Modulating piezoelectricity and mechanical strength via three-dimensional gradient structure for piezoelectric composites.

Advanced flexible electronic devices make urgent demand for wearing comfort and data accuracy. Piezoelectric composites exhibit great potential, but mutually constrained mechanical strength and electrical output limit their further applications. Here, we design a gradient PMN-PT/PVDF nanocomposite via a non-equilibrium process integrated with a modified electrospinning and hot-pressing process to modulate the piezoelectric output and mechanical strength. The enhanced piezoelectric output together with the mechanical strength of the gradient structure are verified from both the experimental and simulation results. Ascribed to a unique three-dimensional gradient distribution, the prepared PMN-PT/PVDF nanocomposite exhibits an excellent mechanical strength (830 MPa) and piezoelectric performance (1.08 V), which are substantially higher than those of a randomly dispersed nanocomposite. The enhancement mechanism is revealed in terms of polarization, stress and crystallinity. These results of the gradient structure offer new opportunities to understand the structure-related mechanical and electrical behaviors of a nanocomposite, and support the design of a nanocomposite with overall performance.

Interpretable machine-learning model for real-time, clustered risk factor analysis of sepsis and septic death in critical care.

BACKGROUND AND OBJECTIVE: Interpretable and real-time prediction of sepsis and risk factor analysis could enable timely treatment by clinicians and improve patient outcomes. To develop an interpretable machine-learning model for the prediction and risk factor analysis of sepsis and septic death. METHODS: This is a retrospective observational cohort study based on the Medical Information Mart for Intensive Care (MIMIC-IV) dataset; 69,619 patients from the database were screened. The two outcomes include patients diagnosed with sepsis and the death of septic patients. Clinical variables from ICU admission to outcomes were analyzed: demographic data, vital signs, Glasgow Coma Scale scores, laboratory test results, and results for arterial blood gasses (ABGs). Model performance was compared using the area under the receiver operating characteristic curve (AUROC). Model interpretations were based on the Shapley additive explanations (SHAP), and the clustered analysis was based on the combination of K-means and dimensionality reduction algorithms of t-SNE and PCA. RESULTS: For the analysis of sepsis and septic death, 47,185 and 2480 patients were enrolled, respectively. The XGBoost model achieved a predictive value of area under the curve (AUC): 0.745 [0.731-0.759] for sepsis prediction and 0.8 [0.77, 0.828] for septic death prediction. The real-time prediction model was trained to predict by day and visualize the individual or combined risk factor effects on the outcomes based on SHAP values. Clustered analysis separated the two phenotypes with distinct risk factors among patients with septic death. CONCLUSION: The proposed real-time, clustered prediction model for sepsis and septic death exhibited superior performance in predicting the outcomes and visualizing the risk factors in a real-time and interpretable manner to distinguish and mitigate patient risks, thus promising immense potential in effective clinical decision making and comprehensive understanding of complex diseases such as sepsis.

CXCL8 induces M2 macrophage polarization and inhibits CD8+ T cell infiltration to generate an immunosuppressive microenvironment in colorectal cancer.

The poor prognosis of immunotherapy in patients with colorectal cancer (CRC) necessitates a comprehensive understanding of the immunosuppressive mechanisms within tumor microenvironment (TME). Undoubtedly, the anti-tumor immune cells play an indispensable role in immune tolerance. Therefore, it is imperative to investigate novel immune-related factors that have the capacity to enhance anti-tumor immunity. Here, we employed bioinformatic analysis using R and Cytoscape to identify the hub gene chemokine (C-X-C motif) ligand 8 (CXCL8), which is overexpressed in CRC, in the malignant progression of CRC. However, its specific role of CXCL8 in CRC immunity remains to be elucidated. For this purpose, we evaluated how tumor-derived CXCL8 promotes M2 macrophage infiltration by in vivo and in vitro, which can be triggered by IL-1ß within TME. Mechanistically, CXCL8-induced polarization of M2 macrophages depends on the activation of the STAT3 signaling. Finally, immunohistochemistry and multiplexed immunohistochemistry analysis identified that CXCL8 not only enhances PD-L1+ M2 macrophage infiltration but also attenuates the recruitment of PD-1+ CD8+ T cells in murine CRC models. Together, these findings emphasize the critical role for CXCL8 in promoting M2 macrophage polarization and inhibiting CD8+ T cell infiltration, thereby links CXCL8 to the emergency of immunosuppressive microenvironment facilitating tumor evasion. Overall, these findings may provide novel strategy for CRC immunotherapy.

Efficient FMT reconstruction based on L1-αL2 regularization via half-quadratic splitting and a two-probe separation light source strategy.

Fluorescence molecular tomography (FMT) can achieve noninvasive, high-contrast, high-sensitivity three-dimensional imaging in vivo by relying on a variety of fluorescent molecular probes, and has excellent clinical transformation prospects in the detection of tumors in vivo. However, the limited surface fluorescence makes the FMT reconstruction have some ill-posedness, and it is difficult to obtain the ideal reconstruction effect. In this paper, two different emission fluorescent probes and L 1-L 2 regularization are combined to improve the temporal and spatial resolution of FMT visual reconstruction by introducing the weighting factor α and a half-quadratic splitting alternating optimization (HQSAO) iterative algorithm. By introducing an auxiliary variable, the HQSAO method breaks the sparse FMT reconstruction task into two subproblems that can be solved in turn: simple reconstruction and image denoising. The weight factor α (α>1) can increase the weight of nonconvex terms to further promote the sparsity of the algorithm. Importantly, this paper combines two different dominant fluorescent probes to achieve high-quality reconstruction of dual light sources. The performance of the proposed reconstruction strategy was evaluated by digital mouse and nude mouse single/dual light source models. The simulation results show that the HQSAO iterative algorithm can achieve more excellent positioning accuracy and morphology distribution in a shorter time. In vivo experiments also further prove that the HQSAO algorithm has advantages in light source information preservation and artifact suppression. In particular, the introduction of two main emission fluorescent probes makes it easy to separate and reconstruct the dual light sources. When it comes to localization and three-dimensional morphology, the results of the reconstruction are much better than those using a fluorescent probe, which further facilitates the clinical transformation of FMT.

Magnetic flux leakage detection based on a sensitivity-enhanced fiber Bragg grating magnetic field sensor.

We propose a sensitivity-enhanced fiber Bragg grating (FBG) magnetic field sensor for magnetic flux leakage (MFL) detection. The testing system consists of the FBG, suspended strain concentration structure, and two ceramic tubes bonded on a Terfenol-D base. We show the relation between the MFL and the width and depth of the crack, the lift-off of the sensor away from the surface of the workpiece, and the angle between the orientation of the sensor and the magnetization direction. The experimental results are very consistent with those obtained from finite element analysis simulations. The sensitivity of the sensor is increased to 81.11 pm/mT for increasing magnetic fields and 91.55 pm/mT for decreasing magnetic fields. The MFL test demonstrates that the sensor can identify a crack with a width of 0.5 mm and depth of 2 mm in an 8 mm thick workpiece. To the best of our knowledge, the magnetic field sensor proposed in this work has the highest sensitivity compared with the same types of sensors. Moreover, the application of an FBG-Terfenol-D based magnetic field sensor in the MFL test shows good performance. Compared with traditional electrical MFL testing technologies, the sensitivity-enhanced optical fiber magnetic field sensor has a higher resolution and longer survival time in harsh environments.

UAV hyperspectral combined with LiDAR to estimate chlorophyll content at the stand and individual tree scales.

