Detection Rate Research Articles

Integrating AI in testing automation: Enhancing test coverage and predictive analysis for improved software quality

This research explores the integration of Artificial Intelligence (AI) in testing automation, focusing on its ability to enhance test coverage and enable predictive analysis for improved software quality. As software systems become increasingly complex, traditional testing methods often struggle to meet quality demands. This study evaluates various AI techniques, including machine learning and natural language processing, and their applications in generating test cases, optimizing testing processes, and predicting defects. Through empirical case studies from diverse organizations, we demonstrate significant improvements in test coverage and defect detection rates following AI implementation. The findings highlight the efficiency gains and quality enhancements achieved through AI-driven testing, while also addressing challenges such as data dependency, complexity of implementation, and the need for skilled personnel. This research contributes to the understanding of AI's role in software testing and encourages organizations to adopt these technologies for better quality assurance and faster development cycles.

Blockchain-Enhanced Machine Learning for Robust Detection of APT Injection Attacks in the Cyber-Physical Systems

Cyber-Physical Systems (CPS) have become a research hotspot due to their vulnerability to stealthy network attacks like ZDA and PDA, which can lead to unsafe states and system damage. Recent defense mechanisms for ZDA and PDA often rely on model-based observation techniques prone to false alarms. In this paper, we present an innovative approach to securing CPS against Advanced Persistent Threat (APT) injection attacks by integrating machine learning with blockchain technology. Our system leverages a robust ML model trained to detect APT injection attacks with high accuracy, achieving a detection rate of 99.89%. To address the limitations of current defense mechanisms and enhance the security and integrity of the detection process, we utilize blockchain technology to store and verify the predictions made by the ML model. We implemented a smart contract on the Ethereum blockchain using Solidity, which logs the input features and corresponding predictions. This immutable ledger ensures the integrity and traceability of the detection process, mitigating risks of data tampering and reducing false alarms, thereby enhancing trust in the system's outputs. The implementation includes a user-friendly interface for inputting features, a backend for data processing and model prediction, and a blockchain interaction module to store and verify predictions. The integration of blockchain with Machine learning enhances both the precision and resilience of APT detection while providing an additional layer of security by ensuring the transparency and immutability of the recorded data. This dual approach represents a substantial advancement in protecting CPS from sophisticated cyber threats.

Phenotypes and clinical laboratory data for polycystic ovary syndrome cases: A nationwide survey in Japan.

Describe the current phenotypes and clinical laboratory data regarding polycystic ovary syndrome (PCOS) in Japan, taking into account ethnic differences and obesity status. Data for 986 PCOS cases and 965 control cases were collected using a nationwide survey in Japan. Obese/overweight (body mass index [BMI] ≥25 kg/m2) and non-obese/overweight (BMI <25 kg/m2) cases were compared. Japanese PCOS cases predominantly involved non-obese/overweight patients, accounting for 75% of all cases. Among non-obese/overweight PCOS cases, the incidence of both amenorrhea and clinical/biochemical hyperandrogenism was significantly lower than in obese/overweight PCOS cases, whereas the rate of elevated serum luteinizing hormone (LH) level was significantly higher. Even though the incidence of hirsutism in Japan is only 13.5%, the detection rate for hyperandrogenism increased by as much as 30.4% when hirsutism was added to the Japan Society of Obstetrics and Gynecology (JSOG) criteria for the diagnosis of hyperandrogenism in addition to elevated serum total testosterone level. When evaluated based on timing of blood sampling, the LH level and LH/follicle-stimulating hormone ratio determined at the initial consultation involving a chief complaint of irregular menstrual cycle (after confirming the absence of follicles measuring ≥1 cm in diameter) were significantly higher than on days 2-3 or 4-6 of the menstrual cycle. Ethnic differences, including obesity status, affected the phenotype and clinical laboratory data of Japanese PCOS patients, such as the incidence rates of clinical/biochemical hyperandrogenism and the rate of elevated basal LH level. Adding hirsutism to the JSOG 2024 criteria would enhance the accuracy of PCOS diagnosis and enhance consistency with the Rotterdam 2003 criteria. Measuring basal LH level is useful for assessing the endocrinologic characteristics of Japanese PCOS cases, as well as lean Asian PCOS cases, but the timing of blood sampling can affect the result.

A Prospective Observational Study on Analyzing Lung Cancer Gene Mutation Variant Allele Frequency (VAF) and Its Correlation with Treatment Efficacy

A few studies have reported on the variability of the variant allele frequency (VAF) of gene mutations and the relationship between VAF and the therapeutic effect of molecular-targeted drugs. This joint study was conducted from May 2020 to January 2022 between St. Marianna University School of Medicine and the DNA Chip Research Institute. Cytology samples were used to verify the usefulness of a lung cancer compact panel test, which is a high-sensitivity next-generation sequencing (NGS) gene panel test. We analyzed the distribution of VAF and the duration of the initial molecular-targeted drug administration in patients with advanced-stage epidermal growth factor receptor (EGFR) mutations. Of the 196 patients diagnosed with non-small cell carcinoma (NSCLC), gene mutations were detected in 114 (58.2%) cases and in 68.7% of patients with adenocarcinomas (an increased detection rate). A VAF of 30% or more for DNA mutations was confirmed in 35 patients (33.7%), 10% to &lt;30% in 38 (36.5%), and &lt;10% in 31 (29.8%), including 18 patients (17.3%) with &lt;6%, which is considered the lower limit of the LOD for other companion diagnostic kits. EGFR mutations were detected in 59 patients (30%), of whom 35 were in an advanced stage and received molecular-targeted drugs as their initial treatment. Groups A and B comprised patients with a VAF of ≥10% and &lt;10%, respectively, with 27 patients (median VAF 30.6%, range 11.4–77%) in group A and 8 (median VAF 5.4%, range 0.1–8.5%) in group B. The duration of the administration of molecular-targeted drugs was 17 months (range 3–42 months) in group A and 14 months (range 1–45 months) in group B, with no statistically significant difference between the two groups (p-value = 0.7). Twenty-seven percent of patients had a VAF &lt; 10%. Even in patients with a low VAF for gene mutations, sufficient therapeutic effects were observed with molecular-targeted drugs, suggesting the importance of detecting mutations using a highly sensitive method at initial diagnosis. Further prospective validation studies of a larger number of cases are warranted.

Does the FARNet neural network algorithm accurately identify Posteroanterior cephalometric landmarks?

BackgroundWe explored whether the feature aggregation and refinement network (FARNet) algorithm accurately identified posteroanterior (PA) cephalometric landmarks.MethodsWe identified 47 landmarks on 1,431 PA cephalograms of which 1,177 were used for training, 117 for validation, and 137 for testing. A FARNet-based artificial intelligence (AI) algorithm automatically detected the landmarks. Model effectiveness was calculated by deriving the mean radial error (MRE) and the successful detection rates (SDRs) within 2, 2.5, 3, and 4 mm. The Mann-Whitney U test was performed on the Euclidean differences between repeated manual identifications and AI trials. The direction in differences was analyzed, and whether differences moved in the same or opposite directions relative to ground truth on both the x and y-axis.ResultsThe AI system (web-based CranioCatch annotation software (Eskişehir, Turkey)) identified 47 anatomical landmarks in PA cephalograms. The right gonion SDRs were the highest, thus 96.4, 97.8, 100, and 100% within 2, 2.5, 3, and 4 mm, respectively. The right gonion MRE was 0.94 ± 0.53 mm. The right condylon SDRs were the lowest, thus 32.8, 45.3, 54.0, and 67.9% within the same thresholds. The right condylon MRE was 3.31 ± 2.25 mm. The AI model’s reliability and accuracy were similar to a human expert’s. AI was better at four skeleton points than the expert, whereas the expert was better at one skeletal and seven dental points (P < 0.05). Most of the points exhibited significant deviations along the y-axis. Compared to ground truth, most of the points in AI and the second trial showed opposite movement on the x-axis and the same on the y-axis.ConclusionsThe FARNet algorithm streamlined orthodontic diagnosis.

Influence of PCBM Nanocrystals on the Donor-Acceptor Polymer Ultraviolet Phototransistors.

