Transient Ageusia and Dysgeusia Following Thalamic Cyst Drainage.

Taste consists of sensation and perception. Specific neural structures transmit a stimulus from the taste buds to the gustatory cortex to generate taste sensation. Any disruption of this pathway, whether it affects sensation or perception, can result in taste disorders. Stereotactic procedures involving the thalamus may result in gustatory complications. A 41-year-old female patient who underwent stereotactic drainage of a thalamic cyst suffered transient ageusia. Subsequently, she developed metallic taste perception. When her stereotactic plan was re-evaluated, it was noted that the posteromedial ventral thalamus nucleus was in the path of the needle tract and the needle had passed through it. Follow-up was recommended and her symptoms completely resolved within 2 months following surgery. Modern imaging techniques allow for the visualization of neural structures related to the sense of taste. Additionally, care must be taken when planning stereotactic procedures for such lesions.

Transient Ageusia and Dysgeusia Following Thalamic Cyst Drainage.

Taste consists of perception and sensation. Specific neural structures transmit a stimulus from the taste buds to the gustatory cortex to generate taste sensation. Any disruption of this pathway, whether it affects sensation or perception, can result in taste disorders. Stereotactic procedures involving the thalamus may result in gustatory complications. A 41-year-old female patient who underwent stereotactic drainage of a thalamic cyst suffered transient ageusia. Subsequently, she developed metallic taste perception. When her stereotactic plan was re-evaluated, it was noted that the posteromedial ventral thalamus nucleus was in the path of the needle tract and the needle had passed through it. Follow-up was recommended and her symptoms completely resolved within 2 months following surgery. Modern imaging techniques allow for the visualization of neural structures related to the sense of taste. Additionally, care must be taken when planning stereotactic procedures for such lesions.

GLIDER: function prediction from GLIDE-based neighborhoods.

MOTIVATION: Protein function prediction, based on the patterns of connection in a protein-protein interaction (or association) network, is perhaps the most studied of the classical, fundamental inference problems for biological networks. A highly successful set of recent approaches use random walk-based low-dimensional embeddings that tend to place functionally similar proteins into coherent spatial regions. However, these approaches lose valuable local graph structure from the network when considering only the embedding. We introduce GLIDER, a method that replaces a protein-protein interaction or association network with a new graph-based similarity network. GLIDER is based on a variant of our previous GLIDE method, which was designed to predict missing links in protein-protein association networks, capturing implicit local and global (i.e. embedding-based) graph properties. RESULTS: GLIDER outperforms competing methods on the task of predicting GO functional labels in cross-validation on a heterogeneous collection of four human protein-protein association networks derived from the 2016 DREAM Disease Module Identification Challenge, and also on three different protein-protein association networks built from the STRING database. We show that this is due to the strong functional enrichment that is present in the local GLIDER neighborhood in multiple different types of protein-protein association networks. Furthermore, we introduce the GLIDER graph neighborhood as a way for biologists to visualize the local neighborhood of a disease gene. As an application, we look at the local GLIDER neighborhoods of a set of known Parkinson's Disease GWAS genes, rediscover many genes which have known involvement in Parkinson's disease pathways, plus suggest some new genes to study. AVAILABILITY AND IMPLEMENTATION: All code is publicly available and can be accessed here: https://github.com/kap-devkota/GLIDER. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Majority Vote Cascading: A Semi-Supervised Framework for Improving Protein Function Prediction.

A method to improve protein function prediction for sparsely annotated PPI networks is introduced. The method extends the DSD majority vote algorithm introduced by Cao et al. to give confidence scores on predicted labels and to use predictions of high confidence to predict the labels of other nodes in subsequent rounds. We call this a majority vote cascade. Several cascade variants are tested in a stringent cross-validation experiment on PPI networks from S. cerevisiae and D. melanogaster, and we show that for many different settings with several alternative confidence functions, cascading improves the accuracy of the predictions. A list of the most confident new label predictions in the two networks is also reported. Code and networks for the cross-validation experiments appear at http://bcb.cs.tufts.edu/cascade.

Non-motor connections of the pedunculopontine nucleus of the rat and human brain.

