Search Results (771)

In recent years, low temperature has seriously threatened the citrus industry. Arbuscular mycorrhizal fungi (AMF) can enhance the absorption of nutrients and water and tolerance to abiotic stresses. In this study, pot experiments were conducted to study the effects of low-temperature stress on citrus (trifoliate orange, Poncirus trifoliata L. Raf.) with AMF (Diversispora epigaea D.e). The results showed that AMF inoculation significantly increased plant growth, chlorophyll fluorescence, and photosynthetic parameters. Compared with 25 °C, −5 °C significantly increased the relative conductance rate and the contents of malondialdehyde, hydrogen peroxide, soluble sugar soluble protein, and proline, and also enhanced the activities of catalase and superoxide dismutase, but dramatically reduced photosynthetic parameters. Compared with the non-AMF group, AMF significantly increased the maximum light quantum efficiency and steady-state light quantum efficiency at 25 °C (by 16.67% and 61.54%), and increased the same parameters by 71.43% and 140% at −5 °C. AMF also significantly increased the leaf net photosynthetic rate and transpiration rate at 25 °C (by 54.76% and 29.23%), and increased the same parameters by 72.97% and 26.67% at −5 °C. Compared with the non-AMF treatment, the AMF treatment significantly reduced malondialdehyde and hydrogen peroxide content at 25 °C (by 46.55% and 41.29%), and reduced them by 28.21% and 29.29% at −5 °C. In addition, AMF significantly increased the contents of soluble sugar, soluble protein, and proline at 25 °C (by 15.22%, 34.38%, and 11.38%), but these increased by only 9.64%, 0.47%, and 6.09% at −5 °C. Furthermore, AMF increased the activities of superoxide dismutase and catalase at 25 °C (by 13.33% and 13.72%), but these increased by only 5.51% and 13.46% at −5 °C. In conclusion, AMF can promote the growth of the aboveground and underground parts of trifoliate orange seedlings and enhance their resistance to low temperature via photosynthesis, osmoregulatory substances, and their antioxidant system. Full article

Chronic coronary syndrome (CCS) and atrial fibrillation (AF) are prevalent cardiovascular conditions that share numerous risk factors and pathophysiological mechanisms. While clinical scores commonly used in AF—such as CHA₂DS₂VA (which includes congestive heart failure, hypertension, age ≥ 75, diabetes, stroke/TIA, vascular disease, and age 65–74), HAS-BLED (which incorporates hypertension, abnormal renal/liver function, stroke, bleeding history, labile INR, elderly age, and drug/alcohol use), and C₂HEST (incorporating coronary artery disease, COPD, hypertension, elderly age ≥ 75, systolic heart failure, and thyroid disease)—are traditionally applied to rhythm or bleeding risk prediction, their value in estimating the angiographic severity of coronary artery disease (CAD) remains underexplored. We conducted a prospective, single-center study including 131 patients with suspected stable CAD referred for coronary angiography, stratified according to coronary angiographic findings into two groups: significant coronary stenosis (S-CCS) and non-significant coronary stenosis (N-CCS). At admission, AF-related scores (CHA₂DS₂, CHA₂DS₂VA, CHA₂DS₂VA-HSF, CHA₂DS₂VA-RAF, CHA₂DS₂VA-LAF, HAS-BLED, C₂HEST, and HATCH) were calculated. CAD severity was subsequently assessed using the SYNTAX and Gensini scores. Statistical comparisons and Pearson correlation analyses were performed to evaluate the association between clinical risk scores and angiographic findings. Patients in the S-CCS group had significantly higher scores in CHA₂DS₂VA (4.09 ± 1.656 vs. 3.20 ± 1.338, p = 0.002), HAS-BLED (1.98 ± 0.760 vs. 1.36 ± 0.835, p < 0.001), CHA₂DS₂VA-HSF (6.00 ± 1.854 vs. 5.26 ± 1.712, p = 0.021), and C₂HEST (3.49 ± 1.501 vs. 2.55 ± 1.279, p < 0.001). Multivariate logistic regression identified HAS-BLED and C₂HEST as independent predictors of significant coronary lesions. A threshold value of HAS-BLED ≥ 1.5 and C₂HEST ≥ 3.5 demonstrated moderate discriminative ability (AUC = 0.694 and 0.682, respectively), with acceptable sensitivity and specificity. These scores also demonstrated moderate to strong correlations with both Gensini and SYNTAX scores. AF-related clinical scores, especially HAS-BLED and C₂HEST, may serve as practical and accessible tools for early CAD risk stratification in patients with suspected CCS. Their application in clinical practice may serve as supplementary triage tools to help prioritize patients for further diagnostic evaluation, but they are not intended to replace standard imaging or testing. Full article

Malignant melanoma (MM) affects not only humans but also animals, with gray horses being particularly predisposed to acquiring the disease. Multiomics have greatly advanced the understanding of human MM. In contrasty little is known regarding the pathogenesis of gray-horse melanoma and the unique phenomenon of melanoma “dormancy” in some animals. To help close this gap in knowledge, melanoma tissue and intact skin collected from gray horses were subjected to transcriptome analysis using RNAseq. In the next step, cultured primary tumor cells and normal skin fibroblasts were established from gray horses, and their protein expression profiles were determined. The obtained data unambiguously identified gray-horse melanoma (ghM) as a malignant tumor, as reflected by the overrepresentation of pathways typically activated in human melanoma and other human cancers. These included the RAS/RAF/MAPK, the IRS/IGF1R, and the PI3K/AKT signaling networks. In addition, the obtained data suggest that the key molecules RAC1, RAS, and BRAF, which are frequently mutated in human melanoma, may also contain activating mutations in ghM, whilst PTEN may harbor loss-of-function mutations. This issue will be subject to downstream analyses determining the mutational status in ghM to further advance the understanding of this frequent disease in gray horses. Full article

Background/Objectives: RAF pathway aberrations are one of the hallmarks of lung cancer. Sorafenib is a multi-kinase inhibitor targeting the RAF pathway and is FDA-approved for several cancers, yet its efficacy in lung cancer is controversial. Previous clinical research showed that a ARAF p.S214C mutation exhibited exceptional responsiveness to sorafenib in lung adenocarcinoma. Methods: Considering this promising clinical potential, the oncogenic potential and sorafenib response of the ARAF p.S214C mutation were investigated using lung cancer models. ARAF p.S214C mutant, ARAF wild-type (WT), and EGFP control genes were ectopically expressed in lung adenocarcinoma cell lines retroviral transduction. In vitro and in vivo sorafenib sensitivity studies were performed, followed by transcriptomics and proteomics analyses. Results: Compared to the ARAF-WT and EGFP-engineered cells, the ARAF p.S214C-engineered cells activated Raf-MEK-ERK signaling and exhibited enhanced oncogenic potential in terms of in vitro cell proliferation, colony and spheroid formation, migration, and invasion abilities, as well as in vivo tumorigenicity. The ARAF p.S214C-engineered cells also displayed heightened sensitivity to sorafenib in vitro and in vivo. RNA sequencing and reverse-phase protein array analyses demonstrated elevated expression of genes and proteins associated with tumor aggressiveness in the ARAF p.S214C mutants, and its sorafenib sensitivity was likely moderated through inhibition of the cell cycle and DNA replication. The ERK and PI3K signaling pathways were also significantly deregulated in the ARAF p.S214C mutants regardless of sorafenib treatment. Conclusions: This study demonstrates the oncogenicity and sorafenib sensitivity of the ARAF p.S214C mutation in lung cancer cells, which may serve as a biomarker for predicting the sorafenib response in lung cancer patients. Importantly, investigating the gene–drug sensitivity pairs in clinically exceptional responders may guide and accelerate personalized cancer therapies based on specific tumor mutations. Full article

Facial expression recognition (FER) plays a critical role in affective computing, enabling machines to interpret human emotions through facial cues. While recent deep learning models have achieved progress, many still fail under real-world conditions such as occlusion, lighting variation, and subtle expressions. In this work, we propose FERONet, a novel hyper-attentive multimodal transformer architecture tailored for robust and real-time FER. FERONet integrates a triple-attention mechanism (spatial, channel, and cross-patch), a hierarchical transformer with token merging for computational efficiency, and a temporal cross-attention decoder to model emotional dynamics in video sequences. The model fuses RGB, optical flow, and depth/landmark inputs, enhancing resilience to environmental variation. Experimental evaluations across five standard FER datasets—FER-2013, RAF-DB, CK+, BU-3DFE, and AFEW—show that FERONet achieves superior recognition accuracy (up to 97.3%) and real-time inference speeds (<16 ms per frame), outperforming prior state-of-the-art models. The results confirm the model’s suitability for deployment in applications such as intelligent tutoring, driver monitoring, and clinical emotion assessment. Full article

