Size Fractions Research Articles

Characterisation of the Mineralogy, Durability and Physical Properties of Two Earth Mortars: An Experimental Study

Abstract Mortars composed of a blend of earth and cement are widely employed in masonry, particularly in the construction of earth blocks. This study is primarily focused on investigating the influence of mineralogical and chemical constituents on the mechanical characteristics of two types of mortars. Furthermore, we have assessed the water absorption coefficient of these mortars, which vary in cement content, with the aim of enhancing their longevity. The findings reveal a significant enhancement in compressive strength, attributed to the interaction between calcium hydroxide in cement and clay minerals containing silico-aluminous compounds. Importantly, the incorporation of cement not only affects the macroscopic properties concerning particle size fractions but also heavily depends on the mineralogical composition, particularly the clay content. Moreover, the addition of cement results in a reduction in water absorption, whereas an increase in magnesium oxide content within the clay leads to higher water absorption rates.

Hot Deformation Behavior of DT4 Pure Iron in the Austenite Single‐Phase Region: Experiment and Finite Element Simulation

The control of grain size and uniformity during the rolling process of DT4 electromagnetic pure iron is critical for its coercive force. Dynamic recrystallization during hot processing is closely related to grain size and uniformity control; therefore, the study of hot deformation and dynamic recrystallization process of DT4 in the γ‐phase region is essential. A 60% hot deformation of DT4 is conducted at temperatures of 950, 1000, and 1050 °C, respectively, with strain rates ranging from 0.01 to 10 s−1. The results indicate that in the γ‐phase region, after hot compression, the grain size and recrystallization fraction of DT4 decrease as the strain rate increases and the temperature decreases. A constitutive model and dynamic recrystallization model for DT4 are established, which can be used to predict the flow stress, recrystallization fraction, grain size, and critical strain of DT4, based on deformation temperature, strain rate, and strain. The dynamic recrystallization model is integrated into the Deform‐3D to simulate the critical strain during the hot deformation process of DT4. According to the correlation coefficient (R) and root mean square error results, the simulated data are consistent with the experimental data.

Radiation-induced lymphocyte apoptosis and chromosomic aberrations for prediction of toxicities in patients undergoing radical radiotherapy for breast or prostate cancers.

Radiation-induced lymphocyte apoptosis (RILA) and chromosomal damage assays (CDA) assays are proposed predictors of radiotherapy (RT) adverse events (RTAE). This study evaluated RILA and CDA in patients undergoing different RT dose regimens for early breast (FAST trial) or prostate (CHHiP trial) cancer. Consecutive patients were recruited from each trial. Fresh heparinised blood samples were analyzed for RILA and CDA. The primary endpoint was time to first change in photographic breast appearance (FAST) or time to first grade ≥2 RTOG bladder or bowel toxicity (CHHiP). The secondary endpoint in FAST was breast fibrosis. The dataset included 103 FAST and 297 CHHiP trial patients. No significant association of RILA with the primary endpoint was observed in the FAST trial. However, the risk of grade ≥2 breast fibrosis was lower in patients with RILA ≥24% compared to those with RILA ≤16% (p = 0.012). In the CHHiP trial, no significant associations were found between CDA after prostate radiotherapy outcomes. However, higher levels of micronuclei per cell were associated with a lower risk of grade ≥2 RTOG pelvic toxicities. The relative risk of developing grade ≥2 RTAE decreased for patients with RILA ≥ 24% but was not statistically significant. No association was found between RILA and photographic breast appearance. High RILA values were statistically associated with a lower risk of grade ≥2 breast fibrosis. In the CHHiP trial, most assays showed no association with pelvic toxicities. RILA is confirmed as a potential predictor of breast fibrosis regarding fraction sizes.

