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- Neuroimaging and spatial resolution | Scientia News
Peering into the mind Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link Neuroimaging and spatial resolution 10/07/25, 10:24 Last updated: Published: 04/11/24, 14:35 Peering into the mind Introduction Neuroimaging has been at the forefront of brain discovery ever since the first ever images of the brain were recorded in 1919 by Walter Dandy, using a technique called pneumoencephalography (PET). Fast-forward over a decade and neuroimaging is more than just blurry singular images. Modern techniques allow us to observe real time changes in brain activity with millisecond resolution, leading to breakthroughs in scientific discovery that would not be possible without it. Memory is a great example - with functional magnetic resonance imaging (fMRI) techniques we have been able to demonstrate that more recent long-term memories are stored and retrieved with brain activity in the hippocampus, but as memories become more in the distant past, they are transferred to the medial temporal lobe. While neuroimaging techniques keep the doors open for new and exciting discoveries, spatial limitations leave many questions unanswered, especially at a cellular and circuit level. For example - within the hippocampus, is each memory encoded via complete distinct neural circuits? Or do similar memories share similar neural pathways? Within just a millimetre cubed of brain tissue we could have up to 57,000 cells (most of them neurons), all of which may have different properties, be part of different circuits, and produce different outcomes. This almost makes revolutionary techniques such as fMRI, with almost unparalleled image quality, seem pointless. To truly understand how neural circuits work, we have to dig as deep as possible to record the smallest regions possible. So that begs the question, how small can we actually record in the human brain? EEG 2024 marks a decade since the first recorded electroencephalography (also known as EEG) scan by Hans Berger in Germany. This technique involves placing electrodes all around the scalp to record activity throughout the whole outer surface of the brain ( Figure 1 ). Unlike the methods we see later on, EEG scans provide a direct measure of activity in the brain, by measuring electrical activity when the brain is active. However, because electrodes are only placed across the scalp, EEG scans are only able to pick up activity from the outer cortex, missing important activity in deeper parts of the brain. In our memory example, this means it would completely miss any activity in the hippocampus. EEG resolution is also quite underwhelming, typically being able to resolve activity with a few centimetres’ resolution - not great for mapping behaviours to specific structures in the brain. EEG scans are used in a medical environment to measure overall activity levels, assisting with epilepsy diagnosis. Let's look at what we can use to dig deeper into the brain and locate signals of activity… PET Position emission tomography (PET) scans offer a chance to record activity throughout the whole brain by ingesting a radioactive tracer, typically glucose labelled with a mildly radioactive substance. This tracer is tracked and uptake in specific parts of the brain is a sign for greater metabolic activity, indicating a higher signalling rate. PET scans already offer a resolution far beyond the capacities of EEG scans, distinguishing activity between areas with a resolution of up to 4mm. With the use of different radioactive labels, we can also detect activity of specific populations of neurons such as dopamine neurons to diagnose Parkinson's disease. In fact, many studies have reliably demonstrated the ability of PET scans to detect the root cause of Parkinson's disease, which is a reduced number of dopamine neurons in the basal ganglia, before symptoms become too extreme. As impressive as it sounds, a 4mm resolution can locate activity in large areas of the cortex, but is limited in its resolving power for discrete cortical layers. Take the human motor cortex for example - all 6 layers have an average width of only 2.79mm. A PET scan would not be powerful enough to determine which layer is most active, so we need to dig a little deeper… fMRI Since its inception in the early 90's, fMRI has gained the reputation of becoming the gold standard for human neuroimaging, thanks to its non-invasiveness, lack of artefacts, and reliable signalling. fMRI uses Nuclear Magnetic Resonance to measure changes in oxygenated blood flow, which is correlative of neural activity, known as BOLD signals. In comparison to EEG, measuring blood oxygen levels cannot reach a highly impressive temporal resolution, and is also not a direct measure of neural activity. fMRI makes up for this with its superior spatial resolution, resolving spaces as small as 1mm apart. Using our human motor cortex example, this would allow us to resolve activity between every 2-3 layers - not a bad return considering it doesn’t even leave a scar. PET, and especially EEG, pales in comparison to the capabilities of fMRI that has since been used for a wide range of neuroimaging research. Most notably, structural MRI has been used to support the idea of hippocampal involvement during spatial navigation from memory tasks ( Figure 2 ). Its resolving power and highly precise images also make it suitable to be used for mapping surgical procedures. Conclusion With a resolution of up to 1mm, fMRI takes the crown as the human neuroimaging technique with the best spatial resolution! Table 1 shows a brief summary of each neuroimaging method. Unfortunately though, there is still so much more we need to do to look at individual circuits and connections. As mentioned before, even within a millimetre cubed of brain, we have 5 figures worth of cells, making the number of neurons that make up the whole brain impossible to comprehend. To observe the activity of a single neuron, we would need an imaging technique with the power of viewing cells in the 10’s of micrometre range. So what can we do to get to the resolution we desire while still being suitable for humans? Maybe there isn't a solution. Instead, maybe if we want to record singular neuron activity, we have to take inspiration from invasive animal techniques such as microelectrode recordings. Typically used in rats and mice, these can achieve single-cell resolution to look at neuroscience from the smallest of components. It would be unethical to stick an electrode into a healthy human's brain and record activity, but perhaps in the future a non-invasive form of electrode recording could be developed? The current neuroscience field is foggy and shrouded in mystery. Most of these mysteries simply cannot be solved with the current research techniques we have at our disposal. But this is what makes neuroscience exciting - there is still so much to explore! Who knows when we will be able to map behaviours to neural circuits with single-cell precision, but with how quickly imaging techniques are being enhanced and fine-tuned, I wouldn't be surprised if it's sooner than we think. Written by Ramim Rahman Related articles: Neuromyelitis optica / Traumatic brain injuries REFERENCES Hoeffner, E.G. et al. (2011) ‘Neuroradiology back to the future: Brain Imaging’, American Journal of Neuroradiology, 33(1), pp. 5–11. doi:10.3174/ajnr.a2936. Maguire, E.A. and Frith, C.D. (2003) ‘Lateral asymmetry in the hippocampal response to the remoteness of autobiographical memories’, The Journal of Neuroscience, 23(12), pp. 5302–5307. doi:10.1523/jneurosci.23-12-05302.2003. Wong, C. (2024) ‘Cubic millimetre of brain mapped in spectacular detail’, Nature, 629(8013), pp. 739–740. doi:10.1038/d41586-024-01387-9. Butman, J. A., & Floeter, M. K. (2007). Decreased thickness of primary motor cortex in primary lateral sclerosis. AJNR. American journal of neuroradiology, 28(1), 87–91. Loane, C., & Politis, M. (2011). Positron emission tomography neuroimaging in Parkinson's disease. American journal of translational research, 3(4), 323–341. Maguire, E.A. et al. (2000) ‘Navigation-related structural change in the hippocampi of taxi drivers’, Proceedings of the National Academy of Sciences, 97(8), pp. 4398–4403. doi:10.1073/pnas.070039597. [Figure 1] EEG (electroencephalogram) (2024) Mayo Clinic . Available at: https://www.mayoclinic.org/tests-procedures/eeg/about/pac-20393875 (Accessed: 18 October 2024). [Figure 2] Boccia, M. et al. (2016) ‘Direct and indirect parieto-medial temporal pathways for spatial navigation in humans: Evidence from resting-state functional connectivity’, Brain Structure and Function, 222(4), pp. 1945–1957. doi:10.1007/s00429-016-1318-6. Project Gallery
