Search Results (92)

Introduction: Nutrition literacy has garnered growing research attention worldwide, yet only a few instruments have been developed to specifically measure this construct among adolescents. Accordingly, the present research sought to examine the validity and reliability of the Adolescent Nutrition Literacy Scale (ANLS) within a group of Lebanese adolescents. Methods: A cross-sectional study was carried out from December 2022 to March 2023, targeting a nationally representative sample. Results: Fit indices of the three-factor structure were good. Internal reliability was adequate for the following three subscales: Functional Nutrition Literacy (FNL) (ω = 0.88/α = 0.88), Interactive Nutrition Literacy (INL) (ω = 0.87/α = 0.86) and Critical Nutrition Literacy (CNL) (ω = 0.89/α = 0.89). Invariance was established across genders at configural, metric, and scalar levels. A significantly higher mean FNL and INL scores were found in males compared to females, with no significant difference between the two genders in terms of CNL. Higher FNL, but not CNL and INL scores were significantly associated with lower child food security. Conclusions: The Arabic ANLS has exhibited robust psychometric reliability, validity, and cost-effectiveness as a tool for assessing nutrition literacy. By utilizing the Arabic version of the ANLS, we can more efficiently and accurately assess the nutritional literacy of adolescents. Full article

Background: Genetic alterations in CSF3R, typically associated with chronic neutrophilic leukemia (CNL) and atypical chronic myeloid leukemia (aCML), rarely occur in other myeloid neoplasms. Methods: This study characterized the clinical, morphologic, cytogenetic, and molecular features of 13 patients with non-CNL non-aCML myeloid neoplasms with CSF3R alterations. Patients (median age, 77 years) were categorized into groups with a myelodysplastic/myeloproliferative neoplasm (MDS/MPN) (n = 5), acute leukemia (n = 4), and other myeloid neoplasms (n = 4) based on the WHO 2022 and ICC criteria. Results: The CSF3R p.Thr618Ile mutation was most frequent (11/13), with additional pathogenic variants including p.Gln743Ter and frameshift mutations affecting the cytoplasmic tail. Variant allele frequencies (VAFs) ranged from 2% to 49%, with the highest median VAF in the MDS/MPN group. Co-mutations varied by subtype; MDS/MPN, NOS, and CMML cases frequently harbored mutations in epigenetic regulators (ASXL1, TET2) and splicing factors (SF3B1, SRSF2, ZRSR2), while acute leukemia cases showed alterations in JAK3, STAT3, and NRAS. Survival analysis revealed distinct patterns across the three diagnostic groups, with MDS/MPN having the poorest prognosis. Conclusion: This study expands the recognized spectrum of CSF3R-related myeloid neoplasms and highlights the clinical and molecular heterogeneity associated with these mutations, emphasizing the need for comprehensive molecular profiling and the potential for targeted therapies. Full article

Postamputation pain (PAP), including residual limb pain (RLP) and phantom limb pain (PLP), remains a significant and debilitating complication after limb loss. Despite advances in pharmacological management, many patients experience inadequate pain relief, underscoring the need for alternative therapeutic strategies. Objective: This narrative review critically synthesizes current interventional therapies for PAP, focusing on mechanisms, clinical efficacy and practical application. Methods: A literature search was conducted in PubMed, EMBASE, Scopus and Web of Science databases for studies published between 2015 and 2025. Relevant articles on peripheral nerve interventions as well as different neuromodulation techniques were included. Results: Peripheral interventions (such as alcohol neurolysis, radiofrequency ablation (RFA) and cryoneurolysis (CNL)) and neuromodulation techniques (including spinal cord stimulation (SCS), dorsal root ganglion (DRG) stimulation and cauda equina stimulation (CES)) demonstrate promising outcomes for PAP. Peripheral nerve stimulation (PNS) shows favorable safety and efficacy profiles and may help prevent the chronification of pain. Conclusions: Contemporary interventional therapies represent valuable options in the multidisciplinary management of PAP. Nevertheless, further research is required to standardize clinical algorithms, optimize therapeutic decision-making and improve long-term outcomes and quality of life for individuals with PAP. Full article

(1) Background: This study used a microfluidic approach to prepare paeonol (PAE) liposomes with oleanolic acid (PAE-ONLs) instead of cholesterol (PAE-CNLs), aiming to reduce cholesterol levels and enhance stability and anti-inflammatory activity. (2) Methods: The liposome formula was optimized, characterized, and tested for anti-inflammatory activities in zebrafish and RAW 264.7 macrophages, utilizing various stability and molecular interaction methods. (3) Results: The best PAE-ONL preparation conditions were 10.25 mg/mL of soy lecithin, 0.82 mg/mL of oleanolic acid, and 0.22% (wt%) of Tween 80, with an EE of 64.61 ± 0.42%. TEM confirmed the uniform spherical morphology, and FTIR confirmed that oleanolic acid was incorporated into the liposomes. PAE-ONLs showed better stabilities than PAE-CNLs. Molecular interaction results revealed that PAE-ONLs achieved a greater energy reduction, reaching −85.07 kJ/mol vs. the −62.64 kJ/mol of PAE-CNLs, with stable hydrogen bonding interactions. PAE-ONLs significantly reduced inflammatory cell migration in zebrafish and decreased NO, TNF-α, IL-6, and IL-1β levels in LPS-induced RAW 264.7 macrophages at 20 μg/mL. A network pharmacology analysis showed that oleanolic acid and paeonol interacted with 45 and 11 anti-inflammatory targets, respectively, and their combination in PAE-ONLs enhanced their anti-inflammatory coverage. (4) Conclusions: PAE-ONLs, utilizing oleanolic acid as a cholesterol substitute, exhibit enhanced stability and superior anti-inflammatory effects. Full article

The electrochemical impedance spectroscopy (EIS) is a measurement method for characterizing bio-recognition events of a sensor, such as field-effect transistor-based biosensors (BioFETs). Due to the lack of portable impedance spectroscopes, EIS applies mainly in laboratories preventing application-oriented use in the field. This work presents a portable impedance analyzer (PIA) providing a 4-channel EIS of BioFETs. It performs the analysis of the recorded spectra by determining the charge transfer resistance ${\mathrm{R}}_{\mathrm{ct}}$ with a power-saving algorithm. Therefore, a circle is fitted into the Nyquist representation of the Randles circuit, from whose zero crossings ${\mathrm{R}}_{\mathrm{ct}}$ can be determined. The introduced algorithm was evaluated on 100 simulated spectra of Randles circuits. To analyze the overall system, an adjustable reference circuit was developed that simulates configurable Randles circuits. Additional measurements with pH-sensitive ion-sensitive field-effect transistors (ISFETs) demonstrate the application of the measurement system with electrochemical sensors. Using simulated spectra, the circular fitting is able to detect ${\mathrm{R}}_{\mathrm{ct}}$ with a median accuracy of $1.2\%$ at an average nominal power of 40 mW and 3054 µs computing time. The PIA with the embedded implementation of the circuit fitting achieves a median error for R_ct of 4.2% using the introduced Randles circuit simulator (RCS). Measurements with ISFETs show deviations of 6.5 ± 2.8% compared to the complex non-linear least squares (CNLS), but is significantly faster and more efficient. The presented system allows a portable, power-saving performance of EIS. Future optimizations for a specific applications can improve the presented system and enable novel low-power and automated measurements of biosensors outside the laboratory. Full article

Introduction: Rice, a cornerstone of global food security, faces escalating demands for enhanced yield and disease resistance. We collected 300 high-quality genomes, representing both cultivated (Oryza sativa indica, O. sativa japonica, and O. sativa aus) and wild species (O. rufipogon, O. glaberrima, and O. barthii). Methods: Leveraging HMMER, NLR-Annotator, and OrthoFinder, we systematically identified 148,077 leucine-rich repeat (LRR) and 143,459 nucleotide-binding leucine-rich repeat (NLR) genes, with LRR receptor-like kinases (LRR-RLKs) dominating immune receptor proportions, followed by coiled-coil domain containing (CNL)-type NLRs and LRR receptor-like proteins (LRR-RLPs). Results: Benchmarking Universal Single-Copy Orthologs (BUSCO) assessments confirmed robust genome quality (average score: 94.78). Strikingly, 454 TIR-NB-LRR (TNL) genes—typically rare in monocots—were detected, challenging prior assumptions. Phylogenetic analysis with Arabidopsis TNLs highlighted five O. glaberrima genes clustering with dicot TNLs; these genes featured truncated PLN03210 motifs fused to nucleotide-binding adaptor shared by APAF-1, R proteins, and CED-4 (NB-ARC) and LRR domains. Conclusions: By bridging structural genomics, evolutionary dynamics, and domestication-driven adaptation, this work provides a foundation for targeted breeding strategies and advances functional studies of plant immunity in rice. Full article

Total organic carbon (TOC) content is an important parameter for evaluating the abundance of organic matter in, and the hydrocarbon production capacity, of shale. Currently, no prediction method is applicable to all geological conditions, so exploring an efficient and accurate prediction method suitable for the study area is of great significance. In this study, for the shale of the Qingshankou Formation of the Gulong Sag in the Songliao Basin, TOC content prediction models using various machine learning algorithms are established and compared based on measured data, principal component analysis, and the particle swarm optimization algorithm. The results showed that GR, AC, DEN, CNL, LLS, and LLD are the most sensitive parameters using the Pearson correlation coefficient. The four principal components were also identified as input features through PCA processing. The XGBoost prediction model, established after selecting the parameters through PSO intelligence, had the highest accuracy with an $R^2$ and RMSE of 0.90 and 0.1545, respectively, which are superior to the values of the other models. This model is suitable for the prediction of TOC content and provides effective technical support for shale oil exploration and development in the study area. Full article

Endometrial cancer (EC) is the most common gynecologic malignancy in developed countries, with rising incidence due to aging populations and obesity-related factors. This review explores the evolving molecular and FIGO classifications of EC, highlighting their significance in diagnosis, prognosis, and personalized treatment strategies. Molecular subtyping based on The Cancer Genome Atlas (TCGA) classification offers a more precise understanding of EC, dividing it into POLE ultramutated, microsatellite instability-high (MSI-H), copy-number low (CNL), and copy-number high (CNH) subtypes. Each subgroup has distinct genetic, histological, and prognostic characteristics. Recent updates to the FIGO staging system incorporate molecular features, allowing for more tailored treatment approaches. Advances in immunotherapy, targeted therapies, and novel therapeutic combinations have reshaped clinical management. This review emphasizes the integration of molecular diagnostics into routine practice, outlining challenges and future perspectives in managing EC for improved patient outcomes. Full article

Human parvovirus B19 (B19V) is a major human pathogen in which the ssDNA genome is replicated within the nucleus of infected human erythroid progenitor cells (EPCs) through a process involving both cellular and viral proteins, including the non-structural protein (NS)1. We previously characterized the interaction between NS1 classical nuclear localization signal (cNLS: GACHAKKPRIT-182) and host cell importin (IMP)α and proposed it as a potential target for antiviral drug development. Here, we further extend on such findings. First, we demonstrate that NS1 nuclear localization is required for viral production since introducing the K177T substitution in a cloned, infectious viral genome resulted in a non-viable virus. Secondly, we demonstrate that the antiparasitic drug ivermectin (IVM), known to inhibit the IMPα/β dependent nuclear import pathway, could impair the NS1-NLS:IMPα interaction and suppress viral replication in UT7/EpoS1 cells in a dose-dependent manner. We also show that a panel of structurally related avermectins (AVMs) can dissociate the NS1-NLS:IMPα complex with half-maximal inhibitory concentrations in the nanomolar range. Among them, Eprinomectin emerged as the most selective inhibitor of B19V replication, with a selectivity index of c. 5.0. However, when tested in EPCs generated from peripheral blood mononuclear cells, which constitute a cellular population close to the natural target cells in bone marrow, the inhibitory effect of IVM and Eprinomectin was demonstrated to a lesser extent, and both compounds exhibited high toxicity, thus highlighting the need for more specific inhibitors of the NS1-NLS:IMPα interaction. Full article

