13 research outputs found
The competition and equilibrium in power markets under decarbonization and decentralization
Equilibrium analysis has been widely studied as an effective tool to model gaming interactions and predict market results. However, as competition modes are fundamentally changed by the decarbonization and decentralization of power systems, analysis techniques must evolve. This article comprehensively reviews recent developments in modelling methods, practical settings and solution techniques in equilibrium analysis. Firstly, we review equilibrium in the evolving wholesale power markets which feature new entrants, novel trading products and multi-stage clearing. Secondly, the competition modes in the emerging distribution market and distributed resource aggregation are reviewed, and we compare peer-to-peer clearing, cooperative games and Stackelberg games. Furthermore, we summarize the methods to treat various information acquisition degrees, risk preferences and rationalities of market participants. To deal with increasingly complex market settings, this review also covers refined analytical techniques and agent-based models used to compute the equilibrium. Finally, based on this review, this paper summarizes key issues in the gaming and equilibrium analysis in power markets under decarbonization and decentralization
Controlled antibody release from gelatin for on-chip sample preparation
A practical way to realize on-chip sample preparation for point-of-care diagnostics is to store the required reagents on a microfluidic device and release them in a controlled manner upon contact with the sample. For the development of such diagnostic devices, a fundamental understanding of the release kinetics of reagents from suitable materials in microfluidic chips is therefore essential. Here, we study the release kinetics of fluorophore-conjugated antibodies from (sub-) µm thick gelatin layers and several ways to control the release time. The observed antibody release is well-described by a diffusion model. Release times ranging from ~20 s to ~650 s were determined for layers with thicknesses (in the dry state) between 0.25 µm and 1.5 µm, corresponding to a diffusivity of 0.65 µm2/s (in the swollen state) for our standard layer preparation conditions. By modifying the preparation conditions, we can influence the properties of gelatin to realize faster or slower release. Faster drying at increased temperatures leads to shorter release times, whereas slower drying at increased humidity yields slower release. As expected in a diffusive process, the release time increases with the size of the antibody. Moreover, the ionic strength of the release medium has a significant impact on the release kinetics. Applying these findings to cell counting chambers with on-chip sample preparation, we can tune the release to control the antibody distribution after inflow of blood in order to achieve homogeneous cell staining
Robust estimation of bacterial cell count from optical density
Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data
Prognostic model for aneurysmal subarachnoid hemorrhage patients requiring mechanical ventilation
Abstract Objective Aneurysmal subarachnoid hemorrhage (aSAH) is a major cause of death and disability worldwide and imposes serious burdens on society and individuals. However, predicting the long‐term outcomes in aSAH patients requiring mechanical ventilation remains challenging. We sought to establish a model utilizing the Least Absolute Shrinkage and Selection Operator (LASSO)‐penalized Cox regression to estimate the prognosis of aSAH patients requiring mechanical ventilation, based on regularly utilized and easily accessible clinical variables. Methods Data were retrieved from the Dryad Digital Repository. Potentially relevant features were selected using LASSO regression analysis. Multiple Cox proportional hazards analyses were performed to develop a model using the training set. Receiver operating characteristics and calibration curves were used to assess its predictive accuracy and discriminative power. Kaplan–Meier and decision curve analyses (DCA) were used to evaluate the clinical utility of the model. Results Independent prognostic factors, including the Simplified Acute Physiology Score 2, early brain injury, rebleeding, and length of intensive care unit stay, were identified and included in the nomogram. In the training set, the area under the curve values for 1‐, 2‐, and 4‐year survival predictions were 0.82, 0.81, and 0.80, respectively. In the validation set, the nomogram exhibited excellent discrimination ability and good calibration. Moreover, DCA demonstrated that the nomogram was clinically beneficial. Finally, a web‐based nomogram was constructed (https://rehablitation.shinyapps.io/aSAH). Interpretation Our model is a useful tool for accurately predicting long‐term outcomes in patients with aSAH who require mechanical ventilation and can assist in making individualized interventions by providing valuable information
Impact of intercropping grass on the soil rhizosphere microbial community and soil ecosystem function in a walnut orchard
The intercropping of grass in orchards has beneficial effects on soil properties and soil microbial communities and is an important soil management measure for improving orchard productivity and land-use efficiency. However, few studies have explored the effects of grass intercropping on rhizosphere microorganisms in walnut orchards. In this study, we explored the microbial communities of clear tillage (CT), walnut/ryegrass (Lolium perenne L.) (Lp), and walnut/hairy vetch (Vicia villosa Roth.) (Vv) intercropping system using MiSeq sequencing and metagenomic sequencing. The results revealed that the composition and structure of the soil bacterial community changed significantly with walnut/Vv intercropping compared to CT and walnut/Lp intercropping. Moreover, the walnut/hairy vetch intercropping system had the most complex connections between bacterial taxa. In addition, we found that the soil microorganisms of walnut/Vv intercropping had a higher potential for nitrogen cycling and carbohydrate metabolism, which may be related to the functions of Burkholderia, Rhodopseudomonas, Pseudomonas, Agrobacterium, Paraburkholderia, and Flavobacterium. Overall, this study provided a theoretical basis for understanding the microbial communities associated with grass intercropping in walnut orchards, providing better guidance for the management of walnut orchards
Transcriptional profiling of innate immune responses in sheep PBMCs induced by Haemonchus contortus soluble extracts
Abstract Background Pattern recognition receptors (PRRs) can recognize pathogen-associated molecular patterns and activate downstream signalling pathways, resulting in modulation of host immunity against pathogens. Here, we investigated whether PRR-mediated recognition is involved in host immune responses to the blood-feeding nematode Haemonchus contortus. Methods During blood-feeding, H. contortus secretes immune-modulating antigens into host blood. Therefore, we stimulated sheep peripheral blood mononuclear cells (PBMCs) with H. contortus soluble extract (HcAg) and performed transcriptional profiling. Results HcAg upregulated two genetically linked CLRs (CLEC2L and KLRG2), two NLRs attenuating inflammation (NLRP12 and NLRC3) and one G protein-coupled receptor with potent anti-inflammatory effects (HCAR2). Furthermore, several Th2-related transcription factors (ATF3, IRF4, BCL3 and NFATC) were also upregulated, which may confer anti-inflammatory type 2 immune responses to HcAg. Conclusions Together, our preliminary studies provide new insights into how the host innate immune system controls type 2 immunity to H. contortus. Further work will be needed to identify H. contortus products recognized by the host innate immune system and determine the Th2 polarization ability of these putative PRR ligands
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Combined Effects of Electric Stimulation and Microgrooves in Cardiac Tissue‐on‐a‐Chip for Drug Screening
Animal models and traditional cell cultures are essential tools for drug development. However, these platforms can show striking discrepancies in efficacy and side effects when compared to human trials. These differences can lengthen the drug development process and even lead to drug withdrawal from the market. The establishment of preclinical drug screening platforms that have higher relevancy to physiological conditions is desirable to facilitate drug development. Here, a heart-on-a-chip platform, incorporating microgrooves and electrical pulse stimulations to recapitulate the well-aligned structure and synchronous beating of cardiomyocytes (CMs) for drug screening, is reported. Each chip is made with facile lithographic and laser-cutting processes that can be easily scaled up to high-throughput format. The maturation and phenotypic changes of CMs cultured on the heart-on-a-chip is validated and it can be treated with various drugs to evaluate cardiotoxicity and cardioprotective efficacy. The heart-on-a-chip can provide a high-throughput drug screening platform in preclinical drug development