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For multisensor maneuvering target tracking, two important factors affecting the tracking performance are: (1) the uncertainty of the target dynamics model; (2) the cross-correlation of local estimation errors across sensors. For these problems, a new model-level information fusion algorithm based on interacting multiple model (IMM) is proposed. First, in each local sensor, the IMM algorithm is used to deal with the problem of uncertainty of the dynamics model caused by the target maneuver, and the obtained model-level information (Gaussian mixture probability density) instead of the state estimation after model mixing is sent to the fusion center. This effectively avoids the loss of information in the process of model mixing. Second, for the correlation between local estimates, a new model level information decorrelation algorithm for IMM is proposed to obtain decorrelated fusion information. Finally, in the fusion center, the fusion of the de-correlated estimation information is completed by the naive fusion method. The simulation experiments verify the performance of the proposed algorithm.

This study proposes a novel gesture recognition system based on LoRa technology, integrating advanced signal preprocessing, adaptive segmentation algorithms, and an improved SS-ResNet50 deep learning model. Through the combination of residual learning and dynamic convolution techniques, the SS-ResNet50 model significantly enhances the extraction capability of multi-scale gesture features, thereby augmenting the classification accuracy. To counter environmental noise and static interferences, an adaptive segmentation approach based on sliding window variance analysis is introduced in the research. This method effectively increases data diversity while preserving the specific components of gestures. Experimental outcomes indicate that the system exhibits strong robustness in cross-scenario and cross-device tests, with an average recognition accuracy of over 95% for six gestures. The system’s low power consumption, long-distance communication, and strong anti-interference capabilities offer broad prospects for its application in complex environments, particularly in resource-constrained scenarios such as underground mine gesture monitoring and remote control in dynamic environments and other practical applications. This study demonstrates the feasibility of gesture recognition systems based on LoRa technology and provides a new solution for low-power, long-distance non-contact gesture recognition.

Protein N-phosphorylation plays a critical role in central metabolism and two/multicomponent signaling of prokaryotes. However, the current enrichment methods for O-phosphopeptides are not preferred for N-phosphopeptides due to the intrinsic lability of P-N bond under acidic conditions. Therefore, the effective N-phosphoproteome analysis remains challenging. Herein, bis(zinc(II)-dipicolylamine)-functionalized sub-2 μm core-shell silica microspheres (SiO 2 @DpaZn) are tailored for rapid and effective N-phosphopeptides enrichment. Due to the coordination of phosphate groups to Zn(II), N-phosphopeptides can be effectively captured under neutral conditions. Moreover, the method is successfully applied to an E.coli and HeLa N-phosphoproteome study. These results further broaden the range of methods for the discovery of N-phosphoproteins with significant biological functions. N-phosphorylation plays a critical role in central metabolism and signaling processes, however, enrichment methods for N-phosphopeptides are limited by the P-N bond lability. Here, the authors report the synthesis and use of silica microspheres functionalized with bis(zinc(II)-dipicolylamine) in N-phosphopeptides effective enrichment.

The Yellow River is the mother river of the Chinese nation. The source region of the Yellow River is an important region for water conservation in China. The hydro-ecological environment of the Yellow River source region is very fragile. Therefore, the variation processes of runoff and sediment discharge in the Yellow River source region have become the subject of considerable concern in recent years. However, the source region of the Yellow River has been studied relatively little, and the influence of these two process in the source region of the Yellow River remains unclear. In this paper, precipitation, runoff, sediment discharge, and their interactions in the source region of the Yellow River from 1956 to 2018 were analyzed using several different time-series evaluation methods, such as Spearman’s rank correlation coefficient method, the ordered clustering analysis method, and the double-mass curve method. Furthermore, the impact of Huangheyuan hydropower station on these hydrological elements was analyzed in relation to the few other human activities in Sanjiangyuan National Nature Reserve. The results indicated that the precipitation in the source region of the Yellow River increased significantly, the sediment discharge decreased non-significantly, and there was no significant change in runoff over this time period. The years 1995 and 2011 were probable mutation points of the sediment discharge series, and the mutation point of the precipitation series was likely 2001. The Huangheyuan hydropower station is the main reason for the decrease in annual sediment discharge in the source region of the Yellow River.

