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REVIEW 4 major objections 4 minor 43 references

Thermal Radiosensitization Beyond Misrepair: A Mechanistic Model of Temperature-Enhanced DNA Vulnerability

T0 review · 4 major / 4 minor · reviewed 2026-08-06 · deepseek-v4-flash

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Pith's one-line read Heat makes the DNA molecule itself a bigger target for radiation, and this physical effect — not just disabled repair — carries part of hyperthermia's radiosensitizing power.

desk verdict A plausible physical pathway for thermal radiosensitization, but the load-bearing link between DNA breathing and collision cross-section is asserted, not derived, so the quantitative claims outrun the evidence. read the letter →

arxiv 2507.14712 v1 pith:XZLUBEX3 submitted 2025-07-19 physics.bio-ph physics.med-ph

Jose L. Rodríguez , Edwin Munévar , César A. Herreño Fierro , Adriana M. De Mendoza This is my paper · ORCID
classification physics.bio-phphysics.med-ph
keywords thermalenhancementratiohyperthermiaradiotherapyDNAbreathingPeyrard-Bishopmodeldamagecross-sectionthermoradiotherapyradiosensitization
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

The paper sets out to explain why hyperthermia amplifies the effect of radiation beyond the accepted story of disabled DNA-repair enzymes. It argues that heat also makes the DNA molecule physically more fragile: thermal base-pair openings (DNA breathing) grow exponentially with temperature and enlarge the effective cross-section for collisions between DNA and the ions or particles that cause strand breaks. This physical factor, together with repair inhibition and a few weaker terms, is folded into a mechanistic expression for the thermal enhancement ratio (TER), and the model reproduces the temperature-dependent single-strand-break enhancement seen in isolated plasmids. The conclusion is that the temperature-driven growth of the DNA collision cross-section is the second most influential contributor to TER after repair inhibition, so part of hyperthermia's benefit is a purely physical enlargement of the target.

What carries the argument

The load-bearing object is the effective DNA-ion collision cross-section $\sigma_d(T)$, identified with the average Peyrard–Bishop inter-strand opening $\langle y\rangle(T)$. In that model, a chain of base pairs with harmonic nearest-neighbor coupling and a Morse potential for hydrogen-bond stretching leads to a Schrödinger-type transfer-integral eigenvalue problem, and the ground-state wavefunction gives the mean opening, which in the hyperthermia range is fitted as $m e^{aT}$. The model places $\sigma_d$ inside the damage-rate formula, so that thermally enhanced breathing directly inflates the probability of strand breaks. This identification is what converts DNA thermal fluctuations into a quantifiable, temperature-dependent term of the TER.

What would settle it

A decisive test would be a cell-free experiment that measures strand-break enhancement in the same plasmid preparation while independently measuring DNA-breathing amplitude (e.g., UV hyperchromism or single-molecule FRET) across 37–45 °C. If the TER from dose–response curves does not scale with the measured breathing amplitude, or if purified-DNA TER at fixed temperature is zero after controlling for medium density and diffusion, the central claim fails.

Watch

Extended reading notes

Core claim

The central claim is that thermal radiosensitization has a physical component independent of repair biology: as temperature rises, the mean inter-strand opening $\langle y\rangle(T)$ computed from the Peyrard–Bishop DNA-breathing model grows roughly as $m e^{aT}$ in the therapeutic range 40–50 °C, and this quantity is used as the DNA-ion/particle collision cross-section $\sigma_d(T)$. Inserted into the damage-rate construction of [24] and coupled to a phenomenological repair-inhibition factor, this yields $\mathrm{TER}(T,t)\simeq \exp[a(T-T_0)]\,(1+t c e^{b(T-T_g)})$ (Eq. 34). The model reproduces the temperature trend of plasmid single-strand-break enhancement data [23] when the Peyrard–Bishop coupling constant is $k=3\text{–}4\times10^{-3}\,\mathrm{eV/\AA^2}$, and the paper concludes that this cross-section amplification is the second most influential TER factor after repair inhibition.

