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The CMA-MESO/CUACE CW is an atmospheric chemistry coupled model independently developed by China.At present， the CMA-MESO/CUACE CW 3DVar system realized the assimilation of ground-based aerosol observations of PM2.5 and PM10.In order to enhance the assimilation capability of the coupled assimilation system for non-conventional observations， based on the CMA-MESO three-dimensional variational assimilation framework of atmospheric chemical weather coupled system， the aerosol extinction coefficient is obtained by using the look-up table method.And then the observation operator， the tangent linear operator and the adjoint operator are established using the relationship between aerosol optical depth （AOD） and aerosol components.The assimilation tests were carried out for a haze process in North China on December 18 -20， 2016.The results show that after assimilating the AOD observations from the Himawari-8 satellite， the heavily polluted area of the PM2.5 is enlarged， and the analysis in southeastern Shanxi is closer to the actual situation， but the analysis of PM2.5 in the majority of the Shandong region is overestimated.The simultaneous assimilation of Himawari-8 AOD observations and ground-based aerosol concentration observations test is the best for the analysis of PM2.5， it has the highest correlation coefficients （ACCs） and the smallest mean bias， root-mean-square error and standard deviation.The PM2.5 forecast results in the heavily polluted area showed that the positive contribution of the assimilated Himawari-8 AOD observations to the PM2.5 forecasts for the >350 μg·m-3 magnitude could be sustained up to 48 h.However， the simultaneous assimilation of the Himawari-8 AOD observations and the ground-based aerosol site observations had the best test scores of PM2.5 forecasts for each magnitude.

IntroductionETAA1 is recruited to DNA damage sites via its RPA -binding and ATR -activating domain (AAD) motifs, where RPA binding is crucial for ETAA1’s regulation of ATR activity. Methods & resultsOur findings associate Programmed Death- Ligand1 (PD-L1) with the RPA1-ETAA1 axis, suggesting that upregulated RPA1 -dependent ETAA1 may facilitate PD-L1 nuclear accumulation. We observed strong correlations between ETAA1 and RPA1 with the components involved in HDAC2-mediated deacetylation, clathrin -dependent endocytosis, and PD-L1 nucleocytoplasmic shuttling, aligning with the established regulatory pathway of PD-L1 nuclear translocation. Moreover, nuclear PD-L1 transactivates a panel of pro-inflammatory and immune response transcription factors, potentially reshaping the tumor immune microenvironment. We identified a landscape of infiltrating lymphocytes influenced by ETAA1, finding that levels of ETAA1 were negatively correlated with CD8+ T and Natural Killer T (NKT) cells, but positively correlated with CD4+ T helper 2 (Th2) cells, cancer-associated fibroblasts (CAFs), myeloid-derived suppressor cells (MDSCs), neutrophils and regulatory T cells (Tregs), suggesting a potential role in immune evasion. Further analysis shows that the RPA1-ETAA1 axis is significantly associated with multiple metastasis mediators and unfavorable liver cancer progression, with higher expression observed in advanced stages and poorly differentiated subgroups. Discussion & conclusionThese findings expand the role of the RPA1-ETAA1 axis beyond DNA repair, highlighting its potential as a target for cancer therapy.

The capacity of lymphocytes continuously home to lymphoid structures is remarkable for cancer immunosurveillance and immunotherapy. Lymphocyte homing and recirculation within the tumor microenvironment (TME) are now understood to be adaptive processes that are regulated by specialized cytokines and adhesion molecule signaling cascades. Restricted lymphocyte infiltration and recirculation have emerged as key mechanisms contributing to poor responses in cancer immunotherapies like chimeric antigen receptor (CAR)-T cell therapy and immune checkpoint blockades (ICBs). Uncovering the kinetics of lymphocytes in tumor infiltration and circulation is crucial for improving immunotherapies. In this review, we discuss the current insights into the adhesive and migrative molecules involved in lymphocyte homing and transmigration. The potential mechanisms within the TME that restrain lymphocyte infiltration are also summarized. Advanced on these, we outline the determinates for tertiary lymphoid structures (TLSs) formation within tumors, placing high expectations on the prognostic values of TLSs as therapeutic targets in malignancies.

Abstract Heterogeneous organ‐specific responses to immunotherapy exist in lung cancer. Dissecting tumor microenvironment (TME) can provide new insights into the mechanisms of divergent responses, the process of which remains poor, partly due to the challenges associated with single‐cell profiling using formalin‐fixed paraffin‐embedded (FFPE) materials. In this study, single‐cell nuclei RNA sequencing and imaging mass cytometry (IMC) are used to dissect organ‐specific cellular and spatial TME based on FFPE samples from paired primary lung adenocarcinoma (LUAD) and metastases. Single‐cell analyses of 84 294 cells from sequencing and 250 600 cells from IMC reveal divergent organ‐specific immune niches. For sites of LUAD responding well to immunotherapy, including primary LUAD and adrenal gland metastases, a significant enrichment of B, plasma, and T cells is detected. Spatially resolved maps reveal cellular neighborhoods recapitulating functional units of the tumor ecosystem and the spatial proximity of B and CD4+ T cells at immunogenic sites. Various organ‐specific densities of tertiary lymphoid structures are observed. Immunosuppressive sites, including brain and liver metastases, are deposited with collagen I, and T cells at these sites highly express TIM‐3. This study originally deciphers the single‐cell landscape of the organ‐specific TME at both cellular and spatial levels for LUAD, indicating the necessity for organ‐specific treatment approaches.

Wildlife re-identification (Re-ID) techniques are key to animal tracking and preservation. However, the performance of current deep learning methods is unsatisfactory in cross-camera scenarios, especially in terms of mean average precision (mAP). This work introduces ReDeformTR, a novel model designed for wildlife Re-ID tasks, particularly focusing on the identification of individual animals’ images captured by different cameras. ReDeformTR integrates a lightweight deformable transformer architecture capable of multi-image feature fusion, which can extract and fuse features from multiple images and scales, facilitating efficient representation of individual animals and enhancing performance during queries. A convolutional neural network (CNN) backbone is adopted for feature extraction, while a deformable transformer is used for feature refinement and fusion. The deformable attention mechanism reduces computation overhead by selectively sampling features, thereby enhancing efficiency. The experiments show that ReDeformTR demonstrates superior performance in terms of mAP on a cross-camera wildlife dataset in ATRW. The mAP is 84.98%, which represents a significant improvement of 12.29% compared to the state-of-the-art model (PPGNet). Furthermore, our model achieves a significant reduction in model parameter size, positioning it as a promising solution for wildlife Re-ID tasks.

Abstract The heterogeneity of macrophages influences the response to immune checkpoint inhibitor (ICI) therapy. However, few studies explore the impact of APOE+ macrophages on ICI therapy using single‐cell RNA sequencing (scRNA‐seq) and machine learning methods. The scRNA‐seq and bulk RNA‐seq data are Integrated to construct an M.Sig model for predicting ICI response based on the distinct molecular signatures of macrophage and machine learning algorithms. Comprehensive single‐cell analysis as well as in vivo and in vitro experiments are applied to explore the potential mechanisms of the APOE+ macrophage in affecting ICI response. The M.Sig model shows clear advantages in predicting the efficacy and prognosis of ICI therapy in pan‐cancer patients. The proportion of APOE+ macrophages is higher in ICI non‐responders of triple‐negative breast cancer compared with responders, and the interaction and longer distance between APOE+ macrophages and CD8+ exhausted T (Tex) cells affecting ICI response is confirmed by multiplex immunohistochemistry. In a 4T1 tumor‐bearing mice model, the APOE inhibitor combined with ICI treatment shows the best efficacy. The M.Sig model using real‐world immunotherapy data accurately predicts the ICI response of pan‐cancer, which may be associated with the interaction between APOE+ macrophages and CD8+ Tex cells.

Improving the forecasting skills of the meso-scale convective system (MCS) is one of the key scientific problems in the field of numerical weather prediction. The occurrence and development of severe convective weather are affected by multiple factors such as atmospheric thermodynamic and kinetic conditions, topography, and air pollution conditions. Due largely to the uncertainty in models and the inevitable errors of initial values, large uncertainties still exist for the accurate prediction of severe weather produced by the MCS. Therefore, to effectively improve the accuracy of severe convective weather forecasts in China, conducting targeted observation experiments in key areas of interest, which typically helps to reduce the uncertainty level of the model's initial meteorological field, may be one of the effective ways forward. It follows that the initiation and formation mechanisms of MCS can be revealed, and the forecast skills of severe convection will be improved. In this paper, we first propose the technology roadmap of targeted observation as follows. Based on the modern meteorological observational network over the Jing-Jin-Ji area, the typical MCS forecast sensitive regions are identified by using the Ensemble Transform Kalman filter, combined with the atmospheric sounding systems mounted on the mobile vehicle, where targeted observation experiments will be conducted. As such, convective initiation mechanisms are elucidated, and the novel methods expected to improve the forecast skill for MCS are explored. Secondly, in response to the challenge of "finding needles in a haystack" in the vertical observation of the lower atmosphere for short-term forecasting and warning of severe convective weather in large cities, the potential application value of a dynamic triangular observation mesonet in the study of triggering and development mechanisms of severe convective weather was explored through the construction of a Pyramid-shaped LOwer Tropospheric Observational System (PLOTOS) that consists of five stations with simultaneous vertical observation capabilities. Finally, it is suggested that the initiation and formation mechanisms of severe convective weather be unraveled using PLOTOS, and the mesoscale targeted observation technology be developed, which is crucial to the improvement of weather observational networks in large cities and provide new ideas and methods for improving the forecast of severe convective weather processes.

B cells are essential for humoral immune response due to their ability to secrete antibodies. The development of B cells from the bone marrow to the periphery is tightly regulated by a complex set of immune signals, and each subset of B cells has a unique metabolic profile. Mitochondria, which serve as cellular energy powerhouses, play an essential role in regulating cell survival and immune responses. To maintain metabolic homeostasis, mitochondria dynamically adjust their morphology, distribution, and mass via biogenesis, fusion and fission, translocation, and mitophagy. Despite its extreme importance, the role of mitochondrial quality control (MQC) in B cells has not been thoroughly summarized, unlike in T cells. This article aims to review the mechanism of MQC that shapes B cell fate and functions. In addition, we will discuss the physiological and pathological implications of MQC in B cells, providing new insights into potential therapeutic targets for diseases associated with B cell abnormalities.

Since 2003， the World Meteorological Organization （WMO） proposed and coordinated a switch from traditional radiosonde format （TAC code） to second-resolution binary （BUFR） report， which leads the assimilation of second radiosonde data in numerical prediction model becoming the future trend.Data quality control is a key and basic work before assimilation application.In addition， the observational error characteristics of Lband second-level radiosonde are significantly different from that of conventional radiosonde.Therefore， a two-step quality control method for assimilation application is developed in this paper.The first step integrates conventional radiosonde quality control procedures and inserts several additional steps according to the data characteristics of second-level radiosonde， which aims at eliminating human-observation errors as much as possible.The second step introduces a dynamic blacklist checking module into the assimilation system， at the same time remaining the old OMB （observation minus background） check method， so as to control the representative deviation between the observation and the model background.By comparing and analyzing the statistical characteristics of the observation samples before and after the quality control procedure， and combining them with the actual assimilation analysis results of the NWP model， the rationality of the two-step quality control procedure has been comprehensively verified.It reveals that the data anomaly is greatly reduced after the two-step quality control procedure， at the same time the OMB is closer to a Gaussian distribution.Moreover， the validity of data assimilation is enhanced leading to a better assimilation analysis effect.The work lays a foundation for the future operational application of L-band second-level radiosonde data in GRAPES （Global/Regional Assimilation and Prediction System） model.

The fundamental principle of immune checkpoint blockade (ICB) is to protect tumor-infiltrating T cells from being exhausted. Despite the remarkable success achieved by ICB treatment, only a small group of patients benefit from it. Characterized by a hypofunctional state with the expression of multiple inhibitory receptors, exhausted T (Tex) cells are a major obstacle in improving ICB. T cell exhaustion is a progressive process which adapts to persistent antigen stimulation in chronic infections and cancers. In this review, we elucidate the heterogeneity of Tex cells and offer new insights into the hierarchical transcriptional regulation of T cell exhaustion. Factors and signaling pathways that induce and promote exhaustion are also summarized. Moreover, we review the epigenetic and metabolic alterations of Tex cells and discuss how PD-1 signaling affects the balance between T cell activation and exhaustion, aiming to provide more therapeutic targets for applications of combinational immunotherapies.

Abstract Chromodomain helicase DNA binding protein 4 (CHD4) is an ATPase subunit of the nucleosome remodeling and deacetylation complex. It has been implicated in gene transcription, DNA damage repair, maintenance of genome stability, and chromatin assembly. Meanwhile, it is highly related to cell cycle progression and the proceeding of malignancy. Most of the previous studies were focused on the function of CHD4 with tumor cells, cancer stem cells, and cancer cells multidrug resistance. Recently, some researchers have explored the CHD4 functions on the development and differentiation of adaptive immune cells, such as T and B lymphocytes. In this review, we will discuss details of CHD4 in lymphocyte differentiation and development, as well as the critical role of CHD4 in the pathogenesis of the autoimmune disease.