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Recently tetraspanin CD151 has been identified as an important biological target involved in metastatic processes which include cell adhesion, tumor progression processes, and so forth in different types of cancers, such as breast cancer and glioblastoma. This in Silico study considered 1603 compounds from the Food and Drug Administration database, after performing an ADMET analysis; we selected 853 ligands, which were used for docking analysis. The most promising ligands were selected from docking studies, based on two criteria: (a) showed lowest affinity to the CD151 protein and (b) they interact with the QRD motif, located in the second extracellular loop. Furthermore, we investigate the stability of the protein‐ligand complexes through MD simulations as well as free energy MM‐PBSA calculations. From these results, loperamide and glipizide were identified as the best evaluated drugs. We suggest an in vitro analysis is needed to confirm our in silico prediction studies. [ABSTRACT FROM AUTHOR]

In graph theory, graph labeling is an essential area of study because labeled graphs offer useful mathematical models for coding theory, cryptography, astronomy, radar, database administration and communication networks. Consider a bijection for a graph G of order n, f : V (G) → {1, 2, ..., n}. The weight of a vertex z of G, expressed as w(z), is defined as the sum of labels assigned to all vertices adjacent to vertex z in G. If the weights are distinct for every unique pair of vertices y, z in V (G), then the labeling f is referred to as distance antimagic. A distance antimagic graph is any graph G that accepts such a labeling. Distance antimagic labeling on various basic graph products are discussed in this paper. We explore results on (a, d)-distance antimagic labeling for the lexicographic product G * H and distance antimagic labeling for the cartesian product G * H, tensor product G x H and strong product G x H in this work, where the graphs G and H are cycle related graphs, paths or complete graphs. Also, computer-aided algorithms are designed to verify that vertex weights are distinct. [ABSTRACT FROM AUTHOR]

The interferon-gamma releasing assay (IGRA) has been widely used to diagnose latent tuberculosis infection (TBI). However, there are limited data on the association between performance in the IGRA and risk of tuberculosis disease (TBD), as well as on the appropriate IGRA threshold for initiating TBI treatment. The analysis was performed using the IGRA results in the Korean Military Manpower Administration database (January 2017 to December 2021), and TBD cases reported to the Korean Military Medical Command (January 2017 to June 2023). All Korean candidates for 18-month military service underwent the IGRA in the pre-enlistment examination, and enlistees who tested positive (≥0.35 IU/mL) were advised to receive TBI treatment before enlistment. From 2017 to 2021, 1 647 941 individuals were screened, with 29 574 testing positive for IGRA. Excluding nonenlistees namely individuals with TBD before enlistment, 19 387 individuals were IGRA positive and 1 356 324 IGRA negative. Of the positives, 4351 were excluded due to discontinued or ongoing TBI treatment at or after enlistment. During follow-up of 9219 untreated and 5818 treated positive individuals and 1 356 324 negatives, TBD occurred in 22 of the IGRA-positive individuals (97.5/100 000 person-years [95% CI, 61.1–147.7]), predominantly in the untreated group (18 cases, 130.1/100 000 person-years [95% CI, 77.1–205.7]) compared to the treated group (4 cases, 45.9/100 000 person-years [95% CI 12.5 – 117.4]), whereas 57 cases occurred in the IGRA-negative group (2.8/100 000 person-years [95% CI, 2.2–3.6]). Elevating the cutoff of IGRA from 0.35 IU/mL to 1.33 IU/mL increased positive predictive value (0.2% vs. 0.4%, p 0.03), with insignificant loss of sensitivity (24% vs. 20%, p 0.69) and decreased numbers needing treatment from 790.5 to 415.3. Elevated IGRA levels before enlistment are associated with risk of TBD during military service. It is worth considering raising the IGRA threshold for treatment of TBI in cohorts of healthy, young military individuals. [ABSTRACT FROM AUTHOR]

