First report on pesticide sub-chronic and chronic toxicities against dogs using QSAR and chemical read-across

Excessive use of chemicals is the outcome of the industrialization of agricultural sectors which leads to disturbance of ecological balance. Various agrochemicals are widely used in agricultural fields, urban green areas, and to protect from various pest-associated diseases. Due to their long-term health and environmental hazards, chronic toxicity assessment is crucial. Since in vivo and in vitro toxicity assessments are costly, lengthy, and require a large number of animal experiments, in silico toxicity approaches are better alternatives to save time, cost, and animal experimentation. We have developed the first regression-based 2D-QSAR models using different sub-chronic and chronic toxicity data of pesticides against dogs employing 2D descriptors. From the statistical results (n train = 53 - 62 ,   r 2  = 0.614 to 0.754, Q L O O 2  = 0.501 to 0.703 and   Q F 1 2  = 0.531 to 0.718, Q F 2 2 = 0.523 - 0.713 ), it was concluded that the models are robust, reliable, interpretable, and predictive. Similarity-based read-across algorithm was also used to improve the predictivity (Q F 1 2 = 0.595 - 0.813 , Q F 2 2 = 0.573 - 0.809 ) of the models. 5132 chemicals obtained from the CPDat and 1694 pesticides obtained from the PPDB database were also screened using the developed models, and their predictivity and reliability were checked. Thus, these models will be helpful for eco-toxicological data-gap filling, toxicity prediction of untested pesticides, and development of novel, safer & eco-friendly pesticides.

Intracardiac vs Transesophageal Echocardiography for Left Atrial Appendage Occlusion With Watchman FLX in the U.S

BACKGROUND

Intraprocedural imaging is critical for device delivery in transcatheter left atrial appendage occlusion (LAAO). Although pivotal trials of LAAO devices were conducted using transesophageal echocardiography (TEE), intracardiac echocardiography (ICE) is an emerging imaging modality.

OBJECTIVES

This study compared outcomes after ICE- and TEE-guided Watchman FLX implantation in the SURPASS (SURveillance Post Approval AnalySiS Plan) nationwide LAAO registry.

METHODS

Baseline characteristics were compared using chi-square and t-tests. Outcomes were reported in unadjusted and adjusted comparisons via propensity weighting.

RESULTS

Between August 2020 and September 2021, LAAO was attempted in 39,759 patients at 698 sites, including 2,272 cases (5.7%) with ICE and 31,835 (80.0%) with TEE. ICE and TEE patients had similar baseline characteristics and mean procedural times (ICE 82 minutes vs TEE 78 minutes). ICE patients were less likely to receive general anesthesia (54% vs 98%, P < 0.01). Successful device implantation (98.3% vs 97.6%) and complete seal rates at 45 days were similar (n = 25,280; 83% vs 82%). Most adverse event rates were similar; unadjusted mortality rates at 45 days were 1.1% for ICE vs 0.8% for TEE (P = 0.14), and 1.0% vs 0.7% (P = 0.27) in adjusted analyses. Even after adjustment, pericardial effusion rates requiring intervention were significantly higher with ICE at 45 days (1.0% vs 0.5%; P = 0.02). This rate decreased as operators performed more ICE-guided procedures, although 82% of operators had performed <10 ICE-guided procedures overall.

CONCLUSIONS

In the largest comparison to date, ICE use was infrequent. ICE and TEE both achieved high rates of complete LAAO. ICE was associated with significantly higher rates of pericardial effusion requiring intervention.

QSAR assessment of aquatic toxicity potential of diverse agrochemicals

The fast-increasing number of commercially produced chemicals challenges the experimental ecotoxicity assessment methods, which are costly, time-consuming, and dependent on the sacrifice of animals. In this regard, Quantitative Structure-Property/Activity Relationships (QSPR/QSAR) have led the way in developing ecotoxicity assessment models. In this study, QSAR models have been developed using the pEC50 values of 82 diverse agrochemicals or agro-molecules against a planktonic crustacean Daphnia magna with easily interpretable 2D descriptors. Moreover, a link among octanol-water partition coefficient (KOW), bio-concentration factor (BCF), and critical body residue (CBR) has been addressed, and their imputation for the prediction of the toxicity endpoint (EC50) has been done with an objective of the advanced exploration of several ecotoxicological parameters for toxic chemicals. The developed partial least squares (PLS) models were validated rigorously and proved to be robust, sound, and immensely well-predictive. The final Daphnia toxicity model derived from experimental derived properties along with computed descriptors emerged better in statistical quality and predictivity than those obtained solely from computed descriptors. Additionally, the pEC50 and other important properties (log KOW, log BCF, and log CBR) for a set of external agro-molecules, not employed in model development, were predicted to show the predictive ability of the models.

Multiorgan MRI findings after hospitalisation with COVID-19 in the UK (C-MORE): a prospective, multicentre, observational cohort study

INTRODUCTION

The multiorgan impact of moderate to severe coronavirus infections in the post-acute phase is still poorly understood. We aimed to evaluate the excess burden of multiorgan abnormalities after hospitalisation with COVID-19, evaluate their determinants, and explore associations with patient-related outcome measures.

METHODS

In a prospective, UK-wide, multicentre MRI follow-up study (C-MORE), adults (aged ≥18 years) discharged from hospital following COVID-19 who were included in Tier 2 of the Post-hospitalisation COVID-19 study (PHOSP-COVID) and contemporary controls with no evidence of previous COVID-19 (SARS-CoV-2 nucleocapsid antibody negative) underwent multiorgan MRI (lungs, heart, brain, liver, and kidneys) with quantitative and qualitative assessment of images and clinical adjudication when relevant. Individuals with end-stage renal failure or contraindications to MRI were excluded. Participants also underwent detailed recording of symptoms, and physiological and biochemical tests. The primary outcome was the excess burden of multiorgan abnormalities (two or more organs) relative to controls, with further adjustments for potential confounders. The C-MORE study is ongoing and is registered with ClinicalTrials.gov, NCT04510025.

FINDINGS

Of 2710 participants in Tier 2 of PHOSP-COVID, 531 were recruited across 13 UK-wide C-MORE sites. After exclusions, 259 C-MORE patients (mean age 57 years [SD 12]; 158 [61%] male and 101 [39%] female) who were discharged from hospital with PCR-confirmed or clinically diagnosed COVID-19 between March 1, 2020, and Nov 1, 2021, and 52 non-COVID-19 controls from the community (mean age 49 years [SD 14]; 30 [58%] male and 22 [42%] female) were included in the analysis. Patients were assessed at a median of 5·0 months (IQR 4·2-6·3) after hospital discharge. Compared with non-COVID-19 controls, patients were older, living with more obesity, and had more comorbidities. Multiorgan abnormalities on MRI were more frequent in patients than in controls (157 [61%] of 259 vs 14 [27%] of 52; p<0·0001) and independently associated with COVID-19 status (odds ratio [OR] 2·9 [95% CI 1·5-5·8]; padjusted=0·0023) after adjusting for relevant confounders. Compared with controls, patients were more likely to have MRI evidence of lung abnormalities (p=0·0001; parenchymal abnormalities), brain abnormalities (p<0·0001; more white matter hyperintensities and regional brain volume reduction), and kidney abnormalities (p=0·014; lower medullary T1 and loss of corticomedullary differentiation), whereas cardiac and liver MRI abnormalities were similar between patients and controls. Patients with multiorgan abnormalities were older (difference in mean age 7 years [95% CI 4-10]; mean age of 59·8 years [SD 11·7] with multiorgan abnormalities vs mean age of 52·8 years [11·9] without multiorgan abnormalities; p<0·0001), more likely to have three or more comorbidities (OR 2·47 [1·32-4·82]; padjusted=0·0059), and more likely to have a more severe acute infection (acute CRP >5mg/L, OR 3·55 [1·23-11·88]; padjusted=0·025) than those without multiorgan abnormalities. Presence of lung MRI abnormalities was associated with a two-fold higher risk of chest tightness, and multiorgan MRI abnormalities were associated with severe and very severe persistent physical and mental health impairment (PHOSP-COVID symptom clusters) after hospitalisation.

INTERPRETATION

After hospitalisation for COVID-19, people are at risk of multiorgan abnormalities in the medium term. Our findings emphasise the need for proactive multidisciplinary care pathways, with the potential for imaging to guide surveillance frequency and therapeutic stratification.

FUNDING

UK Research and Innovation and National Institute for Health Research.

Understanding mechanism governing the inflammatory potential of metal oxide nanoparticles using periodic table-based descriptors: a nano-QSAR approach

Metal oxide nanoparticles (MeOxNPs) can be made safer by understanding the interaction between the immune system and nanoparticles. A nano-quantitative structure-activity relationship (nano-QSAR) model can be used to evaluate nanoparticle risk quickly and conveniently. The present work attempts to develop nano-QSAR models to determine the inflammatory potential of MeOxNPs based on the THP-1 cell line. A comprehensive dataset comprising 32 MeOxNPs was used to develop a regression model with fold change (FC) of pro-inflammatory cytokine interleukin (IL)-1beta (IL-1b) release in the THP-1 cell line as the endpoint. Further, the same number of MeOx NPs with varying doses was modelled for the cell viability [-ln(p/(1-p))] endpoint. The results obtained from regression models were statistically significant. The descriptors obtained from the developed predictive models inferred that dose, electronegativity and the presence of metal ions and oxygen can be responsible for IL-1β leakage from the THP-1 cell line. Based on our results, we can conclude that periodic table-based descriptors, incorporated into the QSAR models, are reliable for modelling pro-inflammatory potential. Researchers can use these comprehensive results to design metal oxide nanoparticles with lower toxicity and determine the cause of pro-inflammatory conditions induced by MeOxNPs.

Prediction of soil ecotoxicity against Folsomia candida using acute and chronic endpoints

Soil invertebrates serve as great biological indicators of soil quality. However, there are very few in silico models developed so far on the soil toxicity of chemicals against soil invertebrates due to paucity of data. In this study, three available soil ecotoxicity data (pLC₅₀, pLOEL and pNOEL) against the soil invertebrate Folsomia candida were collected from the ECOTOX database (cfpub.epa.gov/ecotox) and subjected to quantitative structure-activity relationship (QSAR) analysis using 2D descriptors. The collected data for each endpoint were initially curated and used to develop a partial least squares (PLS) regression model based on the features selected through a genetic algorithm followed by the best subset selection. Both internal and external validation metrics of the models' predictions are well-balanced and within the acceptable range as per the Organization for the Economic Cooperation and Development (OECD) criteria. From the developed models, it has been found that molecular weight and presence of phosphate group, electron donor groups, and polyhalogen substitution have a significant impact on the soil ecotoxicity. The soil ecotoxicological risk assessment of organic chemicals can therefore be prioritized by these features. With the availability of additional data in the future, the models may be further refined for more precise predictions.

