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1.
Brain Imaging Behav ; 2022 Jan 01.
Artigo em Inglês | MEDLINE | ID: mdl-34973120

RESUMO

Tremor in Parkinson's disease (PD) has distinct responsiveness to dopamine, which is supposed not be exclusively related to dopamine deficiency but has a close relationship with cholinergic system. This phenomenon indicates that cholinergic system may be an important regulatory for distinct dopamine responsiveness of parkinsonian tremor. Through investigating the alterations of cholinergic and dopaminergic network during levodopa administration, we aimed at exploring the mechanisms of differed dopamine responsiveness of parkinsonian tremor. Fifty-two PD patients with tremor were enrolled. MRI scanning, UPDRS III and its sub-symptom scores were collected in OFF and ON status (dopaminergic challenge test). Then, patients were divided into two groups (dopamine-resistant tremor and dopamine-responsive tremor) according to the tremor change rate median score. Dopaminergic and cholinergic network were obtained. LASSO regression was conducted to identify functional connectivity with distinct reactivity during levodopa administration between groups. Afterwards, detailed group comparisons, interaction and correlation analyses were performed. The reactivity of cholinergic connectivity showed the highest possibility to distinguish two groups, especially connectivity of right basal forebrain 123 to right parietal operculum cortex (R.BF123-R.PO). After levodopa administration, connectivity of R.BF123-R.PO was decreased for dopamine-responsive tremor while which remained unchanged for dopamine-resistant tremor. The reactivity of R.BF123-R.PO was negatively correlated with tremor change rate. Reduced cholinergic connectivity to parietal operculum may be an underlying mechanism for the responsive tremor in PD and the distinct cholinergic reactivity of parietal operculum to levodopa may be a core pathophysiology for the differed DA responsiveness of tremor in PD.

2.
Sci Rep ; 11(1): 23513, 2021 Dec 06.
Artigo em Inglês | MEDLINE | ID: mdl-34873241

RESUMO

Rib fracture detection is time-consuming and demanding work for radiologists. This study aimed to introduce a novel rib fracture detection system based on deep learning which can help radiologists to diagnose rib fractures in chest computer tomography (CT) images conveniently and accurately. A total of 1707 patients were included in this study from a single center. We developed a novel rib fracture detection system on chest CT using a three-step algorithm. According to the examination time, 1507, 100 and 100 patients were allocated to the training set, the validation set and the testing set, respectively. Free Response ROC analysis was performed to evaluate the sensitivity and false positivity of the deep learning algorithm. Precision, recall, F1-score, negative predictive value (NPV) and detection and diagnosis were selected as evaluation metrics to compare the diagnostic efficiency of this system with radiologists. The radiologist-only study was used as a benchmark and the radiologist-model collaboration study was evaluated to assess the model's clinical applicability. A total of 50,170,399 blocks (fracture blocks, 91,574; normal blocks, 50,078,825) were labelled for training. The F1-score of the Rib Fracture Detection System was 0.890 and the precision, recall and NPV values were 0.869, 0.913 and 0.969, respectively. By interacting with this detection system, the F1-score of the junior and the experienced radiologists had improved from 0.796 to 0.925 and 0.889 to 0.970, respectively; the recall scores had increased from 0.693 to 0.920 and 0.853 to 0.972, respectively. On average, the diagnosis time of radiologist assisted with this detection system was reduced by 65.3 s. The constructed Rib Fracture Detection System has a comparable performance with the experienced radiologist and is readily available to automatically detect rib fracture in the clinical setting with high efficacy, which could reduce diagnosis time and radiologists' workload in the clinical practice.

