Intravital three-photon microscopy allows visualization over the entire depth of mouse lymph nodes.

Intravital confocal microscopy and two-photon microscopy are powerful tools to explore the dynamic behavior of immune cells in mouse lymph nodes (LNs), with penetration depth of ~100 and ~300 µm, respectively. Here, we used intravital three-photon microscopy to visualize the popliteal LN through its entire depth (600-900 µm). We determined the laser average power and pulse energy that caused measurable perturbation in lymphocyte migration. Long-wavelength three-photon imaging within permissible parameters was able to image the entire LN vasculature in vivo and measure CD8+ T cells and CD4+ T cell motility in the T cell zone over the entire depth of the LN. We observed that the motility of naive CD4+ T cells in the T cell zone during lipopolysaccharide-induced inflammation was dependent on depth. As such, intravital three-photon microscopy had the potential to examine immune cell behavior in the deeper regions of the LN in vivo.

Deep physical neural networks trained with backpropagation.

Deep-learning models have become pervasive tools in science and engineering. However, their energy requirements now increasingly limit their scalability1. Deep-learning accelerators2-9 aim to perform deep learning energy-efficiently, usually targeting the inference phase and often by exploiting physical substrates beyond conventional electronics. Approaches so far10-22 have been unable to apply the backpropagation algorithm to train unconventional novel hardware in situ. The advantages of backpropagation have made it the de facto training method for large-scale neural networks, so this deficiency constitutes a major impediment. Here we introduce a hybrid in situ-in silico algorithm, called physics-aware training, that applies backpropagation to train controllable physical systems. Just as deep learning realizes computations with deep neural networks made from layers of mathematical functions, our approach allows us to train deep physical neural networks made from layers of controllable physical systems, even when the physical layers lack any mathematical isomorphism to conventional artificial neural network layers. To demonstrate the universality of our approach, we train diverse physical neural networks based on optics, mechanics and electronics to experimentally perform audio and image classification tasks. Physics-aware training combines the scalability of backpropagation with the automatic mitigation of imperfections and noise achievable with in situ algorithms. Physical neural networks have the potential to perform machine learning faster and more energy-efficiently than conventional electronic processors and, more broadly, can endow physical systems with automatically designed physical functionalities, for example, for robotics23-26, materials27-29 and smart sensors30-32.

Self-propulsion via slipping: Frictional swimming in multilegged locomotors.

Locomotion is typically studied either in continuous media where bodies and legs experience forces generated by the flowing medium or on solid substrates dominated by friction. In the former, centralized whole-body coordination is believed to facilitate appropriate slipping through the medium for propulsion. In the latter, slip is often assumed minimal and thus avoided via decentralized control schemes. We find in laboratory experiments that terrestrial locomotion of a meter-scale multisegmented/legged robophysical model resembles undulatory fluid swimming. Experiments varying waves of leg stepping and body bending reveal how these parameters result in effective terrestrial locomotion despite seemingly ineffective isotropic frictional contacts. Dissipation dominates over inertial effects in this macroscopic-scaled regime, resulting in essentially geometric locomotion on land akin to microscopic-scale swimming in fluids. Theoretical analysis demonstrates that the high-dimensional multisegmented/legged dynamics can be simplified to a centralized low-dimensional model, which reveals an effective resistive force theory with an acquired viscous drag anisotropy. We extend our low-dimensional, geometric analysis to illustrate how body undulation can aid performance in non-flat obstacle-rich terrains and also use the scheme to quantitatively model how body undulation affects performance of biological centipede locomotion (the desert centipede Scolopendra polymorpha) moving at relatively high speeds (∼0.5 body lengths/sec). Our results could facilitate control of multilegged robots in complex terradynamic scenarios.

Oxidation-induced superelasticity in metallic glass nanotubes.

Although metallic nanostructures have been attracting tremendous research interest in nanoscience and nanotechnologies, it is known that environmental attacks, such as surface oxidation, can easily initiate cracking on the surface of metals, thus deteriorating their overall functional/structural properties1-3. In sharp contrast, here we report that severely oxidized metallic glass nanotubes can attain an ultrahigh recoverable elastic strain of up to ~14% at room temperature, which outperform bulk metallic glasses, metallic glass nanowires and many other superelastic metals hitherto reported. Through in situ experiments and atomistic simulations, we reveal that the physical mechanisms underpinning the observed superelasticity can be attributed to the formation of a percolating oxide network in metallic glass nanotubes, which not only restricts atomic-scale plastic events during loading but also leads to the recovery of elastic rigidity on unloading. Our discovery implies that oxidation in low-dimensional metallic glasses can result in unique properties for applications in nanodevices.

Identification of DNase I hypersensitive sites in the human genome by multiple sequence descriptors.

DNase I hypersensitive sites (DHSs) are chromatin regions highly sensitive to DNase I enzymes. Studying DHSs is crucial for understanding complex transcriptional regulation mechanisms and localizing cis-regulatory elements (CREs). Numerous studies have indicated that disease-related loci are often enriched in DHSs regions, underscoring the importance of identifying DHSs. Although wet experiments exist for DHSs identification, they are often labor-intensive. Therefore, there is a strong need to develop computational methods for this purpose. In this study, we used experimental data to construct a benchmark dataset. Seven feature extraction methods were employed to capture information about human DHSs. The F-score was applied to filter the features. By comparing the prediction performance of various classification algorithms through five-fold cross-validation, random forest was proposed to perform the final model construction. The model could produce an overall prediction accuracy of 0.859 with an AUC value of 0.837. We hope that this model can assist scholars conducting DNase research in identifying these sites.

Coordinating tiny limbs and long bodies: Geometric mechanics of lizard terrestrial swimming.

Although typically possessing four limbs and short bodies, lizards have evolved diverse morphologies, including elongate trunks with tiny limbs. Such forms are hypothesized to aid locomotion in cluttered/fossorial environments but propulsion mechanisms (e.g., the use of body and/or limbs to interact with substrates) and potential body/limb coordination remain unstudied. Here, we use biological experiments, a geometric theory of locomotion, and robophysical models to investigate body-limb coordination in diverse lizards. Locomotor field studies in short-limbed, elongate lizards (Brachymeles and Lerista) and laboratory studies of fully limbed lizards (Uma scoparia and Sceloporus olivaceus) and a snake (Chionactis occipitalis) reveal that body-wave dynamics can be described by a combination of standing and traveling waves; the ratio of the amplitudes of these components is inversely related to the degree of limb reduction and body elongation. The geometric theory (which replaces laborious calculation with diagrams) helps explain our observations, predicting that the advantage of traveling-wave body undulations (compared with a standing wave) emerges when the dominant thrust-generation mechanism arises from the body rather than the limbs and reveals that such soil-dwelling lizards propel via "terrestrial swimming" like sand-swimming lizards and snakes. We test our hypothesis by inducing the use of traveling waves in stereotyped lizards via modulating the ground-penetration resistance. Study of a limbed/undulatory robophysical model demonstrates that a traveling wave is beneficial when propulsion is generated by body-environment interaction. Our models could be valuable in understanding functional constraints on the evolutionary processes of elongation and limb reduction as well as advancing robot designs.

Robotic swimming in curved space via geometric phase.

Locomotion by shape changes or gas expulsion is assumed to require environmental interaction, due to conservation of momentum. However, as first noted in [J. Wisdom, Science 299, 1865-1869 (2003)] and later in [E. Guéron, Sci. Am. 301, 38-45 (2009)] and [J. Avron, O. Kenneth, New J. Phys, 8, 68 (2006)], the noncommutativity of translations permits translation without momentum exchange in either gravitationally curved spacetime or the curved surfaces encountered by locomotors in real-world environments. To realize this idea which remained unvalidated in experiments for almost 20 y, we show that a precision robophysical apparatus consisting of motors driven on curved tracks (and thereby confined to a spherical surface without a solid substrate) can self-propel without environmental momentum exchange. It produces shape changes comparable to the environment's inverse curvatures and generates movement of [Formula: see text] cm per gait. While this simple geometric effect predominates over short time, eventually the dissipative (frictional) and conservative forces, ubiquitous in real systems, couple to it to generate an emergent dynamics in which the swimming motion produces a force that is counter-balanced against residual gravitational forces. In this way, the robot both swims forward without momentum and becomes fixed in place with a finite momentum that can be released by ceasing the swimming motion. We envision that our work will be of use in a broad variety of contexts, such as active matter in curved space and robots navigating real-world environments with curved surfaces.

Engineered nanoparticles enable deep proteomics studies at scale by leveraging tunable nano-bio interactions.

SignificanceDeep profiling of the plasma proteome at scale has been a challenge for traditional approaches. We achieve superior performance across the dimensions of precision, depth, and throughput using a panel of surface-functionalized superparamagnetic nanoparticles in comparison to conventional workflows for deep proteomics interrogation. Our automated workflow leverages competitive nanoparticle-protein binding equilibria that quantitatively compress the large dynamic range of proteomes to an accessible scale. Using machine learning, we dissect the contribution of individual physicochemical properties of nanoparticles to the composition of protein coronas. Our results suggest that nanoparticle functionalization can be tailored to protein sets. This work demonstrates the feasibility of deep, precise, unbiased plasma proteomics at a scale compatible with large-scale genomics enabling multiomic studies.

Prediction of blood-brain barrier penetrating peptides based on data augmentation with Augur.

BACKGROUND: The blood-brain barrier serves as a critical interface between the bloodstream and brain tissue, mainly composed of pericytes, neurons, endothelial cells, and tightly connected basal membranes. It plays a pivotal role in safeguarding brain from harmful substances, thus protecting the integrity of the nervous system and preserving overall brain homeostasis. However, this remarkable selective transmission also poses a formidable challenge in the realm of central nervous system diseases treatment, hindering the delivery of large-molecule drugs into the brain. In response to this challenge, many researchers have devoted themselves to developing drug delivery systems capable of breaching the blood-brain barrier. Among these, blood-brain barrier penetrating peptides have emerged as promising candidates. These peptides had the advantages of high biosafety, ease of synthesis, and exceptional penetration efficiency, making them an effective drug delivery solution. While previous studies have developed a few prediction models for blood-brain barrier penetrating peptides, their performance has often been hampered by issue of limited positive data. RESULTS: In this study, we present Augur, a novel prediction model using borderline-SMOTE-based data augmentation and machine learning. we extract highly interpretable physicochemical properties of blood-brain barrier penetrating peptides while solving the issues of small sample size and imbalance of positive and negative samples. Experimental results demonstrate the superior prediction performance of Augur with an AUC value of 0.932 on the training set and 0.931 on the independent test set. CONCLUSIONS: This newly developed Augur model demonstrates superior performance in predicting blood-brain barrier penetrating peptides, offering valuable insights for drug development targeting neurological disorders. This breakthrough may enhance the efficiency of peptide-based drug discovery and pave the way for innovative treatment strategies for central nervous system diseases.

SIRT5 exacerbates eosinophilic chronic rhinosinusitis by promoting polarization of M2 macrophage.

BACKGROUND: Previous studies implied that local M2 polarization of macrophage promoted mucosal edema and exacerbated TH2 type inflammation in chronic rhinosinusitis with nasal polyps (CRSwNP). However, the specific pathogenic role of M2 macrophages and the intrinsic regulators in the development of CRS remains elusive. OBJECTIVE: We sought to investigate the regulatory role of SIRT5 in the polarization of M2 macrophages and its potential contribution to the development of CRSwNP. METHODS: Real-time reverse transcription-quantitative PCR and Western blot analyses were performed to examine the expression levels of SIRT5 and markers of M2 macrophages in sinonasal mucosa samples obtained from both CRS and control groups. Wild-type and Sirt5-knockout mice were used to establish a nasal polyp model with TH2 inflammation and to investigate the effects of SIRT5 in macrophage on disease development. Furthermore, in vitro experiments were conducted to elucidate the regulatory role of SIRT5 in polarization of M2 macrophages. RESULTS: Clinical investigations showed that SIRT5 was highly expressed and positively correlated with M2 macrophage markers in eosinophilic polyps. The expression of SIRT5 in M2 macrophages was found to contribute to the development of the disease, which was impaired in Sirt5-deficient mice. Mechanistically, SIRT5 was shown to enhance the alternative polarization of macrophages by promoting glutaminolysis. CONCLUSIONS: SIRT5 plays a crucial role in promoting the development of CRSwNP by supporting alternative polarization of macrophages, thus providing a potential target for CRSwNP interventions.

Self-Rectifying All-Optical Modulated Optoelectronic Multistates Memristor Crossbar Array for Neuromorphic Computing.

Researching optoelectronic memristors capable of integrating sensory and processing functions is essential for advancing the development of efficient neuromorphic vision. Here, we experimentally demonstrated an all-optical controlled and self-rectifying optoelectronic memristor (OEM) crossbar array with the function of multilevel storage under light stimuli. The NiO/TiO2 device exhibits an ultrahigh (>104) rectifying ratio (RR) thus overcoming the presence of sneak current. The reversible conductance modulation without electric signal involvement provides a novel way to realize ultrafast information processing. The proposed OEM array realized synaptic functions observed in the human brain, including long-term potentiation (LTP), long-term depression (LTD), paired-pulse facilitation (PPF), the transition from short-term memory (STM) to long-term memory (LTM), and learning experience behaviors successfully. The authors present a novel OEM crossbar that possesses complete light-modulation capabilities, potentially advancing the future development of efficient neuromorphic vision.

Novel Three-Dimensional Artificial Neural Network Based on an Eight-Layer Vertical Memristor with an Ultrahigh Rectify Ratio (>107) and an Ultrahigh Nonlinearity (>105) for Neuromorphic Computing.

In recent years, memristors have successfully demonstrated their significant potential in artificial neural networks (ANNs) and neuromorphic computing. Nonetheless, ANNs constructed by crossbar arrays suffer from cross-talk issues and low integration densities. Here, we propose an eight-layer three-dimensional (3D) vertical crossbar memristor with an ultrahigh rectify ratio (RR > 107) and an ultrahigh nonlinearity (>105) to overcome these limitations, which enables it to reach a >1 Tb array size without reading failure. Furthermore, the proposed 3D RRAM shows advanced endurance (>1010 cycles), retention (>104 s), and uniformity. In addition, several synaptic functions observed in the human brain were mimicked. On the basis of the advanced performance, we constructed a novel 3D ANN, whose learning efficiency and recognition accuracy were enhanced significantly compared with those of conventional single-layer ANNs. These findings hold promise for the development of highly efficient, precise, integrated, and stable VLSI neuromorphic computing systems.

Paraventricular Thalamus Dynamically Modulates Aversive Memory via Tuning Prefrontal Inhibitory Circuitry.

The impact of stress on the formation and expression of memory is well studied, especially on the contributions of stress hormones. But how stress affects brain circuitry dynamically to modulate memory is far less understood. Here, we used male C57BL6/J mice in an auditory fear conditioning as a model system to examine this question and focused on the impact of stress on dorsomedial prefrontal cortex (dmPFC) neurons which play an important role in probabilistic fear memory. We found that paraventricular thalamus (PVT) neurons are robustly activated by acute restraining stress. Elevated PVT activity during probabilistic fear memory expression increases spiking in the dmPFC somatostatin neurons which in turn suppresses spiking of dmPFC parvalbumin (PV) neurons, and reverts the usual low fear responses associated with probabilistic fear memory to high fear. This dynamic and reversible modulation allows the original memory to be preserved and modulated during memory expression. In contrast, elevated PVT activity during fear conditioning impairs synaptic modifications in the dmPFC PV-neurons and abolishes the formation of probabilistic fear memory. Thus, PVT functions as a stress sensor to modulate the formation and expression of aversive memory by tuning inhibitory functions in the prefrontal circuitry.SIGNIFICANCE STATEMENT The impact of stress on cognitive functions, such as memory and executive functions, are well documented especially on the impact by stress hormone. However, the contributions of brain circuitry are far less understood. Here, we show that a circuitry-based mechanism can dynamically modulate memory formation and expression, namely, higher stress-induced activity in paraventricular thalamus (PVT) impairs the formation and expression of probabilistic fear memory by elevating the activity of somatostatin-neurons to suppress spiking in dorsomedial prefrontal parvalbumin (PV) neurons. This stress impact on memory via dynamic tuning of prefrontal inhibition preserves the formed memory but enables a dynamic expression of memory. These findings have implications for better stress coping strategies as well as treatment options including better drug targets/mechanisms.

YTHDF1 facilitates PRC1-mediated H2AK119ub in human ES cells.

Polycomb repressive complexes (PRCs) play critical roles in cell fate decisions during normal development as well as disease progression through mediating histone modifications such as H3K27me3 and H2AK119ub. How exactly PRCs recruited to chromatin remains to be fully illuminated. Here, we report that YTHDF1, the N6-methyladenine (m6 A) RNA reader that was previously known to be mainly cytoplasmic, associates with RNF2, a PRC1 protein that mediates H2AK119ub in human embryonic stem cells (hESCs). A portion of YTHDF1 localizes in the nuclei and associates with RNF2/H2AK119ub on a subset of gene loci related to neural development functions. Knock-down YTHDF1 attenuates H2AK119ub modification on these genes and promotes neural differentiation in hESCs. Our findings provide a noncanonical mechanism that YTHDF1 participates in PRC1 functions in hESCs.

Characterization of metallothionein genes from Broussonetia papyrifera: metal binding and heavy metal tolerance mechanisms.

BACKGROUND: Broussonetia papyrifera is an economically significant tree with high utilization value, yet its cultivation is often constrained by soil contamination with heavy metals (HMs). Effective scientific cultivation management, which enhances the yield and quality of B. papyrifera, necessitates an understanding of its regulatory mechanisms in response to HM stress. RESULTS: Twelve Metallothionein (MT) genes were identified in B. papyrifera. Their open reading frames ranged from 186 to 372 bp, encoding proteins of 61 to 123 amino acids with molecular weights between 15,473.77 and 29,546.96 Da, and theoretical isoelectric points from 5.24 to 5.32. Phylogenetic analysis classified these BpMTs into three subclasses: MT1, MT2, and MT3, with MT2 containing seven members and MT3 only one. The expression of most BpMT genes was inducible by Cd, Mn, Cu, Zn, and abscisic acid (ABA) treatments, particularly BpMT2e, BpMT2d, BpMT2c, and BpMT1c, which showed significant responses and warrant further study. Yeast cells expressing these BpMT genes exhibited enhanced tolerance to Cd, Mn, Cu, and Zn stresses compared to control cells. Yeasts harboring BpMT1c, BpMT2e, and BpMT2d demonstrated higher accumulation of Cd, Cu, Mn, and Zn, suggesting a chelation and binding capacity of BpMTs towards HMs. Site-directed mutagenesis of cysteine (Cys) residues indicated that mutations in the C domain of type 1 BpMT led to increased sensitivity to HMs and reduced HM accumulation in yeast cells; While in type 2 BpMTs, the contribution of N and C domain to HMs' chelation possibly corelated to the quantity of Cys residues. CONCLUSION: The BpMT genes are crucial in responding to diverse HM stresses and are involved in ABA signaling. The Cys-rich domains of BpMTs are pivotal for HM tolerance and chelation. This study offers new insights into the structure-function relationships and metal-binding capabilities of type-1 and - 2 plant MTs, enhancing our understanding of their roles in plant adaptation to HM stresses.

Structure Evolution of 2D Covalent Organic Frameworks Unveiled by Single-Crystal X-ray Diffraction.

We report 9 crystal structures of a two-dimensional (2D) covalent organic framework (COF), including the parent Py-1P, 5 derivatives formed by chemical reactions, and 3 dynamic states by solvent exchange/loss. Structure details of these porous crystals, including stacking mode, interlayer distance, pore aperture, and incline angle, before, during, and after conversion processes in solution, were unveiled by single-crystal X-ray diffraction with resolutions up to 0.85 Å. The structure evolution is triggered by stepwise conformational transformation of the molecular building blocks in 2D COF, while their long-range ordering remained unsacrificed.

Targeted serum proteome profiling reveals nicotinamide adenine dinucleotide phosphate (NADPH)-related biomarkers to discriminate linear IgA bullous disorder from dermatitis herpetiformis.

Linear IgA bullous dermatosis (LABD) and dermatitis herpetiformis (DH) represent the major subtypes of IgA mediated autoimmune bullous disorders. We sought to understand the disease etiology by using serum proteomics. We assessed 92 organ damage biomarkers in LAB, DH, and healthy controls using the Olink high-throughput proteomics. The positive proteomic serum biomarkers were used to correlate with clinical features and HLA type. Targeted proteomic analysis of IgA deposition bullous disorders vs. controls showed elevated biomarkers. Further clustering and enrichment analyses identified distinct clusters between LABD and DH, highlighting the involvement of nicotinamide adenine dinucleotide phosphate (NADPH) oxidase. Comparative analysis revealed biomarkers with distinction between LABD and DH and validated in the skin lesion. Finally, qualitative correlation analysis with DEPs suggested six biomarkers (NBN, NCF2, CAPG, FES, BID, and PXN) have better prognosis in DH patients. These findings provide potential biomarkers to differentiate the disease subtype of IgA deposition bullous disease.

Heterochromatin loosening by the Oct4 linker region facilitates Klf4 binding and iPSC reprogramming.

The success of Yamanaka factor reprogramming of somatic cells into induced pluripotent stem cells suggests that some factor(s) must remodel the nuclei from a condensed state to a relaxed state. How factor-dependent chromatin opening occurs remains unclear. Using FRAP and ATAC-seq, we found that Oct4 acts as a pioneer factor that loosens heterochromatin and facilitates the binding of Klf4 and the expression of epithelial genes in early reprogramming, leading to enhanced mesenchymal-to-epithelial transition. A mutation in the Oct4 linker, L80A, which shows impaired interaction with the BAF complex component Brg1, is inactive in heterochromatin loosening. Oct4-L80A also blocks the binding of Klf4 and retards MET. Finally, vitamin C or Gadd45a could rescue the reprogramming deficiency of Oct4-L80A by enhancing chromatin opening and Klf4 binding. These studies reveal a cooperation between Oct4 and Klf4 at the chromatin level that facilitates MET at the cellular level and shed light into the research of multiple factors in cell fate determination.

FeSA­Ir/Metallene Nanozymes Induce Sequential Ferroptosis­Pyroptosis for Multi­Immunogenic Responses Against Lung Metastasis.

For cancer metastasis inhibition, the combining of nanozymes with immune checkpoint blockade (ICB) therapy remains the major challenge in controllable reactive oxygen species (ROS) generation for creating effective immunogenicity. Herein, new nanozymes with light-controlled ROS production in terms of quantity and variety are developed by conjugating supramolecular-wrapped Fe single atom on iridium metallene with lattice-strained nanoislands (FeSA-Ir@PF NSs). The Fenton-like catalysis of FeSA-Ir@PF NSs effectively produced •OH radicals in dark, which induced ferroptosis and apoptosis of cancer cells. While under second near-infrared (NIR-II) light irradiation, FeSA-Ir@PF NSs showed ultrahigh photothermal conversion efficiency (𝜂, 75.29%), cooperative robust •OH generation, photocatalytic O2 and 1O2 generation, and caused significant pyroptosis of cancer cells. The controllable ROS generation, sequential cancer cells ferroptosis and pyroptosis, led 99.1% primary tumor inhibition and multi-immunogenic responses in vivo. Most importantly, the inhibition of cancer lung metastasis is completely achieved by FeSA-Ir@PF NSs with immune checkpoint inhibitors, as demonstrated in different mice lung metastasis models, including circulating tumor cells (CTCs) model. This work provided new inspiration for developing nanozymes for cancer treatments and metastasis inhibition.

Devastating the Supply Wagons: Multifaceted Liposomes Capable of Exhausting Tumor to Death via Triple Energy Depletion.

The anabolism of tumor cells can not only support their proliferation, but also endow them with a steady influx of exogenous nutrients. Therefore, consuming metabolic substrates or limiting access to energy supply can be an effective strategy to impede tumor growth. Herein, a novel treatment paradigm of starving-like therapy-triple energy-depleting therapy-is illustrated by glucose oxidase (GOx)/dc-IR825/sorafenib liposomes (termed GISLs), and such a triple energy-depleting therapy exhibits a more effective tumor-killing effect than conventional starvation therapy that only cuts off one of the energy supplies. Specifically, GOx can continuously consume glucose and generate toxic H2O2 in the tumor microenvironment (including tumor cells). After endocytosis, dc-IR825 (a near-infrared cyanine dye) can precisely target mitochondria and exert photodynamic and photothermal activities upon laser irradiation to destroy mitochondria. The anti-angiogenesis effect of sorafenib can further block energy and nutrition supply from blood. This work exemplifies a facile and safe method to exhaust the energy in a tumor from three aspects and starve the tumor to death and also highlights the importance of energy depletion in tumor treatment. It is hoped that this work will inspire the development of more advanced platforms that can combine multiple energy depletion therapies to realize more effective tumor treatment.