Screening Technologies Research Articles

LP-35 Use of high-content screening technology for toxicological testing

LP-35 Use of high-content screening technology for toxicological testing

A qualitative study to understand the barriers and enablers of access to diabetic screening services in Nigeria.

Nigeria in working to redefine its health care system's approach to diabetic retinopathy (DR) screening services needs to reduce obstacles and highlight the enablers to services provision. Due to the increased prevalence of diabetes, this has become increasingly necessary. A qualitative study examining the perceptions, practices, and experiences of Nigerian DR healthcare practitioners (HCPs) in relation to the facilitators and barriers of access to DR screening services. Mode of participant recruitment was on-line through e-mails by using snowballing method. In-depth interviews were used to acquire information from 6 DR HCPs (all ophthalmologists) at three eye centers in the three geo-political areas of Nigeria and at international center for eye health (ICEH) in London via on-line Microsoft teams. Thematic analysis was used for data analysis and all the steps applied to the data analysis process. Non-systematic screening, poverty, poor transport systems, insecurity, and poor motivation are key barriers to DR screening access in Nigeria while enablers include government participation through subsidized costs and remuneration of workers. Screening in communities, and using low-cost techniques are key to enable access. Other enablers include collaboration and integration between endocrinology and ocular units in terms of referrals, information sharing, use of intermediary carers, technology, man-power and health resource provision including low- cost services. A dearth of personnel, screening technologies, and resources, have an impact on the effectiveness of the DR screening services in Nigeria as well as social and individual factors, such as the cost of the services and national insecurity.

Policy brief Belgian EBCP mirror group ‘prevention’ and ‘early detection & screening’ in cancer

The availability and linkage of comprehensive data on cancer mortality, incidence, screening and vaccination (HPV/HB) are essential for monitoring the process and impact of all screening and vaccination programmes, and to generate evidence to improve prevention policies. Linkage of data registries will allow better exploitation of real-world data. Simplification of data sharing for epidemiological research is of utmost importance. Human, as well as technical/technological and legal/regulatory barriers need to be tackled in Belgium to aid actors involved in screening, to facilitate organised linkage of data. Rapid advances in technologies for early detection and screening for a broad range of cancer types provide significant opportunities. Such tests are not yet ready for adoption in screening programmes. Emerging evidence should be monitored to ensure that promising innovations can transition to implementation studies in a timely manner. More and sustained research is needed to generate the necessary scientific relevance for new screening techniques in relevant cancer types.

Role of molecular markers in identifying genetic disorders

Molecular markers are critical tools in identifying genetic disorders, allowing for precise diagnosis, risk assessment, and personalized treatment approaches. They are classified into various categories, including single nucleotide polymorphisms (SNPs), short tandem repeats (STRs), and restriction fragment length polymorphisms (RFLPs), each serving distinct roles in genetic diagnostics. SNPs are widely used in genome-wide association studies (GWAS) to identify genetic predispositions to complex diseases, while STRs are valuable in diagnosing disorders like Huntington's disease. RFLPs, though less commonly used today, remain important in specific diagnostic contexts. The application of molecular markers spans a wide range of genetic disorders, from monogenic conditions such as cystic fibrosis (CF) to complex diseases like hereditary breast and ovarian cancer syndrome and fragile X syndrome. These markers enable early detection and targeted interventions, improving patient outcomes. However, several challenges hinder their widespread adoption, including difficulties in interpreting genetic data, limited access to genetic screening, and ethical concerns related to privacy and genetic discrimination. Future directions in the use of molecular markers for genetic screening involve integrating advanced technologies like next-generation sequencing and combining molecular data with other omics approaches to provide a more comprehensive understanding of genetic disorders. Addressing the challenges of data interpretation, accessibility, and ethical issues will be crucial in expanding the utility of molecular markers in clinical practice. The advancements in molecular marker technology and their applications in detecting specific genetic disorders hold promise for improving diagnostic accuracy and personalized treatment strategies. However, ensuring that these technologies are accessible and ethically implemented will be key to their success in transforming healthcare. The ongoing evolution of molecular markers and genetic screening technologies suggests a future where early diagnosis and personalized medicine become standard care for genetic disorders.

