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Given recent technological advances in proteomics, it is now possible to quantify plasma proteomes in large cohorts of patients to screen for biomarkers and to guide the early diagnosis and treatment of depression. Here we used CatBoost machine learning to model and discover biomarkers of depression in UK Biobank data sets (depression n= 4,479, healthy control n= 19,821). CatBoost was employed for model construction, with Shapley Additive Explanations (SHAP) being utilized to interpret the resulting model. Model performance was corroborated through 5-fold cross-validation, and its diagnostic efficacy was evaluated based on the area under the receiver operating characteristic (AUC) curve. A total of 45 depression-related proteins were screened based on the top 20 important features output by the CatBoost model in six data sets. Of the nine diagnostic models for depression, the performance of the traditional risk factor model was improved after the addition of proteomic data, with the best model having an average AUC of 0.764 in the test sets. KEGG pathway analysis of 45 screened proteins showed that the most significant pathway involved was the cytokine-cytokine receptor interaction. It is feasible to explore diagnostic biomarkers of depression using data-driven machine learning methods and large-scale data sets, although the results require validation.

Hollow-core anti-resonant fibers (HC-ARFs) are widely used for high-power laser transmission owing to their low nonlinearity and high damage threshold. However, most existing structural designs are suitable for single-mode guidance but are inadequate for efficient transmission of few- or multi-mode lasers with high output power. In this study, we fabricated a low-loss multi-mode 8-tube nested hollow-core anti-resonant fiber (Nested HC-ARF) with a minimum loss of 3.27 dB/km at 1 μm wavelength, which enabled the efficient transmission of at least five mode groups. Accordingly, we demonstrated the transmission of a record 3 kW few-mode (M2∼1.38) continuous-wave laser with a maximum transmission efficiency of 95.2% using a 10 m multi-mode Nested HC-ARF and an optimized transmission system. The experimental verification of the beam quality and spectrum indicated distortion-free transmission, which paves the way to power delivery on the scale of tens of kilowatts.

Accumulated reactive oxygen species (ROS) and their resultant vascular dysfunction in androgenic alopecia (AGA) hinder hair follicle survival and cause permanent hair loss. However, safe and effective strategies to rescue hair follicle viability to enhance AGA therapeutic efficiency remain challenging. Herein, we fabricated a quercetin-encapsulated (Que) and polydopamine-integrated (PDA@QLipo) nanosystem that can reshape the perifollicular microenvironment to initial hair follicle regeneration for AGA treatment. Both the ROS scavenging and angiogenesis promotion abilities of PDA@QLipo were demonstrated. In vivoassays revealed that PDA@QLipo administrated with roller-microneedles successfully rejuvenated the “poor” perifollicular microenvironment, thereby promoting cell proliferation, accelerating hair follicle renewal, and facilitating hair follicle recovery. Moreover, PDA@QLipo achieved a higher hair regeneration coverage of 92.5% in the AGA mouse model than minoxidil (87.8%), even when dosed less frequently. The nanosystem creates a regenerative microenvironment by scavenging ROS and augmenting neovascularity for hair regrowth, presenting a promising approach for AGA clinical treatment.

Polycyclic aromatic hydrocarbon (PAH) exposure is suspected to be linked to oxidative damage. Herein, ten PAH human exposure biomarkers [hydroxylated PAH metabolites (OH-PAHs)] and five oxidative stress biomarkers (OSBs) were detected in urine samples collected from participants living in a rural area (n= 181) in Northwestern China. The median molar concentration of SOH-PAHs in urine was 47.0 pmol mL–1. The 2-hydroxynaphthalene (2-OHNap; median: 2.21 ng mL–1) was the dominant OH-PAH. The risk assessment of PAH exposure found that hazard index (HI) values were <1, indicating that the PAH exposure of rural people in Jingyuan would not generate significant cumulative risks. Smokers (median: 0.033) obtained higher HI values than nonsmokers (median: 0.015, p< 0.01), suggesting that smokers face a higher health risk from PAH exposure than nonsmokers. Pearson correlation and multivariate linear regression analysis revealed that SOH-PAH concentrations were significant factors in increasing the oxidative damage to deoxyribonucleic acid (DNA) (8-hydroxy-2'-deoxyguanosine, 8-OHdG), ribonucleic acid (RNA) (8-oxo-7,8-dihydroguanine, 8-oxoGua), and protein (o, o'-dityrosine, diY) (p< 0.05). Among all PAH metabolites, only 1-hydroxypyrene (1-OHPyr) could positively affect the expression of all five OSBs (p< 0.05), suggesting that urinary 1-OHPyr might be a reliable biomarker for PAH exposure and a useful indicator for assessing the impacts of PAH exposure on oxidative stress. This study is focused on the relation between PAH exposure and oxidative damage and lays a foundation for the study of the health effect mechanism of PAHs.

Endometrial carcinoma remains a public health concern with a growing incidence, particularly in younger women. Preserving fertility is a crucial consideration in the management of early-onset endometrioid endometrial carcinoma (EEEC), particularly in patients under 40 who maintain both reproductive desire and capacity. To illuminate the molecular characteristics of EEEC, we undertook a large-scale multi-omics study of 215 patients with endometrial carcinoma, including 81 with EEEC. We reveal an unexpected association between exposome-related mutational signature and EEEC, characterized by specific CTNNB1and SIGLEC10hotspot mutations and disruption of downstream pathways. Interestingly, SIGLEC10Q144Kmutation in EEECs resulted in aberrant SIGLEC-10 protein expression and promoted progestin resistance by interacting with estrogen receptor alpha. We also identified potential protein biomarkers for progestin response in fertility-sparing treatment for EEEC. Collectively, our study establishes a proteogenomic resource of EEECs, uncovering the interactions between exposome and genomic susceptibilities that contribute to the development of primary prevention and early detection strategies for EEECs.

Metal–organic gels (MOGs) are a new type of intelligent soft material, which are bridged by metal ions and organic ligands through noncovalent interactions. In this paper, we prepared highly stable P-MOGs, using the classical organic electrochemiluminescence (ECL) luminescence meso-tetra(4-carboxyphenyl)porphine as the organic ligand and Fe3+as the metal ion. Surprisingly, P-MOGs can stably output ECL signals at a low potential. We introduced P-MOGs into the ECL resonance energy transfer strategy (ECL-RET) and constructed a quenched ECL immunosensor for the detection of the SARS-CoV-2 nucleocapsid protein (SARS-CoV-2-N). In the ECL-RET system, P-MOGs were used as energy donors, and Au@Cu2O@Fe3O4were selected as energy acceptors. The ultraviolet-visible spectrum of Au@Cu2O@Fe3O4partially overlaps with the ECL spectrum of P-MOGs, which can effectively touch off the ECL-RET behavior between the donors and receptors. Under the ideal experimental situation, the linear detection range of the SARS-CoV-2-N concentration was 10 fg/mL to 100 ng/mL, and the limit of detection was 1.5 fg/mL. This work has broad application prospects for porphyrin-MOGs in ECL sensing.

Food security is an important issue in the 21st century; preventing and controlling crop diseases and pests are the key to solve this problem. The creation of new pesticides based on natural products is an important and effective method. Herein, coumarins were selected as parent structures, and a series of their derivatives were designed, synthesized, and evaluated for their antiviral activities, fungicidal activities, and insecticidal activities. We found that coumarin derivatives exhibited good to excellent antiviral activities against tobacco mosaic virus (TMV). The antiviral activities of I-1, I-2a, I-4b, II-2c, II-2g, II-3, and II-3bare better than that of ribavirin at 500 μg/mL. Molecular docking research showed that these compounds had a strong interaction with TMV CP. These compounds also showed broad-spectrum fungicidal activities against 14 plant pathogenic fungi. The EC50values of I-1, I-2a, I-3c, and II-2dare in the range of 1.56–8.65 μg/mL against Rhizoctonia cerealis, Physalospora piricola, Sclerotinia sclerotiorum, and Pyricularia grisea. Most of the compounds also displayed good insecticidal activities against Mythimna separata. Pesticide-likeness analysis showed that these compounds are following pesticide-likeness and have the potential to be developed as pesticide candidates. The present work lays a foundation for the discovery of novel pesticide lead compounds based on coumarin derivatives.

Effect of direct aging of 170 °C on corrosion behavior of laser powder bed fused AlSi10Mg (LPBF-AlSi10Mg) was studied by microstructure analysis, electrochemical analysis and X-ray photoelectron spectrometer. The results show that direct aging of 170 °C has little effect on melt pool and Si cellular structure, but promotes the precipitation of nano-Si particles and releases the residual stress. With increasing aging time from 0 to 4 h to 24 h, the corrosion property of the LPBF-AlSi10Mg is deteriorated, which is evidenced by increased corrosion current density and decreased pitting potential and polarization resistance. With increasing the aging time, the thickness of the oxide film formed on surface of the LPBF-AlSi10Mg increases. The Si content of the oxide film of the sample aging for 4 h is the lowest, 9.42 at.%, and it is the highest, 18.62 at.%, for the sample aging for 24 h. The electrochemical noise analysis reveals that the middle-frequency contribution of the Hilbert spectrum is responsible for the deteriorated corrosion performance, which corresponds to metastable pitting initiated by nano-Si particles.

Global illumination (GI) plays a crucial role in rendering realistic results for virtual exhibitions, such as virtual car exhibitions. These scenarios usually include all-frequency bidirectional reflectance distribution functions (BRDFs), although their geometries and light configurations may be static. Rendering all-frequency BRDFs in real time remains challenging due to the complex light transport. Existing approaches, including precomputed radiance transfer, light probes, and the most recent path-tracing-based approaches (ReSTIR PT), cannot satisfy both quality and performance requirements simultaneously. Herein, we propose a practical hybrid global illumination approach that combines ray tracing and cached GI by caching the incoming radiance with wavelets. Our approach can produce results close to those of offline renderers at the cost of only approximately 17 ms at runtime and is robust over all-frequency BRDFs. Our approach is designed for applications involving static lighting and geometries, such as virtual exhibitions.

Hydrogel stands out as one of the most attractive wound dressings due to its excellent moisturizing properties and capacity to absorb wound exudates. However, conventional hydrogel dressings often lack responsiveness to the microenvironment, merely acting as protective barriers for the wound. Consequently, they exhibit limited effectiveness in preventing infection and facilitating wound repair. To address these problems, we have developed a multifunctional injectable hydrogel, CF/MS@HG, based on peroxidase-like nanozymes, aiming at rapidly healing bacterial-infected wounds. The hydrogel is mainly composed of oxidized sodium alginate, aminated gelatin, and polylysine, encapsulating MIL-101(CuFe) NPs (CF) and manganese selenide nanoparticles (MnSe2NPs, or MS NPs). After injection, the complex rapidly gelatinizes at the infected wound site through a Schiff base reaction. In vitroexperiments have demonstrated the hydrogel’s strong adhesion and self-healing capabilities. Moreover, CF exhibiting peroxidase (POD)-like activity, catalyzes in situhydrogen peroxide (H2O2) to generate highly toxic hydroxyl radicals (·OH) within the wound microenvironment, inducing oxidative damage to bacteria. Meanwhile, MS decomposes into H2Se in the slightly acidic wound microenvironment, disrupting bacterial metabolism and inhibiting proliferation. The addition of polylysine further enhances the hydrogel’s antibacterial properties. In vivoexperiments have shown that the hydrogel exhibits excellent biological safety and significantly promotes wound healing. This multifunctional smart hydrogel holds great promise for the treatment of bacterial-infected wounds.

