Using neutrons to ascertain the impact of deposition temperature on amorphous solid water.

Amorphous solid water (ASW), formed vapour deposition under low temperature and pressure conditions, has been the focus of physical- and astro-chemists for some time as it represents the most likely formation process for interstellar ices. The porous structure of ASW has been found to be significantly impacted by deposition conditions, with little literature on the specific impacts of deposition temperature. This work utilises total neutron scattering (TNS) and small angle neutron scattering (SANS) to provide direct experimental evidence that deposition temperature does indeed have a significant impact on the structure of grown ASW.

DNA-directed immobilization fluorescent immunoarray for multiplexed antibiotic residue determination in milk.

The presence of antibiotic residues in cow's milk entails high risk for consumers, the dairy industry, and the environment. Therefore, the development of highly specific and sensitive screening tools for the rapid and cost-effective identification of traces of these compounds is urgently needed. A multiplexed screening platform utilizing DNA-directed immobilization (DDI) was developed aiming to detect three classes of antibiotic residues (fluoroquinolones, sulfonamides, and tylosin) prevalently found in milk.

Decrease in Mortality after the Implementation of a Hospital Model to Improve Performance in Sepsis Care: Princess Sepsis Code.

Sepsis is a time-dependent disease whose prognosis is influenced by early diagnosis and therapeutic measures. Mortality from sepsis remains high, and for this reason, the guidelines of the Surviving Sepsis Campaign recommend establishing specific care programs aimed at patients with sepsis. We present the results of the application of a hospital model to improve performance in sepsis care, called , with the aim of reducing mortality.

Generative models for protein sequence modeling: recent advances and future directions.

The widespread adoption of high-throughput omics technologies has exponentially increased the amount of protein sequence data involved in many salient disease pathways and their respective therapeutics and diagnostics. Despite the availability of large-scale sequence data, the lack of experimental fitness annotations underpins the need for self-supervised and unsupervised machine learning (ML) methods. These techniques leverage the meaningful features encoded in abundant unlabeled sequences to accomplish complex protein engineering tasks.

Generation of synthetic intermediate slices in 3D OCT cubes for improving pathology detection and monitoring.

OCT is a non-invasive imaging technique commonly used to obtain 3D volumes of the ocular structure. These volumes allow the monitoring of ocular and systemic diseases through the observation of subtle changes in the different structures present in the eye. In order to observe these changes it is essential that the OCT volumes have a high resolution in all axes, but unfortunately there is an inverse relationship between the quality of the OCT images and the number of slices of the cube.