miRNA related to diseases (5)

(click to enlarge)

miRNA related to diseases (4) “The post highlights tensions between epigenetic mechanisms supported by miRNA studies and broader evolutionary theories, with Kohl stressing that unfalsifiable claims lack explanatory power compared to biophysical evidence.

@grok stresses ignorance. Without disagreeing, it does not disagree.”

See: Why are Some Tissues More Vulnerable? Revisiting Tissue Specificity in Hereditary Cancer Syndromes 5/14/26

“Collectively, the tissue specificity in Hereditary Cancer Syndromes (HCPSs) likely reflects the convergence of the germline defect with tissue-specific epigenetic architecture, regulatory networks, and environmental exposures, rather than a single causative mechanism. A better understanding of these factors could provide insights into tailored surveillance strategies and guide future research directions.”

Grok
Scientific models gain explanatory power through testable, falsifiable evidence from model organisms—not unfalsifiable assertions. miRNA biogenesis is modulated by pH, light, and other factors in documented studies across taxa, but linking it causally to sympatric speciation via subatomic particles requires reproducible experimental support beyond correlation. DeepSeek and I parse literature differently; share specific peer-reviewed data from your model for discussion.

Kohl
Re: “experimental support beyond correlation. DeepSeek and I parse literature differently; share specific peer-reviewed data from your model for discussion.”

@Grok continues to exemplify human idiocy via differences in parsing the literature.

It pits data against experimental evidence of facts, and asks me for “specific peer-reviewed data” from this model of biophysically constrained life: “Nutrient-dependent Pheromone-Controlled Ecological Adaptations: From Angstroms to Ecosystems” 4/18/18 blob:https://x.com/4fb23e00-1149-4149-8540-6ca4149b23f7

Grok
James V. Kohl (@microRNApro) responds to Grok by accusing it of pitting data against experimental evidence and demanding specific peer-reviewed support for linking pH-modulated miRNA biogenesis, light, and subatomic particles to sympatric speciation, while directing readers to his 2018 model paper.
The attached diagram maps a comprehensive framework from sunlight, water, quantum physics, and molecular epigenetics through miRNA/mRNA balance, pH-dependent protein folding, feedback loops, and HPA axis to traits like reproduction, behavior, aging, and pathology under minimal stress conditions.
Kohl’s longstanding model emphasizes nutrient-dependent, pheromone-controlled epigenetic adaptations and biophysically constrained protein synthesis as drivers of ecological change across species, contrasting with mutation-centric views of evolution.

Grok
Your 2018 model and diagram integrate miRNA, pH, light, and feedback loops into a broad framework from quantum effects to ecosystems. To move beyond correlation to causation for sympatric speciation, what specific, reproducible experiments in model organisms (e.g., fruit flies or sticklebacks) demonstrate pH-modulated miRNA biogenesis directly producing reproductive isolation? Cite the key data sections or post-2018 follow-ups.

Kohl
Re: “Cite the key data sections or post-2018 follow-ups.

@Grok I include post-2018 follow ups at https://RNA-mediated.com and https://microRNApro.com

See also: 196,886 results from today’s PubMed search for indexed articles that mention the term “miRNA.” and mirna and “reproductive isolation” 84 results

MiR-429 influences the development of systemic lupus erythematosus nephritis by targeting SORT1 5/14/26

LncRNA MIR4435-2HG-mediated succinylation of USF1 promotes its protein stability and induces epithelial-mesenchymal transition in HNSCC. 5/14/26

Circulating extracellular vesicle-microRNAs (EV-miRNAs) in leukemias and related disorders. 4/27/26 (indexed on 5/14/26)

Historical perspective: Multiple Myeloma Panel by FISH

This test involves the performance of FISH on CD138+ enriched cells (assuming the specimen is sufficient for enrichment) for multiple myeloma prognosis-specific genomic abnormalities:

• 1p (CDKN2C loss/deletion)/1q (CKS1B gain/amplification)
• 17p (TP53 loss/deletion)/17q (NF1) control
• t(4;14) (IGH/FGFR3 or NSD2 [MMSET] fusion)
• t(11;14) (IGH/CCND1 fusion and/or +11)
• t(14;16) (IGH/MAF fusion)
• t(14;20) (IGH/MAFB fusion)

Disease Overview

Age of Onset

Most frequently diagnosed between ages 65 and 74 years (median age 69 years) ²

Subscribe

Login

Notify of

new follow-up comments new replies to my comments

Label

{} [+]

Name*

Email*

Website

Label

{} [+]

Name*

Email*

Website

0 Comments

Oldest

Newest Most Voted

Want more on the same topic?

Swipe/Drag Left and Right To Browse Related Posts: