Search

Infertility affects ∼12 % of couples, with environmental chemical exposure as a potential contributor. Of the chemicals that are actively manufactured, very few are assessed for reproductive health effects. Rodents are commonly used to evaluate reproductive effects, which is both costly and time consuming. Thus, there is a pressing need for rapid methods to test a broader range of chemicals. Here, we developed a strategy to evaluate large numbers of chemicals for reproductive toxicity via a yeast, S. cerevisiae high-throughput assay to assess gametogenesis as a potential new approach method (NAM). By simultaneously assessing chemicals for growth effects, we can distinguish if a chemical affects gametogenesis only, proliferative growth only or both. We identified a well-known mammalian reproductive toxicant, bisphenol A (BPA) and ranked 19 BPA analogs for reproductive harm. By testing mixtures of BPA and its analogs, we found that BPE and 17 β-estradiol each together with BPA showed synergistic effects that worsened reproductive outcome. We examined an additional 179 environmental chemicals including phthalates, pesticides, quaternary ammonium compounds and per- and polyfluoroalkyl substances and found 57 with reproductive effects. Many of the chemicals were found to be strong reproductive toxicants that have yet to be tested in mammals. Chemicals having affect before meiosis I division vs. meiosis II division were identified for 16 gametogenesis-specific chemicals. Finally, we demonstrate that in general yeast reproductive toxicity correlates well with published reproductive toxicity in mammals illustrating the promise of this NAM to quickly assess chemicals to prioritize the evaluation for human reproductive harm.

Quantitative analysis of complex mixtures, including compounds having similar chemical properties, is demonstrated using an automatic and high throughput approach to microcrystal electron diffraction (MicroED). Compositional analysis of organic and inorganic compounds can be accurately executed without the need of diffraction standards. Additionally, with sufficient statistics, small amounts of compounds in mixtures can be reliably detected. These compounds can be distinguished by their crystal structure properties prior to structure solution. In addition, if the crystals are of good quality, the crystal structures can be generated on the fly, providing a complete analysis of the sample. MicroED is an effective method for analyzing the structural properties of sub-micron crystals, which are frequently found in small-molecule powders. By developing and using an automatic and high throughput approach to MicroED, and with the use of SerialEM for data collection, data from thousands of crystals allow sufficient statistics to detect even small amounts of compounds reliably.

Heteroleptic (mixed‐ligand) coordination cages are of interest as host systems with more structurally and functionally complex cavities than homoleptic architectures. The design of heteroleptic cages, however, is far from trivial. In this work, we experimentally probed the self‐assembly of Pd(II) ions with binary ligand combinations in a combinatorial fashion to search for new cis‐Pd2L2L’2 heteroleptic cages. A hierarchy of computational analyses was then applied to these systems with the aim of elucidating key factors for rationalising self‐assembly outcomes. Simple and inexpensive geometric analyses were shown to be effective in identifying complementary ligand pairs. Preliminary results demonstrated the viability of relatively rapid semi‐empirical calculations for predicting the topology of thermodynamically favoured assemblies with rigid ligands, whilst more flexible systems proved challenging. Stemming from this, key challenges were identified for future work developing effective computational forecasting tools for self‐assembled metallo‐supramolecular systems. [ABSTRACT FROM AUTHOR]

Active wavelength‐scale optoelectronic components are widely used in photonic integrated circuitry, however coherent sources of light – namely optical lasers – remain the most challenging component to integrate. Semiconductor nanowire lasers (NWLs) represent a flexible class of light source where each nanowire (NW) is both gain material and cavity; however, strong coupling between these properties and the performance leads to inhomogeneity across the population. While this has been studied and optimized for individual material systems, no architecture‐wide insight is available. Here, nine NWL material systems are studied and compared using 55,516 NWLs to provide statistically robust insight into performance. These results demonstrate that, while it may be important to optimize internal quantum efficiency for certain materials, cavity effects are always critical. The study provides a roadmap to optimize the performance of NWLs made from any material: this can be achieved by ensuring a narrow spread of lengths and end‐facet reflectivities. [ABSTRACT FROM AUTHOR]

Flow cytometry is a versatile tool used for cell sorting, DNA content imaging, and determining various cellular characteristics. With the possibility of high-throughput analyses, it combines convenient labelling techniques to serve rapid, quantitative, and qualitative workflows. The ease of sample preparation and the broad range of applications render flow cytometry a preferred approach for many scientific questions. Yet, we lack practical adaptations to fully harness the quantitative and high-throughput capabilities of most cytometers for many organisms. Here, we present simple and advanced protocols for the analysis of total DNA content, de novo DNA synthesis, and protein association to chromatin in budding yeast and human cells. Upon optimization of experimental conditions and choice of fluorescent dyes, up to four parameters can be measured simultaneously and quantitatively for each cell of a population in a multi-well plate format. Reducing sample numbers, plastic waste, costs per well, and hands-on time without compromising signal quality or single-cell accuracy are the main advantages of the presented protocols. In proof-of-principle experiments, we show that DNA content increase in S-phase correlates with de novo DNA synthesis and can be predicted by the presence of the replicative helicase MCM2-7 on genomic DNA. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Contemporary Pediatrics is the property of Xiangya Medical Periodical Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Polysorbates are the predominant surfactants used to stabilize protein formulations. Unfortunately, polysorbates can undergo hydrolytic degradation, which releases fatty acids that can accumulate to form visible particles. The detection and quantitation of these fatty acid degradation products are critical for assessing the extent of polysorbate degradation and the associated risks of particle formation. We previously developed a user-friendly mass spectrometric method called Fatty Acids by Mass Spectrometry (FAMS) to quantify the free fatty acids. The FAMS method was validated according to ICH Q2 (R1) guidelines and is suitable for a wide range of products, buffers and protein concentrations. The end-to-end workflow can be automated from sample preparation to data analysis. To broaden method accessibility, the QDa detector selected for fatty acid measurement does not require specific mass spectrometry experience. We provide here a detailed procedure for both manual and automated sample preparation for high-throughput analysis. In addition, we highlight in this protocol the critical operational details, procedural watchouts and troubleshooting tips to support the successful execution of this method in another laboratory. [ABSTRACT FROM AUTHOR]

[Objectives] The purpose of this paper was to develop a method for the high-throughput determination of 8 sulfonamides, 3 tetracyclines, 2 quinolones and trimethoprim drug residues in pork and chicken tissues by colloidal gold immunochromatographic assay(GICA). [Methods] Sulfonamides, tetracyclines, quinolones and trimethoprim in animal muscle tissues were extracted by phosphate buffer and diluted by phosphate buffer with Tween 20, binding to colloidal gold-labeled monoclonal antibodies and inhibiting the binding of the antibodies to the antigen on the nitrocellulose membrane test line(T-line), which resulted in a change of the color of the T-line. The qualitative determination of poly-veterinary drug residues in the samples was made by comparing the color shades of the T-line and control line(C-line). [Results] This test optimized the key factors such as pH value, antibody addition, antigen encapsulation, Tween 20 addition and type of lyophilized protectant. The limit of detection for sulfonamides, tetracyclines, quinolones and trimethoprim was 50, 100, 50 and 35 μg·kg-1, respectively, and the sensitivity ≥97%, the false positive rate ≤2%, the false negative rate ≤3%, and the method was consistent with the results detected by the existing standard method. [Conclusions] The method was simple with high sensitivity, high precision, short detection time and good stability. It could be used for high-throughput rapid detection of multi-veterinary drug residues in animal muscle tissue. [ABSTRACT FROM AUTHOR]

Image-based digitalization of germplasm stock holds significant promise for accelerating plant breeding and crop improvement. This technology facilitates efficient germplasm characterization, evaluation, and management through the capture and analysis of visual phenotypes. However, widespread adoption is hindered by challenges that include image quality control, data analysis complexity, and phenotypic representation limitations. This study investigated these constraints and proposed strategies to address them. By managing technical challenges, refining phenotypic data extraction, and developing robust data analysis pipelines, researchers can fully leverage image-based digitalization to enhance germplasm utilization and contribute to sustainable agriculture. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Estimating the synthesizability is the prerequisite to discovering novel high‐entropy ceramics with exotic properties. Herein, combined with the high‐throughput experiments and machine learning (ML) methods, the synthesizability of high‐entropy hexaborides (HEB6) is investigated. To construct the database, 100 equimolar quinary HEB6 samples synthesized using a self‐developed high‐throughput solid‐state reaction technique and 20 potential synthesizability descriptors calculated from fundamental parameters of constituent precursors are simultaneously collected. By employing the ML and the genetic algorithms, an optimal model consisting of five synthesizability descriptors (l¯$\bar{l}$, δl${\delta }_l$, δχP${\delta }_{{\chi }^{\mathrm{P}}}$, δI1${\delta }_{{I}_1}$, and δEF${\delta }_{{E}_{\mathrm{F}}}$) is determined for predicting the synthesizability of equimolar HEB6 with a high validation accuracy (93.0%), and 7 005 new equimolar quinary HEB6 are then proposed. Moreover, the applicability of our established model on non‐equimolar HEB6 is explored by the prediction of 30 synthesizability diagrams of non‐equimolar quinary HEB6. A high accuracy of 90.9% is further validated by the synthesis experiments of 11 non‐equimolar HEB6 candidates. Our work establishes an effective ML model for assessing the synthesizability of both equimolar and non‐equimolar HEB6 and paves a promising way to accelerate the discovery of new synthetic accessible high‐entropy ceramics. [ABSTRACT FROM AUTHOR]

Novel natural products (NPs) and their derivatives are important sources for drug discovery, which have been broadly applied in the fields of agriculture, livestock, and medicine, making the synthesis of NPs and their derivatives necessarily important. In recent years, biosynthesis technology has received increasing attention due to its high efficiency in the synthesis of high value-added novel products and its advantages of green, environmental protection, and controllability. In this review, the technological advances of biosynthesis strategies in the discovery of novel NPs and their derivatives are outlined, with an emphasis on two areas of host engineering and in vitro enzymatic synthesis. In terms of hosts engineering, multiple microorganisms, including Streptomyces, Aspergillus, and Penicillium, have been used as the biosynthetic gene clusters (BGCs) provider and host strain for the expression of BGCs to discover new compounds over the past years. In addition, the use of in vitro enzymatic synthesis strategy to generate novel compounds such as triterpenoid saponins and flavonoids is also hereby described. [ABSTRACT FROM AUTHOR]

Nitrocellulose microspheres have garnered extensive use in propellants and launching agents due to their inherent safety, robust flowability, and high explosive power. However, conventional preparation methods for these microspheres are often hampered by complex processes, low safety factor and poor sphericity. This study explores an innovative approach to nitrocellulose microsphere fabrication utilizing microfluidic technology. We designed and assembled two high-throughput preparation devices—a coaxial and a centrifugal device—employing 3D printing technology. Our findings demonstrate an 18-fold increase in efficiency over traditional single-pass microfluidic techniques. Additionally, we examined the impact of these devices on the microspheres' size distribution. The proposed device showcases significant advantages, including reduced cost, enhanced efficiency, and shorter production cycles, indicating promising potential for wide-scale application in nitrocellulose microsphere preparation. [ABSTRACT FROM AUTHOR]

The emergence of blockchain technology, characterized by its immutable and decentralized digital ledger system, has sparked significant interest due to its potential to revolutionize several industries. Simultaneously, Long-Term Evolution (LTE) networks have emerged as the fundamental infrastructure for facilitating high-speed wireless communication. The correlation between these two technologies is still a subject that has yet to be well studied despite its potential significance for addressing the scalability issues of blockchain. The article aimed to explore the possible advantages and improvements that might arise from integrating Long-Term Evolution (LTE) networks into blockchain systems, with a specific emphasis on scalability, reliability, and efficiency. This study introduced a unique framework, incorporating Long-Term Evolution (LTE) as a supplementary communication layer to enhance the current Peer-to-Peer (P2P) blockchain architecture. The comprehensive studies included powerful simulation models, practical testing, and comparison analysis against widely used scaling options such as Layer 2 protocols and sharding. Results: The experimental findings indicate that integrating LTE technology with blockchain resulted in a substantial increase in transaction throughput and a noteworthy decrease in confirmation times. Significantly, this innovation did not compromise the inherent decentralized character of the blockchain. Moreover, the LTE-augmented blockchain exhibits a higher resilience level than conventional blockchain systems when faced with common network risks, like Sybil and Eclipse assaults. Long-Term Evolution (LTE) networks in blockchain systems create a collaborative telecom-blockchain framework. This combination could benefit banking, supply chain management, and the Internet of Things. The findings show that LTE networks help blockchain technology scale and survive.

