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Panicum maximum is planted extensively in tropical and subtropical areas, due to its high-quality forage and high biomass yield. This study aims to assess the varied metabolic dynamics of P. maximum subject to different pollution-related wastewater levels, thus providing information for sustainable agriculture and soil restoration. We analyzed the primary and secondary metabolites in P. maximum subject to two different types of polluted wastewater (WW), compared to a control group. The alterations observed in the metabolite profiles were affected by several factors, including nutrient imbalances and oxidative stress induced by heavy metal accumulation. Initially, the increased nutrient availability stemming from wastewater treatment promoted plant growth; however, this positive effect was later diminished by the adverse impacts of heavy metals, which generated oxidative stress, resulting in metabolic disturbances and a decrease in the plant biomass. Importantly, the substantial increase in antioxidant enzymes, related to primary (e.g., sugars) and secondary metabolites (e.g., phenolics and flavonoids), underscores plants’ adaptive strategies to cope with stress. The increased biosynthesis of flavonoids and phenolic compounds is a protective mechanism against oxidative stress, which also improves the antimicrobial activity, following the activation of key biosynthetic pathways involved in their synthesis. These complex interactions among diverse metabolites suggest that plants exposed to polluted wastewater use various biochemical strategies to increase both their survival and defenses against pathogens. Collectively, these findings emphasize the significance of understanding how wastewater management practices can affect plant health, metabolic responses, and the broader implications for food safety and ecosystem stability.

The bioavailability of heavy metals in soil is a crucial factor in determining their potential uptake by plants and their subsequent entry into the food chain. Various methods, including traditional chemical extractants and the diffusive gradients in thin films (DGT) technique, are employed to assess this bioavailability. The bioavailability of heavy metals, particularly cadmium (Cd) and lead (Pb), is also influenced by soil texture and their concentrations in the soil solution. The primary objectives of this experiment were to compare and correlate the assessment of the Cd and Pb bioavailability using the DGT technique and traditional extractants across two soil textural classes: sandy clay loam (SCL) and clay loam (CL) at two contamination levels: aged contaminated (NC) and artificially contaminated (AC). The specific objectives included assessing the bioavailability of Cd and Pb at different growth stages of the wheat plant and correlating the DGT-based bioassessments of Cd and Pb with their concentrations in various plant parts at different growth stages. This study also compared the effectiveness of the DGT method and traditional extraction techniques in assessing the bioavailable fractions of Cd and Pb in soil. The regression analysis demonstrated strong positive correlations between the DGT method and various extraction methods. The results showed that the wheat plants grown in the AC soils exhibited lower root, shoot, and grain weights compared to those grown in the NC soils, indicating that metal contamination negatively impacts plant performance. The concentrations of Cd and Pb in the wheat tissues varied across different growth stages, with the highest levels observed during the grain filling (S3) and maturity (S4) stages. It is concluded that the in situ assessment of Cd and Pb though DGT was strongly and positively correlated with the Cd and Pb concentration in wheat plant parts at the maturity stage. A correlation and regression analysis of the DGT assessment and traditional extractants showed that the DGT method provides a reliable tool for assessing the bioavailability of Cd and Pb in soils and helped in developing sustainable soil management strategies to ensure the safety of agricultural products for human consumption.

The roll bonding of an experimental Al-2%Cu-2%Mn alloy with technically pure 1050A aluminum at true deformations of 0.26, 0.33 and 0.40 has been simulated using the QForm 10.3.0 FEM software. The flow stress of the Al-2%Cu-2%Mn alloy has been measured in temperature and strain rate ranges of 350–450 °C and 0.1–20 s−1, respectively. The simulation results suggest that the equivalent strain in the cladding layer is more intense than that in the base layer, reaching 1.0, 1.4 and 2.0 at strains of 0.26, 0.33 and 0.40, respectively. The latter fact favors a decrease in the difference between the flow stresses of the rolled sheet layer contact surfaces by an average of 25% at the highest strain. The experimental roll bonding has achieved good layer adhesion for all the test samples. The average peeling strength of the samples produced at strains of 0.26 and 0.33 proves to be 12.6 and 18.4 N/mm, respectively, and at a strain of 0.40, it has exceeded the flow stress of the 1050A alloy cladding layer. The change in the rolling force for different rolling routes has demonstrated the best fit with the experimental data.

