Artificial intelligence to enhance clinical value across the spectrum of cardiovascular healthcare.

Artificial intelligence (AI) is increasingly being utilized in healthcare. This article provides clinicians and researchers with a step-wise foundation for high-value AI that can be applied to a variety of different data modalities. The aim is to improve the transparency and application of AI methods, with the potential to benefit patients in routine cardiovascular care. Following a clear research hypothesis, an AI-based workflow begins with data selection and pre-processing prior to analysis, with the type of data (structured, semi-structured, or unstructured) determining what type of pre-processing steps and machine-learning algorithms are required. Algorithmic and data validation should be performed to ensure the robustness of the chosen methodology, followed by an objective evaluation of performance. Seven case studies are provided to highlight the wide variety of data modalities and clinical questions that can benefit from modern AI techniques, with a focus on applying them to cardiovascular disease management. Despite the growing use of AI, further education for healthcare workers, researchers, and the public are needed to aid understanding of how AI works and to close the existing gap in knowledge. In addition, issues regarding data access, sharing, and security must be addressed to ensure full engagement by patients and the public. The application of AI within healthcare provides an opportunity for clinicians to deliver a more personalized approach to medical care by accounting for confounders, interactions, and the rising prevalence of multi-morbidity.

Prophylactic Mesh Placement During Formation of an End-colostomy: Long-term Randomized Controlled Trial on Effectiveness and Safety.

OBJECTIVE: The aim of this study was to determine if prophylactic mesh placement is an effective, safe, and cost-effective procedure to prevent parastomal hernia (PSH) formation in the long term. BACKGROUND: A PSH is the most frequent complication after stoma formation. Prophylactic placement of a mesh has been suggested to prevent PSH, but long-term evidence to support this approach is scarce. METHODS: In this multicentre superiority trial patients undergoing the formation of a permanent colostomy were randomly assigned to either retromuscular polypropylene mesh reinforcement or conventional colostomy formation. Primary endpoint was the incidence of a PSH after 5 years. Secondary endpoints were morbidity, mortality, quality of life, and cost-effectiveness. RESULTS: A total of 150 patients were randomly assigned to the mesh group (n = 72) or nonmesh group (n = 78). For the long-term follow-up, 113 patients were analyzed, and 37 patients were lost to follow-up. After a median follow-up of 60 months (interquartile range: 48.6-64.4), 49 patients developed a PSH, 20 (27.8%) in the mesh group and 29 (37.2%) in the nonmesh group ( P = 0.22; RD: -9.4%; 95% CI: -24, 5.5). The cost related to the meshing strategy was € 2.239 lower than the nonmesh strategy (95% CI: 491.18, 3985.49), and quality-adjusted life years did not differ significantly between groups ( P = 0.959; 95% CI: -0.066, 0.070). CONCLUSIONS: Prophylactic mesh placement during the formation of an end-colostomy is a safe procedure but does not reduce the incidence of PSH after 5 years of follow-up. It does, however, delay the onset of PSH without a significant difference in morbidity, mortality, or quality of life, and seems to be cost-effective.

Using the embryo-uterus statistical model to predict pregnancy chances by using cleavage stage morphokinetics and female age: two centre-specific prediction models and mutual validation.

BACKGROUND: The predictive capability of time-lapse monitoring (TLM) selection algorithms is influenced by patient characteristics, type and quality of data included in the analysis and the used statistical methods. Previous studies excluded DET cycles of which only one embryo implanted, introducing bias into the data. Therefore, we wanted to develop a TLM prediction model that is able to predict pregnancy chances after both single- and double embryo transfer (SET and DET). METHODS: This is a retrospective study of couples (n = 1770) undergoing an in vitro fertilization cycle at the Erasmus MC, University Medical Centre Rotterdam (clinic A) or the Reinier de Graaf Hospital (clinic B). This resulted in 2058 transferred embryos with time-lapse and pregnancy outcome information. For each dataset a prediction model was established by using the Embryo-Uterus statistical model with the number of gestational sacs as the outcome variable. This process was followed by cross-validation. RESULTS: Prediction model A (based on data of clinic A) included female age, t3-t2 and t5-t4, and model B (clinic B) included female age, t2, t3-t2 and t5-t4. Internal validation showed overfitting of model A (calibration slope 0.765 and area under the curve (AUC) 0.60), and minor overfitting of model B (slope 0.915 and AUC 0.65). External validation showed that model A was capable of predicting pregnancy in the dataset of clinic B with an AUC of 0.65 (95% CI: 0.61-0.69; slope 1.223, 95% CI: 0.903-1.561). Model B was less accurate in predicting pregnancy in the dataset of clinic A (AUC 0.60, 95% CI: 0.56-0.65; slope 0.671, 95% CI: 0.422-0.939). CONCLUSION: Our study demonstrates a novel approach to the development of a TLM prediction model by applying the EU statistical model. With further development and validation in clinical practice, our prediction model approach can aid in embryo selection and decision making for SET or DET.

