Publications by authors named "LinBo Wang"

Triple-negative breast cancer (TNBC) represents the most aggressive subtype of breast cancer, lacking effective targeted therapies and presenting with a poor prognosis. In this study, we utilized the epigenomic landscape, TCGA database, and clinical samples to uncover the pivotal role of HJURP in TNBC. Our investigation revealed a strong correlation between elevated HJURP expression and unfavorable prognosis, metastatic progression, and late-stage of breast cancer.

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Background: The impact of pre-infection vaccination on the risk of long COVID remains unclear in the pediatric population. We aim to assess the effectiveness of BNT162b2 on long COVID risks with various strains of the SARS-CoV-2 virus in children and adolescents, using comparative effectiveness methods. We further explore if such pre-infection vaccination can mitigate the risk of long COVID beyond its established protective benefits against SARS-CoV-2 infection using causal mediation analysis.

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Pathophysiological evolutions in early-stage Alzheimer's disease (AD) are not well understood. We used data of 2923 Olink plasma proteins from 51,296 non-demented middle-aged adults. During a follow-up of 15 years, 689 incident AD cases occurred.

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Proteomic alterations preceding the onset of depression offer valuable insights into its development and potential interventions. Leveraging data from 46,165 UK Biobank participants and 2920 plasma proteins profiled at baseline, we conducted a longitudinal analysis with a median follow-up of 14.5 years to explore the relationship between plasma proteins and incident depression.

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  • This study focused on using machine learning to predict prognosis in breast cancer patients by analyzing electronic medical records from 6,477 individuals, identifying 15 key clinical features related to survival.
  • Eight different algorithms, including XGBoost, were tested, with XGBoost being the most effective, achieving an AUC of 0.813 and outperforming existing prognostic models.
  • The findings suggest that incorporating machine learning into clinical practice can enhance decision-making for personalized treatment strategies in breast cancer care.
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Breast reconstruction is essential for improving the appearance of patients after cancer surgery. Traditional breast prostheses are not appropriate for those undergoing partial resections and cannot detect and treat locoregional recurrence. Personalized shape prostheses that can smartly sense tumor relapse and deliver therapeutics are needed.

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  • Sorafenib is a common treatment for advanced hepatocellular carcinoma (HCC), but its effectiveness is often reduced due to drug resistance.
  • A study integrating posttranslational modification analysis and CRISPR screening discovered that ubiquitination of CCT3 plays a key role in this resistance.
  • Targeting the CCT3/ACTN4/TFRC pathway may improve treatment outcomes by enhancing ferroptosis and overcoming resistance to Sorafenib in HCC patients.
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Parkinson's disease (PD) exhibits heterogeneity in terms of symptoms and prognosis, likely due to diverse neuroanatomical alterations. This study employs a contrastive deep learning approach to analyze Magnetic Resonance Imaging (MRI) data from 932 PD patients and 366 controls, aiming to disentangle PD-specific neuroanatomical alterations. The results reveal that these neuroanatomical alterations in PD are correlated with individual differences in dopamine transporter binding deficit, neurodegeneration biomarkers, and clinical severity and progression.

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  • A recent study identified potential new biomarkers for Alzheimer's disease (AD) through an extensive analysis of over 6,300 cerebrospinal fluid proteins from the ADNI database, highlighting YWHAG as a leading candidate for diagnosis.
  • The study demonstrated that combinations of proteins (four or five) significantly improved diagnostic accuracy for AD, showing exceptional performance in distinguishing between AD and non-AD cases.
  • Findings suggest these biomarkers could predict clinical progression to AD dementia and are linked to cognitive decline, with implications for future clinical trials targeting various disease mechanisms.
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Background And Objectives: Identification of individuals at high risk of developing Parkinson disease (PD) several years before diagnosis is crucial for developing treatments to prevent or delay neurodegeneration. This study aimed to develop predictive models for PD risk that combine plasma proteins and easily accessible clinical-demographic variables.

Methods: Using data from the UK Biobank (UKB), which recruited participants across the United Kingdom, we conducted a longitudinal study to identify predictors for incident PD.

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Background: Dementia has a long prodromal stage with various pathophysiological manifestations; however, the progression of pre-diagnostic changes remains unclear. We aimed to determine the evolutional trajectories of multiple-domain clinical assessments and health conditions up to 15 years before the diagnosis of dementia.

Methods: Data was extracted from the UK-Biobank, a longitudinal cohort that recruited over 500,000 participants from March 2006 to October 2010.