- Totality- Our Perfect Eclipse | Scientia News
Total solar eclipses Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link Totality- Our Perfect Eclipse 14/07/25, 15:05 Last updated: Published: 24/05/23, 10:05 Total solar eclipses We are all familiar with the characteristic depiction of a solar eclipse, when the Moon passes directly between the Sun and the Earth. However, the significance of solar eclipses extends far beyond their aesthetic appeal. Major scientific discoveries, cultural practices, and even the behaviour of wild animals are derived from total solar eclipses that we have the privilege of experiencing (See image 1). A solar eclipse occurs when the Earth, Moon, and Sun all appear to lie on a straight line. They are collinear. Total solar eclipses occur when the Moon completely obscures the Sun's photosphere, enabling prominences and coronal filaments to be seen along the limb. This phenomenon is unique to the Earth, Sun, and Moon system and to understand why we must explore the mathematics underlying these ‘orbital gymnastics’. We wish to compare the ‘apparent’ size of the Sun and Moon, a quantity proportional to the ratio of their size and distance from Earth. The Moon has a radius of around 3,400 km, and is approximately 384,000 km from Earth. The Sun has a much larger radius of 1.4 million km, and is located at a distance of 150 million km. By dividing the Sun's radius by the Moon's radius and dividing the Earth-Sun distance by the Earth-Moon distance, we can determine that the Sun is 400 times larger than the Moon and 400 times further away. This unique relationship allows for total solar eclipses, where totality indicates **the complete blocking of sunlight from the Sun’s disk by the Moon. In partial eclipses, only part of the Sun is obscured. One might wonder why we don’t have total solar eclipses every month, and the reason is that the plane of the Moon’s orbit around Earth is tilted at 5 degrees relative to Earth’s orbital plane. This hugely decreases the likelihood of such perfect alignment. Of the hundreds of moons orbiting planets in our Solar System, only our Moon totally eclipses the Sun. For example, none of Jupiter’s 95 moons have the correct size and orbital separation that completely block out the Sun from any point on Jupiter’s surface! Surely this serendipitous interplay of Earth, Sun, and Moon cannot be a coincidence? (See image 2) It is at this point where divine intervention is typically invoked. There are a few problems with doing this. The Moon's eccentric orbit around Earth means that it will be closer during some total solar eclipses than others, resulting in annular eclipses when the Moon is furthest from Earth. Additionally, the Moon is receding from the Earth at a rate of 4 cm/year, which means that total solar eclipses will only be observable for another 250 million years. (See image 3) For those of you who wish to make the most of this brief window of opportunity, this website shows the dates and locations of upcoming total solar eclipses. Written by Joseph Brennan REFERENCE Guillermo Gonzalez, Wonderful eclipses, Astronomy & Geophysics , Volume 40, Issue 3, June 1999, Pages 3.18–3.20, https://doi.org/10.1093/astrog/40.3.3.18 Project Gallery
- Rabies- the scariest disease ever? | Scientia News
The rabies virus infects neurons Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link Rabies- the scariest disease ever? 10/07/25, 10:31 Last updated: Published: 10/10/24, 11:05 The rabies virus infects neurons Rabies is a viral disease that primarily affects the central nervous system (CNS), usually in mammals. Wild animals such as foxes, dogs, and raccoons are frequent carriers of the virus. Transmission occurs through the saliva of an infected animal through a bite or a scratch, allowing the virus to enter the body and travel through the nervous system toward the brain. While rabies can be prevented with a vaccine, once symptoms begin to show, the disease is nearly always fatal once symptoms begin to show. What makes this virus so deadly, and how can it take control of the human body with just five genes in its genome? Why is the virus so hard to kill? To arrive at a sensible answer, we must first understand the ‘tropism’ of the virus – the cell type it likes to infect. Rabies virus infects the neurones (neurotropic), which creates a massive problem for the immune system. Macrophages and neutrophils, which are the prominent cells in killing foreign pathogens that kill foreign pathogens, usually deal collateral damage to the body’s own cells to some extent. This must be avoided with neurones, as neurones cannot replenish themselves after cell death. An inflammation of the nerve cells could lead to paralysis and seizures, compromising the CNS. As a result, the immune system response is significantly lowered around nerve cells to prevent accidental damage, which allows the virus to infect the neural pathway easily. Transmission of the virus See Figure 1 The strategy of the immune system is that the neurones can be protected if the pathogens are intercepted before they travel to their destination. However, this strategy ultimately fails when it comes to rabies, because the transmission is through a bite, which can penetrate and cut through many layers of tissue, providing a direct access to nerve cells. If you were bitten on the leg, then the time it takes for the rabies virus to travel to your brain would be the time it takes for you to travel from Florida, USA to Sweden. This may seem like a long time, but the rabies virus has evolved a technique that is able to hijack the cellular transport system can trick your cells’ transport system to travel quickly through the nerves by binding to a protein called dynein . Dynein is a motor protein that move along the microtubules in cells, converting the chemical energy of ATP into mechanical work. Microtubules are polarized structures, with a plus end (typically towards the axon terminal in neurones) and a minus end (towards the cell body). Dynein moves toward the minus end, facilitating retrograde transport, meaning it moves materials from the periphery of the cell, such as the axon terminals, back toward the cell body. Dynein is transports chemicals inside cells via endocytosis and plays a vital role in the movement of eukaryotic flagella. Rabies has evolved to stick to dynein via the Glycoprotein (G) present on its viral envelope, which allows rabies to travel to the brain much quicker. Dynein may be small, weighing around two megadaltons (3 x 10-18 grams), but it can move at a speed of 800 nanometres per second. At this speed, it takes rabies around 14 days to move up a metre- long neuron. This implies that the closer the animal bites you to the brain, the less time it takes for the symptoms to appear. If you’re bitten on the foot, it could take months for the virus to reach your brain. But if you’re bitten on the neck or face, the virus can get to your brain in just a few days, making it much more dangerous. This explains the broad range in the incubation time which is between 20 to 90 days. Infection and replication- see Figure 2 As the rabies travels through neuronal tracks, it sets up points of concentrated viral production centres called Negri bodies. These replicate the rabies virus within the neurones and inhibit interferon action, which are chemicals that alert white blood cells to the area of infection. Interferon inhibition along with lowered immune response to neurones make rabies extremely effective. However, neurones can undergo apoptosis—controlled cell death—to limit the spread of the virus and allow macrophages to clear the debris. Research in mice suggests that some strains of rabies may prevent this apoptotic response in cells. Additionally, studies indicate that rabies promotes apoptosis in killer T cells, which are responsible for inducing apoptosis in other cells. This mechanism helps to shield nerve cells from immune system attacks. Symptoms Patients with rabies initially experience flu-like symptoms and muscle pain. Once these early symptoms appear, treatment is virtually impossible. As the disease progresses, neurological symptoms develop including hydrophobia due to painful throat spasms when swallowing liquids. About 10 days after these neurological symptoms start, patients enter a coma, often accompanied by prolonged sleep apnoea. As virus attacks the brain throughout this stage, patients develop the urge to bite other organisms to transmit the virus. The virus can reach the salivary glands, allowing for transmission through a bite to occur again. Most patients typically die within three days of reaching this coma stage. Legends Rabies may have influenced the development of vampire and zombie myths due to its distinct symptoms. The disease causes aggression and sensitivity to light, which could have inspired some characteristics of vampires, such as their aversion to light and erratic movements. Additionally, rabies leads to excessive salivation and a tendency to bite, traits that align with vampire lore. Similarly, the delirium and motor dysfunction seen in rabies may have contributed to the depiction of zombies as shuffling, incoherent beings. Conclusion Rabies is a uniquely deadly virus due to its mechanism of hijacking the nervous system. After entering the body, the virus binds to dynein, using it to travel along neuronal pathways toward the brain. It replicates rapidly, forming Negri bodies disrupting neurone function. The virus effectively suppresses immune responses, making it nearly impossible to treat once symptoms appear, leading to almost 100% fatality. Beyond its biological impact, rabies has influenced cultural stories like those of vampires and zombies, with its symptoms—such as aggression, fear of water, and neurological decay—providing eerie parallels to these myths. Despite modern medical advances, rabies remains one of the most feared infectious diseases due to its fatal nature. Written by Baraytuk Aydin Related articles: Rare zoonotic diseases / rAAV gene therapy REFERENCES CUSABIO (2020) Rabies virus overview: Structure, transmission, pathogenesis, symptoms, etc, CUSABIO. Available at: https://www.cusabio.com/infectious-diseases/rabies-virus.html (Accessed: 12 September 2024). Hendricks, A.G. et al. (2012) Dynein tethers and stabilizes dynamic microtubule plus ends, Current biology : CB. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3347920/ (Accessed: 13 September 2024). Lahaye, X. et al. (2009) Functional Characterization of Negri Bodies (NBS) in rabies virus-infected cells: Evidence that NBS are sites of viral transcription and replication, Journal of virology. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2715764/ (Accessed: 13 September 2024). Tarantola, A. (2017) Four thousand years of concepts relating to rabies in animals and humans, its prevention and its cure , MDPI . Available at: https://www.mdpi.com/2414-6366/2/2/5 (Accessed: 15 September 2024). Project Gallery
- Antiretroviral therapy: a key to helping HIV patients | Scientia News
Most research studies are now being diverted to Antiretroviral Therapy (ART) Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link Antiretroviral therapy: a key to helping HIV patients 09/07/25, 10:51 Last updated: Published: 12/10/24, 11:34 Most research studies are now being diverted to Antiretroviral Therapy (ART) Human Immunodeficiency Virus, commonly called HIV, is a sexually transmitted disease that affects approximately 40 million people worldwide and is mostly common in ages 15-49 years. It is spread through direct contact with the blood, semen, pre-seminal fluid, and vaginal fluids of an infected person through mucous membranes—contact with male and female genital tracks. Additionally, HIV can be spread through breast milk from mother to child—studies have shown that infants likely contract the virus when the milk makes contact with the mucous membranes of the gut. How does HIV affect immune cells? HIV is a retrovirus—enveloped RNA viruses that can evade the immune defense system and live within host cells indefinitely. To infect cells HIV uses several mechanisms to make contact with the host cell's membrane. This involves the binding of HIV envelope protein (Env) with the cell receptor CD4 of an immune cell (T-helper cells). Env then binds to a co-receptor on the surface of the cell membrane, triggering membrane fusion. Membrane fusion leads to formation of a fusion pore where HIV successfully enters into the cell's cytoplasm through. Following this, HIV converts its RNA to DNA using enzyme reverse transcriptase and then uses integrase enzymes to become a permanent part of the host cell’s DNA. This allows HIV to replicate at a rapid rate, eventually causing the cells to bloat and rupture, killing the cell all while also “hiding” from the immune defense system and going into latency. Such a process is what weakens the immune system as there is a significant depletion in T-helper cells—cells that fight off infections and diseases. The evolution of ART For the reasons above, HIV is almost impossible to cure. While research is still being conducted to find a cure for HIV, most studies are now being diverted to Antiretroviral Therapy (ART). ART is a revolutionary treatment introduced in the late 198 0s that aims to prevent transmission of HIV, prolong survival, improve immune function and increase CD4 cell count, and improve overall mortality. The first drug released in the late 1980’s was Zidovudine, a nucleoside reverse transcriptase inhibitor (NRTI) that essentially prevents HIV’s RNA from being converted to DNA. This restricted replication hence increasing T-helper cell count. However, while shown to improve the condition of HIV patients, zidovudine did not work well on its own and caused drug resistance from prolonged use. Combination therapy was later introduced where scientists discovered zidovudine to be effective when used alongside another NRTI (dideoxycytidine). This combination did improve CD4 cell count and the overall condition of most patients, not in patients with advanced HIV who had prior use of zidovudine alone. Now, several medications such as NRTIs, non-nucleoside reverse transcriptase inhibitors (NNRTIs), protease inhibitors, and integrase inhibitors have been introduced and are used in a combination of three (Triple-Drug Therapy) to help suppress viral load to undetectable levels in the blood and improve the overall quality of life for patients. Triple-drug therapy can be tailored by doctors to improve the patient's condition. HIV is a sexually transmitted, chronic condition that affects less than 1% of the world's population. There is no cure for HIV, however, treatments (ART) have been introduced to reduce the viral load of HIV as well as improve the overall quality of life of patients. Compared to the past where these medications had to be taken multiple times a day, often causing severe side effects, patients can now take just a single tablet daily. This has changed the course of HIV treatment, allowing people to live lengthy, normal lives with the disease. Written by Sherine A Latheef Related article: CRISPR-Cas9 to potentially treat HIV REFERENCES Guha D, Ayyavoo V. Innate immune evasion strategies by human immunodeficiency virus type 1. ISRN AIDS . 2013;2013:954806. Published 2013 Aug 12. doi:10.1155/2013/954806 AlBurtamani N, Paul A, Fassati A. The Role of Capsid in the Early Steps of HIV-1 Infection: New Insights into the Core of the Matter. Viruses . 2021;13(6):1161. Published 2021 Jun 17. doi:10.3390/v13061161 Pau AK, George JM. Antiretroviral therapy: current drugs. Infect Dis Clin North Am . 2014;28(3):371-402. doi:10.1016/j.idc.2014.06.001 Mayers, Douglas L. “Prevalence and Incidence of Resistance to Zidovudine and Other Antiretroviral Drugs.” The American Journal of Medicine , vol. 102, no. 5, May 1997, pp. 70–75, https://doi.org/10.1016/s0002-9343(97)00067-3 . Accessed 5 Dec. 2021. “Antiretroviral Drug Discovery and Development | NIH: National Institute of Allergy and Infectious Diseases.” Www.niaid.nih.gov , www.niaid.nih.gov/diseases-conditions/antiretroviral-drug-development#:~:text=D urable%20HIV%20Suppression%20with%20Triple%2DDrug%20Therapy&text=In %20December%201995%2C%20saquinavir%20became. CDC. “How HIV Spreads.” HIV , 14 May 2024, www.cdc.gov/hiv/causes/index.html . clinicalinfo.hiv.gov . (n.d.). Protease Inhibitor (PI) | NIH . [online] Available at: https://clinicalinfo.hiv.gov/en/glossary/protease-inhibitor-pi . www.who.int . (n.d.). HIV . [online] Available at: https://www.who.int/data/gho/data/themes/hiv-aids#:~:text=Globally%2C%2039.9 %20million%20%5B36.1%E2%80%93. Project Gallery
- Bone cancer | Scientia News
Pathology and emerging therapeutics Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link Bone cancer 09/07/25, 13:27 Last updated: Published: 12/10/23, 10:38 Pathology and emerging therapeutics Introduction: what is bone cancer? Primary bone cancer can originate in any b one. However, most cases develop in the long bones of the legs or upper arms. Each year, approximately 550 new cases are diagnosed in the United Kingdom. Primary bone cancer is distinct from secondary bone cancer, which occurs when cancer spreads to the bones from another region of the body. The focus of this article is on primary bone cancer. There are several types of bone cancer: osteosarcoma, Ewing sarcoma, and chondrosarcoma. Osteosarcoma originates in the osteoblasts that form bone. It is most common in children and teens, with the majority of cases occurring between the ages of 10 and 30. Ewing (pronounced as YOO-ing) sarcoma develops in bones or the soft tissues around the bones. Like osteosarcoma, this cancer type is more common in children and teenagers. Chondrosarcoma occurs in the chondrocytes that form the cartilage. Chondrosarcoma is most common in adults between the ages of 30 and 70 and is rare in the under-21 age group. Causes of bone cancer include genetic factors such as inherited mutations and syndromes, and environmental factors such as previous radiation exposure. Treatment will often depend on the type of bone cancer, as the specific pathogenesis of each case is unknown. What is the standard treatment for bone cancer? Most patients are treated with a combination of surgical excision, chemotherapy, and radiation therapy. Surgical excision is employed to remove the cancerous bone. Typically, it is possible to repair or replace the bone, although amputation is sometimes required. Chemotherapy involves using powerful chemicals to kill rapidly growing cells in the body. It is widely used for osteosarcoma and Ewing sarcoma but less commonly used for chondrosarcomas. Radiation therapy (also termed radiotherapy) uses high doses of radiation to damage the DNA of cancer cells, leading to the killing of cancer cells or slowed growth. Six out of every ten individuals with bone cancer will survive for at least five years after their diagnosis, and many of these will be completely cured. However, these treatments have limitations in terms of effectiveness and side effects. The limitation of surgical excision is the inability to eradicate microscopic cancer cells around the edges of the tumour. Additionally, the patient must be able to withstand the surgery and anaesthesia. Chemotherapy can harm the bone marrow, which produces new blood cells, leading to low blood cell counts and an increased risk of infection due to a shortage of white blood cells. Moreover, radiation therapy uses high doses of radiation, resulting in the damage of nearby healthy tissues such as nerves and blood vessels. Taken together, this underscores the need for a therapeutic approach that is non-invasive, bone cancer-specific, and with limited side effects. miR-140 and tRF-GlyTCC Dr Darrell Green and colleagues investigated the role of small RNAs (sRNAs) in bone cancer and its progression. Through the analysis of patient chondrosarcoma samples, the researchers identified two sRNA candidates associated with overall patient survival: miR-140 and tRF-GlyTCC. MiR-140 was suggested to inhibit RUNX2, a gene upregulated in high-grade tumours. Simultaneously, tRF-GlyTCC was demonstrated to inhibit RUNX2 expression by displacing YBX1, a multifunctional protein with various roles in cellular processes. Interestingly, the researchers found that tRF-GlyTCC was attenuated during chondrosarcoma progression, indicating its potential involvement in disease advancement. Furthermore, since RUNX2 has been shown to drive bone cancer progression, the identified miR-140 and tRF-GlyTCC present themselves as promising therapeutic targets. CADD522 Dr Darrell Green and colleagues subsequently investigated the impact of a novel therapeutic agent, CADD522, designed to target RUNX2. In vitro experiments have revealed that CADD522 reduced proliferation in chondrosarcoma and osteosarcoma. However, a bimodal effect was observed in Ewing sarcoma, indicating that lower levels of CADD522 promoted sarcoma proliferation, whereas higher levels of the same drug suppressed proliferation. In mouse models treated with CADD522, there was a significant reduction in cancer volumes observed in both osteosarcoma and Ewing sarcoma. Take-home message The results described here contribute to understanding the molecular mechanisms involved in bone cancer. They highlight the anti-proliferative and anti-tumoral effects of CADD522 in treating osteosarcoma and Ewing sarcoma. Further research is necessary to fully elucidate the specific molecular mechanism of CADD522 in bone cancer and to identify potential side effects. Written by Favour Felix-Ilemhenbhio Related articles: Secondary bone cancer / Importance of calcium / Novel neuroblastoma driver for therapeutics Project Gallery
- The future of semiconductor manufacturing | Scientia News
Through photonic integration Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link The future of semiconductor manufacturing 11/07/25, 10:03 Last updated: Published: 22/12/23, 15:11 Through photonic integration Recently the researchers from the University of Sydney developed a compact photonic semiconductor chip by heterogeneous material integration methods which integrates an active electro-optic (E-O) modulator and photodetectors in a single chip. The chip functions as a photonic circuit (PIC) offering a 15 gigahertz of tunable frequencies with a spectral resolution of only 37 MHz and is able to expand the radio frequency bandwidth (RF) to precisely control the information flowing within the chip with the help of advanced photonic filter controls. The application of this technology extends to various fields: • Advanced Radar: The chip's expanded radio-frequency bandwidth could significantly enhance the precision and capabilities of radar systems. • Satellite Systems: Improved radio-frequency performance would contribute to more efficient communication and data transmission in satellite systems. • Wireless Networks: The chip has the potential to advance the speed and efficiency of wireless communication networks. • 6G and 7G Telecommunications: This technology may play a crucial role in the development of future generations of telecommunications networks. Microwave Photonics (MWP) is a field that combines microwave and optical technologies to provide enhanced functionalities and capabilities. It involves the generation, processing, and distribution of microwave signals using photonic techniques. An MWP filter is a component used in microwave photonics systems to selectively filter or manipulate certain microwave frequencies using photonic methods (see Figure 1 ). These filters leverage the unique properties of light and its interaction with different materials to achieve filtering effects in the microwave domain. They can be crucial in applications where precise control and manipulation of microwave signals are required. MWP filters can take various forms, including fiber-based filters, photonic crystal filters and integrated optical filters. These filters are designed to perform functions such as wavelength filtering, frequency selection and signal conditioning in the microwave frequency range. They play a key role in improving the performance and efficiency of microwave photonics systems. The MWP filter operates through a sophisticated integration of optical and microwave technologies as depicted in the diagram. Beginning with a laser as the optical carrier, the photonic signal is then directed to a modulator where it interacts with an input Radio-Frequency (RF) signal. The modulator dynamically influences the optical carrier's intensity, phase or frequency based on the RF input. Subsequently, the modulated signal undergoes processing to shape its spectral characteristics in a manner dictated by a dedicated processor. This shaping is pivotal for achieving the desired filtering effect. The processed optical signal is then fed into a photodiode for conversion back into an electrical signal. This conversion is based on the variations induced by the modulator on the optical carrier. The final output which is represented by the electrical signal reflects the filtered and manipulated RF signal which demonstrates the MWP's ability in leveraging both optical and microwave domains for precise and high-performance signal processing applications. Extensive research has been conducted in the field of MWP chips, as evidenced by a thorough examination in Table 1 . This table compares recent studies based on chip material type, filter type, on-chip component integration, and working bandwidth. Notably, previous studies demonstrated noteworthy advancements in chip research despite the dependence on external components. What distinguishes the new chip is its revolutionary integration of all components into a singular chip which is a significant breakthrough that sets it apart from previous attempts in the field. Here the term "On-chip E-O" involve the integration of electro-optical components directly onto a semiconductor chip or substrate. This integration facilitates the interaction between electrical signals (electronic) and optical signals (light) within the same chip. The purpose is to enable the manipulation, modulation or processing of optical signals using electrical signals typically in the form of voltage or current control. Key components of on-chip electro-optical capabilities include: 1. Modulators which alter the characteristics of an optical signal in response to electrical input which is crucial for encoding information onto optical signals. 2. Photonic detectors convert optical signals back into electrical signals extracting information for electronic processing. 3. Waveguides guide and manipulate the propagation of light waves within the chip, routing optical signals to various components. 4. Switches routes or redirects the optical signals based on electrical control signals. This integration enhances compactness, energy efficiency, and performance in applications such as communication systems and optical signal processing. "FSR-free operation" refers to Free Spectral Range (FSR) which is a characteristic of optical filters and resonators. FSR is the separation in frequency between two consecutive resonant frequencies or transmission peaks. The column "FSR-free operation" indicates whether the optical processing platform operates without relying on a specific or fixed Free Spectral Range. It means that its operation is not bound or dependent on a particular FSR. This could be advantageous in scenarios where flexibility in the spectral range or the ability to operate over a range of frequencies without being constrained by a specific FSR is desired. "On-chip MWP link improvement" refers to enhancements made directly on a semiconductor chip to optimize the performance of MWP links. These improvements aim to enhance the integration and efficiency of communication or signal processing links that involve both microwave and optical signals. The term implies advancements in key aspects such as data transfer rates, signal fidelity and overall link performance. On-chip integration brings advantages such as compactness and reduced power consumption. The manufacturing of the photonic integrated circuit (PIC) involves partnering with semiconductor foundries overseas to produce the foundational chip wafer. This new chip technology will play a crucial role in advancing independent manufacturing capabilities. Embracing this type of chip architecture enables a nation to nurture the growth of its autonomous chip manufacturing sector by mitigating reliance on international foundries. The extensive chip delays witnessed during the 2020 COVID pandemic underscored the global realization of the chip market's significance and its potential impact on electronic manufacturing. Written by Arun Sreeraj Related articles: Advancements in semi-conductor technology / The search for a room-temperature superconductor / Silicon hydrogel lenses / Mobile networks Project Gallery
- A concise introduction to Markov chain models | Scientia News
How do they work? Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link A concise introduction to Markov chain models 20/03/25, 11:59 Last updated: Published: 09/03/24, 18:16 How do they work? Introduction A Markov chain is a stochastic process that models a system that transitions from one state to another, where the probability of the next state only depends on the current state and not on the previous history. For example, assuming that X 0 is the current state of a system or process, the probability of a state, X 1 , depends only on X 0 which is of course the current state of the system as stated. P ( X 1 ) = f ( P ( X 0 )) It may be hard to think of any real-life processes that follow this behaviour because there is the belief that all events happen in a sequence because of each other. Here are some examples: Games e.g. chess - If your king is in a certain spot on a chess board, there will be a maximum of 4 transition states that can be achieved that all depend on the initial position of chess piece. The parameters for the Markov model will obviously vary depending on your position on the board which is the essence of the Markov process. Genetics - The genetic code of an organism can be modelled as a Markov chain, where each nucleotide (A, C, G, or T) is a state, and the probability of the next nucleotide depends only on the current one. Text generation - Consider the current state as the most recent word. The transition states would be all possible words which could follow on from said word. Next word prediction algorithms can utilize a first-order Markov process to predict the next word in a sentence based on the most recent word. The text generation example is particularly interesting because only considering the previous word when trying to predict the next word sentence would lead to a very random sentence. That is where we can change things up using various mathematical techniques. k-Order Markov Chains (adding more steps) In a first-order Markov chain, we only consider the immediately preceding state to predict the next state. However, in k-order Markov chains, we broaden our perspective. Here’s how it works: Definition: a k-order Markov chain considers the previous states (or steps) when predicting the next state. It’s like looking further back in time to inform our predictions. Example: suppose we’re modelling the weather. In a first-order Markov chain, we’d only look at today’s weather to predict tomorrow’s weather. But in a second-order Markov chain, we’d consider both today’s and yesterday’s weather. Similarly, a third-order Markov chain would involve three days of historical data. By incorporating more context, k-order chains can capture longer-term dependencies and patterns. As k increases, the model becomes more complex, and we need more data to estimate transition probabilities accurately. See diagram below for a definition of higher order Markov chains. Markov chains for Natural Language Processing A Markov chain can generate text by using a dictionary of words as the states, and the frequency of words in a corpus of text as the transition probabilities. Given an input word, such as "How", the Markov chain can generate the next word, such as "to", by sampling from the probability distribution of words that follow "How" in the corpus. Then, the Markov chain can generate the next word, such as "use", by sampling from the probability distribution of words that follow "to" in the corpus. This process can be repeated until a desired length or end of sentence is reached. That is a basic example and for more complex NLP tasks we can employ more complex Markov models such as k-order, variable, n-gram or even hidden Markov models. Limitations of Markov models Markov models for tasks such as text generation will struggle because they are too simplistic to create text that is intelligent and sometimes even coherent. Here are some reasons why: Fixed Transition Probabilities: Markov models assume that transition probabilities are constant throughout. In reality, language is dynamic, and context can change rapidly. Fixed probabilities may not capture these nuances effectively. Local Dependencies: Markov chains have local dependencies, meaning they only consider a limited context (e.g., the previous word). They don’t capture long-range dependencies or global context. Limited Context Window: Markov models have a fixed context window (e.g., first-order, second order, etc.). If the context extends beyond this window, the model won’t capture it. Sparse Data : Markov models rely on observed data (transition frequencies) from the training corpus. If certain word combinations are rare or absent, the model struggles to estimate accurate probabilities. Lack of Learning: Markov models don’t learn from gradients or backpropagation. They’re based solely on observed statistics. Written by Temi Abbass Related articles: Latent space transformation s / Evolution of AI FURTHER READING 1. “Improving the Markov Chain Approach for Generating Text Used for…” : This work focuses on text generation using Markov chains. It highlights the chance based transition process and the representation of temporal patterns determined by probability over sample observations . 2 . “Synthetic Text Generation for Sentiment Analysis” : This paper discusses text generation using latent Dirichlet allocation (LDA) and a text generator based on Markov chain models. It explores approaches for generating synthetic text for sentiment analysis . 3. “A Systematic Review of Hidden Markov Models and Their Applications” : This review paper provides insights into HMMs, a statistical model designed using a Markov process with hidden states. It discusses their applications in various fields, including robotics, finance, social science, and ecological time series data analysis . Project Gallery
- The dopamine connection | Scientia News
How your gut influences your mood and behaviour Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link The dopamine connection 11/07/25, 10:02 Last updated: Published: 25/03/24, 12:01 How your gut influences your mood and behaviour Introduction to dopamine Dopamine is a neurotransmitter derived from an amino acid called phenylalanine, which must be obtained through the diet, through foods such as fish, meat, dairy and more. Dopamine is produced and released by dopaminergic neurons in the central nervous system and can be found in different brain regions. The neurotransmitter acts via two mechanisms: wiring transmission and volume transmission. In wiring transmission, dopamine is released to the synaptic cleft and acts on postsynaptic dopamine receptors. In volume transmission, extracellular dopamine arrives at neurons other than postsynaptic ones. Through methods such as diffusion, dopamine then reaches receptors in other neurons that are not in direct contact with the cell that has released the neurotransmitter. In both mechanisms, dopamine binds to the receptors, transmitting signals between neurons and affecting mood and behaviour. The link between dopamine and gut health Dopamine has been known to result in positive emotions, including pleasure, satisfaction and motivation, which can be influenced by gut health. Therefore, what you eat and other factors, including motivation, could impact your mood and behaviour. This was proven by a study (Hamamah et al., 2022), which looked at the bidirectional gut-brain connection. The study found that gut microbiota was important in maintaining the concentrations of dopamine via the gut-brain connection, also known as the gut microbiota-brain axis or vagal gut-to-brain axis. This is the communication pathway between the gut microbiota and the brain facilitated by the vagus nerve, and it is important in the neuronal reward pathway, which regulates motivational and emotional states. Activating the vagal gut-to-brain axis, which leads to dopamine release, suggests that modulating dopamine levels could be a potential treatment approach for dopamine-related disorders. Some examples of gut microbiota include Prevotella, Bacteroides, Lactobacillus, Bifidobacterium, Clostridium, Enterococcus, and Ruminococcus , and they can affect dopamine by modulating dopaminergic activity. These gut microbiota are able to produce neurotransmitters, including dopamine, and their functions and bioavailability in the central nervous system and periphery are influenced by the gut-brain axis. Gut dysbiosis is the disturbance of the healthy intestinal flora, and it can lead to dopamine-related disorders, including Parkinson's disease, ADHD, depression, anxiety, and autism. Gut microbes that produce butyrate, a short-chain fatty acid, positively impact dopamine and contribute to reducing symptoms and effects seen in neurodegenerative disorders. Dopamine as a treatment It is important to understand the link between dopamine and gut health, as this could provide information about new therapeutic targets and improve current methods that have been used to prevent and restore deficiencies in dopamine function in different disorders. Most cells in the immune system contain dopamine receptors, allowing processes such as antigen presentation, T-cell activation, and inflammation to be regulated. Further research into this could open up a new possibility for dopamine to be used as a medication to treat diseases by changing the activity of dopamine receptors. Therefore, dopamine is important in various physiological processes, both in the central nervous and immune systems. For example, studies have shown that schizophrenia can be treated with antipsychotic medications which target dopamine neurotransmission. In addition, schizophrenia has also been treated by targeting the dysregulation (decreasing the amount) of dopamine transmission. Studies have shown promising results regarding dopamine being used as a form of treatment. Nevertheless, further research is needed to understand the interactions between dopamine, motivation and gut health and explore how this knowledge can be used to create medications to treat conditions. Conclusion The bidirectional gut-brain connection shows the importance of gut microbiota in controlling dopamine levels. This connection influences mood and behaviour but also has the potential to lead to new and innovative dopamine-targeted treatments being developed (for conditions including dopamine-related disorders). For example, scientists could target and manipulate dopamine receptors in the immune system to regulate the above mentioned processes: antigen presentation, T-cell activation, and inflammation. While current research has shown some promising results, further investigations are needed to better comprehend the connection between gut health and dopamine levels. Nevertheless, through consistent studies, scientists can gain a deeper understanding of this mechanism to see how changes in gut microbiota could affect dopamine regulation and influence mood and behaviour. Written by Naoshin Haque Related articles: the gut microbiome / Crohn's disease / Microbes in charge Project Gallery
- The new age of forensic neurology | Scientia News
Explaining and predicting the behaviour of serial killers Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link The new age of forensic neurology 14/07/25, 14:58 Last updated: Published: 23/08/23, 16:16 Explaining and predicting the behaviour of serial killers Background Nobody can argue that true crime has taken the media by storm in recent years. In 2021, the search to find Gabby Petito inflamed social media, with the r/gabbypetito subreddit having 120,000 members at its peak. Tiktok ‘psychics’ would amass millions of views by attempting to predict how the case would progress, with predictably terrible results. A small solace remains, however; the fact that increased media presence of murder cases increases the rate at which research into murderers is published. The increase in both research and media attention toward true crime continued through 2022, invigorated by the release of Monster: the Dahmer Story on Netflix, which was viewed on Netflix for over 1 billion hours by its user base. It could be argued that the popularity of this show and others depicting serial killers also increased the publication of research on the neurology of serial killers. The neurological basis of the serial killer refractory period Dilly (2021) encompasses some very interesting correlational research into the neurological factors at play in the evocation of the serial killer refractory period. Following analysis of the refractory periods of ten American serial killers, a metaanalysis of prior research was performed to establish which prior theory most thoroughly explained the patterns derived. The American serial killers utilised in this investigation were: The Golden State Killer, Joseph James DeAngelo. Jeffrey Dahmer. Ted Bundy. John Wayne Gacy. The Night Stalker, Richard Ramirez. The BTK Killer, Dennis Rader. The I-5 Killer, Randall Woodfield. Son of Sam, David Berkowitz. The Green River Killer, Gary Ridgway. The Co-Ed Killer, Edmund Kemper III. Theory no. 1 While this research is purely speculative due to the lack of real-time neurological imaging of the killers both during refractory periods and their murderous rampages, this research was demonstrated to lend credence to a prior theory proposed by Simkin and Roychowdhury (2014). This research, titled Stochastic Modelling of a Serial Killer , theorised based on their own collated data that the refractory period of serial killers functions identically to that of the refractory period of neurons. This theory is based upon the idea that murder precipitates the release of a powerful barrage of neurotransmitters, culminating in widespread neurological activation. In line with neurological refractory periods, it is believed that this extreme change in state of activation is followed by a period of time wherein another global activation event cannot occur. Theory no. 2 Hamdi et al. (2022) delineates the extent to which the subject’s murderous impulses were derived from Fregoli syndrome, rather than his comorbid schizophrenia. This research elucidated how schizophrenic symptoms can synergise with symptoms of delusional identification syndromes (DIS) to create distinct behaviours and thought patterns that catalyse sufferers to engage in homicidal impulses. DIS include a range of disorders wherein sufferers experience issues identifying objects, people, places or events; Fregoli Syndrome is a DIS characterised by the delusional belief that people around the sufferer are familiar figures in disguise. The subject’s Fregoli Syndrome caused the degeneration of his trust of those around him, which quickly led to an increase in aggressive behaviours. The killer attacked each member of his family multiple times before undertaking his first homicide- excluding his father, whom reportedly ‘scared him very much’. Unsurprisingly then, his victim cohort of choice for murder were older men. The neurobiological explanation of Fregoli Syndrome asserts that the impairment of facial identification, wherein cerebrocortical hyperactivity catalyses delusional identification of unfamiliar faces as familiar ones. Conclusion Forensic neurology has been a key element in expanding the understanding of serial killers, with the research of Raine et al. (1997) popularising the use of neurology to answer the many questions posed by the existence of serial killers. Since Raine, Buchsbaum and LaCasse of the 1997 study first used brain scanning techniques to study and understand serial killers, the use of brain scanning techniques to study this population has become a near-perfect art, becoming ever more of a valid option for use both in understanding and predicting serial killer behaviour. In all likelihood, future innovations in forensic neurology research will continue to bring about positive change, reducing homicidal crime with the invention and use of different methods and systems to predict and stop the crimes before they happen. Summarised from a full investigation. Written by Aimee Wilson Related articles: Serial killers in healthcare / Brain of a bully Project Gallery
- Can what we eat, breathe, and do for a living affect our Parkinson’s risk? | Scientia News
New research suggests that the cause extends far beyond the nervous system Facebook X (Twitter) WhatsApp LinkedIn Pinterest Copy link Can what we eat, breathe, and do for a living affect our Parkinson’s risk? Last updated: 21/03/25, 11:59 Published: 10/04/25, 07:00 New research suggests that the cause extends far beyond the nervous system Introduction Parkinson’s disease (PD) is the most prevalent movement disorder and the second most common neurodegenerative disorder worldwide. PD is best known for causing tremors and stiffness, but it’s much more than a movement disorder. It also affects mood and speech. While PD is caused by the loss of dopamine-producing neurons in the brain’s substantia nigra, new research suggests that its roots may extend far beyond the nervous system. Surprisingly, the gut microbiome – trillions of bacteria living in our digestive tract – may play a key role in both the development and prevention of PD. These microbes help regulate inflammation and support brain health by influencing microglia, the brain’s immune cells. Diet also seems to matter: a Mediterranean-style diet rich in fruits, vegetables, and healthy fats appears to lower PD risk, while smoking – despite its well-known dangers – has been linked to a puzzling protective effect, possibly due to nicotine’s impact on the brain. Meanwhile, specific jobs, like farming, may increase PD risk due to pesticide exposure, which has been associated with neurodegeneration. The idea that what we eat, breathe, and do for a living could shape our brain health is intriguing. As research continues to uncover these surprising links, it raises an important question: could simple lifestyle changes help protect against neurodegenerative diseases? Gut-Brain Axis The gut-brain axis (GBA) is a two-way communication network between the enteric nervous system of the gastrointestinal (GI) tract and the central nervous system, connecting emotions and cognition with the intestines’ functions. This involves the brain sending signals to the gut and vice versa, which happens through the vagus nerve, gut hormones and the gut microbiome, which can produce chemicals to impact brain activity. This usually explains why stress signals from the brain can influence the digestion of food, causing symptoms such as stomach pain, bloating or changes in bowel movements. Alternatively, signals travelling from the gut to the brain can be seen when we eat something that makes us feel sick – we naturally avoid that food and the place where we ate it. Gut dysbiosis can be triggered by multiple factors, including diet, antibiotic use, infection, inflammation, and chronic stress. Dysbiosis is the imbalance in the composition and activity of the microbiota (microorganisms present in the gut). It is considered a risk factor for PD, but is not a direct cause of it. Changes in the microbiota can induce metabolic changes, which can result in increased local and systemic inflammation in addition to increased permeability of the intestines, making the gut ‘leaky’. Additionally, this can cause increased harmful gut bacteria (such as E. coli or Salmonella ) as they leak through the intestinal lining, producing amyloid proteins which can travel to the brain and cause the accumulation of α-synuclein – a protein linked to neurodegenerative diseases such as PD. There is also a reduction in healthy gut bacteria – which usually produce short-chain fatty acids (SCFAs) such as butyrate – which reduce inflammation and protect the brain cells. Less SCFAs cause an increase in inflammation and loss of the neuroprotective effects of SCFAs. Increased inflammation can eventually cause the weakening of the gut lining and a cycle of worsening dysbiosis, increased inflammation and increased α-synuclein accumulation, which spreads to the brain. Furthermore, gut dysbiosis can decrease the efficacy of dopaminergic treatments, which may be used to treat PD. In gut dysbiosis, harmful bacteria can produce an enzyme called dopa-decarboxylase – which converts Levodopa (a drug used to treat PD) into dopamine within the intestines. Hence, less Levodopa reaches the bloodstream and the brain, where it primarily acts and is converted to dopamine. This results in less Levodopa being converted to dopamine within the brain, reducing the effectiveness of the treatment. Consequently, this leads to motor symptoms and impairments such as tremors, which is a characteristic symptom of PD. Can food protect the brain? Could your diet be influencing your brain health in ways you never imagined? Research suggests that what you eat might play a critical role in either protecting your brain from PD or increasing your risk. People who follow a Mediterranean diet (MD) – rich in olive oil, fish, fruits, vegetables, whole grains, and nuts – may have up to a 25% lower risk of developing PD. Interestingly, this protective effect appears stronger in younger individuals and those in the early stages of PD. So.. what makes the MD so powerful? Gut microbiome boost: the MD promotes beneficial gut bacteria while reducing harmful microbes, supporting overall brain health. Anti-inflammatory effects: fibre from plant-based foods fuels the gut microbiome, leading to the production of SCFAs, which reduce inflammation and may slow PD progression. Mitochondrial protection: compounds in the MD, such as polyphenols in olive oil and omega-3 fatty acids in fish, help repair and protect mitochondria – the powerhouses of our cells. This helps prevent brain cell damage and maintain dopamine function. Neural growth & repair: walnuts and omega-3s may support neuronal growth and reduce protein clumping, a hallmark of PD. On the other hand, a Western diet – high in processed foods, saturated fats, refined sugars, and excess salt – may increase the risk of developing and worsening PD symptoms. Foods commonly associated with faster PD progression include canned fruits and vegetables, soda, fried foods, beef, ice cream, and cheese. Why does this happen? Microbiome disruption: the Western diet fosters an imbalance in gut bacteria, leading to inflammation and potential brain damage. Gut leakiness and neuroinflammation: a diet high in unhealthy fats and low in fibre can damage the gut lining, allowing harmful substances to enter the bloodstream and trigger brain inflammation. Hormonal imbalance: key gut-derived hormones (GLP-1, GIP, and IGN) that help protect neurons are disrupted by poor diet but can be restored through healthier food choices. While diet alone cannot cure PD, growing evidence suggests it can modify the disease course. A diet rich in fibre, healthy fats, and plant-based foods supports gut health, reduces inflammation, and may protect neurons from degeneration. Understanding these diet-microbiome-brain interactions could open new doors to PD prevention and treatment – proving once again that food truly is medicine. The smoking paradox One of the most intriguing findings in PD research is that smokers appear to have a lower risk of developing the disease. Epidemiological studies consistently show that people who smoke are less likely to be diagnosed with PD compared to non-smokers. But why? Scientists believe that nicotine, a key compound in tobacco, may play a neuroprotective role by affecting dopamine-producing neurons – the same cells that are progressively lost in PD disease. Nicotine interacts with receptors in the brain that influence dopamine release, which could help protect these neurons from degeneration. However, clinical trials testing nicotine as a treatment for PD have not shown significant benefits, suggesting that other compounds in tobacco or alternative mechanisms might be involved. Some researchers propose that additional chemicals in cigarette smoke, such as monoamine oxidase inhibitors, antioxidants, or even carbon monoxide at low levels, might contribute to this protective effect. Others suggest that genetic factors or lifestyle differences between smokers and non-smokers could also explain the association. Despite this fascinating link, smoking is not a recommended strategy for preventing PD. The well-documented risks – including cancer, cardiovascular disease, and lung damage – far outweigh any potential benefit. Instead, scientists are investigating whether specific compounds found in tobacco could be harnessed for new treatments without the harmful effects of smoking itself. What about my job? Can your job affect your risk of developing PD? Some studies suggest that certain occupations – like farming – might increase the risk, while others find no clear connection. So, what’s the truth? Let’s break it down. Some research suggests that farmers are more likely to develop PD, possibly due to exposure to pesticides like paraquat and rotenone, which have been linked to brain cell damage. Additionally, heavy metals found in agricultural environments – such as lead and manganese – may contribute to brain inflammation and oxidative stress, both of which play a role in PD. Furthermore, certain metals, including iron, mercury, copper, and manganese, can build up in the brain over time. Scientists believe that long-term exposure could damage the neurons that produce dopamine. However, the exact link isn’t fully understood, and not everyone exposed to these metals develops PD. That said, not all studies agree. Some large-scale research has found no significant link between farming, pesticide exposure, heavy metals and PD risk. This means that while environmental factors might play a role, other things – like genetics, lifestyle, or how long and intensely someone is exposed – could be just as important. So.. should you worry? If you work in farming or are regularly exposed to pesticides and heavy metals, it might be a good idea to take precautions, like using protective equipment and following safety guidelines. However, more research is needed to fully understand how these exposures contribute to PD. For now, staying informed and taking steps to reduce unnecessary exposure to harmful chemicals is a smart approach. What can you do? While there’s no guaranteed way to prevent PD, research suggests that certain lifestyle choices may help reduce the risk. Here are some science-backed steps you can take: 1. Adopt a Mediterranean-style diet: eating a diet rich in whole, plant-based foods, healthy fats (like olive oil and nuts), and lean proteins has been linked to a lower risk of PD. The Mediterranean diet is packed with antioxidants and anti-inflammatory compounds that may help protect brain cells. 2. Stay active: regular exercise isn’t just good for your muscles and heart – it may also help maintain gut health and protect neurons. Activities like walking, swimming, or strength training have been associated with a reduced risk of PD and other neurodegenerative diseases. 3. Limit pesticide exposure: for those in agricultural or industrial settings, protective measures, such as wearing gloves and masks and following safety guidelines, can help reduce exposure to potentially harmful chemicals linked to PD. 4. Monitor gut health: emerging research suggests that the gut microbiome may play a key role in PD. While scientists are still exploring microbiome-targeted therapies, maintaining good gut health by eating fibre-rich foods, fermented foods (like yogurt and kimchi), and staying hydrated may support overall well-being. Conclusion The connection between diet, gut health, lifestyle, and PD is an exciting area of research. While we don’t yet have all the answers, it’s clear that healthy habits – such as eating well, staying active, and minimising harmful exposures – can support both brain and overall health. As science continues to uncover new insights, making informed choices today can help protect your well-being in the long run! Written by Joecelyn Kirani Tan, Hanin Salem, Devikka Sivashanmuganathan & Barayturk Aydin Related articles: TDP43 and Parkinsonism / Diabetes drug to treat Parkinson's REFERENCES Berthouzoz E, Lazarevic V, Zekeridou A, Castro M, Debove I, Aybek S, Schrenzel J, Burkhard PR, Fleury V. Oral and intestinal dysbiosis in Parkinson's disease. Rev Neurol (Paris). 2023 Nov;179(9):937-946. doi: 10.1016/j.neurol.2022.12.010. Epub 2023 Mar 16. PMID: 36934020. Bisaglia M. Mediterranean Diet and Parkinson's Disease. Int J Mol Sci. 2022 Dec 20;24(1):42. doi: 10.3390/ijms24010042. PMID: 36613486; PMCID: PMC9820428. Firestone JA, Lundin JI, Powers KM, Smith-Weller T, Franklin GM, Swanson PD, Longstreth WT Jr, Checkoway H. Occupational factors and risk of Parkinson's disease: A population-based case-control study. Am J Ind Med. 2010 Mar;53(3):217-23. doi: 10.1002/ajim.20788. PMID: 20025075; PMCID: PMC3299410. Gorell JM, Johnson CC, Rybicki BA, Peterson EL, Richardson RJ. The risk of Parkinson's disease with exposure to pesticides, farming, well water, and rural living. Neurology. 1998 May;50(5):1346-50. doi: 10.1212/wnl.50.5.1346. PMID: 9595985. hms.harvard.edu . (2017). The Gut and the Brain. [online] Available at: https://hms.harvard.edu/news-events/publications-archive/brain/gut-brain . Hrncir, T. (2022). Gut Microbiota Dysbiosis: Triggers, Consequences, Diagnostic and Therapeutic Options. Microorganisms, [online] 10(3), p.578. Available at: https://pmc.ncbi.nlm.nih.gov/articles/PMC8954387/#:~:text=Dysbiosis%20can%20be%20caused%20by,food%20additives)%2C%20and%20hygiene .. Jackson A, Forsyth CB, Shaikh M, Voigt RM, Engen PA, Ramirez V, Keshavarzian A. Diet in Parkinson's Disease: Critical Role for the Microbiome. Front Neurol. 2019 Dec 10;10:1245. doi: 10.3389/fneur.2019.01245. PMID: 31920905; PMCID: PMC6915094. Johns Hopkins Medicine (2025). Can Environmental Toxins Cause Parkinson’s Disease? https://www.hopkinsmedicine.org/health/conditions-and-diseases/parkinsons-disease/can-environmental-toxins-cause-parkinson-disease Kwon, D. et al. (2024) ‘Diet and the gut microbiome in patients with parkinson’s disease’, npj Parkinson’s Disease , 10(1). doi:10.1038/s41531-024-00681-7. Physiopedia. (n.d.). Gut Brain Axis (GBA). [online] Available at: https://www.physio-pedia.com/Gut_Brain_Axis_(GBA) . Project Gallery