Temperate phage can initiate lysis or lysogeny after infecting a bacterial host. The genetic switch between lysis and lysogeny is mediated by phage regulatory genes as well as host and environmental factors. Recently, a new class of decision switches was identified in phage of the SPbeta group, mediated by the extracellular release of small, phage-encoded peptides termed arbitrium. Arbitrium peptides can be taken up by bacteria prior to infection, modulating the decision switch in the event of a subsequent phage infection. Increasing the concentration of arbitrium increases the chance that a phage infection will lead to lysogeny, rather than lysis. Although prior work has centered on the molecular mechanisms of arbitrium-induced switching, here we focus on how selective pressures impact the benefits of plasticity in switching responses. In this work, we examine the possible advantages of near-term adaptation of communication-based decision switches used by the SPbeta-like group. We combine a nonlinear population model with a control-theoretic approach to evaluate the relationship between a putative phage reaction norm (i.e. the probability of lysogeny as a function of arbitrium) and the extent of phage reproduction at a near-term time horizon. We measure phage reproduction in terms of a cellular-level metric previously shown to enable comparisons of near-term phage fitness across a continuum from lysis to latency. We show the adaptive potential of communication-based lysis–lysogeny responses and find that optimal switching between lysis and lysogeny increases the near-term phage reproduction compared to fixed responses, further supporting both molecular- and model-based analyses of the putative benefits of this class of decision switches. We further find that plastic responses are robust to the inclusion of cellular-level stochasticity, variation in life history traits, and variation in resource availability. These findings provide further support to explore the long-term evolution of plastic decision systems mediated by extracellular decision-signaling molecules and the feedback between phage reaction norms and ecological context. However, it is not well understood which strategy would be optimal over what timescales, given the variation in environmental conditions.Lysis–lysogeny decisions are also mediated by small signaling molecules released to the environment. For example, the phage or lysis . In thisng study  deduced ng study . For exaA long-standing rationale for the adaptive benefit of lysogeny is that integration by phage into their bacterial hosts enables viruses to persist even when fluctuations drive bacterial densities to low levels. Using a nonlinear model of population dynamics between phage and bacteria, Stewart and Levin  found thHere, we focus on phage of the SPbeta group and the arbitrium system to explore the potential near-term adaptive benefits of arbitrium-dependent decision switches. In doing so, we utilize a control-theoretic framework embedded as part of a nonlinear population model to identify optimal responses of phage to variation in arbitrium concentration. We select a time horizon to maximize the near-term phage reproduction, as measured in terms of the increase in newly infected cells and lysogens—which correspond to epidemiological birth states for phage. This allows us to explore the link between a continuum of strategies, given the variation in near-term selection horizons. As we show, rapidly switching from lysis to lysogeny with increasing arbitrium represents a control-theoretic optimum to maximize cell-centric measures of phage reproduction in the near term. In the Discussion we consider ways to extend the formalism to evaluate the long-term adaptation and speculate on how the evolution of communication-based systems can help shape long-term phage strategies and fitness.2.2.1S), exposed (E), lytic-fated infected (I), or lysogens (L), as well as virus particles (V), see I, cell) or the lysogenic pathway . The lysis–lysogeny decisions are guided by the concentration of a small quorum sensing peptide A (i.e. arbitrium) ; consequently, a single exposed cell E has a probability I state. We represent this model in terms of systems of nonlinear ordinary differential equations, which can be written as follows S, E, L, I, V, and A denote the densities of susceptible cells, exposed infected cells, lysogens, lytic-fated infected cells, virus particles, and arbitrium molecules, respectively. λ + 1/η (see ψ(R) = max(R/(R + Rμin)) is the Monod equation, where µmax and Rin are the maximal cellular growth rate and the half-saturation constant, J and dR are the influx and decay rates of resources, e is the conversion efficiency, and αS is the selection coefficient that measures the relative difference in the reproductive output between lysogens and susceptible cells. Parameter ϕ is the adsorption rate and dI are the cellular death rates of susceptible cells, exposed infected cells, lysogens, and lytic-fated infected cells, respectively. In addition, dV and dA are the decay rate of viruses and molecules. λ is the transition rate from exposed cells to the fate-determined cells, η is the lysis rate, and β is the burst size. The arbitrium molecules are produced by infected cells: L and I at a production rate of kL and kI, respectively. According to AimR receptor of phage phi3T saturates around 500 nM .For tractability, we assume that the probability function ramework  in order2.2tf. The time-normalized growth rate ρ denotes the effective reproductive