Screening Experiments Research Articles

Enhancing cation and anion exchange capacity of rice straw biochar by chemical modification for increased plant nutrient retention

Biochar, a potential alternative of infield crop residue burning, can prevent nutrient leaching from soil and augment soil fertility. However, pristine biochar contains low cation (CEC) and anion (AEC) exchange capacity. This study developed fourteen engineered biochar by treating a rice straw biochar (RBC-W) first separately with different CEC and AEC enhancing chemicals, and then with their combined treatments to increase CEC and AEC in the novel biochar composites. Following a screening experiment, promising engineered biochar, namely RBC-W treated with O3-HCl-FeCl3 (RBC-O-Cl), H2SO4-HNO3-HCl-FeCl3 (RBC-A-Cl), and NaOH-Fe(NO3)3(RBC-OH-Fe), underwent physicochemical characterization and soil leaching-cum nutrient retention studies. RBC-O-Cl, RBC-A-Cl, and RBC-OH-Fe recorded a spectacular rise in CEC and AEC over RBC-W. All the engineered biochar remarkably reduced the leaching of NH4+-N, NO3− -N, PO43−-P and K+ from a sandy loam soil and increased retention of these nutrients. RBC-O-Cl at 4.46 g kg−1 dosage emerged as the most effective soil amendment increasing the retention of above ions by 33.7, 27.8, 15.0, and 5.74 % over a comparable dose of RBC-W. The engineered biochar could thus enhance plants' nutrient use efficiency and reduce the use of costly chemical fertilizers that are harmful to environmental quality.

Improving the Modeling of Extracellular Ligand Binding Pockets in RosettaGPCR for Conformational Selection.

G protein-coupled receptors (GPCRs) are the largest class of drug targets and undergo substantial conformational changes in response to ligand binding. Despite recent progress in GPCR structure determination, static snapshots fail to reflect the conformational space of putative binding pocket geometries to which small molecule ligands can bind. In comparative modeling of GPCRs in the absence of a ligand, often a shrinking of the orthosteric binding pocket is observed. However, the exact prediction of the flexible orthosteric binding site is crucial for adequate structure-based drug discovery. In order to improve ligand docking and guide virtual screening experiments in computer-aided drug discovery, we developed RosettaGPCRPocketSize. The algorithm creates a conformational ensemble of biophysically realistic conformations of the GPCR binding pocket between the TM bundle, which is consistent with a knowledge base of expected pocket geometries. Specifically, tetrahedral volume restraints are defined based on information about critical residues in the orthosteric binding site and their experimentally observed range of Cα-Cα-distances. The output of RosettaGPCRPocketSize is an ensemble of binding pocket geometries that are filtered by energy to ensure biophysically probable arrangements, which can be used for docking simulations. In a benchmark set, pocket shrinkage observed in the default RosettaGPCR was reduced by up to 80% and the binding pocket volume range and geometric diversity were increased. Compared to models from four different GPCR homology model databases (RosettaGPCR, GPCR-Tasser, GPCR-SSFE, and GPCRdb), the here-created models showed more accurate volumes of the orthosteric pocket when evaluated with respect to the crystallographic reference structure. Furthermore, RosettaGPCRPocketSize was able to generate an improved realistic pocket distribution. However, while being superior to other homology models, the accuracy of generated model pockets was comparable to AlphaFold2 models. Furthermore, in a docking benchmark using small-molecule ligands with a higher molecular weight between 400 and 700 Da, a higher success rate in creating native-like binding poses was observed. In summary, RosettaGPCRPocketSize can generate GPCR models with realistic orthosteric pocket volumes, which are useful for structure-based drug discovery applications.

