Background and Clinical Significance: Immunoglobulin G4-related disease (IgG4-RD) is a systemic immune-mediated fibroinflammatory disorder that can mimic infection or malignancy. Spinal involvement is exceedingly rare and usually limited to pachymeningitis or epidural pseudotumors. True vertebral bone destruction has been reported only sporadically. Case Presentation: A 54-year-old man presented to our emergency department with severe neck pain after a fall. CT and MRI revealed extensive osteolysis of the C1 posterior arch and odontoid process with atlantoaxial subluxation. Following a second inpatient fall, he developed acute tetraparesis. Emergency posterior occipitocervical fusion (C0-C4) with C1-C2 laminectomy and foramen magnum decompression was performed. Histopathology demonstrated dense lymphoplasmacytic infiltration and fibrosis with up to 36 IgG4+ plasma cells per high-power field and an IgG4+/IgG ratio > 40%, confirming IgG4-RD. The patient recovered substantial motor function postoperatively and regained independent ambulation after neurological rehabilitation. Conclusions: IgG4-RD can rarely present as destructive craniovertebral osteolysis with neurological compromise. Unexplained C1-C2 osteolytic lesions should prompt evaluation for IgG4-RD, a rare but treatable cause of cervical instability.
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Digital game-based learning environments (DGBLEs) are increasingly integrated into classrooms as learning tools, yet limited research exists regarding the impact of students' discrete emotions on digital gameplay performance. This study examined the role of emotions and arousal in predicting performance outcomes during digital gameplay. Thirty-two grade 5 students (Mage = 10.99, 62.5% male) played four digital games (two math; two identically designed non-math). During gameplay, real-time heart rate and affective data were collected and analyzed using an interpretable machine learning approach (XGBoost). Results suggest that students performed better on non-math games, as compared to math games. Real-time anger was associated with lower performance, particularly in games, whereas other emotions and physiological measures were not significant predictors. This pilot investigation suggests that discrete emotions, particularly anger, may play a more important role in performance during math gameplay than in comparable non-math activities. The results highlight the importance of supporting emotional regulation during digital math learning, as unmanaged anger may impact performance. This study contributes to the growing literature on affective dynamics in digital game-based learning.
While state incarceration policies have received much attention in research on the causes of mass incarceration in the U.S., their roles in shaping population health and health disparities remain largely unknown. Merging data on state incarceration policies to vital statistics birth records from 1984-2004, we examine the impacts of two signature state incarceration policies adopted during the "tough on crime" era of the 1990s-three strikes and truth in sentencing-on Black and White birth outcomes. Using a difference-in-differences event study research design that models the dynamic impacts of these policies over time, we find that these policies had opposing effects on birth outcomes. Birth weight outcomes-including mean birth weight and low birth weight-for Black infants worsened markedly in the year three strikes policies were adopted. By contrast, birth outcomes for Black and White infants gradually improved after truth in sentencing policies were adopted. The discordant findings point to distinct, countervailing mechanisms by which sentencing policies can affect population health. We provide suggestive evidence that three strikes policies adversely impacted Black birth outcomes through affective mechanisms, by inducing highly racialized, stigmatizing, and criminalizing public discourse around the time of policy adoption. Our results indicate that truth in sentencing likely impacted birth outcomes via material mechanisms, by gradually reducing community incarceration and crime rates. Altogether, these findings point to the need to further interrogate state criminal legal system policies for their impacts on population health, considering whether, how, and for whom these policies result in health impacts.
For vehicle driving scenarios in complex backgrounds, road sign detection faces challenges such as multi-scale targets, long-distances, and low-resolution. To address these challenges, a detection method based on an improved YOLO11n network is proposed. Firstly, to accommodate the multi-scale characteristics of the targets and improve the network's ability to detect low-resolution objects and details, a Multi-path Gated Aggregation (MGA) Module is proposed, achieving these objectives via multi-dimensional feature extraction. Secondly, the Neck is improved by designing a network structure that incorporates high-resolution information from the Backbone, thereby enhancing the detection capabilities for small and blurry targets. Finally, an enhanced Spatial Pyramid Pooling-Fast (SPPF) module is proposed, wherein a Group Convolution-Layer Normalization-SiLU structure is integrated across various stages of information passing. By fusing adjacent channel information, it effectively suppresses complex background noise across multiple scales and amplifies road marking features, which consequently boosts the model's discriminability for distant and obscured targets. Experimental results on a multi-type road sign dataset show that the improved model achieves an mAP@0.5 of 96.96%, which is 1.42% higher than the original model. The mAP@0.5-0.95 and Recall rates are 83.94% and 92.94%, respectively, while the inference speed remains at 134 FPS. Research demonstrates that via targeted modular designs, the proposed approach strikes a superior balance between detection accuracy and real-time efficiency. Consequently, it provides robust technical support for the reliable operation of intelligent vehicle perception systems under complex conditions.
