Search Results (1,374)

CT perfusion (CTP) is widely used in acute ischemic stroke imaging, particularly for treatment selection beyond conventional time windows. However, automated perfusion maps are not direct measurements of irreversible tissue injury, but estimates shaped by deconvolution strategy, temporal correction, dispersion handling, and software-specific thresholds. This review provides a clinically oriented explanation of how CTP algorithms influence the estimation of ischemic core and hypoperfused tissue. Particular attention is given to singular value decomposition (SVD) methods, Bayesian approaches, and timing parameters, including time to maximum (Tmax), Delay, time to peak (TTP), and mean transit time (MTT). Differences in residue function estimation and threshold definition may generate variable outputs across software platforms, even from the same source dataset. Perfusion thresholds should therefore not be treated as universally interchangeable. CTP findings should be integrated with clinical status, non-contrast CT, CT angiography (CTA), collateral status, occlusion site, and imaging-to-treatment context, serving as decision-support tools rather than isolated measures of tissue viability. Full article

Background: Acute intermittent porphyria (AIP) is the most common and severe form of acute hepatic porphyria, caused by heterozygous mutations in the HMBS gene. Due to its non-specific clinical manifestations and low clinical awareness among clinicians, AIP is frequently misdiagnosed, leading to significant diagnostic delays and potentially fatal complications. Case presentation: We report a 20-year-old female patient who presented with a 9-month history of recurrent abdominal pain, paralytic ileus, unexplained liver injury, and hyponatremia, followed by progressive limb weakness. She was initially misdiagnosed with Guillain–Barré syndrome (GBS) and received intravenous immunoglobulin and systemic glucocorticoids. However, her condition deteriorated, and she developed life-threatening respiratory muscle paralysis requiring invasive mechanical ventilation. The diagnosis of AIP was confirmed by positive urinary porphobilinogen (PBG) testing and identification of the heterozygous HMBS c.517C>T pathogenic variant. The patient was treated with high-dose carbohydrate loading therapy and comprehensive supportive care, resulting in gradual clinical improvement. Discussion and Conclusions: This case exemplifies the substantial diagnostic challenges associated with AIP, especially when it manifests with peripheral neuropathy that closely mimics GBS. The triad of absent albuminocytologic dissociation in cerebrospinal fluid, preceding visceral symptoms, and inadequate response to standard first-line GBS therapy should immediately raise clinical suspicion for AIP. Enhanced clinical awareness of this rare disorder and timely implementation of urinary PBG screening are of paramount importance to prevent irreversible neurological complications and optimize long-term patient outcomes. Full article

Hypoxic–ischemic brain injury remains the leading cause of death and neurological disability after cardiac arrest. Although targeted temperature management (TTM) and other neuroprotective strategies have demonstrated promising results in preclinical studies, large randomized controlled trials have largely failed to show consistent clinical benefit. This review examines two major limitations that may contribute to these translational failures: delayed initiation of therapy beyond a time-limited therapeutic window and the lack of baseline injury severity stratification. Evidence from both experimental and clinical studies suggests that the opportunity to modify neurological injury may be confined to the first few hours after return of spontaneous circulation (ROSC). Delayed intervention may occur after irreversible neuronal injury, microvascular dysfunction, and impaired cerebrovascular autoregulation have already become established. In addition, cardiac arrest survivors represent a heterogeneous population. Patients with minimal injury may recover with standard supportive care, whereas those with severe irreversible injury are unlikely to benefit from neuroprotective interventions. Patients with moderate-severity brain injury may represent the subgroup most likely to respond to targeted therapies. Ultra-early stratification using neuroimaging, electroencephalography, circulating biomarkers, and clinical risk scores may help identify patients with therapeutic potential. This review proposes that future post-cardiac arrest research should integrate both time-sensitive intervention strategies and early injury severity stratification. Large prospective studies and randomized controlled trials are needed to determine not only whether interventions are effective, but also when they should be initiated and which patients are most likely to benefit. Full article

Photonic imaging technologies have profoundly transformed neuro-ophthalmic diagnostics by enabling non-invasive visualization of neurodegenerative processes at the retinal level. This review examines how advanced light-based modalities provide unprecedented insights into the structural, physiologic, and biologic relationships between the eye and brain in conditions such as optic neuritis, multiple sclerosis, and glaucoma. Optical coherence tomography has emerged as an essential tool for quantifying thinning of the retinal nerve fiber layer and ganglion cell layer, serving as reliable biomarkers of axonal loss and disease progression across multiple sclerosis subtypes and optic neuropathies. Detection of apoptosing retinal cells imaging enables real-time visualization of retinal ganglion cell apoptosis preceding irreversible structural damage, offering a critical window for early intervention in various neurodegenerative conditions, in particular, glaucoma. Two-photon microscopy with adaptive optics enables subcellular-resolution imaging of retinal neurons, microvascular dynamics, and inflammatory processes in vivo, facilitating the characterization of neurodegenerative mechanisms at unprecedented spatial scales and redefining neuro-ophthalmology by positioning the retina as an accessible extension of the central nervous system. This review critically examines how established and investigational photonic imaging modalities may support earlier disease detection, longitudinal monitoring, and biomarker development in neuro-ophthalmic and neurodegenerative disorders, with potential implications for more timely and targeted management strategies. Full article

Hybrid carbon nanotube–fullerene architectures provide a controllable setting in which to study irreversibility and information flow in strongly structured quantum environments. We analyze entropy generation in a platform where paramagnetic endohedral fullerenes (PEFs), such as N@C₆₀ and P@C₆₀, are encapsulated inside a suspended carbon nanotube (CNT) resonator, such that selected multi-level PEF spin states define an effective qubit coupled to quantized CNT flexural modes. Motivated by prior work on fullerene-filled CNTs, on spin–phonon manipulation in suspended nanotubes, and on exact phase-space propagators for damped driven oscillators, we formulate a hybrid open-system description that combines a driven quantum Brownian description of the CNT resonator with an effective Jaynes–Cummings type spin–vibrational interaction. The resonator dynamics are represented in phase space through the Wigner function, whose time evolution can be written analytically in terms of the initial Wigner distribution and a Gaussian propagator. This representation makes it possible to separate drive-induced phase space displacement, diffusion, and damping, and to connect these features directly to entropy flow. The coupled spin–mechanical dynamics are then embedded in a Lindblad quantum master equation that includes mechanical damping, spin relaxation, pure dephasing, and thermally activated excitation channels. Within this framework we derive the entropy balance equation—identifying entropy flux and non-negative entropy production—and examine how hybridization between the molecular spin and the nanotube vibration redistributes irreversibility between coherent exchange and dissipative channels. We show that spin–phonon coupling enhanced by a magnetic field gradient, resonant driving, and moderate thermal occupation can produce identifiable crossovers between entropy–production regimes dominated by the oscillator and those dominated by the spin. The resulting framework provides a quantitative basis for using CNT–PEF hybrids as nanoscale platforms for studying nonequilibrium quantum thermodynamics, decoherence, and information loss in structured vibrational environments. Full article

Background: Glaucoma is a progressive, age-related optic neuropathy and a leading cause of irreversible blindness worldwide. Ensuring timely diagnosis and equitable access to surgical care is therefore essential to prevent avoidable vision loss. Methods: Nationwide registry-based data on hospital-based glaucoma diagnoses and surgical procedures over an 11-year period were analyzed and stratified by treatment region and area of residence. Population data were age-stratified to allow calculation of standardized diagnosis and surgery rates per 10,000 population aged ≥ 60 years. Regional comparisons were performed, and demographic projections for populations aged ≥ 60 years were generated using an exponential smoothing state space model. Results: Geographic variation in glaucoma care was observed, despite broadly similar demographic profiles across regions. Surgery-to-diagnosis ratios among individuals aged ≥ 60 years differed markedly between regions. Relevant for future healthcare planning, age forecasting suggests an increase in people aged ≥ 60 years over the coming years. Conclusions: Geographic disparities in glaucoma surgical care may persist even in well-resourced healthcare systems. Centralization of surgical services may contribute to differences, although explanations such as variation in referral patterns and clinical decision-making cannot be excluded. These findings highlight a broader, internationally relevant challenge: aligning glaucoma care delivery with shifting demographic needs. Full article

