Publications by authors named "Jia-ning Wang"

A novel thioxoimidazolidin-linked sialoside bovine serum albumin (WM-BSA) conjugate was synthesized and evaluated as an inhibitor of influenza virus hemagglutinin (HA) and neuraminidase (NA). The multivalent conjugate was prepared by the attachment of thioxoimidazolidin-sialoside monomer (WM) to BSA via adipate linker. Surface plasmon resonance analysis revealed that WM-BSA exhibited potent binding to recombinant influenza HA and NA proteins, with dissociation constants in the submicromolar range.

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Article Synopsis
  • The study aims to create a nomogram for early prediction of severe mycoplasma pneumoniae pneumonia (SMPP) in both pediatric and adult patients by analyzing 550 cases, classified into severe and non-severe groups.
  • Various models were developed using clinical data, imaging, and radiomics features, assessed through different statistical methods, including logistic regression and AUC metrics.
  • The integrated model showed strong predictive ability, particularly in testing cohorts, with a notable improvement when combining clinical and imaging features, demonstrating its effectiveness for identifying SMPP.
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Conjugated microporous polymers (CMPs) have unique characteristics and have been used in a range of fascinating applications in separation sciences. In this study, a CMP, designated as CMP-1, was synthesized via the Sonogashira-Hagihara coupling reaction using 1,3,5-triphenylbenzene and 1,4-dibromobenzene as building blocks. CMP-1 features a large surface area, abundant micropore structures, and excellent stability, making it a promising solid-phase extraction adsorbent for the efficient enrichment of neonicotinoid insecticides (NEOs).

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Background: Hepatocellular carcinoma (HCC) is often associated with the overexpression of multiple proteins and genes. For instance, patients with HCC and a high expression of the glypican-3 () gene have a poor prognosis, and noninvasive assessment of expression before surgery is helpful for clinical decision-making. Therefore, our primary aim in this study was to develop and validate multisequence magnetic resonance imaging (MRI) radiomics nomograms for predicting the expression of in individuals diagnosed with HCC.

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Influenza remains a global public health threat, and the development of new antivirals is crucial to combat emerging drug-resistant influenza strains. In this study, we report the synthesis and evaluation of a sialyl lactosyl (TS)-bovine serum albumin (BSA) conjugate as a potential multivalent inhibitor of the influenza virus. The key trisaccharide component, TS, was efficiently prepared via a chemoenzymatic approach, followed by conjugation to dibenzocyclooctyne-modified BSA via a strain-promoted azide-alkyne cycloaddition reaction.

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Influenza viruses contribute significantly to the global health burden, necessitating the development of strategies against transmission as well as effective antiviral treatments. The present study reports a biomimetic strategy inspired by the natural antiviral properties of mucins. A bovine serum albumin (BSA) conjugate decorated with the multivalent neuraminidase inhibitor Zanamivir (ZA-BSA) was synthesized using copper-free click chemistry.

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Article Synopsis
  • Immune checkpoint inhibitors (ICIs) can lead to Vogt-Koyanagi-Harada disease (VKHD)-like uveitis, but this is the first report linking a new PD-1 monoclonal antibody, Toripalimab, to such adverse effects.
  • A case is presented where a patient developed severe binocular acute panuveitis and exudative retinal detachment after completing 20 months of Toripalimab treatment for bladder cancer.
  • The patient's eye condition improved following discontinuation of ICIs and treatment with corticosteroids, highlighting the need for vigilance regarding eye complications in long-term PD-1 therapy.
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  • * Researchers evaluated the effectiveness of single-energy spectral CT imaging in enhancing the visualization of key blood vessels associated with pancreatic tumors, comparing it to mixed energy and lower energy settings.
  • * Findings showed that single-energy spectral CT provided significantly better image quality and higher CT values for blood vessels compared to mixed energy and 70 keV imaging, suggesting it could enhance pre-surgical evaluations.
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Purpose: This study aims to explore the value of clinical features, CT imaging signs, and radiomics features in differentiating between adults and children with Mycoplasma pneumonia and seeking quantitative radiomic representations of CT imaging signs.

