Speak, a global leader in AI-powered language learning, has raised $78 million in Series C funding, achieving a $1 billion valuation. This funding milestone underscores the company’s mission to transform language education by prioritizing spoken fluency through innovative AI technology. Founded in 2016 by Connor Zwick…
Smashing Meets Product Design
I had the pleasure of hosting a recent Smashing Magazine workshop on product design, subbing for Vitaly Friedman who usually runs these things.
What? A front-ender interviewing really smart people about their processes for user research, documenting requirements, and …
Smashing Meets Product Design originally published on CSS-Tricks,…
CSSWG Minutes Telecon (2024-12-04): Just Use Grid vs. Display: Masonry
The CSSWG met to try and finally squash a debate that has been going on for five years: whether Masonry should be a part of Grid or a separate system. We’ve got coverage of both presentations for ya.
CSSWG Minutes Telecon (2024-12-04): Just Use Grid vs. Display:…
Cellular traffic congestion in chronic diseases suggests new therapeutic targets
Chronic diseases like Type 2 diabetes and inflammatory disorders have a huge impact on humanity. They are a leading cause of disease burden and deaths around the globe, are physically and economically taxing, and the number of people with such diseases is growing.
Treating chronic disease has proven difficult because there is not one simple cause, like a single gene mutation, that a treatment could target. At least, that’s how it has appeared to scientists. However, new research from MIT professor of biology and Whitehead Institute for Biomedical Research member Richard Young and colleagues, published in the journal Cell on Nov. 27, reveals that many chronic diseases have a common denominator that could be driving their dysfunction: reduced protein mobility.
What this means is that around half of all proteins active in cells slow their movement when cells are in a chronic disease state, reducing the proteins’ functions. The researchers’ findings suggest that protein mobility may be a linchpin for decreased cellular function in chronic disease, making it a promising therapeutic target.
In their paper, Young and colleagues in his lab, including MIT postdoc Alessandra Dall’Agnese, graduate students Shannon Moreno and Ming Zheng, and Research Scientist Tong Ihn Lee, describe their discovery of this common mobility defect, which they call proteolethargy; explain what causes the defect and how it leads to dysfunction in cells; and propose a new therapeutic hypothesis for treating chronic diseases.
“I’m excited about what this work could mean for patients,” says Dall’Agnese. “My hope is that this will lead to a new class of drugs that restore protein mobility, which could help people with many different diseases that all have this mechanism as a common denominator.”
“This work was a collaborative, interdisciplinary effort that brought together biologists, physicists, chemists, computer scientists and physician-scientists,” Lee says. “Combining that expertise is a strength of the Young lab. Studying the problem from different viewpoints really helped us think about how this mechanism might work and how it could change our understanding of the pathology of chronic disease.”
Commuter delays cause work stoppages in the cell
How do proteins moving more slowly through a cell lead to widespread and significant cellular dysfunction? Dall’Agnese explains that every cell is like a tiny city, with proteins as the workers who keep everything running. Proteins have to commute in dense traffic in the cell, traveling from where they are created to where they work. The faster their commute, the more work they get done. Now, imagine a city that starts experiencing traffic jams along all the roads. Stores don’t open on time, groceries are stuck in transit, meetings are postponed. Essentially all operations in the city are slowed.
The slowdown of operations in cells experiencing reduced protein mobility follows a similar progression. Normally, most proteins zip around the cell bumping into other molecules until they locate the molecule they work with or act on. The slower a protein moves, the fewer other molecules it will reach, and so the less likely it will be able to do its job. Young and colleagues found that such protein slowdowns lead to measurable reductions in the functional output of the proteins. When many proteins fail to get their jobs done in time, cells begin to experience a variety of problems — as they are known to do in chronic diseases.
Discovering the protein mobility problem
Young and colleagues first suspected that cells affected in chronic disease might have a protein mobility problem after observing changes in the behavior of the insulin receptor, a signaling protein that reacts to the presence of insulin and causes cells to take in sugar from blood. In people with diabetes, cells become less responsive to insulin — a state called insulin resistance — causing too much sugar to remain in the blood. In research published on insulin receptors in Nature Communications in 2022, Young and colleagues reported that insulin receptor mobility might be relevant to diabetes.
Knowing that many cellular functions are altered in diabetes, the researchers considered the possibility that altered protein mobility might somehow affect many proteins in cells. To test this hypothesis, they studied proteins involved in a broad range of cellular functions, including MED1, a protein involved in gene expression; HP1α, a protein involved in gene silencing; FIB1, a protein involved in production of ribosomes; and SRSF2, a protein involved in splicing of messenger RNA. They used single-molecule tracking and other methods to measure how each of those proteins moves in healthy cells and in cells in disease states. All but one of the proteins showed reduced mobility (about 20-35 percent) in the disease cells.
“I’m excited that we were able to transfer physics-based insight and methodology, which are commonly used to understand the single-molecule processes like gene transcription in normal cells, to a disease context and show that they can be used to uncover unexpected mechanisms of disease,” Zheng says. “This work shows how the random walk of proteins in cells is linked to disease pathology.”
Moreno concurs: “In school, we’re taught to consider changes in protein structure or DNA sequences when looking for causes of disease, but we’ve demonstrated that those are not the only contributing factors. If you only consider a static picture of a protein or a cell, you miss out on discovering these changes that only appear when molecules are in motion.”
Can’t commute across the cell, I’m all tied up right now
Next, the researchers needed to determine what was causing the proteins to slow down. They suspected that the defect had to do with an increase in cells of the level of reactive oxygen species (ROS), molecules that are highly prone to interfering with other molecules and their chemical reactions. Many types of chronic-disease-associated triggers, such as higher sugar or fat levels, certain toxins, and inflammatory signals, lead to an increase in ROS, also known as an increase in oxidative stress. The researchers measured the mobility of the proteins again, in cells that had high levels of ROS and were not otherwise in a disease state, and saw comparable mobility defects, suggesting that oxidative stress was to blame for the protein mobility defect.
The final part of the puzzle was why some, but not all, proteins slow down in the presence of ROS. SRSF2 was the only one of the proteins that was unaffected in the experiments, and it had one clear difference from the others: its surface did not contain any cysteines, an amino acid building block of many proteins. Cysteines are especially susceptible to interference from ROS because it will cause them to bond to other cysteines. When this bonding occurs between two protein molecules, it slows them down because the two proteins cannot move through the cell as quickly as either protein alone.
About half of the proteins in our cells contain surface cysteines, so this single protein mobility defect can impact many different cellular pathways. This makes sense when one considers the diversity of dysfunctions that appear in cells of people with chronic diseases: dysfunctions in cell signaling, metabolic processes, gene expression and gene silencing, and more. All of these processes rely on the efficient functioning of proteins — including the diverse proteins studied by the researchers. Young and colleagues performed several experiments to confirm that decreased protein mobility does in fact decrease a protein’s function. For example, they found that when an insulin receptor experiences decreased mobility, it acts less efficiently on IRS1, a molecule to which it usually adds a phosphate group.
From understanding a mechanism to treating a disease
Discovering that decreased protein mobility in the presence of oxidative stress could be driving many of the symptoms of chronic disease provides opportunities to develop therapies to rescue protein mobility. In the course of their experiments, the researchers treated cells with an antioxidant drug — something that reduces ROS — called N-acetyl cysteine and saw that this partially restored protein mobility.
The researchers are pursuing a variety of follow-ups to this work, including the search for drugs that safely and efficiently reduce ROS and restore protein mobility. They developed an assay that can be used to screen drugs to see if they restore protein mobility by comparing each drug’s effect on a simple biomarker with surface cysteines to one without. They are also looking into other diseases that may involve protein mobility, and are exploring the role of reduced protein mobility in aging.
“The complex biology of chronic diseases has made it challenging to come up with effective therapeutic hypotheses,” says Young. “The discovery that diverse disease-associated stimuli all induce a common feature, proteolethargy, and that this feature could contribute to much of the dysregulation that we see in chronic disease, is something that I hope will be a real game-changer for developing drugs that work across the spectrum of chronic diseases.”
Jamie Caramanica, DISCO’s SVP of Engineering – Interview Series
Jamie Caramanica, is DISCO’s Senior Vice President of Engineering. DISCO brings artificial intelligence, cloud computing, and data analytics to the practice of law so attorneys can focus on what matters most: securing justice for their clients and winning the most important disputes in the world. What…
How Business Leaders Can Achieve Their Goals in Both AI and Sustainability
For companies, balancing AI adoption and environmental impact is an imperative. According to the World Economic Forum (WEF), the power needed to support AI’s growth is doubling every 100 days. By 2028, AI’s energy consumption could exceed the total power used by Iceland in 2021. AI…
Dr. Devavrat Shah, Co-Founder & CEO of Ikigai Labs – Interview Series
Dr. Devavrat Shah is the Co-founder and CEO of Ikigai Labs and he is a professor and a director of Statistics and Data Science Center at MIT. He co-founded Celect, a predictive analytics platform for retailers, which he sold to Nike. Devavrat holds a Bachelor and PhD in Computer…
Revisiting reinforcement learning
Dopamine is a powerful signal in the brain, influencing our moods, motivations, movements, and more. The neurotransmitter is crucial for reward-based learning, a function that may be disrupted in a number of psychiatric conditions, from mood disorders to addiction.
Now, researchers led by MIT Institute Professor Ann Graybiel have found surprising patterns of dopamine signaling that suggest neuroscientists may need to refine their model of how reinforcement learning occurs in the brain. The team’s findings were published recently in the journal Nature Communications.
Dopamine plays a critical role in teaching people and other animals about the cues and behaviors that portend both positive and negative outcomes; the classic example of this type of learning is the dog that Ivan Pavlov trained to anticipate food at the sound of bell. Graybiel, who is also an investigator at MIT’s McGovern Institute, explains that according to the standard model of reinforcement learning, when an animal is exposed to a cue paired with a reward, dopamine-producing cells initially fire in response to the reward. As animals learn the association between the cue and the reward, the timing of dopamine release shifts, so it becomes associated with the cue instead of the reward itself.
But with new tools enabling more detailed analyses of when and where dopamine is released in the brain, Graybiel’s team is finding that this model doesn’t completely hold up. The group started picking up clues that the field’s model of reinforcement learning was incomplete more than 10 years ago, when Mark Howe, a graduate student in the lab, noticed that the dopamine signals associated with reward were released not in a sudden burst the moment a reward was obtained, but instead before that, building gradually as a rat got closer to its treat. Dopamine might actually be communicating to the rest of the brain the proximity of the reward, they reasoned. “That didn’t fit at all with the standard, canonical model,” Graybiel says.
Dopamine dynamics
As other neuroscientists considered how a model of reinforcement learning could take those findings into account, Graybiel and postdoc Min Jung Kim decided it was time to take a closer look at dopamine dynamics. “We thought: Let’s go back to the most basic kind of experiment and start all over again,” she says.
That meant using sensitive new dopamine sensors to track the neurotransmitter’s release in the brains of mice as they learned to associated a blue light with a satisfying sip of water. The team focused its attention on the striatum, a region within the brain’s basal ganglia, where neurons use dopamine to influence neural circuits involved in a variety of processes, including reward-based learning.
The researchers found that the timing of dopamine release varied in different parts of the striatum. But nowhere did Graybiel’s team find a transition in dopamine release timing from the time of the reward to the time to the cue — the key transition predicted by the standard model of reinforcement learning model.
In the team’s simplest experiments, where every time a mouse saw a light it was paired with a reward, the lateral part of the striatum reliably released dopamine when animals were given their water. This strong response to the reward never diminished, even as the mice learned to expect the reward when they saw a light. In the medial part of the striatum, in contrast, dopamine was never released at the time of the reward. Cells there always fired when a mouse saw the light, even early in the learning process. This was puzzling, Graybiel says, because at the beginning of learning, dopamine would have been predicted to respond to the reward itself.
The patterns of dopamine release became even more unexpected when Graybiel’s team introduced a second light into its experimental setup. The new light, in a different position than the first, did not signal a reward. Mice watched as either light was given as the cue, one at a time, with water accompanying only the original cue.
In these experiments, when the mice saw the reward-associated light, dopamine release went up in the centromedial striatum and surprisingly, stayed up until the reward was delivered. In the lateral part of the region, dopamine also involved a sustained period where signaling plateaued.
Graybiel says she was surprised to see how much dopamine responses changed when the experimenters introduce the second light. The responses to the rewarded light were different when the other light could be shown in other trials, even though the mice saw only one light at a time. “There must be a cognitive aspect to this that comes into play,” she says. “The brain wants to hold onto the information that the cue has come on for a while.” Cells in the striatum seem to achieve this through the sustained dopamine release that continued during the brief delay between the light and the reward in the team’s experiments. Indeed, Graybiel says, while this kind of sustained dopamine release has not previously been linked to reinforcement learning, it is reminiscent of sustained signaling that has been tied to working memory in other parts of the brain.
Reinforcement learning, reconsidered
Ultimately, Graybiel says, “many of our results didn’t fit reinforcement learning models as traditionally — and by now canonically — considered.” That suggests neuroscientists’ understanding of this process will need to evolve as part of the field’s deepening understanding of the brain. “But this is just one step to help us all refine our understanding and to have reformulations of the models of how basal ganglia influence movement and thought and emotion. These reformulations will have to include surprises about the reinforcement learning system vis-á-vis these plateaus, but they could possibly give us insight into how a single experience can linger in this reinforcement-related part of our brains,” she says.
This study was funded by the National Institutes of Health, the William N. and Bernice E. Bumpus Foundation, the Saks Kavanaugh Foundation, the CHDI Foundation, Joan and Jim Schattinger, and Lisa Yang.
YoloBox Ultra is a Game Changer
Looking for a powerful, all-in-one device to elevate your live streaming and video production? The YoloBox Ultra might be just what you need! In this unboxing and detailed overview by The Tech Preacher on YouTube, you’ll discover why the YoloBox Ultra is a game-changer for professionals and content creators alike.