Left Atrial Appendage Occlusion in the Elderly: Insights From PROTECT-AF, PREVAIL, and Continuous Access Registries

BACKGROUND

Data on the safety and efficacy of left atrial appendage occlusion (LAAO) in elderly patients are limited.

OBJECTIVES

We aimed to compare the outcomes of LAAO between patients ≥80 and <80 years of age.

METHODS

We included patients enrolled in randomized trials and nonrandomized registries of the Watchman 2.5 device. The primary efficacy endpoint was a composite of cardiovascular/unknown death, stroke, or systemic embolism at 5 years. Secondary endpoints included cardiovascular/unknown death, stroke, systemic embolism, and major and nonprocedural bleeding. Survival analyses were performed using the Kaplan-Meier, Cox proportional hazards, and competing risk analysis methods. Interaction terms were used to compare the 2 age groups. We also estimated the average treatment effect of the device with the use of inverse probability weighting.

RESULTS

We studied 2,258 patients, of whom 570 (25.2%) were ≥80 years old, and 1,688 (74.8%) were <80 years old. Procedural complications at 7 days were similar in both age groups. The primary endpoint occurred in 12.0% in the device group vs 13.8% in the control group (HR: 0.9; 95% CI: 0.6-1.4) among patients <80 years of age and in 25.3% vs 21.7%, respectively (HR: 1.2; 95% CI: 0.7-2.0) among patients ≥80 (interaction P value = 0.48). There was no interaction between age and treatment effect for any of the secondary outcomes. The average treatment effects of LAAO (compared with warfarin) were similar in the elderly population (compared with younger patients).

CONCLUSIONS

Despite the higher event rates, octogenarians derive similar benefits from LAAO as their younger counterparts. Age alone should not preclude LAAO in otherwise suitable candidates.

Clinical characteristics with inflammation profiling of long COVID and association with 1-year recovery following hospitalisation in the UK: a prospective observational study

BACKGROUND

No effective pharmacological or non-pharmacological interventions exist for patients with long COVID. We aimed to describe recovery 1 year after hospital discharge for COVID-19, identify factors associated with patient-perceived recovery, and identify potential therapeutic targets by describing the underlying inflammatory profiles of the previously described recovery clusters at 5 months after hospital discharge.

METHODS

The Post-hospitalisation COVID-19 study (PHOSP-COVID) is a prospective, longitudinal cohort study recruiting adults (aged ≥18 years) discharged from hospital with COVID-19 across the UK. Recovery was assessed using patient-reported outcome measures, physical performance, and organ function at 5 months and 1 year after hospital discharge, and stratified by both patient-perceived recovery and recovery cluster. Hierarchical logistic regression modelling was performed for patient-perceived recovery at 1 year. Cluster analysis was done using the clustering large applications k-medoids approach using clinical outcomes at 5 months. Inflammatory protein profiling was analysed from plasma at the 5-month visit. This study is registered on the ISRCTN Registry, ISRCTN10980107, and recruitment is ongoing.

FINDINGS

2320 participants discharged from hospital between March 7, 2020, and April 18, 2021, were assessed at 5 months after discharge and 807 (32·7%) participants completed both the 5-month and 1-year visits. 279 (35·6%) of these 807 patients were women and 505 (64·4%) were men, with a mean age of 58·7 (SD 12·5) years, and 224 (27·8%) had received invasive mechanical ventilation (WHO class 7-9). The proportion of patients reporting full recovery was unchanged between 5 months (501 [25·5%] of 1965) and 1 year (232 [28·9%] of 804). Factors associated with being less likely to report full recovery at 1 year were female sex (odds ratio 0·68 [95% CI 0·46-0·99]), obesity (0·50 [0·34-0·74]) and invasive mechanical ventilation (0·42 [0·23-0·76]). Cluster analysis (n=1636) corroborated the previously reported four clusters: very severe, severe, moderate with cognitive impairment, and mild, relating to the severity of physical health, mental health, and cognitive impairment at 5 months. We found increased inflammatory mediators of tissue damage and repair in both the very severe and the moderate with cognitive impairment clusters compared with the mild cluster, including IL-6 concentration, which was increased in both comparisons (n=626 participants). We found a substantial deficit in median EQ-5D-5L utility index from before COVID-19 (retrospective assessment; 0·88 [IQR 0·74-1·00]), at 5 months (0·74 [0·64-0·88]) to 1 year (0·75 [0·62-0·88]), with minimal improvements across all outcome measures at 1 year after discharge in the whole cohort and within each of the four clusters.

INTERPRETATION

The sequelae of a hospital admission with COVID-19 were substantial 1 year after discharge across a range of health domains, with the minority in our cohort feeling fully recovered. Patient-perceived health-related quality of life was reduced at 1 year compared with before hospital admission. Systematic inflammation and obesity are potential treatable traits that warrant further investigation in clinical trials.

FUNDING

UK Research and Innovation and National Institute for Health Research.

Transcervical Fibroid Ablation (TFA) with the Sonata System: Updated Review of a New Paradigm for Myoma Treatment

Purpose of Review

This paper provides an update of the recent evidence related to transcervical fibroid ablation (TFA) with the Sonata® System.

