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INTRODUCTION: The established cerebrospinal fluid (CSF) phosphorylated tau181 (p‐tau181) may not reliably reflect concomitant Alzheimer's disease (AD) and primary age‐related tauopathy (PART) found in Creutzfeldt–Jakob disease (CJD) at autopsy. METHODS: We investigated CSF N‐terminal p‐tau181, p‐tau217, and p‐tau231 with in‐house Simoa assays in definite CJD (n = 29), AD dementia (n = 75), mild cognitive impairment (MCI) due to AD (n = 65), and subjective cognitive decline (SCD, n = 28). Post‐mortem examination performed in patients with CJD 1.3 (0.3–14.3) months after CSF collection revealed no co‐pathology in 10, concomitant AD in 8, PART in 8, and other co‐pathologies in 3 patients. RESULTS: N‐terminal p‐tau was increased in CJD versus SCD (p < 0.0001) and correlated with total tau (t‐tau) in the presence of AD and PART co‐pathology (rho = 0.758–0.952, p ≤ 001). Concentrations in CJD+AD were indistinguishable from AD dementia, with the largest fold‐change in p‐tau217 (11.6), followed by p‐tau231 and p‐tau181 (3.2–4.5). DISCUSSION: Variable fold‐changes and correlation with t‐tau suggest that p‐tau closely associates with neurodegeneration and concomitant AD in CJD. Highlights: N‐terminal phosphorylated tau (p‐tau) biomarkers are increased in Creutzfeldt–Jakob disease (CJD) with and without concomitant AD.P‐tau217, p‐tau231, and p‐tau181 correlate with total tau (t‐tau) and increase in the presence of amyloid beta (Aβ) co‐pathology.N‐terminal p‐tau181 and p‐tau231 in Aβ‐negative CJD show variation among PRNP genotypes.Compared to mid‐region–targeting p‐tau181, cerebrospinal fluid (CSF) N‐terminal p‐tau has greater potential to reflect post‐mortem neuropathology in the CJD brain. [ABSTRACT FROM AUTHOR]

Ear images have been shown to be a reliable modality for biometric recognition with desirable characteristics, such as high universality, distinctiveness, measurability and permanence. While a considerable amount of research has been directed towards ear recognition techniques, the problem of ear alignment is still under‐explored in the open literature. Nonetheless, accurate alignment of ear images, especially in unconstrained acquisition scenarios, where the ear appearance is expected to vary widely due to pose and view point variations, is critical for the performance of all downstream tasks, including ear recognition. Here, the authors address this problem and present a framework for ear alignment that relies on a two‐step procedure: (i) automatic landmark detection and (ii) fiducial point alignment. For the first (landmark detection) step, the authors implement and train a Two‐Stack Hourglass model (2‐SHGNet) capable of accurately predicting 55 landmarks on diverse ear images captured in uncontrolled conditions. For the second (alignment) step, the authors use the Random Sample Consensus (RANSAC) algorithm to align the estimated landmark/fiducial points with a pre‐defined ear shape (i.e. a collection of average ear landmark positions). The authors evaluate the proposed framework in comprehensive experiments on the AWEx and ITWE datasets and show that the 2‐SHGNet model leads to more accurate landmark predictions than competing state‐of‐the‐art models from the literature. Furthermore, the authors also demonstrate that the alignment step significantly improves recognition accuracy with ear images from unconstrained environments compared to unaligned imagery. [ABSTRACT FROM AUTHOR]

Blue phases (BPs) are soft and stimuli‐responsive photonic crystals that are interesting for sensing, display, and lasing applications. Polycrystallinity has, however, limited both the study and applicability of BPs. Continuum simulations, which lack molecule‐specific details, predict that striped chemical patterns, consisting of alternating homeotropic and planar regions, can be used to nucleate single crystals of BPs. Here it is experimentally demonstrated that, independent of the chemistry and complexity of the BP forming material, chemical patterns direct the self‐assembly of BPs; these results indicate that a general, thermodynamics‐based continuum description of BP self‐assembly is adequate for a broad range of materials. When the pattern periodicity equals the BPII unit cell size, single crystals with (100) orientation form for all studied materials. Chemical patterns also promote the growth of BPI crystals with (110) orientation. Importantly, the self‐assembly of a photopolymerizable BP is directed and thermally stable, UV‐polymerized single crystals are prepared. The ability to create arbitrarily large, polymeric photonic single crystals with uniform lattice orientation, may have broad implications for optical applications. [ABSTRACT FROM AUTHOR]

