Rates of Adverse Events in Patients With Ulcerative Colitis Undergoing Colectomy During Treatment With Tofacitinib vs Biologics: A Multicenter Observational Study.

INTRODUCTION: Patients with ulcerative colitis (UC) receiving immunosuppressive drugs are at substantial risk of colectomy. We aimed to assess the risk of postoperative complications of tofacitinib exposure before colectomy in comparison with biologics. METHODS: A multicenter, retrospective, observational study was conducted in patients with UC who underwent total colectomy for medically refractory disease, exposed to tofacitinib or a biologic before surgery. Primary outcome was the occurrence of any complication within 30 (early) and 90 (late) days after surgery. Secondary outcomes were the occurrence of infections, sepsis, surgical site complications, venous thromboembolic events (VTE), hospital readmissions, and redo surgery within the same timepoints. RESULTS: Three hundred one patients (64 tofacitinib, 162 anti-tumor necrosis factor-α agents, 54 vedolizumab, and 21 ustekinumab) were included. No significant differences were reported in any outcome, except for a higher rate of early VTE with anti-tumor necrosis factor-α agents ( P = 0.047) and of late VTE with vedolizumab ( P = 0.03). In the multivariate analysis, drug class was not associated with a higher risk of any early and late complications. Urgent colectomy increased the risk of any early (odds ratio [OR] 1.92, 95% confidence interval [CI] 1.06-3.48) complications, early hospital readmission (OR 4.79, 95% CI 1.12-20.58), and early redo surgery (OR 7.49, 95% CI 1.17-47.85). A high steroid dose increased the risk of any early complications (OR 1.96, 95% CI 1.08-3.57), early surgical site complications (OR 2.03, 95% CI 1.01-4.09), and early redo surgery (OR 7.52, 95% CI 1.42-39.82). Laparoscopic surgery decreased the risk of any early complications (OR 0.54, 95% CI 0.29-1.00), early infections (OR 0.39, 95% CI 0.18-0.85), and late hospital readmissions (OR 0.34, 95% CI 0.12-1.00). DISCUSSION: Preoperative tofacitinib treatment demonstrated a postoperative safety profile comparable with biologics in patients with UC undergoing colectomy.

Using machine learning to combine genetic and environmental data for maize grain yield predictions across multi-environment trials.

KEY MESSAGE: Incorporating feature-engineered environmental data into machine learning-based genomic prediction models is an efficient approach to indirectly model genotype-by-environment interactions. Complementing phenotypic traits and molecular markers with high-dimensional data such as climate and soil information is becoming a common practice in breeding programs. This study explored new ways to combine non-genetic information in genomic prediction models using machine learning. Using the multi-environment trial data from the Genomes To Fields initiative, different models to predict maize grain yield were adjusted using various inputs: genetic, environmental, or a combination of both, either in an additive (genetic-and-environmental; G+E) or a multiplicative (genotype-by-environment interaction; GEI) manner. When including environmental data, the mean prediction accuracy of machine learning genomic prediction models increased up to 7% over the well-established Factor Analytic Multiplicative Mixed Model among the three cross-validation scenarios evaluated. Moreover, using the G+E model was more advantageous than the GEI model given the superior, or at least comparable, prediction accuracy, the lower usage of computational memory and time, and the flexibility of accounting for interactions by construction. Our results illustrate the flexibility provided by the ML framework, particularly with feature engineering. We show that the feature engineering stage offers a viable option for envirotyping and generates valuable information for machine learning-based genomic prediction models. Furthermore, we verified that the genotype-by-environment interactions may be considered using tree-based approaches without explicitly including interactions in the model. These findings support the growing interest in merging high-dimensional genotypic and environmental data into predictive modeling.

The Development of a Novel Nitrate Portable Measurement System Based on a UV Paired Diode-Photodiode.

