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Dr. Paul Hanona and Dr. Arturo Loaiza-Bonilla discuss how to safely and smartly integrate AI into the clinical workflow and tap its potential to improve patient-centered care, drug development, and access to clinical trials. TRANSCRIPT Dr. Paul Hanona: Hello, I'm Dr. Paul Hanona, your guest host of the ASCO Daily News Podcast today. I am a medical oncologist as well as a content creator @DoctorDiscover, and I'm delighted to be joined today by Dr. Arturo Loaiza-Bonilla, the chief of hematology and oncology at St. Luke's University Health Network. Dr. Bonilla is also the co-founder and chief medical officer at Massive Bio, an AI-driven platform that matches patients with clinical trials and novel therapies. Dr. Loaiza-Bonilla will share his unique perspective on the potential of artificial intelligence to advance precision oncology, especially through clinical trials and research, and other key advancements in AI that are transforming the oncology field. Our full disclosures are available in the transcript of the episode. Dr. Bonilla, it's great to be speaking with you today. Thanks for being here. Dr. Arturo Loaiza-Bonilla: Oh, thank you so much, Dr. Hanona. Paul, it's always great to have a conversation. Looking forward to a great one today. Dr. Paul Hanona: Absolutely. Let's just jump right into it. Let's talk about the way that we see AI being embedded in our clinical workflow as oncologists. What are some practical ways to use AI? Dr. Arturo Loaiza-Bonilla: To me, responsible AI integration in oncology is one of those that's focused on one principle to me, which is clinical purpose is first, instead of the algorithm or whatever technology we're going to be using. If we look at the best models in the world, they're really irrelevant unless we really solve a real day-to-day challenge, either when we're talking to patients in the clinic or in the infusion chair or making decision support. Currently, what I'm doing the most is focusing on solutions that are saving us time to be more productive and spend more time with our patients. So, for example, we're using ambient AI for appropriate documentation in real time with our patients. We're leveraging certain tools to assess for potential admission or readmission of patients who have certain conditions as well. And it's all about combining the listening of physicians like ourselves who are end users, those who create those algorithms, data scientists, and patient advocates, and even regulators, before they even write any single line of code. I felt that on my own, you know, entrepreneurial aspects, but I think it's an ethos that we should all follow. And I think that AI shouldn't be just bolted on later. We always have to look at workflows and try to look, for example, at clinical trial matching, which is something I'm very passionate about. We need to make sure that first, it's easier to access for patients, that oncologists like myself can go into the interface and be able to pull the data in real time when you really need it, and you don't get all this fatigue alerts. To me, that's the responsible way of doing so. Those are like the opportunities, right? So, the challenge is how we can make this happen in a meaningful way – we're just not reacting to like a black box suggestion or something that we have no idea why it came up to be. So, in terms of success – and I can tell you probably two stories of things that we know we're seeing successful – we all work closely with radiation oncologists, right? So, there are now these tools, for example, of automated contouring in radiation oncology, and some of these solutions were brought up in different meetings, including the last ASCO meeting. But overall, we know that transformer-based segmentation tools; transformer is just the specific architecture of the machine learning algorithm that has been able to dramatically reduce the time for colleagues to spend allotting targets for radiation oncology. So, comparing the target versus the normal tissue, which sometimes it takes many hours, now we can optimize things over 60%, sometimes even in minutes. So, this is not just responsible, but it's also an efficiency win, it's a precision win, and we're using it to adapt even mid-course in response to tumor shrinkage. Another success that I think is relevant is, for example, on the clinical trial matching side. We've been working on that and, you know, I don't want to preach to the choir here, but having the ability for us to structure data in real time using these tools, being able to extract information on biomarkers, and then show that multi-agentic AI is superior to what we call zero-shot or just throwing it into ChatGPT or any other algorithm, but using the same tools but just fine-tuned to the point that we can be very efficient and actually reliable to the level of almost like a research coordinator, is not just theory. Now, it can change lives because we can get patients enrolled in clinical trials and be activated in different places wherever the patient may be. I know it's like a long answer on that, but, you know, as we talk about responsible AI, that's important. And in terms of what keeps me up at night on this: data drift and biases, right? So, imaging protocols, all these things change, the lab switch between different vendors, or a patient has issues with new emerging data points. And health systems serve vastly different populations. So, if our models are trained in one context and deployed in another, then the output can be really inaccurate. So, the idea is to become a collaborative approach where we can use federated learning and patient-centricity so we can be much more efficient in developing those models that account for all the populations, and any retraining that is used based on data can be diverse enough that it represents all of us and we can be treated in a very good, appropriate way. So, if a clinician doesn't understand why a recommendation is made, as you probably know, you probably don't trust it, and we shouldn't expect them to. So, I think this is the next wave of the future. We need to make sure that we account for all those things. Dr. Paul Hanona: Absolutely. And even the part about the clinical trials, I want to dive a little bit more into in a few questions. I just kind of wanted to make a quick comment. Like you said, some of the prevalent things that I see are the ambient scribes. It seems like that's really taken off in the last year, and it seems like it's improving at a pretty dramatic speed as well. I wonder how quickly that'll get adopted by the majority of physicians or practitioners in general throughout the country. And you also mentioned things with AI tools regarding helping regulators move things quicker, even the radiation oncologist, helping them in their workflow with contouring and what else they might have to do. And again, the clinical trials thing will be quite interesting to get into. The first question I had subsequent to that is just more so when you have large datasets. And this pertains to two things: the paper that you published recently regarding different ways to use AI in the space of oncology referred to drug development, the way that we look at how we design drugs, specifically anticancer drugs, is pretty cumbersome. The steps that you have to take to design something, to make sure that one chemical will fit into the right chemical or the structure of the molecule, that takes a lot of time to tinker with. What are your thoughts on AI tools to help accelerate drug development? Dr. Arturo Loaiza-Bonilla: Yes, that's the Holy Grail and something that I feel we should dedicate as much time and effort as possible because it relies on multimodality. It cannot be solved by just looking at patient histories. It cannot be solved by just looking at the tissue alone. It's combining all these different datasets and being able to understand the microenvironment, the patient condition and prior treatments, and how dynamic changes that we do through interventions and also exposome – the things that happen outside of the patient's own control – can be leveraged to determine like what's the best next step in terms of drugs. So, the ones that