Objective: To investigate the neuroprotective effects of Syzygium aromaticum(S.aromaticum)extract(500 mg/kg) on AlCl_3(300 mg/kg)-induced mouse model of oxidative stress and neurotoxicity.Methods: An ethanolic extract...Objective: To investigate the neuroprotective effects of Syzygium aromaticum(S.aromaticum)extract(500 mg/kg) on AlCl_3(300 mg/kg)-induced mouse model of oxidative stress and neurotoxicity.Methods: An ethanolic extract of S.aromaticum seeds was prepared and the active compounds were identified using nuclear magnetic resonance spectroscopy.BALB/c mice were divided into five groups(negative control, AlCl_3-treated, self-recovery, AlCl_3 + S.aromaticum, S.aromaticum only; n=10) and treated with AlCl_3 and S.aromaticum extract.Expression of oxidative markers [Superoxide dismutase 1(SOD1) and peroxiredoxin 6(Prdx6)] and amyloid precursor protein(APP) in the hippocampus and cortex was evaluated via PCR.Histopathological assessment was performed to investigate the extent of neurodegeneration.Results: It was observed that AlCl_3 exposure increased the expression of APP770 while simultaneously down regulated the expression of APP695.AlCl_3 also induced a significant decrease(P<0.05) and an increase(P<0.05) in the expression level of SOD1 and Prdx6, respectively.A substantial decrease substantial(P<0.05) in the density of Nissl substance was also observed in cortex of the mice treated with AlCl_3.Interestingly, treatment with S.aromaticum extract normalized the alterations in the expression level of SOD1, Prdx6 and APPisoforms and improved the neuronal structural damage.Conclusions: The results showed that S.aromaticum is a promising antioxidant and a neuroprotective agent.展开更多
Accurate identification of spatial patterns and risk factors of disease occurrence is crucial for public health interventions.However,the Modifiable Areal Unit Problem(MAUP)poses challenges in disease modelling by imp...Accurate identification of spatial patterns and risk factors of disease occurrence is crucial for public health interventions.However,the Modifiable Areal Unit Problem(MAUP)poses challenges in disease modelling by impacting the reliability of statistical inferences drawn from spatially aggregated data.This study examines the effect of MAUP on ecological model inference using locally and overseas-acquired COVID-19 case data from 2020 to 2023 in Queensland,Australia.Bayesian spatial Besag-York-Mollié(BYM)models were applied across four Statistical Area(SA)levels,as defined by the Australian Statistical Geography Standard,with and without covariates:Socio-Economic Indexes for Areas(SEIFA)and overseas-acquired(OA)COVID-19 cases.OA COVID-19 cases were also considered a response variable in our study.Results indicated that finer spatial scales(SA1 and SA2)captured localized patterns and significant spatial autocorrelation,while coarser levels(SA3 and SA4)smoothed spatial variability,masking potential outbreak clusters.Incorporating SEIFA as a covariate in locally-acquired(LA)cases reduced spatial autocorrelation in residuals,effectively capturing socioeconomic disparities.Conversely,OA cases showed limited effectiveness in reducing autocorrelation at finer scales.For LA cases,higher socioeconomic disadvantage was associated with increased COVID-19 incidence at finer scales,but this association became non-significant at coarser scales.OA cases showed significant positive association with higher SEIFA scores at finer scales.Model parameters displayed narrower credible intervals at finer scales,indicating greater precision,while coarser levels had increased uncertainty.SA2 emerged as an arguably optimal scale,striking a balance between spatial resolution,model stability,and interpretability.To improve inference on COVID-19 incidence,it is recommended to use data from both SA1 and SA2 levels to leverage their respective strengths.The findings emphasize the importance of selecting appropriate spatial scales and covariates or evaluating the inferential impacts of multiple scales,to address MAUP to facilitate more reliable spatial analysis.The study advocates exploring intermediate aggregation levels and multi-scale approaches to better capture nuanced disease dynamics and extend these analyses across Australia and replicating in other countries with low population densities to enhance generalizability.展开更多
