ChatGPT is a language model developed by OpenAI, designed to understand and generate human-like text based on the input it receives. ChatGPT does not predict the future, solve highly technical chromatographic problems, or troubleshoot an instrument for you. So, what can ChatGPT do, and why is the entire world talking about it?
I first want to mention that I am not an AI expert (nor blogger), but rather someone who loves separations, gas chromatography, and anything that could simplify academic work. I believe ChatGPT is such a tool; however, it is sometimes misunderstood for something that it is not. Allow me to share my story with ChatGPT and some of its intriguing “tricks” with you.
In January 2023, just two months after the public release of ChatGPT, I was traveling to the 14th Multidimensional Chromatography Workshop in Liege, Belgium, all the way from Los Angeles (true story). Amid a longer layover, I decided to give ChatGPT a try. The initial requirement was to complete registration, and that&#39;s precisely where my journey took a pause. Tired of repeatedly entering my information and fabricating fake email addresses, I often encountered rapid responses like, &quot;This email address (poopitypoo@gmail.com) does not exist.&quot; Their efficiency left me intrigued. This marked my initial, almost comical first encounter with ChatGPT.
Following an enjoyable conference experience, I made my way back, engaging with my students and prompting them to embark on a paper-writing endeavor. Our starting point was the creation of a paper outline. Concluding the meeting, I strolled to my office (a 90-second walk), receiving a text from my students along the way:
<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/The_LCGC_Blog_Are_You_Sick_of_Hearing_About_Chat_GPT_text_messages_Petr_Vozka_2023_05737766ab/The-LCGC-Blog-Are-You-Sick-of-Hearing-About-ChatGPT-text-messages-(Petr-Vozka-2023).jpg" alt="The LCGC Blog: Are You Sick of Hearing About ChatGPT - text messages (Petr Vozka, 2023)"/>
In no time, the outline landed in my inbox. And at that point, I finished the registration and started exploring ChatGPT&#39;s capabilities. And if you&#39;re wondering why, simply see below: the ChatGPT-generated outline (achieved in under 90 seconds) with the outline I had envisioned (added parts are marked in italics and omitted parts with bold).
<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/The_LCGC_Blog_Are_You_Sick_of_Hearing_About_Chat_GPT_prompt_1_Petr_Vozka_2023_0243dfb1c8/The-LCGC-Blog-Are-You-Sick-of-Hearing-About-ChatGPT-prompt-1-(Petr-Vozka-2023).jpg" alt="The LCGC Blog: Are You Sick of Hearing About ChatGPT - prompt 1 (Petr Vozka, 2023)"/>
<h5>I. Introduction</h5>
A. Brief overview of the importance of olefin quantification in gas chromatography fuels made from plastic waste
B. Introduction of two dimensional gas chromatography (GCXGC) and flame ionization detector (FID)
<h5>II. Method Development</h5>
A. Selection of column dimensions and stationary phases
B. Optimization of GCXGC parameters such as modulation time and flow rate
C. Determination of optimum temperature programs for each column
E. Development of calibration standards using olefinic compounds and saturated hydrocarbons
F. Comparison of FID response factors for olefins and saturated hydrocarbons
G. Derivatization techniques for improving olefin detection and quantification
H. Normalization of chromatograms and calculations
<h5>III. Results and Discussion</h5>
A. Evaluation of the developed method for olefin detection and quantification
B. Comparison of the developed method with existing GC methods ASTM-approved methods
C. Discussion of the advantages and limitations of the developed method
D. GCxGC method linearity
<h5>IV. Conclusion</h5>
A. Summary of the key findings of the study
B. Implications of the developed method for olefin quantification in various industries
C. Future directions for further improvements of the developed method.
So, that isn&#39;t bad, is it? It&#39;s important to note that ChatGPT may not always provide accurate or reliable information, and its responses are based on patterns it learned from its training data. It can sometimes generate plausible-sounding yet incorrect or nonsensical answers, so critical thinking is advised when using its outputs. This aspect becomes particularly evident when ChatGPT is prompt to provide reference suggestions, as the references it generates are mostly made up but sound plausible due to ChatGPT&#39;s lack of direct access to external databases.
