Fecal Calprotectin in Patients with Crohn's Disease: A Study Based on the History of Bowel Resection and Location of Disease.

Fecal calprotectin (FC) is commonly used to assess Crohn's disease (CD) activity. However, standardized cut-off values accounting for bowel resection history and disease location are lacking. In this study, we analyzed data from patients with CD who underwent magnetic resonance enterography, ileocolonoscopy, and FC measurements from January 2017 to December 2018. In 267 cases from 254 patients, the FC levels in the 'operated' patients were higher when the disease was active compared with those who were in the remission group (178 vs. 54.7 µg/g; p < 0.001), and similar findings were obtained for the 'non-operated' patients (449.5 vs. 40.95 µg/g; p < 0.001). The FC levels differed significantly according to the location of inflammation, with lower levels in the small bowel compared to those in the colon. The FC cut-off levels of 70.8 µg/g and 142.0 µg/g were considered optimal for predicting active disease for operated and non-operated patients, respectively. The corresponding FC cut-off levels of 70.8 µg/g and 65.0 µg/g were observed for patients with disease only in the small bowel. In conclusion, different FC cut-off values would be applicable to patients with CD based on their bowel resection history and disease location. Tight control with a lower FC target may benefit those with a history of bowel resection or small-bowel-only disease.

Development and Usability Evaluation of an Opioid Management App.

We describe the development and usability evaluation of a novel patient engagement tool (OPY) in its early stage from perspectives of both experts and end-users. The tool is aimed at engaging patients in positive behaviors surrounding the use, weaning, and disposal of opioid medications in the post-surgical setting. The messaging and design of the application were created through a behavioral economics lens. Expert-based heuristic analysis and user testing were conducted and demonstrated that while patients found the tool to be easy to use and subjectively somewhat useful, additional work to enhance the user interface and features is needed in close partnership with developers and stakeholders.

A Systematic Review of Nurses' Perceptions of Electronic Health Record Usability Based on the Human Factor Goals of Satisfaction, Performance, and Safety.

The poor usability of electronic health records contributes to increased nurses' workload, workarounds, and potential threats to patient safety. Understanding nurses' perceptions of electronic health record usability and incorporating human factors engineering principles are essential for improving electronic health records and aligning them with nursing workflows. This review aimed to synthesize studies focused on nurses' perceived electronic health record usability and categorize the findings in alignment with three human factor goals: satisfaction, performance, and safety. This systematic review was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analysis. Five hundred forty-nine studies were identified from January 2009 to June 2023. Twenty-one studies were included in this review. The majority of the studies utilized reliable and validated questionnaires (n = 15) to capture the viewpoints of hospital-based nurses (n = 20). When categorizing usability-related findings according to the goals of good human factor design, namely, improving satisfaction, performance, and safety, studies used performance-related measures most. Only four studies measured safety-related aspects of electronic health record usability. Electronic health record redesign is necessary to improve nurses' perceptions of electronic health record usability, but future efforts should systematically address all three goals of good human factor design.

Blood Pb levels are associated with prostate cancer prevalence among general adult males: Linking National Cancer Registry (2002-2017) and KNHANES (2008-2017) databases of Korea.

BACKGROUND: Exposure to heavy metals may increase the risk of developing prostate cancer. However, these observations are often inconsistent and not based on clinically diagnosed cases. OBJECTIVE: To investigate the association of lead (Pb), cadmium (Cd), and mercury (Hg) exposure with clinically determined prostate cancer cases among adult males in South Korea. METHODS: Metal biomonitoring data and cancer information from the general Korean population were extracted by linking National Cancer Center (NCC) cancer registration data (2002-2017) with Korea National Health and Nutrition Examination Survey (KNHANES) data (2008-2017). Among them, 46 prostate cancer cases (designated as 'all-prostate'), including 25 diagnosed after heavy metal measurement (designated as 'post-prostate'), and 93 matching controls were chosen. Logistic regression analysis was used to calculate the odds ratios (ORs) and 95% confidence intervals (CIs) between the heavy metal levels and prostate cancer. RESULTS: Post-prostate patients exhibited higher blood Pb levels than controls (median 3.1 µg/dL vs. 2.38 µg/dL, p = 0.01). For all-prostate cancer, the OR of prostate cancer increased by 2.04-fold for every doubling of Pb levels (95% CI = 1.08-3.87, p = 0.03). The OR was also significantly elevated when comparing the third quartile (Q3) to the lowest quartile (Q1), with ORs ranging from 3.38 to 7.95, depending on model (p < 0.05). Blood Pb levels maintained a positive association with inconsistent significance for post-prostate cancer patients. For Cd and Hg, no statistically significant association was established. SIGNIFICANCE: By linking two national health databases for the first time, we constructed an unbiased database of prostate cancer cases and matching controls. We found that blood Pb concentrations were associated with the risk of prostate cancer in Korean men at the current level of exposure.

Association of blood metal exposure with age at menarche in Korean women: KNHANES (2008-2017).

Humans are exposed to metals in their daily lives and this metal exposure is responsible for various adverse health effects. Delayed pubertal development has been suggested as an adverse outcome of metal exposure; however, evidence in nationally representative populations, especially in Asia, is limited. We evaluated the association of blood cadmium (Cd), lead (Pb), and mercury (Hg) levels with the age at menarche in Korean females whose blood heavy metals were measured as part of the Korean National Health and Nutrition Examination Survey (KNHANES) 2008-2017. Among the females 16 years of age or older, all measured heavy metals in blood, i.e., Cd, Pb, and Hg, were positively associated with age at menarche. These associations remained significant in a model adjusted for age, survey year, income, education, body mass index, smoking history, and menopausal status as covariates (ß: 0.10, 95% confidence interval (CI): 0.03-0.18 for Cd; ß: 0.17, 95%CI: 0.06-0.27 for Pb; ß: 0.12, 95%CI: 0.05-0.19 for Hg). When the population was separated by age group at the time of the survey, the significance between heavy metal levels and age at menarche became inconsistent, but the general trends were similar. Among those in their 20s and 40s, blood Cd showed a significant association, while Pb was significant among those in their 40s and 50s. A similar trend was observed in the sensitivity analysis in the girls aged 10-15 years at the time of the survey. Blood Cd levels were associated with decreased odds of precocious menarche (OR: 0.57, 95%CI: 0.31-1.03). Delayed menarche is a risk factor for cardiovascular and chronic kidney diseases in later life; hence, public health implication of heavy metal exposure warrants a public health attention.

Influence of endoscopists' expertise level on clinical outcomes after bridge-to-surgery stenting in obstructive colorectal cancer.

BACKGROUND AND AIM: This study aimed to investigate the effect of stenting-related factors, including endoscopists' expertise, on clinical outcomes after bridge-to-surgery (BTS) stenting for obstructive colorectal cancer (CRC). METHODS: We analyzed BTS stenting-related factors, including stenting expertise and the interval between stenting and surgery, in 233 patients (63 [13] years, 137 male) who underwent BTS stenting for obstructive CRC. We evaluated the influence of these factors on post-BTS stenting clinical outcomes such as stent-related complications and cancer recurrence. RESULTS: The interval between stenting and surgery was ≤ 7 days in 79 patients (33.9%) and > 7 days in 154 patients (66.1%). BTS stenting was performed by endoscopists with ≤ 50, 51-100, and > 100 prior stenting experiences in 94, 43, and, 96 patients, respectively. The clinical success rate of BTS stenting was 93.1%. Stent-related and postoperative complications developed in 19 (8.2%) and 20 (8.6%) patients, respectively. Cancer recurrence occurred in 76 patients (32.6%). Short BTS interval of ≤ 7 days increased the risk of postoperative complications (odds ratio [OR], 2.61 [1.03-6.75]; P = 0.043). Endoscopists' stenting experience > 100 showed greater clinical success of stenting (OR, 5.50 [1.45-28.39]; P = 0.021) and fewer stent-related complications (OR, 0.26 [0.07-0.80]; P = 0.028) compared with stenting experience ≤ 50. BTS stenting-related factors did not affect long-term oncological outcomes. CONCLUSION: Greater expertise of endoscopists was associated with better short-term outcomes, including high stenting success rate and low rate of stent-related complications after BTS stenting for obstructive CRC. An interval of > 7 days between BTS stenting and surgery was required to decrease postoperative complications.

Extended aperture image reconstruction for plane-wave imaging.

