Cell type- and region-specific translatomes in an MPTP mouse model of Parkinson's disease.

Parkinson's disease (PD) is the most common neurodegenerative movement disorder, characterized by the progressive loss of nigrostriatal dopaminergic neurons (DANs), involving the dysregulation of both neurons and glial cells. Cell type- and region-specific gene expression profiles can provide an effective source for revealing the mechanisms of PD. In this study, we adopted the RiboTag approach to obtain cell type (DAN, microglia, astrocytes)- and brain region (substantia nigra, caudate-putamen)-specific translatomes at an early stage in an MPTP-induced mouse model of PD. Through DAN-specific translatome analysis, the glycosphingolipid biosynthetic process was identified as a significantly downregulated pathway in the MPTP-treated mice. ST8Sia6, a key downregulated gene related to glycosphingolipid biosynthesis, was confirmed to be downregulated in nigral DANs from postmortem brains of patients with PD. Specific expression of ST8Sia6 in DANs exerts anti-inflammatory and neuroprotective effects in MPTP-treated mice. Through cell type (microglia vs. astrocyte) and brain region (substantia nigra vs. caudate-putamen) comparisons, nigral microglia showed the most intense immune responses. Microglia and astrocytes in the substantia nigra showed similar levels of activation in interferon-related pathways and interferon gamma (IFNG) was identified as the top upstream regulator in both cell types. This work highlights that the glycosphingolipid metabolism pathway in the DAN is involved in neuroinflammation and neurodegeneration in an MPTP mouse model of PD and provides a new data source for elucidating the pathogenesis of PD.

Trichosanthin-induced autophagy in gastric cancer cell MKN-45 is dependent on reactive oxygen species (ROS) and NF-κB/p53 pathway.

Trichosanthin (TCS), isolated from the root tuber of Trichosanthes kirilowii tubers in the Cucurbitaceae family, owns a great deal of biological and pharmacological activities including anti-virus and anti-tumor. TCS has been reported to induce cell apoptosis of a diversity of cancers, including cervical cancer, choriocarcinoma, and gastric cancer, etc. However, whether TCS would induce autophagy in gastric cancer cells was seldom investigated. In current study, human gastric cancer MKN-45 cell growth was significantly inhibited by TCS. The anti-proliferation effect of TCS was due to an increased autophagy, which was confirmed by monodansylcadervarine (MDC) staining, up-regulation of Autophagy protein 5 (Atg5), and conversion of LC3 I to LC3 II (autophagosome marker). In addition, TCS induced reactive oxygen species (ROS) in MKN-45 cells and ROS scavenger N-acetylcysteine (NAC) significantly reversed TCS-induced autophagy. Furthermore, NF-κB/p53 pathway was activated during the process of autophagy induced by TCS and the ROS generation was mediated by it in MKN-45 cells. In vivo results showed that TCS exerted significantly anti-tumor effect on MKN-45 bearing mice. Considering the clinical usage of TCS on other human diseases, these research progresses provided a new insight into cancer research and new therapeutic avenues for patients with gastric cancer.

Prediction of protein-protein interactions with clustered amino acids and weighted sparse representation.

With the completion of the Human Genome Project, bioscience has entered into the era of the genome and proteome. Therefore, protein-protein interactions (PPIs) research is becoming more and more important. Life activities and the protein-protein interactions are inseparable, such as DNA synthesis, gene transcription activation, protein translation, etc. Though many methods based on biological experiments and machine learning have been proposed, they all spent a long time to learn and obtained an imprecise accuracy. How to efficiently and accurately predict PPIs is still a big challenge. To take up such a challenge, we developed a new predictor by incorporating the reduced amino acid alphabet (RAAA) information into the general form of pseudo-amino acid composition (PseAAC) and with the weighted sparse representation-based classification (WSRC). The remarkable advantages of introducing the reduced amino acid alphabet is being able to avoid the notorious dimensionality disaster or overfitting problem in statistical prediction. Additionally, experiments have proven that our method achieved good performance in both a low- and high-dimensional feature space. Among all of the experiments performed on the PPIs data of Saccharomyces cerevisiae, the best one achieved 90.91% accuracy, 94.17% sensitivity, 87.22% precision and a 83.43% Matthews correlation coefficient (MCC) value. In order to evaluate the prediction ability of our method, extensive experiments are performed to compare with the state-of-the-art technique, support vector machine (SVM). The achieved results show that the proposed approach is very promising for predicting PPIs, and it can be a helpful supplement for PPIs prediction.

[The Function of Neuroinflammation in Parkinson Disease].

Parkinson disease (PD) is the second most common neurodegenerative disorder, characterized by a progressive loss of dopaminergic neurons in the substantia nigra (SN). The pathology of PD remains unclear. Recent findings suggests neuroinflammation plays a critical role in PD. Occurrence of neuroinflammation, including microglia and astrocyte activation, T lymphocyte infiltration and blood-brain barrier disruption, has been identified in PD. However, the mechanism of neuroinflammation regulation in PD is not fully deciphered. In this review, we focus on the cutting edge in researches of neuroinflammation in PD, which may provide us new ideas in prevention and recovery of PD.

Tumor necrosis factor and interleukin-6 gene polymorphisms and endometriosis risk in Asians: a systematic review and meta-analysis.

A relationship between endometriosis and tumor necrosis factor (TNF-α) and interleukin-6 (IL-6) gene polymorphisms has been raised for Asians. However, this topic is controversial. This study was a meta-analysis to explore whether TNF-α/IL-6 gene polymorphisms were associated with a risk of endometriosis in Asians. By searching PubMed, HuGENet, and China National Knowledge Infrastructure (CNKI) databases, 17 studies were identified and included (3372 cases and 4008 controls). The odds ratio (OR) with 95% confidence interval (CI) was used to assess the association between TNF-α/IL-6 gene polymorphisms and endometriosis risk. An association of TNF-α gene -1031T/C polymorphism with endometriosis was found (TT + TC vs. CC: OR 0.50, 95% CI 0.30-0.82, I(2) = 37.1%, P = 0.20; TT vs. CC: OR 0.50, 95% CI 0.30-0.82, I(2) = 43.0%, P = 0.173; TC vs. CC: OR 0.49, 95% CI 0.29-0.83, I(2) = 10.6%, P = 0.327). In addition, TNF-α-238A/G and IL-6 -174C/G gene polymorphisms were also likely to be associated with endometriosis in Asians. For the TNF-α-238A/G gene polymorphism, the OR was 1.577 (95% CI: 1.01-2.48). For the IL-6 -174C/G gene polymorphism, the OR was 1.554 (95% CI: 1.04-2.31). No associations were detected between the TNF-α-308A/G and IL-6 -634C/G polymorphisms and susceptibility to endometriosis. Our results indicate that the TNF-α gene -1031T/C polymorphism can reduce the risk of endometriosis, but for Asians, TNF-α-238A/G and IL-6 -174C/G gene polymorphisms may be a risk factor for endometriosis. No association was found for the TNF-α-308A/G and IL-6 -634C/G gene polymorphisms.

Site-specific phosphorylation protects glycogen synthase kinase-3ß from calpain-mediated truncation of its N and C termini.

Glycogen synthase kinase-3ß (GSK-3ß), a key regulator of neuronal apoptosis, is inhibited by the phosphorylation of Ser-9/Ser-389 and was recently shown to be cleaved by calpain at the N terminus, leading to its subsequent activation. In this study calpain was found to cleave GSK-3ß not only at the N terminus but also at the C terminus, and cleavage sites were identified at residues Thr-38-Thr-39 and Ile-384-Gln-385. Furthermore, the cleavage of GSK-3ß occurred in tandem with Ser-9 dephosphorylation during cerebellar granule neuron apoptosis. Increasing Ser-9 phosphorylation of GSK-3ß by inhibiting phosphatase 1/2A or pretreating with purified active Akt inhibited calpain-mediated cleavage of GSK-3ß at both N and C termini, whereas non-phosphorylatable mutant GSK-3ß S9A facilitated its cleavage. In contrast, Ser-389 phosphorylation selectively inhibited the cleavage of GSK-3ß at the C terminus but not the N terminus. Calpain-mediated cleavage resulted in three truncated products, all of which contained an intact kinase domain: ΔN-GSK-3ß (amino acids 39-420), ΔC-GSK-3ß (amino acids 1-384), and ΔN/ΔC-GSK-3ß (amino acids 39-384). All three truncated products showed increased kinase and pro-apoptotic activity, with ΔN/ΔC-GSK-3ß being the most active form. This observation suggests that the GSK-3ß C terminus acts as an autoinhibitory domain similar to the N terminus. Taken together, these findings demonstrate that calpain-mediated cleavage activates GSK-3ß by removing its N- and C-terminal autoinhibitory domains and that Ser-9 phosphorylation inhibits the cleavage of GSK-3ß at both termini. In contrast, Ser-389 phosphorylation inhibits only C-terminal cleavage but not N-terminal cleavage. These findings also identify a mechanism by which site-specific phosphorylation and calpain-mediated cleavage operate in concert to regulate GSK-3ß activity.

GSK-3α/ß-mediated phosphorylation of CRMP-2 regulates activity-dependent dendritic growth.

Neuronal activity shapes the dendritic arbour; however, most of the molecular players in this process remain to be identified. We observed that depolarization-induced neuronal activity causes an increase in the phosphorylation of glycogen synthase kinase-3 (GSK-3)α/ß on Ser21/9 in cerebellar granule neurons. Using several approaches, including gene knockdown and GSK-3α/ß(S21A/S21A/S9A/S9A) double knockin mice, we demonstrated that both GSK-3ß and GSK-3α mediate activity-dependent dendritic growth and that Ser21/9 phosphorylation of GSK-3α/ß plays an important role in this process. Collapsin response mediator protein-2 (CRMP-2), which is crucial for axon development, is phosphorylated at Thr514 and inactivated by GSK-3. We found CRMP-2 was located mainly in the dendrites of cerebellar granule neurons, in contrast to the axonal distribution in hippocampal neurons. Over-expression of CRMP-2 promoted and knockdown of CRMP-2 impaired dendritic growth, suggesting that CRMP-2 is necessary and sufficient for activity-dependent dendritic development. Furthermore, silencing CRMP-2 completely blocked the dendritic growth-promoting effects of GSK-3 knockdown, and expression of Thr514 nonphosphorylated form of CRMP-2 counteracted the inhibitory effect of constitutively active GSK-3. This data indicate that CRMP-2 functions downstream of GSK-3. Together, these findings identify a novel GSK-3/CRMP-2 pathway that connects neuronal activity to dendritic growth.

An immunomodulatory role of Fc receptor γ chain independent of FcγR ligation by IgG in acute neuroinflammation triggered by MPTP intoxication.

Aberrant microglial activation is a prominent feature of neuroinflammation, which is implicated in the pathogenesis of neurological disorders. Fc receptor common γ-chain (FcRγ), one of the two immunoreceptor tyrosine-based activation motif-bearing adaptor proteins, is abundantly expressed in microglia. It couples with different receptors, such as receptors for the Fc portion of IgG. In this study, we observed increased FcRγ expression along with increased IgG-binding during acute neuroinflammation triggered by MPTP intoxication, where adaptive immune responses should not be involved. Notably, FcRγ was expressed not only in the cell membrane but also in the cytoplasm in the activated microglia. FcRγ deficiency exacerbated microglial activation, pro-inflammatory factor upregulation, nigral dopaminergic neuronal loss and motor deficits, implicating a beneficial role of FcRγ in this model. Blockade of Fcγ receptor ligation by IgG in mice by Endoglycosidase S treatment, a bacterial endo-ß-N-acetylglucosaminidase cleaving specifically the Asn297-linked glycan of IgG, or by using the mice deficient in mature B cells (muMT) with IgG production defects, did not show similar phenotypes to those observed in FcRγ-deficient mice, indicating that the beneficial effect mediated by FcRγ did not depend on FcγR ligation by IgG. Further, FcRγ knockout aggravated the expression and activation of STAT1 in microglia, suggesting FcRγ modulated neuroinflammation by dampening STAT1 signaling. Collectively, these results revealed that FcRγ-associated receptors could function as negative regulators of neuroinflammation and dopaminergic neurodegeneration.

