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The electric vehicle (EV) can be utilized as a dynamically configurable dispersed energy storage in the vehicle-to-building (V2B) operation mode to balance the energy demand. To enable efficient V2B integration, we propose a collaborative decision model to cooperatively operate building and EVs. A commercial building (medium office building) which has thermal and electric storage system, combine cooling, heating, and power system, and photovoltaic (PV) panel is assumed to be interconnected with a EV charging station which has its own PV panel. A multi-objective mixed integer linear programming (MILP) problem is formulated to study the energy exchange between the building and the EV charging station to minimize the operational cost for the building and the EV charging station simultaneously. A set of binary variables are introduced to model the EV's behaviors, such as entering, connecting to, or leaving the charging station. We employ a weighted sum approach to solve the multi-objective MILP to obtain Pareto operation decisions for trade-off analysis between the building and the charging station. Our experimental results demonstrate that the collaborative V2B integration can significantly reduce the operation cost for both the building and the charging station comparing to the non-cooperative strategy where the building and the charging station are operated separately. [ABSTRACT FROM AUTHOR]

• Profit allocation in local transaction is compared for both non-/cooperative games. • Bargaining solution is Shapley value if bargaining power is marginal contribution. • Selfish leader could take away 89% of collective benefit by internal arbitraging. • Max social welfare & fairer profit allocation can be achieved with uniform price. With the increasing integration of distributed energy resources, localized peer-to-peer energy transactions are receiving more attention since they could absorb more distributed renewables locally and stabilize the power grid. To better study the trading behavior and provide guidance for a viable local market design, different game-theoretical frameworks including cooperative and non-cooperative games are established and compared in this study. For the cooperative grand coalition, the maximum social welfare is guaranteed, the Shapley value and bargaining based approaches are implemented for further profit redistribution. It is shown that the asymmetrical bargaining power can be critical in the final payment clearing and it is equivalent to the Shapley value allocation if prosumers bargain based on their marginal contributions. Non-cooperative trading is formulated by using a Stackelberg bilevel model in which the upper level has the privilege in internal price setting. However, system optimum is not obtained due to competition, and the selfish leader could take away 89% of the collective benefit by price-gap based arbitraging. Aiming for a long-lasting trading market, a virtual benevolent leader and a uniform price structure in which purchase price equals selling price are tested. Experimental results indicate that maximum social welfare and a fairer profit allocation can be achieved with a uniform price structure, regardless of the selfish or benevolent attitude. [ABSTRACT FROM AUTHOR]

Each pluripotent stem cell line has a physical entity as well as a digital phenotype, but linking the two unambiguously is confounded by poor naming practices and assumed knowledge. Registration gives each line a unique and persistent identifier that links to phenotypic data generated over the lifetime of that line. Registration is a key recommendation of the 2023 ISSCR Standards for the use of human stem cells in research. Here we consider how community adoption of stem cell line registration could facilitate the establishment of integrated digital phenotypes of specific human pluripotent stem cell (hPSC) lines., Competing Interests: Declaration of interests A.K. is the coordinator of the Horizon Europe-funded registry hPSCreg, and C.A.W. is head of the Phenomics Australia-funded Australian stem cell registry. T.E.L. is a co-inventor and receives a share of royalties on various hPSC media and culture-related patents currently held and licensed by the Wisconsin Alumni Research Foundation., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Many methods using liquid chromatography-mass spectrometry (LC-MS) have been established for identifying residual host cell proteins (HCPs) to aid in the process development and quality control of therapeutic proteins. However, the use of MS-based techniques for adeno-associated virus (AAV) is still in its infancy, with few methods reported and minimal information available on potentially problematic HCPs. In this study, we developed a highly sensitive and effective differential digestion method to profile residual HCPs in AAV. Unlike direct digestion, which completely digests both AAV and HCPs, our differential digestion method takes advantage of AAV's unique characteristics to maintain the integrity of AAV while preferentially digesting HCPs under denaturing and reducing conditions. This differential digestion method requires only several micrograms of sample and significantly enhances the identification of HCPs. Furthermore, this method can be applied to all five different AAV serotypes for comprehensive HCP profiling. Our work fills a gap in AAV HCP analysis by providing a sensitive and robust strategy for detecting, monitoring, and measuring HCPs., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Large-scale kinetic models provide the computational means to dynamically link metabolic reaction fluxes to metabolite concentrations and enzyme levels while also conforming to substrate level regulation. However, the development of broadly applicable frameworks for efficiently and robustly parameterizing models remains a challenge. Challenges arise due to both the heterogeneity, paucity, and difficulty in obtaining flux and/or concentration data but also due to the computational difficulties of the underlying parameter identification problem. Both the computational demands for parameterization, degeneracy of obtained parameter solutions and interpretability of results has so far limited widespread adoption of large-scale kinetic models despite their potential. Herein, we introduce the Kinetic Estimation Tool Capturing Heterogeneous Datasets Using Pyomo (KETCHUP), a flexible parameter estimation tool that leverages a primal-dual interior-point algorithm to solve a nonlinear programming (NLP) problem that identifies a set of parameters capable of recapitulating the (non)steady-state fluxes and concentrations in wild-type and perturbed metabolic networks. KETCHUP is benchmarked against previously parameterized large-scale kinetic models demonstrating an at least an order of magnitude faster convergence than the tool K-FIT while at the same time attaining better data fits. This versatile toolbox accepts different kinetic descriptions, metabolic fluxes, enzyme levels and metabolite concentrations, under either steady-state or instationary conditions to enable robust kinetic model construction and parameterization. KETCHUP supports the SBML format and can be accessed at https://github.com/maranasgroup/KETCHUP., (Copyright © 2024 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.)

