Gold-DNA nanosunflowers for efficient gene silencing and controlled transformation

Gold-DNA nanosunflowers for efficient gene silencing and controlled transformation
Scheme of self-assembled gold-DNA nanosunflowers for enhanced cellular uptake amount, tunable gene silencing efficacy, and controlled tumor inhibition effect by NIR irradiation. (A) (a) Assembly and disassembly of the large-sized nanostructure (200-nm gold-DNA nanosunflowers) from/to ultrasmall nanoparticles (2-nm Au-POY2T NPs). (b) Representative TEM image of the nanosunflowers. (c) Masterpiece: Sunflowers (Vincent van Gogh, 1889). (B) Left: In vivo tumor retention and penetration of transformable nanosunflowers. Right: Enhanced cellular uptake and controlled oncogene silencing process of the nanosunflowers in vitro. ① Large-sized nanosunflowers were taken up by an MCF-7 cell. ② The nanosunflowers standby in the cell cytoplasm. ③ Upon NIR irradiation, large-sized gold-DNA nanostructures dissociate and release small units (2-nm Au-POY2T NPs) to attack the cell nucleus. ④ The silencing sequence POY2T will bind to the P2 promoter of the c-myc oncogene and down-regulate the c-myc expression of MCF-7 cells, which can be controlled (ON/OFF) and regulated (Low/Medium/High) by the NIR irradiation. Credit: Science Advances, doi: 10.1126/sciadv.aaw6264

Developing an efficient delivery system for enhanced and controlled gene interference-based therapeutics is an existing challenge in molecular biology. The advancing field of nanotechnology can provide an effective, cross-disciplinary strategy to facilitate nucleic acid delivery. In a new report, Shuaidong Huo and colleagues in the interdisciplinary departments of Nanoscience, Interactive Materials, Chemistry and Polymer Research in China, Germany and the U.S. used triplex-forming oligonucleotide sequences coupled to its complementary strand to mediate the self-assembly of ultra-small gold nanoparticles.

The resulting sunflower-like nanostructures showed strong near infrared (NIR) absorption and ability for photothermal conversion. When the scientists irradiated the structures with NIR, the larger nanostructures disassembled to generate ultra-small nanoparticles modified with the c-Myc oncogene sequence to directly target the cancer cell nucleus. Huo et al. controlled gene silencing by synergistically controlling the time of preincubating cells with nanoparticles alongside nanostructure self-assembly (in vitro and in vivo) and the time-frame of NIR irradiation. The study provided a new paradigm to construct efficient and tailored nanocarriers for applications of gene interference and therapeutic gene delivery.

Gene therapy has great potential to treat a variety of diseases and complications including infertility, HIV and cancer. Successful gene therapy to alleviate disease symptoms depend on an efficient gene delivery vehicle or vector. During the process, the gene carrier must cross many biological barriers and cell membranes while escaping endosomal entrapment and nuclease-based degradation. Compared to virus-based delivery strategies, non-viral gene delivery approaches face many challenges during the process of loading and releasing DNA/RNA, targeted delivery and intracellular uptake, including incompatibility relative to immune responses in vivo.

Vigorous efforts in nanotechnology are underway to engineer stable and efficient vehicles for gene transfer to cancer cells. Due to their unique physiochemical properties a number of nanomaterials have emerged for gene delivery. Among them, gold nanoparticles (Au NPs) with specific size and surface properties can overcome obstacles in vivo to become one of the most studied gene carrier systems. However, these strategies have encountered a variety of shortcomings and therefore it is important to establish efficient delivery systems or enhanced and controlled gene therapies.

Self-assembly and testing sunflower-like nanostructures

In the present work, Huo et al. were inspired by nature’s ability to hybridize DNA by engineering DNA-mediated, self-assembled gold DNA nanostructures (approximating 200 nm). The sunflower-like design showed strong NIR absorption and photothermal conversion properties. Upon NIR irradiation, the structures disassembled to liberate ultra-small gold nanoparticles (2 nm, Au NPs) with potential for oncogene silencing, improved cell and nuclei permeability and enhanced transfection efficiency. The scientists synergistically controlled the cell-nanomaterial interactions based on the time of pre-incubation in the lab, followed by time of circulation in vivo and the timeline of irradiation. The experiments facilitated increased cellular uptake, tunable gene silencing efficacy and controlled tumor inhibition. The transformable nanosunflowers provided an excellent model to design nanovehicles for drug delivery with great potential in biomedicine.

Gold-DNA nanosunflowers for efficient gene silencing and controlled transformation
Morphology characterization of the self-assembled nanostructures (nanosunflowers). (A) TEM (200 kV) images of the nanosunflowers with enlarged structural details. (B) Bio-TEM (80 kV) images with enlarged polymer structural details. (C) High-resolution TEM (200 kV) images showing the distribution of ultrasmall NPs on the self-assembled nanostructure. (D) SEM images with enlarged surface topography of the nanosunflowers. Credit: Science Advances, doi: 10.1126/sciadv.aaw6264

Huo et al. first synthesized the two-nanometer Au NPs coated with tiopronin and modified them with thiol-oligonucleotides (SH-POY2T) using an established method of ligand exchange. The 23-nucleotide (nt) POY2T oligonucleotide bound the P2 promoter of the c-myc oncogene to form a triplex structure and downregulate oncogenic c-myc expression. In parallel, they designed and synthesized another single-stranded sequence known as CA to complementarily hybridize to the tail of the POY2T sequence and block its binding to the c-myc oncogene. On completion, the nanostructure self-assembled into sunflower-like structures. The team investigated the nanostructure (200 nm) using transmission electron microscopy (TEM). Additional imaging revealed further details of the DNA moieties of the “sunflower” structure. When the materials scientists used scanning electron microscopy (SEM) to validate the TEM results, they observed consistency between the methods.

They investigated the UV-Vis absorption spectra of the ultrasmall Au NPs prior to DNA-mediated . The monodispersed, individual two-nanometer Au-POY2T NPs showed strong absorption in the NIR region to generate heat under NIR irradiation. Huo et al. credited the observed strong NIR absorbance to close interparticle spacing and nonuniform spatial distribution of individual NPs within the larger nanostructure. They tested the heat response of the self-assembled nanostructures under NIR irradiation and noted the melting point of the complementary DNA sequences (POY2T and CA) to approximate 41 degrees C, dissociating half of the duplex structure between complementary DNA sequences. Huo et al. selected 10 minutes as the optimal time for NIR irradiation in the study.

