Variable Concentrations Research Articles

Assessing the combined effects of chemical and mechanical parameters on silar-grown nanostructured ZnO thin films

In the literature, a comprehensive assessment of the combined impacts of chemical and mechanical parameters on the properties of thin films grown by SILAR is missing. In this work, ZnO film formation is investigated under variable precursor concentration, pH, withdrawal speed and number of cycles. Interestingly, the produced ZnO films displayed remarkable aspect ratio and morphological variability, ranging from the commonly obtained nanograins shape towards hexagonal nanorods, flower- like rods and nanoneedles, which to our knowledge have not yet been achieved by using single step SILAR process. More particularly, low concentration and intermediate pH and withdrawal rates were favorable for nanorods formation. In addition, increasing the withdrawal speed from 26 to 30 cm·min-1 resulted in a thinner film with improved rod uniformity and reduced crystallite size. This is the first study on the impact of substrate withdrawal speed on SILAR films. Among all studied parameters, the number of cycles was particularly useful for tuning film thickness, while preserving its target shape. In addition, the films grown under a higher number of cycles showed improved film crystallinity and rod orientation with reduced dislocation density, microstrain and bandgap energy. In our conditions, the most suitable combination of parameters required for exhibiting optimized nanorod-shaped coating are: a concentration of 0.07 M, pH of 10.5, speed of 30 cm·min-1 and 40 cycles. In this case, XRD, XPS, Raman and FTIR spectra displayed typical features of hexagonal Wurtzite structure of ZnO with no impurities within the film surface, whereas AFM measured a thickness of 1.4 μm with 243 nm surface roughness.

Growth-dependent concentration gradient of the oscillating Min system in Escherichia coli.

Cell division in Escherichia coli is intricately regulated by the MinD and MinE proteins, which form oscillatory waves between cell poles. These waves manifest as concentration gradients that reduce MinC inhibition at the cell center, thereby influencing division site placement. This study explores the plasticity of the MinD gradients resulting from the interdependent interplay between molecular interactions and diffusion in the system. Through live cell imaging, we observed that as cells elongate, the gradient steepens, the midcell concentration decreases, and the oscillation period stabilizes. A one-dimensional model investigates kinetic rate constants representing various molecular interactions, effectively recapitulating our experimental findings. The model reveals the nonlinear dynamics of the system and a dynamic equilibrium among these constants, which underlie variable concentration gradients in growing cells. This study enhances quantitative understanding of MinD oscillations within the cellular environment. Furthermore, it emphasizes the fundamental role of concentration gradients in cellular processes.

OPTIMIZING TRANSDERMAL PATCH FORMULATION FOR ENHANCED DELIVERY OF RIVAROXABAN: A COMPREHENSIVE DESIGN OF EXPERIMENTS APPROACH

Objective: To optimize Trans Dermal Patches (TDPs) of rivaroxaban using Poly Vinyl Pyrrolidone (PVP K30) and Hydroxypropyl Methyl Cellulose E50(HPMC E50) as hydrophilic polymers, Propylene Glycol(PG) as a plasticizer, and permeation enhancer. Methods: TDPs were crafted using a solvent casting technique with a 2-level, 3-factor factorial design. These patches were assessed for thickness, folding endurance, in vitro drug release, drug content, and moisture uptake and loss. An 8-stage diffusion cell apparatus facilitated in vitro drug release testing. The independent variables were HPMC E50, PVP K30, and PG. The change in the concentration of these independent variables resulted in the optimization of the transdermal patch. The dependent variables were the thickness, folding endurance, and in vitro diffusion. Results: The patch thickness ranged from 0.311±0.3 to 0.334±0.6. Folding endurance ranged from 58±0.7 92±6. The in vitro drug release ranged from 52.36% to 95.58%. The percentage drug content ranged from 83.58±0.4 to 95.26±0.5. The percentage of moisture content absorbed ranged from 21.36±0.13% to 25.54±0.26%. The percentage of moisture lost ranged from 1.01% to 2.31%. Conclusion: PG increased the release of rivaroxaban because it permeated the membrane. HPMC E50 is highly soluble. Thus, rivaroxaban patches are potentially suitable transdermal drug delivery systems.

