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Biology subjects

Wang, M.

Publications and source records attributed to Wang, M..

At least 469 records · Page 26Linked to original sources

Distinct senescence mechanisms restrain progression of dysplastic nevi

TERT promoter mutations (TPMs) are frequently found in different cancer types, including approximately 70% of sun-exposed skin melanomas. In melanoma, TPMs are among the earliest mutations and can be present during the transition from nevus to melanoma. However, the specific factors that contribute to the selection of TPMs in certain nevi subsets are not well understood. To investigate this, we analyzed a group of dysplastic nevi (DN) by sequencing genes commonly mutated in melanocytic neoplasms. We examined the relationship between the identified mutations, patient age, telomere length, histological features, and the expression of p16. Our findings reveal that TPMs are more prevalent in DN from older patients and are associated with shorter telomeres. Importantly, these TPMs were not found in nevi with BRAF V600E mutations. Conversely, DN with BRAF V600E mutations were observed in younger patients, had longer telomeres, and a higher proportion of p16-positive cells. This suggests that these nevi arrest growth independently of telomere shortening through a mechanism known as oncogene-induced senescence (OIS). These characteristics extend to melanoma sequencing data sets, where melanomas with BRAF V600E mutations were more likely to have CDKN2A inactivation, overriding OIS. In contrast, melanomas without BRAF V600E mutations showed a higher frequency of TPMs. Our data imply that TPMs are selected to bypass replicative senescence (RS) in cells that were not arrested by OIS. Overall, our results indicate that a subset of melanocytic neoplasms face constraints from RS, while others encounter OIS and RS. The order in which these barriers are overcome during progression to melanoma depends on the mutational context.

cancer biology↗

Theranostic Bottle-Brush Polymers Tailored for Universal Solid-Tumour Targeting

Nanomedicines involving nanotechnologies and engineering of nanomaterials for medicines have shown great promise in diagnosis and treatment of diseases including cancers. A major hurdle that limits the successful clinical translation of nanomedicines, however, is how to overcome the cascaded biological barriers and improve the delivery efficacy towards the disease sites and minimize the toxicity against healthy tissues and cells. Here, we report a type of bottle-brush-like polymers systematically optimized in their chemical structures, sizes, and surface charges that lead to their outstanding pharmacokinetics and tumour-targeting performances in a variety of both subcutaneous and orthotopic tumour models. The potential mechanism has been studied by revealing the structure-activity relationship of these polymers in overcoming the biological barriers, including their avoidance by the immune system and deep tumour infiltration. Our study may offer insight for a rational design of highly efficient delivery platform of polymeric nanomedicines that could effectively overcome the cascaded biological barriers and thus lead to high tumour-targeting efficacy and low toxicity.

bioengineering↗

Proguanil and chlorhexidine augment the antibacterial activities of clarithromycin and rifampicin against Acinetobacter baumannii

The emergence of Acinetobacter baumannii infections as a significant healthcare concern in hospital settings, coupled with their association with poorer clinical outcomes, has prompted extensive investigation into novel therapeutic agents and innovative treatment strategies. Proguanil and chlorhexidine, both categorized as biguanide compounds, have displayed clinical efficacy as antimalarial and topical antibacterial agents, respectively. In this study, we conducted an investigation to assess the effectiveness of combining proguanil and chlorhexidine with clarithromycin or rifampicin against both laboratory strains and clinical isolates of A. baumannii. The combination therapy demonstrated rapid bactericidal activity against planktonic multidrug-resistant A. baumannii, exhibiting efficacy in eradicating mature biofilms and impeding the development of antibiotic resistance in vitro. Additionally, when administered in conjunction with clarithromycin or rifampicin, proguanil enhanced the survival rate of mice afflicted with intraperitoneal A. baumannii infections, and chlorhexidine expedited wound healing in mice with skin infections. These findings are likely attributable to the disruption of A. baumannii cell membrane integrity by proguanil and chlorhexidine, resulting in heightened membrane permeability and enhanced intracellular accumulation of clarithromycin and rifampicin. Overall, this study underscores the potential of employing proguanil and chlorhexidine in combination with specific antibiotics to effectively combat A. baumannii infections and improve treatment outcomes in clinically challenging scenarios. IMPORTANCEA. baumannii has emerged as a globally significant nosocomial pathogen due to its remarkable ability to acquire antibiotic resistance and develop biofilms on both biotic and abiotic surfaces. Recent research has demonstrated that the antidiabetic drug metformin has a potentiation effect on doxycycline and minocycline against certain multidrug-resistant bacterial pathogens, suggesting the potential of this biguanide agent as a novel tetracyclines adjuvant. In this study, we provide evidence showing that the combination of proguanil and chlorhexidine with clarithromycin or rifampicin exhibits rapid bactericidal activities against both planktonic cells and mature biofilms of A. baumannii, the capacity to inhibit the development of antibiotic resistance and improvement of the treatment outcomes in A. baumannii-infected mice. Given the advantages of repurposing non-antibiotic drugs as antibiotic adjuvants, proguanil and chlorhexidine show promise as adjuvants of specific antibiotics in combating clinically significant pathogenic A. baumannii.

microbiology↗

Manipulation of Bacterial ROS Production Leads to Self-escalating DNA Damage and Resistance-resistant Lethality for Intracellular Mycobacteria

The high prevalence of drug resistance in mycobacteria calls for antimicrobial mechanisms that suppresses the development of resistance. As a structurally conserved multi-site bio-macromolecule, DNA is presumed to be an ideal candidate for such resistance-resistant drug target. However, survey of marketed and investigational DNA interactors indicates that they are not immune to resistance development. Here, we report our strategy to achieve real resistance-resistant DNA targeting by incurring "catastrophic" DNA damage with an organoruthenium-natural product hybrid. The dual-mode DNA damage, in the form of strong tri-valent binding and concomitant oxidative modification, is achieved by manipulating of bacterias native endogenous ROS production mechanism upon lethal stress (such as DNA binding). Such self-escalating DNA damage, together with precise targeting of intracellular bacteria via vacuole fusion, thus endows the hybrids resistance-resistant lethality against mycobacteria and in vivo efficacy in animal models.

microbiology↗

Malaria resistance-related biological adaptation and complex evolutionary footprints of Tai-Kadai people inferred from 796 genomes

Pathogen-host adaptative interaction and complex population demographical processes, including admixture, drift and Darwen selection, have considerably shaped the Neolithic-to-Modern Western Eurasian population structure and genetic susceptibility to modern human diseases. However, the genetic footprints of evolutionary events in East Asia keep unknown as the underrepresentation of genomic diversity and the design of large-scale population studies. We reported one aggregated database of genome-wide-SNP variations from 796 Tai-Kadai (TK) genomes, including Bouyei first reported here, to explore the genetic history, population structure and biological adaptative features of TK-speaking people from Southern China and Southeast Asia. We found geography-related population substructure among TK-speaking people using the state-of-the-art population genetic structure reconstruction techniques based on the allele frequency spectrum and haplotype-resolved phased fragments. We found that the Northern TK-speaking people from Guizhou harboured one TK-dominant ancestry maximised in Bouyei people, and the Southern one from Thailand obtained more influences from Southeast Asians and indigenous people. We reconstructed the fitted admixture models and demographic graphs, which showed that TK-speaking people received gene flow from ancient rice farmer-related lineages related to the Hmong-Mien and Austroasiatic people and Northern millet farmers associated with the Sino-Tibetan people. Biological adaptation focused on our identified unique TK lineages related to Bouyei showed many adaptive signatures conferring Malaria resistance and low-rate lipid metabolism. Further gene enrichment, the allele frequency distribution of derived alleles, and their correlation with the incidence of Malaria further confirmed that CR1 played an essential role in the resistance of Malaria in the ancient "Baiyue" tribes.

genetics↗

The ChickenGTEx pilot analysis: a reference of regulatory variants across 28 chicken tissues

