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Although numerous organ‐on‐a‐chips have been developed, bone‐on‐a‐chip platforms have rarely been reported because of the high complexity of the bone microenvironment. With an increase in the elderly population, a high‐risk group for bone‐related diseases such as osteoporosis, it is essential to develop a precise bone‐mimicking model for efficient drug screening and accurate evaluation in preclinical studies. Here, we developed a high‐throughput biomimetic bone‐on‐a‐chip platform combined with an artificial intelligence (AI)‐based image analysis system. To recapitulate the key aspects of natural bone microenvironment, mouse osteocytes (IDG‐SW3) and osteoblasts (MC3T3‐E1) were cocultured within the osteoblast‐derived decellularized extracellular matrix (OB‐dECM) built in a well plate‐based three‐dimensional gel unit. This platform spatiotemporally and configurationally mimics the characteristics of the structural bone unit, known as the osteon. Combinations of native and bioactive ingredients obtained from the OB‐dECM and coculture of two types of bone cells synergistically enhanced osteogenic functions such as osteocyte differentiation and osteoblast maturation. This platform provides a uniform and transparent imaging window that facilitates the observation of cell–cell interactions and features high‐throughput bone units in a well plate that is compatible with a high‐content screening system, enabling fast and easy drug tests. The drug efficacy of anti‐SOST antibody, which is a newly developed osteoporosis drug for bone formation, was tested via β‐catenin translocation analysis, and the performance of the platform was evaluated using AI‐based deep learning analysis. This platform could be a cutting‐edge translational tool for bone‐related diseases and an efficient alternative to bone models for the development of promising drugs.

Near‐edge X‐ray absorption fine‐structure (NEXAFS) spectroscopy is a powerful tool for identifying chemical bonding states at synchrotron radiation facilities. Advances in new materials require researchers in both academia and industry to measure tens to hundreds of samples during the available beam time on a synchrotron beamline, which is typically allocated to users. Automated measurement methods, along with analysis software, have been developed for beamlines. Automated measurements facilitate high‐throughput experiments and accumulate vast amounts of measured spectral data. The analysis software supports various functions for analyzing the experimental data; however, these analysis methods are complicated, and learning them can be time‐consuming. To process large amounts of spectral data, a new analysis software, dedicated to NEXAFS spectroscopy, that is easy to use and can provide results in a short time is desired. Herein, the development of Beagle is described, software calculating molecular orientation from NEXAFS spectroscopy data that can report results in a short time comparable with that required to measure one sample at the beamline. It was designed to progress in a single sequence from data loading to the printing of the results with a `click of a button'. The functions of the software include recognizing the dataset, correcting the background, normalizing the plot, calculating the electron yield and determining the molecular orientation. The analysis results can be saved as files (spectral data), files (graphic images) and Origin files (spectral data and graphic images). A new software, Beagle, has been developed to analyze NEXAFS spectroscopy at PAL. It calculates molecular orientation for high‐throughput experiments, handling more than 100 samples per day.

Single‐cell technologies have revolutionized the understanding of cellular heterogeneity, revealing distinct cell populations and functional states with molecular precision. Traditional approaches, however, are constrained by cellular dimension and throughput scale, in addition to its inability preserve spatial information. Recent innovations now allow high throughput, large‐sized cell, and multi‐modal profiling of patient samples, overcoming these limitations. In this perspective, three recently developed single‐cell technologies is described, highlighting how their enhanced throughput, resolution, and sensitivity provide deeper insights into cellular identity and function. Traditional single‐cell technologies are constrained by cellular dimension and throughput scale, in addition to its inability preserve spatial information. With recent innovations, these technologies now allow high throughput, large‐sized cell, and multi‐modal profiling of patient samples, overcoming these limitations. Here, we describe three recently developed single‐cell technologies, highlighting how their enhanced throughput, resolution, and sensitivity provide deeper insights into cellular identity and function.

Artificial cells are based on dynamic compartmentalized systems. Thus, remodeling of membrane-bound systems, such as giant unilamellar vesicles, is finding applications beyond biological studies, to engineer cell-mimicking structures. Giant unilamellar vesicle fusion is rapidly becoming an essential experimental step as artificial cells gain prominence in synthetic biology. Several techniques have been developed to accomplish this step, with varying efficiency and selectivity. To date, characterization of vesicle fusion has relied on small samples of giant vesicles, examined either manually or by fluorometric assays on suspensions of small and large unilamellar vesicles. Automation of the detection and characterization of fusion products is now necessary for the screening and optimization of these fusion protocols. To this end, we implemented a fusion assay based on fluorophore colocalization on the membranes and in the lumen of vesicles. Fluorescence colocalization was evaluated within single compartments by image segmentation with minimal user input, allowing the application of the technique to high-throughput screenings. After detection, statistical information on vesicle fluorescence and morphological properties can be summarized and visualized, assessing lipid and content transfer for each object by the correlation coefficient of different fluorescence channels. Using this tool, we report and characterize the unexpected fusogenic activity of sodium chloride on phosphatidylcholine giant vesicles. Lipid transfer in most of the vesicles could be detected after 20 h of incubation, while content exchange only occurred with additional stimuli in around 8% of vesicles.

