Emerging+trends+and+new+developments+in+regenerative+medicine

Thenew review identifies emerging trends and new developments appearing inthe literature of regenerative medicine based on relevant articles and reviewspublished between 2000 and the fir

1 Introduction

2 Methods

3 Most active topics

4 Emerging trends and new developments

5 Expert opinion

Emerging trends and new developments in regenerative medicine: a scientometric update

Chaomei Chen†, Rachael Dubin & Meen Chul Kim

Drexel University, College of Computing and Informatics, Philadelphia, PA, USAIntroduction: Our previous scientometric review of regenerative medicineprovides a snapshot of the fast-growing field up to the end of 2011 Thenew review identifies emerging trends and new developments appearing inthe literature of regenerative medicine based on relevant articles and reviewspublished between 2000 and the first month of 2014

Areas covered: Multiple datasets of publications relevant to regenerativemedicine are constructed through topic search and citation expansion toensure adequate coverage of the field Networks of co-cited references repre-senting the literature of regenerative medicine are constructed and visualizedbased on a combined dataset of 71,393 articles published between 2000 and

2014 Structural and temporal dynamics are identified in terms of most activetopical areas and cited references New developments are identified in terms

of newly emerged clusters and research areas Disciplinary-level patterns arevisualized in dual-map overlays

Expert opinion: While research in induced pluripotent stem cells remains themost prominent area in the field of regenerative medicine, research related

to clinical and therapeutic applications in regenerative medicine has enced a considerable growth In addition, clinical and therapeutic develop-ments in regenerative medicine have demonstrated profound connectionswith the induced pluripotent stem cell research and stem cell research ingeneral A rapid adaptation of graphene-based nanomaterials in regenera-tive medicine is evident Both basic research represented by stem cell researchand application-oriented research typically found in tissue engineering arenow increasingly integrated in the scientometric landscape of regenerativemedicine Tissue engineering is an interdisciplinary field in its own right.Advances in multiple disciplines such as stem cell research and grapheneresearch have strengthened the connections between tissue engineeringand regenerative medicine

experi-Keywords: CiteSpace, graphene,regenerative medicine, review, scientometrics, tissue engineering

Expert Opin Biol Ther (2014) 14(9):1295-1317

1 Introduction

The fast-growing interdisciplinary field of regenerative medicine offers significantpotential to advance understanding of cellular processes and to enable personalizedtreatments for a wide range of conditions by inducing and encouraging the restora-tion of diseased or damaged tissue[1] As the field has advanced, the cutting edge ofthese treatments has moved from the use of grafts to replace tissue to the introduc-tion of growth factors to encourage the natural tissue healing process, and finally to

