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A high-sensitivity fiber-optic photoacoustic sensor with pressure compensation is proposed to analyze the decomposition component SO2in high-pressure gas insulation equipment. The multiple influence mechanism of pressure on photoacoustic excitation and cantilever detection has been theoretically analyzed and verified. In the high-pressure environment, the excited photoacoustic signal is enhanced, which compensates for the loss of sensitivity of the cantilever. A fiber-optic F–P cantilever is utilized to simultaneously measure static pressure and dynamic photoacoustic wave, and a spectral demodulation method based on white light interference is applied to calculate the optical path difference of the F–P interferometer (FPI). The real-time pressure is judged through the linear relationship between the average optical path difference of FPI and the pressure, which gives the proposed fiber-optic photoacoustic sensor the inherent advantages of being uncharged and resistant to electromagnetic interference. The average optical path difference of FPI is positively related to pressure, with a responsivity of 0.6 μm/atm, which is based on changes in the refractive index of gas. In the range of 1–4 atm, the SO2sensor has a higher detection sensitivity at high-pressure, which benefits from the pressure compensation effect. With the pressure environment of gas insulation equipment at 4 atm as the application background, the SO2gas is tested. The detection limit is 20 ppb with an averaging time of 400 s.

Managing Heating, Ventilation and Air-Conditioning (HVAC) optimally with respect to energy efficiency and adaptively with respect to uncertainties is a recognized bottleneck for multi-zone buildings. This work proposes a management approach where HVAC operation is approximated using averaged thermal dynamics. By doing this, energy management becomes effective due to the linear form of the averaged dynamics, making it possible to use optimal and adaptive control tools. The proposed approach exhibits favorable features for implementation in energy management programs: minimal parameters to be estimated (only those directly related to the thermal coefficients); preservation of the distributed multi-zone topology (only the thermal coefficients with neighboring rooms need to be estimated); simplicity of imposing positivity and controllability properties. Optimality and adaptation are studied analytically in the framework of adaptive linear quadratic control. Numerical validations show that the proposed approach strikes optimal trade-offs between energy consumption and thermal comfort, while handling unknown and possibly time-varying parameters. Improved trade-offs span 3-12% with respect to PID control, 14-47% with respect to non-adaptive control, and 1-20% with respect to alternative adaptation methods proposed in the literature.

Postpartum weight retention (PPWR) is a common problem among women after childbirth. The main objectives of this study are to understand the changes in body weight of breastfeeding mothers during long-term follow-up and preliminarily explore the relationship between maternal body weight and human milk composition, including macronutrients, leptin, and adiponectin. Methods: The study included a longitudinal cohort (122 mothers), and a cross-sectional cohort (37 mothers). The human milk, maternal weight, and dietary surveys were collected in the longitudinal cohort at different follow-up time points (1−14 days postpartum, 2−4 months postpartum, 5−7 months postpartum, and 12−17 months postpartum). The maternal body weight was analyzed using the responses in the survey questionnaires. A milk analyzer based on the mid-infrared spectroscopy (MIRS) was used to determine milk composition, and nutrition analysis software evaluated dietary intakes. In the cross-sectional cohort, participating mothers were asked to provide blood and human milk samples and pertinent information related to maternal body composition. Maternal body composition was measured by bioelectrical impedance analysis (BIA), while ELISA analyzed leptin and adiponectin in milk and serum. Results: At 5−7 months postpartum, the PPWR of breastfeeding mothers was (2.46 ± 3.59) kg. At 12−17 months postpartum, the PPWR was (0.98 ± 4.06) kg. PPWR was found to be negatively correlated with milk fat content within 14 days postpartum and positively correlated at 2−4 months postpartum. In addition, the maternal weight and body muscle mass were positively correlated with leptin and adiponectin in milk. Plasma leptin was positively correlated with the mother's body weight, body mass index (BMI), FAT percentage, and body fat mass, while plasma adiponectin did not correlate with any parameter. The results also indicate that the PPWR did not correlate with leptin and adiponectin in plasma or milk. Conclusions: Breastfeeding mothers may retain considerable weight gain one year after delivery. Human milk composition may be related to changes in maternal body weight. Leptin and adiponectin in breast milk and leptin in plasma are associated with the maternal body composition. This study supports the notion that maternal nutritional status may affect offspring health through lactation, and future research should focus on exploring weight management of postpartum mothers.

