Effects of lakeshore landcover types and environmental factors on microplastic distribution in lakes on the Inner Mongolia Plateau, China.

Microplastic pollution in freshwater environments has received increasing attention. However, limited research on the occurrence and distribution of microplastics in plateau lakes. This study investigated the microplastic characteristics and influencing factors in lakes with different land cover types on the Inner Mongolia Plateau. Results showed that microplastic abundance ranged from 0.5 to 12.6 items/L in water and 50-325 items/kg in sediments. Microplastics in water were predominantly polypropylene (50.5%), fragments (40.5%), and 50-200 µm (66.7%). High-density (27.9%), fibrous (69.3%), and large-sized microplastics (47.7%) were retained primarily in lake sediments. The highest microplastic abundance in water was found in cropland lakes and grassland lakes, while that in sediments was in descending order of desert lakes > cropland lakes > grassland lakes > forest-grassland lakes. Differences among lake types suggest that agriculture, tourism, and atmospheric transport may be critical microplastic sources. Microplastic distribution was positively correlated with farmland and artificial surface coverage, showing that land cover types related to human activities could exacerbate microplastic pollution in lakes. Redundancy analysis showed that ammonia nitrogen and pH were the key physicochemical factors affecting microplastic distribution in lakes, indicating the potential sources of microplastics in lakes and the uniqueness of microplastic occurrence characteristics in desert saline-alkaline lakes, respectively.

The complexation of atmospheric Brown carbon surrogates on the generation of hydroxyl radical from transition metals in simulated lung fluid.

Atmospheric particulate matter (PM) poses great adverse effects through the production of reactive oxygen species (ROS). Various components in PM are acknowledged to induce ROS formation, while the interactions among chemicals remain to be elucidated. Here, we systematically investigate the influence of Brown carbon (BrC) surrogates (e.g., imidazoles, nitrocatechols and humic acid) on hydroxyl radical (OH) generation from transition metals (TMs) in simulated lung fluid. Present results show that BrC has an antagonism (interaction factor: 20-90 %) with Cu2+ in OH generation upon the interaction with glutathione, in which the concentrations of BrC and TMs influence the extent of antagonism. Rapid OH generation in glutathione is observed for Fe2+, while OH formation is very little for Fe3+. The compositions of antioxidants (e.g., glutathione, ascorbate, urate), resembling the upper and lower respiratory tract, respond differently to BrC and TMs (Cu2+, Fe2+ and Fe3+) in OH generation and the degree of antagonism. The complexation equilibrium constants and site numbers between Cu2+ and humic acid were further analyzed using fluorescence quenching experiments. Possible complexation products among TMs, 4-nitrocatechol and glutathione were also identified using quadropule-time-of-flight mass spectrometry. The results suggest atmospheric BrC widely participate in complexation with TMs which influence OH formation in the human lung fluid, and complexation should be considered in evaluating ROS formation mediated by ambient PM.

(Poly)phenol intake, plant-rich dietary patterns and cardiometabolic health: a cross-sectional study.

Diet is an important modifiable risk factor for cardiometabolic diseases. Plant foods contain a complex mixture of nutrients and bioactive compounds such as (poly)phenols. Plant-rich dietary patterns have been associated with reduced cardiometabolic risk in epidemiological studies. However, studies have not fully considered (poly)phenols as a mediating factor in the relationship. A cross-sectional analysis was conducted in 525 healthy participants, aged 41.6 ± 18.3 years. Volunteers completed the validated European Prospective Investigation into Diet and Cancer (EPIC) Norfolk Food Frequency Questionnaire (FFQ). We investigated the associations between plant-rich dietary patterns, (poly)phenol intake, and cardiometabolic health. Positive associations were found between (poly)phenols and higher adherence to dietary scores, except for the unhealthy Plant-based Diet Index (uPDI), which was negatively associated with (poly)phenol intake. Correlations were significant for healthy PDI (hPDI), with positive associations with proanthocyanidins (r = 0.39, p < 0.01) and flavonols (r = 0.37, p < 0.01). Among dietary scores, Dietary Approaches to Stop Hypertension (DASH) showed negative associations with diastolic blood pressure (DBP), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and non-high-density lipoprotein cholesterol (Non-HDL-C) (stdBeta -0.12 to -0.10, p < 0.05). The Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) score was positively associated with flow-mediated dilation (FMD, stdBeta = 0.10, p = 0.02) and negatively associated with the 10-year Atherosclerotic Cardiovascular Disease (ASCVD) risk score (stdBeta = -0.12, p = 0.01). Higher intake of flavonoids, flavan-3-ols, flavan-3-ol monomers, theaflavins, and hydroxybenzoic acids (stdBeta: -0.31 to -0.29, p = 0.02) also showed a negative association with a 10-year ASCVD risk score. Flavanones showed significant associations with cardiometabolic markers such as fasting plasma glucose (FPG) (stdBeta = -0.11, p = 0.04), TC (stdBeta = -0.13, p = 0.03), and the Homeostasis Model Assessment (HOMA) of beta cell function (%B) (stdBeta = 0.18, p = 0.04). Flavanone intake was identified as a potential partial mediator in the negative association between TC and plant-rich dietary scores DASH, Original Mediterranean diet scores (O-MED), PDI, and hPDI (proportion mediated = 0.01% to 0.07%, p < 0.05). Higher (poly)phenol intake, particularly flavanone intake, is associated with higher adherence to plant-rich dietary patterns and favourable biomarkers of cardiometabolic risk indicating (poly)phenols may be mediating factors in the beneficial effects.

Machine Learning Predicting Optimal Preparation of Silica-Coated Gold Nanorods for Photothermal Tumor Ablation.

Gold nanorods (GNRs) coated with silica shells are excellent photothermal agents with high surface functionality and biocompatibility. Understanding the correlation of the coating process with both structure and property of silica-coated GNRs is crucial to their optimizing preparation and performance, as well as tailoring potential applications. Herein, we report a machine learning (ML) prediction of coating silica on GNR with various preparation parameters. A total of 306 sets of silica-coated GNRs altogether were prepared via a sol-gel method, and their structures were characterized to extract a dataset available for eight ML algorithms. Among these algorithms, the eXtreme gradient boosting (XGboost) classification model affords the highest prediction accuracy of over 91%. The derived feature importance scores and relevant decision trees are employed to address the optimal process to prepare well-structured silica-coated GNRs. The high-throughput predictions have been adopted to identify optimal process parameters for the successful preparation of dumbbell-structured silica-coated GNRs, which possess a superior performance to a conventional cylindrical core-shell counterpart. The dumbbell silica-coated GNRs demonstrate an efficient enhanced photothermal performance in vivo and in vitro, validated by both experiments and time domain finite difference calculations. This study epitomizes the potential of ML algorithms combined with experiments in predicting, optimizing, and accelerating the preparation of core-shell inorganic materials and can be extended to other nanomaterial research.

GPGPS: a robust prognostic gene pair signature of glioma ensembling IDH mutation and 1p/19q co-deletion.

MOTIVATION: Many studies have shown that IDH mutation and 1p/19q co-deletion can serve as prognostic signatures of glioma. Although these genetic variations affect the expression of one or more genes, the prognostic value of gene expression related to IDH and 1p/19q status is still unclear. RESULTS: We constructed an ensemble gene pair signature for the risk evaluation and survival prediction of glioma based on the prior knowledge of the IDH and 1p/19q status. First, we separately built two gene pair signatures IDH-GPS and 1p/19q-GPS and elucidated that they were useful transcriptome markers projecting from corresponding genome variations. Then, the gene pairs in these two models were assembled to develop an integrated model named Glioma Prognostic Gene Pair Signature (GPGPS), which demonstrated high area under the curves (AUCs) to predict 1-, 3- and 5-year overall survival (0.92, 0.88 and 0.80) of glioma. GPGPS was superior to the single GPSs and other existing prognostic signatures (avg AUC = 0.70, concordance index = 0.74). In conclusion, the ensemble prognostic signature with 10 gene pairs could serve as an independent predictor for risk stratification and survival prediction in glioma. This study shed light on transferring knowledge from genetic alterations to expression changes to facilitate prognostic studies. AVAILABILITY AND IMPLEMENTATION: Codes are available at https://github.com/Kimxbzheng/GPGPS.git. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MrGPS: an m6A-related gene pair signature to predict the prognosis and immunological impact of glioma patients.

N6-methyladenosine (m6A) RNA methylation is the predominant epigenetic modification for mRNAs that regulates various cancer-related pathways. However, the prognostic significance of m6A modification regulators remains unclear in glioma. By integrating the TCGA lower-grade glioma (LGG) and glioblastoma multiforme (GBM) gene expression data, we demonstrated that both the m6A regulators and m6A-target genes were associated with glioma prognosis and activated various cancer-related pathways. Then, we paired m6A regulators and their target genes as m6A-related gene pairs (MGPs) using the iPAGE algorithm, among which 122 MGPs were significantly reversed in expression between LGG and GBM. Subsequently, we employed LASSO Cox regression analysis to construct an MGP signature (MrGPS) to evaluate glioma prognosis. MrGPS was independently validated in CGGA and GEO glioma cohorts with high accuracy in predicting overall survival. The average area under the receiver operating characteristic curve (AUC) at 1-, 3- and 5-year intervals were 0.752, 0.853 and 0.831, respectively. Combining clinical factors of age and radiotherapy, the AUC of MrGPS was much improved to around 0.90. Furthermore, CIBERSORT and TIDE algorithms revealed that MrGPS is indicative for the immune infiltration level and the response to immune checkpoint inhibitor therapy in glioma patients. In conclusion, our study demonstrated that m6A methylation is a prognostic factor for glioma and the developed prognostic model MrGPS holds potential as a valuable tool for enhancing patient management and facilitating accurate prognosis assessment in cases of glioma.

Controllable Construction of Amino-Functionalized Dynamic Covalent Porous Polymers for High-Efficiency CO2 Capture from Flue Gas.

The design of high-efficiency CO2 adsorbents with low cost, high capacity, and easy desorption is of high significance for reducing carbon emissions, which yet remains a great challenge. This work proposes a facile construction strategy of amino-functional dynamic covalent materials for effective CO2 capture from flue gas. Upon the dynamic imine assembly of N-site rich motif and aldehyde-based spacers, nanospheres and hollow nanotubes with spongy pores were constructed spontaneously at room temperature. A commercial amino-functional molecule tetraethylenepentamine could be facilely introduced into the dynamic covalent materials by virtue of the dynamic nature of imine assembly, thus inducing a high CO2 capacity (1.27 mmol·g-1) from simulated flue gas at 75 °C. This dynamic imine assembly strategy endowed the dynamic covalent materials with facile preparation, low cost, excellent CO2 capacity, and outstanding cyclic stability, providing a mild and controllable approach for the development of competitive CO2 adsorbents.

A Qualitative Signature to Identify TERT Promoter Mutant High-Risk Tumors in Low-Grade Gliomas.

Background: Telomerase reverse transcriptase promoter (TERT-p) mutation has been frequently found, but associated with contrary prognosis, in both low-grade gliomas and glioblastomas. For the low-grade gliomas (Grades II-III), TERT-p mutant patients have a better prognosis than the wildtype patients, whereas for the GBMs (Grade IV), TERT-p mutation is related to a poor prognosis. We hypothesize that there exist high-risk patients in LGGs who share GBM-like molecular features, including TERT-p mutation, and need more intensive treatment than other LGGs. A molecular signature is needed to identify these high-risk patients for an accurate and timely treatment. Methods: Using the within-sample relative expression orderings of gene pairs, we identified the gene pairs with significantly stable REOs, respectively, in both the TERT-p mutant LGGs and GBMs but with opposite directions in the two groups. These reversely stable gene pairs were used as the molecular signature to stratify the LGGs into high-risk and low-risk groups. Results: A signature consisting of 21 gene pairs was developed, which can classify LGGs into two groups with significantly different overall survival. The high-risk group has a similar genetic mutation profile and a similar survival profile as GBMs, and these high-risk tumors may progress to a more malignant state. Conclusion: The 21 gene-pair signature based on REOs is capable of identifying high-risk patients in LGGs and guiding the clinical choice for appropriate and timely intervention.

Evaluating the Consistency of Gene Methylation in Liver Cancer Using Bisulfite Sequencing Data.

