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For most of the history of genetics, the story was simple: you inherit DNA from your parents, that DNA determines your traits, and what happens during your lifetime doesn't change what you pass on. But a field called epigenetics has been quietly rewriting that story.
Epigenetics is the study of changes in gene expression that don't involve changes to the DNA sequence itself. Think of your DNA as a book. Epigenetics is about which pages get read — and which ones get skipped. The letters don't change, but the story being told can be completely different depending on what gets switched on or off.
These switches are controlled by chemical tags attached to DNA — primarily methyl groups (methylation) and proteins called histones. When a methyl group attaches to a gene, it often silences it. When histones are modified, they can make DNA more or less accessible for transcription. These patterns of tags are called the epigenome.
Here's the part that makes this genuinely strange: some of these epigenetic tags can be inherited. Your grandmother's experiences — what she ate, how much stress she experienced, what toxins she was exposed to — may have left chemical marks on her DNA that were passed down through your mother to you.
One of the most studied examples is the Dutch Hunger Winter of 1944–45. During World War II, a Nazi blockade caused mass starvation in the Netherlands. Children who were in the womb during this famine had epigenetic changes that persisted for decades. They had higher rates of obesity, heart disease, and mental illness — not because their DNA changed, but because their epigenome was set by an environment of severe starvation before they were even born. And some of these effects were found in their children too.
Diet is one of the most powerful epigenetic factors. Folate, vitamin B12, and certain plant compounds can influence methylation patterns. Stress — especially chronic stress — activates hormones like cortisol that alter epigenetic marks throughout the body. Exercise, sleep, smoking, and exposure to pollution all leave traces in the epigenome.
This is simultaneously hopeful and sobering. Hopeful because it means your choices genuinely matter — healthy habits can positively reshape your epigenome. Sobering because it means the inequalities people face (poverty, food insecurity, chronic stress) can leave biological marks that persist across generations.
Jean-Baptiste Lamarck famously proposed in the 1800s that traits acquired during a lifetime could be passed to offspring — like a giraffe stretching its neck its whole life and having longer-necked babies. Darwin's natural selection replaced this idea. But epigenetics has brought a version of it back. Not in the cartoon form Lamarck imagined, but in the subtle, molecular sense that environmental experiences really can be inherited.
This doesn't overturn evolution — epigenetic changes are generally reversible over generations, unlike mutations. But it does add a layer of biological inheritance that we barely understood a generation ago. The environment your ancestors lived in is, in a very real sense, part of who you are.
The Sun is so familiar that it's become invisible. It rises, it sets, it gives you sunburn. But once you actually look at the numbers — the temperatures, the distances, the forces at work — it becomes one of the most extreme objects you can imagine.
1. The Sun contains 99.86% of all the mass in the solar system. Everything else — all the planets, moons, asteroids, and comets — is the remaining 0.14%.
2. About 1.3 million Earths could fit inside the Sun. If the Sun were the size of a basketball, Earth would be the size of a grain of sand.
3. Despite being 150 million kilometres away, the Sun's gravity holds Neptune in orbit — a planet so far that light takes over 4 hours to reach it from the Sun.
4. The Sun's core reaches 15 million degrees Celsius. The surface is a comparatively cool 5,500°C.
5. Weirdly, the Sun's outer atmosphere — the corona — is hotter than its surface, reaching over 1 million°C. Scientists are still not fully sure why. This is called the coronal heating problem and it remains unsolved.
6. Every second, the Sun converts 600 million tonnes of hydrogen into helium through nuclear fusion, releasing the energy equivalent of billions of nuclear bombs.
7. The energy produced in the Sun's core takes between 10,000 and 170,000 years to reach the surface — bouncing around constantly — but only 8 minutes to travel from the surface to Earth.
8. The Sun has no solid surface. It's a plasma — a superheated state of matter where electrons are stripped from atoms. What we see as the "surface" is called the photosphere.
9. Sunspots are cooler, darker regions on the Sun's surface caused by intense magnetic activity. They can be larger than Earth and last for weeks.
10. Solar flares — explosions of radiation from the Sun's surface — can release energy equivalent to millions of hydrogen bombs in minutes. Large ones can disrupt satellites and power grids on Earth.
11. The Sun is about 4.6 billion years old and is roughly halfway through its life. It will continue fusing hydrogen for another 5 billion years.
12. When the Sun runs out of hydrogen, it will expand into a red giant — growing to roughly 200 times its current size, likely engulfing Mercury, Venus, and possibly Earth.
13. After the red giant phase, the Sun will shed its outer layers and collapse into a white dwarf — a dense, Earth-sized remnant that will slowly cool over billions of years.
14. The Sun rotates, but not like a solid body — its equator rotates faster than its poles. This is called differential rotation and it's responsible for much of the Sun's magnetic complexity.
15. The Sun is moving. Along with the entire solar system, it orbits the centre of the Milky Way at about 220 kilometres per second. One full orbit takes around 225–250 million years — called a galactic year.
The Sun isn't just a light source. It's a fusion reactor, a magnetic dynamo, a plasma ocean, and the engine of all life on Earth. The fact that it looks so ordinary from down here is almost a trick of familiarity.
Gsolix wasn't planned. It wasn't a business idea. It started as a frustration.
We were students — teenagers trying to understand biology concepts the night before an exam, looking up physics explanations that assumed we already knew half the material, dealing with platforms that hid their best content behind paywalls. And we thought: this shouldn't be this hard. So we started building.
What started as a collection of study notes became something much bigger. Gsolix now has interactive quizzes for Biology, Physics, Mathematics, and Computer Science. It has flip flashcards, practice sets, a global XP leaderboard, live study chat rooms per subject, study clubs, and an AI tutor available around the clock. All completely free. No ads, no subscriptions, no gatekeeping.
We also publish study notes on Stuvia — free guides you can download and use offline. And our YouTube channel, Dom With A Cam, documents the journey of building all of this as teenagers.
Our Instagram (@gs0lix) is where we share science facts, mind-bending discoveries, and updates about the platform. Things like the fact that your ancestors' environment is literally shaping your biology today. Or that the Sun's corona is hotter than its surface and nobody fully knows why. We try to make science feel as fascinating as it actually is — not like a textbook you have to get through.
We're not done. We're working on expanding the blog with more articles that connect to our Instagram content, adding more disciplines, improving the club system, and making the platform feel even more like a real community. The goal has always been the same: build the learning resource we wished existed when we needed it most.
If you have ideas, feedback, or just want to say hi — reach us through the Connection page. We actually read everything.
Gsolix was created by students who wanted free, clear explanations without paywalls or gatekeeping. Too many learning platforms hide their best content behind subscriptions, or explain things in ways that assume you already understand them.
The idea was simple: build the resource we wished existed when we were struggling through biology homework or trying to understand Newton's laws at midnight before a test.
What started as a collection of notes quickly became something bigger — a platform with quizzes, flashcards, live study chat, and a community of people who care about learning for its own sake, not just for grades.
We believe access to quality education should not depend on how much money you have. Gsolix is and will always be completely free.
Building Gsolix as teenagers was not a straightforward process. It involved late nights, broken code, and moments of wondering whether any of it was worth it.
The project started because school was frustrating. Not because learning was hard, but because the system around learning made it harder than it needed to be.
The technical side was its own learning curve — HTML, CSS, JavaScript, then databases for real-time features. Every new feature taught us something about both code and the subject we were trying to explain.
The biggest lesson was not technical. Explaining something well to someone else forces you to understand it properly yourself. Building Gsolix made us better students, not just better developers.
Your muscles are not all the same. Even within a single muscle, there are two distinct types of fibers: fast-twitch and slow-twitch.
Slow-twitch fibers (Type I) are built for endurance. They are dense with mitochondria, resist fatigue well, and generate energy aerobically. Marathon runners rely heavily on these.
Fast-twitch fibers (Type II) are designed for power and speed. They contract forcefully but tire fast. Sprinters and powerlifters depend on these.
Most people have a roughly even split of both types, but genetics play a significant role. Training can influence fiber efficiency but cannot fully convert one type to the other.