Sharp force trauma (SFT) is a leading cause of homicide-related deaths, frequently involving kitchen knives as weapons. Offenders may attempt to eliminate forensic evidence by burning a corpse, complicating medicolegal investigation. While scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDS) has successfully detected metallic traces from sharp objects in skin and fresh bone, its efficacy in burned bone is currently unexplored. This study aimed to evaluate the potential of SEM-EDS to detect metallic residues transferred from sharp tools to bone that was subsequently burned, thereby contributing to the development of an identification procedure in forensic investigation. Ten knife strikes were inflicted on fleshed porcine ribs, which were then burned in an electric muffle furnace at 700 °C for two hours. Sharp lesions were analyzed using SEM-EDS to identify transferred chemical elements. Traces of iron and chromium were detected in seven lesions, with silicon identified in two samples. These elements, absent from the control samples, provided robust evidence of transfer from the blade to the bone. The residues appeared as bright spots with either undefined shapes or well-defined particles, located along the lesion edges. This study is the first to confirm the identification of metallic traces from SFT in bone subsequently exposed to heat using SEM-EDS. Despite thermal exposure, residues persist and remain detectable. SEM-EDS analysis is thus a non-destructive, valuable technique for distinguishing heat-induced bone damage from SFT. Further research with a larger sample and a broader range of implements is needed to validate and extend these findings for forensic applications.
Tactile sensors are essential for robots to interact with complex environment, but the precise perception of surface tackiness remains a critical challenge for robotic interactive intelligence. Quantitative adhesion analysis requires measuring both pressure and pulling forces at the exact same location. However, existing sensors struggle with signal crosstalk and baseline instability, failing to achieve this intrinsically decoupled measurement. Here, we report a surface-soft, magneto-mechanical coupling tactile sensor that achieves intrinsic signal decoupling within a single sensing element. By leveraging a skin-like bidirectional deformation design, inward pressure and outward pulling force generate baseline-separated magnetic signatures. This eliminates the need for complex post-processing and enables continuous, high-stability monitoring of the full adhesion cycle-from initial contact to final pull-off. The sensor exhibits only 0.25% force drift over 10 h and remains below 0.30% after hammer strikes and maintains 99.52% signal coincidence across repeated press-pull cycles. Such exceptional performance metrics grant the sensor a level of tackiness differentiation that rivals standard adhesion testing. When integrated with a neural network, the sensor yields 99.78% tackiness identification accuracy under diverse contact conditions, exceeding human precision (85.71%). This work pushes the boundaries of existing tactile sensing and lays a solid foundation for advanced robotic manipulation of tacky and lightweight objects.
Lightning strikes are a rare but potentially devastating cause of injury, particularly in children. Clinical manifestations range from transient neurological disturbances and cardiac arrhythmias to severe burns, auditory damage, and multisystem trauma. Early recognition and prompt resuscitative measures are essential for improving outcomes, as lightning victims often have a high potential for successful resuscitation if treated rapidly. While musculoskeletal, cardiac, and neurological complications are commonly reported, genitourinary injuries, especially bladder trauma, are exceedingly uncommon and, in fact, underreported. We report an unusual and extremely rare clinical case of a lightning strike victim who presented with an isolated bladder injury.
The transition from lipid flat disks to vesicles under shock waves is essential for producing nanosized vesicles during sonication. We perform non-equilibrium molecular dynamics simulations to examine how shock waves interact with a lipid flat disk. The lipid disk consists of coarse-grained saturated phospholipid models and is approximately 30 nm in diameter in the gel phase. Shock waves are simulated using a piston-driven method, with piston speeds limited to 1.0 km s-1 or less. When a planar shock wave strikes, the disk's structural changes depend on the impact angle and the shock intensity. A disk with its rotation axis parallel to the shock direction decreases in thickness while maintaining its circular shape. In contrast, a disk with its rotation axis perpendicular to the shock wave direction undergoes radial compression in the shock propagation direction, causing a temporary increase in ellipticity. Behind the shock front, lipid molecules become disordered, as indicated by a reduction in the average P2 order parameter of lipid chains and the gel fraction in the disk. This suggests that shock waves can trigger the phase transition of lipid disks from the gel to the liquid phase. The shock's intensity and the resulting structural changes influence subsequent vesicle formation. During recovery, vesicles often form from the disk after exposure to higher-intensity shock waves or after a temporary anisotropic disk induced by a side impact. This highlights the importance of impact angle. These structural changes in lipid flat disks caused by shock waves may help in understanding and controlling vesicle sizes through sonication.
High-throughput spatial transcriptomics (ST) now profiles hundreds of thousands of cells or locations per section, creating computational bottlenecks for routine analysis. Sketching, or intelligent sub-sampling, addresses scale by selecting small, representative subsets. While effective for single-cell RNA sequencing data, existing sketching methods, which optimize coverage in expression space but ignore physical location, can introduce spatial bias when applied to ST data. To explore the impact of sketching on ST analysis, we systematically benchmarked uniform sampling, leverage-score sampling, Geosketch (minimax/Hausdorff), and scSampler (maximin) across multiple real ST datasets (mouse ovary, MERFISH brain, human breast cancer, lung) and simulations, using three input representations: Principle Component Analysis (PCA) embeddings, spatial coordinates, and spatially smoothed embeddings. We show that expression-only designs capture global transcriptomic heterogeneity but distort tissue architecture by over-sampling high-variability regions and under-sampling homogeneous areas. Coordinate-only sampling restores tissue coverage but misses transcriptional extremes. A simple spatially aware extension, computing leverage scores from a randomized singular value decomposition (SVD) basis smoothed by a spatial weights matrix, strikes a favorable balance, recovering rare cell states while maintaining uniform tissue coverage and avoiding edge effects. Across robust Hausdorff distances, clustering stability (Adjusted Rand Index), PCA loading drift, and local cell-type mean squared error (MSE), spatially smoothed leverage scores match or outperform alternatives. These results motivate joint spatial-transcriptomic sketching objectives to enable fast, unbiased analyses of increasingly large ST datasets.
An unintended consequence of wind energy generation is bat fatalities caused by wind turbine blade strikes. One potential approach to reduce collision risk is to use ultrasound to create an uncomfortable or disorienting airspace around wind turbine blades. Ultrasonic deterrents (UDs) have produced mixed results in experimental field studies at commercial wind energy facilities, with effectiveness varying by species and location. It is possible that some species can alter their normal echolocation characteristics to counter the signal of UDs. Our broad objective was to maximize the effectiveness of a UD by comparing changes in echolocation characteristics during three UD frequency emissions among species, between seasons, and between sex. We hypothesized that UD emissions with frequencies most similar to each species' echolocation characteristics would be more likely to alter the bats' echolocation, and bat responses would vary between seasons and sex for each species. We released wild-captured bats into a 60 m × 10 m × 4.4 m (length × width × height) flight cage located in San Marcos, Texas, USA, from July to October 2020 and March to May 2021 and monitored echolocation frequencies with ultrasonic microphones. We conducted trials on Brazilian free-tailed bats (Tadarida brasiliensis; n = 54), cave myotis (Myotis velifer; n = 44), red bats (Lasiurus blossevilli, Lasiurus borealis; n = 41), evening bats (Nycticeius humeralis; n = 32), and tricolored bats (Perimyotis subflavus; n = 8). We found that species with high-frequency echolocation calls altered their echolocation signatures more commonly during high-frequency UD emissions, whereas low-frequency bats altered their echolocation signatures more commonly during low-frequency UD emissions. Additionally, echolocation responses varied between seasons and sexes for several species. Variations in responses may be dependent on species migratory status, differences in mating behavior and mating season, hormonal differences between sexes and seasons, and/or constraints on echolocation adaptability. Our results offer insights into the variable effectiveness of UDs at reducing bat fatalities at wind turbines and provide information for potential adjustments to UDs for improved success.
Previous works have shown that increasing the window size for Transformer-based image super-resolution models (e.g., SwinIR) can significantly improve the model performance. Still, the computation overhead is also considerable when the window size gradually increases. In this paper, we present SRFormer, a simple but novel method that can enjoy the benefit of large window self-attention but introduces even less computational burden. The core of our SRFormer is the permuted self-attention (PSA), which strikes an appropriate balance between the channel and spatial information for self-attention. Without any bells and whistles, we show that our SRFormer achieves a 33.86dB PSNR score on the Urban100 dataset, which is 0.46dB higher than that of SwinIR but uses fewer parameters and computations. In addition, we also attempt to scale up the model by further enlarging the window size and channel numbers to explore the potential of Transformer-based models. Experiments show that our scaled model, named SRFormerV2, can further improve the results and achieves state-of-the-art. We hope our simple and effective approach could be useful for future research in super-resolution model design. The homepage is https://z-yupeng.github.io/SRFormer/.
This study presents a new high-resolution GNSS-derived velocity field and the first internally consistent, segment-resolved block model for the Havran-Balıkesir Fault Zone (HBFZ) in western Anatolia. Inversion of the GNSS velocity field was performed using a dense network of 77 sites within a 3D elastic half-space framework to estimate fault slip rates and interseismic coupling. The results reveal that the HBFZ behaves as a kinematically heterogeneous fault system, with deformation systematically partitioned along strike. Block-modeling results indicate pronounced along-strike variations in interseismic coupling and slip-deficit accumulation. While the westernmost Havran segment is weakly coupled and accommodates limited accumulation, the Turplu and Gökçeyazı segments emerge as major strain-accumulation zones with high and laterally continuous slip-deficit rates. In particular, the Gökçeyazı segment exhibits slip-deficit rates of ~4-6 mm/yr and nearly two millennia of seismic quiescence, implying the potential for a future large-magnitude earthquake (Mw ~7.1-7.3). The strong agreement between GNSS-derived deformation patterns and independent geological and paleoseismological constraints suggests that this segment is currently in an advanced stage of the seismic cycle. These findings highlight the importance of segment-scale geodetic observations for seismic hazard assessment in northwestern Anatolia.
Behavioral lateralization, a consistent directional asymmetry in behavior, has been documented across many vertebrates, yet population-level evidence in snakes remains limited and debated. We examined ambush-posture laterality in the Chinese green tree pit viper (Trimeresurus stejnegeri), a nocturnal sit-and-wait predator, using a large dataset compiled from nocturnal field surveys (2014-2025) and verified citizen-science records from iNaturalist (2013-2025). Ambush-posture direction was classified from photographs using a standardized, anatomically referenced procedure based on head-aligned reference lines, and ambiguous cases were excluded unless observer classifications were concordant. We tested for population-level bias among sites using chi-squared tests and binomial logistic regression, and evaluated effects of age class and perching height. Across 283 observations from three localities, snakes at Yangmingshan exhibited a significant rightward bias in ambush posture (36 of 55 individuals = 65.5%; χ 2 = 5.25, df = 1, p = 0.022), whereas no population-level bias was detected at the other two localities. Neither age class nor perching height significantly affected laterality. These results provide the first evidence for site-specific population-level ambush-posture laterality in a snake and suggest that local ecological or demographic contexts, potentially linked to prey community composition and availability, may modulate the expression of laterality. Future work across additional populations and taxa, together with performance-based tests comparing capture success between left- versus right-curved strikes, will be essential for evaluating the adaptive significance of this pattern.
Earthquake magnitude is controlled by where and when rupture propagation stops. Yet rupture arrest has rarely been directly observed in near-field seismic records of natural earthquakes. Here we present systematic near-field observations of ground-motion stopping phases from large strike-slip earthquakes. Analysis of 12 global events shows that transient overshoot in fault-parallel ground surface displacement is a robust diagnostic signature of abrupt termination of rupture propagation. Dynamic rupture simulations reveal that near-field ground motions are strongly amplified by low wavespeed rocks at shallow depth, which enhance the amplitude of displacement overshoot recorded at the surface. The occurrence of stopping phases at near-fault locations far from mapped rupture termini implies that large strike-slip earthquakes rupture in a segmented manner, with dynamic rupture propagation punctuated by abrupt arrest and reinitiation at internal fault-segment boundaries.
On January 1, 2024, a large-magnitude (M7.6) reverse-fault earthquake struck the Noto Peninsula, Japan, generating a tsunami that caused extensive coastal damage. The source fault, inferred from aftershock distributions by the Japan Meteorological Agency, extends approximately 150 km from the peninsula’s western coast to the northeastern offshore region. High-resolution pre-stack depth migrated seismic profiles reveal a large deformation zone (LDZ) within the 2024 coseismic rupture area. This ~ 2.5–3.8 km wide and ~ 30 km long LDZ consists of steeply southeast-dipping reverse faults (~ 50°–75°), which may represent shallow extensions of the deeper seismogenic listric fault, as well as branching faults suggestive of a local strike-slip component. Numerical simulations of tsunami generation suggest that a coseismic slip of 6–7 m along the reverse fault, followed by reactivation of the LDZ, could have produced up to 3 m of seafloor uplift and triggered subsequent tsunamis. In addition, we identified northwest-dipping reverse faults (~ 50°–55°) that appear to be active but exhibited little coseismic slip during the 2024 event. Our findings provide the first detailed characterization of tsunamigenic fault structures within the rupture area of the 2024 Noto earthquake. The online version contains supplementary material available at 10.1038/s41598-026-48075-4.
We aimed to investigate the effect of Sorbothane insole insertion and foot strike patterns on shock attenuation during running. Nine male students participated in the study. Running was performed on a 15 m runway at a constant speed of 3.33 m/s. Two types of insoles (EVA and Sorbothane) and two-foot strike patterns (forefoot and rearfoot) were used, creating four experimental conditions. The tibial acceleration and vertical ground reaction force (GRF) were measured, and their peak and loading rate were calculated. A two-way ANOVA (insole × foot strike pattern) was performed. Tibial acceleration showed no significant interaction. However, the peak and loading rate of vertical GRF were significantly higher in the rearfoot strike pattern. The Sorbothane insole significantly reduced the loading rate only in the rearfoot strike condition. Ankle joint angles showed differences depending on foot strike and insole type. These findings suggest that the foot strike pattern may has a greater influence on impact characteristics than the difference in insole material under the present conditions. While Sorbothane insoles may offer some benefits in reducing impact loading during rearfoot strike, further studies with larger sample sizes are required to confirm these effects.
Tumors represent a global public-health concern, accounting for approximately one-sixth of all fatalities worldwide annually. Attaining precise management of patients across all stages of diagnosis, treatment, and surveillance is not merely a significant challenge in contemporary clinical practice but also a crucial strategy for enhancing patient survival rates. In comparison with traditional testing approaches, liquid biopsy offers the benefits of being less invasive and enabling repeated sampling. Through the examination of biological specimens that can be readily and repeatedly obtained from the patient's body, liquid biopsy can furnish information throughout the entire continuum of disease diagnosis, treatment, and follow-up prognosis. Consequently, it emerges as a highly prospective substitute for tissue samples in the minimally invasive, real-time, and comprehensive monitoring of tumors in clinical contexts. This article conducts a systematic review of the common liquid biopsy markers in the oncology field and their latest detection technologies. It encompasses detection schemes for non-blood samples such as cerebrospinal fluid and feces. Moreover, it proposes a novel framework for the precise management of the entire tumor process based on "multi-marker combination + full sample coverage". The article further deliberates on a series of challenges currently encountered in developing liquid biopsy into a mature clinical testing project. These challenges include the standardization of sample testing procedures, the establishment of standardized reporting systems, and how to strike a balance between the popularity of detection methods and cost control, with the aim of promoting the development of liquid biopsy in tumor early screening, treatment innovation, and extensive application. We anticipate constructing a full-chain system spanning from basic research to transformational production and clinical application. We aim to develop an integrated detection platform, establish standardized reporting procedures and a well-established regulatory mechanism, offer patients full-cycle precise management from diagnosis to rehabilitation, and ultimately convert cancer from an "incurable disease" into a "preventable and controllable" chronic disease. 肿瘤是世界级公共卫生问题，导致了全球每年约六分之一的死亡。在诊断、治疗和监测的每个阶段实现对患者的精准化管理，既是当前临床实践中的一大挑战，也可作为提升患者生存率的重要策略。液体活检相较于传统检测具有创伤性小、可反复采样的优势。通过对患者身体易于重复获取的生物样本进行检测，液体活检能够在疾病诊断、治疗及预后随访全阶段提供信息，成为临床上实现对肿瘤微创、实时、全面监控的极具前景的组织样本替代方法。本文系统综述了肿瘤领域中常见的液体活检标志物及其最新检测技术，涵盖脑脊液、粪便等非血液样本的检测方案，并提出了基于“多标志物联合+全样本覆盖”的肿瘤全程精准管理新框架。文中也探讨了当前将液体活检发展为成熟临床检测项目所面临的一系列挑战，包括样本检测流程标准化、标准化报告制度的建立，以及如何平衡检测方法的普及性与成本控制等问题，以推动液体活检在肿瘤早筛、治疗革新与广泛应用方面的发展。我们期望通过构建从基础研究到转化生产、临床应用的全链条体系，开发一体化检测平台，建立标准化报告流程与完善监管机制，为患者提供从诊断到康复的全周期精准管理，最终使肿瘤从“不治之症”转变为“可防可控”的慢性疾病。
High-voltage electrical injuries from lightning are not only responsible for causing fatal burns but can also cause various neurological abnormalities. Herein, we present a case of a middle-aged woman who was struck by lightning and presented with disorientation and persistent vomiting. The magnetic resonance imaging (MRI) of the brain revealed confluent, symmetrical T2/fluid-attenuated inversion recovery (FLAIR) hyperintensities in the white matter of both cerebral hemispheres and the brainstem. She received steroids for brain inflammation, and her symptoms improved. This is a rare case of lightning-induced diffuse cerebral and brain stem demyelination.