Detection Rate Research Articles

New Test to Detect Clustered Graphical Passwords in Passpoints Based on the Perimeter of the Convex Hull

This research paper presents a new test based on a novel approach for identifying clustered graphical passwords within the Passpoints scenario. Clustered graphical passwords are considered a weakness of graphical authentication systems, introduced by users during the registration phase, and thus it is necessary to have methods for the detection and prevention of such weaknesses. Graphical authentication methods serve as a viable alternative to the conventional alphanumeric password-based authentication method, which is susceptible to known weaknesses arising from user-generated passwords of this nature. The test proposed in this study is based on estimating the distributions of the perimeter of the convex hull, based on the hypothesis that the perimeter of the convex hull of a set of five clustered points is smaller than the one formed by random points. This convex hull is computed based on the points that users select as passwords within an image measuring 1920 × 1080 pixels, using the built-in function convhull in Matlab R2018a relying on the Qhull algorithm. The test was formulated by choosing the optimal distribution that fits the data from a total of 54 distributions, evaluated using the Kolmogorov–Smirnov, Anderson–Darling, and Chi-squared tests, thus achieving the highest reliability. Evaluating the effectiveness of the proposed test involves estimating type I and II errors, for five levels of significance α∈{0.01,0.02,0.05,0.1,0.2}, by simulating datasets of random and clustered graphical passwords with different levels of clustering. In this study, we compare the effectiveness and efficiency of the proposed test with existing tests from the literature that can detect this type of pattern in Passpoints graphical passwords. Our findings indicate that the new test demonstrates a significant improvement in effectiveness compared to previously published tests. Furthermore, the joint application of the two tests also shows improvement. Depending on the significance level determined by the user or system, the enhancement results in a higher detection rate of clustered passwords, ranging from 0.1% to 8% compared to the most effective previous methods. This improvement leads to a decrease in the estimated probability of committing a type II error. In terms of efficiency, the proposed test outperforms several previous tests; however, it falls short of being the most efficient, using computation time measured in seconds as a metric. It can be concluded that the newly developed test demonstrates the highest effectiveness and the second-highest efficiency level compared to the other tests available in the existing literature for the same purpose. The test was designed to be implemented in graphical authentication systems to prevent users from selecting weak graphical passwords, enhance password strength, and improve system security.

COTTON-YOLO: Enhancing Cotton Boll Detection and Counting in Complex Environmental Conditions Using an Advanced YOLO Model

This study aims to enhance the detection accuracy and efficiency of cotton bolls in complex natural environments. Addressing the limitations of traditional methods, we developed an automated detection system based on computer vision, designed to optimize performance under variable lighting and weather conditions. We introduced COTTON-YOLO, an improved model based on YOLOv8n, incorporating specific algorithmic optimizations and data augmentation techniques. Key innovations include the C2F-CBAM module to boost feature recognition capabilities, the Gold-YOLO neck structure for enhanced information flow and feature integration, and the WIoU loss function to improve bounding box precision. These advancements significantly enhance the model’s environmental adaptability and detection precision. Comparative experiments with the baseline YOLOv8 model demonstrated substantial performance improvements with COTTON-YOLO, particularly a 10.3% increase in the AP50 metric, validating its superiority in accuracy. Additionally, COTTON-YOLO showed efficient real-time processing capabilities and a low false detection rate in field tests. The model’s performance in static and dynamic counting scenarios was assessed, showing high accuracy in static cotton boll counting and effective tracking of cotton bolls in video sequences using the ByteTrack algorithm, maintaining low false detections and ID switch rates even in complex backgrounds.

The many faces of brucellosis: diagnostic and management approach.

This review aims to highlight the multifaceted nature of brucellosis, emphasizing the latest advancements in its diagnosis and management. Given the global prevalence and potential complications of brucellosis, understanding recent advancements in diagnostic techniques and treatment strategies is crucial for clinicians. Recent literature reveals significant progress in diagnostic methods, including the application of fluorescence polarization immunoassay and time-resolved fluorescence resonance energy transfer technologies as well as the invention of artificial Brucella antigens, which offer enhanced sensitivity and specificity. Advances in molecular diagnostics and serological tests have improved early detection rates, however their interpretation remains challenging. Evolving treatment regimens such as the use of hydroxychloroquine as part of triple therapy and the use of nano-delivery systems in therapies have shown promise, in hopes of reducing relapse rates and managing chronic cases. The findings underscore the necessity for clinicians to adopt a comprehensive approach to diagnosing and managing brucellosis. Integrating advanced diagnostic tools with tailored therapeutic strategies can significantly improve patient outcomes. Future research should focus on optimizing these diagnostic techniques and exploring novel therapeutic agents.

