Publications by authors named "Yijia Lin"

The N6-methyladenosine (m6A) modification serves as an essential epigenetic regulator in eukaryotic cells, playing a significant role in tumorigenesis and cancer progression. However, the detailed biological functions and underlying mechanisms of m6A regulation in gastric cancer (GC) are poorly understood. Our research revealed that the m6A demethylase ALKBH5 was markedly downregulated in GC tissues, which was associated with poor patient prognosis.

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Older adults with cognitive frailty often have impaired dual-task walking and prefrontal cortex (PFC) activation. Combining cycling with interactive boxing offers an innovative and interesting dual-task training to challenge both physical and cognitive skills. This study investigated the effects of interactive boxing-cycling on this population.

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Diabetic encephalopathy (DE), a neurological complication of diabetes mellitus, has an unclear etiology. Shreds of evidence show that the nucleotide-binding oligomerization domain-like receptor family protein 3 (NLRP3) inflammasome-induced neuroinflammation and transcription factor EB (TFEB)-mediated autophagy impairment may take part in DE development. The cross talk between these two pathways and their contribution to DE remains to be explored.

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Article Synopsis
  • HER2 assessment is crucial for selecting patients for anti-HER2 treatments, but manually analyzing HER2 amplification is time-consuming and prone to errors due to subjective interpretations and complex cell imagery.
  • To overcome these challenges, a new deep learning model has been developed that can accurately quantify HER2 amplification status in breast cancer by analyzing FISH and DISH datasets, achieving high accuracy and outperforming existing methods.
  • The model was also successfully applied to assess HER2 amplification in gastric cancer patients, yielding promising results with high accuracy and precision, indicating its potential beyond breast cancer applications.
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Background: Frailty is common among older adults, often associated with activity limitations during physical and walking tasks. The interactive boxing-cycling combination has the potential to be an innovative and efficient training method, and our hypothesis was that interactive boxing-cycling would be superior to stationary cycling in improving frailty and activity limitations in frail and prefrail older adults.

Objective: To examine the impact of interactive boxing-cycling on frailty and activity limitations in frail and prefrail older adults compared to stationary cycling.

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Background: Studies evaluating the characteristics of dual primary gastric and colorectal cancer (CRC) (DPGCC) are limited.

Aim: To analyze the clinicopathologic characteristics and prognosis of synchronous and metachronous cancers in patients with DPGCC.

Methods: From October 2010 to August 2021, patients with DPGCC were retrospectively reviewed.

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Context: Previous research evaluating the effects in B-vitamins on the prevention and treatment of cardiovascular disease (CVD) has substantial limitations and lacks recently published large prospective studies; hence, conducting an updated meta-analysis is needed.

Objective: We investigated the association between vitamin B status and human CVD development in order to provide more specific advice about vitamin B intake for those at risk of CVD.

Data Sources: Relevant articles were identified by JSTOR, PubMed, and ProQuest databases.

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Epithelial ovarian cancer (EOC) remains a significant cause of mortality among gynecologic cancers, with the majority of cases being diagnosed at an advanced stage. Before targeted therapies were available, EOC treatment relied largely on debulking surgery and platinum-based chemotherapy. Vascular endothelial growth factors have been identified as inducing tumor angiogenesis.

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Interstitial fibrosis assessment by renal pathologists lacks good agreement, and we aimed to investigate its hidden properties and infer possible clinical impact. Fifty kidney biopsies were assessed by 9 renal pathologists and evaluated by intraclass correlation coefficients (ICCs) and kappa statistics. Probabilities of pathologists' assessments that would deviate far from true values were derived from quadratic regression and multilayer perceptron nonlinear regression.

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Article Synopsis
  • * Traditional microscopic examination for determining HER2 gene amplification is inconsistent and time-consuming due to high variability among pathologists, affecting diagnosis accuracy.
  • * This paper presents an effective deep learning method that significantly improves the detection of breast cancer and HER2 amplification, outperforming existing methods while also being faster and requiring less computational resources.
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Overexpression of human epidermal growth factor receptor 2 (HER2/ERBB2) is identified as a prognostic marker in metastatic breast cancer and a predictor to determine the effects of ERBB2-targeted drugs. Accurate ERBB2 testing is essential in determining the optimal treatment for metastatic breast cancer patients. Brightfield dual in situ hybridization (DISH) was recently authorized by the United States Food and Drug Administration for the assessment of ERRB2 overexpression, which however is a challenging task due to a variety of reasons.

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Background: A connection between plasma levels of haptoglobin (Hp) and Alzheimer's disease (AD) has been shown in several observational studies. It is debatable, nonetheless, how the two are related causally.

Objective: To establish the causal relationship between Hp and AD using a two-sample Mendelian randomization (MR) study.

