Multi-omics convergence in odontogenic neoplasm research: a scientometric and translational mapping study

This article presents a scientometric analysis of Mainland China Translation Studies (TS) scholars' international visibility. The analysis was mainly based on articles published in 13 international TS journals indexed in the SSCI or A&HCI databases between 2005 and 2013. Publication counting, citation analysis, editorial board composition analysis, and word analysis were used to investigate mainland Chinese TS scholars' international productivity, impact, and presence rate in the editorial boards of international TS journals, as well as the thematic landscape of their international contributions. Data analysis indicated that mainland Chinese TS scholars had low international visibility, reflected in their low international productivity, impact, and presence rate in the editorial boards of international TS journals, and that the thematic landscape of their research was different from that of the international TS community. The data also suggested that TS scholars from English-dominant and economically advanced countries had much higher international visibility. Implications were discussed with a view to changing the current state of low visibility. The current study provides not only an overview of the contributions of mainland Chinese TS scholars to the international TS community but also insights for future studies.

This multi-source bibliometric and translational mapping study provides a panoramic synthesis of how research on microglia-mediated spinal pain signaling has evolved from foundational mechanistic studies to clinically oriented innovations. The aim is to identify developmental trajectories, mechanistic hotspots, and translational opportunities, thereby offering strategic insight into guiding the future direction of neuropathic pain research. We analyzed 1313 original research papers from the Web of Science Core Collection (WoSCC; 2005-2024) using CiteSpace and VOSviewer to construct collaboration networks, journal co-citation graphs, and keyword-driven mechanism clustering. To add a translational medicine dimension, we conducted a targeted PubMed search ("microglia AND spinal cord AND (translational OR therapeutic OR drug targets)"), retrieving 692 additional records, enabling cross-database overlay to link mechanistic themes with specific therapeutic targets. The scientometric model indicates that spinal pain research has shifted from primarily descriptive work to more detailed regulatory models. Key themes include glial cell activation, oxidative stress, mitochondrial dysfunction, and changes in microglia state. Research on heat shock protein pathways and sex-related microglial responses is also increasing. Some core terms have remained frequent over the years, such as "neuroinflammation" and "activated protein kinases". In contrast, the explosive emergence of brain-derived neurotrophic factor (BDNF) and spinal cord stimulation (2020-2021; burst intensity = 2.56) indicates a growing interest in synaptic and circuit control and neuromodulation-based approaches. In the PubMed subset, 33.6% of studies directly focused on treatment development, with gene therapy, intrathecal administration, and microenvironment remediation also appearing more frequently. When we combine data from WoSCC and PubMed over the past 20 years, we can see a significant shift in the explanation of spinal pain in this field. Early research often described the problem as "glial cell activation-cytokine release." Recent research, however, focuses on specific pathways, particularly microglial state regulation, oxidative stress-autophagy connections, and kinase signaling. This shift in treatment approaches is also reflected in translational studies. Many studies no longer rely primarily on systemic drugs but instead focus on targeted strategies such as intrathecal administration, gene or cell therapy, extracellular vesicles, and neuromodulation. These trends make polarization-related molecular nodes ideal candidate targets for precision analgesia. However, bibliometric results are dependent on database coverage, keyword processing, and clustering settings. Some "hotspots" may reflect changes in terminology or citation habits rather than true mechanistic importance. The rise of neuromodulation keywords may also reflect broader clinical applications; microglial mechanisms are plausible, but contributions from other circuit-level mechanisms may also play a role. These results indicate that the field is moving beyond a purely inflammatory perspective toward systemic intervention models. Currently, there is a greater focus on microglial homeostasis and M2-like anti-inflammatory/immune repair processes, as well as sex and metabolic factors that may influence responses. This research direction supports immune repair and more personalized analgesia. Simultaneously, stronger mechanistic arguments require cell state-specific measurements rather than broad phenotypic labels.

This article presents a scientometric analysis of Mainland China Translation Studies (TS) scholars' international visibility. The analysis was mainly based on articles published in 13 international TS journals indexed in the SSCI or A&HCI databases between 2005 and 2013. Publication counting, citation analysis, editorial board composition analysis, and word analysis were used to investigate mainland Chinese TS scholars' international productivity, impact, and presence rate in the editorial boards of international TS journals, as well as the thematic landscape of their international contributions. Data analysis indicated that mainland Chinese TS scholars had low international visibility, reflected in their low international productivity, impact, and presence rate in the editorial boards of international TS journals, and that the thematic landscape of their research was different from that of the international TS community. The data also suggested that TS scholars from English-dominant and economically advanced countries had much higher international visibility. Implications were discussed with a view to changing the current state of low visibility. The current study provides not only an overview of the contributions of mainland Chinese TS scholars to the international TS community but also insights for future studies.

Methicillin-resistant Staphylococcus aureus (MRSA) has evolved as an alarming public health thread due to its global spread as hospital and community pathogen. Despite this role, a scientometric analysis has not been performed yet. Therefore, the NewQIS platform was used to conduct a combined density-equalizing mapping and scientometric study. As database, the Web of Science was used, and all entries between 1961 and 2007 were analyzed. In total, 7671 entries were identified. Density equalizing mapping demonstrated a distortion of the world map for the benefit of the USA as leading country with a total output of 2374 publications, followed by the UK (1030) and Japan (862). Citation rate analysis revealed Portugal as leading country with a rate of 35.47 citations per article, followed by New Zealand and Denmark. Country cooperation network analyses showed 743 collaborations with US-UK being most frequent. Network citation analyses indicated the publications that arose from the cooperation of USA and France as well as USA and Japan as the most cited (75.36 and 74.55 citations per collaboration article, respectively). The present study provides the first combined density-equalizing mapping and scientometric analysis of MRSA research. It illustrates the global MRSA research architecture. It can be assumed that this highly relevant topic for public health will achieve even greater dimensions in the future.

Many physiological and pharmacological studies on testosterone(TS), the major male sex hormone, have been carried out over the past decades. This study aimed to quantify the research trend based on TS scientific publications in a 23‐yr period, and provide the quantitative estimates of the TS research associated with botanical agents(BA) using scientometric methods. Total 2,279 bibliographic records retrieved from the SCOPUS database from 1996 to 2018 were analyzed with Knowledge Matrix Plus, VOS viewer and Gephi software. We obtained science map derived from co‐word network analysis and identified TS research area related to BA. The results revealed that TS studies related to BA have concentrated on the modulating effect of BA on TS and TS metabolite levels in environmental, medical, and toxicological research field. The findings report that TS is highly related to risk assessment factors such as endocrine disruption exposed to pollution and wastewater in industrial, agricultural and livestock environments. In medical studies, spermatogenesis, testis, erectile dysfunction, and fertility studies have been observed in TS research involving BA. Research on the development of 5‐alpha‐reductase inhibitor for alopecia, and the regulation of bcl‐2 for carcinogenesis were also revealed. In toxicological studies, side effects of TS therapy for prostate cancer, hyperplasia, hepatotoxicity (cytochrome p450), and lipid peroxidation were investigated in a relatively higher frequency. Support or Funding Information This research was supported by Korea Institute of Science and Technology Information (KISTI) under the research program “Development of Future Technology Analysis System Based on Open Data”.

This study aims to examine machine translation research in journals indexed in the Web of Science to find out the research trending issue, hotspot areas of research, and document co-citation analysis. To this end, 541 documents published between 1992 and 2022 were retrieved and analyzed using CiteSpace, and Bibexcel. Many metrics were analyzed such as document co-citation analysis, sources co-citation analyses, authors’ keywords analysis, and Hirsch index. Data were coded and filtered to include research related to machine translation from the perspectives of language and translation studies. We identified 11 clusters that represented the hotspot research during the period of almost three decades of research. We also discovered that a significant focus of research in machine translation centered around enhancing the translation process through the implementation of neural networks integrated with artificial intelligence. Additionally, we observed the incorporation of human post-editing as a means to refine and improve machine-translated outputs. We found that translation studies journals were the most highly co-cited journals and Google translate was the most highly used machine translation. This study highlights the trending issues and hotspots in machine translation research within language and translation studies. The integration of neural networks with artificial intelligence and human post-editing emerged as prominent areas of focus for enhancing translation quality. The findings of the current study inform future research and technological advancements in machine translation, guiding efforts to improve translation processes and outcomes.

This paper reports on a quantitative analytical methodology which deals with perceptions of scientific experts regarding the intellectual shape and contents (‘cognitive structure’) of their scientific domain. This study examines the method's utility for studying expert views in general, and, more specifically, its strengths and weaknesses as a tool for improving validation studies of bibliometric maps involving subject experts. The main premise is that expert views are based on their internal knowledge structures (‘mental schemes’) of which relevant features can be captured in quantitative data. This approach allows a rigorous and systematic way of studying mental schemes across subject experts. Spatial representations of their data (‘mental maps’) provide insight in properties underlying those knowledge structures. Data from different experts are reconciled to construct a ‘common’ mental map which displays a group view. This study includes a test to establish the validity of individual mental maps and common mental maps. The methodology is applied to the views of 14 researchers in the field of neural network research and related areas. Key-findings are: (i) mental maps can provide valid representations of expert mental schemes, (ii) experts sharing the same subject field are more likely to share views, (iii) expert judgements of bibliometric maps are affected by the structure of their own mental schemes, as well as (iv) by their views regarding the utility of those maps, and (v) common mental maps and a bibliometric co-word map based on the same set of items differ significantly, showing a resemblance on main features only.

Molecular review of odontogenic myxoma

Ameloblastoma is a locally destructive and invasive tumour that can recur despite adequate surgical removal. Molecular studies have offered interesting findings regarding ameloblastoma pathogenesis. In the present review, the following topics are discussed regarding its molecular nature: clonality, cell cycle proliferation, apoptosis, tumour suppressor genes, ameloblastin and other enamel matrix proteins, osteoclastic mechanism and matrix metalloproteinases and other signalling molecules. It is clear from the literature reviewed that translational studies are necessary to identify prognostic markers of ameloblastoma behaviour and to establish new diagnostic tools to the differential diagnosis of unicystic from multicystic ameloblastoma. Finally, molecular biology studies are also important to develop more effective alternative approaches to the treatment of this aggressive odontogenic tumour.

In vivo expression of the Bacillus subtilis spoVE gene was studied by S1 nuclease mapping and spoVE gene fusion analysis. Transcription of spoVE is induced at about the second hour of sporulation from two closely spaced promoters designated P1 and P2. Examination of the precise transcription initiation site by high-resolution primer extension mapping indicated that the nucleotide sequences of the -10 and -35 regions of both P1 and P2 were similar to those of promoters recognized by E sigma E. Moreover, S1 nuclease mapping and translational spoVE-lacZ fusion studies with various spo mutants suggest that the expression of spoVE P2 requires the spoIIG gene product, sigma E. The sporulation of a wild-type strain was inhibited severely in the presence of a multicopy plasmid, pKBVE, carrying the spoVE promoter, indicating the possible titration of a transcriptional regulatory element(s).

The newly identified sin gene affects late growth processes in Bacillus subtilis when it is overexpressed or inactivated in the chromosome. S1 nuclease mapping of the sin gene transcripts in vivo reveals the existence of three transcripts (RNAI, RNAII, and RNAIII). By correlating 5' ends of sin gene transcripts with DNA sequence, we have identified three different promoterlike sequences (P1, P2, and P3) for these transcripts. 3'-End mapping of these transcripts identified three prominent termination sites at the end of the sin gene. These termination sites are localized on two hairpin structures previously identified from the DNA sequence. The most abundant transcript, RNAIII, coded only for the sin gene, while the polycistronic transcripts RNAII and RNAI coded for the sin gene and ORF1 that precedes the sin gene. S1 mapping and translational lacZ fusion studies indicated that ORF1 and the sin gene are regulated differently. ORF1 expression is under developmental control, increasing at the end of vegetative growth, and requires functional spo0A and spo0H gene products. The sin gene is expressed at an almost constant and relatively low level throughout growth and remains largely unaffected by spo0A and spo0H mutations.

To enable rationale vaccine design, studies of molecular and cellular mechanisms of immune recognition need to be linked with clinical studies in humans. A major challenge in conducting such translational research studies lies in the management and integration of large amounts and various types of data collected from multiple sources. For this purpose, we have established “IMMUNOCAT”, an interactive data management system for the epitope discovery research projects conducted by our group. The system provides functions to store, query, and analyze clinical and experimental data, enabling efficient, systematic, and integrative data management. We demonstrate how IMMUNOCAT is utilized in a large-scale research contract that aims to identify epitopes in common allergens recognized by T cells from human donors, in order to facilitate the rational design of allergy vaccines. At clinical sites, demographic information and disease history of each enrolled donor are captured, followed by results of an allergen skin test and blood draw. At the laboratory site, T cells derived from blood samples are tested for reactivity against a panel of peptides derived from common human allergens. IMMUNOCAT stores results from these T cell assays along with MHC:peptide binding data, results from RAST tests for antibody titers in donor serum, and the respective donor HLA typing results. Through this system, we are able to perform queries and integrated analyses of the various types of data. This provides a case study for the use of bioinformatics and information management techniques to track and analyze data produced in a translational research study aimed at epitope identification.

Vaccinia virus rifampicin-resistance locus specifies a late 63,000 Da gene product

Review of the molecular pathogenesis of the odontogenic keratocyst

Genome-wide association (GWA) studies have been remarkably successful in identifying genetic variants associated with common, complex diseases. In the four and a half years since the advent of this technology, over 450 publications have documented over 500 associations with a significance less than 5 x 10-8 in over 130 diseases and traits. In cancer alone, over 70 well-replicated associations with at least 18 distinct forms of neoplasia have been reported. Many of these variants lie in genes previously unsuspected of being related to the associated conditions, and nearly half are in regions containing no known genes at all. Many variants are associated with seemingly unrelated diseases (Table). These findings are shedding new light on the pathophysiology of complex diseases, as well as identifying promising targets for drug development or variants related to drug selection or dosing. Markers assayed on GWA platforms are likely not causal variants, but instead are only in linkage disequilbrium (inherited together) with them. Identifying an association is thus only a first step, albeit an important one, in determining the change(s) in genomic structure and function underlying a given disease. The many hundreds of thousands of variants assayed in each study are known present a substantial possiblity of spurious, false-positive findings. Replication of associations in different study groups and even in different populations is thus essential in isolating GWA signals worthy of in-depth investigation through techniques such as fine mapping, sequencing, and functional studies. Examination of large numbers of cases with a variety of environmental exposures is necessary for identifying possible gene-environment interactions. Such studies are facilitated by wide availability of GWA data in well-characterized, population-based cohorts with extensive exposure information. The challenge of relating millions of genetic variants to potentially hundreds or thousands of traits and exposures, though computationally and inferentially daunting, is essential to understanding the joint role of genes and environment in complex diseases such as cancer. Once a functional variant is identified, its value in risk assessment, disease detection, and treatment selection must be assessed in translational studies for it to be useful clinically. Identifying available therapies, or developing novel treatments to modify the effects of a causal variant, typically takes even greater effort. Surprisingly, most GWA-defined variants confer only small increased risks of disease (less than 30% increase) and taken together generally explain only a small proportion of the familial clustering of a given trait, leaving a large fraction unexplained. Promising approaches for finding this “missing heritability” include targeted or whole-genome sequencing to identify rarer variants (present in less than 5% of the population) that may be in linkage disequilibrium with the typically more common variants assayed on GWA platforms. Identification of even a few dozen low-frequency (0.5%-5%) variants with moderate effects (two- to three-fold odds ratios of disease), would suffice to account for the unexplained heritability in type 2 diabetes, for example. Other promising methods include exploring GWA data for structural variation such as duplications or deletions of germline DNA, and for evidence of interaction among genes. Expanding GWA sample sizes through meta-analyses and consortia, especially in persons of non-European ancestry, also has enormous value in finding variants of small effect and breaking up genomic regions of linkage disequilibrium to better focus the search for causal variation. The value of existing and future GWA studies for identifying disease-related variants can best be enhanced by ensuring wide availability of high-quality data to qualified researchers with appropriate protections for consent and privacy; increasing sample sizes and diversity and ensuring meticulous meta-analyses, particularly for conditions with relatively small sample sizes studied to date; and enhancing phenotyping to include subtler or more quantitative or precise phenotypes. Improvement of GWA platforms should permit capture of larger proportions of variation in implicated genes and expand investigation of the X chromosome, particularly as imputation of X and Y markers improves. Rigorous measurement of environmental exposures, including rare exposures in common diseases, and epigenetic variants in appropriate tissues when technically feasible, will facilitate identification of gene-environment interactions. And although structural variation is at present difficult to assay, linkage disequilibrium patterns in GWA data and improved maps can be used to identify common structural variants reliably. High-throughput sequencing techniques and programs such as the 1,000 Genomes Project will expand identification and tagging of structural variants even further. All of these steps will lead GWA studies into critical new directions of defining the genomic structural and functional changes underlying complex diseases and approaches for modifying their effects. Citation Format: Teri Manolio. Genetic architecture of cancer and other complex diseases: Lessons learned and future directions [abstract]. In: Proceedings of the AACR 101st Annual Meeting 2010; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr SY32-02