Humidity-Responsive Liquid Metal Core-Shell Materials for Enduring Heat Retention and Insulation.

High humidity in extremely cold weather can undermine the insulation capability of the clothing, imposing serious life risks. Current clothing insulation technologies have inherent deficiencies in terms of insulation efficiency and humidity adaptability. Here, we report humidity-stimulated self-heating clothing using aluminum core-liquid metal shell microparticles (Al@LM-MPs) as the filler. Al@LM-MPs exhibit a distinctive capability to react to water molecules in the air to generate heat, exhibiting remarkable sensitivity across a broad temperature range. This ability leads to the creation of intelligent clothing capable of autonomously responding to extreme cold and wet weather conditions, providing both enduring heat retention and insulation capabilities. This article is protected by copyright. All rights reserved.

Multicolor-Assay-on-a-Chip Processed by Robotic Operation (MACpro) with Improved Diagnostic Accuracy for Field-Deployable Detection.

The ability to deploy decentralized laboratories with autonomous and reliable disease diagnosis holds the potential to deliver accessible healthcare services for public safety. While microfluidic technologies provide precise manipulation of small fluid volumes with improved assay performance, their limited automation and versatility confine them to laboratories. Herein, we report the utility of multicolor assay-on-a-chip processed by robotic operation (MACpro), to address this unmet need. The MACpro platform comprises a robot-microfluidic interface and an eye-in-hand module that provides flexible yet stable actions to execute tasks in a programmable manner, such as the precise manipulation of the microfluidic chip along with different paths. Notably, MACpro shows improved detection performance by integrating the microbead-based antibody immobilization with enhanced target recognition and multicolor sensing via Cu2+-catalyzed plasmonic etching of gold nanorods for rapid and sensitive analyte quantification. Using interferon-gamma as an example, we demonstrate that MACpro completes a sample-to-answer immunoassay within 30 min and achieves a 10-fold broader dynamic range and a 10-fold lower detection limit compared to standard enzyme-linked immunosorbent assays (0.66 vs 5.2 pg/mL). MACpro extends the applications beyond traditional laboratories and presents an automated solution to expand diagnostic capacity in diverse settings.

Inducing mitochondriopathy-like damages by transformable nucleopeptide nanoparticles for targeted therapy of bladder cancer.

Mitochondriopathy inspired adenosine triphosphate (ATP) depletions have been recognized as a powerful way for controlling tumor growth. Nevertheless, selective sequestration or exhaustion of ATP under complex biological environments remains a prodigious challenge. Harnessing the advantages of in vivo self-assembled nanomaterials, we designed an Intracellular ATP Sequestration (IAS) system to specifically construct nanofibrous nanostructures on the surface of tumor nuclei with exposed ATP binding sites, leading to highly efficient suppression of bladder cancer by induction of mitochondriopathy-like damages. Briefly, the reported transformable nucleopeptide (NLS-FF-T) self-assembled into nuclear-targeted nanoparticles with ATP binding sites encapsulated inside under aqueous conditions. By interaction with KPNA2, the NLS-FF-T transformed into a nanofibrous-based ATP trapper on the surface of tumor nuclei, which prevented the production of intracellular energy. As a result, multiple bladder tumor cell lines (T24, EJ and RT-112) revealed that the half-maximal inhibitory concentration (IC50) of NLS-FF-T was reduced by approximately 4-fold when compared to NLS-T. Following intravenous administration, NLS-FF-T was found to be dose-dependently accumulated at the tumor site of T24 xenograft mice. More significantly, this IAS system exhibited an extremely antitumor efficacy according to the deterioration of T24 tumors and simultaneously prolonged the overall survival of T24 orthotopic xenograft mice. Together, our findings clearly demonstrated the therapeutic advantages of intracellular ATP sequestration-induced mitochondriopathy-like damages, which provides a potential treatment strategy for malignancies.

Ammonia-oxidizing bacteria and archaea exhibit differential nitrogen source preferences.

Ammonia-oxidizing microorganisms (AOM) contribute to one of the largest nitrogen fluxes in the global nitrogen budget. Four distinct lineages of AOM: ammonia-oxidizing archaea (AOA), beta- and gamma-proteobacterial ammonia-oxidizing bacteria (ß-AOB and γ-AOB) and complete ammonia oxidizers (comammox), are thought to compete for ammonia as their primary nitrogen substrate. In addition, many AOM species can utilize urea as an alternative energy and nitrogen source through hydrolysis to ammonia. How the coordination of ammonia and urea metabolism in AOM influences their ecology remains poorly understood. Here we use stable isotope tracing, kinetics and transcriptomics experiments to show that representatives of the AOM lineages employ distinct regulatory strategies for ammonia or urea utilization, thereby minimizing direct substrate competition. The tested AOA and comammox species preferentially used ammonia over urea, while ß-AOB favoured urea utilization, repressed ammonia transport in the presence of urea and showed higher affinity for urea than for ammonia. Characterized γ-AOB co-utilized both substrates. These results reveal contrasting niche adaptation and coexistence patterns among the major AOM lineages.

In vivo assembly enhanced binding effect augments tumor specific ferroptosis therapy.

Emerging evidence indicates that the activation of ferroptosis by glutathione peroxidase 4 (GPX4) inhibitors may be a prominent therapeutic strategy for tumor suppression. However, the wide application of GPX4 inhibitors in tumor therapy is hampered due to poor tumor delivery efficacy and the nonspecific activation of ferroptosis. Taking advantage of in vivo self-assembly, we develop a peptide-ferriporphyrin conjugate with tumor microenvironment specific activation to improve tumor penetration, endocytosis and GPX4 inhibition, ultimately enhancing its anticancer activity via ferroptosis. Briefly, a GPX4 inhibitory peptide is conjugated with an assembled peptide linker decorated with a pH-sensitive moiety and ferriporphyrin to produce the peptide-ferriporphyrin conjugate (Gi-F-CAA). Under the acidic microenvironment of the tumor, the Gi-F-CAA self-assembles into large nanoparticles (Gi-F) due to enhanced hydrophobic interaction after hydrolysis of CAA, improving tumor endocytosis efficiency. Importantly, Gi-F exhibits substantial inhibition of GPX4 activity by assembly enhanced binding (AEB) effect, augmenting the oxidative stress of ferriporphyrin-based Fenton reaction, ultimately enabling antitumor properties in multiple tumor models. Our findings suggest that this peptide-ferriporphyrin conjugate design with AEB effect can improve the therapeutic effect via induction of ferroptosis, providing an alternative strategy for overcoming chemoresistance.

Microbiome single cell atlases generated with a commercial instrument.

Single cell sequencing is useful for resolving complex systems into their composite cell types and computationally mining them for unique features that are masked in pooled sequencing. However, while commercial instruments have made single cell analysis widespread for mammalian cells, analogous tools for microbes are limited. Here, we present EASi-seq (Easily Accessible Single microbe sequencing). By adapting the single cell workflow of the commercial Mission Bio Tapestri instrument, this method allows for efficient sequencing of individual microbes' genomes. EASi-seq allows thousands of microbes to be sequenced per run and, as we show, can generate detailed atlases of human and environmental microbiomes. The ability to capture large shotgun genome datasets from thousands of single microbes provides new opportunities in discovering and analyzing species subpopulations. To facilitate this, we develop a companion bioinformatic pipeline that clusters microbes by similarity, improving whole genome assembly, strain identification, taxonomic classification, and gene annotation. In addition, we demonstrate integration of metagenomic contigs with the EASi-seq datasets to reduce capture bias and increase coverage. Overall, EASi-seq enables high quality single cell genomic data for microbiome samples using an accessible workflow that can be run on a commercially available platform.

Visual Commonsense-Aware Representation Network for Video Captioning.

Generating consecutive descriptions for videos, that is, video captioning, requires taking full advantage of visual representation along with the generation process. Existing video captioning methods focus on an exploration of spatial-temporal representations and their relationships to produce inferences. However, such methods only exploit the superficial association contained in a video itself without considering the intrinsic visual commonsense knowledge that exists in a video dataset, which may hinder their capabilities of knowledge cognitive to reason accurate descriptions. To address this problem, we propose a simple, yet effective method, called visual commonsense-aware representation network (VCRN), for video captioning. Specifically, we construct a Video Dictionary, a plug-and-play component, obtained by clustering all video features from the total dataset into multiple clustered centers without additional annotation. Each center implicitly represents a visual commonsense concept in a video domain, which is utilized in our proposed visual concept selection (VCS) component to obtain a video-related concept feature. Next, a concept-integrated generation (CIG) component is proposed to enhance caption generation. Extensive experiments on three public video captioning benchmarks: MSVD, MSR-VTT, and VATEX, demonstrate that our method achieves state-of-the-art performance, indicating the effectiveness of our method. In addition, our method is integrated into the existing method of video question answering (VideoQA) and improves this performance, which further demonstrates the generalization capability of our method. The source code has been released at https://github.com/zchoi/VCRN.

Proximity Labeling Expansion Microscopy (PL-ExM) resolves structure of the interactome.

Elucidating the spatial relationships within the protein interactome is pivotal to understanding the organization and regulation of protein-protein interactions. However, capturing the 3D architecture of the interactome presents a dual challenge: precise interactome labeling and super-resolution imaging. To bridge this gap, we present the Proximity Labeling Expansion Microscopy (PL-ExM). This innovation combines proximity labeling (PL) to spatially biotinylate interacting proteins with expansion microscopy (ExM) to increase imaging resolution by physically enlarging cells. PL-ExM unveils intricate details of the 3D interactome's spatial layout in cells using standard microscopes, including confocal and Airyscan. Multiplexing PL-ExM imaging was achieved by pairing the PL with immunofluorescence staining. These multicolor images directly visualize how interactome structures position specific proteins in the protein-protein interaction network. Furthermore, PL-ExM stands out as an assessment method to gauge the labeling radius and efficiency of different PL techniques. The accuracy of PL-ExM is validated by our proteomic results from PL mass spectrometry. Thus, PL-ExM is an accessible solution for 3D mapping of the interactome structure and an accurate tool to access PL quality.

Microbiome single cell atlases generated with a commercial instrument.

Single cell sequencing is useful for resolving complex systems into their composite cell types and computationally mining them for unique features that are masked in pooled sequencing. However, while commercial instruments have made single cell analysis widespread for mammalian cells, analogous tools for microbes are limited. Here, we present EASi-seq (Easily Accessible Single microbe sequencing). By adapting the single cell workflow of the commercial Mission Bio Tapestri instrument, this method allows for efficient sequencing of individual microbes' genomes. EASi-seq allows thousands of microbes to be sequenced per run and, as we show, can generate detailed atlases of human and environmental microbiomes. The ability to capture large shotgun genome datasets from thousands of single microbes provides new opportunities in discovering and analyzing species subpopulations. To facilitate this, we develop a companion bioinformatic pipeline that clusters microbes by similarity, improving whole genome assembly, strain identification, taxonomic classification, and gene annotation. In addition, we demonstrate integration of metagenomic contigs with the EASi-seq datasets to reduce capture bias and increase coverage. Overall, EASi-seq enables high quality single cell genomic data for microbiome samples using an accessible workflow that can be run on a commercially available platform.

Light intensity and spectral quality modulation for improved growth kinetics and biochemical composition of Chlamydomonas reinhardtii.

Effective strategies to optimize algal growth and lipid productivity are critical for the sustainable production of biomass for various applications. Light management has emerged as a promising approach, but the intricate relationship between light intensity, spectral quality, and algal responses remains poorly understood. This study investigated the effects of different light qualities (blue, red-orange, and white-yellow) and intensities (45-305 µmol/m2·s) on Chlamydomonas reinhardtii. Red-orange light exhibited the highest promotion of biomass growth and lipid productivity, with specific growth rates of 1.968 (d-1) and biomass productivity of 0.284 (g/L/d) at 155 µmol/m2·s and 205 µmol/m2·s, respectively. Within the intensity range of 205 µmol/m2·s to 305 µmol/m2·s, lipid mass fractions ranged from 10.5% w/w to 11.0% w/w, accompanied by lipid concentrations ranging from 68.6 mg/L to 74.9 mg/L. Red-orange light positively influenced carbohydrate accumulation, while blue light promoted protein synthesis. These findings highlight the importance of optimizing light quality and intensity to enhance algal biomass productivity and manipulate biochemical composition. Understanding the complex relationship between light parameters and algal physiology will contribute to sustainable algal cultivation practices and the use of microalgae as a valuable bioresource.

An In Vivo Self-Assembled Bispecific Nanoblocker for Enhancing Tumor Immunotherapy.

Anti-PD-L1 monoclonal antibody has achieved substantial success in tumor immunotherapy by T-cells activation. However, the excessive accumulation of extracellular matrix components induced by unsatisfactory T-cells infiltration and poor tumor penetration of antibodies make it challenging to realize efficient tumor immunotherapy. Herein, a peptide-based bispecific nanoblocker (BNB) strategy is reported for in situ construction of CXCR4/PD-L1 targeted nanoclusters on the surface of tumor cells that are capable of boosting T-cells infiltration through CXCR4 blockage and enhancing T-cells activation by PD-L1 occupancy, ultimately realizing high-performance tumor immunotherapy. Briefly, the BNB strategy selectively recognizes and bonds CXCR4/PD-L1 with deep tumor penetration, which rapidly self-assembles into nanoclusters on the surface of tumor cells. Compared to the traditional bispecific antibody, BNB exhibits an intriguing metabolic behavior, that is, the elimination half-life (t1/2 ) of BNB in the tumor is 69.3 h which is ≈50 times longer than that in the plasma (1.4 h). The higher tumor accumulation and rapid systemic clearance overcome potential systemic side effects. Moreover, the solid tumor stress generated by excessive extracellular matrix components is substantially reduced to 44%, which promotes T-cells infiltration and activation for immunotherapy efficacy. Finally, these findings substantially strengthen and extend clinical applications of PD-1/PD-L1 immunotherapy.

Spatial genetic patterns and distribution dynamics of Begonia grandis (Begoniaceae), a widespread herbaceous species in China.

Introduction: Begonia L., one of the 10 largest plant genera, contains over 2,100 species, most of which have a very limited distribution range. Understanding the spatial genetic structure and distribution dynamics of a widespread species in this genus will contribute to clarifying the mechanism responsible for Begonia speciation. Methods: In this study, we used three chloroplast DNA markers (ndhF-rpl32, atpI-atpH, and ndhA intron), coupled with species distribution modeling (SDM), to investigate the population genetic structure and distribution dynamics of Begonia grandis Dryand., the species of Begonia with the widest distribution in China. Results: Thirty-five haplotypes from 44 populations clustered into two groups, and haplotype divergence began in the Pleistocene (1.75 Mya). High genetic diversity (H d = 0.894, H T = 0.910), strong genetic differentiation (F ST = 0.835), and significant phylogeographical structure (G ST/N ST = 0.848/0.917, P < 0.05) were observed. The distribution range of B. grandis migrated northwards after the last glacial maximum, but its core distribution area remained stable. Discussion: Combined, the observed spatial genetic patterns and SDM results identified the Yunnan-Guizhou Plateau, the Three Gorges region, and the Daba Mountains as potential refugia of B. grandis. BEAST-derived chronogram and haplotype network analysis do not support the Flora Reipublicae Popularis Sinicae and Flora of China for subspecies classification based on morphological characteristics. Our results support the hypothesis that population-level allopatric differentiation may be an important speciation process for the Begonia genus and a key contributor to its rich diversity.

3D actuation of foam-core liquid metal droplets.

Precise manipulation of liquid metal (LM) droplets possesses the potential to enable a wide range of applications in reconfigurable electronics, robotics, and microelectromechanical systems. Although a variety of methods have been explored to actuate LM droplets on a 2D plane, versatile 3D manipulation remains a challenge due to the difficulty in overcoming their heavy weight. Here, foam-core liquid metal (FCLM) droplets that can maintain the surface properties of LM while significantly reducing the density are developed, enabling 3D manipulation in an electrolyte. The FCLM droplet is fabricated by coating LM on the surface of a copper-grafted foam sphere. The actuation of the FCLM droplet is realized by electrically inducing Marangoni flow on the LM surface. Two motion modes of the FCLM droplet are observed and studied and the actuation performance is characterized. Multiple FCLM droplets can be readily controlled to form 3D structures, demonstrating their potential to be further developed to form collaborative robots for enabling wider applications.

Scalable Microbial Strain Inference in Metagenomic Data Using StrainFacts.

While genome databases are nearing a complete catalog of species commonly inhabiting the human gut, their representation of intraspecific diversity is lacking for all but the most abundant and frequently studied taxa. Statistical deconvolution of allele frequencies from shotgun metagenomic data into strain genotypes and relative abundances is a promising approach, but existing methods are limited by computational scalability. Here we introduce StrainFacts, a method for strain deconvolution that enables inference across tens of thousands of metagenomes. We harness a "fuzzy" genotype approximation that makes the underlying graphical model fully differentiable, unlike existing methods. This allows parameter estimates to be optimized with gradient-based methods, speeding up model fitting by two orders of magnitude. A GPU implementation provides additional scalability. Extensive simulations show that StrainFacts can perform strain inference on thousands of metagenomes and has comparable accuracy to more computationally intensive tools. We further validate our strain inferences using single-cell genomic sequencing from a human stool sample. Applying StrainFacts to a collection of more than 10,000 publicly available human stool metagenomes, we quantify patterns of strain diversity, biogeography, and linkage-disequilibrium that agree with and expand on what is known based on existing reference genomes. StrainFacts paves the way for large-scale biogeography and population genetic studies of microbiomes using metagenomic data.

Controlled fabrication of functional liver spheroids with microfluidic flow cytometric printing.

Multicellular liver spheroids are 3D culture models useful in the development of therapies for liver fibrosis. While these models can recapitulate fibrotic disease, current methods for generating them via random aggregation are uncontrolled, yielding spheroids of variable size, function, and utility. Here, we report fabrication of precision liver spheroids with microfluidic flow cytometric printing. Our approach fabricates spheroids cell-by-cell, yielding structures with exact numbers of different cell types. Because spheroid function depends on composition, our precision spheroids have superior functional uniformity, allowing more accurate and statistically significant screens compared to randomly generated spheroids. The approach produces thousands of spheroids per hour, and thus affords a scalable platform by which to manufacture single-cell precision spheroids for disease modeling and high throughput drug testing.

Polyhedral Particles with Controlled Concavity by Indentation Templating.

Current methods for fabricating microparticles offer limited control over size and shape. Here, we demonstrate a droplet microfluidic method to form polyhedral microparticles with controlled concavity. By manipulating Laplace pressure, buoyancy, and particle rheology, we generate microparticles with diverse shapes and curvatures. Additionally, we demonstrate the particles provide increased capture efficiency when used for particle-templated emulsification. Our approach enables microparticles with enhanced chemical and biological functionality.

New Insights for Biosensing: Lessons from Microbial Defense Systems.

Microorganisms have gained defense systems during the lengthy process of evolution over millions of years. Such defense systems can protect them from being attacked by invading species (e.g., CRISPR-Cas for establishing adaptive immune systems and nanopore-forming toxins as virulence factors) or enable them to adapt to different conditions (e.g., gas vesicles for achieving buoyancy control). These microorganism defense systems (MDS) have inspired the development of biosensors that have received much attention in a wide range of fields including life science research, food safety, and medical diagnosis. This Review comprehensively analyzes biosensing platforms originating from MDS for sensing and imaging biological analytes. We first describe a basic overview of MDS and MDS-inspired biosensing platforms (e.g., CRISPR-Cas systems, nanopore-forming proteins, and gas vesicles), followed by a critical discussion of their functions and properties. We then discuss several transduction mechanisms (optical, acoustic, magnetic, and electrical) involved in MDS-inspired biosensing. We further detail the applications of the MDS-inspired biosensors to detect a variety of analytes (nucleic acids, peptides, proteins, pathogens, cells, small molecules, and metal ions). In the end, we propose the key challenges and future perspectives in seeking new and improved MDS tools that can potentially lead to breakthrough discoveries in developing a new generation of biosensors with a combination of low cost; high sensitivity, accuracy, and precision; and fast detection. Overall, this Review gives a historical review of MDS, elucidates the principles of emulating MDS to develop biosensors, and analyzes the recent advancements, current challenges, and future trends in this field. It provides a unique critical analysis of emulating MDS to develop robust biosensors and discusses the design of such biosensors using elements found in MDS, showing that emulating MDS is a promising approach to conceptually advancing the design of biosensors.

Malus toringoides (Rehd.) Hughes improves glucose and lipid metabolism and liver injury in high fructose-induced mice.

Malus toringoides (Rehd.) Hughes, as a traditional medicinal and edible plant used in Tibet, China, is used to treat hypertension, hyperlipidemia, and liver diseases. In recent decades, excessive fructose intake with diet has greatly increased the occurrence of a series of metabolic diseases including obesity, insulin resistance, hypertension, and hyperlipidemia. The present study was designed to investigate the effects of an ethanol extract of M. toringoides (EMT) on glucose and lipid metabolism and liver injury in high fructose-induced mice. The C57BL/6J male mice were orally administrated with 30% fructose solution for 8 weeks, and EMT was given orally for another 8 weeks. The level of liver lipids related parameters, hepatic oxidative stress, and inflammatory mediators was detected by the kits. The improving effects of EMT on liver injury and lipid accumulation of mice were observed by hematoxylin and eosin staining and Oil Red O staining. In vitro, the hypolipidemic effect of EMT on palmitic acid-induced HepG2 cells was detected by the kits and Oil Red O staining. Our results showed that EMT has the hypolipidemic effect in vivo and in vitro, and can improve liver injury caused by fructose intake though ameliorating oxidative stress and inflammatory responses. Thus, we suggested that EMT may be a candidate therapeutic agent to improve a series of metabolic diseases including obesity, insulin resistance, and hyperlipidemia. PRACTICAL APPLICATIONS: Our study was aimed to find a novel candidate drug for liver diseases using natural products. We assessed the protective effects of Malus toringoides (Rehd.) Hughes in the pathogenesis of glucose and lipid metabolism. In vivo, the plant significantly improved the disorder of blood lipid and blood glucose, and liver injury in mice induced by fructose, and in vitro, this plant significantly improved the lipid accumulation of HepG2 cells induced by palmitic acid. To sum up, our studies suggested that the plant may be beneficial in the prevention and management of diet-induced abnormal glucose and lipid metabolism and liver diseases. Therefore, it will be a candidate therapeutic agent to improve liver diseases.

Droplet-microfluidics-assisted sequencing of HIV proviruses and their integration sites in cells from people on antiretroviral therapy.

The human immunodeficiency virus (HIV) integrates its genome into that of infected cells and may enter an inactive state of reversible latency that cannot be targeted using antiretroviral therapy. Sequencing such a provirus and the adjacent host junctions in individual cells may elucidate the mechanisms of the persistence of infected cells, but this is difficult owing to the 150-million-fold higher amount of background human DNA. Here we show that full-length proviruses connected to their contiguous HIV-host DNA junctions can be assembled via a high-throughput microfluidic assay where droplet-based whole-genome amplification of HIV DNA in its native context is followed by a polymerase chain reaction (PCR) to tag droplets containing proviruses for sequencing. We assayed infected cells from people with HIV receiving suppressive antiretroviral therapy, resulting in the detection and sequencing of paired proviral genomes and integration sites, 90% of which were not recovered by commonly used nested-PCR methods. The sequencing of individual proviral genomes with their integration sites could improve the genetic analysis of persistent HIV-infected cell reservoirs.

Superelongation of Liquid Metal.

The ability to control interfacial tension electrochemically is uniquely available for liquid metals (LMs), in particular gallium-based LM alloys. This imparts them with excellent locomotion and deformation capabilities and enables diverse applications. However, electrochemical oxidation of LM is a highly dynamic process, which often induces Marangoni instabilities that make it almost impossible to elongate LM and manipulate its morphology directly and precisely on a 2D plane without the assistance of other patterning methods. To overcome these limitations, this study investigates the use of an LM-iron (Fe) particle mixture that is capable of suppressing instabilities during the electrochemical oxidation process, thereby allowing for superelongation of the LM core of the mixture to form a thin wire that is tens of times of its original length. More importantly, the elongated LM core can be manipulated freely on a 2D plane to form complex patterns. Eliminating Marangoni instabilities also allows for the effective spreading and filling of the LM-Fe mixture into molds with complex structures and small features. Harnessing these excellent abilities, a channel-less patterning method for fabricating elastomeric wearable sensors is demonstrated to detect motions. This study shows the potential for developing functional and flexible structures of LM with superior performance.