Search Results (2,336)

Background: Oedema is a multifactorial condition arising from the interplay between increased microvascular permeability, impaired lymphatic clearance, and sustained inflammation. Conventional treatments often fail, highlighting alternative therapies. This study explores a novel nutraceutical formulation (NF) based on the combination of different natural extracts, i.e., Melilotus officinalis L., Olea europaea L., Morinda citrifolia L., Quercus robur L., and bromelain, aimed at reducing inflammation, a key contributor to oedema pathophysiology. In vitro assays further demonstrated that NF exhibits a marked antioxidant capacity and effectively inhibits key enzymes of the arachidonic acid cascade, supporting its ability to counteract oxidative stress and inflammatory signalling involved in oedema pathophysiology. Methods: The antioxidant and anti-inflammatory properties of NF were assessed in vitro using radical scavenging assays and enzyme inhibition tests targeting key components of the arachidonic acid cascade. The immunomodulatory effects of NF were investigated in RAW264.7 macrophages by flow cytometry and RT-qPCR to evaluate macrophage polarisation and cytokine expression. The anti-oedematous and vascular effects were further examined in vivo using acetic acid–induced inflammation and carrageenan-induced paw oedema models in thirty male Sprague–Dawley rats (Charles River, Calco, Italy). Results: The study demonstrated that NF significantly modulates macrophage polarisation, reducing the proportion of pro-inflammatory M1 macrophages (F4/80⁺CD11b⁺) by 3.23 times compared to control (p < 0.01). A quantitative PCR analysis further confirmed a decrease in pro-inflammatory cytokines (TNF-α, IL-6, and IL-1β) by 51.3% (95% CI 48.0–58.7, p < 0.001), 64.1% (95% CI 57.0–71.2, p < 0.001), and 53.7% (95% CI 51.7–55.7, p < 0.001), respectively compared to the control, while anti-inflammatory markers (Arg-1, CD206) increased significantly, suggesting a shift towards an M2 anti-inflammatory state. The NF ability to contrast the pathological alteration characteristic of this disease was further tested in the rat oedema model of thirty male Sprague-Dawley rats. The NF treatment reduced LTB4 and plasma protein levels compared to the control group. In addition, NF could decrease the paw thickness in the rat-based carrageenan-induced oedema model (Charles River, Calco, Italy; n = 30) by 22.5% compared to the control (95% CI 11.0–34.0, p < 0.05). Conclusions: These results suggest that NF may provide a multi-target approach to support the management of some physiopathological changes in complex oedema-related conditions by both modulating inflammation and restoring vascular functionality. Full article

New aminonitrocyclitols were directly synthesized through stereoselective, one-pot, multistep cascade reactions. The aminonitrocyclitol moiety was constructed by the sequential action of two enzymes followed by a spontaneous intramolecular Henry reaction. To construct the carbocycle, two C–C bonds were stereoselectively cleaved, one by aldolase and the other by the intramolecular nitroaldol reaction. The aldolase acceptor substrates were generated by adding an amino group to 4-nitrobutanal. As expected, only the (R,R)- or d-erythroaldol configuration was obtained with l-fuculose-1-phosphate aldolase (F1PA). In the case of l-rhamnulose-1-phosphate aldolase (R1PA), both the aldol (R,S)- or l-threo and erythroaldol (R,R)- or d-erythroaldol configurations were obtained in very close ratios. The presence of a ketone and a terminal nitro group in the aldol formed led to a stereoselective intramolecular Henry reaction. The various aminonitrocyclitols were obtained in amide form with an average overall yield of 60%. Deprotection of the amine function was achieved by hydrolysis of the amide group by the action of papain without epimerization at the ring carbon stereochemistries defined in the previous steps. All these reactions led to the preparation of new aminonitrocyclitols with high stereoselectivity. Full article

