biomedical research topics 2023

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Correction: A novel HIF1α-STIL-FOXM1 axis regulates tumor metastasis

The original article was published in Journal of Biomedical Science 2022 29 :24

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Significance of hepatitis B virus capsid dephosphorylation via polymerase

It is generally believed that hepatitis B virus (HBV) core protein (HBc) dephosphorylation (de-P) is important for viral DNA synthesis and virion secretion. HBV polymerase contains four domains for terminal pr...

Association of TRAIL receptor with phosphatase SHP-1 enables repressing T cell receptor signaling and T cell activation through inactivating Lck

T cell receptor (TCR) signaling and T cell activation are tightly regulated by gatekeepers to maintain immune tolerance and avoid autoimmunity. The TRAIL receptor (TRAIL-R) is a TNF-family death receptor that ...

Improving CRISPR–Cas9 directed faithful transgene integration outcomes by reducing unwanted random DNA integration

The field of genome editing has been revolutionized by the development of an easily programmable editing tool, the CRISPR–Cas9. Despite its promise, off-target activity of Cas9 posed a great disadvantage for g...

A matter of new life and cell death: programmed cell death in the mammalian ovary

The mammalian ovary is a unique organ that displays a distinctive feature of cyclic changes throughout the entire reproductive period. The estrous/menstrual cycles are associated with drastic functional and mo...

Engineered extracellular vesicles carrying let-7a-5p for alleviating inflammation in acute lung injury

Acute lung injury (ALI) is a life-threatening respiratory condition characterized by severe inflammation and lung tissue damage, frequently causing rapid respiratory failure and long-term complications. The mi...

The rise of big data: deep sequencing-driven computational methods are transforming the landscape of synthetic antibody design

Synthetic antibodies (Abs) represent a category of artificial proteins capable of closely emulating the functions of natural Abs. Their in vitro production eliminates the need for an immunological response, st...

Tick-borne encephalitis virus transmitted singly and in duo with Borrelia burgdorferi sensu lato and Anaplasma phagocytophilum bacteria by ticks as pathogens modifying lipid metabolism in human blood

Ticks are vectors of various pathogens, including tick-borne encephalitis virus causing TBE and bacteria such as Borrelia burgdorferi sensu lato and Anaplasma phagocytophilum causing e.g. viral-bacterial co-infec...

Integration of transcription regulation and functional genomic data reveals lncRNA SNHG6’s role in hematopoietic differentiation and leukemia

Long non-coding RNAs (lncRNAs) are pivotal players in cellular processes, and their unique cell-type specific expression patterns render them attractive biomarkers and therapeutic targets. Yet, the functional ...

Reduced interleukin-18 secretion by human monocytic cells in response to infections with hyper-virulent Streptococcus pyogenes

Streptococcus pyogenes (group A streptococcus, GAS) causes a variety of diseases ranging from mild superficial infections of the throat and skin to severe invasive infections, such as necrotizing soft tissue infe...

Metabolism-regulating non-coding RNAs in breast cancer: roles, mechanisms and clinical applications

Breast cancer is one of the most common malignancies that pose a serious threat to women's health. Reprogramming of energy metabolism is a major feature of the malignant transformation of breast cancer. Compar...

Genetic and pharmacologic p32-inhibition rescue CHCHD2-linked Parkinson’s disease phenotypes in vivo and in cell models

Mutations in CHCHD2 have been linked to Parkinson’s disease, however, their exact pathophysiologic roles are unclear. The p32 protein has been suggested to interact with CHCHD2, however, the physiological functio...

The role of pregnancy associated plasma protein-A in triple negative breast cancer: a promising target for achieving clinical benefits

Pregnancy associated plasma protein-A (PAPP-A) plays an integral role in breast cancer (BC), especially triple negative breast cancer (TNBC). This subtype accounts for the most aggressive BC, possesses high tu...

Translational research on drug development and biomarker discovery for hepatocellular carcinoma

Translational research plays a key role in drug development and biomarker discovery for hepatocellular carcinoma (HCC). However, unique challenges exist in this field because of the limited availability of hum...

Germline mutations of homologous recombination genes and clinical outcomes in pancreatic cancer: a multicenter study in Taiwan

Cancer susceptibility germline mutations are associated with pancreatic ductal adenocarcinoma (PDAC). However, the hereditary status of PDAC and its impact on survival is largely unknown in the Asian population.

Rab37 mediates trafficking and membrane presentation of PD-1 to sustain T cell exhaustion in lung cancer

Programmed cell death protein 1 (PD-1) is an immune checkpoint receptor expressed on the surface of T cells. High expression of PD-1 leads to T-cell dysfunction in the tumor microenvironment (TME). However, th...

FLT3L-induced virtual memory CD8 T cells engage the immune system against tumors

Previous research in FMS-like tyrosine kinase 3 ligands (FLT3L) has primarily focused on their potential to generate dendritic cells (DCs) from bone marrow progenitors, with a limited understanding of how thes...

Promising antibacterial efficacy of arenicin peptides against the emerging opportunistic pathogen Mycobacterium abscessus

Mycobacterium abscessus , a fast-growing non-tuberculous mycobacterium, is an emerging opportunistic pathogen responsible for chronic bronchopulmonary infections in people with respiratory diseases such as cystic ...

Targeting MDM2 in malignancies is a promising strategy for overcoming resistance to anticancer immunotherapy

MDM2 has been established as a biomarker indicating poor prognosis for individuals undergoing immune checkpoint inhibitor (ICI) treatment for different malignancies by various pancancer studies. Specifically, ...

Mechanisms and functions of SUMOylation in health and disease: a review focusing on immune cells

SUMOylation, which is a type of post-translational modification that involves covalent conjugation of small ubiquitin-like modifier (SUMO) proteins to target substrates, regulates various important molecular a...

Hesperetin activates CISD2 to attenuate senescence in human keratinocytes from an older person and rejuvenates naturally aged skin in mice

CDGSH iron-sulfur domain-containing protein 2 (CISD2), a pro-longevity gene, mediates healthspan in mammals. CISD2 is down-regulated during aging. Furthermore, a persistently high level of CISD2 promotes longe...

Plectin plays a role in the migration and volume regulation of astrocytes: a potential biomarker of glioblastoma

The expression of aquaporin 4 (AQP4) and intermediate filament (IF) proteins is altered in malignant glioblastoma (GBM), yet the expression of the major IF-based cytolinker, plectin (PLEC), and its contributio...

Modelling the complex nature of the tumor microenvironment: 3D tumor spheroids as an evolving tool

Cancer remains a serious burden in society and while the pace in the development of novel and more effective therapeutics is increasing, testing platforms that faithfully mimic the tumor microenvironment are l...

TEM1/endosialin/CD248 promotes pathologic scarring and TGF-β activity through its receptor stability in dermal fibroblasts

Pathologic scars, including keloids and hypertrophic scars, represent a common form of exaggerated cutaneous scarring that is difficult to prevent or treat effectively. Additionally, the pathobiology of pathol...

Physiology and pharmacological targeting of phase separation

Liquid–liquid phase separation (LLPS) in biology describes a process by which proteins form membraneless condensates within a cellular compartment when conditions are met, including the concentration and postt...

Inactivation of pentraxin 3 suppresses M2-like macrophage activity and immunosuppression in colon cancer

The tumor microenvironment is characterized by inflammation-like and immunosuppression situations. Although cancer-associated fibroblasts (CAFs) are among the major stromal cell types in various solid cancers,...

Engineered EVs with pathogen proteins: promising vaccine alternatives to LNP-mRNA vaccines

Extracellular vesicles (EVs) are tiny, lipid membrane-bound structures that are released by most cells. They play a vital role in facilitating intercellular communication by delivering bioactive cargoes to rec...

