NIH BRAIN Research Articles

Adenosine Metabolism Pathway Alterations in Frontal Cortical Neurons in Schizophrenia.

Schizophrenia is a neuropsychiatric illness characterized by altered neurotransmission, in which adenosine, a modulator of glutamate and dopamine, plays a critical role that is relatively unexplored in the human brain. In the present study, postmortem human brain tissue from the anterior cingulate cortex (ACC) of individuals with schizophrenia (n = 20) and sex- and age-matched control subjects without psychiatric illness (n = 20) was obtained from the Bronx-Mount Sinai NIH Brain and Tissue Repository. Enriched populations of ACC pyramidal neurons were isolated using laser microdissection (LMD). The mRNA expression levels of six key adenosine pathway components-adenosine kinase (ADK), equilibrative nucleoside transporters 1 and 2 (ENT1 and ENT2), ectonucleoside triphosphate diphosphohydrolases 1 and 3 (ENTPD1 and ENTPD3), and ecto-5'-nucleotidase (NT5E)-were quantified using real-time PCR (qPCR) in neurons from these individuals. No significant mRNA expression differences were observed between the schizophrenia and control groups (p > 0.05). However, a significant sex difference was found in ADK mRNA expression, with higher levels in male compared with female subjects (Mann-Whitney U = 86; p < 0.05), a finding significantly driven by disease (t(17) = 3.289; p < 0.05). Correlation analyses also demonstrated significant associations (n = 12) between the expression of several adenosine pathway components (p < 0.05). In our dementia severity analysis, ENTPD1 mRNA expression was significantly higher in males in the "mild" clinical dementia rating (CDR) bin compared with males in the "none" CDR bin (F(2, 13) = 5.212; p < 0.05). Lastly, antipsychotic analysis revealed no significant impact on the expression of adenosine pathway components between medicated and non-medicated schizophrenia subjects (p > 0.05). The observed sex-specific variations and inter-component correlations highlight the value of investigating sex differences in disease and contribute to the molecular basis of schizophrenia's pathology.

BRAIN @ 10: A decade of innovation

Now entering its second decade, the National Institutes of Health Brain Research Through Advancing Innovative Neurotechnologies Initiative, or the NIH BRAIN Initiative, has yielded remarkable success, accelerating research on the neural circuit basis of behavior and breaking new ground toward the treatment of complex human brain disorders.

Comparing the stability and reproducibility of brain-behavior relationships found using canonical correlation analysis and partial least squares within the ABCD sample.

Canonical correlation analysis (CCA) and partial least squares correlation (PLS) detect linear associations between two data matrices by computing latent variables (LVs) having maximal correlation (CCA) or covariance (PLS). This study compared the similarity and generalizability of CCA- and PLS-derived brain-behavior relationships. Data were accessed from the baseline Adolescent Brain Cognitive Development (ABCD) dataset (N > 9,000, 9-11 years). The brain matrix consisted of cortical thickness estimates from the Desikan-Killiany atlas. Two phenotypic scales were examined separately as the behavioral matrix; the Child Behavioral Checklist (CBCL) subscale scores and NIH Toolbox performance scores. Resampling methods were used to assess significance and generalizability of LVs. LV1 for the CBCL brain relationships was found to be significant, yet not consistently stable or reproducible, across CCA and PLS models (singular value: CCA = .13, PLS = .39, p < .001). LV1 for the NIH brain relationships showed similar relationships between CCA and PLS and was found to be stable and reproducible (singular value: CCA = .21, PLS = .43, p < .001). The current study suggests that stability and reproducibility of brain-behavior relationships identified by CCA and PLS are influenced by the statistical characteristics of the phenotypic measure used when applied to a large population-based pediatric sample.

