Rational Design of the Alkali Metal Sn-Based Mixed Halides with Large Birefringence and Wide Transparent Range.

Birefringent materials are widely used in various advanced optical systems, owing to their vital role in creating and controlling polarized light. Currently, Sn2+-based compounds containing stereochemically active lone-pair (SCALP) cations are extensively investigated and considered as one class of promising birefringent materials. To solve the problem of relatively narrow bandgap of Sn2+-based compounds, alkali metals and multiple halogens are introduced to widen the bandgap during the research. Based on this strategy, four new Sn2+-based halides, A2Sn2F5Cl and ASnFCl2 (A = Rb and Cs), with large birefringence, short ultraviolet (UV) cutoff edge, and wide transparent range are successfully found. The birefringences of A2Sn2F5Cl (A = Rb and Cs) are 0.31 and 0.28 at 532 nm, respectively, which are among the largest in Sn-based halide family. Remarkably, A2Sn2F5Cl possess relatively shorter UV cutoff edge (<300 nm) and broad infrared (IR) transparent range (up to 16.6 µm), so they can become promising candidates as birefringent materials applied in both UV and IR regions. In addition, a comprehensive analysis on crystal structures and structure-property relationship of metal Sn2+-based halides is performed to fully understand this family. Therefore, this work provides insights into designing birefringent materials with balanced optical properties.

Phylogenomics of mulberries (Morus, Moraceae) inferred from plastomes and single copy nuclear genes.

Mulberries (genus Morus), belonging to the order Rosales, family Moraceae, are important woody plants due to their economic values in sericulture, as well as for nutritional benefits and medicinal values. However, the taxonomy and phylogeny of Morus, especially for the Asian species, remains challenging due to its wide geographical distribution, morphological plasticity, and interspecific hybridization. To better understand the evolutionary history of Morus, we combined plastomes and a large-scale nuclear gene analyses to investigate their phylogenetic relationships. We assembled the plastomes and screened 211 single-copy nuclear genes from 13 Morus species and related taxa. The plastomes of Morus species were relatively conserved in terms of genome size, gene content, synteny, IR boundary and codon usage. Using nuclear data, our results elucidated identical topologies based on coalescent and concatenation methods. The genus Morus was supported as monophyletic, with M. notabilis as the first diverging lineage and the two North American Morus species, M. microphylla and M. rubra, as sister to the other Asian species. In the Asian Morus species, interspecific relationships were completely resolved. However, cyto-nuclear discordances and gene tree-species tree conflicts were detected in the phylogenies of Morus, with multiple evidences supporting hybridization/introgression as the main cause of discordances between nuclear and plastid phylogenies, while gene tree-species tree conflicts were mainly caused by ILS.

Oral-gut microbial transmission promotes diabetic coronary heart disease.

BACKGROUND: Diabetes is a predominant driver of coronary artery disease worldwide. This study aims to unravel the distinct characteristics of oral and gut microbiota in diabetic coronary heart disease (DCHD). Simultaneously, we aim to establish a causal link between the diabetes-driven oral-gut microbiota axis and increased susceptibility to diabetic myocardial ischemia-reperfusion injury (MIRI). METHODS: We comprehensively investigated the microbial landscape in the oral and gut microbiota in DCHD using a discovery cohort (n = 183) and a validation chohort (n = 68). Systematically obtained oral (tongue-coating) and fecal specimens were subjected to metagenomic sequencing and qPCR analysis, respectively, to holistically characterize the microbial consortia. Next, we induced diabetic MIRI by administering streptozotocin to C57BL/6 mice and subsequently investigated the potential mechanisms of the oral-gut microbiota axis through antibiotic pre-treatment followed by gavage with specific bacterial strains (Fusobacterium nucleatum or fecal microbiota from DCHD patients) to C57BL/6 mice. RESULTS: Specific microbial signatures such as oral Fusobacterium nucleatum and gut Lactobacillus, Eubacterium, and Roseburia faecis, were identified as potential microbial biomarkers in DCHD. We further validated that oral Fusobacterium nucleatum and gut Lactobacillus are increased in DCHD patients, with a positive correlation between the two. Experimental evidence revealed that in hyperglycemic mice, augmented Fusobacterium nucleatum levels in the oral cavity were accompanied by an imbalance in the oral-gut axis, characterized by an increased coexistence of Fusobacterium nucleatum and Lactobacillus, along with elevated cardiac miRNA-21 and a greater extent of myocardial damage indicated by TTC, HE, TUNEL staining, all of which contributed to exacerbated MIRI. CONCLUSION: Our findings not only uncover dysregulation of the oral-gut microbiota axis in diabetes patients but also highlight the pivotal intermediary role of the increased abundance of oral F. nucleatum and gut Lactobacillus in exacerbating MIRI. Targeting the oral-gut microbiota axis emerges as a potent strategy for preventing and treating DCHD. Oral-gut microbial transmission constitutes an intermediate mechanism by which diabetes influences myocardial injury, offering new insights into preventing acute events in diabetic patients with coronary heart disease.

AX·(H2SeO3)n (A = K, Cs; X = Cl, Br; n = 1, 2): A Series of Ionic Cocrystals as Promising UV Birefringent Materials with Large Birefringence and Wide Band Gap.

The design and syntheses of new birefringent crystals will be of great importance in commercial applications and materials science. A series of ultraviolet (UV) birefringent crystals, AX·(H2SeO3)n (A = K, Cs; X = Cl, Br; n = 1, 2), with large sizes up to 23 × 6 × 3 mm3, was successfully synthesized by simple aqueous solution method. These four compounds belong to three different space groups. Isomorphic KCl·(H2SeO3)2 and CsCl·(H2SeO3)2 crystallize in the P1¯ space group, while CsBr·(H2SeO3)2 and CsCl·H2SeO3 crystallize in the P21/m and P21/c space groups, respectively. They exhibit cocrystal structures composed of [2(H2SeO3)]∞ and [AX]∞ frameworks, ingeniously inheriting the large optical anisotropy of selenite and the wide band gap of alkali metal halide. And it proves that these compounds indeed possess large birefringence (0.1-0.17 at 532 nm) and short UV cutoff edges (227-239 nm), achieving a balance of optical properties. This research affords a simple and viable strategy for the design and syntheses of new UV birefringent crystals. Besides, it is also found that the n value and ionic size (A and X ions) have important influences on the crystal structures and optical properties of AX·(H2SeO3)n. And this will promote further understanding of the alkali metal halide selenite family.

Na3K6(CO3)3(NO3)2X·6H2O (X = NO3, Cl, Br): Exploring High-Performance UV Birefringent Crystals Induced by Coplanar π-Conjugated CO3 and NO3 Groups.

Planar π-conjugated groups, like CO3, NO3, and BO3 triangles, are ideal functional units for designing birefringent materials due to their large optical anisotropy and wide band gap. The key point for designing birefringent crystals is to select appropriate functional building blocks (FBBs) and the proper arrangement mode. It is well known that the substitution strategy has proven to be a promising and accessible approach. In this work, alkali metals were chosen to regulate and control two different π-conjugated groups, CO3 and NO3, to build new compounds with large birefringence. Subsequently, three new compounds, Na3K6(CO3)3(NO3)2X·6H2O (X = NO3, Cl, Br), were successfully synthesized using the hydrothermal method. The aliovalent substitution between the [NO3]- anionic group and halogen anions [Cl]-/[Br]- has been achieved in these compounds. Na3K6(CO3)3(NO3)2X·6H2O feature the well-coplanar CO3 and NO3 groups in their crystal structure. This coplanar arrangement mode may effectively enhance the anisotropic polarizability of Na3K6(CO3)3(NO3)2X·6H2O. And their experimental birefringence can reach 0.094-0.131 at 546 nm. Diffuse reflectance spectra demonstrate that these compounds exhibit short ultraviolet (UV) absorption edges of ∼235 nm. Meanwhile, Na3K6(CO3)3(NO3)2X·6H2O also have an easily grown capacity under facile conditions. This work not only reports three new potential UV birefringent crystals but also provides a strategy to make the π-conjugated MO3 group coplanar.

Synergism of ApoE4 and systemic infectious burden is mediated by the APOE-NLRP3 axis in Alzheimer's disease.

BACKGROUND: Systemic infections are associated with the development of AD, especially in individuals carrying the APOE4 genotype. However, the detailed mechanism through which APOE4 affects microglia inflammatory response remains unclear. METHODS: We obtained human snRNA-seq data from the Synapse AD Knowledge Portal and assessed the DEGs between APOE3 and APOE4 isoforms in microglia. To verify the interaction between ApoE and infectious products, we used ApoE to stimulate in vitro and in vivo models in the presence or absence of LPS (or ATP). The NLRP3 gene knockout experiment was performed to demonstrate whether the APOE-NLRP3 axis was indispensable for microglia to regulate inflammation and mitochondrial autophagy. Results were evaluated by biochemical analyses and fluorescence imaging. RESULTS: Compared with APOE3, up-regulated genes in APOE4 gene carriers were involved in pro-inflammatory responses. ApoE4-stimulation significantly increased the levels of NLRP3 inflammasomes and ROS in microglia. Moreover, compared with ApoE4 alone, the co-incubation of ApoE4 with LPS (or ATP) markedly promoted pyroptosis. Both NF-κB activation and mitochondrial autophagy dysfunction were contributed by the increased level of NLRP3 inflammasomes induced by ApoE4. Furthermore, the pathological impairment induced by ApoE4 could be reversed by NLRP3 KO. CONCLUSIONS: Our study highlights the importance of NLRP3 inflammasomes in linking ApoE4 with microglia innate immune function. These findings not only provide a molecular basis for APOE4-mediated neuroinflammatory but also reveal the potential reason for the increased risk of AD in APOE4 gene carriers after contracting infectious diseases.

Self-supervised learning for medical image data with anatomy-oriented imaging planes.

Self-supervised learning has emerged as a powerful tool for pretraining deep networks on unlabeled data, prior to transfer learning of target tasks with limited annotation. The relevance between the pretraining pretext and target tasks is crucial to the success of transfer learning. Various pretext tasks have been proposed to utilize properties of medical image data (e.g., three dimensionality), which are more relevant to medical image analysis than generic ones for natural images. However, previous work rarely paid attention to data with anatomy-oriented imaging planes, e.g., standard cardiac magnetic resonance imaging views. As these imaging planes are defined according to the anatomy of the imaged organ, pretext tasks effectively exploiting this information can pretrain the networks to gain knowledge on the organ of interest. In this work, we propose two complementary pretext tasks for this group of medical image data based on the spatial relationship of the imaging planes. The first is to learn the relative orientation between the imaging planes and implemented as regressing their intersecting lines. The second exploits parallel imaging planes to regress their relative slice locations within a stack. Both pretext tasks are conceptually straightforward and easy to implement, and can be combined in multitask learning for better representation learning. Thorough experiments on two anatomical structures (heart and knee) and representative target tasks (semantic segmentation and classification) demonstrate that the proposed pretext tasks are effective in pretraining deep networks for remarkably boosted performance on the target tasks, and superior to other recent approaches.

Development, validation and visualization of a web-based nomogram for predicting risk of new-onset diabetes after percutaneous coronary intervention.

Simple and practical tools for screening high-risk new-onset diabetes after percutaneous coronary intervention (PCI) (NODAP) are urgently needed to improve post-PCI prognosis. We aimed to evaluate the risk factors for NODAP and develop an online prediction tool using conventional variables based on a multicenter database. China evidence-based Chinese medicine database consisted of 249, 987 patients from 4 hospitals in mainland China. Patients ≥ 18 years with implanted coronary stents for acute coronary syndromes and did not have diabetes before PCI were enrolled in this study. According to the occurrence of new-onset diabetes mellitus after PCI, the patients were divided into NODAP and Non-NODAP. After least absolute shrinkage and selection operator regression and logistic regression, the model features were selected and then the nomogram was developed and plotted. Model performance was evaluated by the receiver operating characteristic curve, calibration curve, Hosmer-Lemeshow test and decision curve analysis. The nomogram was also externally validated at a different hospital. Subsequently, we developed an online visualization tool and a corresponding risk stratification system to predict the risk of developing NODAP after PCI based on the model. A total of 2698 patients after PCI (1255 NODAP and 1443 non-NODAP) were included in the final analysis based on the multicenter database. Five predictors were identified after screening: fasting plasma glucose, low-density lipoprotein cholesterol, hypertension, family history of diabetes and use of diuretics. And then we developed a web-based nomogram ( https://mr.cscps.com.cn/wscoringtool/index.html ) incorporating the above conventional factors for predicting patients at high risk for NODAP. The nomogram showed good discrimination, calibration and clinical utility and could accurately stratify patients into different NODAP risks. We developed a simple and practical web-based nomogram based on multicenter database to screen for NODAP risk, which can assist clinicians in accurately identifying patients at high risk of NODAP and developing post-PCI management strategies to improved patient prognosis.

Network pharmacology, molecular docking, and in vitro experimental verification of the mechanism of Guanxining in treating diabetic atherosclerosis.

ETHNOPHARMACOLOGICAL RELEVANCE: Guanxinning(GXN) tablet is a patented traditional Chinese medicine widely used to prevent and treat cardiovascular diseases. However, its potential mechanism and target in anti-diabetic atherosclerosis have not been clarified. AIM: The aim of this study was to investigate the underlying targets and mechanisms of action GXN in the treatment of diabetic atherosclerosis, employing a combination of network pharmacology, molecular docking, and in vitro experimental verification. METHODS: We predicted the core components and targets of GXN in the treatment of diabetic atherosclerosis through various databases, and made analysis and molecular docking. In vitro, we induced injury in human umbilical vein endothelial cells using glucose/palmitate and observed the effects of GXN on cellular damage high-glucose and high-fat conditions, subsequently elucidating its molecular mechanisms. RESULTS: A total of 14 active components and 157 targets of GXN were identified. Using the PPI network, we selected 9 core active components and 20 targets of GXN. GO functional analysis revealed that these targets were primarily associated with apoptosis signaling pathways in response to endoplasmic reticulum stress and reactive oxygen species responses. Molecular docking confirmed the strong binding affinities of the primary active components of GXN with ERN1, MAPK1 and BECN1. In vitro experiments demonstrated the ability of GXN to restore endothelial cell activity, enhance cell migration and inhibit sICAM secretion, and upregulate the expression of endoplasmic reticulum stress-related proteins (IRE1, XBP1) and autophagy-related proteins (Beclin1, LC3A, and LC3B), while simultaneously inhibiting endothelial cell apoptosis under high-glucose and high-fat conditions. CONCLUSIONS: Our findings suggest that GXN can potentially safeguard endothelial cells from the adverse effects of high-glucose and high-fat by modulating the interactions between endoplasmic reticulum stress and autophagy. Therefore, GXN is a promising candidate for the prevention and treatment of diabetic atherosclerosis.

Influence of inherent minerals on metalworking fluids sludge pyrolysis: Products characterization and heavy metals behavior.

Safely and appropriately disposing of metalworking fluids sludge (MFS) remains a challenge owing to its highly hazardous properties, this work investigated MFS pyrolysis at various temperatures (500, 600, 700, 800, and 900 °C) for energy recovery and safety treatment of MFS. The experimental results indicated that inherent minerals at higher temperatures could enhance the gas yields and promote the qualities of oil and gas from MFS pyrolysis. The highest pyrolysis gas yield was achieved at 18.86 wt% after MFS pyrolysis at 900 °C. GC-MS analysis revealed that the inherent minerals facilitated a decrease in oxygenated and nitrogenated compounds within the oil, while simultaneously leading to a substantial increase in hydrocarbon contents. Notably, the highest content of aromatics (61.16%) was attained during pyrolysis at 900 °C. Moreover, inherent minerals improved carbon sequestration and the characteristics of biochar during the MFS pyrolysis. The leaching contents of heavy metals in biochars were reduced, thereby reducing the heavy metals associated environmental risk. This research suggests that the pyrolysis process was a promising approach for simultaneous energy recovery and MFS disposal with low environmental risk.

Identification of circulating microRNA-126-3p as a new biomarker for coronary artery calcification.

Objective: Several circulating microRNAs, including microRNA-126-3p, have been identified as diagnostic and prognostic biomarker of cardiovascular disease. However, whether microRNA-126-3p is an independent risk predictor for coronary artery calcification is unclear. Methods: In this prospective single-center study, we collected blood samples from coronary artery atherosclerosis patients (n = 54), patients with coronary artery calcification (n = 33) and controls (n = 56). Total RNA was extracted from plasma and blood cells with TRIzol reagents. The microRNA-126-3p level was determined via quantitative real-time polymerase chain reaction (RT-PCR). Results: MicroRNA-126-3p levels were significantly increased in patients with coronary artery calcification than in coronary artery atherosclerosis patients or controls. The highest expression of microRNA-126-3p was observed in patients with moderate calcification who were diagnosed with Grade 2 calcification by coronary angiography. Age, microRNA-126-3p expression in veins, hypertension and diabetes significantly influence the occurrence of coronary artery calcification, among which diabetes and venous microRNA-126-3p expression were found to be independent risk factors for coronary artery calcification. Conclusions: Taken together, the data in this study suggest that circulating microRNA-126-3p may be a novel noninvasive biomarker for coronary artery calcification. Regulating microRNA-126-3p expression may be an effective and promising strategy for the diagnosis and treatment of cardiovascular diseases, especially coronary artery calcification.

NLRP3-mediated autophagy dysfunction links gut microbiota dysbiosis to tau pathology in chronic sleep deprivation.

Emerging evidence indicates that sleep deprivation (SD) can lead to Alzheimer's disease (AD)-related pathological changes and cognitive decline. However, the underlying mechanisms remain obscure. In the present study, we identified the existence of a microbiota-gut-brain axis in cognitive deficits resulting from chronic SD and revealed a potential pathway by which gut microbiota affects cognitive functioning in chronic SD. Our findings demonstrated that chronic SD in mice not only led to cognitive decline but also induced gut microbiota dysbiosis, elevated NLRP3 inflammasome expression, GSK-3ß activation, autophagy dysfunction, and tau hyperphosphorylation in the hippocampus. Colonization with the "SD microbiota" replicated the pathological and behavioral abnormalities observed in chronic sleep-deprived mice. Remarkably, both the deletion of NLRP3 in NLRP3 -/- mice and specific knockdown of NLRP3 in the hippocampus restored autophagic flux, suppressed tau hyperphosphorylation, and ameliorated cognitive deficits induced by chronic SD, while GSK-3ß activity was not regulated by the NLRP3 inflammasome in chronic SD. Notably, deletion of NLRP3 reversed NLRP3 inflammasome activation, autophagy deficits, and tau hyperphosphorylation induced by GSK-3ß activation in primary hippocampal neurons, suggesting that GSK-3ß, as a regulator of NLRP3-mediated autophagy dysfunction, plays a significant role in promoting tau hyperphosphorylation. Thus, gut microbiota dysbiosis was identified as a contributor to chronic SD-induced tau pathology via NLRP3-mediated autophagy dysfunction, ultimately leading to cognitive deficits. Overall, these findings highlight GSK-3ß as a regulator of NLRP3-mediated autophagy dysfunction, playing a critical role in promoting tau hyperphosphorylation.

Moscatilin inhibits vascular calcification by activating IL13RA2-dependent inhibition of STAT3 and attenuating the WNT3/ß-catenin signalling pathway.

INTRODUCTION: Vascular calcification, a devastating vascular complication accompanying atherosclerotic cardiovascular disease and chronic kidney disease, increases the incidence of adverse cardiovascular events and compromises the efficacy of vascular interventions. However, effective therapeutic drugs and treatments to delay or prevent vascular calcification are lacking. OBJECTIVES: This study was designed to test the therapeutic effects and mechanism of Moscatilin (also known as dendrophenol) from Dendrobium huoshanense (an eminent traditional Chinese medicine) in suppressing vascular calcification in vitro, ex vivo and in vivo. METHODS: Male C57BL/6J mice (25-week-old) were subjected to nicotine and vitamin D3 (VD3) treatment to induce vascular calcification. In vitro, we established the cellular model of osteogenesis of human aortic smooth muscle cells (HASMCs) under phosphate conditions. RESULTS: By utilizing an in-house drug screening strategy, we identified Moscatilin as a new naturally-occurring chemical entity to reduce HASMC calcium accumulation. The protective effects of Moscatilin against vascular calcification were verified in cultured HASMCs. Unbiased transcriptional profiling analysis and cellular thermal shift assay suggested that Moscatilin suppresses vascular calcification via binding to interleukin 13 receptor subunit A2 (IL13RA2) and augmenting its expression. Furthermore, IL13RA2 was reduced during HASMC osteogenesis, thus promoting the secretion of inflammatory factors via STAT3. We further validated the participation of Moscatilin-inhibited vascular calcification by the classical WNT/ß-catenin pathway, among which WNT3 played a key role in this process. Moscatilin mitigated the crosstalk between WNT3/ß-catenin and IL13RA2/STAT3 to reduce osteogenic differentiation of HASMCs. CONCLUSION: This study supports the potential of Moscatilin as a new naturally-occurring candidate drug for treating vascular calcification via regulating the IL13RA2/STAT3 and WNT3/ß-catenin signalling pathways.

Research on line loss analysis and intelligent diagnosis of abnormal causes in distribution networks: artificial intelligence based method.

The primary source of energy losses in distribution networks (DNs) is rooted in line losses, which is crucial to conduct a thorough and reasonable examination of any unusual sources of line losses to guarantee the power supply in a timely and safe manner. In recent studies, identifying and analyzing abnormal line losses in DNs has been a widely and challenging research subject. This article investigates a key technology for the line loss analyses of DNs and intelligent diagnosis of abnormal causes by implementing artificial intelligence (AI), resulting in several prominent results. The proposed algorithm optimizes the parameters of the support vector machine (SVM) and suggests an intelligent diagnosis algorithm called the Improved Sparrow Search Algorithm and Support Vector Machine (ISSA-SVM). The ISSA-SVM algorithm is trained to calculate the data anomalies of line losses when changing loads and exhibiting exceptional performance to identify abnormal line losses. The accuracy of abnormality identification employing the ISSA-SVM algorithm reaches an impressive 98%, surpassing the performances of other available algorithms. Moreover, the practical performance of the proposed approach for analyzing large volumes of abnormal line loss data daily in DNs is also noteworthy. The ISSA-SVM accurately identifies the root causes of abnormal line losses and lowers the error in calculating abnormal line loss data. By combining different types of power operation data and creating a multidimensional feature traceability model, the study successfully determines the factors contributing to abnormal line losses. The relationship between transformers and voltage among various lines is determined by using the Pearson correlation, which provides valuable insights into the relationship between these variables and line losses. The algorithm's reliability and its potential to be applied to real-world scenarios bring an opportunity to improve the efficiency and safety of power supply systems. The ISSA that incorporates advanced techniques such as the Sobol sequence, golden sine algorithm, and Gaussian difference mutation appears to be a promising tool.