Browse Articles

Toward scalable and sustainable CO₂ capture: RSM-Guided optimization of Mg(OH)₂ slurry bubble column reactor

Observation of Kondo cloud-coupling in a mirror-symmetric carbon nanotube array-molybdenum structure

Sub-second extracellular impedance measurement of epithelial cell monolayers using step excitations and time-domain analysis

Interfacial W–O–Zr ensembles in tungstated zirconia catalysts enable efficient hydrogen-free recycling of polypropylene waste

Abstract Polyolefins are essential plastics to modern life yet create mounting sustainability challenges. Chemical recycling technologies are key but often require harsh conditions, costly hydrogen, noble metals, or complex catalysts with challenging design. We report hydrogen- and solvent-free depolymerization of polypropylene consumer goods at 240 °C, achieving >80% yield into gasoline hydrocarbons with stable performance. A library of tungstated zirconia catalysts synthesized by flame spray pyrolysis with controlled tungsten speciation enables correlating performance with the density of W–O–Zr ensembles prevalent in sub-nanoclusters, with W:Zr = 1:9 emerging as optimal. These acid sites formed during reaction mediate internal hydrogen transfer and selective backbone C–C scission, as deduced from operando spectroscopy. Life cycle and technoeconomic studies, benchmarked against hydrotreatment-based recycling in a harmonized framework, indicate competitive environmental and economic advantages. Together, this work establishes this route’s promise and underscores the value of precision catalyst synthesis in polyolefin valorization.

Identification and analysis of oxidative stress-related genes associated with the occurrence and development of diabetic retinopathy

Cryo-EM structures of ALECT2 filaments from human renal biopsies

Abstract Leukocyte chemotactic factor 2 is a recently identified amyloidogenic protein, whose abnormal aggregation defines a systemic amyloidosis termed ALECT2 amyloidosis. Due to the lack of reliable biomarkers, diagnosis relies primarily on histological demonstration and typing of amyloid deposits in renal biopsies. However, immunohistochemical detection of ALECT2 is often inconsistent, leading to diagnostic uncertainty. The underlying basis remains poorly understood, reflecting our limited knowledge of ALECT2 deposits. Here, using cryo-electron microscopy (cryo-EM), we determined the structures of ALECT2 filaments from renal biopsies of five living patients. Unlike filaments assembled from recombinant proteins in vitro, all 133 residues of mature LECT2 are incorporated into the filament cores, with native disulfide linkages preserved. The filaments consistently adopt the shared six-layered folds in all five patients, indicating a common mechanism of amyloidogenesis. Because all residues are incorporated into the fibril core, epitope accessibility is limited. This can explain variability in immunohistochemical detection and thus highlights the need for conformation-specific antibodies and antibody-independent detection strategies for improving diagnostic accuracy. This biopsy-based workflow not only expands the availability of patient-derived tissue for cryo-EM studies but also demonstrates the potential of cryo-EM as a tool for precise diagnosis of systemic amyloidosis.

Reliability of methods in assessing proximal femur bone quality for hip prosthesis selection

Tumor sialylation regulates G-CSF stability and promotes neutrophil-mediated immunosuppression in breast cancer

Hybrid PVA-alginate immobilization enables configuration-dependent biohydrogen production from Napier grass and oil palm fronds with superior multi-cycle stability

Ecological and genomic signatures of the convergent evolution of planktivory in fossil and living reef fishes over deep time

