Search Results (847)

The ERK1/2 and PI3K signaling pathways play important roles in cellular proliferation, survival, differentiation, and metabolism. In cancer, these pathways are frequently dysregulated and overactivated, resulting in poor patient prognosis and resistance to treatment. These pathways are activated by receptor tyrosine kinases and send downstream signals to effectors such as RAS, RAF, MEK, AKT, and mTOR. In this review, we highlight the key components of the ERK1/2 and PI3K pathways, the roles they play in tumor progression, and the development of inhibitors and combination therapies designed to enhance therapeutic outcomes and address treatment resistance. Our review demonstrates the need and promise for future research and clinical trials for inhibitors and combination therapies for the ERK1/2 and PI3K pathways in cancer. Full article

Photorhabdus luminescens produces a syringe-like toxin complex to inject toxic enzymes into cells. We demonstrated that the recombinant Photorhabdus toxin complex (PTC) can be engineered for translocation of foreign cargo proteins across cellular membranes. We showed that the system is suitable for injection of trimeric affibodies into mammalian cells in order to influence crucial signaling pathways. As proof of principle, we inhibited Ras-driven tumor cell proliferation by injection of an affibody which interacts with the Ras binding domain of Raf kinase. The system described here could be applicable to target a wide range of signaling molecules for cell biological or therapeutic intervention. Full article

Due to the local similarities between different facial expressions and the subjective influences of annotators, large-scale facial expression datasets contain significant label noise. Recognition-based noisy labels are a key challenge in the field of deep facial expression recognition (FER). Based on this, this paper proposes a simple and effective attention-based fusion consistency network (AFCN), which suppresses the impact of uncertainty and prevents deep networks from overemphasising local features. Specifically, the AFCN comprises four modules: a sample certainty analysis module, a label correction module, an attention fusion module, and a fusion consistency learning module. Among these, the sample certainty analysis module is designed to calculate the certainty of each input facial expression image; the label correction module re-labels samples with low certainty based on the model’s prediction results; the attention fusion module identifies all possible key regions of facial expressions and fuses them; the fusion consistency learning module constrains the model to maintain consistency between the regions of interest for the actual labels of facial expressions and the fusion of all possible key regions of facial expressions. This guides the model to perceive and learn global facial expression features and prevents it from incorrectly classifying expressions based solely on local features associated with noisy labels. Experiments are conducted on multiple noisy datasets to validate the effectiveness of the proposed method. The experimental results illustrate that the proposed method outperforms current state-of-the-art methods, achieving a 3.03% accuracy improvement on the 30% noisy RAF-DB dataset in particular. Full article

Facial Expression Recognition (FER) is a research topic of great practical significance. However, existing FER methods still face numerous challenges, particularly in the interaction between spatial and global information, the distinction of subtle expression features, and the attention to key facial regions. This paper proposes a lightweight Global-Aware Spatial (GAS) Attention module, designed to improve the accuracy and robustness of FER. This module extracts global semantic information from the image via global average pooling and fuses it with local spatial features extracted by convolution, guiding the model to focus on regions highly relevant to facial expressions (such as the mouth and eyes). This effectively suppresses background noise and enhances the model’s ability to perceive subtle expression variations. In addition, we further introduce a Squeeze-and-Excitation (SE) Attention module into the dual-branch architecture to adaptively adjust the channel-wise weights of features, emphasizing critical region information and enhancing the model’s discriminative capacity. Based on these improvements, we develop the Ada-DF++ network model. Experimental results show that the improved model achieves test accuracies of 89.21%, 66.14%, and 63.75% on the RAF-DB, AffectNet (7cls), and AffectNet (8cls) datasets, respectively, outperforming current state-of-the-art methods across multiple benchmarks and demonstrating the effectiveness of the proposed approach for FER tasks. Full article

This paper reports the first case in which a hyperlipidemic retriever (due to hypothyroidism) with a nasal tumor was successfully treated—achieving partial remission—and managed using a metronomic combination of chlorambucil (3.74 mg/m², SID) and prednisolone (0.28 mg/kg, SID) orally for 9 months at a general practice. A 35 kg spayed female golden retriever aged 8 years and 8 months with nosebleeds visited the Bundang New York Animal Hospital in July 2023 after being diagnosed with nasal carcinoma. A protocol of 4 weeks of chemotherapy followed by 1 week of rest was repeated in two cycles and continued metronomically for 9 months without pause after the two cycles. The nasal exudate was significantly reduced. The size of the nasal tumor was monitored using computed tomography (CT) imaging at a referral hospital. Since the first occurrence of epistaxis, 18 months have passed (as of January 2025) and the nasal exudate is barely visible, and the vital signs and weight of the dog remain stable. The size of the nasal tumor significantly decreased after 9 months of chemotherapy completion without moderate side effects, and all the blood work was normalized, including hypercholesteremia. This study demonstrates that, in hyperlipidemic cancer patients, a prednisolone/chlorambucil metronomic combination which is cost-effective can be an alternative to tyrosine kinase inhibitors such as sorafenib, even when excluding the price. Through a literature review, the author also investigates the effect of the hyperlipidemic state on cancer, focusing on carcinoma and vascular endothelial growth factor (VEGF), as well as the RAS-RAF-MEK pathway, which is a target for tyrosine kinase inhibitors, in order to reveal the molecular mechanism of chlorambucil metronomic chemotherapy. Also, the author investigates the molecular pathway of carcinoma development in human hyperlipidemia patients through single-cell RNA sequence analysis using open public data, and discusses the molecular action of chlorambucil. Full article

ELK1 is a Transcription factor (TF) belonging to the ETS-domain TF family, mainly activated via RAS-RAF-MEK-ERK signaling. As a nethermost pathway molecule, ELK1 binds to Serum-response elements (SREs) and directly regulates the transcription of Immediate early genes (IEGs) including FOS and EGR1. Due to ELK1’s influence on key cellular processes such as proliferation, migration, apoptosis evasion, and Epithelial-to-mesenchymal transition (EMT), its role as a key contributor to tumorigenesis is emerging. In recent years, elevated expression and/or activation of ELK1 has been reported in various malignancies, including lung, breast, prostate, colorectal, blood, gastric, liver, cervical, thyroid and ovarian cancer. ELK1 acts primarily through direct DNA binding but also through interaction with other oncogenes, noncoding RNA molecules, TFs, and upstream kinases (other than ERK1/2), thus participating in diverse axes of transcriptional regulation. Its crucial role in IEG expression has been particularly implicated in cancer progression, metastasis, and drug resistance. Owing to its role in multiple cellular functions and its subsequent oncogenic potential, further elucidation of intracellular ELK1 interactions is of paramount importance. This review aims to summarize current evidence on ELK1’s involvement in solid tumors, dissect reported mechanistic roles, and highlight recent insights that could fuel future ventures of high translational interest. Full article

Background and Objective: Colorectal cancer (CRC) most commonly metastasizes to the liver and lungs; however, synchronous metastases to pelvic structures such as the vagina and urethra are extremely rare, posing a significant diagnostic and therapeutic challenge. This report describes an unusual case of sigmoid colon adenocarcinoma with synchronous metastases to the vagina and urethra, highlighting its diagnostic evaluation and the value of a multidisciplinary approach. Methods: A 59-year-old woman with a history of deep vein thrombosis treated with apixaban presented with chronic constipation and pelvic bleeding. A gynecological evaluation revealed a vaginal lesion. A colonoscopy, biopsy, pelvic magnetic resonance imaging, and molecular profiling were performed. Treatment included chemotherapy (capecitabine and oxaliplatin), panitumumab, and pelvic radiotherapy. Results: The biopsy confirmed a moderately differentiated invasive adenocarcinoma in the sigmoid colon with synchronous metastases to the vagina and urethra. Molecular profiling identified a rat sarcoma virus oncogene and BRAF (B-Raf proto-oncogene), allowing for the use of targeted therapy. The patient achieved a complete response according to RECIST 1.1 criteria and significant symptomatic improvement, including pain reduction, although dosages were adjusted for thrombocytopenia. She is currently continuing palliative treatment with good tolerance and durable symptomatic improvement. Conclusions: This case underscores the need to consider unusual metastatic sites in patients with colorectal cancer presenting with gynecological symptoms. Early diagnosis, based on imaging and histology, alongside molecular characterization, is crucial for effective personalized therapy. Multidisciplinary coordination is key to optimizing clinical outcomes in these rare metastatic presentations. Full article

Autosomal Dominant Polycystic Kidney Disease (ADPKD) is a systemic ciliopathy resulting from loss-of-function mutations in the PKD1 and PKD2 genes, which encode polycystin-1 (PC1) and polycystin-2 (PC2), respectively. PC1 and PC2 regulate mechanosensation, calcium signaling, and key pathways controlling tubular epithelial structure and function. Loss of PC1/PC2 disrupts calcium homeostasis, elevates cAMP, and activates proliferative cascades such as PKA–B-Raf–MEK–ERK, mTOR, and Wnt, driving cystogenesis via epithelial proliferation, impaired apoptosis, fluid secretion, and fibrosis. Recent evidence also implicates novel signaling axes in ADPKD progression including, the Hippo pathway, where dysregulated YAP/TAZ activity enhances c-Myc-mediated proliferation; the stimulator of interferon genes (STING) pathway, which is activated by mitochondrial DNA release and linked to NF-κB-driven inflammation and fibrosis; and the TWEAK/Fn14 pathway, which mediates pro-inflammatory and pro-apoptotic responses via ERK and NF-κB activation in tubular cells. Mitochondrial dysfunction, oxidative stress, and maladaptive extracellular matrix remodeling further exacerbate disease progression. A refined understanding of ADPKD’s complex signaling networks provides a foundation for precision medicine and next-generation therapeutics. This review gathers recent molecular insights and highlights both established and emerging targets to guide targeted treatment strategies in ADPKD. Full article

Fat embolism is a critical medical emergency often resulting from long bone fractures or amputations, leading to acute respiratory distress syndrome (ARDS). The NOD-like receptor pyrin domain-containing 3 (NLRP3) inflammasome, a key regulator of innate immunity, is activated by reactive oxygen species and tissue damage, contributing to inflammatory responses. This study examines the role of NLRP3 in fat embolism-induced ARDS and evaluates the therapeutic potential of MCC950, a selective NLRP3 antagonist. Fat embolism was induced by fatty micelle injection into the tail vein of Sprague Dawley rats. Pulmonary injury was assessed through lung weight gain as an edema indicator, NLRP3 expression via Western blot, and IL-1β levels using ELISA. Histological damage and macrophage infiltration were evaluated with hematoxylin and eosin staining. Fat embolism significantly increased pulmonary NLRP3 expression, lipid peroxidation, IL-1β release, and macrophage infiltration within four hours, accompanied by severe pulmonary edema. NLRP3 was localized in type I alveolar cells, co-localizing with aquaporin 5. Administration of MCC950 significantly reduced inflammatory responses, lipid peroxidation, pulmonary edema, and histological damage, while attenuating MAPK cascade phosphorylation of ERK and Raf. These findings suggest that NLRP3 plays a critical role in fat embolism-induced acute respiratory distress syndrome, and its inhibition by MCC950 may offer a promising therapeutic approach. Full article

Flavonoids serve as crucial plant antioxidants in drought tolerance, yet their antioxidant regulatory mechanisms within mycorrhizal plants remain unclear. In this study, using a two-factor design, trifoliate orange (Poncirus trifoliata (L.) Raf.) seedlings in the four-to-five-leaf stage were either inoculated with Funneliformis mosseae or not, and subjected to well-watered (70–75% of field maximum water-holding capacity) or drought stress (50–55% field maximum water-holding capacity) conditions for 10 weeks. Plant growth performance, photosynthetic physiology, leaf flavonoid content and their antioxidant capacity, reactive oxygen species levels, and activities and gene expression of key flavonoid biosynthesis enzymes were analyzed. Although drought stress significantly reduced root colonization and soil hyphal length, inoculation with F. mosseae consistently enhanced the biomass of leaves, stems, and roots, as well as root surface area and diameter, irrespective of soil moisture. Despite drought suppressing photosynthesis in mycorrhizal plants, F. mosseae substantially improved photosynthetic capacity (measured via gas exchange) and optimized photochemical efficiency (assessed by chlorophyll fluorescence) while reducing non-photochemical quenching (heat dissipation). Inoculation with F. mosseae elevated the total flavonoid content in leaves by 46.67% (well-watered) and 14.04% (drought), accompanied by significantly enhanced activities of key synthases such as phenylalanine ammonia-lyase (PAL), chalcone synthase (CHS), chalcone isomerase (CHI), 4-coumarate:coA ligase (4CL), and cinnamate 4-hydroxylase (C4H), with increases ranging from 16.90 to 117.42% under drought. Quantitative real-time PCR revealed that both mycorrhization and drought upregulated the expression of PtPAL1, PtCHI, and Pt4CL genes, with soil moisture critically modulating mycorrhizal regulatory effects. In vitro assays showed that flavonoid extracts scavenged radicals at rates of 30.07–41.60% in hydroxyl radical (•OH), 71.89–78.06% in superoxide radical anion (O₂^•−), and 49.97–74.75% in 2,2-diphenyl-1-picrylhydrazyl (DPPH). Mycorrhizal symbiosis enhanced the antioxidant capacity of flavonoids, resulting in higher scavenging rates of •OH (19.07%), O₂^•− (5.00%), and DPPH (31.81%) under drought. Inoculated plants displayed reduced hydrogen peroxide (19.77%), O₂^•− (23.90%), and malondialdehyde (17.36%) levels. This study concludes that mycorrhizae promote the level of total flavonoids in trifoliate orange by accelerating the flavonoid biosynthesis pathway, hence reducing oxidative damage under drought. Full article

Facial expression recognition (FER) is a critical research direction in artificial intelligence, which is widely used in intelligent interaction, medical diagnosis, security monitoring, and other domains. These applications highlight its considerable practical value and social significance. Face expression recognition models often need to run efficiently on mobile devices or edge devices, so the research on lightweight face expression recognition is particularly important. However, feature extraction and classification methods of lightweight convolutional neural network expression recognition algorithms mostly used at present are not specifically and fully optimized for the characteristics of facial expression images, yet fail to make full use of the feature information in face expression images. To address the lack of facial expression recognition models that are both lightweight and effectively optimized for expression-specific feature extraction, this study proposes a novel network design tailored to the characteristics of facial expressions. In this paper, we refer to the backbone architecture of MobileNet V2 network, and redesign LightExNet, a lightweight convolutional neural network based on the fusion of deep and shallow layers, attention mechanism, and joint loss function, according to the characteristics of the facial expression features. In the network architecture of LightExNet, firstly, deep and shallow features are fused in order to fully extract the shallow features in the original image, reduce the loss of information, alleviate the problem of gradient disappearance when the number of convolutional layers increases, and achieve the effect of multi-scale feature fusion. The MobileNet V2 architecture has also been streamlined to seamlessly integrate deep and shallow networks. Secondly, by combining the own characteristics of face expression features, a new channel and spatial attention mechanism is proposed to obtain the feature information of different expression regions as much as possible for encoding. Thus improve the accuracy of expression recognition effectively. Finally, the improved center loss function is superimposed to further improve the accuracy of face expression classification results, and corresponding measures are taken to significantly reduce the computational volume of the joint loss function. In this paper, LightExNet is tested on the three mainstream face expression datasets: Fer2013, CK+ and RAF-DB, respectively, and the experimental results show that LightExNet has 3.27 M Parameters and 298.27 M Flops, and the accuracy on the three datasets is 69.17%, 97.37%, and 85.97%, respectively. The comprehensive performance of LightExNet is better than the current mainstream lightweight expression recognition algorithms such as MobileNet V2, IE-DBN, Self-Cure Net, Improved MobileViT, MFN, Ada-CM, Parallel CNN(Convolutional Neural Network), etc. Experimental results confirm that LightExNet effectively improves recognition accuracy and computational efficiency while reducing energy consumption and enhancing deployment flexibility. These advantages underscore its strong potential for real-world applications in lightweight facial expression recognition. Full article

Facial expression plays an important role in human–computer interaction and affective computing. However, existing expression recognition methods cannot effectively capture multi-scale structural details contained in facial expressions, leading to a decline in recognition accuracy. Inspired by the multi-scale processing mechanism of the biological visual system, this paper proposes a wavelet-guided global–local feature aggregation network (WGGLFA) for facial expression recognition (FER). Our WGGLFA network consists of three main modules: the scale-aware expansion (SAE) module, which combines dilated convolution and wavelet transform to capture multi-scale contextual features; the structured local feature aggregation (SLFA) module based on facial keypoints to extract structured local features; and the expression-guided region refinement (ExGR) module, which enhances features from high-response expression areas to improve the collaborative modeling between local details and key expression regions. All three modules utilize the spatial frequency locality of the wavelet transform to achieve high-/low-frequency feature separation, thereby enhancing fine-grained expression representation under frequency domain guidance. Experimental results show that our WGGLFA achieves accuracies of 90.32%, 91.24%, and 71.90% on the RAF-DB, FERPlus, and FED-RO datasets, respectively, demonstrating that our WGGLFA is effective and has more capability of robustness and generalization than state-of-the-art (SOTA) expression recognition methods. Full article

B-raf (rapidly accelerated fibrosarcoma) is a crucial player within the ERK/MAPK signaling pathway. In the CNS, B-raf has been implicated in neuronal differentiation, long-term memory, and major depression. Mice with forebrain neuron-specific B-raf knockout show behavioral deficits in spatial learning tasks and impaired hippocampal long-term potentiation (LTP). To elucidate the mechanism(s) underlying diminished synaptic plasticity in B-raf-deficient mice, we performed whole-cell recordings from CA1 pyramidal cells in hippocampal slices of control and B-raf mutant mice. We found that the NMDA/AMPA ratio of excitatory postsynaptic currents (EPSCs) at the Schaffer collateral—CA1 pyramidal cell synapses was significantly reduced in B-raf mutants, which would at least partially account for their impaired LTP. Interestingly, the reduced NMDA component of field postsynaptic potentials in mutant preparations was partially reinstated by blocking the apamin-sensitive small-conductance Ca²⁺-activated K⁺ (SK) channels, which have also been reported to modulate hippocampal LTP and learning tasks. To determine the impact of B-raf-dependent signaling on SK current, we isolated the apamin-sensitive tail current after a strong depolarizing event and found indeed a significantly bigger SK current in B-raf-deficient cells compared to controls, which is consistent with the reduced action potential firing and the stronger facilitating effect of apamin on CA1 somatic excitability in B-raf-mutant hippocampus. Our data suggest that B-raf signaling readjusts the delicate balance between NMDA receptors and SK channels to promote synaptic plasticity and facilitate hippocampal learning and memory. Full article

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