The increasing complexity of managing modern database systems, particularly in terms of optimizing query performance for large datasets, presents significant challenges that traditional methods often fail to address. This paper proposes a comprehensive framework for integrating advanced machine learning (ML) models within the architecture of a database management system (DBMS), with a specific focus on PostgreSQL. Our approach leverages a combination of supervised and unsupervised learning techniques to predict query execution times, optimize performance, and dynamically manage workloads. Unlike existing solutions that address specific optimization tasks in isolation, our framework provides a unified platform that supports real-time model inference and automatic database configuration adjustments based on workload patterns. A key contribution of our work is the integration of ML capabilities directly into the DBMS engine, enabling seamless interaction between the ML models and the query optimization process. This integration allows for the automatic retraining of models and dynamic workload management, resulting in substantial improvements in both query response times and overall system throughput. Our evaluations using the Transaction Processing Performance Council Decision Support (TPC-DS) benchmark dataset at scale factors of 100 GB, 1 TB, and 10 TB demonstrate a reduction of up to 42% in query execution times and a 74% improvement in throughput compared with traditional approaches. Additionally, we address challenges such as potential conflicts in tuning recommendations and the performance overhead associated with ML integration, providing insights for future research directions. This study is motivated by the need for autonomous tuning mechanisms to manage large-scale, heterogeneous workloads while answering key research questions, such as the following: (1) How can machine learning models be integrated into a DBMS to improve query optimization and workload management? (2) What performance improvements can be achieved through dynamic configuration tuning based on real-time workload patterns? Our results suggest that the proposed framework significantly reduces the need for manual database administration while effectively adapting to evolving workloads, offering a robust solution for modern large-scale data environments. [ABSTRACT FROM AUTHOR]

We take the establishment of cross-border e-commerce comprehensive pilot zones as the quasi-natural experiment, based on China’s General Administration of Customs Database, China Customs Online Inquiry Platform, ‘Cross-Border E-Commerce Retail Import Commodity List’ and other data. By employing the staggered DID method, this paper systematically investigates the potential of cross-border e-commerce to enhance the quality of imported products. The research findings reveal the following: Since the introduction of the cross-border e-commerce comprehensive pilot zones, there has been a significant improvement in the quality of imported products in China. These effects, however, vary across different product types and regions, suggesting heterogeneous impacts. The cross-border e-commerce comprehensive pilot zones have facilitated the development of import trade in China through three main avenues: reducing search costs, resolving financing challenges, and lowering tariffs. These measures have collectively contributed to the reduction of trade costs. [ABSTRACT FROM AUTHOR]

BACKGROUND: Exosomes play a role in all stages of wound repair, and there is currently a large body of research on exosomes in skin wound repair, which has been shown to have great potential for clinical applications. OBJECTIVE: To summarize and discuss the main mechanisms and clinical applications of exosomes in the treatment of skin wounds, in order to promote the clinical translation of exosomes. METHODS: PubMed, clinicaltrials.gov, China National Knowledge Infrastructure, Food and Drug Administration database, and Chinese Clinical Trial Register were searched from inception to March 2023. The English search terms were “exosomes, wound healing, stem cells, chronic wound, immunoregulation, inflammation, skin, therapeutic use, isolation, characterization, infections”. The Chinese search terms were “exosomes, wound healing, stem cells, immunomodulation, clinical applications”. A total of 79 articles were included for the summary. RESULTS AND CONCLUSION: (1) Exosomes can improve and accelerate wound healing through inflammation regulation, immune protection, angiogenesis, cell proliferation and migration, and collagen remodeling. (2) Exosomes derived from stem cells have mature preparation techniques and related mechanism research, which is currently the mainstream research direction. Non-stem cell-derived exosomes have the advantages of convenience, economy, and easy production, and can be used as a supplement for clinical applications. (3) The clinical application of exosomes is still in its infancy, but has great potential for application. Various exosome modification techniques have laid the foundation for the future development of clinically personalized services and require further research. (4) The clinical translation of exosomes faces many challenges, such as low yield, high heterogeneity, lack of unified standards for isolation, purification, and quality control, and difficulties in storage. [ABSTRACT FROM AUTHOR]

Background: Eosinophilic esophagitis (EoE) is increasing in prevalence but there is a lack of population-based studies. We sought to determine the prevalence, demographics, and associated atopic diseases in the Veterans Affairs (VA) population. Methods: A nationwide analysis of data from the VA patient population was done using a Veterans Health Administration database. EoE was identified using ICD9 (530.13) and ICD10 (K20.0) codes from October 2008 to June 2020. Demographic data, smoking status, BMI, treatment, and ICD codes for atopic diagnoses were collected. Two sample proportion z-tests, Chi-square tests, two-sample t tests, and one-way ANOVA were used to assess associations across demographic categories. Results: We identified a total of 11,775 patients with an EoE diagnosis: 91% male, 83% White, 8.6% Black, and 5% were of Hispanic ethnicity. The prevalence of EoE increased over time. At diagnosis, the mean age was 48.5 years overall, 51.6 years for Black patients, 45.3 years for Hispanic patients, and 48.2 years for Whites. Dysphagia was the most common symptom overall, but a higher percentage of Blacks and females were found to report chest pain (p < 0.0001, h = 0.32). With the exception of urticaria and atopic dermatitis, both Blacks and Hispanics had a higher incidence of atopic conditions compared to other races and ethnicities (p < 0.0001). Conclusion: While EoE is seen primarily in White males, our study shows that a notable percentage of patients were Black or Hispanic, suggesting that EoE should be considered in non-white patients. The later age of diagnosis in this group could represent a lack of awareness about EoE among non-white patients. More research is needed to study these associations. [ABSTRACT FROM AUTHOR]

