Eliciting a single amino acid change by vaccination generates antibody protection against group 1 and group 2 influenza A viruses.

Broadly neutralizing antibodies (bnAbs) targeting the hemagglutinin (HA) stem of influenza A viruses (IAVs) tend to be effective against either group 1 or group 2 viral diversity. In rarer cases, intergroup protective bnAbs can be generated by human antibody paratopes that accommodate the conserved glycan differences between the group 1 and group 2 stems. We applied germline-engaging nanoparticle immunogens to elicit a class of cross-group bnAbs from physiological precursor frequency within a humanized mouse model. Cross-group protection depended on the presence of the human bnAb precursors within the B cell repertoire, and the vaccine-expanded antibodies enriched for an N55T substitution in the CDRH2 loop, a hallmark of the bnAb class. Structurally, this single mutation introduced a flexible fulcrum to accommodate glycosylation differences and could alone enable cross-group protection. Thus, broad IAV immunity can be expanded from the germline repertoire via minimal antigenic input and an exceptionally simple antibody development pathway.

Allelic polymorphism controls autoreactivity and vaccine elicitation of human broadly neutralizing antibodies against influenza virus.

Human broadly neutralizing antibodies (bnAbs) targeting the hemagglutinin stalk of group 1 influenza A viruses (IAVs) are biased for IGHV1-69 alleles that use phenylalanine (F54) but not leucine (L54) within their CDRH2 loops. Despite this, we demonstrated that both alleles encode for human IAV bnAbs that employ structurally convergent modes of contact to the same epitope. To resolve differences in lineage expandability, we compared F54 versus L54 as substrate within humanized mice, where antibodies develop with human-like CDRH3 diversity but are restricted to single VH genes. While both alleles encoded for bnAb precursors, only F54 IGHV1-69 supported elicitation of heterosubtypic serum bnAbs following immunization with a stalk-only nanoparticle vaccine. L54 IGHV1-69 was unproductive, co-encoding for anergic B cells and autoreactive stalk antibodies that were cleared from B cell memory. Moreover, human stalk antibodies also demonstrated L54-dependent autoreactivity. Therefore, IGHV1-69 polymorphism, which is skewed ethnically, gates tolerance and vaccine expandability of influenza bnAbs.

Guidelines for organizing accessible and inclusive research retreats.

Research retreats are elements of scientific graduate training programs. Although expected to provide strong educational value, some students are reluctant to attend. Here, we identify participation barriers and provide guidelines for retreat design that minimize obstacles and establish an inclusive environment to improve attendance and enrichment for all attendees.

Germline-Encoded Affinity for Cognate Antigen Enables Vaccine Amplification of a Human Broadly Neutralizing Response against Influenza Virus.

Antibody paratopes are formed by hypervariable complementarity-determining regions (CDRH3s) and variable gene-encoded CDRs. The latter show biased usage in human broadly neutralizing antibodies (bnAbs) against both HIV and influenza virus, suggesting the existence of gene-endowed targeting solutions that may be amenable to pathway amplification. To test this, we generated transgenic mice with human CDRH3 diversity but simultaneously constrained to individual user-defined human immunoglobulin variable heavy-chain (VH) genes, including IGHV1-69, which shows biased usage in human bnAbs targeting the hemagglutinin stalk of group 1 influenza A viruses. Sequential immunization with a stalk-only hemagglutinin nanoparticle elicited group 1 bnAbs, but only in IGHV1-69 mice. This VH-endowed response required minimal affinity maturation, was elicited alongside pre-existing influenza immunity, and when IGHV1-69 B cells were diluted to match the frequency measured in humans. These results indicate that the human repertoire could, in principle, support germline-encoded bnAb elicitation using a single recombinant hemagglutinin immunogen.

The Theory and Neuroscience of Cerebellar Cognition.

Cerebellar neuroscience has undergone a paradigm shift. The theories of the universal cerebellar transform and dysmetria of thought and the principles of organization of cerebral cortical connections, together with neuroanatomical, brain imaging, and clinical observations, have recontextualized the cerebellum as a critical node in the distributed neural circuits subserving behavior. The framework for cerebellar cognition stems from the identification of three cognitive representations in the posterior lobe, which are interconnected with cerebral association areas and distinct from the primary and secondary cerebellar sensorimotor representations linked with the spinal cord and cerebral motor areas. Lesions of the anterior lobe primary sensorimotor representations produce dysmetria of movement, the cerebellar motor syndrome. Lesions of the posterior lobe cognitive-emotional cerebellum produce dysmetria of thought and emotion, the cerebellar cognitive affective/Schmahmann syndrome. The notion that the cerebellum modulates thought and emotion in the same way that it modulates motor control advances the understanding of the mechanisms of cognition and opens new therapeutic opportunities in behavioral neurology and neuropsychiatry.

Design of universal Ebola virus vaccine candidates via immunofocusing.

The Ebola virus causes hemorrhagic fever in humans and poses a significant threat to global public health. Although two viral vector vaccines have been approved to prevent Ebola virus disease, they are distributed in the limited ring vaccination setting and only indicated for prevention of infection from orthoebolavirus zairense (EBOV)-one of three orthoebolavirus species that have caused previous outbreaks. Ebola virus glycoprotein GP mediates viral infection and serves as the primary target of neutralizing antibodies. Here, we describe a universal Ebola virus vaccine approach using a structure-guided design of candidates with hyperglycosylation that aims to direct antibody responses away from variable regions and toward conserved epitopes of GP. We first determined the hyperglycosylation landscape on Ebola virus GP and used that to generate hyperglycosylated GP variants with two to four additional glycosylation sites to mask the highly variable glycan cap region. We then created vaccine candidates by displaying wild-type or hyperglycosylated GP variants on ferritin nanoparticles (Fer). Immunization with these antigens elicited potent neutralizing antisera against EBOV in mice. Importantly, we observed consistent cross-neutralizing activity against Bundibugyo virus and Sudan virus from hyperglycosylated GP-Fer with two or three additional glycans. In comparison, elicitation of cross-neutralizing antisera was rare in mice immunized with wild-type GP-Fer. These results demonstrate a potential strategy to develop universal Ebola virus vaccines that confer cross-protective immunity against existing and emerging filovirus species.

scBOL: a universal cell type identification framework for single-cell and spatial transcriptomics data.

MOTIVATION: Over the past decade, single-cell transcriptomic technologies have experienced remarkable advancements, enabling the simultaneous profiling of gene expressions across thousands of individual cells. Cell type identification plays an essential role in exploring tissue heterogeneity and characterizing cell state differences. With more and more well-annotated reference data becoming available, massive automatic identification methods have sprung up to simplify the annotation process on unlabeled target data by transferring the cell type knowledge. However, in practice, the target data often include some novel cell types that are not in the reference data. Most existing works usually classify these private cells as one generic 'unassigned' group and learn the features of known and novel cell types in a coupled way. They are susceptible to the potential batch effects and fail to explore the fine-grained semantic knowledge of novel cell types, thus hurting the model's discrimination ability. Additionally, emerging spatial transcriptomic technologies, such as in situ hybridization, sequencing and multiplexed imaging, present a novel challenge to current cell type identification strategies that predominantly neglect spatial organization. Consequently, it is imperative to develop a versatile method that can proficiently annotate single-cell transcriptomics data, encompassing both spatial and non-spatial dimensions. RESULTS: To address these issues, we propose a new, challenging yet realistic task called universal cell type identification for single-cell and spatial transcriptomics data. In this task, we aim to give semantic labels to target cells from known cell types and cluster labels to those from novel ones. To tackle this problem, instead of designing a suboptimal two-stage approach, we propose an end-to-end algorithm called scBOL from the perspective of Bipartite prototype alignment. Firstly, we identify the mutual nearest clusters in reference and target data as their potential common cell types. On this basis, we mine the cycle-consistent semantic anchor cells to build the intrinsic structure association between two data. Secondly, we design a neighbor-aware prototypical learning paradigm to strengthen the inter-cluster separability and intra-cluster compactness within each data, thereby inspiring the discriminative feature representations. Thirdly, driven by the semantic-aware prototypical learning framework, we can align the known cell types and separate the private cell types from them among reference and target data. Such an algorithm can be seamlessly applied to various data types modeled by different foundation models that can generate the embedding features for cells. Specifically, for non-spatial single-cell transcriptomics data, we use the autoencoder neural network to learn latent low-dimensional cell representations, and for spatial single-cell transcriptomics data, we apply the graph convolution network to capture molecular and spatial similarities of cells jointly. Extensive results on our carefully designed evaluation benchmarks demonstrate the superiority of scBOL over various state-of-the-art cell type identification methods. To our knowledge, we are the pioneers in presenting this pragmatic annotation task, as well as in devising a comprehensive algorithmic framework aimed at resolving this challenge across varied types of single-cell data. Finally, scBOL is implemented in Python using the Pytorch machine-learning library, and it is freely available at https://github.com/aimeeyaoyao/scBOL.

Expanding Archaeal Diversity and Phylogeny: Past, Present, and Future.

The discovery of the Archaea is a major scientific hallmark of the twentieth century. Since then, important features of their cell biology, physiology, ecology, and diversity have been revealed. Over the course of some 40 years, the diversity of known archaea has expanded from 2 to about 30 phyla comprising over 20,000 species. Most of this archaeal diversity has been revealed by environmental 16S rRNA gene amplicon sequencing surveys using a broad range of universal and targeted primers. Of the few primers that target a large fraction of known archaeal diversity, all display a bias against recently discovered lineages, which limits studies aiming to survey overall archaeal diversity. Induced by genomic exploration of archaeal diversity, and improved phylogenomics approaches, archaeal taxonomic classification has been frequently revised. Due to computational limitations and continued discovery of new lineages, a stable archaeal phylogeny is not yet within reach. Obtaining phylogenetic and taxonomic consensus of archaea should be a high priority for the archaeal research community.

The risk of losing health insurance in the United States is large, and remained so after the Affordable Care Act.

Health insurance coverage in the United States is highly uncertain. In the post-Affordable Care Act (ACA), pre-COVID United States, we estimate that while 12.5% of individuals under 65 are uninsured at a point in time, twice as many-one in four-are uninsured at some point over a 2-y period. Moreover, the risk of losing insurance remained virtually unchanged with the introduction of the landmark ACA. Risk of insurance loss is particularly high for those with health insurance through Medicaid or private exchanges; they have a 20% chance of losing coverage at some point over a 2-y period, compared to 8.5% for those with employer-provided coverage. Those who lose insurance can experience prolonged periods without coverage; about half are still uninsured 6 mo later, and almost one-quarter are uninsured for the subsequent 2 y. These facts suggest that research and policy attention should focus not only on the "headline number" of the share of the population uninsured at a point in time, but also on the stability and certainty (or lack thereof) of being insured.

Low-sugar universal mRNA vaccine against coronavirus variants with deletion of glycosites in the S2 or stem of SARS-CoV-2 spike messenger RNA (mRNA).

Since the outbreak of Severe Acute Respiratory Syndrome Virus-2 (SARS-CoV-2) in 2019, more than 15 million spike protein sequences have been identified, raising a new challenge for the development of a broadly protective vaccine against the various emerging variants. We found that the virus, like most other human viruses, depends on host-made glycans to shield the conserved epitopes on spike protein from immune response and demonstrated that deletion of the glycan shields exposed highly conserved epitopes and elicited broadly protective immune responses. In this study, we identified 17 conserved epitopes from 14 million spike protein sequences and 11 of the conserved epitopes are in the S2 domain, including the six most conserved epitopes in the stem region. We also demonstrated that deletion of the glycosites in the spike messenger RNA (mRNA) S2 domain or the stem region exposed the highly conserved epitopes and elicited broadly protective immune responses, particularly CD-8+ T cell response against various SARS-CoV-2 variants, and other human coronaviruses including MERS, SARS viruses, and those causing common cold.

Electron transport chains as a window into the earliest stages of evolution.

The origin and early evolution of life is generally studied under two different paradigms: bottom up and top down. Prebiotic chemistry and early Earth geochemistry allow researchers to explore possible origin of life scenarios. But for these "bottom-up" approaches, even successful experiments only amount to a proof of principle. On the other hand, "top-down" research on early evolutionary history is able to provide a historical account about ancient organisms, but is unable to investigate stages that occurred during and just after the origin of life. Here, we consider ancient electron transport chains (ETCs) as a potential bridge between early evolutionary history and a protocellular stage that preceded it. Current phylogenetic evidence suggests that ancestors of several extant ETC components were present at least as late as the last universal common ancestor of life. In addition, recent experiments have shown that some aspects of modern ETCs can be replicated by minerals, protocells, or organic cofactors in the absence of biological proteins. Here, we discuss the diversity of ETCs and other forms of chemiosmotic energy conservation, describe current work on the early evolution of membrane bioenergetics, and advocate for several lines of research to enhance this understanding by pairing top-down and bottom-up approaches.