Multiobjective optimization problems (MOPs) with expensive constraints pose stiff challenges to existing surrogate-assisted evolutionary algorithms (SAEAs) in a very limited computational cost, due to the fact that the number of expensive constraints for an MOP is often large. For existing SAEAs, they always approximate constraint functions in a single granularity, namely, approximating the constraint violation (CV, coarse-grained) or each constraint (fine-grained). However, the landscape of CV is often too complex to be accurately approximated by a surrogate model. Although the modeling of each constraint function may be simpler than that of CV, approximating all the constraint functions independently may result in tremendous cumulative errors and high computational costs. To address this issue, in this article, we develop a multigranularity surrogate modeling framework for evolutionary algorithms (EAs), where the approximation granularity of constraint surrogates is adaptively determined by the position of the population in the fitness landscape. Moreover, a dedicated model management strategy is also developed to reduce the impact resulting from the errors introduced by constraint surrogates and prevent the population from trapping into local optima. To evaluate the performance of the proposed framework, an implementation called K-MGSAEA is proposed, and the experimental results on a large number of test problems show that the proposed framework is superior to seven state-of-the-art competitors.

Two-dimensional (2D) cell culture methods dominate the current research. However, the inherent responsiveness of cells to their native three-dimensional (3D) microenvironment necessitates a paradigm shift toward the development of advanced hydrogels that faithfully mimic the intricacies of the extracellular matrix (ECM) and enable continuous cell–ECM interactions. To address the constraints of traditional static hydrogel networks that impede effective cell–matrix and cell–cell interactions, and to tackle the inherent stability issues associated with dynamically cross-linked hydrogels, which have become a pressing concern. Herein, we present an interpenetrating polymer network (IPN) hydrogel (HA/Alg-RGD hydrogel) that combines a physically cross-linked network between alginate and calcium ions (Alg-Ca2+) for the enhanced cell growth adaptability with a chemically cross-linked hyaluronic acid (HA) network to ensure macroscopic stability during cell culture. The incorporation of arginine-glycine-aspartic peptide modified alginate (Alg-RGD) further facilitates cell adhesion and improves the cell–hydrogel interaction. Notably, this IPN hydrogel demonstrates mechanical stability and enables cell spreading and growth within its structural framework. Leveraging the reversible characteristics of the ionically cross-linked Alg-Ca2+network within IPN hydrogels, we demonstrate the feasibility of the gelatin sacrificial solution for 3D printing purposes within the hydrogel matrix. Subsequent UV-induced covalent cross-linking enables the fabrication of vascularized microfluidic channels within the resulting construct. Our results demonstrate endothelial cell spreading and spontaneous cell sprouting within the hydrogel matrix, thus highlighting the efficacy of this IPN hydrogel system in facilitating 3D cell growth. Additionally, our study emphasizes the potential of 3D printed constructs as a promising approach for vascularization in tissue engineering. The importance of RGD peptides in promoting favorable cell-hydrogel scaffold interactions is also highlighted, emphasizing their critical role in optimizing biomaterial–cell interfaces.

Developing a multifunctional hydrogel wound dressing with good injectability, self-healing, tissue adhesion, biocompatibility, and fast skin wound healing efficiency remains challenging. In this work, an injectable adhesive dopamine-functionalized oxidized hyaluronic acid/carboxymethyl chitosan/collagen (AHADA/CCS/Col) hydrogel was constructed. The Schiff dynamic bond between AHADA and CCS, the N–Ag–N bond between CCS and Ag ions, and the S–Ag–S dynamic bond between sulfhydryl-modified collagen (ColSH) and Ag ions allowed the hydrogel to be both injectable and self-healing. Moreover, the aldehyde groups and catechol groups presented in the hydrogel could generate force with several groups on the tissue interface; therefore, the hydrogel also had good tissue adhesion. In vitro experiments proved that this hydrogel exhibited good biocompatibility and could promote cell proliferation. Additionally, curcumin (Cur)-loaded gelatin nanoparticles (Cur@Gel NPs) were prepared, which could respond to matrix metalloproteinases (MMPs) and controllably release Cur to hasten wound healing efficiency. Animal experiment results showed that this AHADA/CCS/Col hydrogel loaded with Cur@Gel NPs promoted wound repairing better, indicating its potential as a wound dressing.

ABSTRACTHSPA8 (heat shock protein family A (Hsp70) member 8) plays a significant role in the autophagic degradation of proteins, however, its effect on protein stabilization and anti-bacterial autophagy remains unknown. Here, it is discovered that HSPA8, as a binding partner of RHOB and BECN1, induce autophagy for intracellular bacteria clearance. Using its NBD and LID domains, HSPA8 physically binds to RHOB residues 1–42 and 89–118 as well as to BECN1 ECD domain, preventing RHOB and BECN1 degradation. Intriguingly, HSPA8 contains predicted intrinsically disordered regions (IDRs), and drives liquid-liquid phase separation (LLPS) to concentrate RHOB and BECN1 into HSPA8-formed liquid-phase droplets, resulting in improved RHOB and BECN1 interactions. Our study reveals a novel role and mechanism of HSPA8 in modulating anti-bacterial autophagy, and highlights the effect of LLPS-related HSPA8-RHOB-BECN1 complex on enhancing protein interaction and stabilization, which improves the understanding of autophagy-mediated defense against bacteria.

Chemodynamic therapy (CDT) is a highly tumor-specific treatment, while its efficacy is compromised by the intratumoral Fenton reaction efficiency, which is determined by the following reaction factors, including the availability of Fenton ions (e.g., Fe2+), the amount of H2O2, and the degree of acidity. Synchronous optimization of these factors is a big challenge for efficient CDT. Herein, a strategy of comprehensively optimizing Fenton reaction factors was developed for traceable multistage augmented CDT by charge-reversal theranostics. The customized pH-responsive poly(ethylene)glycol-poly(β-amino esters) (PEG–PAE) micelle (PM) was prepared as the carrier. Glucose oxidase (GOx), Fe2+, and pH-responsive second near-infrared (NIR-II) LET-1052 probe were coloaded by PM to obtain the final theranostics. The activity of metastable Fe2+remained by the unsaturated coordination with PEG–PAE. Then tumor accumulation and exposure of Fe2+were achieved by charge-reversal cationization of PEG–PAE, which was further enhanced by a GOx catalysis-triggered pH decrease. Together with the abundant H2O2generation and pH decrease through GOx catalysis, the limiting factors of the Fenton reaction were comprehensively optimized, achieving the enhanced CDT both in vitroand in vivo. These findings provide a strategy for comprehensively optimizing intratumoral Fenton reaction factors to overcome the intrinsic drawbacks of current CDT.

As a type of wound dressings, adhesive hydrogel dressings have been studied widely. However, due to the problems of moisture loss and secondary damage during dressing changes, the clinical application of adhesive hydrogel dressing remains a significant challenge. Herein, we developed a water-retaining and separable adhesive hydrogel wound dressing composed of methacrylated silk fibroin (SFMA), tannic acid (TA), and urethane diacrylate (UDA). The addition of TA with an abundance of catechol groups endowed the hydrogel with improved mechanical properties, good tissue adhesion and hemostasis abilities. Then, a hydrophobic polyurethane diacrylate (PUA) coating encapsulated the hydrogel by UDA polymerization, which could maintain the long-lasting high water content of the hydrogel. Furthermore, due to the adhesion energy being higher than the fracture energy of the hydrogel, it could be separated upon peeling. Finally, the animal experiments indicated that this adhesive hemostatic hydrogel could increase wound healing efficiency by maintaining long-lasting moist environment and being changed without secondary damage. These results showed that the multifunctional hydrogel might be a promising wound dressing for clinical application.

Robot-assisted lobectomy (RAL) is increasingly used as an alternative to video-assisted lobectomy (VAL) for resectable non-small cell lung cancer (NSCLC). However, there is little evidence of any difference in postoperative health-related quality of life (HRQoL) between these two approaches.

Sparse large-scale multi-objective optimization problems (LSMOPs) widely exist in real-world applications, which have the properties of involving a large number of decision variables and sparse Pareto optimal solutions, i.e., most decision variables of these solutions are zero. In recent years, sparse LSMOPs have attracted increasing attentions in the evolutionary computation community. However, all the recently tailored algorithms for sparse LSMOPs put the sparsity detection and maintenance in the first place, where the nonzero variables can hardly be optimized sufficiently within a limited budget of function evaluations. To address this issue, this paper proposes to enhance the connection between real variables and binary variables within the two-layer encoding scheme with the assistance of variable grouping techniques. In this way, more efforts can be devoted to the real part of nonzero variables, achieving the balance between sparsity maintenance and variable optimization. According to the experimental results on eight benchmark problems and three real-world applications, the proposed algorithm is superior over existing state-of-the-art evolutionary algorithms for sparse LSMOPs.

Electronic skin (e-skin) is one of the most important components of future wearable electronic devices, whose sensing performances can be improved by constructing micropatterns on its sensitive layer. However, in traditional e-skins it is difficult to balance sensitivity and the pressure sensing range, and most micropatterns are generally prepared by some complex technologies. Herein, mushroom-mimetic micropatterns with 3D hierarchical architecture and an interdigital electrode are facilely prepared. The micropatterned sensitive layer is further developed through spraying carbon nanotube (CNT) dispersion on the thermoplastic polyurethane (TPU) film with mushroom-mimetic micropatterns (denoted as MMTC). Thanks to the “interlocking effect” between mushroom-mimetic micropatterns and the interdigital electrode in the as-prepared MMTC/interdigital electrode e-skin, the e-skin exhibits a high sensitivity (up to 600 kPa−1), a wide pressure sensing range (up to 150 kPa), a short response time (<20 ms) and excellent durability (15 000 cycles). The MMTC/interdigital electrode e-skin is capable of precisely monitoring health conditions viathe as-acquired physiological parameters in real time. Moreover, such e-skins can be used to monitor gestures wirelessly, sense the trajectory of pressure stimuli and recognize Morse code under water. This study provides a cost-efficient, facile strategy to design e-skin for future-oriented wearable intelligent systems.

Effectively reducing the voltage loss in organic solar cells (OSCs) is critical to improving the power conversion efficiency (PCE) of OSCs. In this study, highly efficient ternary OSCs were constructed by adding a non-fullerene acceptor Qx2 with a high open-circuit voltage (VOC) and low energy loss (Eloss) into PM6:m-BTP-PhC6 based binary devices. The third component Qx2 shows slightly complementary absorption with m-BTP-PhC6 and also optimizes the molecular packing, orientation, and morphology of the active layer. Moreover, the incorporation of Qx2 reduced the energetic disorder and improved the electroluminescence quantum efficiency, which suppresses the Elossand further leads to a higher VOCthan the PM6:m-BTP-PhC6 binary blend. Consequently, synergetic enhancements of VOC, short circuit current (JSC), and fill factor (FF) are realized, resulting in the PCE of 18.60%. This work shows that the selection of the appropriate third component has positive implications for reducing Elossand improving the PCE of OSCs.

