Genetic circuitry controlling Drosophila female germline overgrowth.

Germ cells mutant for bam or bgcn are locked in a germline stem cell (GSC)-like state, leading to tumor-like overgrowth in Drosophila ovaries. Our previous studies have demonstrated that germline overgrowth in bam mutants can be suppressed by defects in the miRNA pathway but enhanced by a null mutation in hippo. However, the genetic epistasis between the miRNA and Hippo pathways still remains unknown. Here, we determined that the miRNA pathway acts downstream of the Hippo pathway in regulating this process. Germ cells mutant for bam or bgcn and defective in both pathways divide very slowly, phenocopying those defective only in the miRNA pathway. In addition, we found that Yki, a key oncoprotein in the Hippo pathway, promotes the growth of both wild-type germ cells and bam mutant GSC-like cells. Like wild-type GSCs, bam mutant GSC-like cells predominantly stay in the G2 phase. Remarkably, many of those defective in the miRNA pathway are arrested before entering this phase. Furthermore, our studies identified bantam as a critical miRNA promoting germline overgrowth in bam or bgcn mutants. Taken together, these findings establish a genetic circuitry controlling Drosophila female germline overgrowth.

Accurate identification of structural variations from cancer samples.

Structural variations (SVs) are commonly found in cancer genomes. They can cause gene amplification, deletion and fusion, among other functional consequences. With an average read length of hundreds of kilobases, nano-channel-based optical DNA mapping is powerful in detecting large SVs. However, existing SV calling methods are not tailored for cancer samples, which have special properties such as mixed cell types and sub-clones. Here we propose the Cancer Optical Mapping for detecting Structural Variations (COMSV) method that is specifically designed for cancer samples. It shows high sensitivity and specificity in benchmark comparisons. Applying to cancer cell lines and patient samples, COMSV identifies hundreds of novel SVs per sample.

HGCLAMIR: Hypergraph contrastive learning with attention mechanism and integrated multi-view representation for predicting miRNA-disease associations.

Existing studies have shown that the abnormal expression of microRNAs (miRNAs) usually leads to the occurrence and development of human diseases. Identifying disease-related miRNAs contributes to studying the pathogenesis of diseases at the molecular level. As traditional biological experiments are time-consuming and expensive, computational methods have been used as an effective complement to infer the potential associations between miRNAs and diseases. However, most of the existing computational methods still face three main challenges: (i) learning of high-order relations; (ii) insufficient representation learning ability; (iii) importance learning and integration of multi-view embedding representation. To this end, we developed a HyperGraph Contrastive Learning with view-aware Attention Mechanism and Integrated multi-view Representation (HGCLAMIR) model to discover potential miRNA-disease associations. First, hypergraph convolutional network (HGCN) was utilized to capture high-order complex relations from hypergraphs related to miRNAs and diseases. Then, we combined HGCN with contrastive learning to improve and enhance the embedded representation learning ability of HGCN. Moreover, we introduced view-aware attention mechanism to adaptively weight the embedded representations of different views, thereby obtaining the importance of multi-view latent representations. Next, we innovatively proposed integrated representation learning to integrate the embedded representation information of multiple views for obtaining more reasonable embedding information. Finally, the integrated representation information was fed into a neural network-based matrix completion method to perform miRNA-disease association prediction. Experimental results on the cross-validation set and independent test set indicated that HGCLAMIR can achieve better prediction performance than other baseline models. Furthermore, the results of case studies and enrichment analysis further demonstrated the accuracy of HGCLAMIR and unconfirmed potential associations had biological significance.

p53 regulation of ammonia metabolism through urea cycle controls polyamine biosynthesis.

Cancer cells exhibit altered and usually increased metabolic processes to meet their high biogenetic demands1,2. Under these conditions, ammonia is concomitantly produced by the increased metabolic processing. However, it is unclear how tumour cells dispose of excess ammonia and what outcomes might be caused by the accumulation of ammonia. Here we report that the tumour suppressor p53, the most frequently mutated gene in human tumours, regulates ammonia metabolism by repressing the urea cycle. Through transcriptional downregulation of CPS1, OTC and ARG1, p53 suppresses ureagenesis and elimination of ammonia in vitro and in vivo, leading to the inhibition of tumour growth. Conversely, downregulation of these genes reciprocally activates p53 by MDM2-mediated mechanism(s). Furthermore, the accumulation of ammonia causes a significant decline in mRNA translation of the polyamine biosynthetic rate-limiting enzyme ODC, thereby inhibiting the biosynthesis of polyamine and cell proliferation. Together, these findings link p53 to ureagenesis and ammonia metabolism, and further reveal a role for ammonia in controlling polyamine biosynthesis and cell proliferation.

Publisher Correction: p53 regulation of ammonia metabolism through urea cycle controls polyamine biosynthesis.

In Fig. 1c of this Letter, the labels p53+/+ and p53-/- were inadvertently swapped. The original figure has been corrected online.

rhFGF-21 accelerates corneal epithelial wound healing through the attenuation of oxidative stress and inflammatory mediators in diabetic mice.

Diabetic keratopathy, commonly associated with a hyperactive inflammatory response, is one of the most common eye complications of diabetes. The peptide hormone fibroblast growth factor-21 (FGF-21) has been demonstrated to have anti-inflammatory and antioxidant properties. However, whether administration of recombinant human (rh) FGF-21 can potentially regulate diabetic keratopathy is still unknown. Therefore, in this work, we investigated the role of rhFGF-21 in the modulation of corneal epithelial wound healing, the inflammation response, and oxidative stress using type 1 diabetic mice and high glucose-treated human corneal epithelial cells. Our experimental results indicated that the application of rhFGF-21 contributed to the enhancement of epithelial wound healing. This treatment also led to advancements in tear production and reduction in corneal edema. Moreover, there was a notable reduction in the levels of proinflammatory cytokines such as TNF-α, IL-6, IL-1ß, MCP-1, IFN-γ, MMP-2, and MMP-9 in both diabetic mouse corneal epithelium and human corneal epithelial cells treated with high glucose. Furthermore, we found rhFGF-21 treatment inhibited reactive oxygen species production and increased levels of anti-inflammatory molecules IL-10 and SOD-1, which suggests that FGF-21 has a protective role in diabetic corneal epithelial healing by increasing the antioxidant capacity and reducing the release of inflammatory mediators and matrix metalloproteinases. Therefore, we propose that administration of FGF-21 may represent a potential treatment for diabetic keratopathy.

Neural correlates of semantic-driven syntactic parsing in sentence comprehension.

For sentence comprehension, information carried by semantic relations between constituents must be combined with other information to decode the constituent structure of a sentence, due to atypical and noisy situations of language use. Neural correlates of decoding sentence structure by semantic information have remained largely unexplored. In this functional MRI study, we examine the neural basis of semantic-driven syntactic parsing during sentence reading and compare it with that of other types of syntactic parsing driven by word order and case marking. Chinese transitive sentences of various structures were investigated, differing in word order, case making, and agent-patient semantic relations (i.e., same vs. different in animacy). For the non-canonical unmarked sentences without usable case marking, a semantic-driven effect triggered by agent-patient ambiguity was found in the left inferior frontal gyrus opercularis (IFGoper) and left inferior parietal lobule, with the activity not being modulated by naturalness factors of the sentences. The comparison between each type of non-canonical sentences with canonical sentences revealed that the non-canonicity effect engaged the left posterior frontal and temporal regions, in line with previous studies. No extra neural activity was found responsive to case marking within the non-canonical sentences. A word order effect across all types of sentences was also found in the left IFGoper, suggesting a common neural substrate between different types of parsing. The semantic-driven effect was also observed for the non-canonical marked sentences but not for the canonical sentences, suggesting that semantic information is used in decoding sentence structure in addition to case marking. The current findings illustrate the neural correlates of syntactic parsing with semantics, and provide neural evidence of how semantics facilitates syntax together with other information.

Sustainable Electrosynthesis of N,N-Dimethylformamide via Relay Catalysis on Synergistic Active Sites.

Electrified synthesis of high-value organonitrogen chemicals from low-cost carbon- and nitrogen-based feedstocks offers an economically and environmentally appealing alternative to traditional thermocatalytic methods. However, the intricate electrochemical reactions at electrode surfaces pose significant challenges in controlling selectivity and activity, especially for producing complex substances such as N,N-dimethylformamide (DMF). Herein, we tackle this challenge by developing relay catalysis for efficient DMF production using a composite WO2-NiOOH/Ni catalyst with two distinctive active sites. Specifically, WO2 selectively promotes dimethylamine (DMA) electrooxidation to produce strongly surface-bound (CH3)2N*, while nearby NiOOH facilitates methanol electrooxidation to yield more weakly bound *CHO. The disparity in binding energetics of the key C- and N-intermediates expedites C-N coupling at the WO2-NiOOH interface. In situ infrared spectroscopy with isotope-labeling experiments, quasi-in situ electron paramagnetic resonance trapping experiments, and electrochemical operating experiments revealed the C-N coupling mechanism and enhanced DMF-synthesis selectivity and activity. In situ X-ray absorption spectroscopy (XAS) and postreaction transmission electron microscopy (TEM) studies verified the stability of WO2-NiOOH/Ni during extended electrochemical operation. A Faradaic efficiency of ∼50% and a production rate of 438 µmol cm-2 h-1 were achieved at an industrially relevant current density of 100 mA cm-2 over an 80 h DMF production period. This study introduces a new paradigm for developing electrothermo relay catalysis for the sustainable and efficient synthesis of valuable organic chemicals with industrial potential.

Oncofetal SNRPE promotes HCC tumorigenesis by regulating the FGFR4 expression through alternative splicing.

BACKGROUND: Due to insufficient knowledge about key molecular events, Hepatocellular carcinoma (HCC) lacks effective treatment targets. Spliceosome-related genes were significantly altered in HCC. Oncofetal proteins are ideal tumor therapeutic targets. Screening of differentially expressed Spliceosome-related oncofetal protein in embryonic liver development and HCC helps discover effective therapeutic targets for HCC. METHODS: Differentially expressed spliceosome genes were analysis in fetal liver and HCC through bioinformatics analysis. Small nuclear ribonucleoprotein polypeptide E (SNRPE) expression was detected in fetal liver, adult liver and HCC tissues. The role of SNRPE in HCC was performed multiple assays in vitro and in vivo. SNRPE-regulated alternative splicing was recognized by RNA-Seq and confirmed by multiple assays. RESULTS: We herein identified SNRPE as a crucial oncofetal splicing factor, significantly associated with the adverse prognosis of HCC. SOX2 was identified as the activator for SNRPE reactivation. Efficient knockdown of SNRPE resulted in the complete cessation of HCC tumorigenesis and progression. Mechanistically, SNRPE knockdown reduced FGFR4 mRNA expression by triggering nonsense-mediated RNA decay. A partial inhibition of SNRPE-induced malignant progression of HCC cells was observed upon FGFR4 knockdown. CONCLUSIONS: Our findings highlight SNRPE as a novel oncofetal splicing factor and shed light on the intricate relationship between oncofetal splicing factors, splicing events, and carcinogenesis. Consequently, SNRPE emerges as a potential therapeutic target for HCC treatment. Model of oncofetal SNRPE promotes HCC tumorigenesis by regulating the AS of FGFR4 pre-mRNA.

Tumor microenvironment characteristics association with clinical outcome in patients with resected intestinal-type gastric cancer.

BACKGROUND: Tumor microenvironment (TME) characteristics including tumor stroma ratio (TSR), tumor budding (TB), and tumor-infiltrating lymphocytes (TILs) were examined in resected gastric cancer. These TME features have been shown to indicate metastatic potential in colon cancer, and intestinal-type gastric cancer (IGC) has pathological similarities with that malignancy. METHODS: TSR, TB, and TILs were quantified in routine histological sections from 493 patients with IGC who underwent radical resection at 2 university hospitals in China from 2010 to 2016. TME variables were dichotomized as follows: TSR (50%), TILs (median), TB per international guidelines (4 buds/0.785mm2), and platelet-lymphocyte ratio (PLR) per survival ROC. Association of TME features with patient clinicopathological characteristics, time-to-recurrence (TTR), and cancer-specific-survival (CSS) were examined using univariate and multivariate analysis, including a relative contribution analysis by Cox regression. RESULTS: Patients whose tumors showed high TSR or high TB or low TILs were each significantly associated with increased T and N stage, higher histological grade, and poorer TTR and CSS at 5 years. Only TSR and N stage were independently associated with TTR and CSS after adjustment for covariates. PLR was only independently associated with TTR after adjustment for covariates. Among the variables examined, only TSR was significantly associated with both TTR (HR 1.72, 95% CI, 1.14-2.60, P = .01) and CSS (HR 1.62, 95% CI, 1.05-2.51, P = .03) multivariately. Relative contribution to TTR revealed that the top 3 contributors were N stage (45.1%), TSR (22.5%), and PLR (12.9%), while the top 3 contributors to CSS were N stage (59.9%), TSR (14.7%), and PLR (10.9%). CONCLUSIONS: Among the examined TME features, TSR was the most robust for prognostication and was significantly associated with both TTR and CSS. Furthermore, the relative contribution of TSR to patient TTR and CSS was second only to nodal status.

Copper Nanosheet-Based Wash-Free Fluorescence Imaging of Cancer Cells.

Near-infrared fluorescence (NIRF) probes greatly facilitate in vivo imaging of various biologically important species. However, there are several significant limitations such as consuming washing steps, photobleaching, and low signal intensity. Herein, we synthesized fluorescent copper nanosheets templated with DNA scaffolds (DNS/CuNSs). We employ them and Cy5.5 of the fluorescence resonance energy transfer (FRET) system, which have a larger Stokes shift (∼12-fold) than the traditional NIRF dye Cy5.5. Based on their excellent fluorescence properties, we employ DNS/CuNSs-Cy5.5 for fluorescence probes in cancer cell imaging. Compared with the free Cy5.5 fluorescence probe, the novel fluorescence imaging probe implements wash-free imaging and exhibits enhanced anti-photobleaching ability (∼5.5-fold). Moreover, the FRET system constructed by DNS/CuNSs has a higher signal amplification ability (∼4.17-fold), which is more similar to that of Cu nanoclusters prepared with DNA nanomonomers as a template. This work provides a new idea for cancer cell MCF-7 imaging and is expected to promote the development of cancer cell fluorescence imaging.

FeN3S1─OH Single-Atom Sites Anchored on Hollow Porous Carbon for Highly Efficient pH-Universal Oxygen Reduction Reaction.

Regulating the asymmetric active center of a single-atom catalyst to optimize the binding energy is critical but challenging to improve the overall efficiency of the electrocatalysts. Herein, an effective strategy is developed by introducing an axial hydroxyl (OH) group to the Fe─N4 center, simultaneously assisting with the further construction of asymmetric configurations by replacing one N atom with one S atom, forming FeN3S1─OH configuration. This novel structure can optimize the electronic structure and d-band center shift to reduce the reaction energy barrier, thereby promoting oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) catalytic activities. The optimal catalyst, FeSA-S/N-C (FeN3S1─OH anchored on hollow porous carbon) displays remarkable ORR performance with a half-wave potential of 0.92, 0.78, and 0.64 V versus RHE in 0.1 m KOH, 0.5 m H2SO4, and 0.1 m PBS, respectively. The rechargeable liquid Zn-air batteries (LZABs) equipped with FeSA-S/N-C display a higher power density of 128.35 mW cm-2, long-term operational stability of over 500 h, and outstanding reversibility. More importantly, the corresponding flexible solid-state ZABs (FSZABs@FeSA-S/N-C) display negligible voltage changes at different bending angles during the charging and discharging processes. This work provides a new perspective for the design and optimization of asymmetric configuration for single-atom catalysts applied to the area of energy conversion and storage.

Predicting multiple types of miRNA-disease associations using adaptive weighted nonnegative tensor factorization with self-paced learning and hypergraph regularization.

More and more evidence indicates that the dysregulations of microRNAs (miRNAs) lead to diseases through various kinds of underlying mechanisms. Identifying the multiple types of disease-related miRNAs plays an important role in studying the molecular mechanism of miRNAs in diseases. Moreover, compared with traditional biological experiments, computational models are time-saving and cost-minimized. However, most tensor-based computational models still face three main challenges: (i) easy to fall into bad local minima; (ii) preservation of high-order relations; (iii) false-negative samples. To this end, we propose a novel tensor completion framework integrating self-paced learning, hypergraph regularization and adaptive weight tensor into nonnegative tensor factorization, called SPLDHyperAWNTF, for the discovery of potential multiple types of miRNA-disease associations. We first combine self-paced learning with nonnegative tensor factorization to effectively alleviate the model from falling into bad local minima. Then, hypergraphs for miRNAs and diseases are constructed, and hypergraph regularization is used to preserve the high-order complex relations of these hypergraphs. Finally, we innovatively introduce adaptive weight tensor, which can effectively alleviate the impact of false-negative samples on the prediction performance. The average results of 5-fold and 10-fold cross-validation on four datasets show that SPLDHyperAWNTF can achieve better prediction performance than baseline models in terms of Top-1 precision, Top-1 recall and Top-1 F1. Furthermore, we implement case studies to further evaluate the accuracy of SPLDHyperAWNTF. As a result, 98 (MDAv2.0) and 98 (MDAv2.0-2) of top-100 are confirmed by HMDDv3.2 dataset. Moreover, the results of enrichment analysis illustrate that unconfirmed potential associations have biological significance.

H-NS involved in positive regulation of glycerol dehydratase gene expression in Klebsiella pneumoniae 2e.

Glycerol dehydratase is the key and rate-limiting enzyme in the 1,3-propanediol synthesis pathway of Klebsiella pneumoniae, which determined the producing rate and yield of 1,3-propanediol. However, the expression regulation mechanism of glycerol dehydratase gene dhaB remains poorly unknown. In this study, a histone-like nucleoid-structuring (H-NS) protein was identified and characterized as the positive transcription regulator for dhaB expression in K. pneumoniae 2e, which exhibited high tolerance against crude glycerol in our previous study. Deletion of hns gene significantly decreased the transcription level of dhaB in K. pneumoniae 2e, which led to a remarkable defect on strain growth, glycerol dehydratase activity, and 3-hydroxypropanal production during glycerol fermentation. The transcription level of dhaB was significantly up-regulated in crude glycerol relative to pure glycerol, while the inactivation of H-NS resulted in more negative effect for transcription level of dhaB in the former. Though the H-NS expression level was almost comparable in both substrates, its multimer state was reduced in crude glycerol relative to pure glycerol, suggesting that the oligomerization state of H-NS might have contributed for positive regulation of dhaB expression. Furthermore, electrophoretic mobility shift and DNase I footprinting assays showed that H-NS could directly bind to the upstream promoter region of dhaB by recognizing the AT-rich region. These findings provided new insight into the transcriptional regulation mechanism of H-NS for glycerol dehydratase expression in K. pneumoniae, which might offer new target for engineering bacteria to industrially produce 1,3-propanediol.IMPORTANCEThe biological production of 1,3-propanediol from glycerol by microbial fermentation shows great promising prospect on industrial application. Glycerol dehydratase catalyzes the penultimate step in glycerol metabolism and is regarded as one of the key and rate-limiting enzymes for 1,3-propanediol production. H-NS was reported as a pleiotropic modulator with negative effects on gene expression in most studies. Here, we reported for the first time that the expression of glycerol dehydratase gene is positively regulated by the H-NS. The results provide insight into a novel molecular mechanism of H-NS for positive regulation of glycerol dehydratase gene expression in K. pneumoniae, which holds promising potential for facilitating construction of engineering highly efficient 1,3-propanediol-producing strains.

Peroxidase gene TaPrx109-B1 enhances wheat tolerance to water deficit via modulating stomatal density.

Increasing the tolerance of crops to water deficit is crucial for the improvement of crop production in water-restricted regions. Here, a wheat peroxidase gene (TaPrx109-B1) belonging to the class III peroxidase gene family was identified and its function in water deficit tolerance was revealed. We demonstrated that overexpression of TaPrx109-B1 reduced leaf H2O2 level and stomatal density, increased leaf relative water content, water use efficiency, and tolerance to water deficit. The expression of TaEPF1 and TaEPF2, two key negative regulators of stomatal development, were significantly upregulated in TaPrx109-B1 overexpression lines. Furthermore, exogenous H2O2 downregulated the expression of TaEPF1 and TaEPF2 and increased stomatal density, while exogenous application of diphenyleneiodonium chloride, a potent NADPH oxidase inhibitor that repressed the synthesis of H2O2, upregulated the expression of TaEPF1 and TaEPF2, decreased stomatal density, and enhanced wheat tolerance to water deficit. These findings suggest that TaPrx109-B1 influences leaf stomatal density by modulation of H2O2 level and the expression of TaEPF1 and TaEPF2. The results of the field trial showed that overexpressing TaPrx109-B1 increased grain number per spike, which reduced the yield loss caused by water deficiency. Therefore, TaPrx109-B1 has great potential in breeding wheat varieties with improved water deficit tolerance.

Innovative rapid liquid concentration measurement based on thermal lens effect and machine learning.

This study addresses the critical need for rapid and online measurement of liquid concentrations in industrial applications. Although the thermal lens effect (TLE) is extensively explored in laser systems for determining thermal lens focal lengths, its application in quantifying solution concentrations remains underexplored. This research explores the relationship between various liquid concentrations and the interference fringes induced by the TLE. A novel approach is introduced, utilizing TLE to measure solution concentrations, with integration of image processing and discrete Fourier transform (DFT) techniques for feature extraction from interference rings. Further, machine learning, specifically backpropagation artificial neural network (BP-ANN), is employed to model concentration measurement. The model demonstrates high accuracy, evidenced by low root mean square error (RMSE) values of 3.055 and 5.396 for the training and test sets, respectively. This enables precise, real-time determination of soy sauce concentration, offering significant implications for industrial testing, environmental monitoring, and other related fields.

Relationship between stress hyperglycemia ratio and acute kidney injury in patients with congestive heart failure.

BACKGROUND: The stress hyperglycemia ratio (SHR) has been demonstrated as an independent risk factor for acute kidney injury (AKI) in certain populations. However, this relationship in patients with congestive heart failure (CHF) remains unclear. Our study sought to elucidate the relationship between SHR and AKI in patients with CHF. METHODS: A total of 8268 patients with CHF were included in this study. We categorized SHR into distinct groups and evaluated its association with mortality through logistic or Cox regression analyses. Additionally, we applied the restricted cubic spline (RCS) analysis to explore the relationship between SHR as a continuous variable and the occurrence of AKI. The primary outcome of interest in this investigation was the incidence of AKI during hospitalization. RESULTS: Within this patient cohort, a total of 5,221 (63.1%) patients experienced AKI during their hospital stay. Upon adjusting for potential confounding variables, we identified a U-shaped correlation between SHR and the occurrence of AKI, with an inflection point at 0.98. When the SHR exceeded 0.98, for each standard deviation (SD) increase, the risk of AKI was augmented by 1.32-fold (odds ratio [OR]: 1.32, 95% CI: 1.22 to 1.46). Conversely, when SHR was below 0.98, each SD decrease was associated with a pronounced increase in the risk of AKI. CONCLUSION: Our study reveals a U-shaped relationship between SHR and AKI in patients with CHF. Notably, we identified an inflection point at an SHR value of 0.98, signifying a critical threshold for evaluating AKI in this population.

Associations of 50 modifiable risk factors with atrial fibrillation using Mendelian randomization analysis.

BACKGROUND: Substantial focus has been placed on atrial fibrillation (AF) treatment and associated stroke prevention rather than preventing AF itself. We employed Mendelian randomization (MR) approach to examine the causal relationships between 50 modifiable risk factors (RFs) and AF. METHODS: Instrumental variables for genetically predicted exposures were derived from corresponding genome-wide association studies (GWASs). Summary-level statistical data for AF were obtained from a GWAS meta-analysis (discovery dataset, N = 1,030,836) and FinnGen (validation dataset, N = 208,594). Univariable and multivariable MR analyses were performed, primarily using inverse variance weighted method with a series of robust sensitivity analyses. RESULTS: Genetic predisposition to insomnia, daytime naps, apnea, smoking initiation, moderate to vigorous physical activity and obesity traits, including body mass index, waist-hip ratio, central and peripheral fat/fat-free mass, exhibited significant associations with an increased risk of AF. Coffee consumption and ApoB had suggestive increased risks. Hypertension (odds ratio (OR) 95% confidence interval (CI): 5.26 (4.42, 6.24)), heart failure (HF) (OR 95% CI, 4.77 (2.43, 9.37)) and coronary artery disease (CAD) (OR 95% CI: 1.20 (1.16, 1.24)) were strongly associated with AF, while college degree, higher education attachment and HDL levels were associated with a decreased AF risk. Reverse MR found a bidirectional relationship between genetically predicted AF and CAD, HF and ischemic stroke. Multivariable analysis further indicated that obesity-related traits, systolic blood pressure and lower HDL levels independently contributed to the development of AF. CONCLUSIONS: This study identified several lifestyles and cardiometabolic factors that might be causally related to AF, underscoring the importance of a holistic approach to AF management and prevention.

A remote sensing method for mapping alpine grasslines based on graph-cut.

Climate change has induced substantial shifts in vegetation boundaries such as alpine treelines and shrublines, with widespread ecological and climatic influences. However, spatial and temporal changes in the upper elevational limit of alpine grasslands ("alpine grasslines") are still poorly understood due to lack of field observations and remote sensing estimates. In this study, taking the Tibetan Plateau as an example, we propose a novel method for automatically identifying alpine grasslines from multi-source remote sensing data and determining their positions at 30-m spatial resolution. We first identified 2895 mountains potentially having alpine grasslines. On each mountain, we identified a narrow area around the upper elevational limit of alpine grasslands where the alpine grassline was potentially located. Then, we used linear discriminant analysis to adaptively generate from Landsat reflectance features a synthetic feature that maximized the difference between vegetated and unvegetated pixels in each of these areas. After that, we designed a graph-cut algorithm to integrate the advantages of the Otsu and Canny approaches, which was used to determine the precise position of the alpine grassline from the synthetic feature image. Validation against alpine grasslines visually interpreted from a large number of high-spatial-resolution images showed a high level of accuracy (R2 , .99 and .98; mean absolute error, 22.6 and 36.2 m, vs. drone and PlanetScope images, respectively). Across the Tibetan Plateau, the alpine grassline elevation ranged from 4038 to 5380 m (5th-95th percentile), lower in the northeast and southeast and higher in the southwest. This study provides a method for remotely sensing alpine grasslines for the first-time at large scale and lays a foundation for investigating their responses to climate change.

Association between Hematocrit and Acute Kidney Injury in Patients with Acute Myocardial Infarction.

Backgrounds: Hematocrit is found an independent risk factor for acute kidney injury (AKI) in certain patients, but this effect in patients with acute myocardial infarction (AMI) is unclear. We aim to identify the relationship between hematocrit and AKI in patients with AMI. Methods: The patient data for the discovery and validation cohorts were extracted from the electronic Intensive Care Unit database and the Medical Information Mart for Intensive Care III database, respectively, to identify the relationship between hematocrit and AKI. With normal hematocrit as the reference, patients were divided into five groups based on the initial hematocrit value. The primary outcome was AKI during hospitalization. A multivariable logistic regression and a marginal effect analysis were used to evaluate the relationship between hematocrit and AKI. Results: In this study, a total of 9692 patients diagnosed with AMI were included, with 7712 patients in the discovery cohort and 1980 patients in the validation cohort. In the discovery cohort, hematocrit in 30-33%, 27-30% or < 27% were independent risk factors for AKI in the multivariate logistic analysis, with odds ratio (OR) of 1.774 (95% confidence interval [CI]: 1.203-2.617, p = 0.004), 1.834 (95% CI: 1.136-2.961, p = 0.013) and 2.577 (95% CI: 1.510-4.397, p < 0.001), respectively. Additionally, in the validation cohort, low hematocrit levels independently contributed to an increased risk of AKI among patients with AMI. During the analysis of marginal effects, a significant negative linear relationship between hematocrit levels and AKI was observed. Conclusions: Decreased hematocrit was an independent risk factor for AKI in patients with AMI. The relationship between hematocrit and AKI was negative linear.