Dynamic Research Field Research Articles

A novel algorithm for identifying arrival times of P and S Waves in seismic borehole surveys

The arrival times of P and S waves, originating from earthquakes, diverse seismic tests, and events, are crucial geotechnical parameters. Derived from the inversion of these travel times, VP (P-wave velocity) and VS (S-wave velocity) are pivotal in geotechnical engineering, correlating directly with dynamic soil properties and enabling calculations of Poisson's Ratio (ν), Young's modulus (E), Shear modulus (μ), and Bulk modulus (B). Both VP and VS are crucial for evaluating soil behaviour under various conditions, aiding in modelling soil for settlement, wave propagation, seismic wave interaction, liquefaction potential analysis, seismic response analysis, and many more. The selection of arrival times for seismic tests, including Crosshole, Downhole, and Uphole tests, is done manually, which is time-consuming and potentially erroneous. To address this issue, various algorithms have been developed to automate the picking process. Some of these algorithms use wavelet transforms and Bayesian information criteria, while others use machine learning techniques such as artificial neural networks. These methods vary in terms of their accuracy, yet each one possesses inherent limitations when it comes to processing data with different levels of signal-to-noise ratio. The advancement of automated algorithms for determining arrival times is an ongoing and dynamic field of research. Apart from the existing research focused on determining the arrival time of P waves, there is a dearth of studies investigating the detection of S wave arrival times. To fill this gap, this study proposes new approaches for detecting both P and S wave arrival time(s). One approach entails the utilization of an iterative optimization algorithm to accurately fit a curve to the leading edge of the P waveform. The arrival time is determined by calculating a fraction relative to the highest point obtained from the fitted peak. The second approach entails identifying the exact moment of the S wave's arrival by determining the points of intersection between the oppositely polarized S waveforms. These methods provide a promising approach for automatically detecting both P and S wave arrival time(s), which has the potential to improve the precision and efficiency in picking up arrival time(s).

The Archaeology of Early Cities: “What Is the City but the People?”

The archaeology of early urbanism is a growing and dynamic field of research, which has benefited in recent years from numerous advances at both a theoretical and a methodological level. Scholars are increasingly acknowledging that premodern urbanization was a much more diverse phenomenon than traditionally thought, with alternative forms of urbanism now identified in numerous parts of the world. In this article, we review recent developments, focusing on the following main themes: (a) what cities are (including questions of definitions); (b) what cities do (with an emphasis on the concentration of people, institutions, and activities in space); (c) methodological advances (from LiDAR to bioarchaeology); (d) the rise and fall of cities (through a focus on persistence); and (e) challenges and opportunities for urban archaeology moving forward. Our approach places people—with their activities and networks—at the center of analysis, as epitomized by the quotation from Shakespeare used as the subtitle of our article.

Intermittent theta burst stimulation in adolescents and young adults with depressive disorders: protocol of a randomized, sham-controlled study with a sequential Bayesian design for adaptive trials.

Intermittent theta burst stimulation (iTBS), a variant of repetitive transcranial magnetic stimulation (rTMS), is an established treatment for adults with major depressive disorder (MDD). Due to its favorable safety profile, iTBS is also a promising early intervention in the transition phase from adolescence to early adulthood, but thishas not been systematically investigated to date. Thus, the EARLY-BURST trial investigates the efficacy and safety of iTBS over the left dorsolateral prefrontal cortex (lDLPFC) in treatment-seeking young patients (age 16-26years) with depressive disorders (i.e. major depressive disorder, persistent depressive disorder, bipolar depression), allowing for relevant co-morbidities. Participants have not received antidepressant or antipsychotic medication during the last 12months except for short-term (< 2weeks) on-demand medication. The trial will employ a novel sequential Bayesian, randomized, double-blind, parallel-group, sham-controlled design. Up to 90 patients at two clinical sites (Munich, Augsburg) will be randomized 1:1 to the treatment groups, with sequential analyses starting after 26 patients in each group completed the treatment. The primary outcome will be the difference in depression severity at week 6 (post-treatment visit) between active iTBS and sham iTBS, assessed with the Montgomery-Åsberg Depression Rating Scale (MADRS). The trial is planned to be expanded towards a three-arm leapfrog design, contingent on securing additional funding. Thus, in addition to potentially providing evidence of iTBS's efficacy in adolescents and young adults with depressive disorders, the EARLY-BURST trial aims at setting the stage for subsequent platform trials in this dynamic research field, where novel adaptive study designs are required to meet the need for rapidly testing promising new vs established rTMS protocols.Trial registration: DRKS00033313.

