Search Queries Research Articles

Facial Filler Injections– Questions Patients Ask and Where They Find Answers

Introduction: The most pressing questions patients ask about facial fillers and the sources to which patients are directed remain incompletely understood. Methods: The search engine optimization tool Ahrefs was utilized to extract Google metadata on searches performed in the United States. The most frequently asked questions were categorized by topic, while websites were categorized by authoring organization. JAMA benchmark criteria were used for website information quality assessment. Results: A total of 300 questions for the term “fillers” were extracted. The majority of search queries (24.0%) and monthly search volume (39.3%) pertained to procedural costs. The mean JAMA score for private practice sources (1.1 ± 0.57) was significantly lower than that of corporate sources (2.6 ± 0.55, p= 0.0003) but not significantly lower than academic pages (1.6 ± 1.34, p=0.483). With respect to monthly search volume, queries concerning lip fillers have been increasingly asked at a rate that exceeds other injection sites. Conclusion: Online searches for facial fillers often involve the topic of cost, and frequently direct patients to websites that contain inadequate information on authorship, attribution, disclosure and currency. When compared to other anatomic sites, search queries involving lip fillers have increased over the last three years.

SAT solving for variants of first-order subsumption

AbstractAutomated reasoners, such as SAT/SMT solvers and first-order provers, are becoming the backbones of rigorous systems engineering, being used for example in applications of system verification, program synthesis, and cybersecurity. Automation in these domains crucially depends on the efficiency of the underlying reasoners towards finding proofs and/or counterexamples of the task to be enforced. In order to gain efficiency, automated reasoners use dedicated proof rules to keep proof search tractable. To this end, (variants of) subsumption is one of the most important proof rules used by automated reasoners, ranging from SAT solvers to first-order theorem provers and beyond. It is common that millions of subsumption checks are performed during proof search, necessitating efficient implementations. However, in contrast to propositional subsumption as used by SAT solvers and implemented using sophisticated polynomial algorithms, first-order subsumption in first-order theorem provers involves NP-complete search queries, turning the efficient use of first-order subsumption into a huge practical burden. In this paper we argue that the integration of a dedicated SAT solver opens up new venues for efficient implementations of first-order subsumption and related rules. We show that, by using a flexible learning approach to choose between various SAT encodings of subsumption variants, we greatly improve the scalability of first-order theorem proving. Our experimental results demonstrate that, by using a tailored SAT solver within first-order reasoning, we gain a large speedup in solving state-of-the-art benchmarks.

Basic instruments for measuring the quality of life in patients after stroke (literature review)

Improvements in drug therapy have led to an increase in the number of patients surviving after the acute period of the stroke. A significant proportion of stroke patients experience consequences such as impaired motor function, psychological and social disorders. This affects the quality of life (QoL) of patients. General and specialized tests are used to assess the QoL in patients after a stroke. The purpose of the study. Systematization of information about the main questionnaires used in assessing QoL in patients after the acute period of stroke. The search for relevant sources devoted to the topic of work was carried out in the bibliographic database Pubmed / Medline and the Google information system. The following keywords were used in the search queries: “quality of life”, “stroke”, “indicators” etc. Test names were also used as keywords. The characteristics of a number of general and specialized questionnaires that allow analyzing QoL in patients after a stroke are considered. Key practical information about the main questionnaires used abroad is summarized. Information on their applicability in domestic studies of QoL in patients who have suffered from a stroke is presented. The instruments that are most widely used in foreign practice are noted. The tests reviewed (general and specific) have usually acceptable psychometric properties (validity and reliability), although none are ideal or suitable for all situations. Continuing the development of comprehensive methods for assessing QoL in patients with stroke consequences at are best suited for everyday clinical practice remains one of the important tasks of medicine. Further development and widespread introduction of promising methods of QOL analysis into regular medical practice will increase the information content of assessments of the outcomes of therapy and rehabilitation.

