Traditional Screening Methods Research Articles

FAM Tag Size Separation-Based Capture-Systematic Evolution of Ligands by Exponential Enrichment for Sterigmatocystin-Binding Aptamers with High Specificity.

Sterigmatocystin (ST) is a known toxin whose aptamer has rarely been reported because ST is a water-insoluble small-molecule target with few active sites, leading to difficulty in obtaining its aptamer using traditional target fixation screening methods. To obtain aptamer for ST, we incorporated FAM tag size separation into the capture-systematic evolution of ligands by exponential enrichment and combined it with molecular activation for aptamer screening. The screening process was monitored using a quantitative polymerase chain reaction fluorescence amplification curve and recovery of negative-, counter-, and positive-selected ssDNA. The affinity and specificity of the aptamer were verified by constructing an aptamer-affinity column, and the binding sites were predicted using molecular docking simulations. The results showed that the Kd value of the H Seq02 aptamer was 25.3 nM. The aptamer-affinity column based on 2.3 nmol of H Seq02 exhibited a capacity of about 80 ng, demonstrating better specificity than commercially available antibody affinity columns. Molecular simulation docking predicted the binding sites for H Seq02 and ST, further explaining the improved specificity. In addition, circular dichroism and isothermal titration calorimetry were used to verify the interaction between the aptamer and target ST. This study lays the foundation for the development of a new ST detection method.

Advances in Droplet-Based Microfluidic High-Throughput Screening of Engineered Strains and Enzymes Based on Ultraviolet, Visible, and Fluorescent Spectroscopy

Genetic engineering and directed evolution are effective methods for addressing the low yield and poor industrialization level of microbial target products. The current research focus is on how to efficiently and rapidly screen beneficial mutants from constructed large-scale mutation libraries. Traditional screening methods such as plate screening and well-plate screening are severely limited in their development and application due to their low efficiency and high costs. In the past decade, microfluidic technology has become an important high-throughput screening technology due to its fast speed, low cost, high automation, and high screening throughput, and it has developed rapidly. Droplet-based microfluidic high-throughput screening has been widely used in various fields, such as strain/enzyme activity screening, pathogen detection, single-cell analysis, drug discovery, and chemical synthesis, and has been widely applied in industries such as those involving materials, food, chemicals, textiles, and biomedicine. In particular, in the field of enzyme research, droplet-based microfluidic high-throughput screening has shown excellent performance in discovering enzymes with new functions as well as improved catalytic efficiency or stability, acid-base tolerance, etc. Currently, droplet-based microfluidic high-throughput screening technology has achieved the high-throughput screening of enzymes such as glycosidase, lipase, peroxidase, protease, amylase, oxidase, and transaminase as well as the high-throughput detection of products such as riboflavin, coumarin, 3-dehydroquinate, lactic acid, and ethanol. This article reviews the application of droplet-based microfluidics in high-throughput screening, with a focus on high-throughput screening strategies based on UV, visible, and fluorescence spectroscopy, including labeled optical signal detection screening, as well as label-free electrochemical detection, mass spectrometry, Raman spectroscopy, nuclear magnetic resonance, etc. Furthermore, the research progress and development trends of droplet-based microfluidic technology in enzyme modification and strain screening are also introduced.

Age-Specific Reference Values for Amino Acid Content in Dried Blood Spots in Children in Western Kazakhstan, Measured by Tandem Mass Spectrometry