Identifying TSM dynamics in arid inland lakes combining satellite imagery and wind speed

The Chah Nimeh Reservoirs (CNRs), located in Iran’s Sistan region, are critical arid inland lakes that support agriculture and supply drinking water to the region. A major concern regarding water quality in these reservoirs is the concentration of Total Suspended Matter (TSM), which has significant implications for both the local communities and the aquatic ecosystem. This study demonstrates the complicated connection between wind speed and TSM values, indicating that wind speed is an essential variable influencing TSM concentrations. By combining in-situ wind measurements with satellite imagery, we mapped TSM distributions using empirically derived models. Our investigation identified the Long Short-Term Memory (LSTM) and Attention-Mechanism-Based Dynamic Inner Partial Least Squares Long Short-Term Memory (ADiPLS-LSTM) models as effective predictors of TSM levels. Specifically, two distinct machine learning models were utilized: Rrs2TSM, which relies solely on Remote Sensing Reflectance (Rrs(λ)), and the more advanced Rrs&Wind2TSM, which incorporates both Rrs(λ) and wind data. The ADiPLS-LSTM model generated results with minimal variance, showing exceptional consistency. The Root Mean Square Error (RMSE) remains low at 0.617, while the R2 value maintained continually elevated at 0.997. It’s interesting to note that modest variations in TSM concentrations occurred when wind speed data was incorporated into the algorithm, especially during times of greater wind speeds. This study emphasizes the significant impact of wind speed on TSM dynamics in arid inland lakes, showcasing the value of satellite imagery in conducting such analyses. The findings provide essential insights for developing strategies that promote sustainable water resource management.

High-Level Calculation for Assessing the Atmospheric Reactivity of Pentachlorophenol with Hydroxyl Radical: Mechanism and Kinetics.

This work aims to investigate the reactivity of the pentachlorophenol (PCP) compound, C6Cl5OH, with a hydroxyl (OH) radical in the gas phase. Geometry optimizations and vibrational frequency calculations were performed using DFT-M06-2X/6-311++G(d,p). Single-point energy calculations were carried out using the single-reference coupled cluster method, specifically CCSD(T), and the multiconfigurational CASPT2 level of theory to characterize the atmospheric degradation processes of PCP with OH radicals and to identify which chemical species resulting from their decomposition could remain in the gas phase. The performance of various families of basis sets was tested. The widely used augmented-correlation-consistent basis set family aug-cc-pVXZ-DK (X = D, T, and Q) was compared to the atomic natural orbital basis sets ANO-RCC-VXZP (X = D, T, and Q). The energy profile at 298 K showed that the Cl- and OH-abstractions are not energetically favorable. H-abstraction and OH-addition/Ck (k = 1-6) are characterized by the lowest Gibbs energies of activation and are strongly exothermic. The canonical transition state theory (TST) with a simple Wigner tunneling correction is used to predict the rate constants over the 220-400 K temperature range for each reaction channel. The overall rate constant at 298 K based on our calculations is about 3.25 × 10-13, 3.10 × 10-15, and 2.21 × 10-15 cm3 molecule-1 s-1 at M06-2X, CASPT2/ANO-RCC-VQZP, and CASPT2/aug-cc-pVQZ-DK levels of theory, respectively. The PCP atmospheric lifetime at 298 K is predicted to be in the range from 1 to 12-16 years at 0 km in the presence of variable OH concentration (9.00 × 105 to 1.50 × 107 molecules cm-3) based on CASPT2 data.

Informing the prediction of forage quality of Mediterranean grasslands using hyperspectral reflectance: Concentration vs content, phenology, and generalisation of models

ContextRemote sensing has shown potential to provide accurate and real-time information on grassland forage quality, crucial for the management of livestock systems. However, there are still uncertainties that must be considered to make models reliable and practical. A source of discrepancy regards the measurement unit describing forage quality variables, namely either mass-based concentration (%) or mass per surface area content (kg ha−1). Furthermore, phenological patterns largely influence grassland reflectance and have a strong impact on model accuracy. Also, the generalisation of empirical models in heterogeneous grasslands can hinder their applicability. Objectives1) Assess the suitability of retrieving forage quality parameters as concentration (%) versus content (kg ha−1). 2) Investigate the performance of multitemporal compared to phenophase-specific models. 3) Evaluate the generalisation ability of the models. MethodsSamples were collected from five farms to determine Dry Matter Yield (DMY) and both, concentration (%) and content (kg ha−1) of forage quality variables including crude protein (CP), neutral and acid detergent fibre (NDF, ADF), and enzyme digestibility of organic matter (EDOM). The relationship between forage quality variables and DMY were analysed by Pearson Correlations and Principal Component Analysis. Reflectance was recorded with a FieldSpec spectroradiometer. Partial Least Squares Regression (PLSR) was used to explore the relationship between forage variables and reflectance. ResultsThe forage quality variables were strongly correlated to DMY when expressed as content (kg ha−1) r>0.83 but not when expressed as concentration (%). For the best predicted variables, CP and NDF, the results of the PLSR models indicated better performance in concentration-based estimation. CP% was the best predicted variable (R2cv=0.8, NRMSEcv=9.8 %). Multitemporal models showed overall higher performance (CP%, R2cv=0.81) than phenophase-specific models (CP%, R2cv=0.60 green, R2cv=0.70 green-senescent and R2cv<0 senescent grasslands). The generalisation ability was low and varied among farms (R2test 0–0.60). ConclusionsThe use of concentration (%) is more accurate and representative of forage quality than content (kg ha−1), which seemed redundant with DMY and misleading from the true nutritive value for livestock.Multitemporal models performed better than phenophase-specific models due to their larger range of values. The ability to predict forage quality in senescent grasslands is low. The usefulness of the models is context-dependent, and their application requires knowledge of the limitations and status of the grasslands. Efforts must be directed toward improving the generalisation ability through the development of models calibrated with larger and more diverse datasets.

Fabrication, structure, optical and gamma-ray attenuation properties of borotellurite glasses doped with variable concentrations of cadmium oxide

Fabrication, structure, optical and gamma-ray attenuation properties of borotellurite glasses doped with variable concentrations of cadmium oxide

Activated Growth Factor (AGF): An Advanced Modality of Platelet-Rich Plasma as a New Biological Agent for the Treatment of Degenerative and Traumatic Conditions

Platelet-rich plasma (PRP) has emerged as a promising therapeutic modality for various medical applications, particularly in regenerative medicine and wound healing. This is largely attributed to its rich concentration of growth factors (GFs) that play pivotal roles in tissue repair and regeneration. However, the inherent limitations of PRP, such as the variable GF concentrations and short-lived release kinetics, have spurred the development of advanced modalities to enhance its therapeutic efficacy. Activated growth factor (AGF) represents one such advancement, aiming to optimize the release and bioavailability of GFs from platelets. This comprehensive review delves into the biological mechanisms underlying AGF, its preparation methodologies, preclinical and clinical evidence supporting its use, and its potential applications in treating degenerative and traumatic conditions. Furthermore, it explores the advantages of AGF over conventional PRP and discusses future directions for research and clinical translation.

Abstract PR019: Transfer learning for accurate tissue of origin classification from cfDNA methylation

Abstract Accurately predicting the tissue of origin (TOO) is required for blood-based multi-cancer screening to guide follow-up imaging and care when cancer is detected. However, precisely determining the TOO using cell-free DNA (cfDNA) methylation remains challenging due to low and variable concentrations of circulating tumor DNA and cfDNA and the complex, poorly characterized nature of tissue-specific methylation patterns. To address these challenges, we developed a transfer learning approach that leverages methylation profiles learned from tissue biopsy samples to predict the TOO of cfDNA cancer samples. Our model achieved 89% balanced accuracy (BA) in classifying the TOO across 10 cancer groups and outperformed models trained solely on plasma cfDNA data. Unmatched tissue biopsy (N=517) and blood (N=1,155, NCT05435066) samples were collected from treatment-naïve cancer patients across 21 tumor types consolidated into 17 cancer groups. All samples were analyzed using a custom targeted bisulfite sequencing hybrid capture assay. Five unique metrics were used to quantify informative methylation signal at each TOO region of interest. A feed-forward neural network was first trained on biopsy methylation features, where the cancer signal is strongest. Subsequently, the model was fine-tuned using plasma cfDNA methylation features, which have significantly lower signal-to-noise ratio, allowing the model to adapt its predictions to the noisier data. The Adam optimizer was employed for both training and fine-tuning, with early stopping implemented to prevent overfitting. Dropout layers were incorporated to enhance model generalization and performance was evaluated using 10-fold cross validation on plasma cfDNA samples across 10 cancer groups for which at least 25 plasma samples were available (N=1,041). The same architecture was trained exclusively on plasma cfDNA samples for comparison. Results are reported for samples with tumor content greater than 0.1% (N=415). Our TOO prediction achieved 73% BA in top-one predictions, where the true label matched the highest probability prediction, and 89% BA in top-two predictions, where the true label matched the highest or the second-highest probability prediction. Multi-class classification revealed our method significantly outperforms a model trained only on plasma cfDNA data. The plasma only model achieved 69% and 82% BA in top-one and top-two predictions, respectively. Accuracy per indication revealed that training on biopsy data significantly improves the detection of tumor types that shed DNA at low rates compared to training on plasma data alone (breast cancer +14%, prostate cancer +12%, and uterine cancer +20% points). In conclusion, our transfer learning approach, utilizing tissue biopsy methylation data, significantly improves cfDNA-based TOO detection accuracy. This approach highlights the capability of transfer learning to enable automated feature extraction from signal-rich data to enhance the analysis of more challenging, heterogeneous cfDNA samples, advancing non-invasive cancer diagnostics. Citation Format: Shiva Farashahi, Amirali Kia, Dorna Kashef, Esther Brown, Feras Hantash, Kieran I Chacko. Transfer learning for accurate tissue of origin classification from cfDNA methylation [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr PR019.

Control of hydrogen concentrations by microbial sulfate reduction in two contrasting anoxic coastal sediments.

Molecular hydrogen is produced by the fermentation of organic matter and consumed by organisms including hydrogenotrophic methanogens and sulfate reducers in anoxic marine sediment. The thermodynamic feasibility of these metabolisms depends strongly on organic matter reactivity and hydrogen concentrations; low organic matter reactivity and high hydrogen concentrations can inhibit fermentation so when organic matter is poor, fermenters might form syntrophies with methanogens and/or sulfate reducers who alleviate thermodynamic stress by keeping hydrogen concentrations low and tightly controlled. However, it is unclear how these metabolisms effect porewater hydrogen concentrations in natural marine sediments of different organic matter reactivities. We measured aqueous concentrations of hydrogen, sulfate, methane, dissolved inorganic carbon, and sulfide with high-depth-resolution and 16S rRNA gene assays in sediment cores with low carbon reactivity in White Oak River (WOR) estuary, North Carolina, and those with high carbon reactivity in Cape Lookout Bight (CLB), North Carolina. We calculated the Gibbs energies of sulfate reduction and hydrogenotrophic methanogenesis. Hydrogen concentrations were significantly higher in the sulfate reduction zone at CLB than WOR (mean: 0.716 vs. 0.437 nM H2) with highly contrasting hydrogen profiles. At WOR, hydrogen was extremely low and invariant (range: 0.41-0.52 nM H2) in the upper 15 cm. Deeper than 15 cm, hydrogen became more variable (range: 0.312-2.56 nM H2) and increased until methane production began at ~30 cm. At CLB, hydrogen was highly variable in the upper 15 cm (range: 0.08-2.18 nM H2). Ratios of inorganic carbon production to sulfate consumption show AOM drives sulfate reduction in WOR while degradation of organics drive sulfate reduction in CLB. We conclude more reactive organic matter increases hydrogen concentrations and their variability in anoxic marine sediments. In our AOM-dominated site, WOR, sulfate reducers have tight control on hydrogen via consortia with fermenters which leads to the lower observed variance due to interspecies hydrogen transfer. After sulfate depletion, hydrogen accumulates and becomes variable, supporting methanogenesis. This suggests that CLB's more reactive organic matter allows fermentation to occur without tight metabolic coupling of fermenters to sulfate reducers, resulting in high and variable porewater hydrogen concentrations that prevent AOM from occurring through reverse hydrogenotrophic methanogenesis.

Concentration-QT modeling demonstrates that the selective mineralocorticoid receptor modulator, balcinrenone (AZD9977), does not prolong QT interval.

Balcinrenone (AZD9977) is a selective mineralocorticoid receptor modulator in development in combination with dapagliflozin for treatment of heart failure with impaired kidney function and chronic kidney disease. A prespecified concentration-QT analysis was performed based on data from a phase I single ascending dose study prospectively designed as a thorough QT study substitute. Oral single doses of balcinrenone of 5-800 mg, plus fractionated doses of 800 and 1200 mg, were evaluated in 62 healthy male participants. Time-matched 12-lead digital electrocardiogram and plasma concentrations were measured pre-dose and up to 48 h postdose in the participants. Analysis was performed using a linear mixed-effect model, where baseline-adjusted Fridericia-corrected QT interval (ΔQTcF) was a dependent variable and time-matched balcinrenone concentration an independent variable. The model fit was deemed adequate by evaluation of goodness-of-fit plots, and the slope of the concentration-ΔQTcF relationship was nonsignificant (-0.003 ms/μmol/L; 95% confidence interval [CI]: -0.181, 0.176). The high clinical exposure scenario was defined as the maximum concentration (2.156 μmol/L) following the highest expected therapeutic dose (40 mg once daily) under fed conditions and in presence of a strong cytochrome P4503A4 inhibitor. Estimated baseline-adjusted and placebo-corrected QTcF interval (ΔΔQTcF) at this concentration was 0.35 ms (90% CI: -1.29, 2.00). Furthermore, the upper 90% ΔΔQTcF CI was estimated to be below the threshold of regulatory concern of 10 ms at all observed concentrations (up to 16.7 μmol/L). Hence, it can be concluded that balcinrenone does not induce QTcF prolongation at the high clinical exposure scenario.

The Petrogenesis of the Lower Critical Zone and Lower Group Chromitites, Eastern Bushveld Complex: Incremental Development of Igneous Layering and Injection of Chromite Slurries

Abstract The petrogenesis of the mafic-ultramafic layered rocks of the Bushveld Complex, South Africa, remains uncertain despite more than a century of intensive research. There is little evidence for the existence of a shallow crustal magma chamber, a principle entrenched in the scientific literature for many years, and we prefer an alternative hypothesis in which igneous layering developed from successive intrusive events. Geochemical discontinuities are explained by radical switches in the composition of intruding parental magmas. Here we investigate the origin of the Lower Critical zone, a sequence of five pyroxenitic and two peridotitic units containing the Lower Group (LG) of chromitites, of which LG6 is a major resource for chromium ore in the eastern limb. The pyroxenitic and peridotitic units are not part of magmatic cycles. Two discrete lineages of parental magma are recognized: a pyroxenitic magma sourced from deep crustal staging chambers, and a mantle-derived peridotitic magma. The pyroxenitic units reveal an absence of modal layering (with the exception of the 0.1- to 1-m-thick layers of chromitite) and limited height-related fractionation trends (enstatite: En86–811). Magma was fed as thin laminae. Intrusion rates were insufficient to create a magma reservoir because the supply of magma matched the rate of batch crystallization. There is little evidence of a fractionated residue having been removed. The recognition of minor geochemical trends of Mg- and Fe-enrichment in the pyroxenitic units reflects minor oscillations in the composition of the parental magma. The composition of the orthopyroxene and of the Cr spinel was primarily established at depth. The anomalous concentrations of chromite are explained by the introduction of pyroxenitic magmas containing crystals of Cr spinel, sufficiently abundant in some cases as to have created crystal slurries. The Cr spinel was entrained at depth, in the staging chambers. Each layer of chromitite is related to injection of a crystal slurry. The tiny size of the rounded xenocrysts of Cr spinel facilitated the mobile and dynamic nature of slurries. Coarse-grained mosaics of Cr spinel developed in the compacted layers of chromitite from prolonged periods of annealing. The irregular spacing of the chromitites, and occurrence of variable concentrations of disseminated Cr spinel in the pyroxenites, is explained by fluctuations in the proportion of entrained xenocrysts, rather than changes in the composition of the melt fraction of the magma. The peridotitic units are interpreted as sills, the chromitite layers having been inherited from the earlier formed pyroxenitic stratigraphy. The most primitive layers of dunite and harzburgite (olivine: Fo90-85 in which Fo = forsterite) accumulated in the center of sills, where a high magma flux facilitated growth of pegmatitic oikocrysts.

