Search Results (4,385)

Proteolytic processing of viral polyproteins by virally encoded proteases is essential for the replication of many RNA viruses, including retroviruses and coronaviruses, which are two of the best characterized model systems discussed in this review. These proteases are initially synthesized as polyprotein precursors that possess intrinsic, albeit comparatively low, catalytic activity and undergo tightly regulated autoprocessing to generate the mature enzymes required for viral replication. Accumulating evidence indicates that protease precursors are catalytically and mechanistically distinct from their mature counterparts, exhibiting unique biochemical properties and regulatory features that govern their activation. Therefore, precursor autoprocessing represents a critical checkpoint in viral maturation and an attractive, yet largely unexplored, target for antiviral intervention. This review examines the current understanding of the molecular mechanisms underlying precursor autoprocessing of HIV-1 protease and coronavirus main protease, with particular emphasis on the structural, biochemical, and regulatory features that distinguish precursor enzymes from their mature forms. It also highlights the experimental challenges associated with studying these highly dynamic and conformationally heterogeneous precursors, as well as recent advances in functional screening platforms that have enabled the discovery of proof-of-concept small molecules targeting precursor autoprocessing. Notably, several hit compounds retain activity against HIV-1 variants resistant to clinically approved protease inhibitors (PIs), while also inhibiting the wild-type strain. Together, these findings suggest that protease precursor autoprocessing may serve as a promising antiviral target and provide a conceptual framework for the development of next-generation therapeutics that complement existing mature-protease inhibitors. Full article

Oxidative stress is caused by the imbalance between the generation of free reactive oxygen species (ROS)/reactive nitrogen species (RNS) and the antioxidant defense systems, which participate in animal growth, development, disease pathogenesis, and aging. This review summarizes endogenous and exogenous triggers of ROS/RNS overproduction, as well as model animals and cell models together with oxidative stress biomarkers and detection methods. We further dissect the three-layered redox regulatory network, focusing on crosstalk among four core pathways (Nrf2-ARE, NF-κB, MAPK, PI3K/Akt) that govern cell fate via oxidative eustress or distress. Excessive ROS/RNS trigger irreversible DNA damage and metabolic disorders, leading to inflammation and apoptosis. Finally, we prospect integrating non-model animals and multi-omics to advance oxidative stress research. This work provides a comprehensive theoretical framework for animal redox biology studies. Full article

Sedimentary heavy metal background levels vary among lake types in heterogeneous floodplain lake systems worldwide. Uniform regional values may therefore bias contamination assessment. We developed a source–process–sink framework linking lake typology to type-specific geochemical baselines for 91 lakes in the Middle and Lower Yangtze River Plain. Ward hierarchical clustering of 24 indicators spanning freshwater, terrestrial and human landscapes plus two spatial metrics identified four groups: shallow river network (Group I, n = 28), small peri-urban lakes (Group II, n = 20), hill–plain transition lakes (Group III, n = 23) and large river-connected lakes (Group IV, n = 20). Pre-industrial layers of four dated representative sediment cores yielded type-specific Cr, Cu, Pb and Zn baselines. Surface heavy metal enrichment and contamination were assessed using the single-factor pollution index (Pi) and geo-accumulation index (Igeo), respectively. Baselines differed markedly with lake groups, with maximum-to-minimum ratios of 2.18, 3.82, 2.39 and 3.64 for Cr, Cu, Pb and Zn, respectively. Greater catchment development triggered the strongest multi-metal enrichment in Group I: P_i values for all four metals exceeded 1 in 92.9% of lakes. Igeo values for Pb exceeded 0 in 85.0% and 78.3% of Group II and III lakes, respectively. Group IV showed the weakest overall enrichment under lower catchment development. Although P_i values for Pb exceeded 1 in 85.0% of its lakes, no lake reached moderate or higher contamination for any metal. Coupling lake typology with type-specific baselines supports enrichment assessment and differentiated management at the lake group scale in China’s Middle and Lower Yangtze River Plain. Full article

Fuel cell systems require high-efficiency DC–DC interfaces capable of regulating rapid voltage variations while respecting the operational constraints of proton-exchange membrane fuel cells (PEMFCs). The floating interleaved boost converter (FIBC) is a strong candidate for this purpose due to its reduced current ripple, improved power sharing, and lower component stress. The design of control strategies for FIBCs supplied by PEMFCs remains challenging because explicitly enforcing fuel cell operational constraints under fast converter dynamics is inherently difficult, particularly when detailed fuel cell models are unavailable or undesirable, as reflected in existing approaches such as classical linear regulators and single-model predictive schemes. Therefore, this paper proposes a multi-model finite control set model-based predictive control (MM-FCS-MPC) strategy for FIBC converters supplied by PEMFCs. The method employs multiple discrete prediction models with cost functions defined by the converter switching mode, integrates a fuel cell-aware reference-generation mechanism to ensure nominal and safe PEMFC operation by enforcing current and power constraints within the predictive framework, and enables fast, accurate output-voltage regulation. Detailed modelling of the FIBC, component sizing, and PEMFC characteristics is provided. Obtained results under load disturbances and reference variations validate the proposed control scheme, demonstrating improved transient dynamics, reduced steady-state error, and enhanced current-sharing performance. Obtained results under load disturbances and reference variations validate the proposed control scheme, demonstrating improved transient dynamics, reduced steady-state error, and enhanced current-sharing performance, with a rise time of approximately 4.4 ms, a $\pm 2\%$ settling time of 10.3 ms, a maximum overshoot of only 0.056%, and a phase delay of approximately 4.26${}^{\circ }$, compared with 9.6${}^{\circ }$ for the conventional PI voltage-tracking baseline. Full article

There is a growing need for high-efficiency power electronic converters that can effectively convert energy, regulate voltages, and enhance power quality in standalone power generators, as the use of renewable energy sources and battery energy storage devices increases. The quasi-impedance-source inverter (qZSI) has attracted significant interest due to its single-stage buck-boost operation, continuous input current, reduced reliance on passive elements, and increased reliability. In this paper, the control strategy and implementation of the qZSI with battery assistance for standalone photovoltaic energy generation are discussed. To analyze the operational characteristics and design the control strategy of the qZSI, the system equations are linearized around the nominal operating point to develop a small-signal model, from which the direct current (DC) side and alternative current (AC) side transfer functions are derived and used as the basis for controller design. Using the proposed model, hybrid controllers are designed to control the shoot-through duty cycle, maintain DC link voltage stability, and battery charging to achieve stable power generation. Furthermore, the SPWM technique is applied to produce AC power with minimal harmonic content and higher efficiency. Application results show stable dynamic behavior, effective battery energy management, improved voltage regulation, and reduced harmonic distortion in the output waveform. The main contribution is a low-complexity coordinated PI and PR control framework for standalone battery-assisted qZSI operation, experimentally validated under DC- and AC-side disturbances without requiring an additional battery-side power-conversion stage. Full article

Single-photon avalanche diode (SPAD) arrays enable photon-starved applications, including time-of-flight imaging and stellar intensity interferometry. Their astronomical use remains scarcely explored, as the bottleneck is usually not detection but rather acquisition electronics for high-rate event streams. This work presents a modular, event-driven acquisition system for a 64 × 64 SPAD array within the La Palma Quantum Interferometer (LPQI) project, repurposing a LiDAR detector for multi-telescope interferometry. Two stages are used: a Raspberry Pi 5 with a custom board for validation, and an AMD Kria KR260 (Zynq UltraScale+ MPSoC) implementing the Address-Event Representation (AER) handshake in hardware at 100 MHz. The system streams AER events without per-event timestamping; sub-nanosecond time-tagging is left for a future stage based on the White Rabbit protocol. Optical bench tests confirmed spatial detection and localization of photons at a measured throughput of up to ≈124 keps under the highest illumination condition tested, and dark-count-rate characterization showed a rate below 10 Hz for most pixels (median: 1.68 Hz at 27.8 °C); raw per-pixel event-count maps further confirmed, for the first time on this array, the expected 2 × 2 spatial pattern of inter-pixel crosstalk from its shared-cathode pixel groups. The results demonstrate the feasibility of repurposing a LiDAR SPAD sensor and establish an acquisition-electronics baseline to aid the development of a timestamped, multi-telescope system for deployment on five telescopes of the Roque de los Muchachos Observatory. Full article

