bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sewer Inlets Detection in UAV Images Clouds based on Convolution Neural Networks
Authors: Ibrahim Haysam M. , Fawaz Essam M. , El Sheshtawy Amr M. , Hamdy Ahmed M. 
Published: June 2024

Background
Unmanned aerial vehicle (UAV) systems have underwent significant advancements in recent years, which enabled the capture of high-resolution images and accurate measurements, with the tremendous development in artificial intelligence, especially deep learning techniques, Which allows it to be used in the development of Drainage infrastructures that represent a major challenge to confront the flood risks in urban areas and represent a considerable investment, but they are often not as well classified as they should be.

Methods
In this study, we present an automatic framework for the detection of sewer inlets and Ground Control Points (GCPs) from image clouds acquired by an Unmanned Aerial Vehicle (UAV) based on a YOLO CNN architecture. The framework depends on the high image overlap of unmanned aerial vehicle imaging surveys. The framework uses the latest YOLO model trained to detect and localize sewer inlets and Ground Control Points (GCPs) in aerial images with a ground sampling distance (GSD) of 1 cm/pixel. Novel Object-detection algorithms, including YOLOv5, YOLOv7, and YOLOv8 were compared in terms of the classification and localization of sewer inlets and GCPs marks. The approach is evaluated by cross-validating results from an image cloud of 500 UAV images captured over a 40,000-m2 study area with 30 sewer inlets and 90 GCPs. To analyze the model accuracy among classes, two-way ANOVA is used.

Results
Images with models’ performances from the literature, the new YOLO model tested on UAV images in this study demonstrates satisfactory performance, improving both precision and recall. The results show that YOLOv5 offers the best precision (91%) and recall (96%), whereas YOLOv8 achieved less accuracy in precision and recall (82%) and (80%), respectively. Additionally, increasing image size in the training stage is a very important modification in the model.

Conclusion
The study approach has a remarkable ability to detect sewer inlets and can be used to develop the inventory of drainage infrastructure in urban areas.
Explicating the Phyto-pharmacological Virtues of Solanum torvum Swartz: A Contemporary Update
Authors: Garg Madhukar , Vaid Lavish , Sharma Parth , Rani Nidhi , Deswal Geeta , Grewal Sonam , Dhingra Ashwani K. , Tailor Navin Kumar , Grewal Ajmer Singh 
Published: June 2024

Abstract:
Solanum torvum Swartz has been considered to shed light on the diverse phytochemical
and pharmacological abilities relevant to its profound health benefits. The present review attempted
to emphasize the phytochemical and pharmacological investigations on Solanum torvum Swartz.
Furthermore, the investigators aimed to provide an elaborative outline regarding the tissue culture
studies of the mentioned plant. This plant has been reported to contain various types of
phytoconstituents, including alkaloids, alkaloid glycosides, allenes, coumarins, diterpenoids, fatty
acid esters, fatty acids, flavonoids, isoflavones, furan derivatives, glycosides, lignans,
monoterpenoids, phenolic acids, sesquiterpenoids, saponins, steroidal derivatives, and triterpenoids.
An array of pharmacological activities has been reported for this plant, including hypotensive, antiplatelet
aggregation, anti-ulcerogenic, antimicrobial, analgesic, anti-inflammatory, antioxidant,
immunomodulatory, wound healing, antiparasitic, larvicidal, antimalarial, anti-trichomonal,
leishmanicidal, anticancer, diuretic, anxiolytic, antidepressant, antidiabetic, anthelmintic, thrombolytic,
antiarthritic, antihyperlipidemic, hepato-protective, anti-Alzheimer, and cardioprotective activities.
This work provides researchers with up-to-date information on the health benefits of plants
attributed to their bioactive compounds. The information highlights the need for further research to
develop novel formulations using these bioactive principles for potential treatment and preventive
medicine applications targeting various ailments.
Triage Performance Across Large Language Models, ChatGPT, and Untrained Doctors in Emergency Medicine: Comparative Study
Authors: Masanneck Lars , Schmidt Linea , Seifert Antonia , Kölsche Tristan , Huntemann Niklas , Jansen Robin , Mehsin Mohammed , Bernhard Michael , Meuth Sven G , Böhm Lennert , Pawlitzki Marc 
Published: June 2024

Background
Large language models (LLMs) have demonstrated impressive performances in various medical domains, prompting an exploration of their potential utility within the high-demand setting of emergency department (ED) triage. This study evaluated the triage proficiency of different LLMs and ChatGPT, an LLM-based chatbot, compared to professionally trained ED staff and untrained personnel. We further explored whether LLM responses could guide untrained staff in effective triage.

Objective
This study aimed to assess the efficacy of LLMs and the associated product ChatGPT in ED triage compared to personnel of varying training status and to investigate if the models’ responses can enhance the triage proficiency of untrained personnel.

Methods
A total of 124 anonymized case vignettes were triaged by untrained doctors; different versions of currently available LLMs; ChatGPT; and professionally trained raters, who subsequently agreed on a consensus set according to the Manchester Triage System (MTS). The prototypical vignettes were adapted from cases at a tertiary ED in Germany. The main outcome was the level of agreement between raters’ MTS level assignments, measured via quadratic-weighted Cohen κ. The extent of over- and undertriage was also determined. Notably, instances of ChatGPT were prompted using zero-shot approaches without extensive background information on the MTS. The tested LLMs included raw GPT-4, Llama 3 70B, Gemini 1.5, and Mixtral 8x7b.

Results
GPT-4–based ChatGPT and untrained doctors showed substantial agreement with the consensus triage of professional raters (κ=mean 0.67, SD 0.037 and κ=mean 0.68, SD 0.056, respectively), significantly exceeding the performance of GPT-3.5–based ChatGPT (κ=mean 0.54, SD 0.024; P<.001). When untrained doctors used this LLM for second-opinion triage, there was a slight but statistically insignificant performance increase (κ=mean 0.70, SD 0.047; P=.97). Other tested LLMs performed similar to or worse than GPT-4–based ChatGPT or showed odd triaging behavior with the used parameters. LLMs and ChatGPT models tended toward overtriage, whereas untrained doctors undertriaged.

Conclusions
While LLMs and the LLM-based product ChatGPT do not yet match professionally trained raters, their best models’ triage proficiency equals that of untrained ED doctors. In its current form, LLMs or ChatGPT thus did not demonstrate gold-standard performance in ED triage and, in the setting of this study, failed to significantly improve untrained doctors’ triage when used as decision support. Notable performance enhancements in newer LLM versions over older ones hint at future improvements with further technological development and specific training.
Examining HIV Testing Coverage and Factors Influencing First-Time Testing Among Men Who Have Sex With Men in Zhejiang Province, China: Cross-Sectional Study Based on a Large Internet Survey
Authors: He Lin , Jiang Tingting , Chen Wanjun , Jiang Shaoqiang , Zheng Jinlei , Chen Weiyong , Wang Hui , Ma Qiaoqin , Chai Chengliang 
Published: June 2024

Background
Men who have sex with men (MSM) constitute a significant population of patients infected with HIV. In recent years, several efforts have been made to promote HIV testing among MSM in China.

Objective
This study aimed to assess HIV testing coverage and factors associated with first-time HIV testing among MSM to provide a scientific basis for achieving the goal of diagnosing 95% of patients infected with HIV by 2030.

Methods
This cross-sectional study was conducted between July 2023 and December 2023. MSM were recruited from the “Sunshine Test,” an internet platform that uses location-based services to offer free HIV testing services to MSM by visiting the WeChat official account in Zhejiang Province, China. Participants were required to complete a questionnaire on their demographic characteristics, sexual behaviors, substance use, and HIV testing history. A logistic regression model was used to analyze first-time HIV testing and its associated factors.

Results
A total of 7629 MSM participated in the study, with 87.1% (6647) having undergone HIV testing before and 12.9% (982) undergoing HIV testing for the first time. Multivariate logistic regression analysis revealed that first-time HIV testing was associated with younger age (adjusted odds ratio [aOR] 2.55, 95% CI 1.91-3.42), lower education (aOR 1.39, 95% CI 1.03-1.88), student status (aOR 1.35, 95% CI 1.04-1.75), low income (aOR 1.55, 95% CI 1.16-2.08), insertive anal sex role (aOR 1.28, 95% CI 1.05-1.56), bisexuality (aOR 1.69, 95% CI 1.40-2.03), fewer sex partners (aOR 1.44, 95% CI 1.13-1.83), use of rush poppers (aOR 2.06, 95% CI 1.70-2.49), unknown HIV status of sex partners (aOR 1.40, 95% CI 1.17-1.69), lack of awareness of HIV pre-exposure prophylaxis (aOR 1.39, 95% CI 1.03-1.88), and offline HIV testing uptake (aOR 2.08, 95% CI 1.80-2.41).

