Publications by authors named "S Kovaleva Yu"

Objective: To investigate the probability of hepatocellular carcinoma (HCC) in a large number of gray-zone (GZ) patients with chronic hepatitis B (CHB) in clinical practice.

Methods: The patients with CHB who were diagnosed and treated in our hospital from January 2013 to January 2023 were analyzed retrospectively.

Results: According to the different levels of HBeAg, ALT and HBV DNA, GZ patients were divided into four categories: (1) Gray zone A (GZ-A): HBeAg positive, normal ALT level, HBV DNA ≤ 10 IU/ml; (2) Gray zone B (GZ-B): HBeAg positive, ALT>ULN, HBV DNA ≤ 2 × 10 IU/ml; (3) Gray zone C (GZ-C): HBeAg negative, normal ALT level, HBV DNA ≥ 2 × 10 IU/ml; and (4) Gray zone D (GZ-D): HBeAg negative, ALT > ULN, serum HBV DNA ≤ 2 × 10 IU/ml.

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Background: Contrast-enhanced ultrasound (CEUS) shows potential for the differential diagnosis of breast lesions in general, but its effectiveness remains unclear for the differential diagnosis of lesions highly suspicious for breast cancers.

Objective: This study aimed to evaluate the diagnostic value of CEUS in differentiating pathological subtypes of suspicious breast lesions defined as category 4 of US-BI-RADS.

Methods: The dataset of 150 breast lesions was prospectively collected from 150 patients who underwent routine ultrasound and CEUS examination and were highly suspected of having breast cancers.

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Introduction: COQ4 mutation often leads to a fatal multi-system disease in infants. Recently, it was reported that the biallelic COQ4 variants may be a potential cause of hereditary spastic paraplegia (HSP). This study aims to describe the clinical features and genotype of the COQ4 associated hereditary spastic paraplegia (HSP).

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Extensive neovascularization is a hallmark of glioblastoma (GBM). In addition to supplying oxygen and nutrients, vascular endothelial cells provide trophic support to GBM cells via paracrine signaling. Here we report that Endocan (ESM1), an endothelial-secreted proteoglycan, confers enhanced proliferative, migratory, and angiogenic properties to GBM cells and regulates their spatial identity.

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Background: The individualized prediction and discrimination of precancerous lesions of gastric cancer (PLGC) is critical for the early prevention of gastric cancer (GC). However, accurate non-invasive methods for distinguishing between PLGC and GC are currently lacking. This study therefore aimed to develop a risk prediction model by machine learning and deep learning techniques to aid the early diagnosis of GC.

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