The establishment of Saorstát Éireann (the Irish Free State) in 1922 did not herald a fundamental overhaul of the administrative machinery inherited from Whitehall and Dublin Castle. Path dependent continuities in legislation and executive orders underpinned the new dispensation. At the same time, a process of evolutionary change, which we call 'administrative greening', was underway. Drawing on data in the Irish State Administration Database (ISAD), and building on our analysis in Biggins, J., MacCarthaigh, M., & Scott, C. (2024). Priming the state: Continuity and junctures in the foundation of the Irish administration. Irish Political Studies, we explore these dynamics of both continuity and change in the formative years of the new state's public administration. In so doing, we attest to patterns of normative production and reproduction, illustrated with reference to a number of legislative and administrative examples. [ABSTRACT FROM AUTHOR]

The continuously updated database of failures and censored data of numerous products has become large, and on some covariates, information regarding the failure times is missing in the database. As the dataset is large and has missing information, the analysis tasks become complicated and a long time is required to execute the programming codes. In such situations, the divide and recombine (D&R) approach, which has a practical computational performance for big data analysis, can be applied. In this study, the D&R approach was applied to analyze the real field data of an automobile component with incomplete information on covariates using the Weibull regression model. Model parameters were estimated using the expectation maximization algorithm. The results of the data analysis and simulation demonstrated that the D&R approach is applicable for analyzing such datasets. Further, the percentiles and reliability functions of the distribution under different covariate conditions were estimated to evaluate the component performance of these covariates. The findings of this study have managerial implications regarding design decisions, safety, and reliability of automobile components. [ABSTRACT FROM AUTHOR]

To identify which medications are mostly associated with ejaculatory disorders through a disproportionality analysis. The Food and Drug Administration Adverse Event Reporting System (FDA-FAERS) and the Eudra-Vigilance (EV) database were queried to identify medications more commonly associated to ejaculatory disorders from September 10, 2012 to June 1, 2023. Proportional Reported Ratios (PRRs) were computed for all the selected drugs. Overall, 7404 reports of ejaculatory disorders reports were identified, and of these, 6854 cases (92.6%) were attributed to ten specific medications. On FDA-FAERS and EV databases, Paroxetine and Tamsulosin were the main responsible of delayed ejaculation (103/448 events, 23.0%) and retrograde ejaculation (366/1033 events, 35.4%), respectively. Finasteride was mostly related to painful ejaculation and ejaculation failure, with 150 events (7.8%) and 735 events (38.4%) respectively. Within the group of high-risk medications, Sildenafil presented higher risk of ejaculatory disorders than Tadalafil (PRR = 5.85 (95%CI 5.09-6.78), P <.01). Ten drugs were recognized to display significant reporting levels of ejaculatory disorders. Among them, Finasteride and Sildenafil were responsible for the most reports in FDA-FAERS and in EV databases, respectively. Physicians should thoroughly counsel patients treated with these drugs about the risk of ejaculatory disorders. Further integration into clinical trials is needed to enhance the applicability and significance of these results. [ABSTRACT FROM AUTHOR]

