Search Results (4,125)

Internalized Weight Bias (IWB) is consistently associated with poor body image, elevated depression, and diminished self-esteem. However, very little research has examined how additional psychological constructs may indirectly influence the association between IWB and these outcomes. This investigation examined whether IWB was associated with body image, depression, and self-esteem among individuals with overweight and obesity indirectly through body shame, experiential avoidance, and self-compassion. The current sample included 403 participants, with slightly over half the participants (51%) identifying as a female with an average age of 48.3 (SD = 16.9, range 18 to 84), and an average BMI of 33.1 (SD = 7.5, range 25 to 68). Participants were recruited through a Qualtrics research panel that was reflective of the United States population on variables of education, geographic location, income, and biological sex. All participants were aged 18+ and had a BMI ≥ 25. To maximize racial/ethnic diversity, the current sample contained three equally represented self-identified racial/ethnic groups: Black non-Hispanic or Latino/a (N = 140), Hispanic or Latino/a (N = 133), and White non-Hispanic or Latino/a (N = 130). Results showed a significant indirect effect of IWB on psychological and body image outcomes through body shame, experiential avoidance, and self-compassion. Future longitudinal research examining the contexts in which body shame, experiential avoidance, and self-compassion may act as mediators will be important to further develop an understanding of IWB. Full article

Responsive microgels have emerged as a versatile class of soft materials for biomedical applications owing to their tunable physicochemical properties, high water content, and ability to respond dynamically to external and biological stimuli. This review summarizes recent advances in the design, synthesis, and biomedical utilization of responsive microgels, with a focus on their functional roles across key application domains. First, the fundamental principles governing microgel responsiveness and structure–property relationships are briefly introduced. The application of responsive microgels in controlled drug delivery is then discussed, highlighting stimulus-triggered release mechanisms, payload protection, and spatiotemporal control of therapeutic delivery. Advances in tissue engineering are reviewed with emphasis on microgel-based scaffolds, injectable constructs, and cell–matrix interactions that promote tissue regeneration. The use of microgels in biomedical imaging is examined, including their roles as contrast agents, signal amplifiers, and carriers for imaging probes. Finally, recent developments in microgel-enabled diagnostics are presented, showcasing their utility in biosensing, biomarker detection, and point-of-care platforms. The literature was selected based on the authors’ expertise, focusing on representative and recent studies, and identified through general academic databases and key references. Collectively, this review provides a comprehensive overview of the multifunctional capabilities of responsive microgels and discusses current challenges and future opportunities toward their clinical translation. Full article

Hybrid materials, combining synthetic and biological components, leverage the biocompatibility of biological tissues—even after decellularization—alongside the mechanical strength, durability, and impermeability of synthetic polymers. This study presents the functional assessment of two hybrid conduits developed by coupling decellularized porcine pericardium and decellularized swine intestinal submucosa with a commercial polycarbonate urethane, intended for use as vascular and urinary substitutes, respectively. The response of the hybrid conduits to pulsatile flow was evaluated under physiologically relevant conditions in terms of pressure and flow rate. Their ability to withstand cyclic dilations was assessed using a dedicated image processing method that integrates classical approaches with AI-based segmentation techniques. Mechanical tests were also performed before and after hydrodynamic testing to investigate the potential effects of two different fluids—distilled water and simulated body fluid—on the hybrid materials following cyclic hydrodynamic stimulation. The results demonstrate that hybrid conduits deserve to be subjected to further evaluations to prove their potential use as substitutes in vascular and urological surgical applications. Full article

The diagnostic field of prostate cancer (PCa) has undergone a significant evolution with the widespread integration of multiparametric magnetic resonance imaging (mpMRI) and mpMRI-targeted biopsies (TBx). This approach has been shown to improve the detection of clinically significant prostate cancer (csPCa) while reducing the overdiagnosis of low-risk disease. However, a conceptual and clinical challenge, which can be referred to as the “Precision Paradox,” has emerged. By directing biopsy cores almost exclusively into the most suspicious MRI lesions, clinicians may inadvertently overrepresent the biological significance of a limited high-grade component. This can lead to grade migration and pathological downgrading at the time of radical prostatectomy (RP). Although downgrading does not automatically equate to clinical overtreatment, it introduces prognostic uncertainty that complicates risk stratification for active surveillance (AS) and focal therapy. This conceptual commentary provides a critical perspective on this diagnostic issue. We synthesize recent meta-analyses to evaluate the true rates of grade mismatch associated with TBx and combined biopsy approaches. Furthermore, we discuss the spatial limitations of biopsy sampling, the pathological mechanisms driving grade discordance, and the clinical relevance of minor high-grade components such as cribriform architecture. Finally, we highlight the role of multi-omics and validated genomic biomarkers in risk models, ultimately fostering improved shared decision-making in the modern mpMRI era. Full article

Plastic pollution has emerged as one of the most pervasive environmental challenges, with microplastics (MPs) widely distributed across marine ecosystems worldwide. This study aimed to assess the uptake of MPs by key fish and invertebrate species from different locations in the coastal zone of the Bulgarian Black Sea. Fish were collected during routine monitoring surveys in September–November 2024, while invertebrates were obtained via scuba diving. The presence of MPs in fish stomachs and invertebrate soft tissues, and their polymer composition, shape and size were analyzed using an Agilent 8700 LDIR Chemical Imaging System. Potential biological effects of ingested MPs were evaluated by an integrated Specific Oxidative Stress (SOS) index. The results revealed MP uptake levels comparable to those reported globally. Small-sized particles (<50 µm) with rounded shapes were most abundant across studied taxa. Polymer composition varied considerably depending on species and sampling region, indicating differences in exposure sources and environmental conditions. Oxidative stress levels in both fish and invertebrates showed substantial interspecific variation, and clear differences between the northern and southern region of the Bulgarian Black Sea. Overall, elevated uptake of MPs appears to contribute to oxidative stress in marine organisms, potentially affecting their health status, resilience, and adaptive capacity, as reflected by increased SOS index values. Full article

Background/Objectives: The frontal sinus exhibits individual morphological variability that may support human identification. Its development progresses through childhood and adolescence and stabilizes in early adulthood, with age-related changes potentially affecting radiological comparisons. This study presents a forensic case report and discusses it in light of the literature on frontal sinus development and forensic identification. Methods: A comparative radiological analysis was conducted using images obtained at two distinct stages of biological maturation (14 and 21 years of age). Manual delineation combined with semi-automated computational analysis was applied to assess morphological features of the frontal sinus, including contour configuration, lobulation, and dimensional parameters. Results: The intra vitam record was obtained at 14 years of age, during an active developmental phase, and the post mortem examination was obtained at 21 years, corresponding to early adulthood. Comparative analysis revealed significant morphological differences, including increased lobulation, contour complexity, and sinus expansion. These changes limited the reliability of frontal sinus morphology for identification in this case. Friction ridge examination independently established positive identification. Conclusions: This study highlights the limitations of frontal sinus analysis when applied across periods of active development and underscores the risk of misinterpretation if age-related changes are not adequately considered. Full article

Breast implants are among the most frequently used long-term implantable medical devices in aesthetic and reconstructive surgery. In addition to correcting anatomical deficits, they have significant psychosocial effects, influencing body image, self-esteem, and quality of life, particularly in patients undergoing postmastectomy reconstruction. This review provides a comprehensive overview of the historical development, biological interactions, material characteristics, and clinical outcomes of breast implants. Early reconstructive attempts using foreign materials and injectable substances were associated with severe complications, underscoring the need for safer technologies. The introduction of silicone gel implants in the 1960s marked a pivotal advancement, followed by the development of saline-filled devices and highly cohesive silicone gels with enhanced mechanical stability. Key surgical considerations, including incision type and implant placement plane (subglandular, submuscular, dual-plane, and subfascial), are discussed in relation to aesthetic outcomes and complication risk. Emphasis is placed on the implant–tissue interface and the foreign body response (FBR), a process involving protein adsorption, immune cell activation, fibrous capsule formation, and potential chronic inflammation. Persistent inflammatory stimulation, often associated with bacterial biofilm formation, contributes to capsular contracture, the most common long-term complication. Additional adverse events include implant rupture, silicone gel bleed, granulomatous reactions, infection, hematoma, implant malposition, and rare but clinically significant conditions such as breast implant-associated anaplastic large cell lymphoma (BIA-ALCL). The review also summarizes implant classification according to construction, filling material, shape, and surface topography, highlighting the influence of surface characteristics on host response and clinical outcomes. Advances in biomaterials, cohesive gel formulations, and surface engineering aim to enhance biocompatibility and long-term safety, supported by standardized mechanical and biological testing protocols. Full article

Exposure to blast waves without kinetic, penetrating, thermal, or toxic components causes a distinct form of traumatic brain injury, termed primary blast-induced TBI (pbTBI). Clinical manifestations of pbTBI span a wide spectrum, ranging from life-threatening intracranial hemorrhage, hyperemia, and delayed cerebral edema to mild and transient neurological symptoms without detectable structural abnormalities on routine imaging. At the mild end of the spectrum, symptoms after a single exposure may resolve quickly, yet repeated exposures—even at very low levels, termed “subconcussive”—can develop into post-concussive syndrome (PCS) or persistent post-concussive symptoms (PPCS) in a subset of individuals. Despite extensive studies, the molecular pathobiology linking primary blast exposure to delayed and sometimes chronic neurobehavioral deficits remains incompletely understood. A mechanistic framework connecting blast-wave physics to biomechanics to biological vulnerability may therefore help define exposure hazards, interpret clinical symptomatology, and guide diagnostic and therapeutic development. This review summarizes the physics of primary blast waves, the resulting biomechanical responses, and candidate biological substrates, emphasizing structures and interfaces with distinct acoustic impedances across anatomical, tissue, cellular, and molecular scales. We synthesize evidence supporting the hypothesis that the cerebral vasculature and endothelial cells represent critically vulnerable substrates of primary blast-wave injury, in part because the vascular tree constitutes the brain’s largest and most widely distributed interface between compartments with different acoustic impedances. Across experimental and human studies, endothelial stress, vascular injury, and downstream neuroinflammation emerge as convergent molecular responses to primary blast exposure. Temporal dynamics are central to understanding pbTBI because many blast-induced processes unfold in sequential phases. These observations support conceptualizing pbTBI as a condition characterized by prominent cerebrovascular injury of varying severity with secondary consequences for neuronal signaling, network function, and behavior. Within this framework, cerebrovascular and neurovascular unit (NVU) dysfunction provides a parsimonious bridge between primary blast-wave exposure and chronic symptom trajectories, where vascular pathology may offer more accessible therapeutic targets than neuronal injury. Key knowledge gaps include identifying which physical component(s) of the blast are most injurious, establishing biologically meaningful dose–response relationships at molecular and physiological levels, and defining windows of vulnerability during recovery that are relevant to repeated exposures. Addressing these gaps is essential for refining safety protocols, improving diagnostic specificity through mechanism-informed biomarkers, and developing evidence-based molecular and vascular therapeutic targets for pbTBI-associated conditions. Progress will require integrating waveform-aware dosimetry with longitudinal physiological and molecular monitoring across both preclinical and human cohorts. Such integration offers a practical path toward translating blast physics into actionable medical guidance for prevention, triage, and recovery management. Full article

The non-invasive determination of live weight and body composition of ewes is an important element in ensuring precision livestock management and animal well-being. Traditional practices tend to be subjective, labor-intensive, or rely on expensive medical imaging such as Computed Tomography (CT). This paper proposes a new hybrid deep learning method to predict live weight and carcass traits in Coopworth ewes. The dataset of 1184 images taken from 156 ewes was analyzed and compared using a hybrid model (ResNet18 with Multi-Layer Perceptron through simple concatenation) and two more advanced models: Attention-Guided Feature Fusion Network (AGFF-Net) based on cross-modal attention and a Vision Transformer-based Hybrid Regressor (ViT-HR). Auxiliary tabular variables are the Body Condition Score (BCS) and size category. The Transformer architecture predicts (R² = 0.93) the live weight of ewes by dynamically ranking each visual patch and asking it to query the self-attention sequence. This technique treats the BCS as a distinct token in the self-attention sequence. Data partitioning at the animal level was stringent, thereby giving strong generalization. Findings indicate that the best advanced fusion systems are far better than baseline concatenation, with a high accuracy confirmed with gold standards obtained by CT. Grad-CAM visual explainability makes sure that models are able to localize biologically relevant anatomical locations successfully. The study closes the gap between complex deep learning models and real-world agriculture implementation to provide a correct, interpretable and scalable solution to real-time livestock measurements. Full article

Background: Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) represents a group of rare systemic autoimmune disorders marked by inflammation and damage to small- and medium-sized blood vessels. The clinical presentation of AAV is highly variable, ranging from isolated organ involvement to severe, life-threatening multisystem disease, posing significant challenges in diagnosis, treatment, and prognosis. Objective: To demonstrate the clinical heterogeneity and different outcomes in three pediatric cases of ANCA-positive disease and emphasize the importance of integrating clinical findings with laboratory and imaging investigations for accurate diagnosis. Methods: We present three pediatric patients (ages 12–15 years) with ANCA-positive results but distinct clinical presentations, evaluated at the Children’s Emergency Hospital “Louis Turcanu”, Timisoara, between 2020 and 2024. All cases were investigated according to EULAR/PRINTO/PReS criteria for pediatric vasculitis. Results: Case 1 (PR3-ANCA positive) developed severe multi-organ involvement, including granulomatosis with polyangiitis (GPA) with pulmonary hemorrhage, pericarditis, thrombotic events, and renal impairment, requiring intensive immunosuppression with cyclophosphamide, rituximab, and mycophenolate mofetil, ultimately developing chronic kidney disease stage 3a. Case 2 (BPI-ANCA positive) presented with purpuric lesions and painless joint swelling, responding favorably to corticosteroid therapy with subsequent remission. Case 3 (MPO-ANCA) manifested as polyarticular arthritis without other organ involvement and was ultimately diagnosed as seronegative juvenile idiopathic arthritis (JIA), achieving complete remission with adalimumab therapy. Conclusions: This case series highlights the diverse clinical and biological features of ANCA-positive conditions in children, emphasizing that ANCA positivity requires careful clinical correlation as it may indicate true vasculitis requiring aggressive treatment or alternative diagnoses such as JIA with incidental ANCA positivity. Tailored therapeutic strategies based on clinical presentation and continued research are essential to improve patient outcomes. Full article

Three-dimensional (3D) bioreactor systems are essential for vascular tissue engineering as they provide controlled environments that better mimic physiological conditions compared to static culture systems. In this study, an IoT-enabled modular rotating 3D bioreactor platform was designed, fabricated using Fused Deposition Modeling (FDM), and biologically validated. The system integrates a Wi-Fi-supported ESP8266 controller and a touchscreen human–machine interface (HMI), enabling real-time monitoring and remote operation. Agarose-chitosan-based tubular hydrogel constructs were seeded with human aortic smooth muscle cells (HASMCs) and cultured under dynamic conditions for 14 days. Biocompatibility was assessed using a lactate dehydrogenase (LDH) assay, while cellular distribution and mitochondrial activity were evaluated by confocal microscopy using DAPI and MitoTracker staining. Fluorescence intensity was further quantified using ImageJ, and 3D surface plots were generated to visualize spatial signal distribution. The results demonstrated sustained cell viability with decreasing cytotoxicity over time. Confocal analysis confirmed a homogeneous distribution of cells within the hydrogel matrix, and quantitative fluorescence analysis showed significantly higher MitoTracker intensity compared to DAPI, indicating increased metabolic activity under dynamic conditions. These findings suggest that the developed bioreactor provides a stable, controllable, and effective platform for vascular tissue engineering applications. Full article

Early pregnancy diagnosis is a key component of reproductive management in swine production systems. Accurate identification of pregnant and non-pregnant sows within the first 30 days after insemination allows timely reproductive decisions and reduces non-productive days. The present systematic review evaluates the diagnostic efficiency of ultrasonographic and progesterone-based methods used for early detection of pregnancy in sows. A structured literature search was conducted in accordance with the PRISMA Statement guidelines, using major scientific databases. Studies evaluating pregnancy diagnosis in sows within the first 30 days after insemination were included. Diagnostic approaches were analyzed with respect to methodological design, timing of examination, biological sample matrix, and reported indicators of diagnostic accuracy. Ultrasonographic techniques have evolved from early acoustic detection in A-mode to real-time imaging in B-mode and more recently algorithm-assisted interpretation of ultrasound images. Real-time ultrasonography allows direct visualization of gestational structures; in one study, diagnostic accuracy above 95% was reported after approximately 23–24 days of pregnancy under optimal examination conditions. Progesterone-based analyses evaluate luteal endocrine activity and are particularly useful for early identification of non-pregnant animals after luteolysis. The diagnostic efficiency of hormonal assays depends strongly on the timing of sampling and the biological matrix used for analysis, including plasma, serum, dried blood spots, saliva, or feces. The comparative analysis shows that ultrasonography provides morphological confirmation of pregnancy, whereas progesterone analyses serve mainly as functional indicators of luteal activity. These methods play complementary roles in reproductive management. Ultrasonography remains the most reliable method for confirming pregnancy, while progesterone-based analyses are valuable tools for early reproductive screening and identification of non-pregnant sows. Full article

Silver nanoparticles (AgNPs) have attracted substantial scientific interest in biomedical research owing to their unique physicochemical characteristics, broad-spectrum antimicrobial activity, plasmonic properties, and therapeutic versatility. Although conventional physicochemical synthesis methods enable controlled NPs fabrication, their dependence on hazardous reagents, elevated energy input, and environmentally detrimental processing conditions has stimulated the development of sustainable biogenic alternatives. Biological synthesis utilizing plants, microorganisms, fungi, algae, and purified biomolecules has emerged as an eco-friendly and bio-compatible strategy for AgNP fabrication, enabling simultaneous reduction, stabilization, and intrinsic biofunctionalization of NPs. However, traditional biogenic synthesis remains constrained by limited mechanistic understanding, poor batch reproducibility, inadequate control over physicochemical properties, and challenges in large-scale manufacturing. Recent advances in bioengineering have transformed this field through the integration of metabolic engineering, synthetic biology, microfluidic-assisted synthesis, artificial intelligence-guided process optimization, and continuous-flow biomanufacturing, collectively enabling precision fabrication of biogenic AgNPs with enhanced uniformity, scalability, and functional tunability. Furthermore, strategic surface engineering and functionalization have expanded the applicability of biogenic AgNPs across targeted anticancer therapy, antimicrobial intervention, wound healing, regenerative medicine, drug delivery, and theranostic imaging. Despite these advancements, critical challenges remain regarding nano–bio interactions, toxicological safety, regulatory compliance, and translational scalability. Unlike conventional reviews focused primarily on green synthesis approaches, this review critically highlights emerging bioengineering paradigms that enable programmable, scalable, and precision-controlled biogenic AgNP fabrication. This review comprehensively examines next-generation paradigms and strategies for AgNPs biosynthesis, elucidates the molecular mechanisms governing their formation, highlights emerging functionalization and biomedical application paradigms, and discusses current translational barriers. Forming biogenic composites of AgNPs and heteroatom doped carbon nanodots needs intense research in near future. Full article

Recognizing human actions from static images in complex industrial environments remains challenging due to insufficient feature representation and high computational complexity. This issue is particularly critical in power-grid safety monitoring, where improper worker postures (e.g., bending, climbing, falling) can lead to severe accidents and personal injuries, necessitating automated monitoring systems that operate reliably on resource-constrained edge devices. This study proposes a bio-inspired lightweight recognition framework that integrates an improved YOLO-Pose model with a gated recurrent unit (GRU) network. The scientific motivation is grounded in the observation that the human musculoskeletal system achieves highly efficient motion perception through three key mechanisms: hierarchical muscle coordination providing intrinsic rotation invariance, proprioceptive feedback enabling real-time error correction, and selective neural gating reducing redundant information transmission. These biological principles directly inspire our technical contributions: polar-coordinate encoding provides rotation invariance, three-stage filtering mimics proprioceptive feedback, and GRU gating mirrors selective information propagation. Unlike prior approaches that treat pose-based action recognition as a generic computer vision problem, this work explicitly incorporates anatomical structural constraints into the computational pipeline. The framework addresses three research gaps: (1) existing methods lack biomechanically derived invariance properties; (2) GCN-based approaches use fixed topologies that fail to adapt to occlusion patterns; (3) the trade-off between model complexity and accuracy remains unsatisfactory for edge deployment. Experiments on the self-constructed SKPose dataset demonstrate that the proposed method achieves 95.04% accuracy, outperforming ST-GCN by 3.67 percentage points and 2s-AGCN by 1.94 percentage points, with an inference speed of 48 FPS on 8.7 M parameters in underground power-grid environments and provides practical support for biomimetic perception systems and industrial safety monitoring. Full article