Determinants for Sugar-Induced modulation of thermodynamic stability of lysozyme

The current study focuses on the experimental evidence to describe the molecular mechanism by which the sugars modulate the thermodynamic stability of hen egg-white lysozyme (Lyz) at pH 2.3. Analysis of thermal and chemical denaturation curves of Lyz under variable concentrations of sugar (trehalose, sucrose, maltose, glucose, ribose, glycerol) at pH 2.3 depicted important results: (i) sugar increases the thermodynamic stability of Lyz, and it typically tracks the order as: trehalose > sucrose > maltose > glucose > ribose > glycerol, and (ii) sugar increases the thermodynamic stability of Lyz via preferential exclusion of sugar at the protein surface, but the repulsive enthalpic interactions of sugar with protein also add to the sugar-mediated increase in thermodynamic stability of the protein. Analysis of the sugar effect on denaturant concentration dependent denaturation free energy of Lyz at pH 2.3 revealed that the sugar counteracts the denaturant (urea, guanidinium chloride (GdnCl)) efficacy to decrease the thermodynamic stability of Lyz. Furthermore, the counteraction efficiency of sugar on denaturant impact to decrease thermodynamic stability of Lyz typically tracks the order as: trehalose > sucrose > maltose > glucose > ribose > glycerol.

Medicinal Plants Approach for Diabetes Mellitus-A Computational Model

The multidimensional metabolic syndrome that includes diabetes mellitus poses a serious threat to world health. There is an increasing interest in researching herbal remedies for their possible therapeutic advantages, even as traditional allopathic treatments continue to be widely used. This work throws light on the multiple ways of metabolism and biochemical interactions of medicinal plants in the control of glucose level, highlighting their crucial role in the process. The work clarifies several herbal extracts' efficacy and safety profiles, such as Aloe vera, Garlic, Gurmar, Bitter Melon, Neem, Tulsi, and through a thorough literature review and empirical evidence. These plants, which are abundant in bioactive substances like tannins, flavonoids, and alkaloids, show promise in treating insulin resistance, improving pancreatic function, and controlling blood sugar level. A further assessment of the rising risk associated with diabetes mellitus is discussed, and a differential equation model for diabetes mellitus is developed to minimize the complications. When using medicinal plants to treat diabetes, several factors are considered, including blood sugar level, sugar intake activity, and plasma insulin concentrations. The stability criterion for the mathematical model is examined through the system of differential equations. A representation highlighting the medicinal plants that can aid individuals with diabetes mellitus is provided. The blood sugar level, insulin generalization variable and plasma insulin concentration have all been measured at different points in time. Aloe vera, Gurmar, Garlic, Tulsi, Bitter Melon and Neem are among the medicinal plants selected for their demonstrated anti-hyperglycemic properties due to their easy availability in India. Mathematical solutions were calculated for every plant and proved to be steady.

Physio-chemical and microbial assessment of the source of drinking water and the prevailing waterborne diseases in Gwagwalada Municipal Area Council of Abuja, Nigeria

Water contamination poses a serious threat to the wellbeing of people globally. In Nigeria, there have been increasing cases of waterborne diseases owing to water contamination, thus becoming public health concerns. This study investigated the physio-chemical properties, microbial loads of borehole water samples from Gwagwalada area council of Abuja and its prevailing waterborne diseases. Borehole water samples were collected from five wards of the council area (Gwagwalada central (YZTM), University of Abuja Staff quarters (YZTMB), Dobi (SBWTM), Tunga Maje (TMCBW), and Ikwa (YZBTM) in triplicate and analyzed for physiochemical properties (temperature, conductivity, pH, turbidity, salinity, total dissolved solids (TDS), and heavy metals) and microbial contamination using standard methods. Surveillance to determine the prevalence of waterborne diseases was also carried out in the health facilities of the area council. All samples showed variable concentrations in most of the physiochemical parameters and were within the recommended thresholds except for conductivity (596.01 ± 0.00 μS/cm) and chlorine (254.18 ± 0.00 mg/l) in TMCBW sample and total dissolved solids in TMCBW (948.01 ± 14.14 mg/l) and YZTM (GC) (1871.00 ± 55.15 mg/l) water samples. E. coli, Enterobacter spp., Shigella spp., Lactobacillus spp., Pseudomonas ssp., and Proteus ssp. were bacteria isolates of the samples. Principal component analysis of interrelationship showed a strong positive relationship between some physio-chemical parameters and sampling locations. Also, there was heavy burden of gastrointestinal (waterborne) diseases. The study concludes that the borehole samples from the area were contaminated and maybe unfit for consumption. Thus, call for interventions that provide safer portable water or treat existing water sources towards achieving SDG No. 6 and to prevent outbreaks of waterborne diseases that could emanate from the consumption of unsafe water.

