Dual-Polymer Functionalized Melanin-AgNPs Nanocomposite with Hydroxyapatite Binding Ability to Penetrate and Retain in Biofilm Sequentially Treating Periodontitis.

Periodontitis is the leading cause of adult tooth missing. Thorny bacterial biofilm and high reactive oxygen species (ROS) levels in tissue are key elements for the periodontitis process. It is meaningful to develop an advanced therapeutic system with sequential antibacterial/ antioxidant ability to meet the overall goals of periodontitis therapy. Herein, a dual-polymer functionalized melanin-AgNPs (P/D-MNP-Ag) with biofilm penetration, hydroxyapatite binding, and sequentially treatment ability are fabricated. Polymer enriched with 2-(Dimethylamino)ethyl methacrylate (D), can be protonated in an acid environment with enhanced positive charge, promoting penetration in biofilm. The other polymer is rich in phosphate group (P) and can chelate Ca2+, promoting the polymer to adhere to the hydroxyapatite surface. Melanin has good ROS scavenging and photothermal abilities, after in situ reduction Ag, melanin-AgNPs composite has sequentially transitioned between antibacterial and antioxidative ability due to heat and acid accelerated Ag+ release. The released Ag+ and heat have synergistic antibacterial effects for bacterial killing. With Ag+ consumption, the antioxidant ability of MNP recovers to scavenge ROS in the inflammatory area. When applied in the periodontitis model, P/D-MNP-Ag has good therapeutical effects to ablate biofilm, relieve inflammation state, and reduce alveolar bone loss. P/D-MNP-Ag with sequential treatment ability provides a reference for developing advanced oral biofilm eradication systems.

Molecular radio afterglow probes for cancer radiodynamic theranostics.

X-ray-induced afterglow and radiodynamic therapy tackle the tissue penetration issue of optical imaging and phototherapy. However, inorganic nanophosphors used in this therapy have their radio afterglow dynamic function as always on, limiting the detection specificity and treatment efficacy. Here we report organic luminophores (IDPAs) with near-infrared afterglow and 1O2 production after X-ray irradiation for cancer theranostics. The in vivo radio afterglow of IDPAs is >25.0 times brighter than reported inorganic nanophosphors, whereas the radiodynamic production of 1O2 is >5.7 times higher than commercially available radio sensitizers. The modular structure of IDPAs permits the development of a smart molecular probe that only triggers its radio afterglow dynamic function in the presence of a cancer biomarker. Thus, the probe enables the ultrasensitive detection of a diminutive tumour (0.64 mm) with superb contrast (tumour-to-background ratio of 234) and tumour-specific radiotherapy for brain tumour with molecular precision at low dosage. Our work reveals the molecular guidelines towards organic radio afterglow agents and highlights new opportunities for cancer radio theranostics.

Liquid chromatography-mass spectrometry-based metabolomics and fluxomics reveals the metabolic alterations in glioma U87MG multicellular tumor spheroids versus two-dimensional cell cultures.

RATIONALE: Multicellular tumor spheroids (MCTSs) that reconstitute the metabolic characteristics of in vivo tumor tissue may facilitate the discovery of molecular biomarkers and effective anticancer therapies. However, little is known about how cancer cells adapt their metabolic changes in complex three-dimensional (3D) microenvironments. Here, using the two-dimensional (2D) cell model as control, the metabolic phenotypes of glioma U87MG multicellular tumor spheroids were systematically investigated based on static metabolomics and dynamic fluxomics analysis. METHODS: A liquid chromatography-mass spectrometry-based global metabolomics and lipidomics approach was adopted to survey the cellular samples from 2D and 3D culture systems, revealing marked molecular differences between them. Then, by means of metabolomic pathway analysis, the metabolic pathways altered in glioma MCTSs were found using 13 C6 -glucose as a tracer to map the metabolic flux of glycolysis, the tricarboxylic acid (TCA) cycle, de novo nucleotide synthesis, and de novo lipid biosynthesis in the MCTS model. RESULTS: We found nine metabolic pathways as well as glycerolipid, glycerophospholipid and sphingolipid metabolism to be predominantly altered in glioma MCTSs. The reduced nucleotide metabolism, amino acid metabolism and glutathione metabolism indicated an overall lower cellular activity in MCTSs. Through dynamic fluxomics analysis in the MCTS model, we found that cells cultured in MCTSs exhibited increased glycolysis activity and de novo lipid biosynthesis activity, and decreased the TCA cycle and de novo purine nucleotide biosynthesis activity. CONCLUSIONS: Our study highlights specific, altered biochemical pathways in MCTSs, emphasizing dysregulation of energy metabolism and lipid metabolism, and offering novel insight into metabolic events in glioma MCTSs.

