The effects of ownership structure, sub-optimal cash holdings and investment inefficiency on dividend policy: evidence from Indonesia

We investigate how a firm's decision to hold excessive cash or to overinvest could influence its dividend payout policy in Indonesia. Additionally, we examine the association between corporate ownership structure and cash dividends. Using a data set of Indonesian listed firms for the period from 1995 to 2014, we find that excessive cash holding (overinvestment) positively (negatively) affects a firm's likelihood of paying dividends. Also, we find that family, foreign, state and institutional ownership have significantly negative links with dividends, which suggests the signals of expropriation of firms' wealth by major shareholders. These findings strongly support the expropriation hypothesis that commonly applies to firms with higher level of concentration or to firms in a weak legal environment by which the rights of minority interests are put at risk by large shareholders

miR-34a-FOXP1 Loop in Ovarian Cancer

Ovarian cancer (OC) is the main cause of gynecological cancer mortality in most developed countries. microRNA (miR) expression dysregulation has been highlighted in human cancers, and miR-34a is found to be downregulated and associated with inhibition of tumor growth and invasion in several malignancies, including OC. The winged helix transcription factor forkhead box P1 (FOXP1) is reported as either an oncogene or tumor suppressor in various cancers. This study aimed to elucidate potential clinical and biological associations of miR-34a and transcription factor FOXP1 in OC. We investigated nine OC patients’ blood samples and two OC cell lines (SKOV-3 and OVCAR-3) using quantitative real-time reverse transcription polymerase chain reaction (RT-qPCR) to determine both miR-34a and FOXP1 expressions. We have found that miR-34a and FOXP1 are reversely correlated in both in vitro and in vivo. Inhibition of miR-34a transiently led to upregulation of FOXP1 mRNA expression and increased cellular invasion in vitro. Our data indicate that miR-34a could be a potential biomarker for improving the diagnostic efficiency of OC, and miR-34a overexpression may reduce OC pathogenesis by targeting FOXP1

GUILDify v2.0:A Tool to Identify Molecular Networks Underlying Human Diseases, Their Comorbidities and Their Druggable Targets

The genetic basis of complex diseases involves alterations on multiple genes. Unraveling the interplay between these genetic factors is key to the discovery of new biomarkers and treatments. In 2014, we introduced GUILDify, a web server that searches for genes associated to diseases, finds novel disease genes applying various network-based prioritization algorithms and proposes candidate drugs. Here, we present GUILDify v2.0, a major update and improvement of the original method, where we have included protein interaction data for seven species and 22 human tissues and incorporated the disease-gene associations from DisGeNET. To infer potential disease relationships associated with multi-morbidities, we introduced a novel feature for estimating the genetic and functional overlap of two diseases using the top-ranking genes and the associated enrichment of biological functions and pathways (as defined by GO and Reactome). The analysis of this overlap helps to identify the mechanistic role of genes and protein-protein interactions in comorbidities. Finally, we provided an R package, guildifyR, to facilitate programmatic access to GUILDify v2.0 (http://sbi.upf.edu/guildify2).The authors received support from: ISCIII-FEDER (PI13/00082, CP10/00524, CPII16/00026); IMI-JU under grants agreements no. 116030 (TransQST) and no. 777365 (eTRANSAFE), resources of which are composed of financial contribution from the EU-FP7 (FP7/2007- 2013) and EFPIA companies in kind contribution; the EU H2020 Programme 2014-2020 under grant agreements no. 634143 (MedBioinformatics) and no. 676559 (Elixir-Excelerate); the Spanish Ministry of Economy (MINECO) [BIO2017-85329-R] [RYC-2015-17519]; "Unidad de Excelencia María de Maeztu", funded by the Spanish Ministry of Economy [ref: MDM-2014-0370]. The Research Programme on Biomedical Informatics (GRIB) is a member of the Spanish National Bioinformatics Institute (INB), PRB2-ISCIII and is supported by grant PT13/0001/0023, of the PE I+D+i 2013-2016, funded by ISCIII and FEDER

Quantum beat spectroscopy: stimulated emission probe of hyperfine quantum beats in the atomic Cs 8p 2P3/2^{2}P_{3/2} level

Measurements of hyperfine polarization quantum beats are used determine the magnetic dipole (A) and electric quadrupole (B) coupling constants in the excited atomic Cs 8p level. The experimental approach is a novel combination of pulsed optical pumping and time-delayed stimulated emission probing of the excited level. From the measured evolution of the atomic linear polarization degree as a function of probe delay time, we determine the hyperfine coupling constants A = 7.42(6) MHz and B = 0.14(29) MHz

Genetic and functional characterization of disease associations explains comorbidity

Understanding relationships between diseases, such as comorbidities, has important socio-economic implications, ranging from clinical study design to health care planning. Most studies characterize disease comorbidity using shared genetic origins, ignoring pathway-based commonalities between diseases. In this study, we define the disease pathways using an interactome-based extension of known disease-genes and introduce several measures of functional overlap. The analysis reveals 206 significant links among 94 diseases, giving rise to a highly clustered disease association network. We observe that around 95% of the links in the disease network, though not identified by genetic overlap, are discovered by functional overlap. This disease network portraits rheumatoid arthritis, asthma, atherosclerosis, pulmonary diseases and Crohn's disease as hubs and thus pointing to common inflammatory processes underlying disease pathophysiology. We identify several described associations such as the inverse comorbidity relationship between Alzheimer's disease and neoplasms. Furthermore, we investigate the disruptions in protein interactions by mapping mutations onto the domains involved in the interaction, suggesting hypotheses on the causal link between diseases. Finally, we provide several proof-of-principle examples in which we model the effect of the mutation and the change of the association strength, which could explain the observed comorbidity between diseases caused by the same genetic alterations

An ensemble learning approach for modeling the systems biology of drug-induced injury

Background: Drug-induced liver injury (DILI) is an adverse reaction caused by the intake of drugs of common use that produces liver damage. The impact of DILI is estimated to affect around 20 in 100,000 inhabitants worldwide each year. Despite being one of the main causes of liver failure, the pathophysiology and mechanisms of DILI are poorly understood. In the present study, we developed an ensemble learning approach based on different features (CMap gene expression, chemical structures, drug targets) to predict drugs that might cause DILI and gain a better understanding of the mechanisms linked to the adverse reaction. Results: We searched for gene signatures in CMap gene expression data by using two approaches: phenotype-gene associations data from DisGeNET, and a non-parametric test comparing gene expression of DILI-Concern and No-DILI-Concern drugs (as per DILIrank definitions). The average accuracy of the classifiers in both approaches was 69%. We used chemical structures as features, obtaining an accuracy of 65%. The combination of both types of features produced an accuracy around 63%, but improved the independent hold-out test up to 67%. The use of drug-target associations as feature obtained the best accuracy (70%) in the independent hold-out test. Conclusions: When using CMap gene expression data, searching for a specific gene signature among the landmark genes improves the quality of the classifiers, but it is still limited by the intrinsic noise of the dataset. When using chemical structures as a feature, the structural diversity of the known DILI-causing drugs hampers the prediction, which is a similar problem as for the use of gene expression information. The combination of both features did not improve the quality of the classifiers but increased the robustness as shown on independent hold-out tests. The use of drug-target associations as feature improved the prediction, specially the specificity, and the results were comparable to previous research studies.The authors received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreements TransQST and eTRANSAFE (refs: 116030, 777365). This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA companies in kind contribution. The authors also received support from Spanish Ministry of Economy (MINECO, refs: BIO2017–85329-R (FEDER, EU), RYC-2015-17519) as well as EU H2020 Programme 2014–2020 under grant agreement No. 676559 (Elixir-Excelerate) and from Agència de Gestió D’ajuts Universitaris i de Recerca Generalitat de Catalunya (AGAUR, ref.: 2017SGR01020). L.I.F. received support from ISCIII-FEDER (ref: CPII16/00026). The Research Programme on Biomedical Informatics (GRIB) is a member of the Spanish National Bioinformatics Institute (INB), PRB2-ISCIII and is supported by grant PT13/0001/0023, of the PE I + D + i 2013–2016, funded by ISCIII and FEDER. The DCEXS is a “Unidad de Excelencia María de Maeztu”, funded by the MINECO (ref: MDM-2014-0370). J.A.P. received support from the CAMDA Travel Fellowship

Past Achievements and Future Challenges in 3D Photonic Metamaterials

Photonic metamaterials are man-made structures composed of tailored micro- or nanostructured metallo-dielectric sub-wavelength building blocks that are densely packed into an effective material. This deceptively simple, yet powerful, truly revolutionary concept allows for achieving novel, unusual, and sometimes even unheard-of optical properties, such as magnetism at optical frequencies, negative refractive indices, large positive refractive indices, zero reflection via impedance matching, perfect absorption, giant circular dichroism, or enhanced nonlinear optical properties. Possible applications of metamaterials comprise ultrahigh-resolution imaging systems, compact polarization optics, and cloaking devices. This review describes the experimental progress recently made fabricating three-dimensional metamaterial structures and discusses some remaining future challenges

Is complexity leadership theory complex enough? A critical appraisal, some modifications and suggestions for further research

Scholars are increasingly seeking to develop theories that explain the underlying processes whereby leadership is enacted. This shifts attention away from the actions of ‘heroic’ individuals and towards the social contexts in which people with greater or lesser power influence each other. A number of researchers have embraced complexity theory, with its emphasis on non-linearity and unpredictability. However, some complexity scholars still depict the theory and practice of leadership in relatively non-complex terms. They continue to assume that leaders can exercise rational, extensive and purposeful influence on other actors to a greater extent than is possible. In effect, they offer a theory of complex organizations led by non-complex leaders who establish themselves by relatively non-complex means. This testifies to the enduring power of ‘heroic’ images of leader agency. Without greater care, the terminology offered by complexity leadership theory could become little more than a new mask for old theories that legitimize imbalanced power relationships in the workplace. This paper explores how these problems are evident in complexity leadership theory, suggests that communication and process perspectives help to overcome them, and outlines an agenda for further research on these issues

Review of experimental methods to determine spontaneous combustion susceptibility of coal – Indian context

This paper presents a critical review of the different techniques developed to investigate the susceptibility of coal to spontaneous combustion and fire. These methods may be sub-classified into the two following areas: (1) Basic coal characterisation studies (chemical constituents) and their influence on spontaneous combustion susceptibility. (2) Test methods to assess the susceptibility of a coal sample to spontaneous combustion. This is followed by a critical literature review that summarises previous research with special emphasis given to Indian coals