Functional Electrochemistry: On-Nerve Assessment of Electrode Materials for Electrochemistry and Functional Neurostimulation.

Emerging therapies in bioelectronic medicine highlight the need for deeper understanding of electrode material performance in the context of tissue stimulation. Electrochemical properties are characterized on the benchtop, facilitating standardization across experiments. On-nerve electrochemistry differs from benchtop characterization and the relationship between electrochemical performance and nerve activation thresholds are not commonly established. This relationship is important in understanding differences between electrical stimulation requirements and electrode performance. We report functional electrochemistry as a follow-up to benchtop testing, describing a novel experimental approach for evaluating on-nerve electrochemical performance in the context of nerve activation. An ex-vivo rat sciatic nerve preparation was developed to quantify activation thresholds of fiber subtypes and electrode material charge injection limits for platinum iridium, iridium oxide, titanium nitride and PEDOT. Finally, we address experimental complexities arising in these studies, and demonstrate statistical solutions that support rigorous material performance comparisons for decision making in neural interface development.

The repurposing of Tebipenem pivoxil as alternative therapy for severe gastrointestinal infections caused by extensively drug-resistant Shigella spp.

Background: Diarrhoea remains one of the leading causes of childhood mortality globally. Recent epidemiological studies conducted in low-middle income countries (LMICs) identified Shigella spp. as the first and second most predominant agent of dysentery and moderate diarrhoea, respectively. Antimicrobial therapy is often necessary for Shigella infections; however, we are reaching a crisis point with efficacious antimicrobials. The rapid emergence of resistance against existing antimicrobials in Shigella spp. poses a serious global health problem. Methods: Aiming to identify alternative antimicrobial chemicals with activity against antimicrobial resistant Shigella, we initiated a collaborative academia-industry drug discovery project, applying high-throughput phenotypic screening across broad chemical diversity and followed a lead compound through in vitro and in vivo characterisation. Results: We identified several known antimicrobial compound classes with antibacterial activity against Shigella. These compounds included the oral carbapenem Tebipenem, which was found to be highly potent against broadly susceptible Shigella and contemporary MDR variants for which we perform detailed pre-clinical testing. Additional in vitro screening demonstrated that Tebipenem had activity against a wide range of other non-Shigella enteric bacteria. Cognisant of the risk for the development of resistance against monotherapy, we identified synergistic behaviour of two different drug combinations incorporating Tebipenem. We found the orally bioavailable prodrug (Tebipenem pivoxil) had ideal pharmacokinetic properties for treating enteric pathogens and was effective in clearing the gut of infecting organisms when administered to Shigella-infected mice and gnotobiotic piglets. Conclusions: Our data highlight the emerging antimicrobial resistance crisis and shows that Tebipenem pivoxil (licenced for paediatric respiratory tract infections in Japan) should be accelerated into human trials and could be repurposed as an effective treatment for severe diarrhoea caused by MDR Shigella and other enteric pathogens in LMICs. Funding: Tres Cantos Open Lab Foundation (projects TC239 and TC246), the Bill and Melinda Gates Foundation (grant OPP1172483) and Wellcome (215515/Z/19/Z).

Benchmarking network propagation methods for disease gene identification.

In-silico identification of potential target genes for disease is an essential aspect of drug target discovery. Recent studies suggest that successful targets can be found through by leveraging genetic, genomic and protein interaction information. Here, we systematically tested the ability of 12 varied algorithms, based on network propagation, to identify genes that have been targeted by any drug, on gene-disease data from 22 common non-cancerous diseases in OpenTargets. We considered two biological networks, six performance metrics and compared two types of input gene-disease association scores. The impact of the design factors in performance was quantified through additive explanatory models. Standard cross-validation led to over-optimistic performance estimates due to the presence of protein complexes. In order to obtain realistic estimates, we introduced two novel protein complex-aware cross-validation schemes. When seeding biological networks with known drug targets, machine learning and diffusion-based methods found around 2-4 true targets within the top 20 suggestions. Seeding the networks with genes associated to disease by genetics decreased performance below 1 true hit on average. The use of a larger network, although noisier, improved overall performance. We conclude that diffusion-based prioritisers and machine learning applied to diffusion-based features are suited for drug discovery in practice and improve over simpler neighbour-voting methods. We also demonstrate the large impact of choosing an adequate validation strategy and the definition of seed disease genes.