Load-bearing premise

The load-bearing premise is that the average one-dimensional base-pair opening $\langle y\rangle(T)$ from the Peyrard–Bishop model is proportional to the two-dimensional collision cross-section $\sigma_d(T)$ between DNA and ionizing species, with no derivation or independent measurement linking the two; if base-pair opening does not enlarge the geometric target, the match to the plasmid data and the ranking of cross-section as the second factor would collapse.

Editorial extensions

If this is right

  • Because the cross-section growth acts only while the DNA is hot, it explains why simultaneous hyperthermia and radiotherapy give the largest TER and why separating the treatments rapidly erodes the enhancement.
  • TER inherits the compact form $\mathrm{TER}\simeq e^{a(T-T_0)}(1+tce^{b(T-T_g)})$: exponential in temperature and linear in treatment time, with the exponential temperature term surviving even in cell-free systems where repair biology is absent.
  • The cross-section term predicts a non-negligible thermal enhancement in purified DNA without any repair machinery, roughly 3–5% over the therapeutic range and up to about 10–20% in the plasmid reference data, so cell-free experiments should see it.
  • Temperature sensitivity dominates treatment duration: the model's sensitivity indices show $S_T$ roughly 40 times larger than $S_t$, making precise thermal control the decisive lever for optimizing combined protocols.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • If the cross-section mechanism is real, the effect should grow with radiation quality: high-LET radiations, where direct DNA hits matter more, ought to show a larger geometric-target enhancement than the low-LET indirect path the paper emphasizes; this is an extension, not a paper claim.
  • A scheduling corollary not drawn by the authors is that short, precisely timed heat pulses synchronized with radiation fractions could capture most of the physical cross-section benefit while limiting cumulative repair-protein denaturation.
  • The identification of $\sigma_d$ with $\langle y\rangle$ could be tested directly by measuring breathing amplitude (UV hyperchromism or single-molecule FRET) and strand-break yield in the same plasmid preparation under identical temperature ramps; the model predicts the two track each other.
  • Chromatin compaction or DNA-bound ligands, by changing the effective collision geometry, would shift TER even without any change in repair capacity; that prediction goes beyond the paper's text.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

4 major / 4 minor

Summary. The paper proposes a mechanistic model of the thermal enhancement ratio (TER) in thermoradiotherapy. Starting from the Deppman radiation-DNA interaction formalism and the LQ model of Chadwick and Leenhouts, it expresses TER as a product of temperature- and time-dependent ratios of physicochemical factors: medium density, ion diffusion distance, ion generation rate, DNA-ion collision cross-section, and the number of vulnerable sites. The central quantitative claim is Eq. (34), TER ≈ exp[a(T-T0)]·(1 + t c exp[b(T-Tg)]), where the exponential factor comes from the Peyrard-Bishop DNA breathing amplitude interpreted as a collision cross-section. The model is compared in Fig. 5 and Table 2 with the Tomita plasmid SSB data for three values of the Peyrard-Bishop coupling k. The paper concludes that, after repair inhibition, the temperature-dependent amplification of the DNA-ion/particle interaction cross-section is the second most influential contributor to TER.

Significance. If the central quantitative claim were established, the paper would make a useful contribution by identifying a fast, repair-independent, physical pathway for the enhanced TER observed under simultaneous hyperthermia and radiotherapy, and by providing a compact closed-form TER expression that could be used in treatment planning. Strengths include the transparent derivation from existing formalisms, the explicit parameter table, the cautionary statements about the scarcity of molecular-level data and the absence of spatial heterogeneity, and the clearly stated plan for Monte Carlo validation. However, the significance of the paper rests on an unsupported identification of the one-dimensional Peyrard-Bishop opening amplitude with the two-dimensional DNA-ion collision cross-section; until that link is derived or measured, the quantitative ranking of mechanisms and the match to Tomita data remain suggestive rather than established.

major comments (4)
  1. [§3.2, Fig. 5, Table 2] The paper identifies the DNA-ion collision cross-section σ_d(T) with the Peyrard-Bishop mean opening <y>(T) without a derivation: <y> is a one-dimensional displacement (Å), while σ_d is a two-dimensional area (m²). Table 1 lists the amplitude m in eV/Ų, which is neither a length nor an area; m cancels in the ratio in Eq. (21) only under the exact proportionality σ_d = m exp(aT), so the unit inconsistency is a symptom of the missing geometric link. If the physical cross-section is σ_d(T) = A + B<y>(T), with A set by the intact duplex radius and B a reaction-radius factor, then the TER ratio is (A+B<y>(T))/(A+B<y>(T0)), which can be substantially smaller than <y>(T)/<y>(T0) when A is not negligible. The claimed 3–5% cross-section contribution in §3.1 and the agreement in Fig. 5 would then not follow. This step is load-bearing for Eq. (34) and must be derived from a geometric model, measured experimentally, or explicitly reframed as an untested scaling assumption.
  2. [§2.7, Eqs. 33–35] The validation against Tomita data is not independent: the Peyrard-Bishop coupling k is scanned over three values, and the two models that match the data are selected after seeing the data. Table 2 shows that at T0=37°C model (b) has a relative deviation of 1.5% while model (c) has 2.2%, contradicting the text's statement that model accuracy improves with increasing k. The comparison uses only single-strand break data from one plasmid study over a narrow temperature range; no DSB data and no cellular data are used. The match in Fig. 5 therefore supports plausibility but not the quantitative claim that the cross-section is the second most influential factor; an out-of-sample test or an a priori constraint on k is needed.
  3. [§2.4, Eq. 21, and §2.7] The claim that the cross-section is the second most influential factor is not supported by the sensitivity analysis as presented. Because TER in Eq. (21) is a product of ratios, the normalized sensitivity index S_x in Eq. (33) equals 1 for every multiplicative factor individually; the paper then computes only S_T and S_t in Eq. (35), not indices that rank σ_d against (n0f0). The ranking in §3.1 rests on the fractional changes of individual factors, which depend on the chosen values of a, b, c, and Tg and on the selected k. Without a decomposition of log TER into additive contributions that includes parameter uncertainty, the ordering of mechanisms is not robust.
  4. [§2.4, Eq. 21, and §2.7] The notation kϵ is used inconsistently. In Eq. (3), d n_i = k ε dl defines kϵ as a number of ions per unit track length, whereas in Section 2.7 the same symbol is modeled as kϵ = t A exp(-Ea/k_B T), an Arrhenius time-dependent rate, and the text asserts that t cancels in the TER. This prevents the reader from verifying the time dependence of Eq. (34). Please clarify whether kϵ is per unit length or per unit time and show explicitly how the cancellation works.
minor comments (4)
  1. [Figure 3 and caption] The caption labels the two panels as (a) and (c), while the body text refers to panels (a) and (b); the logarithmic middle panel is not labeled consistently. Please renumber the panels and update all references.
  2. [§3.2, Table 2] The sentence 'model accuracy improves with increasing k' should be qualified, because at T0=37°C model (b) outperforms model (c) in Table 2.
  3. [Affiliations and typos] There are several typographical errors, including 'Univsersidad' in the affiliation, 'Ramman' for Raman, and 'equiation' in Appendix B; these should be corrected.
  4. [Equation 30 and Appendix C] The recovery of Eq. (30) from Appendix C requires the replacement d → sqrt(2) d, but this step is not explained in the text; please clarify the notation so the two forms can be directly compared.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the P-B-to-Tomita benchmark is external, and the model's exponential TER form is an explicit assumption rather than a fitted prediction.

