Predicting health outcomes in dogs using insurance claims data.

In this paper we propose a machine learning-based approach to predict a multitude of insurance claim categories related to canine diseases. We introduce several machine learning approaches that are evaluated on a pet insurance dataset consisting of 785,565 dogs from the US and Canada whose insurance claims have been recorded over 17 years. 270,203 dogs with a long insurance tenure were used to train a model while the inference is applicable to all dogs in the dataset.

Ageing-associated changes in transcriptional elongation influence longevity.

Physiological homeostasis becomes compromised during ageing, as a result of impairment of cellular processes, including transcription and RNA splicing. However, the molecular mechanisms leading to the loss of transcriptional fidelity are so far elusive, as are ways of preventing it. Here we profiled and analysed genome-wide, ageing-related changes in transcriptional processes across different organisms: nematodes, fruitflies, mice, rats and humans.

Impact of Regional Block Failure in Ambulatory Hand Surgery on Patient Management: A Cohort Study.

Regional anesthesia (RA) is an anesthetic technique essential for the performance of ambulatory surgery. Failure rates range from 6% to 20%, and the consequences of these failures have been poorly investigated. We determined the incidence and the impact of regional block failure on patient management in the ambulatory setting.

The proteome microenvironment determines the protective effect of preconditioning in cisplatin-induced acute kidney injury.

Acute kidney injury (AKI) leads to significant morbidity and mortality; unfortunately, strategies to prevent or treat AKI are lacking. In recent years, several preconditioning protocols have been shown to be effective in inducing organ protection in rodent models. Here, we characterized two of these interventions-caloric restriction and hypoxic preconditioning-in a mouse model of cisplatin-induced AKI and investigated the underlying mechanisms by acquisition of multi-layered omic data (transcriptome, proteome, N-degradome) and functional parameters in the same animals.

Accuracy of patient's turnover time prediction using RFID technology in an academic ambulatory surgery center.

Patients flow in outpatient surgical unit is a major issue with regards to resource utilization, overall case load and patient satisfaction. An electronic Radio Frequency Identification Device (RFID) was used to document the overall time spent by the patients between their admission and discharge from the unit. The objective of this study was to evaluate how a RFID-based data collection system could provide an accurate prediction of the actual time for the patient to be discharged from the ambulatory surgical unit after surgery.