This work aimed to develop a high-throughput analytical method based on QuEChERS coupled with ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) for the determination of 13 mycotoxins in plant-solid beverages. The samples were homogenized and dissolved in water. QuEChERS method was used for pretreatment, ultrasonic extraction with 2% formic acid-acetonitrile solution, and purification with octadecylsilane bonded silica gel (C18). The extraction solution was then separated by a Kinetex F5 column, detected by a tandem mass spectrometry detector in multiple reaction monitoring mode (MRM), and quantified by matrix-matched standard calibration. The optimum conditions achieved limits of detections (LODs) in the range of 0.04~16.9 μg/kg, with correlation coefficient over 0.9916. The limit of quantifications (LOQs) were in the range 0.12~38.2 μg/kg. The recoveries in real plant-solid beverages ranged from 82.2% to 103.3%, with relative standard deviations (RSDs) below 9.0%. Moreover, the proposed method was applied to analyze mycotoxins in 18 plant-solid beverage samples, a positive detection rate of 4/18 was obtained, and the detected analytes included deoxynivalenol and fumonisin B3. This proposed method has the advantages of simple operation, low cost, high sensitivity and accuracy, which can be used for the high-throughput screening of multiple mycotoxins in plant-solid beverages.

Abstract Electrospinning is a specialized processing technique for the formation of submicron diameter fibers of polymeric and ceramic materials using an electrostatic field. The process has multiple advantages over other nano- and micro- fiber synthesis methods; however, generally suffers from very low fabrication speeds, making it undesirable for scalability. This work assesses the performance of a needle-less, self-contained, high throughput electrospinning system. It further compares the fiber fabrication rates obtained versus two single needle setups with different collectors: (i) a conventional single needle and flat plate geometry, and (ii) a single needle with a rotating collector geometry. Polyvinylpyrrolidone (PVP) in ethanol was used as the model material. The fabrication rate of the high throughput system “HTES” was measured at about 2.6 g/h and was about 15 times that collected of the flat plate. Comparing it to other systems reported in the literature also proved it to be a viable option for high throughput, lab scale electrospinning.

Abstract Background The intestinal microbiota plays a significant role in maintaining systemic and intestinal homeostasis, but can also influence diseases such as inflammatory bowel disease (IBD) and cancer. Certain bacterial species within the intestinal tract can chronically activate the immune system, leading to low-grade intestinal inflammation. As a result, plasma cells produce high levels of secretory antigen-specific immunoglobulin A (IgA), which coats the immunostimulatory bacteria. This IgA immune response against intestinal bacteria may be associated with the maintenance of homeostasis and health, as well as disease. Unraveling this dichotomy and identifying the immunostimulatory bacteria is crucial for understanding the relationship between the intestinal microbiota and the immune system, and their role in health and disease. IgA-SEQ technology has successfully identified immunostimulatory, IgA-coated bacteria from fecal material. However, the original technology is time-consuming and has limited downstream applications. In this study, we aimed to develop a next-generation, high-throughput, magnet-based sorting approach (ng-IgA-SEQ) to overcome the limitations of the original IgA-SEQ protocol. Results We show, in various settings of complexity ranging from simple bacterial mixtures to human fecal samples, that our magnetic 96-well plate-based ng-IgA-SEQ protocol is highly efficient at sorting and identifying IgA-coated bacteria in a high-throughput and time efficient manner. Furthermore, we performed a comparative analysis between different IgA-SEQ protocols, highlighting that the original FACS-based IgA-SEQ approach overlooks certain nuances of IgA-coated bacteria, due to the low yield of sorted bacteria. Additionally, magnetic-based ng-IgA-SEQ allows for novel downstream applications. Firstly, as a proof-of-concept, we performed metagenomic shotgun sequencing on 10 human fecal samples to identify IgA-coated bacterial strains and associated pathways and CAZymes. Secondly, we successfully isolated and cultured IgA-coated bacteria by performing the isolation protocol under anaerobic conditions. Conclusions Our magnetic 96-well plate-based high-throughput next-generation IgA-SEQ technology efficiently identifies a great number of IgA-coated bacteria from fecal samples. This paves the way for analyzing large cohorts as well as novel downstream applications, including shotgun metagenomic sequencing, culturomics, and various functional assays. These downstream applications are essential to unravel the role of immunostimulatory bacteria in health and disease. Video Abstract

Diffuse midline glioma (DMG), H3K27-altered, is lethal pediatric-type, high-grade, localized to the midline region of the central nervous system. Effective treatment guidelines are absent, and clinical trials are preferred for primary or recurrent DMG patients. Recently, epigenetic agent-based immunotherapy has exhibited promising therapeutic effects in the clinical setting. However, the underlying mechanisms remain a mystery. The rare DMG tumor samples from biopsy or resection largely impede basic research, by using patient-derived tumor cells which better recapitulate the parental tumor's heterogeneity compared to established cell lines. As an epigenetic reprogramming disease, DMG exhibits a global loss of H3K27 trimethylation (H3K27me3) and a gain of H3K27 acetylation (H3K27ac). Analysis of multiple epigenetic marks is fundamentally necessary. However, traditional techniques cannot allow ultra-low input and high-throughput. Herein we have developed a new method called high-throughput in situ tagged immunoprecipitation sequencing (HiTIP-seq), which uses an integrated superhydrophobic microwell array technology (InSMART). We were able to perform 100 parallel assays from as few as 100 cells per microwell on a single chip. We applied the technology to profile epigenetic alterations of three-dimensional (3D) cell cultures derived from DMG patients. Our HiTIP-seq integrated with RNA sequencing (RNA-seq) analysis revealed that the combination of epigenetic agents (panobinostat and tazemetostat), reprogrammed histone modifications and drove transcriptome changes. Among them, Wnt inhibitory factor 1 (WIF1) has a gain of H3K27ac and a loss of H3K27me3, which leads to the upregulated expression. Altogether, HiTIP-seq is a versatile method for high-throughput analysis of histone modifications, suitable for both DMG research and studying rare 3D models.

Wildlife fecal samples were collected across two Air Force installations to evaluate the effectiveness of commercially available DNA and RNA extraction kits. Four DNA kits, two DNA/RNA kits and one RNA only kit were used. Sample extracts were evaluated on nucleic acid concentration, TapeStation DNA or RNA Integrity Number values and presence of PCR inhibitors. For the DNA kits, PFP produced higher concentrations compared with PLM and RPM, while MWFM gave higher DNA Integrity Number values when compared with RPM. No PCR inhibition was detected. For the RNA kits, RPM gave higher concentrations compared with MWTV and no differences were seen in RNA Integrity Number values. PCR inhibition was observed in all RNA samples, with MWTV exhibiting higher inhibition compared with RPM.

Monoclonal antibodies (mAbs) hold significant potential as therapeutic agents and are invaluable tools in biomedical research. However, the lack of efficient high-throughput screening methods for single antibody-secreting cells (ASCs) has limited the diversity of available antibodies. Here, we introduce a novel, integrated workflow employing self-seeding microwells and an automated microscope-puncher system for the swift, high-throughput screening and isolation of single ASCs. The system allows for the individual screening and isolation of up to 6,400 cells within approximately one day, with the opportunity for parallelization and efficient upscaling. We successfully applied this workflow to both hybridomas and human patient-derived B cells, enabling subsequent clonal expansion or antibody sequence analysis through an optimized, single-cell nested reverse transcription-polymerase chain reaction (RT-PCR) procedure. By providing a time-efficient and more streamlined single ASC screening and isolation process, our workflow holds promise for driving forward progress in mAb development.

Production and storage of synthetic mRNA can introduce a variety of byproducts which reduce the overall integrity and functionality of mRNA vaccines and therapeutics. mRNA integrity is therefore designated as a critical quality attribute which must be evaluated with state-of-the-art analytical methods before clinical use. The current study first demonstrates the effect of heat degradation on transcript translatability and then describes a novel enzymatic approach to assess the integrity of conventional mRNA and long self-amplifying mRNA. By first hybridizing oligo-T to the poly(A) tail of intact mRNA and subsequently digesting the unhybridized RNA fragments with a 3’-5’ exoribonuclease, individual nucleotides can be selectively released from RNA fragments. The adenosine-based fraction of these nucleotides can then be converted into ATP and detected by luminescence as a sensitive indicator of mRNA byproducts. We developed a polynucleotide phosphorylase (PNPase)-based assay that offers fast and sensitive evaluation of mRNA integrity, regardless of its length, thus presenting a novel and fully scalable alternative to chromatographic-, electrophoresis-, or sequencing-based techniques.

Porphyromonas gingivalis is a keystone pathogen in periodontitis, and Streptococcus sanguinis is an abundant oral commensal bacterium associated with periodontal health. However, the interaction between P. gingivalis and S. sanguinis remains obscure. Here, we established a strategy for high‐throughput measurement of the cell number of P. gingivalis in the coculture with S. sanguinis by detecting the concentration of hydrogen sulfate. The interaction between P. gingivalis and over 2000 S. sanguinis single‐gene mutants was characterized using this strategy, and several interaction‐associated genes in S. sanguinis were determined by detecting more P. gingivalis cells in the coculture with matched S. sanguinis mutants. Three S. sanguinis interaction‐associated genes were predicted to be responsible for cysteine metabolism, and the supplementation of exogenous L‐cysteine promoted the cell number of P. gingivalis in the coculture with S. sanguinis. Thus, exogenous L‐cysteine and the compromised cysteine metabolism in S. sanguinis enhanced the growth of P. gingivalis in the existence of S. sanguinis. Additionally, the interaction between P. gingivalis and other Streptococcus spp. was examined, and S. pneumoniae was the only streptococci that had no inhibition on the cell number of P. gingivalis. In total, this study established a new strategy for high‐throughput screening of the interaction between Streptococcus and P. gingivalis and discovered a set of genes in S. sanguinis that impacted the interaction. The influence of exogenous L‐cysteine on the interaction between P. gingivalis and S. sanguinis in the oral cavity needs further investigation. [ABSTRACT FROM AUTHOR]

Abstract Background Microbial robustness is crucial for developing cell factories that maintain consistent performance in a challenging environment such as large-scale bioreactors. Although tools exist to assess and understand robustness at a phenotypic level, the underlying metabolic and genetic mechanisms are not well defined, which limits our ability to engineer more strains with robust functions. Results This study encompassed four steps. (I) Fitness and robustness were analyzed from a published dataset of yeast mutants grown in multiple environments. (II) Genes and metabolic processes affecting robustness or fitness were identified, and 14 of these genes were deleted in Saccharomyces cerevisiae CEN.PK113-7D. (III) The mutants bearing gene deletions were cultivated in three perturbation spaces mimicking typical industrial processes. (IV) Fitness and robustness were determined for each mutant in each perturbation space. We report that robustness varied according to the perturbation space. We identified genes associated with increased robustness such as MET28, linked to sulfur metabolism; as well as genes associated with decreased robustness, including TIR3 and WWM1, both involved in stress response and apoptosis. Conclusion The present study demonstrates how phenomics datasets can be analyzed to reveal the relationship between phenotypic response and associated genes. Specifically, robustness analysis makes it possible to study the influence of single genes and metabolic processes on stable microbial performance in different perturbation spaces. Ultimately, this information can be used to enhance robustness in targeted strains.

Objective To establish a non-invasive single nucleotide polymorphism genotyping technology based on direct TaqMan-PCR for high-throughput genotyping of site rs688 and rs964184 associated with lipid metabolism to meet the need for early screening of at-risk populations. Methods Extracted DNA was used to optimize the PCR annealing extension temperature and amplification procedure for the designed TaqMan probe; the oral swabs were placed into the sample treatment solution and then briefly centrifuged, and a small amount of the supernatant was taken for the direct qPCR amplification analysis; the freeze-thawing stability of probe and the effects of sample storage time on genotyping results were explored. Results The technology requires only simple treatment of oral swab for PCR analysis and can be stored at room temperature for 4 d. The optimized method was able to distinguish homozygous wild type, homozygous mutant type and heterozygote at rs688 and rs964184 loci. Conclusions A fast, convenient, high-throughput, and low-cost SNP genotyping method has been established, providing an efficient and accurate new approach for large-scale screening of high-risk populations carrying susceptibility genes.