Predicting pregnancy chances leading to term live birth in oligo/anovulatory women diagnosed with PCOS.

RESEARCH QUESTION: Which patient features predict the time to pregnancy (TTP) leading to term live birth in infertile women diagnosed with polycystic ovary syndrome (PCOS)? DESIGN: Prospective cohort follow-up study was completed, in which initial standardized phenotyping was conducted at two Dutch university medical centres from January 2004 to January 2014. Data were linked to the Netherlands Perinatal Registry to obtain pregnancy outcomes for each participant. All women underwent treatment according to a standardized protocol, starting with ovulation induction as first-line treatment. Predictors of pregnancies (leading to term live births) during the first year after PCOS diagnosis were evaluated. RESULTS: A total of 1779 consecutive women diagnosed with PCOS between January 2004 and January 2014 were included. In the first year following screening, 659 (37%) women with PCOS attained a pregnancy leading to term birth (≥37 weeks of gestational age). A higher chance of pregnancy was associated with race, smoking, body mass index (BMI), insulin, total testosterone and sex hormone-binding globulin (SHBG) concentrations (c-statistic = 0.59). CONCLUSIONS: Predictors of an increased chance of a live birth include White race, no current smoking, lower BMI, insulin and total testosterone concentrations, and higher SHBG concentrations. This study presents a nomogram to predict the chances of achieving a pregnancy (leading to a term live birth) within 1 year of treatment.

External validation of the Rotterdam prostate cancer risk calculator within a high-risk Dutch clinical cohort.

PURPOSE: This study aims to externally validate the Rotterdam Prostate Cancer Risk Calculator (RPCRC)-3/4 and RPCRC-MRI within a Dutch clinical cohort. METHODS: Men subjected to prostate biopsies, between 2018 and 2021, due to a clinical suspicion of prostate cancer (PCa) were retrospectively included. The performance of the RPCRC-3/4 and RPCRC-MRI was analyzed in terms of discrimination, calibration and net benefit. In addition, the need for recalibration and adjustment of risk thresholds for referral was investigated. Clinically significant (cs) PCa was defined as Gleason score ≥ 3 + 4. RESULTS: A total of 1575 men were included in the analysis. PCa was diagnosed in 63.2% (996/1575) of men and csPCa in 41.7% (656/1575) of men. Use of the RPCRC-3/4 could have prevented 37.3% (587/1575) of all MRIs within this cohort, thereby missing 18.3% (120/656) of csPCa diagnoses. After recalibration and adjustment of risk thresholds to 20% for PCa and 10% for csPCa, use of the recalibrated RPCRC-3/4 could have prevented 15.1% (238/1575) of all MRIs, resulting in 5.3% (35/656) of csPCa diagnoses being missed. The performance of the RPCRC-MRI was good; use of this risk calculator could have prevented 10.7% (169/1575) of all biopsies, resulting in 1.2% (8/656) of csPCa diagnoses being missed. CONCLUSION: The RPCRC-3/4 underestimates the probability of having csPCa within this Dutch clinical cohort, resulting in significant numbers of csPCa diagnoses being missed. For optimal performance of a risk calculator in a specific cohort, evaluation of its performance within the population under study is essential.

A standardized method to measure the membranous urethral length (MUL) on MRI of the prostate with high inter- and intra-observer agreement.

