Screening Mode Research Articles

Rapid Campimetry in glaucoma – correspondence with standard perimetry and OCT

The Rapid Campimetry (RC), a kinetic visual field test proved to reliably detect visual field defects within the central 10° degrees, the most crucial part for visual acuity and quality of life, affected even at very early stages of glaucoma, within a short measurement epoch, ~ 1 min. This study aims to further investigate RC correspondence with standard tests in glaucoma, namely standard automated perimetry (SAP) and optical coherence tomography (OCT) within 10° of visual field (VF). For this purpose, we included 41 participants, [21 glaucoma (GLA, mean age: 65.9 ± 12.4; 12 preperimetric eyes and 11 with VF defects) and 20 healthy controls (HC; mean age: 65.0 ± 10.3); 20 eyes]. At first, we compared the rate of detection/exclusion of VF defects in RC vs. SAP. Then, for those with VF defects (11 eyes), we investigated the 68-pointwise correspondence of 10 − 2 layout of RC and SAP. For functional and structural (SF) correspondence, pointwise correspondence of RC, SAP vs. OCTmacula [ macular ganglion cell thickness (GCL)] was also performed. Further, we compared sector-based correspondence of RC, SAP vs. OCTmacula accounting for GCL displacement at the fovea as well as sector-based correspondence with OCTdisc [peripapillary retinal nerve fiber layer thickness (pRNFL)]. Agreement estimates were reported along with Cohen Kappa (\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:\\kappa\\:$$\\end{document}) statistic. For overall performance, RC and SAP showed 100% agreement (\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:\\kappa\\:=1$$\\end{document}) for the exclusion of VF defects (HC and preperimetric GLA) and for detection of VF defects [11 eyes of 9 GLA, (\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:\\kappa\\:=1)$$\\end{document}]. Further, RC outperformed SAP in detection of arcuate scotomas, 7 vs. 5, respectively. Pointwise correspondence of VF defects (11 eyes), RC-SAP agreement reached 90% accuracy (\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:\\kappa\\:=0.77,\\:substantial\\:agreement$$\\end{document}). For SF correspondence, RC [SAP] showed 62% [69%] pointwise agreement with OCTmacula, (\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:\\kappa\\:=0.10\\:\\left[0.33\\right]$$\\end{document}). For macular sector-based correspondence, SF correspondence improved and reached 83% [83%] agreement, (\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:\\kappa\\:=0.57\\:\\left[0.57\\right]$$\\end{document}). For OCTdisc sector-based analysis, SF correspondence was highest, 100% [100%] agreement, (\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:\\kappa\\:=1\\:\\left[1\\right]$$\\end{document}). Rapid Campimetry gave reproducible results in comparison to SAP and OCT with high potential as a screening VF method given its short testing duration, ~ 1 min in screening mode, and compatibility with telemedicine technologies upon future optimization and automation.

When and How to Evaluate Vitamin D Status? A Viewpoint from the Belgian Bone Club.

Low serum vitamin D levels have been associated with a variety of health conditions which has led the medical community but also the general population to evaluate vitamin D status quite liberally. Nevertheless, there remain questions about the efficacy and cost-effectiveness of such a broad and untargeted approach. This review therefore aims to summarize the current evidence and recommendations on when and how to evaluate vitamin D status in human health and disease. For the general population, most guidelines do not recommend universal screening but suggest a targeted approach in populations at risk. Also, some guidelines do not even recommend evaluating vitamin D status when vitamin D substitution is indicated anyway, such as in children or patients receiving anti-osteoporosis drugs. In those guidelines that recommend the screening of vitamin D status, serum 25(OH)D levels are universally proposed as the preferred screening tool. However, little attention is given to analytical considerations and almost no guidelines discuss the timing and frequency of screening. Finally, there is the known variability in diagnostic thresholds for defining vitamin D insufficiency and deficiency. Overall, the existing guidelines on the evaluation of vitamin D status differ broadly in screening strategy and screening implementation, and none of these guidelines discusses alternative screening modes, for instance, the vitamin metabolic ratio. Efforts to harmonize these different guidelines are needed to enhance their efficacy and cost-effectiveness.

