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Abstract In this work, a heat transfer model is developed for thermally-driven material extrusion additive manufacturing of semicrystalline polymers that considers the heat generated during crystallization by coupling crystallization kinetics with heat transfer. The materials used in this work are Technomelt PA 6910, a semicrystalline hot melt adhesive with sub-ambient glass transition temperature (Tg) and slow crystallization, and PA 6/66, a traditional semicrystalline polyamide with a higher Tg and fast crystallization. The coupled model shows that the released heat during crystallization depends on material selection, with Technomelt PA 6910 and PA 6/66’s temperatures increased by less than 1 °C and up to 6.3 °C, respectively, due to enthalpy of crystallization. Increasing the layer time decreases the layer temperature as well as the initial crystallinity. However, its effect on final crystallinity in Technomelt PA 6910 is negligible due to continued crystallization of the material after printing. Experimental validation shows good agreement for Technomelt PA 6910, but consistently underpredicts PA 6/66 crystallinity. Increasing modeled environmental temperature leads to better agreement with experimental results for PA 6/66, suggesting that higher temperatures may have been experienced. Shear-induced crystallization may also be contributing to crystallinity in this material. The results from this model highlight the importance of and interrelationships between material and processing parameter selection and can aid in achieving quality prints from semicrystalline thermoplastics.

Abstract This research explores the application of Artificial Intelligence (AI) techniques to assess the mechanical properties of geopolymer concrete made from a blend of Banana Peel-Ash (BPA) and Sugarcane Bagasse Ash (SCBA), using a sodium silicate (Na2SiO3) to sodium hydroxide (NaOH) ratio ranging from 1.5 to 3. Utilizing three AI methodologies—Artificial Neural Networks (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), and Gene Expression Programming (GEP)—the study aims to enhance prediction accuracy for the mechanical properties of geopolymer concrete based on 104 datasets. By optimizing mix designs through varying proportions of BPA and SCBA, alkaline activator molarity, and aggregate-to-binder ratios, the research identified combinations that significantly enhance mechanical properties, demonstrating notable international relevance as it contributes to global efforts in sustainable construction by effectively utilizing industrial by-products. The experimental results demonstrated that increasing the molarity of the alkaline activator from 4 to 10 M significantly enhanced both the compressive and flexural strengths of the geopolymer concrete. Specifically, a mixture containing 52.5% SCBA and 47.5% BPA at a 10 M molarity achieved a maximum compressive strength of 33.17 MPa after 20 h of curing. In contrast, a mixture composed of 95% SCBA and 5% BPA at a 4 M molarity exhibited a substantially lower compressive strength of only 21.27 MPa. Additionally, the highest recorded flexural strength of 9.95 MPa (77.25% SCBA and 22.5 BPA) was observed at the 10 M molarity, while the flexural strength at 4 M was lowest, at 4.12 MPa (95% SCBA and 5% BPA). Microstructural analysis through Scanning Electron Microscopy with Energy-Dispersive X-ray Spectroscopy (ED-SEM) revealed insights into the pore structure and elemental composition of the concrete, while Thermogravimetric Analysis (TGA) provided data on the material’s thermal stability and decomposition characteristics. Performance analysis of the AI models showed that the ANN model had an average MSE of 1.338, RMSE of 1.157, MAE of 3.104, and R2 of 0.989, while the ANFIS model outperformed with an MSE of 0.345, RMSE of 0.587, MAE of 1.409, and R2 of 0.998. The GEP model demonstrated an MSE of 1.233, RMSE of 1.110, MAE of 1.828, and R2 of 0.992, confirming that ANFIS is the most accurate model for predicting the mechanical and rheological properties of geopolymer concrete. This study highlights the potential of integrating AI with experimental data to optimize the formulation and performance of geopolymer concrete, advancing sustainable construction practices by effectively utilizing industrial by-products.

