Search Results (2,157)

The present review discusses vitamin A/retinoid metabolism as a cross-organ axis in which hepatic clock-dependent retinoid handling may affect immune clock gene expression through the stimulation of retinoic acid 6–Janus kinase 2–signal transducer and activator of transcription 5 signaling, potentially promoting pro-inflammatory monocyte states. We further highlight mechanosensory signaling as a second convergent layer that integrates hemodynamic forces with tissue microenvironmental cues. Among these pathways, G protein-coupled receptor 68, a proton- and flow-sensitive G protein-coupled receptor, is discussed as a representative druggable node linking mechanical and inflammatory signaling in chronic kidney disease-associated cardiac injury. Finally, we outline potential therapeutic directions, including (i) circadian alignment/chronopharmacology, (ii) modulation of retinoid metabolism and signaling, and (iii) targeted inhibition of primary immune and mechanosensory effectors. Full article

This article introduces an intelligent framework using deep learning to recognize and classify different faults through the real-time detection of multiple faults in power distribution systems. A collection of data representing normal operating conditions, alongside various fault scenarios including line-to-ground (LG), line-to-line (LL), double line-to-ground (LLG), and three-phase line (LLL) faults, was created using three phase current signals obtained from the Real-Time Digital Simulator (RTDS) microgrid test system. To properly model the system dynamics, a feature extraction method that integrates phase currents, differential currents, summation currents and magnitude results was developed. The temporal features of the fault signals were identified by using a sliding window approach to fit the data. A one-dimensional convolutional neural network (CNN) was developed to identify different types of faults. This model performed well, obtaining nearly 96.15% accuracy while testing. In order to evaluate the feasibility of the approach, the trained model was loaded on Raspberry Pi 5, NodeMCU, ESP32 and existing sensing devices. The fault classification performed in real-time was time-sensitive. The proposed intelligent framework is applicable to low-scale operation for smart grid fault monitoring and protection and it is an economically viable solution. Full article

Shared GPU clusters often execute multiple distributed training jobs concurrently under fluctuating contention. We reinterpret this setting as a two-scale control problem, where the micro scale captures intra-job learning dynamics and the macro scale captures inter-job resource arbitration. We propose an entropy-guided hierarchical framework that links these two scales through a unified uncertainty signal computed from training logits. Unlike existing uncertainty-aware methods that typically use uncertainty for only a single level of decision making, our approach uses the same entropy-based signal to jointly support both intra-job adaptation and inter-job scheduling within a hierarchical control loop. At the micro level, each worker estimates predictive uncertainty via normalized entropy and converts it into stable weights that drive epoch-level controls for uncertainty-aware data sharding, fixed-budget batch-size reallocation, and learning-rate modulation, while remaining compatible with standard synchronous data-parallel training. At the macro level, the same signal is aggregated into a job utility score that guides admission, ordering, and GPU quota assignment under contention. In large-scale workload-driven simulation, our method reduces average job completion time (JCT) by 23.7% and shortens cluster makespan by 15.7% relative to a strong learning-unaware baseline, demonstrating that uncertainty-aligned scheduling can improve cluster-level efficiency while preserving training correctness. We further validate scalability using a calibrated simulator up to 1024 nodes. Full article

Background: Magnesium sulfate (MgSO₄) has been investigated as an adjuvant in perioperative analgesia because of its antagonistic effects on the N-methyl-D-aspartate receptor (NMDA receptor) and its potential to attenuate central sensitization. However, clinical findings regarding its analgesic efficacy remain inconsistent across surgical procedures. Lumbar microdiscectomy is a common spinal procedure in which effective early postoperative pain control is important for patient comfort and early mobilization. This study aimed to evaluate the effect of intraoperative MgSO₄ administration on early postoperative analgesia and perioperative outcomes in patients undergoing lumbar microdiscectomy. Methods: This retrospective single-center cohort study included thirty-eight patients with American Society of Anesthesiologists (ASA) physical status I–II who underwent elective single-level lumbar microdiscectomy under general anesthesia. Patients were divided into two groups according to intraoperative magnesium administration: a control group receiving standard anesthesia without MgSO₄ (n = 19) and an MgSO₄ group receiving an intravenous MgSO₄ bolus of 30 mg/kg followed by a continuous infusion of 10 mg/kg/h until skin closure (n = 19). Postoperative pain intensity was assessed using the Numeric Rating Scale (NRS) at 0, 5, 10, 15, and 30 min after admission to the post-anesthesia care unit. Secondary outcomes included intraoperative remifentanil consumption, extubation time, and time to first mobilization. Complementary in silico analyses included molecular docking and protein–protein interaction (PPI) network analysis. Results: Postoperative NRS scores were numerically lower in the MgSO₄ group; however, between-group differences were not statistically significant. Mean intraoperative remifentanil consumption was numerically lower in the MgSO₄ group (236 ± 166 µg) compared with the control group (319 ± 298 µg), without statistical significance (p = 0.27). Repeated-measures analysis demonstrated the significant effect of time on postoperative NRS scores, whereas the overall group effect was not significant. Molecular analyses indicated stable morphine binding to opioid receptors and highlighted glutamatergic signaling components as central nodes within the interaction network. Conclusions: Intraoperative MgSO₄ administration was not associated with significant improvements in early postoperative pain scores or perioperative recovery parameters following lumbar microdiscectomy. Molecular analyses provide exploratory in silico insights and should be interpreted cautiously given the retrospective design and the in silico nature of these findings. Full article

Despite effective antiretroviral therapy, HIV persists in diverse tissue reservoirs that pose major barriers to a cure. This review examines the heterogeneous maintenance mechanisms of HIV reservoirs in lymph nodes, intestinal mucosa, and the central nervous system (CNS). It analyzes how distinct tissue microenvironments—including immune-privileged niches, specialized cellular subsets, and local signaling networks—govern viral persistence and latency. Lymph nodes function as a dynamic hub interconnected with systemic reservoirs; the intestinal mucosa represents a site shaped by barrier integrity, microbial translocation, and mucosal immunity; the CNS constitutes a compartmentalized sanctuary protected by the blood–brain barrier. The review further discusses tissue-specific antiretroviral drug penetration and targeted clearance strategies, providing a foundation for developing multi-site intervention approaches toward HIV cure. Full article

Background/Objectives: Craniofacial malformations such as orofacial clefts affect ~1 in 700 births; 40–60% lack clear genetic etiology, and many exhibit asymmetry and variable expressivity unexplained by classical Sonic Hedgehog (SHH) morphogen gradient models. We investigated whether integrated molecular modules linking morphogen signaling with metabolic stress responses may better account for craniofacial developmental outcomes. Methods: Sequential UniProt gene set integration identified 186 candidate craniofacial regulators. STRING network analysis revealed modular architecture. Molecular docking profiled 17 compounds against SMO, CK1δ, PINK1, and TIE2 (control). Pathway reconstruction integrated the SHH–CK1δ–HIF1A–HEY1–PINK1 axis with in-silico-predicted CK1δ phosphorylation sites on SMO (S615, T593, S751), HIF1A (Ser247), and GLI1/2/3 transcription factors. A developmental decision tree mapped affinity profiles to node-specific phenotype hypotheses. Results: CK1δ and PINK1 emerged as candidate nodes coupling morphogen signaling with mitochondrial quality control. Cross-docking showed preferential binding to developmental kinases (CK1δ: −8.34 kcal/mol; PINK1: −8.80 kcal/mol) versus TIE2 control (−6.76 kcal/mol; p < 0.001). Pathway reconstruction suggested that CK1δ-mediated Ser247 phosphorylation of HIF1A disrupts ARNT dimerization, redirecting HIF1A toward ARNT-independent HEY1 induction and consequent PINK1 suppression. Based on computed profiles, node-specific associations were proposed as computational hypotheses: SMO perturbation → midline defects; CK1δ → facial asymmetry/clefting; PINK1 → mandibular hypoplasia. Multi-target compounds (e.g., purmorphamine, taladegib) generated composite phenotype predictions consistent with clinical complexity. Conclusions: This strictly in silico study identifies candidate integrated morphogenic modules whose multi-node perturbation may underlie anatomically specific craniofacial malformation patterns. Node–phenotype associations are prioritized computational hypotheses requiring experimental validation; if confirmed, the framework could inform developmental toxicity assessment, therapeutic design, and reclassification of idiopathic craniofacial anomalies. Full article

Cannabinoid receptors occupy strategic control nodes within motor circuitry, making them potential targets for modulating different motor manifestations. They are positioned both within basal ganglia circuits that regulate movement and within spinal circuits that control skeletal muscle tone. Consequently, cannabinoids have been studied across diverse motor disorders, most notably in movement disorders and tone disorders, particularly those resulting in spasticity. Because motor control spans multiple anatomically and functionally distinct levels, relating cannabinoid signaling to effects on motor function is not straightforward. Limited understanding of cannabinoid receptor distribution has led to cannabinoids being tested even in disorders where receptor localization would predict little or no benefit. Mapping receptor distribution within individual motor circuits and integrating them with their pharmacological effects can help anticipate how cannabinoid signaling shapes motor output. Combined with characteristic motor manifestations, one can identify motor disorders in which cannabinoids may have therapeutic value. In this review, we integrate existing evidence to place cannabinoid receptors within key motor pathways, ranging from basal ganglia circuits controlling movement to peripheral mechanisms governing muscle tone. We consider both cannabinoid 1 receptor (CB₁R) and cannabinoid 2 receptor (CB₂R), with CB₂R gaining attention only recently for its potential relevance within the central nervous system. Building on this framework, we infer how cannabinoids acting at these sites may modulate motor control, and consequently, influence motor manifestations across major motor disorders. Finally, we examine how these distribution-based expectations align with available clinical observations. Full article

Background: The clinical efficacy of the BCL-2 inhibitor venetoclax in acute myeloid leukemia (AML) is significantly undermined by the frequent emergence of drug resistance, which precipitates disease progression and poor patient outcomes. However, the molecular landscape of this resistance remains insufficiently understood. Methods: To address this, we developed venetoclax-resistant AML cell models and utilized transcriptomic profiling integrated with comprehensive in vitro and in vivo functional assays. Results: Resistant cells demonstrated sustained proliferation even under the suppression of BCL-2, MCL-1, and key intrinsic apoptotic markers, including cleaved PARP and caspase-9, indicating a bypass mechanism independent of classical BCL-2 signaling. Compared to their sensitive counterparts, resistant Kasumi-1 (VENK) and MV4-11 (VENM) cells exhibit aggressive growth phenotypes in vitro and in vivo, characterized by larger, more numerous spheroids and colonies, alongside heightened tumorigenicity in murine models. Transcriptomic profiling and KEGG analysis identified the neuroactive ligand–receptor interaction (NLRI) pathway as a significant signaling node shared between these resistant lines. While multiple NLRI-associated genes were altered, CHRNB4 was consistently and significantly downregulated in both VENK and VENM cells and tumors. Re-expression of CHRNB4 in resistant cells, a primary gain-of-function approach, significantly impaired colony formation, and tumor growth in vivo. Clinically, CHRNB4 downregulation correlates with shortened overall survival and diminished response to venetoclax. Conclusions: Our findings implicate the NLRI pathway in venetoclax resistance and identify CHRNB4 as a robust prognostic indicator and a promising therapeutic target for developing next-generation AML strategies. Full article

Vascular remodeling driven by the phenotypic switching of vascular smooth muscle cells (VSMCs) poses a significant health risk to astronauts during long-duration spaceflight. While the morphological and molecular changes are well recognized, the underlying metabolic drivers and potential translational countermeasures remain elusive. To investigate the metabolic determinants of VSMCs phenotypic switching, human aortic smooth muscle cells (HASMCs) were subjected to cyclic mechanical stretch, an in vitro model offering indirect mechanistic insights into mechanical loading conditions relevant to spaceflight-associated hemodynamic alterations. An integrated approach combining quantitative proteomics, flux analysis (Seahorse), and functional assays (cell cycle, wound healing, transwell) was used to characterize the accompanying metabolic and phenotypic alterations. Molecular mechanisms were assessed using immunoprecipitation, protein crosslinking, and immunofluorescence. Mechanical stretch triggered a contractile-to-synthetic phenotypic switch in HASMCs, accompanied by a shift from oxidative phosphorylation to aerobic glycolysis. Pyruvate kinase M2 (PKM2) was identified as a central metabolic regulator of this process, its silencing reversed the pro-synthetic phenotype. Notably, lactate, a glycolytic product, was found to exert a self-limiting feedback signal. Exogenous lactate suppressed the synthetic switch in associated with increased PKM2 lactylation. Further analysis indicated that PKM2 lactylation was associated with enhanced stability of its active tetrameric conformation, which was associated with a metabolic shift toward oxidative phosphorylation and restored expression of contractile markers. Although specific lactylation sites on PKM2 were not identified in this study, and direct causality between lactylation and tetramerization remains to be established, these findings identify a previously unrecognized association. This study reveals a novel metabolic regulatory mechanism in which lactate correlates with the suppression of synthetic switching of VSMCs, linked to PKM2 lactylation and tetramer stabilization. The observed lactate-PKM2 axis represents a candidate metabolic node associated with VSMCs phenotype regulation and offers a potential therapeutic target for modulating vascular remodeling. Upon direct validation under relevant conditions in future studies, this mechanism may inform the development of novel therapeutic strategies for managing vascular adaptation during long-duration spaceflight and other aerospace-related physiological challenges. Full article