Synthesis, biological screening, and binding mode analysis of some N-substituted tetrahydroquinoline analogs as apoptosis inducers and anticancer agents

One of the most common malignancies in the world is lung cancer. Lung cancer involves mutations in many different genes, however, EGFR, KRAS, PTEN, and PIK3CA involvement is more frequent. The lack of effective drugs and drug resistance are major issues and obstacles associated with the current treatment of lung cancer. Seven novel tetrahydroquinoline analogs were synthesized and screened against a range of cancer cell lines in this study. Among these, 17f (IC50=0.082 µM) was shown to be the most potent when compared to the standard drug 5-Flurouracil (5FU) (IC50=0.28 µM). Moreover, flow cytometry analysis was carried out to ascertain the nature of programmed cell death. This provides conclusive evidence of late apoptosis in all synthesized compounds when contrasted with the standard drug (5FU) and control. After comparing all of the outputs, additional binding mode analysis was carried out to determine the potential mechanism of its anticancer activity. Molecular docking and MD simulation studies were carried out, and the results show that all of the synthesized compounds 17-a-f (17f docking score -10.5 Kcal/mol) have a better binding affinity towards mTOR (PDB id: 4JT6) than both the standard drug 5FU and the co-crystal ligand X6K (docking score: -7.6 Kcal/mol). Despite the aforementioned information, strong hit compounds from this series may eventually be developed to become lead mTOR inhibitors for the treatment of lung cancer.

Understanding experiences and perspectives in addressing unmet social needs of children and families in a paediatric weight management program: a qualitative descriptive study

ObjectiveThe objective is to describe the experiences and perceptions of caregivers who participated in a community systems navigator intervention that addressed unmet social needs.Design, setting and patientsA qualitative descriptive study...

Rapid discovery of natural skin-lightening ingredients based on an integrated screening strategy based on molecular docking and zebrafish model.

Natural herbs have been widely considered a reservoir for skin-lightening ingredients, but discovery of the effective ingredients from herbs remains a large challenge. This research aimed to rapidly identify compounds with skin-lightening activity in Chinese herbs. The structure information of herbal compounds was collected and selected from the open-source data. High throughput virtual screening (HTVS) and Extra precision (XP) docking modes were used to screen for compounds that could bind to the mushroom tyrosinase involved in melanin synthesis. Furthermore, molecular dynamics (MD) simulations were introduced to assess the binding stability of those compounds with the key target protein. The candidate compounds found by this kind of multidimensional molecular screening were finally tested for their ability to inhibit pigmentation and potential toxicity using an invivo zebrafish animal model. A Natural Compounds Database was established with 5616 natural compounds. Fourteen compounds with favorable binding capability were screened by the XP docking mode with mushroom tyrosinase and five compounds among them were found to have superior dynamic binding performance through MD simulations. Then the Zebrafish animal experiments revealed that two components, sennoside B (SB) and sennoside C (SC), could significantly inhibit melanogenesis rather than the other three compounds. Meanwhile, there were no obvious side effects observed in SB and SC about the morphology, heart rate, or body length of zebrafish. A strategy for rapid screening of compounds with whitening activity has been established, and two potent skin-lightening compounds, SB and SC, have been identified from a vast library of herbal compounds. This study revealed that SB and SC have potential for topical use in skin lightening for the first time. The findings of this study would provide an important theoretical basis for the application of these two compounds in the cosmetic field in the future.

Separation of quinoline from quinoline/2-methylnaphthalene using deep eutectic solvents: Experimental and COSMO-RS prediction

The high-temperature coal tar wash oil contains two valuable components, namely, quinoline and 2-methylnaphthalene. These two components are challenging to separate during the deep processing. To address this issue, the COSMO-RS (Conductor-like Screening Mode for Real Solvent) model was utilized to identify them as a potential deep eutectic solvents (DESs) extractant. Based on the calculated infinite dilution activity coefficient, the performance indexes of DESs, including selectivity, solubility, and performance index were determined and utilized to identify high-performance extractants for the quinoline/2-methylnaphthalene system. Finally five DESs were selected based on these indexes, they are DES1 formed by Choline chloride: propionic acid with the molar ratio of 1:1, similarly, DES2 is Choline chloride:oxalic acid of 1:1, DES3 Tetraethylammonium chloride:propionic acid of 1:1, DES4 Tetraethylammonium bromide:itaconic acid of 1:2 and DES5 Tetraethylammonium bromide:propionic acid of 1:2. The liquid–liquid phase equilibrium experiments of the aforementioned five DESs at different temperatures (30 ℃, 40 ℃, and 50 ℃) under atmospheric pressure were conducted. The results showed that five kinds of DESs had good extraction effect on quinoline. The DESs formed by choline chloride and anhydrous oxalic acid had the best extraction effect. The quantum chemical single-molecule optimization of different HBDs and HBAs in DESs, intermolecular interaction energy analysis and independent gradient modeling shows that it is mainly induced by the formation of shared electron pairs by providing empty orbitals from DESs and lone pair of electrons from the quinoline molecule, and the main force is the weak hydrogen bonding force.

Targeted quantification and untargeted exploration of furan and derivatives in infant food by headspace extraction-gas chromatography-Q Exactive Orbitrap mass spectrometry

The aim of the present study was to assess the performance and complementarity of methods capable of both quantifying furan, 2-Methylfuran (2-MF) and 3-Methylfuran (3-MF) in infant foods, but also to comprehensively explore other furan derivatives. It is more particularly a question of validating and comparing the couplings of the two headspace extraction methods most used for the analysis of furan compounds − Headspace Solid Phase Microextraction (HS-SPME) and Static HeadSpace (SHS) – with gas chromatography hyphenated to a high-resolution mass detector (Q Exactive-Orbitrap MS) which allows both targeted quantification and suspect screening. Firstly, the accuracy profile approach was implemented to assess, validate and compare HS-SPME- and SHS-GC-Q Exactive-Orbitrap MS for the quantification of furan in two model infant foods, apple puree and first infant formula. SHS-GC-Q Exactive-Orbitrap MS, showed better accuracy (uncertainty < 17.2 % vs 22.5 % for HS-SPME GC-Q Exactive-Orbitrap MS) and better sensitivity (LOQ < 2.8 vs LOQ < 4.0 µg/kg) over a broader validation range (2–100 µg/kg vs 5–100 µg/kg in apple puree). Secondly, SHS-GC-Q Exactive-Orbitrap MS was assessed and validated by accuracy profile for the quantification of 2-MF and 3-MF, with performance close to those for furan except for 3-MF in apple puree. Thirdly, SHS-GC-Q Exactive-Orbitrap MS was used to quantify the levels of these compounds in 20 commercial samples (n = 3) belonging to the four main categories of infant food (infant formulae, fruit purees, infant cereals, vegetable/fish baby meals). Furan was quantified in 75 % of the samples, with maximum levels in the vegetable/fish-based infant foods (up to 127 µg/kg) while 2-MF and 3-MF were quantified in 45 % and 15 % of products respectively, with maximum levels of 14.1 µg/kg in follow-on formula 3rd age and 9.2 µg/kg in apple puree. Finally, SHS- and HS-SPME-GC-Q Exactive-Orbitrap MS data of the 20 infant products were processed in suspect screening mode using Compound DiscovererTM software. Coupling with HS-SPME, it made it possible to identify 13 additional furan derivatives, i.e. 5 more than with SHS. The relevance and safety status of the compounds identified are discussed.

Discovery of novel benzimidazole derivatives as selective and reversible monoamine oxidase B inhibitors for Parkinson's disease treatment

Parkinson's disease (PD) is a common neurodegenerative disorder characterized by the loss of dopaminergic neurons in the substantia nigra pars compacta. The development of novel scaffolds for human monoamine oxidase B (hMAO-B) inhibitors with reversible properties represents an important strategy to improve the efficacy and safety for PD treatment. In the current work, we have devised and assessed two innovative derivative series serving as hMAO-B inhibitors. These series have utilized benzimidazole as a scaffold and strategically incorporated a primary amide group, which is recognized as a pivotal pharmacophore in subsequent activity screening and reversible mode of action. Among these compounds, 16d has emerged as the most potent hMAO-B inhibitor with an IC50 value of 67.3 nM, comparable to safinamide (IC50 = 42.6 nM) in vitro. Besides, 16d demonstrated good selectivity towards hMAO-B isoenzyme with a selectivity index over 387. Importantly, in line with the design purpose, 16d inhibited hMAO-B in a competitive and reversible manner (Ki = 82.50 nM). Moreover, 16d exhibited a good safety profile in both cellular and acute toxicity assays in mice. It also displayed ideal pharmacokinetic properties and blood-brain barrier permeability in vivo, essential prerequisites for central nervous system medicines. In the MPTP-induced PD mouse model, 16d significantly alleviated the motor impairment, especially muscle relaxation and motor coordination. Therefore, 16d, serving as a lead compound, holds instructive significance for subsequent investigations regarding its application in the treatment of PD.

