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Residual cognitive capacities in patients with cognitive motor dissociation, and their implications for well-being
No full textPatients with severe disorders of consciousness are thought to be unaware of themselves or their environment. However, research suggests that a minority of patients diagnosed as having a disorder of consciousness remain aware. These patients, designated as having “cognitive motor dissociation” (CMD), can demonstrate awareness by imagining specific tasks, which generates brain activity detectable via functional neuroimaging. The discovery of consciousness in these patients raises difficult questions about their well-being, and it has been argued that it would be better for these patients if they were allowed to die. Conversely, I argue that CMD patients may have a much higher level of well-being than is generally acknowledged. It is far from clear that their lives are not worth living, because there are still significant gaps in our understanding of how these patients experience the world. I attempt to fill these gaps, by analyzing the neuroscientific research that has taken place with these patients to date. Having generated as comprehensive a picture as possible of the capacities of CMD patients, I examine this picture through the lens of traditional philosophical theories of well-being. I conclude that the presumption that CMD patients do not have lives worth living is not adequately supported
Solving the synoptic puzzle: introducing the case for the Farrer hypothesis
No full textThe question of how the Gospels of Matthew, Mark, and Luke relate to each other has become the subject of often intense debate. No longer is it safe to assume that the long dominant Two Document Hypothesis can be accepted without much question. In this book, Eve introduces students and other interested readers to the issues surrounding the Synoptic Problem and goes on to argue for an alternative theory (the Farrer Hypothesis) which does away with the need for the hypothetic source Q. In the course of doing so he also provides a helpful discussion of the how and why of first-century Gospel authorship. While the reader is alerted to the difficulties and complexities that surround solving the puzzle of Synoptic relations, the discussion is kept as accessible as possible and assumes no prior knowledge of New Testament scholarship or Greek
Examination of optimized protocols for pCASL: Sensitivity to macrovascular contamination, flow dispersion, and prolonged arterial transit time
No full textPurpose
Previously, multi- post-labeling delays (PLD) pseudo-continuous arterial spin labeling (pCASL) protocols have been optimized for the estimation accuracy of the cerebral blood flow (CBF) with/without the arterial transit time (ATT) under a standard kinetic model and a normal ATT range. This study aims to examine the estimation errors of these protocols under the effects of macrovascular contamination, flow dispersion, and prolonged arrival times, all of which might differ substantially in elderly or pathological groups.
Methods
Simulated data for four protocols with varying degrees of arterial blood volume (aBV), flow dispersion, and ATTs were fitted with different kinetic models, both with and without explicit correction for macrovascular signal contamination (MVC), to obtain CBF and ATT estimates. Sensitivity to MVC was defined and calculated when aBV > 0.5%. A previously acquired dataset was retrospectively analyzed to compare with simulation.
Results
All protocols showed underestimation of CBF and ATT in the prolonged ATT range. With MVC, the protocol optimized for CBF only (CBFopt) had the lowest sensitivity value to MVC, 33.47% and 60.21% error per 1% aBV in simulation and in vivo, respectively, among multi-PLD protocols. All multi-PLD protocols showed a significant decrease in estimation error when an extended kinetic model was used. Increasing flow dispersion at short ATTs caused increasing CBF and ATT overestimation in all protocols.
Conclusion
CBFopt was the least sensitive protocol to prolonged ATT and MVC for CBF estimation while maintaining reasonably good performance in estimating ATT. Explicitly including a macrovascular component in the kinetic model was shown to be a feasible approach in controlling for MVC
Phenotypic manifestation of α-synuclein strains derived from Parkinson’s disease and multiple system atrophy in human dopaminergic neurons
No full textα-Synuclein is critical in the pathogenesis of Parkinson’s disease and related disorders, yet it remains unclear how its aggregation causes degeneration of human dopaminergic neurons. In this study, we induced α-synuclein aggregation in human iPSC-derived dopaminergic neurons using fibrils generated de novo or amplified in the presence of brain homogenates from Parkinson’s disease or multiple system atrophy. Increased α-synuclein monomer levels promote seeded aggregation in a dose and time-dependent manner, which is associated with a further increase in α-synuclein gene expression. Progressive neuronal death is observed with brain-amplified fibrils and reversed by reduction of intraneuronal α-synuclein abundance. We identified 56 proteins differentially interacting with aggregates triggered by brain-amplified fibrils, including evasion of Parkinson’s disease-associated deglycase DJ-1. Knockout of DJ-1 in iPSC-derived dopaminergic neurons enhance fibril-induced aggregation and neuronal death. Taken together, our results show that the toxicity of α-synuclein strains depends on aggregate burden, which is determined by monomer levels and conformation which dictates differential interactomes. Our study demonstrates how Parkinson’s disease-associated genes influence the phenotypic manifestation of strains in human neurons
DLAB: deep learning methods for structure-based virtual screening of antibodies
No full textMotivation
Antibodies are one of the most important classes of pharmaceuticals, with over 80 approved molecules currently in use against a wide variety of diseases. The drug discovery process for antibody therapeutic candidates however is time- and cost-intensive and heavily reliant on in vivo and in vitro high throughput screens. Here, we introduce a framework for structure-based deep learning for antibodies (DLAB) which can virtually screen putative binding antibodies against antigen targets of interest. DLAB is built to be able to predict antibody–antigen binding for antigens with no known antibody binders.
Results
We demonstrate that DLAB can be used both to improve antibody–antigen docking and structure-based virtual screening of antibody drug candidates. DLAB enables improved pose ranking for antibody docking experiments as well as selection of antibody–antigen pairings for which accurate poses are generated and correctly ranked. We also show that DLAB can identify binding antibodies against specific antigens in a case study. Our results demonstrate the promise of deep learning methods for structure-based virtual screening of antibodies.