Materials And Methods: In a retrospective analysis of 981 cases of mycoplasmal pneumonia patients from November 2021 to December 2023, 590 internal data (adults:450, children: 140) randomly divided into a training set and a validation set with an 8:2 ratio and 391 external test data (adults:121; children:270) were included. Using univariate analysis, CT imaging signs and clinical features with significant differences ( < 0.

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Background: The prevalence of hypertensive heart disease (HHD) is high and there is currently no easy way to detect early HHD. Explore the application of radiomics using cardiac magnetic resonance (CMR) non-enhanced cine sequences in diagnosing HHD and latent cardiac changes caused by hypertension.

Methods: 132 patients who underwent CMR scanning were divided into groups: HHD (42), hypertension with normal cardiac structure and function (HWN) group (46), and normal control (NOR) group (44).

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Accurate diagnosis and effective antiviral treatments are urgently needed for the prevention and control of flu caused by influenza viruses. In this study, a novel oleanic acid (OA) functionalized gold nanorod OA-AuNP was prepared through a convenient ligand-exchange reaction. As hemagglutinin (HA) on the viral surface binds strongly to the multiple OA molecules on the surface of the nanoparticle, the prepared OA-AuNP was found to exhibit potent antiviral activity against a wide range of influenza A virus strains.

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Is the radiomic approach, utilizing diffusion-weighted imaging (DWI), capable of predicting the various pathological grades of intrahepatic mass-forming cholangiocarcinoma (IMCC)? Furthermore, which model demonstrates superior performance among the diverse algorithms currently available? The objective of our study is to develop DWI radiomic models based on different machine learning algorithms and identify the optimal prediction model. We undertook a retrospective analysis of the DWI data of 77 patients with IMCC confirmed by pathological testing. Fifty-seven patients initially included in the study were randomly assigned to either the training set or the validation set in a ratio of 7:3.

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Berberine (BBR) is a Chinese herb with antioxidant and anti-inflammatory properties. In a previous study, we found that BBR had a protective effect against light-induced retinal degeneration in BALB/c mice. The purinergic P2X7 receptor (P2X7R) plays a key role in retinal degeneration via inducing oxidative stress, inflammatory changes, and cell death.

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Endometrial carcinoma (EC) risk stratification prior to surgery is crucial for clinical treatment. In this study, we intend to evaluate the predictive value of radiomics models based on magnetic resonance imaging (MRI) for risk stratification and staging of early-stage EC. The study included 155 patients who underwent MRI examinations prior to surgery and were pathologically diagnosed with early-stage EC between January, 2020, and September, 2022.

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Due to the crucial regulatory mechanism of cyclin-dependent kinase 9 (CDK9) in mRNA transcription, the development of kinase inhibitors targeting CDK9 holds promise as a potential treatment strategy for cancer. A structure-based virtual screening approach has been employed for the discovery of potential novel CDK9 inhibitors. First, compounds with kinase inhibitor characteristics were identified from the ZINC15 database virtual high-throughput screening.

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Objective: To investigate the coagulation function indicators and identify influence factors of hypercoagulability in patients with adrenocorticotropic hormone (ACTH) independent Cushing syndrome (CS).

Methods: In our retrospective study, the electronic medical records system of Peking University First Hospital was searched for the patients diagnosed with ACTH independent CS on discharge from January 2014 to June 2019. Nonfunctional adrenal adenoma patients were chosen as control group and matched 1 ∶1 by body mass index (BMI), gender, and discharge date.

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To validate a radiomics model based on multi-sequence magnetic resonance imaging (MRI) in predicting the ki-67 expression levels in early-stage endometrial cancer, 131 patients with early endometrial cancer who had undergone pathological examination and preoperative MRI scan were retrospectively enrolled and divided into two groups based on the ki-67 expression levels. The radiomics features were extracted from the T2 weighted imaging (T2WI), dynamic contrast enhanced T1 weighted imaging (DCE-T1WI), and apparent diffusion coefficient (ADC) map and screened using the Pearson correlation coefficients (PCC). A multi-layer perceptual machine and fivefold cross-validation were used to construct the radiomics model.

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In the last several years, there has been a surge in the development of machine learning potential (MLP) models for describing molecular systems. We are interested in a particular area of this field - the training of system-specific MLPs for reactive systems - with the goal of using these MLPs to accelerate free energy simulations of chemical and enzyme reactions. To help new members in our labs become familiar with the basic techniques, we have put together a self-guided Colab tutorial (https://cc-ats.

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Objective: To establish a machine learning-based radiomics model to differentiate between glioma and solitary brain metastasis from lung cancer and its subtypes, thereby achieving accurate preoperative classification.

Materials And Methods: A retrospective analysis was conducted on MRI T1WI-enhanced images of 105 patients with glioma and 172 patients with solitary brain metastasis from lung cancer, which were confirmed pathologically. The patients were divided into the training group and validation group in an 8:2 ratio for image segmentation, extraction, and filtering; multiple layer perceptron (MLP), support vector machine (SVM), random forest (RF), and logistic regression (LR) were used for modeling; fivefold cross-validation was used to train the model; the validation group was used to evaluate and assess the predictive performance of the model, ROC curve was used to calculate the accuracy, sensitivity, and specificity of the model, and the area under curve (AUC) was used to assess the predictive performance of the model.

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Purpose: To investigate the value of multimodal diffusion weighted imaging (DWI) in preoperative evaluation of Ki-67 expression of endometrial carcinoma (EC).

Materials And Methods: Patients who had undergone pelvic DWI, intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI) sequence MRI scan before surgery were retrospectively enrolled. Single index model, double index model, and DKI were used for post-processing of the DWI data, and the apparent diffusion coefficient (ADC), real diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f), non-Gaussian mean diffusion kurtosis (MK), mean diffusion coefficient (MD) and anisotropy fraction (FA) were calculated and compared between the Ki-67 high (≥50%) and low (<50%) expression groups.

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Objective: To analyze the important effect of 3D printing personalized lumbar support on lumbar pain and lumbar function in patients with lumbar disc herniation.

Methods: From October 2018 to May 2021, 60 patients initially diagnosed with lumbar disc herniation were selected and divided into an observation group and a control group, with 30 patients in each group. Among them, there were 18 males and 12 females in the observation group;the age ranged from 24 to 56 years old, with an average of (45.

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Methylation at the C5 position of cytosine, a naturally occurring epigenetic modification on DNA, shows a high correlation with mutational hotspots in disease such as skin cancer. Due to its essential biological relevance, numerous studies were devoted to confirming that the methylated sites favor the formation of the cyclobutane pyrimidine dimer (CPD), a well-known UV-induced lesion. However, photophysical and photochemical properties of dinucleotides and polynucleotides containing 5-methylcytosine (C) remain elusive.

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In silico investigations of enzymatic reactions and chemical reactions in condensed phases often suffer from formidable computational costs due to a large number of degrees of freedom and enormous important volume in phase space. Usually, accuracy must be compromised to trade for efficiency by lowering the reliability of the Hamiltonians employed or reducing the sampling time. Reference-potential methods (RPMs) offer an alternative approach to reaching high accuracy of simulation without much loss of efficiency.

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Background: This study investigated the value of a deep learning (DL) model based on computed tomography (CT) enhancement for predicting human epidermal growth factor receptor 2 (HER2) expression in patients with liver metastasis from breast cancer.

Methods: Data were collected for 151 female patients with liver metastasis from breast cancer who underwent abdominal enhanced CT examination in the Department of Radiology at the Affiliated Hospital of Hebei University between January 2017 and March 2022. Liver metastases were confirmed in all patients by pathology.

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Complex polysaccharides (e.g. cellulose, xylan, and chitin), the most abundant renewable biomass resources available on Earth, are mainly degraded by microorganisms in nature.

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