Healthcare analytics, AI solutions for biological big data, providing an AI platform for the biotech, life sciences, medical and pharmaceutical industries, as well as for related technological approaches, i.e., curation and text analysis with machine learning and other activities related to AI applications to these industries.
Stroke is a leading cause of death worldwide and the most common cause of long-term disability amongst adults, more particularly in patients with diabetes mellitus and arterial hypertension. Increasing evidence suggests that disordered physiological variables following acute ischaemic stroke, especially hyperglycaemia, adversely affect outcomes.
Post-stroke hyperglycaemia is common (up to 50% of patients) and may be rather prolonged, regardless of diabetes status. A substantial body of evidence has demonstrated that hyperglycaemia has a deleterious effect upon clinical and morphological stroke outcomes. Therefore, hyperglycaemia represents an attractive physiological target for acute stroke therapies.
However, whether intensive glycaemic manipulation positively influences the fate of ischaemic tissue remains unknown. One major adverse event of management of hyperglycaemia with insulin (either glucose-potassium-insulin infusions or intensive insulin therapy) is the occurrence of hypoglycaemia, which can also induce cerebral damage.
Doctors all over the world have debated whether intensive glucose management, which requires the use of IV insulin to bring blood sugar levels down to 80-130 mg/dL, or standard glucose control using insulin shots, which aims to get glucose below 180 mg/dL, lead to better outcomes after stroke.
A period of hyperglycemia is common, with elevated blood glucose in the periinfarct period consistently linked with poor outcome in patients with and without diabetes. The mechanisms that underlie this deleterious effect of dysglycemia on ischemic neuronal tissue remain to be established, although in vitro research, functional imaging, and animal work have provided clues.
While prompt correction of hyperglycemia can be achieved, trials of acute insulin administration in stroke and other critical care populations have been equivocal. Diabetes mellitus and hyperglycemia per se are associated with poor cerebrovascular health, both in terms of stroke risk and outcome thereafter.
Interventions to control blood sugar are available but evidence of cerebrovascular efficacy are lacking. In diabetes, glycemic control should be part of a global approach to vascular risk while in acute stroke, theoretical data suggest intervention to lower markedly elevated blood glucose may be of benefit, especially if thrombolysis is administered.
Both hypoglycaemia and hyperglycaemia may lead to further brain injury and clinical deterioration; that is the reason these conditions should be avoided after stroke. Yet, when correcting hyperglycaemia, great care should be taken not to switch the patient into hypoglycaemia, and subsequently aggressive insulin administration treatment should be avoided.
Early identification and prompt management of hyperglycaemia, especially in acute ischaemic stroke, is recommended. Although the appropriate level of blood glucose during acute stroke is still debated, a reasonable approach is to keep the patient in a mildly hyperglycaemic state, rather than risking hypoglycaemia, using continuous glucose monitoring.
The primary results from the Stroke Hyperglycemia Insulin Network Effort (SHINE) study, a large, multisite clinical study showed that intensive glucose management did not improve functional outcomes at 90 days after stroke compared to standard glucose therapy. In addition, intense glucose therapy increased the risk of very low blood glucose (hypoglycemia) and required a higher level of care such as increased supervision from nursing staff, compared to standard treatment.
Record Innovations in Drug Discovery by Koch Institute @MIT Members and Affiliates
Reporter: Aviva Lev-Ari, PhD, RN
In Good Company
Trovagene announced a new patent for the use of the drug onvansertib in combination with other anti-androgen drugs for the treatment of prostate cancer. Last fall, Trovagene secured exclusive rights to develop combination therapies and clinical biomarkers for prostate cancer based in part on Bridge Project-funded research. Read more.
Lyndra Therapeutics, co-founded by KI member Bob Langer, raised $55 million in its Series B round, with new investors including the Bill and Melinda Gates Foundation and Gilead Sciences. Phase 2 trials for its ultra long-acting drug delivery capsule are expected to begin next year. Read more.
Dragonfly Therapeutics, co-founded by KI director Tyler Jacks, has committed $10 million to launch the first clinical studies of its TriNKETs (Tri-specific, NK cell Engager Therapies) platform for both solid tumor and hematological cancers. Read more.
KI member Bob Langer and collaborator Omid Farokhzad co-founded Seer— combining nanotechnology, protein chemistry, and machine learning—to develop liquid biopsy tests for the early detection of cancer and other diseases. Read more.
