Novel chemistry of fluorinated carbanions

The research described within this thesis may be divided into four main subject areas: I. The amine fluoride TDAE(^2+)2F- (10) has been used as a useful soluble source of fluoride ion in both C-F and C-C bond forming reactions. Methods of synthesis of (10) are described. This work Jed to the observation that TDAE (8), and other amines, could be used as agents for the in situ generation of fluoride, by nucleophilic attack on fluoro-alkenes. Its use allows the effective isolation of the products of dimerisation, co-dimerisation and the perfluoroalkylation reactions for the first time. II. Synthesis and reactions of perfluoro-3, 4-dimethylhexa-2, 4-diene (14) are described. Particular attention is paid to reactions with oxygen and carbon centred nucleophiles. The novel tetrakis(2,3,4,5-trifluoromethyl)benzodioxocin ring system (54) so produced was extensively studied. III. The synthetically useful cyclic diene hexakis(trifluoromethyl)cyclopentadiene (96) has been synthesised from diene (14), by fluoride ion induced reaction with pentafluoropropene (97). This diene can be reduced to the exceptionally stable pentakis(trifluoromethyl)cyclopentadienide anion (84) upon reaction with a range of alkali metal and tetralkylammonium iodides. The mechanism of this reaction appears to be a radical one and, indeed, electrochemical reduction is rapid. The intrinsic stability of (84) is borne out by the fact that concentrated sulphuric acid is required to synthesis its derived acid (109). IV. Diene (96) reacts with a variety of transition metal powders to give corresponding pentakis(trifluoromethyl)cyclopentadienide metal salts. The role of acetonitrile as a solvent in the reaction appears to be crucial to the formation and stabilisation of these species. The salt produced by reaction of (96) with copper powder, tetrakis(acetonitrile)copper (I) pentakis(trifluoromethyl)cyclopentadienide (118), is remarkably stable and an x-ray crystal structure was obtained

Dementia Prevalence Estimates in Sub-Saharan Africa: Comparison of two Diagnostic Criteria.

We have previously reported the prevalence of dementia in older adults living in the rural Hai district of Tanzania according to the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) criteria. The aim of this study was to compare prevalence rates using the DSM-IV criteria with those obtained using the 10/66 diagnostic criteria, which is specifically designed for use in low- and middle-income countries. In phase I, 1,198 people aged 70 and older were screened for dementia. A stratified sample of 296 was then clinically assessed for dementia according to the DSM-IV criteria. In addition, data were collected according to the protocol of the 10/66 Dementia Research Group, which allowed a separate diagnosis of dementia according to these criteria to be established. The age-standardised prevalence of clinical DSM-IV dementia was 6.4% (95% confidence interval [CI] 4.9-7.9%) and of '10/66 dementia' was 21.6% (95% CI 17.5-25.7%). Education was a significant predictor of '10/66 dementia', but not of DSM-IV dementia. There are large discrepancies in dementia prevalence rates depending on which diagnostic system is used. In rural sub-Saharan Africa, it is not clear whether the association between education and dementia using the 10/66 criteria is a genuine effect or the result of an educational bias within the diagnostic instrument. Despite its possible flaws, the DSM-IV criteria represent an international standard for dementia diagnosis. The 10/66 diagnostic criteria may be more appropriate when identification of early and mild cognitive impairment is required

Improving the predictions of computational models of convection-enhanced drug delivery by accounting for diffusion non-gaussianity

Convection-enhanced delivery (CED) is an innovative method of drug delivery to the human brain, that bypasses the blood-brain barrier by injecting the drug directly into the brain. CED aims to target pathological tissue for central nervous system conditions such as Parkinson's and Huntington's disease, epilepsy, brain tumors, and ischemic stroke. Computational fluid dynamics models have been constructed to predict the drug distribution in CED, allowing clinicians advance planning of the procedure. These models require patient-specific information about the microstructure of the brain tissue, which can be collected non-invasively using magnetic resonance imaging (MRI) pre-infusion. Existing models employ the diffusion tensor, which represents Gaussian diffusion in brain tissue, to provide predictions for the drug concentration. However, those predictions are not always in agreement with experimental observations. In this work we present a novel computational fluid dynamics model for CED that does not use the diffusion tensor, but rather the diffusion probability that is experimentally measured through diffusion MRI, at an individual-participant level. Our model takes into account effects of the brain microstructure on the motion of drug molecules not taken into account in previous approaches, namely the restriction and hindrance that those molecules experience when moving in the brain tissue, and can improve the drug concentration predictions. The duration of the associated MRI protocol is 19 min, and therefore feasible for clinical populations. We first prove theoretically that the two models predict different drug distributions. Then, using in vivo high-resolution diffusion MRI data from a healthy participant, we derive and compare predictions using both models, in order to identify the impact of including the effects of restriction and hindrance. Including those effects results in different drug distributions, and the observed differences exhibit statistically significant correlations with measures of diffusion non-Gaussianity in brain tissue. The differences are more pronounced for infusion in white-matter areas of the brain. Using experimental results from the literature along with our simulation results, we show that the inclusion of the effects of diffusion non-Gaussianity in models of CED is necessary, if reliable predictions that can be used in the clinic are to be generated by CED models

Brief of Scholars of the History and Original Meaning of the Fourth Amendment as Amici Curiae in Support of Petitioner, Carpenter v. United States, No. 16-402 (U.S. Aug. 14, 2017)

Obtaining and examining cell site location records to find a person is a “search” in any normal sense of the word — a search of documents and a search for a person and her personal effects. It is therefore a “search” within the meaning of the Fourth Amendment in that it constitutes “examining,” “exploring,” “looking through,” “inquiring,” “seeking,” or “trying to find.” Nothing about the text of the Fourth Amendment, or the historical backdrop against which it was adopted, suggests that “search” should be construed more narrowly as, for example, intrusions upon subjectively manifested expectations of privacy that society is prepared to recognize as reasonable.Entrusting government agents with unfettered discretion to conduct searches using cell site location information undermines Fourth Amendment rights. The Amendment guarantees “[t]he right of the people to be secure in their persons, houses, papers, and effects, against unreasonable searches.” The Framers chose that language deliberately. It reflected the insecurity they suffered at the hands of “writs of assistance,” a form of general warrant that granted state agents broad discretion to search wherever they pleased. Such arbitrary power was “unreasonable” to the Framers, being “against the reason of the common law,” and it was intolerable because of its oppressive impact on “the people” as a whole. As emphasized in one of the seminal English cases that inspired the Amendment, this kind of general power to search was “totally subversive of the liberty of the subject.” James Otis’s famous speech denouncing a colonial writ of assistance similarly condemned those writs as “the worst instrument of arbitrary power,” placing “the liberty of every man in the hands of every petty officer.” Thus, although those who drafted and ratified the Fourth Amendment could not have anticipated cellphone technology, they would have recognized the dangers inherent in any state claim of unlimited authority to conduct searches for evidence of criminal activity. Cell site location information provides insight into where we go and what we do. Because this information is constantly generated and can be retrieved by the government long after the activities it memorializes have taken place, unfettered government access to cell site location information raises the specter of general searches and undermines the security of “the people.

Improving the Predictions of Computational Models of Convection-Enhanced Drug Delivery by Accounting for Diffusion Non-gaussianity

Convection-enhanced delivery (CED) is an innovative method of drug delivery to the human brain, that bypasses the blood-brain barrier by injecting the drug directly into the brain. CED aims to target pathological tissue for central nervous system conditions such as Parkinson's and Huntington's disease, epilepsy, brain tumors, and ischemic stroke. Computational fluid dynamics models have been constructed to predict the drug distribution in CED, allowing clinicians advance planning of the procedure. These models require patient-specific information about the microstructure of the brain tissue, which can be collected non-invasively using magnetic resonance imaging (MRI) pre-infusion. Existing models employ the diffusion tensor, which represents Gaussian diffusion in brain tissue, to provide predictions for the drug concentration. However, those predictions are not always in agreement with experimental observations. In this work we present a novel computational fluid dynamics model for CED that does not use the diffusion tensor, but rather the diffusion probability that is experimentally measured through diffusion MRI, at an individual-participant level. Our model takes into account effects of the brain microstructure on the motion of drug molecules not taken into account in previous approaches, namely the restriction and hindrance that those molecules experience when moving in the brain tissue, and can improve the drug concentration predictions. The duration of the associated MRI protocol is 19 min, and therefore feasible for clinical populations. We first prove theoretically that the two models predict different drug distributions. Then, using in vivo high-resolution diffusion MRI data from a healthy participant, we derive and compare predictions using both models, in order to identify the impact of including the effects of restriction and hindrance. Including those effects results in different drug distributions, and the observed differences exhibit statistically significant correlations with measures of diffusion non-Gaussianity in brain tissue. The differences are more pronounced for infusion in white-matter areas of the brain. Using experimental results from the literature along with our simulation results, we show that the inclusion of the effects of diffusion non-Gaussianity in models of CED is necessary, if reliable predictions that can be used in the clinic are to be generated by CED models

Balancing Prediction and Sensory Input in Speech Comprehension: The Spatiotemporal Dynamics of Word Recognition in Context.

Spoken word recognition in context is remarkably fast and accurate, with recognition times of ∼200 ms, typically well before the end of the word. The neurocomputational mechanisms underlying these contextual effects are still poorly understood. This study combines source-localized electroencephalographic and magnetoencephalographic (EMEG) measures of real-time brain activity with multivariate representational similarity analysis to determine directly the timing and computational content of the processes evoked as spoken words are heard in context, and to evaluate the respective roles of bottom-up and predictive processing mechanisms in the integration of sensory and contextual constraints. Male and female human participants heard simple (modifier-noun) English phrases that varied in the degree of semantic constraint that the modifier (W1) exerted on the noun (W2), as in pairs, such as "yellow banana." We used gating tasks to generate estimates of the probabilistic predictions generated by these constraints as well as measures of their interaction with the bottom-up perceptual input for W2. Representation similarity analysis models of these measures were tested against electroencephalographic and magnetoencephalographic brain data across a bilateral fronto-temporo-parietal language network. Consistent with probabilistic predictive processing accounts, we found early activation of semantic constraints in frontal cortex (LBA45) as W1 was heard. The effects of these constraints (at 100 ms after W2 onset in left middle temporal gyrus and at 140 ms in left Heschl's gyrus) were only detectable, however, after the initial phonemes of W2 had been heard. Within an overall predictive processing framework, bottom-up sensory inputs are still required to achieve early and robust spoken word recognition in context.SIGNIFICANCE STATEMENT Human listeners recognize spoken words in natural speech contexts with remarkable speed and accuracy, often identifying a word well before all of it has been heard. In this study, we investigate the brain systems that support this important capacity, using neuroimaging techniques that can track real-time brain activity during speech comprehension. This makes it possible to locate the brain areas that generate predictions about upcoming words and to show how these expectations are integrated with the evidence provided by the speech being heard. We use the timing and localization of these effects to provide the most specific account to date of how the brain achieves an optimal balance between prediction and sensory input in the interpretation of spoken language