Main Source Of Variation Research Articles

Video-based peer assessment of collaborative teamwork in a large-scale interprofessional learning activity.

The assessment of team performance within large-scale Interprofessional Learning (IPL) initiatives is an important but underexplored area. It is essential for demonstrating the effectiveness of collaborative learning outcomes in preparing students for professional practice. Using Kane's validity framework, we investigated whether peer assessment of student-produced videos depicting collaborative teamwork in an IPL activity was sufficiently valid for decision-making about team performance, and where the sources of error might lie to optimise future iterations of the assessment. A large cohort of health professional students (n = 1218) of 8 differing professions was divided into teams containing 5-6 students. Each team collaborated on producing a short video to evidence their management of one of 12 complex patient cases. Students from two other teams, who had worked on the same case, individually rated each video using a previously developed assessment scale. A generalisability study quantified sources of error that impacted the reliability of peer assessment of collaborative teamwork. A decision study modeled the impact of differing numbers of raters. A modified Angoff determined the pass/fail mark. Within a large-scale learning activity, peer assessment of collaborative teamwork was reliable (G = 0.71) based on scoring by students from two teams (n = 10-12) for each video. The main sources of variation were the stringency and subjectivity of fellow student assessors. Whilst professions marked with differing stringency, and individual student assessors had different views of the quality of a particular video, none of that individual assessor variance was attributable to the assessors' profession. Teams performed similarly across the 12 cases overall, and no particular professions marked differently on any particular case. A peer assessment of a student-produced video depicting interprofessional collaborative teamwork around the management of complex patient cases can be valid for decision-making about student team performance. Further refining marking rubrics and student assessor training could potentially modify assessor subjectivity. The impact of professions on assessing individual peers and the case-specificity of team performances in IPL settings need further exploration. This innovative approach to assessment offers a promising avenue for enhancing the measurement of collaborative learning outcomes in large-scale Interprofessional learning initiatives.

Evaluation of yield and stability of sugar beet (beta vulgaris L.) genotypes using GGE biplot and AMMI analysis

Rhizomania is the most destructive sugar beet disease in the world, and in recent years, it has widespread in most of the sugar beet growing areas in Iran. Since the control of this soil-borne disease is a difficult task, the use of resistant genotypes is known as the best measure against the disease. The ultimate goal of sugar beet breeders is to produce genotypes that can be used in both infected and non-infected fields without any reduction in terms of yield and quality. Twenty-one sugar beet genotypes along with four controls were evaluated in randomized complete block design with four replications in fields with natural infection to rhizomania in five research stations. Important sugar beet traits including root yield, sugar yield, sugar content, and white sugar yield were evaluated for two years (2021 and 2022). For all traits, location was the main source of variation that spanned 33 to 55% of the total sum of the square followed by the location×year×genotype accounted for 3–40% of the variation. Based on the results of analysis of variance, multivariate stability parameters were computed to evaluate the genotypes’ stability. The first two principal components (IPCA1 and IPCA2) generated by GGE biplot contributed for 31.3 and 17.5% difference in genotype×environment interaction for root yield, respectively. According to the GGE biplot, genotypes RM-11 and RM-12 were identified as the winning genotypes across environments for both root yield and white sugar yield traits whereas AMMI model identified RM-14 and RM-9 (for root yield) and RM-1 (for white sugar yield) as best genotypes. Based on the ideal genotype ranking, RM-11 and RM-10 were the best performer with a high mean yield as well as stability in the studied environments. The biplot rendered using the weighted average of absolute scores (WAASB) and root yield and white sugar yield identified RM-11 and RM-9 as superior genotypes in terms of yield and stability. The selected genotypes can be used in breeding programs to transfer the disease resistance and cultivar development.

When words are your scalpel, what and how information is exchanged may be differently salient to assessors.

