Towards a standardized framework for AI-assisted, image-based monitoring of nocturnal insects.

Automated sensors have potential to standardize and expand the monitoring of insects across the globe. As one of the most scalable and fastest developing sensor technologies, we describe a framework for automated, image-based monitoring of nocturnal insects-from sensor development and field deployment to workflows for data processing and publishing. Sensors comprise a light to attract insects, a camera for collecting images and a computer for scheduling, data storage and processing. Metadata is important to describe sampling schedules that balance the capture of relevant ecological information against power and data storage limitations. Large data volumes of images from automated systems necessitate scalable and effective data processing. We describe computer vision approaches for the detection, tracking and classification of insects, including models built from existing aggregations of labelled insect images. Data from automated camera systems necessitate approaches that account for inherent biases. We advocate models that explicitly correct for bias in species occurrence or abundance estimates resulting from the imperfect detection of species or individuals present during sampling occasions. We propose ten priorities towards a step-change in automated monitoring of nocturnal insects, a vital task in the face of rapid biodiversity loss from global threats. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Urinary excretion of enzymes in cirrhotics with renal failure.

We studied the significance of urinary enzyme measurements in diagnosing proximal tubular damage in cirrhosis of the liver. Urinary excretion (u-enzyme) and fractional urinary excretion (FEenzyme) of gamma-glutamyltranspeptidase (GGT), leucine aminopeptidase (LAP), alkaline phosphatase (AP) and beta-glucuronidase (B-GLU) were quantified in 14 control subjects (group I), 12 cirrhotics with functional renal failure (group II), 13 cirrhotics with renal tubular damage (group III) and 7 non-liver patients with renal tubular damage (group IV). Urinary enzyme excretion and fractional enzyme excretion were significantly higher in the cirrhotics of group III than in the controls or group II. In group III, these tests usually reached values within the range of group IV. The sensitivity of urinary enzyme excretion was 0.92 and specificity ranged from 0.75 (u-LAP) to 1 (u-GGT; u-B-GLU). The sensitivity of fractional enzyme excretion was between 0.61 (FEB-GLU) and 0.84 (FEGGT; FELAP), while specificity was from 0.91 (FELAP; FEAP) to 1 (FEGGT; FEB-GLU). The results indicate that measurement of urinary enzymes may be very useful in diagnosing renal tubular damage in cirrhotic patients with impaired renal function.