Development of over 30-years of high spatiotemporal resolution air pollution models and surfaces for California

California’s diverse geography and meteorological conditions necessitate models capturing fine-grained patterns of air pollution distribution. This study presents the development of high-resolution (100 m) daily land use regression (LUR) models spanning 1989–2021 for nitrogen dioxide (NO2), fine particulate matter (PM2.5), and ozone (O3) across California. These machine learning LUR algorithms integrated comprehensive data sources, including traffic, land use, land cover, meteorological conditions, vegetation dynamics, and satellite data. The modeling process incorporated historical air quality observations utilizing continuous regulatory, fixed site saturation, and Google Streetcar mobile monitoring data. The model performance (adjusted R2) for NO2, PM2.5, and O3 was 84 %, 65 %, and 92 %, respectively.Over the years, NO2 concentrations showed a consistent decline, attributed to regulatory efforts and reduced human activities on weekends. Traffic density and weather conditions significantly influenced NO2 levels. PM2.5 concentrations also decreased over time, influenced by aerosol optical depth (AOD), traffic density, weather, and land use patterns, such as developed open spaces and vegetation. Industrial activities and residential areas contributed to higher PM2.5 concentrations. O3 concentrations exhibited no significant annual trend, with higher levels observed on weekends and lower levels associated with traffic density due to the scavenger effect. Weather conditions and land use, such as commercial areas and water bodies, influenced O3 concentrations.To extend the prediction of daily NO2, PM2.5, and O3 to 1989, models were developed for predictors such as daily road traffic, normalized difference vegetation index (NDVI), Ozone Monitoring Instrument (OMI)–NO2, monthly AOD, and OMI-O3. These models enabled effective estimation for any period with known daily weather conditions.Longitudinal analysis revealed a consistent NO2 decline, regulatory-driven PM2.5 decreases countered by wildfire impacts, and spatially variable O3 concentrations with no long-term trend. This study enhances understanding of air pollution trends, aiding in identifying lifetime exposure for statewide populations and supporting informed policy decisions and environmental justice advocacy.

Snow as an Indicator of Atmospheric Transport of Anthropogenic Particles (Microplastics and Microfibers) from Urban to Arctic Regions

We report anthropogenic particles (AP) &gt; 100μm, including microplastics and microfibers, from 70 surface snow samples collected from the urban Greater Toronto Area (GTA), remote and sparsely inhabited regions in the Yukon and Northwest Territories, and the unpopulated high Arctic. Concentrations and proportions of particles of anthropogenic origin were conservatively estimated after blank and ‘anthropogenic origin’ corrections were performed based on visual analysis and micro-Fourier transform infrared spectroscopy (µFTIR). AP were dominated by microfibers (95-100%), with variable concentrations across and within regions. Microfibers were distinguished as synthetic, regenerated semi-synthetic, anthropogenically modified cellulosic, and natural cellulosic or proteinaceous. Among microfibers with confirmed anthropogenic origin, most were polyester/PET (8-22%) and semi-synthetic rayon (1-18%), with anthropogenic cellulose comprising a small proportion (3-7%) across all regional areas. Greater diversity of coloured non-fibrous particles (fragments, films and foams) in settled regions (i.e., GTA and Carcross, Yukon) suggests direct input from local sources. Back trajectory analyses performed for days leading up to sample collection showed high frequency transport (&gt;10%) from population centres exceeding 200km distance. Our findings of APs in snow from uninhabited areas support the hypothesis that APs, especially microfibers, undergo long-range atmospheric transport whereby snow can scavenge and deposit APs in remote northern regions.

Analysis of Volatile Organic Compound Emissions in 3D Printing: Implications for Indoor Air Quality

This study provides a comprehensive analysis of volatile organic compound (VOC) emissions in the context of 3D printing, a rapidly advancing technology that is transforming manufacturing processes. As the adoption of 3D printing grows, concerns regarding its potential impact on indoor air quality have emerged. This research addresses these concerns by investigating the risks associated with VOC emissions and proposing effective mitigation strategies. Using a robust methodology, filament and resin-based 3D printers were employed alongside VOC sampling equipment (Tenax tubes and personal pumps) to assess emissions. A detailed analysis of 49 VOCs revealed variable concentrations across different printing materials, with ethyl acetate being the dominant compound in resin printing and decanal in filament printing. While individual VOC levels were below 1% of occupational exposure limits, total VOC concentrations frequently exceeded the recommended indoor threshold of 200 µg/m3, particularly in resin-based processes. This raises concerns about the combined effects of multiple VOCs, some of which are known carcinogens. These findings underscore the need for further investigation into the cumulative health impacts of prolonged exposure to multiple VOCs. The study also emphasises the importance of accounting for both facility-specific conditions and material emissions to fully understand the environmental and health consequences of 3D printing. Preventative measures, such as enclosing 3D printers and equipping them with extraction systems, are recommended to safeguard user health.