Variable assessments of learner performances can occur when different assessors determine different elements to be differently important or salient. How assessors determine the importance of performance elements has historically been thought to occur idiosyncratically and thus be amenable to assessor training interventions. More recently, a main source of variation found among assessors was two underlying factors that were differently emphasised: medical expertise and interpersonal skills. This gave legitimacy to the theory that different interpretations of the same performance may represent multiple truths. A faculty development activity introducing assessors to entrustable professional activities in which they estimated a learner's level of readiness for entrustment provided an opportunity to qualitatively explore assessor variation in the context of an interaction and in a setting in which interpersonal skills are highly valued. Using a constructivist grounded theory approach, we explored variation in assessment processes among a group of palliative medicine assessors who completed a simulated direct observation and assessment of the same learner interaction. Despite identifying similar learner strengths and areas for improvement, the estimated level of readiness for entrustment varied substantially among assessors. Those who estimated the learner as not yet ready for entrustment seemed to prioritise what information was exchanged and viewed missed information as performance gaps. Those who estimated the learner as ready for entrustment seemed to prioritise how information was exchanged and viewed the same missed information as personal style differences or appropriate clinical judgement. When presented with a summary, assessors expressed surprise and concern about the variation. A main source of variation among our assessors was the differential salience of performance elements that align with medical expertise and interpersonal skills. These data support the theory that when assessing an interaction, differential salience for these two factors may be an important and perhaps inevitable source of assessor variation.

A Multivariate Phenotypical Approach of Sepsis and Septic Shock—A Comprehensive Narrative Literature Review

Despite medical advances, sepsis and septic shock remain some of the leading causes of mortality worldwide, with a high inter-individual variability in prognosis, clinical manifestations and response to treatment. Evidence suggests that pulmonary sepsis is one of the most severe forms of sepsis, while liver dysfunction, left ventricular dysfunction, and coagulopathy impact the prognostic. Sepsis-related hypothermia and a hypoinflammatory state are related to a poor outcome. Given the heterogeneity of sepsis and recent technological progress amongst machine learning analysis techniques, a new, personalized approach to sepsis is being intensively studied. Despite the difficulties when tailoring a targeted approach, with the use of artificial intelligence-based pattern recognition, more and more publications are becoming available, highlighting novel factors that may intervene in the high heterogenicity of sepsis. This has led to the devise of a phenotypical approach in sepsis, further dividing patients based on host and trigger-related factors, clinical manifestations and progression towards organ deficiencies, dynamic prognosis algorithms, and patient trajectory in the Intensive Care Unit (ICU). Host and trigger-related factors refer to patients’ comorbidities, body mass index, age, temperature, immune response, type of bacteria and infection site. The progression to organ deficiencies refers to the individual particularities of sepsis-related multi-organ failure. Finally, the patient’s trajectory in the ICU points out the need for a better understanding of interindividual responses to various supportive therapies. This review aims to identify the main sources of variability in clustering septic patients in various clinical phenotypes as a useful clinical tool for a precision-based approach in sepsis and septic shock.

The Impact of Liver Steatosis on Interleukin and Growth Factors Kinetics during Chronic Hepatitis C Treatment.

Background/Objectives: Various biological response modifiers play important roles in the immunopathogenesis of chronic hepatitis C (CHC). While serum levels of cytokines and growth factors change with the disease severity and treatment responses, the impact of concomitant liver steatosis on systemic inflammatory response is largely unknown. The aim of this study was to analyze the characteristics and kinetics of serum profiles of interleukins and growth factors in CHC patients with steatotic liver disease (SLD). Methods: Serum concentrations of 12 cytokines (IL-5, IL-13, IL-2, IL-6, IL-9, IL-10, IFN-γ, TNF-α, IL-17A, IL-17F, IL-4 and IL-22) and 6 growth factors (Angiopoietin-2, EGF, EPO, HGF, SCF, VEGF) were analyzed in 56 CHC patients at four time points (baseline, week 4, week 8 and SVR12) with bead-based flow cytometry assay. Results: At baseline, patients with SLD had significantly lower IL-9, IL-10, IL-13 and IL-22 and higher serum concentrations of EGF, VEGF and ANG. In a subgroup of patients with advanced liver fibrosis, SLD was linked with lower serum concentrations of IL-4, IL-5, IL-9, IL-10, IL-13 and IL-22 and higher concentrations of HGH and VEGF. Distinct cytokine kinetics during DAA treatment was observed, and SLD was identified as the main source of variation for IL-5, IL-9, IL-10, IL-13, IL-17A, IL-22, EGF, VEGF and ANG. Patients with SLD at SVR12 had significantly higher VEGF and HGF serum concentrations. Conclusions: SLD is associated with distinct cytokine and growth factor profiles and kinetics during CHC treatment, which might be associated with disease severity and the capacity for liver regeneration and contribute to fibrosis persistence.