This cross-sectional study aimed to estimate the relationship between food insecurity (FI) and health-related quality of life (HRQoL) in patients with celiac disease (CD) and assess whether this relationship is mediated or moderated by adherence to the gluten-free diet (GFD). The results of 1162 samples of patients diagnosed with CD showed that 8.3% of individuals who have a combined score of less than 13 exhibited excellent or very good adherence to the GFD. Furthermore, moderate and fair to poor adherence to the GFD was demonstrated, respectively and 71.9% of the patients had poor HRQoL levels. A significant and moderate positive correlation between FI and GFD adherence (r = 0.489) was found, indicating that 24% of the variance in FI is shared with GFD adherence. The patients’ gender, marital status, and monthly income made statistically significant contributions to the prediction (p < 0.05). Females had significantly lower HRQoL scores than males (B = −4.619, 95% CL: −6.08, −3.16) after holding all other variables constant. In conclusion, FI is mediated by GFD adherence to HRQoL. Moreover, a significant total effect relation was found between HRQoL and both FI and GFD adherence, suggesting that lowering symptoms and complications associated with CD may reduce the impact of FI on HRQoL.

Jordan experienced flash floods that resulted in numerous fatalities and injuries. This research focuses on identifying the Wadi Mujib’s flash flood potential zones and evaluating their potential magnitude. In this work, hydrological models were developed by integrating GIS settings with HEC-HMS software (V. 4.11). The hydrological model for Wadi Mujib is simulated in this research by means of the Soil Conservation Service (curve number method) while using rainfall data from 1970 to 2022. The results show that the optimum curve number values (CN) were 78.5 at normal antecedent moisture content. Additionally, in order to aid in the decision-making process for flash flood warnings, a flash flood potential index (FFPI) was also introduced based on four main physiographic parameters (slope, land use, plant cover, and soil texture) ranging from 1 to 10. The accumulative chart’s FFPI threshold, which indicates the areas with the highest potential for flash floods, was set at 95% or above. The FFPI threshold was chosen using the accumulative chart of FFPI, which shows that the FFPM threshold value is 7 and covers 13.39% of the study area.

Groundwater, a primary source of freshwater on Earth, is rapidly declining due to natural and anthropogenic activities. This study aimed to investigate the spatial distribution of dissolved organic matter (DOM) and heavy metals (HMs) in two municipal groundwater networks (A and B) from tube wells to taps in an industrial city, Faisalabad. The results showed that parameters such as color, turbidity, pH, EC, TDS, Ca2+, Mg2+, CO32−, HCO3−, Cl−, CaCO3, Na+, and NO3− were within the permissible limits set by the World Health Organization (WHO) and Pakistan Environmental Quality Standards (PEQSs). However, parameters like DO and COD exceeded standard values along the routes. Odor, taste, temperature, BOD, NH4+, T. coli, and F. coli surpassed acceptable levels at the tap end of both networks. Fluorescence EEM-PARAFAC spectra were analyzed at an excitation wavelength of 220–500 nm and emission wavelength of 240–550 nm, revealing UVA-humic-like (C1–C2) and UVC-humic-like (C3) components in the DOM. Based on fluorescence intensity, DOM was dominated by C2 > C1 > C3 compounds in both networks. The mean concentrations of HMs, including Cu, Zn, and Fe, fell below the prescribed limits in both networks. However, concentrations of Pb (A: 0.015–0.028 mg/L), (B: 0.013–0.027 mg/L), and Cd (A: 0.004–0.006 mg/L), (B: 0.005–0.008 mg/L) exceeded permissible limits from tube wells to taps. Moreover, C1 demonstrated a significant positive correlation with Cd and Cu in networks A and B, respectively. Furthermore, C2 displayed a significant positive correlation with Cd in network A. This study concludes that the groundwater in both networks (A and B) is contaminated by agricultural runoff, industrial and sewage water, plumbing materials, and eroded pipelines. As a result, the water is unsafe for cooking and drinking, posing risks of kidney, lung, and bladder cancers. Therefore, this study urgently recommends pipeline reconstruction and the implementation of proper groundwater remediation approaches before these sources are used for drinking.