we heard the news the most is, for example, the Nobel Prize-winning [for Chemistry awarded to Demis Hassabis and John Jumper for] AlphaFold, an AI system that predicts protein structures right? So, we solved this very interesting concept of protein folding where, in the past, it would take the history of the known universe, basically – what's called the Levinthal's paradox – to be able to just predict on amino acid structure alone or the sequence alone, the way that three-dimensionally the proteins will fold. So, with that problem being solved and the Nobel Prize being won, the next step is, “Okay, now we know how this protein is there and just by sequence, how can we really understand any new drug that can be used as a candidate and leverage all the data that has been done for many years of testing against a specific protein or a specific gene or knockouts and what not?” So, this is the future of oncology and where we're probably seeing a lot of investments on that. The key challenge here is mostly working on the side of not just looking at pathology, but leveraging this digital pathology with whole slide imaging and identifying the microenvironment of that specific tissue. There's a number of efforts currently being done. One isn't just H&E, like hematoxylin and eosin, slides alone, but with whole imaging, now we can use expression profiles, spatial transcriptomics, and gene whole exome sequencing in the same space and use this transformer technology in a multimodality approach that we know already the slide or the pathology, but can we use that to understand, like, if I knock out this gene, how is the microenvironment going to change to see if an immunotherapy may work better, right? If we can make a microenvironment more reactive towards a cytotoxic T cell profile, for example. So, that is the way where we're really seeing the field moving forward, using multimodality for drug discovery. So, the FDA now seems to be very eager to support those initiatives, so that's of course welcome. And now the key thing is the investment to do this in a meaningful way so we can see those candidates that we're seeing from different companies now being leveraged for rare disease, for things that are going to be almost impossible to collect enough data, and make it efficient by using these algorithms that sometimes, just with multiple masking – basically, what they do is they mask all the features and force the algorithm to find solutions based on the specific inputs or prompts we're doing. So, I'm very excited about that, and I think we're going to be seeing that in the future. Dr. Paul Hanona: So, essentially, in a nutshell, we're saying we have the cancer, which is maybe a dandelion in a field of grass, and we want to see the grass that's surrounding the dandelion, which is the pathology slides. The problem is, to the human eye, it's almost impossible to look at every single piece of grass that's surrounding the dandelion. And so, with tools like AI, we can greatly accelerate our study of the microenvironment or the grass that's surrounding the dandelion and better tailor therapy, come up with therapy. Otherwise, like you said, to truly generate a drug, this would take years and years. We just don't have the throughput to get to answers like that unless we have something like AI to help us. Dr. Arturo Loaiza-Bonilla: Correct. Dr. Paul Hanona: And then, clinical trials. Now, this is an interesting conversation because if you ever look up our national guidelines as oncologists, there's always a mention of, if treatment fails, consider clinical trials. Or in the really aggressive cancers, sometimes you might just start out with clinical trials. You don't even give the standard first-line therapy because of how ineffective it is. There are a few issues with clinical trials that people might not be aware of, but the fact that the majority of patients who should be on clinical trials are never given the chance to be on clinical trials, whether that's because of proximity, right, they might live somewhere that's far from the institution, or for whatever reason, they don't qualify for the clinical trial, they don't meet the strict inclusion criteria. But a reason you mentioned early on is that it's simply impossible for someone to be aware of every single clinical trial that's out there. And then even if you are aware of those clinical trials, to actually find the sites and put in the time could take hours. And so, how is AI going to revolutionize that? Because in my mind, it's not that we're inventing a new tool. Clinical trials have always been available. We just can't access them. So, if we have a tool that helps with access, wouldn't that be huge? Dr. Arturo Loaiza-Bonilla: Correct. And that has been one of my passions. And for those who know me and follow me and we've spoke about it in different settings, that's something that I think we can solve. This other paradox, which is the clinical trial enrollment paradox, right? We have tens of thousands of clinical trials available with millions of patients eager to learn about trials, but we don't enroll enough and many trials close to accrual because of lack of enrollment. It is completely paradoxical and it's because of that misalignment because patients don't know where to go for trials and sites don't know what patients they can help because they haven't reached their doors yet. So, the solution has to be patient-centric, right? We have to put the patient at the center of the equation. And that was precisely what we had been discussing during the ASCO meeting. There was an ASCO Education Session where we talked about digital prescreening hubs, where we, in a patient-centric manner, the same way we look for Uber, Instacart, any solution that you may think of that you want something that can be leveraged in real time, we can use these real-world data streams from the patient directly, from hospitals, from pathology labs, from genomics companies, to continuously screen patients who can match to the inclusion/exclusion criteria of unique trials. So, when the patient walks into the clinic, the system already knows if there's a trial and alerts the site proactively. The patient can actually also do decentralization. So, there's a number of decentralized clinical trial solutions that are using what I call the “click and mortar” approach, which is basically the patient is checking digitally and then goes to the site to activate. We can also have the click and mortar in the bidirectional way where the patient is engaged in person and then you give the solution like the ones that are being offered on things that we're doing at Massive Bio and beyond, which is having the patient to access all that information and then they make decisions and enroll when the time is right. As I mentioned earlier, there is this concept drift where clinical trials open and close, the patient line of therapy changes, new approvals come in and out, and sites may not be available at a given time but may be later. So, having that real-time alerts using tools that are able already to extract data from summarization that we already have in different settings and doing this natural language ingestion, we can not only solve this issue with manual chart review, which is extremely cumbersome and takes forever and takes to a lot of one-time assessments with very high screen failures, to a real-time dynamic approach where the patient, as they get closer to that eligibility criteria, they get engaged. And those tools can be built to activate trials, audit trials, and make them better and accessible to patients. And something that we know is, for example, 91%-plus of Americans live close to either a pharmacy or an imaging center. So, imagine that we can potentially activate certain of those trials in those locations. So, there's a number of pharmacies, special pharmacies, Walgreens, and sometimes CVS trying to do some of those efforts. So, I think the sky's the limit in terms of us working together. And we've been talking with corporate groups, they're all interested in those efforts as well, to getting patients digitally enabled and then activate the same way we activate the NCTN network of the corporate groups, that are almost