Allergy & Immunology

Prediction of lipid nanoparticles for mRNA vaccines by the machine learning algorithm.

Lipid nanoparticle (LNP) is commonly used to deliver mRNA vaccines. Currently, LNP optimization primarily relies on screening ionizable lipids by traditional experiments which consumes intensive cost and time. Current study attempts to apply computational methods to accelerate the LNP development for mRNA vaccines. Firstly, 325 data samples of mRNA vaccine LNP formulations with IgG titer were coll...

Rapid detection of using magnetic nanobead-based immunoseparation and quantum dot-based immunofluorescence.

In recent years, the scale of population exposure and food poisoning caused by () has shown a significant upward trend, becoming one of the primary food-borne pathogens. Herein, we developed a rapid and sensitive detection of by integrating the technology of magnetic nanobeads (MBs) based immunoseparation (IMS) with quantum dots (QDs) based immunofluorescence. Firstly, specific rabbit polyclone ...

Long-term safety and efficacy of rilpivirine in combination with nucleoside/nucleotide reverse transcriptase inhibitors in HIV-1 infected patients: 336-week rollover study of phase 2b and 3 clinical studies.

BACKGROUND: To evaluate the long-term safety and efficacy of rilpivirine (RPV), a non-nucleoside reverse transcriptase inhibitor (NNRTI), in combinati...

Deep learning model enables the discovery of a novel immunotherapeutic agent regulating the kynurenine pathway.

Kynurenine (Kyn) is a key inducer of an immunosuppressive tumor microenvironment (TME). Although indoleamine 2,3-dioxygenase (IDO)-selective inhibitor...

Genes and regulatory mechanisms associated with experimentally-induced bovine respiratory disease identified using supervised machine learning methodology.

Bovine respiratory disease (BRD) is a multifactorial disease involving complex host immune interactions shaped by pathogenic agents and environmental ...

A Study of the Recent Trends of Immunology: Key Challenges, Domains, Applications, Datasets, and Future Directions.

The human immune system is very complex. Understanding it traditionally required specialized knowledge and expertise along with years of study. Howeve...

Detecting immunotherapy-sensitive subtype in gastric cancer using histologic image-based deep learning.

Immune checkpoint inhibitor (ICI) therapy is widely used but effective only in a subset of gastric cancers. Epstein-Barr virus (EBV)-positive and micr...

Classification of renal biopsy direct immunofluorescence image using multiple attention convolutional neural network.

BACKGROUND AND OBJECTIVES: Direct immunofluorescence (DIF) is an important medical evaluation tool for renal pathology. In the DIF images, the deposit...

Imaging flow cytometry data analysis using convolutional neural network for quantitative investigation of phagocytosis.

Macrophages play an important role in the adaptive immune system. Their ability to neutralize cellular targets through Fc receptor-mediated phagocytos...

Development and validation of a supervised deep learning algorithm for automated whole-slide programmed death-ligand 1 tumour proportion score assessment in non-small cell lung cancer.

AIMS: Immunohistochemical programmed death-ligand 1 (PD-L1) staining to predict responsiveness to immunotherapy in patients with advanced non-small ce...

Advanced Recovery and High-Sensitive Properties of Memristor-Based Gas Sensor Devices Operated at Room Temperature.

Fast recovery, high sensitivity, high selectivity, and room temperature (RT) sensing characteristics of NO gas sensors are essential for environmental...

iDHS-DT: Identifying DNase I hypersensitive sites by integrating DNA dinucleotide and trinucleotide information.

DNase I hypersensitive sites (DHSs) is important for identifying the location of gene regulatory elements, such as promoters, enhancers, silencers, an...

Identification of asthma control factor in clinical notes using a hybrid deep learning model.

BACKGROUND: There are significant variabilities in guideline-concordant documentation in asthma care. However, assessing clinician's documentation is ...

Machine learning implicates the IL-18 signaling axis in severe asthma.

Asthma is a common disease with profoundly variable natural history and patient morbidity. Heterogeneity has long been appreciated, and much work has ...

The viral expression and immune status in human cancers and insights into novel biomarkers of immunotherapy.

BACKGROUND: Viral infections are prevalent in human cancers and they have great diagnostic and theranostic values in clinical practice. Recently, thei...

Predicting response to immunotherapy plus chemotherapy in patients with esophageal squamous cell carcinoma using non-invasive Radiomic biomarkers.

OBJECTIVES: To develop and validate a radiomics model for evaluating treatment response to immune-checkpoint inhibitor plus chemotherapy (ICI + CT) in...

Deep Learning Algorithms-Based CT Images in Glucocorticoid Therapy in Asthma Children with Small Airway Obstruction.

CT image information data under deep learning algorithms was adopted to evaluate small airway function and analyze the clinical efficacy of different ...

Correlation of serum microRNA-122 level with the levels of Alanine aminotransferase and HBV-DNA in Chronic HBV-infected patients.

The microRNA-122 (miR-122) is a liver-specific microRNA that can be used as a potential molecular marker for predicting liver injury. There is a posi...

Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy.

Cancer immunotherapy provides durable clinical benefit in only a small fraction of patients, and identifying these patients is difficult due to a lack...

Content-based Image Retrieval by Using Deep Learning for Interstitial Lung Disease Diagnosis with Chest CT.

Background Evaluation of interstitial lung disease (ILD) at CT is a challenging task that requires experience and is subject to substantial interreade...