Browse Articles

NQQR: scalable qutrit image representation

Abstract Ternary quantum image processing (TQIP) integrates qutrit-based quantum computing with image representation, offering a promising pathway for efficient image encoding models. This paper introduces Novel Qutrit Quantum Representation (NQQR) model, a scalable and optimized ternary model for representing grayscale and RGB images of size $$3^n \times 3^n$$ in a ternary quantum system. The proposed model encodes pixel positions using the superposition of 2 n qutrits and assigns grayscale or color intensity values using 6 qutrits, while an additional color qutrit and an ancilla qutrit are employed to reduce the complexity of multi-controlled N -qutrit gates, thereby lowering the overall quantum cost. Experimental results show that the NQQR achieves a time complexity of $$O(n3^{2n})$$ and the optimized NQQR model significantly reduces quantum cost, with improvements up to $$99.36\%$$ for grayscale images and $$99.33\%$$ for RGB images when compared to equivalent non-optimized qubit/qutrit-based encoding models. In addition, the performance of the proposed model is evaluated under quantum depolarizing noise using MSE and PSNR metrics computed between the original and reconstructed images under different noise levels. These results demonstrate the efficiency and scalability of the proposed NQQR model at the representation level and suggest its potential as a building block for future research in TQIP.

High-temporal-resolution slope-aspect deformation extraction and evolution analysis of the Xiongba landslide group based on time-series InSAR and unscented Kalman filter

DAN-YOLO-L: a lightweight YOLO approach for efficient infrared small object detection from UAV perspectives

Digital twin optimization of water supply pump stations considering energy use, water hammer, and lifespan

Phytochemical profile and bioactivities of hydroethanolic extracts of Pteleopsis suberosa and Piliostigma thonningii used in traditional medicine in Togo

META-DIFF: a k-mer-based pipeline that detects differentially abundant sequences in metagenomics whole genome sequencing

Graph informed biomarker discovery framework using transcriptomic machine learning for glioblastoma prognosis

Abstract Identifying reproducible, interpretable prognostic signals from high-dimensional transcriptomics remains challenging because gene-level models often ignore network context. We developed Graph-Informed Biomarker Discovery (GIBD), a locked transcriptomics-only framework for primary glioblastoma that integrates RNA-seq expression with high-confidence STRING topology through weighted protein–protein interaction (WPPI) self-preserving feature construction. Model development, feature selection, scaler fitting, threshold selection, and locking used The Cancer Genome Atlas (TCGA) only, followed by post-lock external validation in the Chinese Glioma Genome Atlas (CGGA). The final TCGA cohort included 147 patients, and the empirical TCGA median overall survival of 357 days defined binary risk groups. The binary-evaluable CGGA cohort included 131 patients. The locked GIBD-XGBoost K100 model used 100 features (65 WPPI-derived, 35 raw-expression features) and threshold 0.53. TCGA out-of-fold AUC was 0.617. Post-lock CGGA validation yielded an AUC of 0.609, sensitivity of 73.9%, specificity of 50.6%, balanced accuracy of 62.3%, and a C-index of 0.537. SHAP identified TSPAN13 as the strongest global contributor, and full-transcriptome TCGA GSEA identified 156 terms at FDR < 0.05, with coherent high-risk inflammatory, hypoxic, metabolic, extracellular-matrix, complement/coagulation, and angiogenic enrichment. GIBD preserved an external transcriptomic risk-prioritization signal requiring prospective recalibration and multimodal validation before translational use.

A deep learning-based multi-modal fusion framework for football foul recognition and referee decision assistance

Abstract Accurate referee decision-making remains a critical challenge in football, where the distinction between legal and illegal contact often depends on subtle contextual factors. This paper presents FoulMFNet, an integrated deep learning framework for automated foul recognition designed to assist officiating judgment. The proposed system employs a multi-modal fusion architecture that jointly processes appearance features, motion dynamics, and skeletal representations through dynamically weighted integration. An attention-based temporal focusing mechanism identifies decisive contact moments within extended video sequences, while a confidence calibration module produces well-calibrated probability estimates reflecting prediction reliability. Comprehensive experiments conducted on a dataset comprising 12,463 incident clips from professional matches demonstrate that the proposed framework achieves 87.3% recognition accuracy across five foul categories, outperforming established baseline methods by 4.1 to 10.4 percentage points. Consistency analysis with FIFA-certified referees yields a Cohen’s kappa of 0.82, indicating substantial agreement with professional standards. The system maintains real-time performance with median latency of 127 ms, enabling practical deployment alongside existing Video Assistant Referee infrastructure. Interpretability components provide comprehensible visualizations of decision rationale, facilitating referee evaluation of system recommendations.

A rigorous analytical model and design framework for broadband graphene based THz absorbers

RIPK4 is associated with altered bioenergetics and invasive in melanoma three-dimensional models

Abstract Melanoma is an aggressive cancer characterized by metabolic reprogramming that supports invasion and metastasis. Receptor-interacting protein kinase 4 (RIPK4) has been linked to tumor progression, but its role in melanoma metabolism remains unclear. This study examined whether RIPK4 is associated with melanoma aggressiveness through modulation of cellular bioenergetics. Previously generated RIPK4-knockout A375 and WM266.4 melanoma cell lines (CRISPR/Cas9) were used, and RIPK4 expression was restored by plasmid transfection. Cellular metabolism was assessed using the Seahorse XF Mito Stress Test in 2D monolayer cultures. In 3D spheroid models, ATP assays, qRT-PCR, and Western blotting were performed, together with functional analyses using 3D matrix invasion and CCID assays. In vivo relevance was evaluated by immunohistochemical analysis of RIPK4 and GLUT1 in lung metastases from NOD/SCID mouse xenografts. RIPK4 knockout induced a metabolically compromised state, characterized by reduced mitochondrial respiration and glycolysis, decreased HK2 and GLUT1 expression, and increased SDHB levels also impaired 3D invasive behavior, including reduced formation of invasive protrusions and decreased intravascular invasion. GLUT1 expression was detected in lung metastases but was reduced in RIPK4-deficient tumors. RIPK4 re-expression restored AKT phosphorylation and partially rescued HK2 and GLUT1 levels; however, metabolic flux (OCR/ECAR) was not recovered. These findings suggest that RIPK4 is associated with melanoma metabolic regulation and invasion, potentially involving AKT-linked signaling, but also indicate that additional mechanisms beyond AKT–GLUT1 contribute to the observed metabolic phenotype.

Linking structural forest heterogeneity and ecological processes using Sentinel-2 and FAD-based zoning

Host genetic regulation of rumen 6-hydroxymelatonin reduces methane emissions in dairy cattle

The mechanisms linking host genetics to ruminal methane emissions remain unclear. Here, we integrated multiomics data from 304 lactating cows and demonstrated that methane emission per dry matter intake (M/D) exhibitd higher heritability ( h 2 = 0.42) than microbiability ( m 2 = 0.19), highlighting the predominant role of host genetics. Mendelian randomization (MR) analysis identified three heritable Prevotella species (including Prevotella_bryantii ) that causally reduce methane emissions. Network suggested that Prevotella_bryantii , which harbors the [NiFe]_Group_1d hydrogenase, exerts this effect by competing with methanogens for H₂. Furthermore, the methane-reducing effect of Prevotella _bryantii was confirmed by in vitro fermentation experiments. To trace the host regulation upstream, the host-derived metabolite 6-hydroxymelatonin was identified as a key regulator that positively influences these Prevotella species by MR analysis, which was further validated by in vitro fermentation and pure bacterial culture experiments. Genome-wide association studies linked ruminal 6-hydroxymelatonin levels to host genetic variants (e.g., 5:106926534) near candidate genes including ITFG 2. Functional studies in bovine hepatocytes revealed that ITFG 2 knockdown activated the mTORC1 pathway, upregulated CYP 1 A 2 expression, and increased 6-hydroxymelatonin synthesis. Furthermore, cattle carrying the TA genotype at 5:106926534 exhibited significantly lower predicted and measured methane emissions. Collectively, this study unveils a pathway whereby host genetics (via ITFG 2/mTORC1) modulate hepatic 6-hydroxymelatonin synthesis, which enriches specific rumen Prevotella that compete with methanogens for hydrogen, thereby reducing methane.

High-throughput protein target mapping enables accelerated bioactivity discovery for ToxCast and PFAS compounds

Chemical pollution is a global threat to human health, yet the toxicity mechanisms of most contaminants remains unknown. Here, we applied an ultrahigh-throughput affinity selection–mass spectrometry (AS–MS) platform to systematically identify protein targets of prioritized chemical contaminants. After benchmarking the platform, we screened 50 human proteins against 481 prioritized chemicals, including 446 ToxCast chemicals and 35 per- and polyfluoroalkyl substances (PFAS). Among 24,050 interactions assessed, we discovered 35 interactions involving 13 proteins, with fatty acid–binding proteins (FABPs) emerging as the most ligandable protein family. Given this, we selected FABPs for further validation, which revealed a distinct PFAS binding pattern: legacy PFAS selectively bound to FABP1, whereas replacement compounds, perfluoroether carboxylic acids, unexpectedly interacted with all FABPs. X-ray crystallography further revealed that the ether group enhances the molecular flexibility of alternative PFAS to accommodate the binding pockets of FABPs. Our findings demonstrate that AS–MS is a robust platform for the discovery of protein targets beyond the scope of ToxCast and highlight the broader protein-binding spectrum of alternative PFAS as potential regrettable substitutes.

Eugene Braunwald, MD, 1929–2026

Beyond the Beats: The ECG Tells More Than We Think

Galectin-1 Fuels Monocyte Hyperinflammation and Represents a Novel Therapeutic Target in Myeloproliferative Neoplasms

Dysregulation of galectins and global protein glycosylation have been reported in various cancers, but their role in myeloproliferative neoplasms (MPNs) have remained incompletely understood. We performed single-cell RNA sequencing (scRNA-seq) which revealed significant enrichment of galectin genes in MPN monocytes. Cell-cell communication analysis predicted monocytes as a pivotal mediator of cell interactions and galectin signaling as a robust input/output pathway for monocytes. We identified elevated expression of galectin-1 (Gal-1, LGALS1) in monocytes from both human MPN samples and mouse models. Mass cytometry (CyTOF) profiling of MPN blood samples demonstrated that recombinant galectin-1 (rGal-1) significantly increased levels of multiple inflammatory cytokines in monocytes without affecting other cell types. Incubation of CD14+ monocytes from MPN patients with rGal-1 led to markedly increased transcription and secretion of inflammatory cytokines. Mechanistically, we uncovered crosstalk between the TLR4 and Gal-1 signaling pathways, as evidenced by protein 3D modeling and co-immunoprecipitation. Notably, TLR4 inhibition abrogated Gal-1 mediated proinflammatory effects in monocytes. We further identified NF-κB-dependent signaling as a key downstream effector of Gal-1, as reporter assays demonstrated rGal-1 mediated activation of NF-κB signaling in a TLR4-dependent manner. We corroborated these findings in vivo in a murine model driven by MPLW515L in which genetic abrogation of Lgals1 ameliorated key MPN disease features, including leukocytosis and splenomegaly. Additionally, Gal-1 inhibition suppressed carrageenan-induced thrombosis and inflammation in vivo. In summary, we identify Gal-1 enrichment in MPN monocytes as a driver of monocyte-mediated inflammation through TLR4 and NF-κB activation and uncover a novel therapeutic avenue for MPNs.

ALTO EN IMPACTO: Dr Guido Girardi and Chile’s Food Labeling Law: A Conversation With Guido Girardi, MD, MPH

NG2-ITGA4 axis regulates Rho GTPases and leukemic aggressiveness in KMT2A-r B-ALL and is targetable with natalizumab

KMT2A-rearranged B-cell acute lymphoblastic leukemia (KMT2A-r B-ALL) is an aggressive subtype of leukemia, characterized by high relapse rates, therapy resistance, and poor prognosis. Although CD19-targeted immunotherapies have significantly benefited patients with relapsed/refractory (R/R) disease, relapses remain common and long-term survival is especially poor in KMT2A-r B-ALL patients. We recently identified the membrane-bound proteoglycan NG2 (CSPG4) as direct transcriptional target of KMT2A fusions, with its expression associated with poor prognosis, early relapse, and glucocorticoid resistance in KMT2A-r B-ALL. However, the molecular mechanism underlying the aggressiveness of KMT2A-r B-ALL remains poorly understood. Here, we identify the α4 integrin subunit (ITGA4) and NG2 as a key biological axis contributing to leukemic aggressiveness. NG2 expression promotes proliferation and migration of KMT2A-r B-ALL cells and it is associated with Rho GTPase activity in an ITGA4-dependent manner. In vivo studies using immunodeficient mice demonstrated that ITGA4 and NG2 cooperate to promote leukemia progression as combined genetic ablation of both genes significantly delayed disease onset and prolonged survival. Notably, Natalizumab (NTZ) - an FDA/EMA-approved monoclonal antibody targeting ITGA4 - delayed leukemia progression and potentiated the efficacy of standard-of-care chemotherapy in KMT2A-r B-ALL patient-derived xenograft (PDX) models. Collectively, our findings define a novel ITGA4-NG2 signaling axis that drives the aggressiveness of KMT2A-r B-ALL and support the repurpose of NTZ as an adjuvant therapeutic strategy for this high-risk leukemia subtype.

Transition Metal‐Free Borata‐Alkene/Alkyne Metathesis Enables Access to Cyclopentenes

ABSTRACT Metathesis reactions are fundamental transformations in organic synthesis, enabling efficient reorganization of unsaturated bonds and underpinning broad applications in pharmaceuticals, functional materials, and polymer science. To date, the conceptual and methodological development of metathesis transformations has been focused predominantly on carbon–carbon unsaturated bonds, and strategies that combine unsaturated bond reorganization with the direct incorporation of heteroatoms remain rare. Additionally, the established metathesis methodologies have been developed typically within the framework of transition metal catalysis, and transition metal‐free alternatives are scarcely explored. Here, we demonstrate that borata‐alkenes can serve as non‐metal alkylidene surrogates to enable a transition metal‐free hetero‐enyne metathesis to access cyclopentene derivatives. This process accommodates diverse electrophiles and can be integrated into cascade sequences, allowing three‐ and four‐component couplings from readily accessible 1,1,1‐triborylalkanes. The resulting chemodivergent products include cyclopentenyl boronic esters, geminal borylsilylalkanes, conjugated dienes, and, in a sequential four‐component variant, highly substituted ketones and enol ethers. Mechanistic studies and density functional theory (DFT) calculations support a borata‐alkene‐mediated metathesis pathway, establishing a transition metal‐free approach for cyclopentene synthesis via carbon–carbon bond reorganization.

Interventional MRI-Guided Ablation of Left Ventricular Tachycardia