Ben Kaplan

We’re honored to have Paolo Cassano, MD, PhD , on our latest episode. As a dual researcher and clinician at Harvard Medical School and Massachusetts General Hospital, Dr. Cassano focuses on addressing brain health disparities with groundbreaking light therapies like photobiomodulation. Key Takeaways:🌟 Learn about the science behind photobiomodulation, using red and near-infrared light to stimulate brain cells, enhancing their energy production, and treating conditions like depression and anxiety. 🌟 Gain insights from real-world applications and patient stories that showcase the remarkable benefits of light therapy. 🌟 Explore the broader implications of photobiomodulation for cognitive enhancement and its role in preventive medicine for aging populations. Dr. Cassano’s expertise in phototherapy, Low Level Light Therapy (LLLT), and Near-Infrared Radiation (NIR) offers a new perspective on brain health. This episode is a must-listen for those interested in cutting-edge medical treatments. 🎧 Listen now on Spotify https://lnkd.in/gRXF4Gyq Apple https://lnkd.in/g3-ZkGay #Photobiomodulation #Inflammation #Pain #RedLightTherapy #DrSinicropi #LightTherapy #HarvardMedicalSchool #WellnessPodcast #BrainHealth #MentalHealth #CognitiveEnhancement

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🙌🏻 Now is the time to take action! Genomic sequencing is the future of health, and with each breakthrough, we move closer to preventive and personalized care. Thank you, Carolyn, for appreciating our work and emphasizing its importance. 💙 Here, Dr. Robert Green MD, MPH, leader of the BabySeq project at Mass General Brigham, explained the significance of genetic testing in newborns, noting that over 700 treatable genetic conditions can only be detected by examining the DNA itself. In the BabySeq study, more than 10% of seemingly healthy babies showed unexpected yet actionable genetic findings. This does not mean all of these children will develop a disease, but it does indicate that 10% were at risk for a genetic condition that could be managed or treated with early intervention. Dr. Robert shares how he hopes the attention will lead to more screening for genetic conditions in newborn babies. You can read his full interview for CBS News here: https://lnkd.in/g-KUmFvK #genomes2people #babyseq #babyseqproject #raredisease #genetics #geneticconditions #geneticdiseases #geneticdisorders #childhooddisorders #childhooddiseases #genetictesting #geneticcounseling #dna #genome #genomics #genomicsresearch #screening #newbornscreening #newbornhealth #sequencing #genomicsequencing #newbornsequencing #earlyprevention #health #preventivehealthcare #personalizedhealthcare #healthcare #healthcommunication #sciencecommunication #scicomm

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Check out our latest issue, where we interview C. Brandon Ogbunu, who studies evolutionary and population genetics, computational biology and epidemiology at Yale University and the Santa Fe Institute. Link here: https://lnkd.in/dWxARpYS

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Join us tomorrow at MIA - Neriman Tokcan from UMass Boston will talk about tensor factorization methods for zero-inflated multi-dimensional genomics data. 📅 Wednesday, October 30, 2024 💬 Neriman Tokcan 💡 Primer, 9:00 am: Tensor Methods for Omics Data Analysis 💡 Seminar, 10:00 am: C-ZIPTF: stable tensor factorization for zero-inflated multi-dimensional genomics data 💌 Join our mailing list: https://bit.ly/MIACast ℹ️ For more information on MIA, including a list of all fall talks and abstracts, visit broad.io/MIA. Both talks will be in person at the Broad and broadcast over Zoom. If you do not have a Broad badge, please arrive at the 75 Ames St. entrance 10 minutes early with an ID to check in with security. We will escort folks up to M1 at 8:55 and 9:55; please email [email protected] if you arrive outside of these times. Broad Institute of MIT and Harvard #UMassBoston #SchmidtCenter #NerimanTokcan #MIA #ModelsInferenceAlgorithms #ScienceNews #ScienceResearch #ComputationalBiology #ML #AI #AppliedMathematics

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Excellent suggestions for navigating the NIH biosketch! Be sure to bookmark this one. #ucdresearchdevelopment #ucdproposaldevelopment #researchdevelopment #proposaldevelopment #nihfunding #nihbiosketch

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Read about the stellar science panel from #StateOfPossible24 and what was said about external innovation, finding success in down years, rebooting the immune system, advances in oncology & obesity, and what the panelists think is most exciting right now in the industry. https://lnkd.in/ep5ydWUM If you're a #MassBioMember, you can watch the panel in its entirety on MB Vision: https://lnkd.in/e5UeUPZ5. Abraham (Abe) Ceesay | Emma Lees | Stan Wang, MD, PhD | Jacob Petersen | Chris Garabedian

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Read about the first Myositis Common Data Elements Consensus Conference, and how ODSS is contributing to CDEs development, in the December edition of the Environmental Factor from the National Institute of Environmental Health Sciences (NIEHS). #NIHData ⤵️

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Here at Rowan, we're building molecular design & simulation tools for all chemists—not just people with years of expertise in simulation and computer science. A huge part of this mission is helping to educate non-computational scientists about what computation can do and where it can be most useful. And as our platform grows more powerful and feature-complete, it becomes more and more important for us to document and explain all of its functionality. Towards this goal, we've recently released a set of video tutorials for common workflows in Rowan, with accompanying transcripts. Our goal here is to make it easy to understand what a given workflow accomplishes, how it works, and how to run it through our platform. We have nine workflows and transcripts live right now on a variety of topics, and will be releasing more in the coming weeks. If you're curious about what computation can do for your problems, check it out at https://lnkd.in/eSAsX6KS

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If you're working with bioimage data in the life sciences, you might find this course exploring how public bioimaging data resources enable and enhance machine learning based image analysis especially useful: https://lnkd.in/eRi32hTn After the course you should be able to: - Interact programmatically with the BioImage Archive (https://lnkd.in/dG2H-K4) and other data resources - Interact with data formats for biological imaging data, particularly cloud-optimised formats - Apply pre-built machine learning models to image data - Train and retrain machine learning models on image data - Utilise machine learning approaches for object detection, image segmentation, and de-noising - Generate quantitative conclusions from images Applications close 5 January 2025 #BioImageArchive #bioimaging #microscopy #machinelearning #datascience #sciencelearning #sciencetraining #EMBL #EMBLEBI

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A new study into AI technologies in reproductive medicine from Giles Palmer, Omar Paredes, Andrew Drakeley, Alejandro Chavez-Badiola, MD, PhD, Thomas Woolley, Katerina Kaouri, and Jacques Cohen surveyed over 700 ART laboratory professionals around the world to reveal their levels of awareness, adoption and comprehension of AI. As well as directly addressing reproductive scientist’s attitudes towards AI tools, the results also reveal attitudes towards, relationship between AI and women in tech, highlights ongoing debates about data ownership, privacy, and fair compensation in AI, commercial use of data in the field, job security and concepts of data as labor. The results illustrate an interesting milestone in AI within the field, with many respondents poised to implement AI with proper data and training. However, there is also some hesitation at wide-scale enthusiasm while developers provide rigorous proof of enhanced IVF outcomes to justify clinical integration. The full paper is available now as a pre-proof to RBMO subscribers from our in-press articles section now: https://lnkd.in/eUV96Cnm #ReproductionTechnologyAndSociety #IVFLaboratoryStaff #AIEmbryology #Technology #AIethics #AIinTheWorkplace #DataasLabor #WomenandAI

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NIH researchers discover potential therapeutic target for degenerative eye disease. Study reveals cellular pathology of “dry” AMD. Read:  https://lnkd.in/e7m_QcE7 The National Institutes of Health National Institutes of Health National Institutes of Health #sciencesdelavie #biotechnology #biotechnology #innovation #innovations #research #sciences #medicaments #research #drugresearch #laboratories #labs #chemistry #chemistry #biology #biologie #biopharma #eyehealth #santedesyeux #maculardegeneration #degenerescencemaculaire

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Can AI speed up drug discovery by predicting side effects? University of California, San Francisco's James Fraser, PharmD, with help from UCSF’s Quantitative Biosciences Institute (QBI), is leading a cutting-edge effort to map the drug-protein interactions that cause side effects and create and test drug molecules that will avoid them. This AI-powered research, funded by up to $30M from the federal Advanced Research Projects Agency for Health (ARPA-H) program, stands to revolutionize how we create safe, effective therapeutics. Nevan Krogan https://lnkd.in/gfeDjUVz

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#Announcement from Frederick National Laboratory for Cancer Research You are invited to join the user group for the #NEW Computational Resources for Cancer Research portal that launched at #AACR!   1. The first user group meeting will be held on Tuesday, May 14, 2024, 3:00 pm – 4:30 pm ET. This meeting is planned for 90 minutes; future meetings may be less. 2. We will start the discussion about cancer computing needs at the first user group meeting. 3. For reference, see the portal launch announcement, below, and watch for the calendar invitation coming soon! Please join us!   Who: Cancer data scientists, students, and biomedical researchers who want to help increase the scientific impact and usability of the resources on the portal. All #career levels are encouraged to participate: students, 1st year investigators, professors and PIs, physician-scientists, and clinicians!   What: First computational.cancer.gov user group meeting Purpose: Help increase the scientific impact and usability of the resources on the new portal! Current resources include computational models, scientific software, data and datasets, educational use cases, publications, collaborations, emerging areas, and events.   When: Tuesday, May 14, 2024, 3:00 pm – 4:30 pm ET                                                                                                                                                                                                                                                                 Link: Meeting link Meeting ID: 216 030 092 621 Passcode: pwetT7

