Search Results (9,364)

The agricultural pest Drosophila suzukii exhibits a strong preference for feeding on fresh fruits, demonstrating high adaptability to sugary environments. Meanwhile, high sugar levels stimulate insulin secretion, thereby regulating the steady state of sugar metabolism. Understanding the mechanisms related to sugar metabolism in D. suzukii is crucial due to its adaptation to these specific environmental conditions. The insulin signaling pathway is an evolutionarily conserved phosphorylation cascade with significant roles in development and metabolism. We observed that the activation of the insulin signaling pathway inhibited FoxO activity and downregulated the expression of Pepck, thereby activating glycolysis and reducing glucose levels. By contrast, inhibiting insulin signaling increased the FoxO activity and upregulated the expression of Pepck, which activated gluconeogenesis and led to increased glucose levels. Our findings demonstrated the crucial role of the insulin signaling pathway in mediating glucose metabolism through the FoxO–Pepck axis, which supports the ecological adaptation of D. suzukii to high-sugar niches, thereby providing insights into its metabolic control and suggesting potential strategies for pest management. Elucidating these molecular processes is important for understanding metabolic regulation and ecological specialization in D. suzukii. Full article

Idiosyncratic drug-induced liver injury (iDILI) by flucloxacillin presents as both cholestatic and hepatocellular injury. Its mechanistic steps are explored in the present analysis as limited data exist on the cascade of events leading to iDILI in patients with an established diagnosis assessed for causality by the Roussel Uclaf Causality Assessment Method (RUCAM). Studies with human liver microsomes showed that flucloxacillin is a substrate of cytochrome P450 (CYP) with ist preferred isoforms CYP 3A4/3A7 that toxified flucloxacillin toward 5′-hydroxymethylflucloxacillin, which was cytotoxic to human biliary epithelial cell cultures, simulating human cholestatic injury. This provided evidence for a restricted role of the metabolic CYP-dependent hypothesis. In contrast, 5′-hydroxymethylflucloxacillin generated metabolically via CYP 3A4/3A7 was not cytotoxic to human hepatocytes due to missing genetic host features and a lack of non-parenchymal cells, including immune cells, which commonly surround the hepatocytes in the intact liver in abundance. This indicated a mechanistic gap regarding the clinical hepatocellular iDILI, now closed by additional studies and clinical evidence based on HLA B*57:01-positive patients with iDILI by flucloxacillin and a verified diagnosis by the RUCAM. Naïve T-cells from volunteers expressing HLA B*57:01 activated by flucloxacillin when the drug antigen was presented by dendritic cells provided the immunological basis for hepatocellular iDILI caused by flucloxacillin. HLA B*57:01-restricted activation of drug-specific T-cells caused covalent binding of flucloxacillin to albumin acting as a hapten. Following drug stimulation, T-cell clones expressing CCR4 and CCR9 migrated toward CCL17 and CCL25 and secreted interferon-γ and cytokines. In conclusion, cholestatic injury can be explained metabolically, while hepatocellular injury requires both metabolic and immune activation. Full article

