Guide Target Selection Research Articles

Controlling Antigen Fate in Therapeutic Cancer Vaccines by Targeting Dendritic Cell Receptors.

Antigen-presenting cells (APCs) orchestrate immune responses and are therefore of interest for the targeted delivery of therapeutic vaccines. Dendritic cells (DCs) are professional APCs that excel in presentation of exogenous antigens toward CD4+ T helper cells, as well as cytotoxic CD8+ T cells. DCs are highly heterogeneous and can be divided into subpopulations that differ in abundance, function, and phenotype, such as differential expression of endocytic receptor molecules. It is firmly established that targeting antigens to DC receptors enhances the efficacy of therapeutic vaccines. While most studies emphasize the importance of targeting a specific DC subset, we argue that the differential intracellular routing downstream of the targeted receptors within the DC subset should also be considered. Here, we review the mouse and human receptors studied as target for therapeutic vaccines, focusing on antibody and ligand conjugates and how their targeting affects antigen presentation. We aim to delineate how targeting distinct receptors affects antigen presentation and vaccine efficacy, which will guide target selection for future therapeutic vaccine development.

Target-Distractor Competition Modulates Saccade Trajectories in Space and Object Space.

Saccade planning and execution can be affected by a multitude of factors present in a target selection task. Recent studies have shown that the similarity between a target and nearby distractors affects the curvature of saccade trajectories, because of target-distractor competition. To further understand the nature of this competition, we varied the distance between and the similarity of complex target and distractor objects in a delayed match-to-sample task to examine their effects on human saccade trajectories and better understand the underlying neural circuitry. For trials with short saccadic reaction times (SRTs) when target-distractor competition is still active, the distractor is attractive and saccade trajectories are deviated toward the distractor. We found a robust effect of distance consistent with saccade vector averaging, whereas the effect of similarity suggested the existence of an object-based suppressive surround. At longer SRTs, there was sufficient time for competition between the objects to complete and the distractor to be repulsive, which resulted in saccade trajectory deviations away from the distractor exhibiting the effects of a spatial suppressive surround. In terms of similarity, as the target-distractor similarity decreased, the initial saccade angle shifted toward the target, reflecting stronger distractor inhibition. There were no interactions between distance and similarity at any point in the time course of target-distractor competition. Together, saccade trajectories reflect target-distractor competition that is affected independently by both spatial and object space suppressive surrounds. The differences in saccade trajectories at short and long SRTs distinguish between active and completed decision-making processes.

The Sparse Atmospheric Model Sampling Analysis (SAMOSA) Intercomparison: Motivations and Protocol Version 1.0: A CUISINES Model Intercomparison Project

Planets in synchronous rotation around low-mass stars are the most salient targets for current ground- and space-based missions to observe and characterize. Such model calculations can help to prioritize targets for observation with current and future missions; however, intrinsic differences in the complexity and physical parameterizations of various models can lead to different predictions of a planet’s climate state. Understanding model differences is necessary if such models are to guide target selection and aid in the analysis of observations. This paper presents a protocol to intercompare models of a hypothetical planet with a 15-day synchronous rotation period around a 3000 K blackbody star across a parameter space of surface pressure and incident instellation. We conduct a sparse sample of 16 cases from a previously published exploration of this parameter space with the ExoPlaSim model. By selecting particular cases across this broad parameter space, the SAMOSA intercomparison will identify areas where simpler models are sufficient, as well as areas where more complex GCMs are required. Our preliminary comparison using ExoCAM shows general consistency between the climate state predicted by ExoCAM and ExoPlaSim except in regions of the parameter space most likely to be in a steam atmosphere or incipient runaway greenhouse state. We use this preliminary analysis to define several options for participation in the intercomparison by models of all levels of complexity. The participation of other GCMs is crucial to understand how the atmospheric states across this parameter space differ with model capabilities.

