Arbitrary Threshold Research Articles

Association between arterial oxygen tension with clinical outcomes in patients undergoing VA-ECMO support: a systematic review and dose-response meta-analysis

Abstract Background Arterial hyperoxia has been associated with a worse prognosis in critically ill patients. However, studies conducted in patients undergoing Veno-Arterial Extracorporeal Membrane Oxygenation (VA-ECMO) used inconsistent and arbitrary thresholds for defining hyperoxia, which impeded the determination of the optimal target for arterial oxygen tension (PaO2) in this population. Purpose To investigate and visualise the dose-response relationship between post-ECMO level of PaO2 with early mortality (in-hospital and 1-month) and poor neurological outcomes in adult patients undergoing VA-ECMO support, including Extracorporeal Cardiopulmonary Resuscitation (ECPR). Methods A systematic search was conducted through Pubmed and Embase to include studies that stratified patients based on PaO2 levels and evaluated relevant outcomes. We utilised either adjusted Odds Ratio (OR) with 95% Confidence Interval (CI) when available, or unadjusted OR against the lowest exposure category. The median, mean, or midpoint value of PaO2 was assigned as the corresponding dose. A random-effects one-stage dose-response meta-analysis was performed to assess linear association for every 10 mmHg increase in PaO2, while potential non-linear relationship was explored with restricted cubic splines at 3 knots (10th, 50th, and 90th percentile). Non-linearity was assessed by using Wald test with p value <0.05 considered significant. Statistical analyses were performed using STATA 17.0. Results Fourteen eligible records were identified (cardiogenic shock/CS = 5 records; ECPR = 8 records; both = 1 record). Only four studies classified a separate category for hypoxemic patients (<60 mmHg). PaO2 levels were measured within 24-72 hours of VA-ECMO initiation, except in one study. PaO2 level was not associated with early mortality (9 studies; OR 1.021 [95% CI 0.988–1.055]; p for non-linearity = 0.893), but found to have a linear association with composite poor neurological outcomes (6 studies; OR 1.016 [1.009–1.024]; p for non-linearity = 0.346). Subgroup analysis of CS patients revealed a linear association between PaO2 >100 mmHg and early mortality (4 studies; OR 1.025 [95%CI 1.018–1.032]; p for non-linearity = 0.255). For ECPR patients, a J-shaped relationship was observed between PaO2 and early mortality (5 studies; p for non-linearity = 0.004), with the lowest odds being at PaO2 level of 110-210 mmHg, while PaO2 level >110 mmHg showed a linear trend towards higher odds of poor neurological function (4 studies; OR 1.091 [95%CI 0.938–1.269]; p for non-linearity = 0.257). Conclusion Pooled data from observational studies suggest that PaO2 >100 mmHg should be avoided in CS patients on VA-ECMO support, given its linear association with mortality, but it cannot be extrapolated to hypoxemic patients. In ECPR patients, PaO2 level around 110-210 mmHg conferred the best clinical outcomes. However, these findings should be confirmed through randomised controlled trials.

Can molecular patterns help to classify overlapping entities in myeloid neoplasms?

Myeloid neoplasms include myeloproliferative and myelodysplastic neoplasms and acute myeloid leukaemia. Historically, these diseases have been diagnosed based on clinicopathological features with sometimes arbitrary thresholds that have persisted even as molecular features were gradually incorporated into their classification. As such, although current diagnostic approaches can classify the majority of myeloid neoplasms accurately using a combination of molecular and clinicopathological features, some areas of overlap persist and occasionally pose diagnostic challenges. These include overlap across BCR::ABL1-negative myeloproliferative neoplasms; between clonal cytopenia of undetermined significance and myelodysplastic neoplasms; myelodysplastic/myeloproliferative neoplasms; and, detection of KIT mutations in myeloid neoplasms other than mastocytosis, raising the prospect of systemic mastocytosis. Molecular testing has become state of the art in the diagnostic work-up of myeloid neoplasms, and molecular patterns can inherently help to classify overlapping entities if considered within a framework of haematological presentations. For future development, molecular testing will likely include whole genome and transcriptome sequencing, and primarily molecular classifications of myeloid neoplasms have already been suggested. As such, genetically defined groups should still constitute the basis for our understanding of disease development from early onset to progression, while clinicopathological features could then be used to describe the stage of the disease rather than the specific type of myeloid neoplasm.

