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Functionalization of magnetic TMU-17-NH2 MOF with organic ligands for stabilization of copper species as an efficient heterogeneous catalyst for the Biginelli reaction and the synthesis of pyran derivatives
PERK orchestrates an endoplasmic reticulum stress alternative splicing program via CLK1/SRSF1
Abstract The unfolded protein response (UPR) is a critical adaptive program triggered upon cellular stresses that profoundly reshapes the transcriptome and translatome. In the very first minutes of cellular stress, translation blockage, RNA decay and RNA granules formation prompt the synthesis of proteins essential to the stress response. Due to the dynamic nature of these processes, investigating translation upon stress has proven to be challenging; therefore, our understanding of these mechanisms and translatome rewiring upon stress remains limited. Here, we exploit O-Propargyl-puromycin (OPP) labelling of de novo peptides followed by LC-MS/MS to identify de novo proteins translated upon endoplasmic reticulum (ER) stress. Combined with transcriptomic analyses, our approach reveals that ER stress profoundly impacts the synthesis of core splicing factor proteins leading to a significant reshaping of the splicing landscape. We identify a signature of seven splicing events consistently occurring in mammalian cells exposed to ER stress. Using pharmacological, genetic, phosphoproteomic and sequencing approaches, we demonstrate that this specific signature is driven by PERK activation and is dependent on the axis CLK1/SRSF1. Our findings identify PERK/CLK1/SRSF1 -mediated splicing regulation as a new facet of ER stress, defining an ER i-splice signature spanning healthy and malignant tissues.
Life-cycle sustainability assessment of public general hospital buildings in China
Electron-rich dianion vacancies boost diazenide intermediates for efficient chemical looping ammonia synthesis
Novel image-free arc detection method for pantograph–catenary systems based on direct DWT–ANN signal analysis
Abstract Arc faults in pantograph catenary systems pose a significant threat to the reliability, safety, and efficiency of the electric railways. However, Conventional approaches relying on image processing and deep learning are hindered in real-time applications due to computational delays exceeding the arc time constant. Therefore, this study proposes a novel image-free arc detection method that directly analyzes measured traction current signals using DWT–ANN (Discrete Wavelet Transform-Artificial Neural Networks). The significance of this work lies in its ability to extract transient arc features directly from the traction current waveform, providing a computationally efficient solution for real-time monitoring without the need for additional sensing modalities. Various mother wavelet families are evaluated, and specific detail levels are identified as the most informative for capturing arc transients. Among these, Daubechies db9 and Symlet sym8 showed the highest discriminative performance and were used as inputs to a compact ANN structure. The network, trained with normalized feature data, achieved a high regression coefficient, indicating excellent classification accuracy. Additionally, algorithm robustness was validated by training the neural network on db4-extracted features and testing it across all accepted wavelets, with consistent detection performance. The results confirm the robustness and practicality of the proposed DWT-ANN framework for real-time arc detection in railway systems.
Conformational landscape and ligand-dependent clustering of the human type 2 IP3 receptor
A quantum multi-sensor data fusion self-supervised learning framework for IIoT anomaly detection
Controlled assembly of two-dimensional porphyrin heterostructures toward directed energy transfer and charge separation
Daily stressor control buffers stressor-related negative and positive affect associations
Single-cell RNA sequencing profiles drug activity within spatially engineered 3D cultures
Abstract Spatial transcriptomic techniques provide a wealth of information useful in guiding drug development, while three-dimensional (3D) cell cultures have demonstrated power in accelerating drug approvals. However, techniques for robust spatial analysis of 3D cultures are limited. Here, we present a transfection-based method for constructing cellular spheroids through a layer-by-layer approach, in which DNA barcodes encode the spatial positioning of cells. Our technique facilitates multiplex single-cell RNA sequencing, providing spatial maps of gene expression and drug response, while correlative imaging reveals the locations of barcoded cell populations and quantifies local tissue elasticity. We show that model HeLa 3D spheroids display heterogeneous responses to drugs, which may arise through diffusion gradients of the drug, or from differences in metabolism, nutrient supply, and cellular stressors. The ability to create spatially encoded cellular assemblies may help to reveal spatial variation in gene expression within 3D culture models.
Cervicovaginal microbiome diversity was not associated with mucosal pharmacokinetics of systemically delivered HIV broadly neutralizing antibodies
Table-top three-dimensional photoemission orbital tomography with a femtosecond extreme ultraviolet light source
Abstract Following electronic processes in molecules and materials at the level of the quantum mechanical electron wavefunction with ångström-level spatial resolution and with full access to its femtosecond temporal dynamics is at the heart of ultrafast condensed matter physics. A breakthrough invention allowing experimental access to electron wavefunctions was the reconstruction of molecular orbitals from angle-resolved photoelectron spectroscopy data in 2009, termed photoemission orbital tomography (POT). This invention opens a route towards ultrafast three-dimensional (3D) POT, with many new prospects for the study of ultrafast light-matter interaction, femtochemistry, and photo-induced phase transitions. Here, we develop a synergistic experimental-algorithmic approach to realize the first 3D-POT experiment using a short-pulse extreme ultraviolet light source. We combine a new variant of photoelectron spectroscopy, namely ultrafast momentum microscopy, with a table-top spectrally-tunable high-harmonic generation light source and a tailored algorithm for efficient 3D reconstruction from sparse, undersampled data. This combination dramatically speeds up the experimental data acquisition, while at the same time reducing the sampling requirements to achieve complete 3D information. We demonstrate the power of this approach by full 3D imaging of the frontier orbitals of a prototypical organic semiconductor adsorbed on pristine Ag(110).
Phytochemical-mediated green synthesis, mechanistic insights integrated with biological evaluation, density functional theory calculations and molecular docking studies of copper oxide nanoparticles
Lateral septum GABAergic neurons mediate the effects of dexmedetomidine on allodynia and sleep in a male mouse model of neuropathic pain
Abstract Chronic pain and sleep disorders frequently co-occur and exacerbate each other, yet the neural mechanisms underlying this comorbidity remain poorly understood. Here, we found that hyperactivity of GABAergic neurons in the dorsal division of the lateral septum (LS GABA ) drives both pain-like behavior and sleep disruption induced by spared nerve injury (SNI) in male mice. We showed that systemic or local application of dexmedetomidine (DEX), with known sedative and analgesic properties, reduces LS GABA hyperactivity via α 2 A adrenergic receptor activation, alleviating pain-like behavior and sleep disruption. LS GABA can project onto the glutamatergic and GABAergic neurons in the lateral preoptic area (LPO), respectively. The LS GABA →LPO Glu circuit and the LS GABA → LPO GABA circuit contribute to mechanical allodynia and sleep disruption, respectively. Furthermore, LS α 2 A adrenergic receptor plays an important role in DEX-regulated activity of LPO GABA and LPO Glu . Taken together, these findings reveal a shared neural substrate for chronic pain and sleep disorders and establish DEX as a potential treatment for this comorbidity through selective modulation of LS GABA -driven circuits.
Contamination levels and health risk assessment of heavy metals in edible leafy vegetables distributed in Rafsanjan, southeast Iran
Mechanistic and antigenic boundaries of Henipavirus and Parahenipavirus glycoproteins
Interfacial Charge Transfer Directing Intermolecular Hydrogen Transfer for On-Surface C–H Activation
Personalized optimal pillow shape and pneumatic smart pillow maintaining natural cervical curvature: a pilot study
Recurrent intra-tumour heterogeneity is a hallmark of metastatic prostate cancer
Abstract The evolution to metastatic disease is a major determinant of cancer mortality. Cancer evolution involves a complex interplay between intrinsic genetics and transcriptional alterations and the microenvironment. To define mechanisms underpinning metastatic heterogeneity in late-stage disease, we focus on metastatic castration-resistant prostate cancer and employed single-cell multi-omics and whole-genome sequencing to deeply profile 34 metastatic lesions obtained from 9 patients through rapid autopsy. We find evolutionary convergence of intra-tumour heterogeneity, characterised by recurrent tumour populations acting as critical functional components of the tumour ecosystem, irrespective of clonal and microenvironmental backgrounds. We find little evidence of the microenvironment driving transcriptional heterogeneity, but there are signatures of co-adaptation between the microenvironment and tumour cells. In contrast, clonal evolution primarily foster widespread transcriptional changes that did not result in de novo functional states. Intra-patient functional convergence of tumour ecosystems across metastases indicates system-level selection pressures that drive the heterogeneity landscape of metastatic castration-resistant prostate cancer. Our findings reveal functional evolutionary convergence of metastatic disease into distinct intra-tumour subpopulations, identifying critical determinants for therapeutic targeting.