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Patients with Parkinson’s disease undergo a loss of melanized neurons in substantia nigra pars compacta and locus coeruleus. Very few studies have assessed substantia nigra pars compacta and locus coeruleus pathology in Parkinson’s disease simultaneously with magnetic resonance imaging (MRI). Neuromelanin-sensitive MRI measures of substantia nigra pars compacta and locus coeruleus volume based on explicit magnetization transfer contrast have been shown to have high scan-rescan reproducibility in controls, but no study has replicated detection of Parkinson’s disease-associated volume loss in substantia nigra pars compacta and locus coeruleus in multiple cohorts with the same methodology. Two separate cohorts of Parkinson’s disease patients and controls were recruited from the Emory Movement Disorders Clinic and scanned on two different MRI scanners. In cohort 1, imaging data from 19 controls and 22 Parkinson’s disease patients were acquired with a Siemens Trio 3 Tesla scanner using a 2D gradient echo sequence with magnetization transfer preparation pulse. Cohort 2 consisted of 33 controls and 39 Parkinson’s disease patients who were scanned on a Siemens Prisma 3 Tesla scanner with a similar imaging protocol. Locus coeruleus and substantia nigra pars compacta volumes were segmented in both cohorts. Substantia nigra pars compacta volume (Cohort 1: p = 0.0148; Cohort 2: p = 0.0011) and locus coeruleus volume (Cohort 1: p = 0.0412; Cohort 2: p = 0.0056) were significantly reduced in the Parkinson’s disease group as compared to controls in both cohorts. This imaging approach robustly detects Parkinson’s disease effects on these structures, indicating that it is a promising marker for neurodegenerative neuromelanin loss.

Effect of minor chemical structures such as 1,2-diol content, ethylene content, tacticity, a degree of polymerization, and a degree of saponification of the main chain on biodegradability of polyvinyl alcohol (PVA) is summarized. Most PVA-degraders are Gram-negative bacteria belonging to the Pseudomonads and Sphingomonads, but Gram-positive bacteria also have PVA-degrading abilities. Several examples show symbiotic degradation of PVA by different mechanisms. Penicillium sp. is the only reported eukaryotic degrader. A vinyl alcohol oligomer-utilizing fungus, Geotrichum fermentans WF9101, has also been reported. Lignolytic fungi have displayed non-specific degradation of PVA. Extensive published studies have established a two-step process for the biodegradation of PVA. Some bacteria excrete extracellular PVA oxidase to yield oxidized PVA, which is partly under spontaneous depolymerization and is further metabolized by the second step enzyme (hydrolase). On the other hand, PVA (whole and depolymerized to some extent) must be taken up into the periplasmic space of some Gram-negative bacteria, where PVA is oxidized by PVA dehydrogenase, coupled to a respiratory chain. The complete pva operon was identified in Sphingopyxis sp. 113P3. Anaerobic biodegradability of PVA has also been suggested.

There have been successful applications of deep learning to functional magnetic resonance imaging (fMRI), where fMRI data were mostly considered to be structured grids, and spatial features from Euclidean neighbors were usually extracted by the convolutional neural networks (CNNs) in the computer vision field. Recently, CNN has been extended to graph data and demonstrated superior performance. Here, we define graphs based on functional connectivity and present a connectivity-based graph convolutional network (cGCN) architecture for fMRI analysis. Such an approach allows us to extract spatial features from connectomic neighborhoods rather than from Euclidean ones, consistent with the functional organization of the brain. To evaluate the performance of cGCN, we applied it to two scenarios with resting-state fMRI data. One is individual identification of healthy participants and the other is classification of autistic patients from normal controls. Our results indicate that cGCN can effectively capture functional connectivity features in fMRI analysis for relevant applications.

Most neuroimaging studies of resting state networks have concentrated on functional connectivity (FC) based on instantaneous correlation in a single network. In this study we investigated both FC and effective connectivity (EC) based on Granger causality of four important networks at resting state derived from functional magnetic resonance imaging data — default mode network (DMN), hippocampal cortical memory network (HCMN), dorsal attention network (DAN) and fronto-parietal control network (FPCN). A method called correlation-purged Granger causality analysis was used, not only enabling the simultaneous evaluation of FC and EC of all networks using a single multivariate model, but also accounting for the interaction between them resulting from the smoothing of neuronal activity by hemodynamics. FC was visualized using a force-directed layout upon which causal interactions were overlaid. FC results revealed that DAN is very tightly coupled compared to the other networks while the DMN forms the backbone around which the other networks amalgamate. The pattern of bidirectional causal interactions indicates that posterior cingulate and posterior inferior parietal lobule of DMN act as major hubs. The pattern of unidirectional causal paths revealed that hippocampus and anterior prefrontal cortex (aPFC) receive major inputs, likely reflecting memory encoding/retrieval and cognitive integration, respectively. Major outputs emanating from anterior insula and middle temporal area, which are directed at aPFC, may carry information about interoceptive awareness and external environment, respectively, into aPFC for integration, supporting the hypothesis that aPFC-seeded FPCN acts as a control network. Our findings indicate the following. First, regions whose activities are not synchronized interact via time-delayed causal influences. Second, the causal interactions are organized such that cingulo-parietal regions act as hubs. Finally, segregation of different resting state networks is not clear cut but only by soft boundaries. ►In resting state, regions whose activities are not instantaneously synchronized, interact via time-delayed causal influences ►The bi-directional causal interactions at rest are organized such that cingulo-parietal regions act as hubs ►Unidirectional causal paths revealed that hippocampus and anterior prefrontal cortex (aPFC) receive major inputs, likely reflecting memory encoding/retrieval and cognitive integration, respectively ►Major outputs emanating from anterior insula and middle temporal area, which are directed at aPFC, may carry information about interoceptive awareness and external environment, respectively, into aPFC for integration, supporting the hypothesis that aPFC-seeded FPCN acts as a control network ►Segregation of different resting state networks is not clear cut but only by soft boundaries