EntoSieve: Automated Size‐Sorting of Insect Bulk Samples to Aid Accurate Megabarcoding and Metabarcoding

ABSTRACTWidespread insect decline necessitates the development and use of standardized protocols for regular monitoring. These methods have to be rapid, efficient and cost‐effective to allow for large‐scale implementation. Many insect sampling and molecular methods have been developed. These include Malaise trapping, high‐throughput DNA barcoding (‘megabarcoding’) and metabarcoding. The latter allows for assessing the species diversity in whole samples using few steps, but sample heterogeneity in terms of body size remains a challenge since large insects contribute disproportionately more mtDNA than small ones. This can potentially overwhelm the template DNA from small species that then go undetected. Size‐sorting can mitigate this problem, but no satisfying automated, rapid and non‐destructive solutions are available. We introduce the EntoSieve, a low‐cost and DIY motorized instrument that disentangles and sorts abundant insect bulk samples into several body size fractions while minimizing damage to specimens, thus reducing the risk of DNA contamination across size fractions (e.g. legs of large specimens in small body size fraction). EntoSieve utilizes readily available components, 3D‐printed parts and customizable meshes, thus enabling parallelization at low cost. We here show the efficiency of the EntoSieve for three samples with more than 10,000 specimens using three sieving protocols and assess the impact on specimen integrity. Efficiency ranged from 92% to 99%, achieved within 18–60 min, and specimen damage was not significant for subsamples. By facilitating rapid pre‐processing, the device contributes to producing morphologically valuable vouchers for megabarcoding and is likely to improve compositional diversity accuracy across size classes when using metabarcoding.

Spatiotemporal distributions of microplastics in Buffalo River, South Africa: abundance, characteristics and adsorption of heavy metals

Abstract The omnipresence of microplastic (MP) particles in environmental matrices of rivers is on the rise and has become a focal point of aquatic research. The study investigated the spatiotemporal distribution of MPs and adsorption of heavy metals (HMs) in the Buffalo River of South Africa. The findings of the study showed that a sum of 874 MPs was enumerated from the samples collected in the river system. The MP particles ranged between 0.35–0.75 particles·L−1 during the dry winter and 0.3–0.9 particles·L−1 in wet summer seasons in surface water. The range in sediments was 3–32 particles·kg−1 and 2–23 particles·kg−1 during the dry winter and wet summer seasons, respectively. The results showed that temporal rainfall patterns had a significant (p = 0.009 < 0.05) influence on MP abundances in sediments. Fibers and fragments were the main shapes, while polyethylene and polypropylene were ubiquitous. HMs such as nickel, copper, and iron with concentrations of 36.49 ± 3.96, 14.33 ± 0.87, and 356.47 ± 73.66 µg·g−1 were adsorbed on surfaces of the microplastics, with iron being strongly correlated with the 3 mm and 1 mm size fractions and copper with the 2 mm fraction. The study has provided insights into the influence of climatic conditions on MP abundances and how plastics adsorb chemical pollutants such as HMs in environmental conditions. Moreover, the study has yielded baseline data on MP pollution in Buffalo River, which is helpful to the relevant authorities of the country’s ongoing River Health Program.

Apparent soil electrical conductivity and gamma-ray spectrometry to map particle size fraction in micro-irrigated citrus orchards in California

In specialty crops, water and nutrient management may be optimized using accurate, high-resolution soil maps, especially in resource-constrained farmland, such as California. We evaluated the use of soil apparent electrical conductivity (ECa) and gamma-ray spectrometry (GRS) to map particle size fraction across three micro-irrigated non-saline citrus orchards in California. Our research showed that ECa was a reliable predictor of soil texture, particularly sand and silt contents, with Pearson correlation coefficients (r) as high as -0.92 and 0.94, respectively, at the field level. Locally-adjusted analysis of covariance (ANOCOVA) regressions using ECa data returned accurate sand, silt, and clay content estimations with mean absolute errors (MAE) below 0.06, even when calibrated with a limited dataset (n=5 per field). On the other hand, we observed mixed results with GRS. We observed negative correlations between GRS total counts and sand content over the entire dataset (r = -0.55). However, one site (Strathmore) showed a field-scale positive correlation (r = 0.88). Clay content significantly correlated with gamma-ray total counts (TC) over the entire dataset (r = 0.37) but not at the field scale. Additional soil data analyses using GRS radionuclide ratios and soil laboratory analyses using diffuse reflectance infrared Fourier transform spectroscopy and acid ammonium oxalate extractable elements indicated unique geochemical and mineralogical characteristics in Strathmore, suggesting that factors such as soil mineralogy influenced the GRS measurements. This inconsistency prevented the development of a multi-field GRS-based soil texture ANOCOVA model. These findings confirm that ECa is highly effective for soil texture mapping in non-saline soils using linear modeling, while GRS may require field-specific calibration due to variations in local mineralogy. Integrating multi-sensor data is a viable means for reducing ground-truthing requirements and related costs, and improving the quality and accuracy of soil maps in agriculture.

Разработка рекомендаций по регулированию кусковатости строительных горных пород при взрывном разрушении

Deposits of construction materials are most often found in the Ural region. Therefore, the issue of developing a methodology and technological parameters of mining to obtain the required lump size of the construction rocks is the most important task of modern mining enterprises in the Southern Urals. The paper studies the distribution of the particle size distribution of the construction rocks before and after blasting, after the excavation and haulage processes using the logarithmic normal law. Analysis of the obtained data helps to establish patterns in the change of the main distribution law indicators from the physical and technological properties of rocks and their structural and textural features. The obtained dependencies make it possible to promptly adjust the drilling and blasting parameters in order to obtain the required fragmentation of rocks of varying strength and fracturing. The required degree of blast fragmentation of the construction rocks is determined by the minimum total energy consumption for the entire cycle of preparation, extraction and processing (the primary crushing stage), taking into account the maximum yield of commercial size fractions. Research has shown that for different types of construction rocks, the yield of the commercial fractions at a constant degree of crushing will depend on the hardness and fracturing of the rock masses and can vary by up to 20–30%.

Spatio-temporal dynamics of bacterial community composition in a Western European watershed, the Meuse River watershed.

This study aimed to identify factors influencing bacterial diversity in the Meuse River watershed by analyzing 42 locations sampled in spring and summer 2019, combined with biweekly sampling of one mid-stream location for a year. Bacterial community composition (BCC) was assessed in the small (SF; <5µm) and large fractions (LF; ≥5µm,), alongside physico-chemical parameters. LF consistently exhibited greater alpha diversity than SF. During the spatial campaigns, alpha diversity increased downstream in spring with high discharge, and BCC differed significantly between headwaters and the main river. Along this axis, several genera, Flavobacterium, Limnohabitans, and Aquirufa stood out as indicators of good water quality. Rhodoferax, another taxon indicative of good water quality, prevailed in the headwaters and during winter. In contrast, two cyanobacteria genera indicators of poor river quality, Microcystis PCC 7914 and Cyanobium PCC 6307, peaked in summer. BCC in spring and summer temporal samples aligned with spatial ones, while winter and autumn samples had distinct BCC. Finally, season, temperature, and distance from river mouth were the main driving parameters of beta diversity, outweighing the effect of fraction size on the BCC. These findings reinforce the notion that local conditions exert significant influence on bacterial communities in rivers.

Impact of Aggregate-Associated Carbon on Soil Mechanical Properties: Stability and Compaction Indices in Pomegranate Orchards of Different Ages

The relationships between soil aggregates, aggregate-associated carbon (C), and soil compaction indices in pomegranate orchards of varying ages (0–30 years) in Assiut, Egypt, were investigated. Soil bulk density (Bd) and organic carbon (OC) content increased with orchard age in both the surface (0.00–0.20 m) and subsurface (0.20–0.40 m) layers 0.20–0.40 m). The percentage of macroaggregates (R0.25) and their OC content in the aggregate fraction &gt; 0.250 mm increased as the pomegranate orchard ages increased in the surface layer (0.00–0.20 m). Older pomegranate orchards show improved soil structure, indicated by higher mean weight diameter (MWD) and geometric mean diameter (GMD), alongside reduced fractal dimension (D) and erodibility (K). As orchard ages increased, maximum bulk density (BMax) decreased due to an increase in OC, while the degree of compactness (DC) increased, reaching a maximum at both soil layers for the 30 Y orchards. Soil organic carbon and aggregate-associated C significantly influenced BMax, which led to reducing the soil compaction risk. Multivariate analyses identified the &gt;2 mm aggregate fraction as the most critical factor influencing the DC, soil compaction, and K indices in pomegranate orchards. The OC content in the &gt;2 mm aggregates negatively correlated with BMax, DC, and K but was positively associated with MWD and GMD. Moreover, DC and Bd decreased with higher proportions of &gt;2 mm aggregates, whereas DC increased with a higher fraction of 2–0.250 mm aggregation. These findings highlight the role of aggregate size fractions and their associated C in enhancing soil structure stability, mitigating compaction, and reducing erosion risks in pomegranate orchards.

Minimising feeding behaviour interference: A hay-shaker device to assess dust exposure in horses.

