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The acidity of atmospheric aerosols influences fundamental physicochemical processes that affect climate and human health. We recently developed a novel and facile water-probe-based method for directly measuring of the pH for micrometer-size droplets, providing a promising technique to better understand aerosol acidity in the atmosphere. The complex chemical composition of fine particles in the ambient air, however, poses certain challenges to using a water-probe for pH measurement, including interference from interactions between compositions and the influence of similar compositions on water structure. To explore the universality of our method, it was employed to measure the pH of ammonium, nitrate, carbonate, sulfate, and chloride particles. The pH of particles covering a broad range (0-14) were accurately determined, thereby demonstrating that our method can be generally applied, even to alkaline particles. Furthermore, a standard spectral library was developed by integrating the standard spectra of common hydrated ions extracted through the water-probe. The library can be employed to identify particle composition and overcome the spectral overlap problem resulting from similar effects. Using the spectral library, all ions were identified and their concentrations were determined, in turn allowing successful pH measurement of multicomponent (ammonium-sulfate-nitrate-chloride) particles. Insights into the synergistic effect of Cl-, NO3-, and NH4+ depletion obtained with our approach revealed the interplay between pH and volatile partitioning. Given the ubiquity of component partitioning and pH variation in particles, the water probe may provide a new perspective on the underlying mechanisms of aerosol aging and aerosol-cloud interaction.

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INTRODUCTION: Heat stress poses a severe threat to the growth and production of soybean (Glycine max). Brassinosteroids (BRs) actively participate in plant responses to abiotic stresses, however, the role of BR signaling pathway genes in response to heat stress in soybean remains poorly understood. OBJECTIVES: In this study, we investigate the regulatory mechanisms of GmBSK1 and GmBES1.5 in response to heat stress and the physiological characteristics and yield performance under heat stress conditions. METHODS: Transgenic technology and CRISPR/Cas9 technology were used to generated GmBSK1-OE, GmBES1.5-OE and gmbsk1 transgenic soybean plants, and transcriptome analysis, LUC activity assay and EMSA assay were carried out to elucidate the potential molecular mechanism underlying GmBSK1-GmBES1.5-mediated heat stress tolerance in soybean. RESULTS: CRISPR/Cas9-generated gmbsk1 knockout mutants exhibited increased sensitivity to heat stress due to a reduction in their ability to scavenge reactive oxygen species (ROS). The expression of GmBES1.5 was up-regulated in GmBSK1-OE plants under heat stress conditions, and it directly binds to the E-box motif present in the promoters of abiotic stress-related genes, thereby enhancing heat stress tolerance in soybean plants. Furthermore, we identified an interaction between GmGSK1 and GmBES1.5, while GmGSK1 inhibits the transcriptional activity of GmBES1.5. Interestingly, the interaction between GmBSK1 and GmGSK1 promotes the localization of GmGSK1 to the plasma membrane and releases the transcriptional activity of GmBES1.5. CONCLUSION: Our findings suggest that both GmBSK1 and GmBES1.5 play crucial roles in conferring heat stress tolerance, highlighting a potential strategy for breeding heat-tolerant soybean crops involving the regulatory module consisting of GmBSK1-GmGSK1-GmBES1.5.

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Global warming and eutrophication contribute to frequent occurrences of toxic algal blooms in freshwater systems globally, while there is a limited understanding of their combined impacts on toxin-producing algal species under interspecific competitions. This study investigated the influences of elevated temperatures, lights, nutrient enrichments and interspecific interactions on growth and microcystin (MC) productions of Microcystis aeruginosa in laboratory condition. Our results indicated that elevated temperatures and higher nutrient levels significantly boosted biomass and specific growth rates of Microcystis aeruginosa, which maintained a competitive edge over Chlorella sp. Specifically, with phosphorus levels between 0.10 and 0.70 mg P L-1, the growth rate of Microcystis aeruginosa in mixed cultures increased by 23 %-52 % compared to mono-cultures, while the growth rate of Chlorella sp. shifted from positive in mono-cultures to negative in mixed cultures. Redundancy and variance partition analyses suggested that Chlorella sp. stimulate MC production in Microcystis aeruginosa and nutrient levels outshine temperature for toxin productions during competition. Lotka‒Volterra model revealed a positive correlation between the intensities of competitions and MC concentration. Our findings indicate that future algal bloom mitigation strategies should consider combined influence of temperature, nutrients, and interspecific competition due to their synergistic effects on MC productions.