Abstract The development of geopolymer concrete offers promising prospects for sustainable construction practices due to its reduced environmental impact compared to conventional Portland cement concrete. However, the complexity involved in geopolymer concrete mix design often poses challenges for engineers and practitioners. In response, this study proposes a simplified approach for designing geopolymer concrete mixtures, drawing upon principles from Portland cement concrete mix design standards and recommended molar ratios of oxides involved in geopolymer synthesis. The proposed methodology aims to streamline the mix design process while optimizing key factors such as chemical composition, alkali activation solution, water content, and curing conditions to achieve desired compressive strength and workability. By leveraging commonalities between Portland cement concrete and geopolymer concrete, this approach seeks to facilitate the adoption of geopolymer concrete in practical construction applications. The proposed mix design guidelines have been validated through examples for concrete cured under different conditions, including outdoor and oven curing. Future research should focus on validating the proposed methodology through experimental studies and exploring cost-effective alternatives for alkali activation solutions to enhance the feasibility and scalability of geopolymer concrete production. Overall, the proposed simplified approach holds promise for advancing the utilization of geopolymer concrete as a sustainable alternative in the construction industry.

Abstract There is conflicting evidence on the role of lipid biomarkers in breast cancer (BC), and no study to our knowledge has examined this association among African women. We estimated odds ratios (ORs) and 95% confidence intervals (95% CI) for the association of lipid biomarkers—total cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL), and triglycerides—with odds of BC overall and by subtype (Luminal A, Luminal B, HER2-enriched and triple-negative or TNBC) for 296 newly diagnosed BC cases and 116 healthy controls in Nigeria. Each unit standard deviation (SD) increase in triglycerides was associated with 39% increased odds of BC in fully adjusted models (aOR: 1.39; 95% CI: 1.03, 1.86). Among post-menopausal women, higher total cholesterol (aOR: 1.65; 95% CI: 1.06, 2.57), LDL cholesterol (aOR: 1.59; 95% CI: 1.04, 2.41), and triglycerides (aOR: 1.91; 95% CI: 1.21, 3.01) were associated with increased odds of BC. Additionally, each unit SD increase in LDL was associated with 64% increased odds of Luminal B BC (aOR 1.64; 95% CI: 1.06, 2.55). Clinically low HDL was associated with 2.7 times increased odds of TNBC (aOR 2.67; 95% CI: 1.10, 6.49). Among post-menopausal women, higher LDL cholesterol and triglycerides were significantly associated with increased odds of Luminal B BC and HER2 BC, respectively. In conclusion, low HDL and high LDL are associated with increased odds of TN and Luminal B BC, respectively, among African women. Future prospective studies can definitively characterize this association and inform clinical approaches targeting HDL as a BC prevention strategy.

The study aims to explore whether work-life balance mediates the impact of work-family conflict and its dimensions on psychological well-being. Using a survey method, data were collected from a sample of 258 working women in Hebei province in China. The analysis was carried out using IBM SPSS and the PROCESS macro in order to test the mediation model. The findings show that work-family conflict has an indirect effect on psychological well-being through work-life balance. In the case of work-to-family conflict, a suppression effect is detected in which the mediator shows an underlying relationship between the work-to-family conflict and psychological well-being. On the other hand, family-to-work conflict is fully moderated by work-life balance. Based on these results, it can be concluded that enhancing the quality of work-life balance may help to reduce the negative impact of work-family conflict on psychological health. The findings of this study can be beneficial to organizations and policy makers to formulate policies that would enhance the mental health and work productivity of women professionals in China. [ABSTRACT FROM AUTHOR]

Four hundred Phytochemical (bio-active) compounds having predictive activity for treating Sickle Cell Anemia were screened, using PASS online computational resource. Twenty-six compounds out of the four hundred compounds which showed high probability for treating sickle were further screened for pharmacokinetics profiles (ADMET properties) using SwissAdmet, AdmetSAR 2 and Pro-tox II online resources. Only thirteen compounds that displayed good ADMET properties from the twenty-six were further used for DFT calculations and molecular docking against carbonmonoxy sickle hemoglobin (PDB ID: 5E6E). Molecular docking analysis reinforced by DFT calculations showed that two compounds, phenanthrene-5,6-dione (A9) and 2-(3,4-dihydroxyphenyl)-5,7-dihydroxychromen-4-one (A13, Luteolin) had the best binding affinity of − 8.3 and − 8.9 kcal/mol, respectively, compared to voxelotor (GBT-440), a drug use in treating sickle cell disease. Molecular dynamic simulations showed that 2-(3,4-dihydroxyphenyl)-5,7-dihydroxychromen-4-one (A13, Luteolin) is highly stable with the protein than voxelotor. [ABSTRACT FROM AUTHOR]