CNL is a rare subtype of MPNs characterized by persistent neutrophilia, bone marrow hypercellularity, and specific genetic mutations, particularly in the CSF3R gene. Advances in molecular diagnostics have greatly enhanced our understanding of CNL, distinguishing it from other myeloproliferative disorders and refining diagnostic criteria. This review provides an updated overview of CNL, focusing on breakthroughs in genetic profiling, including novel mutations with potential prognostic value and implications for targeted therapy. We discuss current management strategies, emphasizing the role of JAK inhibitors, allogeneic stem cell transplantation, and evolving investigational treatments. Challenges in early diagnosis, therapeutic resistance, and future directions in research are also addressed, underscoring the need for a personalized medicine approach to improve outcomes for patients with CNL. Full article

We test here the prediction capabilities of the new generation of deep learning predictors in the more challenging situation of multistate multidomain proteins by using as a case study a coiled-coil family of Nucleotide-binding Oligomerization Domain-like (NOD-like) receptors from A. thaliana and a few extra examples for reference. Results reveal a truly remarkable ability of these platforms to correctly predict the 3D structure of modules that fold in well-established topologies. A lower performance is noticed in modeling morphing regions of these proteins, such as the coiled coils. Predictors also display a good sensitivity to local sequence drifts upon the modeling solution of the overall modular configuration. In multivalued 1D to 3D mappings, the platforms display a marked tendency to model proteins in the most compact configuration and must be retrained by information filtering to drive modeling toward the sparser ones. Bias toward order and compactness is seen at the secondary structure level as well. All in all, using AI predictors for modeling multidomain multistate proteins when global templates are at hand is fruitful, but the above challenges have to be taken into account. In the absence of global templates, a piecewise modeling approach with experimentally constrained reconstruction of the global architecture might give more realistic results. Full article

To investigate the influencing factors of the shear failure behavior of rock joints, especially the shear instability characteristics, direct shear tests were performed on marble joints with various grain sizes under different constant normal loads (CNLs). The experimental results show that the grain size and CNL have significant effects on the shear mechanical properties of rock joints. The peak shear strength (τ_p), peak shear displacement (u_p), post-peak modulus (S), and stress drop (Δτ) of rock joints all increase first and then decrease with the increase in grain size, but they increase with the increase in CNL. The mineral composition and microstructure also have a certain influence on the shear mechanical properties of rock joints. In addition, the post-peak soften modulus (S_p) was proposed to describe the shear instability characteristics of rock joints, and its relationship with grain size and CNL was established. The mechanical model of the shear instability of rock joints was established, and the shear instability criterion of rock joints was proposed based on the stiffness criterion and the proposed post-peak soften modulus (S_p). This paper further reveals the shear instability mechanism of rock joints, which can provide a reference for the stability analysis of jointed rockmass. Full article

Myeloproliferative neoplasms (MPNs) are clonal hematopoietic cancers characterized by hyperproliferation of the myeloid lineages. These clonal marrow disorders are extremely rare in pediatric patients. MPN is reported to occur 100 times more frequently in adults, and thus research is primarily focused on this patient group. At present, modern diagnostic techniques, primarily genetic, facilitate the identification of the biology of these diseases. The key genes are JAK2, MPL, and CALR, namely, driver mutations, which are present in approximately 90% of patients with suspected MPN. Moreover, there are more than 20 other mutations that affect the development of these hematological malignancies, as evidenced by a review of the literature. The pathogenic mechanism of MPNs is characterized by the dysregulation of the JAK/STAT signaling pathway (JAK2, MPL, CALR), DNA methylation (TET2, DNMT3A, IDH1/2), chromatin structure (ASXL1, EZH2), and splicing (SF3B1, U2AF2, SRSF2). Although rare, myeloproliferative neoplasms can involve young patients and pose unique challenges for clinicians in diagnosis and therapy. The paper aims to review the biological markers of MPNs in pediatric populations—a particular group of patients that has been poorly studied due to the low frequency of MPN diagnosis. Full article

The Solanaceae family occupies a significant position, and the study of resistance genes within this family is extremely valuable. Therefore, our goal is to examine disease resistance genes based on the high-quality representative genomes of Solanaceae crops, and to develop corresponding Simple Sequence Repeat (SSR) molecular markers. Among nine representative Solanaceae species, we identified 819 NBS-LRR genes, which were further divided into 583 CC-NBS-LRR (CNL), 54 RPW8-NBS-LRR (RNL), and 182 TIR-NBS-LRR (TNL) genes. Whole genome duplication (WGD) has played a very important role in the expansion of NBS-LRR genes in Solanaceae crops. Gene structure analysis showed the striking similarity in the conserved motifs of NBS-LRR genes, which suggests a common ancestral origin, followed by evolutionary differentiation and amplification. Gene clustering and events like rearrangement within the NBS-LRR family contribute to their scattered chromosomal distribution. Our findings reveal that the majority of NBS-LRR family genes across all examined species predominantly localize to chromosomal termini. The analysis indicates the significant impact of the most recent whole genome triplication (WGT) on the NBS-LRR family genes. Moreover, we constructed Protein–Protein Interaction (PPI) networks for all 819 NBS-LRR genes, identifying 3820 potential PPI pairs. Notably, 97 genes displayed clear interactive relationships, highlighting their potential role in disease resistance processes. A total of 22,226 SSRs were detected from all genes of nine Solanaceae species. Among these SSRs, we screened 43 NBS-LRR-associated SSRs. Our study lays the foundation for further exploration into SSR development and genetic mapping related to disease resistance in Solanaceae species. Full article

Powdery mildew and anthracnose are the main diseases of rubber trees. In recent years, there have been large outbreaks in the rubber-planting areas of Asia, seriously affecting the yield and quality of rubber latex. ZAR1 is a conserved and distinctive coiled-coil nucleotide-binding leucine-rich (CNL) repeat in the plant kingdom, playing a crucial role in disease-resistance processes. To elucidate the function of the HbZAR1 gene in rubber trees (Hevea brasiliensis), three candidate HbZAR1 genes were identified using bioinformatics methods and comprehensively analyzed. The results indicate that the HbZAR1 protein is conserved in different plant species. Examination of cis-regulatory element sequences of HbZAR1genes reveals that the HbZAR1 gene promoter exhibits a remarkable enrichment of stress, light, and hormone elements. An expression analysis shows that the expression levels of the three HbZAR1 genes are highest in the bark and lowest in latex. Three HbZAR1 genes can respond to both rubber tree Erysiphe quercicola and Colletotrichum siamense infection; especially, HbZAR1.1 and HbZAR1.2 show significant upregulation in expression levels during the early stages of infection. These findings suggest that the three HbZAR1 genes may be involved in rubber tree susceptibility to E. quercicola and C. siamense through different immune mechanisms. Subcellular localization results indicate that the HbZAR1 genes are expressed in the nucleus and plasma membrane. This study also shows that the three HbZAR1 genes and activated mutant HbZAR1.1^D481V do not induce stable ROS production and cell death, suggesting possible gene degradation, functional redundancy, or acting as minor genes in disease resistance. This research provides valuable insights for further studying the function of HbZAR1 genes in rubber trees and the mechanisms of immune molecules. Full article