PubMed Health⌕ Search

PubMed · 16292895

Transition state theory: variational formulation, dynamical corrections, and error estimates.

Abstract

Transition state theory (TST) is revisited, as well as evolutions upon TST such as variational TST in which the TST dividing surface is optimized so as to minimize the rate of recrossing through this surface and methods which aim at computing dynamical corrections to the TST transition rate constant. The theory is discussed from an original viewpoint. It is shown how to compute exactly the mean frequency of transition between two predefined sets which either partition phase space (as in TST) or are taken to be well-separated metastable sets corresponding to long-lived conformation states (as necessary to obtain the actual transition rate constants between these states). Exact and approximate criterions for the optimal TST dividing surface with minimum recrossing rate are derived. Some issues about the definition and meaning of the free energy in the context of TST are also discussed. Finally precise error estimates for the numerical procedure to evaluate the transmission coefficient kappaS of the TST dividing surface are given, and it is shown that the relative error on kappaS scales as 1/square root(kappaS) when kappaS is small. This implies that dynamical corrections to the TST rate constant can be computed efficiently if and only if the TST dividing surface has a transmission coefficient kappaS which is not too small. In particular, the TST dividing surface must be optimized upon (for otherwise kappaS is generally very small), but this may not be sufficient to make the procedure numerically efficient (because the optimal dividing surface has maximum kappaS, but this coefficient may still be very small).

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Eric Vanden-Eijnden, Fabio A Tal. 2005-11-08. Transition state theory: variational formulation, dynamical corrections, and error estimates.. https://doi.org/10.1063/1.2102898

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Effectiveness of high-dose versus standard-dose influenza vaccines against hospitalisation according to frailty risk: a prespecified analysis of the randomised trial DANFLU-2.

BACKGROUND: Frailty is a major risk factor for influenza-related complications and can influence vaccine effectiveness. We aimed to assess the relative vaccine effectiveness (rVE) of high-dose (HD-IIV) versus standard-dose inactivated influenza vaccine (SD-IIV) in older adults aged 65 years or older according to frailty risk. METHODS: This study was a prespecified analysis of DANFLU-2, an open-label, individually randomised trial, conducted in Denmark during three consecutive influenza seasons (2022-23, 2023-24, and 2024-25). Adults aged 65 years or older were randomised (1:1) to the HD-IIV or SD-IIV group. The primary endpoint was hospitalisation for influenza or pneumonia. Frailty was defined according to the validated Hospital Frailty Risk Score (HFRS) based on ICD-10 codes within 10 years before randomisation. Participants were stratified into three HFRS categories, namely low (<5 points), intermediate (5-15 points), and high (>15 points) frailty risk. The rVE of HD-IIV versus SD-IIV against the primary endpoint was assessed across prespecified HFRS categories and treating HFRS as a continuous variable. Pearson's chi-square test was used to compare safety events across frailty risk groups and randomisation groups. FINDINGS: Among 332&#x2009;438 randomised participants (mean age 73&#xb7;7 years [SD 5&#xb7;8]; 161&#x2009;538 [48&#xb7;6%] were female), 276&#x2009;173 (83&#xb7;1%) had low frailty risk, 52&#x2009;395 (15&#xb7;8%) had intermediate frailty risk, and 3861 (1&#xb7;2%) had high frailty risk. The primary endpoint of hospitalisation for influenza or pneumonia occurred in 1424 (0&#xb7;5%) of 276&#x2009;173 participants with low frailty risk, 761 (1&#xb7;5%) of 52&#x2009;395 with intermediate frailty risk, and 163 (4&#xb7;2%) of 3861 with high frailty risk (relative risk [RR] for intermediate vs low frailty risk 2&#xb7;8 [95% CI 2&#xb7;6-3&#xb7;1]; RR for high vs low frailty risk 8&#xb7;2 [7&#xb7;0-9&#xb7;6]). HFRS as a continuous variable significantly modified the effect of HD-IIV versus SD-IIV against the primary endpoint with higher rVE estimates with increasing HFRS (pinteraction=0&#xb7;020). The rVE was 0&#xb7;2% (95% CI -10&#xb7;8 to 10&#xb7;2) among those with low frailty risk, 13&#xb7;1% (-0&#xb7;4 to 24&#xb7;8) among those with intermediate frailty risk, and 19&#xb7;9% (-10&#xb7;3 to 42&#xb7;1) among those with high frailty risk. No significant interaction was observed when HFRS was assessed according to the prespecified categorical frailty groups (pinteraction=0&#xb7;17). The proportion of participants with at least one serious adverse event increased across frailty risk groups (13&#x2009;366 [4&#xb7;8%] of 275&#x2009;795 for low frailty risk, 5475 [10&#xb7;5%] of 52&#x2009;315 for intermediate frailty risk, and 777 [20&#xb7;2%] of 3850 for high frailty risk; p<0&#xb7;0001), with similar proportions of serious adverse events in the HD-IIV and SD-IIV groups for each frailty risk group. INTERPRETATION: Among adults aged 65 years or older in Denmark, frailty risk might modify the effects of HD-IIV versus SD-IIV against hospitalisation for influenza or pneumonia, with higher rVE estimates with increasing frailty risk. These findings might support considering high-dose influenza vaccines for frail older adults. However, effect modification was not evident when frailty was assessed using prespecified categorical subgroups, and subgroup-specific estimates were imprecise, with 95% CIs crossing the null. These results should be considered exploratory, warranting further investigation. FUNDING: The DANFLU-2 trial was funded by Sanofi.

Journal Article↗