Respiration monitoring has been attracting substantial attention because of its potential for assessing sleep stages and quality. Traditional approaches for respiratory rate (RR) tracking require dedicated wearable devices, which can intrude upon and create an unwelcoming experience for users. To address this, researchers have proposed Wi-Fi-based respiration monitoring systems that capitalize on Wi-Fi’s ubiquity, cost-effectiveness, and noncontact nature, effectively converting existing infrastructure into ubiquitous sensors. However, existing systems often struggle with the subtle signal-to-noise ratio of embedded breathing signals, leading to limited coverage and inflexible deployment in noisy environments. This article presents Wi-Fi respiration perception (WiResP), an ingenious and pragmatic Wi-Fi-based system for tracking respiration, employing the spectrum enhancement approach to boost respiration detection. By treating the spectrum of the breathing signal obtained from channel state information as an image, the system can leverage image processing techniques to greatly enhance the respiration signal trace, improving detectability and increasing sensing coverage for RR estimation. Moreover, an image-based continuity checker module is proposed to verify the signal trace continuity to reduce false alarms (FAs). We conducted extensive experiments and assessed WiResP under different settings. The experiments demonstrate that WiResP can reliably capture RR during sleep and achieve a detection rate of 92% and an FA rate <5%, leading to significantly improved sleep stage recognition under flexible device placements. The promising performance positions WiResP as a candidate for a real-world in-home respiration tracking system.

Monte Carlo based methods such as path tracing are widely used in movie production. To achieve low noise, they require many samples per pixel, resulting in long rendering time. To reduce the cost, one solution is Monte Carlo denoising, which renders the image with fewer samples per pixel (as little as 128) and then denoises the resulting image. Many Monte Carlo denoising methods rely on deep learning: they use convolutional neural networks to learn the relationship between noisy images and reference images, using auxiliary features such as position and normal together with image color as inputs. The network predicts kernels which are then applied to the noisy input. These methods show powerful denoising ability, but tend to lose geometric or lighting details and to blur sharp features during denoising.

Time reversal is a physical principle well known for its deterministic focusing effect. Recently discovered statistical effects show that the time reversal focusing spot is not a point but has a Bessel power distribution. This finding offers accurate and reliable speed estimation indoors, where multipaths are abundant, with mostly nonline-of-sight (NLOS) conditions, and enable various indoor applications, such as wireless sensing and tracking. No known techniques can thrive in such scenarios. In essence, time reversal is an effective tool that embraces multipaths as virtual sensors with hundreds of thousands of degrees of freedom for our utilization.

The main aspect powering GNNs is the multi-layer network architecture to learn the nonlinear representation for graph learning task. The core operation in GNNs is the message propagation in which each node updates its information by aggregating the information from its neighbors. Existing GNNs usually adopt either linear neighborhood aggregation (e.g. mean, sum) or max aggregator in their message propagation. 1) For linear aggregators, the whole nonlinearity and network's capacity of GNNs are generally limited because deeper GNNs usually suffer from the over-smoothing issue due to their inherent information propagation mechanism. Also, linear aggregators are usually vulnerable to the spatial perturbations. 2) For max aggregator, it usually fails to be aware of the detailed information of node representations within neighborhood. To overcome these issues, we re-think the message propagation mechanism in GNNs and develop the new general nonlinear aggregators for neighborhood information aggregation in GNNs. One main aspect of our nonlinear aggregators is that they all provide the optimally balanced aggregator between max and mean/sum aggregators. Thus, they can inherit both i) high nonlinearity that enhances network's capacity, robustness and ii) detail-sensitivity that is aware of the detailed information of node representations in GNNs’ message propagation. Promising experiments show the effectiveness, high capacity and robustness of the proposed methods.