Epizyme, co-founded by KI member Bob Horvitz, is submitting a New Drug Application to gain accelerated approval of tazemetostat for patients with relapsed or refractory follicular lymphoma. Read more.
Ribon Therapeutics, founded by former KI member PaulChang, launched with $65 million in a Series B funding round with Victoria Richon, a veteran of Sanofi and Epizyme, at the helm. Ribon focuses on developing PARP7 inhibitors for cancer treatment. Read more.
The relationship between gut microbial metabolism and mental health is one of the most intriguing and controversial topics in microbiome research. Bidirectional microbiota–gut–brain communication has mostly been explored in animal models, with human research lagging behind. Large-scale metagenomics studies could facilitate the translational process, but their interpretation is hampered by a lack of dedicated reference databases and tools to study the microbial neuroactive potential.
Out of all the many ways, the teeming ecosystem of microbes in a person’s gut and other tissues might affect health. But, its potential influences on the brain may be the most provocative for research. Several studies in mice had indicated that gut microbes can affect behavior, and small scale studies on human beings suggested this microbial repertoire is altered in depression. Studies by two large European groups have found that several species of gut bacteria are missing in people with depression. The researchers can’t say whether the absence is a cause or an effect of the illness, but they showed that many gut bacteria could make substances that affect the nerve cell function—and maybe the mood.
Butyrate-producing Faecalibacterium and Coprococcus bacteria were consistently associated with higher quality of life indicators. Together with Dialister, Coprococcus spp. was also depleted in depression, even after correcting for the confounding effects of antidepressants. Two kinds of microbes, Coprococcus and Dialister, were missing from the microbiomes of the depressed subjects, but not from those with a high quality of life. The researchers also found the depressed people had an increase in bacteria implicated in Crohn disease, suggesting inflammation may be at fault.
Looking for something that could link microbes to mood, researchers compiled a list of 56 substances important for proper functioning of nervous system that gut microbes either produce or break down. They found, for example, that Coprococcus seems to have a pathway related to dopamine, a key brain signal involved in depression, although they have no evidence how this might protect against depression. The same microbe also makes an anti-inflammatory substance called butyrate, and increased inflammation is implicated in depression.
Still, it is very much unclear that how microbial compounds made in the gut might influence the brain. One possible channel is the vagus nerve, which links the gut and brain. Resolving the microbiome-brain connection might lead to novel therapies. Some physicians and companies are already exploring typical probiotics, oral bacterial supplements, for depression, although they don’t normally include the missing gut microbes identified in the new study.
From: Tom Lane [mailto:Tom.Lane@mathworks.com] Sent: Tuesday, January 15, 2019 12:59 PM To: Tom Lane Subject: [BCASA] INFORMS talk “Impact of Bots on Opinions in Social Networks” Wed Feb 6 at MITRE in Bedford
Upcoming event from INFORMS, kindly shared with BCASA members:
Please join us for the first INFORMS BC talk of 2019 on the Impact of Bots on Opinions in Social Networks by Professor Tauhid Zaman
·1. Please join us for the first INFORMS BC talk of 2019 on the Impact of Bots on Opinions in Social Networks by Professor Tauhid Zaman
MITRE is asking that if you plan to attend please RSVP by sending an email to lservi@mitre.org indicating your 1) name, 2) email, (3) company or university, (4) whether you are a US citizen and, if not, country of citizenship.
Date: Wednesday Feb 6, 2019, at 6:30 PM
Location:
The MITRE Corporation
M Building, 202 Burlington Road
Bedford, MA
Title: The Impact of Bots on Opinions in Social Networks
Speaker: Tauhid Zaman
Abstract:
We present an analysis of the impact of automated accounts, or bots, on opinions in a social network. We model the opinions using a variant of the famous DeGroot model, which connects opinions with network structure. We find a nontrivial correlation between opinions based on this network model and based on the content of tweets of Twitter users discussing the 2016 U.S. presidential election between Hillary Clinton and Donald Trump, providing evidence supporting the validity of the model. We then utilize the network model to predict what the opinions would have been if the network did not contain any bots which may be trying to manipulate opinions. Using a bot detection algorithm, we identify bot accounts which comprise less than 1% of the network. By analyzing the bot posts, we find that there are twice as many bots supporting Donald Trump as there are supporting Hillary Clinton. We remove the bots from the network and recalculate the opinions using the network model. We find that the bots produce a significant shift in the opinions, with the Clinton bots producing almost twice as large a change as the Trump bots, despite being fewer in number. Analysis of the bot behavior reveals that the large shift is due to the fact that the bots post one hundred times more frequently than humans. The asymmetry in the opinion shift is due to the fact that the Clinton bots post 50% more frequently than the Trump bots. Our results suggest a small number of highly active bots in a social network can have a disproportionate impact on opinions.
