Cryosectioning the intestinal crypt-villus axis: An ex vivo method to study the dynamics of epigenetic modifications from stem cells to differentiated cells

AbstractThe intestinal epithelium is a particularly attractive biological adult model to study epigenetic mechanisms driving adult stem cell renewal and cell differentiation. Since epigenetic modifications are dynamic, we have developed an original ex vivo approach to study the expression and epigenetic profiles of key genes associated with either intestinal cell pluripotency or differentiation by isolating cryosections of the intestinal crypt-villus axis. Gene expression, DNA methylation and histone modifications were studied by qRT-PCR, methylation-specific PCR and micro-chromatin immunoprecipitation, respectively. Using this approach, it was possible to identify segment-specific methylation and chromatin profiles. We show that (i) expression of intestinal stem cell markers (Lgr5, Ascl2) exclusively in the crypt is associated with active histone marks, (ii) promoters of all pluripotency genes studied and transcription factors involved in intestinal cell fate (Cdx2) harbour a bivalent chromatin pattern in the crypts and (iii) expression of differentiation markers (Muc2, Sox9) along the crypt-villus axis is associated with DNA methylation. Hence, using an original model of cryosectioning along the crypt-villus axis that allows in situ detection of dynamic epigenetic modifications, we demonstrate that regulation of pluripotency and differentiation markers in healthy intestinal mucosa involves different and specific epigenetic mechanisms

Partially Detected Intelligent Traffic Signal Control: Environmental Adaptation

Partially Detected Intelligent Traffic Signal Control (PD-ITSC) systems that can optimize traffic signals based on limited detected information could be a cost-efficient solution for mitigating traffic congestion in the future. In this paper, we focus on a particular problem in PD-ITSC - adaptation to changing environments. To this end, we investigate different reinforcement learning algorithms, including Q-learning, Proximal Policy Optimization (PPO), Advantage Actor-Critic (A2C), and Actor-Critic with Kronecker-Factored Trust Region (ACKTR). Our findings suggest that RL algorithms can find optimal strategies under partial vehicle detection; however, policy-based algorithms can adapt to changing environments more efficiently than value-based algorithms. We use these findings to draw conclusions about the value of different models for PD-ITSC systems.Comment: Accepted by ICMLA 201

A vision transformer-based framework for knowledge transfer from multi-modal to mono-modal lymphoma subtyping models

Determining lymphoma subtypes is a crucial step for better patients treatment targeting to potentially increase their survival chances. In this context, the existing gold standard diagnosis method, which is based on gene expression technology, is highly expensive and time-consuming making difficult its accessibility. Although alternative diagnosis methods based on IHC (immunohistochemistry) technologies exist (recommended by the WHO), they still suffer from similar limitations and are less accurate. WSI (Whole Slide Image) analysis by deep learning models showed promising new directions for cancer diagnosis that would be cheaper and faster than existing alternative methods. In this work, we propose a vision transformer-based framework for distinguishing DLBCL (Diffuse Large B-Cell Lymphoma) cancer subtypes from high-resolution WSIs. To this end, we propose a multi-modal architecture to train a classifier model from various WSI modalities. We then exploit this model through a knowledge distillation mechanism for efficiently driving the learning of a mono-modal classifier. Our experimental study conducted on a dataset of 157 patients shows the promising performance of our mono-modal classification model, outperforming six recent methods from the state-of-the-art dedicated for cancer classification. Moreover, the power-law curve, estimated on our experimental data, shows that our classification model requires a reasonable number of additional patients for its training to potentially reach identical diagnosis accuracy as IHC technologies

Does taking endurance into account improve the prediction of weaning outcome in mechanically ventilated children?

INTRODUCTION: We conducted the present study to determine whether a combination of the mechanical ventilation weaning predictors proposed by the collective Task Force of the American College of Chest Physicians (TF) and weaning endurance indices enhance prediction of weaning success. METHOD: Conducted in a tertiary paediatric intensive care unit at a university hospital, this prospective study included 54 children receiving mechanical ventilation (≥6 hours) who underwent 57 episodes of weaning. We calculated the indices proposed by the TF (spontaneous respiratory rate, paediatric rapid shallow breathing, rapid shallow breathing occlusion pressure [ROP] and maximal inspiratory pressure during an occlusion test [Pi(max)]) and weaning endurance indices (pressure-time index, tension-time index obtained from P(0.1 )[TTI(1)] and from airway pressure [TTI(2)]) during spontaneous breathing. Performances of each TF index and combinations of them were calculated, and the best single index and combination were identified. Weaning endurance parameters (TTI(1 )and TTI(2)) were calculated and the best index was determined using a logistic regression model. Regression coefficients were estimated using the maximum likelihood ratio (LR) method. Hosmer–Lemeshow test was used to estimate goodness-of-fit of the model. An equation was constructed to predict weaning success. Finally, we calculated the performances of combinations of best TF indices and best endurance index. RESULTS: The best single TF index was ROP, the best TF combination was represented by the expression (0.66 × ROP) + (0.34 × Pi(max)), and the best endurance index was the TTI(2), although their performance was poor. The best model resulting from the combination of these indices was defined by the following expression: (0.6 × ROP) – (0.1 × Pi(max)) + (0.5 × TTI(2)). This integrated index was a good weaning predictor (P < 0.01), with a LR(+ )of 6.4 and LR(+)/LR(- )ratio of 12.5. However, at a threshold value <1.3 it was only predictive of weaning success (LR(- )= 0.5). CONCLUSION: The proposed combined index, incorporating endurance, was of modest value in predicting weaning outcome. This is the first report of the value of endurance parameters in predicting weaning success in children. Currently, clinical judgement associated with spontaneous breathing trials apparently remain superior

Tumour biology of colorectal liver metastasis is a more important factor in survival than surgical margin clearance in the era of modern chemotherapy regimens

AbstractBackgroundThe aim of the authors was to reassess the impact of a positive surgical margin (R1) after a liver resection for colorectal liver metastases (CLMs) on survival in the era of modern chemotherapy, through their own experience and a literature review.MethodsInclusion criteria were: R1 or R0 resection with no local treatment modalities, extra‐hepatic metastases or other cancer.ResultsAmong 337 patients operated between 2000 and 2010, 273 patients were eligible (214 R0/59 R1). The mean follow‐up was 43 ± 29 months. Compared with a R0 resection, a R1 resection offered a lower 5‐year overall (39.1% versus 54.2%, P = 0.010), disease‐free (15.2% versus 31.1%, P = 0.021) and progression‐free (i.e. time to the first non‐curable recurrence; 33.1% versus 47.3%, P = 0.033) survival rates. Metastases in the R1 group were more numerous, larger and more frequently synchronous. Independent factors of poor survival were: number, size and short‐time interval of CLM occurrence, N status, rectal primary, absence of adjuvant chemotherapy, but not a R1 resection. With the more‐systematic administration of chemotherapy since 2005, the intergroup difference in progression‐free survival disappeared (P = 0.264).ConclusionA R1 resection had no prognostic value per se but reflected a more severe disease. The recent change in the prognostic value of a R1 resection may be linked to the beneficial effect of chemotherapy

The intensive care medicine clinical research agenda in paediatrics

BACKGROUND: Intensive Care Medicine set us the task of outlining a global clinical research agenda for paediatric intensive care (PIC). In line with the clinical focus of this journal, we have limited this to research that may directly influence patient care. METHODS: Clinician researchers from PIC research networks of varying degrees of formality from around the world were invited to answer two main questions: (1) What have been the major recent advances in paediatric critical care research? (2) What are the top 10 studies for the next 10 years? RESULTS: (1) Inclusive databases are well established in many countries. These registries allow detailed observational studies and feasibility testing of clinical trial protocols. Recent trials are larger and more valuable, and (2) most common interventions in PIC are not evidenced-based. Clinical studies for the next 10 years should address this deficit, including: ventilation techniques and interfaces; fluid, transfusion and feeding strategies; optimal targets for vital signs; multiple organ failure definitions, mechanisms and treatments; trauma, prevention and treatment; improving safety; comfort of the patient and their family; appropriate care in the face of medical complexity; defining post-PICU outcomes; and improving knowledge generation and adoption, with novel trial design and implementation strategies. The group specifically highlighted the need for research in resource-limited environments wherein mortality remains often tenfold higher than in well-resourced settings. CONCLUSIONS: Paediatric intensive care research has never been healthier, but many gaps in knowledge remain. We need to close these urgently. The impact of new knowledge will be greatest in resource-limited environments

Refining the Pediatric Multiple Organ Dysfunction Syndrome

Since its introduction into the medical literature in the 1970s, the term multiple organ dysfunction syndrome (or some variant) has been applied broadly to any patient with >1 concurrent organ dysfunction. However, the epidemiology, mechanisms, time course, and outcomes among children with multiple organ dysfunction vary substantially. We posit that the term pediatric multiple organ dysfunction syndrome (or MODS) should be reserved for patients with a systemic pathologic state resulting from a common mechanism (or mechanisms) that affects numerous organ systems simultaneously. In contrast, children in whom organ injuries are attributable to distinct mechanisms should be considered to have additive organ system dysfunctions but not the syndrome of MODS. Although such differentiation may not always be possible with current scientific knowledge, we make the case for how attempts to differentiate multiple organ dysfunction from other states of additive organ dysfunctions can help to evolve clinical and research priorities in diagnosis, monitoring, and therapy from largely organ-specific to more holistic strategies