While the Internal Model Principle (IMP) and Disturbance Observer (DOB) are fundamental to robust control, their systematic equivalence within a unified framework has received limited attention. IMP-based control achieves robustness through the structural inclusion of signal generators, whereas DOB-based methods rely on extended state representations for disturbance estimation. This paper bridges this gap by designing a state-space Reduced-Order Disturbance Observer (RODOB)-based controller that achieves systematic equivalence with an IMP-based transfer function controller. As a design example, an IMP-based controller is synthesized using a Linear Quadratic Regulator (LQR) for an augmented system in error space, with reference inputs directly integrated into the RODOB structure to eliminate the need for additional filters. Simulations and hardware experiments on a Brushless DC (BLDC) motor verify that both structures exhibit consistent control input and output characteristics, significantly outperforming conventional cascade and PID strategies. Numerical stability during digital implementation is ensured via partial fraction expansion. Furthermore, a method for estimating equivalent disturbances—encompassing both external loads and model uncertainties—is proposed by leveraging RODOB states. These findings suggest significant potential for future applications in fault diagnosis and real-time condition monitoring. Full article

Heat damage caused by elevated temperature and humidity during storage significantly affects soybean seed quality and viability. Early detection remains challenging due to the lack of visible symptoms in mildly damaged seeds. In this study, hyperspectral imaging (HSI) was adopted to capture detailed spectral information associated with internal physiological changes in soybean seeds. To simulate realistic thermal stress scenarios, soybean seeds were subjected to two temperature conditions: a control group stored at 25 °C and 55% RH and a heat-treated group stored at 45 °C and 80% RH. Within the high-temperature group, different durations (20 and 30 days) were used to generate mildly and severely damaged seeds, respectively. After image acquisition using a 400–1000 nm VNIR-HSI system, multiplicative scatter correction (MSC) was selected as the optimal preprocessing method to reduce scattering effects. Spectral dimensionality was then reduced using a recursive feature elimination–principal component analysis (RFE-PCA) cascade to retain key discriminative features. Finally, a support vector classifier was constructed and optimized using a Lévy–Sine-enhanced Egret Swarm Optimization Algorithm (LSESOA), yielding a classification accuracy of 96.75% and a macro-F1 score of 96.76% on the test set. This study demonstrates the feasibility of applying HSI combined with metaheuristic optimization to achieve accurate, non-destructive evaluation of heat-damaged soybean seeds, providing technical support for quality control during storage and logistics. Full article

Maintaining stable pressure in the oxidation–compressor section of purified terephthalic acid (PTA) plants is essential for ensuring efficient and reliable operation. Conventional single-loop proportional integral derivative (PID) controllers frequently perform inadequately because of the large pressure drop between the compressor discharge and reactor inlet, which should ideally remain at approximately 1.2 kg/cm² above the reactor pressure setpoint but can reach up to 2.8 kg/cm² due to downstream vapor-phase disturbances. Through this study, we aimed to address this issue by developing a robust cascade pressure control strategy to improve pressure stability and reduce energy losses. Dynamic process models were constructed using system identification techniques to represent real plant behavior, and the best-performing models—identified based on minimum root mean square error (RMSE)—were determined using the Wade method for pressure indicating controller PIC-101, the Lilja method for PIC-102, and the Smith method for pressure differential indicating controller PDIC-101. The proposed cascade configuration was tuned using the Lopez ISE method and evaluated under representative disturbance scenarios. The results showed that the cascade controller significantly improved pressure control, enhanced disturbance rejection, and lowered the risk of reactor shutdowns compared with the conventional proportional-integral PI-based approach. Overall, this study demonstrated that model-driven cascade control can enhance robustness, operational reliability, and energy efficiency in large-scale PTA oxidation processes. Full article

The blood–brain barrier (BBB) is a major obstacle to the development of brain-targeted drug delivery systems, restricting greater than 98% of small molecules (<500 Da) and virtually all large-molecule drugs from entering the brain tissues from the bloodstream, resulting in suboptimal drug doses and therapeutic failure in the treatment of Alzheimer’s disease (AD). However, the advent of nanotechnology has provided significant solutions to the BBB challenges, enabling particle size reduction, enhanced drug solubility, reduced premature drug degradation, extended and sustained drug release, enhanced drug transport across the BBB, increased drug target specificity and enhanced therapeutic efficacy. In corollary, a library of brain-targeted surface-functionalized nanotherapeutics has been widely reported in the current literature. These promising in vitro, in vivo and pre-clinical results from the existing literature provide quantitative evidence for the relative clinical utility of each of the techniques, indicating remarkable capacity for brain-targeted carrier systems; many of them are still being tested in human clinical trials. However, despite the recorded research successes in drug transport across the BBB, there are currently no clinically proven medications that can slow or reverse the progression of AD because most of the novel therapeutics have not been successful during the clinical trials. Therefore, the main option for the treatment of AD is symptomatic treatment using cholinesterase inhibitors and N-methyl-D-aspartate (NMDA) receptor antagonists. Although these therapies help to alleviate symptoms of AD and improve patients’ quality of life, they neither slow the progression of disease nor cure it. Thus, an effective disease-modifying therapy for the treatment of AD is an unmet clinical need. It is apparent that a deeper understanding of the structural complexity and controlling dynamic functions of the BBB in tandem with a comprehensive elucidation of AD pathogenesis are crucial to the development of novel nanocarriers for the effective treatment of AD. Therefore, this narrative review describes the contextual analysis of several promising strategies that enhance brain-targeted drug delivery across the BBB in AD treatment and recent research efforts on two major AD biomarkers that have revolutionized AD diagnosis, amyloid-beta plaques and phosphorylated tau protein tangle, as potential targets in AD drug development. This has led to the Food and Drug Administration (FDA)’s approval of two intravenous (IV) anti-amyloid monoclonal antibodies, Lecanemab (Leqembi^®) and Donanemab (Kisunla^®), which were developed based on the Aβ cascade hypothesis for the treatment of early AD. This review also discusses the recent shift in the Aβ cascade hypothesis to Aβ oligomer (conformer), a soluble intermediate of Aβ, which is the most toxic mediator of AD and could be the most potent drug target in the future for a more accurate and effective drug development model for the treatment of AD. Furthermore, various promising nanoparticle-based drug carriers (therapeutic nanoparticles) that were developed from intensive research are discussed, including their clinical utility, challenges and prospects in the treatment of AD. Overall, it suffices to state that the advent of nanotechnology provided several innovative techniques for overcoming the BBB and improving drug delivery to the brain; however, their long-term biosafety is a relevant concern. Full article

Chronic stress and sustained hypothalamic–pituitary–adrenal (HPA) axis activation are major contributors to metabolic bone diseases, including osteoporosis. However, the precise molecular mechanisms by which chronic stress-induced HPA axis dysregulation drives bone deterioration remain unclear. A Chronic Unpredictable Mild Stress (CUMS) model was established in male rats to simulate prolonged stress exposure. Animals were randomly allocated into three groups: control, 10-week CUMS, and 20-week CUMS (n = 10/group). Model validity was confirmed via behavioral assessments. Bone mineral density (BMD) and trabecular microarchitecture were quantified using micro-computed tomography (micro-CT). Serum corticosterone (CORT) levels, HPA axis negative feedback function, and the expression of pro-inflammatory cytokines (IL-1β, TNF-α) in HPA-regulatory brain regions (hippocampus, prefrontal cortex, hypothalamus) were assessed. Critically, glucocorticoid receptor (GR) expression and nuclear translocation in these brain regions and bone tissue were examined by immunofluorescence and Western blot analysis. CUMS exposure induced progressive, time-dependent bone loss, with the 20-week group exhibiting significantly greater reductions in BMD and trabecular quality compared to the 10-week and control groups. While the HPA axis showed initial hyperactivation, the 20-week group displayed adrenal exhaustion (reduced serum CORT) alongside elevated ACTH, indicating feedback failure. Mechanistically, stress significantly impaired GR nuclear translocation in both brain and bone tissues, coinciding with the upregulation of FKBP5 and pro-inflammatory cytokines. Notably, despite low systemic CORT at late stages, skeletal 11β-HSD1 expression was significantly upregulated, creating a local microenvironment of glucocorticoid toxicity that aggravated osteoblast apoptosis. Our findings demonstrate that chronic stress induces progressive, time-dependent bone loss through a cascade of HPA axis dysregulation and impaired GR signaling. The FKBP5-mediated impairment of GR nuclear translocation in both central and peripheral tissues fosters glucocorticoid resistance, perpetuating hypercortisolemia and a pro-inflammatory milieu that directly accelerates osteoblast apoptosis and bone deterioration. These findings identify the HPA-GR axis as a critical pathway linking chronic stress to osteoporosis and suggest that restoring GR signaling offers a potential therapeutic strategy. Full article

