The Future of AI in Cardiology

Reporter: Arav Gandhi, Research Assistant 2, Domain Content: Cardiovascular Diseases, Series A


AI, also known as artificial intelligence, has not only taken over the objectives of major technology giants such as Google and Microsoft, but also introduced itself to many fields, one of which being the medical field. Several advancements have been made to improve the way medical professionals view patients and their ability to see beyond their own perspective. One such field within medicine that has been primarily transformed is cardiology.

Cardiology is a branch of medicine dealing with all diseases and possible abnormalities found within the heart. For a medical professional, it can be viewed as a stressful occupation dependent on making the right diagnosis at the right time while a patient may view it as one of “the most unsettling moments” of their life hoping to receive the right treatment. But what if the pressure and uncertainty of cardiologists could be reduced? This is where artificial intelligence comes into play. Common medical devices such as ECGs to CT scans can be used to an extent beyond the capability of the human mind. With artificial intelligence, it can capture invaluable data with concepts such as machine learning geared to develop more accurate diagnostics as it receives more data. This not only improves the ability to which clinicians can understand the results of a test, but improve overall patient care: the most critical aspect of medicine. There are several examples by which artificial intelligence aids cardiologists.

If a patient is found with heart palpitations, chest pain or any other cardiac symptoms, an accurate diagnosis with respect to time is of the essence. Although technologies such as portable ultrasounds output results and observations, it is the smart use of data generated that allows for a significant decrease in uncertainty than before. Artificial intelligence is able to automate such measurements and interpretations complexifying the data to reveal much more beyond the human mind. For instance, a 3D CT angiography can show coronary stenosis and a cardiac MRI can show the downstream effect. By implementing artificial intelligence, it can interpret both results in relation to each other to develop a diagnosis and allow cardiologists to understand the patient beyond their own intuition. Not only does artificial intelligence play an important role in interpretation of results, but also in treatment.

After the diagnosis of the patient, there must be a treatment plan optimized to efficiency of time and risk tailored to the patient itself. Artificial intelligence showcases its true power of precision when subject to the cases of patients affected by disease. For instance, through guided imaging solutions such as X-ray, AI is able to explore all possible procedures from minimally invasive to complex methods. Moreover, it even allows clinicians to understand the full perspective of the procedure and determine the best possible tools to use. Yet, AI proves to be helpful beyond the operation room.

With AI, it can reduce clinician and patient exposure to radiation while still obtaining an optimal image quality. Not only has it contributed to safety, but AI has allowed for a better understanding of patient flow and issue real-time notifications so clinicians can prioritize which patients need their attention. With the cardiology department constantly going through issues throughout a day, AI can help reduce this and ease the stress at which the clinicians go through.

Although many fear that artificial intelligence may replace clinicians entirely, this is merely a misconception by which clinicians rather can use artificial intelligence to improve their own view of a patient. Not only does this improve access to quality care, but it also gives those in the field of medicine a piece of mind knowing that they are able to consider all possibilities before developing treatment on a patient.

To learn more about the topic, check out the article below.


“Can AI Transform Cardiology?” GE HealthCare, GE, 2 Feb. 2022, http://www.gehealthcare.com/insights/article/can-ai-transform-cardiology?utm_campaign=USC-NU-HCD-CRD-Cardiology-Innovation.

Overview of Alzheimer’s Disease and Novel Treatments Targeting Beta-Amyloid Deposits

Reporter: Sharada Kittur, Research Assistant 1, Synthetic Biology in Drug Discovery

Alzheimer’s disease (AD) is a common type of dementia. People diagnosed with this disease suffer memory loss. Severe forms of the condition prevent the patients from responding to the environment. Alzheimer’s disease patients may also experience difficulty completing basic tasks, decreased or poor judgement as their executive function competence declines. Frequent changes in mood, personality, or behavior. AD is the 7th leading cause of death in the United States, and the 5th leading cause of death for adults aged 65 and over. Unlike cancer and heart disease, whose death rates are declining, the number of people struggling with Alzheimer’s disease is projected to increase in the coming years.  

Currently, there are no cures for the disease. Many of the drugs on the market target only symptoms of the disease. The key mechanism of action (MOA) of AD drugs is inhibiting acetylcholinesterase. Acetylcholinesterase (AChE) is an enzyme that breaks down a neurotransmitter called acetylcholine (Ach), which is an important factor for memory functions. On average, Alzheimer’s disease patients have lower concentrations of acetylcholine. In order to treat this biomarker, scientists found molecules that can inhibit AChE, and reduce the breakdown of acetylcholine, thus improving the memory of patients with Alzheimer’s disease by enabling average levels of Ach. Some examples of AChE inhibitors currently on the market are

  • donepezil,
  • rivastigmine, and
  • galantamine. 

One of the main causes of Alzheimer’s disease is believed to be the buildup of beta-amyloid plaques in the brain. Beta-amyloid is a toxic protein that is normally produced in small amounts in the brain. Then microglia, a type of macrophages in the nervous system, clear out the beta-amyloid deposits. In patients with Alzheimer’s disease, the microglia can’t clear away the beta-amyloid, and this obstructs neural function and attacks neurons. The cause of the microglia’s malfunction is still unknown, but it could be due to a gene called TREM2, that tells the microglia to clear the beta-amyloid proteins. When TREM2 doesn’t function properly, the microglia collects all of the beta-amyloid, but isn’t able to dispose of it. It then releases inflammatory chemicals, which increase the production of the amyloid precursor protein (APP). This also increases the production of β-secretase and γ-secretase, enzymes that form beta-amyloid by breaking down APP. This further exacerbates the problem. 

On July 06, 2023, the Food and Drug Administration (FDA) fully approved Leqembi (lecanemab-irmb) to treat Alzheimer’s disease. Leqembi is a monoclonal antibody that specifically targets beta-amyloid proteins in the brain. It binds to the beta-amyloid proteins and clears them. This is very promising as in placebo-controlled clinical trials, it significantly decreased the beta-amyloid deposits in 18 months, and delayed cognitive decline by 5.3 months. It’s the first beta-amyloid targeting drug that was approved by the FDA as a Traditional Approval. 

Leqembi is not a cure, however. It significantly slows down the mental function deterioration of the patients, but hasn’t been shown to fully maintain it at the current level over time. In addition, Leqembi has many side effects, such as headaches, and presents amyloid-related imaging abnormalities (ARIAs). ARIAs can cause swelling and bleeding in parts of the brain, but they should be temporary for most patients. Severe ARIAs only occur in a very small percentage of patients. 

As researchers make progress in understanding the complex causes of Alzheimer’s disease, new treatments that are developed can help improve the lives of millions of people worldwide. 


“Alzheimer’s Association Welcomes U.S. FDA Traditional Approval of Leqembi: Full Details.” Alzheimer’s Disease and Dementia, Alzheimer’s Association, 6 July 2023, www.alz.org/news/2023/lecanemab-leqembi-traditional-fda-approval-full#:~:text=CHICAGO%2C%20July%206%2C%202023%20%E2%80%94,confirmation%20of%20elevated%20amyloid%20beta.