THE POSSIBILITIES OF USING VIRTUAL AND AUGMENTED REALITY TECHNOLOGIES IN MODERN CARDIOLOGY

Justification. Technological innovations have revolutionized medical practice, especially in the field of cardiac surgery, where the complex nature of interventions requires precision and foresight. The use of virtual (VR) and augmented reality (AR) in this field opens up huge prospects for improving preoperative planning, improving the quality of medical education and, ultimately, improving patient treatment outcomes. Aim. to analyze the literature on the role of VR/AR in modern cardiology, to discuss the current role and future directions in this field. Material and methods. As a result of the search, 3,858 publications were extracted from PubMed/MEDLINE, 69 publications from eLibrary and 1,115 publications found using Google Scholar. The search queries included the following keywords and their combinations: virtual reality, augmented reality, cardiology, cardiac surgery, virtual reality, augmented reality, cardiology, cardiac surgery. Search time interval: since the foundation of the corresponding database until May 2024. Results. Modern cardiological care includes increasingly complex procedures that require a high level of expertise. VR is becoming a powerful tool for both pre-procedural planning and educational events. VR opens up new opportunities for education and training of specialists in the field of cardiology. With its help, you can create realistic simulations of various situations that doctors may encounter in their work. This allows students to gain hands-on experience without risking real patients. Conclusion. The integration of VR into cardiology practice has great potential, but for full integration it is necessary to solve a number of problems. It is necessary to develop standards for the safety and effectiveness of using VR for medical purposes. Additional research is also needed to assess the long-term health effects of VR use on patients.

An evaluation of a visual interface for supporting query formulation in scholarly searching

Performing an effective literature review is a fundamental academic skill. Whether writing up a final project, preparing a research proposal, or simply finding answers to complex questions, students need to be able to systematically gather and analyse evidence from a variety of sources. However, many students have difficulty formulating effective search queries and understanding how to optimise their search strategy. This paper evaluates a novel approach to query formulation based on an alternative, visual interface. The approach is evaluated alongside a conventional, form-based interface in a comparative, controlled setting. The study finds that overall, participants considered the visual interface to be more complex and difficult to use. However, at the same time they used significantly more terms, facets and reformulations in the visual interface, and gave more attention to creating and refining more complex queries. In addition, the majority considered the visual interface to have greater transparency, with a clearer overview of the search tasks that encouraged them to invest greater effort in completing them successfully. The results demonstrate that visual approaches can offer tangible benefits in developing and improving students’ competence in exploratory search tasks.

Improving Search Query Accuracy for Specialized Websites Through Intelligent Text Correction and Reconstruction Models

Improving Search Query Accuracy for Specialized Websites Through Intelligent Text Correction and Reconstruction Models

Quantitative Analysis within Language Studies: An Analytical Views Based on the Bibliometrics Method

Abstract Background: While qualitative research methods have provided insights into linguistic structures and processes, the recent decades have witnessed a growing emphasis on quantitative approaches. Methodology: This study utilizes a bibliometric analysis based on the PRISMA guidelines to explore research trends in “Quantitative Analysis within Language Studies” from 2014 to 2024 by analyzing the metadata of 53,575 journal articles retrieved from a reputable database, i.e., Dimensions. Findings: The findings show that (1) there was a steady rise in publications throughout the period; (2) the total citations increased by over 113,000, representing a nearly 100-fold growth (1,141 citations in 2014 compared to 41,203 citations in 2024); (3) according to the ANZSRC 2020 classification, the field of Language, Communication and Culture has the highest number of publications (53,575), followed by Linguistics (32,121) and Language Studies (18,272); (4) there was the top 10 journals from 2014 to 2024; (5) there was a detail into the publication productivity and citation impact of 20 leading researchers; and (6) it has been extracted 1,028 terms concerning the examined query that classified into eight clusters. Conclusion: By integrating the insights gleaned from publication trends, citation analysis, leading authors, journal distribution, map-based visualizations, and cluster analysis of terms, this study provides a comprehensive and detailed picture of research trends within the search query. Originality: While current several research in quantitative language studies tends to delve into specific subfields, offering piecemeal understandings of the overall landscape, this study takes a distinct approach. By examining 53,575 articles content and metadata, this study aims to provide a more comprehensive perspective compare to previous fragmented insights.