Availability and implementation
The DLAB source code and pre-trained models are available at https://github.com/oxpig/dlab-public.
Supplementary information
Supplementary data are available at Bioinformatics online
DDX3X loss is an adverse prognostic marker in diffuse large B-cell lymphoma and is associated with chemoresistance in aggressive non-Hodgkin lymphoma subtypes
No full textProbing the distinct chemosensitivity of Plasmodium vivax liver stage parasites and demonstration of 8-aminoquinoline radical cure activity in vitro
No full textImproved control of Plasmodium vivax malaria can be achieved with the discovery of new antimalarials with radical cure efficacy, including prevention of relapse caused by hypnozoites residing in the liver of patients. We screened several compound libraries against P. vivax liver stages, including 1565 compounds against mature hypnozoites, resulting in one drug-like and several probe-like hits useful for investigating hypnozoite biology. Primaquine and tafenoquine, administered in combination with chloroquine, are currently the only FDA-approved antimalarials for radical cure, yet their activity against mature P. vivax hypnozoites has not yet been demonstrated in vitro. By developing an extended assay, we show both drugs are individually hypnozonticidal and made more potent when partnered with chloroquine, similar to clinically relevant combinations. Post-hoc analyses of screening data revealed excellent performance of ionophore controls and the high quality of single point assays, demonstrating a platform able to support screening of greater compound numbers. A comparison of P. vivax liver stage activity data with that of the P. cynomolgi blood, P. falciparum blood, and P. berghei liver stages reveals overlap in schizonticidal but not hypnozonticidal activity, indicating that the delivery of new radical curative agents killing P. vivax hypnozoites requires an independent and focused drug development test cascade
Switchable polymerization catalysis using a tin(II) catalyst and commercial monomers to toughen poly(L-lactide)
No full textSustainable plastics sourced without virgin petrochemicals, that are easily recyclable and with potential for degradation at end of life, are urgently needed. Here, copolymersand blends meeting these criteria are efficiently prepared using a single catalyst and existing commercial monomers l-lactide, propylene oxide, and maleic anhydride. The selective, one-reactor polymerization applies an industry-relevant tin(II) catalyst. Tapered, miscible block polyesters are formed with alkene groups which are postfunctionalized to modulate the polymer glass transition temperature. The polymers are blended at desirable low weight fractions (2 wt %) with commercial poly(l-lactide) (PLLA), increasing toughness, and elongation at break without compromising the elastic modulus, tensile strength, or thermal properties. The selective polymerization catalysis, using commercial monomers and catalyst, provides a straightforward means to improve bioplastics performances
Bond-dependent exchange, order-by-disorder and nodal quasiparticles' intensity signature in a honeycomb cobaltate
No full textRecent theoretical proposals have argued that cobaltates with edge-sharing octahedral coordination can have significant bond-dependent exchange couplings thus offering a platform in 3d ions for such physics beyond the much-explored realizations in 4d and 5d materials. Here we present high-resolution inelastic neutron scattering data within the magnetically ordered phase of the stacked honeycomb magnet CoTiO3 revealing the presence of a finite energy gap and demonstrate that this implies the presence of bond-dependent anisotropic couplings. We also show through an extensive theoretical analysis that the gap further implies the existence of a quantum order-by-disorder mechanism that, in this material, crucially involves virtual crystal field fluctuations. Our data also provide an experimental observation of a universal winding of the scattering intensity in angular scans around linear band-touching points for both magnons and dispersive spin-orbit excitons, which is directly related to the non-trivial topology of the quasiparticle wavefunction in momentum space near nodal points.
The deposited data package contains neutron powder diffraction and single crystal inelastic neutron scattering data to probe the magnetic ordering and dynamics. The zip archive contains the data in the format of multi-column ASCII files, a README.txt that explains the content of all the files and matlab code to plot the data in all the files, together with relevant RGB colourmap
Capability of the variogram to quantify the spatial patterns of surface fluxes and soil moisture simulated by land surface models
No full textUp to now, relatively little effort has been dedicated to the quantitative assessment of the differences in spatial patterns of model outputs. In this paper, we employed a variogram-based methodology to quantify the differences in the spatial patterns of root-zone soil moisture, net radiation, and latent and sensible heat fluxes simulated by three land surface models (SURFEX/ISBA, JULES and CHTESSEL) over three European geographic domains – namely, UK, France and Spain. The model output spatial patterns were quantified through two metrics derived from the variogram: i) the variogram sill, which quantifies the degree of spatial variability of the data; and ii) the variogram integral range, which represents the spatial length scale of the data. The higher seasonal variation of the spatial variability of sensible and latent heat fluxes over France and Spain, compared to the UK, is related to a more frequent occurrence of a soil-moisture-limited evapotranspiration regime during summer dry spells in the south of France and Spain. The small differences in spatial variability of net radiation between models indicate that the spatial patterns of net radiation are mostly driven by the climate forcing data set. However, the models exhibit larger differences in latent and sensible heat flux spatial variabilities, which are related to their differences in i) soil and vegetation ancillary datasets and ii) physical process representation. The highest discrepancies in spatial patterns between models are observed for soil moisture, which is mainly related to the type of soil hydraulic function implemented in the models. This work demonstrates the capability of the variogram to enhance our understanding of the spatiotemporal structure of the uncertainties in land surface model outputs. Therefore, we strongly encourage the implementation of the variogram metrics in model intercomparison exercises