Background/Objectives: Chronic stress poses a major threat to animal health and welfare, yet current interventions are often invasive, poorly compliant, or lack long-term feasibility. This narrative review synthesizes preclinical mechanistic evidence from mammalian animal models to examine how structured auditory stimulation engages neurotrophic signaling. Structured light music—an auditory stimulus with defined acoustic parameters (e.g., tempo, intensity, and spectral frequency)—has emerged as a promising non-invasive strategy for promoting stress adaptation. However, the molecular mechanism of its effects remains unclear, and systematic analyses linking acoustic features to signaling pathways are scarce. Brain-derived neurotrophic factor (BDNF) and its high-affinity receptor tropomyosin receptor kinase B (TrkB) constitute a central signaling axis regulating neuroplasticity and stress adaptation, suggesting that this pathway may serve as a critical molecular interface linking auditory stimulation to stress-regulatory processes. Methods: In this review, we focus on structured light music stimuli with distinct acoustic characteristics and examine the molecular mechanisms by which they regulate neural plasticity through the BDNF/TrkB pathway. Results: Existing studies have shown that light music is associated with reversal of stress-induced down-regulation of BDNF/TrkB signaling in the hippocampus and prefrontal cortex. This effect is accompanied by enhanced neurogenesis, dendritic spine remodeling, and synaptic protein synthesis, which are linked to the coordinated activation of three downstream pathways: PI3K/Akt, MAPK/ERK and PLCγ. This cascade reaction further correlates with restoration of negative feedback inhibition of the hypothalamic–pituitary–adrenal axis in the hippocampus, reduces the level of glucocorticoids, and alleviates oxidative stress and inflammatory damage. Conclusions: This review proposes that the BDNF/TrkB pathway may serve as a key molecular basis for light music to regulate neural plasticity and achieve systemic anti-stress effects, and provides new ideas for animal welfare management and the formulation of standardized acoustic intervention strategies. Full article

In photovoltaic-based hybrid energy storage systems (PV–HESS), rapid power transients accelerate battery degradation, directly reducing the operating lifetime and sustainability of renewable power resources. To address this issue, the current study proposes an optimal coordinated framework for the simultaneous and coordinated tuning of battery and supercapacitor current-loop proportional–integral (PI) controllers. The proposed framework treats the four PI gains of the battery and supercapacitor controllers as a unified optimization problem, applying five metaheuristic algorithms: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Gazelle Optimization Algorithm (GOA), Artificial Protozoa Optimizer (APO), and White Shark Optimization (WSO). The optimization problem is directly coupled with a full nonlinear MATLAB 2022b/Simulink PV–HESS model, capturing the dynamic interactions among the PV array, bidirectional converters, DC-link capacitor, storage units, and load. A combined Integral of Time-weighted Absolute Error (ITAE) objective function is used to minimize current tracking errors, ensuring the supercapacitor absorbs fast power fluctuations while shielding the battery from high-frequency thermal and electrical stress. The controllers are evaluated across four operating scenarios involving steady irradiance shifts, rapid irradiance fluctuations, load disturbances, and a simultaneous irradiance drop from 1000 W/m² to 400 W/m² with a 33% load increase. The results confirm stable DC-link regulation and effective power sharing. Specifically, APO delivers superior performance in the high-stress scenario, GOA minimizes transient-error indices, and GA achieves the lowest DC-link voltage RMSE. These findings demonstrate that coordinated tuning effectively balances high-frequency dynamics, extending battery service life and enhancing the long-term operational sustainability of solar microgrid storage. Full article

BOOLE is a four-face educational platform integrating analog, combinational-logic, and sequential-logic activities with optional AI-assisted component identification and datasheet support. The system was developed through requirements translation, circuit simulation, two-layer PCB design, mechanical review, fabrication, assembly, functional verification, and iterative refinement. A Raspberry Pi 5, Camera Module 3 NoIR, and touchscreen support image capture and local interaction, while an Arduino Mega provides deterministic control of the physical learning faces. Segmented power energizes only the selected face and activity, and removable boards improve maintenance and fault isolation. Hardware demonstrations reproduced the intended voltage-divider, diode threshold/polarity, counter, and sequential-logic states. Ten one-versus-rest classifiers were fine-tuned from a pretrained ViT-Base model using 2000 original photographs, with 200 images for each of ten categories. The dataset was partitioned class-wise into mutually exclusive 80/10/10 training, validation, and final-test sets before augmentation, which was applied only to training data. Final-test accuracy ranged from 91.0% to 99.5%, with precision, recall, F1-score, specificity, balanced accuracy, and confusion matrices also evaluated. A 73-student pilot produced 89–96% positive (Yes) responses across six binary survey items, providing preliminary evidence of learner-perceived effectiveness, engagement, usability, and theory-to-practice support. Overall, BOOLE demonstrates a feasible, serviceable architecture for progressive electronics education. Full article

Sodium glucose cotransporter-2 inhibitors (SGLT2is) have rapidly evolved from glucose-lowering agents to multifaceted therapies with significant renoprotective and cardioprotective potential. Although originally developed to inhibit glucose reabsorption within the renal proximal tubule for the treatment of Type 2 diabetes mellitus (T2DM), growing evidence indicates that SGLT2is exert broad systemic actions extending beyond glycemic control. Among this drug class, dapagliflozin has emerged as a clinically important agent with pleiotropic effects involving renal hemodynamics, inflammatory signaling, mitochondrial function, fibrosis regulation, and cellular stress adaptation. This review outlines the historical progression from the discovery of phlorizin to the development of highly selective modern SGLT2 inhibitors while emphasizing mechanistic insights gained from experimental and clinical studies of dapagliflozin. In addition to the established effects on sodium–glucose transport, dapagliflozin modulates multiple epithelial transport proteins including NHE3, NaPi-2a, NCC, and NCX1, highlighting complex regulatory effects on sodium handling and tubular electrolyte transport. Emerging evidence further demonstrates that dapagliflozin suppresses inflammatory and profibrotic pathways involving YAP/TAZ, STAT1, TGF-β, NLRP3, and NF-KB signaling. Restoration of tubuloglomerular feedback, attenuation of oxidative stress, and preservation of mitochondrial function also appear to contribute substantially to the renoprotective actions of SGLT2 inhibition. Beyond the kidney, dapagliflozin and related SGLT2is exert cardioprotective effects through coordinated improvements in cardiac energetics, inflammatory regulation, and hemodynamic function. Emerging studies additionally suggest potential pulmonary benefits, including reductions in inflammatory signaling, pulmonary edema, and respiratory complications. Collectively, these findings support a shift in understanding SGLT2is from targeted metabolic therapies to broader regulators of cellular and organ function. Continued investigation into the glucose-independent mechanisms of dapagliflozin may reveal additional therapeutic applications across chronic metabolic, cardiovascular, and inflammatory diseases. Full article

The study seeks to develop a multifunctional germanium-enriched nanocomposite coating on titanium and to evaluate its ability to modulate early inflammatory responses while promoting osteogenic differentiation in a dental pulp stem cell (DPSC)-based regenerative model. A multifunctional Ti/Coating composed of nanohydroxyapatite (nHAp) particles, chitosan-oligolactate (ChOL), and germanium (Ge) was developed using a combined anodizing/anaphoretic electrodeposition approach. The Ti/Coating system exhibited good biocompatibility, as confirmed by microscopy, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and lactate dehydrogenase (LDH) assays, with cell viability consistently exceeding 90% and moderate LDH release across all time points. Annexin V/PI assay demonstrated a predominance of viable cells (>94%), while intracellular ROS analysis indicated moderate oxidative activity. Gene expression analysis revealed significant downregulation of pro-inflammatory markers (TNF-α, IL-1β, IL-6, COX-2, and MAPK), suggesting attenuation of inflammatory signalling. Flow cytometry further demonstrated reduced CD120b (TNFR2) expression, while intracellular TNF-α levels remained unchanged, indicating selective modulation at the receptor level. In addition, the Ti/Coating promoted osteogenic differentiation, as evidenced by enhanced mineralization, and upregulation of osteogenic genes (ALP, RUNX2, BMP2). Full article

Vision-based hand gesture recognition (HGR) systems are predominantly developed for frontal camera viewpoints, whereas smart-home cameras are often ceiling-mounted, creating a viewpoint-induced domain gap. To investigate this issue, we collected and manually annotated CeilGest, an 18-class ceiling-view hand gesture dataset comprising 156,282 annotated frames from 68 participants recorded in distinct domestic environments. We then systematically evaluated frontal-to-ceiling transfer using YOLO-based detectors trained on HaGRID and compared their performance with an in-domain CeilGest-trained model. On identical ceiling-view footage, the frontal-trained YOLOv8n produced approximately 24× more class-to-class misclassified frames than the in-domain model (486 vs. 20 across 27,000 frames); this large paired difference remained evident when temporal dependence within gesture holds was taken into account. The effect was strongly class-dependent, with AP decreasing by up to 5.5 percentage points for the worst-affected gesture, while the aggregate same-architecture mAP50 difference was 0.6 percentage points. Across five YOLOv8 variants evaluated on frontal HaGRID, mAP50 remained at 0.995, supporting selection of the lightweight YOLOv8n for edge deployment. The complete ceiling-view HGR pipeline was implemented on Raspberry Pi 5 using NCNN and Jetson Orin Nano using TensorRT. Mean inference latency was 74.69 ± 4.72 ms and 12.72 ± 0.12 ms, respectively. During a 10 min continuous Raspberry Pi 5 test, mean inference latency increased by 17.6% and junction temperature reached 90.8 °C with thermal throttling. Power consumption and INT8 inference were not evaluated. Overall, the results show that training–deployment viewpoint consistency is a major consideration for ceiling-mounted HGR and establish an in-domain supervised baseline relative to frontal-only training without domain adaptation. Full article

The coupling of power and natural gas infrastructures introduces gas-side constraints and cyberattack risks into load frequency control (LFC). This paper proposes an auxiliary Kalman filter (AKF)-based tube-based MPC (TMPC) framework for gas–electricity coupling systems under gas pressure false data injection attacks (FDIAs). A pressure-dependent gas turbine (GT) power limit is incorporated into the frequency control constraint, and an auxiliary pressure model is identified from attack-free data as a virtual pressure sensor. Residuals, normalized innovation squared statistics (NIS), and cumulative sum (CUSUM) statistics are used for attack detection, while compromised pressure measurements are reconstructed using the AKF estimates. Simulations on a two-area power system coupled with an 11-node gas network show that under attack-free operations, the integral absolute error (IAE) values of TMPC, conventional MPC, and PI control are 0.7040, 1.9626, and 2.9834 Hz·s, respectively. Thus, TMPC reduces the accumulated frequency deviation by approximately 64% and 76%, compared with conventional MPC and PI control, respectively. Under FDIAs, the IAE decreases from 1.1645 to 0.7039 Hz·s after AKF-based pressure reconstruction, corresponding to an approximately 40% reduction. Meanwhile, the mean absolute error (MAE) of gas pressure reconstruction decreases from 0.1714 to 0.0157 bar, corresponding to an approximately 91% reduction in pressure reconstruction error. Compared with the denoising autoencoder (DAE) and graph signal recovery approaches, the proposed method achieves the highest detection rate of 98.39%, effectively limiting FDIA propagation to GT constraints and frequency regulation. Full article

