Publications by authors named "Xing Zhe"

To evaluate the drug release, cytocompatibility with periodontal ligament cells (PDLCs), and therapeutic efficacy of GelMA hydrogel loaded with resolvin D1 (RvD1) in treating rat periodontal inflammation and alveolar bone damage. An RvD1 complexed with GelMA was prepared, and its release kinetics and compatibility with PDLCs were assessed. Rats with induced periodontitis were treated weekly with topical applications of vehicle, GelMA, RvD1, or RvD1 complexed with GelMA for four weeks.

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To assess the environmental status of an abandoned aquaculture and breeding area in the northeast coast of the Hainan Island, surface and well water, sediment and surface soils were sampled and analyzed for conventional physicochemical properties, heavy metals and antibiotics. Metagenome tests were also conducted to determine the composition and diversity of the microbial community in typical habitats. Affected by the discharge of wastewater from higher-place pond aquaculture, coastal freshwater rivers have undergone significant salinization, Cl and Na were as high as 4.

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In the realm of wearable technology, strategically placing sensors at various body locations enhances the detection of diverse physiological indicators crucial for remote medical care. However, current devices often focus on a single body part for specific physical parameters, which hinders the seamless integration of sensors across multiple body parts and necessitates redesign for new detection capabilities. Here, we propose a modular, reconfigurable circuit assembly method that can be adaptable for multiple body locations to construct the body net.

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Group 3 innate lymphoid cells (ILC3s) are essential for both pathogen defense and tissue homeostasis in the intestine. Dysfunction of ILC3s could lead to increased susceptibility to intestinal inflammation. However, the precise mechanisms governing the maintenance of intestinal ILC3s are yet to be fully elucidated.

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Group 3 innate lymphoid cells (ILC3s) play key roles in intestinal inflammation. Olfactomedin 4 (OLFM4) is highly expressed in the colon and has a potential role in dextran sodium sulfate-induced colitis. However, the detailed mechanisms underlying the effects of OLFM4 on ILC3-mediated colitis remain unclear.

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Objective: This study aimed to explore the electroencephalogram (EEG) indicators and clinical factors that may lead to poor prognosis in patients with prolonged disorder of consciousness (pDOC), and establish and verify a clinical predictive model based on these factors.

Methods: This study included 134 patients suffering from prolonged disorder of consciousness enrolled in our department of neurosurgery. We collected the data of sex, age, etiology, coma recovery scales (CRS-R) score, complications, blood routine, liver function, coagulation and other laboratory tests, resting EEG data and follow-up after discharge.

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Epigenetic dysregulation drives aberrant transcriptional programs playing a critical role in hepatocellular carcinoma (HCC), which may provide novel insights into the heterogeneity of HCC. This study performed an integrated exploration on the epigenetic dysregulation of miRNA and methylation. We discovered and validated three patterns endowed with gene-related transcriptional traits and clinical outcomes.

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Aims: In an era of evolving diagnostic possibilities, existing diagnostic systems are not fully sufficient to promptly recognize patients with early-stage hypertrophic cardiomyopathy (HCM) without symptomatic and instrumental features. Considering the sudden death of HCM, developing a novel diagnostic model to clarify the patients with early-stage HCM and the immunological characteristics can avoid misdiagnosis and attenuate disease progression.

Methods And Results: Three hundred eighty-five samples from four independent cohorts were systematically retrieved.

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Background: Recently, long non-coding RNAs (lncRNAs) have been demonstrated as essential roles in tumor immune microenvironments (TIME). Nevertheless, researches on the clinical significance of TIME-related lncRNAs are limited in lung adenocarcinoma (LUAD).

Methods: Single-cell RNA sequencing and bulk RNA sequencing data are integrated to identify TIME-related lncRNAs.

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The intricate crosstalk of various cell death forms was recently implicated in cancers, laying a foundation for exploring the association between cell death and cancers. Recent evidence has demonstrated that biological networks outperform snapshot gene expression profiles at discovering promising biomarkers or heterogenous molecular subtypes across different cancer types. In order to investigate the behavioral patterns of cell death-related interaction perturbation in colorectal cancer (CRC), this study constructed the interaction-perturbation network with 11 cell death pathways and delineated four cell death network (CDN) derived heterogeneous subtypes (CDN1-4) with distinct molecular characteristics and clinical outcomes.

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In recent years, wearable sensors have revolutionized health monitoring by enabling continuous, real-time tracking of human health and performance. These noninvasive devices are usually designed to monitor human physical state and biochemical markers. However, enhancing their functionalities often demands intricate customization by designers and additional expenses for users.

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Approximately 10-15% of stage II and 25-30% of stage III colorectal cancer (CRC) patients experience recurrence within 5 years after surgery, and existing taxonomies are insufficient to meet the needs of clinical precision treatment. Thus, robust biomarkers and precise management were urgently required to stratify stage II and III CRC and identify potential patients who will benefit from postoperative adjuvant therapy. Alongside, interactions of ligand-receptor pairs point to an emerging direction in tumor signaling with far-reaching implications for CRC, while their impact on tumor subtyping has not been elucidated.

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Most gastric cancer (GC) subtypes are identified through transcriptional profiling overlooking dynamic changes and interactions in gene expression. Based on the background network of global immune genes, we constructed sample-specific edge-perturbation matrices and identified four molecular network subtypes of GC (MNG). MNG-1 displayed the best prognosis and vigorous cell cycle activity.

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Background: Long noncoding RNAs (lncRNAs) have been reported to play an important role in tumor immune modification. Nonetheless, the clinical implication of immune-associated lncRNAs in renal cell carcinoma (RCC) remains to be further explored.

Methods: 76 combinations of machine learning algorithms were integrated to develop and validate a machine learning-derived immune-related lncRNA signature (MDILS) in five independent cohorts (n = 801).

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The primary goal of bone tissue engineering is to fabricate scaffolds that can provide a microenvironment similar to that of natural bone. Therefore, various scaffolds have been designed to replicate the bone structure. Although most tissues exhibit complicated structures, their basic structural unit includes stiff platelets arranged in a staggered micro-array.

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Suppressor of cytokine signalling (SOCS) 1/2/3/4 are involved in the occurrence and progression of multiple malignancies; however, their prognostic and developmental value in patients with glioblastoma (GBM) remains unclear. The present study used TCGA, ONCOMINE, SangerBox3.0, UALCAN, TIMER2.

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Article Synopsis
  • The updated guidelines emphasize the importance of gene expression-based multigene panels for assessing overall survival and enhancing treatment strategies for lung adenocarcinoma (LUAD) patients, though challenges in clinical utility remain due to limited data and validation issues.
  • A study analyzing 2,330 LUAD samples applied various machine learning algorithms to create a robust genome-wide expression signature (RGS), which was found to independently predict patient risk and survival outcomes.
  • The findings suggest that RGS can help identify high-risk patients and tailor therapies, as specific drugs like alisertib and RITA were linked to the corresponding risk groups, potentially improving clinical outcomes.
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Background: Gastric cancer (GC) is one of the most common malignant tumors of the digestive tract which seriously endangers the health of human beings worldwide. Transcriptomic deregulation by epigenetic mechanisms plays a crucial role in the heterogeneous progression of GC. This study aimed to investigate the impact of epigenetically regulated genes on the prognosis, immune microenvironment, and potential treatment of GC.

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Background: CD276 (also known as B7-H3) is one of the most important immune checkpoints of the CD28 and B7 superfamily, and its abnormal expression is closely associated with various types of cancer. It has been shown that CD276 is able to inhibit the function of T cells, and that this gene may potentially be a promising immunotherapy target for different types of cancer.

Methods: Since few systematic studies have been published on the role of CD276 in cancer to date, the present study has employed single-cell sequencing and bioinformatics methods to analyze the expression patterns, clinical significance, prognostic value, epigenetic alterations, DNA methylation level, tumor immune cell infiltration and immune functions of CD276 in different types of cancer.

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Article Synopsis
  • - The text presents a new approach to classifying colorectal cancer (CRC) using gene interaction networks, leading to the identification of six distinct molecular subtypes (GINS1-6) that reflect different tumor characteristics and behaviors.
  • - Each subtype has unique features: GINS1 is proliferative with high tumor purity but resistant to immunotherapy; GINS2 is stromal-rich with high recurrence potential; GINS3 is characterized by activation of specific receptors; GINS4 shows mixed activity; GINS5 is immune-activated with favorable outcomes; and GINS6 has metabolic traits.
  • - The study suggests that this refined classification offers insights into CRC management, potentially leading to more tailored treatment strategies based on the specific subtype of cancer.*
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Article Synopsis
  • Pancreatic cancer (PACA) remains one of the most aggressive tumors with little progress in treatment outcomes over the past decade, highlighting the need for better prognostic tools.
  • Researchers developed an artificial intelligence-derived prognostic signature (AIDPS) using data from 1,280 patients, which demonstrated superior predictive abilities compared to existing methods and could classify patient prognosis accurately across various cohorts.
  • The AIDPS also revealed critical insights into patient outcomes, with low scores indicating poor prognosis and potential immunotherapy sensitivity, while high scores were associated with longer survival, suggesting the tool's utility in personalized treatment strategies.
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  • Researchers developed a consensus artificial intelligence-derived gene signature (AIGS) using large-scale data to better predict outcomes in bladder cancer (BLCA) patients, showing that a high AIGS score correlates with increased risks of mortality and disease progression.
  • AIGS proved to be superior to traditional clinical traits and molecular markers in predicting patient outcomes, and when combined with AJCC stage, it offered enhanced performance in risk assessments.
  • Low AIGS scores indicated sensitivity to immunotherapy, while high scores pointed towards specific potential treatments; the study also identified genetic and molecular changes associated with AIGS, establishing it as a valuable tool for personalized patient management in BLCA.
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Article Synopsis
  • - The study highlights that while immunotherapy has improved melanoma survival rates, challenges like tumor heterogeneity and drug resistance still exist, limiting further benefits.
  • - Researchers developed a machine learning-based prognostic signature (MLPS) from 1002 melanoma samples, demonstrating superior predictive power for patient survival compared to existing clinical traits and signatures.
  • - MLPS effectively identifies two patient groups: those with better outcomes who may respond well to immunotherapy and those with poorer outcomes who are more likely to benefit from BRAF inhibitors like dabrafenib.
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