Recent Findings

An additional 27 papers representing over 400 women and more than 800 treated fibroids have been published. These demonstrate consistent, positive results, representing multiple prospective clinical trials, subgroup analyses, health economic analyses, case series, and systematic reviews of TFA. These include a 147-patient prospective clinical trial of TFA (the SONATA Clinical Trial) that demonstrated sustained symptom relief and an 8.2% cumulative reintervention rate through 3 years, a long-term study (VITALITY) confirming durable symptom relief with an 11.8% reintervention rate over > 5 years of mean follow-up, a clinical trial (OPEN) suggesting minimal potential for intrauterine adhesiogenesis post-TFA, preliminary results of a global registry (SAGE), and two subgroup analyses of TFA reporting favorable and safe outcomes in women with large fibroids > 5 cm in diameter. Three comparative health economic studies demonstrate favorable economic outcomes against both myomectomy and hysterectomy. A recent ACOG Practice Bulletin also noted equivalent outcomes for transcervical, laparoscopic, and transvaginal fibroid ablation.

Summary

Accumulated clinical evidence, including systematic reviews and longitudinal prospective clinical trials, continues to confirm the safety and efficacy of TFA in women with symptomatic fibroids, including myomata > 5 cm. As a transcervical treatment modality that can safely address all nonpedunculated uterine fibroid types, the continued evidence base confirms TFA as an innovative and useful treatment option that meets a significant unmet clinical need, including among underserved populations, delivering significant durable reductions in fibroid symptoms.

Application of cross-validation strategies to avoid overestimation of performance of 2D-QSAR models for the prediction of aquatic toxicity of chemical mixtures

The quantitative structure-activity relationship (QSAR) modelling of mixtures is not as simple as that for individual chemicals, and it needs additional care to avoid overestimation of the performance. In this research, we have developed a 2D-QSAR model using only 2D interpretable and reproducible descriptors to predict the aquatic toxicity of mixtures of polar and non-polar narcotic substances present in the environment. Partial least squares (PLS) regression has been used to model the response variable (log 1/EC50 against Photobacterium phosphoreum) and the structural features of 84 binary mixtures of polar and nonpolar narcotic toxicants complying with the Organization of Economic Co-operation and Development (OECD) protocols. The model was cross-validated by mixtures-out and compounds-out cross-validation to nullify the developmental bias. The reliability of prediction of the model has been judged by the Prediction Reliability Indicator (PRI) tool using a newly designed set. The new model is robust, reproducible, extremely predictive, easily interpretable, and can be used for reliable prediction of aquatic toxicity of any untested chemical mixtures within the applicability domain. We have additionally used a machine learning-based chemical read-across algorithm in this study to improve the quality of predictions for the toxicity of the mixtures with the modelled descriptors.

Identification of potential antivirals against 3CLpro enzyme for the treatment of SARS-CoV-2: A multi-step virtual screening study

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) outbreak is posing a serious public health threat worldwide in the form of COVD-19. Herein, we have performed two-dimensional quantitative structure-activity relationship (2D-QSAR) and three-dimensional pharmacophore modelling analysis employing inhibitors of 3-chymotrypsin-like protease (3CLpro), the leading protease that is crucial for the replication of SARS-CoV-2. The investigation aims to identify the important structural features responsible for the enzyme inhibition and the search for novel 3CLpro enzyme inhibitors as effective therapeutics for treating SARS-CoV-2. Furthermore, we carried out molecular docking studies using the most and least active compounds in the dataset, aiming to validate the contributions of various features as appeared in the QSAR models. Later, the stringently validated 2D-QSAR model was used to estimate the 3CLpro inhibitory activity of compounds from five chemical databases. Compounds with the significant predicted activity were then subjected to pharmacophore-based virtual screening to screen the top-rated compounds, which were then further subjected to molecular docking analysis, absorption, distribution, metabolism, excretion - toxicity (ADMET) profiling, and molecular dynamics (MD) simulation. The multi-step virtual screening analyses suggested that compounds CASAntiV-865453-58-3, CASAntiV-865453-40-3, and CASAntiV-2043031-84-9 could be used as effective therapeutic agents for the treatment of SARS-CoV-2.

QSAR modelling of organic dyes for their acute toxicity in Daphnia magna using 2D-descriptors

The present study reports quantitative structure-activity relationship (QSAR) models for 22 organic dyes spanning a broad chemical domain to predict their toxicity in Daphnia magna [log (1/EC₅₀)]. Only two-dimensional descriptors with clear physicochemical meaning were used to construct the QSAR models. The process of development, validation, and interpretation of models adheres to the stringent recommendations of the Organization for Economic Cooperation and Development (OECD) guidelines. In this study, the multi-layered stepwise regression method and linear discriminant analysis (LDA) method were employed for the deployment of regression - and classification-based models respectively; however, the final regression-based QSAR models were obtained through the partial least squares (PLS) regression. Additionally, the applicability domain of the developed models was verified. The constructed models should be applicable in the absence of toxicity data of new or untested dye structures, particularly when the compounds fall within the developed models' scope, and also implementable to develop more environmentally friendly alternatives.

1664 A rare case of Stenotrophomas maltophilia affecting an ACL Endobutton: A Case Report and Review of the literature

Background

Stenotrophomas maltophilia (SM) is a ubiquitous opportunistic gram-negative bacillus known to cause hospital acquired infections, commonly in immunosuppressed individuals. However, occurrence of this microorganism is rarely reported in the musculoskeletal system. We report a case of a young healthy man with recurrent knee swelling caused by SM. This organism has been reported to form biofilms over orthopaedic implants, with increased resistance to antibiotic therapy, making it difficult to eradicate once established.