SequenceMorph: A Unified Unsupervised Learning Framework for Motion Tracking on Cardiac Image Sequences.

Modern medical imaging techniques, such as ultrasound (US) and cardiac magnetic resonance (MR) imaging, have enabled the evaluation of myocardial deformation directly from an image sequence. While many traditional cardiac motion tracking methods have been developed for the automated estimation of the myocardial wall deformation, they are not widely used in clinical diagnosis, due to their lack of accuracy and efficiency. In this paper, we propose a novel deep learning-based fully unsupervised method, SequenceMorph, for in vivo motion tracking in cardiac image sequences. In our method, we introduce the concept of motion decomposition and recomposition. We first estimate the inter-frame (INF) motion field between any two consecutive frames, by a bi-directional generative diffeomorphic registration neural network. Using this result, we then estimate the Lagrangian motion field between the reference frame and any other frame, through a differentiable composition layer. Our framework can be extended to incorporate another registration network, to further reduce the accumulated errors introduced in the INF motion tracking step, and to refine the Lagrangian motion estimation. By utilizing temporal information to perform reasonable estimations of spatio-temporal motion fields, this novel method provides a useful solution for image sequence motion tracking. Our method has been applied to US (echocardiographic) and cardiac MR (untagged and tagged cine) image sequences; the results show that SequenceMorph is significantly superior to conventional motion tracking methods, in terms of the cardiac motion tracking accuracy and inference efficiency.

Repressing PTBP1 fails to convert reactive astrocytes to dopaminergic neurons in a 6-hydroxydopamine mouse model of Parkinson's disease.

Lineage reprogramming of resident glial cells to dopaminergic neurons (DAns) is an attractive prospect of the cell-replacement therapy for Parkinson's disease (PD). However, it is unclear whether repressing polypyrimidine tract binding protein 1 (PTBP1) could efficiently convert astrocyte to DAns in the substantia nigra and striatum. Although reporter-positive DAns were observed in both groups after delivering the adeno-associated virus (AAV) expressing a reporter with shRNA or CRISPR-CasRx to repress astroglial PTBP1, the possibility of AAV leaking into endogenous DAns could not be excluded without using a reliable lineage-tracing method. By adopting stringent lineage-tracing strategy, two other studies show that either knockdown or genetic deletion of quiescent astroglial PTBP1 fails to obtain induced DAns under physiological condition. However, the role of reactive astrocytes might be underestimated because upon brain injury, reactive astrocyte can acquire certain stem cell hallmarks that may facilitate the lineage conversion process. Therefore, whether reactive astrocytes could be genuinely converted to DAns after PTBP1 repression in a PD model needs further validation. In this study, we used Aldh1l1-CreERT2-mediated specific astrocyte-lineage-tracing method to investigate whether reactive astrocytes could be converted to DAns in a 6-hydroxydopamine (6-OHDA) mouse model of PD. However, we found that no astrocyte-originated DAn was generated after effective and persistent knockdown of astroglial PTBP1 either in the substantia nigra or in striatum, while AAV 'leakage' to nearby neurons was easily observed. Our results confirm that repressing PTBP1 does not convert astrocytes to DAns, regardless of physiological or PD-related pathological conditions.

Mitolysosome exocytosis, a mitophagy-independent mitochondrial quality control in flunarizine-induced parkinsonism-like symptoms.

