GTI-space : the space of generalized topological indices

A new extension of the generalized topological indices (GTI) approach is carried out torepresent 'simple' and 'composite' topological indices (TIs) in an unified way. Thisapproach defines a GTI-space from which both simple and composite TIs represent particular subspaces. Accordingly, simple TIs such as Wiener, Balaban, Zagreb, Harary and Randićconnectivity indices are expressed by means of the same GTI representation introduced for composite TIs such as hyper-Wiener, molecular topological index (MTI), Gutman index andreverse MTI. Using GTI-space approach we easily identify mathematical relations between some composite and simple indices, such as the relationship between hyper-Wiener and Wiener index and the relation between MTI and first Zagreb index. The relation of the GTI space with the sub-structural cluster expansion of property/activity is also analysed and some routes for the applications of this approach to QSPR/QSAR are also given

New Polynomial-Based Molecular Descriptors with Low Degeneracy

In this paper, we introduce a novel graph polynomial called the ‘information polynomial’ of a graph. This graph polynomial can be derived by using a probability distribution of the vertex set. By using the zeros of the obtained polynomial, we additionally define some novel spectral descriptors. Compared with those based on computing the ordinary characteristic polynomial of a graph, we perform a numerical study using real chemical databases. We obtain that the novel descriptors do have a high discrimination power

QSAR studies on a number of pyrrolidin-2-one antiarrhythmic arylpiperazinyls

The activity of a number of 1-[3-(4-arylpiperazin-1-yl)propyl]pyrrolidin-2-one antiarrhythmic (AA) agents was described using the quantitative structure–activity relationship model by applying it to 33 compounds. The molecular descriptors of the AA activity were obtained by quantum chemical calculations combined with molecular modeling calculations. The resulting model explains up to 91% of the variance and it was successfully validated by four tests (LOO, LMO, external test, and Y-scrambling test). Statistical analysis shows that the AA activity of the studied compounds depends mainly on the PCR and JGI4 descriptors

Active surveillance in renal transplant patients with prostate cancer: a multicentre analysis

Introduction: Due to medical improvements leading to increased life expectancy after renal transplantation and widened eligibility criteria allowing older patients to be transplanted, incidence of (low-risk) prostate cancer (PCa) is increasing among renal transplant recipients (RTR). It remains to be established whether active surveillance (AS) for PCa represents a safe treatment option in this setting. Therefore, we aim to compare AS discontinuation and oncological outcomes of AS for PCa of RTR vs. non-transplant patients. Methods: Multicentre study including RTR diagnosed with PCa between 2008 and 2018 in whom AS was initiated. A subgroup of non-RTR from the St. Antonius hospital AS cohort was used as a control group. Comparison of RTR vs. non-RTR was performed by 2:1 propensity score matched survival analysis. Outcome measures included tumour progression-free survival, treatment-free survival, metastasis rates, biochemical recurrence rates and overall survival. Patients were matched based on age, year of diagnosis, PSA, biopsy ISUP grade group, relative number of positive biopsy cores and clinical stage. Results: A total of 628 patients under AS were evaluated, including 17 RTRs and 611 non-RTRs. A total of 13 RTR cases were matched with 24 non-RTR cases. Median overall follow-up for the RTR and non-RTR matched cases was, respectively, 5.1 (IQR 3.2–8.7) years and 5.7 (IQR 4.8–8.1) years. There were no events of metastasis and biochemical recurrence among matched cases. The matched-pair analysis results in a 1-year and 5-year survival of the RTR and non-RTR patients were, respectively, 100 vs. 92%, and 39 vs. 76% for tumour progression, 100 vs. 91% and 59 vs. 76% for treatment-free survival and, respectively, 100 vs. 100% and 88 vs. 100% for overall survival. No significant differences in tumour progression-free survival (p = 0.07) and treatment-free survival were observed (p = 0.3). However, there was a significant difference in overall survival comparing both groups (p = 0.046). Conclusions: AS may be carefully considered in RTR with low-risk PCa. In our preliminary analysis, no major differences were present in AS outcomes between RTR and non-RTR. Overall mortality was significantly higher in the RTR subgroup

Modeling complex metabolic reactions, ecological systems, and financial and legal networks with MIANN models based on Markov-Wiener node descriptors

[Abstract] The use of numerical parameters in Complex Network analysis is expanding to new fields of application. At a molecular level, we can use them to describe the molecular structure of chemical entities, protein interactions, or metabolic networks. However, the applications are not restricted to the world of molecules and can be extended to the study of macroscopic nonliving systems, organisms, or even legal or social networks. On the other hand, the development of the field of Artificial Intelligence has led to the formulation of computational algorithms whose design is based on the structure and functioning of networks of biological neurons. These algorithms, called Artificial Neural Networks (ANNs), can be useful for the study of complex networks, since the numerical parameters that encode information of the network (for example centralities/node descriptors) can be used as inputs for the ANNs. The Wiener index (W) is a graph invariant widely used in chemoinformatics to quantify the molecular structure of drugs and to study complex networks. In this work, we explore for the first time the possibility of using Markov chains to calculate analogues of node distance numbers/W to describe complex networks from the point of view of their nodes. These parameters are called Markov-Wiener node descriptors of order kth (Wk). Please, note that these descriptors are not related to Markov-Wiener stochastic processes. Here, we calculated the Wk(i) values for a very high number of nodes (>100,000) in more than 100 different complex networks using the software MI-NODES. These networks were grouped according to the field of application. Molecular networks include the Metabolic Reaction Networks (MRNs) of 40 different organisms. In addition, we analyzed other biological and legal and social networks. These include the Interaction Web Database Biological Networks (IWDBNs), with 75 food webs or ecological systems and the Spanish Financial Law Network (SFLN). The calculated Wk(i) values were used as inputs for different ANNs in order to discriminate correct node connectivity patterns from incorrect random patterns. The MIANN models obtained present good values of Sensitivity/Specificity (%): MRNs (78/78), IWDBNs (90/88), and SFLN (86/84). These preliminary results are very promising from the point of view of a first exploratory study and suggest that the use of these models could be extended to the high-throughput re-evaluation of connectivity in known complex networks (collation)

Information Indices with High Discriminative Power for Graphs

In this paper, we evaluate the uniqueness of several information-theoretic measures for graphs based on so-called information functionals and compare the results with other information indices and non-information-theoretic measures such as the well-known Balaban index. We show that, by employing an information functional based on degree-degree associations, the resulting information index outperforms the Balaban index tremendously. These results have been obtained by using nearly 12 million exhaustively generated, non-isomorphic and unweighted graphs. Also, we obtain deeper insights on these and other topological descriptors when exploring their uniqueness by using exhaustively generated sets of alkane trees representing connected and acyclic graphs in which the degree of a vertex is at most four

The Inclusiveness and Emptiness of <i>Gong Qi</i>: A Non-Anglophone Perspective on Ethics from a Sino-Japanese Corporation

This article introduces a non-Anglophone concept of gong qi(communal vessel, 公器) as a metaphor for ‘corporation’. It contributes an endogenous perspective from a Sino-Japanese organizational context that enriches mainstream business ethics literature, otherwise heavily reliant on Western traditions. We translate the multi-layered meanings of gong qi based on analysis of its ideograms, its references into classical philosophies, and contemporary application in this Japanese multinational corporation in China. Gong qi contributes a perspective that sees a corporation as an inclusive and virtuous social entity, and also addresses the elusive, implicit, and forever evolving nature of organizational life that is rarely noticed. We propose gong qi can be applied in other organizations and wider cultural contexts to show a new way of seeing and understanding business ethics and organization. Rather than considering virtue as a list of definable individual qualities, we suggest that the metaphor of gong qi reveals how virtue can be experienced as indeterminate, yet immanently present, like the substance of emptiness. This, then allows us to see the virtue of immanence, the beauty of implicitness, and hence, the efficacy of gong qi