Poly(A)-binding protein promotes VPg-dependent translation of potyvirus through enhanced binding of phosphorylated eIFiso4F and eIFiso4F∙eIF4B

The phosphorylation of eukaryotic translational initiation factors has been shown to play a significant role in controlling the synthesis of protein. Viral infection, environmental stress, and growth circumstances cause phosphorylation or dephosphorylation of plant initiation factors. Our findings indicate that casein kinase 2 can phosphorylate recombinant wheat eIFiso4E and eIFiso4G generated from E. coli in vitro. For wheat eIFiso4E, Ser-207 was found to be the in vitro phosphorylation site. eIFiso4E lacks an amino acid that can be phosphorylated at the position corresponding to Ser-209, the phosphorylation site in mammalian eIF4E, yet phosphorylation of eIFiso4E has effects on VPg binding affinity that are similar to those of phosphorylation of mammalian eIF4E. The addition of VPg and phosphorylated eIFiso4F to depleted wheat germ extract (WGE) leads to enhancement of translation of both uncapped and capped viral mRNA. The addition of PABP together with eIFiso4Fp and eIF4B to depleted WGE increases both uncapped and capped mRNA translation. However, it exhibits a translational advantage specifically for uncapped mRNA, implying that the phosphorylation of eIFiso4F hinders cap binding while promoting VPg binding, thereby facilitating uncapped translation. These findings indicate TEV virus mediates VPg-dependent translation by engaging a mechanism entailing phosphorylated eIFiso4Fp and PABP. To elucidate the molecular mechanisms underlying these observed effects, we studied the impact of PABP and/or eIF4B on the binding of VPg with eIFiso4Fp. The inclusion of PABP and eIF4B with eIFiso4Fp resulted in about 2-fold increase in affinity for VPg (Kd = 24 ± 1.7 nM), as compared to the affinity of eIFiso4Fp alone (Kd = 41.0 ± 3.1 nM). The interactions between VPg and eIFiso4Fp were determined to be both enthalpically and entropically favorable, with the enthalpic contribution accounting for 76-97% of the ΔG at 25°C, indicating a substantial role of hydrogen bonding in enhancing the stability of the complex. The binding of PABP to eIFiso4Fp·4B resulted in a conformational alteration, leading to a significant enhancement in the binding affinity to VPg. These observations suggest PABP enhances the affinity between eIFiso4Fp and VPg, leading to an overall conformational change that provides a stable platform for efficient viral translation.

Di- and Tricyanovinyl-Substituted Triphenylamines: Structural and Computational Studies

We report herein on the solid-state structures of three closely related triphenylamine derivatives endowed with tricyanovinyl (TCV) and dicyanovinyl (DCV) groups. The molecules described contain structural features commonly found in the design of functional organic materials, especially donor-acceptor molecular and polymeric architectures. The common feature noticeable in these structures is the impact of these exceptionally strong electron-accepting groups in forcing partial planarity of the portion of the molecule carrying these groups and directing the molecular packing in the solid state, resulting in the formation of π-stacks of dimers within the unit cell of each. Stacks are formed between phenyl groups bearing electron-accepting groups on two adjacent molecules. Short π-π stack distances ranging from 3.283 to 3.671 Å were observed. Such motif patterns are thought to be conducive for better charge transport in organic semiconductors and enhanced device performance. Intramolecular charge transfer is evident from the shortening of the observed experimental bond lengths in all three compounds. The nitrogen atoms (of the cyano groups) have been shown to be extensively involved in short contacts in all three structures, primarily through C-H···NC interactions with distances as short as 2.462 Å. The compounds reported here are (3,3-dicyano-2-(4-(diphenylamino)phenyl)-1λ3-allylidene)amide or tricyanovinyltriphenylamine, Ph3NTCV (1); 2-(4-(diphenylamino)benzylidene)-malononitrile or dicyanovinyltriphenylamine, Ph3NDCV (2); and (3,3-dicyano-2-(4-(di-p-tolylamino)phenyl)-1λ3-allylidene)amide or dimethyltricyanovinyltriphenylamine, Me2Ph3NTCV (3). Results of density functional theory calculations using DFT-B3LYP/6-31G(d,p) indicate the lowering of LUMO levels as a result of the introduction of these groups with band gaps of 3.13, 2.61, and 2.55 eV for compounds 1-3, respectively, compared with 4.65 eV calculated for triphenylamine. This is supported by the electronic and fluorescence spectra of these molecules with absorption λmax of 483, 515, and 545 nm for compounds 1, 2, and 3, respectively.