Co-flowering richness has variable effects on pollen quantity and quality limitation in four Clarkia species.

Pollination failure occurs from insufficient pollen quantity or quality. However, the relative contributions of pollen quantity vs quality to overall pollen limitation, and how this is affected by the co-flowering context, remain unknown for most plant populations. Here, we studied patterns of pollen deposition and pollen tube formation across populations of four predominately outcrossing species in the genus Clarkia to evaluate how richness of co-flowering congeners affects the contribution of pollen quantity and quality to pollen limitation. We partition variation in pollen deposition and pollen tube production across individuals, populations and species to identify the main sources of variation in components of reproductive success. We further quantify the relative contribution of pollen quantity and quality limitation to the reproductive success of the four Clarkia species using piecewise regression analyses. Finally, we evaluate how variation in the number of co-flowering Clarkia species in the community affects the strength of pollen quality and quality limitation. Across all contexts, pollen deposition and the proportion of pollen tubes produced varied greatly among individuals, populations, and species, and these were not always correlated. For instance, C. xantiana received the smallest pollen loads yet produced the highest proportion of pollen tubes, while C. speciosa exhibited the opposite pattern. Yet, co-flowering richness had variable effects on the strength of pollen quantity and quality limitation among populations. Specifically, breakpoint values, which are an indicator of overall pollen limitation, were two times larger in the four-species community compared with one and two-species communities for two Clarkia species, suggesting that pollen limitation can increase with increasing richness of co-flowering congeners. Our results reveal a complex interplay between quantity and quality of pollen limitation and co-flowering context that may have different evolutionary outcomes across species and populations.

Assessment of hepatic transporter function in rats using dynamic gadoxetate-enhanced MRI: a reproducibility study

ObjectivePrevious studies have revealed a substantial between-centre variability in DCE-MRI biomarkers of hepatocellular function in rats. This study aims to identify the main sources of variability by comparing data measured at different centres and field strengths, at different days in the same subjects, and over the course of several months in the same centre.Materials and methods13 substudies were conducted across three facilities on two 4.7 T and two 7 T scanners using a 3D spoiled gradient echo acquisition. All substudies included 3–6 male Wistar-Han rats each, either scanned once with vehicle (n = 76) or twice with either vehicle (n = 19) or 10 mg/kg of rifampicin (n = 13) at follow-up. Absolute values, between-centre reproducibility, within-subject repeatability, detection limits, and effect sizes were derived for hepatocellular uptake rate (Ktrans) and biliary excretion rate (kbh). Sources of variability were identified using analysis of variance and stratification by centre, field strength, and time period.ResultsData showed significant differences between substudies of 31% for Ktrans (p = 0.013) and 43% for kbh (p < 0.001). Within-subject differences were substantially smaller for kbh (8%) but less so for Ktrans (25%). Rifampicin-induced inhibition was safely above the detection limits, with an effect size of 75 ± 3% in Ktrans and 67 ± 8% in kbh. Most of the variability in individual data was accounted for by between-subject (Ktrans = 23.5%; kbh = 42.5%) and between-centre (Ktrans = 44.9%; kbh = 50.9%) variability, substantially more than the between-day variation (Ktrans = 0.1%; kbh = 5.6%). Significant differences in kbh were found between field strengths at the same centre, between centres at the same field strength, and between repeat experiments over 2 months apart in the same centre.DiscussionBetween-centre bias caused by factors such as hardware differences, subject preparations, and operator dependence is the main source of variability in DCE-MRI of liver function in rats, closely followed by biological between-subject differences. Future method development should focus on reducing these sources of error to minimise the sample sizes needed to detect more subtle levels of inhibition.

