Screening Methodology Research Articles

Derivation of human toxicokinetic parameters and internal threshold of toxicological concern for tenuazonic acid through a human intervention trial and hierarchical Bayesian population modeling.

Tenuazonic acid (TeA), a mycotoxin produced by Alternaria alternata, contaminates various food commodities and is known to cause acute and chronic health effects. However, the lack of human toxicokinetic (TK) data and the reliance on external exposure estimates have stalled a comprehensive risk assessment for TeA. To bridge this gap, a human TK trial and population-based TK (PopTK) modeling were applied to determine human TK parameters of TeA, and the results were applied for risk screening using population biomonitoring data and threshold of toxicological concern (TTC)-based approaches. Ten healthy volunteers participated in the TK trial during which the volunteers ingested a bolus dose of TeA at the (external) TTC (1500 ng/kg bw). Blood, urine, and fecal samples were collected over 48 h and analyzed using UPLC-MS/MS. Concentration-time profiles were fit with a multi-compartmental PopTK model using a hierarchical Bayesian population structure. Utilizing a probabilistic framework, fitted TK parameters were used to derive internal TTC (iTTC) values for comparison to blood and urine biomonitoring data. Risk screening with data from five diverse biomonitoring cohorts was performed using Hazard Quotient (HQ) and probabilistic individual margin of exposure (IMOE) approaches. TeA was estimated to have a population median half-life of 1.9 [90% CI: 1.4-2.7] hours and volume of distribution of 4.4 [3.1-6.1] L/kg, with inter-individual variability geometric standard deviations of 2.4- and 1.7-fold, respectively. Probabilistic lower confidence bound iTTCs were derived of 0.5 nmol/L in blood and 2.53 nmol/kg-d urinary excretion. Risk screening HQs were mostly >1 for the three blood biomonitoring cohorts and < 1 for the two urinary biomonitoring cohorts; results from probabilistic IMOE calculations were qualitatively consistent. A comprehensive human TK study was performed for TeA for the first time, demonstrating the importance of integrating TK and population variability for a more comprehensive risk evaluation, particularly for interpreting biomonitoring data. The results for TeA point to the critical need for toxicity data to move beyond TTC-based risk screening. A critical gap in food safety research was addressed studying the toxicokinetics of tenuazonic acid (TeA) in humans and using these data to derive an internal threshold of toxicological concern (iTTC) for comparison to human biomonitoring data. The innovative approach-combining a human intervention trial with population-based toxicokinetic modeling-accounts for inter-individual variability and provides a more comprehensive understanding of population exposure to TeA. The resulting probabilistic iTTC and risk screening methodologies offer improved tools for interpretation of biomonitoring data. These findings have significant implications for food safety regulations and public health protection, potentially influencing future mycotoxin risk assessment strategies.

Mastering the complexities of cancer nanomedicine with text mining, AI and automation.

In this contribution to the Orations - New Horizons of the Journal of Controlled Release, I present a personal perspective on the complexities of cancer nanomedicine and the approaches to master them. This oration draws mainly from my lab's journey to explore three transformative approaches to master complexities in the field: (1) leveraging text mining to construct dynamic knowledge bases for hypothesis generation in cell-specific drug delivery, (2) introducing the concept of meta-synergy to further optimize and classify multi-drug combinations across dimensions such as chemical loading, pharmacodynamics, and pharmacokinetics (3) utilizing automation to accelerate nanoparticle discovery with advanced screening methodologies such as aggregation-induced emission (AIE). I argue that by embracing complexity in nanomedicine, we can manifest new therapeutic possibilities, paving the way for more effective, precise, and adaptive treatment strategies.

Novel Quinazoline Derivatives Inhibit Splicing of Fungal Group II Introns.

We report the discovery of small molecules that target the RNA tertiary structure of self-splicing group II introns and display potent antifungal activity against yeasts, including the major public health threat Candida parapsilosis. High-throughput screening efforts against a yeast group II intron resulted in an inhibitor class which was then synthetically optimized for enhanced inhibitory activity and antifungal efficacy. The most highly refined compounds in this series display strong, gene-specific antifungal activity against C. parapsilosis. This work demonstrates the utility of combining advanced RNA screening methodologies with medicinal chemistry pipelines to identify high-affinity ligands targeting RNA tertiary structures with important roles in human health and disease.

Laboratory Methodology for Screening of Cruciferous Host for Egg Laying Preference of Diamondback Moth, Plutella xylostella (L.)

Background: Diamondback moth (DBM), Plutella xylostella (L.), significantly damages Cole crops worldwide, causing major yield losses and management costs. Efficient control measures, including host plant resistance are imperative. While molecular methods offer insights into resistance mechanisms, conventional screening methods remain advantageous. Here, we present a novel laboratory-based oviposition preference screening method for DBM, significantly shortening screening time in resistance breeding. Methods: We studied DBM’s oviposition preferences among cruciferous hosts and plant tissues. Extract was prepared from leaves and heads of dark green and light green cabbage varieties, as well as cauliflower. Aluminum egg-laying sheets were treated with these extracts and introduced into mating boxes with insects. Egg-laying was monitored over seven days, with the number of eggs recorded daily. Result: DBM adults preferred light green cabbage for egg laying (1238±10.54 eggs), with no significant difference between leaf and head tissues. Dark green cabbage was the second choice (514.5±15.78 eggs), while cauliflower was the least preferred (217±37.2 eggs). Interestingly, DBM exhibited varying preferences between leaf and head tissues, with cauliflower heads being favored over leaves. Additionally, we observed distinct day-wise egg laying trends, providing insights into DBM’s oviposition behavior over time. This study demonstrates the efficiency of lab-based screening in identifying resistant crop varieties, aiding sustainable pest management and crop production and highlights the importance of considering host plant selection and tissue specificity in screening of genotype for resistance breeding programs.

A framework for assessing microbial degradation of organophosphate ester plasticizers in seawater.

The assessment of persistence of organic pollutants in seawater is limited by the lack of user-friendly, quick protocols for assessing one of their main sinks, degradation by marine bacteria. Here we present an experimental workflow to identify organic pollutants degradation, taking organophosphate esters flame retardants and plasticizers (OPEs-FR-PL), as a model family of synthetic chemicals released into the marine environment that are particularly widespread due to their persistence and semi-volatile nature. The proposed novel workflow combines culture-dependent techniques, solvent demulsification-dispersive liquid-liquid microextraction, with quantitative liquid chromatography coupled with mass spectrometry analyses in order to identify marine bacterial isolates with the potential to degrade OPEs-FR-PL in the marine environment. This methodology evaluates growth rates, degradation capacities of different OPEs-FR-PL, and the ability of bacteria to utilize these pollutants as a sole source of carbon, phosphorus and energy. The proposed framework is more cost-effective than previous approaches as it is less time-consuming, reduces the use of solvents making it environmentally friendly, and can be used as a high throughput screening methodology. Although optimized here for OPEs-FR-PL degradation, this methodology can be adapted to a wide variety of contaminants of emerging concern. Using this developed workflow, we could detect that coastal Antarctic seawater harbors several bacterial taxa with the potential to degrade OPEs-FR-PL.

Cervical Cancer Screening: Patient Perspectives on Transitioning to Primary High-Risk Human Papillomavirus Testing Alone.

In 2018, the US Preventive Services Task Force updated cervical cancer screening recommendations to allow for screening every 5 years with primary human papillomavirus (HPV) testing in combination with cytology (cotesting) or every 5 years with primary HPV screening alone. Despite these changes, the uptake of primary HPV screening has been lower than expected. The purpose of this study was to evaluate the patient perspective of an integrated health system transition from cotesting to primary HPV testing among a 30- to 65-year-old cohort. Semistructured phone interviews were conducted from July to December 2023 at Kaiser Permanente Colorado with 16 members aged 30-65 years. Interviews asked about reactions to the forthcoming change in cervical cancer screening, personal concern about cervical cancer risk, feedback on patient-facing education materials, and preference on communication timing and modality. Participants reported concerns about cervical cancer screening intervals, primarily the reduction in frequency leading to underdiagnosis of sexually transmitted infections (STIs). Participants recommended defining the rationale for the change to primary HPV testing in the patient education materials. Participants preferred communication about the change in-clinic between practitioner and patient. The interviews identified key themes, including the differentiation between cervical cancer and STI screening methodologies, potential underdiagnosis of STI and cervical cancer, and the rationale supporting primary HPV testing and associated screening intervals. These qualitative findings can inform health systems of potential patient concerns to address when considering the transition from cotesting every 3 years to primary HPV testing every 5 years for cervical cancer screening.

Rapid visual screening methodology for multi-hazard vulnerability assessment of reinforced concrete buildings in hilly region

Rapid visual screening methodology for multi-hazard vulnerability assessment of reinforced concrete buildings in hilly region

The Importance of Shari’ah Screening in Islamic Bank: An Islamic Jurisprudence Analysis

Islamic Banking and Finance (IBF) is a rapidly growing industry worldwide. Islamic finance (IBF) is a financial system based on Islamic law (Shari’ah). The fundamental principle of IBF is to comply with Islamic law, known as Shari’ah. Shari’ah prohibits the charging or paying interest and investment in activities considered harmful or risky. Shari’ah screening is the process of identifying companies that comply with Shari’ah law. This is to ensure that their investments are in accordance with Shari’ah principles which prohibit the elements of riba, maysir and gharar. Shari’ah screening is an essential aspect of IBF as it ensures that all financial transactions and products comply with Shari’ah’s principles. This is important for investors who want to invest in IBF products and services. This paper provides an overview of Shari’ah screening and its importance in IBF. It also discusses the different methods that are used to conduct Shari’ah screening. This paper also aims to provide an Islamic jurisprudence analysis of the importance of Shari’ah screening in IBF. The paper concludes by arguing that Shari’ah screening is an essential part of IBF and helps ensure that IBF products and services comply with Shari’ah law. The objective of this paper is to discuss the importance of Shari’ah screening in the context of Islamic banking and finance and Islamic jurisprudence also a new screening methodology in comparison with the previous methodology. This paper has used information that has been derived from research papers, journal articles as well as official authentic websites and annual reports to provide an ideology about shariah screening in methodologies.

Supersaturation Behavior: Investigation of Polymers Impact on Nucleation Kinetic Profile for Rationalizing the Polymeric Precipitation Inhibitors.

Although nucleation kinetic data is quite important for the concept of supersaturation behavior, its part in rationalizing the crystallization inhibitor has not been well understood. This study aimed to investigate the nucleation kinetic profile of Dextromethorphan HBr (as an ideal drug, BCS-II) by measuring liquid-liquid phase segregation, nucleation induction time, and Metastable Zone width. Surfeit action was examined by a superfluity assay of the drug. The concentration was scrutinized by light scattering techniques (UV spectrum (novel method) and Fluorometer (CL 53)). The drug induction time was 20 min without polymer and 90 and 110 min with polymers, such as HPMC K15M and Xanthan Gum, respectively. Therefore, the order of the polymer's ability to inhibit nucleation was Xanthan Gum > HPMC K15M in the medium (7.4 pH). Similarly, the drug induction time was 30 min without polymer and 20, 110, and 90 min with polymers, such as Sodium CMC, HPMC K15M, and Xanthan Gum, respectively. Therefore, the order of the polymer's ability to inhibit nucleation was HPMC K15M > Xanthan Gum > Sodium CMC in SIFsp (6.8 pH), which synchronizes the polymer's potentiality to interdict the drug precipitation. The HPMC K15M and xanthan Gum showed the best crystallization inhibitor effect for the maintenance of superfluity conditions till the drug absorption time. The xanthan gum is based on the "glider" concept, and this shows the novelty of this preliminary research. The screening methodology used for rationalizing the best polymers used in the superfluity formulations development successfully.

Rapid discovery and optimization of novel brain shuttles and shuttle‐enabled anti‐amyloid therapeutics using multiplexed in vivo biologics design

AbstractBackgroundDrug delivery to the central nervous system has long been hindered by the restrictive properties of the blood‐brain barrier (BBB). Recent advances have highlighted the ability of certain antibody “shuttles'' to traverse the BBB and enhance the delivery of diverse therapeutic payloads. However the true potential of this approach remains underexplored and is limited by traditional in vitro screening platforms that fail to capture the complexities of in vivo biology. Novel technologies that facilitate the development of brain shuttles and shuttle‐enabled neuromedicines could improve the uptake, efficacy, safety, and dosing of broad classes of therapeutics, and transform the treatment of vast numbers of patients with neurological disease.MethodHere, we introduce a high‐throughput in vivo screening methodology based on Manifold’s mCodeTM technology to evaluate BBB penetration and uptake of over 1000 brain shuttling antibody candidates targeting 10+ different receptors (Figure).ResultOur approach reveals antibody shuttles with diverse molecular properties and distinct pharmacokinetic profiles in brain, blood, and other peripheral tissues. We leverage this large in vivo dataset using machine learning to further engineer these antibodies for enhanced brain uptake and residence time. Engineering of brain shuttles with anti‐amyloid antibodies against BACE1 and amyloid beta significantly improved the uptake and efficacy of these fusions versus unshuttled controls and comparator shuttled molecules.ConclusionCollectively, our work (1) expands the pool of known targets and molecules capable of shuttling therapeutic payloads across the BBB, (2) validates the utility of these molecules toward the design of novel neuromedicines for Alzheimer’s disease, and (3) signifies a paradigm shift in utilizing thoughtfully‐designed, high‐throughput in vivo screening in early stages of drug discovery.

Monitoring of pesticide residues in Brazilian infant formulas using the suspect screening methodology by GC-HRMS

Monitoring of pesticide residues in Brazilian infant formulas using the suspect screening methodology by GC-HRMS

DETECT‐AD ‐ Digital Evaluations and Technologies Enabling Clinical Translation for Alzheimer’s Disease: Results of amyloid screening methodologies in a simulated anti‐amyloid clinical trial using digital biomarkers as primary outcome measures

DETECT‐AD ‐ Digital Evaluations and Technologies Enabling Clinical Translation for Alzheimer’s Disease: Results of amyloid screening methodologies in a simulated anti‐amyloid clinical trial using digital biomarkers as primary outcome measures

Computational Discovery of Optimal Dopants for Electrode to Enhance Sea Water Splitting

A strategic approach has been proposed for designing robust, high-performing oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) catalysts tailored for saline/sea water splitting. By employing a density functional theory (DFT)-based computational screening process, a set of promising dopants were identified from a range of twenty-six 3d to 5d transition metals, with the aim of enhancing the activity and saline water resilience of the catalysts. The screening methodology was threefold, encompassing evaluations of OER / HER energetics, chlorine evolution reaction (ClER) energetics, and chloride-corrosion energetics. The screening led to the promising dopants, which substantially elevated the performance of each of the host catalysts. This study contributes to the understanding of alkaline ClER and chloride-corrosion mechanisms, providing insights into catalyst behavior in saline/sea conditions.

Redox Stability of Co-Doped Barium Niobate Thin Films in Reducing Conditions Analyzed Using Cyclic Voltammetry Measurements

Perovskite anodes (general chemical formula ABO3) for the high temperature (>750 °C) electrolysis of methane to ethylene in a ceramic solid oxide electrolysis cell require both high activity, chemical and mechanical stability as well as durability for future commercialization efforts. We have previously shown co-doped barium niobate perovskites as stable anode materials for electrochemical oxidation of methane (E-OCM)1 . The mechanism for the excellent chemical stability is highly connected to the flexible oxidation state switching of Nb4+/Nb5+ cations associated with changes in lattice oxygen concentration2 ,3. To further evaluate their chemical stability in highly reducing conditions to understand their applicable potential window , this work utilizes the Ca and Fe codoped perovskite BaCa0.33Nb0.67-xFexO3-δ (BCNF). BCNF has shown very good methane activation properties and higher activities in E-OCM operation via increased conductivity and ethylene selectivity4. We deposited BCNF thin films utilizing pulsed laser deposition on various substrates such as quartz glass and yttria stabilized zirconia (YSZ) and analyzed their electrical properties using electrochemical impedance spectroscopy (EIS) in various oxygen partial pressures and cyclic voltammetry (CV) in a homemade test setup that allow for redox stability under controlled gas environments to be examined. This advanced screening methodology allows for holding at desired operating temperatures while altering the applied potential bias to simulate electrode reduction in various gas environments (for a single test). The results of these measurements along with physical characterization of the thin films by TEM, SEM, AFM will be presented to demonstrate the utility of BCNF perovskites in E-OCM applications.

Fully Solution‐Processed Polymeric Multilayer Piezoelectric Devices

AbstractThis study demonstrates fully solution‐processed polymeric multilayer piezoelectric devices. The key challenge, the effective control of the redissolution issue that will cause severe electrical shorting and inconsistent piezoelectric output, is overcome by searching for and using a solvent that offers adequate solubility but extremely slow dissolution for the piezoelectric polymer. The solvent screening methodology is established and demonstrated. The process parameters is systematically optimized to maximize the piezoelectric performance of the multilayer devices. The multilayer devices can output a high charge density of 376 µC m−2, even higher than the record charge density of 250 µC m−2 achieved by traditional contact electrification‐based triboelectric nanogenerators operated in ambient air. The crucial factors for increasing device fabrication yield, namely resistance to short circuits and poling‐induced breakdown, are analyzed. The potential of multilayer devices in practical applications is demonstrated using a five‐layer device as a direct power source and energy harvester. More importantly, the process developed here is transferrable for cost‐effective high‐throughput roll‐to‐roll production. This work thus lays the foundation for the mass production of polymeric multilayer piezoelectric devices and paves the way for their future commercialization.

Biophysical and biochemical parameters of Sorghum associated to shoot fly resistance

The sorghum shoot fly, Atherigona soccata (Muscidae: Diptera), represents a significant biotic constraint to sorghum production, leading to considerable yield losses globally. This study aimed to systematically classify sorghum genotypes based on their resistance to A. soccata infestation. A total of 188 genotypes were subjected to rigorous evaluation employing standardized screening methodologies. The analysis revealed substantial variability in resistance levels across the genotypes. Based on damage assessments in field trials, 14 genotypes were selected for further investigation under controlled pot culture conditions. Comprehensive biochemical analyses were conducted on each genotype under both uninfested and infested scenarios. Among the evaluated genotypes, IS 10588 and IS 8380 exhibited high levels of resistance, IS 12787 demonstrated moderate resistance, while TNFS 230 was classified as moderately resistant to A. soccata infestation. Critical morphological and biochemical traits associated with resistance were identified, including trichome density, leaf glossiness, and enzyme activity levels of peroxidase (PO), polyphenol oxidase (PPO), tannins, and phenolic compounds. The study concludes that these morpho-physiological and biochemical characteristics contribute significantly to the resistance mechanisms in sorghum against A. soccata. Thus, these identified genotypes may serve as valuable genetic resources for breeding programs aimed at enhancing resistance to A. soccata in sorghum.

Decoding transaminase motifs: Tracing the unknown patterns for enhancing the accuracy of computational screening methodologies

Transaminases, enzymes known for their amino group transfer capabilities, encompass four distinct subfamilies: D-alanine transaminase (DATA), L-selective Branched chain aminotransferase (BCAT), and 4-amino-4-deoxychorismate lyase (ADCL) and R-selective aminotransferase (RATA). RATA enzymes are particularly valuable in biocatalysis for synthesizing chiral amines and resolving racemic mixtures, yet their identification in sequence databases is challenging due to the lack of robust motif-based screening methods. Constructing a sequence dataset of transaminases, and categorizing them to various subfamilies, the conserved motifs are screened over the experimentally known ones, and the novel motifs are explored. Phylogenetic clustering of these subfamilies and structural localization of the identified motifs on the Alphafold-predicted protein models of the representative sequences validate their functional importance. For the ADCL, BCAT, DATA, and RATA datasets, we identified 5, 7, 10, and 2 novel motifs, with 3, 5, 7, and 2 motifs localized on secondary structures, confirming their structural importance. Furthermore, the analysis revealed 1, 3, 2, and 1 unique residue patterns of 293-KxxxR-297; 336-KxxxxY-341, 379-ExxxxNxF-386, and 453-ExFxxGT-459; 187-HxxRL-191, and 284-DxRWxxCDIK-293; and 191-HxxRL-195, integrating of which in the known computational tools would improve their accuracy. The conserved residue pattern or motif-based computational approach for robustly screening the transaminases holds promise for unveiling the novel RATA enzymes, facilitating their exploitation in biocatalytic applications.

Preparticipation Cardiovascular Screening of Athletes: Current Controversies and Challenges for the Future.

Sports cardiology is an evolving field in cardiology, with several topics remaining controversial. Beyond the several well-known benefits of regular exercise practice, the occurrence of adverse clinical events during sports in apparently healthy individuals, especially sudden cardiac death, and the described long-term adverse cardiac adaptations associated to high volume of exercise, remain challenging. The early identification of athletes with increased risk is critical, but the most appropriate preparticipation screening protocols are also debatable and a more personalized evaluation, considering individual and sports-related characteristics, will potentially optimize this evaluation. As the risk of major clinical events during sports is not zero, independently of previous evaluation, ensuring the capacity for cardiopulmonary resuscitation, especially with availability of automated external defibrillators, in sports arenas, is crucial for its prevention and to improve outcomes. As in other areas of medicine, application of new digital technologies, including artificial intelligence, is promising and could improve in near future several aspects of sports cardiology. This paper aims to review the methodology of athletes' preparticipation screening, emphasizing current controversies and future challenges, in order to improve early diagnosis of conditions associated with sudden cardiac death.

Evaluating offshore legacy wells for geologic carbon storage: A case study from the Galveston and Brazos areas in the Gulf of Mexico

Federal offshore waters in the Gulf of Mexico are of interest for large-scale geologic carbon storage (GCS). However, more than 80,000 offshore oil and gas wells exist in the region, which could impact the integrity of sealing intervals. In this study, we propose a screening methodology for ranking offshore legacy wells based on the challenge they may present to GCS. The methodology relies on the review of well regulatory records to 1) identify leakage pathways and assess the potential hazards that wells pose to planned GCS operations, 2) evaluate well features that impact the accessibility of wells to determine the feasibility of potential corrective actions, and 3) rank wells based on the overall challenge they may pose for GCS. We demonstrate our framework by evaluating the construction and abandonment of 156 wells across eight areas of interest (AOIs) in shallow federal waters along the Texas Gulf Coast. The majority (99.3 %) of wells considered were constructed and plugged in a manner that did not isolate prospective GCS targets in the Upper and Lower Miocene formations and may potentially require a challenging or uncertain corrective action prior to GCS. Dataset trends suggest that the observed well construction and plugging designs may be common in shallow offshore federal waters along the Texas Gulf Coast. Consequently, operators pursuing offshore GCS projects in the region may consider selecting areas that avoid challenging wells or performing robust evaluations of legacy well leakage risks to plan corrective action prior to CO2 injection.

Computational Advances in Ionic Liquid Applications for Green Chemistry: A Critical Review of Lignin Processing and Machine Learning Approaches.

The valorization and dissolution of lignin using ionic liquids (ILs) is critical for developing sustainable biorefineries and a circular bioeconomy. This review aims to critically assess the current state of computational and machine learning methods for understanding and optimizing IL-based lignin dissolution and valorization processes reported since 2022. The paper examines various computational approaches, from quantum chemistry to machine learning, highlighting their strengths, limitations, and recent advances in predicting and optimizing lignin-IL interactions. Key themes include the challenges in accurately modeling lignin's complex structure, the development of efficient screening methodologies for ionic liquids to enhance lignin dissolution and valorization processes, and the integration of machine learning with quantum calculations. These computational advances will drive progress in IL-based lignin valorization by providing deeper molecular-level insights and facilitating the rapid screening of novel IL-lignin systems.