just-in-time. You can activate a trial the patient is eligible for and we get all these breakthroughs from the NIH and NCI, just activate it in my site within a week or so, as long as we have the understanding of the protocol. So, using clinical trial matching in a digitally enabled way and then activate in that same fashion, but not only for NCTN studies, but all the studies that we have available will be the key of the future through those prescreening hubs. So, I think now we're at this very important time where collaboration is the important part and having this silo-breaking approach with interoperability where we can leverage data from any data source and from any electronic medical records and whatnot is going to be essential for us to move forward because now we have the tools to do so with our phones, with our interests, and with the multiple clinical trials that are coming into the pipelines. Dr. Paul Hanona: I just want to point out that the way you described the process involves several variables that practitioners often don't think about. We don't realize the 15 steps that are happening in the background. But just as a clarifier, how much time is it taking now to get one patient enrolled on a clinical trial? Is it on the order of maybe 5 to 10 hours for one patient by the time the manual chart review happens, by the time the matching happens, the calls go out, the sign-up, all this? And how much time do you think a tool that could match those trials quicker and get you enrolled quicker could save? Would it be maybe an hour instead of 15 hours? What's your thought process on that? Dr. Arturo Loaiza-Bonilla: Yeah, exactly. So one is the matching, the other one is the enrollment, which, as you mentioned, is very important. So, it can take, from, as you said, probably between 4 days to sometimes 30 days. Sometimes that's how long it takes for all the things to be parsed out in terms of logistics and things that could be done now agentically. So, we can use agents to solve those different steps that may take multiple individuals. We can just do it as a supply chain approach where all those different steps can be done by a single agent in a simultaneous fashion and then we can get things much faster. With an AI-based solution using these frontier models and multi-agentic AI – and we presented some of this data in ASCO as well – you can do 5,000 patients in an hour, right? So, just enrolling is going to be between an hour and maximum enrollment, it could be 7 days for those 5,000 patients if it was done at scale in a multi-level approach where we have all the trials available. Dr. Paul Hanona: No, definitely a very exciting aspect of our future as oncologists. It's one thing to have really neat, novel mechanisms of treatment, but what good is it if we can't actually get it to people who need it? I'm very much looking for the future of that. One of the last questions I want to ask you is another prevalent way that people use AI is just simply looking up questions, right? So, traditionally, the workflow for oncologists is maybe going on national guidelines and looking up the stage of the cancer and seeing what treatments are available and then referencing the papers and looking at who was included, who wasn't included, the side effects to be aware of, and sort of coming up with a decision as to how to treat a cancer patient. But now, just in the last few years, we've had several tools become available that make getting questions easier, make getting answers easier, whether that's something like OpenAI's tools or Perplexity or Doximity or OpenEvidence or even ASCO has a Guidelines Assistant as well that is drawing from their own guidelines as to how to treat different cancers. Do you see these replacing traditional sources? Do you see them saving us a lot more time so that we can be more productive in clinic? What do you think is the role that they're going to play with patient care? Dr. Arturo Loaiza-Bonilla: Such a relevant question, particularly at this time, because these AI-enabled query tools, they're coming left and right and becoming increasingly common in our daily workflows and things that we're doing. So, traditionally, when we go and we look for national guidelines, we try to understand the context ourselves and then we make treatment decisions accordingly. But that is a lot of a process that now AI is helping us to solve. So, at face value, it seems like an efficiency win, but in many cases, I personally evaluate platforms as the chief of hem/onc at St. Luke's and also having led the digital engagement things through Massive Bio and trying to put things together, I can tell you this: not all tools are created equal. In cancer care, each data point can mean the difference between cure and progression, so we cannot really take a lot of shortcuts in this case or have unverified output. So, the tools are helpful, but it has to be grounded in truth, in trusted data sources, and they need to be continuously updated with, like, ASCO and NCCN and others. So, the reason why the ASCO Guidelines Assistant, for instance, works is because it builds on all these recommendations, is assessed by end users like ourselves. So, that kind of verification is critical, right? We're entering a phase where even the source material may be AI-generated. So, the role of human expert validation is really actually more important, not less important. You know, generalist LLMs, even when fine-tuned, they may not be enough. You can pull a few API calls from PubMed, etc., but what we need now is specialized, context-aware, agentic tools that can interpret multimodal and real-time clinical inputs. So, something that we are continuing to check on and very relevant to have entities and bodies like ASCO looking into this so they can help us to be really efficient and really help our patients. Dr. Paul Hanona: Dr. Bonilla, what do you want to leave the listener with in terms of the future direction of AI, things that we should be cautious about, and things that we should be optimistic about? Dr. Arturo Loaiza-Bonilla: Looking 5 years ahead, I think there's enormous promise. As you know, I'm an AI enthusiast, but always, there's a few priorities that I think – 3 of them, I think – we need to tackle head-on. First is algorithmic equity. So, most AI tools today are trained on data from academic medical centers but not necessarily from community practices or underrepresented populations, particularly when you're looking at radiology, pathology, and what not. So, those blind spots, they need to be filled, and we can eliminate a lot of disparities in cancer care. So, those frameworks to incentivize while keeping the data sharing using federated models and things that we can optimize is key. The second one is the governance on the lifecycle. So, you know, AI is not really static. So, unlike a drug that is approved and it just, you know, works always, AI changes. So, we need to make sure that we have tools that are able to retrain and recall when things degrade or models drift. So, we need to use up-to-date AI for clinical practice, so we are going to be in constant revalidation and make it really easy to do. And lastly, the human-AI interface. You know, clinicians don't need more noise or we don't need more black boxes. We need decision support that is clear, that we can interpret, and that is actionable. “Why are you using this? Why did we choose this drug? Why this dose? Why now?” So, all these things are going to help us and that allows us to trace evidence with a single click. So, I always call it back to the Moravec's paradox where we say, you know, evolution gave us so much energy to discern in the sensory-neural and dexterity. That's what we're going to be taking care of patients. We can use AI to really be a force to help us to be better clinicians and not to really replace us. So, if we get this right and we decide for transparency with trust, inclusion, etc., it will never replace any of our work, which is so important, as much as we want, we can actually take care of patients and be personalized, timely, and equitable. So, all those things are what get me excited every single day about these conversations on AI. Dr. Paul Hanona: All great thoughts, Dr. Bonilla. I'm very excited to see how this field evolves. I'm excited to see how oncologists really come to this field. I think with technology, there's always a bit of a lag in adopting it, but I think if we jump on board and grow with it, we can do amazing things for the field of oncology in general. Thank you for the advancements that you've made in your own career in the field of AI and oncology and just ultimately with the hopeful outcomes of improving patient care, especially cancer patients. Dr. Arturo Loaiza-Bonilla: Thank you so much, Dr. Hanona. Dr. Paul Hanona: Thanks to our listeners for your time today. If you value the insights that you hear on ASCO Daily News Podcast, please take a moment to rate, review, and subscribe wherever you get your podcasts. Disclaimer: The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions. Guests on this podcast express their own opinions, experience, and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity, or therapy should not be construed as an ASCO endorsement. More on today's speakers: Dr. Arturo Loaiza-Bonilla @DrBonillaOnc Dr. Paul Hanona @DoctorDiscover on YouTube Follow ASCO on social media: @ASCO on Twitter ASCO on Facebook ASCO on LinkedIn ASCO on BlueSky Disclosures: Paul Hanona: No relationships to disclose. Dr. Arturo-Loaiza-Bonilla: Leadership: Massive Bio Stock & Other Ownership Interests: Massive Bio Consulting or Advisory Role: Massive Bio, Bayer, PSI, BrightInsight, CardinalHealth, Pfizer, AstraZeneca, Medscape Speakers' Bureau: Guardant Health, Ipsen, AstraZeneca/Daiichi Sankyo, Natera
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Dr. David Levinthal, Director of the Neurogastroenterology & Motility Center at the University of Pittsburgh Medical Center joins us in this episode to explain how marijuana can affect our digestive health. He recently gave a talk on trends in Cannabinoids at the American Neurogastroenterology and Motility Society (ANMS) Annual Meeting in Austin, Texas. Dr. Levinthal shares some of the pros and cons of medical marijuana in clinical use cases and how it can impact certain gastrointestinal conditions. He also provides insight on the gut-brain connection and much more in this wide-ranging discussion. As always, the information in this episode is for education purposes only and not medical advice. We caution our listeners to consult with their healthcare providers before embarking on any treatment option.
Get the chance to discover a state-of-the-art platform that revolutionizes commercial real estate lending today with Mitch Ginsberg. Check this episode out to hear the features that make this lending marketplace superior and its process of connecting investors to the best lenders and capital markets. Technology and real estate are a power duo!Key Takeaways to Listen for Upsides of processing your loan applications onlineA walk-through of the primary service offered by CommLoanHow CommLoan assists borrowers within the loan periodPersonal viewpoint on the status of the commercial real estate3-ingredient recipe that will lead to business successResources Mentioned in This EpisodeArthur Young & Co.Brevitest Technologies Free Apartment Syndication Due Diligence Checklist for Passive InvestorUse CommLoan's FREE Commercial Mortgage Calculator to calculate the details of a commercial mortgage with efficiency and without hassle by going to https://www.commloan.com/commercial-mortgages/calculator About Mitch GinsbergBorn and raised in South Africa, Mitch holds a bachelor's degree in accounting and a master's in finance. Following his CPA qualification, he kick-started his career with Arthur Young and later Levinthal & Horwath. After 25 years in the business, Mitch built a residential mortgage bank that funded billions in loans in five western states. He exited residential lending after the 2008 economic collapse. After his exposure to the arduousness of obtaining commercial mortgages, Mitch recognized a problem that needed to be solved. Right then, he resolved to craft a platform that would give borrowers more control and revolutionize the process of obtaining commercial and multifamily financing. With the help of an expert development team, he was able to make his vision a reality - the CommLoan platform (CUPID™)Connect with MitchWebsite: CommLoanLinkedIn: Mitch Ginsberg | CommLoanFacebook: CommLoanInstagram: @commloanTo Connect With UsPlease visit our website: www.bonavestcapital.com, and please click here, to leave a rating and review!SponsorsGrow Your Show, LLCThinking About Creating and Growing Your Own Podcast But Not Sure Where To Start?Visit GrowYourShow.com and Schedule a call with Adam A. Adams
We meet artist Aubrey Levinthal from her studio in Philadelphia!!!Softly-rendered portraits by Aubrey Levinthal explore contemporary psychology. In the works, figures go about familiar daily routines - eating, sleeping and daydreaming. The artist is inspired by a range of modernist painters, from portraitist Alice Neel to collagist Romare Bearden and modernist David Hockney. Her intentionally muted palette of predominantly grey tones is created by layering light washes of oil paint onto panels, and then scraping them down with a blade. This technique renders the skin of her characters as almost translucent - either emerging from, or dissolving into, their surfaces.Much of Levinthal's recent work relates to the COVID-19 pandemic. The loneliness and claustrophobia of social isolation is told through melancholic facial expressions and slumped postures. Recurring motifs, such as browning bananas and unfinished meals, allude to the passing of time, while irregularities in proportion and perspective engage the ways in which a home becomes strange when you spend all your time within it. These details embody the crux of Levinthal's practice - how we inhabit spaces, and how they inhabit us.Levinthal's paintings focus on her own daily interiority and the quotidian, mostly situated in the home. More recently, Levinthal reflects on ones' relationship to the outside world and moves the psychology away from the isolated self to a more unknown drifting space. The paintings are infused with more daylight, colour has become brighter, and the figures are larger. Shared environments, such as neighborhood coffee shops, yoga studios, hospitals, hotels and pools are fraught with nuanced tension and personal connection. Levinthal heightens the psychological space between observing and knowing. The paintings explore a sense of insecurity, self-reflection and curiosity in collective spaces. In Bagel Line (2022), a group of friends situated outside a bagel shop huddle closely together in winter coats. Their expressions range from anxious to annoyed to eager highlighting ones' own duality. The artist projects an interior life onto these strangers: a barista, a person standing in line, a blue-haired teenager at a take-out counter, or a shopper in a clothing store. Within the paintings, objects take on abstract shapes and act as barriers. In Crab Shack (2022), two brown paper bags give the impression of a wall in front of a pensive young woman. Levinthal draws inspiration from the Renassiance period to Modernists such as, Mary Fedden (1915-2012), Milton Avery (1885-1965) and Fairfield Porter (1907-1975). Levinthal's tenderly observed paintings illuminate the strangeness of daily interiority and introspection. In Yoga Mat (2022), the viewer is confronted with a lone woman in a yoga pose. The figure also doubles as an ancient sculpture, most evident in the shapes used and the manner in which the feet are depicted, as if resembling stone. This painting was directly inspired by the Egyptian sculpture titled Statue of Sitepehu (1479-1458 BCE), which is part of the permanent collection at the Penn Museum, Philadelphia. The artist lives and works in Philadelphia, PA and is represented by Monya Rowe Gallery, NY.Follow @AubreyLevinthal on Instagram and their official website https://aubreylevinthal.com/ Follow their gallery: @Monya_Rowe_GalleryAubrey's new work is included in group show 'Close' at GRIMM Gallery curated by Talk Art co-host Russell Tovey from 4th March - 6th April, 2023 2 Bourdon Street, London (UK). Hosted on Acast. See acast.com/privacy for more information.
