functional localization
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Author(s):  
Kuo-Lung Lor ◽  
Yeun-Chung Chang ◽  
Chong-Jen Yu ◽  
Cheng-Yi Wang ◽  
Chung-Ming Chen ◽  
...  

AbstractAdvanced bronchoscopic lung volume reduction treatment (BLVR) is now a routine care option for treating patients with severe emphysema. Patterns of low attenuation clusters indicating emphysema and functional small airway disease (fSAD) on paired CT, which may provide additional insights to the target selection of the segmental or subsegmental lobe of the treatments, require further investigation. The low attenuation clusters (LACS) were segmented to identify the scalar and spatial distribution of the lung destructions, in terms of 10 fractions scales of low attenuation density (LAD) located in upper lobes and lower lobes. The LACs of functional small airway disease (fSAD) were delineated by applying the technique of parametric response map (PRM) on the co-registered CT image data. Both emphysematous LACs of inspiratory CT and fSAD LACs on expiratory CT were used to derive the coefficients of the predictive model for estimating the airflow limitation. The voxel-wise severity is then predicted using the regional LACs on the co-registered CT to indicate the functional localization, namely, the bullous parametric response map (BPRM). A total of 100 subjects, 88 patients with mild to very severe COPD and 12 control participants with normal lung functions (FEV1/FVC % > 70%), were evaluated. Pearson’s correlations between FEV1/FVC% and LAV%HU-950 of severe emphysema are − 0.55 comparing to − 0.67 and − 0.62 of LAV%HU-856 of air-trapping and LAV%fSAD respectively. Pearson’s correlation between FEV1/FVC% and FEV1/FVC% predicted by the proposed model using LAD% of HU-950 and fSAD on BPRM is 0.82 (p < 0.01). The result of the Bullous Parametric Response Map (BPRM) is capable of identifying the less functional area of the lung, where the BLVR treatment is aimed at removing from a hyperinflated area of emphysematous regions.


2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Hitoshi Maezawa ◽  
Momoka Fujimoto ◽  
Yutaka Hata ◽  
Masao Matsuhashi ◽  
Hiroaki Hashimoto ◽  
...  

AbstractCorticokinematic coherence (CKC) between magnetoencephalographic and movement signals using an accelerometer is useful for the functional localization of the primary sensorimotor cortex (SM1). However, it is difficult to determine the tongue CKC because an accelerometer yields excessive magnetic artifacts. Here, we introduce a novel approach for measuring the tongue CKC using a deep learning-assisted motion capture system with videography, and compare it with an accelerometer in a control task measuring finger movement. Twelve healthy volunteers performed rhythmical side-to-side tongue movements in the whole-head magnetoencephalographic system, which were simultaneously recorded using a video camera and examined using a deep learning-assisted motion capture system. In the control task, right finger CKC measurements were simultaneously evaluated via motion capture and an accelerometer. The right finger CKC with motion capture was significant at the movement frequency peaks or its harmonics over the contralateral hemisphere; the motion-captured CKC was 84.9% similar to that with the accelerometer. The tongue CKC was significant at the movement frequency peaks or its harmonics over both hemispheres. The CKC sources of the tongue were considerably lateral and inferior to those of the finger. Thus, the CKC with deep learning-assisted motion capture can evaluate the functional localization of the tongue SM1.


Biology ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 53
Author(s):  
Eid I. Ibrahim ◽  
Kotb A. Attia ◽  
Abdelhalim I. Ghazy ◽  
Kimiko Itoh ◽  
Fahad N. Almajhdi ◽  
...  

Small ubiquitin-related modifier (SUMO) regulates the cellular function of diverse proteins through post-translational modifications. The current study defined a new homolog of SUMO genes in the rice genome and named it OsSUMO7. Putative protein analysis of OsSUMO7 detected SUMOylation features, including di-glycine (GG) and consensus motifs (ΨKXE/D) for the SUMOylation site. Phylogenetic analysis demonstrated the high homology of OsSUMO7 with identified rice SUMO genes, which indicates that the OsSUMO7 gene is an evolutionarily conserved SUMO member. RT-PCR analysis revealed that OsSUMO7 was constitutively expressed in all plant organs. Bioinformatic analysis defined the physicochemical properties and structural model prediction of OsSUMO7 proteins. A red fluorescent protein (DsRed), fused with the OsSUMO7 protein, was expressed and localized mainly in the nucleus and formed nuclear subdomain structures. The fusion proteins of SUMO-conjugating enzymes with the OsSUMO7 protein were co-expressed and co-localized in the nucleus and formed nuclear subdomains. This indicated that the OsSUMO7 precursor is processed, activated, and transported to the nucleus through the SUMOylation system of the plant cell.


2021 ◽  
pp. 343-372
Author(s):  
Lydia Chougar ◽  
Delphine Leclercq ◽  
Pierre-François Van de Moortele ◽  
Stéphane Lehéricy

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Jiao Li ◽  
Guo-Rong Wu ◽  
Bing Li ◽  
Feiyang Fan ◽  
Xiaopeng Zhao ◽  
...  

AbstractIntersubject variability is a fundamental characteristic of brain organizations, and not just “noise”. Although intrinsic functional connectivity (FC) is unique to each individual and varies across brain gray-matter, the underlying mechanisms of intersubject functional variability in white-matter (WM) remain unknown. This study identified WMFC variabilities and determined the genetic basis and macroscale imaging in 45 healthy subjects. The functional localization pattern of intersubject variability across WM is heterogeneous, with most variability observed in the heteromodal cortex. The variabilities of heteromodal regions in expression profiles of genes are related to neuronal cells, involved in synapse-related and glutamic pathways, and associated with psychiatric disorders. In contrast, genes overexpressed in unimodal regions are mostly expressed in glial cells and were related to neurological diseases. Macroscopic variability recapitulates the functional and structural specializations and behavioral phenotypes. Together, our results provide clues to intersubject variabilities of the WMFC with convergent transcriptomic and cellular signatures, which relate to macroscale brain specialization.


2021 ◽  
Vol 14 (6) ◽  
pp. 1652-1653
Author(s):  
Benjamin Kalloch ◽  
Ole Numssen ◽  
Thomas Knösche ◽  
Gesa Hartwigsen ◽  
Konstantin Weise

2021 ◽  
Vol 15 ◽  
Author(s):  
Ronald S. Petralia ◽  
Ya-Xian Wang

The post-embedding immunogold (PI) technique for immunolabeling of neuronal tissues utilizing standard thin-section transmission electron microscopy (TEM) continues to be a prime method for understanding the functional localization of key proteins in neuronal function. Its main advantages over other immunolabeling methods for thin-section TEM are (1) fairly accurate and quantifiable localization of proteins in cells; (2) double-labeling of sections using two gold particle sizes; and (3) the ability to perform multiple labeling for different proteins by using adjacent sections. Here we first review in detail a common method for PI of neuronal tissues. This method has two major parts. First, we describe the freeze-substitution embedding method: cryoprotected tissue is frozen in liquid propane via plunge-freezing, and is placed in a freeze-substitution instrument in which the tissue is embedded in Lowicryl at low temperatures. We highlight important aspects of freeze-substitution embedding. Then we outline how thin sections of embedded tissue on grids are labeled with a primary antibody and a secondary gold particle-conjugated antibody, and the particular problems encountered in TEM of PI-labeled sections. In the Discussion, we compare our method both to earlier PI methods and to more recent PI methods used by other laboratories. We also compare TEM immunolabeling using PI vs. various pre-embedding immunolabeling methods, especially relating to neuronal tissue.


2021 ◽  
Vol 12 ◽  
Author(s):  
Christopher Laohathai ◽  
John S. Ebersole ◽  
John C. Mosher ◽  
Anto I. Bagić ◽  
Ai Sumida ◽  
...  

Magnetoencephalography (MEG) is a neurophysiologic test that offers a functional localization of epileptic sources in patients considered for epilepsy surgery. The understanding of clinical MEG concepts, and the interpretation of these clinical studies, are very involving processes that demand both clinical and procedural expertise. One of the major obstacles in acquiring necessary proficiency is the scarcity of fundamental clinical literature. To fill this knowledge gap, this review aims to explain the basic practical concepts of clinical MEG relevant to epilepsy with an emphasis on single equivalent dipole (sECD), which is one the most clinically validated and ubiquitously used source localization method, and illustrate and explain the regional topology and source dynamics relevant for clinical interpretation of MEG-EEG.


2021 ◽  
Author(s):  
Hitoshi Maezawa ◽  
Momoka Fujimoto ◽  
Yutaka Hata ◽  
Masao Matsuhashi ◽  
Hiroaki Hashimoto ◽  
...  

Measuring the corticokinematic coherence (CKC) between magnetoencephalographic and movement signals using an accelerometer can evaluate the functional localization of the primary sensorimotor cortex (SM1) of the upper limbs. However, it is difficult to determine the tongue CKC because an accelerometer yields excessive magnetic artifacts. We introduce and validate a novel approach for measuring the tongue CKC using a deep learning-assisted motion capture system with videography, and compare it with an accelerometer in a control task measuring finger movement. Twelve healthy volunteers performed rhythmical side-to-side tongue movements in the whole-head magnetoencephalographic system, which were simultaneously recorded using a video camera and examined offline using a deep learning-assisted motion capture system. In the control task, right finger CKC measurements were simultaneously evaluated via motion capture and an accelerometer. The right finger CKC with motion capture was significant at the movement frequency peaks or its harmonics over the contralateral hemisphere; the motion-captured CKC was 84.9% similar to that with the accelerometer. The tongue CKC was significant at the movement frequency peaks or its harmonics over both hemispheres, with no difference between the left and right hemispheres. The CKC sources of the tongue were considerably lateral and inferior to those of the finger. Thus, the CKC based on deep learning-assisted motion capture can evaluate the functional localization of the tongue SM1. In this approach, because no devices are placed on the tongue, magnetic noise, disturbances due to tongue movements, risk of aspiration of the device, and risk of infection to the experimenter are eliminated.


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