Search Results (1,901)

Antibody–drug conjugates (ADCs) are a promising therapeutic modality for treating cancer. TM4SF1 is an integral membrane protein that internalizes from the cell surface along microtubules to the nucleus and is highly expressed on the surface of both tumor endothelium and tumor cells. We previously reported that in human tumor xenografts in mice, an ADC directed to mouse TM4SF1 (2A7A-LP2) effectively regressed tumors through an anti-vascular mechanism, and an ADC directed to human TM4SF1 (v1.10-LP2) effectively regressed tumors through an anti-tumor cell mechanism. In this study, we investigated the actions of the mouse TM4SF1-directed ADC on VEGF-A-provoked angiogenic vessels. We employed an adenovirus expressing mouse VEGF-A¹⁶⁴ (Ad-VEGF-A) to induce surrogate tumor blood vessels in the ears of nude mice. We showed that an immune effector function-ablated ADC, 3m2A7A-LP2, was better tolerated than its parent 2A7A-LP2. Homing of 3m2A7A to Ad-VEGF-A-induced new blood vessels became evident within six hours after intraperitoneal injection. A single dose of 3m2A7A-LP2 at 3 mg/kg disrupted evolving Ad-VEGF-A-provoked blood vessels within forty-eight hours, and three doses of 3m2A7A-LP2 at 48 h intervals caused striking local ear necrosis; in each case, there was no apparent harm to vessels in the corresponding control virus-injected ears and the surrounding tissues of the same mice. Our studies demonstrate that an ADC-directed against mouse TM4SF1 specifically targeted the newly formed blood vessels induced by Ad-VEGF-A at multiple stages of their development. Thus, TM4SF1-directed ADCs, through their ability to target angiogenic vessels, represent an alternative anti-angiogenic approach for treating solid tumors. Full article

Background/Objectives: Interstitial cystitis/bladder pain syndrome (IC/BPS) is a chronic condition characterized by pelvic pain, urinary symptoms, and reduced quality of life, with limited effective treatment options. Regenerative approaches using adipose-derived mesenchymal stromal cells (MSCs) have shown promising preclinical results. This study aimed to evaluate the feasibility, safety, and preliminary efficacy of transurethral implantation of autologous micronized adipose tissue (MAT) in patients with refractory IC/BPS. Methods: We conducted a single-center retrospective observational pilot study including 20 patients with refractory IC/BPS treated between April and October 2024. Adipose tissue was harvested via liposuction and mechanically processed using a closed system (Matrigen device) to obtain minimally manipulated micronized adipose tissue. The product was injected transurethrally into the bladder submucosa. Patients were evaluated at baseline and at 1, 3, and 6 months using validated questionnaires (ICSI/ICPI, SF-36, MOS Sexual Function), verbal rating scale (VRS) for pain and urgency, urodynamic parameters, and cystoscopic findings. Changes over time were assessed using paired non-parametric tests. Results: At 6 months, 65% of patients met responder criteria, defined as ≥50% improvement in pain and/or urgency or a positive global response. Significant improvements were observed in IC Problem Index, SF-36, MOS scores, and VRS urgency, while VRS pain improved significantly at 6 months. Urodynamic parameters showed increased bladder capacity (median 275 to 325 mL, p < 0.001) and reduced post-void residual volume (80 to 40 mL, p < 0.001). Cystoscopic findings demonstrated improvement in bladder mucosal appearance. The procedure was well tolerated, with no serious adverse events or immunological complications observed. Conclusions: In this exploratory pilot study, transurethral implantation of autologous micronized adipose tissue was associated with improvements in symptoms, bladder function, and cystoscopic findings in patients with refractory IC/BPS. These results support the feasibility and potential role of minimally manipulated adipose-derived therapies in this setting. Given the small sample size and absence of a control group, findings should be considered exploratory. Larger controlled studies are warranted to confirm efficacy and evaluate long-term outcomes. Full article

