42 research outputs found
Classifying Smoking Urges Via Machine Learning
Smoking is the largest preventable cause of death and diseases in the developed world, and advances in modern electronics and machine learning can help us deliver therapies to smokers in novel ways. If a mobile device monitoring a smoker's situation could detect when the smoker is likely to have an urge to smoke, it would be helpful for optimizing the timing of real-time intervention. In this thesis, we examine different machine learning approaches to use situational features associated with having or not having urges to smoke during a quit attempt in order to accurately classify high-urge states. To test our machine learning approaches --specifically naive Bayes, discriminant analysis and decision tree learning methods-- we used a dataset collected from over 300 participants who had recently initiated a quit attempt. The three classification approaches are evaluated observing sensitivity, specificity, accuracy and precision. The outcome of the analysis showed that algorithms based on feature selection make it possible to obtain high classification rates with only a few features selected from the entire dataset. The classification tree method outperformed the naive Bayes and discriminant analysis methods, with an accuracy of the classifications up to 86%
Combined Liver-Kidney Transplantation With Preformed Anti-human Leukocyte Antigen Donor-Specific Antibodies
Introduction: the impact of preformed donor-specific anti-human leukocyte antigen (HLA) antibodies (pDSAs) after combined liver-kidney transplantation (CLKT) is still uncertain. Methods: we conducted a retrospective study in 8 European high-volume transplant centers and investigated the outcome of 166 consecutive CLKTs, including 46 patients with pDSAs. Results: patient survival was lower in those with pDSAs (5-year patient survival rate of 63% and 78% with or without pDSA, respectively; P = 0.04). The presence of pDSAs with a mean fluorescence intensity (MFI) ≥ 5000 (hazard ratio 4.96; 95% confidence interval: 2.3-10.9; P < 0.001) and the presence of 3 or more pDSAs (hazard ratio 6.5; 95% confidence interval: 2.5-18.8; P = 0.05) were independently associated with death. The death-censored liver graft survival was similar in patients with or without pDSAs. Kidney graft survival was comparable in both groups. (The 1- and 5-year death-censored graft survival rates were 91.6% and 79.5%, respectively, in patients with pDSAs and 93% and 88%, respectively, in the donor-specific antibody [DSA]-negative group, P = not significant). Despite a higher rate of kidney graft rejection in patients with pDSAs (5-year kidney graft survival rate without rejection of 87% and 97% with or without pDSAs, respectively; P = 0.04), kidney function did not statistically differ between both groups at 5 years post-transplantation (estimated glomerular filtration rate 45 ± 17 vs. 57 ± 29 ml/min per 1.73 m2, respectively, in patients with and without pDSAs). Five recipients with pDSAs (11.0%) experienced an antibody-mediated kidney rejection that led to graft loss in 1 patient. Conclusion: our results suggest that CLKT with pDSAs is associated with a lower patients' survival despite good recipients', liver and kidney grafts' outcome
Unraveling the interplay between senescent dermal fibroblasts and cutaneous squamous cell carcinoma cell lines at different stages of tumorigenesis
Forest edge effects on termites in a neotropical rainforest
Termites dominate tropical soils and play a major role in organic mater decomposition, especially in rainforests. However, tropical forests are heavily fragmented which implies a loss of surface as well as an increase in forest edges. The later characterized by different environmental conditions from the interior of the forest. Both factors —fragment area reduction and forest edge increase— are hard to study independently. Here, we investigated the occurrence and depth of edge effects on the termite assemblage in an otherwise continuous neotropical rainforest. Three sites were sampled in the Amazonian rainforest in French Guiana along the almost straight edge of a 90-m wide powerline clearing. Whereas edge effects on other insects such as ants and dung beetles have been reported up to 100-300 m into the interior, neotropical termites were not significantly affected. Soil feeder frequency was not lower near the forest edge although they have an allegedly thinner cuticle and require moist and moist soil. Finally, no variation in beta diversity was found near the edge either. Overall, termites appear as resilient insects against forest edges as long as they do not suffer from fragment size reduction. However, a threefold increase in frequency of an opportunistic pest species (Heterotermes tenuis) was found near the edge. We hypothesize that H. tenuis good adaptability and dispersibility may have allowed it to quickly colonize and dominate this environment before more cryptic species, as has been shown for ants.info:eu-repo/semantics/publishe
PeTriBERT : Augmenting BERT with tridimensional encoding for inverse protein folding and design
Abstract Protein is biology workhorse. Since the recent break-through of novel folding methods, the amount of available structural data is increasing, closing the gap between data-driven sequence-based and structure-based methods. In this work, we focus on the inverse folding problem that consists in predicting an amino-acid primary sequence from protein 3D structure. For this purpose, we introduce a simple Transformer model from Natural Language Processing augmented 3D-structural data. We call the resulting model PeTriBERT: Proteins embedded in tridimensional representation in a BERT model. We train this small 40-million parameters model on more than 350 000 proteins sequences retrieved from the newly available AlphaFoldDB database. Using PetriBert, we are able to in silico generate totally new proteins with a GFP-like structure. These 9 of 10 of these GFP structural homologues have no ressemblance when blasted on the whole entry proteome database. This shows that PetriBert indeed capture protein folding rules and become a valuable tool for de novo protein design
Forest edge effects on termites in a neotropical rainforest
info:eu-repo/semantics/publishe
Impact of the COVID-19 pandemic on liver transplant waitlist outcome in France
Abstract The objective of this study was to investigate the impact of the COVID-19 pandemic on the outcome of patients on the liver transplantation (LT) waitlist in 2020 in France, in particular, the incidence of deaths and delisting for worsening condition, depending on the allocation score component. The 2020 cohort of patients on the waiting list was compared with the 2018/2019 cohorts. 2020 saw fewer LTs than in either 2019 or 2018 (1128, 1356, and 1325, respectively), together with fewer actual brain dead donors (1355, 1729, and 1743). In 2020, deaths or delisting for worsening condition increased significantly versus 2018/2019 (subdistribution hazard ratio 1.4, 95% confidence interval [CI] 1.2–1.7), after adjustment for age, place of care, diabetes, blood type, and score component, although COVID-19-related mortality was low. This increased risk mainly concerned patients with hepatocellular carcinoma (1.52, 95% CI 1.22–1.90), with 650 MELD exception points (2.19, 95% CI 1.08–4.43), and especially those without HCC and MELD scores from 25 to 30 (3.36 [95% CI 1.82–6.18]). In conclusion, by significantly decreasing LT activity in 2020, the COVID-19 pandemic increased the number of waitlist deaths and delisting for worsening condition, and significantly more for particular components of the score, including intermediate severity cirrhosis
Analysis of the pen pressure and grip force signal during basic drawing tasks: The timing and speed changes impact drawing characteristics
International audienceWriting is a complex fine and trained motor skill, involving complex biomechanical and cognitive processes. In this paper, we propose the study of writing kinetics using three angles: the pen-tip normal force, the total grip force signal and eventually writing quality assessment. In order to collect writing kinetics data, we designed a sensor collecting these characteristics simultaneously. Ten healthy right-handed adults were recruited and were asked to perform four tasks: first, they were instructed to draw circles at a speed they considered comfortable; they then were instructed to draw circles at a speed they regarded as fast; afterwards, they repeated the comfortable task compelled to follow the rhythm of a metronome; and eventually they performed the fast task under the same timing constraints. Statistical differences between the tasks were computed, and while pen-tip normal force and total grip force signal were not impacted by the changes introduced in each task, writing quality features were affected by both the speed changes and timing constraint changes. This verifies the already-studied speed-accuracy trade-off and suggest the existence of a timing constraints-accuracy trade-off