Whole blood transcriptional responses of very preterm infants during late-onset sepsis

Background Host immune responses during late-onset sepsis (LOS) in very preterm infants are poorly characterised due to a complex and dynamic pathophysiology and challenges in working with small available blood volumes. We present here an unbiased transcriptomic analysis of whole peripheral blood from very preterm infants at the time of LOS. Methods RNA-Seq was performed on peripheral blood samples (6–29 days postnatal age) taken at the time of suspected LOS from very preterm infants <30 weeks gestational age. Infants were classified based on blood culture positivity and elevated C-reactive protein concentrations as having confirmed LOS (n = 5), possible LOS (n = 4) or no LOS (n = 9). Bioinformatics and statistical analyses performed included pathway over-representation and protein-protein interaction network analyses. Plasma cytokine immunoassays were performed to validate differentially expressed cytokine pathways. Results The blood leukocyte transcriptional responses of infants with confirmed LOS differed significantly from infants without LOS (1,317 differentially expressed genes). However, infants with possible LOS could not be distinguished from infants with no LOS or confirmed LOS. Transcriptional alterations associated with LOS included genes involved in pathogen recognition (mainly TLR pathways), cytokine signalling (both pro-inflammatory and inhibitory responses), immune and haematological regulation (including cell death pathways), and metabolism (altered cholesterol biosynthesis). At the transcriptional-level cytokine responses during LOS were characterised by over-representation of IFN-α/β, IFN-γ, IL-1 and IL-6 signalling pathways and up-regulation of genes for inflammatory responses. Infants with confirmed LOS had significantly higher levels of IL-1α and IL-6 in their plasma. Conclusions Blood responses in very preterm infants with LOS are characterised by altered host immune responses that appear to reflect unbalanced immuno-metabolic homeostasis

Sirocco: cost-effective fine-grain distributed shared memory

Software fine-grain distributed shared memory (FGDSM) provides a simplified shared-memory programming interface with minimal or no hardware support. Originally software FGDSMs targeted uniprocessor-node parallel machines. This paper presents Sirocco, a family of software FGDSMs implemented on a network of low-cost SMPs. Sirocco takes full advantage of SMP nodes by implementing inter-node sharing directly in hardware and overlapping computation with protocol execution. To maintain correct shared-memory semantics, however SMP nodes require mechanisms to guarantee atomic coherence operations. Multiple SMP processors may also result in contention for shared resources and reduce performance. SMP nodes also impact the cost trade-off. While SMPs typically charge higher price-premiums, for a given system size SMP nodes substantially reduce networking hardware requirement as compared to uniprocessor nodes. In this paper, we ask the question “Are SMPs cost-effective building blocks for software FGDSM?” We present experimental measurements on Sirocco implementations ranging from an all-software system to a system with minimal hardware support. Together with simple cost models we show that low-cost SMP nodes: (i) result in competitive performance with uniprocessor nodes, (ii) substantially reduce hardware requirement and are more cost- effective than uniprocessor nodes, (iii) significantly benefit from hardware support for coherence operations, and (iv) are especially beneficial for FGDSMs with high-overhead coherence operation

Comparison of Psychological Distress between Type 2 Diabetes Patients with and without Proteinuria

We investigated the link between proteinuria and psychological distress among patients with type 2 diabetes mellitus (T2DM). A total of 130 patients with T2DM aged 69.1±10.3 years were enrolled in this cross-sectional study. Urine and blood parameters, age, height, body weight, and medications were analyzed, and each patient’s psychological distress was measured using the six-item Kessler Psychological Distress Scale (K6). We compared the K6 scores between the patients with and without proteinuria. Forty-two patients (32.3%) had proteinuria (≥±) and the level of HbA1c was 7.5±1.3%. The K6 scores of the patients with proteinuria were significantly higher than those of the patients without proteinuria even after adjusting for age and sex. The clinical impact of proteinuria rather than age, sex and HbA1c was demonstrated by a multiple regression analysis. Proteinuria was closely associated with higher psychological distress. Preventing and improving proteinuria may reduce psychological distress in patients with T2DM

Mechanisms for cooperative shared memory

This paper explores the complexity of implementing directory protocols by examining their mechanisms - primitive operations on directories, caches, and network interfaces. We compare the following protocols: Dir1B, Dir4B, Dir4NB, DirnNB, Dir1SW and an improved version of Dir1SW (Dir1SW+). The comparison shows that the mechanisms and mechanism sequencing of Dir1SW and Dir1SW+ are simpler than those for other protocols. We also compare protocol performance by running eight benchmarks on 32 processor systems. Simulations show that Dir1SW+'s performance is comparable to more complex directory protocols. The significant disparity in hardware complexity and the small difference in performance argue that Dir1SW+ may be a more effective use of resources. The small performance difference is attributable to two factors: the low degree of sharing in the benchmarks and Check-In/Check-Out (CICO) directives