Organic dust from hay is a primary trigger of equine asthma. (1) To introduce a novel hay-shaker (HS) device for standardised hay dust generation, enabling simultaneous measurements of various particulate matter (PM) size fractions. (2) To compare these measurements with those in the horse's breathing zone (BZ) to assess the influence of environmental and individual factors. Comparative experimental study. A HS generating dust was developed. Total dust (PMT) and size fractions (PM1, PM2.5, PM4 and PM10, representing particle size in μm) were measured from 50 hay samples provided by clients using an aerosol monitor (DustTrak DRX 8534) in the HS (HS-PMx) and the BZ (BZ-PMx) of 50 horses (26 healthy, 24 asthmatic) during hay feeding. Linear regression analysis evaluated the relationship between HS-PMx and ln BZ-PMx for each fraction, accounting for environmental (humidity, temperature) and individual factors (horse characteristics and feeding behaviour, assessed with the Hay Contact Score). The HS generated measurable dust across all PM sizes. Regression models explained 69% to 73% of ln BZ-PMx variance, showing a weak positive association between HS-PMx and ln BZ-PMx across all size fractions. Hay Contact Score had the strongest positive association with ln BZ-PMx. Cohort, ambient temperature and humidity were negatively associated with ln BZ-PMx for certain particle sizes. The final model, incorporating HS-PM4, Hay Contact Score, cohort, temperature, and humidity as predictors, demonstrated robust predictive accuracy for BZ-PM4 (adjusted R2 = 0.73). Clinical impact of hay dust and poor-quality hay was not assessed. The HS reliably generates hay dust for measuring standard PM fractions, particularly respirable PM4, critical to equine respiratory health. BZ dust concentrations are significantly influenced by feeding behaviour. The HS offers a standardised method for assessing hay quality, enabling informed decisions on hay selection to support respiratory health in stabled horses.

Characterizing the Temporal Variation of Airborne Particulate Matter in an Urban Area Using Variograms

This study aims to determine the optimal frequency for monitoring airborne pollutants in densely populated urban areas to effectively capture their temporal variations. While environmental organizations worldwide typically update air quality data hourly, there is no global consensus on the ideal monitoring frequency to adequately resolve pollutant (particulate matter) time series. By applying temporal variogram analysis to particulate matter (PM) data over time, we identified specific measurement intervals that accurately reflect fluctuations in pollution levels. Using January 2023 air quality data from the Joppa neighborhood of Dallas, Texas, USA, temporal variogram analysis was conducted on three distinct days with varying PM2.5 (particulate matter of size ≤ 2.5 μm in diameter) pollution levels. For the most polluted day, the optimal sampling interval for PM2.5 was determined to be 12.25 s. This analysis shows that highly polluted days are associated with shorter sampling intervals, highlighting the need for highly granular observations to accurately capture variations in PM levels. Using the variogram analysis results from the most polluted day, we trained machine learning models that can predict the sampling time using meteorological parameters. Feature importance analysis revealed that humidity, temperature, and wind speed could significantly impact the measurement time for PM2.5. The study also extends to the other size fractions measured by the air quality monitor. Our findings highlight how local conditions influence the frequency required to reliably track changes in air quality.

Spatial distribution, geochemistry and provenance of heavy minerals in Miri beach sediments, NW Borneo, Malaysia

In this study, the spatial distribution of heavy minerals (HMs) in Miri beach sediments was assessed to quantify the abundance and determine the provenance. Surface sediment samples were collected in Miri beaches during low tide with respect to longitudinal, lateral and depth samplings. The collected samples were processed for grain size analysis by using sieving method. Then the HMs separation at different grain size fractions was carried out by using gravity and magnetic separation methods. Polarising Microscope was used to identify various HMs present in the sediment samples. In addition, selected sediment samples were analysed by using X-ray Fluorescence (XRF) to determine the elemental composition and major oxides for the geochemistry and provenance. From the results, HMs found in Miri beach sediments were zircon, magnetite, tourmaline, and rutile. Magnetite was abundant in 600–250 μm size fraction, zircon in 125–63 μm size fraction, tourmaline in 125–63 μm size fraction, and rutile in 250–125 μm size fraction. Longitudinally, magnetite was found to have higher abundance towards the southern part of the coastline. However, the abundance of rutile and tourmaline was found in the northern part of the coastline. Zircon was more abundant in the middle and southern parts of the coastline. Laterally, the concentration of HMs was higher towards the landward side. In terms of depth, the distribution of HMs varies and abundant in the surface sample. Geochemically, the beach sediments were found to be highly weathered in the north beaches (CIA = 78.9), moderately weathered in the middle (CIA = 63.8 to 66.5) and poorly weathered in the southern beaches (CIA = 40.4–49.6). The high content of quartz in the sediments are derived from the quartzose sedimentary origin, which undergone recycling process. Environmental indices such as contamination factor (CF), geoaccumulation index (Igeo), and enrichment factor (EF) indicate that the Miri beach sediments were highly concentrated with Cr, Ni, and Ta.

