Search Results (11,211)

Heavy metal contamination is a serious environmental problem worldwide, with substantial negative ecological and economic effects. Serine hydroxymethyltransferase (SHMT) is a key metabolic and photorespiratory enzyme in plant cells, and it is also involved in stress responses. In this study, LcSHMT4 was isolated from sheepgrass (Leymus chinensis (Trin.) Tzvel) after transcriptome sequence analysis. The transcript levels of LcSHMT4 in sheepgrass seedlings increased under Cd and Mn stresses, and subcellular localization analysis in tobacco leaves revealed that its encoded protein localizes at the mitochondria. Transgenic yeast and rice lines overexpressing LcSHMT4 showed increased tolerance to Cd and Mn, compared with that of their controls. In addition, compared with the control, transgenic rice overexpressing LcSHMT4 accumulated more Cd and Mn in brown rice grains. The transcript levels of genes encoding Cd or Mn transporters were increased in the LcSHMT4-overexpressing transgenic rice lines. We speculate that LcSHMT4 may enhance Cd and Mn tolerance by increasing the activities of antioxidant enzymes and the glutathione content and increase heavy metal accumulation by inducing the expression of genes encoding transporters. These results highlight useful genetic resources and provide a theoretical basis for further research on heavy metal tolerance and the phytoremediation of heavy-metal-contaminated soil. Full article

The ε4 allele of the apolipoprotein E (APOE) gene strongly increases Alzheimer’s disease (AD) risk, though its molecular mechanisms remain unclear. AD-associated genetic signals also extend to neighboring genes TOMM40 and APOC1, suggesting a complex cis-regulatory landscape. To investigate chromatin architecture and its impact on gene regulation across this region, we performed chromosome conformation capture in human cell lines and postmortem brain tissues, consistently identifying TOMM40–APOE and APOE–APOC1 interactions. We further developed a digital PCR assay to quantify APOE–APOC1 interaction strength and measured APOC1 mRNA via RT-qPCR. Enhanced chromatin interaction correlated with elevated APOC1 transcription in AD specimens. Genotypic analysis showed that ε3/ε4 carriers had strong chromatin interaction and transcriptional activation, whereas ε4/ε4 homozygotes exhibited minimal chromatin remodeling despite similar APOC1 expression, suggesting a decoupling of chromatin architecture and transcriptional output. These findings underscore the interplay of AD status, APOE genotype, and locus-specific chromatin dynamics in disease susceptibility. Integration of 3D genome topology with transcriptomic profiling offers a framework to study APOE-related disorders and supports broader application across neurodegenerative loci for genotype-guided therapy development. Full article

Jasmonate-ZIM domain (JAZ) proteins act as repressors in the jasmonic acid (JA) signaling pathway and also function as plant-specific proteins participating in plant growth and development, stress response, and defense. In our study, a total of 25 JAZ genes were identified in B. rapa based on their conserved domains. First, the primary characteristics were surveyed, including the lengths of the CDS and proteins, molecular weights, and isoelectric points. Next, a phylogenetic tree of JAZ proteins among B. rapa, A. thaliana, O. sativa, B. oleracea, and B. napus was constructed, which revealed that these proteins cluster into four groups based on sequence homology rather than by species. Synteny analysis of JAZ genes among these species demonstrated that the highest number of collinear pairs was found between B. rapa and B. napus. Most BrJAZ genes were highly expressed in root, stem, and leaf. Moreover, the expression levels of BrJAZ1a and BrJAZ6b were induced by drought, high salt, black rot, and MeJA. Over-expressed these genes in A. thaliana lines enhanced their tolerance to drought and high salt stress, which was associated with higher enzymatic activities of SOD and POD. Both BrJAZ1a-GFP and BrJAZ6b-GFP were localized in the nucleus. Full article