Statistically principled feature selection for single cell transcriptomics.

The high dimensionality of data in single cell transcriptomics (scRNAseq) requires investigators to choose subsets of genes (feature selection) for downstream analysis (e.g., unsupervised cell clustering). The evaluation of different approaches to feature selection is hampered by the fact that, as we show here, the performance of feature selection methods varies greatly with the task being performed. For routine cell type identification, even randomly chosen features can perform well, but for cell type differences that are subtle, both number of features and selection strategy can matter strongly. Here we present a simple feature selection method grounded in an analytical model that, without resorting to arbitrary thresholds or user-defined parameters, allows for interpretable delineation of both how many and which features to choose, facilitating identification of biologically meaningful rare cell types. We compare this method to default methods in scanpy and Seurat, as well as SCTransform, showing how greater accuracy can often be achieved with surprisingly few, well-chosen features.

Approach to Newborns with Elevated TSH: A Different Perspective from the International Guidelines for Iodine-Deficient Countries.

Lowering of thyroid-stimulating hormone (TSH) cutoffs in newborn screening programs has created a management dilemma by leading to more frequent detection of neonates with elevated TSH concentrations due to false-positive results, transient neonatal hyperthyrotropinemia (NHT), and milder forms of congenital hypothyroidism. Current consensus guidelines recommend starting treatment if the venous TSH level is >20 mU/l in the face of a normal free thyroxin (FT4) level, which is an arbitrary threshold for treatment decisions. In countries such as Türkiye, where transient NHT may be more common due to iodine deficiency and/or overload, putting this recommendation into daily practice may lead to unnecessary and over treatments, long-term follow-ups, and increased workload and costs. In this review, we addressed alternative approaches for infants with elevated TSH concentrations detected at newborn screening. Our management approach can be summarized as follows: Infants with mild NHT (TSH<20 mU/l) should be followed without treatment. In moderate NHT (TSH 20-30 mU/l), treatment or monitoring decisions can be made according to age, TSH trend and absolute FT4 level. Moderate cases of NHT should be treated if age at confirmatory testing is >21 days or if there is no downward trend in TSH and FT4 level is in the lower half of age-specific reference range in the first 21 days. In in-between cases of moderate NHT, thyroid ultrasound can guide treatment decision by determining mild cases of thyroid dysgenesis that require life-long treatment. Otherwise, monitoring is a reasonable option. Infants with compensated hypothyroidism (TSH>30 mU/l) and persistent hyperthyrotropinemia (>6-10 mU/l after neonatal period) should receive L-thyroxine treatment. But all treated cases of isolated TSH elevation should be closely monitored to avoid overtreatment, and re-evaluated by a trial off therapy. This alternative approach will largely eliminate unnecessary treatment of infants with transient NHT, mostly caused by iodine deficiency or excess, and will reduce workload and costs by preventing unwarranted investigation and long-term follow-up.

The updated mouse universal genotyping array bioinformatic pipeline improves genetic QC in laboratory mice.

The MiniMUGA genotyping array is a popular tool for genetic quality control of laboratory mice and genotyping samples from most experimental crosses involving laboratory strains, particularly for reduced complexity crosses. The content of the production version of the MiniMUGA array is fixed; however, there is the opportunity to improve the array's performance and the associated report's usefulness by leveraging thousands of samples genotyped since the initial description of MiniMUGA. Here, we report our efforts to update and improve marker annotation, increase the number and the reliability of the consensus genotypes for classical inbred strains and substrains, and increase the number of constructs reliably detected with MiniMUGA. In addition, we have implemented key changes in the informatics pipeline to identify and quantify the contribution of specific genetic backgrounds to the makeup of a given sample, remove arbitrary thresholds, include the Y Chromosome and mitochondrial genome in the ideogram, and improve robust detection of the presence of commercially available substrains based on diagnostic alleles. Finally, we have updated the layout of the report to simplify the interpretation and completeness of the analysis and added a section summarizing the ideogram in table format. These changes will be of general interest to the mouse research community and will be instrumental in our goal of improving the rigor and reproducibility of mouse-based biomedical research.