When toxicity is not just from gluten: a systematic review on financial toxicity and celiac disease

Abstract Background With an incidence of up to ∼2% globally, Celiac Disease (CD) is probably one of the most life-long common chronic conditions. Although ‘Financial toxicity’ (FT) has been mainly linked to oncology, significant financial burdens have been described across all healthcare domains, even in CD and to the unexpected economic effort resulting from illness and the need for treatments. This study aimed to investigate the potential relationship between CD and FT. Methods A systematic literature review was performed according to the PRISMA Statement 2020 guidelines. The search query queried the following databases: PubMed, Scopus, CINAHL and APA PsycInfo. No time and study design limits were included. Results 105 articles were found, and 25 were included in the review. The main results revealed that CD impacts physical health and imposes a significant financial burden on patients and their families. FT in CD is primarily due to the high costs of diagnosis, lifestyle changes, and expenses for gluten-free foods. Several studies highlighted the scarce adherence to the therapeutic diet due to the cost of food and poor acceptance of CD. Furthermore, since 2007, there has been increased attention to the difficulty of finding gluten-free products and their expensive fees. All these aspects, even for low-income countries, were faced differently globally, as documented by the heterogeneity of government subsidy policies highlighting the health inequity. Conclusions Considering the prevalence, a comprehensive health assessment with a global health approach should consider clinical, social, and economic aspects. This regard could improve the quality of life for CD patients and ensure fair and personalised access to care, regardless of their geographical location or financial situation. This review has highlighted the fragmentation of resources available internationally, underlining the relevance from a public health point of view. Key messages • Celiac Disease is one of the most common life-long disorders, and financial toxicity is an aspect that should be taken into account also from a public health point of view to ensure health equity. • The gluten-free diet represents an important therapeutic choice in CD; the related expensive fees could increase scarce adherence and worse health outcomes.

ANALYZING USER BEHAVIOR PATTERNS FOR PERSONALIZED RECOMMENDER SYSTEMS IN E-COMMERCE: A LITERATURE REVIEW

Abstract: E-commerce thrives on a user-centric strategy, and recommender systems are at the cutting edge of personalizing the purchasing experience. These systems may forecast preferences and recommend appropriate items by analyzing user behavior patterns, resulting in many benefits such as increased customer satisfaction, increased sales and conversions, and increased efficiency. To accomplish these benefits, recommender systems utilize complex algorithms that examine numerous elements of user behavior such as purchase history, browsing behavior, search queries, demographic data, and implicit feedback. Sophisticated algorithms can recognise complicated patterns in user data, resulting in more accurate and personalized suggestions. Analyzing user reviews, product descriptions, and social media interactions may help you better understand consumer preferences and product features. Systems can make real-time suggestions depending on a user’s current browsing session, resulting in a more dynamic purchasing experience. Personalized recommender systems will play an increasingly important role in molding the future of e-commerce as user behavior analysis techniques are constantly refined. The study intends to make important advances to the field of personalized recommender systems by undertaking a thorough research of user behavior patterns in the e-commerce domain. We strive to improve the performance of recommender systems by extracting insightful features from various data sources and exploring sophisticated machine learning techniques, resulting in a more engaging and tailored user experience that fosters customer satisfaction and drives business growth. A comprehensive review of user behavior patterns and their influence on personalized recommender systems in the e-commerce industry reveals the critical role of data analysis and machine learning algorithms in tailoring product suggestions to individual preferences, thereby enhancing customer satisfaction and driving sales growth. By implementing the tactics and approaches expressed in this study, e-commerce platforms may stay ahead of the curve, providing a smooth and tailored purchasing experience that surpasses customer expectations and contributes to their competitive advantage in the changing e-commerce environment.

Pain Management Methods and Techniques in Lumbar Disc Surgery: A Narrative Review Study

Background and Aim: This study examines the complex field of pain treatment related to lumbar disc disorders in a narrative review. Methods and Materials/Patients: Our search strategy involved utilizing specific terms, including ‘pain management,’ ‘lumbar disc surgery,’ ‘methods,’ and ‘techniques.’ We formulated a search query using Boolean operators: (‘Pain management’ OR ‘analgesia’) AND (‘lumbar disc surgery’ OR ‘spinal surgery’) AND (‘techniques’ OR ‘procedures’ OR ‘approaches’ OR ‘methods’) AND ‘narrative review.’ A systematic search was conducted across reputable medical databases including PubMed, MEDLINE, and Cochrane Library. Filters were applied to refine search results based on publication type and date, with a focus on material published within the past two decades to ensure the inclusion of current, high-quality literature. Results: This study synthesized information from several sources, demonstrating the changing methods used to address pain in lumbar disc disorders. The article explored the historical background of medical treatments, emphasized both contemporary surgical and non-surgical methods, and investigated the predicted factors that affect the results. The study investigated the range of surgical incidents and examined the clinical factors to be taken into account for treatments. The value of efficient pain treatment in alleviating chronic back pain and maximizing patient results was emphasized. Conclusion: In conclusion, this review underscores the paramount importance of comprehensive management of lumbar disc pain. It stresses that effective pain control not only alleviates immediate suffering but also plays a pivotal role in ensuring positive surgical experiences, enhancing patient outcomes, and promoting long-term well-being.

