Screening Methodology Research Articles

Iterative screening methodology for optimal modeling of bubble coalescence/breakup and interphase force in CMFD simulation of flow boiling

The Euler–Euler two fluid approach has been widely adopted in computational multi-fluid dynamic (CMFD) simulation of nucleate boiling flow. Accurate prediction of bubble size and interphase forces are desired to properly model interphase momentum transfer in the CMFD simulation. Bubble dynamics, including nucleation, coalescence/breakup and condensation, should be modeled to calculate bubble size variation. In the meantime, modeling of interphase forces is crucial to predict distribution of void fraction. Numerous closure models have been developed for bubble dynamics and interphase forces. Diverse model combinations were reported depending on the specific application. As a step forward to converge the diversity, efforts are dedicated to establish a methodology to iteratively screen the closure models for nucleate flow boiling at elevated pressures based on the DEBORA experiment. In the proposed methodology, the closure models for each physics are first evaluated and sorted based on the predicted value in fixed-point analysis and its effect on CMFD results observed in separate-effect analysis. The second part of the methodology is iterative screening. To achieve accurate bubble size prediction, the optimal coalescence model is identified for each breakup model. With the optimal coalescence counterpart, the optimal breakup model is then identified. For the interphase force models, the optimal lift force model is first determined based on the CMFD simulation with the same drag force model and without wall lubrication force model. The optimal wall lubrication force and drag force model are selected in sequence. Utilized one single case of DEBORA experiments, the optimal set of the coalescence/breakup models, i.e., Prince et al.’s and Luo et al.’s models, and the interphase models, i.e., Tomiyama et al.’s models for drag and lift force, Lubchenko et al.’s model for wall lubrication force and Burns et al.’s model for turbulence dispersion force has been selected. Validation of the model combination based on more DEBORA experiment datasets and Bartolomei et al.’s experiment shows promising prediction accuracy.

Chemometrics-based Discrimination of Virgin and Recycled Acrylonitrile-Butadiene-Styrene Plastics Toys via Non-targeted Screening of Volatile Substances

Owing to the growing emphasis on child safety, it is greatly urgent to identify and assess the unknown compounds and discriminate the recycled materials for plastic toys. In this study, gas chromatography mass spectrometry coupled with static headspace has been optimized by response surface methodology for non-targeted screening of unknown volatiles in acrylonitrile-butadiene-styrene (ABS) plastic toys. Optimum conditions for static headspace were 120 °C for extraction temperature and 48 min for extraction time. A total of 83 volatiles in 11 categories were qualitatively identified by matching the NIST database library, retention index and standard materials. Considering high positive rate and potential toxicity, high-risk volatiles in ABS plastic toys were listed and traced for safety pre-warning. Moreover, the differential volatiles between virgin and recycled ABS plastics were screened out by orthogonal partial least-squares discrimination analysis. Principal component analysis, hierarchical cluster analysis and linear discrimination analysis were employed to successfully discriminate recycled ABS plastic toys based on the differential volatiles. The proposed strategy represents an effective and promising analytical method for non-targeted screening and risk assessment of unknown volatiles and discrimination of recycled materials combining with various chemometric techniques for children's plastic products to safeguard children's health.

Ex Vivo Evaluation of Combination Immunotherapy Using Tumor-Microenvironment-on-Chip.

Combination immunotherapy has emerged as a promising strategy to address the challenges associated with immune checkpoint inhibitor (ICI) therapy in breast cancer. The efficacy of combination immunotherapy hinges upon the intricate and dynamic nature of the tumor microenvironment (TME), characterized by cellular heterogeneity and molecular gradients. However, current methodologies for drug screening often fail to accurately replicate these complex conditions, resulting in limited predictive capacity for treatment outcomes. Here, a tumor-microenvironment-on-chip(TMoC), integrating a circulation system and ex vivo tissue culture with physiological oxygen and nutrient gradients, is described. This platform enables spatial infiltration of cytotoxic CD8+ T cells and their targeted attack on the tumor, while preserving the high complexity and heterogeneity of the TME. The TMoC is employed to assess the synergistic effect of five targeted therapy drugs and five chemotherapy drugs in combination with immunotherapy, demonstrating strong concordance between chip and animal model responses. The TMoC holds significant potential for advancing drug development and guiding clinical decision-making, as it offers valuable insights into the complex dynamics of the TME.

