Publications by authors named "Jianfu Li"

Materials that effectively facilitate the transport of ionic and electronic charges are crucial for advancing technological innovations in next-generation energy storage devices. This work proposed a new class of high-performance mixed ionic-electronic conductors (MIECs) in graphite intercalation compounds with the composition XC (X = {Ca, Sr, and Ba}) using molecular dynamics based on machine learning force fields combined with first-principles calculations. The calculated mean squared displacement and radial distribution functions indicate that CaC, SrC, and BaC transition to the superionic state at temperatures of 1500, 1800, and 2100 K, respectively.

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Objective: Human Papillomavirus (HPV) vaccine is an effective measure to prevent and control the diseases caused by HPV. However, widespread misinformation and vaccine hesitancy remain significant barriers to its uptake. This study focuses on the development of VaxBot-HPV, a chatbot aimed at improving health literacy and promoting vaccination uptake by providing information and answering questions about the HPV vaccine.

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Objective: Adverse event (AE) extraction following COVID-19 vaccines from text data is crucial for monitoring and analyzing the safety profiles of immunizations, identifying potential risks and ensuring the safe use of these products. Traditional deep learning models are adept at learning intricate feature representations and dependencies in sequential data, but often require extensive labeled data. In contrast, large language models (LLMs) excel in understanding contextual information, but exhibit unstable performance on named entity recognition (NER) tasks, possibly due to their broad but unspecific training.

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Background: Effective management of dual antiplatelet therapy (DAPT) following drug-eluting stent (DES) implantation is crucial for preventing adverse events. Traditional prognostic tools, such as rule-based methods or Cox regression, despite their widespread use and ease, tend to yield moderate predictive accuracy within predetermined timeframes. This study introduces a new contrastive learning-based approach to enhance prediction efficacy over multiple time intervals.

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Background: Limited research exists on screening thresholds for low-dose CT in detecting malignant pure ground-glass lung nodules (pGGNs) in the Chinese population.

Materials And Methods: A retrospective analysis of the Guangzhou Lung-Care programme was conducted, retrieving average transverse diameter, location, histopathology, frequency and follow-up intervals. Diagnostic performances for 'lung cancers' were evaluated using areas under the curve (AUCs), decision curve analysis (DCA), sensitivities and specificities, with thresholds ranging from 5 mm to 10 mm.

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Clinical mastitis (CM) is a prevalent and severe inflammatory disease in dairy cows affecting the mammary glands. Fatty acid (FA) metabolism and associated enzymes are crucial for many physiological and pathological processes in dairy cows. However, the relationships among FA metabolism, FA-associated enzymes, and CM, as well as the mechanisms underlying their interactions, in dairy cows are not fully understood.

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Objectives: This study aims to explore how pre-existing conditions such as blood types, family history of cancer and comorbid diseases correlate with the genetic and programmed death-ligand 1 (PD-L1) expression that contributes to the heterogeneous biological behaviours of non-small cell lung cancer (NSCLC).

Materials And Methods: A cohort of 5507 NSCLC patients who underwent surgical resection between January 2014 and July 2018 was studied. Targeted next-generation sequencing was used to detect mutations in nine pivotal cancer-related genes, and immunohistochemical staining was applied to assess PD-L1 expression.

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Background: Recently, the impact of solar radiation (RAD) on diseases worldwide has garnered growing attention. However, the association between RAD and lung cancer remains largely unknow and no consensus has been reached. The aim of this study was to investigate the lag exposure-response of RAD on lung cancer and provide robust scientific evidence for updating prevention and treatment strategies of lung cancer.

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. Until now, limited knowledge remains regarding the association among childhood obesity, cognitive behavior, and brain networks. Utilizing a publicly available dataset, we aimed to investigate the relationships between childhood obesity and functional networks during the stop-signal task.

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Objective: Medical laboratory testing is essential in healthcare, providing crucial data for diagnosis and treatment. Nevertheless, patients' lab testing results are often transferred via fax across healthcare organizations and are not immediately available for timely clinical decision making. Thus, it is important to develop new technologies to accurately extract lab testing information from scanned laboratory reports.

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Background: Real-world data on C-MET protein overexpression in non-small cell lung cancer (NSCLC) patients, particularly among the Asian Chinese population, are limited.

Objectives: This study aimed to evaluate the clinicomolecular characteristics and prognosis of C-MET overexpression in Chinese NSCLC patients, focusing on those with positive C-MET overexpression (immunohistochemistry (IHC) 3+).

Design: A retrospective and observational study.

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Article Synopsis
  • - The study developed VaxBot-HPV, a chatbot designed to increase health literacy and boost HPV vaccination rates by providing helpful information and responses related to the HPV vaccine.
  • - VaxBot-HPV was trained using a knowledge base of 451 documents and 202 question-answer pairs, and assessed alongside other models, GPT-3.5 and GPT-4, focusing on answer relevancy and faithfulness.
  • - Results showed VaxBot-HPV excelled in providing relevant and accurate answers, highlighting the potential for chatbots in enhancing healthcare communication and medical education.
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Objective: The diversity of electrode placement systems brought the problem of channel location harmonization in large-scale electroencephalography (EEG) applications to the forefront. Therefore, our goal was to resolve this problem by introducing and assessing the reference electrode standardization technique (REST) to transform EEGs into a common electrode distribution with computational zero reference at infinity offline.

Methods: Simulation and eye-closed resting-state EEG datasets were used to investigate the performance of REST for EEG signals and power configurations.

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Background: Micropapillary (MPP) adenocarcinoma is considered one of the most aggressive pathological types of lung adenocarcinoma (LADC). This retrospective study aimed to evaluate the prognostic significance and benefit of postoperative adjuvant therapy (PAT) in stage IA LADC patients with different proportions of MPP components.

Materials And Methods: We retrospectively examined clinical stage IA LADC patients who underwent surgical resection between August 2012 and December 2019.

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Article Synopsis
  • The study investigates the effectiveness of large language models (LLMs), particularly fine-tuned GPT-3.5, in accurately extracting acupoint location relations from a specific dataset of acupuncture points provided by the WHO.
  • The researchers compared various models, focusing on key relation types and found that fine-tuned GPT-3.5 achieved the highest micro-average F1 score of 0.92 in performance metrics.
  • The findings highlight the importance of domain-specific fine-tuning in improving model performance for acupuncture, paving the way for better clinical decision support and educational tools in this field.
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Background: Respiratory cancer is the leading cause of cancer-related deaths worldwide, but its statistics vary between the East and West. This study aimed to estimate the burdens of tracheal, bronchus, and lung (TBL) cancer and larynx cancer and their attributable risks from 1990 to 2019 in Asia, and at regional and national levels.

Methods: This research evaluated the incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life years (DALYs) for respiratory tract cancers using the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 database.

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Background: Light at night (LAN) has become a concern in interdisciplinary research in recent years. This global interdisciplinary study aimed to explore the exposure-lag-response association between LAN exposure and lung cancer incidence.

Methods: LAN data were obtained from the Defense Meteorological Satellite Program's Operational Linescan System.

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Background: Vaccines have revolutionized public health by providing protection against infectious diseases. They stimulate the immune system and generate memory cells to defend against targeted diseases. Clinical trials evaluate vaccine performance, including dosage, administration routes, and potential side effects.

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Tumor-draining lymph nodes (TDLNs) are usually the first station of tumor metastasis in lung cancer. TDLNs+ have distinct pathomorphologic and tumor microenvironment (TME)-compositional patterns, which still need to be thoroughly investigated in lung adenocarcinoma (LUAD). Here, we enrolled 312 LUAD patients with TDLNs+ from our institution between 2015 and 2019.

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During estrus, the poll glands of male Bactrian Camels () become slightly raised, exuding a large amount of pale yellow watery secretion with a characteristic odor that may contain hydrogen sulfide (HS). However, whether HS can be synthesized in the poll glands of male Bactrian Camels and its role in inducing camel estrus remains unclear. This study aimed to identify differentially expressed proteins (DEPs) and signaling pathways in the poll gland tissues of male Bactrian Camels using data independent acquisition (DIA) proteomics.

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To tackle misdiagnosis in lung cancer screening with low-dose computed tomography (LDCT), we aimed to compile a genome atlas for differentiating benign, preinvasive, and invasive lung nodules and characterize their molecular pathogenesis. We collected 432 lung nodule tissue samples from Chinese patients, spanning benign, atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IA). We performed comprehensive sequencing, examining somatic variants, gene expressions, and methylation levels.

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Background: The COVID-19 pandemic, caused by SARS-CoV-2, has had a profound impact worldwide, leading to widespread morbidity and mortality. Vaccination against COVID-19 is a critical tool in controlling the spread of the virus and reducing the severity of the disease. However, the rapid development and deployment of COVID-19 vaccines have raised concerns about potential adverse events following immunization (AEFIs).

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