High-mass star formation across the Large Magellanic Cloud

Context. The formation of massive stars passes through a so-called hot molecular core phase, where the temperature of molecular gas and dust rises to above 100 K within a size scale of approximately 0.1 pc. The hot molecular cores are rich in chemical compounds found in the gas phase, which are a great probe of ongoing star formation. Aims. To study the impact of the initial effects of metallicity (i.e., the abundance of elements heavier than helium) on star formation and the formation of different molecular species, we searched for hot molecular cores in the sub-solar metallicity environment of the Large Magellanic Cloud (LMC). Methods. We conducted Atacama Large Millimeter/submillimeter Array (ALMA) Band 6 observations of 20 fields centered on young stellar objects (YSOs) distributed over the LMC in order to search for hot molecular cores in this galaxy. Results. We detected a total of 65 compact 1.2 mm continuum cores in the 20 ALMA fields and analyzed their spectra with XCLASS software. The main temperature tracers are CH3OH and SO2, with more than two transitions detected in the observed frequency ranges. Other molecular lines with high detection rates in our sample are CS, SO, H13CO+, H13CN, HC15N, and SiO. More complex molecules, such as HNCO, HDCO, HC3N, CH3CN, and NH2CHO, and multiple transitions of SO and SO2 isotopologues showed tentative or definite detection toward a small subset of the cores. According to the chemical richness of the cores and high temperatures from the XCLASS fitting, we report the detection of four hot cores and one hot core candidate. With one new hot core detection in this study, the number of detected hot cores in the LMC increases to seven. Conclusions. Six out of seven hot cores detected in the LMC to date are located in the stellar bar region of this galaxy. These six hot cores show emission from complex organic molecules (COMs), such as CH3OH, CH3CN, CH3OCHO, and CH3OCH3. The only known hot core in the LMC with no detection of COMs is located outside the bar region. The metallicity in the LMC presents a shallow gradient increasing from outer regions toward the bar. Various studies emphasize the interaction between the LMC and the Small Magellanic Cloud, which resulted in the mixing and inhomogeneity of the interstellar medium of the two galaxies. These interactions triggered a new generation of star formation in the LMC. We suggest that the formation of hot molecular cores containing COMs ensues from the new generation of stars forming in the more metal-rich environment of the LMC bar.

What makes a video game localisation tester? Exploring the effect of individual factors on error detection

Video game quality assurance (QA) is vital to ensuring a high-quality gaming experience across different languages and regions. Competent localisation testers are expected to have advanced language skills, exceptional attention to detail, and familiarity with the game they are testing. However, individual testing performance differs, prompting the question of what constitutes a proficient localisation tester. In this study, students (N = 43) from the degree in Translation and Interpreting from the University of Alicante and the Specialist degree in Translation for the Video Game Industry from the University of Vigo were asked to test a localised video game which contained deliberate errors introduced for the purpose of this study. Subsequently, they completed questionnaires regarding localisation-related attitudes, personality traits, and trait anxiety levels. The results of various bivariate correlation and multivariate linear regression analyses indicate that translation expertise, low emotional stability, and a preference for screen reading were significant predictors of higher error detection rates. Furthermore, other variables such as attitudes towards video games, punctiliousness, and reading speed correlated with error detection in video game localisation testing. These findings may contribute to the enhancement of tester selection and training processes, resulting in superior localisations and more satisfying player experiences across diverse languages and cultures.

Baseline surveillance in Li Fraumeni syndrome using whole-body MRI: a systematic review and updated meta-analysis.

Li-Fraumeni syndrome (LFS) is a cancer syndrome associated with early-onset neoplasias. The use of whole-body magnetic resonance imaging (WBMRI) is recommended for regular cancer screening, however, evidence supporting the benefits in asymptomatic LFS patients is limited. This study aims to assess the clinical utility of WBMRI in germline TP53 mutation carriers at baseline and follow-up. We systematically searched PubMed, Cochrane, and Embase databases for studies evaluating WBMRI as an early detection method for tumor screening in patients with LFS. We pooled the prevalence of the included variables along with their corresponding 95% confidence intervals (CIs). Statistical analyses were performed using R software, version 4.3.1. From 1687 results, 11 comprising 703 patients (359 females (51%); with a median age of 32 years (IQR 1-74)) were included. An estimated detection rate of 31% (95% CI: 0.28, 0.34) for any suspicious lesions was found in asymptomatic TP53 carriers who underwent baseline WBMRI. A total of 277 lesions requiring clinical follow-up were identified in 215 patients. Cancer was confirmed in 46 lesions across 39 individuals. The estimated cancer diagnosis rate among suspicious lesions was 18% (95% CI: 0.13, 0.25). WBMRI detected 41 of the 46 cancers at an early-disease stage, with an overall detection rate of 6% (95% CI: 0.05, 0.08). The incidence rate was 2% per patient round of WBMRI (95% CI: 0.01, 0.04), including baseline and follow-up. This meta-analysis provides evidence that surveillance with WBMRI is effective in detecting cancers in asymptomatic patients with LFS. Our study demonstrates that whole-body MRI is an effective tool for early cancer detection in asymptomatic Li-Fraumeni Syndrome patients, highlighting its importance in surveillance protocols to improve diagnosis and treatment outcomes. Current evidence for whole-body MRI screening of asymptomatic Li-Fraumeni Syndrome (LFS) patients remains scarce. Whole-body MRI identified 41 out of 46 cancers at an early stage, achieving an overall detection rate of 6%. Whole-body MRI surveillance is a valuable method for detecting cancers in asymptomatic LFS patients.