Marine picocyanobacterial PhnD1 shows specificity for various phosphorus sources but likely represents a constitutive inorganic phosphate transporter

Despite being fundamental to multiple biological processes, phosphorus (P) availability in marine environments is often growth-limiting, with generally low surface concentrations. Picocyanobacteria strains encode a putative ABC-type phosphite/phosphate/phosphonate transporter, phnDCE, thought to provide access to an alternative phosphorus pool. This, however, is paradoxical given most picocyanobacterial strains lack known phosphite degradation or carbon-phosphate lyase pathway to utilise alternate phosphorus pools. To understand the function of the PhnDCE transport system and its ecological consequences, we characterised the PhnD1 binding proteins from four distinct marine Synechococcus isolates (CC9311, CC9605, MITS9220, and WH8102). We show the Synechococcus PhnD1 proteins selectively bind phosphorus compounds with a stronger affinity for phosphite than for phosphate or methyl phosphonate. However, based on our comprehensive ligand screening and growth experiments showing Synechococcus strains WH8102 and MITS9220 cannot utilise phosphite or methylphosphonate as a sole phosphorus source, we hypothesise that the picocyanobacterial PhnDCE transporter is a constitutively expressed, medium-affinity phosphate transporter, and the measured affinity of PhnD1 to phosphite or methyl phosphonate is fortuitous. Our MITS9220_PhnD1 structure explains the comparatively lower affinity of picocyanobacterial PhnD1 for phosphate, resulting from a more limited H-bond network. We propose two possible physiological roles for PhnD1. First, it could function in phospholipid recycling, working together with the predicted phospholipase, TesA, and alkaline phosphatase. Second, by having multiple transporters for P (PhnDCE and Pst), picocyanobacteria could balance the need for rapid transport during transient episodes of higher P availability in the environment, with the need for efficient P utilisation in typical phosphate-deplete conditions.

Fabrication of Omniphobic‐Omniphilic Micropatterns using GPOSS‐PDMS Coating

AbstractSurfaces with special wettability properties, such as omniphobicity or omniphilicity, are essential for functional devices that use both aqueous and organic media. Micropatterning of omniphobic and omniphilic properties can provide a wide range of applications, including miniaturized experiments using both aqueous and organic media. Herein, an approach for creating omniphobic‐omniphilic micropatterns based on selective photoacid polymerization of octa(3‐glycidyloxypropyl) polyhedral oligomeric silsesquioxane modified with mono‐aminopropyl‐terminated polydimethylsiloxane is reported. The composition of the polymeric coatings using infrared spectroscopy; patterning accuracy using atomic force microscopy and scanning electron microscopy; wettability characteristics of the omniphobic, and omniphilic surfaces using contact angle measurements are studied. The proposed approach allows for single‐step micropatterning (sub‐10 µm) or macropatterning (3 mm). Liquids with surface tensions >22.8 mN m−1 can be confined to the omniphilic areas by the omniphobic borders. C2C12 cells are successfully cultivated in omniphilic areas, demonstrating their cell compatibility. The cells adhere to and grow on the entire surface of the pattern, without any signs of cytotoxicity. However, the strongest adhesion is observed in the omniphilic areas, making it possible to create cell micropatterns in a single step. The proposed method for the fabrication of omniphobic‐omniphilic transparent, mechanically robust, biocompatible patterns can find applications in microfluidics, biotechnology or miniaturized biological screening experiments.

Design of Experiments Study on Scottish Wood Biochars and Process Parameter Influence on Final Biochar Characteristics

Native Scottish wood samples were investigated as potential, locally sourced, raw materials for biochar production. Screening experiments identified pure softwood as the preferable feedstock. Influence of operational parameters, i.e. activating gas flow rate (CO2), heating ramp rate and contact time on final biochar characteristics, was investigated using design of experiments. Surface area and biochar yield were selected as response variables. Minitab was used to define experimental run conditions and suggested an optimal output at 60 min contact time and 15 °C/min ramp rate for maximum responses. The highest surface area (764 m2/g) was achieved at 850 °C from softwood, albeit with a low yield of 15%. Under optimised conditions, the observed surface area was 613 m2/g with ~ 18% yield. Pareto charts suggested no influence of gas flow rate on chosen responses, which correlated well with experimental data. Pore structure was a combination of micro- and mesopores with average pore widths of 3–5 nm and an average point of zero charge of 7.40 ± 0.02. Proximate analysis showed an increase in fixed carbon content from 20%, in the feedstock, to 80%, in the optimised biochar. Morphological analysis showed a layered carbon structure in the biochars. The results show the significance of the selected feedstock as a potential source of biochar material and the relevance of interplay of operational variables in biochar development and their final characteristics.