Conclusions
A notable 12.9% (982/7629) of MSM had never undergone HIV testing before this large internet survey. We recommend enhancing HIV intervention and testing through internet-based platforms and gay apps to promote testing among MSM and achieve the target of diagnosing 95% of patients infected with HIV by 2030.
PENSAMENTO COMPUTACIONAL: UMA OFICINA PEDAGÓGICA PARA PROFESSORES DE CIÊNCIAS
Authors: Teixeira Risiberg Ferreira , Cardoso Giovana da Silva , Jesus Vitor Luiz  Bastos de , Oliveira Alexandre  Lopes de 
Published: June 2024

O desenvolvimento do Pensamento Computacional pode ser uma abordagem eficaz que possibilita o aprendizado de uma variedade de disciplinas, como as ciências, além de aprimorar as habilidades do raciocínio lógico para criação de jogos educacionais. Devido a isso, foi elaborado e executado uma oficina pedagógica para vivenciar os fundamentos do Pensamento Computacional para o público-alvo formado por licenciandos e professores da educação básica. O objetivo da oficina foi levantar os requisitos de informações que podem fundamentar a elaboração de um curso de extensão para formação de professores. O estudo utilizou uma metodologia qualitativa de abordagem interpretativa e observação participativa. Para a coleta de dados, formulários foram preenchidos pelos participantes para determinar suas percepções sobre a oficina. Os resultados da oficina apontaram o caminho para a elaboração do curso de extensão sobre Pensamento Computacional.
1-PUB: Impaired Kidney Function in Diabetic Patients—A Warning
Authors: SABOO BANSHI D. , GUPTA AMIT , JOSHI SHASHANK R. , KESHAVDEV JOTHYDEV , JOSHI RAJA , PANCHOLI MANN N. , PATEL RIA , KALOO SUPRIYA , VERMA GARIMA 
Published: June 2024

Introduction & Objective: Diabetic patients contribute to the major burden of DKD and there is a severe dearth of testing for the renal parameters responsible for the development and progression among diabetic patients. In this study, we studied the screening results of the investigations patients underwent testing.
Methods: Data extracted from HealthPlix EMR (https://healthplix.com/) was studied.
Results: In 2022, only 25% of the 1.7 million diabetic patients got tested and the overall average for testing was 24% across the time period of 2018-2022. 37% of the patients who got themselves tested for one or more renal parameters (creatinine or ACR or eGFR or albumin) at least once a year didn’t fall within the prescribed ranges (Figure 1). Creatinine levels were seen to be elevated in approximately 29% (average) of the patients (22% of the diabetic population who tested for creatinine levels). It was observed that out of 21% of the diabetic patients who got eGFR investigated in 2022, 25% had decreased eGFR. 3% of diabetic patients got themselves tested for ACR in 2022. Of this pool, 37% of the patients had a ratio beyond 30 mg/g.
Conclusion: Among the patients who got themselves tested, there is a significant proportion of patients who don’t fall within the prescribed limits. These numbers would have been significantly higher than now if there had been no gap between expectations and reality. Hence, regular screening is important to prevent future complications.

Disclosure
B.D. Saboo: None. A. Gupta: None. S.R. Joshi: Consultant; Twin Health, Marico, Franco Indian, Zydus Cadila, Glenmark Pharmaceuticals. Other Relationship; Novo Nordisk, Sanofi, MSD, Abbott Nutrition, Abbott, Biocon, Alkem, USV Private Limited, Boehringer-Ingelheim. J. Keshavdev: None. R. Joshi: None. M.N. Pancholi: None. R. Patel: None. S. Kaloo: None. G. Verma: None.
1017-P: Experience of Using Continuous Glucose Monitor among Chinese Americans with Type 2 Diabetes
Authors: ZHENG YAGUANG , GREENLEE MICHAELA D. , CHEN KEER , SUN MINGUI , WU BEI , ZWEIG SUSAN , JIA WENYAN , MELKUS GAIL D.E. , PAREKH NIYATI , WYLIE-ROSETT JUDITH 
Published: June 2024

