Search Results (96)

Background: Long COVID, or post-COVID-19 condition (PCC), affects around 36% of individuals following SARS-CoV-2 infection, manifesting as persistent fatigue, cognitive dysfunction, and dysautonomia among its hallmark features. Affecting an estimated 400 million individuals globally, it imposes an annual economic burden exceeding $1 trillion, yet no pharmacological therapy has demonstrated consistent efficacy in adequately powered randomized controlled trials. Transcutaneous auricular vagus nerve stimulation (taVNS) has emerged as a candidate intervention targeting the autonomic dysfunction and neuroinflammation responsible for PCC pathophysiology. Methods: We conducted a PRISMA 2020-compliant systematic review (PROSPERO: CRD420261287286) searching PubMed, Scopus, Cochrane, and Web of Science databases from inception to January 2026 for studies evaluating any form of VNS in adults with Long COVID. Risk of bias was assessed using the Cochrane Risk of Bias 2 (RoB 2) tool, the JADAD scale, and the PEDro scale. Certainty of evidence was evaluated using the GRADE framework. Narrative synthesis followed SWiM guidelines. Results: Five studies (n = 154 participants) (three randomized controlled trials (RCTs) and two single-arm studies) met inclusion criteria. Three of five studies (60%) were rated high overall risk of bias; only two RCTs achieved “some concerns.” The only adequately double-blinded RCT found no significant between-group differences across all outcomes. Paradoxically, in the best-powered RCT (Percin et al.), sham stimulation produced significantly greater fatigue improvement than active taVNS, despite active taVNS producing significant HRV increases consistent with cardiac autonomic modulation. All efficacy outcomes were rated “very low” certainty (GRADE); safety was rated “low” certainty. Conclusions: Currently available evidence supporting the use of taVNS for Long COVID remains limited, and the absence of reliable target engagement markers in the included studies constrains confidence in this approach. Nonetheless, the physiological rationale remains sound, and the favorable safety profile across all included studies supports the feasibility of future investigation. However, given that positive findings were confined to inadequately controlled studies, enthusiasm for further research should be directed first toward mechanistic clarification and rigorous dose-finding work. Large-scale, double-blind, sham-controlled trials incorporating validated markers of vagal engagement are required before taVNS can be firmly recommended for COVID-19 sequelae management. Full article

Background: Cognitive difficulties are common after SARS-CoV-2 infection, yet their neurobiological underpinnings remain uncertain. Cognitive symptoms in post-COVID-19 condition (PCC) are often characterised by attentional and executive dysfunction, although the relationship between subjective symptoms and objective neurobiological changes remains uncertain. Methods: Adults previously hospitalised with COVID-19 who reported persistent cognitive symptoms underwent neuropsychological testing and 3 T MRI. The protocol included high-resolution volumetric imaging, diffusion-based tractography, and magnetic resonance spectroscopy (MRS) of frontal white matter. Data were compared with age- and sex-matched controls from a pre-COVID-19 cohort and against pooled normative MRS datasets. Analyses adjusted for intracranial volume, sex, and time since infection, with false-discovery-rate correction. This study was exploratory and hypothesis-generating in design. Results: Thirty participants were recruited; twenty-nine completed MRI acquisition. Participants (mean age 58 years; 62% female; approximately two years post-infection) demonstrated selective impairments in attention, working memory, and verbal fluency. No widespread volumetric or white-matter differences were identified, although reduced posterior hypothalamic volume and altered occipito-parietal connectivity were observed. MRS demonstrated reduced N-acetylaspartate and elevated choline, myo-inositol, and glutamate-glutamine ratios relative to normative reference ranges. No significant associations were observed between imaging measures and cognitive or symptoms outcomes after correction. Conclusions: PCC is characterised by circumscribed cognitive changes and subtle neural differences, but these objective changes do not closely align with subjective symptom severity. This mismatch shares phenotypic features with functional cognitive disorder and suggests that post-COVID-19 “brain fog” is not driven by structural or neurochemical changes alone. Instead, it potentially reflects a combination of mild neurobiological effects and functional cognitive processes. Together, these findings highlight the importance of considering both brain-based and functional contributors to persistent cognitive complaints after SARS-CoV-2 infection. Full article

The increasing penetration of inverter-based distributed energy resources (DERs) within distribution networks has resulted in harmonic distortion risks that can affect transformer thermal loading, service life, and network hosting capacity. This study assesses harmonic behaviour under increasing DER penetration using a detailed MATLAB 2025b/Simulink model of the CIGRÉ low-voltage benchmark feeder, adapted to reflect representative network parameters and run at a 400 V point of common coupling (PCC). DER penetration is incrementally increased from 0% to 195% of feeder load, and for each penetration level the PCC currents and voltages are examined using FFT-based spectrum extraction. The short-circuit strength is first calculated (I_SC/I_L = 14.1), and harmonic current and voltage distortion thresholds are benchmarked against IEEE 519:2022 and NRS 048-2:2025 respectively. Results show that while DER inverters introduce increasing odd-order harmonics, mainly the 3rd, 5th, 7th and 11th, the feeder’s moderate short-circuit capacity suppresses PCC voltage distortion, keeping voltage THD below 3% across all scenarios. As the inverter-based DER penetration increases, so does the harmonic current distortion. At 180%, Total Demand Distortion (TDD) nears the IEEE limit of 5%. Full article

DC distribution systems are increasingly utilized in data centers, electric vehicle charging infrastructures, and microgrids due to their superior power conversion efficiency compared to AC systems. In DC networks, the protection coordination of overcurrent relays (OCRs) is essential for selectively isolating faults and maintaining operational stability. However, the integration of distributed energy resources (DERs), such as photovoltaics, introduces significant challenges by altering the magnitude and rate of change of fault currents. This study conducts a comprehensive analysis of various scenarios by varying both the fault location and the points of common coupling (PCC) for DER. The simulation results reveal that specific configurations lead to critical instances of protection mis-operation and failure to operate, which cause coordination failures and compromised coordination time intervals (CTIs). These findings demonstrate that conventional protection strategies may fail to ensure reliability in DER-integrated DC systems due to the dynamic nature of fault current characteristics. In this paper, these diverse scenarios and the resulting vulnerabilities in protection coordination were modeled and verified using PSCAD/EMTDC V5.0. Full article

Background/Objectives: Post-COVID-19 condition (PCC) remains poorly characterized beyond two years, particularly among intensive care unit (ICU) survivors. We aimed to describe the prevalence, persistence, and late consequences of PCC up to 32 months after discharge in an ICU cohort. Methods: This single-center longitudinal cohort included 170 adults with confirmed SARS-CoV-2 infection admitted to an ICU in Cáceres (Spain) between March 2020 and March 2021. 94 survivors entered follow-up at discharge and 3, 6, 12, 18, 24, and 32 months. PCC manifestations were grouped into five organ system domains (respiratory, cardiovascular, renal, infectious, and musculoskeletal/neuromuscular) and recorded only when supported by clinician-confirmed diagnoses or diagnostic tests. Prevalence at each visit, persistence, and new onset of manifestations between 3 and 6 months, and the cumulative incidence of new chronic diseases between 18 and 32 months were estimated with 95% confidence intervals. Results: Any PCC manifestation was almost universal at discharge (96.8% [95% CI, 91.1–98.9]) and remained high at 12 months (85.2% [95% CI, 76.3–91.2]), declining to 48.6% at 24 months and 25.7% at 32 months. Respiratory manifestations predominated early and were largely resolved by 32 months, whereas musculoskeletal/neuromuscular involvement remained relatively stable. From 18 to 32 months, 36.5% (95% CI, 26.4–47.9) of survivors developed at least one chronic condition, most frequently cardiovascular disease (14.9% [95% CI, 8.5–24.7]). Conclusions: Long-term PCC manifestations and incident chronic diseases are common among ICU COVID-19 survivors, underscoring the need for prolonged follow-up and post-ICU care. Full article

Background/Objectives: This study aimed to determine the prevalence of persistent symptoms and the radiological and laboratory evolution at 6 months and 5 years after discharge in patients hospitalized for SARS-CoV-2 pneumonia during the first wave of the pandemic in Spain and to estimate the healthcare impact of their follow-up. Methods: A retrospective longitudinal observational study was conducted at the “Hospital Central de la Defensa”. A total of 200 patients aged >18 years with a diagnosis of SARS-CoV-2 pneumonia were screened. Clinical, radiological, and laboratory data were collected from electronic medical records. Patients with symptoms or radiological abnormalities at discharge underwent in-person evaluations, while the remainder were assessed by telephone. Results: A total of 182 patients met the inclusion and exclusion criteria. Of these, 112 were assessed in the outpatient setting; 60.7% required in-person evaluations, with normal pulmonary auscultation in 93.6%, complete radiological resolution in 85%, and normalized laboratory parameters in almost all cases. At 6 months, 26.5% presented at least one residual symptom, whereas only three patients (4.5%) reported symptoms at 5 years. No risk factors associated with symptom persistence were identified. The estimated cumulative healthcare cost was EUR 21,627.50. Conclusions: Among patients hospitalized for SARS-CoV-2 pneumonia during the first wave of the pandemic, 26.7% and 4.46% presented at least one persistent symptom at 6 months and 5 years after discharge, respectively. Full article

Background: Persistent low-grade inflammation has been proposed as part of the biological mechanisms underlying post-COVID condition (PCC), which can result in laboratory tests abnormalities. However, the accuracy of routine laboratory tests for the diagnosis and follow-up of PCC is still under discussion. Methods: Patients with SARS-CoV-2 infection enrolled in the prospective, multinational ORCHESTRA cohort study, which included both European and non-European countries, were followed up for 18 months after acute infection. Blood test results were collected at acute infection and at 6, 12, and 18 months. A multivariable analysis was performed to estimate the relationship between the alterations of biochemical markers and the presence of four distinct PCC phenotypes, identified previously through a principal component analysis—respiratory (RESc), chronic pain (CPc), chronic fatigue (CFc), and neurosensorial (NSc)—during follow-up. Furthermore, this study investigated the correlation between biochemical parameters measured during the acute phase and the subsequent development of PCC. Finally, the relationship between the severity of the acute infection and biochemical abnormalities observed during follow-up was assessed. Results: The cohort included 4587 patients, 58% male, with a mean age of 58.7 (±15.5) years. A robust multivariable analysis demonstrated that, compared to controls, patients with PCC, and in particular those in the RESc cluster, presented higher mean C-reactive protein (CRP) levels at the 12- and 18-month follow-up (p-value = 0.01). In each follow-up, CRP values in patients with PCC and RESc were above 3 mg/L, corresponding to those observed in low-grade inflammation (3–10 mg/L). The severity of COVID-19 acute infection was associated with increased levels of CRP, ferritin and LDH during follow-up (p < 0.001). Biochemistry abnormalities detected during the early stages of acute COVID-19 did not correlate with an increased risk of developing PCC and its phenotypes. Conclusions: In patients with the RESc PCC phenotype, identified through a principal component analysis, blood test abnormalities consistent with prolonged and sustained low-grade inflammation can be detected up to 18 months after acute infection, supporting its role in the pathogenesis of PCC. Based on these results, trials on anti-inflammatory drugs, together with symptom-tailored interventions for patients with RESc, should be planned to prove their effectiveness in managing PCC and improving patient outcomes. Full article

Gold nanoparticles (AuNPs) are of significant interest due to their unique properties and applications in biomedicine. While hyaluronic acid (HA) has been used to modify pre-formed AuNPs, its thiolated derivative (HA−SH) has been less explored for the direct synthesis and stabilization of AuNPs. This study investigates the use of thiolated hyaluronic acid as a key component in the synthesis of AuNPs. A series of HA-AuNPs (HA-AuNP1-4) were synthesized by reacting HA-SH with HAuCl₄ at different mass ratios. The resulting nanoparticles were characterized using UV-Vis spectroscopy, scanning/transmission electron microscopy (SEM/STEM), X-ray photoelectron spectroscopy (XPS), photon cross-correlation spectroscopy (PCCS), and zeta potential measurements. The chemical transformations of the thiol ligand were studied using NMR spectroscopy. The morphologies and sizes of AuNPs depended on the HA-SH-to-HAuCl₄ ratio, ranging from icosahedral and triangular particles (≥146 nm) to quasi-spherical particles with a bimodal distribution (6–7 nm and 45–60 nm). XPS confirmed the presence of metallic gold (Au⁰) and a Au−S bond, while NMR and XPS revealed the partial oxidation of thiol groups to sulfonic acid. Zeta potential measurements showed that lower HAuCl₄ concentrations resulted in higher negative charge (up to −41.5 mV), enhancing colloidal stability. This work demonstrates a versatile approach to the synthesis of hyaluronic acid-based gold nanomaterials with tunable properties for potential biomedical applications. Full article

Video-based point cloud compression (V-PCC) is a 3D point cloud compression standard that first projects the point cloud from 3D space onto 2D space, thereby generating geometric and attribute videos, and then encodes the geometric and attribute videos using high-efficiency video coding (HEVC). In the whole coding process, the coding of geometric videos is extremely time-consuming, mainly because the division of geometric video coding units has high computational complexity. In order to effectively reduce the coding complexity of geometric videos in video-based point cloud compression, we propose a fast segmentation algorithm based on the occupancy type of coding units. First, the CUs are divided into three categories—unoccupied, partially occupied, and fully occupied—based on the occupancy graph. For unoccupied CUs, the segmentation is terminated immediately; for partially occupied CUs, a geometric visual perception factor is designed based on their spatial depth variation characteristics, thus realizing early depth range skipping based on visual sensitivity; and, for fully occupied CUs, a lightweight fully connected network is used to make the fast segmentation decision. The experimental results show that, under the full intra-frame configuration, this algorithm significantly reduces the coding time complexity while almost maintaining the coding quality; i.e., the BD rate of D1 and D2 only increases by an average of 0.11% and 0.28% under the total coding rate, where the geometric video coding time saving reaches up to 58.71% and the overall V-PCC coding time saving reaches up to 53.96%. Full article

The irregular and highly non-uniform spatial distribution inherent to dynamic three-dimensional (3D) point clouds (DPCs) severely hampers the extraction of reliable temporal context, rendering inter-frame compression a formidable challenge. Inspired by two-dimensional (2D) image and video compression methods, existing approaches attempt to model the temporal dependence of DPCs through a motion estimation/motion compensation (ME/MC) framework. However, these approaches represent only preliminary applications of this framework; point consistency between adjacent frames is insufficiently explored, and temporal correlation requires further investigation. To address this limitation, we propose a hierarchical ME/MC framework that adaptively selects the granularity of the estimated motion field, thereby ensuring a fine-grained inter-frame prediction process. To further enhance motion estimation accuracy, we introduce a dual-attention-based KNN block-matching (DA-KBM) network. This network employs a bidirectional attention mechanism to more precisely measure the correlation between points, using closely correlated points to predict inter-frame motion vectors and thereby improve inter-frame prediction accuracy. Experimental results show that the proposed DPC compression method achieves a significant improvement (gain of 70%) in the BD-Rate metric on the 8iFVBv2 dataset. compared with the standardized Video-based Point Cloud Compression (V-PCC) v13 method, and a 16% gain over the state-of-the-art deep learning-based inter-mode method. Full article

With the large-scale integration of renewable energy devices into the power grid, the voltage stability of the renewable energy base is becoming increasingly weak, and the problem of transient overvoltage is becoming increasingly severe. Grid-forming (GFM) converters can provide strong voltage support. When GFM converters are paralleled with grid-following (GFL) converters, they can effectively reduce transient overvoltage. However, hybrid systems involve many parameters and exhibit complex dynamics, making assessment of transient overvoltage difficult. To address this, this paper first uses Thevenin’s theorem to reduce the renewable transmission system to an equivalent model. Next, the voltage assessment of the hybrid system is analyzed across the pre-fault, mid-fault, and post-fault stages of a short-circuit fault. Then, based on the characteristics of a phase-locked loop (PLL), this paper innovatively derives an assessment method for transient overvoltage at the common coupling point (PCC) under different PLL stability conditions. Additionally, the influence of GFL converter parameters, GFM converter parameters, the GFM capacity ratio on transient overvoltage, and the external system reactance are analyzed. Finally, the proposed evaluation method and factor analysis are validated through electromechanical transient simulation using the simulation software STEPS v2.2.0. Full article

With the development of smart agriculture, the precise identification of fruit tree trunks by orchard management robots has become a key technology for achieving autonomous navigation. To solve the issue of tree trunks being hard to see against their background in orchards, this study introduces PCC-YOLO (PENet, CoT-Net, and Coord-SE attention-based YOLOv8), a new trunk detection model based on YOLOv8. It improves the ability to identify features in low-contrast situations by using a pyramid enhancement network (PENet), a context transformer (CoT-Net) module, and a combined coordinate and channel attention mechanism. By introducing a pyramid enhancement network (PENet) into YOLOv8, the model’s feature extraction ability under low-contrast conditions is enhanced. A context transformer module (CoT-Net) is then used to strengthen global perception capabilities, and a combination of coordinate attention (Coord-Att) and SENetV2 is employed to optimize target localization accuracy. Experimental results show that PCC-YOLO achieves a mean average precision (mAP) of 82.6% on a self-built orchard dataset (5000 images) and a detection speed of 143.36 FPS, marking a 4.8% improvement over the performance of the baseline YOLOv8 model, while maintaining a low computational load (7.8 GFLOPs). The model demonstrates a superior balance of accuracy, speed, and computational cost compared to results for the baseline YOLOv8 and other common YOLO variants, offering an efficient solution for the real-time autonomous navigation of orchard management robots. Full article

As an important representation form of three-dimensional scenes, the point cloud contains rich geometry and attribute information. The video-based point cloud compression standard (V-PCC) divides and projects three-dimensional data directionally onto a two-dimensional plane. The generated geometric and attribute graphs contain occupied pixels obtained by projection and unoccupied pixels used for smooth filling. Among them, the non-occupied pixels have no practical effect on the reconstructed point cloud. However, in the process of encoding bitrate allocation, V-PCC still uses the original bitrate control method, resulting in insufficient bitrate utilization efficiency. To this end, this paper proposes a method for optimizing the unoccupied pixels of point cloud videos based on V-PCC and jointly controlling the coding rate of geometries and attribute graphs. For geometric graphs, this paper improves the allocation of bitrate weights based on whether the encoded blocks contain non-occupied pixels and the proportion of occupied pixels, and stops allocating bitrates to encoded blocks that are all non-occupied pixels. For the attribute graph, the input pixel improvement algorithm is designed by using the occupation map, and the invalid unoccupied pixel information is cavitation. Experiments show that under the All Intra configuration, compared with the original scheme, this method reduces the Geom.BD-GeomRate by an average of 15.67% and 16.68%, respectively, in the point-to-point D1 and point-to-face D2 metrics. The end-to-end BD-AttrRate is reduced by an average of 4.38%, 0.68%, and 1.74%, respectively. Overall, the average savings are 29.88%, 31.50%, 5.50%, 2.66%, and 3.34%, respectively, achieving bitrate optimization and effectively controlling encoding loss. Full article

Long- or post-COVID-19 syndrome, which is also designated by WHO as Post COVID-19 Condition (PCC), is characterized by the persistent symptoms that remain after recovery from SARS-CoV-2 infection. A worldwide consortium of Long COVID-19 Host Genetics Initiative (Long COVID-19 HGI) identified an SNP rs9367106 (G>C; chr6:41,515,652, GRCh38, p = 1.76 × 10⁻¹⁰, OR = 1.63, 95% CI: 1.40–1.89) that is associated with PCC. Unraveling the functional significance of this SNP is of prime importance to understanding the development of the PCC phenotypes and their therapy. Here, in Silico, I explored how the risk allele of this SNP alters the functional mechanisms and molecular pathways leading to the development of PCC phenotypes. Bioinformatic methods include physical interactions using HI-C and Chia-PET analysis, Transcription Factors (TFs) binding ability, RNA structure modeling, epigenetic, and pathway analysis. This SNP resides within two long RNA genes, LINC01276 and FOXP4-AS1, and is located at ~31 kb upstream of a transcription factor FOXP4. This DNA region, including this SNP, physically interacts with FOXP4-AS1 and FOXP4, implying that this regulatory SNP could alter the normal cellular function of FOXP4-AS1 and FOXP4. Furthermore, rs9367106 is in eQTL with the FOXP4 gene in lung tissue. rs9367106 carrying DNA sequences act as distant enhancers and bind with several transcription factors (TFs) including YY1, PPAR-α, IK-1, GR-α, and AP2αA. The G>C transition extensively modifies the RNA structure that may affect the TF bindings and enhancer functions to alter the interactions and functions of these RNA molecules. This SNP also includes an ALU/SINE sequence and alteration of which by the G>C transition may prevent IFIH1/MDA5 activation, leading to suppression of host innate immune responses. LINC01276 targets the MED20 gene that expresses mostly in brain tissues, associated with sleep disorders and basal ganglia abnormalities similar to some of the symptoms of PCC phenotypes. Taken together, G>C transition of rs9367601 may likely alter the function of all three genes to explain the molecular basis of developing the long-term symptomatic abnormalities in the lungs and brain observed after COVID-19 recovery. Full article

Post-COVID condition (PCC) is a complex syndrome characterized by the persistence of diverse symptoms—including respiratory, neurological, and psychiatric manifestations—that last for weeks or months after acute Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection. Epidemiological data indicate a higher prevalence among women and older adults, with significant impacts on daily functioning. The pathophysiology of PCC is multifactorial, involving immune dysregulation, viral persistence, mitochondrial dysfunction, and oxidative stress, all of which contribute to sustained neuroinflammation. This narrative review examines the clinical features, risk factors, and current evidence on antioxidant-based interventions as potential therapeutic strategies for PCC. A wide range of compounds—including vitamins, polyphenols, and endogenous antioxidants—have shown promise in mitigating neuroinflammation and oxidative damage in both clinical and experimental settings. Antioxidants may help restore redox balance and improve neurological outcomes in affected patients. However, further clinical research is essential to determine their efficacy, safety, and optimal therapeutic protocols. Full article