Browse Articles

Identification of common transcriptional responses to salinity of two halophytes: Bruguiera gymnorrhiza and Populus euphratica

Higher-order neuromorphic Ising machines—autoencoders and Fowler-Nordheim annealers are all you need for scalability

Retraction: Myogenic differentiation of VCP disease-induced pluripotent stem cells: A novel platform for drug discovery

Distinct trajectory of measurable residual disease in t(11;14) myeloma treated with quadruplet therapy

Abstract Quadruplet (QUAD) induction and autologous stem cell transplantation (ASCT) leads to high rates of measurable residual disease (MRD) negativity with improved outcomes in multiple myeloma (MM). The t(11;14) confers unique biology and different kinetics of treatment response. We analyzed MRD trajectories of patients treated with QUAD/ASCT and MRD-adapted post-ASCT management. Of the 302 patients assessed, 47 (16%) had t(11;14)+ MM. Median follow-up was 45.8 months. MRD negativity at <10−5 level (MRD <10−5) for t(11;14)+ vs t(11;14)− MM was 9% vs 31%, 36% vs 59%, and 53% vs 75% after induction, after ASCT, and any time on treatment, respectively. The rates of sustained MRD negativity <10−5 (S-MRD <10−5) were 38% vs 46%. Median time to MRD <10−5 was 13.6 vs 7.7 months for t(11;14)+ vs t(11;14)− MM, respectively. Progression-free survival (PFS) was superior for patients with t(11;14)+ MM, with 4-year PFS rates of 90% vs 72%. In multivariable analysis, S-MRD <10−5 were associated with reduced risk of progression or death, with no progression seen in those with t(11;14)+ MM who achieved S-MRD <10−5. In the setting of QUAD/ASCT therapy and MRD-adapted post-ASCT management, t(11;14)+ newly diagnosed MM is associated with improved prognosis despite slow conversion to MRD negativity.

Influence of connection configuration on the punching resistance of CFST column–RC slab systems under eccentric loading

Abstract This study investigates the punching shear behaviour and failure mechanisms of concrete-filled steel tube (CFST) column reinforced concrete (RC) slab connections subjected to eccentric loading through an integrated experimental and numerical approach. Twelve specimens with different connection details, including welded bars, bolted connections, and C-shaped embedded bars, were tested to assess the influence of connection configuration, reinforcement arrangement, and bolt embedment length on structural performance. The experimental results showed that welded and bolted connections markedly enhanced cracking load, ultimate capacity, and ductility compared with the control specimen, while the combined welded–bolted configuration achieved the most favourable overall response. The study enhances the understanding of load transfer mechanisms in CFST–RC slab connections. Incorporation of welded bars and bolts substantially enhanced the connection stiffness, strength, and ductility. The two-row welded bar configuration showed significant improvements in load-carrying capacity, while the hybrid welded–bolted connection demonstrated the highest overall performance.

Piezocatalytic reforming of plastics into high-value chemicals

Experimental studies on the mechanical properties of garlic scape

Garlic plants are composite materials with multi-scale structures, and the efficient separation of garlic scapes from pseudo-stems is the core challenge in the mechanized harvesting of garlic scape. To deeply elucidate the separation mechanism of garlic scapes and pseudo-stems, this study first confirmed the orthogonal anisotropy characteristics of garlic plants through microscopic morphology characterization. Based on the theory of composite material mechanics, a mechanical model of garlic plants was constructed. Tensile, compressive, and shear tests were conducted on intact garlic plants and their respective components (garlic scapes and pseudo-stems) using a universal testing machine, and key mechanical parameters were obtained systematically. Significant differences were identified between garlic scapes and pseudo-stems in terms of elastic modulus, peak strain, tensile strength, and shear strength through significance analysis, providing a mechanical basis for their selective separation. To verify the reliability of the experimental data, finite element simulation was performed to validate compression tests of garlic plants. The results indicated a high degree of agreement between the experimental and simulated curves, confirming the validity of the compressive tests. Furthermore, theoretical verification of the shear test results was carried out based on the mixing rule of composite materials, which revealed that the theoretical values of the plant elastic modulus were higher than the measured values in the tests. Combined with scanning electron microscopy (SEM) analysis, it was shown that this discrepancy primarily stemmed from the uneven slippage occurring inside the garlic scapes during the shearing process. This study systematically clarifies the differences in mechanical properties and the underlying separation mechanism between garlic scapes and pseudo-stems, providing critical parameters and theoretical foundations for the efficient and low-damage separation of garlic scapes from pseudo-stems in mechanized harvesting.

Cloudy with a chance of platelets: forecasting chronic ITP

High-precision pothole detection using the ECC-YOLO network with deformable convolution and attention mechanisms

Abstract Road potholes present a significant challenge to urban traffic safety and infrastructure maintenance. Traditional manual inspection methods fail to meet the demands for real-time performance and high accuracy. In this study, we propose ECC-YOLO, a lightweight object detection model based on YOLOv11n, specifically designed for pothole detection in complex road environments. First, we introduce the C3k2DCY module, which extracts multi-scale features and leverages deformable convolution to enhance the model’s ability to capture irregular geometric structures of potholes. Next, a Contrast-Driven Feature Aggregation (CDFA) module is designed to improve feature discriminability at boundary regions by reinforcing the contrast between potholes and surrounding backgrounds, thereby significantly boosting detection precision. Furthermore, an Edge-aware Lightweight Attention-based Spatial Feature Pyramid Network (ELA-HSFPN) is integrated to enable effective fusion and semantic enhancement of multi-level features, jointly combining low-level edge details and high-level semantic cues for improved localization and classification of pothole targets. Experiments conducted on a custom pothole dataset demonstrate that ECC-YOLO achieves an accuracy of 84.5%, a recall of 67.9%, and a mAP@0.5 of 74.2%, while maintaining real-time performance. Compared to the baseline YOLOv11n model, ECC-YOLO improves accuracy by 1.7% points, recall by 2.5% points, and mAP@0.5 by 1.4% points. Ablation studies further confirm the individual contribution of each module to overall performance. Overall, ECC-YOLO demonstrates excellent capability in enhancing detection accuracy, reducing false positives, and adapting to complex environments, indicating strong potential for real-world deployment.

Structurally exclusive Teneurin complexes orchestrate divergent programs in early cortical development

Abstract Cortical migration is a complex process in which neurons migrate along radial glial cells (RGC) to form functional layers. Teneurins (Ten1-4) play a role by interacting with Latrophilins (Lphn/ADGRL1-3). Teneurins are also known as cell adhesion molecules, but how homophilic and heterophilic Teneurin interactions are integrated is unknown. Here, single-particle-cryo-EM data of Ten2 shows that canonical Latrophilin-binding is sterically incompatible with Ten2-dimerisation, making these interactions exclusive. We engineered surface mutations that specifically disrupt Ten2-Ten2 or Ten2-Latrophilin interactions. These are transferrable to Ten4, suggesting conserved binding mechanisms. Proteomics, in-vivo-gene-editing and super-resolution-microscopy show that Ten4 is expressed along RGC fibres and that migrating neurons switch from low-to-high Ten4-expression. Ten4 expression is highest in the cortical plate where Ten4-Ten4 interactions reduce RGC-attachment. In the intermediate zone, Ten4-Latrophilin interactions are required to promote neuron-RGC association. The results show how Ten4 orchestrates different stages of cortical migration by using a structural/functional switch between high-affinity Lphn interactions and low-affinity homophilic interactions, underpinning the integration of distinct migration programmes.

MobileLAMP: A low-cost, portable incubation device for isothermal nucleic acid amplification

Isothermal amplification-based methods for pathogen DNA or RNA detection offer high sensitivity, rapid detection, and the potential for deployment in remote fields and home testing. Consequently, they are emerging as alternatives to PCR and saw a surge in research activity and deployment for the rapid detection of SARS-CoV-2 during the Covid-19 pandemic. The most common isothermal DNA detection methods rely on minimal reagents for DNA amplification and simple hardware that can maintain isothermal conditions and read-out a fluorescent or colorimetric signal. Many researchers globally are working on improving these components based on diverse end-user needs. In this work, we present MobileLAMP, an open-source, 3D-printed incubation device designed for loop-mediated isothermal amplification (LAMP). Composed of off-the-shelf components, MobileLAMP is easily manufacturable and can be powered via any 5V USB source. The device maintains high thermal stability (standard deviation = 0.2°C) across a functional range typically used for LAMP (55–65°C) while consuming only 365 mA of current. Efficacy was demonstrated through the colorimetric detection of SARS-CoV-2 and Salmonella enterica serovar Typhi within a 60-minute incubation period. With a total component cost of less than $5, MobileLAMP provides a highly accessible platform for decentralised molecular diagnostics, supporting both distributed manufacturing and field-based applications.