Predicting sepsis severity at first clinical presentation:The role of endotypes and mechanistic signatures

BACKGROUND: Inter-individual variability during sepsis limits appropriate triage of patients. Identifying, at first clinical presentation, gene expression signatures that predict subsequent severity will allow clinicians to identify the most at-risk groups of patients and enable appropriate antibiotic use. METHODS: Blood RNA-Seq and clinical data were collected from 348 patients in four emergency rooms (ER) and one intensive-care-unit (ICU), and 44 healthy controls. Gene expression profiles were analyzed using machine learning and data mining to identify clinically relevant gene signatures reflecting disease severity, organ dysfunction, mortality, and specific endotypes/mechanisms. FINDINGS: Gene expression signatures were obtained that predicted severity/organ dysfunction and mortality in both ER and ICU patients with accuracy/AUC of 77–80%. Network analysis revealed these signatures formed a coherent biological program, with specific but overlapping mechanisms/pathways. Given the heterogeneity of sepsis, we asked if patients could be assorted into discrete groups with distinct mechanisms (endotypes) and varying severity. Patients with early sepsis could be stratified into five distinct and novel mechanistic endotypes, named Neutrophilic-Suppressive/NPS, Inflammatory/INF, Innate-Host-Defense/IHD, Interferon/IFN, and Adaptive/ADA, each based on ∼200 unique gene expression differences, and distinct pathways/mechanisms (e.g., IL6/STAT3 in NPS). Endotypes had varying overall severity with two severe (NPS/INF) and one relatively benign (ADA) groupings, consistent with reanalysis of previous endotype studies. A 40 gene-classification tool (accuracy=96%) and several gene-pairs (accuracy=89–97%) accurately predicted endotype status in both ER and ICU validation cohorts. INTERPRETATION: The severity and endotype signatures indicate that distinct immune signatures precede the onset of severe sepsis and lethality, providing a method to triage early sepsis patients

Log-based architectures for general-purpose monitoring of deployed code

Runtime monitoring tools are invaluable for detecting various types of bugs, in both sequential and multi-threaded programs. However, these tools often slow down the monitored program by an order of magnitude or more [4], implying that the tools are ill-suited for always-on monitoring of deployed code. Fortunately, the emergence of chip multiprocessors as a dominant computing platform means that resources are available on-chip to assist in monitoring tasks. In this brief note, we advocate Log-Based Architectures (LBA) that exploit such on-chip resources in order to dramatically reduce the overhead of runtime program monitoring. Specifically, we propose adding hardware support for logging a main program's trace and delivering it to another (otherwise idle) processing core for inspection. A life-guard program running on this other core executes the desired monitoring task

Preparing for Life: Plasma Proteome Changes and Immune System Development During the First Week of Human Life.

Neonates have heightened susceptibility to infections. The biological mechanisms are incompletely understood but thought to be related to age-specific adaptations in immunity due to resource constraints during immune system development and growth. We present here an extended analysis of our proteomics study of peripheral blood-plasma from a study of healthy full-term newborns delivered vaginally, collected at the day of birth and on day of life (DOL) 1, 3, or 7, to cover the first week of life. The plasma proteome was characterized by LC-MS using our established 96-well plate format plasma proteomics platform. We found increasing acute phase proteins and a reduction of respective inhibitors on DOL1. Focusing on the complement system, we found increased plasma concentrations of all major components of the classical complement pathway and the membrane attack complex (MAC) from birth onward, except C7 which seems to have near adult levels at birth. In contrast, components of the lectin and alternative complement pathways mainly decreased. A comparison to whole blood messenger RNA (mRNA) levels enabled characterization of mRNA and protein levels in parallel, and for 23 of the 30 monitored complement proteins, the whole blood transcript information by itself was not reflective of the plasma protein levels or dynamics during the first week of life. Analysis of immunoglobulin (Ig) mRNA and protein levels revealed that IgM levels and synthesis increased, while the plasma concentrations of maternally transferred IgG1-4 decreased in accordance with their in vivo half-lives. The neonatal plasma ratio of IgG1 to IgG2-4 was increased compared to adult values, demonstrating a highly efficient IgG1 transplacental transfer process. Partial compensation for maternal IgG degradation was achieved by endogenous synthesis of the IgG1 subtype which increased with DOL. The findings were validated in a geographically distinct cohort, demonstrating a consistent developmental trajectory of the newborn's immune system over the first week of human life across continents. Our findings indicate that the classical complement pathway is central for newborn immunity and our approach to characterize the plasma proteome in parallel with the transcriptome will provide crucial insight in immune ontogeny and inform new approaches to prevent and treat diseases