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Chemotherapy is the main clinical treatment for ovarian cancer, but still faces challenges of low drug targeting efficiency and insufficient drug permeability. Drug-loaded nanoparticle collectives, which are actuated by magnetic field, could be targeted to a designated location and achieve targeted drug delivery. In this work, we report a strategy that utilizes magnetic mesoporous silica nanoparticles loaded with cis-diaminodichloroplatinum (Fe3O4@SiO2-CDDP) for targeted delivery of chemotherapeutic drugs and enhances penetration into deep tumors. The Fe3O4@SiO2-CDDP collectives actively moved to the target tumor site, and this movement was regulated by a magnetic actuation system. Under the action of a torque-force hybrid magnetic field (TFMF), Fe3O4@SiO2-CDDP could further penetrate into the interior of tumors and achieve pH-responsive drug release in the tumor environment. The feasibility of this strategy was verified in three-dimensional cell spheres in vitro and in a tumor-bearing mouse model in vivo. This magnetically actuated nanoparticle collectives enhanced drug penetration strategy provides a new paradigm for targeted drug delivery and potentiated tumor therapy.

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[This corrects the article DOI: 10.1371/journal.pone.0301909.].

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Low-carbon pilot city (LCPC) plays a pivotal role in stimulating green innovation among enterprises. However, relying solely on policy often proves less effective, necessitating support from financial development. Yet, current research frequently overlooks the impact of financial development on LCPC policy. Drawing on economic, management, and organizational psychology theories, we investigate the influence of the financial development level on enterprise green innovation in LCPC, utilizing data from listed companies between 2010 and 2018. The main finding is that LCPC facilitates institutional-level green innovation. Concurrently, financial development augments the effectiveness of LCPC policy, further expediting green innovation activities among enterprises in these pilot cities. Heterogeneity analyses reveal that financial development significantly promotes green innovation, particularly among state-owned enterprises, those with myopic management, non-high technology industries, and businesses in the southern region within LCPC. Mechanism tests identify enterprises' financing constraints and R&D investment levels as key pathways through which financial development fosters green economic development in LCPC. This study provides micro-level evidence from China elucidating the effects of environmental policies and offers practical implications for the low-carbon transformation of the manufacturing sector amid peak emissions and carbon-neutral targets. Additionally, it provides valuable guidance for other emerging economies seeking enhanced resource and environmental protection through the implementation of energy-saving and emission-reduction fiscal policy.

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OBJECTIVE: The study was designed to examine the effects of simultaneous combination of aerobic exercise and video game training on executive functions (EFs) and brain functional connectivity in older adults. DESIGN: A four-armed, quasi-experimental study. SETTING AND PARTICIPANTS: Community-dwelling adults aged 55 years and older. METHODS: A total of 97 older adults were divided into one of four groups: aerobic exercise (AE), video game (VG), combined intervention (CI), and passive control (PC). Participants in intervention groups received 32 sessions of training over a 4-month period at a frequency of twice a week. EFs was evaluated using a composite score derived from a battery of neuropsychological tests. The Montreal Cognitive Assessment (MoCA) was employed to evaluate overall cognitive function, while the 6-Minute Walking Test (6MWT) was utilized to gauge physical function. Additionally, the functional connectivity (FC) of the frontal-parietal networks (FPN) was examined as a neural indicator of cognitive processing and connectivity changes. RESULTS: In terms of EFs, both VG and CI groups demonstrated improvement following the intervention. This improvement was particularly pronounced in the CI group, with a large effect size (Hedge's g = 0.83), while the VG group showed a medium effect size (Hedge's g = 0.56). A significant increase in MoCA scores was also observed in both the VG and CI groups, whereas a significant increase in 6MWT scores was observed in the AE and CI groups. Although there were no group-level changes observed in FC of the FPN, we found that changes in FC was behaviorally relevant as increased FC was associated with greater improvement in EFs. CONCLUSION: The study offers preliminary evidence that both video game training and combined intervention could enhance EFs in older adults. Simultaneous combined intervention may hold greater potential for facilitating EFs gains. The initial evidence for correlated changes in brain connectivity and EFs provides new insights into understanding the neural basis underlying the training gains.

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BACKGROUND: Genetic disorders significantly affect patients in neonatal intensive care units, where establishing a diagnosis can be challenging through routine tests and supplementary examinations. Whole-exome sequencing offers a molecular-based approach for diagnosing genetic disorders. This study aimed to assess the importance of whole-exome sequencing for neonates in intensive care through a retrospective observational study within a Chinese cohort. METHODS: We gathered data from neonatal patients at Tianjin Children's Hospital between January 2018 and April 2021. These patients presented with acute illnesses and were suspected of having genetic disorders, which were investigated using whole-exome sequencing. Our retrospective analysis covered clinical data, genetic findings, and the correlation between phenotypes and genetic variations. RESULTS: The study included 121 neonates. Disorders affected multiple organs or systems, predominantly the metabolic, neurological, and endocrine systems. The detection rate for whole-exome sequencing was 52.9% (64 out of 121 patients), identifying 84 pathogenic or likely pathogenic genetic variants in 64 neonates. These included 13 copy number variations and 71 single-nucleotide variants. The most frequent inheritance pattern was autosomal recessive (57.8%, 37 out of 64), followed by autosomal dominant (29.7%, 19 out of 64). In total, 40 diseases were identified through whole-exome sequencing. CONCLUSION: This study underscores the value and clinical utility of whole-exome sequencing as a primary diagnostic tool for neonates in intensive care units with suspected genetic disorders. Whole-exome sequencing not only aids in diagnosis but also offers significant benefits to patients and their families by providing clarity in uncertain diagnostic situations.

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RATIONALE AND OBJECTIVES: The proliferative nature of hepatocellular carcinoma (HCC) is closely related to early recurrence following radical resection. This study develops and validates a deep learning (DL) prediction model to distinguish between proliferative and non-proliferative HCCs using dynamic contrast-enhanced MRI (DCE-MRI), aiming to refine preoperative assessments and optimize treatment strategies by assessing early recurrence risk. MATERIALS AND METHODS: In this retrospective study, 355 HCC patients from two Chinese medical centers (April 2018-February 2023) who underwent radical resection were included. Patient data were collected from medical records, imaging databases, and pathology reports. The cohort was divided into a training set (n = 251), an internal test set (n = 62), and external test sets (n = 42). A DL model was developed using DCE-MRI images of primary tumors. Clinical and radiological models were generated from their respective features, and fusion strategies were employed for combined model development. The discriminative abilities of the clinical, radiological, DL, and combined models were extensively analyzed. The performances of these models were evaluated against pathological diagnoses, with independent and fusion DL-based models validated for clinical utility in predicting early recurrence. RESULTS: The DL model, using DCE-MRI, outperformed clinical and radiological feature-based models in predicting proliferative HCC. The area under the curve (AUC) for the DL model was 0.98, 0.89, and 0.83 in the training, internal validation, and external validation sets, respectively. The AUCs for the combined DL and clinical feature models were 0.99, 0.86, and 0.83 in these sets, while the AUCs for the combined DL, clinical, and radiological model were 0.99, 0.87, and 0.8, respectively. Among models predicting early recurrence, the DL plus clinical features model showed superior performance. CONCLUSION: The DL-based DCE-MRI model demonstrated robust performance in predicting proliferative HCC and stratifying patient risk for early postoperative recurrence. As a non-invasive tool, it shows promise in enhancing decision-making for individualized HCC management strategies.

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Testing is more beneficial for memory retention than restudying the same content. However, the effect of the initial encoding method on the testing effect remains unclear. In this study, a classical testing effect paradigm was employed, along with event-related potentials (ERP), to investigate the electrophysiological processes underlying the effect of enactment encoding on the testing effect. Participants were randomly assigned to the Self-Performed Test (SPT) or Verbalized Test (VT) groups. Both groups underwent three stages: an initial encoding phase, an initial test phase (comprising a source memory task and a restudy task), and a final test phase. During the initial encoding phase, the SPT group encoded action phrases through enactment, while the VT group encoded information through reading. During the initial test phase, the SPT group exhibited superior recognition performance in item memory compared with the VT group. Both groups exhibited significant parietal old/new effects in the source memory task, with only the SPT group displaying parietal positivity during the restudy task. During the final test phase, the behavioral testing effect was exclusively observed in the VT group. Furthermore, the VT group displayed a more pronounced parietal positivity in the test condition compared to the restudy condition, while the parietal positivity between the two conditions was comparable in the SPT group. In summary, the absence of a final behavioral testing effect in the SPT group may be attributed to both enactment and testing primarily enhancing memory performance through recollection-based retrieval, as indicated by the parietal positivity. Consequently, the initial enactment encoding method leaves limited scope for further improvements through subsequent testing. These findings suggest that initial enactment encoding, and subsequent testing may be redundant in improving episodic memory performance.

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Uptake of methylmercury (MeHg), a potent neurotoxin, by phytoplankton is a major concern due to its role as the primary pathway for MeHg entry into aquatic food webs, thereby posing a significant risk to human health. While it is widely believed that the MeHg uptake by plankton is negatively correlated with the concentrations of dissolved organic matter (DOM) in the water, ongoing debates continue regarding the specific components of DOM that exerts the dominant influence on this process. In this study, we employed a widely-used resin fractionation approach to separate and classify DOM derived from algae (AOM) and natural rivers (NOM) into distinct components: strongly hydrophobic, weakly hydrophobic, and hydrophilic fractions. We conduct a comparative analysis of different DOM components using a combination of spectroscopy and mass spectrometry techniques, aiming to identify their impact on MeHg uptake by Microcystis elabens, a prevalent alga in freshwater environments. We found that the hydrophobic components had exhibited more pronounced spectral characteristics associated with the protein structures while protein-like compounds between hydrophobic and hydrophilic components displayed significant variations in both distributions and the values of m/z (mass-to-charge ratio) of the molecules. Regardless of DOM sources, the low-proportion hydrophobic components usually dominated inhibition of MeHg uptake by Microcystis elabens. Results inferred from the correlation analysis suggest that the uptake of MeHg by the phytoplankton was most strongly and negatively correlated with the presence of protein-like components. Our findings underscore the importance of considering the diverse impacts of different DOM fractions on inhibition of phytoplankton MeHg uptake. This information should be considered in future assessments and modeling endeavors aimed at understanding and predicting risks associated with aquatic Hg contamination.

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Ovarian cancer presents a substantial challenge due to its high mortality and recurrence rates among gynecological tumors. Existing clinical chemotherapy treatments are notably limited by drug resistance and systemic toxic side effects caused by off target drugs. Sonodynamic therapy (SDT) has emerged as a promising approach in cancer treatment, motivating researchers to explore synergistic combinations with other therapies for enhanced efficacy. In this study, we developed magnetic sonodynamic nanorobot (Fe3O4@SiO2-Ce6, FSC) by applying a SiO2 coating onto Fe3O4 nanoparticle, followed by coupling with the sonosensitizer Ce6. The magnetic FSC nanorobot collectives could gather at fixed point and actively move to target site regulated by magnetic field. In vitro experiments revealed that the magnetic FSC nanorobot collectives enabled directional navigation to the tumor cell area under guidance. Furthermore, under low-intensity ultrasonic stimulation, FSC nanorobot collectives mediated sonodynamic therapy exhibited remarkable anti-tumor performance. These findings suggest that magnetically actuated sonodynamic nanorobot collectives hold promising potential for application in target cancer therapy.

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In the field of pathology, the scarcity of certain diseases and the difficulty of annotating images hinder the development of large, high-quality datasets, which in turn affects the advancement of deep learning-assisted diagnostics. Few-shot learning has demonstrated unique advantages in modeling tasks with limited data, yet explorations of this method in the field of pathology remain in the early stages. To address this issue, we present a dual-channel prototype network (DCPN), a novel few-shot learning approach for efficiently classifying pathology images with limited data. The DCPN leverages self-supervised learning to extend the pyramid vision transformer (PVT) to few-shot classification tasks and combines it with a convolutional neural network to construct a dual-channel network for extracting multi-scale, high-precision pathological features, thereby substantially enhancing the generalizability of prototype representations. Additionally, we design a soft voting classifier based on multi-scale features to further augment the discriminative power of the model in complex pathology image classification tasks. We constructed three few-shot classification tasks with varying degrees of domain shift using three publicly available pathological datasets-CRCTP, NCTCRC, and LC25000-to emulate real-world clinical scenarios. The results demonstrated that the DCPN outperformed the prototypical network across all metrics, achieving the highest accuracies in same-domain tasks-70.86% for 1-shot, 82.57% for 5-shot, and 85.2% for 10-shot setups-corresponding to improvements of 5.51%, 5.72%, and 6.81%, respectively, over the prototypical network. Notably, in the same-domain 10-shot setting, the accuracy of the DCPN (85.2%) surpassed that of the PVT-based supervised learning model (85.15%), confirming its potential to diagnose rare diseases within few-shot learning frameworks.

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BACKGROUND: Phosphoserine aminotransferase deficiency (PSATD) is an autosomal recessive disorder associated with hypertonia, psychomotor retardation, and acquired microcephaly. Patients with PSATD have low concentrations of serine in plasma and cerebrospinal fluid. METHODS: We reported a 2-year-old female child with developmental delay, dyskinesia, and microcephaly. LC-MS/MS was used to detect amino acid concentration in the blood and whole-exome sequencing (WES) was used to identify the variants. PolyPhen-2 web server and PyMol were used to predict the pathogenicity and changes in the 3D model molecular structure of protein caused by variants. RESULTS: WES demonstrated compound heterozygous variants in PSAT1, which is associated with PSATD, with a paternal likely pathogenic variant (c.235G>A, Gly79Arg) and a maternal likely pathogenic variant (c.43G>C, Ala15Pro). Reduced serine concentration in LC-MS/MS further confirmed the diagnosis of PSATD in this patient. CONCLUSIONS: Our findings demonstrate the importance of WES combined with LC-MS/MS reanalysis in the diagnosis of genetic diseases and expand the PSAT1 variant spectrum in PSATD. Moreover, we summarize all the cases caused by PSAT1 variants in the literature. This case provides a vital reference for the diagnosis of future cases.

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A new type of embedded composite material health monitoring nano-sensor is designed to ensure that the unique material advantages of nanofillers can be maximized. The carbon nanotubes (CNTs)/polysulfone (PSF)/polyimide (PI) thin film sensor in this paper is obtained by the self-assembly of a PSF/PI asymmetric porous membrane which is prepared by a phase inversion method through vacuum filtration of SWCNTs. It is a new structure for a practical CNT sensor that can take into account both 'composite health monitoring and damage warning' and 'composite mechanical enhancement'. The new structure of the CNTs/PSF/PI film sensor is divided into two parts. The upper part consists of small-aperture finger-like holes filled with SWCNTs (the SWCNT content is 0.0127 mg cm-2). The lower part consists of large-aperture cavities conducive to resin infiltration, which enhance the interface bonding force between the sensor and the composite material. This unique structure allows the CNTs/PSF/PI film sensor to change the influence of the embedded sensor from 'introducing defects' to 'local enhancement', and the mechanical strength of the enhanced specimen can reach up to 1.68 times that of the original specimen, and the service interval can reach 2.01 times that of the original specimen. In addition, the CNTs/PSF/PI film sensor also has good sensitivity (GF = 2.54) and extremely high linearity (R2 = 0.9995), and has excellent follow-up and interface bonding ability. It can also maintain excellent fatigue resistance and stability over 46 500 vibration cycles, which provides new research ideas and research methods for the field of composite-life monitoring sensors.

