Continuous Utilization Research Articles

Ethnobotanical uses of traditional African vegetables among three selected villages of Madibeng Local Municipality, South Africa

Abstract Traditional African vegetables have been an integral part of the local diet and traditional medicine practices for generations. However, with the increasing influence of modernisation and urbanisation, the knowledge and utilisation of traditional African vegetables have been gradually diminishing. This study investigated the indigenous knowledge and cultural significance of locally sourced leafy vegetables among households in three selected villages (Jericho, Bethanie, and Maboloka) within the Madibeng Local Municipality, North West Province, South Africa. A mixed method was used for data collection. A representative sample of households in the selected villages was obtained using snowball sampling. A total of 33 participants were interviewed from the three selected villages. The results revealed 11 traditional African vegetables consumed among the selected villages. The most common vegetables were Amaranthus hybridus L. (82%), Cucurbita maxima Duchesne ex Lam. (70%), Cleome gynandra L. (70%), and Phaseolus vulgaris L. var. vulgaris (60%). The utilisation of leafy vegetables was driven by factors such as health benefits, affordability, and cultural traditions. Furthermore, traditional knowledge and practices regarding the cultivation, harvesting, and preparation of leafy vegetables are still prevalent in these villages. Participants emphasised the importance of passing down this knowledge to future generations to ensure the continued utilisation and preservation of leafy vegetables. It was evident that traditional African vegetables remained an integral part of the diet in the selected villages of Madibeng Local Municipality. The cultural significance and traditional knowledge associated with these vegetables play a vital role in their utilisation.

THE EXPERIENCE OF SOCIAL WORKERS IN BIG DATA–BASED CARE SERVICES ON PREVENTING SOCIAL ISOLATION FOR OLDER ADULTS

Abstract In response to the increasing occurrence of social isolation among older adults in South Korea, local governments and ICT companies are collaborating to introduce various intelligent care initiatives based on big data, including AI care calls, AI speakers, and activity detection sensors. This study investigates the experiences of social workers providing on-site intelligent care services to older individuals living alone to prevent social isolation. Five focus group interviews involving 15 welfare officials and social workers were conducted. The findings are as follows. Firstly, they recognized biases regarding intelligent technology, such as concerns about privacy infringement, as barriers to identifying high-risk groups and accepting services. Secondly, challenging living environments with limited internet access and low digital literacy were acknowledged as obstacles hindering the sustained use of intelligent care services. Thirdly, the presence of personnel capable of providing education and support for smart device usage was deemed essential for the continued utilization of services. Fourthly, it was acknowledged that additional personnel and support beyond smart devices are necessary for groups with impaired vision, hearing, or mobility. Lastly, the involvement of social workers with a deep understanding of high-risk groups, from planning to evaluation of service models, was recognized as essential for enhancing the effectiveness and efficiency of services. Based on these findings, this study suggests practical and policy implications regarding intelligent living environments, digital literacy, ethics of artificial intelligence, caregiver training, and the involvement of social workers.

Microorganism-Derived Bisindole Alkaloids With Anticancer Potential and Their Mechanisms: A Comprehensive Review.

Bisindole alkaloids constitute a significant class of natural compounds distinguished by their characteristic bisindole structure and renowned for their anticancer properties. Over the last six decades, researchers have isolated 425 microorganism-derived bisindole alkaloids (MDBAs). Among them, 187 MDBAs have demonstrated anticancer properties against various in vitro cancer cell lines, primarily by impeding the cell cycle, restraining cell proliferation, and inducing apoptosis and autophagy. These effects are mediated by regulating key targets and signaling pathways such as hypoxia-inducible factor (HIF)-1, MAPK, and phosphatidylinositol 3-kinase (PI3K)/AKT/mTOR. This review provides a comprehensive examination of the sources, chemical diversity, and anticancer properties of these compounds. Furthermore, it summarizes the structure-activity relationship (SAR), druggability, and the mechanisms underlying MDBAs' anticancer effects. Ultimately, this article aims to furnish a thorough overview of the advancements in the investigation of microorganism-derived bisindole alkaloids for their continued development and utilization.