Smith, Tyler. “How Well Does Leqembi Work to Fight Alzheimer’s? First FDA-Approved Alzheimer’s Drug Offers Both Promise and Challenges.” UCHealth Today, 11 Aug. 2023, www.uchealth.org/today/how-well-does-leqembi-fight-alzheimers-first-fda-approved-alzheimers-drug/

Wang, Shaoxun, et al. “Is Beta-Amyloid Accumulation a Cause or Consequence of Alzheimer’s Disease?” Journal of Alzheimer’s Parkinsonism & Dementia, U.S. National Library of Medicine, 17 Nov. 2016, www.ncbi.nlm.nih.gov/pmc/articles/PMC5555607/

“What Happens to the Brain in Alzheimer’s Disease?” National Institute on Aging, U.S. Department of Health and Human Services, 16 May 2017, www.nia.nih.gov/health/what-happens-brain-alzheimers-disease#:~:text=In%20a%20person%20with%20Alzheimer’s,beta%2Damyloid%20and%20tau%20proteins.

“What Is Alzheimer’s Disease?” Centers for Disease Control and Prevention, Centers for Disease Control and Prevention, 26 Oct. 2020, www.cdc.gov/aging/aginginfo/alzheimers.htm#:~:text=Alzheimer’s%20disease%20is%20the%20most,thought%2C%20memory%2C%20and%20language.


Other related articles published in this Open Access Online Scientific Journal include the following:

Alzheimer’s Disease: Novel Therapeutical Approaches — Articles of Note @PharmaceuticalIntelligence.com

Curators: Larry H. Bernstein, MD, FCAP and Aviva Lev-Ari, PhD, RN


Role of infectious agent in Alzheimer’s Disease?

Alzheimer’s disease, snake venome, amyloid and transthyretin

Alzheimer’s Disease – tau art thou, or amyloid

Breakthrough Prize for Alzheimer’s Disease 2016

Tau and IGF1 in Alzheimer’s Disease

Amyloid and Alzheimer’s Disease

Important Lead in Alzheimer’s Disease Model

BWH Researchers: Genetic Variations can Influence Immune Cell Function: Risk Factors for Alzheimer’s Disease,DM, and MS later in life

BACE1 Inhibition role played in the underlying Pathology of Alzheimer’s Disease

Late Onset of Alzheimer’s Disease and One-carbon Metabolism

Alzheimer’s Disease Conundrum – Are We Near the End of the Puzzle?

Ustekinumab New Drug Therapy for Cognitive Decline resulting from Neuroinflammatory Cytokine Signaling and Alzheimer’s Disease

New Alzheimer’s Protein – AICD

Developer of Alzheimer’s drug Exelon at Hebrew University’s School of Pharmacy: Israel Prize in Medicine awarded to Prof. Marta Weinstock-Rosin

TyrNovo’s Novel and Unique Compound, named NT219, selectively Inhibits the process of Aging and Neurodegenerative Diseases, without affecting Lifespan

@NIH – Discovery of Causal Gene Mutation Responsible for two Dissimilar Neurological diseases: Amyotrophic Lateral Sclerosis (ALS) and Frontotemporal Dementia (FTD)

Introduction to Nanotechnology and Alzheimer disease

Genomic Promise for Neurodegenerative Diseases, Dementias, Autism Spectrum, Schizophrenia, and Serious Depression

New ADNI Project to Perform Whole-genome Sequencing of Alzheimer’s Patients,

Brain Biobank

Removing Alzheimer plaques

Tracking protein expression

Schizophrenia genomics

Breakup of amyloid plaques

Mindful Discoveries

Beyond tau and amyloid

Serum Folate and Homocysteine, Mood Disorders, and Aging

Long Term Memory and Prions

Retromer in neurological disorders

Neurovascular pathways to neurodegeneration

Studying Alzheimer’s biomarkers in Down syndrome

Amyloid-Targeting Immunotherapy Targeting Neuropathologies with GSK33 Inhibitor

Brain Science

Sleep quality, amyloid and cognitive decline

microglia and brain maintenance

Notable Papers in Neurosciences

New Molecules to reduce Alzheimer’s and Dementia risk in Diabetic patients

The Alzheimer Scene around the Web

MRI Cortical Thickness Biomarker Predicts AD-like CSF and Cognitive Decline in Normal Adults



  • Alzheimer’s disease
  • microglia
  • gliosis
  • neurodegeneration
  • inflammation


The Implications and Association of Stair Climbing with Atherosclerotic Cardiovascular Disease (ASCVD)

Reporter: Arav Gandhi, Research Assistant 2, Domain Content: Cardiovascular Diseases, Series A


Atherosclerotic Cardiovascular Disease (ASCVD) is a condition in which cholesterol builds up in the arteries to an extent that develops long-term complications for other areas of the body and in some cases emergence of symptoms such as chest pain, dizziness, and shortness of breath are presented and reported to PCPs. This can cause a strain on daily activities such as walking and especially may be noticed when climbing stairs which represents a form of exertion related to elevation. To further understand the significance of ASCVD upon daily activities, Zimin Song et al. (2023), using a sample of 458,860 participants (55.9% female) from the UK Biobank, aimed to evaluate the intensity of stair climbing and the present risk of ASCVD. All participants had a history of ASCVD, put at risk for ASCVD, or had a recorded levels of genetic risk.

Prior to the study, all participants underwent blood tests and other necessary measurements. During the study, the researchers assessed the intensity of stair climbing through a self-reported structure in which participants were asked a set of questions addressing the duration of climbing stairs and whether they continued to climb. Additional questionnaires were administered to collect sociodemographic characteristics, lifestyle factors, and health status. Following the conclusion of the study, the researchers found, with an application of statistical analysis, that over a period of 12.5 years individuals with a higher intensity of stair climbing were of younger age, female, and non-regular smokers. Moreover, those individuals exemplified a higher level of education and income along with healthier dietary habits and prolonged exercise durations. Beyond demographic characteristics, researchers found that when individuals especially those with a family history of ASCVD increased the intensity of stair climbing, the risk of ASCVD was reduced. This remained consistent across other groups of participants finding an association between the intensity of stair climbing and the risk of ASCVD.

Ultimately, given the large sample of UK adults, the findings conclude that high-intensity climbing, or climbing more than five flights of stairs daily was associated with over a 20% reduction in risk of obtaining ASCVD. Despite the variance of disease tendencies among individuals, active engagement in stair climbing can significantly reduce the risk of ASCVD in contrast to those who discontinued stair climbing leading to a higher risk of ASCVD. However, the intensity of stair climbing was limited to a threshold in which it no longer decreased the risk of ASCVD.

Simply climbing stairs can be considered a prevention strategy for ASCVD, but the application of active engagement in physical activities may be associated with reducing the risk of obtaining other diseases. For instance, the positive effects of stair climbing on reducing the risk of ASCVD may also apply to

  • atrial fibrillation,
  • diabetes, and
  • hypertension.

Other existing studies find associations with a

  • lower risk of metabolic syndrome, and even
  • mortality.

In contrast to structured sports and exercise, stair climbing proves to be an effective method with minimal equipment and low cost that allows an individual to practice cardiorespiratory fitness reducing the risks of various diseases while improving their overall standard of life. Although further studies need to be conducted on the extent to which intense stair climbing improves different areas of the body and what diseases it helps prevent, current studies prove the effects of stair climbing to be beneficial to an extent in which individuals should be encouraged in incorporate it in their daily routine yielding both short-term and long-term benefits.

To learn more about the topic, check out the article below.


Song Z, Wan L, Wang W, et al. Daily stair climbing, disease susceptibility, and risk of atherosclerotic cardiovascular disease: A prospective cohort study. Atherosclerosis. 2023:117300. doi: 10.1016/j.atherosclerosis.2023.117300


Other related articles published in this Open Access Online Scientific Journal include the following:

Archive for the ‘Atherogenic Processes & Pathology’ Category

N =178 articles

Series A: e-Books on Cardiovascular Diseases

Series A Content Consultant: Justin D Pearlman, MD, PhD, FACC



Etiologies of Cardiovascular Diseases:

Epigenetics, Genetics and Genomics





Larry H Bernstein, MD, FCAP, Senior Editor, Author and Curator


Aviva Lev-Ari, PhD, RN, Editor and Curator


2.1.3 Physical Activity and Prevention of Cardiovascular Diseases

  • Causes
  • Biomarkrs
  • Therapies  In Two-thirds of Waking Hours Older Women are Sedentary

Aviva Lev-Ari, PhD, RN Walking and Running: Similar Risk Reductions for Hypertension, Hypercholesterolemia, DM, and possibly CAD

Aviva Lev-Ari, PhD, RN Cardiac Arrhythmias: A Risk for Extreme Performance Athletes

Aviva Lev-Ari, PhD, RN Preventive Medicine Philosophy: Exercise vs. Drug, IF More of the First THEN Less of the Second

Aviva Lev-Ari, PhD, RN Heart Rate Variability (HRV) as a Tool

Larry H. Bernstein, MD, FCAP   Is it Hypertension or Physical Inactivity: Cardiovascular Risk and Mortality – New results in 3/2013

Aviva Lev-Ari, PhD, RN  2014 Epidemiology and Prevention, Nutrition, Physical Activity and Metabolism Conference: San Francisco, Ca.   Conference Dates:  San Francisco, CA 3/18-21, 2014

Aviva Lev-Ari, PhD, RN

The Nobel Prize in Physiology or Medicine 2023, jointly to Katalin Karikó and Drew Weissman for their discoveries concerning nucleoside base modifications that enabled the development of effective mRNA vaccines against COVID-19

Reporter: Aviva Lev-Ari, PhD, RN

The breakthrough

Karikó and Weissman noticed that dendritic cells recognize in vitro transcribed mRNA as a foreign substance, which leads to their activation and the release of inflammatory signaling molecules. They wondered why the in vitro transcribed mRNA was recognized as foreign while mRNA from mammalian cells did not give rise to the same reaction. Karikó and Weissman realized that some critical properties must distinguish the different types of mRNA.

RNA contains four bases, abbreviated A, U, G, and C, corresponding to A, T, G, and C in DNA, the letters of the genetic code. Karikó and Weissman knew that bases in RNA from mammalian cells are frequently chemically modified, while in vitro transcribed mRNA is not. They wondered if the absence of altered bases in the in vitro transcribed RNA could explain the unwanted inflammatory reaction. To investigate this, they produced different variants of mRNA, each with unique chemical alterations in their bases, which they delivered to dendritic cells. The results were striking: The inflammatory response was almost abolished when base modifications were included in the mRNA. This was a paradigm change in our understanding of how cells recognize and respond to different forms of mRNA. Karikó and Weissman immediately understood that their discovery had profound significance for using mRNA as therapy. These seminal results were published in 2005, fifteen years before the COVID-19 pandemic.



Other Nobel Prize Winners included in this category of research include N = 21

Archive for the ‘Nobel Prize Winners’ Category


See other Interviews with Scientific Leaders: N=302



The Current Impact and Future of Technology within Cardiovascular Surgery

Reporter: Arav Gandhi, Research Assistant 2, Domain Content: Cardiovascular Diseases, Series A


Medical professionals have been able to explore new methods and strategies to tackle complex medical conditions, especially with the limitations of other pre-existing conditions. For instance, through recent cardiology advancements, if the patient requires a heart transplant due to heart failure disease and is unable to undergo a human donor heart transplant as a result of pre-existing disease conditions or existing internal bleeding complications, there is a greater alternative to leaving it untreated. Medical professionals developed alternatives to humman donor transplants. One such a solution is transplanting a genetically modified pig heart, a new advanced experimental procedure that has been used over recent cases. Researchers continue to develop solutions that not only presents an alternative to current methods but also continue to maximize the potential of medical devices technology and of our understanding of medicine.

Recently, cardiologists at Henry Ford Health Hospital found themselves as the first physicians in the United States to employ an investigational device to treat a patient with severe tricuspid regurgitation. Having never been experimented upon prior to the situation, the K-Clip Transvascular Tricuspid Repair System utilizes a corkscrew anchor, which then clips the ring-shaped region of the valve. Similar to most dire situations where new technology is used, the patient, an 85-year-old male, continued to experience worsening symptoms for an entire year. His tricuspid valve, key in ensuring blood flow to the right ventricle and then to the pulmonary valve, was enlarged from his condition, resulting in the mass of his heart tripling in size. Cardiologists were then prompted to either utilize the new procedure or go untreated. With optimism, the cardiologists selected the procedure and applied a unique approach of an incision through the neck to reduce further risks of opening the chest and placed the device using real-time 3D imaging and 4D modeling. The medical professionals followed a minimally invasive procedure through the neck in contrast to traditional open-heart surgery and effectively employed recent advancements in imaging and modeling to ensure precision when planting the device, a new artificial tricuspid valve. The patient was later reported to have experience improve in the valve condition and a significant decrease in leakage, along with an improvement in his overall quality of life. 

As a result, researchers should continue to focus not only on understanding undiscovered diseases and complications but also on developing alternative solutions to resolve cases in which the best practice approach can not be applied.

With the advancements in technology, the true extent of its application can not be discovered without experimentation and the application of imaging and other devices to resolve certain conditions. Beyond the technology itself, the introduction of new methods allows for less costly treatment plans, aiding especially those who come from a low-income background and currently struggle to afford basic healthcare. In the united States they are covered by MedicAid at all ages and by Medicare at age 65 and beyond. This is not the case in many countries in the World excluding Europe. The overall development of the field of medicine through advancement of medical technologies can indirectly allow for a improvement to the overall Global health care delivery and ascertain an increased life expectancies. This is primarily true, chiefly, in developing countries where established surgeries to resolve complex medical conditions still have the ability to achieve life-changing quality of life and longevity.

To learn more about the topic, check out the article below.


Walter, Michael. “Cardiologists Use New Annular Clipping Device for First Time in Us to Treat Severe Tricuspid Regurgitation.” Cardiovascular Business, Innovate Healthcare, 15 Sept. 2023, cardiovascularbusiness.com/topics/clinical/interventional-cardiology/cardiologists-severe-tricuspid-regurgitation-valve-k-clip?utm_source=newsletter

Other related articles on tricuspid valve procedures published in this Open Access Online Journal, include the following:

Volume Six: Interventional Cardiology for Disease Diagnosis and Cardiac Surgery for Condition Treatment


On Amazon.com since 12/24/2018

Chapter 13: Valve Replacement, Valve Implantation and Valve Repair


The Voice of Series A Content Consultant: Justin D. Pearlman, MD, PhD, FACC

As catheter techniques evolved to compete with bypass surgery they progressed from balloon cracking of obstructive lesions (POBA=plain old balloon angioplasty) to placement of stents (wire fences). Surgeons sometimes use in-stent valves, and now devices analogous to in-stent valves can be placed by catheter for valve replacement in patients with too much co-morbidity to go through heart surgery. Aortic valve replacement by stent (TAVR) has had sufficient success to be considered for all patients who have sufficient impairment to merit intervention. The diameter is large, so a vascular surgeon participates in the arterial access and repair of the access site.

13.5   Tricuspid Valve

13.5.1 First-in-Man Mitral Valve Repairs Device used for Tricuspid Valve Repair: Cardioband used by University Hospital Zurich Heart Team

Reporter: Aviva Lev-Ari, PhD, RN



13.5.2 Advances and Future Directions for Transcatheter Valves – Mitral and Tricuspid valve repair technologies now in development

Reporter: Aviva Lev-Ari, PhD, RN



Volume Six: Interventional Cardiology for Disease Diagnosis and Cardiac Surgery for Condition Treatment

The Continued Impact and Possibilities of AI in Medical and Pharmaceutical Industry Practices

Reporter: Adam P. Tubman, MSc Biotechnology, Research Associate 3, Computer Graphics and AI in Drug Discovery


Researchers have been able to discover many ways to incorporate AI into the practices of healthcare, both in terms of medical healthcare and also in pharmaceutical drug development. For example, given the situation where a doctor provides an inaccurate diagnosis to a patient because the doctor had an incomplete or inaccurate medical record/history, AI presents a solution that has the potential to rapidly and correctly account for human error and predict the correct diagnosis based on the patterns identified in other patient’s medical history to disease diagnosis indication. In the pharmaceutical industry, companies are changing and expanding approaches to drug discovery and development given the possibilities that AI can offer. One company, Reverie Labs, located in Cambridge, MA, is a pharmaceutical company utilizing AI for application of machine learning and computational chemistry to discover new possible compounds to be used in the development of cancer treatments.

Today, AI uses have had many other applications in medicine including managing healthcare data and performing robotic surgery, both of which transform the in-person patient and doctor experience. AI has even been used to change in-person cancer patient experiences. For example, Freenome, a company in San Francisco, CA uses AI in initial screenings, blood tests and diagnostic tests when a patient is being initially tested for cancer. The hope is that this technology will aide in speeding up cancer diagnoses and lead to new treatment developments.

The future will continue to bring many possibilities of AI, provided an acceptable level of accuracy is still maintained by AI technologies and that the technology remains beneficial. If research continues to focus on diagnosing diseases at a faster rate given the potential human errors in having an inaccurate or incomplete medical record upon diagnosis, AI could provide an improved experience for patients given the quicker diagnosis and treatment combined with less time spent either treating the wrong underlying condition or not knowing what condition to treat when accounting for an incomplete medical record. If this technology is proven to be successful not just in theory, but in practice, technology would then be available and could be beneficially applied to all diagnoses and treatment plans, across the world.

However, the reality regarding AI development is that its evolution depends on how much human effort is involved in its development. Therefore, the world won’t know or see the full benefits of AI until it is developed and actively applied. Similarly, the impact that AI will have in medical and pharmaceutical practices won’t be known until scientists fully develop and apply the technologies. Many possibilities, including a possible drastic lowering of the cost for pharmaceutical drugs across the board once drugs are much more readily discovered and produced, may carry a profound benefit to patients who currently struggle to afford their own treatment plans. Additionally, unforeseen advances in the medicinal and pharmaceutical fields because of AI development will lead to unforeseen effects on the global economy and many other life changing variables for the entire world.

For more information on this topic, please check out the article below.


Daley, S. (2018). Artificial Intelligence in healthcare: 39 examples Improving the Future of Medicine. Built In. https://builtin.com/artificial-intelligence/artificial-intelligence-healthcare

Regulatory T cells (Tregs) are important for sperm tolerance and male fertility

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

Regulatory T cells (Tregs) are specialized immune cells that modulate tissue homeostasis. They are a specialized subset of T lymphocytes that function as suppressive immune cells and inhibit various elements of immune response in vitro and in vivo. While there are constraints on the number or function of Tregs which can be exploited to evoke an effective anti-tumor response, sufficient expansion of Tregs is essential for successful organ transplantation and for promoting tolerance of self and foreign antigens. Current studies have provided evidence that a defect in the number or function of Tregs contributes to the etiology of several reproductive diseases.

In the male reproductive tract, prevention of autoimmune responses against antigenic spermatozoa, while ensuring protection against stressors, is a key determinant of fertility. Using an autoimmunity-induced model, it was uncovered that the role of Tregs in maintaining the tolerogenic state of the testis and epididymis. The loss of tolerance induced an exacerbated immune cell infiltration and the development of anti-sperm antibodies, which caused severe male subfertility. By identifying immunoregulatory mechanisms in the testis and epididymis.

Tregs modulate tissue homeostatic processes and immune responses. Understanding tissue-Treg biology will contribute to developing precision-targeting treatment strategies. Here, it was reported that Tregs maintain the tolerogenic state of the testis and epididymis, where sperm are produced and mature. It was found that Treg depletion induces severe autoimmune orchitis and epididymitis, manifested by an exacerbated immune cell infiltration [CD4 T cells, monocytes, and mononuclear phagocytes (MPs)] and the development of anti-sperm antibodies (ASA).

In Treg-depleted mice, MPs increased projections toward the epididymal lumen as well as invading the lumen. ASA-bound sperm enhance sperm agglutination and might facilitate sperm phagocytosis. Tolerance breakdown impaired epididymal epithelial function and altered extracellular vesicle cargo, both of which play crucial roles in the acquisition of sperm fertilizing ability and subsequent embryo development. The affected mice had reduced sperm number and motility and severe fertility defects.

Deciphering these immunoregulatory mechanisms may lead to the development of therapies for infertility and identifying potential targets for immuno-contraception. Ultimately, such knowledge fills gaps related to reproductive mucosa, which is an understudied facet of human male health.