Exploring the use of extended multiplicative scattering correction for near infrared spectra of wood with fungal decay

Extended Multiplicative Signal Correction (EMSC) is a multivariate linear modelling technique for multi-channel measurements that can identify and correct for different types of systematic variation patterns, known or unknown. It is typically used for pre-processing to separate light absorbance spectra, obtained by diffuse reflectance of intact samples, into three main sources of variation: additive variations due to chemical composition (≈Beer's law), mixed multiplicative and additive variations due to physical light scattering (≈Lambert's law) and more or less random measurement noise. The present work evaluates the use of EMSC to pre-process near infrared spectra obtained by hyperspectral imaging of Scots pine sapwood, inoculated with two different basidiomycete fungi and at various degradation stages. The spectral changes due to fungal decay and resulting mass loss are assessed by interpretation of the EMSC parameters and the partial least squares regression (PLSR) results. Including a cellulose (analyte) or bound water (interferent) spectral profile in the EMSC pre-processing model generally improves the predictive performance of the PLS modelling, but it can also make it worse. The inclusion of the additional polynomial baselines does not necessarily lead to a better separation of the physical and chemical effects present in the spectra. The estimated EMSC parameters provide insight into the differences in decay mechanisms. A detailed analysis of the EMSC results highlights advantages and disadvantages of using a complex pre-processing model.

Addressing the sources of inter-subject variability in E-field parameters in anodal tDCS stimulation over motor cortical network

Objetive: . Although transcranial direct current stimulation constitutes a non-invasive neuromodulation technique with promising results in a great variety of applications, its clinical implementation is compromised by the high inter-subject variability reported. This study aims to analyze the inter-subject variability in electric fields (E-fields) over regions of the cortical motor network under two electrode montages: the classical C3Fp2 and an alternative P3F3, which confines more the E-field over this region. Approach. Computational models of the head of 98 healthy subjects were developed to simulate the E-field under both montages. E-field parameters such as magnitude, focality and orientation were calculated over three regions of interest (ROI): M1S1, supplementary motor area (SMA) and preSMA. The role of anatomical characteristics as a source of inter-subject variability on E-field parameters and individualized stimulation intensity were addressed using linear mixed-effect models.Main results. P3F3 showed a more confined E-field distribution over M1S1 than C3Fp2; the latter elicited higher E-fields over supplementary motor areas. Both montages showed high inter-subject variability, especially for the normal component over C3Fp2. Skin, bone and CSF ROI volumes showed a negative association with E-field magnitude irrespective of montage. Grey matter volume and montage were the main sources of variability for focality. The curvature of gyri was found to be significantly associated with the variability of normal E-fields.Significance. Computational modeling proves useful in the assessment of E-field variability. Our simulations predict significant differences in E-field magnitude and focality for C3Fp2 and P3F3. However, anatomical characteristics were also found to be significant sources of E-field variability irrespective of electrode montage. The normal E-field component better captured the individual variability and low rate of responder subjects observed in experimental studies.

Genetic diversity of the Turkish accessions of two progenitor species, Triticum baeoticum Boiss. and Triticum urartu Thum. ex Gandil., using DArTSeq markers

AbstractThe aim of this study was to reveal the intra and interspecies differences between Triticum baeoticum and Triticum urartu using Diversity Arrays Technology sequencing (DArTseq) on 94 accessions representing Turkish populations. Seeds were gathered from the US Department of Agriculture, and from the Turkish Seed Gene Bank. Isolated and purified DNA samples were sent to Diversity Arrays Technologies for DArTseq. After the necessary quality filtering, a total of 16,898 and 100,103 loci were obtained respectively from the single nucleotide polymorphism (SNP) and SilicoDArT datasets. ADMIXTURE software was used to reveal the intra and interspecies population structures. Analysis of molecular variance was carried out to reveal the variance between the populations of the T. urartu and T. baeoticum species. Principal coordinate analysis was conducted to visualize the main sources of variation between the populations on a 2-dimensional plane. To reveal the evolutionary relationship, SNP dataset was used to reconstruct the phylogenetic dendrograms by using the maximum likelihood statistical method and the unweighted pair group method with arithmetic mean clustering algorithm. As a result of this study, the accessions of T. urartu and T. baeoticum species formed separate clusters and revealed as two different species. In line with the results obtained, it is obvious that the identification of some accessions should be re-evaluated. The results demonstrated that DArTseq, is a fast, low-cost, and high-accuracy method that can be used in species and population discrimination and an effective tool for Gene Bank management.

