In the era of big science, countries allocate big research and development budgets to large scientific facilities that boost collaboration and research capability. A nuclear fusion device called the “tokamak” is a source of great interest for many countries because it ideally generates sustainable energy expected to solve the energy crisis in the future. Here, to explore the scientific effects of tokamaks, we map a country’s research capability in nuclear fusion research with normalized revealed comparative advantage on five topical clusters—material, plasma, device, diagnostics, and simulation—detected through a dynamic topic model. Our approach captures not only the growth of China, India, and the Republic of Korea but also the decline of Canada, Japan, Sweden, and the Netherlands. Time points of their rise and fall are related to tokamak operation, highlighting the importance of large facilities in big science. The gravity model points out that two countries collaborate less in device, diagnostics, and plasma research if they have comparative advantages in different topics. This relation is a unique feature of nuclear fusion compared to other science fields. Our results can be used and extended when building national policies for big science. Big science is characterized by its big budgets, manpower, and machines. It includes a number of multidisciplinary fields such as nuclear fusion, particle accelerators, and space science . Most ofA large facility is considered the core resource of big science. From construction to operation, it requires participation of various stakeholders under the leadership of national government, resulting in economic spillovers to society –8. A larAmong many aspects of the national research capacity, this study focuses on academic publishing to estimate the capacity quantitatively –22, whicFor a case study, we investigate nuclear fusion, in which the construction of large facilities and international collaborations are crucial. Nuclear fusion is a field that countries have interest in as it produces clean, affordable, and sustainable energy , 27. TheOur approach successfully captures various aspects of nuclear fusion from a bibliographic database over 40 years, 1976–2016. The dynamic topic model disentangles multidisciplinarity and classifies 41 topics grouped into five topical clusters: material, plasma, device, diagnostics, and simulation. Furthermore, the revealed comparative advantage identifies leading countries that participate in international projects or have their own tokamak. The rise and fall of these countries match well with tokamak operation. With the gravity model of scientific collaboration, we additionally address whether complementarity leads to collaboration in nuclear fusion research. The regression results show that countries collaborate less if they have research capability in different topics. It is a unique characteristic of nuclear fusion compared to other sciences in which complementarity enhances collaborations –42. ThisWe analyzed 25,085 nuclear fusion research papers published during 1976-2016. They were collected from the Scopus database (document type: article) and contain the term “tokamak” in the title, abstract, or keyword fields. Papers without affiliation information were manually filled by checking their original documents. When an author had multiple affiliations, we considered the first one as her/his nationality. We used the fractional counting method to obtain the number of papers for each country. For example, if a paper was written by three American and two Korean researchers, 0.6 and 0.4 were assigned to both countries’ paper counts.The fractional counting method gives more weight to leading countries, so that would embrace their inherent academic leadership. Nevertheless, the fractional counting method gives less biased results than the full counting method that assigns an equal weight to all countries in a paper. The full counting method could overrepresent some countries (e.g. the United States) which participate in many international projects. Systemic comparisons of the two methods recommend the fractional counting method in co-authorship analysis , 44, espAmong 75 countries in our dataset, we focused on the top 14 countries that published more than 250 papers in our time scope. The distribution of paper counts was highly skewed. These 14 countries published more than 90% of the research articles. The top 14 countries were the United States, Japan, China, Germany, the United Kingdom, Russia, France, Italy, the Republic of Korea, Switzerland, India, Sweden, Canada, and the Netherlands. The basic statistics of these countries are listed in αt and βt by each year. αt affects the topic distribution of a document, and βt indicates the word distribution in a topic. The DTM infers both parameters to reproduce the empirical word distribution under the assumption that a document is made by both processes in year t, choosing a topic for a document by αt and sampling words in that topic by βt. αt and βt are used as references to estimate αt+1 and βt+1.The dynamic topic model (DTM) conceptualizes the knowledge in nuclear fusion research , 24. TheK needed to be determined before running the DTM. Following the recent approach [K = 41  values were less than 0.01. Then, we used the words that appeared more than 10 times in the whole document. As a result, our dictionary contained 7,851 unique words, and the documents contained 1,619,233 words in total. The number of topics approach , we spec= 41 see . Open socies see .The DTM provides an article’s topic distribution based on the learned parameters. As we set the number of topics to 41, the topic distribution of an article was given as a vector of length 41. Topic distribution was allocated to countries in proportion to their contributions on each article. For instance, if an article was written by American authors only, the topic distribution of the article was fully given to the United States. For another article written by three American and two Korean researchers, 60% of the topic distribution would be added to the United States. In this way, a country’s research capability over 41 topics was estimated for each year from 1976–2016.t when nt papers are published, we have two matrices, the fractional publication counts by countries (At: nt papers × 75 countries) and the topic distributions of papers (Bt: nt papers × 41 topics). t. Based on the five topical clusters that we found . Collaborations were also counted in fractions. We multiplied the country profile of a paper and its transpose to obtain the collaboration matrix. The matrix was distributed over five matrices in proportion to topical cluster weights.The fractional counting method was used for calculating a country’s publication and collaboration counts . For yeawe found , the frai’s research capability on topical cluster j at year t. i on topical cluster j at year t, is calculated asi’s research capability across five topical clusters at year t  , one of m and n on topical cluster j at year t the capability distance cmn,j,t. A high cmn,j,t represents that two countries are in complementary relation where their differences in research capability generate synergy by collaborations.Countries have comparative advantages on different topics as it is almost impossible to be competitive in all topics. We measured how similar two countries’ research capabilities are as follows. First, the NRCA of each country was transformed into the binary vector milarity . We callm and n in topical cluster j at year t, wmn,j,t, is related to the number of publications of the two  and their geographical distance (dmn). The gravity model explains their relationships in many scientific fields [Pm,j,t and Pn,j,t positively and dmn negatively affects wmn,j,t. We added the capability distance to the gravity model for checking whether complementarity increases collaboration. Our basic model is written asdmn is the Haversine distance (km) between capitals. For two countries m and n, we counted wmn,j,t, Pm,j,t, and Pn,j,t in real values, and calculated cmn,j,t from the binary transformed NRCA vectors. A positive λ indicates that complementarity stimulates collaboration.Scientific collaboration between country c fields , 49. Pm,k1 and k2 was obtained by the Jensen-Shannon distance [The DTM detected 41 topics in the dataset. Each topic had its word distribution indicating the extent of word assignments to the topic. We assumed that two topics were close if their word distributions were similar. The topic distance between topic distance , a squarD method . The hieEach cluster is clearly characterized by its topics. We observe the details of each branch from the top of the tree. The “material” cluster is described by tokamak edge plasmas and components as plasmas interact with wall materials at the edge. The “plasma” cluster contains general plasma-related topics , major instabilities in tokamak configurations , and heating methods . The “device” cluster includes mechanical components in tokamaks  and several tokamaks . The “diagnostics” cluster is composed of plasma diagnostics methods such as soft X-ray, neutron detector, and spectroscopy. Finally, the “simulation” cluster focuses on analytic calculations and computations.Normalized revealed comparative advantage (NRCA) on the fractional publication counts extracted national research capability over 40 years . In all Complementarity positively affects collaboration in many science fields –42. ReseIn all topical clusters, as expected, the number of publications had a positive coefficient, and the geographical distance had a negative coefficient. This means that collaborations occur frequently when two countries have high research capability and locate closely. In contrast to our assumption, the capability distance negatively affects collaboration, indicating that countries collaborate less if they have research capabilities in different topics. This tendency is found in three clusters, plasma, device, and diagnostics, with respect to fusion reaction in tokamak facilities. Collaborations on material and simulation are not related to the capability distance. The regression results suggest that complementarity would affect collaborations differently by topics in big science. International collaborations in core knowledge fields happen when two countries mutually benefit based on similar research capability.Large facilities and international collaboration, two core components of big science, were investigated with bibliographic data, the dynamic topic model, and revealed comparative advantage. In this study, we chose nuclear fusion for a case study. Word similarity between topics unfolded the knowledge structure of nuclear fusion comprising five multidisciplinary topical clusters: material, plasma, device, diagnostics, and simulation. Different countries have different comparative advantages over these clusters. The time points that the comparative advantage trend changes match well with tokamak operation. Catching-up countries that have built their own tokamaks have developed their research capability while countries that do not operate a tokamak miss their productivity.Revealed comparative advantage can be used as a new indicator of big science project evaluation. Through time series analysis , we can The international collaboration in nuclear fusion was estimated by the gravity model with the capability distance that represents how similar two countries’ research capabilities are. The regression results show high capability distance distracts the international collaborations in fusion reaction related clusters: plasma, device, and diagnostics. This tendency contrasts with that of other science fields favoring collaborators that have complementary comparative advantages –42. RealOur approach can be applied to other fields of big science. Particle physics and Antarctic science are the potential targets. They depend on large facilities, particle accelerators, and research stations in Antarctica. In particle physics, we expect that the dynamic topic model differentiates various types of particle accelerators . A countS1 Appendix(PDF)Click here for additional data file.S1 FigK = 500 model to calculate the cutoff that specifies sufficiently used topics. The minimum of KDE (blue line) derivative determines the cutoff (red dashed line), and the number of topics above this point, K = 41, is used for the DTM.We used the topic usage distribution for static (TIF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.


Phoma medicaginis var. medicaginis Malbr. & Roum causes large losses to alfalfa. However, till now, little is known about alfalfa-P. medicagnis interactions and the pathogenicity mechanisms of the pathogen. Here, alfalfa inoculated with P. medicaginis was subjected to GC-MS based metabolic profiling. The metabolic response in P. medicaginis-inoculated and mock-inoculated alfalfa leaves was assessed at 2, 4, 6, 8, 12, 16, 20, 24, 26 and 28 days post inoculation. In total, 101 peaks were detected in the control and inoculated groups, from which 70 metabolites were tentatively identified. Using multivariate analysis, 16 significantly regulated compounds, including amino acids, nitrogen-containing compounds and organic acids, polyols, fatty acids, and sugars were tentatively identified . Among these metabolites, the levels of malate, 5-oxoproline, palmitic acid and stearic acid were increased significantly in P. medicaginis-infected alfalfa leaves compared to the controls. In contrast, the levels ofγ-aminobutyric acid and 2-pyrrolidinone were significantly decreased in infected leaves compared to the controls. Further metabolic pathway analysis of the 16 significantly regulated compounds demonstrated that glycolysis, the tricarboxylic acid cycle, and β-oxidation of fatty acids were significantly induced in the alfalfa leaves at later stages of P. medicaginis infection. The strong induction of tricarboxylic acid cycle pathways at later infection stages caused by the pathogen may induce senescence in the alfalfa leaves, leading to plant death. However, intermediate metabolites of these metabolic pathways, and inositol phosphate, glutathione, the metabolic pathways of some amino acids accumulated rapidly and strongly at early stages of infection, which may enhance the ability of alfalfa to resist necrotrophic P. medicaginis disease. Understanding metabolic pathways is essential for understanding pathogenesis.Information on disease process and pathogenicity mechanisms is important for understanding plant disease. Spring black stem and leaf spot caused by the necrotrophic pathogen  Medicago sativa L.) is grown worldwide as a perennial high quality forage [Phoma medicaginis var. medicaginis Malbr. & Roum commonly occurs in China [P. medicaginis decreased the transfer rate and capture efficiency of photosynthetic electrons, the amount of non-photochemical quenching (qN), and the carboxylation efficiency (CE) in alfalfa leaves [P. medicaginis, the fungitoxic phytoalexins, isoflavonoids such as medicarpin, sativan, formononetin 7-O-glucoside, and malonylated formononetin 7-O-glucoside increased in alfalfa leaves infected by P. medicaginis [P. medicaginis on alfalfa, information which is important for the development of novel disease-control strategies and breeding resistant varieties. In this study, we analyzed the expressions of metabolites in P. medicaginis-inoculated and mock-inoculated alfalfa plant leaves using GC-MS. The up- or down-regulated metabolites were further analysed for their metabolism pathways and a complex metabolic network was developed. This complex metabolic network should extend our understanding of the mechanisms controlling P. medicaginis pathogenicity and alfalfa tolerance to this pathogen.Alfalfa  was isolated from alfalfa leaves collected from the field in Gansu province, China. The isolate was cultured on potato dextrose agar (PDA) media at 25 °C without light in an incubator for 3 weeks. A spore suspension was prepared with sterile distilled water, and the number of spores in the suspension was adjusted to 1–1.5×106 spores⋅mL−1 with a hemocytometer [P. medicaginis using an atomizer, and the seedlings were covered with black plastic bags for 48 h to promote infection, then, grown without plastic bags in the greenhouse. Thirty additional pots of seedlings were sprayed with sterile water as healthy controls, and 10 pots of seedlings were retained for positive controls to observe symptoms and disease development. Symptoms were observed after inoculation. All plants were grown under the same conditions. Fully expanded leaves at the same development stage were harvested from the P. medicaginis- or water-inoculated plants at 2, 4, 6, 8, 12, 16, 20, 24, 26 and 28 days post inoculation (dpi). Three pots with six plants each were sampled at each sampling date. The harvested leaves were quickly frozen with liquid nitrogen and stored at -80°C until use.The strain of ytometer . Seeds oytometer  were sow2O  and 75 μL ribitol , which was used as an internal standard. MeOH soluble fractions were dried individually with nitrogen and each sample was gently mixed with 45 μL methoxyamine hydrochloride . The mixtures were incubated at 30 °C for 90 min followed by addition of 45 μL N,O-bis-(trimethylsilyl)-trifluoroacetamide (J&K Scientific Ltd.) to each sample and incubation at 70 °C for 30 min. Each sample was diluted with 90 μL hexane prior to injection as described previously [Leaf samples  were pulverised individually in mortars, and extracted with MeOH: H-1, splitless injection, and mass range at m/z 50–650. Constituents were determined under the following conditions: 80 to 240 °C at 6 °C per min, 240 to 280 °C at 10 °C per min, and 280°C for 10 min. The injection temperature was 270 °C. Three replication for GC-MS.An Agilent 7890A/5975C gas chromatograph-tandem mass spectrometer equipped with an autosampler 7693  was used for GC-MS detection. The detection conditions were as follows: ion source temperature at 230 °C, electron beam at 70 eV, Agilent 19191S-433 column with 30 m × 0.25 mm internal diameter and 0.25 μm film thickness, helium gas flow rate at 1 ml/minCompounds in leaves were tentatively identified with Automated Mass Spectral Deconvolution and Identification System (AMDIS), our in-house mass spectra library and the standard mass spectral database . The signal/noise (S/N) of the tentatively identified compound was higher than 10 in the AMDIS and the compound shared greater than or equal to 80% similarity with the known compounds in the database, indicating that the metabolite identification was reliable ,22.2 value is a prediction error obtained through OPLS-DA analyses, and values greater than or equal to 0.5 are generally considered to have good predictive capability [p value was less than 0.05, this metabolite was considered to be a significantly regulated metabolite compared to the controls [www.metaboanalyst.ca/). The final metabolic network was established according to KEGG (http://www.genome.jp/kegg/) [The amounts of tentatively identified compounds were normalised with the mean value of the internal standard. The normalised data were imported into SIMCA14.1  for further multi-variate statistical analysis, including principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA). The Qpability . To valicontrols . The sigp/kegg/) . A heat Symptoms were observed as small black spots on inoculated leaf blades on the sixth day post inoculation . SubsequIn total, 101 peaks were detected by GC-MS. From the peaks, 70 unique compounds were tentatively identified, including 23 carbohydrates and alcohols, 23 amino acids, 5 nitrogen-containing compounds, 10 organic acids, 5 lipids, 4 other compounds .2X (cum) value of the PCA model is 0.529, as shown in 2 ellipse (2Y(cum) and Q2 values of this model were 1.000 and 0.817, respectively. Validation plots showed R2 and Q2 values from the permuted analysis (bottom left) are lower than the corresponding original R2 and Q2 values (top right), indicating a good fit for the model (The R ellipse . The R2Yhe model .p < 0.05) associated with the pathogen infection were identified using the OPLS-DA model. These metabolites included eight amino acids , one nitrogen-containing compound (2-pyrrolidinone), two organic acids , two polyols , one sugar (sucrose) and two fatty acids   .P. medicaginis-inoculated leaves compared to the mock-inoculated leaves after 6 dpi. In contrast, the level of lysine in the P. medicaginis-inoculated leaves was gradually upregulated 39.1% by 28 dpi.Several amino acids, such as glycine, leucine, isoleucine, methionine and tyrosine, and sucrose, myoinositol and inositol 1, 3, 4, 5, 6-pentakisphosphate were downregulated in the P. medicaginis-inoculated leaves compared with mock-inoculated leaves; for example, the level of 5-oxoproline in the P. medicaginis-inoculated leaves reached a maximum level of 137.9% by 24 dpi, falling to 74.2% by 28 dpi. Malate dramatically increased by 352.4% at 4 dpi. The levels of palmitic acid and stearic acid reached a maximum level of 266.8% and 291.4%, at 28 dpi, respectively.Some compounds showed a dramatic increase in the P. medicaginis-inoculated leaves compared with the mock-inoculated leaves. The levels of GABA (γ-Aminobutyric acid) and 2-pyrrolidinone decreased over time compared with the control groups, and the levels of malonic acid significantly decreased at early infection stages (p<0.05), but increased by 67.2% at 24 dpi and 38.1% at 28 dpi .Some compounds showed a large decrease in the p<0.05). For example, at 28 dpi, pyruvic acid increased 1.69 fold, asparagine increased 1.41 fold, succinate increased 1.90 fold, fumarate increased 1.37 fold, and citrate increased by 2.16 fold compared with the control groups , 2-pyrrolidinone and organic acids , sucrose, alcohols , and fatty acids .As disease progressed, lesions enlarged and coalesced, leaves became yellow, and the levels of 16 metabolites in the infected plants were significantly changed compared to the non-infected plants during P. medicaginis-infected alfalfa leaves decreased compared to the uninfected plants. These amino acids are not only the basic units of protein synthesis, but also enhance defense responses to biotic stresses including strengthening of plant cell walls, regulation of jasmonic acid (JA), and biosynthesis of phytoalexins. [The levels of glycine, isoleucine, leucine and tyrosine in the alexins. –30. ThisP. medicaginis infection, 5-oxoproline levels significantly increased in the inoculated alfalfa leaves in different infection stages, but especially in the later infection (p<0.05). This suggests that the antioxidant system based on the glutathione-mediated detoxification pathway may be induced mostly later in infection. High accumulation of 5-oxoproline may increase plant resistance, and lower levels of the metabolite at early infection stages may help the pathogen colonize the plant. Previous studies showed that antioxidant enzyme activity was induced earlier and to higher levels in the resistant varieties of alfalfa than in the susceptible varieties [As shown in arieties . These rP. medicaginis infection, lysine and its degradation product pipecolic acid were induced later and strongly in infected alfalfa leaves, compared with control leaves, which could be related to alfalfa susceptibility. Pipecolic acid was previously shown to induce systemic acquired resistance (SAR) [Arabidopsis leaves inoculated with the incompatible, HR-inducing Psm avrRpm1 strain than in Arabidopsis leaves infected with the compatible Psm strain, and pipecolic acid accumulated to higher levels during later stages of the compatible interaction [With ce (SAR) . Pipecoleraction . TherefoUstilago maydis and Fusairum graminearum, showed only reduced pathogenicity on plant leaves and were still able to penetrate and colonize host tissues [P. medicaginis infection, methionine levels decreased, which may be related to the assimilation of P. medicaginis. The