Browse Articles
Discover research articles across all indexed journals
The OMB and the Politicization of Science
Effects of combined resistance and high-intensity interval training on some biomarkers in men with metabolic dysfunction-associated steatotic liver disease
Uranus and Neptune may not be ‘ice giants’ after all
A growing number of theories propose Uranus and Neptune are rocky worlds
A Rash and Red Urine
Polarity-dependent modulation of sensory circuits by cerebellar tDCS: local and distant effects
Erratum for the Research Article “Awake Hippocampal Sharp-Wave Ripples Support Spatial Memory”
Phase 3 Trials of Inhaled Treprostinil for Idiopathic Pulmonary Fibrosis
RBM15 plays a key driving role in the tumorigenesis of EGFR-mutant lung adenocarcinoma and gefitinib resistance
C1q and immunoglobulins mediate activity-dependent synapse loss in the adult brain
Complement component 1q (C1q), the initiator of the classical complement cascade, mediates synaptic elimination in development and disease, yet the triggers for its deposition on synapses remain unclear. Using in vivo chemogenetics, we demonstrate that neuronal hyperactivity induces region-specific, C1q-dependent synapse loss in the adult hippocampus. Suppressing perforant pathway hyperactivity in a mouse model of Alzheimer’s disease reduced local amyloid-β amounts and C1q deposition and partially rescued synapse loss. Combining spatial transcriptomics, live cell tracking, and super-resolution microscopy, we identified association of antibody-secreting B-lineage cells in the adult hippocampus with activity-dependent, C1q-mediated synapse loss under physiological conditions. Together, these findings link neuronal hyperactivity to C1q-mediated synapse loss in the adult brain and implicate immunoglobulins as players in this process.
Condyloma Acuminata of the Urethra
Optimizing sowing time and foliar boron application improves soil moisture use, physiological efficiency, and yield stability of field pea (Pisum sativum L.) in rainfed rice-fallow systems
A note to my younger self
Caring for an Aging America — The Looming Crisis of the Long-Term–Care Workforce
Serotype-specific neutralizing activity and clinical outcomes associated with intravenous immunoglobulin in pediatric HAdV-3 and HAdV-7 infections
What do we know about sex? <b>Poking the Squid: What We Can Learn from Animal Sex</b> <i>Perrin Roosevelt Ireland</i> Norton, 2026. 272 pp. <b>On the Origin of Sex: The Weird and Wonderful Science of Reproduction</b> <i>Lixing Sun</i> Basic Books, 2026. 368 pp.
It depends on whom you ask
Mandated State-Level Surveillance of Assisted Reproductive Technology — An Emerging Threat in the United States
A two-stage hierarchical support vector machine framework detects roasted coffee adulterants through principal component analysis of hyperspectral imaging data
Abstract Economically motivated adulteration (EMA) of roasted coffee presents a critical challenge to global market integrity and consumer safety, specifically regarding the surreptitious inclusion of high-risk allergens like barley and soybeans. The detection of such contaminants is historically hindered by the Maillard reaction, a thermal convergence during roasting that renders adulterants visually and spectrally indistinguishable from the coffee matrix. To address this forensic gap, this study presents a targeted hyperspectral imaging (HSI) framework (400–1000 nm) integrated with a two-stage hierarchical Support Vector Machine (SVM) designed to decouple detection from specific biological diagnosis. A core contribution of this methodology is the implementation of Principal Component Analysis (PCA) to resolve spectral redundancy across the 128-band hypercube. By distilling the data into two primary components capturing over 92% of the cumulative variance, the framework establishes a “spectrochemical bridge” that isolates hidden chromatic and biochemical variances invisible to traditional RGB sensors. This high-significance feature space allows the SVM to overcome the “Euclidean trap” inherent in unsupervised clustering, which frequently suffers from “class collapse” in roasted materials. Experimental results demonstrate that the hierarchical pipeline achieves an optimal overall accuracy of 88.6% and a Kappa coefficient of 0.378. The system attained high reliability during the Stage-1 binary screening, achieving an F1-score of 0.922 to protect the primary coffee matrix, while the Stage-2 multi-class model successfully mapped the spatial distribution of the highly camouflaged allergens. By providing pixel-wise, automated risk assessments, this work establishes a data-driven proof-of-concept for ‘Smart Food Safety’ systems, highlighting the potential for forensic authentication in future industrial quality control environments.
The owl wars
Northern spotted owls were spared from logging. Now, scientists are making a last stand to save them from a new threat