full rationale

The central claim — that DNA-ion collision cross-section grows with temperature via Peyrard–Bishop (P–B) breathing — is imported from an external theory (Peyrard & Bishop, Ref. [26]) and compared against an external dataset (Tomita et al., Ref. [23]). No Tomita data point enters the P–B calculation; the three coupling constants k are presented as explicit model variants, and variant (a) visibly fails, which gives the comparison falsification content. Equation 34 is constructed by substituting the assumed T-dependencies for sigma_d and n0*f0; the resulting exponential-in-T, linear-in-t form is therefore not an independent discovery, but that is ordinary modeling, not circularity. The only self-citation that enters the model is the misrepair functional form K(T)=c e^{b(T-Tg)} from Ref. [15] (Section 2.5: 'Based on the ideas presented in [15], we propose...'). That term is a background component of Eq. 34 and is independently supported by external references [1,40]; it does not carry the novel claim, which is the P–B cross-section term. The paper itself flags the limited validation base: Section 3.2 states 'To our knowledge, only one study—by Tomita et al. (1995)—has reported both single- and double-strand breaks in isolated plasmid DNA...' and later concedes 'Given the current scarcity of experimental data at the molecular level...'. Real correctness risks exist but are not circularity: sigma_d(T)=m e^{aT} is asserted as the cross-section while m and a are fitted to the P–B mean opening <y>(T) (Section 2.6), Table 1 lists m in eV/Å^2 even though Fig. 3's ordinate is Å, and no derivation converts the 1D opening to a 2D collision area; additionally, the choice of k=3–4e-3 eV/Å^2 is made after inspecting the Tomita agreement (Table 2: 'model accuracy improves with increasing k'), which is post-hoc model selection. These issues weaken the strength of the Fig. 5 match and the 'second most influential' ranking, but they are assumptions and selection choices, not predictions forced by construction or a self-citation chain. No equation in the paper is defined in terms of the quantity it purports to predict, and no parameter fitted to the validation data is recycled as a prediction of that same data. The derivation is therefore self-contained against external benchmarks in the sense relevant to circularity.

Assumptions & free parameters 6 free parameters · 6 assumptions · 0 invented entities

The model rests on established radiobiological frameworks (Deppman damage rate, Chadwick-Leenhouts LQ model) plus two author-specific or ad hoc ingredients: the repair-inhibition term imported from the authors' prior paper [15], and the identification of the temperature-dependent collision cross-section with the Peyrard-Bishop average opening. The latter is the most fragile link because no derivation connects the one-dimensional breathing amplitude to the two-dimensional cross-section, and the fitted parameters a and m depend on the chosen coupling constant k. No new physical entities are introduced.

