Severe toxicity of skin rash, fever and diarrhea associated with imatinib: case report and review of skin toxicities associated with tyrosine kinase inhibitors

Chronic myeloid leukemia (CML) is characterized by a Philadelphia chromosome which contains an oncogene, bcr-abl. This oncogene encodes a tyrosine kinase which is constitutively activated. Imatinib, a tyrosine kinase inhibitor (TKI), has been widely used in the treatment of CML. Dasatinib and nilotinib were recently approved for the treatment of CML. Other TKIs, such as bosutinib, erlotinib, and sunitinib, are under study for the treatment of CML as well as other hematologic and solid malignancies. Skin rash has been reported as one of the most common side effects of the TKIs. Here we present a case of severe skin rash together with unusual symptoms of high fever and diarrhea induced by imatinib in a CML patient. The dermatologic toxicities from a variety of tyrosine kinase inhibitors are reviewed and general principles of management are also discussed

Efficient Segmentation with Texture in Ore Images Based on Box-supervised Approach

Image segmentation methods have been utilized to determine the particle size distribution of crushed ores. Due to the complex working environment, high-powered computing equipment is difficult to deploy. At the same time, the ore distribution is stacked, and it is difficult to identify the complete features. To address this issue, an effective box-supervised technique with texture features is provided for ore image segmentation that can identify complete and independent ores. Firstly, a ghost feature pyramid network (Ghost-FPN) is proposed to process the features obtained from the backbone to reduce redundant semantic information and computation generated by complex networks. Then, an optimized detection head is proposed to obtain the feature to maintain accuracy. Finally, Lab color space (Lab) and local binary patterns (LBP) texture features are combined to form a fusion feature similarity-based loss function to improve accuracy while incurring no loss. Experiments on MS COCO have shown that the proposed fusion features are also worth studying on other types of datasets. Extensive experimental results demonstrate the effectiveness of the proposed method, which achieves over 50 frames per second with a small model size of 21.6 MB. Meanwhile, the method maintains a high level of accuracy compared with the state-of-the-art approaches on ore image dataset. The source code is available at \url{https://github.com/MVME-HBUT/OREINST}.Comment: 14 pages, 8 figure

Prediction of Biological Motion Perception Performance from Intrinsic Brain Network Regional Efficiency

Biological motion perception (BMP) is a vivid perception of the moving form of a human figure from a few light points on the joints of the body. BMP is commonplace and important, but there is great inter-individual variability in this ability. This study used multiple regression model analysis to explore the association between the BMP performance and intrinsic brain activity, in order to investigate the neural substrates underlying inter-individual variability of BMP performance. The resting-state functional magnetic resonance imaging (rs-fMRI) and BMP performance data were collected from 24 healthy participants. For each participant, the intrinsic brain network was constructed, and a graph-based network efficiency metric was measured. Then, a multiple linear regression model was used to explore the association between network regional efficiency and BMP performance. We found that the local and global network efficiency of many regions was significantly correlated with the BMP performance. Further analysis showed that the local efficiency rather than global efficiency could be used to explain most of the BMP inter-individual variability, and the regions involved were predominately located at the Default Mode Network (DMN). Additionally, the discrimination analysis showed that the local efficiency over regions including thalamus could be used to classify BMP performance across participants. Notably, the association pattern between the network nodal efficiency and the BMP was different from the association pattern that of the static directional/gender information perception. Overall, these findings showed that intrinsic brain network efficiency may be considered as a neural factor that explains BMP inter-individual variability. Keywords: Biological motion; Resting-state network; Network efficiency; Multiple linear regression model; Brain-behavior analysi

Methotrimeprazine-induced Corneal Deposits and Cataract Revealed by Urine Drug Profiling Test

Two schizophrenic patients who had been taking medication for a long period presented with visual disturbance of 6-month duration. Slit-lamp examination revealed fine, discrete, and brownish deposits on the posterior cornea. In addition, bilateral star-shaped anterior subcapsular lens opacities, which were dense, dust-like granular deposits, were noted. Although we strongly suspected that the patient might have taken one of the drugs of the phenothiazine family, we were unable to obtain a history of medications other than haloperidol and risperidone, which were taken for 3 yr. We performed a drug profiling test using urine samples and detected methotrimeprazine. The patient underwent surgery for anterior subcapsular lens opacities. Visual acuity improved in both eyes, but the corneal deposits remained. We report an unusual case of methotrimeprazine-induced corneal deposits and cataract in a patient with psychosis, identified by using the urine drug profiling test

Fundamental issues in systems biology.

types: Journal Article; Research Support, Non-U.S. Gov'tIn the context of scientists' reflections on genomics, we examine some fundamental issues in the emerging postgenomic discipline of systems biology. Systems biology is best understood as consisting of two streams. One, which we shall call 'pragmatic systems biology', emphasises large-scale molecular interactions; the other, which we shall refer to as 'systems-theoretic biology', emphasises system principles. Both are committed to mathematical modelling, and both lack a clear account of what biological systems are. We discuss the underlying issues in identifying systems and how causality operates at different levels of organisation. We suggest that resolving such basic problems is a key task for successful systems biology, and that philosophers could contribute to its realisation. We conclude with an argument for more sociologically informed collaboration between scientists and philosophers.Funding received from the Economic and Social Research Council (ESRC), UK, and Overseas Conference Funding from the British Academy

Widespread known and novel phosphonate utilization pathways in marine bacteria revealed by functional screening and metagenomic analyses

Phosphonates (Pn), compounds with a direct C–P bond instead of the more common C–O–P ester bond, constitute a significant fraction of marine dissolved organic phosphorus and recent evidence suggests that they may be an alternative source of P for marine microorganisms. To further characterize the microorganisms and pathways involved in Pn utilization, we screened bacterioplankton genomic libraries for their ability to complement an Escherichia coli strain unable to use Pns as a P source. Using this approach we identified a phosphonatase pathway as well as a novel pair of genes that allowed utilization of 2-aminoethylphosphonate (2-AEPn) as the sole P source. These pathways are present in diverse bacteria common in marine plankton including representatives of Proteobacteria, Planctomycetes and Cyanobacteria. Analysis of metagenomic databases for Pn utilization genes revealed that they are widespread and abundant among marine bacteria, suggesting that Pn metabolism is likely to play an important role in P-depleted surface waters, as well as in the more P-rich deep-water column.National Science Foundation (U.S.) (Microbial Observatory award (MCB-0348001)Gordon and Betty Moore FoundationUnited States. Dept. of Energy (Genomics GTL Program

Directionality of large-scale resting-state brain networks during eyes open and eyes closed conditions

The present study examined directional connections in the brain among resting-state networks (RSNs) when the participant had their eyes open (E0) or had their eyes closed (EC). The resting state fMRI data were collected from 20 healthy participants (9 males, 20.17 +/- 2.74 years) under the EO and EC states. Independent component analysis (ICA) was applied to identify the separated RSNs (i.e., the primary/high-level visual, primary sensory-motor, ventral motor, salience/dorsal attention, and anterior/posterior default-mode networks), and the Gaussian Bayesian network (BN) learning approach was then used to explore the conditional dependencies among these RSNs. The network-to-network directional connections related to EO and EC were depicted, and a support vector machine (SVM) was further employed to identify the directional connection patterns that could effectively discriminate between the two states. The results indicated that the connections among RSNs are directionally connected within a BN during the EO and EC states. The directional connections from the salience network (SN) to the anterior/posterior default-mode networks and the high-level to primary-level visual network were the obvious characteristics of both the EO and EC resting-state BNs. Of the directional connections in BN, the directional connections of the salience and dorsal attention network (DAN) were observed to be discriminative between the EO and EC states. In particular, we noted that the properties of the salience and DANs were in opposite directions. Overall, the present study described the directional connections of RSNs using a BN learning approach during the E0 and EC states, and the results suggested that the directionality of the attention systems (i.e., mainly for the salience and the DAN) in resting state might have Important roles in switching between the EO and EC conditions