Soil’s hydraulic properties are an essential characteristic that influences the hydrologic cycle by influencing infiltration and runoff and the transport of soil water and salt in the process of vegetation rehabilitation in coastal saline soils. To date, few studies have specifically addressed the soil’s hydraulic properties and root–soil interactions of coastal saline soil under revegetation. This study aimed to identify the unique hydraulic characteristics of soil, the pore size distribution parameter, Gardner α, and the different contributions of soil’s physical properties and vegetation’s root morphological characteristics with regard to soil infiltration. For this purpose, disc infiltration experiments at different pressure heads were performed on three vegetation types, Salix matsudana (SM), Hibiscus syriacus (HC), and Sabina vulgaris (SV), after two years of vegetation rehabilitation. The results demonstrated that the initial and steady infiltration rate, Gardner α, and soil porosity fraction exhibit significant differences among the three plant species. A correlation analysis indicated that the soil water content, surface area, density, and dry weight of roots had inverse relationships with soil infiltration at heads of pressure of 0 cm and 9 cm. The regulation of soil infiltration was influenced by the root dry weight and root average diameter, which played crucial roles in determining the roots’ morphological properties and the formation of pathways and soil pores.

Southwestern China is receiving excessive chemical fertilizers to meet the challenges of continuous cropping. These practices are deteriorating the soil environment and affecting tobacco (Nicotiana tabacum L.) yield and quality adversely. A novel microbially enriched biochar-based fertilizer was synthesized using effective microorganisms, tobacco stalk biochar and basal fertilizer. A field-scale study was conducted to evaluate the yield response of tobacco grown on degraded soil amended with our novel biochar-based microbial fertilizer (BF). Four treatments of BF (0%, 1.5%, 2.5% and 5%) were applied in the contaminated field to grow tobacco. The application of BF1.5, BF2.5 and BF5.0 increased the available water contents by 9.47%, 1.18% and 2.19% compared to that with BF0 respectively. Maximum growth of tobacco in terms of plant height and leaf area was recorded for BF1.5 compared to BF0. BF1.5, BF2.5 and BF5.0 increased SPAD by 13.18–40.53%, net photosynthetic rate by 5.44–60.42%, stomatal conductance by 8.33–44.44%, instantaneous water use efficiency by 55.41–93.24% and intrinsic water use efficiency by 0.09–24.11%, while they decreased the intercellular CO2 concentration and transpiration rate by 3.85–6.84% and 0.29–47.18% relative to BF0, respectively (p < 0.05). The maximum increase in tobacco yield was recorded with BF1.5 (23.81%) compared to that with BF0. The present study concludes that the application of BF1.5 improves and restores the degraded soil by improving the hydraulic conductivity and by increasing the tobacco yield.

Lettuce is a water-sensitive stem-used plant, and its rapid growth process causes significant disturbances to the soil. Few studies have focused on the gaseous carbon emissions from lettuce fields under different irrigation methods. Therefore, this study investigated the effect of different drip-irrigation lower limits and methods (drip and furrow irrigation) on greenhouse gas (CO2, CH4) emissions from lettuce fields. Thus, drip irrigation (DI) was implemented using three different lower limits of irrigation corresponding to 75%, 65%, and 55% of the field capacity, and named DR1, DR2, and DR3, respectively. Furrow irrigation (FI) was used as a control treatment. The CO2 and CH4 emission fluxes, soil temperature, and soil enzyme activities were detected. The results showed that the cumulative CO2 emission was highest under DR3 and relatively lower under DR1. For the FI treatment, the cumulative CO2 emission (382.7 g C m−2) was higher than that under DR1 but 20.2% lower than that under DR2. The cumulative CH4 emissions under FI (0.012 g C m−2) were the greatest in the whole lettuce growth period, while DR2 and DR3 treatments emitted lower amounts of CH4. The irrigation method considerably enhanced the activity of urease and catalase, meanwhile promoting CO2 emission. The low irrigation amount each time combined with high irrigation frequency reduced soil CO2 emission while increasing CH4 emission. From the perspective of the total reduction of gaseous carbon, DR1 is the optimal drip irrigation method among all the irrigation lower limits and methods.

