Pharmacokinetics and drug-likeness of anti-cancer traditional Chinese medicine: molecular docking and molecular dynamics simulation study.

MCM7 (Minichromosome Maintenance Complex Component 7) is a component of the DNA replication licensing factor, which controls DNA replication. The MCM7 protein is linked to tumor cell proliferation and has a function in the development of several human cancers. Several types of cancer may be treated by inhibiting the protein, as it is strongly produced throughout this process. Significantly, Traditional Chinese Medicine (TCM), which has a long history of clinical adjuvant use against cancer, is rapidly gaining traction as a valuable medical resource for the development of novel cancer therapies, including immunotherapy. Therefore, the goal of the research was to find small molecular therapeutic candidates against the MCM7 protein that may be used to treat human cancers. A computational-based virtual screening of 36,000 natural TCM libraries is carried out for this goal using a molecular docking and dynamic simulation technique. Thereby, ∼8 novel potent compounds i.e., ZINC85542762, ZINC95911541, ZINC85542617, ZINC85542646, ZINC85592446, ZINC85568676, ZINC85531303, and ZINC95914464 were successfully shortlisted, each having the capacity to penetrate the cell as potent inhibitors for MCM7 to curb this disorder. These selected compounds were found to have high binding affinities compared to the reference (AGS compound) i.e. < -11.0 kcal/mol. ADMET and pharmacological properties showed that none of these 8 compounds poses any toxic property (carcinogenicity) and have anti-metastatic, and anticancer activity. Additionally, MD simulations were run to assess the compounds' stability and dynamic behavior with the MCM7 complex for about 100 ns. Finally, ZINC95914464, ZINC95911541, ZINC85568676, ZINC85592446, ZINC85531303, and ZINC85542646 are identified as highly stable within the complex throughout the 100 ns simulations. Moreover, the results of binding free energy suggested that the selected virtual hits significantly bind to the MCM7 which implied these compounds may act as a potential MCM7 inhibitor. However, in vitro testing protocols are required to further support these results. Further, assessment through various lab-based trial methods can assist with deciding the action of the compound that will give options in contrast to human cancer immunotherapy.Communicated by Ramaswamy H. Sarma.

Investigating the self-assembling of nicotinic hydrazide-based amphiphile into nano-range vesicles and its amphotericin B loading applications.

Most of the drugs are hydrophobic and have low water solubility, therefore posing issues in their absorption and bioavailability. Nonionic surfactants improve the solubility of hydrophobic drugs by entrapping them in their lipid bilayers. Two nonionic surfactants NODNH-16 and NODNH-18 are synthesized and characterized using different techniques i.e. EI-MS, 1H NMR, and FTIR. These newly synthesized surfactants were screened for blood hemolysis assay and cell toxicity studies using the NIH/3T3 cell line to assess their biocompatibility. Then amphotericin B was loaded into niosomal vesicles, and the drug entrapment efficiency of these surfactants was measured using UV-visible spectroscopy. The morphology of drug-loaded niosomes of synthesized surfactants was investigated using AFM, and their size, polydispersity, and zeta potential were measured with the Zetasizer instrument. Finally, a simulation study was performed to determine the pattern of self-assembly of the synthesized amphiphiles. Both synthesized nonionic surfactants showed good entrapment efficiency of 60.65 ± 2.12% and 68.45 ± 2.12%, respectively. It was also confirmed that both these synthesized nonionic surfactants were safe and biocompatible and showed less blood hemolysis (i.e. 21.13 ± 2.11% and 23.32 ± 2.45%) and higher 3T3 cells' viability at 150 µg/mL concentration as compared to Tween®-80. The antifungal potential of amphotericin B-loaded niosomes has been evaluated against unicellular multi-fungal species, which showed a promising potential for fungicidal activity. These results are substantiated by constructing a safe vehicle system for drug delivery.

Positive leadership and employee engagement: The roles of state positive affect and individualism-collectivism.

Drawing upon broaden-and-build theory, this study examined the influence of positive leadership on employee engagement through the mediating role of employees' state positive affect and the moderating effect of individualism-collectivism orientation in a Chinese cultural context. A sample of 215 valid questionnaires was obtained through a two-wave survey of 48 teams working in central China. Hypotheses were tested by a method of hierarchical linear modelling. The results indicate that positive leadership promotes employees' state positive affect and engagement. State positive affect partially mediates the association between positive leadership and employee engagement. Moreover, a multilevel moderation analysis reveals that collectivism weakens the effect of positive leadership on employees' state positive affect. Theoretical and managerial implications and future directions are discussed.

Integrated Bioinformatics-Based Subtractive Genomics Approach to Decipher the Therapeutic Drug Target and Its Possible Intervention against Brucellosis.

Brucella suis, one of the causative agents of brucellosis, is Gram-negative intracellular bacteria that may be found all over the globe and it is a significant facultative zoonotic pathogen found in livestock. It may adapt to a phagocytic environment, reproduce, and develop resistance to harmful environments inside host cells, which is a crucial part of the Brucella life cycle making it a worldwide menace. The molecular underpinnings of Brucella pathogenicity have been substantially elucidated due to comprehensive methods such as proteomics. Therefore, we aim to explore the complete Brucella suis proteome to prioritize the novel proteins as drug targets via subtractive proteo-genomics analysis, an effort to conjecture the existence of distinct pathways in the development of brucellosis. Consequently, 38 unique metabolic pathways having 503 proteins were observed while among these 503 proteins, the non-homologs (n = 421), essential (n = 350), drug-like (n = 114), virulence (n = 45), resistance (n = 42), and unique to pathogen proteins were retrieved from Brucella suis. The applied subsequent hierarchical shortlisting resulted in a protein, i.e., isocitrate lyase, that may act as potential drug target, which was finalized after the extensive literature survey. The interacting partners for these shortlisted drug targets were identified through the STRING database. Moreover, structure-based studies were also performed on isocitrate lyase to further analyze its function. For that purpose, ~18,000 ZINC compounds were screened to identify new potent drug candidates against isocitrate lyase for brucellosis. It resulted in the shortlisting of six compounds, i.e., ZINC95543764, ZINC02688148, ZINC20115475, ZINC04232055, ZINC04231816, and ZINC04259566 that potentially inhibit isocitrate lyase. However, the ADMET profiling showed that all compounds fulfill ADMET properties except for ZINC20115475 showing positive Ames activity; whereas, ZINC02688148, ZINC04259566, ZINC04232055, and ZINC04231816 showed hepatoxicity while all compounds were observed to have no skin sensitization. In light of these parameters, we recommend ZINC95543764 compound for further experimental studies. According to the present research, which uses subtractive genomics, proteins that might serve as therapeutic targets and potential lead options for eradicating brucellosis have been narrowed down.

Authoritarian leadership and cyberloafing: A moderated mediation model of emotional exhaustion and power distance orientation.

Drawing upon the conservation of resource theory (COR), this study proposes a moderated mediation model of authoritarian leadership on subordinates' cyberloafing. Paired samples of 360 employees working in 103 teams from Chinese companies were collected at 2 points in time. The results show that authoritarian leadership positively affects subordinates' cyberloafing and this relationship is mediated by emotional exhaustion. Furthermore, power distance orientation negatively moderates the relationship between authoritarian leadership and emotional exhaustion and also negatively moderates the indirect effect of authoritarian leadership on subordinates' cyberloafing through subordinates' emotional exhaustion. Our findings expand and enrich the literature on authoritarian leadership and cyberloafing and have significant practical implications for managing employees in this digital era.

Identification of New Drug Target in Staphylococcus lugdunensis by Subtractive Genomics Analysis and Their Inhibitors through Molecular Docking and Molecular Dynamic Simulation Studies.

Staphylococcus lugdunensis is a coagulase-negative, Gram-positive, and human pathogenic bacteria. S. lugdunensis is the causative agent of diseases, such as native and prosthetic valve endocarditis, meningitis, septic arthritis, skin abscesses, brain abscess, breast abscesses, spondylodiscitis, post-surgical wound infections, bacteremia, and peritonitis. S. lugdunensis displays resistance to beta-lactam antibiotics due to the production of beta-lactamases. This study aimed to identify potential novel essential, human non-homologous, and non-gut flora drug targets in the S. lugdunensis strain N920143, and to evaluate the potential inhibitors of drug targets. The method was concerned with a homology search between the host and the pathogen proteome. Various tools, including the DEG (database of essential genes) for the essentiality of proteins, the KEGG for pathways analysis, CELLO V.2.5 for cellular localization prediction, and the drug bank database for predicting the druggability potential of proteins, were used. Furthermore, a similarity search with gut flora proteins was performed. A DNA-binding response-regulator protein was identified as a novel drug target against the N920143 strain of S. lugdunensis. The three-dimensional structure of the drug target was modelled and validated with the help of online tools. Furthermore, ten thousand drug-like compounds were retrieved from the ZINC15 database. The molecular docking approach for the DNA-binding response-regulator protein identified ZINC000020192004 and ZINC000020530348 as the most favorable compounds to interact with the active site residues of the drug target. These two compounds were subjected to an MD simulation study. Our analysis revealed that the identified compounds revealed more stable behavior when bound to the drug target DNA-binding response-regulator protein than the apostate.