Jacobian Spheroids, Shallow Encounters, and the Keyhole Map

The study of the dynamics of flybys is featured in several space-mission-related applications, spanning from the design of interplanetary orbits to the computation of impact probabilities with given celestial bodies in planetary protection and defense tasks. While patched-conics, two-body models suffice in accuracy for trajectory planning cases, collision probability assessment requires instead more insightful approaches. High-fidelity simulations have shown impact patterns to happen outside nominally colliding trajectories in terms of two-body analysis, all caused by distant or weak interactions between the given trajectory-celestial body pairs. This work proposes a novel concept of sphere of influence based on the Jacobian of the three-body dynamics, resulting in a wider definition of encounters that encompasses weak interactions up to an arbitrary threshold. The so-defined Jacobian spheroids are then used to construct the Keyhole map, a graphical tool that maps in the orbital elements space both nominal and off-nominal keyholes, i.e., collision paths accounting for three-body weak interactions. The proposed concepts arise from and are compared against the on-ground casualty risk assessment of the European Space Agency’s mission JUICE.

Comparison of data-driven thresholding methods using directed functional brain networks.

Over the past two centuries, intensive empirical research has been conducted on the human brain. As an electroencephalogram (EEG) records millisecond-to-millisecond changes in the electrical potentials of the brain, it has enormous potential for identifying useful information about neuronal transactions. The EEG data can be modelled as graphs by considering the electrode sites as nodes andthe linear and nonlinear statistical dependencies among them as edges (with weights). The graph theoretical modelling of EEG data results in functional brain networks (FBNs), which are fully connected (complete) weighted undirected/directed networks. Since various brain regions are interconnected via sparse anatomical connections, the weak links can be filtered out from the fullyconnected networks using a process called thresholding. Multiple researchers in the past decades proposed many thresholding methods to gather more insights about the influential neuronal connections of FBNs. This paper reviews various thresholding methods used in the literature for FBN analysis. The analysis showed that data-driven methods are unbiased since no arbitrary user-specified threshold is required. The efficacy of four data-driven thresholding methods, namely minimum spanning tree (MST), minimum connected component (MCC), union of shortest path trees (USPT), and orthogonal minimum spanning tree (OMST), in characterizing cognitive behavior of the normal human brain is analysed using directed FBNs constructed from EEG data of different cognitive load states. The experimental results indicate that both MCC and OMST thresholding methods can detect cognitive load-induced changes in the directed functional brain networks.

Adapting the percentage intensity method to assess accelerations and decelerations in football: moving beyond absolute and arbitrary thresholds.

We adapted the percentage intensity approach to monitor accelerations and decelerations allowing players' individualisation. Forty-two players were monitored during four microcycles via global navigation satellite system devices. Raw velocity and time data were collected to calculate acceleration and deceleration magnitudes according to specific starting speed intervals, and the efforts intensities were established as very low (<25% of the maximal effort), low (25-50%), moderate (50-75%) and high (>75%). Linear regressions and Pearson correlation (r) analysed the relationship between maximal efforts and starting speeds; additionally, mean paired differences compared efforts magnitudes between subsequent starting speed intervals. Most very low intensity accelerations (86%) and decelerations (79%) started from <5 km.h-1. Correlation between maximal efforts and starting speeds were r = -0.97 (p < .001) for acceleration, and r = -0.94 (p < .01) for deceleration. Maximal acceleration decreased as starting speed increases (very large effect sizes), but deceleration is less starting speed dependent (unclear to large effect sizes). This adaptation allows practitioners to individualise accelerations and decelerations classification during real-life scenarios, leading to a more precise training prescription. The very low intensity interval could be excluded to consider only relevant efforts. Maximal acceleration should be collected for each starting speed interval because accelerations are starting speed dependents.

Ordering molecular diversity in untargeted metabolomics via molecular community networking.

Nature's molecular diversity is not random but displays intricate organization stemming from biological necessity. Molecular networking connects metabolites with structural similarity, enabling molecular discoveries from mass spectrometry data using arbitrary similarity thresholds that can fracture natural metabolite families. We present molecular community networking (MCN), that optimizes connectivity for each metabolite, rescuing lost relationships and capturing otherwise "hidden" metabolite connections. Using MCN, we demonstrate the discovery of novel dipeptide-conjugated bile acids.

Portfolio default losses driven by idiosyncratic risks

We consider a portfolio of general defaultable assets with low individual default risk and study the probability of the portfolio default loss exceeding an arbitrary threshold. The latent variables driving defaults are modeled by a mixture structure that combines common shock, systematic risk, and idiosyncratic risk factors. While common shocks and systematic risk have been found by many studies to contribute significantly to portfolio losses, the role of idiosyncratic risks is often found to be negligible. Such conclusions are usually established under the assumption that the portfolio size tends to infinity and idiosyncratic risk factors are not dominant. We study under-investigated scenarios where the portfolio size is fixed and the idiosyncratic risk factors are heavy-tailed, exploring two distinct scenarios: an independence scenario and an asymptotic dependence scenario. The former is standard in the literature, while the latter is motivated by recent studies that have found the inadequacy of relying solely on common factors to capture default clustering. This consideration also reflects the possibility that idiosyncratic reasons can trigger contagion among firms with liabilities to each other. In the independence scenario, even with heavy-tailed idiosyncratic risk factors, the probability of a substantial portfolio loss remains low unless a single asset carries a disproportionately large weight. Conversely, in the asymptotic dependence scenario, the primary drivers of increased exceedance probability are the dependent idiosyncratic risk factors.

Metapresence: a tool for accurate species detection in metagenomics based on the genome-wide distribution of mapping reads.

Shotgun metagenomics allows comprehensive sampling of the genomic information of microbes in a given environment and is a tool of choice for studying complex microbial systems. Mapping sequencing reads against a set of reference or metagenome-assembled genomes is in principle a simple and powerful approach to define the species-level composition of the microbial community under investigation. However, despite the widespread use of this approach, there is no established way to properly interpret the alignment results, with arbitrary relative abundance thresholds being routinely used to discriminate between present and absent species. Such an approach can be affected by significant biases, especially in the identification of rare species. Therefore, it is important to develop new metrics to overcome these biases. Here, we present Metapresence, a new tool to perform reliable identification of the species in metagenomic samples based on the distribution of mapped reads on the reference genomes. The analysis is based on two metrics describing the breadth of coverage and the genomic distance between consecutive reads. We demonstrate the high precision and wide applicability of the tool using data from various synthetic communities, a real mock community, and the gut microbiome of healthy individuals and antibiotic-associated-diarrhea patients. Overall, our results suggest that the proposed approach has a robust performance in hard-to-analyze microbial communities containing contaminated or closely related genomes in low abundance.IMPORTANCEDespite the prevalent use of genome-centric alignment-based methods to characterize microbial community composition, there lacks a standardized approach for accurately identifying the species within a sample. Currently, arbitrary relative abundance thresholds are commonly employed for this purpose. However, due to the inherent complexity of genome structure and biases associated with genome-centric approaches, this practice tends to be imprecise. Notably, it introduces significant biases, particularly in the identification of rare species. The method presented here addresses these limitations and contributes significantly to overcoming inaccuracies in precisely defining community composition, especially when dealing with rare members.

