Independent Classification Systems Research Articles

The role of institutional mining investors in driving responsible tailings management

Recent devastating tailings dam failures have led many investors to view mining projects as increasingly risky investments compared with other industrial projects. In 2019, institutional investors worth US$14 trillion in assets called for the development of an independent classification system for quantifying the safety risks associated with tailings storage facilities (TSF), and played a central role in the Global Tailings Dam Portal Project disclosure request which called for a significant increase in transparency of TSF data. This paper draws upon an extensive literature review to explore the role and motivations of institutional mining investors in mitigating TSF failure risks. Results from qualitative interviews with institutional mining investors are presented to triangulate findings. It is concluded that the financial materiality of TSF failures cannot be argued to be the sole motivating factor for increased investor interest in this topic. Increasingly, the risk of TSF failure is being recognized as a critical environmental, social and governance (ESG) issue. Despite growing interest by investors to directly influence TSF management at mining sites, challenges arise due to the lack of a global tailings standard, technical training and differing regulations across jurisdictions. However, it is found that investors can also play an important role through pressuring company boards, and in improving the overall transparency of data associated with TSF risks. An outstanding research challenge lies in developing tools and frameworks to support investors to meaningfully incorporate TSF risks into investment decisions.

Alteration, Chemical Processes, and Parent Rocks of Haléo-Danielle Plateau Bauxite, Adamawa–Cameroon

The Haleo-Danielle Plateau bauxite deposit forms the largest part of the 15 km long Minim-Martap Bauxite ore district in the Adamawa Region of Cameroon. The plateau is covered with thin Upper Pleistocene to Holocene alluvial layer. It covers by laterites and bauxites formed on Tertiary-Quaternary basalts. Gibbsite and boehmite are the aluminum oxide found in the bauxite, while goethite is the main oxyhydroxide iron mineral. Bauxite rock samples from the plateau were collected and investigated with the XRF technique for their chemical composition and parent rocks. Chemical investigation reveals average concentration of the major ore components as: Al2O3 (43.73%), Fe2O3 (24.53%), SiO2 (2.12%), and TiO2 (3.54%). Abundant trace and rare elements include Zr (667.25 ppm), V (446.4 ppm), Ce (107.93 ppm), Sr (98.46 ppm), Nb (92.1 ppm), La (58.05 ppm), Ga (55.3 ppm), Ba (53.53 ppm), Nd (37.96 ppm), and ΣREE (245.8%). Calculations of the degree of chemical weathering (Ruxton Ratio) and geochemical coefficient (CIA) indicate that plateau rocks were subjected to intensive weathering, which led to the formation of industrial bauxite deposits. According to the results of processing the chemical composition of bauxites using three independent classification systems, plateau deposits can be classified as ferruginous bauxites. Parent rocks investigation indicates that bauxite was formed due to the decomposition of magnesium-ferrous andesite-basalts under conditions with a near neutral redox potential.

Mapping the Injury Phenotypes of Heart Transplant

In previous studies we used microarray analysis to characterize the rejection phenotypes of heart transplant endomyocardial biopsies. Although these phenotypes were associated with graft survival, gene-based analyses indicated that survival was more strongly associated with injury- than with rejection-related genes. We therefore built a second model using injury genes, analogous to our earlier rejection model, in order to have an independent classification system more concordant with outcomes. We used microarrays to analyzed gene expression of previously annotated injury-associated transcripts in 1320 biopsies (645 patients) from 13 centers in the INTERHEART study. Categories were defined using unsupervised archetypal analysis. These categories and those from the rejection analysis were used to predict low LVEF (<=55), and 3-year graft survival, using random forest analysis. The injury analysis identified four phenotypes: I1severe; I2late; I3early; and I4no-injury. These were related to the rejection phenotypes: R1normal, R2TCMR, R3ABMR, R4injury, and R5minor. Comparison with the rejection classification showed that severe and late injury were often but not always associated with rejection. TCMR was almost always injured, but ABMR was less consistent. When injury and rejection phenotypes were combined in random forests, the injury scores were the best predictors of low rejection fraction (LVEF) (Figure 1A), and graft loss, although R4injury was also important (Figure 1B). Parenchymal injury and late changes (atrophy-fibrosis) can be mapped in heart transplant biopsies, and their presentation correlates with low LVEF and lower 3-year survival. Injury is often, but not always, associated with rejection. Severe acute injury and the late fibrosis phenotypes are often associated with TCMR. Thus parenchymal injury is the intermediate phenotype by which rejection mediates disturbed function and survival. ClinicalTrials.gov #NCT02670408.

