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Glycolysis is a fundamental metabolic pathway for glucose catabolism across biology, and glycolytic enzymes are among the most abundant proteins in cells. Their expression at such levels provides a particular challenge. Here we demonstrate that the glycolytic mRNAs are localized to granules in yeast and human cells. Detailed live cell and smFISH studies in yeast show that the mRNAs are actively translated in granules, and this translation appears critical for the localization. Furthermore, this arrangement is likely to facilitate the higher level organization and control of the glycolytic pathway. Indeed, the degree of fermentation required by cells is intrinsically connected to the extent of mRNA localization to granules. On this basis, we term these granules, core fermentation (CoFe) granules; they appear to represent translation factories, allowing high-level coordinated enzyme synthesis for a critical metabolic pathway.Concerns regarding increased antibiotic resistance arising from the emergent properties of biofilms have spurred interest in the discovery of novel antibiotic agents and techniques to directly estimate metabolic activity in biofilms. Although a number of methods have been developed to quantify biofilm formation, real-time quantitative assessment of metabolic activity in label-free biofilms remains a challenge. Production of electrical current via extracellular electron transport (EET) has recently been found in pathogens and appears to correlate with their metabolic activity. Accordingly, monitoring the production of electrical currents as an indicator of cellular metabolic activity in biofilms represents a new direction for research aiming to assess and screen the effects of antimicrobials on biofilm activity. In this article, we reviewed EET-capable pathogens and the methods to monitor biofilm activity to discuss advantages of using the capability of pathogens to produce electrical currents and effective combination of these methods. Moreover, we discussed EET mechanisms by pathogenic and environmental bacteria and open questions for the physiological roles of EET in pathogen's biofilm. The present limitations and possible future directions of in situ biofilm metabolic activity assessment for large-scale screening of antimicrobials are also discussed.Electroacupuncture (EA) has been accepted to effectively relieve neuropathic pain. Current knowledge of its neural modulation mainly covers the spinal cord and subcortical nuclei, with little evidence from the cortical regions. Using in vivo two-photon imaging in mice with chronic constriction injury, we found that EA treatment systemically modulated the Ca2+ activity of neural circuits in the primary somatosensory cortex, including the suppression of excitatory pyramidal neurons, potentiation of GABAergic somatostatin-positive interneurons, and suppression of vasoactive intestinal peptide-positive interneurons. [https://www.selleckchem.com/products/atuzabrutinib.html learn more] Furthermore, EA-mediated alleviation of pain hypersensitivity and cortical modulation were dependent on the activation of endocannabinoid receptor 1. These findings collectively reveal a cortical circuit involved in relieving mechanical or thermal hypersensitivity under neuropathic pain and identify one molecular pathway directing analgesic effects of EA.Metal-organic frameworks (MOFs) are multifunctional materials with a unique advantage of high porosity and surface area and size tunability and can be modified without altering the topology. The interesting and desirable properties of MOFs led to their exploration for the triboelectric nanogenerator. Herein, a biodegradable MOF MIL-88A for TENG (MIL-TENG) is reported. MIL-88A can be easily synthesized by coordinating iron chloride and fumaric acid in water, thus offering eco-friendly synthesis. Various materials are selected as opposite layers to MIL-88A to analyze triboelectric behavior and performance. The MIL-TENG exhibits an output trend of TENGEC less then TENGKapton less then TENGFEP. The MIL-88A and FEP generated an output voltage of 80 V and an output current of 2.2 μA. The surface potential measurement and electrical output trend suggest the positive triboelectric behavior of MIL-88A concerning FEP and Kapton. The utilization of biomechanical motions and numerous low-rating electronics powered via a capacitor are demonstrated.Brain organoids closely recapitulate many features and characteristics of in vivo brain tissue. This technology in turn allows unprecedented possibilities to investigate brain development and function in the dish. Several brain organoid protocols have been established, and the studies have focused on validating the architecture, cellular composition, and function of the organoids. In future, the improved and advanced organoid models will enable us to understand cellular and molecular features of the developing brain. However, several obstacles, such as the quality of the organoids, 3D structural analysis, and measurement of the neural connectivity need to be improved. In this perspective, we will provide an overview of the current state of the art of the brain organoid field, with a focus on protocols and organoid characterization. Additionally, we will address the current limitations of this evolving field and provide an understanding of the current brain organoid landscape and insight toward the next steps.Lithium-ion battery technologies have conquered the current energy storage market as the most preferred choice thanks to their development in a longer lifetime. However, choosing the most suitable battery aging modeling methodology based on investigated lifetime characterization is still a challenge. In this work, a comprehensive aging dataset of nickel-manganese-cobalt oxide (NMC) cell is used to develop and/or train different capacity fade models to compare output responses. The assessment is conducted for semi-empirical modeling (SeM) approach against a machine learning model and an artificial neural network model. Among all, the nonlinear autoregressive network (NARXnet) can predict the capacity degradation most precisely minimizing the computational effort as well. This research work signifies the importance of lifetime methodological choice and model performance in understanding the complex and nonlinear Li-ion battery aging behavior.