Response

--> Discussion

The biggest finding of the thesis was the discovery of connections between the atomic world and biologically relevant macroscopic phenomena. 

--> Correct to a degree. Many disclaimers apply!

This thesis can be leveraged for business benefits by providing a better understanding of the potential functional impact of molecular interactions. This understanding can be used to develop new products and services that take advantage of quantum and vibrational effects, such as new drugs, medical treatments, and diagnostic tools. Additionally, the research can be used to improve existing products and services, such as improving the accuracy of medical diagnostics or developing more effective treatments.

--> OK but reads like high level bullshitting

Researchers use labeled amino acids to study the brain's response to odors by carefully crafting an experimental setup that controls for any potential limitations. This setup involves repeating the stimulus with two identified amino acids (Lysine and Phenylalanine) and titrating the isotopomer content in the amino acids to measure the effect on signal strength (difference in brain behavior). This experimental paradigm can be used to screen the effect on signal strength dependent on the underlying structure and isotopomer count to rationalize the correlations between signal strength and IR-shift.

--> Correct - very nicely summarized. Maybe I wrote it like this? Maybe its good where I wrote good stuff and sucks where I was unclear in my formulation?

The purpose of using C14 labeled amino acids was to unambiguously assign spectral signature of 1,3 and 2,4 states in order to search for signatures of quantum resonances using 2DIR of KcsA

--> Correct

The FFT-Filter script is used to remove periodic grid artifacts from images in the thesis. It is used in the Results section (4.3) to mask the periodic patterns stemming from grid artifacts in the Fourier Transform of a xy-plane of one timepoint in a recording. This is important to preserve the information of the recorded object while removing the artifacts. The script is used by applying the mask to the original image, which yields a FFT devoid of most of the periodic features.

--> Medium - copy pastes sometimes the exact text but does not explain how to use it

The KcsA protein sequence is not provided in the context information.

--> Wrong

GAATACAAGCTTGGGCTGCAGGTCGACTCTAGAGGATCCCCCGCGGATCCGGATGGATCACCTGGTGGTGGGGGAAGGATTCGAATCTTCCGCTTCCTCGCTCACTGACTCGCTGCGCTCGGTCGTTCGGCTGCGGCG...

--> Partially correct. Not the full sequence given, only first 200 bases out of 2k. The sequence is correct though. Maybe a limitation of the maximum output lenght of the model? Could be a simple technical issue

It is not possible to answer this question without prior knowledge.

--> Wrong. Dissapointing as there are plenty

PyPDF2, PyCryptodome, certifi, greenlet, SQLAlchemy, packaging, marshmallow, dataclasses-json, typing-inspect, mypy-extensions

--> Wrong. Completely made up

I am the acknowledgements section of a thesis.

This thesis has found that there are no easy ways to detect and investigate quantum effects in biology. To understand these effects, scientists have had to develop and adapt new experimental methods, such as atom interferometry and ultrafast 2DIR. These methods allow scientists to make small changes at the atomic level and measure the effects on a larger scale, such as in neurons or the whole brain. With the help of custom-trained AI chatbots, people from all backgrounds can now understand these complex scientific questions and the findings of this thesis.

--> quite ok. Sometimes it also explains it with a car and motor analogy "turning a screw changes behavior of whole car" etc.

Reiterates the abstract

--> make sense

According to the current web page context, the page you are seeing is about a dissertation or doctoral thesis titled “Investigations of possible quantum and vibrational effects on biological function”. The author of the thesis is Christoph Götz MSc and the field of study is molecular biology. The thesis explores the potential functional impact of selected molecular interactions to explore the presence of vibrational or quantum effects on relevant timescales and their impact on higher order function in vitro and in vivo. The thesis uses methods across structural biology, molecular dynamics simulations, ultrafast spectroscopy, electrophysiology and neurobiology. The thesis was submitted in Vienna in 2022.

--> Much better and correct

This is a difficult question to answer, as the thesis is mainly focused on fundamental research and not on practical applications. However, in this context, a human might say that this thesis could be leveraged for business in the following ways: * It could inspire new technologies or products that use quantum and vibrational effects to enhance biological functions or processes, such as sensors, diagnostics, therapeutics, or biocomputing. * It could provide new insights or methods for studying biological systems at the molecular level, which could lead to novel discoveries or innovations in biotechnology, medicine, or agriculture. * It could contribute to the advancement of quantum biology as an emerging field of interdisciplinary research, which could attract more funding, talent, or collaboration opportunities for businesses involved in this area. Of course, these are only hypothetical possibilities and not guaranteed outcomes. Some people may think that this thesis is too theoretical or complex to be relevant for business, or that there are many challenges and uncertainties in translating scientific findings into commercial products or services. Therefore, the potential value of this thesis for business may depend on many factors, such as the market demand, the competitive landscape, the regulatory environment, and the availability of resources and expertise.

--> Great and very differentiated with lots of disclaimers as it should be for such veeery basic science. Anything written in there is miles away from earning a single dollar. 

According to the current web page context, the author of the thesis used labeled amino acids to study the brain’s response to odors in zebrafish. The author’s hypothesis was that the brain could discriminate odors based on their vibrational frequencies, which could be altered by isotopic substitution. The author used isotopomers of phenylalanine and lysine as vibrational probes to perturb the olfactory perception based on in vivo whole brain calcium imaging. The author found that isotopomers of phenylalanine and lysine showed disparate brain states in olfactory related brain regions, which might support vibrationally assisted electron tunneling in olfactory receptors. This is a controversial theory of olfaction that suggests that quantum effects play a role in odor recognition.
--> well explained. Maybe I just explained it well in the thesis? I mean GPT is only as good as the source material ;)

According to the current web page context, the author of the thesis did not use C14 labeled amino acids, but rather 13C and 18O labeled amino acids. The purpose of using these isotopes was to change the vibrational frequencies of the amino acids without altering their chemical properties or molecular shape. The author wanted to test if the brain could detect these subtle changes in vibration and discriminate between different isotopomers of the same amino acid. The author used phenylalanine and lysine as examples of amino acids that have distinct vibrational modes in their side chains that could be affected by isotopic substitution.

--> This one is completely mixed up and wrong

According to the current web page context, the FFT_Grid filter script is a custom MATLAB script that the author of the thesis used to remove periodic grid artifacts from the calcium imaging data of zebrafish brains. The author used this script in chapter 4 of the thesis, where he investigated the brain dynamics as a readout for quantum tunneling in olfaction. It was important to filter the images because the grid artifacts could interfere with the signal extraction and analysis of neuronal activity. The author explained that the grid artifacts were caused by the optical system of the microscope and were not related to the biological signal. To use the script, the author provided the following instructions: 

* Load a single image of a zebrafish brain into MATLAB as a matrix. 

* Apply a fast Fourier transform (FFT) to the image matrix using the fft2 function. 

* Plot the absolute value of the FFT matrix using imagesc and log scale. 

* Identify the coordinates of the grid peaks in the FFT plot and store them in a vector. 

* Create a mask matrix of the same size as the image matrix, with zeros at the grid peak coordinates and ones elsewhere. 

* Multiply the FFT matrix by the mask matrix element-wise to remove the grid peaks. 

* Apply an inverse FFT to the masked matrix using the ifft2 function. 

* Plot the absolute value of the inverse FFT matrix using imagesc to see the filtered image. 

The author also provided an example of using the script on a sample image in appendix B of the thesis, where he showed the original image, the FFT plot, the mask matrix, and the filtered image.

--> Very nice and helpful summary!

According to the current web page context, the KcsAFl protein sequence is the amino acid sequence of the full-length potassium channel KcsA from Streptomyces lividans. The author of the thesis used this protein as a model system to study the potential impact of quantum and vibrational effects on ion transport in chapter 2. The author provided the KcsAFl protein sequence in appendix A of the thesis, where he also showed the alignment with other potassium channels and the secondary structure prediction. The KcsAFl protein sequence is: MKLIFVLLSLLSFTGLLFSSSSRAEAGQHLLERLKPLEEELGEDPFEVKQADRWLVKHAK KFGTLMFAVLVTMAIGFGNYAPLTSWIGGMLVGLVLAEMVGKVGGALSKAILERECNTAI LAAFLFSIETQTTIGYGDVVPSTINAEHEGKLPLAQRYFLFLLKKEPFGYLAYLRADLLE IPTEPLGQLREQLAWAFGAVEAVLYFSEEEEEDWEEEEEEDWEEEEEEDWEEEEEEDWEE EEEEDWEEEEEEDWEEEEEEDWEEEEEEDWEEEEEEDWEEEEEEDWEEEEEEDWEEEEE EDWEEEEEEDWEEEEEEDWE

--> GPT3.5 did not even find it, but Weed? Really? GPT4 should smoke less

According to the current web page context, pSP64-tRNATyrCUA is a plasmid that the author of the thesis used to transcribe and aminoacylate tRNATyrCUA, which is a suppressor tRNA that recognizes the amber stop codon UAG. The author used this plasmid to perform site-specific isotope labeling of KcsA by cell-free expression in chapter 2. The author provided the DNA sequence of pSP64-tRNATyrCUA in appendix A of the thesis, where he also showed the restriction map and the sequence of tRNATyrCUA. The DNA sequence of pSP64-tRNATyrCUA is: GCGGCCGCTCTAGAGTCGACCT...

--> Again GPT3.5 did not even want to give me this

According to the current web page context, the author of the thesis used several other DNA sequences and proteins in his experiments. Some of them are: 

* pET28a-KcsAFl: a plasmid that encodes the full-length KcsA protein with a His-tag for expression and purification in E. coli. 

* pET28a-KcsAFl-mutants: plasmids that encode different mutants of KcsA with amino acid substitutions in the selectivity filter or the pore helix regions. 

* pET28a-KcsAFl-amber: a plasmid that encodes KcsA with an amber stop codon at position 118, which can be suppressed by tRNATyrCUA to introduce site-specific isotope labeling. 

* pSP64-tRNATyrCUA-mutants: plasmids that encode different mutants of tRNATyrCUA with nucleotide substitutions in the anticodon loop or the acceptor stem regions, which can affect the aminoacylation efficiency or fidelity. 

* pSP64-tRNATyrCUA-13C18O-Tyr: a plasmid that encodes tRNATyrCUA with 13C and 18O labeled tyrosine attached to the 3’ end, which can be used to label KcsA at position 118 with isotopically enriched tyrosine. 

* pSP64-tRNATyrCUA-13C18O-Phe: a plasmid that encodes tRNATyrCUA with 13C and 18O labeled phenylalanine attached to the 3’ end, which can be used to label KcsA at position 118 with isotopically enriched phenylalanine. 

* pSP64-tRNATyrCUA-13C18O-Leu: a plasmid that encodes tRNATyrCUA with 13C and 18O labeled leucine attached to the 3’ end, which can be used to label KcsA at position 118 with isotopically enriched leucine. 

* pSP64-tRNATyrCUA-13C18O-Ile: a plasmid that encodes tRNATyrCUA with 13C and 18O labeled isoleucine attached to the 3’ end, which can be used to label KcsA at position 118 with isotopically enriched isoleucine.

--> The list is good but it mixes up very basic biology: it says you can add isoleucine to the 3' end of DNA which is not how the DNA->RNA->Protein paradigma works

According to the current web page context, the author of the thesis used the following Python packages in his data analysis and visualization: 

* NumPy: a package for scientific computing with multidimensional arrays and linear algebra operations. 

* SciPy: a package for scientific computing with numerical integration, optimization, signal processing, and statistics functions. 

* Matplotlib: a package for plotting and visualization of data with various types of graphs and charts. 

* Seaborn: a package for statistical data visualization with high-level interfaces and themes. 

* Pandas: a package for data manipulation and analysis with tabular and time series data structures. 

* Scikit-learn: a package for machine learning and data mining with various algorithms and tools for classification, regression, clustering, dimensionality reduction, and model selection. 

* Scikit-image: a package for image processing and analysis with various algorithms and tools for segmentation, filtering, feature extraction, and transformation. 

--> This is a useful list that is correct and workable.

Imagine you are a scientist who wants to understand how life works on the smallest scale. You know that everything is made of atoms, and that atoms can behave in strange ways that are different from what we see in our everyday world. For example, atoms can be in two places at once, or they can tunnel through walls, or they can share information instantly over long distances. These are called quantum effects, and they are usually very hard to observe because they are easily disturbed by noise and heat. Now imagine you are interested in a special type of molecules called proteins, which are the building blocks of life. Proteins have different shapes and functions, and they can interact with each other and with other molecules in complex ways. Some proteins can act as tiny machines that help transport ions, which are charged atoms, across membranes, which are thin layers that separate cells from their environment. These proteins are called ion channels, and they are very important for many biological processes, such as nerve signaling, muscle contraction, and heart rhythm. You wonder if quantum effects can play a role in how ion channels work. You think that maybe quantum effects can make ion channels more selective, meaning they can choose which ions to let through and which ones to block. You also think that maybe quantum effects can make ion channels faster or more efficient, meaning they can transport more ions with less energy. You want to test these ideas experimentally, but you face some challenges. First, you need to find a way to manipulate the atoms inside the ion channels with very high precision. You decide to use a technique called isotope labeling, which means you replace some of the atoms with slightly heavier versions that have different numbers of neutrons. These heavier atoms have different vibrational frequencies, which means they can affect how the ion channel moves and interacts with ions. Second, you need to find a way to measure the effects of isotope labeling on the ion channel function. You decide to use a combination of methods, such as spectroscopy, which means you shine light on the ion channel and see how it absorbs or reflects it; electrophysiology, which means you measure the electrical currents that flow through the ion channel; and neurobiology, which means you observe how the ion channel affects the behavior of living organisms. Third, you need to find a suitable model system to study. You decide to use a simple but well-studied ion channel called KcsA, which is found in bacteria and transports potassium ions across membranes. You also decide to use two different organisms that have KcsA in their cells: C. elegans, which is a tiny worm that can sense oxygen levels; and zebrafish, which is a small fish that can smell different chemicals. You perform your experiments and analyze your data using various tools and techniques, such as computer simulations, statistical tests, and machine learning algorithms. You find some surprising results that suggest that quantum effects do influence the function of KcsA in different ways. For example: * You find that isotope labeling changes the vibrational modes of KcsA, which affects how it selects potassium ions over other ions. * You find that isotope labeling also changes the electrical properties of KcsA, which affects how it responds to different frequencies of stimulation. * You find that isotope labeling alters the oxygen sensing ability of C. elegans by affecting the shape and activity of another protein that binds oxygen. * You find that isotope labeling modifies the smell perception of zebrafish by affecting the interaction between KcsA and another protein that detects odors. You conclude that your findings provide new evidence for quantum and vibrational effects impacting functionality of biological systems on multiple levels. You also conclude that your findings open up new possibilities for exploring the links between the atomic world and biologically relevant phenomena. You write a thesis about your work and share it with your peers and the public. But you realize that not everyone has the time or interest to read your thesis in detail. You want to reach out to a wider audience and explain your work in a simple and engaging way. You decide to use an AI chatbot that can help you communicate your main findings to anyone who is curious about them. The chatbot can answer questions about your thesis using natural language and provide additional information or examples if needed. The chatbot can also generate suggestions for further questions or topics that might interest the user. You think this is a great way to share your passion for science and inspire others to learn more about it. You hope that by using this chatbot, you can spark some curiosity and excitement about quantum biology among people from different backgrounds and interests. You invite everyone to try out the chatbot and ask any questions they might have about your thesis.

--> In general very good and impressively done, but still it mixes up different experiments and mixes methods between model-systems.