Kam and Kary are joined by Real Housewives of Orange County Alum, Kelly Dodd Leventhal, to catch up and chat about life on and off their respective shows. Sharing their experiences and thoughts from industry politics to bad apples, maybe some networks should hold the applause. The ladies keep it real and keep it fun, there always has to be a bit of both. Tune in for a Dallas and Orange County special!
Episode No. 549 features artists Aubrey Levinthal and Doron Langberg. Levinthal and Langberg are included in "A Place for Me: Figurative Painting Now" at the Institute of Contemporary Art, Boston. The exhibition, which was curated by Ruth Erickson, spotlights painters who are particularly interested in depicting what is near and dear to them, including friends, lovers, family, studio spaces, and their homes. "A Place for Me" is at the ICA through September 5. Aubrey Levinthal is a Philadelphia-based artist whose work explores the everyday in ways that engage with painting's history. She's shown her work in galleries in New York, Los Angeles, Berlin and Philadelphia. In addition to the ICA Boston exhibition, Levinthal's work is in "Women of Now: Dialogues of Memory, Place & Identity" at the Green Family Art Foundation in Dallas. It was curated by Clare Milliken and Bailey Summers, and is on view through May 15. Doron Langberg is a New York-based artist whose often large-scale works explore intimacy, color and touch. Langberg has been included in group shows at the RISD Museum, the Frick Madison, and the LSU Museum. His work is in the collection of the Pennsylvania Academy of the Fine Arts and the RISD Museum.
David Levinthal is a New York–based photographer whose work explores the relationship between photographic imagery and the fantasies, myths, events and characters that shape the collective American consciousness. Refining a personal photographic style and vision, Levinthal utilizes toy figures and structures as subject matter for the creation of a surrogate reality. Levinthal has endeavored to create a 'fictional world' that simultaneously calls into question our sense of truth and credibility.Levinthal's photographs of soldiers at war, cowboys and Barbie dolls reference and reexamine the iconic images and historical events that have shaped postwar American culture. Through his expansive series such as Hitler Moves East, Modern Romance, Wild West and History, Levinthal's photographs also reveal the false memories and stereotypes that lurk beneath the surface, challenging viewers to confront the stories we tell about ourselves and our country. Levinthal is a recipient of the National Endowment for the Arts Fellowship and a Guggenheim Fellowship, and his photographs reside in the permanent collections of New York's The Museum of Modern Art, the Metropolitan Museum of Art, and the Whitney Museum of American Art, the Centre Pompidou in Paris, the Art Institute of Chicago, LACMA, the National Gallery of Art and the Smithsonian American Art Museum in Washington, DC, among others.In 1997, The International Center for Photography in New York presented the first retrospective of his work titled David Levinthal: Work from 1977 – 1996. The George Eastman Museum in Rochester, New York, organized the most recent retrospective, David Levinthal: War, Myth, Desire, in 2018. And In 2019, the Smithsonian American Art Museum organized American Myth & Memory: David Levinthal Photographs to showcase seventy-four color photographs.
Should members of Congress be allowed to trade stocks? It's a question that legislators are debating right now, in the wake of a searing investigation from the publication Insider. In this interview, Lindsay chats with Dave Levinthal, Insider's deputy Washington Bureau chief. They discuss some of the shocking discoveries from Levinthal's reporting. And they consider whether Congress might be willing to pass new, sweeping legislation.Listen to new episodes 1 week early and to all episodes ad free with Wondery+. Join Wondery+ for exclusives, binges, early access, and ad free listening. Available in the Wondery App https://wondery.app.link/americanscandal.Support us by supporting our sponsors!Jordan Harbinger Show - Find the Jordan Harbinger Show wherever you listen to podcast!Better Help - American Scandal listeners get 10% off their first month at betterhelp.com/asSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
Mike grew up in the looming shadows of an early Silicon Valley, before it developed its now-infamous reputation. Being surrounded by such entrepreneurial-minded people, including within his own home, Mike felt the pressure, yet was also humble enough to realize how lucky he was to know so many smart minds. He attended Stanford with a plan to go into engineering, yet after relocating to the Boston area where his brother was attending college, he began to explore the world of venture capital. Forty years later, Mike hasn't looked back. He's been involved in countless corporate successes, although he will admit he was a part of far more failures. Now living in Park City, he talks of going back to school to reignite some of his early passions, while also looking for the next early-stage business opportunity.
Eugene Shakhnovich is a Professor of Chemistry and Chemical Biology, Department of Chemistry and Chemical Biology at Harvard University. Head of Shakhnovich Biophysics Lab. The research of Professor Eugene Shakhnovich and his group is directed towards understanding the basic principles of protein folding and structural and dynamical properties of other complex polymer systems. Some of the questions addressed are: 1) what is required for polypeptide chains to have a unique structure? 2) how is this structure encoded by aminoacid sequence ("prediction problem")? and 3) how does the polypeptide chain form this unique structure in a finite time (the so-called "Levinthal paradox")? The approach to a solution of these problems is based on utilization and development of modern analytical methods of statistical mechanics such as replicas, renormalization group etc., and numeric studies of non-traditional lattice models with exhaustively enumerated conformations. Other fields of interest to Professor Shakhnovich include investigation of microdomain structure in random polymer melts and diffusion-controlled processes in living cells. Current projects include: 1) Development of a new approach to and algorithm for the prediction of stable conformations of a protein, based on a combination of statistical mechanical methods such as mean-field theory, exhaustive enumeration of all conformations within a given fold, and Monte-Carlo dynamical simulation. 2) Development of the quantitative theory of protein stability, which takes into account the majority of interactions in protein molecules. 3) Monte-Carlo simulations of folding of polypeptides in which conformations are exhaustively enumerated. These simulations make it possible to address the "Levinthal paradox" and develop a theory of kinetics of protein folding. Within this project also is an evolutionary question of the way in which sequences that are able to fold evolved. 4) Theory of microdomain structure in random copolymers and analysis of unusual phases in such systems. FIND EUGENE ON SOCIAL MEDIA LinkedIn | Facebook | Twitter | Instagram ================================ SUPPORT & CONNECT: Support on Patreon: https://www.patreon.com/denofrich Twitter: https://twitter.com/denofrich Facebook: https://www.facebook.com/denofrich YouTube: https://www.youtube.com/denofrich Instagram: https://www.instagram.com/den_of_rich/ Hashtag: #denofrich © Copyright 2022 Den of Rich. All rights reserved.