free parameters (6)
  • a (Peyrard-Bishop exponential temperature coefficient) = 0.0798, 0.0136, 0.0090 K^-1 for k = 2e-3, 3e-3, 4e-3 eV/A^2
    Obtained by exponential fit (R^2 near 1) to the Peyrard-Bishop average opening curves in Fig. 3; used in the TER factor exp[a(T-T0)].
  • m (amplitude of the cross-section exponential) = 1e-10, 0.0222, 0.0584 eV/A^2
    Fitted amplitude of the <y> exponential approximation; the units are inconsistent with a cross-section, and m cancels in TER ratios but defines sigma_d(T).
  • k (Peyrard-Bishop inter-base coupling) = chosen among 2e-3, 3e-3, 4e-3 eV/A^2; best fit k = 3-4e-3
    The standard value k = 2e-3 eV/A^2 overestimates Tomita TER; the two larger values are selected post hoc to match the data in Section 3.2.
  • b (repair-inhibition temperature coefficient) = not reported
    Slope of the denaturation rate K(T) = c exp[b(T-Tg)], imported from ref [15]; value not given and adjustable.
  • c (frequency coefficient in repair-inhibition term) = c approximately 1/min
    From ref [15]; needed for the vulnerable-sites term 1 + t c exp[b(T-Tg)] in Eq. 34.
  • Tg (melting temperature of DNA-repair proteins) = not reported
    Threshold in the repair-inhibition exponential; adjustable parameter from ref [15].
assumptions (6)
  • domain assumption DNA damage rate from radiation follows Deppman's relation with Km = sigma_d k rho0 r_i/(1 + zeta k epsilon)
    Adopted from ref [24] as the physical backbone of the model in Eqs. 8-11.
  • domain assumption Cell survival is governed by the LQ model S(D) = exp(-(alpha D + beta D^2)) with alpha and beta linked to DSB yields
    Assumed in Section 2.2 to convert DNA breaks to survival for the TER derivation.
  • ad hoc to paper Repair inhibition multiplies vulnerable sites by 1 + t c exp[b(T-Tg)]
    Phenomenological rate-limited increase proposed in the authors' prior work [15]; used in Eqs. 22-23 and Eq. 34.
  • ad hoc to paper DNA-ion collision cross-section sigma_d is proportional to the Peyrard-Bishop average opening <y>, approximated as m exp(aT)
    The paper fits <y> to an exponential and uses it as sigma_d without deriving how the 1D opening amplitude sets the 2D collision area (Section 2.6).
  • domain assumption Temperature field is uniform and HT and RT are simultaneous, so treatment time cancels in diffusion and Arrhenius factors
    Stated in Section 2.7; limits applicability to concurrent uniform heating.
  • standard math Ground-state dominance in the Peyrard-Bishop transfer integral and semiclassical expansion of the Gaussian convolution
    Standard statistical-mechanics approximations used in Appendices A and B to solve the transfer integral.

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Cite this review

Pith. "Pith review of Thermal Radiosensitization Beyond Misrepair: A Mechanistic Model of Temperature-Enhanced DNA Vulnerability." pith.science (2026). https://pith.science/paper/XZLUBEX3

@misc{pith2026250714712,
  author       = {Pith},
  title        = {Pith review of: Thermal Radiosensitization Beyond Misrepair: A Mechanistic Model of Temperature-Enhanced DNA Vulnerability},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/XZLUBEX3}},
  note         = {Machine review of arXiv:2507.14712}
}
read the original abstract

Objective: Hyperthermia (HT), characterized by elevated tissue temperatures above physiological levels, is a well-established radiosensitizer. When combined with radiotherapy (RT), forming thermoradiotherapy (TRT), a synergistic effect is observed across in vitro, in vivo, and clinical studies. The greatest radiosensitization occurs when HT and RT are applied simultaneously. This work aims to explore physical mechanisms -- beyond DNA repair inhibition -- that contribute to this synergy. Approach: We developed a biophysical model for the thermal enhancement ratio (TER), incorporating temperature-dependent variations in the number of vulnerable DNA sites, the DNA-ion/particle interaction cross-section, and other physicochemical parameters. These include ion production rate, diffusion processes, and medium density. The model includes misrepair effects phenomenologically, which make it consistent with other studies. Main results: The model reproduces TER values observed under simultaneous HT and RT in isolated plasmids with variable temperature. Our results indicate that, in addition to misrepair, other physical factors contribute to radiosensitization under concurrent treatment. Among these, the temperature-dependent amplification of DNA-ion/particle interaction cross-section -- driven by enhanced DNA thermal fluctuations structure -- emerges as the second most influential factor. Significance: These findings suggest that thermal radiosensitization arises not only from impaired repair, but also from increased physical vulnerability of the DNA. The model provides mechanistic insight for optimizing TRT parameters.

Figures

Figures reproduced from arXiv: 2507.14712 by the authors.

