To the Editor:Anti-N-methyl-D-aspartate receptor(NMDAR)encephalitis is a potentially lethal autoimmune disease characterized by prominent psychiatric symptoms and seizures.It usually occurs in young female patients wi...To the Editor:Anti-N-methyl-D-aspartate receptor(NMDAR)encephalitis is a potentially lethal autoimmune disease characterized by prominent psychiatric symptoms and seizures.It usually occurs in young female patients with ovarian teratomas.[1] Here,we describe a severe case of anti-NMDAR encephalitis.The patient was originally misdiagnosed as psychosis and did not improve within the first 4 weeks of first-line immunotherapy.Although she did not continue to receive second-line immunotherapy,the patient still recovered well and had no recurrence or tumor observed during 3 years of follow-up.展开更多
To the Editor:Bilateral medial medullary infarction(MMI)is a rare stroke subtype.[1]usually leads to quadriplegia,sensory disturbance,hypoglossal palsy,bulbar paralysis,etc.[2]We encountered a patient with rapidly pro...To the Editor:Bilateral medial medullary infarction(MMI)is a rare stroke subtype.[1]usually leads to quadriplegia,sensory disturbance,hypoglossal palsy,bulbar paralysis,etc.[2]We encountered a patient with rapidly progressive tetraparesis and diffusion-weighted imaging(DWI)exhibited a“heart appearance”sign in the bilateral ventral medulla.Computed tomography angiography(CTA)demonstrated that the left vertebral artery(VA)was hypoplastic and there was an atherosclerotic stenosis in the V4 segment.展开更多
This study introduces a novel conditional recycle generative adversarial network for facial attribute transfor- mation, which can transform high-level semantic face attributes without changing the identity. In our app...This study introduces a novel conditional recycle generative adversarial network for facial attribute transfor- mation, which can transform high-level semantic face attributes without changing the identity. In our approach, we input a source facial image to the conditional generator with target attribute condition to generate a face with the target attribute. Then we recycle the generated face back to the same conditional generator with source attribute condition. A face which should be similar to that of the source face in personal identity and facial attributes is generated. Hence, we introduce a recycle reconstruction loss to enforce the final generated facial image and the source facial image to be identical. Evaluations on the CelebA dataset demonstrate the effectiveness of our approach. Qualitative results show that our approach can learn and generate high-quality identity-preserving facial images with specified attributes.展开更多
文摘To the Editor:Anti-N-methyl-D-aspartate receptor(NMDAR)encephalitis is a potentially lethal autoimmune disease characterized by prominent psychiatric symptoms and seizures.It usually occurs in young female patients with ovarian teratomas.[1] Here,we describe a severe case of anti-NMDAR encephalitis.The patient was originally misdiagnosed as psychosis and did not improve within the first 4 weeks of first-line immunotherapy.Although she did not continue to receive second-line immunotherapy,the patient still recovered well and had no recurrence or tumor observed during 3 years of follow-up.
文摘To the Editor:Bilateral medial medullary infarction(MMI)is a rare stroke subtype.[1]usually leads to quadriplegia,sensory disturbance,hypoglossal palsy,bulbar paralysis,etc.[2]We encountered a patient with rapidly progressive tetraparesis and diffusion-weighted imaging(DWI)exhibited a“heart appearance”sign in the bilateral ventral medulla.Computed tomography angiography(CTA)demonstrated that the left vertebral artery(VA)was hypoplastic and there was an atherosclerotic stenosis in the V4 segment.
基金This work was supported by the National Natural Science Foundation of China under Grant Nos. 61672520, 61573348, 61620106003, and 61720106006, the Beijing Natural Science Foundation of China under Grant No. 4162056, the National Key Technology Research and Development Program of China under Grant No. 2015BAH53F02, and the CASIA-Tencent YouTu Jointly Research Project. The Titan X used for this research was donated by the NVIDIA Corporation.
文摘This study introduces a novel conditional recycle generative adversarial network for facial attribute transfor- mation, which can transform high-level semantic face attributes without changing the identity. In our approach, we input a source facial image to the conditional generator with target attribute condition to generate a face with the target attribute. Then we recycle the generated face back to the same conditional generator with source attribute condition. A face which should be similar to that of the source face in personal identity and facial attributes is generated. Hence, we introduce a recycle reconstruction loss to enforce the final generated facial image and the source facial image to be identical. Evaluations on the CelebA dataset demonstrate the effectiveness of our approach. Qualitative results show that our approach can learn and generate high-quality identity-preserving facial images with specified attributes.
