Structures of SenB and SenA enzymes from Variovorax paradoxus provide insights into carbon-selenium bond formation in selenoneine biosynthesis.

Selenoneine, an ergothioneine analog, is important for antioxidation and detoxification. SenB and SenA are two crucial enzymes that form carbon-selenium bonds in the selenoneine biosynthetic pathway. To investigate their underlying catalytic mechanisms, we obtained complex structures of SenB with its substrate UDP-N-acetylglucosamine (UDP-GlcNAc) and SenA with N-α-trimethyl histidine (TMH). SenB adopts a type-B glycosyltransferase fold. Structural and functional analysis of the interaction network at the active center provide key information on substrate recognition and suggest a metal-ion-independent, inverting mechanism is utilized for SenB-mediated selenoglycoside formation. Moreover, the complex structure of SenA with TMH and enzymatic activity assays highlight vital residues that control substrate binding and specificity. Based on the conserved structure and substrate-binding pocket of the type I sulfoxide synthase EgtB in the ergothioneine biosynthetic pathway, a similar reaction mechanism was proposed for the formation of C-Se bonds by SenA. The structures provide knowledge on selenoneine synthesis and lay groundwork for further applications of this pathway.

Kernel Bayesian logistic tensor decomposition with automatic rank determination for predicting multiple types of miRNA-disease associations.

Identifying the association and corresponding types of miRNAs and diseases is crucial for studying the molecular mechanisms of disease-related miRNAs. Compared to traditional biological experiments, computational models can not only save time and reduce costs, but also discover potential associations on a large scale. Although some computational models based on tensor decomposition have been proposed, these models usually require manual specification of numerous hyperparameters, leading to a decrease in computational efficiency and generalization ability. Additionally, these linear models struggle to analyze complex, higher-order nonlinear relationships. Based on this, we propose a novel framework, KBLTDARD, to identify potential multiple types of miRNA-disease associations. Firstly, KBLTDARD extracts information from biological networks and high-order association network, and then fuses them to obtain more precise similarities of miRNAs (diseases). Secondly, we combine logistic tensor decomposition and Bayesian methods to achieve automatic hyperparameter search by introducing sparse-induced priors of multiple latent variables, and incorporate auxiliary information to improve prediction capabilities. Finally, an efficient deterministic Bayesian inference algorithm is developed to ensure computational efficiency. Experimental results on two benchmark datasets show that KBLTDARD has better Top-1 precision, Top-1 recall, and Top-1 F1 for new type predictions, and higher AUPR, AUC, and F1 values for new triplet predictions, compared to other state-of-the-art methods. Furthermore, case studies demonstrate the efficiency of KBLTDARD in predicting multiple types of miRNA-disease associations.

HyperGCN: an effective deep representation learning framework for the integrative analysis of spatial transcriptomics data.

BACKGROUND: Advances of spatial transcriptomics technologies enabled simultaneously profiling gene expression and spatial locations of cells from the same tissue. Computational tools and approaches for integration of transcriptomics data and spatial context information are urgently needed to comprehensively explore the underlying structure patterns. In this manuscript, we propose HyperGCN for the integrative analysis of gene expression and spatial information profiled from the same tissue. HyperGCN enables data visualization and clustering, and facilitates downstream analysis, including domain segmentation, the characterization of marker genes for the specific domain structure and GO enrichment analysis. RESULTS: Extensive experiments are implemented on four real datasets from different tissues (including human dorsolateral prefrontal cortex, human positive breast tumors, mouse brain, mouse olfactory bulb tissue and Zabrafish melanoma) and technologies (including 10X visium, osmFISH, seqFISH+, 10X Xenium and Stereo-seq) with different spatial resolutions. The results show that HyperGCN achieves superior clustering performance and produces good domain segmentation effects while identifies biologically meaningful spatial expression patterns. This study provides a flexible framework to analyze spatial transcriptomics data with high geometric complexity. CONCLUSIONS: HyperGCN is an unsupervised method based on hypergraph induced graph convolutional network, where it assumes that there existed disjoint tissues with high geometric complexity, and models the semantic relationship of cells through hypergraph, which better tackles the high-order interactions of cells and levels of noise in spatial transcriptomics data.

A study on the physical aging characteristics of the older people over 70 years old in China.

Aim: In China, with the increase of life expectancy and the decrease of fertility rate, the aging problem has become increasingly prominent, and the physical problems of the older people over 70 years are the key and difficult problems. Method: Based on the interactive logic between the aging problem and the older people health, in the study, a questionnaire survey and a nationwide physical fitness test were carried out on the older people over 70, to divide into different age groups (70-74 years old, 75-79 years old, 80-84 years old, 85 years old and older) and different genders. There were 8,400 valid samples, and 1,050 persons in each group. One-way ANOVA was used to compare the differences among groups of different ages, and a broken line chart was drawn to discuss the aging characteristics of various physical indexes of the older people over 70 in China. Result: (1) Body morphology: male waist circumference, male waist-to-height ratio and female BMI showed a gradual downward trend with the increase of age; (2) Physiological function: male and female vital capacity showed a decreasing trend with the increase of age, while female pulse pressure showed a gradual upward trend. (3) Physical quality: the indicators of male and female muscle strength, flexibility quality, aerobic endurance and balance showed a downward trend with the increase of age. Conclusion: Vital capacity, flexibility quality, muscle strength, aerobic endurance, balance ability and so on, decreased significantly with the growth of age. 80 years old is the inflection point of the rapid decline of various indicators. Blood pressure, silent pulse, BMI, waist-to-hip ratio, waist-to-height ratio and other indicators did not change regularly with age. Indicators such as blood pressure, BMI, waist-to-hip ratio and waist-to-height ratio were in the high-risk range of metabolic diseases and cardiovascular and cerebrovascular diseases. The study conducted physical fitness test on the older people over 70 years old in 7 geographical regions of China, which is the first nationwide physical fitness test for the older people, which is an extension and expansion of the national physical fitness monitoring system, and also shows that the test indicators involved in the "Health fitness scale" are simple and feasible. And the study added a series of test data over 70 years old, which is the basis for scientific and reasonable formulation of physical fitness evaluation standards for the older people, and is of great significance for improving the national physical fitness database and grasping the dynamic changes of national physical health status, and providing data support for scientific guidance of physical exercise for the older people.

Citrobacter rodentium infection impairs dopamine metabolism and exacerbates the pathology of Parkinson's disease in mice.

Parkinson's disease (PD) is a prevalent neurodegenerative disorder with indistinct etiology and ill-defined pathophysiology. Intestinal inflammation involved in the pathogenesis of PD, but the underlying mechanism is not fully understood. Citrobacter rodentium (C.R) is a gram-negative bacterium that can be used to induce human inflammatory bowel disease in mice. Here, we investigated whether the proinflammatory effects caused by C.R infection initiate PD-like injury and/or exacerbate PD pathology and extensively studied the underlying mechanism. Mice were gavaged once with C.R and monitored for several pathological features at 9 days post infection. The results showed that C.R delivery in mice induced IBD-like symptoms, including significant weight loss, increased fecal water content, an impaired intestinal barrier, intestinal hyperpermeability and inflammation, and intestinal microbiota disturbances. Notably, C.R infection modified dopamine (DA) metabolism in the brains of both male and female mice. Subsequently, a single high dose of MPTP or normal saline was administered at 6 days post infection. At 3 days after MPTP administration, the feces were collected for 16 S rRNA analysis, and PD-like phenotypes and mechanisms were systemically analyzed. Compared with C.R or MPTP injection alone, the injection of C.R and MPTP combined worsened behavioral performance. Moreover, such combination triggered more severe dopaminergic degeneration and glial cell overactivation in the nigrostriatal pathway of mice. Mechanistically, the combination of C.R and MPTP increased the expression of TLR4 and NF-κB p65 in the colon and striatum and upregulated proinflammatory cytokine expression. Therefore, C.R infection-induced intestinal inflammation can impair dopamine metabolism and exacerbate PD pathological processes.

De novo design of SARS-CoV-2 main protease inhibitors with characteristic binding modes.

The coronavirus disease 2019 (COVID-19) is caused by a novel coronavirus called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which spreads rapidly all over the world. The main protease (Mpro) is significant to the replication and transcription of viruses, making it an attractive drug target against coronaviruses. Here, we introduce a series of novel inhibitors which are designed de novo through structure-based drug design approach that have great potential to inhibit SARS-CoV-2 Mproin vitro. High-resolution structures show that these inhibitors form covalent bonds with the catalytic cysteine through the novel dibromomethyl ketone (DBMK) as a reactive warhead. At the same time, the designed phenyl group beside the DBMK warhead inserts into the cleft between H41 and C145 through π-π stacking interaction, splitting the catalytic dyad and disrupting proton transfer. This unique binding model provides novel clues for the cysteine protease inhibitor development of SARS-CoV-2 as well as other pathogens.

Hybrid Membrane-Camouflaged Biomimetic Immunomodulatory Nanoturrets with Sequential Multidrug Release for Potentiating T Cell-Mediated Anticancer Immunity.

Ascorbic acid (AA) has been attracting great attention with its emerging potential in T cell-dependent antitumor immunity. However, premature blood clearance and immunologically "cold" tumors severely compromise its immunotherapeutic outcomes. As such, the reversal of the immunosuppressive tumor microenvironment (TME) has been the premise for improving the effectiveness of AA-based immunotherapy, which hinges upon advanced AA delivery and amplified immune-activating strategies. Herein, a novel Escherichia coli (E. coli) outer membrane vesicle (OMV)-red blood cell (RBC) hybrid membrane (ERm)-camouflaged immunomodulatory nanoturret is meticulously designed based on gating of an AA-immobilized metal-organic framework (MOF) onto bortezomib (BTZ)-loaded magnesium-doped mesoporous silica (MMS) nanovehicles, which can realize immune landscape remodeling by chemotherapy-assisted ascorbate-mediated immunotherapy (CAMIT). Once reaching the acidic TME, the acidity-sensitive MOF gatekeeper and MMS core within the nanoturret undergo stepwise degradation, allowing for tumor-selective sequential release of AA and BTZ. The released BTZ can evoke robust immunogenic cell death (ICD), synergistically promote dendritic cell (DC) maturation in combination with OMV, and ultimately increase T cell tumor infiltration together with Mg2+. The army of T cells is further activated by AA, exhibiting remarkable antitumor and antimetastasis performance. Moreover, the CD8-deficient mice model discloses the T cell-dependent immune mechanism of the AA-based CAMIT strategy. In addition to providing a multifunctional biomimetic hybrid nanovehicle, this study is also anticipated to establish a new immunomodulatory fortification strategy based on the multicomponent-driven nanoturret for highly efficient T cell-activation-enhanced synergistic AA immunotherapy.

Ceria nanoparticles: biomedical applications and toxicity. / 二氧化铈纳米颗粒：生物医学应用和毒性.

Ceria nanoparticles (CeO2 NPs) have become popular materials in biomedical and industrial fields due to their potential applications in anti-oxidation, cancer therapy, photocatalytic degradation of pollutants, sensors, etc. Many methods, including gas phase, solid phase, liquid phase, and the newly proposed green synthesis method, have been reported for the synthesis of CeO2 NPs. Due to the wide application of CeO2 NPs, concerns about their adverse impacts on human health have been raised. This review covers recent studies on the biomedical applications of CeO2 NPs, including their use in the treatment of various diseases (e.|g., Alzheimer's disease, ischemic stroke, retinal damage, chronic inflammation, and cancer). CeO2 NP toxicity is discussed in terms of the different systems of the human body (e.|g., cytotoxicity, genotoxicity, respiratory toxicity, neurotoxicity, and hepatotoxicity). This comprehensive review covers both fundamental discoveries and exploratory progress in CeO2 NP research that may lead to practical developments in the future.

The Promising Potential of Gallium Based Liquid Metals for Energy Storage.

Energy storage devices play a crucial role in various applications, such as powering electronics, power backup for homes and businesses, and support for the integration of renewable energy sources into electrical grid applications. Electrode materials for energy storage devices are preferred to have a flexible nature, conductive, better capacity, and low-toxicity. Using Gallium based liquid metal alloys, such as Eutectic Gallium-Indium (EGaIn), Eutectic Gallium-Tin (EGaSn), and Eutectic Gallium-Indium-Tin (EGaInSn), as electrode materials play very important role in energy storage devices. These liquid metals have some interesting properties with a self-healing nature, high mechanical stability, compatibility with various materials, fluidity, low young's modulus, high electrical and thermal conductivity. Those properties have made it suitable to be used in various energy storage devices. In this mini review, we have concisely described the advantages and challenges of using liquid metal as electrode materials for various energy storage devices.

Polyaniline/Tungsten Trioxide Organic-Inorganic Hybrid Anode for Aqueous Proton Batteries.

Aqueous proton batteries have received increasing attention due to their outstanding rate performance, stability and high capacity. However, the selection of anode materials in strongly acidic electrolytes poses a challenge in achieving high-performance aqueous proton batteries. This study optimized the proton reaction kinetics of layered metal oxide WO3 by introducing interlayer structural water and coating polyaniline (PANI) on its surface to prepare organic-inorganic hybrid material (WO3 ⋅ 2H2O@PANI). We constructed an aqueous proton battery with WO3 ⋅ 2H2O@PANI anode and MnO2@GF cathode. After 1500 cycles at a current density of 10 A g-1, the capacity retention rate can still reach 80.2 %. These results can inspire the development of new aqueous proton batteries.

A machine learning-based approach to predict energy layer for each field in spot-scanning proton arc therapy for lung cancer: A feasibility study.

BACKGROUND: Determining the optimal energy layer (EL) for each field, under considering both dose constraints and delivery efficiency, is crucial to promoting the development of proton arc therapy (PAT) technology. PURPOSE: This study aimed to explore the feasibility and potential clinical benefits of utilizing machine learning (ML) technique to automatically select EL for each field in PAT plans of lung cancer. METHODS: Proton Bragg peak position (BPP) was employed to characterize EL. The ground truth BPPs for each field were determined using the modified ELO-SPAT framework. Features in geometric, water-equivalent thicknesses (WET) and beamlet were defined and extracted. By analyzing the relationship between the extracted features and ground truth, a polynomial regression model with L2-norm regularization (Ridge regression) was constructed and trained. The performance of the regression model was reported as an error between the predictions and the ground truth. Besides, the predictions were used to make PAT plans (PAT_PRED). These plans were compared with those using the ground truth BPPs (PAT_TRUTH) and the mid-WET of the target volumes (PAT_MID) in terms of relative biological effectiveness-weighted dose (RWD) distributions. One hundred ten patients with lung cancer, a total of 7920 samples, were enrolled retrospectively, with 5940 cases randomly selected as the training set and the remaining 1980 cases as the testing set. Nine patients (648 samples) were collected additionally to evaluate the regression model in terms of plan quality and robustness. RESULTS: With regard to the prediction errors, the root mean squared errors and mean absolute errors between the ML-predicted and ground truth BPPs for the testing set were 9.165 and 6.572 mm, respectively, indicating differences of approximately two to three ELs. As for plan quality, the PAT_TRUTH and PAT_PRED plans performed similarly in terms of plan robustness, target coverage and organs at risk (OARs) protection, with differences smaller than 0.5 Gy(RBE). This trend was also observed for dose conformity and uniformity. The PAT_MID plans produced the lowest robustness index and lowest doses to OARs, along with the highest heterogeneity index, indicating better protection for OARs, improved plan robustness, but compromised dose homogeneity. Additionally, for relatively small tumor sizes, the PAT_MID plan demonstrated a notably poor dose conformity index. CONCLUSIONS: Within this cohort under investigation, our study demonstrated the feasibility of using ML technique to predict ELs for each field, offering a fast (within 2 s) and memory-efficient reduced way to select ELs for PAT plan.

An Amino Acids and Dipeptide Injection Inhibits the TNF-α/HMGB1 Inflammatory Signaling Pathway to Reduce Pyroptosis and M1 Microglial Polarization in POCD Mice: the Gut to the Brain.

Peripheral surgery-induced neural inflammation is a key pathogenic mechanism of postoperative cognitive dysfunction (POCD). However, the mechanism underlying neuroinflammation and associated neural injury remains elusive. Surgery itself can lead to gut damage, and the occurrence of POCD is accompanied by high levels of TNF-α in the serum and blood‒brain barrier (BBB) damage. Reductions in stress, inflammation and protein loss have been emphasized as strategies for enhanced recovery after surgery (ERAS). We designed an amino acids and dipeptide (AAD) formula for injection that could provide intestinal protection during surgery. Through the intraoperative infusion of AAD based on the ERAS concept, we aimed to explore the effect of AAD injection on POCD and its underlying mechanism from the gut to the brain. Here, we observed that AAD injection ameliorated neural injury in POCD, in addition to restoring the function of the intestinal barrier and BBB. We also found that TNF-α levels decreased in the ileum, blood and hippocampus. Intestinal barrier protectors and TNF-α inhibitors also alleviated neural damage. AAD injection treatment decreased HMGB1 production, pyroptosis, and M1 microglial polarization and increased M2 polarization. In vitro, AAD injection protected the impaired gut barrier and decreased TNF-α production, alleviating damage to the BBB by stimulating cytokine transport in the body. HMGB1 and Caspase-1 inhibitors decreased pyroptosis and M1 microglial polarization and increased M2 polarization to protect TNF-α-stimulated microglia in vitro. Collectively, these findings suggest that the gut barrier-TNF-α-BBB-HMGB1-Caspase-1 inflammasome-pyroptosis-M1 microglia pathway is a novel mechanism of POCD related to the gut-brain axis and that intraoperative AAD infusion is a potential treatment for POCD.

Photoactivated Formation of an Extravascular Dynamic Hydrogel as an Intelligent Blood Flow Regulator to Reprogram the Immunogenic Landscape.

Long-term tumor starvation may be a potential strategy to elevate the antitumor immune response by depriving nutrients. However, combining long-term starvation therapy with immunotherapy often yields limited efficacy due to the blockage of immune cell migration pathways. Herein, an intelligent blood flow regulator (BFR) is first established through photoactivated in situ formation of the extravascular dynamic hydrogel to compress blood vessels, which can induce long-term tumor starvation to elicit metabolic stress in tumor cells without affecting immune cell migration pathways. By leveraging methacrylate-modified nanophotosensitizers (HMMAN) and biodegradable gelatin methacrylate (GelMA), the developed extravascular hydrogel dynamically regulates blood flow via enzymatic degradation. Additionally, aPD-L1 loaded into HMMAN continuously blocks immune checkpoints. Systematic in vivo experiments demonstrate that the combination of immune checkpoint blockade (ICB) and BFR-induced metabolic stress (BIMS) significantly delays the progression of Lewis lung and breast cancers by reshaping the tumor immunogenic landscape and enhancing antitumor immune responses.

Association of urinary bisphenol A levels with heart failure risk in U.S. adults from the NHANES (2003-2016).

Introduction: Although heart failure (HF) has been linked to bisphenol A (BPA), few studies have investigated the cut-off values for the effects of urinary BPA levels on heart failure risk. The association between urinary BPA levels and HF prognosis has not been investigated. Methods: This study included 11,849 adults over 20 years old using information from the National Health and Nutrition Examination Survey (NHANES), which was conducted from 2003 to 2016. The relationship between urinary BPA levels and the risk of HF was determined via a multivariable logistic regression model, and restricted cubic spline (RCS) methods were used to determine the cut-off for the effect of BPA levels on HF risk. Based on the available NT-proBNP concentration data from the NHANES (2003-2004), multivariable linear regression was applied to determine the linear association between the NT-proBNP concentration and urinary BPA concentration. Results: The results revealed a positive correlation between a urinary BPA concentration in the fourth quartile and the occurrence of heart failure [OR 1.49, 95% CI (1.09, 2.04), p = 0.012]. A one-unit increase (1 ng/mg creatinine) in the ln-transformed BPA concentration was linked to a 15% increase in the incidence of HF [OR 1.15, 95% CI (1.03, 1.29), p = 0.014]. The cut-off urinary BPA concentration for HF risk was 1.51 ng/mg creatinine. There was a positive correlation between urinary BPA and NT-proBNP concentrations [ß = 0.093, 95% CI (0.014, 0.171), p = 0.02] in males, but there was no linear association [ß = 0.040, 95% CI (-0.033, 0.113), p = 0.283] in females. Discussion: Increased urinary BPA levels are linked to an increased risk of heart failure and poor prognosis. There is a significant increase in the risk of heart failure if the urinary concentration of BPA exceeds 1.51 ng/mg creatinine.

MicroRNA-19a-3p augments TGF-ß1-induced cardiac fibroblast activation via targeting BAMBI.

The main pathogenic factor leading to cardiac remodeling and heart failure is myocardial fibrosis. Recent research indicates that microRNAs are essential for the progress of cardiac fibrosis. Myocardial fibrosis is considered to be alleviated through the bone morphogenetic protein and activin membrane-bound inhibitor (BAMBI), which does this by blocking the transforming growth factor ß1 (TGF-ß1) signaling pathway. Here, this study sought to elucidate the post-transcriptional regulation of miR-19a-3p on BAMBI and its role in TGF-ß1-induced cardiac fibroblast activation. Transverse aortic constriction (TAC) caused both myocardial interstitial and perivascular collagen deposition. RT-PCR showed that miR-19a-3p was upregulated in the myocardial tissue of cardiac fibrosis, and TGF-ß1 induced an increase of miR-19a-3p expression in cardiac fibroblasts. The dual-luciferase reporter test and qRT-PCR confirmed that miR-19a-3p directly combined with BAMBI mRNA 3'UTR, thus reduced BAMBI expression, which diminished the capability of BAMBI to inhibit TGF-ß1. Furthermore, miR-19a-3p mimic increased the activation of TGF-ß1/SMAD2/3 pathway signaling, which supported cardiac fibroblast activation, which blocked by overexpression of BAMBI. These findings imply that miR-19a-3p enhances the activation of TGF-ß1/SMAD2/3 by inhibiting BAMBI, further boosting the activation of cardiac fibroblasts, and may thus offer a novel strategy to tackling myocardial fibrosis.

Atorvastatin-induced intracerebral hemorrhage is inhibited by berberine in zebrafish.

Intracerebral hemorrhage (ICH), for which there are currently no effective preventive or treatment methods, has a very high fatality rate. Statins, such as atorvastatin (ATV), are the first-line drugs for regulating blood lipids and treating hyperlipidemia-related cardiovascular diseases. However, ATV-associated ICH has been reported, although its incidence is rare. In this study, we aimed to investigate the protective action and mechanisms of berberine (BBR) against ATV-induced brain hemorrhage. We established an ICH model in zebrafish induced by ATV (2 µM) and demonstrated the effects of BBR (10, 50, and 100 µM) on ICH via protecting the vascular network using hemocyte staining and three transgenic zebrafish. BBR was found to reduce brain inflammation and locomotion injury in ICH-zebrafish. Mechanism research showed that ATV increased the levels of VE-cadherin and occludin proteins but disturbed their localization at the cell membrane by abnormal phosphorylation, which decreased the number of intercellular junctions between vascular endothelial cells (VECs), disrupting the integrity of vascular walls. BBR reversed the effects of ATV by promoting autophagic degradation of phosphorylated VE-cadherin and occludin in ATV-induced VECs examined by co-immunoprecipitation (co-IP). These findings provide crucial insights into understanding the BBR mechanisms involved in the maintenance of vascular integrity and in mitigating adverse reactions to ATV.