Existing GNNs usually conduct the layer-wise message propagation via the ‘full’ aggregation of all neighborhood information which are usually sensitive to the structural noises existed in the graphs, such as incorrect or undesired redundant edge connections. To overcome this issue, we propose to exploit Sparse Representation (SR) theory into GNNs and propose Graph Sparse Neural Networks (GSNNs) which conduct sparse aggregation to select reliable neighbors for message aggregation. GSNNs problem contains discrete/sparse constraint which is difficult to be optimized. Thus, we then develop a tight continuous relaxation model Exclusive Group Lasso GNNs (EGLassoGNNs) for GSNNs. An effective algorithm is derived to optimize the proposed EGLassoGNNs model. Experimental results on several benchmark datasets demonstrate the better performance and robustness of the proposed EGLassoGNNs model.

In the electrochemical CO2reduction reaction (CO2RR), CO2activation is always the first step, followed by the subsequent hydrogenation. The catalytic performance of CO2RR is intrinsically restricted by the competition between molecular CO2activation and CO2reduction product release. Here, we design a heteronuclear Fe1-Mo1dual-metal catalytic pair on ordered porous carbon that features a high catalytic performance for driving electrochemical CO2reduction to CO. Combining real-time near-ambient pressure X-ray photoelectron spectroscopy, operando 57Fe Mössbauer spectroscopy, and in situattenuated total reflectance surface-enhanced infrared absorption spectroscopy measurements with density functional theory calculations, chemical adsorption of CO2is observed on the Fe1-Mo1catalytic pair through a bridge configuration, which prompts the bending of the CO2molecule for CO2activation and then facilitates the subsequent hydrogeneration reaction. More importantly, the dynamic adsorption configuration transition from the bridge configuration of CO2on Fe1-Mo1to the linear configuration of CO on the Fe1center results in breaking the scaling relationship in CO2RR, simultaneously promoting the CO2activation and the CO release.

Prostate-specific membrane antigen (PSMA) overexpressed on prostate cancer (PCa) cells is a satisfactory theranostic target in PCa. To seek novel non-glutamate-urea-based PSMA inhibitors by the strategy of bioisosterism, 10 ligands were designed, synthesized, and characterized. Among them, ligands 17, 18, and 21–24bearing the squaramic acid moiety proved to be potent PSMA inhibitors, with Kivalues ranging from 0.40 to 2.49 nM, which are comparable or higher in inhibitory potency compared to previously reported glutamate-urea-based inhibitors. Docking studies of 15, 17, and 19were carried out to explore their binding mode in the active site of PSMA. Two near-infrared (NIR) probes, 23(λEM= 650 nm) and 24(λEM= 1088 nm), displayed favorable in vivo NIR imaging and successful NIR-II image-guided tumor resection surgery in PSMA-positive tumor-bearing mice, which demonstrated the effectiveness of these new squaramic acid-based inhibitors.

Two-dimensional (2D) hybrid perovskites take an emerging position in optoelectronics. Especially, ferroelectric crystals in this family can be potentially used as polarized light detectors because photocurrent, induced by the ferroelectric bulk photovoltaic effect (BPVE), is the function of the intersection angle between the polarization directions of polarized light and the spontaneous polarization (Ps) direction of ferroelectric crystals. Herein, exceptionally strong polarization responses to polarized light are achieved in ferroelectric crystals of (isopentylammonium)2CsPb2Br7(1), which is closely involved with the Ps-directed BPVE. Structurally, the alternate packing of organic spacers and inorganic sheets leads to its intrinsic anisotropy of optical dichroism (αc/αa∼ 3.1), thus creating sinusoidal photocurrents with a polarization ratio of ∼1.2 at 10 V bias. It is noteworthy that the exceptional polarization responses with a large polarization ratio of ∼7.2 can be further obtained based on its BPVE at zero bias (self-powered mode). This figure-of-merit is significantly superior to that of some 2D materials, nanowires, and homologues, e.g., ReS2(∼3.5), GeSe (∼2.16), CsPbBr3nanowire (∼2.6), and (n-butylammonium)2(methylammonium)Pb2Br7(∼2.0). This work sheds light on the optimization of photoelectric behaviors on the targeted optoelectronic device applications by ferroelectric BPVE.

In the present study, 2219-T87 Al alloy plates, 4 mm in thickness, were subjected to bobbin tool friction stir welding (BT-FSW) under relatively high welding speeds of 200 and 400 mm/min, with the aim to analyze the effect of welding speeds on fatigue properties of the joints. The results showed that the tension–tension high-cycle fatigue performance of the BT-FSW joints at room temperature was significantly enhanced compared to that of other joints of 2xxx series Al alloys counterparts. Particularly at a high welding speed of 400 mm/min, the fatigue strength of the joint reached 78% of the base material together with a high tensile strength of 311 MPa. It was found that the joint line remnants had no effects on the fatigue properties of the BT-FSW joints due to the elimination of root flaws under the action of the lower shoulder. Most of the samples with the welding speed of 200 mm/min failed at the thermo-mechanical zone (TMAZ) during fatigue tests, attributable to the coarsened grains and precipitates, but all of the samples with high welding speed of 400 mm/min randomly failed at the nugget zone due to the improved hardness value in the TMAZ.

The demand and requirement for high-capacity power electronic devices increase rapidly, and integrated emitter turn-off thyristor (IETO) has excellent performance in both on-state voltage drop and turn-off capability. An advanced 6-in 4.5 kV IETO device is proposed and developed, including optimized package and driver unit. A low-thickness package with compact disc spring assemblies is put forward, which achieved excellent pressure distribution with the same thickness as integrated gate commutated thyristor for complex IETO structure. A composite signal extraction structure without hindrance for ceramic seal is also proposed. Several electromagnetic transient problems during large current turn-off are analyzed, such as the emitter voltage oscillation during commutation, the damping characteristics of gate control signals, and the induced voltage on signal extraction structure. Based on the analysis, a new external driver unit with higher reliability for large current is designed. After optimization, a prototype was developed with all problems solved. According to the experiments, the 6-in 4.5 kV IETO achieved 17.5 kA turn-off current, and the transient characteristics were verified. The commutation time is less than 300 ns, which has enormous potential for larger turn-off current with better gate commutated thyristor (GCT) wafers. Compared with the other GCT-based devices, the IETO in this article reaches the maximum turn-off current.

Methyl parathion (MP) is a widely used organophosphate insecticide that is extremely toxic due to its ability to irreversibly inhibit acetylcholinesterase in the body and persistently accumulate in the environment. Timely detection of MP can prevent harmful residue exposure to humans. Therefore, the development of fast, efficient electrochemical methods to detect trace MP has been highly beneficial for monitoring harmful residues in foods and environment to ensure food safety and ecological conservation. Herein, a novel hybrid metal–organic framework (MOF) nanocomposite composed of Pt nanoparticles (PtNPs), multi-walled carbon nanotubes (MWCNTs), and UiO-66-NH2(PtNPs/UiO-66-NH2/MWCNTs) was rationally designed and prepared by a facile two-step strategy for the sensitive determination of MP. The synergistic effects are illustrated in detail using XRD, XPS, FTIR, TEM, and SEM studies as well as electrochemical technologies such as CV, EIS, and DPV. In addition, the performance of the ternary nanocomposite for detecting MP was investigated by comparing it with the binary-component one. The results showed that the PtNPs/UiO-66-NH2/MWCNT-based electrochemical sensor exhibited outstanding sensitivity of 21.9 μA μM−1cm−2, satisfactory low detection limit of 0.026 μM and wide linear range of 0.11–227.95 μM for MP analysis. Furthermore, the fabricated sensor delivered distinguished freedom from interferences, outstanding regeneration ability, and adequate recoveries for fresh foods and river water samples. In conclusion, the proposed PtNPs/UiO-66-NH2/MWCNT-based sensor provides a potentially useful analytical tool for determining hazardous residues of OPs in foods and the environment.