Background & Objective: Growing evidence has shown continuous glucose monitoring (CGM) has improved glycemic control. However, culturally-relevant facilitators and barriers to CGM use is unclear among Chinese Americans with type 2 diabetes (T2D), although they face high T2D prevalence with disparities in diabetes care. Thus, we aimed to evaluate the feasibility of using CGM for diabetes care among Chinese Americans with T2D.
Methods: This is a one-group prospective study. Participants wore a CGM for 2 weeks and kept a diary recording food, medication, and physical activity. Individual interviews were conducted after 2-week use to discuss their experience. Two independent and trained research assistants applied ATLAS.ti software to thematically analyze the transcription of the interview data.
Results: The Chinese Americans (N=11) aged 42-77 years with 3 females. Facilitators of using CGM included (1) CGM was comfortable and easy-to-use compared to finger sticks; (2) CGM made Chinese Americans with T2D mindful of meal choices (e.g., highlighting the need to reduce portion size even for commonly consumed foods related to Chinese culture, such as rice, noodles, and steam buns, debunking the misperceptions that one needs to only reduce sugar intake); and (3) CGM motivated them to change eating behaviors by informing their food portion size decisions. The most common barriers include the sensor falling off, getting trapped in clothes, followed by skin sensitivity.
Conclusions: Our findings suggest that it is feasible for Chinese Americans with T2D to use CGM in their diabetes care. Using CGM to reduce routine food intake with high carbohydrates may be particularly beneficial for Chinese Americans, as CGM can help Chinese Americans to understand how their culturally-related diet impacts their glucose response. Future study needs to apply CGM in a larger sample for a longer duration to inform effective diabetes management, which may improve health equity and reduce diabetes care disparity.

Disclosure
Y. Zheng: None. M.D. Greenlee: None. K. Chen: None. M. Sun: None. B. Wu: None. S. Zweig: None. W. Jia: None. G.D.E. Melkus: None. N. Parekh: None. J. Wylie-Rosett: None.

Funding
NIH/NCATS (UL1TR001445); CTSI Collaborative Translational Pilot Project Award (P30DK111022-08); New York Regional Center for Diabetes Translation Research (NY-CDTR); Pilot and Feasibility (P&F) Program Funding
1039-P: Insurance Type, Income, and Risk for Cost-Related Barriers to Care in a National Sample of Adults with Diabetes
Authors: TORRES HUGO A. , MOIN TANNAZ 
Published: June 2024

Objective: Out-of-pocket costs for insured patients have soared in recent years. Medicaid insurance for low-income individuals has minimal cost sharing but private insurance and Medicare have rising levels of cost-sharing that vary widely. We compared cost barriers and out-of-pocket expenditures among a national sample of adults with diabetes.
Methods: We used 2018-21 Medical Expenditure Panel Survey data to examine cost barriers. We categorized adults with diabetes into 3 groups: 1) low income (&lt;250% federal poverty level [FPL]) on Medicaid; 2) low income on private insurance or Medicare; 3) high income (&lt;u&gt;&gt;&lt;/u&gt;250% of FPL) on private insurance or Medicare. Logistic regression adjusted for age, sex, race, ethnicity, region, income (% of FPL), number of chronic conditions, self-rated health status, limitation of activities, and insulin use.
Results: We included a national sample of 6,219 adults with diabetes. Compared to low-income Medicaid recipients, low income and privately or Medicare-insured adults had higher reporting of delays or forgoing of medical care (OR=1.78, p=0.001) and medications (OR=1.45, p=0.01) due to cost. The high-income group had significantly higher odds of reporting delays and/or forgoing medication use (OR=1.58, p=0.005) but not medical care (OR=1.35, p=0.1). Out-of-pocket expenditures were significantly higher for private and Medicare insured adults compared to those in the low-income Medicaid group (low income, private or Medicare insurance group paid $267 more for medications and $755 more for care; high income group paid $315 and $967 more, respectively).
Conclusion: We found most adults with diabetes face cost barriers to care but low-income, privately or Medicare-insured adults are at highest risk of delaying or forgoing care and medication use due to cost. As the gap between rich and poor Americans widens, affordability of diabetes care will be harder to achieve, especially among low income privately or Medicare-insured adults.

Disclosure
H.A. Torres: None. T. Moin: None.
1043-P: Screening for Presence of High-Risk Metabolic Dysfunction–Associated Steatotic Liver Disease (MASLD) In the U.S. Primary Care Is Cost Effective
Authors: YOUNOSSI ZOBAIR , PAIK JAMES M. , HENRY LINDA , STEPANOVA MARIA , NADER FATEMA 
Published: June 2024

Introduction & Objective: Scientific associations recommend a sequential combination of non-invasive tests (NITs) to identify high-risk MASLD patients in primary care, but their cost-effectiveness is unknown.
Methods: Cost-utility model including a decision tree and Markov model was developed to compare nine screening strategies with FIB-4 followed by Enhanced Liver Fibrosis (ELF) or Vibration Controlled Transient Elastography (VCTE) to no-screening. The decision tree distributes patients between true and false positive and negative diagnoses based on the sensitivity and specificity of the diagnostic pathways. The Markov model updated disease state and mortality status over 20-years. Per patient costs, health utilities, and incremental cost-effectiveness ratios (ICERs) were calculated per strategy and reported as quality-adjusted life years (QALYs). The model simulated patients seen at primary care (type 2 diabetes (T2D), prediabetes (Pre-D), or nondiabetic ≥1 cardiometabolic risks (≥1-CMR) without other causes of liver disease). Additional scenario analysis was simulated considering the availability of VCTE and ELF in the U.S.
Results: After 20-years, all 9 screening strategies provided lower cumulative mortality (4.1% to 5.8% reduction), reduction in advanced fibrosis (24.7% to 30.9% reduction) and were cost-effective as compared to no screening [ICERs ranging between $22,119 to $28,778 per QALY gained in T2D, $69,289 to $79,260 in Pre-D, and $69,686 to $80,034 in ≥1-CMR (willingness-to-pay threshold of $100,000 per QALY)]. The cost-effectiveness of screening strategies was consistent with scenario and sensitivity analyses.
Conclusions: Recently published guidelines for high-risk MASLD screening are cost-effective and should be considered in primary care.

Disclosure
Z. Younossi: Consultant; Gilead Sciences, Inc., Bainan Biotech, AbbVie Inc., Bristol-Myers Squibb Company, Abbott, Novo Nordisk, Madrigal Pharmaceuticals, Inc., Merck & Co., Inc., Siemens Healthcare Diagnostics, Intercept Pharmaceuticals, Inc. J.M. Paik: None. L. Henry: None. M. Stepanova: None. F. Nader: None.
105-OR: Single-Cell Multiomic Analysis of the Effect of GIP and GIP-1 Mono- and Multi-agonism on the Hypothalamus and Hindbrain
Authors: GUTGESELL ROBERT M. , MAITY-KUMAR GANDHARI , GARCIA CACERES CRISTINA , TSCHÖP MATTHIAS H. , MÜLLER TIMO D. 
Published: June 2024

The discovery of incretin mimetics represents a major turning point in obesity and diabetes medicine. These small molecules are agonists of one or more receptors of glucagon, GLP-1, and GIP. Despite their efficacy and widespread use, the mechanism for the reduction in bodyweight has not been elucidated. Energy homeostasis is regulated in the hypothalamus and hindbrain, where incretin receptors are also expressed, leading to the hypothesis that incretin mimetics act in these brain regions to exert their appetite suppressing effects. The aim of this study is to identify mechanisms of action in the hypothalamus and hindbrain of GLP-1 and GIP agonists.Adult, diet-induced obese male CL57BL/6-J mice were injected IP with vehicle, GLP-1R agonist, GIPR agonist, GIPR antagonist, and MAR709, a mouse and human GLP-1R/GIPR dual-agonist, n=6. 8h after injection, the hypothalamus and hindbrain were collected and single-nuclei RNA and ATAC (assay for transposase-accessible chromatin) sequencing was performed, yielding 211537 hypothalamic and 57844 hindbrain nuclei after pre-processing (removal of low-quality nuclei & doublets).Cell type annotations from the Allen Institute mouse brain atlas were transferred to this data using correlation mapping. To identify cell types acted on by the incretin agonists, cell types were ranked by transcriptional and accessible chromatin changes between groups using Pertpy. Differences in intercellular communication were identified using a novel atlas-informed cell-cell communication method.We have generated the largest single-cell multiome dataset in the hindbrain and hypothalamus to date and identified gene expression and gene regulatory changes by which GIP and GLP-1 mimetics act to exert their anti-obesity effects. These data and analysis identified candidate mechanisms of action of incretin-mediated weight loss.

Disclosure
R.M. Gutgesell: None. G. Maity-Kumar: None. C. Garcia Caceres: None. M.H. Tschöp: Consultant; Boeher Inglehim. T.D. Müller: Stock/Shareholder; Novo Nordisk, Eli Lilly and Company. Research Support; Novo Nordisk. Speaker's Bureau; Novo Nordisk, Merck & Co., Inc., Eli Lilly and Company, Novo Nordisk.