scGIR: deciphering cellular heterogeneity via gene ranking in single-cell weighted gene correlation networks.

Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for investigating cellular heterogeneity through high-throughput analysis of individual cells. Nevertheless, challenges arise from prevalent sequencing dropout events and noise effects, impacting subsequent analyses. Here, we introduce a novel algorithm, Single-cell Gene Importance Ranking (scGIR), which utilizes a single-cell gene correlation network to evaluate gene importance. The algorithm transforms single-cell sequencing data into a robust gene correlation network through statistical independence, with correlation edges weighted by gene expression levels. We then constructed a random walk model on the resulting weighted gene correlation network to rank the importance of genes. Our analysis of gene importance using PageRank algorithm across nine authentic scRNA-seq datasets indicates that scGIR can effectively surmount technical noise, enabling the identification of cell types and inference of developmental trajectories. We demonstrated that the edges of gene correlation, weighted by expression, play a critical role in enhancing the algorithm's performance. Our findings emphasize that scGIR outperforms in enhancing the clustering of cell subtypes, reverse identifying differentially expressed marker genes, and uncovering genes with potential differential importance. Overall, we proposed a promising method capable of extracting more information from single-cell RNA sequencing datasets, potentially shedding new lights on cellular processes and disease mechanisms.

SCTC: inference of developmental potential from single-cell transcriptional complexity.

Inferring the developmental potential of single cells from scRNA-Seq data and reconstructing the pseudo-temporal path of cell development are fundamental but challenging tasks in single-cell analysis. Although single-cell transcriptional diversity (SCTD) measured by the number of expressed genes per cell has been widely used as a hallmark of developmental potential, it may lead to incorrect estimation of differentiation states in some cases where gene expression does not decrease monotonously during the development process. In this study, we propose a novel metric called single-cell transcriptional complexity (SCTC), which draws on insights from the economic complexity theory and takes into account the sophisticated structure information of scRNA-Seq count matrix. We show that SCTC characterizes developmental potential more accurately than SCTD, especially in the early stages of development where cells typically have lower diversity but higher complexity than those in the later stages. Based on the SCTC, we provide an unsupervised method for accurate, robust, and transferable inference of single-cell pseudotime. Our findings suggest that the complexity emerging from the interplay between cells and genes determines the developmental potential, providing new insights into the understanding of biological development from the perspective of complexity theory.

Functional characterisation of BnaA02.TOP1α and BnaC02.TOP1α involved in true leaf biomass accumulation in Brassica napus L.

Leaves, as primary photosynthetic organs essential for high crop yield and quality, have attracted significant attention. The functions of DNA topoisomerase 1α (TOP1α) in various biological processes, including leaf development, in Brassica napus remain unknown. Here, four paralogs of BnaTOP1α, namely BnaA01.TOP1α, BnaA02.TOP1α, BnaC01.TOP1α and BnaC02.TOP1α, were identified and cloned in the B. napus inbred line 'K407'. Expression pattern analysis revealed that BnaA02.TOP1α and BnaC02.TOP1α, but not BnaA01.TOP1α and BnaC01.TOP1α, were persistently and highly expressed in B. napus true leaves. Preliminary analysis in Arabidopsis thaliana revealed that BnaA02.TOP1α and BnaC02.TOP1α paralogs, but not BnaA01.TOP1α and BnaC01.TOP1α, performed biological functions. Targeted mutations of four BnaTOP1α paralogs in B. napus using the CRISPR-Cas9 system revealed that BnaA02.TOP1α and BnaC02.TOP1α served as functional paralogs and redundantly promoted true leaf number and size, thereby promoting true leaf biomass accumulation. Moreover, BnaA02.TOP1α modulated the levels of endogenous gibberellins, cytokinins and auxins by indirectly regulating several genes related to their metabolism processes. BnaA02.TOP1α directly activated BnaA03.CCS52A2 and BnaC09.AN3 by facilitating the recruitment of RNA polymerase II and modulating H3K27me3, H3K36me2 and H3K36me3 levels at these loci and indirectly activated the BnaA08.PARL1 expression, thereby positively controlling the true leaf size in B. napus. Additionally, BnaA02.TOP1α indirectly activated the BnaA07.PIN1 expression to positively regulate the true leaf number. These results reveal the important functions of BnaTOP1α and provide insights into the regulatory network controlling true leaf biomass accumulation in B. napus.

