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Abstract β‐secretase (BACE1) is instrumental in amyloid‐β (Aβ) production, with overexpression noted in Alzheimer's disease (AD) neuropathology. The interaction of Aβ with the receptor for advanced glycation endproducts (RAGE) facilitates cerebral uptake of Aβ and exacerbates its neurotoxicity and neuroinflammation, further augmenting BACE1 expression. Given the limitations of previous BACE1 inhibition efforts, the study explores reducing BACE1 expression to mitigate AD pathology. The research reveals that the anticancer agent 6‐thioguanosine (6‐TG) markedly diminishes BACE1 expression without eliciting cytotoxicity while enhancing microglial phagocytic activity, and ameliorate cognitive impairments with reducing Aβ accumulation in AD mice. Leveraging advanced deep learning‐based tool for target identification, and corroborating with surface plasmon resonance assays, it is elucidated that 6‐TG directly interacts with RAGE, modulating BACE1 expression through the JAK2‐STAT1 pathway and elevating soluble RAGE (sRAGE) levels in the brain. The findings illuminate the therapeutic potential of 6‐TG in ameliorating AD manifestations and advocate for small molecule strategies to increase brain sRAGE levels, offering a strategic alternative to the challenges posed by the complexity of AD.

Based on the advances made by artificial intelligence (AI) technologies in drug discovery, including target identification, hit molecule identification, and lead optimization, this study investigated natural compounds that could act as transient receptor potential vanilloid 1 (TRPV1) channel protein antagonists. Using a molecular transformer drug–target interaction (MT-DTI) model, troxerutin was predicted to be a TRPV1 antagonist at IC50 582.73 nM. In a TRPV1-overexpressing HEK293T cell line, we found that troxerutin antagonized the calcium influx induced by the TRPV1 agonist capsaicin in vitro. A structural modeling and docking experiment of troxerutin and human TRPV1 confirmed that troxerutin could be a TRPV1 antagonist. A small-scale clinical trial consisting of 29 participants was performed to examine the efficacy of troxerutin in humans. Compared to a vehicle lotion, both 1% and 10% w/v troxerutin lotions reduced skin irritation, as measured by skin redness induced by capsaicin, suggesting that troxerutin could ameliorate skin sensitivity in clinical practice. We concluded that troxerutin is a potential TRPV1 antagonist based on the deep learning MT-DTI model prediction. The present study provides a useful reference for target-based drug discovery using AI technology and may provide useful information for the integrated research field of AI technology and biology.

Emerging Zoned Namespace (ZNS) SSDs, providing the coarse-grained zone abstraction, hold the potential to significantly enhance the cost efficiency of future storage infrastructure and mitigate performance unpredictability. However, existing ZNS SSDs have a static zoned interface, making them in-adaptable to workload runtime behavior, unscalable to underlying hardware capabilities, and interfering with co-located zones. Applications either under-provision the zone resources yielding unsatisfied throughput, create over-provisioned zones and incur costs, or experience unexpected I/O latencies. We propose eZNS, an elastic-ZNS interface that exposes an adaptive zone with predictable characteristics. eZNS comprises two major components: a zone arbiter that manages zone allocation and active resources on the control plane, and a hierarchical I/O scheduler with read congestion control and write admission control on the data plane. Together, eZNS enables the transparent use of a ZNS SSD and closes the gap between application requirements and zone interface properties. Our evaluations over RocksDB demonstrate that eZNS outperforms a static zoned interface by 17.7% and 80.3% in throughput and tail latency, respectively, at most. [ABSTRACT FROM AUTHOR]

Based on the advances made by artificial intelligence (AI) technologies in drug discovery, including target identification, hit molecule identification, and lead optimization, this study investigated natural compounds that could act as transient receptor potential vanilloid 1 (TRPV1) channel protein antagonists. Using a molecular transformer drug–target interaction (MT-DTI) model, troxerutin was predicted to be a TRPV1 antagonist at IC50 582.73 nM. In a TRPV1-overexpressing HEK293T cell line, we found that troxerutin antagonized the calcium influx induced by the TRPV1 agonist capsaicin in vitro. A structural modeling and docking experiment of troxerutin and human TRPV1 confirmed that troxerutin could be a TRPV1 antagonist. A small-scale clinical trial consisting of 29 participants was performed to examine the efficacy of troxerutin in humans. Compared to a vehicle lotion, both 1% and 10% w/v troxerutin lotions reduced skin irritation, as measured by skin redness induced by capsaicin, suggesting that troxerutin could ameliorate skin sensitivity in clinical practice. We concluded that troxerutin is a potential TRPV1 antagonist based on the deep learning MT-DTI model prediction. The present study provides a useful reference for target-based drug discovery using AI technology and may provide useful information for the integrated research field of AI technology and biology. [ABSTRACT FROM AUTHOR]

Assembly of the peptidoglycan is crucial in maintaining viability of bacteria and in defining bacterial cell shapes, both of which are important for existence in the ecological niche that the organism occupies. Here, eight crystal structures for a member of the cell-shape-determining class of Campylobacter jejuni, the peptidoglycan peptidase 3 (Pgp3), are reported. Characterization of the turnover chemistry of Pgp3 reveals cell wall d,d-endopeptidase and d,d-carboxypeptidase activities. Catalysis is accompanied by large conformational changes upon peptidoglycan binding, whereby a loop regulates access to the active site. Furthermore, prior hydrolysis of the crosslinked peptide stem from the saccharide backbone of the peptidoglycan on one side is a pre-requisite for its recognition and turnover by Pgp3. These analyses reveal the noncanonical nature of the transformations at the core of the events that define the morphological shape for C. jejuni as an intestinal pathogen. Peptidoglycans (PG) define bacterial cell shapes. Here, the authors provide mechanistic insights into the peptidoglycan peptidase 3 (Pgp3) from the spiral shaped human pathogen Campylobacter jejuni by determining its crystal structure alone and in complex with synthetic cell-wall PG derivatives, and they further show that the enzyme has both d,d-endopeptidase and d,d-carboxypeptidase activities [ABSTRACT FROM AUTHOR]

A 64-word-line-stacked 512-Gb 3-b/cell 3-D NAND flash memory is presented. After briefly examining the challenges that occur to a stack, several technologies are suggested to resolve the issues. For performance enhancement, a novel program method hiding two-page data loading time is presented. This paper also discusses an electrical annealing improving reliability characteristic by removing holes in shallow traps. In addition, a valley tracking read for reducing timing overhead at a read retry is introduced by fast finding optimal read levels. Finally, a high-speed self-test mode for IO operation is presented. The chip, designed with the fourth generation of V-NAND technology, achieved an areal density of 3.98 Gb/mm2 and operated up to 1 Gb/s at 1.2 V. [ABSTRACT FROM PUBLISHER]

Most memory-chip manufacturers keep trying to supply cost-effective storage devices with high-performance characteristics such as shorter tPROG, lower power consumption and higher endurance. For many years, every effort has been made to shrink die size to lower cost and to improve performance. However, the previously used node-shrinking methodology is facing challenges due to increased cell-to-cell interference and patterning difficulties caused by decreasing dimension. To overcome these limitations, 3D-stacking technology has been developed. As a result of long and focused research in 3D stacking technology, we succeed in developing 128 Gb 3b/cell Vertical NAND with 32 stack WL layers for the first time, which is the smallest 128 Gb NAND Flash. The die size is 68.9 mm^2, program time is 700 us and I/O rate is 1 Gb/s. [ABSTRACT FROM PUBLISHER]