Pediatric Bone Age Assessment Using Deep Convolutional Neural Networks

Skeletal bone age assessment is a common clinical practice to diagnose endocrine and metabolic disorders in child development. In this paper, we describe a fully automated deep learning approach to the problem of bone age assessment using data from Pediatric Bone Age Challenge organized by RSNA 2017. The dataset for this competition is consisted of 12.6k radiological images of left hand labeled by the bone age and sex of patients. Our approach utilizes several deep learning architectures: U-Net, ResNet-50, and custom VGG-style neural networks trained end-to-end. We use images of whole hands as well as specific parts of a hand for both training and inference. This approach allows us to measure importance of specific hand bones for the automated bone age analysis. We further evaluate performance of the method in the context of skeletal development stages. Our approach outperforms other common methods for bone age assessment.Comment: 14 pages, 9 figure

SICI during changing brain states: Differences in methodology can lead to different conclusions

Background: Short-latency intracortical inhibition (SICI) is extensively used to probe GABAergic inhibitory mechanisms in M1. Task-related changes in SICI are presumed to reflect changes in the central excitability of GABAergic pathways. Usually, the level of SICI is evaluated using a single intensity of conditioning stimulus so that inhibition can be compared in different brain states. Objective: Here, we show that this approach may sometimes be inadequate since distinct conclusions can be drawn if a different CS intensity is used. Methods: We measured SICI using a range of CS intensities at rest and during a warned simple reaction time task. Conclusions: Our results show that SICI changes that occurred during the task could be either larger or smaller than at rest depending on the intensity of the CS. These findings indicate that careful interpretation of results are needed when a single intensity of CS is used to measure task-related physiological changes

MIDGARD: A Simulation Platform for Autonomous Navigation in Unstructured Environments

We present MIDGARD, an open-source simulation platform for autonomous robot navigation in outdoor unstructured environments. MIDGARD is designed to enable the training of autonomous agents (e.g., unmanned ground vehicles) in photorealistic 3D environments, and to support the generalization skills of learning-based agents through the variability in training scenarios. MIDGARD's main features include a configurable, extensible, and difficulty-driven procedural landscape generation pipeline, with fast and photorealistic scene rendering based on Unreal Engine. Additionally, MIDGARD has built-in support for OpenAI Gym, a programming interface for feature extension (e.g., integrating new types of sensors, customizing exposing internal simulation variables), and a variety of simulated agent sensors (e.g., RGB, depth and instance/semantic segmentation). We evaluate MIDGARD's capabilities as a benchmarking tool for robot navigation utilizing a set of state-of-the-art reinforcement learning algorithms. The results demonstrate MIDGARD's suitability as a simulation and training environment, as well as the effectiveness of our procedural generation approach in controlling scene difficulty, which directly reflects on accuracy metrics. MIDGARD build, source code and documentation are available at https://midgardsim.org/

The assessment and the within-plant variation of the morpho-physiological traits and VOCs profile in endemic and rare Salvia ceratophylloides Ard. (Lamiaceae)

Salvia ceratophylloides (Ard.) is an endemic and rare plant species recently rediscovered as very few individuals at two different Southern Italy sites. The study of within-plant variation is fundamental to understand the plant adaptation to the local conditions, especially in rare species, and consequently to preserve plant biodiversity. Here, we reported the variation of the morpho-ecophysiological and metabolic traits between the sessile and petiolate leaf of S. ceratophylloides plants at two different sites for understanding the adaptation strategies for surviving in these habitats. The S. ceratophylloides individuals exhibited different net photosynthetic rate, maximum quantum yield, light intensity for the saturation of the photosynthetic machinery, stomatal conductance, transpiration rate, leaf area, fractal dimension, and some volatile organic compounds (VOCs) between the different leaf types. This within-plant morpho-physiological and metabolic variation was dependent on the site. These results provide empirical evidence of sharply within-plant variation of the morpho-physiological traits and VOCs profiles in S. ceratophylloides, explaining the adaptation to the local conditions

Analysis of the muscarinic receptor subtype mediating inhibition of the neurogenic contractions in rabbit isolated vas deferens by a series of polymethylene tetra-amines