Application of AI-assisted Breast Ultrasound Technology in Breast Cancer Screening

To explore the application effect of artificial intelligence-assisted breast screening ultrasound technology in breast cancer screening. Methods 170 suspected breast cancer patients who underwent breast ultrasound examination in our hospital from July 2022 to June 2024 were retrospectively analyzed, and the results of breast biopsy were taken as the gold standard by physician analysis, artificial intelligence analysis, and combined artificial intelligence analysis. To compare the application effect of ultrasonography in breast cancer screening in three ways. Results Among 170 suspected breast cancer patients, 132 were positive, 38 were negative, 113 were true positive, and 29 were true negative. Sensitivity was 85.61%, specificity was 76.32%, consistency was 83.53%, positive predictive value was 92.62%, and negative predictive value was 60.42%. There were 124 true positive cases and 33 true negative cases, the sensitivity was 93.94%, the specificity was 86.84%, the consistency was 92.35%, the positive predictive value was 96.12%, and the negative predictive value was 80.49%. The results showed that 131 cases were true positive, and 37 were true negative. The sensitivity was 99.24%, the specificity was 97.37%, the consistency was 98.82%, the positive predictive value was 99.24%, and the negative predictive value was 97.37%. Taking the results of breast puncture biopsy as the "gold standard," the diagnostic sensitivity, specificity, consistency, positive predictive value, and negative predictive value of physician-combined artificial intelligence analysis were significantly higher than those of physician-only analysis or artificial intelligence analysis. Conclusion The application of AI-assisted breast screening ultrasound technology to breast cancer screening in our hospital not only helps to realize the consistency and accuracy of early identification and diagnosis of breast cancer so that patients can get more accurate treatment but also helps to reduce the workload of radiologists.

The Effects of the Virtual Background on French as a Second Foreign Language Vocabulary Learning

The purpose of this research was to investigate how the use of green screen technology affects vocabulary acquisition in LOTE (languages other than English) learners, particularly Chinese students learning French as a second foreign language. Two groups (a control group and an experimental group) with a total of 58 students participated in the study. Data were collected through in-class and delayed vocabulary tests, learning questionnaire, and semi-structured interviews. The study results demonstrate significant benefits in terms of providing an authentic learning experience, improving understanding, increasing motivation, and facilitating interaction. The results also confirm the technology’s effectiveness in enhancing both immediate and long-term vocabulary retention. The effectiveness is particularly evident for location-related words, as the technology provides visual context that facilitates recall of these words, which may not have easily retrievable mental images compared to more concrete words with tangible references. Further research can also be undertaken to compare the impact of virtual background on vocabulary retention with other immersive technologies. Nevertheless, virtual backgrounds are likely to be a cost-effective and accessible tool that can already offer promising improvements in learning outcomes and can be easily implemented with existing software like Zoom (5.2.0 or higher) and Tencent Meeting (1.3.0 or higher).

Pledgeability and bank lending technology

What is the effect of an expansion of eligible collateral on different lending technologies? We show that expanding eligible collateral (i) increases transactional (T) banks’ interest income and decreases relationship (R) banks’ interest income, (ii) increases average loan volume more for T- than for R-banks, (iii) decreases average loan risk and (iv) decreases T-banks’ non-interest income while it increases R-banks’ non-interest income. (v) In sum, T-banks’ profitability increases and R-bank’s profitability remains unaffected. Expanding the set of collateral from immovable to movable assets typically benefits SMEs because it allows them to obtain secured loans instead of unsecured ones. A-priori, it is unclear whether SMEs will continue borrowing from R-banks or switch to T-banks. R-banks benefit from customer relationships and T-banks have the collateral screening technology in place. We show that competition between T- and R-banks gives T-banks a comparative advantage, but R-banks can substitute lost interest income with non-interest income.

The Performance of The Opening Ceremony of the 2022 Beijing Winter Olympics

This study adopts research methods such as literature review and interview to analyze the performance of the opening ceremony of the 2022 Beijing Winter Olympics. The study focuses on the Olympic concept, duration, national culture, AI use, optical application, stage design, fireworks performance, venue selection, and the relationship with technological development. give the result as follows1. Simplicity, beauty, modernity. Showcasing three themes, namely China's pursuit and longing for world peace, "Faster, Higher, Stronger, and more united", and "Together towards the future".2. The blessing of technology is more important than any previous Olympic opening ceremony performance. Human screen dance technology, holographic projection technology, AI technology empowerment, 3D lighting stage technology, double-sided screen technology, laser engraving technology, and irregular screen technology will be the main means of empowering the Olympic opening ceremony performance.3.The color scheme of the opening ceremony of the Beijing Winter Olympics is mainly cold, which blends harmoniously with the emphasis on ice and snow in the Winter Olympics.4.The development and utilization of ethnic elements in the opening ceremony performance of this Winter Olympics are reasonable and appropriate, mainly including Chinese paintings, Chinese totems, Chinese stories, Chinese proverbs, Chinese characters, Chinese clothing, etc.5.The selection of the performance venue for the opening ceremony at the National Stadium of China seems somewhat conservative.6.Reduced the fixed construction stage and replaced it with a variable and mobile stage. Technological stage. The use of LED screens makes the performance more diverse.7.The ignition ceremony highlights the ice and snow of the Winter Olympics, showcases the subtle fire in a low-key manner, highlights the theme, and also embodies the concept of low-carbon environmental protection8.The opening ceremony performance of this Winter Olympics focuses more on sports performances, downplaying artistic performances and highlighting sports characteristics. Performed by ordinary citizens, primary, secondary, and high school students, as well as young people from all over the world, emphasizing the need for everyone to come together.

Predicting Clinical Outcomes of SARS-CoV-2 Drug Efficacy with a High-Throughput Human Airway Microphysiological System.

The average cost to bring a new drug from its initial discovery to a patient's bedside is estimated to surpass $2 billion and requires over a decade of research and development. There is a need for new drug screening technologies that can parse drug candidates with increased likelihood of clinical utility early in development in order to increase the cost-effectiveness of this pipeline. For example, during the COVID-19 pandemic, resources were rapidly mobilized to identify effective therapeutic treatments but many lead antiviral compounds failed to demonstrate efficacy when progressed to human trials. To address the lack of predictive preclinical drug screening tools, PREDICT96-ALI, a high-throughput (n = 96) microphysiological system (MPS) that recapitulates primary human tracheobronchial tissue,is adapted for the evaluation of differential antiviral efficacy of native SARS-CoV-2 variants of concern. Here, PREDICT96-ALI resolves both the differential viral kinetics between variants and the efficacy of antiviral compounds over a range of drug doses. PREDICT96-ALI is able to distinguish clinically efficacious antiviral therapies like remdesivir and nirmatrelvir from promising lead compounds that do not show clinical efficacy. Importantly, results from this proof-of-concept study track with known clinical outcomes, demonstrate the feasibility of this technology as a prognostic drug discovery tool.

Inhibition of Macrophage Pyroptosis─A New Therapeutic Strategy to Alleviate T-2 Toxin-Induced Subacute Liver Injury by Directly Competing with the Key Target.

Multiple compounds are related to the development of liver injury, such as toxins, drugs, and environmental pollutants. Although there are reports that the T-2 toxin can cause liver injury, its toxic mechanism remains unclear, which further impedes the development of effective antidotes. In this study, CRISPR-Cas9 genome-wide screening technology was used to identify transformation-related protein 53 inducible nuclear protein 1 (trp53inp1) as a toxic target of the T-2 toxin. Mechanism studies have shown that the T-2 toxin induced pyroptosis of macrophages (J774A.1 cells) by activating the trp53inp1/NF-κB/NLRP3/GSDMD-N pathway, leading to a subacute liver injury. Also, the new drug berberine (BER) identified through virtual screening significantly alleviated the subacute liver injury by competitively binding trp53inp1 via His224; the effect was better than those of the positive control drugs N-acetylcysteine (NAC) and disulfiram (DSF). In summary, the above results indicate that trp53inp1 is a key target for T-2 toxin to induce subacute liver injury and that inhibiting macrophage pyroptosis is a new method for treating liver injury. In addition, this study provides a new method and strategy for the discovery of key disease targets and the search for effective drugs.

