Deep learning increases the availability of organism photographs taken by citizens in citizen science programs.

Citizen science programs using organism photographs have become popular, but there are two problems related to photographs. One problem is the low quality of photographs. It is laborious to identify species in photographs taken outdoors because they are out of focus, partially invisible, or under different lighting conditions. The other is difficulty for non-experts to identify species. Organisms usually have interspecific similarity and intraspecific variation, which hinder species identification by non-experts. Deep learning solves these problems and increases the availability of organism photographs. We trained a deep convolutional neural network, Xception, to identify bee species using various quality of bee photographs that were taken by citizens. These bees belonged to two honey bee species and 10 bumble bee species with interspecific similarity and intraspecific variation. We investigated the accuracy of species identification by biologists and deep learning. The accuracy of species identification by Xception (83.4%) was much higher than that of biologists (53.7%). When we grouped bee photographs by different colors resulting from intraspecific variation in addition to species, the accuracy of species identification by Xception increased to 84.7%. The collaboration with deep learning and experts will increase the reliability of species identification and their use for scientific researches.

The sole rupture of flexor digitorum tendons to the index finger following volar locking plate fixation of distal radius fracture: A case report.

Distal radius fracture is a common injury, especially in elderly people, and internal fixation with volar locking plate (VLP) is becoming an increasingly popular technique for the management of displaced and/or unstable distal radius fractures. One of the most common complications of this treatment is the flexor tendon rupture, mostly of the flexor pollicis longus (FPL). While the rupture of flexor digitorum tendons to the index (FDI) mostly occurs concomitantly with the rupture of FPL after the treatment using volar plating for distal radial fracture, sole rupture of the FDI without FPL rupture is very rare. Here, we report a case of the sole rupture of FDI after volar locking plating and analyze its pathogenesis indicating that the lift-up of the distal ulnar edge of the plate related to the malcorrection of the fracture site is the culprit for this specific complication.

[Pharmacokinetics and safety of dolutegravir in healthy Japanese subjects].

Dolutegravir (DTG) is a once-daily, unboosted integrase inhibitor that has been shown to be effective by once daily dosing. The impact of race on dolutegravir pharmacokinetics has not yet been fully characterized. This study was a Phase 1, open label, single dose study to determine pharmacokinetics (PK), safety and tolerability of DTG following 50mg single oral administration in the fasted state in healthy adult Japanese subjects. Subjects had a screening visit within 30 days prior to the administration of study drug, and a follow-up visit within 7 to 14 days after the administration of study drug. Safety evaluation and serial PK samplings were performed pre-dose and for 72 hours after dosing. Non-compartmental analysis was performed for PK parameter calculation. Data were compared to historical values from a similar Phase 1 study conducted in non-Asian, healthy adult subjects (n = 18, 17 Caucasian and 1 Arabic/North African). Ten subjects were enrolled and completed the study. DTG was well tolerated with no adverse events reported throughout the study period. Geometric means (CV%) of single dose DTG PK parameters in Japanese subjects for C(max), AUC(inf), t1/2 and C24 were 2.14microg/mL (47%), 43.4 microg x hr/mL (46%), 14.6 hours (10%) and 0.67 microg/mL (45%). The pharmacokinetics and safety profiles of DTG following single dose oral administration to Japanese healthy adult subjects were consistent with findings previously observed in non-Japanese healthy adult subjects. DTG may be given to Japanese subjects without dose-adjustment.

Applying geographic profiling used in the field of criminology for predicting the nest locations of bumble bees.

We tested whether geographic profiling (GP) can predict multiple nest locations of bumble bees. GP was originally developed in the field of criminology for predicting the area where an offender most likely resides on the basis of the actual crime sites and the predefined probability of crime interaction. The predefined probability of crime interaction in the GP model depends on the distance of a site from an offender's residence. We applied GP for predicting nest locations, assuming that foraging and nest sites were the crime sites and the offenders' residences, respectively. We identified the foraging and nest sites of the invasive species Bombus terrestris in 2004, 2005, and 2006. We fitted GP model coefficients to the field data of the foraging and nest sites, and used GP with the fitting coefficients. GP succeeded in predicting about 10-30% of actual nests. Sensitivity analysis showed that the predictability of the GP model mainly depended on the coefficient value of buffer zone, the distance at the mode of the foraging probability. GP will be able to predict the nest locations of bumble bees in other area by using the fitting coefficient values measured in this study. It will be possible to further improve the predictability of the GP model by considering food site preference and nest density.