Hyperspectral analysis of amyloid beta (Aβ) evolutional changes in preclinical to late‐stage Alzheimer’s disease using matched brain and retinal tissue

AbstractBackgroundAlzheimer’s disease (AD) is a progressive, degenerative brain disorder that leads to cognitive impairment and eventually death. It is marked by buildup of abnormal amyloid aggregates (Aβ) in the brain. This study aimed to elucidate the neuropathologic sequence and corresponding [RetiSpec] hyperspectral signals of Aβ evolutional changes in preclinical to late‐stage AD using retinal and brain samples.MethodWe used brain‐ and retina‐matched human tissue samples from the NIH Brain Bank at Johns Hopkins. Study groups included: No AD neuropathologic change with negative AD neuropathology (n = 15); Low‐level AD neuropathologic change with positive AD neuropathology (n = 15); High level AD neuropathologic change with positive AD neuropathology (n = 15). To validate retinal hyperspectral imaging (rHSI) detection of Aβ in these retinal samples, we quantified Aβ oligomers (AβOs) in human retinal tissue. Immunohistochemistry was performed. We used humanized, affinity‐matured, IgG2 mAβ selective biotinylated antibody (ACU‐193) to detect soluble AβOs in retinal and brain tissues followed by objective quantification of ACU193 retinal staining by performing annotations and data extraction using QuPath software. One‐way ANOVA and t‐tests were performed to compare between controls and AD stages.ResultWhen assessing ACU193 staining present from retinal tissue samples, we observed 29‐53% retinal tissue area positivity in controls and 15‐72% retinal tissue area positivity in the AD group. Level of AD pathology demonstrated an effect on the rHSI spectra (450‐600nm) in regions near the optic disc and the ventral periphery: intermediate AD pathology showed the strongest rHSI signature (decrease in optical transmittance) followed by high, then low AD pathology samples. Correlation of the Braak neurofibrillary tangle stage and ΔOD offered a Pearson r score of 0.79 (p = 0.004).ConclusionThis study was the first to assess and quantify AβOs in clinically, neuropathologically, and hyperspectrally characterized postmortem matched brain and retinal tissues. Progression of well‐established neuropathologically classified AD stages (e.g Braak) may correlate with retinal AβO levels measured using rHSI. Certain retina regions that share nervous tissue with the brain (optic disc, periphery) are likely more sensitive to rHSI‐mediated detection of AD pathology. Larger samples are needed to comprehensively assess and quantify retinal AβOs.

The Fifth Bioelectronic Medicine Summit Hosted by the Feinstein Institutes for Medical Research (Manhasset, NY) and Columbia Engineering (NY, NY) at The Garden City Hotel, Garden City, NY 11530 on October 11-12th, 2022- Bioelectronic Medicine: Today’s Tools, Tomorrow’s Therapies

The Fifth Bioelectronic Medicine Summit Hosted by the Feinstein Institutes for Medical Research (Manhasset, NY) and Columbia Engineering (NY, NY) at The Garden City Hotel, Garden City, NY 11530 on October 11-12th, 2022- Bioelectronic Medicine: Today’s Tools, Tomorrow’s Therapies

Better Approaches to Derisking Psychiatric Drug Development are Needed, Not New Funding Mechanisms.

The pulling back of large pharma from psychiatric drug development over the last 15 years has been a cause of concern. The uncertainty of success with any novel mechanism raises questions concerning whether current funding mechanisms for the various components of drug development need to be revisited. Alternatively, advances in neuroscience and translational methods may provide a sufficient incentive for continued private sector investment. Narrative commentary drawing on personal positions in both NIH and Industry devoted to translation of CNS compounds from bench to bedside coupled with specific examples of efforts to improve the selection of compounds to take into large clinical trials. Strategies for increasing R&D productivity in the field of CNS drugs articulated over a decade ago have been implemented over the same period with pre-competitive consortia involved in developing the tools needed to show that before being taken into large trials adequate evidence of postulated brain effects are required. In parallel, the field and the FDA have focused much more on the search for domain specific treatments rather than those depending on traditional measures of efficacy in DSM disorders. NIMH programs such as RDoC and the "Fast-Fail" initiative are provided as efforts which influence and involve partnerships with industry. The evolution of the field over the last decade is such that there is a shared focus across sources of funding in the public sector, especially NIH brain institutes, on the tools needed to de-risk psychiatric drug development to the degree needed to encourage private sector investment in the clinical trials needed to advance potential new treatments for areas of greatest need. Expansion of funding for translational tool development will have the highest impact on delivering novel treatments.

Survey of Investigators About Sharing Human Research Data in the Neurosciences.

In the neurosciences, significant opportunities for sharing individual-level data are underexploited. Commentators suggest various barriers to data sharing, which may need to be addressed. Investigators' perspectives on the main barriers are unclear. Furthermore, bioethicists have raised concerns about the potential misuse of neuroscience data, although discussions are hampered by uncertainty about the potential risks. It is unclear how common sensitive data are obtained and whether investigators judge them as sensitive. An online survey was disseminated among 1,190 principal investigators (PIs) of active National Institute of Neurological Disorders and Stroke, National Institute of Mental Health, or NIH Brain Research Through Advancing Innovative Neurotechnologies Initiative grants involving human subject research. A total of 397 investigators responded to the survey (response rate 33%). Most investigators (84%) support efforts to increase sharing of deidentified individual-level data. However, investigators perceive many barriers to data sharing. The largest barriers were costs and time; limited interpretation of the data without understanding the context of data collection; lack of incentives; limited standardization and norms for data acquisition, formatting, and description; and heterogeneity of data types. Several types of data described as sensitive in the literature are common among neuroscience studies, for example, neural correlates of behavior, emotions, or decision making (71%) and/or predictive data (54%). Although most investigators consider it unlikely or extremely unlikely for their research data to be misused to harm individual research participants (82%), the majority were at least slightly concerned about potential harm to individuals if their research data were misused (65%). Investigators with more easily reidentifiable data, data from vulnerable groups, and neural data were more concerned about the likelihood of misuse and/or magnitude of harm of misuse of their research data. We hope these data help prioritize the development of tools and strategies to overcome the main barriers to data sharing. Furthermore, these data provide input on what may be sensitive data for which additional safeguards should be considered.

Ways of Knowing of the Brain and Mind: A Scoping Review of the Literature About Global Indigenous Perspectives

Indigenous peoples’ pursuit of brain health has been challenged by the violation of their rights to practice their cultures, speak their languages, and engage in traditional medical practices. Despite ongoing systemic oppression, indigenous knowledges and healing practices endure today and contribute to global understandings of the brain and mind. We conducted a scoping review of the academic literature, both research and reviews, which has examined the perspectives of global Indigenous people relevant to the neurological sciences. We searched three academic databases using phrases and terms pertaining to brain, neuro, mind, and Indigenous populations. Of the 66 articles included for analysis, 46 were research and 20 reviews or commentaries. The earliest date of publication was 1963; the majority were published after 2000. Most research studies involved consultations through focus groups or interviews, and involved people spanning all age groups. Sixty Indigenous communities were identified in the articles across 21 countries and regions and five continents. By contrast, the countries of affiliation of the corresponding authors were far less diverse: two-thirds were affiliated with institutions in the USA, Canada, Australia, or New Zealand. Only seven authors were in Latin America or Asia, and there were no corresponding authors primarily affiliated with institutions in Africa. The most prevalent focus of the articles was on mental health and illness, followed by aging and dementia. Ethics topics were embedded in two-thirds of articles, with substantial coverage of issues pertaining to public policy and public health, and cultural diversity and heterogeneity. The concepts of wellness and well-being, spirituality, holism and relationality were prominent reference features of this diverse body of research. This work supports the meaningful incorporation of Indigenous knowledges into initiatives involving the neurological sciences, such as the International Brain Initiative, the Canadian Brain Research Strategy, and the USA NIH BRAIN 2.0. Research with Indigenous populations that is collaborative and situates ethics at its core is key to the realization of a truly global, collaborative neuroscience. J Neurol Res. 2022;12(2):43-53 doi: https://doi.org/10.14740/jnr708

BRAIN 2.0: Transforming neuroscience

The NIH BRAIN Initiative is entering a new phase. Three large new projects-a comprehensive human brain cell atlas, a whole mammalian brain microconnectivity map, and tools for precision access to brain cell types-promise to transform neuroscience research and the treatment of human brain disorders.

Advancing scientific excellence through inclusivity in the NIH BRAIN Initiative

Leveraging breadth and depth of the scientific workforce invites creativity, relevance, and differing views that directly tie into innovation and problem solving. The NIH BRAIN Initiative is using a multi-pronged strategy to enhance diversity and inclusion toward promoting the best science.

NIH BRAIN Circuits Programs: An Experiment in Supporting Team Neuroscience

The NIH BRAIN Initiative is aimed at revolutionizing our understanding of the human brain. Here, we present a discussion of support for team research in investigative neuroscience at different stages and on various scales.

NeuroEthics and the BRAIN Initiative: Where Are We? Where Are We Going?

From its inception, the NIH Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative, an ambitious project focused on understanding the human brain, has made a concerted effort to integrate neuroethics into its science. In the past five years, the BRAIN Initiative has given rise to powerful tools and neurotechnologies capable of probing deeply into the brain circuits in animal models. As these tools mature and move to human applications they will raise a host of important neuroethical considerations not just for the medical community but for society as a whole. Now marks a pivotal moment to assess the status and consider the future of the BRAIN Initiative’s neuroethics efforts. Here we describe core issues of neuroscience advances, the state of neurotechnologies in human neuroscience, and how ethics will be incorporated into the BRAIN Initiative as this ten-year project enters its second phase. BRAIN Initiative neurotechnologies have immense potential to transform the way we diagnose and treat neurological disease; therefore, they may become more commonplace in research, medicine, and society. We also discuss future global efforts to ensure continued guidance and open dialogue surrounding neuroethics.

A field-monitoring-based approach for correcting eddy-current-induced artifacts of up to the 2nd spatial order in human-connectome-project-style multiband diffusion MRI experiment at 7T: A pilot study

Over the recent years, significant advances in Spin-Echo (SE) Echo-Planar (EP) Diffusion MRI (dMRI) have enabled improved fiber tracking conspicuity in the human brain. At the same time, pushing the spatial resolution and using higher b-values inherently expose the acquired images to further eddy-current-induced distortion and blurring. Recently developed data-driven correction techniques, capable of significantly mitigating these defects, are included in the reconstruction pipelines developed for the Human Connectome Project (HCP) driven by the NIH BRAIN initiative. In this case, however, corrections are derived from the original diffusion-weighted (DW) magnitude images affected by distortion and blurring. Considering the complexity of k-space deviations in the presence of time varying high spatial order eddy currents, distortion and blurring may not be fully reversed when relying on magnitude DW images only. An alternative approach, consisting of iteratively reconstructing DW images based on the actual magnetic field spatiotemporal evolution measured with a magnetic field monitoring camera, has been successfully implemented at 3T in single band dMRI (Wilm et al., 2017, 2015). In this study, we aim to demonstrate the efficacy of this eddy current correction method in the challenging context of HCP-style multiband (MB ​= ​2) dMRI protocol.The magnetic field evolution was measured during the EP-dMRI readout echo train with a field monitoring camera equipped with 16 19F NMR probes. The time variation of 0th, 1st and 2nd order spherical field harmonics were used to reconstruct DW images. Individual DW images reconstructed with and without field correction were compared. The impact of eddy current correction was evaluated by comparing the corresponding direction-averaged DW images and fractional anisotropy (FA) maps.19F field monitoring data confirmed the existence of significant field deviations induced by the diffusion-encoding gradients, with variations depending on diffusion gradient amplitude and direction. In DW images reconstructed with the field correction, residual aliasing artifacts were reduced or eliminated, and when high b-values were applied, better gray/white matter delineation and sharper gyri contours were observed, indicating reduced signal blurring. The improvement in image quality further contributed to sharper contours and better gray/white matter delineation in mean DW images and FA maps.In conclusion, we demonstrate that up-to-2nd-order-eddy-current-induced field perturbation in multiband, in-plane accelerated HCP-style dMRI acquisition at 7T can be corrected by integrating the measured field evolution in image reconstruction.

The NIH BRAIN Initiative: Integrating Neuroethics and Neuroscience

The NIH Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative is focused on developing new tools and neurotechnologies to transform our understanding of the brain, and neuroethics is an essential component of this research effort. Coordination with other brain projects around the world will help maximize success.

SU94 - EXPLORING THE SOMATIC VARIATION IN SCHIZOPHRENIA

Background The presence of somatic variation in the human brain has been elucidated over the past several decades. Most recently, single-cell whole-genome sequencing studies have provided unequivocal evidence that individual human brain cells harbor unique genetic variants. The functional significance of this phenomenon is unclear, but some studies have suggested that it contributes to risk of neuropsychiatric disease. Currently, cost and labor requirement render difficult the sequencing of individual genomes at the scale that will likely be necessary to fully uncover the extent and role of somatic variation in the brain. A scalable alternative, however, has been developed in the field of cancer genomics wherein somatic variants are identified by comparing the frequencies of variant alleles in tumor and normal bulk tissue specimens from the same individual. Here, we apply this approach to investigate the role of somatic variation in schizophrenia in a pilot study of 9 individuals (5 schizophrenia cases and 4 unaffected controls). Methods Specimens from the prefrontal cortex and temporal muscle of 5 schizophrenia cases and 4 controls were obtained from the Mount Sinai NIH Brain and Tissue Repository. Deep whole-exome sequencing (250X coverage) was performed using DNA extracted from neuronal and non-neuronal nuclei, which were isolated from cortical specimens by fluorescent-activated nuclear sorting. We followed standard protocols for mapping and filtering reads, then called somatic Single Nucleotide Variants (sSNVs) using a suite of 6 calling algorithms. For each individual, the calling algorithms were utilized to call variants in the exomes of both the neuronal and non-neuronal cells of the brain by comparing them to a matched “normal” sample from the same individual (i.e., the temporal muscle). Variants were then filtered using an in-house quality control pipeline, and a subset of the remaining calls were validated with digital PCR (dPCR) and parallel sequencing of multiple clones (clone-seq). Results We identified 26 sSNVs in neuronal and non-neuronal cells from the brains of 9 individuals. We chose 10 of 26 for experimental validation using dPCR and clone-seq, observing a validation rate of 80%. We noted that 13 of the 26 sSNVs were found in a single schizophrenia case; as such, 4 of the 10 sSNVs included in validation experiments were from this individual, 3 of which were successfully validated. For 5 sSNVs, only the neuronal exome of the individual had the variant, for 17 only the non-neuronal exome and for 4 both the neuronal and non-neuronal exomes. At least 1 sSNV was observed in all 5 of the cases and in 2 of the 4 controls. We noted that 2 of the 23 somatic SNVs in cases fell within one of the 16 copy number variants implicated in schizophrenia by the largest study of copy number variation in schizophrenia to date. Several of the sSNVs observed in our cohort fall within genes known to function in determining cellular fate and development, including WNT10B, SMAD1 and FGF1. Discussion Here, we present a pipeline suitable for the large-scale investigation of somatic variation in the human brain. We show evidence that somatic variation occurs in a cell-type specific manner in the human brain. Genes affected by sSNVs in the brain have known roles in determining cell fate. Greater number of sSNVs in schizophrenia cases compared to controls was observed, and multiple case sSNVs fall within known schizophrenia CNVs. Larger sample sizes are needed so as to further elucidate the extent and role of somatic variation in the human brain.

The State of the NIH BRAIN Initiative

The BRAIN Initiative arose from a grand challenge to "accelerate the development and application of new technologies that will enable researchers to produce dynamic pictures of the brain that show how individual brain cells and complex neural circuits interact at the speed of thought." The BRAIN Initiative is a public-private effort focused on the development and use of powerful tools for acquiring fundamental insights about how information processing occurs in the central nervous system (CNS). As the Initiative enters its fifth year, NIH has supported >500 principal investigators, who have answered the Initiative's challenge via hundreds of publications describing novel tools, methods, and discoveries that address the Initiative's seven scientific priorities. We describe scientific advances produced by individual laboratories, multi-investigator teams, and entire consortia that, over the coming decades, will produce more comprehensive and dynamic maps of the brain, deepen our understanding of how circuit activity can produce a rich tapestry of behaviors, and lay the foundation for understanding how its circuitry is disrupted in brain disorders. Much more work remains to bring this vision to fruition, and the National Institutes of Health continues to look to the diverse scientific community, from mathematics, to physics, chemistry, engineering, neuroethics, and neuroscience, to ensure that the greatest scientific benefit arises from this unique research Initiative.

(Invited) The NIH BRAIN Initiative – the Road Thus Far and into the Future

Nick B. Langhals, Ph.D. serves as the Program Director for Neural Engineering at the National Institute of Neurological Disorders and Stroke (NINDS), where he manages a portfolio of grants focused on the development and translations of neurotechnologies. He is heavily involved in the Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative teams focused on both implantable and non-invasive technologies for recording and modulating neural activity. He also serves as the NINDS lead for the Bioengineering Research and Stimulating Peripheral Activity to Relieve Conditions (SPARC) programs at NIH. Within this talk, he will discuss many of the recent advances in neural interface materials, devices, electronics, and instrumentation that have been developed through NIH BRAIN funding in many of these areas. Further, he will also discuss a vision for future opportunities in research and development in these areas and where the electrochemical community could play an active role.

Neuroethics and the NIH BRAIN Initiative

ABSTRACTThe Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative is focused on developing new tools and neurotechnologies to revolutionize our understanding of how the brain functions in health and disease, in large part to address the growing societal impact of neurological, mental health, and substance use disorders. Recent advances in neurotechnology are delivering unprecedented ways to interrogate and modulate brain function, and the BRAIN Initiative is focused on translation for human medical uses over the next decade. Since its inception, the NIH component of the BRAIN Initiative has utilized an iterative model of integrating ethics into the scientific trajectory of the Initiative, most recently with the creation of a Neuroethics Division of the NIH BRAIN Initiative Multi-Council Working Group. The Division serves as a resource of expertise, to help the BRAIN Initiative navigate issues involving ethics. Here we discuss the BRAIN Initiative, and its implications and aspirations for neuroethics. We also discuss new opportunities for collaboration and for integrating stakeholder voices.

Host genetic factors predisposing to HIV-associated neurocognitive disorder.

The success of combination antiretroviral therapy (cART) in transforming the lives of HIV-infected individuals with access to these drugs is tempered by the increasing threat of HIV-associated neurocognitive disorders (HAND) to their overall health and quality of life. Intensive investigations over the past two decades have underscored the role of host immune responses, inflammation, and monocyte-derived macrophages in HAND, but the precise pathogenic mechanisms underlying HAND remain only partially delineated. Complicating research efforts and therapeutic drug development are the sheer complexity of HAND phenotypes, diagnostic imprecision, and the growing intersection of chronic immune activation with aging-related comorbidities. Yet, genetic studies still offer a powerful means of advancing individualized care for HIV-infected individuals at risk. There is an urgent need for 1) longitudinal studies using consistent phenotypic definitions of HAND in HIV-infected subpopulations at very high risk of being adversely impacted, such as children, 2) tissue studies that correlate neuropathological changes in multiple brain regions with genomic markers in affected individuals and with changes at the RNA, epigenomic, and/or protein levels, and 3) genetic association studies using more sensitive subphenotypes of HAND. The NIH Brain Initiative and Human Connectome Project, coupled with rapidly evolving systems biology and machine learning approaches for analyzing high-throughput genetic, transcriptomic and epigenetic data, hold promise for identifying actionable biological processes and gene networks that underlie HAND. This review summarizes the current state of understanding of host genetic factors predisposing to HAND in light of past challenges and suggests some priorities for future research to advance the understanding and clinical management of HAND in the cART era.

Long-term recordings improve the detection of weak excitatory-excitatory connections in rat prefrontal cortex.

Characterization of synaptic connectivity is essential to understanding neural circuit dynamics. For extracellularly recorded spike trains, indirect evidence for connectivity can be inferred from short-latency peaks in the correlogram between two neurons. Despite their predominance in cortex, however, significant interactions between excitatory neurons (E) have been hard to detect because of their intrinsic weakness. By taking advantage of long duration recordings, up to 25 h, from rat prefrontal cortex, we found that 7.6% of the recorded pyramidal neurons are connected. This corresponds to ∼70% of the local E-E connection probability that has been reported by paired intracellular recordings (11.6%). This value is significantly higher than previous reports from extracellular recordings, but still a substantial underestimate. Our analysis showed that long recording times and strict significance thresholds are necessary to detect weak connections while avoiding false-positive results, but will likely still leave many excitatory connections undetected. In addition, we found that hyper-reciprocity of connections in prefrontal cortex that was shown previously by paired intracellular recordings was only present in short-distance, but not in long distance (∼300 micrometers or more) interactions. As hyper-reciprocity is restricted to local clusters, it might be a minicolumnar effect. Given the current surge of interest in very high-density neural spike recording (e.g., NIH BRAIN Project) it is of paramount importance that we have statistically reliable methods for estimating connectivity from cross-correlation analysis available. We provide an important step in this direction.