Correlation of Fc Receptor Polymorphisms with Pneumococcal Antibodies in Vaccinated Kidney Transplant Recipients

Several polymorphisms within Fc receptors (FCR) have been described, some of which correlate with allograft function. In the current study, we determined three Fcγ receptor and five Fcα receptor dimorphisms in 47 kidney transplant recipients who had been vaccinated against Streptococcus pneumoniae. We analyzed if FCR genotypes correlated with pneumococcal antibodies and their serotype-specific opsonophagocytic function, tested prior to and at months 1 and 12 post-vaccination. In parallel, we assessed antibodies against HLA and MICA and determined kidney function. We observed that IgG2 antibodies against pneumococci at months 1 and 12 after vaccination and IgA antibodies at month 1 differed significantly between the carriers of the three genotypes of FCGR3A rs396991 (V158F, p = 0.02; 0.04 and 0.009, respectively). Moreover, the genotype of FCGR3A correlated with serotype-specific opsonophagocytic function, reaching statistical significance (p < 0.05) at month 1 for 9/13 serotypes and at month 12 for 6/13 serotypes. Heterozygotes for FCGR3A had the lowest antibody response after pneumococcal vaccination. On the contrary, heterozygotes tended to have more antibodies against HLA class I and impaired kidney function. Taken together, our current data indicate that heterozygosity for FCGR3A may be unfavorable in kidney transplant recipients

Artificial Intelligence Algorithms to Diagnose Glaucoma and Detect Glaucoma Progression: Translation to Clinical Practice

Purpose: This concise review aims to explore the potential for the clinical implementation of artificial intelligence (AI) strategies for detecting glaucoma and monitoring glaucoma progression. / Methods: Nonsystematic literature review using the search combinations "Artificial Intelligence," "Deep Learning," "Machine Learning," "Neural Networks," "Bayesian Networks," "Glaucoma Diagnosis," and "Glaucoma Progression." Information on sensitivity and specificity regarding glaucoma diagnosis and progression analysis as well as methodological details were extracted. / Results: Numerous AI strategies provide promising levels of specificity and sensitivity for structural (e.g. optical coherence tomography [OCT] imaging, fundus photography) and functional (visual field [VF] testing) test modalities used for the detection of glaucoma. Area under receiver operating curve (AROC) values of > 0.90 were achieved with every modality. Combining structural and functional inputs has been shown to even more improve the diagnostic ability. Regarding glaucoma progression, AI strategies can detect progression earlier than conventional methods or potentially from one single VF test. / Conclusions: AI algorithms applied to fundus photographs for screening purposes may provide good results using a simple and widely accessible test. However, for patients who are likely to have glaucoma more sophisticated methods should be used including data from OCT and perimetry. Outputs may serve as an adjunct to assist clinical decision making, whereas also enhancing the efficiency, productivity, and quality of the delivery of glaucoma care. Patients with diagnosed glaucoma may benefit from future algorithms to evaluate their risk of progression. Challenges are yet to be overcome, including the external validity of AI strategies, a move from a "black box" toward "explainable AI," and likely regulatory hurdles. However, it is clear that AI can enhance the role of specialist clinicians and will inevitably shape the future of the delivery of glaucoma care to the next generation. / Translational Relevance: The promising levels of diagnostic accuracy reported by AI strategies across the modalities used in clinical practice for glaucoma detection can pave the way for the development of reliable models appropriate for their translation into clinical practice. Future incorporation of AI into healthcare models may help address the current limitations of access and timely management of patients with glaucoma across the world

Identifying multiple sclerosis subtypes using unsupervised machine learning and MRI data

Multiple sclerosis (MS) can be divided into four phenotypes based on clinical evolution. The pathophysiological boundaries of these phenotypes are unclear, limiting treatment stratification. Machine learning can identify groups with similar features using multidimensional data. Here, to classify MS subtypes based on pathological features, we apply unsupervised machine learning to brain MRI scans acquired in previously published studies. We use a training dataset from 6322 MS patients to define MRI-based subtypes and an independent cohort of 3068 patients for validation. Based on the earliest abnormalities, we define MS subtypes as cortex-led, normal-appearing white matter-led, and lesion-led. People with the lesion-led subtype have the highest risk of confirmed disability progression (CDP) and the highest relapse rate. People with the lesion-led MS subtype show positive treatment response in selected clinical trials. Our findings suggest that MRI-based subtypes predict MS disability progression and response to treatment and may be used to define groups of patients in interventional trials