Impact budgétaire de l'utilisation de l'autotest dans le cadre du programme national de dépistage du cancer du col de l'utérus

ObjectivesA nationwide screening program for cervical cancer (CC) was organized in 2018 as part of the 2014-2019 French cancer plan, with the objective of reducing CC incidence and mortality in France by reaching an 80 % coverage rate. As an alternative to pap smear, vaginal self-sampling (VSS) aimed at identifying high-risk HPV carriage could help to achieve this goal. The objective of the present study is to compare the respective budgetary impacts of several self-sampling strategies. MethodA budget impact model was developed to compare non-use of self-sampling in CC screening to the 5-year costs of 5 VSS strategies viewed from an all-payer perspective. While the first strategy was based on mailing the VSS kit with a reminder to participate in the screening program, the second was based on accompanying the mailed kit with an invitation to participate. The third and fourth strategies were based on providing health professionals with the kit, and thereby offering self-sampling as an alternative to pap smears for women undergoing CC screening and having previously received the kits. Finally, the fifth strategy was based on self-sampling as the one and only CC screening modality. The parameters of the model were based on past screening participation data and experiments in France on organized screening and VSS use. The costs included those of procedures associated with screening and program organization. ResultsAll in all, the costs associated with cervical cancer screening would represent approximately 1 billion euros over 5 years. All strategies would be associated with participation ranging from 81% to 84%, which would represent an increase of 4.7% to 5.2% of lesions diagnosed by screening and a cost reduction between €30M and €87M over 5 years, with the exception of the strategy based on sending the kit (with the reminder associated or not) to the health professionals offering this option (+€23M and +€6M). ConclusionsIn conclusion, the use of self-sampling as an alternative to pap smears for non-participating women would increase participation, with only a moderate budgetary impact and could, in some cases, even induce savings.

Inference of glioblastoma migration and proliferation rates using single time-point images

Cancer cell migration is a driving mechanism of invasion in solid malignant tumors. Anti-migratory treatments provide an alternative approach for managing disease progression. However, we currently lack scalable screening methods for identifying novel anti-migratory drugs. To this end, we develop a method that can estimate cell motility from single end-point images in vitro by estimating differences in the spatial distribution of cells and inferring proliferation and diffusion parameters using agent-based modeling and approximate Bayesian computation. To test the power of our method, we use it to investigate drug responses in a collection of 41 patient-derived glioblastoma cell cultures, identifying migration-associated pathways and drugs with potent anti-migratory effects. We validate our method and result in both in silico and in vitro using time-lapse imaging. Our proposed method applies to standard drug screen experiments, with no change needed, and emerges as a scalable approach to screen for anti-migratory drugs.

Genome-wide association screening and MassARRAY for detection of high-temperature resistance-related SNPs and genes in a hybrid abalone (Haliotis discus hannai ♀ × H. fulgens ♂) based on super genotyping-by-sequencing

High seawater temperatures in summer often lead to high mortality in farmed abalone, which greatly increases the cost of farming. The hybrid abalone (Haliotis discus hannai ♀ × H. fulgens ♂, DF), is one of the main varieties of abalone cultured in Fujian Province, China, to resist the high temperature. In this study, the high-temperature resistance of DF abalones was assessed under 28 °C - 32 °C. 31 °C was applied in the subsequent screening experiments of high-temperature resistant individuals. A total of 614,321 single nucleotide polymorphisms (SNPs) were identified via super genotyping-by-sequencing (S-GBS), and 69 SNPs involved in 42 candidate genes were identified by genome-wide association study (GWAS). In addition, according to gene functional annotation, the locus with the lowest P value was screened within the threshold range (−log10P = 4.98296). The genotyping was verified by Sequenom MassARRAY, and 7 SNPs were proved to be related to high temperature resistance in DF population of 100 individuals. 7 candidate genes (fabp, e3rglg4, rgs2, tanc2x6, osbp1, arsb, and uch1) were identified near these SNPs. Finally, these candidate genes were further proved to be associated with the high-temperature resistance trait of DF by the analysis of differential expression genes between sensitive and tolerant individuals. These candidate genes involved regulatory mechanisms such as cell stability, protein repair, lipid metabolism and immune regulation. Notably, the mechanism by which the e3rglg4 gene was involved in the degradation of abnormally folded proteins of abalone under heat stress, corroborating the reliability of the results of GWAS and Sequenom MassARRA. These results complement the shortage of molecular markers for heat resistance of hybrid abalone, provide a reference for marker-assisted selection (MAS) and accelerate the development of heat-resistant abalone varieties.

BoMyrosinase plays an essential role in sulforaphane accumulation in response to selenite treatment in broccoli

Sulforaphane, a naturally specialized metabolite, plays significant roles in human disease prevention and plant defense. Myrosinase (MY) is a key gene responsible for the catalysis of sulforaphane formation, but the molecular mechanisms through which MY regulates sulforaphane biosynthesis in plants remains largely unknown. Here, we discovered that the change of sulforaphane content in broccoli sprouts caused by exogenous selenite treatments is positively related to BoMY expression. BoMY overexpression in the Arabidopsis thaliana tgg1 mutants could dramatically increase myrosinase activity and sulforaphane content in the rosette leaves of 35S::BoMY/tgg1 and rescue its phenotypes. Moreover, an obvious increase of myrosinase activity and sulforaphane content was displayed in transgenic BoMY-overexpressed broccoli lines. In addition, a 2 033 bp promoter fragment of BoMY was isolated. Yeast one-hybrid (Y1H) library screening experiment uncovered that one bHLH transcription factor, BoFAMA, could directly bind to BoMY promoter to activate its expression, which was further evidenced by Y1H assay and dual-luciferase reporter assay. BoFAMA is a selenite-responsive transcription factor that is highly expressed in broccoli leaves; its protein is solely localized to nucleus. Additionally, genetic evidence suggested that the knockdown of FAMA gene in Arabidopsis thaliana could significantly decrease sulforaphane yield by inhibiting the expression of myrosinase genes. Interestingly, exogenous selenite supply could partially restore the low level of sulforaphane content in transgenic Arabidopsis FAMA-silencing plants. Our findings uncover a novel function of FAMA-MY module in the regulation of selenite-mediated sulforaphane synthesis and provide a new insights into the molecular mechanism by which selenite regulates the accumulation of sulforaphane in plants.

3D-Sensitive Encoding of Pharmacophore Features.

In the presence of structural data, one sometimes need to compare 3D ligands. We design an overlay-free method to rank order 3D molecules in the pharmacophore feature space. The proposed encoding includes only two fittable parameters, is sparse, and is not too high dimensional. At the cost of an additional parameter, to delineate the binding site from a protein-ligand complex, the method can compare binding sites. The method was benchmarked on the LIT-PCBA data set for ligand-based virtual screening experiments and the sc-PDB and a Vertex data set when comparing binding sites. In similarity searches, the proposed method outperforms an open-source software doing optimal superposition of ligand-based pharmacophores and RDKit's 3D pharmacophore fingerprints. When comparing binding sites, the method is competitive with state of the art approaches. On a single CPU core, up to 374,000 ligand/s or 132,000 binding site/s can be rank ordered. The "AutoCorrelation of Pharmacophore Features" open-source software is released at https://github.com/tsudalab/ACP4.

Abstract 2911: Identification of novel CAR transmembrane and endodomains for improved persistence and cytotoxicity of NK cell therapies

Abstract Natural killer cells offer a promising treatment strategy for cancer due to their efficacy and favorable safety profile. However, CAR NK cells in solid tumors have had limited success and considerable efforts are being undertaken to improve their efficacy and persistence. Designing optimal CAR transmembrane and intracellular endodomains may increase expression, strength of activation, co-localization within synapses, and improve functional outcomes. First generation NK CARs had CD8ɑ or CD28 transmembrane domains, similar to CAR T cells. They also included endodomain combinations of CD3ζ, CD28, and 4-1BB, while subsequent generations included combinations of NKG2D, DNAM-1, and 2B4 endodomains, with the intent of incorporating NK-specific activation signals. To identify optimal design sequences for NK-based CARs, we developed an in vitro screening platform based on the functional attributes of NK cells, cytotoxicity and persistence. We designed and synthesized two CAR libraries comprising ~2,700 and ~1,300 endodomains drawn from pairwise combinations of 52 and 36 co-stimulatory motifs, respectively. Through a pooled screening experiment, we identified multiple signaling domains that improved the persistence of NK cells in low cytokine conditions throughout two weeks of re-stimulation. Isolated lines of NK cells expressing the top hits demonstrated higher cytotoxicity both immediately after transfection and after two weeks of re-stimulation with tumor cell lines, validating their improved therapeutic potential. We additionally trained a machine learning model using the counts of signaling domain-binding motifs as features to predict the cytotoxicity and persistence of the screened endodomains. This discriminator model and the feature importance can be used to recommend novel co-stimulatory motif combinations for future screens. Top hits in these screens included co-stimulatory domains known to enhance proliferation, cytotoxicity, and tumor clearance in animal models and commonly used in CAR T cell therapies. We frequently observed these domains in novel combinations or in combination with other endodomains not presently used in CAR T therapies. Additionally, we identified transmembrane domains derived from NK surface receptors that increased the presentation of CAR on the NK cell surface. We subsequently integrated these transmembrane domains with hits from our endodomain screen and again used re-stimulation and cytotoxicity assays to functionally test potentially positive interactions between transmembrane domains and endodomains in CAR-NKs. These screening data are ideal for developing predictive models endodomain combinations that enhance NK cell cytotoxicity and persistence. Our results suggest that this approach can be used to identify CAR structural components tailored to cell type, binder specificity, and tumor microenvironment. Citation Format: Maddie Williams, Aye Chen, Matt Stone, Rebekah Turk, Nora Kearns, Nick Bogard, Lan Guo, Brian Belmont, Mary H. Young, Bryce Daines, Max Darnell. Identification of novel CAR transmembrane and endodomains for improved persistence and cytotoxicity of NK cell therapies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2911.

Abstract 2090: Comprehensive interrogation of gene lists from genome-scale cancer screens with oncoEnrichR

Abstract Genome-scale screening experiments in cancer produce long lists of candidate genes that require extensive interpretation for biological insight and prioritization for follow-up studies. Interrogation of gene lists frequently represents a significant and time-consuming undertaking, in which experimental biologists typically combine results from a variety of bioinformatics resources in an attempt to portray and understand cancer relevance. As a means to simplify and strengthen the support for this endeavor, we have developed oncoEnrichR, a flexible bioinformatics tool that allows cancer researchers to comprehensively interrogate a given gene list along multiple facets of cancer relevance. oncoEnrichR differs from general gene set analysis frameworks through the integration of an extensive set of prior knowledge specifically relevant for cancer, including ranked gene-tumor type associations, literature-supported proto-oncogene and tumor suppressor gene annotations, target druggability data, regulatory interactions, synthetic lethality predictions, as well as prognostic associations, gene aberrations, and co-expression patterns across tumor types. The software produces a structured and user-friendly analysis report as its main output, where versions of all underlying data resources are explicitly logged, the latter being a critical component for reproducible science. We demonstrate the usefulness of oncoEnrichR through interrogation of two candidate lists from proteomic and CRISPR screens. oncoEnrichR is freely available as a web-based workflow hosted by the Galaxy platform (https://oncotools.elixir.no), and can also be accessed as a stand-alone R package (https://github.com/sigven/oncoEnrichR). Citation Format: Sigve Nakken, Sveinung Gundersen, Fabian L. Bernal, Dimitris Polychronopoulos, Eivind Hovig, Jørgen Wesche. Comprehensive interrogation of gene lists from genome-scale cancer screens with oncoEnrichR [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2090.

