Simple Systematic Synthesis of Periodic Mesoporous Organosilica Nanoparticles with Adjustable Aspect Ratios

One-dimensional periodic mesoporous organosilica (PMO) nanoparticles with tunable aspect ratios are obtained from a chain-type molecular precursor octaethoxy-1,3,5-trisilapentane. The aspect ratio can be tuned from 2:1 to >20:1 simply by variation in the precursor concentration in acidic aqueous solutions containing constant amounts of triblock copolymer Pluronic P123. The mesochannels are highly ordered and are oriented parallel to the longitudinal axis of the PMO particles. No significant Si–C bond cleavage occurs during the synthesis according to29Si MAS NMR. The materials exhibit surface areas between 181 and 936 m2 g−1

Critical Role of CD2 Co-stimulation in Adaptive Natural Killer Cell Responses Revealed in NKG2C-Deficient Humans

Infection by human cytomegalovirus (HCMV) leads to NKG2C-driven expansion of adaptive natural killer (NK) cells, contributing to host defense. However, approximately 4% of all humans carry a homozygous deletion of the gene that encodes NKG2C ($\textit{NKG2C}^{-/-}$). Assessment of NK cell repertoires in 60 $\textit{NKG2C}^{-/-}$ donors revealed a broad range of NK cell populations displaying characteristic footprints of adaptive NK cells, including a terminally differentiated phenotype, functional reprogramming, and epigenetic remodeling of the interferon (IFN)-$\gamma$ promoter. We found that both NKG2C$^{-}$ and NKG2C$^{+}$ adaptive NK cells expressed high levels of CD2, which synergistically enhanced ERK and S6RP phosphorylation following CD16 ligation. Notably, CD2 co-stimulation was critical for the ability of adaptive NK cells to respond to antibody-coated target cells. These results reveal an unexpected redundancy in the human NK cell response to HCMV and suggest that CD2 provides "signal 2" in antibody-driven adaptive NK cell responses.This work was supported by grants from the Swedish Research Council, the Swedish Children’s Cancer Society, the Swedish Cancer Society, the Tobias Foundation, the Swedish Foundation for Strategic Research, the Karolinska Institutet, the Wenner-Gren Foundation, the Norwegian Cancer Society, the Norwegian Research Council, the South-Eastern Norway Regional Health Authority, and the KG Jebsen Center for Cancer Immunotherapy. J.T. and J.A.T. are supported by the MRC and the Welcome Trust with partial funding from the National Institute for Health Research Cambridge Biomedical Research Centre. V.B. is supported by the French National Research Agency (ANR) (grant no. NKIR-ANR-13-PDOC- 0025-01)

Remodeling of secretory lysosomes during education tunes functional potential in NK cells

Inhibitory signaling during natural killer (NK) cell education translates into increased responsiveness to activation; however, the intracellular mechanism for functional tuning by inhibitory receptors remains unclear. Secretory lysosomes are part of the acidic lysosomal compartment that mediates intracellular signalling in several cell types. Here we show that educated NK cells expressing self-MHC specific inhibitory killer cell immunoglobulin-like receptors (KIR) accumulate granzyme B in dense-core secretory lysosomes that converge close to the centrosome. This discrete morphological phenotype is independent of transcriptional programs that regulate effector function, metabolism and lysosomal biogenesis. Meanwhile, interference of signaling from acidic Ca2+ stores in primary NK cells reduces target-specific Ca2+-flux, degranulation and cytokine production. Furthermore, inhibition of PI(3,5)P2 synthesis, or genetic silencing of the PI(3,5)P2-regulated lysosomal Ca2+-channel TRPML1, leads to increased granzyme B and enhanced functional potential, thereby mimicking the educated state. These results indicate an intrinsic role for lysosomal remodeling in NK cell education

A computational framework for complex disease stratification from multiple large-scale datasets.

BACKGROUND: Multilevel data integration is becoming a major area of research in systems biology. Within this area, multi-'omics datasets on complex diseases are becoming more readily available and there is a need to set standards and good practices for integrated analysis of biological, clinical and environmental data. We present a framework to plan and generate single and multi-'omics signatures of disease states. METHODS: The framework is divided into four major steps: dataset subsetting, feature filtering, 'omics-based clustering and biomarker identification. RESULTS: We illustrate the usefulness of this framework by identifying potential patient clusters based on integrated multi-'omics signatures in a publicly available ovarian cystadenocarcinoma dataset. The analysis generated a higher number of stable and clinically relevant clusters than previously reported, and enabled the generation of predictive models of patient outcomes. CONCLUSIONS: This framework will help health researchers plan and perform multi-'omics big data analyses to generate hypotheses and make sense of their rich, diverse and ever growing datasets, to enable implementation of translational P4 medicine