Research on Relationship Between Image Perception, Place Attachment and Tourists' Pro-environment Behavior

Ice and snow tourism, as a special way of tourism, is booming with the continuous development and utilization of ice and snow tourism resources in the world. China is rich in ice and snow tourism resources. In recent years, the ice and snow tourism industry has developed rapidly. However, problems such as ecological destruction and over-exploitation of resources have become increasingly prominent. In this context, pro-environment behavior has become an important means to alleviate the environmental pressure of ice and snow tourism destinations; At the same time, research on the relationship between the perceived image of ice and snow tourism destination, place attachment and tourists' pro-environment behavior has important theoretical value and practical significance for promoting the sustainable development of ice and snow tourism, enhancing tourists' environmental awareness and responsibility, and improving the image and attractiveness of ice and snow tourism destination. Based on the cognitive affective theory, place attachment, etc., and on the basis of literature research, this thesis proposes several hypotheses, constructs conceptual models, develops or cites corresponding measurement scales for the relationship among the four variables of cognitive image, emotional image, place attachment and pro-environment behavior, and takes Chongli Ski Resort as a case for empirical research. Using questionnaire survey data, the structural equation model of 264 valid questionnaires was analyzed to suggest the influence mechanism of cognitive image, emotional image and place attachment on tourists' pro-environment behavior. The findings are as follows: (1) Cognitive image has significant positive effects on affective image, place attachment and pro-environment behavior, and affective image and place attachment can mediate this process; (2) Emotional image has a significant positive impact on place attachment and pro-environment behavior, and place attachment can be used as a mediator to have a positive impact on them; (3) Place attachment has a significant positive effect on pro-environment behavior. As an emotional bond, it connects the emotional connection between tourists and tourist destinations. Accordingly, this study also puts forward the strategy to promote the tourists' pro-environment behavior in Chongli ski Resort in order to promote the sustainable development of ice and snow tourism. Including: (1) to enhance the attractiveness of ice and snow tourism; (2) Enhance the emotional connection between places and tourists; (3) Strengthen environmental awareness education. It is hoped that this study will have some reference value for the improvement of pro-environment behavior of tourists in other similar ice and snow tourism destinations.

Molecular mechanisms impact on fluoroquinolone resistance among E.coli from enteric carriage monitoring before prostate biopsy and earliest description of qnrB81

Fluoroquinolone-resistant (FQs-R) microorganisms causing infectious complications after ultrasound-guided needle biopsy of the prostate (TRUS-BP) have become an important challenge in healthcare settings globally, questioning the continued utility of FQ as the preferred prophylactic agent. This study aimed to characterize molecular mechanisms of resistance on FQs-R E. coli isolated from the enteric microbiota of patients undergoing (TRUS-BP) and to highlight their impact on Minimum Inhibitory Concentrations (MICs). From February 2016 to December 2018, the incidence of rectal carriage of Qs-FQs resistant Enterobacterales detected from rectal swabs of patients before undergoing (TRUS-BP) was 61.06% (80/131) all related to E. coli species. Based on the MICs range of Qs (24–256 mg/L) and FQs (0.24–128 mg/L) breakpoint by EUCAST, we categorized these E. coli isolates into three resistance profiles (I, II, and III) associated with the patterns of chromosomal mutations in the quinolone resistance-determining regions (QRDRs) of gyrA and parC and the plasmid-mediated quinolone resistance encoding genes (PMQRs) detected by PCR-based assay and sequencing; MICs increase in an escalation step according to the co-occurrence of multiple molecular mechanisms. The mutation of the gyrA gene was the most frequent on codons (Ser83Leu/Thr/Tyr/Trp and Asp87Asn); mutation on the parC gene was the least on codons (Ser80Iso/Leu and Glu84 Val/Gly/Lys). PMQRs genes (4 qnrB ,7 qnrS, and one aac(6’)-Ib-cr) were determined within 15% of the isolates. Allelic variation allows us to report earliest the qnrB81 determinant in an E. coli isolate. Among isolates (35%) belonged to the notorious ST131 lineage. The phylogenetic group showed a predominance of B2 group (51, 25%), however (PFGE) revealed a high level of clonal variability. Worrying incidence of FQs-R E. coli isolates in the rectal flora of our local population showed the potential to cause post-infection. FQ resistance is a complex interplay between mutations in the QRDRs and PMQR determinants that impact MICs. The importance of intestinal microbiota as a reservoir of resistant strains and pandemic clones encourages driving mitigation challenges to characterize molecular mechanisms of antimicrobial resistance to adapt prophylactic therapy, control infection, and ensure epidemiological monitoring.

Evaluate the Differential Effectiveness of the Case Management and Primary Nursing Models in the Implementation of Discharge Planning.

This study aims to compare the effectiveness of the case management model and the primary nursing care model by focusing on hospital stay length, readmission, follow-up resource utilisation and survival. To improve patient continuity of care, a discharge planning team has been established at the hospital to implement the service concept of long-term medical care. The team works with a multidisciplinary medical team to provide case management, which ensures high-quality patient care. Retrospective case-control study. This study collected data from the medical record information system database and the Ministry of Health and Welfare's care service management information system to explore medical and follow-up care utilisation of patients discharged between 2017 and 2018. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines, with the checklist used to ensure transparent and complete reporting of the methodology and results. To ensure comparability between the case management model group and the primary nursing model group, propensity score matching was used. After matching, 660 individuals from the case management model group and 2876 individuals from the primary nursing model group were selected for further analysis. In this study, patients were primarily involved in the research as participants, providing data through their medical records for analysis. However, no direct involvement from the public or patients was used in the planning or design stages of the research. The study found that factors such as activities of daily living (ADL) score ≤ 60 points, catheterisation, poor chronic disease control and inadequate primary caregiver capacity can lead to longer hospitalisations. Males and patients with catheters have a higher risk of readmission within 30 days, and men, those aged ≥ 75 years, those with ADL score ≤ 60, catheterisation, pressure sores or unclean wounds, financial problems, insufficient primary caregiver capacity and those readmitted within 14 days after discharge had significantly increased mortality after discharge. Although the case management model group had higher hospitalisation days, they had lower readmission rates and higher survival rates than the primary nursing model group. Early consultation with the case manager for discharge planning can help patients to continue to receive care and utilise relevant resources after returning home. Identifying and addressing patient-specific factors can significantly improve patient outcomes by reducing hospitalizations and readmissions, and lowering mortality rates. The case management model is more effective than the primary nursing care model in reducing readmission rates and increasing survival rates. Early consultation with case managers for discharge planning is crucial to ensuring patient care continuity and resource utilization.

Comparative Analysis of Sustainable AI Techniques Used to Reduce the Carbon Footprints in the Healthcare Sector

The healthcare sector plays an important role in human well-being, however, the continuous utilization of its resources has led to environmental degradation. It has become one of the reasons for climate change, primarily through significant carbon emissions and misuse of clinical equipment. With the advancement in ongoing research, efforts are being made for sustainable healthcare development. This review paper compares the existing models and approaches based on sustainable AI to reduce carbon footprints within the healthcare sector. The paper presents a detailed study of existing literature and initiatives that use AI-driven solutions to make healthcare services more eco-friendly and economically feasible. This paper presents how AI technologies, including machine learning, data analytics, Deep Learning, and optimization algorithms, are being applied in the Supply chain, clinical trials, predictive management, and various other departments of Medicine to prevent carbon emissions arising from infrastructure, data centers, transportation, and medical equipment. Keywords: Healthcare, Carbon Footprints, Sustainable AI, Deep Learning, Machine Learning, Predictive Management

Flowing Forward: Continuous Synthesis of and with Ionic Liquids

AbstractHerein, the developments in the field of continuous ionic liquid synthesis and continuous ionic liquid utilization from the last seven years are reviewed. Starting by discussing recent strategies for the preparation of ionic liquids themselves in different flow reactors, the review will further focus on various continuous strategies employing ionic liquids. The application of ionic liquids in continuous processes, particularly as supported catalytic layers, has drawn significant scientific interest in the last decades. These catalyst frameworks provide a versatile tool in many organic transformations, and their application became an attractive strategy in continuous catalytic approaches.

Highly Accurate Customer Churn Prediction in the Telecommunications Industry Using MLP

Predicting customer Churn is of principal importance for many businesses, as it directly influences the continued utilization of company products by consumers and has a significant impact on company’s financial health and sustainability. However, accurately forecasting customer attrition within the telecommunications sector presents considerable challenges. In response to this need, we propose a novel and highly accurate churn prediction model utilizing a Multilayer Perceptron (MLP) architecture. Our methodology begins with thorough data preprocessing, followed by the application of MLP to predict customer Churn. By employing the Synthetic Minority Over-sampling Technique (SMOTE) and iterative balancing, our proposed model has demonstrated an accuracy improvement of at least 5%, alongside a minimum 5% increase in the F1-score, when compared to existing state-of-the-art algorithms on the widely recognized Telco-Customer-Churn dataset. This research not only expands the opportunities for enhancing the interpretability of predictive models but also fosters a deeper understanding of Churn prediction mechanisms. Ultimately, these advancements contribute to the commercial sustainability and financial stability of telecommunications companies by facilitating more informed decision-making processes regarding customer retention strategies.

Three-Dimensional Culture of Glioblastoma Cells Using a Tissueoid Cell Culture System.

In classical cell culture techniques, cancer cells typically proliferate in a single layer by adhering to the undersurface of laboratory vessels. Consequently, concerns have been raised regarding the fidelity of the morphological and functional characteristics of these cultured cancer cells compared to those of their in vivo counterparts. Our previous studies have investigated various epithelial malignant tumors utilizing the Tissueoid cell culture system, a three-dimensional (3D) cultivation method employing Cellbed-a nonwoven sheet composed of high-purity silica fibers as a scaffold. In this investigation, we have achieved successful 3D culturing of glioblastoma cells (A172 and T98G), which are non-epithelial in nature. As such our focus is to juxtapose their morphological features against that of those cultivated via conventional two-dimensional (2D) methods. Our findings will be elucidated using immunostaining, immunofluorescence staining, and scanning electron microscopy, substantiated with accompanying imaging. Notably, cells cultured in the 3D environment exhibited distinct morphological attributes compared to those of their 2D counterparts, notably featuring pronounced cellular protrusions. We envisage the continued utilization of the 3D culture platform to facilitate diverse avenues of research, encompassing the exploration of novel therapeutic modalities for glioblastoma cells and beyond.

Thermodynamic analysis of a novel compressed carbon dioxide energy storage coupled dry methane reforming system with integrated carbon capture

Chemical absorption CO2 capture, compressed carbon dioxide energy storage (CCES) and dry reforming of methane (DRM) can be used for continuous carbon capture, storage and utilization. However, CO2 capture is often accompanied by significant energy consumption. Considering the waste high-grade thermal energy at the exit of solar methane reforming, the article proposes a coupled system in which the thermal energy at the exit of the DRM system is used in CCES to improve the system's work capacity, and the remaining heat and the compression heat of the CCES are used for CO2 capture. The study established mathematical models of the three subsystems, performed thermodynamic analyses, and completed experiments on dry reforming of methane. The results show that the coupled system can increase the electro-electric conversion efficiency by 150.49 % reaching 220.33 % and the energy efficiency by 7.25 % reaching 77.09 %. The coupled system can save up to 43.33 % of CO2 capture heat. The DRM subsystem can utilize the higher temperature CO2 in the tail end of the CCES system, and its methane conversion efficiency and solar-fuel efficiency can be increased by 3.54 % and 3.20 % respectively to reach 58.22 % and 61.02 %. And the economic analysis found that the coupled system has better economics.

The Adversarial Robust and Generalizable Stereo Matching for Infrared Binocular Based on Deep Learning.

Despite the considerable success of deep learning methods in stereo matching for binocular images, the generalizability and robustness of these algorithms, particularly under challenging conditions such as occlusions or degraded infrared textures, remain uncertain. This paper presents a novel deep-learning-based depth optimization method that obviates the need for large infrared image datasets and adapts seamlessly to any specific infrared camera. Moreover, this adaptability extends to standard binocular images, allowing the method to work effectively on both infrared and visible light stereo images. We further investigate the role of infrared textures in a deep learning framework, demonstrating their continued utility for stereo matching even in complex lighting environments. To compute the matching cost volume, we apply the multi-scale census transform to the input stereo images. A stacked sand leak subnetwork is subsequently employed to address the matching task. Our approach substantially improves adversarial robustness while maintaining accuracy on comparison with state-of-the-art methods which decrease nearly a half in EPE for quantitative results on widely used autonomous driving datasets. Furthermore, the proposed method exhibits superior generalization capabilities, transitioning from simulated datasets to real-world datasets without the need for fine-tuning.

Cause of death for heart transplant patients, an autopsy study

IntroductionHeart transplantations are lifesaving for patients with end-stage heart failure. It is pertinent for the multidisciplinary care team to understand how heart transplant patients succumbed to death and the complications that occurred. In this study, we performed a comprehensive retrospective review of all the autopsies performed in our institute for heart transplant patients and report the trend of demographic data, cause of death, and autopsy findings. Materials and methodsReports, photos, and slides of autopsies performed at our institute from 1990 to 2023 for heart transplant patients were reviewed. Pertinent demographic data (age, gender, pretransplant diagnosis), clinical data (clinical history of rejection, complication, time interval from transplant to death, clinical cause of death) and pathological findings (allograft pathology, infectious etiology, other findings related to cause of death) were reviewed, documented, and analyzed. ResultsWe identified 88 cases, consisting of 53 male and 35 female patients. The median age at transplant was 26 years, while 28.5 years was the median age at death. The median interval from transplant to death was 10 months. The cases were classified in three categories based on length of survival post-transplant: Superacute (<1 month, 21%), Early (1 month-12 months, 30%), and Late (> 12 months, 49%). Slides were unavailable for review in 15 cases, which were excluded from cause of death (COD) evaluation. We categorized 41.1% of cases as allograft-related COD and 58.9% as non-allograft-related COD. Six of the CODs were not perceived premortem. These unexpected CODs included moderate/severe acute cellular rejection in a patient with a recently negative biopsy, dehiscent suture caused by a fungal abscess, an aorto-bronchial fistula, CMV myocarditis, acute abdominal bleeding, and ruptured atherosclerotic plaques with acute myocardial infarction. ConclusionWe systematically reviewed 33 years of heart transplant autopsies. We found that 41.1% of deaths were allograft related, with infection being the most frequent COD. While the rate of unexpected findings was low, the findings demonstrate the continued utility of autopsy in patient evaluation.

