
by KeAi Communications Co., Ltd.
February 11, 2025
from
SciTechDaily Website

Could COVID-19 have originated
from a fusion
of rare infectious diseases
rather
than wildlife?
A
groundbreaking study
using A.I.-driven
max-logistic intelligence
suggests
exactly that.
A.I.
Uncovers
Hidden
Genetic Clues
that
Challenge COVID-19's Origins
It's
complicated.
The
A.I. specific recipe for Covid-19 may never be recovered,
but using other A.I. techniques can reverse-engineer the
virus up to a point.
Now
enough evidence has been presented suggesting that
Covid-19 itself was a sophisticated bio-weapon made in a
laboratory.
Source
A surprising new study suggests that,
COVID-19 may not have
originated from bats or pangolins, but rather from a rare fusion of
human diseases...
Using an advanced
A.I.-driven approach called max-logistic
intelligence, researchers identified genetic links between COVID-19
and two obscure infections -
glanders and
Sennetsu fever -
potentially rewriting the narrative of how the virus emerged.
Unraveling the Origins of COVID-19
The origins of
COVID-19 remain uncertain despite extensive research.
A
new study published in Advances in Biomarker
Sciences and Technology (ABST) takes an A.I.-driven approach to
analyze DNA methylation patterns at 865,859 CpG sites in blood
samples from early COVID-19 patients.
Led by Zhengjun Zhang from the University of Wisconsin's
Department of Statistics, the study used max-logistic intelligence
to identify strong genetic links.
The findings suggest that COVID-19 may have
resulted from the natural fusion of two rare infectious diseases -
glanders and Sennetsu fever - combined with common human illnesses.

Visualization of
site-site relationship
and site-risk
probabilities.
Credit: Zhang, Z.
A Shift Away from Wildlife Origins
This challenges the widely accepted belief that the virus originated
in bats or pangolins, raising the possibility that previous studies
placed too much emphasis on wildlife origins.
"Establishing such connections across 865,859
CpG sites is quite a challenge, with random correlations
occurring at a probability of less than one in ten million,"
says Zhang.
"However, when factoring in the rarity of
these diseases, the odds of discovering a meaningful link drop
to just one in one hundred million, further strengthening the
validity of these results."
Max-Logistic Intelligence - A Game
Changer?
Max-logistic intelligence has been previously demonstrated in cancer
biomarker studies.
Unlike traditional A.I. algorithms or modern
machine learning techniques such as
random forests, deep learning, and support vector machines,
max-logistic intelligence offers greater interpretability,
consistency, and robustness, making it especially useful for
establishing causal relationships.
Zhang emphasized that while identifying reliable biomarkers is
critical for scientific progress, many gene markers identified in
isolated studies fail in other cohorts, resulting in low or no
cross-group commonality.
"DNA methylation, the process by which methyl
groups are added to DNA, plays a central role in gene expression
and disease development," explains Zhang.
"Errors in methylation can trigger diseases,
prompting studies into COVID-19's DNA methylation patterns."
Reference
|