Measuring the level of amino acids in the blood is one of the stages in the early diagnosis of inborn errors of metabolism (IEM), implying timely initiation of therapeutic measures. Tandem mass spectrometry (MS/MS) is now replacing traditional IEM screening methods. Dried blood spot amino acid reference values developed for the pediatric population are crucial for interpreting test results and diagnosing aminoacidopathies. The study aims to establish reference values for amino acid (AAs) concentrations in samples of dried blood spots from newborns in Western Kazakhstan using LC-MS/MS (liquid chromatography-tandem mass spectrometry) technology. Methods: The cross-sectional study included 250 healthy newborns of Western Kazakhstan aged 1-3 days, born at term and breastfed, 49.2% male and 50.2% female. To establish the age-specific reference values for AAs, newborns were divided into three groups: (1) 1 day, (2) 2 days, and (3) 3 days. Blood samples on Guthrie cards were collected on days 1–3 of life and quantified by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Nonparametric statistical approaches were used to generate the 2.5th–97.5th percentile distributions for newborns. Results: 3 of the 15 DBS amino acid distributions were dependent on gender. There was a statistically significant difference in the mean level of alanine, citrulline, and glutamic acid in males and females. The highest values were determined in the female group. Age-related differences in glutamic acid, leucine, ornithine, tyrosine, and valine concentration levels were observed. No significant correlations were found between the concentrations of 15 amino acids in dried blood spots and the body weight of newborns. Conclusion: The present study established amino acid concentrations that can be utilized as reference standards in Kazakhstan's newborn screening program for inherited metabolic diseases.

High-grade cervical lesions diagnosed by JAM3/PAX1 methylation in high-risk human papillomavirus-infected patients.

Currently, traditional cervical cancer screening methods, such as high-risk human papillomavirus testing and liquid based cytology (LBC), still possess limitations. This study aims to identify new diagnostic biomarkers to achieve the goal of "precision screening" via exploring the clinical value of DNA methylation [ΔCtP: paired box gene 1 (PAX1)and ΔCtJ: junctional adhesion molecule 3 (JAM3)] detection in cervical exfoliated cells for the diagnosis of high-grade cervical lesions. A total of 136 patients who underwent gynecological examinations in the vaginal room of the Department of Gynecology at the Third Xiangya Hospital of Central South University from June 2021 to June 2022 were retrospectively studied. Among them, 122 patients had non-high-grade cervical lesions, and 14 patients had high-grade cervical lesions. The variables included general information (age, body mass index, and menopause status), LBC, high-risk human papillomavirus, cervical tissue pathology, vaginal examination results, and the ΔCt values of JAM3 and PAX1 gene methylation. Logistic regression analysis was used to identify the factors affecting the diagnosis of high-grade cervical lesions, followed by correlation analysis and construction of a conditional inference tree model. Logistic regression analysis showed that the methylation ΔCt values of PAX1 and JAM3 genes and LBC detection results were statistically significant between the high-grade cervical lesions group and the non-high-grade cervical lesions group (all P<0.05). Correlation analysis revealed a negative correlation between cervical pathological changes and ΔCtP (r=-0.36, P<0.001), ΔCtJ (r=-0.448, P<0.001), LBC (r=-0.305, P<0.001), or bacterial diversity (r=-0.183, P=0.037). The conditional inference tree showed that when ΔCtJ>10.13, all of patients had non-high-grade cervical lesions, while ΔCtP>6.22, the number of non-high-grade lesions accounted for 97.5% (117/120), and high-grade lesions accounted for only 2.5% (3/120). When ΔCtJ>8.61 and LBC were atypical squamous cell of undetermined significance or negative for intraepithelial lesions or malignancy (NILM), 105 (99.1%) patients were non-high-grade cervical lesions, only 1 (0.9%) patient was high-grade lesion. When the results of LBC were high-grade lesions, only 9 patients' histopathological examination was the high-grade lesions and 3 non-high-grade lesions. When LBC indicated low-grade lesions, atypical squamous cell of undetermined significance, no intraepithelial lesions, and ΔCtP>6.22, 117 (97.5%) of patients' histopathological examination was the non-high-grade lesions. The JAM3/PAX1 gene methylation test can be used independently for the stratified diagnosis of high-grade/non-high-grade cervical lesions in women with high-risk human papillomavirus infection, independent of the cytological results of cervical excision. The JAM3/PAX1 gene methylation test can also be used in combination with LBC to make up for the shortcomings of low sensitivity of LBC. In addition, the application of methylation kit in large-scale cervical cancer screening in the future will be good to the detection of more patients with high-grade cervical lesions, and achieve early screening and early treatment for cervical lesions/cancer.

HIt Discovery using docking ENriched by GEnerative Modeling (HIDDEN GEM): A novel computational workflow for accelerated virtual screening of ultra-large chemical libraries.

Recent rapid expansion of make-on-demand, purchasable, chemical libraries comprising dozens of billions or even trillions of molecules has challenged the efficient application of traditional structure-based virtual screening methods that rely on molecular docking. We present a novel computational methodology termed HIDDEN GEM (HIt Discovery using Docking ENriched by GEnerative Modeling) that greatly accelerates virtual screening. This workflow uniquely integrates machine learning, generative chemistry, massive chemical similarity searching and molecular docking of small, selected libraries in the beginning and the end of the workflow. For each target, HIDDEN GEM nominates a small number of top-scoring virtual hits prioritized from ultra-large chemical libraries. We have benchmarked HIDDEN GEM by conducting virtual screening campaigns for 16 diverse protein targets using Enamine REAL Space library comprising 37 billion molecules. We show that HIDDEN GEM yields the highest enrichment factors as compared to state of the art accelerated virtual screening methods, while requiring the least computational resources. HIDDEN GEM can be executed with any docking software and employed by users with limited computational resources.

Nucleic acid amplification testing (NAT) impact on blood safety compared to Immunoassays in blood banks: A Review

Blood transfusions are fundamental to clinical procedures; however, many people worldwide cannot access safe blood. Blood product safety must be essential in each country’s national health policies. Several aspects of the blood donation process are carefully performed, including laboratory testing comprising blood type determination, antigen-antibody analyses, and nucleic acid amplification testing (NAT); however, NAT is not mandatory in all countries. The traditional screening method is based on antigen-antibody binding techniques, such as ELISA (enzyme-linked immunosorbent assay), with high sensitivity and specificity. Nevertheless, these methods have a seroconversion window period (WP), in which antigen-antibody testing cannot detect the pathogen and has not caused any symptoms yet. NAT is a sensitive molecular method based on viral nucleic acid amplification and detection. Moreover, its use in blood banks is increasing worldwide because it narrows the window period. For example, Huang et al. in 2017 reported the detection of 22 samples reactive only by nucleic acid testing for either HIV, HBV, or HCV compared with ELISA. The present article shows how blood safety has improved by implementing NAT as a routine method for viral nucleic acid detection, highlighting the importance of this technique as evidenced by the findings presented herein. Moreover, these results are highly significant, demonstrating the relevance of NAT and advocating for its application on a global scale in blood management protocols. This development could be particularly beneficial for regions with a high viral infection prevalence, including many countries. Keywords: Nucleic acid amplification, Immunoassay, viral infection, blood bank.

High-throughput screening technologies for drug discovery

The development of high-throughput screening technologies has revolutionized the field of drug discovery by significantly improving the efficiency of compound library screening. Traditional screening methods, such as manual screening and biochemical assays, were time-consuming and limited in their ability to identify lead compounds. However, the advent of high-throughput screening technologies has overcome these limitations and provided researchers with a more efficient and effective approach. This review begins by examining the background, characteristics, and limitations of conventional screening methods. These methods often required large amounts of time, resources, and labor, making them impractical for large-scale compound screening. In recent years, some new technologies have emerged, including virtual screening, image analysis, prediction methods, and microarray-based screening. Each of these approaches has its own strengths and limitations, but collectively they have greatly enhanced the efficiency and accuracy of compound identification. These viewpoints highlight the successful application of these technologies in identifying lead compounds for various therapeutic targets. Finally, the review envisions the future development of high-throughput screening technologies. It emphasizes the need for continuous optimization and innovation to further improve the efficiency and effectiveness of compound identification. The ultimate goal is to shorten drug development timelines and provide high-quality lead compounds for the benefit of patients. In conclusion, the emergence of high-throughput screening technologies has significantly improved the efficiency of compound library screening and provided better lead compounds for drug discovery. Ongoing advancements in these technologies hold great promise for the future of pharmaceutical research and development.

Current controversies in prenatal diagnosis: Noninvasive prenatal testing should replace other screening strategies for fetal trisomies 13, 18, 21.

This is a written summary of the oral debate presented at the International Society for Prenatal Diagnosis annual conference in Edinburgh in 2023. The topic under debate is whether noninvasive prenatal testing (NIPT) using cell-free fetal DNA should replace other screening strategies for the detection of fetal trisomies 13, 18, 21. There is no disagreement that NIPT is far more sensitive and has better positive predictive values for identifying trisomies 13, 18, and 21 than traditional screening approaches using biochemical markers and measurement of nuchal translucency. The major issue lies in the potential adverse consequences associated with abandoning traditional screening methods. The source of disagreement stems primarily from whether you consider the role of ultrasound in the context of screening to be strictly for nuchal translucency measurement or whether it should be combined with a fetal anatomy scan. The debate featured two experts who presented evidence in favor of each argument.

Advancements in virtual screening techniques for study of enzyme inhibitor compounds

Enzymes are closely associated with the onset and progression of numerous diseases, making enzymes a primary target in innovative drug development. However, the challenge remains in identifying compounds that exhibit potent inhibitory effects on the target enzymes. With the continuous expansion of the total number of natural products and increasing difficulty in isolating and enriching new compounds, traditional high-throughput screening methods are finding it increasingly challenging to meet the demands of new drug development. Virtual screening, characterized by its high efficiency and low cost, has gradually become an indispensable technology in drug development. It represents a prominent example of the integration of artificial intelligence with biopharmaceuticals and is an inevitable trend in the rapid development of innovative drug screening in the future. Therefore, this article primarily focused on systematically reviewing the recent applications of virtual screening technology in the development of enzyme inhibitors and explored the prospects and advantages of using this technology in developing new drugs, aiming to provide essential theoretical insights and references for the application of related technologies in the field of new drug development.

Enhancing Provider Mental Health Screening in Primary Care: A Quality Improvement Project.

Background: Depression and anxiety occur in 7.8% and 19.1% of the US population, respectively. About half of those patients are diagnosed in primary care. Objective: The purpose of this quality improvement project was to improve the screening and diagnosing of anxiety and/or depression among adult patients at a primary care clinic by implementing an evidence-based mental health screening interview technique. Methods: The team implemented a mental health screening interview technique that incorporates background, affect, trouble, handling, and empathy and motivational interviewing techniques in addition to self-report surveys. Pre- and post-intervention surveys were conducted to assess providers' perceptions of the new interview technique. ICD-10 code data were gathered to assess the effectiveness of the new mental health screening interview technique. Results: The number of documented diagnoses of single-episode major depressive disorder decreased by 18%, recurrent major depressive disorder increased by 34%, and anxiety disorders increased by 3%. There were more favorable provider perceptions of the new screening interview technique versus the traditional screening method. Conclusions: The results show an improvement in provider comfort and providers preferred the new mental health screening when using an evidence-based mental health screening interview technique. Implications for nursing: The results show the potential benefits of using a structured mental health interview with self-report screening tools when diagnosing anxiety and depression in primary care.

Recent Advances in Non-Targeted Screening of Compounds in Plastic-Based/Paper-Based Food Contact Materials.

Ensuring the safety of food contact materials has become a pressing concern in recent times. However, detecting hazardous compounds in such materials can be a complex task, and traditional screening methods may not be sufficient. Non-targeted screening technologies can provide comprehensive information on all detectable compounds, thereby supporting the identification, detection, and risk assessment of food contact materials. Nonetheless, the non-targeted screening of food contact materials remains a challenging issue. This paper presents a detailed review of non-targeted screening technologies relying on high-resolution mass spectrometry for plastic-based and paper-based food contact materials over the past five years. Methods of extracting, separating, concentrating, and enriching compounds, as well as migration experiments related to non-targeted screening, are examined in detail. Furthermore, instruments and devices of high-resolution mass spectrometry used in non-targeted screening technologies for food contact materials are discussed and summarized. The research findings aim to provide a theoretical basis and practical reference for the risk management of food contact materials and the development of relevant regulations and standards.

Comparative assessment of veneral disease research laboratory (VDRL) and point of care (POC) tests for diagnosing syphilis among pregnant women at a tertiary health facility in Lagos: A retrospective cohort study

Background: Syphilis is a systemic infection caused by the Spirochete Treponema Pallidum. The infection is of particular concern during pregnancy because of the high risk of vertical transmission causing adverse outcome including death. Traditional screening method is with Venereal Disease Research Laboratory (VDRL), which has a high false positive result and an increased waiting time. Aim: To compare the syphilis detection rate between Point-of-Care testing and Venereal Disease Research Laboratory testing among pregnant women. Methods: The retrospective cohort study was conducted at 68 Nigerian Army Reference Hospital Yaba (68NARHY), Lagos between July 2021 and June 2023. Data from antenatal clinic records were retrieved. All eligible pregnant women had both POC and VDRL testing. The primary outcome measures were false positive, false negative, true positive, true negative of the two tests. The sensitivity, and specificity and the diagnostic accuracy of both tests were calculated following which the ROC curve was drawn. Women with incomplete record or who did not conduct both testing were excluded from the study. All data set were collected using a well-designed purpose driven proforma. The data set were stored and later analyzed using the IBM SPSS for Windows, version 26.0 Armonk, NY: IBM corp. Analysis was both descriptive and inferential. The p-value of &lt; 0.05 was set as statistically significant levels. Result: The mean age of the participants was 31.30±5.3. About 45.5% were of low parity while military personnel consisted of more than half of the study population. The prevalence of syphilis was 1.8% and 4.3% using VDRL and POC test kits respectively. When compared, there was a significant difference (P&lt;0.001). It was also noted that a greater proportion of military personnel were reactive to the screening using either of those kits as against civilians. Conclusion: In our study, POC has demonstrated its ability to detect more cases of syphilis than VDRL as a screening test. Therefore, POC may serve as a cost-effective replacement screening test for VDRL, to rapidly and accurately detect syphilis infection. This step is crucial for early diagnosis, prompt treatment, and the prevention of further transmission of syphilis.

Online Feature Screening for Data Streams With Concept Drift

Screening feature selection methods are often used as a preprocessing step for reducing the number of variables before training step. Traditional screening methods only focus on dealing with complete high dimensional datasets. Modern datasets not only have higher dimension and larger sample size, but also have properties such as streaming input, sparsity and concept drift. Therefore a considerable number of online feature selection methods were introduced to handle these kind of problems in recent years. Online screening methods are one of the categories of online feature selection methods. The methods that we proposed in this research are capable of handling all three situations mentioned above. Our research study focuses on classification datasets. Our experiments show proposed methods can generate the same feature importance as their offline version with faster speed and less storage consumption. Furthermore, the results show that online screening methods with integrated model adaptation have a higher true feature detection rate than without model adaptation on data streams with the concept drift property. Among the two large real datasets that potentially have the concept drift property, online screening methods with model adaptation show advantages in either saving computing time and space, reducing model complexity, or improving prediction accuracy.

Three-dimensional, PEG-based hydrogels induce spheroid formation and enhance viability of A2058 melanoma cells.

Traditional drug screening methods use monolayer (2D) tumor cell cultures, which lack basic features of tumor complexity. As an alternative, 3D hydrogels have begun to emerge as simple, time-, and cost-saving systems. One of the most promising candidates, synthetic alkoxysilane-PEG (polyethylene glycol)-based hydrogels, are formed by "sol-gel" polymerization in an aqueous medium, which allows control over the incorporated elements. Our aims were to optimize siloxane-PEG hydrogels for three different cell lines of skin origin and utilize these 3D hydrogels as a feasible drug (e.g., daunorubicin) screening assay. A drastic increase in survival and the formation of cellular aggregates (spheroids) could be observed in A2058 melanoma cells, but not in keratinocyte and endothelial cell lines. A deep-learning neural network was trained to recognize and distinguish between the cellular formations and allowed the fast processing of hundreds of microscopic images. We developed an artificial intelligence (AI)-assisted application (https://github.com/enyecz/CancerDetector2), which indicated that, in terms of average area of the spheroids treated with daunorubicin, A2058 melanoma cell 3D aggregates have better survival in a hydrogel containing 15% bis-mono-ethoxysilane-PEG.

