Our staff editors continue to share brilliant, thoughtful, and meaningful topics and articles in the recommended series.
This week, we would like to share several the latest articles from our editorial board. You are welcome to read, share, and leave your comments.
Title: The neuroprotective effects of oxygen therapy in Alzheimer's disease: a narrative review
Authors: Cui Yang, Qiu Yang, Yang Xiang, Xian-Rong Zeng, Jun Xiao, Wei-Dong Le
Alzheimer’s disease (AD) is a degenerative neurological disease that primarily affects the elderly. Drug therapy is the main strategy for AD treatment, but current treatments suffer from poor efficacy and a number of side effects. Non-drug therapy is attracting more attention and may be a better strategy for treatment of AD. Hypoxia is one of the important factors that contribute to the pathogenesis of AD. Multiple cellular processes synergistically promote hypoxia, including aging, hypertension, diabetes, hypoxia/obstructive sleep apnea, obesity, and traumatic brain injury. Increasing evidence has shown that hypoxia may affect multiple pathological aspects of AD, such as amyloid-beta metabolism, tau phosphorylation, autophagy, neuroinflammation, oxidative stress, endoplasmic reticulum stress, and mitochondrial and synaptic dysfunction. Treatments targeting hypoxia may delay or mitigate the progression of AD. Numerous studies have shown that oxygen therapy could improve the risk factors and clinical symptoms of AD. Increasing evidence also suggests that oxygen therapy may improve many pathological aspects of AD including amyloid-beta metabolism, tau phosphorylation, neuroinflammation, neuronal apoptosis, oxidative stress, neurotrophic factors, mitochondrial function, cerebral blood volume, and protein synthesis. In this review, we summarized the effects of oxygen therapy on AD pathogenesis and the mechanisms underlying these alterations. We expect that this review can benefit future clinical applications and therapy strategies on oxygen therapy for AD.
Access this article: https://doi.org/10.4103/1673-5374.343897
Title: A multiple-tissue-specific magnetic resonance imaging model for diagnosing Parkinson's disease: a brain radiomics study
Authors: Xiao-Jun Guan, Tao Guo, Cheng Zhou, Ting Gao, Jing-Jing Wu, Victor Han, Steven Cao, Hong-Jiang Wei, Yu-Yao Zhang, Min Xuan, Quan-Quan Gu, Pei-Yu Huang, Chun-Lei Liu, Jia-Li Pu, Bao-Rong Zhang, Feng Cui, Xiao-Jun Xu, Min-Ming Zhang
Type: Research Article
Brain radiomics can reflect the characteristics of brain pathophysiology. However, the value of T1-weighted images, quantitative susceptibility mapping, and R2* mapping in the diagnosis of Parkinson’s disease (PD) was underestimated in previous studies. In this prospective study to establish a model for PD diagnosis based on brain imaging information, we collected high-resolution T1-weighted images, R2* mapping, and quantitative susceptibility imaging data from 171 patients with PD and 179 healthy controls recruited from August 2014 to August 2019. According to the inclusion time, 123 PD patients and 121 healthy controls were assigned to train the diagnostic model, while the remaining 106 subjects were assigned to the external validation dataset. We extracted 1408 radiomics features, and then used data-driven feature selection to identify informative features that were significant for discriminating patients with PD from normal controls on the training dataset. The informative features so identified were then used to construct a diagnostic model for PD. The constructed model contained 36 informative radiomics features, mainly representing abnormal subcortical iron distribution (especially in the substantia nigra), structural disorganization (e.g., in the inferior temporal, paracentral, precuneus, insula, and precentral gyri), and texture misalignment in the subcortical nuclei (e.g., caudate, globus pallidus, and thalamus). The predictive accuracy of the established model was 81.1 ± 8.0% in the training dataset. On the external validation dataset, the established model showed predictive accuracy of 78.5 ± 2.1%. In the tests of identifying early and drug-naïve PD patients from healthy controls, the accuracies of the model constructed on the same 36 informative features were 80.3 ± 7.1% and 79.1 ± 6.5%, respectively, while the accuracies were 80.4 ± 6.3% and 82.9 ± 5.8% for diagnosing middle-to-late PD and those receiving drug management, respectively. The accuracies for predicting tremor-dominant and non-tremor-dominant PD were 79.8 ± 6.9% and 79.1 ± 6.5%, respectively. In conclusion, the multiple-tissue-specific brain radiomics model constructed from magnetic resonance imaging has the ability to discriminate PD and exhibits the advantages for improving PD diagnosis.