The YoloBox Ultra offers unparalleled flexibility with advanced features such as multiple streaming modes, 4K capabilities, NDI and SRT integration, cellular bonding, ISO recordings, and a wide range of input options. Here’s a closer look at what makes the YoloBox Ultra stand out:
1. Streaming Modes for Maximum Flexibility
The YoloBox Ultra supports both Live Streaming Mode (horizontal) for up to three destinations and Vertical Streaming Mode for two vertical platforms. This makes it compatible with popular platforms like TikTok, Facebook, and YouTube, catering to diverse content formats.
2. 4K Live Broadcasting with Snapdragon 865 Power
Built with a Snapdragon 865 processor, the YoloBox Ultra delivers seamless 4K live streaming. Its multifunctional design includes a switcher, monitor, encoder, and recorder, making it an ideal choice for events ranging from weddings to sports productions.
3. Reliable Connectivity with Cellular Bonding
Ensure uninterrupted streaming in any environment! The YoloBox Ultra supports up to five network connections, including USB modems, LTE, Wi-Fi, and Ethernet, providing unmatched reliability for live productions.
4. ISO Recordings for Post-Production Control
With ISO recording capabilities, you can capture all video inputs separately, allowing for greater control in editing. Customize resolution and bitrate to fit your production needs and streamline post-production workflows.
5. Comprehensive Input Options for Multi-Camera Setups
The YoloBox Ultra is designed for versatility with four HDMI inputs, multiple USB ports, and support for over ten live video sources. Whether you’re managing a multi-camera livestream or producing a professional broadcast, this device can handle it all.
6. Built-In Production Enhancements
From customizable overlays and multicam instant replay to video cropping and PTZ control, the YoloBox Ultra is packed with features that enhance viewer engagement and simplify production.
Why Choose the YoloBox Ultra?
The YoloBox Ultra is more than just a live streaming tool—it’s a comprehensive solution for professional-grade video production. Whether you’re a seasoned producer or a content creator exploring new possibilities, this device delivers unmatched performance and versatility.
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The Synergy Between NDI and LiveU in Live Broadcasting Workflows: Transforming Remote Production and Cloud Solutions
In this article by Daniel Pisarski for LiveU, the author explores the powerful synergy between NDI (Network Device Interface) and LiveU, two game-changing technologies in the world of live broadcasting. Since NDI’s introduction in 2015, LiveU recognized its potential as a simple, IP-based protocol for local interconnectivity, providing broadcasters with the ability to easily integrate video contributions from remote locations. By incorporating NDI into its receive servers like the LU2000 and LU4000, LiveU enabled broadcasters to seamlessly inject video into IP workflows, further enhancing broadcast quality and efficiency. This integration, coupled with LiveU’s proprietary Reliable Transport (LRT™), allows broadcasters to transmit live video content over cellular networks, leveraging the simplicity and scalability of NDI for efficient IP video transmission.
As NDI’s influence in live broadcasting has grown, it has become a popular choice for a variety of industries, including live sports, news, and streaming. Initially embraced in Pro-AV, live streaming, and houses of worship, NDI has expanded its reach into larger broadcast environments, gaining significant traction in the wake of the COVID-19 pandemic. The protocol’s scalability and ability to support cloud-based workflows made it the ideal solution for broadcasters navigating remote production challenges. While larger broadcasters were initially hesitant due to concerns over competing protocols like SMPTE, NDI’s ability to support cloud workflows and its increasing industry support have made it an attractive option for broadcasters seeking to modernize their operations.
NDI stands out for its low-latency, lossless quality, and wide adoption, making it the preferred protocol for broadcasters operating in private cloud environments. Although alternatives like JPEG XS are emerging, NDI’s ease of use, cost-effectiveness, and widespread support have solidified its role as the go-to solution for cloud production. As broadcasters increasingly migrate to virtual private clouds, the ability to seamlessly integrate technologies like LiveU’s bonded cellular solutions with NDI interconnect solutions is essential for maintaining efficient workflows.
The COVID-19 pandemic highlighted the need for flexible, cloud-based broadcasting solutions. As broadcasters struggled with limited access to traditional facilities, cloud production became a critical solution, enabling them to continue producing content remotely. LiveU played a key role in this transition, providing a ground-to-cloud video contribution solution, while NDI facilitated in-cloud interconnectivity. This combination of LiveU’s reliable transport and NDI’s interconnect solutions allowed broadcasters to scale operations, remain agile, and embrace the flexibility of remote production.
The collaboration between LiveU and NDI has reshaped live broadcasting, offering broadcasters greater efficiency, scalability, and the ability to work seamlessly in cloud-based environments. As broadcasters continue to explore the benefits of cloud workflows and remote production, the integration of NDI and LiveU technologies will remain pivotal in driving innovation and improving live broadcast operations.
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Read the full article by Dan Pisarski for LiveU HERE
Learn more about LiveU below: