Characterizing dissolved organic matter and bacterial community interactions in a river network under anthropogenic landcover.

Anthropogenic landcover could rise nutrient concentrations and impact the characteristics and bioavailability of dissolved organic matter (DOM) in a river network. Exploring the interactions between DOM and microbials might be conducive to revealing biogeochemistry behaviors of organic matter. In this study, synchronous fluorescence spectra (SFS) with Gaussian band fitting and two-dimensional correlation spectroscopy (2D-COS) were employed to identify DOM fractions and reveal their interactions with bacterial communities. DOM was extracted from a river network under eco-agricultural rural (RUR), eco-residential urban (URB), eco-economical town (TOW), and eco-industrial park (IND) regions in Jiashan Plain of eastern China. The overlapping peaks observed in the SFS were successfully separated into four fractions using Gaussian band fitting, i.e., tyrosine-like fluorescence (TYLF), tryptophan-like fluorescence (TRLF), microbial humic-like fluorescence (MHLF), and fulvic-like fluorescence (FLF) materials. Across all four regions, TRLF (44.79% ± 7.74%) and TYLF (48.09% ± 8.85%) were the dominant components. Based on 2D-COS, variations of TYLF and TRLF were extremely larger than those of FLF in RUR-TOW. However, in URB-IND, the former exhibited lower variations compared to the latter. These suggested that FLF be likely derived continuously from lignin and other residue of terrestrial plant origin along the river network, and TYLF and TRLF be originated discontinuously from domestic wastewater in RUR-TOW. By high-throughput sequenced OTUs, the number of organisms in RUR-TOW could be higher than those in URB-IND, while genes associated with carbohydrate metabolism were lower in former than those in the latter. According to co-occurrence networks, microbes could promote the production of TYLF and TRLF in RUR-TOW. In contrast, microbial communities in URB-IND might contribute to decompose FLF. The obtained results could not only reveal interactions between DOM fractions and bacterial communities in the river network, but this methodology may be applied to other water bodies from different landscapes.

A Copper Silicate-Based Multifunctional Nanoplatform with Glutathione Depletion and Hypoxia Relief for Synergistic Photodynamic/Chemodynamic Therapy.

Chemodynamic therapy (CDT) alone cannot achieve sufficient therapeutic effects due to the excessive glutathione (GSH) and hypoxia in the tumor microenvironment (TME). Developing a novel strategy to improve efficiency is urgently needed. Herein, we prepared a copper silicate nanoplatform (CSNP) derived from colloidal silica. The Cu(II) in CSNP can be reduced to Cu(I), which cascades to induce a subsequent CDT process. Additionally, benefiting from GSH depletion and oxygen (O2) generation under 660 nm laser irradiation, CSNP exhibits both Fenton-like and hypoxia-alleviating activities, contributing to the effective generation of superoxide anion radical (•O2-) and hydroxyl radical (•OH) in the TME. Furthermore, given the suitable band-gap characteristic and excellent photochemical properties, CSNP can also serve as an efficient type-I photosensitizer for photodynamic therapy (PDT). The synergistic CDT/PDT activity of CSNP presents an efficient antitumor effect and biosecurity in both in vitro and in vivo experiments. The development of an all-in-one nanoplatform that integrates Fenton-like and photosensing properties could improve ROS production within tumors. This study highlights the potential of silicate nanomaterials in cancer treatment.

Enhancing Medical Signal Processing and Diagnosis with AI-Generated Content Techniques.

In medical diagnostics, the accurate classification and analysis of biomedical signals play a crucial role, particularly in the diagnosis of neurological disorders such as epilepsy. Electroencephalogram (EEG) signals, which represent the electrical activity of the brain, are fundamental in identifying epileptic seizures. However, challenges such as data scarcity and imbalance significantly hinder the development of robust diagnostic models. Addressing these challenges, in this paper, we explore enhancing medical signal processing and diagnosis, with a focus on epilepsy classification through EEG signals, by harnessing AI-generated content techniques. We introduce a novel framework that utilizes generative adversarial networks for the generation of synthetic EEG signals to augment existing datasets, thereby mitigating issues of data scarcity and imbalance. Furthermore, we incorporate an attention-based temporal convolutional network model to efficiently process and classify EEG signals by emphasizing salient features crucial for accurate diagnosis. Our comprehensive evaluation, including rigorous ablation studies, is conducted on the widely recognized Bonn Epilepsy Data. The results achieves an accuracy of 98.89% and F1 score of 98.91%. The findings demonstrate substantial improvements in epilepsy classification accuracy, showcasing the potential of AI-generated content in advancing the field of medical signal processing and diagnosis.

Silencing of long noncoding RNA X-inactive specific transcript alleviates Aß1-42-induced microglia-mediated neurotoxicity by shifting microglial M1/M2 polarization.

OBJECTIVES: This experimental study aims to investigate the role of long noncoding RNA X-inactive specific transcript (lncRNA XIST) in the microglial polarization and microglia-mediated neurotoxicity in Alzheimer's disease (AD). METHODS: The levels of XIST and microRNA-107 (miR-107) were detected by quantitative real-time polymerase chain reaction. The spatial learning and memory capability of APPswe/PS1dE9 (APP/PS1) mice were evaluated by the Morris water maze test. The morphology of mouse hippocampus cells was evaluated by hematoxylin and eosin staining. The Iba1-positive microglia were labeled by immunohistochemistry staining. The protein levels were determined by western blot and enzyme-linked immunosorbent assay. Neurotoxicity was evaluated by the terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling, caspase-3 activity, and Cell Counting Kit-8 assay. The XIST, miR-107, and AD targets were predicted by bioinformatics analysis. RESULTS: The level of XIST was increased in APP/PS1 mice, and XIST silencing ameliorated AD progression. XIST silencing suppressed microglia activation, microglial M1 polarization, and proinflammatory factor levels, but promoted microglial M2 polarization in APP/PS1 mice and Aß1-42-treated BV-2 cells. XIST knockdown reduced Aß1-42-induced microglia-mediated apoptosis and enhanced cell viability in HT22 cells. XIST silencing down-regulated miR-107 level and attenuated Aß1-42-caused suppression of the phosphatidylinositol 3-kinase (PI3K)/Akt signaling. Those effects of XIST silencing were attenuated by miR-107 inhibitor or LY294002. CONCLUSION: Downregulation of XIST lessened Aß1-42-induced microglia-mediated neurotoxicity by modulating microglial M1/M2 polarization, which may be mediated by the miR-107/PI3K/Akt pathway.

Iron Activates cGAS-STING Signaling and Promotes Hepatic Inflammation.

Iron deposition and chronic inflammation are associated with chronic liver diseases, such as alcoholic liver disease, nonalcoholic fatty liver disease, and chronic hepatitis B and C. However, the relationship between iron deposition and chronic inflammation in these diseases is still unclear. In the current study, we aimed to investigate the effect of iron on chronic inflammation in HepG2 cells and mice liver. We demonstrated that iron treatment enhanced the expression of cGAS, STING, and their downstream targets, including TBK1, IRF-3, and NF-κB in HepG2 cells and mice liver. We also found that treatment of HepG2 cells and mice with ferric ammonium citrate increased the expression of inflammatory cytokines, such as IFN-ß. Finally, we found that genes involved in iron metabolism and the STING signaling pathway were up-regulated in liver cancer tissues, and the survival time of patients with high expression of these genes in tumor tissues was significantly shortened. These results suggest that iron overload may promote the progress of the chronic liver disease by activating cGAS-STING-mediated chronic inflammation, which provides a new idea for the development of drugs for the treatment of the chronic liver disease.

[Determination of aminobutanol by high performance liquid chromatography based on charge transfer reaction].

A method was developed for the determination of the content of aminobutanol by high performance liquid chromatography (HPLC) based on charge transfer reaction. Under the condition of a borax-boric acid buffer solution of pH 8.4, aminobutanol and tetra-chloro-benzoquinone reacted at 60℃ for 60 min, and were analyzed by an HPLC-ultraviolet detector. The charge-transfer complex was separated on an Agilent Extend C18 column (250 mm×4.6 mm, 5 µm) with 0.001% (v/v) triethylamine and methanol as the mobile phases for gradient elution at a flow rate of 1 mL/min. The limit of quantification of aminobutanol was 0.01 g/L, the linear range was 0.1-0.6 g/L, and the correlation coefficient (R2) was 0.9994. The spiked recoveries of the method were 98.3%-103.6% with relative standard deviations (RSDs) of 0.9%-1.6%. The method is simple and quick, and suitable for the rapid detection of aminobutanol.