Modeling the population health impact of incorporating a multi-cancer early detection (MCED) test to existing cancer screening among immunocompromised individuals

Objective: To assess the screening efficiency of an MCED test added to SoC screening, compared to SoC screening alone, among immunocompromised individuals, and to estimate the diagnostic workup costs associated with positive screening results. Methods: We estimated the potential impact of cancer screening among immunocompromised individuals aged 50-79 years within the University of Utah Health system who underwent a stem cell/solid organ transplant or were diagnosed with a primary or secondary immunodeficiency disorder between January 2000 and February 2018. We derived cancer incidence rates from the Huntsman Cancer Institute Tumor Registry, and screening performance of SoC screening and an MCED test from published literature. Outcomes of screening efficiency included the true-positive to false-positive (TP:FP) ratio, diagnostic yield (DY), and cancer detection rate (CDR) for SoC screening alone and an incremental MCED test. Scenario and probabilistic sensitivity analyses were conducted. Results: Among 4932 immunocompromised individuals aged 50-79 years, we estimated that 2595 tests would be done under SoC screening and assumed that all individuals received an additional MCED test. Adding an MCED test to SoC screening substantially improved screening efficiency (TP:FP 1:1, DY 5.15/1000 tests, CDR 42.0%), compared to SoC screening alone (TP:FP 1:99, DY 1.23/1000 tests, CDR 5.3%), assuming an MCED test with 100% uptake. Our findings were also robust to parameter uncertainty. Conclusion: Adding an MCED test to complement existing screening may be a highly efficient strategy to increase the detection of cancers among immunocompromised individuals. These results could help to improve cancer prevention and detection efforts among individuals with multiple cancer risk factors.

The potential of repeated mean arterial pressure measurements for predicting early- and late-onset pre-eclampsia in twin pregnancies: Prediction model study.

To investigate the contribution of longitudinal mean arterial pressure (MAP) measurement during the first, second, and third trimesters of twin pregnancies to the prediction of pre-eclampsia. A retrospective cohort study was conducted on women with twin pregnancies. Historical data between 2019 and 2021 were analyzed, including maternal characteristics and mean artery pressure measurements were obtained at 11-13, 22-24, and 28-33 weeks of gestation. The outcome measures included pre-eclampsia with delivery <34 and ≥34 weeks of gestation. Models were developed using logistic regression, and predictive performance was evaluated using the area under the curve, detection rate at a given false-positive rate of 10%, and calibration plots. Internal validation was conducted via bootstrapping. A total of 943 twin pregnancies, including 36 (3.82%) women who experienced early-onset pre-eclampsia and 93 (9.86%) who developed late-onset pre-eclampsia, were included in this study. To forecast pre-eclampsia during the third trimester, the most accurate prediction for early-onset pre-eclampsia resulted from a combination of maternal factors and MAP measured during this trimester. The optimal predictive model for late-onset pre-eclampsia includes maternal factors and MAP data collected during the second and third trimesters. The areas under the curve were 0.937 (95% confidence interval [CI] 0.894-0.981) and 0.887 (95% CI 0.852-0.921), respectively. The corresponding detection rates were 83.33% (95% CI 66.53%-93.04%) for early-onset pre-eclampsia and 68.82% (95% CI 58.26%-77.80%) for late-onset pre-eclampsia. Repeated measurements of MAP during pregnancy significantly improved the accuracy of late-onset pre-eclampsia prediction in twin pregnancies. The integration of longitudinal data into pre-eclampsia screening may be an effective and valuable strategy.