rate of these infected cells and is given as: We quantify viral reproduction in terms of infected cells in order to compare pure lytic and context-dependent lysis–lysogenic strategies. We use a standard definition of Malthusian fitness, expressed as the time-normalized growth rate of phage-infected cells, from either the lytic or lysogenic pathway e.g. . Newly i2.3θ, θ affects the probability function and changes the exposed cells and lysogens produced at the final time. Thus, the optimization problem can be written as We formulate an optimization problem over different probability functions with the aim of achieving a maximum of near-term phage reproduction as defined in the previous section using a cell-centric metric. By controlling the lysis–lysogeny decisions θ for optimization problem (Q with respect to θ. Let the state vector of the system be represented by n = 7) and let the dependence of the payoff function on the final state be given by Ψ, i.e. Q is linear. Here ei represents the ith unit vector. We represent the nonlinear system  and the rest are set to 0. The initial resource concentration is 40 µ g/ml with no influx, except when the effect of resource level on switching point is studied . Simulation code is written in MATLAB R2020a and is available for download at https://github.com/WeitzGroup/ArbitriumLysisLysogeny.The parameter values used for these results are given in 3.3.1P. We first consider three cases—that of purely lytic (P = 0), mixed (P = 0.5), and purely lysogenic (P = 1) phage , stochastic with an equal probability of lysis or lysogeny (P = 0.5), or the phage always initiates lysogeny (P = 1). In each case, the susceptible cells show a transient increase due to the initial resource concentration, followed by a decline as a consequence of resource scarcity and cellular decay. Lysis also contributes to the decline for the cases of P = 0 and P = 0.5. In the first case of obligate lysis, the viral population quickly increases and a large number of exposed cells are generated, without the formation of lysogens. In the second case, the viral population does not increase as quickly as in the case of a purely lytic strategy due to the fact that half of the infections generate lysogens (which do not produce more virus particles). The mixed strategy also leads to lysogens (in addition to exposed cells), both of which are considered epidemiological birth states. For the last case of pure lysogeny, there is no increase in the virus particles density given the absence of lysis in the initial decision switch . This means the virion density rapidly decreases due to decay and infection of host cells. A purely lysogenic strategy does generate both types of birth states, i.e. exposed and lysogens; however, very few bacterial cells are infected. Consequently, the total aggregate density of exposed cells and lysogens is significantly less than that of either the purely lytic or stochastic strategy.The first, second, and third panels of P = 0), mixed (P = 0.5), and purely lysogenic (P = 1) cases over a 48-h time horizon. As stated previously, the cell-centric metric of fitness depends on the population of lysogens and exposed cells. P = 0.5) becomes more favorable. The change in outcomes with timescales implies that phages that adaptively sense and respond to the state of the infection could potentially outperform phages that utilize fixed strategies.We compare the relative fitness of the purely lytic  where A is the concentration of arbitrium in the system. We initialized the system with 107 bacteria and an MOI of 0.01. For each time horizon we use the optimization framework described in We evaluate the near-term phage reproduction of temperate phage using a communication molecule for lysis–lysogeny decisions and show how time horizons shape the responsiveness to the signaling molecule. Hence, rather than using a fixed value of tf being the time horizon for optimization), with arbitrium production rates of 5 × 107molecules/cell h-1 and 107 molecules/cell h-1, respectively. For the different generation rates, the decision strategy is robust and a corresponding shift in the switching point (from lysis to lysogeny) can be observed. The switching point scales linearly with the production rate of arbitrium . The strategy based on communication performs better than any fixed probability strategy in terms of the sum of the lysogens and exposed cells at the final time. Optimal switching is more than four times better than the highest value achieved for a fixed strategy (for a fixed probability of 0.2), which demonstrates that a phage following such a communication strategy would have a higher near-term reproduction compared to a phage following any other fixed probability strategy. As seen in In order to evaluate the benefits of lysis–lysogeny switching based on responses to communication signals, we compare phage reproduction as measured using a cell-centric metric by computing an optimal strategy with that resulting from fixed strategies. P = 0, P = 0.5, and P = 1). Next, we perform the same analysis for all optimal strategies for the time horizons of 12–48 h and compare them to three fixed strategies  increased initial concentration of resources and (2) resource influx which maintains higher levels of resources in the environment throughout the focal period similar to chemostat growth conditions. As before, we use the optimization approach described in tf . Although the growth rate declines for long time horizons, lysogeny ensures that the phage can persist despite