P-397 A retrospective analysis shows a high effect in reproductive outcomes as age increases associated to endometrial factor in IVF advanced maternal age (AMA) patients

Abstract Study question Is there an increasing risk of a negative reproductive outcomes with every passing year associated with endometrial factor in AMA patients? Summary answer The risk of implantation failure and pregnancy loss associated with endometrial factor increase in 2.0% and 1.2% respectively with each passing year in AMA patients. What is known already Nowadays, there is a delay in maternity due to lifestyle, leading to a progressive increase in the age of women at the first childbirth increasing infertility. However, no universal definition of AMA has been established yet. Typically, studies are performed between different groups of age, establishing arbitrary thresholds. Besides, studies about AMA infertility mainly focus on the decline in oocyte quality, but the effects of age on the endometrium are often overlooked. Therefore, there is a lack of studies centered on endometrial factor and considering age year-by-year to be able to strictly establish when fertility decline starts and its magnitude. Study design, size, duration This retrospective study included a total of 33,735 single embryo transfers from 21,506 IVF AMA patients (&amp;gt;35 y.o, BMI 19-25 kg/m2) performed with high quality embryos (embryos from donated oocytes (donor &amp;lt;35 y.o) or euploid embryos from their own oocyte cohort) transferred in day 5 in an endometrial Hormonal Replacement Therapy (HRT) cycle. Evaluated transfers were performed between 2001 and 2022 in 19 clinics in Spain. This study was approved by an IRB (2203-FIVI-030-PD). Participants/materials, setting, methods A logistic regression analysis was performed, considering the patient’s age (42.93±3.45 y.o.) as a continuous and dependent variable and the reproductive outcome as an independent variable. The risk of obtaining a negative pregnancy outcome was estimated as risk ratios at a 95% confidence interval. A p-value&amp;lt;0.05 was considered as statistically significant. Reproductive rates (live birth and pregnancy loss) were calculated and compared each passing year in the studied range of ages (35-51 y.o). Main results and the role of chance The rates of live birth, Implantation failure and pregnancy loss associated to endometrial factor were affected as age increased in IVF AMA patients (&amp;gt;35 y.o). The implantation failure risk was increased in each passing year a 2% (Risk Ratio (RR) = 1.020 (1.003, 1.021) 95% confidence interval (95%CI), p-value=6.0E-09) and pregnancy loss risk was increased in each passing year a 1.2% (RR = 1.012, (1.003, 1.021) 95%CI, p-value=0.0096). Live birth rate decreased progressively from 42% observed in 35 y.o. to 32% in 50 y.o. Nevertheless, the pregnancy loss rate increased progressively from 29% in 35 y.o. to 37% in 50 y.o. Moreover, results shown a more drastic decrease of implantation failure rate after 42 years old and a pregnancy loss rate after 45 years old. Limitations, reasons for caution Only transfers from Spanish population under a HRT cycle were included, decreasing the results variability. However, the results could not be generalized to other hormonal cycles. Moreover, biochemical and clinical pregnancy loss could not be distinguished in this study considering pregnancy loss as a term that includes both of them. Wider implications of the findings To our knowledge, this is the first study in which the endometrial factor in AMA patients was analyzed year by year, helping to define in a more reliable way the ages at which the sharpest changes occur to improve clinical practices on endometrial implantation failure in AMA patients. Trial registration number Not applicable

Low-to-moderate alcohol consumption is associated with increased fibrosis in individuals with metabolic dysfunction-associated steatotic liver disease

Both metabolic dysfunction and alcohol consumption cause steatotic liver disease (SLD). The distinction between metabolic dysfunction-associated SLD (MASLD) and MetALD categories is based on arbitrary thresholds of alcohol intake. Thus, we assessed the impact of different levels of alcohol consumption on SLD severity and their interaction with metabolic comorbidities. We performed a population-based study with transient elastography (FibroScan®) data from participants in Spain (derivation cohort) and the US (validation cohort). A controlled attenuation parameter ≥275dB/m was used to define SLD. At least one cardiometabolic risk factor was required to define MASLD. Among patients with MASLD, low alcohol consumption was defined as an average of 5-9 drinks/week, moderate consumption as 10-13 drinks/week for females and 10-20 drinks/week for males, and increased alcohol intake (MetALD) as 14-35 drinks/week for females and 21-42 drinks/week for males. Significant fibrosis was defined as a liver stiffness measurement ≥8kPa and at-risk metabolic dysfunction-associated steatohepatitis (MASH) as a FAST score ≥0.35. The derivation cohort included 2,227 individuals with MASLD (9% reported low, 14% moderate alcohol consumption) and 76 cases with MetALD. Overall prevalences of significant fibrosis and at-risk MASH were 7.6% and 14.8%, respectively. In the multivariable analysis, alcohol consumption was independently associated with significant fibrosis and at-risk MASH. A dose-dependent increase in the prevalence of significant fibrosis and at-risk MASH was observed between the number of drinks/week and the number of cardiometabolic factors. The validation cohort included 1,732 participants with MASLD, of whom 17% had significant fibrosis and 13% at-risk MASH. This cohort validated the association between moderate intake and MASLD at risk of progression (odds ratio 1.69, 95% CI 1.06-2.71). Moderate alcohol intake is commonly seen in MASLD and increases the risk of advanced disease to a level similar to that observed in MetALD. Metabolic risk factors such as overweight, diabetes or dyslipidemia, and alcohol consumption can cause liver disease. These factors frequently coexist, but their joint effects on liver fibrosis remain uncertain. In this study, we have analyzed individuals from the general population with MASLD (metabolic dysfunction-associated steatotic liver disease) enrolled in Spain and the US. We show that moderate alcohol consumption has a supra-additive effect with metabolic risk factors, exponentially increasing the risk of liver fibrosis. These results suggest that there are no safe limits of daily alcohol intake in patients with unhealthy metabolic status and MASLD.

Global sensitivity analysis of ultrasonic testing simulations of slot-like defects with multifidelity modeling

Abstract In this paper, an efficient global sensitivity analysis (GSA) method for simulation-based ultrasonic testing (UT) of slot-like defects using multifidelity modeling with novel termination criterion is proposed. GSA quantifies the effect of quantities of interest with variability (e.g., position, height, and angle) on the output (e.g., amplitude). GSA with Sobol' indices requires the use of Monte Carlo simulations (MCS) when dealing with nonlinear problems having many parameters. It is impractical to perform GSA directly on high-fidelity physics-based models due to their long evaluation times and the large number of required samples. Multifidelity methods construct surrogate models based on data from an accurate high-fidelity model (HFM) and fast low-fidelity models (LFMs). The multifidelity surrogates evaluate quickly and can be used in lieu of the HFM to accelerate the GSA. Conventional multifidelity methods construct the surrogate to meet a prespecified error metric before using it within an analysis. This requires a separate set of testing data and an often arbitrary error metric threshold. To avoid these, a novel multifidelity modeling termination criterion for GSA is proposed that is based on the absolute relative change of the Sobol' indices. The proposed approach is demonstrated on a simulated UT case inspecting a slot-like defect with three uncertainty variables. The results show a potential for significant reduction in computational cost compared with conventional approaches.

Leveraging unsupervised machine learning to examine women's vulnerability to climate change

AbstractWe provide an application of machine learning to identify the distributional consequences of climate change in Malawi. We compare climate impact estimates based on drought indicators established objectively from the k‐means algorithm to more traditional measures. Young women affected by drought were 5 percentage points more likely to be married by 18 than those living in nondrought areas. Our approach generates robust results when varying the number of clusters and definition of treatment status. In some cases, we find the design using k‐means to define treatment is more likely to satisfy the assumptions underlying the difference‐in‐differences strategy than when using arbitrary thresholds. Projections from the estimates indicate future drought risk may lead to larger declines in labor productivity due to women's engagement in early age marriage than other factors affecting their participation rates. Under the extreme representative concentration pathway scenario, drought exposure encourages the exit of 3.3 million women workers by 2100.

A survey of experimental and computational identification of small proteins.

Small proteins (SPs) are typically characterized as eukaryotic proteins shorter than 100 amino acids and prokaryotic proteins shorter than 50 amino acids. Historically, they were disregarded because of the arbitrary size thresholds to define proteins. However, recent research has revealed the existence of many SPs and their crucial roles. Despite this, the identification of SPs and the elucidation of their functions are still in their infancy. To pave the way for future SP studies, we briefly introduce the limitations and advancements in experimental techniques for SP identification. We then provide an overview of available computational tools for SP identification, their constraints, and their evaluation. Additionally, we highlight existing resources for SP research. This survey aims to initiate further exploration into SPs and encourage the development of more sophisticated computational tools for SP identification in prokaryotes and microbiomes.

