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Repulsive Gas–Electrode van der Waals Forces Enable Charge Transfer Reactions under Chemically Modified Bubbles
Five-year survival outcomes from TRANSCEND NHL 001 of lisocabtagene maraleucel in R/R LBCL
We present 5-year survival results in patients with R/R LBCL from TRANSCEND NHL 001 (TRANSCEND), including data from the separate long-term follow-up (LTFU) study. Overall, 345 patients were leukapheresed, 270 received liso-cel, and 257 were efficacy evaluable. Among efficacy-evaluable patients, median overall survival (OS) was 27.5 months (95% confidence interval [CI], 16.2‒47.3; leukapheresed set, 15.2 months [95% CI, 11.5‒23.4]) with estimated 5-year OS rate of 38% (95% CI, 32‒45; leukapheresed set, 33% [95% CI, 28‒39]). Median disease-specific survival (DSS; excludes deaths unrelated to disease progression) was 67.8 months (95% CI, 23.5‒not reached [NR]; leukapheresed set, 27.4 months [95% CI, 14.4‒69.7]) with estimated 5-year DSS rate of 52% (95% CI, 45‒59; leukapheresed set, 47% [95% CI, 41‒52]). Among efficacy-evaluable patients from TRANSCEND who were alive at end-of-study and enrolled in the LTFU (n=84), median OS and DSS were NR (95% CI, NR‒NR) and estimated 5-year OS and DSS rates were 78% (95% CI, 67‒86) and 92% (95% CI, 84‒97), respectively. Most deaths occurred ≤2 years after infusion; no new safety signals were observed with low rates of late severe infections and second primary malignancies. These data support the curative potential of liso-cel in patients with R/R LBCL. Clinicaltrials.gov: NCT02631044, NCT03435796.
Alcohol-related health information on Chinese short-video platforms: a cross-sectional content analysis of Douyin and Bilibili
Genetic architecture of white matter microstructure captured by unsupervised deep representation learning of fractional anisotropy maps
Abstract Fractional anisotropy (FA) from diffusion MRI is a widely used marker of white matter (WM) integrity, but conventional FA-based genetic studies typically rely on tract- or atlas-defined averages that may obscure spatially distributed WM variation and limit genetic discovery. Here, we propose a deep learning framework, termed unsupervised deep representation of WM (UDR-WM), which uses voxel-wise FA maps to derive brain-wide unsupervised deep imaging phenotypes (UDIP-FA) without prior anatomical assumptions. Compared with traditional FA phenotypes, UDIP-FA shows greater sensitivity to aging and substantially higher SNP-based heritability. Multivariate GWAS identified 939 lead SNPs across 586 loci, mapping to 3,480 UDIP-FA-associated genes. These genes are enriched in glial cells, especially astrocytes and oligodendrocytes, and form disease-relevant modules in protein interaction and co-expression networks implicating myelination and axonal structure. UDIP-FA is genetically associated with multiple brain disorders, cognitive traits, and polygenic risk. Together, our results suggest that UDIP-FA provides a biologically meaningful view of white matter, complementing conventional ROI-based FA measures and offering a more refined way to study its genetic architecture.
GLUL pitches in thrombocytopoiesis by restricting ammonia accumulation during megakaryocyte maturation
Polyploidization resulted from massive DNA synthesis is crucial for megakaryocyte maturation, while the regulatory mechanisms of cell fitness upon this special cellular process remain poorly understood. Here, we reveal that glutamine synthetase (GLUL) facilitates thrombocytopoiesis by restricting ammonia accumulation during polyploidization. GLUL is found to be distinctly expressed in platelet-producing megakaryocytes and increasingly elevated with the progression of polyploidization, and GLUL deficiency impairs megakaryocyte maturation and platelet production. Mechanistically, GLUL detoxifies ammonia derived from adenosine deaminase acting on RNA 1 (ADAR1)-mediated double-stranded RNA (dsRNA) editing in megakaryocytes undergoing polyploidization. Ammonia accumulation is observed in megakaryocytes defective in GLUL, leading to lysosomal and mitochondrial damage and even cell death. Fulvotomentoside A (FtA) is identified as a potential GLUL agonist with the capacity to promote thrombocytopoiesis in mice after radiation and chemotherapy injury. Our findings uncover the biological significance of GLUL in megakaryocyte maturation and provide a new avenue for regulating thrombocytopoiesis.
Coupling-aware efficiency modeling of outphasing power amplifiers for wearable wireless power transfer
Abstract Outphasing power amplifiers (PAs) enable high efficiency under output back-off through constant-envelope operation, making them attractive for wireless power transfer (WPT) systems. However, in practical wearable scenarios, overall efficiency is strongly influenced by the interaction between the power combiner and the coupling-dependent impedance of the inductive link—an effect that has not been systematically characterized. In this work, we present a system-level analytical framework that jointly models outphasing PA operation, Wilkinson and Chireix combiner behavior, and coupling-dependent WPT load variations. The proposed approach enables explicit determination of optimal operating conditions as a function of the coupling coefficient. The analysis shows that for the Wilkinson combiner, the optimal outphasing angle is always θ = 0°, with efficiency primarily limited by wireless link coupling. In contrast, for the Chireix combiner, peak efficiency consistently occurs at the compensation angle θc, while its magnitude is strongly modulated by coupling conditions. These results translate into practical design insights: Chireix-based architectures with θc = 60°–70° can outperform Wilkinson combiners by up to 8% points at moderate coupling (k ≈ 0.2), whereas Wilkinson configurations offer greater robustness under weak or dynamically varying coupling (k < 0.15). Circuit-level harmonic balance simulations for both Wilkinson and Chireix combiners further confirm the analytical trends, demonstrating that the predicted efficiency behavior is physically realizable for both topologies. The proposed framework provides actionable guidelines for early-stage design and architecture selection in wearable WPT systems without requiring device-level or full electromagnetic simulations.
PKMYT1 is a Targetable Vulnerability in del(17p) High-Risk Multiple Myeloma
Deletion of 17p is among the most adverse cytogenetic abnormalities in multiple myeloma (MM). By integrating RNA-seq data from patient MM cells with genetic dependency data from MM cell lines, we identified the protein kinase membrane-associated tyrosine/threonine 1 (PKMYT1) kinase, a member of the Wee family, as a potential therapeutic target in MM cells harboring del(17p). Genetic suppression or pharmacological inhibition of PKMYT1 activity with the selective inhibitor RP-6306 triggered accumulation of DNA damage, micronucleus formation and mitotic catastrophe, resulting in preferential cell death in del(17p) MM cells while largely sparing del(17p)-negative MM cells and healthy cells. RP-6306 also reduced tumor burden and extended survival in vivo in both xenograft and TP53-deficient syngeneic models. Collectively, our findings nominate PKMYT1 as an actionable target and support PKMYT1 inhibition as a biomarker-driven therapeutic strategy for patients with del(17p)/TP53-deficient MM.
ScaHybNet: a scalogram-based hybrid ensemble network for ECG arrhythmia classification
Abstract Cardiovascular diseases are the leading cause of death in the world, requiring the accurate and timely detection of arrhythmias to prevent sudden cardiac death. In this work, ScaHybNet, a deep learning ensemble model is proposed for multi-class arrhythmia classification using the widely adopted ECG Heartbeat Categorization Dataset. The dataset comprises 109,446 samples across five heartbeat classes (N, S, V, F, Q), enabling comprehensive arrhythmia analysis. The proposed method first transforms the ECG signals to 224 × 224 RGB-scalogram images using CWT with the Morlet wavelet. Then, a hybrid model is developed, which is composed of (1) a residual block-based CNN with skip connections to learn spatial features, (2) a BiLSTM layer for learning temporal features from the CNN feature maps and (3) a Transformer encoder layer with a custom-built multi-head self-attention mechanism to capture long-term dependencies. Thus, to address the extreme class imbalance within the data, stratified balancing of the data among normal beat, supraventricular ectopic beat, ventricular ectopic beat, fusion beat, and unknown beat, and inverse-frequency class weighting were performed. They assessed model robustness using fivefold cross-validation. Hyperparameters set to final values included a batch size of 2, 150 epochs, and an Adam optimizer. Ensemble train accuracy 99.81% and the mean accuracy on the fivefold cross validation set was 90.42% ± 1.26 (std) for ScaHybNet. On the test set (unseen data), it showed a total ensemble test accuracy of 94.73%, precision of 76.51%, recall of 82.93%, and F1-score of 77.40%. The ablation test proved the joint efficacy of each part of the model, and state-of-the-art analysis revealed better or equal results on current standards regarding ECG data with noise and imbalance. ScaHybNet appears to offer the potential to act as a more patient-centric tool that could offer considerable benefits to the medical field.