Cross-interface architectures are increasingly central to large-scale ocean observation systems, where underwater sensor nodes transmit data to spatially distributed buoys that relay information to terrestrial networks. In these deployments, the inherent broadcast nature of underwater acoustic (UWA) propagation enables a single node’s signals to be captured by multiple buoys. However, substantial and dynamic propagation delays lead to inherent reception asynchrony and severe multi-user interference. Conventional detection relies on large hydrophone arrays on single platforms and assumes strict synchronization, hindering scalability and elevating costs. This study proposes a distributed asynchronous reception framework for buoy-assisted UWA networks. Under a cloud software-defined acoustic (C-SDA) architecture, spatially separated buoys are treated as a virtual distributed multiple-input multiple-output (MIMO) receiver. We introduce a minimum-delay-based equivalent reconstruction to regularize the asynchronous structure, followed by blind channel identification and pilot-assisted synchronization for robust multi-user detection. By leveraging long-delay broadcast propagation as a source of spatial diversity, the framework facilitates scalable and cost-effective multi-user access. The results demonstrate that the architecture provides a practical paradigm for the underwater Internet of Things and long-term ocean observation. Full article

Background: Extracranial metastasis (EM) from glioblastoma (GB), IDH-wildtype (WHO CNS 2021 grade 4) is rare and often under-recognized, yet it has immediate implications for staging and management. We report a case series integrating advanced neuroimaging, whole-body imaging, and pathology/biomarkers to characterize imaging–pathology correlates of EM and highlight practical clinical triggers that should prompt systemic evaluation. Case presentation: We report three patients with adult-type, IDH-wildtype GB who developed EM confirmed by cytology/histology and/or concordant multimodality imaging. Brain MRI (1.5T/3T) demonstrated aggressive primary tumors with qualitative elevation of DSC-perfusion and frequent tumor–surface contact (dural, ependymal/leptomeningeal contact). Intratumoral susceptibility signal reached grade 3 where assessed. All patients underwent surgical resection followed by temozolomide-based chemoradiation; two received fotemustine and bevacizumab, and one underwent re-irradiation. EM presented with clinical triggers including severe axial/back pain, palpable cervical masses, and/or cytopenias. Initial EM sites were bone marrow/vertebrae (n = 1) and cervical lymph nodes (n = 2); staging revealed additional osseous disease in both nodal cases and a small pulmonary nodule in one. Nodal and osseous lesions were FDG-avid on 18F-FDG PET/CT. OLIG2-positive cytology confirmed cervical nodal metastases, and bone marrow aspiration with GFAP/OLIG2 positivity confirmed medullary infiltration. All tumors shared a molecular profile of TERT-promoter mutation, ATRX wild-type, TP53 mutation, and MGMT-promoter methylation. Despite attempts at second- and third-line therapies, disease progression was rapid, and all patients succumbed within 8–16 months of diagnosis. Discussion: This series underscores that EM can occur despite MGMT-promoter methylation and supports the concept of heterogeneous metastatic phenotypes in GB. Our cases reinforce that new axial/back pain or hematologic abnormalities may signal osseous or marrow involvement, and necrotic cervical lymphadenopathy in GB patients warrants dedicated imaging and tissue confirmation with glial markers. Integrating brain MRI features (high perfusion, surface contact, susceptibility burden) with FDG-PET/CT and targeted cytology/pathology can expedite diagnosis and inform multidisciplinary care. Conclusions: EM can arise despite MGMT-promoter methylation in IDH-wildtype GBM. Imaging red flags (high perfusion, surface contact, necrotic/FDG-avid cervical nodes) and clinical cues (axial pain, cytopenias, neck masses) should prompt early systemic staging (CT/PET-CT) and targeted tissue confirmation to advance management. Full article

Targeted therapies are reshaping oncology by enabling treatment selection based on actionable molecular alterations, improving precision, and reducing unnecessary toxicity. This review provides an up-to-date overview of current targeted treatment modalities and the medicinal chemistry principles that support their discovery and optimization. We synthesize evidence on small-molecule and biologic strategies spanning receptor and non-receptor kinases and their major signaling axes (PI3K-AKT-mTOR and RAS-RAF-MEK-ERK), apoptosis regulation (BCL-2 family), DNA repair via poly(ADP-ribose) polymerase (PARP) inhibition, and epigenetic or metabolic targets including histone deacetylases (HDACs), bromodomain and extra-terminal proteins (BET), and mutant isocitrate dehydrogenases (IDH1/2). Across these areas, we summarize recurrent resistance mechanisms and the rationale for combination or sequential approaches. Biologic targeted therapy is discussed in parallel, including immune checkpoint blockade, antibody–drug conjugates, bispecific antibodies (BsAb), and cell therapies such as chimeric antigen receptor T cells, with emphasis on biomarker-guided patient stratification. Finally, we outline emerging directions beyond canonical nodes, including modulation of the p53-MDM2/MDM4 axis, ferroptosis control through AIFM2/FSP1, and innate immune pathways such as CD47-SIRPa and the stimulator of interferon genes (STING). Overall, the field is shifting from single-target inhibition toward integrated strategies that combine precise molecular targeting with an understanding of signaling network dynamics, resistance evolution, and therapeutic vulnerabilities. Full article