OBJECTIVES: The membranous urethral length (MUL), defined as the length between the apex and penile base as measured on preoperative prostate magnetic resonance imaging (MRI), is an important predictor for urinary incontinence after radical prostatectomy. Literature on inter- and intra - observer agreement of MUL measurement is limited. We studied the inter- and intra-observer agreement between radiologists using a well-defined method to measure the MUL on the prostate MRI. METHODS: Prostate cancer patients underwent a preoperative MRI and robot-assisted radical prostatectomy (RARP) at one high-volume RARP center. MUL measurement was based on well-defined landmarks on sagittal T2-weighted (anatomical) images. Three radiologists independently performed MUL measurements retrospectively in 106 patients blinded to themselves, to each other, and to clinical outcomes. The inter- and intra-observer agreement of MUL measurement between the radiologists were calculated, expressed as intra-class correlation coefficient (ICC). RESULTS: The initial inter-observer agreement was ICC 0.63; 95% confidence interval (CI) 0.28-0.81. Radiologist 3 measured the MUL mean 3.9 mm (SD 3.3) longer than the other readers, interpreting the caudal point of the MUL (penile base) differently. After discussion on the correct anatomical definition, radiologist 3 re-assessed all scans, which resulted in a high inter-observer agreement (ICC 0.84; 95% CI 0.66-0.91). After a subsequent reading by radiologists 1 and 2, the intra-observer agreements were ICC 0.93; 95% CI 0.89-0.96, and ICC 0.98; 95% CI 0.97-0.98, respectively. Limitation is the monocenter design. CONCLUSIONS: The MUL can be measured reliably with high agreement among radiologists. KEY POINTS: • After discussion on the correct anatomical definition, the inter- and intra - observer agreements of membranous urethral length (MUL) measurement on magnetic resonance imaging (MRI) were high. • A reproducible method to measure the MUL can improve the clinical usefulness of prediction models for urinary continence after RARP which may benefit patient counselling.

Multiallelic models for QTL mapping in diverse polyploid populations.

Quantitative trait locus (QTL) analysis allows to identify regions responsible for a trait and to associate alleles with their effect on phenotypes. When using biallelic markers to find these QTL regions, two alleles per QTL are modelled. This assumption might be close to reality in specific biparental crosses but is unrealistic in situations where broader genetic diversity is studied. Diversity panels used in genome-wide association studies or multi-parental populations can easily harbour multiple QTL alleles at each locus, more so in the case of polyploids that carry more than two alleles per individual. In such situations a multiallelic model would be closer to reality, allowing for different genetic effects for each potential allele in the population. To obtain such multiallelic markers we propose the usage of haplotypes, concatenations of nearby SNPs. We developed "mpQTL" an R package that can perform a QTL analysis at any ploidy level under biallelic and multiallelic models, depending on the marker type given. We tested the effect of genetic diversity on the power and accuracy difference between bi-allelic and multiallelic models using a set of simulated multiparental autotetraploid, outbreeding populations. Multiallelic models had higher detection power and were more precise than biallelic, SNP-based models, particularly when genetic diversity was higher. This confirms that moving to multi-allelic QTL models can lead to improved detection and characterization of QTLs. KEY MESSAGE: QTL detection in populations with more than two functional QTL alleles (which is likely in multiparental and/or polyploid populations) is more powerful when using multiallelic models, rather than biallelic models.

Exploring the alpha-gliadin locus: the 33-mer peptide with six overlapping coeliac disease epitopes in Triticum aestivum is derived from a subgroup of Aegilops tauschii.

Most alpha-gliadin genes of the Gli-D2 locus on the D genome of hexaploid bread wheat (Triticum aestivum) encode for proteins with epitopes that can trigger coeliac disease (CD), and several contain a 33-mer peptide with six partly overlapping copies of three epitopes, which is regarded as a remarkably potent T-cell stimulator. To increase genetic diversity in the D genome, synthetic hexaploid wheat lines are being made by hybridising accessions of Triticum turgidum (AB genome) and Aegilops tauschii (the progenitor of the D genome). The diversity of alpha-gliadins in A. tauschii has not been studied extensively. We analysed the alpha-gliadin transcriptome of 51 A. tauschii accessions representative of the diversity in A. tauschii. We extracted RNA from developing seeds and performed 454 amplicon sequencing of the first part of the alpha-gliadin genes. The expression profile of allelic variants of the alpha-gliadins was different between accessions, and also between accessions of the Western and Eastern clades of A. tauschii. Generally, both clades expressed many allelic variants not found in bread wheat. In contrast to earlier studies, we detected the 33-mer peptide in some A. tauschii accessions, indicating that it was introduced along with the D genome into bread wheat. In these accessions, transcripts with the 33-mer peptide were present at lower frequencies than in bread wheat varieties. In most A. tauschii accessions, however, the alpha-gliadins do not contain the epitope, and this may be exploited, through synthetic hexaploid wheats, to breed bread wheat varieties with fewer or no coeliac disease epitopes.

The Diagnostic Accuracy of Abdominal Computed Tomography in Diagnosing Internal Herniation Following Roux-en-Y Gastric Bypass Surgery: A Systematic Review and Meta-analysis.

OBJECTIVE: To analyze the diagnostic accuracy of abdominal computed tomography (CT) in diagnosing internal herniation (IH) following Rouxen-Y gastric bypass (RYGB) surgery. SUMMARY OF BACKGROUND DATA: IH is one of the most important and challenging complications following RYGB. Therefore, early and adequate diagnosis of IH is necessary. Currently, exploratory surgery is considered the gold standard in diagnosing IH. Although CT scans are frequently being used, the true diagnostic accuracy in diagnosing IH remains unclear. METHODS: PubMed, Embase, and Cochrane databases were systematically searched for relevant articles describing the diagnostic accuracy of abdominal CT in diagnosing IH after RYGB. Data were extracted, recalculated, and pooled to report on the overall diagnostic accuracy of CT in diagnosing IH, and the diagnostic accuracy of specific radiological signs. RESULTS: A total of 20 studies describing 1637 patients were included. seventeen studies provided data regarding the overall diagnostic accuracy: pooled sensitivity of 82.0%, specificity of 84.8%, positive predictive value of 82.7%, and negative predictive value of 85.8% were calculated. Eleven studies reported on specific CT signs and their diagnostic accuracy. The radiological signs with the highest sensitivity were the signs of venous congestion, swirl, and mesenteric oedema (sensitivity of 78.7%, 77.8%, and 67.2%, respectively). CONCLUSIONS: This meta-analysis demonstrates that CT is a reliable imaging modality for the detection of IH. Therefore, abdominal CT imaging should be added to the diagnostic work-up for RYGB patients who present themselves with abdominal pain suggestive of IH to improve patient selection for explorative surgery.

Forskolin-induced organoid swelling is associated with long-term cystic fibrosis disease progression.

RATIONALE: Cystic fibrosis (CF) is a monogenic life-shortening disease associated with highly variable individual disease progression which is difficult to predict. Here we assessed the association of forskolin-induced swelling (FIS) of patient-derived organoids with long-term CF disease progression in multiple organs and compared FIS with the golden standard biomarker sweat chloride concentration (SCC). METHODS: We retrieved 9-year longitudinal clinical data from the Dutch CF Registry of 173 people with mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. Individual CFTR function was defined by FIS, measured as the relative size increase of intestinal organoids after stimulation with 0.8 µM forskolin, quantified as area under the curve (AUC). We used linear mixed-effect models and multivariable logistic regression to estimate the association of FIS with long-term forced expiratory volume in 1 s % predicted (FEV1pp) decline and development of pancreatic insufficiency, CF-related liver disease and diabetes. Within these models, FIS was compared with SCC. RESULTS: FIS was strongly associated with longitudinal changes of lung function, with an estimated difference in annual FEV1pp decline of 0.32% (95% CI 0.11-0.54%; p=0.004) per 1000-point change in AUC. Moreover, increasing FIS levels were associated with lower odds of developing pancreatic insufficiency (adjusted OR 0.18, 95% CI 0.07-0.46; p<0.001), CF-related liver disease (adjusted OR 0.18, 95% CI 0.06-0.54; p=0.002) and diabetes (adjusted OR 0.34, 95% CI 0.12-0.97; p=0.044). These associations were absent for SCC. CONCLUSION: This study exemplifies the prognostic value of a patient-derived organoid-based biomarker within a clinical setting, which is especially important for people carrying rare CFTR mutations with unclear clinical consequences.

