Incorporating green chemistry concepts into nanotechnology is an important focus area in nanoscience. The demand for green metal oxide nanoparticle production has grown in recent years. The ...beneficial effects of using nanoparticles in agriculture have already been established. Here, we highlight some potential antifungal properties of Zizyphus spina leaf extract-derived copper oxide nanoparticles (CuO-Zs-NPs), produced with a spherical shape and defined a 13-30 nm particle size. Three different dosages of CuO-Zs-NPs were utilized and showed promising antifungal efficacy in vitro and in vivo against the selected fungal strain of F. solani causes tomato root rot disease, which was molecularly identified with accession number (OP824846). In vivo results indicated that, for all CuO-Zs-NPs concentrations, a significant reduction in Fusarium root rot disease occurred between 72.0 to 88.6% compared to 80.5% disease severity in the infected control. Although treatments with either the chemical fungicide (Kocide 2000) showed a better disease reduction and incidence with (18.33% and 6.67%) values, respectively, than CuO-Zs-NPs at conc. 50 mg/l, however CuO-Zs-NPs at 250 mg/l conc. showed the highest disease reduction (9.17 ± 2.89%) and lowest disease incidence (4.17 ± 3.80%). On the other hand, CuO-Zs-NPs at varied values elevated the beneficial effects of tomato seedling vigor at the initial stages and plant growth development compared to either treatment with the commercial fungicide or Trichoderma Biocide. Additionally, CuO-Zs-NPs treatments introduced beneficial results for tomato seedling development, with a significant increase in chlorophyll pigments and enzymatic activity for CuO-Zs-NPs treatments. Additionally, treatment with low concentrations of CuO-Zs-NPs led to a rise in the number of mature pollen grains compared to the immature ones. however the data showed that CuO-Zs-NPs have a unique antifungal mechanism against F. solani, they subsequently imply that CuO-Zs-NPs might be a useful environmentally friendly controlling agent for the Fusarium root rot disease that affects tomato plants.
Plant-derived natural products have long been considered a valuable source of lead compounds for drug development. Natural extracts are usually composed of hundreds to thousands of metabolites, ...whereby the bioactivity of natural extracts can be represented by synergism between several metabolites. However, isolating every single compound from a natural extract is not always possible due to the complex chemistry and presence of most secondary metabolites at very low levels. Metabolomics has emerged in recent years as an indispensable tool for the analysis of thousands of metabolites from crude natural extracts, leading to a paradigm shift in natural products drug research. Analytical methods such as mass spectrometry (MS) and nuclear magnetic resonance (NMR) are used to comprehensively annotate the constituents of plant natural products for screening, drug discovery as well as for quality control purposes such as those required for phytomedicine. In this review, the current advancements in plant sample preparation, sample measurements, and data analysis are presented alongside a few case studies of the successful applications of these processes in plant natural product drug discovery.
Cancer remains one of the most lethal diseases worldwide. There is an urgent need for new drugs with novel modes of action and thus considerable research has been conducted for new anticancer drugs ...from natural sources, especially plants, microbes and marine organisms. Marine populations represent reservoirs of novel bioactive metabolites with diverse groups of chemical structures. This review highlights the impact of marine organisms, with particular emphasis on marine plants, algae, bacteria, actinomycetes, fungi, sponges and soft corals. Anti-cancer effects of marine natural products in in vitro and in vivo studies were first introduced; their activity in the prevention of tumor formation and the related compound-induced apoptosis and cytotoxicities were tackled. The possible molecular mechanisms behind the biological effects are also presented. The review highlights the diversity of marine organisms, novel chemical structures, and chemical property space. Finally, therapeutic strategies and the present use of marine-derived components, its future direction and limitations are discussed.
