Publications by authors named "Runyu Miao"

The incidence of metabolic diseases-hypertension, diabetes, obesity, metabolic dysfunction-associated steatotic liver disease (MASLD), and atherosclerosis-is increasing annually, imposing a significant burden on both human health and the social economy. The occurrence and development of these diseases are closely related to the disruption of ion homeostasis, which is crucial for maintaining cellular functions and metabolic equilibrium. However, the specific mechanism of ion homeostasis in metabolic diseases is still unclear.

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The burgeoning field of microbiomics has unveiled significant insights into the role of the oral microbiome in the pathophysiology of Type 2 Diabetes Mellitus (T2DM), with this review focusing on recent advancements in diabetic oral microbiology, its clinical applications, and identifying factors that may affect study interpretations. A comprehensive review across various databases, including PubMed and Google Scholar, was conducted to collate original research data published in the past five years, specifically targeting studies exploring the impact of the oral microbiome on T2DM and emphasizing research that employs microbiomic approaches in clinical patient populations. The findings delineate the intricate interplay between T2DM and oral microbiome dysbiosis, highlighting significant microbial shifts following periodontal and antidiabetic treatments, and pointing to the complexity of the relationship between oral health and systemic disease.

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Diabetic vascular complications attract increased attention due to their high morbidity, mortality and disability rate. Comprehensive and in-depth exploration of the etiology and pathogenesis of diabetic vascular complications is important for diagnosis and treatment. Endothelial extracellular vesicles (EVs) serve as potential intercellular communicators, transmitting biological information from the donor cell to the recipient cell, exerting both harmful and beneficial effects on vascular function.

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This review examines the complexities of Type 2 Diabetes Mellitus (T2DM), focusing on the critical role of integrating omics technologies with traditional experimental methods. It underscores the advancements in understanding the genetic diversity of T2DM and emphasizes the evolution towards personalized treatment modalities. The paper analyzes a variety of omics approaches, including genomics, methylation, transcriptomics, proteomics, metabolomics, and intestinal microbiomics, delineating their substantial contributions to deciphering the multifaceted mechanisms underlying T2DM.

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Extensive case-control association studies have been conducted over the past few decades to investigate the relationship between MTHFR polymorphism and type 2 diabetes mellitus (T2DM) microangiopathy. However, the strength of the evidence and clinical significance are unclear. Consequently, a meta-analysis was performed to examine the correlations between two prevalent MTHFR single nucleotide polymorphisms, MTHFR C677T and A1298C, and T2DM microangiopathy.

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Objective: Gastrointestinal dysfunction are often associated with type 2 diabetes mellitus (T2DM), a complicated metabolic illness. Contributing factors have been proposed, including genetic predisposition, gene environmental, and lifestyle interactions, but the pathophysiology remains unknown.

Methods: We aim to explore the possible causes behind gastrointestinal dysfunction caused by type 2 diabetes in this study.

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Article Synopsis
  • The pKa value of a molecule is important in drug design as it affects ADMET properties and biological activity, but determining it experimentally can be complicated and time-consuming.
  • Existing pKa prediction methods often fall short due to limitations in training data and their ability to handle complex molecular features, which hampers their accuracy.
  • A new model, GR-pKa, uses a message-passing neural network and multi-fidelity learning to effectively predict pKa values, achieving significantly better accuracy than previous methods, as demonstrated by low error rates and high R2 values on the SAMPL7 dataset.
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Background: Diabetic foot complications impose a significant strain on healthcare systems worldwide, acting as a principal cause of morbidity and mortality in individuals with diabetes mellitus. While traditional methods in diagnosing and treating these conditions have faced limitations, the emergence of Machine Learning (ML) technologies heralds a new era, offering the promise of revolutionizing diabetic foot care through enhanced precision and tailored treatment strategies.

Objective: This review aims to explore the transformative impact of ML on managing diabetic foot complications, highlighting its potential to advance diagnostic accuracy and therapeutic approaches by leveraging developments in medical imaging, biomarker detection, and clinical biomechanics.

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Article Synopsis
  • * Understanding the cellular mechanisms behind diabetic endothelial cells is crucial for early diagnosis and effective treatment of these complications.
  • * Mitochondria are key players in maintaining endothelial cell health, and targeting mitochondrial issues presents a new avenue for therapy in diabetes-related vascular problems.
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Article Synopsis
  • * The review discusses the underlying mechanisms of these complications, protective strategies, and both current and emerging secondary prevention methods for T2DM patients.
  • * It emphasizes research conducted after 2020, evaluating solid evidence regarding the secondary prevention of macrovascular complications in T2DM, while also addressing research limitations and future research directions.
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Single-cell sequencing is a novel and rapidly advancing high-throughput technique that can be used to investigating genomics, transcriptomics, and epigenetics at a single-cell level. Currently, single-cell sequencing can not only be used to draw the pancreatic islet cells map and uncover the characteristics of cellular heterogeneity in type 2 diabetes, but can also be used to label and purify functional beta cells in pancreatic stem cells, improving stem cells and islet organoids therapies. In addition, this technology helps to analyze islet cell dedifferentiation and can be applied to the treatment of type 2 diabetes.

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The accurate prediction of binding free energy is a major challenge in structure-based drug design. Quantum mechanics (QM)-based approaches show promising potential in predicting ligand-protein binding affinity by accurately describing the behavior and structure of electrons. However, traditional QM calculations face computational limitations, hindering their practical application in drug design.

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Background: Migraine is a common and recurrent type of headache. Avoiding trigger factors is not often successful in reducing headache frequency, duration, and severity. Prophylactic medications may be effective but are limited by strict indications and daily medication intake.

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Background: Dietary soy protein (SP) is a potential intervention for protecting the kidneys and improving glucose and lipid metabolism. However, whether this effect is related to the percentage of SP intake remains unclear.

Objective: This study aims to review and analyze the results of randomized clinical trials (RCTs) in patients with type 2 diabetic nephropathy (T2DN) who received diets with different percentages of SP.

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Diabetes mellitus (DM) has become a surge burden worldwide owing to its high prevalence and range of associated complications such as coronary artery disease, blindness, stroke, and renal failure. Accordingly, the treatment and management of DM have become a research hotspot. Mulberry leaves ( L.

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On-chip electrostatic discharge (ESD) protection is required for all integrated circuits (ICs). Conventional on-chip ESD protection relies on in-Si PN junction-based device structures for ESD. However, such in-Si PN-based ESD protection solutions pose significant challenges related to ESD protection design overhead, including parasitic capacitance, leakage current, and noises, as well as large chip area consumption and difficulty in IC layout floor planning.

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Background: Diabetic gastroparesis (DGP) is a prevalent complication of diabetes that impairs people's quality of life and places a significant financial burden on them. The gastrointestinal symptoms of DGP patients can be improved by several Traditional Chinese Medicine (TCM) decoctions that have been shown to be effective in treating the disease. There are still many unanswered questions regarding the identification of appropriate therapeutic agents for the treatment of DGP in clinical practice.

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The maintenance of iron homeostasis is essential for proper endocrine function. A growing body of evidence suggests that iron imbalance is a key factor in the development of several endocrine diseases. Nowadays, ferroptosis, an iron-dependent form of regulated cell death, has become increasingly recognized as an important process to mediate the pathogenesis and progression of type 2 diabetes mellitus (T2DM).

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The pancreatic duodenum homeobox-1 () is a transcription factor encoded by a Hox-like homeodomain gene that plays a crucial role in pancreatic development, β-cell differentiation, and the maintenance of mature β-cell functions. Research on the relationship between and diabetes has gained much attention because of the increasing prevalence of diabetes melitus (DM). Recent studies have shown that the overexpression of regulates pancreatic development and promotes β-cell differentiation and insulin secretion.

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Glycolipid metabolism disorder are major threats to human health and life. Genetic, environmental, psychological, cellular, and molecular factors contribute to their pathogenesis. Several studies demonstrated that neuroendocrine axis dysfunction, insulin resistance, oxidative stress, chronic inflammatory response, and gut microbiota dysbiosis are core pathological links associated with it.

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Article Synopsis
  • Traditional Chinese medicine (TCM) is commonly used in China as a supplementary treatment for diabetes mellitus and angina, showing promising results in regulating glucose and lipid metabolism.
  • The study highlights TCM's potential benefits for patients with both diabetes and coronary heart disease (CHD), improving cardiac function, reducing inflammation, and lowering the risk of angina and cardiovascular events.
  • However, further rigorous randomized controlled trials and long-term studies are necessary to validate these findings and fully understand TCM's role in this context.
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Berberine is a natural active ingredient extracted from the rhizome of , which interacts with multiple intracellular targets and exhibits a wide range of pharmacological activities. Previous studies have preliminarily confirmed that the regulation of mitochondrial activity is related to various pharmacological actions of berberine, such as regulating blood sugar and lipid and inhibiting tumor progression. However, the mechanism of berberine's regulation of mitochondrial activity remains to be further studied.

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As the demands for improved performance of integrated circuit (IC) chips continue to increase, while technology scaling driven by Moore's law is becoming extremely challenging, if not impractical or impossible, heterogeneous integration (HI) emerges as an attractive pathway to further enhance performance of Si-based complementary metal-oxide-semiconductor (CMOS) chips. The underlying basis for using HI technologies and structures is that IC performance goes well beyond classic logic functions; rather, functionalities and complexity of smart chips span across the full information chain, including signal sensing, conditioning, processing, storage, computing, communication, control, and actuation, which are required to facilitate comprehensive human-world interactions. Therefore, HI technologies can bring in more function diversifications to make system chips smarter within acceptable design constraints, including costs.

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Glucose and lipid metabolism disturbances has become the third major disease after cancer and cardio-cerebrovascular diseases. Emerging evidence shows that berberine can effectively intervene glucose and lipid metabolism disturbances, but the underlying mechanisms of this remain unclear. To investigate this issue, we performed metagenomic and metabolomic analysis in a group of normal mice (the NC group), mice with disturbances in glucose and lipid metabolism (the MC group) and mice with disturbances in glucose and lipid metabolism after berberine intervention (the BER group).

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The serine/threonine kinase Akt, also known as protein kinase B (PKB), is one of the key factors regulating glucose and lipid energy metabolism, and is the core focus of current research on diabetes and metabolic diseases. Akt is mostly expressed in key metabolism-related organs and it is activated in response to various stimuli, including cell stress, cell movement, and various hormones and drugs that affect cell metabolism. Genetic and pharmacological studies have shown that Akt is necessary to maintain the steady state of glucose and lipid metabolism and a variety of cellular responses.

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