Publications by authors named "Jian-ping Li"

As the extensive use of antibiotics has led to the rapid spread of antibiotic resistance, there is an urgent need for quantitative assessment of antibiotic residues in the environment. Surface-enhanced Raman spectroscopy (SERS) has emerged as a rapid and cost-effective detection method, but it suffers from the high variability in signal intensities, its quantitative detection remains challenging. Herein, we have developed a SERS calibration substrate with a silent region internal standard, enabling simultaneous and reliable quantitative detection of three commonly antibiotics of penicillin potassium (PP), tetracycline hydrochloride (TCH) and levofloxacin (LEV).

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HLA-A*02:406 differs from HLA-A*02:01:01:01 by one nucleotide substitution in codon 116 in exon 3.

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HLA-A*02:407 differs from HLA-A*02:01:01:01 by one nucleotide substitution in codon 109 in exon 3.

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Article Synopsis
  • HLA-B*15:358 and HLA-B*15:02:01:01 are two variants of the HLA-B gene.
  • They differ by only one nucleotide change at position 685 in exon 4 of the gene.
  • This slight genetic variation may affect the function or expression of the HLA-B protein.
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Article Synopsis
  • The study investigates bloodstream infections caused by a specific bacteria in pediatric patients at a hospital, collecting data from 2019 to 2023 to better understand its prevalence and clinical characteristics.
  • It reveals that these infections are particularly common in children with hematological diseases and tumors, with 43.5% of cases showing contamination spread across various departments.
  • Additionally, the resistance to antibiotics was notable, with 21.6% of isolates showing multi-drug resistance, emphasizing the need for ongoing monitoring of antimicrobial resistance trends.
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Background: The outbreak of coronavirus disease 2019 (COVID-19) infection posed a huge threat and burden to public healthcare in late 2022. Non-drug measures of traditional Chinese medicine (TCM), such as acupuncture, cupping and moxibustion, are commonly used as adjuncts in China to help in severe cases, but their effects remain unclear.

Objectives: To observe the clinical effect of TCM non-drug measures in improving respiratory function and symptoms among patients with severe COVID-19.

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Objective: This study aimed to investigate the impact of foot orthoses on foot radiological parameters and pain in children diagnosed with flexible flatfoot.

Methods: A comprehensive search was conducted across several databases, including PubMed, Web of Science, EMBASE, Cochrane Library, and EBSCO, covering publications from the inception of each database up to 8 June 2024. The study focused on randomized controlled trials investigating the use of foot orthoses for treating flexible flat feet in children.

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In the Internet of Things (IoT) healthcare sector, the wireless body area network (WBAN) is being used to optimize medical results by tracking and treating patients as they go about their daily lives. Health insurance has also been one of the cybercriminal's main goals. The Systematic Review of IoT Healthcare systems particularly wireless body area networks is significant, to reach the benefits and challenges faced by existing methods in the domain.

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Background: Congenital sideroblastic anemia (CSA) is a rare and heterogeneous group of genetic disorders. Conventional treatment include pyridoxine (vitamin B6) and allogeneic hematopoietic stem cell transplantation (allo-HSCT), and can alleviate anemia in the majority of cases. Nevertheless, some CSA cases remain unresponsive to pyridoxine or are unable to undergo allo-HSCT.

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Introduction: In the evolving healthcare landscape, we aim to integrate hyperspectral imaging into Hybrid Health Care Units to advance the diagnosis of medical diseases through the effective fusion of cutting-edge technology. The scarcity of medical hyperspectral data limits the use of hyperspectral imaging in disease classification.

Methods: Our study innovatively integrates hyperspectral imaging to characterize tumor tissues across diverse body locations, employing the Sharpened Cosine Similarity framework for tumor classification and subsequent healthcare recommendation.

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Background: The prognosis of hepatocellular carcinoma (HCC) combined with portal and hepatic vein cancerous thrombosis is poor, for unresectable patients the combination of targeted therapy and immune therapy was the first-line recommended treatment for advanced HCC, with a median survival time of only about 2.7-6 months. In this case report, we present the case of a patient with portal and hepatic vein cancerous thrombosis who achieved pathologic complete response after conversion therapy.

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Article Synopsis
  • Heart disease poses significant health challenges, highlighting the need for accurate and timely detection methods.
  • This research introduces an advanced machine learning system that combines Random Forest and Ada Boost classifiers, along with data pre-processing techniques like standard scaling and Recursive Feature Elimination (RFE), to improve cardiac disease diagnosis.
  • The proposed system achieved an impressive accuracy of 99.25%, demonstrating its effectiveness compared to traditional models and its potential integration into IoT-enabled healthcare for better patient outcomes.
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Aging can cause degenerative changes in multiple tissues and organs. Gastrointestinal diseases and dysfunctions are common in the elderly population. In this study, we investigated the effects of polysaccharide (APS) and ethanol extract (AEE) on age-related intestinal dysfunction and gut microbiota dysbiosis in naturally aging mice.

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This research explores the use of gated recurrent units (GRUs) for automated brain tumor detection using MRI data. The GRU model captures sequential patterns and considers spatial information within individual MRI images and the temporal evolution of lesion characteristics. The proposed approach improves the accuracy of tumor detection using MRI images.

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Objective: To investigate the associated factors of endogenous erythropoietin (EPO) and its association with 10-year risks of atherosclerotic cardiovascular disease in a Chinese community-based general population.

Methods: The participants of this study were from an atherosclerosis cohort survey which was established by the Department of Cardiology, Peking University First Hospital in 2011. The cohort survey was performed in the Gucheng and Pingguoyuan communities of Shijingshan district in Beijing, China.

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HLA-B*15:270 differs from HLA-B*15:12:01 by one nucleotide substitution at position 679 in exon 4.

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HLA-A*02:405 differs from HLA-A*02:06:01:01 by one nucleotide substitution in codon 161 in exon 3.

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Article Synopsis
  • HLA-B*15:269 and HLA-B*15:63 are two different genetic variants of the HLA-B gene.
  • The difference between these two variants is due to two nucleotide changes in a specific region known as exon 3.
  • These variations can influence how the immune system recognizes and responds to different antigens.
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Background: Many studies have demonstrated the benefit of complete multivessel revascularization versus culprit-only intervention in patients of ST-segment elevation myocardial infarction (STEMI) and multivessel coronary artery disease. However, only a few single-center retrospective studies were performed on small Chinese cohorts. Our study aims to demonstrate the advantage of multivessel percutaneous intervention (PCI) strategy on 30-day in-hospital outcomes to patients with STEMI and multivessel disease in larger Chinese population.

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Inflammatory bowel disease (IBD) is a recurrent disease associated with a potential risk of colorectal cancer. (AM), a Chinese herbal medicine, is known to alleviate IBD. However, its mechanism of action requires further clarification.

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Breast tumor detection and classification on the Internet of Medical Things (IoMT) can be automated with the potential of Artificial Intelligence (AI). Deep learning models rely on large datasets, however, challenges arise when dealing with sensitive medical data. Restrictions on sharing these medical data result in limited publicly available datasets thereby impacting the performance of the deep learning models.

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Accurate breast cancer (BC) diagnosis is a difficult task that is critical for the proper treatment of BC in IoMT (Internet of Medical Things) healthcare systems. This paper proposes a convolutional neural network (CNN)-based diagnosis method for detecting early-stage breast cancer. In developing the proposed method, we incorporated the CNN model for the invasive ductal carcinoma (IDC) classification using breast histology image data.

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