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The extractant-assisted transport of metal ions from aqueous to organic environments by liquid-liquid extraction has been widely used to separate and recover critical elements on an industrial scale. While current efforts focus on designing better extractants and optimizing process conditions, the mechanism that underlies ionic transport remains poorly understood. Here, we report a nonequilibrium process in the bulk aqueous phase that influences interfacial ion transport: the formation of metastable ion-extractant precipitates away from the liquid-liquid interface, separated from it by a depletion region without precipitates. Although the precipitate is soluble in the organic phase, the depletion region separates the two and ions are sequestered in a long-lived metastable state. Since precipitation removes extractants from the aqueous phase, even extractants that are sparingly soluble in water will continue to be withdrawn from the organic phase to feed the aqueous precipitation process. Solute concentrations in both phases and the aqueous pH influence the temporal evolution of the process and ionic partitioning between the precipitate and organic phase. Aqueous ion-extractant precipitation during liquid-liquid extraction provides a reaction path that can influence the extraction kinetics, which plays an important role in designing advanced processes to separate rare earths and other minerals.
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BACKGROUND: HCC-1 (hemofiltrate CC chemokine-1), a CC-type chemokine, exerts function to change intracellular calcium concentration, induce leukocyte, and manipulate enzyme release especially in monocytes. It has been reported that HCC-1 could predict the persistent acute kidney injury or suppress hepatocellular carcinoma by modulating cell cycle and promoting apoptosis, while the effect of HCC-1 on atherosclerosis is poorly understood. Here, we aimed to clarify the function and mechanism of HCC-1 in atherosclerosis and whether it could serve as a novel biomarker for the diagnosis of atherosclerosis. METHODS: HCC-1 expression in serum, atherosclerotic plaques, and normal arterial tissue from patients with atherosclerosis and control group was assessed by ELISA, immunohistochemistry and confocal microscope, and bioinformatic analysis. The atherosclerotic model of HCC-1 overexpressing and control mice was generated by tail vein injection of adeno-associated virus serotype 9-HCC-1 on an ApoE-/- background. Cell adhesion, polarization, and pyroptosis were evaluated in vitro. The relationship between HCC-1 concentration in serum and atherosclerosis was analyzed in patients with atherosclerosis. RESULTS: HCC-1 expression was positively correlated with the occurrence and stable-unstable switch of atherosclerosis under bioinformatic analysis, which is further supported by the results of increased HCC-1 expression in AS patients both in serum and atherosclerotic plaque. adeno-associated virus serotype 9-HCC-1 mice had higher levels of inflammatory factors, increased macrophage accumulation and pyroptotic rate in plaque, and decreased atherosclerotic plaque stability. In vitro, HCC-1 promoted monocyte adhesion and M1 polarization and induced inflammation and pyroptosis both in ECs and macrophages. CONCLUSIONS: HCC-1 expression was increased in patients with atherosclerosis, and HCC-1 overexpression accelerated atherosclerotic burden via an enhancement in monocyte recruitment, M1 polarization, and pyroptosis both in ECs and macrophages. Our findings suggested that HCC-1 may serve as an early biomarker for the diagnosis of atherosclerosis, with the capacity to reflect the degree of stenosis.
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Poliovirus receptor-related immunoglobulin domain-containing protein, or PVRIG, is a newly discovered immune checkpoint that has emerged as a promising target for cancer immunotherapy. It is primarily expressed on activated T and natural killer (NK) cells, and once engaged with its ligand, PVRL2, it induces inhibitory signaling in T cells, thereby promoting the functional exhaustion of tumor-infiltrating lymphocytes (TILs). Here, we characterized IBI352g4a, a novel humanized anti-PVRIG antibody with Fc-competent function, explored the mechanism of its antitumor activity in preclinical models, and systemically evaluated the contribution of FcrR engagement to PVRIG blockade-induced antitumor activity. IBI352g4a binds to the extracellular domain of human PVRIG with high affinity (Kd = 0.53 nM) and specificity, and fully blocks the interaction between PVRIG and its ligand PVRL2. Unlike other immune checkpoints, IBI352g4a significantly induced NK cell activation and degranulation, but had a minimal effect on T-cell activation in in vitro functional assays. IBI352g4a induced strong antitumor effect in several preclinic models, through in vivo mechanism analysis we found that both NK and T cells contribute to the antitumor effect, but NK cells play predominant roles. Specifically, a single dose of IBI352g4a induced significant NK cell activation in TILs, but T-cell activation was observed only after the second dose. Moreover, the Fc effector function is critical for both NK cell activation and treatment efficacy in vitro and in vivo. Our study, for the first time, demonstrates that both NK activation and FcrR engagement are required for antitumor efficacy induced by PVRIG blockade.
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Células Matadoras Naturais , Neoplasias , Humanos , Ligantes , Imunoterapia , Linfócitos do Interstício Tumoral , Neoplasias/metabolismoRESUMO
BACKGROUND: In this study, an automatic corneal contour extraction algorithm with a shared model is developed to extract contours from dynamic corneal videos containing noise, which improves the accuracy of corneal biomechanical evaluation and clinical diagnoses. The algorithm does not require manual labeling and completes the unsupervised semantic segmentation of each frame in corneal dynamic deformation videos based on a fully convolutional deep-learning network using corneal geometry and texture information. RESULTS: We included 1027 corneal videos at Tianjin Eye Hospital (Nankai University Affiliated Eye Hospital) from May 2020 to November 2021. The videos were obtained by the ultra-high-speed Scheimpflug camera, and then we used the shared model mechanism to accelerate the segmentation of corneal regions in videos, effectively resist noise, determine corneal regions based on shape factors, and finally achieve automatic and accurate extraction of corneal region contours. The Intersection over Union (IoU) of the extracted and real corneal contours using this algorithm reached 95%, and the average overlap error was 0.05, implying that the extracted corneal contour overlapped almost completely with the real contour. CONCLUSIONS: Compared to other algorithms, the method introduced in this study does not require manual annotation of corneal contour data in advance and can still extract accurate corneal contours from noisy corneal videos with good repeatability.
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Algoritmos , Córnea , Humanos , Córnea/diagnóstico por imagem , SemânticaRESUMO
Pain is a multi-dimensional phenomenon that encompasses both physical pain experienced physiologically and social pain experienced emotionally. The interactions between them are thought to lead to increased pain load. However, the effect of social pain on physical pain perception during interactions remains unclear. Four experiments were conducted merging physical and social pains to examine the behavioral pattern and neural mechanism of the effect of social pain on physical pain perception. Seemingly paradoxical effects of social pain were observed, which both facilitated and inhibited physical pain perception under different attention orientations. Brain imaging revealed that the posterior insula encoded the facilitatory effect, whereas the frontal pole engaged in the inhibitory effect. At a higher level, the thalamus further modulated both processes, playing a switch-like role under different concern statuses of social pain. These results provide direct evidence for the dual-pathway mechanism of the effect of social pain on physical pain.
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Long-term consumption of mixed fraudulent edible oils increases the risk of developing of chronic diseases which has been a threat to the public health globally. The complicated global supply-chain is making the industry malpractices had often gone undetected. In order to restore the confidence of consumers, traceability (and accountability) of every level in the supply chain is vital. In this work, we shown that machine learning (ML) assisted windowed spectroscopy (e.g., visible-band, infra-red band) produces high-throughput, non-destructive, and label-free authentication of edible oils (e.g., olive oils, sunflower oils), offers the feasibility for rapid analysis of large-scale industrial screening. We report achieving high-level of discriminant (AUC > 0.96) in the large-scale (n ≈ 11,500) of adulteration in olive oils. Notably, high clustering fidelity of 'spectral fingerprints' achieved created opportunity for (hypothesis-free) self-sustaining large database compilation which was never possible without machine learning. (137 words).
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Contaminação de Alimentos , Óleos de Plantas , Óleos de Plantas/química , Azeite de Oliva/química , Óleo de Girassol , Análise Espectral , Contaminação de Alimentos/análiseRESUMO
Efficient, fast, and robust scintillators for ionizing radiation detection are crucial in various fields, including medical diagnostics, defense, and particle physics. However, traditional scintillator technologies face challenges in simultaneously achieving optimal performance and high-speed operation. Herein we introduce colloidal quantum shell heterostructures as X-ray and electron scintillators, combining efficiency, speed, and durability. Quantum shells exhibit light yields up to 70,000 photons MeV-1 at room temperature, enabled by their high multiexciton radiative efficiency thanks to long Auger-Meitner lifetimes (>10 ns). Radioluminescence is fast, with lifetimes of 2.5 ns and sub-100 ps rise times. Additionally, quantum shells do not exhibit afterglow and maintain stable scintillation even under high X-ray doses (>109 Gy). Furthermore, we showcase quantum shells for X-ray imaging achieving a spatial resolution as high as 28 line pairs per millimeter. Overall, efficient, fast, and durable scintillation make quantum shells appealing in applications ranging from ultrafast radiation detection to high-resolution imaging.
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Understanding and interpreting dynamics of functional materials in situ is a grand challenge in physics and materials science due to the difficulty of experimentally probing materials at varied length and time scales. X-ray photon correlation spectroscopy (XPCS) is uniquely well-suited for characterizing materials dynamics over wide-ranging time scales. However, spatial and temporal heterogeneity in material behavior can make interpretation of experimental XPCS data difficult. In this work, we have developed an unsupervised deep learning (DL) framework for automated classification of relaxation dynamics from experimental data without requiring any prior physical knowledge of the system. We demonstrate how this method can be used to accelerate exploration of large datasets to identify samples of interest, and we apply this approach to directly correlate microscopic dynamics with macroscopic properties of a model system. Importantly, this DL framework is material and process agnostic, marking a concrete step towards autonomous materials discovery.
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BACKGROUND: Psychological stress is associated with various diseases including liver dysfunction, yet effective intervention strategies remain lacking due to the unrevealed pathogenesis mechanism. PURPOSE: This study aims to explore the relevance between BMAL1-controlled circadian rhythms and lipoxygenase 15 (ALOX15)-mediated phospholipids peroxidation in psychological stress-induced liver injury, and to investigate whether hepatocyte phospholipid peroxidation signaling is involved in the hepatoprotective effects of a Chinese patent medicine, Pien Tze Huang (PZH). METHODS: Restraint stress models were established to investigate the underlying molecular mechanisms of psychological stress-induced liver injury and the hepatoprotective effects of PZH. Redox lipidomics based on liquid chromatography-tandem mass spectrometry was applied for lipid profiling. RESULTS: The present study discovered that acute restraint stress could induce liver injury. Notably, lipidomic analysis confirmed that phospholipid peroxidation was accumulated in the livers of stressed mice. Additionally, the essential core circadian clock gene Brain and Muscle Arnt-like Protein-1 (Bmal1) was altered in stressed mice. Circadian disruption in mice, as well as BMAL1-overexpression in human HepaRG cells, also appeared to have a significant increase in phospholipid peroxidation, suggesting that stress-induced liver injury is closely related to circadian rhythm and phospholipid peroxidation. Subsequently, arachidonate 15-lipoxygenase (ALOX15), a critical enzyme that contributed to phospholipid peroxidation, was screened as a potential regulatory target of BMAL1. Mechanistically, BMAL1 promoted ALOX15 expression via direct binding to an E-box-like motif in the promoter. Finally, this study revealed that PZH treatment significantly relieved pathological symptoms of psychological stress-induced liver injury with a potential mechanism of alleviating ALOX15-mediated phospholipid peroxidation. CONCLUSION: Our findings illustrate the critical role of BMAL1-triggered phospholipid peroxidation in psychological stress-induced liver injury and provide new insight into treating psychological stress-associated liver diseases by TCM intervention.