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Don't miss our poster presentations at Discovery on Target in Boston, MA! 📃 "Identification and characterization of small molecules inhibiting RNA targets: miRNA" 🏷 Session A, poster A39 📆 October 1st to 2nd a.m. 👩🏼‍🔬 Paola C., PhD, Director Alliance Management Abstract: RNA plays a key role in transcription and translation: gene regulation, proliferation, apoptosis, and development. The biological function is linked to the unique secondary and tertiary structures. Many diseases are associated with dysregulation of RNA functions, so there is a growing interest in RNAs as drug targets for novel therapies or targeting undruggable proteins. The most used modalities are antisense oligonucleotides (ASOs), CRISPR gene editing, and more recently small molecules. [...] Discover more about our approach that demonstrates a miRNA targeting platform that could be applied to other oncogenic miRNA targets: https://lnkd.in/edM4ecJj For more questions and details, come and meet our team at our booth 508! #DrugDiscovery #Biophysics #RNA #SPR #microRNA #DiscoveryOnTarget #BostonDOT24

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Stemloop Reads: New Platform for aTF Biosensors 🧬 Last week, Kyle Nishikawa, Jackie Chen, Vatsan Raman, and collaborators published an article in Nature Communications detailing their development of a new platform, Sensor-seq, to design allosteric transcription factors (aTF) for non-native ligands. Using Sensor-seq, they screened over 17,000 TtgR variants against 2 native and 7 non-native ligands to identify new aTFs of varying specificity with activity on 8 out of the 9 ligands tested. The activity of several of these variants was confirmed with secondary and tertiary testing. To gain structural insights, the team applied unsupervised learning to identify key amino acid residues responsible for ligand specificity profiles. The authors also obtained a crystal structure of one variant to better understand the structural features driving specificity. Finally, the authors developed two cell-free biosensors using TtgR variants identified in the study for important small molecules in the pharmaceutical space with sensitivities in the nM range. The first targets naltrexone, a molecule with applications in detecting opioid use. The second focuses on quinine, offering potential for monitoring water safety. Here at Stemloop, we are always excited to hear about new ways scientists are expanding upon the aTF toolkit that nature started for us. With more high-throughput techniques, we get closer to the possibility of being able to make a biosensor for anything! Read more here: https://lnkd.in/g3AWHKEB  #SyntheticBiology #Biosensors #Biotechnology #Innovation

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🌟 NIH Researchers Use AI to Improve Clinical Trial Recruitment 🤖 NIH researchers have developed TrialGPT, an AI model designed to match patients with clinical trials by analyzing medical summaries. A recent study published in Nature Communications shows the tool achieves 87.3% accuracy, comparable to human performance, and speeds up patient screening by 40%. ⏱️ While TrialGPT has some limitations, such as occasional errors in medical reasoning, it holds promise for addressing recruitment challenges faced by clinical trials. The tool is now being tested in real-world settings as part of the NIH’s 2024 Director’s Challenge Innovation Award. #ClinicalTrials #AIHealthcare #TrialGPT #PatientRecruitment #NIH #HealthTech https://lnkd.in/ef-ZrHhU

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Want to understand how we make our digital maps of biology? Our updated preprint explains. “Building, Benchmarking, and Exploring Perturbative Maps of Transcriptional and Morphological Data” reveals how scientists at Recursion and Genentech are scaling genetic perturbation techniques with high-dimensional assays such as cellular microscopy and RNA-sequencing in order to create digital “maps of biology” that both capture known biological relationships and uncover new associations that can lead to new therapeutic discoveries. The paper shows how datasets from various experiments (including CRISPR-Cas9 knockout, CRISPRi knockdown, and compound treatment) are combined to create these maps – unified, relatable embedding spaces allowing for the generation of genome-scale sets of pairwise comparisons. In the paper, the researchers:  (1) establish a standardized terminology for the steps involved in perturbative map building (2) introduce key classes of benchmarks to assess the quality of such maps (3) construct maps from four genome-scale datasets employing different cell types, perturbation technologies, and data readout modalities (4) generate benchmark metrics for the constructed maps and investigate the reasons for performance variations, and  (5) demonstrate utility of these maps to discover new biology by suggesting roles for two largely uncharacterized genes. Learn more: https://lnkd.in/e9UmvZQ8 #ai #ml #maps #tech #drugdiscovery #techbio #digitalmaps #biology Safiye C. Jan-Christian Hütter, Nathan Lazar, PhD, Rahul Mohan, Conor Tillinghast, Tommaso Biancalani, Marta Fay, Berton Earnshaw, Imran Haque

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