Organic phototransistors, renowned for their exceptional biocompatibility, hold promise in phototherapy for tracking the efficacy of photosensitive drugs within treatment areas. Nevertheless, it has been found that organic semiconductors are less effective in detecting ultraviolet (UV) light because of their narrow bandgap. Here, we show that UV photodetection in phototransistors using donor-acceptor (D-A) polymer semiconductors can be significantly enhanced by incorporating PCBM nanocrystals. This integration results in a band mismatch between the nanocrystals and the D-A polymer at the interface. These nanocrystals also demonstrate a notable capability of modulating threshold voltage under UV light. The devices incorporating nanocrystals exhibit a photoresponsivity of 0.16 A/W, surpassing the photoresponsivity of the devices without nanocrystals by 50%. The specific detection rate of devices with nanocrystals is around 2.00 × 1010 Jones, which is twice as high as that of devices without nanocrystals. The presented findings offer a potential avenue to improve the efficiency of polymer phototransistors for UV detection.

Label-free detection and simultaneous viability determination of CTCs by lens-free imaging cytometry.

The detection of extremely rare circulating tumor cells (CTCs) in peripheral blood and simultaneously identifying their viabilities are significant for cancer diagnosis and prognosis as well as monitoring the efficacy of personalized treatment. A lens-free imaging system features high-resolution images taken over a large field of view (FOV), which has great potential for CTC detection and viability determination. But current still lens-free systems restrict the application for CTC detection in real samples due to the inherent limitations of lens-free technology: (1) the location of cells in the FOV will affect the imaging; (2) the extremely rare CTCs probably did not exist in one observation. In this paper, we realized the detection of CTCs in whole blood and the simultaneous determination of their viabilities by lens-free imaging cytometry. Our in-flow system plus a large FOV range of lens-free imaging highly increased the detection rate of rare CTCs with a high throughput of 150,000 cells per minute and improved the recognition efficiency for blood cells, living/dead CTCs by using a cell tracing-assisted deep learning algorithm. With this method, the average precision of blood cells, living/dead lung cancer cells A549, and living/dead colon cancer cells SW620 reached 98.80%, 97.88%, 97.93%, 97.72%, and 98.60%, respectively. Our system got a highly consistent result with the manual counting method using fluorescent staining (Pearson's r 99.93% for SW620) and can easily detect as few as 10 dead or living CTCs from 100,000 white blood cells (WBCs). Finally, real clinical samples were detected in our system. Both dead and living CTCs were found in all six advanced-stage cancer patients, and the number of living CTCs per million WBCs ranged from 13 to 39, more than that of the dead CTCs (5 to 25), while none of the CTCs were detected in six healthy control subjects. Moreover, we also found that CTCs died very quickly after leaving the human body, indicating that CTCs should be studied as soon as possible after sampling. Although this method is implemented for CTCs, it can also be used for the detection of other rare cells.

Warning values of serum total kappa/lambda ratio for M-proteinemia

BackgroundTo introduce the serum total kappa/lambda ratio (K/L) in humoral immunity testing reports to improve the detection rate of M-proteinemia.Methods156 M protein-positive and 5464 M protein-negative samples confirmed by serum immunofixation electrophoresis(sIFE) were accumulated from January 2021 to December 2023 in the First Affiliated Hospital of Soochow University and the contents of immunoglobulins (IgG, IgA, IgM, kappa and lambda) were tested by Beckman IMMAGE800. All the samples were divided into two groups by time: the modeling group and the validation group. The K/L values in the modeling group were analyzed by SPSS 27.0 to get the receiver operating characteristic curve (ROC). Furthermore, a more in-depth analysis was conducted to verify the reliability of the optimal cutoff values in the validation group. In addition, the levels of immunoglobulins of another group including 106 patients with definite diagnosis of monoclonal gammopathy ranging from January 2021 to June 2024 were traced back to improve the diagnostic efficiency.ResultsThe optimal cutoff values of K/L were 2.31 and 1.43 corresponding to K-type and L-type M-proteinemia respectively by ROC analysis. The sensitivity and specificity were validated as 76.14% and 77.42%. False positives were mainly found in samples with systemic sclerosis (36.84%), hypohepatia (28.71%) and sicca syndrome (27.27%). While false negatives were mainly found in IgA monoclonal gammopathy (38.39%) and IgM monoclonal gammopathy (28.57%). Combining with the detection rules of IgG, IgA and IgM, the sensitivities for the diagnosis of immunoglobulin light chain amyloidosis(AL) and monoclonal gammopathy of undetermined significance(MGUS) can be increased to 83.33% and 85%.ConclusionsK/L > 2.31 and K/L < 1.43 can be used as warning values for M-proteinemia. In addition, the content of the heavy chain in IgA- or IgM-type M-proteinemia may be considered to improve the detection rate.

Detection of Bovine Respiratory Syncytial Virus in Cattle: A Systematic Review and Meta-Analysis

Bovine respiratory syncytial virus (BRSV) is an economically important pathogen of cattle and contributes to the bovine respiratory disease complex (BRDC). Despite individual studies investigating BRSV prevalence, risk factors, and detection methodologies, a systematic review and meta-analysis have been lacking. The aim of the current study was to conduct a systematic review and meta-analysis to determine the prevalence and detection rate of BRSV and identify associated risk factors. Additionally, the study aimed to explore the variability in BRSV prevalence based on different detection methods and associated risk factors. Adhering to PRISMA guidelines, data from three databases—Web of Science, PubMed, and Scopus—were systematically retrieved, screened and extracted. Out of 2790 initial studies, 110 met the inclusion criteria. The study found that prevalence and detection rates varied based on the detection methods used (antibody, antigen, and nucleic acid), study populations, production systems, and geographic locations. Findings were reported as a pooled proportion. The pooled proportion, hereafter referred to as prevalence or detection rate, was determined by calculating the ratio of cattle that tested positive for BRSV to the total number of cattle tested. Key findings include a pooled prevalence of 0.62 for antibody-based methods, 0.05 for antigen-based methods, and 0.09 (adjusted to 0.03) for nucleic acid-based methods. Detection rates in BRDC cases also varied, with antibody methods showing a rate of 0.34, antigen methods 0.16, and nucleic acid methods 0.13. The certainty of evidence of the meta-analysis results, assessed using GRADE, was moderate for antibody detection methods and low for antigen and nucleic acid methods. The study identified significant risk factors and trends affecting BRSV prevalence, such as geographical location, herd size, age, and co-infections. The results of the current study showed the complexity of understanding BRSV prevalence in different settings. The variability in BRSV prevalence based on detection methods and associated risk factors, such as geographic location and herd size, highlights the need for tailored approaches to detect and manage BRSV accurately.

Balancing act: evaluating non-target risks of feral cat management in conservation reserves

Context Predation by feral cats continues to place substantial pressure on native Australian wildlife, contributing to significant population declines and localised extirpations of susceptible species. In Western Australia (WA), the registration of the poison bait Eradicat® provides a tool to help manage these introduced predators, but only in areas where the risk to non-target species is considered acceptable. The red-tailed phascogale (Phascogale calura), a small carnivorous marsupial now restricted to vegetation remnants in the highly fragmented agricultural zone of south-western WA (i.e. the Wheatbelt), is one species that may be vulnerable to lethal ingestion. Aim To investigate the impact of repeated Eradicat® baiting, to control feral cats, on the activity levels of the red-tailed phascogale, focusing on populations in two Wheatbelt conservation reserves. Methods We established a novel approach to monitoring red-tailed phascogales by using tree-mounted camera trap arrays in an area with feral cat management using ground-delivered Eradicat® baits, and two control zones with no feral cat management. We examined changes in activity levels (detection rate and occupancy) based on camera trap detections, before and after Eradicat® application, across two autumn and two spring baiting events. We also investigated non-target bait uptake using camera traps. Key results Although a small number of baits (7/60) was removed by red-tailed phascogales from the field of view of a camera, our results showed no overall impact of Eradicat® on their activity levels within the study area. Tree-mounted camera traps proved to be highly effective and efficient at detecting red-tailed phascogales. To maximise camera detections, the optimal time for monitoring red-tailed phascogales is during autumn, prior to male die-off. Conclusions Our results suggested that the risk posed to red-tailed phascogale populations from the repeated use of Eradicat® baits is likely to be low. Implications Integrating the application of Eradicat® to control feral cats with existing fox control in conservation reserves that support populations of red-tailed phascogales is likely to pose minimal risk to the species.