Modeling and analyzing single-cell multimodal data with deep parametric inference.

The proliferation of single-cell multimodal sequencing technologies has enabled us to understand cellular heterogeneity with multiple views, providing novel and actionable biological insights into the disease-driving mechanisms. Here, we propose a comprehensive end-to-end single-cell multimodal analysis framework named Deep Parametric Inference (DPI). DPI transforms single-cell multimodal data into a multimodal parameter space by inferring individual modal parameters. Analysis of cord blood mononuclear cells (CBMC) reveals that the multimodal parameter space can characterize the heterogeneity of cells more comprehensively than individual modalities. Furthermore, comparisons with the state-of-the-art methods on multiple datasets show that DPI has superior performance. Additionally, DPI can reference and query cell types without batch effects. As a result, DPI can successfully analyze the progression of COVID-19 disease in peripheral blood mononuclear cells (PBMC). Notably, we further propose a cell state vector field and analyze the transformation pattern of bone marrow cells (BMC) states. In conclusion, DPI is a powerful single-cell multimodal analysis framework that can provide new biological insights into biomedical researchers. The python packages, datasets and user-friendly manuals of DPI are freely available at https://github.com/studentiz/dpi.

Chirality-Mediated 1D-to-2D Phase Transition in Hybrid Lead Halide Perovskites.

Dimensionality engineering plays a pivotal role in optimizing the performance, ensuring long-term stability, and expanding the versatile applications of lead halide perovskites (LHPs). Currently, the manipulation of LHP dimensions primarily occurs during the synthesis stage, a procedure hampered by constraints, including synthetic complexity and irreversibility. This investigation successfully achieved a transition from one-dimensional (1D) to two-dimensional (2D) structures in chiral LHPs by applying hydrostatic pressure. Remarkably, this pressure-induced transition in dimensionality is absent in the racemic analogue due to the staggered arrangement of inorganic chains and the elevated steric hindrance posed by the organic cations. Notably, the hydrogen bonding between organic cations and the inorganic framework adopts a symmetrical arrangement in the racemic system but a helical configuration along the 1D chain direction in the chiral counterparts. This distinct helical arrangement induces a consequential distortion in the inorganic moiety, resulting in the emergence of a spin-polarized Rashba-Dresselhaus texture that explains the chirality's electronic spin origin. Furthermore, both experimental and density functional theory calculation results demonstrate that the 1D-to-2D phase transition in chiral halide perovskites can induce significant modifications in the electronic structures and associated optical emissions. In summary, the findings unveil novel avenues for manipulating optoelectronic properties in chiral perovskites through dimensionality engineering.

Boosting the Cycle Performance of Iron Trifluoride Based Solid State Batteries at Elevated Temperatures by Engineering the Cathode Solid Electrolyte Interface.

Iron trifluoride (FeF3) is attracting tremendous interest due to its lower cost and the possibility to enable higher energy density in lithium-ion batteries. However, its cycle performance deteriorates rapidly in less than 50 cycles at elevated temperatures due to cracking of the unstable cathode solid electrolyte interface (CEI) followed by active materials dissolution in liquid electrolyte. Herein, by engineering the salt composition, the Fe3O4-type CEI with the doping of boron (B) atoms in a polymer electrolyte at 60 °C is successfully stabilized. The cycle life of the well-designed FeF3-based composite cathode exceeds an unprecedented 1000 cycles and utilizes up to 70% of its theoretical capacities. Advanced electron microscopy combined with density functional theory (DFT) calculations reveal that the B in lithium salt migrates into the cathode and promotes the formation of an elastic and mechanic robust boron-contained CEI (BOR-CEI) during cycling, by which the durability of the CEI to frequent cyclic large volume changes is significantly enhanced. To this end, the notorious active materials dissolution is largely prohibited, resulting in a superior cycle life. The results suggest that engineering the CEI such as tuning its composition is a viable approach to achieving FeF3 cathode-based batteries with enhanced performance.