Terminology of medicines used to control seizure disorders: 2024 ILAE Recommendations and profile of real-world term use

Background. The International League Against Epilepsy (ILAE) has provided recommendations on the terminology of medicines for control of seizure disorders, which should be adapted into different languages.Objective: to evaluate the usage profile of terms describing the effects of medicines used in patients with epilepsy.Material and methods. The search query analysis systems Google Trends and Yandex Wordstat as well as PubMed/MEDLINE, Google Scholar and eLibrary databases were used to evaluate the general public and professional usage profile, respectively.The following terms in Russian and English were studied: “antiepileptic”, “antiepileptic drug”, “antiseizure”, “antiseizure drug”. In order to ascertain a prevailing opinion within professional and patient communities, a questionnaire survey was conducted on the public online resources of the non-profit partnership “The Association of Epileptologists and Patients” carried out via the cloud-based cross-platform social media as well as instant messaging service Telegram and the social media platform VK.Results. In the English-speaking internet segment, the term “antiepileptic” is used more than 5 times frequently than “antiseizure” by the general public. Conversely, in the Russian-language segment, the term “antiseizure” is almost 2.5 times more common. The term “antiepileptic” is more prevalent in scientific community in both segments. This finding aligns with the profile of terminology usage observed among epileptologists and epilepsy patients. The questionnaire survey results revealed that 56.42% of 179 respondents were in favor of the terms “antiepileptic drug”, “AED” and “antiepileptic therapy”, whereas as few as 17.32% of those endorsed the ILAE-proposed terminology.Conclusion. In light of the established practice of terminology use in both professional scientific community and among practicing epileptologists and epileptic patients, as well as the differences in the semantics of English- and Russian-language terms and the identified lack of precision in the ILAE definition of epilepsy, it can be concluded that for the Russian-speaking population, the terms “antiepileptic drug”, “AED” are more preferable rather than the terms “antiseizure medication”, “ASM”. Additionally, it is preferable to use the terms “convulsive ictus” and “epileptic ictus” due to negative connotation with term “seizure” in Russian. The terms “antiseizure” and “antiepileptic” should not be regarded as mutually exclusive in the context of treatment that has a direct impact on epilepsy course. Finally, it is necessary to further refine epilepsy definition and classification.

Health Care Language Models and Their Fine-Tuning for Information Extraction: Scoping Review.

In response to the intricate language, specialized terminology outside everyday life, and the frequent presence of abbreviations and acronyms inherent in health care text data, domain adaptation techniques have emerged as crucial to transformer-based models. This refinement in the knowledge of the language models (LMs) allows for a better understanding of the medical textual data, which results in an improvement in medical downstream tasks, such as information extraction (IE). We have identified a gap in the literature regarding health care LMs. Therefore, this study presents a scoping literature review investigating domain adaptation methods for transformers in health care, differentiating between English and non-English languages, focusing on Portuguese. Most specifically, we investigated the development of health care LMs, with the aim of comparing Portuguese with other more developed languages to guide the path of a non-English-language with fewer resources. This study aimed to research health care IE models, regardless of language, to understand the efficacy of transformers and what are the medical entities most commonly extracted. This scoping review was conducted using the PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) methodology on Scopus and Web of Science Core Collection databases. Only studies that mentioned the creation of health care LMs or health care IE models were included, while large language models (LLMs) were excluded. The latest were not included since we wanted to research LMs and not LLMs, which are architecturally different and have distinct purposes. Our search query retrieved 137 studies, 60 of which met the inclusion criteria, and none of them were systematic literature reviews. English and Chinese are the languages with the most health care LMs developed. These languages already have disease-specific LMs, while others only have general-health care LMs. European Portuguese does not have any public health care LM and should take examples from other languages to develop, first, general-health care LMs and then, in an advanced phase, disease-specific LMs. Regarding IE models, transformers were the most commonly used method, and named entity recognition was the most popular topic, with only a few studies mentioning Assertion Status or addressing medical lexical problems. The most extracted entities were diagnosis, posology, and symptoms. The findings indicate that domain adaptation is beneficial, achieving better results in downstream tasks. Our analysis allowed us to understand that the use of transformers is more developed for the English and Chinese languages. European Portuguese lacks relevant studies and should draw examples from other non-English languages to develop these models and drive progress in AI. Health care professionals could benefit from highlighting medically relevant information and optimizing the reading of the textual data, or this information could be used to create patient medical timelines, allowing for profiling.

