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Genomic epidemiology of mpox virus during the 2022 outbreak in New York City
Structure based drug design and machine learning approaches for identifying natural inhibitors against the human αβIII tubulin isotype
Engineered enzymes can suppress genome-editing errors
Tuning the Lifetimes of Photoinduced Deligation in a Metal–Organic Framework via Linker Functionalization
Musical rhythm abilities and risk for developmental speech-language problems and disorders: epidemiological and polygenic associations
Region specific microstructural complexity of the ovine meniscus root provides an organizational basis for injury susceptibility
Abstract Comprehensive information on the meniscus root microstructure is essential to exactly understand its physiological role and susceptibility to injury. We selected the ovine medial meniscus anterior root (MAR) as model to elucidate the intricate spatial arrangement of its enthesis, root ligament and transition into the medial meniscus anterior horn (MMAH), hypothesizing that its microstructure is comparable to humans. We applied different histological, type-I, -II, and -X collagen immunohistochemical, polarization and confocal analyses to investigate its structural complexity. The results reveal unique region-specific patterns. Cell morphology, proteoglycan, and type-II collagen contents differ between regions. The enthesis is avascular while the MAR ligament and red-red zone of the MMAH are well vascularized. The ovine MAR attachment constitutes an enthesis organ together with a bare area below the root ligament covered by adipose tissue. The MAR ligament comprises large longitudinal fascicles that unweave into a complex network when entering the MMAH, changing their orientation towards its white-white zone. The blood vessels that vascularize the MAR ligament enter at its peripheral-femoral side. Only axial MMAH fibers are immunopositive for type-X collagen. This region-specific microstructural complexity of the ovine MAR is largely similar to published findings in humans, providing an organizational basis for injury susceptibility. Thus, the ovine MAR may serve to study the physiopathology of and therapeutic approaches to human root tears.
Daily briefing: ‘Thinky think before grabby grab’ — lab tips for science success
Development of Cyclooctyne-Nitrone Based Click Release Chemistry for Bioorthogonal Prodrug Activation both <i>In Vitro</i> and <i>In Vivo</i>
Structural remodeling of target-SNARE protein complexes by NSF enables synaptic transmission
Abstract Synaptic vesicles containing neurotransmitters fuse with the plasma membrane upon the arrival of an action potential at the active zone. Multiple proteins organize trans-SNARE complex assembly and priming, leading to fusion. One target membrane SNARE, syntaxin, forms nanodomains at the active zone, and another, SNAP-25, enters non-fusogenic complexes with it. Here, we reveal mechanistic details of AAA+ protein NSF (N-ethylmaleimide sensitive factor) and SNAP (soluble NSF attachment protein) action before fusion. We show that syntaxin clusters are conserved, that NSF colocalizes with them, and characterize SNARE populations that may exist within or near them using cryo-EM. Supercomplexes of NSF, α-SNAP, and either a syntaxin tetramer or one of two binary complexes of syntaxin—SNAP-25 reveal atomic details of SNARE processing and show how sequential ATP hydrolysis drives disassembly. These results suggest a functional role for syntaxin clusters as reservoirs and a corresponding role for NSF in syntaxin liberation and SNARE protein quality control preceding fusion.
Attention-enhanced residual autoencoder for NIR spectral feature extraction and classification of grain varieties
Abstract Accurate identification of grain cultivars is critical for improving crop yields, streamlining agricultural workflows, and ensuring global food security. Near-infrared (NIR) spectroscopy offers a rapid, non-destructive solution for grain classification. However, its effectiveness hinges on extracting meaningful spectral features. We propose SpecFuseNet, an attention-enhanced residual autoencoder, as a lightweight deep learning model for extracting NIR spectral features and classifying grain varieties. The encoder integrates Fused Efficient Channel Attention (FusedECA) and a Spectral Residual Gate (SRG) to extract informative spectral features, while a mirrored decoder enables robust spectral reconstruction. This architecture supports both spectral reconstruction and cultivar classification, with robust performance and minimal complexity. We evaluated SpecFuseNet on three NIR datasets: barley (1,200 samples, 24 varieties), chickpea (950 samples, 19 varieties), and sorghum (500 samples, 10 varieties) using stratified 5-fold cross-validation. The model achieved classification accuracies of 89.72%, 96.14%, and 90.67%, respectively, outperforming PCA-based machine learning models (SVM, Random Forest, XGBoost) and deep learning baselines such as standard Autoencoder (AE) and Convolutional Sparse Autoencoder (CSAE). These results demonstrate SpecFuseNet’s potential as a fast, interpretable, and deployable solution for real-time classification in field-based and resource-limited settings, with a lightweight design that enables deployment on portable or smartphone-connected NIR spectrometers, supporting sustainable and precise agricultural practices.
Construction of Zeolite Framework-Anchored Rh–(O–Zn)<sub><i>x</i></sub> Sites for Ethylene Hydroformylation
Three lncRNAs promote PUM protein condensation and germline differentiation
Batch experimental studies on Acid Blue 25 dye removal by synthesized chitosan containing sodium alginate and halloysite nanotubes
What research might be lost after the NIH’s cuts? Nature trained a bot to find out
Pit Morphology, Dissolution Kinetics, and Gas Generation Monitored in Real Time during Localized Anodic Aluminum Corrosion
Role of the real first interface in regulating ionic signal of nanochannels
Human corticospinal tract lateralization at the height of the internal capsule is not related to handedness
Abstract Evaluating the integrity of the corticospinal tract at the height of the posterior limb of the internal capsule with a lateralization index has been applied to predict upper limb motor recovery after stroke in numerous diffusion tensor imaging studies. When comparing patient groups with healthy controls in this context, matching for age and gender is generally recommended. Since a generalized lateralization of diffusion strength to the dominant left hemisphere has been reported, it can be argued that handedness should also be accounted for. To address this question, we used the Human Connectome Project data set containing 1,065 diffusion-weighted MRI sets as well as information on handedness as defined by the Edinburgh Handedness Inventory. We hypothesized that handedness might be related to diffusion strength of the corticospinal tract. As commonly employed, we extracted fractional anisotropy values at the level of the internal capsule to calculate a laterality index. Contrary to our hypothesis, we found no association between corticospinal tract diffusion strength and handedness. We conclude that for handedness, no balancing between patient and control groups is needed when comparing corticospinal tract diffusivity parameters.