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Threshold switching (TS) memristor with a simple structure and high biomimetic offers a more promising way to implement an efficient artificial neuron than traditional methods. To accommodate the complex environments in practical applications, previous memristor-based neurons typically incorporate auxiliary circuits to ensure tunability within circuits. However, this addition not only heightens the design complexity but also reduces the efficiency. In this work, we investigate the conduction process under different thresholds in an NbOx-based memristor and further demonstrate its potential merits in human face recognition. The negative threshold voltage of the device can be linearly modulated by positive stimuli. The conduction mechanisms under different threshold states are systematically investigated by experiments and theoretical analysis, showing that the defects concentration controlled by the electrical field is attributed to the threshold modulation. The revealed mechanism is instructive for device optimization, offering an oxygen-related fabrication method. Based on such a device, we construct a tunable spiking neuron whose threshold can be modulated by only one preoperation on the neuron without other burdensome units. By modulating the threshold based on the light intensities—a lower threshold for the bright condition and a higher threshold for the dark condition—the temporal features of the neuron outputs can be maintained at a normal condition to ensure the correct recognition under different environmental luminance. The function of the proposed tunable neuron is further evaluated in a network for human face recognition. The network finally reaches a 93.25% accuracy with tunable threshold neurons, significantly surpassing the 71.87% with fixed-threshold neurons.

Graph contrastive learning (GCL) has emerged as an effective tool to learn representations for whole graphs in the absence of labels. The key idea is to maximize the agreement between two augmented views of each graph via data augmentation. Existing GCL models mainly focus on applying identical augmentation strategies for all graphs within a given scenario. However, real-world graphs are often not monomorphic but abstractions of diverse natures. Even within the same scenario (e.g., macromolecules and online communities), different graphs might need diverse augmentations to perform effective GCL. Thus, blindly augmenting all graphs without considering their individual characteristics may undermine the performance of GCL arts. However, it is non-trivial to achieve personalized allocation for all graphs since the search space is exponential to the number of graphs. To bridge the gap, we propose the first principled framework, termed as Graph contrastive learning with Personalized Augmentation (GPA). It advances conventional GCL by allowing each graph to choose its own suitable augmentation operations. To cope with the huge search space, we design a tailored augmentation selector by converting the discrete space into a continuous one, which is a plug-and-play module and can be effectively trained with downstream GCL models end to end. Extensive experiments across 10 benchmark datasets demonstrate the superiority of GPA against state-of-the-art competitors. Moreover, by visualizing the learned augmentation distributions across different types of datasets, we show that GPA can effectively identify the most suitable augmentations for each graph based on its characteristics.

Background Multi-organ metastases represent a substantial life-threatening risk for breast cancer (BC) patients. Nonetheless, the current dearth of assessment tools for patients with multi-organ metastatic BC adversely impacts their evaluation.Methods We conducted a retrospective analysis of BC patients with multi-organ metastases using data from the SEER database from 2010 to 2019. The patients were randomly allocated into a training cohort and a validation cohort in a 7:3 ratio. Univariate COX regression analysis, the LASSO, and multivariate Cox regression analyses were performed to identify independent prognostic factors in the training set. Based on these factors, a nomogram was constructed to estimate overall survival (OS) probability for BC patients with multi-organ metastases. The performance of the nomogram was evaluated using C-indexes, ROC curves, calibration curves, decision curve analysis (DCA) curves, and the risk classification system for validation.Results A total of 3626 BC patients with multi-organ metastases were included in the study, with 2538 patients in the training cohort and 1088 patients in the validation cohort. Age, grade, metastasis location, surgery, chemotherapy, and subtype were identified as significant independent prognostic factors for OS in BC patients with multi-organ metastases. A nomogram for predicting 1-year, 3-year, and 5-year OS was constructed. The evaluation metrics, including C-indexes, ROC curves, calibration curves, and DCA curves, demonstrated the excellent predictive performance of the nomogram. Additionally, the risk grouping system effectively stratified BC patients with multi-organ metastases into distinct prognostic categories.Conclusion The developed nomogram showed high accuracy in predicting the survival probability of BC patients with multi-organ metastases, providing valuable information for patient counseling and treatment decision making.

Graft-versus-host disease (GVHD), an immunological disorder that arises from donor T cell activation through recognition of host alloantigens, is the major limitation in the application of allogeneic hematopoietic stem cell transplantation (allo-HSCT). Traditional immunosuppressive agents can relieve GVHD, but they induce serious side effects. It is highly required to explore alternative therapeutic strategy. Human amniotic epithelial stem cells (hAESCs) were recently considered as an ideal source for cell therapy with special immune regulatory property. In this study, we evaluated the therapeutic role of hAESCs in the treatment of GVHD, based on our previous developed cGMP-grade hAESCs product. Humanized mouse model of acute GVHD (aGVHD) was established by injection of huPBMCs via the tail vein. For prevention or treatment of aGVHD, hAESCs were injected to the mice on day -1 or on day 7 post-PBMC infusion, respectively. We showed that hAESCs infusion significantly alleviated the disease phenotype, increased the survival rate of aGVHD mice, and ameliorated pathological injuries in aGVHD target organs. We demonstrated that hAESCs directly induced CD4+T cell polarization, in which Th1 and Th17 subsets were downregulated, and Treg subset was elevated. Correspondingly, the levels of a series of pro-inflammatory cytokines were reduced while the levels of the anti-inflammatory cytokines were upregulated in the presence of hAESCs. We found that hAESCs regulated CD4+subset polarization in a paracrine mode, in which TGFβ and PGE2 were selectively secreted to mediate Treg elevation and Th1/Th17 inhibition, respectively. In addition, transplanted hAESCs preserved the graft-versus-leukemia (GVL) effect by inhibiting leukemia cell growth. More intriguingly, hAESCs infusion in HSCT patients displayed potential anti-GVHD effect with no safety concerns and confirmed the immunoregulatory mechanisms in the preclinical study. We conclude that hAESCs infusion is a promising therapeutic strategy for post-HSCT GVHD without compromising the GVL effect. The clinical trial was registered at www.clinicaltrials.govas #NCT03764228.

The neuromorphic vision system that utilizes spikes as information carriers is crucial for the formation of spiking neural networks. Here, we present a bioinspired flexible artificial spiking photoreceptor (ASP), which is realized by using a single VO2Mott memristor that can simultaneously sense and encode the stimulus light into spikes. The ASP has high spike-encoded photosensitivity and ultrawide photosensing range (405–808 nm) with good endurance (>7 × 107) and high flexibility (bending radius ∼5 mm). Then, we put forward an all-spike electronic retina architecture that comprises one layer of ASPs and one layer of artificial optical nerves (AONs) to process the spike information. Each AON consists of a single Mott memristor connected in series with a neuro-transistor that is a multiple-input floating-gate MOS transistor. Simulation results demonstrate that the all-spike electronic retina can successfully segment images with high Shannon entropy, thus laying the foundation for the development of a spike-based neuromorphic vision system.

Wave-induced harbour resonance is numerically investigated inside a harbour with lateral cavities. The theoretical solutions for the amplification parameter are compared with the simulated results under varying dimensionless wave numbers in order to verify the simulation model in a rectangular harbour at a constant depth. The results indicate that the numerical model can correctly calculate the natural frequency and the natural wave height. A range of calculations are performed for harbour resonance with one pair of lateral cavities, two pairs of lateral cavities and three pairs of lateral cavities, respectively. The simulated results indicate that the amplitude of the amplification parameter decreases both at the primary natural oscillation and the secondary natural oscillation, as the number of lateral cavities increases. The dimensionless wave number reduces as the number of lateral cavities increases both at the primary natural oscillation and the secondary natural oscillation as well.

Aggregation-induced emission luminogens (AIEgens) that respond to mechanical force are increasingly used as force probes, memory devices, and advanced security systems. Most of the known mechanisms to modulate mechanoresponsive AIEgens have been based on changes in aggregation states, involving only physical alterations. Instances that employ covalent bond cleavage are still rare. We have developed a novel mechanochemical uncaging strategy to unveil AIEgens with diverse emission characteristics using engineered norborn-2-en-7-one (NEO) mechanophores. These NEOmechanophores were covalently integrated into polymer molecules and activated in both the solution and solid states. This activation resulted in highly tunable fluorescence upon immobilization through solidification or aggregation, producing blue, green, yellow, and orange-red emissions. By designing the caged and uncaged forms as donor–acceptor pairs for Förster resonance energy transfer (FRET), we achieved multicolor mechanofluorescence, effectively broadening the color spectrum to include white emission. Additionally, we computationally explored the electronic structures of activated NEOs, providing insights into the observed regiochemical effects of the substituents. This understanding, together with the novel luminogenic characteristics of the caged and activated species, provides a highly tunable reporter that traces progress with continuous color evolution. This advancement paves the way for future applications of mechanoresponsive materials in areas like damage detection and bioimaging.

Perovskite quantum dots (PQDs) have demonstrated great promise in bioimaging applications owing to their outstanding photophysical properties. Nonetheless, their practicality is seriously limited by the instability of PQDs against moisture. Here we develop a post-synthetic ligand exchange strategy to construct silica-coated PQD (PQD@SiO2) nanocrystals, which results in the simultaneous improvement of photoluminescence efficiency and moisture stability. More importantly, compared to the classical in-situligand exchange method of fabricating PQD@SiO2, the issues of chemical etching and resultant photoluminescence degradation are judiciously overcome. Employing the proposed PQD@SiO2, we showcase their robust usefulness in labeling chlorella, paving the way for PQD-based in-vivophotoluminescence bioimaging methodology.

A cooperative Rh(II)/Pd(0) dual-catalysis strategy that enabled divergent reactions of α-diazo 1,3-dicarbonyl compounds with allylic carbonates involving ketene versus carbene intermediates is described. The efficient synthesis of α-quaternary allylated β-keto-esters was accomplished by the Rh(II)/Pd(0) dual-catalysis allylic alkylation of α-diazo 1,3-dicarbonyl compounds. Alternatively, an unprecedented (1+4) annulation of α-diazo 1,3-dicarbonyl compounds with 2-(hydroxymethyl)allyl carbonates via Rh(II)/Pd(0) dual catalysis was also successfully developed, affording a wide variety of α-quaternary tetrahydrofurans in good to high yields.

Pepper (Piper nigrumL.) is a widely used spice plant known for its fruits and roots, which serve as flavor enhancers in culinary applications and hold significant economic value. Despite the popularity of pepper fruits, their roots remain relatively understudied, with limited research conducted on their bioactive components. This study focused on discovering and separating the primary bioactive amide alkaloids found in pepper roots. The process involved using the antioxidant activity of crude fractions and the Global Natural Products Social Molecular Networking analysis platform. The process led to the discovery of 23 previously unknown hydroxyl-amide alkaloids. Notably, compounds 11, 12, and 14showed excellent antioxidant activity, while compound 11exhibited significant inhibitory effects on mushroom tyrosinase. Theoretical exploration of enzyme−ligand interactions was conducted through molecular docking and molecular dynamics simulation. The findings of this study highlight the potential of hydroxyl-amide alkaloids as antioxidant products and natural food preservatives in the pharmaceutical and food cosmetic industries.

Sulfur hexafluoride (SF6) is widely used as an insulating gas, being an etchant and contrast agent in the electrical, semiconductor, and medical industries. However, due to its long lifetime and high global warming potential in the atmosphere, SF6must be carefully handled to prevent leakage during production and usage. Herein, we report a sod-net metal-azolate framework (MAF) named MAF-stu-111, which decorates methyl and aldehyde groups in the porous windows, showing high adsorption affinity for SF6at low pressure. Stability tests, gas adsorption, and breakthrough experiments demonstrated that MAF-stu-111 possesses excellent water and chemical stability, fully reversible SF6uptake, high SF6/N2separation selectivity (10:90, 285.2), good reusability, and high SF6recovery purity (99.03%). Theoretical calculations revealed that hydrogen atoms of methyl and aldehyde groups can form multiple hydrogen bonds with SF6molecules, which ensure that SF6molecules are firmly held within the MAF-stu-111 framework, playing a key role in the selective separation of SF6/N2.

For a highly efficient recycling of a wastewater containing a high concentration of MgCl2, Al(III) and P507 were scheduled to be removed in advance. In this study, the in-situ removal of Al(III) and P507 from a high concentration MgCl2solution at different pH values and Al/P molar ratios was investigated. The results showed that P507 formed organic complexes of Alx(OH)z+y-P507 at pH of 2.0−4.0. At pH of 4.0−5.0, Al(III) precipitated and transferred into Al(OH)3with a flocculent amorphous morphology. Active sites on the Al(OH)3surface enhanced the removal efficiency of P507. At pH of 6.0−6.5, Al(III) and Mg(II) formed layered crystalline Al(OH)3and MgAl2(OH)8with small pore channels and fewer active sites, resulting in a reduced removal efficiency of P507. When the Al/P molar ratio exceeded 13 and the pH was between 4.0 and 5.0, the removal rates of both Al(III) and P507 were higher than 98%, while the concentration loss of Mg(II) was only 0.2%−0.9%.

The effect of backwashing on pollutant removal performance and microbial communities in the denitrification biofilter (DNBF) is a current research blind spot. Therefore, water supply sludge biofilters were constructed to investigate the effects of different backwashing conditions on nitrogen (N) and phosphorus (P) removal, and the microbial community structure and metabolic pathways were analyzed. Studies indicated that backwashing dislodged the biofilm and reduces pollutant removal. As the biofilm gradually rebuilt, the DNBF operation returned to normal. Chemical oxygen demand (COD), total nitrogen (TN) and total phosphorus (TP) were removed at 60 %, 100 %, and 50 % after backwashing for 1 h with a 10 min air flush and 5 min water flush. Proteobacteria, Bacteroidetesand Firmicuteswere easily enriched in the biofilm to act on pollutants during the process. Meanwhile, backwashing promoted Brevundimonas, while prolonged backwashing reduced the abundance of Chryseobacterium, Acinetobacterand Hyphomicrobium. This process affected microbial interactions and metabolism being the predominant functional classification. This study provides ideas for backwashing for pollutant removal in the DNBF.

We present a multiregion surface integral equation (MR-SIE) solution for the analysis of electromagnetic (EM) scattering from an aircraft with plasma sheath. The MR-SIE offers advantages over volume-meshed methods in terms of lower dimensionality of unknowns but requires homogeneity within each region. A flexible piecewise homogeneous modeling method based on K-means clustering is proposed, which accurately and efficiently maps the inhomogeneous plasma sheath into a multiregion model. Compared with the conventional K-means clustering method, a distance formula designed for plasma EM parameters was investigated for the partition of plasma sheath. To further prompt the convenience and efficiency of the MR-SIE solver, the discontinuous Galerkin (DG) method is used to discretize the electric and magnetic current combined field integral equations (JMCFIE) of the multiregion model. Numerical experiments demonstrate that the MR-SIE solution with the flexible piecewise homogeneous modeling exhibits accuracy and efficiency, showing good potential for fast analyzing the EM scattering characteristics of hypersonic vehicles.

Pulmonary hypertension (PH) is a progressive fatal disease with no cure. Canagliflozin (CANA), a novel medication for diabetes, has been found to have remarkable cardiovascular benefits. However, few studies have addressed the effect and pharmacological mechanism of CANA in the treatment of PH. Therefore, our study aimed to investigate the effect and pharmacological mechanism of CANA in treating PH. First, CANA suppressed increased pulmonary artery pressure, right ventricular hypertrophy, and vascular remodeling in both mouse and rat PH models. Network pharmacology, transcriptomics, and biological results suggested that CANA could ameliorate PH by suppressing excessive oxidative stress and pulmonary artery smooth muscle cell proliferation partially through the activation of PPARγ. Further studies demonstrated that CANA inhibited phosphorylation of PPARγ at Ser225 (a novel serine phosphorylation site in PPARγ), thereby promoting the nuclear translocation of PPARγ and increasing its ability to resist oxidative stress and proliferation. Taken together, our study not only highlighted the potential pharmacological effect of CANA on PH but also revealed that CANA-induced inhibition of PPARγ Ser225 phosphorylation increases its capacity to counteract oxidative stress and inhibits proliferation. These findings may stimulate further research and encourage future clinical trials exploring the therapeutic potential of CANA in PH treatment.

Introduction: Critically ill patients often endure pain, a distressing experience that can trigger diverse pathophysiological consequences. While remifentanil, with its rapid kinetics, is commonly used for analgesia in intensive care units (ICU), it frequently leads to opioid-related adverse effects. A promising alternative has emerged in oliceridine, a novel G protein-biased μ-opioid receptor agonist. This new drug offers the potential for effective pain relief with fewer side effects. However, its efficacy and safety profile in mechanically ventilated ICU patients remain to be fully elucidated. Methods: This is a multicenter, prospective, randomized, single-blind, active-controlled trial conducted across 24 ICUs in China. A total of 292 mechanically ventilated patients requiring analgesia and sedation will be randomly assigned in a 1:1 ratio to either the oliceridine or remifentanil group. The oliceridine group will receive oliceridine (2–20 μg/kg/h), while the remifentanil group will receive remifentanil (1.5–12 μg/kg/h). Both groups will receive propofol for sedation if necessary. The target for analgesia is Critical-Care Pain Observation Tool (CPOT) < 3, and for sedation is Richmond Agitation-Sedation Scale (RASS) − 2 to 0. Planned Outcomes: The primary outcome will be the percentage of time within target analgesia during study drug administration. Secondary outcomes will include gastrointestinal dysfunction, respiratory depression, sedative usage, mechanical ventilation duration, ICU stay length, extubation failure rate, etc. Trial Registration: NCT06454292. Registered on June 11, 2024.

The information paradox of black holes has always been a hot topic at the forefront of theoretical physics. In this paper, we aim to understand the information paradox of the dilaton black hole from the perspective of the total correlation quantified by mutual information between the initial subsystems Aand B. We find that the dilaton gravity can redistribute initial mutual information for discrete and continuous variables between the subsystems Aand B, but cannot redistribute initial entanglement. Interestingly, the sum of physically accessible and inaccessible mutual information is equal to the initial mutual information. Therefore, physically accessible mutual information is transformed into physically inaccessible mutual information by the dilaton gravity of the black hole. From the perspective of mutual information, the information of black holes is conserved and not lost.

With the increasing penetration rate of distributed power supply, the interaction between grid-connected inverters and power grid is prone to harmonic oscillation, which will seriously threaten the stable operation of power grid. At present, impedance analysis has been proved to be an effective tool to study the stability of grid-connected systems. However, few studies have considered the influence of frequency coupling effect on the output impedance characteristics of grid-connected inverters. To solve this problem, the sequence impedance model of a three-phase grid-connected inverter controlled by a virtual synchronous generator is established by harmonic linearization method based on the frequency coupling effect. In addition, an improved method of sequence impedance modeling based on grid impedance is proposed to effectively eliminate the influence of coupling terms. Finally, the correctness and practicability of the proposed simplified sequence impedance model are verified by simulation and experiment.

In this study, we present the design, fabrication, and measurements of a 3-D heterogeneous integrated RF-module at W-band. A 3-D transition structure based on micro-bumps is fabricated and measured to obtain the transition loss of one bump. One micro-bump has an insertion loss of 0.21 dB at the W-band. A packaged filter and a benzocyclobutene (BCB)-based back cavity antenna are designed and analyzed in detail. The filter has a 2.6-dB insertion loss at 94 GHz with four transmission zeros (TZs) and a $2.14f_{0}~10$ -dB stopband. An extra loss of 0.9 dB is found after packaging. Then, the filter and antenna are integrated with a SiGe-based low-noise amplifier (LNA) and a mixer to realize a fully packaged receiver by using our in-house Si-based micro-electromechanical systems (MEMS) through-silicon-trench (TST) technology and multilayer photosensitive composite film. The proposed 3-D heterogeneous integrated receiver is measured on-wafer. This low-loss packaging solution can be further used in millimeter-wave communication or radar systems.

Optical crosstalk between adjacent pixels acts as one of the major challenges for miniaturized light-emitting diode (mini-LED) displays. In this letter, the impacts of optical crosstalk on the chromatic characteristics of the four-in-one mini-LED integrated matrix device (IMD) have been investigated. The influence of driving current on the optical crosstalk in four-in-one IMDs has also been determined. To be specific, red mini-LEDs can compromise the color gamut of full-color self-emissive mini-LED displays. This demonstrates the crucial need to optimize the operating conditions of red mini-LEDs to alleviate optical crosstalk in displays using four-in-one IMDs. $\Delta u$ ’v’, the chromatic shift, causing by the optical crosstalk originating from red mini-LEDs reaches 0.024 and 0.045 for green and blue mini-LEDs, and the color gamut decreases from 112.00% to 102.47% under the red crosstalk.

To investigate the role of co-stimulatory and co-inhibitory molecules on immune tolerance in immune thrombocytopenia (ITP), this study mapped the immune cell heterogeneity in the bone marrow of ITP at the single-cell level using Cytometry by Time of Flight (CyTOF). Thirty-six patients with ITP and nine healthy volunteers were enrolled in the study. As soluble immunomodulatory molecules, more sCD25 and sGalectin-9 were detected in ITP patients. On the cell surface, co-stimulatory molecules like ICOS and HVEM were observed to be upregulated in mainly central memory and effector T cells. In contrast, co-inhibitory molecules such as CTLA-4 were significantly reduced in Th1 and Th17 cell subsets. Taking a platelet count of 30×109L−1as the cutoff value, ITP patients with high and low platelet counts showed different T cell immune profiles. Antigen-presenting cells such as monocytes and B cells may regulate the activation of T cells through CTLA-4/CD86 and HVEM/BTLA interactions, respectively, and participate in the pathogenesis of ITP. In conclusion, the proteomic and soluble molecular profiles brought insight into the interaction and modulation of immune cells in the bone marrow of ITP. They may offer novel targets to develop personalized immunotherapies.

Data-driven approaches have been widely applied in fault diagnosis. However, having sufficient labels to effectively develop fault diagnosis models in real-world manufacturing scenarios has remained a challenge. The key issue is to break down data silos and expand the source of data availability while safeguarding data privacy. To address abovementioned gap, a federated learning model using histogram-based gradient boosting tree, is proposed for collaborative fault diagnosis under privacy-preserving. During model training process, only an update of relevant local model parameters is communicated, thus protecting data privacy while contributing to the increased accuracy of the global model. Meanwhile, a data compensation mechanism is introduced to alleviate the disparity problem in data volume across participants. Two case studies are carried out and further compared with traditional situations to reveal the effectiveness of the proposed method. It is envisioned that this developed method can be useful for industrial practitioners to integrate their data for model training while maintaining data privacy, and promoting collaboration in digital manufacturing.

Background: Painful physical symptoms (PPS) are highly prevalent in patients with major depressive disorder (MDD). Presence of PPS in depressed patients are potentially associated with poorer antidepressant treatment outcome. We aimed to evaluate the association of baseline pain levels and antidepressant treatment outcomes. Methods: We searched PubMed, Embase and Cochrane Library databases from inception through February 2023 based on a pre-registered protocol (PROSPERO: CRD42022381349). We included original studies that reported pretreatment pain measures in antidepressant treatment responder/remitter and non-responder/non-remitter among patients with MDD. Data extraction and quality assessment were performed following the Preferred Reporting Items for Systematic Reviews and Meta-analyses by two reviewers independently. The primary outcome was the difference of the pretreatment pain levels between antidepressant treatment responder/remitter and non-responder/non-remitter. Random-effects meta-analysis was used to calculate effect sizes (Hedge’s g) and subgroup and meta-regression analyses were used to explore sources of heterogeneity. Results: A total of 20 studies were included. Six studies reported significantly higher baseline pain severity levels in MDD treatment non-responders (Hedge’s g= 0.32; 95% CI, 0.13–0.51; P= 0.0008). Six studies reported the presence of PPS (measured using a pain severity scale) was significantly associated with poor treatment response (OR = 1.46; 95% CI, 1.04-2.04; P= 0.028). Five studies reported significant higher baseline pain interference levels in non-responders (Hedge’s g= 0.46; 95% CI, 0.32–0.61; P< 0.0001). Four studies found significantly higher baseline pain severity levels in non-remitters (Hedge’s g= 0.27; 95% CI, 0.14–0.40; P< 0.0001). Eight studies reported the presence of PPS significantly associated with treatment non-remission (OR = 1.70; 95% CI, 1.24–2.32; P= 0.0009). Conclusions: This study suggests that PPS are negatively associated with the antidepressant treatment outcome in patients with MDD. It is possible that better management in pain conditions when treating depression can benefit the therapeutic effects of antidepressant medication in depressed patients.

Targeted nanoparticles have been extensively explored for their ability to deliver their payload to a selective cell population while reducing off-target side effects. The design of actively targeted nanoparticles requires the grafting of a ligand that specifically binds to a highly expressed receptor on the surface of the targeted cell population. Optimizing the interactions between the targeting ligand and the receptor can maximize the cellular uptake of the nanoparticles and subsequently improve their activity. Here, we evaluated how the density and presentation of the targeting ligands dictate the cellular uptake of nanoparticles. To do so, we used a DNA-scaffolded PLGA nanoparticle system to achieve efficient and tunable ligand conjugation. A prostate-specific membrane antigen (PSMA) expressing a prostate cancer cell line was used as a model. The density and presentation of PSMA targeting ligand ACUPA were precisely tuned on the DNA-scaffolded nanoparticle surface, and their impact on cellular uptake was evaluated. It was found that matching the ligand density with the cell receptor density achieved the maximum cellular uptake and specificity. Furthermore, DNA hybridization-mediated targeting chain rigidity of the DNA-scaffolded nanoparticle offered ∼3 times higher cellular uptake compared to the ACUPA-terminated PLGA nanoparticle. Our findings also indicated a ∼ 3.7-fold reduction in the cellular uptake for the DNA hybridization of the non-targeting chain. We showed that nanoparticle uptake is energy-dependent and follows a clathrin-mediated pathway. Finally, we validated the preferential tumor targeting of the nanoparticles in a bilateral tumor xenograft model. Our results provide a rational guideline for designing actively targeted nanoparticles and highlight the application of DNA-scaffolded nanoparticles as an efficient active targeting platform.

Gestational diabetes mellitus (GDM) has been found to be a common complication in pregnant women, known to escalate the risk of negative obstetric outcomes. In our study, we genotyped 1,566 Chinese pregnant women for two single nucleotide polymorphisms (SNPs) in the LINGO2gene and one SNP in the GLIS3gene, utilizing targeted next-generation sequencing. The impact of two interacting genes, and the interaction of genes with the environment─including exposure to particulate matter (PM2.5), ozone (O3), and variations in prepregnancy body mass index (BMI)─on the incidence of GDM were analyzed using logistic regression. Our findings identify the variants LINGO2rs10968576 (P= 0.022, OR = 1.224) and rs1412239 (P= 0.018, OR = 1.231), as well as GLIS3rs10814916 (P= 0.028, OR = 1.172), as risk mutations significantly linked to increased susceptibility to GDM. Further analysis underscores the crucial role of gene–gene and gene–environment interactions in the development of GDM among Chinese women (P< 0.05). Particularly, the individuals carrying the rs10968576 G-rs1412239 G-rs10814916 C haplotype exhibit increased susceptibility to GDM during the prepregnancy period when interacting with PM2.5, O3, and BMI (P= 8.004 × 10–7, OR = 1.206; P= 6.3264 × 10–11, OR = 1.280; P= 9.928 × 10–7, OR = 1.334, respectively). In conclusion, our research emphasizes the importance of the interaction between specific gene variations─LINGO2and GLIS3─and environmental factors in influencing GDM risk. Notably, we found significant associations between these gene variations and GDM risk across various environmental exposure periods.

Purpose: Current reinforcement learning (RL) algorithms are facing issues such as low learning efficiency and poor generalization performance, which significantly limit their practical application in real robots. This paper aims to adopt a hybrid model-based and model-free policy search method with multi-timescale value function tuning, aiming to allow robots to learn complex motion planning skills in multi-goal and multi-constraint environments with a few interactions. Design/methodology/approach: A goal-conditioned model-based and model-free search method with multi-timescale value function tuning is proposed in this paper. First, the authors construct a multi-goal, multi-constrained policy optimization approach that fuses model-based policy optimization with goal-conditioned, model-free learning. Soft constraints on states and controls are applied to ensure fast and stable policy iteration. Second, an uncertainty-aware multi-timescale value function learning method is proposed, which constructs a multi-timescale value function network and adaptively chooses the value function planning timescales according to the value prediction uncertainty. It implicitly reduces the value representation complexity and improves the generalization performance of the policy. Findings: The algorithm enables physical robots to learn generalized skills in real-world environments through a handful of trials. The simulation and experimental results show that the algorithm outperforms other relevant model-based and model-free RL algorithms. Originality/value: This paper combines goal-conditioned RL and the model predictive path integral method into a unified model-based policy search framework, which improves the learning efficiency and policy optimality of motor skill learning in multi-goal and multi-constrained environments. An uncertainty-aware multi-timescale value function learning and selection method is proposed to overcome long horizon problems, improve optimal policy resolution and therefore enhance the generalization ability of goal-conditioned RL.

Polysaccharides derived from Agrocybe cylindraceahave been demonstrated to exhibit various bioactivities. However, studies on their structural characteristics during the growth process are limited. This study aimed to compare the physicochemical properties and structural characteristics of alkali-extracted polysaccharides from A. cylindraceafruiting bodies (JACP) across four growth stages. Results showed that the extraction yields and protein levels of JACP declined along with the growth of A. cylindracea, while the contents of neutral sugar and glucose increased significantly. However, JACP exhibited structural characteristics similar to those across the four stages. Four polysaccharide subfractions were isolated from each growth stage, including JACP-Et30, JACP-Et50, JACP-Et60, and JACP-Et70. JACP-Et30 from the four stages and JACP-Et50 from the initial three stages were identified as heteroglucans with β-1,3-d-Glcpand β-1,6-d-Glcpresidues as main chains, respectively. However, other subfractions were considered as β-1,6-d-glucans containing minor glucuronic acid. These subfractions were predominantly replaced by Glcpresidues at the O-3 and O-6 positions. Overall, while JACP exhibited variable physicochemical properties, its structural characteristics remained stable during the growth process, offering new insights into its potential applications in the food and medicinal industries.

Background The prevalence of Hemagglutinin 9 Neuraminidase 2 (H9N2) avian influenza virus (AIV) in poultry in Asia has raised serious concerns about its zoonotic transmission and the potential for a pandemic, underscoring the need for effective therapeutics. Chikusetsusaponin IVa (CHS), a bioactive triterpenoid saponin from Radix saposhnikoviae, has exhibited anti-inflammatory activity in preclinical studies. We hypothesized that CHS could mitigate immunopathology during tumor necrosis factor (TNF)-infection by suppressing excessive inflammation.Objectives CHS is a natural saponin with anti-inflammatory activity. This research aimed to explore the in vitroand in vivoprotective effects and mechanisms of CHS against H9N2 AIV infection.Materials and Methods We employed Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and Gene Ontology (GO) analysis for the prediction of the underlying mechanisms, followed by a network analysis approach. In animal experiments, the toll-like receptor 4 (TLR4)/nuclear factor kappa B (NF-κB) signaling pathways and associated proteins were assessed using immunohistochemistry and western blot analysis.Results In A549 cells, CHS treatment reduced H9N2 AIV-induced apoptosis in a dose-dependent manner. CHS was found to have a suppressive effect on the mRNA expression of various inflammatory cytokines (including TNF-α, interleukin (IL)-6, IL-1β, and IL-8) as well as mediators such as inducible nitric oxide synthase (iNOS) and prostaglandin-endoperoxide synthase 2 (PTGS2). It can be seen that CHS does have anti-inflammatory effects. Bioinformatics analysis indicated that CHS might exhibit anti-inflammatory effects by modulating cytokine–cytokine receptor interaction and the NF-κB signaling pathways. Building upon this, it was found that CHS blocked the activation of TLR4 and NF-κB signaling pathways in A549 cells infected with H9N2 AIV. In vivo, CHS prolonged the survival time and increased the survival rate of H9N2 AIV-infected mice. CHS was found to have a protective effect on the lungs of infected mice, resulting in reduced damage and lower levels of viral load and inflammation. CHS inhibited the production of proinflammatory cytokines (IL-1β, TNF-α, IL-6, and IL-8) and inhibited the activation of TLR4 and NF-κB signaling pathways in the pulmonary tissues of mice that were infected.Conclusion CHS exerts protective effects against H9N2 AIV infection in vitroand in vivo. The anti-inflammatory mechanisms may involve the inhibition of cytokine production and the blockade of TLR4 and NF-κB signaling pathways.