Quercetin (QtN) displays low systemic bioavailability caused by poor water solubility and instability. Consequently, it exerts limited anticancer action in vivo. One solution to increase the ...anticancer efficacy of QtN is the use of appropriate functionalized nanocarriers that preferentially target and deliver the drug to the tumor location. Herein, a direct advanced method was designed to develop water-soluble hyaluronic acid (HA)-QtN-conjugated silver nanoparticles (AgNPs). HA-QtN reduced silver nitrate (AgNO
) while acting as a stabilizing agent to produce AgNPs. Further, HA-QtN#AgNPs served as an anchor for folate/folic acid (FA) conjugated with polyethylene glycol (PEG). The resulting PEG-FA-HA-QtN#AgNPs (further abbreviated as PF/HA-QtN#AgNPs) were characterized both in vitro and ex vivo. Physical characterizations included UV-visible (UV-Vis) spectroscopy, Fourier transform infrared (FTIR) spectroscopy, transmission electron microscopy (TEM), particle size (PS) and zeta potential (ZP) measurements, and biopharmaceutical evaluations. The biopharmaceutical evaluations included analyses of the cytotoxic effects on the HeLa and Caco-2 cancer cell lines using the MTT assay; cellular drug intake into cancer cells using flow cytometry and confocal microscopy; and blood compatibility using an automatic hematology analyzer, a diode array spectrophotometer, and an enzyme-linked immunosorbent assay (ELISA). The prepared hybrid delivery nanosystem was hemocompatible and more oncocytotoxic than the free, pure QtN. Therefore, PF/HA-QtN#AgNPs represent a smart nano-based drug delivery system (NDDS) and could be a promising oncotherapeutic option if the data are validated in vivo.
In this research, two novel series of dibenzob,fazepines (14 candidates) were designed and synthesised based on the rigidification principle and following the reported doxorubicin's pharmacophoric ...features. The anti-proliferative activity was evaluated at the NCI against a panel of 60 cancer cell lines. Further, the promising candidates (5a-g) were evaluated for their ability to inhibit topoisomerase II, where 5e was noticed to be the most active congener. Moreover, its cytotoxicity was evaluated against leukaemia SR cells. Also, 5e arrested the cell cycle at the G1 phase and increased the apoptosis ratio by 37.34%. Furthermore, in vivo studies of 5e showed the inhibition of tumour proliferation and the decrease in its volume. Histopathology and liver enzymes were examined as well. Besides, molecular docking, physicochemical, and pharmacokinetic properties were carried out. Finally, a SAR study was discussed to open the gate for further optimisation of the most promising candidate (5e).
Highlights
Two novel series of dibenzob,fazepines were designed and synthesised based on the rigidification principle in drug design.
The anti-proliferative activity was evaluated at the NCI against a panel of 60 cancer cell lines.
5e was the most active anti-topo II congener (IC
50
= 6.36 ± 0.36 µM).
5e was evaluated against leukaemia SR cells and its cytotoxic effect was confirmed (IC
50
= 13.05 ± 0.62 µM).
In vivo studies of 5e significantly inhibited tumour proliferation by 62.7% and decreased tumour volume to 30.1 mm
3
compared to doxorubicin treatment.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
In this study, a deep learning-based attack detection model is proposed to address the problem of system disturbances in energy systems caused by natural events like storms and tornadoes or ...human-made events such as cyber-attacks. The proposed model is trained using the long time recorded data through accurate phasor measurement units (PMUs). The data is then sent to various machine learning methods based on the effective features extracted out using advanced principal component analysis (PCA) model. The performance of the proposed model is examined and compared with some other benchmarks using various indices such as confusion matrix. The results show that incorporating PCA as the feature selection model could effectively decrease feature redundancy and learning time while minimizing data information loss. Furthermore, the proposed model investigates the potential of deep learning-based and Decision Tree (DT) classifiers to detect cyber-attacks for improving the security and efficiency of modern intelligent energy grids. By utilizing the big data recorded by PMUs and identifying relevant properties or characteristics using PCA, the proposed deep model can effectively detect attacks or disturbances in the system, allowing operators to take appropriate action and prevent any further damage.
Starches from different botanical sources are affected in the presence of enzymes. This study investigated the impact of α-amylase on several properties of pre-gelatinized starches derived from ...chickpea (Cicer arietinum L.), wheat (Triticum aestivum L.), corn (Zea mays L.), white beans (Phaseolus vulgaris), and sweet potatoes (Ipomoea batatas L.). Specifically, the water holding capacity, freezable water content, sugar content, and water sorption isotherm (adsorption and desorption) properties were examined. The source of α-amylase utilized in this study was a germinated sorghum (Sorghum bicolor L. Moench) extract (GSE). The starch samples were subjected to annealing at temperatures of 40, 50, and 60 °C for durations of either 30 or 60 min prior to the process of gelatinization. A significant increase in the annealing temperature and GSE resulted in a notable enhancement in both the water-holding capacity and the sugar content of the starch. The ordering of starches in terms of their freezable water content is as follows: Chickpea starch (C.P.S) > white beans starch (W.B.S) > wheat starch (W.S) > chickpea starch (C.S) > sweet potato starch (S.P.S). The Guggenheim-Anderson-de Boer (GAB) model was only employed for fitting the data, as the Brunauer–Emmett–Teller (BET) model had a low root mean square error (RMSE). The application of annealing and GSE treatment resulted in a shift of the adsorption and desorption isotherms towards greater levels of moisture content. A strong hysteresis was found in the adsorption and desorption curves, notably within the water activity range of 0.6 to 0.8. The GSE treatment and longer annealing time had an impact on the monolayer water content (mo), as well as the C and K parameters of the GAB model, irrespective of the annealing temperature. These results can be used to evaluate the applicability of starch in the pharmaceutical and food sectors.