Abstract 589: Long-term acclimation of target cell lines to tumor microenvironment culture condition provides mechanistic insights into cell therapy effectiveness

Abstract The tumor microenvironment (TME) has several characteristics that distinguish it from normal tissue, including elevated interstitial fluid pressures and hypoxia. To study the effects of TME culture conditions, commonly used target cell lines were serially passaged under hyperbaric and hypoxic conditions for a period of eight weeks. Conventionally expanded parental cell lines (normoxia) were compared against TME-acclimated tumor cell lines (TACTLs; hyperbaric and hypoxic), using RNAseq, ATACseq, and flow cytometry analysis. Commonly used target cell lines for cell therapy development were selected for TME acclimation (SKOV3, A549, JEKO1, and NALM6). TACTLs were generated using an AVATAR system, with culture conditions set at 1% O2 and 2.0 PSI, and serially passaged twice a week for a minimum of 8 weeks. Cell doubling times were measured weekly and compared against parental lines maintained under normoxic culture conditions in a conventional CO2 incubator. In-depth characterization was performed on TME-Acclimated Tumor Cell Lines (TACTLs), utilizing a multi-omic approach. Differential gene expression analysis was performed using RNAseq datasets, and surface biomarkers/targets used for cell therapy development were assessed via nanostring and flow cytometry. Growth kinetics and cell doubling times of TACTLs were initially inhibited during the first two weeks of culture under TME conditions, but eventually reached parity with their normoxia maintained parental cell lines at 6 to 8 weeks, signaling a successful adaptation of the tumor lines to low oxygen and hyperbaric conditions. RNAseq analysis revealed upregulation in glycolytic pathways and epithelial-to-mesenchymal signaling, accompanied by altered metabolic profiles. Surface target expression showed increased expression of checkpoint ligands, such as PD-L1. Cell therapy targets, such as ROR1 were also upregulated in A549 and JEKO1 cell lines passaged under TME. Preliminary drug screening experiments were conducted using checkpoint inhibitors and CAR-T candidates on TACTLs, revealing significant changes in half maximal inhibitory concentration (IC50) when compared to parental tumor lines maintained under normoxia. In summary, acclimation of tumor cell lines to TME culture conditions can provide unique mechanistic insights that can facilitate drug development efforts. Future studies will incorporate TACTLs for CDX tumor models with the goal of identifying cell therapies that work effectively in the tumor microenvironment. Citation Format: James Lim, Albert Wong, Ann Lu, Candy Garcia, Evan Massi, Yewei Xing, Ningchun Liu, Scott Wise. Long-term acclimation of target cell lines to tumor microenvironment culture condition provides mechanistic insights into cell therapy effectiveness [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 589.

MARSY: a multitask deep-learning framework for prediction of drug combination synergy scores.

Combination therapies have emerged as a treatment strategy for cancers to reduce the probability of drug resistance and to improve outcomes. Large databases curating the results of many drug screening studies on preclinical cancer cell lines have been developed, capturing the synergistic and antagonistic effects of combination of drugs in different cell lines. However, due to the high cost of drug screening experiments and the sheer size of possible drug combinations, these databases are quite sparse. This necessitates the development of transductive computational models to accurately impute these missing values. Here, we developed MARSY, a deep-learning multitask model that incorporates information on the gene expression profile of cancer cell lines, as well as the differential expression signature induced by each drug to predict drug-pair synergy scores. By utilizing two encoders to capture the interplay between the drug pairs, as well as the drug pairs and cell lines, and by adding auxiliary tasks in the predictor, MARSY learns latent embeddings that improve the prediction performance compared to state-of-the-art and traditional machine-learning models. Using MARSY, we then predicted the synergy scores of 133722 new drug-pair cell line combinations, which we have made available to the community as part of this study. Moreover, we validated various insights obtained from these novel predictions using independent studies, confirming the ability of MARSY in making accurate novel predictions. An implementation of the algorithms in Python and cleaned input datasets are provided in https://github.com/Emad-COMBINE-lab/MARSY.

Microfluidic Detection of Adenylate Kinase as a Cell Damage Biomarker

In vitro cell cultures are used as models for drug discovery. The detection of cell damage biomarkers such as adenylate kinase (AK) is often used in drug screening and cell biology experiments. A microfluidic platform for AK detection was developed with the capability of detecting the AK resulting from the lysis of 10–100 human colorectal adenocarcinoma HCT116 cells. For this assay, AK was captured on the surface of microbeads integrated into a microfluidic device and optically detected using a fluorescently labelled anti-AK antibody. Microfluidic technologies have in addition been used to develop two- and three-dimensional cell culture models that have the potential to accelerate drug discovery. The microfluidic platform was used to detect the AK resulting from the lysis of HCT116 cells cultivated in a microfluidic biochip, demonstrating the potential for the integration of the miniaturised biosensor with the cell chip.

Improving Students Learning Outcomes and Digital Literacy on Acid-Base Titration Using Titration Screen Experiment Media

<p><span lang="EN-ZA">This study aims to enhance students' digital literacy and learning outcomes in acid-base titration through Titration Screen Experiment Media. The research used a quasi-experimental method with two class samples, including the experimental class utilizing Titration Screen Experiment Media and the control class without it. Data were collected through digital literacy questionnaires and post-test questions evaluating students’ cognitive domain knowledge in acid-base titration. The Multivariate Analysis of Variance (MANOVA) test was used to analyze the data. The results demonstrated that the experimental class, which utilized the Titration Screen Experiment Media, exhibited higher digital literacy levels than the control class and improved learning outcomes in acid-base titration. The average digital literacy score in the experimental class was 56.50, whereas the control class scored 41.70. The experimental class indicated students with intermediate cognitive domain learning outcomes around 84.00, while the control class scored 76.67. These findings suggest that implementing the Titration Screen Experiment Media enhances digital literacy and positively impacts students’ learning outcomes in acid-base titration. Educators can effectively improve students' digital literacy skills by integrating this innovative media into teaching and learning while encouraging their academic achievements in chemistry learning. The research emphasizes the significance of digital literacy in modern education. The practical implication lies in the roles of educators in preparing students’ chemistry digital literacy.</span></p>

A Symbolic Regression Model for the Prediction of Drug Binding to Human Liver Microsomes

It is common practice in the early drug discovery process to conduct in vitro screening experiments using liver microsomes in order to obtain an initial assessment of test compound metabolic stability. Compounds which bind to liver microsomes are unavailable for interaction with the drug metabolizing enzymes. As such, assessment of the unbound fraction of compound available for biotransformation is an important factor for interpretation of in vitro experimental results and to improve prediction of the in vivo metabolic clearance. Various in silico methods have been proposed for the prediction of test compound binding to microsomes, from various simple lipophilicity-based models with moderate performance to sophisticated machine learning models which demonstrate superior performance at the cost of increased complexity and higher data requirements. In this work, we attempt to strike a middle ground by developing easily implementable equations with improved predictive performance. We employ a symbolic regression approach based on a medium-size in-house data set of fraction unbound in human liver microsomes measurements allowing the identification of novel equations with improved performance. We validate the model performance on an in-house held-out test set and an external validation set.

