Diffusion and structural MRI as potential biomarkers in people with Parkinson's disease and cognitive impairment.

OBJECTIVE: To explore the neuroimage change in Parkinson's disease (PD) patients with cognitive impairments, this study investigated the correlation between plasma biomarkers and morphological brain changes in patients with normal cognition and mild cognitive impairment. The objective was to identify the potential target deposition regions of the plasma biomarkers and to search for the relevant early neuroimaging biomarkers on the basis of different cognitive domains. METHODS: Structural brain MRI and diffusion weighted images were analyzed from 49 eligible PD participants (male/female: 27/22; mean age: 73.4 ± 8.5 years) from a retrospective analysis. Plasma levels of α-synuclein, amyloid beta peptide, and total tau were collected. A comprehensive neuropsychological assessment of the general and specific cognitive domains was performed. Difference between PD patients with normal cognition and impairment was examined. Regression analysis was performed to evaluate the correlation between image-derived index and plasma biomarkers or neuropsychological assessments. RESULTS: Significant correlation was found between plasma Aß-42 level and fractional anisotropy of the middle occipital, angular, and middle temporal gyri of the left brain, as well as plasma T-tau level and the surface area of the isthmus or the average thickness of the posterior part of right cingulate gyrus. Visuospatial and executive function is positively correlated with axial diffusivity in bilateral cingulate gyri. CONCLUSION: In nondemented PD patients, the target regions for plasma deposition might be located in the cingulate, middle occipital, angular, and middle temporal gyri. Changes from multiple brain regions can be correlated to the performance of different cognitive domains. CLINICAL RELEVANCE STATEMENT: Cognitive impairment in Parkinson's disease is primarily linked to biomarkers associated with Alzheimer's disease rather than those related to Parkinson's disease and resembles the frontal variant of Alzheimer's disease, which may guide management strategies for cognitive impairment in Parkinson's disease. KEY POINTS: • Fractional anisotropy, surface area, and thickness in the cingulate, middle occipital, angular, and middle temporal gyri can be significantly correlated with plasma Aß-42 and T-tau level. • Axial diffusivity in the cingulate gyri was correlated with visuospatial and executive function. • The pattern of cognitive impairment in Parkinson's disease can be similar to the frontal variant than typical Alzheimer's disease.

The neural basis of pain during labor.

Characterizing a labor pain-related neural signature is a key prerequisite for devising optimized pharmacologic and nonpharmacologic labor pain relief methods. The aim of this study was to describe the neural basis of labor pain and to provide a brief summary of how epidural anesthesia may affect pain-related neuronal activity during labor. Possible future directions are also highlighted. By taking advantage of functional magnetic resonance imaging, brain activation maps and functional neural networks of women during labor that have been recently characterized were compared between pregnant women who received epidural anesthesia and those who did not. In the subgroup of women who did not receive epidural anesthesia, labor-related pain elicited activations in a distributed brain network that included regions within the primary somatosensory cortex (postcentral gyrus and left parietal operculum cortex) and within the traditional pain network (lentiform nucleus, insula, and anterior cingulate gyrus). The activation maps of women who had been administered epidural anesthesia were found to be different-especially with respect to the postcentral gyrus, the insula, and the anterior cingulate gyrus. Parturients who received epidural anesthesia were also compared with those who did not in terms of functional connectivity from selected sensory and affective regions. When analyzing women who did not receive epidural anesthesia, marked bilateral connections from the postcentral gyrus to the superior parietal lobule, supplementary motor area, precentral gyrus, and the right anterior supramarginal gyrus were observed. In contrast, women who received epidural anesthesia showed fewer connections from the postcentral gyrus-being limited to the superior parietal lobule and supplementary motor area. Importantly, one of the most noticeable effects of epidural anesthesia was observed in the anterior cingulate cortex-a primary region that modulates pain perception. The increased outgoing connectivity from the anterior cingulate cortex in women who received epidural anesthesia indicates that the cognitive control exerted by this area might play a major role in the relief from labor pain. These findings not only affirmed the existence of a brain signature for pain experienced during labor, but they also showed that this signature can be altered by the administration of epidural anesthesia. This finding raises a question about the extent to which the cingulo-frontal cortex may exert top-down influences to gate women's experiences of labor-related pain. Because the anterior cingulate cortex is also involved in the processing and modulation of emotional content, such as fear and anxiety, a related question is about the extent to which the use of epidural anesthesia can affect different components of pain perception. Finally, inhibition of anterior cingulate cortex neurons may represent a potential new therapeutic target for alleviating labor-associated pain.

Oct4 and Nanog directly regulate Dnmt1 to maintain self-renewal and undifferentiated state in mesenchymal stem cells.

The roles of Oct4 and Nanog in maintaining self-renewal and undifferentiated status of adult stem cells are unclear. Here, increase in Oct4 and Nanog expression along with increased proliferation and differentiation potential but decreased spontaneous differentiation were observed in early-passage (E), hypoxic culture (H), and p21 knockdown (p21KD) mesenchymal stem cells (MSCs) compared to late-passage (L), normoxic culture (N), and scrambled shRNA-overexpressed (Scr) MSCs. Knockdown of Oct4 and Nanog in E, H, and p21KD MSCs decreased proliferation and differentiation potential and enhanced spontaneous differentiation, whereas overexpression of Oct4 and Nanog in L, N, and Scr MSCs increased proliferation and differentiation potential and suppressed spontaneous differentiation. Oct4 and Nanog upregulate Dnmt1 through direct binding to its promoter, thereby leading to the repressed expression of p16 and p21 and genes associated with development and lineage differentiation. These data demonstrate the important roles of Oct4 and Nanog in maintaining MSC properties.

Potential predictors for health-related quality of life in stroke patients undergoing inpatient rehabilitation.

BACKGROUND: Improving HRQOL is the desired outcome for patients with stroke undergoing inpatient rehabilitation services. This study aimed to comprehensively identify the potential health-related quality of life (HRQOL) predictors in patients with stroke undergoing inpatient rehabilitation within the first year after stroke; thus far, such an investigation has not been conducted. METHODS: We enrolled 119 patients (88 males, 31 females) with stroke, and examined 12 potential predictors: age, sex, stroke type, stroke side, duration after onset, cognition (Mini-Mental State Examination; MMSE), depression (Beck Depression Inventory-II), stroke severity (National Institutes of Health Stroke Scale; NIHSS), upper- and lower-extremity motor function scores of the Fugl-Meyer Assessment (FMA) scale, balance (Berg Balance Scale; BBS), and functional status (Functional Independence Measure). HRQOL was measured using Stroke Impact Scale (SIS) 3.0. RESULTS: NIHSS score predicted the strength domain and total SIS score (41.5% and 41.7% of the variances, respectively). BBS score was a major predictor of mobility and participation/role domains (48.6% and 10% of the variances, respectively). MMSE score predicted the memory and communication domains (22.5% and 36.3% of the variances, respectively). Upper extremity score of the FMA scale predicted the daily living/instrumental activities of daily life and hand function domains (40.3% and 20.6% of the variances, respectively). Stroke side predicted the emotion domain (11.6% of the variance). CONCLUSIONS: NIHSS, MMSE, BBS, FMA, and stroke side predicted most HRQOL domains. These findings suggest that different factors predicted various HRQOL domains in patients with stroke.

Hypoxia inhibits senescence and maintains mesenchymal stem cell properties through down-regulation of E2A-p21 by HIF-TWIST.

