A Research Agenda for Hybrid Intelligence:Augmenting Human Intellect With Collaborative, Adaptive, Responsible, and Explainable Artificial Intelligence

We define hybrid intelligence (HI) as the combination of human and machine intelligence, augmenting human intellect and capabilities instead of replacing them and achieving goals that were unreachable by either humans or machines. HI is an important new research focus for artificial intelligence, and we set a research agenda for HI by formulating four challenges

Outcome of Colorectal Cancer Patients Treated with Combination Bevacizumab Therapy: A Pooled Retrospective Analysis of Three European Cohorts from the Angiopredict Initiative

Background/Aims: This study is aimed at analyzing the survival rates and prognostic factors of stage IV colorectal cancer patients from 3 European cohorts undergoing combination chemotherapy with bevacizumab. Methods: Progression free-survival (PFS) and overall survival (OS) were analyzed in 172 patients using the Kaplan–Meier method and uni- and multivariable Cox proportional hazards regression models. Results: The median PFS was 9.7 and the median OS 27.4 months. Patients treated at centers in Germany (n = 97), Ireland (n = 32), and The Netherlands (n = 43) showed a median PFS of 9.9, 9.2, and 9.7 months, OS of 34.0, 20.5, and 25.1 months, respectively. Patients >65 years had a significantly shorter PFS (9.5 vs. 9.8 months) but not OS (27.4 vs. 27.5 months) than younger patients. High tumor grade (G3/4) was associated with a shorter PFS, T4 classification with both shorter PFS and OS. Fluoropyrimidine (FP) chemotherapy backbones (doublets and single) had comparable outcomes, while patients not receiving FP backbones had a shorter PFS. In multivariable analysis, age and non-FP backbone were associated with inferior PFS, T4 classification and therapy line >2nd were significantly associated with poor PFS and OS. Conclusion: The observed survival rates confirm previous studies and demonstrate reproducible benefits of combination bevacizumab regimens. Classification T4, non-FP chemotherapy backbone, and age >65 were associated with inferior outcome

Combination of a six microRNA expression profile with four clinicopathological factors for response prediction of systemic treatment in patients with advanced colorectal cancer

Background First line chemotherapy is effective in 75 to 80% of patients with metastatic colorectal cancer (mCRC). We studied whether microRNA (miR) expression profiles can predict treatment outcome for first line fluoropyrimidine containing systemic therapy in patients with mCRC. Methods MiR expression levels were determined by next generation sequencing from snap frozen tumor samples of 88 patients with mCRC. Predictive miRs were selected with penalized logistic regression and posterior forward selection. The prediction co-efficients of the miRs were re-estimated and validated by real-time quantitative PCR in an independent cohort of 81 patients with mCRC. Results Expression levels of miR-17-5p, miR-20a-5p, miR-30a-5p, miR-92a-3p, miR-92b-3p and miR-98-5p in combination with age, tumor differentiation, adjuvant therapy and type of systemic treatment, were predictive for clinical benefit in the training cohort with an AUC of 0.78. In the validation cohort the addition of the six miR signature to the four clinicopathological factors demonstrated a significant increased AUC for predicting treatment response versus those with stable disease (SD) from 0.79 to 0.90. The increase for predicting treatment response versus progressive disease (PD) and for patients with SD versus those with PD was not significant. in the validation cohort. MiR-17-5p, miR-20a-5p and miR-92a-3p were significantly upregulated in patients with treatment response in both the training and validation cohorts. Conclusion A six miR exp

La industrialización posible de la vivienda latinoamericana

La industrialización posible de la vivienda latinoamerican

Skewed X-inactivation is common in the general female population

X-inactivation is a well-established dosage compensation mechanism ensuring that X-chromosomal genes are expressed at comparable levels in males and females. Skewed X-inactivation is often explained by negative selection of one of the alleles. We demonstrate that imbalanced expression of the paternal and maternal X-chromosomes is common in the general population and that the random nature of the X-inactivation mechanism can be sufficient to explain the imbalance. To this end, we analyzed blood-derived RNA and whole-genome sequencing data from 79 female children and their parents from the Genome of the Netherlands project. We calculated the median ratio of the paternal over total counts at all X-chromosomal heterozygous single-nucleotide variants with coverage ≥10. We identified two individuals where the same X-chromosome was inactivated in all cells. Imbalanced expression of the two X-chromosomes (ratios ≤0.35 or ≥0.65) was observed in nearly 50% of the population. The empirically observed skewing is explained by a theoretical model where X-inactivation takes place in an embryonic stage in which eight cells give rise to the hematopoietic compartment. Genes escaping X-inactivation are expressed from both alleles and therefore demonstrate less skewing than inactivated genes. Using this characteristic, we identified three novel escapee genes (SSR4, REPS2, and SEPT6), but did not find support for many previously reported escapee genes in blood. Our collective data suggest that skewed X-inactivation is common in the general population. This may contribute to manifestation of symptoms in carriers of recessive X-linked disorders. We recommend that X-inactivation results should not be used lightly in the interpretation of X-linked variants

Predictive and prognostic biomarkers for colorectal cancer patients

Colorectal cancer (CRC) is the second most frequent cause of cancer-related death worldwide. Detecting CRC in a premalignant or early stage can improve survival of patients. When the CRC is metastasized (mCRC) to other organs patients are offered systemic treatment to prolong survival. However, not all patients respond to the available treatment while they do suffer from treatment related toxicities. In this thesis we studied the effects of CRC screening programmes on incidence and mortality. In addition, we studied tumor genomics and clinicopathological factors for the prediction of response to systemic therapy in patients with mCRC. The first chapter of this thesis described the effects of CRC screening on incidence and survival of patients with CRC. It was expected that screening for CRC would result in the detection of 1600 additional stage I and II CRCs per year in the first few years after its introduction in The Netherlands. This increase in detected stage I and II resulted in a decrease in the proportion of CRCs diagnosed at stages III or IV from 47% to 20%. Studies described in the next chapters aimed to improve treatment of patients with mCRC and to reduce unnecessary treatment related toxicity by patient selection for systemic therapy. Patient selection can be done with predictive biomarkers based on tumor genomics. A large number of genomic tumor characteristics can be analysed. This high dimensional data makes statistics challenging, as corrections for multiple testing are crucial to avoid overoptimistic results. Moreover, stable estimation of parameters is crucial for determining reproducible biomarkers. In chapter 2 we described a method with multi-parameter shrinkage options to overcome these statistical challenges. In chapter 3 we demonstrated that the miRNA expression profiles of metastases closely resemble that of their corresponding primary CRCs (pCRC). Only 8 (0.5%) of the 1714 miRNAs were significantly different expressed between pCRC and their matched metastases. Based on these results, we expected that miRNA expression profiles of primary tumors and metastases may be of similar predictive value for predicting prognosis or treatment response for patients with mCRC. In chapter 4 we analysed the miRNA expression levels of metastasised colorectal tumors in addition to known predictive clinocopathological factors. This study demonstrated that expression levels of miR-17-5p, miR-20a-5p, miR-30a-5p, miR-92a-3p, miR-92b-3p and miR-98-5p in combination with age, tumor differentiation, adjuvant therapy and type of systemic treatment, were predictive for clinical benefit (response and stable disease (SD)) of first-line chemotherapy in the training cohort with an AUC of 0.78. In the validation cohort the addition of the six miRNA signature to the four clinicopathological factors demonstrated a significant increased AUC for predicting treatment response versus those with SD from 0.79 to 0.90. However, our six miRNA signature did not add predictive value to the four selected clinicopathological factors for separating patients with PD from those with SD or response. Besides miRNAs, other readouts of tumor genomics may be used to improve sensitivity and specificity. In chapter 5 we analysed tumor copy number aberrations, microsatellite instability and known cancer related mutations for their predictive value for treatment response. Based on baseline clinicopathological factors, response to first and second line treatment in patients with mCRC could be predicted with an AUC of 0.73 and 0.69 respectively. Unfortunately, these prediction characteristics could not be improved by the addition of mutation status and copy number aberrations. The addition of clinicopathological factors acquired during first line treatment significantly increased the performance to predict response to second line treatment (AUC of 0.75 (p = 0.04)). Again, this was not sufficient to guide treatment decisions

Developing effective and resilient human-agent teamwork using team design patterns

Human-agent teams exhibit emergent behavior at the team level, as a result of interactions between individuals within the team. This begs the question how to design artificial team members (agents) as adequate team players that contribute to the team processes advancing team performance, resilience and learning. This paper proposes the development of a library of Team Design Patterns as a way to make dynamic team behavior at the team and individual level more explicit. Team Design Patterns serve a dual purpose: (1) In the system development phase, designers can identify desirable team patterns for the creation of artificial team members. (2) During the operational phase, team design patterns can be used by artificial team members to drive and stimulate team development, and to adaptively mitigate problems that may arise. We describe a pattern language for specifying team design patterns, discuss their use, and illustrate the concept using representative human-agent teamwork applications

Control of an air pressure actuated disposable bioreactor for cultivating heart valves

Tissue-engineered heart valves, cultured from human stem cells, are a possible alternative for replacing failing aortic heart valves, where nowadays biological and mechanical heart valves are used. Growing and conditioning is done by mechanically stimulating the tissue in a bioreactor. The disposable injection molded bioreactor [24] uses flexible membranes and steering valves to mimic a physiological heart cycle. In this work, an air pressure actuation control system for this bioreactor is designed. One membrane is position controlled to achieve a desired flow through the heart valve, while another membrane controls the aortic pressure. A third actuator controls a steering valve used to impose a resistance on the flow back to the first membrane, in order to control the heart valve closing pressure. Due to the repetitive character of the setpoints, iterative learning controllers are implemented. A high position tracking performance is achieved and pressure setpoints are mimicked successfully, but the main focus is on preventing large pressure oscillations and other events that could be damaging for the tissue heart valve. The control system allows full adjustability of operating conditions needed for the growing, conditioning and testing phases