The study aims to develop new approach for soil suitability evaluation, Based on the fact that choosing the proper agricultural sites is a requirement for good ergonomic and financial feasibility. ...The AHP included a selection of different criteria used for analysis and categorized according to their usefulness in relation to the growth conditions/requirements of the selected crops. Lithology, soil physicochemical, topography (slope and elevation), climate (temperature and rainfall), and irrigation water were the main criteria selected for the study. The study indicated that the area is suitable for agricultural use, taking into account the quality of the water used to maintain the quality of the soil. According to the FAO the suitability result was for S1 (0.71%), S2 (19.81%), S3 (41.46%), N1 (18.33%) and N2 (19.68%) of the total area. While the results obtained from the new approach for the study 9.51%, 30.82%, 40.12% and 19.54 for very high, high, moderate, low and very low suitability respectively, Taking into account that the constraints units of FAO is located in very low suitability class with 0.69% of the total area which Not valid for crop production due to some restrictions. The findings of the study will help narrow the area to the suitable sites that may further be sustainably used for annual and/or perennial crops. The proposed approach has high potential in applications for assessing land conditions and can facilitate optimal planning for agricultural use.
The effectiveness of hydrocolloids (2% maximum in various combinations) from various sources, including maltodextrins (MD) with polymerization degree (DP) 18 and ziziphus gum (ZG), on the dough ...properties and quality of panned bread, as well as the possibility of using them to delay the bread staling process, have been investigated after 24, 72, and 96 h of storage. By evaluating the pasting capabilities of wheat flour slurry, dough properties, and the final product, the effects of the ziziphus gum (ZG) and maltodextrins (MD) were ascertained. A TA-TXT texture analyzer, a texture profile analysis test, and Micro-doughLab were used to evaluate the dough mixing properties. Additionally, a hedonic sensory evaluation of the overall acceptance of the bread, as well as its texture, aroma, taste, and color, was done. It is clear that MD had a more distinct impact than ZG on the way dough was mixed, the texture of the gel, and the finished product. The combination of MD and ZG significantly altered the bread's physical characteristics and its aging over time. The decreased peak viscosity and noticeably smaller setback of wheat flour gels, which corresponded to lower gel hardness, serve as evidence of reduced amylose retrogradation. At 2%, MD outperformed ZG in terms of increasing water absorption, dough stability, and bread loaf volume. With the exception of the blend that included three times as much MD as ZG, all mixes, including the control, exhibited an increase in bread firmness as a function of time after storage. Overall, the panelists liked (score of 5 and above) the bread made with mixes that had either MD or ZG, or a combination of both.
A deep understanding of the causes of liability to SARS-CoV-2 is essential to develop new diagnostic tests and therapeutics against this serious virus in order to overcome this pandemic completely. ...In the light of the discovered role of antimicrobial peptides such as human b-defensin-2 (hBD-2) and cathelicidin LL-37 in the defense against SARS-CoV-2, it became important to identify the damaging missense mutations in the genes of these molecules and study their role in the pathogenesis of COVID-19.
We conducted a comprehensive analysis with multiple in silico approaches to identify the damaging missense SNPs for hBD-2 and LL-37; moreover, we applied docking methods and molecular dynamics analysis to study the impact of the filtered mutations.
The comprehensive analysis reveals the presence of three damaging SNPs in hBD-2; these SNPs were predicted to decrease the stability of hBD-2 with a damaging impact on hBD-2 structure as well. G51D and C53G mutations were located in highly conserved positions and were associated with differences in the secondary structures of hBD-2. Docking-coupled molecular dynamics simulation analysis revealed compromised binding affinity for hBD-2 SNPs towards the SARS-CoV-2 spike domain. Different protein-protein binding profiles for hBD-2 SNPs, in relation to their native form, were guided through residue-wise levels and differential adopted conformation/orientation.
The presented model paves the way for identifying patients prone to COVID-19 in a way that would guide the personalization of both the diagnostic and management protocols for this serious disease.
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