Successful treatment of COVID-19 infection with convalescent plasma in B-cell-depleted patients may promote cellular immunity

Treatment with convalescent plasma has been shown to be safe in coronavirus disease in 2019 (COVID-19) infection, although efficacy reported in immunocompetent patients varies. Nevertheless, neutralizing antibodies are a key requisite in the fight against viral infections. Patients depleted of antibody-producing B cells, such as those treated with rituximab (anti-CD20) for hematological malignancies, lack a fundamental part of their adaptive immunity. Treatment with convalescent plasma appears to be of general benefit in this particularly vulnerable cohort. We analyzed clinical course and inflammation markers of three B-cell-depleted patients suffering from COVID-19 who were treated with convalescent plasma. In addition, we measured serum antibody levels as well as peripheral blood CD38/HLA-DR-positive T-cells ex vivo and CD137-positive T-cells after in vitro stimulation with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-derived peptides in these patients. We observed that therapy with convalescent plasma was effective in all three patients and analysis of CD137-positive T-cells after stimulation with SARS-CoV-2 peptides showed an increase in peptide-specific T-cells after application of convalescent plasma. In conclusion, we here demonstrate efficacy of convalescent plasma therapy in three B-cell-depleted patients and present data that suggest that while application of convalescent plasma elevates systemic antibody levels only transiently, it may also boost specific T-cell responses.     

Artificial Intelligence for Fast and Accurate 3-Dimensional Tooth Segmentation on Cone-beam Computed Tomography

IntroductionTooth segmentation on cone-beam computed tomographic (CBCT) imaging is a labor-intensive task considering the limited contrast resolution and potential disturbance by various artifacts. Fully automated tooth segmentation cannot be achieved by merely relying on CBCT intensity variations. This study aimed to develop and validate an artificial intelligence (AI)-driven tool for automated tooth segmentation on CBCT imaging.MethodsA total of 433 Digital Imaging and Communications in Medicine images of single- and double-rooted teeth randomly selected from 314 anonymized CBCT scans were imported and manually segmented. An AI-driven tooth segmentation algorithm based on a feature pyramid network was developed to automatically detect and segment teeth, replacing manual user contour placement. The AI-driven tool was evaluated based on volume comparison, intersection over union, the Dice score coefficient, morphologic surface deviation, and total segmentation time.ResultsOverall, AI-driven and clinical reference segmentations resulted in very similar segmentation volumes. The mean intersection over union for full-tooth segmentation was 0.87 (±0.03) and 0.88 (±0.03) for semiautomated (SA) (clinical reference) versus fully automated AI-driven (F-AI) and refined AI-driven (R-AI) tooth segmentation, respectively. R-AI and F-AI segmentation showed an average median surface deviation from SA segmentation of 9.96 μm (±59.33 μm) and 7.85 μm (±69.55 μm), respectively. SA segmentations of single- and double-rooted teeth had a mean total time of 6.6 minutes (±76.15 seconds), F-AI segmentation of 0.5 minutes (±8.64 seconds, 12 times faster), and R-AI segmentation of 1.2 minutes (±33.02 seconds, 6 times faster).ConclusionsThis study showed a unique fast and accurate approach for AI-driven automated tooth segmentation on CBCT imaging. These results may open doors for AI-driven applications in surgical and treatment planning in oral health care.     

Dilution of candidates: the case of iron-related genes in restless legs syndrome

Restless legs syndrome (RLS) is a common multifactorial disease. Some genetic risk factors have been identified. RLS susceptibility also has been related to iron. We therefore asked whether known iron-related genes are candidates for association with RLS and, vice versa, whether known RLS-associated loci influence iron parameters in serum. RLS/control samples (n=954/1814 in the discovery step, 735/736 in replication 1, and 736/735 in replication 2) were tested for association with SNPs located within 4 Mb intervals surrounding each gene from a list of 111 iron-related genes using a discovery threshold of P=5 × 10⁻⁴. Two population cohorts (KORA F3 and F4 with together n=3447) were tested for association of six known RLS loci with iron, ferritin, transferrin, transferrin-saturation, and soluble transferrin receptor. Results were negative. None of the candidate SNPs at the iron-related gene loci was confirmed significantly. An intronic SNP, rs2576036, of KATNAL2 at 18q21.1 was significant in the first (P=0.00085) but not in the second replication step (joint nominal P-value=0.044). Especially, rs1800652 (C282Y) in the HFE gene did not associate with RLS. Moreover, SNPs at the known RLS loci did not significantly affect serum iron parameters in the KORA cohorts. In conclusion, the correlation between RLS and iron parameters in serum may be weaker than assumed. Moreover, in a general power analysis, we show that genetic effects are diluted if they are transmitted via an intermediate trait to an end-phenotype. Sample size formulas are provided for small effect sizes.     

From CO2‐Based Multifunctional Polycarbonates With a Controlled Number of Functional Groups to Graft Polymers

Copolymerization of CO₂ and epoxides is employed to generate functional polycarbonates. The introduction of reactive double bonds at a poly(propylene carbonate) (PPC) backbone is realized by the copolymerization of aliphatic alkene epoxides with propylene oxide (PO) and carbon dioxide (CO₂). A series of copolymers with random structure and varying comonomer content (3–22%) with molecular weights in the range of 22 000–34 000 g mol^?1 is synthesized and characterized with respect to their microstructure and thermal properties. The facile transformation of the double bonds is verified by a thiol‐ene reaction, resulting in quantitative conversion of the double bonds. Polycarbonate derivatives with multiple functionalities are prepared, providing suitable moieties for further grafting.

     

Expectancies, Socioeconomic Status, and Self-Rated Health: Use of the Simplified TOMCATS Questionnaire

Background

Coping has traditionally been measured with inventories containing many items meant to identify specific coping strategies. An alternative is to develop a shorter inventory that focusses on coping expectancies which may determine the extent to which an individual attempts to cope actively.

Purpose

This paper explores the usefulness and validity of a simplified seven-item questionnaire (Theoretically Originated Measure of the Cognitive Activation Theory of Stress, TOMCATS) for response outcome expectancies defined either as positive (“coping”), negative (“hopelessness”), or none (“helplessness”). The definitions are based on the Cognitive Activation Theory of Stress (CATS; Ursin and Eriksen, Psychoneuroendocrinology, 29(5):567–92, 2004). The questionnaire was tested in two different samples. First, the questionnaire was compared with a traditional test of coping and then tested for validity in relation to socioeconomic differences in self-reported health.

Methods

The first study was a comparison of the brief TOMCATS with a short version of the Utrecht Coping List (UCL; Eriksen et al., Scand J Psychol, 38(3):175–82, 1997). Both questionnaires were tested in a population of 1,704 Norwegian municipality workers. The second study was a cross-sectional analysis of TOMCATS, subjective and objective socioeconomic status, and health in a representative sample of the Swedish working population in 2003–2005 (N?=?11,441).

Results

In the first study, the coping item in the TOMCATS questionnaire showed an expected significant positive correlation with the UCL factors of instrumental mastery-oriented coping and negative correlations with passive and depressive scores. There were also the expected correlations for the helplessness and hopelessness scores, but there was no clear distinction between helplessness and hopelessness in the way they correlated with the UCL. In the second study, the coping item in TOMCATS and the three-item helplessness scores showed clear and monotonous gradients over a subjective socioeconomic status (SES) ladder. Positive response outcome expectancy (“coping”) was related to high subjective SES and no expectancy (“helplessness”) to low subjective SES. In a model including age and sex, TOMCATS scores explained more variance (r ²?=?0.16) in self-reported health than both subjective (r ²?=?0.08) and objective SES (r ²?=?0.02).

Conclusion

The brief TOMCATS questionnaire showed acceptable and significant correlations with a traditional coping questionnaire and is sensitive enough to register systematic differences in response outcome expectancies across the socioeconomic ladder. The results furthermore confirm that psychological and learning factors contribute to the socioeconomic gradient in health.     

Three‐dimensional imaging and analysis of human cartilage degeneration using Optical Coherence Tomography

Optical Coherence Tomography (OCT) is an evolving imaging technology allowing non‐destructive imaging of cartilage tissue at near‐histological resolution. This study investigated the diagnostic value of real time 3‐D OCT in comparison to conventional 2‐D OCT in the comprehensive grading of human cartilage degeneration. Fifty‐three human osteochondral samples were obtained from eight total knee arthroplasties. OCT imaging was performed by either obtaining a single two‐dimensional cross‐sectional image (2‐D OCT) or by collecting 100 consecutive parallel 2‐D OCT images to generate a volumetric data set of 8 × 8 mm (3‐D OCT). OCT images were assessed qualitatively according to a modified version of the DJD classification and quantitatively by algorithm‐based evaluation of surface irregularity, tissue homogeneity, and signal attenuation. Samples were graded according to the Outerbridge classification and statistically analyzed by one‐way ANOVA, Kruskal Wallis and Tukey's or Dunn's post‐hoc tests. Overall, the generation of 3‐D volumetric datasets and their multiple reconstructions such as rendering, surface topography, parametric, and cross‐sectional views proved to be of potential diagnostic value. With increasing distance to the mid‐sagittal plane and increasing degeneration, score deviations increased, too. In conclusion, 3‐D imaging of cartilage with image analysis algorithms adds considerable potential diagnostic value to conventional OCT diagnostics. © 2015 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 33:651–659, 2015.