In Optica, Optica Publishing Group’s journal for high-impact research, investigators led by Susumu Noda from Kyoto University in Japan describe their new nonmechanical 3D lidar system, which fits in the palm of the hand. They also show that it can be used to measure the distance of poorly reflective objects and automatically track the motion of these objects.

“With our lidar system, robots and vehicles will be able to reliably and safely navigate dynamic environments without losing sight of poorly reflective objects such as black metallic cars,” said Noda. “Incorporating this technology into cars, for example, would make autonomous driving safer.”

The new system is possible thanks to a unique light source the researchers developed called a dually modulated photonic-crystal laser (DM-PCSEL). Because this light source is chip-based it could eventually enable the development of an on-chip all-solid-state 3D lidar system.

“The DM-PCSEL integrates non-mechanical, electronically controlled beam scanning with flash illumination used in flash lidar to acquire a full 3D image with a single flash of light,” said Noda. “This unique source allows us to achieve both flash and scanning illumination without any moving parts or bulky external optical elements, such as lenses and diffractive optical elements.”

Combining scanning and flash illumination

Lidar systems map objects within view by illuminating those objects with laser beams and then calculating the distance of those objects by measuring the beams’ time of flight (ToF) — the time it takes for the light to travel to objects, be reflected and then return to the system. Most lidar systems in use and under development rely on moving parts such as motors to scan the laser beam, making these systems bulky, expensive and unreliable.

One non-mechanical approach, known as flash lidar, simultaneously illuminates and evaluates the distances of all objects in the field of view with a single broad, diffuse beam of light. However, flash lidar systems can’t be used to measure the distances of poorly reflective objects like black metallic cars due to the very small amount of light reflected from these objects. These systems also tend to be large because of the external lenses and optical elements needed to create the flash beam.

To address these critical limitations, the researchers developed the DM-PCSEL light source. It has both a flash source that can illuminate a wide 30°×30° field of view and a beam-scanning source that provides spot illumination with 100 narrow laser beams.

They incorporated the DM-PCSEL into a 3D lidar system, which allowed them to measure the distances of many objects simultaneously using wide flash illumination while also selectively illuminating poorly reflective objects with a more concentrated beam of light. The researchers also installed a ToF camera to perform distance measurements and developed software that enables automatic tracking of the motion of poorly reflective objects using beam-scanning illumination.

Measuring objects with varying reflectivity

“Our DM-PCSEL-based 3D lidar system lets us range highly reflective and poorly reflective objects simultaneously,” said Noda. “The lasers, ToF camera and all associated components required to operate the system were assembled in a compact manner, resulting in a total system footprint that is smaller than a business card.”

The researchers demonstrated the new lidar system by using it to measure the distances of poorly reflective objects placed on a table in a lab. They also showed that the system can automatically recognize poorly reflective objects and track their movement using selective illumination.

The researchers are now working to demonstrate the system in practical applications, such as the autonomous movement of robots and vehicles. They also want to see if replacing the ToF camera with a more optically sensitive single-photon avalanche photodiode array would allow the measurement of objects across even longer distances.

Researchers from Aarhus University have come closer to answering this question in a large study, which has just been published in the journal Nature Genetics.

Together with national and international partners, the researchers have studied more than six million genetic variants in 38,691 people with ADHD and 186,843 people without ADHD. By this means it has been possible to identify 27 genetic risk variants for the common neurodevelopmental disorder.

Risk genes are expressed in the brain and neurons

The study is ground-breaking, inter alia because it finds more than twice as many risk variants as previous studies have identified.

The term “genetic variants” means specific variations in the DNA code — in this case, variants which are observed more frequently in people with ADHD than in people without the diagnosis. Variants in DNA affect, for example, the degree to which a gene is expressed and subsequently the amount of protein that is encoded by the gene.

By linking the genetic variants — i.e. the variations in DNA — to specific genes, the researchers have gained new knowledge about which tissues and cell types are particularly affected in individuals with ADHD. The study is based on data from the Danish iPSYCH cohort, deCODE Genetics in Iceland and the Psychiatric Genomics Consortium.

Subsequently, the researchers combined the results with existing data on gene expression in different tissues, cell types and brain development stages, and they discovered that genes involved in ADHD have a particularly high level of expression in a wide range of brain tissues and early in brain development — in fact already at the embryonic stage.

“This emphasises that ADHD should be seen as a brain developmental disorder, and that this is most likely influenced by genes that have a major impact on the brain’s early development,” says Professor Ditte Demontis of the Department of Biomedicine at Aarhus University, who is first author of the study.

In addition, the researchers found that the genetics that increase the risk of ADHD particularly affect genes that are expressed in neurons, especially dopaminergic neurons.

“This is interesting because dopamine plays a role in relation to the reward response in the brain, and because a frequently used form of ADHD medicine works by increasing the concentration of dopamine in different brain regions. Our results indicate that the imbalance in dopamine in the brains of people with ADHD is partly attributable to genetic risk factors,” says Ditte Demontis.

Associated with reduced concentration capacity and short-term memory

ADHD is influenced by many common genetic variants, each of which increases the risk slightly, says the professor.

In fact, with the help of advanced statistical models, the researchers have estimated that there are around 7,300 common genetic variants that increase the risk of ADHD. It is particularly interesting that the vast majority of these variants — 84-98 percent — also have an influence on other mental disorders, e.g. autism, depression and schizophrenia.

It has previously been shown that risk variants for ADHD can affect a person’s cognitive abilities.

