Teal Health has introduced the Teal Wand, the first FDA-authorized at-home cervical cancer screening kit in the US, starting in California. The kit, which includes a telehealth component, uses a self-collected sample for HPV testing with Roche's cobas HPV test. A clinical trial found that 94% of women preferred the Teal Wand over in-office Pap smears.

A study in the journal Frontiers in Medicine involving 26 patients examined the use of 18F-FDG PET/CT metabolic parameters, genetic markers and clinical characteristics to evaluate treatment efficacy and prognosis in Langerhans cell histiocytosis. The study found that high values of metabolic parameters were associated with disease progression or recurrence.

Athena Diagnostics has introduced a laboratory-developed test to identify genetic causes of ataxia, a movement disorder. The test targets long DNA sequences with repeating patterns, which are often missed by conventional sequencing. Developed with PacBio's PureTarget technology, the test follows initial screening with polymerase chain reaction testing and is available through Athena Diagnostics.

Researchers have developed a model using electronic health record data to predict patients' risk of developing multiple myeloma within five years, potentially allowing earlier intervention. The model, detailed in the British Journal of Hematology, uses clinical and laboratory parameters and has the potential to shift the treatment paradigm for the condition.

A study in Cardiovascular Diabetology describes a machine learning model that uses blood biomarkers to predict vulnerable carotid plaques, highlighting sex-specific risk patterns. The Random Forest model, which had an area under the curve of 0.847, identified gender, age, and several biomarkers as top predictors.

A study in the journal Communications Engineering highlights how machine learning combined with spectroscopic imaging can improve biomedical research. Researchers at Zhejiang University found the approach may allow for faster and more precise analysis of complex molecular data.

Researchers at St. Jude Children's Research Hospital used AI to design more effective bi-specific chimeric antigen receptor T cells, addressing challenges such as poor CAR expression and suboptimal cancer-killing properties. The method, described in the journal Molecular Therapy, optimized the structure of the CAR's variable regions, leading to greater cell surface expression and enhanced tumor-killing ability.

Researchers have developed generative AI models that create new antibiotics capable of combating multidrug-resistant bacteria. The models produced two lead compounds, NG1 and DN1, which showed effectiveness against resistant strains of gonorrhea and methicillin-resistant Staphylococcus aureus. The research, published in Cell, involved a collaboration with Phare Bio to advance these candidates toward clinical use.

A study in the journal Clinica Chimica Acta suggests that artificial intelligence combined with liquid biopsy could improve early detection of gastrointestinal cancers by increasing the sensitivity and specificity of diagnostics. The researchers noted that liquid biopsy is a promising noninvasive method for cancer detection but requires advanced analytical techniques to interpret complex data.