Attenuation of neurovirulence of chikungunya virus by a single amino acid mutation in viral E2 envelope protein

Chikungunya virus (CHIKV) has reemerged as a major public health concern, causing chikungunya fever with increasing cases and neurological complications.

Scaffold-based 3D cell culture models in cancer research

Three-dimensional (3D) cell cultures have emerged as valuable tools in cancer research, offering significant advantages over traditional two-dimensional (2D) cell culture systems. In 3D cell cultures, cancer c...

Therapeutic antibodies for the prevention and treatment of cancer

The developments of antibodies for cancer therapeutics have made remarkable success in recent years. There are multiple factors contributing to the success of the biological molecule including origin of the an...

Immune evasion in cell-based immunotherapy: unraveling challenges and novel strategies

Cell-based immunotherapies (CBIs), notably exemplified by chimeric antigen receptor (CAR)-engineered T (CAR-T) cell therapy, have emerged as groundbreaking approaches for cancer therapy. Nevertheless, akin to ...

Exploring the relationship between metabolism and immune microenvironment in osteosarcoma based on metabolic pathways

Metabolic remodeling and changes in tumor immune microenvironment (TIME) in osteosarcoma are important factors affecting prognosis and treatment. However, the relationship between metabolism and TIME needs to ...

The synergism of cytosolic acidosis and reduced NAD + /NADH ratio is responsible for lactic acidosis-induced vascular smooth muscle cell impairment in sepsis

During sepsis, serve vascular dysfunctions lead to life-threatening multiple organ failure, due to vascular smooth muscle cells (VSMC) impairments, resulting in vasoplegia, hypotension and hypoperfusion. In ad...

Localization, traffic and function of Rab34 in adipocyte lipid and endocrine functions

Excessive lipid accumulation in the adipose tissue in obesity alters the endocrine and energy storage functions of adipocytes. Adipocyte lipid droplets represent key organelles coordinating lipid storage and m...

Nano-modified viruses prime the tumor microenvironment and promote the photodynamic virotherapy in liver cancer

As of 2020, hepatocellular carcinoma (HCC), a form of liver cancer, stood as the third most prominent contributor to global cancer-related mortality. Combining immune checkpoint inhibitors (ICI) with other the...

A novel mucosal bivalent vaccine of EV-A71/EV-D68 adjuvanted with polysaccharides from Ganoderma lucidum protects mice against EV-A71 and EV-D68 lethal challenge

Human enteroviruses A71 (EV-A71) and D68 (EV-D68) are the suspected causative agents of hand-foot-and-mouth disease, aseptic meningitis, encephalitis, acute flaccid myelitis, and acute flaccid paralysis in chi...

A secreted form of chorismate mutase (Rv1885c) in Mycobacterium bovis BCG contributes to pathogenesis by inhibiting mitochondria-mediated apoptotic cell death of macrophages

Mycobacterium tuberculosis is the causative agent of tuberculosis (TB), and its pathogenicity is associated with its ability to evade the host defense system. The secretory form of the chorismate mutase of M. tub...

ARID1A loss activates MAPK signaling via DUSP4 downregulation

ARID1A , a tumor suppressor gene encoding BAF250, a protein participating in chromatin remodeling, is frequently mutated in endometrium-related malignancies, including ovarian or uterine clear cell carcinoma (CCC)...

SCEL regulates switches between pro-survival and apoptosis of the TNF-α/TNFR1/NF-κB/c-FLIP axis to control lung colonization of triple negative breast cancer

Patients with metastatic triple-negative breast cancer (mTNBC) have a higher probability of developing visceral metastasis within 5 years after the initial diagnosis. Therefore, a deeper understanding of the p...

Butterflies in the gut: the interplay between intestinal microbiota and stress

Psychological stress is a global issue that affects at least one-third of the population worldwide and increases the risk of numerous psychiatric disorders. Accumulating evidence suggests that the gut and its ...

Spatiotemporal roles of AMPK in PARP-1- and autophagy-dependent retinal pigment epithelial cell death caused by UVA

Although stimulating autophagy caused by UV has been widely demonstrated in skin cells to exert cell protection, it remains unknown the cellular events in UVA-treated retinal pigment epithelial (RPE) cells.

The ‘speck’-tacular oversight of the NLRP3-pyroptosis pathway on gastrointestinal inflammatory diseases and tumorigenesis

The NLRP3 inflammasome is an intracellular sensor and an essential component of the innate immune system involved in danger recognition. An important hallmark of inflammasome activation is the formation of a s...

Complete spectrum of adverse events associated with chimeric antigen receptor (CAR)-T cell therapies

Chimeric antigen receptor (CAR)-T cell therapies have been approved by FDA to treat relapsed or refractory hematological malignancies. However, the adverse effects of CAR-T cell therapies are complex and can b...

Small interfering RNA (siRNA)-based therapeutic applications against viruses: principles, potential, and challenges

RNA has emerged as a revolutionary and important tool in the battle against emerging infectious diseases, with roles extending beyond its applications in vaccines, in which it is used in the response to the CO...

Human ACE2 protein is a molecular switch controlling the mode of SARS-CoV-2 transmission

Human angiotensin-converting enzyme 2 (hACE2) is the receptor mediating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. hACE2 expression is low in the lungs and is upregulated after SAR...

Crosstalk between mitochondrial biogenesis and mitophagy to maintain mitochondrial homeostasis

Mitochondrial mass and quality are tightly regulated by two essential and opposing mechanisms, mitochondrial biogenesis (mitobiogenesis) and mitophagy, in response to cellular energy needs and other cellular a...

Extracellular release in the quality control of the mammalian mitochondria

Mammalian cells release a wealth of materials to their surroundings. Emerging data suggest these materials can even be mitochondria with perturbed morphology and aberrant function. These dysfunctional mitochon...

mRNA-based vaccines and therapeutics: an in-depth survey of current and upcoming clinical applications

mRNA-based drugs have tremendous potential as clinical treatments, however, a major challenge in realizing this drug class will promise to develop methods for safely delivering the bioactive agents with high e...

Clinical trials of new drugs for Alzheimer disease: a 2020–2023 update

Alzheimer's disease (AD) is the leading cause of dementia, presenting a significant unmet medical need worldwide. The pathogenesis of AD involves various pathophysiological events, including the accumulation o...

Induced pluripotent stem cells: ex vivo models for human diseases due to mitochondrial DNA mutations

Mitochondria are essential organelles for cellular metabolism and physiology in eukaryotic cells. Human mitochondria have their own genome (mtDNA), which is maternally inherited with 37 genes, encoding 13 poly...

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Journal of Biomedical Science

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December 19, 2023

The Biggest Health and Medicine Stories of 2023

From new uses for weight-loss drugs to the first CRISPR gene editing therapy, these were some of the most impactful health stories of the year

By Tanya Lewis

In an operating room at the University of Maryland Medical Center on September 20, 2023, surgeons transfer a genetically modified pig heart to the operative field for transplant.

University of Maryland School of Medicine

In world with so much urgent and depressing news, it can be hard to take a moment and reflect on all of the encouraging scientific and medical progress that has happened. But looking back at 2023, there was plenty on the health beat to be awed by.

From the arrival of the first safe and effective vaccines for a common respiratory disease to the first U.S. Food and Drug Administration–approved CRISPR gene editing treatment, these were some of the biggest stories in the health world this year.

New Weight-Loss Drugs Revealed New Tricks

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A new generation of drugs that result in significant weight loss appeared on the scene a few years ago with dramatic effects. This past year we learned a lot more about other potential benefits of the drugs, which include Novo Nordisk’s Wegovy and Ozempic and Eli Lilly’s Mounjaro. These range from reducing the risk of heart attack or stroke to possibly treating addiction . But the medications come with side effects such as gastrointestinal problems and muscle loss. They’re not cheap, either—they can cost around $1,000 or more out of pocket—and it’s not clear whether insurance will cover them . Still, these drugs are driving significant interest as we continue to learn more about them.

