Search Results (13)

The algae-derived bio-binder (ADBB) from hydrothermal liquefaction has been reported to be an effective and sustainable new alternative to petroleum-based curing agents for epoxy resin. However, there is still room for the epoxy/ADBB system to attain the comprehensive mechanical performance of conventional epoxy-based nanocomposites, typically reinforced with surface-functionalized nanofillers (e.g., glass nanoparticles (GNPs)) by petroleum-based silane coupling agents. Herein, we explored the use of ADBB as an innovative surface-modifying agent to functionalize GNPs and evaluated the potential of ADBB surface-functionalized GNPs (ADBB-GNPs) as a reinforcing agent in the epoxy/ADBB matrix nanocomposite by comparing them to pristine GNPs and (3-aminopropyl) triethoxysilane (APTES) (a popular silane coupling agent) surface-modified GNPs (APTES-GNPs). The surface functionalization of GNPs with ADBB was carried out and characterized by scanning electron microscopy (SEM), dynamic light scattering (DLS), and Fourier-transform infrared spectroscopy (FTIR). Material performance including tensile, flexural, and Izod impact properties and thermal properties of the resulting epoxy/ADBB nanocomposites were investigated by corresponding ASTM mechanical test standards and thermogravimetric analysis (TGA). Our results revealed that the ADBB is a sustainable and effective surface-modifying agent that can functionalize GNPs. The obtained ADBB-GNPs significantly improved the mechanical performance of the epoxy/ADBB system at ultra-low loading (0.5 wt.%) by up to 42% and the maximum decomposition rate temperature increased from 419 °C to 422 °C, both of which outperformed APTES-GNPs. This research sheds light on developing sustainable surface-modifying agents for nanofillers to create high-performance sustainable polymer composite materials. Full article

Background: The goal of this study was to evaluate the antitumor immune effects of B7-1 gene expression in addition to immune checkpoint inhibitor against squamous cell carcinoma. Methods: A murine SCC cell line, KLN205, was infected with adenoviral vector carrying B7-1 (AdB7). Infected cells were injected subcutaneously in the flanks of DBA/2 mice. Three weeks after implantation, anti-mouse PD-1 antibody (antiPD1) was intraperitonially administrated twice a week for a total of six times. Results: CD80 was significantly overexpressed in the AdB7-infected tumors. IFN-gamma in the T cells in the spleen was significantly increased and tumor size was significantly reduced in the mice treated with both AdB7 and antiPD1. Targeted tumors treated with both AdB7 and antiPD1 exhibited significantly increased cell densities of total immune cells as well as Ki-67+ CD8+ T cells and decreased regulatory T cells. Conclusions: These results suggest that the B7-1 gene transfer may enhance the antitumor effect of anti-PD1 antibody against SCC. Full article

This paper presents a variable-gain low-noise amplifier (VGLNA) based on an adaptive bias (ADB) circuit for the radar receiver front end. The ADB circuit processes the signal separated by a coupler at the LNA output port. First, the ADB circuit rectifies the coupled signal into positive DC voltage through a rectifier, which is then inverted to control a junction-gate field-effect transistor (JFET). The voltage-controlled current of JFET flows through a voltage-divider network and finally produces the DC biasing voltage for the BJT base termination, which decreases with the increase in the input RF power. The proposed VGLNA operates automatically in high gain at low input power and low gain at high input power, providing a wider dynamic range as compared to the constant-bias counterpart. For validation, a prototype is fabricated and measured at 6 GHz. As observed, the base biasing voltage generated by the ADB circuit is changed from 858 mV to 798 mV as the input power increases from −50 dBm to 0 dBm. As a result, the dynamic range represented by the input P1dB point (IP1dB) has an increase of 6.5 dB, while LNA still maintains a high gain of 15.15 dB at low input power. Full article

How to search for a convenient method without a complicated calculation process to predict the physicochemical properties of inorganic crystals through a simple micro-parameter is a greatly important issue in the field of materials science. Herein, this paper presents a new and facile technique for the comprehensive estimation of lattice energy (U), bulk modulus (B), chemical hardness (ƞ), and electronic polarizability (α), just by using a simple mathematic fitting formula with a few structure parameters, such as the systems of rock salt crystals (group I–VII, II–VI) and tetrahedral coordinated crystals (group II–VI, III–V). For the typical binary A^NB^8-N crystal systems, our present conclusions suggest that a good quantitative correlation between U, B, ƞ, α and chemical bond length (d) is observed, the normal mathematical expression is P = a·d^b (P represents these physicochemical parameters), constants a and b depend on the type of crystals, and the relevant squares of the correlation coefficient (R²) are larger than 0.9. The results indicate that lattice energy, bulk modulus, and chemical hardness decrease with increases in chemical bond length, but electronic polarizability increases with an increase in chemical bond length. Meanwhile, the new data on the lattice energy, bulk modulus, chemical hardness, and electronic polarizability values of binary A^NB^8-N crystal systems considered in the present study are calculated via the obtained curve fitting equations without any complex calculation process. We find that there is a very good linear trend in our calculated results along with the values reported in the literature. The present study will be important in solid-state chemistry, which may give researchers useful guidance in searching for relevant data for predicting the properties of new materials or synthetic routes based on a simple mathematic empirical model. Full article

In this study, we investigated the use of artificial intelligence algorithms (AIAs) in combination with VIS-NIR-SWIR hyperspectroscopy for the classification of eleven lettuce plant varieties. For this purpose, a spectroradiometer was utilized to collect hyperspectral data in the VIS-NIR-SWIR range, and 17 AIAs were applied to classify lettuce plants. The results showed that the highest accuracy and precision were achieved using the full hyperspectral curves or the specific spectral ranges of 400–700 nm, 700–1300 nm, and 1300–2400 nm. Four models, AdB, CN2, G-Boo, and NN, demonstrated exceptional R² and ROC values, exceeding 0.99, when compared between all models and confirming the hypothesis and highlighting the potential of AIAs and hyperspectral fingerprints for efficient, precise classification and pigment phenotyping in agriculture. The findings of this study have important implications for the development of efficient methods for phenotyping and classification in agriculture and the potential of AIAs in combination with hyperspectral technology. To advance our understanding of the capabilities of hyperspectroscopy and AIs in precision agriculture and contribute to the development of more effective and sustainable agriculture practices, further research is needed to explore the full potential of these technologies in different crop species and environments. Full article

Recently, the high demand for marble stones has progressed in the construction industry, ultimately resulting in waste marble production. Thus, environmental degradation is unavoidable because of waste generated from quarry drilling, cutting, and blasting methods. Marble waste is produced in an enormous amount in the form of odd blocks and unwanted rock fragments. Absence of a systematic way to dispose of these marble waste massive mounds results in environmental pollution and landfills. To reduce this risk, an effort has been made for the incorporation of waste marble powder into concrete for sustainable construction. Different proportions of marble powder are considered as a partial substitute in concrete. A total of 40 mixes are prepared. The effectiveness of marble in concrete is assessed by comparing the compressive strength with the plain mix. Supervised machine learning algorithms, bagging (Bg), random forest (RF), AdaBoost (AdB), and decision tree (DT) are used in this study to forecast the compressive strength of waste marble powder concrete. The models’ performance is evaluated using correlation coefficient (R²), root mean square error, and mean absolute error and mean square error. The achieved performance is then validated by using the k-fold cross-validation technique. The RF model, having an R² value of 0.97, has more accurate prediction results than Bg, AdB, and DT models. The higher R² values and lesser error (RMSE, MAE, and MSE) values are the indicators for better performance of RF model among all individual and ensemble models. The implementation of machine learning techniques for predicting the mechanical properties of concrete would be a practical addition to the civil engineering domain by saving effort, resources, and time. Full article

Zebrafish (ZF; Danio rerio) larvae have become a popular in vivo model in drug metabolism studies. Here, we investigated the metabolism of methyl 2-[1-(4-fluorobutyl)-1H-indazole-3-carboxamido]-3,3-dimethylbutanoate (4F-MDMB-BINACA) in ZF larvae after direct administration of the cannabinoid via microinjection, and we visualized the spatial distributions of the parent compound and its metabolites by mass spectrometry imaging (MSI). Furthermore, using genetically modified ZF larvae, the role of cannabinoid receptor type 1 (CB1) and type 2 (CB2) on drug metabolism was studied. Receptor-deficient ZF mutant larvae were created using morpholino oligonucleotides (MOs), and CB2-deficiency had a critical impact on liver development of ZF larva, leading to a significant reduction of liver size. A similar phenotype was observed when treating wild-type ZF larvae with 4F-MDMB-BINACA. Thus, we reasoned that the cannabinoid-induced impaired liver development might also influence its metabolic function. Studying the metabolism of two synthetic cannabinoids, 4F-MDMB-BINACA and methyl 2-(1-(5-fluoropentyl)-1H-pyrrolo[2,3-b]pyridine-3-carboxamido)-3,3-dimethylbutanoate (7′N-5F-ADB), revealed important insights into the in vivo metabolism of these compounds and the role of cannabinoid receptor binding. Full article

Staphylococcus epidermidis strains play an important role in nosocomial infections, especially in the ones associated with biofilm formation on medical devices. The paper was aimed at analyzing the mechanisms of antibiotic resistance and confirming the biofilm-forming ability among S. epidermidis strains isolated from the blood of hospitalized newborns. Genetic analysis of resistance mechanism determinants included multiplex PCR detection of mecA, ermA, ermB, ermC, msrA, and mef genes. Biofilm analysis comprised phenotypic and genotypic methods including Christensen and Freeman methods and PCR detection of the icaADB gene complex. Among the tested S. epidermidis strains, 89% of the isolates were resistant to methicillin, 67%—to erythromycin, 53%—to clindamycin, 63%—to gentamicin, and 23%—to teicoplanin, while all the strains were susceptible to vancomycin and linezolid. The mecA gene was detected in 89% of the isolates, the ermC gene was the most common and present among 56% of the strains, while the msrA gene was observed in 11% isolates. Eighty-five percent of the strains were described as biofilm-positive by phenotypic methods and carried the icaADB gene cluster. Multidrug resistance and the biofilm-forming ability in most of the strains tested may contribute to antimicrobial therapy failure (p < 0.05). Full article

Machine Learning (ML) algorithms provide an alternative for the prediction of pollutant concentration. We compared eight ML algorithms (Linear Regression (LR), uniform weighting k-Nearest Neighbor (UW-kNN), variable weighting k-Nearest Neighbor (VW-kNN), Support Vector Regression (SVR), Artificial Neural Network (ANN), Regression Tree (RT), Random Forest (RF), and Adaptive Boosting (AdB)) to evaluate the feasibility of ML approaches for estimation of Total Suspended Solids (TSS) using the national stormwater quality database. Six factors were used as features to train the algorithms with TSS concentration as the target parameter: Drainage area, land use, percent of imperviousness, rainfall depth, runoff volume, and antecedent dry days. Comparisons among the ML methods demonstrated a higher degree of variability in model performance, with the coefficient of determination (R²) and Nash–Sutcliffe (NSE) values ranging from 0.15 to 0.77. The Root Mean Square (RMSE) values ranged from 110 mg/L to 220 mg/L. The best fit was obtained using the AdB and RF models, with R² values of 0.77 and 0.74 in the training step and 0.67 and 0.64 in the prediction step. The NSE values were 0.76 and 0.72 in the training step and 0.67 and 0.62 in the prediction step. The predictions from AdB were sensitive to all six factors. However, the sensitivity level was variable. Full article

Zebrafish (Danio rerio) larvae have gained attention as a valid model to study in vivo drug metabolism and to predict human metabolism. The microinjection of compounds, oligonucleotides, or pathogens into zebrafish embryos at an early developmental stage is a well-established technique. Here, we investigated the metabolism of zebrafish larvae after microinjection of methyl 2-(1-(5-fluoropentyl)-1H-pyrrolo[2,3-b]pyridine-3-carboxamido)-3,3-dimethylbutanoate (7′N-5F-ADB) as a representative of recently introduced synthetic cannabinoids. Results were compared to human urine data and data from the in vitro HepaRG model and the metabolic pathway of 7′N-5F-ADB were reconstructed. Out of 27 metabolites detected in human urine samples, 19 and 15 metabolites were present in zebrafish larvae and HepaRG cells, respectively. The route of administration to zebrafish larvae had a major impact and we found a high number of metabolites when 7′N-5F-ADB was microinjected into the caudal vein, heart ventricle, or hindbrain. We further studied the spatial distribution of the parent compound and its metabolites by mass spectrometry imaging (MSI) of treated zebrafish larvae to demonstrate the discrepancy in metabolite profiles among larvae exposed through different administration routes. In conclusion, zebrafish larvae represent a superb model for studying drug metabolism, and when combined with MSI, the optimal administration route can be determined based on in vivo drug distribution. Full article