Geovisual analytics provides a framework for the development of decision support tools for landscape design,analysis and optimisation.An important application is modelling the spatial-temporal movements of ruminants a...Geovisual analytics provides a framework for the development of decision support tools for landscape design,analysis and optimisation.An important application is modelling the spatial-temporal movements of ruminants and their grazing behaviour using global positioning system(GPS)collar units.This study describes the mapping and analysis of spatial distributions of animal waste products(which correlate with farm nitrogen[N]emissions)and also determination of animal feeding preferences(which correlate with animal welfare and production).Segmentation of local regions of animal N emissions provides support in meeting targets for local and international N leaching and greenhouse gas emissions.An agent-based model was used for prescreening in order to gain insights into the clustering behaviour of sheep during feeding activities.Subsequent spatial analysis demonstrated that livestock excreta are not always randomly located,but concentrated around highly localised animal gathering points,separated by the nature of the excretion.In a separate study,the statistical significance of feeding choices was determined by testing a null hypothesis on animal boundary transitions between adjacent pastures using the binomial approximation.The analysis also included compensation for the precision of the GPS sensor,which produced a fuzzy decision boundary.展开更多
In this study,we harnessed the properties of desert plants to synthesize silver nanoparticles to explore potential antimicrobial solutions.Chrozophora plicata and Heliotropium curassavicum extracts were used as green ...In this study,we harnessed the properties of desert plants to synthesize silver nanoparticles to explore potential antimicrobial solutions.Chrozophora plicata and Heliotropium curassavicum extracts were used as green reducing agents to transform silver ions into nanoparticles.Our findings revealed novel properties of C.plicata,which have not been reported before.Surface plasmon resonance peak at 453.6 and 431 nm for C.plicata and H.curassavicum,respectively,via ultraviolet(UV)spectral analysis evidenced the successful fabrication of silver nanoparticles with particle sizes ranging from 4.3-8 and 3.1-6.97 nm respectively,which was validated by field emission scanning electron microscopy(FE-SEM).X-ray diffraction analysis revealed that the crystal structure of these nanoparticles had a face-centered cubic geometry.Fourier transform infrared spectrometry of the plant extract showed strong signals corresponding to carbohydrates,proteins,and phenolics.Antibacterial assays of the silver nanoparticles from C.plicata displayed zones of inhibition at 5 and 4 mm against Staphylococcus aureus and Escherichia coli,respectively.Meanwhile,the silver nanoparticles from H.curassavicum exhibited zones of inhibition against both pathogens at 10 and 7 mm,respectively.The test samples were substantial inhibitors of S.aureus and E.coli biofilm formation since these displayed IC_(50) values in the range of 8.88-10.57 mg/mL,which is as potent as the reference ciprofloxacin.Consequently,the silver nanoparticles derived from these desert plants can be potential drug candidates for treating respiratory and digestive tract infections alone or in combination with existing antibiotics.展开更多
基金supported by research grant by National University of Sciences and Technology (NUST), Islamabad, Pakistan
文摘Objective: To investigate the neuroprotective effects of Syzygium aromaticum(S.aromaticum)extract(500 mg/kg) on AlCl_3(300 mg/kg)-induced mouse model of oxidative stress and neurotoxicity.Methods: An ethanolic extract of S.aromaticum seeds was prepared and the active compounds were identified using nuclear magnetic resonance spectroscopy.BALB/c mice were divided into five groups(negative control, AlCl_3-treated, self-recovery, AlCl_3 + S.aromaticum, S.aromaticum only; n=10) and treated with AlCl_3 and S.aromaticum extract.Expression of oxidative markers [Superoxide dismutase 1(SOD1) and peroxiredoxin 6(Prdx6)] and amyloid precursor protein(APP) in the hippocampus and cortex was evaluated via PCR.Histopathological assessment was performed to investigate the extent of neurodegeneration.Results: It was observed that AlCl_3 exposure increased the expression of APP770 while simultaneously down regulated the expression of APP695.AlCl_3 also induced a significant decrease(P<0.05) and an increase(P<0.05) in the expression level of SOD1 and Prdx6, respectively.A substantial decrease substantial(P<0.05) in the density of Nissl substance was also observed in cortex of the mice treated with AlCl_3.Interestingly, treatment with S.aromaticum extract normalized the alterations in the expression level of SOD1, Prdx6 and APPisoforms and improved the neuronal structural damage.Conclusions: The results showed that S.aromaticum is a promising antioxidant and a neuroprotective agent.
基金The National Health and Medical Research Council(NHMRC)Special Initiative in Human Health and Environmental Change(Grant No.2008937).
文摘Accurate identification of spatial patterns and risk factors of disease occurrence is crucial for public health interventions.However,the Modifiable Areal Unit Problem(MAUP)poses challenges in disease modelling by impacting the reliability of statistical inferences drawn from spatially aggregated data.This study examines the effect of MAUP on ecological model inference using locally and overseas-acquired COVID-19 case data from 2020 to 2023 in Queensland,Australia.Bayesian spatial Besag-York-Mollié(BYM)models were applied across four Statistical Area(SA)levels,as defined by the Australian Statistical Geography Standard,with and without covariates:Socio-Economic Indexes for Areas(SEIFA)and overseas-acquired(OA)COVID-19 cases.OA COVID-19 cases were also considered a response variable in our study.Results indicated that finer spatial scales(SA1 and SA2)captured localized patterns and significant spatial autocorrelation,while coarser levels(SA3 and SA4)smoothed spatial variability,masking potential outbreak clusters.Incorporating SEIFA as a covariate in locally-acquired(LA)cases reduced spatial autocorrelation in residuals,effectively capturing socioeconomic disparities.Conversely,OA cases showed limited effectiveness in reducing autocorrelation at finer scales.For LA cases,higher socioeconomic disadvantage was associated with increased COVID-19 incidence at finer scales,but this association became non-significant at coarser scales.OA cases showed significant positive association with higher SEIFA scores at finer scales.Model parameters displayed narrower credible intervals at finer scales,indicating greater precision,while coarser levels had increased uncertainty.SA2 emerged as an arguably optimal scale,striking a balance between spatial resolution,model stability,and interpretability.To improve inference on COVID-19 incidence,it is recommended to use data from both SA1 and SA2 levels to leverage their respective strengths.The findings emphasize the importance of selecting appropriate spatial scales and covariates or evaluating the inferential impacts of multiple scales,to address MAUP to facilitate more reliable spatial analysis.The study advocates exploring intermediate aggregation levels and multi-scale approaches to better capture nuanced disease dynamics and extend these analyses across Australia and replicating in other countries with low population densities to enhance generalizability.
文摘Geovisual analytics provides a framework for the development of decision support tools for landscape design,analysis and optimisation.An important application is modelling the spatial-temporal movements of ruminants and their grazing behaviour using global positioning system(GPS)collar units.This study describes the mapping and analysis of spatial distributions of animal waste products(which correlate with farm nitrogen[N]emissions)and also determination of animal feeding preferences(which correlate with animal welfare and production).Segmentation of local regions of animal N emissions provides support in meeting targets for local and international N leaching and greenhouse gas emissions.An agent-based model was used for prescreening in order to gain insights into the clustering behaviour of sheep during feeding activities.Subsequent spatial analysis demonstrated that livestock excreta are not always randomly located,but concentrated around highly localised animal gathering points,separated by the nature of the excretion.In a separate study,the statistical significance of feeding choices was determined by testing a null hypothesis on animal boundary transitions between adjacent pastures using the binomial approximation.The analysis also included compensation for the precision of the GPS sensor,which produced a fuzzy decision boundary.
文摘In this study,we harnessed the properties of desert plants to synthesize silver nanoparticles to explore potential antimicrobial solutions.Chrozophora plicata and Heliotropium curassavicum extracts were used as green reducing agents to transform silver ions into nanoparticles.Our findings revealed novel properties of C.plicata,which have not been reported before.Surface plasmon resonance peak at 453.6 and 431 nm for C.plicata and H.curassavicum,respectively,via ultraviolet(UV)spectral analysis evidenced the successful fabrication of silver nanoparticles with particle sizes ranging from 4.3-8 and 3.1-6.97 nm respectively,which was validated by field emission scanning electron microscopy(FE-SEM).X-ray diffraction analysis revealed that the crystal structure of these nanoparticles had a face-centered cubic geometry.Fourier transform infrared spectrometry of the plant extract showed strong signals corresponding to carbohydrates,proteins,and phenolics.Antibacterial assays of the silver nanoparticles from C.plicata displayed zones of inhibition at 5 and 4 mm against Staphylococcus aureus and Escherichia coli,respectively.Meanwhile,the silver nanoparticles from H.curassavicum exhibited zones of inhibition against both pathogens at 10 and 7 mm,respectively.The test samples were substantial inhibitors of S.aureus and E.coli biofilm formation since these displayed IC_(50) values in the range of 8.88-10.57 mg/mL,which is as potent as the reference ciprofloxacin.Consequently,the silver nanoparticles derived from these desert plants can be potential drug candidates for treating respiratory and digestive tract infections alone or in combination with existing antibiotics.