3.
Eur J Neurol ; 2021 Dec 09.
Artigo em Inglês | MEDLINE | ID: mdl-34882309

RESUMO

BACKGROUND: To investigate the effect of genetic risk on whole-brain white matter (WM) integrity in patients with Parkinson's disease (PD). METHODS: Data were acquired from Parkinson's Progression Markers Initiative (PPMI) database. Polygenic load was estimated by calculating weighted polygenic risk scores (PRS) using 1) all available 26 PD-risk single nucleotide polymorphisms (SNPs) (PRS1) and 2) 23 SNPs with minor allele frequency (MAF) >0.05 (PRS2). According to the PRS2, and combined with clinical and diffusion tensor imaging (DTI) data over 3 years follow-up, 60 PD patients were screened and assigned to low PRS group (n=30) and high PRS group (n=30) to investigate inter-group difference of clinical profiles and WM microstructure measured by DTI cross-sectionally and longitudinally. RESULTS: PRS were associated with younger age at onset in patients with PD (PRS1, Spearman ρ = -0.190, p = 0.003; PRS2, Spearman ρ = -0.189, p = 0.003). High PRS group showed more extensive WM microstructural degeneration compared with low PRS group, mainly involved in the anterior thalamic radiation (AThR) and inferior fronto-occipital fasciculus (IFOF) (p < 0.05). Further, WM microstructural changes in AThR correlated with declining cognitive function (r=-0.401, p=0.028) and increasing dopaminergic deficits in caudate (r=-0.405, p=0.030). CONCLUSIONS: These findings suggest that PD-associated polygenic load would aggravate the WM microstructural degeneration and these changes may lead to poor cognition with continuous dopamine depletion. This study provides advanced evidence that combined with a cumulative PRS and DTI methods may predict disease progression in PD patients.

4.
Annu Int Conf IEEE Eng Med Biol Soc ; 2021: 3676-3679, 2021 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-34892034

RESUMO

Deep brain nuclei are closely related to the pathogenesis of neurodegenerative diseases. Automatic segmentation for brain nuclei plays a significant role in aging and disease-related assessment. Quantitative susceptibility mapping (QSM), as a novel MRI imaging technique, attracts increasing attention in deep gray matter (DGM) nuclei-related research and diagnosis. This paper proposes DeepQSMSeg, a deep learning-based end-to-end tool, to segment five pairs of DGM structures from QSM images. The proposed model is based on a 3D encoder-decoder fully convolutional neural network. For concentrating network on the target regions, spatial and channel attention modules are adopted in both encoder and decoder stages. Dice loss is combined with focal loss to alleviate the imbalance of ROI classes. The result shows that our method can segment DGM structures from QSM images precisely, rapidly and reliably. Comparing with ground truth, the average Dice coefficient for all ROIs in the test dataset achieved 0.872±0.053, and Hausdorff distance was 2.644±2.917 mm. Finally, an age-related susceptibility development model was used to confirm the reliability of DeepQSMSeg in aging and disease-related studies.Clinical Relevance-Accurate and automatic segmentation tool for sub-cortical regions in QSM can significantly alleviate the pressure of radiologists. It can also accelerate the progress of related research and clinical translation.

5.
Hum Brain Mapp ; 2021 Dec 14.
Artigo em Inglês | MEDLINE | ID: mdl-34904766

RESUMO

Parkinson's disease (PD) is primarily characterized by the loss of dopaminergic cells and atrophy in subcortical regions. However, the impact of these pathological changes on large-scale dynamic integration and segregation of the cortex are not well understood. In this study, we investigated the effect of subcortical dysfunction on cortical dynamics and cognition in PD. Spatiotemporal dynamics of the phase interactions of resting-state blood-oxygen-level-dependent signals in 159 PD patients and 152 normal control (NC) individuals were estimated. The relationships between subcortical atrophy, subcortical-cortical fiber connectivity impairment, cortical synchronization/metastability, and cognitive performance were then assessed. We found that cortical synchronization and metastability in PD patients were significantly decreased. To examine whether this is an effect of dopamine depletion, we investigated 45 PD patients both ON and OFF dopamine replacement therapy, and found that cortical synchronization and metastability are significantly increased in the ON state. The extent of cortical synchronization and metastability in the OFF state reflected cognitive performance and mediates the difference in cognitive performance between the PD and NC groups. Furthermore, both the thalamic volume and thalamocortical fiber connectivity had positive relationships with cortical synchronization and metastability in the dopaminergic OFF state, and mediate the difference in cortical synchronization between the PD and NC groups. In addition, thalamic volume also reflected cognitive performance, and cortical synchronization/metastability mediated the relationship between thalamic volume and cognitive performance in PD patients. Together, these results highlight that subcortical dysfunction and reduced dopamine levels are responsible for decreased cortical synchronization and metastability, further affecting cognitive performance in PD. This might lead to biomarkers being identified that can predict if a patient is at risk of developing dementia.