Chicken is a valuable model for understanding fundamental biology, vertebrate evolution and diseases, as well as a major source of nutrient-dense and lean-protein-enriched food globally. Although it is the first non-mammalian amniote genome to be sequenced, the chicken genome still lacks a systematic characterization of functional impacts of genetic variants. Here, through integrating 7,015 RNA-Seq and 2,869 whole-genome sequence data, the Chicken Genotype- Tissue Expression (ChickenGTEx) project presents the pilot reference of regulatory variants in 28 chicken tissue transcriptomes, including millions of regulatory effects on primary expression (including protein-coding genes, lncRNA and exon) and post-transcriptional modifications (alternative splicing and 3 untranslated region alternative polyadenylation). We explored the tissue-sharing and context-specificity of these regulatory variants, their underlying molecular mechanisms of action, and their utility in interpreting adaptation and genome-wide associations of 108 chicken complex traits. Finally, we illustrated shared and lineage-specific features of gene regulation between chickens and mammals, and demonstrated how the ChickenGTEx resource can further assist with translating genetic findings across species. One-Sentence SummaryThe ChickenGTEx provides a multi-tissue reference of regulatory variants for chicken genetics and genomics, functional genomics, precision breeding, veterinary medicine, vertebrate evolution and even human biomedicine.

genetics↗

Vocabulary Matters: An Annotation Pipeline and Two Deep Learning Algorithms for Enzyme Named Entity Recognition

Enzymes are indispensable substances in many biological processes. With biomedical literature growing exponentially, it becomes more difficult to review the literature effectively. Hence, text-mining techniques are needed to facilitate and speed up literature review. The aims of this study are to create a corpus with annotated enzymes to train and evaluate enzyme named-entity recognition (NER) models. A novel pipeline was built using a combination of dictionary matching and rulebased keyword searching to automatically annotate enzyme entities in over 4,800 biomedical full texts. Two Bidirectional Long Short-Term Memory (BiLSTM) networks using BioBERT and SciBERT as tokeniser and word embedding layers were trained on this corpus and evaluated on a manually annotated test set of 526 full-text publications. The dictionary- and rule-based annotation pipeline achieved an F1-score of 0.863 (precision 0.996, recall 0.762). The SciBERT-BiLSTM model (F1-score 0.965, precision 0.981, recall 0.954) largely out-performed the BioBERT-BiLSTM model (F1-score 0.955, precision 0.981, recall 0.937). This study contributed a novel dictionary- and rule-based automatic pipeline with almost perfect precision which runs in a matter of seconds on a standard laptop. Both deep learning (DL) models achieved state-of-the-art performance (F1>0.95) for enzyme NER, with the SciBERT-based model outperforming the BioBERT-based model in terms of recall, demonstrating the vocabulary used by models matters. The proposed pipeline with the DL models can facilitate more effective enzyme text-mining and information extraction research for literature review and are the first algorithms specifically for enzyme NER. AvailabilityAll codes are available for automatic annotation and model training (including data), with instructions on how to deploy the model on new text, from https://github.com/omicsNLP/enzymeNER.

bioinformatics↗

Language model-based B cell receptor sequence embeddings can effectively encode receptor specificity

High throughput sequencing of B cell receptors (BCRs) is increasingly applied to study the immense diversity of antibodies. Learning biologically meaningful embeddings of BCR sequences is beneficial for predictive modeling and interpretability. Several embedding methods have been developed for BCRs, but no direct performance benchmarking exists. Moreover, the impact of the input sequence length and paired-chain information on the prediction remains to be explored. We evaluated the performance of multiple embedding models to predict BCR sequence properties and receptor specificity. Despite the differences in model architectures, most embeddings effectively capture BCR sequence properties and specificity. BCR-specific embeddings slightly outperform general protein language models in predicting specificity. In addition, incorporating full-length heavy chains and paired light chain sequences improve the prediction performance of all embeddings. This study provides insights into the properties of BCR embeddings to improve downstream prediction applications for antibody analysis and discovery.

bioinformatics↗

Distinguished biological adaptation architecture aggravated population differentiation of Tibeto-Burman-speaking people inferred from 500 whole genome data from 39 populations

Tibeto-Burman (TB) people have tried to adapt to the hypoxic, cold and high-UV high-altitude Tibetan Plateau and complex disease exposure in the lowland wet and hot rainforest since the late Paleolithic period. However, the full landscape of genetic history and biological adaptation of geographically diverse TB people and their interaction mechanism remained unknown. We generated a whole-genome-based meta-database of 500 individuals from 39 TB populations from East Asia and Southeast Asia and presented a comprehensive landscape of genetic diversity, admixture history and differentiated adaptative features of geographically different TB people. We identified geography/language-related genetic differentiation among Tibetan Plateau, Tibetan-Yi-Corridor (TYC) and Southeast Asian TB people, consistent with their differentiated admixture process with incoming or indigenous ancestral source populations. A robust genetic connection between TYC people and ancient YR people supported the Northern origin hypothesis of TB people. We reported population substructure-related differentiated biological adaptative signatures between highland Tibetans and lowland TB people and between geographically different Lolo speakers. Highland adaptative EPAS1 and EGLN variants riched in Tibetans but lacked in TYC people whose adaptation is associated with the physical features and skin pigmentation (EDAR and SLC24A5), hepatic alcohol metabolism (ALDH9A1), regulation of cell-cell adhesion of muscle cells (CTNNA3) and immune/fat metabolism-related adaptative signature. TB-related genomic resources provided new insights into the genetic basis of phenotype differences and better reference for the anthropologically-informed sampling design in biomedical and genomic cohort research.