Introduction: Phosphorylated tau (p‐tau) in cerebrospinal fluid (CSF) is an established Alzheimer's disease (AD) biomarker. Novel immunoassays targeting N‐terminal and mid‐region p‐tau181 and p‐tau217 fragments are available, but head‐to‐head comparison in clinical settings is lacking. Methods: N‐terminal‐directed p‐tau217 (N‐p‐tau217), N‐terminal‐directed p‐tau181 (N‐p‐tau181), and standard mid‐region p‐tau181 (Mid‐p‐tau181) biomarkers in CSF were evaluated in three cohorts (n = 503) to assess diagnostic performance, concordance, and associations with amyloid beta (Aβ). Results: CSF N‐p‐tau217 and N‐p‐tau181 had better concordance (88.2%) than either with Mid‐p‐tau181 (79.7%–82.7%). N‐p‐tau217 and N‐p‐tau181 were significantly increased in early mild cognitive impairment (MCI)‐AD (A+T–N–) without changes in Mid‐p‐tau181 until AD‐dementia. N‐p‐tau217 and N‐p‐tau181 identified Aβ pathophysiology (area under the curve [AUC] = 94.8%–97.1%) and distinguished MCI‐AD from non‐AD MCI (AUC = 82.6%–90.5%) signficantly better than Mid‐p‐tau181 (AUC = 91.2% and 70.6%, respectively). P‐tau biomarkers equally differentiated AD from non‐AD dementia (AUC = 99.1%–99.8%). Discussion: N‐p‐tau217 and N‐p‐tau181 could improve diagnostic accuracy in prodromal‐AD and clinical trial recruitment as both identify Aβ pathophysiology and differentiate early MCI‐AD better than Mid‐p‐tau181. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) is marked by accumulation of Aβ and tau protein causing neurodegeneration in the brain. AD represents a pathological and clinical continuum, ranging from mild cognitive impairment (MCI) to dementia. A specific metabolic imaging biomarker of AD ‐ Alzheimer's disease‐related pattern (ADRP) has been previously identified from 2‐[18F]fluorodeoxyglucose positron emission tomography (2‐[18F]FDG‐PET) scans of clinically diagnosed AD patients, using scaled subprofile model based on principal component analysis (SSM/PCA) 1–3. However the clinical diagnosis may be wrong in substantial number of cases 4. We aimed to identify ADRP on patients with Alzheimer's pathological changes in cerebrospinal (CSF) fluid and to validate it in an independent group of AD and other dementia patients and compare it to the original ADRP 1. Method: 2‐[18F]FDG‐PET scans from 20 AD1 and 20 normal controls (NC1) were used for pattern identification. Additional 110 scans were analyzed for validation: 68 from AD patients (37 AD2, 13 atypical clinical presentation AD (atAD), 18 MCI), 21 with frontotemporal dementia (FTD), 8 non‐AD MCI and 13 NC2 (Table 1). AD was defined with CSF biomarkers as: Aβ42 < 815 pg/ml, pTau > 60 pg/ml, tTau > 400 pg/ml. Topographic profile rating algorithm was used to prospectively calculate ADRP Z‐scores from subjects scans3. Mini‐mental state examination (MMSE) was performed in all patients. Results: ADRP was identified and voxel weights were found to be stable by bootstrap resampling, Figure 1. Pattern's expression was significantly higher in AD1 than NC1 (p<0.001) and it strongly correlated (r=‐0.70) with MMSE. Pattern's expression was also higher in AD2 than NC2 (p<0.001), MCI vs. NC2 (p<0.001), MCI vs. non‐AD MCI (p=0.02) and AD2 vs. FTD (p=0.02), Figure 2. Newly identified pattern moderately correlated (r=0.52) with the original one 1. Conclusions: We identified ADRP on a cohort of pathologically confirmed AD patients, which was not done before. ADRP has shown to be a reliable metabolic biomarker of AD related neurodegeneration. References: (1) Mattis,PJ. et al. Neurology 87,1925–33(2016); (2) Teune,LK. et al. Curr Alzheimer Res 11,725–32(2014); (3) Spetsieris,PG. & Eidelberg,D. Neuroimage 54,2899–914(2011); (4) Beach,TG. et al. J. Neuropathol. Exp. Neurol. 71,266–273(2012). [ABSTRACT FROM AUTHOR]

Object detection and segmentation represents the basis for many tasks in computer and machine vision. In biometric recognition systems the detection of the region‐of‐interest (ROI) is one of the most crucial steps in the processing pipeline, significantly impacting the performance of the entire recognition system. Existing approaches to ear detection, are commonly susceptible to the presence of severe occlusions, ear accessories or variable illumination conditions and often deteriorate in their performance if applied on ear images captured in unconstrained settings. To address these shortcomings, we present a novel ear detection technique based on convolutional encoder‐decoder networks (CEDs). We formulate the problem of ear detection as a two‐class segmentation problem and design and train a CED‐network architecture to distinguish between image‐pixels belonging to the ear and the non‐ear class. Unlike competing techniques, our approach does not simply return a bounding box around the detected ear, but provides detailed, pixel‐wise information about the location of the ears in the image. Experiments on a dataset gathered from the web (a.k.a. in the wild) show that the proposed technique ensures good detection results in the presence of various covariate factors and significantly outperforms competing methods from the literature. [ABSTRACT FROM AUTHOR]

