An immune cell atlas reveals the dynamics of human macrophage specification during prenatal development.

Macrophages are heterogeneous and play critical roles in development and disease, but their diversity, function, and specification remain inadequately understood during human development. We generated a single-cell RNA sequencing map of the dynamics of human macrophage specification from PCW 4-26 across 19 tissues. We identified a microglia-like population and a proangiogenic population in 15 macrophage subtypes. Microglia-like cells, molecularly and morphologically similar to microglia in the CNS, are present in the fetal epidermis, testicle, and heart. They are the major immune population in the early epidermis, exhibit a polarized distribution along the dorsal-lateral-ventral axis, and interact with neural crest cells, modulating their differentiation along the melanocyte lineage. Through spatial and differentiation trajectory analysis, we also showed that proangiogenic macrophages are perivascular across fetal organs and likely yolk-sac-derived as microglia. Our study provides a comprehensive map of the heterogeneity and developmental dynamics of human macrophages and unravels their diverse functions during development.

Host-Viral Infection Maps Reveal Signatures of Severe COVID-19 Patients.

Viruses are a constant threat to global health as highlighted by the current COVID-19 pandemic. Currently, lack of data underlying how the human host interacts with viruses, including the SARS-CoV-2 virus, limits effective therapeutic intervention. We introduce Viral-Track, a computational method that globally scans unmapped single-cell RNA sequencing (scRNA-seq) data for the presence of viral RNA, enabling transcriptional cell sorting of infected versus bystander cells. We demonstrate the sensitivity and specificity of Viral-Track to systematically detect viruses from multiple models of infection, including hepatitis B virus, in an unsupervised manner. Applying Viral-Track to bronchoalveloar-lavage samples from severe and mild COVID-19 patients reveals a dramatic impact of the virus on the immune system of severe patients compared to mild cases. Viral-Track detects an unexpected co-infection of the human metapneumovirus, present mainly in monocytes perturbed in type-I interferon (IFN)-signaling. Viral-Track provides a robust technology for dissecting the mechanisms of viral-infection and pathology.

Dysfunctional CD8 T Cells Form a Proliferative, Dynamically Regulated Compartment within Human Melanoma.

Tumor immune cell compositions play a major role in response to immunotherapy, but the heterogeneity and dynamics of immune infiltrates in human cancer lesions remain poorly characterized. Here, we identify conserved intratumoral CD4 and CD8 T cell behaviors in scRNA-seq data from 25 melanoma patients. We discover a large population of CD8 T cells showing continuous progression from an early effector "transitional" into a dysfunctional T cell state. CD8 T cells that express a complete cytotoxic gene set are rare, and TCR sharing data suggest their independence from the transitional and dysfunctional cell states. Notably, we demonstrate that dysfunctional T cells are the major intratumoral proliferating immune cell compartment and that the intensity of the dysfunctional signature is associated with tumor reactivity. Our data demonstrate that CD8 T cells previously defined as exhausted are in fact a highly proliferating, clonal, and dynamically differentiating cell population within the human tumor microenvironment.

The CD8+ T cell tolerance checkpoint triggers a distinct differentiation state defined by protein translation defects.

Peripheral CD8+ T cell tolerance is a checkpoint in both autoimmune disease and anti-cancer immunity. Despite its importance, the relationship between tolerance-induced states and other CD8+ T cell differentiation states remains unclear. Using flow cytometric phenotyping, single-cell RNA sequencing (scRNA-seq), and chromatin accessibility profiling, we demonstrated that in vivo peripheral tolerance to a self-antigen triggered a fundamentally distinct differentiation state separate from exhaustion, memory, and functional effector cells but analogous to cells defectively primed against tumors. Tolerant cells diverged early and progressively from effector cells, adopting a transcriptionally and epigenetically distinct state within 60 h of antigen encounter. Breaching tolerance required the synergistic actions of strong T cell receptor (TCR) signaling and inflammation, which cooperatively induced gene modules that enhanced protein translation. Weak TCR signaling during bystander infection failed to breach tolerance due to the uncoupling of effector gene expression from protein translation. Thus, tolerance engages a distinct differentiation trajectory enforced by protein translation defects.

