143 research outputs found
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Mineral Magnetic Characterization of High‐Latitude Sediments From Lake Levinson‐Lessing, Siberia
Levinson-Lessing Lake in northern Central Siberia is a sedimentary archive characterized by continuous, widely constant sedimentation at high rates (0.7 m ka−1 for >32 ka). This study provides the first evidence of the suitability of the lake′s sediments for paleomagnetic analyses using the 46-m-long core Co1401. Although the lowermost 8 m are disturbed, the upper 38 m of Co1401 provide the preconditions for an exceptional, high-resolution paleomagnetic record located within the tangent cylinder of the inner core. High-resolution analyses of magnetic susceptibility, anhysteretic remanent magnetization, isothermal remanent magnetization, and hysteresis parameters show largely uniform mineral magnetic properties. First-order reversal curves indicate magnetite particles in pseudo-single domain state are the main remanence carrier, supplemented by single-domain particles, originating likely from magnetotactic bacteria. Above 6.7 m, the bulk magnetic mineralogy is slightly harder than below and initial greigite formation occurs. However, the main remanence carriers are still of detrital origin
Catalytic Kinetic Resolution of a Dynamic Racemate: Highly Stereoselective β-Lactone Formation by N-Heterocyclic Carbene Catalysis
This study describes the combined experimental and computational elucidation of the mechanism and origins of stereoselectivities in the NHC-catalyzed dynamic kinetic resolution (DKR) of α-substituted-β-ketoesters. Density functional theory computations reveal that the NHC-catalyzed DKR proceeds by two mechanisms, depending on the stereochemistry around the forming bond: 1) a concerted, asynchronous formal (2+2) aldol-lactonization process, or 2) a stepwise spiro-lactonization mechanism where the alkoxide is trapped by the NHC-catalyst. These mechanisms contrast significantly from mechanisms found and postulated in other related transformations. Conjugative stabilization of the electrophile and non-classical hydrogen bonds are key in controlling the stereoselectivity. This reaction constitutes an interesting class of DKRs in which the catalyst is responsible for the kinetic resolution to selectively and irreversibly capture an enantiomer of a substrate undergoing rapid racemization with the help of an exogenous base
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Catalytic Kinetic Resolution of a Dynamic Racemate: Highly Stereoselective β-Lactone Formation by N-Heterocyclic Carbene Catalysis
This study describes the combined experimental and computational elucidation of the mechanism and
origins of stereoselectivities in the NHC-catalyzed dynamic kinetic resolution (DKR) of α-substituted-β-ketoesters. Density functional theory computations reveal that the NHC-catalyzed DKR proceeds by two
mechanisms, depending on the stereochemistry around the forming bond: 1) a concerted, asynchronous
formal (2+2) aldol-lactonization process, or 2) a stepwise spiro-lactonization mechanism where the
alkoxide is trapped by the NHC-catalyst. These mechanisms contrast significantly from mechanisms
found and postulated in other related transformations. Conjugative stabilization of the electrophile and
non-classical hydrogen bonds are key in controlling the stereoselectivity. This reaction constitutes an
interesting class of DKRs in which the catalyst is responsible for the kinetic resolution to selectively and
irreversibly capture an enantiomer of a substrate undergoing rapid racemization with the help of an
exogenous base
Computational planning of the synthesis of complex natural products
Training algorithms to computationally plan multistep organic syntheses has been a challenge for more than 50 years(1-7). However, the field has progressed greatly since the development of early programs such as LHASA(1,7), for which reaction choices at each step were made by human operators. Multiple software platforms(6,8-14) are now capable of completely autonomous planning. But these programs 'think' only one step at a time and have so far been limited to relatively simple targets, the syntheses of which could arguably be designed by human chemists within minutes, without the help of a computer. Furthermore, no algorithm has yet been able to design plausible routes to complex natural products, for which much more far-sighted, multistep planning is necessary(15,16) and closely related literature precedents cannot be relied on. Here we demonstrate that such computational synthesis planning is possible, provided that the program's knowledge of organic chemistry and data-based artificial intelligence routines are augmented with causal relationships(17,18), allowing it to 'strategize' over multiple synthetic steps. Using a Turing-like test administered to synthesis experts, we show that the routes designed by such a program are largely indistinguishable from those designed by humans. We also successfully validated three computer-designed syntheses of natural products in the laboratory. Taken together, these results indicate that expert-level automated synthetic planning is feasible, pending continued improvements to the reaction knowledge base and further code optimization. A synthetic route-planning algorithm, augmented with causal relationships that allow it to strategize over multiple steps, can design complex natural-product syntheses that are indistinguishable from those designed by human experts
Stroke Rehabilitation Reaches a Threshold
Motor training with the upper limb affected by stroke partially reverses the loss of cortical representation after lesion and has been proposed to increase spontaneous arm use. Moreover, repeated attempts to use the affected hand in daily activities create a form of practice that can potentially lead to further improvement in motor performance. We thus hypothesized that if motor retraining after stroke increases spontaneous arm use sufficiently, then the patient will enter a virtuous circle in which spontaneous arm use and motor performance reinforce each other. In contrast, if the dose of therapy is not sufficient to bring spontaneous use above threshold, then performance will not increase and the patient will further develop compensatory strategies with the less affected hand. To refine this hypothesis, we developed a computational model of bilateral hand use in arm reaching to study the interactions between adaptive decision making and motor relearning after motor cortex lesion. The model contains a left and a right motor cortex, each controlling the opposite arm, and a single action choice module. The action choice module learns, via reinforcement learning, the value of using each arm for reaching in specific directions. Each motor cortex uses a neural population code to specify the initial direction along which the contralateral hand moves towards a target. The motor cortex learns to minimize directional errors and to maximize neuronal activity for each movement. The derived learning rule accounts for the reversal of the loss of cortical representation after rehabilitation and the increase of this loss after stroke with insufficient rehabilitation. Further, our model exhibits nonlinear and bistable behavior: if natural recovery, motor training, or both, brings performance above a certain threshold, then training can be stopped, as the repeated spontaneous arm use provides a form of motor learning that further bootstraps performance and spontaneous use. Below this threshold, motor training is “in vain”: there is little spontaneous arm use after training, the model exhibits learned nonuse, and compensatory movements with the less affected hand are reinforced. By exploring the nonlinear dynamics of stroke recovery using a biologically plausible neural model that accounts for reversal of the loss of motor cortex representation following rehabilitation or the lack thereof, respectively, we can explain previously hard to reconcile data on spontaneous arm use in stroke recovery. Further, our threshold prediction could be tested with an adaptive train–wait–train paradigm: if spontaneous arm use has increased in the “wait” period, then the threshold has been reached, and rehabilitation can be stopped. If spontaneous arm use is still low or has decreased, then another bout of rehabilitation is to be provided
Effect of aliskiren on post-discharge outcomes among diabetic and non-diabetic patients hospitalized for heart failure: insights from the ASTRONAUT trial
Aims The objective of the Aliskiren Trial on Acute Heart Failure Outcomes (ASTRONAUT) was to determine whether aliskiren, a direct renin inhibitor, would improve post-discharge outcomes in patients with hospitalization for heart failure (HHF) with reduced ejection fraction. Pre-specified subgroup analyses suggested potential heterogeneity in post-discharge outcomes with aliskiren in patients with and without baseline diabetes mellitus (DM). Methods and results ASTRONAUT included 953 patients without DM (aliskiren 489; placebo 464) and 662 patients with DM (aliskiren 319; placebo 343) (as reported by study investigators). Study endpoints included the first occurrence of cardiovascular death or HHF within 6 and 12 months, all-cause death within 6 and 12 months, and change from baseline in N-terminal pro-B-type natriuretic peptide (NT-proBNP) at 1, 6, and 12 months. Data regarding risk of hyperkalaemia, renal impairment, and hypotension, and changes in additional serum biomarkers were collected. The effect of aliskiren on cardiovascular death or HHF within 6 months (primary endpoint) did not significantly differ by baseline DM status (P = 0.08 for interaction), but reached statistical significance at 12 months (non-DM: HR: 0.80, 