The study uses a case study (Parliament House, Ghana) to identify a sustainable energy pathway for public institutions in emerging economies, from technical and economic viewpoints, towards the net-zero agenda. Technically, the study uses GIS (Google Earth Pro, v7.3.7) mapping and Python (Jupyter notebook from Anaconda, v4.20) simulation to assess rooftop/carport solar PV–grid integration and explore green hydrogen and ammonia productions. It combines a GIS rooftop solar resources assessment with a forward/backward sweep hosting-capacity analysis and a cascaded economic comparison of grid, hydrogen (H₂), and ammonia (NH₃) to inform decisions about RE investment scenarios in Ghana. The economic assessment uses net present value (NPV), internal rate of return (IRR), profitability index (PI), discounted payback period (DPP), and levelized cost of energy (LCOE, LCOH, and LCOA). A 6.3 MW (10,569 MWh) solar electricity system is proposed to meet the 2.56 MW (7554 MWh) demand with 3014 MWh excess. Hydrogen and ammonia production stood at 60.3 tons and 343,579 kg from excess electricity, respectively. The facility’s CO₂ contribution in 25 years period with the grid supply is 160,539 tons, while with PV deployment, it can save 211,611 tons. A total of GHS 58,558,962 (GHS 36,306,556 for local demand and GHS 22,252,405 for grid sales), GHS 12,328,785, and GHS 43,805,636 are required to set up the solar PV, hydrogen, and ammonia plants, respectively. Results from 100% local consumption and grid sales scenarios indicate an NPV of GHS 106.91, an IRR of 75%, a payback period of 3 years, a profitability index of 3.1, and an LCOE of GHS 0.68. An NPV of GHS 84.57 million, IRR of 56%, PI of 3.8, DPP of 4 years, and LCOE of GHS 1.06/kWh were recorded for the grid sales. Hydrogen sales had a negative NPV of GHS 16.78 million, a PI of 0.7, and an LCOH of GHS 87.2 per kg. Similarly, a negative NPV of GHS 70.72 million, a PI of 0.27, and an LCOA of GHS 29,419.55 per ton were recorded for the ammonia sales. The Parliament House can save 106.91 million GHS over 25 years if it chooses to go solar after meeting its local requirements. Results from the Python simulation show a 5.6% reduction in bus voltage for the system without PV, while the configuration with PV injections saw a voltage increase of up to 11.4%. The system loss increased 113.3 kW in case 1 to 1659.2 kW in case 2. Solar-to-grid is the recommended pathway, while H2/NH3 are not competitive under present costs. The sensitivity analysis shows that changes in key input variables (CAPEX, electricity input cost, and selling price) affect the prospective H₂/NH₃ sales under current market conditions in Ghana. Therefore, policymakers should make conscious efforts to lower these parameters (CAPEX and electricity input cost) to boost green hydrogen and ammonia penetration in the transition agenda. A new law is required to encourage consumers to sell to the grid rather than rely on the current net metering scheme, which limits prosumers’ generation to 500 kW and forbids grid sales. Full article

Background: Obesity is a multifaceted metabolic disorder characterized by systemic disturbances, particularly impaired energy homeostasis, chronic low-grade inflammation, and mitochondrial dysfunction across the brain, gut, adipose tissue, and liver axes. Objectives: This review aims to examine the metabolic properties and molecular mechanisms of six key phytochemicals (berberine, resveratrol, catechins, capsaicin, thymoquinone, and phycocyanin) and the exercise-induced myokine irisin, and their roles in mitochondrial signaling and metabolic reprogramming. Sources of Evidence: A comprehensive literature search was conducted across major electronic databases, including PubMed, Web of Science, and Scopus, to identify relevant mechanistic, in vivo, and in vitro studies. Results: Both the selected phytochemicals and irisin act as multi-target regulators that modulate key signaling pathways, including AMPK, PI3K/Akt/mTOR, SIRT1, Nrf2, and PPARγ. These phytochemicals and irisin can drive cell- and tissue-specific metabolic reprogramming, promoting the browning of white adipocytes, suppressing de novo lipogenesis in hepatocytes, and enhancing fatty acid oxidation in skeletal myocytes. This synergistic metabolic reprogramming enhances thermogenesis and increases energy expenditure. Conclusions: Co-targeting redox signaling and metabolic pathways via phytochemicals and irisin offers a powerful strategy against obesity. This integrative framework restores multi-organ homeostasis, laying the groundwork for targeted metabolic therapies. Full article