Moreover, the arrayed Ag@G possesses excellent chemical stability due to the protection of graphitic shell, providing stable plasmonic effect for integrating PTT and surface enhanced Raman scattering (SERS) analysis even in the GOx‐produced H2O2 environment. With in situ SERS identification of bacterial intrinsic signals in the mouse wound model, such SGA realizes superior synergistic antibacterial effect on the infected Escherichia coli, Staphylococcus aureus, and methicillin‐resistant Staphylococcus aureus in vivo, while without causing significant biotoxicity. This system provides a therapeutic method with low resistance and in situ diagnosis capability for efficiently eliminating bacteria.Increasing antibiotic resistance becomes a serious threat to public health. Photothermal therapy (PTT) and antibacterial enzyme‐based therapy are promising nonresistant strategies for efficiently killing drug‐resistant bacteria. However, the poor thermostability of enzymes in PTT hinders their synergistic therapy. Herein, antibacterial glucose oxidase (GOx) is embedded in a Ag graphitic nanocapsule (Ag@G) arrayed silk film to fabricate a GOx‐synergistic PTT system . The SGA system can stabilize GOx by a vitrification process through the restriction of hydrogen bond and rigid  2O2 environment in vivo.Antibacterial glucose oxidase embedded Ag graphitic nanocapsule arrayed silk film‐based efficient enzyme‐synergistic photothermal therapy (PTT) system is rationally designed. Such a versatile system can stabilize the antibacterial activity of enzymes in the hyperthermal PTT environment, while keeping the stable plasmonic effect for integrating PTT and in situ bacterial surface enhanced Raman scattering (SERS) identification in the enzyme‐produced H Photothermal therapy (PTT), as a nonresistant, rapid and effective therapeutic method with great potential for combination therapy, has attracted numerous efforts and possesses tremendous potential for drug‐resistant bacteria elimination. PTT makes use of the plasmonic property of noble metal nanoparticles, such as Au, Ag and Cu, or the calorigenic property of polymers by absorbing light to create a hyperthermia environment. The hyperthermia environment can cause irreversible oxidation of phospholipid layer of bacterial membrane, protein denaturation, cytoplasmic pyknosis and destruction of membrane structure, while without causing drug resistance. High temperature of ≈85 °C is required to realize an antibacterial efficacy of 90 %, and the excessive temperature can cause normal cell necrosis and pro‐inflammatory responses. To minimize these adverse effects, PTT combining plasmonic Ag nanoparticles (AgNPs) or antibiotics‐based synergistic strategies are subsequently developed. However, these synergistic PTT strategies still carry the risk of drug resistance or releasing of silver ions from AgNPs, resulting in unstable PTT effect and undesirable cytotoxicity. Therefore, developing antibiotic‐free, stable nonresistant synergistic method in PTT to minimize adverse effects of PTT is urgently needed.Drug‐resistant bacteria infection has become one of the biggest problems threatening human health.1 Many can attack pathogenic bacteria in diverse pathways, and exhibit great potential in synergistic PTT of bacteria. Among antibacterial enzymes, glucose oxidase (GOx) can continuously consume O2 and catalyze the oxidation of β‐D‐glucose into H2O2 and gluconic acid to realize the antibacterial effect. The produced H2O2 can cause the peroxidation of cell membranes, the oxidation of oxygen scavengers, thiol groups and nucleosides, and the disruption of energy production, enzyme function and protein synthesis. Meanwhile, the oxygen deficiency and lowered pH also affect bacterial growth negatively. Moreover, with the continuous attacking of H2O2, the pathogenic bacteria could be sensitized to heat. Hence, antibacterial enzyme‐based therapy has great potential as the nonresistant synergistic method along with PTT to reduce adverse effects. However, the poor thermostability of antibacterial enzymes cause irreversible unfolding of the tertiary structure to a disordered polypeptide, further seriously hindering their practical application in the hyperthermia environment of PTT. Thus, stabilizing antibacterial enzymes in hyperthermia environment is the key for efficient and nonresistant enzyme‐synergistic PTT.Natural antibacterial enzymes, with low propensity to develop bacterial resistance,10 can The choice of embedding material is critical for the enzyme stabilization. Regenerated silk fibroin (RSF), the main dissociated component of domesticated silkworm cocoons, stands out among different embedding materials in biomedicine field owing to its excellent biodegradability and non‐immunogenic nature. The versatile RSF can be manufactured into different geometries, and show an excellent performance of stabilizing drugs, antibodies, etc. Based on the stabilization in RSF materials, the thermostability of antibacterial enzymes can be significantly increased through physical embedding method, which brings a new opportunity for the synergistic application of nonresistant bactericidal GOx along with the hyperthermal PTT process.Among the enzyme stabilization methods against hyperthermia, physical embedding is rapid, simple and low‐cost comparing to enzyme engineering, chemical modification, crosslinking immobilization methods.15 The2O2 environment. Moreover, such Ag@G possessed excellent surface enhanced Raman scattering (SERS) effect while the SGA system was optical transparent because of the vitrification of silk fibroin. The transparent plasmonic SGA could provide the possibility of in situ bacterial SERS identification for guiding the GOx‐synergistic PTT. The SGA system demonstrated efficient GOx‐synergistic PTT effect on Escherichia coli (E. coli), Staphylococcus aureus (S. aureus), and methicillin‐resistant Staphylococcus aureus (MRSA) in vivo under the guideline of in situ bacterial SERS identification. This GOx‐synergistic PTT system provided an alternative method of stabilizing synergistic antibacterial enzymes in hyperthermal PTT for efficiently eliminating bacterial infection.Herein, we rationally designed and fabricated a GOx‐synergistic PTT system (SGA) for bacterial elimination. The SGA consisted of GOx‐embedded silk film with arrayed plasmonic Ag graphitic nanocapsules (Ag@G). Such plasmonic SGA system could stabilize the embedded antibacterial GOx even in the hyperthermal PTT process to realize a continuous GOx‐synergistic PTT. The Ag@G, with Ag nanoparticle encapsuled in thin graphitic shell, possessed excellent chemical stability, providing stable plasmonic effect for PTT in H fibroin.19 The2Figure  Then RSF hydrogel was mixed with antibacterial enzyme GOx. The RSF hydrogel and mixed RSF‐GOx hydrogel were dried to a pure silk film (SF) and a GOx‐embedded SF (SG) on polystyrene molds through a vitrification process, respectively. After Ag@G array sprayed on SF and SG respectively, transparent plasmonic Ag@G‐arrayed SF (SA) and Ag@G‐arrayed SG (SGA) integrating in situ Raman diagnosis with GOx‐synergistic PTT capabilities were obtained.The fabrication process of SGA was shown in Figure 21 The−1, respectively. Microstructures of Bombyx mori silk  in Figure The ultraviolet–visible (UV–vis) absorption spectrum of Ag@G contained graphitic and Ag plasmonic absorption peaks at 265 and 435 nm, respectively Figure , the resk Figure . The Ag@−1), 1620 cm−1 (green region), and 1698 cm−1 peaks were assigned to β‐sheet, 1645–1655 cm−1 peak (blue region) to random coil/helix, and 1685 cm−1 peak to β‐turn. The absorbance ratios of β‐sheet to random coil/helix were calculated to be 0.876, 0.815, 0.814, 0.760 for SF, SG, SA, and SGA, respectively. The results showed a reduced content ratio of β‐sheet of SG, SA, and SGA, suggesting the interaction of fibroin with embedded GOx and sprayed Ag@G disturbed the formation of β‐sheet. Further mechanical property was assessed on tensile tester  spectroscopy  effect of Ag@G, which endowed it with huge potential for in situ bacteria Raman identification and effective photothermal therapy. The schematic diagram of SERS and photothermal effect of Ag@G was shown in m Figure . Then, pm Figure . As the C Figure . After s Antibacterial enzyme GOx had great potential to be employed in synergistic PTT by consuming glucose and O2 from wounds and producing H2O2. However, the GOx had a poor thermal stability in the hyperthermia environment. Encouragingly, the fibroin‐based SGA could stabilize the activity of GOx by hydrogen bonding and hydrophobic interactions. Schematic diagram of stabilizing antibacterial GOx by SGA in hyperthermal environment was shown in Figure 2O2. Before investigating the stabilizing effect of SF on the GOx, the enzyme‐like activity of Ag@G was tested  and H‐SG (ZDH‐SG) in Figure H‐SG/ZDH‐FG along with the increased RSF/GOx weight ratio revealed a better stabilization of GOx with more fibroin. The RSF/GOx weight ratio of 2000 , demonstrating obvious difference of inhibition zone between H‐SG and H‐FG, was employed in the subsequent experiment. In special PTT process, the temperature need to reach around 85 °C. Hence, the condition of 85 °C photothermal treatment by 808 nm laser irradiation for 1 h was utilized to further investigate the stabilization of GOx  outside the cell wall. Peaks at ≈1445 and ≈1500 cm−1 in the Raman spectra of E. coli attributed to the CH2 deformation of proteins and phenylalanine respectively, while peak at ≈1460 cm−1 in the Raman spectra of S. aureus attributed to CH2 bending vibration of saturated lipids. The results were consistent with previous report that the cell wall of Gram negative E. coli contained more proteins than the Gram positive S. aureus. Therefore, the differences in the Raman signals of E. coli and S. aureus originated from the metabolic differences between different bacterial strains. Relative peak intensity was evaluated by the ratio of I/IG, where I represented the intensity of the bacterial signal peak to be investigated and IG represented the intensity of G band as an internal standard, to minimize potential influence from the inhomogeneity of the plasmonic Ag@G. According to peak position and relative peak intensity, infection types can be distinguished by principal component analysis (PCA)  than that of single enzymatic treatment  or PTT   comparable to SGA, which also verified the stabilization of GOx in SGA. The morphologies of treated bacteria in different groups were characterized by SEM  test  Figure . To veri) Figure . The H‐SM Figure . The celT Figure .Figure S. aureus, E. coli or MRSA were inoculated on wounds respectively. Following the inoculation, various films were attached on the wounds respectively. Then, the SGA group was subjected to SERS diagnosis to identify infection. After SERS identification, single enzymatic therapy of SG, single PTT of SA and GOx‐synergistic PTT of SGA, H‐SGA, and H‐SA‐G were proceeded to evaluate the effects of different therapies in vivo.With excellent synergistic therapeutic effect for bacterial infections in vitro, SGA was further applied to the wound infection model on mice. Schematic diagram illustrating in vivo GOx‐synergistic PTT of bacterial infections was shown in E. coli and S. aureus in the right dotted box region of Figure E. coli, presented in the left dotted box region of Figure  With the superior SERS capability of Ag@G, infected bacteria types on wounds were also identified by means of PCA . AgNPs could accept electron from electron donors, such as graphene oxide, and obtain enhanced catalytic bactericidal capacity, which suggested that Ag@G might have potential long‐term cytotoxicity. Therefore, a 3 d cytotoxicity test of NIH/3T3 cell and a 5 d cytotoxicity test of C3H/10T1/2 cell were implemented using the SA (contain 128 µg Ag@G on SF)  Figure . The res) Figure , and no 32O2‐rich environment due to the protection of graphitic shell, ensuring the robust SERS and photothermal conversion effect. Thermally unstable GOx was stabilized in SGA to obtain thermostability, facilitating the synergistic antibacterial effect of GOx in the hyperthermia environment of PTT. Benefiting from the optical transparency of SGA and plasmonic property of Ag@G, the intrinsic bacterial Raman signal in situ was obtained through the SGA. With in situ bacterial SERS identification and nonresistant GOx‐synergistic PTT effect, the SGA realized more efficient bactericidal effect on E. coli, S. aureus and MRSA in vivo than single PTT and enzymatic therapy, while without causing significant biotoxicity. This proposed GOx‐synergistic PTT system provides unstable therapeutic proteins with new opportunities in hyperthermal environment for efficiently eliminating bacterial infection.In conclusion, we fabricated an efficient GOx‐synergistic PTT system integrating in situ bacterial SERS identification. The Ag@G showed superior stability in the H43), and nutrient agar were purchased from Sinopharm Chemical Reagent Co., Ltd . Luria‐Bertani (LB) broth medium was provided by Beijing AOBOX Bio‐Tech Co., Ltd . Fumed silica, silver nitrate (AgNO3), lithium bromide (LiBr), dipicolinic acid (DPA), and crystal violet (CV) were obtained from Aladdin . Bombyx mori silkworm cocoons were purchased from Guangxi Sericulture Technology Co., Ltd . Horse radish peroxidase , glucose oxidase  and 3,3′,5,5′‐tetramthylbenzidine (TMB) were provided by Sigma‐Aldrich . Gram‐negative Escherichia coli , gram‐positive Staphylococcus aureus  and methicillin‐resistant Staphylococcus aureus  were purchased from Shanghai Luwei Science and Technology Co., Ltd. . Dulbecco's modified Eagle medium (DMEM), trypsin, penicillin‐streptomycin (PS), fetal bovine serum (FBS) and acridine orange/propidium iodide (AO/PI) were purchased from Thermo Fisher Scientific (USA). The mouse embryonic fibroblasts NIH/3T3 and mouse fibroblasts C3H/10T1/2 were obtained from Cell Bank of Chinese Academy of Sciences . The BALB/c female mice (8 weeks old) were obtained from Hunan SJA Laboratory Animal Co., Ltd , and all mice received care under protocols approved by the Institutional Animal Care and Use Committee of Hunan University. Deionized water with a specific resistance over 18.2 MΩ cm−1 was employed throughout the experiment.Citric acid monohydrate, ethanediamine, glucose, sodium bicarbonate  process. Simply, 1 g fumed SiO2 was dispersed into 80 mL methanol solution. After ultrasound for 1 h, 67 mg AgNO3 and 10 µL NCQD solution were added into the mixed solution. After ultrasound for another 2 h, the mixed solution was evaporated to obtain the catalyst powder. Finally, the powder was ground evenly and put into a tube furnace to grow Ag@G at 800 °C for 10 min with a H2 flow rate of 10 sccm. After HF‐etching, cleaning and centrifugation of the mixed powder, the Ag@G nanoparticles were obtained. Bare Ag nanoparticle (AgNP) was synthesized through the method reported previously. The prepared Ag@G and AgNP were also stored at room temperature.Before the synthesis of Ag@G, a N‐doped carbon quantum dot (NCQD) precursor was prepared based on the previous reports.32 Fir First, 10 g natural cocoons were added into 200 mL 0.5 wt% NaHCO3 aqueous solution which was subsequently boiled for 0.5 h and washed for three times. After the boiling and washing process was repeated for three times, the degummed silk was obtained and dried for later use. Then 1 g of degummed silk was cut into pieces and added into 10 mL 9.3 m LiBr solution, and the mixed solution was heated in an oven at 60 °C for 1 h under continuous stirring to dissociate silk fibroin. Next, the dissociated solution was put into a dialysis bag (3 KD) which was put into deionized water for 12 h (deionized water was changed every 3 h) to remove undesired small molecules. After RSF was obtained, a small amount of RSF was taken out to dry and weighed to calibrate the concentration of RSF, and the prepared RSF was stored in a refrigerator at 4 °C. Finally, pure silk film (SF) and silk films with different enzyme contents  were spread out after mixing RSF and GOx at different weight ratios. Whereafter, these SF and SG were put into the microarray dot system (Crysta Core Smartarrayer 48) to spray Ag@G dot matrix to prepare SF‐Ag@G (SA) and SF‐GOx‐Ag@G (SGA) of different specifications.SGA was fabricated by mixing GOx and regenerated silk fibroin (RSF) and spreading the mixed glue into a film. Briefly, RSF was prepared using a previously reported method through series of processes of silk degumming, dissolution and dialysis.35 Fir1 mL Ag@G aqueous solution was used to test the UV–vis absorption spectrum of Ag@G by UV–vis spectrometer , and the size distribution and surface charge of Ag@G were tested on the dynamic light scattering (DLS) instrument . After 8 µL Ag@G aqueous solution was dropped onto the formvar/carbon supported copper grid and dried, the morphology of Ag@G was characterized by transmission electron microscopy (TEM) . SF, SG, SA, and SGA of different specifications were subjected to UV–vis spectrometer to collect transmittance spectra, to infrared spectrometer  to collect infrared spectra and to Raman spectrometer  to collect Raman spectra, then their hydrophilic performances were evaluated on the contact angle measurement instrument (JC2000D2 (RT‐400), POWEREACH, China) and their mechanical properties were tested on the tensile tester . Finally, the morphology of SGA was observed by scanning electron microscopy (SEM) .−6m disinfectant crystal violet (CV) aqueous solution and the mixed aqueous solution of 1 × 10−6m CV and 700 µg mL−1 Ag@G were collected using Raman spectrometer to evaluate the Raman enhancement effect of Ag@G. Then, 50 µL CV of different concentrations  were dropped on SGA (4 mg mL−1 Ag@G) and dried, and their Raman imagings through the films were collected to evaluate the Raman detection sensitivity of SGA.Raman signal spectra of 100 × 10−1) spraying times was investigated by infrared thermal imaging camera (FOTRIC 365). The power of 808 nm laser was 3 W cm−2. To demonstrate the excellent thermal stability of SGA, the photothermal cycling of the SGA with excessive Ag@G  was evaluated by a 5 W cm−2 808 nm laser.The photothermal conversion of SGA with different Ag@G  for 24 h, colonies were transferred to 25 mL sterile Luria‐Bertani (LB) broth medium at 37 °C and cultured to mid‐log phase. After centrifugation and washing for three times, bacterial suspensions with different concentration in PBS were prepared. The concentrations of bacterial suspensions were estimated by flat colony counting method.Gram‐negative m, pH = 6.5) containing 150 × 10−6m glucose, 250 × 10−6m TMB, 1.25 × 10−6 wt% horseradish peroxidase (HRP) and theoretical 0.5 U GOx from SG or free GOx treated with different temperatures for 7 d was immediately put into the UV–vis spectrometer to collect the catalytic kinetics curves at 25 °C. During the collection, absorbance at 635 nm was recorded continuously for 560 s and the absorbance curve was plotted versus time. ΔA635 at 336 s from the linear region of the kinetics curve was assumed as enzymic activity, and enzymic relative residual activity of SG was defined as ΔA635(SG)/ΔA635(GOx). Then, the enzyme activity of SG was evaluated by its inhibitory effect on E. coli and S. aureus. After treated at different temperatures for 7 d, SG  and FP‐GOx  were attached on the nutrient agar medium with the same inoculation number of bacteria, and the diameter D value of inhibition zone was compared to evaluate the enzyme activity. In order to evaluate the GOx stabilization effect of SGA (with GOx inside) and SA‐G (with GOx coated on surface), SGA and SA‐G were subjected to photothermal treatment at 85 °C for 1 h to obtain H‐SGA and H‐SA‐G. Similarly, the inhibition zone diameters of SA, SGA, H‐SGA, and H‐SA‐G were further compared. The bacterial culture medium used above was supplemented with 5 × 10−3m glucose. The free GOx, SG, SGA, H‐SGA were subjected to enzyme kinetics test to calculate the Michaelis constant mK by Lineweaver‐Burk plots.Enzyme activities of GOx in SG and free GOx were assessed by employing glucose as the substrate and monitoring the oxidation rate of TMB. Firstly, the GOx in SG  was released to 1mL phosphate buffer before assessment. Then, 1 mL phosphate buffer (0.1 2). Cell Counting Kit‐8 (CCK‐8) was employed to measure the cell viability of NIH/3T3 cells. First, the infiltrations of SF, SA, SG and SGA (diamter of 20 mm) were extracted through immersing these films in 10 mL DMEM at 37 °C for 24 h respectively. Meanwhile, cells with 100 µL culture medium were seeded into 96‐well plates (10 000 cells each well) and incubated for 24 h to permit cell adhesion. Then, the infiltrations of SF, SA, SG, and SGA were diluted with DMEM to concentrations of 25%, 50%, 75%, 100% respectively. Next, cells were maintained in 100 µL culture medium with or without four different diluted infiltrations for 24 h. Finally, 100 µL fresh cell culture medium containing 10 µL CCK‐8 was added to each well after removal of the supernatant, and the plates were incubated for another 1 h in a dark incubator. The absorbance at 450 nm was measured by a multi‐detection microplate reader  and the assay was repeated for three times. Similarly, The NIH/3T3 cell was continuously incubated for 3 d with SF and SA infiltration respectively, and the C3H/10T1/2 cell was continuously incubated for 5 d with SF and SA infiltration respectively to investigate the long‐term toxicity of Ag@G on SF.The mouse embryonic fibroblasts (NIH/3T3) were cultured in DMEM culture medium supplemented with 1% PS and 10% FBS solution in an incubator  in the 96‐well plate and incubated for 6 h at 37 °C (5% CO2). Then, SF, SG, SA, SGA, H‐SGA, H‐SA‐G  were covered on the nutrient agar. After incubated for 0.5 h in the bacterial incubator, the SGA group were subject to SERS diagnosis in situ. The SERS spectra were assessed by principal component analysis (PCA) to identify different bacterial infections.2 µL 2 × 1011 CFU bacteria and 5 × 10−3m glucose, respectively. After incubation for 0.5 h, the SA group and SGA group were irradiated by laser, and the photothermal temperature was maintained at 60 °C for 2 h. Then, all films were removed, the liquid samples of all groups were centrifuged to isolate bacteria and divided into two parts. One was stained with AO/PI (Acridine Orange/Propidium Iodide), living/dead bacteria were observed at 530/630 nm emission with 488 nm excitation under a fluorescent confocal microscope (FCM) to evaluate the bactericidal effect. Another portion was immobilized with 25% glutaraldehyde aqueous solution for 2 h, and subsequently dehydrated and cleaned with gradient ethanol of 25%, 50%, 75%, and 100%. Then 8 µL ethanol solution of immobilized bacteria was taken out and added to the formvar/carbon supported copper grid. After the copper grid was dried, bacterial morphology was observed by SEM to evaluate the bactericidal mechanism. The antibacterial mechanism was also explored by o‐nitrophenyl‐β‐D‐galactoside (ONPG) test. After different treatments, the groups of blank, SG, SA + laser and SGA + laser were incubated with 2 × 10−3m ONPG for 10 min at 37 °C. Then, the OD420 values of the supernate from these groups were tested.After bacterial identification by SERS diagnosis, SA, SGA, H‐SGA, H‐SA‐G groups were subject a GOx‐synergistic PTT process at 60 °C for 5 min with an 808 nm laser. Then the samples in the wells were respectively dispersed into 5 mL water, and 50 µL dispersing solution was taken out for bacterial growth in plate. After 1 d incubation, the colony count was carried out and the synergistic bactericidal effect was evaluated. GOx‐synergistic PTT effect was also evaluated in bacterial dispersion liquid. SF, SG, SA and SGA were added into 1 mL PBS containing 1 × 108 CFU bacterial cells  was distributed onto the wounds of mice, and SF, SG, SA, SGA, H‐SGA, H‐SA‐G were attached to the wounds respectively. After the mice were housed for 5.5 h, the SERS spectra of SGA group with different bacterial infections and blank group were collected on Raman spectrometer. Then, the SERS spectra were assessed by PCA to identify the two types of infection.First, a full‐thickness cutaneous wound model (diamter of 3 mm) was established on the back of BALB/c female mice (8 weeks old). Then, 2 µL bacterial solution containing 2 × 10−2. Then, the samples from wounds were harvested and dispersed into PBS. Subsequently, the bactericidal effect was assessed by plate colony count.After all groups of mice were fed for 24 h, the SA, SGA, H‐SGA, and H‐SA‐G groups were irradiated with 808 nm laser at 60 °C for 3 min, and the laser power was 1.5 W cm The value of DS was equal to the ratio of the practical activity exhibited by mixtures divided by the sum of the activities of separate components. Based on this definition, the DS of antibacterial effect was calculated in the SGA system by the ratio of the antibacterial effect exhibited by SGA divided by the sum of the antibacterial effect of single enzyme and single PTT.Calculation of the Degree of Synergism: The extent of synergism was quantitatively expressed as “degree of synergism” (DS) in co‐catalytic process of mixed enzymes.37 The+. Then, the contents of Ag+ in different groups were quantitatively analyzed by inductively coupled plasma mass spectrometry (ICP‐MS). By comparing the normalized Ag+ contents (per unit tissue weight) in different groups, the biological distribution of Ag@G and the stability of SGA were evaluated. Meanwhile, the skin and internal organs were stained with hematoxylin‐eosin (H&E) and made into slices. The morphology of the organ cells was observed with a section scanner  to evaluate the biotoxicity of SGA.The above experimental groups were continuously fed for a week, and the body weights of mice were recorded every day. The biocompatibility of the silk composite films was evaluated by comparing the body weight changes of mice. Mice in the SGA group and the blank group were sacrificed after one week of culture, and the SGA on wound, internal organs  and part of the skin adjacent to wound were taken out to be dissolved in concentrated nitric acid by water bath heating. After the dissolution of concentrated nitric acid, the Ag@G in different groups was dissolved into Agt‐test was employed to evaluate the statistical significant difference between groups by GraphPad Prism 6. Results were presented with mean ± s.d. and the significance levels were *p < 0.05, **p < 0.01 and ***p < 0.001, p > 0.05, NS was considered insignificant.First, average value and standard deviation (s.d.) of the results were calculated. Then, two‐tailed The authors declare no conflict of interest.Supporting InformationClick here for additional data file.


Blockchain technology has had a substantial impact across multiple disciplines, creating new methods for storing and processing data with improved transparency, immutability, and reproducibility. These developments come at a time when the reproducibility of many scientific findings has been called into question, including computational studies. Here we present a computational chemistry simulation run directly on a blockchain virtual machine, using a harmonic potential to model the vibration of carbon monoxide. The results demonstrate for the first time that computational science calculations are feasible entirely within a blockchain environment and that they can be used to increase transparency and accessibility across the computational sciences. Blockchain technology has had a substantial impact across multiple disciplines. This study proves that physical simulations can be performed entirely within a blockchain virtual machine. These simulations have improved reproducibility, provenance, and less potential for censorship. However, physical simulations have not previously been performed directly on blockchain virtual machines, and the first simulation of this kind is presented here.Distributed ledger technology has become an area of significant interest since the release of the first blockchain based crypto-currency, Bitcoin, in 2008.1 The details of how proof-of-work operates to maintain these properties have been discussed elsewhere.1,4Open public blockchains aim to create an electronic ledger with a provably tamperproof record of data that is available for anyone to review or add to in perpetuity without the possibility of censorship by a third party. This is carried out principally using a cryptographic hashing function that maps variable length input data to a fixed-length output called a hash. Any change to the input results in an unpredictable change to the hash, and blocks of newly appended data are required to contain a hash of the previous block so that revisions will invalidate the hash of the subsequent block and allow changes to be identified and removed automatically using a process known as “proof-of-work”.et al. examined reproducibility in the psychological scientific literature and found just over a third of the reproduced studies yielded statistically significant results compared to 97% of the original publications, with replication rates of roughly half in cognitive psychology and roughly a quarter in social psychology.5 A 2016 study of the economics literature by Camerer et al. found that ca. 39% of the sampled studies could not be replicated,6 and a 2018 study found that ca. 38% of social and behavioural science papers could not be replicated even when sampled exclusively from the journals Nature and Science.7 A 2008 meta-analysis by Fanelli also indicated that roughly 2% of the scientists surveyed had admitted to fabricating, falsifying or modifying data or results at least once, with roughly a third admitting to “other questionable research practices”,8 further emphasising the importance of replication.Several studies now indicate that a significant amount of the scientific literature cannot be replicated across a wide range of disciplines. In 2015 Aarts 9 harmonic analysis,10 and neuroscience.11,12 Computational replication is often hindered by a lack of access to the original output data, input files, software, hardware, and workflow, which can be difficult to maintain over extended periods of time.13 Reliably storing and accessing data can also be complicated by scientific censorship.14 Many rejections in peer-reviewed journals are due to quality control. However, there is evidence that some journal editors and referees can be hostile to work that challenges their current beliefs,15–22 which can delay or even prevent researchers from gaining access to peer-reviewed archiving services. In extreme cases, governments have also been known to remove or restrict access to the data provided by peer-reviewed journals.23–25Although reproducibility rates are expected to be higher in the computational sciences where simulations made up of a finite set of operations carried out on a deterministic computer allow for bit-for-bit replication, several publications have indicated that replication difficulties persist in fields as diverse as computational chemistry,4 Blockchain based computational science experiments can in principle solve many of the problems discussed for physical simulations by providing an effectively unchangeable record of the computational environment, including the exact piece of software used, a complete record of the associated computational steps, and open access for review and replication. However, computational science experiments using blockchains have not previously been performed. Software has not yet been developed to facilitate this kind of calculation, blockchains are not currently optimized for running these types of calculation, and the computational power of blockchains is still very limited compared to that of most conventional computers.In 2015 the Ethereum network became the first instance of a blockchain acting as a virtual computer capable of performing general computation.26 The simulation was executed for 400 time steps of 0.1 fs with an initial bond length of 120 pm. The model used an equilibrium bond length parameter of 112.8 pm and a force constant of 1855 N m−1, together with the masses of 12C and 16O assigned to the atoms, in order to model carbon monoxide. An equivalent simulation was written using the C# programming language, and executed on a local machine for comparison.In order to prove that physical simulations can be performed using a blockchain, an atomistic molecular dynamics simulation was performed for the carbon monoxide molecule over a 40 fs time scale with a harmonic potential used to model the carbon–oxygen molecular bond. Software compatible with the Ethereum blockchain was written in the Solidity programming language in order to run a diatomic molecular dynamics trajectory with a variation of the velocity Verlet algorithm used to integrate Newton's equations of motion in atomic units.−10 a0. The details of this precision threshold, both algorithms, and their outputs can be found in the ESI.The molecular dynamics trajectories in 1,4 In this case a preliminary trajectory of 10 time steps (1 fs) was run on the Ethereum blockchain prior to the main production run. The two trajectories have been recorded in blocks 9 360 161 and 9 360 178, respectively. This information provides an effective time stamp showing the order in which these simulations were performed. The output data and blockchain address of the preliminary simulation are also given in the ESI,Timing when experiments occur can also be important for a number of reasons. When similar discoveries are made by independent researchers, the claims to the discoveries are often adjudicated based on when the specific observations or calculations were made, with famous examples including the controversy between Leibniz and Newton over who invented calculus. Knowing the order in which experiments were carried out is also useful when analyzing methods of hypothesis testing and conclusion formation that can differ depending on the order in which observations happen. An important property of many blockchains, including Ethereum, is therefore the creation of an internal chronology. New blocks are appended regularly, and the designed immutability of old data means that the position which calculations have in the blockchain acts as an automatic time stamp that can be used to verify the order in which they were performed. The computational complexity of solving the hashing function needed to append data is also commonly modified to give a regular time interval between blocks that can be used to approximate timings between different blockchains.ca. 11 s compared to a ca. 135 ms execution time for the C# simulation when executed on a standalone desktop machine running with a i7-4790k CPU and 32 GB of 1333 MHz DDR3 RAM. Each simulation was also recorded in a single block so as to avoid the need for manual interaction with the blockchain during their execution. While the exact computational power of the Ethereum network is variable, the network has a fixed limit to the maximum amount of computation that can be performed as part of generating a single block. This computational limit is measured in units known as gas, and is currently set at 10 000 000 gas at the time of writing. A more detailed description of the relationship between gas and computational operations can be found in the ESI18 operations per second earlier this year. Significant advancements in blockchain computer science and developments in combining “on-chain” and “off-chain” calculation data are therefore necessary before blockchain calculations can become a routine method for performing computational experiments.The complexity and length of these simulations are currently limited by the capacity of the available blockchains. The Ethereum block for the production simulation was generated in These results show that simulations of this kind are possible and that there can be significant benefits to using blockchains for computational science. The ability to run computational experiments with the properties outlined is expected to have an increasing impact across the computational sciences as the capacity of these blockchains continues to scale, and current plans to introduce blockchain database sharding to the Ethereum network are expected to produce a greater than 1000 fold increase in the computational throughput in the near future. Furthermore, running hybrid computational experiments that use blockchain based calculation and storage for certain parts of an experiment, and conventional off-chain computers for others, may allow some of these advantages to be introduced selectively at a significantly reduced computational cost.The authors declare no competing financial interest.SC-011-D0SC01523G-s001


Upon iridation, the metallo-peptidic construct displayed activity in catalytic hydrogenation that outperforms small molecule analogues and which is dependent on the peptide sequence, a typical feature of metalloenzymes.Inspired by the boom of new artificial metalloenzymes, we developed an Fmoc-protected histidinium salt (Hum) as N-heterocyclic carbene precursor. Hum was placed  A non-natural histidinium amino acid has been developed and used for solid-phase peptide synthesis to construct a peptide iridium carbene conjugate as artificial mini-peptide for hydrogenation catalysis. Therefore, the histidinium salt Fmoc-Hum-OH  and two aromatic resonances at δH 6.87 and 8.31 for Hδ and Hε, respectively. Derivatization of Fmoc-Hum-OHviaHum–OMe with (S)-Mosher's acid indicated at least 95% retention of enantiopurity  in the central position (16 coupling of Fmoc-Hum-OH required longer reaction times (5 vs. 1–2 h) to reach completion (TNBS control). Also, coupling of the subsequent Ala was performed twice to reach optimal results. Subsequent introduction of X and A proceeded again according to standard protocols.position . To test−1 pre-loading). Identity and purity were analyzed by high-resolution ESI-MS, LC–MS and NMR spectroscopy (†). For example, for the sequence ASAḦASA with two Ser and Hum and alternating Ala, 1H–1H COSY identified the Hum CαH-proton as a distinct triplet at δH 4.61, which is well-separated from the CαH-protons of the other amino acids (δH 4.18–4.35). The Hum Hδ and Hε appeared as singlets at δH 7.17 and 8.52 ppm, respectively. The presence of just one set of signals in the 1H and 13C NMR spectra indicate the presence of just one isomer, suggesting that either the d-Hum epimer is not distinguishable by NMR analysis  or that only the l-enantiomer is incorporated into the peptide.TFA-mediated cleavage of the heptapeptide followed by revers-phase HPLC purification yielded the apo-peptides sub-gram quantities . Analysis by HR-MS revealed a most significant signal for [AXAḦAXA–Ir –2Cl]2+ for all peptides except for the Lys-containing heptamer, for which z = 3 due to the basic side chain (†). The NMR spectra of these systems were consistently very broad, though they clearly revealed the Cp* proton signals around 1.6 ppm in the correct integral ratio. Depending on the amino acid sequence, this signal is split in two or more different signals, which however coalesce to a single resonance at 50 °C. Therefore, the different Cp* signals were attributed to distinct rotamers that show restricted interconversion due to the metal fragment bound to Hum, rather than epimers.Analysis by LC–MS of crude samples after resin cleavage revealed only partial metalation, which was attributed to partial hydrolytic Ir–C bond scission in the resin cleavage step due to the presence of TFA rather than to an incomplete metalation. Revers phase HPLC purification yielded the pure peptidic scaffolds AXAḦAXA–Ir constructs showed activity in the hydrogenation of acetophenone as model substrate, albeit without any enantiomeric excess (ee < 3%). Reminiscent to metalloenzymes, the activity of the heptapeptide shows considerable dependence on the type of amino acids in close proximity to the active site (−1) and X = Y .¶¶Chiral GC analysis indicated that the benzyl alcohol was obtained as a racemate in all catalytic runs, which can be rationalized by the fact that the catalytic site is extremely exposed in all modelled structures. Some general trends from this initial activity screen can be deduced. For example, aromatic side chains  have a positive effect on the catalytic activity, possibly because of suitable interactions with the substrate. Potentially coordinating side chains reduce the activity  or induce an induction period . Bulkiness of the side chain has some inhibiting effect , yet this effect was not observed in hydrophobic side chains. These variations indicate that these mini scaffolds can be tailored despite their small size. Moreover, the oligopeptide backbone is highly relevant for the catalytic activity as the iridium-complex 1 bound to protected Hum or a simple NHC iridium analogue (2) showed much lower activity and reached a modest <20% conversion after 24 h  under identical reaction conditions .Since NHC iridium complexes are established hydrogenation catalysts, we investigated the activity of this minimalistic peptidic scaffolds in catalytic hydrogenation in citrate buffer at pH 3. All 17 While neither the root mean square deviation of the conformational changes of the heptapeptide nor the number of clusters from the simulations correlate with the catalytic activity, the histidine exposure revealed a positive correlation with the TOFmax . The peptides were modelled initially with His rather than the Hum–Ir in central position. The Hum–Ir was then constructed as a constrained entity based on reported crystal structure data using the UCSF Chimera software. The conformational changes of the metal-free heptapeptides in 20 ns intervals indicate that despite their short size, most heptapeptides adopt stable secondary structures , data curation  data analysis, validation, visualization, and writing .The authors gratefully acknowledge generous financial support from the ERC (CoG 615653) and the Swiss National Science Foundation (20020_182663 and 200021_192274).There are no conflicts to declare.CC-057-D1CC03158A-s001CC-057-D1CC03158A-s002CC-057-D1CC03158A-s003


The WNT (Wingless/Integrated) signaling pathway is implicated in various stages of glioblastoma, which is an aggressive brain tumor for which therapeutic options are limited. WNT has been recognized as a hallmark of therapeutic challenge due to its context-dependent role and critical function in healthy tissue homeostasis. In this review, we deeply scrutinize the WNT signaling pathway and its involvement in the genesis of glioblastoma as well as its acquired therapy resistance. We also provide an analysis of the WNT pathway in terms of its therapeutic importance in addition to an overview of the current targeted therapies under clinical investigation.  WNT (Wingless/Integrated) signaling regulates key cellular events during the development of the central nervous system. Particularly, it regulates self-renewal, differentiation, migration and signaling of neural stem cells in the fetal ventricular zone, the postnatal subventricular zone and the hippocampus ,2. It haWNT signaling operates through a group of signal transduction pathways that pass signals from outside of the cell through cell surface receptors into the cytoplasm and then into the nucleus . Three W2+-dependent transcription factor that is down stream of this pathway, is highly expressed in GBM where it regulates invasion [The non-canonical planar cell polarity pathway is initiated by the binding of WNT proteins to FZD; the signal is then transduced to DVL, which subsequently activates the GTPases Rho and Rac. Rac then activates c-Jun N-terminal kinase-dependent transcription and Rho activates Yes-associated protein/Transcriptional Co-activator with PDZ-biding Motif-dependent transcription . Since tinvasion .Recent efforts have been spent on targeting the β-catenin/TCF4 complex, i.e., the catenin responsive transcription (CRT), with an expectation to inhibit its downstream signaling. The CRT complex interacts with several gene regulators through a conserved mechanism, thus raising questions about the specificity of this approach. One recent study reports the discovery of inhibitor iCRT-3, which targets the CRT complex . While tGlioblastoma multiforme (GBM) is recognized as the most aggressive primary malignant brain tumor with a median survival of only 12–18 months upon diagnosis . The staGBM tumors display a high degree of complexity in terms of heterogeneity and cellular stratification—this indicates genomic and molecular diversity profiles of tumors ,27,28. PDespite accounting for less than 1% of cells within any given GBM tumor, cancer stem cells known as glioma stem cells (GSCs) have been associated with the origin and recurrence of GBM . These tThe WNT pathway, along with Notch, Hedgehog, RAS/RAF/MAPK and PI3K/Akt/MTOR, constitute the main signaling transduction pathways that confer stemness in GBM . NSC devWNT5A, a non-canonical WNT molecule, increases neural differentiation and is expressed during NSC proliferation ,55. ShRNThe canonical WNT pathway and the non-canonical (β-catenin-independent) WNT pathways are involved in promoting components of the epithelial-to-mesenchymal transition (EMT), a complex process that describes a pattern of phenotypic changes observed during embryonic development and regeneration. The EMT program, which has a role in metastasis, is hardly ever fully executed in solid tumor cells. Executing the endpoint of the transition would presumably result in differentiation, which generally follows the EMT events that occur during embryogenesis, and therefore a reduction in adaptive potential ,40. EMT-2+ and planar cell polarity pathways [2+ pathway [As previously stated, the non-canonical signaling predominantly activates the WNT/Capathways ,68. Thespathways ,69. The pathways . The uti pathway . In a st pathway .The capacity for aberrant WNT signaling to initiate and maintain stem-like characteristics in a subset of GBM tumor cells implicates this system in the onset, progression and recurrence of GBM, although the extent to which it is involved in each stage is highly variable among patients and within tumors. Although tumorigenic cells from GBM tissue will be enriched with WNT-dependent GSCs, subpopulations of GSC that are not functionally reliant on WNT signaling have been observed in GBM samples. Nevertheless, WNT-dependent GSCs are a pharmacologically relevant subpopulation of cells, as they are more associated with an aggressive phenotype . WNT sigThe importance of viewing the WNT system as a highly conserved means of cellular communication cannot be understated. The implications of an aberrant communication system extend at the very least to non-tumor cells in the tumor microenvironment, which is a crucial factor in cancer progression. Exposing microglial cells, which are common in the tumor microenvironment, to GBM-conditioned medium results in an increase in WNT3A expression and cell viability . GBM-der+ GSCs [WNT signaling has a role in many of the most pernicious characteristics of GBM, including resistance to therapeutics. Similar to GBM onset and progression, the inevitable recurrence after stand-of-care treatment is thought to be primarily mediated by GSCs. Cancer Stem cells CSCs, as well as normal stem cells, naturally possess an increased capacity for DNA repair and predisposes them to preferentially survive therapeutics that target DNA . Another+ GSCs . The WNTThe methylation status of O6-methylguanine-DNA methyltransferase (MGMT) is perhaps the most important epigenetic marker in the context of GBM treatment options. One of the predominant TMZ-induced DNA adducts, O6-methylguanine, is repaired by this mismatch repair protein ,89. TOPFAutophagy can operate as a pro-survival mechanism that assists in the TMZ resistance of GBM cell lines . ATG9B, WNT pathway proteins have been considered an attractive and validated cancer target for its critical roles in tumorigenesis and cancer progression as described above. Over the past decade, much effort has been made to develop WNT pathway inhibitors, some of which have been tested in clinical studies ,96. HoweVantictumab is a human IgG2 monoclonal antibody that binds Frizzled (FZD) receptors 1, 2, 5, 7 and 8 in the WNT signaling pathway and thereby prevents the activation of canonical WNT signaling . This anIpafricept is a recombinant fusion protein comprising the FZD8 cysteine-rich domain (CRD) fused to the human Fc domain . This fuThe radioimmunoconjugate drug, 90Y-OTSA101, comprises a humanized monoclonal FZD10 antibody OTSA101 labelled with 90Y . RadioacPORCN is a membrane-bound O-acyltransferase (MBOAT) involved in the posttranslational modification of WNT ligands, which is an important step for WNT ligand secretion. Therefore, the development of small molecule inhibitors that block PORCN have gained increasing attention. WNT974 (LGK974) is a first-in-class PORCN inhibitor that was shown to be potent and efficacious in multiple tumor models . In an oETC-159 is an orally administered and potent porcupine inhibitor that has shown preclinical efficacy in combinations with phosphoinositide 3-kinase (PI-3K) inhibitors and poly (ADP-ribose) polymerase (PARP) inhibitors ,111. ETCFLT3-mutant AML [PRI-724 is a first-in-class inhibitor of the interaction between β-catenin and its coactivator CBP. PRI-724 potently disrupts β-catenin interaction with CBP, thereby inhibiting acute myeloid leukemia (AML) cells and synergizing with FLT3 inhibition in tant AML . It alsotant AML ,118. A rtant AML . In a phtant AML ,121. Thetant AML , may mittant AML , will fuIn addition to the canonical WNT pathway targets, non-canonical WNT pathways are emerging as a new cancer target. One of the β-catenin-independent WNT pathway targets is a co-receptor for WNT ligands, ROR1 . ROR1, aCirmtuzumab is a humanized monoclonal antibody that targets ROR1. Treatment with Cirmtuzumab and ibrutinib was shown to be highly effective in clearing leukemia cells in vivo . Moreoven = 7/15) of patients with mantle cell lymphoma (MCL) and 80% (n = 4/5) of patients with diffuse large B-cell lymphoma.VLS-101 is an antibody-drug conjugate (ADC) for suppressing ROR1-positive cancers. VLS-101 comprises UC-961 (Cirmtuzumab), which is a maleimidocaproyl-valine-citrulline-para-aminobenzoate (mc-vc-PAB) linker, and the anti-microtubule cytotoxin monomethyl auristatin E (MMAE). VLS-101 dramatically decreased tumor burden in all Richter syndrome-colonized tissues and significantly prolonged survival in mouse models . RecentlAnother ADC for ROR1 is NBE-002; NBE-002 has recently entered clinical trials to evaluate its safety and efficacy in patients with triple negative breast cancer and other solid tumors. NBE-002 uses a novel anthracycline payload which has been shown to induce a long-lasting anti-tumor immunity in preclinical models of solid tumors. Interestingly, the first chimeric antigen receptor (CAR) T-cell therapeutic for ROR1 developed by BMS/Celgene has entered a clinical trial . AdditioFor successful WNT pathway drug development, strategies to reduce normal cell toxicity and selectively kill cancer cells are necessary. Additionally, overcoming the unique challenges of targeting the CNS will require novel improvements to drug modalities and precise clinical trial design. As genomics, epigenomics, proteomics and related fields evolve, new drug targets derived from the discovery of unique molecular characteristics of WNT signaling in GBM will supply researchers with more options for treating this devasting condition. Testing new targets to identify untapped opportunities for WNT pathway therapies may help mitigate the negative impacts on tissue homeostasis and regeneration. Previous WNT pathway inhibitors have largely relied on antibodies and small molecules. Given the recent clinical data on ROR1-ADC, new modalities, such as ADC, CAR-T, CAR-NK and proteolysis targeting chimera (PROTAC), provide promising approaches that will either provide better patient outcomes or at least produce valuable data that will ultimately guide researchers to improved treatment solutions.


Music has been a therapeutic strategy proposed to improve impaired movement performance, but there remains a lack of understanding of how music impacts motor cortical activity. Thus, the purpose of this study is to use a time–frequency analysis  of electroencephalographic (EEG) data to determine differences in motor and auditory cortical activity when moving to music at two different rates. Twenty healthy young adults tapped their index finger while electroencephalography was collected. There were three conditions (tapping in time with a tone and with two contrasting music styles), and each condition was repeated at two different rates (70 and 140 beats per minute). A time–frequency Morlet wavelet analysis was completed for electrodes of interest over the sensorimotor areas  and the primary auditory areas . Cluster‐based permutation testing was applied to the electrodes of interest for all conditions. Results showed few differences between cortical oscillations when moving to music versus a tone. However, the two music conditions elicited a variety of distinct responses, particularly at the slower movement rate. These results suggest that music style and movement rate should be considered when designing therapeutic applications that include music to target motor performance. This exploratory study sought to understand how music influenced sensorimotor activity. Results revealed that the style of music and movement rate had the greatest impact on differences in sensorimotor cortical oscillations. Thus, music style and movement rate are components to consider in the development of therapeutic strategies using music to improve movement performance. No intent was made to recruit musicians or non‐musicians for this project, rather a representative population of healthy young adults. However, information about previous music experience was collected. See Table 2.2Methods for this study have previously been reported  was placed on the dorsum of the index finger. Electromyography (EMG) sensors were placed on the first dorsal interosseous (FDI) and the extensor digitorum communis (EDC) . EMG signals were recorded at a sampling rate of 2048 Hz, bandpass filtered in a range from 20–500 Hz, and notch filtered at 60 Hz . Both the position and EMG data were used to determine movement onset. EEG was also recorded at a sampling rate of 2000 Hz using a 64‐channel unit conforming to the international 10–20 system .2.4https://github.com/Neuro‐Tools. Initially, data was inspected and all excessively noisy and/or faulty channels were removed from analysis. The EEG data were then down sampled to 256 Hz and re‐referenced using an average reference. Data were filtered using a dual‐pass Butterworth filter with a passband of 0.1 to 30 Hz and a notch filter at 60 Hz. Following this, a restricted Infomax independent components analysis (ICA) was conducted to identify ocular artifacts  around movement onset (determined by EMG onset of the FDI) for each condition and were baseline corrected from −500 to −300 ms (the 70 BPM condition) or −300 to −100 (the 140 BPM condition). For each condition, the number of epochs depended on the number of times the participant tapped. As such, for the 140 BPM conditions, this produced an average of 85 epochs per participant per condition  while in the 70 BPM conditions this produced an average of 43 epochs per participant per condition . Finally, all segments underwent an artifact rejection algorithm that removed segments that had gradients greater than 30 μV/ms and/or a 150 μV absolute within‐segment difference Luck, . The arthttps://github.com/Neuro‐Tools), adapted from Cohen  was baseline corrected between −500 and −300 ms pre‐movement onset. In contrast, the Fast tapping condition (140 BPM) was baseline corrected using a window of −300 to −100 ms pre‐movement onset. We choose these separate baselines for the Slow and Fast conditions due to the possible overlap of previous finger taps in the Fast tapping condition if −500 to −300 ms had been used. The baseline procedure was divisive.2.5https://github.com/Neuro‐Tools). In order to compute the permutation test, at each time point and frequency, the average EEG activity across each condition for each participant were computed. We compared the following conditions: (1) Activating and Tone Only, (2) Relaxing and Tone Only, and (3) Activating and Relaxing. This was repeated across both the Slow (70 BPM) condition and the Fast (140 BPM) condition. That is, for each of the three comparisons, we took the participant averages for each condition, and then randomly permutated the condition labels across the averages for each time and frequency. After this, repeated measures t‐tests were computed at each point for each permutation. From this random distribution, the most negative and most positive  observations were chosen. Clusters were then defined as continuously significant cells across both time and frequency. This process of extracting the clusters of the random permutations across time and frequency was repeated 1000 times. This led to the creation of a distribution of the most extreme random t‐scores  across both time and frequency. Repeated measures t‐tests at all time points and frequencies for our own data were completed. That is, using the participant's observed (non‐permuted) average for each of the three comparisons , we ran repeated measures t‐tests across all time points and frequencies and any clusters that were larger than the 95‐percentile of the null hypothesis from the permutation test were kept. As per above, this was repeated across both the Slow (70 BPM) and Fast (140 BPM) conditions. In order to avoid edge artifacts due to smearing, a permutation window that was between −300 and 800 ms was chosen. After extracting the data, the outputs were z‐score corrected for each individual condition and participant by taking each data point  in each condition and subtracting the mean and standard deviation of all conditions and data points. Specifically, this normalization occurred individually for each condition music and pace condition  within each participant.A cluster‐based permutation testing was applied to all conditions  for all comparisons from the standardized data.The cluster‐based permutation test for all six comparisons was completed for the following electrodes of interest: three frontal electrodes , three central electrodes , and two temporal electrodes  =2.67,p<.02,d=0.59). No other differences were revealed for frontal, temporal or the remaining central electrodes within the 70 BPM tapping condition. For the 140 BPM tapping condition, differences were revealed over electrode FCz. The Relaxing condition had higher power than the Tone Only condition between 8 to 30 Hz from −300 to 800 ms =2.12,p<.05,d=0.48). A difference at electrode Cz for the 140 BPM condition was also observed. The Relaxing condition had higher power than the Tone Only condition between 8 and 30 Hz from −300 to 800 ms =2.65,p<.05,d=0.59). No other differences were revealed for central, temporal, or the remaining frontal electrodes at 140 BPM =2.81,p<.02,d=−0.58). In addition, for the 70 BPM music, a difference at electrode T7 was found. The Activating condition had lower power than the Relaxing condition between 2 and 13 Hz from −40 to 788 ms =2.65,p<.02,d=−0.59). There were no other differences across any of electrodes in the 70 BPM music. For the 140 BPM condition, a number of differences were also revealed. Over electrode FC3, the Activating condition had lower power between 17 to 30 Hz from −300 to 350 ms =2.76,p<.05,d=0.62).For electrode Cz, the Activating condition had lower power than the Relaxing condition between 3 and 30 Hz from −276 to 800 ms at electrode Cz =2.62,p<.02,d=−0.59). There were no other differences for any other electrodes for the 140 BPM condition  and the alpha and beta band over electrode Cz (140 BPM). This is in keeping with our previous study that showed a significant increase in beta band power at 70 BPM and a significant increase in alpha band at 140 BPM when comparing both music conditions to the Tone Only condition . For those comparisons, significant differences occurred in electrodes FC3 (140 BPM), Cz (140 BPM), C4 (70 BPM),and T7 (70 BPM). Previous research has suggested that music style may impact sensorimotor activity  Relaxing (left) and Tone‐Only (right) at electrode FCz, (b) Activating (left) and Relaxing (right) at electrode C4, (c) Activating (left) and Relaxing (right) at electrode T7.Click here for additional data file.Supplemental Figure 2. Conditional Wavelets for 140 BPM. (a) Relaxing (left) and Move (right) at electrode C3, (b) Relaxing (left) and Move (right) at electrode Cz, (c) Activating (left) and Relaxing (right) at electrode FC3, (d) Activating (left) and Relaxing (right) at electrode Cz.Click here for additional data file.


However, pretreatment with MFSC-Ex inhibited LPS/IFN-γ-induced these pro-inflammatory mediators. To clarify the molecular mechanisms underlying the anti-inflammatory property of MFSC-Ex, we analyzed nuclear factor-kappa B (NF-κB) and mitogen-activated protein kinases (MAPKs) protein expressions by Western blotting. Our study showed that treatment of MFSC-Ex significantly down-regulated inducible nitric oxide synthase (iNOS) and COX-2 protein expressions. Furthermore, phosphorylation of extracellular signal-regulated kinase (ERK) and p38 was also blocked by treatment with MFSC-Ex, indicating that inhibitory effect of MFSC-Ex on MAPK signaling cascade may attribute to inactivation of NF-κB. From these findings, we suggest that MFSC-Ex exert anti-inflammatory activities, which suppressed LPS/IFN-γ-induced production of NO, COX-2 and PGE2 by regulation of NF-κB and MAPK signaling pathway in RAW 264.7 macrophages. In conclusion, MFSC-Ex might provide a new therapeutic opportunity to treatment of inflammatory-related diseases.Recently, adipose-derived stem cells (ADSCs) are considered to be ideal for application in cell therapy or tissue regeneration, mainly due to their wide availability and easy access. In this study, we examined the anti-inflammatory effects of membrane-free stem cell extract (MFSC-Ex) derived from ADSCs against lipopolysaccharide (LPS)/interferon-gamma (IFN-γ) on RAW 264.7 macrophage cells. Exposure of RAW macrophages to LPS and IFN-γ stimuli induced high levels of nitric oxide (NO), cyclooxygenase-2 (COX-2), and prostaglandin E After that, the membranes were incubated with appropriate secondary antibodies  for 1 h. The Western blot bands were visualized by using pico-enhanced peroxidase detection and assessed with a Davinci-Chemiluminescent imaging system .post-hoc test (p < 0.05).Results were expressed as means ± SD. Statistical analysis was performed using IBM SPSS statistics software version 23 . Statistical differences were determined by one-way ANOVA followed by Duncan’s 2 production via down-regulation of iNOS and COX-2 protein expression, and its inhibitory effect might be associated with the decreased protein levels of phospho-ERK and -p38 in RAW 264.7 macrophage cells. Therefore, MFSC-Ex have anti-inflammatory properties in macrophages and may be useful for the prevention or treatment of inflammatory-related disorders as a non-cell-based stem cell therapy.Taken together, our findings showed that MFSC-Ex, which is stem cell components without cell membrane, suppressed LPS/IFN-γ-induced NO, COX-2, and PGE


In this research the interlayer contact condition was considered between the adjacent layers of orthotropic steel deck pavement, and an interface contact bonding model was applied to simulate the interlayer bonding condition and evaluate the response of deck pavement under vehicle loads. An advantage of this model is that it can simulate not only the full-bond condition but also the debonding condition at somewhere between adjacent layers. The responses of the orthotropic steel deck pavement were calculated and analyzed by the model, and it found that this model is reasonable and credible to evaluate the responses of the deck pavement comparing with the previous researches. The full-bond condition was an ideal condition between adjacent layers, which was prone to underestimate the responses and deformation of the deck pavement. Moreover, the position and size of the disengaging area have a notable influence on the tensile strain at the top of SMA layer and the bottom of GA layer, and the tensile strain of them also increase with the increase of the disengaging area. Finally, the responses of the steel deck pavement changed obviously when the vehicle speed increase, so the suitable speed limit may reduce the responses and deformation for prolonging the service life of the orthotropic steel deck pavement. Compared with concrete bridges, the high degree of pre-fabrication, lightweight-design, and rapid erection capability of this type of steel bridges make it a better option for many applications, including long-span bridges, movable bridges, and bridges with restricted beam depth2. Asphalt concrete deck pavement is an important role paved on OSD bridges, which is used to provide the essential functions of load distribution and skid resistance, and to protect the steel bridge deck as well as providing service to the vehicle4. The asphalt concrete deck pavement is exposed chronically and directly to adverse environmental condition and traffic conditions, and this reduce its service life compare with other parts of the OSD bridges5. Therefore, the asphalt concrete deck pavement needs to be designed carefully to provide the high service level and the long service life of the OSD bridges6.Orthotropic steel deck (OSD) has the characteristics of high strength-to-weight ratio, ease of assembly, and modular construction, and therefore widely used in the construction of long-span bridges and urban bridges10. However, the mechanical behaviors of these asphalt mixtures change much significant with the climate, and also affected by vehicle speed11. Therefore, the responses of OSD pavement should be calculated and analyzed under different temperature and loading conditions in order to make a suitable evaluation and obtain a deep understanding of the mechanical properties of OSD pavement. Besides, the bonding condition between the adjacent layers is an important factor, which affects the mechanical responses of OSD pavement in finite element simulation12. The good bonding condition between adjacent layers can help the asphalt concrete surface course and the steel deck pavement form an integral structure to resist the external loads, on the contrary, the weak bonding between adjacent layer is disadvantage for steel deck pavement and prone to cause deck pavement diseases. In some of previous researches16, full-bond condition and no-bond condition are two commonly bonding condition between adjacent layers, however, a few researchers hold that the interlayer bonding condition of adjacent layers lies in somewhere between full-bond condition and no-bond condition17. In a recent study18, the ultra-high performance concrete (UHPC) has been utilized to reinforce the orthotropic steel bridge, which is an innovative cement-based material for enhancing the stiffness of bridge deck and improving the fatigue performance. The composite action between UHPC layer and the deck plate of OSD were realized by shear studs and coupling the vertical translational degrees of freedom, i.e., partial slip. So the interlayer condition need be considered in simulating the bonding condition between adjacent layers of OSD pavement.Asphalt mixtures are the mainly and commonly paving materials which are used for building the OSD pavement, such as gussasphalt (GA), stone mastic asphalt (SMA), and epoxy asphalt (EA) mixturesIn this study, an orthotropic steel bridge with two-layer paving structure was investigated to estimate the responses and performance of the deck pavement. The first objective is to build a finite element model that can simulate the interlayer bonding condition between adjacent layers of the OSD pavement accurately. To accomplish the objective, the interface contact bonding model was built to evaluate the response of orthotropic steel deck pavement under vehicle loads, where the interface condition is different from full-bond condition and no-bond condition. The model can simulate not only the interface bonding condition between adjacent layers but also the phenomenon of bonding failure at somewhere between adjacent layers, which is the obvious difference with the model used by the other related researches. The second objective is to predict the responses of OSD pavement by the developing model under the different temperature and loading conditions. The temperature has an effect on the performance of the asphalt mixtures, which makes the deformation of the OSD bridges with asphalt pavement notable at the high temperature. So the responses of OSD pavement will be calculated and analyzed by the interface contact bonding model under the high temperature to understand the mechanical behaviors of the deck pavement. Meanwhile, the effects of bonding failure on the response of the OSD pavement will be analyzed and discussed, and it is helpful for knowing the bonding failure between adjacent layers to the damage of deck pavement. Moreover, the influence of the thickness of the deck plate and the U-rib on the responses of deck pavement was conducted respectively. Finally, it is expected that the findings in this research will help to obtain a better insight into the responses of the OSD pavement.8, and it is proved to be reasonable for evaluating the responses of the OSD pavement. Otherwise, this type of model has the general characteristics of OSD pavement structure, which has the universality, and it can also reduce the time for computing. In this paper, the section of the OSD pavement structure is shown in Fig. 19, 3600 mm and 9000 mm, respectively. The thickness and depth of the cross beam plate are 10 mm and 750 mm, respectively, and the spacing between two adjacent cross beams is 3000 mm. The thickness of U-rib is 8 mm. The vertical pressure applied on the surface of the pavement layer was used to simulate the traffic loading, which is corresponding to a single axle with dual-tires, and placed at the right of the midspan.A three-dimensional finite element model with ‘deck-pavement’ was built by ANSYS software, and the model is a simplified structure model for simulating and calculating the responses of the OSD pavement. This structure model is employed by some researchers in their studies2, which is a 20 cm × 20 cm rectangular loading area and red regions shown in Fig. 20. The contact pressure corresponding to the traffic loading was 0.625 MPa.As seen in Fig. The force of rolling friction mentclass2pt{minim21:dn = 1, and July 1st, dn = 181. In this paper, Xi’an (in China) is the observing site, and the value of the latitude is about 34 (°). dn = 187, The materials are the SMA and GA for the deck pavement and steel for the components of the orthotropic steel deck. It is well known that the SMA used for the surface layer has an excellent rut-resistance and fatigue cracking resistance. The GA used for the base course bonds quite well to orthotropic steel deck, and the impermeability of it is also very well. However, the responses of these asphalt mixture are affected by environment temperature and loading time dramatically. The deck pavement is prone to deform in the high temperature compare with the normal temperature, then it may turn into damage under traffic loading. Therefore it is more valuable to calculate and analyze the responses of the deck pavement under the high temperature. It should be noted that the temperature of each layer of the deck pavement is varying with the depth and environment, and then in this study the temperature of the deck pavement was calculated by the following formula (In Summer)11. On the contrary, the poor bonding condition will reduce the shear strength between adjacent interfaces, thereby decrease the capability for stress transferring and energy dissipation and lead to several pavement distresses. The full-bond or no-bond condition is an ideal interface bonding condition, which were usually used to predict the responses of the pavement structure and steel deck pavement in some of previous researches. However, in recent years some researches and early diseases of pavement show that the interface bonding condition of adjacent layers are neither fully bond (full-bond condition) nor completely debond (no-bond condition) with each other, but lies in somewhere between these two ideal interface bonding condition.The full-bond condition between adjacent layers, especially the deck plate and the pavement layer is a desired result in the ‘deck-pavement’ structure. The good bonding condition between adjacent interfaces will help the ‘deck-pavement’ structure constitute a monolithic structure to resist against the effect of traffic and environment12. In the ICB model, the upper layer and lower layer of the adjacent layers are covered by contact element and target element respectively, and contact element and target element are connected by three-direction translational spring element at the corresponding nodes. Then two kind of contact bonding interfaces are built, which are applied to imitate the interface condition between the SMA layer and the GA layer and the interface condition between the GA layer and the deck plate, respectively. The translational springs between contact element and target element can measure the value of compression or tension in each direction, and the stress and strain between adjacent layers will be calculated by the measured value according to contact algorithm22. x direction and z direction, respectively. Once the material parameters are determined and the mesh is completed, the three stiffness coefficients can be generated automatically based on the contact algorithm. But sometimes a reduction coefficient may be used to modify the three stiffness coefficients to get a better computation.In this study the interface condition of adjacent layers are supposed to be interface contact bonding condition (ICB condition), and the Fig. 22 under the ICB condition, and the tangent stress between the adjacent layers satisfies the following conditions11:The stress along normal and tangent direction at the adjacent interface will be computed according to the augmented Lagrangian method12, and In Eq. , \documethe Eqs.  and 9)..\documenthe Eqs. , assuminThe phenomenon of insufficient bonding strength or bonding failure between adjacent layers at somewhere may not be simulated by previous model, but these phenomena do occur sometime during the service life of pavements. The ICB model can easily capture these phenomena by adjusting the value of the bonding stress 6 the geometric parameters of the OSD bridge with asphalt pavement and the loading position are almost at the same with them in ours, so these researches are chosen to validate our model. However, the notable difference between the literatures6 and our study is the interface condition of adjacent layers. In the literatures6, the interface condition between the adjacent layers is the full-bond condition, but the interface contact bonding condition was used in this research. The transverse stress of the deck pavement under static loads is shown in Fig. 5. The results from Kim et al. are verified by a strain gauge and a linear variable differential transducer, and the responses of the transverse stress of the deck pavement are similar to other studies mentioned in their research. Tensile stress, which was marked red in Fig. In order to estimate the accuracy and rationality of the ICB model, the response of the deck pavement was calculated under static loads and moving loads at the normal temperature and compare with the result of other researches. For validating our model, we find that in the literatures23:The responses of the deck pavement under the moving loads are calculated according to the following dynamic algorithm6, who got the transverse strain of the OSD bridge with asphalt pavement under moving loads by strain measurements, and the magnitude and trend of transverse strain of the OSD pavement under different vehicle speed simulated by ours is in accord with the results of Cheng et al. Meanwhile, the transverse strain of the deck pavement all decease when the vehicle speed increase, this is same with the results of other researches12 including results of Cheng et al.The transverse strain at the bottom of SMA layer and at the bottom of GA layer was calculated between the dual tires, which are shown in Fig. In summary, compared with the responses calculated or measured by other studies to verify the EF model we used, and the responses of the deck pavement we simulate basically stay in step with them in the literatures under the static loads or moving loads at the normal temperature. So the responses of the deck pavement calculated by the ICB model are basically reasonable and reliable.The critical responses of the deck pavement play a crucial part in the structure design and materials requirement of pavement, especially at the high temperature. In order to analyze the influence of interface bonding condition and vehicle speed on the performance and service life of the deck pavement at the high temperature, the critical responses of the deck pavement would be calculated to study the strain and deformation of the deck pavement.The responses of the SMA layer and the GA layer at the top or bottom were computed, ranging from − 1.2 to 1.2 m along the X axis under dual-tires, where 97 nodes were defined in the response profile. The responses of the deck pavement with the full-bond condition are shown in Fig. The responses of the deck pavement with the ICB condition are shown in Fig. In this study, entclass1pt{minimaThe phenomenon of the bonding failure between the adjacent interface at somewhere may happen with the aging of the deck pavement and the repeatedly action of vehicle load. To simulate the phenomenon of the bonding failure and investigate the effect on the responses of the deck pavement, the bonding failure is considered between the GA layer and the steel plate. The six types of the disengaging area shown in Fig. The response analysis under moving loads is a better way to study the behaviors of the deck pavement, so the critical response of deck pavement at different vehicle speed were calculated and shown in Fig. The thickness of the deck plate and the thickness of the U-rib have an influence on the responses of asphalt pavement, so sensitivity analysis of these parameters are performed to improve the design of OSD. The critical responses with the different thickness of deck plate at the high temperature are calculated and listed in Table In Table In Table An interface contact bonding model was used to simulate the interface contact bonding condition between adjacent layers for the OSD pavement. Comparing the response results with previous researches, the response results from the interface contact bonding model are basely acceptable and credible.The responses under the full-bond condition and the interface contact bonding condition were calculated, respectively, and it was found that there was a clear difference between the responses at the bottom of SMA layer and GA layer under the two kind of the interface condition. However, the responses with the interface contact bonding condition were more reasonable according to previous researches.A clear advantage is that the interface contact bonding model can simulate the bonding failure at somewhere between adjacent layers. The bonding failure between the GA layer and the steel plate was investigated, which have an obvious effect on the transverse strains at the bottom of the GA layer with the increase of the disengaging area, and relatively weaker influence on the responses at the top of the SMA layer.The responses of the deck pavement under moving loads were calculated, and the peak value of the responses of SMA layer and GA layer all decreased with the increase of the vehicle speed. Hence, restricting vehicle speed within a reasonable range can not only reduce the responses of the deck pavement, but also ensure driving safety.By the sensitivity analysis of thickness parameters, it is advised that the thickness of the deck plate is no less than 14 mm, and the thickness of it is no less than 16 mm for the condition of heavy traffic and long-term high temperature. The 8 mm thickness of the U-rib is a reasonable and good choice.In order to capture the interface state between adjacent layers and obtain the credible responses of deck pavement under vehicle loads, a two-layer paving structure was investigated to estimate the response characteristics of the OSD pavement by finite element model at the high temperature, and some important results of this study are summarized as follows: