Cyclic peptides- small and big and their conformational aspects

Cyclic peptides form an interesting class of compounds for study by conformational analysis, by virtue of their unique conformational features and biological properties. The small cyclic peptides having 3-6 peptide units in their ring, show a variety of conformational characteristics such as occurrence ofcis peptide units, flexibility of peptide dimension and variety in hydrogen bonding. The different possible conformations of cyclic tri- and hexa-peptides are given and certain specific conformational features are discussed for cyclic tetra and pentapeptides. For higher cyclic peptides, the hydrogen bonding requirement for stability of the backbone of the ring, is seen to be kept to a minimum. These various features and their significance are examined and discussed in the light of energy minimization studies and analysis of available experimental data

Students' perceptions of learning environment in an Indian medical school

<p>Abstract</p> <p>Background</p> <p>Learning environment in any medical school is found to be important in determining students' academic success. This study was undertaken to compare the perceptions of first year and clinical phase students regarding the learning environment at Melaka Manipal Medical College (MMMC) (Manipal Campus) and also to identify the gender wise differences in their perceptions.</p> <p>Methods</p> <p>In the present study, the Dundee Ready Education Environment Measure (DREEM) inventory was used. DREEM was originally developed at Dundee and has been validated as a universal diagnostic inventory for assessing the quality of educational environment. In the present study, DREEM was administered to undergraduate medical students of first year (n = 118) and clinical phase (n = 108) and the scores were compared using a nonparametric test.</p> <p>Results</p> <p>Among the two batches, first year students were found to be more satisfied with the learning environment at MMMC (as indicated by their higher DREEM score) compared to the clinical batch students. Gender wise, there was not much difference in the students' perceptions.</p> <p>Conclusion</p> <p>The present study revealed that both groups of students perceived the learning environment positively. Nevertheless, the study also revealed problematic areas of learning environment in our medical school which enabled us to adopt some remedial measures.</p

Image and Information Fusion Experiments with a Software-Defined Multi-Spectral Imaging System for Aviation and Marine Sensor Networks

The availability of Internet, line-of-sight and satellite identification and surveillance information as well as low-power, low-cost embedded systems-on-a-chip and a wide range of visible to long-wave infrared cameras prompted Embry Riddle Aeronautical University to collaborate with the University of Alaska Arctic Domain Awareness Center (ADAC) in summer 2016 to prototype a camera system we call the SDMSI (Software-Defined Multi-spectral Imager). The concept for the camera system from the start has been to build a sensor node that is drop-in-place for simple roof, marine, pole-mount, or buoy-mounts. After several years of component testing, the integrated SDMSI is now being tested, first on a roof-mount at Embry Riddle Prescott. The roof-mount testing demonstrates simple installation for the high spatial, temporal and spectral resolution SDMSI. The goal is to define and develop software and systems technology to complement satellite remote sensing and human monitoring of key resources such as drones, aircraft and marine vessels in and around airports, roadways, marine ports and other critical infrastructure. The SDMSI was installed at Embry Riddle Prescott in fall 2016 and continuous recording of long-wave infrared and visible images have been assessed manually and compared to salient object detection to automatically record only frames containing objects of interest (e.g. aircraft and drones). It is imagined that ultimately users of the SDMSI can pair with it via wireless to browse salient images. Further, both ADS-B (Automatic Dependent Surveillance-Broadcast) and S-AIS (Satellite Automatic Identification System) data are envisioned to be used by the SDMSI to form expectations for observing in future tests. This paper presents the preliminary results of several experiments and compares human review with smart image processing in terms of the receiver-operator characteristic. The system design and software are open architecture, such that other researchers are encouraged to construct and participate in sharing results and networking identical or improved versions of the SDMSI for safety, security and drop-in-place scientific image sensor networking

Human-Centric AI Adoption and Its Influence on Worker Productivity: An Empirical Investigation

This empirical study looks at how the industrial sector is affected by the deployment of human-centric AI and finds some amazing changes in the workplace. Following implementation, employee productivity increased by 35.5%, demonstrating the significant advantages of AI in automating repetitive jobs and improving overall efficiency. Simultaneously, job satisfaction increased by a significant 20.6%, highlighting the alignment of AI with worker well-being. Employee skill development increased by 29.6% as a result of structured AI training, which is consistent with the larger goals of adopting AI that is human-centric. Significant cost reductions of up to 40% of budgets were also realized by departments, resulting in significant economic benefits. These revelations highlight the revolutionary potential of AI integration in Industry 5.0, promoting a harmonic convergence of intelligent technology and human skills for an industrial future that is more productive, happy, and financially stable

Establishing and augmenting acceptability of the Fever trial: a mixed methods feasibility study

Introduction: Paediatric clinical trials in critical care settings are challenging to conduct. Establishing trial acceptability can help inform trial design and avoid research waste. This paper reports on how research with parents and staff established and augmented perspectives and the design of a trial investigating temperature thresholds in critically ill children with fever and infection (Fever trial). // Methods: We used a mixed methods approach to explore perspectives at three time points: 1) before, 2) during and 3) after a pilot trial. This included: 1) pre-trial focus groups with staff and interviews with parents; 2) questionnaires with parents of randomised children following trial recruitment; 3) post-trial interviews with parents and focus groups and a survey with staff. Data analysis drew on Sekhon et al (2017) theoretical framework of acceptability. // Results: 1) 25 parents were interviewed and 56 staff took part focus groups, 2) 60 parents of 57 randomised children took part in questionnaires, 3) 19 parents were interviewed and 50 staff took part in focus group and 48 in a survey. There was initial support for the trial, although both groups raised concerns regarding proposed thresholds and not using paracetamol for pain or discomfort. Pre-trial findings informed pilot trial protocol changes and training, which assisted practitioner ‘buy in’. However, concerns about children being in pain or discomfort when weaned from ventilation led to cases of withdrawal and protocol non-adherence. Nevertheless, 95% of parents provided consent and all supported the trial. Those trained by the Fever team found the trial more acceptable than those trained by colleagues. Trusting parent and staff relationships were linked to trial acceptability. // Conclusions: Pre-trial findings and pilot trial experience augmented perspectives, providing insight into how challenges may be overcome. The proposed trial was deemed feasible. We present an adapted theoretical framework of acceptability to inform the design of future trial feasibility studies

Establishing and augmenting views on the acceptability of a paediatric critical care randomised controlled trial (the FEVER trial): a mixed methods study

OBJECTIVE: To explore parent and staff views on the acceptability of a randomised controlled trial investigating temperature thresholds for antipyretic intervention in critically ill children with fever and infection (the FEVER trial) during a multi-phase pilot study. DESIGN: Mixed methods study with data collected at three time points: (1) before, (2) during and (3) after a pilot trial. SETTING: English, Paediatric Intensive Care Units (PICUs). PARTICIPANTS: (1) Pre-pilot trial focus groups with pilot site staff (n=56) and interviews with parents (n=25) whose child had been admitted to PICU in the last 3 years with a fever and suspected infection, (2) Questionnaires with parents of randomised children following pilot trial recruitment (n=48 from 47 families) and (3) post-pilot trial interviews with parents (n=19), focus groups (n=50) and a survey (n=48) with site staff. Analysis drew on Sekhon et al's theoretical framework of acceptability. RESULTS: There was initial support for the trial, yet some held concerns regarding the proposed temperature thresholds and not using paracetamol for pain or discomfort. Pre-trial findings informed protocol changes and training, which influenced views on trial acceptability. Staff trained by the FEVER team found the trial more acceptable than those trained by colleagues. Parents and staff found the trial acceptable. Some concerns about pain or discomfort during weaning from ventilation remained. CONCLUSIONS: Pre-trial findings and pilot trial experience influenced acceptability, providing insight into how challenges may be overcome. We present an adapted theoretical framework of acceptability to inform future trial feasibility studies. TRIAL REGISTRATION NUMBERS: ISRCTN16022198 and NCT03028818

Avenues for Professional Development: Faculty Perspectives from an Indian Medical School

ABSTRACT Backgroun

First-line support for assistance in breathing in children: statistical and health economic analysis plan for the FIRST-ABC trial

BACKGROUND: The FIRST-ABC trial comprises of two pragmatic, multicentre, parallel groups, non-inferiority randomised clinical trials designed to evaluate the clinical non-inferiority of first-line use of high flow nasal cannula (HFNC) to continuous positive airway pressure (CPAP) in critically ill children who require non-invasive respiratory support (NRS). OBJECTIVES: To describe the pre-specified statistical and health economic analysis for the FIRST-ABC trial before completion of patient recruitment and data collection. METHODS: The statistical analysis plan was designed by the chief investigators and statisticians. We define the primary and secondary outcomes, summarise methods for data collection and safety monitoring, and present a detailed description of the planned statistical and health economic analysis. RESULTS: The primary clinical outcome is time to liberation from respiratory support. The primary effect estimate will be the adjusted hazard ratio, reported with a 95% confidence interval. As a sensitivity analysis, the primary analysis will be repeated using time to start weaning of NRS. Subgroup analyses will be performed to test for interactions between the effect of allocated treatment group and pre-specified baseline covariates. The health economic analysis will follow the intention-to-treat principle and report the mean (95% confidence interval) incremental costs, quality-adjusted life years (QALYs) and cost-effectiveness up to 6 months. All analyses will be performed separately for each of the two trials, and any results will not be combined. CONCLUSION: The FIRST-ABC trial will assess the non-inferiority of HFNC compared to CPAP in two parallel trials with shared infrastructure (step-up RCT and step-down RCT). We have developed a pre-specified statistical and health economics analysis plan for the FIRST-ABC study before trial completion to minimise analytical bias. TRIAL REGISTRATION: ISRCTN ISRCTN60048867 . Registered on 19 June 2019

Coronavirus (COVID-19) infection in children at a specialist centre: outcome and implications of underlying ‘high-risk’ comorbidities in a paediatric population

Background: There is evolving evidence of significant differences in severity and outcomes of coronavirus disease 2019 (COVID-19) in children compared to adults. Underlying medical conditions associated with increased risk of severe disease are based on adult data, but have been applied across all ages resulting in large numbers of families undertaking social ‘shielding’ (vulnerable group). We conducted a retrospective analysis of children with suspected COVID-19 at a Specialist Children’s Hospital to determine outcomes based on COVID-19 testing status and underlying health vulnerabilities. Methods: Routine clinical data were extracted retrospectively from the Institution’s Electronic Health Record system and Digital Research Environment for patients with suspected and confirmed COVID-19 diagnoses. Data were compared between Sars-CoV-2 positive and negative patients (CoVPos / CoVNeg respectively), and in relation to presence of underlying health vulnerabilities based on Public Health England guidance. Findings Between 1st March and 15th May 2020, 166 children (<18 years of age) presented to a specialist children’s hospital with clinical features of possible COVID-19 infection. 65 patients (39.2%) tested positive for SARS-CoV-2 virus. CoVPos patients were older (median 9 [0.9 - 14] years vs median 1 [0.1 - 5.7.5] years respectively, p<0.001). There was a significantly reduced proportion of vulnerable cases (47.7% vs 72.3%, p=0.002), but no difference in proportion of vulnerable patients requiring ventilation (61% vs 64.3%, p = 0.84) between CoVPos and CoVNeg groups. However, a significantly lower proportion of CoVPos patients required mechanical ventilation support compared to CoVNeg patients (27.7 vs 57.4%, p<0.001). Mortality was not significantly different between CoVPos and CoVNeg groups (1.5 vs 4% respectively, p=0.67) although there were no direct COVID-19 related deaths in this highly preselected paediatric population. Interpretation COVID-19 infection may be associated with severe disease in childhood presenting to a specialist hospital, but does not appear significantly different in severity to other causes of similar clinical presentations. In children presenting with pre-existing ‘COVID-19 vulnerable’ medical conditions at a specialist centre, there does not appear to be significantly increased risk of either contracting COVID-19 or severe complications, apart from those undergoing chemotherapy, who are over-represented. Competing Interest Statement The authors have declared no competing interest. Funding Statement: Funding RI is funded by a British Heart Foundation Research Fellowship Grant. HH is funded by NIHR UCLH BRC and HDRUK, NJS is funded by GOSHCC and HDRUK. Role of the funding source The study sponsor / funders had no role or influence in study design, in the collection, analysis, and interpretation of data, in the writing of the report or in the decision to submit the paper for publicatio

Evidence-based decision support for pediatric rheumatology reduces diagnostic errors.

BACKGROUND: The number of trained specialists world-wide is insufficient to serve all children with pediatric rheumatologic disorders, even in the countries with robust medical resources. We evaluated the potential of diagnostic decision support software (DDSS) to alleviate this shortage by assessing the ability of such software to improve the diagnostic accuracy of non-specialists. METHODS: Using vignettes of actual clinical cases, clinician testers generated a differential diagnosis before and after using diagnostic decision support software. The evaluation used the SimulConsult® DDSS tool, based on Bayesian pattern matching with temporal onset of each finding in each disease. The tool covered 5405 diseases (averaging 22 findings per disease). Rheumatology content in the database was developed using both primary references and textbooks. The frequency, timing, age of onset and age of disappearance of findings, as well as their incidence, treatability, and heritability were taken into account in order to guide diagnostic decision making. These capabilities allowed key information such as pertinent negatives and evolution over time to be used in the computations. Efficacy was measured by comparing whether the correct condition was included in the differential diagnosis generated by clinicians before using the software ( unaided ), versus after use of the DDSS ( aided ). RESULTS: The 26 clinicians demonstrated a significant reduction in diagnostic errors following introduction of the software, from 28% errors while unaided to 15% using decision support (p \u3c 0.0001). Improvement was greatest for emergency medicine physicians (p = 0.013) and clinicians in practice for less than 10 years (p = 0.012). This error reduction occurred despite the fact that testers employed an open book approach to generate their initial lists of potential diagnoses, spending an average of 8.6 min using printed and electronic sources of medical information before using the diagnostic software. CONCLUSIONS: These findings suggest that decision support can reduce diagnostic errors and improve use of relevant information by generalists. Such assistance could potentially help relieve the shortage of experts in pediatric rheumatology and similarly underserved specialties by improving generalists\u27 ability to evaluate and diagnose patients presenting with musculoskeletal complaints. TRIAL REGISTRATION: ClinicalTrials.gov ID: NCT02205086