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CXCL10 (IP-10) plays a key role in leukocyte homing to the inflamed tissues and its increased levels are associated with the pathophysiology of various inflammatory diseases including obesity and type 2 diabetes. IL-1β is a key proinflammatory cytokine that is found upregulated in meta-inflammatory conditions and acts as a potent activator, inducing the expression of cytokines/chemokines by immune cells. However, it is unclear whether IL-1β induces the expression of CXCL10 in monocytic cells. We, therefore, determined the CXCL10 induction using IL-1β in THP1 monocytic cells and investigated the mechanisms involved. Monocytes (human monocytic THP-1 cells) were stimulated with IL-1β. CXCL10 gene expression was determined with real-time RT-PCR. CXCL10 protein was determined using ELISA. Signaling pathways were identified by using Western blotting, inhibitors, siRNA transfections, and kinase assay. Our data show that IL-1β induced the CXCL10 expression at both mRNA and protein levels in monocytic cells (p = 0.0001). Notably, only the JNK inhibitor (SP600125) significantly suppressed the IL-1β-induced CXCL10 expression, while the inhibitors of MEK1/2 (U0126), ERK1/2 (PD98059), and p38 MAPK (SB203580) had no significant effect. Furthermore, IL-1β-induced CXCL10 expression was decreased in monocytic cells deficient in JNK/c-Jun. Accordingly, inhibiting the JNK kinase activity markedly reduced the IL-1β-induced JNK/c-Jun phosphorylation in monocytic cells. NF-κB inhibition by Bay-117085 and resveratrol also suppressed the CXCL10 expression. Our findings provide preliminary evidence that IL-1β stimulation induces the expression of CXCL10 in monocytic cells which requires signaling via the JNK/c-Jun/NF-κB axis.

This study unveils verapamil’s compelling cytoprotective and proliferative effects on pancreatic β-cells amidst diabetic stressors, spotlighting its unforeseen role in augmenting cholecystokinin (CCK) expression. Through rigorous investigations employing MIN6 β-cells and zebrafish models under type 1 and type 2 diabetic conditions, we demonstrate verapamil’s capacity to significantly boost β-cell proliferation, enhance glucose-stimulated insulin secretion, and fortify cellular resilience. A pivotal revelation of our research is verapamil’s induction of CCK, a peptide hormone known for its role in nutrient digestion and insulin secretion, which signifies a novel pathway through which verapamil exerts its therapeutic effects. Furthermore, our mechanistic insights reveal that verapamil orchestrates a broad spectrum of gene and protein expressions pivotal for β-cell survival and adaptation to immune-metabolic challenges. In vivo validation in a zebrafish larvae model confirms verapamil’s efficacy in fostering β-cell recovery post-metronidazole infliction. Collectively, our findings advocate for verapamil’s reevaluation as a multifaceted agent in diabetes therapy, highlighting its novel function in CCK upregulation alongside enhancing β-cell proliferation, glucose sensing, and oxidative respiration. This research enriches the therapeutic landscape, proposing verapamil not only as a cytoprotector but also as a promoter of β-cell regeneration, thereby offering fresh avenues for diabetes management strategies aimed at preserving and augmenting β-cell functionality.

The global incidence of Type 2 diabetes (T2D) is on the rise, fueled by factors such as obesity, sedentary lifestyles, socio-economic factors, and ethnic backgrounds. T2D is a multifaceted condition often associated with various health complications, including adverse effects on bone health. This study aims to assess key biomarkers linked to bone health and remodeling—Osteoprotegerin (OPG), Receptor Activator of Nuclear Factor Kappa-Β Ligand (RANKL), and Glycoprotein Non-Metastatic Melanoma Protein B (GPNMB)—among individuals with diabetes while exploring the impact of ethnicity on these biomarkers. A cross-sectional analysis was conducted on a cohort of 2083 individuals from diverse ethnic backgrounds residing in Kuwait. The results indicate significantly elevated levels of these markers in individuals with T2D compared to non-diabetic counterparts, with OPG at 826.47 (405.8) pg/mL, RANKL at 9.25 (17.3) pg/mL, and GPNMB at 21.44 (7) ng/mL versus 653.75 (231.7) pg/mL, 0.21 (9.94) pg/mL, and 18.65 (5) ng/mL in non-diabetic individuals, respectively. Notably, this elevation was consistent across Arab and Asian populations, except for lower levels of RANKL observed in Arabs with T2D. Furthermore, a positive and significant correlation between OPG and GPNMB was observed regardless of ethnicity or diabetes status, with the strongest correlation (r = 0.473, p < 0.001) found among Arab individuals with T2D. Similarly, a positive and significant correlation between GPNMB and RANKL was noted among Asian individuals with T2D (r = 0.401, p = 0.001). Interestingly, a significant inverse correlation was detected between OPG and RANKL in non-diabetic Arab individuals. These findings highlight dysregulation in bone remodeling markers among individuals with T2D and emphasize the importance of considering ethnic variations in T2D-related complications. The performance of further studies is warranted to understand the underlying mechanisms and develop interventions based on ethnicity for personalized treatment approaches.

Angiopoietins are crucial growth factors for maintaining a healthy, functional endothelium. Patients with type 2 diabetes (T2D) exhibit significant levels of angiogenic markers, particularly Angiopoietin-2, which compromises endothelial integrity and is connected to symptoms of endothelial injury and failure. This report examines the levels of circulating angiopoietins in people with T2D and diabetic nephropathy (DN) and explores its link with ANGPTL proteins. We quantified circulating ANGPTL3, ANGPTL4, ANGPTL8, Ang1, and Ang2 in the fasting plasma of 117 Kuwaiti participants, of which 50 had T2D and 67 participants had DN. The Ang2 levels increased with DN (4.34 ± 0.32 ng/mL) compared with T2D (3.42 ± 0.29 ng/mL). This increase correlated with clinical parameters including the albumin-to-creatinine ratio (ACR) (r = 0.244, p = 0.047), eGFR (r = −0.282, p = 0.021), and SBP (r = −0.28, p = 0.024). Furthermore, Ang2 correlated positively to both ANGPTL4 (r = 0.541, p < 0.001) and ANGPTL8 (r = 0.41, p = 0.001). Multiple regression analysis presented elevated ANGPTL8 and ACRs as predictors for Ang2’s increase in people with DN. In people with T2D, ANGPTL4 positively predicted an Ang2 increase. The area under the curve (AUC) in receiver operating characteristic (ROC) analysis of the combination of Ang2 and ANGPTL8 was 0.77 with 80.7% specificity. In conclusion, significantly elevated Ang2 in people with DN correlated with clinical markers such as the ACR, eGFR, and SBP, ANGPTL4, and ANGPTL8 levels. Collectively, this study highlights a close association between Ang2 and ANGPTL8 in a population with DN, suggesting them as DN risk predictors.

One of the challenges in site-specific phosphorus (P) management is the substantial spatial variability in plant available P across fields. To overcome this barrier, emerging sensing, data fusion, and spatial predictive modeling approaches are needed to accurately reveal the spatial heterogeneity of P. Seven spatially variable fields located in Ontario, Canada are clustered into two zones; four fields are located in eastern Ontario and three others are located in western Ontario. This study compares Bayesian Additive Regression Trees (BART), Support Vector Machine regressor (SVM), and Ordinary Kriging (OK), along with novel data fusion concepts, to analyze integrated high-density spatial data layers related to spatial variability in soil available P. Feature selection and interaction detection using BART variable selection and Recursive Feature Elimination (RFE) for SVM were applied to 42 predictors, including soil-vegetation indices derived from PlanetScope multispectral imagery, high-density apparent soil electrical conductivity (ECa), and high-resolution topographic attributes derived from DUALEM-21S and a Real-Time Kinematic (RTK) global navigation satellite systems (GNSS) receiver, respectively. Modeling spatial heterogeneity of soil available P with BART showed higher accuracy than SVM and OK in both zones of this study when trained and tested on ground truth data from clusters of farms. A BART variable selection approach resulted in six auxiliary predictors of soil available P in the eastern zone, while only four predictors were selected to predict P in the western zone. RFE for SVM resulted in models with 15 and 12 auxiliary predictors in the eastern and western Ontario zones. Topographic elevation was the most influential predictor of soil available P in both zones. Compared with the SVM and OK methods, BART exhibited lower average RMSE values for individual fields of 1.86 ppm and 3.58 ppm across the eastern and western Ontario zones, respectively, along with higher R2 values of 0.85 and 0.83, respectively. In contrast, SVM had RMSE values for individual fields in the eastern and western Ontario zones, respectively, averaging 5.04 ppm and 7.51 ppm and R2 values of 0.27 and 0.43. RMSE values for soil available P in individual fields across the eastern and western Ontario zones averaged 4.77 ppm and 7.81 ppm, respectively, with the OK method, while R2 values averaged 0.19 and 0.44. The selection of suitable auxiliary predictors and data fusion, combined with BART spatial machine learning algorithms, have potential to be a useful tool to accurately estimate spatial patterns in soil available P for agricultural fields in Ontario, Canada.

Non-alcoholic fatty liver disease (NAFLD) is manifested by hepatic steatosis, insulin resistance, hepatocyte death, and systemic inflammation. Obesity induces steatosis and chronic inflammation in the liver. However, the precise mechanism underlying hepatic steatosis in the setting of obesity remains unclear. Here, we report studies that address this question. After 14 weeks on a high-fat diet (HFD) with high sucrose, C57BL/6 mice revealed a phenotype of liver steatosis. Transcriptional profiling analysis of the liver tissues was performed using RNA sequencing (RNA-seq). Our RNA-seq data revealed 692 differentially expressed genes involved in processes of lipid metabolism, oxidative stress, immune responses, and cell proliferation. Notably, the gene encoding neutral sphingomyelinase, SMPD3, was predominantly upregulated in the liver tissues of the mice displaying a phenotype of steatosis. Moreover, nSMase2 activity was elevated in these tissues of the liver. Pharmacological and genetic inhibition of nSMase2 prevented intracellular lipid accumulation and TNFα-induced inflammation in in-vitro HepG2-steatosis cellular model. Furthermore, nSMase2 inhibition ameliorates oxidative damage by rescuing PPARα and preventing cell death associated with high glucose/oleic acid-induced fat accumulation in HepG2 cells. Collectively, our findings highlight the prominent role of nSMase2 in hepatic steatosis, which could serve as a potential therapeutic target for NAFLD and other hepatic steatosis-linked disorders.

The removal of contaminants from aqueous solutions by adsorption onto carbonaceous materials has attracted increasing interest in recent years. In this study, pristine and oxidized activated carbon (AC) fabrics with different surface textures and porosity characteristics were used for the removal of crystal violet (CV) dye from aqueous solutions. Batch adsorption experiments were performed to investigate the CV adsorption performance of the AC fabrics in terms of contact time, temperature, adsorbate concentration and adsorbent amount. Evaluation of the thermodynamic parameters and the adsorption performance of the AC fabrics in ground water and sea water solutions were also carried out. Langmuir isotherm model, pseudo first and pseudo second order kinetics models were utilized to analyze and fit the adsorption data. The introduction of oxygen-based functional groups on the surface of AC fabrics was carried out through a nitric acid treatment. This oxidation process resulted in a significant reduction in the surface area and pore volume, along with a small increase in the average pore size and a significant enhancement in the CV adsorption capacity, indicating that the dye molecules are mainly adsorbed on the external surface of the carbon fabrics. The herein evaluated 428 mg/g adsorption capacity at 55 °C for the oxidized non-woven AC fabric is one of the highest adsorption capacity values reported in the literature for CV removal using AC materials. Thermodynamic studies showed that the adsorption occurs spontaneously and is an endothermic and entropy-driven reaction. Furthermore, pristine and oxidized non-woven AC fabrics displayed more than 90% CV uptake from sea water samples, underlining the great potential these fabrics possess for the removal of dyes from natural/multicomponent waters.

Dysregulated metabolic dynamics are evident in both cancer and diabetes, with metabolic alterations representing a facet of the myriad changes observed in these conditions. This review delves into the commonalities in metabolism between cancer and type 2 diabetes (T2D), focusing specifically on the contrasting roles of oxidative phosphorylation (OXPHOS) and glycolysis as primary energy-generating pathways within cells. Building on earlier research, we explore how a shift towards one pathway over the other serves as a foundational aspect in the development of cancer and T2D. Unlike previous reviews, we posit that this shift may occur in seemingly opposing yet complementary directions, akin to the Yin and Yang concept. These metabolic fluctuations reveal an intricate network of underlying defective signaling pathways, orchestrating the pathogenesis and progression of each disease. The Warburg phenomenon, characterized by the prevalence of aerobic glycolysis over minimal to no OXPHOS, emerges as the predominant metabolic phenotype in cancer. Conversely, in T2D, the prevailing metabolic paradigm has traditionally been perceived in terms of discrete irregularities rather than an OXPHOS-to-glycolysis shift. Throughout T2D pathogenesis, OXPHOS remains consistently heightened due to chronic hyperglycemia or hyperinsulinemia. In advanced insulin resistance and T2D, the metabolic landscape becomes more complex, featuring differential tissue-specific alterations that affect OXPHOS. Recent findings suggest that addressing the metabolic imbalance in both cancer and diabetes could offer an effective treatment strategy. Numerous pharmaceutical and nutritional modalities exhibiting therapeutic effects in both conditions ultimately modulate the OXPHOS–glycolysis axis. Noteworthy nutritional adjuncts, such as alpha-lipoic acid, flavonoids, and glutamine, demonstrate the ability to reprogram metabolism, exerting anti-tumor and anti-diabetic effects. Similarly, pharmacological agents like metformin exhibit therapeutic efficacy in both T2D and cancer. This review discusses the molecular mechanisms underlying these metabolic shifts and explores promising therapeutic strategies aimed at reversing the metabolic imbalance in both disease scenarios.

The identification and assessment of plant stress using wetland satellite images is a major task in remote sensing. In this study, one of the largest constructed wetlands (CWs) in the world, located in the Sultanate of Oman, was examined, assessed, and evaluated using remote sensor data from Sentinel-2. This CW system treats produced water generated during oil exploration activities in a desert environment; thus, CW vegetation is subjected to stress induced by oil hydrocarbons and water salinity. This study examined the plant stress and detected changes between the years of 2017 and 2019. Sentinel satellite images were evaluated for vegetation status extraction. The Normalized Difference Vegetation Index (NDVI), Modified Soil-Adjusted Vegetation Index (MSAVI), and Normalized Difference Salinity Index (NDSI) were used to evaluate the vegetation change. The results showed a comprehensive mapping identification of the plant stress and water flow parameter factors including oil in water contamination (OIW), dissolved oxygen (DO), water temperature (WT), and water conductivity (COND). Among the three indices, it was found that the NDVI showed a very good correlation with all parameters in both years with average R2 = 0.78, 0.67, 0.75, and 0.60 for OIW, DO, WT, and COND, respectively. The same trend was found for MSAVI but with R2 = 0.59, 0.48, 0.55, and 0.56 for OIW, DO, WT, and COND, respectively. This shows that the NDVI performed better than the MSAVI in evaluating the water flow parameters. On the other hand, the NDSI showed a strong correlation with one flow parameter, that is, water conductivity, especially at the outlet cells of the CW with R2 = 0.86 and 0.82 for winter time and summer time, respectively. The synchronization and correlation between the water flow parameters and remote sensing vegetation indices in this study lead to a new approach to large-scale landscape wetland monitoring that improves and helps predict any degradation or stress on vegetation growth. Furthermore, the results of this work can help decision makers potentially modify the wetland design and water flow path to improve future expansion phases. The mapping of such a critical and massive industrial CW should consider the use of high spatial resolution sensors where identifications and classifications are further improved. In summary, this research demonstrates that it is feasible to estimate vegetation stress within the constructed wetland using remote sensing techniques across extensive regions when an ample dataset comprising field data, satellite imagery, and supporting information is accessible.

Background: Angiopoietin-like protein 8 (ANGPTL8) is known to regulate lipid metabolism and inflammation. It interacts with ANGPTL3 and ANGPTL4 to regulate lipoprotein lipase (LPL) activity and with IKK to modulate NF-κB activity. Further, a single nucleotide polymorphism (SNP) leading to the ANGPTL8 R59W variant associates with reduced low-density lipoprotein/high-density lipoprotein (LDL/HDL) and increased fasting blood glucose (FBG) in Hispanic and Arab individuals, respectively. In this study, we investigate the impact of the R59W variant on the inflammatory activity of ANGPTL8. Methods: The ANGPTL8 R59W variant was genotyped in a discovery cohort of 867 Arab individuals from Kuwait. Plasma levels of ANGPTL8 and inflammatory markers were measured and tested for associations with the genotype; the associations were tested for replication in an independent cohort of 278 Arab individuals. Impact of the ANGPTL8 R59W variant on NF-κB activity was examined using approaches including overexpression, luciferase assay, and structural modeling of binding dynamics. Results: The ANGPTL8 R59W variant was associated with increased circulatory levels of tumor necrosis factor alpha (TNFα) and interleukin 7 (IL7). Our in vitro studies using HepG2 cells revealed an increased phosphorylation of key inflammatory proteins of the NF-κB pathway in individuals with the R59W variant as compared to those with the wild type, and TNFα stimulation further elevated it. This finding was substantiated by increased luciferase activity of NF-κB p65 with the R59W variant. Modeled structural and binding variation due to R59W change in ANGPTL8 agreed with the observed increase in NF-κB activity. Conclusion: ANGPTL8 R59W is associated with increased circulatory TNFα, IL7, and NF-κB p65 activity. Weak transient binding of the ANGPTL8 R59W variant explains its regulatory role on the NF-κB pathway and inflammation.

Nitrogen (N) deficiency can limit rice productivity, whereas the over- and underapplication of N results in agronomic and economic losses. Process-based crop models are useful tools and could assist in optimizing N management, enhancing the production efficiency and profitability of upland rice production systems. The study evaluated the ability of CSM–CERES–Rice to determine optimal N fertilization rate for different sowing dates of upland rice. Field experimental data from two growing seasons (2018–2019 and 2019–2020) were used to simulate rice responses to four N fertilization rates (N30, N60, N90 and a control–N0) applied under three different sowing windows (SD1, SD2 and SD3). Cultivar coefficients were calibrated with data from N90 under all sowing windows in both seasons and the remaining treatments were used for model validation. Following model validation, simulations were extended up to N240 to identify the sowing date’s specific economic optimum N fertilization rate (EONFR). Results indicated that CSM–CERES–Rice performed well both in calibration and validation, in simulating rice performance under different N fertilization rates. The d-index and nRMSE values for grain yield (0.90 and 16%), aboveground dry matter (0.93 and 13%), harvest index (0.86 and 7%), grain N contents (0.95 and 18%), total crop N uptake (0.97 and 15%) and N use efficiencies (0.94–0.97 and 11–15%) during model validation indicated good agreement between simulated and observed data. Extended simulations indicated that upland rice yield was responsive to N fertilization up to 180 kg N ha−1 (N180), where the yield plateau was observed. Fertilization rates of 140, 170 and 130 kg N ha−1 were identified as the EONFR for SD1, SD2 and SD3, respectively, based on the computed profitability, marginal net returns and N utilization. The model results suggested that N fertilization rate should be adjusted for different sowing windows rather than recommending a uniform N rate across sowing windows. In summary, CSM–CERES–Rice can be used as a decision support tool for determining EONFR for seasonal sowing windows to maximize the productivity and profitability of upland rice production.

Post-translational modifications (PTMs) play important roles in regulating several human diseases, like cancer, neurodegenerative disorders, and metabolic disorders. Investigating PTMs’ contribution to protein functions is critical for modern biology and medicine. Proprotein convertases (PCs) are irreversible post-translational modifiers that have been extensively studied and are considered as key targets for novel therapeutics. They cleave proteins at specific sites causing conformational changes affecting their functions. Furin is considered as a PC model in regulating growth factors and is involved in regulating many pro-proteins. The mammalian target of the rapamycin (mTOR) signaling pathway is another key player in regulating cellular processes and its dysregulation is linked to several diseases including type 2 diabetes (T2D). The role of furin in the context of diabetes has been rarely explored and is currently lacking. Moreover, furin variants have altered activity that could have implications on overall health. In this review, we aim to highlight the role of furin in T2D in relation to mTOR signaling. We will also address furin genetic variants and their potential effect on T2D and β-cell functions. Understanding the role of furin in prediabetes and dissecting it from other confounding factors like obesity is crucial for future therapeutic interventions in metabolic disorders.

A suitable nitrogen (N) application rate (NAR) and ideal planting period could improve upland rice productivity, enhance the soil water utilization, and reduce N losses. This study was conducted for the assessment and application of the EPIC model to simulate upland rice productivity, soil water, and N dynamics under different NARs and planting windows (PWs). The nitrogen treatments were 30 (N30), 60 (N60), and 90 (N90) kg N ha−1 with a control (no N applied −N0). Planting was performed as early (PW1), moderately delayed (PW2), and delayed (PW3) between September and December of each growing season. The NAR and PW impacted upland rice productivity and the EPIC model predicted grain yield, aboveground biomass, and harvest index for all NARs in all PWs with a normalized good–excellent root mean square error (RMSEn) of 7.4–9.4%, 9.9–12.2%, and 2.3–12.4% and d-index range of 0.90–0.98, 0.87–0.94, and 0.89–0.91 for the grain yield, aboveground biomass, and harvest index, respectively. For grain and total plant N uptake, RMSEn ranged fair to excellent with values ranging from 10.3 to 22.8% and from 6.9 to 28.1%, and a d-index of 0.87–0.97 and 0.73–0.99, respectively. Evapotranspiration was slightly underestimated for all NARs at all PWs in both seasons with excellent RMSEn ranging from 2.0 to 3.1% and a d-index ranging from 0.65 to 0.97. A comparison of N and water balance components indicated that PW was the major factor impacting N and water losses as compared to NAR. There was a good agreement between simulated and observed soil water contents, and the model was able to estimate fluctuations in soil water contents. An adjustment in the planting window would be necessary for improved upland rice productivity, enhanced N, and soil water utilization to reduce N and soil water losses. Our results indicated that a well-calibrated EPIC model has the potential to identify suitable N and seasonal planting management options.

Cellulose is the most abundant organic material on our planet which has a key role in our daily life (e.g., paper, packaging). In recent years, the need for replacing fossil-based materials has expanded the application of cellulose and cellulose derivatives including into electronics and sensing. The combination of nanostructures with cellulose nanofibers (CNFs) is expected to create new opportunities for the development of innovative electronic devices. In this paper, we report on a single-step process for the low temperature (

Among the different drug targets of SARS-CoV-2, a multi-domain protein known as NSP3 is a critical element of the translational and replication machinery. The macrodomain-I, in particular, has been reported to have an essential role in the viral attack on the innate immune response. In this study, we explore natural medicinal compounds and identify potential inhibitors to target the SARS-CoV-2–NSP3 macrodomain-I. Computational modeling and simulation tools were utilized to investigate the structural-dynamic properties using triplicates of 100 ns MD simulations. In addition, the MM/GBSA method was used to calculate the total binding free energy of each inhibitor bound to macrodomain-I. Two significant hits were identified: 3,5,7,4′-tetrahydroxyflavanone 3′-(4-hydroxybenzoic acid) and 2-hydroxy-3-O-beta-glucopyranosyl-benzoic acid. The structural-dynamic investigation of both compounds with macrodomain-I revealed stable dynamics and compact behavior. In addition, the total binding free energy for each complex demonstrated a robust binding affinity, of ΔG −61.98 ± 0.9 kcal/mol for Compound A, while for Compound B, the ΔG was −45.125 ± 2.8 kcal/mol, indicating the inhibitory potential of these compounds. In silico bioactivity and dissociation constant (KD) determination for both complexes further validated the inhibitory potency of each compound. In conclusion, the aforementioned natural products have the potential to inhibit NSP3, to directly rescue the host immune response. The current study provides the basis for novel drug development against SARS-CoV-2 and its variants.

ANGPTL8 is recognized as a regulator of lipid metabolism through its role in inhibiting lipoprotein lipase activity. ANGPTL8 gene variants, particularly rs2278426 leading to the R59W variant in the protein, have been associated with lipid traits in various ethnicities. We aimed to use metabolomics to understand the impact of the ANGPTL8 R59W variant on metabolites in humans. We used the Biocrates-p400 kit to quantify 408 plasma metabolites in 60 adult male Arab individuals from Kuwait and identify differences in metabolite levels between individuals carrying reference genotypes and those with carrier genotypes at ANGPTL8 rs2278426. Individuals with carrier genotypes (CT+TT) compared to those carrying the reference genotype (CC) showed statistically significant differences in the following metabolites: acylcarnitine (perturbs metabolic pathways), phosphatidylcholine (supports liver function and cholesterol levels), cholesteryl ester (brings chronic inflammatory response to lipoprotein depositions in arteries), α-aminoadipic acid (modulates glucose homeostasis), histamine (regulates glucose/lipid metabolism), sarcosine (links amino acid and lipid metabolism), diacylglycerol 42:1 (regulates homeostasis of cellular lipid stores), and lysophosphatidylcholine (regulates oxidative stress and inflammatory response). Functional aspects attributed to these metabolites indicate that the ANGPTL8 R59W variant influences the concentrations of lipid- and inflammation-related metabolites. This observation further highlights the role of ANGPTL8 in lipid metabolism.

Obesity is characterized by chronic low-grade inflammation. Obese people have higher levels of caveolin-1 (CAV1), a structural and functional protein present in adipose tissues (ATs). We aimed to define the inflammatory mediators that influence CAV1 gene regulation and the associated mechanisms in obesity. Using subcutaneous AT from 27 (7 lean and 20 obese) normoglycemic individuals, in vitro human adipocyte models, and in vivo mice models, we found elevated CAV1 expression in obese AT and a positive correlation between the gene expression of CAV1, tumor necrosis factor-alpha (TNF-α), and the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB). CAV1 gene expression was associated with proinflammatory cytokines and chemokines and their cognate receptors (r ≥ 0.447, p ≤ 0.030), but not with anti-inflammatory markers. CAV1 expression was correlated with CD163, indicating a prospective role for CAV1 in the adipose inflammatory microenvironment. Unlike wild-type animals, mice lacking TNF-α exhibited reduced levels of CAV1 mRNA/proteins, which were elevated by administering exogenous TNF-α. Mechanistically, TNF-α induces CAV1 gene transcription by mediating NF-κB binding to its two regulatory elements located in the CAV1 proximal regulatory region. The interplay between CAV1 and the TNF-α signaling pathway is intriguing and has potential as a target for therapeutic interventions in obesity and metabolic syndromes.

Tumor cells express antigens that should induce immune-mediated rejection; however, spontaneous rejection of established tumors is rare. Recent evidence suggests that patients suffering from cancer exhibit an elevation in regulatory T cells population, a subset of CD4+ T cells, which suppress tumor recognition and elimination by cytotoxic T cells. This study investigates immunotherapeutic strategies to overcome the immunosuppressive effects exerted by regulatory T cells. A novel immunotherapeutic strategy was developed by simultaneous administration of oral microparticulate breast cancer vaccines and cyclophosphamide, a regulatory T cell inhibitor. Breast cancer vaccine microparticles were prepared by spray drying, and administered orally to female mice inoculated with 4TO7 murine breast cancer cells in combination with a low dose of intraperitoneally administered cyclophosphamide. Mice receiving the combination of vaccine microparticles and cyclophosphamide exhibited maximal tumor regression and the highest survival rate compared with the control groups. This study highlights the importance of cancer vaccination along with regulatory T cell depletion in cancer therapy, and suggests that a low dose of cyclophosphamide that specifically and significantly depletes regulatory T cells may be a highly effective immunotherapeutic strategy for the treatment of cancer.

Commonly known as a subsistence culture, cassava came to be considered a commodity and key to adding value. However, this tuber’s processing for starch and flour production is responsible for generating a large amount of waste that causes serious environmental problems. This biomass of varied biochemical composition has excellent potential for producing fuels (biogas, bioethanol, butanol, biohydrogen) and non-energetic products (succinic acid, glucose syrup, lactic acid) via biorefinery. However, there are environmental challenges, leading to uncertainties related to the sustainability of biorefineries. Thus, the provision of information generated in life cycle assessment (LCA) can help reduce bottlenecks found in the productive stages, making production more competitive. Within that, this review concentrates information on the production of value-added products, the environmental impact generated, and the sustainability of biorefineries.

Steroid receptor RNA activator gene (SRA1) emerges as a player in pathophysiological responses of adipose tissue (AT) in metabolic disorders such as obesity and type 2 diabetes (T2D). We previously showed association of the AT SRA1 expression with inflammatory cytokines/chemokines involved in metabolic derangement. However, the relationship between altered adipose expression of SRA1 and the innate immune Toll-like receptors (TLRs) as players in nutrient sensing and metabolic inflammation as well as their downstream signaling partners, including interferon regulatory factors (IRFs), remains elusive. Herein, we investigated the association of AT SRA1 expression with TLRs, IRFs, and other TLR-downstream signaling mediators in a cohort of 108 individuals, classified based on their body mass index (BMI) as persons with normal-weight (N = 12), overweight (N = 32), and obesity (N = 64), including 55 with and 53 without T2D. The gene expression of SRA1, TLRs-2,3,4,7,8,9,10 and their downstream signaling mediators including IRFs-3,4,5, myeloid differentiation factor 88 (MyD88), interleukin-1 receptor-associated kinase 1 (IRAK1), and nuclear factor-κB (NF-κB) were determined using qRT-PCR and SRA1 protein expression was determined by immunohistochemistry. AT SRA1 transcripts’ expression was significantly correlated with TLRs-3,4,7, MyD88, NF-κB, and IRF5 expression in individuals with T2D, while it associated with TLR9 and TRAF6 expression in all individuals, with/without T2D. SRA1 expression associated with TLR2, IRAK1, and IRF3 expression only in individuals with obesity, regardless of diabetes status. Furthermore, TLR3/TLR7/IRAK1 and TLR3/TLR9 were identified as independent predictors of AT SRA1 expression in individuals with obesity and T2D, respectively. Overall, our data demonstrate a direct association between the AT SRA1 expression and the TLRs together with their downstream signaling partners and IRFs in individuals with obesity and/or T2D.

In the original article [...]

Caveolin-1 (CAV1) is implicated in the pathophysiology of diabetes and obesity. Previously, we demonstrated an association between the CAV1 rs1997623 C > A variant and metabolic syndrome (MetS). Here, we decipher the functional role of rs1997623 in CAV1 gene regulation. A cohort of 38 patients participated in this study. The quantitative MetS scores (siMS) of the participants were computed. CAV1 transcript and protein expression were tested in subcutaneous adipose tissue using RT-PCR and immunohistochemistry. Chromatin immunoprecipitation assays were performed using primary preadipocytes isolated from individuals with different CAV1 rs1997623 genotypes (AA, AC, and CC). The regulatory region flanking the variant was cloned into a luciferase reporter plasmid and expressed in human preadipocytes. Additional knockdown and overexpression assays were carried out. We show a significant correlation between siMS and CAV1 transcript levels and protein levels in human adipose tissue collected from an Arab cohort. We found that the CAV1 rs1997623 A allele generates a transcriptionally active locus and a new transcription factor binding site for early B-cell factor 1 (EBF1), which enhanced CAV1 expression. Our in vivo and in vitro combined study implicates, for the first time, EBF1 in regulating CAV1 expression in individuals harboring the rs1997623 C > A variant.

Research in metal matrix composites (MMCs) indicates that superior mechanical properties may be achieved by embedding reinforcement materials. However, the development of new composite powder for additive manufacturing requires an in-depth understanding of its key characteristics prior to its use in the fabrication process. This paper focuses on the low-energy ball milling (LEBM) of aluminium 2024 alloy (AA2024) reinforced with graphene nanoplatelets (GNPs). The main aim is to investigate the effect of the milling time (from 0.5 to 16 h) on the morphology and flowability of the powder. The study shows that, while short milling times (under 2 h) could not break the Van der WaRals forces between nanoparticles, GNPs were well separated and sufficiently covered the powder surface after 4 h of milling, thanks to the continuously applied impact energy. Longer milling time provides increasingly similar flowability results, confirmed by both the experimental work and discrete element model (DEM) simulations. Moreover, the ball milling process decreases the crystallite size of the milled powder by 24%, leading to a 3% higher microhardness. Lastly, the surface energy of the powder was determined as 1.4 mJ/m2 by DEM, using the angle of repose of the as-received powder from experimental work.

Background: Diabetes is associated with several complications, including neuropathic pain, which is difficult to manage with currently available drugs. Descending noradrenergic neurons possess antinociceptive activity; however, their involvement in diabetic neuropathic pain remains to be explored. Methods: To infer the regulatory role of this system, we examined as a function of diabetes, the expression and localization of alpha-2A adrenoceptors (α2-AR) in the dorsal root ganglia and key regions of the central nervous system, including pons and lumbar segment of the spinal cord using qRT-PCR, Western blotting, and immunofluorescence-based techniques. Results: The data revealed that presynaptic synaptosomal-associated protein-25 labeled α2-AR in the central and peripheral nervous system of streptozotocin diabetic rats was upregulated both at the mRNA and protein levels. Interestingly, the levels of postsynaptic density protein-95 labeled postsynaptic neuronal α2-AR remained unaltered as a function of diabetes. These biochemical abnormalities in the noradrenergic system of diabetic animals were associated with increased pain sensitivity as typified by the presence of thermal hyperalgesia and cold/mechanical allodynia. The pain-related behaviors were assessed using Hargreaves apparatus, cold-plate and dynamic plantar aesthesiometer. Chronically administered guanfacine, a selective α2-AR agonist, to diabetic animals downregulated the upregulation of neuronal presynaptic α2-AR and ameliorated the hyperalgesia and the cold/mechanical allodynia in these animals. Conclusion: Together, these findings demonstrate that guanfacine may function as a potent analgesic and highlight α2-AR, a key component of the descending neuronal autoinhibitory pathway, as a potential therapeutic target in the treatment of diabetic neuropathic pain.

In obesity, macrophage activation and infiltration in adipose tissue (AT) underlie chronic low-grade inflammation-induced insulin resistance. Although dectin-1 is primarily a pathogen recognition receptor and innate immune response modulator, its role in metabolic syndromes remains to be clarified. This study aimed to investigate the dectin-1 gene expression in subcutaneous AT in the context of obesity and associated inflammatory markers. Subcutaneous AT biopsies were collected from 59 nondiabetic (lean/overweight/obese) individuals. AT gene expression levels of dectin-1 and inflammatory markers were determined via real-time reverse transcriptase-quantitative polymerase chain reaction. Dectin-1 protein expression was assessed using immunohistochemistry. Plasma lipid profiles were measured by ELISA. AT dectin-1 transcripts and proteins were significantly elevated in obese as compared to lean individuals. AT dectin-1 transcripts correlated positively with body mass index and fat percentage (r ≥ 0.340, p ≤ 0.017). AT dectin-1 RNA levels correlated positively with clinical parameters, including plasma C-reactive protein and CCL5/RANTES, but negatively with that of adiponectin. The expression of dectin-1 transcripts was associated with that of various proinflammatory cytokines, chemokines, and their cognate receptors (r ≥ 0.300, p ≤ 0.05), but not with anti-inflammatory markers. Dectin-1 and members of the TLR signaling cascade were found to be significantly associated, suggesting an interplay between the two pathways. Dectin-1 expression was correlated with monocyte/macrophage markers, including CD16, CD68, CD86, and CD163, suggesting its monocytes/macrophage association in an adipose inflammatory microenvironment. Dectin-1 expression was independently predicted by CCR5, CCL20, TLR2, and MyD88. In conclusion, dectin-1 may be regarded as an AT biomarker of metabolic inflammation in obesity.

Herein, we describe the facile synthesis of spinel MgFe2O4 ferrite and its potential use as a gas sensor using a straightforward and reliable sol–gel approach, i.e., the glycine-assisted auto-combustion route. The novelty in obtaining the sensing material via the auto-combustion route is its inherent simplicity and capability to produce the material at an industry scale. The said cost-effective process makes use of simple metal salts (Mg and Fe-nitrates) and glycine in an aqueous solution, which leads to the formation of spinel MgFe2O4 ferrite. A single-phase crystallinity with crystallite sizes ranging between 36 and 41 nm was observed for the synthesized materials using the X-ray diffraction (XRD) technique. The porous morphologies of the synthesized materials caused by auto-ignition during the combustion process were validated by the microscopic investigations. The EDS analysis confirmed the constituted elements such as Mg, Fe, and O, without any impurity peaks. The gas-sensing ability of the synthesized ferrites was examined to detect various reducing gases such as LPG, ethanol, acetone, and ammonia. The ferrite showed the highest response (>80%) toward LPG with the response and recovery times of 15 s and 23 s, respectively. Though the sensor responded low toward ammonia (~30%), its response and recovery times were very quick, i.e., 7 s and 9 s, respectively. The present investigation revealed that the synthesized ferrite materials are good candidates for fabricating high-performance sensors for reducing gases in real-world applications.

