73 research outputs found

    Behaviour-aware Malware Classification: Dynamic Feature Selection

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    Despite the continued advancements in security research, malware persists as being a major threat in this digital age. Malware detection is a primary defence strategy for most networks but the identification of malware strains is becoming increasingly difficult. Reliable identification is based upon characteristic features being detectable within an object. However, the limitations and expense of current malware feature extraction methods is significantly hindering this process. In this paper, we present a new method for identifying malware based on behavioural feature extraction. Our proposed method has been evaluated using seven classification methods whilst analysing 2,068 malware samples from eight different families. The results achieved thus far have demonstrated promising improvements over existing approaches

    Secular trend, seasonality and effects of a community-based intervention on neonatal mortality: follow-up of a cluster-randomised trial in Quang Ninh province, Vietnam.

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    BACKGROUND: Little is know about whether the effects of community engagement interventions for child survival in low-income and middle-income settings are sustained. Seasonal variation and secular trend may blur the data. Neonatal mortality was reduced in a cluster-randomised trial in Vietnam where laywomen facilitated groups composed of local stakeholders employing a problem-solving approach for 3 years. In this analysis, we aim at disentangling the secular trend, the seasonal variation and the effect of the intervention on neonatal mortality during and after the trial. METHODS: In Quang Ninh province, 44 communes were allocated to intervention and 46 to control. Births and neonatal deaths were assessed in a baseline survey in 2005, monitored during the trial in 2008-2011 and followed up by a survey in 2014. Time series analyses were performed on monthly neonatal mortality data. RESULTS: There were 30 187 live births and 480 neonatal deaths. The intervention reduced the neonatal mortality from 19.1 to 11.6 per 1000 live births. The reduction was sustained 3 years after the trial. The control areas reached a similar level at the time of follow-up. Time series decomposition analysis revealed a downward trend in the intervention areas during the trial that was not found in the control areas. Neonatal mortality peaked in the hot and wet summers. CONCLUSIONS: A community engagement intervention resulted in a lower neonatal mortality rate that was sustained but not further reduced after the end of the trial. When decomposing time series of neonatal mortality, a clear downward trend was demonstrated in intervention but not in control areas. TRIAL REGISTRATION NUMBER: ISRCTN44599712, Post-results

    CD33 Expression on Peripheral Blood Monocytes Predicts Efficacy of Anti-PD-1 Immunotherapy Against Non-Small Cell Lung Cancer

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    Non-small cell lung carcinoma (NSCLC) is the leading cause of cancer-related deaths globally. Immune checkpoint blockade (ICB) has transformed cancer medicine, with anti-programmed cell death protein 1 (anti-PD-1) therapy now well-utilized for treating NSCLC. Still, not all patients with NSCLC respond positively to anti-PD-1 therapy, and some patients acquire resistance to treatment. There remains an urgent need to find markers predictive of anti-PD-1 responsiveness. To this end, we performed mass cytometry on peripheral blood mononuclear cells from 26 patients with NSCLC during anti-PD-1 treatment. Patients who responded to anti-PD-1 ICB displayed significantly higher levels of antigen-presenting myeloid cells, including CD9+ nonclassical monocytes, and CD33hi classical monocytes. Using matched pre-post treatment samples, we found that the baseline pre-treatment frequencies of CD33hi monocytes predicted patient responsiveness to anti-PD-1 therapy. Moreover, some of these classical and nonclassical monocyte subsets were associated with reduced immunosuppression by T regulatory (CD4+FOXP3+CD25+) cells in the same patients. Our use of machine learning corroborated the association of specific monocyte markers with responsiveness to ICB. Our work provides a high-dimensional profile of monocytes in NSCLC and links CD33 expression on monocytes with anti-PD-1 effectiveness in patients with NSCLC

    Identification of an Early Unipotent Neutrophil Progenitor with Pro-tumoral Activity in Mouse and Human Bone Marrow

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    Neutrophils are short-lived cells that play important roles in both health and disease. Neutrophils and monocytes originate from the granulocyte monocyte progenitor (GMP) in bone marrow; however, unipotent neutrophil progenitors are not well defined. Here, we use cytometry by time of flight (CyTOF) and single-cell RNA sequencing (scRNA-seq) methodologies to identify a committed unipotent early-stage neutrophil progenitor (NeP) in adult mouse bone marrow. Importantly, we found a similar unipotent NeP (hNeP) in human bone marrow. Both NeP and hNeP generate only neutrophils. NeP and hNeP both significantly increase tumor growth when transferred into murine cancer models, including a humanized mouse model. hNeP are present in the blood of treatment-naive melanoma patients but not of healthy subjects. hNeP can be readily identified by flow cytometry and could be used as a biomarker for early cancer discovery. Understanding the biology of hNeP should allow the development of new therapeutic targets for neutrophil-related diseases, including cancer

    Single-cell immune profiling reveals long-term changes in myeloid cells and identifies a novel subset of CD9(+) monocytes associated with COVID-19 hospitalization

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    Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can result in severe immune dysfunction, hospitalization, and death. Many patients also develop long-COVID-19, experiencing symptoms months after infection. Although significant progress has been made in understanding the immune response to acute SARS-CoV-2 infection, gaps remain in our knowledge of how innate immunity influences disease kinetics and severity. We hypothesized that cytometry by time-of-flight analysis of PBMCs from healthy and infected subjects would identify novel cell surface markers and innate immune cell subsets associated with COVID-19 severity. In this pursuit, we identified monocyte and dendritic cell subsets that changed in frequency during acute SARS-CoV-2 infection and correlated with clinical parameters of disease severity. Subsets of nonclassical monocytes decreased in frequency in hospitalized subjects, yet increased in the most severe patients and positively correlated with clinical values associated with worse disease severity. CD9, CD163, PDL1, and PDL2 expression significantly increased in hospitalized subjects, and CD9 and 6-Sulfo LacNac emerged as the markers that best distinguished monocyte subsets amongst all subjects. CD9+ monocytes remained elevated, whereas nonclassical monocytes remained decreased, in the blood of hospitalized subjects at 3-4 months postinfection. Finally, we found that CD9+ monocytes functionally released more IL-8 and MCP-1 after LPS stimulation. This study identifies new monocyte subsets present in the blood of COVID-19 patients that correlate with disease severity, and links CD9+ monocytes to COVID-19 progression

    Human CD79b<sup>+</sup> neutrophils in the blood are associated with early-stage melanoma.

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    PurposeDue to their abundance in the blood, low RNA content, and short lifespan, neutrophils have been classically considered to be one homogenous pool. However, recent work has found that mature neutrophils and neutrophil progenitors are composed of unique subsets exhibiting context-dependent functions. In this study, we ask if neutrophil heterogeneity is associated with melanoma incidence and/or disease stage.Experimental designUsing mass cytometry, we profiled melanoma patient blood for unique cell surface markers among neutrophils. Markers were tested for their predictiveness using flow cytometry data and random forest machine learning.ResultsWe identified CD79b+ neutrophils (CD3-CD56-CD19-Siglec8-CD203c-CD86LoCD66b+CD79b+) that are normally restricted to the bone marrow in healthy humans but appear in the blood of subjects with early-stage melanoma. Further, we found CD79b+ neutrophils present in tumors of subjects with head and neck cancer. AI-mediated machine learning analysis of neutrophils from subjects with melanoma confirmed that CD79b expression among peripheral blood neutrophils is highly important in identifying melanoma incidence. We noted that CD79b+ neutrophils possessed a neutrophilic appearance but have transcriptional and surface-marker phenotypes reminiscent of B cells. Compared to remaining blood neutrophils, CD79b+ neutrophils are primed for NETosis, express higher levels of antigen presentation-related proteins, and have an increased capacity for phagocytosis.ConclusionOur work suggests that CD79b+ neutrophils are associated with early-stage melanoma

    Genetic Rearrangements Can Modify Chromatin Features at Epialleles

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    Analogous to genetically distinct alleles, epialleles represent heritable states of different gene expression from sequence-identical genes. Alleles and epialleles both contribute to phenotypic heterogeneity. While alleles originate from mutation and recombination, the source of epialleles is less well understood. We analyze active and inactive epialleles that were found at a transgenic insert with a selectable marker gene in Arabidopsis. Both converse expression states are stably transmitted to progeny. The silent epiallele was previously shown to change its state upon loss-of-function of trans-acting regulators and drug treatments. We analyzed the composition of the epialleles, their chromatin features, their nuclear localization, transcripts, and homologous small RNA. After mutagenesis by T-DNA transformation of plants carrying the silent epiallele, we found new active alleles. These switches were associated with different, larger or smaller, and non-overlapping deletions or rearrangements in the 3′ regions of the epiallele. These cis-mutations caused different degrees of gene expression stability depending on the nature of the sequence alteration, the consequences for transcription and transcripts, and the resulting chromatin organization upstream. This illustrates a tight dependence of epigenetic regulation on local structures and indicates that sequence alterations can cause epigenetic changes at some distance in regions not directly affected by the mutation. Similar effects may also be involved in gene expression and chromatin changes in the vicinity of transposon insertions or excisions, recombination events, or DNA repair processes and could contribute to the origin of new epialleles
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