The role of desmoglein-2 in kidney disease

Desmosomes are multi-protein cell-cell adhesion structures supporting cell stability and mechanical stress resilience of tissues, best described in skin and heart. The kidney is exposed to various mechanical stimuli and stress, yet little is known about kidney desmosomes. In healthy kidneys, we found desmosomal proteins located at the apical-junctional complex in tubular epithelial cells. In four different animal models and patient biopsies with various kidney diseases, desmosomal components were significantly upregulated and partly miss-localized outside of the apical-junctional complexes along the whole lateral tubular epithelial cell membrane. The most upregulated component was desmoglein-2 (Dsg2). Mice with constitutive tubular epithelial cell-specific deletion of Dsg2 developed normally, and other desmosomal components were not altered in these mice. When challenged with different types of tubular epithelial cell injury (unilateral ureteral obstruction, ischemia-reperfusion, and 2,8-dihydroxyadenine crystal nephropathy), we found increased tubular epithelial cell apoptosis, proliferation, tubular atrophy, and inflammation compared to wild-type mice in all models and time points. In vitro, silencing DSG2 via siRNA weakened cell-cell adhesion in HK-2 cells and increased cell death. Thus, our data show a prominent upregulation of desmosomal components in tubular cells across species and diseases and suggest a protective role of Dsg2 against various injurious stimuli.

Harnessing Artificial Intelligence for Enhanced Renal Analysis: Automated Detection of Hydronephrosis and Precise Kidney Segmentation

Background and objective

Hydronephrosis is essential in the diagnosis of renal colic. We automated the detection of hydronephrosis from ultrasound images to standardize the therapy and reduce the misdiagnosis of renal colic.

Methods

Anonymously collected ultrasound images of human kidneys, both normal and hydronephrotic, were preprocessed for neural networks. Six "state of the art" models were trained and cross-validated for the detection of hydronephrosis, and two convolutional networks were used for kidney segmentation. In the testing phase, performance metrics included true positives, true negatives, false positives, false negatives, accuracy, and F1 score, while the evaluation of the segmentation task involved accuracy, precision, dice, jaccard, recall, and ASSD.

Key findings and limitations

A total of 523 sonographic kidney images (423 nonhydronephrotic and 100 hydronephrotic) were collected from three different ultrasound devices. After training on this dataset, all models were used to evaluate 200 new ultrasound kidney images (142 nonhydronephrotic and 58 hydronephrotic kidneys). The highest validation accuracy (98.5%) was achieved by the AlexNet model (GoogLeNet 97%, AlexNet_v2 96%, ResNet50 96%, ResNet101 97.5%, and ResNet152 95%). The deeplabv3_resnet50 and deeplabv3_resnet101 reached a dice coefficient of 94.74% and 94.48%, respectively, on the task of automated kidney segmentation. The study is limited by analyzing only hydronephrosis, but this specific focus enabled high detection accuracy.

Conclusions and clinical implications

We show that our automated ultrasound deep learning model can be trained and used to interpret and segmentate ultrasound images from different sources with high accuracy. This method will serve as an automated tool in the diagnostic algorithm of acute renal failure in the future.

Patient summary

Hydronephrosis is crucial in the diagnosis of renal colic. Recent advances in artificial intelligence allow automated detection of hydronephrosis in ultrasound images with high accuracy. These methods will help standardize the diagnosis and treatment renal colic.

Matrix Metalloproteinase-7 in Urinary Extracellular Vesicles Identifies Rapid Disease Progression in Autosomal Dominant Polycystic Kidney Disease

SIGNIFICANCE STATEMENT

There is an unmet need for biomarkers of disease progression in autosomal dominant polycystic kidney disease (ADPKD). This study investigated urinary extracellular vesicles (uEVs) as a source of such biomarkers. Proteomic analysis of uEVs identified matrix metalloproteinase 7 (MMP-7) as a biomarker predictive of rapid disease progression. In validation studies, MMP-7 was predictive in uEVs but not in whole urine, possibly because uEVs are primarily secreted by tubular epithelial cells. Indeed, single-nucleus RNA sequencing showed that MMP-7 was especially increased in proximal tubule and thick ascending limb cells, which were further characterized by a profibrotic phenotype. Together, these data suggest that MMP-7 is a biologically plausible and promising uEV biomarker for rapid disease progression in ADPKD.

BACKGROUND

In ADPKD, there is an unmet need for early markers of rapid disease progression to facilitate counseling and selection for kidney-protective therapy. Our aim was to identify markers for rapid disease progression in uEVs.

METHODS

Six paired case-control groups ( n =10-59/group) of cases with rapid disease progression and controls with stable disease were formed from two independent ADPKD cohorts, with matching by age, sex, total kidney volume, and genetic variant. Candidate uEV biomarkers were identified by mass spectrometry and further analyzed using immunoblotting and an ELISA. Single-nucleus RNA sequencing of healthy and ADPKD tissue was used to identify the cellular origin of the uEV biomarker.

RESULTS

In the discovery proteomics experiments, the protein abundance of MMP-7 was significantly higher in uEVs of patients with rapid disease progression compared with stable disease. In the validation groups, a significant >2-fold increase in uEV-MMP-7 in patients with rapid disease progression was confirmed using immunoblotting. By contrast, no significant difference in MMP-7 was found in whole urine using ELISA. Compared with healthy kidney tissue, ADPKD tissue had significantly higher MMP-7 expression in proximal tubule and thick ascending limb cells with a profibrotic phenotype.

CONCLUSIONS

Among patients with ADPKD, rapid disease progressors have higher uEV-associated MMP-7. Our findings also suggest that MMP-7 is a biologically plausible biomarker for more rapid disease progression.

Sublethal necroptosis signaling promotes inflammation and liver cancer

It is currently not well known how necroptosis and necroptosis responses manifest in vivo. Here, we uncovered a molecular switch facilitating reprogramming between two alternative modes of necroptosis signaling in hepatocytes, fundamentally affecting immune responses and hepatocarcinogenesis. Concomitant necrosome and NF-κB activation in hepatocytes, which physiologically express low concentrations of receptor-interacting kinase 3 (RIPK3), did not lead to immediate cell death but forced them into a prolonged "sublethal" state with leaky membranes, functioning as secretory cells that released specific chemokines including CCL20 and MCP-1. This triggered hepatic cell proliferation as well as activation of procarcinogenic monocyte-derived macrophage cell clusters, contributing to hepatocarcinogenesis. In contrast, necrosome activation in hepatocytes with inactive NF-κB-signaling caused an accelerated execution of necroptosis, limiting alarmin release, and thereby preventing inflammation and hepatocarcinogenesis. Consistently, intratumoral NF-κB-necroptosis signatures were associated with poor prognosis in human hepatocarcinogenesis. Therefore, pharmacological reprogramming between these distinct forms of necroptosis may represent a promising strategy against hepatocellular carcinoma.

MASI enables fast model-free standardization and integration of single-cell transcriptomics data

Single-cell transcriptomics datasets from the same anatomical sites generated by different research labs are becoming increasingly common. However, fast and computationally inexpensive tools for standardization of cell-type annotation and data integration are still needed in order to increase research inclusivity. To standardize cell-type annotation and integrate single-cell transcriptomics datasets, we have built a fast model-free integration method, named MASI (Marker-Assisted Standardization and Integration). We benchmark MASI with other well-established methods and demonstrate that MASI outperforms other methods, in terms of integration, annotation, and speed. To harness knowledge from single-cell atlases, we demonstrate three case studies that cover integration across biological conditions, surveyed participants, and research groups, respectively. Finally, we show MASI can annotate approximately one million cells on a personal laptop, making large-scale single-cell data integration more accessible. We envision that MASI can serve as a cheap computational alternative for the single-cell research community.

IL-6 in the infarcted heart is preferentially formed by fibroblasts and is modulated by purinergic signaling

Plasma IL-6 is elevated after myocardial infarction (MI) and is associated with increased morbidity and mortality. Which cardiac cell type preferentially contributes to IL-6 and how its production is regulated is largely unknown. Here, we studied the cellular source and purinergic regulation of IL-6 formation in a murine MI model. IL-6, measured in various cell types in post MI hearts by qPCR, RNAscope and at protein level, was preferentially formed by fibroblasts (CFs). scRNAseq in infarcted mouse and human hearts confirmed this finding. Adenosine stimulated fibroblast IL-6 formation via A2bR in a Gq-dependent manner. CFs highly expressed Adora2b, rapidly degraded extracellular ATP to AMP but lacked CD73. In mice and humans Adora2B was also mainly expressed by fibroblasts (scRNAseq). Global IL-6 formation was assessed in isolated hearts in mice lacking CD73 on T-cells (CD4CD73-/-) a condition known to be associated with adverse cardiac remodeling. The ischemia-induced release of IL-6 was strongly attenuated in CD4CD73-/- mice, suggesting adenosine-mediated modulation. Together this demonstrates that post-MI IL-6 is mainly derived from activated CFs and is controlled by T-cell derived adenosine. Purinergic metabolic cooperation between CFs and T-cells is a novel mechanism with therapeutic potential which modulates IL6 formation by the heart.

Single-nucleus RNA sequencing in ischemic cardiomyopathy reveals common transcriptional profile underlying end-stage heart failure

Ischemic cardiomyopathy (ICM) is the leading cause of heart failure worldwide, yet the cellular and molecular signature of this disease is largely unclear. Using single-nucleus RNA sequencing (snRNA-seq) and integrated computational analyses, we profile the transcriptomes of over 99,000 human cardiac nuclei from the non-infarct region of the left ventricle of 7 ICM transplant recipients and 8 non-failing (NF) controls. We find the cellular composition of the ischemic heart is significantly altered, with decreased cardiomyocytes and increased proportions of lymphatic, angiogenic, and arterial endothelial cells in patients with ICM. We show that there is increased LAMININ signaling from endothelial cells to other cell types in ICM compared with NF. Finally, we find that the transcriptional changes that occur in ICM are similar to those in hypertrophic and dilated cardiomyopathies and that the mining of these combined datasets can identify druggable genes that could be used to target end-stage heart failure.

Platelet-instructed SPP1+ macrophages drive myofibroblast activation in fibrosis in a CXCL4-dependent manner

Fibrosis represents the common end stage of chronic organ injury independent of the initial insult, destroying tissue architecture and driving organ failure. Here we discover a population of profibrotic macrophages marked by expression of Spp1, Fn1, and Arg1 (termed Spp1 macrophages), which expands after organ injury. Using an unbiased approach, we identify the chemokine (C-X-C motif) ligand 4 (CXCL4) to be among the top upregulated genes during profibrotic Spp1 macrophage differentiation. In vitro and in vivo studies show that loss of Cxcl4 abrogates profibrotic Spp1 macrophage differentiation and ameliorates fibrosis after both heart and kidney injury. Moreover, we find that platelets, the most abundant source of CXCL4 in vivo, drive profibrotic Spp1 macrophage differentiation. Single nuclear RNA sequencing with ligand-receptor interaction analysis reveals that macrophages orchestrate fibroblast activation via Spp1, Fn1, and Sema3 crosstalk. Finally, we confirm that Spp1 macrophages expand in both human chronic kidney disease and heart failure.

Targeting Immune-Fibroblast Crosstalk in Myocardial Infarction and Cardiac Fibrosis

Inflammation and tissue fibrosis co-exist and are causally linked to organ dysfunction. However, the molecular mechanisms driving immune-fibroblast crosstalk in human cardiac disease remains unexplored and there are currently no therapeutics to target fibrosis. Here, we performed multi-omic single-cell gene expression, epitope mapping, and chromatin accessibility profiling in 38 donors, acutely infarcted, and chronically failing human hearts. We identified a disease-associated fibroblast trajectory marked by cell surface expression of fibroblast activator protein (FAP), which diverged into distinct myofibroblasts and pro-fibrotic fibroblast populations, the latter resembling matrifibrocytes. Pro-fibrotic fibroblasts were transcriptionally similar to cancer associated fibroblasts and expressed high levels of collagens and periostin (POSTN), thymocyte differentiation antigen 1 (THY-1), and endothelin receptor A (EDNRA) predicted to be driven by a RUNX1 gene regulatory network. We assessed the applicability of experimental systems to model tissue fibrosis and demonstrated that 3 different in vivo mouse models of cardiac injury were superior compared to cultured human heart and dermal fibroblasts in recapitulating the human disease phenotype. Ligand-receptor analysis and spatial transcriptomics predicted that interactions between C-C chemokine receptor type 2 (CCR2) macrophages and fibroblasts mediated by interleukin 1 beta (IL-1β) signaling drove the emergence of pro-fibrotic fibroblasts within spatially defined niches. This concept was validated through in silico transcription factor perturbation and in vivo inhibition of IL-1β signaling in fibroblasts where we observed reduced pro-fibrotic fibroblasts, preferential differentiation of fibroblasts towards myofibroblasts, and reduced cardiac fibrosis. Herein, we show a subset of macrophages signal to fibroblasts via IL-1β and rewire their gene regulatory network and differentiation trajectory towards a pro-fibrotic fibroblast phenotype. These findings highlight the broader therapeutic potential of targeting inflammation to treat tissue fibrosis and restore organ function.

Fast model-free standardization and integration of single-cell transcriptomics data

Single-cell transcriptomics datasets from the same anatomical sites generated by different research labs are becoming increasingly common. However, fast and computationally inexpensive tools for standardization of cell-type annotation and data integration are still needed in order to increase research inclusivity. To standardize cell-type annotation and integrate single-cell transcriptomics datasets, we have built a fast model-free integration method, named MASI (Marker-Assisted Standardization and Integration). MASI first identifies putative cell-type markers from reference data through an ensemble approach. Then, it converts gene expression matrix to cell-type score matrix with the identified putative cell-type markers for the purpose of cell-type annotation and data integration. Because of integration through cell-type markers instead of model inference, MASI can annotate approximately one million cells on a personal laptop, which provides a cheap computational alternative for the single-cell community. We benchmark MASI with other well-established methods and demonstrate that MASI outperforms other methods based on speed. Its performance for both tasks of data integration and cell-type annotation are comparable or even superior to these existing methods. To harness knowledge from single-cell atlases, we demonstrate three case studies that cover integration across biological conditions, surveyed participants, and research groups, respectively.

Dissecting CD8+ T cell pathology of severe SARS-CoV-2 infection by single-cell immunoprofiling

Introduction

SARS-CoV-2 infection results in varying disease severity, ranging from asymptomatic infection to severe illness. A detailed understanding of the immune response to SARS-CoV-2 is critical to unravel the causative factors underlying differences in disease severity and to develop optimal vaccines against new SARS-CoV-2 variants.

Methods

We combined single-cell RNA and T cell receptor sequencing with CITE-seq antibodies to characterize the CD8⁺ T cell response to SARS-CoV-2 infection at high resolution and compared responses between mild and severe COVID-19.

Results

We observed increased CD8⁺ T cell exhaustion in severe SARS-CoV-2 infection and identified a population of NK-like, terminally differentiated CD8⁺ effector T cells characterized by expression of FCGR3A (encoding CD16). Further characterization of NK-like CD8⁺ T cells revealed heterogeneity among CD16⁺ NK-like CD8⁺ T cells and profound differences in cytotoxicity, exhaustion, and NK-like differentiation between mild and severe disease conditions.

Discussion

We propose a model in which differences in the surrounding inflammatory milieu lead to crucial differences in NK-like differentiation of CD8⁺ effector T cells, ultimately resulting in the appearance of NK-like CD8⁺ T cell populations of different functionality and pathogenicity. Our in-depth characterization of the CD8⁺ T cell-mediated response to SARS-CoV-2 infection provides a basis for further investigation of the importance of NK-like CD8⁺ T cells in COVID-19 severity.

Adult human kidney organoids originate from CD24+ cells and represent an advanced model for adult polycystic kidney disease

Adult kidney organoids have been described as strictly tubular epithelia and termed tubuloids. While the cellular origin of tubuloids has remained elusive, here we report that they originate from a distinct CD24+ epithelial subpopulation. Long-term-cultured CD24+ cell-derived tubuloids represent a functional human kidney tubule. We show that kidney tubuloids can be used to model the most common inherited kidney disease, namely autosomal dominant polycystic kidney disease (ADPKD), reconstituting the phenotypic hallmark of this disease with cyst formation. Single-cell RNA sequencing of CRISPR-Cas9 gene-edited PKD1- and PKD2-knockout tubuloids and human ADPKD and control tissue shows similarities in upregulation of disease-driving genes. Furthermore, in a proof of concept, we demonstrate that tolvaptan, the only approved drug for ADPKD, has a significant effect on cyst size in tubuloids but no effect on a pluripotent stem cell-derived model. Thus, tubuloids are derived from a tubular epithelial subpopulation and represent an advanced system for ADPKD disease modeling.

Single-nucleus profiling of human dilated and hypertrophic cardiomyopathy

Heart failure encompasses a heterogeneous set of clinical features that converge on impaired cardiac contractile function1,2 and presents a growing public health concern. Previous work has highlighted changes in both transcription and protein expression in failing hearts3,4, but may overlook molecular changes in less prevalent cell types. Here we identify extensive molecular alterations in failing hearts at single-cell resolution by performing single-nucleus RNA sequencing of nearly 600,000 nuclei in left ventricle samples from 11 hearts with dilated cardiomyopathy and 15 hearts with hypertrophic cardiomyopathy as well as 16 non-failing hearts. The transcriptional profiles of dilated or hypertrophic cardiomyopathy hearts broadly converged at the tissue and cell-type level. Further, a subset of hearts from patients with cardiomyopathy harbour a unique population of activated fibroblasts that is almost entirely absent from non-failing samples. We performed a CRISPR-knockout screen in primary human cardiac fibroblasts to evaluate this fibrotic cell state transition; knockout of genes associated with fibroblast transition resulted in a reduction of myofibroblast cell-state transition upon TGFβ1 stimulation for a subset of genes. Our results provide insights into the transcriptional diversity of the human heart in health and disease as well as new potential therapeutic targets and biomarkers for heart failure.

Dosimetric properties of thermoluminescent NaCl pellets from Khewra Salt Mines, Pakistan

Thermoluminescence (TL) and extended dosimetric characteristics of naturally occurring NaCl salt were studied. Pellets were prepared from mined crystalline salt obtained from Khewra salt mines, Pakistan and irradiated from 1 mGy to 10,000 mGy using Co-60 gamma source. The TL response showed two dominant peaks around 125 °C and 230 °C respectively at low doses, with an additional peak in between at doses beyond 300 mGy. A linear and supra-linear TL response was observed between 1 mGy-100 mGy and 100 mGy-10 Gy dose ranges respectively. During first 24 hours post irradiation, the TL intensity dropped by 20%. A maximum angular dependence of up to 50% was observed between 0 to 360°. For photon energies between 33 keV-1.25 MeV significant energy dependence was observed for photons <100 keV only. Sample sensitivity increased with dose a qualitatively similar behaviour to TLD-200. Zeff of the sample (14.6) was comparable to TLD-200 (16.3). No significant dose rate effects (deviation for a Co-60 source within 3.5%) on the TL sensitivity of the sample were found. The lowest detectable dose limit (LDDL) for salt sample was found to be 0.8 mGy whereas the sample reproducibility test showed a maximum of ±11% deviation from the first value.

Thermoluminescence (TL), kinetic parameters and dosimetric features of Pakistani limestone

Thermoluminescence (TL), kinetic parameters and dosimetric features of Pakistani limestone (CaCO₃) is reported in this study. Both compositional and structural analyses reveal that the material has a crystalline nature with rhombohedral structure and non-uniform crystallite size having major content of CaCO₃. A powdered limestone sample of 30 mg is found to be the optimized weight for TL and other dosimetric studies. After irradiating the samples with a test dose of 100 Gy using a β source three composite glow peaks termed as P1, P2 and P3 are visible at 100, 230 and 330 °C respectively using a linear heating rate of 1 °C/s during the TL readout. The Coefficient of Variation (COV) is found to be about 4%. Kinetic parameters (i.e., frequency factor (f), activation energy (E), and the kinetic order (b)) are estimated using both first and second Order of kinetics using an in-house Computerized Glow Curve Deconvolution (GCD) software. The figure-of-merit (FOM) is found to be 2.12%. The distribution of continuum traps with activation energy in the range of 0.77-2.59 eV is observed in the kinetic parameter analysis of the glow peaks of the sample. The TL response in the dose range of 1-5 Gy (not reported previously) and linearity in the dose response in the dose range of 1-10 Gy is observed in samples of Pakistani limestone. The Minimum Detectable Dose (MDD) is 1.01 Gy clearly resembling the experimentally linear fitted results. After a fading study for a period of thirty days, only the first peak i.e., P1 majorly fades while no major change is observed in the amplitude of peaks P2 and P3. In addition, P1 is the main contributor fading by 92% within the first 24 h of irradiation while P2 fades by 30 %. However, P3 shows stability with a very minor fading of 0.05% within 24 h of irradiation. This study concludes that Pakistani limestone can be further assessed as a potential radiation dosimeter for various applications.

Novel Ta/chitosan-doped CuO nanorods for catalytic purification of industrial wastewater and antimicrobial applications

Novel tantalum (Ta) and chitosan (CS)-doped CuO nanorods (NRs) were synthesized using a single step co-precipitation route. Different concentrations (2 and 4%) of Ta were used in fixed amounts of CS and CuO to examine their catalytic activity and antimicrobial potential. For critical analysis, synthesized NRs were systematically examined using XRD, FTIR HRTEM, EDS, UV-Vis and PL spectroscopy. The XRD technique revealed the monoclinic structure of CuO while an increase in its crystallite size (from 15.5 to 18.5 nm) was observed upon doping. FTIR spectra were examined to study the functional groups of CuO where peaks at 514 cm-1 and 603 cm-1 confirmed the formation of CuO NRs. PL spectra depicted the charge transfer efficiency of the synthesized samples. The presence of dopants (Ta and CS) and constituent elements (Cu, O) was detected using EDS spectra. Additionally, the pH based catalytic performance of fabricated NRs revealed 99.7% dye degradation of toxic methylene blue (MB) dye in neutral media, 99.4% in basic media and 99.5% in acidic media along with promising antibacterial activities for Gram negative/positive bacteria, respectively upon doping of Ta (4%) into CS/CuO. The adsorption energies of CuO co-doped with CS/Ta led to the creation of stable structures that were investigated theoretically using density functional theory.

Characteristics, reasons and patterns of Road Traffic Injuries presenting in emergency department of a tertiary care public hospital in Karachi

Objectives: To determine the main characteristics, reasons and patterns of road traffic injuries (RTIs) in a tertiary care public hospital of Karachi. Methods: It was a hospital based cross sectional study conducted in a public tertiary care hospital emergency department with a sample size 425 selected conveniently. Participants included the consenting victims or caretaking attendants of road traffic injuries (RTIs) from 25th May to 28th June in 2019. A structured questionnaire was developed after literature review and was translated into “Urdu” language. The questionnaire collected detailed information on socio-demographic characteristics, possible reasons of RTI’s such as condition of vehicle, over speeding and breaking traffic rules. Data was analyzed by using software SPSS version 20. Results: Almost half of RTI victims (43.1%) belonged to the age group 18-29. Majority of the victims were males (86.6%). The most common vehicle involved was motorbike (87.50%) followed by Rickshaw (6.8%) and Car (2.4%). Majority of RTIs occurred on main road (75.30%). The most common sites of injuries were lower limb (64%), upper limb (37.60%) and head (32.2%). The severe injuries were significantly more likely to happen in events in which direct collision with other vehicle/thing was involved, road conditions were wet and pedestrian were crossing the road. Conclusion: Motorbikes were involved in majority of RTIs. Main reasons of RTIs included irresponsible road behaviors including over-speeding, careless road crossing, breaking the signal and riding on wet roads which lead to moderate to severe injuries in almost two thirds of participants doi: https://doi.org/10.12669/pjms.38.4.4490 How to cite this:Muhammad K, Shaikh S, Ashraf J, Hayat S. Characteristics, reasons and patterns of Road Traffic Injuries presenting in emergency department of a tertiary care public hospital in Karachi. Pak J Med Sci. 2022;38(4):---------.  doi: https://doi.org/10.12669/pjms.38.4.4490 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

MACA: marker-based automatic cell-type annotation for single-cell expression data

SUMMARY

Accurately identifying cell types is a critical step in single-cell sequencing analyses. Here, we present marker-based automatic cell-type annotation (MACA), a new tool for annotating single-cell transcriptomics datasets. We developed MACA by testing four cell-type scoring methods with two public cell-marker databases as reference in six single-cell studies. MACA compares favorably to four existing marker-based cell-type annotation methods in terms of accuracy and speed. We show that MACA can annotate a large single-nuclei RNA-seq study in minutes on human hearts with ∼290K cells. MACA scales easily to large datasets and can broadly help experts to annotate cell types in single-cell transcriptomics datasets, and we envision MACA provides a new opportunity for integration and standardization of cell-type annotation across multiple datasets.

AVAILABILITY AND IMPLEMENTATION

MACA is written in python and released under GNU General Public License v3.0. The source code is available at https://github.com/ImXman/MACA.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Multiscale interactome analysis coupled with off-target drug predictions reveals drug repurposing candidates for human coronavirus disease

The COVID-19 pandemic has highlighted the urgent need for the identification of new antiviral drug therapies for a variety of diseases. COVID-19 is caused by infection with the human coronavirus SARS-CoV-2, while other related human coronaviruses cause diseases ranging from severe respiratory infections to the common cold. We developed a computational approach to identify new antiviral drug targets and repurpose clinically-relevant drug compounds for the treatment of a range of human coronavirus diseases. Our approach is based on graph convolutional networks (GCN) and involves multiscale host-virus interactome analysis coupled to off-target drug predictions. Cell-based experimental assessment reveals several clinically-relevant drug repurposing candidates predicted by the in silico analyses to have antiviral activity against human coronavirus infection. In particular, we identify the MET inhibitor capmatinib as having potent and broad antiviral activity against several coronaviruses in a MET-independent manner, as well as novel roles for host cell proteins such as IRAK1/4 in supporting human coronavirus infection, which can inform further drug discovery studies.

Optimized biotransformation of acid-treated water melon peel hydrolyzate into ethanol

Today, global focus of research is to explore the solution of energy crisis and environmental pollution. Like other agricultural countries, bulk quantities of watermelon peels (WMP) are disposed-off in environment as waste in Pakistan and appropriate management of this waste is the need of hour to save environment from pollution. The work emphasizes the role of ethanologenic yeasts to utilize significant sugars present in WMP for low-cost bioethanol fermentation. Dilute hydrochloric acid hydrolysis of WMP was carried out on optimized conditions employing RSM (response surface methodology) following central composite design (CCD). This experimental design is based on optimization of ethanologenesis involving some key independent parameters such as WMP hydrolysate and synthetic media ratio (X1), incubation temperature (X2) and incubation temperature (X3) for maximal ethanol yield exploiting standard (Saccharomyces cerevisiae K7) as well as experimental (Metchnikowia cibodasensisY34) yeasts. The results revealed that maximal ethanol yields obtained from S. cerevisiae K7 was 0.36±0.02 g/g of reducing sugars whereas M. cibodasensisY34, yielded 0.40±0.01 g ethanol/g of reducing sugars. The yeast isolate M. cibodasensisY34 appeared as promising ethanologen and embodies prospective potential for fermentative valorization of WMP-to-bioethanol.

Antiadhesion and antibiofilm potential of Fagonia indica from Cholistan desert against clinical multidrug resistant bacteria

High resistance to antimicrobials is associated with biofilm formation responsible for infectious microbes to withstand severe conditions. Therefore, new alternatives are necessary as biofilm inhibitors to control infections. In this study, the antimicrobial and antibiofilm activities of Fagonia indica extracts were evaluated against MDR clinical isolates. The extract exhibited its antibiofilm effect by altering adherence and disintegration of bacterial cell wall. Fagonia indica has antibacterial effect as minimum inhibitory concentration (MIC) values ranging from 125 to 500 µg mL-1 and minimum bactericidal concentration (MBC) value was 500-3000 µg mL-1 against multidrug resistant (MDR) clinical isolates. The extract exhibited its antibiofilm effect by altering adherence and disintegration of bacterial cell wall. Fagonia indica had antibacterial effect as minimum inhibitory concentration (MIC) values ranging from 125 to 500 µg mL-1 and minimum bactericidal concentration (MBC) value was 500-3000 µg mL-1 against MDR isolates. The maximum inhibitory effects of Fagonia indica chloroform extract on biofilm formation was observed on Staphylococcus aureus (71.84%) followed by Klebsiella pneumoniae (70.83%) after 48 hrs showing that inhibition is also time dependent. Our results about bacterial cell protein leakage indicated that MDR isolates treated with chloroform extract of Fagonia indica showed maximum protein leakage of K. pneumoniae (59.14 µg mL-1) followed by S. aureus (56.7 µg mL-1). Cell attachment assays indicated that chloroform extract resulted in a 43.5-53.5% inhibition of cell adherence to a polystyrene surface. Our results revealed that extracts of Fagonia indica significantly inhibited biofilm formation among MDR clinical isolates, therefore, could be applied as antimicrobial agents and cost effective biofilm inhibitor against these MDR isolates.

Novel Ag/cellulose-doped CeO2 quantum dots for efficient dye degradation and bactericidal activity with molecular docking study

In the present study, the novel Ag/cellulose nanocrystal (CNC)-doped CeO₂ quantum dots (QDs) with highly efficient catalytic performance were synthesized using one pot co-precipitation technique, which were then applied in the degradation of methylene blue and ciprofloxacin (MBCF) in wastewater. Catalytic activity against MBCF dye was significantly reduced (99.3%) for (4%) Ag dopant concentration in acidic medium. For Ag/CNC-doped CeO₂ vast inhibition domain of G-ve was significantly confirmed as (5.25-11.70 mm) and (7.15-13.60 mm), while medium- to high-concentration of CNC levels were calculated for G + ve (0.95 nm, 1.65 mm), respectively. Overall, (4%) Ag/CNC-doped CeO₂ revealed significant antimicrobial activity against G-ve relative to G + ve at both concentrations, respectively. Furthermore, in silico molecular docking studies were performed against selected enzyme targets dihydrofolate reductase (DHFR), dihydropteroate synthase (DHPS), and DNA gyrase belonging to folate and nucleic acid biosynthetic pathway, respectively to rationalize possible mechanism behind bactericidal potential of CNC-CeO₂ and Ag/CNC-CeO₂.

Thermoluminescence study of pellets prepared using NaCl from Khewra Salt Mines in Pakistan

In this study, the thermoluminescence characteristics of naturally occurring salt (NaCl) were assessed for the development of a radiation dosimeter. For this purpose, mined crystalline samples of salt were procured directly from Khewra salt mines in Pakistan. The samples were hand crushed, sieved, and compressed to pellets comparable in size to standard TLD chips, and irradiated to gamma radiation doses in the range of 5 mGy and 5000 mGy. Thermoluminescence (TL) response showed three main peaks in the glow curve around 115-130 °C, 150-170 °C, and 220-240 °C. A linear TL response was observed for the dose range of 5-100 mGy. The TL response became supra-linear for the dose ranges of 100-1000 mGy and 1000-5000 mGy. The T_m-T_stop method was applied to identify the overlapping peaks of the glow curve. Computerized glow curve deconvolution (CGCD) was then employed for the characterization of electron trap parameters such as frequency factor (s), activation energy (E), and the kinetic order (b), using General Order (GO) kinetics. The figure-of-merit (FOM) was found to be 1.08%, 0.94%, 0.77%, and 0.75%, at 500 mGy, 1 Gy, 2 Gy, and 5 Gy, respectively. The TL intensity faded by 20% within the first 24 h after irradiation and finally stabilized after two weeks. In addition, structural, morphological, and elemental analyses, were also performed using various analytical techniques. X-ray diffraction (XRD) showed that the salt crystallizes in a face-centered cubic structure. Scanning electron microscope (SEM) micrographs indicated that the crystallites are closely packed and cubic-shaped with non-uniform size, and mostly found in the agglomerated form. Similarly, the elemental analysis confirmed the presence of impurities such as Mg, Sr, S, K, O, and Ca, in the samples. The present study concludes that the pellets made from salt samples from Khewra mines have a potential for use as radiation dosimeters.

Integrative Analysis Reveals a Molecular Stratification of Systemic Autoimmune Diseases

OBJECTIVE

Clinical heterogeneity, a hallmark of systemic autoimmune diseases, impedes early diagnosis and effective treatment, issues that may be addressed if patients could be classified into groups defined by molecular pattern. This study was undertaken to identify molecular clusters for reclassifying systemic autoimmune diseases independently of clinical diagnosis.

METHODS

Unsupervised clustering of integrated whole blood transcriptome and methylome cross-sectional data on 955 patients with 7 systemic autoimmune diseases and 267 healthy controls was undertaken. In addition, an inception cohort was prospectively followed up for 6 or 14 months to validate the results and analyze whether or not cluster assignment changed over time.

RESULTS

Four clusters were identified and validated. Three were pathologic, representing "inflammatory," "lymphoid," and "interferon" patterns. Each included all diagnoses and was defined by genetic, clinical, serologic, and cellular features. A fourth cluster with no specific molecular pattern was associated with low disease activity and included healthy controls. A longitudinal and independent inception cohort showed a relapse-remission pattern, where patients remained in their pathologic cluster, moving only to the healthy one, thus showing that the molecular clusters remained stable over time and that single pathogenic molecular signatures characterized each individual patient.

CONCLUSION

Patients with systemic autoimmune diseases can be jointly stratified into 3 stable disease clusters with specific molecular patterns differentiating different molecular disease mechanisms. These results have important implications for future clinical trials and the study of nonresponse to therapy, marking a paradigm shift in our view of systemic autoimmune diseases.

Graphene Oxide-Doped MgO Nanostructures for Highly Efficient Dye Degradation and Bactericidal Action

Various concentrations (0.01, 0.03 and 0.05 wt ratios) of graphene oxide (GO) nanosheets were doped into magnesium oxide (MgO) nanostructures using chemical precipitation technique. The objective was to study the effect of GO dopant concentrations on the catalytic and antibacterial behavior of fixed amount of MgO. XRD technique revealed cubic phase of MgO, while its crystalline nature was confirmed through SAED profiles. Functional groups presence and Mg-O (443 cm-1) in fingerprint region was evident with FTIR spectroscopy. Optical properties were recorded via UV-visible spectroscopy with redshift pointing to a decrease in band gap energy from 5.0 to 4.8 eV upon doping. Electron-hole recombination behavior was examined through photoluminescence (PL) spectroscopy. Raman spectra exhibited D band (1338 cm-1) and G band (1598 cm-1) evident to GO doping. Formation of nanostructure with cubic and hexagon morphology was confirmed with TEM, whereas interlayer average d-spacing of 0.23 nm was assessed using HR-TEM. Dopants existence and evaluation of elemental constitution Mg, O were corroborated using EDS technique. Catalytic activity against methyl blue ciprofloxacin (MBCF) was significantly reduced (45%) for higher GO dopant concentration (0.05), whereas bactericidal activity of MgO against E. coli was improved significantly (4.85 mm inhibition zone) upon doping with higher concentration (0.05) of GO, owing to the formation of nanorods.

Clinical characteristic and epidemiological features of SARS CoV -2 disease patients from a COVID 19 designated Hospital in New Delhi

SARS CoV -2 infection is rapidly evolving as a serious global pandemic. The present study describes the clinical characteristics of SARS CoV-2 infection patients. The Samples were subjected to RT - PCR or Rapid Antigen test for diagnosis of SARS CoV- 2. A cohort of 3745 patients with confirmed diagnosis of SARS CoV -2 infection in a tertiary care center in New Delhi, India were included in this study. Data was collected from offline and online medical records over a period of six months. Amongst 3745 SARS CoV -2 infected patients, 2245 (60%) were symptomatic and 1500 (40%) were asymptomatic. Most common presenting symptom was cough (49.3%) followed febrile episodes (47.1%), breathlessness (42.7%) and sore throat (35.1%). Cough along with breathlessness (24.1) was the most common combination of symptoms followed by fever with cough (22.7). The most common comorbidity found among symptomatic group was diabetes (42.5%) followed by hypertension (21.4%) and chronic kidney disease (18%). Comorbidities like diabetes mellitus, chronic diseases of lungs, heart and kidneys were found to be common in symptomatic group and this was found to be statistically significant (p<0.05). COVID-19 is an evolving disease and data from our study help in understanding the clinic-epidemiological profile of patients. This article is protected by copyright. All rights reserved.

Myocyte-Specific Upregulation of ACE2 in Cardiovascular Disease: Implications for SARS-CoV-2-Mediated Myocarditis

Supplemental Digital Content is available in the text.

AB0176 RISK OF ANTI-CITRULLINATED PEPTIDE ANTIBODIES AND RHEUMATOID FACTOR IN MALE SMOKERS: DATA FROM KUWAIT REGISTRY FOR RHEUMATIC DISEASES (KRRD)

Background:

Smoking has been proposed to be associated with the development of anti-citrullinated peptide antibodies (ACPA) in rheumatoid arthritis (RA) patients.

Objectives:

To study the relationship between smoking and ACPA as well as smoking and RF in patients with RA in Kuwait Registry for Rheumatic Diseases (KRRD).

Methods:

Data on RA patients were extracted from KRRD from four major hospitals from February 2013 through December 2019. As females rarely smoke in Kuwait with a smoking prevalence of 3% in female RA patients in KRRD, females were excluded from the study population to reach the minimum statistical percentage needed to perform chi square test and assess the association between smoking and other variables. Statistical tests were applied where appropriate. Logistic regression was conducted to adjust for possible confounders including age, disease duration, comorbidities, family history of a rheumatic disease, ANA, treatment agents and disease activity and quality of life assessment tools.

Results:

A total of 863 RA male patients were studied with a mean age of 53.9±12.5 years and a mean disease duration 7.3±5.5 years. 652 (75.6%) had positive RF and 624 (72.3%) had positive ACPA. 431 (50%) had at least one comorbidity. 640 (74.2%) were on conventional disease modifying agents (cDMARD’s) and 223 (25.8%) were on biologic therapy. 183 (21.2%) were smokers. After adjustment of other factors, logistic regression showed that smokers were significantly different than non-smokers in terms of a positive ACPA (β=-1.051,p<0.001, odds=4.019) and a positive RF (β=-0.804,p=0.019, odds=2.517).

Conclusion:

Smokers have a higher risk of expressing a positive RF and a positive ACPA in a male population. Smoking should be considered as a possible risk factor for RA and efforts should be done to educate the population to cease smoking to possibly lower that risk.

References:

[1]Benowitz, N.L., 2009. Pharmacology of nicotine: addiction, smoking-induced disease, and therapeutics. Annual review of pharmacology and toxicology, 49, pp.57-71.

[2]Firestein, G.S., 2003. Evolving concepts of rheumatoid arthritis. Nature, 423(6937), p.356.

[3]Heliövaara, M., Aho, K., Aromaa, A., Knekt, P. and Reunanen, A., 1993. Smoking and risk of rheumatoid arthritis. The Journal of rheumatology, 20(11), pp.1830-1835.

[4]Hoy, K. W., 2009. Quantitative Research in Education: A Primer. SAGE. pp. 69-86.

[5]Kerlan-Candon, S., Combe, B., Vincent, R., Clot, J., Pinet, V. and Eliaou, J.F., 2001. HLA-DRB1 gene transcripts in rheumatoid arthritis. Clinical & Experimental Immunology, 124(1), pp.142-149.

[6]Kuada, J., 2012. Research Methodology: A Project Guide for University Students. Samfundslitteratur. pp. 45-56.

[7]Kumar, R., 2010. Research Methodology: A Step-by-Step Guide for Beginners. SAGE. pp. 148-159.

[8]Masdottir, B., Jonsson, T., Manfreðsdóttir, V., Víkingsson, A., Brekkan, Á. and Valdimarsson, H., 2000. Smoking, rheumatoid factor isotypes and severity of rheumatoid arthritis. Rheumatology, 39(11), pp.1202-1205.

[9]Neuman, W., 2009. Understanding research. Boston: Pearson. pp. 230- 255.

Disclosure of Interests:

None declared

THU0556 MISSING DATA AND MULTIPLE IMPUTATION IN RHEUMATOID ARTHRITIS REGISTRIES USING SEQUENTIAL RANDOM FOREST METHOD

Background:

Missing data in clinical epidemiological researches violate the intention to treat principle,

reduce statistical power and can induce bias if they are related to patient’s response to treatment. In multiple imputation (MI), covariates are included in the imputation equation to predict the values of missing data.

Objectives:

To find the best approach to estimate and impute the missing values in Kuwait Registry for Rheumatic Diseases (KRRD) patients data.

Methods:

A number of methods were implemented for dealing with missing data. These includedMultivariate imputation by chained equations(MICE),K-Nearest Neighbors(KNN),Bayesian Principal Component Analysis(BPCA),EM with Bootstrapping(Amelia II),Sequential Random Forest(MissForest) and mean imputation. Choosing the best imputation method was

judged by the minimum scores ofRoot Mean Square Error(RMSE),Mean Absolute Error(MAE) and

Kolmogorov–Smirnov D test statistic(KS) between the imputed datapoints and the original datapoints that were subsequently sat to missing.

Results:

A total of 1,685 rheumatoid arthritis (RA) patients and 10,613 hospital visits were included in the registry. Among them, we found a number of variables that had missing values exceeding 5% of the total values. These included duration of RA (13.0%), smoking history (26.3%), rheumatoid factor (7.93%), anti-citrullinated peptide antibodies (20.5%), anti-nuclear antibodies (20.4%), sicca symptoms (19.2%), family history of a rheumatic disease (28.5%), steroid therapy (5.94%), ESR (5.16%), CRP (22.9%) and SDAI (38.0%), The results showed that among the methods used, MissForest gave the highest level of accuracy to estimate the missing values. It had the least imputation errors for both continuous and categorical variables at each frequency of missingness and it had the smallest prediction differences when the models used imputed laboratory values. In both data sets, MICE had the second least imputation errors and prediction differences, followed by KNN and mean imputation.

Conclusion:

MissForest is a highly accurate method of imputation for missing data in KRRD and outperforms other common imputation techniques in terms of imputation error and maintenance of predictive ability with imputed values in clinical predictive models. This approach can be used in registries to improve the accuracy of data, including the ones for rheumatoid arthritis patients.

References:

[1]Junninen, H.; Niska, H.; Tuppurainen, K.; Ruuskanen, J.; Kolehmainen, M. Methods for imputation of

missing values in air quality data sets.Atmospheric Environment2004,38, 2895–2907.

[2]Norazian, M.N.; Shukri, Y.A.; Azam, R.N.; Al Bakri, A.M.M. Estimation of missing values in air pollution

data using single imputation techniques.ScienceAsia2008,34, 341–345.

[3]Plaia, A.; Bondi, A. Single imputation method of missing values in environmental pollution data sets.

Atmospheric Environment2006,40, 7316–7330.

[4]Kabir, G.; Tesfamariam, S.; Hemsing, J.; Sadiq, R. Handling incomplete and missing data in water network

database using imputation methods.Sustainable and Resilient Infrastructure2019, pp. 1–13.

[5]Di Zio, M.; Guarnera, U.; Luzi, O. Imputation through finite Gaussian mixture models.Computational

Statistics & Data Analysis2007,51, 5305–5316.

Disclosure of Interests:

None declared

Myocyte Specific Upregulation of ACE2 in Cardiovascular Disease: Implications for SARS-CoV-2 mediated myocarditis

Coronavirus disease 2019 (COVID-19) is a global pandemic caused by a novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). SARS-CoV-2 infection of host cells occurs predominantly via binding of the viral surface spike protein to the human angiotensin-converting enzyme 2 (ACE2) receptor. Hypertension and pre-existing cardiovascular disease are risk factors for morbidity from COVID-19, and it remains uncertain whether the use of angiotensin converting enzyme inhibitors (ACEi) or angiotensin receptor blockers (ARB) impacts infection and disease. Here, we aim to shed light on this question by assessing ACE2 expression in normal and diseased human myocardial samples profiled by bulk and single nucleus RNA-seq.

Mechanistic insights into cancer cell killing through interaction of phosphodiesterase 3A and schlafen family member 12

Cytotoxic molecules can kill cancer cells by disrupting critical cellular processes or by inducing novel activities. 6-(4-(Diethylamino)-3-nitrophenyl)-5-methyl-4,5-dihydropyridazin-3(2H)-one (DNMDP) is a small molecule that kills cancer cells by generation of novel activity. DNMDP induces complex formation between phosphodiesterase 3A (PDE3A) and schlafen family member 12 (SLFN12) and specifically kills cancer cells expressing elevated levels of these two proteins. Here, we examined the characteristics and covariates of the cancer cell response to DNMDP. On average, the sensitivity of human cancer cell lines to DNMDP is correlated with PDE3A expression levels. However, DNMDP could also bind the related protein, PDE3B, and PDE3B supported DNMDP sensitivity in the absence of PDE3A expression. Although inhibition of PDE3A catalytic activity did not account for DNMDP sensitivity, we found that expression of the catalytic domain of PDE3A in cancer cells lacking PDE3A is sufficient to confer sensitivity to DNMDP, and substitutions in the PDE3A active site abolish compound binding. Moreover, a genome-wide CRISPR screen identified the aryl hydrocarbon receptor-interacting protein (AIP), a co-chaperone protein, as required for response to DNMDP. We determined that AIP is also required for PDE3A-SLFN12 complex formation. Our results provide mechanistic insights into how DNMDP induces PDE3A-SLFN12 complex formation, thereby killing cancer cells with high levels of PDE3A and SLFN12 expression.

Evaluation of colorectal cancer subtypes and cell lines using deep learning

Colorectal cancer (CRC) is a common cancer with a high mortality rate and a rising incidence rate in the developed world. Molecular profiling techniques have been used to better understand the variability between tumors and disease models such as cell lines. To maximize the translatability and clinical relevance of in vitro studies, the selection of optimal cancer models is imperative. We have developed a deep learning-based method to measure the similarity between CRC tumors and disease models such as cancer cell lines. Our method efficiently leverages multiomics data sets containing copy number alterations, gene expression, and point mutations and learns latent factors that describe data in lower dimensions. These latent factors represent the patterns that are clinically relevant and explain the variability of molecular profiles across tumors and cell lines. Using these, we propose refined CRC subtypes and provide best-matching cell lines to different subtypes. These findings are relevant to patient stratification and selection of cell lines for early-stage drug discovery pipelines, biomarker discovery, and target identification.

P2837Day-case complex left atrial ablation is safe and cost-effective: experience from a UK tertiary centre

Background

Day-case standard catheter ablation is becoming routine. However, patients having complex left atrial ablation for atrial fibrillation (AF) or left atrial tachycardia (LAT) often stay overnight. We have been performing day-case complex left atrial ablation since 2015.

Purpose

To evaluate the safety, efficacy and cost-effectiveness of day-case complex left atrial ablation compared with those who stayed overnight.

Methods

A retrospective analysis of all consecutive complex left atrial ablations performed in a UK tertiary cardiac centre between 2010–2018. Data were collected on baseline parameters, procedure details including mapping technique, ablation strategy, immediate efficacy, and acute complications.

Results

A total of 830 complex left atrial catheter ablations were performed; mean age±SD=60±12 years, 63% male. The majority were AF ablation (n=804, 96.9%), with the rest being LAT/left-atrial flutter. Of the AF cases, 545 were paroxysmal (≤7 days), 212 persistent (>7 days) and 47 long-standing (>1yr); 98% of cases were elective. Pulmonary vein isolation was performed in all; additional LA lines were done in 163, CTI ablation in 129 and CFAEs in 33. 3D-mapping (Carto/Precision)=44.7% (with contact sensing=38.0%), PVAC=18.7%, PVI cryo-balloon=36.6%. Of the cohort 331 (39.9%) were done as day-case. Acute success= 94.9%, acute complications=4.58% (femoral site complications, n=12; pericardial effusion, n=19 (9 needing drain); stroke/cerebral embolus, n=3; phrenic nerve palsy, n=5; first degree heart block, n=1). Comparison of day-case vs non day-case revealed no significant difference in number of complications (Table 1). An overnight stay at out hospital costs £350. During the period of study our institution saved £115.850 (∼140,000 euros).

Day-case vs non day-case ablation Parameters Day-case (n=331) Non day-case (n=499) p-value Mean age ± SD (years) 61.2±11.6 59.1±11.9 0.009 Males (n, %) 205 (61.9%) 321 (64.3%) 0.484 Normal heart (n, %) 243 (73.4%) 383 (76.8%) 0.276 Paroxysmal AF (n, %) 218 (65.9%) 327 (65.5%) 0.928 Fluoroscopy time (mins) 23.8±13.9 27.0±14.5 0.001 Procedure time (mins) 150±89.6 163±68.2 0.025 % with 3D-mapping 30.8% 56.9% <0.001 Acute complications (n, %) 12 (3.63%) 26 (5.21%) 0.285

Conclusions

Day-case complex left atrial cardiac ablation is safe and effective. It is associated with good clinical outcomes and leads to significant cost savings as an overnight stay is not needed.

P5975Diminished LV systolic velocity on tissue Doppler imaging is linked to an amplified risk of lethal arrhythmias independently of LV ejection fraction

Background

Life threatening arrhythmias (LTA) can trigger sudden cardiac death, or provoke implantable cardioverter defibrillator (ICD) discharges that escalate morbidity and mortality. Longitudinal myofibrils predominate in the subendocardium which is uniquely sensitive to arrhythmogenic triggers.

Objectives

To test the hypothesis that mitral annular systolic velocity (S'), a tissue Doppler index of LV long-axis systolic function, might predict lethal arrhythmias irrespective of LVEF.

Methods

We analysed data from diverse ICD and cardiac resynchronization therapy defibrillator (CRT-D) patients at 2 London centres. Channelopathies were excluded. S' was averaged from medial and lateral mitral annuli velocities. Primary outcome was time to sustained ventricular tachycardia (VT) or fibrillation (VF) needing device therapy.

Results

In 302 patients (mean age 68 years, LVEF 32%, 77% male, 52% ischemic, 35% primary prevention, and 53% CRT-D), median S' was 5.1 (IQR: 4.0–6.2) cm/s and lower in CRT-D than ICD subjects. After a median follow-up of 15 months, 56 (19%) subjects had LTA and those who did had a lower S' than those who did not (4.6±1.4 cm/s vs. 5.4±1.7 cm/s, P=0.003-Fig A). Each 1cm/s lower S' correlated to a 43% increased risk of LTA (HR: 0.70, 95% CI: 0.57–0.87, P=0.001) independently of age, gender, β-blocker use, centre, ICD use and LVEF. Adding S' to the baseline model improved net reclassification (P=0.02) implying incremental utility (Fig B). An S' ≤5.6cm/s was the best cut-off, conferring a 2.4-fold higher LTA risk than an S'>5.6 cm/s (95% CI: 1.17–4.37, P=0.02–Fig C).

Conclusion

A lower S' forecasts an enhanced probability of LTA in cardiac device recipients irrespective of LVEF, and could be used to titrate medical, device and ablative therapies to mitigate future arrhythmic risk.

P6561Diagnostic yield of implantable loop recorders: a comparison of arrhythmia nurse specialists versus clinicians

Background

Implantable loop recorders (ILR) are recommended in guidelines to determine symptom-rhythm correlation. Arrhythmia Nurse Specialists (ANS) play a critical role in the assessment of such patients. Their effectiveness at risk stratification for ILR implantation is unknown. The ESC 2018 Syncope guidelines recommend more research in this field.

Aim

To evaluate the diagnostic yield of consecutive ILR implants at a tertiary centre over a 2year period and compare ANS versus Clinicians.

Methods

A retrospective study of all patients undergoing ILR implant between April 2016 and April 2018. Data collected included baseline patient demographics, referral source and management changes made by ILR findings.

Results

305 patients had an ILR; median age was 71yrs (interquartile range 52–81), 55% male. Median follow-up time was 15months. Referrals were from general cardiology (GC) = 98 (32%), electrophysiology (EP) = 105 (34%), and ANS-led syncope clinic = 102 (34%). Indications for ILR implant were syncope = 203 (65.9%), palpitation = 21 (6.9%), pre-syncope = 16 (5.2%), cryptogenic stroke = 35 (11.5%) and others 7 (8.9%) (falls, channelopathies). Of the entire cohort, 102 (34.0%) experienced arrhythmias recorded on the ILR that resulted in a change of management. This included: pacemaker implant = 49 (16.1%), complex-device implant = 7 (2.3%), AF=28 (9.2%), SVT=14 (4.6%), VT=1 (0.3%). Of those with a syncope indication (n=203), findings on ILR altered management in 73patients (36.0%) over a median follow-up of 18months; a pacing indication in this syncope group was present in 44 (21.9%) patients (median time to diagnosis: 2.7 months) with 24 receiving a pacemaker indication within 3 months of ILR insertion. ANS had a higher pacemaker implant rate. Overall, an ILR resulted in a diagnostic yield of 34.1% (n=104). Specialist nurse referral resulted in an overall greater trend towards change of management in 38.2% of patients compared with GC (32.7%) and EP (31.0%) (p=0.593 nurse vs. consultant).

Conclusion

The overall diagnostic yield of ILR insertion was 34% in our study. ANS had a trend towards a greater diagnostic yield compared with clinicians, and significantly more pacemaker indications. Our data suggests that ANS patient selection for ILR insertion are at least comparable to clinicians.

Abnormalities of age-related T cell senescence in Parkinson's disease

BACKGROUND

A wealth of evidence implicates both central and peripheral immune changes as contributing to the pathogenesis of Parkinson's disease (PD). It is critical to better understand this aspect of PD given that it is a tractable target for disease-modifying therapy. Age-related changes are known to occur in the immune system (immunosenescence) and might be of particular relevance in PD given that its prevalence rises with increasing age. We therefore sought to investigate this with respect to T cell replicative senescence, a key immune component of human ageing.

METHODS

Peripheral blood mononuclear cells were extracted from blood samples from 41 patients with mild PD (Hoehn and Yahr stages 1-2, mean (SD) disease duration 4.3 (1.2) years) and 41 age- and gender-matched controls. Immunophenotyping was performed with flow cytometry using markers of T lymphocyte activation and senescence (CD3, CD4, CD8, HLA-DR, CD38, CD28, CCR7, CD45RA, CD57, CD31). Cytomegalovirus (CMV) serology was measured given its proposed relevance in driving T cell senescence.

RESULTS

Markers of replicative senescence in the CD8+ population were strikingly reduced in PD cases versus controls (reduced CD57 expression (p = 0.005), reduced percentage of 'late differentiated' CD57_loCD28_hi cells (p = 0.007) and 'TEMRA' cells (p = 0.042)), whilst expression of activation markers (CD28) was increased (p = 0.005). This was not driven by differences in CMV seropositivity. No significant changes were observed in the CD4 population.

CONCLUSIONS

This study demonstrates for the first time that the peripheral immune profile in PD is distinctly atypical for an older population, with a lack of the CD8+ T cell replicative senescence which characterises normal ageing. This suggests that 'abnormal' immune ageing may contribute to the development of PD, and markers of T cell senescence warrant further investigation as potential biomarkers in this condition.

Is foliar spray of proline sufficient for mitigation of salt stress in Brassica juncea cultivars?

The effects of foliar application of proline (20 mM) on growth, physio-biochemical, and yield parameters were assessed in two Brassica juncea (L.) Czern & Coss cultivars, namely, Varuna and RH-30, at different levels (2.8, 4.2, or 5.6 dsm(-1)) of NaCl in soil. At 29 days after sowing (DAS), plants were sprayed with either 20 mM proline or water in the presence or absence of NaCl stress. The NaCl negatively affected parameters related to growth, photosynthesis, and yield in both varieties but more in RH-30 than in Varuna. Exogenous application of proline counteracted the effects of salt stress in Varuna only, by increasing the antioxidative capacity of the plants. Moreover, proline was not effective in alleviating the detrimental effects of higher salt concentrations on the studied parameters. Proline application to unstressed plants increased growth, photosynthesis, and yield parameters in both varieties; however, the effects were more prominent in Varuna than in RH-30.

Comprehensive Molecular Portraits of Invasive Lobular Breast Cancer

Invasive lobular carcinoma (ILC) is the second most prevalent histologic subtype of invasive breast cancer. Here, we comprehensively profiled 817 breast tumors, including 127 ILC, 490 ductal (IDC), and 88 mixed IDC/ILC. Besides E-cadherin loss, the best known ILC genetic hallmark, we identified mutations targeting PTEN, TBX3, and FOXA1 as ILC enriched features. PTEN loss associated with increased AKT phosphorylation, which was highest in ILC among all breast cancer subtypes. Spatially clustered FOXA1 mutations correlated with increased FOXA1 expression and activity. Conversely, GATA3 mutations and high expression characterized luminal A IDC, suggesting differential modulation of ER activity in ILC and IDC. Proliferation and immune-related signatures determined three ILC transcriptional subtypes associated with survival differences. Mixed IDC/ILC cases were molecularly classified as ILC-like and IDC-like revealing no true hybrid features. This multidimensional molecular atlas sheds new light on the genetic bases of ILC and provides potential clinical options.

Inclusion of dyad-repeat pattern improves topology prediction of transmembrane β-barrel proteins

: Accurate topology prediction of transmembrane β-barrels is still an open question. Here, we present BOCTOPUS2, an improved topology prediction method for transmembrane β-barrels that can also identify the barrel domain, predict the topology and identify the orientation of residues in transmembrane β-strands. The major novelty of BOCTOPUS2 is the use of the dyad-repeat pattern of lipid and pore facing residues observed in transmembrane β-barrels. In a cross-validation test on a benchmark set of 42 proteins, BOCTOPUS2 predicts the correct topology in 69% of the proteins, an improvement of more than 10% over the best earlier method (BOCTOPUS) and in addition, it produces significantly fewer erroneous predictions on non-transmembrane β-barrel proteins.

AVAILABILITY AND IMPLEMENTATION

BOCTOPUS2 webserver along with full dataset and source code is available at http://boctopus.bioinfo.se/

CONTACT

: arne@bioinfo.se

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Automated retinal vessel recognition and measurements on large datasets

The characteristics of the retinal vascular network have been prospectively associated with many systemic and vascular diseases. QUARTZ is a fully automated software that has been developed to localize and quantify the morphological characteristics of blood vessels in retinal images for use in epidemiological studies. This software was used to analyse a dataset containing 16,000 retinal images from the EPIC-Norfolk cohort study. The objective of this paper is to both assess the suitability of this dataset for computational analysis and to further evaluate the QUARTZ software.