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, with drug resistance representing the primary barrier to effective treatment. Current research has largely focused on individual signaling pathways or isolated organelle functions, yet a comprehensive understanding of how these subcellular structures coordinate to drive resistance remains lacking. This review synthesizes current knowledge through the perspective of subcellular structural homeostasis, the dynamic balance maintained by intracellular organelles. We examine how key subcellular structures, the cell membrane, mitochondria, endoplasmic reticulum, ribosomes, lysosomes, exosomes, and stress granules, undergo functional remodeling to promote drug resistance. It is crucial that these organelles do not work independently but form an integrated and dynamic communication network. Mitochondria serve as the intracellular signaling hub, integrating calcium signals, metabolic progress, and stress responses, while exosomes function as intercellular messengers that spread the anti-drug-resistant phenotype between cells. This framework reveals why targeting individual structures often fails and highlights the therapeutic potential of disrupting inter-organelle communication. We discuss emerging clinical strategies targeting subcellular structures and identify critical knowledge gaps, including the need for non-invasive biomarkers and combination approaches that target multiple network nodes. By shifting the focus from isolated organelles to their coordinated interplay, this review offers a new paradigm for overcoming drug resistance in PDAC. Full article

Recommender systems are central to helping users navigate the rapidly expanding entertainment ecosystem, yet achieving strong personalization with limited feedback while maintaining interpretability remains difficult, particularly under cold-start conditions and heterogeneous item metadata. This work presents an end-to-end hybrid recommendation framework that unifies a Large Language Model (LLM) with Graph Attention Network (GAT)-based collaborative filtering to improve both ranking accuracy and explanation quality across movies, books, and music. LLM-based agents first transform raw metadata such as titles, genres, descriptions, and auxiliary attributes into semantically grounded user and item profiles, which are embedded and used as initial node features in a user–item bipartite graph processed by a GAT-based recommender. Model optimization relies on a hybrid objective combining Bayesian Personalized Ranking, cosine-similarity regularization, and robust negative sampling to better align semantic and collaborative signals. Finally, in the post-processing stage, an LLM-based agent re-ranks the GAT outputs using a proposed Hybrid Confidence-Weighted Binary Search Tree, and another LLM-based agent that produces natural-language justifications tailored to each user. Experiments on diverse benchmark datasets and extensive ablations demonstrate that the proposed methodology increases precision, recall, NDCG, and MAP across various values of K. In addition, the post processing step is especially effective in cold-start scenarios, consistently strengthening recommendation metrics and enhancing transparency at smaller values of K. Overall, integrating LLM-enriched representations with attention-based graph modeling enables more accurate and explainable entertainment recommendations. Full article

As Open Radio Access Network (O-RAN) deployments expand and adversaries adopt “store-now, decrypt-later” strategies, operators need empirical data on the cost of migrating critical control interfaces to post-quantum cryptography (PQC). This paper experimentally evaluates the impact of integrating a NIST-aligned Module-Lattice Key-Encapsulation Mechanism (ML-KEM) into IKEv2/IPsec, protecting the E2 interface between the 5G Node B (gNB) and the Near-Real-Time RAN Intelligent Controller (Near-RT RIC). Using an open-source testbed built from srsRAN, Open5GS, FlexRIC and strongSwan (with liboqs), we compare three configurations: no IPsec, classical Elliptic Curve Diffie–Hellman (ECDH)-based IPsec, and ML-KEM-based IPsec. This study focuses on IPsec tunnel-setup latency and the runtime behaviour of Near-RT RIC xApps under realistic signalling workloads. Results from repeated, automated runs show that ML-KEM integration adds a small overhead to tunnel establishment, which is approximately 2.7~4.7 ms in comparison to classical IPsec, while xApp operation and RIC control loops remain stable in our experiments. These findings, produced from an open, reproducible testbed, indicate that ML-KEM-based IPsec on the E2 interface is practically feasible and inform quantum-safe migration strategies for O-RAN deployments. Full article