Literature-Related Discovery (LRD): Potential treatments for Parkinson's Disease

Literature-Related Discovery (LRD) is the linking of two or more literature concepts that have heretofore not been linked (i.e., disjoint), in order to produce novel, interesting, plausible, and intelligible knowledge (i.e., potential discovery). The open discovery systems (ODS) component of LRD starts with a problem to be solved, and generates solutions to that problem through potential discovery. We have been using ODS LRD to identify potential treatments or preventative actions for challenging medical problems, among myriad other applications. The previous two papers in this Special Issue describe the application of ODS LRD to Raynaud's Phenomenon (RP) and to cataracts.Parkinson's Disease (PD) is a progressive neurodegenerative disorder, affecting approximately 1% of individuals older than 60 years, and is characterized by resting tremor, rigidity, bradykinesia, and postural instability. We selected the subject of PD because of its global prevalence, and its apparent intractability to all treatments except for palliative remediation mainly through drugs or surgery.Our first goal was to identify non-drug non-surgical treatments that would 1) prevent the occurrence, or 2) reduce the progression rate, or 3) stop the progression, or 4) maybe even reverse the progression, of PD. Our second goal was to demonstrate that we could again solve an ODS problem (using LRD) with no prior knowledge of any results or prior work (unlike the case of the RP problem). As in the ‘cataract’ example, we used the MeSH taxonomy of MEDLINE to restrict potential discoveries to selected semantic classes, and to identify potential discoveries efficiently. Our third goal was to generate large amounts of potential discovery in more than an order of magnitude less time than required for the RP study. The discovery generation methodology has been developed to the point where ODS LRD problems can be solved with no results or knowledge of any prior work.     

Literature-related discovery (LRD): Potential treatments for Multiple Sclerosis

Literature-related discovery (LRD) is the linking of two or more literature concepts that have heretofore not been linked (i.e., disjoint), in order to produce novel, interesting, plausible, and intelligible knowledge (i.e., potential discovery). The open discovery systems (ODS) component of LRD starts with a problem to be solved, and generates solutions to that problem through potential discovery. We have been using ODS LRD to identify potential treatments or preventative actions for challenging medical problems, among myriad other applications. The previous three papers in this Special Issue describe the application of ODS LRD to Raynaud's Phenomenon (RP), cataracts, and Parkinson's Disease (PD).Multiple Sclerosis (MS) is a progressive neurodegenerative disorder (typically preceded by periods of remission and relapse), affecting mainly people in their early-mid life. MS is characterized by changes in sensation (hypoesthesia), muscle weakness, abnormal muscle spasms, or difficulty to move; difficulties with coordination and balance (ataxia); problems in speech (Dysarthria) or swallowing (Dysphagia), visual problems (Nystagmus, optic neuritis, or diplopia), fatigue and acute or chronic pain syndromes, bladder and bowel difficulties, cognitive impairment, or emotional symptomatology (mainly depression).We selected the subject of MS because of its global prevalence, and its apparent intractability to all treatments except for palliative remediation mainly through drugs or surgery. Our first goal was to identify non-drug non-surgical treatments that would 1) prevent the occurrence, or 2) reduce the progression rate, or 3) stop the progression, or 4) maybe even reverse the progression, of MS. Our second goal was to demonstrate that we could again solve an ODS problem (using LRD) with no prior knowledge of any results or prior work (unlike the case of the RP problem). As in the ‘cataract’ and PD examples, we used the MeSH taxonomy of MEDLINE to restrict potential discoveries to selected semantic classes, and to identify potential discoveries efficiently. Our third goal was to generate large amounts of potential discovery in more than an order of magnitude less time than required for the RP study. The discovery generation methodology has been developed to the point where ODS LRD problems can be solved with no results or knowledge of any prior work.     

Literature-related discovery (LRD): Potential treatments for Raynaud's Phenomenon

Literature-related discovery (LRD) is the linking of two or more literature concepts that have heretofore not been linked (i.e., disjoint), in order to produce novel, interesting, plausible, and intelligible knowledge (i.e., potential discovery). The open discovery systems (ODS) component of LRD starts with a problem to be solved, and generates solutions to that problem through potential discovery. We have been using ODS LRD to identify potential treatments or preventative actions for challenging medical problems, among myriad other applications.Raynaud's Phenomenon (RP) is a condition in which small arteries, most commonly in fingers and toes, contract and cause the skin to turn pale or a patchy red to blue. We selected the subject of RP for analysis by LRD because of RP's global prevalence, and its apparent intractability to all treatments except for palliative remediation mainly through drugs or surgery. Our main goal was to identify non-drug non-surgical treatments that would 1) prevent the occurrence, or 2) reduce the progression rate, or 3) stop the progression, or 4) maybe even reverse the progression, of RP. Our secondary goal was to compare our ODS LRD approach to the RP problem with other investigators who have addressed the RP problem since Swanson's pioneering 1986 ODS LRD paper on potential RP treatments [D.R. Swanson, Fish oil, Raynauds syndrome, and undiscovered public knowledge, Perspectives in Biology and Medicine 30 (1) (1986) 7-18].We used Medline from 1965-1985 to identify potential discovery for RP. We differ from all the other authors who have addressed this problem in two major respects: we make no numerically-based filtering assumptions, and we generate substantial potential discovery (∼ 130 potential discoveries). Further, we believe our reported results are the tip of the iceberg. Much more potential discovery is possible with an adequately resourced study using the lessons learned from this demonstration study and the other demonstration studies that follow in this Special Issue.     

Literature-related discovery: Potential treatments and preventatives for SARS

Literature-related discovery (LRD) is the linking of two or more previously disjoint concepts in order to produce novel, interesting, plausible, and intelligible connections (i.e., potential discovery). LRD has been used to identify potential treatments or preventative actions for challenging medical problems, among myriad other applications.Severe acute respiratory syndrome (SARS) was the first pandemic of the 21st century. SARS was eventually controlled through increased hygienic measures (e.g., face mask protection, frequent hand washing, living quarter disinfection), travel restrictions, and quarantine. According to recent reviews of SARS, none of the drugs that were used during the pandemic worked.For the present paper, SARS was selected as the first application of LRD to an infectious disease. The main goal of this research was to identify non-drug non-surgical treatments that would 1) prevent the occurrence, or 2) reduce the progression rate, or 3) stop/reverse the progression of SARS. The MeSH taxonomy of Medline was used to restrict potential discoveries to selected semantic classes, and to identify potential discoveries efficiently. To enhance the volume of potential discovery, databases were used in addition to Medline. These included the Science Citation Index (SCI) and, in contrast to previous work, a full text database. Because of the richness of the full text, ‘surgical’ queries were developed that targeted the exact types of potential discovery of interest while eliminating clutter more efficiently.     

Literature-related discovery (LRD): Lessons learned, and future research directions

Literature-related discovery (LRD) is the linking of two or more literature concepts that have heretofore not been linked (i.e., disjoint), in order to produce novel, interesting, plausible, and intelligible knowledge (i.e., potential discovery). The open discovery systems (ODS) component of LRD starts with a problem to be solved, and generates solutions to that problem through potential discovery. We have been using ODS LRD to identify potential treatments or preventative actions for challenging medical problems, among myriad other applications. The five immediately preceding papers in this Special Issue describe the application of ODS LRD to Raynaud's Phenomenon (RP), cataracts, Parkinson's Disease (PD), Multiple Sclerosis (MS), and Water Purification (WP). We describe the lessons learned from each application, and how the techniques can be improved further.Generation of much potential discovery using ODS LRD is possible when the conceptual roadblocks to discovery are removed. Some of these roadblocks include use of numerical filters that are unrelated to generating discovery, and excessive reliance on literatures directly related to the problem literature of interest. The issue of how to handle large amounts of potential discovery has not been addressed in the literature, since most ODS LRD researchers have tried to find a relatively few potential discovery items. We present a development strategy that capitalizes on the large amounts of potential discovery we have identified.     

Literature-related discovery (LRD): Methodology

Literature-related discovery (LRD) is linking two or more literature concepts that have heretofore not been linked (i.e., disjoint), in order to produce novel, interesting, plausible, and intelligible knowledge. LRD has two components: Literature-based discovery (LBD) generates potential discovery through literature analysis alone, whereas literature-assisted discovery (LAD) generates potential discovery through a combination of literature analysis and interactions among selected literature authors. In turn, there are two types of LBD and LAD: open discovery systems (ODS), where one starts with a problem and arrives at a solution, and closed discovery systems (CDS), where one starts with a problem and a solution, then determines the mechanism(s) that links them.The generic methodology for identifying potential discovery candidates through ODS LRD, focusing mainly on its ODS LBD component, is described in this paper. A comprehensive flow chart showing the details of our systematic potential discovery generation process, including the evolution of the flow chart steps through each of the studies performed, is presented. Also shown is a vetting procedure that insures potential discoveries claimed are potential discoveries realized. The semantic filters that replace the numerical filters of other ODS LBD approaches are overviewed. The rationale for addressing the five topics studied (Raynaud's Phenomenon (RP), Cataracts, Parkinson's Disease (PD), Multiple Sclerosis (MS), and Water Purification (WP)) is summarized.     

Literature-related discovery (LRD): Water purification

Literature-related discovery (LRD) is the linking of two or more literature concepts that have heretofore not been linked (i.e., disjoint), in order to produce novel, interesting, plausible, and intelligible knowledge (i.e., potential discovery). LRD has two main components that differ in their methodological approach to discovery: Literature-based discovery (LBD) produces potential discovery through analysis of the technical literature alone; Literature-assisted discovery (LAD) produces potential discovery through both analysis of the technical literature and use of selected authors of that literature. These authors generate potential discovery as proposers, workshop/panel participants, or in other active roles.The open discovery systems (ODS) component of LRD starts with a problem to be solved, and generates solutions to that problem through potential discovery. We have been using ODS LRD to identify potential treatments or preventative actions for challenging medical problems, among myriad other applications. The previous four papers in this Special Issue describe the application of ODS LRD (specifically, the ODS LBD variant) to Raynaud's Phenomenon (RP), cataracts, Parkinson's Disease (PD), and Multiple Sclerosis (MS).One goal of the present study was to determine whether LRD could be successfully applied (for the first time) to a challenging non-medical technical problem to generate potential discovery. The second goal was to explore the use of both LRD variants (LBD and LAD) to a non-medical technical problem. We selected the problem of water purification (WP) because of universal applicability and sponsor interest.We used LRD to identify purification concepts, technology components and systems that could lead to improved water purification techniques. We accessed many disparate disciplines to identify purification concepts from literatures not normally associated with water purification. We used two LBD approaches, Cluster Filtering and Latent Semantic Indexing (LSI), to search for potential discovery. We generated voluminous amounts of potential discovery, and believe we have only scratched the surface of what is possible. We also ran a short experiment using LAD to identify experts associated with potential discovery concepts, and use their expertise to generate potential discovery for water purification.     

Literature-Related Discovery (LRD): Introduction and background

Discovery in science is the generation of novel, interesting, plausible, and intelligible knowledge about the objects of study. Literature-related discovery (LRD) is the linking of two or more literature concepts that have heretofore not been linked (i.e., disjoint), in order to produce novel, interesting, plausible, and intelligible knowledge (i.e., potential discovery). LRD has two main components that differ in their methodological approach to discovery:

•

Literature-based discovery (LBD) produces potential discovery through analysis of the technical literature alone.

•

Literature-assisted discovery (LAD) produces potential discovery through both analysis of the technical literature and use of selected authors of that literature. These authors generate potential discovery as proposers, workshop/panel participants, or in other active roles.

LRD offers the promise of large amounts of potential discovery, for the following reasons:

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the burgeoning technical literature contains a very large pool of technical concepts in myriad technical areas;

•

researchers spend full time trying to cover the literature in their own research fields and are relatively unfamiliar with research in other especially disparate fields of research;

•

the large number of technical concepts (and disparate technical concepts) means that many combinations of especially disparate technical concepts exist

•

by the laws of probability, some of these combinations will produce novel, interesting, plausible, and intelligible knowledge about the objects of study.

This Special Issue presents the LRD methodology and voluminous discovery results from five problem areas: four medical (treatments for Parkinson's Disease (PD), Multiple Sclerosis (MS), Raynaud's Phenomenon (RP), and Cataracts) and one non-medical (Water Purification (WP)). In particular, the open discovery systems (ODS) aspect of LRD (start with problem, generate potential solution(s), or vice versa) is addressed, rather than the closed discovery systems (CDS) aspect (start with problem and potential solution(s), generate linking mechanism(s)). In the presentation of potential discovery, a ‘vetting’ process is used that insures both requirements for ODS LBD are met: concepts are linked that have not been linked previously, and novel, interesting, plausible, and intelligible knowledge is produced.The potential discoveries for the PD, MS, Cataracts, and WP problems are the first we have seen reported by this ODS LBD approach, and the numbers of potential discoveries for the ODS LBD benchmark RP problem are almost two orders of magnitude greater than those reported in the open literature by any other ODS LBD researcher who has addressed this benchmark RP problem. The WP problem is the first non-medical technical topic to have been addressed successfully by ODS LBD.In all cases, but especially the medical, we have barely scratched the surface of quantity and quality of potential discovery that could be generated with adequately resourced studies. Based on the many potential discoveries we have obtained, and the promise of far more potential discoveries with adequately resourced studies, we have generated a new paradigm relative to discovery: while the key challenge in traditional discovery is finding a needle-in-a-haystack, the key challenge in ODS LRD (used appropriately) is handling the overwhelming amount of potential discovery available.Additionally, it is our thesis, as the specific ODS LBD studies will demonstrate, that synergistic combinations of our mainly individual potential discoveries are themselves potential discoveries. We demonstrate throughout this Special Issue the synergistic effects of combining a very few potential discoveries or interesting core literature concepts, and believe that these synergistic benefits are operable at larger scales of combination. In the final lessons-learned paper of this Special Issue, we also show that providing evidence for the synergistic benefits of large numbers of potential discoveries or interesting core concepts is very difficult due to the large numbers of potential combinations involved.One variant of the LAD operational mode (identifying disparate discipline recipients for Broad Agency Announcement (BAA) notifications in order to stimulate proposals of new ideas from these disparate disciplines) is presented for WP. Other possible applications of LAD include:

1.

Recipients of solicitation announcements (other solicitations similar to BAA, journal Special Issue calls for papers, etc),

2.

Participants in Workshops, Advisory Panels, Review Panels, Roadmaps, and War Games,

3.

Points of Contact for Field Science Advisors, Foreign Field Offices, Program Officer site visits, and potential transitions.

     

The association between the severity of chronic kidney disease and medical costs among patients with type 2 diabetes

Aims: Examine healthcare costs across chronic kidney disease (CKD) stages for US patients with type 2 diabetes (T2D).

Materials and methods: IQVIA Real World Data Adjudicated Claims linked electronic medical records and insurance claims from January 1, 2012 through March 31, 2017 were used for this retrospective study. Adults diagnosed with T2D and comorbid CKD were included. General linear models incorporating splines were constructed, and information from these regressions were used to inform the relationship between medical costs and CKD. Multivariable analyses controlled for patient characteristics, vital signs, general health, prior medication use, prior visit to specialists, index A1c, and year of index date.

Results: There were 6,645 individuals who met the study criteria. Results generally indicate sharp increases in annual total medical costs and non-drug medical costs in the 1?year post-period for patients with Stage 4 or 5 CKD (estimated glomerular filtration rate [eGFR]?≤?30?mL/min/1.73 m²) with each 1 point reduction in eGFR from 30 associated with an increase of $1,870 in all-cause total medical costs (p?<?0.0001) and $1,805 of all-cause non-drug medical costs (p?<?0.0001). Similarly, each point decline below 30?mL/min was associated annual cost increases of $1,701 for CKD-related total medical costs, $1,695 for CKD-related non-drug medical costs, $173 for diabetes-related medical costs, and $187 for diabetes-related non-drug medical costs (all p?<?0.0001).

Limitations: The investigation included only patients with medical insurance and laboratory test results, and results may not be generalizable to all T2D patients with CKD. The methodology allowed us to determine associations, not causation, and potential confounders, such as duration of diabetes, diet, exercise, or social support, could not be assessed.

Conclusions: Results indicate there are sharp and significant increases in medical costs among T2D patients with Stage 4 and 5 CKD compared to those with earlier stages of CKD.     

Combining Revealed Preference Data with Stated Preference Data: A Latent Class Approach

A substantial literature exists combining data from revealed preference (RP) and stated preference (SP) sources, aimed either at testing for the convergent validity of the two approaches used in nonmarket valuation or as a means of drawing on their relative strengths to improve the ultimate estimates of value. In doing so, it is assumed that convergence of the two elicitation approaches is an “all or nothing” proposition; i.e., the RP and SP data are either consistent with each other or they are not. The purpose of this paper is to propose an alternative framework that allows for possible divergence among individuals in terms the consistency between their RP and SP responses. In particular, we suggest the use of a latent class approach to segment the population into two groups. The first group has RP and SP responses that are internally consistent, while the remaining group exhibits some form of inconsistent preferences. An EM algorithm is employed in an empirical application that draws on the Alberta and Saskatchewan moose hunting data sets used in earlier combined RP and SP exercises. The empirical results suggest that somewhere between one-third and one-half the sample exhibits consistent preferences. We also examine differences in welfare estimates drawn from the two classes.     

An Entrepreneurial Perspective of Institutional Change

Utilizing Kirzner's theory of entrepreneurial discovery, Schumpeter's two types of economic responses and the Austrian theory of institutions as building blocks, this paper constructs an entrepreneurial theory of institutional change. Focusing on the coordinating role of human institutions, this paper argues that entrepreneurial extraordinary discovery destroys the stability of institutions and creates uncertainty in the market (creative response). As a result, institutions are incapable of coordinating economic activities because market participants' stocks of knowledge are no longer adequate to solve new problems. Hence, profit gaps or mismatches of market participants' plans occur. Given new technologies, new relative prices and tastes, imitative entrepreneurs soon identify and capitalize on the opportunities created by Schumpeterian extraordinary discoveries (adaptive response). Imitators improve production methods, modify rules and alter property rights in order to improve coordination. Through learning, experimentation, trial and error, the more rewarding methods are then selected. Successful actions are imitated and repeated in the market, and gradually crystallized into new institutions which once again serve as social coordinators.     

Exploring potential R&D collaboration partners through patent analysis based on bibliographic coupling and latent semantic analysis

The aim of the present research is to provide a new systematic methodology to explore potential Research and Development (R&D) collaboration partners using patent information. The potential R&D collaboration partners are visualised as a patent assignee level map based on technological similarity between patents by using the network analysis. The proposed framework utilises two analytic methods to measure technological similarity. The first method, bibliographic coupling analysis, measures technological similarity based on the citation relationship using patent bibliographic information. Second, latent semantic analysis is utilised based on semantic similarity using patent textual information. The fuel cell membrane electrode assembly technology field is selected and applied to illustrate the proposed methodology. The proposed approach allows firms, universities, research institutes and governments to identify potential R&D collaborators as a systematic decision-making support tool.     

绿色战略供应商的优选模型研究

环境与资源日益成为人类生存与发展的制约因素,根据企业的具体目标,运用多目标规划对供应商进行优选,从而得出企业最终要选择的供应商.以ABB公司的供应商的优选为案例,将文中的模型进行具体应用,通过目标规划模型的求解得出其绿色战略供应商的组合和相应的采购数量.     

Resource discovery and the politics of fiscal decentralization

If the central government is a revenue maximizing Leviathan then resource discovery and democratization should have discernible impacts on the degree of fiscal decentralization. We systematically explore these effects by exploiting exogenous variation in giant oil and mineral discoveries and permanent democratization. Using a global dataset of 77 countries over the period 1970–2012 we find that resource discovery has very little effect on revenue decentralization but induces expenditure centralization. Oil discovery appears to be the main driver of centralization and not minerals. Resource discovery leads to centralization in locations which have not experienced permanent democratization. Tax and intergovernmental transfers respond most to resource discovery shocks and democratization whereas own source revenue, property tax, educational expenditure, and health expenditure do not seem to be affected. Higher resource rent leads to more centralization and the effect is moderated by democratization.     

Commons with increasing marginal costs: random priority versus average cost*

Indivisible units are produced with increasing marginal costs. Under average cost, each user pays average cost. Under random priority, users are randomly ordered (without bias) and successively offered to buy at the true marginal cost. Both average cost (AC) and random priority (RP) inefficiently overproduce. RP tends to overproduce less, but which game collects more surplus depends much on the demand configuration. We show that a key to compare the welfare properties of the two mechanisms is the crowding factor, i.e., the number of potential users over the number of units of output users can afford: The more crowded the commons, the more RP outperforms AC. In the quadratic cost case, beyond the threshold value of 2.4 for the crowding factor, RP strongly outperforms AC; beneath it AC only mildly outperforms RP. Thus the RP mechanism manages crowded commons better than AC.     

Price regulation of drugs: Lessons from Germany

This paper purports to explain the pricing policy of pharmaceutical companies in Germany prior and after the introduction of reference prices (RP) in 1989. First, the threat of such regulation may have kept prices finite despite a completely insured market. Next, the pricing policies of both the producer of an innovative drug and of a competing generic under RP are predicted. These predictions are then confronted with actual pricing policy for three products in the guise of case studies. Finally, the impact of modified copayment rules on pricing decisions is analyzed.The authors would like to thank Dr Michael Wiegand (Bonn) for valuable information and two anonymous referees for helpful criticisms.     

Competitive investing equilibrium under a procurement mechanism

This paper proposes a procurement mechanism for a research and development (R&D) project, in which the stochastic nature of R&D is incorporated, and the potential agents needed to invest prior to the agent are selected. The incentive contract aims to attract the investment of potential agents through a sharing rate. By establishing the stopping time game, an optimal investing strategy for potential agents is derived. Furthermore, the investment equilibria are discussed, and the conditions under which the equilibrium represents preemption or simultaneous investment are presented.     

收入分配研究述评

收入差距拉大引发的社会两极分化问题已成为中国社会最为敏感问题之一,这一问题也影响着社会与经济的可持续发展。收入分配不公带来的社会冲突、分层加剧、资源配置失衡等危害也已引起政府的高度关注。本文着重从行业垄断、税收调控、社会保障等方面评述影响收入分配差距拉大的因素。为改善我国收入分配不平等状况,需要对初次分配与再分配加以规范。因此,限制公共权力,加强对垄断的监管,规范劳动力市场是关键,与此同时,税收、转移支付与社会保障等宏观调控手段应被广泛采用。     

中国企业家创业环境地区差异的实证研究

利用问卷调查数据,对中国企业家创业环境的地区差异进行了实证研究,发现企业家创业环境方面,与东部相比,中部和西部都表现出地区间的显著差异;中部与西部之间则表现出明显的相似之处;企业家创业环境因素中,地方政府效率对企业家创业的影响显著;中部和西部地区的资金环境已经严重阻碍了企业家的创业活动。这些发现有助于我们深入认识中西部企业家创业环境改善的途径,从而有助于培育企业家精神。