Postmortem single-cell studies have transformed understanding of lower respiratory tract diseases (LRTDs), including coronavirus disease 2019 (COVID-19), but there are minimal data from African settings where HIV, malaria and other environmental exposures may affect disease pathobiology and treatment targets. In this study, we used histology and high-dimensional imaging to characterize fatal lung disease in Malawian adults with (n = 9) and without (n = 7) COVID-19, and we generated single-cell transcriptomics data from lung, blood and nasal cells. Data integration with other cohorts showed a conserved COVID-19 histopathological signature, driven by contrasting immune and inflammatory mechanisms: in US, European and Asian cohorts, by type I/III interferon (IFN) responses, particularly in blood-derived monocytes, and in the Malawian cohort, by response to IFN-γ in lung-resident macrophages. HIV status had minimal impact on histology or immunopathology. Our study provides a data resource and highlights the importance of studying the cellular mechanisms of disease in underrepresented populations, indicating shared and distinct targets for treatment.

The infective larvae of the helminth Heligmosomoides polygyrus bakeri migrate to the small intestine, invade the submucosa, and trigger granuloma formation around each parasite. Here, we employ spatial transcriptomics to elucidate the transcriptional intricacies and cell interactions in H. polygyrus- infected mice. We find a generalised reduction in expression of homeostatic genes such as Epcam , Pls1 (fimbrin) and Zg16 , while cell adhesion (eg Cldn3 , Cdh17 ) and immune-protective ( Pla2g4c ) loci are upregulated. Specific genes and cell types are associated with different spatial niches (lower crypt, upper crypt, villi and granuloma). Within the crypts, pathway analysis indicates activation of the osteopontin ( Spp1 ) and pleiotrophin ( Ptn ) pathways that are poorly represented in steady-state tissues, whilst Wnt signalling within the crypts is abrogated by day 7 of infection. Granulomas contain concentrations of myeloid cells, NK and dendritic cells, with high expression levels of genes linked to M2 macrophages ( Arg1 , Retlna , Fcer1g ) and wound repair pathways ( Reg3b and Mxra7 ) as well as elevated Tmbx4 that has not previously been noted. Analysis of potential ligand-receptor pairs confirmed a major complementarity between granuloma-localised SPP1 and CD44 receptors in both crypt and granuloma, as well as TGF-β/receptor interactions. Infected tissues also revealed abundant chemokine representation; among the latter category CCL6, CCL8 and MIF (macrophage migration inhibitory factor) dominated potential interactions. These results both enhance our understanding of the murine small intestine’s transcriptional landscape and also identify a new set of molecular interactions underpinning tissue-specific responses to infection that can be targeted for therapeutic intervention.

Factors governing the coagulopathy and pneumonitis associated with severe viral infections remain unresolved. We previously found that the expression of protein S (PROS1) is increased in lung epithelium of patients with mild COVID-19 as compared to severe COVID-19. We hypothesised that PROS1 may exert a local effect that protects the upper airway against severe inflammation by modulating epithelial and myeloid cell responses. To test this, in vitro air-interface cultures, seeded from primary healthy human lung epithelial cells, were infected with different SARS-CoV-2 clades. This model, validated by single-cell RNAseq analysis, recapitulated the dynamic cell-profile and pathogenic changes of COVID-19. We showed that PROS1 was located in the basal cells of healthy pseudostratified epithelium. During SARS-Cov-2 infection, PROS1 was released by basal cells, which was partially mediated by interferon. Transcriptome analysis showed that SARS-CoV-2 infection induced proinflammatory phenotypes (CXCL10/11 ^high , PTGS2 ^pos F3 ^high , S100A8/A9 ^high ) of basal and transitional cells. PROS1 strongly downregulated these cells and transformed the proinflammatory CXCL10/11 ^high basal cells into the regenerative S100A2 ^pos KRT ^high basal cell phenotype. In addition, SARS-CoV-2 infection elevated M-CSF secretion from epithelium, which induced MERTK, a receptor for PROS1, on monocytes added into 3D lung epithelial culture. We demonstrated that SARS-CoV-2 drives monocyte phenotypes expressing coagulation (F13A1) and complement (C1Ǫ) genes. PROS1 significantly downregulated these phenotypes and induced higher expression of MHC class II. Overall, this study demonstrated that the epithelium-derived PROS1 during SARS-CoV-2 infection inhibits the proinflammatory epithelial phenotypes, favours basal cell regeneration, and inhibits myeloid inflammation while enhancing antigen presentation. These findings highlight the importance of basal epithelial cells and PROS1 protection from viral infection induced severe lung pathology. Abstract Figure: 1) SARS-CoV2 infection of the epithelium results in release of IFN. 2) IFN secretion has an autocrine effect on epithelial cells 3) Infection and IFN cause release of PROS1 from the basal cells, as well as M-CSF from the epithelium 4) PROS1 acts on basal cells which express MERTK, a PROS1 receptor 5) PROS1 downregulated the proinflammatory phenotypes expanded by viral infection, while upregulating KRT ^high basal cells with repair phenotypes 6) The secreted M-CSF drives MERTK expression on monocytes in cocultures with epithelium. 7) PROS1 induces downregulation of monocyte clusters characteristic of viral infection that express pro-coagulation and complement genes, while upregulating clusters with higher MHC class II. 8) In summary, PROS1 mediates phenotypic switch of SARS-Cov2 induced pathogenic myeloid clusters with complement and coagulation phenotypes into phenotype with efficient antigen presentation, reduces proinflammatory activation of epithelium and induces epithelial barrier repair, resulting in mild COVID-19.