Eugene Shakhnovich is a Professor of Chemistry and Chemical Biology, Department of Chemistry and Chemical Biology at Harvard University. Head of Shakhnovich Biophysics Lab. The research of Professor Eugene Shakhnovich and his group is directed towards understanding the basic principles of protein folding and structural and dynamical properties of other complex polymer systems.Some of the questions addressed are: 1) what is required for polypeptide chains to have a unique structure? 2) how is this structure encoded by aminoacid sequence ("prediction problem")? and 3) how does the polypeptide chain form this unique structure in a finite time (the so-called "Levinthal paradox")?The approach to a solution of these problems is based on utilization and development of modern analytical methods of statistical mechanics such as replicas, renormalization group etc. and numeric studies of non-traditional lattice models with exhaustively enumerated conformations.Other fields of interest to Professor Shakhnovich include investigation of microdomain structure in random polymer melts and diffusion-controlled processes in living cells. Current projects include: 1) Development of a new approach to and algorithm for the prediction of stable conformations of a protein, based on a combination of statistical mechanical methods such as mean-field theory, exhaustive enumeration of all conformations within a given fold, and Monte-Carlo dynamical simulation. 2) Development of the quantitative theory of protein stability, which takes into account the majority of interactions in protein molecules. 3) Monte-Carlo simulations of folding of polypeptides in which conformations are exhaustively enumerated. These simulations make it possible to address the "Levinthal paradox" and develop a theory of kinetics of protein folding. Within this project also is an evolutionary question of the way in which sequences which are able to fold evolved. 4) Theory of microdomain structure in random copolymers and analysis of unusual phases in such systems.FIND EUGENE ON SOCIAL MEDIALinkedIn | Facebook | Twitter | Instagram================================PODCAST INFO:Podcast website: https://www.uhnwidata.com/podcastApple podcast: https://apple.co/3kqOA7QSpotify: https://spoti.fi/2UOtE1AGoogle podcast: https://bit.ly/3jmA7ulSUPPORT & CONNECT:Support on Patreon: https://www.patreon.com/denofrichTwitter: https://www.instagram.com/denofrich/Instagram: https://www.instagram.com/denofrich/Facebook: https://www.facebook.com/denofrich
Rep. Blake Moore violated federal law by failing to report up to $1.1 million in stock trades. But, for that he was fined just $200 by the House Ethics Committee.Dave Levinthal, Deputy Washington Editor for Insider.com, who broke the Moore story, says these laws are in place for a reason.“It was put in place to defend against potential conflicts of interest or just give the public the ability to see what members of Congress are doing in terms of their personal stock trades at a time when they're being lobbied by the very companies they themselves may invest in,” Leventhal said. “These companies many times will have tens of millions, hundreds of millions of dollars at stake with the decisions being made by the government, including contracts the government hands out to them. There's a tangled web of financial interests here, and this was put in place to shine sunlight and provide transparency,” Levinthal added. He also says the small fine Moore was required to pay shows how poorly Congress does when it comes to regulating themselves. “It's like having two football teams take the field and there's no referee. The two teams just sort of decide how they're going to play the game. Oftentimes you'll have situations where the penalties are quite low because nobody really wants to put themselves into a situation that could be precarious,” Leventhal said.Dave Levinthal on Twitter: @DaveLevinthal
On today's ID the Future, physicist Brian Miller continues his review of James Tour's origin-of-life YouTube series. As Miller explains, Tour, a world-renowned synthetic organic chemist and professor at Rice University, was inspired to create the series when YouTuber and evolutionist Dave Farina critiqued Tour's critique of contemporary origin-of-life claims. In reviewing Tour's video series, Miller and host Eric Anderson praise the Tour series and discuss the Levinthal paradox of the interactome, the ridiculously long odds of blind processes assembling the first living cell, and the challenge of cell death (think Humpty Dumpty and what all the king's men couldn't do). Also discussed: entropy, molecular machines, the challenges that Brownian motion and homochirality pose, the presence of intelligent design in Read More › Source
As part of the rich buffet of joy that MS lays out for us, problems with your gut and pooping have to be right at the top of the charts - or the shit-list, if you will.Just to state it for the record, not everyone with MS will have these issues - as we know, MS isn’t a one-size-fits-all deal. But it is something that a lot of people deal with, which is why we’re covering it here.So my guest today is Dr. David Levinthal, the Director of the Neurogastroenterology and Motility Center at the University of Pittsburgh Medical Centre. Dr. Levinthal got his doctorate in Neuroscience and has a particular interest in functional and motility disorders of the GI tract, and GI symptoms that arise in the context of neurological disorders, including MS.So as far as gut issues and MS are concerned, it’s safe to say that he knows his shit! Topics covered in this episode include:What are the GI issues which commonly affect people with MS? How neural circuitry interacts with the gutWhy are these issues overrepresented in people with MS?Current experiments with brain stimulationNew developments, treatment options, and Dr. Levinthal’s current focusWhat on earth is the Bristol Stool Chart?!Resources for this episode (clickable links):Get your copy of Kathy’s ebook with Erin Glace: "Bowel and Bladder Issues in Multiple Sclerosis by Two Pee Brains With Potty Mouths Talking Shit About MS"Connect with Dr. Levinthal on Twitter and view his Clinical Provider PageVisit the American Neurogastroenterology and Motility Society websiteWeb MD page about The Bristol Stool ChartHelp keep FUMS alive at the FUMS Podcast Patreon page Sign up for the Patients Getting Paid course email waiting list** Sign up for The FUMS 6-Pack here: The FUMS 6-Pack.~ Special thanks to my podcast editor Steve Woodward. Do you have a podcast or are you interested in starting a pod? I HIGHLY recommend adding Steve to your team. Find him at PodcastingEditor.com