Rapid detection of plant phenotypic traits is crucial for plant breeding and cultivation. Traditional measurement methods are carried out by richexperienced agronomists, which are time-consuming and labor-intensive. However, with the increasing demand for rapid and high-throughput testing in tea plants traits, digital breeding and smart cultivation of tea plants rely heavily on precise plant phenotypic trait measurement techniques, among which hyperspectral imaging (HSI) technology stands out for its ability to provide real-time and rich-information. In this paper, we provide a comprehensive overview of the principles of hyperspectral imaging technology, the processing methods of cubic data, and relevant algorithms in tea plant phenomics, reviewing the progress of applying hyperspectral imaging technology to obtain information on tea plant phenotypes, growth conditions, and quality indicators under environmental stress. Lastly, we discuss the challenges faced by HSI technology in the detection of tea plant phenotypic traits from different perspectives, propose possible solutions, and envision the potential development prospects of HSI technology in the digital breeding and smart cultivation of tea plants. This review aims to provide theoretical and technical support for the application of HSI technology in detecting tea plant phenotypic information, further promoting the trend of developing high quality and high yield tea leaves. [ABSTRACT FROM AUTHOR]

Background: Microbial robustness is crucial for developing cell factories that maintain consistent performance in a challenging environment such as large-scale bioreactors. Although tools exist to assess and understand robustness at a phenotypic level, the underlying metabolic and genetic mechanisms are not well defined, which limits our ability to engineer more strains with robust functions. Results: This study encompassed four steps. (I) Fitness and robustness were analyzed from a published dataset of yeast mutants grown in multiple environments. (II) Genes and metabolic processes affecting robustness or fitness were identified, and 14 of these genes were deleted in Saccharomyces cerevisiae CEN.PK113-7D. (III) The mutants bearing gene deletions were cultivated in three perturbation spaces mimicking typical industrial processes. (IV) Fitness and robustness were determined for each mutant in each perturbation space. We report that robustness varied according to the perturbation space. We identified genes associated with increased robustness such as MET28, linked to sulfur metabolism; as well as genes associated with decreased robustness, including TIR3 and WWM1, both involved in stress response and apoptosis. Conclusion: The present study demonstrates how phenomics datasets can be analyzed to reveal the relationship between phenotypic response and associated genes. Specifically, robustness analysis makes it possible to study the influence of single genes and metabolic processes on stable microbial performance in different perturbation spaces. Ultimately, this information can be used to enhance robustness in targeted strains. [ABSTRACT FROM AUTHOR]

Quantifying viral growth rates is key to understanding evolutionary dynamics and the potential for mutants to escape antiviral drugs. Defining evolutionary escape paths and their impact on viral fitness allows for the development of drugs that are resistant to escape. In the case of HIV, combination antiretroviral therapy can successfully prevent or treat infection, but it relies on strict adherence to prevent escape. Here, we present a method termed QuickFit that enables the quantification of viral fitness by employing large numbers of parallel viral cultures to measure growth rates accurately. QuickFit consistently recapitulated HIV growth measurements obtained by traditional approaches, but with significantly higher throughput and lower rates of error. This method represents a promising tool for rapid and consistent evaluation of viral fitness. [ABSTRACT FROM AUTHOR]

X-ray diffraction (XRD) is used for characterizing the crystal structure of molecular sieves after synthetic experiments. However, for a high-throughput molecular sieve synthetic system, the huge amount of data derived from large throughput capacity makes it difficult to analyze timely. While the kernel step of XRD analysis is to search peaks, an automatic way for peak search is needed. Thus, we proposed a novel semantic mask-based two-step framework for peak search in XRD patterns: (1) mask generation, we proposed a multi-resolution net (MRN) to classify the data points of XRD patterns into binary masks (peak/background). (2) Peak search, based on the generated masks, the background points are used to fit an n-order polynomial background curve and estimate the random noises in XRD patterns. Then we proposed three rules named mask, shape, and intensity to screening peaks from initial peak candidates generated by maximum search. Besides, a voting strategy is proposed in peak screening to obtain a precise peak search result. Experiments show that the proposed MRN achieves the state-of-the-art performance compared with other semantic segmentation methods and the proposed peak search method performs better than Jade when using f1 score as the evaluation index. [ABSTRACT FROM AUTHOR]

Yeast plays a significant role in a variety of fields. In particular, it is extensively used as a model organism in genetics and cellular biology studies, and is employed in the production of vaccines, pharmaceuticals, and biofuels. Traditional "bulk"-based studies on yeast growth often overlook cellular variability, emphasizing the need for single-cell analysis. Micro-droplets, tiny liquid droplets with high surface-area-to-volume ratios, offer a promising platform for investigating single or a small number of cells, allowing precise control and monitoring of individual cell behaviors. Microfluidic devices, which facilitate the generation of micro-droplets, are advantageous due to their reduced volume requirements and ability to mimic in vivo micro-environments. This study introduces a custom-designed microfluidic device to encapsulate yeasts in micro-droplets under various conditions in a parallel manner. The results reveal that optimal glucose concentrations promoted yeast growth while cycloheximide and Cu2+ ions inhibited it. This platform enhances yeast cultivation strategies and holds potential for high-throughput single-cell investigations in more complex organisms. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Inorganic Analytical Chemistry / Zhongguo Wuji Fenxi Huaxue is the property of Beijing Research Institute of Mining & Metallurgy Technology Group and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To predict the favorable thermodynamical conditions and characterize cryogenic pellet formations for applications in nuclear fusion reactors, a high–throughput molecular dynamics study based on a unified framework to simulate the growth process of cryogenic solids (molecular deuterium, neon, argon) under gas pressure have been designed. These elements are used in fusion nuclear plants as fuel materials and to reduce the damage risks for the plasma-facing components in case of a plasma disruption. The unified framework is based on the use of workflows that permit management in HPC facilities, the submission of a massive number of molecular dynamics simulations, and handle huge amounts of data. This simplifies a variety of operations for the user, allowing for significant time savings and efficient organization of the generated data. This approach permits the use of large-scale parallel simulations on supercomputers to reproduce the solid–gas equilibrium curves of cryogenic solids like molecular deuterium, neon, and argon, and to analyze and characterize the reconstructed solid phase in terms of the separation between initial and reconstructed solid slabs, the smoothness of the free surfaces and type of the crystal structure. These properties represent good indicators for the quality of the final materials and provide effective indications regarding the optimal thermodynamical conditions of the growing process. [ABSTRACT FROM AUTHOR]

Objective To investigate a method of rapidly screen monoclonal antibodies with high affinity to trophoblastic glycoprotein (TPBG) from the prepared monoclonal antibodies. Methods High-throughput surface plasmon resonance (SPR) technology was used to immobilize TPBG of different species on the GLC sensor chip by amino coupling. Gradient dilution of the antibody was used as the flow phase to screen monoclonal antibodies that can highly affinity TPBG, and the kinetic constants of the interaction were determined. Antibody 1 binds to human and cynomolgus monkey TPBG with affinity of 65.0 and 31. 6 nmol/L, respectively. Antibody 6 binds to human, mouse and cynomolgus monkey TPBG with affinity of 77.6, 92.1 and 87.7 nmol/L, respectively. Results This study successfully screened two monoclonal antibodies that can specifically bind to TPBG. Meanwhile, the specific binding of these two antibodies to TPBG protein was stable by binding kinetic. Conclusion The monoclonal antibodies with high affinity to TPBG protein are screened out by SPR, which provides a method for the development of some new anti-tumor drugs. [ABSTRACT FROM AUTHOR]

The successful implementation of artificial intelligence algorithms depends on the capacity to execute numerous repeated operations, which, in turn, requires systems with high data throughput. Although emerging computing‐in‐memory (CIM) eliminates the need for frequent data transfer between the memory and processing blocks and enables parallel activation of multiple rows, the traditional structure, where each row has only one identical input value, significantly limits its further application. To solve this problem, this study proposes a dual‐SRAM CIM architecture in which two SRAM arrays are coupled such that all operands are different, thus rendering the use of CIM considerably more flexible. The proposed dual‐SRAM array was implemented through a 55‐nm process, essentially delivering a frequency of 361 MHz for a 1.2‐V supply and energy efficiency of 161 TOPS/W at 0.9 V supply. [ABSTRACT FROM AUTHOR]

Genetic gains made by plant breeders are limited by generational cycling rates and flowering time. Several efforts have been made to reduce the time to switch from vegetative to reproductive stages in plants, but these solutions are usually species-specific and require flowering. The concept of in vitro nurseries is that somatic plant cells can be induced to form haploid cells that have undergone recombination (creating artificial gametes), which can then be used for cell fusion to enable breeding in a Petri dish. The induction of in vitro meiosis, however, is the largest current bottleneck to in vitro nurseries. To help overcome this, we previously described a high-throughput, bi-fluorescent, single cell system in Arabidopsis thaliana, which can be used to test the meiosis-like induction capabilities of candidate factors. In this present work, we validated the system using robust datasets (>4M datapoints) from extensive simulated meiosis induction tests. Additionally, we determined false-detection rates of the fluorescent cells used in this system as well as the ideal tissue source for factor testing. [ABSTRACT FROM AUTHOR]

Purpose: Polysorbates are among the most used surfactants in biopharmaceutical products containing proteins. Our work aims to develop a high-throughput fluorometric assay to further diversify the analytical toolbox for quantification of PSs. Method: The assay leverages the micelle activated fluorescence signal from N-Phenyl-1-Naphthylamine (NPN). The development and optimization of assay parameters were guided by the pre-defined analytical target profile. Furthermore, NMR was used to probe the interaction between protein, PS80 and NPN in the measurement system and understand protein interference. Results: All assay parameters including excitation and emission wavelengths, standard curve, NPN concentration, and incubation time have been optimized and adapted to a microplate format, making it compatible with automated solutions that will be pursued in the near future to drive consistency and efficiency in our workflows. The specificity, accuracy, and precision of the assay have been demonstrated through a case study. Furthermore, NMR results provided additional insight into the change of the interaction dynamics between PS80 and NPN as the protein concentration increases. The results indicate minimal interaction between the protein and PS80 at lower concentration. However, when the concentration exceeds 75 mg/mL, there is a significant interaction between the protein and PS-80 micelle and monomer. Conclusion: A high-throughput fluorometric assay has been developed for quantification of polysorbates in biopharmaceutical samples including in-process samples, drug substance and drug product. The assay reported herein could serve as a powerful analytical tool for polysorbate quantification and control, complementing the widely used liquid chromatography with charged aerosol detection method. [ABSTRACT FROM AUTHOR]

• Isogenic CF cell models generated by CRISPR/Cas9 gene editing. • Four cell models each has a specific CFTR mutation of class I, II, III or IV. • Cell models integrated with halide-sensitive fluorescent reporter. • Capable of high-throughput screening of novel CF therapeutics. Cystic fibrosis (CF) is a single-gene disorder that affects the lung, digestive system, and other organs. Mutations in the CF transmembrane conductance regulator (CFTR) gene are classified into several classes based on their pathogenic mechanism and clinical severity. The distinct and heterogeneous clinical behavior of each CF class and the respective CFTR mutations have made the development of a durable therapy for all CF patients extremely challenging. While the FDA-approved drug elexacaftor/tezacaftor/ivacaftor (Trikafta) benefits CF patients carrying at least one F508del mutation in CFTR, it's not effective for many CF patients carrying a variety of other CFTR mutations. To establish a better understanding of CF pathophysiology and aid the development of novel therapeutics for different classes of CF patients, we have created four CF-mutation-specific cell models that recapitulate respectively four distinct CF classes and disease phenotypes, as confirmed by sequencing, CFTR mRNA and protein quantification. The channel function of each cell model was first validated using a well-established FLIPR (Fluorescent Imaging Plate Reader) membrane potential assay and then assessed by the YFP-based functional assay. Integrated with a halide-sensitive fluorescent reporter, these CF cell models can be used for high-throughput drug screening, as demonstrated by a proof-of-concept study using Trikafta. These cell models have the potential to advance CFTR mutation-specific therapies thus addressing the unmet needs of CF patients with rare mutations. [ABSTRACT FROM AUTHOR]

Embryonic stem cell fate is regulated by various cellular processes. Recently, the process of endocytosis has been implicated in playing a role in the maintenance of self‐renewal and pluripotency of mouse embryonic stem cells. A previous siRNA‐based screen interrogated the function of core components of the endocytic machinery in maintaining the pluripotency of embryonic stem cells, revealing a crucial role for clathrin mediated endocytosis. A number of other proteins involved in key signaling pathways have also been shown to both regulate and be regulated by endocytosis. We collated a list of 1141 genes in connection to the term "endocytosis" from Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO), excluding those previously interrogated, and examined the effect of their knockdown on the pluripotency of mouse embryonic stem cells (mESCs) using levels of green fluorescent protein driven by the Oct4 promoter. We used high‐throughput screening followed by an automated MATrix LABoratory (MATLAB)‐based analysis pipeline and assessed changes in GFP fluorescence as a readout for ESC pluripotency. Through this screen we identified a number of genes, many hitherto not associated with stem cell pluripotency, which upon knockdown either resulted in a significant increase or decrease of GFP fluorescence. We further present validation for some of these hits. We present a workflow aimed to identify genes involved in signaling pathways which can be regulated by endocytosis, and that affect the pluripotency of ESCs. [ABSTRACT FROM AUTHOR]

Despite many recent efforts, the field of organic electrosyn‐thesis faces important challenges due to the intricate nature of heterogeneous redox processes, the wide parameter space to be explored and the lack of standardized methods. To overcome these limitations, we developed a cost‐effective high‐throughput electrochemical (HTE) reactor capable of running 24 individually controlled parallel reactions. This system allows the rapid testing of electrochemical parameters on a given reaction, assessing not only yield but also reproducibility. Using the hypervalent iodine‐mediated dearomatization of phloretic acid as a demonstration of HTE capabilities, we ran more than 200 electrosyntheses in different experimental conditions and demonstrate the effect of parameters such as total charge transferred, current, electrode materials, electrolyte formulation and concentration, mediator formulation and concentration and electrochemical technique of oxidation. Notably, this report demonstrates that while catalytic amounts of iodine mediator can be used successfully, the reproducibility may be affected, which calls for a cautious approach when developing similar transformations. Using cyclic voltammetry, density functional theory, chronopotentiometry, and Raman spectroscopy, we shed light on the causes of this issue. [ABSTRACT FROM AUTHOR]

Indoles and pyrroloindoles are structural motifs present in many biologically active natural products. Multiple classes of enzymes catalyze the transformation of indoles into pyrroloindoles via group transfer followed by intramolecular cyclization, such as peroxydases, methyltransferases, and prenyltransferases. Due to the selective introduction of a stereogenic center, these enzymes receive increasing attention as catalytic tools for the production of pharmacologically relevant compounds. Two new colorimetric assays are described in this work, which allow for the quantification of such enzymatic reactions from the perspective of the substrate and the product. For the substrates, the indole assay is based on a modified version of the Ehrlich test, with the use of light as a driving force for color formation. The pyrroloindole assay uses cerium sulfate as a reagent for the colorimetric quantification of the enzymatic products. The assays are complementary and both were successfully utilized for enzymatic activity determination of a C3‐indole methyltransferase. They can facilitate high‐throughput screening of mutant libraries, offering support for the engineering of such enzymes, but can also be used as stand‐alone methods for the detection and quantification of natural products. [ABSTRACT FROM AUTHOR]

Objective To establish a non-invasive single nucleotide polymorphism genotyping technology based on direct TaqMan-PCR for high-throughput genotyping of site rs688 and rs964184 associated with lipid metabolism to meet the need for early screening of at-risk populations. Methods Extracted DNA was used to optimize the PCR annealing extension temperature and amplification procedure for the designed TaqMan probe; the oral swabs were placed into the sample treatment solution and then briefly centrifuged, and a small amount of the supernatant was taken for the direct qPCR amplification analysis; the freeze-thawing stability of probe and the effects of sample storage time on genotyping results were explored. Results The technology requires only simple treatment of oral swab for PCR analysis and can be stored at room temperature for 4 d. The optimized method was able to distinguish homozygous wild type, homozygous mutant type and heterozygote at rs688 and rs964184 loci. Conclusions A fast, convenient, high-throughput, and low-cost SNP genotyping method has been established, providing an efficient and accurate new approach for large-scale screening of high-risk populations carrying susceptibility genes. [ABSTRACT FROM AUTHOR]

Log blockchain can be used to ensure the integrity of log data. However, current methods are facing the problems of throughput mismatch and rough audit granularity. Packaging multiple logs to generate integrity proofs improves throughput but reduces audit granularity, and the auditor can only locate the tampering log packet instead of specific records. This paper proposes CFAuditChain, an audit blockchain based on a cuckoo filter, where the proof of existence (PoE) of the single log is calculated while calculating the integrity proof of packet logs. The PoE is saved in the cuckoo filter and stored using blockchain for immutability. Therefore, the auditor can verify the credibility of each log based on the filter when the integrity proof of a log packet does not match. The theoretical analysis and experimental results show that CFAuditChain provides the granularity of audit logs down to the records level at an acceptable cost. [ABSTRACT FROM AUTHOR]

The biopharmaceutical industry is replacing fed‐batch with perfusion processes to take advantage of reduced capital and operational costs due to the operation at high cell densities (HCD) and improved productivities. HCDs are achieved by cell retention and continuous medium exchange, which is often based on the cell‐specific perfusion rate (CSPR). To obtain a cost‐productive process the perfusion rate must be determined for each process individually. However, determining optimal operating conditions remain labor‐intensive and time‐consuming experiments, as investigations are performed in lab‐scale perfusion bioreactors. Small‐scale models such as microwell plates (MWPs) provide an option for screening multiple perfusion rates in parallel in a semi‐perfusion mimic. This study investigated two perfusion rate strategies applied to the MWP platform operated in semi‐perfusion. The CSPR‐based perfusion rate strategy aimed to maintain multiple CSPR values throughout the cultivation and was compared to a cultivation with a perfusion rate of 1 RV d−1. The cellular performance was investigated with the dual aim (i) to achieve HCD, when inoculating at conventional and HCDs, and (ii) to maintain HCDs, when applying an additional manual cell bleed. With both perfusion rate strategies viable cell concentrations up to 50 × 106 cells mL−1 were achieved and comparable results for key metabolites and antibody product titers were obtained. Furthermore, the combined application of cell bleed and CSPR‐based medium exchange was successfully shown with similar results for growth, metabolites, and productivities, respectively, while reducing the medium consumption by up to 50% for HCD cultivations. [ABSTRACT FROM AUTHOR]

The promise of continuous processing to increase yields and improve product quality of biopharmaceuticals while decreasing the manufacturing footprint is transformative. Developing and optimizing perfusion operations requires screening various parameters, which is expensive and time‐consuming when using benchtop bioreactors. Scale‐down models (SDMs) are the most feasible option for high‐throughput data generation and condition screening. However, new SDMs mimicking perfusion are required, enabling experiments to be run in parallel. In this study, a method using microwell plates (MWP) operating in semi‐perfusion mode with an implemented cell bleed step is presented. A CHO cell line was cultivated in a 24‐well MWP (Vw = 1.2 mL) and grown at four high cell density (HCD) setpoints. Quasi steady‐state condition was obtained by manually performing cell bleeds followed by a total medium exchange after centrifugation. Further, two HCD setpoints were scaled up (VW = 30 mL), comparing a squared six‐well deepwell plate (DWP) to shake flasks (SF). This evaluation showed comparable results between systems (DWP vs. SF) and scales (MWP vs. DWP + SF). The results show that the well‐plate‐based methods are suitable to perform HCD and quasi steady‐state cultivations providing a robust solution to industrially relevant challenges such as cell clone and media selection. [ABSTRACT FROM AUTHOR]

Thermal stability of proteins is a primary metric for evaluating their physical properties. Although researchers attempted to predict it using machine learning frameworks, their performance has been dependent on the quality and quantity of published data. This is due to the technical limitation that thermodynamic characterization of protein denaturation by fluorescence or calorimetry in a high‐throughput manner has been challenging. Obtaining a melting curve that derives solely from the target protein requires laborious purification, making it far from practical to prepare a hundred or more samples in a single workflow. Here, we aimed to overcome this throughput limitation by leveraging the high protein secretion efficacy of Brevibacillus and consecutive treatment with plate‐scale purification methodologies. By handling the entire process of expression, purification, and analysis on a per‐plate basis, we enabled the direct observation of protein denaturation in 384 samples within 4 days. To demonstrate a practical application of the system, we conducted a comprehensive analysis of 186 single mutants of a single‐chain variable fragment of nivolumab, harvesting the melting temperature (Tm) ranging from −9.3 up to +10.8°C compared to the wild‐type sequence. Our findings will allow for data‐driven stabilization in protein design and streamlining the rational approaches. [ABSTRACT FROM AUTHOR]

Polymerase chain reaction (PCR)-based assays were widely deployed during the SARS-CoV-2 pandemic for population-scale testing. High-throughput molecular diagnostic laboratories required a high degree of process automation to cope with huge testing demands, fast turnaround times, and quality requirements. However, process developers and optimizers often neglected the critical step of preparing a PCR Master Mix. The construction of PCR Master Mix depends on operator skill during the manual pipetting of reagents. Manual procedures introduce variation, inconsistency, wastage, and potentially risks data integrity. To address this, we developed a liquid-handler-based solution for automated, traceable, and compliant PCR Master Mix preparation. Here, we show that a fully automated PCR Master Mix protocol can replace manual pipetting, even in a diagnostic environment, without affecting accuracy or precision. Ultimately, this method eliminated operator-induced wastage and improved the consistency of the quality of results.

ABSTRACT: Avian pathogenic Escherichia coli (APEC) cause avian colibacillosis and accurately distinguishing infectious isolates is critical for controlling its transmission. Multilocus sequence typing (MLST) is an accurate and efficient strain identification method for epidemiological surveillance. This research aimed to develop a fast and high-throughput workflow that simultaneously sequences the Achtman typing scheme's 7 housekeeping genes of multiple E. coli isolates using the Oxford Nanopore Technologies (ONT) platform for large-scale APEC study. E. coli strains were isolated from poultry farms, the housekeeping genes were amplified, and amplicons were sequenced on an R9.4 MinION flow cell using the Nanopore GridION sequencer (ONT, Oxford, UK) following the initial workflow (ONT-MLST). Moreover, the workflow was revised by introducing large-scale DNA extraction and multiplex PCR into the ONT-MLST workflow and applied to 242 new isolates, 18 isolates from the previous workflow, and 5 ATCC reference strains using Flongle flow cell on the Nanopore MinION Mk1C sequencer (ONT, Oxford, UK). Finally, the sequence type (ST) results of the 308 isolates collected from infected chickens and poultry farm environments were reported and analyzed. Data indicated that E. coli belonging to ST159, ST8578, and ST355 have the potential to infect multiple organs in broiler. In addition, zoonotic STs, ST69, ST10, ST38, and ST131, were detected from poultry farms. With the advantages of the high throughput of ONT, this study provides a rapid workflow for large-scale E. coli typing and identified frequently isolated sequence types related to APEC infection in poultry.

Abstract Additive Manufacturing (AM) is revolutionizing aerospace, transportation, and biomedical sectors with its potential to create complex geometries. However, the metallic materials currently used in AM are not intended for high‐energy beam processes, suggesting performance improvement. The development of materials for AM still faces challenge because of the inefficient trial‐and‐error conventional methods. This review examines the challenges and current state of materials including aluminum alloys, titanium alloys, superalloys, and high‐entropy alloys (HEA) in AM, and summarizes the high‐throughput methods in alloy development for AM. In addition, the advantages of high‐throughput preparation technology in improving the properties and optimizing the microstructure mechanism of major additive manufacturing alloys are described. This article concludes by emphasizing the importance of high‐throughput techniques in pushing the boundaries of AM materials development, pointing toward a future of more effective and innovative material solutions.

The sorting of nano- and microparticles according to different properties is an industrially highly relevant but partly unsolved problem. In this study, we investigate the sorting of a complex microparticle mixture on the basis of their different properties by insulator-based dielectrophoretic filtration at high throughput. We demonstrate here that such a high selectivity demanding sorting process is possible in a single device thanks to recent advances in the development of dielectrophoretic filters, which has been shown using simple binary mixtures in a previous study. In that study, a filter with a regular structure (mesh) is introduced with pores several orders of magnitude larger than the target particles so that the particles are trapped solely by the action of positive dielectrophoresis. In this work, we demonstrate the improvement of the filter design, by comparing the trapping behavior to an alternative, irregular porous ceramic structure as a filter medium. A significantly higher selectivity for positive dielectrophoresis could be reached using the regular mesh structure. This high selectivity enables a stepwise operation mode, combining a selective trapping step and several subsequent selective remobilization steps. A mixture of polystyrene-based particles could be sorted by size, shape, and surface coating in one pass of the filter. The proposed method is therefore a promising technique to efficiently create highly specific particle systems in the future.

Newborn disease screening increases survival, improves quality of life and reduces treatment costs for healthcare systems. Mass spectrometry (MS) is an effective method for metabolic screening. However, conventional analytical methods require biofluid handling and cooling conditions during transport, making the logistics difficult and expensive, especially for remote regions. ’Paper-spray’ (PS) ionization generates a charged solvent spray from samples deposited on paper strips. Therefore, samples can be applied on a suitable matrix and shipped as dried spots to diagnostic laboratories with standard postal or messenger services. We built a robotic platform, the ’Open SprayBot’, to automatically analyze paper-deposited samples via PS-MS and increase the sample throughput. The system is operated via RUMBA32 and Arduino Mega boards. A commercial syringe pump and power supply provide solvent application and electrical current required for PS-MS. The usability of the Open SprayBot was demonstrated by quantifying palmitoyl-l-carnitine, a common biomarker in newborn screening.