34 research outputs found
Machine-learning-aided prediction of brain metastases development in non-small-cell lung cancers
Purpose
Nonâsmall-cell lung cancer (NSCLC) shows a high incidence of brain metastases (BM). Early detection is crucial to improve clinical prospects. We trained and validated classifier models to identify patients with a high risk of developing BM, as they could potentially benefit from surveillance brain MRI.
Methods
Consecutive patients with an initial diagnosis of NSCLC from January 2011 to April 2019 and an in-house chest-CT scan (staging) were retrospectively recruited at a German lung cancer center. Brain imaging was performed at initial diagnosis and in case of neurological symptoms (follow-up). Subjects lost to follow-up or still alive without BM at the data cut-off point (12/2020) were excluded. Covariates included clinical and/or 3D-radiomics-features of the primary tumor from staging chest-CT. Four machine learning models for prediction (80/20 training) were compared. Gini Importance and SHAP were used as measures of importance; sensitivity, specificity, area under the precision-recall curve, and Matthew's Correlation Coefficient as evaluation metrics.
Results
Three hundred and ninety-five patients compromised the clinical cohort. Predictive models based on clinical features offered the best performance (tuned to maximize recall: sensitivityâŒ70%, specificityâŒ60%). Radiomics features failed to provide sufficient information, likely due to the heterogeneity of imaging data. Adenocarcinoma histology, lymph node invasion, and histological tumor grade were positively correlated with the prediction of BM, age, and squamous cell carcinoma histology were negatively correlated. A subgroup discovery analysis identified 2 candidate patient subpopulations appearing to present a higher risk of BM (female patients + adenocarcinoma histology, adenocarcinoma patients + no other distant metastases).
Conclusion
Analysis of the importance of input features suggests that the models are learning the relevant relationships between clinical features/development of BM. A higher number of samples is to be prioritized to improve performance. Employed prospectively at initial diagnosis, such models can help select high-risk subgroups for surveillance brain MRI
Cancellous bone and theropod dinosaur locomotion. Part Iâan examination of cancellous bone architecture in the hindlimb bones of theropods
This paper is the first of a three-part series that investigates the architecture of cancellous (âspongyâ) bone in the main hindlimb bones of theropod dinosaurs, and uses cancellous bone architectural patterns to infer locomotor biomechanics in extinct non-avian species. Cancellous bone is widely known to be highly sensitive to its mechanical environment, and has previously been used to infer locomotor biomechanics in extinct tetrapod vertebrates, especially primates. Despite great promise, cancellous bone architecture has remained little utilized for investigating locomotion in many other extinct vertebrate groups, such as dinosaurs. Documentation and quantification of architectural patterns across a whole bone, and across multiple bones, can provide much information on cancellous bone architectural patterns and variation across species. Additionally, this also lends itself to analysis of the musculoskeletal biomechanical factors involved in a direct, mechanistic fashion.
On this premise, computed tomographic and image analysis techniques were used to describe and analyse the three-dimensional architecture of cancellous bone in the main hindlimb bones of theropod dinosaurs for the first time. A comprehensive survey across many extant and extinct species is produced, identifying several patterns of similarity and contrast between groups. For instance, more stemward non-avian theropods (e.g. ceratosaurs and tyrannosaurids) exhibit cancellous bone architectures more comparable to that present in humans, whereas species more closely related to birds (e.g. paravians) exhibit architectural patterns bearing greater similarity to those of extant birds. Many of the observed patterns may be linked to particular aspects of locomotor biomechanics, such as the degree of hip or knee flexion during stance and gait. A further important observation is the abundance of markedly oblique trabeculae in the diaphyses of the femur and tibia of birds, which in large species produces spiralling patterns along the endosteal surface. Not only do these observations provide new insight into theropod anatomy and behaviour, they also provide the foundation for mechanistic testing of locomotor hypotheses via musculoskeletal biomechanical modelling