Broadband lens and graphene/silicon photodiode for wide spectral imaging.

We designed a broadband lens along with a graphene/silicon photodiode for wide spectral imaging ranging from ultraviolet to near-infrared wavelengths. By using five spherical glass lenses, the broadband lens, with the modulation transfer function of 0.38 at 100 lp/mm, corrects aberrations ranging from 340 to 1700 nm. Our design also includes a broadband graphene/silicon Schottky photodiode with the highest responsivity of 0.63 A/W ranging from ultraviolet to near-infrared. By using the proposed broadband lens and the broadband graphene/silicon photodiode, several single-pixel imaging designs in ultraviolet, visible, and near-infrared wavelengths are demonstrated. Experimental results show the advantages of integrating the lens with the photodiode and the potential to realize broadband imaging with a single set of lens and a detector.

Fabrication of PHFPO Surface-Modified Conductive AgNWs/PNAGA Hydrogels with Enhanced Water Retention Capacity toward Highly Sensitive Strain Sensors.

Conductive hydrogels, characterized by their unique features of flexibility, biocompatibility, electrical conductivity, and responsiveness to environmental stimuli, have emerged as promising materials for sensitive strain sensors. In this study, a facile strategy to prepare highly conductive hydrogels is reported. Through rational structural and synthetic design, silver nanowires (AgNWs) are incorporated into poly(N-acryloyl glycinamide) (PNAGA) hydrogels, achieving high electrical conductivity (up to 0.88 S m-1), significantly enhanced mechanical properties, and elevated deformative sensitivity. Furthermore, surface modification with polyhexafluoropropylene oxide (PHFPO) has substantially improved the water retention capacity and dressing comfort of this hydrogel material. Based on the above merits, these hydrogels are employed to fabricate highly sensitive wearable strain sensors which can detect and interpret subtle hand and finger movements and enable precise control of machine interfaces. The AgNWs/PNAGA based strain sensors can effectively sense finger motion, enabling the control of robotic fingers to replicate the human hand's gestures. In addition, the high deformative sensitivity and elevated water retention performance of the hydrogels makes them suitable for flow sensing. These conceptual applications demonstrate the potential of this conductive hydrogel in high-performance strain sensors in the future.

Biogeographic patterns of meio- and micro-eukaryotic communities in dam-induced river-reservoir systems.

Although the Three Gorges Dam (TGD) is the world's largest hydroelectric dam, little is known about the spatial-temporal patterns and community assembly mechanisms of meio- and micro-eukaryotes and its two subtaxa (zooplankton and zoobenthos). This knowledge gap is particularly evident across various habitats and during different water-level periods, primarily arising from the annual regular dam regulation. To address this inquiry, we employed mitochondrial cytochrome c oxidase I (COI) gene-based environmental DNA (eDNA) metabarcoding technology to systematically analyze the biogeographic pattern of the three communities within the Three Gorges Reservoir (TGR). Our findings reveal distinct spatiotemporal characteristics and complementary patterns in the distribution of meio- and micro-eukaryotes. The three communities showed similar biogeographic patterns and assembly processes. Notably, the diversity of these three taxa gradually decreased along the river. Their communities were less shaped by stochastic processes, which gradually decreased along the longitudinal riverine-transition-lacustrine gradient. Hence, deterministic factors, such as seasonality, environmental, and spatial variables, along with species interactions, likely play a pivotal role in shaping these communities. Environmental factors primarily drive seasonal variations in these communities, while hydrological conditions, represented as spatial distance, predominantly influence spatial variations. These three communities followed the distance-decay pattern. In winter, compared to summer, both the decay and species interrelationships are more pronounced. Taken together, this study offers fresh insights into the composition and diversity patterns of meio- and micro-eukaryotes at the spatial-temporal level. It also uncovers the mechanisms behind community assembly in various environmental niches within the dam-induced river-reservoir systems. KEY POINTS: • Distribution and diversity of meio- and micro-eukaryotes exhibit distinct spatiotemporal patterns in the TGR. • Contribution of stochastic processes in community assembly gradually decreases along the river. • Deterministic factors and species interactions shape meio- and micro-eukaryotic community.