Gold-DNA nanosunflowers for efficient gene silencing and controlled transformation
Photothermal property and disassembly behavior study of the self-assembled nanostructures. (A) Visible absorption spectra of 2-nm core-sized NPs and 200-nm self-assembled nanostructures. a.u., absorbance unit. (B) Temperature response of self-assembled nanostructures, upon NIR irradiation, dispersed in water and cell culture medium. Mean values ± SD, n = 3. (C) Temperature rise of self-assembled nanostructures, upon NIR irradiation, dispersed in water and cell culture medium. (D) Change of maximum absorbance (767 nm) of 2-nm core-sized NPs and 200-nm self-assembled nanostructures upon NIR irradiation. (E and F) TEM observation of disassembly behavior of 200-nm self-assembled nanostructures before (top) and after (bottom) NIR irradiation (808 nm, 10 min). (G) Hydrodynamic diameter of (a) monodispersed 2-nm Au-POY2T NPs and size change of the 200-nm nanosunflowers before (b) and after (c and d) NIR irradiation for different time periods (3 and 10 min). Credit: Science Advances, doi: 10.1126/sciadv.aaw6264

Disassembly behaviour of the self-assembled nanostructures and proof-of-conceptThe scientists hypothesized the self-assembled nanostructures would shrink and disassemble into individual ultrasmall Au-POY2T NPs. After 10 minutes of NIR irradiation, the maximum absorption (767 nm) of nanostructures markedly decreased to disassemble the sunflower structure. They followed the experiments before and after NIR irradiation with TEM observations and used particle size analysers to understand the disassembly process and size transformation of the nanostructures up to six nanometers in size and confirmed the optimal suitability of the 10-minute timeline.

Huo et al. applied NIR irradiation to MCF-7 cells treated with self-assembled gold DNA nanostructures and tested their cellular uptake in vitro as proof-of-concept. They determined the cellular internalization of Au-POY2T (2 nm) across diverse incubation times and quantified their cellular uptake using inductively coupled plasma mass spectroscopy (ICP-MS) and previous methods. They noted increased internalization after six hours of incubation compared to 24-hour incubation timelines. They did not observe inhibitors of endocytosis to influence Au-POY2T NP uptake, suggesting the involvement of an alternative path such as membrane fusion.

Understanding gene silencing behavior of the self-assembled nanostructures

Gold-DNA nanosunflowers for efficient gene silencing and controlled transformation
Controlled nucleus localization and gene silencing study in vitro of the self-assembled nanostructures. (A) Schematic of the in vitro cell experimental setup for the controlled NP nucleus localization and gene regulation study. (B) Number of 2-nm Au-POY2T NPs localized in the MCF-7 cell nucleus with treatment of ① individual 2-nm Au-POY2T NPs, ② 200-nm nanosunflowers, and 200-nm nanosunflowers with NIR irradiation (10 min) after different preincubation times (③ 1, ④ 3, ⑤ 6, and ⑥ 12 hours). Mean values ± SD, n = 3. Statistical differences were determined by two-tailed Student’s t test; *P < 0.05 and **P < 0.01. (C) Confocal observation of distribution of fluorescein isothiocyanate–labeled nanosunflowers (green) before (top) and after (bottom) NIR irradiation in MCF-7 cells. Nucleus was labeled by 4′,6-diamidino-2-phenylindole (blue). (D) Bio-TEM image of the localization of large-sized nanosunflowers (top, red arrow) in the cytoplasm and distribution of released small NPs (bottom, blue arrow) in cytoplasm and nucleus after NIR irradiation in MCF-7 cells. (E) Cytotoxicity evaluation of MCF-7 cells with treatment of 200-nm nanosunflowers after NIR irradiation (after a period of preincubation time: 1, 3, 6, and 12 hours, respectively) compared to control, 2-nm Au-TIOP NPs, POY2T sequence, CA sequence, 2-nm Au-POY2T NPs, 200-nm nanosunflowers without NIR irradiation, and NIR exposure only. All the concentrations of treatments were at or equal to 1 μM in POY2T sequence and were tested after a total of 24 hours of incubation. Mean values ± SD, n = 3. Statistical differences were compared with the treatment group of ① individual 2-nm Au-POY2T NPs determined by two-tailed Student’s t test; *P < 0.05 and **P < 0.01. (F) C-myc mRNA level determined by real-time PCR after different treatments as described above. Mean values ± SD, n = 3. Statistical differences were determined by two-tailed Student’s t test; **P < 0.01 and ***P < 0.001. (G) C-myc protein levels determined by Western blot and (H) corresponding quantitative histogram after different treatments as described above. GAPDH, glyceraldehyde phosphate dehydrogenase. Credit: Science Advances, doi: 10.1126/sciadv.aaw6264

After enhanced cellular uptake of self-assembled nanostructures in vitro, the research team investigated the distribution of nanoparticles within the cell nuclei using “standby” and “attack” strategies after NIR triggering. For this, they extracted cell nuclei after incubation, for ICP-MS analysis after NIR irradiation across diverse periods of incubation (one, three, six and 12 hours). They noted that the pre-incubation period largely affects nanoparticle internalization within the cell nucleus, and the researchers regulated Au-POY2T NPs in the cell nucleus based on the time of pre-incubation and NIR irradiation.

Huo et al. also investigated NIR-irradiation controlled therapeutic effects of nanosunflowers using cell viability tests; they observed oncogene silencing to increase markedly (80 percent) and kill more cancer cells. The research team controlled the therapeutic impact effectively by changing the timeline of pre-incubation and irradiation efficiently. The results supported a superior ability of the transformable nanosunflowers to silence the c-myc oncogene and oncoprotein. The scientists controlled the gene silencing process by tuning pre-incubation timelines prior to NIR irradiation.

Controlling tumor growth inhibition using self-assembled nanosunflowers

To test the controllable anti-tumor efficiency of nanosunflowers in vivo, the scientists first investigated their blood compatibility to confirm good blood biocompatibility. The research team then established the MCF-7 tumor model using the BALB/c nude mice, allowed the tumor volumes to reach 50 mm3 and randomly divided the animals into nine groups and treated them with 1000 µl of varying POY2T formulations. After each injection, they irradiated the animal groups with NIR lasers for 10 minutes to reach a local temperature above 41 degrees C.

