Introduction Suicide rates and the proportion of alcohol-involved suicides rose during the 2008–2009 recession. Associations between county-level poverty, foreclosures, and unemployment and suicide ...rates and proportion of alcohol-involved suicides were investigated. Methods In 2015, National Violent Death Reporting System data from 16 states in 2005–2011 were utilized to calculate suicide rates and a measure of alcohol involvement in suicides at the county level. Panel models with year and state fixed effects included county-level measures of unemployment, foreclosure, and poverty rates. Results Poverty rates were strongly associated with suicide rates for both genders and all age groups, were positively associated with alcohol involvement in suicides for men aged 45–64 years, and negatively associated for men aged 20–44 years. Foreclosure rates were negatively associated with suicide rates for women and those aged ≥65 years but positively related for those aged 45–64 years. Unemployment rate effects on suicide rates were mediated by poverty rates in all groups. Conclusions Population risk of suicide was most clearly associated with county-level poverty rates, indicating that programs addressing area poverty should be targeted for reducing suicide risk. Poverty rates were also associated with increased alcohol involvement for men aged 45–64 years, indicating a role for alcohol in suicide for this working-aged group. However, negative associations between economic indicators and alcohol involvement were found for four groups, suggesting that non-economic factors or more general economic effects not captured by these indicators may have played a larger role in alcohol-related suicide increases.
BACKGROUND:Cognitive impairment is common in later life. Identifying potential modifiable risk factors for cognitive decline may ameliorate the burden of disease. Cross-sectional studies show an ...association between blood pressure (BP) variability and impaired cognitive function in patients with hypertension and/or dementia. However, research examining the association between BP variability and cognitive function in the general older population is scarce.
OBJECTIVE:In this study, we examined the association between BP variability and cognitive function over 5-year follow-up in an unselected community-dwelling cohort.
METHODS:Ambulatory BP monitoring was performed in 353 community-dwelling people aged at least 65 years. Cognitive assessment, using the Mini Mental State Examination (MMSE) and Cambridge Cognitive Examination (CAMCOG), was performed at baseline and at 5-year follow-up. BP variability was calculated using the coefficient of variation. Cognitive change over 5 years was defined as baseline score minus follow-up score.
RESULTS:Increased daytime systolic variability was associated with poorer performance on the CAMCOG total score and subscores. Daytime diastolic variability was associated with poorer performance on total CAMCOG, CAMCOG executive score, and MMSE. These findings were independent of demographic and cardiovascular risk factors. Daytime systolic variability was also independently associated with greater decline in total CAMCOG and MMSE scores over 5-year follow-up.
CONCLUSION:Increased BP variability is associated with poorer cognitive function in older people and may represent a novel modifiable risk factor for cognitive decline.
A new electron-deficient chiral triazolium salt has been shown to catalyze the formation of quaternary stereocenters by an asymmetric intramolecular Stetter reaction. Pentafluorophenyl substitution ...on an aminoindanol-derived catalyst affords tertiary ether, thioether, and quaternary stereocenters in typically greater than 90% ee and very good chemical yield. Aromatic and aliphatic aldehydes are equally competent substrates for this reaction. The reaction proceeds at room temperature under mild conditions to provide quaternary stereocenters with functional group relationships that are particularly difficult to access by other methods.
In the multimodal neuroimaging framework, data on a single subject are collected from inherently different sources such as functional MRI, structural MRI, behavioral and/or phenotypic information. ...The information each source provides is not independent; a subset of features from each modality maps to one or more common latent dimensions, which can be interpreted using generative models. These latent dimensions, or “topics,” provide a sparse summary of the generative process behind the features for each individual. Topic modeling, an unsupervised generative model, has been used to map seemingly disparate features to a common domain. We use Non-Negative Matrix Factorization (NMF) to infer the latent structure of multimodal ADHD data containing fMRI, MRI, phenotypic and behavioral measurements. We compare four different NMF algorithms and find that the sparsest decomposition is also the most differentiating between ADHD and healthy patients. We identify dimensions that map to interpretable, recognizable dimensions such as motion, default mode network activity, and other such features of the input data. For example, structural and functional graph theory features related to default mode subnetworks clustered with the ADHD-Inattentive diagnosis. Structural measurements of the default mode network (DMN) regions such as the posterior cingulate, precuneus, and parahippocampal regions were all related to the ADHD-Inattentive diagnosis. Ventral DMN subnetworks may have more functional connections in ADHD-I, while dorsal DMN may have less. ADHD topics are dependent upon diagnostic site, suggesting diagnostic differences across geographic locations. We assess our findings in light of the ADHD-200 classification competition, and contrast our unsupervised, nominated topics with previously published supervised learning methods. Finally, we demonstrate the validity of these latent variables as biomarkers by using them for classification of ADHD in 730 patients. Cumulatively, this manuscript addresses how multimodal data in ADHD can be interpreted by latent dimensions.
•We identify latent dimensions (topics) in multimodal ADHD (fMRI, MRI, phenotypic).•We compare four different Non-negative Matrix Factoriation (NMF) algorithms.•The sparsest NMF algorithms discriminates best between ADHD and healthy subjects.•“Site” nominated within “topics” suggests ADHD diagnosis may differ by location.•One topic suggests differential changes in the default-mode subnetwork for ADHD.
