Prediction of Postprandial Glycemic Exposure Utility of fasting and 2-h glucose measurements alone and in combination with assessment of body composition, fitness, and strength

OBJECTIVE —To determine the best predictors of total postprandial glycemic exposure and peak glucose concentrations in nondiabetic humans. RESEARCH DESIGN AND METHODS —Data from 203 nondiabetic volunteers who ingested a carbohydrate-containing mixed meal were analyzed. RESULTS —Fasting glucose and insulin concentrations were poor predictors of postprandial glucose area above basal ( R 2 = ∼0.07, P < 0.001). The correlation was stronger for 2-h glucose concentration ( R 2 = 0.55, P < 0.001) and improved slightly but significantly ( P < 0.001) with the addition of fasting glucose, insulin, age, sex, and body weight to the model ( r 2 = 0.58). The 2-h glucose concentration also predicted the peak glucose concentration ( R 2 = 0.37, P < 0.001) with strength of the prediction increasing ( P < 0.001) modestly with the addition of fasting glucose, insulin, age, sex, and body weight to the model ( R 2 = 0.48, P < 0.001). On the other hand, addition of measures of body function and composition did not improve prediction of total glycemic exposure or peak glucose concentration. CONCLUSIONS —Isolated measures of fasting or 2-h glucose concentrations alone or in combination with more complex measures of body composition and function are poor predictors of postprandial glycemic exposure or peak glucose concentration. This may explain, at least in part, the weak and at times inconsistent relationship between these parameters and cardiovascular risk

Identification of protein-protein interactions of human HtrA1.

The human heat shock protein HtrA1, a member of the HtrA family of serine proteases, is a evolutionarily highly conserved factor which displays a widespread pattern of expression. The yeast two-hybrid technique was employed to identify new cellular proteins physically interacting with HtrA1, and thus potential targets of this serine protease. An enzymatically inactive HtrA1 point mutant, HtrA1-S328A, was generated and used as bait in a yeast two-hybrid system. Fifty-two plasmids were isolated from primary positive yeast clones. Subsequent sequencing and BLAST analysis revealed cDNAs encoding for 13 different proteins. These putative binding partners of HtrA1 appeared to be a) components of extracellular matrix; b) factors related to signal pathways, and c) unknown proteins. Among the 13 positive clones identified and reported here, it is worth of note that the interaction of HtrA1 with tubulin and collagen (extracellular matrix proteins) and with tuberin (cytoplasmic protein) is confirmed by other studies, and this further supports previous findings in which HtrA1 can be found active as an intracytoplasmic protein or as secreted protein as well

Novel risk stratification algorithm for estimating the risk of death in patients with relapsed multiple myeloma: external validation in a retrospective chart review.

OBJECTIVES AND DESIGN: A novel risk stratification algorithm estimating risk of death in patients with relapsed multiple myeloma starting second-line treatment was recently developed using multivariable Cox regression of data from a Czech registry. It uses 16 parameters routinely collected in medical practice to stratify patients into four distinct risk groups in terms of survival expectation. To provide insight into generalisability of the risk stratification algorithm, the study aimed to validate the risk stratification algorithm using real-world data from specifically designed retrospective chart audits from three European countries. PARTICIPANTS AND SETTING: Physicians collected data from 998 patients (France, 386; Germany, 344; UK, 268) and applied the risk stratification algorithm. METHODS: The performance of the Cox regression model for predicting risk of death was assessed by Nagelkerke's R2, goodness of fit and the C-index. The risk stratification algorithm's ability to discriminate overall survival across four risk groups was evaluated using Kaplan-Meier curves and HRs. RESULTS: Consistent with the Czech registry, the stratification performance of the risk stratification algorithm demonstrated clear differentiation in risk of death between the four groups. As risk groups increased, risk of death doubled. The C-index was 0.715 (95% CI 0.690 to 0.734). CONCLUSIONS: Validation of the novel risk stratification algorithm in an independent 'real-world' dataset demonstrated that it stratifies patients in four subgroups according to survival expectation

An Explainable AI System for Automated COVID-19 Assessment and Lesion Categorization from CT-scans

COVID-19 infection caused by SARS-CoV-2 pathogen is a catastrophic pandemic outbreak all over the world with exponential increasing of confirmed cases and, unfortunately, deaths. In this work we propose an AI-powered pipeline, based on the deep-learning paradigm, for automated COVID-19 detection and lesion categorization from CT scans. We first propose a new segmentation module aimed at identifying automatically lung parenchyma and lobes. Next, we combined such segmentation network with classification networks for COVID-19 identification and lesion categorization. We compare the obtained classification results with those obtained by three expert radiologists on a dataset consisting of 162 CT scans. Results showed a sensitivity of 90\% and a specificity of 93.5% for COVID-19 detection, outperforming those yielded by the expert radiologists, and an average lesion categorization accuracy of over 84%. Results also show that a significant role is played by prior lung and lobe segmentation that allowed us to enhance performance by over 20 percent points. The interpretation of the trained AI models, moreover, reveals that the most significant areas for supporting the decision on COVID-19 identification are consistent with the lesions clinically associated to the virus, i.e., crazy paving, consolidation and ground glass. This means that the artificial models are able to discriminate a positive patient from a negative one (both controls and patients with interstitial pneumonia tested negative to COVID) by evaluating the presence of those lesions into CT scans. Finally, the AI models are integrated into a user-friendly GUI to support AI explainability for radiologists, which is publicly available at http://perceivelab.com/covid-ai

Bone safety of dual-release hydrocortisone in patients with autoimmune primary adrenal insufficiency

BackgroundConventional glucocorticoids (C-GC) replacement regimens have a detrimental effect on skeletal health in patients with adrenal insufficiency (AI), ultimately leading to an increased fracture risk. The novel dual-release hydrocortisone (DR-HC) formulations are characterized by a more favourable safety profile on various clinical endpoints. Data comparing the impact of C-GC and DR-HC on bone, however, are scarce.MethodsTwenty-seven patients with autoimmune primary AI (PAI; 13 treated with C-GC and 14 treated with DR-HC) were evaluated to compare bone-related parameters between the two treatment groups.ResultsNo significant differences between the two treatments groups were observed with respect to bone turnover markers. Patients treated with C-GC showed a lower bone mineral density (BMD) at lumbar spine (LS; 0.791 ± 0.195 vs. 0.942 ± 0.124 g/cm2, p=0.025) and at femoral neck (FN; 0.633 ± 0.114 vs. 0.716 ± 0.088 g/cm2, p=0.045). Moreover, they were characterized by a lower trabecular bone score (TBS; 1.236 ± 0.035 vs. 1.383 ± 0.030, p=0.004) and by a higher mean number of vertebral fractures per patient (0.75 vs. 0 fractures, p=0.002). TBS was the best predictor of fracture risk, with a pseudo-R2 of 0.593; moreover, at mediation analysis, it was able to fully explain the observed detrimental effect of C-GC, compared to DR-HC, on fracture risk.ConclusionsThese results suggest that DR-HC is associated with less bone-related complications compared to C-GC in patients with PAI. Moreover, TBS seems to play a pivotal role in the mediation of the relationship between glucocorticoid treatment regimens and fracture risk

Global assessment of marine plastic exposure risk for oceanic birds

Plastic pollution is distributed patchily around the world’s oceans. Likewise, marine organisms that are vulnerable to plastic ingestion or entanglement have uneven distributions. Understanding where wildlife encounters plastic is crucial for targeting research and mitigation. Oceanic seabirds, particularly petrels, frequently ingest plastic, are highly threatened, and cover vast distances during foraging and migration. However, the spatial overlap between petrels and plastics is poorly understood. Here we combine marine plastic density estimates with individual movement data for 7137 birds of 77 petrel species to estimate relative exposure risk. We identify high exposure risk areas in the Mediterranean and Black seas, and the northeast Pacific, northwest Pacific, South Atlantic and southwest Indian oceans. Plastic exposure risk varies greatly among species and populations, and between breeding and nonbreeding seasons. Exposure risk is disproportionately high for Threatened species. Outside the Mediterranean and Black seas, exposure risk is highest in the high seas and Exclusive Economic Zones (EEZs) of the USA, Japan, and the UK. Birds generally had higher plastic exposure risk outside the EEZ of the country where they breed. We identify conservation and research priorities, and highlight that international collaboration is key to addressing the impacts of marine plastic on wide-ranging speciespublishedVersio

Global assessment of marine plastic exposure risk for oceanic birds

Plastic pollution is distributed patchily around the world’s oceans. Likewise, marine organisms that are vulnerable to plastic ingestion or entanglement have uneven distributions. Understanding where wildlife encounters plastic is crucial for targeting research and mitigation. Oceanic seabirds, particularly petrels, frequently ingest plastic, are highly threatened, and cover vast distances during foraging and migration. However, the spatial overlap between petrels and plastics is poorly understood. Here we combine marine plastic density estimates with individual movement data for 7137 birds of 77 petrel species to estimate relative exposure risk. We identify high exposure risk areas in the Mediterranean and Black seas, and the northeast Pacific, northwest Pacific, South Atlantic and southwest Indian oceans. Plastic exposure risk varies greatly among species and populations, and between breeding and non-breeding seasons. Exposure risk is disproportionately high for Threatened species. Outside the Mediterranean and Black seas, exposure risk is highest in the high seas and Exclusive Economic Zones (EEZs) of the USA, Japan, and the UK. Birds generally had higher plastic exposure risk outside the EEZ of the country where they breed. We identify conservation and research priorities, and highlight that international collaboration is key to addressing the impacts of marine plastic on wide-ranging species

Global assessment of marine plastic exposure risk for oceanic birds

Plastic pollution is distributed patchily around the world's oceans. Likewise, marine organisms that are vulnerable to plastic ingestion or entanglement have uneven distributions. Understanding where wildlife encounters plastic is crucial for targeting research and mitigation. Oceanic seabirds, particularly petrels, frequently ingest plastic, are highly threatened, and cover vast distances during foraging and migration. However, the spatial overlap between petrels and plastics is poorly understood. Here we combine marine plastic density estimates with individual movement data for 7137 birds of 77 petrel species to estimate relative exposure risk. We identify high exposure risk areas in the Mediterranean and Black seas, and the northeast Pacific, northwest Pacific, South Atlantic and southwest Indian oceans. Plastic exposure risk varies greatly among species and populations, and between breeding and non-breeding seasons. Exposure risk is disproportionately high for Threatened species. Outside the Mediterranean and Black seas, exposure risk is highest in the high seas and Exclusive Economic Zones (EEZs) of the USA, Japan, and the UK. Birds generally had higher plastic exposure risk outside the EEZ of the country where they breed. We identify conservation and research priorities, and highlight that international collaboration is key to addressing the impacts of marine plastic on wide-ranging species.B.L.C., C.H., and A.M. were funded by the Cambridge Conservation Initiative’s Collaborative Fund sponsored by the Prince Albert II of Monaco Foundation. E.J.P. was supported by the Natural Environment Research Council C-CLEAR doctoral training programme (Grant no. NE/S007164/1). We are grateful to all those who assisted with the collection and curation of tracking data. Further details are provided in the Supplementary Acknowledgements. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.Peer reviewe

Global assessment of marine plastic exposure risk for oceanic birds

Plastic pollution is distributed patchily around the world’s oceans. Likewise, marine organisms that are vulnerable to plastic ingestion or entanglement have uneven distributions. Understanding where wildlife encounters plastic is crucial for targeting research and mitigation. Oceanic seabirds, particularly petrels, frequently ingest plastic, are highly threatened, and cover vast distances during foraging and migration. However, the spatial overlap between petrels and plastics is poorly understood. Here we combine marine plastic density estimates with individual movement data for 7137 birds of 77 petrel species to estimate relative exposure risk. We identify high exposure risk areas in the Mediterranean and Black seas, and the northeast Pacific, northwest Pacific, South Atlantic and southwest Indian oceans. Plastic exposure risk varies greatly among species and populations, and between breeding and non-breeding seasons. Exposure risk is disproportionately high for Threatened species. Outside the Mediterranean and Black seas, exposure risk is highest in the high seas and Exclusive Economic Zones (EEZs) of the USA, Japan, and the UK. Birds generally had higher plastic exposure risk outside the EEZ of the country where they breed. We identify conservation and research priorities, and highlight that international collaboration is key to addressing the impacts of marine plastic on wide-ranging species