Investigation of the agricultural reuse potential of urban wastewater and other resources derived by using membrane bioreactor technology within the circular economy framework

The European Union, as delineated in Regulation (EU) 2020/741, sets forth minimum criteria for the reuse of wastewater. Directive 86/278/CEE sets the regulations for the reuse of sewage sludge in agriculture. This study aimed to investigate the treated water derived from a pilot plant situated in Granada, Spain, that utilizes membrane bioreactor technology to process real urban wastewater with the quality standards necessary for agricultural reuse. Additionally, the study evaluated the utilization potential of other resources generated during wastewater treatment, including biogas and biostabilized sludge. The pilot plant incorporated a membrane bioreactor featuring four ultrafiltration membranes operating continuously alongside a sludge treatment line operating in batch mode. The pilot plant operated during four cycles, each with distinct hydraulic retention times (6 h and 12 h) and variable mixed liquor-suspended solids concentrations (ranging from 2688 mg L−1 to 7542 mg L−1). During these cycles, the plant was doped with increasing concentrations of emerging contamination compounds (diclofenac, ibuprofen, and erythromycin) to test their effect on the resources derived from the treatment. Subsequently, a tertiary treatment involving an advanced oxidation process was applied to the different water lines, which left the wastewater treatment plant for a period of 30 min and utilized varying concentrations of oxidant. The results indicate that the effluent obtained meets the required quality standards for agricultural use. Therefore, there is potential to use this waste as a resource, which is in line with the principles of the circular economy. Furthermore, the other resources generated during the treatment process, such as the biogas produced during the digestion process and the biostabilized sludge, have the potential to be used as resources according to the circular economy indicators.

VALIDATION OF 2HG-TARGETTED MR SPECTROSCOPY FOR IDENTIFYING IDH-MUTANT GLIOMAS

Abstract AIMS Diffuse gliomas, the most common adult primary brain tumour, are classified by their histological and molecular characteristics and genetic profile. Isocitrate dehydrogenase (IDH) mutant gliomas correlate with longer mean survival and progression-free survival time. In tumour cells, IDH mutations lead to metabolic changes and the production of oncometabolite 2-hydroxyglutarate (2HG). MR spectroscopy (MRS) can assess metabolic changes in disease states in-vivo and non-invasively. In this study, we demonstrate a validation pathway for two advanced MRS methods to be used as IDH-mutation biomarkers in clinic. METHOD Simulated, phantom, and healthy volunteer experiments were performed to optimise and validate three MRS sequences tuned for measuring 2HG. A PRESS sequence was used with TR/TE of 2500/97 ms aiming at the 2HG peaks around 2.25 ppm. An edited PRESS sequence, named MEGA-PRESS, tailored to 2HG 4.02 ppm peak was used with TR/TE of 3000/68 ms, 128 averages, and with editing pulses at 1.9 and 7.5 ppm. A long TE semi-LASER MRS sequence, with improved voxel localisation, was also used (TR/TE: 2500/110 ms). RESULTS Simulations were performed to find optimised sequence parameters and to develop basis sets for analysing the phantom and healthy volunteer acquisitions. Tumour-mimicking phantoms with variable concentrations of 2HG and cystathionine were created and validated with 800 MHz NMR spectroscopy. Phantoms were then used to assess the sensitivity and specificity of the MRS for 2HG and cystathionine. MEGA-PRESS proved Synthetic in-vivo 2HG spectra, combined from healthy volunteers and simulated or phantom-2HG spectra, were used to assess the spectral quality needed to reliably measure 2HG. CONCLUSION MEGA-PRESS proved to be the most robust MRS method and demonstrated accurate and precise measurement of phantom and synthetic 2HG with acceptable SNR. Clinical validation of the technique will need to be performed on LGG patient population, and the overall accuracy will be compared with patient IDH mutation status.