In the present study, innovative active gelatin–chitosan films enriched with blackberry (ACTIVE-BF) and sage flower (ACTIVE-SF) extracts were developed and comprehensively characterised with regard to their physicochemical, functional and environmental properties. The incorporation of phenolic compounds increased the film’s UV–Vis (ultraviolet–visible spectroscopy) absorbance, confirming the presence of chromophoric groups and the improvement of light-barrier properties. FTIR (Fourier Transform Infrared Spectroscopy) analysis revealed hydrogen bond formation and intermolecular interactions between polyphenols and the –OH/–NH groups of the biopolymer matrix, which enhanced the structural stability of the films. Adding blackberry and sage extracts slightly increased the hydrophilicity and solubility of the films (40–48%), without significantly affecting their water vapour transmission rate (531–547 g/m²·d). The obtained films exhibited strong antioxidant activity, with FRAP (Ferric Reducing Antioxidant Power) values ranging from 17.75 to 40.83 mM Trolox/mg, DPPH (2,2-diphenyl-1-picrylhydrazyl) radical scavenging capacity between 42.58 and 46.88%, and metal chelating ability up to 50.82%. During the nine-day storage of salmon fillets at 4 °C, the active films effectively inhibited microbial growth (reduction of 1.5–2.1 log CFU/g) while maintaining pH stability (6.2–6.4). Respiration activity confirmed environmental safety. The developed materials represent biodegradable, multifunctional films with high potential for application as sustainable active packaging for perishable food products. Full article

This paper presents a fuzzy-based adaptive admittance control (FAAC) framework for position-controlled robots in uncertain contact environments. The proposed FAAC regulates admittance parameters using three fuzzy adaptation maps rather than directly generating robot control inputs. The Mass-Adaptation Fuzzy Map (MAFM) adjusts the dominant virtual mass eigenvalue, the Damper–Mass Ratio Fuzzy Map (DMRFM) adapts the damping-related ratio, and the Rendering-Quality Supervisory Fuzzy Map (RQ-SFM) restricts unsafe low-mass adaptation based on rendering quality and vibration metrics. An energy-tank-based admissibility filter is integrated to preserve passivity during online parameter adaptation and contact transitions. Comparative simulations against a stiffness-adaptive baseline and an ablated mass–damping adaptive baseline under nominal, noisy, and filtered sensing conditions verify the robustness of the proposed architecture. Experiments on a UR10 polishing task further show that the proposed FAAC improves force-tracking consistency and contact-maintenance robustness compared with fixed-parameter AAC baselines and FAAC-M. In particular, the proposed FAAC achieved the lowest force standard deviation of 2.76 N and no contact-loss events, whereas the baseline AAC controllers exhibited force fluctuations associated with abrupt desired stiffness changes during contact. These results demonstrate the effectiveness of FAAC for robust robot–environment interaction under uncertain contact conditions. Full article

To address the issues of insufficient robustness, large depth recovery errors, and poor scene adaptability currently present in the initialisation phase of event-based stereo visual inertial SLAM systems, we propose a global BA initialisation method based on an adaptive threshold robust kernel function, ES-ATRK. The algorithm first achieves spatio-temporal fusion of events and visual features. Event features are triangulated to obtain depth values that serve as the 3D map, whilst visual features provide 2D observations; both modalities jointly feed the Structure from Motion (SfM) pipeline, laying the foundation for global bundle adjustment (BA) optimisation. The core contribution lies in incorporating a robust kernel function into the global BA to suppress outlier interference and in designing an adaptive thresholding algorithm that dynamically determines the kernel threshold. Furthermore, the algorithm calculates an initial threshold based on the quantile distribution of residuals prior to BA optimisation, combined with validity checks and a multi-round iterative smoothing adjustment strategy, thereby achieving scene-adaptive thresholding. In over 85% of the test scenes on the VECtor dataset, its localisation accuracy improved by at least 10% compared to existing mainstream event-based SLAM methods, such as ESVIO and USLAM. In high-dynamic scenes, its ATE performance is approximately twice that of mainstream models such as ESIO, and it maintains excellent positioning accuracy and stability of three-axis errors in generalisation tests on the HKU and MVSEC datasets. Furthermore, in the large-scale outdoor testing scenarios of the DSEC dataset, ES-ATRK also demonstrates superior feature tracking and trajectory estimation performance. This method effectively enhances the robustness of initialisation and depth recovery performance in event-based stereo visual inertial SLAM systems, reduces overall positioning error, and offers greater adaptability in challenging scenarios such as low-texture, high-dynamic, and HDR environments. Full article

Background: Facial skin aging is a multifactorial process characterized by wrinkles, pigmentary alterations, reduced elasticity, and dermal structural changes, in which oxidative stress and low-grade inflammation play key roles. Polyphenols have gained interest in cosmetic science due to their antioxidant and skin-protective properties. Objective: We evaluated the antioxidant activity, clinical–instrumental performance, and tolerability of a topical cream containing 4% w/w Aliophen^®, a polyphenol-rich malt–hop extract, after 56 days of twice-daily application. Methods: Antioxidant activity was assessed in HaCaT keratinocytes exposed to tert-butyl hydroperoxide (tBHP, 500 μM), with intracellular reactive oxygen species (ROS) measured by DCFH-DA assay after Aliophen^® treatment (4–16 mg/mL). A prospective, single-center, open-label study included 20 women aged 45–65 years with facial aging signs. Instrumental assessments included wrinkle depth (PrimosCR SF), pigmentation (ITA°), skin biomechanics (Cutometer^® R0, R2), and dermal echogenicity (50 MHz ultrasound) at baseline, Day 28, and Day 56. A small subgroup with mild-to-moderate atopic skin (N = 5) was descriptively monitored using SCORAD. Results: Aliophen^® significantly reduced ROS in a dose-dependent manner. Wrinkle depth decreased at Day 28 (−8.1%; p = 0.003) and Day 56 (−15.9%; p < 0.001). ITA° increased (+11.5% and +18.2%; p ≤ 0.003). Skin biomechanics improved (R0 −5.3%; R2 +5.5%; p ≤ 0.004). Dermal echogenicity increased at Day 56 (+1.38; p = 0.002). SCORAD showed descriptive improvement. No serious adverse events occurred. Conclusions: A topical cream containing 4% Aliophen^® improved instrumental markers of facial aging with good tolerability, supporting further randomized, vehicle-controlled studies. Full article

Underwater image enhancement has been widely studied to improve visual quality; however, its impact on downstream geometric tasks such as sparse 3D reconstruction remains insufficiently understood. In particular, visually enhanced images do not necessarily lead to improved feature matching or reconstruction performance. This work addresses the problem of selecting appropriate preprocessing strategies for underwater Structure-from-Motion (SfM) pipelines from a task-oriented perspective. We propose a lightweight machine-learning-based preprocessing selector that predicts reconstruction performance from image statistics and recommends suitable enhancement strategies for each input sequence. To ensure reliable evaluation, we introduce a grouped leave-one-parent-sequence-out protocol that avoids overlap-induced bias common in clip-wise splitting. Experiments are conducted on challenging underwater datasets derived from the Real-world Underwater Image Enhancement (RUIE) benchmark, with the primary comparison variable defined as the number of reconstructed sparse 3D points. Supporting geometric variables, including the number of registered images, mean track length, and mean reprojection error, are recorded for interpretation. Results show that preprocessing choices significantly affect reconstruction outcomes and that the optimal strategy is scene-dependent. The proposed selector consistently improved over raw input on the evaluated grouped subset and remained competitive with a strong fixed preprocessing baseline. The grouped leave-one-parent-sequence-out protocol is intended to reduce overlap-induced bias common in clip-wise splitting and to provide a more conservative estimate of generalization. This work highlights the importance of task-aware preprocessing and reliable evaluation in underwater vision systems, offering practical insights for deploying enhancement strategies in real-world 3D reconstruction pipelines. Full article

Metabolic dysfunction-associated steatotic liver disease (MASLD) is increasingly recognized as a systemic disorder shaped by genetic variants and network-level interactions beyond obesity and insulin resistance. This study aimed to define the genetic and proteomic architecture of MASLD by integrating GWAS and plasma proteomic profiling from the UK Biobank. Genome-wide association analyses were conducted under additive and dominant models, with functional annotations performed using SIFT, PolyPhen-2, PROVEAN, REVEL, CADD, MutationTaster, and conservation metrics (GERP++, phyloP, phastCons, and B-statistic). Differential protein expression was assessed using the Olink^® platform, and STRING was applied for protein–protein interaction analysis. MASLD patients showed male predominance and significant differences in hepatic (AST, ALT, GGT, PDFF), metabolic (glucose, triglycerides, TyG index), and inflammatory markers (CRP, neutrophils, NLR, CAR). GWAS confirmed PNPLA3 (rs738409, I148M) and TM6SF2 (rs58542926, E167K) as major risk variants, while SAMM50 and NCAN showed weaker but conserved associations. Proteomics revealed downregulation of IGFBP2, IGFBP1, PON3, CKB, and APOF and upregulation of CPM, IGSF9, GUSB, ACY1, AFM, LEP, and GSTA1/3. PPI analysis identified ADIPOQ, LEP, FGF21, and ADH1B as central hubs in metabolic and inflammatory regulation. MASLD should be regarded as a network disease involving lipid metabolism, insulin/IGF signaling, mitochondrial function, and ECM–inflammatory pathways. These findings highlight PNPLA3 and TM6SF2 as major genetic drivers, while SAMM50, NCAN, and peripheral proteins contribute regulatory roles, suggesting novel biomarkers and therapeutic targets. Full article

Background: Lumbar disc herniation (LDH) is the most common etiological cause of low back pain (LBP). Objective and precise pain evaluation is of significant clinical value. Functional near-infrared spectroscopy (fNIRS) as a noninvasive neuroimaging modality, has been increasingly validated to reflect subjective pain perception through hemodynamic correlates. This study aimed to analyze the fNIRS changes in patients with LDH about to receive Unilateral Biportal Endoscopy and to further explore the feasibility of fNIRS as an objective biomarkers for clinical assessment of LDH. Methods: Resting-state fNIRS data were acquired from 67 preoperative LDH patients and 20 healthy controls (HC). Brain functional maps—including z-standardized fractional amplitude of low-frequency fluctuations (zfALFF) and seed-based functional connectivity (FC)—were extracted and quantified. Group-level comparisons were performed between LDH and HC groups across four predefined regions of interest; additionally, correlation analyses were conducted between fNIRS metrics and clinical assessment scores within the LDH cohort. Results: Compared with HC, LDH patients exhibited significantly altered zfALFF in the medial prefrontal cortex (mPFC): decreased amplitude at channel CH12 (t = −2.031, p = 0.045) and increased amplitude at CH21 (t = 2.462, p = 0.016). Whole-brain FC analysis further revealed widespread changes—particularly between the parietal somatosensory cortex and prefrontal regions. Among all tested FC–clinical indicator associations, 56 reached statistical significance after FDR correction (q < 0.05). VAS_ lumbar and SF-36_SF exhibited the highest number of significant connections. Conclusions: LDH patients with LBP exhibit notable alterations in prefrontal resting-state ALFF and FC between the parietal somatosensory cortex and prefrontal cortex relative to HC. Importantly, these neural alterations exhibit significant associations with both pain severity (VAS) and long-term health-related quality of life (SF-36), thereby strengthening their candidacy as neural correlates meriting prospective validation as objective, mechanism-informed biomarkers for clinical evaluation of lumbar disc herniation (LDH). Moreover, these findings highlight candidate neural targets for future longitudinal studies investigating early prognostic prediction and treatment response monitoring in LDH. Full article