Cyclic AMP binding to a universal stress protein in Mycobacterium tuberculosis is essential for viability.

Mycobacterial genomes encode multiple adenylyl cyclases and cAMP effector proteins, underscoring the diverse ways these bacteria utilize cAMP. We identified universal stress proteins, Rv1636 and MSMEG_3811 in Mycobacterium tuberculosis and Mycobacterium smegmatis, respectively, as abundantly expressed, novel cAMP-binding proteins. Rv1636 is secreted via the SecA2 secretion system in M. tuberculosis but is not directly responsible for the efflux of cAMP from the cell. In slow-growing mycobacteria, intrabacterial concentrations of Rv1636 were equivalent to the concentrations of cAMP present in the cell. In contrast, levels of intrabacterial MSMEG_3811 in M. smegmatis were lower than that of cAMP and therefore, overexpression of Rv1636 increased levels of "bound" cAMP. While msmeg_3811 could be readily deleted from the genome of M. smegmatis, we found that the rv1636 gene is essential for the viability of M. tuberculosis and is dependent on the cAMP-binding ability of Rv1636. Therefore, Rv1636 may function to regulate cAMP signaling by direct sequestration of the second messenger. This is the first evidence of a "sponge" for any second messenger in bacterial signaling that would allow mycobacterial cells to regulate the available intrabacterial "free" pool of cAMP.

Streptococcus pyogenes Cas9 ribonucleoprotein delivery for efficient, rapid and marker-free gene editing in Trypanosoma and Leishmania.

Kinetoplastids are unicellular eukaryotic flagellated parasites found in a wide range of hosts within the animal and plant kingdoms. They are known to be responsible in humans for African sleeping sickness (Trypanosoma brucei), Chagas disease (Trypanosoma cruzi), and various forms of leishmaniasis (Leishmania spp.), as well as several animal diseases with important economic impact (African trypanosomes, including Trypanosoma congolense). Understanding the biology of these parasites necessarily implies the ability to manipulate their genomes. In this study, we demonstrate that transfection of a ribonucleoprotein complex, composed of recombinant Streptococcus pyogenes Cas9 (SpCas9) and an in vitro-synthesized guide RNA, results in rapid and efficient genetic modifications of trypanosomatids, in marker-free conditions. This approach was successfully developed to inactivate, delete, and mutate candidate genes in various stages of the life cycle of T. brucei and T. congolense, and Leishmania promastigotes. The functionality of SpCas9 in these parasites now provides, to the research community working on these parasites, a rapid and efficient method of genome editing, without requiring plasmid construction and selection by antibiotics but requires only cloning and PCR screening of the clones. Importantly, this approach is adaptable to any wild-type parasite.

Origin and Evolution of the Universal Genetic Code.

The standard genetic code (SGC) is virtually universal among extant life forms. Although many deviations from the universal code exist, particularly in organelles and prokaryotes with small genomes, they are limited in scope and obviously secondary. The universality of the code likely results from the combination of a frozen accident, i.e., the deleterious effect of codon reassignment in the SGC, and the inhibitory effect of changes in the code on horizontal gene transfer. The structure of the SGC is nonrandom and ensures high robustness of the code to mutational and translational errors. However, this error minimization is most likely a by-product of the primordial code expansion driven by the diversification of the repertoire of protein amino acids, rather than a direct result of selection. Phylogenetic analysis of translation system components, in particular aminoacyl-tRNA synthetases, shows that, at a stage of evolution when the translation system had already attained high fidelity, the correspondence between amino acids and cognate codons was determined by recognition of amino acids by RNA molecules, i.e., proto-tRNAs. We propose an experimentally testable scenario for the evolution of the code that combines recognition of amino acids by unique sites on proto-tRNAs (distinct from the anticodons), expansion of the code via proto-tRNA duplication, and frozen accident.

Trimerized S expressed by modified vaccinia virus Ankara (MVA) confers superior protection against lethal SARS-CoV-2 challenge in mice.

The reoccurrence of successive waves of SARS-CoV-2 variants suggests the exploration of more vaccine alternatives is imperative. Modified vaccinia virus Ankara (MVA) is a virus vector exhibiting excellent safety as well as efficacy for vaccine development. Here, a series of recombinant MVAs (rMVAs) expressing monomerized or trimerized S proteins from different SARS-CoV-2 variants are engineered. Trimerized S expressed from rMVAs is found predominantly as trimers on the surface of infected cells. Remarkably, immunization of mice with rMVAs demonstrates that S expressed in trimer elicits higher levels of binding IgG and IgA, as well as neutralizing antibodies for matched and mismatched S proteins than S in the monomer. In addition, trimerized S expressed by rMVA induces enhanced cytotoxic T-cell responses than S in the monomer. Importantly, the rMVA vaccines expressing trimerized S exhibit superior protection against a lethal SARS-CoV-2 challenge as the immunized animals all survive without displaying any pathological conditions. This study suggests that opting for trimerized S may represent a more effective approach and highlights that the MVA platform serves as an ideal foundation to continuously advance SARS-CoV-2 vaccine development. IMPORTANCE: MVA is a promising vaccine vector and has been approved as a vaccine for smallpox and mpox. Our analyses suggested that recombinant MVA expressing S in trimer (rMVA-ST) elicited robust cellular and humoral immunity and was more effective than MVA-S-monomer. Importantly, the rMVA-ST vaccine was able to stimulate decent cross-reactive neutralization against pseudoviruses packaged using S from different sublineages, including Wuhan, Delta, and Omicron. Remarkably, mice immunized with rMVA-ST were completely protected from a lethal challenge of SARS-CoV-2 without displaying any pathological conditions. Our results demonstrated that an MVA vectored vaccine expressing trimerized S is a promising vaccine candidate for SARS-CoV-2 and the strategy might be adapted for future vaccine development for coronaviruses.

UniDL4BioPep: a universal deep learning architecture for binary classification in peptide bioactivity.

Identification of potent peptides through model prediction can reduce benchwork in wet experiments. However, the conventional process of model buildings can be complex and time consuming due to challenges such as peptide representation, feature selection, model selection and hyperparameter tuning. Recently, advanced pretrained deep learning-based language models (LMs) have been released for protein sequence embedding and applied to structure and function prediction. Based on these developments, we have developed UniDL4BioPep, a universal deep-learning model architecture for transfer learning in bioactive peptide binary classification modeling. It can directly assist users in training a high-performance deep-learning model with a fixed architecture and achieve cutting-edge performance to meet the demands in efficiently novel bioactive peptide discovery. To the best of our best knowledge, this is the first time that a pretrained biological language model is utilized for peptide embeddings and successfully predicts peptide bioactivities through large-scale evaluations of those peptide embeddings. The model was also validated through uniform manifold approximation and projection analysis. By combining the LM with a convolutional neural network, UniDL4BioPep achieved greater performances than the respective state-of-the-art models for 15 out of 20 different bioactivity dataset prediction tasks. The accuracy, Mathews correlation coefficient and area under the curve were 0.7-7, 1.23-26.7 and 0.3-25.6% higher, respectively. A user-friendly web server of UniDL4BioPep for the tested bioactivities is established and freely accessible at https://nepc2pvmzy.us-east-1.awsapprunner.com. The source codes, datasets and templates of UniDL4BioPep for other bioactivity fitting and prediction tasks are available at https://github.com/dzjxzyd/UniDL4BioPep.

Immunosuppressant therapy averts rejection of allogeneic FKBP1A-disrupted CAR-T cells.

Chimeric antigen receptor (CAR) T cells from allogeneic donors promise "off-the-shelf" availability by overcoming challenges associated with autologous cell manufacturing. However, recipient immunologic rejection of allogeneic CAR-T cells may decrease their in vivo lifespan and limit treatment efficacy. Here, we demonstrate that the immunosuppressants rapamycin and tacrolimus effectively mitigate allorejection of HLA-mismatched CAR-T cells in immunocompetent humanized mice, extending their in vivo persistence to that of syngeneic humanized mouse-derived CAR-T cells. In turn, genetic knockout (KO) of FKBP prolyl isomerase 1A (FKBP1A), which encodes a protein targeted by both drugs, was necessary to confer CD19-specific CAR-T cells (19CAR) robust functional resistance to these immunosuppressants. FKBP1AKO 19CAR-T cells maintained potent in vitro functional profiles and controlled in vivo tumor progression similarly to untreated 19CAR-T cells. Moreover, immunosuppressant treatment averted in vivo allorejection permitting FKBP1AKO 19CAR-T cell-driven B cell aplasia. Thus, we demonstrate that genome engineering enables immunosuppressant treatment to improve the therapeutic potential of universal donor-derived CAR-T cells.

Engineering allorejection-resistant CAR-NKT cells from hematopoietic stem cells for off-the-shelf cancer immunotherapy.

The clinical potential of current FDA-approved chimeric antigen receptor (CAR)-engineered T (CAR-T) cell therapy is encumbered by its autologous nature, which presents notable challenges related to manufacturing complexities, heightened costs, and limitations in patient selection. Therefore, there is a growing demand for off-the-shelf universal cell therapies. In this study, we have generated universal CAR-engineered NKT (UCAR-NKT) cells by integrating iNKT TCR engineering and HLA gene editing on hematopoietic stem cells (HSCs), along with an ex vivo, feeder-free HSC differentiation culture. The UCAR-NKT cells are produced with high yield, purity, and robustness, and they display a stable HLA-ablated phenotype that enables resistance to host cell-mediated allorejection. These UCAR-NKT cells exhibit potent antitumor efficacy to blood cancers and solid tumors, both in vitro and in vivo, employing a multifaceted array of tumor-targeting mechanisms. These cells are further capable of altering the tumor microenvironment by selectively depleting immunosuppressive tumor-associated macrophages and myeloid-derived suppressor cells. In addition, UCAR-NKT cells demonstrate a favorable safety profile with low risks of graft-versus-host disease and cytokine release syndrome. Collectively, these preclinical studies underscore the feasibility and significant therapeutic potential of UCAR-NKT cell products and lay a foundation for their translational and clinical development.

Universal healthcare as pandemic preparedness: The lives and costs that could have been saved during the COVID-19 pandemic.

The fragmented and inefficient healthcare system in the United States leads to many preventable deaths and unnecessary costs every year. During a pandemic, the lives saved and economic benefits of a single-payer universal healthcare system relative to the status quo would be even greater. For Americans who are uninsured and underinsured, financial barriers to COVID-19 care delayed diagnosis and exacerbated transmission. Concurrently, deaths beyond COVID-19 accrued from the background rate of uninsurance. Universal healthcare would alleviate the mortality caused by the confluence of these factors. To evaluate the repercussions of incomplete insurance coverage in 2020, we calculated the elevated mortality attributable to the loss of employer-sponsored insurance and to background rates of uninsurance, summing with the increased COVID-19 mortality due to low insurance coverage. Incorporating the demography of the uninsured with age-specific COVID-19 and nonpandemic mortality, we estimated that a single-payer universal healthcare system would have saved about 212,000 lives in 2020 alone. We also calculated that US$105.6 billion of medical expenses associated with COVID-19 hospitalization could have been averted by a single-payer universal healthcare system over the course of the pandemic. These economic benefits are in addition to US$438 billion expected to be saved by single-payer universal healthcare during a nonpandemic year.

Two-dimensional quantum universality in the spin-1/2 triangular-lattice quantum antiferromagnet Na2BaCo(PO4)2.

An interplay of geometrical frustration and strong quantum fluctuations in a spin-1/2 triangular-lattice antiferromagnet (TAF) can lead to exotic quantum states. Here, we report the neutron-scattering, magnetization, specific heat, and magnetocaloric studies of the recently discovered spin-1/2 TAF Na2BaCo(PO4)2, which can be described by a spin-1/2 easy axis XXZ model. The zero-field neutron diffraction experiment reveals an incommensurate antiferromagnetic ground state with a significantly reduced ordered moment of about 0.54(2) µB/Co. Different magnetic phase diagrams with magnetic fields in the ab plane and along the easy c-axis were extracted based on the magnetic susceptibility, specific heat, and elastic neutron-scattering results. In addition, two-dimensional (2D) spin dispersion in the triangular plane was observed in the high-field polarized state, and microscopic exchange parameters of the spin Hamiltonian have been determined through the linear spin wave theory. Consistently, quantum critical behaviors with the universality class of d = 2 and νz = 1 were established in the vicinity of the saturation field, where a Bose-Einstein condensation (BEC) of diluted magnons occurs. The newly discovered quantum criticality and fractional magnetization phase in this ideal spin-1/2 TAF present exciting opportunities for exploring exotic quantum phenomena.