During discourse comprehension, every new word adds to an evolving representation of meaning that accumulates over consecutive sentences and constrains the next words. To minimize repetition and utterance length, languages use pronouns, like the word ‘she’, to refer to nouns and phrases that were previously introduced. It has been suggested that language comprehension requires that pronouns activate the same neuronal represen­tations as the nouns themselves. We recorded individual neurons in the human hippocampus during a reading task. Brain-imaging studies have gained insight into the brain regions that activate during sentence and discourse comprehension. However, the resolution of these methods does not suffice to track the neuronal assemblies that encode individual concepts in the human brain during reading. It has become possible to directly record the activity of single neurons in patients who are implanted with electrodes to locate the source of their epilepsy. These studies demonstrated the existence of ‘concept cells’ in the medial temporal lobe. Concept cells have an invariant and multimodal selective response to a concept. They contribute to the representation of meaning because they not only activate when the participant sees a picture of a specific individual for example, but also when the participant hears or reads the name of this person, or recalls this individual from memory. We hypothesized that monitoring the activity of concept cells during reading could provide insight into the dynamics of semantic representations during language comprehension. We found that cells that were selective to a particular noun were later reactivated by pronouns that refer to the cells’ preferred noun. These results imply that concept cells contribute to a rapid and dynamic semantic memory network that is recruited during language comprehension.

Objective: To investigate the association between discordant amyloid-β PET and CSF biomarkers at baseline and the emergence of tau pathology 5 years later. Methods: We included 730 ADNI participants without dementia (282 cognitively normal, 448 mild cognitive impairment) with baseline [18F]Florbetapir PET and CSF Aβ42 available. Amyloid-β CSF/PET status was determined at baseline using established cut-offs. Longitudinal data was available for [18F]florbetapir (Aβ) PET (baseline to 4.3±1.9 years), CSF (p)tau (baseline to 2.0±0.1 years), cognition (baseline to 4.3±2.0 years), and [18F]flortaucipir (tau) PET (measured 5.2±1.2 years after baseline to 1.6±0.7 years later). We used linear mixed modelling to study the association between amyloid-β CSF/PET status and tau pathology measured in CSF or using PET. Additionally, we calculated the proportion of CSF+/PET- participants who during follow-up (i) progressed to amyloid-β CSF+/PET+, and/or (ii) became tau-positive based on [18F]flortaucipir PET. Results: Amyloid-β CSF+/PET+ (N=318) participants had elevated CSF (p)tau levels and worse cognitive performance at baseline, while CSF+/PET- (N=80) participants were overall similar to the CSF-/PET- (N=306) group. Five years after baseline, [18F]flortaucipir PET uptake in the CSF+/PET- group (1.20±0.13) did not differ from CSF-/PET- (1.18±0.08, p=0.69), but was substantially lower than CSF+/PET+ (1.48±0.44, p<0.001). Of the CSF+/PET- subjects, 21/64 (33%) progressed to amyloid-β CSF+/PET+, whereas only one (3%, difference p<0.05) became tau-positive based on [18F]flortaucipir PET.  Conclusions: Amyloid-β load detectable by both CSF and PET seems to precede substantial tau deposition. Compared to participants with abnormal amyloid-β levels on both PET and CSF, the CSF+/PET- group has a distinctly better prognosis.