The parameterization of kinetic models requires measurement of fluxes and/or metabolite levels for a base strain and a few genetic perturbations thereof. Unlike stoichiometric models that are mostly invariant to the specific strain, it remains unclear whether kinetic models constructed for different strains of the same species have similar or significantly different kinetic parameters. This important question underpins the applicability range and prediction limits of kinetic reconstructions. To this end, herein we parameterize two separate large-scale kinetic models using K-FIT with genome-wide coverage corresponding to two distinct strains of Saccharomyces cerevisiae: CEN.PK 113-7D strain (model k-sacce306-CENPK), and growth-deficient BY4741 (isogenic to S288c; model k-sacce306-BY4741). The metabolic network for each model contains 306 reactions, 230 metabolites, and 119 substrate-level regulatory interactions. The two models (for CEN.PK and BY4741) recapitulate, within one standard deviation, 77% and 75% of the fitted dataset fluxes, respectively, determined by 13 C metabolic flux analysis for wild-type and eight single-gene knockout mutants of each strain. Strain-specific kinetic parameterization results indicate that key enzymes in the TCA cycle, glycolysis, and arginine and proline metabolism drive the metabolic differences between these two strains of S. cerevisiae. Our results suggest that although kinetic models cannot be readily used across strains as stoichiometric models, they can capture species-specific information through the kinetic parameterization process., Competing Interests: Declaration of competing interest The authors declare no commercial or financial conflict of interest., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

High molecular weight (HMW) species are product-related variants that may impact therapeutic product safety and efficacy. Therefore, HMW species and aggregates are considered critical quality attributes and their levels should be closely monitored and controlled during drug development, commercial manufacturing, and shelf-life storage period for therapeutic monoclonal antibody drug products. Various biophysical and analytical methods have been developed to characterize the HMW species to understand their mechanisms of formation and assess potential product risk. However, host cell protein (HCP) analysis has seldom been conducted to characterize the impurities in aggregates. In this work, HCP analysis of enriched HMW species and drug substance (DS) from five different monoclonal antibodies (mAbs) was performed. More HCPs are identified in the enriched HMW than in the DS, thus demonstrating a potential interaction between HCPs and HMW. Certain HCPs, including commonly detected HCPs and problematic HCPs, were enriched in HMW fractions. Especially, the most abundant HCP from mAb1, CC motif chemokine, was 46 times more abundant in enriched HMW than DS. The enriched HMW was further fractionated into enriched dimers and enriched very HMW (vHMW) fractions. The CC motif chemokine was found to interact mainly with mAb1 dimer species rather than vHMW fraction. Removing the HMW species from mAb1 significantly decreased the CC motif chemokine level in the final mAb1 DS. Our findings demonstrate that some HCPs are more preferentially bound to HMW species and this finding may provide a new opportunity for removing HCPs in downstream purification steps., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: [Mengqi Hu, Rosalynn Molden, Yunli Hu, Yu Huang, Haibo Qiu, Ning Li has patent pending to Regeneron Pharmaceuticals.]., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

The evaluation of regional water resource carrying capacity has been repeatedly conducted to provide a scientific basis for the local water resource management and the sustainable development, in particular in the water-limited regions. However, the definition of regional water resource carrying capacity and its evaluation method are still arguable. Through a case study of Inner Mongolia, located in the arid and semi-arid northern China, this paper developed an improved method to calculate regional water resource carrying capacity by the combination of the water supply-demand analysis and the S-shaped curve threshold analysis. The spatial and temporal patterns of the regional water resource carrying capacity in Inner Mongolia during 2000-2019 was evaluated at three scales, namely the province scale, the basin scale and the city scale. The results showed that the average regional water resource carrying capacity of the whole province was 0.25 (the full mark is 1.00); at the basin scale, the Yellow River Basin had the lowest regional water resource carrying capacity (0.17) among all the basins, showing that the utilization of the water resources was unreasonable; at the city scale, the average regional water resource carrying capacities in Hulunbuir and Xilingol were both over 0.25, while those in Alxa, BayanNur and Wuhai were below 0.1; Hulunbuir had 25.48 billion m 3 water surplus, while BayanNur suffered from an average water deficit of 4.51 billion m 3 from 2000 to 2019. This paper has provided a reasonable way to measure the regional water resource carrying capacity using an improved method by incorporating S-shaped curve threshold analysis, which may have a wider application for the clustering and optimization of regional water management. In addition, the spatial and temporal patterns of regional water carrying capacity are beneficial for policymakers in the implementation of the effective water usage., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

In this work, a novel structural series of brain-penetrant GluN2B NMDAR antagonists were designed, synthesized and biologically evaluated as anti-stroke therapeutic agents via merging the structures of NBP and known GluN2B ligands. Approximately half of them exhibited superior neuroprotective activity to NBP against NMDA-induced neurotoxicity in hippocampal neurons at 10 μM, and compound 45e and 45f exerted equipotent activity to ifenprodil, an approved GluN2B- selective NMDAR antagonist. In particular, 45e, with the most potent neuroprotective activity throughout this series, displayed dramatically enhanced activity (K i  = 3.26 nM) compared to ifenprodil (K i  = 14.80 nM) in Radioligand Competitive Binding Assay, and remarkable inhibition (IC 50  = 79.32 nM) against GluN1/GluN2B receptor-mediated current in Patch Clamp Assay. Meanwhile, 45e and its enantiomers exhibited low inhibition rate against the current mediated by other investigated receptors at the concentration of 10 μM, indicating their favorable selectivity for GluN1/GluN2B. In the rat model of middle cerebral artery ischemia (MCAO), 45e exerted comparable therapeutic efficacy to ifenprodil at the same dosage. In addition to the attractive in vitro and in vivo potency, 45e displayed a favorable bioavailability (F = 63.37%) and an excellent brain exposure. In further repeated dose toxicity experiments, compound 45e demonstrated an acceptable safety profile. With the above merits, 45e is worthy of further functional investigation as a novel anti-stroke therapeutic agent., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021. Published by Elsevier Masson SAS.)

Legionella pneumophila is a waterborne bacterium known for causing Legionnaires' Disease, a severe pneumonia. Cooling towers are a major source of outbreaks, since they provide ideal conditions for L. pneumophila growth and produce aerosols. In such systems, L. pneumophila typically grow inside protozoan hosts. Several abiotic factors such as water temperature, pipe material and disinfection regime affect the colonization of cooling towers by L. pneumophila. The local physical and biological factors promoting the growth of L. pneumophila in water systems and its spatial distribution are not well understood. Therefore, we built a lab-scale cooling tower to study the dynamics of L. pneumophila colonization in relationship to the resident microbiota and spatial distribution. The pilot was filled with water from an operating cooling tower harboring low levels of L. pneumophila. It was seeded with Vermamoeba vermiformis, a natural host of L. pneumophila, and then inoculated with L. pneumophila. After 92 days of operation, the pilot was disassembled, the water was collected, and biofilm was extracted from the pipes. The microbiome was studied using 16S rRNA and 18S rRNA genes amplicon sequencing. The communities of the water and of the biofilm were highly dissimilar. The relative abundance of Legionella in water samples reached up to 11% whereas abundance in the biofilm was extremely low (≤0.5%). In contrast, the host cells were mainly present in the biofilm. This suggests that L. pneumophila grows in host cells associated with biofilm and is then released back into the water following host cell lysis. In addition, water temperature shaped the bacterial and eukaryotic community of the biofilm, indicating that different parts of the systems may have different effects on Legionella growth., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2019 Elsevier B.V. All rights reserved.)