A new approach to quantify asymmetry in human movement

In this perspective paper, we propose a new approach to quantify the asymmetries in human movement. Before describing this approach, we delve into the asymmetry in human movement, often defined as the opposite of symmetry, and its implications for studying human movement. We critically examine the various methods available to quantify and describe bilateral differences, from arbitrary thresholds (such as the commonly employed 10–15% difference) to the measure of the smallest meaningful changes, and we stress the need for consideration of interindividual variability in the analysis. Our proposal centers on a straightforward metric, the probability of agreement, and a corresponding plot summarizing the agreement between measures from two limbs. Critically, the agreement between two limbs depends on the value of the clinically acceptable difference. The agreement will increase with larger values of clinically acceptable difference and decrease with smaller values of clinically acceptable difference. Data from various movements and conditions in athletes’ sports training and rehabilitation are used to illustrate this approach. Our perspective provides valuable insights into the nature of asymmetry in human movement, considering that a rational understanding of asymmetry in human movement requires a thoughtful approach encompassing both statistical and clinical significance. The data and codes employed in our research are openly accessible in the supplementary materials, enabling others in the field to replicate and build upon our findings.

Assessing the distribution of cancer stem cells in tumorspheres

Cancer Stem Cells presumably drive tumor growth and resistance to conventional cancer treatments. From a previous computational model, we inferred that these cells are not uniformly distributed in the bulk of a tumorsphere. To confirm this result, we cultivated tumorspheres enriched in stem cells, and performed immunofluorescent detection of the stemness marker SOX2 using confocal microscopy. In this article, we present an image processing method that reconstructs the amount and location of the Cancer Stem Cells in the spheroids. Its advantage is the use of a statistical criterion to classify the cells in Stem and Differentiated, instead of setting an arbitrary threshold. Moreover, the analysis of the experimental images presented in this work agrees with the results from our computational models, thus enforcing the notion that the distribution of Cancer Stem Cells in a tumorsphere is non-homogeneous. Additionally, the method presented here provides a useful tool for analyzing any image in which different kinds of cells are stained with different markers.

Adults in the room? The auditor and dividends in small firms: evidence from a natural experiment

We examine the effect of auditing on dividends in small private firms. We hypothesize that auditing can constrain dividends by way of promoting accounting conservatism. We use register data on private Norwegian firms and random variation induced by the introduction of a policy allowing small private firms to forgo the use of an auditor to estimate the effect of auditing on dividend payout. Identification is obtained by a regression discontinuity around the arbitrary thresholds for the policy. Propensity score matching is used to create a balanced synthetic control. We consistently find that forgoing auditing led to a significant increase in dividends in small private firms.

Mapping Single Nucleotide Polymorphism Markers Associated with the Pre-Flowering Morphological Performance of Fenugreek under Different Levels of Salt Stress

Salinity is a significant factor restricting plant growth and production. The effect of salinity stress on different growth parameters of 111 fenugreek genotypes was examined in an experiment with three salinity levels (0, 3000, 6000 mgL−1). A completely randomized block design with two replicated pots per treatment was used. Non-significant treatment effects were observed on fresh weight (FW); however, all traits showed significant genotype-by-treatment (GxT) interactions. This GxT was reflected in substantial SNP x environment interactions. Of 492 significant SNPs associated with the measured traits, 212 SNPs were linked to the correlated traits using an arbitrary threshold of three. Several SNPs were associated with FW and dry weight, measured under the same salinity treatment. The correlation between both traits was 0.98 under the three salinity treatments. In addition, 280 SNPs with conditional neutrality effects were mapped. The identified SNPs can be used in future marker-assisted breeding programs to select salt-tolerant genotypes. The results of this research shed light on the salt-tolerant properties of fenugreek.