Whole-exome sequencing as the first-tier test for patients in neonatal intensive care unit: a Chinese single-center study.

BACKGROUND: Genetic disorders significantly affect patients in neonatal intensive care units, where establishing a diagnosis can be challenging through routine tests and supplementary examinations. Whole-exome sequencing offers a molecular-based approach for diagnosing genetic disorders. This study aimed to assess the importance of whole-exome sequencing for neonates in intensive care through a retrospective observational study within a Chinese cohort. METHODS: We gathered data from neonatal patients at Tianjin Children's Hospital between January 2018 and April 2021. These patients presented with acute illnesses and were suspected of having genetic disorders, which were investigated using whole-exome sequencing. Our retrospective analysis covered clinical data, genetic findings, and the correlation between phenotypes and genetic variations. RESULTS: The study included 121 neonates. Disorders affected multiple organs or systems, predominantly the metabolic, neurological, and endocrine systems. The detection rate for whole-exome sequencing was 52.9% (64 out of 121 patients), identifying 84 pathogenic or likely pathogenic genetic variants in 64 neonates. These included 13 copy number variations and 71 single-nucleotide variants. The most frequent inheritance pattern was autosomal recessive (57.8%, 37 out of 64), followed by autosomal dominant (29.7%, 19 out of 64). In total, 40 diseases were identified through whole-exome sequencing. CONCLUSION: This study underscores the value and clinical utility of whole-exome sequencing as a primary diagnostic tool for neonates in intensive care units with suspected genetic disorders. Whole-exome sequencing not only aids in diagnosis but also offers significant benefits to patients and their families by providing clarity in uncertain diagnostic situations.

The developmental characteristics of proactive and reactive aggression in late childhood: The effect of parental control.

Previous research has confirmed that parental control is related to children's aggressive behavior. However, few studies have focused on proactive and reactive aggression to distinguish the different effects of parental psychological and behavioral control. Moreover, additional longitudinal evidence is needed to understand these links. In the current paper, a three-wave longitudinal study was conducted to examine the developmental characteristics of proactive and reactive aggression and the role of parental control in China. A total of 484 4th- and 7th-grade students participated at wave 1 (51.65% in 4th-grade, Mage = 11.66 ± 1.52 years), 465 students (52.04% in 4th-grade) at wave 2, and 447 children (51.90% in 4th-grade) at wave 3. The results showed that: (1) Proactive aggression in late childhood remained stable overall, while reactive aggression displayed a clear upward trend. (2) In proactive aggression, boys and girls had a consistent developmental trend. The initial level of boys was higher than that of girls. In reactive aggression, the growth rate was inversely associated with their initial level and the initial level of boys in 7th-grade was significantly higher than that of girls. (3) Both parental psychological and behavioral control positively predicted students' reactive aggression in 4th- and 7th-grade, whereas only parental behavioral control positively predicted proactive aggression in 7th-grade students, with no gender differences.

Hydrogen Spillover-Driven Dynamic Evolution and Migration of Iron Oxide for Structure Regulation of Versatile Magnetic Nanocatalysts.

Magnetic nanocatalysts with properties of easy recovery, induced heating, or magnetic levitation play a crucial role in advancing intelligent techniques. Herein, we report a method for the synthesis of versatile core-shell-type magnetic nanocatalysts through "noncontact" hydrogen spillover-driven reduction and migration of iron oxide with the assistance of Pd. In situ analysis techniques were applied to visualize the dynamic evolution of the magnetic nanocatalysts. Pd facilitates the dissociation of hydrogen molecules into activated H*, which then spills and thus drives the iron oxide reduction, gradual outward split, and migration through the carbonaceous shell. By controlling the evolution stage, nanocatalysts having diverse architectures including core-shell, split core-shell, or hollow type, each featuring Pd or PdFe loaded on the carbon shell, can be obtained. As a showcase, a magnetic nanocatalyst (Pd-loaded split core-shell) can hydrogenate crotonaldehyde to butanal (26 624 h-1 in TOF, ∼100% selectivity), outperforming reported Pd-based catalysts. This is due to the synergy of the enhanced local magnetothermal effect and the preferential adsorption of -C═C on Pd with a small d bandwidth. Another catalyst (PdFe-loaded split core-shell) also delivers a robust performance in phenylacetylene semihydrogenation (100% conversion, 97.5% selectivity) as PdFe may inhibit the overhydrogenation of -C═C. Importantly, not only Pd, other noble metals (e.g., Pt, Ru, and Au) also showed a similar property, revealing a general rule that hydrogen spillover drives the dynamic reduction, splitting, and migration of encapsulated nanosized iron oxide, resulting in diverse structures. This study would offer a structure-controllable fabrication of high-performance magnetic nanocatalysts for various applications.