Effectiveness of extracorporeal shock wave therapy in comparison with other methods of treatment of patients with plantar fasciitis: literature review

Plantar fasciitis (PF) is one of the most common causes of pain in the heel area, which is associated with the presence of inflammation in the plantar fascia and is most often localized in the medial part of the heel area. Extracorporeal shock wave therapy (ESWT) is a method of hardware treatment that has been used in orthopedics and traumatology for the past decades. One of the main diseases successfully treated with this method is plantar fasciitis. The aim of the work was to determine the effectiveness of extracorporeal shock wave therapy in the treatment of plantar fasciitis compared to other methods of conservative treatment based on the literature review. Research literary sources from scientific electronic databases PubMed, Medline and other sources of scientific and medical information were analyzed. A literature search was performed using search queries specifying the method under study and plantar fasciitis, namely: «Extracorporeal Shockwave Therapy», «Plantar Fasciitis», «Conservative Treatment», «Physiotherapy». During the search, 473 scien­tific articles devoted to the treatment of plantar fasciitis were selected. Given the large number of articles and the desire to present up-to-date data, the query was limited to the last 9 years (from 2015 to 2023) and 417 articles were selected. Articles devoted to other methods of treatment of PF (conservative and surgical) and articles devoted to the use of ESWT in orthopedic and traumatological diseases of other localizations were excluded from the search results. At the second stage of the search, articles devoted exclusively to the treatment of PF by the ESWT method were excluded, and sources comparing the effectiveness of ESWT treatment with other methods of conservative treatment were selected (31 articles). The main results – it was determined that extracorporeal shock wave therapy continues to remain one of the main methods of conservative treatment of PF, which has been used for the last decades. It has proven its high efficiency and safety in the treatment of PF. Compared with other methods of conservative treatment of PF, extracorporeal shock wave therapy remains one of the most effective, it is successfully used in the treatment of PF.

Therapeutic potential of phytocompounds of Bacopa monnieri (L.) Wettst (literature review)

The aim of the work was to evaluate the pharmacological effects and therapeutic potential of individual compounds and extracts of B. monnieri based on the analysis of data from scientific periodicals regarding chemical composition and biological action. Theoretically significant were the studies of the materials of the scientific-metric database PubMed and Google Scholar over the last five years regarding the chemical composition and biological action of extracts based on B. monnieri and their individual components. The search query was carried out by the Latin name of the plant, with the exception of publications related to botanical research. In separate PubChem searches, names of individual phytocompounds were used to establish structure and distribution in plants. The SuperPred web server was used to predict therapeutic potential. The authors analyzed the chemical composition of the extracts, presented the structural and pharmacological characteristics of bacosides and their aglycones: bacosin and juubogenin, cucurbitacin E, loliolide, betulinic and asiatic acids and the flavonoid oroxindin. The mechanism of action of bacoside on β-amyloid is characterized and illustrated. Using machine learning, the prospects for using the main compounds of bacopa to create drugs were calculated taking into account the ATC classification, their biological effects and alternative plant sources were given. Experimental animal studies of whole aqueous or ethanolic extracts of B. monnieri have been found to support a cognitive enhancement effect. The extract was not toxic to humans. Numerous clinical trials show the effectiveness of the use of extracts in the treatment of anhedonia, depression, Alzheimer's disease, Parkinson's disease, dementia and hyperactivity. An analysis of clinical studies in Ukraine shows that drugs based on B. monnieri can be used in the complex treatment of cognitive impairment associated with dyscirculatory encephalopathy in adults and perinatal CNS damage in children. Considering the amphiphilicity of bacosides and the non-toxicity of extracts, they can be involved in the development of various dosage forms with a wide range of therapeutic applications. Further study of the pharmacological action of B. monnieri and the development of drug technology for solid and liquid dosage forms based on it are promising.

