The 1918-1920 influenza pandemic was one of the deadliest epidemics of our century. Yet its vast impact remains difficult to comprehend due to lack of high-coverage genomes from medical historical specimens [5, 6]. Therefore, this research provides precisely dated and fully sequenced pandemic wave genome from Europe – for which precise dates and sequence data exist.
1. Background
DNA of living organisms not only contains code for proteins but also long-range global patterns and correlations that cannot be seen with linear perspectives alone. These features can be seen through non-coding portions of human genome (the 98% that does not code genes), including non-coding portions called non-encoded regions which encode information as waves; this wave form can be detected using Dynamic Light Scattering Laser or DLSL spectrometer.
Researchers have reported that certain viruses can be identified using this technology, suggesting there may be additional ways DNA communicates information to cells, tissues and organisms besides simply passing along genetic instructions.
These new methods can be applied to analyze pandemic waves, as illustrated by the 1918-1920 influenza pandemic. Unfortunately, due to a limited sample of virus genomes from this pandemic, its multi-wave nature remains poorly understood. Recent research from Russia has hinted at its multi-wave nature – although recent work suggests otherwise; recent findings from Russian researcher Peter Gariaev show how wave genetics may play an integral part.
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2. Methods
Dynamic light scattering laser spectroscopy was employed in order to conduct wave genome Germany. This technique measures how material scatters impacting laser light which is then used to study its structure. The scattering pattern shows vibration modes of molecules in solution; by analyzing this vibration data we are able to identify relevant chromosomal segments, as well as identify ancestral blocks of the chromosomes as well as any possible admixture events that occurred through this information-rich scattering pattern.
This method can have its limitations when it comes to detecting small and informative ancestral blocks in empirical data, so we used a much wider window of overlapping chromosomes in order to increase its power for detection of ancestral blocks. Since data is often noisy and needs filtering in order to avoid false positives, supervised learning algorithms were utilized as well to remove noise from our results and ensure greater accuracy of admixture analyses.
As whole-genome sequencing can only be applied to limited samples due to its high cost, its utility cannot easily be evaluated in other settings such as epidemiological studies. Luckily, however, an alternative protocol known as phenol/chloroform-free protocol allows this technique to be performed on smaller sample sizes – and has proven successful through published negative controls.
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3. Results
The results of Wave Genome Germany demonstrate how an innovative new approach to genomic sequencing can enhance detection of historical admixture events and provide important biological insights not available through traditional biochemical methods. The approach centers around geometric optics of chromosomes as a nonlocal unique biohologram that transmits genetic information for each individual via its scalar wave diffraction grating; its signal being transmitted across space and time and explaining why genes cannot exist without their respective genome.
To test our method, we conducted a genome wide association study (GWAS) on COVID-19 genomes from nine European countries collected between February 2022 and June 2023. The GWASs identified several SNPs associated with admixture such as G16D and L283P substitutions that may have provided advantages during early pandemic phases; several markers associated with Omicron variant were most prevalent among Italian cases from December 2021-2023.
We compared our GWASs with those from other studies using long COVID HGI data freeze 4. Estonia had the best performing GWAS with an R-squared value of 0.16 and an average admixture time of 24.9 generations, followed by Finland (0.4) and a Czech study with 0.25 R-squared value and 18.4 generation average admixture times respectively.
Our results from these GWASs indicate that the geometric recurrence method can detect ancient admixture events in Europe; however, its detection may be limited due to low density of informative SNPs in our dataset. Therefore, it would be worthwhile pursuing efforts towards gathering larger-scale and higher quality GWAS datasets so as to detect additional ancient admixture events.
Russian research by Peter Gariaev and his colleagues has demonstrated that, at their core, biochemical molecules consist of quantum fields which seem insubstantial; this discovery could have significant ramifications on our understanding of living systems as a whole and how to harness its power for treating disease more effectively.
4. Conclusions
Swabian chromosomes share many segments with Germans, suggesting low inbreeding rates; this fits well with the theory that most genetic variation arises through population founder events. Furthermore, inbreeding among Swabians and other Europeans appears minimal; indeed it appears negligible among this two-group combination.
There is the possibility that the 98% non-coding part of DNA, known as its ‘junk’, may contain global patterns and long-range correlations invisible from linear perspectives. If so, these non-coding sequences could ultimately be transported or “teleported” immaterially and nonlocally creating quantum spin interference patterns with vacuum.
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