ChatGPT Chemistry Assistant for Text Mining and the Prediction of MOF Synthesis

Reporter: Aviva Lev-Ari, PhD, RN

ChatGPT Chemistry Assistant for Text Mining and the Prediction of MOF Synthesis

  • Zhiling Zheng
  • Oufan Zhang
  • Christian Borgs
  • Jennifer T. Chayes
  • Omar M. Yaghi*

Cite this: J. Am. Chem. Soc. 2023, 145, 32, 18048–18062 Publication Date:August 7, 2023 https://doi.org/10.1021/jacs.3c05819 Copyright © 2022 American Chemical Society. This publication is licensed under these Terms of Use.https://pubs.acs.org/doi/10.1021/jacs.3c05819



We use prompt engineering to guide ChatGPT in the automation of text mining of metal–organic framework (MOF) synthesis conditions from diverse formats and styles of the scientific literature. This effectively mitigates ChatGPT’s tendency to hallucinate information, an issue that previously made the use of large language models (LLMs) in scientific fields challenging. Our approach involves the development of a workflow implementing three different processes for text mining, programmed by ChatGPT itself. All of them enable parsing, searching, filtering, classification, summarization, and data unification with different trade-offs among labor, speed, and accuracy. We deploy this system to extract 26 257 distinct synthesis parameters pertaining to approximately 800 MOFs sourced from peer-reviewed research articles. This process incorporates our ChemPrompt Engineering strategy to instruct ChatGPT in text mining, resulting in impressive precision, recall, and F1 scores of 90–99%. Furthermore, with the data set built by text mining, we constructed a machine-learning model with over 87% accuracy in predicting MOF experimental crystallization outcomes and preliminarily identifying important factors in MOF crystallization. We also developed a reliable data-grounded MOF chatbot to answer questions about chemical reactions and synthesis procedures. Given that the process of using ChatGPT reliably mines and tabulates diverse MOF synthesis information in a unified format while using only narrative language requiring no coding expertise, we anticipate that our ChatGPT Chemistry Assistant will be very useful across various other chemistry subdisciplines.

This publication is licensed for personal use by The American Chemical Society.

Concluding Remarks

Our research has successfully demonstrated the potential of LLMs, particularly GPT models, in the domain of chemistry research. We presented a ChatGPT Chemistry Assistant that includes three different but connected approaches to text mining with ChemPrompt Engineering: Process 3 is capable of conducting search and filtration, Processes 2 and 3 classify synthesis paragraphs, and Processes 1, 2, and 3 are capable of summarizing synthesis conditions into structured data sets. Enhanced by three fundamental principles of prompt engineering specific to chemistry text processing, coupled with the interactive prompt refinement strategy, the ChatGPT-based assistant has substantially advanced the extraction and analysis of the MOF synthesis literature, with precision, recall, and F1 scores exceeding 90%.
We elucidated two crucial insights from the data set of synthesis conditions. First, the data can be employed to construct predictive models for reaction outcomes, which shed light on the key experimental factors that influence the MOF crystallization process. Second, it is possible to create an MOF chatbot that can provide accurate answers based on text mining, thereby improving access to the synthesis data set and achieving a data-to-dialogue transition. This investigation illustrates the potential for rapid advancement inherent in ChatGPT and other LLMs as a proof of concept.
On a fundamental level, this study provides guidance on interacting with LLMs to serve as AI assistants for chemists, accelerating research with minimal prerequisite coding expertise and thus bridging the gap between chemistry and the realms of computational and data science more effectively. Through interaction and chatting, the code and design of experiments can be modified, democratizing data mining and enhancing the landscape of scientific research. Our work sets a foundation for further exploration and application of LLMs across various scientific domains, paving the way for a new era of AI-assisted chemistry research.



ChatGPT accelerates chemistry discovery for climate response, study shows

Yaghi said. “AI has transformed many other sectors of our society – commerce, banking, travel. Why not transform science?”
These datasets on the synergy of the highly-porous materials known as metal-organic frameworks (MOFs) will inform predictive models. The models will accelerate chemists’ ability to create or optimize MOFs, including ones that alleviate water scarcity and capture air pollution. All chemists – not just coders – can build these databases due to the use of AI-fueled chatbots.

To help them teach ChatGPT to generate accurate and relevant information, they modified an approach called “prompt engineering” into “ChemPrompt Engineering.” They developed prompts that avoided asking ChatGPT for made up or misleading content; laid out detailed directions that explained to the chatbot the context and format for the response; and provided the large language model a template or instructions for extracting data.

The chatbot’s literature review – and the experts’ approach – was successful. ChatGPT finished in a fraction of an hour what would have taken a student years to complete, said Borgs, BIDMaP’s director. It mined the synthetic conditions of MOFs with 95% accuracy, Yaghi said.

Eight Subcellular Pathologies driving Chronic Metabolic Diseases – Methods for Mapping Bioelectronic Adjustable Measurements as potential new Therapeutics: Impact on Pharmaceuticals in Use



THE VOICE of Aviva Lev-Ari, PhD, RN

In this curation we wish to present two breaking through goals:

Goal 1:

Exposition of a new direction of research leading to a more comprehensive understanding of Metabolic Dysfunctional Diseases that are implicated in effecting the emergence of the two leading causes of human mortality in the World in 2023: (a) Cardiovascular Diseases, and (b) Cancer

Goal 2:

Development of Methods for Mapping Bioelectronic Adjustable Measurements as potential new Therapeutics for these eight subcellular causes of chronic metabolic diseases. It is anticipated that it will have a potential impact on the future of Pharmaceuticals to be used, a change from the present time current treatment protocols for Metabolic Dysfunctional Diseases.

According to Dr. Robert Lustig, M.D, an American pediatric endocrinologist. He is Professor emeritus of Pediatrics in the Division of Endocrinology at the University of California, San Francisco, where he specialized in neuroendocrinology and childhood obesity, there are eight subcellular pathologies that drive chronic metabolic diseases.

These eight subcellular pathologies can’t be measured at present time.

In this curation we will attempt to explore methods of measurement for each of these eight pathologies by harnessing the promise of the emerging field known as Bioelectronics.

Unmeasurable eight subcellular pathologies that drive chronic metabolic diseases

  1. Glycation
  2. Oxidative Stress
  3. Mitochondrial dysfunction [beta-oxidation Ac CoA malonyl fatty acid]
  4. Insulin resistance/sensitive [more important than BMI], known as a driver to cancer development
  5. Membrane instability
  6. Inflammation in the gut [mucin layer and tight junctions]
  7. Epigenetics/Methylation
  8. Autophagy [AMPKbeta1 improvement in health span]

Diseases that are not Diseases: no drugs for them, only diet modification will help

Image source

Robert Lustig, M.D. on the Subcellular Processes That Belie Chronic Disease



Exercise will not undo Unhealthy Diet

Image source

Robert Lustig, M.D. on the Subcellular Processes That Belie Chronic Disease



These eight Subcellular Pathologies driving Chronic Metabolic Diseases are becoming our focus for exploration of the promise of Bioelectronics for two pursuits:

  1. Will Bioelectronics be deemed helpful in measurement of each of the eight pathological processes that underlie and that drive the chronic metabolic syndrome(s) and disease(s)?
  2. IF we will be able to suggest new measurements to currently unmeasurable health harming processes THEN we will attempt to conceptualize new therapeutic targets and new modalities for therapeutics delivery – WE ARE HOPEFUL

In the Bioelecronics domain we are inspired by the work of the following three research sources:

  1. Biological and Biomedical Electrical Engineering (B2E2) at Cornell University, School of Engineering https://www.engineering.cornell.edu/bio-electrical-engineering-0
  2. Bioelectronics Group at MIT https://bioelectronics.mit.edu/
  3. The work of Michael Levin @Tufts, The Levin Lab
Michael Levin is an American developmental and synthetic biologist at Tufts University, where he is the Vannevar Bush Distinguished Professor. Levin is a director of the Allen Discovery Center at Tufts University and Tufts Center for Regenerative and Developmental Biology. Wikipedia
Born: 1969 (age 54 years), Moscow, Russia
Education: Harvard University (1992–1996), Tufts University (1988–1992)
Affiliation: University of Cape Town
Research interests: Allergy, Immunology, Cross Cultural Communication
Awards: Cozzarelli prize (2020)
Doctoral advisor: Clifford Tabin
Most recent 20 Publications by Michael Levin, PhD
The nonlinearity of regulation in biological networks
1 Dec 2023npj Systems Biology and Applications9(1)
Co-authorsManicka S, Johnson K, Levin M
Toward an ethics of autopoietic technology: Stress, care, and intelligence
1 Sep 2023BioSystems231
Co-authorsWitkowski O, Doctor T, Solomonova E
Closing the Loop on Morphogenesis: A Mathematical Model of Morphogenesis by Closed-Loop Reaction-Diffusion
14 Aug 2023Frontiers in Cell and Developmental Biology11:1087650
Co-authorsGrodstein J, McMillen P, Levin M
30 Jul 2023Biochim Biophys Acta Gen Subj1867(10):130440
Co-authorsCervera J, Levin M, Mafe S
Regulative development as a model for origin of life and artificial life studies
1 Jul 2023BioSystems229
Co-authorsFields C, Levin M
The Yin and Yang of Breast Cancer: Ion Channels as Determinants of Left–Right Functional Differences
1 Jul 2023International Journal of Molecular Sciences24(13)
Co-authorsMasuelli S, Real S, McMillen P
Bioelectricidad en agregados multicelulares de células no excitables- modelos biofísicos
Jun 2023Revista Española de Física32(2)
Co-authorsCervera J, Levin M, Mafé S
Bioelectricity: A Multifaceted Discipline, and a Multifaceted Issue!
1 Jun 2023Bioelectricity5(2):75
Co-authorsDjamgoz MBA, Levin M
Control Flow in Active Inference Systems – Part I: Classical and Quantum Formulations of Active Inference
1 Jun 2023IEEE Transactions on Molecular, Biological, and Multi-Scale Communications9(2):235-245
Co-authorsFields C, Fabrocini F, Friston K
Control Flow in Active Inference Systems – Part II: Tensor Networks as General Models of Control Flow
1 Jun 2023IEEE Transactions on Molecular, Biological, and Multi-Scale Communications9(2):246-256
Co-authorsFields C, Fabrocini F, Friston K
Darwin’s agential materials: evolutionary implications of multiscale competency in developmental biology
1 Jun 2023Cellular and Molecular Life Sciences80(6)
Co-authorsLevin M
Morphoceuticals: Perspectives for discovery of drugs targeting anatomical control mechanisms in regenerative medicine, cancer and aging
1 Jun 2023Drug Discovery Today28(6)
Co-authorsPio-Lopez L, Levin M
Cellular signaling pathways as plastic, proto-cognitive systems: Implications for biomedicine
12 May 2023Patterns4(5)
Co-authorsMathews J, Chang A, Devlin L
Making and breaking symmetries in mind and life
14 Apr 2023Interface Focus13(3)
Co-authorsSafron A, Sakthivadivel DAR, Sheikhbahaee Z
The scaling of goals from cellular to anatomical homeostasis: an evolutionary simulation, experiment and analysis
14 Apr 2023Interface Focus13(3)
Co-authorsPio-Lopez L, Bischof J, LaPalme JV
The collective intelligence of evolution and development
Apr 2023Collective Intelligence2(2):263391372311683SAGE Publications
Co-authorsWatson R, Levin M
Bioelectricity of non-excitable cells and multicellular pattern memories: Biophysical modeling
13 Mar 2023Physics Reports1004:1-31
Co-authorsCervera J, Levin M, Mafe S
There’s Plenty of Room Right Here: Biological Systems as Evolved, Overloaded, Multi-Scale Machines
1 Mar 2023Biomimetics8(1)
Co-authorsBongard J, Levin M
Transplantation of fragments from different planaria: A bioelectrical model for head regeneration
7 Feb 2023Journal of Theoretical Biology558
Co-authorsCervera J, Manzanares JA, Levin M
Bioelectric networks: the cognitive glue enabling evolutionary scaling from physiology to mind
1 Jan 2023Animal Cognition
Co-authorsLevin M
Biological Robots: Perspectives on an Emerging Interdisciplinary Field
1 Jan 2023Soft Robotics
Co-authorsBlackiston D, Kriegman S, Bongard J
Cellular Competency during Development Alters Evolutionary Dynamics in an Artificial Embryogeny Model
1 Jan 2023Entropy25(1)
Co-authorsShreesha L, Levin M

5 total citations on Dimensions.

Article has an altmetric score of 16
Co-authorsClawson WP, Levin M
Future medicine: from molecular pathways to the collective intelligence of the body
1 Jan 2023Trends in Molecular Medicine
Co-authorsLagasse E, Levin M

THE VOICE of Dr. Justin D. Pearlman, MD, PhD, FACC


THE VOICE of  Stephen J. Williams, PhD

Ten TakeAway Points of Dr. Lustig’s talk on role of diet on the incidence of Type II Diabetes


  1. 25% of US children have fatty liver
  2. Type II diabetes can be manifested from fatty live with 151 million  people worldwide affected moving up to 568 million in 7 years
  3. A common myth is diabetes due to overweight condition driving the metabolic disease
  4. There is a trend of ‘lean’ diabetes or diabetes in lean people, therefore body mass index not a reliable biomarker for risk for diabetes
  5. Thirty percent of ‘obese’ people just have high subcutaneous fat.  the visceral fat is more problematic
  6. there are people who are ‘fat’ but insulin sensitive while have growth hormone receptor defects.  Points to other issues related to metabolic state other than insulin and potentially the insulin like growth factors
  7. At any BMI some patients are insulin sensitive while some resistant
  8. Visceral fat accumulation may be more due to chronic stress condition
  9. Fructose can decrease liver mitochondrial function
  10. A methionine and choline deficient diet can lead to rapid NASH development


ChatGPT Searches and Advent of Meta Threads: What it Means for Social Media and Science 3.0

Curator: Stephen J. Williams, PhD

The following explains how popular ChatGPT has become and how the latest social media platforms, including Meta’s (FaceBook) new platform Threads, is becoming as popular or more popular than older social Platforms.  In fact, since its short inception since last week (Threads launced 7/07/2023), Threads is threatening Twitter for dominance in that market.

The following is taken from an email from Charlie Downing Jones from journoreasearch.org and  https://www.digital-adoption.com/ :

U.S. searches for ChatGPT overtake TikTok, Pinterest, and Zoom

  • Google searches for ChatGPT have overtaken TikTok in the U.S., jumping to 7.1 million monthly searches compared to 5.1 million
  • The term ‘ChatGPT’ is now one of the top 100 search terms in the U.S., ranking 92nd, according to Ahrefs data
  • ChatGPT is now searched more than most major social networks, including LinkedIn, Pinterest, TikTok, and Reddit

Analysis of Google search data reveals that online searches for ChatGPT, the popular AI chatbot, have overtaken most popular social networks in the U.S. This comes when search interest in artificial intelligence is at its highest point in history.


The findings by Digital-adoption.com reveal that US-based searches for ChatGPT have exploded and overtaken popular social networks, such as LinkedIn, Pinterest, and Tiktok, some by millions.


Ranking Keyword US Search Volume (Monthly)
1 Facebook                                  70,920,000
2 YouTube                                  69,260,000
3 Twitter                                  15,440,000
4 Instagram                                  12,240,000
5 ChatGPT                                  7,130,000
6 LinkedIn                                  6,990,000
7 Pinterest                                  5,790,000
8 TikTok                                  5,130,000
9 Reddit                                  4,060,000
10 Snapchat                                  1,280,000
11 WhatsApp                                  936,000


Since its release in November 2022, searches for ChatGPT have overtaken those of most major social networks. According to the latest June search figures by search tool Ahrefs, searches for ‘ChatGPT’ and ‘Chat GPT’ are made 7,130,000 times monthly in the U.S.

That’s more than the monthly search volume for most of the top ten social networks, including LinkedIn, Pinterest, and TikTok. TikTok is one of the largest growing social media apps, with 100 million users in just a year.























The term ‘ChatGPT’ is now one of the top 100 search terms in the U.S., ranking 92nd, according to Ahrefs data


Searches for ChatGPT have eclipsed other major networks in the U.S., such as Reddit, by millions.

Every day search terms such as ‘maps’ and ‘flights’ have even seen their search volumes pale compared to the rising popularity of ChatGPT. ‘Maps’ is currently searched 440,000 times less than the chatbot each month, and ‘Flights’ is now Googled 2.2 million times less.

2023 has been a breakout year for AI, as searches for the term have more than doubled from 17 million in January 2023 to 42 million in May. In comparison, there were 7.9 million searches in January 2022. There has been an 825% increase in searches for ‘AI’ in the US compared to the average over the last five years.

There is a correlation between the uptick and the public releases of accessible AI chatbots such as ChatGPT, released on November 30, 2022, and Bing AI and Google Bard, released in May 2023.

According to TikTok data, interest in artificial intelligence has soared tenfold since 2020, and virtual reality has more than tripled.

AI has been a big topic of conversation this year as accessible AI chatbots and new technologies were released and sparked rapid adoption, prompting tech leaders like Elon Musk to call for AI regulation.

A spokesperson from Digital-adoption.com commented on the findings: “There has been a massive surge in AI interest this year. Apple’s announcement of Vision Pro has captured audiences at the right time, when new AI technologies, like ChatGPT, have become accessible to almost anyone. The rapid adoption of ChatGPT is surprising, with it becoming one of the fastest-growing tools available”.

All data was gathered from Ahrefs and Google Trends.

If using this story, please include a link to https://www.digital-adoption.com/ who conducted this study. A linked credit allows us to keep supplying you with content that you may find useful in the future.


If you need anything else, please get in touch.

All the best,
Charlie Dowling-Jones




Journo Research

Part of Search Intelligence Ltd. Company registered in England No. 09361526

Why LPBI Needs to consider the new Meta Threads Platform

From Barrons

Threads Hits 100 Million Users Faster Than ChatGPT. Now It Needs Them to Stay.



Adam ClarkFollow

Updated July 10, 2023 9:00 am ET / Original July 10, 2023 7:44 am ET

The launch of Meta Platforms’ Threads looks to have outpaced even the viral success of ChatGPT in terms of signing up users. The next challenge will be keeping them around.

Since its inception on Thursday 7/07/2023, Meta’s new Threads platform has been signing up new users at an alarming rate.  On rollout date 5 million signed up, then 30 million by next morning and now as of today (7/1/2023) Threads has over 100 million signups.  Compare that to Twitter’s 436 million users, of which are tweeting on average 25% less than a few years ago, and it is easy to see why many social media pundits are calling Threads the new Twitter killer app.


Here are a few notes from the New York Times podcast The Daily

The Daily

1 day ago

Will Threads Kill Twitter?

Play • 33 min

Last week, Meta, the parent company of Facebook and Instagram, released Threads, a social media platform to compete with Twitter. In just 16 hours, Threads was downloaded more than 30 million times.

Mike Isaac, who covers tech companies and Silicon Valley for The Times, explains how Twitter became so vulnerable and discusses the challenges Meta faces to create a less toxic alternative.

Guest: Mike Isaac, a technology correspondent for The New York Times.

Background reading:

Here are a few notes from the podcast:

Mike Isaac lamented that Twitter has become user unfriendly for a host of reasons.  These include:

  • The instant reply’guys’ – people who reply but don’t really follow you or your thread
  • Your followers or following are not pushed to top of thread
  • The auto bots – the automated Twitter bots
  • Spam feeds
  • The changes in service and all these new fees: Twitter push to monetize everything – like airlines

Elon Musk wanted to transform Twitter but his history is always cutting, not just trimming the excess but he is known to just eliminate departments just because he either doesn’t want to pay or CAN’T pay.  With Twitter he gutted content moderation.


Twitter ad business is plumetting but Musk wants to make Twitter a subscription business (the Blue check mark)

Twitter only gets a couple of million $ per month from Twitter Blue but Musk has to pay billions to just pay the interest on Twitter loan for Twitter puchase years ago

It is known that Musk is not paying rent on some California offices (some are suggesting he defaulted on leases) and Musk is selling Tesla stock to pay for Twitter expenses (why TSLA stock has been falling … the consensus out there)

Twitter is largest compendium of natural language conversations and Musk wanted to limit bots from scraping Twitter data to do AI and NLP on Twitter threads.  This is also a grievance from other companies… that these ‘scrapers’ are not paying enough for Twitter data.  However as Mike asks why do the little Twitter user have to pay in either fees or cutbacks from service.  (the reason why Elon is limiting viewing per day is to limit these bots from scraping Twitter for data)

Another problem is that Twitter does not have its own servers so pays a lot to Google and AWS for server space.  It appears Elon and Twitter are running out of money.


Zuckerberg has spent billions of infrastructure spending and created a massive advertising ecosystem.  This is one of the thoughts behind his push and entry into this space.  Zuckerberg actually wanted to but Twitter a decade ago.