The diagnosis of Parkinson’s disease (PD) occurs after pathogenesis is advanced and many substantia nigra (SN) dopamine neurons have already died. Now that therapies to block this neuronal loss are under development, it is imperative that the disease be diagnosed at earlier stages and that the response to therapies is monitored. Recent studies suggest this can be accomplished by magnetic resonance imaging (MRI) detection of neuromelanin (NM), the characteristic pigment of SN dopaminergic, and locus coeruleus (LC) noradrenergic neurons. NM is an autophagic product synthesized via oxidation of catecholamines and subsequent reactions, and in the SN and LC it increases linearly during normal aging. In PD, however, the pigment is lost when SN and LC neurons die. As shown nearly 25 years ago by Zecca and colleagues, NM’s avid binding of iron provides a paramagnetic source to enable electron and nuclear magnetic resonance detection, and thus a means for safe and noninvasive measure in living human brain. Recent technical improvements now provide a means for MRI to differentiate between PD patients and age-matched healthy controls, and should be able to identify changes in SN NM with age in individuals. We discuss how MRI detects NM and how this approach might be improved. We suggest that MRI of NM can be used to confirm PD diagnosis and monitor disease progression. We recommend that for subjects at risk for PD, and perhaps generally for older people, that MRI sequences performed at regular intervals can provide a pre-clinical means to detect presymptomatic PD.

In this work, we investigated the effect of the regional variability of the hemodynamic response on the sensitivity of Granger causality (GC) analysis of functional magnetic resonance imaging (fMRI) data to neuronal causal influences. We simulated fMRI data by convolving a standard canonical hemodynamic response function (HRF) with local field potentials (LFPs) acquired from the macaque cortex and manipulated the causal influence and neuronal delays between the LFPs, the hemodynamic delays between the HRFs, the signal-to-noise ratio (SNR), and the sampling period (TR) to assess the effect of each of these factors on the detectability of the neuronal delays from GC analysis of fMRI. In our first bivariate implementation, we assumed the worst-case scenario of the hemodynamic delay being at the empirical upper limit of its normal physiological range and opposing the direction of neuronal delay. We found that, in the absence of HRF confounds, even tens of milliseconds of neuronal delays can be inferred from fMRI. However, in the presence of HRF delays which opposed neuronal delays, the minimum detectable neuronal delay was hundreds of milliseconds. In our second multivariate simulation, we mimicked the real situation more closely by using a multivariate network of four time series and assumed the hemodynamic and neuronal delays to be unknown and drawn from a uniform random distribution. The resulting accuracy of detecting the correct multivariate network from fMRI was well above chance and was up to 90% with faster sampling. Generically, under all conditions, faster sampling and low measurement noise improved the sensitivity of GC analysis of fMRI data to neuronal causality.

Cytokine effects on behavior may be related to alterations in glutamate metabolism. We therefore measured glutamate concentrations in brain regions shown to be affected by inflammatory stimuli including the cytokine interferon (IFN)-alpha. IFN-alpha is known to alter neural activity in the dorsal anterior cingulate cortex (dACC) and basal ganglia in association with symptoms of depression and increases in peripheral cytokines including the tumor necrosis factor (TNF) and its soluble receptor. Single-voxel magnetic resonance spectroscopy (MRS) was employed to measure glutamate concentrations normalized to creatine (Glu/Cr) in dACC and basal ganglia of 31 patients with hepatitis C before and after ∼ 1 month of either no treatment (n = 14) or treatment with IFN-alpha (n = 17). Depressive symptoms were measured at each visit using the Inventory of Depressive Symptoms-Clinician Rating (IDS-C) and the Multidimensional Fatigue Inventory. IFN-alpha was associated with a significant increase in Glu/Cr in dACC and left basal ganglia. Increases in dACC Glu/Cr were positively correlated with scores on the IDS-C in the group as a whole, but not in either group alone. Glu/Cr increases in left basal ganglia were correlated with decreased motivation in the group as a whole and in IFN-alpha-treated subjects alone. No Glu/Cr changes were found in the right basal ganglia, and no significant correlations were found between Glu/Cr and the inflammatory markers. IFN-alpha-induced increases in glutamate in dACC and basal ganglia are consistent with MRS findings in bipolar depression and suggest that inflammatory cytokines may contribute to glutamate alterations in patients with mood disorders and increased inflammation.

Neurocognitive aging researchers are increasingly focused on the locus coeruleus, a neuromodulatory brainstem structure that degrades with age. With this rapid growth, the field will benefit from consensus regarding which magnetic resonance imaging (MRI) metrics of locus coeruleus structure are most sensitive to age and cognition. To address this need, the current study acquired magnetization transfer- and diffusion-weighted MRI images in younger and older adults who also completed a free recall memory task. Results revealed significantly larger differences between younger and older adults for maximum than average magnetization transfer-weighted contrast (MTC), axial than mean or radial single-tensor diffusivity (DTI), and free than restricted multi-compartment diffusion (NODDI) metrics in the locus coeruleus; with maximum MTC being the best predictor of age group. Age effects for all imaging modalities interacted with sex, with larger age group differences in males than females for MTC and NODDI metrics. Age group differences also varied across locus coeruleus subdivision for DTI and NODDI metrics, and across locus coeruleus hemispheres for MTC. Within older adults, however, there were no significant effects of age on MTC or DTI metrics, only an interaction between age and sex for free diffusion. Finally, independent of age and sex, higher restricted diffusion in the locus coeruleus was significantly related to better (lower) recall variability, but not mean recall. Whereas MTC has been widely used in the literature, our comparison between the average and maximum MTC metrics, inclusion of DTI and NODDI metrics, and breakdowns by locus coeruleus subdivision and hemisphere make important and novel contributions to our understanding of the aging of locus coeruleus structure.

Anaplastic thyroid carcinoma (ATC) is an extremely malignant type of endocrine cancer frequently accompanied by extrathyroidal extension or metastasis through mechanisms that remain elusive. We screened for the CREB3 transcription - factor family in a large cohort, consisting of four microarray datasets. This revealed that CREB3L1 was specifically up regulated in ATC tissues and negatively associated with overall survival of patients with thyroid cancer. Consistently, high expression of CREB3L1 was negatively correlated with progression - free survival in an independent cohort. CREB3L1 knockdown dramatically attenuated invasion of ATC cells, whereas overexpression of CREB3L1 facilitated the invasion of papillary thyroid carcinoma (PTC) cells. Loss of CREB3L1 inhibited metastasis and tumor growth of ATC xenografts in zebrafish and nude mouse model. Single - cell RNA-sequencing analysis revealed that CREB3L1 expression gradually increased during the neoplastic progression of a thyroid follicular epithelial cell to an ATC cell, accompanied by the activation of the extracellular matrix (ECM) signaling. CREB3L1 knockdown significantly decreased the expression of collagen subtypes in ATC cells and the fibrillar collagen in xenografts. Due to the loss of CREB3L1, ATC cells were unable to activate alpha - smooth muscle actin (α - SMA) - positive cancer - associated fibroblasts (CAFs). After CREB3L1 knockdown, the presence of CAFs inhibited the growth of ATC spheroids and the metastasis of ATC cells. Further cytokine array screening showed that ATC cells activated α - SMA - positive CAFs through CREB3L1 - mediated IL - 1α production. Moreover, KPNA2 mediated the nuclear translocation of CREB3L1, thus allowing it to activate downstream ECM signaling. These results demonstrate that CREB3L1 maintains the CAF - like property of ATC cells by activating the ECM signaling, which remodels the tumor stromal microenvironment and drives the malignancy of ATC. Graphical Abstract

To investigate the process method to inhibit the cracking of the laser cladding layer, based on the concept of synchronized micro-forging, this paper applies a self-developed laser cladding synchronized rolling auxiliary device to prepare Ni60-WC cladding layer by laser cladding on the surface of Q235 steel substrate. An optical microscope, scanning electron microscope, Vickers microhardness tester, X-ray diffractometer, friction and wear tester, and three-dimensional optical profilometer were used to observe, test, and analyze the macroscopic morphology, microstructure, physical phase composition, microhardness and wear-resistant properties of the fused cladding layer. This paper focuses on comparing the observation of cracking defects with and without the application of a synchronized rolling-assisted device to prepare the cladding layer and analyzes the reasons for the different results. The results show that: the synchronized rolling auxiliary process can effectively inhibit the generation of cracks, synchronized roller in the synchronized rolling device, under the action of high laser power, produces the effect of a secondary heat source, which has the effect of heating and heat preservation on the fusion cladding layer, reduces the temperature gradient of the fusion cladding layer when it is cooled, and the accumulation of thermal stress is reduced. In the synchronized rolling process, the molten cladding layer is in the dynamic response to the recrystallization stage, the growth time of the grain is relatively longer, the grain size increases slightly, the hardness decreases slightly, but the plasticity and toughness increases, the amount of wear is reduced, and the wear resistance is improved.