Although low-density culture provides an efficient method for rapid expansion of human mesenchymal stem cells (MSCs), MSCs enriched by this method undergo senescence and lose their stem cell properties, which could be preserved by combining low-density and hypoxic culture. The mechanism was mediated through direct down-regulation of E2A-p21 by the hypoxia-inducible factor-1α (HIF-1α)-TWIST axis. Expansion under normoxia induced E2A and p21 expression, which were abrogated by overexpression of TWIST, whereas siRNA against TWIST up-regulated E2A and p21 in hypoxic cells. Furthermore, siRNA against p21 in normoxic cells enhanced proliferation and increased differentiation potential, whereas overexpression of p21 in hypoxic cells induced a decrease in proliferation and a loss of differentiation capacity. More importantly, MSCs expanded under hypoxic conditions by up to 100 population doublings, exhibited telomerase activity with maintained telomere length, normal karyotyping, and intact genetic integrity, and did not form tumors. These results support low-density hypoxic culture as a method for efficiently expanding MSCs without losing stem cell properties or increasing tumorigenicity.

Diffusion tensor imaging for the differential diagnosis of Parkinsonism by machine learning.

BACKGROUND: There are currently no specific tests for either idiopathic Parkinson's disease or Parkinson-plus syndromes. The study aimed to investigate the diagnostic performance of features extracted from the whole brain using diffusion tensor imaging concerning parkinsonian disorders. METHODS: The retrospective data yielded 625 participants (average age: 61.4 ± 8.2, men/women: 313/312; healthy controls/idiopathic Parkinson's disease/multiple system atrophy/progressive supranuclear palsy: 219/286/51/69) between 2008 and 2017. Diffusion-weighted images were obtained using a 3T MR scanner. The 90th, 50th, and 10th percentiles of fractional anisotropy and mean/axial/radial diffusivity from each parcellated brain area were recorded. Statistical analysis was evaluated based on the features extracted from the whole brain, as determined using discriminant function analysis and support vector machine. 20% of the participants were used as an independent blind dataset with 5 times cross-verification. Diagnostic performance was evaluated by the sensitivity and the F1 score. RESULTS: Diagnoses were accurate for distinguishing idiopathic Parkinson's disease from healthy control and Parkinson-plus syndromes (87.4 ± 2.1% and 82.5 ± 3.9%, respectively). Diagnostic F1 scores varied for Parkinson-plus syndromes with 67.2 ± 3.8% for multiple system atrophy and 71.6 ± 3.5% for progressive supranuclear palsy. For early and late detection of idiopathic Parkinson's disease, the diagnostic performance was 79.2 ± 7.4% and 84.4 ± 6.9%, respectively. The diagnostic performance was 68.8 ± 11.0% and 52.5 ± 8.9% in early and late detection to distinguish different Parkinson-plus syndromes. CONCLUSIONS: Features extracted from diffusion tensor imaging of the whole brain can provide objective evidence for the diagnosis of healthy control, idiopathic Parkinson's disease, and Parkinson-plus syndromes with fair to very good diagnostic performance.

A fixel-based analysis of white matter reductions early detects Parkinson disease with mild cognitive impairment.

BACKGROUND: White matter (WM) tract alterations are early signs of cognitive impairment in Parkinson disease (PD) patients. Fixel-based analysis (FBA) has advantages over traditional diffusion tensor imaging in managing complex and crossing fibers. We used FBA to measure fiber-specific changes in patients with PD mild cognitive impairment (PD-MCI) and PD normal cognition (PD-NC). METHODS: Seventy-one patients with PD without dementia were included: 39 PD-MCI and 32 PD-NC. All underwent diffusion-weighted imaging, clinical examinations, and tests to evaluate their cognitive function globally and in five cognitive domains. FBA was used to investigate fiber-tract alterations and compare PD-MCI with PD-NC subjects. Correlations with each cognitive test were analyzed. RESULTS: Patients with PD-MCI were significantly older (P = 0.044), had a higher male-to-female ratio (P = 0.006) and total Unified Parkinson's Disease Rating Scale score (P = 0.001). All fixel-based metrics were significantly reduced within the body of the corpus callosum and superior corona radiata in PD-MCI patients (family-wise error-corrected P value < 0.05) compared with PD-NC patients. The cingulum, superior longitudinal fasciculi, and thalamocortical circuit exhibited predominantly fiber-bundle cross-section (FC) changes. In regression analysis, reduced FC values in cerebellar circuits were associated with poor motor function in PD-MCI patients and poor picture-naming ability in PD-NC patients. CONCLUSIONS: PD-MCI patients have significant WM alterations compared with PD-NC patients. FBA revealed these changes in various bundle tracts, helping us to better understand specific WM changes that are functionally implicated in PD cognitive decline. FBA is potentially useful in detecting early cognitive decline in PD.