Geometry Optimization Algorithms in Conjunction with the Machine Learning Potential ANI-2x Facilitate the Structure-Based Virtual Screening and Binding Mode Prediction.

Structure-based virtual screening utilizes molecular docking to explore and analyze ligand-macromolecule interactions, crucial for identifying and developing potential drug candidates. Although there is availability of several widely used docking programs, the accurate prediction of binding affinity and binding mode still presents challenges. In this study, we introduced a novel protocol that combines our in-house geometry optimization algorithm, the conjugate gradient with backtracking line search (CG-BS), which is capable of restraining and constraining rotatable torsional angles and other geometric parameters with a highly accurate machine learning potential, ANI-2x, renowned for its precise molecular energy predictions reassembling the wB97X/6-31G(d) model. By integrating this protocol with binding pose prediction using the Glide, we conducted additional structural optimization and potential energy prediction on 11 small molecule-macromolecule and 12 peptide-macromolecule systems. We observed that ANI-2x/CG-BS greatly improved the docking power, not only optimizing binding poses more effectively, particularly when the RMSD of the predicted binding pose by Glide exceeded around 5 Å, but also achieving a 26% higher success rate in identifying those native-like binding poses at the top rank compared to Glide docking. As for the scoring and ranking powers, ANI-2x/CG-BS demonstrated an enhanced performance in predicting and ranking hundreds or thousands of ligands over Glide docking. For example, Pearson's and Spearman's correlation coefficients remarkedly increased from 0.24 and 0.14 with Glide docking to 0.85 and 0.69, respectively, with the addition of ANI-2x/CG-BS for optimizing and ranking small molecules binding to the bacterial ribosomal aminoacyl-tRNA receptor. These results suggest that ANI-2x/CG-BS holds considerable potential for being integrated into virtual screening pipelines due to its enhanced docking performance.

Impact of Tutorial Modes with Different Time Flow Rates in Virtual Reality Games

Virtual reality's (VR) unique affordances compared to traditional media have produced innovative interaction modes and tutorial methodologies in VR games. Existing research predominantly focuses on the performance of VR tutorial modes, such as the placement of text and diagrams within tutorial content. However, few studies have delved into other attributes of tutorials. This study categorizes 4 VR game tutorial modes based on time flow: (1) traditional instruction screen, (2) slow motion, (3) bullet time, and (4) context-sensitive mode. This paper evaluates the impact of these 4 VR game tutorial modes with varying time flow rates on controls learnability, engagement-related outcomes, and player performance. We conducted a between-subjects experiment with 59 participants. Results indicated that bullet time significantly enhanced controls learnability, reduced cognitive load, and improved player performance when compared to other tutorial modes. Our research contributes to a more comprehensive understanding of VR game tutorials and offers practical guidance for game designers, underscoring the potential of bullet time to enhance learnability and game experience.

Abstract PO3-08-01: Decision curve analysis to compare breast cancer risk predictions for a polygenic integrated clinical risk model with those of a gold standard

