Past Successes Research Articles

High-Efficiency Multi-Drug Functional Profiling in a Microfluidic Device Towards Personalized Predictions in Pediatric Leukemia

Treatment of pediatric acute lymphoblastic leukemia (ALL) has seen dramatic improvements over the last several decades, leading to overall survival rates of over 85%. However, for patients with relapsed/refractory disease, achieving complete remission remains extremely challenging. Improving treatment outcomes for these patients will require increasingly personalized treatment strategies that make use of functional screens in addition to molecular profiling technologies for treatment selection. Given the past success of combination chemotherapy in cancer treatment and recent promise for newly developed targeted agents, functional assays that are able to evaluate patient response to combinations of therapies will likely be most effective in identifying clinically actionable treatment protocols. Moreover, assays that can achieve this with minimal patient sample and reduced experimental workload will have the greatest potential for clinical translation and integration into clinical workflows. To that end, this work aims to develop a microfluidic assay to directly test candidate combinations of therapeutics in patient derived ALL cells. We aim for this to serve as a more effective way to screen for drug combination response and higher order interactions relative to standard wellplate formats. Once validated, this assay can be used to identify biomarkers of response to standard and experimental combination regimens in pediatric ALL, and ultimately, could be used to prospectively guide therapy in newly diagnosed patients. The developed device achieves this by enabling simultaneous exposure to 3 superimposed small molecule drug gradients across a 3D culture of leukemia cells such that each location in the device comprises a unique combination of all 3 drugs within a simplex (Fig 1A). Single cell drug concentration exposure is determined from experimentally validated steady state computational fluid dynamics (CFD) model predictions, and single cell viability is analyzed via Calcein (live), PI (dead) and Hoechst (nuclear) staining following 48 hours of treatment. Using this system, we then develop a novel experimental and computational framework for evaluating drug combination efficacy and synergy across the full range of combination ratios captured in our device. Specifically, we evaluate response across multiple devices at optimally spaced dose levels, increasing coverage of the 3-drug combination space and allowing for custom implementation of established synergy models. This enables synergy assessment in a continuous gradient of drug combination ratios, as opposed to the discrete combination ratios commonly evaluated in standard assays, and may further improve detection of drug synergy and identification of the most potent and efficacious combination ratios. To demonstrate this, we analyze response to a combination of daunorubicin, vincristine, and nelarabine in Jurkats, a T-ALL cell line, across 7 different devices at 7 different dose levels (Fig 1B). We quantify viability as a function of concentration across each device and each dose level, and generate dose response curves at distinct zones within the device. Specifically, we generate dose response curves in zones dominated by daunorubicin, vincristine, and nelarabine alone and find half maximal effective concentration values (EC50 values) similar to those reported in literature. We further evaluate response at varying ratios of each 2-drug combination, and generate dose response curves as shown in Fig 1B. Analyzing the 2-drug combination dose responses relative to single-drug dose responses allows for quantification of 2-drug combination synergy based on Loewe and DiaMOND synergy models, and future work will extend our developed method to analyze emergent 3-drug combination synergy. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

INNV-18. PROLONGED REMISSION AFTER TREATMENT WITH SINGLE-AGENT IBRUTINIB AS MAINTENANCE THERAPY FOLLOWING SALVAGE RADIATION THERAPY FOR REFRACTORY/RELAPSE PRIMARY CNS LYMPHOMA

Abstract INTRODUCTION Primary central nervous system lymphoma (PCNSL) is a rare and aggressive disease. Standard induction therapy for PCNSL consists of a high-dose methotrexate-based (HD-MTX) regimen. For relapsed or refractory primary CNS lymphoma (r/r PCNSL), most of the non-standard treatment regimens including additional chemotherapy, stem cell transplant, or whole brain radiation therapy (WBRT) may not reach long-term remission due to intolerance of the treatment by the patients or lack of effects. Here we report a case with r/r PCNSL reached more than 50-month remission after salvage WBRT followed by single agent ibrutinib maintenance therapy. CASE REPORT: a 75-year-old female with PCNSL, experienced disease recurrence, despite undergoing multiple lines of treatment including initial HD-MTX, second-line rituximab and temozolomide, repeated HD-MTX, and a clinical trial. Because her disease was refractory to these treatment options, we decided to start WBRT as salvage therapy, which resulted in significant reduction of tumor burden. Prior studies, however, showed that r/r PCNSL patients who underwent salvage WBRT alone had a median survival of only 1-2 years. Therefore, to extend the remission after salvage WBRT, she opted to try ibrutinib, a Bruton’s tyrosine kinase inhibitor with past success in treating r/r PCNSL patients, as maintenance therapy after salvage WBRT. She tolerated well and decided to be off the treatment after 18 month-maintenance therapy. The patient has been stable clinically. She has since survived for more than 50 months after the completion of salvage WBRT plus maintenance therapy with ibrutinib. DISCUSSION Compared to prior reports of 11 to 16 months of median survival after salvage WBRT alone for r/r PCNSL, our case has had prolonged survival, which supports the potential positive effect of ibrutinib as maintenance therapy for r/r PCNSL after salvage WBRT

A Bibliographic Analysis of Adaptive Techniques for the Development of Environment-Friendly Renewable Energy Systems

Renewable Energy Sources (RES) have always been seen as a sustainable and environment-friendly solution to the energy needs of the globe. It is a club of many sources that have been explored widely in the last five decades, and many ways have been designed to harness energy from these sources. But unavailability at all times and fluctuations affect the power quality and reliability of these units. Many adaptive techniques have been designed to maintain these parameters of energy systems. The development is still going on and will go on to find more efficient techniques to extract reliable and quality power. This study presents a bibliographic view of the research in this area for different adaptive techniques. This study also presented an ongoing trend and the future possibilities and past successes that have been achieved in this arena. In the paper, many papers have been reviewed on the recent development in adaptive techniques for power systems in the last five decades. IEEE, the biggest source platform for researchers and scientists, is considered for a survey and statistical analysis of recent developments. Based on a survey and detailed study, graphical analysis is designed to give a very accomplished perspective of adaptive techniques in energy systems for the researchers. The present study suggested many measures and techniques which can contribute to establishing renewable energy systems, thus, decreasing pollution and providing a clean, green and sustainable environment. This study presents a Hybrid energy system with hybrid adaptive techniques as a key solution to overcome the problem of pollution using RES as much as possible and to satisfy the energy demand also. This study can be a major reference point for researchers and power engineers for providing an environment-friendly and sustainable RES-based energy solutions.

Radio Astronomical Antennas in the Central African Region to Improve the Sampling Function of the VLBI Network in the SKA Era?

On the African continent, South Africa has world-class astronomical facilities for advanced radio astronomy research. With the advent of the Square Kilometre Array project in South Africa (SA SKA), six countries in Africa (SA SKA partner countries) have joined South Africa to contribute towards the African Very Long Baseline Interferometry (VLBI) Network (AVN). Each of the AVN countries aims to construct a single-dish radio telescope that will be part of the AVN, the European VLBI Network, and the global VLBI network. The SKA and the AVN will enable very high sensitivity VLBI in the southern hemisphere. In the current AVN, there is a gap in the coverage in the central African region. This work analyses the increased scientific impact of having additional antennas in each of the six countries in central Africa, i.e., Cameroon, Gabon, Congo, Equatorial Guinea, Chad, and the Central African Republic. A number of economic human capital impacts of having a radio interferometer in central Africa are also discussed. This work also discusses the recent progress on the AVN project and shares a few lessons from some past successes in ground stations retrofitting.

ЭВОЛЮЦИОННЫЙ ПОПУЛЯЦИОННЫЙ МЕТОД РЕШЕНИЯ ТРАНСПОРТНОЙ ЗАДАЧИ

The paper considers an evolutionary population method for solving a transport problembased on the metaheuristics of crystallization of a placer of alternatives. We study a closed (orbalanced) model of the transport problem: the amount of cargo from suppliers is equal to the totalamount of needs at destinations. The goal of optimization is to minimize the cost (achieving a minimumof transportation costs) or distances and the criterion of time (a minimum of time is spent ontransportation). The metaheuristics of the crystallization of a placer of alternatives is based on astrategy based on remembering and repeating past successes. The strategy emphasizes «collectivememory», which refers to any kind of information that reflects the past history of development andis stored independently of individuals. An ordered sequence Dk of routes is considered as a codefor solving the transport problem. The objects are routes, the alternatives are the set of positions Pin the list, where np is the number of positions in the list Dk. The set of objects Dk corresponds tothe set of all routes. The set of alternative states P of the object corresponds to the set of alternativeoptions for placing the object in the list Dk. The operation of the population evolutionary algorithmfor the crystallization of a placer of alternatives is based on a collective evolutionarymemory called a placer of alternatives. A scattering of solution alternatives is a data structureused as a collective evolutionary memory that carries information about the solution, includinginformation about the realized alternatives of agents in this solution and about the usefulness ofthe solution. A constructive algorithm for the formation of a reference plan by decoding the list Dkhas been developed. At each step t, the problem of choosing the next route in the sequence Dk anddetermining the amount of cargo transported from the point of departure Ai to the point of destinationBj along this route is solved. The developed algorithm is population-based, implementing thestrategy of random directed search. Each agent is a code for some solution of the transport problem.At the first stage of each iteration l, a constructive algorithm based on the integral placer ofalternatives generates nk decision codes Dk. The formation of each decision code Dk is performedsequentially in steps by sequentially selecting an object and position. For the constructed solutioncode Dk, the solution estimate ξk and the utility estimate δk are calculated. An individual scatteringof alternatives Rk is formed and a transition to the construction of the next solution code is formed.At the second stage of the iteration, the integral placer of alternatives formed at previous iterationsfrom l to (l-1) is summed with all individual placers of alternatives formed at iteration l.At the third stage of iteration l, all integral utility estimates r*αβ of the integral placer of alternativesR*(l) are reduced by δ*. The algorithm for solving the transport problem was implemented inC++ in the Windows environment. Comparison of the values of the criterion, on test examples,with a known optimum showed that in 90% of the examples the solution obtained was optimal, in2% of the examples the solutions were 5% worse, and in 8% of the examples the solutions differedby less than 2%. The time complexity of the algorithm, obtained experimentally, lies within O(n2).

The Role of Industry 4.0 Technologies in Manufacturing Sustainability Assessment

Abstract To understand the past successes and future opportunities for applying Industry 4.0 technologies toward manufacturing sustainability assessment, this state-of-the-art review examines previous literature at the intersection of these domains. Specifically, we focus on the application of Industry 4.0 technologies in the context of the following stages in manufacturing sustainability assessment: (i) planning, infrastructure development, and problem definition, (ii) performance measurement, (iii) results interpretation and decision-making, as well as (iv) intervention, control, and validation strategies. On the basis of the literature review, we present the trends, benefits, research gaps, and required future work for holistically integrating the research domains mentioned above. To accompany this literature review, we performed a meta-analysis of 14,498 articles and compared them to 316 articles compiled from a focused literature search. Based on database-controlled keywords, networks representing keyword co-occurrences were constructed to reveal clusters of related terms and evaluate overall term centrality (i.e., importance). Results from this analysis showed that the two datasets exhibited a similar network structure and also helped reveal Industry 4.0-related opportunities for manufacturing sustainability assessment. They include areas such as automation, robotics, and advanced inspection technologies, which are yet to be exploited in manufacturing sustainability assessment. Further research is needed to investigate whether the incorporation of such areas can (i) facilitate more robust and accessible assessments of manufacturing sustainability and (ii) make manufacturing systems themselves more sustainable.

Buy and buy again: The impact of unique reference points on (re)purchase decisions

AbstractBehavioral finance has uncovered that investor engage emotionally when trading. We investigate how three psychological factors influence purchase and repurchase decisions: representativeness, the influence of prior gains, and reference points. Using trading data of 7200 UK investors we find that purchase decisions are influenced by representative heuristic and repurchase decisions are influenced by both representative heuristic and prior profitability. Further survival analysis showed that investors use the prior selling price as a unique reference point. Investors are more likely to repurchase a stock when trading above its reference point, but more likely to initiate the repurchase when trading below. Investors are influenced by previous experience and engage learning behavior when they seek to reinforce past success. As reference points are inferred but infrequently researched, this research adds to the literature and provides important and robust results for those engaging with financial planning clients.

The benefits of thinking about past successes. Recalling agency leads to greater susceptibility to positive cues in ambiguous facial expressions

ABSTRACT Positive affect can increase sensitivity to expressions of joy on people’s faces. One of the sources of positive emotions is the awareness of having important and valued attributes, such as agency and communion. The study investigated whether recalling experiencing agency and communion enhanced positive emotion recognition on emotionally ambiguous faces of other people. 180 students (50% women) were randomly divided into three groups: agency activation, communion activation and control group. In the first two conditions, participants were asked to recall a situation when they experienced agency or communion, in the last one they completed a control task. Then, they had to indicate what emotions were presented on faces showing ambiguous emotional expressions. Recalling agency led to the evaluation of ambiguous faces as more joyful compared to the control group, but the results depended on sex of the participants and of the presented face.

Resentment and ressentiment as motivating forces in Better Call Saul

This article argues that the philosophical and psychological concepts of resentment and ressentiment serve as compelling motivational forces in the lives and actions of the central characters that comprise the American TV series Better Call Saul (2015–22). For Nietzsche and Scheler, ressentiment involves the internalization of hostile affects that tend to reinforce a sense of powerlessness and feelings of inferiority. Unlike ressentiment, which can linger for a long time, resentment is an active and immediate mode of resistance that supports its stance against the conformist tendencies of passive or reactive forces. Resentment, if properly directed externally, can serve as an empowering and a creative, active force in a character’s life. For Jimmy McGill, resentment functions as a primary catalyst for his eventual transformation into the unethical, yet prosperous, criminal attorney Saul Goodman. Resentment, if directed inwards, can produce debilitating effects such as Jimmy’s older brother Chuck’s incapability to move past his hatred and envy over his younger brother’s past actions and successes as a lawyer. This article illuminates the role and character of resentment and ressentiment as affective forces for characters in television melodramas.

Resilience, reliability, and coordination in autonomous multi-agent systems

Multi-agent systems is an evolving discipline that encompasses many different branches of research. The long-standing Agents at Aberdeen ( A 3 ) group undertakes research across several areas of multi-agent systems, focusing in particular on aspects related to resilience, reliability, and coordination. In this article we introduce the group and highlight past research successes in those themes, building a picture of the strengths within the group. We close the paper outlining the future direction of the group and identify key open challenges and our vision towards solving them.

Directed Evolution of Herbicide Biosensors in a Fluorescence-Activated Cell-Sorting-Compatible Yeast Two-Hybrid Platform.

Developing sensory modules for specific molecules of interest represents a fundamental challenge in synthetic biology and its applications. A somewhat generalizable approach for this challenge is demonstrated here by evolving a naturally occurring chemically induced heterodimer into a genetically encoded sensor for herbicides. The interaction between PYRABACTIN-RESISTANT-like receptors and type-2C protein phosphatases is induced by abscisic acid—a small-molecule hormone in plants. We considered abscisic acid receptors as a potential scaffold for the development of biosensors because of past successes in their engineering, a structurally defined ligand cavity and the availability of large-scale assays for their activation. A panel of 475 receptor variants, mutated at ligand-proximal residues, was screened for activation by 37 herbicides from several classes. Twelve compounds activated at least one member of the mutant panel. To facilitate the subsequent improvement of herbicide receptors through directed evolution, we engineered a yeast two-hybrid platform optimized for sequential positive and negative selection using fluorescence-activated cell sorting. By utilizing this system, we were able to isolate receptors with low nanomolar sensitivity and a broad dynamic range in sensing a ubiquitous group of chloroacetamide herbicides. Aside from its possible applicative value, this work lays down conceptual groundwork and provides infrastructure for the future development of biosensors through directed evolution.

The Spillover Effect of Category Performance on Existing Entrepreneurial Crowd-Fundraising

Studies of entrepreneurial crowdfunding typically focus on the role of entrepreneurs’ traits and storytelling capability in promoting campaigns’ fundraising, while paying less attention to the spillover effect from other fundraising projects. We propose that the consequences assembled from the previous entrepreneurs’ actions within the same industry can be a source of category legitimacy for subsequent entrepreneurial fundraising. We further decompose this legitimacy spillover effect into two types: accumulated versus immediate effects and study their distinct influences on fundraising. Our empirical data, collected from 31767 Kickstarter projects of four basic categories from 2010 to 2020, confirmed the legitimacy spillover effect of past categorial performance on the fundraising of existing crowdfunding projects. We further show that the accumulated legitimacy spillover effect is much stronger than the immediate legitimacy spillover effect and that this spillover effect weakens in the case of entrepreneurs with past successes. Our study contributes to the crowdfunding and legitimacy spillover literature.

Games of Norms: Why Category Switching Is Penalized in Crowdfunding Platforms

While strategic change is key to the effective adaptation of new organizations, it often breeds doubt and assessment by resource holders. This study explores this dynamic by studying how resource holders guided by a community logic respond to category switching, a critical change in a producer’s positioning. Using reward-based crowdfunding as an empirical context, we theorize that backers assess category-switching creators as less trustworthy and committed to the values, ideals, and advancement of a specific community than nonswitching creators, therefore reducing their funding and support. The extent of these penalties, however, may vary depending on the attributes of both creators and backers. We hypothesize that backers may reduce the severity of sanctions to category switchers who demonstrate trustworthiness and competence either by indicating past success or presenting a more typical identity. In contrast, we expect that experienced backers, who hold a stronger sense of belonging and identification, will penalize switchers more harshly than new audience members and be less lenient toward competent or typical creators. We test our hypotheses using an extensive longitudinal sample of 34,701 entrepreneurial projects in Kickstarter from 2009 to 2016 and find support for most of our hypotheses. We discuss implications for studying how change affects resource acquisition when resource holders are guided by a community logic and for research studying categorical nonconformity.

Strategic Inertia and Renewal: Contrasting Responses to Market Changes

The academic, consulting, and practitioner-oriented literatures present many examples of companies that have failed to adapt their strategy in the face of a changing competitive arena, even when their top managers and executives acknowledged the need for change—and had a reasonable idea of what ought to be done. By means of an in-depth study of two polar cases of large companies from the fast-moving consumer goods sector, we shed light on the complex intertwined causes that might lead some companies into strategic inertia, while others engage in strategic renewal. Our findings suggest that strategic inertia is a multilevel phenomenon, which extends beyond the “usual suspects” presented, in isolation or in combination, in the literature (i.e., cognitions, power and politicking, emotions, and communication). We found that encouragement of divergent judgments and a participative planning process, as well as propensity to experiment, may lead a company to jettison the drivers of its past success and embrace novel pathways with serenity to deal with short-term uncertainty and anguish.

Algorithmic vs. Managerial Prioritization: Evidence from an Industrial B2B Sales Organization

Algorithms are increasingly deployed in organizations to replace and augment human intelligence. To understand more precisely the potential benefits of algorithms in organizations, there is a need to understand how and why the decisions of human organizational members are likely to differ from those of algorithms. We draw on the behavioral theory of the firm to elucidate the origins of those differences in the context of customer prioritization, using a unique dataset comparing managerial prioritization and algorithmic classification of customers in a large business-to-business (B2B) organization. We discuss two potential benefits of algorithms in prioritization tasks: enhancing the accuracy of existing prioritization logics and identifying new ones. The potential gains from enhancing accuracy of an existing prioritization logic are relatively easy to realize but the potential for performance improvement may be incremental. Identifying new prioritization logics has greater potential because organizations have a tendency to become anchored in replicating past successes and, thus, ignore latent opportunities. Algorithmic prioritization can counter this. However, the practical value of using algorithms to create new prioritization logics is constrained by the fact that the organizational repertoire of actions is tailored to the existing prioritization logic.

The Evolution of Behavioural Science in Public Policy

Interventions are to the social sciences what inventions are to the physical sciences—an application of science as technology. Behavioural science has emerged as a powerful toolkit for developing policy interventions and public programs for changing behaviour. Such behavioural change intervention can support societies in creating a better world together. However, the translation from principles to practice is often moderated by contextual factors—such as culture—that thwart attempts to generalize past successes. Here we discuss cultural evolution as a framework for addressing this contextual gap. We describe the history of behavioural science in public organisations and the role that cultural evolution plays as a natural next step. We review research that may be considered cultural evolutionary behavioural science in public policy, illustrating concrete applications in fields such as public health, corruption, and sustainable development. We synthesize the promises and challenges for designing cultural evolution informed interventions and assess their impact. Finally, we discuss the value of applied research as a crucial test of basic science: if theories, lab, and field experiments don’t work in the real world, they don’t work at all.

Rising to the Challenge: How Medical Reserve Corps Volunteers Serve as a Scalable Workforce for Local Health Departments in Response to COVID-19 and Beyond.

Rising to the Challenge: How Medical Reserve Corps Volunteers Serve as a Scalable Workforce for Local Health Departments in Response to COVID-19 and Beyond.

Does Explaining Past Success Require (Enough) Retention? The Case of Ptolemaic Astronomy

According to selective, retentive, scientific realism, past empirical success may be explained only by the parts of past theories that are responsible of their successful predictions being approximately true, and thus theoretically retained, or approximated, by the parts of posterior theories responsible of the same successful predictions. In this article, we present as case study the transit from Ptolemy’s to Kepler’s astronomy, and their successful predictions for Mars’ orbit. We present an account of Ptolemy’s successful prediction of Mars’ orbit from Kepler’s perspective, and scrutinize whether the theoretical elements responsible for Ptolemy’s empirical success are approximately retained in Kepler. In order to give to the realist the best chances, we try different strategies. We conclude that all fail and thereby this case constitutes a prima facie strong anomaly for selective retentive realism. Structural realists may call preservation of structure to the rescue, but the existing notions of structure do not work. In absence of a new notion that works, the burden of the proof lies on the realist side.

Evaluating the accuracy of the AMBER protein force fields in modeling dihydrofolate reductase structures: misbalance in the conformational arrangements of the flexible loop domains

Protein flexible loop regions were once thought to be simple linkers between other more functional secondary structural elements. However, as it becomes clearer that these loop domains are critical players in a plethora of biological processes, accurate conformational sampling of 3D loop structures is vital to the advancement of drug design techniques and the overall growth of knowledge surrounding molecular systems. While experimental techniques provide a wealth of structural information, the resolution of flexible loop domains is sometimes low or entirely absent due to their complex and dynamic nature. This highlights an opportunity for de novo structure prediction using in silico methods with molecular dynamics (MDs). This study evaluates some of the AMBER protein force field’s (ffs) ability to accurately model dihydrofolate reductase (DHFR) conformations, a protein complex characterized by specific arrangements and interactions of multiple flexible loops whose conformations are determined by the presence or absence of bound ligands and cofactors. Although the AMBER ffs, including ff19SB, studied well model most protein structures with rich secondary structure, results obtained here suggest the inability to significantly sample the expected DHFR loop–loop conformations – of the six distinct protein-ligand systems simulated, a majority lacked consistent stabilization of experimentally derived metrics definitive the three enzyme conformations. Although under-sampling and the chosen ff parameter combinations could be the cause, given past successes with these MD approaches for many protein systems, this suggests a potential misbalance in available ff parameters required to accurately predict the structure of multiple flexible loop regions present in proteins. Communicated by Ramaswamy H. Sarma

Examination of Altshuller's Trends of Technical System Evolution in Automotive Passenger Vehicles

AbstractAlthough Genrich Altshuller is perhaps better known for developing the Theory of Inventive Problem Solving (TRIZ), his work also includes eight trends of technical system evolution that he believed could be used to predict the future of products or systems. Those working in any high‐tech industry have always sought techniques to better forecast the evolution of their product in order to pursue the most promising of multiple possible evolutionary paths and make the most fruitful investments of time and money in new technologies. The authors are interested in including Altshuller's trends in their toolbox for predicting the future of the automobile but felt it would first be prudent to look back on the auto industry's approximately 160‐year history to see if Altshuller's trends appear consistent with that history. The assumption is that if the past history of the evolution of the automobile is consistent with those trends, then increased confidence can be had in any future predictions made by applying those same trends to the current state of the automobile to predict the future. When the history of the automobile was examined in roughly decade‐level time intervals, it was observed that in each time interval considered, typically six or more of Altshuller's eight trends were apparent. Interestingly, the authors found that there were a number of unsuccessful products throughout history that were largely consistent with the trends. This suggested that satisfaction of the trends of system evolution may be a necessary condition for system evolution but is not a sufficient condition for success. This work proposes that consideration of context and satisfaction of some typical system architecting heuristics can largely differentiate past success vs. failure amongst various systems that satisfy the eight trends, and hence recommend a hybrid approach consisting of Altshuller's trends of system evolution with specific attention to system context along with the application of system architecting heuristics as a potentially useful and valuable way to predict the future evolution of the automobile.