Background: During the coronavirus disease (COVID)-19 pandemic several drugs were used to manage the patients mainly those with a severe phenotype. Potential drugs were used off-label and major concerns arose from their applicability to managing the health crisis highlighting the importance of clinical trials. In this context, we described the mechanisms of the three repurposed drugs [Ivermectin-antiparasitic drug, Chloroquine/Hydroxychloroquine-antimalarial drugs, and Azithromycin-antimicrobial drug]; and, based on this description, the study evaluated the clinical efficacy of those drugs published in clinical trials. The use of these drugs reflects the period of uncertainty that marked the beginning of the COVID-19 pandemic, which made them a possible treatment for COVID-19. Methods: In our review, we evaluated phase III randomized controlled clinical trials (RCTs) that analyzed the efficacy of these drugs published from the COVID-19 pandemic onset to 2023. We included eight RCTs published for Ivermectin, 11 RCTs for Chloroquine/Hydroxychloroquine, and three RCTs for Azithromycin. The research question (PICOT) accounted for P—hospitalized patients with confirmed or suspected COVID-19; I—use of oral or intravenous Ivermectin OR Chloroquine/Hydroxychloroquine OR Azithromycin; C—placebo or no placebo (standard of care); O—mortality OR hospitalization OR viral clearance OR need for mechanical ventilation OR clinical improvement; and T—phase III RCTs. Results: While studying these drugs’ respective mechanisms of action, the reasons for which they were thought to be useful became apparent and are as follows: Ivermectin binds to insulin-like growth factor and prevents nuclear transportation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), therefore preventing cell entrance, induces apoptosis, and osmotic cell death and disrupts viral replication. Chloroquine/Hydroxychloroquine blocks the movement of SARS-CoV-2 from early endosomes to lysosomes inside the cell, also, this drug blocks the binding between SARS-CoV-2 and Angiotensin-Converting Enzyme (ACE)-2 inhibiting the interaction between the virus spike proteins and the cell membrane and this drug can also inhibit SARS-CoV-2 viral replication causing, ultimately, the reduction in viral infection as well as the potential to progression for a higher severity phenotype culminating with a higher chance of death. Azithromycin exerts a down-regulating effect on the inflammatory cascade, attenuating the excessive production of cytokines and inducing phagocytic activity, and acts interfering with the viral replication cycle. Ivermectin, when compared to standard care or placebo, did not reduce the disease severity, need for mechanical ventilation, need for intensive care unit, or in-hospital mortality. Only one study demonstrated that Ivermectin may improve viral clearance compared to placebo. Individuals who received Chloroquine/Hydroxychloroquine did not present a lower incidence of death, improved clinical status, or higher chance of respiratory deterioration compared to those who received usual care or placebo. Also, some studies demonstrated that Chloroquine/Hydroxychloroquine resulted in worse outcomes and side-effects included severe ones. Adding Azithromycin to a standard of care did not result in clinical improvement in hospitalized COVID-19 participants. In brief, COVID-19 was one of the deadliest pandemics in modern human history. Due to the potential health catastrophe caused by SARS-CoV-2, a global effort was made to evaluate treatments for COVID-19 to attenuate its impact on the human species. Unfortunately, several countries prematurely justified the emergency use of drugs that showed only in vitro effects against SARS-CoV-2, with a dearth of evidence supporting efficacy in humans. In this context, we reviewed the mechanisms of several drugs proposed to treat COVID-19, including Ivermectin, Chloroquine/Hydroxychloroquine, and Azithromycin, as well as the phase III clinical trials that evaluated the efficacy of these drugs for treating patients with this respiratory disease. Conclusions: As the main finding, although Ivermectin, Chloroquine/Hydroxychloroquine, and Azithromycin might have mechanistic effects against SARS-CoV-2 infection, most phase III clinical trials observed no treatment benefit in patients with COVID-19, underscoring the need for robust phase III clinical trials. Full article

Aiming at the problems of high peak value fault current, fast rising speed, and being unable to ensure the reliability of the power supply in the non-fault zone in a multi-terminal DC system, a new cascade flexible current limiter and mechanical DC circuit breaker for medium- and high-voltage distribution networks are proposed. Firstly, the flexible current limiter is triggered by differential under-voltage protection to achieve the effect of interpole voltage clamping, suppressing the fault current and improving the dynamic recovery characteristics of the DC system after fault clearing. Secondly, according to the breaking speed of the DC circuit breaker, the action time of the current limiter can be set flexibly. The directional pilot protection signal of the circuit breaker is used to ensure the continuous action of the current limiter at the converter station side in the fault zone, until the circuit breaker acts to isolate the fault. The protection strategy can also avoid the blocking of the converter station and reduce the requirements for the breaking speed and breaking capacity of the circuit breaker. Finally, a four-terminal medium voltage distribution network model is built in MATLAB/SIMULINK, and the effect of the current limiter and the feasibility of the proposed protection strategy are verified by simulation. Full article

The analysis of complex system reliability is an area of growing interest, particularly given the diverse and intricate nature of the subsystems and components these systems encompass. Tackling the reliability of such multifaceted systems presents challenges, including component wear, multiple failure modes, the cascading effects of these failures, and the associated uncertainties, which require careful consideration. While traditional studies have examined these elements, the dynamic interplay of information between subsystems and the overarching system has only recently begun to draw focus. A notably understudied aspect is the reliability analysis of complex real-time systems that must adapt to evolving operational conditions. This paper proposes a novel methodology for assessing the reliability of complex real-time systems. This method integrates complex network theory, thus capturing the intricate operational characteristics of these systems, with adjustments to several key complex network parameters to define the nuances of communication within the network framework. To showcase the efficacy and adaptability of our approach, we present case studies on railway and maritime systems. For the railway system, our analysis spans various operational scenarios: from single train operations to simultaneous operations across multiple or different radio block center regions, accounting for node and edge failures. In maritime systems, the case studies employing the VHF data exchange system under operational scenarios are subject to network reliability analysis, successfully pinpointing critical vulnerabilities and modules of high importance. The findings of our research are promising, demonstrating that the proposed method not only accurately evaluates the overall reliability of complex systems but also identifies the pivotal weak points—be it modules or links—warranting attention for system enhancement. Full article

Medical imaging instrumentation design and construction is based on radiation sources and radiation detectors/sensors. This review focuses on the detectors and sensors of medical imaging systems. These systems are subdivided into various categories depending on their structure, the type of radiation they capture, how the radiation is measured, how the images are formed, and the medical goals they serve. Related to medical goals, detectors fall into two major areas: (i) anatomical imaging, which mainly concerns the techniques of diagnostic radiology, and (ii) functional-molecular imaging, which mainly concerns nuclear medicine. An important parameter in the evaluation of the detectors is the combination of the quality of the diagnostic result they offer and the burden of the patient with radiation dose. The latter has to be minimized; thus, the input signal (radiation photon flux) must be kept at low levels. For this reason, the detective quantum efficiency (DQE), expressing signal-to-noise ratio transfer through an imaging system, is of primary importance. In diagnostic radiology, image quality is better than in nuclear medicine; however, in most cases, the dose is higher. On the other hand, nuclear medicine focuses on the detection of functional findings and not on the accurate spatial determination of anatomical data. Detectors are integrated into projection or tomographic imaging systems and are based on the use of scintillators with optical sensors, photoconductors, or semiconductors. Analysis and modeling of such systems can be performed employing theoretical models developed in the framework of cascaded linear systems analysis (LCSA), as well as within the signal detection theory (SDT) and information theory. Full article

Existing antithrombotic drugs have side effects such as bleeding, and there is an urgent need to discover antithrombotic drugs with better efficacy and fewer side effects. In this study, a zebrafish thrombosis model was used to evaluate the antithrombotic activity and mechanism of Brevianamide F, a deep-sea natural product, with transcriptome sequencing analysis, RT-qPCR analysis, and molecular docking. The results revealed that Brevianamide F significantly attenuated the degree of platelet aggregation in the thrombus model zebrafish, leading to an increase in the number of circulating platelets, an augmentation in the return of blood to the heart, an elevated heart rate, and a significant restoration of caudal blood flow velocity. Transcriptome sequencing and RT-qPCR validation revealed that Brevianamide F may exert antithrombotic effects through the modulation of the MAPK signaling pathway and the coagulation cascade reaction. Molecular docking analysis further confirmed this result. This study provides a reference for the development of therapeutic drugs for thrombosis. Full article

Pansharpening refers to enhancing the spatial resolution of multispectral images through panchromatic images while preserving their spectral features. However, existing traditional methods or deep learning methods always have certain distortions in the spatial or spectral dimensions. This paper proposes a remote sensing spatial–spectral fusion method based on a multi-scale dual-stream convolutional neural network, which includes feature extraction, feature fusion, and image reconstruction modules for each scale. In terms of feature fusion, we propose a multi cascade module to better fuse image features. We also design a new loss function aim at enhancing the high degree of consistency between fused images and reference images in terms of spatial details and spectral information. To validate its effectiveness, we conduct thorough experimental analyses on two widely used remote sensing datasets: GeoEye-1 and Ikonos. Compared with the nine leading pansharpening techniques, the proposed method demonstrates superior performance in multiple key evaluation metrics. Full article

Objectives: This study examined the effect of a 4-week unsweetened cranberry beverage (CRAN) (317 mg polyphenols) versus placebo beverage (PLAC) ingestion (240 mL/day) on moderating exercise-induced changes in innate immunity. Methods: Participants included 25 male and female non-elite cyclists. A randomized, placebo-controlled, double-blind crossover design was used with two 4-week supplementation periods and a 2-week washout period. Supplementation periods were followed by an intensive 2.25 h cycling bout. Six blood samples were collected before and after supplementation (in an overnight fasted state) and at 0 h, 1.5 h, 3 h, and 24 h post-exercise. Stool and urine samples were collected pre- and post-supplementation. Outcome measures included serum creatine kinase, myoglobin, and cortisol, complete blood counts, plasma untargeted proteomics, plasma-targeted oxylipins, untargeted urine metabolomics, and stool microbiome composition via whole genome shotgun (WGS) sequencing. Results: Urine CRAN-linked metabolites increased significantly after supplementation, but no trial differences in alpha or beta microbiota diversity were found in the stool samples. The 2.25 h cycling bout caused significant increases in plasma arachidonic acid (ARA) and 53 oxylipins (FDR q-value < 0.05). The patterns of increase for ARA, four oxylipins generated from ARA-cytochrome P-450 (CYP) (5,6-, 8,9-, 11,12-, and 14,15-diHETrEs), two oxylipins from linoleic acid (LA) and CYP (9,10-DiHOME, 12,13-DiHOME), and two oxylipins generated from LA and lipoxygenase (LOX) (9-HODE, 13-HODE) were slightly but significantly higher for the CRAN versus PLAC trial (all interaction effects, p < 0.05). The untargeted proteomics analysis showed that two protein clusters differed significantly between the CRAN and PLAC trials, with CRAN-related elevations in proteins related to innate immune activation and reduced levels of proteins related to the regulation of the complement cascade, platelet activation, and binding and uptake of ligands by scavenger receptors. No trial differences were found for cortisol and muscle damage biomarkers. Conclusions: CRAN versus PLAC juice resulted in a significant increase in CRAN-related metabolites but no differences in the gut microbiome. CRAN supplementation was associated with a transient and modest but significant post-exercise elevation in selected oxylipins and proteins associated with the innate immune system. Full article

In the context of locomotive traction systems, the power electronic traction transformer (PETT) represents a pivotal component, fulfilling essential functions pertaining to electrical isolation and power control. The majority of existing PETT prototypes employ a combination of a cascade structure and an ISOP structure. The aforementioned scheme effectively reduces the voltage withstand level of the power devices on the input side, yet it also necessitates the utilisation of a greater number of power devices and passive components within the PETT. In order to further reduce the number of power devices used, this paper proposes a new cascaded PETT design. The proposed PETT will adopt a scheme combining a cascade structure and a hardware circuit multiplexing. This paper first analyses the operation principle of the new circuit under non-single frequency PWM control. It then derives the design equations for some hardware parameters and control circuits. Finally, it verifies the effectiveness of the proposed PETT through simulation analysis. Full article

Ubiquitination is one of the most important post-translational modifications in eukaryotes. The ubiquitination cascade includes ubiquitin-activating enzymes (E1), ubiquitin-conjugating enzymes (E2), and ubiquitin ligases (E3). The E3 ligases, responsible for substrate recognition, are the most abundant and varied proteins in the cascade and the most studied. SKP1-CUL1-F-Box (SCF)-type E3 ubiquitin ligases are multi-subunit RING (Really Interesting New Gene) E3 ubiquitin ligases, composed of CUL1 (Cullin 1), RBX1 (RING BOX 1), SKP1 (S-phase Kinase-associated Protein 1), and F-box proteins. In vitro ubiquitination assays, used for studying the specific recognition of substrate proteins by E3 ubiquitin ligases, require the purification of all components involved in the cascade, and for assays with SCF-type E3 ligases, additional proteins (several SCF complex subunits). Here, the Duet expression system was used to co-express E1, E2, ubiquitin, ubiquitylation target (substrate), and the four subunits of a SCF-type E3 ligase in E. coli. When these proteins co-exist in bacterial cells, ubiquitination occurs and can be detected by Western Blot. The effectiveness of this bacterial system for detecting ubiquitination cascade activity was demonstrated by replicating both AtSCF^TIR1-mediated and human SCF^FBXO28-mediated ubiquitylation in bacteria. This system provides a basic but adaptable platform for the study of SCF-type E3 ubiquitin ligases. Full article