INTRODUCTION: The connections of the pedunculopontine nucleus (PPN) with motor areas of the central nervous system (CNS) are well described in the literature, in contrast relations with non-motor areas are lacking. Thus, the aim of the present study is to define the non-motor connections of the PPN in rats using the fluoro-gold (FG) tracer and compare the presence of these connections in healthy human adults using diffusion tensor tractography (DTI). MATERIALS AND METHODS: We injected FG into the PPN of 12 rats. The non-motor connections of the PPN with cortical, subcortical, and brainstem structures were documented. The non-motor connections of the rats were compared with the DTI obtained from 35 healthy adults. RESULTS: The results of the tract-tracing study in the rat showed that the PPN was connected to non-motor cortical (cingulate, somatosensory, visual, auditory, medial frontal cortices), subcortical (amygdala, hypothalamus, thalamus, habenular, and bed nucleus of stria terminalis), and brainstem (medullary reticular, trigeminal spinal, external cuneate, pontine reticular, vestibular, superior and inferior colliculus, locus ceruleus, periaqueductal gray, parabrachial, dorsal raphe, pretectal, lateral lemniscus nuclei, and the contralateral PPN) structures. The DTI obtained from healthy adults showed similar PPN non-motor connections as in rats. CONCLUSION: Understanding the connections of the PPN with non-motor cortical, subcortical, and brainstem areas of the CNS will enrich our knowledge of its contribution in various circuits and the areas that PPN activity can influence. Further, it will provide insight into the role of Parkinson's disease and related disorders and explain the non-motor complications which occur subsequent to deep brain stimulation (DBS) of the PPN.

MUNDO: protein function prediction embedded in a multispecies world.

Motivation: Leveraging cross-species information in protein function prediction can add significant power to network-based protein function prediction methods, because so much functional information is conserved across at least close scales of evolution. We introduce MUNDO, a new cross-species co-embedding method that combines a single-network embedding method with a co-embedding method to predict functional annotations in a target species, leveraging also functional annotations in a model species network. Results: Across a wide range of parameter choices, MUNDO performs best at predicting annotations in the mouse network, when trained on mouse and human protein-protein interaction (PPI) networks, in the human network, when trained on human and mouse PPIs, and in Baker's yeast, when trained on Fission and Baker's yeast, as compared to competitor methods. MUNDO also outperforms all the cross-species methods when predicting in Fission yeast when trained on Fission and Baker's yeast; however, in this single case, discarding the information from the other species and using annotations from the Fission yeast network alone usually performs best. Availability and implementation: All code is available and can be accessed here: github.com/v0rtex20k/MUNDO. Supplementary information: Supplementary data are available at Bioinformatics Advances online. Additional experimental results are on our github site.

The Use of Treatment Response Assessment Maps in Discriminating Between Radiation Effect and Persistent Tumoral Lesion in Metastatic Brain Tumors Treated with Gamma Knife Radiosurgery.

BACKGROUND: Traditional imaging modalities are not useful in the follow-up of irradiated metastatic brain tumors, because radiation can change imaging characteristics. We aimed to assess the ability of treatment response assessment maps (TRAMs) calculated from delayed-contrast magnetic resonance imaging (MRI) in differentiation between radiation effect and persistent tumoral tissue. METHODS: TRAMs were calculated by subtracting three-dimensional T1 MRIs acquired 5 minutes after contrast injection from the images acquired 60-105 minutes later. Red areas were regarded as radiation effect and blue areas as persistent tumoral lesion. Thirty-seven patients with 130 metastatic brain tumors who were treated with Gamma Knife radiosurgery and who underwent TRAMs perfusion-weighted MRI were enrolled in this retrospective study. RESULTS: The median age was 58 years and the most common primary diagnosis was lung cancer (n = 21). The median follow-up period of patients was 12 months. The overall local control rate was 100% at 1 year and 98.9% at 2 years. The median progression-free survival was 12 months. The mean overall survival was 27.3 months. The radiologic and clinical follow-up showed a clinicoradiologic diagnosis of a persistent tumoral lesion in 3 tumors (2.3%) and radiation effect in 127 tumors (97.7%). There was a fair agreement between clinicoradiologic diagnosis and TRAMs analysis (κ = 0.380). The sensitivity and positive predictive value of TRAMs in diagnosing radiation effect were 96.06% and 99.2%, respectively. TRAMs showed comparable results to perfusion-weighted MRI, with a diagnostic odds ratio of 27.4 versus 20.7, respectively. CONCLUSIONS: The presented results show the ability of TRAMs in differentiating radiation effect and persistent tumoral lesions.