Conquering the cytokine storm in COVID-19-induced ARDS using placenta-derived decidua stromal cells

Acute respiratory distress syndrome (ARDS) is the most common cause of death in COVID-19 patients. The cytokine storm is the main driver of the severity and magnitude of ARDS. Placenta-derived decidua stromal cells (DSCs) have a stronger immunosuppressive effect than other sources of mesenchymal stromal cells. Safety and efficacy study included 10 patients with a median age of 50 (range 14–68) years with COVID-19-induced ARDS. DSCs were administered 1–2 times at a dose of 1 × 10⁶/kg. End points were safety and efficacy by survival, oxygenation and effects on levels of cytokines. Oxygenation levels increased from a median of 80.5% (range 69–88) to 95% (range 78–99) (p = 0.012), and pulmonary infiltrates disappeared in all patients. Levels of IL-6 decreased from a median of 69.3 (range 35.0–253.4) to 11 (range 4.0–38.3) pg/ml (p = 0.018), and CRP decreased from 69 (range 5–169) to 6 (range 2–31) mg/ml (p = 0.028). Two patients died, one of a myocardial infarction and the other of multiple organ failure, diagnosed before the DSC therapy. The other patients recovered and left the intensive care unit (ICU) within a median of 6 (range 3–12) days. DSC therapy is safe and capable of improving oxygenation, decreasing inflammatory cytokine level and clearing pulmonary infiltrates in patients with COVID-19.     

Glioma IL13Rα2 Is Associated with Mesenchymal Signature Gene Expression and Poor Patient Prognosis

A major challenge for successful immunotherapy against glioma is the identification and characterization of validated targets. We have taken a bioinformatics approach towards understanding the biological context of IL-13 receptor α2 (IL13Rα2) expression in brain tumors, and its functional significance for patient survival. Querying multiple gene expression databases, we show that IL13Rα2 expression increases with glioma malignancy grade, and expression for high-grade tumors is bimodal, with approximately 58% of WHO grade IV gliomas over-expressing this receptor. By several measures, IL13Rα2 expression in patient samples and low-passage primary glioma lines most consistently correlates with the expression of signature genes defining mesenchymal subclass tumors and negatively correlates with proneural signature genes as defined by two studies. Positive associations were also noted with proliferative signature genes, whereas no consistent associations were found with either classical or neural signature genes. Probing the potential functional consequences of this mesenchymal association through IPA analysis suggests that IL13Rα2 expression is associated with activation of proinflammatory and immune pathways characteristic of mesenchymal subclass tumors. In addition, survival analyses indicate that IL13Rα2 over-expression is associated with poor patient prognosis, a single gene correlation ranking IL13Rα2 in the top ~1% of total gene expression probes with regard to survival association with WHO IV gliomas. This study better defines the functional consequences of IL13Rα2 expression by demonstrating association with mesenchymal signature gene expression and poor patient prognosis. It thus highlights the utility of IL13Rα2 as a therapeutic target, and helps define patient populations most likely to respond to immunotherapy in present and future clinical trials.     

Unusually High Occurrence of Drug Reactions with Nafcillin

Five patients seen during a two-month period who developed untoward systemic reactions following high dose intravenous administration of nafcillin are described. Recovery was complete upon discontinuation of the drug. The clustering of these cases and the high incidence (5 of 5) of side effects are highly unusual, and suggest that the frequency of nafcillin reactions might be higher than previously suspected.     

The Role of Programmed Cell Death Ligand-1 (PD-L1/CD274) in the Development of Graft versus Host Disease

Programmed cell death ligand-1 (PD-L1/CD274) is an immunomodulatory molecule involved in cancer and complications of bone marrow transplantation, such as graft rejection and graft-versus-host disease. The present study was designed to assess the dynamic expression of this molecule after hematopoietic stem cell transplantation in relation to acute graft-versus-host disease. Female BALB/c mice were conditioned with busulfan and cyclophosphamide and transplanted with either syngeneic or allogeneic (male C57BL/6 mice) bone marrow and splenic cells. The expression of PD-L1 was evaluated at different time points employing qPCR, western blot and immunohistochemistry. Allogeneic- but not syngeneic-transplanted animals exhibited a marked up-regulation of PD-L1 expression in the muscle and kidney, but not the liver, at days 5 and 7 post transplantation. In mice transplanted with allogeneic bone marrow cells, the enhanced expression of PD-L1 was associated with high serum levels of IFNγ and TNFα at corresponding intervals. Our findings demonstrate that PD-L1 is differently induced and expressed after allogeneic transplantation than it is after syngeneic transplantation, and that it is in favor of target rather than non-target organs at the early stages of acute graft-versus-host disease. This is the first study to correlate the dynamics of PD-L1 at the gene-, protein- and activity levels with the early development of acute graft-versus-host disease. Our results suggest that the higher expression of PD-L1 in the muscle and kidney (non-target tissues) plays a protective role in skeletal muscle during acute graft-versus-host disease.     

Plant–Microbe Symbiosis: What Has Proteomics Taught Us?

Beneficial microbes have a positive impact on the productivity and fitness of the host plant. A better understanding of the biological impacts and underlying mechanisms by which the host derives these benefits will help to address concerns around global food production and security. The recent development of omics‐based technologies has broadened our understanding of the molecular aspects of beneficial plant–microbe symbiosis. Specifically, proteomics has led to the identification and characterization of several novel symbiosis‐specific and symbiosis‐related proteins and post‐translational modifications that play a critical role in mediating symbiotic plant–microbe interactions and have helped assess the underlying molecular aspects of the symbiotic relationship. Integration of proteomic data with other “omics” data can provide valuable information to assess hypotheses regarding the underlying mechanism of symbiosis and help define the factors affecting the outcome of symbiosis. Herein, an update is provided on the current and potential applications of symbiosis‐based “omic” approaches to dissect different aspects of symbiotic plant interactions. The application of proteomics, metaproteomics, and secretomics as enabling approaches for the functional analysis of plant‐associated microbial communities is also discussed.     

Monitoring depth of anesthesia using combination of EEG measure and hemodynamic variables

Monitoring depth of anesthesia (DOA) via vital signs is a major ongoing challenge for anesthetists. A number of electroencephalogram (EEG)-based monitors such as the Bispectral (BIS) index have been proposed. However, anesthesia is related to central and autonomic nervous system functions whereas the EEG signal originates only from the central nervous system. This paper proposes an automated DOA detection system which consists of three steps. Initially, we introduce multiscale modified permutation entropy index which is robust in the characterization of the burst suppression pattern and combine multiscale information. This index quantifies the amount of complexity in EEG data and is computationally efficient, conceptually simple and artifact resistant. Then, autonomic nervous system activity is quantified with heart rate and mean arterial pressure which are easily acquired using routine monitoring machine. Finally, the extracted features are used as input to a linear discriminate analyzer (LDA). The method is validated with data obtained from 25 patients during the cardiac surgery requiring cardiopulmonary bypass. The experimental results indicate that an overall accuracy of 89.4 % can be obtained using combination of EEG measure and hemodynamic variables, together with LDA to classify the vital sign into awake, light, surgical and deep anesthetised states. The results demonstrate that the proposed method can estimate DOA more effectively than the commercial BIS index with a stronger artifact-resistance.