Gold-DNA nanosunflowers for efficient gene silencing and controlled transformation
Controlled tumor growth inhibition study of the self-assembled nanostructures. (A) The MCF-7 tumor BALB/c nude mice model was established at day 0. After tumors were ready, the mice were randomly divided into nine groups and treated with 100 μl of various formulations (equivalent to 10 μM in POY2T sequence; group ① with 2-nm Au-POY2T NPs and groups ②, ③, ④, ⑤, and ⑥ with 200-nm nanosunflowers) at days 9, 12, and 15. In groups ③, ④, ⑤, and ⑥, the tumors were irradiated with a NIR laser for 10 min at 1, 3, 6, and 12 hours after each intravenous injection. Saline, NIR only, and POY2T were used as control groups. The (B) body weights and (C) tumor volumes were measured every 3 days. Scale bar, 1 cm. After the mice were sacrificed at day 24, all tumors were (D) isolated and (E) weighted, respectively. Mean values ± SD, n = 4. Statistical differences were determined by two-tailed Student’s t test; *P < 0.05, **P < 0.01, and ***P < 0.001. (Photo credit: Ningqiang Gong, National Center for Nanoscience and Technology, China.) (F) Hematoxylin and eosin staining images of organs including the heart, liver, spleen, lung, kidney, and tumor after different treatments. Scale bar, 200 μm. Credit: Science Advances, doi: 10.1126/sciadv.aaw6264

Of note, mice treated with the nanosunflower-treated group and irradiated at 12 hours showed the most significant anti-tumor effects, indicating efficient delivery of gene silencing units into the tumor site. After 24 days, Huo et al. sacrificed the animals, isolated the tumors and weighed them to demonstrate nanosunflower based NIR-controlled tumor growth inhibition in vivo. Based on histological studies, the team showed the treatment significantly reduced tumor growth and did not affect the morphology of other organs. The results verified the therapeutic efficiency and lack of side effects for nanosunflowers and NIR therapy.

In this way, Shuaidong Huo and colleagues designed, developed and optimized nanoagents for effective anti-tumor therapy. They engineered self-assembled sunflower-like nanostructures to act as multiparticle carriers loaded with many ultrasmall therapeutic units. Upon NIR irradiation, the nanostructures dissociated to release swarms of small NPs to target the cell nucleus. In tumor-bearing mice, the large sunflowers passively targeted the tumor site followed by NIR irradiation to transform the tumor genetic composition and shrink it. The research team aim to improve transfection efficiency and provide a blueprint for controllable gene silencing at tumor sites using transformable gene interference carriers for intricate theranostics at the level of the single cell.

Explore further

Thermo-triggered release of a genome-editing machinery by modified gold nanoparticles for tumor therapy

More information: Shuaidong Huo et al. Gold-DNA nanosunflowers for efficient gene silencing with controllable transformation, Science Advances (2019). DOI: 10.1126/sciadv.aaw6264Reinhard Waehler et al. Engineering targeted viral vectors for gene therapy, Nature Reviews Genetics (2007). DOI: 10.1038/nrg2141

N. L. Rosi. Oligonucleotide-Modified Gold Nanoparticles for Intracellular Gene Regulation, Science (2006). DOI: 10.1126/science.1125559

© 2019 Science X Network

Science just totally rewrote the story of human evolution (again)

The earliest humans could have lived in what is now northern Botswana, close to the remains of an enormous lake

Noctiluxx / Getty

In the last three decades, scientists have uncovered around half of the 20 known human ancestors. But when it comes to where the first Homo sapiens lived, things start to get a little blurry.

One group of researchers, however, claim they’ve narrowed in on the exact region. Modern humans originated around 200,000 years ago in northern Botswana, according to new research published in the scientific journal Nature. The group narrowed down the spot where humans evolved to the the Makgadikgadi–Okavango palaeo-wetland, south of the Zambezi river.

Researchers collected DNA from Khoe-San people in southern Africa, who represent the earliest human maternal lineages, and from people who don’t identify as Khoe-San but who the researchers predicted also carried the lineages.

They analysed the DNA fibres in more than 1,200 mitochondrial genomes. We only inherit mitochondrial DNA from our mothers, so it doesn’t change much across generations. The researchers focused on L0 mitochondrial DNA, a genome found on the first branch in the earliest lineage of all modern humans’ maternal ancestors.

They worked with a geologist and climate physicist to understand what the climate, land and geology was like at this time period, and found that there was a substantial population of L0 on the Zambezi river 200,000 years ago, and that multiple Khoe-San sub-lineages were the predominant human population in the world then.

The region used to be Lake Makgadikgadi, which ran from northern Namibia across northern Botswana into Zimbabwe. It would have been the biggest lake in Africa today, the researchers say, and survived for around for 200 million years before shifting tectonic plates broke it up and a wetland formed in its place.

The breaking up of the lake – researchers think – increased humidity and opened strips of lush animal and plant life that allowed populations to migrate northeast and southwest after surviving there for 700,000 years.

However, some experts warn that any claims about the origins of humans must investigate the whole genome, as the mitochondria makes up a very small percentage of our genome, and only represents our direct maternal line, says Carina Schlebusch, associate professor of human evolution at Uppsala University in Sweden.

“It doesn’t represent all of our other potential ancestors we could’ve had,” she says. “So genetic variation can only be captured by the rest of our chromosomes.” The ancestors of mitochondrial lineages were not the only people living in Africa 200,000 years ago, and might not have transmitted the rest of their DNA, says Eleanor Scerri, professor and independent group leader at the Pan African Evolution Research Group at the Max Planck Institute for the Science of Human History.

“Reconstructing deep ancestry from mitochondrial DNA is like trying to reconstruct a language from a handful of words, whereas using whole genome or nuclear DNA is like trying to reconstruct a dead language after hearing it being spoken for a day,” she says. The researchers chose to look at mitochondrial genomes because this is the most accurate way to determine timelines while whole genome data is lacking, and see where a lineage appeared.

Eva Chan, one of the study’s authors and senior research officer of human comparative and prostate cancer genomics at the Garvan Institute, says the origins of our ancestors is a hotly debated topic, and with more data, the theories will change, “But all our evidence points to this palaeo-wetland as the birthplace of all humans today.”

“We could include sequences of the whole genome, but there are still limitations to computer power, and at the moment we could only compare the whole genome of a few individuals.” The paper contradicts some recent findings suggesting humans originated in other parts of Africa. For example, research analysing the male-inherited Y chromosome suggests the earliest modern humans could have emerged in west Africa, not southern Africa.

But a reliable argument for human origin would need to account for far more than just genetics, says Scerri. “The paper ignores a swathe of fossil and archaeological evidence supporting an older origin for our species,” she says. James Cole, principal lecturer in archaeology at the University of Brighton, says archaeological evidence in different fossils across Africa throws into question the study’s basic findings. “You might get the impression that human evolution story started 200,000 years ago, but we know from fossil and archaeological records that Homo sapiens’ evolution starts around 300,000 years ago.”

This includes partial skull and lower jaw remains, stone tools and evidence of fire uncovered in Morocco, north Africa, after only previously finding evidence in south and east Africa. While the new study helps us further understand where we came from, it also highlights how complex our evolution has been, says Cole.

“Nexus of populations spring up all over place – this study shows a really strong one around 200,000 years ago that have genetically survived in today’s human population, but there will be others.”

“We knew human evolution was complicated from archaeology and fossil records, but we didn’t know how complicated it was until palaeontologists started to shine a torch on dark masses of complexity and highlight strands we can pull out and see where we came from,” says Cole.

The paper has reignited the argument that modern humans didn’t originate from any one place, but multiple groups shaped who we are today, and the whole African continent could be the origin of our species.

In a widely-praised paper published last year, Scerri argues that a mixture of genetic traits evolved across different regions in Africa. Jon Marks, professor of Anthropology at the University of North Carolina, says this is his “go-to idea” when teaching human origins in Africa, rather than, “Trying to pinpoint where the first person with a chin and forehead lived”.

But aside from mounting evidence to support a continent-wide origin theory, there’s another reason scientists are rejecting the theory that modern humans came from one place. The new paper relies on the assumption that the Khoe-San people have stayed in one place for hundreds of thousands of years. It mentions anatomically modern humans without having studied bones, Marks points out, and the link between mitochondrial DNA from 200,000 years ago and the emergence of anatomically correct humans at the same time is unknown. In fact, he adds, there may be no relationship between the two.

The authors have made a good case that the earliest mitochondrial DNA was in southern Africa 200,000 years ago, he says, but how do we know that the people sampled in the research haven’t moved around in the last 200,000 years?

“That’s a lot of time to be staying in the same place,” Marks says. Some researchers see the argument that any contemporary population represents the earliest modern human as problematic, especially one that may have been widespread in the past.

“Accepting these results means accepting that the Khoe-San are evolutionary relicts who have neither changed nor moved geographically for tens or even hundreds of thousand years, Scerri says. “Do we really still have to point out how factually incorrect and ethically problematic such a view is, in 2019?”

Is this brain cell your ‘mind’s eye’?

Credit: CC0 Public Domain

No-one knows what connects awareness—the state of consciousness—with its contents, i.e. thoughts and experiences. Now researchers propose an elegant solution: a literal, structural connection.

‘Content circuits’ within the cortex are plugged into ‘switchboard circuits’ that allocate awareness, says the theory, via  called L5p neurons.

Writing in Frontiers in Systems Neuroscience, one group offers evidence—and caveats. Their challenge to experimentalists: if  requires L5p neurons, all brain activity without them must be unconscious.

State vs. contents of conscious

Most neuroscientists chasing the neural mechanisms of consciousness focus on its contents, measuring changes in the brain when it thinks about a particular thing—a smell, a memory, an emotion. Quite separately, others study how the brain behaves during different conscious states, like alert wakefulness, dreaming, deep sleep or anesthesia.

Most agree the two are indivisible: you can’t think or feel or experience anything without being aware, nor be ‘aware’ of nothing. But because of the divided approach, “nobody knows how and why the contents and state of consciousness are so tightly coupled,” says Dr. Jaan Aru, neuroscientist at Humboldt University, Berlin, and lead author of the new theory.

Separate circuits

The divide created between state and contents of consciousness is anatomical.

Our conscious state is thought to depend on the activity of so-called ‘thalamo-cortical’ circuits. These are connections between neurons in the cortex, and neurons in the thalamus—a thumb-sized relay center in the middle of the brain that controls information inflow from the senses (except smell). Thalamocortical circuits are thought to be the target of general anesthesia, and damage to these neurons due to tumors or stroke often results in coma.

In contrast, functional brain imaging studies locate the contents of consciousness mostly within the cortex, in ‘cortico-cortical’ circuits.

The missing link?

Aru and colleagues believe that L5p neurons are uniquely placed to bridge the divide.

“Thalamo-cortical and cortico-cortical circuits intersect via L5p neurons,” explains Aru. “Studies tracing these cells under the microscope suggest they participate in both circuits, by exchanging connections with both thalamus and cortex.”

Functional brain studies suggest these cells may indeed couple the state and contents of consciousness. Cellular-level brain imaging in mice shows that L5p neurons respond to a sensory stimulus (air puff to the leg); that this response increases when the animal is awake; and that it is strongest by far when the animal reacts to the stimulus (moves its leg).

“We can’t tell what the mouse is thinking,” concedes Aru. “But if we assume that it reacts only when it is conscious of the stimulus, then this study demonstrates the interaction between the state [wakefulness] and contents [sensory experience] of consciousness in L5p neurons.”

The assumption is consistent with a similar mouse study. This one went further, showing that directly activating the stimulus-responsive L5p neurons (e.g. with drugs) makes the animal react to a weaker sensory stimulus—and sometimes without any stimulus.

“It’s as if the mouse experiences an illusory stimulus; as if L5p stimulation creates consciousness,” Aru adds.

Testing the theory

The theory is a first iteration that needs refinement, stresses Aru.

“Our goal here is to convince others that future work on the mechanisms of consciousness should specifically target L5p neurons.”

Nevertheless, this general arrangement could account for some well-known quirks of consciousness.

For example, the processing delay of this long relay—from cortico-cortical circuit to thalamo-cortical and back again via L5p neurons—could explain why rapid changes of stimuli often escape conscious perception. (Think subliminal messages spliced into video.)

One feature of this phenomenon is ‘backward masking’: when two images are presented briefly in rapid succession (50-100 ms), only the second image is consciously perceived. In this case, posits Aru, “by the time the stimulus completes the L5p-thalamus-L5p relay, the second image has taken over early cortical representation and steals the limelight lit by the first image.”

The theory could also help explain why we usually have little conscious insight into some  processes, like planning movement or even syntax.

“All  that does not (sufficiently) involve L5p  remains unconscious,” predicts Aru.

Therein lies the key to testing this exciting theory.

Explore further

Waking up the visual system

More information: Jaan Aru et al, Coupling the State and Contents of Consciousness, Frontiers in Systems Neuroscience (2019). DOI: 10.3389/fnsys.2019.00043
Provided by Frontiers

Electrek has uncovered a previously unseen Tesla concept made by the lead designer of the upcoming Tesla ‘cyberpunk’ Pickup truck and it looks like it could give us some hints.

We know a lot about Tesla’s plans for its electric pickup truck thanks to comments from CEO Elon Musk.

Earlier this year, he said that the Tesla Pickup truck will cost less than $50,000 and ‘be better than a Ford F150’.

The CEO revealed some planned features, like an option for 400 to 500 miles of range, Dual Motor All-wheel-drive powertrain with dynamic suspension, as well as ‘300,000 lbs of towing capacity’.

But when it comes to the design of the Tesla Pickup truck, Musk’s comments have been more confusing.

The CEO shocked some when he said that the Tesla Pickup Truck will have a ‘really futuristic-like cyberpunk Blade Runner’ design without explaining what that meant other than saying that ‘it won’t be for everyone’.

On top of the comments not being clear, Musk didn’t really help anyone when he released a very cryptic teaser image for the pickup truck during the Model Y unveiling earlier this year.

Most people didn’t even understand which part of the electric pickup truck was shown by Tesla in the teaser image.

Some amateur designers tried to interpret what it would look like based on the teaser image and Musk’s comments, but the CEO said that he hadn’t seen one render that looks like what Tesla is working on.

We now have a new render, but it’s not just any fan render.

Electrek found out that Tesla designer Sahm Jafari is behind the concept for Tesla’s “Cyberpunk Truck”.

Jafari got hired by Tesla out of the Art Center College of Design in California.

He interned at Tesla while completing his degree and Electrek has uncovered one of his designs meant for Tesla while studying at the prestigious design school that is particularly interesting.

It’s called the ‘Tesla Model Zero’ (pictures via

Obviously, it’s not a pickup truck. Jafari wrote that he meant it as a car positioned under the Model 3:

“A car that slots under Model 3 with the goal of making the electric lifestyle accessible to all. The Model Zero strengthens the brand image toward the entry-level market and opens up the doors to sustainable commuting to nearly anyone looking to get into a new vehicle.”

But some of the design accents of the ‘Tesla Model Zero’ could give us some clues of Jafari’s work on Tesla’s “Cyberpunk Truck”.

For example, the front-end that runs in a straight line all the way up the windshield looks similar to the teaser image released by Tesla:

Musk confirmed that the teaser was the front-end of the Tesla pickup truck.

In order for the Tesla Pickup to achieve a long-range as Musk promised, it will have to either have an incredible battery capacity or be significantly more energy-efficient than the average truck.

An elongated front-end like that could help improve aerodynamic performance and ultimately the efficiency of a larger vehicle like a pickup.

The concept also looks fairly futuristic and the CEO has said several times that the Tesla Pickup looks futuristic.

Although, he also said that it looks ‘cyberpunk’ and “Blade Runneresque” and Jafari’s concept doesn’t have many “cyberpunk” design accents.

Tesla is expected to unveil its pickup truck concept next month (November 2019), which also happens to be when the events of the Blade Runner movie happened.

It was also set in Los Angeles, where Tesla often launches its new vehicles.

Genetic variations linked to oxygen drops during sleep

October 24, 2019
NIH/National Heart, Lung and Blood Institute
Researchers have identified 57 genetic variations of a gene strongly associated with declines in blood oxygen levels during sleep. Low oxygen levels during sleep are a clinical indicator of the severity of sleep apnea, a disorder that increases the risk of heart disease, dementia, and death.

Researchers have identified 57 genetic variations of a gene strongly associated with declines in blood oxygen levels during sleep. Low oxygen levels during sleep are a clinical indicator of the severity of sleep apnea, a disorder that increases the risk of heart disease, dementia, and death. The study, published today in the American Journal of Human Genetics, was funded by the National Heart, Lung, and Blood Institute (NHLBI), part of the National Institutes of Health.

“A person’s average blood oxygen levels during sleep are hereditary, and relatively easy to measure,” said study author Susan Redline, M.D., senior physician in the Division of Sleep and Circadian Disorders at Brigham and Women’s Hospital, and professor at Harvard Medical School. “Studying the genetic basis of this trait can help explain why some people are more susceptible to sleep disordered breathing and its related morbidities.”

When we sleep, the oxygen level in our blood drops, due to interruptions in breathing. Lung and sleep disorders tend to decrease those levels further, and dangerously so. But the range of those levels during sleep varies widely between individuals and, researchers suspect, is greatly influenced by genetics.

Despite the key role blood oxygen levels play in health outcomes, the influence of genetics on their variability remains understudied. The current findings contribute to a better understanding, particularly because researchers looked at overnight measurements of oxygen levels. Those provide more variability than daytime levels due to the stresses associated with disordered breathing occurring during sleep.

The researchers analyzed whole genome sequence data from the NHLBI’s Trans-Omics for Precision Medicine (TOPMed) program. To strengthen the data, they incorporated results of family-based linkage analysis, a method for mapping genes that carry hereditary traits to their location in the genome. The method uses data from families with several members affected by a particular disorder.

“This study highlights the advantage of using family data in searching for rare variants, which is often missed in genome-wide association studies,” said James Kiley, Ph.D., director of the Division of Lung Diseases at NHLBI. “It showed that, when guided by family linkage data, whole genome sequence analysis can identify rare variants that signal disease risks, even with a small sample. In this case, the initial discovery was done with fewer than 500 samples.”

The newly identified 57 variants of the DLC1 gene were clearly associated with the fluctuation in oxygen levels during sleep. In fact, they explained almost 1% of the variability in the oxygen levels in European Americans, which is relatively high for complex genetic phenotypes, or traits, that are influenced by myriad variants.

Notably, 51 of the 57 genetic variants “influence and regulate human lung fibroblast cells, a type of cell producing scar tissue in the lungs,” said study author Xiaofeng Zhu, Ph.D., professor at the Case Western Reserve University School of Medicine. This is important, he said, because “Mendelian Randomization analysis, a statistical approach for testing causal relationship between an exposure and an outcome, shows a potential causal relationship between how the DLC1 gene modifies fibroblasts cells and the changes in oxygen levels during sleep.”

This relationship, Kiley added, suggests that a shared molecular pathway, or a common mechanism, may be influencing a person’s susceptibility to the lack of oxygen caused by sleep disordered breathing and other lung illnesses such as emphysema.

Story Source:

Materials provided by NIH/National Heart, Lung and Blood InstituteNote: Content may be edited for style and length.