<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/The_LCGC_Blog_Are_You_Sick_of_Hearing_About_Chat_GPT_prompt_2_Petr_Vozka_2023_2dd3e9b59a/The-LCGC-Blog-Are-You-Sick-of-Hearing-About-ChatGPT-prompt-2-(Petr-Vozka-2023).jpg" alt="The LCGC Blog: Are You Sick of Hearing About ChatGPT - prompt 2 (Petr Vozka, 2023)"/>
Here are a few examples generated by ChatGPT:
(1) Marriott, P. J., &amp; Shellie, R. (2002). Comprehensive two-dimensional gas chromatography–a review. Journal of Chromatography A, 965(1-2), 175-195.
(2) Phillips, J. B., Harada, R. M., &amp; Reichenbacher, K. (2011). Performance of a two-dimensional gas chromatography system with a nonpolar–polar column combination for the separation of compounds in gasoline and diesel fuels. Journal of Chromatography A, 1218(28), 4391-4397.
Unfortunately, these publications do not exist; however, if they were, we would definitely want to include them in our manuscript.
In a similar manner, ChatGPT can assist you in preparing the structure for the Introduction. Another useful tool is to ask ChatGPT to condense your Abstract if you need to meet a word count requirement. If the Abstract generated by ChatGPT turns out to be too short or long, you can continue with the instructions and direct ChatGPT to extend or shorten it. Alternatively, if you find yourself pressed for time and unable to read an entire paper, you can request ChatGPT to provide a summary of the results for you.
Since English is not my native language, I often use ChatGPT to check my grammar and even to rewrite, polish, or paraphrase certain paragraphs. For example, each paragraph presented here has been reviewed by ChatGPT. (Here is a helpful tip: copy and paste each paragraph individually before proceeding to the next one.) You might even move this one step forward and generate a paragraph.
<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/The_LCGC_Blog_Are_You_Sick_of_Hearing_About_Chat_GPT_prompt_3_Petr_Vozka_2023_aba47a96e0/The-LCGC-Blog-Are-You-Sick-of-Hearing-About-ChatGPT-prompt-3-(Petr-Vozka-2023).jpg" alt="The LCGC Blog: Are You Sick of Hearing About ChatGPT - prompt 3 (Petr Vozka, 2023)"/>
“Using ChatGPT responsibly within academia involves a balanced approach that harnesses its advantages while upholding scholarly principles. Remember, ChatGPT is a tool, not a replacement for critical thinking or original research. To optimize its utility, define the specific aid you need, whether refining language or idea generation. Employ focused and evolving prompts to elicit accurate responses, cross-referencing its suggestions with reliable sources and experts to ensure credibility. While ChatGPT enhances your work, avoid overdependence by using it as a supplementary resource rather than a primary creator. Uphold ethical standards by transparently acknowledging ChatGPT&#39;s contributions in your work. By adhering to these practices, a symbiotic relationship between AI technology and academia can be nurtured, fostering responsible and effective integration.” – ChatGPT, 2023
No, there&#39;s no need to say &quot;please.&quot; I just prefer to be polite, just in case ChatGPT becomes Skynet from “The Terminator” movies one day.
You might come across a rumor suggesting that ChatGPT can answer questions from MIT exams, leading to the assertion that AI could potentially earn a university degree from such esteemed institutions. This was later refuted by several studies, with the conclusion that ChatGPT is indeed not capable of obtaining a degree from MIT. However, ChatGPT can answer simpler questions in a very efficient way. During the COVID-19 pandemic, many universities switched to remote teaching, which included remote student exams. Since students were capable of consistently finding methods to search for answers online despite the exams not being open-book format, one solution was to implement essay-type or true/false questions. However, these are no longer viable options, as ChatGPT can solve these general questions without the need for students to gather information from several sources and writing the summary in their own words (see below).
<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/The_LCGC_Blog_Are_You_Sick_of_Hearing_About_Chat_GPT_exam_answer_1_Petr_Vozka_2023_395cc2443c/The-LCGC-Blog-Are-You-Sick-of-Hearing-About-ChatGPT-exam-answer-1-(Petr-Vozka-2023).jpg" alt="The LCGC Blog: Are You Sick of Hearing About ChatGPT - exam answer 1 (Petr Vozka, 2023)"/>
<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/The_LCGC_Blog_Are_You_Sick_of_Hearing_About_Chat_GPT_exam_answer_2_Petr_Vozka_2023_1712617c72/The-LCGC-Blog-Are-You-Sick-of-Hearing-About-ChatGPT-exam-answer-2-(Petr-Vozka-2023).jpg" alt="The LCGC Blog: Are You Sick of Hearing About ChatGPT - exam answer 2 (Petr Vozka, 2023)"/>
An example of an essay-type question to support my argument could be: &quot;Briefly describe how a TOF mass analyzer works, based on the relationship between flight time (t), mass-to-charge ratio (m/z), and electric field (E).&quot; I haven&#39;t included the answer here, but you can give it a try yourself. As more and more students are using ChatGPT, professors will have to adapt as well.
So, what is the conclusion if there is one at all? Up until now, ChatGPT has remained ad-free and freely accessible, a rarity in my view. So, why not take advantage of it? Just keep in mind that ChatGPT is &quot;only&quot; proficient in a diverse array of natural language processing tasks, encompassing but not limited to: generating text (offering coherent and contextually relevant content based on given prompts, thus facilitating the creation of articles, blogs, poems, and more), completing text (forming sentences or paragraphs, serving as a valuable tool for brainstorming, writing prompts, and content generation), summarizing text (concisely condensing lengthy passages while retaining essential information), translating languages, extracting data (retrieving structured data from unstructured text), and much more.
<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Petr_Vozka_Petr_Vozka_Assistant_Professor_na_California_State_University_Los_Angeles_2_1e25f61f27/Petr-Vozka-Petr-Vozka-Assistant-Professor-na-California-State-University-Los-Angeles-2.jpg" alt="Petr Vozka: Petr Vozka, Assistant Professor na California State University, Los Angeles"/>
<blockquote>
<h4>About the Author: Petr Vozka (<a href="https://gcms.labrulez.com/companies/219">Complex Chemical Composition Analysis Lab (C³AL)</a></h4>
</blockquote>
<blockquote>
<a href="https://gcms.labrulez.com/articles?search=Petr+Vozka">Petr Vozka</a> is an assistant professor of analytical chemistry in the Department of Chemistry and Biochemistry at the California State University, Los Angeles, USA. He is also the director of the Complex Chemical Composition Analysis Lab (C3AL). His research focuses on characterizing complex chemical mixtures using state-of-the-art techniques, such as two-dimensional gas chromatography (GC×GC) and high‑resolution mass spectrometry (HRMS). His primary focus is on developing methods for analyzing products from plastic waste conversion processes and organic compounds adsorbed on microplastics. He has one patent, six military reports, 25 journal publications, and over 30 research presentations, which include 10 invited lectures and invited presentations. He was invited as a keynote speaker to the 14th Multidimensional Chromatography Workshop in 2023.
</blockquote>

The LCGC Blog: Are You Sick of Hearing About ChatGPT?

Scientists gathered around the international software project <a href="https://lcms.labrulez.com/library?search=MZmine">MZmine</a>, led by Dr. Robin Schmid and <a href="https://pluskal.group.uochb.cz/en">Dr. Tomáš Pluskal</a> from the Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, have come up with a new piece of software that significantly speeds up and simplifies the identification of chemicals in tissues. It enables researchers to confidently recognize chemicals and visualize their distribution in organs. Compared to established workflows, the new pipeline requires less work in the laboratory to gain similar insights into the chemistry happening within, for example, tumours and inflammatory lesions. The paper presenting this software to the global scientific community has just been published in the influential scientific journal Nature Communications.
At IOCB Prague, Dr. Robin Schmid is mostly involved in developing the software SIMSEF (spatial ion mobility-scheduled exhaustive fragmentation) together with his colleagues from the group of Prof. Dr. Karst at the University of Münster, Germany, where he was previously based. The work is done in collaboration with the developers of the timsTOF fleX state-of-the-art mass spectrometer from Bruker Daltonics, which enables high-level elucidation of the composition of molecules by measuring the mobility of ions.
‘Up until now, scientists could tell with a mass spectrometer that this was the formula of the molecule they were looking at, but then when they looked at the database and tried to identify this substance, it was very difficult. The reason is that biological samples can contain numerous distinct lipids and combinations of molecules that are often biologically very different. Now, thanks to the new algorithm, it is possible to look inside the molecule, learn what it is made up of and even compare images with each other,’ explains Robin Schmid. This can provide important information, for example that a specific part of the brain contains a different type of lipid than another part of this essential organ and that this particular lipid is absent in other tissue.
<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/UOCHB_Nova_zobrazovaci_metoda_biologickych_vzorku_pomuze_vedcum_a_lekarum_rychleji_identifikovat_napriklad_rakovinne_tkane_Dr_Tomas_Pluskal_c1948c1c8b/UOCHB-Nova-zobrazovaci-metoda-biologickych-vzorku-pomuze-vedcum-a-lekarum-rychleji-identifikovat-napriklad-rakovinne-tkane-Dr.Tomas-Pluskal.jpg" alt="IOCB Prague/Tomáš Belloň: A new imaging method for biological samples will help scientists and doctors to more quickly identify, for example, cancerous tissue"/>
The SIMSEF algorithm was developed in collaboration with medical experts from German and Swiss universities. Crucially for medical doctors, the detection of clinical biomarkers for diagnostic purposes is also significantly accelerated. Learning very quickly, for example, whether they are dealing with a lipid or metabolite that is only found in cancerous tissue plays a critical role in deciding on further treatment. Needless to say, this has great implications for its outcome.
The new algorithm is part of the open-source software package MZmine, which has been helping experts worldwide to analyse mass spectrometry data since 2005. Steffen Heuckeroth from the MZmine team and the Institute of Inorganic and Analytical Chemistry at the University of Münster has been the main developer of the SIMSEF algorithm and is the first author of the paper now published in Nature Communications. He adds: ‘The article in question does not contain any specific discovery in the field of biology. However, thanks to our new method, many scientists can improve and accelerate their work, which opens up room for new discoveries.’
<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/UOCHB_Nova_zobrazovaci_metoda_biologickych_vzorku_pomuze_vedcum_a_lekarum_rychleji_identifikovat_napriklad_rakovinne_tkane_ce3d99705c/UOCHB-Nova-zobrazovaci-metoda-biologickych-vzorku-pomuze-vedcum-a-lekarum-rychleji-identifikovat-napriklad-rakovinne-tkane.jpg" alt="ÚOCHB/Tomáš Belloň: Nová zobrazovací metoda biologických vzorků pomůže vědcům a lékařům rychleji identifikovat například rakovinné tkáně"/>
‘I always think it&#39;s great when we enable other people to improve the working conditions for their research and also to communicate it to other scientists. Thanks to the feedback from the scientific community using MZmine, the program itself directly pushes their research forward,’ adds Robin Schmid from IOCB Prague.
The director of IOCB Prague Prof. Jan Konvalinka points out: ‘Everybody is talking about machine learning and artificial intelligence these days. Our colleagues from Dr. Pluskal’s team are using it to solve highly specific problems in research as well as in clinical praxis.’
The third generation of MZmine, <a href="https://lcms.labrulez.com/article/2726">reported</a> in spring 2023 in the journal Nature Biotechnology, can process thousands of samples per hour. The algorithms newly developed by this international team thus further enhance existing capabilities to link different types of data, including combining data from analytical and imaging methods, which until now has not been possible with any academic or commercial software.

A new imaging method for biological samples will help scientists and doctors to more quickly identify, for example, cancerous tissue

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The Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences (IOCB Prague) is a leading scientific institution in the Czech Republic, recognized internationally. Its primary mission is basic research in the fields of chemical biology and medicinal chemistry, organic and material oriented chemistry, chemistry of natural compounds, biochemistry and molecular biology, physical chemistry, theoretical chemistry, and analytical chemistry. 

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