Introduction 18F‐fluorodeoxyglucose (FDG)‐PET metabolic patterns of brain differ among autoimmune encephalitis with different neuronal surface antigens. In this case report, we compared the topographical relationship of cerebral glucose metabolism and antigen distribution in the patients with anti‐NMDAR and anti‐AMPAR encephalitis. Literature review summarized the common features of brain metabolism of autoimmune encephalitis. Methods The cerebral glucose metabolism was evaluated by FDG‐PET/CT during acute‐to‐subacute stage of autoimmune encephalitis and after treatment. The stereo and quantitative analysis of cerebral metabolism used standardized z‐score and visualized on three‐dimensional stereotactic surface projection. To map NMDAR and AMPAR in human brain, we adopted genetic atlases from the Allen Institute and protein atlases from Zilles's receptor densities. Results The three‐dimensional stereotactic surface projection displayed frontal‐dominant hypometabolism in a 66‐year‐old female patient with anti‐AMPAR encephalitis and occipital‐dominant hypometabolism in a 29‐year‐old female patient with anti‐NMDAR encephalitis. Receptor density maps revealed opposite frontal–occipital gradients of AMPAR and NMDAR, which reflect reduced metabolism in the correspondent encephalitis. FDG‐PET hypometabolic areas possibly represent receptor hypofunction with spatial correspondence to receptor distributions of the autoimmune encephalitis. The reversibility of hypometabolism was in line with patients' cognitive improvement. The literature review summarized six features of metabolic anomalies of autoimmune encephalitis: (a) temporal hypermetabolism, (b) frontal hypermetabolism and (c) occipital hypometabolism in anti‐NMDAR encephalitis, (d) hypometabolism in association cortices, (e) sparing of unimodal primary motor cortex, and (e) reversibility in recovery. Conclusions The distinct cerebral hypometabolic patterns of autoimmune encephalitis were representative for receptor hypofunction and topographical distribution of antigenic receptors. The reversibility of hypometabolism marked the clinical recovery of autoimmune encephalitis and made FDG‐PET of brain a valuable diagnostic tool.

Macroautophagy is a dynamic process whereby portions of the cytosol are encapsulated in double-membrane vesicles and delivered to the lysosome for degradation. Phosphatidylinositol-3-phosphate (PtdIns3P) is concentrated on autophagic vesicles and recruits effector proteins that are crucial for this process. The production of PtdIns3P by the class III phosphatidylinositol 3-kinase Vps34, has been well established; however, protein phosphatases that antagonize this early step in autophagy remain to be identified. To identify such enzymes, we screened human phosphatase genes by RNA interference and found that loss of PTPσ, a dual-domain protein tyrosine phosphatase (PTP), increases levels of cellular PtdIns3P. The abundant PtdIns3P-positive vesicles conferred by loss of PTPσ strikingly phenocopied those observed in cells starved of amino acids. Accordingly, we discovered that loss of PTPσ hyperactivates both constitutive and induced autophagy. Finally, we found that PTPσ localizes to PtdIns3P-positive membranes in cells, and this vesicular localization is enhanced during autophagy. We therefore describe a novel role for PTPσ and provide insight into the regulation of autophagy. Mechanistic knowledge of this process is crucial for understanding and targeting therapies for several human diseases, including cancer and Alzheimer's disease, in which abnormal autophagy might be pathological.

Objective: To test whether strokes increase around the time of cancer diagnosis, we comprehensively examined the correlations of cancer and stroke by employing a population-based cohort study design. Methods: One million people insured under the Taiwan's National Health Insurance program in 2005 were randomly sampled to create the study's dataset. According to the presence of cancer and/or stroke, patients were separated into cancer and stroke, cancer-only, and stroke-only groups. Diagnoses of cancer, stroke, and comorbidities were defined according to ICD9-CM codes. Cancer and non-cancer populations were matched by age at cancer diagnosis, gender, and stroke risk factors, and each patient with cancer was matched with two non-cancer controls nested in the same year of cancer diagnosis. The hazards of stroke and cumulative incidences within a year after cancer diagnosis were evaluated using Fine and Gray's subdistributional hazard model. Results: The temporal distribution of first-ever stroke in patients with both cancer and stroke was a sharpened bell shape that peaked between 0.5 years before and after cancer diagnosis. Frequencies of stroke were further adjusted by number of cancer survivors. The monthly event rate of stroke remained nested around the time of cancer diagnosis in all strokes. Brain malignancies, lung cancer, gastric cancer, prostate cancer, and leukemia patients obtained higher ratio of stroke, while breast cancer and thyroid cancer patients had low percentage of combining stroke. When compared to non-cancer matched control, the hazard of stroke within one year after cancer diagnosis was increased by cancer at a subdistributional hazard ratio of 1.72 (95% confident interval 1.48 to 2.01; p < 0.0001). Conclusions: Cancer increased the risk of stroke and stroke events were nested around the time of cancer diagnosis, occurring 0.5 years prior to cancer on average regardless of stroke type.