On the Development of Catalytic Carba-6π Electrocyclizations

Hexatriene substrates substituted in the 2-position with carbonyl groups were studied in the context of catalytic 6π electrocyclizations. The nature of the carbonyl group and the substitution pattern on the hexatriene have significant effects on the ability of these substrates to succumb to catalysis. A novel 2-formyl hexatriene dimerization was observed. The first example of a catalytic asymmetric carba-6π electrocyclization is reported along with the discovery of an unusual kinetic resolution via a catalytic photochemical electrocyclic ring-opening

Sources of Klebsiella and Raoultella species on dairy farms: Be careful where you walk

Klebsiella spp. are a common cause of mastitis, milk loss, and culling on dairy farms. Control of Klebsiella mastitis is largely based on prevention of exposure of the udder to the pathogen. To identify critical control points for mastitis prevention, potential Klebsiella sources and transmission cycles in the farm environment were investigated, including oro-fecal transmission, transmission via the indoor environment, and transmission via the outdoor environment. A total of 305 samples was collected from 3 dairy farms in upstate New York in the summer of 2007, and included soil, feed crops, feed, water, rumen content, feces, bedding, and manure from alleyways and holding pens. Klebsiella spp. were detected in 100% of rumen samples, 89% of water samples, and approximately 64% of soil, feces, bedding, alleyway, and holding pen samples. Detection of Klebsiella spp. in feed crops and feed was less common. Genotypic identification of species using rpoB sequence data showed that Klebsiella pneumoniae was the most common species in rumen content, feces, and alleyways, whereas Klebsiella oxytoca, Klebsiella variicola, and Raoultella planticola were the most frequent species among isolates from soil and feed crops. Random amplified polymorphic DNA-based strain typing showed heterogeneity of Klebsiella spp. in rumen content and feces, with a median of 4 strains per 5 isolates. Observational and bacteriological data support the existence of an oro-fecal transmission cycle, which is primarily maintained through direct contact with fecal contamination or through ingestion of contaminated drinking water. Fecal shedding of Klebsiella spp. contributes to pathogen loads in the environment, including bedding, alleyways, and holding pens. Hygiene of alleyways and holding pens is an important component of Klebsiella control on dairy farms

Fish movement patterns in Virgin Islands National Park, Virgin Islands Coral Reef National Monument and adjacent waters

NOAA’s National Centers for Coastal Ocean Science (NCCOS)-Center for Coastal Monitoring and Assessment’s (CCMA) Biogeography Branch, National Park Service (NPS), US Geological Survey, and the University of Hawaii used acoustic telemetry to quantify spatial patterns and habitat affinities of reef fishes around the island of St. John, US Virgin Islands. The objective of the study was to define the movements of reef fishes among habitats within and between the Virgin Islands Coral Reef National Monument (VICRNM), the Virgin Islands National Park (VIIS), and Territorial waters surrounding St. John. In order to better understand species’ habitat utilization patterns among management regimes, we deployed an array of hydroacoustic receivers and acoustically tagged reef fishes. Thirty six receivers were deployed in shallow near-shore bays and across the shelf to depths of approximately 30 m. One hundred eighty four individual fishes were tagged representing 19 species from 10 different families with VEMCO V9-2L-R64K transmitters. The array provides fish movement information at fine (e.g., day-night and 100s meters within a bay) to broad spatial and temporal scales (multiple years and 1000s meters across the shelf). The long term multi-year tracking project provides direct evidence of connectivity across habitat types in the seascape and among management units. An important finding for management was that a number of individuals moved among management units (VICRNM, VINP, Territorial waters) and several snapper moved from near-shore protected areas to offshore shelf-edge spawning aggregations. However, most individuals spent the majority of their time with VIIS and VICRNM, with only a few wide-ranging species moving outside the management units. Five species of snappers (Lutjanidae) accounted for 31% of all individuals tagged, followed by three species of grunts (Haemulidae) accounting for an additional 23% of the total. No other family had more than a single species represented in the study. Bluestripe grunt (Haemulon sciurus) comprised 22% of all individuals tagged, followed by lane snappers (Lutjanus synagris) at 21%, bar jack (Carangoides ruber) at 11%, and saucereye porgy (Calamus calamus) at 10%. The largest individual tagged was a 70 cm TL nurse shark (Ginglymostoma cirratum), followed by a 65 cm mutton snapper (Lutjanus analis), a 47 cm bar jack, and a 41 cm dog snapper (Lutjanus jocu). The smallest individuals tagged were a 19 cm blue tang (Acanthurus coeruleus) and a 19.2 cm doctorfish (Acanthurus chirurgus). Of the 40 bluestriped grunt acoustically tagged, 73% were detected on the receiver array. The average days at large (DAL) was 249 (just over 8 months), with one individual detected for 930 days (over two and a half years). Lane snapper were the next most abundant species tagged (N = 38) with 89% detected on the array. The average days at large (DAL) was 221 with one individual detected for 351 days. Seventy-one percent of the bar jacks (N = 21) were detected on the array with the average DALs at 47 days. All of the mutton snapper (N = 12) were detected on the array with an average DAL of 273 and the longest at 784. The average maximum distance travelled (MDT) was ca. 2 km with large variations among species. Grunts, snappers, jacks, and porgies showed the greatest movements. Among all individuals across species, there was a positive and significant correlation between size of individuals and MDT and between DAL and MDT

Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.Peer reviewe

Rare coding variants in PLCG2, ABI3, and TREM2 implicate microglial-mediated innate immunity in Alzheimer's disease

We identified rare coding variants associated with Alzheimer’s disease (AD) in a 3-stage case-control study of 85,133 subjects. In stage 1, 34,174 samples were genotyped using a whole-exome microarray. In stage 2, we tested associated variants (P<1×10-4) in 35,962 independent samples using de novo genotyping and imputed genotypes. In stage 3, an additional 14,997 samples were used to test the most significant stage 2 associations (P<5×10-8) using imputed genotypes. We observed 3 novel genome-wide significant (GWS) AD associated non-synonymous variants; a protective variant in PLCG2 (rs72824905/p.P522R, P=5.38×10-10, OR=0.68, MAFcases=0.0059, MAFcontrols=0.0093), a risk variant in ABI3 (rs616338/p.S209F, P=4.56×10-10, OR=1.43, MAFcases=0.011, MAFcontrols=0.008), and a novel GWS variant in TREM2 (rs143332484/p.R62H, P=1.55×10-14, OR=1.67, MAFcases=0.0143, MAFcontrols=0.0089), a known AD susceptibility gene. These protein-coding changes are in genes highly expressed in microglia and highlight an immune-related protein-protein interaction network enriched for previously identified AD risk genes. These genetic findings provide additional evidence that the microglia-mediated innate immune response contributes directly to AD development

Temporal order of clinical and biomarker changes in familial frontotemporal dementia

Data availability: The datasets analyzed for the current study reflect collaborative efforts of two research consortia: ALLFTD and GENFI. Each consortium provides clinical data access based on established policies for data use: processes for request are available for review at allftd.org/data for ALLFTD data and by emailing [email protected]. Certain data elements from both consortia (for example raw MRI images) may be restricted due to the potential for identifiability in the context of the sensitive nature of the genetic data. The deidentified combined dataset will be available for request through the FTD Prevention Initiative in 2023 (https://www.thefpi.org/).Code availability: Custom R code is available at https://doi.org/10.5281/zenodo.6687486.Copyright © The Author(s). Unlike familial Alzheimer’s disease, we have been unable to accurately predict symptom onset in presymptomatic familial frontotemporal dementia (f-FTD) mutation carriers, which is a major hurdle to designing disease prevention trials. We developed multimodal models for f-FTD disease progression and estimated clinical trial sample sizes in C9orf72, GRN and MAPT mutation carriers. Models included longitudinal clinical and neuropsychological scores, regional brain volumes and plasma neurofilament light chain (NfL) in 796 carriers and 412 noncarrier controls. We found that the temporal ordering of clinical and biomarker progression differed by genotype. In prevention-trial simulations using model-based patient selection, atrophy and NfL were the best endpoints, whereas clinical measures were potential endpoints in early symptomatic trials. f-FTD prevention trials are feasible but will likely require global recruitment efforts. These disease progression models will facilitate the planning of f-FTD clinical trials, including the selection of optimal endpoints and enrollment criteria to maximize power to detect treatment effects.Data collection and dissemination of the data presented in this paper were supported by the ALLFTD Consortium (U19: AG063911, funded by the National Institute on Aging and the National Institute of Neurological Diseases and Stroke) and the former ARTFL and LEFFTDS Consortia (ARTFL: U54 NS092089, funded by the National Institute of Neurological Diseases and Stroke and National Center for Advancing Translational Sciences; LEFFTDS: U01 AG045390, funded by the National Institute on Aging and the National Institute of Neurological Diseases and Stroke). The manuscript was reviewed by the ALLFTD Executive Committee for scientific content. The authors acknowledge the invaluable contributions of the study participants and families as well as the assistance of the support staffs at each of the participating sites. This work is also supported by the Association for Frontotemporal Degeneration (including the FTD Biomarkers Initiative), the Bluefield Project to Cure FTD, Larry L. Hillblom Foundation (2018-A-025-FEL (A.M.S.)), the National Institutes of Health (AG038791 (A.L.B.), AG032306 (H.J.R.), AG016976 (W.K.), AG062677 (Ron C. Peterson), AG019724 (B.L.M.), AG058233 (Suzee E. Lee), AG072122 (Walter Kukull), P30 AG062422 (B.L.M.), K12 HD001459 (N.G.), K23AG061253 (A.M.S.), AG062422 (RCP), K24AG045333 (H.J.R.)) and the Rainwater Charitable Foundation. Samples from the National Centralized Repository for Alzheimer Disease and Related Dementias (NCRAD), which receives government support under a cooperative agreement grant (U24 AG021886 (T.F.)) awarded by the National Institute on Aging (NIA), were used in this study. This work was also supported by Medical Research Council UK GENFI grant MR/M023664/1 (J.D.R.), the Bluefield Project, the National Institute for Health Research including awards to Cambridge and UCL Biomedical Research Centres and a JPND GENFI-PROX grant (2019–02248). Several authors of this publication are members of the European Reference Network for Rare Neurologic Diseases, project 739510. J.D.R. and L.L.R. are also supported by the National Institute for Health and Care Research (NIHR) UCL/H Biomedical Research Centre, the Leonard Wolfson Experimental Neurology Centre Clinical Research Facility and the UK Dementia Research Institute, which receives its funding from UK DRI Ltd, funded by the UK Medical Research Council, Alzheimer’s Society and Alzheimer’s Research UK. J.D.R. is also supported by the Miriam Marks Brain Research UK Senior Fellowship and has received funding from an MRC Clinician Scientist Fellowship (MR/M008525/1) and the NIHR Rare Disease Translational Research Collaboration (BRC149/NS/MH). M.B. is supported by a Fellowship award from the Alzheimer’s Society, UK (AS-JF-19a-004-517). RC and C.G. are supported by a Frontotemporal Dementia Research Studentships in Memory of David Blechner funded through The National Brain Appeal (RCN 290173). J.B.R. is supported by NIHR Cambridge Biomedical Research Centre (BRC-1215-20014; the views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care), the Wellcome Trust (220258), the Cambridge Centre for Parkinson-plus and the Medical Research Council (SUAG/092 G116768); I.L.B. is supported by ANR-PRTS PREV-DemAls, PHRC PREDICT-PGRN, and several authors of this publication are members of the European Reference Network for Rare Neurological Diseases (project 739510). J.L. is funded by the Deutsche Forschungsgemeinschaft (German Research Foundation) under Germany’s Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy – ID 390857198). R.S.-V. was funded at the Hospital Clinic de Barcelona by Instituto de Salud Carlos III, Spain (grant code PI20/00448 to RSV) and Fundació Marató TV3, Spain (grant code 20143810 to R.S.-V.). M.M. was, in part, funded by the UK Medical Research Council, the Italian Ministry of Health and the Canadian Institutes of Health Research as part of a Centres of Excellence in Neurodegeneration grant, by Canadian Institutes of Health Research operating grants (MOP- 371851 and PJT-175242) and by funding from the Weston Brain Institute. R.L. is supported by the Canadian Institutes of Health Research and the Chaire de Recherche sur les Aphasies Primaires Progressives Fondation Famille Lemaire. C.G. is supported by the Swedish Frontotemporal Dementia Initiative Schörling Foundation, Swedish Research Council, JPND Prefrontals, 2015–02926,2018–02754, Swedish Alzheimer Foundation, Swedish Brain Foundation, Karolinska Institutet Doctoral Funding, KI Strat-Neuro, Swedish Dementia Foundation, and Stockholm County Council ALF/Region Stockholm. J.L. is supported by Germany’s Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (German Research Foundation, EXC 2145 Synergy 390857198). The Dementia Research Centre is supported by Alzheimer’s Research UK, Alzheimer’s Society, Brain Research UK, and The Wolfson Foundation. This work was supported by the National Institute for Health Research UCL/H Biomedical Research Centre, the Leonard Wolfson Experimental Neurology Centre Clinical Research Facility and the UK Dementia Research Institute, which receives its funding from UK DRI Ltd, funded by the UK Medical Research Council, Alzheimer’s Society, and Alzheimer’s Research UK

The impact of PICALM genetic variations on reserve capacity of posterior cingulate in AD continuum

Phosphatidylinositolbinding clathrin assembly protein (PICALM) gene is one novel genetic player associated with late-onset Alzheimer’s disease (LOAD), based on recent genome wide association studies (GWAS). However, how it affects AD occurrence is still unknown. Brain reserve hypothesis highlights the tolerant capacities of brain as a passive means to fight against neurodegenerations. Here, we took the baseline volume and/or thickness of LOAD-associated brain regions as proxies of brain reserve capacities and investigated whether PICALM genetic variations can influence the baseline reserve capacities and the longitudinal atrophy rate of these specific regions using data from Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. In mixed population, we found that brain region significantly affected by PICALM genetic variations was majorly restricted to posterior cingulate. In sub-population analysis, we found that one PICALM variation (C allele of rs642949) was associated with larger baseline thickness of posterior cingulate in health. We found seven variations in health and two variations (rs543293 and rs592297) in individuals with mild cognitive impairment were associated with slower atrophy rate of posterior cingulate. Our study provided preliminary evidences supporting that PICALM variations render protections by facilitating reserve capacities of posterior cingulate in non-demented elderly

Early role of vascular dysregulation on late-onset Alzheimer's disease based on multifactorial data-driven analysis

Multifactorial mechanisms underlying late-onset Alzheimer's disease (LOAD) are poorly characterized from an integrative perspective. Here spatiotemporal alterations in brain amyloid-β deposition, metabolism, vascular, functional activity at rest, structural properties, cognitive integrity and peripheral proteins levels are characterized in relation to LOAD progression. We analyse over 7,700 brain images and tens of plasma and cerebrospinal fluid biomarkers from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Through a multifactorial data-driven analysis, we obtain dynamic LOAD–abnormality indices for all biomarkers, and a tentative temporal ordering of disease progression. Imaging results suggest that intra-brain vascular dysregulation is an early pathological event during disease development. Cognitive decline is noticeable from initial LOAD stages, suggesting early memory deficit associated with the primary disease factors. High abnormality levels are also observed for specific proteins associated with the vascular system's integrity. Although still subjected to the sensitivity of the algorithms and biomarkers employed, our results might contribute to the development of preventive therapeutic interventions

Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images

Neuroimaging measurements derived from magnetic resonance imaging provide important information required for detecting changes related to the progression of mild cognitive impairment (MCI). Cortical features and changes play a crucial role in revealing unique anatomical patterns of brain regions, and further differentiate MCI patients from normal states. Four cortical features, namely, gray matter volume, cortical thickness, surface area, and mean curvature, were explored for discriminative analysis among three groups including the stable MCI (sMCI), the converted MCI (cMCI), and the normal control (NC) groups. In this study, 158 subjects (72 NC, 46 sMCI, and 40 cMCI) were selected from the Alzheimer's Disease Neuroimaging Initiative. A sparse-constrained regression model based on the l2-1-norm was introduced to reduce the feature dimensionality and retrieve essential features for the discrimination of the three groups by using a support vector machine (SVM). An optimized strategy of feature addition based on the weight of each feature was adopted for the SVM classifier in order to achieve the best classification performance. The baseline cortical features combined with the longitudinal measurements for 2 years of follow-up data yielded prominent classification results. In particular, the cortical thickness produced a classification with 98.84% accuracy, 97.5% sensitivity, and 100% specificity for the sMCI–cMCI comparison; 92.37% accuracy, 84.78% sensitivity, and 97.22% specificity for the cMCI–NC comparison; and 93.75% accuracy, 92.5% sensitivity, and 94.44% specificity for the sMCI–NC comparison. The best performances obtained by the SVM classifier using the essential features were 5–40% more than those using all of the retained features. The feasibility of the cortical features for the recognition of anatomical patterns was certified; thus, the proposed method has the potential to improve the clinical diagnosis of sub-types of MCI and predict the risk of its conversion to Alzheimer's disease

Quantitative 18F-AV1451 Brain Tau PET Imaging in Cognitively Normal Older Adults, Mild Cognitive Impairment, and Alzheimer's Disease Patients

Recent developments of tau Positron Emission Tomography (PET) allows assessment of regional neurofibrillary tangles (NFTs) deposition in human brain. Among the tau PET molecular probes, 18F-AV1451 is characterized by high selectivity for pathologic tau aggregates over amyloid plaques, limited non-specific binding in white and gray matter, and confined off-target binding. The objectives of the study are (1) to quantitatively characterize regional brain tau deposition measured by 18F-AV1451 PET in cognitively normal older adults (CN), mild cognitive impairment (MCI), and AD participants; (2) to evaluate the correlations between cerebrospinal fluid (CSF) biomarkers or Mini-Mental State Examination (MMSE) and 18F-AV1451 PET standardized uptake value ratio (SUVR); and (3) to evaluate the partial volume effects on 18F-AV1451 brain uptake.Methods: The study included total 115 participants (CN = 49, MCI = 58, and AD = 8) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Preprocessed 18F-AV1451 PET images, structural MRIs, and demographic and clinical assessments were downloaded from the ADNI database. A reblurred Van Cittertiteration method was used for voxelwise partial volume correction (PVC) on PET images. Structural MRIs were used for PET spatial normalization and region of interest (ROI) definition in standard space. The parametric images of 18F-AV1451 SUVR relative to cerebellum were calculated. The ROI SUVR measurements from PVC and non-PVC SUVR images were compared. The correlation between ROI 18F-AV1451 SUVR and the measurements of MMSE, CSF total tau (t-tau), and phosphorylated tau (p-tau) were also assessed.Results:18F-AV1451 prominently specific binding was found in the amygdala, entorhinal cortex, parahippocampus, fusiform, posterior cingulate, temporal, parietal, and frontal brain regions. Most regional SUVRs showed significantly higher uptake of 18F-AV1451 in AD than MCI and CN participants. SUVRs of small regions like amygdala, entorhinal cortex and parahippocampus were statistically improved by PVC in all groups (p &lt; 0.01). Although there was an increasing tendency of 18F-AV-1451 SUVRs in MCI group compared with CN group, no significant difference of 18F-AV1451 deposition was found between CN and MCI brains with or without PVC (p &gt; 0.05). Declined MMSE score was observed with increasing 18F-AV1451 binding in amygdala, entorhinal cortex, parahippocampus, and fusiform. CSF p-tau was positively correlated with 18F-AV1451 deposition. PVC improved the results of 18F-AV-1451 tau deposition and correlation studies in small brain regions.Conclusion: The typical deposition of 18F-AV1451 tau PET imaging in AD brain was found in amygdala, entorhinal cortex, fusiform and parahippocampus, and these regions were strongly associated with cognitive impairment and CSF biomarkers. Although more deposition was observed in MCI group, the 18F-AV-1451 PET imaging could not differentiate the MCI patients from CN population. More tau deposition related to decreased MMSE score and increased level of CSF p-tau, especially in ROIs of amygdala, entorhinal cortex and parahippocampus. PVC did improve the results of tau deposition and correlation studies in small brain regions and suggest to be routinely used in 18F-AV1451 tau PET quantification