Nitrates can cause severe ecological imbalances in aquatic ecosystems, with considerable consequences for human health. Therefore, monitoring this inorganic form of nitrogen is essential for any water quality management structure. This research was conducted to develop a novel Nitrate Portable Measurement System (NPMS) to monitor nitrate concentrations in water samples. NPMS is a reagent-free ultraviolet system developed using low-cost electronic components. Its operation principle is based on the Beer-Lambert law for measuring nitrate concentrations in water samples through light absorption in the spectral range of 295-315 nm. The system is equipped with a ready-to-use ultraviolet sensor, light emission diode (LED), op-amp, microcontroller, liquid crystal display, quartz cuvette, temperature sensor, and battery. All the components are assembled in a 3D-printed enclosure box, which allows a very compact self-contained equipment with high portability, enabling field and near-real-time measurements. The proposed methodology and the developed instrument were used to analyze multiple nitrate standard solutions. The performance was evaluated in comparison to the Nicolet Evolution 300, a classical UV-Vis spectrophotometer. The results demonstrate a strong correlation between the retrieved measurements by both instruments within the investigated spectral band and for concentrations above 5 mg NO3-/L.

Importance of genetic architecture in marker selection decisions for genomic prediction.

KEY MESSAGE: We demonstrate potential for improved multi-environment genomic prediction accuracy using structural variant markers. However, the degree of observed improvement is highly dependent on the genetic architecture of the trait. Breeders commonly use genetic markers to predict the performance of untested individuals as a way to improve the efficiency of breeding programs. These genomic prediction models have almost exclusively used single nucleotide polymorphisms (SNPs) as their source of genetic information, even though other types of markers exist, such as structural variants (SVs). Given that SVs are associated with environmental adaptation and not all of them are in linkage disequilibrium to SNPs, SVs have the potential to bring additional information to multi-environment prediction models that are not captured by SNPs alone. Here, we evaluated different marker types (SNPs and/or SVs) on prediction accuracy across a range of genetic architectures for simulated traits across multiple environments. Our results show that SVs can improve prediction accuracy, but it is highly dependent on the genetic architecture of the trait and the relative gain in accuracy is minimal. When SVs are the only causative variant type, 70% of the time SV predictors outperform SNP predictors. However, the improvement in accuracy in these instances is only 1.5% on average. Further simulations with predictors in varying degrees of LD with causative variants of different types (e.g., SNPs, SVs, SNPs and SVs) showed that prediction accuracy increased as linkage disequilibrium between causative variants and predictors increased regardless of the marker type. This study demonstrates that knowing the genetic architecture of a trait in deciding what markers to use in large-scale genomic prediction modeling in a breeding program is more important than what types of markers to use.

A Portable Measurement Device Based on Phenanthroline Complex for Iron Determination in Water.

In this work, a newly developed self-contained, portable, and compact iron measurement system (IMS) based on spectroscopy absorption for determination of Fe2+ in water is presented. One of the main goals of the IMS is to operate the device in the field as opposed to instruments commonly used exclusively in the laboratory. In addition, the system has been tuned to quantify iron concentrations in accordance with the values proposed by the regulations for human consumption. The instrument uses the phenanthroline standard method for iron determination in water samples. This device is equipped with an optical sensing system consisting of a light-emitting diode paired with a photodiode to measure absorption radiation through ferroin complex medium. To assess the sensor response, four series of Fe2+ standard samples were prepared with different iron concentrations in various water matrices. Furthermore, a new solid reagent prepared in-house was investigated, which is intended as a "ready-to-use" sample pre-treatment that optimizes work in the field. The IMS showed better analytical performance compared with the state-of-the-art instrument. The sensitivity of the instrument was found to be 2.5 µg Fe2+/L for the measurement range established by the regulations. The linear response of the photodiode was determined for concentrations between 25 and 1000 µg Fe2+/L, making this device suitable for assessing iron in water bodies.

Optical topometry and machine learning to rapidly phenotype stomatal patterning traits for maize QTL mapping.

Stomata are adjustable pores on leaf surfaces that regulate the tradeoff of CO2 uptake with water vapor loss, thus having critical roles in controlling photosynthetic carbon gain and plant water use. The lack of easy, rapid methods for phenotyping epidermal cell traits have limited discoveries about the genetic basis of stomatal patterning. A high-throughput epidermal cell phenotyping pipeline is presented here and used for quantitative trait loci (QTL) mapping in field-grown maize (Zea mays). The locations and sizes of stomatal complexes and pavement cells on images acquired by an optical topometer from mature leaves were automatically determined. Computer estimated stomatal complex density (SCD; R2 = 0.97) and stomatal complex area (SCA; R2 = 0.71) were strongly correlated with human measurements. Leaf gas exchange traits were genetically correlated with the dimensions and proportions of stomatal complexes (rg = 0.39-0.71) but did not correlate with SCD. Heritability of epidermal traits was moderate to high (h2 = 0.42-0.82) across two field seasons. Thirty-six QTL were consistently identified for a given trait in both years. Twenty-four clusters of overlapping QTL for multiple traits were identified, with univariate versus multivariate single marker analysis providing evidence consistent with pleiotropy in multiple cases. Putative orthologs of genes known to regulate stomatal patterning in Arabidopsis (Arabidopsis thaliana) were located within some, but not all, of these regions. This study demonstrates how discovery of the genetic basis for stomatal patterning can be accelerated in maize, a C4 model species where these processes are poorly understood.

Phenotyping stomatal closure by thermal imaging for GWAS and TWAS of water use efficiency-related genes.

Stomata allow CO2 uptake by leaves for photosynthetic assimilation at the cost of water vapor loss to the atmosphere. The opening and closing of stomata in response to fluctuations in light intensity regulate CO2 and water fluxes and are essential for maintaining water-use efficiency (WUE). However, a little is known about the genetic basis for natural variation in stomatal movement, especially in C4 crops. This is partly because the stomatal response to a change in light intensity is difficult to measure at the scale required for association studies. Here, we used high-throughput thermal imaging to bypass the phenotyping bottleneck and assess 10 traits describing stomatal conductance (gs) before, during and after a stepwise decrease in light intensity for a diversity panel of 659 sorghum (Sorghum bicolor) accessions. Results from thermal imaging significantly correlated with photosynthetic gas exchange measurements. gs traits varied substantially across the population and were moderately heritable (h2 up to 0.72). An integrated genome-wide and transcriptome-wide association study identified candidate genes putatively driving variation in stomatal conductance traits. Of the 239 unique candidate genes identified with the greatest confidence, 77 were putative orthologs of Arabidopsis (Arabidopsis thaliana) genes related to functions implicated in WUE, including stomatal opening/closing (24 genes), stomatal/epidermal cell development (35 genes), leaf/vasculature development (12 genes), or chlorophyll metabolism/photosynthesis (8 genes). These findings demonstrate an approach to finding genotype-to-phenotype relationships for a challenging trait as well as candidate genes for further investigation of the genetic basis of WUE in a model C4 grass for bioenergy, food, and forage production.

Machine learning-enabled phenotyping for GWAS and TWAS of WUE traits in 869 field-grown sorghum accessions.

Sorghum (Sorghum bicolor) is a model C4 crop made experimentally tractable by extensive genomic and genetic resources. Biomass sorghum is studied as a feedstock for biofuel and forage. Mechanistic modeling suggests that reducing stomatal conductance (gs) could improve sorghum intrinsic water use efficiency (iWUE) and biomass production. Phenotyping to discover genotype-to-phenotype associations remains a bottleneck in understanding the mechanistic basis for natural variation in gs and iWUE. This study addressed multiple methodological limitations. Optical tomography and a machine learning tool were combined to measure stomatal density (SD). This was combined with rapid measurements of leaf photosynthetic gas exchange and specific leaf area (SLA). These traits were the subject of genome-wide association study and transcriptome-wide association study across 869 field-grown biomass sorghum accessions. The ratio of intracellular to ambient CO2 was genetically correlated with SD, SLA, gs, and biomass production. Plasticity in SD and SLA was interrelated with each other and with productivity across wet and dry growing seasons. Moderate-to-high heritability of traits studied across the large mapping population validated associations between DNA sequence variation or RNA transcript abundance and trait variation. A total of 394 unique genes underpinning variation in WUE-related traits are described with higher confidence because they were identified in multiple independent tests. This list was enriched in genes whose Arabidopsis (Arabidopsis thaliana) putative orthologs have functions related to stomatal or leaf development and leaf gas exchange, as well as genes with nonsynonymous/missense variants. These advances in methodology and knowledge will facilitate improving C4 crop WUE.

Assessment of two statistical approaches for variance genome-wide association studies in plants.

Genomic loci that control the variance of agronomically important traits are increasingly important due to the profusion of unpredictable environments arising from climate change. The ability to identify such variance-controlling loci in association studies will be critical for future breeding efforts. Two statistical approaches that have already been used in the variance genome-wide association study (vGWAS) paradigm are the Brown-Forsythe test (BFT) and the double generalized linear model (DGLM). To ensure that these approaches are deployed as effectively as possible, it is critical to study the factors that influence their ability to identify variance-controlling loci. We used genome-wide marker data in maize (Zea mays L.) and Arabidopsis thaliana to simulate traits controlled by epistasis, genotype by environment (GxE) interactions, and variance quantitative trait nucleotides (vQTNs). We then quantified true and false positive detection rates of the BFT and DGLM across all simulated traits. We also conducted a vGWAS using both the BFT and DGLM on plant height in a maize diversity panel. The observed true positive detection rates at the maximum sample size considered (N = 2815) suggest that both of these vGWAS approaches are capable of identifying epistasis and GxE for sufficiently large sample sizes. We also noted that the DGLM decisively outperformed the BFT for simulated traits controlled by vQTNs at sample sizes of N = 500. Although we conclude that there are still certain aspects of vGWAS approaches that need further refinement, this study suggests that the BFT and DGLM are capable of identifying variance-controlling loci in current state-of-the-art plant or agronomic data sets.

Proactive infliximab is more effective than vedolizumab in inducing fecal calprotectin remission in inflammatory bowel disease.

BACKGROUND: Current evidence suggests vedolizumab (VDZ) may be as effective as Infliximab (IFX) in inflammatory bowel disease. It is unknown if proactive therapeutic drug monitoring (PTDM) of IFX may improve these results. METHODS: Case-control study including consecutive patients with primary response to conventional IFX (n = 70), proactive IFX (n = 148), and VDZ (n = 95). PTDM was performed at week 14 and every other infusion, aiming at a trough level between 5 and 10 µg/ml. The primary outcome was fecal calprotectin (Fc) remission (<250 µg/g) at 1 year of treatment. Secondary outcomes included Fc remission at week 14 (proactive IFX/VDZ), clinical remission, treatment discontinuation, hospitalization, and surgery at 1-year of follow-up. RESULTS: Proactive IFX was superior to conventional IFX and VDZ in inducing Fc remission at 1-year (69.4% vs 47.1% vs 37.9%, p = .003 and p < .001). Results remained significant in biologic naïve patients (70.8% vs 44.4% vs 51.4%, p = .001 and p = .043) but comparisons between conventional IFX and VDZ were not significant (p = .265 and p = .664). In multivariate analysis correcting for prior biologic exposure, proactive IFX was more effective than conventional IFX (OR 2.480 95%CI [1.367-4.499], p = .003) and VDZ (OR 3.467 95%CI [1.578-7.617], p = .002) in inducing Fc remission. Amongst secondary outcomes, only clinical remission was significant between proactive IFX and VDZ in the overall cohort (80.4% vs 55.8%, p < .001) and in biologic naïve patients (80.2% vs 62.9%, p = .043). Fc remission at 1-year was associated with better results in most secondary outcomes. CONCLUSION: Proactive IFX was superior to VDZ in inducing Fc remission at 1-year, which was associated with improved clinical outcomes.SUMMARYCurrent evidence suggests that vedolizumab may be as effective as Infliximab in the treatment of patients with inflammatory bowel disease.There have been no studies comparing vedolizumab with proactively optimized Infliximab based on trough levels.We confirm that conventional IFX is as effective as vedolizumab but proactive IFX appears superior to vedolizumab in inducing fecal calprotectin remission.Fecal calprotectin remission associates with better clinical outcomes.

Can improved canopy light transmission ameliorate loss of photosynthetic efficiency in the shade? An investigation of natural variation in Sorghum bicolor.

Previous studies have found that maximum quantum yield of CO2 assimilation (Φ CO2,max,app) declines in lower canopies of maize and miscanthus, a maladaptive response to self-shading. These observations were limited to single genotypes, leaving it unclear whether the maladaptive shade response is a general property of this C4 grass tribe, the Andropogoneae. We explored the generality of this maladaptation by testing the hypothesis that erect leaf forms (erectophiles), which allow more light into the lower canopy, suffer less of a decline in photosynthetic efficiency than drooping leaf (planophile) forms. On average, Φ CO2,max,app declined 27% in lower canopy leaves across 35 accessions, but the decline was over twice as great in planophiles than in erectophiles. The loss of photosynthetic efficiency involved a decoupling between electron transport and assimilation. This was not associated with increased bundle sheath leakage, based on 13C measurements. In both planophiles and erectophiles, shaded leaves had greater leaf absorptivity and lower activities of key C4 enzymes than sun leaves. The erectophile form is considered more productive because it allows a more effective distribution of light through the canopy to support photosynthesis. We show that in sorghum, it provides a second benefit, maintenance of higher Φ CO2,max,app to support efficient use of that light resource.

simplePHENOTYPES: SIMulation of pleiotropic, linked and epistatic phenotypes.

BACKGROUND: Advances in genotyping and phenotyping techniques have enabled the acquisition of a great amount of data. Consequently, there is an interest in multivariate statistical analyses that identify genomic regions likely to contain causal mutations affecting multiple traits (i.e., pleiotropy). As the demand for multivariate analyses increases, it is imperative that optimal tools are available to assess their performance. To facilitate the testing and validation of these multivariate approaches, we developed simplePHENOTYPES, an R/CRAN package that simulates pleiotropy, partial pleiotropy, and spurious pleiotropy in a wide range of genetic architectures, including additive, dominance and epistatic models. RESULTS: We illustrate simplePHENOTYPES' ability to simulate thousands of phenotypes in less than one minute. We then provide two vignettes illustrating how to simulate sets of correlated traits in simplePHENOTYPES. Finally, we demonstrate the use of results from simplePHENOTYPES in a standard GWAS software, as well as the equivalence of simulated phenotypes from simplePHENOTYPES and other packages with similar capabilities. CONCLUSIONS: simplePHENOTYPES is a R/CRAN package that makes it possible to simulate multiple traits controlled by loci with varying degrees of pleiotropy. Its ability to interface with both commonly-used marker data formats and downstream quantitative genetics software and packages should facilitate a rigorous assessment of both existing and emerging statistical GWAS and GS approaches. simplePHENOTYPES is also available at https://github.com/samuelbfernandes/simplePHENOTYPES .

Multi-Trait Genome-Wide Association Studies Reveal Loci Associated with Maize Inflorescence and Leaf Architecture.

Maize inflorescence is a complex phenotype that involves the physical and developmental interplay of multiple traits. Given the evidence that genes could pleiotropically contribute to several of these traits, we used publicly available maize data to assess the ability of multivariate genome-wide association study (GWAS) approaches to identify pleiotropic quantitative trait loci (pQTL). Our analysis of 23 publicly available inflorescence and leaf-related traits in a diversity panel of n = 281 maize lines genotyped with 376,336 markers revealed that the two multivariate GWAS approaches we tested were capable of identifying pQTL in genomic regions coinciding with similar associations found in previous studies. We then conducted a parallel simulation study on the same individuals, where it was shown that multivariate GWAS approaches yielded a higher true-positive quantitative trait nucleotide (QTN) detection rate than comparable univariate approaches for all evaluated simulation settings except for when the correlated simulated traits had a heritability of 0.9. We therefore conclude that the implementation of state-of-the-art multivariate GWAS approaches is a useful tool for dissecting pleiotropy and their more widespread implementation could facilitate the discovery of genes and other biological mechanisms underlying maize inflorescence.

Conserved defense responses between maize and sorghum to Exserohilum turcicum.

BACKGROUND: Exserohilum turcicum is an important pathogen of both sorghum and maize, causing sorghum leaf blight and northern corn leaf blight. Because the same pathogen can infect and cause major losses for two of the most important grain crops, it is an ideal pathosystem to study plant-pathogen evolution and investigate shared resistance mechanisms between the two plant species. To identify sorghum genes involved in the E. turcicum response, we conducted a genome-wide association study (GWAS). RESULTS: Using the sorghum conversion panel evaluated across three environments, we identified a total of 216 significant markers. Based on physical linkage with the significant markers, we detected a total of 113 unique candidate genes, some with known roles in plant defense. Also, we compared maize genes known to play a role in resistance to E. turcicum with the association mapping results and found evidence of genes conferring resistance in both crops, providing evidence of shared resistance between maize and sorghum. CONCLUSIONS: Using a genetics approach, we identified shared genetic regions conferring resistance to E. turcicum in both maize and sorghum. We identified several promising candidate genes for resistance to leaf blight in sorghum, including genes related to R-gene mediated resistance. We present significant advancements in the understanding of host resistance to E. turcicum, which is crucial to reduce losses due to this important pathogen.

Population Structure Analyses Provide Insight into the Source Populations Underlying Rural Isolated Communities in Illinois.

We have previously hypothesized that relatively small and isolated rural communities may experience founder effects, defined as the genetic ramifications of small population sizes at the time of a community's establishment. To explore this, we used an Illumina Infinium Omni2.5Exome-8 chip to collect data from 157 individuals from four Illinois communities, three rural and one urban. Genetic diversity estimates of 999,259 autosomal markers suggested that the reduction in heterozygosity due to shared ancestry was approximately 0, indicating a randomly mating population. An eigenanalysis, which is similar to a principal component analysis but run on a genetic coancestry matrix, conducted in the SNPRelate R package revealed that most of these individuals formed one cluster, with a few putative outliers obscuring population variation. An additional eigenanalysis on the same markers in a combined data set including the 2,504 individuals in the 1000 Genomes database found that most of the 157 Illinois individuals clustered into one group in close proximity to individuals of European descent. A final eigenanalysis of the Illinois individuals with the 503 individuals of European descent (within the 1000 Genomes Project) revealed two clusters of individuals and likely two source populations; one British and one consisting of multiple European subpopulations. We therefore demonstrate the feasibility of examining genetic relatedness across Illinois populations and assessing the number of source populations using publicly available databases. When assessed, population structure information can contribute to the understanding of genetic history in rural populations.

Treat to target in inflammatory bowel disease: a survey of treatment strategies amongst Portuguese doctors.

BACKGROUND: treatment goals in inflammatory bowel disease have changed over the last few years and have shifted from a mainly symptom-based management to objective endpoints, such as mucosal healing and deep remission. A treat-to-target strategy to achieve these goals has been proposed by several experts, although the real-life clinical data is still lacking. This study aimed to investigate the current practices among Portuguese gastroenterologists who treat inflammatory bowel disease patients. METHODS: Portuguese gastroenterologists were asked to participate in an anonymous online survey. The questions focused on opinions and current practice with regard to treatment targets in inflammatory bowel disease. RESULTS: sixty-two physicians agreed to participate in the survey, 40 were gastroenterology specialists and 22 (35.5%) were fellows. Deep remission was considered as the main treatment goal for Crohn's disease and ulcerative colitis by 82% and 83.9% of the participants, respectively. Mucosal healing as a treatment target was used by 95% and 80% of participants in ulcerative colitis and Crohn's disease, respectively; 71% intensified the treatment to achieve mucosal healing after clinical remission. The most common definition of mucosal healing in Crohn's disease and ulcerative colitis was the absence of mucosal ulceration (32.3%) and a Mayo endoscopic sub-score of 0 (41.9%). Only 3.2% escalated treatment with the aim to achieve histologic remission in ulcerative colitis. CONCLUSION: a treat-to-target strategy to achieve mucosal healing and deep remission is currently accepted by a substantial number of Portuguese gastroenterologists.

Efficiency of multi-trait, indirect, and trait-assisted genomic selection for improvement of biomass sorghum.

KEY MESSAGE: We compare genomic selection methods that use correlated traits to help predict biomass yield in sorghum, and find that trait-assisted genomic selection performs best. Genomic selection (GS) is usually performed on a single trait, but correlated traits can also help predict a focal trait through indirect or multi-trait GS. In this study, we use a pre-breeding population of biomass sorghum to compare strategies that use correlated traits to improve prediction of biomass yield, the focal trait. Correlated traits include moisture, plant height measured at monthly intervals between planting and harvest, and the area under the growth progress curve. In addition to single- and multi-trait direct and indirect GS, we test a new strategy called trait-assisted GS, in which correlated traits are used along with marker data in the validation population to predict a focal trait. Single-trait GS for biomass yield had a prediction accuracy of 0.40. Indirect GS performed best using area under the growth progress curve to predict biomass yield, with a prediction accuracy of 0.37, and did not differ from indirect multi-trait GS that also used moisture information. Multi-trait GS and single-trait GS yielded similar results, indicating that correlated traits did not improve prediction of biomass yield in a standard GS scenario. However, trait-assisted GS increased prediction accuracy by up to [Formula: see text] when using plant height in both the training and validation populations to help predict yield in the validation population. Coincidence between selected genotypes in phenotypic and genomic selection was also highest in trait-assisted GS. Overall, these results suggest that trait-assisted GS can be an efficient strategy when correlated traits are obtained earlier or more inexpensively than a focal trait.

An unusual cause of Boerhaave´s syndrome in a young patient.

An 18-year-old male patient with a history of atopy and intermittent dysphagia for solids, presented to the emergency department with sudden onset total dysphagia followed by hematemesis, after ingesting an ibuprofen tablet. Urgent upper gastrointestinal endoscopy revealed a deep laceration just above the tablet impacted in the distal esophagus. Abdominal CT-scan confirmed the suspicion of an esophageal perforation. The impacted tablet was broken up with biopsy forceps, and a covered metallic stent (Hanarostent® 60/100x20/26mm) was placed across the cardia effectively excluding the fistula. Recovery was uneventful and the stent was easily removed 6 weeks later. Follow-up biopsies showed marked mucosal infiltration by eosinophils confirming the diagnosis of eosinophilic esophagitis (EE). The patient was treated with oral budesonide and remains asymptomatic.

Intrahepatic clear cell cholangiocarcinoma - An uncommon histologic subtype: case report and literature review.

Clear-cell cholangiocarcinoma is a very uncommon variant of cholangiocarcinoma with a largely unknown natural history and prognosis. We report a case of a 51-year-old previously healthy woman presenting with a large liver nodule found on routine imaging. Needle biopsy of the lesion suggested a non-hepatocellular carcinoma. After extensive workup for other primary neoplasms, the patient underwent a partial hepatectomy. Histopathology was compatible with a moderately differentiated clear-cell cholangiocarcinoma. There was no evidence of liver disease in the remaining tissue. The patient underwent chemotherapy and remains in clinical remission after two years.

Acute cholangitis in an old patient with Crigler-Najjar syndrome type II - a case report.

BACKGROUND: Crigler-Najjar syndrome (CN) is a very rare genetic disorder characterized by an inability to conjugate bilirubin. Contrary to CN type I, patients with CN II exhibit residual capacity to conjugate bilirubin and may present a normal life expectancy. CASE PRESENTATION: We report an unusual late diagnosis of CN type II in an 80-year-old female admitted with severe acute cholangitis. While the patient present typical clinical and radiologic signs of bile duct obstruction and cholangitis, her blood analysis showed severe unconjugated hyperbilirubinemia. Endoscopic retrograde cholangiopancreatography confirmed the diagnosis and allowed therapeutic intervention. The anatomopathologic examination of her gallbladder following cholecystectomy showed signs of chronic cholecystitis. CONCLUSION: The risk of gallstone disease may be increased in patients with CN syndrome. While unusual, we alert to this curious and potential life-threatening presentation.