Figure 1
Figure 1. Schematic representation of the mechanisms by which ionizing radiation induces DNA strand breaks. (a) Direct action: Ionizing particles (np) interact directly with DNA molecules, depositing energy that leads to strand breaks at specific sites (nm target molecules). (b) Indirect action: Radiation ionizes water molecules near the DNA, producing reactive oxygen species (ROS). These ions diffuse over a distance ri from … view at source ↗
Figure 2
Figure 2. Biophysical mechanisms of DNA double-strand break (DSB) formation and thermal fluctuations. (a) Two distinct pathways can lead to DSBs: a single-hit DSB results from a single radiation particle or ion directly breaking both DNA strands, while a two-hit DSB occurs when two closely spaced single-strand breaks (within 10 base pairs) lead to a double-strand rupture. (b) Schematic representation of the Peyrard–Bishop mod… view at source ↗
Figure 3
Figure 3. Mean amplitude of DNA thermal fluctuations (DNA-breathing) calculated using the Peyrard–Bishop model [26] (Eqs. 25 and 32) for three different values of coupling between neighboring bases: k = 2.0 × 10−3 eV/˚A 2 , k = 3.0 × 10−3 eV/˚A 2 , and k = 4.0 × 10−3 eV/˚A 2 . The value of the constant k affects the temperature at which denaturation occurs, and therefore is crucial for the DNA-breathing dynamics. Panel (a) sh… view at source ↗
Figures from the paper (2 more)
Figure 4
Figure 4. Figure 4: Sensitivity analysis of the thermal enhancement ratio (TER). Panel (a) shows the evolution of TER as a function of temperature and hyperthermia (HT) treatment duration. Multiple views are provided to enhance visualization of the surface topology, highlighting the expon…
Figure 5
Figure 5. Figure 5: Temperature Enhancement Ratio (TER) as a function of temperature for different values of the stiffness constant k in the Peyrard-Bishop model, labeled as (a), (b), and (c), respectively. TER values were normalized with respect to their corresponding values at 20°C. Mod…

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Reference graph

Works this paper leans on

43 extracted references · 41 canonical work pages

  1. [1]

    Overgaard J 1980International Journal of Radiation Oncology*Biology*Physics61507–1517 ISSN 0360-3016 URL http://www.sciencedirect.com/science/article/pii/0360301680900085

    work page arXiv

  2. [2]

    Horsman M and Overgaard J 2007Clinical Oncology19418–426 ISSN 0936-6555 importance of Radiobiology to Cancer Therapy: Current Practice and Future Perspectives URL http://www.sciencedirect.com/science/article/pii/S0936655507005870

    work page

  3. [3]

    Overgaard J 2013Radiotherapy and Oncology109185–187

    work page

  4. [4]

    Mei X, ten Cate R, van Leeuwen C M, Rodermond H M, de Leeuw L, Dimitrakopoulou D, Stalpers L J A, Crezee J, Kok H P, Franken N A P and Oei A L 2020Cancers12ISSN 2072-6694 URLhttps://www.mdpi.com/2072-6694/12/3/582

    work page

  5. [5]

    Elming P B, Sørensen B S, Oei A L, Franken N A P, Crezee J, Overgaard J and Horsman M R 2019Cancers11ISSN 2072-6694 URLhttps://europepmc.org/articles/PMC6356970

    work page

  6. [7]

    van Leeuwen C M, Oei A L, Chin K W T K, Crezee J, Bel A, Westermann A M, Buist M R, Franken N A P, Stalpers L J A and Kok H P 2017Radiation Oncology121–8 URL https://doi.org/10.1080/02656736.2018.1468930

    work page arXiv 2018

  7. [8]

    Lindegaard J C 1992International Journal of Hyperthermia8561–586 URL https://doi.org/10.3109/02656739209037994

    work page doi:10.3109/02656739209037994

  8. [9]

    Oei A L, Vriend L E M, Crezee J, Franken N A P and Krawczyk P M 2015Radiation Oncology165

    work page

Show all 43 references
  1. [10]

    Lepock J R 2004International Journal of Hyperthermia20115–130 URL https://doi.org/10.1080/02656730310001637334

    doi

  2. [11]