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The overexpression of the human epidermal growth factor receptor 2 (HER2) is a predictive biomarker in therapeutic effects for metastatic breast cancer. Accurate HER2 testing is critical for determining the most suitable treatment for patients. Fluorescent in situ hybridization (FISH) and dual in situ hybridization (DISH) have been recognized as FDA-approved methods to determine HER2 overexpression.

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Background: Diabetic encephalopathy (DE) is a complication of type 2 diabetes mellitus (T2DM) that features Alzheimer's disease (AD)-like pathology, which can be degraded by the autophagy-lysosome pathway (ALP). Since transcription factor EB (TFEB) is a master regulator of ALP, TFEB-mediated ALP activation might have a therapeutic effect on DE, but this has yet to be investigated.

Methods: We established T2DM mouse models and cultured HT22 cells under high-glucose (HG) conditions to confirm the role of ALP in DE.

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Interstitial inflammation scoring is incorporated into the Banff Classification of Renal Allograft Pathology and is essential for the diagnosis of T-cell mediated rejection. However, its reproducibility, including inter-rater and intra-rater reliabilities, has not been carefully investigated. In this study, eight renal pathologists from different hospitals independently scored 45 kidney allograft biopsies with varying extents of interstitial inflammation.

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Background And Aims: Running can induce advantageous cardiovascular effects such as improved arterial stiffness and blood-supply perfusion. However, the differences between the vascular and blood-flow perfusion conditions under different levels of endurance-running performance remains unclear. The present study aimed to assess the vascular and blood-flow perfusion conditions among 3 groups (44 male volunteers) according to the time taken to run 3 km: Level 1, Level 2, and Level 3.

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(1) Background: A major challenge for post-discharged gastric cancer patients following gastrectomy is the impact of the anatomy change on decreased oral intake, nutritional status, and, ultimately, quality of life. The purpose of this study is to examine the feasibility and preliminary effects of an individualized mHealth nutrition (iNutrition) intervention in post-discharged gastric cancer patients following gastrectomy. (2) Methods: A mixed-method feasibility study with a parallel randomized controlled design was conducted.

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Article Synopsis
  • The study focuses on improving patient selection for the targeted therapy bevacizumab, which inhibits blood vessel formation in cancer treatment, particularly for newly diagnosed ovarian cancer.
  • It examines the expression patterns of three proteins related to angiogenesis and utilizes a deep learning model to predict patient responses to bevacizumab therapy based on these protein levels.
  • The results show high predictive accuracy and identify patients likely to benefit from the therapy, correlating low cancer recurrence rates with specific protein expressions, thus aiding in personalized treatment planning.
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Long sit-to-stand (STS) time has been identified as a feature of impaired functional mobility. The changes in biomechanics of STS performance with simultaneous hip adductor contraction have not been studied, which may limit indications for use of hip adductor activation during STS training. Ten individuals with hemiplegia (mean age 61.

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Background: The prognostic value of the advanced lung cancer inflammation index (ALI) has been demonstrated in various tumors. However, the prognostic significance of ALI in non-metastatic gastric cancer (GC) remains unclear. This study aimed to identify the prognostic values of ALI in patients with non-metastatic GC who underwent radical surgical resection.

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Article Synopsis
  • * Detecting the BRAF (V600E) mutation in thyroid cancer can indicate malignancy and poor prognosis, and an automated deep learning framework has been developed to predict this mutation's presence in FNAC samples.
  • * The deep learning technique showed high performance with an accuracy of 87%, outperforming existing methods, and offers a promising tool for improving diagnosis and treatment decisions in thyroid cancer using advanced technology.
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We developed an insulated isothermal PCR (iiPCR) method for the efficient and rapid detection of (Fo), which is a fungus that infects various hosts and causes severe crop losses. The Fo iiPCR method was sensitive enough to detect up to 100 copies of standard DNA template and 10 fg of Fo genomic DNA. In addition, it could directly detect 1 pg of mycelium and 10 spores of Fo without DNA extraction.

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  • According to the World Health Organization's 2022 report, cancer is the leading cause of death globally, responsible for nearly one in six fatalities, highlighting the need for early detection to lower mortality rates.
  • The study introduces a soft label fully convolutional network (SL-FCN) designed to enhance breast cancer therapy and diagnose thyroid cancer by automatically segmenting critical features in medical images.
  • Evaluations against thirteen other deep learning models show that SL-FCN demonstrates strong performance in accuracy and recall, achieving up to 94.64% accuracy in detecting HER2 amplification in breast cancer datasets and effectively segmenting papillary thyroid carcinoma in thyroid cases.
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Lung cancer is the biggest cause of cancer-related death worldwide. An accurate nodal staging is critical for the determination of treatment strategy for lung cancer patients. Endobronchial-ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) has revolutionized the field of pulmonology and is considered to be extremely sensitive, specific, and secure for lung cancer staging through rapid on-site evaluation (ROSE), but manual visual inspection on the entire slide of EBUS smears is challenging, time consuming, and worse, subjective, on a large interobserver scale.

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