To investigate this further, the researchers analysed data from an independent dataset, consisting of 4,973 people who had undergone extensive neuro-cognitive tests. By using information from the new study about which variants increase the risk of ADHD, they found in the independent data set that an increased load of ADHD risk variants in the genome of an individual is associated with reduced reading and mathematical abilities, reduced attention and reduced short-term memory.

“The results increase our knowledge of the biological mechanisms underlying ADHD, and they point to specific genes, tissues and cell types involved in ADHD. This knowledge can be used as a starting point for further studies of the disease mechanisms and identification of new drug targets,” explains Ditte Demontis.

And the study must be followed up, she emphasises.

“We have only mapped a small fraction of the common variants that influence ADHD — just 27 of the 7,300 that potentially exist. So there is a need for larger genetic studies,” she says.

International cross-disciplinary collaboration is the way forward

Large international collaborations are crucial to identifying the genetic causes of psychiatric diseases and neurodevelopmental disorders, because to do so requires studies of tens or hundreds of thousands of people with these conditions. Just as in the current ADHD study, there are often 100 or more researchers involved, with different areas of expertise, such as genetics, psychiatry, psychology, epidemiology, molecular biology, statistics, bioinformatics and computer science.

“In order to understand more of the genetic and biological mechanisms, it is important to have even larger studies, involving more people with ADHD,” says Professor Anders Børglum of the Department of Biomedicine, Aarhus University, who is the last author of the study and one of the research directors of the Danish iPSYCH project.

“But it is also important to undertake studies that focus on identifying how the genetic risk variants perturb biological processes in the brain cells (the neurons), and their way of joining up and communicating with each other in the brain. For the latter, both brain cells and early developmental stages of the brain, so-called mini-brains or brain organoids, are currently being examined” he says.

“In worms, flies, and mice, calorie restriction can slow biological processes of aging and extend healthy lifespan” says senior author Daniel Belsky, PhD, associate professor of epidemiology at Columbia Mailman School and a scientist with Columbia’s Butler Aging Center. “Our study aimed to test if calorie restriction also slows biological aging in humans.”

The CALERIE™ Phase-2 randomized controlled trial, funded by the US National Institute on Aging, is the first ever investigation of the effects of long-term calorie restriction in healthy, non-obese humans. The trial randomized 220 healthy men and women at three sites in the U. S. to a 25 percent calorie-restriction or normal diet for two years.  CALERIE™ is an acronym for ‘Comprehensive Assessment of Long-Term Effects of Reducing Intake of Energy’.

To measure biological aging in CALERIE Trial participants, Belsky’s team analyzed blood samples collected from trial participants at pre-intervention baseline and after 12- and 24-months of follow-up. “Humans live a long time,” explained Belsky, “so it isn’t practical to follow them until we see differences in aging-related disease or survival. Instead, we rely on biomarkers developed to measure the pace and progress of biological aging over the duration of the study.” The team analyzed methylation marks on DNA extracted from white blood cells. DNA methylation marks are chemical tags on the DNA sequence that regulate the expression of genes and are known to change with aging.

In the primary analysis Belsky and colleagues focused on three measurements of the DNA methylation data, sometimes known as “epigenetic clocks”. The first two, the PhenoAge and GrimAge clocks, estimate biological age, or the chronological age at which a person’s biology would appear “normal”. These measures can be thought of as “odometers” that provide a static measure of how much aging a person has experienced. The third measure studied by the researchers was DunedinPACE, which estimates the pace of aging, or the rate of biological deterioration over time. DunedinPACE can be thought of as a “speedometer”.

“In contrast to the results for DunedinPace, there were no effects of intervention on other epigenetic clocks,” noted Calen Ryan, PhD, Research Scientist at Columbia’s Butler Aging Center and co-lead author of the study. “The difference in results suggests that dynamic ‘pace of aging’ measures like DunedinPACE may be more sensitive to the effects of intervention than measures of static biological age.”

Our study found evidence that calorie restriction slowed the pace of aging in humans” Ryan said.  “But calorie restriction is probably not for everyone. Our findings are important because they provide evidence from a randomized trial that slowing human aging may be possible. They also give us a sense of the kinds of effects we might look for in trials of interventions that could appeal to more people, like intermittent fasting or time-restricted eating.”

A follow-up of trial participants is now ongoing to determine if the intervention had long-term effects on healthy aging. In other studies, slower DunedinPACE is associated with reduced risk for heart disease, stroke, disability, and dementia.  “Our study of the legacy effects of the CALERIE™ intervention will test if the short-term effects observed during the trial translated into longer-term reduction in aging-related chronic diseases or their risk factors,” says Sai Krupa Das, a senior scientist and CALERIE investigator who is leading the long-term follow up of CALERIE™ participants.

DunedinPACE was developed by Daniel Belsky and colleagues at Duke University and the University of Otago. To develop DunedinPACE, researchers analyzed data from the Dunedin Longitudinal Study, a landmark birth cohort study of human development and aging that follows 1000 individuals born in 1972-73 in Dunedin, New Zealand. Researchers first analyzed the rate of change in 19 biomarkers across 20 years of follow-up to derive a single composite measure of the Pace of Aging. Next, the researchers used machine-learning techniques to distill this 20-year Pace of Aging into a single-time-point DNA methylation blood test. The values of the DunedinPACE algorithm correspond to the years of biological aging experienced during a single calendar year, providing a measure of the pace of aging.

The study was supported by US National Institute on Aging grant R01AG061378 and also utilized resources provided by the CALERIE Research Network (R33AG070455) and the Dunedin Study (R01AG032282). Coauthors received additional support from the American Brain Foundation, and NIH grants P30AG028716, R01AG054840, R33AG070455, CIHR RN439810, R01 AG071717, R03AG071549 U01AG060906.