TLE4 is a repressor of the oncogenic activity of TLX3 in T-cell acute lymphoblastic leukemia.

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematological disease originating from the malignant transformation of T-cell progenitors, caused by the accumulation of genetic aberrations. One-fifth of T-ALL patients are characterized by ectopic expression of the homeobox transcription factor TLX3. However, the role of TLX3 in T-ALL remains elusive, partly due to the lack of suitable study models.

Predicting doxorubicin-induced cardiotoxicity in breast cancer: leveraging machine learning with synthetic data.

Doxorubicin (DOXO) is a primary treatment for breast cancer but can cause cardiotoxicity in over 25% of patients within the first year post-chemotherapy. Recognizing at-risk patients before DOXO initiation offers pathways for alternative treatments or early protective actions. We analyzed data from 78 Brazilian breast cancer patients, with 34.

Neurodevelopment in the first year of children exposed to SARS-CoV-2 during intrauterine period: systematic review.

Objective: To identify, in the literature, the implications of gestational exposure to SARS-CoV-2 on neurodevelopment in the first postnatal year, focusing on changes in the motor, personal-social, socio-emotional, and communication and language domains.

Method: Systematic review with narrative synthesis, considering neurodevelopmental outcomes, categorized according to gross and fine motor skills, personal-social interaction, socio-emotional aspects, and communication and language. Searches were conducted in PubMed, LILACS/BIREME, and EMBASE databases between January 2020 and June 2023.

Complete blood count as a biomarker for preeclampsia with severe features diagnosis: a machine learning approach.

Objective: This study introduces the complete blood count (CBC), a standard prenatal screening test, as a biomarker for diagnosing preeclampsia with severe features (sPE), employing machine learning models.

Methods: We used a boosting machine learning model fed with synthetic data generated through a new methodology called DAS (Data Augmentation and Smoothing). Using data from a Brazilian study including 132 pregnant women, we generated 3,552 synthetic samples for model training.

Carbon Nanomaterials with SOD-like Activity: The Effect of the Ionic Strength.

Electrogenerated hydrophilic carbon (EHC) nanomaterials emerge as a highly attractive option for mimicking the activity of the superoxide dismutase enzyme (SOD) due to their exceptional water solubility and electron-transfer reversibility. Motivated by these properties, the EHC nanomaterials were utilized to assess the effect of ionic strength on the SOD-like activity. Superoxide anion radicals (O) were generated using the hypoxanthine-xanthine oxidase system, with nitro blue tetrazolium chloride serving as the detecting system.