Non-small cell lung cancer (NSCLC), representing 85% of lung cancer cases, is characterized by its heterogeneity and progression through distinct stages. This study applied Weighted Gene Co-expression Network Analysis (WGCNA) to explore the molecular mechanisms of NSCLC and identify potential therapeutic targets. Gene expression data from the GEO database were analyzed across four NSCLC stages (NSCLC1, NSCLC2, NSCLC3, and NSCLC4), with the NSCLC2 dataset selected as the reference for module preservation analysis. WGCNA identified eight highly preserved modules—Cyan, Yellow, Red, Dark Turquoise, Turquoise, White, Purple, and Royal Blue—across datasets, which were enriched in key pathways such as “Cell cycle” and “Pathways in cancer”, involving processes like cell division and inflammatory responses. Hub genes, including PLK1, CDK1, and EGFR, emerged as critical regulators of tumor proliferation and immune responses. Estrogen receptor ESR1 was also highlighted, correlating with improved survival outcomes, suggesting its potential as a prognostic marker. Signature-based drug repurposing analysis identified promising therapeutic candidates, including GW-5074, which inhibits RAF and disrupts the EGFR–RAS–RAF–MEK–ERK signaling cascade, and olomoucine, a CDK1 inhibitor. Additional candidates like pinocembrin, which reduces NSCLC cell invasion by modulating epithelial-mesenchymal transition, and citalopram, an SSRI with anti-carcinogenic properties, were also identified. These findings provide valuable insights into the molecular underpinnings of NSCLC and suggest new directions for therapeutic strategies through drug repurposing. Full article

Star anise, a widely popular spice, benefits from classification that enhances its economic value. In response to the low identification efficiency and accuracy of star anise varieties in the market, as well as the scarcity of related research, this study proposes an efficient identification method based on non-similarity augmentation and a lightweight cascaded neural network. Specifically, this approach utilizes a Siamese enhanced data network and a front-end SRGAN network to address sample imbalance and the challenge of identifying blurred images. The YOLOv8 model is further lightweight to reduce memory usage and increase detection speed, followed by optimization of the weight parameters through an extended training strategy. Additionally, a diversified fusion dataset of star anise, incorporating open data, was constructed to further validate the feasibility and effectiveness of this method. Testing showed that the SA-SRYOLOv8 detection model achieved an average detection precision (mAP) of 96.37%, with a detection speed of 146 FPS. Ablation experiment results showed that compared to the original YOLOv8 and the improved YOLOv8, the cascade model’s mAP increased by 0.09 to 0.81 percentage points. Additionally, when compared to mainstream detection models such as SSD, Fast R-CNN, YOLOv3, YOLOv5, YOLOX, and YOLOv7, the cascade model’s mAP increased by 1.81 to 19.7 percentage points. Furthermore, the model was significantly lighter, at only about 7.4% of the weight of YOLOv3, and operated at twice the speed of YOLOv7. Visualization results demonstrated that the cascade model accurately detected multiple star anise varieties across different scenarios, achieving high-precision detection targets. The model proposed in this study can provide new theoretical frameworks and ideas for constructing real-time star anise detection systems, offering new technological applications for smart agriculture. Full article

The increasing frequency of urban flooding, driven by global climate change, poses significant threats to the safety and resilience of urban rail transit systems. This study systematically examines the cascading failure processes and resilience of these networks under flood conditions, with a specific focus on the Shanghai Metro. A comprehensive resilience evaluation model was developed by integrating geographic information, static network characteristics, and dynamic passenger flow indicators. This study employs an improved Coupled Map Lattice (CML) model to simulate cascading failures by considering the coupling effects of station centrality, geographic elevation, and passenger flow dynamics. The results indicate that stations with higher degrees of centrality are more likely to trigger rapid cascading failures across the network. However, incorporating dynamic passenger flow and geographic elevation data helps mitigate these effects, emphasizing the need for multi-dimensional resilience strategies. The findings provide valuable insights for urban transit management, offering a scientific foundation for developing targeted disaster response strategies to enhance network resilience against floods. This study advances our understanding of the vulnerability of urban rail transit systems and offers practical guidance for improving disaster preparedness in urban transportation infrastructure. Full article

The Mar Menor, Europe’s largest saline lagoon, has experienced significant eutrophication. The concentration of chlorophyll-a (Chl-a) in the water is used as a critical indicator of this eutrophication process and can alert us to possible ecosystemic changes such as a massive fish die-off. The main objective of this paper is to predict chlorophyll-a concentration using various time series models. Among them, multivariate models such as short-term memory networks (LSTM) and, in particular, the autoregressive integrated moving average model with eXogenous variables (ARIMAX) demonstrated superior performance. These models incorporate multiple predictors, such as humidity, water temperature, conductivity and turbidity, thus capturing the complex interactions that affect Chl-a levels. Despite their effectiveness, these multivariate models introduce cascading errors due to the uncertainty inherent in the exogenous inputs. Consequently, the application of univariate models—such as Prophet, Triple Exponential Smoothing and ARIMA—are also studied for their relative robustness to error propagation. Full article