One of the major attributes of boiled cassava roots is its ability to soften within a short period, otherwise known as mealiness. This study aimed to establish and validate standard operating procedures for assessing the mealiness of boiled cassava roots. Twenty cassava genotypes, including landrace and improved varieties, were selected for the protocol development, with an additional ten genotypes used for validation. Following cooking, the cassava roots were evaluated for hardness and work done in extrusion using a texturometer equipped with a five-blade Ottawa cell probe. The same samples were assessed for sensory texture analysis using trained panelists for parameters such as softness and chewiness. Pearson's correlation analysis revealed significant positive correlations (p < 0.01) between sensory softness and instrumental texture measurements, as well as between softness and cooking time (p < 0.01, r = 0.94), and between chewiness and cooking time (p < 0.05, r = 0.81). Validation results confirmed significant correlations (p < 0.01) between cooking time, sensory softness, and chewiness. These findings suggest that cooking time can serve as a reliable indicator, closely associated with sensory attributes, in determining the mealiness of boiled cassava roots. This approach offers a practical, mid-throughput method for assessing cassava root mealiness, with implications for breeding improved varieties, farmers adoption, and consumer acceptance. [ABSTRACT FROM AUTHOR]

Breast cancer remains a leading cause of cancer-related deaths among women globally, necessitating the development of more effective therapeutic agents with minimal side effects. This study explores novel 1,2,4-triazine-3(2H)-one derivatives as potential inhibitors of Tubulin, a pivotal protein in cancer cell division, highlighting a targeted approach in cancer therapy. Using an integrated computational approach, we combined quantitative structure–activity relationship (QSAR) modeling, ADMET profiling, molecular docking, and molecular dynamics simulations to evaluate and predict the efficacy and stability of these compounds. Our QSAR models, developed through rigorous statistical analysis, revealed that descriptors such as absolute electronegativity and water solubility significantly influence inhibitory activity, achieving a predictive accuracy (R2) of 0.849. Molecular docking studies identified compounds with high binding affinities, particularly Pred28, which exhibited the best docking score of − 9.6 kcal/mol. Molecular dynamics simulations conducted over 100 ns provided further insights into the stability of these interactions. Pred28 demonstrated notable stability, with the lowest root mean square deviation (RMSD) of 0.29 nm and root mean square fluctuation (RMSF) values indicative of a tightly bound conformation to Tubulin. The novelty of this work lies in its methodological rigor and the integration of multiple advanced computational techniques to pinpoint compounds with promising therapeutic potential. Our findings advance the current understanding of Tubulin inhibitors and open avenues for the synthesis and experimental validation of these compounds, aiming to offer new solutions for breast cancer treatment. [ABSTRACT FROM AUTHOR]

Free Fatty Acid Receptor 4 (FFAR4), a G-protein-coupled receptor, is responsible for triggering intracellular signaling pathways that regulate various physiological processes. FFAR4 agonists are associated with enhancing insulin release and mitigating the atherogenic, obesogenic, pro-carcinogenic, and pro-diabetogenic effects, normally associated with the free fatty acids bound to FFAR4. In this research, molecular structure-based machine-learning techniques were employed to evaluate compounds as potential agonists for FFAR4. Molecular structures were encoded into bit arrays, serving as molecular fingerprints, which were subsequently analyzed using the Bayesian network algorithm to identify patterns for screening the data. The shortlisted hits obtained via machine learning protocols were further validated by Molecular Docking and via ADME and Toxicity predictions. The shortlisted compounds were then subjected to MD Simulations of the membrane-bound FFAR4-ligand complexes for 100 ns each. Molecular analyses, encompassing binding interactions, RMSD, RMSF, RoG, PCA, and FEL, were conducted to scrutinize the protein–ligand complexes at the inter-atomic level. The analyses revealed significant interactions of the shortlisted compounds with the crucial residues of FFAR4 previously documented. FFAR4 as part of the complexes demonstrated consistent RMSDs, ranging from 3.57 to 3.64, with minimal residue fluctuations 5.27 to 6.03 nm, suggesting stable complexes. The gyration values fluctuated between 22.8 to 23.5 nm, indicating structural compactness and orderliness across the studied systems. Additionally, distinct conformational motions were observed in each complex, with energy contours shifting to broader energy basins throughout the simulation, suggesting thermodynamically stable protein–ligand complexes. The two compounds CHEMBL2012662 and CHEMBL64616 are presented as potential FFAR4 agonists, based on these insights and in-depth analyses. Collectively, these findings advance our comprehension of FFAR4’s functions and mechanisms, highlighting these compounds as potential FFAR4 agonists worthy of further exploration as innovative treatments for metabolic and immune-related conditions. [ABSTRACT FROM AUTHOR]