Curriculum Based Multi-Task Learning for Parkinson's Disease Detection.

There is great interest in developing radiological classifiers for diagnosis, staging, and predictive modeling in progressive diseases such as Parkinson's disease (PD), a neurodegenerative disease that is difficult to detect in its early stages. Here we leverage severity-based meta-data on the stages of disease to define a curriculum for training a deep convolutional neural network (CNN). Typically, deep learning networks are trained by randomly selecting samples in each mini-batch. By contrast, curriculum learning is a training strategy that aims to boost classifier performance by starting with examples that are easier to classify. Here we define a curriculum to progressively increase the difficulty of the training data corresponding to the Hoehn and Yahr (H&Y) staging system for PD (total N=1,012; 653 PD patients, 359 controls; age range: 20.0-84.9 years). Even with our multi-task setting using pre-trained CNNs and transfer learning, PD classification based on T1-weighted (T1-w) MRI was challenging (ROC AUC: 0.59-0.65), but curriculum training boosted performance (by 3.9%) compared to our baseline model. Future work with multimodal imaging may further boost performance.

Comparison of Anatomical and Diffusion MRI for detecting Parkinson's Disease using Deep Convolutional Neural Network.

Parkinson's disease (PD) is a progressive neurodegenerative disease that affects over 10 million people worldwide. Brain atrophy and microstructural abnormalities tend to be more subtle in PD than in other age-related conditions such as Alzheimer's disease, so there is interest in how well machine learning methods can detect PD in radiological scans. Deep learning models based on convolutional neural networks (CNNs) can automatically distil diagnostically useful features from raw MRI scans, but most CNN-based deep learning models have only been tested on T1-weighted brain MRI. Here we examine the added value of diffusion-weighted MRI (dMRI) - a variant of MRI, sensitive to microstructural tissue properties - as an additional input in CNN-based models for PD classification. Our evaluations used data from 3 separate cohorts - from Chang Gung University, the University of Pennsylvania, and the PPMI dataset. We trained CNNs on various combinations of these cohorts to find the best predictive model. Although tests on more diverse data are warranted, deep-learned models from dMRI show promise for PD classification. Clinical Relevance: This study supports the use of diffusion-weighted images as an alternative to anatomical images for AI-based detection of Parkinson's disease.

Comparison of Anatomical and Diffusion MRI for detecting Parkinson's Disease using Deep Convolutional Neural Network.

Parkinson's disease (PD) is a progressive neurodegenerative disease that affects over 10 million people worldwide. Brain atrophy and microstructural abnormalities tend to be more subtle in PD than in other age-related conditions such as Alzheimer's disease, so there is interest in how well machine learning methods can detect PD in radiological scans. Deep learning models based on convolutional neural networks (CNNs) can automatically distil diagnostically useful features from raw MRI scans, but most CNN-based deep learning models have only been tested on T1-weighted brain MRI. Here we examine the added value of diffusion-weighted MRI (dMRI) - a variant of MRI, sensitive to microstructural tissue properties - as an additional input in CNN-based models for PD classification. Our evaluations used data from 3 separate cohorts - from Chang Gung University, the University of Pennsylvania, and the PPMI dataset. We trained CNNs on various combinations of these cohorts to find the best predictive model. Although tests on more diverse data are warranted, deep-learned models from dMRI show promise for PD classification.Clinical Relevance- This study supports the use of diffusion-weighted images as an alternative to anatomical images for AI-based detection of Parkinson's disease.

