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Fragile X mental retardation protein (FMRP), an RNA binding protein (RBP), is aberrantly hyper‐expressed in human tumors and plays an essential role in tumor invasion, metastasis and immune evasion. However, there is no small‐molecule inhibitor for FMRP so far. In this study, we developed the first FMRP‐targeting degrader based on PROteolysis TArgeting Chimera (PROTAC) technology and constructed a heterobifunctional PROTAC through linking a FMRP‐targeting G‐quadruplex RNA (sc1) to a von Hippel‐Lindau (VHL)‐targeting ligand peptide (named as sc1‐VHLL). Sc1‐VHLL specifically degraded endogenous FMRP via ubiquitination pathway in both mouse and human cancer cells. The FMRP degradation significantly changed the secretion pattern of cancer cells, resulting in higher expression of pro‐inflammatory cytokine and smaller amounts of immunomodulatory contents. Furthermore, sc1‐VHLL, when encapsulated into ionizable liposome nanoparticles (LNP), efficiently targeted tumor site and degraded FMRP in cancer cells. In CT26 tumor‐bearing mouse model, FMRP degradation within tumors substantially promoted the infiltration of lymphocytes and CD8 T cells and reduced the proportion of Treg cells, reshaping the proinflammatory tumor microenvironment and accordingly transforming cold tumor into hot tumor. When combined with immune checkpoint blockade (ICB) therapy, sc1‐VHLL based treatment remarkably inhibited the tumor growth. [ABSTRACT FROM AUTHOR]

Fragile X mental retardation protein (FMRP), an RNA binding protein (RBP), is aberrantly hyper‐expressed in human tumors and plays an essential role in tumor invasion, metastasis and immune evasion. However, there is no small‐molecule inhibitor for FMRP so far. In this study, we developed the first FMRP‐targeting degrader based on PROteolysis TArgeting Chimera (PROTAC) technology and constructed a heterobifunctional PROTAC through linking a FMRP‐targeting G‐quadruplex RNA (sc1) to a von Hippel‐Lindau (VHL)‐targeting ligand peptide (named as sc1‐VHLL). Sc1‐VHLL specifically degraded endogenous FMRP via ubiquitination pathway in both mouse and human cancer cells. The FMRP degradation significantly changed the secretion pattern of cancer cells, resulting in higher expression of pro‐inflammatory cytokine and smaller amounts of immunomodulatory contents. Furthermore, sc1‐VHLL, when encapsulated into ionizable liposome nanoparticles (LNP), efficiently targeted tumor site and degraded FMRP in cancer cells. In CT26 tumor‐bearing mouse model, FMRP degradation within tumors substantially promoted the infiltration of lymphocytes and CD8 T cells and reduced the proportion of Treg cells, reshaping the proinflammatory tumor microenvironment and accordingly transforming cold tumor into hot tumor. When combined with immune checkpoint blockade (ICB) therapy, sc1‐VHLL based treatment remarkably inhibited the tumor growth. [ABSTRACT FROM AUTHOR]

The g-C3N5, characterized by its two-dimensional layered structure, substantial surface area, and narrow bandgap, has found extensive application in photocatalysis. This study involves the incorporation of cerium-doped g-C3N5 with ZnO to form a S-scheme photocatalyst, significantly enhancing the photocatalytic activity of the material. The ZnO/Ce-g-C3N5 composite photocatalyst shows a degradation efficiency for methylene blue (MB) that is 5.0 times higher than that of g-C3N5 and 2.9 times higher than that of ZnO. This superior performance is attributed to the synergistic effect of Ce doping and S-type heterojunction formation, which markedly enhances the separation of photo-induced electron-hole pairs and broadens the light response range, while also maintaining the high redox capacity of the S-scheme ZnO/Ce-g-C3N5 system. The fabrication of this novel photocatalyst holds promising prospects for the treatment of organic pollutants in water. Highlights: A novel S-scheme heterojunction photocatalyst, ZN/Ce–CN, featured a unique nanoparticle/flake coupling configuration. The degradation efficiency of ZN/Ce–CN for MB was 2.9 and 5.0 times greater than that of ZnO and g-C3N5, respectively. Holes (h+) and hydroxyl radicals (•OH) are the predominant reactive species in the photocatalytic degradation process. Ce doping, acting as trapping centers for photogenerated electrons, enhances photo-induce e-/h+ pairs separation and broadens the light response range. [ABSTRACT FROM AUTHOR]

The high exploration and development production capacity of the Jiyang Depression, Bohai Bay Basin, China in the early stage confirms the huge exploration and development potential of shale oil in the study area. Due to the complexity of the depositional mechanism in the study area, the distribution law of fine-grained sedimentary rocks is not well understood, which restricts further exploration breakthroughs. This paper comprehensively observes rock cores and thin sections, combines mineral components, Rock-Eval pyrolysis, rock-cutting logging and logging data to classify lithofacies, and clarifies the distribution law of various lithofacies. The research results show that, according to lithological characteristics, various lithofacies origins are classified into three categories: terrigenous, mixed, and endogenous sources, and six lithofacies types are distinguished: terrigenous low-organic-matter massive siltstone (LF1), terrigenous low-organic-matter massive mudstone (LF2), mixed-source medium-organic-matter massive mudstone (LF3), mixed-source medium-to-high-organic matter laminated-massive mudstone (LF4), mixed-source medium-to-high-organic-matter laminated mudstone (LF5), and endogenous-sourced medium-to-high-organic matter laminated limestone (LF6). The distribution of lithofacies in plane is symmetrical in the east–west direction and is characterized by a banded distribution; the distribution in profile shows a stable depositional process and a continuous depositional sequence. The various lithofacies depositional models have been summarized; the terrigenous input from the northern steep-slope zone has influenced the hydrodynamic conditions of the lake basin, significantly affecting the lithofacies depositional variations from the steep-slope zone to the deep-sag area. The geological evaluation of each lithofacies has been conducted; LF1 + LF4 + LF5 are classified as Class I—target reservoirs for shale oil development, while LF3 + LF6 are considered Class II—favorable reservoirs. The result of the study provide a reference for the classification of fine-grained sedimentary-rock facies and distribution characteristics, and the evaluation of shale-oil-reservoir sweet spots in graben lake basins. [ABSTRACT FROM AUTHOR]

Highly reliable software systems rarely fail during tests because they are usually designed with fault-tolerant mechanisms and tested comprehensively. It is usually difficult to obtain sufficient failure data to carry out reliability measurements by using traditional software reliability models. These models are typically based on probabilistic statistics, and the measurement accuracy cannot be guaranteed with insufficient failure data. We propose a nonparametric bootstrap (NBP) resampling method and six parametric bootstrap (PB) resampling methods to construct software reliability models for small sample conditions based on commonly used models, i.e., the Jelinski–Moranda (J–M), Goel–Okumoto (G–O), Musa–Okumoto (M–O), Schneidewind, Duane and Littlewood-Verrall models. The bootstrap is a statistical procedure that resamples a single dataset to create many simulated samples. Our experimental results on fourteen failure datasets collected from industry and academia show that the proposed models improve by 10.2–18.0% failure time prediction accuracy, 24.7–30.7% curve fitting accuracy, and 7.7–42.9% reliability measurement accuracy compared with the original models. Furthermore, our approaches achieve 58.3–91.1% better failure time prediction accuracy in the case of small sample conditions compared to state-of-the-art machine learning and neural network-based methods. Overall, our approaches can perform more accurate reliability measurements than the original models even in scenarios with limited failure data. [ABSTRACT FROM AUTHOR]

Manipulating the thermal emission in the infrared (IR) range significantly impacts both fundamental scientific research and various technological applications, including IR thermal camouflage, information encryption, and radiative cooling. While prior research has put forth numerous materials and structures for these objectives, the significant challenge lies in attaining spatially resolved and dynamically multilevel control over their thermal emissions. In this study, a one-step ultrafast laser writing technique is experimentally demonstrated to achieve position-selective control over thermal emission based on the phase-change material Ge2Sb2Te5 (GST). Ultrafast laser writing technique enables direct fabrication and manipulation of laser-induced crystalline micro/nano-structures on GST films. Thermal emission can be precisely controlled by adjusting the pulse energy of the ultrafast laser, achieving a high thermal emissivity modulation precision of 0.0014. By controlling thermal emission, the ultrafast laser writing technique enables multilevel patterned processing. This provides a promising approach for multilevel IR thermal camouflage, which is demonstrated with emissivity-modulated GST emitters. Remarkably, ultrafast laser-induced crystalline micro/nano-structures display geometric grating features, resulting in a diffraction-based structural color effect. This study demonstrates the effective use of laser-printed patterns for storing information in both visible and infrared spectrum. [ABSTRACT FROM AUTHOR]

Water resources are crucial for human life. However, current water resource treatment methods have limitations. In this regard, photocatalysis is a promising water resource treatment technology with a simple operation, green environmental protection, and high economic benefits. Therefore, this study prepared a Co-TiO2/Ag3PO4 (CTAP) photocatalyst for the treatment of water resources. Here, a Co-TiO2/Ag3PO4 photocatalyst was prepared using a hydrothermal method combined with calcination. Under visible light irradiation, the methylene blue (MB) degradation degree of CTAP composite reached 96.4% within 14 min, and the degradation rate constant was 0.23516 min–1. These reaction rates are 137 and 3.4 times higher than those of pure TiO2 and Ag3PO4 samples, respectively. Thus, doping and heterojunctions significantly improved the photocatalytic performance of CTAP composites, primarily due to grain size reduction of TiO2 after Co2+ doping. The formation of a close interfacial connection with Ag3PO4 increased the active site of the reaction and promoted the transfer of photogenerated charges, thus improving the photocatalytic performance of CTAP composites. According to the photocatalytic capture experiments of the active species, e-, h+, •O2–, and •OH play a common role in the degradation of MB. This paper provides insights into the design and preparation of a Z-scheme photocatalyst that can be considered for the degradation of pollutants in water. [ABSTRACT FROM AUTHOR]

The concentrations of atmospheric particulate matter and many of its constituents are temporally auto-correlated. However, this information has not been utilized in source apportionment methods. Here, we present a Bayesian matrix factorization model (BAMF) that considers the temporal auto-correlation of the components (sources) and provides a direct error estimation. The performance of BAMF is compared with positive matrix factorization (PMF) using synthetic Time-of-Flight Aerosol Chemical Speciation Monitor data, representing different urban environments from typical European towns to megacities. We find that BAMF resolves sources with overall higher factorization performance (temporal behavior and bias) than PMF on all datasets with temporally auto-correlated components. Highly correlated components continue to be challenging and ancillary information is still required to reach good factorizations. However, we demonstrate that adding even partial prior information about the chemical composition of the components to BAMF improves the factorization. Overall, BAMF-type models are promising tools for source apportionment and merit further research. [ABSTRACT FROM AUTHOR]

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Objectives: This study aimed to investigate the incidence rate and spectrum of gene mutations of Glucose-6-phosphate dehydrogenase (G6PD) deficiency in the Huizhou city of southern China to provide a scientific basis for disease prevention and control in the area. Methods: From March 2003 to December 2022, newborn screening for G6PD enzyme activity was carried out in Huizhou city using the fluorescence quantitative method. Infants who tested positive during the initial screening were diagnosed using the nitroblue tetrazolium ratio method, while a subset of infants received further gene mutation analysis using the multicolor probe melting curve analysis method. Results: A total of 1,291,274 newborns were screened and the screening rate has increased from 20.39% to almost 100%. In the 20-year period, 57,217 (4.43%) infants testing positive during the initial screening. Out of these infants, 49,779 (87%) were recalled for confirmatory testing. G6PD deficiency was confirmed in 39,261 of the recalled infants, indicating a positive predictive value of 78.87%. The estimated incidence rate of G6PD deficiency in the region was 3.49%, which was significantly higher than the average incidence rate of 2.1% in southern China. On the other hand, seven pathogenic G6PD variants were identified in the analysis of the 99 diagnosed infants with the most common being c.1388 G > A (48.5%), followed by c.95 A > G (19.2%), c.1376 G > T (15.2%), c.871 G > A (9.1%), c.1360 C > T (3.0%), c.392 G > T (3.0%), and c.487 G > A (1.0%). Conclusion: The incidence of G6PD deficiency in newborns in the Huizhou city was higher than the southern China average level, while the types and frequencies of gene mutations were found to vary slightly from other regions. Our findings suggested that free government screening and nearby diagnosis strategies could reduce the incidence of G6PD deficiency in the area. [ABSTRACT FROM AUTHOR]

DNA logic circuits (DLC) enable the accurate identification of specific cell types, such as cancer cells, but they face the challenges of weak output signals and a lack of competent platforms that can efficiently deliver DLC components to the target site in the living body. To address these issues, we rationally introduced a cascaded biological amplifier module based on the Primer Exchange Reaction inspired by electronic circuit amplifier devices. As a paradigm, three abnormally expressed Hela cell microRNAs (‐30a, ‐17, and ‐21) were chosen as "AND" gate inputs. DLC response to these inputs was boosted by the amplifier markedly enhancing the output signal. More importantly, the encapsulation of DLC and amplifier components into ZIF‐8 nanoparticles resulted in their efficient delivery to the target site, successfully distinguishing the Hela tumor subtype from other tumors in vivo. Thus, we envision that this strategy has great potential for clinical cancer diagnosis. [ABSTRACT FROM AUTHOR]

DNA logic circuits (DLC) enable the accurate identification of specific cell types, such as cancer cells, but they face the challenges of weak output signals and a lack of competent platforms that can efficiently deliver DLC components to the target site in the living body. To address these issues, we rationally introduced a cascaded biological amplifier module based on the Primer Exchange Reaction inspired by electronic circuit amplifier devices. As a paradigm, three abnormally expressed Hela cell microRNAs (‐30a, ‐17, and ‐21) were chosen as "AND" gate inputs. DLC response to these inputs was boosted by the amplifier markedly enhancing the output signal. More importantly, the encapsulation of DLC and amplifier components into ZIF‐8 nanoparticles resulted in their efficient delivery to the target site, successfully distinguishing the Hela tumor subtype from other tumors in vivo. Thus, we envision that this strategy has great potential for clinical cancer diagnosis. [ABSTRACT FROM AUTHOR]

g‐C3N5 has wide‐ranging applications in photocatalysis owing to its two‐dimensional layered structure, large surface area, and small band gap. In this study, the surface of g‐C3N5 was subjected to inorganic acid modification and combined with BiOCl to form a heterojunction, effectively improving the photocatalytic activity of the material. The rates of degradation of rhodamine B and ciprofloxacin by the 15‐C3N5‐BiOCl composite photocatalyst were 22.2 and 20.7 times higher, respectively, than those of degradation by g‐C3N5. This was attributed to the Z‐type heterojunction formed by g‐C3N5 and BiOCl, which significantly improved the efficiency of photogenerated electron–hole pairs separation and broadened the optical response range. The preparation of novel photocatalysts has broad application prospects in the treatment of organic pollutants in water. [ABSTRACT FROM AUTHOR]

Background: Population-specific variation database of inborn errors of metabolism (IEMs) is essential for precise genetic diagnosis and disease prevention. Here we presented a systematic review of clinically relevant variants of 13 IEMs genes reported among Chinese patients. Methods: A systematic search of the following electronic databases for 13 IEMs genes was conducted: PubMed-NCBI, China national knowledge infrastructure and Wanfang databases. Patient data was extracted from articles eligible for inclusion and recorded in Excel electronic form using a case-by-case approach. Results: A total of 218 articles, 93 published in English and 125 in Chinese, were retrieved. After variant annotation and deduplication, 575 unique patients (241 from articles published in Chinese) were included in the population-specific variation database. Patients identified by newborn screening and symptomatic presentation were 231 (40.17%) and 344 (59.83%), respectively. Biallelic variants were observed in 525/575 (91.3%). Among the 581 unique variants identified, 83 (14.28%) were described ≥ 3 times and 97 (16.69%) were not recorded in Clinvar or HGMD. Four variants were reclassified as benign and dozens of confusing variants deserved further research. Conclusion: This review provides a unique resource of the well-characterized diseases and causative variants that have accumulated in Chinese population and is a preliminary attempt to build the Chinese genetic variation database of IEMs. [ABSTRACT FROM AUTHOR]

The concentrations and sources of particulate matter in the atmosphere are temporally auto-correlated. Here, we present a Bayesian matrix factorization model (BAMF) that considers the temporal auto-correlation of the components (sources) and provides a direct error estimation. The performance of BAMF is compared to positive matrix factorization (PMF) using synthetic Time-of-Flight Aerosol Chemical Speciation Monitor data, representing different urban environments from typical European towns to megacities. We find that BAMF resolves sources better than PMF on all datasets with auto-correlated components, highly cross-correlated components continue to be challenging. However, we demonstrate that adding even partial prior information about the chemical composition of the components to BAMF improves the factorization. Overall, BAMF-type models are promising tools for source apportionment and merit further research. [ABSTRACT FROM AUTHOR]

Cell‐specific aptamers offer a powerful tool to study membrane receptors at the single‐molecule level. Most target receptors of aptamers are highly expressed on the cell surface, but difficult to analyze in situ because of dense distribution and fast velocity. Therefore, we herein propose a random sampling‐based analysis strategy termed ligand dilution analysis (LDA) for easily implemented aptamer‐based receptor study. Receptor density on the cell surface can be calculated based on a regression model. By using a synergistic ligand dilution design, colocalization and differentiation of aptamer and monoclonal antibody (mAb) binding on a single receptor can be realized. Once this is accomplished, precise binding site and detailed aptamer‐receptor binding mode can be further determined using molecular docking and molecular dynamics simulation. The ligand dilution strategy also sets the stage for an aptamer‐based dynamics analysis of two‐ and three‐dimensional motion and fluctuation of highly expressed receptors on the live cell membrane. [ABSTRACT FROM AUTHOR]

Cell‐specific aptamers offer a powerful tool to study membrane receptors at the single‐molecule level. Most target receptors of aptamers are highly expressed on the cell surface, but difficult to analyze in situ because of dense distribution and fast velocity. Therefore, we herein propose a random sampling‐based analysis strategy termed ligand dilution analysis (LDA) for easily implemented aptamer‐based receptor study. Receptor density on the cell surface can be calculated based on a regression model. By using a synergistic ligand dilution design, colocalization and differentiation of aptamer and monoclonal antibody (mAb) binding on a single receptor can be realized. Once this is accomplished, precise binding site and detailed aptamer‐receptor binding mode can be further determined using molecular docking and molecular dynamics simulation. The ligand dilution strategy also sets the stage for an aptamer‐based dynamics analysis of two‐ and three‐dimensional motion and fluctuation of highly expressed receptors on the live cell membrane. [ABSTRACT FROM AUTHOR]

Particulate matter (PM) has become a major concern in terms of human health and climate impact. In particular, the source apportionment (SA) of organic aerosols (OA) present in submicron particles (PM 1) has gained relevance as an atmospheric research field due to the diversity and complexity of its primary sources and secondary formation processes. Moreover, relatively simple but robust instruments such as the Aerosol Chemical Speciation Monitor (ACSM) are now widely available for the near-real-time online determination of the composition of the non-refractory PM 1. One of the most used tools for SA purposes is the source-receptor positive matrix factorisation (PMF) model. Even though the recently developed rolling PMF technique has already been used for OA SA on ACSM datasets, no study has assessed its added value compared to the more common seasonal PMF method using a practical approach yet. In this paper, both techniques were applied to a synthetic dataset and to nine European ACSM datasets in order to spot the main output discrepancies between methods. The main advantage of the synthetic dataset approach was that the methods' outputs could be compared to the expected "true" values, i.e. the original synthetic dataset values. This approach revealed similar apportionment results amongst methods, although the rolling PMF profile's adaptability feature proved to be advantageous, as it generated output profiles that moved nearer to the truth points. Nevertheless, these results highlighted the impact of the profile anchor on the solution, as the use of a different anchor with respect to the truth led to significantly different results in both methods. In the multi-site study, while differences were generally not significant when considering year-long periods, their importance grew towards shorter time spans, as in intra-month or intra-day cycles. As far as correlation with external measurements is concerned, rolling PMF performed better than seasonal PMF globally for the ambient datasets investigated here, especially in periods between seasons. The results of this multi-site comparison coincide with the synthetic dataset in terms of rolling–seasonal similarity and rolling PMF reporting moderate improvements. Altogether, the results of this study provide solid evidence of the robustness of both methods and of the overall efficiency of the recently proposed rolling PMF approach. [ABSTRACT FROM AUTHOR]

The identification of reliability-critical primary input leads (RCPIs) plays an important role in the testing and prediction of reliability boundaries of logic circuits. This article presents a gate-sensitive-attributes-based approach to estimate the criticality of the primary input leads in combinational circuits to their reliability. Oriented to the input vector, a subcircuit-based traversal method marks the critical input leads of each gate in a circuit. Gate-sensitive attributes and a reverse recursive algorithm quantify the effect of each RCPI on circuit reliability under the input vector. A parallel calculation method based on subcircuits with only one primary output reduces the computational complexity to accelerate the calculation process. Similarity-based clustering avoids unnecessary calculations, and a self-adaptive strategy is used to check convergence. Experimental results on benchmark circuits show that the average accuracy of this approach is 0.9634 with Monte Carlo (MC) as the reference and it is 3445 times faster than the MC on average while its average memory cost is 1.67 greater than the MC model. Although the fitness of the worst input vector obtained by other reference methods is 1.09 times better than that of this approach on average, this approach is approximately 21 times faster than that reference method on average. [ABSTRACT FROM AUTHOR]

This article presents a bounded model checking (BMC)-based temperature-aware software-based self-testing (SBST) technique to test worst case delay faults within the highest temperature range. The BMC-based SBST method first defines the sequential constraint. It develops a sequentially constrained automatic test pattern generation (ATPG) to ensure that the generated delay test patterns can emerge in functional mode. It then uses the processor’s multiple-level information to reduce the model complexity, avoid aborts due to time-outs during the BMC process, and generate test programs automatically. A temperature-aware SBST method has then been developed to ensure that the test temperature is within the specified range and test the worst case delays under high temperature. Experimental results demonstrate that the proposed technique achieves an extremely high coverage for delay faults and effectively avoids yield loss caused by the overtesting problem. Its test quality also outperforms that of the existing methods. The generated SBST programs are successful and efficient in testing worst case delay faults under high temperature. [ABSTRACT FROM AUTHOR]

Reliable circuits help prevent artificial intelligence (AI) systems from being corrupted by the soft errors occurred in memories or combinational circuits, which promotes the development of AI security. However, it is a great challenge to measure the reliability of combinational circuits at register transfer level (RTL) rapidly and efficiently. In this paper, a new fast and accurate computational model based on stochastic computation (SC) is presented to meet these objectives. In the proposed approach, the circuit netlists at RTL are parsed to satisfy the requirements of SC on the bitstream structure of the circuits, and then a Sobol sequence‐based algorithm for generating uniform non‐Bernoulli sequences is built to reduce the random fluctuations occurred in probability calculations. After that, an adaptive algorithm based on a MAX–MIN ant system is constructed using graphics processing unit‐based parallel schemes to greatly accelerate the calculation. The experimental results validate our proposed technique, showing that this approach was approximately 51 and 42 times faster than the traditional SC approach and the stochastic computational model (SCM), respectively; its required sequence length was approximately 1.66 times shorter than that of the traditional SC approach, and its relative error was two times smaller than that of the SCM. [ABSTRACT FROM AUTHOR]

Approximate arithmetic circuit (AAC) has emerged as a promising high-performance and energy-efficient circuit paradigm, which can be used in many applications with inherent error tolerance. To guarantee the usability of AACs and the availability of resilient applications, it is necessary to analyze the reliability of AACs. Most current literature focus on the error characteristics of AACs and few methods can be applied to estimate the reliability of AACs. These methods mostly have exponential time complexities and evaluate the average reliability assuming the input combinations are equally likely. In reality, the primary input (PI) signals can be given with any probability from 0 to 1. In this article, we assume that the PIs have random signal probabilities and propose approaches to reliability boundary estimation for AACs. First, we propose a new efficient and accurate method to evaluate the reliability of AACs. The method mainly calculates the AAC reliability for an input vector set, and furthermore, during the calculation, the correlation problem is considered to increase accuracy. Then, based upon the proposed AAC reliability evaluation method, we present the approaches to finding the reliability boundary. Randomly given signal probabilities of every PI, two heuristic search algorithms are utilized to find the lowest reliability. A comparison of the results on three series of AACs and the circuits in the EvoApprox8b library confirms that the proposed reliability evaluation method is more accurate and efficient than the previous method. Further experiments verify the plausibility of the calculated reliability boundary of AACs. [ABSTRACT FROM AUTHOR]

The phonon Boltzmann transport equation combined with first-principles calculation has achieved great success in exploring the lattice thermal conductivity (κ) of various materials. However, the convergence of the predicted κ is a critical issue, leading to quite scattered results recorded in the literature, even for the same material. In this paper, we explore the origin for the convergence of thermal conductivity in two-dimensional (2D) materials. Two kinds of typical 2D materials, graphene and silicene, are studied, and the bulk silicon is also compared as a control system for a three-dimensional material. The effect of the cutoff radius ( r c ) in the third-order interatomic force constants on κ is studied for these three materials. It is found that that κ of these three materials exhibits diverse convergence behaviors with respect to r c , which coincides very well with the strength of hydrodynamic phonon transport. By further analyzing the phonon lifetime and scattering rates, we reveal that the dominance of the normal scattering process gives rise to the hydrodynamic phonon transport in both graphene and silicene, which results in long-range interaction and a large lifetime of low-frequency flexural acoustic phonons, while the same phenomenon is absent in bulk silicon. Our study highlights the importance of long-range interaction associated with hydrodynamic phonon transport in determining the thermal conductivity of 2D materials. [ABSTRACT FROM AUTHOR]

A novel design method of microstrip patch antenna with photonic crystal substrate is proposed and analyzed. The method is different from the traditional one. Early work uses natural materials as the substrate to design microstrip patch antenna. In the work, dielectric cylinder arrays are designed based on periodic waveguide theory to realize the substrates with controllable dielectric constants. Meanwhile, applying dielectric cylinder array and microstrip antenna design theory, we designed and simulated a new type of antenna. The proposed antenna model is compared with homogeneous substrate structure antenna-based microstrip patch antenna and analyzed the radiation characteristics. The consistency of results shows that this method is feasible for antenna design. Afterwards, we fabricated a novel antenna with an equivalent dielectric constant of 2.94, which is further verify the feasibility of the method. Finally, the performance of designed antenna is analyzed with different cylinder height. The results show that the novel antenna design method maybe possess great significance to the design of high-gain miniaturized antenna. [ABSTRACT FROM AUTHOR]

Owing to the great harm that water pollution has caused to the natural environment, the effective treatment of sewage is crucial. In this study, Sm‐TiO2/g‐C3N4 composites were synthesized for the degradation of MB and TC pollutants. The experimental results showed that up to 91.8% and 93.3% of MB and TC pollutants were removed within 120 min of illumination, which were 2.8 and 2.3 times greater than that of pure TiO2, respectively, showing the good optical properties of the composites. Due to the coupling between Sm‐TiO2 and g‐C3N4, the separation of photogenerated electron holes is accelerated, thereby enhancing the photocatalytic activity of the composites. This not only enabled the strong redox ability of TiO2 to be retained, but also effectively promoted electron migration, thus improving the photocatalytic activity of the composites. [ABSTRACT FROM AUTHOR]

There is an increasing interest in the use of polyether ether ketone (PEEK) for biomedical applications. Herein, we have developed silver nanoparticles (AgNPs) decorated PEEK with gelatin (GEL) nanocomposite hydrogel with enhanced antibacterial and biocompatibility through the blending method. The prepared highly porous PEEK/GEL/AgNPs nanocomposite hydrogel was characterized using SEM, TEM, FTIR, and XRD analysis. The SEM image showed that AgNPs were encapsulated in the porous PEEK/GEL hydrogel; within this porous hydrogel, the AgNPs were homogeneously dispersed. Furthermore, the tensile strength, flexural strength, and Young's modulus were 99 ± 2.4 MPa, 154 ± 7.7 MPa, and 2.3 ± 0.1 GPa, respectively, when AgNPs were added to PEEK/GEL hydrogels it exhibited the mechanical performances. The antibacterial assays demonstrate that the AgNPs-decorated PEEK/GEL nanocomposite hydrogel effectively inhibits the antibacterial effect against Gram-negative (Escherichia coli) and Gram-positive (Staphylococcus aureus) bacteria, respectively. Then, MC3T3-E1 cells demonstrated that the AgNPs-decorated PEEK/GEL nanocomposite hydrogel significantly enhanced cell viability and superior alkaline phosphatase (ALP) activity compared with PEEK/GEL hydrogel. This work opens a new avenue of the facile and effective modification of PEEK/GEL/AgNPs nanocomposite hydrogel has increased in vitro antibacterial and biocompatibility properties has great potential to be used as biomedical applications. [ABSTRACT FROM AUTHOR]

Obesity, which is often caused by adipocyte metabolism dysfunction, is rapidly becoming a serious global health issue. Studies in the literature have shown that camellia oil (Camellia oleifera Abel) exerted potential lipid regulation and other multiple biological activities. Here, we aimed to investigate the effects of camellia oil on obese mice induced by a high-fat diet and to explore gut microbiota alterations after camellia oil intervention. The results showed that oral administration of camellia oil dramatically attenuated the fat deposits, serum levels of the total cholesterol, triacylglycerol, low-density lipoprotein cholesterol, fasting plasma glucose, the atherosclerosis index, the hepatic steatosis and inflammation in high-fat diet-induced obese mice. Meanwhile, the high-density lipoprotein cholesterol level in obese mice was enhanced after the camellia oil treatment. Furthermore, 16S rRNA analysis showed that certain aspects of the gut microbiota, especially the gut microbiota diversity and the relative abundance of Actinobacteria, Coriobacteriaceae, Lactobacillus and Anoxybacillus , were significantly increased by camellia oil treatment while the ratio of Firmicutes to Bacteroidetes was decreased. Taken together, our finding suggested that camellia oil was a potential dietary supplement and functional food for ameliorating fat deposits, hyperglycemia and fatty liver, probably by modifying the gut microbiota composition. [ABSTRACT FROM AUTHOR]

The use of aptamers in bioanalytical and biomedical applications exploits their ability to recognize cell surface protein receptors. Targeted therapeutics and theranostics come to mind in this regard. However, protein receptors occur on both cancer and normal cells; as such, aptamers are now taxed with identifying high vs. low levels of protein expression. Inspired by the flexible template mechanism and elegant control of natural nucleic acid-based structures, we report an allosteric regulation strategy for constructing a structure-switching aptamer for enhanced target cell recognition by engineering aptamers with DNA intercalated motifs (i-motifs) responsive to the microenvironment, such as pH. Structure-switching sensitivity can be readily tuned by manipulating i-motif sequences. However, structure-switching sensitivity is difficult to estimate, making it equally difficult to effectively screen modified aptamers with the desired sensitivity. To address this problem, we selected a fluorescent probe capable of detecting G-quadruplex in complicated biological media. [ABSTRACT FROM AUTHOR]

Increasing evidence from experimental studies suggests that the losses of semi-volatile vapors to chamber walls could be responsible for the underestimation of organic aerosol (OA) in air quality models that use parameters obtained from chamber experiments. In this study, a box model with a volatility basis set (VBS) scheme was developed, and the secondary organic aerosol (SOA) yields with vapor wall loss correction were optimized by a genetic algorithm based on advanced chamber experimental data for biomass burning. The vapor wall loss correction increases the SOA yields by a factor of 1.9–4.9 and leads to better agreement with measured OA for 14 chamber experiments under different temperatures and emission loads. To investigate the influence of vapor wall loss correction on regional OA simulations, the optimized parameterizations (SOA yields, emissions of intermediate-volatility organic compounds from biomass burning, and enthalpy of vaporization) were implemented in the regional air quality model CAMx (Comprehensive Air Quality Model with extensions). The model results from the VBS schemes with standard (VBS_BASE) and vapor-wall-loss-corrected parameters (VBS_WLS), as well as the traditional two-product approach, were compared and evaluated by OA measurements from five Aerodyne aerosol chemical speciation monitor (ACSM) or aerosol mass spectrometer (AMS) stations in the winter of 2011. An additional reference scenario, VBS_noWLS, was also developed using the same parameterization as VBS_WLS except for the SOA yields, which were optimized by assuming there is no vapor wall loss. The VBS_WLS generally shows the best performance for predicting OA among all OA schemes and reduces the mean fractional bias from -72.9 % (VBS_BASE) to -1.6 % for the winter OA. In Europe, the VBS_WLS produces the highest domain average OA in winter (2.3 µgm-3), which is 106.6 % and 26.2 % higher than VBS_BASE and VBS_noWLS, respectively. Compared to VBS_noWLS, VBS_WLS leads to an increase in SOA by up to ∼80 % (in the Balkans). VBS_WLS also leads to better agreement between the modeled SOA fraction in OA (fSOA) and the estimated values in the literature. The substantial influence of vapor wall loss correction on modeled OA in Europe highlights the importance of further improvements in parameterizations based on laboratory studies for a wider range of chamber conditions and field observations with higher spatial and temporal coverage. [ABSTRACT FROM AUTHOR]

The advent of SELEX (systematic evolution of ligands by exponential enrichment) technology has shown the ability to evolve artificial ligands with affinity and specificity able to meet growing clinical demand for probes that can, for example, distinguish between the target leukemia cells and other cancer cells within the matrix of heterogeneity, which characterizes cancer cells. Though antibodies are the conventional and ideal choice as a molecular recognition tool for many applications, aptamers complement the use of antibodies due to many unique advantages, such as small size, low cost, and facile chemical modification. This Minireview will focus on the novel applications of aptamers and SELEX, as well as opportunities to develop molecular tools able to meet future clinical needs in biomedicine. [ABSTRACT FROM AUTHOR]

Royal jelly is a nutritious food that has beneficial effects to human health. However, the functional substances remain unclear. Herein, we fractioned the royal jelly proteins of Xinjing black bees according to the Osboren method. Two main proteins from the ethanol‐soluble fraction were purified and identified. RJG‐1 was determined as glucosylceramidase, and RJG‐2 was major royal jelly protein 1 (MRJP1). RJG‐1 showed potent cytotoxicity toward various mammalian cells, and caused quick disruption of cell membranes. With glucosylceramidase activity, RJG‐1 may degrade the glucosylceramide of the cell membranes and disrupt the membrane structure, thereby resulting in cell necrosis. This study extends our knowledge about the composition and function of royal jelly, and is significant for the application of royal jelly. [ABSTRACT FROM AUTHOR]

The advent of SELEX (systematic evolution of ligands by exponential enrichment) technology has shown the ability to evolve artificial ligands with affinity and specificity able to meet growing clinical demand for probes that can, for example, distinguish between the target leukemia cells and other cancer cells within the matrix of heterogeneity, which characterizes cancer cells. Though antibodies are the conventional and ideal choice as a molecular recognition tool for many applications, aptamers complement the use of antibodies due to many unique advantages, such as small size, low cost, and facile chemical modification. This Minireview will focus on the novel applications of aptamers and SELEX, as well as opportunities to develop molecular tools able to meet future clinical needs in biomedicine. [ABSTRACT FROM AUTHOR]

The focus of this modeling study is on the role of ammonia in European air quality in the past as well as in the future. Ammonia emissions have not decreased as much as the other secondary inorganic aerosol (SIA) precursors – nitrogen oxides (NOx) and sulfur dioxide (SO2) – since the 1990s and are still posing problems for air quality and the environment. In this study, air quality simulations were performed with a regional chemical transport model at decadal intervals between 1990 and 2030 to understand the changes in the chemical species associated with SIA under varying land and ship emissions. We analyzed the changes in air concentrations of ammonia, nitric acid, ammonium, particulate nitrate and sulfate as well as changes in the dry and wet deposition of ammonia and ammonium. The results show that the approximately 40 % decrease in SIA concentrations between 1990 and 2010 was mainly due to reductions in NOx and SO2 emissions. The ammonia concentrations on the other hand decreased only near the high-emission areas such as the Netherlands and northern Italy by about 30 %, while there was a slight increase in other parts of Europe. Larger changes in concentrations occurred mostly during the first period (1990–2000). The model results indicate a transition period after 2000 for the composition of secondary inorganic aerosols due to a larger decrease in sulfate concentrations than nitrate. Changes between 2010 and 2030 – assuming the current legislation (CLE) scenario – are predicted to be smaller than those achieved earlier for all species analyzed in this study. The scenario simulations suggest that if ship emissions will be regulated more strictly in the future, SIA formation will decrease especially around the Benelux area, North Sea, Baltic Sea, English Channel and the Mediterranean region, leaving more ammonia in the gas phase, which would lead to an increase in dry deposition. In the north of the domain, the decrease in SIA would be mainly due to reduced formation of particulate nitrate, while the change around the Mediterranean would be caused mainly by decreased sulfate aerosol concentrations. One should also keep in mind that potentially higher temperatures in the future might increase the evaporation of ammonium nitrate to form its gaseous components NH3 and HNO3. Sensitivity tests with reduced NOx and NH3 emissions indicate a shift in the sensitivity of aerosol formation from NH3 towards NOx emissions between 1990 and 2030 in most of Europe except the eastern part of the model domain. [ABSTRACT FROM AUTHOR]

Particulate matter is a component of ambient air pollution that has been linked to millions of annual premature deaths globally1–3. Assessments of the chronic and acute effects of particulate matter on human health tend to be based on mass concentration, with particle size and composition also thought to play a part4. Oxidative potential has been suggested to be one of the many possible drivers of the acute health effects of particulate matter, but the link remains uncertain5–8. Studies investigating the particulate-matter components that manifest an oxidative activity have yielded conflicting results7. In consequence, there is still much to be learned about the sources of particulate matter that may control the oxidative potential concentration7. Here we use field observations and air-quality modelling to quantify the major primary and secondary sources of particulate matter and of oxidative potential in Europe. We find that secondary inorganic components, crustal material and secondary biogenic organic aerosols control the mass concentration of particulate matter. By contrast, oxidative potential concentration is associated mostly with anthropogenic sources, in particular with fine-mode secondary organic aerosols largely from residential biomass burning and coarse-mode metals from vehicular non-exhaust emissions. Our results suggest that mitigation strategies aimed at reducing the mass concentrations of particulate matter alone may not reduce the oxidative potential concentration. If the oxidative potential can be linked to major health impacts, it may be more effective to control specific sources of particulate matter rather than overall particulate mass. Observations and air-quality modelling reveal that the sources of particulate matter and oxidative potential in Europe are different, implying that reducing mass concentrations of particulate matter alone may not reduce oxidative potential. [ABSTRACT FROM AUTHOR]

The design of controllable dynamic systems is vital for the construction of organelle‐like architectures in living cells, but has proven difficult due to the lack of control over defined topological transformation of self‐assembled structures. Herein, we report a DNA based dynamic assembly system that achieves lysosomal acidic microenvironment specifically inducing topological transformation from nanoparticles to organelle‐like hydrogel architecture in living cells. Designer DNA nanoparticles are constructed from double‐stranded DNA with cytosine‐rich stick ends (C‐monomer) and are internalized into cells through lysosomal pathway. The lysosomal acidic microenvironment can activate the assembly of DNA monomers, inducing transformation from nanoparticles to micro‐sized organelle‐like hydrogel which could further escape into cytoplasm. We show how the hydrogel regulates cellular behaviors: cytoskeleton is deformed, cell tentacles are significantly shortened, and cell migration is promoted. [ABSTRACT FROM AUTHOR]

The design of controllable dynamic systems is vital for the construction of organelle‐like architectures in living cells, but has proven difficult due to the lack of control over defined topological transformation of self‐assembled structures. Herein, we report a DNA based dynamic assembly system that achieves lysosomal acidic microenvironment specifically inducing topological transformation from nanoparticles to organelle‐like hydrogel architecture in living cells. Designer DNA nanoparticles are constructed from double‐stranded DNA with cytosine‐rich stick ends (C‐monomer) and are internalized into cells through lysosomal pathway. The lysosomal acidic microenvironment can activate the assembly of DNA monomers, inducing transformation from nanoparticles to micro‐sized organelle‐like hydrogel which could further escape into cytoplasm. We show how the hydrogel regulates cellular behaviors: cytoskeleton is deformed, cell tentacles are significantly shortened, and cell migration is promoted. [ABSTRACT FROM AUTHOR]

Rapid advancement in micro-electromechanical techniques leads to the wide application of wireless sensor networks (WSNs). In a linear WSN (LWSN), all sensor nodes are arranged in a straight line to monitor health status of some linear infrastructure structure such as bridges, highways, pipelines, etc. To enhance reliability of the infrastructure monitoring services, LWSNs are often designed to incorporate a limited number of backbone nodes for transferring or relaying information, leading to a more complex hybrid structure. In this paper, a multivalued decision diagram (MDD)-based analytical approach is proposed to evaluate performance of an LWSN system with backbone nodes. Particularly, we model and analyze the probability that the hybrid LWSN performs at a particular performance level, which is characterized by the number of sensor nodes being able to reach the base station. A single compact MDD model is constructed by sharing all isomorphic submodel structures involved in different performance levels. The MDD model, once being constructed, can be reused for evaluation using different failure time distributions or mission time. A case study is presented to substantiate the application of the proposed MDD approach for developing the optimal backbone node allocation strategy to guarantee the reliability requirement on the infrastructure monitoring services. [ABSTRACT FROM AUTHOR]

Increasing evidence from experimental studies suggests that the losses of semi-volatile vapors to the chamber walls could be responsible for the underestimation of organic aerosol (OA) in air quality models which use parameters obtained from the chamber experiments. In this study, a box model with volatility basis set (VBS) scheme was developed and the secondary organic aerosol (SOA) yields with vapor wall loss corrected were optimized by a genetic algorithm based on advanced chamber experimental data for biomass burning. The vapor wall loss correction increases the SOA yields by a factor of 1.9-4.9, and leads to a better agreement with the measured OA for 14 chamber experiments under different temperatures and emission loads. To investigate the influence of vapor wall loss correction on regional OA simulations, the optimized parameterizations (SOA yields, emissions of intermediate-volatility organic compounds from biomass burning, and enthalpy of vaporization) were implemented in the regional air quality model CAMx (Comprehensive Air Quality Model with extensions). The modeled results from the standard and vapor wall loss corrected VBS schemes, as well as the traditional two-product approach were compared and evaluated by OA measurements from five Aerodyne aerosol chemical speciation monitor (ACSM)/aerosol mass spectrometer (AMS) stations in the winter of 2011. The vapor wall loss corrected VBS (VBS_WLS) generally shows the best performance for predicting OA among all OA schemes, and reduces the mean fractional bias from -72.9 % (with the standard VBS (VBS_BASE)) to -1.6 % for the winter OA. In Europe, the VBS_WLS produces the highest domain average OA in winter (2.3 µ g m-3), which is 106.6 % and 26.2 % higher than the standard VBS and the reference scenario (VBS_noWLS, same parameterization as VBS_WLS, except with the default yields without vapor wall loss correction), respectively. Compared to VBS_noWLS, VBS_WLS leads to an increase in SOA by up to ~ 80 % in Romania. VBS_WLS also leads to a better agreement between the modeled SOA fraction in OA (fSOA) and the estimated measured values in the literature. The substantial influence of vapor wall loss correction on modeled OA in Europe highlights the importance of further improvements in the parameterizations based on laboratory studies with a wider range of chamber conditions and field observations with higher spatial and temporal coverage. [ABSTRACT FROM AUTHOR]

At present, prestress detection is a worldwide problem. Corrosion has an important impact on the accuracy of the stress detection results of prestressed tendons. Once the steel strands in service is corroded, stress corrosion will occur, which seriously affects the safe operation of the prestressed structure. Based on the LC electromagnetic resonance circuit to detect the prestressing force of steel strands, this research has been successfully applied to the detection of the corrosion rate of steel strands, which lays the foundation for the nondestructive detection of the healthy state of steel strands in the existing structure. In this study, the steel strands were regarded as an external inductor embedded in the LC resonance circuit. After the steel strands was corroded, its electromagnetic characteristics would change, and this change was manifested by the resonance frequency. In this paper, the regular change of the resonance frequency caused by the change of the inductance of the steel wire after corrosion was explained theoretically, and a theoretical model of the relationship between the electromagnetic resonance frequency and the corrosion rate was established. In this study, it was proved through experiments that the LC electromagnetic resonance method can accurately detect the overall corrosion degree of bare steel stranded wires, and a fitting formula for corrosion detection of steel stranded wires was established. Through the analysis and exploration of the test data and test phenomena, it has been found that the action mechanism of the stranded wire decreases with the increase of the corrosion rate and the inductance thereof, which leads to the increase of the resonance frequency. The discovery of these laws will provide an improved basis for the prestress detection of in-service steel strands by LC resonant circuits and make the method to be further applied to practical engineering. [ABSTRACT FROM AUTHOR]

Johanson–Blizzard Syndrome (JBS) is a rare autosomal recessive genetic disorder characterized by exocrine pancreatic insufficiency, distinct abnormal facial appearance and varying degrees of growth retardation. Variants in UBR1 gene are considered to be responsible for the syndrome. Here, we describe a 3-year old boy, who visited our clinic for severe growth retardation and frequent oily diarrhea. The physical examination revealed nasal alae aplasia, scalp defect, and maldescent of left testicle. Transabdominal ultrasound and computed tomography scan of his abdomen demonstrated complete fatty replacement of the pancreas. The clinical, laboratory, and imaging findings strongly suggest the diagnosis of hereditary pancreatitis. Whole exome sequencing revealed two rare compound heterozygous variants, c.2511T > G (p.H837Q) and c.1188T > G (p.Y396X), in the UBR1 gene of this boy, so, the diagnosis of JBS was established. This is the first report of Chinese patient with JBS, and our study indicates that transabdominal ultrasound and computed tomography are two useful and noninvasive imaging methods for the diagnosis and evaluation of JBS, and identification of these two novel variants expands the database of UBR1 gene variants. Furthermore, with the availability of the identification technology for these variants, prenatal diagnosis could be offered for future pregnancies. [ABSTRACT FROM AUTHOR]

Protein-dominant cellular processes cannot be fully decoded without precise manipulation of their activity and localization in living cells. Advances in optogenetics have allowed spatiotemporal control over cellular proteins with molecular specificity; however, these methods require recombinant expression of fusion proteins, possibly leading to conflicting results. Instead of modifying proteins of interest, in this work, we focus on design of a tunable recognition unit and develop an aptamer-based near-infrared (NIR) light-responsive nanoplatform for manipulating the subcellular localization of specific proteins in their native states. Our results demonstrate that this nanoplatform allows photocontrol over the cytoplasmic-nuclear shuttling behavior of the target RelA protein (a member of the NF-κβ family), enabling regulation of RelA-related signaling pathways. With a modular design, this aptamer-based nanoplatform can be readily extended for the manipulation of different proteins (e.g., lysozyme and p53), holding great potential to develop a variety of label-free protein photoregulation strategies for studying complex biological events. Optogenetic manipulation of protein localisation in cells involves the creation of fusions that can influence activity. Here the authors develop a near-infrared light-responsive aptamer-based system to regulate the nuclear-cytoplasmic shuttling of NF-κB subunit RelA. [ABSTRACT FROM AUTHOR]

Generating functional tests for processors has been a challenging problem for decades in the very large-scale integration testing field. This paper presents a method that generates software-based self-tests by leveraging bounded model checking (BMC) techniques and targeting, for the first time, out-of-order [out-of-order execution (OOE)] superscalar processors. To combat the state-space explosion associated with BMC, the proposed method starts by combining module-level abstraction-refinement with slicing to reduce the size of the model under verification. Next, an off-the-shelf BMC solver is used on the obtained extended finite-state machines to generate the leading sequences that are necessary to excite internal processor functions. Finally, constrained automatic test-pattern generation is used to cover all structural faults within every function excited by the obtained leading sequences. Experimental results show that the proposed method leads to extremely high fault coverage on the critical components corresponding to OOE operations in functional mode. The method therefore helps in tackling the over-testing problem that is inherent to the full-scan test approach. [ABSTRACT FROM AUTHOR]

Stress loss of prestressed steel strands of existing bridges influences their bearing capacity, so it is of great significance to realize the stress detection. A steel strand that has an inductive property is designed into the resonant circuit, which can realize the stress measurement of the steel strands by testing the resonant frequency. This method is a promising approach for the stress detection of the steel strands. Previous research found that structural stress made the permeability of steel strands change due to the influence of magnetoelastic effect. In the process, the length of steel strands is also changed. Therefore, further research needs to be done to verify the main influence parameter affecting the resonant frequency of the circuit. Furthermore, it is very important to know how the stress affects the resonant frequency to realize the detection of the prestressed force of the steel strands. Therefore, in this paper, the relationship between stress and relative permeability and length is analyzed theoretically, and the theory of stress frequency of steel strands is modified and verified by experiments. The stress-frequency experiments of steel strands and aluminum strands with great difference in relative permeability are carried out. Experiments on stress frequencies of 7-Ф15.20 mm steel strands with different lengths are carried out. The influence of length and permeability parameters on resonance frequency is analyzed. The experimental results show that under the same conditions, the resonant frequencies of steel strands and aluminum strands are almost the same on LC electric circuits, and the resonant frequency decreases linearly with the increase of the natural length of the component and increases linearly with the increase of stress. Consequently, compared with the influence of length change on LC electromagnetic resonance frequency, the relative permeability of the stress change component can be ignored. The stress changes the resonant frequency mainly by changing the length of the strands. [ABSTRACT FROM AUTHOR]

Biofilm poses a serious challenge for the treatment of bacterial infections, as it endows bacteria a pronounced resistance to traditional antibiotics. Antimicrobial peptides (AMPs) are considered potential substitutes for antibiotics. Combinational use of AMPs with other compounds to exert antibiofilm effects has been proved to be an effective means to reduce their toxicity and maximize their antimicrobial activity. However, the combination of various AMPs with different action mechanisms is rarely investigated. A newly designed lytic AMP ZXR-2.3 combined with antibiofilm peptide IDR-1018 or KT2 was tested for the antibiofilm effect on mature Streptococcus mutans biofilms. In general, the combination of ZXR-2.3 + IDR-1018 displayed synergistic effect on both biofilm eradication and bacterial killing, while ZXR-2.3 + KT2 showed no obvious synergism. The confocal images of preformed S. mutans biofilms confirmed the effective bactericidal activity of ZXR-2.3 + IDR-1018. A tube system was applied to investigate the biofilm infection under a flow of medium and SEM images indicated the biofilm disruption and bacterial killing effects of ZXR-2.3 + IDR-1018. Quantitative RT-PCR analysis showed that IDR-1018 induced dramatic changes in the mRNA expressions of the quorum sensing (QS) related genes comC, comD, vicR, and vicK of S. mutans in mature biofilms, whereas the other peptides and ciprofloxacin did not cause obvious changes in these genes. This might explain the better synergism of ZXR-2.3 and IDR-1018. The results of this study provide a potential application using the combination of different AMPs in the treatment of mature biofilm infection. [ABSTRACT FROM AUTHOR]

Source apportionment of organic aerosols (OAs) is of great importance to better understand the health impact and climate effects of particulate matter air pollution. Air quality models are used as potential tools to identify OA components and sources at high spatial and temporal resolution; however, they generally underestimate OA concentrations, and comparisons of their outputs with an extended set of measurements are still rare due to the lack of long-term experimental data. In this study, we addressed such challenges at the European level. Using the regional Comprehensive Air Quality Model with Extensions (CAMx) and a volatility basis set (VBS) scheme which was optimized based on recent chamber experiments with wood burning and diesel vehicle emissions, and which contains more source-specific sets compared to previous studies, we calculated the contribution of OA components and defined their sources over a whole-year period (2011). We modeled separately the primary and secondary OA contributions from old and new diesel and gasoline vehicles, biomass burning (mostly residential wood burning and agricultural waste burning excluding wildfires), other anthropogenic sources (mainly shipping, industry and energy production) and biogenic sources. An important feature of this study is that we evaluated the model results with measurements over a longer period than in previous studies, which strengthens our confidence in our modeled source apportionment results. Comparison against positive matrix factorization (PMF) analyses of aerosol mass spectrometric measurements at nine European sites suggested that the modified VBS scheme improved the model performance for total OA as well as the OA components, including hydrocarbon-like (HOA), biomass burning (BBOA) and oxygenated components (OOA). By using the modified VBS scheme, the mean bias of OOA was reduced from -1.3 to -0.4 µ g m -3 corresponding to a reduction of mean fractional bias from -45 % to -20 %. The winter OOA simulation, which was largely underestimated in previous studies, was improved by 29 % to 42 % among the evaluated sites compared to the default parameterization. Wood burning was the dominant OA source in winter (61 %), while biogenic emissions contributed ∼ 55 % to OA during summer in Europe on average. In both seasons, other anthropogenic sources comprised the second largest component (9 % in winter and 19 % in summer as domain average), while the average contributions of diesel and gasoline vehicles were rather small (∼ 5 %) except for the metropolitan areas where the highest contribution reached 31 %. The results indicate the need to improve the emission inventory to include currently missing and highly uncertain local emissions, as well as further improvement of VBS parameterization for winter biomass burning. Although this study focused on Europe, it can be applied in any other part of the globe. This study highlights the ability of long-term measurements and source apportionment modeling to validate and improve emission inventories, and identify sources not yet properly included in existing inventories. [ABSTRACT FROM AUTHOR]

Residential wood combustion remains one of the most important sources of primary organic aerosols (POA) and secondary organic aerosol (SOA) precursors during winter. The overwhelming majority of these precursors have not been traditionally considered in regional models, and only recently were lignin pyrolysis products and polycyclic aromatics identified as the principal SOA precursors from flaming wood combustion. The SOA yields of these components in the complex matrix of biomass smoke remain unknown and may not be inferred from smog chamber data based on single-compound systems. Here, we studied the ageing of emissions from flaming and smoldering-dominated wood fires in three different residential stoves, across a wide range of ageing temperatures (-10 , 2 and 15 ∘ C) and emission loads. Organic gases (OGs) acting as SOA precursors were monitored by a proton-transfer-reaction time-of-flight mass spectrometer (PTR-ToF-MS), while the evolution of the aerosol properties during ageing in the smog chamber was monitored by a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS). We developed a novel box model based on the volatility basis set (VBS) to determine the volatility distributions of the oxidation products from different precursor classes found in the emissions, grouped according to their emission pathways and SOA production rates. We show for the first time that SOA yields in complex emissions are consistent with those reported in literature from single-compound systems. We identify the main SOA precursors in both flaming and smoldering wood combustion emissions at different temperatures. While single-ring and polycyclic aromatics are significant precursors in flaming emissions, furans generated from cellulose pyrolysis appear to be important for SOA production in the case of smoldering fires. This is especially the case at high loads and low temperatures, given the higher volatility of furan oxidation products predicted by the model. We show that the oxidation products of oxygenated aromatics from lignin pyrolysis are expected to dominate SOA formation, independent of the combustion or ageing conditions, and therefore can be used as promising markers to trace ageing of biomass smoke in the field. The model framework developed herein may be generalizable for other complex emission sources, allowing determination of the contributions of different precursor classes to SOA, at a level of complexity suitable for implementation in regional air quality models. [ABSTRACT FROM AUTHOR]