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Tthis paper is NOT reliable. A non-exhaustive list of problems in no particular order appears below, but first let's consider their Results:

Regarding the question: "Question: Do the results really indicate reverse-transcription of viral mRNA...?" They provide results suggesting this, but missing key additional data (see Figure 5 comments below).

Regarding the question: "Do the results really indicate ... integration of the cDNA into the genome of this cell line?" No, they provide no evidence of that (see Figure 5 comments below).

Regarding the question: " If so, to what extent is this relevant to side-effects of the vaccine administered in the clinic." As they fail to convincingly show the above points, and are working in a cell line system of questionable relevance to normal human cells in the body, this paper seems to have no real relevance to side-effects of the vaccine administered in the clinic. See below comments.

This paper is NOT reliable. A non-exhaustive list of problems in no particular order appears below, but first let's consider their Results:

1. It's clear they don't understand some of the features they discuss, such as LINE1 elements, calling LINE1 "endogenous reverse transcriptase" when they are actually transposons. They also seem to think there is just one LINE1 gene, not understanding that they are present in thousands of copies throughout the genome (having "jumped" into many genes).

2. It's clear they don't understand how to do statistics properly. If you just do more and more comparisons between different experiments, eventually you will find a difference just by chance. To correct for this, you must reduce your significance threshold proportional to the number of comparisons you make. This is called "Bonferroni correction" and there is no evidence they used it. As far as I can tell, after the Bonferroni correction is applied, essentially none of their meaningful comparisons end up being statistically significant.

3. Their main "control" consists of no vaccine, rather than a dummy/different vaccine. Effects associated with vaccine presence could for example be due to the lipid nanoparticles or modified RNA -- that is, they could be non-specific responses.

4. The fundamental flaw: as a stand-in for human cells, they use only a highly chromosomally abonormal cultered liver cancer cell line Huh-7. According to a description of the line, "The majority of Huh-7 cells show a chromosome number between 55 and 63 (mode 60) and are highly heterogeneous." (normal cell count is 46) In addition to "...containing many mutations and INDELS, it is worthy to note the Huh7 cells have a point mutation in the p53 gene."

5. The LINE1 protein they image likely appears in tumor cell lines (like the Huh-7 line they use), but not in normal cells. From "Methods Mol Biol. 2016; 1400: 261–280. doi: 10.1007/978-1-4939-3372-3_17 ""Using immunohistochemistry, we found nearly half of human cancers stain positively for ORF1p, with immunoreactivity in some common cancers approaching 100% of cases. No staining was observed in the cognate normal tissues"

1. It's clear they don't understand some of the features they discuss, such as LINE1 elements, calling LINE1 "endogenous reverse transcriptase" when they are actually transposons. They also seem to think there is just one LINE1 gene, not understanding that they are present in thousands of copies throughout the genome (having "jumped" into many genes).

2. It's clear they don't understand how to do statistics properly. If you just do more and more comparisons between different experiments, eventually you will find a difference just by chance. To correct for this, you must reduce your significance threshold to take into account the number of comparisons you make. An easy way of doing this is called "Bonferroni correction" and there is no evidence they used it or any other such correction. As far as I can tell, after the Bonferroni correction is applied, essentially none of their meaningful comparisons end up being statistically significant.

3. Their main "control" consists of no vaccine, rather than a dummy/different vaccine. Effects associated with vaccine presence could for example be due to the lipid nanoparticles or modified RNA -- that is, they could be non-specific responses.

4. The fundamental flaw: as a stand-in for human cells, they use only a highly chromosomally abonormal cultered liver cancer cell line Huh-7. According to a description of the line, "The majority of Huh-7 cells show a chromosome number between 55 and 63 (mode 60) and are highly heterogeneous." (normal cell count is 46) In addition to "...containing many mutations and INDELS, it is worthy to note the Huh7 cells have a point mutation in the p53 gene."

5. The LINE1 protein they image likely appears in tumor cell lines (like the Huh-7 line they use), but not in normal cells. From "Methods Mol Biol. 2016; 1400: 261–280. doi: 10.1007/978-1-4939-3372-3_17 ""Using immunohistochemistry, we found nearly half of human cancers stain positively for ORF1p, with immunoreactivity in some common cancers approaching 100% of cases. No staining was observed in the cognate normal tissues"

No, this paper is NOT reliable. A non-exhaustive list of problems in no particular order:

The Zhang et al. (PNAS May 25, 2021 118 (21) e2105968118; https://doi.org/10.1073/pnas.2105968118 ) paper mentioned at the end of your question is discussed in my answer to a Medical Sciences StackExchange question: MedicalSciencesQuestionAboutZhangPaper The summary of my answer to "can the SARS-COV-2 RNA modify our DNA[based on this paper]" is "The short answer is maybe, but rarely, and the whole Covid virus has never been seen to integrate into the cell's DNA intact. Any integration requires "helper" molecules not found in the Covid virus, and only very rarely found in a normal cell."

Tthis paper is NOT reliable. A non-exhaustive list of problems in no particular order appears below, but first let's consider their Results:

Figure 2: Yes, they show that BNT162b2 vaccine mRNA enters the cultured cells. However, all their statistical comparisons except for those against the controls are invalid -- see pt. 2 below.

Figure 3: They fail to show that BNT162b2 affects LINE1 mRNA levels. First, the control plots are visually not different from those of the vaccine-treated samples. Second, essentially all their statistical comparisons seem to be invalid -- see pt. 2 below.

Figure 4: Fluorescence always makes pretty pictures, but this figure again seems to fail to show anything useful. First, the LINE1 protein antibody used binds to the LINE1 ORF1 protein, which does not have reverse transcriptase activity, rather than the ORF2 protein, which does contain reverse transcriptase activity. An anti-ORF2 Ab is available, but they did not use it. Also, from Fig. 3 we see no significant difference in LINE1 RNA levels, so LINE1 protein levels would be unlikely to vary. Finally, the statistical comparisons shown are likely to be invalid -- again, see pt. 2 below.

Figure 5: This section claims to detect reverse-transcribed BNT162b2 in DNA preps from buffer-washed cells previously exposed to BNT162b2. Maybe they have, but key controls are missing.

The one piece of evidence shown is successful PCR amplification of a segment of the vaccine sequence. They do show some useful controls, such as lanes for cells not treated with the vaccine, but miss other essential controls such as cells treated with a different mRNA vaccine not containing that amplicon, and DNA from relatively karyotypically and morphologically normal cultured cells treated with BNT162b2, another mRNA vaccine, or nothing. It's all too easy to have a few stray molecules of a DNA fragment present in the lab (like the BNT162b2 PCR amplicon) contaminate other samples and lead to false positives after lots of cycles of amplification. They also provide no evidence any reverse-transcribed BNT162b2 is integrated into the cells' genomic DNA.

As for the paper's significance to BNT162b2 influence on actual normal human cells, there really isn't any because of how abnormal this immortalized liver tumor-derived cell line is in terms of of genomic stability and of gene expression. It's sort of like using Godzilla as a model organism for humans.

The promised non-exhaustive list of problems:

The Zhang et al. (PNAS May 25, 2021 118 (21) e2105968118; https://doi.org/10.1073/pnas.2105968118 ) paper mentioned in this paper is discussed in my answer to a Medical Sciences StackExchange question: MedicalSciencesQuestionAboutZhangPaper The summary of my answer to "can the SARS-COV-2 RNA modify our DNA[based on this paper]" is "The short answer is maybe, but rarely, and the whole Covid virus has never been seen to integrate into the cell's DNA intact. Any integration requires "helper" molecules not found in the Covid virus, and only very rarely found in a normal cell."