Development of a Moderated Online Intervention to Treat Social Anxiety in First-Episode Psychosis.

Background: It is well established that social anxiety disorder (SAD) is a significant clinical problem for individuals with a psychotic disorder. Comorbid social anxiety in individuals with psychosis has been associated with poorer premorbid functioning, increased depression, and a reduced quality of life. Cognitive behavior therapy (CBT) is recommended for people with psychosis as a first-line psychological treatment; however, its focus and evaluation primarily revolves around reducing psychotic symptoms and not necessarily targeting comorbid social anxiety symptoms. We developed a novel online social cognitive behavioral intervention (entitled EMBRACE) specifically designed to treat social anxiety symptoms in first episode psychosis (FEP). Methods: The key clinical and engagement features of the intervention were established through integrating evidence-based material derived from 1) CBT-based treatment models for SAD, 2) relevant literature findings related to psychosis and its clinical correlates (e.g., shame, social rank, and its relationship with social anxiety and paranoia), 3) feedback from youth focus groups in order to inform a user-centered intervention design, and 4) a highly multidisciplinary collaborative development approach to design therapy comics. Results: A detailed description of the final version of the 12-week online social intervention to treat social anxiety in FEP is presented. Conclusion: The EMBRACE intervention was designed to provide young people with the necessary skills and confidence to overcome social anxiety within a supportive, safe online space. By design, it allows young people the opportunity to practice their newly learnt skills to connect with others and in doing so, learn to embrace their true authentic selves

Duodenal enteroglucagonoma revealed by differential comparison of serum and tissue glucagon reactivity with Siemens' Double Glucagon Antibody and DakoCytomation's Polyclonal Rabbit Anti-Human Glucagon: a case report

<p>Abstract</p> <p>Introduction</p> <p>This case report demonstrates that the differential immunohistochemical reactivities of Siemens' <it>Double Antibody Glucagon </it>compared to DakoCytomation's <it>Polyclonal Rabbit Anti-Human Glucagon </it>allow for pathologic distinction of enteral versus pancreatic glucagonoma.</p> <p>Case presentation</p> <p>A 64-year-old Caucasian man was diagnosed with a duodenal enteroglucagonoma following presentation with obstructive jaundice. He had a low serum glucagon level using Siemens' <it>Double Antibody Glucagon</it>, a clinical syndrome consistent with glucagon hypersecretion. A periampullary mass biopsy proved to be a neuroendocrine tumor, with positive immunohistochemical reactivity to DakoCytomation's <it>Polyclonal Rabbit Anti-Human Glucagon</it>.</p> <p>Conclusions</p> <p>Differential comparison of the immunohistochemical reactivities of Siemens' <it>Double Antibody Glucagon </it>and DakoCytomation's <it>Polyclonal Rabbit Anti-Human Glucagon </it>discerns enteroglucagon from pancreatic glucagon.</p

The safety and feasibility of extracorporeal high-intensity focused ultrasound (HIFU) for the treatment of liver and kidney tumours in a Western population

High-intensity focused ultrasound (HIFU) provides a potential noninvasive alternative to conventional therapies. We report our preliminary experience from clinical trials designed to evaluate the safety and feasibility of a novel, extracorporeal HIFU device for the treatment of liver and kidney tumours in a Western population. The extracorporeal, ultrasound-guided Model-JC Tumor Therapy System (HAIFU™ Technology Company, China) has been used to treat 30 patients according to four trial protocols. Patients with hepatic or renal tumours underwent a single therapeutic HIFU session under general anaesthesia. Magnetic resonance imaging 12 days after treatment provided assessment of response. The patients were subdivided into those followed up with further imaging alone or those undergoing surgical resection of their tumours, which enabled both radiological and histological assessment. HIFU exposure resulted in discrete zones of ablation in 25 of 27 evaluable patients (93%). Ablation of liver tumours was achieved more consistently than for kidney tumours (100 vs 67%, assessed radiologically). The adverse event profile was favourable when compared to more invasive techniques. HIFU treatment of liver and kidney tumours in a Western population is both safe and feasible. These findings have significant implications for future noninvasive image-guided tumour ablation

Qualitative prediction of blood–brain barrier permeability on a large and refined dataset