the more recent use of materials such as stem cells, each of

which has the potential to differentiate into a wide range of

different types of cells[2] Thus, stem cells provide an ideal

medium for generating tissues and have roused a great deal

of excitement in the field

Acquiring stem cells for use in research and treatment poses

a challenge Embryonic stem cells are pluripotent, having the

ability to differentiate into any cell type, and are therefore

tre-mendously valuable for regenerative medicine applications

However, due to moral concerns surrounding the destruction

of embryos for stem cell use, this line of research faces ethical

as well as legal barriers[3] Adult stem cells also provide many

opportunities, such as the generation of bone tissue from

adipose-derived mesenchymal stem cells [4] or the use of

epithelial or mesenchymal dental stem cells for regenerative

dentistry[2] However, adult stem cells are comparatively

lim-ited and can differentiate only into cell types derived from

their same embryological germ layer[3] Induced pluripotent

stem cells (iPSCs) offer an alternative option; these types of

stem cells are derived from differentiated, mature cells, but

like embryonic stem cells they are pluripotent

The 2012 Nobel Prize in Physiology or Medicine was

awarded to John B Gurdon and Shinya Yamanaka for their

finding that pluripotent stem cells can be produced by

‘reprogramming’ mature, specialized cells Gurdon performed

his early work in this area with cells taken from tadpoles[5] In

this foundational study, he took nuclei from tadpole intestinal

epithelium cells and transplanted them into tadpole eggs and

found that some of the eggs with donor nuclei developed into

normal tadpoles (others reaching various stages of abnormal

development) These results demonstrated that a cell which

was already differentiated contained sufficient genetic

infor-mation to produce all types of cells necessary to develop a

normal organism, and alluded to the possibility of

transform-ing mature cells into pluripotent stem cells In Takahashi and

Yamanaka’s study[6], or in Takahashi2006, as we will refer to

in the scientometric study, transcription factors supporting

the continued pluripotency of embryonic stem cells were

isolated and introduced into mature mouse cells (specificallytail-tip fibroblasts) The resulting cells were identical to embry-onic stem cells and, when injected into live mice, formedtumors which contained cells from all three embryonic germlayers

The development of a pluripotent embryonic stem cell intoits differentiated adult state was long thought to be a one waytrip; cells became ever more specialized and, with only fewexceptions, lost their ability to self-renew Although it wasinitially believed that these adult cells lacked the genetic infor-mation required to produce different types of cells, Gurdon’sstudy demonstrated that sufficient information was present byimplanting nuclei taken from adult tadpoles into tadpoleeggs [5] Nuclear transfer continued to serve as a powerfulmethod, for instance, enabling the cloning of Dolly thesheep[7]and of other animals However, this method is fairlyinefficient, with many embryos generated from transferrednuclei experiencing genetic defects of various levels of severitydue to factors such as the condition of the donor cell[8] Othertechniques were developed to improve efficiency, such as theuse of teratocarcinomas to produce embryonal carcinoma cells(ECCs), which served as an immortal line of pluripotent cells.Although these ECCs are not typically effective in generatingtissue directly, they can be used in cellular fusion to enableother cells to exhibit pluripotency [9] However, it was theNobel Prize-winning discovery that brought recognition ofhow the specific transcription factors at work in embryonicstem cells could induce pluripotency in a mature cell[6].Our previous scientometric study of regenerative medicinepresented a snapshot of the literature of regenerative medicine

as of the end of November 2011[10] Since its data cutoff datewas in 2011, we will refer to it as the 2011 review In 2011, itbecame clear that two articles on the discovery of iPSCs hadgenerated a tremendously high impact; they were highly cited

at an increasingly faster rate a phenomenon known as acitation burst They influenced many newer articles withthe discovered technique The significance of the iPSCresearch was detected in the literature several months prior

to the announcement of the award of the Nobel Prize inOctober 2012

Responses to the breakthrough creation of iPSCs quicklyfocused on possible applications of the new technique; forexample, the use of reprogrammed iPSCs to treat sickle-cellanemia in a mouse model [11] or the generation of new,healthy motor neurons from iPSCs derived from a patientwith amyotrophic lateral sclerosis [12] In addition to treat-ment applications, iPSCs have also been used to advanceunderstanding of a variety of disorders including Alzheimer’sdisease[13]and congenital long QT syndrome[14]

Researchers have investigated some of the drawbacks anddangers of iPSC generation and use Suppression of thep53 pathway has been investigated as a means of improvingthe efficiency of iPSC generation and reducing the likelihood

of malignant tumors[15] Although the use of patient-derivediPSCs suggests the unlikelihood of rejection, immunogenicity

Article highlights.

The literature of regenerative medicine has increased

considerably over the past 2 years.

The previously overwhelming dominance of research on

induced pluripotent stem cells (iPSCs) found at the end

of 2011 has shifted to multiple prominent areas of

research, notably iPSC-related research, tissue

engineering of a new generation and clinical and

therapeutic applications.

A rapid adaptation of graphene-based nanomaterials is

evident A profound impact on many aspects of

regenerative medicine is expected.