Growth, assembly and collective integration of ZnO nanowires : application to biosensing
Les rĂ©seaux bidimensionnels de nanofils (NFs) dâoxyde de zinc (ZnO) alĂ©atoirement orientĂ©s, ou nanonets (pour « nanowire networks »), constituent des nanostructures innovantes et prometteuses pour de nombreuses applications. Lâobjectif de cette thĂšse est de dĂ©velopper des nanonets de ZnO en vue dâapplications Ă la dĂ©tection de molĂ©cules biologiques ou gazeuses, en particulier de lâADN, ceci selon une procĂ©dure bas coĂ»t et industrialisable. Dans ce but, il est essentiel de bien maitriser les diffĂ©rentes Ă©tapes dâĂ©laboration qui sont : (i) le dĂ©pĂŽt de couches minces de germination de ZnO sur des substrats de silicium par voie sol-gel, (ii) la croissance de NFs de ZnO sur ces couches de germination par synthĂšse hydrothermale, et (iii) lâassemblage par filtration sous vide de ces NFs en nanonets de ZnO. Des Ă©tudes approfondies de chacun de ces procĂ©dĂ©s ont donc Ă©tĂ© menĂ©es. Ces travaux ont permis dâĂ©laborer des couches minces, des NFs et des nanonets de ZnO reproductibles et homogĂšnes dont les propriĂ©tĂ©s morphologiques sont prĂ©cisĂ©ment contrĂŽlĂ©es sur une large gamme. Deux protocoles de biofonctionnalisation des nanonets avec de lâADN ont ensuite Ă©tĂ© dĂ©veloppĂ©s et ont abouti Ă des rĂ©sultats encourageants mais restant Ă optimiser. Les nanonets ont Ă©galement Ă©tĂ© intĂ©grĂ©s au sein de dispositifs fonctionnels et les premiĂšres caractĂ©risations Ă©lectriques ont fourni des rĂ©sultats prometteurs. A terme, ce travail ouvre la voie Ă lâintĂ©gration collective de NFs de ZnO qui permettrait la rĂ©alisation dâune nouvelle gĂ©nĂ©ration de capteurs (de biomolĂ©cules, de gazâŠ) Ă la fois portables, rapides et trĂšs sensibles.Two-dimensional randomly oriented zinc oxide (ZnO) nanowire (NW) networks, or nanonets, represent innovative and promising nanostructures for numerous applications. The objective of this thesis is to develop ZnO nanonets for the detection of biological or gaseous molecules, in particular DNA, by using a low cost and scalable procedure. To this end, it is essential to control the different elaboration steps which are: (i) the deposition of ZnO seed layer films on silicon substrates by sol-gel approach, (ii) the growth of ZnO NWs on these seed layer films by hydrothermal synthesis, and (iii) the assembly of these NWs into ZnO nanonets by vacuum filtration. In-depth studies of each of these processes were thus carried out. This work enabled to elaborate reproducible and homogenous ZnO thin films, NWs and nanonets whose morphological properties are precisely controlled over a wide range. Two DNA biofunctionnalization protocols were then developed for the nanonets and led to encouraging results which need however to be further optimized. The nanonets were also integrated into functional devices and the first electrical characterizations provided promising results. In the longer term, this work opens the way to the collective integration of ZnO NWs which would enable the development of a new generation of portable, fast and ultra-sensitive (bio- or gas-) sensors
Croissance, assemblage et intégration collective de nanofils de ZnO : application à la biodétection
Two-dimensional randomly oriented zinc oxide (ZnO) nanowire (NW) networks, or nanonets, represent innovative and promising nanostructures for numerous applications. The objective of this thesis is to develop ZnO nanonets for the detection of biological or gaseous molecules, in particular DNA, by using a low cost and scalable procedure. To this end, it is essential to control the different elaboration steps which are: (i) the deposition of ZnO seed layer films on silicon substrates by sol-gel approach, (ii) the growth of ZnO NWs on these seed layer films by hydrothermal synthesis, and (iii) the assembly of these NWs into ZnO nanonets by vacuum filtration. In-depth studies of each of these