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• Rice (Oryza sativa) tiller angle is a key component for achieving ideal plant architecture and higher grain yield. However, the molecular mechanism underlying rice tiller angle remains elusive. • We characterized a novel rice tiller angle mutant lazy2 (la2) and isolated the causative gene LA2 through map-based cloning. Biochemical, molecular and genetic studies were conducted to elucidate the LA2-involved tiller angle regulatory mechanism. • The la2 mutant shows large tiller angle with impaired shoot gravitropism and defective asymmetric distribution of auxin. We found that starch granules in amyloplasts are completely lost in the gravity-sensing leaf sheath base cells of la2, whereas the seed development is not affected. LA2 encodes a novel chloroplastic protein that can interact with the starch biosynthetic enzyme Oryza sativa plastidic phosphoglucomutase (OspPGM) to regulate starch biosynthesis in rice shoot gravity-sensing cells. Genetic analysis showed that LA2 regulates shoot gravitropism and tiller angle by acting upstream of LA1 to mediate lateral auxin transport. • Our studies revealed that LA2 acts as a novel regulator of rice tiller angle by specifically regulating starch biosynthesis in gravity-sensing cells, and established the framework of the starch-statolith-dependent rice tiller angle regulatory pathway, providing new insights into the rice tiller angle regulatory network.

Hypoxia-based agents (HBAs), such as anaerobic bacteria and bioreductive prodrugs, require both a permeable and hypoxic intratumoural environment to be fully effective. To solve this problem, herein, we report that perfluorocarbon nanoparticles (PNPs) can be used to create a long-lasting, penetrable and hypoxic tumour microenvironment for ensuring both the delivery and activation of subsequently administered HBAs. In addition to the increased permeability and enhanced hypoxia caused by the PNPs, the PNPs can be retained to further achieve the long-term inhibition of intratumoural O 2 reperfusion while enhancing HBA accumulation for over 24 h. Therefore, perfluorocarbon materials may have great potential for reigniting clinical research on hypoxia-based drugs. Hypoxia-based agents need permeable and hypoxic intratumour environment to be effective. Here, the authors show that perfluorocarbon nanoparticles promote increased permeability and sustained hypoxia to improve accumulation of hypoxia-based agents, and inhibit intratumour oxygen reperfusion.

The joint detection and tracking of multiple targets from raw thermal infrared (TIR) image observations plays a significant role in the video surveillance field, and it has extensive applied foreground and practical value. In this paper, a novel multiple-target track-before-detect (TBD) method, which is based on background subtraction within the framework of labeled random finite sets (RFS) is presented. First, a background subtraction method based on a random selection strategy is exploited to obtain the foreground probability map from a TIR sequence. Second, in the foreground probability map, the probability of each pixel belonging to a target is calculated by non-overlapping multi-target likelihood. Finally, a δ generalized labeled multi-Bernoulli ( δ -GLMB) filter is employed to produce the states of multi-target along with their labels. Unlike other RFS-based filters, the proposed approach describes the target state by a pixel set instead of a single point. To meet the requirement of factual application, some extra procedures, including pixel sampling and update, target merging and splitting, and new birth target initialization, are incorporated into the algorithm. The experimental results show that the proposed method performs better in multi-target detection than six compared methods. Also, the method is effective for the continuous tracking of multi-targets.

Long noncoding RNA (lncRNA) have proved to be important regulators in various diseases. CDKN2B-AS1 was a newly identified tumor-related lncRNA, and previous studies have reported its function in laryngeal squamous cancer and osteosarcoma. However, the function and mechanism of lncRNA CDKN2B-AS1 in lung cancer are still unknown. Cell proliferation, invasion, migration and apoptosis were detected via CCK-8, transwell assay and Western blot. Bioinformatics analysis was used to predict the potential target of CDKN2B-AS1. A rescue experiment was performed to identify the relationship between CDKN2B-AS1 and miR-378b. The expression of lncRNA CDKN2B-AS1 was significantly upregulated in lung cancer tissues and cell lines. Overexpression of CDKN2B-AS1 promoted cell proliferation, invasion and reduced cell apoptosis. Knockdown of CDKN2B-AS1 inhibited cell proliferation, invasion and increased cell apoptosis. Bioinformatics analysis predicted that miR-378b was the direct target. We also provided evidence that NR2C2 was the target of miR-378b. The expression of NR2C2 was significantly upregulated in lung cancer tissues and cell lines. The rescue experiment further confirmed the relationship between CDKN2B-AS1 and miR-378b. Overexpression of miR-378b completely reversed the function of CDKN2B-AS1. Taken together, our results comprehensively analyzed the function of CDKN2B-AS1 in lung cancer and provided a possible mechanism that CDKN2B-AS1 facilitates lung cancer development by regulating miR-378b and NR2C2. Thus, our study offers a potential therapeutic target for treating lung cancer.

Catalytic hydrogenation or transfer hydrogenation of quinolines was thought to be a direct strategy to access dihydroquinolines. However, the challenge is to control the chemoselectivity and regioselectivity. Here we report an efficient partial transfer hydrogenation system operated by a cobalt-amido cooperative catalyst, which converts quinolines to 1,2-dihydroquinolines by the reaction with H 3 N·BH 3 at room temperature. This methodology enables the large scale synthesis of many 1,2-dihydroquinolines with a broad range of functional groups. Mechanistic studies demonstrate that the reduction of quinoline is controlled precisely by cobalt-amido cooperation to operate dihydrogen transfer from H 3 N·BH 3 to the N=C bond of the substrates. Controlling the partial reduction of quinolines is challenging, given the competing overreduction to tetrahydroquinolines. Here, the authors report a cobalt-amido cooperative catalyst for the selective, partial transfer hydrogenation of quinolines to 1,2-dihydroquinolines with H 3 N·BH 3 as reductant.

Radar-based continuous human activity recognition (HAR) in realistic scenarios faces challenges in segmenting and classifying overlapping or concurrent activities. This paper introduces a feedback-driven adaptive segmentation framework for multi-label classification in continuous HAR, leveraging Bayesian optimization (BO) and reinforcement learning (RL) to dynamically adjust segmentation parameters such as segment length and overlap in the data stream, optimizing them based on performance metrics such as accuracy and F1-score. Using a public dataset of continuous human activities, the method trains ResNet18 models on spectrogram, range-Doppler, and range-time representations from a 20% computational subset. Then, it scales optimized parameters to the full dataset. Comparative analysis against fixed-segmentation baselines was made. The results demonstrate significant improvements in classification performance, confirming the potential of adaptive segmentation techniques in enhancing the accuracy and efficiency of continuous multi-label HAR systems.

Great photoelectric properties can herald the high potentials of CsPbBr 3 nanocrystals (NCs) to function as the fluorescent probes for early tumor diagnosis. However, the intrinsic water vulnerability of CsPbBr 3 NCs highly restricts their biomedical applications. To conquer this challenge, we herein introduce a nature inspired \"stress-response\" method to tightly encapsulate CsPbBr 3 into SiO 2 nano-shells that can dramatically improve the water stability of CsPbBr 3 @SiO 2 nanoparticles for over 48 h. We further highlighted the advantageous features of CsPbBr 3 @SiO 2 by using them as the fluorescent probes for CT26 tumor cell imaging with their high water stability, biocompatibility, and low cytotoxicity. Our work for the first time exhibited the potential of lead halide perovskite NCs for tumor diagnosis, and can highly anticipate the further in vivo biomedical applications that light up live cells.

Transition metal carbyne complexes are of fundamental importance in carbon-carbon bond formation, alkyne metathesis, and alkyne coupling reactions. Most reported iron carbyne complexes are stabilized by incorporating heteroatoms. Here we show the synthesis of bioinspired FeMo heterobimetallic carbyne complexes by the conversion of C 2 H 2 through a diverse series of intermediates. Key reactions discovered include the reduction of a μ-η 2 :η 2 -C 2 H 2 ligand with a hydride to produce a vinyl ligand (μ-η 1 :η 2 -CH = CH 2 ), tautomerization of the vinyl ligand to a carbyne (μ-CCH 3 ), and protonation of either the vinyl or the carbyne compound to form a hydrido carbyne heterobimetallic complex. Mechanistic studies unveil the pivotal role of H 2 O as a proton shuttle, facilitating the proton transfer that converts the vinyl group to a bridging carbyne. Bioinspired Fe-Mo complexes are promising for the activation of small molecules, offering valuable insights into the interactions and transformations of unsaturated hydrocarbons with abundant metals. Here, the authors report the synthesis and mechanistic studies of FeMo carbyne complexes and unveil the pivotal role of H 2 O as a proton shuttle.

Type 2 myocardial infarction (T2MI), distinguished from Type 1 myocardial infarction (T1MI) by oxygen supply - demand mismatch, has unique features. Acute kidney injury (AKI) following MI leads to severe consequences. Existing research mostly centers on T1MI, leaving a gap in T2MI related AKI studies. To address this, our research aims to explore AKI risk factors in T2MI patients and leverage machine learning algorithms to develop a model for accurate early prediction of AKI risk in this patient group. This retrospective study utilized the MIMIC-IV database (2008–2022) to analyze T2MI patients in critical care. The dataset was split 70:30 for model development. 12 machine learning algorithms underwent Boruta-based feature selection and hyperparameter optimization. All 12 machine learning algorithms were trained independently (i.e., no integration into a SuperLearner or other ensemble learning frameworks was performed). Model performance was assessed via AUROC, with SHAP analysis interpreting predictions, followed by web deployment for clinical use. Among 1,378 critically ill patients, 60.5% developed AKI post-ICU admission. Eleven variables were selected for machine learning modeling. XGBoost demonstrated superior predictive performance (test AUROC: 0.82, 95% CI 0.77–0.86). SHAP analysis identified mechanical ventilation as the strongest predictor, followed by minimum mean arterial pressure, maximum heart rate, maximum aspartate aminotransferase, and minimum white blood cell count. An interactive web tool ( https://qhdpanguo.shinyapps.io/2MI-AKI/ ) was developed for clinical application.

Antimicrobial proteins contribute to host-microbiota interactions and are associated with inflammatory bowel disease (IBD), but our understanding on antimicrobial protein diversity and functions remains incomplete. Ribonuclease 4 (Rnase4) is a potential antimicrobial protein with no known function in the intestines. Here we find that RNASE4 is expressed in intestinal epithelial cells (IEC) including Paneth and goblet cells, and is detectable in human and mouse stool. Results from Rnase4- deficient mice and recombinant protein suggest that Rnase4 kills Parasutterella to modulate intestinal microbiome, thereby enhancing indoleamine-2,3-dioxygenase 1 (IDO1) expression and subsequently kynurenic and xanthurenic acid production in IECs to reduce colitis susceptibility. Furthermore, deceased RNASE4 levels are observed in the intestinal tissues and stool from patients with IBD, correlating with increased stool Parasutterella . Our results thus implicate Rnase4 as an intestinal antimicrobial protein regulating gut microbiota and metabolite homeostasis, and as a potential diagnostic biomarker and therapeutic target for IBD. Antimicrobial proteins have been implicated in inflammatory bowel disease (IBD). Here the authors report, using both mouse genetic models and human samples, RNASE4 as a potential antimicrobial protein targeting Parasutterella to alter gut microbiota and metabolite homeostasis, impact susceptibility to IBD, and serve as a potential target for IBD therapy.