B-mode images undergo degradation in the boundary region because of the limited number of elements in the ultrasound probe. Herein, a deep learning-based extended aperture image reconstruction method is proposed to reconstruct a B-mode image with an enhanced boundary region. The proposed network can reconstruct an image using pre-beamformed raw data received from the half-aperture of the probe. To generate a high-quality training target without degradation in the boundary region, the target data were acquired using the full-aperture. Training data were acquired from an experimental study using a tissue-mimicking phantom, vascular phantom, and simulation of random point scatterers. Compared with plane-wave images from delay and sum beamforming, the proposed extended aperture image reconstruction method achieves improvement at the boundary region in terms of the multi-scale structure of similarity and peak signal-to-noise ratio by 8% and 4.10 dB in resolution evaluation phantom, 7% and 3.15 dB in contrast speckle phantom, and 5% and 3 dB in in vivo study of carotid artery imaging. The findings in this study prove the feasibility of a deep learning-based extended aperture image reconstruction method for boundary region improvement.

Data Science Implementation Trends in Nursing Practice: A Review of the 2021 Literature.

OBJECTIVES: The goal of this work was to provide a review of the implementation of data science-driven applications focused on structural or outcome-related nurse-sensitive indicators in the literature in 2021. By conducting this review, we aim to inform readers of trends in the nursing indicators being addressed, the patient populations and settings of focus, and lessons and challenges identified during the implementation of these tools. METHODS: We conducted a rigorous descriptive review of the literature to identify relevant research published in 2021. We extracted data on model development, implementation-related strategies and measures, lessons learned, and challenges and stakeholder involvement. We also assessed whether reports of data science application implementations currently follow the guidelines of the Developmental and Exploratory Clinical Investigations of DEcision support systems driven by AI (DECIDE-AI) framework. RESULTS: Of 4,943 articles found in PubMed (NLM) and CINAHL (EBSCOhost), 11 were included in the final review and data extraction. Systems leveraging data science were developed for adult patient populations and were primarily deployed in hospital settings. The clinical domains targeted included mortality/deterioration, utilization/resource allocation, and hospital-acquired infections/COVID-19. The composition of development teams and types of stakeholders involved varied. Research teams more frequently reported on implementation methods than implementation results. Most studies provided lessons learned that could help inform future implementations of data science systems in health care. CONCLUSION: In 2021, very few studies report on the implementation of data science-driven applications focused on structural- or outcome-related nurse-sensitive indicators. This gap in the sharing of implementation strategies needs to be addressed in order for these systems to be successfully adopted in health care settings.

Association of smoking and dietary polycyclic aromatic hydrocarbon exposure on the prevalence of metabolic syndrome in Korean adults.

BACKGROUND: Polycyclic aromatic hydrocarbons (PAHs) are environmental pollutants that are potentially hazardous to human health. Dietary exposure is recognized as one of the major pathways of exposure to PAHs among humans. While some PAH exposures have been associated with metabolic syndrome (MetS) in the general population, most epidemiological studies are based on urinary metabolites of a few noncarcinogenic PAHs. OBJECTIVE: To investigate the association between estimates of dietary exposure to major carcinogenic PAHs and MetS in Korean adults. METHODS: Multi-cycle Korean National Health and Nutrition Examination Survey (KNHANES) database (n = 16,015) and PAH measurement data from the total diet survey were employed to estimate daily PAH intake for each participating adult. After adjusting for potential confounders, multinomial logistic regression analysis was used to calculate the odds ratios (ORs) and 95% confidence intervals (CIs) between PAHs and MetS of the participating adults. RESULTS: Benzo(a)pyrene exposure was associated with an increased risk of MetS in men (OR = 1.30; 95% Cl: 1.03-1.63; P-trend = 0.03). In women, however, only chrysene and low high-density lipoprotein (HDL-c) were positively associated with an increased risk of MetS (OR = 1.24; 95% CI: 1.03-1.48; P-trend = 0.0172). Among men, smokers were at an increased risk for MetS, regardless of whether they were exposed to low or high total PAHs and benzo(a)pyrene levels. SIGNIFICANCE: Our findings suggested that PAHs are associated with the risk of MetS and MetS components in Korean adults. In particular, it was confirmed that smoking may influence the relationship between PAH exposure and MetS.Further prospective cohort studies are required to confirm the causal relationship between PAHs and MetS. IMPACT STATEMENT: Epidemiological studies on PAH exposure are often hampered by a lack of reliable exposure estimates, as biomonitoring of urine does not capture exposure to more toxic PAHs. Using multi-cycle KNHANES data and the measurement data from a total diet survey of Korea, we could develop a personalized PAH intake estimate for each participating adult and assessed the association with MetS.

Vascular wall motion detection models based on long short-term memory in plane-wave-based ultrasound imaging.

Objective.Vascular wall motion can be used to diagnose cardiovascular diseases. In this study, long short-term memory (LSTM) neural networks were used to track vascular wall motion in plane-wave-based ultrasound imaging.Approach.The proposed LSTM and convolutional LSTM (ConvLSTM) models were trained using ultrasound data from simulations and tested experimentally using a tissue-mimicking vascular phantom and anin vivostudy using a carotid artery. The performance of the models in the simulation was evaluated using the mean square error from axial and lateral motions and compared with the cross-correlation (XCorr) method. Statistical analysis was performed using the Bland-Altman plot, Pearson correlation coefficient, and linear regression in comparison with the manually annotated ground truth.Main results.For thein vivodata, the median error and 95% limit of agreement from the Bland-Altman analysis were (0.01, 0.13), (0.02, 0.19), and (0.03, 0.18), the Pearson correlation coefficients were 0.97, 0.94, and 0.94, respectively, and the linear equations were 0.89x+ 0.02, 0.84x+ 0.03, and 0.88x+ 0.03 from linear regression for the ConvLSTM model, LSTM model, and XCorr method, respectively. In the longitudinal and transverse views of the carotid artery, the LSTM-based models outperformed the XCorr method. Overall, the ConvLSTM model was superior to the LSTM model and XCorr method.Significance.This study demonstrated that vascular wall motion can be tracked accurately and precisely using plane-wave-based ultrasound imaging and the proposed LSTM-based models.

Defect Detection in Printed Circuit Boards Using Semi-Supervised Learning.

Defect inspection is essential in the semiconductor industry to fabricate printed circuit boards (PCBs) with minimum defect rates. However, conventional inspection systems are labor-intensive and time-consuming. In this study, a semi-supervised learning (SSL)-based model called PCB_SS was developed. It was trained using labeled and unlabeled images under two different augmentations. Training and test PCB images were acquired using automatic final vision inspection systems. The PCB_SS model outperformed a completely supervised model trained using only labeled images (PCB_FS). The performance of the PCB_SS model was more robust than that of the PCB_FS model when the number of labeled data is limited or comprises incorrectly labeled data. In an error-resilience test, the proposed PCB_SS model maintained stable accuracy (error increment of less than 0.5%, compared with 4% for PCB_FS) for noisy training data (with as much as 9.0% of the data labeled incorrectly). The proposed model also showed superior performance when comparing machine-learning and deep-learning classifiers. The unlabeled data utilized in the PCB_SS model helped with the generalization of the deep-learning model and improved its performance for PCB defect detection. Thus, the proposed method alleviates the burden of the manual labeling process and provides a rapid and accurate automatic classifier for PCB inspections.

Documentation of Complementary and Integrative Health Therapies in the Electronic Health Record: A Scoping Review.

Introduction: Complementary and integrative health (CIH) therapies refers to massage therapy, acupuncture, aromatherapy, and guided imagery. These therapies have gained increased attention in recent years, particularly for their potential to help manage chronic pain and other conditions. National organizations not only recommend the use of CIH therapies but also the documentation of these therapies within electronic health records (EHRs). Yet, how CIH therapies are documented in the EHR is not well understood. The purpose of this scoping review of the literature was to examine and describe research that focused on CIH therapy clinical documentation in the EHR. Methods: The authors conducted a literature search using six electronic databases: Cumulative Index to Nursing and Allied Health Literature (CINAHL), Ovid MEDLINE, Scopus, Google Scholar, Embase, and PubMed. Predefined search terms included "informatics," "documentation," "complementary and integrative health therapies," "non-pharmacological approaches," and "electronic health records" using AND/OR statements. No restrictions were placed on publication date. The inclusion criteria were as follows: (1) Original peer-reviewed full article in English, (2) focus on CIH therapies, and (3) CIH therapy documentation practice used in the research. Results: The authors identified 1684 articles, of which 33 met the criteria for a full review. A majority of the studies were conducted in the United States (20) and hospitals (19). The most common study design was retrospective (9), and 26 studies used EHR data as a data source for analysis. Documentation practices varied widely across all studies, ranging from the feasibility of documenting integrative therapies (i.e., homeopathy) to create changes in the EHR to support documentation (i.e., flowsheet). Discussion: This scoping review identified varying EHR clinical documentation trends for CIH therapies. Pain was the most frequent reason for use of CIH therapies across all included studies and a broad range of CIH therapies were used. Data standards and templates were suggested as informatics methods to support CIH documentation. A systems approach is needed to enhance and support the current technology infrastructure that will enable consistent CIH therapy documentation in EHRs.

UBP12/UBP13-mediated deubiquitination of salicylic acid receptor NPR3 suppresses plant immunity.

Salicylic acid (SA), a defense hormone produced after pathogen challenge, is critical for plant immunity. Arabidopsis NONEXPRESSER OF PR GENES 1 (NPR1) and its paralogs NPR3 and NPR4 can bind SA and mediate SA signal transduction. NPR1 functions as a transcriptional co-activator to promote defense gene expression, whereas NPR3 and NPR4 have been shown to function as negative regulators in the SA signaling pathway. Although the mechanism about NPR1 regulation has been well studied, how NPR3/NPR4 proteins are regulated in immune responses remains largely unknown. Here, we show that the stability of NPR3/NPR4 is enhanced by SA. In the absence of pathogen challenge, NPR3/NPR4 are unstable and degraded by the 26S proteasome, whereas the increase in cellular SA levels upon pathogen infection suppresses NPR3/NPR4 degradation. We found that UBP12 and UBP13, two homologous deubiquitinases from a ubiquitin-specific protease subfamily, negatively regulate plant immunity by promoting NPR3/NPR4 stability. Our genetic results further showed that UBP12/UBP13-mediated immunity suppression is partially dependent on NPR3/NPR4 functions. By interacting with NPR3 in the nucleus in an SA-dependent manner, UBP12 and UBP13 remove ubiquitin from polyubiquitinated NPR3 to protect it from being degraded. The stabilization of NPR3/NPR4 promoted by UBP12/UBP13 is essential for negative regulation of basal and SA-induced immunity.

Inositol polyphosphates-regulated polyubiquitination of PHR1 by NLA E3 ligase during phosphate starvation response in Arabidopsis.

Phosphate (Pi) availability is a major factor limiting plant growth and development. The key transcription factor controlling Pi-starvation response (PSR) is PHOSPHATE STARVATION RESPONSE 1 (PHR1) whose transcript levels do not change with changes in Pi levels. However, how PHR1 stability is regulated at the post-translational level is relatively unexplored in Arabidopsis thaliana. Inositol polyphosphates (InsPn) are important signal molecules that promote the association of stand-alone SPX domain proteins with PHR1 to regulate PSR. Here, we show that NITROGEN LIMITATION ADAPTATION (NLA) E3 ligase can associate with PHR1 through its conserved SPX domain and polyubiquitinate PHR1 in vitro. The association with PHR1 and its ubiquitination is enhanced by InsP6 but not by InsP5. Analysis of InsPn-related mutants and an overexpression plant shows PHR1 levels are more stable in itpk4-1 and vih2-4/VIH1amiRNA but less stable in ITPK4 overexpression plants. Under Pi-deficient conditions, nla seedlings contain high PHR1 levels, display long root hair and accumulate anthocyanin in shoots phenocopying PHR1 overexpression plants. By contrast, NLA overexpression plants phenocopy phr1 whose phenotypes are opposite to those of nla. Our results suggest NLA functions as a negative regulator of Pi response by modulating PHR1 stability and the NLA/PHR1 association depends on InsPn levels.

Label-free detection of leukemic myeloblasts in hyaluronic acid.

Chronic myeloid leukemia is generally required bone marrow biopsy for diagnosis. Although examining peripheral blood is less invasive, it has not been fully validated as a routine diagnostic test due to suboptimal sensitivity. To overcome this limitation, a number of methodologies based on microfluidics have been developed for sorting circulating tumor cells from peripheral blood of patients with leukemia.In order to develop a more convenient method, we designed an analysis protocol using motion microscopy that amplifies cellular micro motions in a captured video by re-rendering pixels to generate extreme magnified visuals. Intriguingly, no fluctuations around leukemic myeloblasts were observed with a motion microscope at any wavelength of 0-10 Hz. However, use of 0.05% hyaluronic acid, one type of non-newtonian fluid, demonstrated fluctuations around leukemic myeloblasts under conditions of 25 µm/s and 0.5-1.5 Hz with a motion microscope.Thus, the non-invasive detection of leukemic myeloblasts can offer a valuable supplementary diagnostic tool for assessment of drug efficacy for monitoring patients with chronic myeloid leukemia.

Semantic Segmentation of Pancreatic Cancer in Endoscopic Ultrasound Images Using Deep Learning Approach.

Endoscopic ultrasonography (EUS) plays an important role in diagnosing pancreatic cancer. Surgical therapy is critical to pancreatic cancer survival and can be planned properly, with the characteristics of the target cancer determined. The physical characteristics of the pancreatic cancer, such as size, location, and shape, can be determined by semantic segmentation of EUS images. This study proposes a deep learning approach for the segmentation of pancreatic cancer in EUS images. EUS images were acquired from 150 patients diagnosed with pancreatic cancer. A network with deep attention features (DAF-Net) is proposed for pancreatic cancer segmentation using EUS images. The performance of the deep learning models (U-Net, Attention U-Net, and DAF-Net) was evaluated by 5-fold cross-validation. For the evaluation metrics, the Dice similarity coefficient (DSC), intersection over union (IoU), receiver operating characteristic (ROC) curve, and area under the curve (AUC) were chosen. Statistical analysis was performed for different stages and locations of the cancer. DAF-Net demonstrated superior segmentation performance for the DSC, IoU, AUC, sensitivity, specificity, and precision with scores of 82.8%, 72.3%, 92.7%, 89.0%, 98.1%, and 85.1%, respectively. The proposed deep learning approach can provide accurate segmentation of pancreatic cancer in EUS images and can effectively assist in the planning of surgical therapies.

Deubiquitination of BES1 by UBP12/UBP13 promotes brassinosteroid signaling and plant growth.

As a key transcription factor in the brassinosteroid (BR) signaling pathway, the activity and expression of BES1 (BRI1-EMS-SUPPRESSOR 1) are stringently regulated. BES1 degradation is mediated by ubiquitin-related 26S proteasomal and autophagy pathways, which attenuate and terminate BR signaling; however, the opposing deubiquitinases (DUBs) are still unknown. Here, we showed that the ubp12-2w/13-3 double mutant phenocopies the BR-deficient dwarf mutant, suggesting that the two DUBs UBP12/UBP13 antagonize ubiquitin-mediated degradation to stabilize BES1. These two DUBs can trim tetraubiquitin with K46 and K63 linkages in vitro. UBP12/BES1 and UBP13/BES1 complexes are localized in both cytosol and nuclei. UBP12/13 can deubiquitinate polyubiquitinated BES1 in vitro and in planta, and UBP12 interacts with and deubiquitinates both inactive, phosphorylated BES1 and active, dephosphorylated BES1 in vivo. UBP12 overexpression in BES1OE plants significantly enhances cell elongation in hypocotyls and petioles and increases the ratio of leaf length to width compared with BES1OE or UBP12OE plants. Hypocotyl elongation and etiolation result from elevated BES1 levels because BES1 degradation is retarded by UBP12 in darkness or in light with BR. Protein degradation inhibitor experiments show that the majority of BES1 can be degraded by either the proteasomal or the autophagy pathway, but a minor BES1 fraction remains pathway specific. In conclusion, UBP12/UBP13 deubiquitinate BES1 to stabilize the latter as a positive regulator for BR responses.

Reconstruction for plane-wave ultrasound imaging using modified U-Net-based beamformer.

An image reconstruction method that can simultaneously provide high image quality and frame rate is necessary for diagnosis on cardiovascular imaging but is challenging for plane-wave ultrasound imaging. To overcome this challenge, an end-to-end ultrasound image reconstruction method is proposed for reconstructing a high-resolution B-mode image from radio frequency (RF) data. A modified U-Net architecture that adopts EfficientNet-B5 and U-Net as the encoder and decoder parts, respectively, is proposed as a deep learning beamformer. The training data comprise pairs of pre-beamformed RF data generated from random scatterers with random amplitudes and corresponding high-resolution target data generated from coherent plane-wave compounding (CPWC). To evaluate the performance of the proposed beamforming model, simulation and experimental data are used for various beamformers, such as delay-and-sum (DAS), CPWC, and other deep learning beamformers, including U-Net and EfficientNet-B0. Compared with single plane-wave imaging with DAS, the proposed beamforming model reduces the lateral full width at half maximum by 35% for simulation and 29.6% for experimental data and improves the contrast-to-noise ratio and peak signal-to-noise ratio, respectively, by 6.3 and 9.97 dB for simulation, 2.38 and 3.01 dB for experimental data, and 3.18 and 1.03 dB for in vivo data. Furthermore, the computational complexity of the proposed beamforming model is four times less than that of the U-Net beamformer. The study results demonstrate that the proposed ultrasound image reconstruction method employing a deep learning beamformer, trained by the RF data from scatterers, can reconstruct a high-resolution image with a high frame rate for single plane-wave ultrasound imaging.