Facial emotion recognition (FER) is vital for improving human–machine interactions, serving as the foundation for AI systems that integrate cognitive and emotional intelligence. This helps bridge the gap between mechanical processes and human emotions, enhancing machine engagement with humans. Considering the constraints of low hardware specifications often encountered in real-world applications, this study leverages recent advances in deep learning to propose an enhanced model for FER. The model effectively utilizes texture information from faces through Gabor and Local Binary Pattern (LBP) feature extraction techniques. By integrating these features into a specially modified AlexNet architecture, our approach not only classifies facial emotions more accurately but also demonstrates significant improvements in performance and adaptability under various operational conditions. To validate the effectiveness of our proposed model, we conducted evaluations using the FER2013 and RAF-DB benchmark datasets, where it achieved impressive accuracies of 98.10% and 93.34% for the two datasets, with standard deviations of 1.63% and 3.62%, respectively. On the FER-2013 dataset, the model attained a precision of 98.2%, a recall of 97.9%, and an F1-score of 98.0%. Meanwhile, for the other dataset, it achieved a precision of 93.54%, a recall of 93.12%, and an F1-score of 93.34%. These results underscore the model’s robustness and its capability to deliver high-precision emotion recognition, making it an ideal solution for deployment in environments where hardware limitations are a critical concern. Full article

This paper addresses the central issue arising from the (SDAC) of facial expressions, namely, to balance the competing demands of good global features for detection, and fine features for good facial expression classifications by replacing the feature extraction part of the “neck” network in the feature pyramid network in the You Only Look Once X (YOLOX) framework with a novel architecture involving three attention mechanisms—batch, channel, and neighborhood—which respectively explores the three input dimensions—batch, channel, and spatial. Correlations across a batch of images in the individual path of the dual incoming paths are first extracted by a self attention mechanism in the batch dimension; these two paths are fused together to consolidate their information and then split again into two separate paths; the information along the channel dimension is extracted using a generalized form of channel attention, an adaptive graph channel attention, which provides each element of the incoming signal with a weight that is adapted to the incoming signal. The combination of these two paths, together with two skip connections from the input to the batch attention to the output of the adaptive channel attention, then passes into a residual network, with neighborhood attention to extract fine features in the spatial dimension. This novel dual path architecture has been shown experimentally to achieve a better balance between the competing demands in an SDAC problem than other competing approaches. Ablation studies enable the determination of the relative importance of these three attention mechanisms. Competitive results are obtained on two non-aligned face expression recognition datasets, RAF-DB and SFEW, when compared with other state-of-the-art methods. Full article

Facial expression recognition (FER) is a core technology that enables computers to understand and react to human emotions. In particular, the use of face alignment algorithms as a preprocessing step in image-based FER is important for accurately normalizing face images in terms of scale, rotation, and translation to improve FER accuracy. Recently, FER studies have been actively leveraging feature maps computed by face alignment networks to enhance FER performance. However, previous studies were limited in their ability to effectively apply information from specific facial regions that are important for FER, as they either only used facial landmarks during the preprocessing step or relied solely on the feature maps from the face alignment networks. In this paper, we propose the use of Keypoint Features extracted from feature maps at the coordinates of facial landmarks. To effectively utilize Keypoint Features, we further propose a Keypoint Feature regularization method using landmark perturbation for robustness, and an attention mechanism that emphasizes all Keypoint Features using representative Keypoint Features derived from a nasal base landmark, which carries information for the whole face, to improve performance. We performed experiments on the AffectNet, RAF-DB, and FERPlus datasets using a simply designed network to validate the effectiveness of the proposed method. As a result, the proposed method achieved a performance of 68.17% on AffectNet-7, 64.87% on AffectNet-8, 93.16% on RAF-DB, and 91.44% on FERPlus. Furthermore, the network pretrained on AffectNet-8 had improved performances of 94.04% on RAF-DB and 91.66% on FERPlus. These results demonstrate that the proposed Keypoint Features can achieve comparable results to those of the existing methods, highlighting their potential for enhancing FER performance through the effective utilization of key facial region features. Full article

Background/Objectives: Melanoma is one of the most aggressive forms of skin cancer and is frequently associated with the B-Raf⁶⁰⁰E mutation, which constitutively activates the MAPK signaling pathway. Although selective inhibitors such as Vemurafenib offer clinical benefits, their long-term efficacy is often hindered by resistance mechanisms and adverse effects. In this study, twelve phytochemicals from Brazilian green propolis were evaluated for their potential as selective B-Raf⁶⁰⁰E inhibitors using a computational approach. Methods: Physicochemical, ADME, and electronic properties were assessed, followed by molecular docking using the B-Raf⁶⁰⁰E crystal structure (PDB ID: 3OG7). Redocking validation and 500 ns molecular dynamics simulations were performed to investigate the stability of the ligand-protein complexes, and free energy calculations were then computed. Results: Among the tested compounds, Artepillin C exhibited the strongest binding affinity (−8.17 kcal/mol) in docking and maintained stable interactions with key catalytic residues throughout the simulation, also presenting free energy of binding ΔG of −20.77 kcal/mol. HOMO-LUMO and electrostatic potential analyses further supported its reactivity and selectivity. Notably, Artepillin C remained bound within the ATP-binding site, mimicking several critical interactions observed with Vemurafenib. Results: Among the tested compounds, Artepillin C exhibited the strongest binding affinity (−8.17 kcal/mol) and maintained stable interactions with key catalytic residues throughout the simulation. HOMO-LUMO and electrostatic potential analyses further supported its reactivity and selectivity. Notably, Artepillin C remained bound within the ATP-binding site, mimicking several critical interactions observed with Vemurafenib. Conclusions: These findings indicate that Artepillin C is a promising natural compound for further development as a selective B-Raf⁶⁰⁰E inhibitor and suggest its potential utility in melanoma treatment strategies. This study reinforces the value of natural products as scaffolds for targeted drug design and supports continued experimental validation. Full article

This study presents the first comprehensive theoretical investigation of the antioxidant mechanisms of trans-isoferulic acid against hydroperoxyl (HOO^•) radicals in aqueous solution, using the DFT/M062X/6-311+G(d,p)/PCM method. Thermodynamic and kinetic parameters, including reaction energy barriers and bimolecular rate constants, were determined for the three major pathways: hydrogen transfer (HT), radical adduct formation (RAF), and single electron transfer (SET). The results indicate that, at physiological pH, the RAF mechanism is both more exergonic and approximately eight-times faster than HT. At a higher pH, where the phenolate anion dominates, antioxidant activity is enhanced by an additional fast, diffusion-limited SET pathway. Isoferulic acid was also found to effectively chelate Fe²⁺ ions at pH 7.4 and above, forming stable complexes that could inhibit Fenton-type hydroxyl radical generation. Moreover, its strong UV absorption suggests a role in limiting photo-induced free radical formation. These findings not only clarify the antioxidant behavior of isoferulic acid but also provide novel theoretical insights applicable to related phenolic compounds. The compound’s multi-target antioxidant profile highlights its potential as a photoprotective agent in sunscreen formulations. Full article

Reciprocal signaling between acute myeloid leukemia (AML) cells and the surrounding bone-marrow microenvironment (BMME) promotes AML progression through several mechanisms. One of the most important mechanisms is the induction of Galectin-3 (Gal-3) expression by AML cells and bone marrow mesenchymal stromal cells (BM-MSCs). Emerging evidence indicates that Gal-3 upregulation in the BMME promotes AML cell adhesion and survival, leading to the development of chemotherapy resistance, relapse, and poor prognosis. Identifying the biological function and critical signaling pathways of Gal-3 may contribute to overcoming acquired drug resistance and preventing post-treatment relapse. Gal-3 is involved in several molecular signaling pathways, including PI3K/AKT/mTOR, Ras/Raf/MEK/ERK, JAK/STAT, JNK, Wnt/β-catenin, PLC/PKC and NF-κB, which are interconnected to promote AML cell survival and resistance to chemotherapy. This review focuses on the biological effects, molecular mechanisms of action and regulation of Gal-3 in the pathogenesis and progression of AML. The therapeutic potential of potent synthetic small-molecule Gal-3 inhibitors in high-risk patients with AML is also discussed based on preclinical and clinical evidence from several human diseases. Currently, the effect of these Gal-3 inhibitors in AML has not been investigated either in vitro or in vivo. The findings provide a rationale for targeting Gal-3 that may be a very promising therapeutic approach, especially for patients with relapsed/refractory AML, and may enhance the efficacy of conventional chemotherapeutic drugs and/or immune checkpoint inhibitors. Full article