The COVID Public Health Emergency Ended

The federal public health emergency put in place to combat the COVID pandemic ended on May 11. The end of the public health emergency marked the conclusion of a set of policies that made it easier and cheaper to access COVID tests, vaccines and treatments, as well as telehealth visits. Consumers must now obtain many of these things with coverage through private insurance, Medicare, or Medicaid or bear the cost themselves. SARS-CoV-2, the virus that causes COVID, continues to circulate and pose a threat to public health. But in May the World Health Organization declared that disease no longer constituted a public health emergency of international concern and said that it was time to transition to long-term management of the COVID pandemic.

We Got Closer to Xenotransplants

There’s an enormous need for organ transplants, but donor organs are in short supply. Improvements in transplant science have made more organs available and usable. Yet too many people still die waiting for one. Now some scientists are exploring another approach: transplanting organs from nonhuman animals . In the past year they have made significant progress in such “xenotransplants.” Following the first transplant of a genetically engineered pig heart into a human in early 2022, this year doctors completed the second such transplant . (Both surgeries were performed on a compassionate use basis because the recipients were terminally ill.) Sadly, the man who received the heart in the latest surgery died after six weeks, likely because his immune system rejected the organ. Other researchers completed successful xenotransplant experiments in people who had suffered brain death, and monkeys that received pig kidneys survived for up to two years . Scientists are hopeful that they can improve the procedures enough to test these techniques in clinical trials in people soon.

RSV Vaccines Finally Arrived

Respiratory syncytial virus (RSV) causes annoying coldlike symptoms in most people, yet in very young children or older adults the disease can be deadly. For decades scientists have tried to develop a vaccine to protect against RSV , but a series of disastrous clinical trials in the 1960s ended up making the illness more severe, leading to the deaths of two children. Researchers persisted, however, and as of this year, several safe and effective RSV vaccines were approved by the FDA to protect pregnant people and older adults. The agency also approved an antibody drug that protects children after they’re born.

The First CRISPR-Based Treatment Was Approved

Nearly a decade after it was first discovered, the gene editing method known as CRISPR is resulting in its first treatments. In December the FDA approved the first CRISPR-based treatment for sickle cell disease . The new therapy is known as exa-cel and made by the biotech companies Vertex Pharmaceuticals and CRISPR Therapeutics. It deactivates a faulty gene for the hemoglobin protein, which transports oxygen around the body. Without the treatment, the gene causes blood cells to develop a sicklelike shape, making them clog up blood vessels. The illness, which disproportionately affects Black people, causes debilitating pain and fatigue. The new treatment, as well as another gene therapy approved at the same time, prevented symptoms of the disease for a year in clinical trials. But longer follow-up is needed to see if there are any side effects, and the cost could make it hard for many people to access.

We Gained New Insight Into Long COVID

Even as the immediate danger of COVID has receded somewhat, tens of millions of people continue to be affected by long COVID—a cluster of symptoms such as fatigue, body aches and brain fog that linger long after an infection. The causes of long COVID are still mysterious, yet as Stephani Sutherland wrote in our March issue, it increasingly resembles a neurological disease . Not only does it cause cognitive problems with memory, attention, sleep and mood, but it also has symptoms such as pain and postexertional malaise—extreme fatigue after exercise—that seem to stem from the autonomic nervous system, the autopilot system that controls breathing and digestion, among other things. This new understanding could help guide treatments.

Chat-Based AI Systems Entered Medicine

When ChatGPT was released in November 2022, it caused ripples throughout numerous fields—and medicine was no exception. This chat-based artificial intelligence program made by the company OpenAI—along with large language models made by Google and others—is capable of generating text that convincingly mimics human writing. People have already begun to use these programs to diagnose medical conditions , and while the AIs appear surprisingly accurate in some early studies, doctors caution that they are not a substitute for professional medical care. Other people are turning to AI chatbots for therapy . Such apps could help meet the growing demand for mental health services, but as with using them for medical advice, experts urge caution.

First Face and Eye Transplant Was Completed

Xenotransplants weren’t the only groundbreaking type of transplant to occur this year. In May doctors in New York City completed the first partial face and whole-eye transplant in an Arkansas man who had suffered severe electrical burns while working as a lineman. While corneal transplants are routine, this was the first time an entire human eye was transplanted and remained healthy six months later, according to the transplant team. The recipient, 46-year-old Aaron James, has not regained sight in that eye, but doctors say the eye’s retinal tissue is intact, and there are signs it may be sending signals to the brain. The feat opens the door to restoring the appearance—and possibly, one day, the function—of people who have had traumatic eye injuries.

Articles on Biomedical research

Displaying 1 - 20 of 48 articles.

Two decades of stagnant funding have rendered Canada uncompetitive in biomedical research. Here’s why it matters, and how to fix it.

Stephen L Archer , Queen's University, Ontario

Organ-on - a-chip models allow researchers to conduct studies closer to real-life conditions – and possibly grease the drug development pipeline

Chengpeng Chen , University of Maryland, Baltimore County

Visualizing the inside of cells at previously impossible resolutions provides vivid insights into how they work

Jeremy Berg , University of Pittsburgh

Nanomedicines for various diseases are in development – but research facilities produce vastly inconsistent results on how the body will react to them

Morteza Mahmoudi , Michigan State University

What is ethical animal research? A scientist and veterinarian explain

Lana Ruvolo Grasser , National Institutes of Health and Rachelle Stammen , Emory University

Altruism – but also vulnerability – drive healthy volunteers to take part in clinical research

Isabelle Remy-Jouet , Université d'Angers ; François Eisinger , Inserm , and François Hirsch , Inserm

Peer review: Can this critical step in the publication of science research be kinder?

Catherine Clase , McMaster University ; Josee Bouchard , Université de Montréal ; Manish M Sood , L’Université d’Ottawa/University of Ottawa ; Rachel Holden , Queen's University, Ontario , and Sunny Hartwig , University of Prince Edward Island

Sex matters in biomedical research: Many conditions affect men and women differently

Monica De Paoli , McMaster University

Major study shows the need to improve how scientists approach early-stage cancer research

Robert Nadon , McGill University

Figuring out omicron – here’s what scientists are doing right now to understand the new coronavirus variant

Peter Kasson , University of Virginia

Remembering Tania Douglas: a brilliant biomedical engineer, academic and friend

Ernesta M. Meintjes , University of Cape Town

We’re creating ‘humanized pigs’ in our ultraclean lab to study human illnesses and treatments

Christopher Tuggle , Iowa State University and Adeline Boettcher , Iowa State University

COVID has left Australia’s biomedical research sector gasping for air

Gina Ravenscroft , The University of Western Australia and Elizabeth E. Gardiner , Australian National University

COVID-19 vaccine update: Pfizer may be the frontrunner, but Canada has hedged its bets

Aïssatou Aïcha Sow , Institut national de la recherche scientifique (INRS)

A tiny circular racetrack for light can rapidly detect single molecules

Judith Su , University of Arizona

Surgical corsets, respirators: a new exhibition showcases the art hidden in medical devices

Peter Hobbins , University of Sydney

Cell-like decoys could mop up viruses in humans – including the one that causes  COVID-19

Liangfang Zhang , University of California, San Diego

This 3D printed ‘bone brick’ could transform how we treat bomb injuries – inside story

Paulo Bartolo , University of Manchester

AI tool searches thousands of scientific papers to guide researchers to coronavirus insights

Amalie Trewartha , University of California, Berkeley and John Dagdelen , University of California, Berkeley

A mysterious illness is striking children amid the coronavirus pandemic – but is it Kawasaki disease?

Mark Hicar , University at Buffalo

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Associate Professor of Public Policy and Women's Studies, University of Michigan

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Director of Translational Institute of Medicine (TIME), Queen's University, Ontario

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Head of Knowledge, Australian National Maritime Museum and Honorary Affiliate, University of Sydney

Professor of Bioethics, Macquarie University

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New Trends in Vascular Biology 2023

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Medical Topics News

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Tuesday, april 9, 2024.

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Wednesday, April 3, 2024

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Tuesday, April 2, 2024

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Tuesday, March 26, 2024

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Monday, March 25, 2024

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Tuesday, March 19, 2024

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Q&A: How generative AI could help accelerate biomedical research

by Corie Lok, Broad Institute of MIT and Harvard

The recent explosion of generative AI tools has prompted many discussions in virtually all fields about the benefits and risks of these technologies. These tools, including ChatGPT, Bard and others, have been trained on huge amounts of content and can produce text and images that often look eerily like human-generated content.

At the Broad Institute of MIT and Harvard, a group of researchers, software engineers , administrators, and communicators (yes, us) has been exploring the use of these chatbots and similar tools, surveying the community and developing recommendations.

To dive deeper into this topic, we spoke with Mehrtash Babadi, an institute scientist, director of computational methods, and a machine learning and AI expert in Broad's Data Sciences Platform. He talked about how generative AI techniques can be used not just to analyze human language but also the language of genes and cells—raw biological data—to shed light on how cells and tissues work in health and disease.

He also shared his thoughts on the benefits of language-based generative models like ChatGPT, Bard, and GitHub Copilot for writing computer code, developing hypotheses, and other tasks.

"I think these systems will become increasingly useful not only for software engineers and programmers, but also for basically everyone else in every profession in the same sense that a search engine has become an indispensable part of our lives for accessing information," said Babadi, who routinely uses ChatGPT to search the internet and write emails and research summaries.

The following conversation was edited (by humans) for length and clarity.

How have you been thinking about generative AI in biology?

Generative AI is something that has been brewing for a long time in the machine learning community, going back to the fundamental tenets of Bayesian statistics. We've been using those for a long while, for modeling various aspects of biology like genomic variation, experimental artifacts, single-cell biology, and other areas.

Now with the advancement of these models, their combination with deep neural networks , vast amounts of training data and computing power, and in particular the progress of these models in generating images and natural language, they have really exploded and all of a sudden everybody is excited about them.

We are now thinking about how the same approaches that have been so successful in modeling natural language and images could be used for learning the intrinsic, innate language of biological systems like cells and tissues, and predicting their fate and response to various stimuli in silico. That's an area of active research for us, and we have made a little bit of headway, but there's a lot of work that needs to be done.

Can you explain more about how generative AI can be used to analyze biological data?

Right now, there's a lot of excitement about ChatGPT and similar conversational AI systems, and for good reasons, because these are really capable and powerful systems, and there's also a lot of emerging work in the field showing that these models also have a good grasp of biology. You can ask them questions like "what is the function of this gene?" and they will tell you because they have read textbooks and papers. So the models have learned what we know about biology.

And that's exactly the problem, because we don't know much about many aspects of biology! Our understanding of biology is still evolving and is very biased and some of the literature is not even reproducible. The natural language models are trained on that substrate, and so they're subject to the same biases and incomplete understandings of biology that we are subject to.

So we are trying to directly learn the language of biological systems from raw biological measurements and data without any human interpretation in between.

How would a researcher use a generative model trained on raw biological data?

For example, you can envision a generative model that's been trained on biological data describing how certain tissues or cells work, and then using that model to generate data that describe new cell states or new tissues. You can even make models that you could prompt with something like "here's a cell in a tissue, generate another cell nearby" to make predictions about how different cells might work together to form a tissue, as an example.

These models could also be fine-tuned on interventional data, such as genetic or pharmacological screens, to learn to predict future screens. In a nutshell, generative models have the potential to computationalize many aspects of cell and tissue biology and perturbation screens.

What becomes very interesting now is to interface these models of cells and tissues with natural language models. So we can take natural language models and the more unbiased and comprehensive models of cells, and then fuse them together into a system that is more powerful than each of them separately. That's an active area of AI research called multimodal generative AI, where one basically combines generative models of different modalities, or interface them together, and allow them to talk to each other.

The advantage of this is that with the models based on the innate language of biology, you avoid the bias that's inherent in the natural language models of biology. But you can use the natural language models to allow a human scientist to put in the right prompts.

What progress has been made in multimodal generative AI for biology?

We do now have multimodal generative AI of natural language and text, natural language and images, but generative AI models of biological systems are still in their infancy. We have yet to see multimodal AI systems that combine natural language with the language of biological systems.

Can generative AI be useful for hypothesis generation?

One potential example I can think of is a typical drug development project, where we want to understand the underlying mechanism for a disease and then identify a therapeutic target. Right now, this is typically done through a combination of subject matter expert insights and the design of very smart experiments that test smart hypotheses using innovative techniques to manipulate cells and whatnot.

But as we do more and more of these types of experiments, each of these experiments is a sort of lesson for a generative AI system that says "here's a cell and here's how we intervened and here's what happened." And the more of these lessons we catalog, the more we can teach a generative AI system to predict future experiments without us needing to do all of them in the lab. There is this immense opportunity to reuse all of the experimental data that we've collected so far.

But won't some of those predictions be wrong?

Even if these generative models are sometimes wrong, they're not entirely wrong. This means that if, for example, you use them to identify a certain therapeutic target, if the systems are appropriately trained, it is highly likely that at least some of those targets actually make some sense.

That's probably one of the best applications of these systems: to take their outputs as potential hypotheses and then subject them to experimental validation. Depending on the nature of the outcome, the resulting data from the follow-up experiments will either reinforce the model's belief or correct it, ultimately making it slightly more accurate for future queries.

Let's talk about the natural language models like ChatGPT. How useful are these tools for coding and software development?

Some of us use GitHub Copilot, which is a system that helps coders and programmers write some of the more standard, boilerplate parts of code, rather than the most innovative and challenging parts. These systems are really good at helping you write parts of your code that everybody knows how to write, but you still need to do it anyway.

These systems are also really good at helping you document your code and comment on your code. So we're using these systems right now for these purposes and as smarter versions of the conventional code-completion systems.

Do you have any concerns about these language models, like inaccuracies or potential misuse?

The challenge is that these models are well known to "hallucinate" once in a while or just very confidently lie. So you have to do your own fact-checking. As for misuse, I'm less worried about the science and engineering communities because scientists and engineers are, by training, skeptics and they tend to not take things at face value. So even if they use a generative AI system to help them solve a problem, they would test the output of these systems.

I think where I'd be worried more is how these systems could be exploited in other areas, such as generating misinformation and in other discourses where people are not as inclined to do their own fact-checking. That's where I'm worried, especially because these systems can generate content much, much faster than we can. So it's very easy to flood the space, so to speak, with lots of deliberately false, AI-generated content.

But as tools for biological research and software development, I think there's a lot of promise in helping to make some parts of research more efficient. The pace at which we're generating data, which is exponentially increasing, is far exceeding our expert capability to make sense of that data. That's where generative AI and in general, machine learning and other AI methods, could become extremely useful to help us uncover the regularities, commonalities, and differences in all this data in a way that is less biased and also more efficient and faster than we humans can do.

Provided by Broad Institute of MIT and Harvard

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Top 10 Biomedical Issues of the Next Decade

Some biomedical trends will defuse old arguments; others will spark new disputes

Forecasting the future is a dangerous activity. Still, even if forcasting is difficult, it is important to try to anticipate what is to come in the not-so-distant future, if only to trigger the requisite public debate about the ethics of what is perhaps likely to come. So, in the service of keeping the ethics ahead of the biomedical science, here are my top 10 picks for exciting, likely, troubling, and attention-grabbing issues for the next 10 years. I look forward to the addendums and emendations that are sure to come!

