Studies Toward the Total Synthesis of Hinckdentine A using Under Utilised Reactions and Functional Groups

Many useful organic transformations remain underutilised because they have not been thoroughly investigated and understood. We have sought to expand the utility of neglected reactions and functional groups by investigating their mechanism and examining their scope. We planned to demonstrate utility of these transformations by incorporating them as key steps in the total synthesis of the natural product hinckdentine A. We developed a rational and consistent theory for mechanism of on-water catalysis. This new theory has allowed us to identify previously unrecognised examples of this phenomenon. The traditionally difficult conjugate addition of anilines was found to be facile under on-water conditions and this reaction was further improved through the incorporation of N-acylpyrroles. N-Acylpyrroles were also found to facilitate the Stetter reaction and expand the scope of subsequent transformations. The understanding gained from these studies allowed us to undertake studies toward the total synthesis of hinckdentine A, by an innovative route which included the aforementioned reactions as integral transformations

Multi-Task Recurrent Neural Network for Surgical Gesture Recognition and Progress Prediction

Surgical gesture recognition is important for surgical data science and computer-aided intervention. Even with robotic kinematic information, automatically segmenting surgical steps presents numerous challenges because surgical demonstrations are characterized by high variability in style, duration and order of actions. In order to extract discriminative features from the kinematic signals and boost recognition accuracy, we propose a multi-task recurrent neural network for simultaneous recognition of surgical gestures and estimation of a novel formulation of surgical task progress. To show the effectiveness of the presented approach, we evaluate its application on the JIGSAWS dataset, that is currently the only publicly available dataset for surgical gesture recognition featuring robot kinematic data. We demonstrate that recognition performance improves in multi-task frameworks with progress estimation without any additional manual labelling and training.Comment: Accepted to ICRA 202

Direct detection of methylation in genomic DNA

The identification of methylated sites on bacterial genomic DNA would be a useful tool to study the major roles of DNA methylation in prokaryotes: distinction of self and nonself DNA, direction of post-replicative mismatch repair, control of DNA replication and cell cycle, and regulation of gene expression. Three types of methylated nucleobases are known: N(6)-methyladenine, 5-methylcytosine and N(4)-methylcytosine. The aim of this study was to develop a method to detect all three types of DNA methylation in complete genomic DNA. It was previously shown that N(6)-methyladenine and 5-methylcytosine in plasmid and viral DNA can be detected by intersequence trace comparison of methylated and unmethylated DNA. We extended this method to include N(4)-methylcytosine detection in both in vitro and in vivo methylated DNA. Furthermore, application of intersequence trace comparison was extended to bacterial genomic DNA. Finally, we present evidence that intrasequence comparison suffices to detect methylated sites in genomic DNA. In conclusion, we present a method to detect all three natural types of DNA methylation in bacterial genomic DNA. This provides the possibility to define the complete methylome of any prokaryote

Pulmonary granulocyte influx and impaired alveolar macrophage adenylyl cyclase responsiveness in developing respiratory distress

Alveolar macrophages have recently been postulated as being involved in the aetiology of adult respiratory distress syndrome (ARDS). To evaluate their role, basal cyclic AMP levels and responsiveness of adenylyl cyclase alveolar macrophages were determined at four intermediate stages of developing respiratory distress in piglets using a protocol with repeated lung lavage. Examination of alveolar cells recovered from the subsequent lavages reveals an influx of granulocytes (neutrophils and eosinophils) within 1 h of two intensive lung lavages. During the developing respiratory distress the basal cyclic AMPlevel of alveolar macrophages increases and adenylyl cyclase responsiveness to prostaglandin E2 (PGE2) and isoprelanaline diminishes. The previously observed impairment of macrophage activity can then be explained at a subcellular level

Evaluation of a procedure to assess the adverse effects of illicit drugs.

The assessment procedure of new synthetic illicit drugs that are not documented in the UN treaty on psychotropic drugs was evaluated using a modified Electre model. Drugs were evaluated by an expert panel via the open Delphi approach, where the written score was discussed on 16 items, covering medical, health, legal, and criminalistic issues of the drugs. After this face-to-face discussion the drugs were scored again. Taking the assessment of ketamine as an example, it appeared that each expert used its own scale to score, and that policymakers do not score deviant from experts trained in the medical-biological field. Of the five drugs evaluated by the panel, p-methoxy-metamphetamine (PMMA), gamma-hydroxybutyric acid (GHB), and 4-methylthio-amphetamine (MTA) were assessed as more adverse than ketamine and psilocine and psilocybine-containing mushrooms. Whereas some experts slightly adjusted during the assessment procedure their opinion on ketamine and PMMA, the opinion on mushrooms was not affected by the discussion held between the two scoring rounds. All experts rank the five drugs in a similar way on the adverse effect scale i.e., concordance scale of the Electre model, indicating unanimity in the expert panel with respect to the risk classification of these abused drugs

Gesture Recognition in Robotic Surgery with Multimodal Attention

Automatically recognising surgical gestures from surgical data is an important building block of automated activity recognition and analytics, technical skill assessment, intra-operative assistance and eventually robotic automation. The complexity of articulated instrument trajectories and the inherent variability due to surgical style and patient anatomy make analysis and fine-grained segmentation of surgical motion patterns from robot kinematics alone very difficult. Surgical video provides crucial information from the surgical site with context for the kinematic data and the interaction between the instruments and tissue. Yet sensor fusion between the robot data and surgical video stream is non-trivial because the data have different frequency, dimensions and discriminative capability. In this paper, we integrate multimodal attention mechanisms in a two-stream temporal convolutional network to compute relevance scores and weight kinematic and visual feature representations dynamically in time, aiming to aid multimodal network training and achieve effective sensor fusion. We report the results of our system on the JIGSAWS benchmark dataset and on a new in vivo dataset of suturing segments from robotic prostatectomy procedures. Our results are promising and obtain multimodal prediction sequences with higher accuracy and better temporal structure than corresponding unimodal solutions. Visualization of attention scores also gives physically interpretable insights on network understanding of strengths and weaknesses of each sensor