Multiscale structural mapping of Alzheimer's disease neurodegeneration

The recently described biological framework of Alzheimer's disease (AD) emphasizes three types of pathology to characterize this disorder, referred to as the 'amyloid/tau/neurodegeneration' (A-T-N) status. The 'neurodegenerative' component is typically defined by atrophy measures derived from structural magnetic resonance imaging (MRI) such as hippocampal volume. Neurodegeneration measures from imaging are associated with disease symptoms and prognosis. Thus, sensitive image-based quantification of neurodegeneration in AD has an important role in a range of clinical and research operations. Although hippocampal volume is a sensitive metric of neurodegeneration, this measure is impacted by several clinical conditions other than AD and therefore lacks specificity. In contrast, selective regional cortical atrophy, known as the 'cortical signature of AD' provides greater specificity to AD pathology. Although atrophy is apparent even in the preclinical stages of the disease, it is possible that increased sensitivity to degeneration could be achieved by including tissue microstructural properties in the neurodegeneration measure. However, to facilitate clinical feasibility, such information should be obtainable from a single, short, noninvasive imaging protocol. We propose a multiscale MRI procedure that advances prior work through the quantification of features at both macrostructural (morphometry) and microstructural (tissue properties obtained from multiple layers of cortex and subcortical white matter) scales from a single structural brain image (referred to as 'multi-scale structural mapping'; MSSM). Vertex-wise partial least squares (PLS) regression was used to compress these multi-scale structural features. When contrasting patients with AD to cognitively intact matched older adults, the MSSM procedure showed substantially broader regional group differences including areas that were not statistically significant when using cortical thickness alone. Further, with multiple machine learning algorithms and ensemble procedures, we found that MSSM provides accurate detection of individuals with AD dementia (AUROC = 0.962, AUPRC = 0.976) and individuals with mild cognitive impairment (MCI) that subsequently progressed to AD dementia (AUROC = 0.908, AUPRC = 0.910). The findings demonstrate the critical advancement of neurodegeneration quantification provided through multiscale mapping. Future work will determine the sensitivity of this technique for accurately detecting individuals with earlier impairment and biomarker positivity in the absence of impairment

Multiscale structural mapping of Alzheimer's disease neurodegeneration

The recently described biological framework of Alzheimer’s disease (AD) emphasizes three types of pathology to characterize this disorder, referred to as the ‘amyloid/tau/neurodegeneration’ (A-T-N) status. The ‘neurodegenerative’ component is typically defined by atrophy measures derived from structural magnetic resonance imaging (MRI) such as hippocampal volume. Neurodegeneration measures from imaging are associated with disease symptoms and prognosis. Thus, sensitive image-based quantification of neurodegeneration in AD has an important role in a range of clinical and research operations. Although hippocampal volume is a sensitive metric of neurodegeneration, this measure is impacted by several clinical conditions other than AD and therefore lacks specificity. In contrast, selective regional cortical atrophy, known as the ‘cortical signature of AD’ provides greater specificity to AD pathology. Although atrophy is apparent even in the preclinical stages of the disease, it is possible that increased sensitivity to degeneration could be achieved by including tissue microstructural properties in the neurodegeneration measure. However, to facilitate clinical feasibility, such information should be obtainable from a single, short, noninvasive imaging protocol. We propose a multiscale MRI procedure that advances prior work through the quantification of features at both macrostructural (morphometry) and microstructural (tissue properties obtained from multiple layers of cortex and subcortical white matter) scales from a single structural brain image (referred to as ‘multi-scale structural mapping’; MSSM). Vertex-wise partial least squares (PLS) regression was used to compress these multi-scale structural features. When contrasting patients with AD to cognitively intact matched older adults, the MSSM procedure showed substantially broader regional group differences including areas that were not statistically significant when using cortical thickness alone. Further, with multiple machine learning algorithms and ensemble procedures, we found that MSSM provides accurate detection of individuals with AD dementia (AUROC = 0.962, AUPRC = 0.976) and individuals with mild cognitive impairment (MCI) that subsequently progressed to AD dementia (AUROC = 0.908, AUPRC = 0.910). The findings demonstrate the critical advancement of neurodegeneration quantification provided through multiscale mapping. Future work will determine the sensitivity of this technique for accurately detecting individuals with earlier impairment and biomarker positivity in the absence of impairment

sj-docx-1-tae-10.1177_20420188221118750 – Supplemental material for Association between the metabolic profile of serum fatty acids and diabetic nephropathy: a study conducted in northeastern China

Supplemental material, sj-docx-1-tae-10.1177_20420188221118750 for Association between the metabolic profile of serum fatty acids and diabetic nephropathy: a study conducted in northeastern China by Yazhuo Liu, Yingying Li, Hui Shen, Yike Li, Yanbing Xu, Mi Zhou, Xinghai Xia and Binyin Shi in Therapeutic Advances in Endocrinology and Metabolism</p

Thermal/Water-Induced Phase Transformation and Photoluminescence of Hybrid Manganese(II)-Based Chloride Single Crystals

Mn(II)-based hybrid halides have attracted great attention from the optoelectronic fields due to their nontoxicity, special luminescent properties, and structural diversity. Here, two novel organic–inorganic hybrid Mn(II)-based halide single crystals (1-mpip)MnCl4·3H2O and (1-mpip)2MnCl6 (1-mpip = 1-methylpiperazinium, C5H14N2+) were grown by a slow evaporation method in ambient atmosphere. Interestingly, (1-mpip)2MnCl6 single crystals exhibit the green emission with a PL peak at 522 nm and photoluminescence quantum yields (PLQYs) of ≈5.4%, whereas (1-mpip)MnCl4·3H2O single crystals exhibit no emission characteristics. More importantly, there exists a thermal-induced phase transformation from (1-mpip)MnCl4·3H2O to emissive (1-mpip)2MnCl6 at 372 K. Moreover, a reversible luminescent conversion between (1-mpip)MnCl4·3H2O and (1-mpip)2MnCl6 was simply achieved when heated to 383 K and placed in a humid environment or sprayed with water. This work not only deepens the understanding of the thermal-induced phase transformation and humidity-sensitive luminescent conversion of hybrid Mn(II)-based halides, but also provides a guidance for thermal and humidity sensing and anticounterfeiting applications of these hybrid materials

Shanghai cognitive intervention of mild cognitive impairment for delaying progress with longitudinal evaluation-a prospective, randomized controlled study (SIMPLE): rationale, design, and methodology

Abstract Background Mild cognitive impairment is an early stage of Alzheimer’s disease. Increasing evidence has indicated that cognitive training could improve cognitive abilities of MCI patients in multiple cognitive domains, making it a promising therapeutic approach for MCI. However, the effect of long-time training has not been widely explored. It is also necessary to evaluate the extent how it could reduce the convertion rate from MCI to AD. Methods/design The SIMPLE study is a multicenter, randomized, single-blind prospective clinical trial assessing the effects of computerized cognitive training on different cognitive domains in MCI patients. It is carried out in 7 centers in China. The study population includes patients aged 50–85, and they are randomly allocated to the training or control group. The primary outcome is to compare the conversion rate of MCI within 36-month follow-up. Structural and functional MRI will be used to interpret the effect of cognitive training. The cognitive training comprises a variety of games related with cognitive domains such as attention, memory, visualspatial ability and executive function. We cautiously set 50% reduction in the rate of conversion as estimated effect. With 80–90% statistical power and 12% as the overall probability of conversion within the study period, 600–800 patients are finally required in the study. The first patent has been recruited in April 2017. Discussion Previous studies suggested the benefit of cognitive training for MCI, but neither long-time nor Chinese culture were investigated. The SIMPLE designs and utilizes an improved computerized cognitive training approach and assesses its effects on MCI progress. In addition, neural activities explaining the effects on cognition function changes will be revealed, which could in turn to imply more useful therapeutic approaches. Trial registration ClinicalTrials.gov Identifier: NCT03119051

Multifunctional Nanostructure RAP‐RL Rescues Alzheimer's Cognitive Deficits through Remodeling the Neurovascular Unit

Abstract Cerebrovascular dysfunction characterized by the neurovascular unit (NVU) impairment contributes to the pathogenesis of Alzheimer's disease (AD). In this study, a cerebrovascular‐targeting multifunctional lipoprotein‐biomimetic nanostructure (RAP‐RL) constituted with an antagonist peptide (RAP) of receptor for advanced glycation end‐products (RAGE), monosialotetrahexosyl ganglioside, and apolipoprotein E3 is developed to recover the functional NVU and normalize the cerebral vasculature. RAP‐RL accumulates along the cerebral microvasculature through the specific binding of RAP to RAGE, which is overexpressed on cerebral endothelial cells in AD. It effectively accelerates the clearance of perivascular Aβ, normalizes the morphology and functions of cerebrovasculature, and restores the structural integrity and functions of NVU. RAP‐RL markedly rescues the spatial learning and memory in APP/PS1 mice. Collectively, this study demonstrates the potential of the multifunctional nanostructure RAP‐RL as a disease‐modifying modality for AD treatment and provides the proof of concept that remodeling the functional NVU may represent a promising therapeutic approach toward effective intervention of AD

<i>NGFR</i> Gene and Single Nucleotide Polymorphisms, rs2072446 and rs11466162, Playing Roles in Psychiatric Disorders

Psychiatric disorders are a class of complex disorders characterized by brain dysfunction with varying degrees of impairment in cognition, emotion, consciousness and behavior, which has become a serious public health issue. The NGFR gene encodes the p75 neurotrophin receptor, which regulates neuronal growth, survival and plasticity, and was reported to be associated with depression, schizophrenia and antidepressant efficacy in human patient and animal studies. In this study, we investigated its association with schizophrenia and major depression and its role in the behavioral phenotype of adult mice. Four NGFR SNPs were detected based on a study among 1010 schizophrenia patients, 610 patients with major depressive disorders (MDD) and 1034 normal controls, respectively. We then knocked down the expression of NGFR protein in the hippocampal dentate gyrus of the mouse brain by injection of shRNA lentivirus to further investigate its behavioral effect in mice. We found significant associations of s2072446 and rs11466162 for schizophrenia. Ngfr knockdown mice showed social and behavioral abnormalities, suggesting that it is linked to the etiology of neuropsychiatric disorders. We found significant associations between NGFR and schizophrenia and that Ngfr may contribute to the social behavior of adult mice in the functional study, which provided meaningful clues to the pathogenesis of psychiatric disorders

sj-pdf-1-jcb-10.1177_0271678X231153730 - Supplemental material for In vivo synaptic density loss correlates with impaired functional and related structural connectivity in Alzheimer’s disease

Supplemental material, sj-pdf-1-jcb-10.1177_0271678X231153730 for In vivo synaptic density loss correlates with impaired functional and related structural connectivity in Alzheimer’s disease by Junfang Zhang, Jie Wang, Xiaomeng Xu, Zhiwen You, Qi Huang, Yiyun Huang, Qihao Guo, Yihui Guan, Jun Zhao, Jun Liu, Wei Xu, Yulei Deng, Fang Xie and Binyin Li in Journal of Cerebral Blood Flow & Metabolism</p

Image1_College students’ screening early warning factors in identification of suicide risk.jpg

This study aimed to explore the main influencing factors of suicide risk among Chinese students and establish an early warning model to provide interventions for high-risk students. We conducted surveys of students in their first and third years from a cohort study at Jining Medical College. Logistic regression models were used to screen the early warning factors, and four machine learning models were used to establish early warning models. There were 8 factors related to suicide risk that were eventually obtained through screening, including age, having a rough father, and CES-D, OHQ, ASLEC-4, BFI-Neuroticism, BFI-Openness, and MMC-AF-C scores. A random forest model with SMOTE was adopted, and it verified that these 8 early warning signs, for suicide risk can effectively predict suicide risk within 2 years with an AUC score of 0.947. Among the factors, we constructed a model that indicated that different personality traits affected suicide risk by different paths. Moreover, the factors obtained by screening can be used to identify college students in the same year with a high risk of suicide, with an AUC score that reached 0.953. Based on this study, we suggested some interventions to prevent students going high suicide risk.</p