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Arsenic (As)-contaminated soil poses great health risk to human mostly through inadvertent oral exposure. We investigated CaAl-layered double hydroxide (CaAl-LDH), a promising immobilising agent, for the remediation of As-contaminated Chinese soils. The effects on specific soil properties and As fractionation were analyzed, and changes in the health risk of soil As were accurately assessed by means of advanced in vivo mice model and in vitro PBET-SHIME model. Results showed that the application of CaAl-LDH significantly increased soil pH and concentration of Fe and Al oxides, and effectively converted active As fractions into the most stable residual fraction, guaranteeing long-term remediation stability. Based on in vivo test, As relative bioavailability was significantly reduced by 37.75%. Based on in vitro test, As bioaccessibility in small intestinal and colon phases was significantly reduced by 25.65% and 28.57%, respectively. Furthermore, As metabolism (reduction and methylation) by the gut microbiota inhabiting colon was clearly observed. After immobilisation with CaAl-LDH, the concentration of bioaccessible As(Ⅴ) in the colon fluid was significantly reduced by 61.91%, and organic As (least toxic MMA(V) and DMA(V)) became the main species, which further reduced the health risk of soil As. In summary, CaAl-LDH proved to be a feasible option for immobilisation remediation of As-contaminated soils, and considerable progress was made in relevant health risk assessment.

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Tris (1,3-dichloro-2-propyl) phosphate (TDCPP) is a growing concern and may be a potential risk to marine environmental health due to its widespread usage and distribution. However, the toxic effects of TDCPP on cardiac development in marine fish have not been reported. In this study, Oryzias melastigma embryos were exposed to TDCPP at doses of 0, 0.04, 0.4, 4 and 40 µg/L from early embryogenesis to 10 days postfertilization (dpf). Then, the heart rate and sinus venosus-bulbus arteriosus (SV-BA) distance of the exposed embryos were measured at 5, 6, 8 and 10 dpf. Furthermore, alterations in the mRNA levels of the genes encoding cyclooxygenase-2 (COX-2), bone morphogenetic protein 4 (BMP4), fibroblast growth factor 8 (FGF8), and GATA-binding protein 4 (GATA4) were evaluated at 5, 6, 8 and 10 dpf. We found that the heart rate significantly increased in all TDCPP exposure groups at 10 dpf. The SV-BA distance significantly decreased in all TDCPP exposure groups at all developmental stages (except for the 0.4 µg/L group at 5 dpf and the 4 µg/L group at 10 dpf). The mRNA expression of COX-2 was downregulated at 5 dpf, BMP4 was downregulated at 5 and 6 dpf, FGF8 was downregulated at 5, 6 and 8 dpf, GATA4 was downregulated at 8 dpf, and GATA4 was upregulated at 10 dpf. These results indicate that the changes in heart rate and SV-BA distance might be accompanied by disturbances in the four genes involved in cardiac development. Our findings will help to illustrate the possible cardiac toxic effects of marine fish exposed to TDCPP.

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Whether coexisting microplastics (MPs) affect the ecological and health risks of cadmium (Cd) in soils is a cutting-edge scientific issue. In this study, four typical Chinese soils were prepared as artificially Cd-contaminated soils with/without aged polystyrene (PS). TCLP and in vitro PBET model were used to determine the leachability (ecological risk) and oral bioaccessibility (human health risk) of soil Cd. The mechanisms by which MPs influence soil Cd were discussed from direct and indirect perspectives. Results showed that there was no significant difference in the leachability of soil Cd with/without aged PS. Additionally, aged PS led to a significant decrease in the bioaccessibility of soil Cd in gastric phase, but not in small intestinal phase. The increase in surface roughness and the new characteristic peaks (e.g., Si-O-Si) of aged PS directly accounted for the change in Cd bioaccessibility. The change in organic matter content indirectly accounted for the exceptional increase in Cd bioaccessibility of black soil with aged PS in small intestinal phase. Furthermore, the changes in cation exchange capacity and Cd mobility factor caused by aged PS explained the change in Cd leachability. These results contribute to a deeper understanding about environmental and public health in complicated emerging scenarios.

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BACKGROUND: The effects of a solitary neonatal exposure to anesthesia plus surgery (anesthesia/surgery) on cognitive function and the underlying mechanism in developing brains remains largely undetermined. We, therefore, set out to investigate the impact of single exposure to anesthesia/surgery in neonatal mice. METHODS: Six-day-old male and female mice received abdominal surgery under 3% sevoflurane plus 50% oxygen for 2 h. The new object recognition (NOR) and Morris water maze (MWM) were used to evaluate cognitive function in young adult mice. Western blot, ELISA and RT-PCR were used to measure levels of NR2B and IL-6 in medial prefrontal cortex and IL-6 in blood of the mice. We employed NR2B siRNA and IL-6 antibody in the interaction studies. RESULTS: The anesthesia/surgery decreased the ratio of novel time to novel plus familiar time in NOR and the number of platform crossings, but not escape latency, in MWM compared to sham condition. The mice in anesthesia/surgery group had increased NR2B expression in medial prefrontal cortex, and IL-6 amounts in blood and medial prefrontal cortex. Local injection of NR2B siRNA in medial prefrontal cortex alleviated the anesthesia/surgery-induced cognitive impairment. IL-6 antibody mitigated the anesthesia/surgery-induced upregulation of NR2B and cognitive impairment in young adult mice. CONCLUSIONS: These results suggest that a single neonatal exposure to anesthesia/surgery causes impairment of memory, but not learning, in young adult mice through IL-6-regulated increases in NR2B concentrations in medial prefrontal cortex, highlighting the need for further research on the underlying mechanisms of anesthesia/surgery's impact on cognitive function in developing brains.

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The development of bioinspired gradient hydrogels with self-sensing actuated capabilities for remote interaction with soft-hard robots remains a challenging endeavor. Here, we propose a novel multifunctional self-sensing actuated gradient hydrogel that combines ultrafast actuation and high sensitivity for remote interaction with robotic hand. The gradient network structure, achieved through a wettability difference method involving the rapid precipitation of MoO2 nanosheets, introduces hydrophilic disparities between two sides within hydrogel. This distinctive approach bestows the hydrogel with ultrafast thermo-responsive actuation (21° s-1) and enhanced photothermal efficiency (increase by 3.7 °C s-1 under 808 nm near-infrared). Moreover, the local cross-linking of sodium alginate with Ca2+ endows the hydrogel with programmable deformability and information display capabilities. Additionally, the hydrogel exhibits high sensitivity (gauge factor 3.94 within a wide strain range of 600%), fast response times (140 ms) and good cycling stability. Leveraging these exceptional properties, we incorporate the hydrogel into various soft actuators, including soft gripper, artificial iris, and bioinspired jellyfish, as well as wearable electronics capable of precise human motion and physiological signal detection. Furthermore, through the synergistic combination of remarkable actuation and sensitivity, we realize a self-sensing touch bioinspired tongue. Notably, by employing quantitative analysis of actuation-sensing, we realize remote interaction between soft-hard robot via the Internet of Things. The multifunctional self-sensing actuated gradient hydrogel presented in this study provides a new insight for advanced somatosensory materials, self-feedback intelligent soft robots and human-machine interactions.