An attention-based deep learning approach for the classification of subjective cognitive decline and mild cognitive impairment using resting-state EEG

Objective. This study aims to design and implement the first deep learning (DL) model to classify subjects in the prodromic states of Alzheimer's disease (AD) based on resting-state electroencephalographic (EEG) signals.Approach. EEG recordings of 17 healthy controls (HCs), 56 subjective cognitive decline (SCD) and 45 mild cognitive impairment (MCI) subjects were acquired at resting state. After preprocessing, we selected sections corresponding to eyes-closed condition. Five different datasets were created by extracting delta, theta, alpha, beta and delta-to-theta frequency bands using bandpass filters. To classify SCDvsMCI and HCvsSCDvsMCI, we propose a framework based on the transformer architecture, which uses multi-head attention to focus on the most relevant parts of the input signals. We trained and validated the model on each dataset with a leave-one-subject-out cross-validation approach, splitting the signals into 10 s epochs. Subjects were assigned to the same class as the majority of their epochs. Classification performances of the transformer were assessed for both epochs and subjects and compared with other DL models.Main results. Results showed that the delta dataset allowed our model to achieve the best performances for the discrimination of SCD and MCI, reaching an Area Under the ROC Curve (AUC) of 0.807, while the highest results for the HCvsSCDvsMCI classification were obtained on alpha and theta with a micro-AUC higher than 0.74.Significance. We demonstrated that DL approaches can support the adoption of non-invasive and economic techniques as EEG to stratify patients in the clinical population at risk for AD. This result was achieved since the attention mechanism was able to learn temporal dependencies of the signal, focusing on the most discriminative patterns, achieving state-of-the-art results by using a deep model of reduced complexity. Our results were consistent with clinical evidence that changes in brain activity are progressive when considering early stages of AD

Degradation of EEG microstates patterns in subjective cognitive decline and mild cognitive impairment: Early biomarkers along the Alzheimer's Disease continuum?

Alzheimer's disease (AD) pathological changes may begin up to decades earlier than the appearance of the first symptoms of cognitive decline. Subjective cognitive decline (SCD) could be the first pre-clinical sign of possible AD, which might be followed by mild cognitive impairment (MCI), the initial stage of clinical cognitive decline. However, the neural correlates of these prodromic stages are not completely clear yet. Recent studies suggest that EEG analysis tools characterizing the cortical activity as a whole, such as microstates and cortical regions connectivity, might support a characterization of SCD and MCI conditions. Here we test this approach by performing a broad set of analyses to identify the prominent EEG markers differentiating SCD (n = 57), MCI (n = 46) and healthy control subjects (HC, n = 19). We found that the salient differences were in the temporal structure of the microstates patterns, with MCI being associated with less complex sequences due to the altered transition probability, frequency and duration of canonic microstate C. Spectral content of EEG, network connectivity, and spatial arrangement of microstates were instead largely similar in the three groups. Interestingly, comparing properties of EEG microstates in different cerebrospinal fluid (CSF) biomarkers profiles, we found that canonic microstate C displayed significant differences in topography in AD-like profile. These results show that the progression of dementia might be associated with a degradation of the cortical organization captured by microstates analysis, and that this leads to altered transitions between cortical states. Overall, our approach paves the way for the use of non-invasive EEG recordings in the identification of possible biomarkers of progression to AD from its prodromal states

Novel mutations in human and mouse SCN4A implicate AMPK in myotonia and periodic paralysis

Mutations in the skeletal muscle channel (SCN4A), encoding the Nav1.4 voltage-gated sodium channel, are causative of a variety of muscle channelopathies, including non-dystrophic myotonias and periodic paralysis. The effects of many of these mutations on channel function have been characterized both in vitro and in vivo. However, little is known about the consequences of SCN4A mutations downstream from their impact on the electrophysiology of the Nav1.4 channel. Here we report the discovery of a novel SCN4A mutation (c.1762A>G; p.I588V) in a patient with myotonia and periodic paralysis, located within the S1 segment of the second domain of the Nav1.4 channel. Using N-ethyl-N-nitrosourea mutagenesis, we generated and characterized a mouse model (named draggen), carrying the equivalent point mutation (c.1744A>G; p.I582V) to that found in the patient with periodic paralysis and myotonia. Draggen mice have myotonia and suffer from intermittent hind-limb immobility attacks. In-depth characterization of draggen mice uncovered novel systemic metabolic abnormalities in Scn4a mouse models and provided novel insights into disease mechanisms. We discovered metabolic alterations leading to lean mice, as well as abnormal AMP-activated protein kinase activation, which were associated with the immobility attacks and may provide a novel potential therapeutic target

Orphan GPR116 mediates the insulin sensitizing effects of the hepatokine FNDC4 in adipose tissue

The proper functional interaction between different tissues represents a key component in systemic metabolic control. Indeed, disruption of endocrine inter-tissue communication is a hallmark of severe metabolic dysfunction in obesity and diabetes. Here, we show that the FNDC4-GPR116, liver-white adipose tissue endocrine axis controls glucose homeostasis. We found that the liver primarily controlled the circulating levels of soluble FNDC4 (sFNDC4) and lowering of the hepatokine FNDC4 led to prediabetes in mice. Further, we identified the orphan adhesion GPCR GPR116 as a receptor of sFNDC4 in the white adipose tissue. Upon direct and high affinity binding of sFNDC4 to GPR116, sFNDC4 promoted insulin signaling and insulin-mediated glucose uptake in white adipocytes. Indeed, supplementation with FcsFNDC4 in prediabetic mice improved glucose tolerance and inflammatory markers in a white-adipocyte selective and GPR116-dependent manner. Of note, the sFNDC4-GPR116, liver-adipose tissue axis was dampened in (pre) diabetic human patients. Thus our findings will now allow for harnessing this endocrine circuit for alternative therapeutic strategies in obesity-related pre-diabetes. The soluble bioactive form of the transmembrane protein fibronectin type III domain containing 4 (sFNDC4) has anti-inflammatory effects and improves insulin sensitivity. Here the authors show that liver derived sFNDC4 signals through adipose tissue GPCR GPR116 to promote insulin-mediated glucose uptake.Peer reviewe

3D morphometric analysis of calcified cartilage properties using micro-computed tomography

OBJECTIVE: Our aim is to establish methods for quantifying morphometric properties of calcified cartilage (CC) from micro-computed tomography (muCT). Furthermore, we evaluated the feasibility of these methods in investigating relationships between osteoarthritis (OA), tidemark surface morphology and open subchondral channels (OSCCs). METHOD: Samples (n = 15) used in this study were harvested from human lateral tibial plateau (n = 8). Conventional roughness and parameters assessing local 3-dimensional (3D) surface variations were used to quantify the surface morphology of the CC. Subchondral channel properties (percentage, density, size) were also calculated. As a reference, histological sections were evaluated using Histopathological osteoarthritis grading (OARSI) and thickness of CC and subchondral bone (SCB) was quantified. RESULTS: OARSI grade correlated with a decrease in local 3D variations of the tidemark surface (amount of different surface patterns (rs = -0.600, P = 0.018), entropy of patterns (EP) (rs = -0.648, P = 0.018), homogeneity index (HI) (rs = 0.555, P = 0.032)) and tidemark roughness (TMR) (rs = -0.579, P = 0.024). Amount of different patterns (ADP) and EP associated with channel area fraction (CAF) (rp = 0.876, P < 0.0001; rp = 0.665, P = 0.007, respectively) and channel density (CD) (rp = 0.680, P = 0.011; rp = 0.582, P = 0.023, respectively). TMR was associated with CAF (rp = 0.926, P < 0.0001) and average channel size (rp = 0.574, P = 0.025). CC topography differed statistically significantly in early OA vs healthy samples. CONCLUSION: We introduced a mu-CT image method to quantify 3D CC topography and perforations through CC. CC topography was associated with OARSI grade and OSCC properties; this suggests that the established methods can detect topographical changes in tidemark and CC perforations associated with OA

Search for top-down and bottom-up drivers of latitudinal trends in insect herbivory in oak trees in Europe

International audienceAim: The strength of species interactions is traditionally expected to increase toward the Equator. However, recent studies have reported opposite or inconsistent latitudinal trends in the bottom-up (plant quality) and top-down (natural enemies) forces driving herbivory. In addition, these forces have rarely been studied together thus limiting previous attempts to understand the effect of large-scale climatic gradients on herbivory. Location: Europe. Time period: 2018–2019. Major taxa studied: Quercus robur. Methods: We simultaneously tested for latitudinal variation in plant–herbivore–natural enemy interactions. We further investigated the underlying climatic factors associated with variation in herbivory, leaf chemistry and attack rates in Quercus robur across its complete latitudinal range in Europe. We quantified insect leaf damage and the incidence of specialist herbivores as well as leaf chemistry and bird attack rates on dummy caterpillars on 261 oak trees. Results: Climatic factors rather than latitude per se were the best predictors of the large-scale (geographical) variation in the incidence of gall-inducers and leaf-miners as well as in leaf nutritional content. However, leaf damage, plant chemical defences (leaf phenolics) and bird attack rates were not influenced by climatic factors or latitude. The incidence of leaf-miners increased with increasing concentrations of hydrolysable tannins, whereas the incidence of gall-inducers increased with increasing leaf soluble sugar concentration and decreased with increasing leaf C : N ratios and lignins. However, leaf traits and bird attack rates did not vary with leaf damage. Main conclusions: These findings help to refine our understanding of the bottom-up and top-down mechanisms driving geographical variation in plant–herbivore interactions, and indicate the need for further examination of the drivers of herbivory on trees

Emerging concepts in biomarker discovery; The US-Japan workshop on immunological molecular markers in oncology

Supported by the Office of International Affairs, National Cancer Institute (NCI), the "US-Japan Workshop on Immunological Biomarkers in Oncology" was held in March 2009. The workshop was related to a task force launched by the International Society for the Biological Therapy of Cancer (iSBTc) and the United States Food and Drug Administration (FDA) to identify strategies for biomarker discovery and validation in the field of biotherapy. The effort will culminate on October 28th 2009 in the "iSBTc-FDA-NCI Workshop on Prognostic and Predictive Immunologic Biomarkers in Cancer", which will be held in Washington DC in association with the Annual Meeting. The purposes of the US-Japan workshop were a) to discuss novel approaches to enhance the discovery of predictive and/or prognostic markers in cancer immunotherapy; b) to define the state of the science in biomarker discovery and validation. The participation of Japanese and US scientists provided the opportunity to identify shared or discordant themes across the distinct immune genetic background and the diverse prevalence of disease between the two Nations