Chemical and isotopic genesis of fine and ultra-fine aerosols in the coastal urban atmosphere.

Chemical and isotopic genesis of fine and ultra-fine aerosols in the coastal urban atmosphere.

Influence of Agricultural Land Use Management on Soil Particle Size Distribution and Nutrient Adsorption in Western Kenya

Abstract In Kenya, less than 10% of the land is arable, out of which 30% suffers severe soil degradation. This study investigates impact of various agricultural land use management practices (on the concentration and distribution of essential nutrients in different soil particle size fractions (SPSF) within Oroba Valley, Nandi County. Two agricultural plots were selected: Plot 1 (non-terraced) and Plot 2 (terraced cultivation), with topsoil (0–20 cm) sampled using a stratified method. Soil particles were separated by sieving (2000–500 µm, 500–100 µm, 100–50 µm, 50–25 µm) and sedimentation (25–10 µm and &lt; 10 µm). Organic matter (OM), soil pH, and nutrient concentrations were quantified using loss on ignition (LOI), a pH meter in CaCl2, and ICP-QQQ analysis, respectively. Median soil pH was 5.6 for Plot 1 and 5.9 for Plot 2, with OM concentrated at 40% in smaller particles (&lt; 25 µm) and 24% in larger particles (100–2000 µm). Nutrients such as I, Se, Zn, Mg, P, Al, Mn, Fe, Co, Mo, and Cu were concentrated in SPSF of &lt; 10 µm, while Na, K, and Ca were concentrated in medium particle sizes (25 µm–100 µm). Terraced plot (Plot 2) experience greater nutrient loss down the slope compared to Plot 1, that showed nutrient accumulation at lower elevations. Principal component analysis (PCA) revealed that soil pH did not significantly influence element adsorption within SPSFs. Differences in land use management between plots directly impacted nutrient distribution. Optimising agricultural land management can improve soil health, contributing to attaining the United Nations sustainable development goals 1, 2, 6, and 8.

Feasibility assessment of low-grade iron ore from El Ouenza mine by high-intensity magnetic separation

Purpose. The objective of this work in the first stage is to characterize the poor iron ore from the El Ouenza mine. Then, in the second stage, it is a question of valorizing it by high intensity magnetic separation. Methodology. The characterization of representative samples taken from the study area was carried out using several techniques, including X-ray fluorescence spectrometry (XRF), X-ray diffraction (XRD), scanning electron microscopy coupled with energy dispersive spectroscopy (SEM-EDS), thermogravimetric analysis and differential scanning calorimetry (TGA/DSC), and Fourier transform infrared spectroscopy (FTIR). Processes involving a combination of calcination and high-intensity dry magnetic separation were used to upgrade the poor iron ore to meet the requirements of the steel industry. Findings. The results obtained show that the El Ouenza iron ore consists mainly of ferrous minerals, notably hematite and goethite, as well as a siliceous and calcareous gangue. The treatment results enabled us to achieve a grade of 51.94 % for the sample calcined at 900 °C using a magnetic field of 2.3 T on the size fraction (-0.5 0.125) mm. Originality. The originality of the work lies in the possibility of using combined methods, calcination and magnetic separation, to valorize poor iron ore from the Ouenza mine. Practical value. This study shows that the results obtained by calcination and magnetic separation are very significant. These techniques enable us to obtain a concentrate with an iron content of 51.94 %, bringing value to the steel industry, eliminating the reserves of poor iron ore stored near the mine site and preserving the environment.