95% CI: 0.64-0.99; DM: HR: 1.16, 95% CI: 0.91-1.47; P = 0.03 for interaction). Risk of 12-month all-cause death with aliskiren significantly differed by the presence of baseline DM (non-DM: HR: 0.69, 95% CI: 0.50-0.94; DM: HR: 1.64, 95% CI: 1.15-2.33; P < 0.01 for interaction). Among non-diabetics, aliskiren significantly reduced NT-proBNP through 6 months and plasma troponin I and aldosterone through 12 months, as compared to placebo. Among diabetic patients, aliskiren reduced plasma troponin I and aldosterone relative to placebo through 1 month only. There was a trend towards differing risk of post-baseline potassium ≥6 mmol/L with aliskiren by underlying DM status (non-DM: HR: 1.17, 95% CI: 0.71-1.93; DM: HR: 2.39, 95% CI: 1.30-4.42; P = 0.07 for interaction). Conclusion This pre-specified subgroup analysis from the ASTRONAUT trial generates the hypothesis that the addition of aliskiren to standard HHF therapy in non-diabetic patients is generally well-tolerated and improves post-discharge outcomes and biomarker profiles. In contrast, diabetic patients receiving aliskiren appear to have worse post-discharge outcomes. Future prospective investigations are needed to confirm potential benefits of renin inhibition in a large cohort of HHF patients without D
Repositioning of the global epicentre of non-optimal cholesterol
High blood cholesterol is typically considered a feature of wealthy western countries(1,2). However, dietary and behavioural determinants of blood cholesterol are changing rapidly throughout the world(3) and countries are using lipid-lowering medications at varying rates. These changes can have distinct effects on the levels of high-density lipoprotein (HDL) cholesterol and non-HDL cholesterol, which have different effects on human health(4,5). However, the trends of HDL and non-HDL cholesterol levels over time have not been previously reported in a global analysis. Here we pooled 1,127 population-based studies that measured blood lipids in 102.6 million individuals aged 18 years and older to estimate trends from 1980 to 2018 in mean total, non-HDL and HDL cholesterol levels for 200 countries. Globally, there was little change in total or non-HDL cholesterol from 1980 to 2018. This was a net effect of increases in low- and middle-income countries, especially in east and southeast Asia, and decreases in high-income western countries, especially those in northwestern Europe, and in central and eastern Europe. As a result, countries with the highest level of non-HDL cholesterol-which is a marker of cardiovascular riskchanged from those in western Europe such as Belgium, Finland, Greenland, Iceland, Norway, Sweden, Switzerland and Malta in 1980 to those in Asia and the Pacific, such as Tokelau, Malaysia, The Philippines and Thailand. In 2017, high non-HDL cholesterol was responsible for an estimated 3.9 million (95% credible interval 3.7 million-4.2 million) worldwide deaths, half of which occurred in east, southeast and south Asia. The global repositioning of lipid-related risk, with non-optimal cholesterol shifting from a distinct feature of high-income countries in northwestern Europe, north America and Australasia to one that affects countries in east and southeast Asia and Oceania should motivate the use of population-based policies and personal interventions to improve nutrition and enhance access to treatment throughout the world.Peer reviewe
Global variations in diabetes mellitus based on fasting glucose and haemogloblin A1c
Fasting plasma glucose (FPG) and haemoglobin A1c (HbA1c) are both used to diagnose
diabetes, but may identify different people as having diabetes. We used data from 117
population-based studies and quantified, in different world regions, the prevalence of
diagnosed diabetes, and whether those who were previously undiagnosed and detected
as having diabetes in survey screening had elevated FPG, HbA1c, or both. We developed
prediction equations for estimating the probability that a person without previously
diagnosed diabetes, and at a specific level of FPG, had elevated HbA1c, and vice versa.
The age-standardised proportion of diabetes that was previously undiagnosed, and
detected in survey screening, ranged from 30% in the high-income western region to 66%
in south Asia. Among those with screen-detected diabetes with either test, the agestandardised
proportion who had elevated levels of both FPG and HbA1c was 29-39%
across regions; the remainder had discordant elevation of FPG or HbA1c. In most low- and
middle-income regions, isolated elevated HbA1c more common than isolated elevated
FPG. In these regions, the use of FPG alone may delay diabetes diagnosis and
underestimate diabetes prevalence. Our prediction equations help allocate finite
resources for measuring HbA1c to reduce the global gap in diabetes diagnosis and
surveillance.peer-reviewe
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