Health Catch-UP!: a realist evaluation of an innovative multi-disease screening and vaccination tool in UK primary care for at-risk migrant patients

BackgroundMigrants to the UK face disproportionate risk of infections, non-communicable diseases, and under-immunisation compounded by healthcare access barriers. Current UK migrant screening strategies are unstandardised with poor implementation and low uptake. Health Catch-UP! is a collaboratively produced digital clinical decision support system that applies current guidelines (UKHSA and NICE) to provide primary care professionals with individualised multi-disease screening (7 infectious diseases/blood-borne viruses, 3 chronic parasitic infections, 3 non-communicable disease or risk factors) and catch-up vaccination prompts for migrant patients.MethodsWe carried out a mixed-methods process evaluation of Health Catch-UP! in two urban primary healthcare practices to integrate Health Catch-UP! into the electronic health record system of primary care, using the Medical Research Council framework for complex intervention evaluation. We collected quantitative data (demographics, patients screened, disease detection and catch-up vaccination rates) and qualitative participant interviews to explore acceptability and feasibility.ResultsNinety-nine migrants were assessed by Health Catch-UP! across two sites (S1, S2). 96.0% (n = 97) had complete demographics coding with Asia 31.3% (n = 31) and Africa 25.2% (n = 25), the most common continents of birth (S1 n = 92 [48.9% female (n = 44); mean age 60.6 years (SD 14.26)]; and S2 n = 7 [85.7% male (n = 6); mean age 39.4 years (SD16.97)]. 61.6% (n = 61) of participants were eligible for screening for at least one condition and uptake of screening was high 86.9% (n = 53). Twelve new conditions were identified (12.1% of study population) including hepatitis C (n = 1), hypercholesteraemia (n = 6), pre-diabetes (n = 4), and diabetes (n = 1). Health Catch-UP! identified that 100% (n = 99) of patients had no immunisations recorded; however, subsequent catch-up vaccination uptake was poor (2.0%, n = 1). Qualitative data supported acceptability and feasibility of Health Catch-UP! from staff and patient perspectives, and recommended Health Catch-UP! integration into routine care (e.g. NHS health checks) with an implementation package including staff and patient support materials, standardised care pathways (screening and catch-up vaccination, laboratory, and management), and financial incentivisation.ConclusionsClinical Decision Support Systems like Health Catch-UP! can improve disease detection and implementation of screening guidance for migrant patients but require robust testing, resourcing, and an effective implementation package to support both patients and staff.

Evaluation of the diagnostic techniques in the detection of hookworm infestation among school children in Ethiopia: Cross-sectional study design

BackgroundHookworm infestation is an important public health concern especially in regions with poor sanitation and limited resources. In healthcare institutions in Ethiopia, wet mount microscopy with low performance has been used as the sole diagnostic technique. Sensitive diagnostic methods are essential for the proper identification of hookworm infection in national strategies for hookworm prevention and management. Thus, the objective of the article was to evaluate the performance of diagnostic techniques in the detection of hookworm infestation among school children in the Gozamin district, Northwest Ethiopia. MethodsA cross-sectional study with 530 school children was conducted from February to April 2022 in Ethiopia. The study participants were selected by using systematic random sampling technique. Direct wet mount (DWM), Richie’s, Kato-Katz (KK), and spontaneous tube sedimentation (STS) diagnostic techniques were utilized to process the stool samples. The data were entered into the Epi-data version 4.2 and the data was analyzed using SPSS version 25.0. The sensitivity, specificity, predictive values and test efficiency of the test were calculated with respect to the Composite Reference Standard (CRS) as the reference method. The degree of agreement with the methods of diagnosis was assessed by the Kappa value. ResultsThe overall prevalence of hookworm was 34.9 %. The detection rate of STS, Richie’s, KK and DWM techniques in hookworm detection was 30.2 %, 27.0 %, 22.3 % and 15.1 %, respectively. The sensitivity and test efficiency of STS to detect hookworm were 86.5 % and 95.3 %, for Richie’s 77.3 % and 92.1 %, for KK 63.8 % and 87.4 %, for DWM method 43.2 % and 80.2 %, respectively. The agreement of STS, Richie’s, KK and DWM techniques with CRS were perfect (κ = 0.893), perfect (κ = 0.816), substantial (κ = 0.696) and moderate (κ = 0.498), respectively in detecting hookworm parasites. ConclusionThe prevalence of hookworm among school children was high. The STS method is superior to other methods for detecting hookworm infections. The Richie’s technique was more successful in detecting the hookworm parasite than the KK and DWM techniques. It is important to implement the STS technique in routine diagnostic methods and in endemic areas of hookworm infection because it cheaper, easy to perform, and identifies a wide range of parasitic species.

Porcine Nose Atrophy Assessed by Automatic Imaging and Detection of Bordetella bronchiseptica and Other Respiratory Pathogens in Lung and Nose

The nasal mucosa is a crucial filtering organ to prevent attachment and invasion of pathogens. To assess nasal health in relation to lung health, transverse cross sections of the nasal turbinates of 121 pigs suffering from respiratory disease and sent for diagnostic necropsy were scored visually and by an artificial intelligence (AI) medical diagnostic application (AI DIAGNOS), resulting in a high correlation of both scores (p &lt; 0.001). Nasal samples of the diseased pigs were examined only for Bordetella (B.) bronchiseptica (PCR and bacteriological culture) and Pasteurella (P.) multocida (bacteriological culture). All pigs showed various degrees of inflammatory lung tissue alterations, and 35.5% of the pigs had atrophy of the nasal turbinates with no relation to detection rates of B. bronchiseptica (54.5%) and P. multocida (29.0%) in the nose. All P. multocida strains from nose samples were negative for the toxA gene so non-progressive atrophic rhinitis was diagnosed. Pigs positive for B. bronchiseptica in the nose were more often positive for B. bronchiseptica in the lung (p &lt; 0.001) and for other bacterial species in the lower respiratory tract (p = 0.005). The new diagnostic application for scoring cross sections of nasal turbinates is a valuable tool for a fast and reproducible diagnostic.

The discrepancy of somatic BRCA1/2 pathogenic variants from two different platforms in epithelial ovarian, fallopian tube, and peritoneal cancer

The somatic BRCA1 or BRCA2 Pathogenic Variant (PV)/Likely PV (LPV) from Next Generation Sequencing (NGS) is the most important biomarker for PARP inhibitor use and maintenance-targeted therapies. A discrepancy in the detection rates of BRCA1 and BRCA2 PV/LPV was identified among the NGS platforms. The objective of this study was to compare the somatic BRCA results from two distinct platforms using the same cohort and to identify the causes of these differences. Patients with epithelial ovarian cancer who concurrently underwent tumor NGS using two different platforms between January 2022 and June 2023 were included in this study. The two platforms used were in-house tumor NGS (Illumina NextSeq 550Dx, SureSelectXT library kit, and datasets from 1000 Genomes, ESP6500, ExAC, and ClinVar) and GreenPlan homologous recombination deficiency (HRD) test (Illumina NextSeq 550Dx, customized Twist Bioscience library kit, and datasets from COSMIC and OncoKB). The results of somatic mutations in BRCA1 and BRCA2 were compared between the two platforms. Of the 118 patients, 11.9% (n = 14) exhibited a discordant interpretation of BRCA1 or BRCA2 between the two platforms. Eleven patients (9.3%) exhibited negative results in the in-house platform but positive results (eight seven as PV of BRCA1, one as PV of BRCA2, one as LPV of BRCA1, and two as LPV of BRCA2) in the GreenPlan HRD test, while three patients (2.6%) had positive BRCA pathogenic variants (two as PV of BRCA1 [c.3340G > T, c.5152 + 3 A > C], one as LPV of BRCA2 [c.8174G > T], and one as LPV of BRCA1 [c.5017_5019delCAC]) in the in-house platform but a negative result in the GreenPlan HRD test. The discordance rate of somatic BRCA1 or BRCA2 mutations from different platforms was approximately 12%. In the case of the strong implication of BRCA PV/LPV with a negative result with one genetic test, different platforms could be considered in limited cases. Careful interpretation and further studies for the cross-validation of gene analysis platforms are needed.

Comparative analysis of aldosterone and renin assays for primary aldosteronism screening

The transition from radioimmunoassay (RIA) to chemiluminescent enzyme immunoassay (CLEIA) for plasma aldosterone concentration (PAC) assays has raised concerns over its impact on primary aldosteronism (PA) diagnosis. This study investigated the correlation between PAC and renin values using RIA, CLEIA, and liquid chromatography/mass spectrometry/mass spectrometry (LC–MS/MS), established cutoff values for PA diagnosis using the aldosterone-to-renin ratio (ARR) with PAC_CLEIA, and assessed the differences in PAC values by measuring weak mineralocorticoids (WMs). This retrospective study evaluated 312 serum PAC samples using RIA, CLEIA, and LC–MS/MS, and analyzed 315 plasma renin samples. Method correlations were assessed through Passing-Bablok regression. Receiver operating characteristic curves determined ARR cutoffs for PA diagnosis. WMs were quantified to evaluate their impact on ΔPAC (RIA-LC–MS/MS) through multiple regression analysis. PAC_CLEIA and PAC_LC-MS/MS values were highly correlated. ARRs derived from PAC_RIAs demonstrated more false positives and lower specificity than ARRs using PAC_CLEIA or PAC_LC-MS/MS. WMs significantly influenced ΔPAC in both the PA and non-PA groups. ARRs using PAC_CLEIA are valuable for determining PA cutoffs in clinical practice. The transition to PAC using CLEIA may enhance PA detection rates. WMs were found to interfere with PAC measurements in the RIA method, affecting outcomes.

Gastric neoplasm detection of computer-aided detection-assisted esophagogastroduodenoscopy changes with implement scenarios: a real-world study.

The implementation of computer-aided detection (CAD) devices in esophagogastroduodenoscopy (EGD) could autonomously identify gastric precancerous lesions and neoplasms and reduce the miss rate of gastric neoplasms in prospective trials. However, there is still insufficient evidence of their use in real-life clinical practice. A real-world, two-center study was conducted at Wenzhou Central Hospital (WCH) and Renmin Hospital of Wuhan University (RHWU). High biopsy rate and low biopsy rate strategies were adopted, and CAD devices were applied in 2019 and 2021 at WCH and RHWU, respectively. We compared differences in gastric precancerous and neoplasm detection of EGD before and after the use of CAD devices in the first half of the year. A total of 33 885 patients were included and 32 886 patients were ultimately analyzed. In WCH of which biopsy rate >95%, with the implementation of CAD, more the number of early gastric cancer divided by all gastric neoplasm (EGC/GN) (0.35% vs 0.59%, P=0.028, OR [95% CI]=1.65 [1.0-2.60]) was found, while gastric neoplasm detection rate (1.39% vs 1.36%, P=0.897, OR [95% CI]=0.98 [0.76-1.26]) remained stable. In RHWU of which biopsy rate <20%, the gastric neoplasm detection rate (1.78% vs 3.23%, P<0.001, OR [95% CI]=1.84 [1.33-2.54]) nearly doubled after the implementation of CAD, while there was no significant change in the EGC/GN. The application of CAD devices devoted to distinct increases in gastric neoplasm detection according to different biopsy strategies, which implied that CAD devices demonstrated assistance on gastric neoplasm detection while varied effectiveness according to different implementation scenarios.

DCS-YOLO: Defect detection model for new energy vehicle battery current collector.

The future trend in global automobile development is electrification, and the current collector is an essential component of the battery in new energy vehicles. Aiming at the misjudgment and omission caused by the confusing distribution, a wide range of sizes and types, and ambiguity of target defects in current collectors, an improved target detection model DCS-YOLO (DC-SoftCBAM YOLO) based on YOLOv5 is proposed. Firstly, the detection rate of defects with different scales is improved by adding detection layers; Secondly, we use the designed DC module as the backbone network to help the model capture the global information and semantic dependencies of the target, and effectively improve the generalization ability and detection performance of the model. Finally, in the neck part, we integrate our designed Convolutional Block Attention Module (SoftPool Convolutional Block Attention Module, SoftCBAM), which can adaptively learn the importance of channels, enhance feature representation, and enable the model to better deal with target details. Experimental results show that the mAP50 of the proposed DCS-YOLO model is 92.2%, which is 5.1% higher than the baseline model. The FPS reaches 147.1, and the detection accuracy of various defect categories is improved, especially Severely bad and No cover, and the detection recall rate reaches 100%. This method has high target detection model efficiency and meets the requirements of real-time detection of battery collector defects.

