73 research outputs found
Genomic Profiling of Two Histologically Distinct Rare Urothelial Cancers in a Clinical Setting to Identify Potential Therapeutic Options for Treatment and Management of Disease.
Molecular profiling of urothelial cancers for therapeutic and prognostic potential has been very limited due to the absence of cancer-specific targeted therapies. We describe here 2 clinical cases with a histological diagnosis of an invasive sarcomatoid and a poorly differentiated carcinoma favoring urothelial with some neuroendocrine differentiation, two of the rarer types of urothelial cancers, which were evaluated for mutations in 212 genes for single-nucleotide variants and copy-number variants and 53 genes for fusions associated with solid tumors. In both cases, we identified variants in 2 genes, Case Rep Oncol 2018 Mar 27; 11(1):196-205
The NMDA agonist D-cycloserine facilitates fear memory consolidation in humans
Animal research suggests that the consolidation of fear and
extinction memories depends on N-methyl D-aspartate (NMDA)-
type glutamate receptors. Using a fear conditioning and extinction
paradigm in healthy normal volunteers, we show that postlearning
administration of the NMDA partial agonist D-cycloserine (DCS)
facilitates fear memory consolidation, evidenced behaviorally by
enhanced skin conductance responses, relative to placebo, for
presentations of a conditioned stimulus (CS) at a memory test
performed 72 h later. DCS also enhanced CS-evoked neural
responses in a posterior hippocampus/collateral sulcus region and
in the medial prefrontal cortex at test. Our data suggest a role for
NMDA receptors in regulating fear memory consolidation in humans
2,8-Disubstituted-1,6-Naphthyridines and 4,6-Disubstituted-Isoquinolines with Potent, Selective Affinity for CDK8/19
We demonstrate a designed scaffold-hop approach to the discovery of 2,8-disubstituted-1,6-naphthyridine- and 4,6-disubstituted-isoquinoline-based dual CDK8/19 ligands. Optimized compounds in both series exhibited rapid aldehyde oxidase-mediated metabolism, which could be abrogated by introduction of an amino substituent at C5 of the 1,6-naphthyridine scaffold or at C1 of the isoquinoline scaffold. Compounds 51 and 59 were progressed to in vivo pharmacokinetic studies, and 51 also demonstrated sustained inhibition of STAT1SER727 phosphorylation, a biomarker of CDK8 inhibition, in an SW620 colorectal carcinoma human tumor xenograft model following oral dosing
Genomic Profiling of Two Histologically Distinct Rare Urothelial Cancers in a Clinical Setting to Identify Potential Therapeutic Options for Treatment and Management of Disease
Scaling Effects and Spatio-Temporal Multilevel Dynamics in Epileptic Seizures
Epileptic seizures are one of the most well-known dysfunctions of the nervous system. During a seizure, a highly synchronized behavior of neural activity is observed that can cause symptoms ranging from mild sensual malfunctions to the complete loss of body control. In this paper, we aim to contribute towards a better understanding of the dynamical systems phenomena that cause seizures. Based on data analysis and modelling, seizure dynamics can be identified to possess multiple spatial scales and on each spatial scale also multiple time scales. At each scale, we reach several novel insights. On the smallest spatial scale we consider single model neurons and investigate early-warning signs of spiking. This introduces the theory of critical transitions to excitable systems. For clusters of neurons (or neuronal regions) we use patient data and find oscillatory behavior and new scaling laws near the seizure onset. These scalings lead to substantiate the conjecture obtained from mean-field models that a Hopf bifurcation could be involved near seizure onset. On the largest spatial scale we introduce a measure based on phase-locking intervals and wavelets into seizure modelling. It is used to resolve synchronization between different regions in the brain and identifies time-shifted scaling laws at different wavelet scales. We also compare our wavelet-based multiscale approach with maximum linear cross-correlation and mean-phase coherence measures
RUN and FYVE domain-containing protein 4 enhances autophagy and lysosome tethering in response to Interleukin-4
Autophagy is a key degradative pathway coordinated by external cues, including starvation, oxidative stress, or
pathogen detection. Rare are the molecules known to contribute mechanistically to the regulation of autophagy and
expressed specifically in particular environmental contexts or in distinct cell types. Here, we unravel the role of RUN
and FYVE domain–containing protein 4 (RUFY4) as a positive molecular regulator of macroautophagy in primary
dendritic cells (DCs). We show that exposure to interleukin-4 (IL-4) during DC differentiation enhances autophagy flux
through mTORC1 regulation and RUFY4 induction, which in turn actively promote LC3 degradation, Syntaxin 17–
positive autophagosome formation, and lysosome tethering. Enhanced autophagy boosts endogenous antigen presentation
by MHC II and allows host control of Brucella abortus replication in IL-4–treated DCs and in RUFY4-expressing
cells. RUFY4 is therefore the first molecule characterized to date that promotes autophagy and influences endosome
dynamics in a subset of immune cells
Long-term medical treatment in congenital hyperinsulinism: a descriptive analysis in a large cohort of patients from different clinical centers
The past, present, and future of the Brain Imaging Data Structure (BIDS)
The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of
data and metadata from a growing range of neuroscience modalities. This paper is meant as a
history of how the standard has developed and grown over time. We outline the principles
behind the project, the mechanisms by which it has been extended, and some of the challenges
being addressed as it evolves. We also discuss the lessons learned through the project, with the
aim of enabling researchers in other domains to learn from the success of BIDS
On the processing of vowels in the mammalian auditory system
The mammalian auditory system generates representations of the physical world in terms of auditory objects. To decide which object class a particular sound belongs to, the auditory system must recognise the patterns of acoustic components that form the acoustic “fingerprint” of the sound’s auditory class. Where in the central auditory system such patterns are detected and what form the neural processing takes that underlies their detection are unanswered questions in sensory neurophysiology. In the research conducted for this thesis I used artificial vowel sounds to explore the neural and perceptual characteristics of auditory object recognition in rats. I recorded cortical responses from the primary auditory cortex (A1) in anaesthetised rats and determined how well the spiking responses, evoked by artificial vowels, resolve the spectral components that define vowel classes in human perception. The recognition of an auditory class rests on the ability to detect the combination of spectral components that all member sounds of the class share. I generated and evaluated models of the integration by A1 responses of the acoustic components that define human vowels classes. The hippocampus is a candidate area for neural responses that are specific to particular object classes. In this thesis I also report the results of a collaboration during which we investigated how the hippocampus responds to vowels in awake behaving animals. Finally, I explored the processing of vowels behaviourally, testing the perceptual ability of rats to discriminate and classify vowels and in particular whether rats use combinations of spectral components to recognise members of vowel classes. For the behavioural training I built a novel integrated housing and training cage that allows rats to train themselves in auditory recognition tasks. Combining the results and methods presented in this thesis will help reveal how the mammalian auditory system recognises auditory objects.This thesis is not currently available in ORA
Neural Resolution of Formant Frequencies in the Primary Auditory Cortex of Rats.
Pulse-resonance sounds play an important role in animal communication and auditory object recognition, yet very little is known about the cortical representation of this class of sounds. In this study we shine light on one simple aspect: how well does the firing rate of cortical neurons resolve resonant ("formant") frequencies of vowel-like pulse-resonance sounds. We recorded neural responses in the primary auditory cortex (A1) of anesthetized rats to two-formant pulse-resonance sounds, and estimated their formant resolving power using a statistical kernel smoothing method which takes into account the natural variability of cortical responses. While formant-tuning functions were diverse in structure across different penetrations, most were sensitive to changes in formant frequency, with a frequency resolution comparable to that reported for rat cochlear filters
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