Clinical implications of molecular subtyping in bladder cancer.

The purpose of this review is to examine and evaluate similarities and differences in bladder cancer expression subtypes and to understand the clinical implications of the molecular subtyping. Four independent classification systems have been described, and there are broad similarities among the subtyping callers. Two major subtypes have been identified, that is, luminal and basal, with underlying subcategories based on various distinct characteristics. Luminal tumors generally bear a better prognosis and increased survival than basal tumors, although there is subtle variation in prognosis among the different subtypes within the luminal and basal classifications. Clinical subtyping is now commercially available, although there are limitations to its generalizability and application. Expression subtyping is a new method to personalize bladder cancer management. However, there is probably not sufficient evidence to incorporate use into current standards-of-care. Validation cohorts with clinically meaningful outcomes may further establish the clinical relevance of molecular subtyping of bladder cancer. Additionally, genetic alterations in bladder cancer may 'color' the interpretation of individual tumors beyond the expression subtype to truly personalize care for bladder cancer.

A comparison of the Web of Science and publication-level classification systems of science

Abstract In this paper, we propose a new criterion for choosing between a pair of classification systems of science that assign publications (or journals) to a set of clusters. Consider the standard target (cited-side) normalization procedure in which cluster mean citations are used as normalization factors. We recommend system A over system B whenever the standard normalization procedure based on system A performs better than the standard normalization procedure based on system B. Performance is assessed in terms of two double tests – one graphical, and one numerical – that use both classification systems for evaluation purposes. In addition, a pair of classification systems is compared using a third, independent classification system for evaluation purposes. We illustrate this strategy by comparing a Web of Science journal-level classification system, consisting of 236 journal subject categories, with two publication-level algorithmically constructed classification systems consisting of 1363 and 5119 clusters. There are two main findings. Firstly, the second publication-level system is found to dominate the first. Secondly, the publication-level system at the highest granularity level and the Web of Science journal-level system are found to be non-comparable. Nevertheless, we find reasons to recommend the publication-level option.

Abstract 3175: Identification of a unique subpopulation of mesenchymal-like colorectal cancers associated with better survival

Abstract The epithelial-mesenchymal transition (EMT) has been well-recognized as an important mechanism promoting cancer cell invasion and “stemness”, metastasis and therapeutic resistance. Various types of cancers with high-EMT (mesenchymal-like) features have been correlated with poorer survival. For example, recently, an international consortium (Guinney et al, Nature Medicine, 2015) has coalesced six independent classification systems of colorectal cancers into four consensus molecular subtypes (CMSs), among which only CMS4 (mesenchymal, 23%) was associated with worse overall survival and worse relapse free survival. Here we report an analysis of 458 colorectal tumors that identified a subpopulation (n = 31, 6.8%) of mesenchymal-like colorectal cancers with unique molecular features. Surprisingly, these tumors were significantly associated with better survival. All samples underwent targeted exome sequencing of 1,321 cancer-related genes, global gene expression profiling and microsatellite instability (MSI) analysis, and were evaluated for the Kaplan-Meier survival and various additional correlation analyses. We explored gene expression signatures to measure EMT, RAS/MAPK, growth factor signaling, and mucinous characteristics. While we recently found that colorectal tumors with wild-type APC (n = 151, 33.0%) were associated with worse outcome, we identified a mucinous subpopulation of these tumors (n = 31, 20.7%) which were associated with better overall survival (p = 0.004). This subpopulation of wt APC tumors were mesenchymal-like, as indicated by its significantly higher mRNA expression of the mesenchymal marker VIM (p = 0.0001) along with a robustly higher EMT signature scores (p&amp;lt;0.0001). This is in contrast to another mucinous colorectal subpopulation, MSI tumors that are epithelial-like, also with a good survival. Moreover, unlike hyper-mutated MSI tumors, the subpopulation identified appears to be correlated with the least-mutated tumors that lack common drivers (e.g. TP53, KRAS and BRAF). Compared to other wt APC tumors, this subpopulation had lower mRNA expression of a number of “canonical” Wnt/beta-catenin targeted genes including MYC (p = 0.009), MET (p&amp;lt;0.0001), CDKN2A (p = 0.03), LGR5 (p = 0.0015), HNF1A (p = 0.003), and SOX9 (p = 0.01), while expression of other targeted genes TCF4 (p&amp;lt;0.0001), TNC (p = 0.04) and NOTCH2 (p = 0.0006) were upregulated. Furthermore, these tumors were also characterized by attenuated activation of RAS/MAPK and growth factor-mediated signaling. Taken together, we have identified a specific subpopulation of colorectal cancers with distinct biological and prognostic features, indicating that a “fine-tune” classification of colorectal cancers is necessary to improve resolution of appropriate therapy. Citation Format: Mingli Yang, Michael J. Schell, Michael V. Nebozhyn, Andrey Loboda, Timothy J. Yeatman. Identification of a unique subpopulation of mesenchymal-like colorectal cancers associated with better survival. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3175.

Impact of Microsatellite Instability in Signet-Ring Cell and Mucinous Components in Patients With Colorectal Carcinoma.

Impact of Microsatellite Instability in Signet-Ring Cell and Mucinous Components in Patients With Colorectal Carcinoma.

The consensus molecular subtypes of colorectal cancer.

Colorectal cancer (CRC) is a frequently lethal disease with heterogeneous outcomes and drug responses. To resolve inconsistencies among the reported gene expression–based CRC classifications and facilitate clinical translation, we formed an international consortium dedicated to large-scale data sharing and analytics across expert groups. We show marked interconnectivity between six independent classification systems coalescing into four consensus molecular subtypes (CMS) with distinguishing features: CMS1 (MSI Immune, 14%), hypermutated, microsatellite unstable, strong immune activation; CMS2 (Canonical, 37%), epithelial, chromosomally unstable, marked WNT and MYC signaling activation; CMS3 (Metabolic, 13%), epithelial, evident metabolic dysregulation; and CMS4 (Mesenchymal, 23%), prominent transforming growth factor β activation, stromal invasion, and angiogenesis. Samples with mixed features (13%) possibly represent a transition phenotype or intra-tumoral heterogeneity. We consider the CMS groups the most robust classification system currently available for CRC – with clear biological interpretability – and the basis for future clinical stratification and subtype–based targeted interventions.

Abstract 603: Consensus molecular subtyping through a community of experts advances unsupervised gene expression-based disease classification and facilitates clinical translation

Abstract Background: Gene expression-based subtyping is widely accepted as a relevant source of disease stratification. Despite the widespread use, its translational and clinical utility is hampered by discrepant results, likely related to differences in data processing and algorithms applied to diverse patient cohorts, sample preparation methods, and gene expression platforms. In the absence of a clear methodological gold standard to perform such analyses, a more general framework that integrates and compares multiple strategies is needed to define common disease patterns in a principled, unbiased manner. Methods: We formed a consortium of 6 independent experts groups - each with a previously published CRC classifier, ranging from 3 to 6 subtypes - to understand similarities and differences of their subtyping systems. Sage Bionetworks functioned as neutral party to aggregate public and proprietary data (Synapse platform) and perform meta-analysis. Each group applied its CRC subtyping signature to the collection of data sets with gene expression (n = 4,151, predominantly stage II and III). Using the resulting subtype labels, we developed a network-based model and applied a Markov cluster algorithm to detect robust network substructures that would indicate recurring subtype patterns and therefore a consensus subtyping system. Correlative analyses using clinico-pathological, genomic and epigenomic features was performed to robustly characterize the identified subtypes. Results: This analytical framework revealed significant interconnectivity between the six independent classification systems, leading to the identification of four biologically distinct consensus molecular subtypes (CMS) enriched for key pathway traits: CMS1 (MSI Immune), hypermutated, microsatellite unstable, with strong immune activation; CMS2 (Canonical), epithelial, chromosomally unstable, with marked WNT and MYC signaling activation; CMS3 (Metabolic), epithelial, with evident metabolic dysregulation; and CMS4 (Mesenchymal), prominent TGFβ activation, angiogenesis, stromal invasion. Patients diagnosed with MSI Immune tumors had worse survival after relapse and those with mesenchymal tumors had increased risk of metastasis and worse overall survival. Discussion: We describe a novel methodological paradigm for deriving benchmarks of disease subtyping. Our work represents the first example of a community of experts identifying and advocating for a single reproducible model for cancer subtyping, effectively unifying previous classifiers. In the CRC domain, the uniformity afforded by this new classification system and its application to a large data set revealed important subtype-specific biological associations that were previously unnoticed or marginally significant, supporting a new taxonomy of the disease. Citation Format: Justin Guinney, Rodrigo Dienstmann, Xin Wang, Aurelien de Reynies, Andreas Schlicker, Charlotte Soneson, Laetitia Marisa, Paul Roepman, Gift Nyamundanda, Paolo Angelino, Brian Bot, Jeffrey S. Morris, Iris Simon, Sarah Gerster, Evelyn Fessler, Felipe de Sousa e Melo, Edoardo Missiaglia, Hena Ramay, David Barras, Krisztian Homicsko, Dipen Maru, Ganiraju Manyam, Bradley Broom, Valerie Boige, Ted Laderas, Ramon Salazar, Joe W. Gray, Josep Tabernero, Rene Bernards, Stephen Friend, Pierre Laurent-Puig, Jan P. Medema, Anguraj Sadanandam, Lodewyk Wessels, Mauro Delorenzi, Scott Kopetz, Louis Vermeulen, Sabine Tejpar. Consensus molecular subtyping through a community of experts advances unsupervised gene expression-based disease classification and facilitates clinical translation. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 603. doi:10.1158/1538-7445.AM2015-603

LacSubPred: predicting subtypes of Laccases, an important lignin metabolism-related enzyme class, using in silico approaches.

BackgroundLaccases (E.C. 1.10.3.2) are multi-copper oxidases that have gained importance in many industries such as biofuels, pulp production, textile dye bleaching, bioremediation, and food production. Their usefulness stems from the ability to act on a diverse range of phenolic compounds such as o-/p-quinols, aminophenols, polyphenols, polyamines, aryl diamines, and aromatic thiols. Despite acting on a wide range of compounds as a family, individual Laccases often exhibit distinctive and varied substrate ranges. This is likely due to Laccases involvement in many metabolic roles across diverse taxa. Classification systems for multi-copper oxidases have been developed using multiple sequence alignments, however, these systems seem to largely follow species taxonomy rather than substrate ranges, enzyme properties, or specific function. It has been suggested that the roles and substrates of various Laccases are related to their optimal pH. This is consistent with the observation that fungal Laccases usually prefer acidic conditions, whereas plant and bacterial Laccases prefer basic conditions. Based on these observations, we hypothesize that a descriptor-based unsupervised learning system could generate homology independent classification system for better describing the functional properties of Laccases.ResultsIn this study, we first utilized unsupervised learning approach to develop a novel homology independent Laccase classification system. From the descriptors considered, physicochemical properties showed the best performance. Physicochemical properties divided the Laccases into twelve subtypes. Analysis of the clusters using a t-test revealed that the majority of the physicochemical descriptors had statistically significant differences between the classes. Feature selection identified the most important features as negatively charges residues, the peptide isoelectric point, and acidic or amidic residues. Secondly, to allow for classification of new Laccases, a supervised learning system was developed from the clusters. The models showed high performance with an overall accuracy of 99.03%, error of 0.49%, MCC of 0.9367, precision of 94.20%, sensitivity of 94.20%, and specificity of 99.47% in a 5-fold cross-validation test. In an independent test, our models still provide a high accuracy of 97.98%, error rate of 1.02%, MCC of 0.8678, precision of 87.88%, sensitivity of 87.88% and specificity of 98.90%.ConclusionThis study provides a useful classification system for better understanding of Laccases from their physicochemical properties perspective. We also developed a publically available web tool for the characterization of Laccase protein sequences (http://lacsubpred.bioinfo.ucr.edu/). Finally, the programs used in the study are made available for researchers interested in applying the system to other enzyme classes (https://github.com/tweirick/SubClPred).

The comparison of normalization procedures based on different classification systems

In this paper, we develop a novel methodology within the IDCP measuring framework for comparing normalization procedures based on different classification systems of articles into scientific disciplines. Firstly, we discuss the properties of two rankings, based on a graphical and a numerical approach, for the comparison of any pair of normalization procedures using a single classification system for evaluation purposes. Secondly, when the normalization procedures are based on two different classification systems, we introduce two new rankings following the graphical and the numerical approaches. Each ranking is based on a double test that assesses the two normalization procedures in terms of the two classification systems on which they depend. Thirdly, we also compare the two normalization procedures using a third, independent classification system for evaluation purposes. In the empirical part of the paper we use: (i) a classification system consisting of 219 sub-fields identified with the Web of Science subject-categories; an aggregate classification system consisting of 19 broad fields, as well as a systematic and a random assignment of articles to sub-fields with the aim of maximizing or minimizing differences across sub-fields; (ii) four normalization procedures that use the field or sub-field mean citations of the above four classification systems as normalization factors; and (iii) a large dataset, indexed by Thomson Reuters, in which 4.4 million articles published in 1998–2003 with a five-year citation window are assigned to sub-fields using a fractional approach. The substantive results concerning the comparison of the four normalization procedures indicate that the methodology can be useful in practice.

Histological Subtypes of Lung Adenocarcinoma Have Differential 18F-Fluorodeoxyglucose Uptakes on the Positron Emission Tomography/Computed Tomography Scan

Previous studies have shown that lung squamous cell carcinoma has higher ¹⁸F-fluorodeoxyglucose (FDG) uptake on positron emission tomography (PET) than adenocarcinoma. We hypothesized that histological subtypes of lung adenocarcinoma were also different in ¹⁸F-FDG uptake. Patients who had preoperative PET/computed tomography (CT) scan and had undergone complete resection for lung adenocarcinoma between April 2007 and December 2009 were enrolled in this study. Because of the limitation of spatial resolution on PET/CT, tumors less than 1 cm were excluded for analysis. Two independent classification systems were used to categorize histological subtypes of adenocarcinoma; one was modified from the current World Health Organization classification and the other used the morphological features of the terminal respiratory unit (TRU). The maximal standardized uptake value (SUVmax) on PET/CT and the glucose transporter type 1 (GLUT-1) expression of the tumors were measured and correlated to the histology of lung adenocarcinoma. One hundred fifty-two patients with 153 primary lung adenocarcinomas were included. There was a significant difference in SUVmax among different histological subtypes. Namely, solid predominant adenocarcinomas had significantly higher SUVmax than those with other predominant histology (p < 0.001), and TRU-type adenocarcinomas had significantly lower SUVmax than non-TRU-type adenocarcinomas (p < 0.001). Consistently, GLUT-1 expression was higher in tumors with a solid growth pattern than those without (p < 0.001) and in tumors with non-TRU type than TRU type (p < 0.001). The histological subtypes of lung adenocarcinomas differ in GLUT-1 expression and ¹⁸F-FDG uptake on the PET/CT scan, suggesting that histological subtyping not only has morphological but also biological implications.

Individuals, kinds and events: classifier coercion of nouns

This paper challenges the traditional view that nominal classifiers classify individuals. Instead, we suggest that classifiers coerce nouns to refer to kinds and events as well as to individuals. This finding argues against the view that nouns refer only to entities, and suggests that classifiers do not simply agree with a noun, but instead coerce a particular meaning from it. Moreover, the Mandarin classifier system creates a taxonomic system involving events, kinds and individuals respectively. Within each classifier type an independent classification system of the collocating noun type is created. These findings are important first because they emphasize that the understanding of the semantics of nouns involves more than simple reference to an individual entity. Second, it is the first time that the previously abstract semantic distinctions among kinds, individuals and events, as well as within kinds and within events, have been found to be instantiated in a particular system of a natural language grammar, namely, the classifier system.

Structure, function and evolution of glutathione transferases: implications for classification of non-mammalian members of an ancient enzyme superfamily

The glutathione transferases (GSTs; also known as glutathione S-transferases) are major phase II detoxification enzymes found mainly in the cytosol. In addition to their role in catalysing the conjugation of electrophilic substrates to glutathione (GSH), these enzymes also carry out a range of other functions. They have peroxidase and isomerase activities, they can inhibit the Jun N-terminal kinase (thus protecting cells against H2O2-induced cell death), and they are able to bind non-catalytically a wide range of endogenous and exogenous ligands. Cytosolic GSTs of mammals have been particularly well characterized, and were originally classified into Alpha, Mu, Pi and Theta classes on the basis of a combination of criteria such as substrate/inhibitor specificity, primary and tertiary structure similarities and immunological identity. Non-mammalian GSTs have been much less well characterized, but have provided a disproportionately large number of three-dimensional structures, thus extending our structure–function knowledge of the superfamily as a whole. Moreover, several novel classes identified in non-mammalian species have been subsequently identified in mammals, sometimes carrying out functions not previously associated with GSTs. These studies have revealed that the GSTs comprise a widespread and highly versatile superfamily which show similarities to non-GST stress-related proteins. Independent classification systems have arisen for groups of organisms such as plants and insects. This review surveys the classification of GSTs in non-mammalian sources, such as bacteria, fungi, plants, insects and helminths, and attempts to relate them to the more mainstream classification system for mammalian enzymes. The implications of this classification with regard to the evolution of GSTs are discussed.

Structure, function and evolution of glutathione transferases: implications for classification of non-mammalian members of an ancient enzyme superfamily.

The glutathione transferases (GSTs; also known as glutathione S-transferases) are major phase II detoxification enzymes found mainly in the cytosol. In addition to their role in catalysing the conjugation of electrophilic substrates to glutathione (GSH), these enzymes also carry out a range of other functions. They have peroxidase and isomerase activities, they can inhibit the Jun N-terminal kinase (thus protecting cells against H(2)O(2)-induced cell death), and they are able to bind non-catalytically a wide range of endogenous and exogenous ligands. Cytosolic GSTs of mammals have been particularly well characterized, and were originally classified into Alpha, Mu, Pi and Theta classes on the basis of a combination of criteria such as substrate/inhibitor specificity, primary and tertiary structure similarities and immunological identity. Non-mammalian GSTs have been much less well characterized, but have provided a disproportionately large number of three-dimensional structures, thus extending our structure-function knowledge of the superfamily as a whole. Moreover, several novel classes identified in non-mammalian species have been subsequently identified in mammals, sometimes carrying out functions not previously associated with GSTs. These studies have revealed that the GSTs comprise a widespread and highly versatile superfamily which show similarities to non-GST stress-related proteins. Independent classification systems have arisen for groups of organisms such as plants and insects. This review surveys the classification of GSTs in non-mammalian sources, such as bacteria, fungi, plants, insects and helminths, and attempts to relate them to the more mainstream classification system for mammalian enzymes. The implications of this classification with regard to the evolution of GSTs are discussed.