A Retrospective and Prospective Cohort Study Comparing Pediatric Patients With Cleft Lip and Palate From the United States and Guatemala.

Orofacial clefts (OFC) remain among the most prevalent congenital abnormalities worldwide. In the United States in 2010 to 2014, 16.2 of 10,000 live births are born with OFC compared with 23.

Antimicrobial Activity of Five Apitoxins from on Two Common Foodborne Pathogens.

Antimicrobial resistance is one of today's major public health challenges. Infections caused by multidrug-resistant bacteria have been responsible for an increasing number of deaths in recent decades. These resistant bacteria are also a concern in the food chain, as bacteria can resist common biocides used in the food industry and reach consumers.

Crowdsourcing pneumothorax annotations using machine learning annotations on the NIH chest X-ray dataset.

Pneumothorax is a potentially life-threatening condition that requires prompt recognition and often urgent intervention. In the ICU setting, large numbers of chest radiographs are performed and must be interpreted on a daily basis which may delay diagnosis of this entity. Development of artificial intelligence (AI) techniques to detect pneumothorax could help expedite detection as well as localize and potentially quantify pneumothorax.

Antimicrobial activity of apitoxin from Apis mellifera in Salmonella enterica strains isolated from poultry and its effects on motility, biofilm formation and gene expression.

Salmonella is a major global food-borne pathogen. One of the main concerns related to Salmonella and other food-borne pathogens is their capacity to acquire antimicrobial resistance and produce biofilms. Due to the increased resistance to common antimicrobials used to treat livestock animals and human infections, the discovery of new antimicrobial substances is one of the main challenges in microbiological research.

Augmenting the National Institutes of Health Chest Radiograph Dataset with Expert Annotations of Possible Pneumonia.

This dataset is intended to be used for machine learning and is composed of annotations with bounding boxes for pulmonary opacity on chest radiographs which may represent pneumonia in the appropriate clinical setting.