Prediction and analysis of dominant factors influencing moisture content during vacuum screening based on machine learning

The study of the dominant factors influencing moisture content is essential for investigating vacuum filtration mechanisms. In view of the present situation where there is insufficient experimental data and the dominant factors influencing the moisture content of a filter cake have not been identified, in this study a vacuum filtration apparatus was designed and constructed. Quartz sand particles were used as the filtration material. 300 datasets of moisture contents of a filter cake were obtained under different experimental conditions. Multiple Linear Regression, artificial neural network, decision tree, random forest, and extreme gradient boosting were used to establish a prediction model for moisture content during vacuum screening. By comprehensively analyzing the feature importance rankings and the effects of positive and negative correlations, the dominant factors influencing the moisture content of the filter cake during vacuum screening were the particle ratio, screen mesh, and airflow rate. This finding not only provides a scientific basis for the optimization of vacuum screening technology but also points the way for improving screening efficiency in practical applications. It is of significant importance for deepening the understanding of the vacuum screening mechanism and promoting its extensive application.

New Approach for Plasma Nitrocarburizing of Stainless Steels by a Modified Reactor Configuration Using a Plasma‐Activated Solid Carbon Precursor

Stainless steel surfaces can be modified using plasma‐assisted thermochemical treatments to improve properties like hardness, wear, and pitting corrosion resistance. To specifically adjust the desired properties, a precise control of the produced treatment‐relevant gas species with regard to their type and concentration is essential. This requires the adjustment of the parameters for the generation of the gas species, being independent from heating parameters, as well as their real‐time measurement. Therefore, this study presents the use of a plasma‐activated solid carbon precursor in a cold‐wall reactor using active screen technology and in a modified hot‐wall reactor during plasma nitrocarburizing of austenitic stainless steel. In addition, the modified hot‐wall reactor combined with a compact laser‐based absorption spectroscopy sensor for real‐time monitoring and concentration evaluation of in‐site generated gas species. It is shown that implementing a plasma‐activated solid carbon precursor in a modified hot‐wall reactor enables adjustable generation of C‐containing gas species, particularly HCN, with high production yield by an independent power management. Therefore, HCN is produced independent from heating while the limitations arising during active screen technology using a carbon screen are avoided. The presented technological development thus opens up new possibilities for better control of the plasma nitrocarburizing treatments of steels.

Methodological Considerations in Evaluating Breast Cancer Screening Studies.

In evidence-based medicine frameworks, the highest level of evidence is derived from quantitative synthesis of double-masked, high-quality, randomly assigned controlled trials. Meta-analyses of randomly assigned controlled trials have demonstrated that screening mammography reduces breast cancer deaths. In the United States, every major guideline-producing organization has recommended screening mammography in average-risk women; however, there are controversies about age and frequency. Carefully controlled observational research studies and statistical modeling studies can address evidence gaps and inform evidence-based, contemporary screening practices. As breast imaging radiologists develop and evaluate existing and new screening tests and technologies, they will need to understand the key methodological considerations and scientific criteria used by policy makers and health service researchers to support dissemination and implementation of evidence-based screening tests. The Wilson and Jungner principles and the U.S. Preventive Services Task Force general analytic framework provide structured evaluations of the effectiveness of screening tests. Key considerations in both frameworks include public health significance, natural history of disease, cost-effectiveness, and characteristics of screening tests and treatments. Rigorous evaluation of screening tests using analytic frameworks can maximize the benefits of screening tests while reducing potential harms. The purpose of this article is to review key methodological considerations and analytic frameworks used to evaluate screening studies and develop evidence-based recommendations.

Alternative endpoints to mortality in cancer screening trials.

The reliance on mortality endpoints in cancer screening trials is not always compatible with the need to accelerate progress in outcomes for patient and public benefit. Evaluation of novel cancer screening technologies, such as multi-cancer early detection (MCED) tests, could be expedited by using alternative metrics that are measurable earlier than mortality. These include endpoints based on cancer stage at diagnosis, such as reduction in late-stage cancer incidence, and endpoints following cancer diagnosis, such as eligibility for curative therapy. Innovative trial designs with earlier measures that complement cancer mortality are needed to realise the potential benefits of novel screening technologies such as MCEDs more rapidly.

A high-throughput system for drug screening based on the movement analysis of zebrafish

Zebrafish is a highly advantageous model animal for drug screening and toxicity evaluation thanks to its amenability to optical imaging (i.e., transparency), possession of organ structures similar to humans, and the ease with which disease models can be established. However, current zebrafish drug screening technologies and devices suffer from limitations such as low level of automation and throughput, and low accuracy caused by the heterogeneity among individual zebrafish specimens. To address these issues, we herein develop a high-throughput zebrafish drug screening system. This system is capable of maintaining optimal culturing conditions and simultaneously monitoring and analyzing the movement of 288 zebrafish larvae under various external conditions, such as drug combinations. Moreover, to eliminate the effect of heterogeneity, locomotion of participating zebrafish is assessed and grouped before experiments. It is demonstrated that in contrast to the experimental results without pre-selection, which shows ∼20 % damaged motor function (i.e., degree of attenuation), the drug-induced variations among zebrafish with equivalent mobility reaches ∼80 %. Overall, our high-throughput zebrafish drug screening system overcomes current limitations by improving automation, throughput, and accuracy, resulting in enhanced detection of drug-induced variations in zebrafish motor function.

Ultra-Low Frequency Transmitted Ultrasound Breast Imaging vs DBT (Digital Breast Tomosynthesis): A Patient-Reported Outcome Study.

Breast cancer screening remains a challenge in the United States. Many women do not get a mammogram because of pain associated with the exam, radiation exposure, false-positive results, and additional costs. Others who may benefit from annual screening do not qualify because of young age and radiation risk. We hypothesize that a novel volumetric transmitted breast ultrasound, Quantitative Transmission (QT) Scan may encourage more women to have annual breast cancer screening. Assessing results from patient-reported outcomes (PROs) may predict the value of newer, more desirable screening technologies. Pre- and post-menopausal women who qualified for breast cancer screening were enrolled in a prospective trial of Quantitative Transmission (QT Scan) vs traditional mammography via Digital Breast Tomosynthesis (DBT) Clinical Trials.gov NCT03052166. These women completed questionnaires to assess their experiences with QT Scan and DBT. Associations between QT Scan or DBT and differences in PRO scores were examined. A total of 430 subjects completed the PRO instrument analyzed. A total of 36 questions were asked, 34 were paired for both QT and DBT and two were asked regarding exclusively the QT Scan. Physical discomfort, perceptions of safety and low efficacy, false-positive results and additional out-of-pocket expenses were concerns identified as highest risk for opting out of screening mammography (differences between 2.1 and 2.9 indicate significant differences between means and standard deviations using the Cohen's d statistic). Student's T-test shows a significance level of <10 -10. Statistically significant differences in PROs between QT Scan and DBT were observed by 14 of the 17 paired experience questions (p<0.001). Significant differences in PROs were found between QT scan and DBT, indicating women have significantly more negative experiences with traditional mammography via DBT and are less inclined to undergo screening mammography. Identification of PRO differences could be used to help identify a more desirable breast cancer screening modality.

Integrated MUSIC array for high-precision damage diagnosis in complex composite structures

Guided Wave (GW)-based Multiple Signal Classification (MUSIC) damage imaging presents several advantages, such as high resolution, which makes it a promising technique for localizing damage in composite structures. However, the application of this technology in aircraft is confronted with various challenges. The variability in performance of MUSIC array sensors is attributed to material and manufacturing process dispersion. Additionally, the conventional wiring of MUSIC array sensors adds considerable weight and is not compatible with complex structural configurations. Furthermore, within intricate configurations, the attenuation of scattering signals induced by structural damage impacts the accuracy of imaging. Moreover, the manual and individual placement of sensors on structures, along with structural anisotropy, may introduce phase errors in the signals detected by MUSIC array sensors. This can lead to a reduction in the accuracy of MUSIC imaging and result in compromised long-term sensor reliability. This paper proposes a high-precision integrated MUSIC array for the diagnosis of complex composite damage. This approach aims to address the challenges related to damage imaging in materials with complex structures. Impedance curve screening and surface-mount co-curing technology are utilized to manage the performance variation of MUSIC array sensors, enhance layout uniformity, and improve long-term stability. Subsequently, a focus compensation algorithm is proposed within the integrated MUSIC design to enhance precision, reduce weight, and adapt to complex structures. The effectiveness of the proposed method is confirmed through experimental validation on an actual complex composite wing box segment, demonstrating a maximum error of 2 cm in locating impact damage.

Comparative analysis of modified partial least squares regression and hybrid deep learning models for predicting protein content in Perilla (Perilla frutescens L.) seed meal using NIR spectroscopy

Perilla seed meal (PSM), a byproduct of oil extraction from Perilla frutescens L. seeds, is rich in protein (24.26–42.85%) and holds potential as an economical and sustainable animal feed. Traditional methods for assessing protein content are labor-intensive and costly. This study explores Near-Infrared Reflectance Spectroscopy (NIRS) for the rapid, precise, and non-destructive determination of PSM protein content in 126 samples. We developed and evaluated Modified Partial Least Squares (MPLS) regression and deep learning (DL) models, including 1D-CNN (Convolutional Neural Network), LSTM Long Short-Term Memory), and hybrid architectures incorporating skip connections, inception modules, and spectral derivatives. Model performance was validated externally using parameters such as RSQexternal (R-squared), bias, SEP(C) (Standard Error of Prediction), RPD (Residual Prediction Deviation), slope, SD (Standard Deviation), p-value (≥0.05), and the correlation between reference and predicted values. The 1D CNN-LSTM-Inception derivative 1 model achieved the best performance (RPD: 8.0, RSQexternal: 0.98), followed by the MPLS-based model (RPD: 4.88, RSQexternal: 0.96) and the 1D CNN derivative 1 model (RPD: 3.07, RSQexternal: 0.96). These models provide a reliable and advanced technology for the non-destructive screening of PSM protein content, thus aiding in the rapid identification and selection of superior perilla chemotypes from varied backgrounds.

An efficient DNAzyme-locked leakless enzyme-free amplification system for alpha-foetoprotein detection in liver cancer and breast cancer.

Alpha-foetoprotein (AFP) is taken as a diagnostic tumor marker for the screening and diagnosis of cancer. Nucleic acid-based isothermal amplification strategies are emerging as a potential technology in early screening and clinical diagnosis of AFP. The leakages between hairpins dramatically increase the background and reduce the sensitivity. Thus, it is necessary to develop some strategies to reduce the leakage for isothermal amplification strategies. A DNAzyme-locked leakless enzyme-free amplification system was developed for AFP detection in liver cancer and breast cancer. AFP could open the apt-hairpin and initiate the catalytic hairpin assembly (CHA) reaction to produce a Y-shaped duplex. Two tails of a Y-shaped duplex cleaved the two kinds of leakless hairpins. Then, the third tail of the Y-shaped duplex catalyzed the second CHA between the cleaved leakless hairpins to recover the fluorescent intensity. The limit of detection reached 5fg/mL by the two levels of signal amplifications. Importantly, the leakless hairpin design effectively reduced leakage between hairpins and weakened the background. In addition, it also showed a great promising potential for AFP detection in early screening and clinical diagnosis.

New epilepsy therapies in development.

Epilepsy is a common brain disorder, characterized by spontaneous recurrent seizures, with associated neuropsychiatric and cognitive comorbidities and increased mortality. Although people at risk can often be identified, interventions to prevent the development of the disorder are not available. Moreover, in at least 30% of patients, epilepsy cannot be controlled by current antiseizure medications (ASMs). As a result of considerable progress in epilepsy genetics and the development of novel disease models, drug screening technologies and innovative therapeutic modalities over the past 10 years, more than 200 novel epilepsy therapies are currently in the preclinical or clinical pipeline, including many treatments that act by new mechanisms. Assisted by diagnostic and predictive biomarkers, the treatment of epilepsy is undergoing paradigm shifts from symptom-only ASMs to disease prevention, and from broad trial-and-error treatments for seizures in general to mechanism-based treatments for specific epilepsy syndromes. In this Review, we assess recent progress in ASM development and outline future directions for the development of new therapies for the treatment and prevention of epilepsy.