Bovine Omasum-Inspired Interfacial Carbon-Based Nanocomposite for Saliva Metabolic Screening of Gastric Cancer.

Gastric cancer is one of the most common malignant digestive cancers, and its diagnostic has still faced challenges based on metabolic analysis due to complex sample pretreatment and low metabolite abundance. In this study, inspired by the structure of bovine omasum, we in situ synthesized a novel interfacial carbon-based nanocomposite of graphene supported nickel nanoparticles-encapsulated in the nitrogen-doped carbon nanotube (Ni/N-CNT/rGO), which was served as a novel matrix with enhanced ionization efficiency for the matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) saliva metabolic analysis of gastric cancer. Benefiting from its high sp2 graphitic degree, large surface area, strong UV absorption, and rich active sites, Ni/N-CNT/rGO matrix exhibited excellent performances of reproducibility, coverage, salt-tolerance, sensitivity, and adsorption ability in MALDI-TOF MS. The differential scanning calorimetry (DSC) and thermal conversion behaviors explained the highly efficient LDI mechanism. Based on saliva metabolic fingerprints, Ni/N-CNT/rGO assisted LDI MS with cross-validation analysis could successfully distinguish gastric cancer patients from healthy controls through the screening of four potential biomarkers with an accuracy of 92.50%, specificity of 88.03%, and sensitivity of 97.12%. This work provided a fast and sensitive MS sensing platform for the metabolomics characterization of gastric cancer and might have potential value for precision medicine in the future.

On-Tissue Chemical Oxidation Followed by Derivatization for Mass Spectrometry Imaging Enables Visualization of Primary and Secondary Hydroxyl-Containing Metabolites in Biological Tissues.

On-tissue chemical derivatization combined with mass spectrometry imaging (MSI) can effectively visualize low-abundance and poorly ionizable molecules in biological tissues. Owing to the lack of an effective chemical reaction environment on the tissue surface, the development of direct one-step derivatization reactions is challenging. Herein, we present a two-step reaction involving on-tissue chemical oxidation followed by derivatization combined with airflow-assisted desorption electrospray ionization-MSI, enabling the visualization of primary and secondary hydroxyl-containing metabolites (PSHMs) within the tissue sections. This method indirectly achieved on-tissue derivatization by combining two reactions. Hydroxyl was converted to carbonyl using chemical oxidants, and subsequently, carbonyl was derived using Girard's P reagent. Using this methodology, 169 PSHMs, including hydroxy fatty acids (OH-FAs), fatty alcohols (FOHs), and sterol lipids, were detected and imaged in the tissues of rat brain, kidney, and liver. Moreover, we found that the abundant PSHMs, fatty aldehydes, and oxo fatty acids were significantly dysregulated in the liver and kidney tissues of type 2 diabetic rats; in particular, OH-FAs and FOHs were remarkably up-regulated in the diabetic rat liver tissues. The aberrations of these oxidative metabolites provide insights into the understanding of the molecular pathological mechanism of diabetes. This study demonstrates a novel, two-step reaction strategy for on-tissue derivatization with the analysis of previously inaccessible molecules using MSI.

Database-Driven Spatially Resolved Lipidomics Highlights Heterogeneous Metabolic Alterations in Type 2 Diabetic Mice.

Spatially resolved lipidomics is pivotal for detecting and interpreting lipidomes within spatial contexts using the mass spectrometry imaging (MSI) technique. However, comprehensive and efficient lipid identification in MSI remains challenging. Herein, we introduce a high-coverage, database-driven approach combined with air-flow-assisted desorption electrospray ionization (AFADESI)-MSI to generate spatial lipid profiles across whole-body mice. Using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS), we identified 2868 unique lipids in the serum and various organs of mice. Subsequently, we systematically evaluated the distinct ionization properties of the lipids between LC-MS and MSI and created a detailed MSI database containing 14 123 ions. This method enabled the visualization of aberrant fatty acid and phospholipid metabolism across organs in a diabetic mouse model. As a powerful extension incorporated into the MSIannotator tool, our strategy facilitates the rapid and accurate annotation of lipids, providing new research avenues for probing spatially resolved heterogeneous metabolic changes in response to diseases.

Total serum vitamin B12 (cobalamin) LC-MS/MS assay as an arbiter of clinically discordant immunoassay results.

OBJECTIVES: Measurement of the serum levels of vitamin B12 (VB12) is key for evaluating VB12 deficiency-dependent anemia. Immunoassay, the major method for determining VB12, tends to give false-normal results because of the presence of anti-intrinsic factor (IF-Ab) or other factors such as heterophilic antibodies et al. This study aimed to develop a liquid chromatography tandem mass spectrometry (LC-MS/MS) method that is helpful for distinguish false normal VB12 results measured by the immunoassay. METHODS: Different forms of VB12 were derivatized into CN-B12, which was collected through solid-phase extraction and analyzed via LC-MS/MS. 236 serum samples were measured both by LC-MS/MS and immunoassay, results were compared, and the IF-Ab effect was evaluated. RESULTS: The LC-MS/MS assay afforded a linear slope from 20 to 4,000 pmol/L for CN-B12. OH-VB12, methyl-VB12, and CoA-VB12 showed recovery within 89.3-109.5%. The intra-assay CV of VB12 was 2.6-4.1%, whereas the total CV was 9.3-9.8%. Passing-Bablok regression between LC-MS/MS and immunoassay results showed that the slope was 1.085 and the intercept was -15.691. The Bland-Altman plot showed that the mean difference and difference% were -34.6 pmol/L and 0.3%, respectively. Inter-rater agreement analysis showed that the linear weighted kappa value was 0.885, implying good agreement between the two methods. However, two samples were falsely elevated and one sample was falsely normal in the immunoassay compared with LC-MS/MS. The LC-MS/MS method helped in the distinction of false-normal VB12 results shown by the immunoassay. CONCLUSIONS: The VB12 LC-MS/MS method can be used as an arbiter of clinically discordant immunoassay results.

Nanoscale metal-organic framework delivers rapamycin to induce tissue immunogenic cell death and potentiates cancer immunotherapy.

Rapamycin has great potential in the antitumor application, but its therapeutic effect is seriously affected by poor water solubility, targeting ability, and low bioavailability. Here, we constructed a novel composite nanomaterial with PCN-224 as a drug carrier and loaded rapamycin, named R@BP@HA. The nanoplate not only improves targeting, but also synergizes rapamycin with PCN-224 to effectively promote tumor cell apoptosis, which subsequently causes immunogenic cell death (ICD), and shows strong therapeutic effect in 4T1 breast cancer model. The treatment effect depends on three main points:(i)Proapoptotic effect of rapamycin on tumor cells;(ii)ROS production by PCN-224-mediated photodynamic therapy;(iii)ICD induced DC maturation, increased immune response and promoted T cell proliferation and differentiation. This nanoplate offers potential antitumor efficacy in combination with chemotherapy, photodynamic therapy, and immunotherapy.

A novel bidirectional perfusion-like administered system for NIR-II fluorescence imaging precision diagnosis of bladder cancer.

Intravesical instillation has been considered an efficient route for detecting bladder cancer. However, only a small fraction of administered dose permeates into tumor tissues, and insufficient retention time limits their application. In this work, a novel intravesical bidirectional perfusion-like administered mode was developed to improve diagnostic accuracy of bladder tumor imaging. Specifically, the ultrasmall AuPd-P-FA Nanoprobe exhibit excellent NIR-II FL imaging performance due to electronic structure perturbation. Benefiting from the size advantage for kidney metabolism and FA targeting specificity, AuPd-P-FA could effectively administration to bladder tumor. When AuPd-P-FA reached maximum enrichment at 1 h post-injection, the localized and mild thermal energy produced upon laser irradiation activated a phase transition. This thermo-sensitive characteristic could prolong the retention time in bladder and the fluorescence signal could be clearly observed at 6 h post-injection with high accuracy. This novel intravesical bidirectional perfusion-like administered mode is expected to achieve a non-invasive diagnosis of early bladder cancer.