Rendering glinty details from specular microstructure enhances the level of realism in computer graphics. However, naive sampling fails to render such effects, due to insufficient sampling of the contributing normals on the surface patch visible through a pixel. Other approaches resort to searching for the relevant normals in more explicit ways, but they rely on special acceleration structures, leading to increased storage costs and complexity. In this article, we propose to render specular glints through a different method: differentiable regularization. Our method includes two steps: first, we use differentiable path tracing to render a scene with a larger light size and/or rougher surfaces and record the gradients with respect to light size and roughness. Next, we use the result for the larger light size and rougher surfaces, together with their gradients, to predict the target value for the required light size and roughness by extrapolation. In the end, we get significantly reduced noise compared to rendering the scene directly. Our results are close to the reference, which uses many more samples per pixel, although our method cannot guarantee unbiased convergence to the reference. The overhead for differentiable rendering and prediction is small, so our improvement is almost free. We demonstrate our differentiable regularization on several normal maps, all of which benefit from the method.

Speech enhancement and separation have been a long-standing problem, especially with the recent advances using a single microphone. Although microphones perform well in constrained settings, their performance for speech separation decreases in noisy conditions. In this work, we propose RadioSES, an audioradio speech enhancement and separation system that overcomes inherent problems in audio-only systems. By fusing a complementary radio modality, RadioSES can estimate the number of speakers, solve the source association problem, separate and enhance noisy mixture speeches, and improve both intelligibility and perceptual quality. We perform millimeter-wave sensing to detect and localize speakers and introduce an audioradio deep learning framework to fuse the separate radio features with the mixed audio features. Extensive experiments using commercial off-the-shelf devices show that RadioSES outperforms a variety of state-of-the-art baselines, with consistent performance gains in different environmental settings. Similar to the audiovisual methods, RadioSES provides significant performance improvements (e.g. 3 dB gains in SiSDR, when compared with the corresponding audio-only method), along with the benefits of lower computational complexity and better privacy preservation.

Nanoparticle surfactant (NPS) offers a powerful strategy to generate all-liquid constructs that integrate the inherent properties of the NPs into 3D architectures. Here, using the co-assembly of fluorescent polymeric nanoparticles and amine-functionalized polyhedral oligomeric silsesquioxane, the assembly and jamming behavior of a new type of NPS at the oil–water interface is uncovered. Unlike “solid” inorganic nanoparticles, “soft” polymeric nanoparticles can reorganize when jammed, leading to a relaxation and deformation of the interfacial assemblies, for example, the 3D printed sugar-coated haw stick-like liquid tubules. With NPS serving as emulsifiers, stable Pickering emulsions are prepared that can be converted into robust colloidosomes with pH responsiveness, showing numerous potential applications for encapsulation and controlled release.

To elucidate the regulatory mechanisms that impact variability in albumen quality of laying hens from the peak of lay to the late production phase. A 60-wk study was conducted on a cohort of 20,000 Hy-Line Brown laying hens from 20 to 80 wk old. Before commencement at 20 wk, the 10-wk-old hens were acclimatized for 10 wk. This study examined changes in albumen quality, serum, and liver antioxidant capacity, magnum morphology, and expression of albumen-protein-related genes in the magnum. To reduce sampling error, we collected eggs (n = 90) from pre-determined cages at every sampling point (5-wk intervals), and 8 hens were selected at 10-wk intervals for blood and tissue collection. Our findings revealed that age significantly affected most evaluated parameters. Albumen gel properties, including hardness, gumminess, and chewiness, increased significantly with age (P< 0.05). With the increasing of hens' age from 20 to 80 wk, the albumen proportion of eggs was decreased, but eggshell proportion, yolk proportion, thick albumen proportion, thick to thin ratio, thick albumen solid content, albumen height, Haugh units (HU), and yolk color were increased and then decreased (P< 0.05). Compared to hens aged 20 to 60 wk, the hens (70–80 wk) had significantly reduced total antioxidant capacity (TAC) and glutathione levels (GSH) in the liver and lower serum TAC and superoxide dismutase levels (SOD) (P< 0.05). The magnum mucosal folds were highest in 40 to 60 wk-old hens, and the luminal diameter increased with age (P< 0.05). In the magnum, the mRNA expression levels for OVA, CPE, and NUP205increased significantly between 30 and 40 wk, while FBN1expression was higher between 30 and 50 wk (P< 0.05). At 70 to 80 wk, the expression of BRCA2was significantly downregulated (P< 0.05). Albumen height, thick albumen proportion with protein secretion-related genes, enhanced antioxidant function, and luminal diameter correlated positively. However, the thick-to-thin albumen ratio negatively correlated with BRCA2, downregulated in aged laying hens. We used principal component and cluster analysis to deduce albumen quality changes during 3 phases: 25 to 35, 40 to 55, and 60 to 80 wk. The decline in albumen quality in aging hens is linked with decreased antioxidant capacity, magnum health, and downregulation of key genes involved in protein synthesis and secretion. These findings emphasize critical albumen quality changes in laying hens and suggest molecular pathways underlying age-related albumen quality alterations.

The limitations of tumor treatment have long been attributed to drug resistance and the restricted therapeutic effects of chemotherapy. This study presents a simple and efficient one-pot synthesis approach to prepare a high drug-loading composite nanoparticle PVP/Fe-DOX@QCT (PFDQ). PFDQ exhibits excellent tumor targeting properties, with sustained drug release in the acidic environment of tumors. Furthermore, loading doxorubicin (DOX) and quercetin (QCT) in PFDQ not only reduces the toxicity of DOX to healthy cells but also inhibits the function of P-glycoprotein (P-gp), thus effectively blocking drug efflux. In addition, PFDQ shows excellent photothermal properties. When combined with photothermal therapy, PFDQ can effectively achieve light-to-heat conversion, thereby exerts synergistic effects. By integrating chemotherapy (DOX and QCT) with photothermal therapy, PFDQ established a powerful multimodal anti-tumor platform.

Pyroelectric materials with the capability of converting temperature changes into electrical signals have been widely used as essential elements for assembling integrated smart electronic detectors. Regarding the conversion efficiency of the voltage output, however, it is significant but quite challenging to exploit new candidates with large pyroelectricity figures-of-merit (FOMs) at room temperature. Herein, we have acquired giant near-room-temperature pyroelectric FOMs in the two-dimensional (2D) perovskite-type improper ferroelectric crystals of (BA)2(EA)2Pb3I10(1, where BA = n-butylammonium and EA = ethylammonium), for which the room-temperature voltage FOM (Fv= 1.06 × 10–2cm2/μC) is about 10 times as large as that of the state-of-the-art inorganic oxides (often ∼0.1 × 10–2cm2/μC), while the peak values near the Tcare almost 2–3 orders of magnitude higher than those of the typical oxide counterparts. Such ultrahigh FOMs are mainly due to their large pyroelectric coefficients and unusual bistability of dielectric behavior, that is, an extremely small-amplitude dielectric variation caused by dipole reorientations during the ferroelectric-to-antiferroelectric phase transition at ∼315 K. This achievement of ultrahigh pyroelectric FOMs in improper ferroelectrics is in sharp contrast to the proper counterparts. Moreover, the low-cost and facile integration of crystal-based devices favors their great potential as smart pyroelectric detectors. As far as we know, the findings of giant pyroelectricity FOMs are unprecedented in 2D hybrid perovskites, which probably recall their broader prospects toward high-performance electronic device application.

Commercial 6061 Al alloy and SiCp reinforced 6092 Al matrix composite (AMC) were joined by friction-stir welding (FSW) with different tool offsets. Results show offsetting the pin to Al alloy side could significantly reduce tool wear, while maintaining ultimate tensile strength of the joint around 180 MPa. As tool offset increased from zero to 3 mm, pin and shoulder wear length reduced from 0.17 mm to almost zero and from 0.28 to 0.02 mm, respectively. The corresponding estimated maximum safe welding length increased from 568 to 3125 mm. Fe debris were generated from the steel pin by the sharp SiC particles, then transferred into the nugget zone, eventually formed Al8Fe2Si particles during the FSW process.