RESUMEN

In recombinant protein purification, differences in isoelectric point (pI)/surface charge and hydrophobicity between the product and byproducts generally form the basis for separation. For bispecific antibodies (bsAbs), in many cases the physicochemical difference between product and byproducts is subtle, making byproduct removal considerably challenging. In a previous report, with a bsAb case study, we showed that partition coefficient (Kp) screening for the product and byproducts under various conditions facilitated finding conditions under which effective separation of two difficult-to-remove byproducts was achieved by anion exchange (AEX) chromatography. In the current work, as a follow-up study, we demonstrated that the same approach enabled identification of conditions allowing equally good byproduct removal by mixed-mode chromatography with remarkably improved yield. Results from the current and previous studies proved that separation factor determination based on Kp screening for product and byproduct is an effective approach for finding conditions enabling efficient and maximum byproduct removal, especially in challenging cases.

Asunto(s)

Anticuerpos Biespecíficos , Proteínas Recombinantes , Anticuerpos Biespecíficos/química , Anticuerpos Biespecíficos/aislamiento & purificación , Proteínas Recombinantes/química , Proteínas Recombinantes/genética , Proteínas Recombinantes/aislamiento & purificación , Cromatografía por Intercambio Iónico/métodos , Humanos

RESUMEN

A novel grapevine viroid was discovered in an asymptomatic grapevine of Indian rootstocks. The whole genome sequence of the viroid (370 nt) was determined by high-throughput sequencing as well as RT-PCR followed by cloning and Sanger sequencing. The terminal conserved region (TCR), central conserved region (CCR) upper strand, and CCR lower strand are conserved regions found in the viroid that are unique to the members of the genus Apscaviroid. Based on our findings and the demarcation criteria for viroids, the novel viroid, which we have tentatively named "grapevine yellow speckle viroid 3" is a putative new member of the genus Apscaviroid.

Asunto(s)

Genoma Viral , Secuenciación de Nucleótidos de Alto Rendimiento , Filogenia , Enfermedades de las Plantas , Viroides , Vitis , Vitis/virología , Viroides/genética , Viroides/aislamiento & purificación , Viroides/clasificación , Genoma Viral/genética , Enfermedades de las Plantas/virología , ARN Viral/genética , Secuenciación Completa del Genoma/métodos , Secuencia de Bases

RESUMEN

Programmed death-ligand 1 (PD-L1) on tumor-derived small extracellular vesicles (sEVs) limits therapeutic effectiveness by interacting with the PD-1 receptor on host immune cells. Targeting the secretion of sEV PD-L1 has emerged as a promising strategy to enhance immunotherapy. However, the lack of small-molecule inhibitors poses a challenge for clinical translation. In this study, we developed a target and phenotype dual-driven high-throughput screening strategy that combined virtual screening with nanoflow-based experimental verification. We identified ibuprofen (IBP) as a novel inhibitor that effectively targeted sEV PD-L1 secretion. IBP disrupted the biogenesis and secretion of PD-L1+ sEVs in tumor cells by physically interacting with a critical regulator of sEV biogenesis, hepatocyte growth factor-regulated tyrosine kinase substrate. Notably, the mechanism of action of IBP is distinct from its commonly known targets, cyclooxygenases. Administration of IBP stimulated antitumor immunity and enhanced the efficacy of anti-PD-1 therapy in melanoma and oral squamous cell carcinoma mouse models. To address potential adverse effects, we further developed an IBP gel for topical application, which demonstrated remarkable therapeutic efficacy when combined with anti-PD-1 treatment. The discovery of this specific small inhibitor provides a promising avenue for establishing durable, systemic antitumor immunity.

RESUMEN

Alzheimer's disease (AD) is a neurological condition that progressively impairs cognitive function and results in memory loss. Despite substantial research efforts, little is known about the specific processes driving AD, and there are few proven therapies. Because of their physiological and genetic resemblance to humans, zebrafish (Danio rerio) have become an important model organism for furthering research on AD. This abstract discusses the difficulties faced, looks at the insights currently garnered from zebrafish models, and suggests future research options. AD knowledge has greatly benefited from the use of zebrafish models. Transgenic zebrafish that express human AD-associated genes, such as tau and amyloid precursor protein (APP), display tau neurofibrillary tangles (NFTs) and amyloid-beta (Aß) plaques, two of the disease's main clinical characteristics. These models have clarified the roles of oxidative stress, inflammation, and calcium homeostasis in the course of AD and allowed for the purpose of high-throughput screening of potential therapeutic agents. Understanding the growth and deterioration of neurons has been greatly aided by real-time zebrafish imaging. Fully using zebrafish models in AD research requires addressing a number of issues. The dissimilarities in zebrafish anatomy and physiology from humans, the difficulty of developing models that replicate progressive and late-onset AD (LOAD), and the requirement for standardized procedures to evaluate alterations in zebrafish cognition and behavior are a few issues. Furthermore, variations in the genetic makeup of zebrafish strains might affect the results of experiments. Future directions include developing standardized behavioral assays and cognitive tests, working together to create extensive databases of zebrafish genetic and phenotypic data, and using genetic engineering techniques like CRISPR/Cas9 to create more complex zebrafish models. Combining zebrafish models with other model species helps expedite the conversion of research results into therapeutic applications and offers a more thorough knowledge of AD. To sum up, zebrafish models have made a substantial contribution to Alzheimer's research by offering insightful information on the causes of the illness and possible therapies. By tackling present issues and formulating a planned future path, we can improve the use of zebrafish to decipher the mysteries of Alzheimer's and help create successful treatments.

RESUMEN

High-throughput dynamic imaging of cells and organelles is essential for understanding complex cellular responses. We report Mantis, a high-throughput 4D microscope that integrates two complementary, gentle, live-cell imaging technologies: remote-refocus label-free microscopy and oblique light-sheet fluorescence microscopy. Additionally, we report shrimPy (Smart High-throughput Robust Imaging and Measurement in Python), an open-source software for high-throughput imaging, deconvolution, and single-cell phenotyping of 4D data. Using Mantis and shrimPy, we achieved high-content correlative imaging of molecular dynamics and the physical architecture of 20 cell lines every 15 min over 7.5 h. This platform also facilitated detailed measurements of the impacts of viral infection on the architecture of host cells and host proteins. The Mantis platform can enable high-throughput profiling of intracellular dynamics, long-term imaging and analysis of cellular responses to perturbations, and live-cell optical screens to dissect gene regulatory networks.

RESUMEN

The sensing of and response to ambient chemical gradients by microorganisms via chemotaxis regulates many microbial processes fundamental to ecosystem function, human health, and disease. Microfluidics has emerged as an indispensable tool for the study of microbial chemotaxis, enabling precise, robust, and reproducible control of spatiotemporal chemical conditions. Previous techniques include combining laminar flow patterning and stop-flow diffusion to produce quasi-steady chemical gradients to directly probe single-cell responses or loading micro-wells to entice and ensnare chemotactic bacteria in quasi-steady chemical conditions. Such microfluidic approaches exemplify a trade-off between high spatiotemporal resolution of cell behavior and high-throughput screening of concentration-specific chemotactic responses. However, both aspects are necessary to disentangle how a diverse range of chemical compounds and concentrations mediate microbial processes such as nutrient uptake, reproduction, and chemorepulsion from toxins. Here, we present a protocol for the multiplexed chemotaxis device (MCD), a parallelized microfluidic platform for efficient, high-throughput, and high-resolution chemotaxis screening of swimming microbes across a range of chemical concentrations. The first layer of the two-layer polydimethylsiloxane (PDMS) device comprises a serial dilution network designed to produce five logarithmically diluted chemostimulus concentrations plus a control from a single chemical solution input. Laminar flow in the second device layer brings a cell suspension and buffer solution into contact with the chemostimuli solutions in each of six separate chemotaxis assays, in which microbial responses are imaged simultaneously over time. The MCD is produced via standard photography and soft lithography techniques and provides robust, repeatable chemostimulus concentrations across each assay in the device. This microfluidic platform provides a chemotaxis assay that blends high-throughput screening approaches with single-cell resolution to achieve a more comprehensive understanding of chemotaxis-mediated microbial processes. Key features • Microchannel master molds are fabricated using photolithography techniques in a clean room with a mask aligner to fabricate multilevel feature heights. • The microfluidic device is fabricated from PDMS using standard soft lithography replica molding from the master molds. • The resulting microchannel requires a one-time calibration of the driving inlet pressures, after which devices from the same master molds have robust performance. • The microfluidic platform is optimized and tested for measuring chemotaxis of swimming prokaryotes.

RESUMEN

BACKGROUND: In high-throughput sequencing studies, sequencing depth, which quantifies the total number of reads, varies across samples. Unequal sequencing depth can obscure true biological signals of interest and prevent direct comparisons between samples. To remove variability due to differential sequencing depth, taxa counts are usually normalized before downstream analysis. However, most existing normalization methods scale counts using size factors that are sample specific but not taxa specific, which can result in over- or under-correction for some taxa. RESULTS: We developed TaxaNorm, a novel normalization method based on a zero-inflated negative binomial model. This method assumes the effects of sequencing depth on mean and dispersion vary across taxa. Incorporating the zero-inflation part can better capture the nature of microbiome data. We also propose two corresponding diagnosis tests on the varying sequencing depth effect for validation. We find that TaxaNorm achieves comparable performance to existing methods in most simulation scenarios in downstream analysis and reaches a higher power for some cases. Specifically, it balances power and false discovery control well. When applying the method in a real dataset, TaxaNorm has improved performance when correcting technical bias. CONCLUSION: TaxaNorm both sample- and taxon- specific bias by introducing an appropriate regression framework in the microbiome data, which aids in data interpretation and visualization. The 'TaxaNorm' R package is freely available through the CRAN repository https://CRAN.R-project.org/package=TaxaNorm and the source code can be downloaded at https://github.com/wangziyue57/TaxaNorm .

Asunto(s)

Secuenciación de Nucleótidos de Alto Rendimiento , Microbiota , Microbiota/genética , Secuenciación de Nucleótidos de Alto Rendimiento/métodos , Humanos , Algoritmos

RESUMEN

Daqu is usually produced in an open environment, which makes its quality unstable. The microbial community of Daqu largely determines its quality. Therefore, in order to improve the fermentation characteristics of Daqu, samples were collected from Jinsha County (MT1), Xishui County (MT2), and Maotai Town (MT3) in Guizhou Province to explore the microbial diversity of Daqu and its impact on Daqu's metabolites.Off-target metabolomics was used to detect metabolites, and high-throughput sequencing was used to detect microorganisms. Metabolomics results revealed that MT1 and MT2 had the highest relative fatty acid content, whereas MT3 had the highest organooxygen compound content. Principal component analysis and partial least squares discriminant analysis revealed significant differences in the metabolites among the three groups, followed by the identification of 33 differential metabolites (key metabolites) filtered using the criteria of variable importance in projection >1 and p < 0.001. According to the microbiological results, Proteobacteria was the dominant bacteria phylum in three samples. Gammaproteobacteria was the dominant class in MT1(26.84 %) and MT2(36.54 %), MT3 is Alphaproteobacteria(25.66 %). And Caulobacteraceae was the dominant family per the abundance analysis, MTI was 24.32 %, MT2 and MT3 were 33.71 % and 24.40 % respectively. Three samples dominant fungi phylum were Ascomycota, and dominant fungi family were Thermoascaceae. Pseudomonas showed a significant positive connection with various fatty acyls, according to correlation analyses between dominant microorganisms (genus level) and key metabolites. Fatty acyls and Thermomyces showed a positive correlation, but Thermoascus had the reverse relation. These findings offer a theoretical framework for future studies on the impact of metabolites on Baijiu quality during fermentation.

