments was also performed with the OrBITS platform and compared to the gold standard, CellTiter-Glo 3D assay. Finally, the optimal parameters and drug response metrics were identified to improve patient stratification. Results OrBITS allowed for the detection and tracking of organoids in routine extracellular matrix domes, advanced Gri3D (R)-96 well plates, and high-throughput 384-well microplates, solely based on brightfield imaging. The obtained organoid Count, Mean Area, and Total Area had a strong correlation with the nuclear staining, Hoechst, following pairwise comparison over a broad range of sizes. By incorporating a fluorescent cell death marker, infra-well normalization for organoid death could be achieved, which was tested with a 10-point titration of cisplatin and validated against the current gold standard ATP-assay, CellTiter-Glo 3D. Using this approach with OrBITS, screening of chemotherapeutics and targeted therapies revealed further insight into the mechanistic action of the drugs, a feature not achievable with the CellTiter-Glo 3D assay. Finally, we advise the use of the growth rate-based normalised drug response metric to improve accuracy and consistency of organoid drug response quantification. Conclusion Our findings validate that OrBITS, as a scalable, automated live-cell image analysis software, would facilitate the use of patient-derived organoids for drug development and therapy screening. The developed wet-lab workflow and software also has broad application potential, from providing a launching point for further brightfield-based assay development to be used for fundamental research, to guiding clinical decisions for personalized medicine.

Abstract: Plasma bioscience and medicine are both rapidly growing fields. Their aim is to utilize cold physical plasmas for desired biological outcomes in medicine, biotechnology, agriculture, and general hygienic purposes. Great success has been achieved in many applications with individually designed plasma sources and plasma parameters. Although lab and application-specific tuning of plasmas is a great advantage of this technology, standardized units to define plasma treatments are required to facilitate comparison of the effects found by different researchers who do not use the same plasma sources. By drawing conclusions from over a century of plasma biomedical research, we propose that all researchers adopt the use of a standardized value, the plasma treatment unit (PTU), to describe the biological effects of different cold plasma sources and treatment regimens. It quantifies a key plasma effector in biological systems as an indicator and may provide the foundation for an analogous and clinically relevant unit in the future.

Abstract: A database-driven approach combined with ab initio density functional theory (DFT) simulations is used to identify and simulate alternative ferroelectric materials beyond Hf(Zr)O-2. The database-driven screening method identifies a class of wurtzite ferroelectric materials. DFT simulations of wurtzite magnesium chalcogenides, including MgS, MgSe, and MgTe, show their potential to achieve improved ferroelectric (FE) stability, simple atomistic unit cell structure, and large FE polarization. Strain engineering can effectively modulate the FE switching barrier height for facilitating FE switching. The effect of the piezoelectric property on the FE switching barrier heights is also examined.