Humor at work that works: A multi-level examination of when and why leader humor promotes employee creativity.

Although the role of leadership in fostering employee creativity has been extensively studied, it is still unclear whether and how leader humor affects employee creativity. Drawing upon cultural representation theory (CRT), we examined creative self-efficacy as a mediator and traditionality as a situational factor in the relationship between leader humor and employee creativity by analyzing a sample of 306 employees and 88 leaders (paired data) collected through survey questionnaire from firms based in Hubei Province, China, covering the industries of automobile, IT, and medicine. Following the multi-level examination, leader humor was positively related to employee creativity, and creative self-efficacy was found to mediate the impact of leader humor on employee creativity. Furthermore, traditionality moderated the effect of leader humor on creative self-efficacy, as well as the indirect effect of leader humor on employee creativity through creative self-efficacy. This study provides a social psychological explanation for the association between humor and employee creativity, deepens the current understanding of the influence process of leader humor. Finally, the theoretical and practical implications of the study are discussed at the end alongside limitations and recommendations for future research.

Reverse vaccinology approach for multi-epitope centered vaccine design against delta variant of the SARS-CoV-2.

The ongoing COVID-19 outbreak, initially identified in Wuhan, China, has impacted people all over the globe and new variants of concern continue to threaten hundreds of thousands of people. The delta variant (first reported in India) is currently classified as one of the most contagious variants of SARS-CoV-2. It is estimated that the transmission rate of delta variant is 225% times faster than the alpha variant, and it is causing havoc worldwide (especially in the USA, UK, and South Asia). The mutations found in the spike protein of delta variant make it more infective than other variants in addition to ruining the global efficacy of available vaccines. In the current study, an in silico reverse vaccinology approach was applied for multi-epitope vaccine construction against the spike protein of delta variant, which could induce an immune response against COVID-19 infection. Non-toxic, highly conserved, non-allergenic and highly antigenic B-cell, HTL, and CTL epitopes were identified to minimize adverse effects and maximize the efficacy of chimeric vaccines that could be developed from these epitopes. Finally, V1 vaccine construct model was shortlisted and 3D modeling was performed by refinement, docking against HLAs and TLR4 protein, simulation and in silico expression. In silico evaluation showed that the designed chimeric vaccine could elicit an immune response (i.e., cell-mediated and humoral) identified through immune simulation. This study could add to the efforts of overcoming global burden of COVID-19 particularly the variants of concern.

Nanoparticles Loaded Thermoresponsive In Situ Gel for Ocular Antibiotic Delivery against Bacterial Keratitis.

Antibiotics delivered through conventional dosage against ophthalmic infections show lower therapeutic efficacy due to their low residence time. Therefore, there is a great need to design and develop novel dosage forms that would increase the ocular residence time of antibiotics at the site of infection. This study describes the development of nanoparticles laden in situ gelling solution, intended to sustain antibiotic release for improved therapeutic efficiency. Oxytetracycline-loaded gelatin-polyacrylic acid nanoparticles were prepared and incorporated in poloxamer-N407 solution. The rheological properties of the system were studied concerning time and temperature. Moreover, in vivo biocompatibility of the system was ascertained using the Draize test and histological studies. Finally, the optimized formulation was evaluated for in vitro antibacterial activity against one of the most common keratitis causing bacteria, Pseudomonas aeruginosa. Additionally, the in vivo efficacy was evaluated on the rabbit's eye conjunctivitis model. The formulation showed a sustained effect against keratitis; furthermore, the antibacterial activity was comparable with the commercial product.

Negative Influences of Differentiated Empowering Leadership on Team Members' Helping Behaviors: The Mediating Effects of Envy and Contempt.

PURPOSE: Given the popularity of empowerment practices among scholars and practitioners, this research examines whether a manager's differentiated empowering leadership negatively affects team members' helping behaviors and, if so, how. METHODS: The authors conducted one multi-source and time-lagged survey (with 44 managers and 212 team members) and two scenario-based experiments (with 120 participants in Study 2 and 121 participants in Study 3) to test the research model. RESULTS: Team managers' differentiated empowering leadership decreases team members' helping behaviors. In particular, for team members who receive less empowerment, differentiated empowering leadership may decrease their helping behaviors by eliciting their envy. For team members who receive more empowerment, differentiated empowering leadership may decrease their helping behaviors by inducing their contempt. CONCLUSION: This research introduces the concept of differentiated empowering leadership in response to calls to investigate the dark side of empowering leadership. It reveals that unequal distribution of authority among team members by managers can undermine employee relations and elicit negative emotions of envy and contempt, thereby decreasing employees' helping behaviors.

ExAID: A multimodal explanation framework for computer-aided diagnosis of skin lesions.

BACKGROUND AND OBJECTIVES: One principal impediment in the successful deployment of Artificial Intelligence (AI) based Computer-Aided Diagnosis (CAD) systems in everyday clinical workflows is their lack of transparent decision-making. Although commonly used eXplainable AI (XAI) methods provide insights into these largely opaque algorithms, such explanations are usually convoluted and not readily comprehensible. The explanation of decisions regarding the malignancy of skin lesions from dermoscopic images demands particular clarity, as the underlying medical problem definition is ambiguous in itself. This work presents ExAID (Explainable AI for Dermatology), a novel XAI framework for biomedical image analysis that provides multi-modal concept-based explanations, consisting of easy-to-understand textual explanations and visual maps, to justify the predictions. METHODS: Our framework relies on Concept Activation Vectors to map human-understandable concepts to those learned by an arbitrary Deep Learning (DL) based algorithm, and Concept Localisation Maps to highlight those concepts in the input space. This identification of relevant concepts is then used to construct fine-grained textual explanations supplemented by concept-wise location information to provide comprehensive and coherent multi-modal explanations. All decision-related information is presented in a diagnostic interface for use in clinical routines. Moreover, the framework includes an educational mode providing dataset-level explanation statistics as well as tools for data and model exploration to aid medical research and education processes. RESULTS: Through rigorous quantitative and qualitative evaluation of our framework on a range of publicly available dermoscopic image datasets, we show the utility of multi-modal explanations for CAD-assisted scenarios even in case of wrong disease predictions. We demonstrate that concept detectors for the explanation of pre-trained networks reach accuracies of up to 81.46%, which is comparable to supervised networks trained end-to-end. CONCLUSIONS: We present a new end-to-end framework for the multi-modal explanation of DL-based biomedical image analysis in Melanoma classification and evaluate its utility on an array of datasets. Since perspicuous explanation is one of the cornerstones of any CAD system, we believe that ExAID will accelerate the transition from AI research to practice by providing dermatologists and researchers with an effective tool that they can both understand and trust. ExAID can also serve as the basis for similar applications in other biomedical fields.

Differential analysis of Orientia tsutsugamushi genomes for therapeutic target identification and possible intervention through natural product inhibitor screening.

Orientia tsutsugamushi (Ott) is a causative agent of scrub typhus, and one of the emerging pathogens that could affect a large human population. It is one of the misdiagnosed and under-reported, febrile illnesses that infects various body organs (skin, heart, lung, kidney, and brain). The control of this infection is hampered due to the lack of drugs or vaccine against it. This study was undertaken to identify potential drug targets from the core genome of Ott and investigate novel natural product inhibitors against them. Hence, the available genomes for 22 strains of Ott were downloaded from the PATRIC database, and pan-genomic analysis was performed. Only 202 genes were present in the core region. Among these, 94 were identified as essential, 32 non-homologous to humans, nine non-homologous to useful gut flora and a single gene dapD as a drug target. Product of this gene (2,3,4,5-tetrahydropyridine-2-carboxylate N-succinyltransferase) was modeled and docked against traditional Indian (Ayurvedic) and Chinese phytochemical libraries, with best hits selected for docking, based on multiple target-drug/s interactions and minimum energy scores. ADMET profiling and molecular dynamics simulation was performed for top three compounds from each library to assess the toxicity and stability, respectively. We presume that these compounds (ZINC8214635, ZINC32793028, ZINC08101133, ZINC85625167, ZINC06018678, and ZINC13377938) could be successful inhibitors of Ott. However, in-depth experimental and clinical research is needed for further validation.

Bad apples spoiling the metaphor? How and why self-serving leaders stir up counterproductive behaviors at work.