processes were thus carried out. This work enabled to elaborate reproducible and homogenous ZnO thin films, NWs and nanonets whose morphological properties are precisely controlled over a wide range. Two DNA biofunctionnalization protocols were then developed for the nanonets and led to encouraging results which need however to be further optimized. The nanonets were also integrated into functional devices and the first electrical characterizations provided promising results. In the longer term, this work opens the way to the collective integration of ZnO NWs which would enable the development of a new generation of portable, fast and ultra-sensitive (bio- or gas-) sensors.Les rĂ©seaux bidimensionnels de nanofils (NFs) dâoxyde de zinc (ZnO) alĂ©atoirement orientĂ©s, ou nanonets (pour « nanowire networks »), constituent des nanostructures innovantes et prometteuses pour de nombreuses applications. Lâobjectif de cette thĂšse est de dĂ©velopper des nanonets de ZnO en vue dâapplications Ă la dĂ©tection de molĂ©cules biologiques ou gazeuses, en particulier de lâADN, ceci selon une procĂ©dure bas coĂ»t et industrialisable. Dans ce but, il est essentiel de bien maitriser les diffĂ©rentes Ă©tapes dâĂ©laboration qui sont : (i) le dĂ©pĂŽt de couches minces de germination de ZnO sur des substrats de silicium par voie sol-gel, (ii) la croissance de NFs de ZnO sur ces couches de germination par synthĂšse hydrothermale, et (iii) lâassemblage par filtration sous vide de ces NFs en nanonets de ZnO. Des Ă©tudes approfondies de chacun de ces procĂ©dĂ©s ont donc Ă©tĂ© menĂ©es. Ces travaux ont permis dâĂ©laborer des couches minces, des NFs et des nanonets de ZnO reproductibles et homogĂšnes dont les propriĂ©tĂ©s morphologiques sont prĂ©cisĂ©ment contrĂŽlĂ©es sur une large gamme. Deux protocoles de biofonctionnalisation des nanonets avec de lâADN ont ensuite Ă©tĂ© dĂ©veloppĂ©s et ont abouti Ă des rĂ©sultats encourageants mais restant Ă optimiser. Les nanonets ont Ă©galement Ă©tĂ© intĂ©grĂ©s au sein de dispositifs fonctionnels et les premiĂšres caractĂ©risations Ă©lectriques ont fourni des rĂ©sultats prometteurs. A terme, ce travail ouvre la voie Ă lâintĂ©gration collective de NFs de ZnO qui permettrait la rĂ©alisation dâune nouvelle gĂ©nĂ©ration de capteurs (de biomolĂ©cules, de gazâŠ) Ă la fois portables, rapides et trĂšs sensibles
Study of sol-gel ZnO thin films â A 1st step toward ZnO nanowire growth and their integration into DNA biosensors
National audienc
ZnO nanowire networks: Fabrication and application to label-free electrical DNA biosensors
International audienc
Comprehensive study of ZnO nanowires grown by hydrothermal synthesis
International audienc
Etude de la croissance de n anofils de ZnO par synthĂšse hydrothermale : une 1Ăšre Ă©tape vers la rĂ©alisation de biocapteurs dâADN Ă©lectriques sans marqueurs Ă base de rĂ©seaux de nanofils de ZnO
National audienc
Comprehensive study of hydrothermally grown ZnO nanowires
International audienceA hydrothermal procedure has been implemented to grow single-crystal ZnO nanowires (NWs) on solâgel deposited seed layers. The main characteristics (diameter, length, and aspect ratio) of derived NWs have been studied by scanning electron microscopy in relation to morphological and structural properties of the ZnO films (mean grain size, surface coverage rate, and texture coefficient) and growth process parameters (growth duration and multi-growth procedure). It is shown how suitable combinations arising from the influence of the seed layer properties, growths of various durations, and implementation of a multi-growth process enable to finely tune the NW characteristics in a large range of values, i.e., a diameter, length, and aspect ratio varying in the 30â225 nm, 1.0â9.0 ”m, and 30â50 ranges, respectively. On the basis of investigated experimental conditions, a simple model is developed that suitably describes the NW crystal growth as a function of the seed layer properties and growth duration. According to this model, lateral and longitudinal growth rates of around 0.01 nm/min and 25â30 nm/min, respectively, are extracted from experimental data and a minimal NW diameter of around 20 nm is predicted
ZnO nanonets: functional nanomateials designed for electrical detection
Session sensing (Highlight)International audienc