Usage and growth:  The launch of Threads was Thursday 7-07-23. There were 2 million initial signups and by next morning 30 million overnight.  Today Monday 7-10-23 there are 100 million, rivaling Twitter’s 436 million accounts.  And as Musk keeps canceling Twitter accounts, angering users over fees or usage restrictions, people are looking for a good platform.  Mastedon in too technical and not having the adoption like Meta Threads is having.  Mike Isaac hopes Threads will not go the way of Google Hangouts or Plus but Google strategy did not involve social media like Facebook.

Signup and issues: Signup on Threads is easy but you need to go through Instagram.  Some people have concerns about having their instagram thread put on their Threads feed but Mike had talked to the people at Meta and they are working to allow users to keep the feeds separate, mainly because Meta understands that the Instgagram and Twitter social cultures are different and users may want to keep Threads more business-like.

Important issues for LPBI: Twitter had decided, by end of May 2023 to end their relationship with WordPress JetPack service, in which WordPress posts could automatically be posted to your Twitter account and feed.  Twitter is making users like WordPress pay for this API and WordPress said it would be too expensive as Twitter is not making a flat fee but per usage fee.  This is a major hindrance even though the Twitter social share button is still active on posts.

Initial conversations between META and WordPress have indicated META will keep this API service free for WordPress.


So a little background on Meta Threads and signup features from Meta (Facebook) website:


  • Threads is a new app, built by the Instagram team, for sharing text updates and joining public conversations.
  • You log in using your Instagram account and posts can be up to 500 characters long and include links, photos, and videos up to 5 minutes in length.
  • We’re working to soon make Threads compatible with the open, interoperable social networks that we believe can shape the future of the internet.

Mark Zuckerberg just announced the initial version of Threads, an app built by the Instagram team for sharing with text. Whether you’re a creator or a casual poster, Threads offers a new, separate space for real-time updates and public conversations. We are working toward making  Threads compatible with the open, interoperable social networks that we believe can shape the future of the internet.

Instagram is where billions of people around the world connect over photos and videos. Our vision with Threads is to take what Instagram does best and expand that to text, creating a positive and creative space to express your ideas. Just like on Instagram, with Threads you can follow and connect with friends and creators who share your interests – including the people you follow on Instagram and beyond. And you can use our existing suite of safety and user controls.

Join the Conversation from Instagram

It’s easy to get started with Threads: simply use your Instagram account to log in. Your Instagram username and verification will carry over, with the option to customize your profile specifically for Threads.

Everyone who is under 16 (or under 18 in certain countries) will be defaulted into a private profile when they join Threads. You can choose to follow the same accounts you do on Instagram, and find more people who care about the same things you do. The core accessibility features available on Instagram today, such as screen reader support and AI-generated image descriptions, are also enabled on Threads.

Your feed on Threads includes threads posted by people you follow, and recommended content from new creators you haven’t discovered yet. Posts can be up to 500 characters long and include links, photos, and videos up to 5 minutes in length. You can easily share a Threads post to your Instagram story, or share your post as a link on any other platform you choose.

Tune Out the Noise

We built Threads with tools to enable positive, productive conversations. You can control who can mention you or reply to you within Threads. Like on Instagram, you can add hidden words to filter out replies to your threads that contain specific words. You can unfollow, block, restrict or report a profile on Threads by tapping the three-dot menu, and any accounts you’ve blocked on Instagram will automatically be blocked on Threads.

As with all our products, we’re taking safety seriously, and we’ll enforce Instagram’s Community Guidelines on content and interactions in the app. Since 2016 we’ve invested more than $16 billion in building up the teams and technologies needed to protect our users, and we remain focused on advancing our industry-leading integrity efforts and investments to protect our community.

Compatible with Interoperable Networks

Soon, we are planning to make Threads compatible with ActivityPub, the open social networking protocol established by the World Wide Web Consortium (W3C), the body responsible for the open standards that power the modern web. This would make Threads interoperable with other apps that also support the ActivityPub protocol, such as Mastodon and WordPress – allowing new types of connections that are simply not possible on most social apps today. Other platforms including Tumblr have shared plans to support the ActivityPub protocol in the future.

We’re committed to giving you more control over your audience on Threads – our plan is to work  with ActivityPub to provide you the option to stop using Threads and transfer your content to another service. Our vision is that people using compatible apps will be able to follow and interact with people on Threads without having a Threads account, and vice versa, ushering in a new era of diverse and interconnected networks. If you have a public profile on Threads, this means your posts would be accessible from other apps, allowing you to reach new people with no added effort. If you have a private profile, you’d be able to approve users on Threads who want to follow you and interact with your content, similar to your experience on Instagram.

The benefits of open social networking protocols go well beyond the ways people can follow each other. Developers can build new types of features and user experiences that can easily plug into other open social networks, accelerating the pace of innovation and experimentation. Each compatible app can set its own community standards and content moderation policies, meaning people have the freedom to choose spaces that align with their values. We believe this decentralized approach, similar to the protocols governing email and the web itself, will play an important role in the future of online platforms.

Threads is Meta’s first app envisioned to be compatible with an open social networking protocol – we hope that by joining this fast-growing ecosystem of interoperable services, Threads will help people find their community, no matter what app they use.

What’s Next

We’re rolling out Threads today in more than 100 countries for iOS and Android, and people in those countries can download the app from the Apple App Store and Google Play Store.

In addition to working toward making Threads compatible with the ActivityPub protocol, soon we’ll be adding a number of new features to help you continue to discover threads and creators you’re interested in, including improved recommendations in feed and a more robust search function that makes it easier to follow topics and trends in real time.


Should Science Migrate over to Threads Instead of Twitter?

I have written multiple time of the impact of social media, Science and Web 2.0 and the new Science and Web 3.0 including

Will Web 3.0 Do Away With Science 2.0? Is Science Falling Behind?

Science Has A Systemic Problem, Not an Innovation Problem


It, as of this writing, appears it is not crucial that scientific institutions need to migrate over to Threads yet, although the impetus is certainly there.  Many of the signups have of course been through Instagram (which is the only way to signup for now) and a search of @Threads does not show that large scientific organizations have signed up for now.


A search for NIH, NCBI, AACR, and Personalized Medicine Coalition or PMC which is the big MGH orgaization on personalized medicine appears to return nothing yet.  Pfizer and most big pharma is on @Threads now but that is because they maintain a marketing thread on Instagram.  How necessary is @Threads for communicating science over Science 3.0 platform remains to be seen.  In addition, how will @Threads be used for real time scientific conference coverage?  Will Meta be able to integrate with virtual reality?

Other articles of Note on this Open Access Scientific Journal Include:

Will Web 3.0 Do Away With Science 2.0? Is Science Falling Behind?

Science Has A Systemic Problem, Not an Innovation Problem

Relevance of Twitter.com forthcoming Payment System for Scientific Content Promotion and Monetization

Is It Time for the Virtual Scientific Conference?: Coronavirus, Travel Restrictions, Conferences Cancelled

Part One: The Process of Real Time Coverage using Social Media