Objective: To investigate the association between apolipoprotein E (APOE) genotype and amyloid-β (Aβ) burden, as measured by PET in patients with subcortical vascular cognitive impairment (SVCI) and those with Alzheimer’s disease-related cognitive impairment (ADCI). Methods: This was a cross-sectional study of 310 patients with SVCI and 999 with ADCI. To evaluate the effects of APOE genotype or diagnostic group on Aβ-positivity, we performed multivariate logistic regression analyses. Further distinctive underlying features of latent subgroups were examined by employing a latent class cluster analysis approach. Results: In comparison with ε3 homozygotes, in the ADCI group, ε2 carriers showed a lower frequency of Aβ-positivity (odds ratio [OR] 0.43, 95% CI 0.23–0.79) while in the SVCI group, ε2 carriers showed a higher frequency of Aβ-positivity (OR 2.26, 95% CI 1.02–5.01). In particular, we observed an interaction effect of ε2 carrier status and diagnostic group on Aβ-positivity (OR 5.12, 95% CI 1.93–13.56), in that relative to ε3 homozygotes, there were more Aβ-positive ε2 carriers in the SVCI group than in the ADCI group. We also identified latent subgroups of Aβ-positive APOE ε2 carriers with SVCI and Aβ-positive APOE ε4 carriers with ADCI. Conclusions: Our findings suggest that APOE ε2 shows distinctly associated with Aβ deposition in patients with SVCI and those with ADCI. Our findings further suggest that there is a distinctive subgroup of Aβ-positive APOE ε2 carriers with SVCI among patients with cognitive impairments.

Background: The effects of shared clinical notes on patients, care partners, and clinicians (“open notes”) were first studied as a demonstration project in 2010. Since then, multiple studies have shown clinicians agree shared progress notes are beneficial to patients, and patients and care partners report benefits from reading notes. To determine if implementing open notes at a hematology/oncology practice changed providers’ documentation style, we assessed the length and readability of clinicians’ notes before and after open notes implementation at an academic medical center in Boston, MA. Methods: We analyzed 143,888 notes from 60 hematology/oncology clinicians before and after the open notes debut at Beth Israel Deaconess Medical Center, from January 1, 2012, to September 1, 2016. We measured the providers’ (medical doctor/nurse practitioner) documentation styles by analyzing character length, the number of addenda, note entry mode (dictated vs. typed) and note readability. Measurements used five different readability formulas and were assessed on notes written before and after the introduction of open notes on November 25, 2013. Results: After the introduction of open notes, the mean length of progress notes increased from 6,174 characters to 6,648 characters (P<0.001), and the mean character length of the “assessment and plan” (A&P) increased from 1,435 characters to 1,597 characters (P<0.001). The Average Grade Level Readability of progress notes decreased from 11.50 to 11.33, and overall readability improved by 0.17 (P=0.01). There were no statistically significant changes in the length or readability of “Initial Notes” or Letters, inter-doctor communication, nor in the modality of the recording of any kind of note. Conclusions: After the implementation of open notes, progress notes and A&P sections became both longer and easier to read. This suggests clinician documenters may be responding to the perceived pressures of a transparent medical records environment.

Objective: To determine whether atrophy relates to phenotypical variants of posterior cortical atrophy (PCA) recently proposed in clinical criteria; dorsal, ventral, dominant-parietal and caudal, we assessed associations between latent atrophy factors and cognition. Methods: We employed a data-driven Bayesian modelling framework based on latent Dirichlet allocation to identify latent atrophy factors in a multi-center cohort of 119 individuals with PCA (age:64±7, 38% male, MMSE:21±5, 71% amyloid-β-positive, 29% amyloid-β status unknown). The model uses standardized gray matter density images as input (adjusted for age, sex, intracranial volume, field-strength and whole-brain gray matter volume) and provides voxelwise probabilistic maps for a predetermined number of atrophy factors, allowing every individual to express each factor to a degree without a-priori classification. Individual factor expressions were correlated to four PCA-specific cognitive domains (object-perception, space-perception, non-visual/parietal functions and primary visual processing) using general linear models. Results: The model revealed four distinct yet partially overlapping atrophy factors; right-dorsal, right-ventral, left-ventral, and limbic. We found that object-perception and primary visual processing were associated with atrophy that predominantly reflects the right-ventral factor. Furthermore, space-perception was associated with atrophy that predominantly represents the right-dorsal and right-ventral factors. However, individual participant profiles revealed that the vast majority expressed multiple atrophy factors and had mixed clinical profiles with impairments across multiple domains, rather than displaying a discrete clinical-radiological phenotype. Conclusion: Our results indicate that particular brain-behavior networks are vulnerable in PCA, but most individuals display a constellation of affected brain-regions and symptoms, indicating that classification into four mutually exclusive variants is unlikely to be clinically useful.