KRAS is a pivotal oncoprotein that regulates cell proliferation and survival through interactions with downstream effectors such as RAF1. Despite significant advances in understanding KRAS biology, the structural and dynamic mechanisms of KRAS allostery remain poorly understood. In this study, we employ microsecond molecular dynamics simulations, mutational scanning, and binding free energy calculations together with dynamic network modeling to dissect how engineered DARPin proteins K27, K55, K13, and K19 engage KRAS through diverse molecular mechanisms ranging from effector mimicry to conformational restriction and allosteric modulation. Mutational scanning across all four DARPin systems identifies a core set of evolutionarily constrained residues that function as universal hotspots in KRAS recognition. KRAS residues I36, Y40, M67, and H95 consistently emerge as critical contributors to binding stability. Binding free energy computations show that, despite similar binding modes, K27 relies heavily on electrostatic contributions from major binding hotspots while K55 exploits a dense hydrophobic cluster enhancing its effector-mimetic signature. The allosteric binders K13 and K19, by contrast, stabilize a KRAS-specific pocket in the α3–loop–α4 motif, introducing new hinges and bottlenecks that rewire the communication architecture of KRAS without full immobilization. Network-based analysis reveals a strikingly consistent theme: despite their distinct mechanisms of recognition, all systems engage a unifying allosteric architecture that spans multiple functional motifs. This architecture is not only preserved across complexes but also mirrors the intrinsic communication framework of KRAS itself, where specific residues function as central hubs transmitting conformational changes across the protein. By integrating dynamic profiling, energetic mapping, and network modeling, our study provides a multi-scale mechanistic roadmap for targeting KRAS, revealing how engineered proteins can exploit both conserved motifs and isoform-specific features to enable precision modulation of KRAS signaling in oncogenic contexts. Full article

Background/Objective: Salinity is a growing problem affecting a large portion of global agricultural land, particularly in areas where water resources are scarce. The objective of this study was to provide physiological and molecular information on salt-tolerant citrus rootstocks to mitigate the detrimental effects of salinity on citriculture. Methods: Ten accessions belonging to eight Citrus species and four to Poncirus trifoliata Raf. were tested for salinity tolerance (0 and 15 mM NaCl for 1 year) in terms of vegetative and Cl⁻ tissue distribution traits. In addition, most accessions were evaluated for leaf Na⁺ and other cations. Results: All salt tolerant accessions tended to restrict the leaf Cl⁻ content, although in a lower degree than the Cleopatra mandarin. However, differences in their ability to restrict leaf [Na⁺] were evident, contributing to a classification of trifoliate and sour orange accessions that matched their genotypic grouping based on allele sharing at a marker targeting candidate gene coding for the NPF5.9 transporter within LCL-6 quantitative trait locus. Conclusions: Our markers targeting LCl-6 candidate genes coding for NPF5.9, PIP2.1, and CHX20 (citrus GmSALT3 ortholog) could be efficient tools for managing the detected salt tolerance diversity in terms of both Cl⁻ and Na⁺ homeostasis in rootstock breeding programs derived from these species, in addition to Citrus reshni. Full article

Pediatric gliomas encompass the most common brain tumor in children and are subdivided into pediatric low-grade gliomas (pLGGs) and pediatric high-grade gliomas (pHGGs). The era of molecular diagnosis has shifted the treatment paradigms and management of these patients. RAS/MAPK pathway alterations serve as the driver in the majority of pLGGs, a subset of pHGG and NF1-related plexiform neurofibromas (PNs). The role of small molecule inhibitors in the treatment of these tumors has evolved in the past decade, facilitated through multiple clinical trials and moving into earlier stages of treatment. Although these developments hold promise, questions remain regarding targeted therapy, the long-term toxicities, the duration of treatment and the potential effects on the natural history of the tumor behavior. Full article