6.
Hum Brain Mapp ; 2021 Dec 31.
Artigo em Inglês | MEDLINE | ID: mdl-34970835

RESUMO

Identifying a whole-brain connectome-based predictive model in drug-naïve patients with Parkinson's disease and verifying its predictions on drug-managed patients would be useful in determining the intrinsic functional underpinnings of motor impairment and establishing general brain-behavior associations. In this study, we constructed a predictive model from the resting-state functional data of 47 drug-naïve patients by using a connectome-based approach. This model was subsequently validated in 115 drug-managed patients. The severity of motor impairment was assessed by calculating Unified Parkinson's Disease Rating Scale Part III scores. The predictive performance of model was evaluated using the correlation coefficient (rtrue ) between predicted and observed scores. As a result, a connectome-based model for predicting individual motor impairment in drug-naïve patients was identified with significant performance (rtrue  = .845, p < .001, ppermu  = .002). Two patterns of connection were identified according to correlations between connection strength and the severity of motor impairment. The negative motor-impairment-related network contained more within-network connections in the motor, visual-related, and default mode networks, whereas the positive motor-impairment-related network was constructed mostly with between-network connections coupling the motor-visual, motor-limbic, and motor-basal ganglia networks. Finally, this predictive model constructed around drug-naïve patients was confirmed with significant predictive efficacy on drug-managed patients (r = .209, p = .025), suggesting a generalizability in Parkinson's disease patients under long-term drug influence. In conclusion, this study identified a whole-brain connectome-based model that could predict the severity of motor impairment in Parkinson's patients and furthers our understanding of the functional underpinnings of the disease.

7.
Front Oncol ; 11: 752158, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34745982

RESUMO

Background: Brain invasion in meningioma has independent associations with increased risks of tumor progression, lesion recurrence, and poor prognosis. Therefore, this study aimed to construct a model for predicting brain invasion in WHO grade II meningioma by using preoperative MRI. Methods: One hundred seventy-three patients with brain invasion and 111 patients without brain invasion were included. Three mainstream features, namely, traditional semantic features and radiomics features from tumor and tumor-to-brain interface regions, were acquired. Predictive models correspondingly constructed on each feature set or joint feature set were constructed. Results: Traditional semantic findings, e.g., peritumoral edema and other four features, had comparable performance in predicting brain invasion with each radiomics feature set. By taking advantage of semantic features and radiomics features from tumoral and tumor-to-brain interface regions, an integrated nomogram that quantifies the risk factor of each selected feature was constructed and had the best performance in predicting brain invasion (area under the curve values were 0.905 in the training set and 0.895 in the test set). Conclusions: This study provided a clinically available and promising approach to predict brain invasion in WHO grade II meningiomas by using preoperative MRI.

8.
Eur J Neurosci ; 2021 Nov 14.
Artigo em Inglês | MEDLINE | ID: mdl-34779047

RESUMO

Brain iron affects working memory (WM) but the impact of iron content in deep grey matter nuclei on WM networks is unknown. We aimed to test whether deep grey matter nuclei iron concentration can affect resting-state functional connectivity (rsFC) within brain networks modifying WM performance. An N-back WM paradigm was applied in a hundred healthy younger adults. The participants then underwent a resting-state functional magnetic resonance imaging (fMRI) for brain network analysis and quantitative susceptibility mapping (QSM) imaging for assessment of deep grey matter nuclei iron concentration. Higher substantia nigra (SN) iron concentration was associated with lower rsFC between SN and brain regions of the temporal/frontal lobe but with better WM performance after controlling for age, gender and education. A follow-up mediation analysis also indicated that functional connectivity may mediate the link between SN iron and WM performance. Our results suggest that high SN iron concentration may affect communication between the SN and temporal/frontal lobe and is associated with strengthened WM performance in younger adults.