The authors developed a mathematical model of arachidonic acid (AA) degradation to prostaglandins (PGs) and leukotrienes (LTs), which are implicated in the processes of inflammation and hypersensitivity to non‐steroidal anti‐inflammatory drugs (NSAIDs). The model focuses on two PGs (PGE2 and PGD2) and one LT (LTC4), their % increases and their ratios. Results are compared with experimental studies obtained from non‐asthmatics (NAs), and asthmatics tolerant (ATA) or intolerant (AIA) to aspirin. Simulations are carried out for predefined model populations NA, ATA and three AIA, based on the differences of two enzymes, PG E synthase and/or LTC4‐synthase in two states, that is, no‐inflammation and inflammation. Their model reveals that the model population with concomitant malfunctions in both enzymes is the most sensitive to NSAIDs, since the duration and the capacity for bronchoconstriction risk are highest after simulated oral dosing of indomethacin. Furthermore, inflammation prolongs the duration of the bronchoconstriction risk in all AIA model populations, and the sensitivity analysis reveals multiple possible scenarios leading to hypersensitivity, especially if inflammatory processes affect the expression of multiple enzymes of the AA metabolic pathway. Their model estimates the expected fold‐changes in enzyme activities and gives valuable information for further targeted transcriptomic/proteomic and metabolomic studies. [ABSTRACT FROM AUTHOR]

Background: The increasing number of patients with neurodegenerative dementia is a major public health issue. While clinical features of neurodegenerative disorders causing dementia are overlapping, accurate diagnosis is a prerequisite for an effective drug development. Besides the need for a better biomarker of Alzheimer’s disease (AD), development of non‐AD biomarkers is necessary. Behavioral variant of frontotemporal dementia (bvFTD) is the second most common neurodegenerative dementia in patients younger than 65 years. The aim of our study was to identify and validate bvFTD specific metabolic brain pattern using voxel‐based spatial covariance analysis according to the scaled subprofile model (SSM/PCA) on a new cohort of European patients and to study its biologic significance. Method: 20 patients with clinical diagnosis of bvFTD and 20 age‐matched normal controls (NC) underwent metabolic imaging with FDG PET. CSF results were available for 10/20 bvFTD patients and potential AD was excluded based on the biomarker profile. Using SSM/PCA, we identified a significant bvFTD‐related metabolic pattern termed bFDRP‐Slov. The stability of voxel weights on this pattern was evaluated using bootstrap resampling. For validation, pattern expression values were computed in an independent testing set comprised of 25 bvFTD and 22 NC subjects. The specificity of the pattern for bvFTD was assessed by computing values in patients with other causes of dementia: 26 with AD and 16 with sporadic Creutzfeldt‐Jakob disease (sCJD). bFDRP expression was correlated with disease duration and with MMSE. Result: The bFDRP was characterized by pronounced metabolic reduction in the medial frontal cortex, middle and inferior frontal gyri, anterior cingulum, insula, bilateral caudate and thalamus. bvFDRP expression values discriminated bvFTD patients from their counterparts with AD, sCJD and NC (p<0.0001; one‐way ANOVA). The expression of this pattern was abnormally elevated in bvFTD patients in the identification and validation cohorts (p<0.0001). bvFTD patients’ pattern expression of values did not correlate disease duration or MMSE. Conclusion: bFDRP is a promising metabolic network biomarker of the disorder, consistent with previously identified disease pattern. Further research is needed to study its clinical significance. Identification of multiple neurodegenerative brain networks may be critical as the combination of different patterns can improve diagnostic accuracy. [ABSTRACT FROM AUTHOR]

Background: Nowadays, Alzheimer's disease (AD) can be diagnosed in vivo using both cerebrospinal fluid (CSF) and positron emission tomography (PET) biomarkers. Although highly accurate, their broad implementation has been impeded due to limitations including high cost, perceived invasiveness and limited availability. Thus, much effort has been placed in the discovery of blood biomarkers. In this context, our high performance blood immunoassay for p‐tau181 has already showed an excellent ability to specifically identify AD. Therefore, the aim of this study was to investigate if plasma p‐tau181 reflects AD pathology in post‐mortem confirmed cases and if this biomarker can successfully discriminate AD from non‐AD dementia pathologies. Method: Using our plasma p‐tau181 assay, we studied a unique cohort of 115 individuals selected from the Maudsley and King's Healthcare Partners Dementia Case Register, which incorporates the Alzheimer's Research UK cohort. The cohort included longitudinal plasma collections and clinical evaluation at 8, 4 and 2 years followed by neuropathological examination after death. Result: Our results demonstrate that plasma p‐tau181 accurately predicts AD pathology and Braak staging at least 8 years before death. Moreover, plasma p‐tau181 proved to accurately discriminate AD from non‐AD pathologies (AUC=97.5%, 95% CI=94.1‐100%). This strongly suggests that a clinical diagnosis of AD dementia combined with low plasma p‐tau181 levels would be useful to identify non‐AD pathology. Additionally, we described the longitudinal trajectory of plasma p‐tau181 in AD patients. We found that the main increase in plasma p‐tau181 levels occurred between 8 and 4 years before death, and later plateaus. Conclusion: Altogether, our results demonstrate that plasma p‐tau181 is highly specific and predictive of AD pathology several years before neuropathological examination. Moreover, these results strongly support the implementation of plasma p‐tau181 in clinical diagnosis, longitudinal monitoring and therapeutic trial recruitment. [ABSTRACT FROM AUTHOR]

Background: Cerebrospinal fluid (CSF) phospho‐tau181 (p‐tau181) is an established biomarker of tangle pathology in Alzheimer's disease (AD), but does not detect aberrant tau phosphorylation in other tauopathies. Recently, tau phosphorylation at threonine‐217 (p‐tau217) was suggested to be a superior biomarker for AD pathology. However, it is unclear if p‐tau217 is increased in other neurodegenerative diseases, including Creutzfeldt–Jakob disease (CJD) with concomitant amyloid/tau pathology or in primary tauopathies such as progressive supranuclear palsy (PSP). Method: We validated an ultrasensitive Single molecule array (Simoa) p‐tau217 immunoassay and tested its diagnostic performance in the CSF of AD (n=110), CJD (n=22), and PSP (n=22) patients as well as age‐matched controls (n=106). Prospectively recruited patients were classified based on clinical presentation and the core CSF biomarker profile (amyloid‐beta‐42[Aβ1‐42 <650 pg/ml], [Aβ1‐42/Aβ1‐40 ratio<0.08], total‐tau <400 pg/ml and p‐tau181 >60 pg/ml) measured by INNOTEST® immunoassays (Fujirebio). Diagnostic performance was compared against INNOTEST® p‐tau181 using area under the curve (AUC). Result: The in‐house p‐tau217 assay demonstrated a lower limit of quantification of 1.4pg/ml with robust analytical performance, including dilution linearity (mean recovery=104%), spike recovery (mean recovery=97%) and antibody specificity. P‐tau217 correlated strongly with p‐tau181 in all participants (r=0.82, p<0.0001) and showed six‐fold mean increase in both AD and CJD versus either controls or PSP (p<0.0001). In contrast, p‐tau181 was only increased 2.5‐fold in AD patients (p>0.05), but not CJD. P‐tau217 and p‐tau181 had similar performances in separating AD from controls (AUC>97%), and AD from PSP (AUC>95%). P‐tau217 poorly differentiated AD from CJD (AUC=63%, compared with 87% for p‐tau181) due to the highly overlapping p‐tau217 concentrations in both groups. However, p‐tau217 better distinguished CJD from controls (AUC=96%) compared with p‐tau181 (AUC=76%). Cross‐sectionally, p‐tau217 associated with CSF Aβ1‐42 (r= ‐0.76, p<0.0001). In diagnostic group‐stratified analyses, p‐tau217 correlated with Aβ1‐42/Aβ1‐40 only in AD (r= ‐0.31, p<0.05). Conclusion: Unlike the AD‐specific p‐tau181, p‐tau217 had a very high diagnostic accuracy in distinguishing both AD and CJD from controls. P‐tau217 increases in CJD appear independent of amyloidosis. P‐tau217 identifies tau pathology in both diseases whilst p‐tau181 is useful for confirming AD diagnosis. [ABSTRACT FROM AUTHOR]

In the autumn of 2004, tuberculosis caused by Mycobacterium caprae occurred in a zoo in Slovenia. A dromedary camel ( Camelus dromedarius) was killed after a history of progressive emaciation. Necropsy findings indicated disseminated tuberculosis, which was confirmed by cultivation of M. caprae. Consequently, a tuberculin skin test was performed in all epidemiologically linked animals and another dromedary camel and six bison ( Bison bison) were positive and killed. Mycobacterium caprae was isolated from two bison while M. scrofulaceum and Mycobacterium spp. were found in two other bison, respectively. The second dromedary camel was found to be negative for mycobacteria under both microscopic and culture tests. The isolates were investigated with commercial identification kits, IS 6110 PCR, IS 6110 restriction fragment length polymorphism analysis, spoligotyping and mycobacterial interspersed repetitive units typing. Genotyping results revealed that the dromedary camel and the two bison were infected by the same M. caprae. [ABSTRACT FROM AUTHOR]