Accurate Information Research Articles

Abstract 3711: Procedure establishment of EGFR mutation test with circulating tumor cells of lung cancer by in vitro assay

Abstract Introduction: Non-small cell lung cancer (NSCLC) is the most common subtype, accounting for approximately 80% of lung cancer. The treatment for NSCLC has significantly improved since the introduction of targeted therapies. Epidermal growth factor receptor (EGFR) mutations are the most frequently found genetic alterations in NSCLC, and deletion of exon 19 is a representative example. Searching for this mutation may provide important clues to the use of EGFR tyrosine kinase inhibitors in NSCLC. So, the detection of EGFR mutation is important step in cancer diagnosis and determining the drug treatment strategy, but the detection of mutation with tissues has limitations such as clinical challenge to poorly accessible tumor tissues before and after treatment. The aim of this study was to explore the feasibility and utility of implementation of EGFR molecular testing from circulating tumor cells (CTC) in NSCLC. Here, we developed and optimized the procedure of mutated EGFR detection in CTC after isolation with CytoGen’s Smart BiopsyTM CTC isolator by cobas® EGFR Mutation Test. This EGFR mutation test in CTC showed the potential to overcome the limitations of tissue biopsy with high sensitivity and specificity in an in vitro assay. Method: PC-9 cells were used the positive control of EGFR mutation (EGFR exon 19 deletion). Limit of detection (LOD) was performed with PC-9 cells (200 cells to 5 cells, 6 points) spiked into blood sample (5mL, healthy donor) to mimic CTC in the blood of lung cancer patient. CTC were isolated from spiked samples using CytoGen’s Smart BiopsyTM CTC isolator, subsequently cobas® EGFR Mutation Test was carried out to detect of EGFR mutation. Results: In in vitro experiments of recovery test using cell lines spiked into blood from healthy donor, the recovery rate of CytoGen’s Smart Biopsy TM CTC isolator showed over 80%. As a result of LOD test, EGFR exon19 deletion mutation of PC-9 cells was clearly detected even in the smallest number of cells were spiked into blood (5 cells in 5mL blood) and was not detected at all in the negative controls. The result suggested that CytoGen’s Smart Biopsy TM CTC isolator can isolate CTC with high recovery rate and apply the test of oncogenic mutations including EGFR mutation in CTC. Conclusions: Confirmation of EGFR mutation is important step in the diagnosis and selection of optimal drug for cancer patients. However, tissue biopsy has several limitations such as difficulties to get tissue samples and inaccurate information due to invasive method and tumor heterogeneity. Detection of EGFR mutation in CTC might overcome and make up for limitations of tissue biopsy. In this study, we optimized the EGFR mutation detection procedure of intact live CTC isolated by CytoGen’s Smart BiopsyTM CTC isolator. Citation Format: Jihyun Lee, Hoin Kang, Min Hyung Kim, Jubi Lee, Hyoyong Kim, Soee Kim, Hae Ung Lee, Hai-Chon Lee, Jung Won Kim. Procedure establishment of EGFR mutation test with circulating tumor cells of lung cancer by in vitro assay [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3711.

Remote Sensing Extraction of Crown Planar Area and Plant Number of Papayas Using UAV Images with Very High Spatial Resolution

The efficient management of commercial orchards strongly requires accurate information on plant growing status for the implementation of necessary farming activities such as irrigation, fertilization, and pest control. Crown planar area and plant number are two very important parameters directly relating to fruit growth conditions and the final productivity of an orchard. In this study, in order to propose a novel and effective method to extract the crown planar area and number of mature and young papayas based on visible light images obtained from a DJ Phantom 4 RTK, we compared different vegetation indices (NGRDI, RGBVI, and VDVI), filter types (high- and low-pass filters), and filter convolution kernel sizes (3–51 pixels). Then, Otsu’s method was used to segment the crown planar area of the papayas, and the mean–standard deviation threshold (MSDT) method was used to identify the number of plants. Finally, the extraction accuracy of the crown planar area and number of mature and young papayas was validated. The results show that VDVI had the highest capability to separate the papayas from other ground objects. The best filter convolution kernel size was 23 pixels for the low-pass filter extraction of crown planar areas in mature and young plants. As to the plant number identification, segmentation could be set to the threshold with the highest F-score, i.e., the deviation coefficient n = 0 for single young papaya plants, n = 1 for single mature ones, and n = 1.4 for crown-connecting mature ones. Verification indicated that the average accuracy of crown planar area extraction was 93.71% for both young and mature papaya orchards and 95.54% for extracting the number of papaya plants. This set of methods can provide a reference for information extraction regarding papaya and other fruit trees with a similar crown morphology.

