Detection Rate Research Articles

Enhancement of detection accuracy for preventing iris presentation attack

A system that recognizes the iris is susceptible to presentation attacks (PAs), in which a malicious party shows artefacts such as printed eyeballs, patterned contact lenses, or cosmetics to obscure their personal identity or manipulate someone else’s identity. In this study, we suggest the dual channel DenseNet presentation attack detection (DC-DenseNetPAD), an iris PA detector based on convolutional neural network architecture that is dependable and effective and is known as DenseNet. It displays generalizability across PA datasets, sensors, and artifacts. The efficiency of the suggested iris PA detection technique has been supported by tests performed on a popular dataset which is openly accessible (LivDet-2017 and LivDet-2015). The proposed technique outperforms state-of-the-art techniques with a true detection rate of 99.16% on LivDet-2017 and 98.40% on LivDet-2015. It is an improvement over the existing techniques using the LivDet-2017 dataset. We employ Grad-CAM as well as t-SNE plots to visualize intermediate feature distributions and fixation heatmaps in order to demonstrate how well DC-DenseNetPAD performs.

Prospective comparison of 68Ga-DOTA-ibandronate and bone scans for detecting bone metastases in breast cancer

Introduction68Ga labeled DOTA-Ibandronate (68Ga-DOTA-IBA) positron emission tomography/computed tomography (PET/CT), is a novel bone-targeting imaging tracer and promising diagnostic method for bone metastases detection. Therefore, this study aimed to compare 68Ga-DOTA-IBA PET/CT to the 99mTc-MDP whole-body bone scan (WBBS) for detecting bone metastases in breast cancer (BC).Materials and methodsIn this prospective study, 45 women with BC underwent imaging via 68Ga-DOTA-IBA PET/CT and 99mTc-MDP WBBS. Clinical and demographic information as well as BC imaging features were recorded. The two methods were compared in terms of their detection rate for bone metastases and the number of lesions.ResultsThe 45 women were aged 53.5 ± 11.0 years. The bone metastases detection rate with 68Ga-DOTA-IBA PET/CT was 100% (45/45) and with 99mTc-MDP WBBS was 95.6% (43/45). A total of 546 bone metastases lesions were detected. The lesion detection rate using 68Ga-DOTA-IBA PET/CT was 100% (546/546) and using 99mTc-MDP WBBS was 67.8% (370/546). More lesions were found at each site via 68Ga-DOTA-IBA than via 99mTc-MDP WBBS.Conclusions68Ga-DOTA-IBA PET/CT is a more sensitive method than 99mTc-MDP WBBS for assessing bone metastases in BC and may therefore represent a useful imaging technique for bone metastases, while offering a visual basis for 177Lu-DOTA-IBA diagnosis and therapy response assessments for BC. Further validation using a broader study cohort is warranted to confirm these findings.Clinical trial registrationhttps://www.chictr.org.cn/showproj.html?proj=170163, identifier ChiCTR2200064487.

OPIN-ITP: Optimized Physics Informed Network with Trimmed Score Regression Based Insider Threats Prediction in Cloud Computing

INTRODUCTION: Insider threats are a major issue for cyber security. In contrast to external attackers, insiders have more privileges and authorized access to data and resources, which can cause an organization great harm. To completely understand an insider's activities throughout the organization, a more sophisticated method is needed. OBJECTIVES: Based on an organization's login activity, this study proposes a novel conceptual method for insider threat detection. Behavioural activities such as HTTP, Email and Login details are collected to create a dataset which is further processed for pre-processing using data transformation and Trimmed Score Regression (TSR). METHODS: These pre-data are given to the feature extraction process using Deep Feature Synthesis (DFS) extraction. The extracted data are fed to Physics Informed Neural Networks (PINN) for insider threat detection. RESULTS: The prediction process of PINN was improved through optimally choosing parameters such as learning rate and weight using Hunter-prey Optimization (HPO). The proposed model offers 68% detection rate, 98.4% accuracy, 5% FDR, 95% F1_score and 0.7005 sec execution time. CONCLUSION: Observed outcomes are compared to other traditional approaches of validation. The contrast with traditional approaches shows that the proposed model provides better outcomes than in traditional models and is therefore a good fit for real-time threat prediction.

The Influence of Race on Detected and Undetected Sexual Offense Histories: A Comparison of White and Black Men Committed as Sexually Violent Persons.

Understanding the difference between the proportion of sexual offenses that are officially detected versus the total number of sexual crimes that occur has been of interest to decision makers for some time. Previous studies have not considered possible racial differences. More aggressive responses by police and the criminal justice system as well as cultural differences in victim type/reporting rates may result in differences between detection rates of Black versus White men. In the current study (N = 190), we examined the difference between Black (n = 51) and White (n = 139) men committed to a forensic hospital as a Sexually Violent Person on factors that could impact the detected rate. Overall, we found that White men had significantly more total victims, undetected victims, undetected and detected child victims, total male victims, undetected male victims, undetected acquaintance victims, and total (detected and undetected) acquaintance victims than Black men. Black men had significantly more detected adult victims, but this difference did not remain when accounting for undetected victims. We explore reasons for these differences as well as provide recommendations for practice.

Evaluation of the Most Important Ultrasound Parameters in Detection of Thyromegaly and its Relationship with Anthropometric Factors

Background: Approximately, 200 million people suffer from thyroid disorders worldwide. Thyromegaly is a disorder in which the thyroid gland becomes abnormally enlarged. High-resolution ultrasound of the thyroid is a useful diagnostic method for assessing thyroid disorders, including thyromegaly. To investigate the thyromegaly, the thyroid lobe dimensions are measured separately using an ultrasound device and, the thyroid volume is estimated using a formula which is time-consuming process. Besides, thyroid volume depends on a variety of factors such as age, sex, anthropometric parameters, and genetic factors. Objectives: The aim of the present study is to find the most important ultrasound parameters measured to increase the rate of thyromegaly detection and also to find the relationship between thyroid volume and some anthropometric characteristics in the study population. Methods: A total of 131 people were referred to the Ultrasound Department of Imam Reza Hospital in Kermanshah, Iran during July 2017 and 2019, and after recording the anthropometric characteristics, thyroid ultrasound was taken. Thyroid dimensions including longitudinal (L) and anterior-posterior or depth (AP), and width (W) diameter of the thyroid lobes and isthmus were measured and thyroid volume was calculated using the ellipsoid formula. According to the opinion of a fellow radiologist and considering cut-off point of volume (11.1 for women and 11.6 for men), individuals were divided into two groups: Case or thyromegaly (n = 69) and control or normal group (n = 62), and statistical analysis was then carried out. Results: Statistical analysis showed that the mean weight, Body Mass Index (BMI), thyroid dimensions, and total thyroid volume were significantly higher in the case group than the control group (P < 0.05). In the case group, only the mean width of the right lobe is significantly larger than the left lobe, while the mean length and depth of the right lobe is significantly larger in the control group than the left lobe. In addition, cut-off point values for the width of right lobe, depth of the right lobe, length of the right lobe, volume of the right lobe, width of the left lobe, depth of the left lobe, length of the left lobe, volume of the left lobe, total volume and isthmus volume were 16.5,15.5, 47.5, 6.45, 15.5, 14.5, 44.5, 5.55, 11.15, and 2.45, respectively based on the best sensitivity and specificity of the receiver operating characteristic (ROC) curve. According to logistic regression, the three factors of width of the right lobe, depth of the right lobe, and length of the right lobe, respectively, were selected as the most important ultrasound parameters in detection of thyromegaly. Thyroid volume was not significantly related with sex, age, and height, but it was directly and significantly related with weight and BMI. Conclusions: Considering the increasing use of ultrasound in detection of thyroid disease and its acceptable accuracy in determining the thyroid volume, the radiologists need to first know the normal thyroid volume and the effect of physiological variables (such as age, sex, body weight, and BMI) on the thyroid volume in their community so that they can distinguish pathological cases from normal ones. Also, the three factors of width of the right lobe, depth of the right lobe, and length of the right lobe, respectively, were determined as the most important factors in detection of thyromegaly. Thyroid volume was not significantly related with sex, age, and height, but it was directly and significantly related with weight and BMI.

Experience in the application of the Graf technique in Beijing

Aim: The aim was to review several aspects of work using ultrasound in diagnosing developmental dysplasia of the hip and analyze the application status of the Graf technique in Beijing over 15 years. Methods: First, data on the promotion and development of the Graf technique in Beijing over the past 15 years were retrospectively analyzed. Second, data on hip ultrasound (US) screening and the effect of consecutive brace therapy were collected and analyzed. Infants were divided into subgroups according to Graf type, age at initiation of treatment, sex, and affected side. Results: The ultrasound detection rate of developmental dysplasia of the hip (DDH) was high at Beijing Jishuitan Hospital. The total detection rate of type IIa, IIb, IIc, D, III and IV (abbreviated as: types IIa and worse) was 4.58%, and that of type IIb, IIc, D, III and IV (abbreviated as: types IIb and worse) was 1.40%. Clinicians should pay attention to DDH, and early treatment is important; therefore, it is recommended that infants and young children undergo DDH ultrasound screening as soon as possible. Our research shows that when the α angle was more than 43°, the efficacy of brace therapy was 95.95%. Conclusions: It was confirmed that the Graf technique has greater practicality and accuracy. The Graf technique, as an important means for the early screening of DDH, has been widely recognized around the world, and it is recommended to be widely used in China to preserve future health in as many children as possible.

Key influences on dysglycemia across Fujian's urban-rural divide.

Screening and treatment of dysglycemia (prediabetes and diabetes) represent significant challenges in advancing the Healthy China initiative. Identifying the crucial factors contributing to dysglycemia in urban-rural areas is essential for the implementation of targeted, precise interventions. Data for 26,157 adults in Fujian Province, China, were collected using the Social Factors Special Survey Form through a multi-stage random sampling method, wherein 18 variables contributing to dysglycemia were analyzed with logistic regression and the random forest model. Investigating urban-rural differences and critical factors in dysglycemia prevalence in Fujian, China, with the simultaneous development of separate predictive models for urban and rural areas. The detection rate of dysglycemia among adults was 35.26%, with rates of 34.1% in urban areas and 35.8% in rural areas. Common factors influencing dysglycemia included education, age, BMI, hypertension, and dyslipidemia. For rural residents, higher income (OR = 0.80, 95% CI [0.74, 0.87]), average sleep quality (OR = 0.89, 95% CI [0.80, 0.99]), good sleep quality (OR = 0.89, 95% CI [0.80, 1.00]), and high physical activity (PA) (OR = 0.87, 95% CI [0.79, 0.96]) emerged as protective factors. Conversely, a daily sleep duration over 8 hours (OR = 1.46, 95% CI [1.03, 1.28]) and middle income (OR = 1.12, 95% CI [1.03, 1.22]) were specific risk factors. In urban areas, being male (OR = 1.14, 95% CI [1.02, 1.26]), cohabitation (OR = 1.18, 95% CI [1.02, 1.37]), and central obesity (OR = 1.35, 95% CI [1.19, 1.53]) were identified as unique risk factors. Using logistic regression outcomes, a random forest model was developed to predict dysglycemia, achieving accuracies of 75.35% (rural) and 76.95% (urban) with ROC areas of 0.77 (rural) and 0.75 (urban). This study identifies key factors affecting dysglycemia in urban and rural Fujian residents, including common factors such as education, age, BMI, hypertension, and dyslipidemia. Notably, rural-specific protective factors are higher income and good sleep quality, while urban-specific risk factors include being male and central obesity. These findings support the development of targeted prevention and intervention strategies for dysglycemia, tailored to the unique characteristics of urban and rural populations.

Implementation of Sibi Sign Language Realtime Detection Program (Case Studi At Sekolah Luar Biasa Negeri 1 Tabanan)

Indonesian deaf people utilize SIBI to communicate using spoken words, gestures, facial expressions, and body language. SIBI, certified for Special Schools (SLB), helps deaf pupils communicate. This project implements SIBI (Indonesian Sign Language System) a real-time detection algorithm at Sekolah Luar Biasa Negeri 1 Tabanan using image processing and YoloV8 ultralytics deep learning. The program trains a sign language gesture detection model on Google Colab's GPU. The SIBI sign language images were used to train a YoloV8 object detection model. The camera captures movements, which the YoloV8 algorithm trained on SIBI gesture data processes. It can recognize gestures in real time and generate text to non-sign language users. The dataset has 107 class vocabulary and 7 class affix prefixes for complete gesture recognition. Shirt color, room brightness, and webcam quality affect detection rates. Optimal detection accuracy is 87.74% and subpar 58.02%. Despite these limitations, the strategy helps deaf students communicate more effectively with non-sign language speakers. This program improves inclusivity and communication in schools, making learning easier for hearing-impaired pupils. This work provides a reliable and quick sign language identification system to help deaf educators and caregivers with daily interactions and education.

Optimal prenatal genetic diagnostic approach for posterior fossa malformation: karyotyping, copy number variant testing, or whole-exome sequencing?

BackgroundPosterior fossa malformation (PFM) is a relatively uncommon prenatal brain malformation. Genetic diagnostic approaches, including chromosome karyotyping, copy number variant (CNV) testing, and whole-exome sequencing (WES), have been applied in several cases of fetal structural malformations. However, the clinical value of appropriate genetic diagnostic approaches for different types of PFMs has not been confirmed. Therefore, in this study, we aimed to analyze the value of different combined genetic diagnostic approaches for various types of fetal PFMs.MethodsThis retrospective study was conducted at Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital. Fifty-one pregnant women diagnosed with fetal PFMs who underwent genetic testing in our hospital from January 1, 2017 to December 31, 2022 were enrolled; women with an isolated enlarged cisterna magna were excluded. All participants were categorized into two groups according to the presence of other abnormalities: isolated and non-isolated PFMs groups. Different combined approaches, including karyotype analysis, CNV testing, and trio-based WES, were used for genetic analysis. The detection rates of karyotype analysis, CNV testing, and WES were measured in the isolated and non-isolated groups.ResultsIn isolated PFMs, pathogenic/likely pathogenic (P/LP) CNVs were detected in four cases (36.36%, 4/11), whereas G-banding karyotyping and WES showed negative results. In non-isolated PFMs, a sequential genetic approach showed a detection rate of 47.5% (19/40); karyotyping revealed aneuploidies in five cases (16.67%, 5/30), CNV testing showed P/LP CNVs in five cases (16.13%, 5/31), and WES identified P/LP variants (in genes CEP20, TMEM67, OFD1, PTPN11, ARID1A, and SMARCA4) in nine cases (40.91%, 9/22). WES showed a detection rate of 83.33% (5/6) in fetuses with Joubert syndrome. Only six patients (five with Blake’s pouch cyst and one with unilateral cerebellar hemisphere dysplasia) survived.ConclusionsWe recommend CNV testing for fetuses with isolated PFMs. A sequential genetic approach (karyotyping, CNV testing, and WES) may be beneficial in fetuses with non-isolated PFMs. Particularly, we recommend WES as the first-line genetic diagnostic tool for Joubert syndrome.

The FRB-searching Pipeline of the Tianlai Cylinder Pathfinder Array

This paper presents the design, calibration, and survey strategy of the Fast Radio Burst (FRB) digital backend and its real-time data processing pipeline employed in the Tianlai Cylinder Pathfinder Array. The array, consisting of three parallel cylindrical reflectors and equipped with 96 dual-polarization feeds, is a radio interferometer array designed for conducting drift scans of the northern celestial semi-sphere. The FRB digital backend enables the formation of 96 digital beams, effectively covering an area of approximately 40 square degrees with the 3 dB beam. Our pipeline demonstrates the capability to conduct an automatic search of FRBs, detecting at quasi-real-time and classifying FRB candidates automatically. The current FRB searching pipeline has an overall recall rate of 88%. During the commissioning phase, we successfully detected signals emitted by four well-known pulsars: PSR B0329+54, B2021+51, B0823+26, and B2020+28. We report the first discovery of an FRB by our array, designated as FRB 20220414A. We also investigate the optimal arrangement for the digitally formed beams to achieve maximum detection rate by numerical simulation.