Is designed data collection still relevant in the big data era? – A discussion

Is designed data collection still relevant in the big data era? – A discussion

Comparison of Pronase versus Manual Dechorionation of Zebrafish Embryos for Small Molecule Treatments.

Zebrafish are a powerful animal model for small molecule screening. Small molecule treatments of zebrafish embryos usually require that the chorion, an acellular envelope enclosing the embryo, is removed in order for chemical compounds to access the embryo from the bath medium. For large-scale studies requiring hundreds of embryos, manual dechorionation, using forceps, can be a time-consuming and limiting process. Pronase is a non-specific protease that is widely used as an enzymatic alternative for dechorionating zebrafish embryos. However, whether pronase treatments alter the effects of subsequent small molecule treatments has not been addressed. Here, we provide a detailed protocol for large-scale pronase dechorionation of zebrafish embryos. We tested whether pronase treatment can influence the efficacy of drug treatments in zebrafish embryos. We used a zebrafish model for Duchenne muscular dystrophy (DMD) to investigate whether the efficacies of trichostatin-A (TSA) or salermide + oxamflatin, small molecule inhibitors known to ameliorate the zebrafish dmd muscle degeneration phenotype, are significantly altered when embryos are treated with pronase versus manual dechorionation. We also tested the effects of pronase on the ability of the anthracycline cancer drug doxorubicin to induce cardiotoxicity in zebrafish embryos. When comparing pronase- versus forceps-dechorionated embryos used in these small molecule treatments, we found no appreciable effects of pronase on animal survival or on the effects of the small molecules. The significant difference that was detected was a small improvement in the ability of salermide + oxamflatin to ameliorate the dmd phenotype in pronase-treated embryos when compared with manual dechorionation. Our study supports the use of pronase treatment as a dechorionation method for zebrafish drug screening experiments.

Intra-Domain Residue Coevolution in Transcription Factors Contributes to DNA Binding Specificity.

Understanding the basis of the DNA-binding specificity of transcription factors (TFs) has been of long-standing interest. Despite extensive efforts to map millions of putative TF binding sequences, identifying the critical determinants for DNA binding specificity remains a major challenge. The coevolution of residues in proteins occurs due to a shared evolutionary history. However, it is unclear how coevolving residues in TFs contribute to DNA binding specificity. Here, we systematically collected publicly available data sets from multiple large-scale high-throughput TF-DNA interaction screening experiments for the major TF families with large numbers of TF members. These families included the Homeobox, HLH, bZIP_1, Ets, HMG_box, ZF-C4, and Zn_clus TFs. We detected TF subclass-determining sites (TSDSs) and showed that the TSDSs were more likely to coevolve with other TSDSs than with non-TSDSs, particularly for the Homeobox, HLH, Ets, bZIP_1, and HMG_box TF families. By in silico modeling, we showed that mutation of the highly coevolving residues could significantly reduce the stability of the TF-DNA complex. The distant residues from the DNA interface also contributed to TF-DNA binding activity. Overall, our study gave evidence that coevolved residues relate to transcriptional regulation and provided insights into the potential application of engineered DNA-binding domains and proteins. IMPORTANCE While unraveling DNA-binding specificity of TFs is the key to understanding the basis and molecular mechanism of gene expression regulation, identifying the critical determinants that contribute to DNA binding specificity remains a major challenge. In this study, we provided evidence showing that coevolving residues in TF domains contributed to DNA binding specificity. We demonstrated that the TSDSs were more likely to coevolve with other TSDSs than with non-TSDSs. Mutation of the coevolving residue pairs (CRPs) could significantly reduce the stability of THE TF-DNA complex, and even the distant residues from the DNA interface contribute to TF-DNA binding activity. Collectively, our study expands our knowledge of the interactions among coevolved residues in TFs, tertiary contacting, and functional importance in refined transcriptional regulation. Understanding the impact of coevolving residues in TFs will help understand the details of transcription of gene regulation and advance the application of engineered DNA-binding domains and protein.