Nanotechnology has emerged as a promising approach for the controlled release of nutrients, particularly phosphorus and potassium. These essential plant nutrients are often applied in excess, leading to environmental pollution and loss of efficiency in crop production. Innovative economic and highly efficient fertilizers are urgently needed to achieve the targeted crop production worldwide in the presence of limited land and water resources. Therefore, in this study, novel, eco-friendly, cost-effective and enhanced efficiency nano-enabled fertilizers, NEF (nWTF1and nWTF2) were synthesized by impregnation of nanostructured water treatment residuals (nWTR) with (KH2PO4 + MgO) at 1:1 and 3:1 (w/w) ratios respectively using a planetary ball mill. The nWTR, nWTF1 and nWTF2 were extensively characterized. The water retention behavior and the sustained release of nutrients from the fabricated nano-enabled fertilizers (nWTF1 and nWTF2) in distilled water and sandy soil were investigated and monitored over time. The water retention capacity of the soil treated with nWTF2 after 26 days was 9.3 times higher than that of soil treated with conventional fertilizer. In addition, the nWTF2 exhibited lower release rates of P, K and Mg nutrients for longer release periods in comparison with the conventional fertilizers. This is a significant advantage over traditional fertilizers, which release nutrients quickly and can lead to leaching and nutrient loss. The main interaction mechanisms of PO4–K–Mg ions with nWTR surface were suggested. The results of the kinetics study revealed that power function was the best suitable model to describe the kinetics of P, K and Mg release data from NEF in water and soil. The produced NEF were applied to Zea maize plants and compared to commercial chemical fertilizer control plants. The obtained results revealed that the nano-enabled fertilizers (nWTF1 and nWTF2) significantly promoted growth, and P content compared with the commercial chemical fertilizer treated plants. The present work demonstrated the power of nano enabled fertilizers as efficient and sustained release nano-fertilizers for sustainable agriculture and pollution free environment. [ABSTRACT FROM AUTHOR]

Climatic factors influence malaria transmission via the effect on the Anopheles vector and Plasmodium parasite. Modelling and understanding the complex effects that climate has on malaria incidence can enable important early warning capabilities. Deep learning applications across fields are proving valuable, however the field of epidemiological forecasting is still in its infancy with a lack of applied deep learning studies for malaria in southern Africa which leverage quality datasets. Using a novel high resolution malaria incidence dataset containing 23 years of daily data from 1998 to 2021, a statistical model and XGBOOST machine learning model were compared to a deep learning Transformer model by assessing the accuracy of their numerical predictions. A novel loss function, used to account for the variable nature of the data yielded performance around + 20% compared to the standard MSE loss. When numerical predictions were converted to alert thresholds to mimic use in a real-world setting, the Transformer's performance of 80% according to AUROC was 20–40% higher than the statistical and XGBOOST models and it had the highest overall accuracy of 98%. The Transformer performed consistently with increased accuracy as more climate variables were used, indicating further potential for this prediction framework to predict malaria incidence at a daily level using climate data for southern Africa. [ABSTRACT FROM AUTHOR]

The amount of polycyclic aromatic hydrocarbons (PAHs) can be reduced by food additives. In this study, the impact of various flavors was investigated on the formation of PAHs in roasted sunflower seeds. PAHs was measured in the shell and kernel of sunflower with the flavors of lemon, golpar (hogweed), salt, ketchup and raw sunflower. Measuring the amount of PAHs was analyzed by Gas chromatography–mass spectrometry (GC–MS). PAHs with low molecular weight were detected. The total of PAHs of sunflower seeds were in the range of 0.4–3.2 mg kg−1. The lowest amount was related to the hogweed kernel, and the highest amount was related to the lemon. High molecular weight PAHs were not detected because the temperature did not rise above 100 °C during roasting. Some flavors, such as hogweed can reduce the amount of PAHs because of their antioxidant properties. On the contrary, the PAHs level with lemon juice was higher than other flavors. [ABSTRACT FROM AUTHOR]