Relationship between foliar polycyclic aromatic hydrocarbons (PAHs) concentrations and plant traits: Intracanopy variability for a broadleaf species in an urban environment

The emission of potentially harmful compounds, including polycyclic aromatic hydrocarbons (PAHs), and the resulting air pollution is a serious problem in modern cities. It is therefore important to develop mitigation strategies, such as “smart” planting of trees that act as sinks for PAHs. However, the intra-individual (within-tree) variability in leaf PAH concentrations remains unknown. In this paper, we studied 15 ornamental apple trees (Malus × moerlandsii ‘Profusion’) growing on a main street in a medium-sized city in Galicia (NW Spain). We determined the PAH concentrations at 12 canopy positions in each tree (2 orientations and 2 distances from the trunk at 3 heights), measured various ecological traits (specific leaf area [SLA], δ13C, stomatal density, fatty acid contents and leaf hairiness) and analyzed the variability in traits within the canopy in relation to PAH concentrations. We observed high intra-individual variability in the PAH concentrations and the leaf traits. Statistical analyses revealed that leaf height was the main source of variability both in the PAH concentrations and in the traits, mainly due to the leaf morphology, particularly to the SLA. Therefore, the ideal vegetation to remove PAHs would be high leaf biomass trees, not too tall and with a high proportion of shade leaves.

In-depth analysis of volatolomic and odorous profiles of novel craft beer by permutation test features selection and multivariate correlation analysis

This research explored the impact of binary cereal blends [barley with durum wheat (DW) and soft wheat (CW)], four autochthonous yeast strains (9502, 9518, 14061 and 17290) and two refermentation sugar concentrations (6–9 g/L), on volatolomics (VOCs) and odour profiles of craft beers using unsupervised statistics. For the first time, we applied permutation test to select volatiles with higher significance in explaining variance among samples. The unsupervised approach on the 19 selected VOCs revealed cereal-yeast interaction to be the main source of variability and DW-9502-6/9, DW-17290-6, CW-17290-6 and CW-9518-6 being the best technological strategies. In particular, in samples DW-9502-6/9, concentrations of some of the selected volatiles were observed to be approximately three to more than seven times higher than the average. PLS-correlation between VOCs and odour profiles proved to be very useful in assessing the weight of each of the selected VOCs on the perception of odour notes.

The Rio Grande Rise circulation: Dynamics of an internal tide conversion hotspot in the Southwestern Atlantic

The Rio Grande Rise (RGR) is a plateau located at 31°S in the Southwestern Atlantic, rising from 5916m up to 161m below the sea level. The RGR is an important site for future mining of Fe-Mn crusts and can lead to an expansion of Brazil’s Exclusive Economic Zone. The Cruzeiro do Sul Rift (CSR) fault cuts through the RGR from southeast to northwest. In this study we characterize the RGR circulation, showing that M2 tides are the main source of variability in the region, with an amplitude that can reach 0.3ms−1, larger than the mean flow. These M2 tides are dominated by the baroclinic component and intensified near the bottom. The generation of M2 internal tides occurs mainly in the CSR slopes, with most energy converted from the barotropic tide being radiated away in the form of tidal beams. In addition, the impingement of the mean southern South Equatorial Current and tidal rectification generates anticyclonic circulations around the RGR peaks, with the latter mechanism being responsible for a bottom intensified anticyclonic circulation of 0.2ms−1. Finally, our results reveal that the RGR is a hotspot of internal tide generation in the Southwestern Atlantic.

Day-to-day variation in trace and macro-mineral concentrations in corn and mixed grass–legume silages of Canadian commercial dairy herds

The aims were to assess the day-to-day variation in trace minerals (TM), macro-minerals, dry matter, and physical effectiveness factor in grass–legume and corn silages and to evaluate the variance partition. Grass–legume and corn silage samples were collected in nine Canadian dairy herds during two episodes of five consecutive days at 4 weeks apart by the same individual. All variables were analyzed in duplicate. The proportion of variation due to the farm was more variable within TM than macro-minerals. Using TM software reference values of silages for formulating rations can lead to important errors. Except for physical effectiveness factor, the within-farm variations between sampling episodes were more marked for mixed grass–legume than corn silage. For most of the minerals and nutrients analyzed, the sampling + day-to-day variations were the main source of variability, accounting for over 50% of the within-farm variance for both silage types. The remaining within-farm variance was explained by subsampling and laboratory analyses. The high within-herd variation suggests that a silage sampling over more than 1 day can be useful to get a representative sample for TM analysis. Accurate nutrients and TM values when formulating cow diets is essential to cow health and productivity.