Chronic low-grade inflammation induced by obesity is a central risk factor for the development of metabolic syndrome. High low-density lipoprotein cholesterol (LDL-c) induces inflammation, which is a common denominator in metabolic syndrome. IL-23 plays a significant role in the pathogenesis of meta-inflammatory diseases; however, its relationship with LDL-c remains elusive. In this cross-sectional study, we determined whether the adipose tissue IL-23 expression was associated with other inflammatory mediators in people with increased plasma LDL-c concentrations. Subcutaneous adipose tissue biopsies were collected from 60 people, sub-divided into two groups based on their plasma LDL-c concentrations (p < 0.01); IL-23 correlated positively with LDL-c (r = 0.471, p < 0.0001). Immunochemistry analysis showed that AT IL-23 protein expression was also elevated in the people with H-LDL-c. IL-23 expression in the high LDL-c group was associated with multiple adipose inflammatory biomarkers (p ≤ 0.05), including macrophage markers (CD11c, CD68, CD86, CD127), TLRs (TLR8, TLR10), IRF3, pro-inflammatory cytokines (TNF-α, IL-12, IL-18), and chemokines (CXCL8, CCL3, CCL5, CCL15, CCL20). Notably, in this cohort, IL-23 expression correlated inversely with plasma adiponectin. In conclusion, adipose IL-23 may be an inflammatory biomarker for disease progression in people with high LDL-c.

The gold-standard approach for diagnosing and confirming Severe Acute Respiratory Syndrome Corona Virus-2 (SARS-CoV-2) infection is reverse transcription-polymerase chain reaction (RT-PCR). This method, however, is inefficient in detecting previous or dormant viral infections. The presence of antigen-specific antibodies is the fingerprint and cardinal sign for diagnosis and determination of exposure to infectious agents including Corona virus disease-2019 (COVID-19). This cross-sectional study examined the presence of SARS-CoV-2 spike-specific immunoglobulin G (IgG) among asymptomatic blood donors in Makkah region. A total of 4368 asymptomatic blood donors were enrolled. They were screened for spike-specific IgG using ELISA and COVID-19 RNA by real-time PCR. COVID-19 IgG was detected among 2248 subjects (51.5%) while COVID-19-RNA was detected among 473 (10.8%) subjects. The IgG frequency was significantly higher among males and non-Saudi residents (p < 0.001 each) with no significant variation in IgG positivity among blood donors with different blood groups. In addition, COVID-19 RNA frequency was significantly higher among donors below 40-years old (p = 0.047, χ2 = 3.95), and non-Saudi residents (p = 0.001, χ2 = 304.5). The COVID-19 IgG levels were significantly higher among the RNA-positive donors (p = 001), and non-Saudi residents (p = 0.041), with no variations with age or blood group (p > 0.05). This study reveals a very high prevalence of COVID-19 IgG and RNA among asymptomatic blood donors in Makkah, Saudi Arabia indicating a high exposure rate of the general population to COVID-19; particularly foreign residents. It sheds light on the spread on COVID-19 among apparently healthy individuals at the beginning of the pandemic and could help in designing various control measures to minimize viral spread.

The C-type lectin receptors (CLRs) Dectin-1 and Dectin-2 are involved in several innate immune responses and are expressed mainly in dendritic cells, monocytes, and macrophages. Dectin-1 activation exacerbates obesity, inflammation, and insulin resistance/type 2 diabetes (T2D). However, the role of Dectin-2 is not clear in T2D. This study aims to evaluate the expression and function of Dectin-2 in peripheral blood mononuclear cells (PBMCs) isolated from diabetic patients and non-diabetic controls. Flow-cytometry and qRT-PCR were performed to evaluate the expression of Dectin-2 in different leukocyte subpopulations isolated from T2D patients (n = 10) and matched non-diabetic controls (n = 11). The functional activity of Dectin-2 was identified in PBMCs. CRP, IL-1β, and TNF-α concentrations were determined by ELISA. siRNA transfection and Western blotting were performed to assess p-Syk and p-NF-kB expression. siRNA transfection was performed to knock down the gene of interest. Our results show that Dectin-2 expression was the highest in monocytes compared with other leukocyte subpopulations. The expression of Dectin-2 was significantly increased in the monocytes of T2D patients compared with non-diabetic controls. Dectin-2 expression positively correlated with markers of glucose homeostasis, including HOMA-IR and HbA1c. The expression of inflammatory markers was elevated in the PBMCs of T2D patients. Interestingly, SOCS3, a negative regulator of inflammation, was expressed significantly lowlier in the PBMCs of T2D patients. Moreover, SOCS3 expression was negatively correlated with Dectin-2 expression level. The further analysis of inflammatory signaling pathways showed a persistent activation of the Dectin-2-Syk-NFkB pathway that was instigated by the diminished expression of SOCS3. Dectin-2 activation failed to induce SOCS3 expression and suppress subsequent inflammatory responses in the PBMCs of diabetic patients. siRNA-mediated knockdown of SOCS3 in PBMCs displayed a similar inflammatory phenotype to diabetic PBMCs when exposed to Dectin-2 ligands. Altogether, our findings suggest that elevated Dectin-2 and its relationship with SOCS3 could be involved in the abnormal immune response observed in T2D patients.

Nitrogen balance index (NBI) is an important indicator for scientific diagnostic and quantitative research on crop growth status. The quick and accurate assessment of NBI is necessary for farmers to make timely N management decisions. The objective of the study was to estimate winter wheat NBI based on canopy hyperspectral features between 400–1350 nm combined with machine learning (ML) methods in the individual and whole growth stages. In this study, 3 years of winter wheat plot experiments were conducted. Ground-level canopy hyperspectral reflectance and corresponding plant NBI values were measured during the jointing, booting, flowering and filling stages. Continuous removal spectra (CRS) and logarithmic transformation spectra (LOGS) were derived from the original canopy spectra. Sensitive bands and vegetation indices (VIs) highly correlated with NBI under different spectral transformations were selected as hyperspectral features to construct the NBI estimation models combined with ML algorithms. The study indicated that the spectral transformation significantly improved the correlation between the sensitive bands, VIs and the NBI. The correlation coefficient of the sensitive band in CRS in the booting stage increased by 27.87%, reaching −0.78. The leaf chlorophyll index (LCI) in LOGS had the highest correlation with NBI in the filling stage, reaching a correlation coefficient of −0.96. The NBI prediction accuracies based on the sensitive band combined with VIs were generally better than those based on the univariate hyperspectral feature, and the prediction accuracy of each growth stage was better than that of the whole growth stage. The random forest regression (RFR) method performed better than the support vector regression (SVR) and partial least squares regression (PLS) methods. The NBI estimation model based on the LOGS-RFR method in the filling stage could explain 95% of the NBI variability with relative prediction deviation (RPD) being 3.69. These results will provide a scientific basis for better nitrogen nutrition monitoring, diagnosis, and later for field management of winter wheat.