Bio: Tauhid is an Associate Professor of Operations Management at the MIT Sloan School of Management. He received his BS, MEng, and PhD degrees in electrical engineering and computer science from MIT. His research focuses on solving operational problems involving social network data using probabilistic models, network algorithms, and modern statistical methods. Some of the topics he studies in the social networks space include predicting the popularity of content, finding online extremists, and geo-locating users. His broader interests cover data driven approaches to investing in startup companies, non-traditional choice modeling, algorithmic sports betting, and biometric data. His work has been featured in the Wall Street Journal, Wired, Mashable, the LA Times, and Time Magazine.
eScientific Publishing a Case in Point: Evolution of Platform Architecture Methodologies and of Intellectual Property Development (Content Creation by Curation) Business Model
Author: Aviva Lev- Ari, PhD, RN
Six demonstrations that justify the claims made in our 2019 VISION:
Point #1: Top Author, Chief Scientific Officer, MD, FCAP – share in the Journal’s archive computed
Point #2: Top authors by e-Readers per article – A Team at work
Point #3: Team members Led by Key Opinion Leader [https://lnkd.in/eEyn69r] generated Intellectual Property (IP) of Three Asset Classes
Point #4: Functions and Forms by Asset Class
Point #5: SYNERGY among the Three Asset Classes stimulates Value Creation
Point #6: Plan for Team membership augmentation and Training under existing Leadership and New Ownership
POINT #1: Top Author, Chief Scientific Officer, a retired Chief of Pathology, LHB, MD, FCAP – share in the Journal’s archive computed
Journal archive has 5,486 articles published
LHB has published 1,390 articles = 25.33% – he joined our team with a publication list of +200 articles in referred academic journals. LHB is co-curator of many articles with many of the team members
The Young Surgeon and The Retired Pathologist: On Science, Medicine and HealthCare Policy– The Best Writers Among the WRITERS
· Multi-Authoring Platform – wordpress.com· Authoring Privilege levels· Categories of research forming the Journal’s Ontology, a Dynamic Relational and Hierarchical database Multi-Authoring architecture· Generation of new categories by authors developing the categories they are Owners of· Article update policy
· eTOCs design by Editors· e-Book Style uniformity across all eSeries· Structure of eBook Parts· Structure of Chapters· Structure of Articles· Commission of Articles Specifically for given e-Books by Editor-in-Chief· Overarching guidance for e-Books within each eSeries and across eSeries
Business ModelDevelopment: Content Creation by Curation of Scientific Findings
· Author/Curator initiated article· Article Commissions by Editor-in-Chief· Co-Curations· Research Category Ownership· e-Books Editors role defined (Job description)
· e-Books in Kindle Store· 30,000 Oncologists in the US· 40,000 Cardiologists in the US· All Primary Care Physicians· All Medical Schools for Curriculum development· Global market for Medical EducationALL BioMed 16 Volumes [$515+$190+$175+$190+$274 = $1,344]@Amazon BUNDLED 6 Volumes Cardiovascular Diseases for $515https://lnkd.in/e6WkMgF@Amazon UNBUNDLED 10 Volumeshttps://lnkd.in/ekWGNqA· Genomics 1,2 ($190)· Cancer 1,2 ($175)· Metabolomics, Immunology, Infectious Diseases 1,2,3 (#190)· Precision Medicine 1,2,3,4 ($274)
· The market is defined as “All Biotech Conferences Organizers around the Globe” in need to own eProceedings for their Conferences for electronic dissemination to conference attendees.· Digital Archive of Conferences eProceedingsPart Three: Conference eProceedings DELIVERABLES & Social Media Analytics
· The market is defined as “All Biotech Conferences Organizers around the Globe” in need to own eProceedings for their Conferences for electronic dissemination to conference attendees.
>> Intellectual Property Development (Content Creation by Curation) Business Model
The market is defined as “All Biotech Conferences Organizers around the Globe” in need to own eProceedings for their Conferences for electronic dissemination to conference attendees.
Digital Archive of Conferences eProceedings
POINT #5: SYNERGY among the Three Asset Classes stimulates Value Creation
Concepts from +60 Conferences I covered yielded ~300 new articles, five new per conference, at least
Electronic Table of Contents [eTOCs] for each e-Book of the [1,2,3..,16] is derived from the Research categories of the Journal
Journal Ontology has 700 Research Categories – knowledge architecture designed by experts
Every article in the Journal is connected with Social Media Icons on wordpress.com as an engine for
Pingbacks
New eReaders
Scientists applying to author for the Journal
+7,300 Scientific comments on 5,486 articles published – AGORA
Electronic Scientific AGORA: Comment Exchanges by Global Scientists on Articles published in the Open Access Journal @pharmaceuticalintelligence.com – Four Case Studies
POINT #6: Plan for Team membership augmentation and Training under existing Leadership and New Ownership
Work-in-Progress
Other related articles published in this Open Access Online Scientific Journal include the following:
Innovations in electronic Scientific Publishing (eSP): Case Studies in Marketing eContent, Curation Methodology, Categories of Research Functions, Interdisciplinary conceptual innovations by Cross Section of Categories, Exposure to Frontiers of Science by Real Time Press coverage of Scientific Conferences
e-Scientific Publishing: The Competitive Advantage of a Powerhouse for Curation of Scientific Findings and Methodology Development for e-Scientific Publishing – LPBI Group, A Case in Point
Today’s lesson 3 explains how extracellular signals are transduced (transmitted) into the cell through receptors to produce an agonist-driven event (effect). This lesson focused on signal transduction from agonist through G proteins (GTPases), and eventually to the effectors of the signal transduction process. Agonists such as small molecules like neurotransmitters, hormones, nitric oxide were discussed however later lectures will discuss more in detail the large growth factor signalings which occur through receptor tyrosine kinases and the Ras family of G proteins as well as mechanosignaling through Rho and Rac family of G proteins.
Transducers: The Heterotrimeric G Proteins (GTPases)
An excellent review of heterotrimeric G Proteins found in the brain is given by
Cyclic AMP is an important second messenger. It forms, as shown, when the membrane enzyme adenylyl cyclase is activated (as indicated, by the alpha subunit of a G protein).
The cyclic AMP then goes on the activate specific proteins. Some ion channels, for example, are gated by cyclic AMP. But an especially important protein activated by cyclic AMP is protein kinase A, which goes on the phosphorylate certain cellular proteins. The scheme below shows how cyclic AMP activates protein kinase A.
Updated 7/15/2019
Additional New Studies on Regulation of the Beta 2 Adrenergic Receptor
We had discussed regulation of the G protein coupled beta 2 adrenergic receptor by the B-AR receptor kinase (BARK)/B arrestin system which uncouples and desensitizes the receptor from its G protein system. In an article by Xiangyu Liu in Science in 2019, the authors describe another type of allosteric modulation (this time a POSITIVE allosteric modulation) in the intracellular loop 2. See below:
Mechanism of β2AR regulation by an intracellular positive allosteric modulator
Xiangyu Liu1,*, Ali Masoudi2,*, Alem W. Kahsai2,*, Li-Yin Huang2, Biswaranjan Pani2, Dean P. Staus2, Paul J. Shim2, Kunio Hirata3,4, Rishabh K. Simhal2, Allison M. Schwalb2, Paula K. Rambarat2, Seungkirl Ahn2, Robert J. Lefkowitz2,5,6,†, Brian Kobilka1
Positive reinforcement in a GPCR
Many drug discovery efforts focus on G protein–coupled receptors (GPCRs), a class of receptors that regulate many physiological processes. An exemplar is the β2-adrenergic receptor (β2AR), which is targeted by both blockers and agonists to treat cardiovascular and respiratory diseases. Most GPCR drugs target the primary (orthosteric) ligand binding site, but binding at allosteric sites can modulate activation. Because such allosteric sites are less conserved, they could possibly be targeted more specifically. Liu et al. report the crystal structure of β2AR bound to both an orthosteric agonist and a positive allosteric modulator that increases receptor activity. The structure suggests why the modulator compound is selective for β2AR over the closely related β1AR. Furthermore, the structure reveals that the modulator acts by enhancing orthosteric agonist binding and stabilizing the active conformation of the receptor.
