Near-Optimal Modulo-and-Forward Scheme for the Untrusted Relay Channel

This paper studies an untrusted relay channel, in which the destination sends artificial noise simultaneously with the source sending a message to the relay, in order to protect the source's confidential message. The traditional amplify-and-forward (AF) scheme shows poor performance in this situation because of the interference power dilemma: providing better security by using stronger artificial noise will decrease the confidential message power from the relay to the destination. To solve this problem, a modulo-and-forward (MF) operation at the relay with nested lattice encoding at the source is proposed. For this system with full channel state information at the transmitter (CSIT), theoretical analysis shows that the proposed MF scheme approaches the secrecy capacity within 1/2 bit for any channel realization, and hence achieves full generalized security degrees of freedom (G-SDoF). In contrast, the AF scheme can only achieve a small fraction of the G-SDoF. For this system without any CSIT, the total outage event, defined as either connection outage or secrecy outage, is introduced. Based on this total outage definition, analysis shows that the proposed MF scheme achieves the full generalized secure diversity gain (G-SDG) of order one. On the other hand, the AF scheme can only achieve a G-SDG of 1/2 at most

Structure of dual receptor binding to botulinum neurotoxin B

Botulinum neurotoxins are highly toxic, and bind two receptors to achieve their high affinity and specificity for neurons. Here we present the first structure of a botulinum neurotoxin bound to both its receptors. We determine the 2.3 Å structure of a ternary complex of botulinum neurotoxin type B bound to both its protein receptor Synaptotagmin II and its ganglioside receptor GD1a. We show that there is no direct contact between the two receptors, and that the binding affinity towards Synaptotagmin II is not influenced by the presence of GD1a. The interactions of botulinum neurotoxin type B with the sialic acid 5 moiety of GD1a are important for the ganglioside selectivity. The structure demonstrates that the protein receptor and the ganglioside receptor occupy nearby but separate binding sites, thus providing two independent anchoring points

Cytotoxicity of Botulinum Neurotoxins Reveals a Direct Role of Syntaxin 1 and SNAP-25 in Neuron Survival

Botulinum neurotoxins (BoNT/A-G) are well-known to act by blocking synaptic vesicle exocytosis. Whether BoNTs disrupt additional neuronal functions has not been addressed. Here we report that cleavage of syntaxin 1 (Syx 1) by BoNT/C and cleavage of SNAP-25 by BoNT/E both induce degeneration of cultured rodent and human neurons. Furthermore, although SNAP-25 cleaved by BoNT/A can still support neuron survival, it has reduced capacity to tolerate additional mutations and also fails to pair with syntaxin isoforms other than Syx 1. Syx 1 and SNAP-25 are well-known for mediating synaptic vesicle exocytosis, but we found that neuronal death is due to blockage of plasma membrane recycling processes that share Syx 1/SNAP-25 for exocytosis, independent of blockage of synaptic vesicle exocytosis. These findings reveal neuronal cytotoxicity for a subset of BoNTs and directly link Syx 1/SNAP-25 to neuron survival as the prevalent SNARE proteins mediating multiple fusion events on neuronal plasma membranes

Widespread Sequence Variations in VAMP1 across Vertebrates Suggest a Potential Selective Pressure from Botulinum Neurotoxins

Botulinum neurotoxins (BoNT/A-G), the most potent toxins known, act by cleaving three SNARE proteins required for synaptic vesicle exocytosis. Previous studies on BoNTs have generally utilized the major SNARE homologues expressed in brain (VAMP2, syntaxin 1, and SNAP-25). However, BoNTs target peripheral motor neurons and cause death by paralyzing respiratory muscles such as the diaphragm. Here we report that VAMP1, but not VAMP2, is the SNARE homologue predominantly expressed in adult rodent diaphragm motor nerve terminals and in differentiated human motor neurons. In contrast to the highly conserved VAMP2, BoNT-resistant variations in VAMP1 are widespread across vertebrates. In particular, we identified a polymorphism at position 48 of VAMP1 in rats, which renders VAMP1 either resistant (I48) or sensitive (M48) to BoNT/D. Taking advantage of this finding, we showed that rat diaphragms with I48 in VAMP1 are insensitive to BoNT/D compared to rat diaphragms with M48 in VAMP1. This unique intra-species comparison establishes VAMP1 as a physiological toxin target in diaphragm motor nerve terminals, and demonstrates that the resistance of VAMP1 to BoNTs can underlie the insensitivity of a species to members of BoNTs. Consistently, human VAMP1 contains I48, which may explain why humans are insensitive to BoNT/D. Finally, we report that residue 48 of VAMP1 varies frequently between M and I across seventeen closely related primate species, suggesting a potential selective pressure from members of BoNTs for resistance in vertebrates