Mutations in the daf‐2 gene of the conserved Insulin/Insulin‐like Growth Factor (IGF‐1) pathway double the lifespan of the nematode Caenorhabditis elegans . This phenotype is completely suppressed by deletion of Forkhead transcription factor daf‐16. To uncover regulatory mechanisms coordinating this extension of life, we employed a quantitative proteomics strategy with daf‐2 mutants in comparison with N2 and daf‐16; daf‐2 double mutants. This revealed a remarkable longevity‐specific decrease in proteins involved in mRNA processing and transport, the translational machinery, and protein metabolism. Correspondingly, the daf‐2 mutants display lower amounts of mRNA and 20S proteasome activity, despite maintaining total protein levels equal to that observed in wild types. Polyribosome profiling in the daf‐2 and daf‐16;daf‐2 double mutants confirmed a daf‐16‐ dependent reduction in overall translation, a phenotype reminiscent of Dietary Restriction‐mediated longevity, which was independent of germline activity. RNA interference (RNAi)‐mediated knockdown of proteins identified by our approach resulted in modified C. elegans lifespan confirming the importance of these processes in Insulin/IGF‐1‐mediated longevity. Together, the results demonstrate a role for the metabolism of proteins in the Insulin/IGF‐1‐mediated extension of life. Quantitative proteomics, lifespan analysis, and biochemical assays were utilized to show that Insulin/IGF‐1‐mediated longevity in C. elegans is strongly associated with a daf‐16 dependent global reduction in protein metabolism. Synopsis Quantitative proteomics, lifespan analysis, and biochemical assays were utilized to show that Insulin/IGF‐1‐mediated longevity in C. elegans is strongly associated with a daf‐16 dependent global reduction in protein metabolism. A daf‐16 dependent global reduction in protein translation is observed in daf‐2 long‐lived mutant. The reduction in active translation is independent of germline activity A role for protein metabolism is identified in the Insulin/IGF‐1‐mediated extension of life.

Where does flow injection analysis mass spectrometry (FIA-MS) stand relative to ambient mass spectrometry (MS) and chromatography-MS? Improvements in FIA-MS methods have resulted in fast-expanding uses of this technique. Key advantages of FIA-MS over chromatography-MS are fast analysis (typical run time <60 s) and method simplicity, and FIA-MS offers high-throughput without compromising sensitivity, precision and accuracy as much as ambient MS techniques. Consequently, FIA-MS is increasingly becoming recognized as a suitable technique for applications where quantitative screening of chemicals needs to be performed rapidly and reliably. The FIA-MS methods discussed herein have demonstrated quantitation of diverse analytes, including pharmaceuticals, pesticides, environmental contaminants, and endogenous compounds, at levels ranging from parts-per-billion (ppb) to parts-per-million (ppm) in very complex matrices (such as blood, urine, and a variety of foods of plant and animal origin), allowing successful applications of the technique in clinical diagnostics, metabolomics, environmental sciences, toxicology, and detection of adulterated/counterfeited goods. The recent boom in applications of FIA-MS for high-throughput quantitative analysis has been driven in part by (1) the continuous improvements in sensitivity and selectivity of MS instrumentation, (2) the introduction of novel sample preparation procedures compatible with standalone mass spectrometric analysis such as salting out assisted liquid–liquid extraction (SALLE) with volatile solutes and NH₄ ⁺ QuEChERS, and (3) the need to improve efficiency of laboratories to satisfy increasing analytical demand while lowering operational cost. The advantages and drawbacks of quantitative analysis by FIA-MS are discussed in comparison to chromatography-MS and ambient MS (e.g., DESI, LAESI, DART). Generally, FIA-MS sits ‘in the middle’ between ambient MS and chromatography-MS, offering a balance between analytical capability and sample analysis throughput suitable for broad applications in life sciences, agricultural chemistry, consumer safety, and beyond. Graphical abstract Position of FIA-MS relative to chromatography-MS and ambient MS in terms of analytical figures of merit and sample analysis throughput.

Unmasking the subtleties of the immune system requires both a comprehensive knowledge base and the ability to interrogate that system with intimate sensitivity. That task, to a considerable extent, has been handled by an iterative expansion in flow cytometry methods, both in technological capability and also in accompanying advances in informatics. As the field of fluorescence-based cytomics matured, it reached a technological barrier at around 30 parameter analyses, which stalled the field until spectral flow cytometry created a fundamental transformation that will likely lead to the potential of 100 simultaneous parameter analyses within a few years. The simultaneous advance in informatics has now become a watershed moment for the field as it competes with mature systematic approaches such as genomics and proteomics, allowing cytomics to take a seat at the multi-omics table. In addition, recent technological advances try to combine the speed of flow systems with other detection methods, in addition to fluorescence alone, which will make flow-based instruments even more indispensable in any biological laboratory. This paper outlines current approaches in cell analysis and detection methods, discusses traditional and microfluidic sorting approaches as well as next-generation instruments, and provides an early look at future opportunities that are likely to arise.

A method for the high-throughput analysis of the relative lignin contents of Cryptomeria japonica samples over a wide concentration range (3–73%), independent of the type of chemical pretreatment, was developed by using Fourier transform infrared spectroscopy. First, the assignments of the infrared absorbance related to lignin were reviewed. Then, various chemical treatments, including alkaline, acid, and hydrothermal processes, and a sodium chlorite oxidation treatment, were performed to prepare samples containing a wide range of different lignin contents. Principal component analysis indicated high variability among the chemical treatments in terms of the corresponding lignin contents as well as the resulting changes in the chemical structure of hemicellulose; this conclusion was supported by the loading vectors. The intensity of the key band of lignin at 1508 cm −1 was calculated using the absorbance at 2900 cm −1 as a reference; a reliable calibration curve with an R 2 of 0.968 was obtained independent of the chemical treatment performed. This simple and rapid method for determining the lignin content is expected to be widely applicable for optimizing bioethanol production, as well as monitoring biomass degradation processes.

Modern organic reaction discovery and development relies on the rapid assessment of large arrays of hypothesis-driven experiments. The time-intensive nature of reaction analysis presents the greatest practical barrier for the execution of this iterative process that underpins the development of new bioactive agents. Toward addressing this critical bottleneck, we report herein a high-throughput analysis (HTA) method of reaction mixtures by photocapture on a 384-spot diazirine-terminated self-assembled monolayer, and self-assembled monolayers for matrix-assisted laser desorption/ionization mass spectrometry (SAMDI-MS) analysis. This analytical platform has been applied to the identification of a single-electron-promoted reductive coupling of acyl azolium species.

Health-strengthening (Fu-Zheng) herbs is a representative type of traditional Chinese medicine (TCM) widely used for cancer treatment in China, which is in contrast to pathogen eliminating (Qu-Xie) herbs. However, the commonness in the biological basis of health-strengthening herbs remains to be holistically elucidated. In this study, an innovative high-throughput research strategy integrating computational and experimental methods of network pharmacology was proposed, and 22 health-strengthening herbs were selected for the investigation. Additionally, 25 pathogen-eliminating herbs were included for comparison. First, based on network-based, large-scale target prediction, we analyzed the target profiles of 1446 TCM compounds. Next, the actions of 166 compounds on 420 antitumor or immune-related genes were measured using a unique high-throughput screening strategy by high-throughput sequencing, referred to as HTS2. Furthermore, the structural information and the antitumor activity of the compounds in health-strengthening and pathogen-eliminating herbs were compared. Using network pharmacology analysis, we discovered that: (1) Functionally, the predicted targets of compounds from health strengthening herbs were enriched in both immune-related and antitumor pathways, similar to those of pathogen eliminating herbs. As a case study, galloylpaeoniflorin, a compound in a health strengthening herb Radix Paeoniae Alba (Bai Shao), was found to exert antitumor effects both in vivo and in vitro. Yet the inhibitory effects of the compounds from pathogen eliminating herbs on tumor cells proliferation as a whole were significantly stronger than those in health-strengthening herbs (p < 0.001). Moreover, the percentage of assay compounds in health-strengthening herbs with the predicted targets enriched in the immune-related pathways (e.g., natural killer cell mediated cytotoxicity and antigen processing and presentation) were significantly higher than that in pathogen-eliminating herbs (p < 0.05). This finding was supported by the immune-enhancing effects of a group of compounds from health-strengthening herbs indicated by differentially expressed genes in the HTS2 results. (2) Compounds in the same herb may exhibit the same or distinguished mechanisms in cancer treatment, which was demonstrated as the compounds influence pathway gene expressions in the same or opposite directions. For example, acetyl ursolic acid and specnuezhenide in a health-strengthening herb Fructus Ligustri lucidi (Nv Zhen Zi) both upregulated gene expressions in T cell receptor signaling pathway. Together, this study suggested greater potentials in tumor immune microenvironment regulation and tumor prevention than in direct killing tumor cells of health-strengthening herbs generally, and provided a systematic strategy for unveiling the commonness in the biological basis of health-strengthening herbs in cancer treatment.