Cells operate as open thermodynamic systems where energy transformations and transport processes occur across membranes, exhibiting distinct thermo-electro-biochemical behaviours in healthy versus diseased states. Living organisms generate waste heat due to internal irreversibility, which dissipates into the environment and serves as an observable flow of information. By analysing this heat loss and its changes under external influences, new insights into cellular behaviour can be gained. This paper highlights recent advances in this thermodynamic approach, which frames living systems as black boxes, focusing on their input–output dynamics and introducing the emerging field of bioengineering thermodynamics. A key challenge in applying extremely low-frequency electromagnetic fields (ELF-EMF) to proliferative disorders has been the empirical selection of effective field parameters. To address this, we employed a bio-thermodynamic engineering model to calculate the ELF frequency that maximizes mean entropy changes based on cellular biophysical parameters. This entropy change corresponds to a metabolic shift that reduces cell proliferation. Experimental validation was performed on six human cancer cell lines, where proliferation rates served as indicators confirming the model’s predictions. For the first time, this approach enabled the calculation and experimental validation of ELF frequencies selectively effective on different cell types, demonstrating a promising method for targeted therapeutic applications. Full article

Knee Osteoarthritis (KOA) is a leading contributor to global physical disability, where delayed diagnosis often results in irreversible joint damage and socio-economic cost. Early diagnosis remains challenging due to subtle radiographic biomarkers and limited access to specialized expertise, particularly in distributed healthcare settings. Within the evolving landscape of the Future Internet, characterized by Internet of Medical Things (IoMT), edge–cloud computing, and intelligent digital health infrastructures, there is an increasing demand for scalable, low-latency, and explainable AI-driven diagnostic solutions. In this work, we propose a Dual-Stream Wavelet Fusion Network (DS-WFN) alongside a distributed edge-cloud architectural roadmap tailored for deployment in distributed and edge-enabled healthcare ecosystems. The framework integrates a spatial morphological stream with a spectral wavelet stream, augmented by an Adaptive Wavelet Selection Mechanism (AWSM). The AWSM dynamically selects optimal frequency bases (Haar, Symlet, Daubechies) to preserve fine-grained diagnostic features typically lost in conventional CNN architectures. An Adaptive Spatial Alignment (ASA) module further ensures efficient fusion of heterogeneous representations, enabling robust feature integration across computational nodes. Experimental results across a five-fold patient-isolated cross-validation protocol demonstrate that the DS-WFN achieves a mean classification accuracy of 76.3% (95% CI: 71.6–80.8%) and a macro-averaged F1-score of 0.747 (95% CI: 0.697–0.795), consistently outperforming single-stream baselines while preventing patient-level data leakage. Furthermore, Grad-CAM visualizations provide interpretable outputs aligned with clinical diagnostic criteria, supporting trustworthy AI integration into digital healthcare workflows. Furthermore, we disclose a methodological framework for edge-based implementation, highlighting how localized inference ensures data sovereignty and real-time clinical support. By combining multiscale signal processing with deep learning under a Future Internet paradigm, this work contributes a scalable, explainable, and edge-ready diagnostic framework for early KOA detection, enabling intelligent, connected, and resource-efficient healthcare services. Full article