Chlorophyll is an important indicator of vegetation health status, accurate estimation of which is important for evaluating forest carbon sink. In this study, we estimated the chlorophyll content of coniferous forests, broad-leaved forests and mixed forest stands at stand and individual tree level by unmanned air vehicle (UAV) hyperspectral data combined with light detection and ranging (LiDAR) point clouds, which improved the non-destructive estimation accuracy of forest chlorophyll. We further comprehensively analyzed the spatial distribution of chlorophyll content at different scales. A total of 36 spectral characteristic variables related to chlorophyll content were screened by correlation analysis based on the fusion of UAV hyperspectral data and LiDAR point clouds combining with the empirical data from ground plots. We constructed multiple models for chlorophyll estimation by using statistical model, including multiple stepwise regression, BP neural network, BP neural network optimized by firefly algorithm, random forest and hybrid data-driven PROSPECT mechanism model. The optimal model was selected to estimate the chlorophyll content. The horizontal and vertical distribution of chlorophyll content at the stand level and individual tree level were analyzed. The results showed that the random forest model was superior to the models constructed by multiple stepwise regression, BP neural network and BP neural network optimized by firefly algorithm for chlorophyll estimation with R2 and RMSE of 0.59-0.64 and 3.79-5.83 µg·cm-2, respectively. The accuracy of the mechanism model was the highest, with R2 and RMSE of 0.97 and 3.40 µg·cm-2. The chlorophyll contents differed across stand types, with that in broad-leaved forest (25.25-31.60 µg·cm-2) being higher than mixed forest (13.52-23.93 µg·cm-2) and coniferous forest (6.40-13.71 µg·cm-2). There were significant differences in chlorophyll contents the in vertical direction among different stands. For individual tree of different species, the chlorophyll content inside the canopy was lower than that outside the canopy in the horizontal direction. In the vertical direction, there was no difference in chlorophyll content among different layers of Pinus sylvestris var. mongolica canopy. However, significant differences were observed among the upper, middle, and lower layers of Juglans mandshurica canopy. Using the fusion of hyperspectral image and LiDAR point cloud data, the mechanism model driven by hybrid data could effectively improve the accuracy and stability of chlorophyll content estimation at different scales.

Colloidal tubular microrobots for cargo transport and compression.

Microrobot swarms have seen increased interest in recent years due to their potentials for in vivo delivery and imaging with cooperative propulsion modes and enhanced imaging signals. Yet most swarms developed so far are limited to dense particle aggregates, far simpler than complicated three-dimensional assemblies of anisotropic particles. Here, we show via assembly path design that complex hollow tubular structures can be assembled from simple isotropic colloidal spheres and those complicated, metastable, microtubes can be formed from simple, energetically favorable colloidal membranes. The assembled microtubes can remain intact and roll under a precessing magnetic field, with propulsion directions and velocities precisely controlled by field components. The hollow spaces inside enable these tubular microrobots to grab, transport, and release cargos on command. We also demonstrate unique compressing and uncompressing capabilities with our tubular microrobots, making them effective microtweezers. Our work shows that complicated microrobots can be transformed from simple assemblies, providing an insight on building micromachines.

BEX1 supports the stemness of hepatoblastoma by facilitating Warburg effect in a PPARγ/PDK1 dependent manner.

BACKGROUND: Hepatoblastoma (HB) is a highly aggressive paediatric malignancy that exhibits a high presence of cancer stem cells (CSCs), which related to tumour recurrence and chemotherapy resistance. Brain expressed X-linked protein 1 (BEX1) plays a pivotal role in ciliogenesis, axon regeneration and differentiation of neural stem cells. However, the role of BEX1 in metabolic and stemness programs in HB remains unclear. METHODS: BEX1 expression in human and mouse HB was analyzed using gene expression profile data from NCBI GEO and immunohistochemical validation. Seahorse extracellular flux analyzer, ultra-high-performance liquid-chromatography mass spectrometry (LC-MS), flow cytometry, qRT-PCR, Western Blot, sphere formation assay, and diluted xenograft tumour formation assay were used to analyze metabolic and stemness features. RESULTS: Our results indicated that overexpression of BEX1 significantly enhanced the Warburg effect in HB cells. Furthermore, glycolysis inhibition largely attenuated the effects of BEX1 on HB cell growth and self-renewal, suggesting that BEX1 promotes stemness maintenance of HB cells by regulating the Warburg effect. Mechanistically, BEX1 enhances Warburg effect through the downregulation of peroxisome proliferator-activated receptor-gamma (PPARγ). Furthermore, pyruvate dehydrogenase kinase isozyme 1 (PDK1) is required for PPARγ-induced inhibition of Warburg effect in HB. In addition, BEX1 supports the stemness of HB by enhancing Warburg effect in a PPARγ/PDK1 dependent manner. CONCLUSIONS: HB patients with high BEX1 and PDK1 expression had a poor prognosis. BEX1 promotes the stemness maintenance of HB cells via modulating the Warburg effect, which depends on PPARγ/PDK1 axis. Pioglitazone could be used to target BEX1-mediated stemness properties in HB by upregulating PPARγ.

ParSE-seq: A Calibrated Multiplexed Assay to Facilitate the Clinical Classification of Putative Splice-altering Variants.

Background: Interpreting the clinical significance of putative splice-altering variants outside 2-base pair canonical splice sites remains difficult without functional studies. Methods: We developed Parallel Splice Effect Sequencing (ParSE-seq), a multiplexed minigene-based assay, to test variant effects on RNA splicing quantified by high-throughput sequencing. We studied variants in SCN5A, an arrhythmia-associated gene which encodes the major cardiac voltage-gated sodium channel. We used the computational tool SpliceAI to prioritize exonic and intronic candidate splice variants, and ClinVar to select benign and pathogenic control variants. We generated a pool of 284 barcoded minigene plasmids, transfected them into Human Embryonic Kidney (HEK293) cells and induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs), sequenced the resulting pools of splicing products, and calibrated the assay to the American College of Medical Genetics and Genomics scheme. Variants were interpreted using the calibrated functional data, and experimental data were compared to SpliceAI predictions. We further studied some splice-altering missense variants by cDNA-based automated patch clamping (APC) in HEK cells and assessed splicing and sodium channel function in CRISPR-edited iPSC-CMs. Results: ParSE-seq revealed the splicing effect of 224 SCN5A variants in iPSC-CMs and 244 variants in HEK293 cells. The scores between the cell types were highly correlated (R 2 =0.84). In iPSCs, the assay had concordant scores for 21/22 benign/likely benign and 24/25 pathogenic/likely pathogenic control variants from ClinVar. 43/112 exonic variants and 35/70 intronic variants with determinate scores disrupted splicing. 11 of 42 variants of uncertain significance were reclassified, and 29 of 34 variants with conflicting interpretations were reclassified using the functional data. SpliceAI computational predictions correlated well with experimental data (AUC = 0.96). We identified 20 unique SCN5A missense variants that disrupted splicing, and 2 clinically observed splice-altering missense variants of uncertain significance had normal function when tested with the cDNA-based APC assay. A splice-altering intronic variant detected by ParSE-seq, c.1891-5C>G, also disrupted splicing and sodium current when introduced into iPSC-CMs at the endogenous locus by CRISPR editing. Conclusions: ParSE-seq is a calibrated, multiplexed, high-throughput assay to facilitate the classification of candidate splice-altering variants.

Expanded interlayer spacing of SnO2 QDs-Decorated MXene for highly selective luteolin detection with Ultra-Low limit of detection.

Although there have been advancements in electrochemical catalysts for luteolin detection, their practical use is constrained by low sensitivity, inadequate selectivity, and unsatisfactory limit of detection. MXene, a class of 2D materials, possesses exceptional physical-chemical properties that make it highly suitable for electrochemical detection. Nevertheless, the self-stacking and limited interlayer spacing of MXene impede its extensive application in electrochemical detection. Herein, a SnO2 QDs-MXene composite is synthesized for selective electrochemical detection of luteolin. Inserting SnO2 QDs between tightly stacked MXene layers expands the d-spacing of MXene, enhancing the specific surface area and enabling abundant active sites for redox reactions. The inclusion of MXene in the modified SnO2 QDs-MXene/GCE electrode significantly enhances electron transfer. As a result, the electrode demonstrates exceptional luteolin detection capabilities, including a wide linear range (0.1-1200 nM), high sensitivity (12.4 µA µM-1), and an ultra-low limit of detection (0.14 nM). Additionally, the SnO2 QDs-MXene/GCE electrode exhibits good repeatability, excellent reproducibility, remarkable stability, and high selectivity, making it suitable for practical sample analysis. This research contributes to advancing ultra-low limit of detection sensors for accurate luteolin detection.

Genetically engineered Lactobacillus paracasei rescues colonic angiotensin converting enzyme 2 (ACE2) and attenuates hypertension in female Ace2 knock out rats.

Engineered gut microbiota represents a new frontier in medicine, in part serving as a vehicle for the delivery of therapeutic biologics to treat a range of host conditions. The gut microbiota plays a significant role in blood pressure regulation; thus, manipulation of gut microbiota is a promising avenue for hypertension treatment. In this study, we tested the potential of Lactobacillus paracasei, genetically engineered to produce and deliver human angiotensin converting enzyme 2 (Lacto-hACE2), to regulate blood pressure in a rat model of hypertension with genetic ablation of endogenous Ace2 (Ace2-/- and Ace2-/y). Our findings reveal a sex-specific reduction in blood pressure in female (Ace2-/-) but not male (Ace2-/y) rats following colonization with the Lacto-hACE2. This beneficial effect of lowering blood pressure was aligned with a specific reduction in colonic angiotensin II, but not renal angiotensin II, suggesting the importance of colonic Ace2 in the regulation of blood pressure. We conclude that this approach of targeting the colon with engineered bacteria for delivery of ACE2 represents a promising new paradigm in the development of antihypertensive therapeutics.

Histone methyltransferase SETD2 inhibits M1 macrophage polarization and glycolysis by suppressing HIF-1α in sepsis-induced acute lung injury.

Sepsis is a severe syndrome caused by the imbalance of the host response to infection, accompanied by multiple organ damage, especially acute lung injury. SET Domain-Containing 2 (SETD2) is a methyltransferase catalyzing H3 lysine 36 trimethylation (H3K36me3) that regulates multiple biological processes. This study focused on explicating the action of SETD2 on macrophage function in sepsis and the precise mechanism involved. Enzyme-linked immunosorbent assay, real-time quantitative polymerase chain reaction (RT-qPCR), and Western blotting were used to determine expression. Luciferase reporter assay and chromatin immunoprecipitation assay were conducted to detect the binding of SETD2 or H3K36me3 with the hypoxia-inducible factor 1, alpha subunit (Hif1a) gene. A sepsis-induced acute lung injury model was constructed via cecal ligation and puncture (CLP). SETD2 was decreased in RAW 264.7 cells stimulated by lipopolysaccharide (LPS). Besides, SETD2 suppressed M1 macrophage polarization and glycolysis caused by LPS. HIF-1α was enhanced in RAW 264.7 cells stimulated by LPS and inversely related to SETD2 expression. In addition, SETD2-catalyzed H3K36me3 bound to the Hif1a gene to modulate HIF-1α expression. Furthermore, Hif1a silencing suppressed Setd2 silencing-induced M1 macrophage polarization and glycolysis in RAW 264.7 cells. Moreover, overexpression of Setd2 inhibited CLP-induced lung injury and M1 macrophage polarization in mice. SETD2 suppressed M1 macrophage polarization and glycolysis via regulating HIF-1α through catalyzing H3K36me3 in sepsis.

Current Status of Research on Tuina for Analgesia: A Bibliometric and Visual Analysis.

Purpose: Tuina is a nonpharmacological modality for pain relief that has found applications in the treatment of several pain disorders. Tuina analgesia has been increasingly studied; however, few studies have focused on the previous publication trends, prevalent research areas, collaborations, and other factors. This study aimed to systematically analyze research trends and hot topics in the field of tuina analgesia over the past 30 years, using bibliometric analysis, to inform future research. Methods: The web of science database was searched for literature on tuina analgesia from 1992-2023. VOSviewer and CiteSpace were used to analyze annual publication volumes, countries, institutions, journals and CO-cited journals, authorship, articles, and keywords and their relevance, and to perform co-occurrence and clustering analyses. Results: A total of 621 literature elements were included in the analysis. The annual volume of publications has increased steadily in recent years. The top three high-yielding countries were the United States, China, and Canada, respectively. The top three institutional outputs were from Shanghai University of Chinese medicine, Beijing University of Chinese medicine, and McMaster University, respectively. Notably, there was an imbalance between national outputs and centrality, with higher centrality in the United States (0.35) and lower in China (0.01). Cochrane Database of Systematic Reviews was the journal with the most publications (22), and PAIN was the most influential co-cited journals (publications=306). Moreover, current research in this field was dominated by studies on Tuina for relieving postoperative pain, the effectiveness of Tuina analgesia, and Tuina treatment for pain accompanied by anxiety. Conclusion: This study employed bibliometrics to analyze the literature on Tuina for pain treatment over a 30-year period, identifying potential collaborators, institutions, hot topics, and future research trends that will inform potential future directions.

Effect of Nano Ni Particles on the Microstructure and Thermophysical Properties of Sn-Bi-Zn Heat Transfer and Heat Storage Alloys.

The specific heat capacity plays a crucial role in influencing the heat transfer efficiency of materials. Considering the relatively low specific heat capacity of metals, this study focuses on investigating the impact of second-phase nano Ni particles on the microstructure and thermophysical properties of the alloy matrix. The alloys' phase compositions and microstructures were examined using X-ray diffraction phase analysis (XRD), electron probe micromorphology analysis (EPMA), and X-ray fluorescence spectroscopy (XRF). Furthermore, the thermophysical properties of the alloys were comprehensively analyzed through the employment of a differential scanning calorimeter (DSC) and the laser flash method (LFA). The addition of second-phase nanoparticles significantly increased the specific heat capacity of the alloy in the liquid state; however, the phenomenon of nanoparticle agglomeration diminishes this improvement. The analysis of the specific heat enhancement mechanism indicates that ordered states are formed between the second-phase solid nanoparticles and the melted metal in the liquid state. With the increase in temperature, the destruction of these ordered states requires additional heat, resulting in the increase of specific heat capacity.

Identification and Expression Analysis of the Alfin-like Gene Family in Tomato and the Role of SlAL3 in Salt and Drought Stresses.

Alfin-like (AL) transcription factors are a family of plant-specific genes with a PHD-finger-like structural domain at the C-terminus and a DUF3594 structural domain at the N-terminus that play important roles in plant development and stress response. In the present study, genome-wide identification and analysis were performed of the AL protein family in cultivated tomato (Solanum lycopersicum) and three wild relatives (S. pennellii, S. pimpinellifolium, and S. lycopersicoides) to evaluate their response to different abiotic stresses. A total of 39 ALs were identified and classified into four groups and based on phylogenetic tree and evolutionary analysis were shown to have formed prior to the differentiation of monocotyledons and dicots. Moreover, cis-acting element analysis revealed that various phytohormone response and abiotic stress response elements were highly existed in tomato. In addition, further analysis of the SlAL3 gene revealed that its expression was induced by drought and salt stresses and localized to the nucleus. In conclusion, our findings concerning AL genes provide useful information for further studies on their functions and regulatory mechanisms and provide theoretical references for studying AL gene response to abiotic stresses in plants.

A High-Certainty Visual Servo Control Method for a Space Manipulator with Flexible Joints.

This paper introduces a novel high-certainty visual servo algorithm for a space manipulator with flexible joints, which consists of a kinematic motion planner and a Lyapunov dynamics model reference adaptive controller. To enhance kinematic certainty, a three-stage motion planner is proposed in Cartesian space to control the intermediate states and minimize the relative position error between the manipulator and the target. Moreover, a planner in joint space based on the fast gradient descent algorithm is proposed to optimize the joint's deviation from the centrality. To improve dynamic certainty, an adaptive control algorithm based on Lyapunov stability analysis is used to enhance the system's anti-disturbance capability. As to the basic PBVS (position-based visual servo methods) algorithm, the proposed method aims to increase the certainty of the intermediate states to avoid collision. A physical experiment is designed to validate the effectiveness of the algorithm. The experiment shows that the visual servo motion state in Cartesian space is basically consistent with the planned three-stage motion state, the average joint deviation index from the centrality is less than 40%, and the motion trajectory consistency exceeds 90% under different inertial load disturbances. Overall, this method reduces the risk of collision by enhancing the certainty of the basic PBVS algorithm.

Regulating tumor glycometabolism and the immune microenvironment by inhibiting lactate dehydrogenase with platinum(iv) complexes.