In Vivo Near-Infrared Fluorescence Resonance Energy Transfer (NIR-FRET) Imaging of MMP-2 in ALI/ARDS in LPS-Treated Mice

Matrix metalloproteinases (MMPs) are zinc-dependent proteinases that are capable of cleavage of extracellular matrix (ECM) proteins and enzymes and play an important role in lung dysfunction. Specifically, MMP-2 is produced in the lung by alveolar epithelial and endothelial cells and other immune cells, such as macrophages. MMP-2 regulatory pathway is initiated in alveolar macrophages during acute lung injury (ALI), which may increase pulmonary inflammation. Therefore, there is a critical need for fast and reliable techniques to track the acute respiratory distress syndrome (ARDS). Here, we describe near-infrared fluorescence resonance energy transfer (NI-FRET) MMP-2-based probe for the in vivo detection of ALI induced by lipopolysaccharides (LPS). LPS-induced MMP-2 was measured using near-infrared (NIR) imaging after 1, 2, 4, 5, and 24 h of LPS exposure. Our results were compared with the data obtained from ELISA and Western blotting, demonstrating that MMP-2 fluorescence probe provide a promising in vivo diagnostic tool for ALI/ARDS in infected mice.

Occupational Safety and Health for Adult Saudi Arabian Women: Utilizing National Anthropometric Data

In the last five years, the female labor force has increased rapidly in Saudi Arabia. This is due to the new government's vision to empower women. For many decades, Saudi females were excluded from working in certain fields due to cultural restrictions. Nowadays, Saudi women are not only joining the service workforce but are currently employed in more physically demanding careers, such as manufacturing and military jobs, which were previously dominated by males. It becomes necessary to design workplaces, tools, and equipment to safely accommodate the female physical attributes, which include body dimensions. This study presents the anthropometric measurements of Saudi Arabian adult females. In total, 504 female subjects aged 20-70 participated in the study. Thirty-eight body measurements, including weight and triceps skinfold, were taken in sitting and standing postures. The main contribution of this study is to provide a national anthropometric database of Saudi females, which is very limited, especially for females in the age groups under study. The availability of such data will allow foreign and local manufacturers to design usable and safe products and workspaces for a wide range of Saudi adult females. The findings reveal that there are no significant differences in the body dimensions of Saudi females across all age groups, except for stature height, eye height, chest depth, skinfold (mm), sitting height, buttock-knee length, and hip breadth. The study also reveals that Saudi females' body sizes are different from other Asian, Middle Eastern, and British nations, which invalidates the assumption of using other nations' body measurements to estimate Saudis' body measurements. Utilizing the supermarket cashier workstation to assess the appropriateness of commercial station fit for Saudi females' body dimensions, the results underscore the crucial role of anthropometric measurements in addressing differences between product design and the unique body dimensions of Saudi females. The identified anthropometric mismatch highlights potential risks, emphasizing the threat to the working safety of Saudi females. Moreover, the data can be used by health professionals as a base to evaluate the health of Saudi adult females. Descriptive statistics and extreme values are determined. The data are presented in standard anthropometric tables.

A Comprehensive Study of Electronic, Optical, and Thermoelectric Characteristics of Cs2PbI2Br2 Inorganic Layered Ruddlesden-Popper Mixed Halide Perovskite through Systematic First-Principles Analysis

In this research, we present a comprehensive study on the influence of layer-dependent structural, electronic, and optical properties in the two-dimensional (2D) Ruddlesden-Popper (RP) perovskite Cs2PbI2Br2. Employing first-principles computations within the density functional theory method, including spin orbit coupling contribution, we examine the impact of various factors on the material. Our results demonstrate that the predicted 2D-layered RP perovskite Cs2PbI2Br2 structures exhibit remarkable stability both structurally and energetically, making them promising candidates for experimental realization. Furthermore, we observe that the electronic band gap and optical absorption coefficients of Cs2PbI2Br2 strongly depend on the thickness variation of the layers. Interestingly, Cs2PbI2Br2 exhibits a notable absorption coefficient in the visible region. Using a combination of density functional theory and Boltzmann transport theory, the thermoelectric properties were forecasted. The calculation involved determining the Seebeck coefficient (S) and other associated thermoelectric characteristics, such as electronic and thermal conductivities, as they vary with the chemical potential at room temperature. These findings open up exciting opportunities for the application of this 2D RP perovskite in solar cells and thermoelectric devices, owing to its unique properties.

Low-Cost Point-of-Care Monitoring of ALT and AST Is Promising for Faster Decision Making and Diagnosis of Acute Liver Injury

Alanine aminotransferase (ALT) and aspartate aminotransferase (AST) are important liver enzymes in clinical settings. Their levels are known to be elevated in individuals with underlying liver diseases and those consuming hepatotoxic drugs. Serum ALT and AST levels are crucial for diagnosing and assessing liver diseases. Serum ALT is considered the most reliable and specific candidate as a disease biomarker for liver diseases. ALT and AST levels are routinely analyzed in high-risk individuals for the bioanalysis of both liver function and complications associated with drug-induced liver injury. Typically, ALT and AST require blood sampling, serum separation, and testing. Traditional methods require expensive or sophisticated equipment and trained specialists, which is often time-consuming. Therefore, developing countries have limited or no access to these methods. To address the above issues, we hypothesize that low-cost biosensing methods (paper-based assays) can be applied to the analysis of ALT and AST levels in biological fluids. The paper-based biodetection technique can semi-quantitatively measure ALT and AST from capillary finger sticks, and it will pave the way for the development of an inexpensive and rapid alternative method for the early detection and diagnosis of liver diseases. This method is expected to significantly reduce the economic burden and aid routine clinical analysis in both developed and underdeveloped countries. The development of low-cost testing platforms and their diagnostic utility will be extremely beneficial in helping millions of patients with liver disorders.

Emerging Biosensing Methods to Monitor Lung Cancer Biomarkers in Biological Samples: A Comprehensive Review

Lung cancer is the most commonly diagnosed of all cancers and one of the leading causes of cancer deaths among men and women worldwide, causing 1.5 million deaths every year. Despite developments in cancer treatment technologies and new pharmaceutical products, high mortality and morbidity remain major challenges for researchers. More than 75% of lung cancer patients are diagnosed in advanced stages, leading to poor prognosis. Lung cancer is a multistep process associated with genetic and epigenetic abnormalities. Rapid, accurate, precise, and reliable detection of lung cancer biomarkers in biological fluids is essential for risk assessment for a given individual and mortality reduction. Traditional diagnostic tools are not sensitive enough to detect and diagnose lung cancer in the early stages. Therefore, the development of novel bioanalytical methods for early-stage screening and diagnosis is extremely important. Recently, biosensors have gained tremendous attention as an alternative to conventional methods because of their robustness, high sensitivity, inexpensiveness, and easy handling and deployment in point-of-care testing. This review provides an overview of the conventional methods currently used for lung cancer screening, classification, diagnosis, and prognosis, providing updates on research and developments in biosensor technology for the detection of lung cancer biomarkers in biological samples. Finally, it comments on recent advances and potential future challenges in the field of biosensors in the context of lung cancer diagnosis and point-of-care applications.

Aptasensors Are Conjectured as Promising ALT and AST Diagnostic Tools for the Early Diagnosis of Acute Liver Injury

Abnormal levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) in human serum are the most sensitive indicator of hepatocellular damage. Because liver-related health problems are directly linked to elevated levels of ALT and AST, it is important to develop accurate and rapid methods to detect these enzymes for the early diagnosis of liver disease and prevention of long-term liver damage. Several analytical methods have been developed for the detection of ALT and AST. However, these methods are based on complex mechanisms and require bulky instruments and laboratories, making them unsuitable for point-of-care application or in-house testing. Lateral flow assay (LFA)-based biosensors, on the other hand, provide rapid, accurate, and reliable results, are easy to operate, and are affordable for low-income populations. However, due to the storage, stability, batch-to-batch variations, and error margins, antibody-based LFAs are considered unaffordable for field applications. In this hypothesis, we propose the selection of aptamers with high affinity and specificity for the liver biomarkers ALT and AST to build an efficient LFA device for point-of-care applications. Though the aptamer-based LFA would be semiquantitative for ALT and AST, it would be an inexpensive option for the early detection and diagnosis of liver disease. Aptamer-based LFA is anticipated to minimize the economic burden. It can also be used for routine liver function tests regardless of the economic situation in each country. By developing a low-cost testing platform, millions of patients suffering from liver disease can be saved.

