From supported membranes to tethered vesicles: lipid bilayers destabilisation at the main transition

We report results concerning the destabilisation of supported phospholipid bilayers in a well-defined geometry. When heating up supported phospholipid membranes deposited on highly hydrophilic glass slides from room temperature (i.e. with lipids in the gel phase), unbinding was observed around the main gel to fluid transition temperature of the lipids. It lead to the formation of relatively monodisperse vesicles, of which most remained tethered to the supported bilayer. We interpret these observations in terms of a sharp decrease of the bending rigidity modulus $\kappa$ in the transition region, combined with a weak initial adhesion energy. On the basis of scaling arguments, we show that our experimental findings are consistent with this hypothesis.Comment: 11 pages, 3 figure

TeCNO: Surgical Phase Recognition with Multi-Stage Temporal Convolutional Networks

Automatic surgical phase recognition is a challenging and crucial task with the potential to improve patient safety and become an integral part of intra-operative decision-support systems. In this paper, we propose, for the first time in workflow analysis, a Multi-Stage Temporal Convolutional Network (MS-TCN) that performs hierarchical prediction refinement for surgical phase recognition. Causal, dilated convolutions allow for a large receptive field and online inference with smooth predictions even during ambiguous transitions. Our method is thoroughly evaluated on two datasets of laparoscopic cholecystectomy videos with and without the use of additional surgical tool information. Outperforming various state-of-the-art LSTM approaches, we verify the suitability of the proposed causal MS-TCN for surgical phase recognition.Comment: 10 pages, 2 figure

Using Visual Cues to Enhance Haptic Feedback for Palpation on Virtual Model of Soft Tissue

This paper explores methods that make use of visual cues aimed at generating actual haptic sensation to the user, namely pseudo-haptics. We propose a new pseudo-haptic feedback based method capable of conveying 3D haptic information and combining visual haptics with force feedback to enhance the user’s haptic experience. We focused on an application related to tumor identification during palpation and evaluated the proposed method in an experimental study where users interacted with a haptic device and graphical interface while exploring a virtual model of soft tissue, which represented stiffness distribution of a silicone phantom tissue with embedded hard inclusions. The performance of hard inclusion detection using force feedback only, pseudo-haptic feedback only, and the combination of the two feedbacks were compared with the direct hand touch. The combination method and direct hand touch had no significant difference in the detection results. Compared with the force feedback alone, our method increased the sensitivity by 5%, the positive predictive value by 4%, and decreased detection time by 48.7%. The proposed methodology has great potential for robot-assisted minimally invasive surgery and in all applications where remote haptic feedback is needed

A New Pipeline for the Normalization and Pooling of Metabolomics Data

Pooling metabolomics data across studies is often desirable to increase the statistical power of the analysis. However, this can raise methodological challenges as several preanalytical and analytical factors could introduce differences in measured concentrations and variability between datasets. Specifically, different studies may use variable sample types (e.g., serum versus plasma) collected, treated, and stored according to different protocols, and assayed in different laboratories using different instruments. To address these issues, a new pipeline was developed to normalize and pool metabolomics data through a set of sequential steps: (i) exclusions of the least informative observations and metabolites and removal of outliers; imputation of missing data; (ii) identification of the main sources of variability through principal component partial R-square (PC-PR2) analysis; (iii) application of linear mixed models to remove unwanted variability, including samples' originating study and batch, and preserve biological variations while accounting for potential differences in the residual variances across studies. This pipeline was applied to targeted metabolomics data acquired using Biocrates AbsoluteIDQ kits in eight case-control studies nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Comprehensive examination of metabolomics measurements indicated that the pipeline improved the comparability of data across the studies. Our pipeline can be adapted to normalize other molecular data, including biomarkers as well as proteomics data, and could be used for pooling molecular datasets, for example in international consortia, to limit biases introduced by inter-study variability. This versatility of the pipeline makes our work of potential interest to molecular epidemiologists

Molecular Detection of Multiple Emerging Pathogens in Sputa from Cystic Fibrosis Patients

Background: There is strong evidence that culture-based methods detect only a small proportion of bacteria present in the respiratory tracts of cystic fibrosis (CF) patients. Methodology/Principal Findings: Standard microbiological culture and phenotypic identification of bacteria in sputa from CF patients have been compared to molecular methods by the use of 16S rDNA amplification, cloning and sequencing. Twenty-five sputa from CF patients were cultured that yield 33 isolates (13 species) known to be pathogens during CF. For molecular cloning, 760 clones were sequenced (7.263.9 species/sputum), and 53 different bacterial species were identified including 16 species of anaerobes (30%). Discrepancies between culture and molecular data were numerous and demonstrate that accurate identification remains challenging. New or emerging bacteria not or rarely reported in CF patients were detected including Dolosigranulum pigrum, Dialister pneumosintes, and Inquilinus limosus. Conclusions/Significance: Our results demonstrate the complex microbial community in sputa from CF patients, especially anaerobic bacteria that are probably an underestimated cause of CF lung pathology. Metagenomic analysis is urgentl

CCC meets ICU: Redefining the role of critical care of cancer patients

<p>Abstract</p> <p>Background</p> <p>Currently the majority of cancer patients are considered ineligible for intensive care treatment and oncologists are struggling to get their patients admitted to intensive care units. Critical care and oncology are frequently two separate worlds that communicate rarely and thus do not share novel developments in their fields. However, cancer medicine is rapidly improving and cancer is eventually becoming a chronic disease. Oncology is therefore characterized by a growing number of older and medically unfit patients that receive numerous novel drug classes with unexpected side effects.</p> <p>Discussion</p> <p>All of these changes will generate more medically challenging patients in acute distress that need to be considered for intensive care. An intense exchange between intensivists, oncologists, psychologists and palliative care specialists is warranted to communicate the developments in each field in order to improve triage and patient treatment. Here, we argue that "critical care of cancer patients" needs to be recognized as a medical subspecialty and that there is an urgent need to develop it systematically.</p> <p>Conclusion</p> <p>As prognosis of cancer improves, novel therapeutic concepts are being introduced and more and more older cancer patients receive full treatment the number of acutely ill patients is growing significantly. This development a major challenge to current concepts of intensive care and it needs to be redefined who of these patients should be treated, for how long and how intensively.</p

Intensive care of the cancer patient: recent achievements and remaining challenges

A few decades have passed since intensive care unit (ICU) beds have been available for critically ill patients with cancer. Although the initial reports showed dismal prognosis, recent data suggest that an increased number of patients with solid and hematological malignancies benefit from intensive care support, with dramatically decreased mortality rates. Advances in the management of the underlying malignancies and support of organ dysfunctions have led to survival gains in patients with life-threatening complications from the malignancy itself, as well as infectious and toxic adverse effects related to the oncological treatments. In this review, we will appraise the prognostic factors and discuss the overall perspective related to the management of critically ill patients with cancer. The prognostic significance of certain factors has changed over time. For example, neutropenia or autologous bone marrow transplantation (BMT) have less adverse prognostic implications than two decades ago. Similarly, because hematologists and oncologists select patients for ICU admission based on the characteristics of the malignancy, the underlying malignancy rarely influences short-term survival after ICU admission. Since the recent data do not clearly support the benefit of ICU support to unselected critically ill allogeneic BMT recipients, more outcome research is needed in this subgroup. Because of the overall increased survival that has been reported in critically ill patients with cancer, we outline an easy-to-use and evidence-based ICU admission triage criteria that may help avoid depriving life support to patients with cancer who can benefit. Lastly, we propose a research agenda to address unanswered questions

Aberrant signaling in T-cell acute lymphoblastic leukemia: biological and therapeutic implications

T-cell acute lymphoblastic leukemia (T-ALL) is a biologically heterogeneous disease with respect to phenotype, gene expression profile and activation of particular intracellular signaling pathways. Despite very significant improvements, current therapeutic regimens still fail to cure a portion of the patients and frequently implicate the use of aggressive protocols with long-term side effects. In this review, we focused on how deregulation of critical signaling pathways, in particular Notch, PI3K/Akt, MAPK, Jak/STAT and TGF-beta, may contribute to T-ALL. Identifying the alterations that affect intracellular pathways that regulate cell cycle and apoptosis is essential to understanding the biology of this malignancy, to define more effective markers for the correct stratification of patients into appropriate therapeutic regimens and to identify novel targets for the development of specific, less detrimental therapies for T-ALL

Noncanonical Compensation of Zygotic X Transcription in Early Drosophila melanogaster Development Revealed through Single-Embryo RNA-Seq

Mmany genes from the X chromosome are expressed at the same level in female and male embryos during early Drosophila development, prior to the establishment of MSL-mediated dosage compensation, suggesting the existence of a novel mechanism