Higher education audiometric research: HEAR—Onsite Assessment of Conservatoire Students

Through analysis of the ISO 1999 dataset it was found that half of noise induced hearing damage occurs in the first three years of adult life. As a result the Higher Education Audiometric Research project was founded in the UK with the ambition of minimizing this damage through educational awareness and on-site testing and assessment. In the UK, 50% of this age group are in higher education. Through the newly established UK Hearing Conversation Association awareness was raised through the “Love Sound – Listen with Care” campaign. Using long-term links with the Royal Academy of Music two on-site hearing screening methodologies were compared in a pilot study involving 23 students. The obvious advantage of onsite testing and assessment being convenience. The two methodologies were audiometry using Kudawave Prime based on active noise canceling headphones, and otoacoustic emissions using Hearing Coach software and Path Medical instrumentation. Presented are the results in terms of consistency, test-retest, and ease of use/practical application.

Electronic structure, theoretical power conversion efficiency, and thermoelectric properties of bismuth-based alkaline earth antiperovskites.

This research paper investigates the properties and potential applications of antiperovskite materials. Antiperovskites are a class of materials with a unique crystal structure, where the central atom is surrounded by a cage of anions. We review recent research on antiperovskite-based materials for energy storage, photovoltaics, catalysis, and sensors. We discovered that these materials display direct band gap semiconductors, strong absorption in the visible (VIS), ultra-violet (UV), and near infrared regions (NIR) based on their fundamental features, which is the most admirable quality that may be found in many optoelectronic devices. Both mechanical and thermodynamic stability have been confirmed for these materials. We discovered that these materials exhibit high figures of merit through the calculation of transport properties, which makes them a promising candidate for thermoelectric devices. It is anticipated that the proposed material BiPMg3, which has a theoretical efficiency of 11.5%, will make a suitable photovoltaic absorber. This paper highlights the potential of these materials for future technological advancements. Herein, we have used most authentic techniques to compute fundamental physical properties of these antiperovskites. Full-potential linear augmented plane wave (FP-LAPW) method has been used to investigate electronic, magnetic, optical properties, and make antiperovskites attractive for a variety of applications. In light of its implementation, we have checked the theoretical power conversion efficiency by first principles spectroscopic screening methodology, and inspect the fundamental physical parameters of antiperovskites, focusing on their potential as functional materials for energy and information technologies.

Department of Biotechnology, Himachal Pradesh University, Shimla, Himachal Pradesh 171005, India

The present study utilized computational-guided experiments to conduct screening of a novel discovered acidic-thermostable α-amylase (AMYT) derived from a metagenome of hot springs. This approach was employed as a cost-effective alternative to the conventional method of functional screening. Initially, a computational screening methodology was employed to identify primary candidate that possess superior properties. AMYT was subjected to cloning, expression, purification, and characterization, among the candidates that were chosen. The AMYT enzyme demonstrated optimal activity at pH of 5.5 and a temperature of 50 °C. The enzyme demonstrated high efficacy in the presence of diverse chemicals, demonstrating a remarkable capacity in the hydrolysis of a wide range of substrates. Furthermore, it was found to be independent of Ca2+ ions. The results of this study demonstrated the efficacy of computational methods in identifying previously unknown acidic thermostable α-amylases. The accuracy of the selection method suggests that the AMYT has the potential to be a viable option for industrial starch processing, as it has the ability to enhance the output of final products and decrease overall costs.

