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Pediatrician, Medical Innovator, Educator — Dr. Jamie Wells, MD, FAAP — Director, Research Science Institute (RSI), Center for Excellence in Education, Massachusetts Institute of Technology (MIT) — Professor, Drexel University School of Biomedical Engineering, Science and Health Systems.


Dr. Jamie L. Wells, MD, FAAP, is an Adjunct Professor at Drexel University’s School of Biomedical Engineering, Science and Health Systems, where she has been involved in helping to spearhead the nation’s first-degree program focused on pediatric engineering, innovation, and medical advancement.

Dr. Wells is an award-winning Board-certified pediatrician with many years of experience caring for patients. With her BA with Honors from Yale, and her MD from Jefferson Medical College, Philadelphia, PA, she has served as a Clinical Instructor/Attending at NYU Langone, Mt. Sinai-Beth Israel and St. Vincent’s Medical Centers in Manhattan.

Archaea are more than just oddball lifeforms that thrive in unusual places — they turn out to be quite widespread. Moreover, they might hold the key to understanding how complex life evolved on Earth. Many scientists suspect that an ancient archaeon gave rise to the group of organisms known as eukaryotes, which include amoebae, mushrooms, plants and people — although it’s also possible that both eukaryotes and archaea arose from some more distant common ancestor.


As scientists learn more about enigmatic archaea, they’re finding clues about the evolution of the complex cells that make up people, plants and more.

“Clearly AI is going to win[against human intelligence]. It’s not even close,” Kahneman told the paper. “How people are going to adjust to this is a fascinating problem.”

Of course, and the reaction, right up to the last minute will be: “No way Man!!! there will be new jobs these crazy Ai’s cant do!”


Artificial intelligence will be beating humans — outworking if not entirely outmoding them — in plenty of functions as the future approaches. Here’s why.

There goes the Coder Camps.


IBM has announced Project CodeNet, a large dataset that aims to help teach AI how to understand and even write code.

Project CodeNet was announced at IBM’s Think conference this week and claims to be the largest open-source dataset for code (approximately 10 times the size of the closest.)

CodeNet features 500 million lines of code, 14 million examples, and spans 55 programming languages including Python, C++, Java, Go, COBOL, Pascal, and more.

In a major breakthrough, researchers at Massachusetts General Hospital (MGH) have discovered how amyloid beta—the neurotoxin believed to be at the root of Alzheimer’s disease (AD)—forms in axons and related structures that connect neurons in the brain, where it causes the most damage. Their findings, published in Cell Reports, could serve as a guidepost for developing new therapies to prevent the onset of this devastating neurological disease.

Among his many contributions to research on AD, Rudolph Tanzi, Ph.D., vice chair of Neurology and co-director of the McCance Center for Brain Health at MGH, led a team in 1986 that discovered the first Alzheimer’s disease gene, known as APP, which provides instructions for making protein precursor (APP). When this protein is cut (or cleaved) by enzymes—first, beta secretase, followed by gamma secretase—the byproduct is amyloid beta (sometimes shortened to Abeta). Large deposits of amyloid beta are believed to cause neurological destruction that results in AD. Amyloid beta formed in the brain’s axons and nerve endings causes the worst damage in AD by impairing communication between nerve cells (or neurons) in the brain. Researchers around the world have worked intensely to find ways to block the formation of amyloid beta by preventing cleavage by beta secretase and gamma secretase. However, these approaches have been hampered by safety issues.

Despite years of research, a major mystery has remained. “We knew that Abeta is made in the axons of the brain’s nerve cells, but we didn’t know how,” says Tanzi. He and his colleagues probed the question by studying the brains of mice, as well as with a research tool known as Alzheimer’s in a dish, a three-dimensional cell culture model of the disease created in 2014 by Tanzi and a colleague, Doo Yeon Kim, Ph.D. Earlier, in 2013, several other MGH researchers, including neurobiologist Dora Kovacs, Ph.D. (who is married to Tanzi), and Raja Bhattacharyya, Ph.D., a member of Tanzi’s lab, showed that a form of APP that has undergone a process called palmitoylation (palAPP) gives rise to amyloid beta. That study indicated that, within the neuron, palAPP is transported in a fatty vesicle (or sac) known as a lipid raft. But there are many forms of lipid rafts.

The National Center of Excellence in Mass Spectrometry Imaging at NPL, in collaboration with the University of Surrey and Ionoptika Ltd reveal latest findings showing how a single fingerprint left at a crime scene could be used to determine whether someone has touched or ingested class A drugs.

In a paper published in Royal Society of Chemistry’s Analyst journal, the consortium reveal how they have been able to identify the differences between the fingerprints of people who touched cocaine compared with those who have ingested the drug—even if the hands are not washed. The science behind the advance is the spectrometry imaging tools applied to the detection of cocaine and its metabolites in fingerprints.

In 2020 researchers were able to determine the difference between touch and ingestion if someone had washed their hands prior to giving a sample. Given that a suspect at a crime scene is unlikely to wash their hands before leaving fingerprints, these new findings are a significant advantage to crime forensics.

In nature, scents emitted by plants attract animals such as insects. However, scents are also used in the industry, for example in the production of perfumes and aromas. In order to achieve a reliable, quick, and objective discrimination of mint scents in particular, researchers at KIT (Karlsruhe Institute of Technology) embarked on an interdisciplinary collaboration and developed an electronic nose with an artificial sense of smell. This E-nose achieves high precision in recognizing different mint species, which makes it a suitable tool for applications ranging from pharmaceutical quality control to the monitoring of mint oil as an environmentally friendly bioherbicide.

“So far, scientists were able to identify an estimated 100000 different biological compounds through which neighboring plants interact with each other or control other organisms, such as insects,” says Professor Peter Nick from the Botanical Institute of KIT. “These compounds are very similar in plants of the same genus.” A classic example from the plant world is mint, where the different varieties produce with very species-specific scents. Industrial quality control of mint oil, in particular, is subject to strict legal regulations in order to prevent adulteration, is time-consuming, and requires a great deal of expertise, the scientist explains. A new “electronic nose” equipped with sensors made from combined materials will support this process.

The continued growth of wireless and cellular data traffic relies heavily on light waves. Microwave photonics is the field of technology that is dedicated to the distribution and processing of electrical information signals using optical means. Compared with traditional solutions based on electronics alone, microwave photonic systems can handle massive amounts of data. Therefore, microwave photonics has become increasingly important as part of 5G cellular networks and beyond. A primary task of microwave photonics is the realization of narrowband filters: The selection of specific data, at specific frequencies, out of immense volumes that are carried over light.

Many photonic systems are built of discrete, separate components and long optical fiber paths. However, the cost, size, and production volume requirements of advanced networks call for a new generation of microwave photonic systems that are realized on a chip. Integrated microwave photonic filters, particularly in silicon, are highly sought after. There is, however, a fundamental challenge: Narrowband filters require that signals are delayed for comparatively long durations as part of their processing.

“Since the is so fast,” says Prof. Avi Zadok from Bar-Ilan University, Israel, “we run out of chip space before the necessary delays are accommodated. The required delays may reach over 100 nanoseconds. Such delays may appear to be short considering daily experience; however, the optical paths that support them are over ten meters long. We cannot possibly fit such long paths as part of a silicon chip. Even if we could somehow fold over that many meters in a certain layout, the extent of optical power losses to go along with it would be prohibitive.”