9.
Neuroimage Clin ; 32: 102873, 2021 Nov 03.
Artigo em Inglês | MEDLINE | ID: mdl-34749290

RESUMO

Degeneration of the locus coeruleus (LC) is recognized as a critical hallmark of Parkinson's disease (PD). Recent studies have reported that noradrenaline produced from the LC has critical effects on brain functional organization. However, it is unknown if LC degeneration in PD contributes to cognitive/motor manifestations through modulating brain functional organization. This study enrolled 94 PD patients and 68 healthy controls, and LC integrity was measured using the contrast-to-noise ratio of the LC (CNRLC) calculated from T1-weighted magnetic resonance imaging. We used graph-theory-based network analysis to characterize brain functional organization. The relationships among LC degeneration, network disruption, and cognitive/motor manifestations in PD were assessed. Whether network disruption was a mediator between LC degeneration and cognitive/motor impairments was assessed further. In addition, an independent PD subgroup (n = 35) having functional magnetic resonance scanning before and after levodopa administration was enrolled to evaluate whether LC degeneration-related network deficiencies were independent of dopamine deficiency. We demonstrated that PD patients have significant LC degeneration compared to healthy controls. CNRLC was positively correlated with Montreal Cognitive Assessment score and the nodal efficiency (NE) of several cognitive-related regions. Lower NE of the superior temporal gyrus was a mediator between LC degeneration and cognitive impairment in PD. However, levodopa treatment could not normalize the reduced NE of the superior temporal gyrus (mediator). In conclusion, we provided evidence for the relationship between LC degeneration and extensive network disruption in PD, and highlight the role of network disorganization in LC degeneration-related cognitive impairment.

10.
Front Aging Neurosci ; 13: 723948, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34566625

RESUMO

The cholinergic system is critical in Parkinson's disease (PD) pathology, which accounts for various clinical symptoms in PD patients. The substantia innominata (SI) provides the main source of cortical cholinergic innervation. Previous studies revealed cholinergic-related dysfunction in PD pathology at early stage. Since PD is a progressive disorder, alterations of cholinergic system function along with the PD progression have yet to be elucidated. Seventy-nine PD patients, including thirty-five early-stage PD patients (PD-E) and forty-four middle-to-late stage PD patients (PD-M), and sixty-four healthy controls (HC) underwent brain magnetic resonance imaging and clinical assessments. We employed seed-based resting-state functional connectivity analysis to explore the cholinergic-related functional alterations. Correlation analysis was used to investigate the relationship between altered functional connectivity and the severity of motor symptoms in PD patients. Results showed that both PD-E and PD-M groups exhibited decreased functional connectivity between left SI and left frontal inferior opercularis areas and increased functional connectivity between left SI and left cingulum middle area as well as right primary motor and sensory areas when comparing with HC. At advanced stages of PD, functional connectivity in the right primary motor and sensory areas was further increased. These altered functional connectivity were also significantly correlated with the Unified Parkinson's Disease Rating Scale motor scores. In conclusion, this study illustrated that altered cholinergic function plays an important role in the motor disruptions in PD patients both in early stage as well as during the progression of the disease.

11.
J Parkinsons Dis ; 11(4): 1631-1640, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34366373

RESUMO

BACKGROUND: The widely divergent responsiveness of Parkinson's disease (PD) patients to levodopa is an important clinical issue because of its relationship with quality of life and disease prognosis. Preliminary animal experiments have suggested that degeneration of the locus coeruleus (LC) attenuates the efficacy of levodopa treatment. OBJECTIVE: To explore the relationship between LC degeneration and levodopa responsiveness in PD patients in vivo. METHODS: Neuromelanin-sensitive magnetic resonance imaging (NM-MRI), a good indicator of LC and substantia nigra (SN) degeneration, and levodopa challenge tests were conducted in 57 PD patients. Responsiveness to levodopa was evaluated by the rates of change of the Unified Parkinson's Disease Rating Scale Part III score and somatomotor network synchronization calculated from resting-state functional MRI before and after levodopa administration. Next, we assessed the relationship between the contrast-to-noise ratio of LC (CNRLC) and levodopa responsiveness. Multiple linear regression analysis was conducted to rule out the potential influence of SN degeneration on levodopa responsiveness. RESULTS: A significant positive correlation was found between CNRLC and the motor improvement after levodopa administration (R = 0.421, p = 0.004). CNRLC also correlated with improvement in somatomotor network synchronization (R = -0.323, p = 0.029). Furthermore, the relationship between CNRLC and levodopa responsiveness was independent of SN degeneration. CONCLUSION: LC degeneration might be an essential factor for levodopa resistance. LC evaluation using NM-MRI might be an alternative tool for predicting levodopa responsiveness and for helping to stratify patients into clinical trials aimed at improving the efficacy of levodopa.

12.
Brain Struct Funct ; 226(8): 2665-2673, 2021 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-34373950

RESUMO

Increasing evidence suggests that genetic factors play a key role in the development of Parkinson's disease (PD). The variant rs11240572 in the PARK16 gene locus is strongly associated with PD. However, its effect on the pathogenesis of PD is yet to be clarified. The objective of the study was to explore the effect of the PARK16 rs11240572 variant on brain structure in PD patients. A total of 51 PD patients were enrolled in the study and genotyped for the rs11240572 variant. Clinical assessments and MRI scans were conducted across all participants. Voxel-based morphometry (VBM) was used to investigate gray matter volume (GMV) of the whole brain between these two groups. Correlation analysis was performed to identify the relationships between GMV and clinical features. There were 17 rs11240572-A variant carriers and 34 non-carriers, with no significant demographic differences between these two groups. Compared with non-carriers, rs11240572-A carriers showed increased GMV in the left caudate nucleus and putamen, but decreased GMV in the left superior temporal gyrus and supramarginal gyrus. In non-carriers, left basal ganglia GMV was positively correlated with UPDRS III (r = 0.365, p = 0.034) and bradykinesia (r = 0.352, p = 0.042), but negatively correlated with MMSE (r = - 0.344, p = 0.047), while in carriers negative correlation between basal ganglia GMV and MMSE was also observed (r = - 0.666, p = 0.004). Moreover, the GMV of left temporoparietal cortex was positively associated with cognitive function in both groups (carriers, r = 0.692, p = 0.002; non-carriers, r = 0.879, p < 0.001). When reducing the sample size of non-carriers to the level of the carrier sample, similar correlations were observed in both groups. Our study showed that the PARK16 rs11240572 variant affects the brain structure of patients with PD, especially in the basal ganglia and temporoparietal cortex. This indicated that this variant might play an important role in the pathogenesis of PD.

13.
Parkinsonism Relat Disord ; 88: 82-89, 2021 07.
Artigo em Inglês | MEDLINE | ID: mdl-34147950

RESUMO

OBJECTIVES: To explore the microstructural alterations in subcortical nuclei in Parkinson's disease (PD) at different stages with diffusion kurtosis imaging (DKI) and tensor imaging and to test the performance of diffusion metrics in identifying PD. METHODS: 108 PD patients (64 patients in early-stage PD group (EPD) and 44 patients in moderate-late-stage PD group (MLPD)) and 64 healthy controls (HC) were included. Tensor and kurtosis metrics in the subcortical nuclei were compared. Partial correlation was used to correlate the diffusion metrics and Unified Parkinson's Disease Rating Scale part-III (UPDRS-III) score. Logistic regression and receiver operating characteristic analysis were applied to test the diagnostic performance of the diffusion metrics. RESULTS: Compared with HC, both EPD and MLPD patients showed higher fractional anisotropy and axial diffusivity, lower mean kurtosis (MK) and axial kurtosis in substantia nigra, lower MK and radial kurtosis (RK) in globus pallidus (GP) and thalamus (all p < 0.05). Compared with EPD, MLPD patients showed lower MK and RK in GP and thalamus (all p < 0.05). MK and RK in GP and thalamus were negatively correlated with UPDRS-III score (all p < 0.01). The logistic regression model combining kurtosis and tensor metrics showed the best performance in diagnosing PD, EPD, and MLPD (areas under curve were 0.817, 0.769, and 0.914, respectively). CONCLUSIONS: PD has progressive microstructural alterations in the subcortical nuclei. DKI is sensitive to detect microstructural alterations in GP and thalamus during PD progression. Combining kurtosis and tensor metrics can achieve a good performance in diagnosing PD.