Structural basis for ligand binding modes of CTP synthase.

Cytidine triphosphate synthase (CTPS), which comprises an ammonia ligase domain and a glutamine amidotransferase domain, catalyzes the final step of de novo CTP biosynthesis. The activity of CTPS is regulated by the binding of four nucleotides and glutamine. While glutamine serves as an ammonia donor for the ATP-dependent conversion of UTP to CTP, the fourth nucleotide GTP acts as an allosteric activator. Models have been proposed to explain the mechanisms of action at the active site of the ammonia ligase domain and the conformational changes derived by GTP binding. However, actual GTP/ATP/UTP binding modes and relevant conformational changes have not been revealed fully. Here, we report the discovery of binding modes of four nucleotides and a glutamine analog 6-diazo-5-oxo-L-norleucine in Drosophila CTPS by cryo-electron microscopy with near-atomic resolution. Interactions between GTP and surrounding residues indicate that GTP acts to coordinate reactions at both domains by directly blocking ammonia leakage and stabilizing the ammonia tunnel. Additionally, we observe the ATP-dependent UTP phosphorylation intermediate and determine interacting residues at the ammonia ligase. A noncanonical CTP binding at the ATP binding site suggests another layer of feedback inhibition. Our findings not only delineate the structure of CTPS in the presence of all substrates but also complete our understanding of the underlying mechanisms of the allosteric regulation and CTP synthesis.

Association between serum copper levels and stroke in the general population: A nationally representative study.

OBJECTIVES: The objective was to explore the association between serum copper levels and the prevalence of stroke. METHODS: Data were obtained from 3 consecutive National Health and Nutrition Examination Survey (NHANES) cycles (2011-2016). Weighted multivariable logistic regression analysis was conducted to evaluate the association between serum copper levels and self-reported stroke. RESULTS: A total of 5,151 adults met the inclusion criteria. A total of 181 (3.51%) stroke patients were identified. In comparison to individuals with serum copper levels in the lowest tertile (<16.4 µmol/l), those with levels in the middle tertile (16.4-19.8 µmol/l) had an odds ratio (OR) of 0.99 (95% confidence interval [CI]: 0.44-2.25), while those with levels in the highest tertile (>19.8 µmol/l) had an OR of 2.36 (95% CI: 1.01-5.52). Furthermore, each standard deviation (SD) increase in serum copper was found to be positively associated with the prevalence of stroke, with an OR of 1.44 (95% CI: 1.11-1.86). Dose‒response analysis showed a positive linear association between serum copper levels and stroke (Pnonlinearity=0.554). CONCLUSIONS: This cross-sectional study suggested a positive association between serum copper levels and stroke among American adults.

Establishing a Comprehensive Nursing Clinic Using the Case Management Model.

OBJECTIVE: To explore the practical effect of the case management model in a comprehensive nursing clinic. METHODS: Based on the case management model, the authors constructed a comprehensive nursing clinic providing wound care, ostomy care, peripherally inserted central catheter care, drainage tube care, nursing consultations, and home care. They evaluated the practical effect of the comprehensive nursing clinic according to workload, economic benefits, and satisfaction of the medical staff and patients. RESULTS: Since the inception of the comprehensive nursing clinic, the number of visits has increased by 63.57%, and the satisfaction of patients and medical staff has also improved. CONCLUSIONS: This comprehensive nursing clinic based on the case management model meets the medical needs of patients, has improved the satisfaction of patients and the medical staff, and enhances the professional sense of value and comprehensive quality of specialized nurses.

Stage-specific and location-specific cartilage calcification in osteoarthritis development.

OBJECTIVES: This study investigated the stage-specific and location-specific deposition and characteristics of minerals in human osteoarthritis (OA) cartilages via multiple nano-analytical technologies. METHODS: Normal and OA cartilages were serially sectioned for micro-CT, scanning electron microscopy with energy dispersive X-ray spectroscopy, micro-Raman spectroscopy, focused ion beam scanning electron microscopy, high-resolution electron energy loss spectrometry with transmission electron microscopy, nanoindentation and atomic force microscopy to analyse the structural, compositional and mechanical properties of cartilage in OA progression. RESULTS: We found that OA progressed by both top-down calcification at the joint surface and bottom-up calcification at the osteochondral interface. The top-down calcification process started with spherical mineral particle formation in the joint surface during early-stage OA (OA-E), followed by fibre formation and densely packed material transformation deep into the cartilage during advanced-stage OA (OA-A). The bottom-up calcification in OA-E started when an excessive layer of calcified tissue formed above the original calcified cartilage, exhibiting a calcified sandwich structure. Over time, the original and upper layers of calcified cartilage fused, which thickened the calcified cartilage region and disrupted the cartilage structure. During OA-E, the calcified cartilage was hypermineralised, containing stiffer carbonated hydroxyapatite (HAp). During OA-A, it was hypomineralised and contained softer HAp. This discrepancy may be attributed to matrix vesicle nucleation during OA-E and carbonate cores during OA-A. CONCLUSIONS: This work refines our current understanding of the mechanism underlying OA progression and provides the foothold for potential therapeutic targeting strategies once the location-specific cartilage calcification features in OA are established.

Direct-detected spectroscopy based on a plasmonic Schottky photodetector and a deep neural network.

Computational algorithms have facilitated the miniaturization of spectrometers, which is essential for on-chip and portable applications. A plasmonic Schottky photodetector provides a filter-free and CMOS-compatible scheme for spectral measurement. In this study, we report on a direct-detected spectral analysis based on an integrated vertically coupled plasmonic nanostructure Schottky photodetector. We demonstrate that the plasmonic Schottky photodetector has a fast response with a -3 dB bandwidth of 600 kHz and a high peak detectivity of 8.65 × 1010 Jones. By designing a deep neural network (DNN), we demonstrate the reconstruction of the unknown spectrum with a mean square error (MSE) of 1.57 × 10-4 at a broad operating wave band of 450-950 nm, using only 20 distinct devices. Moreover, the spectral resolution of the 20 devices can reach to 7 nm. These findings provide a promising route for the development of chip-integrated spectrometers with high spectral accuracy and optical performance.

Sleep Patterns Modify the Association between Vitamin D Status and Coronary Heart Disease: Results from NHANES 2005-2008.

BACKGROUND: Although an increased risk of coronary heart disease (CHD) has been reported in individuals with low vitamin D status, this remains controversial. Growing evidence suggests that sleep behaviors may influence vitamin D endocrine functions. OBJECTIVES: We explored the association between serum 25-hydroxyvitamin D [[25(OH)D] concentrations and CHD and whether sleep behaviors modify this relationship. METHODS: A cross-sectional analysis of 7511 adults aged ≥20 y in 2005-2008 National Health and Nutrition Examination Survey (NHANES) that included serum 25(OH)D concentrations and provided information on sleep behaviors and history of CHD was performed. Logistic regression models were used to assess the association between serum 25(OH)D concentrations and CHD, whereas stratified analyses and multiplicative interaction tests were used to evaluate the modification effect of overall sleep patterns and each sleep factor on this relationship. The overall sleep patterns integrated 4 sleep behaviors (sleep duration, snoring, insomnia, and daytime sleepiness) in the form of healthy sleep score. RESULTS: Serum 25(OH)D concentrations were inversely associated with risk of CHD (P < 0.01). Hypovitaminosis D [serum 25(OH)D <50nmol/L] was associated with a 71% increased risk of CHD (OR: 1.71; 95% CI: 1.28, 2.28; P < 0.01) compared with that in participants with sufficient vitamin D [serum 25(OH)D ≥75nmol/L], and the association was more evident and stable among participants with poor sleep patterns (P-interaction < 0.01). Among the individual sleep behaviors, sleep duration had the strongest interaction with 25(OH)D (P-interaction < 0.05). The association between serum 25(OH)D concentrations and risk of CHD was more pronounced in participants with sleep duration <7 h/d or >8 h/d compared with those with sleep duration 7-8 h/d. CONCLUSIONS: These findings suggest that the influence of lifestyle-related behavioral risk factors, such as sleep behaviors (especially sleep duration), need to be considered when evaluating the association between serum 25(OH)D concentrations and CHD as well as the clinical benefits of vitamin D supplementation.

Current crowding in graphene-silicon schottky diodes.

The performance of the Graphene/Si (Gr/Si) Schottky interface and its potential in future electronics strongly rely on the quality of interconnecting contacts with external circuitry. In this work, we investigate the dominating and limiting factors of Gr/Si interfaces designed for high light absorption, paying particular attention to the nature of the contact failure under high electrostatic discharge (ESD) conditions. Our findings indicate that severe current crowding at contact edges of the graphene is the dominating factor for the device breakdown. Material degradation and electrical breakdown are systematically analyzed by atomic force, Raman, scanning electron, and energy-dispersive x-ray spectroscopies. This work enlists the robustness and limitations of Gr/Si junction in photodiode architecture under high ESD conditions that can be used as general guidelines for 2D-3D electronic and optoelectronic devices.

Tumor necrosis factor-α stimulation endothelial-to-mesenchymal transition during cardiac fibrosis via endothelin-1 signaling.

Cardiac fibrosis is an important pathological change after myocardial infarction (MI). High concentration of tumor necrosis factor-α (TNF-α) contributes to cardiac fibrosis, and TNF-α has been demonstrated to be involved in transforming growth factor-ß1-induced endothelial-to-mesenchymal transition (EndMT). However, the role and molecular mechanisms of TNF-α during cardiac fibrosis remain largely unexplored. In this study, we demonstrated that TNF-α and endothelin-1 (ET-1) were upregulated in cardiac fibrosis after MI, and genes associated with EndMT were also upregulated. An in vitro model of EndMT demonstrated that TNF-α promoted EndMT by upregulation of vimentin and α-smooth muscle actin, and which strongly increased ET-1 expression. ET-1 promoted TNF-α-induced expression of gene program through phosphorylation levels of SMAD family member 2, while subsequent inhibition of ET-1 almost abolished the effect of TNF-α during the process of EndMT. In summary, these findings demonstrated that ET-1 is involved in the EndMT induced by TNF-α during cardiac fibrosis.

Significance of computed tomography combined with postural stimulation test in predicting laterality of primary aldosteronism.

BACKGROUNDS: Adrenal venous sampling (AVS) represents the gold standard for classifying primary aldosteronism (PA). However, AVS is a technically demanding, expensive and invasive procedure. Computed tomography (CT) scans is recommended as the initial study of classification diagnosis by the current guidelines. In addition, postural stimulation test (PST) has been used to provide additional subtype diagnostic information. OBJECTIVE: This work aimed to evaluate the diagnostic utility of the adrenal CT combined with PST in the classification diagnosis of PA. METHODS: We analyzed PA patients who underwent AVS from November 2017 to February 2022 at a single center. Subtype classification of PA was determined by AVS. We analyzed the concordance rate between AVS outcomes, adrenal CT, and PST, and explored the value of adrenal CT combined with PST for predicting laterality of PA. RESULTS: Total 531 PA patients were included in the present study. The concordance rate between AVS and the adrenal CT was 51.0%(271/531). Receiver operating characteristic (ROC) curve of PST showed that the area under curve (AUC) was 0.604 [95% confidence interval (CI): 0.556, 0.652], the optimal cut-off value was 30%. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (+LR), and negative likelihood ratio (-LR) of PST for diagnosis bilateral PA on AVS was 72.8, 46.2%, 0.48, 0.71, 1.35, and 0.59, respectively. The prevalence of unilateral PA on AVS in patients with unilateral lesion on CT and negative PST, unilateral lesion on CT and positive PST, bilateral normal or lesions on CT and negative PST, and bilateral normal or lesions on CT and positive PST was 82.4% (108/131), 59.9% (91/152), 50.7% (37/73), and 44.6% (78/175), respectively. The sensitivity, specificity, PPV, NPV, +LR, and -LR of adrenal CT combined with PST for the diagnosis of unilateral PA were 34.4, 89.4%, 0.82, 0.49, 3.25, and 0.73, respectively. CONCLUSIONS: The combination of CT findings and PST can improve the accuracy of predicting laterality of PA.

Associations between dietary copper intake and hypertriglyceridemia among children and adolescents in the US.

BACKGROUND AND AIMS: A relationship exists between dietary copper intake and hypertriglyceridemia in the United States (US). However, children and adolescents have there is limited research data for children and adolescents, who have not been thoroughly investigated. This study aimed to carefully evaluate this relationship. METHODS AND RESULTS: This cross-sectional study included 3982 children and adolescents who participated in the US National Health and Nutrition Examination Survey 1999-2006. The outcome variable was hypertriglyceridemia, defined as a triglyceride (TG) concentration >150 mg/dL. Multivariate and binary logistic regression models were applied in this study. The median (Q1-Q3) copper intake and TG levels were 0.98 (0.71-1.32) mg/d and 72.00 (53.00-100.00) mg/dL, respectively. The smoothing curve showed an inverted L-shaped relationship between copper intake and the prevalence of hypertriglyceridemia in American children and adolescents. A binary logistic regression model was developed to evaluate the relationship between copper intake and the prevalence of hypertriglyceridemia, and the inflection point was 0.76 mg/d. The odds of developing hypertriglyceridemia significantly increased with increasing levels of copper intake (odds ratio (OR), 2.00; 95% confidence interval (CI): 1.39-2.86) in participants with copper intake >0.76 mg/d (P for log likelihood ratio test = 0.032). The association between high copper intake and increased hypertriglyceridemia risk was significantly stronger in participants with a high body mass index (BMI; ≥23 kg/m2) (OR: 2.09; 95% CI: 1.42-3.07) than in those with a low BMI (tertile 1-2) (p for interaction = 0.048). Moreover, the increase in copper intake in adolescents aged 13-18 years significantly increased the prevalence of hypertriglyceridemia (OR: 1.95; 95% CI: 1.38-2.76; p for interaction = 0.001). CONCLUSION: Higher dietary copper intake increases the prevalence of hypertriglyceridemia, especially among US adolescents with a BMI ≥23 kg/m2.

Coordinated Patient Care via Mobile Phone-Based Telemedicine in Secondary Stroke Prevention: A Propensity Score-Matched Cohort Study.

BACKGROUND: To prevent recurrent stroke, patients need to follow evidence-based practices following discharge; however, adherence to these practices is suboptimal. PURPOSE: To evaluate whether a smartphone mobile application can improve medication adherence and stroke awareness in secondary stroke prevention. METHODS: A retrospective study design was used. Patients with ischemic stroke registered in a database between August 2018 and January 2019 were enrolled. Propensity score matching was used to match patients managed with the mobile application compared with regular practice in a 1:2 ratio. RESULTS: Sixty-five patients were paired with 123 controls. Three-month medication adherence was 93.8% in the application group versus 82.9% in the control group ( P = .036). Patients in the application group were more likely to know stroke warning signs ( P = .003) and when to call an ambulance for stroke symptoms (87.7% vs 72.4%, P = .016). CONCLUSIONS: Using a mobile application may increase medication adherence and stroke awareness in secondary stroke prevention.