Search Results (2,454)

Single nucleotide polymorphism (SNP) involves plenty of genetic disorders in organisms that can be passed down to the next generation or cause the stimulant signal that leads to early mortality in infants, especially within humankind. In medical field, real-time polymerase chain reaction (RT-PCR) is the most popular method for disease diagnosis. The investigation of genetic maps for the prediction of inherited illnesses needs the collaboration of sequencing technique and genome analysis. Although these methods are popular now, the cost for each test is quite high. Moreover, there is the requirement of extra machines and skillful technician or specialist level. Among these popular methods, the allele-specific polymerase chain reaction (AS-PCR), allele-specific loop isothermal mediated amplification (AS-LAMP), and allele-specific recombinase polymerase amplification (AS-RPA) are brought up for screening the nucleotide differences in the genetic sequence which will be noticed in this review as their availability, novelty, and potential for quick distinguishing of disease caused by SNP. Point-of-care testing (POCT) is a system built in a portable size but can perform the entire process of SNP recognition. Along with that, the POCT is intersected with the mentioned amplification methods and the genetic material preparation steps to become a united framework for higher efficiency and accuracy and lower cost. According to that, this review will focus on three common amplification techniques and their combination with POCT in the upstream and downstream process to genotype SNP related to human diseases. Full article

Background: The accurate and rapid genotyping of ABO (chromosome 9q34.2) blood types is critical for clinical diagnostics and transfusion medicine, particularly in scenarios where serological methods yield uncertain results, such as in neonatal testing or with rare ABO subtypes. Methods: This study describes a loop-mediated isothermal amplification (LAMP)-based method for ABO genotyping that offers a faster and more cost-effective alternative to conventional PCR-based techniques. Results: The method targets four key single nucleotide polymorphisms (SNPs) at positions 261, 297, 703, and 930, allowing for the differentiation of common A, B, and O blood types, as well as the rare AB subtype B(A)01. The detection of the B(A)01 subtype is clinically important for preventing transfusion mismatches where serology may be inconclusive. Operating at a constant temperature, the assay can be completed in under an hour without the need for a thermocycler, offering significant time and cost benefits over qPCR. The method demonstrated high specificity, demonstrating detection down to 10 copies across all assays. When validated against a gold-standard method on clinical blood samples, the LAMP assay showed high accuracy (95% C value calculated via binomial exact method): 97.4% for type O, 98.7% for type A, 98.7% for type B, and 100% for the B(A)01 subtype. To enhance usability for point-of-care applications, freeze-dried reagents were developed that permit direct loading of lysed blood samples while maintaining high performance. Conclusions: This simplified and robust format positions the LAMP assay as a promising tool for rapid and reliable ABO genotyping in diverse clinical settings. Full article

The increasing prevalence of common cold viruses and bacteria in daily life has heightened interest in sterilization lamp technologies. Compared with traditional mercury-based ultraviolet (UV) lamps, modern UV lamps offer advantages including extended operational lifespan, high energy efficiency, compact form factor, and the absence of hazardous materials, rendering them both safer and environmentally sustainable. In particular, UV-C LED lamps, which emit at short wavelengths, are capable of disrupting the molecular structure of DNA or RNA in microbial cells, thereby inhibiting cellular replication and achieving effective disinfection and sterilization. Conventional UV-C LED sterilization lamp driver circuits frequently employ a two-stage architecture, which requires a large number of components, occupies substantial physical space, and exhibits reduced efficiency due to multiple stages of power conversion. To address these limitations, this paper proposes a UV-C LED sterilization lamp driver circuit for an AC voltage supply, employing boundary conduction mode (BCM) control with integrated power factor correction (PFC). The proposed single-stage, single-switch topology combines a buck PFC converter and a flyback converter while recovering transformer leakage energy to further improve efficiency. Compared with conventional two-stage designs, the proposed circuit reduces the number of power switches and components, thereby lowering manufacturing cost and enhancing overall energy conversion efficiency. The operating principles of the proposed driver circuit are analyzed, and a prototype is developed for a 110 V AC input with an output specification of 10.8 W (90 V/0.12 A). Experimental results demonstrate that the prototype achieves an efficiency exceeding 92%, a power factor of 0.91, an output voltage ripple of 1.298%, and an output current ripple of 4.44%. Full article

Grain amaranths are recalcitrant to conventional in vitro plant regeneration by organogenesis de novo or through somatic embryogenesis. Consequently, floral organogenesis by these methods, representing the culminating developmental point in angiosperms, is rarely achieved. In the present study, the manipulation of in vitro flowering was explored as part of a strategy designed to overcome grain amaranth’s regeneration recalcitrance. It led to an efficient and reproducible in vitro protocol in which half-longitudinally dissected zygotic embryos generated fully developed Amaranthus hypochondriacus (Ah) plants. The use of high-irradiance illumination with LED lamps with a 3:1 red–blue irradiance ratio was a critical factor, leading to a 70% rate of early flowering events under flowering-inhibiting long-day photoperiod conditions. Contrariwise, no flowering was induced under LED white lights. All in vitro flowering Ah plants yielded viable seeds. To understand the basic molecular mechanisms of the phenomenon observed, gene expression patterns and principal component analysis of key flowering-related genes were analyzed after cultivation in vitro for 4, 8, and 12 weeks under both lighting regimes. These coded for photoreceptors, photomorphogenetic regulators, embryogenic modulators, and flowering activators/repressors. The results highlighted the upregulation of key flowering-regulatory genes, including CONSTANS, FLOWERING LOCUS T, and LEAFY, together with the downregulation of the floral repressor TERMINAL FLOWER1. Ribosome biogenesis- and seed-development-related genes were also differentially expressed, supporting a key role in this process for protein synthesis and embryogenesis. A model is proposed to explain how this light-regulated molecular framework enables in vitro flowering and seed production in Ah plants kept under long-day photoperiods. Full article

Canada goldenrod (Solidago canadensis L.), a short-day plant commonly cultivated as a cut flower, depends on proper lighting management to obtain long stems and higher commercial value. Thus, this study aimed to determine the effect of modifying the light spectrum through the installation of light-emitting diodes (LEDs) and the use of colored shade nets on the production and quality of Canada goldenrod stems. The treatments used were colored shade nets and different LED lighting treatments. Production per plant and productivity per square meter were determined. Twenty stems were selected and evaluated for: stem length; inflorescence length and width; number of floral ramets per inflorescence; number of leaves; stem base diameter (mm); and fresh stem biomass (g). Canada goldenrod plants require an extension of the light period with artificial lighting to produce higher-quality stems, regardless of whether the bulbs emit red or white light. The use of nets with 50% red and white shading promoted higher production and elongation of Canada goldenrod stems, with a production that reached up to 4.2 floral stems per plant and 100.3 floral stems per square meter using the red shade net and white LED. These floral stems were of high commercial standard, with a length of up to 81.35 cm with the red shade net and red LED, and were 31 cm in diameter for the inflorescences, approximately, under black or white shade nets and white or red LEDs. More robust floral stems with greater biomass were observed using any shade net color and LED lamps. Full article

Extracellular vesicles (EVs) from mesenchymal stem cells hold therapeutic promise for inflammatory and degenerative diseases; however, limited delivery and targeting capabilities hinder their clinical use. In this study, we sought to enhance the anti-inflammatory and chondroprotective effects of EVs through CAP-LAMP2b (chondrocyte affinity peptide fused to an EV membrane protein) engineering and ADAMTS4 gene editing hybrid vesicle formation. Human umbilical cord MSCs (hUCMSCs) were characterized via morphology, immunophenotyping, and trilineage differentiation. EVs from control and CAP-LAMP2b-transfected hUCMSCs were fused with liposomes carrying CRISPR-Cas9 ADAMTS4 gRNA. DiI-labeled EV uptake was assessed via fluorescence imaging. CAP-LAMP2b was expressed in hUCMSCs and their EVs. EVs exhibited the expected size (~120 nm), morphology, and exosomal markers (CD9, CD63, CD81, HSP70). CAP-modified hybrid EVs significantly enhanced chondrocyte uptake compared to control EVs and liposomes. IL-1β increased ADAMTS4 expression, whereas CAP-LAMP2b-ADAMTS4 EVs, particularly clone SG3, reversed these effects by reducing ADAMTS4 and restoring aggrecan. Western blotting confirmed suppressed ADAMTS4 and elevated aggrecan protein. CAP-LAMP2b-ADAMTS4 EVs, therefore, showed superior uptake and therapeutic efficacy in inflamed chondrocytes, attenuating inflammatory gene expression and preserving matrix integrity. These results support engineered EVs as a promising cell-free approach for cartilage repair and osteoarthritis treatment. Full article

Artificial light at night (ALAN) is now considered as a driver of evolution, possibly harmful to biodiversity, which constitutes a threat to the terrestrial and marine environment, and as such falls under Sustainable Development Goals (SDGs) 14 and 15. One way of mitigating its impact on the environment is to select an environment-friendly light spectrum, which is made more easily with current LED technologies. In this paper, we propose to adapt the spectrum of the lamps to that of the immediate environment. It makes it possible not to disturb the light environment of animals and plants at night and during the twilight period, at least from a spectral point of view, while ensuring the usual functions of lighting for humans. Apart from its own merit, the proposed concept may also contribute to SDG 13 by saving energy compared to current approaches based on long wavelengths light. The proposed idea may be implemented in various ways and deserves to be discussed in the lighting community and tested in real settings. Full article

While insulator integrity is critical for power grid stability, prevailing detection algorithms often rely on computationally intensive models incompatible with resource-constrained edge devices like unmanned aerial vehicles (UAVs). Key limitations—including redundant feature interference, inadequate sensitivity to small targets, rigid fusion weights, and sample imbalance—further restrict practical deployment. To address those problems, this study presents a lightweight insulator anomaly detection algorithm, LAI-YOLO. First, the SqueezeGate-C3k2 (SG-C3k2) module, equipped with an adaptive gating mechanism, is incorporated into the Backbone network to reduce redundant information during feature extraction. Secondly, we propose a High-level Screening–Feature Weighted Feature Pyramid Network (HS-WFPN) to replace FPN+PAN via selective weighted feature fusion, enabling dynamic cross-scale integration and enhanced small-target detection. Then, a reconstructed lightweight detection head coupled with Slide Weighted Focaler Loss (SWFocalerLoss) mitigates performance degradation from sample imbalance. Ultimately, the layer adaptation for the magnitude-based pruning (LAMP) technique slashes computational demands without sacrificing detection prowess. Experimental results on our insulator anomaly dataset demonstrate that the improved model achieves higher efficacy in identifying insulator anomalies, with mAP@0.5 increasing from 88.2% to 91.1%, while model parameters and FLOPs are diminished to 45.7% and 53.9% of the baseline, respectively. This efficiency facilitates the deployment of edge devices and highlights the method’s considerable application potential. Full article

Welsh onion (Allium fistulosum L.) is a globally significant culinary vegetable with extensive cultivation and high application value. In China, Welsh onion is vulnerable to drought and strong-light stress in summer production, resulting in growth inhibition and quality decline. This study utilized LED-intelligent spectral-customized lamps to simulate high-light stress and a 10% PEG-6000 Hoagland solution to simulate drought stress. The effects of different stress treatments on the nutritional quality, volatile compounds, and mineral element composition of the edible portions were systematically analyzed. The results demonstrated that drought stress significantly promoted the accumulation of alcoholic compounds in leaf tissues while reducing the content of sulfur-containing compounds. High-light stress markedly increased the levels of hydrocarbon compounds in leaves. Sulfur-containing compounds in leaf tissues were predominantly disulfides, but under combined drought and high-light stress, their content decreased, while the proportion of trisulfides significantly increased. Volatile compounds in pseudostems were primarily composed of sulfur-containing and aldehyde compounds, yet their levels markedly declined under combined stress. Additionally, combined stress led to reductions in pyruvic acid, soluble sugars, and soluble protein content in the edible portions, while the crude fiber content increased, thereby significantly impairing nutritional quality. This study provides a scientific basis for understanding the abiotic stress response mechanisms of Welsh onion and offers valuable insights for cultivation management and quality regulation. Full article

Aspergillosis includes a variety of diseases caused by species of the genus Aspergillus, ranging from non-invasive allergic diseases to chronic, invasive pulmonary infections, which are potentially fatal in immunocompromised hosts. Therefore, there is an urgent need for new diagnostic tools and the optimization of existing tests to improve patient care. This work reviews the most commonly used molecular methods for the diagnosis of aspergillosis from clinical samples, emphasizing their advantages. These methods included HTS, NTS, ISH, microarrays, PCR-RFLP, LAMP, and PCR in various modalities (qPCR, multiplex PCR, nested PCR, RT-PCR, endpoint PCR, U-dHRM, and ddPCR). The review showed that the most commonly used methods for diagnosing aspergillosis are NGS and PCR in their different modalities; however, each method has advantages and disadvantages. qPCR is the method that has demonstrated the greatest sensitivity and specificity on clinical samples (such as blood, serum, bronchoalveolar lavage [BAL], tissue, or sputum), since it detects specific sequences, and the validation of this method shows greater progress in achieving this objective. Likewise, NGS showed that BAL is the most suitable sample, with a higher fungal load than sputum or blood. On the other hand, NGS is not a targeted technique, since it sequences all the genetic material present. Additionally, the sensitivity for detecting pathogens decreases when clinical samples are used due to the high background of nucleic acids present in the human host. Full article

Tracing the source of air pollution presents a significant challenge, especially in densely populated urban areas, because of the unpredictable and complex nature of aerodynamics. To address this issue, intelligent lamp posts have been developed with smart sensors and edge computing capabilities. These lamp posts serve as nodes in the EIPA (Edge Intelligent Perception Agent) network within urban campuses. These lamp posts aim to track air pollutants by employing a tracking algorithm that utilizes big data learning and Gaussian diffusion models. This approach focuses on monitoring the quality of urban air and identifying pollution sources, rather than relying solely on traditional CFD simulations for air pollution dispersion. The algorithm comprises three primary components: (1) the Federated Learning framework built on the EIPA system; (2) the LSTM model implemented on the edge nodes of the EIPA system; and (3) a genetic algorithm utilized for optimizing the model parameters. By using CFD simulations in a simulated city park, training data on air dynamic movements is gathered. The usefulness of the method for tracing air pollutants based on federated learning of edge intelligent perception agents is demonstrated by the outcomes of algorithm training. Experimental results show that, compared to the traditional genetic algorithm (GA) and LSTM + genetic algorithm, the proposed FL + LSTM + GA method significantly improves the pollution source positioning accuracy to 99.5% and reduces the average absolute error (MAE) of Gaussian model parameter estimation to 0.20. Full article

This study presents the development and evaluation of an automated ultraviolet-C irradiation system for maize seed treatment, emphasizing disinfection performance, environmental control, and vision-based monitoring. The system features dual 8-watt ultraviolet-C lamps, sensors for temperature and humidity, and an air extraction unit to regulate the microclimate of the chamber. Without air extraction, radiation stabilized within one minute, with internal temperatures increasing by 5.1 °C and humidity decreasing by 13.26% over 10 min. When activated, the extractor reduced heat build-up by 1.4 °C, minimized humidity fluctuations (4.6%), and removed odors, although it also attenuated the intensity of ultraviolet-C by up to 19.59%. A 10 min ultraviolet-C treatment significantly reduced the fungal infestation in maize seeds by 23.5–26.25% under both extraction conditions. Thermal imaging confirmed localized heating on seed surfaces, which stressed the importance of temperature regulation during exposure. Notable color changes ($\Delta E>2.3$) in treated seeds suggested radiation-induced pigment degradation. Ultraviolet-C intensity mapping revealed spatial non-uniformity, with measurements limited to a central axis, indicating the need for comprehensive spatial analysis. The integrated computer vision system successfully detected seed contours and color changes under high-contrast conditions, but underperformed under low-light or uneven illumination. These limitations highlight the need for improved image processing and consistent lighting to ensure accurate monitoring. Overall, the chamber shows strong potential as a non-chemical seed disinfection tool. Future research will focus on improving radiation uniformity, assessing effects on germination and plant growth, and advancing system calibration, safety mechanisms, and remote control capabilities. Full article

We have studied the effect of BITh molecules on the work functions of Ag and Au, with and without quartz lamp illumination. Silver and gold films coated with BITh molecules were fabricated and studied in reflection and Kelvin Probe experiments. The deposition of BITh films on Ag and Au reduced their work functions (in agreement with our recent study, wherein a similar reduction was caused by the deposition of a PMMA polymer). Illumination of the BITh-coated samples with a quartz lamp caused reductions in work functions by several tens of meV, which (almost) returned to their original values when the light was turned off. The characteristic time of this process (~15 min) was much shorter than that of photopolymerization (~180 min), suggesting that these two phenomena are nearly independent of each other. The effects of the Au substrates were qualitatively similar to those of the Ag substrates. Our findings pave the way to fundamental studies and applications of light–matter interactions. Full article

In the event of power outages caused by natural disasters, accidents, or other emergencies, outdoor emergency lighting systems play a critical role in providing illumination to maintain spatial orientation, facilitate evacuation procedures, and help individuals avoid hazardous areas or locate safe shelters. Compared to traditional lighting technologies, LED-based outdoor emergency lighting offers several advantages, including compact size, long operational lifespan, low energy consumption, high safety, resistance to breakage, and the absence of chemical residue or pollution. These characteristics align with contemporary trends in environmental sustainability and energy efficiency. This study proposes a novel LED driver circuit architecture for outdoor emergency lighting applications. The primary circuit topology is based on an improved buck-boost converter integrated with a flyback converter, forming a hybrid buck-boost-flyback configuration. The proposed circuit is capable of recycling the energy stored in the transformer’s leakage inductance, thereby enhancing overall power conversion efficiency. A 12 W (20 V/0.6 A) prototype LED driver circuit was designed and implemented to validate the performance of the proposed system. Experimental measurements, including waveform analysis and efficiency evaluation, demonstrate that the driver circuit achieves a high efficiency exceeding 91%. These results confirm the practical feasibility and effectiveness of the proposed electronic driver for LED-based outdoor emergency lighting applications. Full article

Complex marine infrared images, which suffer from background interference, blurred features, and indistinct contours, hamper detection accuracy. Meanwhile, the limited computing power, storage, and energy of maritime devices require target detection models suitable for real-time detection. To address these issues, we propose DSEE-YOLO (Dynamic Ship Edge-Enhanced YOLO), an efficient lightweight infrared ship detection algorithm. It integrates three innovative modules with pruning and self-distillation: the C3k2_MultiScaleEdgeFusion module replaces the original bottleneck with a MultiEdgeFusion structure to boost edge feature expression; the lightweight DS_ADown module uses DSConv (depthwise separable convolution) to reduce parameters while preserving feature capability; and the DyTaskHead dynamically aligns classification and localization features through task decomposition. Redundant structures are pruned via LAMP (Layer-Adaptive Sparsity for the Magnitude-Based Pruning), and performance is optimized via BCKD (Bridging Cross-Task Protocol Inconsistency for Knowledge Distillation) self-distillation, yielding a lightweight, efficient model. Experimental results show the DSEE-YOLO outperforms YOLOv11n when applied to our self-constructed IRShip dataset by reducing parameters by 42.3% and model size from 10.1 MB to 3.5 MB while increasing mAP@0.50 by 2.8%, mAP@0.50:0.95 by 3.8%, precision by 2.3%, and recall by 3.0%. These results validate its high-precision detection capability and lightweight advantages in complex infrared scenarios, offering an efficient solution for real-time maritime infrared ship monitoring. Full article