Drivers of change behind the spatial distribution and fate of typical trace organic pollutants in fresh waste leachate across China

There have been growing concerns regarding the health and environmental impacts of trace organic pollutants (TOPs). However, fresh leachate from municipal solid waste (MSW) has been overlooked as a potential reservoir of TOPs. Therefore, we investigated 90 legacy and emerging TOPs in fresh leachate from 14 provinces and municipalities in China. Additionally, the fate and final discharge impacts of TOPs in 14 leachate treatment systems were analyzed. The results revealed that the detection rate of 90 TOPs was over 50 % in all samples. Notably, polychlorinated biphenyls, banned for 40 years, were frequently detected in fresh leachate. The concentration of pseudo-persistent TOPs (105–107 ng/L) is significantly higher than that of persistent TOPs (102–104 ng/L). Spatial distribution patterns of TOPs in fresh leachate suggest that economy, population, climate, and policies impact TOPs discharge from MSW. For example, economically developed and densely populated areas displayed higher TOPs concentrations, whereas warmer climates facilitate TOPs leaching from MSW. We confirmed that waste classification policies were a key driver of the decline in multiple TOPs in leachate. Mass balance analysis shows that the final effluent and sludge from current dominant leachate treatment systems contain refractory TOPs, especially perfluoroalkyl acids, which must be prioritized for control. This paper was the first comprehensive investigation of multiple TOPs in fresh leachate at a large geographic scale. The factors affecting the occurrence, spatial distribution, and fate of TOPs in fresh leachate were revealed. It provides a valuable reference for the establishment of policies for the management of TOPs in MSW and the associated leachate.

Effectiveness of colonoscopy, immune fecal occult blood testing, and risk-graded screening strategies in colorectal cancer screening.

Colorectal cancer (CRC) is one of the most common malignant tumors, and early screening is crucial to improving the survival rate of patients. The combination of colonoscopy and immune fecal occult blood detection has garnered significant attention as a novel method for CRC screening. Colonoscopy and fecal occult blood tests, when combined, can improve screening accuracy and early detection rates, thereby facilitating early intervention and treatment. However, certain risks and costs accompany it, making the establishment of a risk classification model crucial for accurate classification and management of screened subjects. To evaluate the feasibility and effectiveness of colonoscopy, immune fecal occult blood test (FIT), and risk-graded screening strategies in CRC screening. Based on the randomized controlled trial of CRC screening in the population conducted by our hospital May 2020 to May 2023, participants who met the requirements were randomly assigned to a colonoscopy group, an FIT group, or a graded screening group at a ratio of 1:2:2 (after risk assessment, the high-risk group received colonoscopy, the low-risk group received an FIT test, and the FIT-positive group received colonoscopy). The three groups received CRC screening with different protocols, among which the colonoscopy group only received baseline screening, and the FIT group and the graded screening group received annual follow-up screening based on baseline screening. The primary outcome was the detection rate of advanced tumors, including CRC and advanced adenoma. The population participation rate, advanced tumor detection rate, and colonoscopy load of the three screening programs were compared. A total of 19373 subjects who met the inclusion and exclusion criteria were enrolled, including 8082 males (41.7%) and 11291 females (58.3%). The mean age was 60.05 ± 6.5 years. Among them, 3883 patients were enrolled in the colonoscopy group, 7793 in the FIT group, and 7697 in the graded screening group. Two rounds of follow-up screening were completed in the FIT group and the graded screening group. The graded screening group (89.2%) and the colonoscopy group (42.3%) had the lowest overall screening participation rates, while the FIT group had the highest (99.3%). The results of the intentional analysis showed that the detection rate of advanced tumors in the colonoscopy group was greater than that of the FIT group [2.76% vs 2.17%, odds ratio (OR) = 1.30, 95% confidence interval (CI): 1.01-1.65, P = 0.037]. There was no significant difference in the detection rate of advanced tumors between the colonoscopy group and the graded screening group (2.76% vs 2.35%, OR = 1.9, 95%CI: 0.93-1.51, P = 0.156), as well as between the graded screening group and the FIT group (2.35% vs 2.17%, OR = 1.09%, 95%CI: 0.88-1.34, P = 0.440). The number of colonoscopy examinations required for each patient with advanced tumors was used as an index to evaluate the colonoscopy load during population screening. The graded screening group had the highest colonoscopy load (15.4 times), followed by the colonoscopy group (10.2 times), and the FIT group had the lowest (7.8 times). A hierarchical screening strategy based on CRC risk assessment is feasible for screening for CRC in the population. It can be used as an effective supplement to traditional colonoscopy and FIT screening programs.

Device programing and SMART pass algorithm activation in subcutaneous implantable defibrillator patients: Data from a remote monitoring database.

The programing of subcutaneous implantable cardioverter-defibrillators (S-ICD) in clinical practice has been little studied, as the activation status of the SMART Pass filter, which was implemented to reduce inappropriate shocks. We assessed device programing during follow-up and the rate of detected arrhythmias in consecutive S-ICD recipients. We analyzed data from 670 S-ICD patients followed on the remote network at 17 Italian centers for a median of 31 months (25th-75th percentile: 16-51). The enhanced SMART Pass version, introduced in October 2022, was expected to reduce the unintentional deactivation rate. At the latest remote data transmission, the median conditional zone cut-off was set to 210bpm (25th-75th percentile: 200-220), the shock zone cutoff was 250bpm (25th-75th percentile: 240-250), and the SMART Pass was enabled in 586 (87%) patients. During follow-up, 194 automatic deactivation events were reported in 118 (18%) patients. Shocks were delivered in 129 (19%) patients, and untreated arrhythmias were recorded in 136 (20%) patients. The rate of shocks was lower when SMART Pass was enabled -0.12/patient-year (95% CI: 0.10-0.14) versus 0.20 (95% CI: 0.15-0.26) (p=.002), as it was the rate of untreated arrhythmias -0.12/patient-year (95% CI: 0.11-0.14) versus 0.23 (95% CI: 0.18-0.30) (p=.001). The enhanced SMART Pass version was associated with a lower rate of deactivations -0.04/patient-year (95% CI: 0.02-0.05) versus 0.14 (95% CI: 0.12-0.16) (p<.001), and with a reduction in treated and untreated arrhythmias (Incidence rate ratios: 0.40 (95% CI: 0.28-0.53) and 0.40 (95% CI: 0.30-0.55), respectively (p<.001)). Centers tend to program devices to detect high ventricular rates for arrhythmia detection, to minimize inappropriate shock occurrences. SMART Pass activation is associated with lower rates of detected and treated arrhythmias. The enhanced SMART Pass version seems associated with a lower deactivation rate and with a further decrease in treated arrhythmias.

Clinically significant prostate cancer detection rate in biopsy-naïve patients with mpMRI and microultrasound topographically discordant lesions: A single-center retrospective analysis

Introduction and objectivesMultiparametric magnetic resonance imaging (mpMRI) has improved the detection of clinically significant prostate cancer (csPCa), and microultrasound (micro-US) shows promise in enhancing detection rates. We compared mpMRI-guided targeted biopsy (MTBx) and micro–US-guided targeted biopsy (micro–US-TBx) in biopsy-naïve patients with discordant lesions at micro-US and mpMRI to detect csPCa (grade group ≥2) and clinically insignificant PCa (ciPCa; grade group 1) and assessed the role of nontargeted systematic biopsy (SBx). Material and MethodsWe analyzed 178 biopsy-naive men with suspected PCa and discordant lesions at mpMRI and micro-US. All patients underwent mpMRI followed by micro-US, the latter being performed immediately before the biopsy. Imaging findings were interpreted blindly, followed by targeted and SBx. Median age was 63 years (IQR, 57–70), median prostate-specific antigen level was 7 ng/mL (IQR, 5–9 ng/mL), and median prostate volume was 49 cm^3 (IQR, 35–64 cm^3). Overall, 86/178 (48%) patients were diagnosed with PCa, 51/178 (29%) with csPCa. ResultsMicro-USTBx detected csPCa in 36/178 men (20%; 95% CI: 26–46), and MTBx detected csPCa in 28/178 men (16%; 95% CI: 36–50), resulting in a -8% difference (95% CI: −10, 4; P = 0.022) and a relative detection rate of 0.043. Micro-USTBx detected ciPCa in 9/178 men (5%; 95% CI: 3, 15), while MTBx detected ciPCa in 12/178 men (7%; 95% CI: 5, 20), resulting in a −3% difference (95% CI: −2 to 4; P = 0.2) and a relative detection rate of 0.1. SBx detected ciPCa in 29 (16%) men. mpMRI plus micro-US detected csPCa in 51/178 men, with no additional cases with the addition of SBx. Similarly, MTBx plus micro-USTBx plus SBx detected ciPCa in 35/178 men (20%; 95% CI: 18, 37) compared to 9 (5%) in the micro-US pathway (P = 0.002) and 14/178 (8%; 95% CI: 6, 26) in the mpMRI plus micro-US pathway (P = 0.004). ConclusionsIn conclusion, a combined micro-US/mpMRI approach could characterize primary disease in biopsy-naïve patients with discordant lesions, potentially avoiding SBx. Further studies are needed to validate our findings and assess micro-US's role in reducing unnecessary biopsies.