During the postpartum period, psychological disorders may emerge. Aims and objectives: With the current study, we aim to explore the biological determinants that act on women during labor and incur the risk for postpartum depression (PPD). To reach the aim, we will perform the following tasks: (i) identify biological peripartum risk factors and calculate pooled prevalence of PPD for each of them; (ii) explore the strength of the relationship between peripartum risk factors and PPD; (iii) rank the predictors by their prevalence and magnitude of association with PPD. The knowledge obtained will support the development and implementation of early diagnostic and preventive strategies. Methods and analysis: We will systematically go through peer-reviewed publications available in the PubMed search engine and online databases: Scopus, Web of Science, EMBASE. The scope of the review will include articles published any time in English, Arabic, or Polish. We will deduplicate literature sources with the Covidence software, evaluate heterogeneity between the study results, and critically assess credibility of selected articles with the Joanna Briggs Institute’s bias evaluation tool. The information to extract is the incidence rate, prevalence, and odds ratio between each risk factor and PPD. A comprehensive analysis of the extracted data will allow us to achieve the objectives. The study findings will contribute to risk stratification and more effective management of PPD in women.

When optimizing irrigation methods, much consideration is given to crop growth indicators while less attention has been paid to soil’s gaseous carbon (C) and nitrogen (N) emission indicators. Therefore, adopting an irrigation practice that can reduce emissions while maintaining crop yield and quality is of great interest. Thus, open-field experiments were conducted from September 2020 to January 2022 using a single-factor randomized block design with three replications. The lettuce plants (“Feiqiao Lettuce No.1”) were grown using four different irrigation methods established by setting the lower limit of drip irrigation to 75%, 65%, and 55% of soil water content at field capacity corresponding to DR1, DR2, and DR3, respectively. Furrow irrigation (FI) was used as a control. Crop growth indicators and soil gas emissions were observed. Results showed that the mean lettuce yield under DR1 (64,500 kg/ha) was the highest, and it was lower under DR3 and FI. The lettuces under DR3 showed greater concentrations of crude fiber, vitamin C, and soluble sugar, and a greater nitrate concentration. Compared with FI, the DR treatments were more conducive to improving the comprehensive quality of lettuce, including the measured appearance and nutritional quality. Among all the irrigation methods, FI had the maximum cracking rate of lettuce, reaching 25.3%, 24.6%, and 22.7%, respectively, for the three continuous seasons. The stem cracking rates under DR2 were the lowest—only 10.1%, 14.4%, and 8.2%, respectively, which were decreased to nearly half compared with FI. The entropy model detected that the weight coefficient evaluation value of DR2 was the greatest, reaching 0.93, indicating that the DR2 method has the optimal benefits under comprehensive consideration of water saving, yield increase, quality improvement, and emission reduction.