Easy Direct Functionalization of 2D MoS2 Applied in Covalent Hybrids with PANI as Dual Blend Supercapacitive Materials

AbstractThe pressing demand for more sustainable energy provision and the ongoing transition toward renewable resources underline the critical need for effective energy storage solutions. To address this challenge, scientists persistently explore new compounds and hybrids and, in such a dynamic research field, 2D materials, particularly transition metal di‐chalcogenides (TMDCs), show great potential for electrochemical energy storage uses. Simultaneously, also conductive polymers (CPs) are interesting and versatile supercapacitor materials, especially polyaniline (PANI), which is extensively studied for this purpose. In this work, a powerful method to combine TMDCs and PANI into covalently grafted hybrids starting from aniline functionalized few‐layers 1T‐MoS2, attained by a facile direct arylation with iodoaniline, is presented. The hybrids provide circa 70 F g−1 specific capacitance in a pseudo device setup, coupled with a robust capacitance retention of well over 80% for up to 5000 cycles. These findings demonstrate the potential of similar covalent composites to work as active components for novel, innovative energy storage technologies. At the same time, the successful synthesis marks the efficacy of direct covalent grafting of conductive polymer on the surface of 2D TMDCs for stable functional materials.

Hundred Years of Inheritance and Innovation: The Historical Evolution of Huang Feihong's Cultural Heritage and Cultural and Creative Designs

This paper delves into the historical evolution of Huang Feihong's cultural heritage and its intersection with cultural and creative design. It seeks a profound comprehension of Huang Feihong's life achievements, the cultural traditions he embodied, and his contributions to Lingnan culture. The study specifically examines the relationship between Huang Fei-hong's cultural legacy and cultural and creative design, focusing on the concepts of cultural and creative products, the application of design, and the dynamic interplay between tradition and modernity. Through a comprehensive analysis of Huang Feihong's culture, this paper unveils the intricate connection between tradition and modernity, highlighting the role of cultural and creative design in both preserving and innovating. This dynamic research field not only enhances our understanding of Huang Feihong's cultural heritage but also imparts valuable insights for the practical aspects of cultural preservation and creative design. The findings offer fresh avenues and possibilities for the continued inheritance and promotion of Chinese cultural traditions.

New Metabolomic Insights Into Cancer.

Cancer has been marked by metabolic irregularities that fuel various aggressive activities such as rapid cell proliferation, evasion of the immune system, and spread to distant organs. Therefore, exploiting cancer metabolism for diagnosis, monitoring, or treatment has been extensively studied in the past couple of decades with various molecular and cellular techniques. More recently, investigating cancer diagnostics and treatments through advanced metabolomics has emerged, and these comprehensive approaches provide a holistic understanding of cancer metabolism, which supported the discovery of metabolic targets relevant across multiple cancer types and the development of more effective treatments. This study offers highlights of new knowledge on cancer metabolism enabled by recent metabolomics studies and their potential applications in aiding cancer research and predicting cancer treatment outcomes. Specifically, we discussed the use of advanced metabolomics in cancer metabolism, tumor microenvironment, and cancer immunotherapy studies to provide valuable insights that can shape future research efforts in the dynamic field of cancer metabolism research.