Effects of post-flowering drought and supplemental irrigation on grain yield and agro-phenological traits in durum wheat

Water deficit and unbalanced distribution rainfall in the Mediterranean rainfed regions are major problems threatening agricultural sustainability, especially durum wheat (Triticum turgidum L. var. durum) production. This study aimed to investigate the effects of drought and supplemental irrigation in post-flowering stage on traits performance of durum wheat trials and to identify traits that significantly contribute to increase the grain yield of durum wheat under different water regimes and recommend new genotypes adapted to climate change. An eight-year field study was conducted from 2014 to 2022, consisting of 36 field experiments, 18 under rainfed and 18 under supplemental irrigation (two times irrigation in flowering and grain-filling stages) conditions through six experimental series of elite durum wheat yield trials each with same genotypes. In each experiment, grain yield, 1000-kernel weight (TKW), plant height (PLH), days to heading (DHE) and maturity (DMA) were recorded. Drought stress tolerance index (STI) and mean productivity (MP) were applied to differentiate high-performing and drought tolerant durum wheat genotypes in each experimental series. The combined analysis of variance for traits studied of each experimental series indicated that the year, water stress treatment, genotype and their interaction effects were significant. For grain yield, year was the main source of variation and had the highest impact on genotypes performance. The results indicated that the supplemental irrigation, depending on genetic materials, significantly increased grain yield (18.7%-45.8%), TKW (8.2%-12.9%), and PLH (1.1%-8.2%) compared with the rainfed condition across years. Supplemental irrigation exhibited for no significant effect on the increase of the maturity time (0.2%-2.2%) of genotypes tested compared with the rainfed condition. The results confirmed the systematic effects of post-flowering drought on yield, grain weight and plant stature of durum wheat. A positive and significant trend (R2=0.62; P<0.01) was observed between yield production in rainfed condition and cumulative rainfall, showing that in 62% of the cases higher rainfall resulted in higher performance. TKW and PLH significantly and positively correlated with mean yield in the both rainfed and irrigated conditions, suggesting the importance of these two traits in breeding programs to assist in developing high yielding genotypes under different water regime conditions. Evaluation of genotypes in terms of mean yield and stability performance using GGE biplot, resulted in identification of superior lines that outperformed the check cultivars. The STI and MP were desirable selection criteria for high yielding and drought tolerant genotypes, thus high yielding genotypes that are tolerant to drought would be expected to have good yield stability in stressful environments. The results highlight the significant effects of drought stress after flowering upon grain yield, and the significant contribution of 1000-kernel weight and plant height to increase grain yield under different water regimes, that could be utilized to aid breeding of high-performing and drought tolerant durum wheat genotypes under the future climate conditions.

Partitioning of nutrient variation in alfalfa and corn silage by source on New York dairy farms

Variation in feed components contributes to variation and uncertainty of diets delivered to dairy cows. Forages often have a high inclusion rate (50 to 70% of DM fed) and variable composition, thus are an important contributor to nutrient variability of delivered diets. Our objective was to quantify the variation and identify the main sources of variability in corn silage and alfalfa-grass haylage composition at harvest (fresh forage) and feed-out (fermented forage) on NY dairy farms. Corn silage and alfalfa-grass haylage were sampled on 8 NY commercial dairy farms during harvest in the summer and fall of 2020 and during their subsequent feed-out in the winter and spring of 2021. At harvest, a composite sample of fresh chopped forage of every 8-ha section of individual fields was collected from piles delivered for silo filling. During a 16-week feed-out period, 2 independent samples of each forage were collected 3 times per week. The fields-of-origin of each forage sample during feed-out were identified and recorded using silo maps created at filling. A mixed-model analysis quantified the variance of corn silage DM, NDF, and starch and haylage DM, NDF, and CP content. Fixed effects included soil type, weather conditions, and management practices during harvest and feed-out while random effects were farm, silo unit, field, and day. At harvest, between-farm variability was the largest source of variation for both corn silage and haylage, but within-farm sources of variation exceeded farm-to-farm variation for haylage at feed-out. At feed-out, haylage DM and NDF content had higher within-farm variability than corn silage. In contrast, corn silage starch showed higher within-farm variation at feed-out than haylage CP content. For DM content at feed-out, day-to-day variation was the most relevant source of within-farm variation for both forages. However, for the nutrient components at feed-out (NDF and CP for haylage; NDF and starch for corn silage) silo-to-silo variation was the largest source of variability. Weather conditions systematically explained a proportion of the farm-to-farm variability for both forages at harvest and feed-out. We concluded that because of the high farm-to-farm variation, corn silage and haylage must be sampled on individual farms. We also concluded that due to the high silo-to-silo variability, and the still significant day-to-day and field-to-field variability within-farm, corn silage and haylage should be sampled within individual silos to better capture changes in forage components at feed-out.

Abstract A087: An ovarian cancer scRNA-seq atlas to dissect tumor-host interactions underlying metastatization and chemoresistance

Abstract The high tumor heterogeneity of high grade serous ovarian cancer (HGSOC) both intra-tumoral and inter-patient is one of the main factors hampering the identification of novel therapeutic treatment to improve survival of HGSOC patients. Single cell technologies are affording new inroads for the deep molecular characterization of such tumor heterogeneity, in both primary and metastatic samples. To this aim, we built a manually curated HGSOC transcriptomics atlas (~ 1,5 million cells, 79 patients) based on publicly available datasets and developed a data integration strategy specifically applicable to very heterogenous single cell data. scRNA-seq data integration is a central methodological challenge related to single cell data analysis, particularly in the context of highly heterogenous datasets. In this context, the main source of variability is the one existing among patients. Previously developed integration methods tend to perform badly on cancer data since they mainly rely on the assumption that cell populations present in different samples are similar, which might not apply for unknown, rare or patient-specific cell populations. Here we show a novel integration approach for patient-derived cancer data. To obtain a more faithful representation of the data, we performed identification of cell populations and metacells derivation separately for every sample to identify the distinct subpopulations characterizing each patient. In addition, to robustly represent the space describing the three main cell populations of the dataset, i.e., tumoral, immune and stromal, for each of the latter we selected the space identified by the union of highly variable genes, computed separately on every dataset, to preserve the variability of the system. Next, we fed a variational autoencoder with metacells data to integrate and characterize the different subpopulations that may be similar across samples. After integration, we were able to identify new robust gene signatures that would have been masked by datasets heterogeneity. The high degree of accuracy in the manual curation of metadata harmonization in the HGSOC atlas and the robustness and scalability of the data integration pipeline allowed us to obtain an in-depth characterization of the tumor subpopulations involved in therapy response by characterizing the chemotherapy induced transcriptional features. At the same time, thanks to the atlas-associated cell types labelling strategy, this atlas represents a transformative resource for the community by enabling the investigation of the interaction between tissue microenvironment (TME) cells and tumoral cells in shaping the metastatic process. This innovative HGSOC atlas will provide the scientific community of ovarian cancer research with a very powerful tool to investigate many aspects of this disease. The robust deep learning-based framework allows to expand the atlas easily and iteratively with newly generated datasets (out of sample extension), will constitute an invaluable resource for the HGSOC scientific field tackling HGSOC pathogenetic mechanism. Citation Format: Marta R. Sallese, Pietro Lo Riso, Carlo Emanuele Villa, Giuseppe Testa. An ovarian cancer scRNA-seq atlas to dissect tumor-host interactions underlying metastatization and chemoresistance [abstract]. In: Proceedings of the AACR Special Conference on Ovarian Cancer; 2023 Oct 5-7; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(5 Suppl_2):Abstract nr A087.