ESGNet: A multimodal network model incorporating entity semantic graphs for information extraction from Chinese resumes

Corporations require screening critical information from numerous resumes with different formats and content for managerial decision-making. However, traditional manual screening methods have low accuracy to meet the demand. Therefore, we propose a multimodal network model incorporating entity semantic graphs, ESGNet, for accurately extracting critical information from Chinese resumes. Firstly, each resume is partitioned into distinct blocks according to content while constructing an entity semantic graph according to entity categories. Then we interact with associated features within image and text modalities to capture the latent semantic information. Furthermore, we employ Transformer containing multimodal self-attention to establish relationships among modalities and incorporate supervised comparative learning concepts into the loss function for categorizing feature information. The experimental results on the real Chinese resume dataset demonstrate that ESGNet achieves the best information extraction results on all three indicators compared with other models, with the comprehensive indicator F1 score reaching 91.65%.

Enhancing Provider Mental Health Screening in Primary Care: A Quality Improvement Project.

Background: Depression and anxiety occur in 7.8% and 19.1% of the US population, respectively. About half of those patients are diagnosed in primary care. Objective: The purpose of this quality improvement project was to improve the screening and diagnosing of anxiety and/or depression among adult patients at a primary care clinic by implementing an evidence-based mental health screening interview technique. Methods: The team implemented a mental health screening interview technique that incorporates background, affect, trouble, handling, and empathy and motivational interviewing techniques in addition to self-report surveys. Pre- and post-intervention surveys were conducted to assess providers' perceptions of the new interview technique. ICD-10 code data were gathered to assess the effectiveness of the new mental health screening interview technique. Results: The number of documented diagnoses of single-episode major depressive disorder decreased by 18%, recurrent major depressive disorder increased by 34%, and anxiety disorders increased by 3%. There were more favorable provider perceptions of the new screening interview technique versus the traditional screening method. Conclusions: The results show an improvement in provider comfort and providers preferred the new mental health screening when using an evidence-based mental health screening interview technique. Implications for nursing: The results show the potential benefits of using a structured mental health interview with self-report screening tools when diagnosing anxiety and depression in primary care.

Rational biodiesel production by screening different long-term stored plant oils via nuclear magnetic resonance spectroscopic measurement

Screening the raw materials for biodiesel production has normally concentrated on the triglyceride (TAG) content and fatty acid profile without considering the oxidation stability, a crucial restriction factor for commercial life of biodiesel. The traditional screening methods had complex procedures by characterizing the raw material’ and the prepared biodiesel’ properties, which was not applicable for large sets of raw materials. These factors propelled the development of a simple and efficient screening method for potential biodiesel feedstock. Herein, we compared two kinds of spectroscopic measurements, the three-dimensional fluorescence (3D-FL) and high field nuclear magnetic resonance (NMR), for screening special and differential raw materials by investigating 19 plant oil species with one-year storage for biodiesel production. Among these samples, 13 kinds of plant oils contained TAGs, and the other 6 were free of TAGs. The results showed that 3D-FL measurements improperly assigned citronella oil as a TAG-containing plant oil and determined limited information about their chemical composition, suggesting unsatisfactory screening performance. In contrast, 1H NMR measurements screened 3 kinds of differential oils out of those 19 plant oil species, including coconut oil (Cocos nucifera L.), cotton seed oil (Gossypium barbadense L.), palm oil (Elaeis guineensis). Hierarchical clustering analysis (HCA) and partial least square discriminant analysis (PLS-DA) presented that the statistically significant NMR spectral bins for their differential compositions were signals at 3.6 ppm (–OCH3), 2.31 ppm (–OCH2–COOH), 4.29 ppm (TAG skeleton), and 5.27 ppm (TAG skeleton), representing the oxidation products, unsaturated fatty acids, and TAGs. Finally, the converted methyl and ethyl esters (biodiesel) from those three differential plant oil samples were subjected to Rancimat tests. They showed quite different oxidation stabilities from Rancimat tests, which was relevant to the composition differences in the NMR analysis. Our results suggested that the rapid, simple, and reliable NMR measurement combined with HCA and PLS-DA can serve as an efficient tool for potential biodiesel feedstock screening.

Performance of the Spot Vision Screener in children with Down syndrome and other special needs

Amblyopia is a common cause of monocular vision impairment and disproportionally affects developmentally delayed children. Photoscreeners have been suggested as a method to detect amblyopia risk factors (ARFs) in children with developmental disabilities who may not be amenable to traditional vision screening methods. The Spot Vision Screener is a commonly used photoscreener for detecting ARF and has shown excellent sensitivity and accuracy in the general pediatric population. The purpose of this study was to evaluate its accuracy in children with Down syndrome and other special needs. Children with various disabilities or delays were recruited from outpatient clinics at the Children's Hospital of Colorado. Participants had their photograph taken with Spot before and after pupil dilation and cycloplegia. Images were compared to results of a comprehensive clinical eye examination. A total of 100 children participated in the study. Images could not be obtained in 12 children; 5 children did not attend their clinical examination. The overall sensitivity of Spot was 90%, with a positive predictive value of 80% in undilated subjects. The area under the receiver operator curve (AUROC) was 0.68 (95% CI, 0.57-0.79), which did not differ significantly from the AUROC after dilation/cycloplegia (0.68; 95% CI, 0.54-0.81). The Spot Vision Screener could be used by primary care clinics and vision screening programs with a high sensitivity to determine which patients with Down syndrome and special needs should be referred for clinical examination.

The effectiveness of non-invasive prenatal test technology and the prenatal screening algorithm based on various methods for determining foetal aneuploidy.

The purpose was to evaluate the effectiveness of a non-invasive prenatal test (NIPT) using mass parallel sequencing (MPS) to detect trisomy 13, 18, 21 and fetal sex chromosome abnormalities in maternal blood samples by isolating freely circulating foetal extracellular DNA (eDNA), and to develop an algorithm for prenatal screening. The research methods used included blood sampling from patients, isolation of eDNA, determination of DNA concentration and quality, library preparation for sequencing, MPS using an Illumina HiSeq2000, positive and negative control samples, monitoring, and analysis of results using the distributed algorithms platform based on calculations of z-value and the average absolute deviation. Pregnant women were divided into two groups based on gestational age at sampling, group 1; 9-14 weeks and group 2; 15-27 weeks. A total of 377 pregnant women were included with a mean (range) age of 33 (23-44) years. The mean gestational age at the time of blood sampling in group 1 was 11 (9-14) weeks, and in group 2 was 21 (15-27) weeks. In the first group, three cases of trisomy 18 chromosomes were detected in patients aged 43 years old, and female children were subsequently born with Edwards syndrome. In the second group, one case of trisomy 21 was detected in a patient aged 36 years and the pregnancy was terminated at 25 weeks. The analysis of freely circulating foetal eDNA was a sensitive method for detecting chromosomal abnormalities. The study has a practical significance, since the NIPT for frequent aneuploidy considerably exceeds the effectiveness of traditional screening methods and allows identifying chromosomal disorders starting from the 9th week of the gestation period.

Construction of a QSAR Model Based on Flavonoids and Screening of Natural Pancreatic Lipase Inhibitors.

Pancreatic lipase (PL) is a key hydrolase in lipid metabolism. Inhibition of PL activity can intervene in obesity, a global sub-health disease. The natural product is considered a good alternative to chemically synthesized drugs due to its advantages, such as low side effects. However, traditional experimental screening methods are labor-intensive and cost-consuming, and there is an urgent need to develop high-throughput screening methods for the discovery of anti-PL natural products. In this study, a high-throughput virtual screening process for anti-PL natural products is provided. Firstly, a predictable anti-PL natural product QSAR model (R2train = 0.9444, R2test = 0.8962) were developed using the artificial intelligence drug design software MolAIcal based on genetic algorithms and their conformational relationships. 1068 highly similar (FS > 0.8) natural products were rapidly enriched based on the structure-activity similarity principle, combined with the QSAR model and the ADMET model, for rapid prediction of a total of five potentially efficient anti-PL natural products (IC50pre < 2 μM). Subsequently, molecular docking, molecular dynamics simulation, and MMGBSA free energy calculation were performed to not only reveal the interaction of candidate novel natural products with the amino acid residues of PL but also to validate the stability of these novel natural compounds bound to PL. In conclusion, this study greatly simplifies the screening and discovery of anti-PL natural products and accelerates the development of novel anti-obesity functional foods.