Mesenchymal stem cells promote formation of colorectal tumors in mice.

BACKGROUND & AIMS: Tumor-initiating cells are a subset of tumor cells with the ability to form new tumors; however, they account for less than 0.001% of the cells in colorectal or other types of tumors. Mesenchymal stem cells (MSCs) integrate into the colorectal tumor stroma; we investigated their involvement in tumor initiation. METHODS: Human colorectal cancer cells, MSCs, and a mixture of both cell types were injected subcutaneously into immunodeficient mice. We compared the ability of each injection to form tumors and investigated the signaling pathway involved in tumor initiation. RESULTS: A small number (≤ 10) of unsorted, CD133⁻, CD166⁻, epithelial cell adhesion molecule⁻(EpCAM⁻), or CD133⁻/CD166⁻/EpCAM⁻ colorectal cancer cells, when mixed with otherwise nontumorigenic MSCs, formed tumors in mice. Secretion of interleukin (IL)-6 by MSCs increased the expression of CD133 and activation of Janus kinase 2-signal transducer and activator of transcription 3 (STAT3) in the cancer cells, and promoted sphere and tumor formation. An antibody against IL-6 or lentiviral-mediated transduction of an interfering RNA against IL-6 in MSCs or STAT3 in cancer cells prevented the ability of MSCs to promote sphere formation and tumor initiation. CONCLUSIONS: IL-6, secreted by MSCs, signals through STAT3 to increase the numbers of colorectal tumor-initiating cells and promote tumor formation. Reagents developed to disrupt this process might be developed to treat patients with colorectal cancer.

Deep learning based diagnosis of Parkinson's Disease using diffusion magnetic resonance imaging.

The diagnostic performance of a combined architecture on Parkinson's disease using diffusion tensor imaging was evaluated. A convolutional neural network was trained from multiple parcellated brain regions. A greedy algorithm was proposed to combine the models from individual regions into a complex one. Total 305 Parkinson's disease patients (aged 59.9±9.7 years old) and 227 healthy control subjects (aged 61.0±7.4 years old) were enrolled from 3 retrospective studies. The participants were divided into training with ten-fold cross-validation (N = 432) and an independent blind dataset (N = 100). Diffusion-weighted images were acquired from a 3T scanner. Fractional anisotropy and mean diffusivity were calculated and was subsequently parcellated into 90 cerebral regions of interest based on the Automatic Anatomic Labeling template. A convolutional neural network was implemented which contained three convolutional blocks and a fully connected layer. Each convolutional block consisted of a convolutional layer, activation layer, and pooling layer. This model was trained for each individual region. A greedy algorithm was implemented to combine multiple regions as the final prediction. The greedy algorithm predicted the area under curve of 94.1±3.2% from the combination of fractional anisotropy from 22 regions. The model performance analysis showed that the combination of 9 regions is equivalent. The best area under curve was 74.7±5.4% from the right postcentral gyrus. The current study proposed an architecture of convolutional neural network and a greedy algorithm to combine from multiple regions. With diffusion tensor imaging, the algorithm showed the potential to distinguish patients with Parkinson's disease from normal control with satisfactory performance.

Fixel-Based Analysis Effectively Identifies White Matter Tract Degeneration in Huntington's Disease.