Comparison of ATP-binding pockets and discovery of homologous recombination inhibitors

The ATP binding sites of many enzymes are structurally related, which complicates their development as therapeutic targets. In this work, we explore a diverse set of ATPases and compare their ATP binding pockets using different strategies, including direct and indirect structural methods, in search of pockets attractive for drug discovery. We pursue different direct and indirect structural strategies, as well as ligandability assessments to help guide target selection. The analyses indicate human RAD51, an enzyme crucial in homologous recombination, as a promising, tractable target. Inhibition of RAD51 has shown promise in the treatment of certain cancers but more potent inhibitors are needed. Thus, we design compounds computationally against the ATP binding pocket of RAD51 with consideration of multiple criteria, including predicted specificity, drug-likeness, and toxicity. The molecules designed are evaluated experimentally using molecular and cell-based assays. Our results provide two novel hit compounds against RAD51 and illustrate a computational pipeline to design new inhibitors against ATPases.

Defining molecular glues with a dual-nanobody cannabidiol sensor

“Molecular glue” (MG) is a term coined to describe the mechanism of action of the plant hormone auxin and subsequently used to characterize synthetic small molecule protein degraders exemplified by immune-modulatory imide drugs (IMiDs). Prospective development of MGs, however, has been hampered by its elusive definition and thermodynamic characteristics. Here, we report the crystal structure of a dual-nanobody cannabidiol-sensing system, in which the ligand promotes protein-protein interaction in a manner analogous to auxin. Through quantitative analyses, we draw close parallels among the dual-nanobody cannabidiol sensor, the auxin perception complex, and the IMiDs-bound CRL4CRBN E3, which can bind and ubiquitinate “neo-substrates”. All three systems, including the recruitment of IKZF1 and CK1α to CRBN, are characterized by the lack of ligand binding activity in at least one protein partner and an under-appreciated preexisting low micromolar affinity between the two proteinaceous subunits that is enhanced by the ligand to reach the nanomolar range. These two unifying features define MGs as a special class of proximity inducers distinct from bifunctional compounds and can be used as criteria to guide target selection for future rational discovery of MGs.

Perturbation of resting-state network nodes preferentially propagates to structurally rather than functionally connected regions

Combining Transcranial Magnetic Stimulation (TMS) with electroencephalography (EEG) offers the opportunity to study signal propagation dynamics at high temporal resolution in the human brain. TMS pulse induces a local effect which propagates across cortical networks engaging distant cortical and subcortical sites. However, the degree of propagation supported by the structural compared to functional connectome remains unclear. Clarifying this issue would help tailor TMS interventions to maximize target engagement. The goal of this study was to establish the contribution of functional and structural connectivity in predicting TMSinducedsignal propagation after perturbation of two distinct brain networks. For this purpose,24 healthy individuals underwent two identical TMS-EEG visits where neuronavigated TMS pulses were delivered to nodes of the default mode network (DMN) and the dorsal attention network (DAN). The functional and structural connectivity derived from each individual stimulation spot were characterized via functional magnetic resonance imaging (fMRI) and Diffusion Weighted Imaging (DWI), and signal propagation across these two metrics was compared. Direct comparison between the signal extracted from brain regions either functionally or structurally connected to the stimulation sites, shows a stronger activation overcortical areas connected via white matter pathways, with a minor contribution of functional projections. This pattern was not observed when analyzing spontaneous resting state EEG activity. Overall, results suggest that structural links can predict network-level response to perturbation more accurately than functional connectivity. Additionally, DWI-based estimation of propagation patterns can be used to estimate off-target engagement of other networks and possibly guide target selection to maximize specificity.

Targeting Transients: The Strategic Logic for Terrorist Targeting of Internally Displaced Persons