14.
Hum Brain Mapp ; 42(13): 4399-4421, 2021 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-34101297

RESUMO

Human brain atlases are essential for research and surgical treatment of Parkinson's disease (PD). For example, deep brain stimulation for PD often requires human brain atlases for brain structure identification. However, few atlases can provide disease-specific subcortical structures for PD, and most of them are based on T1w and T2w images. In this work, we construct a HybraPD atlas using fused quantitative susceptibility mapping (QSM) and T1w images from 87 patients with PD. The constructed HybraPD atlas provides a series of templates, that is, T1w, GRE magnitude, QSM, R2*, and brain tissue probabilistic maps. Then, we manually delineate a parcellation map with 12 bilateral subcortical nuclei, which are highly related to PD pathology, such as sub-regions in globus pallidus and substantia nigra. Furthermore, we build a whole-brain parcellation map by combining existing cortical parcellation and white-matter segmentation with the proposed subcortical nuclei map. Considering the multimodality of the HybraPD atlas, the segmentation accuracy of each nucleus is evaluated using T1w and QSM templates, respectively. The results show that the HybraPD atlas provides more accurate segmentation than existing atlases. Moreover, we analyze the metabolic difference in subcortical nuclei between PD patients and healthy control subjects by applying the HybraPD atlas to calculate uptake values of contrast agents on positron emission tomography (PET) images. The atlas-based analysis generates accurate disease-related brain nuclei segmentation on PET images. The newly developed HybraPD atlas could serve as an efficient template to study brain pathological alterations in subcortical regions for PD research.

15.
J Magn Reson Imaging ; 54(4): 1098-1106, 2021 10.
Artigo em Inglês | MEDLINE | ID: mdl-33949744

RESUMO

BACKGROUND: Excessive iron accumulation is one of the main pathogeneses of Parkinson's disease (PD). Ceruloplasmin plays an important role in keeping the iron homoeostasis. PURPOSE: To explore the association between serum ceruloplasmin depletion and subcortical iron distribution in PD. STUDY TYPE: Prospective. POPULATION: One hundred and twenty-one normal controls, 34 PD patients with low serum ceruloplasmin (PD-LC), and 28 patients with normal serum ceruloplasmin (PD-NC). SEQUENCE: Enhanced susceptibility-weighted angiography (ESWAN) on a 3 T scanner. ASSESSMENT: Quantitative susceptibility mapping was employed to quantify the regional iron content by using a semi-automatic method. Serum ceruloplasmin concentration was measured from peripheral blood sample. Clinical assessments were conducted by a neurologist. STATISTICAL TESTS: General linear model was used to compare the intergroup difference of region iron distribution among groups, and the statistics was adjusted by Bonferroni method (P < 0.01). Partial correlation analysis was used to detect the association between regional iron distribution and serum ceruloplasmin concentration (P < 0.05). RESULTS: Compared with normal controls, significant iron accumulation in substantia nigra, putamen, and red nucleus was observed in PD-LC, while the only region showing significant iron accumulation was SN in PD-NC. Between PD-NC and PD-LC, the iron accumulation in putamen remained significantly different, which had a negative correlation with serum ceruloplasmin in whole PD patients (r = -0.338, P = 0.008). DATA CONCLUSION: Nigral iron accumulation characterizes PD patients without significant association with serum ceruloplasmin. Differentially, when PD patients appear with reduced serum ceruloplasmin, more widespread iron accumulation would be expected with additionally involving putamen and red nucleus. All these findings provide insightful evidence for the abnormal iron metabolism behind the ceruloplasmin depletion in PD. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: 2.


Assuntos
Ceruloplasmina , Doença de Parkinson , Encéfalo/diagnóstico por imagem , Encéfalo/metabolismo , Ceruloplasmina/metabolismo , Humanos , Ferro/metabolismo , Imageamento por Ressonância Magnética , Espectroscopia de Ressonância Magnética , Doença de Parkinson/diagnóstico por imagem , Estudos Prospectivos , Substância Negra
16.
J Orthop Surg Res ; 16(1): 294, 2021 May 05.
Artigo em Inglês | MEDLINE | ID: mdl-33952279

