PubMed Health⌕ Search

PubMed · 11277737

A quantum mechanical/neural net model for boiling points with error estimation.

Abstract

We present QSPR models for normal boiling points employing a neural network approach and descriptors calculated using semiempirical MO theory (AM1 and PM3). These models are based on a data set of 6000 compounds with widely varying functionality and should therefore be applicable to a diverse range of systems. We include cross-validation by simultaneously training 10 different networks, each with different training and test sets. The predicted boiling point is given by the mean of the 10 results, and the individual error of each compound is related to the standard deviation of these predictions. For our best model we find that the standard deviation of the training error is 16.5 K for 6000 compounds and the correlation coefficient (R2) between our prediction and experiment is 0.96. We also examine the effect of different conformations and tautomerism on our calculated results. Large deviations between our predictions and experiment can generally be explained by experimental errors or problems with the semiempirical methods.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

A J Chalk, B Beck, T Clark. A quantum mechanical/neural net model for boiling points with error estimation.. https://doi.org/10.1021/ci0004614

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↗