Spectroscopy-Guided Deep Learning Predicts Solid-Liquid Surface Adsorbate Properties in Unseen Solvents.

Accurately and rapidly acquiring the microscopic properties of a material is crucial for catalysis and electrochemistry. Characterization tools, such as spectroscopy, can be a valuable tool to infer these properties, and when combined with machine learning tools, they can theoretically achieve fast and accurate prediction results. However, on the path to practical applications, training a reliable machine learning model is faced with the challenge of uneven data distribution in a vast array of non-negligible solvent types. Herein, we employ a combination of the first-principles-based approach and data-driven model. Specifically, we utilize density functional theory (DFT) to calculate theoretical spectral data of CO-Ag adsorption in 23 different solvent systems as a data source. Subsequently, we propose a hierarchical knowledge extraction multiexpert neural network (HMNN) to bridge the knowledge gaps among different solvent systems. HMNN undergoes two training tiers: in tier I, it learns fundamental quantitative spectra-property relationships (QSPRs), and in tier II, it inherits the fundamental QSPR knowledge from previous steps through a dynamic integration of expert modules and subsequently captures the solvent differences. The results demonstrate HMNN's superiority in estimating a range of molecular adsorbate properties, with an error range of less than 0.008 eV for zero-shot predictions on unseen solvents. The findings underscore the usability, reliability, and convenience of HMNN and could pave the way for real-time access to microscopic properties by exploiting QSPR.

Small G-Protein Rheb Gates Mammalian Target of Rapamycin Signaling to Regulate Morphine Tolerance in Mice.

BACKGROUND: Analgesic tolerance due to long-term use of morphine remains a challenge for pain management. Morphine acts on µ-opioid receptors and downstream of the phosphatidylinositol 3-kinase signaling pathway to activate the mammalian target of rapamycin (mTOR) pathway. Rheb is an important regulator of growth and cell-cycle progression in the central nervous system owing to its critical role in the activation of mTOR. The hypothesis was that signaling via the GTP-binding protein Rheb in the dorsal horn of the spinal cord is involved in morphine-induced tolerance. METHODS: Male and female wild-type C57BL/6J mice or transgenic mice (6 to 8 weeks old) were injected intrathecally with saline or morphine twice daily at 12-h intervals for 5 consecutive days to establish a tolerance model. Analgesia was assessed 60 min later using the tail-flick assay. After 5 days, the spine was harvested for Western blot or immunofluorescence analysis. RESULTS: Chronic morphine administration resulted in the upregulation of spinal Rheb by 4.27 ± 0.195-fold (P = 0.0036, n = 6), in turn activating mTOR by targeting rapamycin complex 1 (mTORC1). Genetic overexpression of Rheb impaired morphine analgesia, resulting in a tail-flick latency of 4.65 ± 1.10 s (P < 0.0001, n = 7) in Rheb knock-in mice compared to 10 s in control mice (10 ± 0 s). Additionally, Rheb overexpression in spinal excitatory neurons led to mTORC1 signaling overactivation. Genetic knockout of Rheb or inhibition of mTORC1 signaling by rapamycin potentiated morphine-induced tolerance (maximum possible effect, 52.60 ± 9.56% in the morphine + rapamycin group vs. 16.60 ± 8.54% in the morphine group; P < 0.0001). Moreover, activation of endogenous adenosine 5'-monophosphate-activated protein kinase inhibited Rheb upregulation and retarded the development of morphine-dependent tolerance (maximum possible effect, 39.51 ± 7.40% in morphine + metformin group vs. 15.58 ± 5.79% in morphine group; P < 0.0001). CONCLUSIONS: This study suggests spinal Rheb as a key molecular factor for regulating mammalian target of rapamycin signaling.

Programmed cell death 4 governs NLRP3-mediated pyroptosis in septic lung disorders.

INTRODUCTION: Sepsis is a pathogenic syndrome of prolonged excessive inflammation and immunosuppression produced by invading pathogens. Programmed cell death 4 (PDCD4) may be implicated in a range of inflammatory lesions, and this study aimed to confirm the involvement of PDCD4 in septic lung injury. MATERIALS AND METHODS: Mice and bronchial epithelial 16HBE cells were separately subjected to CLP and LPS to generate in vivo and in vitro models. Following the level of PDCD4 was determined, the impacts of PDCD4 knockdown on mouse lung injury degree, inflammation, apoptosis, and pyroptosis levels were evaluated. Afterward, cells were treated with the NLRP3 agonist, and the influences of NLRP3 activation on the regulations of PDCD4 knockdown were determined. RESULTS: PDCD4 was elevated following mice developed septic lung injury, PDCD4 knockdown ameliorated septic lung injury and reduced lung inflammation and apoptosis. Moreover, PDCD4 knockdown suppressed NLRP3-mediated pyroptosis, indicating that PDCD4 also mediated pyroptosis. According to cellular models, NLRP3 activation broke the effects of PDCD4 knockdown on cells. CONCLUSIONS: The current study reveals that PDCD4 governs NLRP3-mediated pyroptosis in septic lung injury. PDCD4 is not only related to apoptosis and expands the knowledge of PDCD4 regulation of different cell death modes.

Comparative brain-wide mapping of ketamine- and isoflurane-activated nuclei and functional networks in the mouse brain.

Ketamine (KET) and isoflurane (ISO) are two widely used general anesthetics, yet their distinct and shared neurophysiological mechanisms remain elusive. In this study, we conducted a comparative analysis of the effects of KET and ISO on c-Fos expression across the mouse brain, utilizing hierarchical clustering and c-Fos-based functional network analysis to evaluate the responses of individual brain regions to each anesthetic. Our findings reveal that KET activates a wide range of brain regions, notably in the cortical and subcortical nuclei involved in sensory, motor, emotional, and reward processing, with the temporal association areas (TEa) as a strong hub, suggesting a top-down mechanism affecting consciousness by primarily targeting higher order cortical networks. In contrast, ISO predominantly influences brain regions in the hypothalamus, impacting neuroendocrine control, autonomic function, and homeostasis, with the locus coeruleus (LC) as a connector hub, indicating a bottom-up mechanism in anesthetic-induced unconsciousness. KET and ISO both activate brain areas involved in sensory processing, memory and cognition, reward and motivation, as well as autonomic and homeostatic control, highlighting their shared effects on various neural pathways. In conclusion, our results highlight the distinct but overlapping effects of KET and ISO, enriching our understanding of the mechanisms underlying general anesthesia.

Broad Complex-Z2 directly activates BmMBF2 to inhibit the silk protein synthesis in the silkworm, Bombyx mori.

Silk proteins, as natural macromolecules, have extensive applications in biomaterials and biomedicine. In the silkworm, the expression of silk protein genes is negatively associated with ecdysone during the molt stage, while it is positively correlated with juvenile hormone during the intermolt stage. In our previous study, overexpression of an isoform Z2 of Broad Complex (BmBrC-Z2), an ecdysone early response factor, significantly reduced the expression of silk protein genes. However, the underlying regulatory mechanism remains unclear. In this study, we conducted transcriptomic analysis and found that overexpressing BmBrC-Z2 significantly upregulated the expression level of multiprotein bridging factor 2 (BmMBF2), an inhibitor of fibroin heavy chain (FibH). Further investigations revealed that BmBrC-Z2 directly regulated BmMBF2 by binding to cis-regulatory elements, as demonstrated using Dual-Luciferase Reporter Gene Assay, EMSA, and ChIP-PCR assay. Additionally, when using the CRISPR/Cas9 system to knock out BmMBF2, silk protein genes were significantly upregulated during the molt stage of mutant larvae. These findings uncover the negative regulation of silk protein synthesis by the ecdysone signaling cascade, specifically through the manipulation of BmMBF2 expression during the molt stage. This study enhances to our understanding of the temporal regulatory mechanism governing silk protein synthesis and offers a potential strategy for improving silk yield.