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Antibody-secreting plasma cells (PCs) are generated in secondary lymphoid organs but are reported to reside in an emerging range of anatomical sites. Analysis of the transcriptome of different tissue-resident (Tr)PC populations revealed that they each have their own transcriptional signature indicative of functional adaptation to the host tissue environment. In contrast to expectation, all TrPCs were extremely long-lived, regardless of their organ of residence, with longevity influenced by intrinsic factors like the immunoglobulin isotype. Analysis at single-cell resolution revealed that the bone marrow is unique in housing a compendium of PCs generated all over the body that retain aspects of the transcriptional program indicative of their tissue of origin. This study reveals that extreme longevity is an intrinsic property of TrPCs whose transcriptome is imprinted by signals received both at the site of induction and within the tissue of residence.

AbstractQuantitative metal grade inversion based on hyperspectral data is an effective approach to achieve the real-time in situ determination of ore body grades and has the advantages of low cost compared with traditional chemical analysis methods. However, the redundant nature of hyperspectral data and the parameter-limiting nature of machine learning algorithms reduce the modeling accuracy and precision, resulting in severe limitations on the application of hyperspectral techniques for the grade inversion of Deerni copper ore bodies. In this paper, we first obtained visible-NIR hyperspectral data for 190 ore samples using a spectrometer and determined the copper content of the sample set using chemical analysis; then, we processed the raw hyperspectral data using three dimensionality reduction algorithms and optimized a BP neural network based on an evolutionary algorithm. Finally, a Deerni copper grade inversion model was established using the hyperspectral data before and after dimensionality reduction, and the inversion accuracy and precision was compared and analyzed with that obtained by the BP neural network, the random forest and the variable hidden layer nodes models. The combination of the LLE dimensionality reduction algorithm and the optimized BP neural network algorithm achieves the highest modeling precision, with an R2of 0.950.

Interleukin-(IL) 22 production by intestinal group 3 innate lymphoid cells (ILC3) is critical to maintain gut homeostasis. However, IL-22 needs to be tightly controlled; reduced IL-22 expression is associated with intestinal epithelial barrier defect while its overexpression promotes tumor development. Here, using a single cell RNAseq approach, we identified a core set of genes associated with increased IL-22 production by ILC3. Among these genes, Programmed cell death 1 (PD-1), extensively studied in the context of cancer and chronic infection, was constitutively expressed on a subset of ILC3. These cells, found in the crypt of the small intestine and colon, displayed superior capacity to produce IL-22. PD-1 expression on ILC3 was dependent on the microbiota and was induced during inflammation in response to IL-23 but, conversely, was reduced in the presence of Notch ligand. PD-1+ILC3 exhibited distinct metabolic activity with increased glycolytic, lipid and polyamine synthesis associated with augmented proliferation compared with their PD-1-counterparts. Further, PD-1+ILC3 showed increased expression of mitochondrial antioxidant proteins which enable the cells to maintain their levels of reactive oxygen species (ROS). Loss of PD-1 signaling in ILC3 led to reduced IL-22 production in a cell intrinsic manner. During inflammation, PD-1 expression was increased on NCR-ILC3 while deficiency in PD-1 expression resulted in increased susceptibility to experimental colitis and failure to maintain gut barrier integrity. Collectively, our findings uncover a new function of the PD-1 and highlight the role of PD-1 signaling in the maintenance of gut homeostasis mediated by ILC3 in mice.

In this paper, the real-time defects inspection was implemented via use of paralleled structure and high-speed operation of FPGA. The hardware circuit based on FPGA was established. According to signal characteristics of polymeric film defects, the preprocessing scheme of defect images based on FPGA was designed. The defect data were packed according to the defined format. Data processed were transferred to PC through USB2.0 real-timely to reconstruct defect microscopic images. The quantity of transferred data was decreased tremendously by this method. The inspecting speed was greatly improved.

Heteroatom-modified carbon-based catalysts (especially nitrogen-doped) have been reported to be effective in activating peroxymonosulfate (PMS). Nevertheless, here our study found that graphitized carbon nanomaterial (GC800) exhibited a similar catalytic capacity as the nitrogen-doped graphitized carbon nanomaterial (NGC800) in the degradation of bisphenol A (BPA) via activating PMS, however, the degradation rate constant of the former was approximately 1.72-times greater than that of the latter. Meanwhile, GC800 showed admirable versatility, wide application range of pH value and excellent stability. Furthermore, the connection between the difference in surface chemistry (surface functional groups, electronic properties) and reaction rate between GC800 and NGC800 was discussed. Quenching experiments combined with electron paramagnetic resonance (EPR) and electrochemical measurements revealed the existence of a multi-pathway synergy in GC800/PMS system dominated by the non-radical electron-transfer pathway and complemented by radical (O2•−)/non-radical (1O2) pathway. The high proportion of carbonyl groups and sp2-hybridized carbon as the main parameters affected the electron density of GC800 in the process of non-radical electron transfer. In contrast, NGC800/PMS system only followed the non-radical oxidation pathway with singlet oxygen being the predominant ROS. Pyrrolic N affected the non-radical oxidation pathway of NGC800. This work verifies the significant role of surface chemistry of carbon materials and the synergy between non-radical electron transfer and radical/non-radical oxidation on the catalytic velocity. And it presents a novel thought in the design of high-efficiency carbon-based catalysts toward green and sustainable ecological restoration.