Subgraph Isomorphic Decision Tree to Predict Radical Thermochemistry with Bounded Uncertainty Estimation.

Detailed chemical kinetic models offer valuable mechanistic insights into industrial applications. Automatic generation of reliable kinetic models requires fast and accurate radical thermochemistry estimation. Kineticists often prefer hydrogen bond increment (HBI) corrections from a closed-shell molecule to the corresponding radical for their interpretability, physical meaning, and facilitation of error cancellation as a relative quantity. Tree estimators, used due to limited data, currently rely on expert knowledge and manual construction, posing challenges in maintenance and improvement. In this work, we extend the subgraph isomorphic decision tree (SIDT) algorithm originally developed for rate estimation to estimate HBI corrections. We introduce a physics-aware splitting criterion, explore a bounded weighted uncertainty estimation method, and evaluate aleatoric uncertainty-based and model variance reduction-based prepruning methods. Moreover, we compile a data set of thermochemical parameters for 2210 radicals involving C, O, N, and H based on quantum chemical calculations from recently published works. We leverage the collected data set to train the SIDT model. Compared to existing empirical tree estimators, the SIDT model (1) offers an automatic approach to generating and extending the tree estimator for thermochemistry, (2) has better accuracy and R2, (3) provides significantly more realistic uncertainty estimates, and (4) has a tree structure much more advantageous in descent speed. Overall, the SIDT estimator marks a great leap in kinetic modeling, offering more precise, reliable, and scalable predictions for radical thermochemistry.

Toward Accurate Quantum Mechanical Thermochemistry: (1) Extensible Implementation and Comparison of Bond Additivity Corrections and Isodesmic Reactions.

Obtaining accurate enthalpies of formation of chemical species, ΔHf, often requires empirical corrections that connect the results of quantum mechanical (QM) calculations with the experimental enthalpies of elements in their standard state. One approach is to use atomization energy corrections followed by bond additivity corrections (BACs), such as those defined by Petersson et al. or Anantharaman and Melius. Another approach is to utilize isodesmic reactions (IDRs) as shown by Buerger et al. We implement both approaches in Arkane, an open-source software that can calculate species thermochemistry using results from various QM software packages. In this work, we collect 421 reference species from the literature to derive ΔHf corrections and fit atomization energy corrections and BACs for 15 commonly used model chemistries. We find that both types of BACs yield similar accuracy, although Anantharaman- and Melius-type BACs appear to generalize better. Furthermore, BACs tend to achieve better accuracy than IDRs for commonly used model chemistries, and IDRs can be less robust because of the sensitivity to the chosen reference species and reactions. Overall, Anantharaman- and Melius-type BACs are our recommended approach for achieving accurate QM corrections for enthalpies.

RMG Database for Chemical Property Prediction.

The Reaction Mechanism Generator (RMG) database for chemical property prediction is presented. The RMG database consists of curated datasets and estimators for accurately predicting the parameters necessary for constructing a wide variety of chemical kinetic mechanisms. These datasets and estimators are mostly published and enable prediction of thermodynamics, kinetics, solvation effects, and transport properties. For thermochemistry prediction, the RMG database contains 45 libraries of thermochemical parameters with a combination of 4564 entries and a group additivity scheme with 9 types of corrections including radical, polycyclic, and surface absorption corrections with 1580 total curated groups and parameters for a graph convolutional neural network trained using transfer learning from a set of >130 000 DFT calculations to 10 000 high-quality values. Correction schemes for solvent-solute effects, important for thermochemistry in the liquid phase, are available. They include tabulated values for 195 pure solvents and 152 common solutes and a group additivity scheme for predicting the properties of arbitrary solutes. For kinetics estimation, the database contains 92 libraries of kinetic parameters containing a combined 21 000 reactions and contains rate rule schemes for 87 reaction classes trained on 8655 curated training reactions. Additional libraries and estimators are available for transport properties. All of this information is easily accessible through the graphical user interface at https://rmg.mit.edu. Bulk or on-the-fly use can be facilitated by interfacing directly with the RMG Python package which can be installed from Anaconda. The RMG database provides kineticists with easy access to estimates of the many parameters they need to model and analyze kinetic systems. This helps to speed up and facilitate kinetic analysis by enabling easy hypothesis testing on pathways, by providing parameters for model construction, and by providing checks on kinetic parameters from other sources.

Prognostic factors and outcome of 438 Chinese patients with hepatocellular carcinoma underwent partial hepatectomy in a single center.

OBJECTIVE: This study was designed to evaluate the prognostic factors and outcome of 438 Chinese patients with hepatocellular carcinoma who underwent partial hepatectomy in a single center. METHODS: Clinicopathological data of 438 patients with hepatocellular carcinoma who underwent partial hepatectomy at the author's hospital between 1991 and 2004 were reviewed retrospectively. The Kaplan-Meier method was adopted for evaluating survival. Prognostic factors were assessed by Cox proportional hazard model and logistic regression model. RESULTS: The perioperative (30 days) mortality and morbidity were 7.5% (33/438) and 21.7% (95/438), respectively. The operative mortality decreased significantly from 10.6% (23/218) in 1991-2001 to 4.5% (10/220) in 2002-2004 (P = 0.019). Postoperative overall survival rates at 1 year, 3 years, and 5 years were 72.2%, 53.5%, and 43.3%, respectively. Cox multivariate analysis indicated that Child-Pugh score, tumor size, capsular invasion, tumor stage, vascular invasion, and resection margin were independent prognostic factors for overall survival (P < 0.05). Also, 254 cases had tumor recurrence after operation and 87 cases of them were reoperated. Logistic multivariate analysis showed that tumor size, capsular invasion, vascular invasion, lymph node metastasis, extrahepatic metastasis, and resection margin were independent risk factors of tumor recurrence (P < 0.05). CONCLUSIONS: Tumor size, capsular invasion, vascular invasion, and resection margin were the main factors that may impact the overall survival and tumor recurrence. Because resection margin was the only factor that relates to the surgery, enough resection margin (>2 cm) should be obtained whenever possible.

Staging systems for predicting survival of patients with hepatocellular carcinoma after surgery.

AIM: To compare the staging systems for stratifying and predicting the prognosis of patients with hepatocellular carcinoma (HCC) after partial hepatectomy (PH). METHODS: Clinical data about 438 HCC patients who underwent PH from January 1991 to December 2004 at our hospital were retrospectively analyzed. Tumor stage was evaluated following the Chinese tumor node metastasis (TNM) and barcelona clinic liver cancer (BCLC) staging systems, respectively. Survival curves for the HCC patients were plotted using the Kaplan-Meier method and differences were compared by the log-rank test. The accuracy of each system for predicting death of HCC patients was evaluated by calculating the area under the receiver operating characteristic curve. RESULTS: The HCC patients were classified into stages I-III, stages I-IV and stages A-C, according to the 3 staging systems, respectively. Log-rank test showed that the cumulative survival rate was significantly different for the HCC patients at 3 Chinese system stages, TNM stages I and II, TNM stages III and IV, and 3 BCLC stages (P < 0.05). However, no significant difference was found in the HCC patients at TNM stages II and III. The accuracy of the Chinese and BCLC staging systems was higher than that of the TNM staging system for predicting the survival rate of HCC patients. CONCLUSION: The Chinese and BCLC staging systems are better for stratifying and predicting the prognosis of HCC patients after PH than the TNM staging system.