genetics↗

Ribosomal protein control of hematopoietic stem cell transformation through direct, non-canonical regulation of metabolism

We report here that expression of the ribosomal protein, RPL22, is frequently reduced in human myelodysplastic syndrome (MDS) and acute myelogenous leukemia (AML); and, reduced RPL22 expression is associated with worse outcomes. Mice null for Rpl22 display characteristics of an MDS-like syndrome and develop leukemia at an accelerated rate. Rpl22-deficient mice also display enhanced hematopoietic stem cell (HSC) self-renewal and obstructed differentiation potential, which arises not from reduced protein synthesis but from altered metabolism including increased fatty acid oxidation (FAO) and a striking induction of the stemness factor Lin28b in the resulting leukemia. Lin28b promotes a substantial increase in lipid content, upon which the survival of Rpl22-deficient leukemias depends. Altogether, these findings reveal that Rpl22 insufficiency enhances the leukemia potential of HSC through regulation of FAO and promotes leukemogenesis through Lin28b promotion of lipid synthesis. HighlightsO_LIRPL22 insufficiency is observed in MDS/AML and is associated with reduced survival C_LIO_LIRpl22-deficiency produces an MDS-like syndrome and facilitates leukemogenesis C_LIO_LIRpl22-deficiency does not impair global protein synthesis by HSC C_LIO_LIRpl22 controls leukemia survival through control of lipid synthesis C_LI eTOC: Rpl22 controls the function and transformation potential of hematopoietic stem cells through regulation of lipid metabolism.

cancer biology↗

Deciphering deep-sea chemosynthetic symbiosis by single-nucleus RNA-sequencing

Bathymodioline mussels dominate deep-sea methane seep and hydrothermal vent habitats and obtain nutrients and energy primarily through chemosynthetic endosymbiotic bacteria in the bacteriocytes of their gill. However, the molecular mechanisms that orchestrate mussel host-symbiont interactions remain unclear. Here, we constructed a comprehensive cell atlas of the gill in the mussel Gigantidas platifrons from the South China Sea methane seeps (1100m depth) using single-nucleus RNA sequencing (snRNA-seq) and whole-mount in situ hybridisation. We identified 13 types of cells, including three previously unknown ones, and uncovered unknown tissue heterogeneity. Every cell type has a designated function in supporting the gills structure and function, creating an optimal environment for chemosynthesis, and effectively acquiring nutrients from the endosymbiotic bacteria. Analysis of snRNA-seq of in situ transplanted mussels clearly showed the shifts in cell state in response to environmental oscillations. Our findings provide insight into principles of host-symbiont interaction and the bivalves environmental adaption mechanisms.

ecology↗

A marker chromosome in psychosis identifies glycine decarboxylase (GLDC) as a novel regulator of neuronal and synaptic function in the hippocampus

The biological significance of a small supernumerary marker chromosome that results in dosage alterations to chromosome 9p24.1, including triplication of the GLDC gene encoding glycine decarboxylase, in two patients with psychosis is unclear. In an allelic series of copy number variant mouse models, we identify that triplication of Gldc reduces extracellular glycine levels as determined by optical fluorescence resonance energy transfer (FRET) in dentate gyrus (DG) but not in CA1, suppresses long-term potentiation (LTP) in mPP-DG synapses but not in CA3-CA1 synapses, reduces the activity of biochemical pathways implicated in schizophrenia and mitochondrial bioenergetics, and displays deficits in prepulse inhibition, startle habituation, latent inhibition, working memory, sociability and social preference. Our results thus provide a link between a genomic copy number variation, biochemical, cellular and behavioral phenotypes, and further demonstrate that GLDC negatively regulates long-term synaptic plasticity at specific hippocampal synapses, possibly contributing to the development of neuropsychiatric disorders.

neuroscience↗

Spatio-temporal variation of bacterial community structure in two intertidal sediment types of Jiaozhou Bay

The intertidal sediment environment is dynamic and the biofilm bacterial community within it must constantly adjust, but an understanding of the differences in the biofilm bacterial community within sediments of different types is still relatively limited. In this study, the structure of the bacterial community in Jiaozhou Bay sediment biofilms are described using high-throughput 16S rRNA gene sequencing and the effects of temporal change and different sediment environment types are discussed. The Shannon index was significantly higher in sandy samples than in muddy samples. The co-occurrence network was tighter and more species were involved in community building in sandy samples. The principal coordinates analysis identified a significant separation between different sediment types and between stations (LiCun estuary, LC and ZhanQiao Pier, ZQ). Proteobacteria, which had a relative abundance of approximately 50% at all phylum levels, was significantly more abundant at ZQ, while Campilobacterota and Firmicutes were significantly more abundant at LC. The relative abundances of Bacteroidetes, Campilobacterota, Firmicutes, and Chloroflexi were significantly higher in the muddy samples, while Actinobacteria and Proteobacteria were higher in the sandy samples. There were different phylum-level biomarkers between sediment types at different stations. There were also different patterns of functional enrichment in biogeochemical cycles between sediment types and stations with the former having more gene families that differed significantly, highlighting their greater role in determining bacterial function. The RDA results, where each months samples were concentrated individually, showed reduced variation between months when the amplicon sequence variant was replaced by KEGG orthologs, presumably the temporal change had an impact on shaping the intertidal sediment bacterial community, although this was less clear at the gene family level. Random forest prediction yielded a combination of 43 family-level features that responded well to temporal change, reflecting the influence of temporal change on sediment biofilm bacteria. HighlightsO_LISandy sediments have more bacterial species involved in community building. C_LIO_LIDifferent substrates from different stations have their own phylum biomarkers. C_LIO_LISubstrates have a greater influence on shaping bacterial function. C_LIO_LITemporal changes have a greater shaping power on bacteria than on gene families. C_LI Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=121 SRC="FIGDIR/small/542048v1_ufig1.gif" ALT="Figure 1"> View larger version (43K): org.highwire.dtl.DTLVardef@1834e64org.highwire.dtl.DTLVardef@18fc695org.highwire.dtl.DTLVardef@369657org.highwire.dtl.DTLVardef@1c85a13_HPS_FORMAT_FIGEXP M_FIG C_FIG

ecology↗

GbyE: A New Genome Wide Association and Prediction Model based on Genetic by Environmental Interaction

Nowadays, studies on genetic by environment interactions (GxE) are receiving increasing attention because of its theoretical and practical importance in explaining individual behavioral traits. Use information from different environments to improve the statistical power of genome-wide association and prediction in the hope of obtaining individuals with better breeding value is the most expedient way. However, there are significant challenges when performing genome-wide association studies (GWAS) and genomic selection (GS) using multiple environments or traits, mainly because most diseases and quantitative traits have numerous associated loci with minimal effects. Therefore, this study constructed a new genotype design model program (GbyE) for genome-wide association and prediction using Kronecker product, which can enhance the statistical power of GWAS and GS by utilizing the interaction effects of multiple environments or traits. The data of 282 maize, 354 yaks and 255 peaches were used to evaluate the power of the model at different levels of heritability and genetic correlation. The results show that GbyE can provide higher statistical power for the traditional GWAS and GS models in any heritability and genetic correlation, and can detect more real loci. In addition, GbyE has increased statistical power to three Bayesian models (BRR, BayesA, and BayesCpi). GbyE can make full use of multiple environment or trait informations to increase the statistical power of the model, which can help us understand the GxE and provide a method for predicting association loci for complex traits.

bioinformatics↗

Development of Synthetic Modulator Enabling Long-Term Propagation and Neurogenesis of Human-Derived Neural Progenitor Cells

Neural progenitor cells (NPCs) are important cells for in vitro drug screening and the cell-based therapy for brain-related disorders, which requires well-defined and reproducible culture systems. Current strategy the use of protein growth factors presents challenges in terms of reproducibility and cost. In this study, we have developed a novel DNA-based modulator to regulate FGFR signaling of NPCs, enabling maintenance of the stemness over 50 passages and neurogenesis towards neurons. The DNA-based FGFR-agonist effectively promoted FGFR1 phosphorylation and activated the downstream ERK signaling pathway in FGFR1-positive cells. Using human embryonic stem cell lines, we differentiated them into NPCs and replaced basic fibroblast growth factor (bFGF) in the regulator culture medium with DNA-based FGFR-agonist for artificially elicited FGFR signaling. The results demonstrated that the FGFR-agonist could promote NPCs proliferation and neurosphere formation, recapitulating the function of bFGF. Notably, transcriptomic analysis revealed that FGFR-agonist could customize the stemness-associated transcription program, while decouples the neuronal differentiation program, highly resembling that the native ligand, bFGF. Moreover, our culture condition facilitated the successful propagation of NPCs for over 50 passages, while retaining their ability to efficiently differentiate into neurons. Overall, our approach provides a highly effective method for expanding NPCs, offering new opportunities for disease-in-dish research and drug screening for neural degeneration.

neuroscience↗

Dissociating instructive from permissive roles of brain circuits with reversible neural activity manipulations

Recent work has demonstrated that both permanent lesions and acute inactivation experiments can lead to erroneous conclusions about the causal role of brain areas in specific behaviors, casting serious doubt on major avenues by which neuroscientists study the brain. To overcome this challenge, we developed a three-stage optogenetic approach which leverages the ability to precisely control the temporal period of regional inactivation with either brief or sustained illumination, enabling investigators to dissociate between putative permissive and instructive roles of brain areas in behavior. We applied this approach to the mouse primary visual cortex (V1) to probe whether V1 is permissive or instructive for the detection low contrast stimuli. Acute inactivation of V1 drastically suppressed performance, but during persistent inactivation, the animals contrast detection recovered to pre-silencing levels. This recovery was itself reversible, as returning the animals to intermittent V1 inactivation reinstated the behavioral deficit. These results argue that V1 is the default circuit mice use to detect visual stimuli, but in its absence, other regions can compensate for it. This novel, temporally controllable optogenetic perturbation paradigm should be useful in other brain circuits to assess whether they are instructive or permissive in a brain function or behavior.

neuroscience↗

Single-cell transcriptome landscape of circulating CD4+ T cell populations in human autoimmune diseases

CD4+ T cells are a key mediator of various autoimmune diseases; however, how they contribute to disease development remains obscure primarily because of their cellular heterogeneity. Here, we evaluated CD4+ T cell subpopulations by decomposition-based transcriptome characterization together with canonical clustering strategies. This approach identified 12 independent transcriptional gene programs governing whole CD4+ T cell heterogeneity, which can explain the ambiguity of canonical clustering. In addition, we performed a meta-analysis using public single-cell data sets of over 1.8M peripheral CD4+ T cells from 953 individuals by projecting cells onto the reference and cataloged cell frequency and qualitative alterations of the populations in 20 diseases. The analyses revealed that the 12 transcriptional programs were useful in characterizing each autoimmune disease and predicting its clinical status. Moreover, genetic variants associated with autoimmune diseases showed disease-specific enrichment within the 12 gene programs. The results collectively provide a landscape of single-cell transcriptomes of CD4+ T cell subpopulations involved in autoimmune disease.

immunology↗

SeMOE allows for quantitative glycan perception and exhibits anti-cancer potentiality

Metabolic oligosaccharide engineering (MOE) is a classical chemical approach to perturb, profile and perceive glycans in physiological systems, but probes upon bioorthogonal reaction require accessibility and background signal readout makes it challenging to achieve absolute glycan quantification. Here we develop SeMOE, a selenosugar-based metabolic oligosaccharide engineering strategy that combines elemental analysis and MOE to enable the absolute quantification and mass spectrometric imaging of glycome in a concise procedure. We demonstrate that SeMOE probes allow for perception, absolute quantification and visualization of glycans in diverse biological contexts. We demonstrate that chemical reporters on conventional MOE can be integrated into a bifunctional SeMOE probe to provide multimodality signal readouts. We further show the anti-cancer potentiality of SeMOE probes. SeMOE thus provides a convenient and simplified method to "see more" of the glyco-world.

bioengineering↗