Screening Method Research Articles

D-allose, a typical rare sugar: properties, applications, and biosynthetic advances and challenges.

D-allose, a C-3 epimer of D-glucose and an aldose-ketose isomer of D-allulose, exhibits 80% of sucrose's sweetness while being remarkably low in calories and nontoxic, making it an appealing sucrose substitute. Its diverse physiological functions, particularly potent anticancer and antitumor effects, render it a promising candidate for clinical treatment, garnering sustained attention. However, its limited availability in natural sources and the challenges associated with chemical synthesis necessitate exploring biosynthetic strategies to enhance production. This overview encapsulates recent advancements in D-allose's physicochemical properties, physiological functions, applications, and biosynthesis. It also briefly discusses the crucial role of understanding aldoketose isomerase structure and optimizing its performance in D-allose synthesis. Furthermore, it delves into the challenges and future perspectives in D-allose bioproduction. Early efforts focused on identifying and characterizing enzymes responsible for D-allose production, followed by detailed crystal structure analysis to improve performance through molecular modification. Strategies such as enzyme immobilization and implementing multi-enzyme cascade reactions, utilizing more cost-effective feedstocks, were explored. Despite progress, challenges remain, including the lack of efficient high-throughput screening methods for enzyme modification, the need for food-grade expression systems, the establishment of ordered substrate channels in multi-enzyme cascade reactions, and the development of downstream separation and purification processes.

Fatty Liver Index (FLI) is the best score to predict MASLD with 50% lower cut-off value in women than in men.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is defined by the presence of hepatic steatosis, detected on ultrasonography (US) imaging or histology, and at least one of criteria for Metabolic Syndrome diagnosis. Simple non-invasive tests (NITs) have been proposed as an acceptable alternative when US and biopsy are not available or feasible but have not been validated for MASLD. In this observational study, we investigated the reliability of NITs for MASLD detection and whether sex-differences in screening methods should be considered. We included 1069 individuals (48% males and 52% females) who underwent their first clinical examination for Metabolic Syndrome in the period between January 2015 and December 2022. Liver steatosis was detected through US and anthropometric and clinical parameters were recorded. Liver steatosis was detected in 648 patients and MASLD was diagnosed in 630 subjects (355 males; 275 females). Women with MASLD showed better metabolic profile and lower prevalence of Metabolic Syndrome criteria than men. Among NITs, Fatty Liver Index (FLI) showed the best ability for detection of MASLD, with a cut-off value of 44 (AUC = 0.82). When considering the two sexes for MASLD detection via FLI, despite no substantial differences regarding FLI correlations with metabolic biomarkers except for age, women showed marked lower FLI cut-off value (32; AUC = 0.80) than men (60; AUC = 0.80). In this study, we found that FLI is the best non-invasive predictor of both liver steatosis and MASLD. The finding that in womenFLI cut-off value for MASLD detection is 50% lower than inmen suggests the need of a sex-specific personalized program of screening and prevention of dysmetabolism-related liver diseases, despite outwardly healthy biomarkers profile.

Ultrasonography screening of hepatic cystic echinococcosis in sheep flocks used for evaluating control progress in a remote mountain area of Hejing County, Xinjiang.

Although ultrasonography (US) has been widely used in the diagnosis of human diseases to monitor the progress of cystic echinococcosis (CE) control, the screening method for hepatic CE in sheep flocks requires adjustment. In this study, we used a US scanner to screen sheep flocks and evaluated the efficacy of dosing dogs once a year with praziquantel for 7 years from 2014 to 2021. All sheep in the three flocks were screened using an ultrasound scanner in 2014 and compared with the prevalence of infection in 2021 in Bayinbuluke, Xinjiang, China. Sheep age was determined using incisor teeth. Cyst activity and calcification were determined using US images. The dogs were dewormed with praziquantel once a year to control echinococcosis in the community. Three flocks had 968 sheep in 2014, with 13.22%, 22.62%, 18.7%, 27.27%, 11.88%, and 6.3% of sheep aged 1, 2, 3, 4, 5, and ≥ 6 years old, respectively. US scanning revealed that the overall CE prevalence was 38.43% (372/968), with active cysts and calcified cysts present in 9.40% (91/968) and 29.02% (281/968) of the sheep, respectively. For the young sheep aged 1 and 2 years, the prevalence of active and calcified cysts was: 1.56% and 0.91%, and 10.94% and 18.72%, respectively. Approximately 15.15% and 16.52% of the 4- and 5-year-old sheep, respectively, harbored active cysts. There was no significant difference in the infection rates of sheep between 2014 and 2021 (P > 0.05). US is a practical tool for the field screening of CE in sheep flocks. One-third of the sheep population in the flocks was 1-2 years old, and these sheep played a very limited role in CE transmission, as most of the cysts were calcified. Old sheep, especially culled aged sheep, play a key role in the transmission of CE. Dosing dogs once a year did not affect echinococcosis control.

Variability in the prevalence of inappropriate medication use among older adults: A review highlighting the importance of screening methods and database types.

The global older population is growing rapidly, and the rise in polypharmacy has increased potentially inappropriate medication (PIM) encounters. PIMs pose health risks, but detecting them automatically in large medical databases is complex. This review aimed to uncover PIM prevalence in individuals aged 65 years or older using health databases and emphasized the risk of underestimating PIM prevalence due to underutilization of detection tools. This study conducted a broad search on the Medline database to identify articles about the prevalence of PIMs in older adults using various databases. Articles published between January 2010 and June 2023 were included, and specific criteria were applied for study selection. Two literature reviews conducted before our study period were integrated to obtain a perspective from the 1990s to the present day. The selected papers were analysed for variables including database type, screening method, adaptations and PIM prevalence. The study categorized databases and original screening tools for clarity, examined adaptations and assessed concordance among different screening methods. This study encompassed 48 manuscripts, covering 58 sample evaluations. The mean prevalence of PIMs within the general population aged over 65 years was 27.8%. Relevant heterogeneity emerged in both the utilized databases and the detection methods. Adaptation of original screening tools was observed in 86.2% (50/58) of cases. Half of the original screening tools used for assessing PIMs belonged to the simple category. About a third of the studies employed less than half of the original criteria after adaptation. Only three studies used over 75% of the original criteria and more than 50 criteria. This extensive review highlights PIM prevalence among the older adults, emphasizing method intricacies and the potential for underestimation due to data limitations and algorithm adjustments. The findings call for enhanced methodologies, transparent algorithms and a deeper understanding of intricate rules' impact on public health implications.

In Search of the Best Low-Cost Methods for Efficient Screening of Conformers.

Locating the lowest energy conformer is crucial for the accurate computation of equilibrium properties of molecular systems. This paper examines the performance of efficient low-cost methods in terms of the alignment and relative energies of their energy minima against the benchmark revDSD-PBEP86-D4/def2-TZVPP//MP2/cc-pVTZ potential energy surface. The low-cost methods considered include GFN-FF, GFN2-xTB, DFTB3, HF-3c, B97-3c, PBEh-3c, and r2SCAN-3c composite methods against a diverse test set of 20 compounds including alkanes, perfluoroalkyl molecules, peptides, open-shell radicals, and Zn(II) complexes of varying sizes. The "3c" composite methods are generally more accurate, but are at least 2-3 orders of magnitude more expensive than tight-binding methods which have energy minima that align well with the benchmark potential energy surface. The findings of this paper were further exploited to introduce a simple strategy involving Grimme's CENSO energy-sorting algorithm that resulted in up to an order of magnitude reduction in computational time for locating the lowest energy conformer on the revDSD-PBEP86-D4/def2-TZVPP//MP2/cc-pVTZ surface.

The Construction and Application of a New Screening Method for Phosphodiesterase Inhibitors

The Construction and Application of a New Screening Method for Phosphodiesterase Inhibitors

A High-throughput Response to the SARS-CoV-2 Pandemic.

Four years after the beginning of the COVID-19 pandemic, it is important to reflect on the events that have occurred during that time and the knowledge that has been gained. The response to the pandemic was rapid and highly resourced; it was also built upon a foundation of decades of federally funded basic and applied research. Laboratories in government, pharmaceutical, academic, and non-profit institutions all played roles in advancing pre-2020 discoveries to produce clinical treatments. This perspective provides a summary of how the development of high-throughput screening methods in a biosafety level 3 (BSL-3) environment at Southern Research Institute (SR) contributed to pandemic response efforts. The challenges encountered are described, including those of a technical nature as well as those of working under the pressures of an unpredictable virus and pandemic.

An Inhibitor-Monitorable Single-Tube Duplex Quantitative Real-Time PCR Assay for the Detection of 'Candidatus Liberibacter asiaticus'.

Huanglongbing (HLB) is a citrus infectious disease caused by 'Candidatus Liberibacter' spp. Recently, it has begun to spread rapidly worldwide, causing significant losses to the citrus industry. Early diagnosis of HLB relies on quantitative real-time PCR assays. However, the PCR inhibitors found in the nucleic acid extracted from plant materials pose challenges for PCR assays because they may result in false-negative results. Internal standard (IS) can be introduced to establish a single-tube duplex PCR for monitoring the influence of the PCR inhibitor, but it also brings the risk of false-negative results because the amplification of IS may compete with the target. To solve this problem, we proposed a mutation-enhanced single-tube duplex PCR (mSTD-PCR) containing IS with mutant-type primers. By introducing the 3'-terminal mutation in the primer of IS to weaken its amplification reaction and its inhibition of 'Candidatus Liberibacter asiaticus' (CLas) detection, the sensitivity and quantitative accuracy of CLas detection will not be affected by IS. In evaluating the sensitivity of CLas detection using simulation samples, the mSTD-PCR showed consistent sensitivity at 25 copies per test compared with the single-plex CLas assay. The detection result of 30 leaves and 30 root samples showed that the mSTD-PCR could recognize false-negative results caused by the PCR inhibitors and reduce workload by 48% compared with the single-plex CLas assay. Generally, the proposed mSTD-PCR provides a reliable, efficient, inhibitor-monitorable, quantitative screening method for accurately controlling HLB and a universal method for establishing a PCR assay for various pathogens.

A “twelve-section ultrasonic screening and diagnosis method” and management system for screening and treating neonatal congenital heart disease at the grassroots level in Tang County, Hebei Province, China

BackgroundTo explore a method for screening and diagnosing neonatal congenital heart disease (CHD) applicable to grassroots level, evaluate the prevalence of CHD, and establish a hierarchical management system for CHD screening and treatment at the grassroots level.MethodsA total of 24,253 newborns born in Tang County between January 2016 and December 2020 were consecutively enrolled and screened by trained primary physicians via the “twelve-section ultrasonic screening and diagnosis method” (referred to as the “twelve-section method”). Specialized staff from the CHD Screening and Diagnosis Center of Hebei Children’s Hospital regularly visited the local area for definite diagnosis of CHD in newborns who screened positive. Newborns with CHD were managed according to the hierarchical management system.ResultsThe centre confirmed that, except for 2 newborns with patent ductus arteriosus missed in the diagnosis of ventricular septal defect combined with severe pulmonary hypertension, newborns with other isolated or concomitant simple CHDs were identified at the grassroots level. The sensitivity, specificity and diagnostic coincidence rate of the twelve-section method for screening complex CHD were 92%, 99.6% and 84%, respectively. A total of 301 children with CHD were identified. The overall CHD prevalence was 12.4‰. According to the hierarchical management system, 113 patients with simple CHD recovered spontaneously during local follow-up, 48 patients continued local follow-up, 106 patients were referred to the centre for surgery (including 17 patients with severe CHD and 89 patients with progressive CHD), 1 patient died without surgery, and 8 patients were lost to follow-up. Eighteen patients with complex CHD were directly referred to the centre for surgery, 3 patients died without surgery, and 4 patients were lost to follow-up. Most patients who received early intervention achieved satisfactory results. The mortality rate of CHD was approximately 28.86 per 100,000 children.ConclusionsThe “twelve-section method” is suitable for screening neonatal CHD at the grassroots level. The establishment of a hierarchical management system for CHD screening and treatment is conducive to the scientific management of CHD, which has important clinical and social significance for early detection, early intervention, reduction in mortality and improvement of the prognosis of complex and severe CHDs.

Cost-Effectiveness Analysis of Digital Breast Tomosynthesis and Mammography in Breast Cancer Screening: A Markov Modeling Study.

