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Abstract Background Telomeres consist of repetitive DNA sequences at the chromosome ends to protect chromosomal stability, and primarily maintained by telomerase or occasionally by alternative telomere lengthening of telomeres (ALT) through recombination-based mechanisms. Additional mechanisms that may regulate telomere maintenance remain to be explored. Simultaneous measurement of telomere length and transcriptome in the same human embryonic stem cell (hESC) revealed that mRNA expression levels of UBQLN1 exhibit linear relationship with telomere length. Methods In this study, we first generated UBQLN1-deficient hESCs and compared with the wild-type (WT) hESCs the telomere length and molecular change at RNA and protein level by RNA-seq and proteomics. Then we identified the potential interacting proteins with UBQLN1 using immunoprecipitation-mass spectrometry (IP-MS). Furthermore, the potential mechanisms underlying the shortened telomeres in UBQLN1-deficient hESCs were analyzed. Results We show that Ubiquilin1 (UBQLN1) is critical for telomere maintenance in human embryonic stem cells (hESCs) via promoting mitochondrial function. UBQLN1 deficiency leads to oxidative stress, loss of proteostasis, mitochondria dysfunction, DNA damage, and telomere attrition. Reducing oxidative damage and promoting mitochondria function by culture under hypoxia condition or supplementation with N-acetylcysteine partly attenuate the telomere attrition induced by UBQLN1 deficiency. Moreover, UBQLN1 deficiency/telomere shortening downregulates genes for neuro-ectoderm lineage differentiation. Conclusions Altogether, UBQLN1 functions to scavenge ubiquitinated proteins, preventing their overloading mitochondria and elevated mitophagy. UBQLN1 maintains mitochondria and telomeres by regulating proteostasis and plays critical role in neuro-ectoderm differentiation.

Health insurance fraud is becoming more common and impacting the fairness and sustainability of the health insurance system. Traditional health insurance fraud detection primarily relies on recognizing established data patterns. However, with the ever-expanding and complex nature of health insurance data, it is difficult for these traditional methods to effectively capture evolving fraudulent activity and tactics and keep pace with the constant improvements and innovations of fraudsters. As a result, there is an urgent need for more accurate and flexible analytics to detect potential fraud. To address this, the Multi-channel Heterogeneous Graph Structured Learning-based health insurance fraud detection method (MHGSL) was proposed. MHGSL constructs a graph of health insurance data from various entities, such as patients, departments, and medicines, and employs graph structure learning to extract topological structure, features, and semantic information to construct multiple graphs that reflect the diversity and complexity of the data. We utilize deep learning methods such as heterogeneous graph neural networks and graph convolutional neural networks to combine multi-channel information transfer and feature fusion to detect anomalies in health insurance data. The results of extensive experiments on real health insurance data demonstrate that MHGSL achieves a high level of accuracy in detecting potential fraud, which is better than existing methods, and is able to quickly and accurately identify patients with fraudulent behaviors to avoid loss of health insurance funds. Experiments have shown that multi-channel heterogeneous graph structure learning in MHGSL can be very helpful for health insurance fraud detection. It provides a promising solution for detecting health insurance fraud and improving the fairness and sustainability of the health insurance system. Subsequent research on fraud detection methods can consider semantic information between patients and different types of entities.

Abstract Background With the rapid growth of healthcare services, health insurance fraud detection has become an important measure to ensure efficient use of public funds. Traditional fraud detection methods have tended to focus on the attributes of a single visit and have ignored the behavioural relationships of multiple visits by patients. Methods We propose a health insurance fraud detection model based on a multilevel attention mechanism that we call MHAMFD. Specifically, we use an attributed heterogeneous information network (AHIN) to model different types of objects and their rich attributes and interactions in a healthcare scenario. MHAMFD selects appropriate neighbour nodes based on the behavioural relationships at different levels of a patient’s visit. We also designed a hierarchical attention mechanism to aggregate complex semantic information from the interweaving of different levels of behavioural relationships of patients. This increases the feature representation of objects and makes the model interpretable by identifying the main factors of fraud. Results Experimental results using real datasets showed that MHAMFD detected health insurance fraud with better accuracy than existing methods. Conclusions Experiment suggests that the behavioral relationships between patients’ multiple visits can also be of great help to detect health care fraud. Subsequent research fraud detection methods can also take into account the different behavioral relationships between patients.

Drug-drug interaction prediction plays an important role in pharmacology and clinical applications. Most traditional methods predict drug interactions based on drug attributes or network structure. They usually have three limitations: 1) failing to integrate drug features and network structures well, resulting in less informative drug embeddings; 2) being restricted to a single view of drug interaction relationships; 3) ignoring the importance of different neighbors. To tackle these challenges, this paper proposed a multiview fusion based on dual-level attention to predict drug interactions (called MFDA). The MFDA first constructed multiple views for the drug interaction relationship, and then adopted a cross-fusion strategy to deeply fuse drug features with the drug interaction network under each view. To distinguish the importance of different neighbors and views, MFDA adopted a dual-level attention mechanism (node level and view level) to obtain the unified drug embedding for drug interaction prediction. Extensive experiments were conducted on real datasets, and the MFDA demonstrated superior performance compared to state-of-the-art baselines. In the multitask analysis of new drug reactions, MFDA obtained higher scores on multiple metrics. In addition, its prediction results corresponded to specific drug reaction events, which achieved more accurate predictions.

Camellia leyeensis Chang ＆ Y. C. Zhong is a plant belonging to the genus Camellia. To determine its correct taxonomic status and better understand its molecular phylogenetic and genetic diversity, we studied the chloroplast genome of this species. Here, we report and characterize the complete chloroplast (cp) genome of C. leyeensis by using Illumina paired-end sequencing data. The chloroplast genome was determined to be 157,063 bp in length with a GC content of 37.30%. The genome contained 136 genes, including 91 protein-coding genes, 37 tRNA genes, and 8 rRNA genes. The sequence contained a large single-copy region (LSC, 86,661 bp), a small single-copy region (SSC, 18,284 bp), and two inverted repeat sequences (IRs, 26,059 bp, each). The GC content of the IR regions (42.96%) was higher than that of the SSC region (30.6%) and LSC region (35.31%). Phylogenetic analysis suggested that Camellia leyeensis is closely related to C. anlungensis with 96% bootstrap support. This chloroplast genome would be helpful for the phylogeny and conservation of Camellia.

How to use a few defect samples to complete the defect classification is a key challenge in the production of mobile phone screens. An attention-relation network for the mobile phone screen defect classification is proposed in this paper. The architecture of the attention-relation network contains two modules: a feature extract module and a feature metric module. Different from other few-shot models, an attention mechanism is applied to metric learning in our model to measure the distance between features, so as to pay attention to the correlation between features and suppress unwanted information. Besides, we combine dilated convolution and skip connection to extract more feature information for follow-up processing. We validate attention-relation network on the mobile phone screen defect dataset. The experimental results show that the classification accuracy of the attention-relation network is 0.9486 under the 5-way 1-shot training strategy and 0.9039 under the 5-way 5-shot setting. It achieves the excellent effect of classification for mobile phone screen defects and outperforms with dominant advantages.

The Chinese wheat landrace Kaixianluohanmai (KL) expresses the ph-like phenotype. A major QTL, QPh.sicau-3A (syn. phKL), responsible for this effect has been mapped to chromosome arm 3AL. This study presents some characteristics of homoeologous pairing and recombination induced by phKL. In KL haploids, the level of homoeologous pairing was elevated relative to Ph1 Chinese Spring (CS) haploids. There was a clear preference for A–D pairing and less frequent for A–B and B–D, reflecting the higher levels of affinity between genomes A and D in wheat. The characteristics of pairing were affected by temperature and magnesium ion supplementation. The suitability of phKL for chromosome engineering was tested on three pairs of homoeologues: 2Sv-2B, 2Sv-2D, and 2RL-2BL. The recombination rates were 1.68%, 0.17%, and 0%, respectively. The phKL locus in KL induced a moderate level of homoeologous chromosome pairing and recombination when the Ph1 locus of wheat was present, both in wheat haploids and hexaploids. The Ph1-imposed criteria for chromosome pairing and crossing over were relaxed to some degree, permitting homoeologous crossing over but only between closely related chromosomes; there was no crossing over between more differentiated chromosomes. Therefore, the phKL system (QPh.sicau-3A) can be a useful tool in chromosome engineering of wheat to transfer genes from closely related species with the benefit of reduced genomic chaos generated by the ph1b mutation.

IntroductionObject detection methods for team ball games players often struggle due to their reliance on dataset scale statistics, resulting in missed detections for players with smaller bounding boxes and reduced accuracy for larger bounding boxes.MethodsThis study introduces a two-fold approach to address these challenges. Firstly, a novel multi-scale attention mechanism is proposed, aiming to reduce reliance on scale statistics by utilizing a specially created SIoU (Similar to Intersection over Union) label that explicitly represents multi-scale features. This label guides the training of multi-scale attention network modules at two granularity levels. Secondly, an integrated scale equalization algorithm within SIoU labels enhances the detection ability of multi-scale targets in imbalanced samples.Results and discussionComparative experiments conducted on basketball, volleyball, and ice hockey datasets validate the proposed method. The relative optimal approach demonstrated improvements in the detection accuracy of players with smaller and larger scale bounding boxes by 11%, 7%, 15%, 8%, 9%, and 4%, respectively.

Abstract Background C‐C chemokine receptor 5 (CCR5) is a major coreceptor for Human immunodeficiency virus (HIV) and simian immunodeficiency virus (SIV) cell entry; however, its role in brain pathogenesis is largely understudied. Thus, we sought to examine cell type‐specific protein expression of CCR5 during SIV infection of the brain. Methods We examined occipital cortical tissue from uninfected rhesus macaques and SIV‐infected animals with or without encephalitis using immunohistochemistry and immunofluorescence microscopy to determine the number and distribution of CCR5‐positive cells. Results An increase in the number of CCR5+ cells in the brain of SIV‐infected animals with encephalitis was accounted for by increased CD3+CD8+ cells expressing CCR5, but not by increased CCR5+ microglia or perivascular macrophages (PVMs), and a concurrent decrease in the percentage of CCR5+ PVMs was observed. Levels of CCR5 and SIV Gag p28 protein expression were examined on a per‐cell basis, and a significant, negative relationship was established indicating decreased CCR5 expression in productively infected cells. While investigating the endocytosis‐mediated CCR5 internalization as a mechanism for CCR5 downregulation, we found that phospho‐ERK1/2, an indicator of clathrin‐mediated endocytosis, was colocalized with infected PVMs and that macrophages from infected animals showed significantly increased expression of clathrin heavy chain 1. Conclusions These findings show a shift in CCR5‐positive cell types in the brain during SIV pathogenesis with an increase in the number of CCR5+ CD8 T cells, and downregulated CCR5 expression on infected PVMs, likely through ERK1/2‐driven, clathrin‐mediated endocytosis.

Spinal surgeons have been drawn to the incidence of osteophytes following intervertebral disc degeneration in clinical practice. However, the production of osteophytes, particularly in the spinal canal, after anterior cervical discectomy and fusion (ACDF) is uncommon. We described a 42-year-old male patient who underwent C4–6 ACDF due to cervical stenosis two years prior in another public hospital in the province. His primary symptoms were significantly relieved, but he developed new pain and weakness in his right leg six months after surgery. The imaging results revealed a large posterior osteophyte at C5/6, compressing the spinal cord anteriorly. Accordingly, we performed cervical open-door laminoplasty to decompress the spinal cord. The patient's clinical symptoms had significantly improved at the one-year follow-up. This case seeks to inform surgeons that cautious, routine follow-ups are necessary for the event that a severe intracanal osteophyte develops at the operated level following ACDF. The comprehensive osteophyte removal and strong fixation at the operative level during ACDF warrant more consideration as these procedures may lower the incidence of new osteophytes. Additionally, surgical procedures may be required.

Premium wheat with a high end-use quality is generally lacking in China, especially high-quality hard and soft wheat. Pina-D1 and Pinb-D1 (puroindoline genes) influence wheat grain hardness (i.e., important wheat quality-related parameter) and are among the main targets in wheat breeding programs. However, the mechanism by which puroindoline genes control grain hardness remains unclear. In this study, three hard wheat puroindoline variants (MY26, GX3, and ZM1) were compared with a soft wheat variety (CM605) containing the wild-type puroindoline genotype. Specifically, proteomic methods were used to screen for differentially abundant proteins (DAPs). In total, 6253 proteins were identified and quantified via a high-throughput tandem mass tag quantitative proteomic analysis. Of the 208 DAPs, 115, 116, and 99 proteins were differentially expressed between MY26, GX3, and ZM1 (hard wheat varieties) and CM605, respectively. The cluster analysis of protein relative abundances divided the proteins into six clusters. Of these proteins, 67 and 41 proteins were, respectively, more and less abundant in CM605 than in MY26, GX3, and ZM1. Enrichment analyses detected six GO terms, five KEGG pathways, and five IPR terms that were shared by all three comparisons. Furthermore, 12 proteins associated with these terms or pathways were found to be differentially expressed in each comparison. These proteins, which included cysteine proteinase inhibitors, invertases, low-molecular-weight glutenin subunits, and alpha amylase inhibitors, may be involved in the regulation of grain hardness. The candidate genes identified in this study may be relevant for future analyses of the regulatory mechanism underlying grain hardness.

Abstract Background In contrast to most animal species, polyploid plant species are quite tolerant of aneuploidy. Here, the global transcriptome of four aneuploid derivatives of a synthetic hexaploid wheat line was acquired, with the goal of characterizing the relationship between gene copy number and transcript abundance. Results For most of the genes mapped to the chromosome involved in aneuploidy, the abundance of transcripts reflected the gene copy number. Aneuploidy had a greater effect on the strength of transcription of genes mapped to the chromosome present in a noneuploid dose than on that of genes mapped elsewhere in the genome. Overall, changing the copy number of one member of a homeologous set had little effect on the abundance of transcripts generated from the set of homeologs as a whole, consistent with the tolerance of aneuploidy exhibited by allopolyploids, whether in the form of a chromosomal deficit (monosomy) or chromosomal excess (trisomy). Conclusions Our findings shed new light on the genetic regulation of homeoallele transcription and contribute to a deeper understanding of allopolyploid genome evolution, with implications for the breeding of polyploid crops.

With the rapid development of e-commerce, online consumption has become a mainstream form of consumption in recent years. Text sentiment analysis for a large number of customer reviews on the e-commerce platform can dramatically improve the customers' consumption experience. Although the sentiment analysis approaches based on deep neural network can achieve higher accuracy without human-design features compared with traditional sentiment analysis methods, the accuracy still cannot meet the demand and the training suffers from the issues of over-fitting, vanishing gradient, etc. In this paper, a novel sentiment analysis model named MBGCV is designed to alleviate these problems and improve the accuracy, MBGCV employs a multichannel paradigm and integrates Bidirectional Gated Recurrent Unit (BiGRU), Convolutional Neural Network (CNN) and Variational Information Bottleneck (VIB). The multichannel is exploited to extract multi-grained sentiment features. In each channel, BiGRU is utilized to extract context information, and then CNN is adopted to extract local features. Furthermore, the model combines the advantages of VIB and Maxout activation function to overcome shortcomings such as over-fitting, vanishing gradient in existing sentiment analysis models. By using real review datasets, we carry out extensive experiments to demonstrate that our proposed model can achieve superior accuracy and improve the performance of text sentiment analysis.

Abstract Background Among cervical cancer patients in the U.S., a disproportionate number are Hispanics/Latinos. Also, about a third of patients diagnosed with cervical cancer annually in Mexico die of the disease. Vaccines are available to protect against HPV, the cause of cervical cancer. Methods A cross-sectional study was conducted with 200 mothers of Mexican origin in the U.S. Midwest and Xalapa, Veracruz, Mexico. Based on a validated bilingual questionnaire, this study elicited information about knowledge and attitudes regarding HPV vaccination and cervical cancer. Results Mothers living in Mexico showed better knowledge about HPV and HPV vaccine (77.8%) than participants living in the U.S. (48%) p

Uploading virtual reality (VR) video over cellular networks is expected to boom in the near future, as general consumers could generate the high-quality VR videos with portable 360-degree cameras and are willing to share with others. Consequently, the concerns of uplink bandwidth and delay arose for current popular technology of tile-based VR video streaming, which requires high-quality video to transcode into multiple representations for further adaptive streaming. Motivated by this, we proposed a novel scheme for uplink delivery of tile-based VR video over cellular networks, in which encoding bit rate of each tile is determined by the uplink resource allocation (RA), and the quality of content (QoC) contribution of each tile and channel quality of user equipments (UEs) are jointly considered during RA. Moreover, the RA problem is formulated as a frequency and time dependent non-deterministic polynomial (NP)-hard problem. Furthermore, we propose three algorithms to explore solving the RA problem. The simulation results show that the proposed approximate convex algorithm with low-complexity can achieve higher utility, i.e., higher total quality of experience (QoE) for viewers.

Virtual reality (VR) is commonly regarded as one of 5G killer-applications. Transmission efficiency and quality of experience (QoE) are the most concerning issues for VR video streaming in 5G networks. Several multicast approaches were proposed to address these issues regardless of variance of personal viewports. In this paper, we explore a novel scheme combining multicast and unicast sessions in heterogeneous cloud-radio access networks (H-CRAN), in which a basic version of the video is transmitted to all users through the g-NB in a multicast session, and tiles of enhanced-version are transmitted to each viewer in a unicast session through its stationed remote radio head (RHH). To ensure the real-time content delivery, a user's viewport is predicted using a method based on historical trajectories and similarity of motion behavior, and then the tiles of predicted viewport in a version dependent on the channel quality are sent to the user in the unicast session. The scheme is formulated into a mixed-integer nonlinear problem (MINLP), and two near-optimal solutions are proposed to solve it by applying greedy approach and approximate approach, respectively. The simulation results show that our proposed scheme ensures better QoE under constrained bandwidth, and the proposed near-optimal solutions can efficiently solve the problem with low complexity and comparable performance.

The US budget for global health funding, which was by far the largest of similar funding in the world, increased from US $1.3 billion in 2001 to more than US $10 billion in recent years. More than 54% of this funding was allocated to the Global Fund to Fight HIV/AIDS through the US President's Emergency Plan for AIDS Relief (PEPFAR) in Africa. However, recent studies indicate contradictory results regarding the effectiveness of PEPFAR. One by Bendavid, Holmes, Bhattacharya, and Miller shows positive effects of PEPFAR in reducing adult mortality in Africa, while another by Duber, Coates, Szekeras, Kaji, and Lewis finds that there are no significant differences in reducing adult mortality in countries that received PEPFAR funding vs countries that did not. Due to their potential impact on policy decisions regarding critical global health funding, we wanted to assess why the results are discrepant. To do this, we replicated the Bendavid study. The replication provides verification that the study replicable and that the analytic choices of the authors are robust to different assumptions or restrictions. This allows us to assess the different choices and data available to the two research groups and draw some conclusions about why the results may be different. Then, focusing on two of the prominently discrepant studies, i.e., the Bendavid study (1998-2008) and the Duber study (2000-2006), we establish why the two studies are in disagreement. We apply appropriate individual-level and country-level analytical methodology as used by Bendavid over the analytical time period used for the Duber study (2000-2006), which originally focused on nationally aggregated data and differed in some key focus countries. For our first objective, we replicated the original Bendavid study findings and our findings support their conclusion that between 1998-2008 all-cause mortality decreased significantly more (OR = 0.84, CI, 0.72-0.99) in countries that implemented PEPFAR. For our second objective (Bendavid's data and methodology applied to Duber's study period), we found reduction in all cause adult mortality to be borderline insignificant (OR = 0.87 CI, 0.75-1.01, p = 0.06), most possibly reflecting the abbreviated fewer number of events and sample size over a shorter period. Therefore, our overall analyses are consistent with the conclusion of positive impact of the PEPFAR program in reducing adult mortality. We believe that the discrepancy observed in the original studies mainly a reflection of shortcomings in the analytical approach necessitated by the Duber study's nationally aggregated dataset or "may reflect a lack of data quality" in the Duber study (Duber, et al. 2010).

Underwater acoustic sensor networks (UASNs) are used extensively in activities such as underwater data collection and water pollution detection. An UASN consists of acoustic sensors that use batteries as their power supply. Because of the complex underwater environments in which UASNs are employed, replacing these batteries is difficult. Prolonging the battery life of UASNs by reducing their energy consumption (improving their energy efficiency) is one of the means of mitigating this problem. This paper proposes an energy-balanced unequal layering clustering (EULC) algorithm that improves the energy efficiency of acoustic sensors. The EULC algorithm designs UASNs with unequal layering based on node depth, providing a solution to the “hot spot”issue through the construction of clusters of varying sizes within the same layer. Simulation results show that the EULC algorithm effectively balances the energy in UASN nodes and thereby prolongs network lifetime.

Leaf pubescence is an important trait closely associated with plant adaptability to specialized habitats. Baimaomai (BMM) is a wheat (Triticum aestivum L.) landrace originating from the high-altitude, drought-prone environment of Sichuan Province, China with long, dense leaf pubescence. A population of 234 recombinant inbred lines (F10) developed from the cross between Chuanmai104 (CM104), which lacks leaf pubescence, and BMM with pubescent leaves, was used to conduct a phenotypic evaluation of leaf pubescence. Three quantitative trait loci (QTLs) were detected on chromosome arms 7BS, 3DL and 3AL using a high-density wheat 50K single-nucleotide polymorphism array in four environments. The QTLs were designated QLp.saas-7BS, QLp.saas-3DL and QLp.saas-3AL. QLp.saas-3AL, derived from BMM, and QLp.saas-3DL, derived from CM104, were new minor-effect loci. QLp.saas-7BS, derived from BMM, was a novel major-effect locus detected in all environments and was localized in a 0.48 Mb interval on chromosome arm 7BS based on the wheat ‘Chinese Spring’ reference genome. QLp.saas-7BS explained up to 40.77% of the total phenotypic variance. KASP markers tightly linked to QLp.saas-7BS were developed and verified. The present results provide valuable information for further fine mapping, cloning, and marker-assisted selection with QLp.saas-7BS in wheat.

Based on the standing-wave theory, a modified method is proposed to separate interface and volume absorption in HfO2 single layers. HfO2 single layers with multiple half-wave optical thickness were pre- pared; in such case, the electric field at air-film and film-substrate interface is equal, and total absorption from both interfaces can be easily expressed by the product of electric field intensity and a simplified total interface absorption coefficient. Ultralow-absorptive substrates were used to eliminate the contribution of substrate absorption.When HfO2 single layer was irradiated from the coated and uncoated side in the photothermal measurement, two equations were obtained and utilized to separate the interface and volume absorption. The validity of our method was further confirmed using another thickness changing approach. By contrast, irradiation direction changing method is better because only one sample is required. [ABSTRACT FROM AUTHOR]

Aims: Patients with diabetes have higher readmission rates than those without diabetes, yet limited data on efforts to reduce their readmissions are available. We describe a novel model of inpatient diabetes care, expanding the role of diabetes educators to include case management, and establishment of a Diabetes Resource Nurse program, aimed at increasing the knowledge of staff nurses, and evaluate the impact of this program on readmission rates. Methods: We performed retrospective analysis of 30-day readmission rates of patients with diabetes before (July 2010–December 2011), and after (January 2012–June 2013) starting the implementation of this tiered inpatient diabetes care delivery model. Results: We analyzed 34,472 discharged patient records from the 18-month pre-intervention period, and 32,046 records from the 18-month post-intervention period. The overall 30-day readmission rate for patients with diabetes decreased significantly from 20.1% (pre) to 17.6% (post) intervention (p

Background: Hepatocellular carcinoma (HCC) is among the leading causes of cancer deaths in China. Considering its poor prognosis when diagnosed late, Chinese guidelines recommend biannual screening for HCC with abdominal ultrasound and serum α-fetoprotein (AFP) test for high-risk populations. Objectives: To investigate the practice, knowledge, and self-perceived barriers for HCC screening among high-risk hospital patients in China. Methods: An interview-based questionnaire was conducted among Chinese patients with chronic hepatitis B and/or chronic hepatitis C infection from outpatient clinics at 2 tertiary medical institutions in Shanghai and Wuhan, China. Findings: Among 352 participating patients, 50.0% had routine screening, 23.3% had irregular screening, and 26.7% had incomplete or no screening. Significant determinants for screening included higher level of education, underlying liver cirrhosis, a family history of HCC, and better knowledge concerning viral hepatitis, HCC, and HCC screening guidelines. Moreover, factors associated with better knowledge were younger age, female gender, urban residency, education level of college or above, annual household income of greater than 150,000 RMB, and longer duration of hepatitis infection. The 3 most common barriers reported for not receiving screening were not aware that screening for HCC exists (41.5%), no symptoms or discomfort (38.3%), and lack of recommendation from physicians (31.9%). Conlusions: Health care professionals and community leaders should actively inform patients regarding the benefits of HCC screening through design of educational programs. Such interventions are expected to increase knowledge about HCC and HCC screening, as well as improve screening adherence and earlier diagnosis.