Pathway-based dissection of the genomic heterogeneity of cancer hallmarks' acquisition with SLAPenrich.

Cancer hallmarks are evolutionary traits required by a tumour to develop. While extensively characterised, the way these traits are achieved through the accumulation of somatic mutations in key biological pathways is not fully understood. To shed light on this subject, we characterised the landscape of pathway alterations associated with somatic mutations observed in 4,415 patients across ten cancer types, using 374 orthogonal pathway gene-sets mapped onto canonical cancer hallmarks. Towards this end, we developed SLAPenrich: a computational method based on population-level statistics, freely available as an open source R package. Assembling the identified pathway alterations into sets of hallmark signatures allowed us to connect somatic mutations to clinically interpretable cancer mechanisms. Further, we explored the heterogeneity of these signatures, in terms of ratio of altered pathways associated with each individual hallmark, assuming that this is reflective of the extent of selective advantage provided to the cancer type under consideration. Our analysis revealed the predominance of certain hallmarks in specific cancer types, thus suggesting different evolutionary trajectories across cancer lineages. Finally, although many pathway alteration enrichments are guided by somatic mutations in frequently altered high-confidence cancer genes, excluding these driver mutations preserves the hallmark heterogeneity signatures, thus the detected hallmarks' predominance across cancer types. As a consequence, we propose the hallmark signatures as a ground truth to characterise tails of infrequent genomic alterations and identify potential novel cancer driver genes and networks.

The novel mu-opioid antagonist, GSK1521498, reduces ethanol consumption in C57BL/6J mice.

RATIONALE: Using the drinking-in-the-dark (DID) model, we compared the effects of a novel mu-opioid receptor antagonist, GSK1521498, with naltrexone, a licensed treatment of alcohol dependence, on ethanol consumption in mice. OBJECTIVE: We test the ability of GSK1521498 to reduce alcohol consumption and compare its intrinsic efficacy to that of naltrexone by comparing the two drugs at doses matched for equivalent receptor occupancy. METHODS: Thirty-six C57BL/6J mice were tested in a DID procedure. In 2-day cycles, animals experienced one baseline, injection-free session, and one test session when they received two injections, one of test drug and one placebo. All animals received GSK1521498 (0, 0.1, 1 and 3 mg/kg, i.p., 30 min pre-treatment) and naltrexone (0, 0.1, 1 and 3 mg/kg, s.c. 10 min pre-treatment) in a cross-over design. Receptor occupancies following the same doses were determined ex vivo in separate groups by autoradiography, using [3H]DAMGO. Binding in the region of interest was measured integrally by computer-assisted microdensitometry and corrected for non-specific binding. RESULTS: Both GSK1521498 and naltrexone dose-dependently decreased ethanol consumption. When drug doses were matched for 70-75% receptor occupancy, GSK1521498 3 mg/kg, i.p., caused a 2.5-fold greater reduction in alcohol consumption than naltrexone 0.1 mg/kg, s.c. Both GSK1521498 and naltrexone significantly reduced sucrose consumption at a dose of 1 mg/kg but not 0.1 mg/kg. In a test of conditioned taste aversion, GSK1521498 (3 mg/kg) reduced sucrose consumption 24 h following exposure to a conditioning injection. CONCLUSIONS: Both opioid receptor antagonists reduced alcohol consumption but GK1521498 has higher intrinsic efficacy than naltrexone.

Identification of BDNF sensitive electrophysiological markers of synaptic activity and their structural correlates in healthy subjects using a genetic approach utilizing the functional BDNF Val66Met polymorphism.