Self-serving leaders satisfy their self-interests at the cost of both employees and organizations, leading to declining organizational competitive advantage and performance. Drawing upon the affective events theory (AET), we constructed and examined a theoretical model of self-serving leadership influencing counterproductive work behavior (CWB), where traditionality plays a significant moderating role through the lens of anger as a mediator. Data were collected in three waves using a survey questionnaire distributed in three industries located in the Southwest district of China. Hierarchical regression analyses were conducted on a sample of 316 employees to test the hypothesized research model. The results showed that self-serving leadership triggers employee anger, which in turn causes CWB. Furthermore, traditionality plays a significant moderating role, in which employees with higher levels of traditionality feel less anger and show less CWB. Overall, research findings have clarified how and why self-serving leadership affects employees' emotions (such as anger) and behavior (such as CWB), bringing new insights into the self-serving leadership and employee behavior literature. Research implications on the management of self-serving leadership, limitations, and future recommendations of research are also discussed.

Identification of a Novel Therapeutic Target against XDR Salmonella Typhi H58 Using Genomics Driven Approach Followed Up by Natural Products Virtual Screening.

Typhoid fever is caused by a pathogenic, rod-shaped, flagellated, and Gram-negative bacterium known as Salmonella Typhi. It features a polysaccharide capsule that acts as a virulence factor and deceives the host immune system by protecting phagocytosis. Typhoid fever remains a major health concern in low and middle-income countries, with an estimated death rate of ~200,000 per annum. However, the situation is exacerbated by the emergence of the extensively drug-resistant (XDR) strain designated as H58 of S. Typhi. The emergence of the XDR strain is alarming, and it poses serious threats to public health due to the failure of the current therapeutic regimen. A relatively newer computational method called subtractive genomics analyses has been widely applied to discover novel and new drug targets against pathogens, particularly drug-resistant ones. The method involves the gradual reduction of the complete proteome of the pathogen, leading to few potential and novel drug targets. Thus, in the current study, a subtractive genomics approach was applied against the Salmonella XDR strain to identify potential drug targets. The current study predicted four prioritized proteins (i.e., Colanic acid biosynthesis acetyltransferase wcaB, Shikimate dehydrogenase aroE, multidrug efflux RND transporter permease subunit MdtC, and pantothenate synthetase panC) as potential drug targets. Though few of the prioritized proteins are treated in the literature as the established drug targets against other pathogenic bacteria, these drug targets are identified here for the first time against S. Typhi (i.e., S. Typhi XDR). The current study aimed at drawing attention to new drug targets against S. Typhi that remain largely unexplored. One of the prioritized drug targets, i.e., Colanic acid biosynthesis acetyltransferase, was predicted as a unique, new drug target against S. Typhi XDR. Therefore, the Colanic acid was further explored using structure-based techniques. Additionally, ~1000 natural compounds were docked with Colanic acid biosynthesis acetyltransferase, resulting in the prediction of seven compounds as potential lead candidates against the S. Typhi XDR strain. The ADMET properties and binding energies via the docking program of these seven compounds characterized them as novel drug candidates. They may potentially be used for the development of future drugs in the treatment of Typhoid fever.

Pan-Genome Reverse Vaccinology Approach for the Design of Multi-Epitope Vaccine Construct against Escherichia albertii.

Escherichia albertii is characterized as an emerging pathogen, causing enteric infections. It is responsible for high mortality rate, especially in children, elderly, and immunocompromised people. To the best of our knowledge, no vaccine exists to curb this pathogen. Therefore, in current study, we aimed to identify potential vaccine candidates and design chimeric vaccine models against Escherichia albertii from the analysis of publicly available data of 95 strains, using a reverse vaccinology approach. Outer-membrane proteins (n = 4) were identified from core genome as vaccine candidates. Eventually, outer membrane Fimbrial usher (FimD) protein was selected as a promiscuous vaccine candidate and utilized to construct a potential vaccine model. It resulted in three epitopes, leading to the design of twelve vaccine constructs. Amongst these, V6 construct was found to be highly immunogenic, non-toxic, non-allergenic, antigenic, and most stable. This was utilized for molecular docking and simulation studies against six HLA and two TLR complexes. This construct can therefore be used for pan-therapy against different strains of E. albertii and needs to be tested in vitro and in vivo.

Refractive index sensing and switching of leaky states in a metasurface.

We theoretically propose leaky states in an electro-optic (EO)-based all-dielectric metasurface. The EO substrate tunes leaky modes to the desired wave band with changes in applied voltage (Vapp). For refractive index (RI) sensing, the highest figure-of-merit (FoM) in this work is 9166, quality factor (Q-factor) is 1.7450e4, sensitivity is 407 nm/RIU (in RI range of 1.00-1.03), minimum detectable RI is 1.0542e-4, and relative sensitivity is 9.94e-4V-1. The structure sustains the figure and line shape of leaky modes, high Q-factor, and FoM at different Vapp and EO-coefficients. Our FoM and Q-factor are high, and the minimum detectable RI is smaller than previously reported. The giant Q-factor is promising for optical filters, modulation, and slow-light device applications.

How does responsible leadership affect employees' voluntary workplace green behaviors? A multilevel dual process model of voluntary workplace green behaviors.

This study aims to explore how to encourage employees to engage in voluntary workplace green behavior. Drawing upon social identity and social information processing theories, we theorized and tested a multilevel model in which responsible leadership triggers employee voluntary workplace green behavior by fostering organizational identification and a green work climate. Additionally, we distinguished these two critical processes by introducing employees' green values as a moderator. A multilevel, multisource study collected from 299 employees and 71 supervisors generally supported our predictions. Specifically, responsible leadership was a significant predictor of voluntary workplace green behavior. Moreover, employees' green values strengthened the organizational identification mechanism and attenuated the green work climate process in the relationship between responsible leadership and voluntary workplace green behavior. The findings and the theoretical underpinning of our study shed a new light on the green work climate, identity, and values in a responsible way shape the voluntary green behaviors among organizational actors and provide practical implications for leaders determined to improve environmental sustainability in organizations.

Optical Bound States in Continuum in MoS2-Based Metasurface for Directional Light Emission.

High quality factor (Q-factor) and strong field localization in nanostructures is a newly emerged direction in nanophotonics. The bound states in the continuum (BIC) have been investigated in nanoparticles with infinite Q-factor. We report BIC in molybdenum disulfide (MoS2) based Mie nanoresonator suspended in air. The ultrathin nanodisk supports symmetry protected BIC, and the quasi-BIC (q-BIC) are exploited by breaking the symmetry of the structure. The strongly localized modes in our MoS2-based nanodisk sustain a similar magnetic field profile before and after symmetry breaking, unlike what has been previously reported in silicon-based structures. Strong directional emission is observed in BIC regime from a hybrid configuration with a resonator placed on the stacked metal-dielectric layers, which transform BIC to q-BIC and exploit highly directional light. The structure persists emission with small variations in normalized intensity at distorted symmetry. The giant Q-factor in q-BIC is highly desired for biosensing and optical filters.

Correction to: Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning.

Following publication of the original article.

Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning.

BACKGROUND: With the advancement of powerful image processing and machine learning techniques, Computer Aided Diagnosis has become ever more prevalent in all fields of medicine including ophthalmology. These methods continue to provide reliable and standardized large scale screening of various image modalities to assist clinicians in identifying diseases. Since optic disc is the most important part of retinal fundus image for glaucoma detection, this paper proposes a two-stage framework that first detects and localizes optic disc and then classifies it into healthy or glaucomatous. METHODS: The first stage is based on Regions with Convolutional Neural Network (RCNN) and is responsible for localizing and extracting optic disc from a retinal fundus image while the second stage uses Deep Convolutional Neural Network to classify the extracted disc into healthy or glaucomatous. Unfortunately, none of the publicly available retinal fundus image datasets provides any bounding box ground truth required for disc localization. Therefore, in addition to the proposed solution, we also developed a rule-based semi-automatic ground truth generation method that provides necessary annotations for training RCNN based model for automated disc localization. RESULTS: The proposed method is evaluated on seven publicly available datasets for disc localization and on ORIGA dataset, which is the largest publicly available dataset with healthy and glaucoma labels, for glaucoma classification. The results of automatic localization mark new state-of-the-art on six datasets with accuracy reaching 100% on four of them. For glaucoma classification we achieved Area Under the Receiver Operating Characteristic Curve equal to 0.874 which is 2.7% relative improvement over the state-of-the-art results previously obtained for classification on ORIGA dataset. CONCLUSION: Once trained on carefully annotated data, Deep Learning based methods for optic disc detection and localization are not only robust, accurate and fully automated but also eliminates the need for dataset-dependent heuristic algorithms. Our empirical evaluation of glaucoma classification on ORIGA reveals that reporting only Area Under the Curve, for datasets with class imbalance and without pre-defined train and test splits, does not portray true picture of the classifier's performance and calls for additional performance metrics to substantiate the results.