Parallel dual adaptive genetic algorithm: A method for satellite constellation task assignment in time-sensitive target tracking

The evolution of satellite surveillance technology, bolstered by advanced onboard intelligent systems and enhanced attitude maneuver capabilities, has thrust mission scheduling and execution into the spotlight as a prominent and dynamic research field in recent years. As the demand intensifies for mission scheduling and execution to transition from static ground targets to time-sensitive moving targets, conventional scheduling methods often fall short of delivering satisfactory results for continuously tracking these dynamic targets with constellation. The paper introduces a rapid yet efficacious satellite constellation task assignment method, termed the Parallel Dual Adaptive Genetic Algorithm (PDA-GA), for the task assignment of multiple moving target tracking. Specifically, the dual adaptive mechanism isolates the genetic algorithm’s sensitivity to parameters, while the parallel mechanism increases the evolutionary process’s computation speed by deploying complex computations to the GPU. Based on the meticulous analysis of the relevant factors that need to be considered in real tracking scenarios, the proposed PDA-GA can improve the search quality and efficiency of the task assignment solution. We conduct an extensive array of contrast and ablation experiments to showcase the performance and efficiency of PDA-GA in conjunction with autonomous attitude control algorithms across five simulated tracking scenarios. Furthermore, to enable high-fidelity simulation of tracking scenarios, we introduce the Constellation Target Tracking Environment (CTTE), which is equipped with a physics engine and algorithms for multi-satellite task assignment and single-satellite attitude control. This endeavor lays a foundation for future research endeavors focused on autonomous tracking of multiple time-sensitive moving targets within large-scale constellation.

Cross-corpus speech emotion recognition with transformers: Leveraging handcrafted features and data augmentation

Speech emotion recognition (SER) stands as a prominent and dynamic research field in data science due to its extensive application in various domains such as psychological assessment, mobile services, and computer games, mobile services. In previous research, numerous studies utilized manually engineered features for emotion classification, resulting in commendable accuracy. However, these features tend to underperform in complex scenarios, leading to reduced classification accuracy. These scenarios include: 1. Datasets that contain diverse speech patterns, dialects, accents, or variations in emotional expressions. 2. Data with background noise. 3. Scenarios where the distribution of emotions varies significantly across datasets can be challenging. 4. Combining datasets from different sources introduce complexities due to variations in recording conditions, data quality, and emotional expressions. Consequently, there is a need to improve the classification performance of SER techniques. To address this, a novel SER framework was introduced in this study. Prior to feature extraction, signal preprocessing and data augmentation methods were applied to augment the available data, resulting in the derivation of 18 informative features from each signal. The discriminative feature set was obtained using feature selection techniques which was then utilized as input for emotion recognition using the SAVEE, RAVDESS, and EMO-DB datasets. Furthermore, this research also implemented a cross-corpus model that incorporated all speech files related to common emotions from three datasets. The experimental outcomes demonstrated the superior performance of SER framework compared to existing frameworks in the field. Notably, the framework presented in this study achieved remarkable accuracy rates across various datasets. Specifically, the proposed model obtained an accuracy of 95%, 94%,97%, and 97% on SAVEE, RAVDESS, EMO-DB and cross-corpus datasets respectively. These results underscore the significant contribution of our proposed framework to the field of SER.

Molecular and Biochemical Therapeutic Strategies for Duchenne Muscular Dystrophy.

Significant progress has been achieved in understanding Duchenne muscular dystrophy (DMD) mechanisms and developing treatments to slow disease progression. This review article thoroughly assesses primary and secondary DMD therapies, focusing on innovative modalities. The primary therapy addresses the genetic abnormality causing DMD, specifically the absence or reduced expression of dystrophin. Gene replacement therapies, such as exon skipping, readthrough, and gene editing technologies, show promise in restoring dystrophin expression. Adeno-associated viruses (AAVs), a recent advancement in viral vector-based gene therapies, have shown encouraging results in preclinical and clinical studies. Secondary therapies aim to maintain muscle function and improve quality of life by mitigating DMD symptoms and complications. Glucocorticoid drugs like prednisone and deflazacort have proven effective in slowing disease progression and delaying loss of ambulation. Supportive treatments targeting calcium dysregulation, histone deacetylase, and redox imbalance are also crucial for preserving overall health and function. Additionally, the review includes a detailed table of ongoing and approved clinical trials for DMD, exploring various therapeutic approaches such as gene therapies, exon skipping drugs, utrophin modulators, anti-inflammatory agents, and novel compounds. This highlights the dynamic research field and ongoing efforts to develop effective DMD treatments.

Facial emotion recognition: A comprehensive review

AbstractFacial emotion recognition (FER) represents a significant outcome of the rapid advancements in artificial intelligence (AI) technology. In today's digital era, the ability to decipher emotions from facial expressions has evolved into a fundamental mode of human interaction and communication. As a result, FER has penetrated diverse domains, including but not limited to medical diagnosis, customer feedback analysis, the automation of automobile driver systems, and the evaluation of student comprehension. Furthermore, it has matured into a captivating and dynamic research field, capturing the attention and curiosity of contemporary scholars and scientists. The primary objective of this paper is to provide an exhaustive review of FER systems. Its significance goes beyond offering a comprehensive resource; it also serves as a valuable guide for emerging researchers in the FER domain. Through a meticulous examination of existing FER systems and methodologies, this review equips them with essential insights and guidance for their future research pursuits. Moreover, this comprehensive review contributes to the expansion of their knowledge base, facilitating a profound understanding of this rapidly evolving field. In a world increasingly dependent on technology for communication and interaction, the study of FER holds a pivotal role in human‐computer interaction (HCI). It not only provides valuable insights but also unlocks a multitude of possibilities for future innovations and applications. As we continue to integrate AI and facial emotion recognition into our daily lives, the importance of comprehending and enhancing FER systems becomes increasingly evident. This paper serves as a stepping stone for researchers, nurturing their involvement in this exciting and ever‐evolving field.

A Novel Digitalization Approach for Smart Materials – Ontology‐Based Access to Data and Models

Smart materials react to physical fields (e.g., electric, magnetic, and thermal fields) and can be used as sensors, actuators, and generators due to their bidirectional behavior. Easy and multiscale access to material data and models enables efficient research and development with regard to the selection of appropriate materials and their optimization towards specific applications. However, different working principles, measurement and analysis methods, as well as data storage approaches lead to heterogeneous and partly inconsistent datasets. The ontology‐based data access (OBDA) is a suitable method to access such heterogeneous datasets easily and quickly, while material models can transform material data across certain scales for different applications. In order to connect both capabilities, an extended approach enabling an ontology‐based data and model access (OBDMA) is presented, also supporting findable, accessible, interoperable, and re‐usable (FAIR). The OBDMA system comprises four main levels, the query, the ontology, the mapping, and the database. Storing knowledge at these different levels increases the interchangeability and enables variable datasets, which is essential, especially for dynamic research fields such as smart materials. In this article, the principles and advantages of the OBDMA approach are demonstrated for different subclasses of smart materials, but can be transferred to other materials, too.

The top 50 most-cited articles about COVID-19 and the complications of COVID-19: A bibliometric analysis.

This bibliometric analysis examines the top 50 most-cited articles on COVID-19 complications, offering insights into the multifaceted impact of the virus. Since its emergence in Wuhan in December 2019, COVID-19 has evolved into a global health crisis, with over 770 million confirmed cases and 6.9 million deaths as of September 2023. Initially recognized as a respiratory illness causing pneumonia and ARDS, its diverse complications extend to cardiovascular, gastrointestinal, renal, hematological, neurological, endocrinological, ophthalmological, hepatobiliary, and dermatological systems. Identifying the top 50 articles from a pool of 5940 in Scopus, the analysis spans November 2019 to July 2021, employing terms related to COVID-19 and complications. Rigorous review criteria excluded non-relevant studies, basic science research, and animal models. The authors independently reviewed articles, considering factors like title, citations, publication year, journal, impact factor, authors, study details, and patient demographics. The focus is primarily on 2020 publications (96%), with all articles being open access. Leading journals include The Lancet, NEJM, and JAMA, with prominent contributions from Internal Medicine (46.9%) and Pulmonary Medicine (14.5%). China played a major role (34.9%), followed by France and Belgium. Clinical features were the primary study topic (68%), often utilizing retrospective designs (24%). Among 22,477 patients analyzed, 54.8% were male, with the most common age group being 26-65 years (63.2%). Complications of COVID-19 affected 13.9% of patients, with a recovery rate of 57.8%. Analyzing these top-cited articles offers clinicians and researchers a comprehensive, timely understanding of influential COVID-19 literature. This approach uncovers attributes contributing to high citations and provides authors with valuable insights for crafting impactful research. As a strategic tool, this analysis facilitates staying updated and making meaningful contributions to the dynamic field of COVID-19 research.

Characterization of Functional Biohybrid Materials Based on Saccharomyces Cerevisiae Biomass

Biohybrid materials and engineered living materials (ELMs) are a dynamic field of research at the interface of material science and synthetic biology. Recently, microorganisms have been described as both functional and structural building blocks of such materials. Dry materials with bacteria as structural building block have previously not been investigated for their ability to retain catalytic activity. Herein, it is shown that Saccharomyces cerevisiae biomass can act as a structural building block in dry, macroscopic materials while simultaneously providing functionality. A benign method for the preparation of both coatings and free‐standing, flexible films is presented. Notably, free‐standing films can be prepared solely from biomass and plasticizers without the need for other additives. During the process, the integrity of the cells and the catalytic activity within is preserved, which is demonstrated by biocatalytic H2O2 degradation. The film‐forming properties of S. cerevisiae biomass and the influence of plasticizing and polymeric additives on the mechanical properties are investigated in detail and compared to related materials. The work presented is a first step toward new, mechanically strong microorganism‐based functional coatings and films.

The top 50 most-cited articles about COVID-19 and the complications of COVID-19: A bibliometric analysis

Background This bibliometric analysis examines the top 50 most-cited articles on COVID-19 complications, offering insights into the multifaceted impact of the virus. Since its emergence in Wuhan in December 2019, COVID-19 has evolved into a global health crisis, with over 770 million confirmed cases and 6.9 million deaths as of September 2023. Initially recognized as a respiratory illness causing pneumonia and ARDS, its diverse complications extend to cardiovascular, gastrointestinal, renal, hematological, neurological, endocrinological, ophthalmological, hepatobiliary, and dermatological systems. Methods Identifying the top 50 articles from a pool of 5940 in Scopus, the analysis spans November 2019 to July 2021, employing terms related to COVID-19 and complications. Rigorous review criteria excluded non-relevant studies, basic science research, and animal models. The authors independently reviewed articles, considering factors like title, citations, publication year, journal, impact factor, authors, study details, and patient demographics. Results The focus is primarily on 2020 publications (96%), with all articles being open access. Leading journals include The Lancet, NEJM, and JAMA, with prominent contributions from Internal Medicine (46.9%) and Pulmonary Medicine (14.5%). China played a major role (34.9%), followed by France and Belgium. Clinical features were the primary study topic (68%), often utilizing retrospective designs (24%). Among 22,477 patients analyzed, 54.8% were male, with the most common age group being 26-65 years (63.2%). Complications of COVID-19 affected 13.9% of patients, with a recovery rate of 57.8%. Conclusion Analyzing these top-cited articles offers clinicians and researchers a comprehensive, timely understanding of influential COVID-19 literature. This approach uncovers attributes contributing to high citations and provides authors with valuable insights for crafting impactful research. As a strategic tool, this analysis facilitates staying updated and making meaningful contributions to the dynamic field of COVID-19 research.

Advancing Research Training in Medical Education: Global Perspectives and Paradigms for Future Development.

This study delves into the dynamic field of medical education research, emphasizing the integration of research training within medical curricula. It seeks to understand the impact of such integration on the competencies of future medical professionals. The primary aim is to systematically categorize and analyze the current trends and future directions in research training in medical education. This involves assessing the influence of research training on medical students' skills and the methodologies used in such research. The research employs an extensive bibliographic literature review across multiple databases. It classifies studies like experiential or case studies, editorials, and original research articles. This classification is based on criteria such as geographical location, research objectives, theoretical frameworks, and methodologies. Findings reveal a diverse landscape in medical education research, with a significant emphasis on research training. The research showcases varying methodologies and approaches used globally, highlighting the thematic focus and geographical distribution of these studies. Research training in medical education is a globally expansive and evolving field. It underscores the importance of continuous investigation, particularly focusing on integrating research elements at curricular levels and exploring innovative educational strategies. The study also points out potential research gaps, especially in underrepresented regions, indicating directions for future research efforts.

The Mediterranean Zoanthid Parazoanthus axinellae as a Novel Source of Antimicrobial Compounds

Marine bioprospecting is a dynamic research field that explores the oceans and their biodiversity as noteworthy sources of new bioactive compounds. Anthozoans are marine animals belonging to the Cnidaria phylum characterized by highly specialized mechanosensory cells used both for defence against predators and prey capture. Here, high concentration of cnidocysts have been isolated from the Mediterranean zoanthid coral Parazoanthus axinellae (Schmidt, 1862) and their antimicrobial potential has been investigated. The cnidocyst extract exerted significant antibacterial activity against some human pathogens capable of developing resistance to conventional antibiotics such as Streptococcus agalactiae and Coccus sp., and against several Vibrio species, including some microbial strains for humans and farmed fish, such as Vibrio alginolyticus, Vibrio anguillarum, Vibrio fischeri, Vibrio harveyi, and Vibrio vulnificus. Results have been discussed in light of both the ecological aspects and biotechnological value of the cnidocyst extract in the nutritional, nutraceutical, and pharmaceutical fields.

The top 50 most-cited articles about COVID-19 and the complications of COVID-19: A bibliometric analysis

Background This bibliometric analysis examines the top 50 most-cited articles on COVID-19 complications, offering insights into the multifaceted impact of the virus. Since its emergence in Wuhan in December 2019, COVID-19 has evolved into a global health crisis, with over 770 million confirmed cases and 6.9 million deaths as of September 2023. Initially recognized as a respiratory illness causing pneumonia and ARDS, its diverse complications extend to cardiovascular, gastrointestinal, renal, hematological, neurological, endocrinological, ophthalmological, hepatobiliary, and dermatological systems. Methods Identifying the top 50 articles from a pool of 5940 in Scopus, the analysis spans November 2019 to July 2021, employing terms related to COVID-19 and complications. Rigorous review criteria excluded non-relevant studies, basic science research, and animal models. The authors independently reviewed articles, considering factors like title, citations, publication year, journal, impact factor, authors, study details, and patient demographics. Results The focus is primarily on 2020 publications (96%), with all articles being open access. Leading journals include The Lancet, NEJM, and JAMA, with prominent contributions from Internal Medicine (46.9%) and Pulmonary Medicine (14.5%). China played a major role (34.9%), followed by France and Belgium. Clinical features were the primary study topic (68%), often utilizing retrospective designs (24%). Among 22,477 patients analyzed, 54.8% were male, with the most common age group being 26-65 years (63.2%). Complications of COVID-19 affected 13.9% of patients, with a recovery rate of 57.8%. Conclusion Analyzing these top-cited articles offers clinicians and researchers a comprehensive, timely understanding of influential COVID-19 literature. This approach uncovers attributes contributing to high citations and provides authors with valuable insights for crafting impactful research. As a strategic tool, this analysis facilitates staying updated and making meaningful contributions to the dynamic field of COVID-19 research.

Low-Valent Transition Metalate Anions in Synthesis, Small Molecule Activation, and Catalysis.

This review surveys the synthesis and reactivity of low-oxidation state metalate anions of the d-block elements, with an emphasis on contributions reported between 2006 and 2022. Although the field has a long and rich history, the chemistry of transition metalate anions has been greatly enhanced in the last 15 years by the application of advanced concepts in complex synthesis and ligand design. In recent years, the potential of highly reactive metalate complexes in the fields of small molecule activation and homogeneous catalysis has become increasingly evident. Consequently, exciting applications in small molecule activation have been developed, including in catalytic transformations. This article intends to guide the reader through the fascinating world of low-valent transition metalates. The first part of the review describes the synthesis and reactivity of d-block metalates stabilized by an assortment of ligand frameworks, including carbonyls, isocyanides, alkenes and polyarenes, phosphines and phosphorus heterocycles, amides, and redox-active nitrogen-based ligands. Thereby, the reader will be familiarized with the impact of different ligand types on the physical and chemical properties of metalates. In addition, ion-pairing interactions and metal-metal bonding may have a dramatic influence on metalate structures and reactivities. The complex ramifications of these effects are examined in a separate section. The second part of the review is devoted to the reactivity of the metalates toward small inorganic molecules such as H2, N2, CO, CO2, P4 and related species. It is shown that the use of highly electron-rich and reactive metalates in small molecule activation translates into impressive catalytic properties in the hydrogenation of organic molecules and the reduction of N2, CO, and CO2. The results discussed in this review illustrate that the potential of transition metalate anions is increasingly being tapped for challenging catalytic processes with relevance to organic synthesis and energy conversion. Therefore, it is hoped that this review will serve as a useful resource to inspire further developments in this dynamic research field.

P266 Predictive tissue-based biomarkers in treatment of Inflammatory Bowel Disease with biologicals and small molecules: a systematic review

Abstract Background The treatment landscape of inflammatory bowel disease (IBD) has changed in the past decade with introduction of new drug classes. For most drugs, only 30% of patients achieve long-term remission. Clinical implementation of predictive biomarkers to support precision medicine is lacking. As the interactions of immune system and microbiome in the colonic mucosa may hold the key to the prediction problem, we performed a systematic review to assess the status of tissue-based biomarkers in the era of biological and small molecule therapies. Methods A literature search was performed in Medline, Embase, the Cochrane Library, Web of science and the ECCO abstract database in July 2023. Papers were considered eligible when reporting on biomarkers, extracted from biopsies obtained during colonoscopy, that had predictive value regarding therapy success of a specific non-TNFα biological or small molecule. Two authors independently assessed eligibility and extracted the data. Results From 10,141 screened records with 155 papers assessed for eligibility, a total of 43 studies were included. The majority was published in the last 5 years (87%). Data on the clinical history of patients and the interval between biopsy and therapy onset was often lacking, in part while 49% of studies were published as conference abstracts. Heterogeneity in therapy success assessment regarding modality (clinical, endoscopic, and/or histologic) and interval (4-58 weeks) was striking. With 28 studies, vedolizumab is the best investigated drug. Of the 16 studies reporting on gene expression, 7 used data from the GEMINI-I/LTS trials. These studies reported a range from a single predictive gene such as TREM1 and OSM to a classifier of 267 differentially expressed genes. Studies looking at the protein level (n=7) focused mostly on target engagement. In 7 studies, biomarker discovery was performed through histological evaluation, mainly looking at mucosal eosinophil counts. One study looking at the microbiome did not find differences between responders and non-responders of vedolizumab. Conclusion Our systematic review shows that tissue-based predictive biomarker discovery in IBD is a young and dynamic field of research. This is reflected by the heterogeneity in how and when therapy success is assessed. Moreover, the various methods to analyze gene expression data yield vastly different results when applied to the same dataset. We therefore propose guideline development to support clinical implementation of predictive biomarkers.

Mapping the research landscape of business ethics, corporate governance, and corporate social responsibility: A bibliometric and citation analysis

The primary objective of the study is to present a comprehensive review and citation analysis of publication data in the interrelated disciplines of "Business Ethics," "Corporate Governance," and "Corporate Social Responsibility." The publication data was obtained from the Clarivate Analytics Web of Science SSCI (Social Science Citation Index) and Elsevier Scopus for bibliometric and citation analysis. The data covers a time span of 2003–2023 for WoS and 1999–2023 for Scopus, with 306 documents for WoS and 347 documents for Scopus after suitable filtrations. The study further evaluates the differences in citation counts across Scopus, Web of Science (WoS), and Google Scholar (GS) for the common top 30 most cited articles based on the WoS and Scopus datasets. The most cited articles in the field are all relatively recent and published in high-impact journals. This suggests that this area is a growing and dynamic field of research. The findings of the study revealed publication trends, prominent journals, leading articles, the most productive countries, and the comparative citation analysis that has garnered significant contributions to the literature. The research publication is an excellent resource for researchers, scholars, and practitioners interested in learning about and contributing to this field. Furthermore, the study will lay the groundwork for future studies in this area.