Mitochondrial quality control plays an important role in maintaining mitochondrial homeostasis and function. Disruption of mitochondrial quality control degrades brain function. We found that flunarizine (FNZ), a drug whose chronic use causes parkinsonism, led to a parkinsonism-like motor dysfunction in mice. FNZ induced mitochondrial dysfunction and decreased mitochondrial mass specifically in the brain. FNZ decreased mitochondrial content in both neurons and astrocytes, without affecting the number of nigral dopaminergic neurons. In human neural progenitor cells, FNZ also induced mitochondrial depletion. Mechanistically, independent of ATG5- or RAB9-mediated mitophagy, mitochondria were engulfed by lysosomes, followed by a vesicle-associated membrane protein 2- and syntaxin-4-dependent extracellular secretion. A genome-wide CRISPR knockout screen identified genes required for FNZ-induced mitochondrial elimination. These results reveal not only a previously unidentified lysosome-associated exocytosis process of mitochondrial quality control that may participate in the FNZ-induced parkinsonism but also a drug-based method for generating mitochondria-depleted mammal cells.

Nurr1 downregulation is caused by CREB inactivation in a Parkinson's disease mouse model.

Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by the loss of dopaminergic neurons in the substantia nigra (SN). Nurr1 (NR4A2), a nuclear receptor essential for the maintenance of midbrain dopaminergic neurons, is transcriptionally downregulated in both patients with PD and animal models and has been considered as a promising therapeutic target for neuroprotection in PD. However, the mechanism underlying Nurr1 downregulation during dopaminergic degeneration has not been fully elucidated. Here, we report that the pro-survival transcription factor CREB is constitutively bound to the Nurr1 promoter in the mouse SN. CREB inactivation by dephosphorylation at Ser133 occurred in parallel with Nurr1 downregulation in the MPTP mouse model of PD. Forced expression of VP16-CREB, a constitutively active mutant, rescued Nurr1 expression and showed prominent neuroprotection in MPTP-intoxicated mice. Collectively, our results demonstrate that Nurr1 downregulation in the MPTP-induced PD mouse model is caused by CREB inactivation, which may provide a new target for neuroprotective therapy in PD.

GSK-3 mediates nuclear translocation of p62/SQSTM1 in MPTP-induced mouse model of Parkinson's disease.

p62/SQSTM1 is a multifunctional, cytoplasmic protein with fundamental roles in autophagy and antioxidant responses. Here we showed that p62 translocated from the cytoplasm to the nucleus in nigral dopaminergic neurons in a 1-methyl-4-phenyl-1,2,3,6-tetrahydropyrid (MPTP)-induced mouse model of Parkinson's disease (PD). We found that p62 was physically associated with glycogen synthase kinase (GSK)-3ß, a serine/threonine protein kinase implicated in dopaminergic neurodegeneration in PD, and that MPTP treatment promoted dissociation of the complex in mice. Conditional knockout of GSK-3 prevented nuclear translocation of p62, suggesting that this translocation was detrimental to dopaminergic neurons. p62 knockout mice were used to investigate the role of p62 in MPTP-induced neuronal death. Knockout of p62 aggravated neuronal injury induced by MPTP intoxication, suggesting that p62 plays an important role in dopaminergic cell survival in stress conditions. Together, our data demonstrate that GSK-3 mediates nuclear translocation of p62 during MPTP-induced parkinsonian neurodegeneration. These findings shed new light on the role of the cytoplasmic-nuclear shuttling of p62 and the mechanism underlying GSK-3-depedent neuronal death in PD pathogenesis.

Dynamic MRI reconstruction with end-to-end motion-guided network.

Temporal correlation in dynamic magnetic resonance imaging (MRI), such as cardiac MRI, is informative and important to understand motion mechanisms of body regions. Modeling such information into the MRI reconstruction process produces temporally coherent image sequence and reduces imaging artifacts and blurring. However, existing deep learning based approaches neglect motion information during the reconstruction procedure, while traditional motion-guided methods are hindered by heuristic parameter tuning and long inference time. We propose a novel dynamic MRI reconstruction approach called MODRN and an end-to-end improved version called MODRN(e2e), both of which enhance the reconstruction quality by infusing motion information into the modeling process with deep neural networks. The central idea is to decompose the motion-guided optimization problem of dynamic MRI reconstruction into three components: Dynamic Reconstruction Network, Motion Estimation and Motion Compensation. Extensive experiments have demonstrated the effectiveness of our proposed approach compared to other state-of-the-art approaches.

TFE3-Mediated Autophagy is Involved in Dopaminergic Neurodegeneration in Parkinson's Disease.

