A Combination of Novel Techniques Solves the Enigma

Using innovative multidisciplinary tools, the research team co-led by Gerard Talavera from the Institut Botànic de Barcelona (IBB, CSIC-CMCNB), Tomasz Suchan from the W. Szafer Institute of Botany, and Clément Bataille, associate professor inthe Department of Earth and Environmental Sciences at the University of Ottawa — with Megan Reich, a postdoctoral researcher from the Department of Biology at uOttawa, Roger Vila and Eric Toro Delgado, scientists from the Institute of Evolutionary Biology (IBE, CSIC-UPF) and Naomi Pierce, a professor of Biology in the Department of Organismic and Evolutionary Biology at Harvard University — embarked on a scientific mission to track the journey and origin of those mysterious Painted Ladies.

First, the research team reconstructed wind trajectories for the period preceding the arrival of these butterflies in October 2013. They found exceptionally favorable wind conditions that could support a transatlantic crossing from western Africa, opening the possibility that those individuals might have flown across the entire ocean.

After sequencing the genomes of these individuals and analyzing them in comparison to populations globally, researchers discovered that the butterflies had a closer genetic relatedness to African and European populations. This result eliminated the likelihood of these individuals coming from North America, thereby reinforcing the hypothesis of an oceanic journey.

Researchers leveraged a unique combination of next-generation molecular techniques. They sequenced the DNA of pollen grains carried by these butterflies. They identified two species of plants that only grow in tropical Africa indicating that the butterflies nectared on African flowers before engaging into their transatlantic journey. They analyzed hydrogen and strontium isotopes in the butterflies’ wings, a chemical signal that acts as a “fingerprint” of the region of natal origin. Combining isotopes with a model of habitat suitability for larval growth revealed potential natal origin in western Europe, possibly France, Ireland, the United Kingdom, or Portugal.

Dr. Bataille underlines the methodological novelty of this study: “It is the first time that this combination of molecular techniques including isotope geolocation and pollen metabarcoding is tested on migratory insects. The results are very promising and transferable to many other migratory insect species. The technique should fundamentally transform our understanding of insect migration.”

“We usually see butterflies as symbols of the fragility of beauty, but science shows us that they can perform incredible feats. There is still much to discover about their capabilities,” emphasizes Roger Vila, a researcher at the Institute of Evolutionary Biology (CSIC-Pompeu Fabra University) and co-author of the study.

Buoyed by the Winds

The researchers assessed the viability of a transatlantic flight by analyzing the energy expenditure for the journey. They predicted that the flight over the ocean, lasting 5 to 8 days without stops, was feasible due to advantageous wind conditions. “The butterflies could only have completed this flight using a strategy alternating between active flight, which is costly energetically, and gliding the wind. We estimate that without wind, the butterflies could have flown a maximum of 780 km before consuming all their fat and, therefore, their energy,” comments Eric Toro-Delgado, one of the article’s co-authors.

The Saharan air layer is emphasized by researchers as a significant aerial route for dispersion. These wind currents are known to transport large amounts of Saharan dust from Africa to America, fertilizing the Amazon. This study now shows that these air currents are capable of transporting living organisms.

The Potential Impact of Migrations in the Context of Global Change

This finding indicates that natural aerial corridors connecting continents may exist, potentially facilitating the dispersal of species on a much larger scale than previously imagined.

“I think this study does a good job of demonstrating how much we tend to underestimate the dispersal abilities of insects. Furthermore, it’s entirely possible that we are also underestimating the frequency of these types of dispersal events and their impact on ecosystems,” comments Megan Reich, a Postdoctoral Fellow at the University of Ottawa who also coauthored the study.

Gerard Talavera, the study’s lead researcher, adds, “Throughout history, migratory phenomena have been important in defining species distributions as we observe them today.”

Researchers emphasize that due to global warming and changing climate patterns, we may witness more notable changes and a potential increase in long-distance dispersal events. This could significantly impact biodiversity and ecosystems worldwide. “It is essential to promote systematic monitoring routines for dispersing insects, which could help predict and mitigate potential risks to biodiversity resulting from global change,” concludes Gerard Talavera.

Several drugs combined into one daily pill for seniors who have trouble remembering to take their medications.

Drugs printed at your local pharmacy at personalized dosages that best suit your health needs.

These are just a few potential advantages of 3D drug printing, a new system for manufacturing drugs and treatments on-site at pharmacies, health care facilities and other remote locations.

In 2015, the Food and Drug Administration approved the first 3D-printed drug, Spritam (levetiracetam), for epilepsy. Several other manufacturers and drug companies are developing their own ones.

But the widespread adoption of 3D drug printing will require stringent quality control measures to ensure that people get the right medication and dosage. Even a tiny mismeasurement of a drug’s ingredient during the printing process could endanger a patient’s health.

In a new research paper, NIST research scientist Thomas P. Forbes assesses various approaches to ensuring that 3D drug printers work as designed. The journal article applies a “quality by design” analysis to evaluate the best procedures and protocols to ensure that 3D printers produce drugs at the correct dosages and with the correct mix of chemicals.

Though various methods exist for remotely printing drugs, Forbes focused on one of the most common: inkjet printers and similar systems that can print personalized medication on demand.

