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1.
Materials (Basel) ; 15(18)2022 Sep 08.
Artículo en Inglés | MEDLINE | ID: mdl-36143569

RESUMEN

Understanding the ultrafine substructure in freshly formed Fe-C martensite is the key point to reveal the real martensitic transformation mechanism. As-quenched martensite, whose transformation temperature is close to room temperature, has been investigated in detail by means of transmission electron microscopy (TEM) in this study. The observation results revealed that the freshly formed martensite after quenching is actually composed of ultrafine crystallites with a grain size of 1−2 nm. The present observation result matches well with the suggestion based on X-ray studies carried out one hundred years ago. Such nanocrystals are distributed throughout the entire martensite. The whole martensite shows a uniform contrast under both bright and dark field observation modes, irrespective of what observation directions are chosen. No defect contrast can be observed inside each nanocrystal. However, a body-centered cubic {112}<111>-type twinning relationship exists among the ultrafine α-Fe grains. Such ultrafine α-Fe grains or crystallites are the root cause of the fine microstructure formed in martensitic steels and high hardness after martensitic transformation. The formation mechanism of the ultrafine α-Fe grains in the freshly formed martensite will be discussed based on a new γ → α phase transformation mechanism.

2.
Neuroimage Clin ; 33: 102930, 2022.
Artículo en Inglés | MEDLINE | ID: mdl-34959050

RESUMEN

The purpose of this study was to reveal the patterns of reorganization of rich club organization in brain functional networks in dementia with Lewy bodies (DLB) and Alzheimer's disease (AD). The study found that the rich club node shifts from sensory/somatomotor network to fronto-parietal network in DLB. For AD, the rich club nodes switch between the temporal lobe with obvious structural atrophy and the frontal lobe, parietal lobe and cerebellum with relatively preserved structure and function. In addition, compared with healthy controls, rich club connectivity was enhanced in the DLB and AD groups. The connection strength of DLB patients was related to cognitive assessment. In conclusion, we revealed the different functional reorganization patterns of DLB and AD. The conversion and redistribution of rich club members may play a causal role in disease-specific outcomes. It may be used as a potential biomarker to provide more accurate prevention and treatment strategies.


Asunto(s)
Enfermedad de Alzheimer , Enfermedad por Cuerpos de Lewy , Enfermedad de Alzheimer/patología , Atrofia/patología , Encéfalo , Humanos , Enfermedad por Cuerpos de Lewy/patología , Imagen por Resonancia Magnética
3.
Front Neurol ; 10: 1265, 2019.
Artículo en Inglés | MEDLINE | ID: mdl-31849824

RESUMEN

Dementia with Lewy bodies (DLB) is characterized by the transient fluctuating cognition and recurrent visual hallucinations, which may be caused by disorders of the intrinsic brain network dynamics. However, little is known regarding the dynamic features of the brain network behind these symptoms in DLB. In the present study, the intra- and inter-brain network dynamics were explored on a time scale in 17 DLB and 20 healthy controls (HC) applying a sliding-window method followed by k-means clustering analysis. To further evaluate the impact of network dynamics on brain performance, the local and global efficiency of the brain network was calculated. Compared with HC, the dynamic functional connectivity variation matrix in DLB patients was represented by a mixed change of intra-network increase and inter-network decrease. DLB patients devoted more time to a negative connectivity pattern, which represents a state of functional separation. Furthermore, the local efficiency of DLB patients was significantly lower compared with HC. These observations indicate an altered dynamic variability and disorders to the time allocation of state sequences in DLB, which might result in a disturbance of the intricate brain network dynamic properties, thereby leading to a lack of integration and flexibility and an ineffective brain function. In conclusion, dynamic functional connectivity analysis could identify differences between DLB and HC, providing evidences for DLB diagnosis and contributing to the understanding of the widespread clinical features and complex treatment strategies in DLB patients.

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