B-109 Outcome of a Large Multicenter Prospective Clinical Study Aimed at Validating a Newly Developed VlsE1/pepC10 IgG/IgM Chemiluminescent Immunoassay (CLIA) in Conjunction with a New Automated Analyzer

Abstract Background Lyme borreliosis is the fastest growing vector-borne illness in North America, with recent estimates as high as 476 000 new cases annually in the U.S. alone. Measurement of Borrelia-specific antibodies via serologic testing remains an important diagnostic aid. Since 1994, serologic testing for Lyme disease in the United States has consisted of a two-stage algorithm, termed standard two-tiered testing (STTT). In the STTT algorithm, specimens equivocal/positive by first tier screening methodologies are subsequently tested via western blots. In recent years, the FDA has cleared several alternatives for replacing western blots with more sensitive second-tier tests, termed modified two-tiered testing (MTTT). We recently developed a VlsE1/pepC10 IgG/IgM chemiluminescent immunoassay (CLIA), to be used in conjunction with a new automated analyzer. The goal of these studies was to conduct a multi-site validation for this new assay and analyzer as a first-tier screening test within an STTT algorithm. Methods Retrospective cohort: 280 clinically characterized samples were provided from the U.S. Centers for Disease Control and Prevention (90 cases, 190 controls). The CDC provided VlsE1/pepC10 IgG/IgM ELISA data derived from their own testing. VlsE1/pepC10 IgG/IgM CLIA and western blotting data were also generated for this panel at ZEUS Scientific. Sensitivity and specificity values were calculated for the retrospective cohort as follows:VlsE1/pepC10-CLIA vs existing VlsE1/pepC10 IgG/IgM-ELISA, and VlsE1/pepC10-CLIA + Western blots, vs VlsE1/pepC10 IgG/IgM-ELISA + Western blots, interpreted as STTT algorithms. All testing of the retrospective cohort was performed at ZEUS Scientific. Prospective Cohort: 600 routine Lyme serology specimens were prospectively collected at three locations (1800 total): Mayo Clinic (MOC), Rochester MN.; Marshfield Clinic (MC), Stevens Point, WI; Health Network Laboratories (HNL), Allentown PA. The samples were assayed and analyzed in the same combinations as described above for the retrospective cohort; however, instead of sensitivity and specificity, the results were reported as positive percent agreement (PPA) and negative percent agreement (NPA) since the prospective samples were not clinically characterized. Testing of the prospective cohort was evenly split across three different laboratories, one of which was ZEUS Scientific. Results Retrospective cohort: [VlsE1/pepC10 CLIA, Sensitivity = (77/90) = 85.56%, Specificity = (177/190) = 93.16%; VlsE1/pepC10 ELISA, Sensitivity = (80/90) = 88.89%, Specificity = (179/190) = 94.21%], [STTT-VlsE1/pepC10-CLIA + Western blots, Sensitivity = (72/90) = 80.00%, Specificity = (190/190) = 100.00%; STTT-VlsE1/pepC10-ELISA + Western blots, Sensitivity = (70/90) = 77.78%, Specificity = (190/190) = 100.00%]. Prospective Cohort (1 sample out of the 1800 collected was omitted due to an invalid western blot result):[VlsE1/pepC10-CLIA vs VlsE1/pepC10-ELISA, PPA = (196/235) = 86.51%, NPA = (1452/1564) = 92.84%; STTT-VlsE1/pepC10-ELISA vs STTT-VlsE1/pepC10-ELISA, PPA = (160/167) = 95.81%, NPA = (1607/11 632) = 98.47%]. Conclusion These studies demonstrate that the newly developed VlsE1/pepC10 IgG/IgM CLIA, in conjunction with a new automated analyzer, yielded accurate results as a first-tier screening assay for both the retrospective and prospective multi-site validation cohorts. Future studies, utilizing the same sample cohorts, will be aimed at validating additional second tier CLIA tests as part of an MTTT algorithm.

Identifying β-secretase 1 (BACE1) inhibitors from plant-based compounds: an approach targeting Alzheimer's therapeutics employing molecular docking and dynamics simulation.