Sex determination and differentiation are nearly universal to all eukaryotic organisms, encompassing diverse systems and mechanisms. Here, we identified a spliceosomal protein gene BmSPX involved in sex determination of the lepidopeteran insect, Bombyx mori. In a transgenic silkworm line that overexpressed the BmSPX gene, transgenic silkworm males exhibited differences in their external genitalia compared to wild-type males, but normal internal genitalia. Additionally, transgenic silkworm females exhibited a developmental disorder of the reproductive organs. Upregulation of BmSPX significantly increased the expression levels of sex-determining genes (BmMasc and BmIMP) and reduced the female-type splice isoform of Bmdsx, which is a key switch gene downstream of the sex-determination pathway. Additionally, co-immunoprecipitation assays confirmed an interaction between the BmSPX protein and BmPSI, an upstream regulatory factor of Bmdsx. Quantitative real-time PCR showed that BmSPX over-expression upregulated the expression of the Hox gene abdominal-B (Adb-B), which is required for specification of the posterior abdomen, external genitalia, and gonads of insects, as well as the genes in the Receptor Tyrosine Kinase (RTK) signaling pathway. In conclusion, our study suggested the involvement of BmSPX, identified as a novel regulatory factor, in the sex-determination pathway and regulation of reproductive organ development in silkworms. Full article

In the silkworm, the sex-determination primary signal Fem controls sex differentiation by specific binding of Fem-derived piRNA to the cleavage site in Masc mRNA, thus inhibiting Masc protein production in the female. In this study, we identified a novel splicing isoform of Masc, named Masc-S, which lacks the intact sequence of the cleavage site, encoding a C-terminal truncated protein. Results of RT-PCR showed that Masc-S was expressed in both sexes. Over-expression of Masc-S and Masc in female-specific cell lines showed that Masc-S could be translated against the Fem-piRNA cut. By RNA-protein pull-down, LC/MS/MS, and EMSA, we identified a protein BmEXU that specifically binds to an exclusive RNA sequence in Masc compared to Masc-S. Knockdown of Masc-S resulted in abnormal morphology in female external genital and increased expression of the Hox gene Abd-B, which similarly occurred by Bmexu RNAi. These results suggest that the splice variant Masc-S against Fem-piRNA plays an important role in female external genital development, of which function is opposite to that of full-length Masc. Our study provides new insights into the regulatory mechanism of sex determination in the silkworm. Full article

This paper presents a basic model that shows the relationship between the diameter of a stem and its flexural rigidity. The model was developed from experimental measurements of biomechanical traits (i.e., tensile and bending traits like maximum forces, stresses, moduli of elasticity, flexural rigidity, strain) of three freshwater macrophyte species (Elodea canadensis Michx., Potamogeton pectinatus L., and P. crispus L.), reflecting the seasonal changes in plant biomechanics throughout the vegetative season. These were obtained with the use of a bench-top testing machine in 2016 and 2017. The presented calculations are based on the ratio of drag-to-bending forces, in which the flexural rigidity plays a key role. The proposed model has the form EI = ad^b, and two approaches based on a regression analysis were applied to determine the parameters of the model—a and b. In the first method, the parameters were identified separately for each day of measurement, while in the second method, the coefficient b was calculated for all data from all days as a unified number for individual plants. The results suggest that coefficient b may provide information about the proportion of changes in drag forces depending on plant stiffness. The values of this coefficient were associated with the shape of the stem cross-section. The more circular the cross-section, the closer the value of the parameter was to 1. The parameter values were 1.60 for E. canadensis, 1.98 for P. pectinatus, and 2.46 for P. crispus. Moreover, this value also depended on the density of the cross-section structure. Most of the results showed that with an increase in stem diameter, the ratio between the drag and bending forces decreased, which led to fewer differences between these two forces. The model application may be introduced in many laboratory measurements of flow–biota interactions as well as in aquatic plant management applications. The implementation of these results in control methods for hydrophytes may help in mitigating floods caused by increases to a river channel’s resistance due to the occurrence of plants. Full article