Decidual-Secreted Factors Alter Invasive Trophoblast Membrane and Secreted Proteins Implying a Role for Decidual Cell Regulation of Placentation

Inadequate or inappropriate implantation and placentation during the establishment of human pregnancy is thought to lead to first trimester miscarriage, placental insufficiency and other obstetric complications. To create the placental blood supply, specialized cells, the ‘extravillous trophoblast’ (EVT) invade through the differentiated uterine endometrium (the decidua) to engraft and remodel uterine spiral arteries. We hypothesized that decidual factors would regulate EVT function by altering the production of EVT membrane and secreted factors. We used a proteomics approach to identify EVT membrane and secreted proteins regulated by decidual cell factors. Human endometrial stromal cells were decidualized in vitro by treatment with estradiol (10−8 M), medroxyprogesterone acetate (10−7 M) and cAMP (0.5 mM) for 14 days. Conditioned media (CM) was collected on day 2 (non-decidualized CM) and 14 (decidualized CM) of treatment. Isolated primary EVT cultured on Matrigel™ were treated with media control, non-decidualized or decidualized CM for 16 h. EVT CM was fractionated for proteins <30 kDa using size-exclusion affinity nanoparticles (SEAN) before trypsin digestion and HPLC-MS/MS. 43 proteins produced by EVT were identified; 14 not previously known to be expressed in the placenta and 12 which had previously been associated with diseases of pregnancy including preeclampsia. Profilin 1, lysosome associated membrane glycoprotein 1 (LAMP1), dipeptidyl peptidase 1 (DPP1/cathepsin C) and annexin A2 expression by interstitial EVT in vivo was validated by immunhistochemistry. Decidual CM regulation in vitro was validated by western blotting: decidualized CM upregulated profilin 1 in EVT CM and non-decidualized CM upregulated annexin A2 in EVT CM and pro-DPP1 in EVT cell lysate. Here, non-decidualized factors induced protease expression by EVT suggesting that non-decidualized factors may induce a pro-inflammatory cascade. Preeclampsia is a pro-inflammatory condition. Overall, we have demonstrated the potential of a proteomics approach to identify novel proteins expressed by EVT and to uncover the mechanisms leading to disease states

Examining the immunological effects of COVID-19 vaccination in patients with conditions potentially leading to diminished immune response capacity – the OCTAVE trial

SARS-COV-2 vaccines have been shown to be efficacious primarily in healthy volunteer populations and population level studies. Immune responses following SARS-CoV-2 vaccination are less well characterised in potentially immune vulnerable patient groups, including those with immune-mediated inflammatory and chronic diseases (inflammatory arthritis [IA] incorporating rheumatoid arthritis [RA] and psoriatic arthritis [PsA]; ANCA-Associated Vasculitis [AAV]; inflammatory bowel disease [IBD]); hepatic disease (HepD), end stage kidney disease requiring haemodialysis (HD) without or with immunosuppression (HDIS); solid cancers (SC) and haematological malignancies (HM), and those that have undergone haemopoietic stem cell transplant (HSCT). The OCTAVE trial is a multi-centre, multi-disease, prospective cohort that will comprehensively assess SARS-CoV-2 vaccine responses within and between the abovementioned disease cohorts using common analytical platforms in patients recruited across the United Kingdom (UK). The majority of subjects received either COVID-19 mRNA Vaccine BNT162b2 (Pfizer/BioNTech) or ChAdOx1 Vaccine (AstraZeneca formerly AZD1222) as part of the UK National COVID19 vaccination programme. As of 13 th August 2021; 2,583 patients have been recruited. We report herein the humoral and T cell immune response results from the first 600 participants recruited where serology data are available at baseline, pre-second vaccine dose (boost) and/or 4 weeks post second dose. We also include in the analysis, data obtained from 231 healthy individuals from the PITCH (Protective Immunity from T cells in Healthcare workers) study. Overall, in comparison to PITCH where 100% of tested individuals (n=93) generated anti-Spike antibodies after vaccine doses, 89% of patients within OCTAVE seroconverted 4 weeks after second vaccine dose. By corollary, approximately 11% of patients across all disease cohorts fail to generate antibodies that react to SARS-CoV-2 spike 4 weeks after two vaccines. Failure to generate spike reactive antibodies was found at a higher proportion in some specific patient subgroups, particularly AAV (72.4%), HD-IS (16.7%) and HepD (16.7%). Importantly, all recruited AAV patients had received Rituximab; a targeted B cell depletion therapy. Furthermore, even in those who seroconverted, 40% of patients across disease cohorts generate lower levels of SARS-CoV-2 antibody reactivity compared to healthy subjects after two SARS-CoV-2 vaccines; the functional significance of these findings in providing protection from subsequent SARS-CoV-2 exposure is not currently known. In contrast to the observed serological response, evaluation of the Spike-specific T cell response revealed that across all patient sub-groups (including AAV) a response similar to healthy individuals was generated. Our data argue strongly for further vaccination strategies to optimise humoral immune responses against SARS-CoV-2 in patients with chronic diseases and/or patients on immune suppressive therapies. Trial Registration: The trial is registered on ISRCTN 12821688.Funding: This work was supported by the Medical Research Council COVID-19 Immunity – National Core Study (IMM-NCS) [grant number MC-PC-20031]. Staff at the Cancer Research UK Clinical Trials Unit (CRCTU) are supported by a core funding grant from Cancer Research UK (C22436/A25354). PK and EB are supported by the NIHR Birmingham Biomedical Research Centres at the University Hospitals Birmingham NHS Foundation Trust and the University of Birmingham Biomedical Research Centres. EB and PK are supported by an NIHR Senior Investigator award. PK is funded by WT109965MA. SJD is funded by an NIHR Global Research Professorship (NIHR300791). TdS is funded by a Wellcome Trust Intermediate Clinical Fellowship (110058/Z/15/Z). DS is supported by the NIHR Academic Clinical Lecturer programme in Oxford. LT is supported by the Wellcome Trust (grant number 205228/Z/16/Z), the U.S. Food and Drug Administration Medical Countermeasures Initiative contract 75F40120C00085. and the National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Emerging and Zoonotic Infections (NIHR200907) at University of Liverpool in partnership with Public Health England (PHE), in collaboration with Liverpool School of Tropical Medicine and the University of Oxford. The PITCH (Protective Immunity from T cells to Covid-19 in Health workers) Consortium, is funded by the UK Department of Health and Social Care with contributions from UKRI/NIHR through the UK Coronavirus Immunology Consortium (UKCIC), the Huo Family Foundation and The National Institute for Health Research (UKRIDHSC COVID-19 Rapid Response Rolling Call, Grant Reference Number COV19-RECPLAS).Declaration of Interest: None to declare. Ethical Approval: This study was approved by the UK Medicines and Healthcare Products Regulatory Agency on the 5th February 2021 and the London and Chelsea Research Ethics Committee (REC Ref:21/HRA/0489) on 12th February 2021, with subsequent amendments approved on 3rd March 2021, 19th April 2021 and 26th April 2021)

Reconstruction of the Scalar-Tensor Lagrangian from a LCDM Background and Noether Symmetry

We consider scalar-tensor theories and reconstruct their potential U(\Phi) and coupling F(\Phi) by demanding a background LCDM cosmology. In particular we impose a background cosmic history H(z) provided by the usual flat LCDM parameterization through the radiation (w_{eff}=1/3), matter (w_{eff}=0) and deSitter (w_{eff}=-1) eras. The cosmological dynamical system which is constrained to obey the LCDM cosmic history presents five critical points in each era, one of which corresponding to the standard General Relativity (GR). In the cases that differ from GR, the reconstructed coupling and potential are of the form F(\Phi)\sim \Phi^2 and U(\Phi)\sim F(\Phi)^m where m is a constant. This class of scalar tensor theories is also theoretically motivated by a completely independent approach: imposing maximal Noether symmetry on the scalar-tensor Lagrangian. This approach provides independently: i) the form of the coupling and the potential as F(\Phi)\sim \Phi^2 and U(\Phi)\sim F(\Phi)^m, ii) a conserved charge related to the potential and the coupling and iii) allows the derivation of exact solutions by first integrals of motion.Comment: Added comments, discussion, references. 15 revtex pages, 5 fugure

Thermal and structural response of in situ prepared biobased poly(ethylene 2,5-furan dicarboxylate) nanocomposites

Poly(ethylene 2,5-furan dicarboxylate) (PEF) is considered the biobased counterpart of the fossil based poly(ethylene terephthalate) for food packaging. In this research, PEF nanocomposites containing 2.5 wt% neat multi walled carbon nanotubes (MWCNTs), or functionalized MWCNTs or graphene oxide (GO), were in situ prepared by applying the melt polycondensation method. The nanocomposites showed faster crystallization rates compared to the pristine material as proved by both differential scanning calorimetry (DSC) and polarized light microscopy (PLM). The latter evidenced an increased nucleation density in nanocomposites, due to the nucleating efficiency of the fillers, resulting in smaller spherulite size. However, a slightly reduced thermal stability was revealed for the nanocomposites by thermog-ravimetric analysis (TGA), especially in the case of GO-containing samples. The solid structure of the materials was studied by performing real time X-ray diffraction (XRD) measurements. In neat PEF, beta-crystals were observed in the solvent treated sample, while alpha-crystals were formed on cooling from the melt or cold-crystallization. On the contrary, in the XRD patterns of the nanocomposites only peaks associated with the alpha-crystal phase were found. Last, but not least, the effect of recrystallization on the thermal behavior was evaluated by means of modulated temperature DSC (MDSC). (C) 2016 Elsevier Ltd. All rights reserved

Discovery and Follow-up of ASASSN-19dj: An X-ray and UV Luminous TDE in an Extreme Post-Starburst Galaxy

We present observations of ASASSN-19dj, a nearby tidal disruption event (TDE) discovered in the post-starburst galaxy KUG 0810+227 by the All-Sky Automated Survey for Supernovae (ASAS-SN) at a distance of d $\simeq$ 98 Mpc. We observed ASASSN-19dj from $-$21 to 392 days relative to peak UV/optical emission using high-cadence, multi-wavelength spectroscopy and photometry. From the ASAS-SN $g$-band data, we determine that the TDE began to brighten on 2019 February 6.8 and for the first 25 days the rise was consistent with a flux $\propto$ $t^2$ power-law. ASASSN-19dj peaked in the UV/optical on 2019 March 6.5 (MJD = 58548.5) at a bolometric luminosity of $L = (6.2 \pm 0.2) \times 10^{44} \text{ erg s}^{-1}$. Initially remaining roughly constant in X-rays and slowly fading in the UV/optical, the X-ray flux increased by over an order of magnitude $\sim$225 days after peak, resulting from the expansion of the X-ray emitting surface. The late-time X-ray emission is well-fit by a blackbody with an effective radius of $\sim 1 \times 10^{12} \text{ cm}$ and a temperature of $\sim 6 \times 10^{5} \text{ K}$. Analysis of Catalina Real-Time Transient Survey images reveals a nuclear outburst roughly 14.5 years earlier with a smooth decline and a luminosity of $L_V$ $\geq$ $1.4 \times 10^{43}$ erg s$^{-1}$, although the nature of the flare is unknown. ASASSN-19dj occurred in the most extreme post-starburst galaxy yet to host a TDE, with Lick H$\delta_{A}$ = $7.67 \pm 0.17$ \AA.Comment: 25 pages, 14 figures. Will be submitted to MNRAS. For a short video description please see https://youtu.be/WjTZwO7vcF

Reproductive health and burn-out among female physicians: nationwide, representative study from Hungary

BACKGROUND: There is a worldwide rising tendency of women deciding to become physicians; hence, one of the most remarkable fields of investigation is the wellbeing of female doctors. The aim of this study was to describe female physicians' reproductive health in Hungary and to explore the potential correlation between their reproductive disorders and burnout symptoms. Up to our present knowledge, there have not been any studies investigating the correlation between reproductive disorders and burnout of female physicians; therefore, our study represents a unique approach. METHODS: Data in this representative cross-sectional epidemiological study were obtained from online questionnaires completed by 3039 female physicians. Participants in a representative nationwide survey (Hungarostudy, 2013) served as controls (n = 1069). Differences between physicians and the control group were disclosed by chi-square test. Correlations between certain factors of reproductive health and the three dimensions of burnout were detected by Pearson correlations and X2 test. Binary logistic regression analysis was used to determine the association between burnout and reproductive health. RESULTS: Female physicians were more often characterised by time-to-pregnancy interval longer than one year (18.4% vs. 9.8%), were bearing more high-risk pregnancies (26.3% vs.16.3%), and were more likely to be undergoing infertility therapy (8.5% vs. 3.4%) and experiencing miscarriage (20.8% vs. 14.6%) during their reproductive years, compared with the general female population. With the exception of miscarriages, the difference remained significant in all comparisons with the professional control group. Both high-risk pregnancies and miscarriages of doctors were associated with depersonalisation (p = 0.028 and p = 0.012 respectively) and personal accomplishment (p = 0.016 and p = 0.008 respectively) dimensions of burnout. Results of the multivariate analysis showed that, beside traditional risk factors, depersonalisation acted as an important explanatory factor in case of high-risk pregnancies (OR = 1.086). CONCLUSIONS: There is a circulatory causality between burnout and the development of reproductive disorders. Burnout is an important risk factor for high-risk pregnancies and miscarriages, and it has a negative effect on the outcome of pregnancies. At the same time, women suffering from reproductive disorders are more likely to develop burnout syndrome. Improvement of working conditions and prevention of burnout in female doctors are equally important tasks

Neuropsychological predictors of conversion from mild cognitive impairment to Alzheimer’s disease: a feature selection ensemble combining stability and predictability

Background Predicting progression from Mild Cognitive Impairment (MCI) to Alzheimer’s Disease (AD) is an utmost open issue in AD-related research. Neuropsychological assessment has proven to be useful in identifying MCI patients who are likely to convert to dementia. However, the large battery of neuropsychological tests (NPTs) performed in clinical practice and the limited number of training examples are challenge to machine learning when learning prognostic models. In this context, it is paramount to pursue approaches that effectively seek for reduced sets of relevant features. Subsets of NPTs from which prognostic models can be learnt should not only be good predictors, but also stable, promoting generalizable and explainable models. Methods We propose a feature selection (FS) ensemble combining stability and predictability to choose the most relevant NPTs for prognostic prediction in AD. First, we combine the outcome of multiple (filter and embedded) FS methods. Then, we use a wrapper-based approach optimizing both stability and predictability to compute the number of selected features. We use two large prospective studies (ADNI and the Portuguese Cognitive Complaints Cohort, CCC) to evaluate the approach and assess the predictive value of a large number of NPTs. Results The best subsets of features include approximately 30 and 20 (from the original 79 and 40) features, for ADNI and CCC data, respectively, yielding stability above 0.89 and 0.95, and AUC above 0.87 and 0.82. Most NPTs learnt using the proposed feature selection ensemble have been identified in the literature as strong predictors of conversion from MCI to AD. Conclusions The FS ensemble approach was able to 1) identify subsets of stable and relevant predictors from a consensus of multiple FS methods using baseline NPTs and 2) learn reliable prognostic models of conversion from MCI to AD using these subsets of features. The machine learning models learnt from these features outperformed the models trained without FS and achieved competitive results when compared to commonly used FS algorithms. Furthermore, the selected features are derived from a consensus of methods thus being more robust, while releasing users from choosing the most appropriate FS method to be used in their classification task.PTDC/EEI-SII/1937/2014; SFRH/BD/95846/2013; SFRH/BD/118872/2016info:eu-repo/semantics/publishedVersio