RESUMEN

The ancient mitochondrial genome of a Siberian roe deer (Capreolus pygargus) coded as NJ26S from Jartai Pass Site was obtained by high throughput sequencing. The damage pattern demonstrated the authenticity and reliability of the ancient DNA data. The length of the mitogenome was 16,357 bp, which contained 13 protein-coding genes, two rRNA genes, 22 tRNA genes, and one control region. The total base composition of the mitochondrial genome is 28.17% A, 25.01% T, 11.89% G, 19.72% C, and 15.21% missing data with an AT composition of 53.18%. A maximum-likelihood phylogenetic tree was recovered including other roe deer sequences under the TIM2 + I + G4 model. This study presents molecular evidence indicating the presence of Capreolus pygargus in the Xinjiang Uygur Autonomous Region in China more than 3,000 years ago.

RESUMEN

High-entropy alloys (HEAs) present both significant potential and challenges for developing efficient electrocatalysts due to their diverse combinations and compositions. Here, we propose a procedural approach that combines high-throughput experimentation with data-driven strategies to accelerate the discovery of efficient HEA electrocatalysts for the hydrogen evolution reaction (HER). This enables the rapid preparation of HEA arrays with various element combinations and composition ratios within a model system. The intrinsic activity of the HEA arrays is swiftly screened using scanning electrochemical cell microscopy (SECCM), providing precise composition-activity data sets for the HEA system. An ensemble machine learning (EML) model is then used to predict the activity database for the composition subspace of the system. Based on these database results, two groups of promising catalysts are recommended and validated through actual electrocatalytic evaluations. This procedural approach, which combines high-throughput experimentation with data-driven strategies, provides a new pathway to accelerate the discovery of efficient HEA electrocatalysts.

RESUMEN

The ongoing co-circulation of multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strains necessitates advanced methods such as high-throughput multiplex pseudovirus systems for evaluating immune responses to different variants, crucial for developing updated vaccines and neutralizing antibodies (nAbs). We have developed a quadri-fluorescence (qFluo) pseudovirus platform by four fluorescent reporters with different spectra, allowing simultaneous measurement of the nAbs against four variants in a single test. qFluo shows high concordance with the classical single-reporter assay when testing monoclonal antibodies and human plasma. Utilizing qFluo, we assessed the immunogenicities of the spike of BA.5, BQ.1.1, XBB.1.5, and CH.1.1 in hamsters. An analysis of cross-neutralization against 51 variants demonstrated superior protective immunity from XBB.1.5, especially against prevalent strains such as "FLip" and JN.1, compared to BA.5. Our finding partially fills the knowledge gap concerning the immunogenic efficacy of the XBB.1.5 vaccine against current dominant variants, being instrumental in vaccine-strain decisions and insight into the evolutionary path of SARS-CoV-2.

Asunto(s)

Anticuerpos Neutralizantes , Anticuerpos Antivirales , COVID-19 , SARS-CoV-2 , SARS-CoV-2/inmunología , SARS-CoV-2/genética , Animales , Humanos , COVID-19/inmunología , COVID-19/virología , Anticuerpos Neutralizantes/inmunología , Anticuerpos Neutralizantes/sangre , Cricetinae , Anticuerpos Antivirales/sangre , Anticuerpos Antivirales/inmunología , Glicoproteína de la Espiga del Coronavirus/inmunología , Glicoproteína de la Espiga del Coronavirus/genética , Vacunas contra la COVID-19/inmunología , Vacunas contra la COVID-19/administración & dosificación , Pruebas de Neutralización/métodos , Fluorescencia , Células HEK293 , Antígenos Virales/inmunología , Anticuerpos Monoclonales/inmunología , Mesocricetus

RESUMEN

This study utilized Fe, Co, Ni elemental powders alongside GH3230 pre-alloyed powder as raw materials, employing high-throughput additive manufacturing based on laser powder bed fusion in situ to alloying technology to fabricate the bulk samples library for GH3230 superalloy efficiently. A quantitative identification algorithm for detecting crack and hole defects in additive manufacturing samples was developed. The primary focus was to analyze the composition variations in specimens at varying Fe, Co, and Ni elemental compositions and their impact on crack formation. Experimental results demonstrated that increased laser power improved element distribution uniformity but it proved to be not significantly effective in reducing crack defects. Moreover, augmented Fe and Co alloying content could not eliminate these defects. However, elevated Ni content led to a decrease in the alloy's solidification cracking index and carbide reduction in solidification products. Notably, a significant reduction in cracks was observed when the Ni content of the alloy reached 63 wt.%, and these defects were nearly eliminated at 67 wt.% Ni content.

RESUMEN

In the field of precision medicine, therapy is optimized individually for each patient, enhancing efficacy while reducing side effects. This involves the identification of promising drug candidates through high-throughput screening on human derived cells in culture. However, screening of drugs which have poor solubility or permeability remains challenging, especially when targeting intracellular components. Therefore, encapsulation of drugs into advanced delivery systems such as nanostructured lipid carries (NLC) becomes necessary. Here we show that the cellular uptake of NLC with different matrix compositions can be assessed in a high-throughput screening system based on acoustic droplet ejection (ADE) technology (Echo liquid handler). Our findings indicate that surface tension and viscosity of the NLC dispersions need to be tailored to enable a reliable ADE transfer. The automated NLC uptake studies indicated that the composition of the matrix, more specifically the amount of oleic acid, significantly influenced cellular uptake. The data obtained were corroborated by imaging based and spectral flow cytometry cellular uptake studies. These findings thus not only provide the basis for a screening tool to rapidly identify the efficacy of NLC uptake but also enable a next step toward precision high-throughput drug screening under consideration of an optimized drug delivery system.

RESUMEN

The interaction between cell surface receptors and their ligands is crucial for intercellular communication. However, current techniques for identifying direct receptor-ligand interactions remain limited. Here, we present a protocol to identify receptors of secreted proteins using a genome-scale CRISPR-Cas9 knockout genetic screening approach. We describe steps for creating a single-guide RNA (sgRNA) lentivirus library, infecting stable Cas9-MCF7 cells, staining with tagged Cholesin, and sorting non-binding cells via flow cytometry. We then detail procedures for extracting DNA, amplifying sgRNAs, and sequencing. For complete details on the use and execution of this protocol, please refer to Hu et al.1.

RESUMEN

BACKGROUND: Over the last decade, increasing attention has been directed to using different substrates as sources of environmental DNA (eDNA) in ecological research. Reports on the use of environmental DNA located on the surface of plant leaves and flowers have highlighted the utility of this DNA source in studies including, but not limited to, biodiversity, invasive species, and pollination ecology. The current study assesses grass inflorescence as a source of eDNA for detecting invertebrate taxa. METHODS AND RESULTS: Inflorescences from four common grass species in a central South African grassland were collected for high-throughput sequencing analysis. Universal COI primers were utilised to detect Metazoan diversity. The sequencing results allowed for the detection of three Arthropoda orders, with most OTUs assigned to fungal taxa (Ascomycota and Basidiomycota). Some biases were detected while observing the relative read abundance (RRA) results. DISCUSSION: The observed biases could be explained by the accidental inclusion of invertebrate specimens during sample collection and DNA extraction. Primer biases towards the amplified taxa could be another reason for the observed RRA results. This study provided insight into the invertebrate community associated with the four sampled grass species. It should be noted that with the lack of negative field controls, it is impossible to rule out the influence of airborne eDNA on the observed diversity associated with each grass species. The lack of the inclusion of PCR and extraction blanks in the sequencing step, as well as the inclusion of negative field controls, including other areas for refinement were highlighted, and suggestions were provided to improve the outcomes of future studies.