Purpose: The objective of this paper is to analyze the evolution of and the latest knowledge in the scientific production on challenges and tensions for the management of social enterprises. Theoretical framework: the theoretical framework was the basis for the choices made regarding data collection and analyses. For that reason, the theoretical framework of this paper approached social enterprises definition, tensions in social enterprises, and bibliometrics and its fundamental laws. Method/design/approach: This article is based on the bibliometric method and our final database was composed of 479 articles from Web of Knowledge. Results and conclusion: We identified that more than 70% of the publications occurred in the last five years. The most cited papers provided important theoretical bases as they address the perspectives of organizational hybridism and social entrepreneurship. These theoretical approaches also converge after 2013. In addition, we identified 12 core journals and three thematic word clusters. Research implications: We expect to encourage new research within the social entrepreneurship and hybridism theoretical perspectives. We also present questions to be addressed related to how challenges and tensions for the management of social enterprises affect and are affected by decisions regarding value creation and distribution to stakeholders, reframing how stakeholders' divergent demands are related to tensions. Originality/value: This article presents a portrait of the literature related to tensions in social enterprises, highlighting the most cited works and authors, and pointing possible research gaps in this field. Objetivo: O objetivo deste artigo é analisar a evolução e o conhecimento mais recente da produção científica sobre os desafios e tensões para a gestão de empresas sociais. Estrutura Teórica: a estrutura teórica foi a base para as escolhas feitas em relação à coleta e análise de dados. Por essa razão, o quadro teórico deste artigo abordou a definição de empresas sociais, tensões em empresas sociais e bibliometria e suas leis fundamentais. Método/projeto/abordagem: Este artigo baseia-se no método bibliométrico e nossa base de dados final foi composta por 479 artigos da Web of Knowledge. Resultados e conclusão: identificamos que mais de 70% das publicações ocorreram nos últimos cinco anos. Os artigos mais citados forneceram importantes bases teóricas, uma vez que abordam as perspectivas do hibridismo organizacional e do empreendedorismo social. Essas abordagens teóricas também convergem após 2013. Além disso, identificamos 12 revistas principais e três grupos de palavras temáticas. Implicações da pesquisa: Esperamos incentivar novas pesquisas dentro das perspectivas teóricas do empreendedorismo social e do hibridismo. Apresentamos também questões a serem abordadas relacionadas ao modo como os desafios e tensões para a gestão de empresas sociais afetam e são afetados por decisões relativas à criação de valor e distribuição às partes interessadas, reformulando o modo como as exigências divergentes das partes interessadas estão relacionadas com tensões. Originalidade/valor: Este artigo apresenta um retrato da literatura relacionada a tensões em empreendimentos sociais, destacando os trabalhos e autores mais citados, apontando possíveis lacunas de pesquisa neste campo. [ABSTRACT FROM AUTHOR]

Introduction Airway compromise is the second leading cause of potentially preventable prehospital combat death. Endotracheal intubation (ETI) remains the most common role 1 airway intervention. Video laryngoscopy (VL) is superior to direct laryngoscopy (DL) for first-attempt intubation, especially in less-experienced providers and for trauma patients. The cost has been a major challenge in pushing VL technology far-forward; however, the cost of equipment continues to become more affordable. We conducted a market analysis of VL devices under $10,000 for possible options for role 1. Materials and Methods We searched Google, PubMed, and the Food and Drug Administration database from August 2022 to January 2023 with a combination of several keywords to identify current VL market options under $10,000. After identifying relevant manufacturers, we then reviewed individual manufacturer or distributor websites for pricing data and system specifications. We noted several characteristics regarding VL device design for comparison. These include monitor features, size, modularity, system durability, battery life, and reusability. When necessary, we requested formal price quotes from respective companies. Results We identified 17 VL options under $10,000 available for purchase, 14 of which were priced below $5,000 for individual units. Infium (n  = 3) and Vimed Medical (n  = 4) provided the largest number of unique models. VL options under $10,000 exist in both reusable and disposable modalities. These modalities included separate monitors as well as monitors attached to the VL handle. Disposable options, on a per-unit basis, cost less than reusable options. Conclusions Several VL options exist within our goal price point in both reusable and disposable options. Clinical studies assessing the technology performance of ETI and deliberate downselection are needed to identify the most cost-effective solution for role 1 dispersion. [ABSTRACT FROM AUTHOR]

The United States Food and Drug Administration Manufacturer and User Facility Device Experience (MAUDE) dataset represents a unique source for post-market surveillance data on adverse events (AE). An analysis of AE with percutaneous mechanical circulatory support (pMCS) devices has previously been reported specifically for microaxial flow pumps. The characteristic AE for the intra-aortic balloon pump (IABP) have not been similarly analyzed or reported. All events in the MAUDE dataset between January 1, 2016 and December 31, 2021 were reviewed involving the Linear, Mega and Sensation devices (Datascope/Getinge, Wayne New Jersey). Data was analyzed by two authors and categorized based on AE type, date, event type and device-related or patient-related AE. A total of 2795 AE were reported over five years. Device malfunction (91.4 %) was the most frequent classification followed by death (5.6 %) and injury (3.0 %). Catheter deformation/fracture/leak accounted for 37.9 % of total AEs. The most common patient event categorization was asymptomatic (90.8 %). Vessel damage/hemorrhage occurred in 1.4 % of reports. Death occurred in 5.6 % of reports and was associated with cardiac arrest in 110 of 156 events. Thrombus formation was described in 1.1 % of AEs. Device optic AE were common and unique to Sensation catheters. Calibration errors were also more common with Sensation (4.6 % versus 1.3 %) compared to other models. Publicly reported AE with IABPs are predominantly device malfunctions without clinical sequelae. Injury, vascular damage, bleeding and thrombosis AEs are not frequent amongst reported AEs. Emphasis should be placed on understanding mechanisms of device malfunction in order to improve both reliability and user experience. • Review of adverse events for Intra-Aortic Balloon Pumps from 2016 to 2021 • Adverse events for IABP mainly device malfunction without clinical sequelae. • Clinically important adverse events are infrequent but life threatening. [ABSTRACT FROM AUTHOR]

Gender pay gaps are present in a wide range of industries, with the medical profession being no exception. The aim of this systematic review was to analyse the peer-reviewed literature to identify whether there is a gender pay gap in orthopaedics. A systematic review was conducted by searching the following databases: MEDLINE, Health & Medical Collection, Nursing & Allied Health Database, Publicly Available Content Database, Consumer Health Database and Healthcare Administration Database. Original research papers pertaining to the earnings of male and female orthopaedic surgeons were included for review. Of 745 papers acquired through the database search, 12 were eligible for inclusion. These were published in the USA, Canada and Taiwan. 6 looked at the relationship between sex and annual income, 4 studied industry payments, one analysed hourly earnings and one compared payments per case between males and females. Men were found to earn significantly higher annual incomes than women, even when confounding factors such as rank, practice setting and subspeciality were accounted for. Men also receive significantly higher payments from industry, and earn more per hour than women. This systematic review has demonstrated that there is a gender pay gap in orthopaedics, with women commonly earning significantly less than their male colleagues. The reasons for this, however, remain unclear, and deserve further investigation. It is incumbent upon orthopaedic departments, healthcare providers and orthopaedic associations to raise awareness and ensure that men and women are paid the same for equal work. • There is a gender pay gap in orthopaedics • Women commonly earn significantly less than their male colleagues • Women more commonly pursue less lucrative subspecialties but the reason is unclear • Fee codes should be reviewed to ensure men and women are paid equally • Orthopaedic associations should consider raising awareness of the gender pay gap [ABSTRACT FROM AUTHOR]

Underlying information about failure, including observations made in free text, can be a good source for understanding, analyzing, and extracting meaningful information for determining causation. The unstructured nature of natural language expression demands advanced methodology to identify its underlying features. There is no available solution to utilize unstructured data for risk assessment purposes. Due to the scarcity of relevant data, textual data can be a vital learning source for developing a risk assessment methodology. This work addresses the knowledge gap in extracting relevant features from textual data to develop cause–effect scenarios with minimal manual interpretation. This study applies natural language processing and text‐mining techniques to extract features from past accident reports. The extracted features are transformed into parametric form with the help of fuzzy set theory and utilized in Bayesian networks as prior probabilities for risk assessment. An application of the proposed methodology is shown in microbiologically influenced corrosion‐related incident reports available from the Pipeline and Hazardous Material Safety Administration database. In addition, the trained named entity recognition (NER) model is verified on eight incidents, showing a promising preliminary result for identifying all relevant features from textual data and demonstrating the robustness and applicability of the NER method. The proposed methodology can be used in domain‐specific risk assessment to analyze, predict, and prevent future mishaps, ameliorating overall process safety. Summary: A novel approach is developed to offer insights from accident databases into what went wrong. It facilitates the implementation of the vast amount of data available and converts it into information that can be used effectively. This work presents an approach to performing a risk assessment using textual data. The approach consists of three methods, implemented systematically. First, natural language processing carries out feature extraction from the database. Second, the fuzzy set theory is used as a bridge to quantify natural language. Last, the Bayesian network is employed to assess objective risk from fuzzy probabilities. Five cases are used to demonstrate the application of the proposed approach, which predicts the correct risk level of all the failures that occurred. Thus, practitioners can use the methodology to predict objective risk levels based on observations. [ABSTRACT FROM AUTHOR]