Nitrogen-rich zeolitic imidazolate frameworks (ZIFs) are ideal precursors for the synthesis of metal single atoms anchored on N-doped carbon. However, the microporous structures of conventional ZIFs lead to low mass transfer efficiency and low metal utilization of their derivatives. Here, we construct a composite of Co single atoms anchored on nitrogen-doped carbon with a three-dimensional ordered macroporous structure (Co-SA/3DOM-NC) by two-step pyrolysis of ordered macro/microporous ZnCo-ZIF. Co-SA/3DOM-NC shows high activity in the oxidative esterification of furfural, achieving a 99% yield of methyl 2-furoate under mild reaction conditions, which is significantly superior to the microporous and the Co-nanoparticle counterparts. The high activity of Co-SA/3DOM-NC should be attributed to the CoN4centers with high intrinsic activity and the ordered macroporous structure, promoting the mass transfer of reactants and accessibility of active sites.Keywords: Heterogeneous catalysis; Hierarchical pores; Ordered macropore; Oxidative esterification reaction; Single-atom catalysts.

This study explored the content and change trend of osteopontin (OPN) in breast milk and analyzed the relationship between OPN in breast milk and maternal body composition.

Hydrogen sulfide (H2S) sensors are in urgent demand in the field of hermetic environment detection and metabolic disease diagnosis. However, most of the reported room-temperature (RT) H2S sensors based on transition metal oxides/salts unavoidably suffer from the poisoning effect, resulting in the unrecoverable behavior to restrain their application. Herein, copper(II) chloride-doped polyaniline emeraldine salt (PANI-CuCl2) was devised for RT-recoverable H2S detection, where the copper ion (Cu2+) was designed as a partial substitution of protons (H+) in PANI. The prepared gas sensor exhibited full recovery capability toward 0.25–10 ppm H2S, good repeatability, and long-term stability under 80% RH. Meanwhile, the changes of the PANI-CuCl2during the H2S sensing period were analyzed via multiple analytical methods to reveal the reversible sensing behavior. Results showed that doping of Cu2+not only promoted the PANI’s response through the formation of conductive copper sulfide (CuS) and following H+redoping in the PANI but also facilitated the sensor’s recovery behavior because of the Cu2+regeneration under the H+/oxygen environment. This work not only proves the changes of the interaction between the PANI and Cu2+during the H2S sensing period but also sheds light on designing recoverable H2S sensors based on transition metal salts.

Obesity is a global public health problem that endangers human health, and a rapid search for compounds with antiadipogenic activity could provide solutions to overcome this problem. Polyphenols are potential antiadipogenic compounds, but the screening strategy, structure–activity relationship (SAR), and elucidation of their mechanisms of action remain poorly understood because of the high diversity of polyphenols. Lipid rafts, enriched with sphingolipids and cholesterol, are considered a potential target of polyphenols for the regulation of cellular processes and diseases. Here, a novel rapid screening active polyphenol strategy that targets the lipid rafts using molecular dynamic simulation was developed and validated by 3T3-L1 preadipocyte assay. The screening strategy is high-throughput, inexpensive, reagent-free, and effort saving. In addition, the SAR and mechanisms of action mediating the differentiation–inhibition of the preadipocyte by polyphenols were well elucidated by utilizing multiple technologies, such as “raft-like liposomes” systems, giant plasma membrane vesicles, noninvasive lipid raft probes, and ultrahigh-resolution microscopy. High inhibitory-activity polyphenols could penetrate deeper into the hydrophobic lipid center, in an inverted V-shaped manner or by insertion of galloyl groups into rafts, thus disrupting the ordered domain of lipid rafts. In contrast, the medium and low inhibitory-activity polyphenols could only localize on the surface of lipid rafts, exerting slight and the weakest interference with a lipid raft structure, respectively. The combined use of reliable technologies could yield new knowledge on the SAR and the molecular mechanisms of polyphenols.

Supplemental Digital Content is available in the text

Controlling Heating, Ventilation and Air-Conditioning (HVAC) in a way that is both optimal (energy efficient) and adaptive (able to cope with uncertainties) is a recognized challenge in the building sector. This work presents a simple modelling approach to HVAC operation aiming for adaptive and optimal control. The proposed framework exhibits several advantages amenable for implementation in energy management systems: minimum number of parameters to be estimated; preserving the distributed nature of multiple zones in the estimation process; easiness of imposing positivity and controllability constraints on the estimated coefficients. Optimality is addressed using an adaptive linear quadratic control philosophy. Comparisons with Proportional-Integral-Derivative (PID) and non-adaptive controllers show the capability of the proposed framework of coping with uncertainty while delivering nearly optimal controls.

Hyaluronic acid (HA) based hydrogels are one of most functional natural biomaterials in the field of cartilage tissue engineering (CTE). Even with the promising advantages of HA hydrogels, the complicated mechanical properties of the native cartilage have not been realized, and fabricating HA hydrogels with excellent mechanical properties to make them practical in CTE still remains a current challenge. Here, a strategy that integrates hydrogels and nanomaterials is shown to form a HA hydrogel with sufficient mechanical loading for cartilage tissue production and recombination. Cellulose nanofibrils (CNFs) are promising nanomaterial candidates as they possess high mechanical strength and excellent biocompatibility. In this study, we developed methacrylate-functionalized CNFs that are able to photo-crosslink with methacrylated HA to fabricate HA/CNF nanocomposite hydrogels. The present composite hydrogels with a compressive modulus of 0.46 ± 0.05 MPa showed adequate compressive strength (0.198 ± 0.009 MPa) and restorability, which can be expected to employ as a stress-bearing tissue such as articular cartilage. Besides, this nanocomposite hydrogel could provide a good microenvironment for bone marrow mesenchymal stem cell proliferation, as well as chondrogenic differentiation, and exhibit prominent repair effect in the full-thickness cartilage defect model of SD rats. These results suggest that the HA/CNF nanocomposite hydrogel creates a new possibility for fabricating a scaffold in CTE.

Although targeted MAPK pathway inhibition has achieved remarkable patient responses in many cancers, the development of resistance has remained a critical challenge. Adaptive tumor response underlies the drug resistance. Furthermore, such bypass mechanisms often lead to the activation of many pro-survival kinases, which complicates the rational design of combination therapies. Here, we performed global tyrosine phosphoproteomic (pTyr) analyses and demonstrated that targeted MAPK signaling inhibition in melanoma leads to a profound remodeling of the pTyr proteome. Intriguingly, altered cholesterol metabolism might drive, in a coordinated fashion, the activation of these kinases. Indeed, we found an accumulation of intracellular cholesterol in melanoma cells (with BRAFV600Emutations) and non-small cell lung cancer cells (with KRASG12Cmutations) treated with MAPK and KRASG12Cinhibitors, respectively. Importantly, depletion of cholesterol not only prevents the feedback activation of pTyr signaling but also enhances the cytotoxic effects of MAPK pathway inhibitors, both in vitro and in vivo. Together, our findings suggest that cholesterol contributes to the tumor adaptive response upon targeted MAPK pathway inhibitors. These results also suggest that MAPK pathway inhibitors could be combined with cholesterol-lowering agents to achieve a more complete and durable response in tumors with hyperactive MAPK signaling.

Fractals are found in nature and play important roles in biological functions. However, it is challenging to controllably prepare biomolecule fractals. In this study, a series of Sierpiński triangles with global organizational chirality is successfully constructed by the coassembly of l-tryptophan and 1,3-bi(4-pyridyl)benzene molecules on Ag(111). The chirality is switched when replacing l-tryptophan by d-tryptophan. The fractal structures are characterized by low-temperature scanning tunneling microscopy at the single-molecule level. Density functional theory calculations reveal that intermolecular hydrogen bonds stabilize the Sierpiński triangles.