A novel ECG compression algorithm using Pulse-Width Modulation integrated quantization for low-power real-time monitoring

Cardiac monitoring systems in Internet of Things (IoT) healthcare, reliant on limited battery and computational capacity, need efficient local processing and wireless transmission for comprehensive analysis. Due to the power-intensive wireless transmission in IoT devices, ECG signal compression is essential to minimize data transfer. This paper presents a real-time, low-complexity algorithm for compressing electrocardiogram (ECG) signals. The algorithm uses just nine arithmetic operations per ECG sample point, generating a hybrid Pulse Width Modulation (PWM) signal storable in a compact 4-bit resolution format. Despite its simplicity, it performs comparably to existing methods in terms of Percentage Root-Mean-Square Difference (PRD) and space-saving while significantly reducing complexity and maintaining robustness against signal noise. It achieves an average Bit Compression Ratio (BCR) of 4 and space savings of 90.4% for ECG signals in the MIT-BIH database, with a PRD of 0.33% and a Quality Score (QS) of 12. The reconstructed signal shows no adverse effects on QRS complex detection and heart rate variability, preserving both the signal amplitude and periodicity. This efficient method for transferring ECG data from wearable devices enables real-time cardiac activity monitoring with reduced data storage requirements. Its versatility suggests potential broader applications, extending to compression of various signal types beyond ECG.

Prospective Study of Supplemental Screening With Contrast-Enhanced Mammography in Women With Elevated Risk of Breast Cancer: Results of the Prevalence Round.

Contrast-enhanced mammography (CEM) and magnetic resonance imaging (MRI) have shown similar diagnostic performance in detection of breast cancer. Limited CEM data are available for high-risk breast cancer screening. The purpose of the study was to prospectively investigate the efficacy of supplemental screening CEM in elevated risk patients. A prospective, single-institution, institutional review board-approved observational study was conducted in asymptomatic elevated risk women age 35 years or older who had a negative conventional two-dimensional digital breast tomosynthesis screening mammography (MG) and no additional supplemental screening within the prior 12 months. Four hundred sixty women were enrolled from February 2019 to April 2021. The median age was 56.8 (range, 35.0-79.2) years; 408 of 460 (88.7%) were mammographically dense. Biopsy revealed benign changes in 22 women (22/37, 59%), high-risk lesions in four women (4/37, 11%), and breast cancer in 11 women (11/37, 30%). Fourteen cancers (10 invasive, tumor size range 4-15 mm, median 9 mm) were diagnosed in 11 women. The overall supplemental cancer detection rate was 23.9 per 1,000 patients, 95% CI (12.0 to 42.4). All cancers were grade 1 or 2, ER+ ERBB2-, and node negative. CEM imaging screening offered high specificity (0.875 [95% CI, 0.844 to 0.906]), high NPV (0.998 [95% CI, 0.993 to 1.000), moderate PPV1 (0.164 [95% CI, 0.076 to 0.253), moderate PPV3 (0.275 [95% CI, 0.137 to 0.413]), and high sensitivity (0.917 [95% CI, 0.760 to 1.000]). At least 1 year of imaging follow-up was available on all patients, and one interval cancer was detected on breast MRI 4 months after negative screening CEM. A pilot trial demonstrates a supplemental cancer detection rate of 23.9 per 1,000 in women at an elevated risk for breast cancer. Larger, multi-institutional, multiyear CEM trials in patients at elevated risk are needed for validation.

Endoscopic Artificial Intelligence for Image Analysis in Gastrointestinal Neoplasms.

Artificial intelligence (AI) using deep learning systems has recently been utilized in various medical fields. In the field of gastroenterology, AI is primarily implemented in image recognition and utilized in the realm of gastrointestinal (GI) endoscopy. In GI endoscopy, computer-aided detection/diagnosis (CAD) systems assist endoscopists in GI neoplasm detection or differentiation of cancerous or non-cancerous lesions. Several AI systems for colorectal polyps have already been applied in colonoscopy clinical practices. In esophagogastroduodenoscopy, a few CAD systems for upper GI neoplasms have been launched in Asian countries. The usefulness of these CAD systems in GI endoscopy has been gradually elucidated. In this review, we outline recent articles on several studies of endoscopic AI systems for GI neoplasms, focusing on esophageal squamous cell carcinoma (ESCC), esophageal adenocarcinoma (EAC), gastric cancer (GC), and colorectal polyps. In ESCC and EAC, computer-aided detection (CADe) systems were mainly developed, and a recent meta-analysis study showed sensitivities of 91.2% and 93.1% and specificities of 80% and 86.9%, respectively. In GC, a recent meta-analysis study on CADe systems demonstrated that their sensitivity and specificity were as high as 90%. A randomized controlled trial (RCT) also showed that the use of the CADe system reduced the miss rate. Regarding computer-aided diagnosis (CADx) systems for GC, although RCTs have not yet been conducted, most studies have demonstrated expert-level performance. In colorectal polyps, multiple RCTs have shown the usefulness of the CADe system for improving the polyp detection rate, and several CADx systems have been shown to have high accuracy in colorectal polyp differentiation. Most analyses of endoscopic AI systems suggested that their performance was better than that of non-expert endoscopists and equivalent to that of expert endoscopists. Thus, Endoscopic AI systems may be useful for reducing the risk of overlooking lesions and improving the diagnostic ability of endoscopists.