The role of tripartite motif-containing 28 in cancer progression and its therapeutic potentials

Tripartite motif-containing 28 (TRIM28) belongs to tripartite motif (TRIM) family. TRIM28 not only binds and degrades its downstream target, but also acts as a transcription co-factor to inhibit gene expression. More and more studies have shown that TRIM28 plays a vital role in tumor genesis and progression. Here, we reviewed the role of TRIM28 in tumor proliferation, migration, invasion and cell death. Moreover, we also summarized the important role of TRIM28 in tumor stemness sustainability and immune regulation. Because of the importance of TRIM28 in tumors, TIRM28 may be a candidate target for anti-tumor therapy and play an important role in tumor diagnosis and treatment in the future

Lysosomal enzyme cathepsin D protects against alpha-synuclein aggregation and toxicity

α-synuclein (α-syn) is a main component of Lewy bodies (LB) that occur in many neurodegenerative diseases, including Parkinson's disease (PD), dementia with LB (DLB) and multi-system atrophy. α-syn mutations or amplifications are responsible for a subset of autosomal dominant familial PD cases, and overexpression causes neurodegeneration and motor disturbances in animals. To investigate mechanisms for α-syn accumulation and toxicity, we studied a mouse model of lysosomal enzyme cathepsin D (CD) deficiency, and found extensive accumulation of endogenous α-syn in neurons without overabundance of α-syn mRNA. In addition to impaired macroautophagy, CD deficiency reduced proteasome activity, suggesting an essential role for lysosomal CD function in regulating multiple proteolytic pathways that are important for α-syn metabolism. Conversely, CD overexpression reduces α-syn aggregation and is neuroprotective against α-syn overexpression-induced cell death in vitro. In a C. elegans model, CD deficiency exacerbates α-syn accumulation while its overexpression is protective against α-syn-induced dopaminergic neurodegeneration. Mutated CD with diminished enzymatic activity or overexpression of cathepsins B (CB) or L (CL) is not protective in the worm model, indicating a unique requirement for enzymatically active CD. Our data identify a conserved CD function in α-syn degradation and identify CD as a novel target for LB disease therapeutics

Seizure and Myelin Oligodendrocyte Glycoprotein Antibody-Associated Encephalomyelitis in a Retrospective Cohort of Chinese Patients

Background: Myelin oligodendrocyte glycoprotein (MOG) antibody associated encephalomyelitis is increasingly being considered a distinct disease entity, with seizures and encephalopathy commonly reported. We investigated the clinical features of MOG-IgG positive patients presenting with seizures and/or encephalopathy in a single cohort.Methods: Consecutive patients with suspected idiopathic inflammatory demyelinating diseases were recruited from a tertiary University hospital in Guangdong province, China. Subjects with MOG-IgG seropositivity were analyzed according to whether they presented with or without seizure and/or encephalopathy.Results: Overall, 58 subjects seropositive for MOG-IgG were analyzed, including 23 (40%) subjects presenting with seizures and/or encephalopathy. Meningeal irritation (P = 0.030), fever (P = 0.001), headache (P = 0.001), nausea, and vomiting (P = 0.004) were more commonly found in subjects who had seizures and/or encephalopathy, either at presentation or during the disease course. Nonetheless, there was less optic nerve (4/23, 17.4%, P = 0.003) and spinal cord (6/16, 37.5%, P = 0.037) involvement as compared to subjects without seizures or encephalopathy. Most MOG encephalomyelitis subjects had cortical/subcortical lesions: 65.2% (15/23) in the seizures and/or encephalopathy group and 50.0% (13/26) in the without seizures or encephalopathy group. Cerebrospinal fluid (CSF) leukocytes were elevated in both groups. Subgroup analysis showed that 30% (7/23) MOG-IgG positive subjects with seizures and/or encephalopathy had been misdiagnosed for central nervous system infection on the basis of meningoencephalitis symptoms and elevated CSF leukocytes (P = 0.002).Conclusions: Seizures and encephalopathy are not rare in MOG encephalomyelitis, and are commonly associated with cortical and subcortical brain lesions. MOG-encephalomyelitis often presents with clinical meningoencephalitis symptoms and abnormal CSF findings mimicking central nervous system infection in pediatric and young adult patients

Fetal brain tissue annotation and segmentation challenge results

In-utero fetal MRI is emerging as an important tool in the diagnosis and analysis of the developing human brain. Automatic segmentation of the developing fetal brain is a vital step in the quantitative analysis of prenatal neurodevelopment both in the research and clinical context. However, manual segmentation of cerebral structures is time-consuming and prone to error and inter-observer variability. Therefore, we organized the Fetal Tissue Annotation (FeTA) Challenge in 2021 in order to encourage the development of automatic segmentation algorithms on an international level. The challenge utilized FeTA Dataset, an open dataset of fetal brain MRI reconstructions segmented into seven different tissues (external cerebrospinal fluid, gray matter, white matter, ventricles, cerebellum, brainstem, deep gray matter). 20 international teams participated in this challenge, submitting a total of 21 algorithms for evaluation. In this paper, we provide a detailed analysis of the results from both a technical and clinical perspective. All participants relied on deep learning methods, mainly U-Nets, with some variability present in the network architecture, optimization, and image pre- and post-processing. The majority of teams used existing medical imaging deep learning frameworks. The main differences between the submissions were the fine tuning done during training, and the specific pre- and post-processing steps performed. The challenge results showed that almost all submissions performed similarly. Four of the top five teams used ensemble learning methods. However, one team's algorithm performed significantly superior to the other submissions, and consisted of an asymmetrical U-Net network architecture. This paper provides a first of its kind benchmark for future automatic multi-tissue segmentation algorithms for the developing human brain in utero

Fetal Brain Tissue Annotation and Segmentation Challenge Results

In-utero fetal MRI is emerging as an important tool in the diagnosis and analysis of the developing human brain. Automatic segmentation of the developing fetal brain is a vital step in the quantitative analysis of prenatal neurodevelopment both in the research and clinical context. However, manual segmentation of cerebral structures is time-consuming and prone to error and inter-observer variability. Therefore, we organized the Fetal Tissue Annotation (FeTA) Challenge in 2021 in order to encourage the development of automatic segmentation algorithms on an international level. The challenge utilized FeTA Dataset, an open dataset of fetal brain MRI reconstructions segmented into seven different tissues (external cerebrospinal fluid, grey matter, white matter, ventricles, cerebellum, brainstem, deep grey matter). 20 international teams participated in this challenge, submitting a total of 21 algorithms for evaluation. In this paper, we provide a detailed analysis of the results from both a technical and clinical perspective. All participants relied on deep learning methods, mainly U-Nets, with some variability present in the network architecture, optimization, and image pre- and post-processing. The majority of teams used existing medical imaging deep learning frameworks. The main differences between the submissions were the fine tuning done during training, and the specific pre- and post-processing steps performed. The challenge results showed that almost all submissions performed similarly. Four of the top five teams used ensemble learning methods. However, one team's algorithm performed significantly superior to the other submissions, and consisted of an asymmetrical U-Net network architecture. This paper provides a first of its kind benchmark for future automatic multi-tissue segmentation algorithms for the developing human brain in utero.Comment: Results from FeTA Challenge 2021, held at MICCAI; Manuscript submitte