Microstructure damage in white matter might be linked to regional and global atrophy in Huntington's Disease (HD). We hypothesize that degeneration of subcortical regions, including the basal ganglia, is associated with damage of white matter tracts linking these affected regions. We aim to use fixel-based analysis to identify microstructural changes in the white matter tracts. To further assess the associated gray matter damage, diffusion tensor-derived indices were measured from regions of interest located in the basal ganglia. Diffusion weighted images were acquired from 12 patients with HD and 12 healthy unrelated controls using a 3 Tesla scanner. Reductions in fixel-derived metrics occurs in major white matter tracts, noticeably in corpus callosum, internal capsule, and the corticospinal tract, which were closely co-localized with the regions of increased diffusivity in basal ganglia. These changes in diffusion can be attributed to potential axonal degeneration. Fixel-based analysis is effective in studying white matter tractography and fiber changes in HD.

Fixel-Based Analysis of White Matter Degeneration in Patients With Progressive Supranuclear Palsy or Multiple System Atrophy, as Compared to Parkinson's Disease.

Introduction: White matter degeneration may contribute to clinical symptoms of parkinsonism. Objective: We used fixel-based analysis (FBA) to compare the extent and patterns of white matter degeneration in different parkinsonian syndromes-including idiopathic Parkinson's disease (PD), multiple system atrophy (MSA), and progressive supranuclear palsy (PSP). Methods: This is a retrospective interpretation of prospectively acquired data of patients recruited in previous studies during 2008 and 2019. Diffusion-weighted images were acquired on a 3-Tesla scanner (diffusion weighting b = 1000 s/mm2-applied along either 64 or 30 non-collinear directions) from 53 patients with PD (men/women: 29/24; mean age: 65.06 ± 5.51 years), 47 with MSA (men/women: 20/27; mean age: 63.00 ± 7.19 years), and 50 with PSP men/women: 20/30; mean age: 65.96 ± 3.14 years). Non-parametric permutation tests were used to detect intergroup differences in fixel-related indices-including fiber density, fiber cross-section, and their combination. Results: Patterns of white matter degeneration were significantly different between PD and atypical parkinsonisms (MSA and PSP). Compared with patients with PD, those with MSA and PSP showed a more extensive white matter involvement-noticeably descending tracts from primary motor cortex to corona radiata and cerebral peduncle. Lesions of corpus callosum were specific to PSP and absent in both MSA and PD. Discussion: FBA identified specific patterns of white matter changes in MSA and PSP patients compared to PD. Our results proved the utility of FBA in evaluation of implied biological processes of white matter changes in parkinsonism. Our study set the stage for future applications of this technique in patients with parkinsonian syndromes.

T1 and T2∗ relaxation time in the parcellated myocardium of healthy Taiwanese participants: A single center study.

BACKGROUND: Quantitative maps from cardiac MRI provide objective information for myocardial tissue. The study aimed to report the T1 and T2∗ relaxation time and its relationship with clinical parameters in healthy Taiwanese participants. METHODS: Ninety-three participants were enrolled between 2014 and 2016 (Males/Females: 43/50; age: 49.7 ± 11.3/49.9 ± 10.3). T1 and T2∗ weighted images were obtained by MOLLI recovery and 3D fully flow compensated gradient echo sequences with a 3T MR scanner, respectively. The T1 map of the myocardium was parcellated into 16 partitions from the American Heart Association. The septal part of basal, mid-cavity, and apical view was selected for the T2∗ map. The difference of quantitative map by sex and age groups were evaluated by Student's TTEST and ANOVA, respectively. The relationship between T1, T2∗ map, and clinical parameters, such as ejection fraction, pulse rate, and blood pressures, were evaluated with partial correlation by controlling BMI and age. RESULTS: Male participants decreased T1 relaxation time in partitions which located in the mid-cavity and apical before 55 years old compared with females (Male/Female: 1143.1.4 ± 72.0-1191.1 ± 37.0/1180.1 ± 54.5-1326.1 ± 113.3 msec, p < 0.01). For female participants, T1 relaxation time was correlated negatively with systolic pressure (p < 0.01) and pulse rate (p < 0.01) before 45 years old. Besides, T1 and T2∗ relaxation time were positively and negatively correlated with ejection fraction and pulse rate after 45 years old in male participants, respectively. Decreased T2∗ relaxation time could be noticed in participants after 45 years old compared with youngers (26.0 ± 6.5/21.9 ± 8.0 msec; 25.2 ± 5.0/21.6 ± 7.2 msec, p < 0.05). CONCLUSION: Reference T1 and T2∗ relaxation time from cardiac MRI in healthy Taiwanese participants were provided with sex and age-dependent manners. The relationship between clinical parameters and T1 or T2∗ relaxation time was also established and could be further investigated for its potential application in healthy/sub-healthy participants.

Overexpression of hTERT increases stem-like properties and decreases spontaneous differentiation in human mesenchymal stem cell lines.

To overcome loss of stem-like properties and spontaneous differentiation those hinder the expansion and application of human mesenchymal stem cells (hMSCs), we have clonally isolated permanent and stable human MSC lines by ectopic overexpression of primary cell cultures of hMSCs with HPV 16 E6E7 and human telomerase reverse transcriptase (hTERT) genes. These cells were found to have a differentiation potential far beyond the ordinary hMSCs. They expressed trophoectoderm and germline specific markers upon differentiation with BMP4 and retinoic acid, respectively. Furthermore, they displayed higher osteogenic and neural differentiation efficiency than primary hMSCs or hMSCs expressed HPV16 E6E7 alone with a decrease in methylation level as proven by a global CpG island methylation profile analysis. Notably, the demethylated CpG islands were highly associated with development and differentiation associated genes. Principal component analysis further pointed out the expression profile of the cells converged toward embryonic stem cells. These data demonstrate these cells not only are a useful tool for the studies of cell differentiation both for the mesenchymal and neurogenic lineages, but also provide a valuable source of cells for cell therapy studies in animal models of skeletal and neurological disorders.

Fibronectin and laminin promote differentiation of human mesenchymal stem cells into insulin producing cells through activating Akt and ERK.

BACKGROUND: Islet transplantation provides a promising cure for Type 1 diabetes; however it is limited by a shortage of pancreas donors. Bone marrow-derived multipotent mesenchymal stem cells (MSCs) offer renewable cells for generating insulin-producing cells (IPCs). METHODS: We used a four-stage differentiation protocol, containing neuronal differentiation and IPC-conversion stages, and combined with pellet suspension culture to induce IPC differentiation. RESULTS: Here, we report adding extracellular matrix proteins (ECM) such as fibronectin (FN) or laminin (LAM) enhances pancreatic differentiation with increases in insulin and Glut2 gene expressions, proinsulin and insulin protein levels, and insulin release in response to elevated glucose concentration. Adding FN or LAM induced activation of Akt and ERK. Blocking Akt or ERK by adding LY294002 (PI3K specific inhibitor), PD98059 (MEK specific inhibitor) or knocking down Akt or ERK failed to abrogate FN or LAM-induced enhancement of IPC differentiation. Only blocking both of Akt and ERK or knocking down Akt and ERK inhibited the enhancement of IPC differentiation by adding ECM. CONCLUSIONS: These data prove IPC differentiation by MSCs can be modulated by adding ECM, and these stimulatory effects were mediated through activation of Akt and ERK pathways.

Fibroblast growth factor 9 stimulates steroidogenesis in postnatal Leydig cells.

Fibroblast growth factor 9 (FGF9) is a potent mitogen and survival factor required for morphogenesis during embryonic development and numerous biological functions at adulthood. The reproductive phenotype of mice lacking Fgf9 gene exhibits male to female sexual reversal, suggesting a crucial role of Fgf9 in male sex determination. Our previous study showed that polymorphic microsatellite of FGF9 genes is associated with 46XY female with ambiguous genitalia, implying that the aberrant expression of FGF9 might affect androgen secretion. In this study, we aimed to investigate the effect of FGF9 on testosterone production in mouse Leydig cell and to study the signalling pathways by which FGF9 modulate steroidogenesis. Our results show that mRNAs of Fgf9 and Fgfr isoforms (Fgfr2IIIc, Fgfr3 and Fgfr4) were all expressed in mouse Leydig cells. FGF9 significantly stimulates mouse Leydig cell testosterone production in a dose- and time-dependent manner. Ras-MAPK, PI3K and PKA signalling pathways are involved in the FGF9-induced steroidogenesis. These results provide supportive evidence linking the aberrant expression of FGF9 to human gonadal dysgenesis and suggest a role of FGF9 in postnatal testicular development.

A Method for the Prediction of Clinical Outcome Using Diffusion Magnetic Resonance Imaging: Application on Parkinson's Disease.

Robust early prediction of clinical outcomes in Parkinson's disease (PD) is paramount for implementing appropriate management interventions. We propose a method that uses the baseline MRI, measuring diffusion parameters from multiple parcellated brain regions, to predict the 2-year clinical outcome in Parkinson's disease. Diffusion tensor imaging was obtained from 82 patients (males/females = 45/37, mean age: 60.9 ± 7.3 years, baseline and after 23.7 ± 0.7 months) using a 3T MR scanner, which was normalized and parcellated according to the Automated Anatomical Labelling template. All patients were diagnosed with probable Parkinson's disease by the National Institute of Neurological Disorders and Stroke criteria. Clinical outcome was graded using disease severity (Unified Parkinson's Disease Rating Scale and Modified Hoehn and Yahr staging), drug administration (levodopa equivalent daily dose), and quality of life (39-item PD Questionnaire). Selection and regularization of diffusion parameters, the mean diffusivity and fractional anisotropy, were performed using least absolute shrinkage and selection operator (LASSO) between baseline diffusion index and clinical outcome over 2 years. Identified features were entered into a stepwise multivariate regression model, followed by a leave-one-out/5-fold cross validation and additional blind validation using an independent dataset. The predicted Unified Parkinson's Disease Rating Scale for each individual was consistent with the observed values at blind validation (adjusted R2 0.76) by using 13 features, such as mean diffusivity in lingual, nodule lobule of cerebellum vermis and fractional anisotropy in rolandic operculum, and quadrangular lobule of cerebellum. We conclude that baseline diffusion MRI is potentially capable of predicting 2-year clinical outcomes in patients with Parkinson's disease on an individual basis.

Acupuncture Effect and Mechanism for Treating Pain in Patients With Parkinson's Disease.

Non-motor symptoms of Parkinson's disease (PD) have been receiving increasing attention. Approximately half of patients with PD have experience PD-related pain. We investigated the effect and mechanism of acupuncture in patients with PD who have pain. PD patients with pain were divided into acupuncture group and control group. Nine patients completed acupuncture treatment; seven patients who received only an analgesic agent underwent resting-state functional magnetic resonance imaging (rs-fMRI) twice. fMRI was performed to evaluate the functional connectivity of the brain regions. After treatment, a decrease in total scores on the King's Parkinson's Disease Pain Scale (KPPS) and Unified Parkinson's Disease Rating Scale was observed in the acupuncture group (-46.2 and -21.6%, respectively). In the acupuncture group, increased connectivity was observed in four connections, one in the left hemisphere between the middle temporal gyrus (MTG) and precentral gyrus, and three in the right hemisphere between the postcentral gyrus and precentral gyrus, supramarginal gyrus and precentral gyrus, and MTG and insular cortex. A significant correlation was noted between the changes in functional connectivity and KPPS. The involved connection was between the left middle frontal gyrus and the right precentral gyrus (R = -0.698, P = 0.037). Acupuncture could relieve pain in PD patients by modulating brain regions related to both sensory-discriminative and emotional aspects. The present study might increase the confidence of users that acupuncture is an effective and safe analgesic tool that can relieve PD-related pain.