Total bodyweight and sex both drive pharmacokinetic variability of fluconazole in obese adults.

BACKGROUND: Fluconazole is commonly used to treat or prevent fungal infections. It is typically used orally but in critical situations, IV administration is needed. Obesity may influence the pharmacokinetics and therapeutic efficacy of a drug. In this study, we aim to assess the impact of obesity on fluconazole pharmacokinetics given orally or IV to guide dose adjustments for the obese population. METHODS: We performed a prospective pharmacokinetic study with intensive sampling in obese subjects undergoing bariatric surgery (n = 17, BMI ≥ 35 kg/m2) and non-obese healthy controls (n = 8, 18.5 ≤ BMI < 30.0 kg/m2). Participants received a semi-simultaneous oral dose of 400 mg fluconazole capsules, followed after 2 h by 400 mg IV. Population pharmacokinetic modelling and simulation were performed using NONMEM 7.3. RESULTS: A total of 421 fluconazole concentrations in 25 participants (total bodyweight 61.0-174 kg) until 48 h after dosing were obtained. An estimated bioavailability of 87.5% was found for both obese and non-obese subjects, with a 95% distribution interval of 43.9%-98.4%. With increasing total bodyweight, both higher CL and Vd were found. Sex also significantly impacted Vd, being 27% larger in male compared with female participants. CONCLUSIONS: In our population of obese but otherwise healthy individuals, obesity clearly alters the pharmacokinetics of fluconazole, which puts severely obese adults, particularly if male, at risk of suboptimal exposure, for which adjusted doses are proposed.

Detecting quantitative trait loci and exploring chromosomal pairing in autopolyploids using polyqtlR.

MOTIVATION: The investigation of quantitative trait loci (QTL) is an essential component in our understanding of how organisms vary phenotypically. However, many important crop species are polyploid (carrying more than two copies of each chromosome), requiring specialized tools for such analyses. Moreover, deciphering meiotic processes at higher ploidy levels is not straightforward, but is necessary to understand the reproductive dynamics of these species, or uncover potential barriers to their genetic improvement. RESULTS: Here, we present polyqtlR, a novel software tool to facilitate such analyses in (auto)polyploid crops. It performs QTL interval mapping in F1 populations of outcrossing polyploids of any ploidy level using identity-by-descent probabilities. The allelic composition of discovered QTL can be explored, enabling favourable alleles to be identified and tracked in the population. Visualization tools within the package facilitate this process, and options to include genetic co-factors and experimental factors are included. Detailed information on polyploid meiosis including prediction of multivalent pairing structures, detection of preferential chromosomal pairing and location of double reduction events can be performed. AVAILABILITYAND IMPLEMENTATION: polyqtlR is freely available from the Comprehensive R Archive Network (CRAN) at http://cran.r-project.org/package=polyqtlR. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Comparison of statistical methods for the analysis of recurrent adverse events in the presence of non-proportional hazards and unobserved heterogeneity: a simulation study.

BACKGROUND: In preventive drug trials such as intermittent preventive treatment for malaria prevention during pregnancy (IPTp), where there is repeated treatment administration, recurrence of adverse events (AEs) is expected. Challenges in modelling the risk of the AEs include accounting for time-to-AE and within-patient-correlation, beyond the conventional methods. The correlation comes from two sources; (a) individual patient unobserved heterogeneity (i.e. frailty) and (b) the dependence between AEs characterised by time-dependent treatment effects. Potential AE-dependence can be modelled via time-dependent treatment effects, event-specific baseline and event-specific random effect, while heterogeneity can be modelled via subject-specific random effect. Methods that can improve the estimation of both the unobserved heterogeneity and treatment effects can be useful in understanding the evolution of risk of AEs, especially in preventive trials where time-dependent treatment effect is expected. METHODS: Using both a simulation study and the Chloroquine for Malaria in Pregnancy (NCT01443130) trial data to demonstrate the application of the models, we investigated whether the lognormal shared frailty models with restricted cubic splines and non-proportional hazards (LSF-NPH) assumption can improve estimates for both frailty variance and treatment effect compared to the conventional inverse Gaussian shared frailty model with proportional hazard (ISF-PH), in the presence of time-dependent treatment effects and unobserved patient heterogeneity. We assessed the bias, precision gain and coverage probability of 95% confidence interval of the frailty variance estimates for the models under varying known unobserved heterogeneity, sample sizes and time-dependent effects. RESULTS: The ISF-PH model provided a better coverage probability of 95% confidence interval, less bias and less precise frailty variance estimates compared to the LSF-NPH models. The LSF-NPH models yielded unbiased hazard ratio estimates at the expense of imprecision and high mean square error compared to the ISF-PH model. CONCLUSION: The choice of the shared frailty model for the recurrent AEs analysis should be driven by the study objective. Using the LSF-NPH models is appropriate if unbiased hazard ratio estimation is of primary interest in the presence of time-dependent treatment effects. However, ISF-PH model is appropriate if unbiased frailty variance estimation is of primary interest. TRIAL REGISTRATION: ClinicalTrials.gov; NCT01443130.

Patient-reported outcomes during repetitive oxaliplatin-based pressurized intraperitoneal aerosol chemotherapy for isolated unresectable colorectal peritoneal metastases in a multicenter, single-arm, phase 2 trial (CRC-PIPAC).

BACKGROUND: CRC-PIPAC prospectively assessed repetitive oxaliplatin-based pressurized intraperitoneal aerosol chemotherapy (PIPAC-OX) as a palliative monotherapy (i.e., without concomitant systemic therapy in between subsequent procedures) for unresectable colorectal peritoneal metastases (CPM). The present study explored patient-reported outcomes (PROs) during trial treatment. METHODS: In this single-arm phase 2 trial in two tertiary centers, patients with isolated unresectable CPM received 6-weekly PIPAC-OX (92 mg/m2). PROs (calculated from EQ-5D-5L, and EORTC QLQ-C30 and QLQ-CR29) were compared between baseline and 1 and 4 weeks after the first three procedures using linear mixed modeling with determination of clinical relevance (Cohen's D ≥ 0.50) of statistically significant differences. RESULTS: Twenty patients underwent 59 procedures (median 3 [range 1-6]). Several PROs solely worsened 1 week after the first procedure (index value - 0.10, p < 0.001; physical functioning - 20, p < 0.001; role functioning - 27, p < 0.001; social functioning - 18, p < 0.001; C30 summary score - 16, p < 0.001; appetite loss + 15, p = 0.007; diarrhea + 15, p = 0.002; urinary frequency + 13, p = 0.004; flatulence + 13, p = 0.001). These PROs returned to baseline at subsequent time points. Other PROs worsened 1 week after the first procedure (fatigue + 23, p < 0.001; pain + 29, p < 0.001; abdominal pain + 32, p < 0.001), second procedure (fatigue + 20, p < 0.001; pain + 21, p < 0.001; abdominal pain + 20, p = 0.002), and third procedure (pain + 22, p < 0.001; abdominal pain + 22, p = 0.002). Except for appetite loss, all changes were clinically relevant. All analyzed PROs returned to baseline 4 weeks after the third procedure. CONCLUSIONS: Patients receiving repetitive PIPAC-OX monotherapy for unresectable CPM had clinically relevant but reversible worsening of several PROs, mainly 1 week after the first procedure. TRIAL REGISTRATION: Clinicaltrials.gov: NCT03246321; Netherlands trial register: NL6426.

Detection of ploidy and chromosomal aberrations in commercial oil palm using high-throughput SNP markers.