Calibration of Cosmic Watch Desktop Muon Detector: Evaluating the Effects of Atmospheric Pressure and Material Interaction on Detection Accuracy

This study focuses on the analysis of data obtained from Cosmic Watch (CW) muon detectors. The objective is to establish a standardised procedures for the enhancement of accuracy of muon detection in varying environments. By applying correlation analysis, the linear regression line is used to addresses the impact of atmospheric pressure on muon detection rates, which is clarified in the dissertation. A significant aspect of the research involves the rectification of systematic errors, which includes inconsistencies in pressure and temporal discrepancies across groups of Cosmic Watch (CW) detectors. Furthermore, the study investigates the influence of diverse materials on muon penetration, with the detectors being covered with lead, iron, and no material, respectively. The corrected data provide more reliable detection of double- and triple-coincident events and insights into the interactions between certain material and muons. Although there are limitations, the developed calibration model provides a robust framework for future experiments involving muon detection, with potential applications in studying the properties of cosmic-ray muons, and angular distribution.

Recombinant MS087-based indirect ELISA for the diagnosis of Mycoplasma synoviae

Accurate detection is a prerequisite for effective prevention and control of Mycoplasma synoviae infection. ELISA is the most popular method for the clinical detection of M. synoviae because of its convenience, low cost, and high detection rate. However, the cross-reactivity of commercially available ELISA kits with other avian pathogen-positive sera needs to be addressed. The aim of this study was to establish an ELISA method with high specificity for the detection of anti-M. synoviae antibodies in chicken serum to evaluate the M. synoviae infection status on poultry farms. The recombinant MS087 (rMS087) protein was expressed in Escherichia coli BL21 (DE3) and purified by Ni2+ affinity chromatography. An antibody against rMS087 was generated by immunizing BALB/c mice. Bioinformatic analysis revealed that MS087 was conserved among M. synoviae strains. Western blotting and indirect immunofluorescence results indicated that MS087 was not only localized in the cytoplasm and on the membrane but also secreted by the organism. For the established ELISA method based on rMS087, the optimal antigen concentration, blocking buffer, blocking duration, serum dilution, serum incubation duration, secondary antibody dilution, secondary antibody incubation duration and colorimetric reaction duration were 2 μg/mL, 1% BSA, 3 h, 1:500, 1.5 h, 1:20,000, 2 h and 5 min, respectively. Validation of the rMS087-based ELISA revealed a cut-off value of 0.5. The coefficients of variation of both the intra-batch and inter-batch methods were less than 9%. The assay was able to differentiate positive serum against M. synoviae from antisera against nine other avian pathogens and was able to recognize M. synoviae-positive sera at a dilution of 1:1,000. Compared with the commercial ELISA method, the rMS087-based ELISA has the potential to recognize more positive sera against M. synoviae. Collectively, the rMS087-based ELISA is a reproducible, specific, and sensitive serological method for detecting antibodies against M. synoviae in chicken serum and has robust potential for large-scale serological epidemiology of M. synoviae infection on poultry farms.

CTR-FAPI PET enables precision management of medullary thyroid carcinoma.

Medullary thyroid carcinoma (MTC) can only be cured through the excision of all metastatic lesions, but 29-60% patients failed to localize the disease in the current clinical practice. Previously, we developed a fibroblast activation protein inhibitor (FAPI)-based covalent targeted radioligand (CTR) for improved detection sensitivity and accuracy. In this first-in-class clinical trial, we head-to-head compared [68Ga]Ga-CTR-FAPI PET-CT and [18F]FDG PET-CT in 50 MTC patients. The primary endpoint was the patient-based detection rate, with [68Ga]Ga-CTR-FAPI exhibiting higher detection than [18F]FDG (98% vs. 66%, p=0.0002). This improved detection was attributed to increased tumor uptake (SUVmax 11.71±9.16 vs. 2.55±1.73, p<0.0001). Diagnostic accuracy, validated on lesions with gold-standard pathology, was greater for [68Ga]Ga-CTR-FAPI compared to [18F]FDG (96.7% vs. 43.3%, p<0.0001). Notably, 32% patients altered management following [68Ga]Ga-CTR-FAPI PET-CT, and 66.7% patients changed their surgical plan. Overall, [68Ga]Ga-CTR-FAPI PET-CT provided superior detection and diagnostic accuracy compared to [18F]FDG PET-CT, enabling precision management of MTC patients.