Ethical and Methodological Considerations in LGBTQ-focused Online Ethnography: A Proposal of a Systematic Review

Lesbian, gay, bisexual, transgender, and queer (LGBTQ) people constitute a vulnerable population that requires research about their needs, representations, and challenges. Among the variant research methods, ethnography is particularly effective in understanding participants and their lived experience. The development of information and communication technologies has transformed traditional ethnography research and contributed to the emergence of online ethnography research that holds potential for studying vulnerable populations (e.g., LGBTQ people) and relevant topics. We propose a systematic review to explore how researchers have considered and addressed ethical and methodological issues in LGBTQ-focused online ethnography research. We used the core collection of the Web of Science to search for relevant literature. We crafted the search query based on studies of LGBTQ populations, online ethnography studies, and other data sources like the Homosaurus vocabulary. Two groups of search terms were compiled and used in combination, including population-related terms (e.g., “queer”, “LGB*”, “GLB*”, and “sexual minorit*”) and method-related terms (e.g., “online ethnograph*”, “netnograph*”, “digital ethnograph*”, and “virtual ethnograph*”). In this review, we focus on empirical journal articles using any type or variant of online ethnography to investigate LGBTQ-focused topics. The eligible articles may include LGBTQ people as participants or stakeholders (e.g., LGBTQ staff), or analyze LGBTQ-related content (e.g., YouTube videos). Most importantly, we will analyze the ethical concerns (e.g., informed consent, power imbalance, cultural sensitivity, and beneficence and justice) and methodological aspects (e.g., research design, sampling, recruitment, data collection, data analysis, and roles of LGBTQ people) of these studies.

Navigating the Challenges of Legacy Data: A Systematic Literature Analysis

Legacy data is data collected systematically in the past, for which contemporary use and reuse are at-risk, difficult, or impossible due to issues such as missing metadata, obsolete storage media, outdated file formats, and unsupported software. As we introduced in Buchanan, et al. (2023), there is a demonstrated need for more systematic understanding of legacy research data efforts and the value of these data and efforts as perceived across stakeholder groups. We are conducting a literature analysis of publications on the topics of legacy research data use, preservation, curation, and management. Using an established search query and online literature databases, we retrieved and manually reviewed a pool of 1,338 results and identified 69 papers that fit the following criteria for our study: peer-reviewed articles published in the last 15 years including studies discussing methodologies and best practices; studies that describe repurposing legacy data; studies focusing on storage or archival methods for older data; and studies that discuss software and migration challenges. We are analyzing the sample of papers using content analysis and bibliometric methods, focusing on references to individuals involved, processes, data types, formats, locations, and problems being addressed.

Confirming the Query Search Method: Balancing AI Advancements in Reference Services

Although artificial intelligence (AI) has quickly become a tool that offers quick, simplistic answers to reference questions (Chen, 2023), in this paper, we interrogate AI’s ability to consider the human-to-human interpersonal nuances that occur and are vital to answering queries. We ask: what is most essential for reference services - human knowledge sharing or the machine’s artificial intelligence? AI, as a mechanistic language model, cannot discern the subtleties of humanity’s questions; AI itself admits that librarians are more efficient at answering reference queries from a humanistic approach and lens (Yang & Mason, 2023). This paper is the second part of our introduction to our methodology for reference services, the Query Search Method (QSM). We present conceptual substantiation that, when enacted, the QSM can incorporate AI as an addition to the librarian’s toolbox for honoring patrons’ ways of knowing that, through the sententiousness of the human experience, invariably seek knowledge beyond “the machine.”

Clinical Evaluation of Blood Culture Identification Gram-Positive Panel on Methicillin Resistant Gene Testing in a Large Metropolitan Teaching Hospital

Abstract Introduction The ePlex blood culture identification (BCID) gram-positive panel is a PCR-based approach used for the detection of common pathogens associated with bloodstream infections and corresponding antibiotic-resistance genes. One of the genes, mecA, is associated with methicillin, penicillin, and other penicillin-like-antibiotic-resistant gram-positive bacteria (GPB). It is unclear whether the BCID panel has predictive utility and accuracy in treating hospital infections due to GPB. This retrospective study attempts to determine the consistency and accuracy of BCID gene testing compared to more traditional susceptibility methods at a large public hospital. Method A search query was performed for all BCID results at one teaching hospital in a large metropolitan area for one year (2022). The query included demographic information, BCID results, culture results, and combined susceptibility data. The results were filtered to include only cases in which the mecA gene was detected. The filtered results were then analyzed to determine if the susceptibility results from the susceptibility platform (VITEK) were consistent with the expected susceptibility of the target gene, specifically for oxacillin and vancomycin. The susceptibility cutoff was set as >0.5 mcg/mL and <1 mcg/mL respectively, the standard threshold used at the institution. Results A total of 1211 culture results were obtained, of which the mecA gene was identified by BCID in 321 cases, along with the following GPB: Staphylococcus aureus, Staphylococcus epidermidis, and Staphylococcus sp. (not aureus). The corresponding cultures grew the following isolates: S. aureus, S. epidermidis, S. hominis, and S. haemolyticus. Of the 321 BCID results, 75 were identified as S. aureus. The isolates grew methicillin-resistant Staph aureus (MRSA) (69/75) 92%, while the typical S. aureus grew (6/75) in 8% of the isolates. In these cases, we compared susceptibility testing for both isolates as either sensitive or resistant, with a MIC of >0.5 mcg/mL for oxacillin to be designated as resistant, and <1 mcg/mL to be designated as sensitive to vancomycin. Of the 75 specimens, the concordance rate was 97% (73/75) for oxacillin and 100% (75/75) for vancomycin. The average receipt to verification turnaround time (TAT) was 36 hours for BCID results and 121 hours (about 5 days) for culture sensitivity results. Conclusion The results show that oxacillin resistance can be predicted by detecting S. aureus and the mecA gene using the BCID panel. However, the mecA gene can be identified in other GPB such as S. epidermidis, in which it should not be used to infer oxacillin or vancomycin susceptibilities. In the case of mecA and S. aureus detection by BCID, treating the patient as a MRSA infection may be appropriate before the susceptibilities have been performed. This approach can reduce the turnaround time for antimicrobial resistance reporting and improve antimicrobial stewardship efforts.

Research trends in innovation ecosystem and circular economy

Understanding innovation ecosystems and the circular economy is crucial for systemic change in business and industry, fostering eco-innovation and advancing sustainable development. This study uses bibliometric analysis to uncover the research trends, patterns, and collaborations, revealing a significant gap in understanding the interactions between innovation ecosystems and the circular economy and offering potential avenues for future research that align with sustainable development. The analysis was carried out with the help of Biblioshiny and VOSviewer on the final selected documents of 2981 from the Scopus database through a search query and the SPAR-4-SLR stages of filtration. The key findings of the study are as follows: collaboration among countries involves accessing countries’ resources, knowledge, markets, and location. The study explores research trends in the innovation ecosystem and circular economy, focusing on five key clusters: the circular economy for eco-innovation and resource recovery, circular business models for fostering sustainable innovation in the bioeconomy, sustainability through renewable energy and sdgs, the sustainable business model for enhancing green innovation through entrepreneurship, and Artificial Intelligence (AI) and the circular business model in Industry 4.0. The bibliometric analysis identifies trends, research gaps, and collaboration patterns, revealing potential avenues for future exploration in industrial symbiosis, energy transition, and the system of innovation. The study analyzed only the documents available in Scopus. The exclusion of papers based on the search period, language, document type, and incomplete details are the limitations of this research and open the scope of potential future research. The findings will help existing researchers in this field as well as new researchers interested in this field by clearly understanding trends and further research scopes. The study also offers actional recommendations and practices to policymakers. Practices, and entrepreneurs for the attainment of global sustainability goals. The novelty and originality of this study rely on a thorough literature review that describes the state of the art in the innovation ecosystem and circular economy.

Federated learning-based natural language processing: a systematic literature review

Federated learning (FL) is a decentralized machine learning (ML) framework that allows models to be trained without sharing the participants’ local data. FL thus preserves privacy better than centralized machine learning. Since textual data (such as clinical records, posts in social networks, or search queries) often contain personal information, many natural language processing (NLP) tasks dealing with such data have shifted from the centralized to the FL setting. However, FL is not free from issues, including convergence and security vulnerabilities (due to unreliable or poisoned data introduced into the model), communication and computation bottlenecks, and even privacy attacks orchestrated by honest-but-curious servers. In this paper, we present a systematic literature review (SLR) of NLP applications in FL with a special focus on FL issues and the solutions proposed so far. Our review surveys 36 recent papers published in relevant venues, which are systematically analyzed and compared from multiple perspectives. As a result of the survey, we also identify the most outstanding challenges in the area.