Search Results (1,107)

The aim of the present study was to compare the cost-effectiveness of 3DMorphic’s spinal 3DFusion Lumbar (3DFL) cages versus Off-The-Shelf (OTS) cages for patients undergoing lumbar interbody fusion in an Australian healthcare setting. 3DFL cages differ from generic OTS cages in that they are Patient-Specific Interbody Cages (PSICs). While several studies have discussed the clinical benefits of PSIC versus OTS cages, no studies have evaluated the cost-effectiveness of this technology. Without a direct randomised controlled trial between the two implant categories, an indirect treatment comparison was performed. The indirect comparison was informed by a clinical trial of 3DFL cages, the Australian Spine Registry and an analysis of reoperation rates for patients undergoing spinal fusion in an Australian cohort. In conclusion, the PSICs were demonstrated to be clinically superior to OTS cages as measured by Health Related Quality of Life (HRQoL) and reoperation rates. The cost-utility analysis demonstrated that 3DFL cages were cost-effective compared to OTS cages in an Australian healthcare setting. Full article

Background/Objectives: Primary dysmenorrhea is a common gynecological disorder characterized by painful uterine contractions. Danggui Buxue Decoction (DBD) is used to treat menstrual irregularities, but its mechanism in primary dysmenorrhea remains unclear. This study investigated the efficacy of DBD against dysmenorrhea and its calcium signaling-related mechanism. Methods: DBD components were analyzed by UPLC–Orbitrap MS. Isolated uterine muscle strips precontracted with oxytocin (OT, 50 ng/mL) or KCl (60 mM) were used to assess the effects of DBD and its active compounds (Quercetin, Formononetin, Ononin, Ferulic acid, Senkyunolide I, Calycosin, Ligustilide, Calycosin-7-O-β-D-glucoside). Ca²⁺-dependent experiments, intracellular calcium release assays, and inhibitor treatments (Nifedipine, 2-APB) were performed to evaluate the involvement of L-type calcium channels and the IP₃R pathway. A primary dysmenorrhea model induced by estradiol benzoate and oxytocin was used to assess the analgesic effects, histopathology, inflammatory factors, and IP₃/Ca²⁺-related proteins and genes following DBD and Quercetin treatment. Results: A total of 161 compounds were identified in DBD. DBD and its eight active constituents relaxed OT (50 ng/mL) or KCl (60 mM)-induced uterine contractions, with Quercetin, Calycosin, and Ligustilide showing particularly prominent relaxant activity. These three compounds suppressed extracellular calcium influx and intracellular calcium release through the blockade of L-type calcium channels and IP₃R. In vivo, DBD and Quercetin alleviated pain, reduced inflammation, and decreased uterine Ca²⁺ and IP₃ levels in dysmenorrhea mice. Conclusions: DBD and its active component Quercetin promote uterine relaxation by lowering Ca²⁺ levels, which is achieved through suppression of L-type calcium channels and the IP₃/Ca²⁺ pathway. This contributes to their therapeutic action against primary dysmenorrhea. Full article

Embedded devices in modern power systems offer increased connectivity and remote reprogrammability/reconfigurability. These features along with interconnections between Information Technology (IT) and Operational Technology (OT) networks enable greater agility, reduced operator workload, and enhanced power system performance and capabilities, as well as expanding the cyber-attack surface. This increased cyber-attack surface, as well as increasingly complex, diverse, and potentially untrustworthy software/hardware supply chains, increases the need for robust real-time monitoring in power systems, and more generally in cyber–physical systems (CPS). We propose a novel framework for real-time monitoring and anomaly detection in CPS, specifically smart grid substations and SCADA systems. The proposed framework enables real-time signal temporal logic condition-based anomaly monitoring by processing raw captured packets from the communication network through a hierarchical semantic extraction and tag processing pipeline into a time series of semantic events and observations, that are then evaluated against expected temporal properties to detect and localize anomalies. We demonstrate the efficacy of our methodology on a hardware in the loop (HITL) testbed under several attack scenarios. The HITL testbed includes multiple physical power system devices (real-time automation controllers and relays) and simulated devices (Phasor Measurement Units—PMUs, relays, Phasor Data Concentrators—PDCs), all interfaced to a dynamic power system simulator. Full article

Precision in radiotherapy requires the development of standardized, reproducible, and biologically relevant models to accurately assess the efficacy and safety of various radiobiological sources. This review presents a novel approach using precision-cut organotypic tissue slices (OTSs), or organotypic tissue cultures (OTCs), as a representative model with potential for unifying the assessment of radiobiological sources. Derived from specific organs, OTSs retain the complex architecture and multicellular environment of the tissue, providing a unique platform that bridges the gap between in vitro cell cultures and in vivo animal models. The typed OTSs can effectively mimic the in vivo physiological responses to ionizing radiation, providing insight into the mechanisms of radiation-induced damage and repair, and the potential for radiation-induced toxicity and side effects. The emerging practices for the use of OTSs in radiobiological studies include slice mechanical preparation, radiation exposure, and outcomes assessment. The prepared approach for OTS preparation promises to improve the reliability and comparability of radiobiological studies, facilitating the development of safer and more effective radiation therapies. OTSs have the potential to significantly advance our understanding and application of radiation medicine and research by providing a physiologically relevant assessment of radiobiological effects of novel ionizing radiation sources. Full article

Industrial Control Systems (ICSs) are the backbone of modern critical infrastructure, such as electric power, water treatment, oil and gas distribution, and manufacturing operations. While the convergence of IT and OT has greatly increased efficiency and observability, it has also greatly expanded the attack surface of these once-isolated systems. High-profile cyber-physical attacks, including Stuxnet (2010), TRITON (2017), and the Colonial Pipeline ransomware attack (2021), have shown that ICS-targeted cyberattacks can cause physical damage, disrupt economic stability, and put public safety at risk. Despite the growing prevalence and intensity of such threats, ICS-based cybersecurity education remains largely under-resourced and underfunded. Traditional ICS training laboratories require highly specialized hardware, vendor-specific tools, and expensive licensing that significantly raise barriers to entry. Traditional labs typically require on-site participation and pose physical safety concerns when cyber-physical attack scenarios are performed. These barriers leave students unable to get necessary security training for ICSs. Therefore, this paper introduces ${\mathrm{AE}}^3$GIS: Agile Emulated Educational Environment for Guided Industrial Security—a fully virtual, lightweight, open-source platform designed to democratize ICS cybersecurity education. Based on the GNS3 network simulation tool, ${\mathrm{AE}}^3$GIS enables rapid deployment of comprehensive ICS environments containing IT and OT systems, industrial communication protocols, control logic, and diverse security tools. ${\mathrm{AE}}^3$GIS is designed to provide practical training for students using realistic ICS cybersecurity scenarios through a local or remote training platform without the cost, safety, or accessibility limitations of hardware-based labs. Full article

Oblivious Transfer (OT) is a fundamental cryptographic primitive for privacy-preserving data exchange. While traditional OT protocols guarantee unconditional receiver anonymity, they inherently lack the mechanisms to prevent abusive mass data harvesting. Traceable Oblivious Transfer (TOT) addresses this by introducing “conditional anonymity,” revoking the privacy of malicious users. However, existing TOT mechanisms either rely on computationally expensive dynamic assumptions or require continuous interaction with a Trusted Third Party (TTP) to manage credentials. To overcome these limitations, we present an Identity-Based Traceable Oblivious Transfer (IB-TOT) protocol. By synergizing polynomial-based secret sharing with Blind Identity-Based Encryption (Blind IBE), our scheme completely eliminates the TTP during the data transfer stage. The Blind IBE extraction algorithm serves as the primary oblivious channel, utilizing data indices as user identities. We strictly bound the receiver’s query quota by embedding a degree-k tracing polynomial directly into the key issuance phase. Honest clients enjoy fully protected retrieval of up to k items, whereas any attempt to exceed this quota deterministically exposes the violator’s identity. Comprehensive security proofs demonstrate that IB-TOT satisfies sender privacy, receiver privacy, and strict accountability under standard static assumptions (DBDH and DL). Full article

Background/Objectives: Stroke is a leading cause of mortality and disability in Saudi Arabia; however, national estimates of stroke-related rehabilitation needs remain limited. This study quantified temporal trends in stroke incidence, prevalence, premature mortality, and disability from 1990 to 2021. It also examined disparities in stroke-related disability by subtype, sex, and age in 2021 and projected rehabilitation demand to 2030 to inform health system planning under Vision 2030. Methods: We conducted a secondary analysis of Global Burden of Disease (GBD) 2021 estimates for Saudi Arabia. Age-standardized rates for incidence, prevalence, years of life lost (YLLs), and years lived with disability (YLDs) were extracted for overall stroke and three subtypes: ischemic stroke, intracerebral hemorrhage (ICH), and subarachnoid hemorrhage (SAH). Temporal trends were evaluated using log-linear regression to estimate the average annual percentage change (AAPC). YLDs were mapped to severity levels and four rehabilitation modalities, physiotherapy (PT), occupational therapy (OT), speech–language therapy (SLT), and multidisciplinary comprehensive rehabilitation (MCR), using utilization probabilities informed by the literature. Projections to 2030 incorporated national population forecasts and included 95% prediction intervals and sensitivity analyses. Results: From 1990 to 2021, age-standardized stroke incidence declined from 166.3 to 130.7 per 100,000 (−21.4%; AAPC, −0.86%, p = 0.004), prevalence from 982.4 to 965.2 per 100,000 (−1.8%; AAPC, −0.10%, p = 0.056), and YLL rates from 3209.0 to 1893.4 per 100,000 (−41.0%; AAPC, −1.76%, p < 0.001). In contrast, YLD rates declined modestly from 133.5 to 129.9 per 100,000 (−2.7%; AAPC, −0.13%; p = 0.032). Despite these reductions in age-standardized rates, absolute stroke-related YLDs more than tripled, increasing from approximately 10,900 (95% UI: 8100–13,900) in 1990 to 36,245 (95% UI: 26,600–46,100) in 2021, largely driven by population growth and aging. In 2021, ischemic stroke accounted for 71.1% of total YLDs, followed by ICH (20.3%) and SAH (8.5%). Among adults aged 15–49 years, females had higher hemorrhagic YLD rates than males, with particularly pronounced differences for SAH (female-to-male ratio, 1.5–1.7). By 2030, the projected YLD-equivalent workload, a standardized proxy measure of relative service demand rather than a direct headcount of required therapists, is expected to increase to 29,758 for PT, 21,809 for OT, 14,879 for SLT, and 15,083 for MCR. Sensitivity analyses showed that rehabilitation demand estimates were sensitive to assumptions regarding severity distribution, with a hemorrhagic-weighted scenario increasing projected MCR demand by 6.8%. Conclusions: The increasing absolute burden of stroke-related disability in Saudi Arabia, despite declining age-standardized rates and substantial reductions in premature mortality, highlights the necessity to expand rehabilitation capacity. Scaling community-based, outpatient, and telerehabilitation services in alignment with the Health Sector Transformation Program and integrating disability-informed planning into Vision 2030 should be prioritized. Full article

This paper proposes a new Unified Namespace (UNS)-based architecture to improve predictive and prescriptive maintenance of industrial equipment and overcome challenges such as incomplete data, poor interoperability, and disconnected IT/OT environments. The framework combines interoperable data formats in real-time sensor data, predictive modeling, prescriptive analytics, and simulations of digital twins, using UNS as a centralized, protocol-agnostic data layer that is scalable and complies with Industry 4.0 and Pharma 4.0 standards. The suggested methodology increases data accessibility, reduces integration complexity, and allows low-latency analytics and automated decision-making. Machine learning predictive models achieved more than 94% accuracy in predicting equipment failures. Prescriptive analytics provides maintenance recommendations to reduce downtime and risks. The feedback loops of digital twins can enhance the accuracy of predictions and allow decision optimization through what-if analysis. A test-bench deployment showed a higher performance compared to traditional point-to-point integration, with lower latency (approximately 18 ms vs. approximately 31 ms), decreasing packet loss (0.40% vs. 3.11%), and higher model accuracy (94.20% vs. 87.51%). The structure avoided more than 4000 simulated breakdowns in the test-bench environment, indicating dependability. The study connects the theoretical applications of the UNS with the actual maintenance processes and provides a sound approach to the industrial analytics and optimization of the equipment. Full article

Background/Objectives: Breast Cancer-Related Lymphedema (BCRL) is one of the most prevalent complications among patients, causing physical limitations and a negative impact on their quality of life. Given its chronic nature and influence on personal autonomy, it is essential to review the therapeutic approaches applied to date. The main objective of this study was to analyze and to compare the effectiveness of the different treatments currently used in the management of BCRL, especially those that incorporate the intervention of an occupational therapist. Methods: A narrative review of the scientific literature published between 2013 and 2025 was conducted. The search was carried out in the PubMed, Scopus, Web of Science, and Dialnet databases. Inclusion and exclusion criteria were applied to select studies with therapeutic interventions, selecting eight studies for review. Results: Complex Decompression Therapy (CDT) is currently the standard treatment, although one of its components, manual lymphatic drainage, is controversial in terms of its effectiveness. Interventions such as Activity-Oriented Proprioceptive Anti-Edema Therapy (TAPA), adapted physical exercise, and hydrotherapy showed significant benefits in quality of life, functionality, and reduction in the volume of lymphedema. Conclusions: The therapeutic approach to BCRL must be multidisciplinary and personalized. Occupational Therapy (OT) provides a person-centered approach that contributes to improving occupational performance and patient well-being. More studies with greater methodological rigor and sample size are needed to unify clinical criteria. Full article

The network traffic of 3D parallel training in large-scale deep learning, featuring burstiness, hot-spots, and periodic large-bandwidth patterns, severely challenges network efficiency, necessitating a high-performance and flexible optical network solution. To address this, this paper proposes Mercury, a hybrid optical network based on physical optical components: its optical timeslot switching (OTS) subnet uses an arrayed waveguide grating router (AWGR) and tunable lasers for dynamic traffic, while the optical circuit switching (OCS) subnet relies on wavelength selective switches (WSSs) for low-latency high-bandwidth transmission, which is coordinated by selective valiant load balancing (S-VLB) and most efficient path configuration (MEPC) mechanisms. Validated via simulations and FPGA-based testbed experiments, Mercury outperforms the Sirius network by reducing epoch training time (e.g., 179s with five jobs) and relieving OTS congestion through offloading large flows to OCS. This work demonstrates that Mercury provides a flexible, high-performance physical optical solution for 3D parallel training of large-scale deep learning models. Full article

The ability to assess molecular binding kinetics in real time is critical for advancing our understanding of molecular interactions in biochemical and biotechnological systems. This work presents a novel optical tweezer (OT)-based method to monitor molecular affinity in real time, focusing on the high-affinity streptavidin–biotin system as a model. Transparent poly(methyl methacrylate) (PMMA) microparticles functionalized with streptavidin were trapped before, during, and after binding with biotinylated bovine serum albumin (biotin–BSA), enabling the analysis of forward-scattered signals to detect nanoscale changes in particle size. By applying the Power Spectral Density method, the friction coefficient of individual particles was calculated, allowing for real-time tracking of binding dynamics and the estimation of the association rate constant ($k_{\mathrm{on}}\approx {10}^6{\mathrm{M}}^{-1}{\mathrm{s}}^{-1}$). These results are consistent with literature values and demonstrate the potential of this OT-based approach for non-invasive, label-free detection of molecular interactions. Compared to existing techniques, such as atomic force microscopy and cantilever-based sensors, this method offers significant advantages, including real-time monitoring, adaptability to different bioaffinity systems, and compatibility with miniaturized setups. This work establishes a foundation for using OT-based tools to monitor high-affinity molecular interactions in real time. While demonstrated here using biotinylated BSA as a model ligand, future studies will explore the method’s applicability to smaller ligands and more subtle surface modifications. Full article

Integrating third-party Machine Learning (ML) models into industrial Operational Technology (OT) creates a procurement deadlock: operators cannot verify vendor performance claims without sharing representative evaluation data with vendors, while vendors refuse to reveal proprietary model weights before purchase, rendering traditional safeguards such as Non-Disclosure Agreements technically unenforceable. This paper introduces a framework combining Zero-Knowledge Proofs (ZKPs) with smart contracts to enable trust-minimized, cryptographically verifiable competitive model procurement in Industrial Cyber-Physical Systems (ICPS). Vendors cryptographically prove that their model outperforms a legacy baseline without disclosing proprietary weights, a process we term cryptographic performance attestation, while the on-chain workflow automates escrow, proof verification, and best-vendor selection with arbiter-based dispute resolution. ZKP privacy is scoped to vendor model weights; operator-side evaluation-data confidentiality is managed separately via synthetic, de-identified, or public benchmark data. We analyze three ZKP workflow variations and evaluate them on consumer-grade hardware, achieving proving times of approximately three seconds and sub-dollar on-chain verification costs under Layer-2 fee assumptions for the recommended single-proof variation, while identifying computational trade-offs of recursive proof aggregation. The entire verification phase operates offline with no impact on real-time OT control paths, bridging the IT/OT pre-transaction trust gap while deferring artifact deployment to existing OT tooling. Full article

Digital Twins (DTs) are increasingly recognized as a strategic technology for enhancing cybersecurity in industrial environments, particularly in the face of rising threats targeting Operational Technology (OT). After comparatively examining closely related DT–cybersecurity frameworks to position the contribution within the existing research landscape, this paper presents a systematic literature review and comparative analysis of 19 recent DT-based cybersecurity studies, focusing on their relevance to incident detection and response in sectors such as Industrial Internet of Things (IIoT), manufacturing, and energy. The analysis evaluates each study across multiple dimensions, including attack types, detection and response mechanisms, DT integration, and technology stacks. From this review, we derive a consolidated set of requirements, categorized as functional, non-functional, security-specific, and domain-specific. These requirements serve as the foundation for a novel, cybersecurity-focused, ISO 23247-based framework. The proposed architecture formalizes a DT-enabled incident detection and response lifecycle aligned with ISO 23247. It is explicitly mapped to the derived requirements and detailed with practical implementation considerations. This work contributes a structured, evidence-based approach to DT-based security engineering and offers a reference design for researchers and practitioners aiming to build resilient, adaptive cybersecurity solutions in industrial settings. Full article

Generative Artificial Intelligence (GenAI) has been a viable technology for decades, yet widespread adoption in healthcare and academic settings has remained limited to research. One possible explanation for this is limited understanding about the beliefs around GenAI use amongst faculty and students training in biomedical disciplines that frequently lead to non-physician healthcare careers, including physical therapy (PT), occupational therapy (OT), allied health (AH), and biomedical engineering (BME). Furthermore, no known studies exist assessing differences that may exist across those disciplines. Given the significant number of professionals in those disciplines and the outsized impact they have on the healthcare system, investigating their beliefs around GenAI use is vital before widespread adoption. Accordingly, we investigated the perceptions of GenAI among students and faculty in the aforementioned fields that frequently lead to careers in healthcare. We found that knowledge of GenAI significantly influences comfort with its use completing college coursework including whether respondents believed it contributed to the process of completing that coursework and whether use of GenAI enhances learning. Interestingly, however, there were no statistically significant differences in perceptions of GenAI across disciplines, roles, or institution sizes. Qualitative findings revealed concerns about plagiarism, decline of critical thinking skills, and ethical challenges, while also recognizing GenAI’s potential to enhance learning efficiency and idea generation. Critically, the study results emphasize the need for proper training and guidelines to ensure GenAI is integrated responsibly into healthcare-related education. Full article

Background/Objectives: The neuromorphological effects of prenatal administration of valproic acid (VPA) on the dopaminergic system has been studied by our groups for some time. Previously, we found a marked defasciculation of the mesotelencephalic pathway, and a reduction of dopaminergic ventrotegmental output, with diminished dopamine in the nucleus accumbens (NAc) but not in the caudatoputamen (CPu), in VPA exposed P7 mice. Further, we reported a marked decrease in the juxtapositions between tyrosine hydroxylase positive (TH+) axon terminals and calretinin or calbindin containing neurons in the NAc and tuberculum olfactorium (OT). Our aim was to test the existing findings, indicating diminished input of TH+ structures to dopamine recipient forebrain, by another robust and unbiased quantitative approach. Methods: Here, the intensity of TH immunolabel was quantified by 3D image analysis of whole-mount, tissue-cleared (by the iDISCO method) brain specimens of P7 mice born to VPA-exposed or control mothers. Results: We observed a robust reduction in TH+ immunostaining (expressed as mean voxel intensity within the ROI) in the OT, and a less prominent but significant reduction of this parameter in the NAc, in VPA exposed vs control mice. No such effect was observed in the CPu, indicating that the decrease of DA input affected predominantly the limbic component of dopamine recipient forebrain regions. Conclusions: Together with previous observations, the current results seem to converge upon a consistent interpretation, i.e., reduced DAergic fiber input to ventral forebrain regions, following VPA exposure of neonatal mice. Weaker supply of DA at a critical time of embryonic development may result in impaired pattern formation of ventrobasal forebrain regions involved in reward and sociability. Full article