1. GMOs save crops struggling with climate change and beset by plant pests that find climate change advantageous

Anti-GMO sentiment will flip as the world utterly fails to achieve control over climate change. With temperatures rising, droughts increasing, and the climate becoming more turbulent, genetically engineered plants are increasingly the Band-Aid to maintain food supply, expand growing seasons, and battle pests. The “value” of genetic engineering becomes self-evident as farmers and fishermen struggle to maintain yields and famine threatens many parts of the world.

2. IVF clinics do vast bulk of their business making healthier babies for the fertile

A drop in the number of people seeking infertility treatment pushes clinics to offer more services to fertile persons that could help achieve “healthier” offspring. Investors own and control clinics, and they market “better” babies aggressively around the world. Richer families seeking an edge in a highly competitive world increasingly turn to these services, ignoring the protests of some who see the emphasis on “health” as code for eugenics.

3. Efforts at protecting patient privacy are abandoned as benefits from full big data meta-studies take off

More and more benefits in terms of earlier diagnoses, preventive measures, and lifestyle enhancements flow from the use of big data. Increasingly interlinked, big data takes in healthcare information around the world. Privacy is not a priority for a generation that has grown up expecting none. The older generation of civil libertarians who see privacy as vital begins to die off. Laws protecting privacy have proven utterly ineffective, especially as hacking remains widespread and bribing data managers to provide access becomes more common. Laws and legislation affirming privacy begin to be abandoned.

4. First transgender birth occurs thanks to transplanted reproductive organs

The entire female reproductive system—uterus, ovary, fallopian tubes—is now transplantable. Those involved in transitioning their gender will pay money to undergo what is essentially experimental surgery but is not in clinical trials given the commercialization of IVF working with transplant programs. Donor organs are hard to obtain, but the first baby has been born via reproductive system transplantation.

5. Gene editing begins to replace gene therapy as therapeutic modality of choice in embryos, fetuses, newborns, and young children

The safety of gene editing along with greater precision has fueled interest in eliminating—and not just treating—genetic diseases and risk factors. Embryo editing is becoming routine for many conditions, some of which are oriented toward enhancement and improvement. Gene therapies are still in use, but genetic medicine and counseling are shifting toward prevention. Some governments are taking an interest in encouraging gene editing to control the high cost of healthcare and disability services.

6. Synthetic biology revolutionalizes vaccine development

Needles and jabs are gone. Genetically edited viruses can be inhaled, opening a new route for vaccinations and helping us fend off most viral and bacterial infections. These can also be used in animals to reduce reliance on antibiotics. The same technology is beginning to be used to help clean out blood vessels clogged with fatty deposits.

7. Artificial blood is introduced, prompting blood banks to shut down and encouraging medics to stock up

The dream of artificial blood, permitting universal donation, is achieved using synthetic biology, cloning, and better bioincubation. This means safer but more expensive transfusions as viral and bacterial risks fall to zero. Blood matching is rapidly disappearing, as is the need for blood drives and blood collections. In the field, transfusion is becoming routine for a variety of needs including traumatic accidents, gunshot wounds, and injuries caused by combat and terrorism. Poorer nations are desperate to acquire the technology (as they have never been able to achieve safe, adequate blood supplies), but the price is prohibitive. The Gates, Zuckerberg, and Bezos Foundations are under enormous pressure to subsidize cost.

8. Life forms are created from scratch

The mystery of “life” has yielded to biological reductionism. Synthetic biologists are creating functioning microbes from DNA and artificial cell parts. The line between organic and inorganic is found to reside in particular genetic messages. Our understanding of how life might have evolved on earth or elsewhere is greatly enhanced.

9. Hospitals close some units as home-based care and residential care rapidly grow

Increasingly, elderly persons desire care for terminal and chronic conditions at home. Telemedicine, better implantables, and robot-assisted chronic care make this option more attractive and lower in cost than institutional care. The explosion in Alzheimer’s disease and other neurological impairments overwhelms the capacity of hospitals and nursing homes, leading to some closure of units in hospitals and nursing homes. Tax breaks and other incentives have led to the beginning of a shift to more residential/home care.

10. First artificial womb is used to deliver preemie infant at 18 weeks

Scientists and biomedical researchers, having studied artificial wombs in sheep, pigs, and primates, have begun to deploy them at a few academic medical centers for fetuses born before 23 weeks with underdeveloped lungs. The experiments require a reexamination of the concept of “viability,” stoking the ongoing battles over abortion in the United States and elsewhere. Some nations and states could pass laws mandating the use of this new, experimental technology.

Arthur L. Caplan, PhD ( [email protected] ), is the Drs. William F. and Virginia Connolly Mitty Professor of Bioethics and founding head of the Division of Medical Ethics at NYU Robert I. Grossman School of Medicine.

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Trends and hot topics in radiology, nuclear medicine and medical imaging from 2011–2021: a bibliometric analysis of highly cited papers

1 School of Foreign Languages, Central China Normal University, Wuhan, 430000 China

Huiting Zhang

2 MR Scientific Marketing, Siemens Healthineers, Wuhan, 430071 China

3 Department of Medical Imaging, Suizhou Central Hospital, Hubei University of Medicine, No.60 Longmen Street, Jiefang Road, Suizhou, 441399 Hubei China

Associated Data

To spotlight the trends and hot topics looming from the highly cited papers in the subject category of Radiology, Nuclear Medicine & Medical Imaging with bibliometric analysis.

Materials and methods

Based on the Essential Science Indicators, this study employed a bibliometric method to examine the highly cited papers in the subject category of Radiology, Nuclear Medicine & Medical Imaging in Web of Science (WoS) Categories, both quantitatively and qualitatively. In total, 1325 highly cited papers were retrieved and assessed spanning from the years of 2011 to 2021. In particular, the bibliometric information of the highly cited papers based on WoS database such as the main publication venues, the most productive countries, and the top cited publications was presented. An Abstract corpus was built to help identify the most frequently explored topics. VoSviewer was used to visualize the co-occurrence networks of author keywords.

The top three active journals are Neuroimage, Radiology and IEEE T Med Imaging . The United States, Germany and England have the most influential publications. The top cited publications unrelated to COVID-19 can be grouped in three categories: recommendations or guidelines, processing software, and analysis methods . The top cited publications on COVID-19 are dominantly in China . The most frequently explored topics based on the Abstract corpus and the author keywords with the great link strengths overlap to a great extent. Specifically, phrases such as magnetic resonance imaging, deep learning, prostate cancer, chest CT, computed tomography, CT images, coronavirus disease, convolutional neural network(s) are among the most frequently mentioned.

The bibliometric analysis of the highly cited papers provided the most updated trends and hot topics which may provide insights and research directions for medical researchers and healthcare practitioners in the future.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11604-022-01268-z.

Introduction

Citation distributions are extremely skewed. Most scientific papers are seldom cited, if ever, in the subsequent scientific literature while some papers receive an unusually high citation counts [ 1 ]. In the past decade, there has been a growing interest in using highly cited papers as indicators in research assessments. There may be two reasons for this tendency. First, the increasing focus on scientific excellence in science policy in the context of the enormous quantities of scientific outputs makes it imperative to screen out the most successful or influential work. “Many countries are moving towards research policies that emphasize excellence; consequently; they develop evaluation systems to identify universities, research groups, and researchers that can be said to be “excellent” [ 2 ]. Second, for visibility issues, academic professionals are consistently interested in pursuing high citations for their own work and also tend to follow the research with higher citations. In this way, they can stay current regarding research trends and make informed decisions on potential research topics. High citations imply more visibility, generally accompanied by more supports from public or private funders. Therefore, scientific researchers will be very much proud if their publications are selected as highly cited papers (HCPs).

Incites Essential Science Indicators (ESI), an analytic tool provided by Clarivate Analytics for identifying the top-charting research in Web of Science (WoS)-indexed journals, is widely used to evaluate HCPs, providing information such as the countries/regions [ 3 , 4 ], institutes [ 5 ], and researchers [ 6 ], etc. ESI-HCPs, representing the top 1% in each of the 22 ESI subject fields, vary by fields and by years in a 10 years’ rolling. A paper is selected as a HCP only if its citation count exceeds the 1% citation threshold of the corresponding research fields and publication year.

Over recent years, a number of studies have been conducted on HCPs based on data from ESI [ 7 – 9 ]. For example, Ioannidis Boyack et al. surveyed the most-cited authors of biomedical research for their views on their own influential published work [ 9 ]. Aksnes found that HCPs are typically authored by a large number of scientists, often involving international collaboration [ 10 ]. Some studies even try to predict the HCPs by mathematical models [ 11 ], implying “the first mover advantage in scientific publication” [ 12 , 13 ]. That is, the first papers in a field will, essentially regardless of content, receive citations at a rate enormously higher than papers published later.

Bibliometrics, a term coined by Pritchard A [ 14 ], is a statistical method used to evaluate scientific development, determine research impacts, compare research performance and identify emerging fronts [ 15 , 16 ]. There have been many bibliometric studies on natural science or social science as a general field [ 17 , 18 ]. There have also been a few subject-specific ones on computer science [ 19 , 20 ], on applied linguistics [ 21 ], and on operations research and management Science [ 22 ]. In this regard, bibliometrics has been applied to summarize the development of a specific subject, generating valuable information such as the most cited publications/journals and the most frequently explored topics, etc. Such information is of great importance and interest to researchers as well as academic institutions and government/private agencies in making funding and science policy decisions. However, to our knowledge, there has not been one bibliometric study on the specific subject “ Radiology, Nuclear Medicine & Medical Imaging ” (RNMI) , a subject that covers resources on radiation research in biology and biophysics. Of the five broad research areas ( Arts & Humanities, Life Sciences & Biomedicine, Physical Sciences, Social Sciences, technology ) in Web of Science database, Life Sciences & Biomedicine has the most number of subject categorizations (76 in total), implying the complexity and richness as well as importance of this research line. As an important subject area in Life Sciences & Biomedicin e in response to the rapidly evolving healthcare industry, the research productivity in this RNMI has been tremendous. A thorough investigation of the existing literature especially the HCPs will help keep researchers informed about the state of the arts and research trends in this subject.

The purpose of this study is to spotlight the trends and hot topics in the subject category of Radiology, Nuclear Medicine & Medical Imaging with the bibliometric analysis of highly cited papers to help researchers get the most updated information in the future study.

A bibliometric approach was used in the present study to map the HCPs in RNMI in WoS. As one of the biggest bibliometric databases, WoS is the most frequently used database in bibliometric studies [ 23 ]. The methods for data retrieval are described as follows.

We searched in WoS Core Collection at the portal of the University library. We filtered the results by clicking the “ Highly Cited in Field ” trophy icon. We then downloaded all the bibliometric data for further analysis including publication years, authors and affiliations, publication titles, countries/regions, organizations, abstracts, citation reports, etc. After the removal of the publications with incomplete bibliometric information, a total of 1325 HCPs were harvested. The yearly publication distributions of the 1325 HCPs were shown in Figure S1 (Online Resource 1). The data retrieval was completed on 15 December, 2021. We collected the impact factor (IF) of each journal from the 2021 Journal Citation Reports (JCR).Table ​ (JCR).Table1 1 shows the strategies of the retrieval queries.

Retrieval strategies

Three points are to be mentioned here. First, the WoS Core Collection was searched because it boasts as an important bibliometric database which includes literature and citation information indexed in SCIE, SSCI and A&HCI. More importantly, it has been widely used in bibliometric analysis of previous studies both in natural sciences [ 24 , 25 ] and in social sciences [ 21 , 26 ]. Because RNMI belongs to the natural sciences, we restrict the index in SCI-expanded to retrieve the relevant data. Second, only articles and reviews are considered in HCPs selection. There is no need to restrict the document types in our search. Third, the dataset of ESI-HCPs is automatically updated every 2 months to include the most recent 10 years of publications. Therefore, only the papers in the recent decade will be counted as HCPs. There is no need to set the date range.

To identify the most influential papers, we ranked all the HCPs by the Relative Citation Rate (RCR), a new metric that uses citation rates to measure influence at the paper level [ 27 ]. Since the citation count a paper receives is closely associated with the number of years it is published, it is invalid to rank paper impact solely on Raw Citations (RC). Therefore, RCR, recently endorsed by the National Institutes of Health, has been employed here to pinpoint the most highly cited papers. RCR is based on weighting the number of citations a paper receives to a comparison group within the same field [ 28 ]. The icite tool is used here to generate RCR metrics for all the HCPs ( https://icite.od.nih.gov/ ).

Word frequency analysis based on corpus is a bibliometric method to identify hotspots and developmental trend of one domain. In this study, we built an Abstract corpus with all the abstracts of the HCPs. The n -grams (2–4) in the corpus were retrieved and analyzed to detect the most frequently researched topics in the HCPs. The procedures to retrieve the n-grams were described as follows. First, the abstracts of all the 1325 HCPs from the downloaded bibliometric data were saved in separate files in txt. Formats in one folder to create a mini abstract corpus with a total of 299,810 tokens. Second, Anthony’s AntConc, a freeware corpus analysis toolkit for concordancing and text analysis, was used to extract n-grams that include clusters of two to four continuous words [ 29 ]. AntConc is widely used in previous studies [ 16 , 21 , 26 ]. It automatically ranks all the retrieved n-grams in decreasing order. We also generated a list of individual nouns in case of missing some important topics. The reason to exclude the pronouns, modals and many other functional words is that research topics are usually phrases that do not contain these functional words. For topic candidacy, we adopt both frequency (10) and range criteria (10). That is, a candidate n-gram has to appear at least ten times and in at least ten different abstracts for further consideration. The frequency threshold ensures the significance of the candidate topics while the range threshold ensures the topics are not overly clustered in a limited number of papers. In this process, we actually tested the frequency and range thresholds several rounds for the inclusion of all the potential topics. In total, we got 521 nouns, 205 2 g, 39 3 g, and 5 4 g. Third, concerning the list of n-grams and monograms (nouns here), the authors discussed extensively to decide which should be taken as the potential research topics until full agreements were reached.

Besides the word frequency analysis based on the Abstract corpus, we performed knowledge mapping (i.e., network analysis) using VOSviewer ( www.vosviewer.com ), in which we focused on the network and “link strength” between author keywords. Knowledge mapping can be employed to map the scope and structure of the discipline while revealing key research clusters [ 30 ]. Since fractional counting approach assigns co-authored publications fractionally to each author, proper field-normalized results can be obtained [ 31 ]. Therefore, we used fractional counting in our analysis. This process produced the co-occurrence network of the most frequently used author keywords. Knowledge mapping of the author keywords was an important addition to the corpus based investigation of the abstracts.

Main publication venues of HCPs

The top 20 journals with more than 17 HCPs published are listed in Table ​ Table2. 2 . They contributed around 80% of the total HCPs (1039/1325). The highest contribution comes from Neuroimage (207) , followed by Radiology (159) . They are also the only 2 journals with more than 100 HCPs, accounting for almost 30% of the total number of the HCPs, overwhelmingly exceeding the others on the list. As the only Q2 journal (between top 50% and top 25%) among the top five (the other four in the Q1, top 25%) by the Journal Citation Reports (JCR) quantile rankings, Neuroimage tops the list with certain surprise.

Main publication venues of the HCPs ranking in decreasing order

Because the total number of papers published in each journal varies greatly per year and the HCPs are also connected with journal circulations, we divide the total number of papers (TP) in the examined years (2011–2021) with the number of the HCPs to acquire the HCP percentage for each journal (HCPs/TP). As we can see, the top six journals with the highest percentage of the HCPs are Med Image Anal (2.91), IEEE T Med Imaging (2.83) , Radiology (2.67) , Neuroimage (1.91) , J Cardiovasc Magn Reson (1.91), JACC-Cardiovasc Imag (1.75). That implies that papers published in these journals have a higher probability to enter the HCPs list. In terms of the latest journal impact factor (IF) in 2021, the top five journals with the highest IF are JACC-Cardiovasc Imag (14.805), Radiology (11.105), J Nucl Med (10.057), IEEE T Med Imaging (10.048) and Eur J Nucl Med Mol I (9.236) . The number of the HCPs in these journals take up a large share of the total HCPs (over 30%), implying a close relationship between the journal IF and the number of the HCPs in the journal.

Countries distribution

The top 16 productive countries with more than 50 HCPs are presented in Fig.  1 . The USA took the lead with 707 HCPs (53.358%), confirming its leading position as a traditional scientific powerhouse in this subject, followed by Germany (20.302%) and England (19.623%). It is to be mentioned that only three Asian countries enter the top 16 list ( China, South Korea, Japan ). China even boasts the fourth position with 196 HCPs (14.792%). However, scholars from outside the traditional publishing countries need to be more visible for their work in RNMI.

Top 16 countries/regions with the most HCPs

Most influential papers by RCR

During the data processing, we found that the papers on COVID-19 published in the year of 2020 had extremely high RCR compared to papers on other subjects. As an unexpected global epidemic starting in late 2019, COVID-19 ignited research interests from all over the world especially in China where the epidemic was first reported. Many papers got quickly published and cited during this period in response to the urgent needs to find treatments. If we mix the papers, paying no attention to this public health incident, the COVID-19-related papers will take up 75% of the top 20 highly cited papers in terms of RCR (15/20), which was unfair for other non-COVID-19-related papers because of the distorted impact image. Therefore, we produced two lists of ranking: one for the non-COVID-19 papers in Table ​ Table3 3 and one for the COVID-19 papers in Table ​ Table4. 4 . The yearly citation trends of each listed HCP can be seen in Figure S2 (Online Resource 2).

The Top 20 HCPs (Non-COVID-19)

Note: To save space, not full information about the HCPs is given. For the source title, only the first five words were kept if the titles are too lengthy. PMID are provided to locate the papers quickly for those interested. For the authors, only the first author who appeared in the author list was given. For the document type, R means Reviews while A means Articles

The top 10 HCPs (COVID-19)

Table ​ Table3 3 shows some interesting patterns. First, 9 out of the top 20 HCPs were published in Neuroimage , which helps corroborate the findings on the main publication venues. Second, in terms of the document types, reviews (11) slightly outnumber articles (9), which may imply that reviews share the same amount of citation opportunities as the articles in the field of medical studies if not more. Third, three types of research orientations can be discerned from the top 20 HCPs: recommendations or guidelines (#1, 6, 11, 16, 18, 19); processing software (#2, 7, 9); analysis methods (#4, 5, 8, 12, 13, 15, 17, etc.).

The top ten highly cited papers on COVID-19 shows a different picture in Table ​ Table4. 4 . 9 out of the top ten HCPs were published in Radiology , which once again testifies its popularity and importance in the field of RNMI . Ai tao ’s (2020) Correlation of Chest CT and …tops the list with RCR at 703.55, three times more than Roberto M Lang (2015) with RCR at 203.92, which shows the enormous attention paid to this unprecedented epidemic outbreak.

Most frequently explored topics

Table ​ Table5 5 presents the top 33 research topics above the observed frequency of 38. The observed frequency count for each topic in the abstract corpus is included in the brackets. Topics such as magnetic resonance imaging (325), deep learning (191), prostate cancer (162), chest CT (145), computed tomography (141), CT images (121), PSMA PET (119), coronavirus disease (115), convolutional neural network(s) (108) and FDG PET (100) were the top ten most frequently mentioned topics based on the corpus analysis of the abstracts. We grouped the topics into five broad categories, including devices, organs, artificial intelligence (AI), images, and others, according to topic relationships.

Categorization of the most explored research topics

The first group is mainly about the imaging devices in the RNMI field including MRI (396) , CT (484) and PET (279) .

The second group concerns the human organs such as brains (250), prostate (162), heart (160), lungs (153), and breast (93) . Cancer-related phrases (prostate cancer, and breast cancer) were among the top list in frequency. For the brain, topics such as functional connectivity and white matter were more mentioned.

The third group are all related to AI technology ( artificial intelligence, deep learning, machine learning, convolutional neural networks, etc.).

The fourth group is about image information. Image quality is an important focus in MR/CT/PET scanning because it determines whether the images can been used or not. Imaging features can provide more information and are widely used in AI.

Topics in the last group constitute the core concepts in radiology. Radiation therapy is the most important treatment method for cancers. Especially when combined with MRI and CT, precise radiotherapy will be a promising alternative for cancer treatment in the future. As the method for assessing diagnosis performance of quantitative parameters, receiver operating characteristic (ROC) is also the main technology. Contrast agents is the important part of CT and MRI scans. Polymerase chain reaction is the gold standard in the detection COVID-19. It is no wonder that these topics enter the hot topic list because they are closely connected to the topics in other categories.

Author keywords analysis

A total of 2796 keywords were retrieved. We set the minimum number of occurrences of a keyword at 5. Then, 131 keywords meet the threshold. For each of the 131 keywords, the total strength of the co-occurrence links with other keywords were calculated. The top 15 keywords with the greatest total link strength were shown in decreasing order in Table ​ Table6. 6 . VOSviewer classified the 131 keywords into 9 clusters, as shown in Fig.  2 . The link strengths for deep learning, covid-19, mri, machine learning, prostate cancer, computed tomography were 79, 74, 42, 40, 39, 39, respectively. The thickness of the lines which was determined by the frequency of the keywords in HCPs shows the link strength between the keywords.

The top keywords in HCPs

The co-occurrence of author’s keywords

A comparison between the word frequency analysis of the Abstract corpus and the knowledge mapping of the author keywords shows similar research activities, which can be evidenced by the overlapping of the high frequent topics and the author keywords. These hot terms not only reflects the important research trends up to now, but also points the direction for future research in RNMI. For example, AI is gaining increasing popularity in the healthcare industry especially in handling a huge amount of patient data and recognizing complex disease patterns. In the future, AI-based technology is bound to unfold more hidden information from big data and inform healthcare policymakers and clinicians in making effective clinical decisions. Besides, considering the complex functioning of the human brain, the research is multidisciplinary in nature. Therefore, a collaboration across scientific disciplines will better reveal the intricacies of the human brains.

To our knowledge, this is the first comprehensive bibliometric study of Highly Cited Papers (HCPs) in the subject category of RNMI across the years spanning from 2011 to 2021. The results showed that Neuroimage, Radiology, IEEE T Med Imaging, J Nucl Med had the largest number of HCPs published, accounting for about 40% of the total 1325 HCPs. The traditional academic powerhouses in RNMI such as the USA, Germany and England are leading the publications while countries such as China and Italy are catching up. For the top 20 non-COVID-19 HCPs, 3 types of research orientations can be detected: recommendations or guidelines; processing soft wares; analysis methods . Reviews slightly outnumber articles in terms of document types. Among the top ten COVID-19 HCPs published in the year 2020, nine were published in Radiology, and chest CT was the most frequent used term in the paper titles.

