Category: Science

Artificial in nature, human-engineered cells can give a new turn to the “human race”. Cells, as we know, are the basic building blocks of a living organism. And, scientists are now using stem cells to create human cells with biological components. Equipped with proper tech, these biological entities could evolve into human-like beings. 

Natural human cells serve as the body’s building blocks, absorb nutrients from meals, transform those nutrients into energy, and perform certain functions. The problem is that our complex human body consists of 37.2 trillion cells. So, it is almost impossible to mimic that exact structure. However, it is not mandatory to imitate the human body. An artificial being could exist and live well with ten complex cells made for them.

To create such a complex entity, many new technologies and methods ask being explored and discovered. Engineers are always exploring different ways to use stem cells in their experiments. In 2008, for example, British researchers claimed that they had created embryos and stem cells using human cells and the egg cells of cows, but said such experiments would not lead to hybrid human-animal babies or even direct medical therapies.

Another example of human-animal hybrid embryos is the “Human-Pig Hybrid,” a contentious move that many expect to be the first step toward creating artificial humans.

In another work, published on Cell.com, scientists claimed that they had successfully grown monkey embryos containing human cells for the first time — the latest milestone in a rapidly advancing field that has drawn ethical questions. The team injected monkey embryos with human stem cells and watched them develop.

However, the scientific community has always been divided on the issue.

Like all the other scientific breakthroughs and technology, we must first be careful about the consequences of this movement, as it can turn “revolutionary.” The main debate is on whether or not this technique should be used to produce real people.

Despite any ethical and other controversies, scientists are continuing with research to create lives. A recent study, published in the journal Cell Stem Cell by Professor Vincent Pasque and his colleagues at KU Leuven, used stem cells to create new human cells in the lab, possibly marking the beginning of making artificial humans.

The new cells resemble their natural counterparts in early human embryos very closely. As a result, scientists are now better able to understand what happens right after an embryo implants in the womb.

If everything goes according to plan, a human embryo implants in the womb seven days after fertilization. At that point, the embryo is no longer available for study due to ethical and technological limitations. To study human development in a dish, scientists have already developed stem cell models for various embryonic and extraembryonic cell types.

Extraembryonic mesoderm cells are a specific type of human embryonic cell, and Vincent Pasque’s team at KU Leuven has developed the first model for such cells. According to Professor Pasque, these cells generate the first blood in an embryo, help to attach the embryo to the future placenta and play a role in forming the primitive umbilical cord.

In humans, this type of cell appears at an earlier developmental stage than in mouse embryos, and there might be other important differences between species. “That makes our model especially important: research in mice may not give us answers that also apply to humans,” said Pasque.

The scientists used human stem cells, which can still grow into every type of cell in an embryo, to make the model cells. The new cells are an excellent model for that cell type since they closely resemble their natural counterparts in human embryos. Pasque expressed hope that the new model would also help to clarify medical issues such as issues with fertility, miscarriages, and developmental disorders.

“You don’t make a new human cell type every day,”  Pasque said, and also asserted that they are very excited because now they can study processes that normally remain inaccessible during development. “The model has already enabled us to find out where extraembryonic mesoderm cells come from,” continued Pasque.

The birth of a new human life would be something incredible. As humans, we are genetically complex beings and can be defined by many traits, millions of DNA base pairs, and all that goes with them. As mentioned earlier, an artificial being would not necessarily mimic our body, brain structure, traits, etc. even if it started from a human embryo. Creating something artificial that is similar in terms of abilities in volume but not in shape sounds unreal.

Keeping in mind all these possible changes in the human race, wouldn’t it be more important to discuss the possibilities before they actually turn into realities?

The idea of creating an artificial human race is not new; it has been debated for a while.

In 2019, for example, scientists developed a new type of life, and this achievement marks a major shift in the science of synthetic biology.

Earlier this year in July, researchers developed a nano-robot made solely of DNA to study biological processes. You could be pardoned for thinking it was science fiction. But it is the focus of significant research conducted at the Structural Biology Center in Montpellier by professionals from Inserm, CNRS, and Université de Montpellier. This extremely cutting-edge “nano-robot” could make it possible to analyze mechanical forces at microscopic scales in greater detail, which are vital for many biological and pathological processes.

Speaking about the latest research published in the journal Cell Stem Cell by Professor Vincent Pasque and his colleagues at KU Leuven, the new model cells aid in the study of early embryonic development. Furthermore, this study moves the field of stem cell research forward as researchers are now able to study processes that typically remain inaccessible during development.

Pasque’s team has demonstrated that it is possible to create a new variety of human cells in the laboratory. The development process will likely lead the research to first create artificial human organs and then gradually an artificial human body. It is unlikely that creating a new human cell will be limited to assisting us in dealing with medical challenges.

Key Points:

• Studies have shown that white noise can hasten your normal sleep-wake cycle.

• Pink noise has more power at lower frequencies and less at higher frequencies, making it deeper.

• Brown noise has greater bass in the lower frequencies due to the change in energy or power.

• Pediatricians suggest keeping any white noise machines at least 7 feet away from your baby’s crib.

If you’re here to find a way to “see” noise, you are not in luck. White noise is random noise that has a flat spectral density—that is, the noise has the same amplitude, or intensity, throughout the audible frequency range (20 to 20,000 hertz). It got its name “white noise” because it’s analogous to white light, which is a mixture of all visible wavelengths of light.

White noise blocks out other sounds and has been shown to signal to the brain that it is time to sleep. Your brain will learn to associate white noise with sleep more quickly the more often you listen to it. Studies have been shown to improve the accuracy of pure sounds. According to studies, white noise can hasten your normal sleep-wake cycle.

My bedtime routines cause me a significant amount of stress. I’ve spent a great deal of time reading up on this topic in the literature, carefully testing out various methods. I’ve finally discovered methods that have helped me, and I can now impart my experience in this article.

White noise may assist with bedtime rituals, but it doesn’t merely improve sleep. Additionally, it generally improves people’s moods and gives them more self-assurance to take on difficulties and problems throughout the day. White noise will enhance their cognitive skills, discipline, and ability to form positive habits.

There are more colors besides “white” that are related to noise. For instance, pink noise contains audible frequencies, with lower frequencies increasing and higher frequencies decreasing. Deep and even sound is generated. Examples comprise:

-Powerful wind 
-Waves, crashing on the beach
-Leaves, rustling
-Rain, beating down

All audible to the human ear, noise frequencies are included in both pink noise and white noise. However, white noise contains all frequencies with equal distribution. Whereas, pink noise has more power at lower frequencies and less at higher frequencies, making it deeper.

The only sound type named for a person, Robert Brown, rather than a color, is brown noise.

White noise and brown noise both produce sounds at random, but in brown noise, frequency increases as energy decreases and vice versa. Keep in mind that white noise is the sum of all frequencies with equal energy. It has greater bass in the lower frequencies due to the change in energy or power, which makes brown noise different. This varies from pink noise in a subtle sense because pink noise loses power as the frequency of its notes rises.

Without a doubt, all three of them enhance your capacity to sleep. Which, though, is the best?

White noise masks outside sounds in a similar way to pink noise. But because it includes all frequencies, white noise may be more effective at keeping out sleep-inducing noises.

According to research, sleep interruption is even worse than having no sleep. When Johns Hopkins University School of Medicine assistant professor of psychiatry and behavioral sciences, Patrick Finan, the study’s lead author, compared the mood ratings of the three groups, he found that both interrupted and short-sleepers experienced drops in positive mood after the first night. But on the following nights, the short sleepers did not—they stayed at around the same level they had reported after the first night—while the interrupted sleepers continued to report falling good feelings.

Regardless of what the participant’s scores on the negative mood scale were, this decline in positive mood still occurred. According to Finan, a lack of sleep may decrease a happy mood more than it can enhance negative emotions.

People who regularly hear traffic at night are more likely to have heart disease and take sleep medicines. But this only partially improves their sleep. White noise reduces the influence of noise, enabling you to sleep longer and deeper and reducing the need for sedatives.

We must meet two equally important goals while trying to fall asleep: falling asleep quickly and staying asleep. If you wake up after 20 minutes, it can be unpleasant and hard to get back to sleep for the required amount of time.

White, pink, and brown noise, the three different types of sleep noises, all aid in sleeping. White noise reduces the likelihood of sleep disturbance, which is a problem worse than having trouble falling asleep because it helps keep outside sounds from waking you up during the middle of the night.

Pediatricians suggest keeping any white noise machines at least 7 feet (200 cm) away from your baby’s crib in light of the AAP results. White noise has been shown to improve sleep in individuals of all ages. White noise devices shouldn’t be louder than what’s safe for infants. Additionally, keep in mind that some newborns may not respond well to white noise and that babies can build a dependency on it.

Add this up with the fact that your brain starts associating white noise with sleep, and you can see how using white noise for a better night’s sleep can be a useful tool for adults who suffer from insomnia too. Using white noise is an effective way to help keep your brain relaxed for the long term.

The five human senses, through which our brain receives information, analyzes, and makes sense of the information, are the next-level-creation of the “nature lab”.

And the current trend of research in Artificial Intelligence, Machine Learning, Robotics, and Humanoids may also have made you curious about if scientists are experimenting to create human senses in the lab. 

If so, you are right, because the AI of the next level will certainly require its own senses, which it cannot borrow from any human. After scientists create senses for them, they will be able to use their own brains to create additional senses and come up with new wisdom. 

How is it possible to create senses in the lab?

Artificial senses, but as powerful as the natural human senses, can pave the way for AI to create its own intelligent and wise systems. They can be used as a test bed for years in the lab before they make it onto the market. 

Artificial Intelligence (AI) focuses on using computers and software to simulate human intelligence. The goal of AI engineers has been to build systems that are able to think, act, learn, and even feel like humans.
If you explore various areas of research on artificial intelligence, you will find that researchers are working towards creating an AI model to have a sense of sight, hearing, or taste, along with analyzing patterns among them and then making sense of them. 

Then there are those scientists who aim to give AI its own “self-awareness” and “emotional intelligence”. The goal is to create humanoids like Sophia, who debuted in 2016. Sophia is considered the most advanced humanoid robot. Starship Delivery Robots, Pepper Humanoid Robots, Bearrobotic Restaurant Robots, Nimbo Security Robots, and Shadow Dexterous Hand are the top 5 advanced AI robots in 2022.

But these robots do not have any sense like humans. They just go along according to the program. The extent of their function depends on the architecture of the system.

The reason why scientists are working towards creating senses for AI is that they want to make it smarter. 

Prerequisites to create senses

To create a sense, it is essential to have a system that can recognize patterns among other senses and then act accordingly to make sense of the data. 

Synapses and neural networks – former: the connection between nodes, or neurons, in an artificial neural network (ANN) and latter: a machine learning process called deep learning respectively – are considered to be the fundamental building blocks of artificial intelligence. These are the basic components that make up the brain’s signals and decisions. The mind of a human or a robot consists of these neurons connected to one another in different patterns. 

Despite the fact that scientists are experimenting with both artificial intelligence (AI) and machine learning, it’s nothing but an enhanced version of artificial neural networks in order to make devices more intuitive, efficient, and intelligent. These components have been continuously making progress over time because they work on multi-variate algorithms that can learn multiple models at once.

The complexity of our senses

However, creating senses in a lab can be a great challenge. It is because each of the five human senses consists of different neurons arranged in a unique pattern in the neural network. 

The sense of sight consists of the sensory organ (the eye) and parts of the central nervous system (the retina containing photoreceptor cells, the optic nerve, the optic tract, and the visual cortex) and other associated structures for processing the image. 

The primary auditory receptor cells, or inner hair cells in our ears, convert sound waves into an electrical signal that is transmitted to the brain through an auditory nerve, which then reaches the auditory cortex to process them further. 

In our mouth, taste buds are responsible for sensing salty, sour, sweet, and bitter tastes through gustatory hairs present on them while they also connect to a part of the brain called the “gustatory cortex.”

The sense of touch consists of 1) single- and mechanoreceptor cells as well as 2) glabrous (skin) epidermous and 3) hair cells for detecting dynamic stimuli. 

The sense of smell is made up of 1) olfactory epithelium, 2) olfactory receptors and the olfactory bulb, 3) olfactory cortex, 4) amygdala and hippocampus, 5) hypothalamus, and 6) thalamus. 

Challenges in creating senses in a lab

You can see how complex the process is of creating a completely new sense in a lab. You will have to start by identifying the key neurons and their connections and then make the necessary modifications, build new ones, or add some new sensory structures.

These structures will then be inserted into the appropriate areas of the brain for processing. After making all these, you should place them in a bioreactor with appropriate medium conditions as well as target cells and tissues for interaction.

However, the most difficult part is to make the brain accept all the new additions. It will need time, patience, and determination from you to be able to do this. Besides, this is not an easy task for those who have never worked in the field.

In order for the sense of touch to be created in a lab, you should start by identifying the key neurons and their connections that are responsible for detecting static stimuli such as pressure, vibration, or pain.

Similarly, a sense of sight can also be created with the help of an optogenetics approach. This involves the release of light-sensitive proteins in the neurons after stimulating them with a specific wavelength of light.

This approach could then be used in the lab to create sensors such as photoreceptors and photodetectors that will allow you to respond to external stimuli in a manner similar to how they work in nature.

In addition to these, one should also acknowledge that they will have to identify the key neurons present in other species that can be used for creating senses as well as parts of the central nervous system that are responsible for processing them.

Risks associated with creating senses

But the most vulnerable part of artificial intelligence is its “senses” mechanism, which can cause fatal accidents if malfunctioned or attacked by hackers.

For example, in a nuclear disaster zone, robots with nuclear plant inspection systems can be sent to assess the damage and clean the radiation by using radio frequency identifiers. But if a hacker steals the access code, he/she can take control of these robots and cause further damage.

Similarly, in order to create artificial senses in a lab, a neural network must be trained to recognize patterns among other sensors. The most vulnerable part of this mechanism is that it can be hacked. 
Ill-minded people may acquire temporary access to it and use it either for personal gain or as part of some political agenda. If so, they can create problems at any level, including assaults on targeted individuals or public and critical infrastructure systems.

In order to guarantee the security aspect of artificial senses in the lab, they will have to train the artificial senses about precaution and protection. 

These sensors must be developed and implemented while keeping in mind their full potential and how they can be used, as well as how they can be prevented from misuse. 

Before you create senses in a lab, you, therefore, need to be sure that:

• Senses (sensors) will include, but not be limited to sight, hearing, taste, and touch. 

• Sensors should be protected against hacking and the use of malicious code to prevent misuse.

• Sensors should also be protected against accidental discharges as well as any potential harm from natural disasters.

• The system needs to be designed in such a way that it will generate the required result without causing an accident in the process.

• It should be able to accurately detect the type of pollution and its extent. 

• Artificial senses should have a physical system capable of linking with devices such as cameras and sensors in order to increase their processing capacity. 

• This can enable better processing time, accuracy, and performance.

To sum up, artificial senses are the next step for dynamic and smart robotic devices, for which you will require more precision, speed, and accuracy to be able to create them in a lab. The level of stability, power consumption, and energy efficiency should be on par with that of organic systems. 

However, due to the complex nature of these systems, a host of developing challenges are being faced by researchers in this field. These include the integration of artificial senses into robotic systems, while they can also help scientists to understand how real senses work as well as provide solutions to the various problems related to artificial senses.