Mammography (MG) has demonstrated its effectiveness in diminishing mortality and advanced-stage breast cancer incidences in breast screening initiatives. Notably, research has accentuated the superior diagnostic efficacy and cost-effectiveness of digital breast tomosynthesis (DBT). However, the scope of evidence validating the cost-effectiveness of DBT remains limited, prompting a requisite for more comprehensive investigation. The present study aimed to rigorously evaluate the cost-effectiveness of DBT plus MG (DBT-MG) compared to MG alone within the framework of Taiwan's National Health Insurance program. All parameters for the Markov decision tree model, encompassing event probabilities, costs, and utilities (quality-adjusted life years, QALYs), were sourced from reputable literature, expert opinions, and official records. With 10,000 iterations, a 2-year cycle length, a 30-year time horizon, and a 2% annual discount rate, the analysis determined the incremental cost-effectiveness ratio (ICER) to compare the cost-effectiveness of the two screening methods. Probabilistic and one-way sensitivity analyses were also conducted to demonstrate the robustness of findings. The ICER of DBT-MG compared to MG was US$5971.5764/QALYs. At a willingness-to-pay (WTP) threshold of US$33,004 (Gross Domestic Product of Taiwan in 2021) per QALY, more than 98% of the probabilistic simulations favored adopting DBT-MG versus MG. The one-way sensitivity analysis also shows that the ICER depended heavily on recall rates, biopsy rates, and positive predictive value (PPV2). DBT-MG shows enhanced diagnostic efficacy, potentially diminishing recall costs. While exhibiting a higher biopsy rate, DBT-MG aids in the detection of early-stage breast cancers, reduces recall rates, and exhibits notably superior cost-effectiveness.

Serum IL-24 combined with CA125 as screening and prognostic biomarkers for NSCLC.

Noninvasive and effective methods for early screening of non-small cell lung cancer(NSCLC) still need to be developed. At present, a reasonable conclusion is that a combination of tumor markers is a superior predictor of screening. Cytokines, as important regulators of cancer development, have great potential for the screening and prognosis of NSCLC. This study screened novel biomarkers related to the early screening and prognosis of NSCLC. In the present study, the biological significance and immunoregulation of interleukin-24(IL-24) were analyzed based on The Cancer Genome Atlas data. Next, 150 serum samples from initially treated patients with NSCLC and 70 controls were collected, and we obtained pathological sections from 60 patients with NSCLC. The ELISA and immunohistochemistryresults showed the differential expression of IL-24 and carbohydrate antigen 125(CA125). The results show that IL-24 is an important tumor suppressor in NSCLCthat helps to improve the poor prognosis of these patients. A significantly negative correlation between IL-24 and CA125 levels was also found. Notably, serum IL-24 levels were significantly negatively correlated with the TNM stage of patients with NSCLC, consistent with an important role for tumor suppressors in NSCLC. The receiver operating characteristic curve analysis showed that a combination of IL-24 and CA125 was an effective panel for discriminating patients with NSCLC from HD, and individuals with other lung diseases. Serum IL-24 and CA125 levels were identified as independent prognostic markers for NSCLC. The IL-24 and CA125 panel exhibited good performance in the screening of NSCLC.

Ultrasound image-based nomogram combining clinical, radiomics, and deep transfer learning features for automatic classification of ovarian masses according to O-RADS

BackgroundAccurate and rapid discrimination between benign and malignant ovarian masses is crucial for optimal patient management. This study aimed to establish an ultrasound image-based nomogram combining clinical, radiomics, and deep transfer learning features to automatically classify the ovarian masses into low risk and intermediate-high risk of malignancy lesions according to the Ovarian- Adnexal Reporting and Data System (O-RADS).MethodsThe ultrasound images of 1,080 patients with 1,080 ovarian masses were included. The training cohort consisting of 683 patients was collected at the South China Hospital of Shenzhen University, and the test cohort consisting of 397 patients was collected at the Shenzhen University General Hospital. The workflow included image segmentation, feature extraction, feature selection, and model construction.ResultsThe pre-trained Resnet-101 model achieved the best performance. Among the different mono-modal features and fusion feature models, nomogram achieved the highest level of diagnostic performance (AUC: 0.930, accuracy: 84.9%, sensitivity: 93.5%, specificity: 81.7%, PPV: 65.4%, NPV: 97.1%, precision: 65.4%). The diagnostic indices of the nomogram were higher than those of junior radiologists, and the diagnostic indices of junior radiologists significantly improved with the assistance of the model. The calibration curves showed good agreement between the prediction of nomogram and actual classification of ovarian masses. The decision curve analysis showed that the nomogram was clinically useful.ConclusionThis model exhibited a satisfactory diagnostic performance compared to junior radiologists. It has the potential to improve the level of expertise of junior radiologists and provide a fast and effective method for ovarian cancer screening.