Unlocking the intricacies of protein structures and interactions within the dynamic landscape of subcellular organelles presents a significant challenge. To address this, we introduce SPACX, a method for s patially resolved p rotein complex profiling via biocomp a tible c hemical cross( x )-linking with subcellular isolation, designed to monitor protein conformation, interactions, and translocation in living cells. By rapidly capturing protein complexes in their native physiological state and efficiently enriching cross-linked peptides, SPACX allows comprehensive analysis of the protein interactome within living cells. Leveraging structure refinement with cross-linking restraints, we identify subcellular-specific conformation heterogeneity of PTEN, revealing dynamic differences in its dual specificity domains between the nucleus and cytoplasm. Furthermore, by discerning conformational disparities, we identify 83 cytoplasm-exclusive and 109 nucleus-exclusive PTEN-interacting proteins, each associated with distinct biological functions. Upon induction of ubiquitin-proteasome system stress, we observe dynamic alterations in PTEN assembly and its interacting partners during translocation. These changes, including the identification of components and interaction sites, are characterized using the SPACX approach. Notably, SPACX enables identification of unique interacting proteins specific to PTEN isoforms, including PTEN and PTEN-Long, through the determination of sequence-specific cross-linking interfaces. These findings underscore the potential of SPACX to elucidate the functional diversity of proteins within distinct subcellular sociology. Unlocking the complexities of protein structures and interactions within subcellular organelles is challenging. Here, the authors introduce SPACX, a method for spatially resolved protein complex profiling using biocompatible chemical cross-linking, enabling the analysis of protein conformation, interactions, and translocation in living cells.

We report the tunable conversion of chloromethane to olefins and aromatics using different metal-promoted zeolites as catalysts. Despite SAPO-34 was industrially used as catalysts for methanol to olefins reaction (MTO), the SAPO-34 based zeolites exhibited low activity and short lifetime when using chloromethane as the feed. Higher chloromethane conversion and longer catalyst lifetime were found on H-ZSM-5. The activity and product distribution can be improved by optimizing the reaction temperature and space velocity. Impregnating the H-ZSM-5 zeolite with 1 wt% and 5 wt% metal oxide as promoters significantly enhanced the conversion efficiency and altered the product distribution. The highest aromatics selectivity (38%) was obtained on the H-ZSM-5 zeolite promoted by 5 wt% Ni, whereas on 5 wt% Mg and 5 wt% Mn promoted H-ZSM-5, the aromatics selectivity is merely 5%. Therefore, different modified H-ZSM-5 could be used to convert chloromethane to either aromatics or olefin-heavy products. It was found that the aromatics yield is strongly correlated to the acidity of the H-ZSM-5 zeolite. Graphic Abstract

Exposure to airborne fine particulate matter (PM 2.5 ) induced various adverse health effects, such as metabolic syndrome, systemic inflammation, and respiratory disease. Many works have studied the effects of PM 2.5 exposure on cells through intracellular proteomics analyses. However, changes of the extracellular proteome under PM 2.5 exposure and its correlation with PM 2.5 -induced cytotoxicity still remain unclear. Herein, the cytotoxicity of PM 2.5 on normal human bronchial epithelia cells (BEAS-2B cells) was evaluated, and the secretome profile of BEAS-2B cells before and after PM 2.5 exposure was investigated. A total of 83 proteins (58 upregulated and 25 downregulated) were differentially expressed in extracellular space after PM 2.5 treatment. Notably, we found that PM 2.5 promoted the release of several pro-apoptotic factors and induced dysregulated secretion of extracellular matrix (ECM) constituents, showing that the abnormal extracellular environment attributed to PM 2.5 -induced cell damage. This study provided a secretome data for the deep understanding of the molecular mechanism underlying PM 2.5 -caused human bronchial epithelia cell damage.

Extracellular vesicles (EVs) carry a variety of bioactive molecules and are becoming a promising alternative to cell therapy. Scale-up EV isolation is necessary for their functional studies and biological applications, while the traditional methods are challenged by low throughput, low yield, and potential damage. Herein, we developed an ion osmolarity-driven sequential concentration-enrichment strategy (IOSCE) for the EV isolation. IOSCE is composed of a novel superabsorbent polymers (SAPs) for EV concentration and a charged polymer for EV enrichment. Based on the driving force of ionic osmotic pressure, IOSCE can isolate EVs on a large scale from cell culture medium. The saturated water absorption capacity of IOSCE is 13.62 times higher than that of commercial SAPs. Compared with the ultracentrifugation method, IOSCE exhibited a 2.64 times higher yield (6.33 × 10 8 particles/mL). Moreover, the mesenchymal stem cell-derived EVs isolated using IOSCE demonstrate strong biological activity and can reduce neuroinflammation by affecting RNA metabolism and translation processes. IOSCE provides a cost-effective, high-throughput, and low-damage method for the scale up EV isolation, which is promising for disease diagnosis and treatment. Graphical Abstract

The study of in situ conformations and interactions of mitochondrial proteins plays a crucial role in understanding their biological functions. Current chemical cross‐linking mass spectrometry (CX‐MS) has difficulty in achieving in‐depth analysis of mitochondrial proteins for cells without genetic modification. Herein, this work develops the reactive oxygen species (ROS)‐responsive cross‐linker delivery nanoparticles (R‐CDNP) targeting mitochondria. R‐CDNP contains mitochondria‐targeting module triphenylphosphine, ROS‐responsive module thioketal, loading module poly(lactic‐co‐glycolic acid) (PLGA), and polyethylene glycol (PEG), and cross‐linker module disuccinimidyl suberate (DSS). After targeting mitochondria, ROS‐triggered cross‐linker release improves the cross‐linking coverage of mitochondria in situ. In total, this work identifies 2103 cross‐linked sites of 572 mitochondrial proteins in HepG2 cells. 1718 intra‐links reveal dynamic conformations involving chaperones with ATP‐dependent conformation cycles, and 385 inter‐links reveal dynamic interactions involving OXPHOS complexes and 27 pairs of possible potential interactions. These results signify that R‐CDNP can achieve dynamic conformation and interaction analysis of mitochondrial proteins in living cells, thereby contributing to a better understanding of their biological functions. Endogenous ROS‐responsive cross‐linker delivery nanoparticles (R‐CDNP) are fabricated for the triggered releasement of cross‐linkers at mitochondria in intact living cells. Without genetically modifying cells or isolating mitochondria, R‐CDNP can capture native mitochondrial protein information, further achieving in situ analysis of protein conformations and interactions with the integration of chemical cross‐linking mass spectrometry.

NgBR is a type I receptor with a single transmembrane domain and was identified as a specific receptor for Nogo-B. Our recent findings demonstrated that NgBR binds farnesylated Ras and recruits Ras to the plasma membrane, which is a critical step required for the activation of Ras signaling in human breast cancer cells and tumorigenesis. Here, we first use immunohistochemistry and real-time PCR approaches to examine the expression patterns of Nogo-B and NgBR in both normal and breast tumor tissues. Then, we examine the relationship between NgBR expression and molecular subtypes of breast cancer, and the roles of NgBR in estrogen-dependent survivin signaling pathway. Results showed that NgBR and Nogo-B protein were detected in both normal and breast tumor tissues. However, the expression of Nogo-B and NgBR in breast tumor tissue was much stronger than in normal breast tissue. The statistical analysis demonstrated that NgBR is highly associated with ER-positive/HER2-negative breast cancer. We also found that the expression of NgBR has a strong correlation with the expression of survivin, which is a well-known apoptosis inhibitor. The correlation between NgBR and survivin gene expression was further confirmed by real-time PCR. In vitro results also demonstrated that estradiol induces the expression of survivin in ER-positive T47D breast tumor cells but not in ER-negative MDA-MB-468 breast tumor cells. NgBR knockdown with siRNA abolishes estradiol-induced survivin expression in ER-positive T47D cells but not in ER-negative MDA-MB-468 cells. In addition, estradiol increases the expression of survivin and cell growth in ER-positive MCF-7 and T47D cells whereas knockdown of NgBR with siRNA reduces estradiol-induced survivin expression and cell growth. In summary, these results indicate that NgBR is a new molecular marker for breast cancer. The data suggest that the expression of NgBR may be essential in promoting ER-positive tumor cell proliferation via survivin induction in breast cancer.