Rice Husk Derived Biomass Briquettes for Boilers: Ingredient-Based Product Quality Study

This research investigates the feasibility of repurposing rice husk waste into sustainable biomass briquettes, addressing environmental and economic challenges associated with conventional biomass sources in Sri Lanka. The study involves a comprehensive analysis of rice husk utilization, focusing on three size fractions: original size, particles less than 5mm, and powder form. Rice husks less than 5mm was observed to have a composition of optimal fixed carbon content (11.63% ± 0.215), moisture content (10.53% ± 0.013), volatile matter (80.72% ± 0.005), and ash content (7.65% ± 0.004). The binding agents, namely starch, dummala tree resin, and wastepaper pulp, were used for briquette production. The optimal compositions for briquettes made with rice husk particles less than 5mm were determined as follows: rice husk with starch (1:6), rice husk with tree resin (1:7), and rice husk with wastepaper pulp (1:5). The calorific values of these optimum briquettes were found to be 15.446 MJ/kg for starch-based briquettes, 15.278 MJ/kg for paper pulp-based briquettes, and 15.323 MJ/kg for tree resin-based briquettes. In addition, briquettes made with an equal ratio (1:1) of binders showed calorific values of 14.175 MJ/kg for starch, 14.227 MJ/kg for paper pulp, and 15.275 MJ/kg for tree resin, with tree resin-based briquettes exhibiting the highest calorific value. In the product quality evaluation study carried out with these results, the proximate and ultimate analyses were conducted to characterize the briquettes and the thermogravimetric analysis (TGA) was conducted to characterize the rice husk and to examine the physical properties of the produced briquettes. The findings indicate that repurposing rice husk waste with various binding agents offers a sustainable solution for biomass fuel production. Accordingly, natural tree resin briquettes exhibited the highest density, compression ratio, and shatter resistance. These results suggest that utilizing natural tree resin can effectively address waste management challenges and create an environmentally friendly and economically viable industrial sector in Sri Lanka. KEYWORDS: Binding agents, Biomass briquettes, Calorific value, Waste management

Indentation and Hardness of Materials: An Inherently Multiscale-Dependent Problem

The method of indentation of an indenter into a material or substrate is widely utilized to characterize one of the mechanical properties of a material, namely hardness. This method is performed on different scales of indenting force, indenter size/dimensions, and size/dimensions of the indented material/substrate. The different scales do not always yield the same hardness output or reading due to material length scales. One of the length scales in a material is related to its heterogeneity, such as in reinforcing particles or second phases. This work performs 3D non-linear finite element analysis using a purely elastic indenter on a composite material. In addition to the scales above that could affect the results, the parameters of particle size, shape, spacing, and volume fraction are all shown to affect the hardness readout in the current work. One of our new findings is that the length scale effect is more phenomenal, especially at scales when the size of the indenter is comparable to any characteristic length in the material beneath the indented surface.

Upcycling Alum Sludge as a Reinforcement in PBAT Composites: A Sustainable Approach to Waste Valorisation

This study explores the valorisation of alum sludge, a byproduct of water treatment processes, as a sustainable reinforcement material in Poly(butylene adipate-co-terephthalate) (PBAT) composites. The research aims to address industrial waste challenges by developing eco-friendly composite materials while promoting circular economy principles. Alum sludge particles, classified into two size distributions (&lt;63 µm and &lt;250 µm), were incorporated into PBAT matrices at varying concentrations. The composites were characterised for their mechanical, thermal, crystallographic, and moisture adsorption properties; and their biodegradation behaviour was evaluated through soil burial tests over 60 days. The results revealed that the 63 µm particle size fraction exhibited superior performance compared to the 250 µm fraction, demonstrating improved mechanical properties, reduced degradation rates, and enhanced interfacial bonding. Composites with 5 wt.% alum sludge achieved a balance between reinforcement and processability, outperforming the other filler concentrations examined. This innovative approach highlights the potential of upcycling alum sludge into functional materials, advancing sustainable waste management and composite manufacturing. Furthermore, the observed variation in degradation rates suggests that these composites can be tailored for applications requiring controlled compostability.

Beyond the loss of beta cells: a quantitative analysis of islet architecture in adults with and without type 1 diabetes.