The rapid expansion of Internet of Things (IoT) technologies has highlighted the need for reliable intrusion detection systems (IDSs), yet the majority of existing studies rely on single-dataset evaluations, raising concerns about their real-world generalisation capability. This study addresses this limitation by systematically investigating distributional shift across heterogeneous IoT intrusion detection datasets and their impact on model behaviour. To achieve this, a unified feature space is constructed using BoT-IoT, ToN-IoT, and UNSW-NB15 datasets, followed by a comprehensive preprocessing pipeline including attack class alignment, distribution-preserving sampling for class imbalance, and feature selection based on cross-dataset feature value propagation analysis. Furthermore, feature-specific transformations and correlation-based dimensionality reduction are applied to enhance statistical consistency and model stability. To simulate realistic deployment scenarios, models are trained on combinations of datasets and evaluated on unseen datasets. The results reveal that distributional inconsistencies and dataset-specific feature biases significantly degrade cross-dataset performance, despite strong within-dataset results. The proposed framework provides a systematic understanding of feature-level behaviour across datasets, identifying both stable and bias-prone features. These findings highlight the necessity of distribution-aware preprocessing and feature analysis for developing robust and generalisable IoT intrusion detection systems.

Single-cell RNA sequencing (scRNAseq) of human tissues has expanded our understanding of the complexity of cellular subsets and their changes in disease. The availability of scRNAseq data in different tissues and disease states provides an opportunity to compare cellular subsets and identify common and unique cellular activation. In this study, we aimed to characterize shared and tissue-specific myeloid and stromal phenotypes and uncover key cellular subtypes involved in pathogenic tissue activation. We analyzed scRNAseq data from 14 public datasets, comprising heart, lung, skin, and synovium in both healthy and diseased states. Our analysis identified distinct and overlapping myeloid and stromal cell populations in these tissues. Despite significant inter-individual variability, we were able to identify both shared and disease-specific changes in these cell populations. These findings provide insights into the conserved and tissue-specific roles of myeloid and stromal cells in health and disease and contribute to a better understanding of tissue pathology and potential therapeutic targets.

Summary: Current rheumatoid arthritis (RA) treatments do not restore immune tolerance. Investigating dendritic cell (DC) populations in human synovial tissue (ST) may reveal pathways to re-instate tolerance in RA. With single-cell and spatial-transcriptomics of synovial tissue biopsies, validated by micro co-culture systems, we identified condition and niche-specific myeloid DC clusters with distinct differentiation trajectories and functions. Healthy synovium contains a unique tolerogenic AXL ^pos DC2 cluster in the superficial sublining layer. In active RA, a macrophage-rich lining-layer niche becomes populated with inflammatory DC3 clusters that specifically activate memory CCL5 ^pos TEM and CCL5 ^pos CXCL13 ^pos TPH, promoting synovitis. In the sublining lymphoid niche, CCR7 ^pos DC2 mReg specifically interact with naïve-T-cells, potentially driving the local expansion of new effector T-cells. Sustained remission sees the resolution of these niches but lacks the recovery of tolerogenic AXL ^pos DC2, indicating latent potential for disease flare. A human RA disease-flare model showed that the activation of blood predecessor of ST-DC3 clusters precedes the onset of inflammation in joints. Therapeutic strategies targeting pathogenic ST-DC3 clusters, or reinstating tolerogenic AXL ^pos DC2, may restore immune homeostasis in RA. In brief: Deconstruction of human RA synovium, using single-cell spatial transcriptomics and micro-culture systems, reveals distinct neighbourhoods within the synovial architecture across health, and RA patients with active disease or sustained remission. Discrete niches are identified that contain distinct myeloid DC clusters that differ in frequency, differentiation trajectories, and effector functions. Highlights: Human RA synovium exhibits condition and niche specific myeloid DC clusters that vary in their tissue differentiation trajectories and functions. ST-CD14 ^pos DC3 (iDC3) support inflammatory CCL5 ^pos TEM and CCL5 ^pos TPH cell activation in the hyperplastic lining layer. ST-CCR7 ^pos DC2 (mReg), driven by MIR155, interact with naïve-T-cells in sublining lymphoid niches. A specific inflammatory signature of blood predecessors of ST-DC3s predict flare in RA. Graphical