AIMC Topic: Humans

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A novel potential biomarker panel to diagnose depression derived from big proteomic data.

Journal of affective disorders
BACKGROUND: There is still no clinical biomarker to diagnose depression. Given the complexity of a multifactorial disease like depression, a single biomarker is unlikely to capture the full heterogeneity of the disease and be applicable in clinical p...

Cervical cancer diagnostics: non-coding RNAs and biosensors to AI-derived methods.

Clinica chimica acta; international journal of clinical chemistry
Cervical cancer ranks fourth in terms of cancer mortality among women. The most important risk factor for cervical cancer is infection with HPV 16 and HPV 18. The prevalence and mortality rates of this cancer are much higher in countries with low and...

Virtual screening of salty peptides from enzymatic and fermented products of wheat gluten and its molecular mechanism of interaction with TMC4 receptor.

Food chemistry
The health risks associated with excessive sodium intake have prompted an exploration of natural salt substitutes. This study was oriented to explore the salty peptides from enzymatic and fermented products of wheat gluten (WG) with different degrees...

AbDesign: database of point mutants of antibodies with associated structures reveals poor generalization of binding predictions from machine learning models.

mAbs
Antibodies are naturally evolved molecular recognition scaffolds that can bind a variety of surfaces. Their designability is crucial to the development of biologics, with computational methods holding promise in accelerating the delivery of medicines...

Understanding the relationship between rosemary odor and mental workload through deep learning.

Neuroscience
This research explores the novel application of aromatic odors, specifically rosemary, in reducing mental workload, employing deep learning methods to analyze electroencephalogram (EEG) signals without feature extraction. Thirty volunteers participat...

A machine learning-based predictive model for multilobar pulmonary consolidation induced by macrolide-resistant pneumonia caused by the 23S rRNA A2063G mutation.

Microbiology spectrum
This study aims to develop a machine learning (ML)-based predictive model for assessing the risk of multilobar pulmonary consolidation in children with macrolide-resistant pneumonia (MRMP) caused by the 23S rRNA A2063G mutation, a subgroup underrepr...

Ionizable Lipid Nanoparticles for mRNA Delivery: Internal Self-Assembled Inverse Mesophase Structure and Endosomal Escape.

Accounts of chemical research
ConspectusThe clinical use of mRNA COVID-19 vaccines developed by Moderna and Pfizer-BioNTech has highlighted the critical role of ionizable lipid nanoparticles (LNPs) in the efficient loading, intracellular delivery, and cytoplasmic release of mRNAs...

Robust myocardium detection and scar severity classification in LGE-CMR using ScarYOLO and contrastive learning.

European journal of medical research
Late gadolinium enhancement cardiac magnetic resonance (LGE-CMR) imaging plays a crucial role in assessing myocardial scar tissues, aiding in the diagnosis and prognosis of cardiovascular diseases. However, accurately classifying scar tissue severity...

Developing an explainable machine learning model to predict false-negative citrin deficiency cases in newborn screening.

Orphanet journal of rare diseases
BACKGROUND: Neonatal Intrahepatic Cholestasis caused by Citrin Deficiency (NICCD) is an autosomal recessive disorder affecting the urea cycle and energy metabolism. Newborn screening (NBS) usually relies on elevated citrulline, but some patients have...