Abstract
Drugs targeting the orthosteric, primary binding site of G protein–coupled receptors are the most common therapeutics. Allosteric binding sites, elsewhere on the receptors, are less well-defined, and so less exploited clinically. We report the crystal structure of the prototypic β2-adrenergic receptor in complex with an orthosteric agonist and compound-6FA, a positive allosteric modulator of this receptor. It binds on the receptor’s inner surface in a pocket created by intracellular loop 2 and transmembrane segments 3 and 4, stabilizing the loop in an α-helical conformation required to engage the G protein. Structural comparison explains the selectivity of the compound for β2– over the β1-adrenergic receptor. Diversity in location, mechanism, and selectivity of allosteric ligands provides potential to expand the range of receptor drugs.
Recent structures of GPCRs bound to allosteric modulators have revealed that receptor surfaces are decorated with diverse cavities and crevices that may serve as allosteric modulatory sites (1). This substantiates the notion that GPCRs are structurally plastic and can be modulated by a variety of allosteric ligands through distinct mechanisms (2-7). Most of these structures have been solved with negative allosteric modulators (NAMs), which stabilize receptors in their inactive states (1). To date, only a single structure of an active GPCR bound to a small-molecule positive allosteric modulator (PAM) has been reported, namely, the M2 muscarinic acetylcholine receptor with LY2119620 (8). Thus, mechanisms of PAMs and their potential binding sites remain largely unexplored.
Fig 1. Structure of the active state T4L-B2AR in complex with the orthosteric agonist BI-167107, nanobody 689, and compound 6FA. (A) The chemical structure of compound-6FA (Cmpd-6FA). (B) Isoproterenol (ISO) competition binding with 125I-cyanopindolol (CYP) to the β2AR reconstituted in nanodisks in the presence of vehicle (0.32% dimethylsulfoxide; DMSO), Cmpd-6, or Cmpd-6FA at 32 μM. Values were normalized to percentages of the maximal 125I-CYP binding level obtained from a one-site competition binding–log IC50 (median inhibitory concentration) curve fit. Binding curves were generated by GraphPad Prism. Points on curves represent mean ± SEM obtained from five independent experiments performed in duplicate. (C) Analysis of Cmpd-6FA interaction with the BI-167107–bound β2AR by ITC. Representative thermogram (inset) and binding isotherm, of three independent experiments, with the best titration curve fit are shown. Summary of thermodynamic parameters obtained by ITC: binding affinity (KD = 1.2 ± 0.1 μM), stoichiometry (N = 0.9 ± 0.1 sites), enthalpy (ΔH = 5.0 ± 1.2 kcal mol−1), and entropy (ΔS =13 ± 2.0 cal mol−1 deg−1). (D) Side view of T4L-β2AR bound to the orthosteric agonist BI-167107, nanobody 6B9 (Nb6B9), and Cmpd-6FA. The gray box indicates the membrane layer as defined by the OPM database. (E) Close-up view of Cmpd-6FA binding site. Covering Cmpd-6FA is 2Fo– Fc electron density contoured at 1.0 σ (green mesh).From Science 28 Jun 2019:
Vol. 364, Issue 6447, pp. 1283-1287
Fig 3. Fig. 3Mechanism of allosteric activation of the β2AR by Cmpd-6FA.
(A) Superposition of the inactive β2AR bound to the antagonist carazolol (PDB code: 2RH1) and the active β2AR bound to the agonist BI-167107, Cmpd-6FA, and Nb6B9. Close-up view of the Cmpd-6FA binding site is shown. The residues of the inactive (yellow) and active (blue) β2AR are depicted, and the hydrogen bond formed between Asp1303.49and Tyr141ICL2 in the active state is indicated by a black dashed line. (B) Topography of Cmpd-6FA binding surface on the active β2AR (left, blue) and the corresponding surface of the inactive β2AR (right, yellow) with Cmpd-6FA (orange sticks) docked on top. Molecular surfaces are of only those residues involved in interaction with Cmpd-6FA. Steric clash between Cmpd-6FA and the surface of inactive β2AR is represented by a purple asterisk. (C) Overlay of the β2AR bound to BI-167107, Nb6B9, and Cmpd-6FA with the β2AR–Gscomplex (PDB code: 3SN6). The inset shows the position of Phe139ICL2 relative to the α subunit of Gs. (D) Superposition of the active β2AR bound to the agonist BI-167107, Nb6B9, and Cmpd-6FA (blue) with the inactive β2AR bound to carazolol (yellow) (PDB code: 2RH1) as viewed from the cytoplasm. For clarity, Nb6B9 and the orthosteric ligands are omitted. The arrows indicate shifts in the intracellular ends of the TM helices 3, 5, and 6 upon activation and their relative distances.
