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Chronic activation of microglia is a driving factor in the progression of neuroinflammatory diseases, and mechanisms that regulate microglial inflammatory signaling are potential targets for novel therapeutics. Regulator of G protein Signaling 10 is the most abundant RGS protein in microglia, where it suppresses inflammatory gene expression and reduces microglia-mediated neurotoxicity. In particular, microglial RGS10 downregulates the expression of pro-inflammatory mediators including cyclooxygenase 2 (COX-2) following stimulation with lipopolysaccharide (LPS). However, the mechanism by which RGS10 affects inflammatory signaling is unknown and is independent of its canonical G protein targeted mechanism. Here, we sought to identify non-canonical RGS10 interacting partners that mediate its anti-inflammatory mechanism. Through RGS10 co-immunoprecipitation coupled with mass spectrometry, we identified STIM2, an endoplasmic reticulum (ER) localized calcium sensor and a component of the store-operated calcium entry (SOCE) machinery, as a novel RGS10 interacting protein in microglia. Direct immunoprecipitation experiments confirmed RGS10-STIM2 interaction in multiple microglia and macrophage cell lines, as well as in primary cells, with no interaction observed with the homologue STIM1. We further determined that STIM2, Orai channels, and the calcium-dependent phosphatase calcineurin are essential for LPS-induced COX-2 production in microglia, and this pathway is required for the inhibitory effect of RGS10 on COX-2. Additionally, our data demonstrated that RGS10 suppresses SOCE triggered by ER calcium depletion and that ER calcium depletion, which induces SOCE, amplifies pro-inflammatory genes. In addition to COX-2, we also show that RGS10 suppresses the expression of pro-inflammatory cytokines in microglia in response to thrombin and LPS stimulation, and all of these effects require SOCE. Collectively, the physical and functional links between RGS10 and STIM2 suggest a complex regulatory network connecting RGS10, SOCE, and pro-inflammatory gene expression in microglia, with broad implications in the pathogenesis and treatment of chronic neuroinflammation.

Two-pore channels (TPCs) are a ubiquitous family of cation channels that localize to acidic organelles in animals and plants to regulate numerous Ca2+-dependent events. Little is known about TPCs in unicellular organisms despite their ancient origins. Here, we characterize a TPC from Toxoplasma gondii, the causative agent of toxoplasmosis. TgTPC is a member of a novel clad of TPCs in Apicomplexa, distinct from previously identified TPCs and only present in coccidians. We show that TgTPC localizes not to acidic organelles but to the apicoplast, a non-photosynthetic plastid found in most apicomplexan parasites. Conditional silencing of TgTPC resulted in progressive loss of apicoplast integrity, severely affecting growth and the lytic cycle. Isolation of TPC null mutants revealed a selective role for TPCs in replication independent of apicoplast loss that required conserved residues within the pore-lining region. Using a genetically-encoded Ca2+ indicator targeted to the apicoplast, we show that Ca2+ signals deriving from the ER but not from the extracellular space are selectively transmitted to the lumen. Deletion of the TgTPC gene caused reduced apicoplast Ca2+ uptake and membrane contact site formation between the apicoplast and the ER. Fundamental roles for TPCs in maintaining organelle integrity, inter-organelle communication and growth emerge.

This study aimed to characterize the population pharmacokinetics of sertraline in Mexican patients with psychiatric and substance use disorders. Fifty‐nine patients (13 to 76 years old) treated with doses of sertraline between 12.5 and 100 mg/day were included. Plasma sertraline concentrations were determined in blood samples and five of the main substances of abuse were determined by rapid tests in urine samples. Demographic, clinical, and pharmacogenetic factors were also evaluated. Population pharmacokinetic analysis was performed using NONMEM software with first‐order conditional estimation method. A one‐compartment model with proportional residual error adequately described the sertraline concentrations versus time. CYP2D6*2 polymorphism and CYP2C19 phenotypes significantly influenced sertraline clearance, which had a population mean value of 66 L/h in the final model. The absorption constant and volume of distribution were fixed at 0.855 1/h and 20.2 L/kg, respectively. The model explained 11.3% of the interindividual variability in sertraline clearance. The presence of the CYP2D6*2 polymorphism caused a 23.1% decrease in sertraline clearance, whereas patients with intermediate and poor phenotype of CYP2C19 showed 19.06% and 48.26% decreases in sertraline clearance, respectively. The model was internally validated by bootstrap and visual predictive check. Finally, stochastic simulations were performed to propose dosing regimens to achieve therapeutic levels that contribute to improving treatment response. [ABSTRACT FROM AUTHOR]