Bisulfite sequencing is considered as the gold standard approach for measuring DNA methylation, which acts as a pivotal part in regulating a variety of biological processes without changes in DNA sequences. In this study, we introduced the most prevalent methods for processing bisulfite sequencing data and evaluated the consistency of the data acquired from different measurements in liver cancer. Firstly, we introduced three commonly used bisulfite sequencing assays, i.e., reduced-representation bisulfite sequencing (RRBS), whole-genome bisulfite sequencing (WGBS), and targeted bisulfite sequencing (targeted BS). Next, we discussed the principles and compared different methods for alignment, quality assessment, methylation level scoring, and differentially methylated region identification. After that, we screened differential methylated genes in liver cancer through the three bisulfite sequencing assays and evaluated the consistency of their results. Ultimately, we compared bisulfite sequencing to 450 k beadchip and assessed the statistical similarity and functional association of differentially methylated genes (DMGs) among the four assays. Our results demonstrated that the DMGs measured by WGBS, RRBS, targeted BS and 450 k beadchip are consistently hypo-methylated in liver cancer with high functional similarity.

Nanoassembly and Multiscale Computation of Multifunctional Optical-Magnetic Nanoprobes for Tumor-Targeted Theranostics.

Gold nanorods, mesoporous silica, gadolinia, folic acid, and polyethylene glycol (PEG) derivatives have been investigated due to their own advantages in cancer theranostics. However, it remains a great challenge to assemble these components into a stable unity with the diverse and enhanced functionality for more potential applications. Herein, as inspired by the first-principles calculation, a highly stable and safe all-in-one nanoprobe is fabricated via a novel nanoassembly strategy. Multiscale calculations were performed to address the atomistic bonding of a nanoprobe, heat necrosis of a tumor adjacent to the vasculature, and thermal diffusion in a photothermal circumstance, respectively. The nanoprobe gains an 8-fold increase in magnetic resonance imaging (MRI) relaxivity compared to the clinical gadolinium diethylenetriaminepentaacetate, achieving a significant MRI signal in vivo. Conjugated with folate-PEG, the nanoprobe can be effectively absorbed by tumoral cells, obtaining a vivid two-photon cell imaging. A specific multisite scheme for photothermal therapy of a solid tumor is proposed to improve low photothermal efficacy caused by thermal diffusion in a large tumor, leading to the successful cure of the mice with xenograft tumor sized 10-12 mm. In vitro and in vivo toxicity, long-term excretion data, and the recovery of the treated mice demonstrate that the theranostic nanoprobe possesses good biocompatibility and metabolism efficacy.

Developments and Applications of Coil-Library-Based Residue-Specific Force Fields for Molecular Dynamics Simulations of Peptides and Proteins.

Molecular dynamics (MD) simulation has become a powerful tool for studying the structures and functional mechanisms of biomolecules, and its reliability crucially depends on the accuracy of underlying force fields. This perspective describes our recent efforts to develop more accurate protein force fields by improving the description of intrinsic conformational preferences of amino acid residues using residue-specific dihedral-angle-related parameters. Both backbone and side-chain conformational distributions and their coupling were optimized to fit those from a protein coil library. The resulting force fields RSFF1 and RSFF2 have been found to be more accurate than popular protein force fields, in reproducing experimental structural data of various peptides and proteins. They have also been successfully used in studying folding mechanisms and refinement of structure models. Further methodology developments related to intrinsically disordered proteins (RSFF2+) and a more universal implementation (RSFF2C) based on CMAP potentials are also described.

Ferroelectric Tunneling Junctions Based on Aluminum Oxide/ Zirconium-Doped Hafnium Oxide for Neuromorphic Computing.

Ferroelectric tunneling junctions (FTJs) with tunable tunneling electroresistance (TER) are promising for many emerging applications, including non-volatile memories and neurosynaptic computing. One of the key challenges in FTJs is the balance between the polarization value and the tunneling current. In order to achieve a sizable on-current, the thickness of the ferroelectric layer needs to be scaled down below 5 nm. However, the polarization in these ultra-thin ferroelectric layers is very small, which leads to a low tunneling electroresistance (TER) ratio. In this paper, we propose and demonstrate a new type of FTJ based on metal/Al2O3/Zr-doped HfO2/Si structure. The interfacial Al2O3 layer and silicon substrate enable sizable TERs even when the thickness of Zr-doped HfO2 (HZO) is above 10 nm. We found that F-N tunneling dominates at read voltages and that the polarization switching in HZO can alter the effective tunneling barrier height and tune the tunneling resistance. The FTJ synapses based on Al2O3/HZO stacks show symmetric potentiation/depression characteristics and widely tunable conductance. We also show that spike-timing-dependent plasticity (STDP) can be harnessed from HZO based FTJs. These novel FTJs will have high potential in non-volatile memories and neural network applications.