Deubiquitylase OTUD3 Mediates Endoplasmic Reticulum Stress through Regulating Fortilin Stability to Restrain Dopaminergic Neurons Apoptosis

OTU domain-containing protein 3 (OTUD3) knockout mice exhibited loss of nigral dopaminergic neurons and Parkinsonian symptoms. However, the underlying mechanisms are largely unknown. In this study, we observed that the inositol-requiring enzyme 1α (IRE1α)-induced endoplasmic reticulum (ER) stress was involved in this process. We found that the ER thickness and the expression of protein disulphide isomerase (PDI) were increased, and the apoptosis level was elevated in the dopaminergic neurons of OTUD3 knockout mice. These phenomena were ameliorated by ER stress inhibitor tauroursodeoxycholic acid (TUDCA) treatment. The ratio of p-IRE1α/IRE1α, and the expression of X-box binding protein 1-spliced (XBP1s) were remarkably increased after OTUD3 knockdown, which was inhibited by IRE1α inhibitor STF-083010 treatment. Moreover, OTUD3 regulated the ubiquitination level of Fortilin through binding with the OTU domain. OTUD3 knockdown resulted in a decrease in the interaction ability of IRE1α with Fortilin and finally enhanced the activity of IRE1α. Taken together, we revealed that OTUD3 knockout-induced injury of dopaminergic neurons might be caused by activating IRE1α signaling in ER stress. These findings demonstrated that OTUD3 played a critical role in dopaminergic neuron neurodegeneration, which provided new evidence for the multiple and tissue-dependent functions of OTUD3

Leaf wax and Sr‐Nd isotope evidence for high‐latitude dust input to the central South China sea and its implication for fertilization

Recent time-series from sediment traps show abnormally high chlorophyll-a concentrations and primary productivity in the oligotrophic central South China Sea (SCS), especially during wintertime. Here we present new insights from compound-specific hydrogen isotopic analysis of leaf wax n-alkanes and Sr-Nd isotope compositions extracted from four basin-wide surface sediment transects. We find that the deepest surface sediments in the central basin contain the most depleted n-alkane hydrogen isotopes, suggesting inputs from higher latitude soils in northern China. This is supported by the Sr-Nd isotope compositions of the same surface sediments. We propose that aeolian dust is transported by the winter monsoon and might fertilize the phytoplankton bloom in the central SCS. This process may have been enhanced in ancient times when the winter monsoon was stronger, driving both vertical mixing and dust transport to the central basin

Leaf wax and Sr‐Nd isotope evidence for high‐latitude dust input to the central South China sea and its implication for fertilization

Recent time-series from sediment traps show abnormally high chlorophyll-a concentrations and primary productivity in the oligotrophic central South China Sea (SCS), especially during wintertime. Here we present new insights from compound-specific hydrogen isotopic analysis of leaf wax n-alkanes and Sr-Nd isotope compositions extracted from four basin-wide surface sediment transects. We find that the deepest surface sediments in the central basin contain the most depleted n-alkane hydrogen isotopes, suggesting inputs from higher latitude soils in northern China. This is supported by the Sr-Nd isotope compositions of the same surface sediments. We propose that aeolian dust is transported by the winter monsoon and might fertilize the phytoplankton bloom in the central SCS. This process may have been enhanced in ancient times when the winter monsoon was stronger, driving both vertical mixing and dust transport to the central basin

Juxtaposed sequence stratigraphy, temporal-spatial variations of sedimentation and development of modern-forming forearc Lichi Melange in North Luzon Trough forearc basin onshore and offshore eastern Taiwan: An overview