Cxcl10+ monocytes define a pathogenic subset in the central nervous system during autoimmune neuroinflammation.

Multiple sclerosis (MS) is characterized by pathological inflammation that results from the recruitment of lymphoid and myeloid immune cells from the blood into the brain. Due to subset heterogeneity, defining the functional roles of the various cell subsets in acute and chronic stages of MS has been challenging. Here, we used index and transcriptional single-cell sorting to characterize the mononuclear phagocytes that infiltrate the central nervous system from the periphery in mice with experimentally induced autoimmune encephalomyelitis, a model of MS. We identified eight monocyte and three dendritic cell subsets at acute and chronic disease stages in which the defined transcriptional programs pointed toward distinct functions. Monocyte-specific cell ablation identified Cxcl10+ and Saa3+ monocytic subsets with a pathogenic potential. Transfer experiments with different monocyte and precursor subsets indicated that these Cxcl10+ and Saa3+ pathogenic cells were not derived from Ly6C+ monocytes but from early myeloid cell progenitors. These results suggest that blocking specific pathogenic monocytic subsets, including Cxcl10+ and Saa3+ monocytes, could be used for targeted therapeutic interventions.

Publisher Correction: Cxcl10+ monocytes define a pathogenic subset in the central nervous system during autoimmune neuroinflammation.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Author Correction: Cxcl10+ monocytes define a pathogenic subset in the central nervous system during autoimmune neuroinflammation.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Innate Immune Landscape in Early Lung Adenocarcinoma by Paired Single-Cell Analyses.

To guide the design of immunotherapy strategies for patients with early stage lung tumors, we developed a multiscale immune profiling strategy to map the immune landscape of early lung adenocarcinoma lesions to search for tumor-driven immune changes. Utilizing a barcoding method that allows a simultaneous single-cell analysis of the tumor, non-involved lung, and blood cells, we provide a detailed immune cell atlas of early lung tumors. We show that stage I lung adenocarcinoma lesions already harbor significantly altered T cell and NK cell compartments. Moreover, we identified changes in tumor-infiltrating myeloid cell (TIM) subsets that likely compromise anti-tumor T cell immunity. Paired single-cell analyses thus offer valuable knowledge of tumor-driven immune changes, providing a powerful tool for the rational design of immune therapies. VIDEO ABSTRACT.

Approaches for studying human macrophages.

Macrophages are vital tissue components involved in organogenesis, maintaining homeostasis, and responses to disease. Mouse models have significantly improved our understanding of macrophages. Further investigations into the characteristics and development of human macrophages are crucial, considering the substantial anatomical and physiological distinctions between mice and humans. Despite challenges in human macrophage research, recent studies are shedding light on the ontogeny and function of human macrophages. In this opinion, we propose combinations of cutting-edge approaches to examine the diversity, development, niche, and function of human tissue-resident macrophages. These methodologies can facilitate our exploration of human macrophages more efficiently, ideally providing new therapeutic avenues for macrophage-relevant disorders.

Proteome and Glycoproteome Analyses Reveal Regulation of Protein Glycosylation Site-Specific Occupancy and Lysosomal Hydrolase Maturation by N-Glycan-Dependent ER-Quality Control.

N-Glycan-dependent endoplasmic reticulum quality control (ERQC) primarily mediates protein folding, which determines the fate of the polypeptide. Monoglucose residues on N-glycans determine whether the nascent N-glycosylated proteins enter into and escape from the calnexin (CANX)/calreticulin (CALR) cycle, which is a central system of the ERQC. To reveal the impact of ERQC on glycosylation and protein fate, we performed comprehensive quantitative proteomic and glycoproteomic analyses using cells defective in N-glycan-dependent ERQC. Deficiency of MOGS encoding the ER α-glucosidase I, CANX, or/and CALR broadly affected protein expression and glycosylation. Among the altered glycoproteins, the occupancy of oligomannosidic N-glycans was significantly affected. Besides the expected ER stress, proteins and glycoproteins involved in pathways for lysosome and viral infection are differentially changed in those deficient cells. We demonstrated that lysosomal hydrolases were not correctly modified with mannose-6-phosphates on the N-glycans and were directly secreted to the culture medium in N-glycan-dependent ERQC mutant cells. Overall, the CANX/CALR cycle promotes the correct folding of glycosylated peptides and influences the transport of lysosomal hydrolases.