Climate change, primarily driven by human activities such as burning fossil fuels, is causing significant long-term changes in temperature and weather patterns. To mitigate these impacts, there is an increased focus on renewable energy sources. However, optimizing power consumption through effective usage control and waste recycling also offers substantial potential for reducing energy demands. This study explores non-intrusive load monitoring (NILM) to estimate disaggregated energy consumption from a single household meter, leveraging advancements in deep learning such as convolutional neural networks. The study uses the UK-DALE dataset to extract and plot power consumption data from the main meter and identify five household appliances. Convolutional neural networks (CNNs) are trained with transfer learning using VGG16 and MobileNet. The models are validated, tested on split datasets, and combined using ensemble methods for improved performance. A new voting scheme for ensembles is proposed, named weighted average confidence voting (WeCV), and it is used to create combinations of the best 3 and 5 models and applied to NILM. The base models achieve up to 97% accuracy. The ensemble methods applying WeCV show an increased accuracy of 98%, surpassing previous state-of-the-art results. This study shows that CNNs with transfer learning effectively disaggregate household energy use, achieving high accuracy. Ensemble methods further improve performance, offering a promising approach for optimizing energy use and mitigating climate change. [ABSTRACT FROM AUTHOR]

A sensitive and rapid ultra-performance liquid chromatography coupled with -tandem mass spectrometry (UPLC-MS/MS) method was developed and validated to determine ceftibuten (CTB) and sulbactam (SUL) in human plasma. An ACQUITY UPLC HSS T3 C18 (2.1 × 100 mm), 1.8 μm column with gradient elution of water (0.1% formic acid) and acetonitrile was used for separation at a flow rate of 0.2 mL/min. This method involves a simple sample preparation with acetonitrile. The calibration curves of CTB and SUL in plasma showed good linearity over the concentration range of 0.50–25 μg/mL and with a correlation coefficient (r 2) >0.99. This method was validated in terms of selectivity, linearity, precision, accuracy and stability. High precision was obtained with coefficients of variation <15%. Excellent recovery in the range of 90–104% was achieved for CTB and SUL was 86–110%. The method has the potential utility to support pharmacometric modeling in clinical practice and biopharmaceutic studies. [ABSTRACT FROM AUTHOR]

The membranization of membrane‐less coacervates paves the way for the exploitation of complex protocells with regard to structural and cell‐like functional behaviors. However, the controlled transformation from membranized coacervates to vesicles remains a challenge. This can provide stable (multi)phase and (multi)compartmental architectures through the reconfiguration of coacervate droplets in the presence of (bioactive) polymers, bio(macro)molecules and/or nanoobjects. Herein, we present a continuous protocell transformation from membrane‐less coacervates to membranized coacervates and, ultimately, to giant hybrid vesicles. This transformation process is orchestrated by altering the balance of non‐covalent interactions through varying concentrations of an anionic terpolymer, leading to dynamic processes such as spontaneous membranization of terpolymer nanoparticles at the coacervate surface, disassembly of the coacervate phase mediated by the excess anionic charge, and the redistribution of coacervate components in membrane. The diverse protocells during the transformation course provide distinct structural features and molecular permeability. Notably, the introduction of multiphase coacervates in this continuous transformation process signifies advancements toward the creation of synthetic cells with different diffusible compartments. Our findings emphasize the highly controlled continuous structural reorganization of coacervate protocells and represents a novel step toward the development of advanced and sophisticated synthetic protocells with more precise compositions and complex (membrane) structures. [ABSTRACT FROM AUTHOR]