It is interesting to find Neuroimage, the only Q2 journal in the top five, tops the list with the most HCPs. Research on human brains is increasing rapidly since the initiation of the WU-Minn Human Connectome Project in America in September 2010, aiming to map macroscopic human brain circuits and their relationship to behavior[ 32 ]. Many countries/regions follow the lead by starting their own brain projects, such as Human Brain Project in European Union, Brain/Minds in Japan, and Brain Science and Brain-Like Intelligence Technology in China. Therefore, topics such as functional connectivity, white matter, brain regions can be found (Table ​ (Table5), 5 ), reflecting the scientific enthusiasm in human brains. The surging research interest in brain functioning in the last decade across the globe stimulated more papers in related journals such as Neuroimage , especially after the initiation of the WU-Minn Human Connectome Project in September 2010. Besides, from January 2020, Neuroimage is an open access journal. Authors who publish in Neuroimage can make their work visible immediately, which might encourage more authors to contribute their work. It can be evidenced by more publications in Neuroimage in 2020 compared to those in previous years.

United States, Germany and England are undoubtedly the most impactful in the research area of RNMI. Historically, western countries, especially the United States, have been at the center of academic publishing, supported by huge investments in scholarly research and technical infrastructure. Besides, because the research in RNMI usually involves highly priced facilities such as MRI scanner, the developed countries with more resources clearly stand in a more advantageous position in research and publishing. It should be noted here that a HCP is usually the joint writing of multiple authors from different institutions and/or countries[ 10 ]. Web of Science will generate all the bibliometric information of the papers, not restricted to the information about the first author or the corresponding author. In other words, all the countries and institutions listed on the HCPs will be treated evenly. In this way, a clearer picture about the HCPs distribution across countries can be painted.

Scientific research has always been driven by practical needs. It comes with no surprise that Roberto M Lang ’s (2015) Recommendations for cardiac chamber quantification [ 33 ] … tops the list with RCR at 203.92. The quantification of cardiac chamber size and function is the cornerstone of cardiac imaging. Jointly written by the American Society of Echo cardiography and the European Association of Cardiovascular Imaging , Roberto M Lang ’s (2015) is the updated recommendations for cardiac chamber quantification that guide the echo cardiographic practice with sweeping popularity. Because COVID-19 was first reported in China, most of the studies during this period were conducted in hospitals or universities in China, which can be easily seen from the top ten HCPs list. Sana Salehi’s (2020) Coronavirus Disease 2019 (COVID-19)… stands as the only HCP among the top ten beyond China (in USA). From the titles, Chest CT emerges as one of the hottest phrases. The fact that most patients infected with COVID-19 had pneumonia and characteristic CT imaging patterns helps explain its frequent use.

A great overlap between the most frequently explored topics and author keywords is identified. The hot topics can be generally grouped into five broad categories: devices, organs, artificial intelligence (AI), images, and others . MRI is the most frequently mentioned phrase. Compared to CT which only shows signal attenuation and has ionizing radiation, MRI can obtain the multi-contract images without ionizing radiation, and is widely used in whole human bodies except the lung. Especially, in the human brain projects, MRI is the main device. However, CT showed greater values in the lung disease than MRI, which can be evidenced by frequent use of CT in the COVID-19 publications. The use of PET (positron emission tomography) scan along with CT in clinical practice increases side by side with publications in this regard which can be seen in such frequent topics as PET CT, PSMA PET, FDG PET . Moreover, the clinical value of PET with MR is also increasing proven. In the future, PET will be an important device in the field of nuclear medicine and radiology.

Besides brain, lung, prostate, heart, and breast are the most concerned organ. According to the World Health Statistics released in 2020, an estimated 41 million people worldwide died of NCDs (noncommunicable diseases) in 2016, equivalent to 71% of all deaths. Four NCDs caused most of those deaths: cardiovascular diseases (17.9 million deaths), cancer (9.0 million deaths), and chronic respiratory diseases (3.8 million deaths), and diabetes (1.6 million deaths) ( World health statistics 2020: monitoring health for the SDGs, sustainable development goals. Geneva: World Health Organization; 2020. ). Of different cancer types, breast cancer, lung cancer, and prostate cancer were the top three most prevalent cancers, according to the latest GLOBOCAN2020 report by the International Agency of Research on Cancer, part of World Health Organization.

In recent years, AI has been a hot theme of modern technology and is creeping into almost every facet of modern life including medical research. Up to now, AI has been actively used in medical images recognition, medical intelligent decision-making, medical intelligent voice, and “Internet plus” medical treatment. As one of the first specialty in healthcare to adopt digital technology, radiology is well positioned to deploy AI for diagnostics due to digital images [ 34 ]. Gulshan first reported that AI could automated detected diabetic retinopathy and diabetic macular edema from over 100 thousand retinal fundus photographs, with high sensitivity and specificity [ 35 ]. In 2017, Golden reported that AI can quickly read photos to diagnose breast cancer with lymph mode metastases, greatly improving the speed of diagnosis [ 36 ]. AI also played an important role in detecting COVID-19 [ 37 – 39 ]. In the future, AI is bound to exert greater influence on the medical field. For example, AI shows great promise in changing treatment models, promoting medicine development, reshaping the medical industry, and even impacting the career paths of the medical practitioners. It is believed that artificial intelligence will bring profound changes to future medical technology and will be a powerful driving force for future medical innovation and reform.

There are several points to be mentioned here as for the most frequently explored topics. Decisions regarding the candidate topics were not easy and involved subjectivity. It was the results of several rounds of discussions from multiple professionals. Some n-grams are discarded because they are too general or not meaningful topics in RNMI. For example, quantitative analysis, high sensitivity, imaging technique and medical image are too general to be included. By meaningful topics, we mean the n-grams can help journal editors and readers to quickly locate their interested fields, as the author keywords such as brain networks, MRI imaging, CT scans. Besides, the examination of the limited 3/4-g and monograms (nouns) revealed that most of them were either not meaningful topics such as cancer detection rate and patients with prostate cancer or they were topics already identified in the 2 g such as weighted MR imaging in MR imaging. Therefore, the final list is mostly 2-g topics.

It should be noted that large numbers of quantitative data have been used here to map the HCPs from different perspectives. Despite the quantitative nature, our study also involves qualitative analysis and hence subjectivity, especially concerning what constitutes the research topics and topic categorization. Given the rapid developments in RNMI, more bibliometric research is needed in the future to help test and enhance the validity and reliability of this research approach and to help keep us accurately informed about the trends in RNMI.

Our study also has some limitations. The subject category of Radiology, Nuclear Medicine & Medical Imaging listed in WoS Categories needs to be further broken down into subcategories and subjects in future analysis. A finer granular subject classification of the research area would have painted a more detailed picture. In additional, the study focuses on the apex of the publishing pyramid in RNMI, the HCPs. And the bibliometric indexes here are all based on the WoS SCI international journals. Although these are the most celebrated and accessible works, some other publications of similar importance or highly localized publications which do not have the chance to enter the list and are not indexed in WoS are not given due attention in our study. This less widely cited research is a rich vein for future study. At last, the study seems to show that the number of citations a review paper receives is higher than that of an original article in RNMI. Therefore, it might be more useful to distinguish the two types of papers in future method design.

In conclusion, our results of the bibliometric analysis provided the updated trends and hot topics in RNMI. And the practitioners and researchers in RNMI can be better aided to locate the relevant literature and keep informed about the hot topics.

Below is the link to the electronic supplementary material.

Acknowledgement

This study was funded by the grant from Humanities and Social Sciences Youth Fund of China, Ministry of Education (MOE) (Grant Number 20YJC740076)

Declarations

The authors declare no conflict of interest.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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