Collection of hematopoietic stem cells from patients with autoimmune diseases

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Three "universal" mesoscopic Josephson effects

1. Introduction 2. Supercurrent from Excitation Spectrum 3. Excitation Spectrum from Scattering Matrix 4. Short-Junction Limit 5. Universal Josephson Effects 5.1 Quantum Point Contact 5.2 Quantum Dot 5.3 Disordered Point Contact (Average supercurrent, Supercurrent fluctuations)Comment: 21 pages, 2 figures; legacy revie

Continuous, Semi-discrete, and Fully Discretized Navier-Stokes Equations

The Navier--Stokes equations are commonly used to model and to simulate flow phenomena. We introduce the basic equations and discuss the standard methods for the spatial and temporal discretization. We analyse the semi-discrete equations -- a semi-explicit nonlinear DAE -- in terms of the strangeness index and quantify the numerical difficulties in the fully discrete schemes, that are induced by the strangeness of the system. By analyzing the Kronecker index of the difference-algebraic equations, that represent commonly and successfully used time stepping schemes for the Navier--Stokes equations, we show that those time-integration schemes factually remove the strangeness. The theoretical considerations are backed and illustrated by numerical examples.Comment: 28 pages, 2 figure, code available under DOI: 10.5281/zenodo.998909, https://doi.org/10.5281/zenodo.99890

Naturally occurring hybrids of coral reef butterflyfishes have similar fitness compared to parental species.

Hybridisation can produce evolutionary novelty by increasing fitness and adaptive capacity. Heterosis, or hybrid vigour, has been documented in many plant and animal taxa, and is a notable consequence of hybridisation that has been exploited for decades in agriculture and aquaculture. On the contrary, loss of fitness in naturally occurring hybrid taxa has been observed in many cases. This can have negative consequences for the parental species involved (wasted reproductive effort), and has raised concerns for species conservation. This study evaluates the relative fitness of previously documented butterflyfish hybrids of the genus Chaetodon from the Indo-Pacific suture zone at Christmas Island. Histological examination confirmed the reproductive viability of Chaetodon hybrids. Examination of liver lipid content showed that hybrid body condition was not significantly different from parent species body condition. Lastly, size at age data revealed no difference in growth rates and asymptotic length between hybrids and parent species. Based on the traits measured in this study, naturally occurring hybrids of Chaetodon butterflyfishes have similar fitness to their parental species, and are unlikely to supplant parental species under current environmental conditions at the suture zone. However, given sufficient fitness and ongoing genetic exchange between the respective parental species, hybrids are likely to persist within the suture zone

Odour-mediated orientation of beetles is influenced by age, sex and morph

The behaviour of insects is dictated by a combination of factors and may vary considerably between individuals, but small insects are often considered en masse and thus these differences can be overlooked. For example, the cowpea bruchid Callosobruchus maculatus F. exists naturally in two adult forms: the active (flight) form for dispersal, and the inactive (flightless), more fecund but shorter-lived form. Given that these morphs show dissimilar biology, it is possible that they differ in odour-mediated orientation and yet studies of this species frequently neglect to distinguish morph type, or are carried out only on the inactive morph. Along with sex and age of individual, adult morph could be an important variable determining the biology of this and similar species, informing studies on evolution, ecology and pest management. We used an olfactometer with motion-tracking to investigate whether the olfactory behaviour and orientation of C. maculatus towards infested and uninfested cowpeas and a plant-derived repellent compound, methyl salicylate, differed between morphs or sexes. We found significant differences between the behaviour of male and female beetles and beetles of different ages, as well as interactive effects of sex, morph and age, in response to both host and repellent odours. This study demonstrates that behavioural experiments on insects should control for sex and age, while also considering differences between adult morphs where present in insect species. This finding has broad implications for fundamental entomological research, particularly when exploring the relationships between physiology, behaviour and evolutionary biology, and the application of crop protection strategies