Narrowband-UVB-emitting gadolinium-doped yttrium oxide nanofilm on xenon excimer lamp for phototherapy

The continuous utilization of ultraviolet (UV) light sources within both academic and industrial contexts necessitates the imperative advancement of alternative UV sources to replace hazardous mercury lamps. Herein, we proposed a mercury-free narrowband UVB (NB-UVB)-emitting device from Y2O3:Gd3+ nanofilm on a tubular quartz substrate. The nanofilm is fabricated utilizing the spin-coating sol-gel precursor technique and is subsequently synthesized via a high-annealing temperature solid-state reaction. This synthesis resulted in the formation of a single-phase cubical structure of Y2O3 characterized by a crack-free morphology. The NB-UVB radiative output with a peak at 315 nm is generated through vacuum UV-induced photoluminescence originating from the emission of Xe excimer, which subsequently excites the Gd3+ luminescent centers incorporated within the Y2O3 host matrix. Moreover, in a high-voltage bipolar power system operating at 19 kV and 19 kHz, the device exhibited an NB-UVB radiance output of 1.34 mW, accompanied by a power efficiency of 0.02 %, whilst preserving exceptional temporal performance. Thus, this investigation introduces an innovative perspective on a mercury-free NB-UVB-emitting device, thereby promoting further exploration into the application of UV radiation sources derived from excimer lamp technology.

TERAPAN ETOS KAIZEN DALAM “MENINGKATKAN KELAS” BISNIS KULINER BERKEARIFAN LOKAL

This community service activity aims to provide counseling to the UMKM Association of Komunitas Sukses Berjamaah Indonesia (KSBI) in South Jakarta regarding the application of the Kaizen ethos in improving the quality and success of their culinary business based on local wisdom. This counseling aims to provide an understanding of the concept of Kaizen ethos and encourage KSBI members to apply it in their culinary business. In this activity, an interactive approach method was used through discussions and case studies to understand the potential for improving local wisdom-based culinary businesses. The participants were invited to identify problems, challenges, and opportunities in their culinary business, as well as to utilize local wisdom as an added value in the business. Key Kaizen principles, such as elimination of waste, quality improvement, employee engagement, and continuous improvement cycle, were explained and applied in the context of KSBI's culinary business. Through the delivery of implementation strategies and successful case examples, participants were given practical guidance to apply the Kaizen ethos in their culinary business. In addition, Q&amp;A and discussion sessions provided an opportunity for KSBI members to share their experiences and obtain solutions to the questions and problems they faced. The results of this activity had a positive impact on the members of the UMKM Community Sukses Berjamaah Indonesia (KSBI) in South Jakarta, focusing on continuous improvement and utilization of local potential, the participants managed to improve their operational efficiency and the quality of their culinary products. Awareness of the importance of innovation and adaptation to market changes has also increased, thus opening up opportunities to expand markets and strengthen the competitiveness of local wisdom-based culinary businesses through the application of the Kaizen ethos.

Integrating Sustainable Educational Innovations and Spatial Cognition: A Study of Factors Affecting College Students’ Sustainable Learning Behavior in Virtual Simulation Environments

Objective: This study investigated the factors influencing college students’ continuous utilization intention of virtual simulation software (Animation Character Virtual Simulation Software V1.0) in the context of current efforts to promote sustainable educational practices and explored design strategies to enhance this willingness in a sustainable manner. Method: Based on the Expectation Confirmation Model of Information System Continuance (ECM-ISC), this study developed a model to examine the impact of college students’ spatial ability (SA) on their virtual simulation learning behavior. Upon administering a questionnaire to the selected participants (N = 164), the survey data were analyzed for reliability and validity. Subsequently, the relationships among the model’s variables were explored. Result: For college students majoring in Digital Media Art, spatial ability significantly positively affects their sustainable utilization intention of virtual simulation software within 3D virtual scenarios. Meanwhile, it positively impacts perceived ease of use (PEU) and flow experience (FE), which are key factors in promoting the sustainable adoption of such technologies. The introduced spatial ability, perceived ease of use, and flow experience influence the endogeneity of the ECM-ISC. Moreover, gender differences in spatial ability are profound among these students. Conclusion: The primary influencing pathway is spatial ability → flow experience → expectation confirmation → perceived usefulness → continuous utilization intention. Enhancing spatial ability is one effective way to advance virtual simulation software, offering new insights for its design and long-term improvement in alignment with sustainable educational practices.