Abstract Transitions from benthic to pelagic habitats often coincide with shifts in diet, yet the genomic basis and macroevolutionary dynamics of these changes remain poorly understood. Surgeonfishes and allies (Acanthuriformes), with their rich fossil record, dietary diversity, and compact genomes, provide a powerful model to investigate these transitions across deep time. We integrate genomic data from 80 extant species with morphological data from 32 fossils to construct total-evidence, tip-dated phylogenomic trees and reconstruct ancestral diets and geographic ranges. We identify at least seven independent origins of planktivory and four reversals, with transitions concentrated in the Tethys and Indo-Pacific oceans. Contrary to the view that planktivory represents an evolutionary dead end, we find higher reversal rates and lower extinction in planktivores. Time-dependent models support both climate and phylogenetic effects on planktivorous lineage diversification. Using a newly assembled chromosome-level genome and 44 additional assemblies, we apply phenotype-aware selection models to identify 39 genes under convergent positive selection in planktivorous lineages. Six of these genes show accelerated evolution tied to metabolism and dietary specialization, and also exhibit codon-level parallelism or convergence. Our findings illuminate the ecological, biogeographic, and genomic basis of repeated dietary shifts and challenge assumptions about evolutionary constraints in pelagic environments.

Reference intervals reimagined with IRIS for earlier detection and better disease monitoring

Abstract Reference intervals (RIs) are the universal established methodology for interpreting numerical clinical data by comparing individual test results to population-based benchmarks. The quality of these RIs significantly influences individual-level decision-making. This study aims to answer the question on how we can effectively leverage an individual’s personal data in conjunction with that of their peers to compute individual reference intervals (IRIs) for key clinical parameters relevant to disease detection and progression. We describe the IRIS workflow that includes prior data processing and data quality check procedures. The computation of IRI involves the test results of multiple “healthy” data points from the same subject(s) and also from the peers. The model adjusts for covariates like sex and age, enhancing accuracy. The workflow demonstrated the potential utility of IRI in clinical and omics data from two longitudinal studies. For healthy populations, IRIs showed diagnostic value in chronic diseases, while in diseased cohorts, they enabled effective disease monitoring. An integrated application IRIS has been developed, incorporating all described steps in an easy-to-use tool in research and/or clinical practice. The IRI may assist in (1) early detection of disease transition in chronic diseases and (2) monitoring personal disease progression. It facilitates the detection of small deviations in clinical measurements, either using standard clinical biochemistry test results or omics data. With adequate data infrastructure, the IRIS workflow can be integrated into clinical practice by embedding personalised biomarker baselines into AI-enabled decision support systems Such integration provides a complementary layer that enhances the sensitivity and specificity of clinical alerts and risk stratification. Ultimately, this approach has the potential to transform personalised disease diagnosis, management, and patient outcomes.

Blood multiomics reveal a dysregulated lipid mediator-mitochondrial network associated with the outcome of advanced cirrhosis

Regression modeling of optical properties for optical design in high-volume white LED manufacturing

Abstract In high-volume manufacturing of white light-emitting diodes (LEDs), maintaining consistent luminous flux and chromaticity is essential for stable optical performance and process consistency. Variations in the radiant flux of the blue LED chip and the concentrations of yellow (YAG:Ce) and red (SCASN) phosphors can lead to significant performance deviations, increasing production costs and reducing product uniformity. This study proposes a data-driven regression framework to predict three key optical outputs—total luminous flux (lm) and chromaticity coordinates ( x ,  y )—from structural parameters, which may facilitate early detection of deviations and support timely process adjustments. We evaluate multiple-input single-output (MISO), multiple-input multiple-output (MIMO), and a hybrid MIMO-LR cascade configuration that reduces MIMO output dimensionality. Five regression models were examined, including multilayer perceptron (MLP), radial basis function network (RBFN), support vector regression (SVR), random forest (RF), and linear regression (LR). Despite the presence of a clear discontinuity in the input–output space caused by SCASN inclusion, all MIMO-based models achieved high prediction accuracy $$(R^2 > 0.97)$$ for total luminous flux and the chromaticity x coordinate, effectively capturing the piecewise optical behavior. The results indicate that such predictive models can support the analysis of complex relationships between structural parameters and optical outputs, and have the potential to contribute to design optimization and process improvement in large-scale LED manufacturing.

Four-dimensional reconfigurable vascular tunneling machine of spatially programmed liquid crystal elastomers

Music-integrated strength–proprioceptive training improves lower-limb performance and postural balance in adolescents with visual impairment: a randomized controlled trial

Abstract Adolescents with visual impairment (VI) often exhibit reduced physical fitness (PF) and functional autonomy due to limited sensory input and restricted opportunities for physical activity (PA). While integrating music into exercise programs has been shown to enhance motor engagement and sensory compensation in other populations, its potential role within physical training for adolescents with VI remains underexplored. Therefore, this study investigated whether integrating music listening into a combined strength–proprioceptive physical training program could further enhance PF in adolescents with congenital VI. Fifty-nine volunteer participants were randomly assigned to a physical training group (PTG), music-physical training group (MPTG) and control group (CG). The sit-to-stand test (STST), the Killy test, the functional reach test (FRT), and the single-leg stance test (SLST) were conducted before and after 8 weeks of training to assess PF. Our results showed significant pre–post improvements in all assessed PF outcomes in both PTG and MPTG (all p  < 0.001) following the intervention. While both PTG and MPTG demonstrated significant pre–post improvements, post-intervention scores in STST (36.80 ± 6.17 vs. 29.47 ± 3.23 reps), Killy test (77.42 ± 20.10 vs. 63.57 ± 21.16 s), and SLST (25.09 ± 4.33 vs. 20.31 ± 5.99 s) were significantly ( p  < 0.001; p  < 0.01; p  < 0.001 respectively) higher in the MPTG compared to the PTG. However, no significant between-group difference was observed for the FRT (42.04 ± 4.81 vs. 40.84 ± 5.82 cm) following the intervention. No meaningful changes were observed in the control group. These findings suggest that integrating music into strength–proprioceptive training may provide an additional benefit for selected functional capacities in adolescents with VI, which may in turn support greater autonomy in daily activities.

An integrative approach for studying immunological variation in an aging population – The Milieu Intérieur follow-up study

Abstract Human immune responses vary across individuals due to both genetic and environmental factors. We previously established the Milieu Intérieur cohort to define boundaries of healthy immune variation and identify their determinants. To evaluate how immune responses change over time and test whether immune states can predict future disease, we conducted a 10-year follow-up of the cohort. Here we show widespread changes in humoral responses to pathogens over this period, including unexpected seroreversion of cytomegalovirus (CMV) status, despite a general age-related increase in CMV antibodies. We also investigated whether immune profiles at initial recruitment are associated with disease development a decade later. Strikingly, whole blood transcriptional responses to Staphylococcus aureus and Candida albicans stimulation were predictive of subsequent infectious disease. Collectively, the Milieu Intérieur longitudinal study represents a valuable resource for evaluating immune aging and may help identify predictors of adverse health outcomes.

MambaFormer-TPEF: a hybrid state space-transformer framework with two-stage peak enhancement for ultra-long sequence photovoltaic power forecasting

Approaching-unity PLQY and high stretchability in polymer emitters via molecular spacers

Plastinated sectional anatomy applied in CT and MRI studies of the body of the crab-eating fox (Cerdocyon thous)

N-Orbit: towards a universal model and metric for comparing tissue microenvironments

Abstract Spatial omics technologies facilitate comprehensive exploration of tissue microenvironments across development and disease. Yet a theoretical framework for modeling and comparing tissue architecture in diverse biological contexts remains lacking. We introduce N-Orbit, a mathematical model that captures both cell-type composition and spatial relationships within tissue cellular neighborhoods, encoding them as vectors for efficient distance calculations. While not a neighborhood detection method itself, N-Orbit enhances insights gleaned from neighborhoods generated by the plethora of recently developed methods. We benchmark the N-Orbit-based neighborhood distance metric on spatial omics datasets that include ground-truth neighborhoods and clinical outcomes. We demonstrate that N-Orbit outperforms cell-type-enrichment-based metrics in discriminating among neighborhood types, predicting clinical variables, and identifying homologous structures across species. Additionally, N-Orbit enhances model interpretability by tracing neighborhoods back to enriched spatial motifs. N-Orbit holds significant potential for deepening our understanding of how tissue microenvironments remodel during development, disease, and evolution.