Development of Continuous Flow Sonogashira Coupling of lead Anti-Cancer Small Molecule Inhibitors for Potential Treatment of Acute Myeloid Leukemia

As the technology for science develops, the research strategy in medicines and therapeutics also improves. In this paper, I will cover the process of Sonogashira cross-coupling and Amide Coupling reaction for an anticancer agent in both batch and flow chemistry. Continuous Flow Chemistry has advantages such as being more efficient, safer, and faster. This paper studies the synthesis of HSNO608, an anticancer lead compound for Acute Myeloid Leukemia (AML), which has a specific potent activity to FTL3 Kinase. Inhibition of FLT3 Kinase leads to inhibition of downstream pathways such as MPK and P13K pathways. In this two-step experiment, the Sonogashira cross-coupling reaction is a crucial step in the flow process. For the amidation reaction, it favored high retention time and low temperatures. For the Sonogashira cross-coupling reactions, different types of Palladium Catalyst and Copper Co-catalyst were screened. The best catalyst found was PdCl2(MeCN)2 with the ligand of [(t-Bu)3PH]BF4 giving us a yield of 88% with high loading (%10) of Copper and Pd catalyst. This condition was further optimized to reduce the catalyst loading to 1%. In conclusion, we were able to optimize and create methods to synthesize lead medicinal compounds. In the future, this approach could be applied to other anticancer targets and other medicinal chemical targets

EVALUATION OF WOUND HEALING ACTIVITY OF POLYHERBAL FORMULATION

Objective: The present study describes the anti-microbial acivity of Acacia arabica and Butea monosperma bark extract.Methods: For this purpose aqueous extract of bark were prepared by Soxhlet extraction methodâ€. The experimentally induced burn wound model in rats by Excision methodâ€.Results: As a result of this study it was found that the extract of bark generally revealed antimicrobial and wound healing activity.Conclusion: The result of the study suggest that the Acacia arabica and Butea monosperma bark of polyherbal gel effective in accelerating wound healing process

Autonomous Tissue Retraction in Robotic Assisted Minimally Invasive Surgery – A Feasibility Study

In this letter, we describe a novel framework for planning and executing semi-autonomous tissue retraction in minimally invasive robotic surgery. The approach is aimed at removing tissue flaps or connective tissue from the surgical area autonomously, thus exposing the underlying anatomical structures. First, a deep neural network is used to analyse the endoscopic image and detect candidate tissue flaps obstructing the surgical field. A procedural algorithm for planning and executing the retraction gesture is then developed from extended discussions with clinicians. Experimental validation, carried out on a DaVinci Research Kit, shows an average 25% increase of the visible background after retraction. Another significant contribution of this letter is a dataset containing 1,080 labelled surgical stereo images and the associated depth maps, representing tissue flaps in different scenarios. The work described in this letter is a fundamental step towards the autonomous execution of tissue retraction, and the first example of simultaneous use of deep learning and procedural algorithms. The same framework could be applied to a wide range of autonomous tasks, such as debridement and placement of laparoscopic clips

Combining Game Design and Data Visualization to Inform Plastics Policy: Fostering Collaboration between Science, Decision-Makers, and Artificial Intelligence

This multi-disciplinary case study details how a public web application combines information and game design to visualize effects of user-defined policies intended to reduce plastic waste. Contextualizing this open source software within a broader lineage of digital media research, this user experience exploration outlines potential directions for facilitating conversation between artificial intelligence, scientists, and decision makers during an iterative policy building process. Furthermore, this system dissection reveals how this interactive science effort considers the practicalities of a treaty's shifting priorities and proposals in its designs. Specifically, this historically situated investigation of the tool's approach highlights options for centering human decision making where artificial intelligence helps reason about interventions but does not prescribe them. Finally, analysis summarizes this application's specific game design-inspired mechanics and their efforts to: enable users' agency to explore solution possibilities freely, invite deep engagement with scientific findings, and simultaneously serve multiple audiences with divergent objectives and expertise.Comment: 29 pages of which 8 are citations, 4 figures, latex generated from markdown via Pandoc (https://pandoc.org/) for Arxi

Burnout in Surgical Trainees: a Narrative Review of Trends, Contributors, Consequences and Possible Interventions

Surgical disciplines are popular and training places are competitive to obtain, but trainees report higher levels of burnout than either their non-surgical peers or attending or consultant surgeons. In this review, we critically summarise evidence on trends and changes in burnout over the past decade, contributors to surgical trainee burnout, the personal and professional consequences of burnout and consider the evidence for interventions. There is no evidence for a linear increase in burnout levels in surgeons over the past decade but the impact of the COVID-19 pandemic has yet to be established and is likely to be significant. Working long hours and experiencing stressful interpersonal interactions at work are associated with higher burnout in trainees but feeling more supported by training programmes and receiving workplace supervision are associated with reduced burnout. Burnout is associated with poorer overall mental and physical well-being in surgical trainees and has also been linked with the delivery of less safe patient care in this group. Useful interventions could include mentorship and improving work conditions, but there is a need for more and higher quality studies

First urology simulation boot camp in the United Kingdom

Objective: Simulation is now firmly established in modern surgical training and is applicable not only to acquiring surgical skills but also to non-surgical skills and professionalism. A 5-day intensive Urology Simulation Boot Camp was run to teach emergency procedural skills, clinical reasoning, and communication skills using clinical scenario simulations, endoscopic and laparoscopic trainers. This paper reports the educational value of this first urology boot camp. Subjects and methods: Sixteen urology UK trainees completed pre-course questionnaires on their operative experience and confidence level in common urological procedures. The course included seven modules covering basic scrotal procedures, laparoscopic skills, ureteroscopy, transurethral resection of the prostate and bladder tumour, green light laser prostatectomy, familiarisation with common endoscopic equipment, bladder washout to remove clots, bladder botox injection, setting up urodynamics. Emergency urological conditions were managed using scenarios on SimMan®. The main focus of the course was hands-on training using animal models, bench-top models and virtual reality simulators. Post-course assessment and feedback on the course structure and utility of knowledge gained together with a global outcome score was collected. Results: Overall all the sections of feedback received score of over 4.5/5, with the hands-on training on simulators getting the best score 4.8/5. When trainees were asked “The training has equipped me with enhanced knowledge, understanding and skills,” the average score was 4.9/5.0. The vast majority of participants felt they would recommend the boot camp to future junior trainees. Conclusion: This first UK Urology Simulation Boot Camp has demonstrated feasibility and effectiveness in enhancing trainee’s experience. Given these positive feedbacks there is a good reason to expect that future courses will improve the overall skills of a new urology trainee

A Comparative Study of Spatio-Temporal U-Nets for Tissue Segmentation in Surgical Robotics

In surgical robotics, the ability to achieve high levels of autonomy is often limited by the complexity of the surgical scene. Autonomous interaction with soft tissues requires machines able to examine and understand the endoscopic video streams in real-time and identify the features of interest. In this work, we show the first example of spatio-temporal neural networks, based on the U-Net, aimed at segmenting soft tissues in endoscopic images. The networks, equipped with Long Short-Term Memory and Attention Gate cells, can extract the correlation between consecutive frames in an endoscopic video stream, thus enhancing the segmentation’s accuracy with respect to the standard U-Net. Initially, three configurations of the spatiotemporal layers are compared to select the best architecture. Afterwards, the parameters of the network are optimised and finally the results are compared with the standard U-Net. An accuracy of 83:77%±2:18% and a precision of 78:42%±7:38% are achieved by implementing both Long Short Term Memory (LSTM) convolutional layers and Attention Gate blocks. The results, although originated in the context of surgical tissue retraction, could benefit many autonomous tasks such as ablation, suturing and debridement

Frontal theta brain activity varies as a function of surgical experience and task error

Objective Investigations into surgical expertise have almost exclusively focused on overt behavioral characteristics with little consideration of the underlying neural processes. Recent advances in neuroimaging technologies, for example, wireless, wearable scalp-recorded electroencephalography (EEG), allow an insight into the neural processes governing performance. We used scalp-recorded EEG to examine whether surgical expertise and task performance could be differentiated according to an oscillatory brain activity signal known as frontal theta—a putative biomarker for cognitive control processes. Design, setting, and participants Behavioral and EEG data were acquired from dental surgery trainees with 1 year (n=25) and 4 years of experience (n=20) while they performed low and high difficulty drilling tasks on a virtual reality surgical simulator. EEG power in the 4–7 Hz range in frontal electrodes (indexing frontal theta) was examined as a function of experience, task difficulty and error rate. Results Frontal theta power was greater for novices relative to experts (p=0.001), but did not vary according to task difficulty (p=0.15) and there was no Experience × Difficulty interaction (p=0.87). Brain–behavior correlations revealed a significant negative relationship between frontal theta and error in the experienced group for the difficult task (r=−0.594, p=0.0058), but no such relationship emerged for novices. Conclusion We find frontal theta power differentiates between surgical experiences but correlates only with error rates for experienced surgeons while performing difficult tasks. These results provide a novel perspective on the relationship between expertise and surgical performance

What Goes Around Comes Around: Learning Sentiments in Online Medical Forums

Currently 19%-28% of Internet users participate in online health discussions. A 2011 survey of the US population estimated that 59% of all adults have looked online for information about health topics such as a specific disease or treatment. Although empirical evidence strongly supports the importance of emotions in health-related messages, there are few studies of the relationship between a subjective lan-guage and online discussions of personal health. In this work, we study sentiments expressed on online medical forums. As well as considering the predominant sentiments expressed in individual posts, we analyze sequences of sentiments in online discussions. Individual posts are classified into one of five categories. We identified three categories as sentimental (encouragement, gratitude, confusion) and two categories as neutral (facts, endorsement). 1438 messages from 130 threads were annotated manually by two annotators with a strong inter-annotator agreement (Fleiss kappa = 0.737 and 0.763 for posts in se-quence and separate posts respectively). The annotated posts were used to analyse sentiments in consec-utive posts. In four multi-class classification problems, we assessed HealthAffect, a domain-specific af-fective lexicon, as well general sentiment lexicons in their ability to represent messages in sentiment recognition