Like inkjet printers in homes, though larger, the printer has nozzles that deposit the drug’s liquified materials, or inks, into tiny wells on a tray or directly into capsules. Through freeze-drying and other processes, the liquid can be turned into a tablet or powder poured into a capsule. It can also be evaporated onto a thin film that dissolves in the mouth.

Forbes’ paper does not make any recommendations. Instead, his research identifies and tests several possible methods and techniques for maintaining quality control in 3D drug printing.

“The most efficient computers are still approximately four orders of magnitude — that’s 10,000 times — higher in energy requirements compared to the human brain for specific tasks such as image processing and recognition, although they outperform the brain in tasks like mathematical calculations,” said UC Santa Barbara electrical and computer engineering Professor Kaustav Banerjee, a world expert in the realm of nanoelectronics. “Making computers more energy efficient is crucial because the worldwide energy consumption by on-chip electronics stands at #4 in the global rankings of nation-wise energy consumption, and it is increasing exponentially each year, fueled by applications such as artificial intelligence.” Additionally, he said, the problem of energy inefficient computing is particularly pressing in the context of global warming, “highlighting the urgent need to develop more energy-efficient computing technologies.”

Neuromorphic (NM) computing has emerged as a promising way to bridge the energy efficiency gap. By mimicking the structure and operations of the human brain, where processing occurs in parallel across an array of low power-consuming neurons, it may be possible to approach brain-like energy efficiency. In a paper published in thejournal Nature Communications, Banerjee and co-workers Arnab Pal, Zichun Chai, Junkai Jiang and Wei Cao, in collaboration with researchers Vivek De and Mike Davies from Intel Labs propose such an ultra-energy efficient platform, using 2D transition metal dichalcogenide (TMD)-based tunnel-field-effect transistors (TFETs). Their platform, the researchers say, can bring the energy requirements to within two orders of magnitude (about 100 times) with respect to the human brain.

Leakage currents and subthreshold swing

The concept of neuromorphic computing has been around for decades, though the research around it has intensified only relatively recently. Advances in circuitry that enable smaller, denser arrays of transistors, and therefore more processing and functionality for less power consumption are just scratching the surface of what can be done to enable brain-inspired computing. Add to that an appetite generated by its many potential applications, such as AI and the Internet-of-Things, and it’s clear that expanding the options for a hardware platform for neuromorphic computing must be addressed in order to move forward.

Enter the team’s 2D tunnel-transistors. Emerging out of Banerjee’s longstandingresearch efforts to develop high-performance, low-power consumption transistors to meet the growing hunger for processing without a matching increase in power requirement, these atomically thin, nanoscale transistors are responsive at low voltages, and as the foundation of the researchers’ NM platform, can mimic the highly energy efficient operations of the human brain. In addition to lower off-state currents, the 2D TFETs also have a low subthreshold swing (SS), a parameter that describes how effectively a transistor can switch from off to on. According to Banerjee, a lower SS means a lower operating voltage, and faster and more efficient switching.

“Neuromorphic computing architectures are designed to operate with very sparse firing circuits,” said lead author Arnab Pal, “meaning they mimic how neurons in the brain fire only when necessary.” In contrast to the more conventional von Neumann architecture of today’s computers, in which data is processed sequentially, memory and processing components are separated and which continuously draw power throughout the entire operation, an event-driven system such as a NM computer fires up only when there is input to process, and memory and processing are distributed across an array of transistors. Companies like Intel and IBM have developed brain-inspired platforms, deploying billions of interconnected transistors and generating significant energy savings.

However, there’s still room for energy efficiency improvement, according to the researchers.

“In these systems, most of the energy is lost through leakage currents when the transistors are off, rather than during their active state,” Banerjee explained. A ubiquitous phenomenon in the world of electronics, leakage currents are small amounts of electricity that flow through a circuit even when it is in the off state (but still connected to power). According to the paper, current NM chips use traditional metal-oxide-semiconductor field-effect transistors (MOSFETs) which have a high on-state current, but also high off-state leakage. “Since the power efficiency of these chips is constrained by the off-state leakage, our approach — using tunneling transistors with much lower off-state current — can greatly improve power efficiency,” Banerjee said.

When integrated into a neuromorphic circuit, which emulates the firing and reset of neurons, the TFETs proved themselves more energy efficient than state-of-the-art MOSFETs, particularly the FinFETs (a MOSFET design that incorporates vertical “fins” as a way to provide better control of switching and leakage). TFETs are still in the experimental stage, however the performance and energy efficiency of neuromorphic circuits based on them makes them a promising candidate for the next generation of brain-inspired computing.

According to co-authors Vivek De (Intel Fellow) and Mike Davies (Director of Intel’s Neuromorphic Computing Lab), “Once realized, this platform can bring the energy consumption in chips to within two orders of magnitude with respect to the human brain — not accounting for the interface circuitry and memory storage elements. This represents a significant improvement from what is achievable today.”

Eventually, one can realize three-dimensional versions of these 2D-TFET based neuromorphic circuits to provide even closer emulation of the human brain, added Banerjee, widely recognized as one of the key visionaries behind 3D integrated circuits that are now witnessing wide scale commercial proliferation.