Iron response elements (IREs)-mRNA of Alzheimer's amyloid precursor protein binding to iron regulatory protein (IRP1): a combined molecular docking and spectroscopic approach

The interaction between the stem-loop structure of the Alzheimer's amyloid precursor protein IRE mRNA and iron regulatory protein was examined by employing molecular docking and multi-spectroscopic techniques. A detailed molecular docking analysis of APP IRE mRNA∙IRP1 reveals that 11 residues are involved in hydrogen bonding as the main driving force for the interaction. Fluorescence binding results revealed a strong interaction between APP IRE mRNA and IRP1 with a binding affinity and an average binding sites of 31.3 × 10⁶ M^-1 and 1.0, respectively. Addition of Fe²⁺(anaerobic) showed a decreased (3.3-fold) binding affinity of APP mRNA∙IRP1. Further, thermodynamic parameters of APP mRNA∙IRP1 interactions were an enthalpy-driven and entropy-favored event, with a large negative ΔH (-25.7 ± 2.5 kJ/mol) and a positive ΔS (65.0 ± 3.7 J/mol·K). A negative ΔH value for the complex formation suggested the contribution of hydrogen bonds and van der Waals forces. The addition of iron increased the enthalpic contribution by 38% and decreased the entropic influence by 97%. Furthermore, the stopped-flow kinetics of APP IRE mRNA∙IRP1 also confirmed the complex formation, having the rate of association (k_on) and the rate of dissociation (k_off) as 341 μM^-1 s^-1, and 11 s^-1, respectively. The addition of Fe²⁺ has decreased the rate of association (k_on) by ~ three-fold, whereas the rate of dissociation (k_off) has increased by ~ two-fold. The activation energy for APP mRNA∙IRP1 complex was 52.5 ± 2.1 kJ/mol. The addition of Fe²⁺ changed appreciably the activation energy for the binding of APP mRNA with IRP1. Moreover, circular dichroism spectroscopy has confirmed further the APP mRNA∙IRP1 complex formation and IRP1 secondary structure change with the addition of APP mRNA. In the interaction between APP mRNA and IRP1, iron promotes structural changes in the APP IRE mRNA∙IRP1 complexes by changing the number of hydrogen bonds and promoting a conformational change in the IRP1 structure when it is bound to the APP IRE mRNA. It further illustrates how IRE stem-loop structure influences selectively the thermodynamics and kinetics of these protein-RNA interactions.

Interplay between personality traits and learning strategies: the missing link

Students with varying personality traits are likely to employ diverse learning and study strategies. However, this relationship has never been explored in the medical education context. This study's aim was to explore the relationship between learning strategies and personality traits among medical students. This study was a cross-sectional study, and a quantitative approach was employed using two self-administered questionnaires: one to assess the personality traits from the Five-Factor Model (Conscientiousness, Neuroticism, Extraversion, Openness, and Agreeableness), and the other to assess 10 learning strategies (Anxiety, Attitude, Concentration, Information Processing, Motivation, Selecting Main Ideas, Self-Testing, Test Strategies, Time Management, and Using Academic Resources). A stratified random sampling technique was used to recruit medical students at Alfaisal University in the preclinical and clinical years (N = 309). Pearson correlation coefficient was used to measure the relationship between variables, and linear regression was used to evaluate how personality traits predicted learning strategy selection. Personality traits predicted the selection of learning strategies, especially Conscientiousness and Neuroticism. Conscientiousness showed a positive correlation with seven learning strategies and was the most important predictor of learning strategies students employ. Neuroticism correlations and predictions were negative. The other three traits showed weaker correlations. These correlations were between Extraversion and Using Academic Resources (r = 0.27), Information Processing (r = 0.23), and Attitude (r = 0.19); Openness and Information Processing (r = 0.29); and Agreeableness and Attitude (r = 0.29). All personality domains influence at least one learning strategy, especially Conscientiousness and Neuroticism. This study helps build a foundation for individualized coaching and mentorship in medical education.NEW & NOTEWORTHY This study aspires to build a foundation for individualized coaching and mentorship in medical education through utilizing personality traits to empower academic success. We demonstrate that all personality domains influence students' selection of at least one learning strategy, especially Conscientiousness and Neuroticism.

Toward efficient dye degradation and the bactericidal behavior of Mo-doped La2O3 nanostructures

In this study, different concentrations (0, 0.02, 0.04, and 0.06 wt%) of Mo doped onto La2O3 nanostructures were synthesized using a one-pot co-precipitation process. The aim was to study the ability of Mo-doped La2O3 samples to degrade toxic methylene blue dye in different pH media. The bactericidal potential of synthesized samples was also investigated. The structural properties of prepared samples were examined by XRD. The observed XRD spectrum of La2O3 showed a cubic and hexagonal structure, while no change was recorded in Mo-doped La2O3 samples. Doping with Mo improved the crystallinity of the samples. UV-Vis spectrophotometry and density functional theory calculations were used to assess the optical characteristics of Mo-La2O3. The band gap energy was reduced while the absorption spectra showed prominent peaks due to Mo doping. The HR-TEM results revealed the rod-like morphology of La2O3. The rod-like network appeared to become dense upon doping. A significant degradation of MB was confirmed with Mo; furthermore, the bactericidal activities against S. aureus and E. coli were measured as 5.05 mm and 5.45 mm inhibition zones, respectively, after doping with a high concentration (6%) of Mo.

Phosphorylation of eukaryotic initiation factor eIFiso4E enhances the binding rates to VPg of turnip mosaic virus

Binding of phosphorylated eIFiso4E with viral genome-linked protein (VPg) of turnip mosaic virus was examined by stopped-flow, fluorescence, circular dichroism (CD) spectroscopy, and molecular docking analysis. Phosphorylation of eIFiso4E increased (4-fold) the binding rates as compared to unphosphorylated eIFiso4E with VPg. Stopped-flow kinetic studies of phosphorylated eIFiso4E with VPg showed a concentration-independent conformational change. The dissociation rate was about 3-fold slower for eIFiso4E∙VPg complex upon phosphorylation. Phosphorylation enhanced the association rates and lowered the dissociation rates for the eIFiso4E∙VPg binding, with having higher preferential binding to eIFiso4Ep. Binding rates for the interaction of eIFiso4Ep with VPg increased (6-fold) with an increase in temperature, 278 K to 298 K. The activation energies for binding of eIFiso4Ep and eIFiso4E with VPg were 37.2 ± 2.8 and 52.6 ± 3.6 kJ/mol, respectively. Phosphorylation decreased the activation energy for the binding of eIFiso4E to VPg. The reduced energy barrier suggests more stable platform for eIFiso4Ep∙VPg initiation complex formation, which was further supported by molecular docking analysis. Moreover, far-UV CD studies revealed that VPg formed complex with eIFiso4Ep with substantial change in the secondary structure. These results suggested that phosphorylation, not only reduced the energy barrier and dissociation rate but also enhanced binding rate, and an overall conformational change, which provides a more stable platform for efficient viral translation.

A smart healthcare framework for detection and monitoring of COVID-19 using IoT and cloud computing

Coronavirus (COVID-19) is a very contagious infection that has drawn the world's attention. Modeling such diseases can be extremely valuable in predicting their effects. Although classic statistical modeling may provide adequate models, it may also fail to understand the data's intricacy. An automatic COVID-19 detection system based on computed tomography (CT) scan or X-ray images is effective, but a robust system design is challenging. In this study, we propose an intelligent healthcare system that integrates IoT-cloud technologies. This architecture uses smart connectivity sensors and deep learning (DL) for intelligent decision-making from the perspective of the smart city. The intelligent system tracks the status of patients in real time and delivers reliable, timely, and high-quality healthcare facilities at a low cost. COVID-19 detection experiments are performed using DL to test the viability of the proposed system. We use a sensor for recording, transferring, and tracking healthcare data. CT scan images from patients are sent to the cloud by IoT sensors, where the cognitive module is stored. The system decides the patient status by examining the images of the CT scan. The DL cognitive module makes the real-time decision on the possible course of action. When information is conveyed to a cognitive module, we use a state-of-the-art classification algorithm based on DL, i.e., ResNet50, to detect and classify whether the patients are normal or infected by COVID-19. We validate the proposed system's robustness and effectiveness using two benchmark publicly available datasets (Covid-Chestxray dataset and Chex-Pert dataset). At first, a dataset of 6000 images is prepared from the above two datasets. The proposed system was trained on the collection of images from 80% of the datasets and tested with 20% of the data. Cross-validation is performed using a tenfold cross-validation technique for performance evaluation. The results indicate that the proposed system gives an accuracy of 98.6%, a sensitivity of 97.3%, a specificity of 98.2%, and an F1-score of 97.87%. Results clearly show that the accuracy, specificity, sensitivity, and F1-score of our proposed method are high. The comparison shows that the proposed system performs better than the existing state-of-the-art systems. The proposed system will be helpful in medical diagnosis research and healthcare systems. It will also support the medical experts for COVID-19 screening and lead to a precious second opinion.