Mapping risk and therapy in secondary CNS lymphoma

Bioactive secretory leukocyte protease inhibitor (SLPI)-derived short peptides (SDSPs) attenuate LPS-induced inflammatory responses in macrophages

Structure of a contractile injection system in Salmonella enterica subsp. salamae

upsML: A high-accuracy machine learning classifier for predicting Plasmodium falciparum var gene upstream groups

Plasmodium falciparum erythrocyte membrane protein 1 ( Pf EMP1), encoded by the hypervariable var gene family, is central to malaria pathogenesis, influencing both disease severity and immune evasion. Classifying var genes into upstream groups (upsA, upsB, upsC, upsE) is important for understanding parasite biology and clinical outcomes, but remains challenging, especially with partial sequences, such as the DBLα tag or RNA-Seq assemblies. We developed upsML, a machine-learning-based classifier trained on 2,530 curated var genes, to accurately assign upstream groups based on sequence features from different partial gene regions. We compared seven methods, including support vector machines, random forests, XGBoost, and HMMER models. Several models in upsML achieve accuracies of 83% for DBLα-tag sequences and 92% for full-length Pf EMP1 sequences, thereby significantly outperforming existing tools. Additionally, we developed a model to distinguish internal from subtelomeric var genes, which we applied to a global collection of P. falciparum genomes, revealing a higher frequency of internal var genes in Asia. upsML is available at https://github.com/sii-scRNA-Seq/upsML , providing a robust and efficient resource for large-scale var gene analysis. It can classify var genes from 20 genomes in under one second.

A compartmentalized inflammatory landscape and macrophage plasticity regulate <i>Tet2</i> <i>+/−</i> -mediated clonal hematopoiesis

Abstract Clonal hematopoiesis of indeterminate potential (CHIP) is driven by hematopoietic stem cells carrying leukemia-associated mutations that expand in the bone marrow. Several prior studies have revealed that the spatial organization of hematopoietic cells in the bone marrow affects clonal behaviors. Specifically, leukemic blasts have been found to expand almost exclusively in a subset of marrow cavities that are undergoing active bone remodeling, but whether these cavities also support the expansion of nonmalignant mutant clones has never been visualized. Although it is widely appreciated that systemic inflammation promotes the selection of mutant clones, this view has emerged without considering the potential heterogeneity in the inflammatory landscape shaped by local bone remodeling. Leveraging intravital imaging and a murine model of CHIP (Tet2+/−), we demonstrated transcriptional and functional compartmentalization of the marrow microenvironment. Macrophages within nonresorptive cavities are inherently anti-inflammatory, which suppresses disease-initiating Tet2+/− cells while preserving their healthy counterparts. Time-lapse imaging further revealed nontransient association between Tet2+/− clones and CD206+ macrophages. Spatially resolved single-cell transcriptomic profiling and functional assessment revealed that physiological bone remodeling influences CD206+ macrophage plasticity and cytokine secretion, which regulate the clonal burden. In addition, antitumor immunity alteration within the microenvironment occurred as early as the formation of initial clones. Suppressing bone remodeling with zoledronate or targeting macrophage-associated niche factors mitigated clonal development. Collectively, our study reveals a previously unrecognized inflammatory landscape shaped by local bone remodeling. The finding presents targetable mechanisms and warrants further studies on the use and precautions of bone-modulating management in clonal blood disorders.

Effect of HEPA filtration air purifiers on cognitive function from a secondary outcome analysis of a pragmatic randomized crossover trial

Evolution of the reptile spine reveals independent trajectories to axial skeletal complexity in amniotes