Unisex and Sex-Specific Prescriptive Fetal Growth Charts for Improved Detection of Small-for-Gestational-Age Babies in a Low-Risk Population: A post hoc Analysis of a Cluster-Randomized Study.

Our aim was to develop and evaluate the performance of population-based sex-specific and unisex prescriptive fetal abdominal circumference growth charts in predicting small-for-gestational-age (SGA) birthweight, severe SGA (sSGA) birthweight, and severe adverse perinatal outcomes (SAPO) in a low-risk population. This is a post hoc analysis of the Dutch nationwide cluster-randomized IRIS study, encompassing ultrasound data of 7,704 low-risk women. IRIS prescriptive unisex and IRIS sex-specific abdominal circumference (AC) fetal growth charts were derived using quantile regression. As a comparison, we used the descriptive unisex Verburg chart, which is commonly applied in the Netherlands. Diagnostic parameters were calculated based on the 34-36 weeks' ultrasound. Sensitivity rates for predicting SGA and sSGA birthweights were more than twofold higher based on the IRIS prescriptive sex-specific (respectively SGA 43%; sSGA 59%) and unisex (SGA 39%; sSGA 55%) charts, compared to the Verburg chart (SGA 16%; sSGA 23% both p &lt; 0.01). Specificity rates were highest for Verburg (SGA 99%; sSGA 98%) and lowest for IRIS sex-specific (SGA 94%; sSGA 92%). Results for predicting SGA with SAPO were similar for the prescriptive charts (44%), and again higher than the Verburg chart (20%). The IRIS sex-specific chart identified significantly more males as SGA and sSGA (respectively, 42%; 60%, p &lt; 0.001) than the IRIS unisex chart (respectively, 35%; 53% p &lt; 0.01). Our study demonstrates improved performance of both the IRIS sex-specific and unisex prescriptive fetal growth compared to the Verburg descriptive chart, doubling detection rates of SGA, sSGA, and SGA with SAPO. Additionally, the sex-specific chart outperformed the unisex chart in detecting SGA and sSGA. Our findings suggest the potential benefits of using prescriptive AC fetal growth charts in low-risk populations and emphasize the importance of considering customizing fetal growth charts for sex. Nevertheless, the increased sensitivity of these charts should be weighed against the decrease in specificity.

Associations of physical activity and soybean product consumption with psychological symptoms: a cross-sectional survey of Chinese university students

IntroductionDeclining physical activity among university students has become a concern, with increasingly poor dietary behaviors and other unfavorable factors having an impact on the occurrence of psychological symptoms. Previous studies have analyzed the association between moderate-to-vigorous physical activity (MVPA) and psychological symptoms, but few studies have investigated the association between soy product consumption and these symptoms. In addition, the associations between physical activity and soy product consumption with psychological symptoms have not been investigated.MethodsIn this study, 7267 university students from different regions of China were surveyed regarding physical activity, soy product consumption, and psychological symptoms. Binary logistic regression was used to analyze the associations among MVPA, soy product consumption, and psychological symptoms. A generalized linear model (GLM) was applied to further analyze the associations of MVPA and soy product consumption with psychological symptoms in this population.ResultsThe detection rate of psychological symptoms among Chinese university students was 17.9%, with the rate among female students (18.9%) higher than that among male students (16.6%). The proportion of university students with MVPA < 30 min/d, 30–60 min/d, and > 60 min/d was 76.1%, 19.3%, and 4.6%, respectively, and the proportion with soy product consumption ≤ 2 times/wk, 3–5 times/wk, and ≥ 5 times/wk was 25.8%, 42.4%, and 31.7%, respectively. The GLM showed that compared with university students who had MVPA < 30 min/d and soy product consumption ≤ 2 times/week, those with the lowest risk of developing psychological symptoms had MVPA > 60 min/d and soy product consumption ≥ 6 times/week (OR = 0.198, 95% CI: 0.100–0.393, P < 0.001). This group was followed by university students with MVPA > 60 min/d and soy product consumption 3–5 times/week (OR = 0.221, 95% CI: 0.102–0.479, P < 0.001).ConclusionIn terms of research, there is an association between physical activity and soy product consumption and psychological symptoms among university students. The results of our study suggest that integrated intervention for psychological symptoms among university students is needed from the perspectives of physical activity and dietary behavior to promote good mental health in this population.

Occurrence and health risk assessment of toxic metals and rare earth elements in microalgae: Insight into potential risk factors in new sustainable food resources

Microalgae are a promising sustainable food source with high nutritional value and environmental benefits. This study investigated the presence of toxic metals and rare earth elements (REEs) in 68 microalgal-based food products and conducted a probabilistic risk assessment to evaluate potential health risks. The findings revealed high detection rates of REEs (80.96% to 100%) and heavy metals (83.82% to 100%), with REE concentrations ranging from 0.0055 to 0.5207 mg/kg. Heavy metals were detected at the following average concentrations: As (2.80 mg/kg) > Cr (1.27 mg/kg) > Pb (0.30 mg/kg) > Cd (0.20 mg/kg) > Hg (0.01 mg/kg). Carcinogenic risk analysis for Cd (3.004 × 10−3), Cr (1.484 × 10−3), and As (1.1283 × 10−2) indicated that 95th percentile values exceeded established safety thresholds (10−4). These findings highlight the critical need for stringent monitoring and the establishment of comprehensive regulatory frameworks for the safety of novel microalgae foods.

The recovery of endoscopic activity and cancer detection after the COVID-19 pandemic

BackgroundThe COVID-19 pandemic had a substantial impact on cancer services. The aim of our study was to evaluate the recovery of endoscopic activity and cancer detection after the COVID-19 pandemic. MethodsEndoscopic data from January 2019 to December 2020 were retrospectively collected to assess the endoscopic activity and cancer detection during the COVID-19 peak period (February 2020) and the post-COVID-19 peak period (March to July 2020). ResultsThe COVID-19 pandemic almost brought endoscopic activity and cancer detection to a standstill. Diagnostic procedure and endoscopic resection showed the greatest reduction. With the decline in COVID-19 infections, endoscopic activity gradually returned to previous level in July. However, the detection rate of gastric cancer resumed in September, whereas colorectal cancer resumed in August. The monthly detection rates of gastric and colorectal cancers decreased from their initial peaks of 2.98 % and 6.45 %, respectively, and finally were even lower than the average in 2019. Similarly, the mean age of patients who received endoscopy also declined as the detection rates resumed. The increasing colonoscopies allowed the missing colorectal cancer patients to be caught up. In contrast, it was expected that 6.69 % of gastric cancer patients were missed and did not receive needed endoscopy. ConclusionsThe recovery of cancer detection occurred later than that of endoscopic activity, especially for gastric cancer. Older people were vulnerable to the continuous impact of COVID-19 pandemic than young people for seeking medical services. Urgent efforts are required to recover and maintain cancer services before subsequent waves of the COVID-19 pandemic.

Introduction of one-view tomosynthesis in population-based mammography screening: Impact on detection rate, interval cancer rate and false-positive rate.

To assess performance endpoints of a combination of digital breast tomosynthesis (DBT) and full-field digital mammography (FFDM) compared with FFDM only in breast cancer screening. This was a prospective population-based screening study, including eligible (50-69 years) women attending the Capital Region Mammography Screening Program in Denmark. All attending women were offered FFDM. A subgroup was consecutively allocated to a screening room with DBT. All FFDM and DBT underwent independent double reading, and all women were followed up for 2 years after screening date or until next screening date, whichever came first. 6353 DBT + FFDM and 395 835 FFDM were included in the analysis and were undertaken in 196 267 women in the period from 1 November 2012 to 12 December 2018. Addition of DBT increased sensitivity: 89.9% (95% confidence interval (CI): 81.0-95.5) for DBT + FFDM and 70.1% (95% CI: 68.6-71.6) for FFDM only, p < 0.001. Specificity remained similar: 98.2% (95% CI: 97.9-98.5) for DBT + FFDM and 98.3% (95% CI: 98.2-98.3) for FFDM only, p = 0.9. Screen-detected cancer rate increased statistically significantly: 11.18/1000 for DBT + FFDM and 6.49/1000 for FFDM only, p < 0.001. False-positive rate was unchanged: 1.75% for DBT + FFDM and 1.73% for FFDM only, p = 0.9. Positive predictive value for recall was 39.0% (95% CI: 31.9-46.5) for DBT + FFDM and 27.3% (95% CI: 26.4-28.2), for FFDM only, p < 0.0005. The interval cancer rate decreased: 1.26/1000 for DBT + FFDM and 2.76/1000 for FFDM only, p = 0.02. DBT + FFDM yielded a statistically significant increase in cancer detection and program sensitivity.