Kolanut contains caffeine and it is widely consumed in various social contexts in Nigeria and other Sub-Saharan African countries. While some studies have suggested that kolanut is consumed by pregnant women, there is a dearth of information on the prevalence, consumption pattern and reasons for kolanut consumption among this group. This study investigated kolanut use among pregnant women in Ibadan, Oyo State, Nigeria. A cross-sectional study involving 478 consenting pregnant women in all trimesters of pregnancy was conducted. Semi-structured questionnaires were used to collect data. Associations between kolanut use and respondent characteristics were investigated using the chi-square test and logistic regression analysis. The mean age of the women was 28.7 ± 6.3 years. One hundred and sixty-two (33.9%) of women reported kolanut use during pregnancy, 140 (29.3%) in the current pregnancy. Fifty-five (39.3%) pregnant women reported frequent use and 46 (32.9%) used it in high quantities. Significant associations were found between current kolanut use and Hausa respondents (p = 0.014), educational level; secondary (p = 0.032), tertiary (p = 0.006), TBA (p = 0.005). The majority (93.7%) used kolanut to prevent spitting, nausea, and vomiting. This study showed that kolanut use is quite common among pregnant women and frequently used in large quantities. [ABSTRACT FROM AUTHOR]

Extreme climate events can have a significant negative impact on maize productivity, resulting in food scarcity and socioeconomic losses. Thus, quantifying their effect is needed for developing future adaptation and mitigation strategies, especially for countries relying on maize as a staple crop, such as South Africa. While several studies have analyzed the impact of climate extremes on maize yields in South Africa, little is known on the quantitative contribution of combined extreme events to maize yield variability and the causality link of extreme events. This study uses existing stress indices to investigate temporal and spatial patterns of heatwaves, drought, and extreme precipitation during maize growing season between 1986/87 and 2015/16 for South Africa provinces and at national level and quantifies their contribution to yield variability. A causal discovery algorithm was applied to investigate the causal relationship among extreme events. At the province and national levels, heatwaves and extreme precipitation showed no significant trend. However, drought severity increased in several provinces. The modified Combined Stress Index (CSIm) model showed that the maize yield nationwide was associated with drought events (explaining 25% of maize yield variability). Heatwaves has significant influence on maize yield variability (35%) in Free State. In North West province, the maize yield variability (46%) was sensitive to the combination of drought and extreme precipitation. The causal analysis suggests that the occurrence of heatwaves intensified drought, while a causal link between heatwaves and extreme precipitation was not detected. The presented findings provide a deeper insight into the sensitivity of yield data to climate extremes and serve as a basis for future studies on maize yield anomalies. [ABSTRACT FROM AUTHOR]

Crop yield and its prediction are crucial in agricultural production planning. This study investigates and predicts arabica coffee yield in order to match the market demand, using artificial neural networks (ANN) and multiple linear regression (MLR). Data of six variables, including areas, productivity zones, rainfalls, relative humidity, and minimum and maximum temperature, were collected for the recent 180 months between 2004 and 2018. The predicted yield of the cherry coffee crop continuously increases each year. From the dataset, it was found that the prediction accuracy of the R2 and RMSE from ANN was 0.9524 and 0.0784 tons, respectively. The ANN model showed potential in determining the cherry coffee yields. [ABSTRACT FROM AUTHOR]

Climate change impacts on maize production in South Africa, i.e., interannual yield variabilities, are still not well understood. This study is based on a recently released reanalysis of climate observations (AgERA5), i.e., temperature, precipitation, solar radiation, and wind speed data. The study assesses climate change effects by quantifying the trend of agrometeorological indicators, their correlation with maize yield, and analyzing their spatiotemporal patterns using Empirical Orthogonal Function. Thereby, the main agrometeorological factors that affected yield variability for the last 31 years (1990/91–2020/21 growing season) in major maize production provinces, namely Free State, KwaZulu-Natal, Mpumalanga, and North West are identified. Results show that there was a significant positive trend in temperature that averages 0.03–0.04 °C per year and 0.02–0.04 °C per growing season. There was a decreasing trend in precipitation in Free State with 0.01 mm per year. Solar radiation did not show a significant trend. Wind speed in Free State increased at a rate of 0.01 ms−1 per growing season. Yield variabilities in Free State, Mpumalanga, and North West show a significant positive correlation (r > 0.43) with agrometeorological variables. Yield in KwaZulu-Natal is not influenced by climate factors. The leading mode (50–80% of total variance) of each agrometeorological variable indicates spatially homogenous pattern across the regions. The dipole patterns of the second and the third mode suggest the variabilities of agrometeorological indicators are linked to South Indian high pressure and the warm Agulhas current. The corresponding principal components were mainly associated with strong climate anomalies which are identified as El Niño and La Niña events. [ABSTRACT FROM AUTHOR]

The current study assesses the prospect of using R. Communis seed oil as a substitute fuel for diesel engines. Biodiesel is prepared from the R. Communis plant seed oil by a single-step base catalytic transesterification procedure. The investigation deals with the Physico-chemical characteristics of R. Communis biodiesel and has been associated with the base diesel. It has been perceived that the characteristics of biodiesel are well-matched with the base diesel under the ASTM D6751 limits correspondingly. R. Communis biodiesel is blended in different proportions with base diesel such as D10, D20, D30, D40, D50 and D100 and is tested in a Kirloskar TV1 single-cylinder, 4 blows DI engine under altered loading conditions. Outcomes demonstrate that BTE and BSFC for D10 as well as D20 are similar to base diesel. BSFC indicates that the precise BSFC of base diesel, D10, D20, D30, D40 and D50 was 0.87, 1.70, 2.60, 3.0, 3.4, and 3.5 kg/kW-hr, respectively. The extreme BTE at full load condition for base diesel, D10, D20, D30, D40, D50 and D100 are 28.2%, 28.1%, 27.9%, 25.5%, 24.1%, and 23.6% , respectively. In the case of engine emissions, R. Communis biodiesel blends provided an average decrease in hydrocarbon (HC), Carbon-monoxide (CO) and carbon dioxide (CO2) associated with base diesel. Nevertheless, R. Communis biodiesel blends discharged high stages of nitrogen oxide (NOx) compares to base diesel. Base diesel, D10, D20, D30, D40, D50, and D100 had UBHC emissions of 45 ppm, 40 ppm, 44 ppm, 46 ppm, 41 ppm, and 43 ppm, respectively. The reduction in CO emissions for D10, D20, D30, D40, D50 and D100 are 0.13%, 0.14%, 0.17%, 0.18% and 0.21% respectively. The dissimilarity in NOx attentiveness within brake powers for D10, D20, D30, D40, and D50 and base diesel are 50-ppm, 100 ppm, 150 ppm, 250 ppm, 350 ppm, and 500 ppm, respectively. The dissimilarity of CO2 emanation with reverence to break powers for the base-diesel, D10, D20, D30, D40, D50, and D100 are 4.8%, 4.9%, 4.8%, 4.56%, 4.9% and 5.1%, respectively. The present research provides a way for renewable petrol blends to substitute diesel for powering diesel engines in that way dropping the reliance on fossil fuels. [ABSTRACT FROM AUTHOR]

The synthesis of different metal oxide nanoparticles (NPs) (e.g., ZnO, MgO and SiO2) using green methods is a promising alternative to traditional chemical methods. In this work, ZnO, MgO, and SiO2 NPs were prepared using lemon peel extract. The synthesized NPs were characterized using Fourier transform infrared spectroscopy, UV–Visible spectroscopy, X-ray diffraction, and transmission electron microscopy. Also, the effects of the green synthesis of different NPs on the irrigation water quality, the availability of some heavy metals in soil and plants, and the productivity of Origanum majorana (marjoram) were studied in detail. The obtained results showed that the addition of the NPs resulted in noticeable variations in the removal percentages of Cu2+ and Fe3+ from aqueous solutions. The maximum values obtained for the adsorption of Cu(II) on ZnO, MgO, and SiO2 NPs within the pH values of 3–5 were 89.9%, 83.3%, and 68.36%, respectively. Meanwhile, the maximum adsorption values of Fe(III) at pH 3.3 were 82%, 80%, and 65% for ZnO, MgO, and SiO2 NPs, respectively. Clearly, the application of the NPs effectively reduced the available Cu2+ in the studied soil samples in the following order: Zn2 > Zn1 > Mg2 > Si2 > Mg1 > Si1 > C (control). The highest values of available Cu2+ were observed in the control treatment, whereas the lowest values were obtained when Zn2 was added. The same tendencies were observed with substantial concentrations of Fe. The addition of NPs to the soil samples positively affected the plants' Cu2+ uptake. The effects of NPs and the additions of Cu2+ and Fe3+ on the availability of nitrogen, phosphorus, and potassium (NPK) in the soil system were very completed and osculated from one treatment to another. The same tendencies were observed with the total concentration of NPK in plants. [ABSTRACT FROM AUTHOR]

There is a limited number of studies assessing the epidemiology of Adverse Drug Events (ADEs) in the outpatient setting, especially those that do not result in healthcare use. The primary objective of this study was to assess the prevalence and determinants of self-reported ADEs among Lebanese outpatients. It was a cross-sectional observational study performed among Lebanese outpatients visiting community pharmacies across Lebanon. A questionnaire was designed to elicit patients' relevant information. The association between categorical variables were evaluated using Pearson χ2 test or Fisher's exact test. Binary logistic regression was performed to identify factors that affect the experience of self-reported ADEs. The study comprised 3148 patients. Around 37% of patients reported experiencing an ADE in the previous year. When ADEs occur, 70.5% of the respondents reported informing their physicians. Increasing number of medications per patient, use of injectable medication, and inquiring about potential drug-drug interactions were associated with higher experience of ADEs (p = 0.049; p = 0.003; and p = 0.009 respectively). Patients who received hospital discharge counseling reported experiencing less ADEs (p = 0.002). Our study showed prevalence of ADEs among Lebanese outpatients especially patients with polypharmacy, and highlighted the need to educate patients about the importance of reporting ADEs to their physicians. [ABSTRACT FROM AUTHOR]

Traditional medicine utilisation during antenatal care has been on the increase in several countries. Therefore, addressing and reinforcing the Sustainable Development Goal of maternal mortality reduction, there is a need to take traditional medicine utilisation during pregnancy into consideration. This paper explores traditional medicine utilisation during antenatal care among women in Bulilima District of Plumtree in Zimbabwe. A cross-sectional survey was conducted on 177 randomly selected women using a semi-structured questionnaire. Fisher's Exact Test, Odds Ratios, and Multiple Logistic Regression were utilised to determine any associations between different demographic characteristics and traditional medicine utilisation patterns using STATA SE Version 13. The prevalence of Traditional Medicine utilisation among pregnant women was estimated to be 28%. Most traditional remedies were used in the third trimester to quicken delivery. The majority of women used holy water and unknown Traditional Medicine during pregnancy. There was a strong association between age and Traditional Medicine utilisation as older women are 13 times more likely to use Traditional Medicine than younger ones. Women use traditional medicine for different purposes during pregnancy, and older women's likelihood to use Traditional Medicine is higher than their counterparts. The traditional system plays an essential role in antenatal care; therefore, there is a need to conduct further studies on the efficacy and safety of utilising Traditional Medicines. [ABSTRACT FROM AUTHOR]

The Palatal Rugae are considered a useful human identification marker for both orthodontists and forensic personnel. The principal aim of the present study was to evaluate the stability of palatal rugae with a 3D-3D superimposition procedure following Slow Maxillary Expansion (SME), in order to assess whether they kept their uniqueness and validity for human identification, even after a specific dental treatment. For this purpose, a sample of 27 digital dental models - belonging to growing patients (13 males and 14 females), aged between 8.5 and 15 years, who underwent SME therapy - was retrospectively studied and compared with a control group of 27 untreated subjects - (13 males and 14 females). Digital dental models were obtained pre-treatment and at device removal; both were processed by means of an intraoral scanner. A superimposition procedure was thus performed to reach the minimum point-to-point distance between two models of palatal rugae. Intra- and inter-observer differences were statistically analyzed by paired Wilcoxon test and Intra-class Correlation coefficient (ICC), showing values larger than 0.93. There was no difference in Root-Mean-Square (RMS) values between untreated control subjects and subjects treated with Leaf Expander (p = 0.062). A RMS value of 0.43 was the threshold to distinguish the pooled group ("Untreated" and "Leaf") from any mismatch. According to the obtained results, this study failed to reject the null hypothesis and presented no differences between the RMS values of the Test group and the RMS values of the untreated control group. This work highlighted the usefulness of 3D superimposition procedure for purposes of human identification, in subjects undergoing dental treatment. However, keeping in sight the forensic use of this technique as a helpful probation element in court, further studies should be performed to confirm these findings.

The glms ribozyme system has been used as an amenable tool to conditionally control expression of genes of interest. It is generally assumed that insertion of the ribozyme sequence does not affect expression of the targeted gene in the absence of the inducer glucosamine-6-phosphate, although experimental support for this assumption is scarce. Here, we report the unexpected finding that integration of the glms ribozyme sequence in the 3′ untranslated region of a gene encoding a HECT E3 ubiquitin ligase, termed Plasmodium falciparum ubiquitin transferase (PfUT), increased steady state RNA and protein levels 2.5-fold in the human malaria parasite P. falciparum. Overexpression of pfut resulted in an S/M phase-associated lengthening of the parasite's intraerythrocytic developmental cycle and a reduced merozoite invasion efficiency. The addition of glucosamine partially restored the wild type phenotype. Our study suggests a role of PfUT in controlling cell cycle progression and merozoite invasion. Our study further raises awareness regarding unexpected effects on gene expression when inserting the glms ribozyme sequence into a gene locus. [ABSTRACT FROM AUTHOR]

This is the first study to assess the risk of co-endemic Plasmodium vivax and Plasmodium falciparum transmission in the Peruvian Amazon using boosted regression tree (BRT) models based on social and environmental predictors derived from satellite imagery and data. Yearly cross-validated BRT models were created to discriminate high-risk (annual parasite index API > 10 cases/1000 people) and very-high-risk for malaria (API > 50 cases/1000 people) in 2766 georeferenced villages of Loreto department, between 2010–2017 as other parts in the article (graphs, tables, and texts). Predictors were cumulative annual rainfall, forest coverage, annual forest loss, annual mean land surface temperature, normalized difference vegetation index (NDVI), normalized difference water index (NDWI), shortest distance to rivers, time to populated villages, and population density. BRT models built with predictor data of a given year efficiently discriminated the malaria risk for that year in villages (area under the ROC curve (AUC) > 0.80), and most models also effectively predicted malaria risk in the following year. Cumulative rainfall, population density and time to populated villages were consistently the top three predictors for both P. vivax and P. falciparum incidence. Maps created using the BRT models characterize the spatial distribution of the malaria incidence in Loreto and should contribute to malaria-related decision making in the area. [ABSTRACT FROM AUTHOR]

Dengue virus (DENV) caused millions of infections around the world annually. Co-infection with different serotypes of DENV is associated with dengue hemorrhagic shock syndrome, leading to an estimate of 50% death rate. No approved therapies are currently available for the treatment of DENV infection. Hence, novel anti-DENV agents are urgently needed for medical therapy. Here we demonstrated that a natural product (2 R,4 R)-1,2,4-trihydroxyheptadec-16-yne (THHY), extracted from avocado (Persea americana) fruit, can inhibit DENV-2 replication in a concentration-dependent manner and efficiently suppresses replication of all DENV serotypes (1-4). We further reveal that the NF-κB-mediated interferon antiviral response contributes to the inhibitory effect of THHY on DENV replication. Using a DENV-infected ICR suckling mouse model, we found that THHY treatment caused an increased survival rate among mice infected with DENV. Collectively, these findings support THHY as a potential agent to control DENV infection. [ABSTRACT FROM AUTHOR]

During blood stage development the malaria parasite resides in a membrane-bound compartment, termed the parasitophorous vacuole (PV). The reasons for this intravacuolar life style and the molecular functions of this parasite-specific compartment remain poorly defined, which is mainly due to our limited knowledge about the molecular make-up of this unique niche. We used an in silico down-scaling approach to select for Plasmodium-specific candidates that harbour signatures of PV residency. Live co-localisation of five endogenously tagged proteins confirmed expression in the PV of Plasmodium berghei blood and liver stages. ER retention was ruled out by addition of the respective carboxyterminal tetrapeptides to a secreted reporter protein. Although all five PV proteins are highly expressed, four proved to be dispensable for parasite development in the mammalian and mosquito host, as revealed by targeted gene deletion. In good agreement with their redundant roles, the knockout parasites displayed no detectable deficiencies in protein export, sequestration, or PV morphology. Together, our approach improved the catalogue of the Plasmodium PV proteome and provides experimental genetics evidence for functional redundancy of several PV proteins. [ABSTRACT FROM AUTHOR]