Increasing evidence suggests that synaptic dysfunction is a core pathophysiological hallmark of neurodegenerative disorders. Brain-derived neurotropic factor (BDNF) is key synaptogenic molecule and targeting synaptic repair through modulation of BDNF signalling has been suggested as a potential drug discovery strategy. The development of such "synaptogenic" therapies depend on the availability of BDNF sensitive markers of synaptic function that could be utilized as biomarkers for examining target engagement or drug efficacy in humans. Here we have utilized the BDNF Val66Met genetic polymorphism to examine the effect of the polymorphism and genetic load (i.e. Met allele load) on electrophysiological (EEG) markers of synaptic activity and their structural (MRI) correlates. Sixty healthy adults were prospectively recruited into the three genetic groups (Val/Val, Val/Met, Met/Met). Subjects also underwent fMRI, tDCS/TMS, and cognitive assessments as part of a larger study. Overall, some of the EEG markers of synaptic activity and brain structure measured with MRI were the most sensitive markers of the polymorphism. Met carriers showed decreased oscillatory activity and synchrony in the neural network subserving error-processing, as measured during a flanker task (ERN); and showed increased slow-wave activity during resting. There was no evidence for a Met load effect on the EEG measures and the polymorphism had no effects on MMN and P300. Met carriers also showed reduced grey matter volume in the anterior cingulate and in the (left) prefrontal cortex. Furthermore, anterior cingulate grey matter volume, and oscillatory EEG power during the flanker task predicted subsequent behavioural adaptation, indicating a BDNF dependent link between brain structure, function and behaviour associated with error processing and monitoring. These findings suggest that EEG markers such as ERN and resting EEG could be used as BDNF sensitive functional markers in early clinical development to examine target engagement or drug related efficacy of synaptic repair therapies in humans.

Attenuation of cocaine and heroin seeking by µ-opioid receptor antagonism.

RATIONALE: Evidence has implicated the endogenous opioids, in particular µ-opioid receptors, in emotional behavior and regulation of reward circuits, especially in the context of heroin addiction and hedonic responses to ingestive rewards. The µ-opioid receptor antagonist naltrexone (NTX) has been reported to be effective in preventing relapse to alcoholism and in reducing alcohol and cocaine craving during abstinence. OBJECTIVES: The aim of the present experiments was to investigate the effects of a novel selective µ-opioid receptor antagonist GSK1521498 on cocaine and heroin seeking and the primary reinforcement of drug self-administration behavior. METHODS: Rats were first trained to self-administer cocaine or heroin and then to seek the drugs over prolonged periods of time under a second-order schedule of reinforcement, in which responding is maintained by contingent presentation of a drug-associated conditioned reinforcer. On a stable baseline, animals were treated with either GSK1521498 (0.1, 1, 3 mg/kg; IP) or NTX (0.1, 1, 3 mg/kg; SC) before each test session. RESULTS: Cocaine seeking was dose-dependently decreased following GSK1521498 treatment. However, the same treatment had no effect on cocaine self-administration under a continuous reinforcement schedule. Treatment with NTX had a less pronounced but similar effect. GSK1521498, but not NTX, dose-dependently reduced heroin seeking both before and after infusion of the drug although both increased heroin self-administration under continuous reinforcement. CONCLUSIONS: These data suggest that GSK1521498, by reducing opioid receptor signaling at the µ-opioid receptor, may have therapeutic potential to reduce the propensity to seek cocaine or heroin and, additionally, to diminish the consequence of an initial relapse to heroin taking.

Macrolide antibiotics broadly and distinctively inhibit cytokine and chemokine production by COPD sputum cells in vitro.

Macrolide antibiotics are known to exert anti-inflammatory actions in vivo, including certain effects in COPD patients. In order to investigate the immunomodulatory profile of activity of macrolide antibiotics, we have studied the effects of azithromycin, clarithromycin, erythromycin and roxithromycin on the in vitro production of a panel of inflammatory mediators from cells isolated from human, steroid-naïve, COPD sputum samples. Macrolide effects were compared to three other commonly used anti-inflammatory compounds, the corticosteroid dexamethasone, the PDE4 inhibitor, roflumilast and the p38 kinase inhibitor, SB203580. Three of the four tested macrolides, azithromycin, clarithromycin and roxithromycin, exhibited pronounced, concentration-related reduction of IL-1ß, IL-6, IL-10, TNF-α, CCL3, CCL5, CCL20, CCL22, CXCL1, CXCL5, and G-CSF release. Further slight inhibitory effects on IL-1α, CXCL8, GM-CSF, and PAI-1 production were also observed. Erythromycin was very weakly active. Qualitatively and quantitatively, macrolides exerted distinctive and, compared to other tested classes of compounds, more pronounced immunomodulatory effects, particularly in terms of chemokine (CCL3, CCL5, CCL20, CCL22, and CXCL5), IL-1ß, G-CSF and PAI-1 release. The described modulation of inflammatory mediators could potentially contribute to further definition of biomarkers of macrolide anti-inflammatory activity in COPD.

Plasma protein biomarkers for depression and schizophrenia by multi analyte profiling of case-control collections.

Despite significant research efforts aimed at understanding the neurobiological underpinnings of psychiatric disorders, the diagnosis and the evaluation of treatment of these disorders are still based solely on relatively subjective assessment of symptoms. Therefore, biological markers which could improve the current classification of psychiatry disorders, and in perspective stratify patients on a biological basis into more homogeneous clinically distinct subgroups, are highly needed. In order to identify novel candidate biological markers for major depression and schizophrenia, we have applied a focused proteomic approach using plasma samples from a large case-control collection. Patients were diagnosed according to DSM criteria using structured interviews and a number of additional clinical variables and demographic information were assessed. Plasma samples from 245 depressed patients, 229 schizophrenic patients and 254 controls were submitted to multi analyte profiling allowing the evaluation of up to 79 proteins, including a series of cytokines, chemokines and neurotrophins previously suggested to be involved in the pathophysiology of depression and schizophrenia. Univariate data analysis showed more significant p-values than would be expected by chance and highlighted several proteins belonging to pathways or mechanisms previously suspected to be involved in the pathophysiology of major depression or schizophrenia, such as insulin and MMP-9 for depression, and BDNF, EGF and a number of chemokines for schizophrenia. Multivariate analysis was carried out to improve the differentiation of cases from controls and identify the most informative panel of markers. The results illustrate the potential of plasma biomarker profiling for psychiatric disorders, when conducted in large collections. The study highlighted a set of analytes as candidate biomarker signatures for depression and schizophrenia, warranting further investigation in independent collections.

Serum proteomic analysis during nicotine self-administration, extinction and relapse in rats.

Nicotine dependence is known to induce long-term neural adaptations in brain. The purpose of this study was to verify whether specific protein patterns related to nicotine self-administration states could also be detected in a peripheral tissue. A serum proteomic analysis was performed by 2-DE on samples taken at six time points: N, naïve; P, priming; S, self-administration; W, withdrawal; E, extinction; R, relapse. After image analysis, spot volume values were submitted to a principal component analysis and relevant comparisons were selected. In N versus S; S versus W; E versus R; S versus R and S versus E comparisons a clear separation between groups could be observed, suggesting that each self-administration state correlates with a specific protein expression pattern. Partial least squares discriminant analysis was adopted to rank proteins by the contribution to the overall separation. A number of spots were identified; among them, C reactive protein and haemopexin displayed a significant reduction after nicotine administration; two haemopexin isoforms were decreased in the S state and antithrombin III was increased in the E phase. This study showed that specific protein patterns related to the nicotine self-administration states exist in serum. Further development of this approach may provide biomarkers to assess dependence states of drug-taking individuals.

Proteomic identification and early validation of complement 1 inhibitor and pigment epithelium-derived factor: Two novel biomarkers of Alzheimer's disease in human plasma.

Emerging disease modifying therapeutic strategies for Alzheimer's disease (AD) have generated a critical need for biomarkers of early stage disease. Here, we describe the identification and assessment of a number of candidate biomarkers in patients with mild to moderate probable AD. Plasma from 47 probable Alzheimer's patients and 47 matched controls were analysed by proteomics to define a significant number of proteins whose expression appeared to be associated with AD. These were compared to a similar proteomic comparison of a mouse transgenic model of amyloidosis, which showed encouraging overlap with the human data. From these studies a prioritised list of 31 proteins were then analysed by immunoassay and/or functional assay in the same human cohort to verify the changes observed. Eight proteins continued to show significance by either immunoassay or functional assay in the human plasma and these were tested in a further set of 100 probable AD patients and 100 controls from the original cohort. From our data it appeared that two proteins, serpin F1 (pigment epithelium-derived factor) and complement C1 inhibitor are down-regulated in plasma from AD patients.