An Organ-Specific Metabolite Annotation Approach for Ambient Mass Spectrometry Imaging Reveals Spatial Metabolic Alterations of a Whole Mouse Body.

Rapid and accurate metabolite annotation in mass spectrometry imaging (MSI) can improve the efficiency of spatially resolved metabolomics studies and accelerate the discovery of reliable in situ disease biomarkers. To date, metabolite annotation tools in MSI generally utilize isotopic patterns, but high-throughput fragmentation-based identification and biological and technical factors that influence structure elucidation are active challenges. Here, we proposed an organ-specific, metabolite-database-driven approach to facilitate efficient and accurate MSI metabolite annotation. Using data-dependent acquisition (DDA) in liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) to generate high-coverage product ions, we identified 1620 unique metabolites from eight mouse organs (brain, liver, kidney, heart, spleen, lung, muscle, and pancreas) and serum. Following the evaluation of the adduct form difference of metabolite ions between LC-MS and airflow-assisted desorption electrospray ionization (AFADESI)-MSI and deciphering organ-specific metabolites, we constructed a metabolite database for MSI consisting of 27,407 adduct ions. An automated annotation tool, MSIannotator, was then created to conduct metabolite annotation in the MSI dataset with high efficiency and confidence. We applied this approach to profile the spatially resolved landscape of the whole mouse body and discovered that metabolites were distributed across the body in an organ-specific manner, which even spanned different mouse strains. Furthermore, the spatial metabolic alteration in diabetic mice was delineated across different organs, exhibiting that differentially expressed metabolites were mainly located in the liver, brain, and kidney, and the alanine, aspartate, and glutamate metabolism pathway was simultaneously altered in these three organs. This approach not only enables robust metabolite annotation and visualization on a body-wide level but also provides a valuable database resource for underlying organ-specific metabolic mechanisms.

Norm ISWSVR: A Data Integration and Normalization Approach for Large-Scale Metabolomics.

Large-scale and long-period metabolomics study is more susceptible to various sources of systematic errors, resulting in nonreproducibility and poor data quality. A reliable and robust batch correction method removes unwanted systematic variations and improves the statistical power of metabolomics data, which undeniably becomes an important issue for the quality control of metabolomics. This study proposed a novel data normalization and integration method, Norm ISWSVR. It is a two-step approach via combining the best-performance internal standard correction with support vector regression normalization, comprehensively removing the systematic and random errors and matrix effects. This method was investigated in three untargeted lipidomics or metabolomics datasets, and the performance was further evaluated systematically in comparison with that of 11 other normalization methods. As a result, Norm ISWSVR decreased the data's median cross-validated relative standard deviation (cvRSD), increased the correlation between QCs, improved the classification accuracy of biomarkers, and was well-compatible with quantitative data. More importantly, Norm ISWSVR also allows a low frequency of QCs, which could significantly decrease the burden of a large-scale experiment. Correspondingly, Norm ISWSVR favorably improves the data quality of large-scale metabolomics data.

Data-Driven Deciphering of Latent Lesions in Heterogeneous Tissue Using Function-Directed t-SNE of Mass Spectrometry Imaging Data.

Mass spectrometry imaging (MSI), which quantifies the underlying chemistry with molecular spatial information in tissue, represents an emerging tool for the functional exploration of pathological progression. Unsupervised machine learning of MSI datasets usually gives an overall interpretation of the metabolic features derived from the abundant ions. However, the features related to the latent lesions are always concealed by the abundant ion features, which hinders precise delineation of the lesions. Herein, we report a data-driven MSI data segmentation approach for recognizing the hidden lesions in the heterogeneous tissue without prior knowledge, which utilizes one-step prediction for feature selection to generate function-specific segmentation maps of the tissue. The performance and robustness of this approach are demonstrated on the MSI datasets of the ischemic rat brain tissues and the human glioma tissue, both possessing different structural complexity and metabolic heterogeneity. Application of the approach to the MSI datasets of the ischemic rat brain tissues reveals the location of the ischemic penumbra, a hidden zone between the ischemic core and the healthy tissue, and instantly discovers the metabolic signatures related to the penumbra. In view of the precise demarcation of latent lesions and the screening of lesion-specific metabolic signatures in tissues, this approach has great potential for in-depth exploration of the metabolic organization of complex tissue.

A "Dual-Source, Dual-Activation" Strategy for an NIR-II Window Theranostic Nanosystem Enabling Optimal Photothermal-Ion Combination Therapy.

The activatable imaging technique in the second near-infrared window (NIR-II) utilizes the stimulation of cancer-associated biomarkers for specific imaging to guide precise NIR-II photothermal therapy. However, most activatable nanoprobes with single-source stimulation are insufficient in providing comprehensive information regarding the tumor, severely restricting the therapeutic optimization, especially in NIR-II photothermal therapy (PTT)-based combination therapy. Herein, a "dual-source, dual-activation" strategy-based multifunctional nanosystem, PPAC, is reported as a promising tool for activatable NIR-II fluorescence (FL)/ratiometric photoacoustic (PA) imaging-guided "localization-timing" photothermal-ion therapy (PTIT). A fibroblast activation protein (FAP)-responsive peptide to modify the surface of Pd nanosheets with excellent NIR-II absorption ability can efficiently cross-link BSA-CQ4T to realize NIR-II FL quenching, followed by the loading of Ag to construct the PPAC. Triggered by the specific cleavage with FAP on the perivascular cancer-associated fibroblasts (first source), the PPAC can correspondingly release BSA-CQ4T for rapid fluorescence recovery. The nanosystems are subsequently taken up by tumor cells, where the overexpressed H2 O2 (second source) promotes the oxidation of Ag shell to Ag+ , and further leads the real-time ratiometric PA signals (Ag-PA660/Pd-PA1050) that can monitor the Ag+ ions-related production efficiency and therapeutic performance. Intelligent integration of dual-modality imaging information can comprehensively provide the right time-point and site-specificity for selective NIR-II PTT.

Dual H2 O2 -Amplified Nanofactory for Simultaneous Self-Enhanced NIR-II Fluorescence Activation Imaging and Synergistic Tumor Therapy.

Activatable fluorescence imaging in the second near-infrared window (NIR-II FL, 1000-1700 nm) is of great significance for accurate tumor diagnosis and targeting therapy. However, the clinical translation of most stimulus-activated nanoprobes is severely restricted by insufficient tumor response and out-of-synchronization theranostic process. Herein, an intelligent nanofactory AUC-GOx/Cel that possesses the "external supply, internal promotion" dual H2 O2 -amplification strategy for homologous activated tumor theranostic is designed. This nanofactory is constructed via a two-step biomineralization method using Au-doped Ag2 S as a carrier for glucose oxidase (GOx) and celastrol, followed by the growing of CuS to "turn off" the NIR-II FL signal. In the overexpressed H2 O2 tumor-microenvironment, the CuS featuring a responsive-degradability behavior can effectively release Cu ions, resulting in the "ON" state of NIR-II FL and Fenton-like activity. The exposed GOx can realize the intratumoral H2 O2 supply (external supply) via the effective conversion of glucose, and mediating tumor-starvation therapy; the interaction of celastrol and mitochondria can offer a substantial increase in the endogenous H2 O2 level (internal promotion), thereby significantly promoting the chemodynamic therapy (CDT) efficacy. Meanwhile, the dual H2 O2 -enhancement performance will in turn accelerate the degradation of AUC-GOx/Cel, and achieve a positive feedback mechanism for self-reinforcing CDT.

Transposon insertions regulate genome-wide allele-specific expression and underpin flower colour variations in apple (Malus spp.).

Allele-specific expression (ASE) can lead to phenotypic diversity and evolution. However, the mechanisms regulating ASE are not well understood, particularly in woody perennial plants. In this study, we investigated ASE genes in the apple cultivar 'Royal Gala' (RG). A high quality chromosome-level genome was assembled using a homozygous tetra-haploid RG plant, derived from anther cultures. Using RNA-sequencing (RNA-seq) data from RG flower and fruit tissues, we identified 2091 ASE genes. Compared with the haploid genome of 'Golden Delicious' (GD), a parent of RG, we distinguished the genomic sequences between the two alleles of 817 ASE genes, and further identified allele-specific presence of a transposable element (TE) in the upstream region of 354 ASE genes. These included MYB110a that encodes a transcription factor regulating anthocyanin biosynthesis. Interestingly, another ASE gene, MYB10 also showed an allele-specific TE insertion and was identified using genome data of other apple cultivars. The presence of the TE insertion in both MYB genes was positively associated with ASE and anthocyanin accumulation in apple petals through analysis of 231 apple accessions, and thus underpins apple flower colour evolution. Our study demonstrated the importance of TEs in regulating ASE on a genome-wide scale and presents a novel method for rapid identification of ASE genes and their regulatory elements in plants.