In complex industrial environments, surveillance videos often exhibit large parallax, low illumination, low texture, and low overlap rate, making it difficult to extract reliable image feature points and consequently leading to video suboptimal stitching performance. To address these challenges, this study proposes a real-time panoramic surveillance video stitching method specifically designed for complex industrial scenarios. In the image registration stage, the Efficient Channel Attention (ECA) and Channel Attention (CA) modules are integrated with ResNet to enhance the feature extraction layers of the UDIS algorithm, thereby improving feature extraction and matching accuracy. A loss function incorporating similarity loss $L_{sim}$ and smoothness loss $L_{smooth}$ is designed to optimize registration errors. In the image fusion stage, gradient terms and motion terms are introduced for improving the energy function of the optimal seam line, enabling the optimal seam line to avoid moving objects in overlapping regions and thus achieve video stitching. Experimental validation is conducted by comparing the proposed image registration method with SIFT + RANSAC, UDIS, UDIS++, and NIS, and the proposed image fusion method with weighted average fusion, dynamic programming, and graph cut. The results show that, in image registration experiments, the proposed method achieves RMSE, PSNR, and SSIM values of 1.965, 25.338, and 0.8366, respectively. In image fusion experiments, the seam transition is smoother and effectively avoids moving objects, significantly improving the visual quality of the stitched videos. Moreover, the real-time stitching frame rate reaches 23 fps, meeting the real-time requirements of industrial surveillance applications. Full article

With the advancement of welding technology, the demand for 70S-6 welding wire steel has steadily increased in industries such as construction, automotive, pressure vessels, and line pipe manufacturing. To optimize the production process of the target material, this study utilized the finite-element software ABAQUS to numerically simulate the multi-pass finish rolling process of 70S-6 welding wire steel. The study investigates the effects of the key rolling parameters—pass distribution (8/10/12 passes), finish rolling temperature (860/880/900 °C), and rolling speed (0.5 Vp/1.0 Vp/1.5 Vp, here Vp denotes the reference industrial rolling speed) on the rolling force, temperature field, and equivalent stress/strain during finish rolling. The results show that the increased number of passes homogenizes deformation, reduces local stress concentration and enhances mechanical properties. Specifically, 12 passes reduce the peak rolling force from 250,972 N to 208,124 N, significantly enhancing stress and temperature uniformity across the section. Increasing the finish rolling temperature lowers the pass-averaged flow stress and attenuates rolling-force fluctuations. At 880 °C, the simulated core–surface temperature gradient is minimal (50 °C), whereas at 900 °C the gradient increases (80 °C) but the rolling-force histories exhibit a lower peak level and smaller low-frequency oscillations; thus 880 °C is preferable when through-thickness thermal uniformity is targeted, while 900 °C is more suitable when a smoother load response is required. Increasing the finish rolling speed from 0.5 Vp to 1.5 Vp reduces the peak rolling force from 233,165 N to 183,665 N and significantly damps low-frequency load oscillations. However, it concurrently intensifies stress localization at the outer-surface tracking points P3/P4, which are in direct contact with the rolls, where the local equivalent stress approaches 523 MPa, even though the overall strain distribution along the bar length becomes more uniform. Overall, the optimal processing window is identified as a 12-pass schedule, a finish rolling temperature of 880–900 °C, and a rolling speed of 1.0–1.5 Vp, which can improve both rolling quality and temperature and stress and strain uniformity. Full article

Frequent extreme-weather events pose severe challenges to the secure and economical operation of power systems with high renewable energy penetration. To strengthen grid resilience against such low-probability, high-impact events while maintaining good performance under normal conditions, this paper proposes an optimal energy storage allocation method for power systems with high-wind-power penetration. We first identify two representative extreme wind power events and develop a risk assessment model that jointly quantifies load-shedding volume and transmission-line security margins. On this basis, a multi-scenario joint siting-and-sizing optimization model is formulated over typical-day and extreme-day scenarios to minimize total system cost, including annualized investment cost, operating cost, and risk cost. To solve the model efficiently, a two-stage hierarchical solution strategy is designed: the first stage determines an investment upper bound from typical-day scenarios, and the second stage optimizes storage allocation under superimposed extreme-day scenarios within this bound, thereby balancing operating economy and extreme-weather resilience. Simulation results show that the proposed method reduces loss-of-load under extreme-weather scenarios by 32.46% while increasing storage investment cost by only 0.18%, significantly enhancing system resilience and transmission-line security margins at a moderate additional cost. Full article

High-speed silicon (Si) photonic transmitters operating in the O-band require higher on-chip optical power to support advanced modulation formats and ever-increasing line rates. A straightforward approach is to operate laser diodes at higher output power or employ more specialized sources, but this raises cost and exacerbates nonlinear effects such as self-phase modulation, two-photon absorption, and free-carrier generation in high-index-contrast Si waveguides. This paper proposes a low-cost 4 × 1 tree-cascade multimode interference (MMI) power combiner on a Si-on-insulator platform at 1310 nm wavelength that enables coherent power scaling while remaining fully compatible with standard commercial O-band lasers. The device employs adiabatic tapers and low-loss S-bends to ensure uniform field evolution, suppress local field enhancement, and mitigate nonlinear phase accumulation. The optimized layout occupies a compact footprint of 12 µm × 772 µm and achieves a simulated normalized power transmission of 0.975 with an insertion loss of 0.1 dB. Spectral analysis shows a 3 dB bandwidth of 15.8 nm around 1310 nm, across the O-band operating window. Thermal analysis shows that wavelength drift associated with ±50 °C temperature variation remains within the device bandwidth, ensuring stable operation under realistic laser self-heating and environmental changes. Owing to its broadband response, fabrication tolerance, and compatibility with off-the-shelf laser diodes, the proposed combiner is a promising building block for O-band transmitters and photonic neural-network architectures based on cascaded splitter and combiner meshes, while preserving linear transmission and enabling dense, large-scale photonic integration. Full article

RNA interference (RNAi) holds promise as a gene-silencing therapy for liver cancer but faces challenges related to siRNA instability, short half-life, and inefficient cellular uptake. In this study, we designed a self-assembling RNA nanoparticle targeting three oncogenes—hTERT, BIRC5, and FGFR1—key drivers of cancer progression. These RNA nanoparticles demonstrated enhanced stability and specificity, eliminating the need for conventional toxic delivery carriers. Functional assays revealed that the nanoparticles effectively suppressed the proliferation, migration, tumor growth and apoptosis of a Hepatocellular carcinoma cell line, Hep3B. The nanoparticles exhibited excellent safety and efficacy in xenograft model mice, without off-target toxicity. This work introduces a scalable, biocompatible RNA nanoparticle platform with multi-targeting capability, paving the way for improved RNAi-based therapeutics. Our findings offer a promising strategy for advancing personalized cancer therapies and underscore the broader potential of RNA nanotechnology in addressing complex malignancies. Full article

This study aims to develop a methodology for implementing solar photovoltaic systems (SSFV) in Caribbean hotels. It begins with an analysis of building characteristics to design and size the SSFV, considering panel support structures, system layout, and grid integration. The methodology also evaluates economic and environmental impacts at both company and national levels. Machine learning analysis identified the variables (Degree Days (DG) and Hotel Days Occupied (HDO)) $HDO\times DG$ as key determinants of energy consumption, with a high coefficient of determination ($R^2$ = 0.97). Implementing a target energy-saving line achieved a 5.3% reduction (1028 kWh) relative to the baseline. Using a genetic algorithm to optimize the SSFV azimuth angle increased photovoltaic energy production by 14.75%, enhancing efficiency and installation area use. Economic assessments showed a challenging scenario for hotels, with a negative internal rate of return of −10%, a 17 year payback period, and a net present value of USD 20,000. However, on a national scale, significant annual savings of USD 225,990.8 from reduced fuel imports were projected. Additionally, carbon emissions reductions of 18,751.4 tons ($tC{O}_2$) were estimated. The findings highlight the feasibility and benefits of SSFV implementation, emphasizing its potential to improve energy efficiency, reduce costs, and enhance sustainability in the Caribbean hotel sector. Full article

Polyploidization is a powerful tool in plant breeding that can induce desirable morphological and physiological modifications. This study aimed to establish an efficient in vitro protocol for inducing autotetraploid plants in cherimoya (Annona cherimola Mill. cv. Fino de Jete) using colchicine. Hypocotyl explants from seedlings germinated in vitro were treated with different colchicine concentrations (0.01–0.2%) for 24 and 48 h, and the effects on shoot regeneration and ploidy level were evaluated by flow cytometry and chromosome counting. Regeneration and survival rates decreased with increasing colchicine concentration and exposure time. The most effective treatment for autotetraploid induction was 0.1% colchicine for 24 h, yielding a 10.5% polyploidization rate with 5.8% autotetraploids. Tetraploid shoots were successfully rooted (80%) and acclimatized (100%) under greenhouse conditions. Autotetraploid plants exhibited significantly larger and more rounded leaves, higher chlorophyll contents and an increased Chl a/Chl b ratio compared with diploids, indicating enhanced photosynthetic efficiency. The induction of stable autotetraploid lines in A. cherimola provides a reliable approach for generating novel genotypes with improved physiological traits and potential tolerance to abiotic stress. These results offer valuable material for future breeding programs aimed at developing new cherimoya rootstocks and cultivars with enhanced vigor and adaptability. Full article

The inspection of power transmission lines using unmanned aerial vehicles primarily relies on object detection. However, the continuous emergence of new obstacle types necessitates frequent updates to detection models, leading to substantial retraining costs. To address this challenge, we propose a novel framework named IViT, which integrates incremental learning with a hybrid CNN-Transformer architecture for improved identification. We combined knowledge distillation with the elastic response selection distillation strategy to enhance detection performance for old classes and strengthen knowledge retention through star convolutional residual blocks constructed via element-wise multiplication. We designed a separable convolution aggregation block that integrates PConv with an attention mechanism, effectively merging global and local information to improve detection accuracy. Finally, we unified the two modules into a hybrid block. In the static detection task, IViT achieves a mAP of 55.3%, a mAP₅₀ of 83.6%, and a mAP₇₅ of 61.0%. For the incremental detection task, it attains a mAP of 57.8%, a mAP₅₀ of 79.7%, and a mAP₇₅ of 62.3%. Extensive experiments on the transmission line corridor external damage dataset and the INSPLAD dataset demonstrate that IViT exhibits outstanding detection performance compared to mainstream static object detection models and incremental object detection models. Full article

The performance of integrated Global Navigation Satellite System and Inertial Navigation System (GNSS/INS) navigation often declines in complex urban environments due to frequent GNSS signal blockages. This poses a significant challenge for autonomous driving applications that require continuous and reliable positioning. To address this limitation, this paper presents a novel hybrid framework that combines a deep learning architecture with an adaptive Kalman Filter. At the core of this framework is a Temporal Convolutional Network and Bidirectional Long Short-Term Memory (TCN-BiLSTM) model, which generates accurate pseudo-GNSS measurements from raw INS data during GNSS outages. These measurements are then fused with the INS data stream using an Adaptive Noise-Regulated Iterated Extended Kalman Filter (ANR-IEKF), which enhances robustness by dynamically estimating and adjusting the process and observation noise statistics in real time. The proposed ANR-IEKF + TCN-BiLSTM framework was validated using a real-world vehicle dataset that encompasses both straight-line and turning scenarios. The results demonstrate its superior performance in positioning accuracy and robustness compared to several baseline models, thereby confirming its effectiveness as a reliable solution for maintaining high-precision navigation in GNSS-denied environments. Validated in 70 s GNSS outage environments, our approach enhances positioning accuracy by over 50% against strong deep learning baselines with errors reduced to roughly 3.4 m. Full article

Background/Objectives: Parkinson’s disease (PD) is an adult-onset neurodegenerative disorder whose pathogenesis is still not completely understood. Several lines of evidence suggest that alterations in epigenetic architecture may contribute to the development of this condition. Here, we present a pilot DNA methylation study from peripheral blood in a cohort of Sicilian PD patients and matched controls. Peripheral tissue analysis has previously been shown to reflect molecular and functional profiles relevant to neurological diseases, supporting their validity as a proxy for studying brain-related epigenetic mechanisms. Methods: We analyzed 20 PD patients and 20 healthy controls (19 males and 21 females overall), matched for sex, with an age range of 60–87 years (mean 72.3 years). Peripheral blood DNA was extracted and processed using the Illumina Infinium MethylationEPIC v2.0 BeadChip, which interrogates over 935,000 CpG sites across the genome, including promoters, enhancers, CpG islands, and other regulatory elements. The assay relies on sodium bisulfite conversion of DNA to detect methylation status at single-base resolution. Results: Epigenome-wide association study (EWAS) data allowed for multiple levels of analysis, including immune cell-type deconvolution, estimation of biological age (epigenetic clocks), quantification of stochastic epigenetic mutations (SEMs) as a measure of epigenomic stability, and differential methylation profiling. Immune cell-type inference revealed an increased but not significant proportion of monocytes in PD patients, consistent with previous reports. In contrast, epigenetic clock analysis did not reveal significant differences in biological age acceleration between cases and controls, partially at odds with earlier studies—likely due to the limited sample size. SEMs burden did not differ significantly between groups. Epivariations reveal genes involved in pathways known to be altered in dopaminergic neuron dysfunction and α-synuclein toxicity. Differential methylation analysis, however, yielded 167 CpG sites, of which 55 were located within genes, corresponding to 54 unique loci. Gene Ontology enrichment analysis highlighted significant overrepresentation of pathways with neurological relevance, including regulation of synapse structure and activity, axonogenesis, neuron migration, and synapse organization. Notably, alterations in KIAA0319, a gene involved in neuronal migration, synaptic formation, and cortical development, have previously been associated with Parkinson’s disease at the gene expression level, while methylation changes in FAM50B have been reported in neurotoxic and cognitive contexts; our data suggest, for the first time, a potential epigenetic involvement of both genes in Parkinson’s disease. Conclusions: This pilot study on a Sicilian population provides further evidence that DNA methylation profiling can yield valuable molecular insights into PD. Despite the small sample size, our results confirm previously reported findings and highlight biological pathways relevant to neuronal structure and function that may contribute to disease pathogenesis. These data support the potential of epigenetic profiling of peripheral blood as a tool to advance the understanding of PD and generate hypotheses for future large-scale studies. Full article

Background/Objectives: The enhancement of antitumor immune responses by radiotherapy (RT) is partially attributed to the activation of the IFN-type-I pathway. However, the loss of HLA-class-I molecules, which occurs in a large percentage of non-small-cell lung cancers (NSCLCs), may block the cytotoxic effect of T-cells and immunotherapy (IO). Moreover, autophagy is also involved in HLA downregulation. We investigated the complex interactions between RT, HLA molecules, autophagy, and IFN-type-I responses. Methods: The A549, H1299, and ATG7-deficient NSCLC cell lines, along with the modified shLC3A H1299 cell line, were used for in vitro experiments. The effect of RT (8 and 3 × 8 Gy) on Interferon beta (IFNβ), IFN-stimulated genes (ISGs), and HLA-class-I expression in combination with IFN-type-I-response inhibitors (Ruxolitinib, Tofacitinib, Amlexanox) targeting the JAK and TBK1 was studied with Flow cytometry and RT-PCR. Results: RT significantly induced HLA-class-I expression. A parallel upregulation of IFNβ and ISGs mRNA levels was also documented. Although the IFN-type-I-response inhibitors suppressed the RT-induced IFNβ and ISGs expression, their effect on HLA-class-I expression was minimal. Blockage of LC3A autophagy (shLC3A cell line) significantly upregulated HLA-class-I basal levels, and RT further enhanced HLA expression. IFN-type-I-response inhibitors blocked the RT-inductive effect in the shLC3A H1299, but had no effect in the ATG7-deficient H1650 cell line. Conclusions: The current study supports the theory that baseline autophagy, RT-induced autophagy blockage, and IFN-type-I response enhancement define the HLA-class-I levels in NSCLC cells. This complex interplay emerges as a promising target for the development of radio-vaccination strategies to enhance the efficacy of radio-immunotherapy. Full article

Colorectal cancer (CRC) remains one of the most lethal malignancies worldwide, with 5-fluorouracil (5-Fu) as a mainstay of treatment. However, intrinsic and acquired resistance to 5-Fu significantly limits therapeutic success. Furin, a proprotein convertase, is known to activate multiple substrates critical for tumor progression, yet its precise role in CRC remains unclear. In this study, we examined furin expression in a large cohort of CRC patient samples and performed functional analyses in CRC cell lines and xenograft models. Furin overexpression was seen in 46.9% (530/1131) of CRC cases and was significantly correlated with TGF-β and ERK1/2 activation. In vitro, induced furin overexpression enhanced proliferation and clonogenicity, accompanied by upregulation of TGF-β and ERK1/2 phosphorylation, whereas furin silencing attenuated tumor cell growth and TGF-β/ERK signaling. Manipulation of TGF-β revealed a reciprocal regulatory loop, whereby TGF-β upregulated furin expression, establishing a feed-forward circuit that augmented ERK signaling and tumor growth. Notably, 5-Fu-resistant CRC cell lines displayed elevated furin, TGF-β, and phospho-ERK1/2, while furin knockdown restored drug sensitivity. In vivo, furin overexpression enhanced tumor growth in xenografts, whereas its depletion markedly reduced tumor burden and TGF-β/ERK signaling activity. Collectively, these findings demonstrate that furin promotes CRC progression and chemoresistance through a positive feedback loop with TGF-β that sustains ERK activation. Targeting furin, alone or in combination with TGF-β/ERK inhibitors, may offer a promising therapeutic strategy for CRC. Full article