12242 Enhancing Continuous Glucose Monitor Utilization In Lower Economic Community Hospital Outpatient Clinics: A Quality Improvement Initiative

Abstract Disclosure: V. Mehta: None. S. Deshpande: None. M. Nieman: None. K. Pereira: None. B. Agrawal: None. S.R. Russell: None. Continuous glucose monitors (CGM) measure the blood glucose level (BGL) and have been used for better glucose control, especially in patients requiring insulin. Primary care physicians (PCP) manage diabetic patients on a large scale in the US, especially in rural settings, and data shows that CGMs are prescribed less in PCP settings than in endocrine clinics. Our study aimed to understand internal medicine (IM) residents' knowledge about CGMs and their application in a community hospital outpatient clinic serving lower-economic populations and demonstrates how a clinical pharmacist (PharmD) led educational intervention successfully increased the adoption of CGMs. A survey was done using a form with multiple-choice questions. 50 residents participated and responded anonymously. Data was analyzed by calculating percentages based on answers, providing understanding of their perspectives on CGMs. 78% knew about and correctly identified CGM. When asked to name indications of CGM, answers varied and included uncontrolled diabetes (34%), insulin-dependent diabetes (34%), elderly and non-compliant patients (14%), any diabetic (12%), and others. Only 14% reported to have had formal training in use and interpretation of CGMs, 70% had prescribed, 34% knew how to apply the device, and 42% knew how to interpret the BGL. More than 95% self-reported having either poor/beginner or fair knowledge about the usage, application, and interpretation, whereas more than 80% professed to need more training to be more confident about prescribing the device. After the survey, our PharmD conducted session demonstrating the indications, types, usage, application, and interpretation of CGM. Following this, an impactful increase in patients who were appropriately prescribed and received CGM was observed. Technologies used in medicine have increased, CGM, being one of them. More than 100 million Americans have prediabetes or diabetes, with more than 10 million using insulin. Hence, access to CGM is crucial for patients for better management. Despite the benefits, many factors play a role in limiting their use, including prescription, cost, insurance coverage, social factors, willingness of the patients, discomfort, and decreased knowledge. Non-compliance, difficulty in application and picking the device from pharmacy was also observed in our clinic. A study by Sherrill et al. on use of CGMs (2014-2020) showed that use of CGM increased almost ten times in 2020 (v/s2014); most patients were younger, employed, and had better insurance coverage.With advances in technology, easier and more efficient devices are available to assess patients' glycemic control. Pharmacists play key role in ensuring continued education among practitioners and trainees. Continued efforts to increase awareness is required to ensure that latest advances are adequately incorporated into graduate medical education. Presentation: 6/3/2024

6894 Disparities in Continuous Glucose Monitor Utilization and Real-Time Remote Sharing in Patients with Type 2 Diabetes Treated with Insulin on Medicare

Abstract Disclosure: K.L. Flint: None. T. Ting: None. K. Rivera: None. P. Tamang: None. C.A. Colling: None. J.H. Li: None. M.S. Putman: Consulting Fee; Self; Synspira Therapeutics. Research Investigator; Self; Dexcom. Other; Self; Vertex Pharmaceuticals Incorporated. Introduction: Continuous glucose monitors (CGM) are FDA-approved for the management of diabetes and have been shown to improve glycemic control. For optimal utilization, CGM can be connected to cloud-based clinic portals for real-time sharing of glycemic data with clinicians to guide clinical care. Although studies have previously identified disparities in access to CGM for patients who receive Medicare, limited data are available examining disparities in CGM utilization and data sharing. Hypothesis: We hypothesized that racial and socioeconomic disparities in CGM access exist both in utilization and in real-time remote sharing of CGM data. Methods: This was a retrospective cohort study examining patients with type 2 diabetes on insulin using Medicare as primary or secondary insurance in a single diabetes clinic affiliated with a tertiary care medical center. Clinical data extracted from the electronic health record (EHR) included age, self-reported race and ethnicity, sex, preferred language, education level, ZIP code-based median household income, and enrollment in the EHR-patient portal. The most recent diabetes clinic note for each patient as of October 2023 was reviewed to assess whether each patient was using CGM at the time of the visit. The clinic’s CGM portal accounts were reviewed to assess whether the patient was connected to and actively sharing CGM data with the clinic. Two sample t-tests and chi-square tests were used to evaluate continuous and categorical predictors of CGM use and real-time remote sharing, respectively. Results: Of the 847 patients who qualified for inclusion, 420 (49.6%) were using CGM and 213 (25.1%) were sharing CGM data in real-time. Compared to patients not using CGM (n=427), patients using CGM were younger (70.8 years vs 73.5 years, p&amp;lt;0.001) and more often enrolled in the EHR-based patient portal (91.9% vs 84.1%, p&amp;lt;0.001); however, there were no differences in racial, ethnic, or socioeconomic factors between the groups (p&amp;gt;0.05 for all). Of the patients using CGM, remote sharing of data was associated with younger age (69.5 years vs 72.3 years, p&amp;lt;0.01), identifying as White (74.2% vs 65.0%, p=0.04), using English as preferred language (92.5% vs 84.2%, p=0.02), higher levels of education (p=0.01), and using the EHR-based patient portal (97.2% vs 86.7%, p&amp;lt;0.001). Conclusions: In this cohort of patients with type 2 diabetes on insulin receiving Medicare, there were no significant socioeconomic disparities in CGM utilization. However, racial and socioeconomic disparities were pronounced in real-time remote sharing of CGM data, suggesting that patients from minoritized racial backgrounds, patients who do not use English as their preferred language, and patients with less education may benefit from additional support and training to connect and share their CGM with their providers. Presentation: 6/2/2024

Empowering Users with ChatGPT and Similar Large Language Models (LLMs): Everyday Information Needs, Uses, and Gratification

ABSTRACTDisruptive technologies such as ChatGPT and similar Large Language Models (LLMs) have transformed mundane everyday tasks of information users since their debut in late 2022. In this study, we leverage uses and gratifications theory to test a distinct set of motivations that drive users' satisfaction and continued use intentions of ChatGPT and similar large language models. Data were collected using a national online survey of 323 adults residing in the United States. We conducted data analysis using Partial Least Squares (PLS‐SEM) to investigate both direct and indirect impact of factors on users' gratification, thereby influencing the continued utilization of these tools for everyday information seeking. Results show four motivational factors ‐ social influence, trust, personalization, and perceived usefulness ‐ that positively influence users' satisfaction or sense of gratification, impacting their intentions to continue using these tools. This is one of the few early studies of ChatGPT and other LLMs from an information science perspective.

High radiative forcing climate scenario relevance analyzed with a ten-million-member ensemble

Developing future climate projections begins with choosing future emissions scenarios. While scenarios are often based on storylines, here instead we produce a probabilistic multi-million-member ensemble of radiative forcing trajectories to assess the relevance of future forcing thresholds. We coupled a probabilistic database of future greenhouse gas emission scenarios with a probabilistically calibrated reduced complexity climate model. In 2100, we project median forcings of 5.1 watt per square meters (5th to 95th percentiles of 3.3 to 7.1), with roughly 0.5% probability of exceeding 8.5 watt per square meters, and a 1% probability of being lower than 2.6 watt per square meters. Although the probability of 8.5 watt per square meters scenarios is low, our results support their continued utility for calibrating damage functions, characterizing climate in the 22nd century (the probability of exceeding 8.5 watt per square meters increases to about 7% by 2150), and assessing low-probability/high-impact futures.