Histidine‑rich Glycoprotein Modulates Platelet Adhesion and Aggregation by Binding to GPIbα and GPIIb/IIIa
Histidine-rich glycoprotein (HRG) is a 75-kDa plasma protein produced by the liver and circulating at about 2 µM, with an additional pool in platelets that is released upon activation. Previously, we demonstrated that HRG downregulates the contact system by binding polyanions and reducing their capacity to activate factor (F) XII. Although HRG localizes on the platelet surface, its role in platelet biology remains uncertain. Accordingly, we investigated whether HRG directly engages platelet receptors to regulate adhesion and aggregation. Using human and murine platelets, we show that HRG (a) binds to glycoprotein (GP)Ibα on resting and activated platelets and to GPIIb/IIIa on activated platelets, (b) competes with von Willebrand factor (VWF) for binding to GPIbα on resting platelets and with fibrinogen for binding to GPIIb/IIIa on activated platelets, and (c) attenuates platelet agglutination, aggregation, and platelet-mediated thrombus growth. Furthermore, in an endothelial-platelet flow system or a collagen-coated microperfusion chamber, HRG reduced VWF-mediated platelet string formation and attenuated platelet deposition under high-shear conditions. Plasma HRG levels in patients with sepsis or COVID-19 were about half those of healthy controls, and reducing HRG to these levels in vitro promoted a hyperreactive platelet phenotype. Therefore, HRG not only modulates coagulation but also platelet adhesion and aggregation by competing with VWF and fibrinogen for binding to GPIbα and GPIIb/IIIa.
Mammalian Brains Seen through the Lens of Evolution
This Viewpoint argues that understanding how the brain controls behavior requires an explicitly evolutionary framework. The mammalian brain did not emerge through the replacement of earlier circuits with perfect alternatives but rather through the elaboration of existing circuits along with the addition of new ones, yielding a hierarchical architecture in which many ancient spinal and brainstem circuits remain functionally essential. In this context, cortex does not directly control behavior but exerts its influence via layer 5 projections to evolutionarily older subcortical motor centers. This view challenges the prevailing corticocentric bias in neuroscience, which often treats cortex as a largely self-contained computational system. We propose that key functions such as attention and efference copy are best understood within this layered organization. Attention may reflect competitive filtering of corticofugal outputs at subcortical bottlenecks, while efference copies arise naturally from branching motor pathways distributed across hierarchical levels that reflect evolutionary history. Crucially, these principles expose important limitations in current computational models, which typically omit subcortical circuitry and treat motor output as a terminal stage of processing. An evolutionary perspective instead demands models that integrate cortex with spinal, brainstem, and midbrain systems as interacting components of a unified sensorimotor hierarchy. Incorporating these constraints will be essential for developing biologically grounded theories of brain function.
Adaptive spatiotemporal graph learning for multi-horizon probabilistic wind power forecasting
Evolutionary Divergence in Dopamine Regulation between Rodents and Primates and Its Implications for Neurobiological Research
Correction: Benchmark evaluation of video large language models in quality assessment of science popularization videos for dry eye
One-argument Lie scaling and sensitivity analysis of UCM liquid flow over a vertical wedge using response surface method
Smart library personalized resource proactive recommendation system integrating user profiling and knowledge graphs
Influence of hybrid fiber reinforcement on strength and durability properties of fly ash blended PSC concrete
Sequential, Multistep, and Cooperative Helicity Evolution in Supramolecular Polymers of Chlorophyll Rosettes
Green synthesis of Rhodobryum roseum-mediated ZnO nanoparticles: a multifunctional evaluation of biomedical activities and agricultural applications
Abstract Nanotechnology is a fast-growing field with diverse applications in various disciplines. Based on the applications in diverse fields and the medicinal significance, R. roseum was phytochemically investigated and was used for the synthesis of zinc oxide nanoparticles (ZnO-NPs). Biosynthesized NPs were characterized using UV spectrophotometry (UV), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and scanning electron microscope (SEM), and used in antioxidant, antibacterial, and seed nano priming activities. Antibacterial activity was observed against Klebsiella pneumoniae, Bacillus subtilis, Enterococcus faecalis, and Staphylococcus aureus, with the maximum zone of inhibition recorded against S. aureus (23 mm ± 0.57) at 1000 µg/ml. ZnO-NPs exhibited the highest antioxidant activity (75.2%) at 100 µg/mL in comparison with the standard (ascorbic acid), which showed 79% activity at the same concentration. The IC50 value of R. roseum -mediated ZnO-NPs obtained was 35.79 at a 20 µg/mL ZnO-NP concentration. Seed priming with R. roseum -mediated ZnO NPs markedly enhanced maize growth, with the highest performance recorded at 200 ppm, yielding 3.33 ± 0.40 g fresh weight, 3.20 ± 0.1 g dry weight, and 6 ± 1 leaves. At this concentration, seedlings also exhibited increased root (13.5 ± 0.57 mm) and shoot length (12.6 ± 0.57 cm) along with elevated chlorophyll content (34.9 ± 4.57), indicating significant improvement in physiological attributes. Compared to the control, nanoparticle treatment at 50 µg/mL increased peroxidase activity from 18.4 to 31.3 U mg⁻ 1 protein, superoxide dismutase from 22.6 to 36.9 U mg⁻ 1 protein, and catalase from 15.2 to 27.8 U mg⁻ 1 protein. In conclusion, green-synthesized ZnO-NPs are effective and can be utilized in agriculture, biomedical, and other fields.