AbstractThe number of internally displaced persons (IDPs) around the world has risen to astronomical levels—approximately 33 million individuals were driven from their homes in 2019 alone. Yet, despite the history of violence which has been perpetrated against these IDPs, little research has been done to uncover the strategic logic for attacking these transient individuals. This paper seeks to fill that gap in the literature through the lens of the West African insurgency known as Boko Haram. While the group has been noted for its tendency to conduct suicide bombings, it has recently added IDP camps to its target profile, in a unique consistent and sustained effort against IDPs by a terrorist organization. In analyzing this case study, I ask: why do terrorist organizations target IDPs in the first place? Is there any existing theory of target selection which explains the targeting of IDP camps at high frequencies? Leveraging a unique dataset tracking all of Boko Haram's suicide bombings from April 2011 to August 2020, this article tests three theories of terrorist target selection to explain this phenomenon. First, it illustrates that theories of efficiency and casualty maximization cannot explain Boko Haram's IDP camp attacks, given the high rates of failure and low rates of casualties. Second, it shows that Boko Haram's targeting practices cannot be understood solely by ideology, as the group only makes religious decisions about who can be victimized, not who should. Instead, the article argues that signaling theory should be extended to target selection—specifically, that targeting of IDP camps can be viewed as part of a broader signaling campaign, which has motivated the group's overall use of suicide bombing. Such insight suggests that signaling theories may guide target selection over time for many terrorist organizations, to communicate that the local and international community are powerless and that the terrorist group cannot be defeated.

Combined Metabolome and Lipidome Analyses for In-Depth Characterization of Lipid Accumulation in the DHA Producing Aurantiochytrium sp. T66.

Thraustochytrids are marine heterotrophic microorganisms known for their potential to accumulate docosahexaenoic acid (DHA)-enriched lipids. There have been many attempts to improve thraustochytrid DHA bioprocesses, especially through traditional optimization of cultivation and media conditions. Nevertheless, thraustochytrid-based bioprocesses are still not commercially competitive for high volume-low cost production of DHA. Thus, it is realized that genetic and metabolic engineering strategies are needed for the development of commercially competitive thraustochytrid DHA cell factories. Here, we present an analytical workflow for high resolution phenotyping at metabolite and lipid levels to generate deeper insight into the thraustochytrid physiology, with particular focus on central carbon and redox metabolism. We use time-series sampling during unlimited growth and nitrogen depleted triggering of DHA synthesis and lipid accumulation (LA) to show-case our methodology. The mass spectrometric absolute quantitative metabolite profiling covered glycolytic, pentose phosphate pathway (PPP) and tricarboxylic acid cycle (TCA) metabolites, amino acids, complete (deoxy)nucleoside phosphate pools, CoA and NAD metabolites, while semiquantitative high-resolution supercritical fluid chromatography MS/MS was applied for the lipid profiling. Interestingly, trace amounts of a triacylglycerols (TG) with DHA incorporated in all three acyl positions was detected, while TGs 16:0_16:0_22:6 and 16:0_22:6_22:6 were among the dominant lipid species. The metabolite profiling data indicated that lipid accumulation is not limited by availability of the acyl chain carbon precursor acetyl-CoA nor reducing power (NADPH) but rather points to the TG head group precursor glycerol-3-phosphate as the potential cause at the metabolite level for the gradual decline in lipid production throughout the cultivation. This high-resolution phenotyping provides new knowledge of changes in the central metabolism during growth and LA in thraustochytrids and will guide target selection for metabolic engineering needed for further improvements of this DHA cell factory.

Explicit Grammatical Intervention for Developmental Language Disorder: Three Approaches.

Purpose This article summarizes the shared principles and evidence underpinning methods employed in the three sentence-level (syntactic) grammatical intervention approaches developed by the authors. We discuss associated clinical resources and map a way forward for clinically useful research in this area. Method We provide an overview of the principles and perspectives that are common across our three syntactic intervention approaches: MetaTaal (Zwitserlood, 2015; Zwitserlood, Wijnen, et al., 2015), the SHAPE CODING system (Ebbels, 2007; Ebbels et al., 2014, 2007), and Complex Sentence Intervention (Balthazar & Scott, 2017, 2018). A description of each approach provides examples and summarizes current evidence supporting effectiveness for children with developmental language disorder ranging in age from 5 to 16 years. We suggest promising directions for future research that will advance our understanding of effective practices and support more widespread adoption of syntactic interventions with school-age children. Conclusion In each approach to syntactic intervention, careful and detailed analysis of grammatical knowledge is used to support target selection. Intervention targets are explicitly described and presented systematically using multimodal representations within engaging and functional activities. Treatment stimuli are varied within a target pattern in order to maximize learning. Similar intervention intervals and intensities have been studied and proven clinically feasible and have produced measurable effects. We identify a need for more research evidence to maximize the effectiveness of our grammatical interventions, encompassing languages other than English, as well as practical clinical tools to guide target selection, measurement of outcomes, and decisions about how to tailor interventions to individual needs.