1. The pharmacological characteristics of the presynaptic muscarinic receptor subtype, which mediates inhibition of the neurogenic contractions in the prostatic portion of rabbit vas deferens, have been investigated by using a series of polymethylene tetra-amines, which were selected for their ability to differentiate among muscarinic receptor subtypes. 2. It was found that all tetra-amines antagonized McN-A-343-induced inhibition in electrically stimulated rabbit vas deferens in a competitive manner and with affinity values (pA2) ranging between 6.27 ± 0.09 (spirotramine) and 8.51 ± 0.02 (AM170). 3. Competition radioligand binding studies, using native muscarinic receptors from rat tissues (M1, cortex; M2, heart; M3, submaxillary gland) or from NG 108-15 cells (M4) and human cloned muscarinic M1-M4 receptors expressed in CHO-K1 cells, were undertaken with the same tetraamines employed in functional assays. All antagonists indicated a one-site fit. 4. The affinity estimates (pKi) of tetra-amines calculated in binding assays using native receptors were similar to those obtained using cloned receptors. Among these compounds some displayed selectivity between muscarinic receptor subtypes, indicating that they may be valuable tools in receptor characterization. Spirotramine was selective for M1 receptors versus all other subtypes (pKi native: M1, 7.32 ± 0.10; M2, 6.50 ± 0.11; M3, 6.02 ± 0.13; M4, 6.28 ± 0.16; pKi cloned: M1, 7.69 ± 0.08; M2, 6.22 ± 0.14; M3, 6.11 ± 0.16; 6.35 ± 0.11) whereas CC8 is highly selective for M2 receptors versus the other subtypes (pKi native: M1 7.50 ± 0.04; M2, 9.01 ± 0.12; M3, 6.70 ± 0.08; M4, 7.56 ± 0.04; pKi cloned: M1, 7.90 ± 0.20; M2, 9.04 ± 0.08; M3, 6.40 ± 0.07; M4, 7.40 ± 0.04). Furthermore, particularly relevant for this investigation were tetra-amines dipitramine and AM172 for their ability to significantly differentiate M1 and M4 receptors. 5. The apparent affinity values (pA2) obtained for tetra-amines in functional studies using the prostatic portion of rabbit vas deferens correlated most closely with the values (pKi) obtained at either native or human recombinant muscarinic M4 receptors. This supports the view that the muscarinic receptor mediating inhibition of neurogenic contractions of rabbit vas deferens may not belong to the M1 type but rather appears to be of the M4 subtype

Surface and deep strain at Mt. Etna volcano (Sicily, Italy) during the 2003-2004 inflation phase

We carried out a study of the seismicity and ground deformation occurred on Mount Etna volcano after the end of 2002-2003 eruption and before the onset of 2004-2005 eruption, and recorded by the permanent local seismic network run by Istituto Nazionale di Geofisica e Vulcanologia - Sezione di Catania and by the geodetic surveys carried out in July 2003 and July 2004 on the GPS network. We provided a description of seismicity rate and main seismic swarms which occurred during the investigated period. Mostly of the earthquakes are clustered in two main clusters located on the north-eastern (E-W aligned and above the sea level) and south-eastern (NW-SE aligned and from 3 to 8 Km below the sea level) sectors of the volcano. in order to better understand the kinematic processes of the volcano, the 3D relocation were used to compute fault plane solutions and a selected dataset was inverted to determine stress and strain tensors. The focal solutions on the north-eastern sector show clear left-lateral kinematics along an E-W fault plane, in good agreement with the Pernicana fault kinematics. The focal solutions on the south-eastern sector show a main right-lateral kinematics along a NW-SE fault plane evidencing a roughly E-W oriented compression coupled with a N-S extension. Surface ground deformation affecting Mt Etna and measured by GPS surveys highlights a marked inflation during the same period, mainly visible on the western and upper sectors of the volcano; on the contrary, its eastern side shows an exceptionally strong seawards and downwards motion with displacements ranging from 5 up to 10 cm along the coastline. The 2D geodetic strain tensor distribution was calculated on a 1.5 km spaced grid, in order to detail the strain axes orientation above the entire GPS network. The results of the 2D geodetic strain calculation evidenced the very strong extension (mainly along an- ENE-WSW axis) of the summit area that was already considered as the cause of the 2004-2005 eruption; this main ENE-WSW extension continues throughout the eastern flank, but here coupled with a WNW-ESE contraction, meaning a right-lateral shear along a NW-SE oriented fault plane. The opposite deformation of the eastern sector of the volcano, as measured by seismicity and ground deformation has to be interpreted by considering the different depths of the two signals. Seismic activity along the NW-SE alignment is, in fact, located between 3 and 8 km b.s.l. and it is then affected by the very strong additional EW compression induced by the inflating source located by inverting GPS data just westwards and at the same depth. Ground deformation measured by GPS at the surface, on the contrary, is mainly affected by the shallower dynamics of the eastern flank, fastly moving towards East that produces an opposite (extension) E-W strain. It is also meaningful, confirming the decoupling between the surface and deep strain, that all the seismicity of the south-eastern sector lies beneath the sliding plane already modeled by geodetic data for the same time interval and for the 2004-2006 period and also beneath the deeper one previously modeled during the 1993-1998 period when the eastern flank velocity was much slower