Impairment of autophagy has been strongly implicated in the progressive loss of nigral dopaminergic neurons in Parkinson's disease (PD). Transcription factor E3 (TFE3), an MiTF/TFE family transcription factor, has been identified as a master regulator of the genes that are associated with lysosomal biogenesis and autophagy. However, whether TFE3 is involved in parkinsonian neurodegeneration remains to be determined. In this study, we found decreased TFE3 expression in the nuclei of the dopaminergic neurons of postmortem human PD brains. Next, we demonstrated that TFE3 knockdown led to autophagy dysfunction and neurodegeneration of dopaminergic neurons in mice, implying that reduction of nuclear TFE3 may contribute to autophagy dysfunction-mediated cell death in PD. Further, we showed that enhancement of autophagy by TFE3 overexpression dramatically reversed autophagy downregulation and dopaminergic neurons loss in the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) model of PD. Taken together, these findings demonstrate that TFE3 plays an essential role in maintaining autophagy and the survival of dopaminergic neurons, suggesting TFE3 activation may serve as a promising strategy for PD therapy.

Object-Guided Instance Segmentation With Auxiliary Feature Refinement for Biological Images.

Instance segmentation is of great importance for many biological applications, such as study of neural cell interactions, plant phenotyping, and quantitatively measuring how cells react to drug treatment. In this paper, we propose a novel box-based instance segmentation method. Box-based instance segmentation methods capture objects via bounding boxes and then perform individual segmentation within each bounding box region. However, existing methods can hardly differentiate the target from its neighboring objects within the same bounding box region due to their similar textures and low-contrast boundaries. To deal with this problem, in this paper, we propose an object-guided instance segmentation method. Our method first detects the center points of the objects, from which the bounding box parameters are then predicted. To perform segmentation, an object-guided coarse-to-fine segmentation branch is built along with the detection branch. The segmentation branch reuses the object features as guidance to separate target object from the neighboring ones within the same bounding box region. To further improve the segmentation quality, we design an auxiliary feature refinement module that densely samples and refines point-wise features in the boundary regions. Experimental results on three biological image datasets demonstrate the advantages of our method. The code will be available at https://github.com/yijingru/ObjGuided-Instance-Segmentation.

GSK-3ß Contributes to Parkinsonian Dopaminergic Neuron Death: Evidence From Conditional Knockout Mice and Tideglusib.

Glycogen synthase kinase-3 (GSK-3) dysregulation has been implicated in nigral dopaminergic neurodegeneration, one of the main pathological features of Parkinson's disease (PD). The two isoforms, GSK-3α and GSK-3ß, have both been suggested to play a detrimental role in neuronal death. To date, several studies have focused on the role of GSK-3ß on PD pathogenesis, while the role of GSK-3α has been largely overlooked. Here, we report in situ observations that both GSK-3α and GSK-3ß are dephosphorylated at a negatively acting regulatory serine, indicating kinase activation, selectively in nigral dopaminergic neurons following exposure of mice to 1-methyl-4-pheny-1,2,3,6-tetrahydropyridine (MPTP). To identify whether GSK-3α and GSK-3ß display functional redundancy in regulating parkinsonian dopaminergic cell death, we analysed dopaminergic neuron-specific Gsk3a null (Gsk3a ΔDat ) and Gsk3b null (Gsk3b ΔDat ) mice, respectively. We found that Gsk3b ΔDat , but not Gsk3a ΔDat , showed significant resistance to MPTP insult, revealing non-redundancy of GSK-3α and GSK-3ß in PD pathogenesis. In addition, we tested the neuroprotective effect of tideglusib, the most clinically advanced inhibitor of GSK-3, in the MPTP model of PD. Administration of higher doses (200 mg/kg and 500 mg/kg) of tideglusib exhibited significant neuroprotection, whereas 50 mg/kg tideglusib failed to prevent dopaminergic neurodegeneration from MPTP toxicity. Administration of 200 mg/kg tideglusib improved motor symptoms of MPTP-treated mice. Together, these data demonstrate GSK-3ß and not GSK-3α is critical for parkinsonian neurodegeneration. Our data support the view that GSK-3ß acts as a potential therapeutic target in PD and tideglusib would be a candidate drug for PD neuroprotective therapy.

Weakly Supervised Deep Nuclei Segmentation Using Partial Points Annotation in Histopathology Images.

Nuclei segmentation is a fundamental task in histopathology image analysis. Typically, such segmentation tasks require significant effort to manually generate accurate pixel-wise annotations for fully supervised training. To alleviate such tedious and manual effort, in this paper we propose a novel weakly supervised segmentation framework based on partial points annotation, i.e., only a small portion of nuclei locations in each image are labeled. The framework consists of two learning stages. In the first stage, we design a semi-supervised strategy to learn a detection model from partially labeled nuclei locations. Specifically, an extended Gaussian mask is designed to train an initial model with partially labeled data. Then, self-training with background propagation is proposed to make use of the unlabeled regions to boost nuclei detection and suppress false positives. In the second stage, a segmentation model is trained from the detected nuclei locations in a weakly-supervised fashion. Two types of coarse labels with complementary information are derived from the detected points and are then utilized to train a deep neural network. The fully-connected conditional random field loss is utilized in training to further refine the model without introducing extra computational complexity during inference. The proposed method is extensively evaluated on two nuclei segmentation datasets. The experimental results demonstrate that our method can achieve competitive performance compared to the fully supervised counterpart and the state-of-the-art methods while requiring significantly less annotation effort.

Progress in Dopaminergic Cell Replacement and Regenerative Strategies for Parkinson's Disease.

Parkinson's disease (PD) is a chronic progressive neurodegenerative disorder symptomatically characterized by resting tremor, rigidity, bradykinesia, and gait impairment. These motor deficits suffered by PD patients primarily result from selective dysfunction or loss of dopaminergic neurons of the substantia nigra pars compacta (SNpc). Most of the existing therapies for PD are based on the replacement of dopamine, which is symptomatically effective in the early stage but becomes increasingly less effective and is accompanied by serious side effects in the advanced stages of the disease. Currently, there are no strategies to slow neuronal degeneration or prevent the progression of PD. Thus, the prospect of regenerating functional dopaminergic neurons is very attractive. Over the last few decades, significant progress has been made in the development of dopaminergic regenerative strategies for curing PD. The most promising approach seems to be cell-replacement therapy (CRT) using human embryonic stem cells (ESCs) or induced pluripotent stem cells (iPSCs), which are unlimitedly available and have gained much success in preclinical trials. Despite the challenges, stem cell-based CRT will make significant steps toward the clinic in the coming decade. Alternatively, direct lineage reprogramming, especially in situ direct conversion of glia cells to induced neurons, which exhibits some advantages including no ethical concerns, no risk of tumor formation, and even no need for transplantation, has gained much attention recently. Evoking the endogenous regeneration ability of neural stem cells (NSCs) is an idyllic method of dopaminergic neuroregeneration which remains highly controversial. Here, we review many of these advances, highlighting areas and strategies that might be particularly suited to the development of regenerative approaches that restore dopaminergic function in PD.

Attentive neural cell instance segmentation.

Neural cell instance segmentation, which aims at joint detection and segmentation of every neural cell in a microscopic image, is essential to many neuroscience applications. The challenge of this task involves cell adhesion, cell distortion, unclear cell contours, low-contrast cell protrusion structures, and background impurities. Consequently, current instance segmentation methods generally fall short of precision. In this paper, we propose an attentive instance segmentation method that accurately predicts the bounding box of each cell as well as its segmentation mask simultaneously. In particular, our method builds on a joint network that combines a single shot multi-box detector (SSD) and a U-net. Furthermore, we employ the attention mechanism in both detection and segmentation modules to focus the model on the useful features. The proposed method is validated on a dataset of neural cell microscopic images. Experimental results demonstrate that our approach can accurately detect and segment neural cell instances at a fast speed, comparing favorably with the state-of-the-art methods. Our code is released on GitHub. The link is https://github.com/yijingru/ANCIS-Pytorch.