NIMG-32. CHALLENGES OF IMAGING INTERPRETATION TO PREDICT OLIGODENDROGLIOMA GRADE

Abstract BACKGROUND A recent report examining 75 Oligodendrogliomas indicated that specific imaging features may help predict grading and guide target selection for biopsy when resection is not possible. This report attempted to validate these findings in a separate sample and evaluate interrater reliability. METHODS Two Neuro-Oncologists, blinded to radiology report and grading reviewed diagnostic pre-radiation MRI. Imaging features and reviewer interpretations were evaluated included contrast enhancement, necrosis, calcification, and restricted diffusion; examiner concordance is reported. RESULTS Sixty-two patients with diagnosis of Oligodendroglioma (50 WHO grade II, 12 WHO grade III); 54 were molecularly confirmed as IDH-mutant/1p19q co-deleted based on the NOB Natural History Study. Four patients (grade III) were excluded due to lack of imaging studies. Among 58 evaluable patients, their location was frontal (n=32), temporal (n=14), parietal (n=4), occipital (n=1), and multi-lobe (n=11). Extent of resection: gross total 9, subtotal 36, biopsy 17. Partial to extensive contrast enhancement was present in 18/58 patients (6 grade II, 33%; 12 grade III, 67%); Kappa interrater agreement k= 0.37 on grade II and k=0.50 on grade III; extensive enhancement was present in 4/58 (all grade III), k= 0.70. Necrosis noted in 7/58 patients (all grade III), k=0.61. Calcification noted in 7/17 patients reviewed (all grade III), k=1.0; restriction noted in only 2/39 patients reviewed (all grade III), k=1.0. CONCLUSIONS THE presence of extensive enhancement, necrosis, calcification and restricted diffusion were only present in grade III with substantial agreement between readers, but there was lower agreement for partial enhancement. Image reviewers commented on the variability of enhancement intensity in normal structures between scans, likely contributing to this poor concordance. Tumor areas with extensive enhancement and/or necrosis are associated with higher grade and can guide biopsy if resection is not feasible. Discrepancies in imaging interpretation may be ameliorated by implementing a standardized imaging protocol.

Remanent magnetization mapping: A tool for greenfields magmatic Ni-Cu-PGE exploration undercover: Part 2

Remanent magnetization dominates induced magnetization in several types of mafic-ultramafic magmatic rocks, and where it is strong, allows remote targeting of mafic lithologies based purely on their magnetization direction. We evaluate practical methods for utilising remanent magnetization as a first pass tool for Ni-Cu-PGE exploration in remote, undercover areas, using examples from the Huckitta area, Central Australia. Modeling results demonstrate that measured magnetizations can be used to accurately model target intrusions regionally. However, of the two automated methods tested for remote mapping of magnetization, neither produced results consistent with prior modeling, or with measured magnetization directions. A customised reduction to pole (RTP) grid transformation based on measured magnetization directions is a simpler, more effective method of mapping specific mafic suites regionally, and was used to guide target selection in an undercover area in the east Arunta region. Several model geometries (e.g., plunging prism, ellipsoid, etc.), constrained by the regionally dominant magnetization, were used to provide a range of end-member target bodies for evaluation. Target models’ volume and depth below surface were used to constrain estimates of economic mineral potential (i.e., volume of modeled body × conservative grade) and “minability” (distance from infrastructure + depth of overburden), as a method of vetting targets in a greenfields exploration program. This is an effective method to discard prospects with almost no chance of being economically viable, and allowed exploration to be focused on follow-up airborne electromagnetic (EM) surveys on targets in the region that were most likely to be economically significant.

