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In this work, we present a comprehensive re-evaluation of the iron–gallium (FeGa) recombination parameters in silicon using injection-dependent lifetime spectroscopy (IDLS). Ga-doped silicon wafers (of varying resistivities) with precise concentrations of intentional iron contamination in the silicon wafer bulk, through ion implantation and distribution, were used. The presence of interstitial Fei and FeGa, and their lifetime-limiting effects in these silicon wafers, were confirmed through measuring the effective minority carrier lifetime changes during the conditions that are known to cause FeGa dissociation and association. The presence of Fe was also confirmed by deep-level transient spectroscopy. To ensure accurate IDLS analysis of the FeGa defect in silicon, a lifetime linearization scheme was employed to effectively filter out interference by other defects. Error analysis was employed to find the combination of defect parameters that best fit the experimental data and to ascertain the range of uncertainty associated with the IDLS best-fit results. The optimal fitting of the experimental IDLS by Shockley–Read–Hall statistics produced an electron capture cross section σ n = 2.3 × 10 − 14 c m 2 , hole capture cross section σ p = 1.1 × 10 − 14 c m 2 , and a trap energy level E t = E V + 0.2 − 0.01 + 0.02 eV for the FeGa defect in silicon. The extracted defect parameters are also verified by experimentally measuring the crossover point of Fei and FeGa lifetime curves. [ABSTRACT FROM AUTHOR]

The COVID‐19 pandemic was an unparalleled stressor that enhanced isolation. Loneliness has been identified as an epidemic by the US Surgeon General. This study aimed to: (1) characterize longitudinal trajectories of loneliness during the acute phase of the COVID‐19 pandemic; (2) identify longitudinal mediators of the relationship of loneliness with anxiety and depression; and (3) examine how loneliness naturally clusters and identify factors associated with high loneliness. Two hundred and twenty‐nine adults (78% female; mean age = 39.5 ± 13.8) completed an abbreviated version of the UCLA Loneliness Scale, Perceived Stress Scale, Emotion Regulation Questionnaire, State Anxiety Inventory, and Patient Health Questionnaire‐8 longitudinally between April 2020 and 2021. Trajectory analyses demonstrated relatively stable loneliness over time, while anxiety and depression symptoms declined. Longitudinal analyses indicated that loneliness effects on anxiety and depression were both partially mediated by perceived stress, while emotion regulation capacity only mediated effects on anxiety. Three stable clusters of loneliness trajectories emerged (high, moderate, and low). The odds of moderate or high loneliness cluster membership were positively associated with higher perceived stress and negatively associated with greater cognitive reappraisal use. Our results demonstrate the important interconnections between loneliness and facets of mental health throughout the early phases of the pandemic and may inform targeted future interventions for loneliness work. [ABSTRACT FROM AUTHOR]

Eco-driving has garnered considerable research attention owing to its potential socio-economic impact, including enhanced public health and mitigated climate change effects through the reduction of greenhouse gas emissions. With an expectation of more autonomous vehicles (AVs) on the road, an eco-driving strategy in hybrid traffic networks encompassing AV and human-driven vehicles (HDVs) with the coordination of traffic lights is a challenging task. The challenge is partially due to the insufficient infrastructure for collecting, transmitting, and sharing real-time traffic data among vehicles, facilities, and traffic control centers, and the following decision-making of agents involved in traffic control. Additionally, the intricate nature of the existing traffic network, with its diverse array of vehicles and facilities, contributes to the challenge by hindering the development of a mathematical model for accurately characterizing the traffic network. In this study, we utilized the Simulation of Urban Mobility (SUMO) simulator to tackle the first challenge through computational analysis. To address the second challenge, we employed a model-free reinforcement learning (RL) algorithm, proximal policy optimization, to decide the actions of AV and traffic light signals in a traffic network. A novel eco-driving strategy was proposed by introducing different percentages of AV into the traffic flow and collaborating with traffic light signals using RL to control the overall speed of the vehicles, resulting in improved fuel consumption efficiency. Average rewards with different penetration rates of AV (5%, 10%, and 20% of total vehicles) were compared to the situation without any AV in the traffic flow (0% penetration rate). The 10% penetration rate of AV showed a minimum time of convergence to achieve average reward, leading to a significant reduction in fuel consumption and total delay of all vehicles. [ABSTRACT FROM AUTHOR]

Objective Methods Results Interpretation Recombinant monoclonal therapeutic antibodies like lecanemab, which target amyloid beta in Alzheimer's disease, offer a promising approach for modifying the disease progression. Due to its relatively short half‐life, lecanemab administered as a bi‐monthly infusion (typically 10 mg/kg) has a relatively brief half‐life. Interaction with abundant plasma proteins binder in the bloodstream can affect pharmacokinetics of drugs, including their half‐life. In this study, we investigated potential plasma protein binding (PPB) interaction to lecanemab using lecanemab biosimilar.Lecanemab biosimilar used in this study was based on publicly available sequences. ELISA and western blotting were used to assess lecanemab biosimilar immunoreactivity in the fractions of human plasma obtained through size exclusion chromatography. The binding of lecanemab biosimilar to candidate plasma binders was confirmed by western blotting, ELISA, and surface plasmon resonance analysis.Using a combination of equilibrium dialysis, ELISA, and western blotting in human plasma, we first describe the presence of likely PPB partners to lecanemab biosimilar and then identify fibrinogen as one of them. Utilizing surface plasmon resonance, we confirmed that lecanemab biosimilar does bind to fibrinogen, although with lower affinity than to monomeric amyloid beta.In the context of lecanemab therapy, these results imply that fibrinogen levels could impact the levels of free antibodies in the bloodstream and that fibrinogen might serve as a reservoir for lecanemab. More broadly, these results indicate that PPB may be an important consideration when clinically utilizing therapeutic antibodies in neurodegenerative disease. [ABSTRACT FROM AUTHOR]

Vanilla orchids are members of the Vanilloideae orchid subfamily, and they hold significant economic value as a spice crop in tropical regions. Despite the presence of 180 known species within this subfamily, commercial production focuses on only three species (Vanilla planifolia, V. odorata, and V. pompona) and one hybrid (V. × tahitensis), prized for their aromatic qualities and bioactive compounds. Limited modern breeding initiatives have been undertaken with vanilla orchids, although recent advancements in genomic research are shedding light on this crop's potential. The protracted breeding cycle of vanilla, coupled with increasing demand for germplasm, underscores the importance of research and breeding efforts in vanilla. This paper outlines a protocol for haploid production in V. planifolia using unfertilized ovaries in tissue culture conditions. Additionally, we present a methodology to confirm the haploid nature of putative haploid lines through stomatal size comparison, chromosome counting, and flow cytometry analysis, proving the successful development of haploid vanilla plants. These findings contribute to the advancement of breeding programs and genetic improvement strategies for the vanilla industry. [ABSTRACT FROM AUTHOR]

Inspired from quantum Monte Carlo, by sampling discrete and continuous variables at the same time using the Metropolis–Hastings algorithm, we present a novel, fast, and accurate high performance Monte Carlo Parametric Expectation Maximization (MCPEM) algorithm. We named it Randomized Parametric Expectation Maximization (RPEM). We compared RPEM with NONMEM's Importance Sampling Method (IMP), Monolix's Stochastic Approximation Expectation Maximization (SAEM), and Certara's Quasi‐Random Parametric Expectation Maximization (QRPEM) for a realistic two‐compartment voriconazole model with ordinary differential equations using simulated data. We show that RPEM is as fast and as accurate as the algorithms IMP, QRPEM, and SAEM for the voriconazole model in reconstructing the population parameters, for the normal and log‐normal cases. [ABSTRACT FROM AUTHOR]

GAAP provisions in loan contracts specify how to address the effect of accounting changes on financial covenants. I document a pronounced upward trend in and the dominance of frozen‐on‐request (FOR) GAAP provisions, which incorporate accounting changes unless either the borrower or the lender requests a freeze. FOR GAAP streamlines the process of incorporating accounting changes into covenant calculations by obviating the need for renegotiations and prevents opportunistic GAAP freezes by requiring good faith renegotiations. Therefore, FOR GAAP is more likely to incorporate accounting changes beneficial to covenant informativeness, leading to lower false positives (i.e., Type I errors of financial covenant violations) and false negatives (i.e., Type II errors of financial covenant violations). Based on a large sample of loan contracts, I find that FOR GAAP decreases false positives and false negatives after controlling for self‐selection bias and that the decrease is more pronounced when accounting changes relevant to financial covenants are more significant. My study provides new evidence of the role accounting standards and GAAP provisions play in debt contracting efficiency. [ABSTRACT FROM AUTHOR]

2D nanomaterials play a critical role in realizing high‐performance flexible electrodes for wearable energy storge devices, owing to their merits of large surface area, high conductivity and high strength. The electrode is a complex system and the performance is determined by multiple and interrelated factors including the intrinsic properties of materials and the structures at different scales from macroscale to atomic scale. Multiscale design strategies have been developed to engineer the structures to exploit full potential and mitigate drawbacks of 2D materials. Analyzing the design strategies and understanding the working mechanisms are essential to facilitate the integration and harvest the synergistic effects. This review summarizes the multiscale design strategies from macroscale down to micro/nano‐scale structures and atomic‐scale structures for developing 2D nanomaterials‐based flexible electrodes. It starts with brief introduction of 2D nanomaterials, followed by analysis of structural design strategies at different scales focusing on the elucidation of structure‐property relationship, and ends with the presentation of challenges and future prospects. This review highlights the importance of integrating multiscale design strategies. Finding from this review may deepen the understanding of electrode performance and provide valuable guidelines for designing 2D nanomaterials‐based flexible electrodes. [ABSTRACT FROM AUTHOR]

The Escherichia coli TetR-related transcriptional regulator RutR is involved in the coordination of pyrimidine and purine metabolism. Here we report that lysine acetylation modulates RutR function. Applying the genetic code expansion concept, we produced site-specifically lysine-acetylated RutR proteins. The crystal structure of lysine-acetylated RutR reveals how acetylation switches off RutR-DNA-binding. We apply the genetic code expansion concept in E. coli in vivo revealing the consequences of RutR acetylation on the transcriptional level. We propose a model in which RutR acetylation follows different kinetic profiles either reacting non-enzymatically with acetyl-phosphate or enzymatically catalysed by the lysine acetyltransferases PatZ/YfiQ and YiaC. The NAD+-dependent sirtuin deacetylase CobB reverses enzymatic and non-enzymatic acetylation of RutR playing a dual regulatory and detoxifying role. By detecting cellular acetyl-CoA, NAD+ and acetyl-phosphate, bacteria apply lysine acetylation of transcriptional regulators to sense the cellular metabolic state directly adjusting gene expression to changing environmental conditions. The mechanisms underlying adaptation of bacteria to changing environmental conditions remain poorly understood. Here, the authors show bacteria using lysine acetylation of transcriptional regulators to adjust gene expression to changing conditions. [ABSTRACT FROM AUTHOR]

Simple Summary: Cadmium (Cd) is a major aquatic pollutant that can cause toxic effects on aquatic animals, including the economically important clam Meretrix meretrix. A transcriptomic analysis was performed on M. meretrix fertilized eggs, D-shaped larvae, pediveligers, and postlarvae following exposure to Cd2+-containing seawater. A number of genes related to the oxidative stress response were found to be differentially expressed in the fertilized egg and the different larval forms when exposed to Cd2+. These included the CCO, Ndh, HPX, A2M, STF, and pro-C3 genes, and changes in their expression levels in response to Cd2+ exposure were confirmed by qRT-PCR assays. In addition, qRT-PCR also revealed marked changes in the expression of two other oxidative stress-related genes, Nrf2 and MT, in the fertilized egg and different larval forms of M. meretrix in response to Cd2+ exposure. The results suggested that changes in oxidative stress-related genes might be crucial for M. meretrix to cope with the adverse effects of Cd during its development. Cadmium (Cd) is one of the major pollutants in the aquatic environment, and it can easily accumulate in aquatic animals and result in toxic effects by changing the metabolism of the body, causing a serious impact on the immune system, reproductive system, and the development of offspring. The clam Meretrix meretrix is one of the commercially important species that is cultivated in large-scale aquaculture in China. To elucidate the underlying molecular mechanisms of Cd2+ in the developmental processes, fertilized eggs and larvae of M. meretrix at different developmental stages were exposed to Cd2+ (27.2 mg L−1 in natural seawater) or just natural seawater without Cd2+ (control), and high-throughput transcriptome sequencing and immunohistochemistry techniques were used to analyze the toxic effects of Cd on larvae at different early developmental stages. The results revealed 31,914 genes were differentially expressed in the different stages of M. meretrix development upon treatment with Cd2+. Ten of these genes were differentially expressed in all stages of development examined, but they comprised only six unigenes (CCO, Ndh, HPX, A2M, STF, and pro-C3), all of which were related to the oxidative stress response. Under Cd exposure, the expression levels of CCO and Ndh were significantly upregulated in D-shaped and pediveliger larvae, while pro-C3 expression was significantly upregulated in the fertilized egg, D-shaped larva, and pediveliger. Moreover, HPX, A2M, and STF expression levels in the fertilized egg and pediveliger larvae were also significantly upregulated. In contrast, CCO, Ndh, HPX, A2M, STF, and pro-C3 expression levels in the postlarva were all downregulated under Cd exposure. Besides the genes with changes in expression identified by the transcriptome, the expression of two other oxidative stress-related genes (MT and Nfr2) was also found to change significantly in the different developmental stages of M. meretrix upon Cd exposure, confirming their roles in combating oxidative stress. Overall, the findings of this study indicated that Cd would interfere with cellular respiration, ion transport, and immune response through inducing oxidative stress, and changes in the expression of oxidative stress-related genes might be an important step for M. meretrix to deal with the adverse effects of Cd at different stages of its development. [ABSTRACT FROM AUTHOR]

The article examines the impact of algorithms, particularly those driven by artificial intelligence (AI), on merger control. It acknowledges the benefits algorithms bring to decision-making processes in various industries but highlights concerns about their potential to facilitate anticompetitive behavior, especially in merger contexts. It argues that while algorithms offer benefits like cost savings and precision, they can also exacerbate market power and anticompetitive conduct.