A Review of Crowdsourcing Update Methods for High-Definition Maps

High-definition (HD) maps serve as crucial infrastructure for autonomous driving technology, facilitating vehicles in positioning, environmental perception, and motion planning without being affected by weather changes or sensor-visibility limitations. Maintaining precision and freshness in HD maps is paramount, as delayed or inaccurate information can significantly impact the safety of autonomous vehicles. Utilizing crowdsourced data for HD map updating is widely recognized as a superior method for preserving map accuracy and freshness. Although it has garnered considerable attention from researchers, there remains a lack of comprehensive exploration into the entire process of updating HD maps through crowdsourcing. For this reason, it is imperative to review and discuss crowdsourcing techniques. This paper aims to provide an overview of the overall process of crowdsourced updates, followed by a detailed examination and comparison of existing methodologies concerning the key techniques of data collection, information extraction, and change detection. Finally, this paper addresses the challenges encountered in crowdsourced updates for HD maps.

Phase compensation of a continuous-variable quantum key distribution via temporal convolutional neural network

Abstract Although the continuous-variable quantum key distribution (CV-QKD) protocol based on a local local oscillator (LLO) can close all the security loopholes from the transmitted local oscillator (TLO), the phase noise caused by the inaccurate phase reference information limits the performance of the protocol. To reduce the residual phase noise, in this work, we propose a phase estimation and compensation method based on the temporal convolutional neural (TCN) model, where a part of phase information obtained by measuring pilot pulses is employed as the training data and input into the TCN module. With a trained TCN module, the subsequent phase drifts can be more accurately estimated, allowing for better phase compensation and lower phase noise. Numerical analysis shows that the proposed scheme can improve the transmission distance and the secret key rate of the LLO protocol.

P240: Sarcopenia of the lower limb on Magnetic Resonance Imaging in patients with Diabetes Mellitus – a systematic review

Abstract Introduction Sarcopenia is defined by low measures of muscle quantity and quality and physical performance. Accelerated sarcopenic changes in diabetic patients leads to biomechanical changes in the foot and limb loss. Aim To systematically review the literature on Magnetic Resonance Imaging (MRI) and sarcopenia in the lower limb in patients with diabetes. Methods A literature review was conducted in accordance with PRISMA guidelines. Embase and Medline databases were searched with Ovid interface, as well as Pubmed and Cochrane. The grey literature was also reviewed on ClinicalTrials.gov, WHO international clinical trials registry platform, Cochrane library and the NIHR journals library and ProQuest. The MeSH terms “sarcopenia” AND “diabetes mellitus” AND “magnetic resonance imaging” were employed in the primary search string. The articles were reviewed by two independent reviewers. Results 874 studies were screened. 20 articles were included in the final review. Methods of measurement included cross sectional area measurements, stereological muscle measurements, muscle volume estimation, adipose infiltration, signal intensity cut-off, Goutallier grading, semiquantitative 5-point scale. Reduction in cross-sectional area and volumes and greater intramuscular fat infiltration was noted in patients with diabetes Sarcopenia ++ in Diabetic polyneuropathy (DPN) compared to non-diabetic and diabetic but non-DPN counterparts. MRI findings correlate with neuropathy disability scores and physical tests. Single study using a semi-automated process to measure sarcopenia. Conclusion MRI has its merit in providing accurate and detailed information on skeletal muscle volume and assessment of fat infiltration in muscle. This is relevant to reducing complications associated with changes in the biomechanics of the foot.

Falsification of registration of organizations and registration of rights to securities in domestic criminal law

The article deals with the genesis of domestic criminal legislation on liability for distortion of accounting register information about legal entities and securities (Art. 1701 of the Criminal Code of the Russian Federation). The relevance of the topic is due to the lack of scientific research in the field of the noted encroachment. The main task is to search for and study criminal-legal norms ensuring the reliability of the mentioned information. Based on formal-legal and historical-legal methods of research it is concluded that the required criminal-legal norms in the pre-revolutionary period were absent, and there was a gap in the part of protection of the reliability of the register of securities owners, which was not filled until 2010. For the first time since the introduction of the registration of organizations in the Soviet period the submission of inaccurate information for this purpose was considered a crime (Art. 90, 226b of the Criminal Code of the RSFSR of 1922, Art. 187 of the Criminal Code of the RSFSR of 1926). At the present stage of the Criminal Code of the Russian Federation initially prohibited only the submission of false or distorted information, preventing fictitious registration in the Unified State Register of Legal Entities of business entities (part 1 of Art. 171), and only since the middle of 2010 (with an addition in 2018) and to this day the reliability of information of the accounting system of the securities market and registration data on all legal entities in the country has been put under the protection of the criminal law against falsification and distortion (Art.1701).

Digital and online tools employed by prospective teachers to access information

The proliferation of digital information technologies has underscored the heightened necessity for online information search. This study is directed towards the analysis of the strategies adopted by prospective teachers in the selection of digital content employed for accessing information, their preferences concerning the use of digital and online tools, and the rationale that underpins these preferences. To achieve this aim, the case study method was used. Employing the purposive sampling method, the study involved a participant pool of 72 teacher candidates in the 3rd and 4th grades within the faculties of education. To collect data, a personal information form, an online interview form, a focus group interview form, and a word association test were employed. The data were analyzed using the content and descriptive analysis methods. At the end of the study, the prospective teachers expressed a common tendency that when it comes to scientific research, they often prefer to search for articles whereas for more general inquiries, they have a propensity for utilizing internet searches. Most of the prospective teachers follow a step-by-step research process when accessing information. In addition, they employ both goal-oriented and general-content resources while in pursuit of scientific information. They pay attention to data reliability, accurate information, speed, and access to the Internet in the process of obtaining information. They consider the tools they use adequate and reliable. Teacher candidates establish complex conceptual networks among the array of tools they employ to access information. A comprehensive discussion concerning the outcomes of the research is also presented.

An Environmental Scan and Appraisal of Patient Online Resources for Managing Rheumatoid Arthritis Flares.

To conduct an environmental scan and appraisal of online patient resources to support rheumatoid arthritis (RA) flare self-management. We used the Google search engine (last search March 2023) using the terms "rheumatoid arthritis" and "flare management." Additional searches targeted major arthritis organizations, as well as regional, national, and international resources. Appraisal of the resources was conducted by 2 research team members and 1 patient partner to assess the understandability and actionability of the resource using the Patient Education Materials Assessment Tool (PEMAT). Resources rating ≥ 60% in both domains by either the research team or the patient partner were further considered for content review. During content review, resources were excluded if they contained product advertisements, inaccurate information, or use of noninclusive language. If content review criteria were met, resources were designated as "highly recommended" if both patient partners and researchers' PEMAT ratings were ≥ 60%. If PEMAT ratings were divergent and had a rating ≥ 60% from only 1 group of reviewers, the resource was designated "acceptable." We identified 44 resources; 12 were excluded as they did not pass the PEMAT assessment. Fourteen resources received ratings ≥ 60% on understandability and actionability from both researchers and patient partners; 10 of these were retained following content review as "highly recommended" flare resources. Of the 18 divergent PEMAT ratings, 8 resources were retained as "acceptable" following content review. There is high variability in the actionability and understandability of online RA flare materials; only 23% of resources were highly recommended by researchers and patient partners.

"There hasn't been a push to identify patients in the emergency department"-Staff perspectives on automated identification of candidates for pre-exposure prophylaxis (PrEP): A qualitative study.

Automated algorithms for identifying potential pre-exposure prophylaxis (PrEP) candidates are effective among men, yet often fail to detect cisgender women (hereafter referred to as "women") who would most benefit from PrEP. The emergency department (ED) is an opportune setting for implementing automated identification of PrEP candidates, but there are logistical and practical challenges at the individual, provider, and system level. In this study, we aimed to understand existing processes for identifying PrEP candidates and to explore determinants for incorporating automated identification of PrEP candidates within the ED, with specific considerations for ciswomen, through a focus group and individual interviews with ED staff. From May to July 2021, we conducted semi-structured qualitative interviews with 4 physicians and a focus group with 4 patient advocates working in a high-volume ED in Chicago. Transcripts were coded using Dedoose software and analyzed for common themes. In our exploratory study, we found three major themes: 1) Limited PrEP knowledge among ED staff, particularly regarding its use in women; 2) The ED does not have a standardized process for assessing HIV risk; and 3) Perspectives on and barriers/facilitators to utilizing an automated algorithm for identifying ideal PrEP candidates. Overall, ED staff had minimal understanding of the need for PrEP among women. However, participants recognized the utility of an electronic medical record (EMR)-based automated algorithm to identify PrEP candidates in the ED. Facilitators to an automated algorithm included organizational support/staff buy-in, patient trust, and dedicated support staff for follow-up/referral to PrEP care. Barriers reported by participants included time constraints, hesitancy among providers to prescribe PrEP due to follow-up concerns, and potential biases or oversight resulting from missing or inaccurate information within the EMR. Further research is needed to determine the feasibility and acceptability of an EMR-based predictive HIV risk algorithm within the ED setting.

Reducing hydrophobic drug adsorption in an in-vitro extracorporeal membrane oxygenation model

Extracorporeal membrane oxygenation (ECMO) is a life-saving cardiopulmonary bypass technology for critically ill patients with heart and lung failure. Patients treated with ECMO receive a range of drugs that are used to treat underlying diseases and critical illnesses. However, the dosing guidelines for these drugs used in ECMO patients are unclear. Mortality rate for patients on ECMO exceeds 40% partly due to inaccurate dosing information, caused in part by the adsorption of drugs in the ECMO circuit and its components. These drugs range in hydrophobicity, electrostatic interactions, and pharmacokinetics. Propofol is commonly administered to ECMO patients and is known to have high adsorption rates to the circuit components due to its hydrophobicity. To reduce adsorption onto the circuit components, we used micellar block copolymers (Poloxamer 188TM and Poloxamer 407TM) and liposomes tethered with poly(ethylene glycol) to encapsulate propofol, provide a hydrophilic shell and prevent its adsorption. Size, polydispersity index (PDI), and zeta potential of the delivery systems were characterized by dynamic light scattering, and encapsulation efficiency was characterized using High Performance Liquid Chromatography (HPLC). All delivery systems used demonstrated colloidal stability at physiological conditions for seven days, cytocompatibility with a human leukemia monocytic cell line, i.e., THP-1 cells, and did not activate the complement pathway in human plasma. We demonstrated a significant reduction in adsorption of propofol in an in-vitro ECMO model upon encapsulation in micelles and liposomes. These results show promise in reducing the adsorption of hydrophobic drugs to the ECMO circuits by encapsulation in nanoscale structures tethered with hydrophilic polymers on the surface.

The value of multimodality MR in T staging evaluation after neoadjuvant therapy for rectal cancer.

Surgery is the preferred treatment for rectal cancer, but surgical treatment alone sometimes does not achieve satisfactory results. To explore the value of multimodal Magnetic Resonance (MR) images in evaluating T staging of rectal cancer after neoadjuvant therapy and to compare and analyze with pathological results. This study retrospectively analyzed 232 patients with stage T3, T4 rectal cancer between January 1, 2017 and October 31, 2022. MR examination was performed within 3 days before surgery. Different MR sequences were used for mrT staging of rectal cancer after neoadjuvant therapy and compared with pathological pT staging. The accuracy of different MR sequences in evaluating T staging of rectal cancer was calculated, and the consistency between the two was analyzed by kappa test. The sensitivity, specificity, negative predictive value and positive predictive value of different MR sequences in evaluating rectal cancer invading mesorectal fascia after neoadjuvant therapy were calculated. A total of 232 patients with rectal cancer were included in the study. The accuracy of high-resolution T2 WI in evaluating T staging of rectal cancer after neoadjuvant therapy was 49.57%, and the Kappa value was 0.261. The accuracy of high-resolution T2WI combined with diffusion weighted imaging (DWI) in evaluating T staging of rectal cancer after neoadjuvant therapy was 61.64%, and the Kappa value was 0.411. The accuracy of high-resolution combined with DCE-MR images in evaluating T staging of rectal cancer after neoadjuvant therapy was 80.60%, and the Kappa value was 0.706. The sensitivity and specificity of high-resolution t2-weighted imaging (HR-T2WI) combined with dynamic contrast-enhancement magnetic resonance (DCE-MR) in evaluating the invasion of mesorectal fascia were 83.46% and 95.33%, respectively. Compared with HR-T2WI combined with DWI images for mrT staging of rectal cancer after neoadjuvant chemoradiotherapy (N-CRT), HR-T2WI combined with DCE-M has the highest accuracy in evaluating mrT staging of rectal cancer after neoadjuvant therapy (80.60%), and has a high consistency with pathological pT staging. It is the best sequence for T staging of rectal cancer after neoadjuvant therapy. At the same time, the sequence has high sensitivity and specificity in evaluating mesorectal fascia invasion, which can provide accurate perioperative information for the formulation of surgical plan.

An audit and analysis of electro convulsive therapy patient information sheets used in local health districts in New South Wales Australia.

Electroconvulsive Therapy (ECT) is a widely used psychiatric treatment; however, it remains contentious. It is therefore important that people are provided with accurate and balanced information before consenting to ECT. The aim of this study was to audit and analyse the content and language of ECT information sheets used in local health districts (LHDs) across the state of New South Wales Australia. Descriptive content analysis and evaluative linguistic analysis were used to investigate the information sheets, with findings then considered from a mad studies perspective. Thirteen ECT information sheets were obtained and reviewed, with the audit finding they lacked accuracy and balance. Linguistic tools were used to exaggerate positive outcomes and minimise negative effects. Despite commonalities, the structure and content of the sheets varied considerably. Findings indicate a need for co-design and co-production approaches to developing ECT information sheets. This should occur in genuine partnership with lived experience representatives based on current evidence, using neutral language, and with attention to their intent as part of processes of informed consent and decision making.

Intermediate-stage hepatocellular carcinoma: refining substaging or shifting paradigm?

This review explores the evolution of cancer staging, focusing on intermediate hepatocellular carcinoma (HCC), and the challenges faced by physicians. The Barcelona Clinic Liver Cancer (BCLC) staging system, introduced in 1999, was designed to address the limitations associated with providing accurate prognostic information for HCC and allocating specific treatments, to avoid overtreatment. However, criticism has emerged, particularly regarding the intermediate stage of HCC (BCLC-B) and its heterogeneous patient population. To overcome this limitation, various subclassification systems, such as the Bolondi and Kinki criteria, have been proposed. These systems are aimed at refining categorizations within the intermediate stage and have demonstrated varying degrees of success in predicting outcomes through external validation. This study discusses the shift in treatment paradigms, emphasizing the need for a more personalized approach rather than strictly adhering to cancer stages, without dismissing the relevance of staging systems. It assesses the available treatment options for intermediate-stage HCC, highlighting the importance of considering surgical and nonsurgical options alongside transarterial chemoembolization for optimal outcomes. In conclusion, the text advocates for a paradigm shift in staging systems prioritizing treatment suitability over cancer stage. This reflects the evolving landscape of HCC management, where a multidisciplinary approach is crucial for tailoring treatments to individual patients, ultimately aiming to improve overall survival.

Optimizing Crop Yield Estimation through Geospatial Technology: A Comparative Analysis of a Semi-Physical Model, Crop Simulation, and Machine Learning Algorithms

This study underscores the critical importance of accurate crop yield information for national food security and export considerations, with a specific focus on wheat yield estimation at the Gram Panchayat (GP) level in Bareilly district, Uttar Pradesh, using technologies such as machine learning algorithms (ML), the Decision Support System for Agrotechnology Transfer (DSSAT) crop model and semi-physical models (SPMs). The research integrates Sentinel-2 time-series data and ground data to generate comprehensive crop type maps. These maps offer insights into spatial variations in crop extent, growth stages and the leaf area index (LAI), serving as essential components for precise yield assessment. The classification of crops employed spectral matching techniques (SMTs) on Sentinel-2 time-series data, complemented by field surveys and ground data on crop management. The strategic identification of crop-cutting experiment (CCE) locations, based on a combination of crop type maps, soil data and weather parameters, further enhanced the precision of the study. A systematic comparison of three major crop yield estimation models revealed distinctive gaps in each approach. Machine learning models exhibit effectiveness in homogenous areas with similar cultivars, while the accuracy of a semi-physical model depends upon the resolution of the utilized data. The DSSAT model is effective in predicting yields at specific locations but faces difficulties when trying to extend these predictions to cover a larger study area. This research provides valuable insights for policymakers by providing near-real-time, high-resolution crop yield estimates at the local level, facilitating informed decision making in attaining food security.

Xylazine: An Abused Tranq Dope and its Safety Concern.

A drug called Xylazine has gained notoriety in recent times, earning the nickname "zombie drug" due to reported alarming effects on its users. Although Xylazine is primarily intended for veterinary use as a sedative and muscle relaxant for animals, there have been growing concerns about its misuse among humans, particularly in the context of illicit drug use. However, it is essential to rely on accurate and evidence-based information when discussing the health risks associated with any substance, rather than resorting to sensationalized terms like "zombie drug." The situation involving Xylazine misuse is a matter of concern, and the United States Drug Enforcement Administration has highlighted it as a significant threat to public health.

Sonographic assessment of hemi-diaphragmatic palsy post brachial plexus blocks

Background and Aim: Brachial plexus blocks (BPB) are indispensable in providing surgical anaesthesia and postoperative analgesia. Although Hemi-diaphragmatic palsy (HDP) after BPB is clinically insignificant in the majority, it can cause significant physiological impairment in patients with reduced pulmonary function. Sonographic assessment of diaphragmatic function using the ABCDE approach provides accurate and quantitative information on HDP. This can be performed bedside before and after administration of the nerve block to quantify HDP. This was a prospective observational study comparing ultrasound-guided diaphragmatic thickness in two approaches of ultrasound-guided BPB. Methodology: Eighty participants receiving eitherinterscalene/supraclavicular BPB were included in this observational study. Baseline vitals, NRS score for pain and ultrasound-guided diaphragm thickness at inspiration and expiration using the ABCDE approach were noted. After 20 minutes of BPB administration, the diaphragm thickness was remeasured. Results: Eighty participants completed the study, forty from either group. Average volume of the total local anaesthetic drug mixture used was noted to be 30ml. The diaphragmatic thickness ratio in the supraclavicular group was found to decrease by 2.34% as compared to 2.39% in the interscalene group. (p-value 0.256 baseline values,0.292 for post block values) The thickness fraction was found to decrease by 9.21% in Group A as compared to 9.04% in Group B (P value 0.248 baseline values and 0.292 post-block values). There was no statistically significant difference between the diaphragm thickness in both the group'spre- and post-block, irrespective of the approach used. Conclusion: The ABCDE approach to measure diaphragm thickness can be used as a simple bedside modality to quantify the amount of HDP occurring after ultrasound-guided BPB. It is easy to learn & a non-invasive modality which can be used to improve patient safety during BPB Bangladesh Journal of Medical Science Vol.23 (Special Issue) 2024 p.S101-S106

Satellite-Derived Indicators of Drought Severity and Water Storage in Estuarine Reservoirs: A Case Study of Qingcaosha Reservoir, China

Estuarine reservoirs are critical for freshwater supply and security, especially for regions facing water scarcity challenges due to climate change and population growth. Conventional methods for assessing drought severity or monitoring reservoir water level and storage are often limited by data availability, accessibility and quality. We present an approach for monitoring estuarine reservoir water levels, storage and extreme drought via satellite remote sensing and waterline detection. Based on the CoastSat algorithm, Landsat-8 and Sentinel-2 images from 2013 to 2022 were adopted to extract the waterline of Qingcaosha Reservoir, the largest estuarine reservoir in the world and a key source of freshwater for Shanghai, China. This study confirmed the accuracy of the satellite-extracted results through two main methods: (1) calculating the angle of the central shoal slope in the reservoir using the extracted waterline data and measured water levels and (2) inverting the time series of water levels for comparison with measured data. The correlation coefficient of the estimated water level reached ~0.86, and the root mean square error (RMSE) of the estimated shoal slope was ~0.2°, indicating that the approach had high accuracy and reliability. We analyzed the temporal and spatial patterns of waterline changes and identified two dates (21 February 2014 and 15 October 2022) when the reservoir reached the lowest water levels, coinciding with periods of severe saltwater intrusions in the estuary. The extreme drought occurrences in the Qingcaosha Reservoir were firstly documented through the utilization of remote sensing data. The results also indicate a strong resilience of the Qingcaosha Reservoir and demonstrate that the feasibility and utility of using satellite remote sensing and waterline detection for estuarine reservoir storage can provide timely and accurate information for water resource assessment, management and planning.

Assessing the Quality and Clarity of YouTube Videos as an Informational Source for Ankle Fractures: A Study of the Turkish Population.

Background and objective The significance of YouTube as a prominent source of healthcare-related information cannot be overstated. Its influence on patient education is substantial. However, despite its popularity, there has been little research into the quality and comprehensibility of videos related to ankle fractures, a condition with increasing incidence rates, particularly in the context of Turkey. To address this gap in the literature and the growing reliance on digital platforms for health information during the coronavirus disease 2019 (COVID-19) pandemic, this study aims to assess the quality, clarity, and pedagogical value of YouTube videos on ankle fractures for the Turkish population. Methodology A comprehensive examination of 150 YouTube videos concerning ankle fractures, employing exacting inclusion and exclusion criteria to identify 52 videos for in-depth analysis was undertaken. The investigation entailed an assessment of content quality, presentation style, and user interaction, utilizing the criteria established by the Journal of the American Medical Association (JAMA) and the Patient Education Materials Assessment Tool (PEMAT), as well as a novel measurement known as the Ankle Fracture Content Score (AFCS). A statistical analysis was executed to gauge the educational value and dependability of the information presented. Results The majority of ankle fracture management videos were found to be uploaded by medical professionals, covering various aspects such as rehabilitation and patient testimonials. However, the overall educational quality was suboptimal, with patient-shared videos lacking in depth and accuracy. Statistical analysis showed no significant differences in content quality across different uploader categories, except for notably lower educational quality in videos shared by patients. Conclusions The findings underscore a significant need for healthcare professionals and academic institutions in Turkey to produce and share high-quality, reliable, and comprehensible videos on ankle fractures. Leveraging YouTube's extensive reach can significantly improve health literacy among the Turkish public, ensuring access to accurate and trustworthy health information.

Assessing the Reliability of Facial Feminization Content on Social Media and Its Impact on the Dissemination of Misinformation.

The surge in social media usage has transformed the dissemination and consumption of healthcare information, notably impacting plastic surgery and cosmetic specialties. This study focuses on the influence of social media, particularly Instagram and TikTok, in shaping perceptions of individuals seeking facial feminization (FF) procedures. Using the validated DISCERN scale, we assessed the reliability and accuracy of FF content on TikTok and Instagram. The study also analyzed the relationship between content reliability on engagement metrics (likes, comments, views) and the type of content shared (educational, testimonial, promotional). The analysis encompassed 225 TikTok videos and 75 Instagram posts. TikTok content showed 9.33% as "very poor," 66.2% as "poor," 22.6% as "fair," and only 1.33% as "excellent." Similarly, Instagram content demonstrated 14.67% as "very poor" and 69.33% as "poor," with no content rated as "good" or "excellent." Educational content received higher reliability scores on both platforms. TikTok engagement metrics showed lower reliability ratings correlating with more views, comments, and likes. The study underscores the critical role of social media in shaping patient perspectives on FF procedures. The prevalence of inaccurate information necessitates a focus on responsible engagement by healthcare professionals, aiming to provide accurate, educational content that aligns with patients' informational needs and ultimately enhances surgical outcomes.

FOREST SEMANTIC SEGMENTATION BASED ON DEEP LEARNING USING SENTINEL-2 IMAGES

Abstract. Forests are invaluable for maintaining biodiversity, watersheds, rainfall levels, bioclimatic stability, carbon sequestration and climate change mitigation, and the sustainability of large-scale climate regimes. In other words, forests provide a wide range of ecosystem services and livelihoods for the people and play a critical role in influencing global atmospheric cycles. Providing sustainable, reliable, and accurate information on forest cover change is essential for an holistic forest management, efficient use of resources, neutralizing the effects of global warming and better monitoring of deforestation activities. Within the scope of this study, it is aimed to perform semantic segmentation of 5 different tree species (larch, red pine, yellow pine, oak, spruce) from Sentinel-2 satellite images. For this purpose, the regions where these tree species are densely populated in Turkey (Marmara, Aegean, Eastern Black Sea) were selected as pilot regions. A unique data set was created using the data of the selected pilot regions. As a result of the study, it was possible to determine the forest types temporally for the selected classes with more than 90% Intersection over Union score for all classes. The developed deep learning model with the created forest data set can be implemented to the other forests areas with same species in other parts of the world.