Asunto(s)

Código de Barras del ADN Taxonómico , ADN Ambiental , Inflorescencia , Poaceae , Código de Barras del ADN Taxonómico/métodos , Poaceae/genética , ADN Ambiental/genética , Animales , Inflorescencia/genética , Biodiversidad , Monitoreo Biológico/métodos , Secuenciación de Nucleótidos de Alto Rendimiento/métodos , Pradera , Sudáfrica , ADN de Plantas/genética

RESUMEN

Inflammatory responses, leading to fibrosis and potential host rejection, significantly hinder the long-term success and widespread adoption of biomedical implants. The ability to control and investigated macrophage inflammatory responses at the implant-macrophage interface would be critical for reducing chronic inflammation and improving tissue integration. Nonetheless, the systematic investigation of how surface topography affects macrophage polarization is typically complicated by the restricted complexity of accessible nanostructures, difficulties in achieving exact control, and biased preselection of experimental parameters. In response to these problems, we developed a large-scale, high-content combinatorial biophysical cue (CBC) array for enabling high-throughput screening (HTS) of the effects of nanotopography on macrophage polarization and subsequent inflammatory processes. Our CBC array, created utilizing the dynamic laser interference lithography (DLIL) technology, contains over 1 million nanotopographies, ranging from nanolines and nanogrids to intricate hierarchical structures with dimensions ranging from 100 nm to several microns. Using machine learning (ML) based on the Gaussian process regression algorithm, we successfully identified certain topographical signals that either repress (pro-M2) or stimulate (pro-M1) macrophage polarization. The upscaling of these nanotopographies for further examination has shown mechanisms such as cytoskeletal remodeling and ROCK-dependent epigenetic activation to be critical to the mechanotransduction pathways regulating macrophage fate. Thus, we have also developed a platform combining advanced DLIL nanofabrication techniques, HTS, ML-driven prediction of nanobio interactions, and mechanotransduction pathway evaluation. In short, our developed platform technology not only improves our ability to investigate and understand nanotopography-regulated macrophage inflammatory responses but also holds great potential for guiding the design of nanostructured coatings for therapeutic biomaterials and biomedical implants.

Asunto(s)

Aprendizaje Automático , Macrófagos , Macrófagos/metabolismo , Ratones , Animales , Propiedades de Superficie , Células RAW 264.7 , Nanoestructuras/química

RESUMEN

Combinatorial spread libraries offer an approach to explore the evolution of material properties over broad concentration, temperature, and growth parameter spaces. However, the traditional limitation of this approach is the requirement for the read-out of functional properties across the library. Here we develop automated piezoresponse force microscopy (PFM) for the exploration of combinatorial spread libraries and demonstrate its application in the SmxBi1-xFeO3 system with the ferroelectric-antiferroelectric morphotropic phase boundary. This approach relies on the synergy of the quantitative nature of PFM and the implementation of automated experiments that allow PFM-based sampling of macroscopic samples. The concentration dependence of pertinent ferroelectric parameters was determined and used to develop the mathematical framework based on the Ginzburg-Landau theory describing the evolution of these properties across the concentration space. We pose that a combination of automated scanning probe microscope and combinatorial spread library approach will emerge as an efficient research paradigm to close the characterization gap in high-throughput materials discovery. We make the data sets open to the community, and we hope that this will stimulate other efforts to interpret and understand the physics of these systems.

RESUMEN

Luteolin, a commonly used traditional Chinese medicine, has been utilized for several decades in the treatment of hepatocellular carcinoma (HCC). Previous research has demonstrated its anti-tumour efficacy, but its underlying mechanism remains unclear. This study aimed to assess the therapeutic effects of luteolin in H22 tumour-bearing mice. luteolin effectively inhibited the growth of solid tumours in a well-established mouse model of HCC. High-throughput sequencing revealed that luteolin treatment could enhance T-cell activation, cell chemotaxis and cytokine production. In addition, luteolin helped sustain a high ratio of CD8+ T lymphocytes in the spleen, peripheral blood and tumour tissues. The effects of luteolin on the phenotypic and functional changes in tumour-infiltrating CD8+ T lymphocytes were also investigated. Luteolin restored the cytotoxicity of tumour-infiltrating CD8+ T lymphocytes in H22 tumour-bearing mice. The CD8+ T lymphocytes exhibited intensified phenotype activation and increased production of granzyme B, IFN-γ and TNF-α in serum. The combined administration of luteolin and the PD-1 inhibitor enhanced the anti-tumour effects in H22 tumour-bearing mice. Luteolin could exert an anti-tumour immune response by inducing CD8+ T lymphocyte infiltration and enhance the anti-tumour effects of the PD-1 inhibitor on H22 tumour-bearing mice.