Abstract The evolution of complex, highly regionalized and heterogeneous axial skeletons within amniotes has traditionally been considered a unique characteristic of Pan-Mammalia, with limited complexity evolving independently in some reptiles. The ability to resolve axial skeletal evolution across Amniota remains restricted due to the lack of studies comprehensively exploring axial skeletal complexity through deep time outside of Pan-Mammalia. Here, we combine 3D geometric morphometrics of vertebral morphology with maximum likelihood model testing in a phylogenetic context to quantify regionalization and morphological heterogeneity in the presacral vertebral column of reptiles and representative tetrapod outgroups. We recover evidence for the evolution of four regions at least four times independently within amniotes, highly heterogeneous axial skeletal anatomies in archosaurs, and no evidence for uniquely complex vertebral anatomies in mammals. Heterogeneity is positively associated with body size in most reptile clades except for theropod dinosaurs, which also reduce regionalization toward the avian crown. The evolution of volancy is correlated with high heterogeneity, potentially associated with functional modularity of the cervical and dorsal regions. Our results indicate that complex axial skeletons arose independently and repeatedly in reptiles in addition to mammals, variably associated with the remarkable diversity in size, body form, function, and ecology across amniotes.

Mathematical modeling of the frozen zone dynamics: Towards using thermal imagers in cryotherapy

Background Thermal imaging is a convenient technique for cryoablation and cryotherapy monitoring; however, it does not provide insight into subsurface temperature distribution. Objectives and methods Our mathematical model can predict a temperature penetration depth during cryotherapy based on surface thermal imaging. We also generalized this model to use with homogeneous media, such as hydrogels, and multilayered biological structures, including skin, muscle, and subcutaneous fat. Results We developed a mathematical model to describe temperature dynamics in non-uniform materials with temperature-dependent thermodynamic properties and a phase-change boundary. We implemented the model with a graphical processing unit (GPU) to simulate the freezing behavior of hydrogels and biological tissues. The model was validated by comparing simulation results with experimental findings from hydrogel cryoapplications and previous in vivo studies on rats during the freezing phase. Hydrogel, which exhibits thermodynamic properties like those of living tissues and possess optical transparency, enabled direct observation of the freezing front using visual morphometry. This model offers a practical tool for estimating optimal cryotherapy duration, helping to minimize damage to healthy cells. The position of the freezing front in semitransparent hydrogels was quantitatively assessed and found to be consistent with morphometric measurements. Conclusions This study provides a useful framework for comparing in vitro and in vivo thermal field dynamics and for estimating optimal timing in cryoapplications. The mathematical model developed here, with its fast and efficient GPU-based implementation, can be extended to investigate thermal behavior in other uniform and non-uniform materials exhibiting temperature-dependent thermodynamic properties during freeze-thawing.

Treatment-related outcomes and patterns of relapse in secondary CNS involvement by large B-cell lymphoma

Abstract Secondary central nervous system (CNS) large B-cell lymphoma (SCNSL) occurs in the de novo setting, as a CNS-isolated relapse, or synchronous (concomitant CNS and systemic) relapse. SCNSL is a devastating event without therapeutic consensus. Thus, we aimed to evaluate treatment outcomes in an international cohort. Progression-free survival (PFS), overall survival (OS), and cumulative incidence of relapse (CIR, estimated using competing-risk models) were reported. Prognostic factors were identified in a 6-month landmark multivariate analysis. Outcomes after thiotepa autologous stem cell transplant (ASCT) and chimeric antigen receptor (CAR) T-cell therapy (CAR-T) delivered at relapse were compared after propensity score matching (PSM). A total of 1139 patients were included in the analysis (de novo: 537; relapsed SCNSL: 602). Two-year PFS estimates were 40.4%, 43.9%, and 16.2% for de novo SCNSL, CNS-isolated relapse, and synchronous relapse, respectively. Patients with CNS-isolated relapse demonstrated low rates of systemic recurrence (24-month CIR, 6%). Thiotepa-ASCT correlated with longer survival in de novo SCNSL (PFS: hazard ratio [HR], 0.57; P = .005; and OS: HR, 0.62; P = .023) and CNS-isolated relapses (PFS: HR, 0.55; P = .002; and OS: HR, 0.39; P&amp;lt; .0001). ASCT (thiotepa or no thiotepa) also associated with improved survival in synchronous relapses (PFS: HR, 0.57; P = .023; and OS: HR, 0.48; P = .019). Higher survival with thiotepa-ASCT than CAR-T was observed after PSM (PFS: HR, 0.45; P = .005 and OS: HR, 0.41; P = .014). These data support thiotepa-ASCT in eligible patients, particularly de novo disease and CNS-isolated relapses. CNS-isolated relapse was infrequently associated with systemic recurrence, supporting treatment regimens adopted from primary CNS lymphoma.