COVID-19

Electrophysiological-based automatic subgroups diagnosis of patients with chronic dysimmune polyneuropathies.

BACKGROUND: Chronic Dysimmune Polyneuropathies (CDP) encompass a group of conditions characterized by autoimmune etiology targeting myelin and/or axonal components. Subgroups include Chronic Inflammatory Demyelinating Polyneuropathy (CIDP) and paraproteinemic neuropathies associated with IgM monoclonal gammopathy of undetermined significance, with anti-MAG antibodies (IgM-MGUS anti-MAG+) and witho...

Predicting the Effects of Charge Mutations on the Second Osmotic Virial Coefficient for Therapeutic Antibodies via Coarse-Grained Molecular Simulations and Deep Learning Methods.

The impact of various charge mutations on the second osmotic virial coefficient was examined for three model therapeutic monoclonal antibodies (MAbs) at representative formulation pH values by using coarse-grained (CG) molecular modeling. The wild-type of each mAb was characterized experimentally in previous work, showing a range of behaviors spanning from weak protein self-interactions to strong ...

The evolving therapeutic landscape of Graves' disease in adults: present and future.

The therapeutic landscape of Graves' hyperthyroidism has been rapidly evolving in the last few years. There has been a shift worldwide towards antithy...

AQP9 and IFITM1 as drivers of immune infiltration and tumor progression in IBD-associated colorectal cancer: from computational insights to experimental validation.

Inflammatory bowel disease (IBD) is a chronic inflammatory disorder of the gastrointestinal tract associated with an increased risk of colorectal canc...

Identification and validation of glucocorticoid receptor and programmed cell death-related genes in spinal cord injury using machine learning.

Spinal cord injury (SCI) is a severe neurological disorder, with glucocorticoids like methylprednisolone commonly used for treatment. However, their e...

Advancements in Tuberculosis Diagnostics: An Update.

Tuberculosis (TB) is one of the major life-threatening diseases caused by a single pathogen which has become a social menace owing to its high resista...

Artificial Intelligence Software Changes Rare Disease Testing Strategy in Real Time: An International Case Series Using Face2Gene.

Genetic disorders commonly share features such as developmental delays, cognitive impairment, and behavioral challenges, yet many conditions also pres...

Rapid identification of Litopenaeus vannamei pathogenic bacteria: a combined approach using surface-enhanced Raman spectroscopy (SERS) and deep learning.

Pathogenic bacterial infections are one of the leading causes of mortality in Litopenaeus vannamei, seriously affecting the economic efficiency of the...

RSLpred2: An Integrated Web Server for the Annotation of Rice Proteome Subcellular Localization Using Deep Learning.

Rice is one of the most important staple crops, providing food for more than one-half of the world's population worldwide. Identifying the localizatio...

Multiomic integration reveals subtype-specific predictors of neoadjuvant treatment response in breast cancer.

Neoadjuvant therapy has been widely used in breast cancer, but treatment response varies among individuals. We conducted multiomic profiling on tumor ...

AI assistance enhances histopathologic distinction between sebaceous and squamous cell carcinoma of the eyelid.

Sebaceous gland carcinoma (SGC) and some poorly differentiated squamous cell carcinomas (SC) of the eyelid may have overlapping clinical and histopath...

Estimation of soil free Iron content using spectral reflectance and machine learning algorithms.

Spectral reflectance technology has emerged as a promising tool for estimating soil properties while offering a rapid, non-destructive, and cost-effec...

D-optimal candexch algorithm-enhanced machine learning UV-spectrophotometry for five-analyte determination in novel anti-glaucoma formulations and ocular fluids: four-color sustainability framework with NQS assessment and UN-SDG integration.

The novel anti-glaucoma ophthalmic preparation containing latanoprost, netarsudil, and benzalkonium chloride has posed a significant challenge due to ...

Identification of proliferating neural progenitors in the adult human hippocampus.

Continuous adult hippocampal neurogenesis is involved in memory formation and mood regulation but is challenging to study in humans. Difficulties find...

Machine learning-based prediction of celiac antibody seropositivity by biochemical test parameters.

The diagnostic delay in celiac disease (CD) is currently a burden for individual and society. Biochemical tests may be used in risk-identification of ...

Smart-Plexer 2.0: Leveraging New Features of Amplification Curves to Enhance the Selection of Multiplex PCR Assays in Multi-Target Identification.

Multiplex PCR plays a critical role in diagnostics by enabling the detection of multiple targets in a single reaction. However, its use is often limit...

Leveraging protein language models for cross-variant CRISPR/Cas9 sgRNA activity prediction.

MOTIVATION: Accurate prediction of single-guide RNA (sgRNA) activity is crucial for optimizing the CRISPR/Cas9 gene-editing system, as it directly inf...

Multimodal nomogram integrating deep learning radiomics and hemodynamic parameters for early prediction of post-craniotomy intracranial hypertension.

To evaluate the effectiveness of deep learning radiomics nomogram in distinguishing early intracranial hypertension (IH) following primary decompressi...

DCAF13 Regulates Cell Proliferation and Immune Escape of Hepatocellular Carcinoma Through Activating the NF-κB Pathway.

Hepatocellular carcinoma (HCC), the third leading cause of global cancer deaths, has a high unmet clinical need due to limited therapeutic efficacy. I...

Integrating CT radiomics and clinical features using machine learning to predict post-COVID pulmonary fibrosis.

BACKGROUND: The lack of reliable biomarkers for the early detection and risk stratification of post-COVID-19 pulmonary fibrosis (PCPF) underscores the...