Allosteric sites may not face the same evolutionary pressure as do orthosteric sites, and thus are more divergent across subtypes within a receptor family (24–26). Therefore, allosteric sites may provide a greater source of specificity for targeting GPCRs.
D. M. Thal, A. Glukhova, P. M. Sexton, A. Christopoulos, Structural insights into G-protein-coupled receptor allostery. Nature 559, 45–53 (2018). doi:10.1038/s41586-018-0259-zpmid:29973731CrossRefPubMedGoogle Scholar
D. Wacker, R. C. Stevens, B. L. Roth, How Ligands Illuminate GPCR Molecular Pharmacology. Cell 170, 414–427 (2017).
D. P. Staus, R. T. Strachan, A. Manglik, B. Pani, A. W. Kahsai, T. H. Kim, L. M. Wingler, S. Ahn, A. Chatterjee, A. Masoudi, A. C. Kruse, E. Pardon, J. Steyaert, W. I. Weis, R. S. Prosser, B. K. Kobilka, T. Costa, R. J. Lefkowitz, Allosteric nanobodies reveal the dynamic range and diverse mechanisms of G-protein-coupled receptor activation. Nature 535, 448–452 (2016). doi:10.1038/nature18636pmid:27409812CrossRefPubMedGoogle Scholar
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Additional information on Nitric Oxide as a Cellular Signal
Nitric oxide is actually a free radical and can react with other free radicals, resulting in a very short half life (only a few seconds) and so in the body is produced locally to its site of action (i.e. in endothelial cells surrounding the vascular smooth muscle, in nerve cells). In the late 1970s, Dr. Robert Furchgott observed that acetylcholine released a substance that produced vascular relaxation, but only when the endothelium was intact. This observation opened this field of research and eventually led to his receiving a Nobel prize. Initially, Furchgott called this substance endothelium-derived relaxing factor (EDRF), but by the mid-1980s he and others identified this substance as being NO.
Nitric oxide is implicated in many pathologic processes as well. Nitric oxide post translational modifications have been attributed to nitric oxide’s role in pathology however, although the general mechanism by which nitric oxide exerts its physiological effects is by stimulation of soluble guanylate cyclase to produce cGMP, these post translational modifications can act as a cellular signal as well. For more information of NO pathologic effects and how NO induced post translational modifications can act as a cellular signal see the following:
The second annual PureTech Health BIG Summit brings together an elite ensemble of leading scientific researchers, investors, and CEOs and R&D leaders from major pharmaceutical, technology, and biotech companies.
The BIG Summit is designed to stimulate ideas that will have an impact on existing pipelines and catalyze future interactions among a group of delegates that represent leaders and innovators in their fields.
Please follow the discussion on Twitter using #BIGAxisSummit
By invitation only; registration is non-transferable.
For more information, please contact PureTechHealthSummit@PureTechHealth.com
Back for final sessions at #BIGAxisSummit. @PureTechH Jim Harper of Sonde Health talking about how voice data — pacing, fine motor articulation, oscillation — can point the way to objective, quantitative measures for detecting and monitoring depression.
Paul Biondi at #BIGAxisSummit : What makes big deals happen is financial, and *deep conviction* of a big future fit. Disproportionate valuation from bidders is expected.
Love this. We often reduce everything to mathematical analyses to champion or ridicule deals. Not that simple
Bob Langer (@MIT) asks how #lymphatics affected by #aging. Santambrogio: typically blame aging #immune cells for increased disease, but aging affects lymphatics too (less efficient trafficking shown). Rejuvenating these could affect several aging-related diseases #BigAxisSummit
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