Objective: To assess the onset of ocrelizumab efficacy on brain magnetic resonance imaging (MRI) measures of disease activity in the Phase II study in relapsing-remitting multiple sclerosis (RRMS), and relapse rate in the pooled Phase III studies in relapsing multiple sclerosis (RMS). Methods: Brain MRI activity was determined in the Phase II trial at monthly intervals in patients with RRMS receiving placebo, ocrelizumab (600 mg), or intramuscular interferon (IFN) β-1a (30 μg). Annualized relapse rate (ARR; over various epochs) and time to first relapse were analyzed in the pooled population of the Phase III OPERA I and OPERA II trials in patients with RMS receiving ocrelizumab (600 mg) or subcutaneous IFN β-1a (44 μg). Results: In patients with RRMS, ocrelizumab reduced the number of new T1 gadolinium-enhancing lesions by Week 4 vs placebo (p=0.042) and by Week 8 vs intramuscular IFN β-1a (p<0.001). Ocrelizumab also reduced the number of new or enlarging T2 lesions appearing between Weeks 4 and 8 vs both placebo and IFN β-1a (both p<0.001). In patients with RMS, ocrelizumab significantly reduced ARR (p=0.005), and the probability of time to first protocol-defined relapse (p=0.014) vs subcutaneous IFN β-1a within the first 8 weeks. Conclusion: Epoch analysis of MRI-measured lesion activity in the Phase II study and relapse rate in the Phase III studies consistently revealed a rapid suppression of acute MRI and clinical disease activity following treatment initiation with ocrelizumab in patients with RRMS and RMS, respectively. Classification of evidence: This study provides Class II evidence that for patients with RRMS and RMS, ocrelizumab suppressed MRI activity within 4 weeks and clinical disease activity within 8 weeks.

OBJECTIVE To assess the relevance of Quantitative electroencephalography (qEEG) measures as outcomes of disease severity and progression in PD. METHODS Main databases were systematically searched (January 2018) for studies of sufficient methodological quality that examined correlations between clinical symptoms of idiopathic PD and cortical (surface) qEEG metrics. RESULTS Thirty-six out of 605 identified studied were included. Results were classified into four domains: cognition (23 studies), motor function (13 studies), effect of treatment (7 studies), and other (10 studies). In cross-sectional studies, EEG slowing correlated with global cognitive impairment and with diffuse deterioration in other domains. In longitudinal studies, decreased dominant frequency and increased θ power, reflecting EEG slowing, were biomarkers of cognitive deterioration at an individual level. Results on motor dysfunction and treatment yielded contrasting findings. Studies on functional connectivity at an individual level, longitudinal studies on other domains or on connectivity measures, were lacking. CONCLUSION QEEG parameters reflecting EEG slowing, particularly decreased dominant frequency and increased θ power, correlate with cognitive impairment and predict future cognitive deterioration. QEEG could provide reliable and widely available biomarkers for non-motor disease severity and progression in PD, potentially promoting early diagnosis of non-motor symptoms and an objective monitoring of progression. More studies are needed to clarify the role of functional connectivity and network analyses.

BACKGROUND Children with acute lymphoblastic leukemia (ALL) often suffer from toxicity of chemotherapeutic drugs such as Methotrexate (MTX). Previously, we reported that 20% of patients receiving high-dose MTX developed oral mucositis. MTX inhibits folate metabolism, which is essential for DNA methylation. We hypothesize that MTX inhibits DNA methylation, which results into adverse effects. We studied DNA methylation markers during high-dose methotrexate treatment in pediatric acute lymphoblastic leukemia (ALL) in relation to developing oral mucositis. MATERIALS & METHODS S-Adenosyl-Methionine (SAM) and S-Adenosyl-Homocysteine (SAH) levels and LINE1 DNA methylation were measured prospectively before and after high-dose methotrexate (HD-MTX 4 x 5g/m2) therapy in 82 children with ALL. Methotrexate-induced oral mucositis was registered prospectively. Oral mucositis (grade ≥ 3 National Cancer Institute Criteria) was used as clinical endpoint. RESULTS SAM levels decreased significantly during methotrexate therapy (-16.1 nmol/L (-144.0 - +46.0), p<0.001), while SAH levels and the SAM:SAH ratio did not change significantly. LINE1 DNA methylation (+1.4% (-1.1 - +6.5), p<0.001) increased during therapy. SAM and SAH levels were not correlated to LINE1 DNA methylation status. No association was found between DNA methylation markers with developing oral mucositis. CONCLUSIONS This was the first study that assessed DNA methylation in relation to MTX-induced oral mucositis in children with ALL. Although global methylation markers did change during methotrexate therapy, methylation status was not associated with developing oral mucositis.

Objective: To identify a plasma metabolomic biomarker signature for migraine. Methods: Plasma samples from 8 Dutch cohorts (n = 10,153: 2,800 migraine patients and 7,353 controls) were profiled on a 1H-NMR-based metabolomics platform, to quantify 146 individual metabolites (e.g., lipids, fatty acids, and lipoproteins) and 79 metabolite ratios. Metabolite measures associated with migraine were obtained after single-metabolite logistic regression combined with a random-effects meta-analysis performed in a nonstratified and sex-stratified manner. Next, a global test analysis was performed to identify sets of related metabolites associated with migraine. The Holm procedure was applied to control the family-wise error rate at 5% in single-metabolite and global test analyses. Results: Decreases in the level of apolipoprotein A1 (β −0.10; 95% confidence interval [CI] −0.16, −0.05; adjusted p = 0.029) and free cholesterol to total lipid ratio present in small high-density lipoprotein subspecies (HDL) (β −0.10; 95% CI −0.15, −0.05; adjusted p = 0.029) were associated with migraine status. In addition, only in male participants, a decreased level of omega-3 fatty acids (β −0.24; 95% CI −0.36, −0.12; adjusted p = 0.033) was associated with migraine. Global test analysis further supported that HDL traits (but not other lipoproteins) were associated with migraine status. Conclusions: Metabolic profiling of plasma yielded alterations in HDL metabolism in migraine patients and decreased omega-3 fatty acids only in male migraineurs.

Background. An unfavorable body composition is often present in chronic arthritis patients. This unfavorable composition is a loss of muscle mass, with a stable or increased (abdominal) fat mass. Since it is unknown when this unfavorable composition develops, we compared body composition in disease-modifying antirheumatic drugs (DMARD)-naive early arthritis patients with non-arthritis controls and explored the association, in early arthritis patients, with disease activity and traditional cardiovascular risk factors. Methods. 317 consecutive early arthritis patients (84% rheumatoid arthritis according to 2010 ACR/EULAR criteria) and 1268 age-/gender-/ethnicity-matched non-arthritis controls underwent a Dual-energy X-ray absorptiometry scan to assess fat percentage, fat mass index, fat mass distribution and appendicular lean (muscle) mass index. Additionally, disease activity, health assessment questionnaire (HAQ), acute phase proteins, lipid profile and blood pressure were evaluated. Results. Loss of muscle mass (corrected for age suspected muscle mass) was 4-5 times more common in early arthritis patients, with a significantly lower mean appendicular lean mass index (females 6% and males 7% lower, p<0.01). Patients had more fat distributed to the trunk (females p<0.01, males p=0.07) and females had a 4% higher mean fat mass index (p<0.01). An unfavorable body composition was associated with a higher blood pressure and an atherogenic lipid profile. There was no relationship with disease activity, HAQ or acute phase proteins. Conclusion. Loss of muscle mass is 4-5 times more common in early arthritis patients, and is in early arthritis patients associated with a higher blood pressure and an atherogenic lipid profile. Therefore, cardiovascular risk is already increased at the clinical onset of arthritis making cardiovascular risk management necessary in early arthritis patients.