What is the protein folding problem that has left researchers stuck for nearly 50 years? Knowing the 3D shape of proteins is so important for our understanding of various diseases and vaccine development. However, these shapes are fantastically complex and difficult to predict. Researchers have spent years trying to determine the 3D structure of proteins. Thanks to AI systems like AlphaFold, it's now much easier and faster to predict protein shapes. AlphaFold is currently leading the way in protein folding research and has been described as a “revolution in biology.” In this episode of Short and Sweet AI, I explore the protein folding problem in more detail and how AlphaFold is accelerating our understanding of protein structures. In this episode, find out: Why protein folding is so important Why it's so difficult to predict protein structures How Google's DeepMind created AlphaFold How successful AlphaFold has been in predicting protein structures Important Links and Mentions: https://www.youtube.com/watch?v=gg7WjuFs8F4 (AlphaFold: The making of a scientific breakthrough) https://www.youtube.com/watch?v=KpedmJdrTpY (Protein folding explained) https://drpepermd.com/episode/walloped-by-alphago/ (Walloped by AlphaGo) https://drpepermd.com/episode/what-is-alphazero/ (What is AlphaZero?) https://deepmind.com/blog/article/AlphaFold-Using-AI-for-scientific-discovery (AlphaFold: Using AI for scientific discovery) Resources: Nature.com - https://www.nature.com/articles/d41586-020-03348-4 (‘It will change everything': DeepMind's AI makes gigantic leap in solving protein structures) SciTech Daily - https://scitechdaily.com/major-scientific-advance-deepmind-ai-alphafold-solves-50-year-old-grand-challenge-of-protein-structure-prediction/ (Major Scientific Advance: DeepMind AI AlphaFold Solves 50-Year-Old Grand Challenge of Protein Structure Prediction) Episode Transcript: Hello to you who are curious about AI. I'm Dr. Peper and today I'm talking about AlphaFold. One of Biology's most difficult challenges, one that researchers have been stuck on for nearly 50 years is how to determine a protein's 3D shape from its amino-acid sequence. It's known as “the protein folding problem”. When I first came across the subject, I thought, ok, that's a biology problem and maybe AI will solve it but there's no big story here. I was wrong. Some biologists spend months, years, or even decades performing experiments to determine the precise shape of a protein. Sometimes they never succeed. But they persist because having the ability to know how a protein folds up can accelerate our ability to understand diseases, develop new medicines and vaccines, and crack one of the greatest challenges in biology. Why is protein folding so important? Proteins structures contain as much, if not more information, than stored in DNA. Their 3D shapes are fantastically complex. Proteins are made up of strings of amino acids, called the building blocks of life. In order to function, the strings twist and fold into a precise, delicate shapes that turn or wrap around each other. These strings can even merge into bigger, megaplex structures. Only then can these proteins function in the way necessary to build and sustain life. A protein's shape defines what the protein can do and what it cannot do. But there's an astronomical number of ways a protein can fold into its final 3D structure. It's called Levinthal's paradox. Cyrus Levinthal, a molecular biologist, published a paper in 1969 called “How to Fold Graciously.” He found there are so many degrees of freedom in an unfolded chain of amino acids, the molecule has an astronomical number of possible configurations. There're an estimated 200 million known proteins with 30 million new ones discovered every year. Each one has a unique 3D shape which determines how it works and what it does. For the last 50 years, biologists discovered the...
STR "Meet the Scholar" Podcast - Strategic Management Division
Ryan talks to Business Insider Senior Washington Correspondent David Levinthal about the coronavirus stimulus package negotiations.
David Levinthal, M.D. Study Could Explain How Stress Encourages Stomach Ulcers Neuroscientists at the University of Pittsburgh Brain Institute have traced neural pathways that connect the brain to the stomach, providing a biological mechanism to explain how stress can foster ulcer development.The findings, published this week in the Proceedings of the National Academy of Sciences, build a scientific basis for the brain’s influence over organ function and emphasize the importance of the brain-body connection. Until now, research exploring the gut-brain interaction has largely focused on the influence of the gut and its microbiome on the brain. But it’s not a one-way street — the brain also influences stomach function. Article: Multiple areas of the cerebral cortex influence the stomach The connection between our thoughts and feelings and our gut Dr. Levinthal details his testing process The 2 branches of our nervous system that control the organs The body reacts to re-living a stressor as a memory the same way it reacts to the original stressor
David Levinthal is a New York-based artist whose photography depicts “the America that never was but always will be.” He uses toys to recreate iconic moments in American history and pop culture, encouraging his audience to question America’s collective memory. Sidedoor visits Levinthal in his studio, and an exhibition of his work at the Smithsonian American Art Museum titled “American Myth & Memory: David Levinthal Photographs” to explore the distinction between fact and fable. Click here to see the images we discuss in the episode.
David Levinthal is a New York-based artist whose photography depicts “the America that never was but always will be.” He uses toys to recreate iconic moments in American history and pop culture, encouraging his audience to question America’s collective memory. Sidedoor visits Levinthal in his studio, and an exhibition of his work at the Smithsonian American Art Museum titled “American Myth & Memory: David Levinthal Photographs” to explore the distinction between fact and fable. Click here to see the images we discuss in the episode.