The South China Sea oceanic lithosphere has been subducting eastward beneath the Huatung Basin/Philippine Sea Plate since the Early Miocene (similar to 18 Ma). The subduction is followed by the oblique collision between the Luzon arc and the subducting Eurasian plate from 6.5 Ma. The North Luzon Trough forearc strata and the Luzon arc are then obducted northwestward as the Coastal Range, eastern Taiwan, in the last 1 Ma. The collision propagates southward and is presently active in the region offshore SE Taiwan. Integrating seismic surveys offshore and a detailed forearc stratigraphy study onshore the Coastal Range, this paper overviews the characteristics of forearc deformation, dynamic sequence stratigraphy, temporal-spatial variations of forearc sedimentation and stratigraphic correlation onshore and offshore forearc sequences in response to the oblique convergent tectonics north of 20 degrees N. Combining onshore and offshore forearc geology together allows us to reconstruct a structural evolution of the North Luzon Trough forearc basin from subduction through collision to obduction, and to discuss the mechanism and processes responsible for developments of the modern-forming forearc Lichi Melange during the active Taiwan orogeny. Seismic surveys offshore show that forearc deformation in the subduction zone is primarily caused by increase of rear prism slope and west-vergent thrusting of forearc strata along the prism top since the early forearc sedimentation. East-vergent backthrusting occurs during the late forearc sedimentation and propagates arcward when the volcanic arc collides with the accretionary prism in the collision zone. Bivergent thrusting leads to a development of the forearc Huatung Ridge popup as a bathymetric high which further controls the sedimentation of the younger forearc sequence in the collision zone. In response to the syn-sedimentation deformation, forearc depocenter shifts progressively eastward. Forearc stratigraphy thus changes from two syn-sequences bounded by an unconformity in the subduction zone to three mega-sequences juxtaposed from west to east unconformably in the collision zone. As a consequence, the forearc deformation and stratigraphy in the oblique collision zone off SE Taiwan show a characteristic temporal-spatial pattern that the lowest mega-sequence with the most intensive deformation occurs restrictedly in the west, whiles the middle and the upper mega-sequences with mild deformation crop out in the center and the eastern part of the forearc basin, respectively. Detailed biostratigraphy study using planktonic foraminifera and calcareous nannoplanktons indicates that the forearc strata onshore the Coastal Range are also composed of three sequences (lower unit S-1: 6.5-5.8 Ma; middle unit S-2: 5.8-3.0 Ma; and upper unit S-3: < 3.0-1 Ma). They were previously mapped as lithostratigraphy units of the Lichi Melange (6.5-3.0 Ma) in the west and the coherent flysch sequences of the Fanshuliao Formation (5.8-3.0 Ma) and the Paliwan Formation (< 3.0-1 Ma) the east. However, the young coherent forearc sequences in the east thrust westward ubiquitously over the old and highly deformed Lichi Melange in the west along the listric east-dipping Tuluanshan fault during the obduction. Detailed biostratigraphy study reveals that the lower sequence unit S-1 exposes restrictedly in the Lichi Melange west of the Tuluanshan fault, whereas the middle sequence unit S-2 are either mapped as part of the Lichi Melange or the coherent Fanshuliao Formation in both sides of the Tuluanshan fault, respectively. The upper sequence unit S-3 exposes exclusively east of middle sequence unit S-2 in the eastern Coastal Range. Stratigraphy and sedimentology study also reveals a temporal-spatial sedimentation variation of the upper sequence unit S-3 owing to deformation of the sequence units S-1 and S-2 together as a Pliocene Forearc Ridge at similar to 3 Ma, a scenario analog to development of the modern Huatung Ridge at similar to 1 Ma in active collision zone offshore. Temporal-spatial pattern of forearc sequences onshore the Coastal Range suggests that these three sequence units are juxtaposed from west to east and are bounded by two unconformities analog to what occur today in the collision zone offshore SE Taiwan. The characteristic deformation and an eastward-youngling trend of strata distribution onshore the Coastal Range all indicate Syn-sedimentation deformation during the oblique collision in 6.5-1 Ma. Furthermore, along the N-S orogenic strike, events of the forearc sedimentation and bivergent thrusting occur earlier onshore the obduction zone in the north than the modem collision zone offshore in the south. Across the orogenic strike forearc strata get older and deformation gets intensive from east to west onshore the Coastal Range, a scenario analog to what observed in the oblique convergent region offshore SE Taiwan. A structure reconstruction reveals that the North Luzon Trough forearc strata have experienced multiple stages of thrust deformation from subduction through collision to obduction. These deformations account for the mechanism and processes to develop the modem-forming highly sheared SSZ-bearing forearc Lichi Melange tectonically in the western Coastal Range during the last 1 Ma

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset