Screening Methodology Research Articles

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.

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.

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.

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.

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.

Opportunities to advance cervical cancer prevention and care

Cervical cancer (CaCx) is a major public health issue, with over 600,000 women diagnosed annually. CaCx kills someone every 90 s, mostly in low- and middle-income countries. There are effective yet imperfect mechanisms to prevent CaCx. Since human papillomavirus (HPV) infections cause most CaCx, they can be prevented by vaccination. Screening methodologies can identify premalignant lesions and allow interventions before a CaCx develops. However, these tools are less feasible in resource-poor environments. Additionally, current screening modalities cannot triage lesions based on their relative risk of progression, which results in overtreatment. CaCx care relies heavily on genotoxic agents that cause severe side effects. This review discusses ways that recent technological advancements could be leveraged to improve CaCx care and prevention.

Structure-based identification of small-molecule inhibitors that target the DIII domain of the Dengue virus glycoprotein E pan-serotypically.

Dengue viral infection is caused by the Dengue virus, which spreads to humans through the bite of infected mosquitos. Dengue affects over half of the global population, with an estimated 500 million infections per year. Despite this, no effective treatment is currently available, however, several promising candidates are undergoing pre-clinical/clinical testing. The existence of four major serotypes is an important challenge in the development of drugs and vaccines to combat Dengue virus infection. Hence, the drug/vaccine thereby developed should neutralize all the four serotypes equally. However, there is no pan-serotype specific treatment for Dengue virus, thereby emphasizing the need for the identification of novel drug-like compounds that can target all serotypes of the Dengue virus equally. To this end, we employed virtual screening methodologies to find drug-like compounds that target the domain III of glycoprotein E. Most importantly, domain III of E protein is involved in viral fusion with the host membrane and is also targeted by neutralizing antibodies. Our study found two small molecule drug-like compounds (out of the 3 million compounds screened) having similar binding affinity with all four serotypes. The compounds thereby identified exhibit favourable drug like properties and can be developed as a treatment for Dengue virus.

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.

Screening of antimicrobial activity in venom: Exploring key parameters

The escalating challenge of antibiotic resistance significantly threatens global health, underscoring the critical need for new antimicrobial agents. Venoms, increasingly recognized as reservoirs of bioactive compounds with diverse pharmacological effects, have been the focus of recent research. This work evaluates the use of various screening methodologies in assessing the antimicrobial activities of 185 venoms against some gram positive and gram negative bacteria, including E. coli ATCC 8739, B. subtilis ATCC 6633, P. aeruginosa ATCC 9027, and S. aureus ATCC 6538P species and explores the influence of settings on the findings. Furthermore, the research explored the possibility of purifying antimicrobial molecules from venoms through HPLC. Several fractions demonstrated antimicrobial activity against the tested strains.Our results reveal that the measured antimicrobial efficacy of venoms varies according to:i) venom concentration, ii) the detection method, including microdilution and radial diffusion assays, and iii) the choice of culture medium, specifically LB or MH.This strategy has allowed us, for the first time, to identify antimicrobial activity in: i) Bitis arietans venom against P. aeruginosa ATCC 9027, ii) Naja nubiae and Bothrops lanceolatus against B. subtilis ATCC 6633, P. aeruginosa ATCC 9027, and S. aureus ATCC 6538P, and iii) Hadogenes zuluanus, Mesobuthus caucasicus, Nebo hierichonticus, Opistophthalmus wahlbergii scorpions, and Mylabris quadripunctata beetles against S. aureus ATCC 6538P.These findings highlight venoms potential as effective antimicrobial resources and improve our understanding of key factors critical for an accurate detection of venoms antimicrobial properties.

Optimization and correction of breast dynamic optical imaging projection data based on deep learning

Breast cancer poses a significant health threat to women, necessitating advancements in diagnostic technologies. Breast dynamic optical imaging (DOI) technology, recognized for its non-invasive and radiation-free properties, is extensively utilized for the early screening and quantitative analysis of breast tumors. The integration of deep learning, a robust technology for automatic image feature extraction, with breast DOI has the potential to enhance tumor detection and diagnosis significantly. This paper introduces a deep learning-enhanced image optimization approach to overcome challenges such as poor image quality and distorted projection data commonly encountered in existing DOI methods. The approach utilizes convolutional neural networks (CNNs) to extract features from raw images and employs generative adversarial networks (GANs) to enhance these images, thereby improving their quality and contrast. Additionally, a novel correction algorithm is developed to address projection data distortion, enabling the reconstruction and correction of this data for more accurate and reliable imaging results. Experimental findings confirm that the proposed method markedly enhances both image quality and projection data accuracy in breast DOI, offering a reliable foundation for clinical diagnosis. This study not only provides a new perspective and methodology for the early screening and diagnosis of breast cancer but also holds substantial clinical importance and prospective applications.

Double Designers: Detection of Bromazolam and Metonitazene in Postmortem Casework.

The identification of novel psychoactive substances (NPSs) in casework at the Los Angeles County Department of Medical Examiner (LACDME) is constantly evolving. The case detailed herein marks the first detection of metonitazene in forensic casework at the LACDME which occurred in August 2023. Furthermore, bromazolam was found in the decedent's system and both substances were identified in drug evidence collected at the death scene. No other drugs were detected and the manner and cause of death were determined as accidental due to effects of bromazolam and metonitazene. The concentrations detected were 1.6 ng/mL and 4.4 ng/mL of metonitazene in the jugular blood and femoral blood, respectively, and 93 ng/mL of bromazolam in the femoral blood. Constraints in screening techniques conducted by toxicology laboratories create challenges in which numerous NPSs available on the illicit drug market can go undetected. Even if labs detect an NPS in their screening methodology, confirmation methods might not cover every NPS, given the impracticality of labs keeping pace with validations as new NPSs emerge in casework. The significance of testing medical evidence collected at death scenes by drug chemistry analysis becomes crucial when initial toxicology results are negative. In cases where there is evidence of potential drug paraphernalia this is especially true as it can be pivotal in determining the cause and manner of death.

Applying Machine Learning and SERS for Precise Typing of DNA Secondary Structures.

Surface-enhanced Raman spectroscopy (SERS) has been demonstrated as an effective method for elucidating secondary structural characteristics of DNA. However, the inherent complexity of the DNA conformation and the lack of SERS samples pose challenges for identifying numerous secondary structures. To address these issues, a synergistic method integrating machine learning with SERS was proposed so as to analyze the SERS spectra of 54 well-defined conformational oligonucleotides, namely, G-quadruplex (G4), i-motif (iM), double-strand (DS), and single-strand (SS) configurations. Principal component analysis (PCA) effectively segregated the oligonucleotides into three distinct conformational groups (G4s, iMs, and others). Furthermore, linear discriminant analysis (LDA), K-nearest neighbor (KNN), and support vector machine (SVM) approaches were utilized to improve the typing accuracy of 54 trained sequences. This enabled the correct classification of the structures of five untrained sequences, as well as the identification of the predominant conformations including G4, iM, and DS formed by two complementary G-rich and C-rich sequences in acidic and neutral pH conditions. The results of this study demonstrated the potential of the proposed methodology for rapid screening and prediction of secondary DNA conformations.

Innovative Circular Biowaste Valorisation—State of the Art and Guidance for Cities and Regions

The management of the organic fraction of municipal solid waste (OFMSW), also called urban biowaste, and urban wastewater sludge (UWWS) represents a challenge for cities and regions, which want to adopt innovative urban bioeconomy approaches for their treatment and production of high-added-value products beyond the traditional anaerobic digestion (AD) and compost. This adoption is often restricted by the availability and maturity of technologies. The research object of this manuscript, based on the findings of EU Horizon 2020 project HOOP, is the identification of state-of-the-art circular technologies for material valorisation of OFMSW and UWWS, following a novel screening methodology based on the scale of implementation (tested at least at pilot scale). The screening resulted in 25 technologies, which have been compared and discussed under a multidisciplinary assessment approach, showing their enabling factors and challenges, their current or potential commercial status and their compatibility with the traditional technologies for urban biowaste treatment (composting and AD). The bioproducts cover market sectors such as agriculture, chemistry, nutrition, bioplastics, materials or cosmetics. Therefore, the results of this review help project promoters at city/region level to select innovative technologies for the conversion of OFMWS and UWWS into high value products.

In silico identification and virtual screening to discover potent therapeutic phytochemicals against CMT2A

Charcot-Marie-Tooth (CMT2A) neuropathies are a set of monogenic diseases that affect the peripheral nervous system. The pathogenesis of CMT2A, a disease caused by genetic mutations, is linked to impaired mitochondrial dynamics and axonal biology. Therapeutic options are still limited, with only a few drugs and other authorized or underdeveloped approaches. A ligand-based virtual screening methodology was used to identify the potential MFN promoters. The natural compound subset of the ZINC database (n = 559600) was obtained and filtered using a ligand-based virtual screening technique. The top 200 compounds were identified to have more than four features that matched the target compound. Pyrx software was used to analyze the molecular docking. Based on the number and type of important binding interactions and docking results, we selected top-20 compounds with the best binding affinities for the targeted protein. 3D-QSAR analyses were performed on potential ligands identified through molecular docking analyses to predict biological activity. The pEC50 and docking scores were used to identify the potential drugs. The ADMET analysis was used to assess the kinetic characteristics of the top two drugs. According to molecular dynamics simulation, the top compound ZINC000005313168 showed high conformational stability. Based on docking results and MD findings, the best in silico hits among the compounds investigated was ZINC000005313168. These findings suggest that the compound ZINC000005313168 could be used to treat CMT2A disease. Further in vivo and in vitro studies are required to consider the present analyses.

Investigation of age-hardening behaviour of Al alloys via feature screening-assisted machine learning

Age hardening stands as a crucial strengthening process for aluminium (Al) alloys. However, determining the optimal ageing conditions has traditionally relied on resource-intensive trial-and-error methods. To streamline the design of Al alloys, this study introduces a novel feature screening-assisted machine learning (ML) approach to explore age-hardening behaviour across varying compositions and heat treatment parameters, focusing on yield tensile strength (YTS), ultimate tensile strength (UTS), and elongation (EL). A comprehensive pool of features, incorporating alloy composition and fundamental elemental properties, was generated to provide metallurgical insights for ML predictions. Subsequently, feature screening methodologies, including correlation analysis, feature elimination, and multi-objective genetic algorithm (MOGA), were employed to identify key features from the vast feature pool, balancing model complexity and prediction accuracy. Employing support vector regression models trained on these optimized feature sets, we demonstrate enhanced prediction accuracy for strength properties while maintaining model simplicity for EL, with minimal impact on accuracy. In addition, experimental results further validate the method's ability to reproduce ageing curves across all three mechanical properties for both commercialized and newly designed Al alloys.

Insights into the methodological perspectives for screening polyunsaturated fatty acids-containing bacteria.

Polyunsaturated fatty acids (PUFA) are vital molecules in the pharmaceutical, medical, and nutritional industries. Exploration of bacterial strains capable of producing significant amounts of PUFAs offers a promising avenue for biotechnological applications and industrial-scale production. However, an extensive screening of several samples from diverse sources is highly needed to identify a potential strain. The present study provides the results of the evaluation of 15 different screening methodologies (including changes in existing protocols in terms of reagent concentration, incubation temperature and time) for identifying PUFA-producing bacteria in comparison to the gold standard method (Gas chromatography-mass spectrometry), for the first time. The results determined the most effective techniques for each critical PUFA, leading to an optimized screening process that saves time and resources. The H2O2 plate assay using 0.5% or 1% H2O2 for 72 & 96h of incubation at 15 °C consistently outperformed others for finding bacteria containing total nutritionally important long chain-PUFA (LC-PUFA), linoleic acid, and arachidonic acid. Whereas the 2,3,5-triphenyl tetrazolium chloride broth assay at 10-15 °C was the most effective and semiquantitative screening methodology for eicosapentaenoic acid (EPA) and alpha-linolenic acid-containing bacteria. Apart from the methodological perspectives, the study also revealed certain potential strains to be targeted in the ongoing research on PUFA-containing bacteria. Further, the manuscript forms the first report on the presence of docosahexaenoic acid (DHA) in Shewanella decolorationis, EPA in Psychrobacter maritimus and Micrococcus aloeverae, and both EPA and DHA in Arthrobacter rhombi. Altogether, the paper generates several thought-provoking insights on the methodological perspectives and identifies potential PUFA-containing bacteria with practical applications in future bacteria-based PUFA research.

Computational exploration of acefylline derivatives as MAO-B inhibitors for Parkinson's disease: insights from molecular docking, DFT, ADMET, and molecular dynamics approaches.

Monoamine oxidase B (MAO-B) plays a pivotal role in the deamination process of monoamines, encompassing crucial neurotransmitters like dopamine and norepinephrine. The heightened interest in MAO-B inhibitors emerged after the revelation that this enzyme could potentially catalyze the formation of neurotoxic compounds from endogenous and exogenous sources. Computational screening methodologies serve as valuable tools in the quest for novel inhibitors, enhancing the efficiency of this pursuit. In this study, 43 acefylline derivatives were docked against the MAO-B enzyme for their chemotherapeutic potential and binding affinities that yielded GOLD fitness scores ranging from 33.21 to 75.22. Among them, five acefylline derivatives, namely, MAO-B14, MAO-B15, MAO-B16, MAO-B20, and MAO-B21, displayed binding affinities comparable to the both standards istradefylline and safinamide. These derivatives exhibited hydrogen-bonding interactions with key amino acids Phe167 and Ile197/198, suggesting their strong potential as MAO-B inhibitors. Finally, molecular dynamics (MD) simulations were conducted to evaluate the stability of the examined acefylline derivatives over time. The simulations demonstrated that among the examined acefylline derivatives and standards, MAO-B21 stands out as the most stable candidate. Density functional theory (DFT) studies were also performed to optimize the geometries of the ligands, and molecular docking was conducted to predict the orientations of the ligands within the binding cavity of the protein and evaluate their molecular interactions. These results were also validated by simulation-based binding free energies via the molecular mechanics energies combined with generalized Born and surface area solvation (MM-GBSA) method. However, it is necessary to conduct in vitro and in vivo experiments to confirm and validate these findings in future studies.