Improvements?

How to improve? 

This section mostly consists of my discussions with Chatgtp on if it were in the future possible to improve quantum sensors and if these ideas have already been tried out/ are possible. 

-> Quantum sensors

If we wanted to detect neural networks without introducing nanoparticles, one would have to detect neural activity by measuring the small magnetic fields generated by the currents. However, the magnetic fields generated by single neurons are extremely weak and still not measurable (on the order of femtoteslas, 10^-15 Tesla). The research here lies on Improvements in quantum sensing technology, combined with better noise filtering. 

For this reason, the best solution so far seems to be: “Quantum sensors would be placed near the neural tissue. These sensors would interact with quantum dots or nanoparticles introduced into the brain that respond to changes in membrane potential (voltage). These particles emit signals that are amplified using quantum entanglement techniques, enabling real-time, non-invasive imaging of neuronal firing patterns and synaptic activity.” 

Some related projects are underway, but no one has combined these advanced techniques. For example:

• Optogenetics is used to control neurons with light, but it’s still highly invasive and lacks real-time observation capacity.

• Quantum sensing is being explored for imaging, but only at a theoretical stage with far less focus on clinical applications.

• Super-resolution microscopy has made strides in cellular biology, but hasn't yet achieved real-time imaging of whole neural networks.

Researchers at MIT, Harvard, and Stanford are working on isolated aspects like optogenetics and quantum sensors, but no one has brought together these technologies into a comprehensive system designed to map neural networks and resolve individual neurons at this scale.

-> Optogenetic-Coupled Super-Resolution Network Mapping (OC-SRM)

fMRI shows the areas of activity but can’t reveal how neural networks are wired and work together. Optogenetics aims at controlling neurons with light and high-precision super-resolution microscopy techniques to observe how neural circuits function in real time.  

An option to follow and distinguish neuronal networks, could be by using nano particles or liposomes to deliver genetic material. Using Focused ultrasound (fUS), it would be possible to temporarily open the blood brain barrier in targeted areas, letting the nanoparticles reach the brain. Another option is magnetofection: here nanoparticles are guided by an external magnetic field to specific brain regions. 

Drug insertion could be monitored by: 

• Gene therapy: Lipid nanoparticles have been used in the delivery of mRNA in vaccines, such as Pfizer-BioNTech and Moderna COVID-19. Lipid nanoparticles were used to encase the mRNA molecules facilitating intracellular activity. LNPs are also used in gene therapy for delivering CRISPR/Cas9 gene-editing tools or other genetic materials. 

• Drug delivery: Mesoporous silica nanoparticles (MSNs) are used to carry drugs and target specific coated cells. They are for example being researched in cancer treatment to deliver drugs directly on the tumor site, reducing systemic effects. (This is possible because cancer cells usually have an over expression of proteins on their surface which can be recognized by MSNs).

• imaging: in bioimaging silica-based nanoparticles can be loaded with contrast agents or fluorescent molecules for improved visualization of tissues and organs in clinical diagnostics. These nanoparticles biosensors are also being used to detect biomarkers for diseases like cancer, Alzheimer's, and diabetes. They enhance the sensitivity and specificity of sensors, allowing for earlier diagnosis through the detection of trace amounts of biomolecules.