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•We extracted features from electronic health records (EHR) to predict diagnosed type 2 diabetes.•We predicted a patient’s diabetes diagnosis using 9948 clinical-quality electronic ...health records.•EHR phenotyping out-performed conventional screening methods with limited features.•EHR phenotyping had superior overall predictive accuracy, using AUC measure of ROC curves.•EHR phenotypes also predicted better whether a new patient had type 2 diabetes.
An estimated 25% of type two diabetes mellitus (DM2) patients in the United States are undiagnosed due to inadequate screening, because it is prohibitive to administer laboratory tests to everyone. We assess whether electronic health record (EHR) phenotyping could improve DM2 screening compared to conventional models, even when records are incomplete and not recorded systematically across patients and practice locations, as is typically seen in practice.
In this cross-sectional, retrospective study, EHR data from 9948 US patients were used to develop a pre-screening tool to predict current DM2, using multivariate logistic regression and a random-forests probabilistic model for out-of-sample validation. We compared (1) a full EHR model containing commonly prescribed medications, diagnoses (as ICD9 categories), and conventional predictors, (2) a restricted EHR DX model which excluded medications, and (3) a conventional model containing basic predictors and their interactions (BMI, age, sex, smoking status, hypertension).
Using a patient’s full EHR or restricted EHR was superior to using basic covariates alone for detecting individuals with diabetes (hierarchical X2 test, p<0.001). Migraines, depot medroxyprogesterone acetate, and cardiac dysrhythmias were associated negatively with DM2, while sexual and gender identity disorder diagnosis, viral and chlamydial infections, and herpes zoster were associated positively. Adding EHR phenotypes improved classification; the AUC for the full EHR Model, EHR DX model, and conventional model using logistic regression, were 84.9%, 83.2%, and 75.0% respectively. For random forest machine learning out-of-sample prediction, accuracy also was improved when using EHR phenotypes; the AUC values were 81.3%, 79.6%, and 74.8%, respectively. Improved AUCs reflect better performance for most thresholds that balance sensitivity and specificity.
EHR phenotyping resulted in markedly superior detection of DM2, even in the face of missing and unsystematically recorded data, based on the ROC curves. EHR phenotypes could more efficiently identify which patients do require, and don’t require, further laboratory screening. When applied to the current number of undiagnosed individuals in the United States, we predict that incorporating EHR phenotype screening would identify an additional 400,000 patients with active, untreated diabetes compared to the conventional pre-screening models.
The most critical question for climate research is no longer about the problem, but about how to facilitate the transformative changes necessary to avoid catastrophic climate-induced change. ...Addressing this question, however, will require massive upscaling of research that can rapidly enhance learning about transformations. Ten essentials for guiding action-oriented transformation and energy research are therefore presented, framed in relation to second-order science. They include: (1) Focus on transformations to low-carbon, resilient living; (2) Focus on solution processes; (3) Focus on ‘how to’ practical knowledge; (4) Approach research as occurring from within the system being intervened; (5) Work with normative aspects; (6) Seek to transcend current thinking; (7) Take a multi-faceted approach to understand and shape change; (8) Acknowledge the value of alternative roles of researchers; (9) Encourage second-order experimentation; and (10) Be reflexive. Joint application of the essentials would create highly adaptive, reflexive, collaborative and impact-oriented research able to enhance capacity to respond to the climate challenge. At present, however, the practice of such approaches is limited and constrained by dominance of other approaches. For wider transformations to low carbon living and energy systems to occur, transformations will therefore also be needed in the way in which knowledge is produced and used.
An α-methyl, non-natural amino acid (NNAA) building block equipped with an alkyl halide tail that could be readily transformed into an organozinc was prepared. This single organometallic was ...cross-coupled to an array of heterocyclic electrophiles using the Pd-PEPPSI-IHeptCl catalyst to produce a wide selection of optically pure α-methyl NNAAs. With these in hand, non-natural peptides are being produced for evaluation in a variety of therapeutic areas in drug discovery.
Solid potential Kerr, Mark S; Cole, Kevin P
Nature chemistry,
05/2021, Letnik:
13, Številka:
5
Journal Article
Recenzirano
Small-molecule drug discovery and development is limited by the ability of chemists to readily synthesize and purify new compounds with suitable chemical diversity. Now, a new twist on solid-phase ...chemical synthesis has enabled rapid and simplified synthesis of pharmaceutically relevant small molecules.
The promising utility of triazolyl N-heterocyclic carbene catalysts in umpolung aldehyde chemistry requires a straightforward reliable synthesis from readily available materials. Herein, we describe ...the synthesis of a variety of triazolyl N-heterocyclic carbene precursors. The reactions commence from commercially available amino acids and proceed in 44−68% overall yields. The N-heterocyclic salts are air-stable crystalline solids that can be stored with no special precaution and can generate the active catalyst when treated with an appropriate base.
A family of chiral triazolium salts has been developed for inducing the asymmetric intramolecular Stetter reaction. The use of an aminoindanol-derived catalyst affords optimal results, with the ...product keto esters formed in 82−97% ee and very good chemical yield. Aromatic and aliphatic aldehydes are equally competent substrates for this reaction. The reaction conditions are reasonably mild and allow the isolation of the newly formed stereocenter without epimerization, although the presumed carbenic intermediates are strong bases.
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