Development and validation of a sensitive and reliable targeted metabolomics method for the quantification of cardiovascular disease-related biomarkers in plasma using ultrahigh-performance liquid chromatography-tandem mass spectrometry.

RATIONALE: Cardiovascular disease, as a multifactorial disease caused by genetics and environment, has emerged as a leading cause of mortality. The discovery of metabolic biomarkers for the clinical diagnosis, early warning and elucidation of the molecular pathogenesis of cardiovascular disease, using metabolomics, has attracted broad interest. Therefore, this work aimed to develop a sensitive and reliable targeted metabolomics method for the quantification of cardiovascular disease-related biomarkers in plasma. METHODS: The method was developed and validated using ultrahigh-performance liquid chromatography augmented with tandem mass spectrometry (UHPLC/MS/MS). The LC conditions and MS parameters were optimized using selected reaction monitoring scanning mode to high-throughput and sensitive separation, and could detect 20 metabolic biomarkers in a single experiment. And the linearity, selectivity, accuracy, precision, stability and recovery of the developed method were assessed according to the Bioanalytical Method Validation guidelines of the United States Food and Drug Administration. RESULTS: These quantified metabolic biomarkers are involved in pathways such as aromatic amino acid catabolism (e.g. phenylalanine, tryptophan, tyrosine), trimethylamine N-oxide (TMAO) biosynthesis (e.g. TMAO, choline, carnitine, betaine) and histidine metabolism (e.g. histidine), among others. All analytes exhibited excellent linearities with coefficients of determination greater than 0.99. Accuracies deviated by less than 15% for medium- and high-concentration samples and less than 20% for low-concentration samples, with intra- and inter-day precisions of 1.12-14.12% and 0.30-13.74%, respectively. Recoveries and stabilities also met the analysis requirements of biological samples. CONCLUSIONS: The targeted metabolomics method was shown to have a powerful ability to accurately analyze metabolic biomarkers, thereby providing valuable information for large-scale biomarker validation and clarifying the potential material basis of cardiovascular disease for clinical diagnosis or early warning.

Contrast-enhanced CT-based radiomics model for differentiating risk subgroups of thymic epithelial tumors.

BACKGROUND: To validate a contrast-enhanced CT (CECT)-based radiomics model (RM) for differentiating various risk subgroups of thymic epithelial tumors (TETs). METHODS: A retrospective study was performed on 164 patients with TETs who underwent CECT scans before treatment. A total of 130 patients (approximately 79%, from 2012 to 2018) were designated as the training set, and 34 patients (approximately 21%, from 2019 to 2021) were designated as the testing set. The analysis of variance and least absolute shrinkage and selection operator algorithm methods were used to select the radiomics features. A logistic regression classifier was constructed to identify various subgroups of TETs. The predictive performance of RMs was evaluated based on receiver operating characteristic (ROC) curve analyses. RESULTS: Two RMs included 16 and 13 radiomics features to identify three risk subgroups of traditional risk grouping [low-risk thymomas (LRT: Types A, AB and B1), high-risk thymomas (HRT: Types B2 and B3), thymic carcinoma (TC)] and improved risk grouping [LRT* (Types A and AB), HRT* (Types B1, B2 and B3), TC], respectively. For traditional risk grouping, the areas under the ROC curves (AUCs) of LRT, HRT, and TC were 0.795, 0.851, and 0.860, respectively, the accuracy was 0.65 in the training set, the AUCs were 0.621, 0.754, and 0.500, respectively, and the accuracy was 0.47 in the testing set. For improved risk grouping, the AUCs of LRT*, HRT*, and TC were 0.855, 0.862, and 0.869, respectively, and the accuracy was 0.72 in the training set; the AUCs were 0.778, 0.716, and 0.879, respectively, and the accuracy was 0.62 in the testing set. CONCLUSIONS: CECT-based RMs help to differentiate three risk subgroups of TETs, and RM established according to improved risk grouping performed better than traditional risk grouping.