Background/Objectives: Abnormal general movements (GMs) in high-risk infants are among the most sensitive early predictors of cerebral palsy (CP) and other neurodevelopmental disorders. This study described changes in the quality of GMs over time in high-risk infants who received the Early Intensive Stojčević–Polovina Rehabilitation Method (EIR–SPM). The EIR–SPM is a rehabilitation method designed for children with CP, those at risk of developing CP, and children with other developmental disabilities. In high-risk infants, it is initiated within the first three months of corrected age, preferably while writhing movements (WMs) are still present. Methods: This study was conducted in eight high-risk infants with abnormal WMs and structural brain injury. The EIR–SPM was initiated between 41 and 47 weeks postmenstrual age (PMA) and was applied until 60 weeks PMA. Prechtl’s General Movements Assessment (GMA), the Detailed GM score, and the Motor Optimality Score–Revised (MOS–R) were assessed. Results: During the writhing period, two infants showed a poor repertoire (PR) pattern and six showed a cramped–synchronized (CS) pattern of GMs; at follow-up, three showed PR, and five showed CS. During the fidgety period, two infants showed normal fidgety movements (F+), two sporadic fidgety movements (sFM), one infant showed abnormal fidgety movements (aFM), and three showed absent fidgety movements (F−) at the first assessment, while at the second assessment, three infants showed F+, two sFM, one aFM, and two F−. The median Detailed GM score increased from 12 (range 11–17) to 13.5 (range 11–19; p = 0.068). The median MOS–R increased from 17.0 (range 12–24) to 19.5 (range 17–27) between the two fidgety assessments (p = 0.027). Conclusions: Improvements in motor repertoire, reflected by increased MOS–R scores, were observed during the EIR–SPM initiated in the writhing period. Larger controlled studies are needed to confirm these preliminary observations. Full article

High-resolution remote-sensing semantic segmentation requires models to simultaneously capture global scene semantics and preserve fine-grained local structures. Although satellite-pretrained vision foundation models provide strong transferable representations, the features extracted by a frozen backbone remain insufficiently adapted to dense prediction, particularly for representing high-frequency details and multiscale local patterns. In addition, correcting residual prediction errors with dense full-map refinement introduces substantial computational redundancy, since hard errors are typically concentrated in only a small subset of locations. To address these challenges, we propose ADVMSeg, an efficient remote-sensing semantic segmentation framework built upon a frozen satellite-pretrained DINOv3 backbone. Specifically, we introduce a Spatial-Frequency Adapter (SF-Adapter) to improve backbone-level dense feature adaptation by jointly modeling global frequency responses and multiscale local spatial details in a lightweight bottleneck space. We further design an Adaptive Sparse Refinement (ASR) module after the pixel decoder, which identifies hard regions from coarse predictions via uncertainty and boundary cues, and performs targeted local cross-attention refinement only on selected critical locations. Extensive experiments on GID-15, LoveDA, and ISPRS Potsdam validate the effectiveness of the proposed framework. Under the unified setting, ADVMSeg achieves 63.1% mIoU on GID-15, 63.5% mIoU on LoveDA, and 81.4% mIoU on ISPRS Potsdam. These results validate the effectiveness of jointly improving backbone-level feature adaptation and prediction-stage computation allocation under the evaluated setting of frozen DINOv3, and three representative remote-sensing semantic-segmentation datasets. Full article

Background: This study aimed to examine whether a physical education program based on the ecological dynamics approach, implemented through small-sided games (SSG), produces greater improvements in motor skills, daily physical activity levels, and perceived physical fitness in middle school students. Methods: Forty-eight students were assigned to an SSG group (ecological dynamics lessons including small-sided games, n = 26) or a Control group (traditional lessons based on teacher-centered instruction and analytical exercises, n = 22). The intervention lasted 12 weeks, with two sessions per week. Motor performance was assessed using the standing broad jump, 5-standing broad jump, 20 m sprint, 10 × 5 m shuttle run, 5-0-5 agility test, and sit-and-reach test. Daily physical activity was evaluated using the International Physical Activity Questionnaire—Short Form (IPAQ-SF), and perceived physical fitness was assessed using the Visual Analogue Fitness Perception Scale for Adolescents (FPVASA). Results: Significant group-by-time interactions were found in all motor tests. IPAQ-SF data revealed significant group-by-time interactions for vigorous and moderate physical activity. Perceived physical fitness showed significant group-by-time interactions for all items except flexibility. Conclusions: Physical education lessons structured according to the ecological dynamics approach and implemented through SSG-based protocols led to greater improvements than traditional methods. The dynamic and variable nature of SSG likely enhances neuromuscular stimulation, motor engagement, and motivation during physical education lessons. Full article

The use of agricultural waste fibres and natural binders is being investigated as alternatives to synthetic indoor acoustic materials. However, few studies have compared the fibre type, biopolymer type, and fibre-to-binder ratio for both sound absorption and sound transmission within a single controlled composite system. This study investigated the acoustic performance of sugarcane fibre (SF) and coconut fibre (CF) with a fixed thickness of 20 mm and density of 200 kg/m³, mixed with cassava, corn and potato starch binders with fibre–binder ratios from 1:1.0 to 1:0.1. Sound absorption coefficient was measured with an impedance tube, according to ISO 10534-2, and the sound transmission coefficient was determined using a four-microphone impedance tube system, according to ASTM E2611. Porosity was also tested for its relation to acoustic behaviour. The results showed that the coconut fibre composite recorded higher peak absorption, including α = 0.95 for cassava 1:0.6 to 1:0.7 and corn 1:0.6, while sugarcane fibre showed stronger transmission resistance, with SF-CAS-200-1:0.3 decreasing from τ = 0.11 at 160 Hz to 0.02 at 5000 Hz, and SF-PT-200-1:0.4 from τ = 0.10 to 0.03. The highest porosity values were 85.29%, recorded for SC-CAS-200-1:0.1, and 84.13% for CF-CAS-200-1:0.1. Overall, sugarcane fibre composites offered the best balance of absorption and low transmission, indicating strong potential for sustainable indoor acoustic panels, such as ceiling linings and wall systems. Further research should evaluate mechanical strength, fire performance, durability, and moisture resistance to support practical building applications. Full article

Hydrological monitoring is crucial for protecting aquatic ecosystems, especially downstream of hydropower plants where water levels can change suddenly and cause the degradation of instream habitats. There are lot of traditional methods used to monitor water levels and river bathymetry, but most of them rely on in situ measurements. Drone-based remote sensing has received more attention in recent years, with the data in turn processed using CNNs. In this paper, we propose a new sequence-based method that uses multiple frames to expand the available context and compare it to already existing methods, such as Lyzenga, Stumpf, CNN, and SfM. The best performing models within this study end up being SfM and CNN, with the former being more accurate on rivers with clean riverbeds and the latter being the most consistent. The sequence-based model shows promise, and even outperforms CNN, in terms of MAE, on rivers where the same location across multiple views is mapped, achieving the most accurate results across different images. This shows that utilizing multiple views to increase the available context can improve the accuracy of riverine depth estimation based on multispectral visual information. Full article

In unmanned aerial vehicle (UAV)-based monocular inspection, cracks typically present as geometrically asymmetric, elongated, low-contrast weak targets, making accurate segmentation and spatial localization challenging. Existing methods are susceptible to missed detections and false positives when handling slender cracks, and monocular 3D reconstruction for localization is often burdened by redundant frames, resulting in limited modeling efficiency. To mitigate these issues, we propose a high-precision framework for crack segmentation and spatial localization from UAV imagery. First, Oriented FAST and Rotated BRIEF–Simultaneous Localization and Mapping, version 3 (ORB-SLAM3) is adopted for keyframe selection to suppress data redundancy and improve reconstruction stability. Second, we develop an enhanced YOLOv11-seg model by integrating the Dilation-wise Residual Segmentation (DWRSeg) module, the Weighted IoU (WIoU) loss, and the Lightweight shared convolutional separator batch-normalization detection head (LSCSBD) to strengthen feature discrimination and segmentation robustness for slender cracks, yielding high-quality crack masks. Finally, the predicted masks are projected onto the reconstructed 3D surface to obtain precise spatial localization. Our experimental results demonstrate that the proposed approach improves the segmentation mAP@50 by 7.2% over the baseline while reducing computational complexity from 10.2 to 9.8 GFLOPs. In addition, keyframe-based processing reduces the 3D modeling time by 59.4% compared to that with full-frame reconstruction. Overall, the proposed framework jointly enhances crack segmentation accuracy and substantially accelerates 3D modeling and localization, providing an effective solution for efficient UAV-based crack inspection. Full article