The mediating effect of internet addiction and the moderating effect of physical activity on the relationship between alexithymia and depression.

There is a certain relationship between alexithymia and depression, but further investigation is needed to explore their underlying mechanisms. The aims of this study was to explore the mediating role of internet addiction between alexithymia and depression and the moderating role of physical activity. A total of 594 valid responses were included in the analysis, with a mean age of 18.72 years (SD = 1.09). The sample comprised 250 males (42.09%) and 344 females (57.91%). These responses were utilized for descriptive analysis, correlation analysis, regression analysis, and the development of mediation and moderation models. Alexithymia showed positive correlations with depression and internet addiction, and physical activity was negatively correlated with internet addiction and depression. Internet addiction partially mediated the relationship between alexithymia and depression, while physical activity weakened the association between internet addiction and depression, acting as a moderator. Our findings suggest that excessive Internet engagement may mediate the relationship between alexithymia and depression as an emotional regulatory coping strategy, and that physical activity attenuates the predictive effect of Internet addiction on depression.

Nanocellulose-mediated bilayer hydrogel actuators with thermo-responsive, shape memory and self-sensing performances.

Inspired by creatures, abundant stimulus-responsive hydrogel actuators with diverse functionalities have been manufactured for applications in soft robotics. However, constructing a shape memory and self-sensing bilayer hydrogel actuator with high mechanical strength and strong interfacial bonding still remains a challenge. Herein, a novel bilayer hydrogel with a stimulus-responsive TEMPO-oxidized cellulose nanofibers/poly(N-isopropylacrylamide) (TOCN/PNIPAM) layer and a non-responsive TOCN/polyacrylamide (TOCN/PAM) layer is proposed as a thermosensitive actuator. TOCNs as a nano-reinforced phase provide a high mechanical strength and endow the hydrogel actuator with a strong interfacial bonding. Due to the incorporation of TOCNs, the TOCN/PNIPAM hydrogel exhibits a high compressive strength (~89.2 kPa), elongation at break (~170.7 %) and tensile strength (~24.0 kPa). The prepared PNIPAM/TOCN/PAM hydrogel actuator performs the roles of an encapsulation, jack, temperature-controlled fluid valve and temperature-control manipulator. The incorporation of Fe3+ further endows the bilayer hydrogel actuator with a synergistic performance of shape memory and temperature-driven, which can be used as a temperature-responsive switch to detect ambient temperature. The PNIPAM/TOCN/PAM-Fe3+ conductive hydrogel can be assembled into a flexible sensor and generate sensing signals when driven by temperature changes to achieve real-time feedback. This research may lead to new insights into the design and manufacturing of intelligent flexible soft robots.

Frequency-encoded eye tracking smart contact lens for human-machine interaction.

Eye tracking techniques enable high-efficient, natural, and effortless human-machine interaction by detecting users' eye movements and decoding their attention and intentions. Here, a miniature, imperceptible, and biocompatible smart contact lens is proposed for in situ eye tracking and wireless eye-machine interaction. Employing the frequency encoding strategy, the chip-free and battery-free lens successes in detecting eye movement and closure. Using a time-sequential eye tracking algorithm, the lens has a great angular accuracy of <0.5°, which is even less than the vision range of central fovea. Multiple eye-machine interaction applications, such as eye-drawing, Gluttonous Snake game, web interaction, pan-tilt-zoom camera control, and robot vehicle control, are demonstrated on the eye movement model and in vivo rabbit. Furthermore, comprehensive biocompatibility tests are implemented, demonstrating low cytotoxicity and low eye irritation. Thus, the contact lens is expected to enrich approaches of eye tracking techniques and promote the development of human-machine interaction technology.