    Lepock J R 2005International Journal of Hyperthermia21681–687 URL https://doi.org/10.1080/02656730500307298

    doi

  3. [12]

    Lepock J, Frey H and Ritchie K 1993Journal of Cell Biology1221267–1276 ISSN 0021-9525 URLhttps://rupress.org/jcb/article-pdf/122/6/1267/385325/1267.pdf

  4. [13]

    Roti-Roti J L 2008International Journal of Hyperthermia243–15 URL https://doi.org/10.1080/02656730701769841

    doi

  5. [14]

    Hildebrandt B, Wust P, Ahlers O, Dieing A, Sreenivasa G, Kerner T, Felix R and Riess H 2002Critical Reviews in Oncology/Hematology4333–56 ISSN 1040-8428 URL http://www.sciencedirect.com/science/article/pii/S1040842801001792

  6. [15]

    De Mendoza A M, Michl ´ ıkov´ a S, Berger J, Karschau J, Kunz-Schughart L A and McLeod D D 2021Scientific Reports111 – 14 URLhttps://doi.org/10.1038/s41598-021-84620-z

    doi

  7. [16]

    De Mendoza A M, Michl ´ ıkov´ a S, Castro P S, Mu˜ noz A G, Eckhardt L, Lange S and Kunz-Schughart L A 2025Physics in Medicine & Biology70025022 URL https://iopscience.iop.org/article/10.1088/1361-6560/ada680

    doi

  8. [17]

    Jungbauer A and Kaar W 2007Journal of Biotechnology128587–596 ISSN 0168-1656 URL https://www.sciencedirect.com/science/article/pii/S0168165606010273 21 IOP PublishingJournalvv(yyyy) aaaaaa Authoret al

  9. [18]

    Parsell D A, Kowal A S, Singer M A and Lindquist S 1994Nature372475–478 ISSN 0168-1656 URLhttps://doi.org/10.1038/372475a0

    doi

  10. [19]

    Seckler R and Jaenicke R 1992The F ASEB Journal62545–2552 URL https://faseb.onlinelibrary.wiley.com/doi/abs/10.1096/fasebj.6.8.1592207

    doi

  11. [20]

    Antonelli F, Campa A, Esposito G, Giardullo P, Belli M, Dini V and et al 2015Radiation Research183417–431 URLhttps://pubmed.ncbi.nlm.nih.gov/25844944/

  12. [21]

    Jakob B, Splinter J and Taucher-Scholz G 2009Radiation Research171405–418 URL https://pubmed.ncbi.nlm.nih.gov/19397441/

  13. [22]

    Chadwick K H and Leenhouts H P 1973Physics in Medicine & Biology1878–87 URL https://doi.org/10.1088%2F0031-9155%2F18%2F1%2F007

  14. [23]

    Tomita H, Kai M, Kusama T and Aoki Y 1995Journal of Radiation Research3646–55 URL https://doi.org/10.1269/jrr.36.46

    doi

  15. [24]

    Deppman A, Echeimberg J O, Gouveia A N, Arruda-Neto J D T, Milian F M, Added N, Camargo M E, Guzman F, Helene O A M, Likhachev V P, Rodriguez O, Schenberg A C G, Vanin V and Vicente E J 2004Brazilian Journal of Physics34958–961 URL https://doi.org/10.1590/S0103-97332004000500068

    doi

  16. [25]

    Ramos-M´ endez J, Garc ´ ıa-Garc ´ ıa O, Dom ´ ınguez-Kondo J, LaVerne J A, Schuemann J, Moreno-Barbosa E and Faddegon B 2022Physics in Medicine & Biology67145007 URL https://dx.doi.org/10.1088/1361-6560/ac79f9

    doi

  17. [26]

    Peyrard M and Bishop A R 1989Phys. Rev. Lett.62(23) 2755–2758 URL https://link.aps.org/doi/10.1103/PhysRevLett.62.2755

    doi

  18. [27]

    Dauxois T, Peyrard M and Bishop A R 1993Phys. Rev. E47(1) 684–695 URL https://link.aps.org/doi/10.1103/PhysRevE.47.684

    doi

  19. [28]

    Joiner Michael C and van der Kogel A J 2009Basic Clinical Radiobiology4th ed (CRC Press) ISBN 978 0 340 929 667

  20. [29]

    Scholz M and Kraft G 1994Radiation Protection Dosimetry5229–33 URL https://doi.org/10.1093/oxfordjournals.rpd.a082156

    doi

  21. [30]

    Radford I R 1985International Journal of Radiation Biology and Related Studies in Physics, Chemistry and Medicine4845–54 URLhttps://doi.org/10.1080/09553008514551051

    doi

  22. [31]

    Fu Q, Wang J and Huang T 2018Journal of radiation research1577–582 URL https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6151638/

  23. [32]

    McMahon S J 2018Physics in Medicine & Biology6401TR01 URL https://iopscience.iop.org/article/10.1088/1361-6560/aaf26a

    doi

  24. [33]

    Zheng D, Preuss K, Milano M T, He X, Gou L, Shi Y, Marples B, Wan R, Yu H, Du H and Zhang C 2025Radiation Oncology201–19 URL https://ro-journal.biomedcentral.com/articles/10.1186/s13014-025-02626-7

    doi

  25. [34]

    Lea D E and Catcheside D G 1942Journal of Genetics44216–245 URL https://link.springer.com/article/10.1007/BF02982830

    doi

  26. [35]

    Scalapino D J, Sears M and Ferrell R A 1972Phys. Rev. B6(9) 3409–3416 URL https://link.aps.org/doi/10.1103/PhysRevB.6.3409

    doi

  27. [36]

    Krumhansl J A and Schrieffer J R 1975Phys. Rev. B11(9) 3535–3545 URL https://link.aps.org/doi/10.1103/PhysRevB.11.3535

    doi

  28. [37]

    Currie J F, Krumhansl J A, Bishop A R and Trullinger S E 1980Phys. Rev. B22(2) 477–496 URLhttps://link.aps.org/doi/10.1103/PhysRevB.22.477

    doi

  29. [38]

    Kassis S, Grondin M and Averill-Bates D A 2021Biochimica et Biophysica Acta (BBA) - Molecular Cell Research1868118924 ISSN 0167-4889 URL https://www.sciencedirect.com/science/article/pii/S0167488920302822 22 IOP PublishingJournalvv(yyyy) aaaaaa Authoret al

  30. [39]

    Alberts B, Bray D, Lewis J, Raff M, Roberts K and Watson J 2002Molecular Biology of the Cell4th ed (Garland)

  31. [40]

    Dikomey E and Jung H W 1991International journal of radiation biology59815–25 URL https://doi.org/10.1080/09553009114550711

    doi

  32. [41]

    Altan-Bonnet G, Libchaber A and Krichevsky O 2003Phys. Rev. Lett.90(13) 138101 URL https://link.aps.org/doi/10.1103/PhysRevLett.90.138101

    doi

  33. [42]

    Jose D, Weitzel S E and von Hippel P H 2012Proceedings of the National Academy of Sciences 10914428–14433 URLhttps://www.pnas.org/doi/abs/10.1073/pnas.1212929109

    doi

  34. [43]

    D’Abramo M, Castellazzi C L, Orozco M and Amadei A 2013The Journal of Physical Chemistry B1178697–8704 pMID: 23799235 URLhttps://doi.org/10.1021/jp403369k

    doi

  35. [44]

    Simon B 2005Functional Integration and Quantum Physics2nd ed AMS Chelsea Series (Providence, RI: AMS Chelsea Publishing) ISBN 978-0821839469 23

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Reviewed August 6, 2026 · model on record in the stance chip above.