Network Intrusion Detection Based on Deep Belief Network Broad Equalization Learning System

Network intrusion detection systems are an important defense technology to guarantee information security and protect a network from attacks. In recent years, the broad learning system has attracted much attention and has been introduced into intrusion detection systems with some success. However, since the traditional broad learning system is a simple linear structure, when dealing with imbalanced datasets, it often ignores the feature learning of minority class samples, leading to a poorer recognition rate of minority class samples. Secondly, the high dimensionality and redundant features in intrusion detection datasets also seriously affect the training time and detection performance of the traditional broad learning system. To address the above problems, we propose a deep belief network broad equalization learning system. The model fully learns the large-scale high-dimensional dataset via a deep belief network and represents it as an optimal low-dimensional dataset, and then introduces the equalization loss v2 reweighing idea into the broad learning system and learns to classify the low-dimensional dataset via a broad equalization learning system. The model was experimentally tested using the CICIDS2017 dataset and fully validated using the CICIDS2018 dataset. Compared with other algorithms in the same field, the model shortens the training time and has a high detection rate and a low false alarm rate.

Relationship between Volpara Density Grade and Compressed Breast Thickness in Japanese Patients with Breast Cancer

Background: High breast density found using mammographs (MGs) reduces positivity rates and is considered a risk factor for breast cancer. Research on the relationship between Volpara density grade (VDG) and compressed breast thickness (CBT) in the Japanese population is still lacking. Moreover, little attention has been paid to pseudo-dense breasts with CBT < 30 mm among high-density breasts. We investigated VDG, CBT, and apparent high breast density in patients with breast cancer. Methods: Women who underwent MG and breast cancer surgery at our institution were included. VDG and CBT were measured. VDG was divided into a non-dense group (NDG) and a dense group (DG). Results: This study included 419 patients. VDG was negatively correlated with CBT. The DG included younger patients with lower body mass index (BMI) and thinner CBT. In the DG, patients with CBT < 30 mm had lower BMI and higher VDG; however, no significant difference was noted in the positivity rate of the two groups. Conclusions: Younger women tend to have higher breast density, resulting in thinner CBT, which may pose challenges in detecting breast cancer on MGs. However, there was no significant difference in the breast cancer detection rate between CBT < 30 mm and CBT ≥ 30 mm.

Epidemiological study of post-pandemic pediatric common respiratory pathogens using multiplex detection

BackgroundThe burden and characteristics of respiratory viral infections in children hospitalized for acute respiratory tract infections (ARTIs) during the post-COVID-19 pandemic era are unclear. We analyzed the epidemiological and clinical characteristics of pediatric patients hospitalized with common respiratory virus infections before and after relaxation of non-pharmaceutical interventions in Hangzhou, China and evaluated the diagnostic value of the six-panel respiratory pathogen detection system.MethodsSix types of respiratory viruses were detected in respiratory samples from children with suspected ARTIs by multiplex real-time quantitative polymerase chain reaction (RT-qPCR). Changes in virus detection rates and epidemiological and clinical characteristics, obtained from electronic health records, were analyzed. Binary logistic regression was used to identify respiratory tract infections risk factors. Multiplex RT-qPCR and targeted next-generation sequencing results were compared in random samples.ResultsAmong the 11,056 pediatric samples, 3228 tested positive for one or more of six common respiratory pathogens. RSV and PIV-3 detection rates differed significantly across age groups (both P < 0.001), and were more common in younger children. PIV-1 was more common in infants, toddlers, and preschoolers than in school-age children (P < 0.001). FluB was predominantly detected in school-age children (P < 0.001). RSV-, ADV-, and PIV-1-positivity rates were higher in 2022 than in 2023. Seasonal viral patterns differed across years. RSV (OR 9.156. 95% CI 5.905–14.195) and PIV-3 (OR 1.683, 95% CI 1.133–2.501) were risk factors for lower respiratory tract infections. RSV-positivity was associated with severe pneumonia (P = 0.044). PIV-3 (OR 0.391, 95% CI 0.170–0.899), summer season (OR 1.982, 95% CI 1.117–3.519), and younger age (OR 0.938, 95% CI 0.893–0.986) influenced pneumonia severity. Multiplex RT-qPCR showed good diagnostic performance.ConclusionAfter changes in COVID-19 prevention and control strategies, six common respiratory viruses in children were prevalent in 2022–2023, with different seasonal epidemic characteristics and age proclivities. RSV and PIV-3 cause lower, and FluA, FluB, and ADV more typically cause upper respiratory tract infections. Infancy and summer season influence severe pneumonia risk. Multiplex RT-qPCR is valuable for accurate and timely detection of respiratory viruses in children, which facilitates management, treatment, and prevention of ARTIs.

TEMDI: A Temporal Enhanced Multisource Data Integration model for accurate PM2.5 concentration forecasting

Accurate forecasting of PM2.5 concentration is crucial for implementing effective protective measures and mitigating the adverse health impacts of air pollution. To address the complex spatial propagation dynamics and temporal variations of PM2.5, we developed the Temporal Enhanced Multisource Data Integration (TEMDI) model. This innovative approach combines spatial modeling by a Graph Neural Network (GNN) to capture the intricate spatial propagation patterns based on multi-source data fusion, and a novel Time Series Enhancement (TSE) module that includes Ensemble Empirical Mode Decomposition (EEMD), Gated Recurrent Units (GRUs), and a self-attention mechanism to adequately manage the time series’ short-term and long-term trends. Our results demonstrate TEMDI’s superior performance, achieving exceptionally high Probability of Detection (POD) rates of 96.15%, 80.28%, and 71.86% for forecast horizons of 3, 36, and 72 h, respectively. Furthermore, our feature importance analysis reveals that multi-scale features extracted by the EEMD component become increasingly crucial as the prediction horizon extends. The TEMDI model’s ability to provide accurate, reliable PM2.5 forecasts and its enhanced interpretability position it as a valuable tool for guiding environmental policy and management decisions to safeguard public health.

Cognitive Targeted Prostate Biopsy Alone for Diagnosing Clinically Significant Prostate Cancer in Selected Biopsy-Naïve Patients: Results from a Retrospective Pilot Study

(1) Background: To identify a particular setting of biopsy-naïve patients in which it would be reasonable to offer only cognitive targeted prostate biopsy (PBx) with a transrectal approach. (2) Methods: We designed an observational retrospective pilot study. Patients with a prostatic specific antigen (PSA) level &gt; 10 ng/mL, either a normal or suspicious digital rectal examination (DRE), and a lesion with a PI-RADS score ≥ 4 in the postero-medial or postero-lateral peripheral zone were included. All patients underwent a transrectal PBx, including both systematic and targeted samples. The detection rate of clinically significant prostate cancer (csPCa) (Gleason Score ≥ 7) was chosen as the primary outcome. We described the detection rate of csPCa in systematic PBx, targeted PBx, and overall PBx. (3) A total of 92 patients were included. Prostate cancer was detected in 84 patients (91.30%) with combined biopsies. A csPCa was diagnosed in all positive cases (100%) with combined biopsies. Systematic PBxs were positive in 80 patients (86.96%), while targeted PBxs were positive in 84 men (91.30%). Targeted PBx alone would have allowed the diagnosis of csPCa in all positive cases; systematic PBx alone would have missed the diagnosis of 8/84 (9.52%) csPCa cases (4 negative patients and 4 not csPCa) (p = 0.011). (4) Conclusions: Cognitive targeted PBx with a transrectal approach could be offered alone to diagnose csPCa in biopsy-naïve patients with PSA ≥ 10 ng/mL, either normal or suspicious DRE, and a lesion with PI-RADS score ≥ 4 in the postero-medial or postero-lateral peripheral zone.

Developing intelligent cyber threat detection systems through quantum computing

In the face of increasingly sophisticated cyber threats, traditional detection systems often fall short in protecting critical supply chains. This research presents the development and evaluation of an intelligent cyber threat detection system integrating Quantum Computing (QC) and Artificial Intelligence (AI). The proposed system significantly enhances detection accuracy, reduces latency, and improves resource efficiency compared to traditional methods. Quantum algorithms, such as Quantum Support Vector Machines (QSVM) and Quantum Neural Networks (QNN), demonstrated superior performance with accuracies of 95.2% and 96.7%, respectively. The system achieved high detection rates for various cyber threats, including malware, phishing, ransomware, and advanced persistent threats (APTs), with reduced false positive rates. The integration of QC also resulted in faster threat detection and response times, with system latency halved across key components. These advancements provide substantial benefits for cyber threat response in supply chains, ensuring robust protection of financial transactions and critical infrastructure. The enhanced scalability and efficiency make the system a valuable asset for safeguarding the United States' financial sector against sophisticated cyber-attacks.

A novel dual-target Septin9 methylation assay for improved detection of early-stage colorectal cancer and high-grade intraepithelial neoplasia

BackgroundColorectal cancer (CRC) ranks as the third most common malignancies in the world, and periodic examination of the patient is advantageous in reducing the mortality of CRC. The first blood-based Septin9 gene methylation assay which recognized by the US FDA for CRC examination was Epi proColon. However, this assay was not broadly applied in the current clinical guideline because of its relatively lower sensitivity in the detection of early-stage CRC.MethodsThis study aimed at developing a new multiplex Septin9 methylation assay (ColonUSK) which simultaneously evaluates two CpG-rich subregions in the promoter of the Septin9 gene and an internal control in a single reaction. ColonUSK proved increased sensitivity, with a detection limit as low as 12pg of the positive DNA compared with the Septin9 assay targeting one CpG-rich subregion. 1366 subjects were prospectively recruited from four comprehensive hospitals in China in an opportunistic screening study for assessing its value in CRC detection. Blind testing was developed to evaluate ColonUSK in comparison with clinical examination using clinical gold standard such as colonoscopy.ResultsThe assay demonstrates clinical sensitivity for diagnosing colorectal cancer (CRC) and advanced adenoma at rates of 77.34% and 25.26%, respectively. Furthermore, ColonUSK exhibits a high degree of specificity for non-CRC cases (95.95%) clinically. Significantly, the detection rate of cases in high-grade intraepithelial neoplasia increased to 54.29%. The value for the assay in the Kappa test was 0.76, showing a high degree of consistency between ColonUSK and clinical gold standard.ConclusionsColonUSK indicated moderate diagnostic value and could become a non-invasive detection way for CRC. The implementation of the ColonUSK assay has the capacity to markedly enhance CRC screening practices.

Trends in antimicrobial resistance in Enterobacterales isolated from children: data from the China Antimicrobial Surveillance Network (CHINET) from 2015–2021

Antimicrobial resistance poses a significant threat to global public health, especially for Enterobacterales. In this study, we investigated the distribution and antimicrobial resistance of Enterobacterales in children in the China Antimicrobial Surveillance Network (CHINET) in 2015–2021. In total, 81,681 strains isolated from children were collected in this period, accounting for 50.1% of Gram-negative organisms. The most frequently isolated Enterobacterales were Escherichia coli, Klebsiella spp., Salmonella spp., and Enterobacter spp. The main sources of the isolates were urine and the respiratory tract, accounting for 29.3% and 27.7% of isolates, respectively. The proportions of E. coli, Klebsiella pneumoniae, and Proteus mirabilis expressing extended-spectrum β-lactamase were 48.8%–57.6%, 49.3%–66.7%, and 23.1%–33.8%, respectively. The prevalence of carbapenem-resistant Enterobacterales was 5.7%–9.5%, which showed a decreasing trend from 2015 to 2021. The detection rates of carbapenem-resistant Klebsiella spp., carbapenem-resistant Enterobacter spp., and carbapenem-resistant E. coli were 14.1%–22.6%, 7.1%–15.7% and 2.0%–3.4%, respectively. In Enterobacterales, the resistance rates to ciprofloxacin were higher than to levofloxacin. However, the Enterobacterales strains were highly susceptible to amikacin, polymyxin B, and tigecycline. The resistance rate of Salmonella spp. to ampicillin was > 70%, whereas their resistance rate to ceftriaxone was < 30%. These findings indicate that the resistant rates of some Enterobacterales isolates in children to common antimicrobial agents show decreasing trends. Continuous monitoring of bacterial resistance should be strengthened to prevent and control the spread of drug-resistant bacteria.

Correlation of PSA blood levels with standard uptake value maximum (SUVmax) and total metabolic tumor volume (TMTV) in 18F-PSMA-1007 and 18F-choline PET/CT in patients with biochemically recurrent prostate cancer.

In this prospective study, we investigated the correlation between prostate-specific antigen (PSA) levels in the blood of patients with prostate cancer in biochemical recurrence after radical treatment with the semiquantitative parameters standard uptake value maximum (SUVmax) and the total metabolic tumor volume (TMTV) in the metastatic foci depicted in 18F-prostate-specific membrane antigen (PSMA)-1007 and 18F-choline PET/computed tomography (CT) imaging. We prospectively examined 104 patients with biochemical relapse of prostate cancer after primary definitive treatment. All patients underwent one 18F-PSMA-1007 and one 18F-choline PET/CT examination in randomized order within a time frame of 10 days and were followed for at least 6 months (182 ± 10 days). The semiquantitative parameters of SUVmax and metabolic tumor volume (MTV) of each neoplastic lesion in PET/CT imaging were calculated, and further summation of each MTV value was done to calculate the TMTV. According to the Spearman correlation analysis, a positive correlation was found between PSA levels and SUVmax and TMTV scores in the metastatic foci of 18F-PSMA-1007 PET/CT (r = 0.24 and 0.35, respectively; P < 0.05) and SUVmax in the lesions of 18F-choline PET/CT (r = 0.28; P < 0.0239). However, a positive but NS correlation was demonstrated between values of PSA and TMTV for each lesion in the 18F-choline PET/CT study (r = 0.22; P = 0.0795). The detection rate of the different PSA levels with a cutoff of 1 ng/ml was higher for 18F-PSMA-1007 than 18F-choline. In biochemical relapse patients there is a positive correlation between PSA levels in the blood and the semiquantitative parameters SUVmax and TMTV of the metastatic foci in the 18F-PSMA-1007 and 18F-Choline PET/CT imaging.

Umbilical Vein Flows and Cardiac Size, Shape, and Ventricular Contractility in Fetuses With Estimated Weight Less-Than 10th Centile.

In a cohort of patients with estimated fetal weights (EFWs) <10th centile, we aimed 1) to compare the prevalence of abnormalities of fetal 4-chamber view (4CV) cardiac size, shape, and ventricular contractility in fetal growth restricted (FGR) and small-for-gestational-age (SGA) fetuses and 2) to compare umbilical vein flow (UVF) measurements to standard Doppler surveillance in predicting abnormalities of cardiac function. Prospective observational cohort study of fetuses with EFW <10th percentile. Measurements of size and shape used were 4CV transverse width, 4CV cardiac area, 4CV global sphericity index, and right-to-left ventricular mid-chamber width ratio. Variables of contractility used were fractional shortening change at the mid-ventricle chamber, global longitudinal strain, fractional area change, and left ventricular cardiac output. The UVF and standard Doppler surveillance including umbilical artery (UA), middle cerebral artery, and cerebroplacental ratio (CPR) were collected. Control data were from previously published studies. A total of 95 fetuses with EFWs <10th centile were included in the study. The rates of abnormalities of cardiac size and shape and ventricular contractility were all significantly elevated compared with normally grown control fetuses but similar between FGR and SGA fetuses. In a subset of 76 patients with UVF data, evaluation UVF identified more patients with any abnormality of contractility compared with UA (37.9 vs 17.2%, P = .02). The addition of UVF doubled the detection rate of ventricular contractility abnormalities. The addition of UVF should be considered in the surveillance of FGR and SGA fetuses to further stratify the severity of hypoxemia and to identify those at greater risk for future cardiovascular dysfunction.