Significant research has been conducted on the effects of fertilizers or agents on the sustainable development of agriculture in salinization areas. By contrast, limited consideration has been given to the interactive effects of microbial fertilizer (MF) and salinity on hydraulic properties in secondary salinization soil (SS) and coastal saline soil (CS). An incubation experiment was conducted to investigate the effects of saline soil types, salinity levels (non-saline, low-salinity, and high-salinity soils), and MF amounts (32.89 g kg−1 and 0 g kg−1) on soil hydraulic properties. Applied MF improved soil water holding capacity in each saline soil compared with that in CK, and SS was higher than CS. Applied MF increased saturated moisture, field capacity, capillary fracture moisture, the wilting coefficient, and the hygroscopic coefficient by 0.02–18.91% in SS, while it was increased by 11.62–181.88% in CS. It increased soil water supply capacity in SS (except for high-salinity soil) and CS by 0.02–14.53% and 0.04–2.34%, respectively, compared with that in CK. Soil available, readily available, and unavailable water were positively correlated with MF, while soil gravity and readily available and unavailable water were positively correlated with salinity in SS. Therefore, a potential fertilization program with MF should be developed to increase hydraulic properties or mitigate the adverse effects of salinity on plants in similar SS or CS areas.

Background: The potential positive interaction between intermittent fasting (IF) and brain-derived neurotrophic factor (BDNF) on cognitive function has been widely discussed. This systematic review tried to assess the efficacy of interventions with different IF regimens on BDNF levels and their association with cognitive functions in humans. Interventions with different forms of IF such as caloric restriction (CR), alternate-day fasting (ADF), time-restricted eating (TRE), and the Ramadan model of intermittent fasting (RIF) were targeted. Methods: A systematic review was conducted for experimental and observational studies on healthy people and patients with diseases published in EMBASE, Scopus, PubMed, and Google Scholar databases from January 2000 to December 2023. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis statements (PRISMA) for writing this review. Results: Sixteen research works conducted on healthy people and patients with metabolic disorders met the inclusion criteria for this systematic review. Five studies showed a significant increase in BDNF after the intervention, while five studies reported a significant decrease in BDNF levels, and the other six studies showed no significant changes in BDNF levels due to IF regimens. Moreover, five studies examined the RIF protocol, of which, three studies showed a significant reduction, while two showed a significant increase in BDNF levels, along with an improvement in cognitive function after RIF. Conclusions: The current findings suggest that IF has varying effects on BDNF levels and cognitive functions in healthy, overweight/obese individuals and patients with metabolic conditions. However, few human studies have shown that IF increases BDNF levels, with controversial results. In humans, IF has yet to be fully investigated in terms of its long-term effect on BDNF and cognitive functions. Large-scale, well-controlled studies with high-quality data are warranted to elucidate the impact of the IF regimens on BDNF levels and cognitive functions.

Biochar application has the potential for mitigating N2O emissions from agricultural soils and has been suggested as a management practice to ameliorate soil fertility and increase crop productivity. Nevertheless, the influence of biochar addition on N2O emissions from soils with different pH levels is not yet clear, which results in a poor understanding of the mechanisms regarding biochar application to soil N2O mitigation. A 40-day incubation experiment was carried out in the present study to investigate the impact of biochar on N2O emissions from soils with different natural pH. Four treatments (control, nitrogen fertilizer application, biochar amendment, and N plus biochar amendment) were set up separately in soils with three different natural pH levels (acidic vegetable soil, neutral rice soil, and alkaline soil). Our results showed that adding biochar significantly decreased N2O emissions by 20.8% and 47.6% in acidic vegetable soil for both N and no N addition treatments, respectively. For neutral and alkaline soils, the reduction of N2O emissions by biochar amendment was only significant for N addition treatments in alkaline soil. Soil pH and NO3−-N concentration were significantly affected by biochar amendment (soil pH increased by 1.43–1.56, 0.57–0.70, and 0.29–0.37 units for acidic vegetable soil, neutral rice soil, and alkaline soil, respectively). Thus, biochar amendment could be used as an effective management practice for mitigating N2O emissions from acidic and alkaline soils.

This comprehensive review explores aquaponics as an environmentally friendly solution aligned with SDGs and food sovereignty, assessing various aspects from system design to automation, and weighing social, economic, and environmental benefits through literature and case studies. However, challenges persist in obtaining organic certification and legislative recognition, hindering its growth. Achieving remarkable water use efficiency, up to 90%, relies on adaptable fish species like Nile tilapia and carp. Nutrient-rich fish feeds notably benefit low-nutrient-demanding greens. Ensuring water quality and efficient nitrification are pivotal, supported by IoT systems. Despite its efficiency, integrating Industry 4.0 involves complexity and cost barriers, necessitating ongoing innovation. Economies of scale and supportive horticultural policies can bolster its viability. Aquaponics, known for its efficiency in enhancing crop yields while minimizing water use and waste, is expanding globally, especially in water-scarce regions. Aquaponics, pioneered by the University of the Virgin Islands, is expanding in Europe, notably in Spain, Denmark, Italy, and Germany. Asia and Africa also recognize its potential for sustainable food production, especially in water-limited areas. While it offers fresh produce and cost savings, challenges arise in scaling up, managing water quality, and meeting energy demands, particularly for indoor systems. Egypt’s interest in desert and coastal regions highlights aquaponics’ eco-friendly food production potential. Despite the associated high costs, there is a quest for practical and affordable designs for everyday integration. Research in arid regions and industry advancements are crucial for aquaponics’ global food production potential. Deeper exploration of intelligent systems and automation, particularly in large-scale setups, is essential, highlighting the industry’s promise. Practical application, driven by ongoing research and local adaptations, is a key to fully harnessing aquaponics for sustainable food production worldwide.

Targeting tumour metabolism through glucose transporters is an attractive approach. However, the role these transporters play through interaction with other signalling proteins is not yet defined. The glucose transporter SLC2A3 (GLUT3) is a member of the solute carrier transporter proteins. GLUT3 has a high affinity for D-glucose and regulates glucose uptake in the neurons, as well as other tissues. Herein, we show that GLUT3 is involved in the uptake of arsenite, and its level is regulated by peroxiredoxin 1 (PRDX1). In the absence of PRDX1, GLUT3 mRNA and protein expression levels are low, but they are increased upon arsenite treatment, correlating with an increased uptake of glucose. The downregulation of GLUT3 by siRNA or deletion of the gene by CRISPR cas-9 confers resistance to arsenite. Additionally, the overexpression of GLUT3 sensitises the cells to arsenite. We further show that GLUT3 interacts with PRDX1, and it forms nuclear foci, which are redistributed upon arsenite exposure, as revealed by immunofluorescence analysis. We propose that GLUT3 plays a role in mediating the uptake of arsenite into cells, and its homeostatic and redox states are tightly regulated by PRDX1. As such, GLUT3 and PRDX1 are likely to be novel targets for arsenite-based cancer therapy.

Silver oxide-doped tin oxide (SnAg2O3) nanoparticles were synthesized and different spectroscopic techniques were used to structurally identify SnAg2O3 nanoparticles. The reduction of 4-nitrophenol (4-NP), congo red (CR), methylene blue (MB), and methyl orange (MO) was studied using SnAg2O3 as a catalyst. Only 1.0 min was required to reduce 95% MO; thus, SnAg2O3 was found to be effective with a rate constant of 3.0412 min−1. Being a powder, SnAg2O3 is difficult to recover and recycle multiple times. For this reason, SnAg2O3 was coated on adhesive tape (AT) to make it recyclable for large-scale usage. SnAg2O3@AT catalyst was assessed toward MO reduction under various conditions. The amount of SnAg2O3@AT, NaBH4, and MO was optimized for best possible reduction conditions. The catalyst had a positive effect since it speed up the reduction of MO by adding more SnAg2O3@AT and NaBH4 as well as lowering the MO concentration. SnAg2O3@AT totally reduced MO (98%) in 3.0 min with a rate constant of 1.3669 min−1. These findings confirmed that SnAg2O3@AT is an effective and useful catalyst for MO reduction that can even be utilized on a large scale for industrial purposes.

Salinity adversely affects the plant’s morphological characteristics, but the utilization of aqueous algal extracts (AE) ameliorates this negative impact. In this study, the application of AE derived from Chlorella vulgaris and Dunaliella salina strains effectively reversed the decline in biomass allocation and water relations, both in normal and salt-stressed conditions. The simultaneous application of both extracts in salt-affected soil notably enhanced key parameters, such as chlorophyll content (15%), carotene content (1%), photosynthesis (25%), stomatal conductance (7%), and transpiration rate (23%), surpassing those observed in the application of both AE in salt-affected as compared to salinity stress control. Moreover, the AE treatments effectively mitigated lipid peroxidation and electrolyte leakage induced by salinity stress. The application of AE led to an increase in GB (6%) and the total concentration of free amino acids (47%) by comparing with salt-affected control. Additionally, salinity stress resulted in an elevation of antioxidant enzyme activities, including superoxide dismutase, ascorbate peroxidase, catalase, and glutathione reductase. Notably, the AE treatments significantly boosted the activity of these antioxidant enzymes under salinity conditions. Furthermore, salinity reduced mineral contents, but the application of AE effectively counteracted this decline, leading to increased mineral levels. In conclusion, the application of aqueous algal extracts, specifically those obtained from Chlorella vulgaris and Dunaliella salina strains, demonstrated significant efficacy in alleviating salinity-induced stress in Phaseolus vulgaris plants.

Cisplatin (cis-diamminedichloroplatinum (II)) is the oldest known chemotherapeutic agent. Since the identification of its anti-tumour activity, it earned a remarkable place as a treatment of choice for several cancer types. It remains effective against testicular, bladder, lung, head and neck, ovarian, and other cancers. Cisplatin treatment triggers different cellular responses. However, it exerts its cytotoxic effects by generating inter-strand and intra-strand crosslinks in DNA. Tumour cells often develop tolerance mechanisms by effectively repairing cisplatin-induced DNA lesions or tolerate the damage by adopting translesion DNA synthesis. Cisplatin-associated nephrotoxicity is also a huge challenge for effective therapy. Several preclinical and clinical studies attempted to understand the major limitations associated with cisplatin therapy, and so far, there is no definitive solution. As such, a more comprehensive molecular and genetic profiling of patients is needed to identify those individuals that can benefit from platinum therapy. Additionally, the treatment regimen can be improved by combining cisplatin with certain molecular targeted therapies to achieve a balance between tumour toxicity and tolerance mechanisms. In this review, we discuss the importance of various biological processes that contribute to the resistance of cisplatin and its derivatives. We aim to highlight the processes that can be modulated to suppress cisplatin resistance and provide an insight into the role of uptake transporters in enhancing drug efficacy.

This paper focuses on the combination of the method of moments and the wire-grid approximation as an effective computational technique for modeling symmetrical antennas with low computational cost and accurate results. The criteria and conditions for the use of wire-grid surface approximation from various sources are presented together with new recommendations for modeling symmetrical antenna structures using the wire-grid approximation. These recommendations are used to calculate the characteristics of biconical and horn antennas at different frequencies. The results obtained using different grid and mesh settings are compared to those obtained analytically. Moreover, the results are compared to those obtained using the finite difference time domain numerical method, as well as the measured ones. All results are shown to be in a good agreement. The recommendations used for building a symmetrical wire-grid of those symmetrical antenna elements provided the most advantageous parameters of the grid and mesh settings and the wire radius, which are able to give quite accurate results with low computational cost. Additionally, the known equal area rule was modified for a rectangular grid form. The obtained radiation patterns of a conductive plate using both the original rule and the modified one are compared with the electrodynamic analysis results. It is shown that the use of the modified rule is more accurate when using a rectangle grid form.

Camera traps deployed in remote locations provide an effective method for ecologists to monitor and study wildlife in a non-invasive way. However, current camera traps suffer from two problems. First, the images are manually classified and counted, which is expensive. Second, due to manual coding, the results are often stale by the time they get to the ecologists. Using the Internet of Things (IoT) combined with deep learning represents a good solution for both these problems, as the images can be classified automatically, and the results immediately made available to ecologists. This paper proposes an IoT architecture that uses deep learning on edge devices to convey animal classification results to a mobile app using the LoRaWAN low-power, wide-area network. The primary goal of the proposed approach is to reduce the cost of the wildlife monitoring process for ecologists, and to provide real-time animal sightings data from the camera traps in the field. Camera trap image data consisting of 66,400 images were used to train the InceptionV3, MobileNetV2, ResNet18, EfficientNetB1, DenseNet121, and Xception neural network models. While performance of the trained models was statistically different (Kruskal–Wallis: Accuracy H(5) = 22.34, p < 0.05; F1-score H(5) = 13.82, p = 0.0168), there was only a 3% difference in the F1-score between the worst (MobileNet V2) and the best model (Xception). Moreover, the models made similar errors (Adjusted Rand Index (ARI) > 0.88 and Adjusted Mutual Information (AMU) > 0.82). Subsequently, the best model, Xception (Accuracy = 96.1%; F1-score = 0.87; F1-Score = 0.97 with oversampling), was optimized and deployed on the Raspberry Pi, Google Coral, and Nvidia Jetson edge devices using both TenorFlow Lite and TensorRT frameworks. Optimizing the models to run on edge devices reduced the average macro F1-Score to 0.7, and adversely affected the minority classes, reducing their F1-score to as low as 0.18. Upon stress testing, by processing 1000 images consecutively, Jetson Nano, running a TensorRT model, outperformed others with a latency of 0.276 s/image (s.d. = 0.002) while consuming an average current of 1665.21 mA. Raspberry Pi consumed the least average current (838.99 mA) with a ten times worse latency of 2.83 s/image (s.d. = 0.036). Nano was the only reasonable option as an edge device because it could capture most animals whose maximum speeds were below 80 km/h, including goats, lions, ostriches, etc. While the proposed architecture is viable, unbalanced data remain a challenge and the results can potentially be improved by using object detection to reduce imbalances and by exploring semi-supervised learning.

Background: Since the coronavirus disease 2019 (COVID-19) was declared a pandemic, there was no doubt that vaccination is the ideal protocol to tackle it. Within a year, a few COVID-19 vaccines have been developed and authorized. This unparalleled initiative in developing vaccines created many uncertainties looming around the efficacy and safety of these vaccines. This study aimed to assess the side effects and perceptions following COVID-19 vaccination in Jordan. Methods: A cross-sectional study was conducted by distributing an online survey targeted toward Jordan inhabitants who received any COVID-19 vaccines. Data were statistically analyzed and certain machine learning (ML) tools, including multilayer perceptron (MLP), eXtreme gradient boosting (XGBoost), random forest (RF), and K-star were used to predict the severity of side effects. Results: A total of 2213 participants were involved in the study after receiving Sinopharm, AstraZeneca, Pfizer-BioNTech, and other vaccines (38.2%, 31%, 27.3%, and 3.5%, respectively). Generally, most of the post-vaccination side effects were common and non-life-threatening (e.g., fatigue, chills, dizziness, fever, headache, joint pain, and myalgia). Only 10% of participants suffered from severe side effects; while 39% and 21% of participants had moderate and mild side effects, respectively. Despite the substantial variations between these vaccines in the presence and severity of side effects, the statistical analysis indicated that these vaccines might provide the same protection against COVID-19 infection. Finally, around 52.9% of participants suffered before vaccination from vaccine hesitancy and anxiety; while after vaccination, 95.5% of participants have advised others to get vaccinated, 80% felt more reassured, and 67% believed that COVID-19 vaccines are safe in the long term. Furthermore, based on the type of vaccine, demographic data, and side effects, the RF, XGBoost, and MLP gave both high accuracies (0.80, 0.79, and 0.70, respectively) and Cohen’s kappa values (0.71, 0.70, and 0.56, respectively). Conclusions: The present study confirmed that the authorized COVID-19 vaccines are safe and getting vaccinated makes people more reassured. Most of the post-vaccination side effects are mild to moderate, which are signs that body’s immune system is building protection. ML can also be used to predict the severity of side effects based on the input data; predicted severe cases may require more medical attention or even hospitalization.