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Effect of complex probiotics on gastrointestinal and behavioral problems in children with autism spectrum disorder based on trace elements and vitamin A/D

开始日期2024-03-15

申办/合作机构

齐齐哈尔医学院

NCT04215549

/ WithdrawnN/AIIT

The Cost of Obsessive-compulsive Disorder (OCD) in China: Multi-center Cross-sectional Survey Based on Hospital

The purpose of this study is to estimate the cost of obsessive-compulsive disorder in China based on the prevalence rate from a social perspective.

开始日期2020-01-02

申办/合作机构

上海市精神卫生中心（上海市心理咨询培训中心）

[+6]

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2025-12-01·Human & Experimental Toxicology

Integrated gut microbiota and serum metabolomics reveal glyphosate-induced hepatic injury in mice

Article

作者: Qi, Yanbo ; Li, Gang ; Cheng, Yu ; Yang, Xiaolei ; Liu, Jicheng ; Chao, Hong ; Qi, Lei ; Chai, Zijun ; Mu, Zhihui ; Li, Hongjie

IntroductionGlyphosate (GLP) is one of the most widely used herbicides in the world. However, its underlying effects on the liver remain unclear. This study aims to investigate the toxic effects and the gut microbiome– and serum metabolite–related mechanisms of GLP on the liver in mice.Methods16S rDNA sequencing and UPLC-Q-TOF-MS/MS were used to investigate the mechanisms of GLP toxicity in mice administered with 0, 50, 250 and 500 mg/kg/day GLP for 30 days.ResultsGLP induced hepatocyte edema and ballooning as well as inflammatory cell infiltration. Exposure to GLP resulted in increased levels of serum ALT, TBIL, DBIL, and GLU. Microbiota analysis at the phylum level demonstrated that the proportions of Patescibacteria decreased in the GLP-treated group. The genus-level analysis identified 11 different genera, with eight decreased and three increased in the GLP-exposed group. Metabolomics analysis of serum showed 42 differential metabolites between the GLP and control groups. The metabolic pathway enrichment analysis revealed that the pentose phosphate pathway (PPP) and pyrimidine metabolism were significantly activated. Spearman analysis showed that the changes in the differential metabolites of the PPP and pyrimidine metabolism and gut microbiota were strongly associated with the biochemical index.DiscussionIn conclusion, GLP exposure induces hepatic injury through alterations in the gut microbiome and metabolic pathways, particularly by activating the pentose phosphate pathway and pyrimidine metabolism.

2025-06-01·Industrial Crops and Products

Simultaneous obtaining hydrophilic and hydrophobic compounds by ultrasonic synergistic extraction technology: The molecular mechanism of extraction and the multiple effects of macroporous adsorption resin

作者: Yang, Xinyu ; Cao, Shuo ; Yang, Ying ; Meng, Yue ; Pan, Xu ; Sui, Xiaoyu ; Liu, Tingting ; Zhang, Honglian

This study used ultrasonic synergistic extraction deep eutectic solvents (DES) technol. to extract polysaccharides and flavonoids from A. membranaceus.Based on a comprehensive consideration of the yield of Astragalus polysaccharides (APS) and flavonoids, the best DES (choline chloride: oxalic acid = 1: 2) was selected from 16 different DES.The binding energy between the solvent and the target mol. was calculated using the d. functional theory (DFT) in order to explore the mol. mechanism of DES for simultaneously extracting compounds with varying polarity.The results showed that the number of hydrogen bonds formed between the selected DES and glucose and calycosin-7-glucoside mols. was higher than that of the traditional solvents used for extracting these two substances.The adsorption capacity of 10 different types of macroporous adsorption resins for polysaccharides and flavonoids in the DES system was studied.Among them, HP-20 macroporous adsorption resin had better adsorption and desorption effects on flavonoids but almost no adsorption effect on polysaccharides.A pseudosecond-order kinetic equation is more suitable for fitting the adsorption characteristics of macroporous adsorption resins for flavonoids.At the same temperature, the Freundlich isotherm model is more suitable for fitting the adsorption behavior of HP-20 macroporous adsorption resin towards flavonoids.The adsorption thermodn. parameters indicate that flavonoids are phys. adsorbed on HP-20 macroporous adsorption resin in a spontaneous, endothermic, and entropy-increasing manner, and a high temperature is more suitable for the occurrence of adsorption behavior.In this study, polysaccharides and flavonoids were simultaneously extracted by green solvent, which provided enlightenment for the sustainable utilization of A. membranaceus resources.

2025-05-01·Annals of Nuclear Medicine

Deep learning in nuclear medicine: from imaging to therapy

Review

作者: Liu, Peng-Fei ; Ji, Xin-Ying ; Su, Pei-Gen ; Wang, Da-Yong ; Zhang, Meng-Xin ; Shang, He-Shan ; Zhu, Jiang-Tao ; Liao, Qi-Ming ; Zhang, Meng-Di

BACKGROUNDDeep learning, a leading technology in artificial intelligence (AI), has shown remarkable potential in revolutionizing nuclear medicine.OBJECTIVEThis review presents recent advancements in deep learning applications, particularly in nuclear medicine imaging, lesion detection, and radiopharmaceutical therapy.RESULTSLeveraging various neural network architectures, deep learning has significantly enhanced the accuracy of image reconstruction, lesion segmentation, and diagnosis, improving the efficiency of disease detection and treatment planning. The integration of deep learning with functional imaging techniques such as positron emission tomography (PET) and single-photon emission computed tomography (SPECT) enable more precise diagnostics, while facilitating the development of personalized treatment strategies. Despite its promising outlook, there are still some limitations and challenges, particularly in model interpretability, generalization across diverse datasets, multimodal data fusion, and the ethical and legal issues faced in its application.CONCLUSIONAs technological advancements continue, deep learning is poised to drive substantial changes in nuclear medicine, particularly in the areas of precision healthcare, real-time treatment monitoring, and clinical decision-making. Future research will likely focus on overcoming these challenges and further enhancing model transparency, thus improving clinical applicability.

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