The organisation and cellular architecture of islets of Langerhans are critical to the physiological regulation of hormone secretion but it is debated whether human islets adhere to the characteristic mantle-core (M-C) structure seen in rodents. It is also unclear whether inherent architectural changes contribute to islet dysfunction in type 1 diabetes, aside from the loss of beta cells. Therefore, we have exploited advances in immunostaining, spatial biology and machine learning to undertake a detailed, systematic analysis of adult human islet architecture in health and type 1 diabetes, by a quantitative analysis of a dataset of >250,000 endocrine cells in >3500 islets from ten individuals. Formalin-fixed paraffin-embedded pancreatic sections (4 μm) from organ donors without diabetes and living donors with recent-onset type 1 diabetes were stained for all five islet hormones and imaged prior to analysis, which employed a novel automated pipeline using QuPath software, capable of running on a standard laptop. Whole-slide image analysis involved segmentation classifiers, cell detection and phenotyping algorithms to identify islets, specific cell types and their locations as(x,y)-coordinatesin regions of interest. Each endocrine cell was categorised into binary variables for cell type (i.e. beta or non-beta) and position (mantle or core). A χ2 test for independence of these properties was performed and the OR was considered to estimate the effect size of the potential association between position and cell type. A quantification of the M-C structure at islet level was performed by computing the probability, r, that the observed number of non-beta cells in the mantle is due to a random arrangement. The distribution of the r values for the islets in the study was contrasted against the r values of a digital population of equivalent randomly arranged islets, termed digital siblings. Both distributions of r values were compared using the earth mover's distance (EMD), a mathematical tool employed to describe differences in distribution patterns. The EMD was also used to contrast the distribution of islet size and beta cell fraction between type 1 diabetes and control islets. The χ2 test supports the existence of a significant (p<0.001) relationship between cell position and type. The effect size was measured via the OR <0.8, showing that non-beta cells are more likely to be found at the mantle (and vice versa). At the islet level, the EMD between the distributions of r values of the observed islets and the digital siblings was emd-1d=0.10951 (0<emd-1d<1). The transport plan showed a substantial group of islets with a small r value, thus supporting the M-C hypothesis. The bidimensional distribution (beta cell fraction vs size) of islets showed a distance emd-2d=0.285 (0<emd-2d<2) between the control and type 1 diabetes islets. The suffixes '-1d' and '-2d' are used to distinguish the comparison between the distribution of one and two variables. Using a novel analysis pipeline, statistical evidence supports the existence of an M-C structure in human adult islets, irrespective of type 1 diabetes status. The methods presented in the current study offer potential applications in spatial biology, islet immunopathology, transplantation and organoid research, and developmental research.

Utilization of the Finer Particle Fraction of Arsenic-Bearing Excavated Rock Mixed with Iron-Based Adsorbent as Sorption Layer

Excavated rocks generated during tunnel construction may pose an environmental hazard due to the release of acidic leachate containing potentially toxic elements (PTEs). Addressing this concern requires strategic countermeasures against mitigating the release of PTEs. This study investigated the efficacy of a novel approach for managing altered excavated rocks that generate acidic leachates with elevated arsenic (As) by utilizing the finer altered rock as a base material for the sorption layer. The proposed method involves classifying the altered excavated rocks into coarse (9.5–37.5 mm) and finer (&lt;9.5 mm) fractions, with the finer fractions incorporated with iron (Fe)-based adsorbent to form a bottom sorption layer for the disposal of coarser rock samples. Leaching behavior and As immobilization efficiency were assessed through shaking, stirring leaching tests, batch sorption tests, and column tests under varying particle size fractions of the rock samples. Results indicate that altered finer rock fractions exhibit increased As leaching under shaking conditions due to enhanced dissolution. The addition of &gt;1% of Fe-based adsorbent to the finer rock in the sorption layer effectively suppressed As leaching concentration, meeting the management criterion of &lt;0.3 mg/L for specially controlled contaminated soils in Japan. Batch sorption tests using the finer rock samples with the Fe-based adsorbent confirmed their efficacy as effective adsorbents. This efficacy was further elucidated in column experiments consisting of the coarse rock samples and fine altered rock samples mixed with the Fe based adsorbent at the bottom as a sorption layer. Results showed that the sorption layer effectively decreased the As leached from the rock layer, utilizing the altered excavated fine rock as a base material in the sorption layer. This approach highlights the potential for repurposing excavated rocks as sorption media, enabling sustainable management strategies for As-contaminated rocks. This study provides an innovative framework for integrating adsorption-based remediation, contributing to sustainable countermeasure strategies for excavated rocks.