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  • Parkinson's disease (PD) patients experience progressive gray matter volume loss, and the study investigates different patterns of this atrophy among patients.* -
  • A total of 107 PD patients were analyzed through MRI scans, leading to the identification of two distinct subtypes based on their rates of brain atrophy: Subtype 1 with moderate atrophy and Subtype 2 with more rapid deterioration.* -
  • Subtype 2 not only showed faster brain atrophy but also correlated with worsened symptoms in non-motor and motor functions, memory, and depression, suggesting the need for tailored treatment approaches.*
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Background: Whether there is hypothalamic degeneration in Parkinson's disease (PD) and its association with clinical symptoms and pathophysiological changes remains controversial.

Objectives: We aimed to quantify microstructural changes in hypothalamus using a novel deep learning-based tool in patients with PD and those with probable rapid-eye-movement sleep behavior disorder (pRBD). We further assessed whether these microstructural changes associated with clinical symptoms and free thyroxine (FT4) levels.

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  • This study analyzes lymph node metastasis in breast cancer patients who did not undergo preoperative treatments, revealing a 25.57% occurrence in a large sample.
  • Multiple factors such as younger age, African-American ethnicity, tumor location, types of carcinoma, HER2 positivity, and tumor size were found to significantly associate with increased risk of lymph node metastasis.
  • The research highlighted the development of predictive nomograms to assist in understanding and predicting the incidence of lymph node involvement based on identified risk factors.
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Developing a single-domain assay to identify individuals at high risk of future events is a priority for multi-disease and mortality prevention. By training a neural network, we developed a disease/mortality-specific proteomic risk score (ProRS) based on 1461 Olink plasma proteins measured in 52,006 UK Biobank participants. This integrative score markedly stratified the risk for 45 common conditions, including infectious, hematological, endocrine, psychiatric, neurological, sensory, circulatory, respiratory, digestive, cutaneous, musculoskeletal, and genitourinary diseases, cancers, and mortality.

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Background: Neoadjuvant chemotherapy (NAC) has been widely applied in operable breast cancer patients. This study aim to identify the predictive factors of overall survival(OS) and recurrence free survival (RFS) in breast cancer patients who received NAC from a single Chinese institution.

Patients And Methods: There were 646 patients recruited in this study.

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Accurate pathologic diagnosis and molecular classification of breast mass biopsy tissue is important for determining individualized therapy for (neo)adjuvant systemic therapies for invasive breast cancer. The CassiII rotational core biopsy system is a novel biopsy technique with a guide needle and a "stick-freeze" technology. The comprehensive assessments including the concordance rates of diagnosis and biomarker status between CassiII and core needle biopsy were evaluated in this study.

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Aconitine is a crucial toxic component in Chinese herbal medicines such as Aconitum, Aconitum coreanum, and Aconitum soongaricum. The poisoning symptoms of the central nervous system and cardiovascular system caused by it are relatively common in China, and there are many studies on cardiovascular system diseases caused by aconitine. However, the specific mechanism of neurotoxicity induced by aconitine is still unclear.

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Increasing evidence suggests that Parkinson's disease (PD) exhibits disparate spatial and temporal patterns of progression. Here we used a machine-learning technique-Subtype and Stage Inference (SuStaIn) - to uncover PD subtypes with distinct trajectories of clinical and neurodegeneration events. We enrolled 228 PD patients and 119 healthy controls with comprehensive assessments of olfactory, autonomic, cognitive, sleep, and emotional function.

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Deep learning has been used to reconstruct super-resolution structured illumination microscopy (SR-SIM) images with wide-field or fewer raw images, effectively reducing photobleaching and phototoxicity. However, the dependability of new structures or sample observation is still questioned using these methods. Here, we propose a dynamic SIM imaging strategy: the full raw images are recorded at the beginning to reconstruct the SR image as a keyframe, then only wide-field images are recorded.

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is the pathogen of psittacosis and infects a wide range of birds and even humans. Human infection occurs most commonly in those with a history of contact with birds or poultry. We describe a case of psittacosis in a human immunodeficiency virus infected patient in Zhejiang Province for the first time.

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Background And Objectives: Mean diffusivity (MD) of diffusion MRI (dMRI) has been used to measure cortical and subcortical microstructural properties. This study investigated relationships of cortical and subcortical MD, clinical progression, and fluid biomarkers in Parkinson disease (PD).

Methods: This longitudinal study using data from the Parkinson's Progression Markers Initiative was collected from April 2011 to July 2022.

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Background: Schizophrenia is among the most persistent and debilitating mental health conditions worldwide. The American Psychological Association (APA) has identified 10 psychosocial treatments with evidence for treating schizophrenia and these treatments are typically provided in person. However, in-person services can be challenging to access for people living in remote geographic locations.

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