Yeast ß-glucan attenuates dextran sulfate sodium-induced colitis: Involvement of gut microbiota and short-chain fatty acids.

Yeast ß-glucan intervention offers a promising strategy for managing colitis; however, the mechanisms remain unknown. In the present work, the protective effects of yeast ß-glucan on DSS-induced colitis in mice was evaluated, focusing on its interaction with gut microbiota. The result showed yeast ß-glucan significantly alleviated colitis symptoms, evidenced by reduced weight loss, lower disease activity index (DAI) scores, and minimized intestinal damage. It enhanced intestinal barrier integrity via upregulation of tight junction proteins, suppressed lipopolysaccharide (LPS) release, and decreased pro-inflammatory cytokines production. Additionally, yeast ß-glucan boosted short-chain fatty acids (SCFAs) production, and activated their receptors, increased the relative abundances of beneficial microbes like Lactobacillus and Lachnospiraceae_UCG-006. Transcriptomic analyses suggest that yeast ß-glucan mitigates inflammation by downregulating gene expression related to IL-17 pathway. Our findings highlight potential of yeast ß-glucan as a therapeutic agent for colitis through modulation of gut microbiota and inflammatory responses.

Polyphenol-based polymer nanoparticles for inhibiting amyloid protein aggregation: recent advances and perspectives.

Polyphenols are a group of naturally occurring compounds that possess a range of biological properties capable of potentially mitigating or preventing the progression of age-related cognitive decline and Alzheimer's disease (AD). AD is a chronic neurodegenerative disease known as one of the fast-growing diseases, especially in the elderly population. Moreover, as the primary etiology of dementia, it poses challenges for both familial and societal structures, while also imposing a significant economic strain. There is currently no pharmacological intervention that has demonstrated efficacy in treating AD. While polyphenols have exhibited potential in inhibiting the pathological hallmarks of AD, their limited bioavailability poses a significant challenge in their therapeutic application. Furthermore, in order to address the therapeutic constraints, several polymer nanoparticles are being explored as improved therapeutic delivery systems to optimize the pharmacokinetic characteristics of polyphenols. Polymer nanoparticles have demonstrated advantageous characteristics in facilitating the delivery of polyphenols across the blood-brain barrier, resulting in their efficient distribution within the brain. This review focuses on amyloid-related diseases and the role of polyphenols in them, in addition to discussing the anti-amyloid effects and applications of polyphenol-based polymer nanoparticles.

From Wilson's Disease to Neurodevelopmental Disorder with Involuntary Movements, Different Genetic Interpretations in a Female Patient.

BACKGROUND: A 19-year-old female patient presented at 2 years of age with dysarthria, incoherent speech, and unsteady ambulation. She is prone to leaning backward when walking and has involuntary movements of the whole body. Besides, she has poor numeracy skills. She has been diagnosed with Wilson's disease (WD) in China and Japan. OBJECTIVE: The objective of this study was to further clarify the diagnosis of this patient. METHODS: The patient and her parents were detected with whole-exome sequencing. RESULTS: Based on the genetic test results, genetic analyses, and clinical manifestations, a diagnosis of WD in this patient was ruled out. The patient was eventually diagnosed with neurodevelopmental disorder with involuntary movements. CONCLUSIONS: This study reinterprets the genetic test results of a young female patient and leads to reflections on the genetic diagnostic criteria for WD: the Leipzig score is suitable for the diagnosis of most WD patients, and the genetic testing section of the score is of great diagnostic value. However, in some special cases, the proband and their first-degree relatives should further complete cosegregation analysis to determine the origin of the lesion gene and to verify the reliability of the genetic test. In addition, this study suggests that further improving the scoring rules of the gene testing part of the Leipzig scoring system may be more helpful in achieving an accurate diagnosis of WD. © 2024 International Parkinson and Movement Disorder Society.

Decoding Wilson disease: a machine learning approach to predict neurological symptoms.

Objectives: Wilson disease (WD) is a rare autosomal recessive disorder caused by a mutation in the ATP7B gene. Neurological symptoms are one of the most common symptoms of WD. This study aims to construct a model that can predict the occurrence of neurological symptoms by combining clinical multidimensional indicators with machine learning methods. Methods: The study population consisted of WD patients who received treatment at the First Affiliated Hospital of Anhui University of Traditional Chinese Medicine from July 2021 to September 2023 and had a Leipzig score ≥ 4 points. Indicators such as general clinical information, imaging, blood and urine tests, and clinical scale measurements were collected from patients, and machine learning methods were employed to construct a prediction model for neurological symptoms. Additionally, the SHAP method was utilized to analyze clinical information to determine which indicators are associated with neurological symptoms. Results: In this study, 185 patients with WD (of whom 163 had neurological symptoms) were analyzed. It was found that using the eXtreme Gradient Boosting (XGB) to predict achieved good performance, with an MCC value of 0.556, ACC value of 0.929, AUROC value of 0.835, and AUPRC value of 0.975. Brainstem damage, blood creatinine (Cr), age, indirect bilirubin (IBIL), and ceruloplasmin (CP) were the top five important predictors. Meanwhile, the presence of brainstem damage and the higher the values of Cr, Age, and IBIL, the more likely neurological symptoms were to occur, while the lower the CP value, the more likely neurological symptoms were to occur. Conclusions: To sum up, the prediction model constructed using machine learning methods to predict WD cirrhosis has high accuracy. The most important indicators in the prediction model were brainstem damage, Cr, age, IBIL, and CP. It provides assistance for clinical decision-making.

Structure-Controllable and Mass-Produced Glycopolymersomes as a Template of the Carbohydrate@Ag Nanobiohybrid with Inherent Antibacteria and Biofilm Eradication.

Glycopolymer-supported silver nanoparticles (AgNPs) have demonstrated a promising alternative to antibiotics for the treatment of multidrug-resistant bacteria-infected diseases. In this contribution, we report a class of biohybrid glycopolymersome-supported AgNPs, which are capable of effectively killing multidrug-resistant bacteria and disrupting related biofilms. First of all, glycopolymersomes with controllable structures were massively fabricated through reversible addition-fragmentation chain transfer (RAFT) polymerization-induced self-assembly (PISA) in an aqueous solution driven by complementary hydrogen bonding interaction between the pyridine and amide groups of N-(2-methylpyridine)-acrylamide (MPA) monomers. Subsequently, Ag+ captured by glycopolymersomes through the coordination between pyridine-N and Ag+ was reduced into AgNPs stabilized by glycopolymersomes upon addition of the NaBH4 reducing agent, leading to the formation of the glycopolymersome@AgNPs biohybrid. As a result, they showed a wide-spectrum and enhanced removal of multidrug-resistant bacteria and biofilms compared to naked AgNPs due to the easier adhesion onto the bacterial surface and diffusion into biofilms through the specific protein-carbohydrate recognition. Moreover, the in vivo results revealed that the obtained biohybrid glycopolymersomes not only demonstrated an effective treatment for inhibiting the cariogenic bacteria but also were able to repair the demineralization of caries via accumulating Ca2+ through the recognition between carbohydrates and Ca2+. Furthermore, glycopolymersomes@AgNPs showed quite low in vitro hemolysis and cytotoxicity and almost negligible acute toxicity in vivo. Overall, this type of biohybrid glycopolymersome@AgNPs nanomaterial provides a new avenue for enhanced antibacterial and antibiofilm activities and the effective treatment of oral microbial-infected diseases.

Correction: Fang et al. Gandouling Mitigates CuSO4-Induced Heart Injury in Rats. Animals 2022, 12, 2703.

In the original publication [...].

Gandouling Mitigates CuSO4-Induced Heart Injury in Rats.

We assessed the protective effects of Gandouling (GDL) on copper sulfate (CuSO4)-induced heart injuries in Sprague−Dawley rats, which were randomly divided into the control, CuSO4, GDL + CuSO4 and penicillamine + CuSO4 groups. The rats received intragastric GDL (400 mg/kg body weight) once per day for 42 consecutive days after 56 days of CuSO4 exposure, and penicillamine was used as a positive control. The levels of plasma inflammatory cytokines (IMA, hFABP, cTn-I and BNP) were determined using the enzyme-linked immunosorbent assay. The histopathological symptoms were evaluated using hematoxylin and eosin staining and transmission electron microscopy. To determine the underlying mechanism, Western blotting was conducted for the detection of the heme oxygenase 1 (HO-1) expression. The results revealed that GDL supplementation alleviated the histopathological symptoms of the rat heart tissue, promoted Cu excretion to attenuate impairment, and significantly decreased inflammatory cytokine levels in the plasma (p < 0.01). In addition, GDL increased the HO-1 expression in the rat hepatic tissue. The protective effect of GDL on the heart was superior to that of penicillamine. Overall, these findings indicate that GDL alleviates hepatic heart injury after a Cu overaccumulation challenge, and GDL supplements can be beneficial for patients with Wilson's disease.