Evolution mechanism of subsurface damage during laser machining process of fused silica.

The machining-induced subsurface damage (SSD) on fused silica optics would incur damage when irradiated by intense lasers, which severely restricts the service life of fused silica optics. The high absorption of fused silica to 10.6 µm makes it possible to utilize pulsed CO2 laser to remove and characterize SSD by layer-by-layer ablation, which improves its laser-induced damage threshold. However, thermal stress during the laser ablation process may have an impact on SSD, leading to extension. Still, the law of SSD morphology evolution mechanism has not been clearly revealed. In this work, a multi-physics simulated model considering light field modulation is established to reveal the evolution law of radial SSD during the laser layer-by-layer ablation process. Based on the simulation of different characteristic structural parameters, two evolution mechanisms of radial SSD are revealed, and the influence of characteristic structural parameters on SSD is also elaborated. By prefabricating the SSD by femtosecond laser, the measurements of SSD during CO2 laser layer-by-layer ablation experiments are consistent with the simulated results, and three stages of SSD depth variation under two evolution processes are further proposed. The findings of this study provide theoretical guidance for effectively characterizing SSD based on laser layer-by-layer ablation strategies on fused silica optics.

Data-based systematic error extraction and compensation methods based on wavelet transform in ultra-precision optical polishing.

Sub-aperture polishing is a key technique for fabricating ultra-precision optics. However, the existence of the polishing errors that are difficult to be compensated by physical modeling seriously affects the manufacturing accuracy and efficiency of optical components. To address this problem, a data-based systematic error extraction and compensation (DSEC) method was proposed to enhance the polishing accuracy on optics. To maximize the extraction quality in a small dataset condition, the wavelet transform is introduced into the extraction process, and the uncertainty of the piston term in the interferometer measurement is improved by L1-norm optimization. Furthermore, two typical error sources (loss of polishing fluid in the edge and the robot trajectory error) are used to verify the effectiveness of the proposed method; in experimental verification, the root mean square (RMS) of the surface figure of a ϕ85-mm mirror was decreased from 0.069λ to 0.017λ, and the RMS of the 610 × 440 mm mirrors was achieved at 0.019λ after the edge compensation, where the polishing accuracy can be improved by more than 4 times; additionally, the RMS of the surface figure with an effective aperture of 480 × 360 mm mirror was reached at 0.011λ after the trajectory error compensation, where the polishing accuracy can be improved by more than 2 times. The proposed DSEC model offers insights that will help achieve advancement in the sub-aperture polishing process.

Hsa_circ_0088036 promotes nonsmall cell lung cancer progression by regulating miR-1343-3p/Bcl-3 axis through TGFß/Smad3/EMT signaling.

Nonsmall cell lung cancer (NSCLC) is the leading cause of cancer-related mortality worldwide. Circular RNAs (circRNAs) have been the focus of numerous studies, and some circRNAs have been linked to the development of multiple malignant tumors, including NSCLC. Nevertheless, the functional role and mechanisms of circRNAs in NSCLC remain largely unknown. The primary objective of this study was to screen the associated circRNA in NSCLC and investigate its mechanism. CircRNA microarray was used to identify circRNAs that were abnormally expressed in NSCLC tissue samples. Expression of hsa_circRNA_0088036 was validated in NSCLC tissues and cell lines after the correlation between hsa_circRNA_0088036 and prognosis was determined. We then used a series of function gain-and-loss assays to determine the role of hsa_circ_0088036 in NSCLC progression. RNA-binding protein immunoprecipitation (RIP), RNA pull-down, and RNA interference assays were used to assess the interaction between hsa_circ_0088036 and miR-1343-3p/Bcl-3 axis. Moreover, mechanistic assays were applied to investigate the involved signaling pathway regulated by the hsa_circ_0088036/miR-1343-3p/Bcl-3 axis. Microarray analysis and reverse transcription polymerase chain reaction confirmed the presence of a circRNA termed hsa_circ 0088036 that was upregulated in NSCLC tissue samples and cell lines and indicated a positive association with patient prognosis. Functionally, hsa_circ_0088036 silencing inhibited proliferative, invasive, and migrative potential of NSCLC cells as well as epithelial-mesenchymal transition (EMT)-related proteins by sponging miR-1343-3p to inhibit Bcl-3. Furthermore, mechanistic experiments demonstrated that hsa_circ_0088036 promoted NSCLC progression by activating the TGFß/Smad3/EMT signaling pathway via miR-1343-3p/Bcl-3 axis. In conclusion, hsa_circ_0088036 functions as an oncogene by targeting the miR-1343-3p/Bcl-3 axis via TGFß/Smad3/EMT signaling pathway.

Statistical perception of the chaotic fabrication error and the self-adaptive processing decision in ultra-precision optical polishing.

Subaperture polishing is a key technique for fabricating ultra-precision optics. However, the error source complexity in the polishing process creates large fabrication errors with chaotic characteristics that are difficult to predict using physical modelling. In this study, we first proved that the chaotic error is statistically predictable and developed a statistical chaotic-error perception (SCP) model. We confirmed that the coupling between the randomness characteristics of chaotic error (expectation and variance) and the polishing results follows an approximately linear relationship. Accordingly, the convolution fabrication formula based on the Preston equation was improved, and the form error evolution in each polishing cycle for various tools was quantitatively predicted. On this basis, a self-adaptive decision model that considers the chaotic-error influence was developed using the proposed mid- and low-spatial-frequency error criteria, which realises the automatic decision of the tool and processing parameters. An ultra-precision surface with equivalent accuracy can be stably realised via proper tool influence function (TIF) selection and modification, even for low-deterministic level tools. Experimental results indicated that the average prediction error in each convergence cycle was reduced to 6.14%. Without manual participation, the root mean square(RMS) of the surface figure of a ϕ100-mm flat mirror was converged to 1.788 nm with only robotic small-tool polishing, and that of a ϕ300-mm high-gradient ellipsoid mirror was converged to 0.008 λ. Additionally, the polishing efficiency was increased by 30% compared with that of manual polishing. The proposed SCP model offers insights that will help achieve advancement in the subaperture polishing process.

Modeling and in-depth analysis of the mid-spatial-frequency error influenced by actual contact pressure distribution in sub-aperture polishing.

In ultra-precision optical processing, the sub-aperture polishing is prone to produce a mid-spatial-frequency (MSF) error. However, the generation mechanism of the MSF error is still not fully clarified, which seriously affects the further improvement of optical component performance. In this paper, it is proved that the actual contact pressure distribution between the workpiece and tool is a crucial source which affects the MSF error characteristics. A rotational periodic convolution (RPC) model is proposed to reveal the quantitative relationship among the contact pressure distribution, speed ratio (spin velocity/feed speed) and MSF error distribution. In-depth analyses show that the MSF error is linearly related to the symmetry level of contact pressure distribution and inversely proportional to the speed ratio, where the symmetry level is effectively evaluated by the proposed method based on Zernike polynomials. In the experiments, according to the actual contact pressure distribution obtained from the pressure-sensitive paper, the error rate of modeling results under different processing conditions is around 15%, which proves the validity of the proposed model. The influence of contact pressure distribution on the MSF error is further clarified through the establishment of RPC model, which can further promote the development of sub-aperture polishing.

Fourier convolution-parallel neural network framework with library matching for multi-tool processing decision-making in optical fabrication.

Intelligent manufacturing of ultra-precision optical surfaces is urgently desired but rather difficult to achieve due to the complex physical interactions involved. The development of data-oriented neural networks provides a new pathway, but existing networks cannot be adapted for optical fabrication with a high number of feature dimensions and a small specific dataset. In this Letter, for the first time to the best of our knowledge, a novel Fourier convolution-parallel neural network (FCPNN) framework with library matching was proposed to realize multi-tool processing decision-making, including basically all combination processing parameters (tool size and material, slurry type and removal rate). The number of feature dimensions required to achieve supervised learning with a hundred-level dataset is reduced by 3-5 orders of magnitude. Under the guidance of the proposed network model, a 260 mm × 260 mm off-axis parabolic (OAP) fused silica mirror successfully achieved error convergence after a multi-process involving grinding, figuring, and smoothing. The peak valley (PV) of the form error for the OAP fused silica mirror decreased from 15.153λ to 0.42λ and the root mean square (RMS) decreased from 2.944λ to 0.064λ in only 25.34 hours. This network framework has the potential to push the intelligence level of optical manufacturing to a new extreme.

Single-cell analysis of regions of interest (SCARI) using a photosensitive tag.

The functional activity and differentiation potential of cells are determined by their interactions with surrounding cells. Approaches that allow unbiased characterization of cell states while at the same time providing spatial information are of major value to assess this environmental influence. However, most current techniques are hampered by a tradeoff between spatial resolution and cell profiling depth. Here, we develop a photocage-based technology that allows isolation and in-depth analysis of live cells from regions of interest in complex ex vivo systems, including primary human tissues. The use of a highly sensitive 4-nitrophenyl(benzofuran) cage coupled to a set of nanobodies allows high-resolution photo-uncaging of different cell types in areas of interest. Single-cell RNA-sequencing of spatially defined CD8+ T cells is used to exemplify the feasibility of identifying location-dependent cell states. The technology described here provides a valuable tool for the analysis of spatially defined cells in diverse biological systems, including clinical samples.

Plug-and-play positioning error compensation model for ripple suppressing in industrial robot polishing.

The industrial robot-based polisher has wide applications in the field of optical manufacturing due to the advantages of low cost, high degrees of freedom, and high dynamic performance. However, the large positioning error of the industrial robot can lead to surface ripple and seriously restrict the system performance, but this error can only be inefficiently compensated for by measurement before each processing at present. To address this problem, we discovered the period-phase evolution law of the positioning error and established a double sine function compensation model. In the self-developed robotic polishing platform, the results show that the Z-axis error in the whole workspace after compensation can be reduced to ±0.06m m, which reaches the robot repetitive positioning error level; the Spearman correlation coefficients between the measurement and modeling errors are all above 0.88. In the practical polishing experiments, for both figuring and uniform polishing, the ripple error introduced by the positioning error is significantly suppressed by the proposed model under different conditions. Besides, the power spectral density (PSD) analysis has shown a significant suppression in the corresponding frequency error. This model gives an efficient plug-and-play compensation model for the robotic polisher, which provides possibilities for further improving robotic processing accuracy and efficiency.

Characterization of the evolution trajectory and immune profiling of new histologic patterns in lung adenocarcinoma.

In lung adenocarcinoma (LUAD), the appearance of morphologically diverse tumor regions, termed histological patterns, is closely associated with disease progression and lymph node metastasis. However, the molecular characteristics of the histological patterns in LUAD and the underlying molecular evolutionary mechanisms between the histological patterns in primary tumors and lymph node metastases are poorly understood. Here, we re-analyzed the large TCGA-LUAD dataset and depicted a comprehensive profiling of the genome and transcriptome across the histological patterns in LUAD. Tumor phylogenetic trajectory analysis suggested that the complex glands is more apt to metastasize to the lymph node. Further deconvolution of the tumor microenvironment demonstrated that the complex glands had a higher infiltration of cancer-associated fibroblasts (CAFs). Single-cell transcriptome profiling of complex glands pattern identified a novel CAF subtype co-expressing fibroblast activation protein-alpha (FAP) and stimulator of interferon genes (STING). Moreover, our data demonstrated that FAP is an important downstream effector of STING in CAFs. In summary, our results provide the basis for the development of innovative therapeutic guidelines and intervention strategies for LUAD patients.