Imperfect first-trimester screening for hypertensive disorders of pregnancy (HDP) means many high-risk women miss the window for preventive aspirin, and the biological heterogeneity of HDPs is overlooked. This study aimed to leverage first-trimester serum proteomics to create a more precise tool for predicting preeclampsia (PE) and differentiating it from other HDPs. A prospective nested case–control study (n = 172) was conducted using targeted liquid chromatography-multiple reaction monitoring-mass spectrometry (LC-MRM-MS) proteomic profiling of 115 proteins. Machine learning (ML) methods were used to develop classifiers from the proteomic data. The signature predictive of PE was characterized by dysregulation of the complement and coagulation cascades (F10, C8A, C1QA, SERPING1, VTN). The profile differentiating gestational hypertension (GAH) from chronic hypertension (CAH) was linked to lipid metabolism (HRG, APOA4, APOC2). An 18-protein support vector machine (SVM) model for predicting PE demonstrated exceptional performance, with 94% sensitivity and 100% specificity, significantly outperforming the standard Fetal Medicine Foundation (FMF) screening algorithm. Pathway analysis confirmed that PE is associated with early activation of innate immunity and coagulation pathways, while GAH is linked to a pregnancy-induced metabolic response. A targeted serum proteomic combined with ML approach represents a new perspective diagnostic tool with strong potential to personalize monitoring for women at the highest risk for specific hypertensive pregnancy complications. Full article

Hydrogen-integrated decentralized energy systems (DIESs) promise communities higher renewable penetration, greater resilience, and sector coupling across electricity, heat, and mobility. AI supports forecasting, dispatch optimization, multi-asset coordination, and planning, yet designing AI-driven hydrogen communities is challenging because it spans physical infrastructure, cyber-control, and governance. This review (2020–2025) synthesizes design strategies for AI-enabled hydrogen DIESs, distilling architectural patterns, electricity–hydrogen co-optimization, uncertainty-aware operation, and digital-twin planning. It summarizes AI benefits (flexibility, efficiency, reduced curtailment) and recurring risks (forecast-optimization cascades, objective mismatch, data drift, safety and constraint breaches, digital-twin credibility gaps, cybersecurity and privacy issues, and weak reproducibility) and proposes a pragmatic roadmap prioritizing safety-aware control, standardized metrics, transparent assumptions, and community-appropriate governance. Full article

Fiber-forming polymers are increasingly used to control blood coagulation, either by accelerating the onset of hemostasis or by limiting thrombogenic events in contact with blood. Despite rapid progress in materials engineering, a unified view linking the molecular mechanisms of the coagulation cascade with specific design strategies of procoagulant and anticoagulant polymeric fibers is still missing. In this review, we summarize current knowledge on how natural and synthetic polymers interact with plasma proteins, platelets, and coagulation factors, emphasizing the role of fiber morphology, surface chemistry, charge distribution, and functionalization. Particular attention was paid to systems based on natural polysaccharides (e.g., chitosan, alginate, and cellulose derivatives), as well as synthetic polymers (e.g., PLA, PCL, polyurethanes, and zwitterionic materials). Two possible courses of action were described: their bioactivity may activate the contact pathway and/or support platelet adhesion or their ability to minimize protein adsorption and inhibit thrombin generation. We discuss how metal–polymer coordination, surface immobilization of heparin or nitric oxide donors, and nanoscale texturing modulate coagulation kinetics in opposite directions. Finally, we highlight emerging fiber-based strategies for achieving either rapid hemostasis or long-term hemocompatibility and propose design principles enabling precise tuning of coagulation responses for wound dressings, vascular grafts, and blood-contacting devices. This general compendium of knowledge on blood–material interactions provides a foundation for further design of biomaterials based on fiber-forming polymers and the development of manufacturing processes. Full article

Automotive System-on-Chips (SoCs) must meet stringent functional safety standards, such as ISO 26262 and IEC 61508, to ensure reliable operation under hardware faults. FPGA-based fault injection has emerged as a practical and cost-effective technique for functional safety verification. However, instrumentation-based methods face scalability challenges when applied to the high fault densities typical of automotive SoCs. To address these challenges, we propose a hybrid cascaded fault-injection controller architecture (HCCA-SAFE) that simultaneously reduces high-fanout global nets and eliminates long serial propagation paths. The architecture constrains enable-signal cluster width and distributes control across cascaded stages, improving timing results and routability under limited FPGA resources. The proposed architecture is evaluated on multiple open-source RISC-V processor cores. On openE902, HCCA-SAFE reduces net delay from 27.276 ns to 22.535 ns and achieves 32.2% and 63.8% lower net delay compared with the representative centralized and shift-chain approaches, respectively. On openE906, the proposed HCCA-SAFE limits the net delay to 12.959 ns and reduces the maximum control-signal fanout to 1763, respectively, compared with 25.825 ns and 40.442 ns in the conventional method. On openC906, the proposed design lowers the maximum control-signal fanout from 7725 to 570 and reduces the net delay to 7.506 ns. Furthermore, HCCA-SAFE produces results fully consistent with software-based RTL simulation, while delivering substantial performance gains. Speed-up factors of $127\times$, $206\times$, and $2123\times$ are achieved on openE902, openE906, and openC906, respectively, with efficiency improvements scaling with processor complexity These results confirm that HCCA-SAFE delivers scalable, timing-robust fault-injection control suitable for large automotive SoCs. Full article

Wind power plants (WPPs), as large-scale cyber–physical systems (CPSs), have become essential to renewable energy generation but are increasingly exposed to cyber threats. Attacks on supervisory control and data acquisition (SCADA) networks can cause cascading physical and economic impacts. The systematic synthesis of cyber risk analysis methods specific to WPPs and cyber–physical energy systems (CPESs) is a need of the hour to identify research gaps and guide the development of resilient protection frameworks. This study employs a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol to review the state of the art in this area. Peer-reviewed studies published between January 2010 and January 2025 were taken from four major journals using a structured set of nine search queries. After removing duplicates, applying inclusion and exclusion criteria, and screening titles and abstracts, 62 studies were examined for analysis on the basis of a synthesis framework. The studies were classified along three methodological dimensions, qualitative vs. quantitative, model-based vs. data-driven, and informal vs. formal, giving us a unified taxonomy of cyber risk analysis approaches. Among the included studies, 45% appeared to be qualitative or semi-quantitative frameworks such as STRIDE, DREAD, or MITRE ATT&CK; 35% were classified as quantitative or model-based techniques such as Bayesian networks, Markov decision processes, and Petri nets; and 20% adopted data-driven or hybrid AI/ML methods. Only 28% implemented formal verification, and fewer than 10% explicitly linked cyber vulnerabilities to safety consequences. Key research gaps include limited integration of safety–security interdependencies, scarce operational datasets, and inadequate modelling of environmental factors in WPPs. This systematic review highlights a predominance of qualitative approaches and a shortage of data-driven and formally verified frameworks for WPP cybersecurity. Future research should prioritise hybrid methods that integrate formal modelling, synthetic data generation, and machine learning-based risk prioritisation to enhance resilience and operational safety of renewable-energy infrastructures. Full article

Duck plague virus (DPV), a highly contagious α-herpesvirus in the livestock and poultry environment, poses a significant threat to the healthy growth of ducks, potentially causing substantial economic losses. Effective control of DPV requires the development of specific diagnostic tools. A new fluorescent biosensor (R-C-CHA) was developed to detect virulent strains of DPV. It combined recombinase polymerase amplification (RPA), a CRISPR/Cas12a system, and catalytic hairpin assembly (CHA) for signal enhancement. The RPA primers were specifically designed to target the conserved DPV-CHv UL2 gene region, allowing for the rapid, efficient amplification of the target nucleic acids in isothermal conditions. The CRISPR/Cas12a system was used for sequence-specific recognition, activating its lateral cleavage activity. Furthermore, the CHA cascade reaction was utilized for enzyme-free fluorescent signal amplification. The results showed that the R-C-CHA biosensor completed the detection process in 40 min with a detection limit of 0.02 fg/μL, which was an approximate five-fold improvement compared to traditional RPA-CRISPR/Cas12a biosensors. The R-C-CHA biosensor also demonstrated perfect consistency with clinical detection and polymerase chain reaction (PCR) diagnosis, highlighting its strong potential for rapid detection in livestock and poultry farming settings. Full article

Methyl farnesoate (MF) is a sesquiterpenoid hormone that controls a variety of physiological processes in crustaceans, including morphogenesis, development, reproduction, and molting. MF action is mediated by a transcriptional signaling cascade consisting of Methoprene-tolerant (Met), Steroid receptor coactivator (Src), Krüppel homolog 1 (Kr-h1), and Ecdysone response gene 93 (E93) transcription factors (TFs), and transcriptional co-regulators CREB-binding protein (CBP) and C-terminal-binding protein (CtBP). Phylogenetic and sequence analyses revealed that these genes were highly conserved across pancrustacean species. Met and Src were characterized as basic helix-loop-helix, Period (Per)-Aryl Hydrocarbon Nuclear Translocator (ARNT)-Single-minded (Sim) protein (bHLH-PAS) TFs; Kr-h1 was characterized as a C₂H₂ zinc finger TF with seven zinc finger motifs; E93 was characterized as a helix-turn-helix, pipsqueak (HTH_Psq) TF. CBP was identified by several zinc finger-binding regions with Transcription Adaptor Zinc Finger 1 and 2, Really Interesting New Gene, Plant homeodomain, and Z-type zinc finger domains; the Kinase-inducible Domain Interacting-transcription factor docking site; the Bromodomain-acetylated lysine recognition and binding site; the histone acetyltransferase domain; and a C-terminal CREB-binding region containing a nuclear receptor co-activator-binding domain. CtBP had a dehydrogenase domain with arginine-glutamate-histidine catalytic triad. 81 Met contigs, 45 Src contigs, 136 Kr-h1 contigs, 66 E93 contigs, 60 CBP contigs, and 172 CtBP contigs were identified across pancrustacean taxa, including decapod crustaceans. Bioinformatic identification and annotation of these TFs and co-regulators in brachyuran Y-organ (YO) transcriptomes suggests that MF signaling influences YO ecdysteroidogenesis; functional tests in the YO are needed to establish causality. Full article

Tunneling nanotubes (TNTs) are thin, actin-based intercellular bridges that enable long-range communication during cellular stress; yet the molecular pathway controlling their formation remains unclear. Here, using gain- and loss-of-function approaches in Cath. a-differentiated (CAD) neuronal cells, we identified a unidirectional regulatory pathway in which myosin-X (Myo10) functions upstream of the actin-bundling protein L-(LCP1) to drive TNT formation. Using Western blotting and fluorescence microscopy, we determined that overexpression of L-plastin significantly increased the proportion of TNT-connected cells, whereas L-plastin downregulation reduced TNT formation, demonstrating that L-plastin is both sufficient and necessary for maintaining normal TNT abundance. Having previously shown that Myo10 is required for TNT formation in CAD cells, we asked whether the relationship is reciprocal. Overexpression/downregulation of L-plastin had no effect on Myo10 protein levels. Conversely, Myo10 downregulation decreased endogenous L-plastin by ~30%, and Myo10 overexpression elevated L-plastin expression and TNT number, demonstrating that Myo10 acts as an upstream regulator of L-plastin. Dual-color 3D imaging revealed co-localization of Myo10 and L-plastin along TNT shafts and filopodia-like precursors (Proto-TNTs). Together, these findings demonstrate that Myo10-dependent TNT formation requires the bundling protein L-plastin, providing a framework for how stress-induced signaling cascades couple TNT initiation to actin-core stabilization during stress and disease. Full article