As an artist, you’ve likely struggled with honing your craft and finding ways to replenish your creativity over the years, I know I have! That’s why I loved my conversation with Aubrey Levinthal and I know you will too! In our conversation, Aubrey opens up about how she got started as an artist, her experience in art school, how she’s honed her craft, what she does to replenish her creativity, and so much more! I know many of you will also enjoy images of Aubrey’s artwork, located at the end of this post, don’t miss it! Honing your craft. What have been some of the unique challenges you’ve faced on your journey to hone and refine your artistic craft? Have you been plagued with self-doubt? Do you struggle with a block in creativity? You are not alone! There are so many of us who have been there and struggled in silence. Artist Aubrey Levinthal has had her fair share of milestones and struggled along the way. The constant in Aubrey’s story is an inner drive she’s cultivated and nurtured over the years. Aubrey holds herself to a very high standard and wants to bring her work to a level of creativity and quality that goes beyond her wildest dreams. Can you relate? What can you learn from Aubrey’s story? Lessons learned from what doesn’t work on the canvas. Too often we can get so focused on what we can learn from the good that we forget the lessons we can learn from the negative or challenging aspects of the creative process. Have you learned some valuable lessons recently? Aubrey Levinthal has a refreshing perspective on what doesn’t work when she approaches her canvas, she sees an opportunity to learn. I love that! You and I need more positive perspectives like Aubrey’s! Let’s leave the negative terminologies and negative mindsets behind and see setbacks as opportunities to learn. Imagine the impact that simple shift could have on your creative process and your career as an artist. Replenishing your creativity. Do you have any tips on replenishing your creativity as an artist? What have you tried? Are you looking for a way to reset and refresh right now? In my conversation with Aubrey Levinthal, we touched on this important topic. Aubrey says that one of the best ways to replenish her creativity to step away and visit a museum or an art gallery to tap into the reason why she loves creating art. Everyone needs to find what works for them, don’t let yourself burn out! The world needs your unique artistic voice, take care of yourself! The answer is in the paint. When you are young and inexperienced, you tend to make mountains out of molehills. At least that was the case for me! Too often I would get sidetracked or let myself get distracted by some seemingly larger than life challenge, I wish someone would have shared with me Aubrey’s wonderful advice! Looking back at herself ten years ago, Aubrey would tell herself, “The answer is in the paint.” Instead of allowing herself to get overwhelmed at all the options or all the possibilities, Aubrey wishes that she would have given herself the permission to try and fail. At the end of the day, as an artist, your job is to create. Whatever you need to do to cut through the noise and put your paintbrush to canvas, do it! Outline of This Episode [1:00] I introduce my guest, Aubrey Levinthal. [2:45] How did Aubrey sense the call to become an artist? [4:15] Artists that inspired Aubrey from an early age & how her parents empowered her. [6:00] Aubrey talks about her experience at art school. [9:30] Discovering your voice and working through criticism. [12:45] Aubrey describes her artwork. [14:00] What catches Aubrey’s eye for her motifs? How does she use her sketchbook? [17:15] Aubrey’s process in her studio. [19:30] Honing in on surprises and a sense of mystery. [23:00] Aubrey opens up about her habits and routines. [29:00] Lessons learned from what doesn’t work on the canvas. [31:00] What is Aubrey working on right now? What does she do to refresh herself? [34:00] Grappling with the perception of the romanticized artist. [40:00] Does Aubrey have a painting that she’d never part with? [41:30] If Aubrey could have artwork from any living artist who would she choose? [43:30] The answer is in the paint. Other artists mentioned on this episode Georgia O'Keeffe Mary Cassatt Angela A'Court Dustin Metz Samantha Mitchell Rebekah Callaghan Adam Lovitz Mariel Capanna Polina Barskaya Resources Mentioned on this episode Check out Aubrey’s website! Connect With Antrese On Facebook On Pinterest On Instagram On Twitter
Jason Levinthal just acquired 4FRNT Skis, so we talk to Levinthal and 4FRNT founder, Matt Sterbenz, about the deal; what brought it about; what we can expect going forward; and the state of the ski industry in general.TOPICS & TIMES:So what exactly just happened here? (2:52)Will this affect where 4FRNT skis are produced? What else will change? (11:41)What does it mean to be an "indie" ski brand in today's arena? (15:20)When did you guys first start talking about the possibility of teaming up? (21:17)What’s going to change and what’s going to stay the same in the next season or two? (25:18)Matt: what’s your favorite LINE ski or J Ski that you’ve seen or been on? (29:15)Do you think we’ll see more acquisitions like this in the coming years — specifically, of indies teaming up? (35:27)Closing Thoughts (43:45) See acast.com/privacy for privacy and opt-out information.
Jason Levinthal has been a visionary in the ski industry for over 20 years. He's know for brand building genius, blue-collar work ethic and keeping his finger on the pulse of tomorrow. He started the revolutionary ski company, Line Skis, out of his parent’s garage and eventually was forced to sell his baby (while still managing it and other brands) to The Jarden Corporation. Jason’s entrepreneurial spirit and passion for timely innovation led him to leave the comfort of his corporate check and start again from scratch with J Skis. Jason Levinthal, Owner, J Skis Jason Levinthal Show Notes :31: What is Jason up to these days? 1:19: Typical work week for Jason 3:30: What group did Jason fit into in High School? 5:26: Jason talks college 7:17: The foundation of Line Skis 8:39: Why the name Line? 11:10: Did anyone believe in Jason Levinthal in the early days? 12:29: At Ski Magazine tests Jason is asked why is he there and told to “throw his skis down the stairs.” 13:55: Sacrificing life for the brand 16:06: Did Jason ever think about enforcing the twin tip patent and working with other brands 21:48: The Reactor Binding and bindings in general 26:40: K2 buys Line 28:50: The future of Levinthal is J Skis 31:10: Josh Malczyk and his Line and Levinthal history 33:00: The game-changing development process of J Skis 35:29: Biggest career regrets 37:42: What is Jason most proud of in his career?
Pamela Levine, VP of Sales at Manduka, talks sales and marketing with Craig Wilson and Matt Levinthal, formerly of Patagonia. Craig Wilson is the author of The Compass and The Nail.
Jeff Denby, former CEO of PACT, talks with Matt Levinthal and Craig Wilson of Compass and Nail, and formerly of Patagonia, about the best ways of Marketing and Branding your company.
Craig Wilson, former Patagonia marketing guru, Matt Levinthal of Compass and Nail, and Tim Rhone, co-owner of the Mob Shop in Ojai, CA discuss marketing and customer loyalty.
Levinthal, David. WHO PUSHED HUMPTY DUMPTY? AND OTHER NOTORIOUS NURSERY TALE MYSTERIES
In part 2 of this week's episodes about wigs, Jessica Glasscock joins us again to speak about the market for human hair in the 19th century, some of the celebrity hairstylists of the early 20th century, wigs and weaves in black haircare practices and--of course--the importance of wigs in drag culture.RECOMMENDED READING: Glasscock, Jessica. Wigging Out: Fake Hair That Made Real History. New York: Blackdog & Levinthal, 2023.Support this podcast at — https://redcircle.com/dressed-the-history-of-fashion/exclusive-contentAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy