Non-steroidal anti-inflammatory drugs (NSAID) have excellent anti-inflammatory and analgesic properties and are extensively used to treat post-traumatic or surgical musculoskeletal pain. Although an extensive literature exists on the administration of NSAID on animal bone healing, no systematic review and meta-analysis of animal studies that investigate the effect of NSAID administration on bone fracture healing. Objective of this study is to conduct a systematic review and meta-analysis to estimate the effect of NSAIDs administration on bone healing biomechanical and histomorphometric measurements in different animal models after bone fracture surgery.We performed a systematic review and meta-analysis of animal studies to estimate the effect of NSAID administration after bone fracture on healing outcomes. We searched eight databases without limiting the search to starting date up to 1 February 2021 for articles on fractured bone healing in animal models in which NSAID were administered.Out of 6732 articles screened, 47 were included and 3 common bone healing outcomes were analysed: biomechanical properties , micro-computed tomography (μ-CT), and histomorphometric measurements. The studies were generally of low-quality scores because crucial information, especially concerning randomization, blinding, and allocation concealment, was poorly reported. Our results show that the negative effects of NSAID after bone fracture on certain biomechanical properties of the healing bones was not statistically significant in mice compared with other animals, in females compared with males, and in younger compared with older animals.The findings demonstrated that NSAIDs administration decreased the biomechanical properties of healing bones after fracture surgery in comparison to the control group. Moreover, different effect on certain outcomes was detected among different sites, sex of the animals, and the time of assessment.https://www.radboudumc.nl/getmedia/757ec408-7a9e-4635-8233-ae951effea54/Non-Steroidal-Anti-inflammatory-Drugs-and-bone-healing-in-animal-Models-Systematic-Review-and-Meta-Analysis.aspxProtocol published and registered in SYstematic Review Center for Laboratory animal Experimentation (SYRCLE) in 2017, The online version contains supplementary material available at 10.1186/s13643-021-01690-w. Non-steroidal anti-inflammatory drugs (NSAID) have been extensively used to treat post-traumatic and surgical musculoskeletal pain because of the excellent anti-inflammatory and analgesic properties of cyclooxygenase (COX) inhibitors –5. HowevSeveral animal models including different animal strains, sex, and fracture techniques have been used to test the effect of types and administration durations of NSAID on bone healing outcomes , 18–24. Although an extensive literature exists on the administration of NSAID on animal bone healing, no systematic review and meta-analysis have yet been conducted on the subject. Such work is important because it can identify the key histomorphometric and biomechanics characteristics during the healing process as well as it provides information on different factors that may affect the healing process after NSAID administration . This information may help to design future experimental trials and facilitate knowledge translation. Therefore, we performed a systematic review and meta-analysis of all identified and available animal studies on the effect of NSAID administration after bone fracture on healing outcomes.Specifically, our objectives were to estimate the extent to which the effect of NSAID administration after bone fracture using animal models: (i) results in less favorable bone-biomechanical and morphometric healing measurements; and (ii) differs by animal type, age and sex, type of NSAID, and length of follow-up.The systematic review methodology was specified and documented in advance using SYstematic Review Center for Laboratory animal Experimentation (SYRCLE)’s protocol template for animal studies and registered in the SYRCLE database  . Th. Th35]. g effect to calculate the SMD, Hedge’s g  [The meta-analysis was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, and using Comprehensive Meta-Analysis software  when five or more independent comparisons from at least three different studies per outcome category were included (provided that outcome measure assessments were sufficiently comparable). We calculated the standardized mean differences (SMD) through Hedges g effect sizes . The calze bias) , 39. AgaDespite the anticipated heterogeneity, the individual effect sizes were subsequently pooled to obtain an overall SMD and 95% confidence interval (95%CI) , 40. We I2 and the Q statistic.Rather than computing a single summary measure, an important objective of meta-analysis is to explore the sources of heterogeneity , a measuZ-test to compare the effect sizes directly. Another method was to use a Q-test to partition the variance and test the between-subgroups portion of the variance. A third one was to use a Q-test to assess the dispersion of the summary effect about the combined effect. All the methods used by the software assess the variance across subgroups effects relative to the variance within subgroups. The row tables for each subgroup analysis generated by the comprehensive meta-analysis software were added in the supplementary information file for detailed results based on the previous described methods  in the systematic review and the risk of bias assessment for each parameter is presented in the Supplementary file For more details regarding each included study . Similarly, animals that received NSAID had an overall decrease in bone stiffness and work-to-failure properties  respectively compared to controls  and work to failure outcomes .Results from 30 studies including 94 comparisons showed that the maximum force to fracture was significantly decreased, indicating bone healing delay, in animals that received an NSAID after bone fracture compared to the control group  and animals older than 16 weeks  did not differ between NSAID and control groups , those that received selective-cyclooxygenase2 NSAID , and for the femur bone model fracture  .We included five comparisons from four studies that measured healing bone using a μ-CT scan in the meta-analysis. The average time of bone collection after animal euthanasia was 19.5 days . Figure I2 = 54.64). Animal models and types of fractured bones were sources of heterogeneity for histomorphometric measurements of healing bones among studies  histomorphometric measurements . The Egger’s regression test intercept result (95% CI − 2.33 to − 0.67); P < 0.001. For the histomorphometric outcome; trim and fill analysis resulted in data points, indicating the presence of publication bias . The Egger’s regression test intercept result (95% CI 1.67 to 5.8); P < 0.001.The possible presence of publication bias was observed when assessing the biomechanical bending and histomorphometric outcome measurements. The inspection of the funnel plot suggested asymmetry resulting from the underrepresentation of studies regarding the effect of NSAID Fig.  a, and bThis unique systematic review and meta-analysis was designed to answer a specific research question regarding the effect of different types of NSAID on bone fracture healing in animal models (in vivo studies). Three important outcomes commonly used to assess bone healing were analyzed: biomechanical properties , micro CT, and histomorphometric measurements.NSAID administration had a negative effect on the biomechanical properties in different animal models of the included studies , 51–59. Depending on the type of NSAID, they are known to inhibit both COX isoforms. Both non-selective NSAID and COX-2-selective drugs decrease prostaglandin production, which plays an essential regulatory role in all phases of bone healing, especially the inflammatory phase –63. ThusAs early as the 1970s, many animal trials strongly emphasized the negative effect of NSAID on bone healing , 59, 64.Some methodological issues that might hamper the interpretation of the experimental animal data and their subsequent translation to the clinical setting should be discussed. First, there was substantial heterogeneity among the various animal studies. We performed subgroup analyses to investigate factors that may modify the effect of NSAID on bone healing outcomes  may be more sensitive than others for bone healing outcomes. Additionally, this finding suggests that the negative effect of NSAID on bone healing is species related for certain outcomes, and this need to be taken into consideration for knowledge translation. Other factors should be taking into consideration in selecting animal model for experimental bone regeneration studies which are highlighted in the 2018 systemic review by Peric et al. such as skeletal features of the selected animals, the model that can mimic the clinical scenarios including relevant doses and statistically supported sample size . The timFinally, we did not find any studies that used animals of both sexes in their experimental design, which seems to be important for future studies because results differed between males and females for the work-to-failure biomechanical outcome.Our study quality checklist assessed aspects of both internal and external validity, and we observed many studies were generally of low-quality scores and tended to overstate the effect size. The overall quality score accounted for a significant proportion of between-study heterogeneity; however, the correlation between the aggregate quality score and the effect was not clear. The reporting and risk of bias assessments indicate the need for protocol registration or publication, and for the reporting of the elements of randomization, blinding, and allocation concealment . This cog effect sizes which is based on Cohen’s D but includes a correction factor for small sample size bias [Several limitations of this work should be considered. One important limitation of this study was the risk of bias analysis which showed most of the included animal studies are poorly reported. This lack of reporting important methodological details might lead to increase bias. This limitation needs to be considered during interpretation of our conclusion from the included animal studies. In addition, we observed a level of heterogeneity present among studies reviewed for certain measured outcomes. This is can be expected as animal studies are explorative and heterogenous with respect species, sex, design, and drug administration protocol compared to clinical trials . Exploriize bias . More spDrug pharmacokinetics vary between species, and this must be considered when extrapolating data from animals to humans. Therefore, it is important to investigate NSAID doses that are equivalent to those used in humans after bone fracture  and to evaluate effects using different types of animal and bone fracture models. The increasing amount of evidence from animal studies and the results from this systematic review and meta-analysis indicate that caution should be exercised when using NSAID after bone fractures or with specific orthopedic surgical procedures until prospective human clinical studies indicate otherwise.Our findings provide some guidance for future laboratory and clinical research. First, it is important to test different hypotheses of bone fracture healing in small animals, and mice especially because mice models provide opportunities to examine genetics and create knock-out species. Our results also indicate the need for studies that compare the effect of NSAID administration on bone healing outcomes between male and female animal models. Overall, choosing appropriate animal model to test the effect of NSAID on fracture bone healing should take into consideration the animals’ species, type of the bone, and age of the animal.Moreover, our results demonstrate it is important to choose the suitable time of sample collection based on what healing outcome to be measured. Histomorphometric outcome measurements require more than 21 days to show results that are comparable to the control group. Second, improvements in internal  and external (publication bias) validity might provide more information for the translation of the data to clinical trials, and more robust exploration of the efficacy limits in such studies could inform inclusion and exclusion criteria for these trials.It is increasingly clear that the function of COX and their products are critical for bone healing. Most animal and human studies support the conclusion that NSAID administration can delay or impair bone fracture healing. However, the anti-inflammatory and analgesic effect of NSAID seems to be beneficial in treating post-traumatic pain and edema. The need for a new approach to using NSAID that preserves its pain control properties without affecting bone healing is justifiable and important.Additional file 1: Table S1. Systematic review and meta-analysis registered protocol in SYRCLE website: https://www.radboudumc.nl/en/research/technology-centers/animal-research-facility/systematic-review-center-for-laboratory-animal-experimentation/protocols NSAIDs effect on bone healing after bone fracture in animal models. Table S2. Search strategy. Table S3. SYRCLE’s tool for assessing the risk of bias  (1). Table S4. Study characteristics. Table S5. Subgroup analysis by species regarding the effect of NSAID administration vs control on maximum force to fracture outcome. Table S6. Subgroup analysis by sex regarding the effect of NSAID administration vs control on maximum force to fracture outcome. Table S7. Subgroup analysis by age regarding the effect of NSAID administration vs control on maximum force to fracture outcome . Table S8. Subgroup analysis by type pf NSAID regarding the effect of NSAID administration vs control on maximum force to fracture outcome. Table S9. Subgroup analysis by time point regarding the effect of NSAID administration vs control on maximum force to fracture outcome . Table S10. Subgroup analysis by bone fracture site regarding the effect of NSAID administration vs control on maximum force to fracture outcome. Table S11. Subgroup analysis by species regarding the effect of NSAID administration vs control on stiffness to fracture outcome. Table S12. Subgroup analysis by sex regarding the effect of NSAID administration vs control on stiffness to fracture outcome. Table S13. Subgroup analysis by age regarding the effect of NSAID administration vs control on stiffness to fracture outcome . Table S14. Subgroup analysis by type of NSAID regarding the effect of NSAID administration vs control on stiffness to fracture outcome. Table S15. Subgroup analysis by type of time point regarding the effect of NSAID administration vs control on stiffness to fracture outcome . Table S16. Subgroup analysis by bone fracture site regarding the effect of NSAID administration vs control on stiffness to fracture outcome. Table S17. Subgroup analysis by species regarding the effect of NSAID administration vs control on work to failure outcome. Table S18. Subgroup analysis by sex regarding the effect of NSAID administration vs control on work to failure outcome. Table S19. Subgroup analysis by age regarding the effect of NSAID administration vs control on work to failure outcome . Table S20. Subgroup analysis by type of NSAID regarding the effect of NSAID administration vs control on work to failure outcome. Table S21. Subgroup analysis by time point regarding the effect of NSAID administration vs control on work to failure outcome . Table S22. Subgroup analysis by bone fracture site the effect of NSAID administration vs control on work to failure outcome. Table S23. Subgroup analysis by species the effect of NSAID administration vs control on histomorphometric outcome. Table S24. Subgroup analysis by sex the effect of NSAID administration vs control on histomorphometric outcome. Table S25. Subgroup analysis by age the effect of NSAID administration vs control on histomorphometric outcome . Table S26. Subgroup analysis by type of NSAID the effect of NSAID administration vs control on histomorphometric outcome. Table S27. Subgroup analysis by time point the effect of NSAID administration vs control on histomorphometric outcome . Table S28. Subgroup analysis by bone fracture site the effect of NSAID administration vs control on histomorphometric outcome.Additional file 2.Additional file 3.


While its efficacy is debated, HCQ has been associated with QT interval prolongation and potentially Torsades de Pointes, especially in patients predisposed to developing drug-induced Long QT Syndrome (LQTS) as silent carriers of variants associated with congenital LQTS. If confirmed, these effects represent a limitation to the at-home use of HCQ for COVID-19 infection as adequate ECG monitoring is challenging. We investigated the proarrhythmic profile of HCQ with Multi-Electrode Arrays after exposure of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) from two healthy donors, one asymptomatic and two symptomatic LQTS patients. We demonstrated that: I) HCQ induced a concentration-dependent Field Potential Duration (FPD) prolongation and halted the beating at high concentration due to the combined effect of HCQ on multiple ion currents. II) hiPSC-CMs from healthy or asymptomatic carriers tolerated higher concentrations of HCQ and showed lower susceptibility to HCQ-induced electrical abnormalities regardless of baseline FPD. These findings agree with the clinical safety records of HCQ and demonstrated that hiPSC-CMs potentially discriminates symptomatic vs. asymptomatic mutation carriers through pharmacological interventions. Disease-specific cohorts of hiPSC-CMs may be a valid preliminary addition to assess drug safety in vulnerable populations, offering rapid preclinical results with valuable translational relevance for precision medicine.In the early phases of the COVID-19 pandemic, drug repurposing was widely used to identify compounds that could improve the prognosis of symptomatic patients infected by SARS-CoV-2. Hydroxychloroquine (HCQ) was one of the first drugs used to treat COVID-19 due to its supposed capacity of inhibiting SARS-CoV-2 infection and replication  Drug repurposing is a key strategy aimed to identify new applications for compounds that have already been approved by regulatory authorities. The known safety profiles and toxicology of the repurposed compounds reduce the chances of failure and drug attrition, shorten the time frame for drug development and lower the costs associated with drug discovery and screening . It had in vitro (Hydroxychloroquine (HCQ), an antimalarial drug successfully used for the treatment of systemic lupus erythematosus and rheumatoid arthritis, was identified as a compound capable of inhibiting SARS-CoV-2 infection and replication in vitro ; its offKr) and the inward delayed-rectifier potassium current (IK1) at therapeutic concentrations, with peak sodium current (INa) and L-type calcium current (ICaL) blocked at higher concentrations . We believe that more information is required to understand the risks and boundaries of HCQ when administered in a potentially susceptible population of patients in which asymptomatic individuals carry a higher predisposition for TdP.Despite the promising  studies . ConclusIn vitro Proarrhythmia Assay (CiPA) consortium (Here we used MultiElectrode Arrays (MEAs), one of the platforms of choice from the Comprehensive nsortium , to repoin vitro; (ii) a genotype-specific response to HCQ can be reproduced with hiPSC-CMs and whether it correlates with clinical observations; and (iii) hiPSC-CMs from homogeneous disease-specific cohorts could provide quick preclinical readouts before repurposing drugs to patients in large trials.We aimed to assess whether: (i) hiPSC-CMs can identify potential proarrhythmic effects by HCQ KCNQ1 or on KCNE1 associated to congenital deafness in addition to the typical cardiac features  in E8 Flex medium and differentiated on cell culture-grade Matrigel. hiPSCs were differentiated to hiPSC-CMs following a protocol based on the modulation of the Wnt-signaling pathway , purifieMultiwell MEAs (MultiChannel Systems) were coated with 40 μg/mL bovine fibronectin and processed as previously described . hiPSC-CHCQ was dissolved in water to obtain a stock solution of 50 mM. After having recorded Field Potentials (FP) values at Baseline, RPMI + B27 in Multiwell MEAs was refreshed with working concentrations of HCQ prepared in RPMI + B27 . Vehicle was balanced accordingly and used as a control in each experiment and each Multiwell MEA plate.A 6-point Field Potential (FP) scoring system was implemented to evaluate the quality of FPs and to classify potential detrimental effects of the drug treatment on FP quality .Score 5: Assigned to FPs with both markedly pronounced positive and negative upstrokes, a unambiguous repolarization wave and a large FP amplitude; noise and signal oscillations at baseline must not be present and the RR interval must be regular.Score 4: Assigned to FPs with either a clear positive or negative depolarization peak, a visible repolarization wave and a large FP amplitude; noise and signal oscillations at baseline must not be present and the RR interval must be regular.Score 3: Assigned to FPs similar to the previous condition but with a smaller FP amplitude, a less markedly pronounced repolarization peak and a potentially ambiguous repolarization peak. Signal oscillations at baseline can be present and RR must be stable.Score 2: Assigned to FPs characterized by a small positive or negative depolarization, a small FP amplitude, a small and potentially ambiguous repolarization peak. Signal oscillations at baseline can be present and RR interval can be irregular.Score 1: Assigned to FPs characterized by a very irregular pattern(s), with small/absent depolarization and a small/absent repolarization peak; noise is present in terms of oscillations at baseline and electrical interference from neighboring electrodes; RR interval can be unstable.Score 0: Assigned to electrically inactive wells.The analysis of FPs was performed as previously described  and autop < 0.05 and is indicated in text and figures with an asterisk. Data are presented in the text as mean, mean ± standard error of the mean (sem) and scatter points where relevant.Comparisons of FP Durations (FPD), RR, corrected FPD (cFPD) were performed for each line with Dunnett’s test using Baseline as reference values. Statistical significance was defined as To exclude any potential bias carried by the endogenous FPD of healthy hiPSC lines, we chose two healthy hiPSC lines characterized by different baseline FPD. Baseline FPD is a reliable parameter for comparisons only in case of isogenic lines or at least in case of lines sharing part of the genetic background  while it might often provide misleading results in case of cross-line comparisons , 2017a.Given the significant non-zero slope of the FPD-RR linear fit for the majority of the lines, data were corrected with the clinically used Bazett’s QT correction formula, validated across all ages . As prevSigns of spontaneous arrhythmias and electrical instability were detected at baseline in MEAs from the JLNS and CALM-LQTS .We first investigated the presence of potential detrimental effects of the exposure to HCQ on the spontaneous activity of hiPSC-CMs monolayers.diast  and a mean peak blood concentration of 129.6 ng/mL (Plaquenil label indication); based on these data, it is reasonable to estimate an in vitro concentration of 0.15–0.387 μM.Although the concentrations and the modality of administration (acute vs. cumulative) are different among ith MEAs  or in a ith MEAs . Our stuin vitro was achieved at concentrations larger than 4 μM (EC50 4.06 μM or higher) regardless of the multiplicity of infection (MOI) used for SARS-CoV-2, 50) in ATCC-1586 cells was around 250 μM. Other studies identified a similar range of concentrations in Vero/VeroE6 cells, with an EC50 of ∼6 μM after 24 h of treatment .in vitro FPD values.A genotype-specific drug response pattern could also be identified and it aligned with the severity of the underlying genotypes. Our data indicate that hiPSC-CMs from the healthy donors or the asymptomatic LQT1 mutation carrier tolerated higher concentrations of HCQ and showed lower susceptibility to HCQ regardless of baseline Importantly and in agreement with previous observations , 2017a, Healthy controls showed a higher tolerance for QTc prolongation and higher resistance to high HCQ concentrations. This might have impacted directly the patients: the asymptomatic LQT1 carrier , for example, was identified in our center only through a family screening of the sibling  and might have been included in one of the COVID-19 clinical trials with HCQ because in most of them the exclusion criteria for QTc were a cutoff of 480 ms. According to our MEA data, this would have meant a significantly higher chance for this patient to experience QTc prolongation, a degradation of the electrical signal  and a poK1, and this could explain the increased beating frequency observed particularly in hiPSC-CMs from WT despite HCQ should inhibit also the funny current (If) , a large decrease in the upstroke velocity and a decrease in the plateau amplitude  that overall could be linked to the decreased FP quality observed in p < 0.05 for WT2, n.s. for LQTS and CALM-LQTS) was observed and, for WT2, was similar to the results at 2 h in Na and dV/dtmax and thus the trend toward APD shortening.Similarly to Chloroquine , also HCent (If) ; in our in vitro and in silico systems  in WT and CALM-LQTS  effectiveness for the prevention or treatment of COVID-19 , the useConversely, caution should be used for subjects who may be particularly susceptible to QT prolongation, and a particular focus should be put on silent or asymptomatic carriers of cLQTS variants and especially when genotype is additive to other detrimental pathophysiological factors or prescribed medications, as frequently occurs in patients with COVID-19 infection. Indeed, in a worldwide survey of COVID-19 associated arrhythmias, with almost 60% of the patients treated with hydroxychloroquine and 50% with azithromycin, those who developed cardiac arrhythmias already had borderline-prolonged QTc at the time of hospital admission and were more frequently affected by comorbidities and by severe pulmonary impairment  . On thisin silico predictive approaches can provide insights with clinical implications for precision medicine (This work confirms that disease-specific hiPSC-CMs may provide additional information to drug screenings performed solely on hiPSC lines from healthy donors and may thus represent a viable option for preclinical drug repurposing screenings aiming for a higher translational readout. Larger homogeneous cohorts of hiPSC-CMs, with the ideal involvement of multiple facilities and including multiple disease-causing variants, genetic backgrounds and clinical manifestations, may represent a solid preliminary validation to assess the proarrhythmic effect of drugs, particularly in situations requiring rapid decisions. The combination of gene-editing and robust commercial iPSC lines from industry may further contribute to enhance and refine this aspect. These results should warn investigators interested in enrolling patients in clinical trials aimed to study the effects of HCQ in the prevention or treatment of COVID-19, of the existence of potentially important cardiac side-effects at concentrations far from those approved for rheumatoid arthritis, which may impact asymptomatic LQTS-mutation carriers whose underlying condition might go unnoticed at admission due to short or borderline QTc intervals. The most critical task indeed remains the identification of who might be a susceptible subject and how a patient or a disease-cohort might respond to a new or repurposed therapy, and in this regard the contribution provided by subject-specific hiPSC-CMs combined with genome sequencing and medicine .The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.LS: study design, hiPSC-CMs culture, MEA, patch clamp, data analysis, and wrote the manuscript. VL: CALM1-p.F142L hiPSC-CMs culture, critical analysis of data and manuscript. MM: LQT1-p.R594Q and JLNS-p.R594Q/p.R190W hiPSC line generation. FG: patch clamp data collection and analysis, critical analysis of the manuscript. AK: iPSCs and iPSC-CMs culture and differentiation, critical analysis of the manuscript. AM: CALM1-p.F142L hiPSC line generation. LC, MG, and PS: critical analysis of the manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Though the lunar samples returned by the Apollo and Luna missions have been studied for more than 50 years, scientists are discovering new clues into the early evolution of the Moon by looking through the lens of modern analytical techniques. The Chinese Lunar Exploration Program has answered this call, with the Chang’E 5 mission bringing samples back from the Moon on December 16, 2020—the first lunar samples returned since Luna. NASA’s recently launched Artemis program aims to send humans back to the Moon and establish a pit-stop on the way to Mars. Furthermore, sealed Apollo samples await opening and first analysis through the Apollo Next Generation Sample Analysis initiative.What can be learned from analyzing 50-year-old lunar samples? Even samples that have been extensively studied still hold secrets to be unveiled by modern analytical techniques, making “old” new once more.5 led by William Nelson of the University of Hawai’i at Mānoa adds value to one of the most well-studied samples in the Apollo collection: lunar troctolite 76535. Lunar troctolites are a rock type within a group of ultramafic, plutonic rocks from the Moon known as the “Mg-suite.”New researchThe Mg-suite samples provide important insights into planetary differentiation. The source region for the Mg-suite is believed to be chemically tied to the first mantle products crystallizing from a global magma ocean. However, the Mg-suite rocks also contain elevated concentrations of incompatible trace elements thought to be a signature of late-stage magma ocean products, i.e., a “KREEP” component enriched in potassium (K), rare earth elements (REE), and phosphorus (P). This conjunction of primary and late-stage magma ocean products characterizes the complex history that lunar scientists are still working to unravel.6. However, this slow cooling rate requires an age for Mg-suite magmas (4421 ± 11 Ma) that pre-dates the formation of the primary lunar crust (4383 ± 17 Ma8). Given that the primary crust must have formed prior to the magmas that later intruded it, the thermal evolution of the Mg-suite rocks warrants re-investigation.Having intruded into the primary lunar crust, Mg-suite magmas represent the first stages of secondary crust building on the Moon. Following this, Nelson and colleagues point out a puzzling observation: previous cooling rate estimates for Mg-suite samples indicate that the rocks cooled slowly within the crust for over 100 million yearsUsing high-resolution analytical techniques, Nelson and colleagues mapped the concentration of the trace element phosphorus within troctolite 76535. Phosphorus diffusion patterns preserved in olivine grains were consistent with a rapid cooling history at high temperatures. The observed diffusion patterns could only be reproduced with a two-stage model involving rapid cooling at high temperatures and slow cooling at lower temperatures. In contrast to the previously proposed 100-million-year cooling duration, this result supports initial rapid cooling of Mg-suite magmas within the lunar crust.These findings motivate the re-examination of additional olivine-bearing Mg-suite samples in order to validate the cooling history determined for 76535 and to investigate any regional variations between landing sites. More importantly, Nelson and colleagues demonstrate the worth of reanalyzing 50-year-old samples and how quickly new data can reshape our understanding of planetary evolution.3 and apatites4 uprooted over 40 years of consensus that the Moon was nominally anhydrous. This prompted a paradigm shift and the total number of publications featuring lunar sample science has been increasing ever since . These observations warrant revision of existing hypotheses related to lunar volcanism and the Moon-forming impact, as new hypotheses must identify processes that simultaneously produce each of the observed compositional variations.Previously unidentified differences in the isotopic compositions of lunar rocks have reinvigorated debates and prompted new questions in lunar science. For example, the analytical precision of iron isotopic measurements by multicollector-inductively coupled plasma mass spectrometer has improved by an order of magnitude in the past decade. In the early 2000s, analyses of the low-Ti and high-Ti lunar mare basalts yielded identical iron isotopic compositions; however, recent re-analysis of these samples has revealed measurable iron isotopic fractionation between the two rock types11 contributed to the tale of lunar troctolites by combining new data from lunar meteorites, orbital remote sensing, and experimental petrology. They concluded that the Mg-suite primary source was KREEP-free and proposed a model that involves low-degree partial melting of the lunar mantle followed by extensive fractional crystallization. This redefinition of the canonical Mg-suite differentiation trend was originally proposed by a study12 of lunar pyroxene compositions. Now, samples collected from the Procellarum KREEP Terrane by the Chang’E 5 mission are providing further evidence for KREEP-free partial melting of the lunar interior13. These independent approaches converge on a similar conclusion and exemplify how, after decades of work, lunar exploration and research will continue to provide new pieces to the ancient puzzle of lunar volcanism.Just as re-investigation of lunar samples can lead to new insights, in some cases, modern studies breathe life into old hypotheses. For instance, Prissel and Gross14 provide a tantalizing target for future sample-return missions and, when combined with the relatively young volcanic material returned by Chang’E 515, would provide critical insight into the evolution of the lunar mantle. Collecting additional samples from previously unexplored regions helps minimize any sampling bias that may exist in our lunar collection; after Apollo 11 discovered high-Ti mare basalts, Apollo 12 sampled younger, low-Ti mare basalts, immediately enhancing our knowledge of the sources and timing of lunar volcanism. Lingering questions regarding the initiation of and heat sources for lunar volcanism could be answered by further sampling outside of the unique KREEP-rich terrane on the lunar nearside. Although samples from the lunar farside have been brought to Earth as meteorites, these lack the geologic context offered by sample-return missions. Now, perhaps more than ever, we recognize the value not only of exploring our solar system but also returning home.Deciphering the history of our ancient Moon requires a synergy of sample science, remote sensing, and experimentation. Exposures of ancient mantle material identified at the South Pole-Aitken impact basin


Colorectal cancer (CRC) constitutes the third most commonly diagnosed cancer in males and the second in females. Precise histopathological classification of CRC tissue pathology is the cornerstone not only for diagnosis but also for patients’ management decision making. An automated system able to accurately classify different CRC tissue regions may increase diagnostic precision and alleviate clinical workload. However, tissue classification is a challenging task due to the variability in morphological and textural characteristics present in histopathology images. In this study, an artificial neural network was trained to classify between eight classes of CRC tissue image patches derived from a public dataset with 5000 CRC histopathology image tiles. A total of 532 multi-level pathomics features examined at different scales were extracted by visual descriptors such as local binary patterns, wavelet transforms and Gabor filters. An exhaustive evaluation involving a variety of wavelet families and parameters was performed in order to shed light on the impact of scale on pathomics based CRC tissue differentiation. Our model achieved a performance accuracy of 95.3% with tenfold cross validation demonstrating superior performance compared to 87.4% reported in recent studies. Furthermore, we experimentally showed that the first and the second levels of the wavelet approximations can be used without compromising classification performance. The main rationale for using wavelets is their ability to decipher textural information from different scales, which has been shown to significantly improve image classification2. However, the impact regarding the choice of wavelet families or level of decomposition on the performance of radiomics/pathomics methods, remains a poorly addressed topic in the literature. Wavelets are widely used in many fields of research such as time-series analysis, signal denoising3 and filtering for radiomics analysis in medical imaging4. In particular, Sharma et al.5 investigated a feature extraction method based on different multi-resolution schemes by incorporating wavelet packet transform (WPT) and Gabor wavelet transform (GWT) over the ROIs (Regions of Interest) of breast ultrasound images. The examined dataset comprised 167 cases of breast lesions including 60 fibro-adenoma, 50 carcinomas and 57 metastases. A support vector machine (SVM) classifier was used for differentiating among breast lesions yielding accuracy (ACC) up-to 89.5% and sensitivity (SN) up-to 95.5%. Wang et al.6 studied 3 datasets with a total of 381 T2-weighted brain images for pathological brain detection (PBD). Discrete Wavelet Packet Transform (DWPT) of the Haar wavelet family and Tsallis entropy (TE) was used for feature extraction. In particular, sixteen wavelet sub-bands were extracted from the original image and TE was calculated on sub-band coefficients. The classification of breast lesions was performed by a Feed-Forward Neural Network (FNN) trained on DWPT-TE features and achieving a performance accuracy of 99.5%. In another study7, the WPT of the Daubechies family was examined as a pre-processing method for the B-mode ultrasound liver images over the RF frames. Statistical and texture features such as first-order gray level parameters, gray-level co-occurrence matrix (GLCM), and local binary patterns (LBP) were calculated and machine-learning selection and classification was applied. The author claims a significant reduction in computational time up-to 75% with a cost of only 1% in terms of performance accuracy. Takruri et al.8 proposed a feature extraction methodology by combining the energy of multiple wavelet coefficients from melanoma histopathology images, achieving a performance accuracy of 87.1%.Pathomics are features stemming from the analysis of digitized histopathology images with the use of image analysis methods that extract sub-visual attributes for characterizing disease appearance and behavior. As in radiomics, the main image processing methodology used to extract a large number of characteristic image features is texture analysis. However, is it well known that texture may exist in different scales9, introduced machine and deep learning analyses on this challenging multi-class problem. A variety of imaging features  and machine learning classifiers  were examined, achieving an accuracy of 87.4%10. Cascianelli et al.11 investigated a pre-trained “off-the-shelf” deep learning (ACC 84%) and machine learning approaches (ACC 72.8%-79.6%) with texture spectrum features and principal component analysis (PCA) over a wide range of datasets including the examined. Sarkar et al.12 proposed a saliency guided dictionary learning (SDL) framework achieving ACC from 51.1 to 73.7% for a 7-class subset of the original set excluding patches from the background class. However, it should be noted that these studies did not follow a multi-scale approach in feature extraction which can be the reason for the limited performance reported.Some noteworthy studies on the examined histopathology dataset18 the impact of different families or level of decomposition on the performance of their experimental methods is rarely investigated. The lack of such an analysis highlights a critical scientific question regarding the optimal use of wavelets in the context of radiomics or pathomics approaches in medical image analysis in order to evaluate the effectiveness of image features at different frequency bands. To this end, an exhaustive multi-scale pathomics analysis integrating WPT filtering with all available wavelet transforms and different levels of decomposition was conducted to identify the optimal set of level, sub-band and family for improved CRC tissue differentiation. In particular, improvements such as lower computational cost of the analysis and increased classification performance (up-to ACC 95.3%) were observed in the examined histopathology dataset compared to the current state-of-the-art literature10 (ACC 87.4%). The main contribution of the presented paper is the first in-depth application of wavelet analysis for pathomics-based multi-class pathology tissue classification, investigating the role of scale through wavelet image decomposition and achieving improved performance compared to the state-of-the-art methods.In this paper, the WPT was used both as a composite pre-processing (filtering), image decomposition scheme and as a feature extraction methodology for improving the performance and accelerating the convergence of machine learning and artificial neural network (ANN) models. It is noteworthy that in oncology imaging studies with waveletscritical value. The Fcritical value was calculated by the percent point function19 using the aforementioned threshold in conjunction with the degrees of freedom of the dataset. It should be noted that the best features were comprised of first order statistics over the raw wavelet and gabor image (4 pixels per circle), local binary pattern features with finer quantization of the angular space, energy, dissimilarity, correlation, angular second moment from grey level features with a distance of one pixel. Three classification strategies were applied: support vector machines with radial basis function trained on full pathomics or selected pathomics and artificial neural networks trained on full pathomics. Only two parameters were variable across each analysis pipeline: the mother wavelet and the level of decomposition. Hyper-parameter optimization  was applied to assess the fitting status and mitigate the overfitting of the ANN. On average, more than 200 epochs were required for the ANN model to converge. The use of an early-stopping technique, in which the training is terminated when the validation error reaches a global minima, aided in preventing model overtraining. A few thousand models were evaluated during the experimental phase of this study. The computational infrastructure used during the experiments comprises an 8-core i7 processor with 24 gigabytes of RAM and a GTX 1070 graphics processor with 8 gigabytes of VRAM. Approximately 150 hours required for the proposed feature extraction process to complete on the entire dataset of 5000 colorectal image patches. This includes the calculation of all the examined wavelet families with up-to six levels of decomposition, selection and the extraction of the multi-level features. Additionally, 20 hours required for the SVM classification (with and without feature selection) and approximately 40 hours for the ANN convergence and evaluation. The SVM-based models (with and without feature selection) achieved accuracy up-to 84%, which is comparable to the published “off-the-shelf” deep learning approach11. It is worth noting that models based on ANNs scored the highest performance (up-to ACC 95.3%), particularly in the second level of approximation of symlet wavelet family, as evident by Table Sample selection bias is a common risk when applying machine learning techniques, particularly in ANN. This can lead to a compromised model with limited generalization capacity. A hold-out method was performed on the full dataset for randomly selecting the 10% of the images as a validation set for applying feature selection on the SVM experiments and hyperparameter optimization during the ANN convergence. In addition to the hold-out method, an iterative tenfold cross-validation process was applied on the rest 90% for splitting the images into a training set for model fitting and an unseen testing set per split for model evaluation. In particular, the validation set consisted of 500 images and at each cross-validation split, 4050 images were used as a training set and 450 for the testing set. The class balance across all sets was preserved to assess an unbiased performance analysis. There are 625 tissue samples (12.5%) of each of the eight categories in the examined colorectal dataset. Maintaining these ratios in the smaller validation and testing sets is important for both the feature selection and model evaluation tasks respectively, because it ensures that each class is represented equally and no bias is introduced from the data stratification process. The studied tissue tiles were subjected to wavelet decomposition up to six layers and using the six discrete wavelet families , generating 378 sets of approximated images. A corresponding number of sets of imaging features were calculated from the WPT images. This resulted in the same number of models per analysis pipeline . A multi-level feature extraction method  performed significantly lower than the proposed methodology (ACC 87.4% versus 95.3%), as shown in Table 10/79.6-8411/73.712%). ANN models were introduced to address the limitations of a feature-based selection process that was followed by the proposed SVM and examined studies12, enabling a fully automated analysis of the complete pathomics feature vector. As a result, a significant reduction in terms of classification error was achieved. The use of WPT in the proposed pathomics classification approach led to an efficient feature extraction pipeline exploiting a variety of mother wavelet transformations with lower computational complexity. Nevertheless, the prediction error increased when deeper levels of WPT decomposition were applied regardless of the mother wavelet, feature extraction or classification method. This effect can be observed in Fig. To date, wavelet decomposition has been used for feature extraction or as a filtering method in medical image analysis and radiomics but the selection of its parameters has not been thoroughly investigated12 excluded the background class. The first and the second decomposition levels were found . The formalin-fixed paraffin-embedded colorectal primary tumor tiles were gathered from the University Medical Center Mannheim (Heidelberg University) in Germany. Manual extraction of 5000 patches with 74 by 74 μm dimension (0.495 μm per pixel) was performed in a set of ten digitized hematoxylin & eosin (H&E) stained tissue slides. In particular, the patches were organized into eight classes  and hyperparameter optimization/early stopping . Additionally, on the remaining images a 10-fold cross-validation was performed iteratively for splitting into training and unseen testing sets. The three separate sets ensured a fair and unbiased model evaluation. In total, three different classification strategies were performed, two based on SVMs and one on ANN. The SVMs were applied on the full pathomics vector and on a set of statistical significant features. An extensive hyperparameter optimization was performed to identify the best configuration of ANN, including the learned parameters (number of neurons and layers) and other parameters such as learning rate, dropout rate, activation functions and optimizer. The ANN models were trained on the 532-pathomics vector.The wide variety of cell and tissue types in the studied dataset constitute a complex classification problem and was the main motivation for proposing a framework for investigating the impact of multi-scale wavelet transformations in terms of texture analysis. WPT was applied on the histopathology tiles using every discrete mother wavelet and level of decomposition available in the pywavelets libraryThe proposed feature extraction approach is comprised of individual operators such as WPT, Gabor, LBP and GLCM paired with first-order statistics and combinations of higher order statistics methods. This diverse set of simple and complex features with multiple levels of analysis aims in forming a discriminative and robust pathomics signature. The final vector consists of 532 imaging features. A detailed depiction of the proposed multi-level feature extraction methodology is provided in Fig. 23.Since a thorough description of the mathematical background is demanding and beyond the scope of this work, we briefly, present the one dimensional continuous wavelet transform below. Further in depth information regarding the two dimensional discrete wavelet transform applied to images can be found in literarureAssume a function f(t) in the set of square integrable functions In Eq. , *represTo explore textural information from the studied histopathology images a variety of bases of discrete mother wavelets were used from the pywavelets library such as Haar (haar), Daubechies (db), Symlets (sym), Coiflets (coif), Biorthogonal (bior), and Reverse biorthogonal (rbio). Other families of such as Gaussian wavelets (gaus), Mexican hat wavelet (mexh), Morlet wavelet (morl), Complex Gaussian wavelets (cgau), Shannon wavelets (shan), Frequency B-Spline wavelets (fbsp), and Complex Morlet wavelets (cmor) wavelets were rejected because of their continuous nature. An indicative illustration of these wavelet transforms applied to a lymphoid follicles tile image is depicted in Fig. 24 calculated over five directions and four wavelengths from 4 to 20 pixels per cycle. Additionally, various rotation angles (from 70° to 190°) were employed on the original input image.The wavelet transformed image tiles were used as the input for filtering with multiple Gabor kernelsIn Eqs.  and 3 K 25. A radius of one pixel and with eight symmetric neighbors was selected for calculating this visual descriptor. The arrow path in Fig. The LBP images were calculated over the WPT approximations with three methods including gray scale invariant, variance measures of the intensities of local texture, and uniform patterns with finer set pointsIn Eq.  P denote26. In particular, four angles from 0° to 135° and three distances from 1 to 5 pixels were calculated. A set of higher order statistical features such as contrast [Eq.  features are based on the co-occurrence of intensities of the pixels at a given direction and distanceast [Eq. ], homogeast [Eq. ], correlast [Eq. ], angulaast [Eq. ] and eneast [Eq. ], were c2 the variance of the intensities of the reference pixels, N is the number of gray levels and Pi,j the normalized GLCM element.In the above equations μ denotes mean, σ27 Test) was used for feature selection on the extracted pathomics in one SVM model of the presented analysis (the other used the full feature vector). The joint analysis of p-values with the corresponding F-values of the examined vector supported the identification of a subset of features establishing a compact and discriminative signature. This method was applied during the experimental phase and solely on the validation set reducing the dimensionality of feature vector. Based on these derived feature labels, the statistically significant components were then selected in both training and testing sets. The later remained unseen throughout this process. No feature selection method was applied during the ANN experiments.The analysis of variance  based SVM models were trained on selected and full pathomics to establish the baseline of the analysis. ANN were trained and evaluated on the complete pathomics signature as high-level data analysis models for end-to-end and fully-automated feature selection and classification. A cross-validation data stratification technique was applied to separate the dataset in ten parts one serving as the unseen testing set and the rest as the training set with iteratively interchangeable roles among the splits.The studied dataset is comprised of 8-classes, as discussed mentioned. Thus, the multiclass model was assessed by the classification accuracy where TP, TN, FP, and FN stand for true-positive, true-negative, false-positive and false-negative respectively. The performance metrics presented in the following sections refer to the average accuracy of the 10-fold cross-validation.


Background: Since December 2019, SARS-CoV-2 has continued to spread rapidly around the world. The effective drugs may provide a long-term strategy to combat this virus. The main protease (Mpro) and papain-like protease (PLpro) are two important targets for the inhibition of SARS-CoV-2 virus replication and proliferation. Materials & methods: In this study, deep reinforcement learning, covalent docking and molecular dynamics simulations were used to identify novel compounds that have the potential to inhibit both Mpro and PLpro. Results and conclusion: Three compounds were identified that can effectively occupy the Mpro protein cavity with the PLpro protein cavity and form high frequency contacts with key amino acid residues . These three compounds can be further investigated as potential lead compounds for SARS-CoV-2 inhibitors. De novo drug design can provide effective treatment for COVID-19. It also has meaningful impact on the prevention and treatment of similar viruses in the future.In this century, three globally endemic coronaviruses have emerged: the severe acute respiratory syndrome coronavirus (SARS-CoV), the Middle East respiratory syndrome coronavirus (MERS-CoV) and the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). SARS-CoV-2 emerged in Wuhan, China, in December 2019 [SARS-CoV-2 is an enveloped, positive-sense, single-stranded RNA virus . This isThe Mpro active site contains a catalytic dyad consisting of the conserved residues His41 and Cys145, and the PLpro active site contains a catalytic triad consisting of Cys111, His272 and Asp286 [In recent years, deep learning (DL) has been applied to various aspects of drug development, such as constructing a quantitative structure activity relationship and predicting compound properties . In addition to these, DL is also used for chemical structure generation. There are several approaches to molecular generation, such as character-level recurrent neural networks ,10, variIn this study, the dual-target covalent inhibitors of Mpro/PLpro were designed using deep reinforcement learning (RL) and traditional computer-aided drug design methods. A library of Mpro/PLpro small molecules was generated using deep RL. The molecules were then screened using molecular docking and dynamics simulations to obtain covalent inhibitors that act on both targets  and related references [The long short-term memory neural network model (LSTM) was used as the generative model. The model was constructed using the VENT 2.0 . First, ferences . The LSTThe Random Forest classifier , generatThe generative and predictive models were integrated into the RL system. Four indicators were used to evaluate the small molecules: the activities to Mpro and PLpro, synthetic accessibility score  (SA) andhttps://www.rcsb.org). Proteins were preprocessed with the Protein Preparation Wizard [Covalent docking was performed on the covalent docking module (CovDock) of the Schrödinger Suite . The cryn Wizard  by assign Wizard . The pren Wizard  score waThe molecular dynamics simulations were carried out using the Desmond program in the Schrödinger Suite with the OPLS 2005 forcefield ,47. The The generative model was constructed using REINVENT 2.0 and the predictive model was constructed using scikit-learn. The generative and predictive models were evaluated, respectively. The validity of the generated molecules was a key metric for evaluating the generative model. The result is shown in Subsequently, the small molecules generated by reinforcement learning were evaluated. Principal component analysis on the features of the training data and the generated small molecules (GSMs) were performed. As shown in As shown in Supplementary Figure 1, and the cdock affinity scores and Molecular Mechanics Poisson-Boltzmann Surface Area (MMGBSA) scores are shown in Supplementary Table 1. The cdock affinity reflects the difficulty of forming covalent bonds between the ligand and the receptor; ligands with low scores are less likely to form covalent bonds to the receptor. Three compounds were selected by comprehensively considering the cdock affinity scores and MMGBSA scores of these 20 compounds in both targets. As shown in After covalently docked to Mpro and PLpro, 105 small molecules were obtained from the 4428 compounds. These 105 small molecules have the capacity to form covalent bonds with Cys145 of Mpro and Cys111 of PLpro. Then the top 20 compounds were docked to Mpro and PLpro using the pose prediction mode. The structures of these 20 compounds are shown in The molecular docking diagrams of the three compounds with Mpro and PLpro are shown in The results of molecular dynamics simulations of the complexes of A3175, A3659 and A3777 with Mpro and PLpro are shown in The results of the protein–ligand interactions during the dynamics simulations are shown in For the design of dual-target inhibitors, the balancing of the effects between the two targets was a complicated and challenging task. DL has unique advantages in balancing multitarget activity. In this work, the dual-target covalent inhibitors of Mpro and PLpro were designed by deep RL and virtual screening. First, a novel library of small molecule inhibitors for SARS-CoV-2 was generated using deep RL. The GSMs inherited the features of the small molecules in the training set. A total of 4428 small molecule compounds were obtained. Subsequently, covalent docking studies were carried out on these small molecules. One hundred five small molecules that can covalently bind to cysteine at the active site of Mpro and PLpro were obtained. The top three compounds according to overall scores were analyzed for docking results. All three compounds can form covalent bonds with cysteines in the catalytic sites of Mpro and PLpro proteins. In addition, the interaction of compounds with key amino acid residues within the cavity of Mpro  and PLpro  proteins was also observed. Dynamics simulations were then carried out for the three compounds. The RMSD results show that all three compounds can bind stably to Mpro and PLpro proteins. The analysis of compound–protein interactions during dynamics simulations showed that all three compounds formed stable hydrogen bonding interactions or hydrophobic interactions with key amino acid residues within the protein cavity, such as His41, Cys145 and Cys111. To summarize, the three compounds have the potential to be lead compounds for dual-target inhibitors of SARS-CoV-2 Mpro and PLpro. This may provide a good foundation for the discovery of anti-SARS-CoV-2 drugs. This study applied deep RL to the design of covalent inhibitors and produced positive results.Dual-targeted drugs have the advantage of fewer adverse effects and better therapeutic outcomes than single-targeted drugs. However, most of the current multitargeted drugs have been discovered by chance, and the rational design of multi-targeted drugs is a complex and sophisticated task. One of the difficulties in the design of dual-target inhibitors is balancing the activity of the compound between the two targets. The recent rise in artificial intelligence drug design offers a new option. Our method incorporates the advantages of existing drug design techniques with artificial intelligence technologies, which will accelerate the discovery of and optimize drug lead compounds, as well as reduce the cost of drug development.Applying deep reinforcement learning to the design of covalent inhibitors.Deep reinforcement learning methods were used to learn the features of existing main protease (Mpro) and papain-like protease (PLpro) inhibitors.A range of small molecules with the features of Mpro and PLpro inhibitors were generated.The generated small molecules were screened using covalent docking.Molecular dynamics simulations further investigate the stability of small molecules bound to proteins and their interactions.High frequency interactions of selected compounds with key residues at the binding site were observed.Selected compounds can facilitate the rational design of anti-SARS-CoV-2 drugs.Click here for additional data file.


Magmatism plays a key role in the process of continental margin breakup and ocean formation. Even in the extremely magma-poor Iberia and Newfoundland margin, studies of field outcrops have shown that syn-rift magmatism had participated in rifting from a very early stage and contributed directly to the rifting process. The final transition from exhumed continental mantle to the ocean formation is also triggered by the accumulation and eruption of magma . TherefoThe South China Sea (SCS) is a marginal sea surrounded by subduction zones on three sides Fig. . OnshoreTo test what kind of thinning process might have controlled the transition from continent to ocean in the SCS, International Ocean Discovery Program (IODP) Expeditions 367, 368 and 368X were carried out in 2017 and 2018. Seven sites were drilled from the Outer Margin High (OMH) to the continent–ocean transition (COT) and to the early ocean basin   and magma-rich (magmatic underplating).Without SDRs being observed, most researchers suggested that the HVLC in the northern continental margin was underplated either in the Mesozoic pre-rift or post-rift stages. The widely distributed HVLC below the highly extended rift center and COT area discords with the pre-rift model. Yao  suggesteEvidence for the melting of a fertile asthenospheric mantle has been found in the middle Miocene E-MORB samples; it was also detected in the ocean island basalt-type samples from early to late Miocene, but not in the 25-Ma MORB samples recovered in southern Taiwan . Thus itMajor- and trace-element analyses suggest that the fertile composition of the upwelling asthenosphere showed strong signals of recycled plates, which might be originated from subduction . SeismicBased on seismic interpretation, forward modeling of gravity and magnetics, seismic tomography and IODP drilling results, we suggest that the northern central margin of the SCS might have experienced two stages of magmatic process. It started with less magmatic extension and a highly extended margin with mainly seaward-dipping detachment faults formed. Diking induced by decompressive melting increased until breakup occurred around 30–34 Ma. Fertile upwelling arrived at the seafloor after ~25 Ma and led to magmatic underplating as well as seamount eruption. Given the co-existence of the MORB and Ocean Island Basalt, the two stages are not completely separated in time. The magmatic overlapping may play an important role in the late-rifting and especially spreading processes. Therefore, we propose that the SCS might represent a ‘plate-edge or Pacific-type’ extensional basin typical of marginal seas . The strNR_MS-2019-118_Supplementary_Data_nwz116Click here for additional data file.


The aim of this study was to evaluate the shear bond strength and the nanoleakage expression of CLEARFIL Universal Bond Quick and Tetric N-Bond adhesive systems bonded to dentin. self group) and Tetric N-Bond (Tetricself group) applied in the self-etch mode, while 2 groups had Universal Bond Quick  and Tetric N-Bond  applied in the total-etch mode. n = 15 for shear bond strength and n = 10 for nanoleakage experiment. One-way ANOVA and Kruskal-Wallis test were utilized to analyze the shear bond strength test and the nanoleakage expression, respectively.  100 freshly extracted human premolar teeth were utilized. The teeth were sectioned to expose dentin. All dentin specimens were assigned into 4 experimental groups; 2 groups had Universal Bond Quick  when compared to the remaining three groups. There were no statistically significant differences between the shear bond strength values recorded in the Tetrictotal, Universalself, and Universaltotal groups (p < 0.05). Both bonding systems applied in the self-etch mode  had no silver nitrate deposits in the hybrid layer and the hybrid layer-adhesive interface (p < 0.001); however, both bonding systems applied in the total-etch mode  had silver nitrate deposits in the hybrid layer, the hybrid layer-adhesive interface, and the bonding layer (p < 0.001).  The highest significant bond strength value was recorded by the Tetric Applying the Universal Bond Quick and Tetric N-Bond in the self-etch mode exhibited better results in terms of nanoleakage expression. Universal Bond Quick showed the stability of the shear bond strength to dentin when applied using the total-etch or self-etch modes. Tetric N-Bond showed significant deterioration in bond strength when applied in the total-etch mode and exhibited the highest bond strength when applied in the self-etch mode. The introduction of self-etch adhesives in the late 1980s revolutionized the science of dental adhesives; many advantages were associated with the use of the self-etch approach to the dentin surface which may include its ease of use [Moreover, the less aggressive acidic treatment associated with the self-etch approach  preserved the smear plugs into the dentinal tubules thus decreasing the deteriorating effect of the pulpal pressure on the adhesive-dentin interface , 3.One of the unique features associated with the use of self-etch adhesives possessed is its capability to simultaneously condition and penetrate the dentin collagen network , 4, 5. TApplication of the self-etch adhesives on dentin cervical cavosurface margins in Class V cavities rendered these margins resistant to a simulated caries attack when compared to etching these margins with phosphoric acid prior to bonding .All of these advantages were reflected as a clinical success of the mild self-etch adhesives in the form of less postoperative pain symptoms and prolonged clinical performance for most of the 2-step mild self-etch systems , 4. ThisThe new generations of one-step self-etch adhesives are currently called universal dental adhesives due to their unique feature of durable bonding to coronal dental tissues –11 and d100 premolar teeth freshly extracted for orthodontic purposes were utilized in the current study. The teeth were collected from the oral surgery department after obtaining the permission of the ethical committee of the faculty. The teeth were hand-scaled from any calculus or soft tissues. The teeth were stored in 0.1% thymol till the start of the experiment according to the guidelines approved by the University. The number of specimens assigned to each group was adopted according to the threshold for significance which was set at 0.05 and means and standard deviation obtained in a pilot study and the power of test which was set at 80% . Randomiself group) and Tetric N-Bond (Tetricself group) applied in the self-etch mode, while 2 groups had Universal Bond Quick  and Tetric N-Bond  applied in the total-etch mode. n = 15 for shear bond strength and n = 10 for nanoleakage experiment.All dentin specimens were assigned into 4 experimental groups; 2 groups had Universal Bond Quick  for 6 h under fluorescent light to reduce silver ions into metallic silver . The silα = 0.05. Software utilized for analysis was SPSS v24 .One-way ANOVA was used to analyze the shear bond strength, whenever there was a significant difference, the post hoc test was utilized for further analysis. The nanoleakage expression results were analyzed the by Kruskal-Wallis test . The levp < 0.001) while it did not affect the Universal Bond Quick system (p < 0.05). The highest significant bond strength value was recorded by the Tetricself specimens (p < 0.05) when compared to the remaining three groups. There were no statistically significant differences between the shear bond strength values recorded in the Tetrictotal, Universalself, and Universaltotal groups (p < 0.05).p < 0.001). Both bonding systems applied in the self-etch mode  had no silver nitrate deposits in the hybrid layer and the hybrid layer-adhesive interface (p < 0.001); however, sporadic particles of silver nitrate particles were observed in the bonding layer itself. Both bonding systems applied in the total-etch mode  had silver nitrate deposits in the hybrid layer, the hybrid layer-adhesive interface, and the bonding layer (p < 0.001).The null hypothesis in the current experiment was rejected as the mode of adhesive system application affected the nanoleakage expression and had significant effect on the shear bond strength. The limitations of this study might include the utilization of the shear bond strength test with cylindrical-shaped composite cylinders having a diameter of 3 mm. If we have utilized the microtensile bond strength test, the tested bonded surface would have been smaller  and thusRegarding the other tests adopted in the current experiment, it is worth mentioning here that the nanoleakage test is considered an important index for the durability and the sealing ability of adhesive restorations , 14–16. The presence of collagen fibrils which are not encapsulated by a resin coating after polymerization of the adhesive resin and forming the hybrid layer may lead to a sequence of detrimental effects on the adhesive restorations –21. ThesOn the other hand, employing the same bonding systems without employing the phosphoric acid etching procedure exhibited less nanoleakage expression which may be attributed to the simultaneous conditioning and penetration of the tested adhesive systems within the dentin structure , 4 whichtotal group which was expressed by the relatively weak EDS silver peak observed in the Universaltotal group when compared to the strong silver peak observed in the Tetrictotal group  than HEMA (logPow (0.3) , indicatal group . Althougtotal group. This dentin-adhesive interface contamination by water might have led to HEMA water sorption [On the contrary, Tetric N-Bond showed significant deterioration in its bond strength when applied in the total-etch mode which may be attributed to the high content of HEMA in this adhesive system which is 10-25% compared to the Universal Bond Quick that contains approximately 2.5%. It is speculated that HEMA in Tetric N-Bond was much affected by the fluids seeping into the denuded collagen fibrils of the hybrid layer that was created due to applying the phosphoric acid in the Tetricsorption  and a deInterestingly, the high content of HEMA seemed to improve the performance of the Tetric N-Bond when applied in the self-etch mode by improving the penetration of the bonding system into the self-etched  dentin sPrevious literature showed controversial outcomes when compared to our results. On the one hand, a clinical study  comparedOn the other hand, another clinical study  showed tAdditionally, a previous review of literature  emphasizThe outcome of this in vitro study should be interpreted carefully in terms of its clinical relevance because this study did not include any durability challenges such as pH cycling, thermal cycling, and cyclic loading which simulate the physiological conditions inside the oral cavity that include repeated expansion and contraction stresses due to oral cavity temperature variation and erosive challenges induced by acidic chemicals in saliva and food , 34. ThuApplying the Universal Bond Quick and Tetric N-Bond in the self-etch mode exhibited better results in terms of nanoleakage expression. Universal Bond Quick showed the stability of the shear bond strength to dentin when applied using total-etch or self-etch modes. Tetric N-Bond showed significant deterioration in bond strength when applied in the total-etch mode and exhibited the highest bond strength when applied in the self-etch mode.


A novel approach to preparing the material for intermediate layer by modifying the graphene flakes by gold nanoparticles is presented. With this approach, we observed a large surface area of material and in consequence high electrical capacitance of electrodes. We have obtained satisfactory results demonstrating that the modification of graphene with gold allows for enhancing electrical and wetting properties of carbon nanomaterial. Electrical capacitance of designed nanocomposite-contacted electrode equals to approximately 280 µF, which in consequence ensures great long-term potential stability defined by the potential drift of 36 μV/h. The modification of graphene with nanoparticles completely changed its wetting properties, as the designed material turned out to be hydrophobic with a water contact angle of 115°. Graphene/gold nanoparticles–contacted electrodes are insensitive to the changing light conditions, exhibiting near-Nernstian response in the potassium concentration range between 10 Nanomaterials, commonly known as materials with a single unit sized up to 100 nm, have been widely applied for the construction of ion-selective electrodes (ISEs) , using tAll-solid-state electrodes have their origin in early 1970s when Catrall and Freiser  made a sNanomaterials belong to a group with large surface area, which ensures that high double-layer capacitance is formed in the interface between the solid-contact layer and membrane. The wide implementation of nanomaterials results from their unique physical and chemical properties, such as large surface/volume ratio and large pore volume, ensuring unique surface chemistry and good conductivity . These fThis work describes the design of a nanomaterial composed by modification of graphene flakes (GR) by gold nanoparticles (AuNPs) and its application in ion-selective electrodes’ construction as solid-contact layer. Graphene (GR) belongs to the group of carbon nanomaterials that are among the most widely used materials for solid-contact layer. It is a two-dimensional carbon material with only one atomic layer that shows unique properties such as a fast electron transportation, a high surface area, a high thermal conductivity, and excellent mechanical properties ,12. The Although both materials used in this work were already applied as solid-contact layers individually, combining them into one material allowed us to obtain a hydrophobic layer, of much higher contact angle and greater electrical parameters in comparison with other, as mentioned above, graphene–based composites. To the best of our knowledge, our group is the first one to apply graphene/gold nanoparticles material in the construction of ion-selective electrodes and obtain satisfactory results demonstrating that the modification of graphene with gold allows for enhancing electrical and wetting properties of carbon nanomaterial. Obtained results are promising in the context of designing solid-contact ion-selective electrodes and were presented in the next sections. This paper has been divided into the following parts: material characteristic and electrical and analytical characterization of ion-selective electrodes with nanomaterial layer.4 acting as a reductor. Graphene flakes decorated with gold nanoparticles were dispersed in dimethylformamide (DMF) (POCH).The solid-contact layer consisted of graphene obtained from ACS Material, gold nanoparticles, and was provided by 3D-nano, Poland, with Sodium borohydride NaBHThe membrane components: potassium ionophore I , lipophilic salt–potassium tetrakis(4-chlorophenyl)borate (KTpClPB), 2-nitrophenyl octyl ether (o-NPOE), and poly(vinyl chloride) (PVC) were purchased from Sigma-Aldrich and dissolved in Tetrahydrofuran .−7 to 10−1 M were used for potentiometry, chronopotentiometry, and EIS measurements. Hydrochloric acid and sodium hydroxide used for adjusting the pH value of solutions during the pH sensitivity test were purchased from POCH, Gliwice, Poland.Potassium chloride (KCl) was purchased from POCH  and solutions of K+ ions concentration from 10Graphene modified with gold nanoparticles was implemented onto the glassy carbon disc electrode’s surface and the material was examined for its suitability as intermediate layers in ion-selective electrodes.4  was mixed thoroughly with DMF/graphene dispersion  for 20 min with the assistance of sonification. Afterwards, NaBH4 , acting as a reducing agent, was added rapidly to the solution being mixed under vigorous stirring. Such a prepared solution was washed by centrifugation  in order to remove the excess of the reducing agent, and subsequently redispersed in DMF. The washing procedure was repeated three times.Solid-contact layer was casted onto glassy carbon disc electrode surface using the drop casting method, which among other techniques is considered to be the fastest and the simplest. In order to obtain the solid-contact layer, the DMF-based solution of graphene modified with nanogold was prepared by a simple one-pot method. For this purpose, HAuClAt the beginning of the preparation process, glassy carbon disc electrodes were polished with alumina slurries and rinsed with water and methanol, alternately. Clean and dried electrodes were casted with 20 µL of solid-contact layer solution. DMF was removed from casted layers by evaporation process until only the solid particles were left at the electrode’s surface. At this stage, the layers were tested without membrane in order to examine their electrochemical properties.w/w), KTpClPB 0.25% (w/w), o-NPOE 65.65% (w/w), and PVC 33.00% (w/w). All membrane components of total weight 0.125 g were dissolved in 1 mL of THF. The solvent was evaporated in the room temperature and after 24 h, the conditioning process begun as electrodes were placed into 0.01 M KCl solution in order to saturate the membrane with K+ ions.The experimental part was followed by casting the obtained layers with 60 µL of ion-selective membrane solution of the following composition: potassium ionophore I 1.10% , contact angle microscope, Electrochemical Impedance Spectroscopy (EIS), and chronopotentiometry method were used for material characterization and the potentiometry method was implemented to evaluate the influence of the layers’ presence on the ion-selective electrodes’ analytical performance.The microstructure of studied graphene/gold nanoparticles material was investigated with Transmission Electron Microscope Tecnai 20 X-TWIN  fitted with Energy Dispersive X-Ray Analysis (EDAX) and High Angle Annular Dark Field (HAADF) detectors.In order to examine the wetting properties of the obtained material, contact angle microscope Theta Lite microscope with One Attension software by Biolin Scientific  was implemented into studies.For chronopotentiometry and electrochemical impedance spectroscopy method, glassy carbon disc electrodes were covered with the studied graphene/gold nanoparticles material and placed into a measuring cell in sequence, together with reference Ag/AgCl electrode with 3 M KCl solution  and auxiliary-glassy carbon electrode. All electrodes were connected to the Autolab analyzer . The cell was filled with 0.01 M KCl solution acting as an electrolyte. Both chronopotentiograms—the potentiometric response of electrode recorded with time in the forced current conditions and Nyquist plots, on which the imaginary part of impedance (Z″) is plotted on the y axis, and the real part of impedance (Z′) on the x axis, were collected using NOVA 2.1 software.−1 to 10−7 M concentration were used as K+ ions standard solutions.For potentiometry method all prepared ion-selective electrodes with gold nanoparticles layer and potassium-selective membrane and the coated-disc electrode were connected to the 16-channel mV-meter  and measurements were conducted against Ag/AgCl electrode  reference electrode in the presence of platinum auxiliary electrode. For this measurement, KCl solutions of 10The examined material was graphene modified with gold nanoparticles, which was tested using TEM microscope to explore the microstructure. Further, a contact angle microscope was used to evaluate the wetting properties and Autolab analyzer was used to evaluate the electrochemical behavior.Pictures obtained from the TEM microscope were presented in w/w) and carbon 80.55% (w/w).In the BF scan nanoparticles are visible as dark points on the graphene flakes (of lighter color) while in the HAADF (High-angle Annular Dark-field) scan, gold nanoparticles can be spotted as light points. This was also confirmed by the EDS analysis, as for the lightest point . The wettability of graphene/gold nanoparticles material was tested using the contact angle microscope; the water droplet of 5 µL was discharged onto the materials’ surface, while software measured the angle between the surface and the tangent to the water drop, as shown in The software gave the contact angle a value of 115°, which indicates that the designed material is hydrophobic. The obtained results were compared with those presented in our previous work concerning the graphene/ruthenium dioxide material. The contact angles of 49.5° and 61.9° were reported for graphene individually and graphene/ruthenium dioxide composite, respectively ,19.Implementing hydrophobic intermediate layer into ion-selective electrodes’ construction was repeatedly shown to prevent the formation of water film. This is not only crucial in the context of analytical performance of electrodes but also when it comes to the lifetime of electrodes, as a water layer under an ion-selective membrane causes the delamination of membrane and, in consequence, mechanical damage of the electrode.Designed electrodes were characterized with the use of two electrochemical techniques: chronopotentiometry and electrochemical impedance spectroscopy.Based on the chronopotentiograms recorded with the use of electrodes covered with tested graphene-gold nanoparticles layer, the electrical parameters of the layer were evaluated including electrical capacitance and resistance. With solid-contact layers for ion-selective electrodes, the higher the electrical capacity, the more stable the potentiometric response of electrodes is. Therefore, high values of electrical capacitance and low values of resistance are considered as desirable features. Another method used for the intermediate layer characterization is electrochemical impedance spectroscopy. The Nyquist plot, being the visualization of the imaginary part of the impedance (−Z″) (axis y) and the real part of impedance (Z′) (axis x), is presented in the After being examined, GR-AuNPs–based layers were covered with ion-selective membrane solution in order to obtain ready-to-use solid-contact ion-selective electrodes. The electrical properties of the studied electrodes were also evaluated using chronopotentiometry and electrochemical impedance spectroscopy. The dependencies obtained in the subsequent measurements are shown in Based on the chronopotentiogram, presented in the The EIS measurement results are shown again in the Nyquist plot in For the potentiometric tests, the studied graphene/gold nanoparticles layer was covered with ion-selective membrane, and the ready-to-use electrode was connected to the potentiometer. The characteristics of solid-contact and coated-disc electrodes were recorded in standard KCl solutions in order to determine such parameters of electrodes as standard potential and sensitivity .Calibration curves were recorded after 24, 48, and 72 h of conditioning in 0.01 M KCl solution for each group of electrodes (solid-contact and coated-disc) and presented in All tested electrodes exhibit the slope of calibration curve consistent with the theoretical Nernstian value.−6 to 10−1 M) (arrow pointing up) and subsequently solutions of decreasing concentration (arrow down), as shown in To compare the repeatability of the response of the electrodes with solid-contact layer and coated disc electrode, calibration curves were recorded firstly by measuring standard solutions of increasing concentration  was prepared and the potentiometric response of the GC/GR-AuNP/K+-ISM electrode was recorded in each solution. Results of the test are presented in With ion-selective electrodes it is important to examine the pH range in which the potential response is stable and repeatable, therefore, the range in which electrodes may be applied. For the purpose of this test 0.01 M K−5.9 M to 10−1 M.This work explores the association of two nanomaterials by combining them into one nanocomposite material by modifying the structure of graphene with nanometric particles of gold. Throughout the paper we have repeatedly proven that the properties of both materials translate into the electrodes’ performance. The modification of graphene with gold nanoparticles (size approximately 5 nm) allowed us to create a layer of rough microstructure observed with the TEM microscope a high water contact angle of 115°, ensuring the hydrophobic properties of designed solid-contact layer. This feature of solid-contact layer prevents the water layer formation, therefore protecting the electrodes from mechanical damage caused by the membrane delamination. The addition of nanometric particles to carbon material caused the increase of surface area of material and in consequence the increase of electrical capacitance value. High electrical capacitance of solid-contact layer (of 1.8 mF) translated into high electrical capacity of graphene/gold nanoparticles-contacted electrodes . The designed electrodes are insensitive to the light conditions, exhibit stable potentiometric response  and may be applied in the pH range between 2 and 10.5 and potassium ions concentration range between 10The paper has proved that the modification of carbon nanomaterial allows for obtaining more satisfactory results in the context of solid-contact ion-selective electrodes and presents a universal approach to designing robust potentiometric sensors for future research.