Abstract Risk-based guidelines have been developed to provide advice on options that are available to women who are at increased risk of breast cancer. We and others are focused on improving risk prediction models for general population use. For breast cancer, polygenic risk has been identified as important for risk prediction, especially when combined with clinical risk factors such as family history, anthropometric measures, breast imaging measures, and hormonal and reproductive risk factors. When comparing the performance of risk prediction models, the AUC is most often used but it focuses on performance in terms of distinguishing between affected and unaffected individuals and does not take into account differences in the specificity (true negative rate) and sensitivity (true positive rate) of the models being compared. In contrast, decision curve analysis takes sensitivity and specificity into account and enables the comparison of the net benefit of risk prediction tools at the clinical risk thresholds that are used to guide clinical management decisions. Herein, we use decision curve analysis to compare breast cancer risk prediction guidelines for BRISK and the Breast Cancer Risk Assessment Tool (BCRAT) in the UK Biobank, and for BRISK and IBIS version 7 in the Nurses’ Health Study. We evaluated the net benefit at the 5-year risk thresholds (1.67% and 3%) that are used to guide clinical management decisions around risk-reducing medication and at the remaining lifetime risk of 20% that is used to guide supplemental MRI surveillance. In the UK Biobank, BRISK showed a net benefit over BCRAT at the 5-year risk thresholds of 1.67% and 3.0%. The AUCs were 0.649 (95% CI = 0.640, 0.695) for BRISK and 0.567 (95% CI = 0.556, 0.577) for BCRAT and showed that, overall, BRISK discriminated between affected and unaffected women better than BCRAT (P &amp;lt; 0.001). In the Nurses’ Health Study, BRISK showed a net benefit over IBIS at the remaining lifetime risk threshold of 20%. The AUCs were 0.647; 95% CI = 0.627, 0.668 for BRISK and 0.571; 95% CI = 0.546, 0.595 for IBIS, a statistically significant improvement for BRISK over IBIS (P &amp;lt; 0.0001). We also looked at sensitivity, specificity, positive predictive value and negative predictive value even though these risk models are one-step removed from breast cancer diagnosis by screening/risk-reduction options. The positive predictive values are higher for the BRISK (27.1%) model compared to BCRAT (5.5%) in the UK Biobank dataset and higher for BRISK (15.4%) compared to IBISv7 (14.0%) in the Nurses’ dataset. We have shown the application of a statistical tool that can be used to directly compare risk models at clinically relevant thresholds. We have shown that BRISK, which comprises polygenic risk and clinical risk factors, shows higher net benefit at both 1.67% and 3% thresholds compared to BCRAT and at 20% remaining lifetime risk for IBIS version 7. In breast cancer risk prediction, a tool with high specificity (and therefore a necessary trade-off for low sensitivity) is preferred because we do not want to incorrectly classify women as not being at high risk and deny them the opportunity for intervention in the form of more frequent screening, alternative modes of screening or risk-reducing medication. This improvement in general population risk stratification that BRISK can provide has the potential to have a clinically significant effect on women’s health. Citation Format: Erika Spaeth, Bernard A Rosner, Gill Dite. Decision curve analysis to compare breast cancer risk predictions for a polygenic integrated clinical risk model with those of a gold standard [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-08-01.

Preferences for a community pharmacy-based pre-exposure prophylaxis (PrEP) delivery program: A discrete choice experiment

BackgroundCommunity pharmacies are ideal venues for pre-exposure prophylaxis (PrEP) delivery. Pharmacists and pharmacy-based PrEP delivery programs have the potential to improve access. ObjectivesThis study elicited preferences for attributes of a hypothetical community pharmacy-based PrEP delivery program among US men who have sex with men (MSM) and assessed predictors of their preferences. MethodsData were collected via a cross-sectional anonymous survey of US MSM, who were aged 18-65 years, not transgender, reported HIV status negative/unknown, and PrEP eligible. A discrete choice experiment was conducted with seven attributes of a pharmacy-based PrEP program: initial PrEP eligibility screening mode, location for human immunodeficiency virus (HIV) tests, timing for HIV test results, PrEP decision-making style, location of PrEP consultations, PrEP medication fill method, and mode for ongoing monitoring. Latent class analysis was performed to analyze preference heterogeneity. Multinomial logistic regression assessed predictors of latent class membership. ResultsThis study included 390 MSM. Time to receive HIV test results was the most important attribute; receiving results on the same day had the highest preference. The next most important attribute was PrEP screening mode; online questionnaires were the most preferred. Respondents’ preferences clustered into four classes: 1) “Same day results and online monitoring” (SDROM) group (63.1%), 2) “Consumerist decision-making” (CDM) group (16.2%), 3) “Self-screening (online questionnaire)” (SOQ) group (11.3%), and 4) “Same day results preferring” (SDRP) group (9.5%). Hispanic MSM (adjusted odds ratio [aOR] =0.31, 95% confidence interval [CI] [0.12-0.84], P = 0.020), MSM of other races (aOR=0.38, 95% CI [0.15-0.97], P = 0.044) vs. White MSM; and those having a sexually transmitted disease recently (aOR=0.37, 95% CI [0.16-0.85], P = 0.018), had lower odds of being in the CDM group vs. the SDROM group. ConclusionsMSM’s preferences for a pharmacy-based PrEP program are heterogeneous. Same day results for HIV tests and online PrEP screening are key components when designing a community pharmacy-based PrEP program.

Autism spectrum disorder detection with kNN imputer and machine learning classifiers via questionnaire mode of screening.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder. ASD cannot be fully cured, but early-stage diagnosis followed by therapies and rehabilitation helps an autistic person to live a quality life. Clinical diagnosis of ASD symptoms via questionnaire and screening tests such as Autism Spectrum Quotient-10 (AQ-10) and Quantitative Check-list for Autism in Toddlers (Q-chat) are expensive, inaccessible, and time-consuming processes. Machine learning (ML) techniques are beneficial to predict ASD easily at the initial stage of diagnosis. The main aim of this work is to classify ASD and typical developed (TD) class data using ML classifiers. In our work, we have used different ASD data sets of all age groups (toddlers, adults, children, and adolescents) to classify ASD and TD cases. We implemented One-Hot encoding to translate categorical data into numerical data during preprocessing. We then used kNN Imputer with MinMaxScaler feature transformation to handle missing values and data normalization. ASD and TD class data is classified using Support vector machine, k-nearest-neighbor (KNN), random forest (RF), and artificial neural network classifiers. RF gives the best performance in terms of the accuracy of 100% with different training and testing data split for all four types of data sets and has no over-fitting issue. We have also examined our results with already published work, including recent methods like Deep Neural Network (DNN) and Convolution Neural Network (CNN). Even using complex architectures like DNN and CNN, our proposed methods provide the best results with low-complexity models. In contrast, existing methods have shown accuracy upto 98% with log-loss upto 15%. Our proposed methodology demonstrates the improved generalization for real-time ASD detection during clinical trials.

Comparing Neurodevelopmental Outcomes in Infants With Patent Ductus Arteriosus Stenting Versus Blalock-Taussig-Thomas Shunt: A Pilot Study

BackgroundPatent ductus arteriosus stenting (PDAS) is a nonsurgical alternative to Blalock-Taussig-Thomas shunt (BTTS) for infants with ductal-dependent congenital heart disease. In this single-center study, we aimed to compare neurodevelopmental outcomes in children who underwent BTTS as initial palliation versus PDAS. MethodsBayley Scales of Infant and Toddler Development Screening Test (Bayley-III) reports and mode of feeding data were collected for any patient who underwent PDAS or BTTS at Rady Children’s Hospital from 2013 to 2021. We also prospectively administered the Parents’ Evaluation of Development Status questionnaire (PEDS) to parents of children aged 2-8 years in this patient population. ResultsOf the 99 patients, 64 received a Bayley-III assessment and/or PEDS screen. Of the 35 who had a Bayley-III, there was a higher proportion of patients with PDAS who scored as developmentally appropriate compared with BTTS. PEDS screen showed that a higher proportion of patients with PDAS had no parental concern for delay than that of patients with BTTS (63% vs 30%). Patients with BTTS were more likely to undergo gastrostomy tube placement than patients with PDAS. ConclusionsOur study suggests that neurodevelopmental measures are feasible, clinically relevant, and should be included in comparative effectiveness studies of infant congenital interventions. Whether PDAS offers neurodevelopmental benefit over BTTS should be confirmed in a prospective powered randomized controlled clinical trial.

Implementing active surveillance for TB: A descriptive survey of healthcare workers in the Eastern Cape, South Africa.

South Africa is a tuberculosis (TB) high-burden country. In the Eastern Cape (EC), community health worker (CHW) teams implement active surveillance for TB to curb spread in disadvantaged communities. However, achieving the goals of the End-TB strategy require coordinated efforts that implement policy and strengthen health systems. This survey described views of healthcare workers (HCWs) in primary care facilities on factors that influence implementation of active surveillance for TB. This survey was conducted across two districts, among healthcare workers working in TB rooms at primary health facilities. A cross-sectional survey of HCW in the EC. The survey included 37 clinics in the OR Tambo Health District (ORTHD) and 44 clinics in the Nelson Mandela Bay Health District (NMBHD). Routine screening at primary care facilities (88.2%) and contact tracing initiatives (80.8%) were the common modes of TB screening. Tuberculosis screening services in the community were only provided by CHWs in 67.3% of instances. Although CHWs were adequately trained and motivated; the lack of transport, limited availability of outreach team leaders (OTLs) and poor security limited implementation of TB screening services in the community. Comparison between both districts revealed TB screening was limited by lack of transport in the rural district and poor security in the urban context. Community engagement provided a platform for improving acceptability. Community-based TB screening was limited. Inadequate coordination of services between stakeholders in the community has limited reach. Further research should describe that coordinating resource allocation and community empowerment could improve the implementation of active surveillance for TB.Contribution:This study highlights the views of TB room HCWs who believe the opportunity for community-level TB screening is improved with effective leadership and community engagement for acceptability of these services.

Malnutrition prevalence according to GLIM and its feasibility in geriatric patients: a prospective cross-sectional study.

In 2019, the Global Leadership Initiative on Malnutrition (GLIM) suggested a 2-step diagnostic format for malnutrition including screening and diagnosis. Prospective validation and feasibility studies, using the complete set of the five GLIM criteria, are needed. The aims of this study were to determine the prevalence of malnutrition, and investigate how the prevalence varied with mode of screening. Furthermore, we assessed the feasibility of GLIM in geriatric patients. Consecutive patients from two acute geriatric wards were included. For screening risk of malnutrition, the Mini Nutritional Assessment-Short Form (MNA-SF) or Malnutrition Screening Tool (MST) were used. In accordance with GLIM, a combination of phenotypic and etiologic criteria were required for the diagnosis of malnutrition. Feasibility was determined based on % data completeness, and above 80% completeness was considered feasible. One hundred patients (mean age 82years, 58% women) were included. After screening with MNA-SF malnutrition was confirmed by GLIM in 51%, as compared with 35% after screening with MST (p = 0.039). Corresponding prevalence was 58% with no prior screening. Using hand grip strength as a supportive measure for reduced muscle mass, 69% of the patients were malnourished. Feasibility varied between 70 and 100% for the different GLIM criteria, with calf circumference as a proxy for reduced muscle mass having the lowest feasibility. In acute geriatric patients, the prevalence of malnutrition according to GLIM varied depending on the screening tool used. In this setting, GLIM appears feasible, besides for the criterion of reduced muscle mass.

Acceptance of Medical Artificial Intelligence in Skin Cancer Screening: Choice-Based Conjoint Survey.

There is great interest in using artificial intelligence (AI) to screen for skin cancer. This is fueled by a rising incidence of skin cancer and an increasing scarcity of trained dermatologists. AI systems capable of identifying melanoma could save lives, enable immediate access to screenings, and reduce unnecessary care and health care costs. While such AI-based systems are useful from a public health perspective, past research has shown that individual patients are very hesitant about being examined by an AI system. The aim of this study was two-fold: (1) to determine the relative importance of the provider (in-person physician, physician via teledermatology, AI, personalized AI), costs of screening (free, 10€, 25€, 40€; 1€=US $1.09), and waiting time (immediate, 1 day, 1 week, 4 weeks) as attributes contributing to patients' choices of a particular mode of skin cancer screening; and (2) to investigate whether sociodemographic characteristics, especially age, were systematically related to participants' individual choices. A choice-based conjoint analysis was used to examine the acceptance of medical AI for a skin cancer screening from the patient's perspective. Participants responded to 12 choice sets, each containing three screening variants, where each variant was described through the attributes of provider, costs, and waiting time. Furthermore, the impacts of sociodemographic characteristics (age, gender, income, job status, and educational background) on the choices were assessed. Among the 383 clicks on the survey link, a total of 126 (32.9%) respondents completed the online survey. The conjoint analysis showed that the three attributes had more or less equal importance in contributing to the participants' choices, with provider being the most important attribute. Inspecting the individual part-worths of conjoint attributes showed that treatment by a physician was the most preferred modality, followed by electronic consultation with a physician and personalized AI; the lowest scores were found for the three AI levels. Concerning the relationship between sociodemographic characteristics and relative importance, only age showed a significant positive association to the importance of the attribute provider (r=0.21, P=.02), in which younger participants put less importance on the provider than older participants. All other correlations were not significant. This study adds to the growing body of research using choice-based experiments to investigate the acceptance of AI in health contexts. Future studies are needed to explore the reasons why AI is accepted or rejected and whether sociodemographic characteristics are associated with this decision.

Application Analysis of AI Technology Combined with Spiral CT Scanning in Early Lung Cancer Screening

At present, the incidence and fatality rate of lung cancer in China rank first among all malignant tumors. Despite the continuous development and improvement of China's medical level, the overall 5-year survival rate of lung cancer patients is still lower than 20% and is staged. A number of studies have confirmed that early diagnosis and treatment of early stage lung cancer is of great significance to improve the prognosis of patients. In recent years, artificial intelligence technology has gradually begun to be applied in oncology. ai is used in cancer screening, clinical diagnosis, radiation therapy (image acquisition, at-risk organ segmentation, image calibration and delivery) and other aspects of rapid development. However, whether medical ai can be socialized depends on the public's attitude and acceptance to a certain extent. However, at present, there are few studies on the diagnosis of early lung cancer by AI technology combined with SCT scanning. In view of this, this study applied the combined method in early lung cancer screening, aiming to find a safe and efficient screening mode and provide a reference for clinical diagnosis and treatment.

Assessment of Knowledge, Attitude and Practices among Healthcare Professionals Regarding Hepatitis B Infection and Vaccination in a Tertiary Care Hospital

Background: Hepatitis B infection is an occupational risk for Healthcare workers (HCWs).[3] They have a greaterrisk of acquiring HBV infection due to exposure to blood or bodily fluids. Compared to the general population, therisk is four times higher for this group of professionals. The present study was carried out to know the vaccinationstatus of Hepatitis B; assess knowledge and attitude towards Hepatitis B vaccination; and to assess the awarenessabout Hepatitis B infection among health care professionals.Methods and Materials: A cross sectional study was conducted in the MY Hospital, Indore for a period of 6months after getting approval from institutional ethics committee. The sample size of 210 healthcare professionalswas selected using simple random sampling technique. The data was collected by using a pre-designed, validatedsemi-structured questionnaire. Data collected through the questionnaires were coded, entered into a database andanalysed using a statistical software SPSS version 25(trial version).Results: 63.81% of HCWs knew about HBV infection. 43.81% were aware about its spread through saliva. 77.36%doctors, 74.78% nurses and 80.95% of the other health care workers never used PPE while handling blood andbody fluids. All the doctors, 54.78% nurses and 21.43 of others knew about the HBV vaccine (p-value&lt;0.00001).88.68% doctors and 41.27% nurses and only 33.33% of the other staff knew that there were three doses of HBVvaccine. Majority of the doctors (83.02%) and nurses (53.04%) had received HBV vaccine, while 69.05% of otherhealth care workers did not receive any dose of HBV vaccine.Conclusion: The study shows that complete knowledge regarding the hepatitis B infection, its mode of transmission,preventive measures and screening is still lacking among the health care workers. Although doctors seem to be themost knowledgeable, there is a need to improve the knowledge and practices among the other workers as well.

Photo-addressable microwell devices for rapid functional screening and isolation of pathogen inhibitors from bacterial strain libraries.

Discovery of new strains of bacteria that inhibit pathogen growth can facilitate improvements in biocontrol and probiotic strategies. Traditional, plate-based co-culture approaches that probe microbial interactions can impede this discovery as these methods are inherently low-throughput, labor-intensive, and qualitative. We report a second-generation, photo-addressable microwell device, developed to iteratively screen interactions between candidate biocontrol agents existing in bacterial strain libraries and pathogens under increasing pathogen pressure. Microwells (0.6 pl volume) provide unique co-culture sites between library strains and pathogens at controlled cellular ratios. During sequential screening iterations, library strains are challenged against increasing numbers of pathogens to quantitatively identify microwells containing strains inhibiting the highest numbers of pathogens. Ring-patterned 365 nm light is then used to ablate a photodegradable hydrogel membrane and sequentially release inhibitory strains from the device for recovery. Pathogen inhibition with each recovered strain is validated, followed by whole genome sequencing. To demonstrate the rapid nature of this approach, the device was used to screen a 293-membered biovar 1 agrobacterial strain library for strains inhibitory to the plant pathogen Agrobacterium tumefaciens sp. 15955. One iterative screen revealed nine new inhibitory strains. For comparison, plate-based methods did not uncover any inhibitory strains from the library (n = 30 plates). The novel pathogen-challenge screening mode developed here enables rapid selection and recovery of strains that effectively suppress pathogen growth from bacterial strain libraries, expanding this microwell technology platform toward rapid, cost-effective, and scalable screening for probiotics, biocontrol agents, and inhibitory molecules that can protect against known or emerging pathogens.