The prediction of blood–brain barrier permeation is vitally important for the optimization of drugs targeting the central nervous system as well as for avoiding side effects of peripheral drugs. Following a previously proposed model on blood–brain barrier penetration, we calculated the cross-sectional area perpendicular to the amphiphilic axis. We obtained a high correlation between calculated and experimental cross-sectional area (r = 0.898, n = 32). Based on these results, we examined a correlation of the calculated cross-sectional area with blood–brain barrier penetration given by logBB values. We combined various literature data sets to form a large-scale logBB dataset with 362 experimental logBB values. Quantitative models were calculated using bootstrap validated multiple linear regression. Qualitative models were built by a bootstrapped random forest algorithm. Both methods found similar descriptors such as polar surface area, pKa, logP, charges and number of positive ionisable groups to be predictive for logBB. In contrast to our initial assumption, we were not able to obtain models with the cross-sectional area chosen as relevant parameter for both approaches. Comparing those two different techniques, qualitative random forest models are better suited for blood-brain barrier permeability prediction, especially when reducing the number of descriptors and using a large dataset. A random forest prediction system (ntrees = 5) based on only four descriptors yields a validated accuracy of 88%

Dramatic pain relief and resolution of bone inflammation following pamidronate in 9 pediatric patients with persistent chronic recurrent multifocal osteomyelitis (CRMO)

<p>Abstract</p> <p>Background</p> <p>Chronic recurrent multifocal osteomyelitis (CRMO) is an inflammatory, non-infectious osteopathy that affects predominantly patients ≤ 18 years of age. There is no uniformly effective treatment. Our objective is to describe clinical, magnetic resonance imaging (MRI), and bone resorption response to intravenous pamidronate in pediatric CRMO.</p> <p>Methods</p> <p>We report our prospectively documented experience with all CRMO patients treated with pamidronate between 2003 and 2008 at a tertiary pediatric centre. Pamidronate was administered as intravenous cycles. The dose of pamidronate varied among subjects but was given as monthly to every 3 monthly cycles depending on the distance the patient lived from the infusion center. Maximum cumulative dose was ≤ 11.5 mg/kg/year. Pamidronate treatment was continued until resolution of MRI documented bone inflammation. Visual analog scale for pain (VAS) and bone resorption marker urine N-telopeptide/urine creatinine (uNTX/uCr) were measured at baseline, preceding each subsequent pamidronate treatment, at final follow-up, and/or at time of MRI confirmed CRMO flare. MRI of the affected site(s) was obtained at baseline, preceding every 2^ndtreatment, and with suspected CRMO recurrence.</p> <p>Results</p> <p>Nine patients (5 F: 4 M) were treated, with a median (range) age at treatment of 12.9 (4.5–16.3) years, and median (range) duration of symptoms of 18 (6–36) months. VAS decreased from 10/10 to 0–3/10 by the end of first 3–day treatment for all patients. The mean (range) time to complete MRI resolution of bone inflammation was 6.0 (2–12) months. The mean (confidence interval (CI)) baseline uNTX/uCr was 738.83 (CI 464.25, 1013.42)nmol/mmol/creatinine and the mean (CI) decrease from baseline to pamidronate discontinuation was 522.17 (CI 299.77, 744.56)nmol/mmol/creatinine. Median (range) of follow-up was 31.4 (24–54) months. Four patients had MRI confirmed CRMO recurrence, which responded to one pamidronate re-treatment. The mean (range) uNTX/uCr change as a monthly rate from the time of pamidronate discontinuation to flare was 9.41 (1.38–19.85)nmol/mmol/creatinine compared to -29.88 (-96.83–2.01)nmol/mmol/creatinine for patients who did not flare by the time of final follow-up.</p> <p>Conclusion</p> <p>Pamidronate resulted in resolution of pain and MRI documented inflammation in all patients. No patient flared while his/her uNTX/uCr remained suppressed. We propose that pamidronate is an effective second-line therapy in persistent CRMO.</p

NeuroML: A Language for Describing Data Driven Models of Neurons and Networks with a High Degree of Biological Detail