Journal Reference:

  1. Jingjing Liang, Brian E. Cade, Karen Y. He, Heming Wang, Jiwon Lee, Tamar Sofer, Stephanie Williams, Ruitong Li, Han Chen, Daniel J. Gottlieb, Daniel S. Evans, Xiuqing Guo, Sina A. Gharib, Lauren Hale, David R. Hillman, Pamela L. Lutsey, Sutapa Mukherjee, Heather M. Ochs-Balcom, Lyle J. Palmer, Jessica Rhodes, Shaun Purcell, Sanjay R. Patel, Richa Saxena, Katie L. Stone, Weihong Tang, Gregory J. Tranah, Eric Boerwinkle, Xihong Lin, Yongmei Liu, Bruce M. Psaty, Ramachandran S. Vasan, Michael H. Cho, Ani Manichaikul, Edwin K. Silverman, R. Graham Barr, Stephen S. Rich, Jerome I. Rotter, James G. Wilson, Susan Redline, Xiaofeng Zhu. Sequencing Analysis at 8p23 Identifies Multiple Rare Variants in DLC1 Associated with Sleep-Related Oxyhemoglobin Saturation LevelThe American Journal of Human Genetics, 2019; DOI: 10.1016/j.ajhg.2019.10.002

Cite This Page:

NIH/National Heart, Lung and Blood Institute. “Genetic variations linked to oxygen drops during sleep.” ScienceDaily. ScienceDaily, 24 October 2019. <>.

Tesla On Track To Release “Feature Complete” Full Self Driving Solution In 2019

October 23rd, 2019 by 


Tesla opened up about its progress on its fully autonomous driving solution, dubbed Full Self Driving, on its Q3 2019 earnings call today. CEO Elon Musk tentatively said that, “it still does appear that we will still be in Early Access release of Full Self Driving by the end of this year.”

Red Model 3 Tesla Charging Station JRR | CleanTechnica

The news did not come with his usual dose of full assurance and made it clear that while Full Self Driving is clearly under active development, the ability for Tesla to deliver it as a product by the end of this year is a bit of a stretch. His caution is well placed, as Full Self Driving (FSD) must bridge a number of life and death scenarios for it to move into production. Identifying and stopping at red lights, stop signs, yield signs, and more can all result in fatalities if not delivered perfectly. There is no room for failure in these areas.

Navigating in parking lots and along unmarked or poorly marked neighborhoods is also extremely challenging compared to the relatively benign environments of freeways, merges, on-ramps, and off-ramps.

A Financial Windfall

Delivering Full Self Driving is a massive financial opportunity for Tesla looking forward, but also allows it to realize a boatload of revenue on cars that have already been sold. Looking ahead, Tesla is aggressively looking to make money from FSD. Furthermore, deferred revenue from the FSD features is a liability Tesla is increasingly able to turn into revenue (for a while). In the Q3 2019 earnings letter, Tesla said, “We also expect to gradually release nearly $500M of accumulated deferred revenue tied to Autopilot and Full Self Driving features.”

The opportunity is not just for Tesla, but for owners as well. On the earnings call today, Musk spoke to the massive increase in value — “that transition, that sort of flipping of the switch from a car that is not a robotaxi to robotaxi will probably be the largest step change increase in asset value in history, by far.” For many existing Tesla owners, banking on Musk’s bold proclamations for the future is nothing new, but some feel burned on the thousands of dollars put down years ago for Tesla’s elusive Full Self Driving feature.


What Does “Feature Complete” Look Like?

It must be a bit of a relief that Musk is promising to deliver a “feature complete” FSD by the end of this year to early adopters. That is surely encouraging, but the switch to belief from disbelief will ultimately flip for real when Tesla puts its money where its mouth is and delivers FSD to the first customers.

But what does a “feature complete” FSD solution really look like? I’m glad you asked, because that was one of the questions on the call today. Elon unpacked it like this:

“Feature complete means the car is able to drive from one’s house to work most likely without interventions. It will still be supervised, but it will be able to drive. It will fill in the gap from low-speed autonomy … you have low-speed autonomy with Summon, you’ve got high-speed autonomy on the highway, and you have intermediate-speed autonomy which really just means traffic lights and stop signs. Feature complete means it will likely be able to do that without intervention, without human intervention, but it will still be supervised.”

It is clear that Tesla has to solve everything from the beginning and end of a drive with its Smart Summon and Smart Park solutions. It is unclear how many steps it will take Tesla to implement that. In the end, all of these actions will eventually merge into a valet-type product that will park and retrieve a vehicle from a parking lot or parking space. Autopilot has been working on freeways for ages now, with Navigate on Autopilot integrating freeway driving with a destination from the navigation system for an experience that is all-but autonomous today.

When the solution is finally stitched together from a parking space all the way to the garage, though, that is just the first step in the other half of the journey for Tesla’s Full Self Driving solution. “There’s the three major levels to autonomy,” Musk said on the conference call. “There’s the car being able to be autonomous, but requiring supervision and intervention at times. That’s feature complete.” Even then, the car won’t be able to do everything all the time. “It doesn’t mean every scenario, everywhere on earth. It means most of the time.”

That’s the point Tesla hopes to achieve by the end of this year, or in the next few weeks, for “early access program” members. At that point, it will take some time for Tesla to refine the system, sharpening its skills into a finely tuned solution that can do anything, anywhere — the second step of a three-step process, or as Musk put it, “Then there’s another level which is from a Tesla standpoint where we think it is safe enough to be driven without supervision.”

Ultimately, Tesla and owners can decide what they are comfortable with and Tesla will bring that data to regulators to hopefully reach the third and final step in the process at the appropriate time. “The third level would be when regulators are also convinced the car can be driven autonomously without supervision,” Musk said. “Those are three different levels.” For now, the ball is in Tesla’s court as it works to stitch its end-to-end FSD solution together. The future is anything but certain, but it is clear that Tesla continues to be on a tear to deliver the fully autonomous driving system that will drive the company — and society — into the future of transport.

Organoids Don’t Accurately Model Human Brain Development

A new study suggests that growing in a stressful environment prevents “brains-in-a-dish” from growing in the same way as their in vivo counterparts.

Oct 23, 2019

A human brain organoid

Brain organoids, small pieces of the human cerebral cortex grown in the lab, are becoming valuable scientific tools. By modeling the growth of brain cells and structures, these “brains-in-a-dish,” which are self-organizing tissues generated from skin or blood cells that are reprogrammed into stem cells, can allow scientists to examine early development and the processes underlying neurodevelopmental diseases.

Despite their potential, organoids still have some critical limitations. In a study presented this week at the Society for Neuroscience meeting in Chicago, Arnold Kriegstein, a stem cell biologist at the University of California, San Francisco, and his team demonstrate that human brain organoids don’t accurately recapitulate all aspects of development. After comparing cells from organoids to those from normally developing tissue, his team reports that organoids have altered gene expression patterns and lack the cellular diversity in found in the human brain.

The Scientist spoke to Kriegstein about the study and its implications.

The Scientist: Why did you decide to conduct this study?

Arnold Kriegstein: We had been working with organoids for a number of years. We’ve used them to model neurodevelopmental disorders and found that to be very useful. In parallel, we’ve been doing a cell census of the developing human brain—doing single-cell RNA sequencing and capturing the full diversity of cell types at key stages during human brain development. That gave us a roadmap against which we could actually benchmark our organoids and see if they were really being faithful to their in vivo counterparts.

We knew that morphologically, some subtypes of cells in the organoids didn’t fully resemble their normal counterparts, but we wanted a deeper dive into just how similar or different they were. In addition, people have made the claim that some of the organoid cell types—even though they don’t distribute, migrate, or layer quite the way they normally do [in vivo]—represent accurate models of their counterparts.

TS: What were the first hints that the organoids might not be recapitulating human cells?

Instead of having multiple subtypes of a certain cell, you have a kind of pan-identity without those really interesting subdivisions of gene patterns that we see in normal development.

AK: I’m especially interested in the neural progenitors, the cells that actually generate the neurons—there are several subtypes that we’ve identified in the normally developing human brain and also among other non-human primates. We were struck that, in our organoids, we had very few of these cell types, even though they were making neurons. Some of these progenitors are key intermediate steps on the way to making specific subtypes of cells. So we started looking there.

We took our organoids and dissociated them into their single-cell components, then used two different methods to actually identify the gene transcriptome of each individual cell—that is, all the RNA molecules that are being transcribed into proteins or signaling factors. Those gave us a fingerprint of the genetic identity of each cell. We already had a dataset from primary tissue, so we were able to not only identify the cell type, but also the stage of maturation.

With that in hand, we went in and looked very carefully at how these cells matured and how they compared to their counterparts in vivo.

TS: What were the most important differences that emerged in your study?

AK: The good news is, the major categories of cell types are reproduced in the organoids. And this has been reported by other labs as well. The bad news is, when you probe more deeply, you’ll see that there are blended gene expression patterns that are not seen in normally developing cells.

To give you an example, in normal tissue, [progenitor cells] don’t express mature neuronal genes, they only express genes that are appropriate for progenitors. In the organoids, we found those same cell types also express some neuronal genes, some of them in very abnormal combinations.

The other thing we noticed is, in the normally developing brain, there’s a really beautiful diversity of cell types and subtypes. That diversity is dramatically reduced in the organoids. Instead of having multiple subtypes of a certain cell, you have a kind of pan-identity without those really interesting subdivisions of gene patterns that we see in normal development.

TS: So from a bird’s-eye view things look similar, but once you dig deeper there seem to be differences.

AK: And you don’t have to dig too deep to see the differences.

I should mention that we have some idea about why the cells aren’t as precise as they should be. The organoids, across all protocols, show a very enhanced level of metabolic stress. . . . This is very different from what we see in normal tissues. We wondered whether the stress itself might contribute to the lack of gene identity.

We explored that in two ways. First, we took cells that were normal—that is, cells that were developing in the normal [human] brain—dissociated them, and put them into organoids. (Editor’s note: The cells were obtained from post-mortem human tissue.) We noticed that within two weeks or so, they demonstrated increased stress, just like the organoid cells. More interesting perhaps, when we looked more deeply at their gene expression patterns, they also had a degraded identity that started to resemble the problem that we noticed in the cells that were generated from the [human] organoids.

Then, we took the organoid cells and grafted them into the brain of the developing mouse. We reasoned that was a more normal environment, and if there was something in the tissue culture environment that was causing the stress, putting them into an environment that was more normal might relieve that stress. In two weeks or so, we saw that the cells had normalized, that the stress levels were drastically reduced. And over time, the cell identity improved as well.

This was a very encouraging sign. It means that the limitations of these organoids are potentially reversible. If the correct culture conditions are met, we might be able to reduce the stress and improve the fidelity of the cells.

TS: If it turns out that the differences are really important, does that suggest people might have to go back and redo studies that have been done already? 

AK: Yes. Right now, as you survey the field, you’ll notice there’s a lot of heterogeneity. Not everybody has been able to reproduce everyone else’s findings. There’s variability, even with the same protocol in different labs.

Some of the disease phenotypes that have been reported haven’t been reproduced or sometimes, there are even opposite results in different laboratories for the same disease. I think part of this variability might have to do with features that are overlooked, for example, the stress that I mentioned. We’d like to get models that are better able to do what everyone wants—namely, model disease and normal development.

TS: The subject of brain organoids often brings up the question of whether these lab-grown tissues might one day develop sentience—and the ethical implications of that. What are your thoughts on this? 

AK: I think it’s appropriate to think about that. But first, I think everyone should realize that we’re very far away from anything like that at the present time. These cells are not actually normal cells—they’re unlikely to function quite the way normal cells would. They also represent a small fraction of the cell types that are in the normal cerebral cortex—and not only do you not have quite the same elements, but you certainly don’t have them in the right circuits.

Besides that, they also don’t have sensory input. And then of course, you’d have to have a certain mass of tissue. These little fragments that people are making are a tiny fraction of the cortex. There are several hurdles along the way before we can begin to think of something that could possibly be an ethical concern.

See “As Brain Organoids Mature, Ethical Questions Arise

Editor’s note: The interview was edited for brevity. 

Diana Kwon is a Berlin-based freelance journalist. Follow her on Twitter @DianaMKwon.

Tesla Pickup Truck On Track To Be Unveiled In Just Weeks

At this point, it seems Tesla and Musk will stick with the original plan.

Pickup trucks are the biggest segment of the US auto market, so the appearance of an electric option will be a big, big deal – perhaps the EV adoption tipping point we’re all waiting for. FordGM and startup Rivian all have electric pickups in various stages of development, but Tesla is the trend-setter, and these companies and many others will be watching Tesla’s unveiling ceremony closely.

  • This article comes to us courtesy of EVANNEX (which also makes aftermarket Tesla accessories). Authored by Charles Morris. The opinions expressed in these articles are not necessarily our own at InsideEVs.

Above: The mysterious pickup truck teaser from Tesla (Source: Tesla)

When Tesla unveiled Model 3 in 2016, the downpour of advance reservations brought a flash flood of publicity to the EV industry. As Electrek recently noted, Tesla didn’t trumpet the reservation numbers after its most recent unveilings (Model Y, the Roadster and the Tesla Semi). Will it do so after the pickup launch? An impressive number could inspire other automakers by demonstrating how much pent-up demand there is for a plug-in pickup.

So far, the most intriguing thing we know about the planned pickup is that it “won’t look like a normal truck,” as Elon Musk told the Ride the Lightning podcast in August. Many artistically inclined Tesla fans have tried their hands at visualizing what it will look like, but they don’t seem to be getting warmer, judging by a recent Musk tweet: “Cybertruck doesn’t look like anything I’ve seen bouncing around the Internet. It’s closer to an armored personnel carrier from the future.”

Above: Musk says that Tesla’s pickup will be “more functional” than a Ford F-150 and boast performance better than a Porsche 911 (YouTube: DPCcars)

Musk has said the Tesla truck will be available with 300,000 pounds of towing capacity and up to 400 to 500 miles of range, and that he’s holding firm on a starting price under 50 grand: “It’s got to be like $49,000 starting price max. Ideally less. It just can’t be unaffordable. There will be versions of the truck that will be more expensive, but you’ve got to be able to get a really great truck for $49,000 or less.”

Another major milestone for electromobility may be at hand: Elon Musk seems to be getting better at holding to deadlines. In a recent tweet to a fan, he said the unveiling ceremony will take place in November, as planned.


This article originally appeared in Charged. Author: Charles Morris. Sources: Ride the LightningElectrek

  • InsideEVs Editor’s Note: EVANNEX, which also sells aftermarket gear for Teslas, has kindly allowed us to share some of its content with our readers, free of charge. Our thanks go out to EVANNEX. Check out the site here.

Elon Musk predicts Tesla’s Model Y will outsell all of its other 3 vehicles combined

Tesla Model Y

Tesla’s Model Y hasn’t begun production, but CEO Elon Musk predicts it will easily outsell the electric-car maker’s first three vehicles.

“I’ve actually recently driven the Model Y release candidate, and I think it’s going to be an amazing product and be very well received,” the billionaire said on a conference call after Tesla’s breakout earnings on Wednesday evening. “I think it’s quite likely to — this is just my opinion, but I think it will outsell S, X, and 3, combined.”

Musk also told investors and analysts on the call that Tesla has moved its production plans for the crossover forward, from fall 2020 to the summer.

“There may be some room for improvement there, but we’re confident about summer 2020,” he said, adding later that this timeline referred to “volume production” of 1,000 units per week.

The new model, which was unveiled in  at the company’s annual meeting, could also help Tesla sustain its return to profitability with higher average selling prices than the Model 3, Tesla Chief Financial Officer Zach Kirkhorn said on the call.

Shares of Tesla surged as much as 20% overnight, pointing to the stock’s biggest gain in six years when markets open Thursday morning if the gains hold.

“There was plenty for the bulls to feed on,” Christopher Eberle, an analyst at Nomura Instinet, said in a note to clients after the earnings report, citing the pull forward of Model Y production, the China factory timeline, and plans to release a new version of Tesla’s solar roof. The firm has a neutral rating on the stock.

“We remain constructive on Tesla’s longer-term opportunity, given the company’s leadership in both hardware and software development and integration,” he said.

Extracting hidden quantum information from a light source

Extracting hidden quantum information from a light source
The total image or direct intensity image is obtained by the accumulation of light on the camera. With the technique, researchers are able to separate the quantum image of the “dead cat,” and then subtract this image to the total image to obtain the classical image of the “alive cat.” Credit: University of Glasgow/H. Defienne

Current super-resolution microscopes or microarray laser scanning technologies are known for their high sensitivities and very good resolutions. However, they implement high light power to study samples, samples that can be light sensitive and thus become damaged or perturbed when illuminated by these devices.

Imaging techniques that employ  are increasing in importance nowadays, since their capabilities in terms of resolution and sensitivity can surpass classical limitations and, in addition, they do not damage the sample. This is possible because quantum  is emitted in , and it uses the property of entanglement to reach lower light intensity regimes.

Now, even though the use of quantum light and quantum detectors has been experiencing a steady development in past years, there are still a few problems that need to be solved. Quantum detectors are themselves sensitive to classical noise, noise which may end up being so significant that it can reduce or even cancel out any kind of quantum advantage over the images obtained.

Thus, launched a year ago, the European project Q-MIC has gathered an international team of researchers with different expertise who have come together to develop and implement quantum imaging technologies to create a quantum enhanced microscope that will be able to go beyond capabilities of current microscopy technologies.

In a study recently published in Sciences Advances, researchers Hugo Defienne and Daniele Faccio from the University of Glasgow and partners of the Q-MIC project, have reported on a new technique that uses image distillation to extract quantum information from an illuminated source that contains both quantum and classical information.

In their experiment, the researchers created a combined  of a “dead” and “alive” cat by using two sources. They used a quantum source trigged by a laser to create entangled pairs of photons, which illuminated a crystal and passed through a filter to produce an infrared image (800nm) of a “dead cat,” or what they refer to as the “quantum cat.” In parallel, they used a classical source with a LED to produce the image of an “alive cat.” Then, with an optical setup, they superimposed both images and sent the combined image to a special CCD camera known as an electron-multiplied charge coupled device (EMCCD).

With this setup, they were able to observe that, in principle, both sources of light have the same spectrum, average intensity, and polarisation, making them indistinguishable from a single measurement of the intensity alone. But, while photons that come from the coherent classical source (the LED light) are uncorrelated, the photons that come from the quantum source ( pairs), are correlated in position.

By using an algorithm, they were able to use these photon correlations in position to isolate the conditional image where two photons arrive at neighbouring pixels on the camera and retrieve the “quantum illuminated” image alone. Consequently, the classical “alive cat” image was also retrieved after subtracting the quantum image from the direct total intensity image.

Another surprising issue from this method is that the researchers were also able to extract reliable  even when the classical illumination was ten times higher. They showed that even when the high classical illumination decreased the quality of the image, they were still able to obtain a sharp image of the shape of quantum image.

This technique opens a new pathway for quantum imaging and quantum enhanced microscopes that aim to observe ultra-sensitive samples. In addition, the results of this study show that this technique could be of utmost importance for quantum communications. The ability to mix and extract specific information carried by both quantum and classical light could be used for encryption techniques and encoding information. In particular, it could be used to hide or encrypt information within a signal when using conventional detectors.

As Prof. Daniele Faccio, comments, “This approach brings a change in the way we are able to encode and then decode information in images, which we hope will find applications in areas ranging from microscopy to covert LIDAR.”

Explore further

Creating different kinds of light with manipulable quantum properties

More information: Hugo Defienne et al, Quantum image distillation, Science Advances (2019). DOI: 10.1126/

Journal information: Science Advances
Provided by ICFO