Publications by authors named "Ruiling Zu"

This study investigates platelet-related subtypes in non-small cell lung cancer (NSCLC) and seeks to identify genes associated with prognosis, focusing on the clinical significance of the chloride ion channel gene BEST3. We utilised sequencing and clinical data from GEO, TCGA and the Xena platform, building a risk model based on genetic features. TCGA and GSE37745 served as training cohorts, while GSE50081, GSE13213, GSE30129 and GSE42127 were validation cohorts.

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Background: Small cell lung cancer (SCLC) is characterized by high invasion rates, rapid progression, and poor prognoses. Thus, identifying SCLC patients at high risk of progression and death is critical to improve long-term survival. In this study, the aspartate transaminase-to-albumin ratio (ATAR) was examined as a prognostic factor for SCLC patients.

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Objectives: This study aimed to evaluate the prognostic significance of postoperative Creatine Kinase type M and B (CK-MB) to total Creatine Kinase (CK) ratio (CK-MB/CK) in colorectal cancer (CRC) patients after radical resection.

Methods: This was a single-center retrospective cohort analysis. Subjects were stage I-III CRC patients hospitalized in Sichuan Cancer Hospital from January 2017 to May 2021.

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It has been proved that Raman spectral intensities could be used to diagnose lung cancer patients. However, the application of Raman spectroscopy in identifying the patients with pulmonary nodules was barely studied. In this study, we revealed that Raman spectra of serum samples from healthy participants and patients with benign and malignant pulmonary nodules were significantly different.

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Oxidative stress (OS) is a chemical imbalance between an oxidant and an antioxidant, causing damage to redox signaling and control or causing molecular damage. Unbalanced oxidative metabolism can produce excessive reactive oxygen species (ROS). These excess ROS can cause drastic changes in platelet metabolism and further affect platelet function.

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Tumor-educated platelets (TEPs) have been widely reported to have promising application potential; nonetheless, platelet isolation from peripheral blood is an important but neglected step in TEPs research for platelet-based liquid biopsy. In this article, we discussed some common influence factors for platelet isolation. To investigate the factors involved in platelet isolation, a prospective multicenter study was conducted on healthy Han Chinese adults (18 to 79 years of age).

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Esophageal squamous cell cancer (ESCC) is a disease with a male predominance. Accordingly, the applicability of prognostic indicators values previously set for the general population with ESCC has not been reported for determining the physical state in females. Patients with ESCC were pooled from 2009 to 2017 at Sichuan Cancer Hospital.

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The recent global focus on big data in medicine has been associated with the rise of artificial intelligence (AI) in diagnosis and decision-making following recent advances in computer technology. Up to now, AI has been applied to various aspects of medicine, including disease diagnosis, surveillance, treatment, predicting future risk, targeted interventions and understanding of the disease. There have been plenty of successful examples in medicine of using big data, such as radiology and pathology, ophthalmology cardiology and surgery.

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Gram-negative bacteremia (GNB) is a common complication in malignant patients. Identifying risk factors and developing a prognostic model for GNB might improve the survival rate. In this observational and real-world study, we retrospectively analyzed the risk factors and outcomes of GNB in malignant patients.

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Many studies in recent years have demonstrated that some messenger RNA (mRNA) in platelets can be used as biomarkers for the diagnosis of pan-cancer. The quantitative real-time polymerase chain reaction (RT-qPCR) molecular technique is most commonly used to determine mRNA expression changes in platelets. Accurate and reliable relative RT-qPCR is highly dependent on reliable reference genes.

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As the pulmonary nodules were hard to be discriminated as benignancy or malignancy only based on imageology, a prospective and observational real-world research was devoted to develop and validate a predictive model for managing the diagnostic challenge. This study started in 2018, and a predictive model was constructed using eXtreme Gradient Boosting (XGBoost) based on computed tomographic, clinical, and platelet data of all the eligible patients. And the model was evaluated and compared with other common models using ROC curves, continuous net reclassification improvement (NRI), integrated discrimination improvement (IDI), and net benefit (NB).

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Hepatocellular carcinoma (HCC) ranks third in the cause of death due to cancer. Circular RNA circSEC24 Homolog A (circSEC24A) has been uncovered to be upregulated in liver cancer. However, the function of circSEC24A in HCC is indistinct.

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The emergence of resistant has made clinical fluconazole (FLC) treatment difficult. Improving sensitivity to FLC is an effective way to treat resistant isolates. Berberine hydrochloride (BBH) is a commonly used traditional Chinese medicine with antimicrobial effects, especially in resistant isolates.

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Article Synopsis
  • The study aimed to evaluate whether specific platelet features in blood and platelet-rich plasma could create a diagnostic model for lung and colon cancer, as well as differentiate between lung malignancies and benign conditions.
  • The research involved 245 participants, categorizing them into training and testing cohorts, where various platelet features were analyzed and a receiver operator characteristic (ROC) curve was used to assess the model's accuracy.
  • Results showed that the diagnostic model effectively distinguished lung cancer and colon cancer from healthy individuals, with notable accuracy rates (AUC up to 0.92), and also had potential in distinguishing malignant lung conditions from benign ones.
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