IL-27 signalling promotes adipocyte thermogenesis and energy expenditure.

Thermogenesis in brown and beige adipose tissue has important roles in maintaining body temperature and countering the development of metabolic disorders such as obesity and type 2 diabetes1,2. Although much is known about commitment and activation of brown and beige adipose tissue, its multiple and abundant immunological factors have not been well characterized3-6. Here we define a critical role of IL-27-IL-27Rα signalling in improving thermogenesis, protecting against diet-induced obesity and ameliorating insulin resistance. Mechanistic studies demonstrate that IL-27 directly targets adipocytes, activating p38 MAPK-PGC-1α signalling and stimulating the production of UCP1. Notably, therapeutic administration of IL-27 ameliorated metabolic morbidities in well-established mouse models of obesity. Consistently, individuals with obesity show significantly decreased levels of serum IL-27, which can be restored after bariatric surgery. Collectively, these findings show that IL-27 has an important role in orchestrating metabolic programs, and is a highly promising target for anti-obesity immunotherapy.

A P-type pentatricopeptide repeat protein ZmRF5 promotes 5' region partial cleavages of atp6c transcripts to restore the fertility of CMS-C maize by recruiting a splicing factor.

A fast evolution within mitochondria genome(s) often generates discords between nuclear and mitochondria, which is manifested as cytoplasmic male sterility (CMS) and fertility restoration (Rf) system. The maize CMS-C trait is regulated by the chimeric mitochondrial gene, atp6c, and can be recovered by the restorer gene ZmRf5. Through positional cloning in this study, we identified the nuclear restorer gene, ZmRf5, which encodes a P-type pentatricopeptide repeat (PPR) family protein. The over-expression of ZmRf5 brought back the fertility to CMS-C plants, whereas its genomic editing by CRISPR/Cas9 induced abortive pollens in the restorer line. ZmRF5 is sorted to mitochondria, and recruited RS31A, a splicing factor, through MORF8 to form a cleaving/restoring complex, which promoted the cleaving of the CMS-associated transcripts atp6c by shifting the major cleavage site from 480th nt to 344 th nt for fast degradation, and preserved just right amount of atp6c RNA for protein translation, providing adequate ATP6C to assembly complex V, thus restoring male fertility. Interestingly, ATP6C in the sterile line CMo17A, with similar cytology and physiology changes to YU87-1A, was accumulated much less than it in NMo17B, exhibiting a contrary trend in the YU87-1 nuclear genome previously reported, and was restored to normal level in the presence of ZmRF5. Collectively these findings unveil a new molecular mechanism underlying fertility restoration by which ZmRF5 cooperates with MORF8 and RS31A to restore CMS-C fertility in maize, complemented and perfected the sterility mechanism, and enrich the perspectives on communications between nucleus and mitochondria.

Construction of lymph nodes-targeting tumor vaccines by using the principle of DNA base complementary pairing to enhance anti-tumor cellular immune response.

Tumor vaccines, a crucial immunotherapy, have gained growing interest because of their unique capability to initiate precise anti-tumor immune responses and establish enduring immune memory. Injected tumor vaccines passively diffuse to the adjacent draining lymph nodes, where the residing antigen-presenting cells capture and present tumor antigens to T cells. This process represents the initial phase of the immune response to the tumor vaccines and constitutes a pivotal determinant of their effectiveness. Nevertheless, the granularity paradox, arising from the different requirements between the passive targeting delivery of tumor vaccines to lymph nodes and the uptake by antigen-presenting cells, diminishes the efficacy of lymph node-targeting tumor vaccines. This study addressed this challenge by employing a vaccine formulation with a tunable, controlled particle size. Manganese dioxide (MnO2) nanoparticles were synthesized, loaded with ovalbumin (OVA), and modified with A50 or T20 DNA single strands to obtain MnO2/OVA/A50 and MnO2/OVA/T20, respectively. Administering the vaccines sequentially, upon reaching the lymph nodes, the two vaccines converge and simultaneously aggregate into MnO2/OVA/A50-T20 particles through base pairing. This process enhances both vaccine uptake and antigen delivery. In vitro and in vivo studies demonstrated that, the combined vaccine, comprising MnO2/OVA/A50 and MnO2/OVA/T20, exhibited robust immunization effects and remarkable anti-tumor efficacy in the melanoma animal models. The strategy of controlling tumor vaccine size and consequently improving tumor antigen presentation efficiency and vaccine efficacy via the DNA base-pairing principle, provides novel concepts for the development of efficient tumor vaccines.

GPX4 aggravates experimental autoimmune encephalomyelitis by inhibiting the functions of CD4+ T cells.

Multiple sclerosis (MS) is a common autoimmunity disease of the central nervous system (CNS) that mostly happens in young adults. The chronic clinical features of MS include inflammatory demyelination, infiltration of immune cells, and secretion of inflammatory cytokines, which have been proved to be associated with CD4+ T cells. Ferroptosis is a newly discovered programmed cell death mediated by the massive lipid peroxidation and more sensitive to CD4+ T cells. However, the effect of ferroptosis of CD4+ T cells on the occurrence and progression of MS retains unclear. Here, the experimental autoimmune encephalomyelitis (EAE) model was used to investigate the role of GPX4, a leading inhibitor of ferroptosis, which plays in the function of CD4+ T cells. Our results showed that GPX4 was highly expressed in CD4+ T cells of MS patients based on existing databases. Strikingly, conditional knockout of GPX4 in CD4cre mice (cKO mice) significantly alleviated the average symptom scores and immunopathology of EAE. The infiltration of immune cells, including CD4+ T and CD8+ T cells, and the generation of GM-CSF, TNF-α, and IL-17A, were remarkably reduced in the CNS from cKO mice compared with WT mice. These findings further revealed the vital role of GPX4 in the expansion and function of CD4+ T cells. Moreover, GPX4-deficient CD4+ T cells were susceptible to ferroptosis in EAE model. Overall, this study provided novel insights into therapeutic strategies targeting GPX4 in CD4+ T cells for inhibiting CNS inflammation and treating MS.

Multimodal image and spectral feature learning for efficient analysis of water-suspended particles.

We have developed a method to combine morphological and chemical information for the accurate identification of different particle types using optical measurement techniques that require no sample preparation. A combined holographic imaging and Raman spectroscopy setup is used to gather data from six different types of marine particles suspended in a large volume of seawater. Unsupervised feature learning is performed on the images and the spectral data using convolutional and single-layer autoencoders. The learned features are combined, where we demonstrate that non-linear dimensional reduction of the combined multimodal features can achieve a high clustering macro F1 score of 0.88, compared to a maximum of 0.61 when only image or spectral features are used. The method can be applied to long-term monitoring of particles in the ocean without the need for sample collection. In addition, it can be applied to data from different types of sensor measurements without significant modifications.

Sensitive dynamics of brain cognitive networks and its resource constraints.

It is well known that brain functions are closely related to the synchronization of brain networks, but the underlying mechanisms are still not completely understood. To study this problem, we here focus on the synchronization of cognitive networks, in contrast to that of a global brain network, as individual brain functions are in fact performed by different cognitive networks but not the global network. In detail, we consider four different levels of brain networks and two approaches, i.e., either with or without resource constraints. For the case of without resource constraints, we find that global brain networks have fundamentally different behaviors from that of the cognitive networks; i.e., the former has a continuous synchronization transition, while the latter shows a novel transition of oscillatory synchronization. This feature of oscillation comes from the sparse links among the communities of cognitive networks, resulting in coupling sensitive dynamics of brain cognitive networks. While for the case of resource constraints, we find that at the global level, the synchronization transition becomes explosive, in contrast to the continuous synchronization for the case of without resource constraints. At the level of cognitive networks, the transition also becomes explosive and the coupling sensitivity is significantly reduced, thus guaranteeing the robustness and fast switch of brain functions. Moreover, a brief theoretical analysis is provided.

Phase frustration induced remote synchronization.

Remote synchronization (RS) may take an important role in brain functioning and its study has attracted much attention in recent years. So far, most studies of RS are focused on the Stuart-Landau oscillators with mean-field coupling. However, realistic cases may have more complicated couplings and behaviors, such as the brain networks. To make the study of RS a substantial progress toward realistic situations, we here present a model of RS with phase frustration and show that RS can be induced for those systems where no RS exists when there is no phase frustration. By numerical simulations on both the Stuart-Landau and Kuramoto oscillators, we find that the optimal range of RS depends on the match of phase frustrations between the hub and leaf nodes and a fixed relationship of this match is figured out. While for the non-optimal range of RS, we find that RS exists only in a linear band between the phase frustrations of the hub and leaf nodes. A brief theoretical analysis is provided to explain these results.

Unsupervised feature learning and clustering of particles imaged in raw holograms using an autoencoder.

Digital holography is a useful tool to image microscopic particles. Reconstructed holograms give high-resolution shape information that can be used to identify the types of particles. However, the process of reconstructing holograms is computationally intensive and cannot easily keep up with the rate of data acquisition on low-power sensor platforms. In this work, we explore the possibility of performing object clustering on holograms that have not been reconstructed, i.e., images of raw interference patterns, using the latent representations of a deep-learning autoencoder and a self-organizing mapping network in a fully unsupervised manner. We demonstrate this concept on synthetically generated holograms of different shapes, where clustering of raw holograms achieves an accuracy of 94.4%. This is comparable to the 97.4% accuracy achieved using the reconstructed holograms of the same targets. Directly clustering raw holograms takes less than 0.1 s per image using a low-power CPU board. This represents a three-order of magnitude reduction in processing time compared to clustering of reconstructed holograms and makes it possible to interpret targets in real time on low-power sensor platforms. Experiments on real holograms demonstrate significant gains in clustering accuracy through the use of synthetic holograms to train models. Clustering accuracy increased from 47.1% when the models were trained only on the real raw holograms, to 64.1% when the models were entirely trained on the synthetic raw holograms, and further increased to 75.9% when models were trained on the both synthetic and real datasets using transfer learning. These results are broadly comparable to those achieved when reconstructed holograms are used, where the highest accuracy of 70% achieved when clustering raw holograms outperforms the highest accuracy achieved when clustering reconstructed holograms by a significant margin for our datasets.

Effect of remote signal propagation in an empirical brain network.

Increasing evidence has shown that brain functions are seriously influenced by the heterogeneous structure of a brain network, but little attention has been paid to the aspect of signal propagation. We here study how a signal is propagated from a source node to other nodes on an empirical brain network by a model of bistable oscillators. We find that the unique structure of the brain network favors signal propagation in contrast to other heterogeneous networks and homogeneous random networks. Surprisingly, we find an effect of remote propagation where a signal is not successfully propagated to the neighbors of the source node but to its neighbors' neighbors. To reveal its underlying mechanism, we simplify the heterogeneous brain network into a heterogeneous chain model and find that the accumulation of weak signals from multiple channels makes a strong input signal to the next node, resulting in remote propagation. Furthermore, a theoretical analysis is presented to explain these findings.

Regulation of Keap-1/Nrf2 Signaling Pathway Is Activated by Oxidative Stress in Patients with Premature Rupture of Membranes.

BACKGROUND The potential mechanisms underlying premature rupture of membrane (PROM) is still unknown. The aim of this study was to determine the role of Keap-1/Nrf2 signaling pathway activation by oxidative stress in patients with preterm premature rupture of membranes. MATERIAL AND METHODS Placental tissues from preterm premature rupture of membranes (PPROM) (n=20), full-term premature rupture of membranes (FPROM) (n=20), and normal-term births (n=20) were collected and amniotic tissues were separated from the placental tissues from pregnant women at Shandong Provincial Qianfoshan Hospital. RT-PCR and Western blot were used to detect the levels of factors in the Keap-1/Nrf2 signaling pathway. To investigate the roles of Nrf2, we downregulated Nrf2 expression using siRNA in primary human amniotic epithelial (HAE) cells. RESULTS Among the control group, FPROM group, and PPROM group, the reactive oxygen species (ROS) levels were significantly increased in the FPROM and PPROM groups. The differences indicated higher levels of oxidative stress in amniotic tissues with FPROM and PPROM after downregulation of si-Nrf2 in HAE cells. Antioxidants were lower in amniotic tissues with the FPROM group and PPROM group than in the control group. The antioxidant enzymes catalase (CAT), glutathione (GSH), glutathione peroxidase (GSHPx), and superoxide dismutases (SOD1 and SOD2) were examined in amniotic tissues. We found that the ROS levels were significantly increased after downregulation of si-Nrf2 compared with the control group. We found that the expression of Heme Oxygenase-1 (HO-1) and Glycogen Synthase Kinase-3ß (GSK-3ß), which is critical in the Keap-1/Nrf2 signaling pathway, increased significantly after downregulation of si-Nrf2 in HAE cells. CONCLUSIONS We found that increased ROS levels and decreased antioxidant enzymes in the PPROM and FPROM patients compared with the control group.

Identification of microplastics in a large water volume by integrated holography and Raman spectroscopy.

A noncontact method to identify sparsely distributed plastic pellets is proposed by integrating holography and Raman spectroscopy in this study. Polystyrene and poly(methyl methacrylate) resin pellets with a size of 3 mm located in a 20 cm water channel were illuminated using a collimated continuous wave laser beam with a diameter of 4 mm and wavelength of 785 nm. The same laser beam was used to take a holographic image and Raman spectrum of a pellet to identify the shape, size, and composition of material. Using the compact system, the morphological and chemical analysis of pellets in a large volume of water was performed. The reported method demonstrates the potential for noncontact continuous in situ monitoring of microplastics in water without collection and separation.

How IQ depends on the running mode of brain network?

Increasing evidence has shown that intelligence quotient (IQ) depends not only on the aspect of phenomenology such as the size of brain and sexuality but also on the topology of the brain network. We here try to get a deeper understanding by asking how the running mode of the brain network influences IQ. We introduce a parameter α to represent the trade-off between wiring cost and processing efficiency and figure out the optimal value of α by the approach of network reconstruction. A negative correlation between optimal index α and IQ is revealed. To further find out the mechanism for the functional difference between males and females, we move to the local level of brain regions and study the relationship between regional optimal α and IQ. We find that the Pearson coefficients of males are significantly different from that of females, including both global and regional levels. These findings show that the functional differences between individuals, including the differences between males and females, are closely related to the different running modes of their brain networks.

NK007 helps in mitigating paclitaxel resistance through p38MAPK activation and HK2 degradation in ovarian cancer.

Ovarian cancer resistance to available medicines is a huge challenge in dire need of a solution, which makes its recurrence and mortality rate further exacerbated. A promising approach to overcome chemoresistance is drug screening from natural products. Here, we report that NK007, a (±)-tylophorine malate isolated from the Asclepiadaceae family, selectively inhibited the proliferation of A2780 and A2780 (Taxol) cells and migration of paclitaxel-sensitive and -resistant ovarian cancer cells. Interestingly, the decline of cell viability, including cell multiplication, clonality, and migration capacity was independent on cell apoptosis. At the molecular level, NK007 considerably induced G1/S arrest and upregulated the expression of phospho-p38 mitogen-activated protein kinase (p-p38MAPK). In addition, hexokinase 2 (HK2) protein degradation was considerably elevated in the presence of NK007, which resulted in the reduction of oxygen consumption rate and extracellular acidification rate. Altogether, our results indicate that NK007, an analog of tylophorine, can overcome paclitaxel (PTX) resistance through p38MAPK activation and HK2 degradation. As an effective, alternative antiresistance agent, NK007 exhibits a promising potential to treat PTX-resistant ovarian cancer.

Optical Microfiber Reader for Enzyme-Linked Immunosorbent Assay.

In clinical diagnosis, accurate and reliable measurement technologies for the detection of disease biomarkers at ultralow concentrations can provide guidance for the initiation of treatment and potentially improve survival for patients. Here, we demonstrate an optical microfiber reader for enhanced analytical sensitivity in enzyme-linked immunosorbent assays (ELISA) that enables the detection of tiny changes of the refractive index (RI) induced by the catalyzed oxidation of substrate, owing to the strong interaction between the evanescent field and surrounding medium. By employing the microfiber reader for the C-reaction protein (CRP) and interleukin-6 (IL-6) assays after the enzymatic signal amplification in ELISA, we experimentally investigate the biosensing capacity of the device. As a result, log-linear relations of CRP and IL-6 detection in PBS and human serum between the concentration and spectral response were obtained at both nanogram and picogram levels, respectively, and anti-CRP/HRP detection as low as 9.75 pg/mL was achieved, which was undetectable by the conventional spectrophotometry. With a stable, accurate, and color-free detection capacity, this optical microfiber reader has a promising prospect in early disease diagnosis and clinical treatment.

Quantitative assessment of disease markers using the naked eye: point-of-care testing with gas generation-based biosensor immunochromatographic strips.

BACKGROUND: Immunochromatographic strips (ICSs) are a practical tool commonly used in point-of-care testing (POCT) applications. However, ICSs that are currently available have low sensitivity and require expensive equipment for quantitative analysis. These limitations prohibit their extensive use in areas where medical resources are scarce. METHODS: We developed a novel POCT platform by integrating a gas generation biosensor with Au@Pt Core/Shell nanoparticle (Au@PtNPs)-based ICSs (G-ICSs). The resulting G-ICSs enabled the convenient and quantitative assessment of a target protein using the naked eye, without the need for auxiliary equipment or complicated computation. To assess this platform, C-reactive protein (CRP), a biomarker commonly used for the diagnosis of acute, infectious diseases was chosen as a proof-of-concept test. RESULTS: The linear detection range (LDR) of the G-ICSs for CRP was 0.05-6.25 µg/L with a limit of detection (LOD) of 0.041 µg/L. The G-ICSs had higher sensitivity and wider LDR when compared with commonly used AuNPs and fluorescent-based ICSs. When compared with results from a chemiluminescent immunoassay, G-ICS concordance rates for CRP detection in serum samples ranged from 93.72 to 110.99%. CONCLUSIONS: These results demonstrated that G-ICSs have wide applicability in family diagnosis and community medical institutions, especially in areas with poor medical resources.

Identifying epidemic threshold by temporal profile of outbreaks on networks.

Identifying epidemic threshold is of great significance in preventing and controlling disease spreading on real-world networks. Previous studies have proposed different theoretical and numerical approaches to determine the epidemic threshold for the susceptible-infected-recovered (SIR) model, but the numerical study of the critical points on networks by utilizing temporal characteristics of epidemic outbreaks is still lacking. Here, we study the temporal profile of epidemic outbreaks, i.e., the average avalanche shapes of a fixed duration. At the critical point, the rescaled average terminating and nonterminating avalanche shapes for different durations collapse onto two universal curves, respectively, while the average number of subsequent events essentially remains constant. We propose two numerical measures to determine the epidemic threshold by analyzing the convergence of the rescaled average nonterminating avalanche shapes for varying durations and the stability of the average number of subsequent events, respectively. Extensive numerical simulations demonstrate that our methods can accurately identify the numerical threshold for the SIR dynamics on synthetic and empirical networks. Compared with traditional numerical measures, our methods are more efficient due to the constriction of observation duration and thus are more applicable to large-scale networks. This work helps one to understand the temporal profile of disease propagation and would promote further studies on the phase transition of epidemic dynamics.

Cell Penetrating Peptide-Based Redox-Sensitive Vaccine Delivery System for Subcutaneous Vaccination.