Salamanders regrow entire limbs. When a salamander loses a limb, cells revert to a flexible state and form a blastema that rebuilds bone, muscle, nerves, and skin in the correct order.
Instead of forming a blastema, human bodies create scar tissue — closing wounds quickly but preventing regeneration. From an evolutionary standpoint, fast healing won over slow regeneration.
Stem cell research is the most promising path forward. Many genes responsible for regeneration in animals already exist in humans but remain inactive. Full limb regeneration is not possible today — but it is an active area of serious scientific research.
Try tickling yourself. Go ahead — drag your fingers across your ribs. Nothing, right? But when someone else does the exact same thing, it's unbearable. Why does the source of the touch change everything?
The answer lies in a mechanism called efference copy. Every time your brain sends a motor command — "move this hand" — it simultaneously sends a copy of that command to the sensory processing areas. This copy says: something is about to happen, expect it, and reduce its impact.
When you touch yourself, your brain already knows exactly what's coming. It cancels out the sensory signal before it registers as surprising. The cerebellum — the brain region involved in movement coordination — compares what actually happened with what was predicted, and when they match, the sensation is dampened.
Tickling works because it is unpredictable. You don't know where the touch is going next, how hard it will be, or when it will stop. That unpredictability triggers the laughter response — a signal that may have evolved as a form of social bonding or a mock-distress signal during play.
This is why a robot or a machine with a slight time delay can tickle you — even though you know it's coming, the tiny lag disrupts the brain's prediction, and the sensation gets through. Some people with schizophrenia can tickle themselves, possibly because disrupted self-monitoring means the brain's predictions are less reliable.
Your inability to tickle yourself is a window into how the brain constantly predicts and filters reality — turning down the volume on things it already expects, and amplifying the things it didn't see coming.
For most of medical history, bacteria in the body were treated as enemies — things to be killed with antibiotics and avoided at all costs. That view has been almost completely overturned. The human gut contains trillions of microorganisms — bacteria, fungi, viruses, and archaea — collectively called the microbiome. And they are not passengers. They are partners.
Your gut microbiome helps digest food your own enzymes can't break down — particularly dietary fibre. It synthesises vitamins like B12 and K2. It trains your immune system from birth, teaching it the difference between harmless molecules and genuine threats. It competes with and suppresses pathogenic bacteria that could make you sick.
But the influence goes further than digestion. The gut contains over 100 million neurons — more than the spinal cord — and communicates directly with the brain via the vagus nerve. This is sometimes called the gut-brain axis. Your microbiome produces neurotransmitters, including about 90% of the body's serotonin. Disruptions to gut bacteria have been linked to anxiety, depression, and cognitive changes in both animal and human studies.
Antibiotics are the most dramatic disruptor — a single course can alter the microbiome for months. Diet is the most consistent one: high-fibre, plant-rich diets feed diverse bacterial communities, while ultra-processed foods favour a narrower, less healthy set. Stress, sleep deprivation, and early-life experiences (including whether you were born by caesarean section) all shape which microbes colonise you and how.
The science here is still young. Microbiome research is one of the most active fields in all of biology. What we know so far suggests that caring for your gut bacteria — through diet, sleep, and avoiding unnecessary antibiotics — is caring for your brain and immune system too.
The dominant scientific view is that consciousness arises from complex neural activity. Damage specific brain regions and abilities disappear. Integrated Information Theory formalizes this.
But philosopher David Chalmers points out that correlation is not explanation. Knowing brain activity accompanies experience doesn't explain why experience exists at all — the "hard problem" of consciousness.
Modern panpsychism suggests consciousness is a basic feature of reality, like mass or charge. Science shows the brain is deeply involved. Philosophy shows this involvement may not be the whole story.
Mathematical truths feel inevitable — two plus two equals four everywhere, regardless of culture. Complex numbers were once called imaginary; later they became essential to quantum mechanics. If math were purely invented, this alignment with reality would be extraordinary.
On the other hand, we choose axioms, create notation, and decide what counts as proof. This suggests our mathematical language is constructed.
Perhaps we invent the tools to explore mathematical space — but once invented, those tools reveal truths we didn't choose. The invention is superficial. The discovery is fundamental.
In the 1980s, neuroscientist Benjamin Libet ran an experiment that still hasn't stopped being unsettling. He asked participants to flex their wrist whenever they felt like it and to note the position of a clock hand at the moment they decided to move. He measured brain activity throughout.
The result: brain activity associated with the movement began about 550 milliseconds before the actual motion — but participants reported deciding to move only about 200 milliseconds before. The brain was preparing to act before the conscious decision was made. The experience of deciding seemed to come after the brain had already started.
One interpretation is bleak: you are not the author of your choices. Your brain — shaped by genetics, experience, and chemistry — decides, and consciousness just takes credit afterward. Every feeling of deliberation is a story told after the fact.
Another interpretation is more nuanced. Libet himself noted that while the brain began preparing early, consciousness might still play a role in vetoing the action — a kind of "free won't" rather than free will. The initiating mechanism may be automatic; the ability to stop it might still be ours.
Most philosophers today take a position called compatibilism: free will and determinism can both be true. What we mean by "free will" isn't some magical ability to escape causality — it's the ability to act according to our own desires and values, without external coercion. If your actions flow from who you genuinely are, they are free in the sense that matters.
Whether or not you find that satisfying may itself be determined. But the question is worth sitting with — because how we think about free will shapes how we think about responsibility, punishment, and what it means to be a person.
Newton described gravity as a force — an invisible pull that predicted planetary orbits with extraordinary accuracy. But Newton admitted he didn't know what gravity actually was or how it acted across empty space.
Einstein's General Relativity offered a completely different picture. Gravity is not a force — it is the curvature of spacetime caused by mass and energy. Objects don't pull each other; they follow the straightest possible path through curved spacetime.
GPS satellites must account for general relativistic effects or their clocks would drift and navigation would fail within hours. When you feel weight pressing you into your chair, you're not being pulled down — you're being pushed up by the chair, resisting the natural path through curved spacetime.
For centuries, physics was divided on the nature of light. Newton believed light was made of particles — corpuscles, he called them. Huygens insisted it was a wave. Then Young's double-slit experiment in 1801 seemed to settle it: light produces interference patterns, and only waves do that. Particles won. Then particles won again. Then it got strange.
In 1905 — the same year he published special relativity — Einstein explained the photoelectric effect. When light shines on certain metals, it knocks out electrons. But the energy of those electrons doesn't depend on the brightness of the light — it depends on its frequency. Brighter light just knocks out more electrons; higher-frequency light knocks out faster ones.
This only makes sense if light comes in discrete packets — photons. A single high-energy photon can knock out an electron; a flood of low-energy photons cannot. Light is a particle again. Einstein won the Nobel Prize for this, not for relativity.
The resolution — if you can call it that — is that light is neither a wave nor a particle in any classical sense. It is a quantum object that behaves like a wave when you're not measuring it and like a particle when you are. The double-slit experiment done with single photons still produces an interference pattern over time — each photon interferes with itself.
This is wave-particle duality, and it applies to electrons, atoms, and molecules too. It is not a limitation of our instruments. It is a fundamental feature of reality at the quantum scale. The question "what is light really?" may not have an answer that satisfies human intuition — because human intuition was built for a world much larger and slower than the quantum one.
Of all the laws in physics, the second law of thermodynamics is the one that feels most personal. It says that in any closed system, entropy — a measure of disorder — always increases over time. Things fall apart. Heat flows from hot to cold, never the reverse. Ice melts in warm water; warm water never spontaneously refreezes. You cannot unscramble an egg.
Entropy is often described as "disorder," but a more precise definition is the number of ways a system can be arranged at the microscopic level while looking the same at the macroscopic level. A room full of evenly spread gas has high entropy — there are countless arrangements of individual molecules that produce the same "spread out" appearance. A room where all the gas is crammed into one corner has low entropy — very few arrangements produce that.
The reason entropy increases is statistical, not magical. There are simply far more ways for things to be disordered than ordered. A shuffled deck of cards is overwhelmingly more likely than one sorted by suit — not because of any force pushing toward disorder, but because of probability.
Entropy is the reason time has a direction. The fundamental laws of physics — Newton's laws, quantum mechanics, electromagnetism — are all time-symmetric. They work the same forwards and backwards. But entropy is not. The past is the direction of lower entropy; the future is the direction of higher entropy. The sense you have of time flowing forward is, at its deepest level, a consequence of this statistical tendency.
Taken to its logical conclusion, the second law predicts that the universe will eventually reach a state of maximum entropy — the heat death. All energy will be evenly distributed, no more gradients to drive processes, no stars, no life, no events. Just an eternal, cold, featureless equilibrium. This will take an unimaginably long time — far longer than the current age of the universe. But entropy demands it.
Traditional software is written as explicit rules — if this, then that. Machine learning inverts this. Instead of writing rules, you give the system data and let it figure out the rules itself.
Modern AI is built on layers of mathematical nodes loosely inspired by neurons. During training, the model makes predictions, compares them to correct answers, and adjusts to reduce errors. Repeat millions of times and the model learns to generalise.
Large language models are trained on vast amounts of text and learn to predict what comes next. Through this simple objective at enormous scale, they develop something that looks like understanding — whether it genuinely is remains an open philosophical question.
Imagine you have a list of 10 names and you need to find a specific one. You could check each name one by one — that's 10 checks in the worst case. Now imagine the list has a million names. Checking one by one would take up to a million checks. The time grows linearly with the input size. This is what Big O notation captures: how does the work scale?
O(1) — Constant time. The operation takes the same time regardless of input size. Looking up a value in a hash map is O(1). It doesn't matter if the map has 10 entries or 10 million — the lookup is just as fast.
O(n) — Linear time. The work grows proportionally with input size. Checking every item in a list once is O(n). Double the list, double the work.
O(n²) — Quadratic time. For every item, you do work proportional to the whole list. Nested loops often produce this. A list of 1,000 items means up to 1,000,000 operations. This gets painful fast.
O(log n) — Logarithmic time. The work grows slowly even as the input grows fast. Binary search — where you repeatedly halve the search space — is O(log n). A list of one billion items takes only about 30 steps to search this way.
A fast computer running an O(n²) algorithm will eventually lose to a slow computer running an O(n log n) algorithm as the input grows large enough. Big O describes the fundamental shape of an algorithm — not how fast it runs on your specific hardware today, but how it will behave at scale. Understanding this is the difference between code that works in testing and code that survives in production.
You type "gsolix.com" into your browser and press Enter. Within a few hundred milliseconds, a webpage appears. That feels instant, but it involves a remarkable chain of events crossing thousands of miles of physical infrastructure.
Your browser doesn't know where "gsolix.com" is. It knows IP addresses — numerical labels like 192.168.1.1. So it asks a DNS server (Domain Name System) to translate the domain name into an IP address. This is like looking up someone's phone number from their name. Your computer checks a local cache first; if it doesn't have the answer, it asks your ISP's DNS server, which may ask further up the chain until it finds the authoritative answer.
Once your browser has the IP address, it establishes a connection using TCP (Transmission Control Protocol). This involves a "three-way handshake" — your computer sends a SYN packet, the server replies with SYN-ACK, and your computer confirms with ACK. Only then does data start flowing. TCP ensures that every packet of data arrives and arrives in order, requesting retransmission if anything gets lost.
Your browser sends an HTTP request — essentially a formatted message saying "please give me the home page." If the site uses HTTPS (which it should), this happens over an encrypted TLS connection established through another handshake. The server receives the request, processes it, and sends back the HTML, CSS, JavaScript, and any other files needed to display the page.
Your browser parses the HTML to build a structure called the DOM (Document Object Model), applies CSS styles, and executes JavaScript. Images and other resources are requested in parallel. The visual result — the page you see — is assembled from all of these pieces in real time. By the time you've read this sentence, your browser has completed thousands of individual steps just to show you text on a screen.