pathogen may need to acquire sufficient amounts of methionine from alfalfa leaves to support its growth. Inhibiting the use of methionine by the pathogen can increase alfalfa resistance.For some pathogens, they need to assimilate methionine or its derivatives from host tissue to support their growth, which is related to their pathogenicity. For instance, methionine auxotrophic mutants of the pathogens  tissues ,34. UndeP. medicaginis infection, myoinositol and inositol derivatives  were induced early but decreased significantly at later infection stages in the infected leaves (p<0.01), which suggested that ability of alfalfa to resist disease decreased. Conversely, early strong induction of myoinositol and inositol derivatives  may enhance alfalfa resistance. The amounts of myoinositol and inositol derivatives in resistant wheat cultivars (Sumai3) were higher than that in susceptible wheat cultivars (Roblin) [As shown in (Roblin) .p<0.05), and accumulated at later infection stages. Malonic acid metabolism likely provides a carbon source for the survival of microorganisms [P. medicaginis to invade, increasing host susceptibility.In this research, malonic acid decreased in the infected leaves significantly at early infection stages  (As shown in p<0.05) . The decp<0.05)  . Moreovep<0.05) . Asparagion rate . GABA alion rate , 2-Pyrroion rate . These rtosystem . In addiP. medicaginis infection, genes in the octadecanoid pathway were induced significantly and accumulated more rapidly in a resistant M. truncatula accession than in a susceptible M. truncatula accession [P. medicaginis infection stages, suggesting that the induction of β-oxidation in the later infection stages may have provided nutrition for P. medicaginis for invasion and growth, while the rapid accumulation of these two fatty acids at early infection stages may enhance plant resistance to the pathogen infection.Palmitic acid involves fatty acid degradation pathways , the priccession . In our M. truncatula infected by P. medicaginis, they found expression of genes associated with disease resistance was induced to lower levels in a resistant cultivar later in infection than for a susceptible cultivar. Their experiment showed the greatest upregulation in PR10 gene expression, lipoxygenase transcripts and isoflavone 2’-hydroxylase in the octadecanoid pathway from resistant plants earlier and to a higher level [This research was carried out on a susceptible cultivar. We anticipate that a resistant cultivar would induce intermediate metabolites of glycolysis, TCA cycle and β-oxidation metabolism pathways, and inositol phosphate, glutathione, some amino acids metabolic pathways, such as glycine, leucine, isoleucine, tyrosine and lysine, rapidly and strongly at an early infection stage. When Kamphuis and coworkers compared susceptible and resistant cultivars of er level . Our worP. medicaginis infection was presented. In the process of P. medicaginis colonization of the alfalfa leaves, glycolysis, TCA cycle and β-oxidation metabolism pathways in the infected leaves accumulated strongly at later infection stages, which may provide ATP, a N source and nutrition for P. medicaginis to colonize alfalfa leaves. Moreover very strong induction of the TCA cycle pathways by the pathogen at later infection stage may induce senescence in alfalfa leaves, leading to plant death. Intermediates metabolites of these metabolic pathways, and inositol phosphate, glutathione, some amino acids metabolic pathways, such as glycine, leucine, isoleucine, tyrosine and lysine, accumulated rapidly and strongly at an early infection stage may enhance the ability of alfalfa to resist necrotrophic P. medicaginis. The tentatively identified differential metabolites and related pathways may serve as potential markers for developing novel disease-control strategies and breeding resistant varieties.A detailed primary metabolic profile of the response of alfalfa leaves to S1 TableRelevant pathways based on MetaboAnalyst 4.0 analysis.(DOCX)Click here for additional data file.S2 TableAmount of individual metabolite normalised to internal standard is shown.(XLSX)Click here for additional data file.


The literature of social class and inequality is not only diverse and rich in sight, but also complex and fragmented in structure. This article seeks to map the topic landscape of the field and identify salient development trajectories over time. We apply the Latent Dirichlet Allocation topic modeling technique to extract 25 distinct topics from 14,038 SSCI articles published between 1956 to 2017. We classified three topics as “hot”, eight as “stable” and 14 as “cold”, based on each topic’s idiosyncratic temporal trajectory. We also listed the three most cited references and the three most popular journal outlets per topic. Our research suggests that future effort may be devoted to Topics “urban inequalities, corporate social responsibility and public policy in connected capitalism”, “education and social inequality”, “community health intervention and social inequality in multicultural contexts” and “income inequality, labor market reform and industrial relations”. Social stratification or social class refers to visible societal layers or classes of differing wealth, income, race, education or power . Social Social scientists have studied social class and inequality at length. In the 19th century, Marxian theories of stratification  considerBased on classic social theories, many studies have empirically examined the determinants and consequences of social class and inequality. Multidisciplinary knowledge in the field is not only diverse and insightful, but also fragmented and multifaceted. There is a pressing need for clear mapping of this ever more complex landscape to help researchers and students to conduct efficient, effective literature reviews. A comprehensive mapping of the field will help by providing an understanding of how it has evolved over time, shedding light on the points of consensus and divergences among scholars, while revealing research gaps in the intellectual structure of the field.This study comprises a computer-based overview of the social class and inequality literature over the period of 1956–2017. First, we mapped out the topic landscape, and then attempted to anticipate hot topics that will generate seminal research in the future. As far as we know, this is the first systematic review of the field across many disciplines over seven decades and the first attempt to forecast topic prevalence in this literature. Our first contribution lies in uncovering a hidden structure of 25 distinct topics and development trajectories in a corpus comprising the abstracts of 14,038 scholarly articles. This study draws on an unprecedentedly large text corpus that includes a broad range of author backgrounds, disciplinary influences and research focuses. Our study will enable researchers to explore not only topic development paths within the overall literature, but also the most salient articles in each individual topic. Our second contribution lies in forecasting the popularities of these 25 topics, based on each topic’s temporal idiosyncrasies which will help both researchers and journal editors to select promising research topics. In the next section, we briefly introduce topic modeling techniques and applications in modeling scientific literature. Then we describe our analyses and results. And finally, we discuss the implications of our work for scholars, journal editors, and practitioners.A document can be represented as a vector of word term weights (i.e. features) from a set of terms (i.e. dictionary) and the topic of a document is made of a joint membership of terms which have a pattern of occurrence . Early dBacked by Bayesian statistics, Latent Dirichlet Allocation (LDA) is developed to apply a probabilistic model to analyze word distributions in text documents and uncover topics in an automated fashion ,11. ThisRecently, some LDA-based techniques have been proposed. For example, Correlated-Topic-Model (CTM) uses a logistic normal distribution to create relations among topics . SuperviLDA has been widely used to process otherwise unmanageably large volumes of text, identify the most salient topic in a single document, investigate similarities between documents, and uncover topic prevalence over time ,13,17. WWe extracted article abstracts from the core collection of the Web of Science (WoS) database using the following criteria: articles published in English, whose topic terms  included “social stratification(s)”, “social class(es)” or “social inequality(ies)” in SSCI indexed journals over the period of 1956 to December 2017. The search found 15,057 articles. We deleted those without keywords and abstracts, leaving 14,038 articles in the collection. Among these articles, 67.11% belong to “social class(es)” alone, 23.60% to “social inequality(ies)” alone and 6.71% to “social stratification(s)” alone. There are 1.74% of articles that belong to both “social class(es)” and “social inequality(ies)”; 0.52% to “social class(es)” and “social stratification(s)”; and 0.26% to both “social inequality(ies)” and “social stratification(s)”. There are only 0.04% of articles that belong to three topic terms.In addition, we built three time series in terms of annual article counts for these three terms respectively. The correlation coefficients between “social class(es)” and “social inequality(ies)” series is 0.87, between “social class(es)” and “social stratification(s)” series is 0.86, and between “social inequality(ies)” and “social stratification(s)” series is 0.97. These statistics confirm that the three topic themes are highly similar. They all reflect the types of social divisions envisaged by Marx and refer to groups defined by their relationship to ownership and control over the means of production, of labor and of distribution . We did The authors of these articles are from 128 countries, especially USA (36.69%), UK (25.64%) and Canada (5.96%). The ten most frequent organizations in the sample are University College London (2.89%), Harvard University (2.05%), University of Michigan (1.91%), University of Helsinki (1.79%), University of Edinburgh (1.55%), University of Bristol (1.44%), University of Toronto (1.33%), Karolinska Institute (1.29%), University of Cambridge (1.28%), and University of Copenhagen (1.22%).Social Science Medicine, Journal of Epidemiology and Community Health, and European Journal of Public Health are the three most frequent outlets in the field  when k was 33. Given that it is unlikely to categorize a large collection of articles like ours into just three topics, we decided the optimal number of topics of the first-stage grid search procedure as kfirst-stage = 33. Then we conducted the second-stage grid search procedure by computing a model set of kfirst-stage +/- 10 in step of one . The second stage procedure suggests that the topic coherence score reaches its maximum when the number of topics is 25. Then, we used Latent Semantic Analysis (LSA) to re-do the two-stage grid-search procedure for the sake of robustness check. The topic coherence scores of LSA were also shown in We conducted LDA topic modeling analysis with the Genism package . The firWe assessed topic modeling quality in the following ways. Firstly, we plotted the distances of 25 topics in Then, we computed the likelihood of each article covering each of the 25 topics with LDA. Note that LDA is a mix-membership model, which means that each document is represented as a mixture of a set of topics and each topic is regarded as a distribution over the words in the vocabulary . We assiFinally, we evaluated the level of topic diversity with the Herfindahl-Hirschman Index (HHI), which has been used in a commonly accepted measure of market or portfolio diversification. As a rule of thumb, a market with an HHI of less than 0.10 is a competitive or diverse marketplace, an HHI of 0.10 to 0.25 is a moderately concentrated marketplace, and an HHI of 0.25 or greater is a highly concentrated or monopolistic marketplace . AnalogiWe manually labeled each topic in the following manner. Firstly, we downloaded the full texts of the 20 articles whose loadings were the highest within each topic and invited 50 graduate students to read them carefully. That is, each student read 20 randomly-chosen articles and each article was read by two students. Each student proposed a preliminary label for each topic. At the same time, the author team read the abstracts of the 50 highest loading articles per topic. Finally, the author team organized several workshops with the students to finalize the labels. For 21 of the 25 topics, the students suggested labels that were identical or highly similar to those generated by the author team. We discussed the four topics for which the labels assigned by the students and the author team differed significantly to reach a consensus on the most appropriate topic labels.The number of articles per topic ranges from 252 to 1,172 . The three most prevalent topics are “globalization, modernization and social class evolution” (Topic 5), “education and social inequality” (Topic 9) and “urban inequality, corporate social responsibility and public policy in connected capitalism” (Topic 22), each of which contains more than 1,000 articles. The three least prevalent topics are “preventive health inequality” (Topic 4), “criminal justice, terrorism, lifestyle exposure and victimization in different social classes” (Topic 10), and “sociolinguistics and social inequality” (Topic 15), each of which contains fewer than or around 300 articles. In addition, “urban inequality, corporate social responsibility and public policy in connected capitalism” (Topics 22), “mortality and social inequality” (Topic 13), and “cancer and social inequality” (Topic 8) exhibit the three highest average loadings (>0.42), indicating that the articles covering these topics tend to be more similar than those covering relatively low-loading ones, for example, “social class schema and theoretical debates” , “discrimination, social value, and gender and racial inequality”  and “pathways of social inequality and psychosocial health” .Social Science & Medicine is one of Top 3 outlets in 16 topics, Journal of Epidemiology and Community Health in 10 topics, and American Journal of Public Health in five topics.Finally, we listed the three most cited references and the three most frequent outlets per topic in Tables Given that the field in general has experienced substantial growth after 1991, we discussed the temporal dynamics of each topic in two periods (i.e. 1956–1990 and 1991–2017). We constructed 26 time series , “childhood social class and adulthood health” (Topic 21), and “preventive health inequality” (Topic 4), did not appear in the 1950s and 1960s. It was not until the 1990s that all 25 topics were present. “Social class schema and theoretical debates” (Topic 3) was prevalent in 1960s and 1970s but suddenly becomes much less popular in the following decades.Then, we intended to identify the trends in the filed as a whole and in each topic using time series forecasting technique. We did not follow conventional trend analysis to employ linear and quadratic time trend regressions for the series of article counts. That is because, on the one hand, article count series usually exhibits strong autocorrelation, which manifests in correlated residuals after a regression model has been fit. The autocorrelation violates the standard assumption of independent errors . On the We constructed 26 time series and identified the appropriate ARIMA terms following the conventional Box-Jenkins Methodology :d parameter) for the training series. Secondly, we specified the number of AR order with the partial autocorrelation function (PACF) plot for the training series. The PACF displays the autocorrelation of each lag of a series after controlling for the auto correlation caused by all preceding lags [p lags, then an ARIMA model should include p autoregressive terms as the previous p-values are responsible for the autocorrelation in the series [q lags and then drops toward zero, then an ARIMA model should include q MA terms [p, d, q) to the training series. To verify the quality of this model, we plotted its residual to see whether it appears as entirely random white noise and conducted the Ljung-Box test to formally check whether the errors are uncorrelated across many lags [Firstly, we split a series into a training part  and a test part . We used the Augmented Dickey–Fuller test to identify the appropriate order of differencing . By comparing these models with the manually specified optimal model in terms of the Ljung-Box test of residuals, AIC and BIC, the ARIMA grid-search results confirm that our order specifications were indeed optimal . Results were summarized in To check the robustness of our ARIMA order specifications, we conducted a grid-search by estimating 1,125 ARIMA models with different combinations of orders , stable topics for those whose rates are positive or equal to zero but smaller than the one of the field, and cold topics for those whose rates are negative. There are three hot topics, eight stable topics and 14 cold topics. We discussed these findings in the next section.We employed the optimized ARIMA models to forecast the publication percentages of the field and of each topic for the next ten years (i.e. 2018–2027) respectively. The forecast average annual growth rate was used as the indicator of future topic prevalence see . The fieThe aim of this study is to provide a systematic review of social class and inequality research over the last seven decades: its evolution, topic landscape, and dynamics. Our topic modelling analyses considerably enhance understanding of the hidden structure of 25 distinct topics covering the overall development in the field. In addition, our analysis of topic dynamics reveals the highly fluctuated nature of the field’s content structure. Our forecasting results suggest that while in general, the field will continue to attract more attention, 14 topics may lose their popularities. In particular, “skeletal, dental and cranial anthropology and social stratification throughout history” (Topic 2) will dramatically shrink -241.18%, followed by “sociolinguistic research and social inequality  and “preventive health inequality” . These findings seem to be reasonable, given that the three topics are not mainstream in the field, all of which took up less than 2.5% of the articles respectively.In addition, the 25 topics can be roughly divided into two categories. The 15 medicine-related research topics dominate the field, comprising 54.86% of the articles. This is not surprising, given that healthcare, the sociology of illness, and the social organization of medicine are among the fastest growing areas of modern research. Studies in these topics use core principles and concepts of medical sociology to elucidate the determinants and consequences of various types of illness and wellness . These articles have extensively examined the socioeconomic risk factors of health and their iatrogenic repercussions. Such research contributes to the field of social class and inequality by exploring the social meaning of illness, by examining the issue of care-taking as well as care-giving actions related to familial, community and governmental responsibilities, and by deconstructing health inequalities grounded in social stratifications. Our research suggests that in general, the research in these topics has substantially grown and matured, because that the forecast annual growth rates of many medicine-related research topics are either negative or close to zero. That is probably because many studies have reached a consensus that the problems of access to health care, inequality in medical coverage, and the influence of oppressive social structures make ‘health’ impossible for many people confined in an unfavorable class position . Future The second category of work in our collection is social sciences-oriented, focusing on topics related to education inequality, social structure evolution, the impact of globalization, business development and public policies. There may be research gaps in “education and social inequality”  and “income inequality, labor market reform and industrial relations” . Growing inequality is regarded as one of the most important developments in today’s industrial relations. This phenomenon has been most pronounced in the West, where rising support for populism has disrupted politics and challenged corporate capitalism in many countries . Future In conclusion, this study applies LDA topic modelling to structure a large text corpus effectively. By doing so, we enable researchers to examine the detailed profile of each topic and estimate its relative salience. By describing the whole body of knowledge at a relatively granular level, we contribute to a rich understanding of the field’s topic landscape. As such, researchers can appreciate the full range of topics and select those they wish to examine in depth. In addition, our topic landscape informs social class and inequality teaching and course design. Instructors can identify important topics to cover in a course, and include relevant articles associated with each topic. Our study also helps postgraduate students and junior researchers identify which research topics to examine. Finally, our findings have many meaningful implications for journal editors. They can compare the field’s current topic landscape against their journal’s editorial priorities, and thus choose promising topics to be reflected in the composition of the editorial board or promoted through special issues.However, our study may be of some limitations. Our sample articles were collected from WoS. Although it is probably the single most authoritative source for “high-impact” publications and has a relatively better coverage of social sciences and arts/humanities than other academic databases, WoS focuses mainly mainstream journals and articles, especially those in English. As a result, our analyses excluded articles published in emerging journals, in non-English languages and other types of publications . Future studies may collect publication records from Google Scholar, as it covers book contents along with other freely-accessible online publications. In addition, we did not take the correlations between topics into account so that we cannot forecast how the values of one topic will be correlated with those of other topics. Future work may employ multivariate time series methods to capture the associations between topic time series. Finally, we did not specify forecasting models with any external bibliometric factors that may correlate with the growth or decline of a topic time series. Future work should investigate bibliometric determinants of topic dynamics.S1 Fig(PDF)Click here for additional data file.


Antimicrobial resistance (AMR) is one of the latest issues to galvanise political and financial investment as an emerging global health threat. This paper explores the construction of AMR as a problem, following three lines of analysis. First, an examination of some of the ways in which AMR has become an object for action—through defining, counting and projecting it. Following Lakoff’s work on emerging infectious diseases, the paper illustrates that while an ‘actuarial’ approach to AMR may be challenging to stabilise due to definitional and logistical issues, it has been successfully stabilised through a ‘sentinel’ approach that emphasises the threat of AMR. Second, the paper draws out a contrast between the way AMR is formulated in terms of a problem of connectedness—a ‘One Health’ issue—and the frequent solutions to AMR being focused on individual behaviour. The paper suggests that AMR presents an opportunity to take seriously connections, scale and systems but that this effort is undermined by the prevailing tendency to reduce health issues to matters for individual responsibility. Third, the paper takes AMR as a moment of infrastructural inversion (Bowker and Star) when antimicrobials and the work they do are rendered more visible. This leads to the proposal of antibiotics as infrastructure—part of the woodwork that we take for granted, and entangled with our ways of doing life, in particular modern life. These explorations render visible the ways social, economic and political frames continue to define AMR and how it may be acted upon, which opens up possibilities for reconfiguring AMR research and action. AMR might usefully be considered such an object of discursive formation, contingent upon relations ‘between institutions, economic and social processes, behavioural patterns, systems of norms, techniques, types of classification, modes of characterisation’ (p. 45). To trace AMR in this way then develops analysis that understands it as an object that emerges in relation to particular rationalities, juxtaposed with other objects that define its difference.Recognising the global nature of the AMR discourse, the numerous institutions, connections and imperatives can be considered to comprise a ‘global assemblage’, hanging together under the umbrella of AMR  as it has emerged in relation to particular priorities and formulations of science and policy. First, I focus on the challenges of stabilising AMR as an object through traditional definitions and counting, and explore the way that projection of AMR as a threat seems to have been more effective for stabilising this object. Second, I juxtapose two core features of the AMR risk discourse—the One Health paradigm, and the behavioural model of intervention—drawing attention to a paradox in AMR as a problem of connectedness to be solved by individualised action. Third, I develop an account of AMR that conceives of antibiotics as infrastructure, opening-up alternative paths for exploring this emergent field.The analysis draws from a range of material that includes published scientific and policy literature, scientific conference presentations and interviews and discussions with scientists and policy makers. The analysis is informed by my own immersion in the field of AMR science and policy, as a researcher and as co-Director of the AMR Centre at the London School of Hygiene & Tropical Medicine.Ethical approval for the fieldwork in this study was granted by the LSHTM Observational Ethics Committee, reference numbers 11598 and 15244.‘There is a gesture often used to describe the antimicrobial resistance (AMR) problem—an inflection of the hand tracing a curve like the up-side of a mountain. At a meeting of scientists, a journalist asks, ‘How afraid should we be of AMR?’. This gesture provides the answer. At an AMR policy event, a civil servant is making the case for investment in AMR, he makes the gesture. I ask a medical doctor in a low-income country, ‘what is your experience of AMR where you practice?’. The same gesture. I see it repeating in settings of science, policy and practice around the globe. I can’t find the curve drawn out in the scientific literature, but we have a shared understanding that this is the shape of the curve. The gesture stands in place of data, communicating the need for response. It mirrors the ‘hockey stick curve’ deployed in the 2014–2015 Ebola response Kelly, , impliciFieldnotesLondon 15 and East Africa 12, 2018Lakoff , 2017 prHere I will explore the way that the actuarial approach to AMR continues to be a strong part of AMR research and implementation agendas—to come to know where AMR is, how much there is and points for control—but that the definitional and technical challenges inherent to this complex category mean that this is challenging to stabilise as an object through this lens. By applying the logic of the sentinel, or speculative, device, it becomes possible to see how AMR has become stabilised on the global stage as a threat, and rendered amenable to particular forms of action—and investment.Histories of AMR identify waves of political enthusiasm in the topic. The troughs between the waves have been attributed to complacency . They argue that ‘rather than see expenditure on antimicrobial policies as a cost, we should think of it as an insurance policy against a catastrophe; albeit one which we hope will never happen’ (ibid. p. 2). Thus, the criteria for economic costing was widened considerably, although also with considerable uncertainty. When the O’Neill report authors commissioned teams from KPMG and RAND Europe to calculate worldwide estimates of the impact of AMR, they followed the principles of this model, resulting in projections of cumulative cost to global economic output of 100 trillion USD by 2050 if no action is taken (O’Neill, As well as the threat of AMR forming a biopolitical project through looming health crisis, an area that has been particularly developed as a threat in AMR compared with other pandemics is the impact on economies. Foregrounded here are the potential economic costs of AMR to health and healthcare in given future scenarios. While earlier economic forecasts found the additional costs associated with AMR compared with susceptible infections to be relatively small (Smith and Coast, O’Neill, . FollowiO’Neill, . This rhO’Neill, .investment into countries to support malaria control (Eckl, The emphasis on investment in health issues on a global scale is not new or unique to AMR. It is an emphasis that has shifted the shape of international health efforts since Rockefeller applied his business models to his Foundation, most notably in the ol Eckl, . Howeverol Eckl, , p. 52. ol Eckl, , fluentlThe language of a ‘sentinel’ approach also reminds us of the securitised nature of the AMR phenomenon. The projections of and preparedness for threats stand to protect publics from danger Caduff, . This daagainst AMR can be read as much as a fight for modernity.Finally, it can already be observed that AMR is understood as a threat not only to health, to economies, to security, but also to modernity itself. Statements that AMR could hail the end of modern medicine echo through the media, and are common in speeches at both policy and research events. For example, at the UK House of Commons Enquiry into AMR, the Chief Medical Officer warned that ‘We will lose modern medicine’, the ability to undertake major surgery, cancer treatment and transplants, ‘There will be a lot of suffering and modern medicine will be lost’ (House of Commons, Therefore, when AMR is presented as one of the most pressing global threats—articulated in terms of a threat to health, economies, security and modernity—we see bound together a classic biopolitical phenomenon in a neoliberal framework. So that despite the ambiguity of the AMR concept, and our lack of ‘actuarial’ knowledge of its current scale or future impact, an imperative to act on AMR has become clear. Just as we saw with the spectre of avian influenza Davis, , the com‘People need to be brought on-board, so we are together in the one health approach’ I hear from an East African civil servant, ‘but implementation is a challenge with irrational use of drugs by villagers’. The rhetoric of a One Health approach, accompanied by frustration at human behaviour, echoes many conversations and consultations I’ve engaged in with experts and policy makers about the intractability of the AMR problem. What is the relationship between these two conceptualisations?FieldnotesEast Africa 18, 2018In the previous section we have seen that AMR has been stabilised as an object in the form of a threat, and that this has been important for galvanising support—‘Why we need to act now: We cannot afford to return to a pre-antibiotic era’ (Tripartite Collaboration on AMR, Today, addressing AMR is often described as requiring a ‘One Health’ approach—typically defined as ‘multisectoral’ (World Health Organisation, The One Health approach to AMR also promotes interdisciplinary collaboration (European Commission, A One Health approach to AMR often also incorporates ‘One World’, reflecting the global nature of the problem with connections through food systems and human travel (Robinson et al., While the One Health approach to AMR mainly focuses on drawing attention to interconnectedness between domains—whether sectoral, disciplinary or countries—it also has allowed for analyses of reasons for the emergence of AMR, drawing attention to the ways we connect with each other and with nature. The relationships between antimicrobial use and resistance remain mysterious, with analyses suggesting a weak link for some drug-bug combinations at both a macro and micro level (Collignon et al., Keep Antibiotics Working campaign specifically ‘focuses on the personal risks of antibiotic resistance’ in an attempt to reduce demand for antibiotic prescriptions from doctors (Public Health England, Given this rhetoric of AMR as a One Health issue, advocating for recognition of complexity and connectedness that requires a multi-sectoral response, it is curious then to observe that the behaviour change of individuals is so frequently cited as a key solution to AMR. For example, Public Health England’s Current interventions for reducing antimicrobial use revolve around raising awareness and what is now widely referred to as ‘stewardship’. Campaigns and programmes orientate around individuals realising their responsibility to prevent a future tragedy that may occur due to their unnecessary use of antimicrobials today. Thus, materials are often designed to communicate risk, linking the future to actions today. For example, ‘Misuse of Antibiotics puts us all at risk’ Fig. . And matUnderlying these behaviour change models—both in the antimicrobial stewardship and hygiene domains—is the assumption that action is instigated by cognitive or habitual functions of individuals. Moreover, it is often assumed that existing practices are rooted in erroneous beliefs or problematic culture that require intervention Haddad, . The focThus, while a review on country AMR progress by the WHO  notes ‘TThere is a recipe for the rapid growth of pig and chicken farming in Uganda: smaller spaces, larger imported breeds, intensive cleaning, imported feed concentrates, and antibiotics. ‘I use a lot of medicines, including antibiotics', explains a middle-aged gentleman who like many others is new to farming, having left employment in the civil service. ‘If I do not, then I cannot make a profit'. He and his fellow farmers describe how the recent push to commercial rather than subsistence farming reflects a number of societal shifts. There is liberalisation, which they say means that they as members of the population now shoulder greater risks—and potential rewards—with commercialised farming models. Then there is modernisation, which they explain increases demand for eggs, chicken and pork, ‘so there is a push to enhance how much your chicken can produce'. Then there is standardisation, whereby a particular sized chicken is given a set price on the market, and if you can produce it in 4 rather than 6 weeks then you can get an edge on balancing your books. In each case, we learn that antibiotics play an important but often invisible role.FieldnotesEast Africa 152, 2018Zauberkugel (Ehrlich, German scientist and Nobel laureate Paul Ehrlich used the term Ehrlich, , or ‘magEhrlich, . AntimicEhrlich, . Along wEhrlich, . HoweverThe present moment of antimicrobial resistance as a major topic of global concern can be understood to represent a moment of inversion—when antimicrobials have been rendered visible where previously they have been a part of the woodwork. In their work on classification systems as infrastructure, Bowker and Star  observe There are numerous ways in which one might productively explore this inversion of infrastructure presented by AMR. Here I propose that analyses of antimicrobials as material, affective and political infrastructures is valuable to an effort of rendering visible the work of these medicines.replaced or reshaped the material infrastructure in maintaining disease control has been less directly studied. Robert Bud draws our attention to the dramatic increase in the number of beds on British medical wards with the founding of the National Health Service in the mid twentieth Century, when ‘the threats of cross-infection created by this increased turnover were again managed by antibiotics’ (Bud, What does the threat of antimicrobial resistance draw our attention to in the material infrastructural arrangements of domestic, health and industrial settings? Historical work has highlighted the role of hygiene and sanitation infrastructure in bringing about infection control Illich, , on the cs’ Bud, , p. 197.cs’ Bud,  suggestscs’ Bud, . Attentipresenteeism amongst health care workers which propogates disease in hospital environments, caused by sick leave policies and the value placed on ‘selfless-acts’ of continuing to work whilst ill (Chow and Mermel, Bringing to the fore antibiotics as affective infrastructure allows for analyses of the ways in which these substances enable and define relations—between people, organisations, countries and so on. One of the most obvious relations that AMR has brought to the fore is that of patients and prescribers—allowing us to see how these medicines have themselves become a form of care, such that in the absence of one medicine, providers often feel compelled to prescribe another (Chandler et al., The exploration of the roles of antibiotics as affective infrastructure also opens-up for analysis the ways they make possible particular political-economic values in the context and drivers of urbanisation and globalisation. They enable, for example, the revisiting of medicalisation—the encroachment of biomedicine into areas hitherto conceived as outside of the medical domain. The process of medicalisation can be understood to have been shaped by values and social policy established in the Enlightenment period of 17th–18th Century, principally ‘faith in the progress and perfectibility of society with the help of science and technology’ Risse, , p. 150.In this paper I have drawn attention to the framing of AMR discourse and its consequences. I have argued that AMR has been less easy to advocate for with an ‘actuarial’ approach and instead support has been galvanised in its formulation as a threat, through a ‘sentinel’ approach (following Lakoff,


We report the novel application of Analytical Ultracentrifugation (AUCF) to characterise the polymeric proanthocyanidin fraction of hops. Extraction of hop samples with 70% acetone (aq) followed by a C-18 Solid Phase Extraction yielded polyphenolic fractions for AUCF analysis. Sedimentation velocity experiments demonstrated the presence of discrete molecular weight bands of proanthocyanidins, as opposed to a continuous distribution of molecular weights. There were 4 such bands for Saaz hop  and 3 bands for Magnum . The method resulted in a reproducible size (sedimentation coefficient) distribution for replicate runs of the same extract and for extracts prepared from different samples of the same hop variety. Sedimentation equilibrium experiments were then used to fit molecular weight distributions using the new SEDFIT-MSTAR method for the same samples. Thus we report for the first time polymeric proanthocyanidins in hops with molecular weights of up to 100 kDa in Saaz hop (or up to 56 kDa in Magnum). This represents the first application of AUCF to characterise complex fractions of polyphenolics extracted from botanical sources and the methodology developed should find wider application in the study of this diverse and bioactive class of compounds. Amongst the polyphenols, proanthocyanidins, , are often associated with these benefits2.Polyphenolic molecules are broadly distributed across the plant kingdom and thus represent an important part of the human diet. Recent studies have demonstrated their beneficial impact on some health conditions, such as urinary tract infections and cystitis3.Proanthocyanidins belong to the flavonoid group, and are polymeric chains of flavanols, mostly composed of catechin or epi-catechin subunits. They are present in a wide range of fruits, vegetables and berries, and their molecular size range varies from dimers to larger polymeric molecules upwards of 15 kDa. For example, the average degree of polymerisation (DP) of proanthocyanidins in chokeberries has been reported to be 50 monomeric units4. This fining activity is linked to the proanthocyanadin content of extracts, as indicated by the acid butanol assay for condensed tannins5. In an attempt to characterise the molecular size of the proanthocyanidins fractions extracted from hops, Linforth et al.4 used a series of molecular weight cut-off spin filters to fractionate extracts. This indicated the presence of molecules greater in size than 30 kDa . However, spin filter fractionation is only a crude method for size characterisation and clearly lacks resolution. Tanaka et al.,6 likewise reported large amounts of highly oligomeric (>20-mer) proanthocyanidins in their hop bract extract. The oligomers were separated using High-Speed Counter-Current Chromatography (HSCCC) fractionation following ultrafiltration (cut-off >3 kDa). Structural studies using 1H and 13C NMR indicated that the proanthocyanidins were of the B-type, with flavan-3-ol units that are linked through C-4 to C-8 (or C-6) interflavan bonds.Polyphenolic fractions extracted from hops have been shown to flocculate yeast and proteins in green beer, and can thus be used to aid beer clarification7. Small polymers, up to the tetramer (DP = 4), are easily fractionated by chromatography6 and analysed by MALDI-TOF8. However, the analysis of large proanthocyanidins (DP >20) by MALDI-TOF is challenging. Monagas et al.8 commented that MALDI-TOF-MS is not well-suited to the analysis of highly polydisperse proanthocyanidins, due to the generation of multiply charged ions which makes spectral interpretation difficult. Furthermore they concluded that high molecular weight polymers were challenging with regard to suppression of ionisation, reduction of desorption and in-source fragmentation to form non-covalent ion clusters. More recent analytical developments have focused on characterising the linkage structure of proanthocyanidins using UHPLC-MS based methodologies10. Furthermore, Longo and co-workers have demonstrated the presence of novel cyclic B-type hexameric proanthocyanidins in red wine using Isotopic Exchange HPLC-HRMS/MS11.The analysis of proanthocyanidins presents characterisation challenges, particularly when it comes to the larger polymers12. Hence there is a need for improved methodology for the analysis of large proanthocyanidin polymers, particularly those species with DP >4. Improved analytical methodologies will help to increase our understanding of the biological roles of these complex compounds13.Chromatographic methods are limited in terms of accurate analysis of molecular weight due to the absence of appropriate calibration standards15. The principle of this technique is to use a high centrifuge velocity in order to move compounds within a solution through a cell. This transport and the signals acquired are dependent on molecular weights and to a lesser extent molecular conformation. The molecular weight of polymers can thus be estimated from hydrodynamic principles, independently of the need for accurate mass calibration standards. Furthermore, the inherent separation and analysis capability of AUCF – without the need for a separation matrix (column or membrane), and its absolute nature makes it extremely promising for characterising complex systems like polyphenols. This technique is usually applied to the characterisation of purified macromolecules or simple polymer mixtures16 and the present study represents the first attempt to apply this technique to analyse complex mixtures of polyphenolics such as are present in fractions extracted from plant materials, taking advantage of recent advances in analysis software such as the SEDFIT-MSTAR procedure of Schuck, Harding and co-workers17.Here we present the development of a novel analytical technique for the characterisation of high molecular weight proanthocyanidins using Analytical Ultracentrifugation (AUCF) to characterise the molecular composition of polyphenolic hop extracts. AUCF is a hydrodynamic method which enables the real-time monitoring of macromolecules in solutionTwo hop varieties  were purchased from the Hop Shop , as whole dried cones. Two further samples of Saaz hop were kindly supplied by Barth Innovations Ltd. , as pellet and whole dried cones (Saaz 2).Beers for fining assays were prepared using Young’s Harvest Pilsner Lager home-brew kit, together with dried light malt extract , and granulated sugar . Fermentation was with Nottingham ale yeast .Acetone, ethyl acetate, methanol, hydrochloric acid, n-butanol, ferric ammonium sulfate were purchased from Sigma Aldrich . Milli-Q water (>18 MΩ/cm) was used in the solid phase extraction (SPE) fractionation method.The hops were milled using a Perten 3600 lab mill . Hop powder (10 g) was then mixed with 100 mL of acetone/water , on a Thermo Denley Spiramix roller-board  for 15 min, and subsequently filtered through Whatman No1 filter paper. The acetone was evaporated using a Buchi R-II rotary evaporator  at 45 °C. The extract was then chilled overnight at 4 °C, before centrifugation at 4000 rpm using a Thermo Jouan CR3i centrifuge  for 10 min and the residue discarded.4(SO4)2 ·12 H2O) was prepared by adding 1 g of ferric ammonium sulfate into 50 mL of 2 N HCl. For each assay, acid butanol reagent (3 mL) was combined with 25 µL of the hop extract sample and 100 µL of the iron reagent solution in a screw-capped glass tube. Tubes were heated at 90 °C for 30 min. Once cooled, absorbance was measured at 550 nm using a Genesys 10S Vis spectrophotometer . Readings were corrected by subtracting the absorbance of a blank containing only extraction solvent, acid butanol and ferric ammonium sulfate in the same proportions as used in the assay.Acid butanol solution was prepared from 95 mL of n-butanol with the addition of 5 mL of concentrated HCl. 2% ferric ammonium sulfate (FeNHGreen beer for fining was made in 25 L polypropylene fermentation bins using one can of the Young’s Pilsner home brew beer kit. The can contents were dissolved in four litres of boiling water. Granulated sugar (500 g) and dried malt extract (500 g) were added before the mix was made up to 23 L with cold water prior to yeast addition. Beer was used for fining experiments after a minimum of 6 days of fermentation at 20 °C.Once the beer had been racked and chilled to 4 °C, 500 mL of beer was filled into a 600 mL beaker. Hop extract (4 mL/L) was introduced into each beaker and the contents mixed using a Yellow line IKA OST20 overhead paddle stirrer at 500 rpm for 30 sec. After mixing, the beaker contents were transferred to individual 1 L polycarbonate graduated Imhoff cones . Sediment depth was recorded 2 h and 24 h post-fining. Beer haze (25° and 90° scatter) was measured using a turbidity meter  at 4 °C 24 h post-fining and after centrifuging samples at 500 rpm for 15 min to remove residual yeast.et al.18.Hop extracts, prepared as described above, were fractionated using Sep-Pak C18 Vac 6 cc solid-phase extraction cartridges . The cartridges were equilibrated with methanol and then conditioned with deonised water. Hop extract (5 mL) was then loaded onto the cartridge and washed twice with water (2 × 10 mL) and twice with ethyl acetate (2 × 10 mL). The sample was then eluted with 5 mL of methanol. This procedure was based on the methodology of Sun Sedimentation velocity experiments were performed using an Optima XL-I analytical ultracentrifuge  employing Rayleigh interference optics. Methanolic fractions of the hop extract at either 6, 10, 12 or 24-fold dilution  were injected into the 12 mm double sector titanium cells with sapphire windows. The 6-fold dilution was run twice in every AUCF experiment. The cells were loaded into the rotor which was spun at 45000 rpm (20.0 °C). Scans were taken at 5 min intervals for an acquisition of 200 scans minimum for each cell.17.Sedimentation equilibrium experiments were performed using the Beckman  Optima XL-I analytical ultracentrifuge and the Rayleigh interference system. Double-sector titanium cells of 20.0 mm optical path length with sapphire windows were filled with 140 µl of hop extract at 40-fold dilution (sample sector) and 140 µL of reference solvent (methanol) in the reference sector cell. Experiments were performed starting with a low centrifuge speed of 20000 rpm before moving to higher speeds. Once equilibrium was reached at each speed the rotational speed was increased by increments of 5000 rpm, up to a maximum of 40000 rpm for the final scans. Scans were taken every hour, until the equilibrium state at a given speed was reached . Samples were analysed at a low concentration (40-fold diluted in methanol) to reduce non-ideality effects19 using the c(s) processing20 and expressed using the sedimentation coefficient distribution c(s) vs s where s is the sedimentation coefficient in Svedberg units (S = 10−13 sec). The sedimentation coefficient distribution is a measure of the size distribution but is influenced by shape. Sedimentation equilibrium data were analysed in SEDFIT-MSTAR17, particularly useful for heterogeneous systems. It is based on the M* function of Creeth and Harding21 and uses a smart-smooth algorithm for generating distributions of molar mass c(M) vs M. Although less resolving (due to the lower speeds) distributions are absolute (i.e. not requiring assumptions over conformation). The two methods (sedimentation velocity and equilibrium) provide, as we now demonstrate, a powerful combination for the analysis of heterogeneous systems such as the polymeric proanthocyanidin system under analysis here.Sedimentation velocity experimental data were analysed in the SEDFIT algorithm of Schuck13.Extraction of proanthocyanidins (PA) from hop material using different proportions of acetone in water yielded a series of extracts. These were analysed for their proanthocyanidin content using the acidic butanol assay. Hydrolysis of proanthocyanidins under these conditions produces anthocyanidins which were measured in a spectrophotometer by absorbance at 550 nm. All hop extracts generated the red magenta colour typical of proanthocyanidin cleavage to anthocyanidins. A range of absorbance values were produced, ranging between 0.6–1.02  yielded the highest level of proanthocyanidins. Furthermore, fining performance in green beer (post-fermentation) was likewise found to be optimal at this solvent ratio. Optimal beer fining is determined as the point at which there is minimal haze present in the beer and at which there is a substantial and relatively compact amount of sediment Table . An extret al.18 for the separation of grape and wine proanthocyanidins) in order to separate proanthocyanidins from other material. The methanolic fraction eluted from the C18 cartridge was hydrolysed and the acid butanol assay showed a 90% recovery of the PA that was present in the original crude extract (data not shown). The resulting fraction is a clear, non-viscous solution, with a colour ranging from yellow to brown depending on the concentration and the hop variety. The cleaned up fractions proved suitably pure for characterisation by AUCF.Preliminary AUCF experiments with crude acetone/water extracts did not yield data that could be processed by the AUCF software, presumably due to the wide range of material present within the sample. A C18 Sep-Pak SPE clean-up method was developed . The density of the solvent used for the processing was that of pure methanol at 20.0 °C.The partial specific volume of a substance is represented by the ratio of the substance’s anhydrous volume to its anhydrous mass, and is a key parameter for the processing of the analytical ultracentrifuge data. Tanaka 20 sedimentation coefficient distributions are generated from the evolution of the concentration distribution in the ultracentrifuge cell with time, to give the derived g(s) as a function of s distribution. Although the sedimentation coefficients of discretely resolved components are unaffected, the distribution can be influenced by diffusive broadening. The c(s) as a function of s method in SEDFIT provides a correction for this by evaluating a parameter known as the frictional ratio. The frictional ratio could not be determined from the literature, because the sample studied is not composed of only one molecular species. Instead a (weight average) frictional ratio was thus determined by iterative fitting using the software and applied to all species. All experiments showed slightly different frictional ratio values between samples, but, a consistent value was typically obtained across a dilution series for a given hop extract.In the SEDFIT procedureSedimentation velocity is an analytical method which measures the rate at which molecules move in response to a high centrifugal force. This force depletes the compounds from the meniscus region (close to the centre of the rotor) ultimately forming a pellet at the outside of the cell. This transport rate is expressed in terms of sedimentation coefficient values, measured in Svedbergs. The sedimentation velocity experiments showed a heterogeneous weight distribution for the polyphenolic extracts of both hop varieties Fig. .Figure 2The diffusion-deconvoluted model, c(s) provides evidence of different oligomeric states of the hop proanthocyanidin fractions; the profiles have peaks at discrete size ranges and are not continuous. For Saaz, the profile Fig.  showed 4These sedimentation coefficient data correspond with a greater fining activity of Saaz compared to Magnum in beer clarification studies (data not shown), supporting the hypothesis that larger proanthocyanidin polymers would result in larger particles of sediment that settle more efficiently.A key feature of any analytical technique is the reproducibility of the data obtained. Each sample run consisted of a set of cells running simultaneously with different dilutions of an extract. The results from each cell were obtained and averaged to give the c(s) values Table . These sThe sedimentation velocity technique appears to be highly reproducible, both within and between runs. There also appears to be varietal consistency. This consistency allows us to clearly demonstrate a difference in hop proanthocyanidin molecular weight profiles between different varieties of hops as can be seen in the Saaz and Magnum data Table .In AUCF, sedimentation velocity can define the profile of a mixture and shows the heterogeneous nature of the sample and its global composition. Although related to molecular size, information on molecular weight cannot be directly extracted from sedimentation velocity profiles. However, these experiments do clearly show a discrete set of peaks with distinct differences in molecular size rather than a continuous distribution. This implies that the hop plant produces a series of PA with particular degrees of polymerisation rather than one main PA with more or less sub units.Sedimentation equilibrium studies can be used to measure the average molecular weight of material in a sample. Although not as resolving as sedimentation velocity, it can provide an absolute estimate of the molecular weights of the major components present. Since the concentration distribution at equilibrium does not change with time, shape and frictional effects do not influence the pattern, which is solely a function of molecular weight. The molecular weight distribution of methanolic SPE fractions derived from Saaz or Magnum hop varieties was studied through sedimentation equilibrium experiments, starting with a low speed of 20000 rpm before moving to higher speeds. Once equilibrium was reached at each speed the rotational speed was increased by increments of 5000 rpm, up to a maximum of 40000 rpm for the final scans. The sedimentation equilibrium studies were consequently of longer duration, taking 4 to 5 days for each run, as compared to the sedimentation velocity experiments which were typically conducted in less than a day. This longer time period is necessary for the sedimentation and diffusive forces to reach equilibrium. Results for Magnum hop variety showed the presence of two distinct peaks, one with a molecular weight average of 5 kDa , and the second peak with a molecular weight of 52 kDa which only accounted for <3% of total area Fig. . In cont4, but also for their various beneficial impacts on human health.Polyphenol-rich hop extracts are of interest for their potential to clarify green beer efficiently6. The most concentrated proanthocyanidin fraction was extracted from hops using 70% acetone (aq) which, not surprisingly, correlates with the solvent composition typically recommended for the extraction of proanthocyanidins23. This fraction also gave the most efficient results in terms of beer fining activity.Degree of polymerisation is an important parameter to take into account in order to extract the highest molecular weight fraction from botanical sources. As the degree of polymerisation of proanthocyanidin polymers increases, they become more hydrophilic14. The results in Table 24, no simple single mathematical correlation was found between the sedimentation peaks using the power law relation (s α Mb) which would apply to species of different molecular weight of similar shape or conformation.Analytical ultracentrifugation is a well-known method for the determination of the molecular weight of molecules such as proteins and polysaccharides. The sedimentation velocity technique has the ability to profile solutions, to determine the complexity of a mixture, and to give a first indication of approximate molecular weight through the sedimentation coefficients obtainedSedimentation equilibrium was used in this study to resolve and determine actual molecular weights for each band of proanthocyanidins in the hop extracts. The c(M) distributions Fig.  indicateThe highest mass peak for Saaz was found during sedimentation velocity experiments at 4.4S, which from the data in Fig. et al.25 have clearly shown the polymer distribution of hop proanthocyanidins with accurate molecular masses, up to hexamers using tandem mass spectrometry. However, due to the noted difficulties in analysing high molecular weight proanthocyanidins, the present results are the first indication that much larger polymers are present in hops. Significantly, AUCF is a non-destructive method which measures the transport properties of molecules through a known distance under centrifugal force.The development of this analytical technique using AUCF has confirmed the presence of very high molecular weight polymers of proanthocyanidins in hops. Despite their low concentrations (approx. 20 mg/mL dry matter in the C18 purified methanolic fractions), AUCF was able to detect this group of polymers. Li 280 nm) into the eluted fraction for analysis. We thus considered that lignin was unlikely to be a significant component of the analysed polyphenolic fraction. Lastly in this regard, if binding between proanthocyanidins and a heterogeneous polymer such as lignin was envisaged, it would seem unlikely that the AUCF sedimentation velocity profiles of 3 different samples of Saaz hop would be so similar to one another as is the case for the results presented in Table et al. reported the presence of ‘high molecular weight polyphenols’ in hop bract extracts (species not specified), estimated to be 36–40 kDa in size26.The possibility remained that high mass species monitored using the AUCF technique might be artefacts of smaller proanthocyanidins bound to other molecules, such as protein or lignin materials from the hop. To investigate this hypothesis we analysed the protein content of the crude 70% acetone (aq) extract using a CB-X assay (G-Biosciences). This indicated a low protein content of less than 1% of dry matter . This would not be enough to contribute the high mass peaks observed which corresponded to around 35% of the material present in the Saaz hop Table . Further27, with Ohmori et al.28 reporting the assembly of catechin monomers to yield a 24-mer. However, this is currently the upward size-limit achieved through synthesis.A significant disadvantage of using chromatographic techniques in proanthocyanidin analysis is the lack of polymer reference standards in a high purity form. Progress has been made in the preparation of synthetic proanthocyanidinsAUCF has not previously been applied to the characterisation of proanthocyanidin polymers. This study thus represents a significant step forwards in developing methods for the analysis and characterisation of proanthocyanidins and may ultimately lead to an improved understanding of proanthocyanidin structures and molecular size distributions across the plant kingdom.This study has reported for the first time the application of AUCF to the characterisation of polyphenolic extracts of hops, and shown the presence of high molecular weight compounds with an upwards size limit in the region of 100 kDa for Saaz (or 56 kDa for Magnum). The polyphenolic hop extracts prepared in this study comprise a diverse group of compounds. Crude extracts in 70% acetone (aq) contained approximately 60 mg/mL of dry matter. Following SPE clean-up this was reduced to around 20 mg/mL of dry matter in the fractions analysed by AUCF. Importantly, this fraction retained the majority of proanthocyanidins, as indicated by the acid butanol assay. However, it is clear from the AUCF analysis that material of a range of molecular weights was present, which would have comprised not only proanthocyanidins, but also monomeric phenolic acids, polyphenols and potentially tannic acids. Although AUCF is normally applied to homogeneous systems, we have demonstrated that it is possible to adapt this technique to the analysis of such complex mixtures. Sedimentation velocity experiments provided evidence of different sedimentation coefficient profiles when comparing extracts of different hop varieties. These were reproducible when different sources of the same hop variety (Saaz) were analysed.29, this methodology should have cross-disciplinary applications in the characterisation of proanthocyanidins from a range of different sources.AUCF is a suitable technique for the non-destructive analysis of high molecular weight proanthocyanidins. As these molecules are also of considerable interest for their beneficial health aspects


Molecular imaging is an emerging technology that enables the noninvasive visualization, characterization, and quantification of molecular events within living subjects. Positron emission tomography (PET) is a clinically available molecular imaging tool with significant potential to study pathogenesis of infections in humans. in situ measurements of intralesional antimicrobial pharmacokinetics in multiple compartments, including privileged sites. Finally, the potential clinical applications of this promising technology are also discussed.Molecular imaging is an emerging technology that enables the noninvasive visualization, characterization, and quantification of molecular events within living subjects. Positron emission tomography (PET) is a clinically available molecular imaging tool with significant potential to study pathogenesis of infections in humans. PET enables dynamic assessment of infectious processes within the same subject with high temporal and spatial resolution and obviates the need for invasive tissue sampling, which is difficult in patients and generally limited to a single time point, even in animal models. This review presents current state-of-the-art concepts on the application of molecular imaging for infectious diseases and details how PET imaging can facilitate novel insights into infectious processes, ongoing development of pathogen-specific imaging, and simultaneous  Conversely, nuclear-medicine-based molecular imaging utilizes “tracers” or “probes” labeled with high-energy emission radionuclides, which can be used to target specific molecular pathways deep inside the body , a glucose analog that is selectively taken up by cells with a high rate of glucose metabolism, is a valuable clinical tool for predicting tumor response to treatment and patient survival . Therefore, target-specific PET probes for cancer are being developed to allow for a more specific diagnosis , a PET tracer used to detect hypoxic lung lesions in a mouse model of TB and confirmed using postmortem analyses. While no tracer accumulation was noted in nonhypoxic TB lesions in acutely infected or in control mice without lesions, a progressive, time-dependent tracer accumulation was noted in chronically infected mice, which are considered hypoxic. These findings were subsequently confirmed in TB patients using 18F-fluoromisonidazole (18F-FMISO) PET imaging  was introduced under the control of a strong mycobacterial promoter. TK phosphorylates 1-(2-deoxy-2-fluoro-β-d-arabinofuranosyl)-5-125I-iodouracil (125I-FIAU), a nucleoside analog, leading to trapping and accumulation of 125I-FIAU in the M. tuberculosis Phsp60 TK strain. Thus, bacteria were specifically and noninvasively detected in experimentally infected animals demonstrating heterogeneous bacterial burdens in visible TB lesions  predicted reactivation TB with high accuracy  identifying reservoirs of the virus even in monkeys controlling the infection  and thus are a risk factor for transmission , or antin silico screen of 961 radiolabeled small molecules followed by bacterial uptake assays of promising candidates and identified several potential bacterium-specific imaging tracers such as para-aminobenzoic acid (PABA), which accumulated in all bacterial species tested, d-mannitol, which accumulated selectively in Gram-negative and Gram-positive bacteria but not mycobacteria, and d-sorbitol, which accumulated selectively in Gram-negative Enterobacteriaceae  which is the largest family of bacterial pathogens in humans. Together, these afford a set of tools for the differential imaging of bacteria in vivo.Mainstay clinical microbiology uses differential bacterial metabolism, such as selective growth media, to differentiate bacteria in the microbiology laboratory . Therefo18F-fluoromaltotriose , which can be easily synthesized from 18F-FDG, demonstrated that the tracer accumulated ∼1,000-fold more in Enterobacteriaceae than in mammalian cells. Moreover, 18F-FDS PET was able to specifically detect and differentiate live Enterobacteriaceae (infected lesion) from sterile inflammation (heat-killed bacteria) in a murine thigh myositis model as well as other animal models of infection , which target the bacterial folate pathway  . Therefo18F-fluoro-3-hydroxy-2-propoxy)methyl]guanine (18F-FHPG), a derivative of ganciclovir, in which one hydroxyl group is replaced with a radioactive fluorine atom (18F-FHPG is selectively phosphorylated by the herpes simplex virus (HSV) TK and becomes trapped within infected cells. This method was utilized to visualize HSV-affected brain regions in a rat model of encephalitis (64Cu-labeled simian immunodeficiency virus (SIV) Gp120-specific antibody has also been utilized to study the viral dynamics and localization of SIV in viremic and antiretroviral therapy-treated macaques using PET  also hold potential to provide a more specific tool for diagnosis , was associated with subsequent development of HIV-related immune reconstitution inflammatory syndrome (IRIS) after initiation of ART (PET is becoming a routine clinical tool and is proliferating in the United States and abroad, although its application to infectious disease is mostly limited to and cure . This inormation . Similarn of ART .124I-DPA-713, a novel tracer for macrophage-associated inflammation, has recently been translated to the clinic. 124I-DPA-713 PET studies in healthy volunteers demonstrate that 124I-DPA-713 clears rapidly from the lungs, with predominantly hepatic elimination, and is safe and well tolerated in healthy adults (11C-rifampin PET to study antimicrobial distribution and optimize treatments for TB meningitis (ex vivo tools.However, there is need for the development and clinical translation of more specific imaging tracers for infections. For example, y adults . Human sningitis  and pulmningitis  have alsningitis , 85 and