The changeable nature of renewable sources creates difficulties in system security and stability. Therefore, it is necessary to study system risk in several power system scenarios. In a wind-integrated deregulated power network, the wind farm needs to submit the bid for its power-generating quantities a minimum of one day ahead of the operation. The wind farm submits the data based on the expected wind speed (EWS). If any mismatch occurs between real wind speed (RWS) and expected wind speed, ISO enforces the penalty/rewards to the wind farm. In a single word, this is called the power market imbalance cost, which directly distresses the system profit. Here, solar PV and battery energy storage systems are used along by the wind farm to exploit system profit by grasping the negative outcome of imbalance cost. Along with system profit, the focus has also been on system risk. The system risk has been calculated using the risk assessment factors, i.e., Value-at-Risk (VaR) and Cumulative Value-at-risk (CVaR). The work is performed on a modified IEEE 14 and modified IEEE 30 bus test system. The solar PV-battery storage system can supply the demand locally first, and then the remaining power is given to the electrical grid. By using this concept, the system risk can be minimized by the incorporation of solar PV and battery storage systems, which have been studied in this work. A comparative study has been performed using three dissimilar optimization methods, i.e., Artificial Gorilla Troops Optimizer Algorithm (AGTO), Artificial Bee Colony Algorithm (ABC), and Sequential Quadratic Programming (SQP) to examine the consequence of the presented technique. The AGTO has been used for the first time in the risk assessment and alleviation problem, which is the distinctiveness of this work.

Background: Severe coronavirus disease 2019 (COVID-19) is associated with increased risk of thrombosis and thromboembolism. Exposure to COVID-19 vaccines is also associated with immune thrombotic thrombocytopenia, ischemic stroke, intracerebral haemorrhage, and cerebral venous thrombosis, and it is linked with systemic activation of coagulation. Methods: We assess the circulating levels of coagulation factors (factors XI, XII, XIII, and prothrombin) and antithrombin in individuals who completed two doses of either ChAdOx1-S or BNT162b2 COVID-19 vaccine, within the timeframe of two months, who had no previous history of COVID-19. Results: Elevated levels of factors XI, XII, XIII, prothrombin, and antithrombin were seen compared to unvaccinated controls. Levels of coagulation factors, antithrombin, and prothrombin to antithrombin ratio were higher with BNT162b2 compared to ChAdOx1-S vaccine. Conclusions: The clinical significance of such coagulation homeostasis disruption remains to be elucidated but it is worthy of global scientific follow-up effort.

(1) Background: In pulmonary arterial hypertension (PAH), pregnancy is regarded a contraindication due to high maternal and fetal morbidity and mortality. We report our experience in the management of pregnancies in PAH. (2) Methods: retrospective observational study in a nationally accredited pulmonary hypertension (PH) center from 2013 to 2021. (3) Results: seven pregnancies in six women with PAH, ranging from low to high risk and 21 to 37 years old. Half had known pre-existing PAH before pregnancy. One had a multifetal gestation, and one was pregnant twice under our care. PH medical therapy and serial clinical assessment throughout pregnancy were implemented with focused attention on optimizing right heart function. Delivery was planned by a multidisciplinary team involving PH cardiology, maternal fetal medicine, and obstetric anesthesiology. Patients delivered between 31 and 40 weeks of gestation; five of the seven were via cesarean section. All received regional anesthesia and were monitored in the PH intermediate step-down unit after delivery until discharge. In all cases, delivery was without complications with excellent outcomes for the mother and child. (4) Conclusions: Multidisciplinary and tailored management of PAH in pregnancy, emphasizing optimized right heart function prior to delivery, can result in excellent clinical outcomes in a referral PH center.

This paper presents the first successful implementation of fully printed electronics for flexible and wearable smart multi-pad stimulation electrodes intended for use in medical, sports and lifestyle applications. The smart multi-pad electrodes with the electronic circuits based on organic electrochemical transistor (OECT)-based electronic circuits comprising the 3–8 decoder for active pad selection and high current throughput transistors for switching were produced by multi-layer screen printing. Devices with different architectures of switching transistors were tested in relevant conditions for electrical stimulation applications. An automated testbed with a configurable stimulation source and an adjustable human model equivalent circuit was developed for this purpose. Three of the proposed architectures successfully routed electrical currents of up to 15 mA at an output voltage of 30 V, while one was reliably performing even at 40 V. The presented results demonstrate feasibility of the concept in a range of conditions relevant to several applications of electrical stimulation.

Antimicrobial drugs face numerous challenges, including drug resistance, systemic toxic effects, and poor bioavailability. To date, treatment choices are limited, which warrants the search for novel potent antivirals, including those extracted from natural products. The seeds of Peganum harmala L. (Zygophyllaceae family) have been reported to have antimicrobial, antifungal, and anticancer activities. In the present study, a 2-hydroxy propyl-β-cyclodextrin (HPβCD)/harmala alkaloid-rich fraction (HARF) host–guest complex was prepared using a thin-film hydration method to improve the water solubility and bioavailability of HARF. The designed complex was then co-encapsulated with ascorbic acid into PLGA nanoparticles coated with polyethylene glycol (HARF–HPßCD/AA@PLGA-PEG NPs) using the W/O/W multiple emulsion-solvent evaporation method. The average particle size, PDI, and zeta potential were 207.90 ± 2.60 nm, 0.17 ± 0.01, and 31.6 ± 0.20 mV, respectively. The entrapment efficiency for HARF was 81.60 ± 1.20% and for ascorbic acid was 88 ± 2.20%. HARF–HPßCD/AA@PLGA-PEG NPs had the highest antibacterial activity against Staphylococcus aureus and Escherichia coli (MIC of 0.025 mg/mL). They also exhibited high selective antiviral activity against the H1N1 influenza virus (IC50 2.7 μg/mL) without affecting the host (MDCK cells). In conclusion, the co-encapsulation of HPCD–HARF complex and ascorbic acid into PLGA-PEG nanoparticles significantly increased the selective H1N1 killing activity with minimum host toxic effects.