Determinants of survival and recurrence in patients with stage I colorectal cancer

BackgroundDue to the novel advanced screening methods, the number of patients diagnosed with stage I colorectal cancer (CRC) is increasing. This retrospective cohort study aimed to identify recurrence and survival risk factors of patients with stage I CRC after surgery.Materials and methodsPatients with stage I CRC were evaluated, and their demographic and clinicopathologic variables were recorded. The log-rank test assessed the association of variables with overall survival (OS), recurrence-free survival (RFS), local recurrence, and distant metastasis.ResultsThe median overall survival period was 51 months. The recurrence rate was 13.7%: 7.2% local and 9.3% distant recurrence. One-, two-, three-, and five-year RFS were 92%, 89%, 87%, and 83%, respectively, and OS were 96%, 93%, 90%, and 89%, respectively. Local and distant recurrence rates were higher in patients with higher tumor grades. Additionally, RFS and OS were worse in patients with higher tumor grades, and perforation was associated with worse OS.ConclusionsThe determinants of survival and recurrence identified in the present study can be used to improve patient outcomes by early diagnosis and appropriate management of high-risk patients.

Exploring breast cancer screening fear through a psychosocial lens.

Breast cancer screening is crucial for early detection and treatment. Yet, underutilization persists due to various psychosocial factors. This manuscript delves into the multifaceted fears that hinder screening adherence. The literature provides a framework categorizing breast cancer screening fears into generalized cancer fear, fear of screening components, and fear of screening outcomes. In this review, we explore fear of screening components (concerns regarding radiation, discomfort, and pain) and fear of screening outcomes (disability and mortality apprehension, treatment fears, obligation anxiety, and financial concerns) as undesirable, and potentially addressable, aspects of breast cancer screening fear. False-positive results exacerbate these anxieties, prolonging distress and impacting patients' lives beyond the screening process. Addressing these concerns requires reframing current screening approaches to prioritize patient comfort, cultural sensitivity, and accessibility. To address current psychosocial challenges in breast cancer screening, this manuscript advocates for modifying breast cancer screening methods to improve adherence and patient well-being.

Research on Estimation Model of Carbon Stock Based on Airborne LiDAR and Feature Screening

The rapid and accurate estimation of forest carbon stock is important for analyzing the carbon cycle. In order to obtain forest carbon stock efficiently, this paper utilizes airborne LiDAR data to research the applicability of different feature screening methods in combination with machine learning in the carbon stock estimation model. First, Spearman’s Correlation Coefficient (SCC) and Extreme Gradient Boosting tree (XGBoost) were used to screen out the variables that were extracted via Airborne LiDAR with a higher correlation with carbon stock. Then, Bagging, K-nearest neighbor (KNN), and Random Forest (RF) were used to construct the carbon stock estimation model. The results show that the height statistical variable is more strongly correlated with carbon stocks than the density statistical variables are. RF is more suitable for the construction of the carbon stock estimation model compared to the instance-based KNN algorithm. Furthermore, the combination of the XGBoost algorithm and the RF algorithm performs best, with an R2 of 0.85 and an MSE of 10.74 on the training set and an R2 of 0.53 and an MSE of 21.81 on the testing set. This study demonstrates the effectiveness of statistical feature screening methods and Random Forest for carbon stock estimation model construction. The XGBoost algorithm has a wider applicability for feature screening.

Opportunistic prediction of osteoporosis in patients with degenerative lumbar diseases: a simplified T12 vertebral bone quality approach

BackgroundOsteoporosis is one of the risk factors for screw loosening after lumbar fusion. However, the probability of preoperative osteoporosis screening in patients with lumbar degenerative disease is low. Therefore, the aim of this study was to investigate whether a simplified vertebral bone quality (VBQ) score based on T12 T1-MRI could opportunistically predict osteoporosis in patients with degenerative lumbar spine diseases.MethodsWe retrospectively analyzed cases treated for lumbar degenerative diseases at a single institution between August 2021 and June 2022. The patients were divided into three groups by the lowest T-score: osteoporosis group, osteopenia group, and normal bone mineral density (BMD) group. The signal intensity based on the T12 vertebral body divided by the signal intensity of the cerebrospinal fluid was calculated to obtain the simplified VBQ score, as well as the CT-based T12HU value and the traditional L1-4VBQ score. Various statistical analyses were used to compare VBQ, HU and DEXA, and the optimal T12VBQ threshold for predicting osteoporosis was obtained by plotting the receiver operating curve (ROC) analysis.ResultsTotal of 166 patients were included in this study. There was a statistically significant difference in T12VBQ scores between the three groups (p < 0.001). Pearson correlation showed that there was a moderate correlation between T12VBQ and T-score (r=-0.406, p < 0.001). The AUC value of T12VBQ, which distinguishes between normal and low BMD, was 0.756, and the optimal diagnostic threshold was 2.94. The AUC value of T12VBQ, which distinguishes osteoporosis from non-osteoporosis, was 0.634, and the optimal diagnostic threshold was 3.18.ConclusionT12VBQ can be used as an effective opportunistic screening method for osteoporosis in patients with lumbar degenerative diseases. It can be used as a supplement to the evaluation of DEXA and preoperative evaluation.Trial registrationretrospectively registered number:1502-009-644; retrospectively registered number date:27 oct 2022.

Prostate cancer biomarkers: from early diagnosis to precision treatment.

Prostate cancer (PCa) is the second most prevalent cancer in men. In 2020, approximately 1,414,259 new cases were reported that accounted for 3,75,324 deaths (Sung et al. in CA 71:209-249, 2021). PCa is often asymptomatic at early stages; hence, routine screening and monitoring based on reliable biomarkers is crucial for early detection and assessment of cancer progression. Early diagnosis of disease is key step in reducing PCa-induced mortality. Biomarkers such as PSA have played vital role in reducing recent PCa deaths. Recent research has identified many other biomarkers and also refined PSA-based tests for non-invasive diagnosis of PCa in patients. Despite progress in screening methods, an important issue that influences treatment is heterogeneity of the cancer in different individuals, necessitating personalized treatment. Currently, focus is to identify biomarkers that can accurately diagnose PCa at early stage, indicate the stage of the disease, metastatic nature and chances of survival based on individual patient profile (Fig.1). Fig.1 Graphical abstract.

Leveraging the Fragment Molecular Orbital and MM-GBSA Methods in Virtual Screening for the Discovery of Novel Non-Covalent Inhibitors Targeting the TEAD Lipid Binding Pocket

Leveraging the Fragment Molecular Orbital and MM-GBSA Methods in Virtual Screening for the Discovery of Novel Non-Covalent Inhibitors Targeting the TEAD Lipid Binding Pocket

Nucleic acid aptamer-based electrochemical sensor for the detection of serum P-tau231 and the instant screening test of Alzheimer's disease.

The instant screening of patients with a tendency towards developing Alzheimer's disease (AD) is significant for providing preventive measures and treatment. However, the current imaging-based technology cannot meet the requirements in the early stage. Developing biosensor-based liquid biopsy technology could be overcoming this bottleneck problem. Herein, we developed a simple, low-cost, and sensitive electrochemical aptamer biosensor for detecting phosphorylated tau protein threonine 231 (P-tau231), the earliest and one of the most efficacious abnormally elevated biomarkers of AD. Gold nanoparticles (AuNPs) were electrochemically synthesized on a glassy carbon electrode as the transducer, exhibiting excellent conductivity, and were applied to amplify the electrochemical signal. A nucleic acid aptamer was designed as the receptor to capture the P-tau231 protein, specifically through the formation of an aptamer-antigen complex. The proposed biosensor showed excellent sensitivity in detecting P-tau 231, with a broad linear detection range from 10 to 107pg/mL and a limit of detection (LOD) of 2.31pg/mL. The recoveries of the biosensor in human serum ranged from 97.59 to 103.26%, demonstrating that the biosensor could be used in complex practical samples. In addition, the results showed that the developed biosensor has good repeatability, reproducibility, and stability, which provides a novel method for the early screening of AD.

Framework for a High-Throughput Screening Method to Assess Polymer/Plasticizer Miscibility: The Case of Hydrocarbons in Polyolefins

Framework for a High-Throughput Screening Method to Assess Polymer/Plasticizer Miscibility: The Case of Hydrocarbons in Polyolefins