Age-related macular degeneration (AMD) is a leading cause of irreversible vision loss in older adults and is characterized by progressive dysfunction of the retinal pigment epithelium (RPE). Although genetic susceptibility and environmental exposure both contribute to disease risk, the mechanisms through which chronic metabolic and oxidative stress are integrated into sustained RPE dysfunction remain incompletely understood. Increasing evidence from human AMD donor tissue and experimental RPE models indicates that epigenetic regulation operates at the interface between mitochondrial dysfunction, redox imbalance, and transcriptional remodeling. This review synthesizes current findings on DNA methylation, chromatin accessibility, histone modification, and RNA-based regulation in AMD, with emphasis on their metabolic and mitochondrial context. Studies in human AMD-RPE demonstrate that epigenetic alterations are generally selective rather than global and frequently involve pathways related to mitochondrial maintenance, lipid metabolism, oxidative stress responses, and cellular homeostasis. Mechanistically, mitochondrial dysfunction and reactive oxygen species (ROS) may influence epigenetic regulation through altered Nicotinamide adenine dinucleotide (NAD⁺) availability, acetyl-CoA metabolism, redox-sensitive chromatin regulation, and modulation of DNA methyltransferase and histone deacetylase activity. Redox-sensitive pathways, including antioxidant signaling, further connect mitochondrial stress to adaptive or maladaptive transcriptional responses in the RPE. Importantly, while several interactions discussed are supported by findings in human AMD tissue, other components of the proposed epigenetic–mitochondrial–redox framework remain inferential or model-based and require further validation. Rather than acting as isolated disease triggers, epigenetic changes are more likely to function as stress-responsive regulatory layers that stabilize transcriptional states over time in a long-lived post-mitotic tissue. We further discuss unresolved questions regarding causality, reversibility, therapeutic feasibility, and stage-specific intervention strategies. Collectively, this framework positions the epigenetic–mitochondrial–redox axis as a unifying model for understanding RPE vulnerability and AMD progression. Full article

Ecosystems can undergo abrupt, often irreversible transitions between alternative states—phenomena termed critical transitions or regime shifts—with profound consequences for biodiversity, ecosystem services, and human well-being. Early warning signals (EWSs) derived from time-series analysis offer the prospect of anticipating such transitions before they occur, potentially enabling preventive management intervention. This review provides a comprehensive synthesis of EWS methods for ecological systems, encompassing theoretical foundations, statistical indicators, empirical applications, and emerging methodological frontiers. We examine the dynamical basis of EWS in critical slowing down theory, wherein systems approaching bifurcation points exhibit characteristic statistical signatures including rising autocorrelation, increasing variance, and spectral reddening. We present a systematic overview of proposed indicators discuss moving-window frameworks for their computation, and critically evaluate preprocessing requirements and sensitivity to analytical choices. Empirical applications across major ecosystem types—including lakes, coral reefs, grasslands, forests, and marine fisheries—reveal both successes and limitations, with EWS performance depending critically on data quality, transition mechanism, and system-specific dynamics. We address recent advances including machine learning approaches, non-equilibrium thermodynamic indicators, multivariate extensions, and the important distinction between bifurcation-induced, noise-induced, and rate-induced tipping. We conclude with recommendations for specialists, emphasizing the integration of EWS within broader monitoring frameworks, systematic sensitivity analysis, and the interpretation of indicators as probabilistic assessments of changing resilience rather than deterministic predictions of imminent collapse. Full article

Background/Objectives: Granulomatous uveitis comprises a clinically heterogeneous group of inflammatory disorders, including ocular sarcoidosis, Vogt–Koyanagi–Harada disease, sympathetic ophthalmia, tuberculosis-associated uveitis, and syphilitic uveitis. Because these entities may share overlapping posterior segment findings, clinical examination alone is often insufficient for differential diagnosis, particularly when choroidal, retinal, or retinal vascular involvement predominates. Methods: This review provides a clinically oriented overview of multimodal imaging in granulomatous uveitis, including optical coherence tomography (OCT), enhanced-depth imaging OCT, swept-source OCT, OCT angiography, fundus autofluorescence, fluorescein angiography, indocyanine green angiography, and ultrawidefield imaging. Results: Emphasis is placed on imaging patterns that help localize the predominant anatomic compartment of inflammation, distinguish major etiologies, identify diagnostic pitfalls, and assess disease activity over time. By integrating current evidence with representative multimodal imaging findings, we propose an anatomic and decision-oriented framework for interpreting granulomatous posterior segment inflammation. Conclusions: Particular attention is given to the distinction between active inflammation and irreversible structural damage, as this distinction may influence treatment escalation or tapering, timing of elective surgery, local corticosteroid therapy, and the need for diagnostic sampling in infectious or masquerade-like presentations. Full article

This paper deals with the optimal integration of power plants, including a storage device. For such systems, numerous structures are possible, involving different numbers of heat exchangers, and for each of them, optimal operating temperatures need to be found. Moreover, the heat-storage system can be located at different temperature levels, offering another degree of freedom when optimizing the whole system. If process simulators are presently very powerful tools for optimizing complex processes, they need to propose a primary design before any optimization steps. Finite-Dimension Thermodynamics (FDT) could help engineers to propose this primary design, close to the optimal one. To this aim, the FDT method is generalized for power-generation systems including a storage device and any number of heat exchangers. The optimization step consists of maximizing the power generation submitted to the thermodynamics constraints (first and second laws) related to each heat exchanger, power block, and thermal storage system. Two types of heat transfer law are studied and compared: Newton’s law $\left(K\times ∆T\right)$ and phenomenological law issued from thermodynamics of irreversible processes $\left(L\times ∆\left(1/T\right)\right)$). Remarkable results have been found: (i) all the studied structures lead to the Curzon–Ahlborn efficiency when optimized with Newton’s law, (ii) for the same driving source (same high temperature and same power), and without any storage system, the output power production varies as N⁻², N being the number of the heat exchangers, (iii) Charge and discharge times scenarios have a big impact on the optimal operating temperatures and on the resulting daily energy production. Efficiencies of operational plants, including nuclear or solar plants and ORC, are finally compared with the theoretical efficiency found at the maximum power point. This shows that FDT provides a good assessment of the actual efficiency of existing power plants. Full article

Reliability degradation in semiconductor devices originates from microscopic stochastic processes such as defect motion, diffusion, bond rearrangement, and charge trapping occurring under electrical and thermal stress. Experimental degradation measurements, however, often exhibit smooth empirical scaling behavior, particularly power-law time dependences extending across many orders of magnitude in time. This tutorial reviews the thermodynamic and kinetic foundations underlying these observations and explains how empirical power-law degradation behavior can emerge from the collective interaction of many microscopic stochastic processes. The discussion begins with irreversible thermodynamics, random walk transport, diffusion, and Arrhenius kinetics and then connects these microscopic concepts to the macroscopic degradation trends commonly observed in semiconductor reliability experiments. Attention is given to the interpretation of stress-dependent power-law degradation kinetics and their implications for accelerated lifetime extrapolation. Practical limitations associated with conventional logarithmic degradation analysis are examined, including baseline sensitivity, logarithmic instability near the measurement floor, and systematic curvature that may remain hidden despite high goodness-of-fit metrics. Methods based on transformed-coordinate linearization and curvature-sensitive extraction are discussed together with their implications for time-to-failure extrapolation and activation-energy interpretation. Experimental studies of phenomena such as bias temperature instability frequently show degradation behavior in which the time exponent depends systematically on voltage and temperature stress conditions. Under such conditions, the reciprocal exponent $m=1/n$ can significantly amplify stress acceleration during lifetime extrapolation. This work provides a conceptual framework connecting microscopic stochastic degradation physics with the empirical methods commonly used in practical semiconductor reliability analysis and long-term lifetime prediction. Full article

The relation between entropy and time is central to debates on thermodynamic irreversibility and the arrow of time. This paper clarifies that relation by distinguishing several roles often associated with entropy in such debates: temporal ordering, temporal orientation, temporal flow and measurement, and thermodynamic asymmetry. The paper does not deny that entropy increase, together with a low-entropy past and suitable coarse-graining, may explain the thermodynamic arrow or help orient an already ordered sequence of states. It also does not deny that thermodynamic or statistical structure may contribute to the selection or measurement of physically meaningful temporal flow in special frameworks. It addresses a narrower question: whether standard entropy notions can themselves supply temporal ordering or serve as general temporal parameters. Using thermodynamic, Boltzmann, Gibbs, and coarse-grained entropy within a minimal dynamical-systems framework, we show that they do not satisfy this role in general. Entropy functionals may be non-injective along trajectories; fine-grained Gibbs entropy is invariant under Hamiltonian flow; coarse-grained entropy depends on descriptive partitions; and entropy monotonicity depends on boundary conditions rather than an intrinsic temporal orientation. An open-system example is included only to illustrate that subsystem entropy may decrease while the dynamical time parameter continues to order the evolution. The novelty is therefore not in the bare claim that entropy and time are non-identical, nor in the attribution of a crude entropy-equals-time thesis to the literature, but in the explicit role-separation argument showing why entropy can characterize asymmetry, help orient an already ordered history, or contribute to temporal-flow selection only after suitable dynamical, statistical, or ordering structure is already given. Entropy remains central to statistical-mechanical accounts of irreversibility, but under standard definitions, it cannot itself supply temporal ordering. Full article

Background and Clinical Significance: Susac syndrome is a rare autoimmune-mediated microangiopathy characterized by the triad of encephalopathy, branch retinal artery occlusion (BRAO), and sensorineural hearing loss. Due to its variable onset and protean manifestations, the syndrome is frequently misdiagnosed, potentially leading to delayed treatment and irreversible organ damage. Ocular involvement is common and often provides the first diagnostic clue. Multimodal imaging, particularly fluorescein angiography (FA) and optical coherence tomography (OCT) as well as optical coherence tomography angiography (OCT-A), enables the detection of both acute and chronic ischemic retinal changes. Their complementary application yields critical insights into disease activity, supports monitoring of relapses, and guides therapeutic strategies. Case Presentation: We describe two patients with Susac syndrome presenting with distinct ocular and neurological features. A 43-year-old male developed recurrent BRAOs in both eyes, documented by FA, OCT, and OCT-A, with preserved best-corrected visual acuity (BCVA) of 0.00 logMAR in both eyes (OU). OCT demonstrated progressive thinning of the retinal nerve fiber layer (RNFL) and inner retinal layers, consistent with sequelae of microinfarctions, while FA revealed focal arteriolar wall hyperfluorescence. Immunosuppressive therapy with corticosteroids and mycophenolate mofetil stabilized his condition. A 31-year-old female with a history of migraine and encephalopathy showed thinning of the RNFL and ganglion cell layer (GCL) with macular atrophy on OCT. FA demonstrated peripheral arteriolar wall hyperfluorescence and microaneurysms. Despite these structural alterations, visual acuity remained unaffected. Serial imaging initially demonstrated mild progression on OCT and OCT-A, followed by disease stabilization under systemic immunosuppressive therapy. Conclusions: These cases highlight the pivotal role of multimodal imaging in the early recognition and long-term monitoring of Susac syndrome. OCT provides a detailed assessment of retinal microinfarctions and chronic atrophy, while FA remains indispensable for detecting vascular leakage and disease activity. The complementary use of OCT, OCT-A, and FA enhances diagnostic accuracy, facilitates timely therapeutic interventions, and supports individualized management. Regular ophthalmological monitoring, including advanced imaging modalities, should be considered an essential component of care in Susac syndrome. Full article