β-secretase 1 (BACE1) is an enzyme that is involved in generating beta-amyloid peptides and is believed to have a significant role in the development of Alzheimer's disease (AD). Therefore, BACE1 has gained attention as a potential therapeutic target for treating AD. Modern drug discovery studies are being conducted to identify potential inhibitors of BACE1, with the goal of reducing the production of beta-amyloid peptides and, thus, slowing the progression of AD. Here, we used a multistep virtual screening methodology to identify phytoconstituents from the IMPPAT library that could inhibit the activity of BACE1. Molecular docking was employed to select initial hits based on their binding affinity toward BACE1. Screening for PAINS patterns, ADMET and PASS properties, was then used to identify potential molecules for BACE1 inhibition. In the end, we discovered two natural compounds, Peiminine and 27-Deoxywithaferin A, which demonstrated a strong affinity, effectiveness, and specific interactions for the BACE1-active site. The elucidated molecules also displayed drug likeliness. A 200ns molecular dynamics (MD) simulation was conducted to investigate the interaction mechanism, complex stability, and conformational dynamics of BACE1 with Peiminine and 27-Deoxywithaferin A. The MD simulations demonstrated that BACE1 was stable during the simulation with Peiminine and 27-Deoxywithaferin A. Overall, the results suggested that Peiminine and 27-Deoxywithaferin A hold significant potential as scaffolds in drug development efforts targeting BACE1 for the purpose of treating AD.

The Challenge of Plastic Management for Waste Electrical and Electric Equipment Recycling in the Global South: A Case Comparison between Europe and Latin America

Countries with emerging legislation on the waste electrical and electric equipment (WEEE), but limited infrastructure, may find in other, more robust, systems the tools to develop adaptable and socioeconomically viable management schemes. Additives found in the plastics in electronic goods, such as brominated flame retardants (BFRs), are components of a safety system, but introduce characteristics that result in their waste being hazardous. Established and emerging regulatory systems need to implement legislation that impacts the management of WEEE, to reduce risks to human health and the environment, while maximising opportunities for resource recovery from widely varying materials. To assess the context of developed and emerging regulatory systems, a baseline study was undertaken of WEEE plastics in Scotland and Uruguay. For the identification of BFRs in plastics, an internationally validated screening methodology using X-ray fluorescence was adopted at different processing operations. It was observed that, using a threshold of 830 mg/kg for Br as a BFR tracer, in Scotland, more than 70% of the plastics would be recyclable, while, in Uruguay, that fraction dropped to 50%. These results, and the wider literature discussion, highlight the impact that regulatory frameworks have on the quality and recyclability of recovered material. We identify future actions to be considered by policy-makers for a more sustainable regulatory approach.

Mobile Electrocardiograms in the Detection of Subclinical Atrial Fibrillation in High-Risk Outpatient Populations: Protocol for an Observational Study.

Single-lead, smartphone-based mobile electrocardiograms (ECGs) have the potential to provide a noninvasive, rapid, and cost-effective means of screening for atrial fibrillation (AFib) in outpatient settings. AFib has been associated with various comorbid diseases that prompt further investigation and screening methodologies for at-risk populations. A simple 30-second sinus rhythm strip from the KardiaMobile ECG (AliveCor) can provide an effective screen for cardiac rhythm abnormalities. The aim of this study is to demonstrate the feasibility of performing Kardia-enabled ECG recordings routinely in outpatient settings in high-risk populations and its potential use in uncovering previous undiagnosed cases of AFib. Specific aim 1 is to determine the feasibility and accuracy of performing routine cardiac rhythm sampling in patients deemed at high risk for AFib. Specific aim 2 is to determine whether routine rhythm sampling in outpatient clinics with high-risk patients can be used cost-effectively in an outpatient clinic without increasing the time it takes for the patient to be seen by a physician. Participants were recruited across 6 clinic sites across the University of Florida Health Network: University of Florida Health Nephrology, Sleep Center, Ophthalmology, Urology, Neurology, and Pre-Surgical. Participants, aged 18-99 years, who agreed to partake in the study were given a consent form and completed a questionnaire regarding their past medical history and risk factors for cardiovascular disease. Single-lead, 30-second ECGs were taken by the KardiaMobile ECG device. If patients are found to have newly diagnosed AFib, the attending physician is notified, and a 12-lead ECG or standard ECG equivalent will be ordered. As of March 1, 2024, a total of 2339 participants have been enrolled. Of the data collected thus far, the KardiaMobile rhythm strip reported 381 abnormal readings, which are pending analysis from a cardiologist. A total of 78 readings were labeled as possible AFib, 159 readings were labeled unclassified, and 49 were unreadable. Of note, the average age of participants was 61 (SD 10.25) years, and the average self-reported weight was 194 (SD 14.26) pounds. Additionally, 1572 (67.25%) participants report not regularly seeing a cardiologist. Regarding feasibility, the average length of enrolling a patient into the study was 3:30 (SD 0.5) minutes after informed consent was completed, and medical staff across clinic sites (n=25) reported 9 of 10 level of satisfaction with the impact of the screening on clinic flow. Preliminary data show promise regarding the feasibility of using KardiaMobile ECGs for the screening of AFib and prevention of cardiological disease in vulnerable outpatient populations. The use of a single-lead mobile ECG strip can serve as a low-cost, effective AFib screen for implementation across free clinics attempting to provide increased health care accessibility. DERR1-10.2196/52647.

A tool for the cheap and rapid screening of SARS-CoV-2 variants of concern (VoCs) by Sanger sequencing.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an emerging virus that, since March 2020, has been responsible for a global and ongoing pandemic. Its rapid spread over the past nearly 3 years has caused novel variants to arise. To monitor the circulation and emergence of SARS-CoV-2 variants, surveillance systems based on nucleotide mutations are required. In this regard, we searched in the spike, ORF8, and nucleocapsid genes to detect variable sites among SARS-CoV-2 variants. We describe polymorphic genetic regions that enable us to differentiate between the Alpha, Beta, Gamma, Delta, and Omicron variants of concern (VoCs). We found 21 relevant mutations, 13 of which are unique for Omicron lineages BA.1/BA.1.1, BA.2, BA.3, BA.4, and BA.5. This genetic profile enables the discrimination between VoCs using only four reverse transcription PCR fragments and Sanger sequencing, offering a cheaper and faster alternative to whole-genome sequencing for SARS-CoV-2 surveillance. IMPORTANCE Our work describes a new (Sanger sequencing-based) screening methodology for SARS-CoV-2, performing PCR amplifications of a few target regions to detect diagnostic mutations between virus variants. Using the methodology developed in this work, we were able to discriminate between the following VoCs: Alpha, Beta, Gamma, Delta, and Omicron (BA.1/BA.1.1, BA.2, BA.3, BA.4, and BA.5). This becomes important, especially in low-income countries where current methodologies like next-generation sequencing have prohibitive costs. Furthermore, rapid detection would allow sanitary authorities to take rapid measures to limit the spread of the virus and therefore reduce the probability of new virus dispersion. With this methodological approach, 13 previously unreported diagnostic mutations among several Omicron lineages were found.

Identification and optimization of TDP1 inhibitors from anthraquinone and chalcone derivatives: consensus scoring virtual screening and molecular simulations

Virtual screening aims to identify and rank compounds with drug/lead-like properties based on their affinity for the protein target. We developed a methodology that integrates structure- and ligand-based screening approaches to enhance hit rates against the TDP1 protein within a database of anthraquinone and chalcone derivatives, followed by evaluation of prioritized compounds through molecular simulations. This technique is particularly useful for training set imbalances. Four screening methods were used: QSAR, pharmacophore, shape similarity, and docking. Each method was individually trained to score compounds, and the scores were fused to create parallel Z-score fusion. The QSAR models exhibited satisfactory R2 values (0.84 to 0.75), whereas the pharmacophoric and shape similarity models demonstrated excellent performance (ROC:0.82–0.88). Docking enrichment analysis identified 6N0D as the optimal TDP1 crystal structure (ROC = 0.73). Remarkably, the consensus scoring method surpassed other screening methods, achieving the highest ROC value of 0.98. Docking screening prioritized compounds with binding modes resembling the co-crystallized ligands, whereas MMGBSA, consensus, and docking produced dynamic simulations that were as stable as the co-crystallized ligands. Additionally, the QSAR-selected compounds exhibited binding modes similar to those of commercially available TDP1 inhibitors. In this study, a strong correlation was found between the inhibitory concentrations and binding energy values of commercialized TDP1 inhibitors, indicating that the top-ranked compounds are expected to have potent inhibitory effects in the nano-/micromolar range. The results of this study establish that consensus scoring can be used as an adaptable mainstay virtual screening methodology, pending subsequent experimental validation for affirmation. Communicated by Ramaswamy H. Sarma

Screening of atrial fibrillation in dental practices: a qualitative feasibility study

ABSTRACT Objectives To increase the detection of unknown atrial fibrillation (AF), general practitioners have started screening their patients using small hand-held devices. It is thought that dental settings could be utilized for screening as they have regular access to patients. The aim of this study was to explore the perceptions of dental staff of screening for AF using a hand-held electronic device in primary dental care. Methods The research took place in one large mixed NHS and private general dental practice. Views from staff including dentists, dental therapists, dental nurses, and managers were elicited via semi-structured interviews conducted face-to-face, audio recorded, and transcribed verbatim. Interviews continued until there were no new themes or patterns emerging from the data, and thematic saturation had been achieved. Results Eleven participants were interviewed. The main themes generated were methodology for screening, acceptability for screening within the practice, attitudes to screening, and implementation of screening. Overall, participants were positive about implementing AF screening in a dental practice but expressed concerns about time and remuneration. Staff also gave encouraging feedback regarding the simplicity of the portable screening device. Conclusions Participants felt that AF screening in primary care dental practices was a good concept but may be challenging to implement in NHS Dentistry, especially due to the pandemic.

A high-throughput screening platform for enzymes active on mucin-type O-glycoproteins.

Mucin-type O-glycosylation is a post-translational modification present at the interface between cells where it has important roles in cellular communication. However, deciphering the function of O-glycoproteins and O-glycans can be challenging, especially as few enzymes are available for their assembly or selective degradation. Here, to address this deficiency, we developed a genetically encoded screening methodology for the discovery and engineering of the diverse classes of enzymes that act on O-glycoproteins. The method uses Escherichia coli that have been engineered to produce an O-glycosylated fluorescence resonance energy transfer probe that can be used to screen for O-glycopeptidase activity. Subsequent cleavage of the substrate by O-glycopeptidases provides a read-out of the glycosylation state of the probe, allowing the method to also be used to assay glycosidases and glycosyltransferases. We further show the potential of this methodology in the first ultrahigh-throughput-directed evolution of an O-glycopeptidase.

A new perspective on predicting the reaction rate constants of hydrated electrons for organic contaminants: Exploring molecular structure characterization methods and ambient conditions

Hydrated electrons (eaq−) exhibit rapid degradation of diverse persistent organic contaminants (OCs) and hold great promise as a formidable reducing agent in water treatment. However, the diverse structures of compounds exert different influences on the second-order rate constant of hydrated electron reactions (keaq−), while the same OCs demonstrate notable discrepancies in keaq− values across different pH levels. This study aims to develop machine learning (ML) models that can effectively simulate the intricate reaction kinetics between eaq− and OCs. Furthermore, the introduction of the pH variable enables a comprehensive investigation into the impact of ambient conditions on this process, thereby improving the practicality of the model. A dataset encompassing 701 keaq− values derived from 351 peer-reviewed publications was compiled. To comprehensively investigate compound properties, this study introduced molecular descriptor (MD), molecular fingerprint (MF), and the integration of both (MD + MF) as model variables. Furthermore, 60 sets of predictive models were established utilizing two variable screening methodologies (MLR and RF) and ten prominent algorithms. Through statistical parameter analysis, it was determined that descriptors combined with MD and MF, the RF screening method, and the symbolism algorithm exhibited the best predictive efficacy. Importantly, the combination of descriptor models exhibited significantly superior performance compared to individual MF and MD models. Notably, the optimal model, denoted as RF - (MF + MD) - LGB, exhibited highly satisfactory predictive results (R2tra = 0.967, Q2tra = 0.840, R2ext = 0.761). The mechanistic explanation study based on Shapley Additive Explanations (SHAP) values further elucidated the crucial influences of polarity, pH, molecular weight, electronegativity, carbon–carbon double bonds, and molecular topology on the degradation of OCs by eaq−. The proposed modeling approach, particularly the integration of MF and MD, alongside the introduction of pH, may furnish innovative ideas for advanced reduction or oxidation processes (ARPs/AOPs) and machine learning applications in other domains.

Comparing the performance of full-field digital mammography and digital breast tomosynthesis in the post-treatment surveillance of patients with a history of breast cancer: A retrospective study

IntroductionThe purpose of our study was to compare the performance of 2D (FFDM) against 3D (FFDM plus DBT) examinations in the post-treatment surveillance of asymptomatic breast cancer survivors. MethodsA list of women with a history of breast cancer who underwent screening mammography (2D or 3D) from 5/2017 to 5/2020 was retrieved. A total of 20,210 examinations were identified and performance metrics were compared. ResultsThere were no statistically significant difference in cancer detection rate (CDR) (p = 0.38), recall rate (RR) (p = 0.087), or positive predictive value (PPV) (p = 0.74) between 2D vs. 3D examinations. Stratification by breast tissue identified no statistically significant difference in CDR (p = 0.581 and p = 0.428), RR (p = 0.230 and p = 0.205), or PPV (p = 0.908 and p = 0.721) between fatty/scattered and heterogeneous/extremely dense breast tissue when comparing 2D vs 3D examinations. Stratification by age did not identify a significant difference in RR or PPV between the two groups. CDR was statistically increased with 2D vs. 3D examinations in the 60–69 years group (p = 0.021). Stratification by race did not identify a significant difference in RR or PPV between the two groups. CDR was statistically increased with 3D vs. 2D examinations in white women (p = 0.036). Stratification by laterality (bilateral vs. unilateral post mastectomy) did not identify a significant difference in RR or PPV between the two groups. CDR was statistically increased in 2D vs. 3D examinations in unilateral studies (p = 0.009). ConclusionFor asymptomatic women with a history of breast cancer, there is no evidence that the addition of DBT to FFDM improves CDR, RR, or PPV. Implications for practiceMore studies are needed concerning screening methodologies supplementing FFDM in the screening regimens of breast cancer survivors.

Proteomics-Driven Biomarkers in Pancreatic Cancer.

Pancreatic cancer is a devastating disease that has a grim prognosis, highlighting the need for improved screening, diagnosis, and treatment strategies. Currently, the sole biomarker for pancreatic ductal adenocarcinoma (PDAC) authorized by the U.S. Food and Drug Administration is CA 19-9, which proves to be the most beneficial in tracking treatment response rather than in early detection. In recent years, proteomics has emerged as a powerful tool for advancing our understanding of pancreatic cancer biology and identifying potential biomarkers and therapeutic targets. This review aims to offer a comprehensive survey of proteomics' current status in pancreatic cancer research, specifically accentuating its applications and its potential to drastically enhance screening, diagnosis, and treatment response. With respect to screening and diagnostic precision, proteomics carries the capacity to augment the sensitivity and specificity of extant screening and diagnostic methodologies. Nonetheless, more research is imperative for validating potential biomarkers and establishing standard procedures for sample preparation and data analysis. Furthermore, proteomics presents opportunities for unveiling new biomarkers and therapeutic targets, as well as fostering the development of personalized treatment strategies based on protein expression patterns associated with treatment response. In conclusion, proteomics holds great promise for advancing our understanding of pancreatic cancer biology and improving patient outcomes. It is essential to maintain momentum in investment and innovation in this arena to unearth more groundbreaking discoveries and transmute them into practical diagnostic and therapeutic strategies in the clinical context.

Dietary phenolics and their microbial metabolites are poor inhibitors of trimethylamine oxidation to trimethylamine N-oxide by hepatic flavin monooxygenase 3

High circulating levels of trimethylamine N-oxide (TMAO) have been associated with cardiovascular disease risk. TMAO is formed through a microbiome-host pathway utilizing primarily dietary choline as a substrate. Specific gut microbiota transform choline into trimethylamine (TMA), and, when absorbed, host hepatic flavin-containing monooxygenase 3 (FMO3) oxidizes TMA into TMAO. Chlorogenic acid and its metabolites reduce microbial TMA production in vitro. However, little is known regarding the potential for chlorogenic acid and its bioavailable metabolites to inhibit the last step: hepatic conversion of TMA to TMAO. We developed a screening methodology to study FMO3-catalyzed production of TMAO from TMA. HepG2 cells were unable to oxidize TMA into TMAO due to their lack of FMO3 expression. Although Hepa-1 cells did express FMO3 when pretreated with TMA and NADPH, they lacked enzymatic activity to produce TMAO. Rat hepatic microsomes contained active FMO3. Optimal reaction conditions were: 50 µM TMA, 0.2 mM NADPH, and 33 µL microsomes/mL reaction. Methimazole (a known FMO3 competitive substrate) at 200 µM effectively reduced FMO3-catalyzed conversion of TMA to TMAO. However, bioavailable chlorogenic acid metabolites did not generally inhibit FMO3 at physiological (1 µM) nor supra-physiological (50 µM) doses. Thus, the effects of chlorogenic acid in regulating TMAO levels in vivo are unlikely to occur through direct FMO3 enzyme inhibition. Potential effects on FMO3 expression remain unknown. Intestinal inhibition of TMA production and/or absorption are thus likely their primary mechanisms of action.

SDPS-08 OSSEOUS METASTASES IN H3G34-MUTANT DIFFUSE HEMISPHERIC GLIOMAS

Abstract Subset of patients with H3G34 gliomas may present with extra-CNS metastasis further complicating both diagnosis and treatment. We describe a case of a 19-year-old female presenting initially with focal motor seizure in right leg along with leg pain. MRI of the leg showed an ill-defined right distal femur expansile osteolytic lesion with central fluid signal, thick rim enhancement, endosteal scalloping, cortical invasion, and smooth enhancing periosteal reaction/soft tissue extension associated with surrounding enhancing marrow signal abnormality worrisome for lesion extension. Contrast brain MRI exhibited multiple frontal and partial lobe T2 FLAIR hyperintense lesions. The largest lesion demonstrated contrast enhancement, internal foci of restricted diffusion, and a focus of intratumoral hemorrhage. A whole-body PET/CT showed intensely FDG-avid lytic lesion in the right distal femur, with FDG activity along the biopsy tract. Hypermetabolic lytic metastases to the right femoral head and mid-sacral body were also observed. A craniotomy with brain lesion biopsy two months later indicated preliminary histopathology of malignant small round blue cell neoplasm. A biopsy from the distal right femur was non-diagnostic of malignancy but a sacral bone biopsy reported malignant small blue cell neoplasm, consistent with involvement by the patient's known cranial neoplasm. Final pathological diagnosis including molecular diagnostics was consistent with WHO grade 4 IDH-wildtype H3G34 mutant diffuse hemispheric glioma with osseous metastases. Patient was treated with chemoradiotherapy with temozolomide (TMZ). Following the sixth cycle of TMZ, MRI brain imaging was stable. Apart from holocephalic headaches, the patient had no significant medication side effects and was seizure-free. A second whole-body PET scan showed improvement and interval decrease in FDG uptake of the sacrum and right femoral head. Given the stress that patients with H3G34 can experience and the poor prognosis, it is imperative to expand our knowledge and ascertain accurate screening and diagnostic methodologies.

Determination of Response Factors for Analytes Detected during Migration Studies, Strategy and Internal Standard Selection for Risk Minimization.

Migration studies are one of the few domains of pharmaceutical analysis employing wide-scope screening methodologies. The studies involve the detection of contaminants within pharmaceutical products that arise from the interaction between the formulation and materials. Requiring both qualitative and quantitative data, the studies are conducted using Liquid Chromatography or Gas Chromatography coupled to a mass spectrometer (LC-MS and GC-MS). While mass spectrometry allows wide-scope analyte detection and identification at the very low Analytical Evaluation Threshold (AET) levels used in these studies, MS detectors are far from "universal response" detectors. Regulation brings the application of uncertainty factors into the picture to limit the risk of potential analytes detected escaping report and further evaluation; however, whether the application of a default value can cover any or all relevant applications is still debatable. The current study evaluated the response of species usually detected in migration studies, generating a suitable representative sample, analyzing said species, and creating a strategy and evaluation mechanism for acceptable classification of the detected species. Incorporating novel methodologies, i.e., Design of Experiments (DoE) for Design Space generation, the LC-MS-based methodology is also evaluated for its robustness in changes performed.