RESUMO

BACKGROUND: Osteosarcoma is a disease with high mortality in children and adolescents, and metastasis is one of the important clinical features of osteosarcoma. N6-Methyladenosine (m6A) is the most abundant methylation modification in mRNA, which is regulated by m6A regulators. It is reported that it is related to the occurrence and development of tumors. However, the mechanism of its action in osteosarcoma is rarely known. The purpose of this study was to identify the potential role of m6A regulatory factor in osteosarcoma and its clinical prognostic value. METHODS: Here, we used The Cancer Genome Atlas (TCGA) to comprehensively analyze the relationship between m6A regulatory factors and osteosarcoma (metastasis group and non-metastasis group). We analyzed their survival relationship and analyzed all the m6A regulatory factors in TCGA tumor data set by using the univariate Cox proportional hazard regression model. Finally, we selected two survival-related methylation regulators (FTO and IGF2BP2) as risk gene signature. RESULTS: According to the median risk, patients were divided into low-risk group and high-risk group. Multivariate Cox regression analysis showed that these two risk genes were considered to be the key factors independently predicting the prognosis of patients with osteosarcoma. In addition, we verified their characteristics with gene expression omnibus (GEO) DataSets and confirmed that they are related to tumor and immune-related signaling pathways through gene set enrichment analysis (GESA) and immune infiltration analysis. CONCLUSIONS: In conclusion, m6A regulators might play an important role in the metastasis of osteosarcoma and have potential important value for the prognosis and treatment strategy of osteosarcoma patients.


Assuntos
Dioxigenase FTO Dependente de alfa-Cetoglutarato/fisiologia , Neoplasias Ósseas/genética , Neoplasias Ósseas/metabolismo , Metiltransferases/genética , Metiltransferases/metabolismo , Metástase Neoplásica/genética , Osteossarcoma/genética , Osteossarcoma/metabolismo , Proteínas de Ligação a RNA/fisiologia , RNA/metabolismo , Adolescente , Neoplasias Ósseas/imunologia , Neoplasias Ósseas/patologia , Criança , Feminino , Previsões , Expressão Gênica , Estudos de Associação Genética , Humanos , Masculino , Metilação , Osteossarcoma/imunologia , Osteossarcoma/patologia , Prognóstico , Análise de Regressão , Risco , Transdução de Sinais/genética , Transdução de Sinais/imunologia
17.
Front Aging Neurosci ; 13: 591347, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33994988

RESUMO

Background: Apolipoprotein E (APOE) ε2 is a protective genetic factor for Alzheimer's disease (AD). However, the potential interaction effects between the APOE ε2 allele and disease status on the intrinsic brain activity remain elusive. Methods: We identified 73 healthy control (HC) with APOE ε3/ε3, 61 mild cognitive impairment (MCI) subjects with APOE ε3/ε3, 24 HC with APOE ε2/ε3, and 10 MCI subjects with APOE ε2/ε3 from the ADNI database. All subjects underwent a resting-state functional MRI and Fluoro-deoxy-glucose positron emission tomography (FDG-PET). We used a fractional amplitude of low-frequency fluctuation (fALFF) to explore the spontaneous brain activity. Based on the mixed-effects analysis, we explored the interaction effects between the APOE ε2 allele versus disease status on brain activity and metabolism in a voxel-wise fashion (GRF corrected, p < 0.01), followed by post hoc two-sample t-tests (Bonferroni corrected, p < 0.05). We then investigated the relationship between the mean imaging metrics and cognitive abilities. Results: There are no significant differences in gender, age, or education among the four groups. The interaction effect on brain activity was located in the inferior parietal lobule (IPL). Post hoc analysis showed that APOE ε2/ε3 MCI had an increased IPL fALFF than APOE ε3/ε3 MCI. Regarding the APOE ε2 allele effects, we found that ε2 carriers had a decreased fALFF in the transverse temporal gyrus than non-carriers. Also, FDG-PET results showed a lower SUVR of the frontal lobe in APOE ε2 carriers than non-carriers. Furthermore, fALFF of IPL was correlated with the visuospatial function (r = -0.16, p < 0.05). Conclusion: APOE ε2 carriers might have a better brain reservation when coping with AD-related pathologies.

18.
Sci Rep ; 11(1): 5148, 2021 03 04.
Artigo em Inglês | MEDLINE | ID: mdl-33664342

RESUMO

This study aimed to clarify and provide clinical evidence for which computed tomography (CT) assessment method can more appropriately reflect lung lesion burden of the COVID-19 pneumonia. A total of 244 COVID-19 patients were recruited from three local hospitals. All the patients were assigned to mild, common and severe types. Semi-quantitative assessment methods, e.g., lobar-, segmental-based CT scores and opacity-weighted score, and quantitative assessment method, i.e., lesion volume quantification, were applied to quantify the lung lesions. All four assessment methods had high inter-rater agreements. At the group level, the lesion load in severe type patients was consistently observed to be significantly higher than that in common type in the applications of four assessment methods (all the p < 0.001). In discriminating severe from common patients at the individual level, results for lobe-based, segment-based and opacity-weighted assessments had high true positives while the quantitative lesion volume had high true negatives. In conclusion, both semi-quantitative and quantitative methods have excellent repeatability in measuring inflammatory lesions, and can well distinguish between common type and severe type patients. Lobe-based CT score is fast, readily clinically available, and has a high sensitivity in identifying severe type patients. It is suggested to be a prioritized method for assessing the burden of lung lesions in COVID-19 patients.


Assuntos
COVID-19/diagnóstico por imagem , Pulmão/diagnóstico por imagem , Radiografia Torácica/métodos , Tomografia Computadorizada por Raios X/métodos , Adulto , Fatores Etários , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Estudos Retrospectivos , Índice de Gravidade de Doença
19.
Front Aging Neurosci ; 12: 572086, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33328954

RESUMO

Background: The corpus callosum (CC) is an important feature of Parkinson's disease (PD) not only in motor but also in non-motor functions. However, CC is not a homogeneous component, and the damage of specific subsection may contribute to corresponding clinical deficit. Objective: The objective of the study is to investigate the structural alterations of different callosal subsections cross-sectionally and longitudinally in PD and evaluate their relationships to clinical performance. Methods: Thirty-nine PD patients who had been longitudinally reexamined and 82 normal controls (NC) were employed. According to their specific callosal-cortical connectivity, 3D CC was divided into five subsections (including prefrontal, premotor, motor, somatosensory, and temporal-parietal-occipital subsection). The fractional anisotropy (FA), mean diffusivity (MD), and volume of whole CC and its subsections were computed and compared between groups. Regression model was constructed to explore the relationships between callosal structure and clinical performance. Results: At baseline, PD did not show any significant macro/microstructural difference compared with NC. During disease course, there was a decreased FA and increased MD of whole CC as well as its subsections (except temporal-parietal-occipital subsection), and the volume of motor subsection was decreased. Moreover, the FA of temporal-parietal-occipital subsection and volume of motor subsection were correlated with the mood domain at baseline, and the MD of somatosensory subsection was associated with the motor domain at follow-up. Conclusion: The structure of CC and its connectivity-specific subsections remain preserved at a relatively early stage in PD and are progressively disrupted during disease course. Besides, different callosal subsections possess specific associations with clinical performance in PD.

20.
Front Aging Neurosci ; 12: 554660, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33178007

RESUMO

Objective: To investigate relationships between whole-brain functional changes and the performance of multiple cognitive functions in early Parkinson's disease (PD). Methods: In the current study, we evaluated resting-state functional MRI (rsfMRI) data and neuropsychological assessments for various cognitive functions in a cohort with 84 early PD patients from the Parkinson's Progression Markers Initiative (PPMI). Eigenvector centrality (EC) mapping based on rsfMRI was used to identify the functional connectivity of brain areas correlated with different neuropsychological scores at a whole-brain level. Results: Our study demonstrated that in the early PD patients, scores of Letter Number Sequencing (LNS) were positively correlated with EC in the left inferior occipital gyrus (IOG) and lingual gyrus. The immediate recall scores of Hopkins Verbal Learning Test-Revised (HVLT-R) were positively correlated with EC in the left superior frontal gyrus. No correlation was found between the EC and other cognitive performance scores. Conclusions: Functional alternations in the left occipital lobe (inferior occipital and lingual gyrus) and left superior frontal gyrus may account for the performance of working memory and immediate recall memory, respectively in early PD. These results may broaden the understanding of the potential mechanism of cognitive impairments in early PD.

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