In immunotherapy, induction of potent cellular immunity by vaccination is essential to treat intracellular infectious diseases and tumors. In this work, we designed a new synthetic peptide carrier, Cys-Trp-Trp-Arg8-Cys-Arg8-Cys-Arg8-Cys, for vaccine delivery by integrating a redox-responsive disulfide bond cross-linking and cell-penetrating peptide arginine octamer. The carrier peptide bound to the antigen protein ovalbumin (OVA) via electrostatic self-assembly to form peptide/OVA nanocomposites. Then, the spontaneous oxidization of the thiols of the cysteine residues induced interpeptide disulfide bond cross-linking to construct denser peptide/OVA condensates. The cell-penetrating peptides incorporated in the carrier peptide could increase antigen uptake by antigen presenting cells. After being internalized by antigen presenting cells, the antigen could be rapidly released in cytoplasm along with degradation of the disulfide bonds by intracellular glutathione, which could promote potent CD8+ T cell immunity. The cross-linked peptide/OVA condensates were used for subcutaneous vaccination. The results showed that the peptide carrier mediated potent antigen-specific immune response by significantly increasing IgG titer; splenocyte proliferation; the secretion level of cytokines INF-γ, IL-12, IL-4, and IL-10; immune memory function, and the activation and maturation of dendritic cells. From the results, the low-molecular weight vaccine-condensing peptide with definite chemical composition could be developed as a novel class of vaccine delivery systems.

A model of spreading of sudden events on social networks.

Information spreading has been studied for decades, but its underlying mechanism is still under debate, especially for those ones spreading extremely fast through the Internet. By focusing on the information spreading data of six typical events on Sina Weibo, we surprisingly find that the spreading of modern information shows some new features, i.e., either extremely fast or slow, depending on the individual events. To understand its mechanism, we present a susceptible-accepted-recovered model with both information sensitivity and social reinforcement. Numerical simulations show that the model can reproduce the main spreading patterns of the six typical events. By this model, we further reveal that the spreading can be speeded up by increasing either the strength of information sensitivity or social reinforcement. Depending on the transmission probability and information sensitivity, the final accepted size can change from continuous to discontinuous transition when the strength of the social reinforcement is large. Moreover, an edge-based compartmental theory is presented to explain the numerical results. These findings may be of significance on the control of information spreading in modern society.

Multiple peaks patterns of epidemic spreading in multi-layer networks.

The study of epidemic spreading on populations of networked individuals has seen recently a great deal of significant progresses. A common point in many of past studies is, however, that there is only one peak of infected density in each single epidemic spreading episode. At variance, real data from different cities over the world suggest that, besides a major single peak trait of infected density, a finite probability exists for a pattern made of two (or multiple) peaks. We show that such a latter feature is distinctive of a multilayered network of interactions, and reveal that a two peaks pattern may emerge from different time delays at which the epidemic spreads in between the two layers. Further, we show that the essential ingredient is a weak coupling condition between the layers themselves, while different degree distributions in the two layers are also helpful. Moreover, an edge-based theory is developed which fully explains all numerical results. Our findings may therefore be of significance for protecting secondary disasters of epidemics, which are definitely undesired in real life.

Zinc protection in fetal rats for maternal mercury exposure-induced growth retardation is probably associated with S100B expression.

AIM: The study was conducted to investigate the effects of maternal mercury exposure on fetal rat development and zinc protection in mercury-exposed rats. METHODS: Pregnant rats were subjected to zinc sulfate pre-feeding, mercury exposure and zinc sulfate co-feeding. The control rats were administered distilled water. On day 19, the placental weight, overall weight, size and tail length of fetal rats, mercury content and S100B level in the placenta were determined using Western blot analysis. RESULTS: Compared with the control, mercury exposure at 2.0 mg/kg.d significantly reduced placental weight and fetal development, resulting in reduced fetal weight, size and tail length, while zinc pre-feeding increased placental weight and other fetal developmental parameters. Compared with mercury exposure, co-feeding with zinc significantly reduced mercury-induced injury in the fetal rats. S100B and mercury content levels were significantly elevated in rats maternally exposed to methylmercury chloride, compared with the unexposed control, while co-feeding with methylmercury chloride and zinc sulfate significantly reduced S100B and mercury levels in the placenta. CONCLUSION: Maternal exposure to mercury results in increased S100B in the placenta. Zinc sulfate feeding could reduce S100B and mercury levels, thereby protecting the rats from mercury damage. S100B level may be used to measure the antagonism between zinc and mercury during pregnancy.