Evaluating Groundwater Quality Using Multivariate Statistical Analysis and Groundwater Quality Index

Under pressure from surface water pollution and climate change, groundwater becomes a critical water source. Information on groundwater quality could contribute to effective groundwater management. This study was carried out to utilize multivariate statistical analysis and the groundwater quality index (GWQI) to evaluate groundwater quality in Ca Mau Province, Vietnam. Twenty-five groundwater samples from residential-urban areas, cemetery areas, landfill areas, and saline intrusion areas were collected for this study. Groundwater quality was evaluated using the National Technical Regulation on Groundwater Quality (QCVN 09-MT:2015/BTNMT) and GWQI. Principal component analysis (PCA) was used to identify potential polluting sources and key variables influencing groundwater quality. Cluster analysis (CA) was applied to cluster groundwater quality, and the sites were recommended for future monitoring. The results revealed that NH4+-N contaminated groundwater in the landfill area, while the saline intrusion area was polluted by TDS and NH4+-N. The groundwater quality classified as excellent, good, poor, and very poor accounted for 44, 40%, 12%, and 4%, respectively. Cluster analysis divided groundwater quality into four groups, mainly based on the presence of NH4+-N and TDS. Nine groundwater sampling locations could be removed from the current groundwater quality program but still ensuring representativeness as a result of CA. PCA proposed two main sources of variation in groundwater quality at each residential-urban area: the cemetery area, the landfilling area, and the saline intrusion area. The groundwater parameters (i.e., pH, TDS, permanganate index, NH4+-N, NO3--N, and Fe) should be continued to monitor. Domestic and industrial wastewater discharge, leachate from cemeteries and landfills, the nature of groundwater aquifers, and seawater intrusion could be potential sources of groundwater variation. The current findings provide scientific information for local environmental authorities to manage and monitor groundwater quality in the study area. Doi: 10.28991/CEJ-2024-010-03-03 Full Text: PDF

Parametrization of the Calcaneus and Medial Cuneiform to Aid Potential Advancements in Flatfoot Surgery.

Flatfoot is a condition commonly seen in children; however, there is general disagreement over its incidence, characterization and correction. Painful flatfoot accompanied with musculoskeletal and soft tissue problems requires surgery to avoid arthritis in adulthood, the most common surgical approach being two osteotomies to the calcaneus and medial cuneiform bones of the foot. This study focuses on the parametrization of these two bones to understand their bone morphology differences in a population sample among 23 normal subjects. Population differences could help in understanding whether bone shape may be an important factor in aiding surgical planning and outcomes. A total of 45 sets of CT scans of these subjects were used to generate surface meshes of the two bones and converted to be iso-topological meshes, simplifying the application of Generalized Procrustes Analysis and Principal Component Analysis, allowing the main sources of variation between the subjects to be quantified. For the calcaneus, 16 Principal Components (PCs) and, for the medial cuneiform, 12 PCs were sufficient to describe 90% of the dataset variability. The quantitative and qualitative analyses confirm that for the calcaneus PC1 describes the Achilles attachment location and PC2 largely describes the anterior part of the bone. For the medial cuneiform, PC1 describes the medial part of the bone, while PC2 mainly describes the superior part. Most importantly, the PCs did not seem to describe the osteotomy sites for both bones, suggesting low population variability at the bone cutting points. Further studies are needed to evaluate how shape variability impacts surgical outcomes. Future implications could include better surgical planning and may pave the way for complex robotic surgeries to become a reality.

Utjecaj sezone parenja i stanja tijela na zootehničke parametre ouled djellal ovaca u polupustinjskim područjima

In this study, a database was created by monitoring 3000 Ouled Djellal ewes, belonging to ten breeding farms and representing two modes of reproduction management. The data collected make it possible to measure the reproductive performance of females and to determine the influence of non-genetic factors on different parameters. The Body Condition Score (BCS) was calculated to compare performance in relation with breeding conditions. The results showed that fertility and prolificacy accounted for 91.1±0.1% and 116.4±0.2% in the reproduction mode respectively based on one lambing/year with exclusive spring control, and of 53.5±0.2% and 101.2±0.1% respectively in the traditional lambing system spread overthe year (with the ram permanently present in the flock) (P&amp;lt;0.05). The BCS varied according to mating season and feeding system. Indeed, as the BCS at mating increased, fertility, prolificacy and productivity improved. Ewes whose BCS at mating was equal to or greater than 3 obtained the best performance, while those with a lower BCS were less fertile, less prolific, and less productive. The average productivity of Ouled Djellal sheep was 107.0±0.1%, and 54.8±0.3%, respectively, in the first and second mode of reproduction management (P&amp;lt;0.05). This study highlights the main sources of variations and their interactions.