Asunto(s)

Linfocitos T CD8-positivos , Carcinoma Hepatocelular , Neoplasias Hepáticas , Luteolina , Linfocitos Infiltrantes de Tumor , Luteolina/farmacología , Luteolina/uso terapéutico , Animales , Linfocitos T CD8-positivos/inmunología , Linfocitos T CD8-positivos/efectos de los fármacos , Carcinoma Hepatocelular/tratamiento farmacológico , Carcinoma Hepatocelular/inmunología , Carcinoma Hepatocelular/patología , Neoplasias Hepáticas/tratamiento farmacológico , Neoplasias Hepáticas/inmunología , Neoplasias Hepáticas/patología , Ratones , Linfocitos Infiltrantes de Tumor/inmunología , Linfocitos Infiltrantes de Tumor/efectos de los fármacos , Linfocitos Infiltrantes de Tumor/metabolismo , Línea Celular Tumoral , Activación de Linfocitos/efectos de los fármacos , Activación de Linfocitos/inmunología , Citocinas/metabolismo , Masculino , Granzimas/metabolismo , Receptor de Muerte Celular Programada 1/antagonistas & inhibidores , Ratones Endogámicos C57BL

RESUMEN

Hydrogen sulfide is a significant byproduct of oil and gas production and is typically recovered as elemental sulfur, a low-value commodity. In recent years, there have been efforts to upgrade H2S through elemental decomposition to S and H2, an essential energy carrier in a sustainable economy. Among the promising approaches is thermocatalytic looping, which involves a sulfide-based redox pair. Unfortunately, the search for sulfides capable of facilitating this conversion is progressing slowly, and primarily focusing on monometallic sulfides. With a few notable exceptions, the field of bimetallic sulfide remains largely unexplored. In this study, a machine learning framework is employed to explore the material space of mono and bimetallic sulfides. The workflow begins by mining sulfides from the Materials Project database, allowing the workflow to be benchmarked using formation enthalpies derived from established density functional theory calculations. Through the machine learning framework, the number of bimetallic sulfide redox pairs considered is expanded from 102 cases in the Materials Project database to 105 cases. This expansion allows for the identification trends that can serve as guidelines for future research and helps prioritize materials for experimental testing.

RESUMEN

Technological advances in drug discovery are exciting to students, but it is challenging for faculty to maintain the pace with these developments, particularly within undergraduate courses. In recent years, a High-throughput Discovery Science and Inquiry-based Case Studies for Today's Students (HITS) Research Coordination Network has been assembled to address the mechanism of how faculty can, on-pace, introduce these advancements. As a part of HITS, our team has developed "Behind the Screen: Drug Discovery using the Big Data of Phenotypic Analysis" to introduce students and faculty to phenotypic screening as a tool to identify inhibitors of diseases that do not have known cellular targets. This case guides faculty and students though current screening methods using statistics and can be applied at undergraduate and graduate levels. Tested across 70 students at three universities and a variety of courses, our case utilizes datasets modeled on a real phenotypic screening method as an accessible way to teach students about current methods in drug discovery. Students will learn how to identify hit compounds from a dataset they have analyzed and understand the biological significance of the results they generate. They are guided through practical statistical procedures, like those of researchers engaging in a novel drug discovery strategy. Student survey data demonstrated that the case was successful in improving student attitudes in their ability to discuss key topics, with both undergraduate and graduate students having a significant increase in confidence. Together, we present a case that uses big data to examine the utility of a novel phenotypic screening strategy, a pedagogical tool that can be customized for a wide variety of courses.