High-dimensional single-cell proteomics analysis identifies immune checkpoint signatures and therapeutic targets in ulcerative colitis.

Immune checkpoints are regulators of immune cells and play key roles in the modulation of immune responses. The role of checkpoints in autoimmune disease is poorly understood but likely to be central since checkpoint inhibition during cancer treatment can cause autoimmunity. We generated a high-dimensional single-cell proteomics data set from PBMCs of healthy individuals and patients with ulcerative colitis (UC) by mass cytometry, enabling systems-wide analyses of immune cell frequencies and cell type-specific expression patterns of 12 immune checkpoints. Subtle but significant changes in immune cell frequencies and checkpoint expression were observed between UC patients on different treatment regimens and between patients and healthy controls. Most strikingly, UC patients showed a reduced number of peripheral NK-cells and those cells showed an altered phenotype including increased TIGIT expression. Based on these results, we modulated NK-cell function ex vivo through targeting of TIGIT pathway members. In summary, we describe a pattern of changes in immune cell abundance and checkpoint expression as a basis for UC patient stratification and we show modulation of a corresponding immune cell subset through checkpoint targeting. Our approach can be used for the identification of pathogenic immune cell subsets and guide target selection in autoimmunity and chronic inflammation.

Habitable Moist Atmospheres on Terrestrial Planets near the Inner Edge of the Habitable Zone around M Dwarfs

Abstract Terrestrial planets in the habitable zones (HZs) of low-mass stars and cool dwarfs have received significant scrutiny recently. Transit spectroscopy of such planets with the James Webb Space Telescope (JWST) represents our best shot at obtaining the spectrum of a habitable planet within the next decade. As these planets are likely tidally locked, improved 3D numerical simulations of such planetary atmospheres are needed to guide target selection. Here we use a 3D climate system model, updated with new water-vapor absorption coefficients derived from the HITRAN 2012 database, to study ocean-covered planets at the inner edge of the HZ around late M to mid-K stars ( ). Our results indicate that these updated water-vapor coefficients result in significant warming compared to previous studies, so the inner HZ around M dwarfs is not as close as suggested by earlier work. Assuming synchronously rotating Earth-sized and Earth-mass planets with background 1 bar atmospheres, we find that planets at the inner HZ of stars with undergo the classical “moist greenhouse” ( mixing ratio in the stratosphere) at significantly lower surface temperature (∼280 K) in our 3D model compared with 1D climate models (∼340 K). This implies that some planets around low-mass stars can simultaneously undergo water loss and remain habitable. However, for stars with , planets at the inner HZ may directly transition to a runaway state, while bypassing the moist greenhouse water loss entirely. We analyze transmission spectra of planets in a moist greenhouse regime and find that there are several prominent features, including a broad feature between 5 and 8 μm, within JWST MIRI instrument range. Thus, relying only on standard Earth-analog spectra with 24 hr rotation period around M dwarfs for habitability studies will miss the strong features that one would expect to see on synchronously rotating planets around M dwarf stars, with JWST.

Abstract 686: onTARGET: a new computational strategy to predict in vivo relevant targets against neuroblastoma

Abstract One of the main bottlenecks of anticancer drug development is the assessment of the in vivo relevance of emerging therapies. Previously, drugs that suppress the in vivo progression of neuroblastoma have been hard to identify. To address this problem, we propose a new computational technique, onTARGET, that enables researchers to select, with good accuracy, compounds that are likely to induce changes in cellular pathways that are consistent with specific clinical outcomes and subgroups. onTARGET prediction is based on an integration of massive expression and other data resources, including the NIH LINCS dataset (with 1,300,000 expression profiles), the NIH TARGET and R2-AMC neuroblastoma cohorts, and our own in-house databases. In a first step, the datasets are preprocessed by factor analysis to remove systematic bias in these large data sets. In a second step, Bayesian statistics are applied to prioritize compounds whose cellular responses match clinically relevant differences between patient subsets, such as MYCN status, survival hazard ratio, or histopathological assessment. To evaluate the method, we used onTARGET prediction to identify compounds and gene targets relevant for clinical outcomes in the NIH-TARGET (n=249) and R2-AMC (n=98) neuroblastoma cohorts. The algorithm confirmed existing targets and made interesting predictions. Of 50 the top-ranking compounds associated with a survival outcome, agents targeting the mTOR/PI3K axis are highly prevalent. The algorithm correctly predicts targeting of the MYC pathway, and predicts possible modulators of MYC signaling, such as TRRAP, AURKA and BMP2. In addition to nominating agents with a favorable outcome, the algorithm can also flag compounds that might worsen prognosis, further facilitating the prioritization of targets for evaluation. In summary, onTARGET may guide target selection for neuroblastoma studies and can be adapted for other cancers as well. The many targets that were identified immediately suggest an opportunity for continued evaluation in cells and in vivo models. This work has been initiated in collaboration with researchers at Lund University. Citation Format: Elin Almstedt, Ingrid Lönnstedt, Cecilia Krona, Sven Nelander. onTARGET: a new computational strategy to predict in vivo relevant targets against neuroblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 686. doi:10.1158/1538-7445.AM2017-686

Use of mathematics to guide target selection in systems pharmacology; application to receptor tyrosine kinase (RTK) pathways

A key element of the drug discovery process is target selection. Although the topic is subject to much discussion and experimental effort, there are no defined quantitative rules around optimal selection. Often ‘rules of thumb’, that have not been subject to rigorous exploration, are used. In this paper we explore the ‘rule of thumb’ notion that the molecule that initiates a pathway signal is the optimal target. Given the multi-factorial and complex nature of this question, we have simplified an example pathway to its logical minimum of two steps and used a mathematical model of this to explore the different options in the context of typical small and large molecule drugs. In this paper, we report the conclusions of our analysis and describe the analysis tool and methods used. These provide a platform to enable a more extensive enquiry into this important topic.

The spatially global control of attentional target selection in visual search

ABSTRACTGlyn Humphreys and his co-workers have made numerous important theoretical and empirical contributions to research on visual search. They have introduced the concept of attentional target templates and investigated the nature of these templates and how they are involved in the control of search performance. In the experiments reported here, we investigated whether feature-specific search templates for particular colours can guide target selection independently for different regions of visual space. We employed behavioural and electrophysiological markers of attentional selection in tasks with targets defined by specific colour/location combinations. In Experiment 1, participants searched for pairs of colour targets in a particular spatial configuration (e.g., red in the upper and blue in the lower visual field). In Experiment 2, they searched for single colour-defined targets at specific locations (e.g., red on the left or blue on the right). Target displays were preceded by non-informative cues containing target-colour items at task-set matching or mismatching locations. Contingent attentional capture was observed only for matching cues. However, both matching and mismatching cues elicited identical N2pc components, indicating equivalent attentional capture. This shows that the rapid deployment of attention towards target features is spatially non-selective, and that selection of colour/location combinations occurs at later post-perceptual stages. This was further corroborated in search displays where targets were accompanied by target-colour distractors at nonmatching locations. Here, spatial biases towards the target emerged late and were strongly attenuated relative to displays without such distractors. These results demonstrate that attentional templates for target-defining features operate in a spatially-global fashion. Feature-based guidance of visual search cannot be restricted to particular locations even when this is required by the demands of an attentional selection task.

Object-based selection modulates top-down attentional shifts

A large body of evidence supports that visual attention – the cognitive process of selectively concentrating on a salient or task-relevant subset of visual information – often works on object-based representation. Recent studies have postulated two possible accounts for the object-specific attentional advantage: attentional spreading and attentional prioritization, each of which modulates a bottom-up signal for sensory processing and a top-down signal for attentional allocation, respectively. It is still unclear which account can explain the object-specific attentional advantage. To address this issue, we examined the influence of object-specific advantage on two types of visual search: parallel search, invoked when a bottom-up signal is fully available at a target location, and serial search, invoked when a bottom-up signal is not enough to guide target selection and a top-down control for shifting of focused attention is required. Our results revealed that the object-specific advantage is given to the serial search but not to the parallel search, suggesting that object-based attention facilitates stimulus processing by affecting the priority of attentional shifts rather than by enhancing sensory signals. Thus, our findings support the notion that the object-specific attentional advantage can be explained by attentional prioritization but not attentional spreading.

Technological advances in the surgical treatment of movement disorders.

Technological innovations have driven the advancement of the surgical treatment of movement disorders, from the invention of the stereotactic frame to the adaptation of deep brain stimulation (DBS). Along these lines, this review will describe recent advances in inserting neuromodulation modalities, including DBS, to the target, and in the delivery of therapy at the target. Recent radiological advances are altering the way that DBS leads are targeted and inserted, by refining the ability to visualize the subcortical targets using high-field strength magnetic resonance imaging and other innovations, such as diffusion tensor imaging, and the development of novel targeting devices enabling purely anatomical implantations without the need for neurophysiological monitoring. New portable computed tomography scanners also are facilitating lead implantation without monitoring, as well as improving radiological verification of DBS lead location. Advances in neurophysiological mapping include efforts to develop automatic target verification algorithms, and probabilistic maps to guide target selection. The delivery of therapy at the target is being improved by the development of the next generation of internal pulse generators (IPGs). These include constant current devices that mitigate the variability introduced by impedance changes of the stimulated tissue and, in the near future, devices that deliver novel stimulation patterns with improved efficiency. Closed-loop adaptive IPGs are being tested, which may tailor stimulation to ongoing changes in the nervous system, reflected in biomarkers continuously recorded by the devices. Finer-grained DBS leads, in conjunction with new IPGs and advanced programming tools, may offer improved outcomes via current steering algorithms. Finally, even thermocoagulation-essentially replaced by DBS-is being advanced by new minimally-invasive approaches that may improve this therapy for selected patients in whom it may be preferred. Functional neurosurgery has a history of being driven by technological innovation, a tradition that continues into its future.

Chemogenomics Profiling of Drug Targets of Peptidoglycan Biosynthesis Pathway in Leptospira interrogans by Virtual Screening Approaches

Leptospirosis is a worldwide zoonosis of global concern caused by Leptospira interrogans. The availability of ligand libraries has facilitated the search for novel drug targets using chemogenomics approaches, compared with the traditional method of drug discovery, which is time consuming and yields few leads with little intracellular information for guiding target selection. Recent subtractive genomics studies have revealed the putative drug targets in peptidoglycan biosynthesis pathways in Leptospira interrogans. Aligand library for the murD ligase enzyme in the peptidoglycan pathway has also been identified. Our approach in this research involves screening of the pre-existing ligand library of murD with related protein family members in the putative drug target assembly in the peptidoglycan biosynthesis pathway. A chemogenomics approach has been implemented here, which involves screening of known ligands of a protein family having analogous domain architecture for identification of leads for existing druggable protein family members. By means of this approach, one murC and one murF inhibitor were identified, providing a platform for developing an antileptospirosis drug targeting the peptidoglycan biosynthesis pathway. Given that the peptidoglycan biosynthesis pathway is exclusive to bacteria, the in silico identified mur ligase inhibitors are expected to be broad-spectrum Gram-negative inhibitors if synthesized and tested in in vitro and in vivo assays.

Measuring and manipulating brain connectivity with resting state functional connectivity magnetic resonance imaging (fcMRI) and transcranial magnetic stimulation (TMS).

Both resting state functional magnetic resonance imaging (fcMRI) and transcranial magnetic stimulation (TMS) are increasingly popular techniques that can be used to non-invasively measure brain connectivity in human subjects. TMS shows additional promise as a method to manipulate brain connectivity. In this review we discuss how these two complimentary tools can be combined to optimally study brain connectivity and manipulate distributed brain networks. Important clinical applications include using resting state fcMRI to guide target selection for TMS and using TMS to modulate pathological network interactions identified with resting state fcMRI. The combination of TMS and resting state fcMRI has the potential to accelerate the translation of both techniques into the clinical realm and promises a new approach to the diagnosis and treatment of neurological and psychiatric diseases that demonstrate network pathology.