Interplays between basic research and

application-oriented research are expected in the further

development of the increasingly interdisciplinary field.

This box summarizes key points contained in the article.

of these cells has also been a topic of exploration[16] Finally,

mutations in iPSCs have been studied in mouse [9] and in

human cells[17]

Alternative techniques for generation and use of iPSCs werealso brought to discussion Potentially risky viral integration of

transcription factors were replaced with the use of neural

progenitor cells and small molecules[18]or ‘piggyBac’

transpo-sition [19] Blood cells, including cord and peripheral blood,

were used to generate iPSCs[20] Recent work has also explored

alternative ways of transforming mature, differentiated cells

into pluripotent ones without the use of transcription factors

Mature cells were shown to become pluripotent once exposed

to a low pH treatment, described as a ‘stimulus-triggered

acquisition of pluripotency’ (STAP)[21], although the

repro-ducibility of the work has been subsequently questioned

Another offshoot of research investigates reprogramming

mature cells not into iPSCs but instead into other types of

mature cells, such as cardiomyocytes[22], or neurons[23]

The literature relevant to regenerative medicine has grownrapidly, as we will show shortly Two full years have elapsed

since we conducted our scientometric study of the field at

the end of 2011 In order to identify significant changes in

the intellectual landscape of regenerative medicine, we revisit

the literature of the field now to conduct a follow-up

sciento-metric study of the field The focus of the new scientosciento-metric

study is on the new developments that can be revealed usingscientometric and visual analytic tools

According to information available on the Internet, majortopics in regenerative medicine are shown in two visualiza-tions inFigure 1 The two visualizations, known as form trees,

were generated using Carrot, http://search.carrotsearch.com/carrot2-webapp, based on the first 100 results of a web search(left) and the 100 results of a PubMed search (right) Stemcell-related research, tissue engineering, organs, repair,patients and would healing are among the leading topics inregenerative medicine In this review, we will rely on scholarlypublications in the Web of Science as a more rigorous andreliable representation of the literature The lightweight viewgenerated using Carrot provides a useful point of reference

so that any substantial discrepancies would be accounted for

2 Methods

The new study will utilize several scientometric and visualanalytic methods In particular, burst detection will be applied

to subject categories and keywords assigned to publications in

a citation-expanded collection of articles relevant to tive medicine as well as noun phrases extracted from titles andabstracts of these articles In addition, burst detection will beapplied to articles in terms of the growth rate of their

regenera-Figure 1 A lightweight survey of major topics on the Internet on regenerative medicine is shown The visualizations were generated by the Carrot system based on first 100 results of search on regenerative medicine Left: search results from the web Right: search results from the PubMed.

citations A burst of an event is a surge of the frequency of the

event, such as the appearance of a keyword or the citation of

an article

The structure and dynamics of the literature of regenerative

medicine will be analyzed in terms of progressively

synthe-sized networks derived from citations made by citing articles

that meet various selection criteria Synthesized networks

will be decomposed into clusters as tightly coupled references

to represent a common theme of research Next, these clusters

will be labeled by using terms extracted from the titles of the

most representative citing articles for each cluster Several

different forms of visualizations will be generated to highlight

new developments since 2012 Although many of the

techni-ques were used in the preparation of our 2011 review, a few

new techniques will be used in the new study

Different networks of articles can be generated by defining

the similarity between two articles differently For example,

similarities defined in terms of co-citation strengths would

lead to co-citation networks, whereas similarities based on

bibliographic coupling would lead to a different network

Dual-map overlays introduced in[24]provide a global

visu-alization of the growth of the literature at a disciplinary level

The dual-map visualization will be used in this study with

recently published high-impact articles as overlays

A predictive modeling method introduced in[25]estimates

the transformative potential of an article in terms of structural

variation metrics This method will be used in the new study

to identify a list of potentially significant articles based on

their structural novelty

Although there are an increasing number of science

map-ping systems and generic tools [26], few systems are readily

accessible and specifically designed to meet the needs for

generating a systematic review of a fast-moving and complex

field, especially with features to facilitate the detection and

interpretation of emerging trends and transition patterns for

analysts who are not domain experts CiteSpace is particularly

designed to support the complete analytic process of

visualiz-ing and analyzvisualiz-ing scientific literature It has been used for

performing several hundreds of scientometric studies An

earlier version of CiteSpace was used in our 2011 review

2.1Datasets

Our new review of regenerative medicine aims to provide an

update of our 2011 review Our 2011 review started with a

topic search for ‘regenerative medicine’ between 2000 and

2011 and focused on original research articles and reviewpapers only with a 3875-record core dataset and an expandeddataset of 35,963 records through forward-citation links.The expanded dataset, consisting of 28,252 articles oforiginal research and 7711 review articles, was considered to

be an adequate representation of the regenerative medicineliterature

We made the decision to include original research papersand review papers primarily for two reasons: i) originalresearch papers are representative of the state of the art ofthe field, although other types of documents such as lettersmay also represent the state of the art; and ii) review papersrepresent an additional layer of representative papers selected

by domain experts (i.e., the authors of review papers).The new review aims to identify new developments in thefield of regenerative medicine since our 2011 review We firstreconstructed the core dataset used in the 2011 review as thedataset DA, then expanded the core dataset with forward-citation links to articles published between 2000 and

2014 as the dataset DB Next, we used the same topic search

to retrieve new articles published after the cutoff date of our

2011 review data collection as the dataset DC Similarly, DC

was expanded through forward citations to form a newexpanded dataset DD The purpose is to identify how manynew articles appeared since our previous review (Table 1).Finally, all the four individual datasets were combined Afterduplicates were removed, the final dataset DABCD was usedfor the analysis We used the dataset DABCDas our primarysource but also used other individual datasets in the review.The growth of the literature over the past 2 years is enormous.The 4331-article core in 2011 has grown to 6957 in February

2014, a 60.6% of increase The 35,963-record expanded set in 2011 is almost doubled to 71,393 in February 2014, a98.5% of increase.Table 1summarizes these datasets

data-Figure 2visualizes a broad context of research in tive medicine in terms of research fronts and the intellectualbase Current research fronts are built on an underlyingintellectual base through backward citations[27] The intellec-tual base consists of 34,805 references cited by researchfront articles drawn from the dataset DABCD(2000 2014).Research front articles are selected if they are among the

regenera-5000 most-cited articles published in the same year duringthe 15-year time span Research front articles are shown asdots in red, whereas intellectual-base references are shown asdots in other colors that indicate the year of their publication

Table 1 A summary of the datasets collected

For example, references published in early years of the time

span are colored in blue, light blue and green, whereas more

recently published references are colored in yellow and

orange

The position of iPSC research is approximately centered inthe rectangular area in the universe of regenerative medicine

The name of the first author of Takahashi2006 and

Takahashi2007 is marked by labels In the rest of this article,

we will use an abbreviated notion to refer to articles identified

in the review with the name of its first author only and the

year of its publication, for example, as in Takahashi 2006;

this is in part because the cited reference field of a

biblio-graphic record in the Web of Science does not include

coauthors’ names

2.2CiteSpace

CiteSpace visualizes the literature in the form of a co-citation

network, which draws on article citations to reveal the

struc-ture of a field or fields [27-29] CiteSpace was used in our

2011 review and will be used for this new review as well

References cited by a given article provide valuable mation regarding intellectual connections between various

infor-scientific concepts[25,30] In a co-citation network, an edge iscreated between two article nodes when a third article citesthem together, and conceptual clusters are formed as certaingroups of articles are repeatedly referenced in conjunctionwith one another CiteSpace depicts the changes which occur

in a body of literature over time by overlaying ‘time slice’ works, each including the citations made in 1 year The newworks published each year may strengthen existing relationsbetween articles or make new ones, and by comparing thesetime slices, we reveal the ever-changing recognition of mean-ingful concepts made by researchers in a field CiteSpaceuses color-coded nodes and edges to discriminate betweencombined networks, with each year in a dataset assigned toits own color The color of a network edge indicates theyear in which the co-citation link was first made Nodes aremade up of ‘tree rings’ of different colors, the thickness ofwhich represents the number of citations the article received

net-in a particular year A red rnet-ing present net-in a particular yeardenotes a citation burst, that is, a surge of citations in thatyear A purple ring is used to represent the degree of a node’sbetweenness centrality A node with high betweenness central-ity links a conceptual cluster in one time with one in another

Figure 2 The research fronts and the intellectual base of regenerative medicine are shown Red dots in the foreground represent research front articles of the D ABCD dataset (2000 2014) A total of 34,805 dots of various other colors in the background represent references that form the intellectual base, which are linked to research front articles by forward citations The underlying intellectual base network is derived from citations made by up to 5000 most-cited research front articles per year during the 15-year period between 2000 and 2014 The first authors of the highest cited references are labeled, notably Takahashi as the first author of the two groundbreaking induced pluripotent stem cells articles.

and can be seen as a bridge extending from earlier to more

recent ideas

2.2.1Document co-citation analysis

A document co-citation network represents a network of

references that have been co-cited by a set of publications

CiteSpace first generates a document co-citation network

from articles published in a single year y as a Document

co-citation analysis (DCA[y]), then it integrates a time series

of the individual DCAs for all the years in a time interval

and produces a synthesized network The dataset DABCD

rep-resents an expanded literature of regenerative medicine

because it contains not only publications that are matched

by topic fields, namely, titles, abstracts, and keywords, but

also publications that cite topic-matched articles Specifically,

the dataset DABCDcontains 71,393 articles published in the

15-year period between 2000 and 2014 The date of data

retrieval was 2 February 2014

When generating an individual DCA network, a selection

threshold is set so that whether an article’s citation behavior

will be taken into account will dependent on the extent the

article has been cited in its own right For example, we may

set the threshold to be top 100 highly cited articles to

repre-sent the citation patterns of a particular year In other words,

articles that failed to be ranked high enough will not be able

to contribute to the network structure, which is preferable

because we would be more interested in the citation pattern

of recognized works In this article, we typically use top

100 articles per year as the selection

CiteSpace provides functions to reduce the number of links

while retaining the most salient structure The link reduction

functions include a Minimum Spanning Tree pruning and a

Pathfinder Network Scaling pruning

Burst detection identifies articles that have attracted the

attention of peer scientists CiteSpace supports the detection

of two types of burst: citation-based burst detection and

occurrence-based burst detection

2.2.2Dual-map overlays

Dual-map overlays introduced in[24] are used for this study

Dual-map overlays are superimposed on a global basemap of

scientific literature The global basemap consists of two

com-ponent maps, hence the term dual-map overlays One

compo-nent basemap represents a network of over 10,000 journals in

terms of their similarity as citing journals computed based on

the 2011 Journal Citation Report of Thomson Reuters The

similarity between two citing journals is determined by the

fre-quency distribution of how often they cite other journals The

other component also represents a network of over

10,000 journals but in terms of their similarities as

cited journals

A distinct set of publications can be used to generate a

dual-map overlay For each article in the publication set, the

journal in which it appears is located in the network of citing

journals on the left-hand side of the basemap References cited

by the articles are located in the network of cited journals onthe right-hand side of the basemap The trajectories of theset over time are shown in terms of the paths formed bythe weight centers of corresponding publications and referen-ces, retrospectively The dynamics of the underlying researchactivities can be revealed in terms of the stability of thecorresponding trajectories

The dataset DA contains 3875 articles published between

2000 and 2011 They were retrieved by a topic search for

‘regenerative medicine’ in the Web of Science The dataset

DA was used in our 2011 review of the field [10], which isused as a point of reference for the new review A dual-mapoverlay of the dataset is generated to illustrate the disciplines

in which these articles were published and the disciplinesfrom which these articles refer to through citation links asthe source of their inspirations

3 Most active topics

Regenerative medicine is an interdisciplinary field of study,which not only involves numerous disciplinary areas but alsodemonstrates shifts of the intensity of publications in terms

of abrupt changes of subject categories and keywords of thesepublications as well as their citations Each publicationindexed in the Web of Science is assigned one or more subjectcategories such as oncology, pathology and microbiology.Each publication is also assigned a number of keywords.The shift of these fast-increasing subject categories orkeywords indicates the most active areas of publications at adisciplinary level The burstness of subject categories, key-words or cited references is a valuable indicator of most activeresearch topics at various levels of granularity

3.1 Subject categories (2000 2014)Burst detection revealed subject categories that increasedabruptly over time (Figure 3) Subject categories of articles inthe combined expanded dataset DABCD(2000 2014) wereanalyzed for their burstness A total of 71,327 of the 71,393records have valid subject categories A total of 186 uniquesubject categories were found Occurrence bursts were detected

in association with 47 subject categories

This time interval is depicted as a blue line The periodtime in which a subject category was found to have a burst

is shown as a red line segment, indicating the beginningyear and the ending year of the duration of the burst Forexample, at the top of the list, subject category general &internal medicine has a period of burst between 2000 and

2005 with a burst strength of 7.3231 Hot areas prior to

2008 all belong to the disciplines of medicine and biology.Hot areas associated with social sciences appeared for the firsttime in 2008 social sciences other topics, ethics and socialissues have strong bursts from 2008 to 2009 with burststrengths over 6.0348 Notably, both Nanoscience & nano-technology (12.6639) and energy & fuels (8.6723) have verystrong bursts since 2013

At a finer-grained level, burst patterns of keywords, that is,indexing terms, may also reveal what was new in regenerative

medicine Each year up to 5000 most-frequently appeared

keywords were selected for the burst detection throughout

the 15-year time span (2000 2014), which resulted in

21,044 unique keywords in total The most common

keywords are in-vitro, appearing in 11,479 articles and

differentiation, appearing in 10,689 articles The keyword

regenerative medicine appeared in 1728 articles

Among the top 100 keywords with the strongest strength ofburst, we are particularly interested in those keywords that

started to burst from 2009 onward (Figure 4) For example,

the keyword human somatic cells bursted between 2009 and

2010 with a burst strength of 29.2 Keywords starting their

bursts since 2013 include nanoparticles (22.1), which

appeared in 1515 articles, neuroregeneration (18.9, in

65 articles) and graphene (16.0, in 59 articles)

The number of articles with graphene listed as a keyword inthe expanded dataset DABCDhas increased rapidly from 3 in

2010 to 125 in 2013 For example, an article on

‘self-assembled graphene hydrogel via a one-step hydrothermal

process’[8]in the expanded dataset was cited 290 times The

most commonly appeared phrases in the titles of these articles

are nanomaterials (16 times), carbon dots (7 times), carbon

nanotubes (6 times), graphene hydrogels and graphene oxide

(both 5 times)

In the expanded dataset, three articles published in 2012contain both graphene and regenerative either in the title or

in the abstract There are seven such articles in 2013 For

example, one article is about ‘a graphene-based platform for

iPSCs culture and differentiation’ [11] and another about

‘self-supporting graphene hydrogel film as an experimental

platform to evaluate the potential of graphene for boneregeneration’[12]

These connections between graphene as nanomaterials andcentral concepts in regenerative medicine and tissue engineer-ing such as iPSCs and hydrogels provide strong evidencethat the surge of the keyword graphene indeed indicates aprofound synergy between nanotechnology and regenerativemedicine

3.2Cited references (2000 2014)Specific growth areas in the field are characterized by articlesthat experienced citation bursts.Figure 5shows top 100 refer-ences with strongest citation bursts during the period between

2000 and 2014 This was based on up to 5000 most-citedarticles per year as the citing articles

A total of 34,805 references were selected from 9,262,246valid references There are another 3894 invalid referencesbecause of incomplete components

The article with the strongest citation burst is shi2006, which was one of the two landmark papers that led

Takaha-to the 2012 Nobel Prize in medicine for research on iPSCs.Its burst lasted for 3 years from 2009 to 2011 with a burststrength of 427.6 (Table 2) The burst of this article wasalso detected in our previous review published in 2012.Takahashi2007 has the fourth-strongest burst of 226.2 from

2012 are associated with four 2011 articles Since their citation

Figure 3 Among 186 subject categories, 47 subject categories have occurrence bursts during (2000 2014).

bursts occurred after the publication of our 2011 review, we

will inspect these four 2011 articles in further detail

Among the articles with strong citation bursts since 2012,

Hanahan and Weinberg’s 2011 article[31], titled ‘Hallmarks

of cancer: The next generation’, has the strongest citation

burst with a burst strength of 93.1 This article published in

Cell identified six biological hallmarks of cancer and arguedthat reprogramming of energy metabolism and evadingimmune destruction as two emerging hallmarks being added

to the list The second article with the most recent citationburst studies the immunogenicity of iPSCs [32] The workhas clinical implications on any therapeutic use of autologous

Figure 4 Keywords with periods of burst from 2009 onward based on up to 5000 most frequently appeared keywords per year for 15 years (2000 2014) are shown.

Figure 5 A total of 100 references with the strongest citation bursts over the period between 2000 and 2014 are shown The burst detection was based on the citations made by the top 5000 articles per year during the 15-year time span.

cells derived from iPSCs The third article that has drawn

much attention since 2012 is a 2011 article by

Anokye-Danso et al.[33]on a more efficient reprogramming approach

than existing approaches to reprogram somatic cells to

pluripotency The fourth article is a review article by

Dasha et al.[34] published in 2011 on new developments of

chitosan-based biomedical applications, including the

chemi-cal and biologichemi-cal properties of chitosan for regenerative

medicine.Table 4list the full references of these four articles

and sentences selected from their abstracts Their numbers

follow Table 3 Articles 9, 10 and 11 are related to various

aspects of iPSC research Articles 9 and 12 are particularly

relevant to regenerative medicine

Figure 5 shows 100 references with the strongest citationbursts in the order of the beginning year of a period of citation

burst

4 Emerging trends and new developments

4.1Clusters of co-cited references (2000 2014)

The datasets DA and DCcollectively represent the literature

defined by a topic search for regenerative medicine

(2000 2014) Our 2011 study reviewed the literature up

to November 2011 What has changed since then?Figure 6

shows two versions of a snapshot of the literature as of thebeginning of February 2014 The structure of the field is char-acterized by a synthesized network of 719 references co-citedbetween 2000 and 2014 by the top 100 most-cited articlesper year The version of the snapshot on the left depicts land-mark articles as large citation rings and hotspot articles withcitation bursts shown as citation rings in red The colors oflinks in this version represent the first year when those linkswere made The version on the right highlights new develop-ments (colored in blue) after our 2011 review and shows hownew clusters are connected with previously established areas(colored in red) For example, two new areas can be identified

as cluster #8 on cell sheeting engineering (located near the top

of the network) and cluster #4 on biologic scaffold (located inthe northeast quadrant)

The focus of the two newly emerged clusters of co-cited ences, #4 and #8, can be partially revealed in terms of what thearticles that cite the members of these clusters have in common.For example, Table 5 lists articles that cited > 10% of themembers of cluster #4 and 22% of the members of cluster #8

refer-Table 2 Top five references with the strongest citation bursts during 2000 2014

Citation burst

Table 3 References with the most recent bursts from 2011

Citation burst

For cluster #4, unique title terms identified in this group of

citing articles include the term “ control” in the context of

controlled stem cell differentiation, control of live cells and

control of neuronal cell adhesion

The pattern in cluster #8 is clearer than in the cluster #4

The term ‘cell sheet engineering’ consistently appeared in the

titles of three of the four top-citing articles of cluster #8

Clus-ter #8 also has a higher degree of concentration than clusClus-ter

#4 Each of the first two citing articles in cluster #8 cited

over 35% of the cluster members (Table 5) In particular,

the first article’s title provides a self-explained definition

of what cell sheet engineering is about: a unique ogy for scaffold-free tissue reconstruction with clinicalapplications in regenerative medicine

nanotechnol-4.2 New co-citation clusters in 2012 2014

To clearly identify new developments in regenerative medicinesince our 2011 scientometric study, we generated two timelinevisualizations based on the combined dataset DABCD, acitation-expanded representation of the literature of

Table 4 The four hot articles with citation bursts since 2012 First authors’ names are used in the references.Additional co-authors, if any, are not included

9 Hanahan and Weinberg (2011) [31] Hallmarks of Cancer: The Next Generation CELL, V144, P646.

‘Conceptual progress in the last decade has added two emerging hallmarks of potential generality to this list reprogramming of energy metabolism and evading immune destruction’.

10 Zhao e t al (2011) [16] Immunogenicity of induced pluripotent stem cells NATURE, V474, P212.

‘These findings indicate that, in contrast to derivatives of ESCs, abnormal gene expression in some cells differentiated from iPSCs can induce T-cell-dependent immune response in syngeneic recipients Therefore, the immunogenicity of therapeutically valuable cells derived from patient-specific iPSCs should be evaluated before any clinic application of these autologous cells into the patients’.

11 Anokye-Danso et al (2011) [33] Highly efficient miRNA-mediated reprogramming of Mouse and human somatic cells to pluripotency CELL STEM CELL, V8, P376.

‘This miRNA-based reprogramming approach is two orders of magnitude more efficient than standard Oct4/Sox2/

Klf4/Myc-mediated methods’.

12 Dash et al (2011) [34] Chitosan A versatile semi-synthetic polymer in biomedical applications PROG POLYM SCI, V36, P981.

‘Chitosan is a polyelectrolyte with reactive functional groups, gel-forming capability, high adsorption capacity and biodegradability In addition, it is innately biocompatible and non-toxic to living tissues as well as having antibacterial, antifungal and antitumor activity These features highlight the suitability and extensive applications that chitosan has in medicine Micro/nanoparticles and hydrogels are widely used in the design of chitosan-based therapeutic systems.

The chemical structure and relevant biological properties of chitosan for regenerative medicine have been summarized

as well as the methods for the preparation of controlled drug release devices and their applications’.

ESCs: Embryonic stem cells; iPSCs: Induced pluripotent stem cells.

Figure 6 Illustrations of regenerative medicine (2000 2014) Left: Landmark nodes (large citation tree rings) and hotspot articles (citation bursts in red rings) Right: New developments (colored in blue) since our 2011 review, for example, #8 cell sheet engineering and #4 biologic scaffold, versus previously identified areas (colored in red).

Table 5 A list of articles that contributed to clusters #4 control or biologic scaffold and #8 cell sheet engineering.

control of live cells

[50]

scaffold-free tissue reconstruction with clinical applications in regenerative medicine

[54]

dishes for establishing advanced cell sheet engineering

[56]

engineering and regenerative engineering

[57]

Figure 7 A timeline visualization for T 2000 2011 is shown.

Figure 8 A timeline visualization for T 2000 2014 is shown New developments since 2012 are included in the visualization, notably in association with clusters #5, #8, #11 and #13.