MAIN CONCLUSION: Karyotyping using high-density genome-wide SNP markers identified various chromosomal aberrations in oil palm (Elaeis guineensis Jacq.) with supporting evidence from the 2C DNA content measurements (determined using FCM) and chromosome counts. Oil palm produces a quarter of the world's total vegetable oil. In line with its global importance, an initiative to sequence the oil palm genome was carried out successfully, producing huge amounts of sequence information, allowing SNP discovery. High-capacity SNP genotyping platforms have been widely used for marker-trait association studies in oil palm. Besides genotyping, a SNP array is also an attractive tool for understanding aberrations in chromosome inheritance. Exploiting this, the present study utilized chromosome-wide SNP allelic distributions to determine the ploidy composition of over 1,000 oil palms from a commercial F1 family, including 197 derived from twin-embryo seeds. Our method consisted of an inspection of the allelic intensity ratio using SNP markers. For palms with a shifted or abnormal distribution ratio, the SNP allelic frequencies were plotted along the pseudo-chromosomes. This method proved to be efficient in identifying whole genome duplication (triploids) and aneuploidy. We also detected several loss of heterozygosity regions which may indicate small chromosomal deletions and/or inheritance of identical by descent regions from both parents. The SNP analysis was validated by flow cytometry and chromosome counts. The triploids were all derived from twin-embryo seeds. This is the first report on the efficiency and reliability of SNP array data for karyotyping oil palm chromosomes, as an alternative to the conventional cytogenetic technique. Information on the ploidy composition and chromosomal structural variation can help to better understand the genetic makeup of samples and lead to a more robust interpretation of the genomic data in marker-trait association analyses.

Pressurized Intraperitoneal Aerosol Chemotherapy (Oxaliplatin) for Unresectable Colorectal Peritoneal Metastases: A Multicenter, Single-Arm, Phase II Trial (CRC-PIPAC).

BACKGROUND: Despite its increasing use, pressurized intraperitoneal aerosol chemotherapy with oxaliplatin (PIPAC-OX) has never been prospectively investigated as a palliative monotherapy for colorectal peritoneal metastases in clinical trials. This trial aimed to assess the safety (primary aim) and antitumor activity (key secondary aim) of PIPAC-OX monotherapy in patients with unresectable colorectal peritoneal metastases. METHODS: In this two-center, single-arm, phase II trial, patients with isolated unresectable colorectal peritoneal metastases in any line of palliative treatment underwent 6-weekly PIPAC-OX (92 mg/m2). Key outcomes were major treatment-related adverse events (primary outcome), minor treatment-related adverse events, hospital stay, tumor response (radiological, biochemical, pathological, ascites), progression-free survival, and overall survival. RESULTS: Twenty enrolled patients underwent 59 (median 3, range 1-6) PIPAC-OX procedures. Major treatment-related adverse events occurred in 3 of 20 (15%) patients after 5 of 59 (8%) procedures (abdominal pain, intraperitoneal hemorrhage, iatrogenic pneumothorax, transient liver toxicity), including one possibly treatment-related death (sepsis of unknown origin). Minor treatment-related adverse events occurred in all patients after 57 of 59 (97%) procedures, the most common being abdominal pain (all patients after 88% of procedures) and nausea (65% of patients after 39% of procedures). Median hospital stay was 1 day (range 0-3). Response rates were 0% (radiological), 50% (biochemical), 56% (pathological), and 56% (ascites). Median progression-free and overall survival were 3.5 months (interquartile range [IQR] 2.5-5.7) and 8.0 months (IQR 6.3-12.6), respectively. CONCLUSIONS: In patients with unresectable colorectal peritoneal metastases undergoing PIPAC-OX monotherapy, some major adverse events occurred and minor adverse events were common. The clinical relevance of observed biochemical, pathological, and ascites responses remains to be determined, especially since radiological response was absent.

Using probabilistic genotypes in linkage analysis of polyploids.

KEY MESSAGE: In polyploids, linkage mapping is carried out using genotyping with discrete dosage scores. Here, we use probabilistic genotypes and we validate it for the construction of polyploid linkage maps. Marker genotypes are generally called as discrete values: homozygous versus heterozygous in the case of diploids, or an integer allele dosage in the case of polyploids. Software for linkage map construction and/or QTL analysis usually relies on such discrete genotypes. However, it may not always be possible, or desirable, to assign definite values to genotype observations in the presence of uncertainty in the genotype calling. Here, we present an approach that uses probabilistic marker dosages for linkage map construction in polyploids. We compare our method to an approach based on discrete dosages, using simulated SNP array and sequence reads data with varying levels of data quality. We validate our approach using experimental data from a potato (Solanum tuberosum L.) SNP array applied to an F1 mapping population. In comparison to the approach based on discrete dosages, we mapped an additional 562 markers. All but three of these were mapped to the expected chromosome and marker position. For the remaining three markers, no physical position was known. The use of dosage probabilities is of particular relevance for map construction in polyploids using sequencing data, as these often result in a higher level of uncertainty regarding allele dosage.

Analysis of allelic variants of RhMLO genes in rose and functional studies on susceptibility to powdery mildew related to clade V homologs.

KEY MESSAGE: Rose has 19 MLO genes. Of these, RhMLO1 and RhMLO2 were shown to be required for powdery mildew infection, which suggests their potential as susceptibility targets towards disease resistance. Powdery mildew, caused by Podosphaera pannosa, is one of the most serious and widespread fungal diseases for roses, especially in greenhouse-grown cut roses. It has been shown that certain MLO genes are involved in powdery mildew susceptibility and that loss of function in these genes in various crops leads to broad-spectrum, long-lasting resistance against this fungal disease. For this reason, these MLO genes are called susceptibility genes. We carried out a genome-wide identification of the MLO gene family in the Rosa chinensis genome, and screened for allelic variants among 22 accessions from seven different Rosa species using re-sequencing and transcriptome data. We identified 19 MLO genes in rose, of which four are candidate genes for functional homologs in clade V, which is the clade containing all dicot MLO susceptibility genes. We detected a total of 198 different allelic variants in the set of Rosa species and accessions, corresponding to 5-15 different alleles for each of the genes. Some diploid Rosa species shared alleles with tetraploid rose cultivars, consistent with the notion that diploid species have contributed to the formation of tetraploid roses. Among the four RhMLO genes in clade V, we demonstrated using expression study, virus-induced gene silencing as well as transient RNAi silencing that two of them, RhMLO1 and RhMLO2, are required for infection by P. pannosa and suggest their potential as susceptibility targets for powdery mildew resistance breeding in rose.

Genome editing of polyploid crops: prospects, achievements and bottlenecks.

Plant breeding aims to develop improved crop varieties. Many crops have a polyploid and often highly heterozygous genome, which may make breeding of polyploid crops a real challenge. The efficiency of traditional breeding based on crossing and selection has been improved by using marker-assisted selection (MAS), and MAS is also being applied in polyploid crops, which helps e.g. for introgression breeding. However, methods such as random mutation breeding are difficult to apply in polyploid crops because there are multiple homoeologous copies (alleles) of each gene. Genome editing technology has revolutionized mutagenesis as it enables precisely selecting targets. The genome editing tool CRISPR/Cas is especially valuable for targeted mutagenesis in polyploids, as all alleles and/or copies of a gene can be targeted at once. Even multiple genes, each with multiple alleles, may be targeted simultaneously. In addition to targeted mutagenesis, targeted replacement of undesirable alleles by desired ones may become a promising application of genome editing for the improvement of polyploid crops, in the near future. Several examples of the application of genome editing for targeted mutagenesis are described here for a range of polyploid crops, and achievements and bottlenecks are highlighted.

Developing more generalizable prediction models from pooled studies and large clustered data sets.

Prediction models often yield inaccurate predictions for new individuals. Large data sets from pooled studies or electronic healthcare records may alleviate this with an increased sample size and variability in sample characteristics. However, existing strategies for prediction model development generally do not account for heterogeneity in predictor-outcome associations between different settings and populations. This limits the generalizability of developed models (even from large, combined, clustered data sets) and necessitates local revisions. We aim to develop methodology for producing prediction models that require less tailoring to different settings and populations. We adopt internal-external cross-validation to assess and reduce heterogeneity in models' predictive performance during the development. We propose a predictor selection algorithm that optimizes the (weighted) average performance while minimizing its variability across the hold-out clusters (or studies). Predictors are added iteratively until the estimated generalizability is optimized. We illustrate this by developing a model for predicting the risk of atrial fibrillation and updating an existing one for diagnosing deep vein thrombosis, using individual participant data from 20 cohorts (N = 10 873) and 11 diagnostic studies (N = 10 014), respectively. Meta-analysis of calibration and discrimination performance in each hold-out cluster shows that trade-offs between average and heterogeneity of performance occurred. Our methodology enables the assessment of heterogeneity of prediction model performance during model development in multiple or clustered data sets, thereby informing researchers on predictor selection to improve the generalizability to different settings and populations, and reduce the need for model tailoring. Our methodology has been implemented in the R package metamisc.