Access this article: https://doi.org/10.4103/1673-5374.339493
Title: Reward ameliorates depressive-like behaviors via inhibition of the substantia innominata to the lateral habenula projection
Authors: Yuting Cui, Xiaodan Huang, Pengcheng Huang, Lu Huang, Zhao Feng, Xinkuan Xiang, Xinfeng Chen, Anan Li, Chaoran Ren, Haohong Li
Type: Research Article
The lateral habenula (LHb) is implicated in emotional processing, especially depression. Recent studies indicate that the basal forebrain (BF) transmits reward or aversive signals to the LHb. However, the contribution of the BF-LHb circuit to the pathophysiology of depression still needs to be determined. Here, we find that the excitatory projection to the LHb from the substantia innominata (SI), a BF subregion, is activated by aversive stimuli and inhibited by reward stimuli. Furthermore, chronic activation of the SI-LHb circuit is sufficient to induce depressivelike behaviors, whereas inhibition of the circuit alleviates chronic stress–induced depressive-like phenotype. We also find that reward consumption buffers depressive-like behaviors induced by chronic activation of the SI-LHb circuit. In summary, we systematically define the function and mechanism of the SI-LHb circuit in modulating depressive-like behaviors, thus providing important insights to better decipher LHb processing in the pathophysiology of depression.
Access this article: https://doi.org/10.1126/sciadv.abn0193
Title: APOE interacts with ACE2 inhibiting SARS-CoV-2 cellular entry and inflammation in COVID-19 patients
Authors: Hongsheng Zhang, Lin Shao, Zhihao Lin, Quan-Xin Long, Huilong Yuan, Lujian Cai, Guangtong Jiang, Xiaoyi Guo, Renzhi Yang, Zepeng Zhang, Bingchang Zhang, Fan Liu, Zhiyong Li, Qilin Ma, Yun-Wu Zhang, Ai-Long Huang, Zhanxiang Wang, Yingjun Zhao, Huaxi Xu
Type: Research Article
Apolipoprotein E (APOE) plays a pivotal role in lipid including cholesterol metabolism. The APOE ε4 (APOE4) allele is a major genetic risk factor for Alzheimer’s and cardiovascular diseases. Although APOE has recently been associated with increased susceptibility to infections of several viruses, whether and how APOE and its isoforms affect SARS-CoV-2 infection remains unclear. Here, we show that serum concentrations of APOE correlate inversely with levels of cytokine/chemokine in 73 COVID-19 patients. Utilizing multiple protein interaction assays, we demonstrate that APOE3 and APOE4 interact with the SARS-CoV-2 receptor ACE2; and APOE/ACE2 interactions require zinc metallopeptidase domain of ACE2, a key docking site for SARS-CoV-2 Spike protein. In addition, immuno-imaging assays using confocal, super-resolution, and transmission electron microscopies reveal that both APOE3 and APOE4 reduce ACE2/Spikemediated viral entry into cells. Interestingly, while having a comparable binding affinity to ACE2, APOE4 inhibits viral entry to a lesser extent compared to APOE3, which is likely due to APOE4’s more compact structure and smaller spatial obstacle to compete against Spike binding to ACE2. Furthermore, APOE ε4 carriers clinically correlate with increased SARS-CoV-2 infection and elevated serum inflammatory factors in 142 COVID-19 patients assessed. Our study suggests a regulatory mechanism underlying SARS-CoV-2 infection through APOE interactions with ACE2, which may explain in part increased COVID-19 infection and disease severity in APOE ε4 carriers.
Access this article: https://www.nature.com/articles/s41392-022-01118-4