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Inspired by structures of natural metalloenzymes, a biomimetic synthetic strategy is developed for scalable synthesis of porous Fe-N 3 single atom nanozymes (pFeSAN) using hemoglobin as Fe-source and template. pFeSAN delivers 3.3- and 8791-fold higher oxidase-like activity than Fe-N 4 and Fe 3 O 4 nanozymes. The high catalytic performance is attributed to (1) the suppressed aggregation of atomically dispersed Fe; (2) facilitated mass transfer and maximized exposure of active sites for the created mesopores by thermal removal of hemoglobin (2 ~ 3 nm); and (3) unique electronic configuration of Fe-N 3 for the oxygen-to-water oxidation pathway (analogy with natural cytochrome c oxidase). The pFeSAN is successfully demonstrated for the rapid colorimetric detection of glutathione with a low limit of detection (2.4 nM) and wide range (50 nM–1 mM), and further developed as a real-time, facile, rapid (~6 min) and precise visualization analysis methodology of tumors via glutathione level, showing its potentials for diagnostic and clinic applications. It is needed yet difficult to achieve a strategy for synthesizing single-atom nanozymes that integrate atomic metal dispersion, elevated mass transport and tailorable coordination environment. Here, the authors address this issue by developing a biomimetic synthetic strategy and demonstrate the application of the resultant single-atom Fe nanozymes for tumor visual identification.

Synthetic biology will transform how we grow food, what we eat, and where we source materials and medicines. Here I have selected six products that are now on the market, highlighting the underlying technologies and projecting forward to the future that can be expected over the next ten years.

Exosomes and extracellular vesicles (EV) are increasingly being explored as circulating biomarkers, but their heterogenous composition will likely mandate the development of multiplexed EV technologies. Iteratively multiplexed analyses of near single EVs have been challenging to implement beyond a few colors during spectral sensing. Here we developed a multiplexed analysis of EV technique (MASEV) to interrogate thousands of individual EVs during 5 cycles of multi-channel fluorescence staining for 15 EV biomarkers. Contrary to the common belief, we show that: several markers proposed to be ubiquitous are less prevalent than believed; multiple biomarkers concur in single vesicles but only in small fractions; affinity purification can lead to loss of rare EV subtypes; and deep profiling allows detailed analysis of EV, potentially improving the diagnostic content. These findings establish the potential of MASEV for uncovering fundamental EV biology and heterogeneity and increasing diagnostic specificity. Multiplexed analyses of near single EVs is currently challenging. Here the authors report the method MASEV, multiplexed analysis of EVs, to interrogate thousands of individual EVs during 5 cycles of multi-channel fluorescence staining for 15 EV biomarkers.

Afterglow luminescent probes with high signal-to-background ratio show promise for in vivo imaging; however, such probes that can be selectively delivered into target sites and switch on afterglow luminescence remain limited. We optimize an organic electrochromic material and integrate it into near-infrared (NIR) photosensitizer (silicon 2,3-naphthalocyanine bis(trihexylsilyloxide) and (poly[2-methoxy-5-(2-ethylhexyloxy)-1,4-phenylenevinylene]) containing nanoparticles, developing an H 2 S-activatable NIR afterglow probe ( F1 2+ -ANP). F1 2+ -ANP displays a fast reaction rate (1563 ± 141 M −1 s −1 ) and large afterglow turn-on ratio (~122-fold) toward H 2 S, enabling high-sensitivity and -specificity measurement of H 2 S concentration in bloods from healthy persons, hepatic or colorectal cancer patients. We further construct a hepatic-tumor-targeting and H 2 S-activatable afterglow probe ( F1 2+ -ANP-Gal) for noninvasive, real-time imaging of tiny subcutaneous HepG2 tumors (<3 mm in diameter) and orthotopic liver tumors in mice. Strikingly, F1 2+ -ANP-Gal accurately delineates tumor margins in excised hepatic cancer specimens, which may facilitate intraoperative guidance of hepatic cancer surgery. Afterglow imaging probes are of interest for in vivo imaging due to high signal-to-background ratios. Here, the authors report on an afterglow nanoparticle which is activated by hydrogen sulphide and demonstrate the measurement of hydrogen sulphide levels and the labelling of hepatic cancer specimens in vivo.

Given that Type-I photosensitizers (PSs) have hypoxia tolerance, developing general approaches to prepare Type-I PSs is of great importance, but remains a challenge. Here, we report a supramolecular strategy for the preparation of Type-I photodynamic agents, which simultaneously generate strong oxidizing cationic radicals and superoxide radicals, by introducing electron acceptors to the existing Type-II PSs. As a proof-of-concept, three electron acceptors were designed and co-assembled with a classical PS to produce quadruple hydrogen-bonded supramolecular photodynamic agents. The photo-induced electron transfer from the PS to the adjacent electron acceptor occurs efficiently, leading to the generation of a strong oxidizing PS +• and an anionic radical of the acceptor, which further transfers an electron to oxygen to form O 2 −• . In addition, these photodynamic agents induce direct photocatalytic oxidation of NADH with a turnover frequency as high as 53.7 min −1 , which offers an oxygen-independent mechanism to damage tumors. Tumour hypoxia is a major issue for conventional photodynamic therapies, Here, the authors report on the supramolecular assembly of electron acceptors with photosensitizers which have improved reactive oxygen species production and are able to directly oxidise NHDH and demonstrate application against hypoxic tumours.

Spontaneous animal behaviour is built from action modules that are concatenated by the brain into sequences 1 , 2 . However, the neural mechanisms that guide the composition of naturalistic, self-motivated behaviour remain unknown. Here we show that dopamine systematically fluctuates in the dorsolateral striatum (DLS) as mice spontaneously express sub-second behavioural modules, despite the absence of task structure, sensory cues or exogenous reward. Photometric recordings and calibrated closed-loop optogenetic manipulations during open field behaviour demonstrate that DLS dopamine fluctuations increase sequence variation over seconds, reinforce the use of associated behavioural modules over minutes, and modulate the vigour with which modules are expressed, without directly influencing movement initiation or moment-to-moment kinematics. Although the reinforcing effects of optogenetic DLS dopamine manipulations vary across behavioural modules and individual mice, these differences are well predicted by observed variation in the relationships between endogenous dopamine and module use. Consistent with the possibility that DLS dopamine fluctuations act as a teaching signal, mice build sequences during exploration as if to maximize dopamine. Together, these findings suggest a model in which the same circuits and computations that govern action choices in structured tasks have a key role in sculpting the content of unconstrained, high-dimensional, spontaneous behaviour. Photometric recordings and optogenetic manipulation show that dopamine fluctuations in the dorsolateral striatum in mice modulate the use, sequencing and vigour of behavioural modules during spontaneous behaviour.

The SARS-CoV-2 Omicron BA.1 variant emerged in 2021 1 and has multiple mutations in its spike protein 2 . Here we show that the spike protein of Omicron has a higher affinity for ACE2 compared with Delta, and a marked change in its antigenicity increases Omicron’s evasion of therapeutic monoclonal and vaccine-elicited polyclonal neutralizing antibodies after two doses. mRNA vaccination as a third vaccine dose rescues and broadens neutralization. Importantly, the antiviral drugs remdesivir and molnupiravir retain efficacy against Omicron BA.1. Replication was similar for Omicron and Delta virus isolates in human nasal epithelial cultures. However, in lung cells and gut cells, Omicron demonstrated lower replication. Omicron spike protein was less efficiently cleaved compared with Delta. The differences in replication were mapped to the entry efficiency of the virus on the basis of spike-pseudotyped virus assays. The defect in entry of Omicron pseudotyped virus to specific cell types effectively correlated with higher cellular RNA expression of TMPRSS2 , and deletion of TMPRSS2 affected Delta entry to a greater extent than Omicron. Furthermore, drug inhibitors targeting specific entry pathways 3 demonstrated that the Omicron spike inefficiently uses the cellular protease TMPRSS2, which promotes cell entry through plasma membrane fusion, with greater dependency on cell entry through the endocytic pathway. Consistent with suboptimal S1/S2 cleavage and inability to use TMPRSS2, syncytium formation by the Omicron spike was substantially impaired compared with the Delta spike. The less efficient spike cleavage of Omicron at S1/S2 is associated with a shift in cellular tropism away from TMPRSS2-expressing cells, with implications for altered pathogenesis. The spike protein of the Omicron variant of SARS-CoV-2 has a higher affinity for ACE2 than Delta, and a marked change in its antigenicity increases Omicron’s evasion of therapeutic and vaccine-elicited neutralizing antibodies.

The molecular machinery of life is founded on chiral building blocks, but no experimental technique is currently available to distinguish or monitor chiral systems in live cell bio-imaging studies. Luminescent chiral molecules encode a unique optical fingerprint within emitted circularly polarized light (CPL) carrying information about the molecular environment, conformation, and binding state. Here, we present a CPL Laser Scanning Confocal Microscope (CPL-LSCM) capable of simultaneous chiroptical contrast based live-cell imaging of endogenous and engineered CPL-active cellular probes. Further, we demonstrate that CPL-active probes can be activated using two-photon excitation, with complete CPL spectrum recovery. The combination of these two milestone results empowers the multidisciplinary imaging community, allowing the study of chiral interactions on a sub-cellular level in a new (chiral) light. Here, the authors introduce a live-cell imaging system using chiroptical contrast, enabling the study of chiral interactions. They demonstrate simultaneous imaging of enantiomeric pairs of molecular probes emitting circularly polarised light, using both single and two-photon excitation.

High throughput drug screening is an established approach to investigate tumor biology and identify therapeutic leads. Traditional platforms use two-dimensional cultures which do not accurately reflect the biology of human tumors. More clinically relevant model systems such as three-dimensional tumor organoids can be difficult to scale and screen. Manually seeded organoids coupled to destructive endpoint assays allow for the characterization of treatment response, but do not capture transitory changes and intra-sample heterogeneity underlying clinically observed resistance to therapy. We present a pipeline to generate bioprinted tumor organoids linked to label-free, time-resolved imaging via high-speed live cell interferometry (HSLCI) and machine learning-based quantitation of individual organoids. Bioprinting cells gives rise to 3D structures with unaltered tumor histology and gene expression profiles. HSLCI imaging in tandem with machine learning-based segmentation and classification tools enables accurate, label-free parallel mass measurements for thousands of organoids. We demonstrate that this strategy identifies organoids transiently or persistently sensitive or resistant to specific therapies, information that could be used to guide rapid therapy selection. Traditional 2D cell culture platforms do not accurately reflect the physiology of human tumors. Here, authors combine bioprinting and high-speed live cell interferometry with machine learning to measure drug sensitivity at single-organoid resolution in a label-free manner.

The landscape of diagnostic testing is undergoing a significant transformation, driven by the integration of artificial intelligence (AI) and machine learning (ML) into decentralized, rapid, and accessible sensor platforms for point-of-care testing (POCT). The COVID-19 pandemic has accelerated the shift from centralized laboratory testing but also catalyzed the development of next-generation POCT platforms that leverage ML to enhance the accuracy, sensitivity, and overall efficiency of point-of-care sensors. This Perspective explores how ML is being embedded into various POCT modalities, including lateral flow assays, vertical flow assays, nucleic acid amplification tests, and imaging-based sensors, illustrating their impact through different applications. We also discuss several challenges, such as regulatory hurdles, reliability, and privacy concerns, that must be overcome for the widespread adoption of ML-enhanced POCT in clinical settings and provide a comprehensive overview of the current state of ML-driven POCT technologies, highlighting their potential impact in the future of healthcare. Recent years have seen an increasing shift from centralized laboratory diagnostics to decentralized point-of-care testing, a shift which has the potential to increase health equity. Here the authors provide their perspective on how the integration of machine learning and artificial intelligence with point-of-care technologies can - and could - support this transition