Biologically detailed single neuron and network models are important for understanding how ion channels, synapses and anatomical connectivity underlie the complex electrical behavior of the brain. While neuronal simulators such as NEURON, GENESIS, MOOSE, NEST, and PSICS facilitate the development of these data-driven neuronal models, the specialized languages they employ are generally not interoperable, limiting model accessibility and preventing reuse of model components and cross-simulator validation. To overcome these problems we have used an Open Source software approach to develop NeuroML, a neuronal model description language based on XML (Extensible Markup Language). This enables these detailed models and their components to be defined in a standalone form, allowing them to be used across multiple simulators and archived in a standardized format. Here we describe the structure of NeuroML and demonstrate its scope by converting into NeuroML models of a number of different voltage- and ligand-gated conductances, models of electrical coupling, synaptic transmission and short-term plasticity, together with morphologically detailed models of individual neurons. We have also used these NeuroML-based components to develop an highly detailed cortical network model. NeuroML-based model descriptions were validated by demonstrating similar model behavior across five independently developed simulators. Although our results confirm that simulations run on different simulators converge, they reveal limits to model interoperability, by showing that for some models convergence only occurs at high levels of spatial and temporal discretisation, when the computational overhead is high. Our development of NeuroML as a common description language for biophysically detailed neuronal and network models enables interoperability across multiple simulation environments, thereby improving model transparency, accessibility and reuse in computational neuroscience

ER Stress-Inducible Factor CHOP Affects the Expression of Hepcidin by Modulating C/EBPalpha Activity

Endoplasmic reticulum (ER) stress induces a complex network of pathways collectively termed the unfolded protein response (UPR). The clarification of these pathways has linked the UPR to the regulation of several physiological processes. However, its crosstalk with cellular iron metabolism remains unclear, which prompted us to examine whether an UPR affects the expression of relevant iron-related genes. For that purpose, the HepG2 cell line was used as model and the UPR was activated by dithiothreitol (DTT) and homocysteine (Hcys). Here, we report that hepcidin, a liver secreted hormone that shepherds iron homeostasis, exhibits a biphasic pattern of expression following UPR activation: its levels decreased in an early stage and increased with the maintenance of the stress response. Furthermore, we show that immediately after stressing the ER, the stress-inducible transcription factor CHOP depletes C/EBPα protein pool, which may in turn impact on the activation of hepcidin transcription. In the later period of the UPR, CHOP levels decreased progressively, enhancing C/EBPα-binding to the hepcidin promoter. In addition, analysis of ferroportin and ferritin H revealed that the transcript levels of these iron-genes are increased by the UPR signaling pathways. Taken together, our findings suggest that the UPR can have a broad impact on the maintenance of cellular iron homeostasis

Ectopic Expression of Neurogenin 2 Alone is Sufficient to Induce Differentiation of Embryonic Stem Cells into Mature Neurons

Recent studies show that combinations of defined key developmental transcription factors (TFs) can reprogram somatic cells to pluripotency or induce cell conversion of one somatic cell type to another. However, it is not clear if single genes can define a cell̀s identity and if the cell fate defining potential of TFs is also operative in pluripotent stem cells in vitro. Here, we show that ectopic expression of the neural TF Neurogenin2 (Ngn2) is sufficient to induce rapid and efficient differentiation of embryonic stem cells (ESCs) into mature glutamatergic neurons. Ngn2-induced neuronal differentiation did not require any additional external or internal factors and occurred even under pluripotency-promoting conditions. Differentiated cells displayed neuron-specific morphology, protein expression, and functional features, most importantly the generation of action potentials and contacts with hippocampal neurons. Gene expression analyses revealed that Ngn2-induced in vitro differentiation partially resembled neurogenesis in vivo, as it included specific activation of Ngn2 target genes and interaction partners. These findings demonstrate that a single gene is sufficient to determine cell fate decisions of uncommitted stem cells thus giving insights into the role of key developmental genes during lineage commitment. Furthermore, we present a promising tool to improve directed differentiation strategies for applications in both stem cell research and regenerative medicine

Plate-based diversity subset screening generation 2: An improved paradigm for high throughput screening of large compound files

High throughput screening (HTS) is an effective method for lead and probe discovery that is widely used in industry and academia to identify novel chemical matter and to initiate the drug discovery process. However, HTS can be time-consuming and costly and the use of subsets as an efficient alternative to screening these large collections has been investigated. Subsets may be selected on the basis of chemical diversity, molecular properties, biological activity diversity, or biological target focus. Previously we described a novel form of subset screening: plate-based diversity subset (PBDS) screening, in which the screening subset is constructed by plate selection (rather than individual compound cherry-picking), using algorithms that select for compound quality and chemical diversity on a plate basis. In this paper, we describe a second generation approach to the construction of an updated subset: PBDS2, using both plate and individual compound selection, that has an improved coverage of the chemical space of the screening file, whilst only selecting the same number of plates for screening. We describe the validation of PBDS2 and its successful use in hit and lead discovery. PBDS2 screening became the default mode of singleton (one compound per well) HTS for lead discovery in Pfizer