Lactate dehydrogenase (LDH) is a key enzyme involved in the process of glycolysis, assisting cancer cells to take in glucose and generate lactate, as well as to suppress and evade the immune system by altering the tumor microenvironment (TME). Platinum(iv) complexes MDP and DDP were prepared by modifying cisplatin with diclofenac at the axial position(s). These complexes exhibited potent antiproliferative activity against a panel of human cancer cell lines. In particular, DDP downregulated the expression of LDHA, LDHB, and MCTs to inhibit the production and influx/efflux of lactate in cancer cells, impeding both glycolysis and glucose oxidation. MDP and DDP also reduced the expression of HIF-1α, ARG1 and VEGF, thereby disrupting the formation of tumor vasculature. Furthermore, they promoted the repolarization of macrophages from the tumor-supportive M2 phenotype to the tumor-suppressive M1 phenotype in the TME, thus enhancing the antitumor immune response. The antitumor mechanism involves reprogramming the energy metabolism of tumor cells and relieving the immunosuppressive TME.

Exclusive confinement of Bi3+-activators in the triangular prism enabling efficient and thermally stable green emission in the tridymite-type phosphor CaBaGa4O8:Bi3.

Recently, Bi3+-activated phosphors have been extensively studied for potential applications in phosphor-converted white light-emitting diodes (pc-WLEDs). However, Bi3+ activators usually exhibit low quantum efficiency and poor thermal stability due to the outermost 6s6p-orbitals of Bi3+ being strongly coupled with the host lattice, inhibiting potential applications. Herein, we rationally design a novel phosphor CaBaGa4O8:Bi3+, which adopts a tridymite-type structure and crystallizes in the space group of Imm2. CaBaGa4O8:Bi3+ presents a bright green light emission peaking at 530 nm with a FWHM narrower than 90 nm. Comprehensive structural and spectroscopic analyses unravelled that Bi3+ emitters were site-selectively incorporated into the triangular prism (Ca2+-site) in CaBaGa4O8:Bi3+ since there exist two distinct crystallographic sites that can accommodate the Bi3+ ions. An excellent luminescence thermal stability of 73% of the ambient temperature photoluminescence intensity can be maintained at 423 K for CaBaGa4O8:0.007Bi3+. Impressively, the quantum efficiency (QE) of CaBaGa4O8:0.007Bi3+ was remarkably improved to 47.2% for CaBaGa4O8:0.007Bi3+,0.03Zn2+via incorporating the Zn2+ compensators without sacrificing the luminescence thermal stability. The high thermal stability and QE of CaBaGa4O8:0.007Bi3+,0.03Zn2+ are superior to most of the Bi3+-activated green-emitting oxide phosphors. The perspective applications in pc-WLEDs for CaBaGa4O8:0.007Bi3+,0.03Zn2+ were also studied by fabricating LED devices.

Discovery of N-(4-(Aminomethyl)phenyl)-5-methylpyrimidin-2-amine Derivatives as Potent and Selective JAK2 Inhibitors.

The JAK2V617F mutation leads to JAK2 autophosphorylation and activation of downstream pathways, eventually resulting in myeloproliferative neoplasms (MPNs). Selective inhibitors showed advantages in terms of side effects; therefore, there is an urgent need to develop novel selective JAK2 inhibitors for treating MPNs. In this study, we described a series of N-(4-(aminomethyl)phenyl)pyrimidin-2-amine derivatives as selective JAK2 inhibitors. Systematic exploration through opening the tetrahydroisoquinoline based on the previous lead compound 13ac led to the discovery of the optimal compound A8. Compound A8 showed excellent potency on JAK2 kinase, with an IC50 value of 5 nM, and inhibited the phosphorylation of JAK2 and its downstream signaling pathway. Moreover, A8 exhibited 38.6-, 54.6-, and 41.2-fold selectivity for JAK1, JAK3, and TYK2, respectively. Compared to the lead compound, A8 demonstrated much better metabolic stabilities, with a bioavailability of 41.1%. These findings suggest that A8 is a relatively selective JAK2 inhibitor, deserving to be developed for treating MPNs.