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Saponins are amphiphilic molecules consisting of carbohydrate and either triterpenoid or steroid aglycone moieties and are noted for their multiple biological activities—Fungicidal, antimicrobial, antiviral, anti-inflammatory, anticancer, antioxidant and immunomodulatory effects have all been observed. Saponins from natural sources have long been used in herbal and traditional medicines; however, the isolation of complexed saponins from nature is difficult and laborious, due to the scarce amount and structure heterogeneity. Chemical synthesis is considered a powerful tool to expand the structural diversity of saponin, leading to the discovery of promising compounds. This review focuses on recent developments in the structure optimization and biological evaluation of synthetic triterpenoid and steroid saponin derivatives. By summarizing the structure–activity relationship (SAR) results, we hope to provide the direction for future development of saponin-based bioactive compounds.

Many researchers have explored the impact of digital games on learning effects in different STEM subjects. The purpose of this meta-analysis is to examine the effect of digital game-based STEM education on the learning achievement of K-12 or higher education students. The analysis results of effect sizes from 33 studies (N = 3894) published from 2010 to 2020 showed that digital games contributed to a moderate overall effect size (ES = 0.667, 95% CI [0.520–0.814], p < 0.001) when compared with other instructional methods. Furthermore, the study explored multiple moderator variables and their potential impacts on learning outcomes such as control treatment, subject discipline, educational level, game type, gaming platform, and intervention duration. The findings suggest that digital games are a promising pedagogical method in STEM education that effectively improves learning gains. Additionally, the study concludes with three recommendations for future research and practices on digital games in STEM education.

Emerging evidence reveals that amino acid metabolism plays an important role in ferroptotic cell death. The conversion of methionine to cysteine is well known to protect tumour cells from ferroptosis upon cysteine starvation through transamination. However, whether amino acids‐produced metabolites participate in ferroptosis independent of the cysteine pathway is largely unknown. Here, the authors show that the tryptophan metabolites serotonin (5‐HT) and 3‐hydroxyanthranilic acid (3‐HA) remarkably facilitate tumour cells to escape from ferroptosis distinct from cysteine‐mediated ferroptosis inhibition. Mechanistically, both 5‐HT and 3‐HA act as potent radical trapping antioxidants (RTA) to eliminate lipid peroxidation, thereby inhibiting ferroptotic cell death. Monoamine oxidase A (MAOA) markedly abrogates the protective effect of 5‐HT via degrading 5‐HT. Deficiency of MAOA renders cancer cells resistant to ferroptosis upon 5‐HT treatment. Kynureninase (KYNU), which is essential for 3‐HA production, confers cells resistant to ferroptotic cell death, whereas 3‐hydroxyanthranilate 3,4‐dioxygenase (HAAO) significantly blocks 3‐HA mediated ferroptosis inhibition by consuming 3‐HA. In addition, the expression level of HAAO is positively correlated with lipid peroxidation and clinical outcome. Together, the findings demonstrate that tryptophan metabolism works as a new anti‐ferroptotic pathway to promote tumour growth, and targeting this pathway will be a promising therapeutic approach for cancer treatment. Tryptophan metabolites 5‐HT and 3‐HA act as potent radical trapping antioxidants to inhibit ferroptosis both in vitro and in vivo. Tryptophan metabolites‐mediated ferroptosis suppression is a new anti‐ferroptosis pathway distinct from cysteine‐mediated ferroptosis inhibition or any other classical anti‐ferroptotic pathways to facilitate tumor development. Therefore, targeting this pathway will be a promising therapeutic approach for cancer treatment.

Terahertz (THz) waves show great potential in nondestructive testing, biodetection and cancer imaging. Despite recent progress in THz wave near-field probes/apertures enabling raster scanning of an object’s surface, an efficient, nonscanning, noninvasive, deep subdiffraction imaging technique remains challenging. Here, we demonstrate THz near-field microscopy using a reconfigurable spintronic THz emitter array (STEA) based on the computational ghost imaging principle. By illuminating an object with the reconfigurable STEA followed by computing the correlation, we can reconstruct an image of the object with deep subdiffraction resolution. By applying an external magnetic field, in-line polarization rotation of the THz wave is realized, making the fused image contrast polarization-free. Time-of-flight (TOF) measurements of coherent THz pulses further enable objects at different distances or depths to be resolved. The demonstrated ghost spintronic THz-emitter-array microscope (GHOSTEAM) is a radically novel imaging tool for THz near-field imaging, opening paradigm-shifting opportunities for nonintrusive label-free bioimaging in a broadband frequency range from 0.1 to 30 THz (namely, 3.3–1000 cm−1).Microscopy: imaging ‘ghosts’ more clearly with terahertz wavesA modification of the technology called terahertz near-field microscopy brings improvements in resolution and speed for biological and medical imaging and nondestructive materials testing. Terahertz waves lie between the microwave and infra-red regions of the electromagnetic spectrum. The improved ‘ghost-imaging’ procedure was developed by researchers in China, Singapore and the USA, led by Li-Guo Zhu at the China Academy of Engineering Physics. In ghost imaging the illuminating radiation is split into one beam that interacts with the object being studied and another beam that does not. The so-called ghost image of the object is then constructed by computational comparison of the different behaviour of the two beams. The innovation depends on gaining enhanced control of the structure of the terahertz radiation using a system called a spintronic terahertz emitter array.

Kidney stone disease is one of the oldest diseases known to medicine; however, the mechanisms of stone formation and development remain largely unclear. Over the past decades, a variety of theories and strategies have been developed and utilized in the surgical management of kidney stones, as a result of recent technological advances. Observations from the authors and other research groups suggest that there are five entirely different main mechanisms for kidney stone formation. Urinary supersaturation and crystallization are the driving force for intrarenal crystal precipitation. Randall's plaques are recognized as the origin of calcium oxalate stone formation. Sex hormones may be key players in the development of nephrolithiasis and may thus be potential targets for new drugs to suppress kidney stone formation. The microbiome, including urease-producing bacteria, nanobacteria and intestinal microbiota, is likely to have a profound effect on urological health, both positive and negative, owing to its metabolic output and other contributions. Lastly, the immune response, and particularly macrophage differentiation, play crucial roles in renal calcium oxalate crystal formation. In the present study, the current knowledge for each of these five aspects of kidney stone formation is reviewed. This knowledge may be used to explore novel research opportunities and improve the understanding of the initiation and development of kidney stones for urologists, nephrologists and primary care.

Acute promyelocytic leukemia (APL) is characterized by t(15;17)(q22;q21), resulting in a PML-RARA fusion that is the master driver of APL. A few cases that cannot be identified with PML-RARA by using conventional methods (karyotype analysis, FISH, and RT-PCR) involve abnormal promyelocytes that are fully in accordance with APL in morphology, cytochemistry, and immunophenotype. To explore the mechanisms involved in pathogenesis and recurrence of morphologically diagnosed APL, we performed comprehensive variant analysis by next-generation sequencing in 111 pediatric patients morphologically diagnosed as APL. Structural variant (SV) analysis in 120 DNA samples from both diagnosis and relapse stage identified 95 samples with RARA rearrangement (including 94 with PML-RARA and one with NPM-RARA) and two samples with KMT2A rearrangement. In the eligible 13 RNA samples without any RARA rearrangement at diagnosis, one case each with CPSF6-RARG, NPM1-CCDC28A, and TBC1D15-RAB21 and two cases with a TBL1XR1-RARB fusion were discovered. These uncovered fusion genes strongly suggested their contributions to leukemogenesis as driver alternations and APL phenotype may arise by abnormalities of other members of the nuclear receptor superfamily involved in retinoid signaling (RARB or RARG) or even by mechanisms distinct from the formation of aberrant retinoid receptors. Single-nucleotide variant (SNV) analysis in 77 children (80 samples) with RARA rearrangement showed recurrent alternations of primary APL in FLT3, WT1, USP9X, NRAS, and ARID1A, with a strong potential for involvement in pathogenesis, and WT1 as the only recurrently mutated gene in relapsed APL. WT1, NPM1, NRAS, FLT3, and NSD1 were identified as recurrently mutated in 17 primary samples without RARA rearrangement and WT1, NPM1, TP53, and RARA as recurrently mutated in 9 relapsed samples. The survival of APL with RARA rearrangement is much better than without RARA rearrangement. Thus, patients morphologically diagnosed as APL that cannot be identified as having a RARA rearrangement are more reasonably classified as a subclass of AML other than APL, and individualized treatment should be considered according to the genetic abnormalities.

Glycolytic reprogramming is one of the most important features of cancer and plays an integral role in the progression of cancer. In cancer cells, changes in glucose metabolism meet the needs of self-proliferation, angiogenesis and lymphangiogenesis, metastasis, and also affect the immune escape, prognosis evaluation and therapeutic effect of cancer. The n6-methyladenosine (m6A) modification of RNA is widespread in eukaryotic cells. Dynamic and reversible m6A modifications are widely involved in the regulation of cancer stem cell renewal and differentiation, tumor therapy resistance, tumor microenvironment, tumor immune escape, and tumor metabolism. Lately, more and more evidences show that m6A modification can affect the glycolysis process of tumors in a variety of ways to regulate the biological behavior of tumors. In this review, we discussed the role of glycolysis in tumor genesis and development, and elaborated in detail the profound impact of m6A modification on different tumor by regulating glycolysis. We believe that m6A modified glycolysis has great significance and potential for tumor treatment.

Sorting recyclable trash is critical to reducing energy consumption and mitigating environmental pollution. Currently, trash sorting heavily relies on manpower. Computer vision technology enables automated trash sorting. However, existing trash image classification datasets contain a large number of images without backgrounds. Moreover, the models are vulnerable to background interference when categorizing images with complex backgrounds. In this work, we provide a recyclable trash dataset that supports model training and design a model specifically for trash sorting. Firstly, we introduce the TrashIVL dataset, an image dataset for recyclable trash sorting encompassing five classes (TrashIVL-5). All images are collected from public trash datasets, and the original images were captured by RGB imaging sensors, containing trash items with real-life backgrounds. To achieve refined recycling and improve sorting efficiency, the TrashIVL dataset can be further categorized into 12 classes (TrashIVL-12). Secondly, we propose the integrated parallel attention module (IPAM). Considering the susceptibility of sensor-based systems to background interference in real-world trash sorting scenarios, our IPAM is specifically designed to focus on the essential features of trash images from both channel and spatial perspectives. It can be inserted into convolutional neural networks (CNNs) as a plug-and-play module. We have constructed a recyclable trash sorting network building upon the IPAM, which produces an acuracy of 97.42% on TrashIVL-5 and 94.08% on TrashIVL-12. Our work is an effective attempt of computer vision in recyclable trash sorting. It makes a positive contribution to environmental protection and sustainable development.

This paper proposes a fingerprint-based indoor localization method, named FPFE (fingerprint feature extraction), to locate a target device (TD) whose location is unknown. Bluetooth low energy (BLE) beacon nodes (BNs) are deployed in the localization area to emit beacon packets periodically. The received signal strength indication (RSSI) values of beacon packets sent by various BNs are measured at different reference points (RPs) and saved as RPs’ fingerprints in a database. For the purpose of localization, the TD also obtains its fingerprint by measuring the beacon packet RSSI values for various BNs. FPFE then applies either the autoencoder (AE) or principal component analysis (PCA) to extract fingerprint features. It then measures the similarity between the features of PRs and the TD with the Minkowski distance. Afterwards, k RPs associated with the k smallest Minkowski distances are selected to estimate the TD’s location. Experiments are conducted to evaluate the localization error of FPFE. The experimental results show that FPFE achieves an average error of 0.68 m, which is better than those of other related BLE fingerprint-based indoor localization methods.

Background Somatic embryogenesis (SE) is a promising technology for plant vegetative propagation, which has an important role in tree breeding. Though rubber tree ( Hevea brasiliensis Muell. Arg.) SE has been founded, few late SE-related genes have been identified and the molecular regulation mechanisms of late SE are still not well understood. Results In this study, the transcriptomes of embryogenic callus (EC), primary embryo (PE), cotyledonary embryo (CE), abnormal embryo (AE), mature cotyledonary embryo (MCE) and withered abnormal embryo (WAE) were analyzed. A total of 887,852,416 clean reads were generated, 85.92% of them were mapped to the rubber tree genome. The de novo assembly generated 36,937 unigenes. The differentially expressed genes (DEGs) were identified in the pairwise comparisons of CE vs. AE and MCE vs. WAE, respectively. The specific common DEGs were mainly involved in the phytohormones signaling pathway, biosynthesis of phenylpropanoid and starch and sucrose metabolism. Among them, hormone signal transduction related genes were significantly enriched, especially the auxin signaling factors ( AUX-like1 , GH3.1 , SAUR32-like , IAA9-like , IAA14-like , IAA27-like , IAA28-like and ARF5-like ). The transcription factors including WRKY40 , WRKY70 , MYBS3-like , MYB1R1 - like , AIL6 and bHLH93-like were characterized as molecular markers for rubber tree late SE. CML13 , CML36 , CAM-7 , SERK1 and LEAD-29-like were also related to rubber tree late SE. In addition, histone modification had crucial roles during rubber tree late SE. Conclusions This study provides important information to elucidate the molecular regulation during rubber tree late SE.