Having a compact yet robust structurally based identifier or representation system is a key enabling factor for efficient sharing and dissemination of research results within the chemistry community, and such systems lay down the essential foundations for future informatics and data-driven research. While substantial advances have been made for small molecules, the polymer community has struggled in coming up with an efficient representation system. This is because, unlike other disciplines in chemistry, the basic premise that each distinct chemical species corresponds to a well-defined chemical structure does not hold for polymers. Polymers are intrinsically stochastic molecules that are often ensembles with a distribution of chemical structures. This difficulty limits the applicability of all deterministic representations developed for small molecules. In this work, a new representation system that is capable of handling the stochastic nature of polymers is proposed. The new system is based on the popular “simplified molecular-input line-entry system” (SMILES), and it aims to provide representations that can be used as indexing identifiers for entries in polymer databases. As a pilot test, the entries of the standard data set of the glass transition temperature of linear polymers (Bicerano, 2002) were converted into the new BigSMILES language. Furthermore, it is hoped that the proposed system will provide a more effective language for communication within the polymer community and increase cohesion between the researchers within the community.

Seizure is a common presenting manifestation and plays an important role in the clinical presentation and quality of life for patients with low-grade gliomas (LGGs). The authors set out to identify factors that influence preoperative seizure characteristics and postoperative seizure control. Cases involving adult patients who had undergone initial surgery for LGGs in a single institution between 2005 and 2009 were retrospectively reviewed. Univariate and multivariate logistic regression analyses were used to identify factors associated with preoperative seizures and postoperative seizure control. Of the 508 patients in the series, 350 (68.9%) presented with seizures. Age less than 38 years and cortical involvement of tumor were more likely to be associated with seizures (P = .003 and .001, respectively, multivariate logistic analysis). For the cohort of 350 patients with seizures, Engel classification was used to evaluate 6- and 12-month outcome after surgery: completely seizure free (Engel class I), 65.3% and 62.5%; not seizure free (Engel classes II, III, IV), 34.7% and 37.5%. After multivariate logistic analysis, favorable seizure prognosis was more common in patients with secondary generalized seizure (P = .006) and with calcification on MRI (.031). With respect to treatment-related variables, patients achieved much better seizure control after gross total resection than after subtotal resection (P < .0001). Ki67 was an independent molecular marker predicting poor seizure control in the patients with a history of seizure if overexpressed but was not a predictor for those without preoperative seizures. These factors may provide insight into developing effective treatment strategies aimed at prolonging patients' survival.