Case Report

A 34-year-old man with psoriasis and asthma presented with right knee swelling and pain, and no history of preceding trauma or fever. He has a past surgical history of anterior cruciate ligament tear and underwent reconstruction with an endobutton two years prior, and a lateral meniscal repair treated in the previous year. At presentation, he was apyrexial and was noted to have a moderate right knee effusion. Initial radiographic imaging identified a large joint effusion with no obvious evidence of bone destruction, laboratory studies also showed a raised white cell count of 11.4 *10^9/L, C-reactive protein of 54mg/L and aspiration cultures were negative. He subsequently underwent numerous washouts, and removal of endobutton with open synovial biopsy which showed SM. The organism was sensitive to cotrimoxazole. The patient had appropriate antibiotics with resolution of symptoms, however he still presented with recurrence.

Conclusions

The persistence of SM despite intervention makes it difficult to treat. Although a rare organism, surgeons should consider it as a differential in recurring knee effusion with orthopaedic implants, and institute early and appropriate management for best outcomes.

QSPR modelling for investigation of different properties of aminoglycoside-derived polymers using 2D descriptors

The quantitative structure-property relationship (QSPR) method is commonly used to predict different physicochemical characteristics of interest of chemical compounds with an objective to accelerate the process of design and development of novel chemical compounds in the biotechnology and healthcare industries. In the present report, we have employed a QSPR approach to predict the different properties of the aminoglycoside-derived polymers (i.e. polymer DNA binding and aminoglycoside-derived polymers mediated transgene expression). The final QSPR models were obtained using the partial least squares (PLS) regression approach using only specific categories of two-dimensional descriptors and subsequently evaluated considering different internationally accepted validation metrics. The proposed models are robust and non-random, demonstrating excellent predictive ability using test set compounds. We have also developed different kinds of consensus models using several validated individual models to improve the prediction quality for external set compounds. The present findings provide new insight for exploring the design of an aminoglycoside-derived polymer library based on different identified physicochemical properties as well as predict their property before their synthesis.

TRAF6-IRF5 kinetics, TRIF, and biophysical factors drive synergistic innate responses to particle-mediated MPLA-CpG co-presentation

Innate immune responses to pathogens are driven by co-presentation of multiple pathogen-associated molecular patterns (PAMPs). Combinations of PAMPs can trigger synergistic immune responses, but the underlying molecular mechanisms of synergy are poorly understood. Here, we used synthetic particulate carriers co-loaded with monophosphoryl lipid A (MPLA) and CpG as pathogen-like particles (PLPs) to dissect the signaling pathways responsible for dual adjuvant immune responses. PLP-based co-delivery of MPLA and CpG to GM-CSF-driven mouse bone marrow-derived antigen-presenting cells (BM-APCs) elicited synergistic interferon-β (IFN-β) and interleukin-12p70 (IL-12p70) responses, which were strongly influenced by the biophysical properties of PLPs. Mechanistically, we found that MyD88 and interferon regulatory factor 5 (IRF5) were necessary for IFN-β and IL-12p70 production, while TRIF signaling was required for the synergistic response. Both the kinetics and magnitude of downstream TRAF6 and IRF5 signaling drove the synergy. These results identify the key mechanisms of synergistic Toll-like receptor 4 (TLR4)-TLR9 co-signaling in mouse BM-APCs and underscore the critical role of signaling kinetics and biophysical properties on the integrated response to combination adjuvants.

Improving Resident Self-Efficacy in Tracheostomy Management Using a Novel Curriculum

INTRODUCTION

Patients receiving pediatric tracheostomy have significant risk for mortality due to compromised airway. Timely management of airway emergencies in children with tracheostomies is an important clinical skill for pediatricians. We developed this curriculum to improve residents' self-efficacy with tracheostomy management.

METHODS

We collected baseline data on 67 residents from two hospitals while creating a blended curriculum with video-based instruction on routine tracheostomy change and team management of tracheostomy emergency. Forty residents enrolled in the curriculum. During an ICU rotation, they received face-to-face instruction on routine tracheostomy change in small groups, followed by assessment of managing a tracheostomy emergency during a simulation. A video completed prior to the simulation took 9 minutes, the routine tracheostomy change didactic session took 15 minutes, and the simulation instruction was completed in 10-15 minutes. We collected feedback on the effectiveness of the curriculum from the participants.

RESULTS

All 107 residents from the baseline and intervention groups completed the self-efficacy survey. The intervention group had significantly higher changes in scores across all self-efficacy domains than the baseline group. On the curriculum feedback survey, residents rated the curriculum very highly, between 4.4 and 4.8 on a 5-point Likert scale.

DISCUSSION

Our blended curriculum increased learners' self-efficacy and promoted learner competence in tracheostomy management. Residents scored more than 80% across all aspects of simulation assessment and reported higher self-efficacy scores following our curricular intervention.

Using digital health technology to evaluate the impact of chocolate on blood pressure: Results from the COCOA-BP study

Background

High blood pressure (BP) is a major risk factor for cardiovascular disease (CVD). Consumption of dark chocolate, which is high in flavonoids that may reduce CVD risk, is an attractive intervention to reduce to BP. Additionally, the use of mobile health (mHealth) technologies (eg, telehealth, smartphones, and wearable devices) can improve outcomes in patients with CVD.

Objective

The purpose of this study was to investigate the impact of dark chocolate intake on BP, subject use of mHealth, and integration of mHealth into a clinical trial.

Methods

The COCOA-BP (ChOcolate COnsumption And Blood Pressure) study was a prospective, single-center, pre-/postintervention study that enrolled 62 healthy volunteers. The study consisted of 3 phases: smartwatch/smart BP monitor familiarization and washout from chocolate (week 1); control (week 2); and intervention (weeks 3 and 4). During the intervention phase, subjects consumed 50 g of dark chocolate per day. The primary endpoint was change in resting systolic BP between the intervention and control phases. Additional endpoints included device accuracy and correlation with physical activity.

Results

Mean resting systolic BP was 116.4 mm Hg before chocolate intake among 62 participants (mean age 37 years; 61% female). After chocolate intake, mean resting systolic BP was 116.0 mm Hg (difference –0.4; P = .69). These findings suggest that 2 weeks of dark chocolate intake did not reduce resting systolic BP. There was poor agreement between mHealth device and standard (nurse-performed) measurements.

Conclusion

In this study, short-term dark chocolate intake did not seem to reduce BP. mHealth technology shows great potential for use in clinical studies, but challenges related to device accuracy and compliance need to be addressed.

Development of a simple, interpretable and easily transferable QSAR model for quick screening antiviral databases in search of novel 3C-like protease (3CLpro) enzyme inhibitors against SARS-CoV diseases

In the context of recently emerged pandemic of COVID-19, we have performed two-dimensional quantitative structure-activity relationship (2D-QSAR) modelling using SARS-CoV-3CLpro enzyme inhibitors for the development of a multiple linear regression (MLR) based model. We have used 2D descriptors with an aim to develop an easily interpretable, transferable and reproducible model which may be used for quick prediction of SAR-CoV-3CLpro inhibitory activity for query compounds in the screening process. Based on the insights obtained from the developed 2D-QSAR model, we have identified the structural features responsible for the enhancement of the inhibitory activity against 3CLpro enzyme. Moreover, we have performed the molecular docking analysis using the most and least active molecules from the dataset to understand the molecular interactions involved in binding, and the results were then correlated with the essential structural features obtained from the 2D-QSAR model. Additionally, we have performed in silico predictions of SARS-CoV 3CLpro enzyme inhibitory activity of a total of 50,437 compounds obtained from two anti-viral drug databases (CAS COVID-19 antiviral candidate compound database and another recently reported list of prioritized compounds from the ZINC15 database) using the developed model and provided prioritized compounds for experimental detection of their performance for SARS-CoV 3CLpro enzyme inhibition.

Exploring 2D-QSAR for prediction of beta-secretase 1 (BACE1) inhibitory activity against Alzheimer's disease

We have developed a robust quantitative structure-activity relationship (QSAR) model employing a dataset of 98 heterocycle compounds to identify structural features responsible for BACE1 (beta-secretase 1) enzyme inhibition. We have used only 2D descriptors for model development purpose thus avoiding the conformational complications arising due to 3D geometry considerations. Following the strict Organization for Economic Co-operation and Development (OECD) guidelines, we have developed models using stepwise regression analysis followed by the best subset selection, while the final model was developed by partial least squares regression technique. The model was validated using various internationally accepted stringent validation parameters. From the insights obtained from the developed model, we have concluded that heteroatoms (nitrogen, oxygen, etc.) present within to an aromatic nucleus and the structural features such as hydrophobic, ring aromatic and hydrogen bond acceptor/donor are responsible for the enhancement of the BACE1 enzyme inhibitory activity. Moreover, we have performed the pharmacophore modelling to unveil the structural requirements for the inhibitory activity against the BACE1 enzyme. Furthermore, molecular docking studies were carried out to understand the molecular interactions involved in binding, and the results are then correlated with the requisite structural features obtained from the QSAR and pharmacophore models.

Ecotoxicological QSAR modelling of organic chemicals against Pseudokirchneriella subcapitata using consensus predictions approach

The present study provides robust consensus quantitative structure-activity relationship (QSAR) models developed from 334 organic chemicals covering a wide chemical domain for the prediction of effective concentrations of chemicals for 50% and 10% inhibition of algal growth. Only 2D descriptors with definite physicochemical meaning were employed for QSAR model building, whereas development, validation and interpretation were achieved following the strict Organization for Economic Co-operation and Development (OECD) recommended guidelines. Genetic algorithm along with stepwise approach was used in feature selection while the final QSAR models were derived using partial least squares regression technique. The applicability domain of the developed models was also checked. The obtained consensus models were then used to predict 64 organic chemicals having no definite observed responses while the confidence of predictions was checked by the 'prediction reliability indicator' tool. The developed models should be applicable for data gap filling in case of new or untested organic chemicals provided they fall within the domain of the model and can also be implemented to design safer alternatives to the environment.

Consensus QSPR modelling for the prediction of cellular response and fibrinogen adsorption to the surface of polymeric biomaterials

In the current study, we have developed predictive quantitative structure-activity relationship (QSAR) models for cellular response (foetal rate lung fibroblast proliferation) and protein adsorption (fibrinogen adsorption (FA)) on the surface of tyrosine-derived biodegradable polymers designed for tissue engineering purpose using a dataset of 66 and 40 biodegradable polymers, respectively, employing two-dimensional molecular descriptors. Best four individual models have been selected for each of the endpoints. These models are developed using partial least squares regression with a unique combination of six and four descriptors for cellular response and protein adsorption, respectively. The generated models were strictly validated using internal and external metrics to determine the predictive ability and robustness of proposed models. Subsequently, the validated individual models for each response endpoints were used for the generation of 'intelligent' consensus models ( http://teqip.jdvu.ac.in/QSAR_Tools/DTCLab/ ) to improve the quality of predictions for the external data set. These models may help in prediction of virtual polymer libraries for rational design/optimization for properties relevant to biomedical applications prior to their synthesis.

QSPR modelling for prediction of glass transition temperature of diverse polymers

The glass transition temperature is a vital property of polymers with a direct impact on their stability. In the present study, we built quantitative structure-property relationship models for the prediction of the glass transition temperatures of polymers using a data set of 206 diverse polymers. Various 2D molecular descriptors were computed from the single repeating units of polymers. We derived five models from different combinations of six descriptors in each case by employing the double cross-validation technique followed by partial least squares regression. The selected models were subsequently validated by methods such as cross-validation, external validation using test set compounds, the Y-randomization (Y-scrambling) test and an applicability domain study of the developed models. All of the models have statistically significant metric values such as r² ranging from 0.713-0.759, Q² ranging from 0.662-0.724 and [Formula: see text] ranging 0.702-0.805. Finally, a comparison was made with recently published models, though the previous models were based on a much smaller data set with limited diversity. We also used a true external set to demonstrate the performance of our developed models, which may be used for the prediction and design of novel polymers prior to their synthesis.

Extinction risk in extant marine species integrating palaeontological and biodistributional data

Extinction risk assessments of marine invertebrate species remain scarce, which hinders effective management of marine biodiversity in the face of anthropogenic impacts. To help close this information gap, in this paper we provide a metric of relative extinction risk that combines palaeontological data, in the form of extinction rates calculated from the fossil record, with two known correlates of risk in the modern day: geographical range size and realized thermal niche. We test the performance of this metric-Palaeontological Extinction Risk In Lineages (PERIL)-using survivorship analyses of Pliocene bivalve faunas from California and New Zealand, and then use it to identify present-day hotspots of extinction vulnerability for extant shallow-marine Bivalvia. Areas of the ocean where concentrations of bivalve species with higher PERIL scores overlap with high levels of climatic or anthropogenic stressors should be considered of most immediate concern for both conservation and management.

Greener chemicals for the future: QSAR modelling of the PBT index using ETA descriptors

Persistent, bioaccumulative and toxic (PBT) chemicals symbolize a group of substances that are not easily degraded; instead, they accumulate in different organisms and exhibit an acute or chronic toxicity. The limited empirical data on PBT chemicals, the high cost of testing together with the regulatory constraints and the international push for reduced animal testing motivate a greater reliance on predictive computational methods like quantitative structure-activity relationship (QSAR) models in PBT assessment. Papa and Gramatica have recently proposed a PBT index that could be computed directly from structural features. In the current study, we have modelled the experimentally derived PBT index data using an extended topological atom (ETA) along with constitutional descriptors to show the usefulness of the ETA indices in modelling the endpoint. The models developed through a double cross-validation (DCV) method gave the best results in terms of both internal and external validation metrics. The developed models were comparable in predictive quality to those previously reported. The current models were further used for consensus predictions of PBT behaviour for a set of pharmaceuticals and a set of synthetic drug-like compounds. The developed models can be used in PBT hazard screening for identification and prioritization of chemicals from the structural information alone.

Molecular and epidemiological evidence of patient-to-patient hepatitis C virus transmission in a Scottish emergency department

BACKGROUND

Transmission of hepatitis C virus (HCV) in the healthcare setting is rare. Routine infection prevention and control measures mean that this should be a preventable 'never event'.

AIM

To investigate the diagnosis of acute healthcare-associated HCV infection.

METHODS

Epidemiological and molecular investigation of a case of acute HCV infection associated with nosocomial exposure.

FINDINGS

Detailed investigation of the treatment history of a patient with acute HCV infection identified transmission from a co-attending patient in an emergency department as the likely source; this possibility was confirmed by virus sequence analysis. The precise route of transmission was not identified, though both patient and source had minimally invasive healthcare interventions. Review of infection, prevention and control identified potentially contributory factors in the causal pathway including hand hygiene, inappropriate use of personal protective equipment, and blood contamination of the surface of the departmental blood gas analyser.

CONCLUSION

We provide molecular and epidemiological evidence of HCV transmission between patients in an emergency department that was made possible by environmental contamination. Patients with HCV infection are higher users of emergency care than the general population and a significant proportion of those affected remain unknown and/or infectious. Equipment, departmental design, staff behaviour, and patient risk require regular review to minimize the risk of nosocomial HCV transmission.

Ecotoxicological modelling of cosmetics for aquatic organisms: A QSTR approach

In this study, externally validated quantitative structure-toxicity relationship (QSTR) models were developed for toxicity of cosmetic ingredients on three different ecotoxicologically relevant organisms, namely Pseudokirchneriella subcapitata, Daphnia magna and Pimephales promelas following the OECD guidelines. The final models were developed by partial least squares (PLS) regression technique, which is more robust than multiple linear regression. The obtained model for P. subcapitata shows that molecular size and complexity have significant impacts on the toxicity of cosmetics. In case of P. promelas and D. magna, we found that the largest contribution to the toxicity was shown by hydrophobicity and van der Waals surface area, respectively. All models were validated using both internal and test compounds employing multiple strategies. For each QSTR model, applicability domain studies were also performed using the "Distance to Model in X-space" method. A comparison was made with the ECOSAR predictions in order to prove the good predictive performances of our developed models. Finally, individual models were applied to predict toxicity for an external set of 596 personal care products having no experimental data for at least one of the endpoints, and the compounds were ranked based on a decreasing order of toxicity using a scaling approach.

Exploring the structural requirements in multiple chemical scaffolds for the selective inhibition of Plasmodium falciparum calcium-dependent protein kinase-1 (PfCDPK-1) by 3D-pharmacophore modelling, and docking studies

Current research on antimalarial protein kinases has provided an opportunity to design kinase-based antimalarial drugs. We have developed a common feature-based pharmacophore model from a set of multiple chemical scaffolds including derivatives of 3,6-imidazopyridazines, pyrazolo[2,3-d]pyrimidines and imidazo[1,5-a]pyrazines, in order to incorporate the maximum structural diversity information in the model for the Plasmodium falciparum calcium-dependent protein kinase-1 (PfCDPK-1) target. The best pharmacophore model (Hypo-1) with the essential features of two hydrogen bond donors (HBD), one hydrophobic aromatic (HYAr) and one ring aromatic (RA) showed the classification accuracies of 86.27%, 78.43% and 100.00% in labelling the training and test set (test set-1 and test set-2) compounds into more active and less active classes. In order to identify the crucial interaction between multiple scaffold ligands and the target protein, we first developed the homology model using a template structure of P. bergheii (PbCDPK1; PDB ID: 3Q5I), and thereafter performed the docking studies. The residues such as Lys85, Phe147, Tyr148, Leu198, Val211, and Asp212 were found to be the most important interacting residues for possessing PfCDPK-1 inhibitory activity.

Current State of Bioabsorbable Polymer-Coated Drug-Eluting Stents

Drug-eluting stents (DES) have been shown to significantly reduce clinical and angiographic restenosis compared to bare metal stents (BMS). The polymer coatings on DES elute antiproliferative drugs to inhibit intimal proliferation and prevent restenosis after stent implantation. Permanent polymers which do not degrade in vivo may increase the likelihood of stent-related delayed arterial healing or polymer hypersensitivity. In turn, these limitations may contribute to an increased risk of late clinical events. Intuitively, a polymer which degrades after completion of drug release, leaving an inert metal scaffold in place, may improve arterial healing by removing a chronic source of inflammation, neoatherosclerosis, and/or late thrombosis. In this way, a biodegradable polymer may reduce late ischemic events. Additionally, improved healing after stent implantation could reduce the requirement for long-term dual antiplatelet therapy and the associated risk of bleeding and cost. This review will focus on bioabsorbable polymer-coated DES currently being evaluated in clinical trials.

Erratum to: 36th International Symposium on Intensive Care and Emergency Medicine: Brussels, Belgium. 15-18 March 2016

[This corrects the article DOI: 10.1186/s13054-016-1208-6.].

Pharmacophore generation, atom-based 3D-QSAR, HQSAR and activity cliff analyses of benzothiazine and deazaxanthine derivatives as dual A2A antagonists/MAO‑B inhibitors

Dual inhibition of A_2A and MAO-B is an emerging strategy in neurodegenerative diseases, such as Alzheimer's disease (AD) and Parkinson's disease (PD). In this study, atom-based three-dimensional quantitative structure-activity relationship (3D-QSAR) and hologram quantitative structure-activity relationship (HQSAR) models were generated with benzothiazine and deazaxanthine derivatives. Based on activity against A_2A and MAO-B, two statistically significant 3D-QSAR models (r² = 0.96, q² = 0.76 and r² = 0.91, q² = 0.63) and HQSAR models (r² = 0.93, q² = 0.68 and r² = 0.97, q² = 0.58) were developed. In an activity cliff analysis, structural outliers were identified by calculating the Mahalanobis distance for a pair of compounds with A_2A and MAO-B inhibitory activities. The generated 3D-QSAR and HQSAR models, activity cliff analysis, molecular docking and dynamic studies for dual target protein inhibitors provide key structural scaffolds that serve as building blocks in designing drug-like molecules for neurodegenerative diseases.

Comparative activities of milk components in reversing chronic colitis

Inflammatory bowel disease (IBD) is a poorly understood chronic immune disorder for which there is no medical cure. Milk and colostrum are rich sources of bioactives with immunomodulatory properties. Here we compared the therapeutic effects of oral delivery of bovine milk-derived iron-saturated lactoferrin (Fe-bLF), angiogenin, osteopontin (OPN), colostrum whey protein, Modulen IBD (Nestle Healthsciences, Rhodes, Australia), and cis-9,trans-11 conjugated linoleic acid (CLA)-enriched milk fat in a mouse model of dextran sulfate-induced colitis. The CLA-enriched milk fat significantly increased mouse body weights after 24d of treatment, reduced epithelium damage, and downregulated the expression of proinflammatory cytokines and nitrous oxide. Modulen IBD most effectively decreased the clinical score at d 12, and Modulen IBD and OPN most effectively lowered the inflammatory score. Myeloperoxidase activity that denotes neutrophil infiltration was significantly lower in mice fed Modulen IBD, OPN, angiogenin, and Fe-bLF. A significant decrease in the numbers of T cells, natural killer cells, dendritic cells, and a significant decrease in cytokine expression were observed in mice fed the treatment diets compared with dextran sulfate administered mice. The Fe-bLF, CLA-enriched milk fat, and Modulen IBD inhibited intestinal angiogenesis. In summary, each of the milk components attenuated IBD in mice, but with differing effectiveness against specific disease parameters.