a depleted host population, which is not possible if lysis is continued indefinitely. We note that the inclusion of near-term time horizons independent of intrinsic dynamic timescales has been shown to lead to important constraints enabling transitions from solitary cells to multicellular groups .Even with this simplified model, we observe interesting properties which can shed light on the balance between the lysis and lysogeny pathways. In our model, phage that utilized a fixed strategy of lysis, lysogeny, or stochastic (but non-responsive) switching had lower reproduction rates than phage with optimally responsive switching strategies. Thus, there is a near-term advantage conferred by temperate phage that sense and ‘choose’ the optimal life cycle (lytic or lysogenic) (consistent with the findings of The optimization approach used here has certain limitations. The optimal control method identifies the switching strategy given a fixed time horizon. However, there is no guarantee that this strategy is an evolutionarily stable strategy over the long term. In related work, Doekes et al. used an eco-evolutionary modeling framework to explore the potential evolution of fixed decision strategies . SystemaIn summary, the control-theoretic framework developed here demonstrates additional support for the adaptive value of a sensing mechanism for initiating lysis or lysogeny based on environmental context informed by prior infections. In doing so, our results suggest that the early lysis of cells by temperate phage provides a mechanism for rapid expansion of virus particles that can then, later, preferentially initiate lysogeny given sensing of an extracellularly released communication peptide. When viewing the reproduction of viruses in terms of infected cells, such changes in strategies represent a form of feedback control by which phages both modulate and reshape their ecological context. Moving forward we hope that this near-term control-theoretic framework is useful in evaluating how such sensing mechanisms may evolve over longer time horizons.


Primordial germ cells differentiate into gametes through complex processes over a long period of time. Along the way, environmental signals are integrated into the chromatin state and epigenome, leading to molecular and cellular phenotypes. As a result, a diverse set of genomic and epigenomic information is passed on to the next generation. Despite a common principle of sexual dimorphism in which two types of gametes are produced and passed on to the next generation, the repertoire of genes involved and their functions are extremely diverse among species.Daphnia. These article Research Topic should facilitate a better understanding of the molecular pathways associated with gametogenesis.This article Research Topic covers papers on sexual reproduction in mammals as well as non-mammalian model organisms, such as medaka and Ishihara et al. identified novel paternally imprinted genes by re-analyzing public sequence data sets of sperm and early embryos published in previous mouse studies. They found that these novel paternally-expressed genes in zygotes are associated with H3K4me3 in the paternal genome in sperm and zygotes at the pronuclear stage 3 (PN3), thus identifying an epigenetic inheritance mechanism that is distinct from DNA methylation- and H3K27me3-based imprinting  . In miceShima provides a mini-review on the latest knowledge related to the role of mini-puberty in spermatogonial stem cell (SSC) formation. This phenomenon is known as temporal activation of the hypothalamic-pituitary-gonadal axis during the neonatal period , substantial progress has been made in understanding the mechanisms underpinning gene regulation during gametogenesis. Further technical innovation would shed light on hitherto unknown mechanisms of gene expression, chromatin structure, and nuclear dynamics in gametogenesis of diverse organisms.


Molecular information about bladder cancer is significant for treatment and prognosis. The immunohistochemistry (IHC) method is widely used to analyze the specific biomarkers to determine molecular subtypes. However, procedures in IHC and plenty of reagents are time and labor-consuming and expensive. This study established a computer-aid diagnosis system for predicting molecular subtypes, p53 status, and programmed death-ligand 1 (PD-L1) status of bladder cancer with pathological images.We collected 119 muscle-invasive bladder cancer (MIBC) patients who underwent radical cystectomy from January 2016 to September 2018. All the pathological sections are scanned into digital whole slide images (WSIs), and the IHC results of adjacent sections were recorded as the label of the corresponding slide. The tumor areas are first segmented, then molecular subtypes, p53 status, and PD-L1 status of those tumor-positive areas would be identified by three independent convolutional neural networks (CNNs). We measured the performance of this system for predicting molecular subtypes, p53 status, and PD-L1 status of bladder cancer with accuracy, sensitivity, and specificity.For the recognition of molecular subtypes, the accuracy is 0.94, the sensitivity is 1.00, and the specificity is 0.909. For PD-L1 status recognition, the accuracy is 0.897, the sensitivity is 0.875, and the specificity is 0.913. For p53 status recognition, the accuracy is 0.846, the sensitivity is 0.857, and the specificity is 0.750.Our computer-aided diagnosis system can provide a novel and simple assistant tool to obtain the molecular subtype, PD-L1 status, and p53 status. It can reduce the workload of pathologists and the medical cost. Bladder cancer is the most common entity of the urinary tract, with an incidence rate of 350,000–380,000 cases being reported per year worldwide , 2. BladIt has been clinically proven that the use of accurate status of molecular subtype, programmed death-ligand 1 (PD-L1), and p53 typically helps to determine the appropriate therapy and thus improves the survival rate for patients with bladder cancer –21. At pIn recent years, more and more attention has been paid to the application of deep learning in the analysis and processing of pathological images. In Nicolas et al.  trained In this study, we aimed to establish a computer-aided diagnosis system based on deep learning to predict the molecular subtypes, the PD-L1 status, and the p53 status directly of bladder cancer from pathological images. To complete this system, our work can be divided into five subtasks: (1) segment tumor area from whole slide images (WSIs); (2) train a CNN for molecular subtype recognition; (3) train a CNN for PD-L1 status recognition; (4) train a CNN for p53 status recognition; and (5) evaluate the computer-aided diagnosis system. Four independent CNNs were employed to handle different classification tasks. Due to the outstanding performance of ResNet in alleviating vanishing and exploding-gradient, ResNet was employed as CNNs in this study . After tThis study was approved by the Ethics Committee of The First Affiliated Hospital, Zhejiang University School of Medicine with the informed consent waived. A total of 119 patients with MIBC who underwent radical cystectomy from January 2016 to September 2018 at the Department of Pathology, The First Affiliated Hospital, Zhejiang University School of Medicine were enrolled in this study. Pathologic diagnosis and tumor-node-metastasis staging were performed according to the current World Health Organization  classifiProgrammed death-ligand 1 IHC was conducted using the following assay: Ventana/SP263 . Human placenta sections were used as positive controls. Monoclonal antibodies against CK5/6 , CK20 , CD44 , and p53  were used according to Envision protocols. Two pathologists blinded to the patients’ outcomes evaluated the results. PD-L1 expressions on TCs and immune cells (ICs) were evaluated. The overall PD-L1 positivity was defined as PD-L1 expressions on ≥ 25% of all TCs and/or ICs. p53 abnormal staining was defined as 0 or > 50% nuclear staining. For the molecular subtype in MIBC, the biomarkers CD44 and CK5/6 score as a surrogate for the basal subtype and CK20 for the luminal subtype. Each case was designated as a basal or luminal subtype using the method based on the highest score of any of the above three markers .p < 0.05). Compared with non-basal subtypes, the positive rate of PD-L1 in basal subtypes was higher (p < 0.05). There was no significant relationship observed between PD-L1 expression, sex, tumor stage, lymph node status, nerve infiltration, tumor size, and p53 expression.As shown in The flowchart of the method is shown in (1) Tumor area segmentationSince cancerous urothelial cells have infiltrated into other tissues and are fragmentary in the image, the pixel-level annotation of pathological images is a fallible and time-consuming task. Large number of pathological images with pixel-level annotations were not easily accessible. Inspired by Xu et al. , a weekl(2) Molecular information recognitionClinically, the molecular information of MIBC is analyzed by quantifying the expression status of tumor and surrounding cells. Therefore, 39,562 image tiles with 50% or above 50% tumor area were selected from 119 WSIs for the further molecular information recognition. Due to the different distribution in three kinds of molecular information, three independent deep learning models were trained for the recognition of molecular subtypes, PD-L1, and p53 status, respectively. ResNet-50 was employed to implement these models. According to the actual proportion of cases in different molecular information, the dataset was allocated into the training set, the validation set, and the testing set. All models were developed and trained on the training set, and their hyper-parameters were fine-tuned using the validation set. The performance of all models was evaluated on the testing set. The detail of the dataset for molecular information recognition is described in All models in this study were implemented on Keras v2.2.5 and trained on two NVIDIA GTX 1080Ti GPUs. Keras is a deep learning application programming interface (API) written in Python, running on top of the machine learning platform TensorFlow.(1) The training of tumor area segmentation: We applied random rotation, random mirroring, and random scaling to augment the training data. Both ResNet-34 in cMIL and the instance classifier were trained using an Adam optimizer with a fixed learning rate of 0.001. In cMIL, ResNet-34 was fine-tuned with the pre-trained model on ImageNet, and the batch size was set to 2. In the instance classifier, the batch size was set to 32. During the segmentation stage, the segmentation model was training using Adam optimizer  with a f(2) The training of molecular information recognition: Data augmentation, such as flipping, contrast adjustment, random rotation (rotation angle range 0–180°), random mirroring, and random scaling, was manipulated to avoid overfitting. Each ResNet-50 was fine-tuned with the pre-trained model on ImageNet using Adam optimizer with a warm-up strategy. The learning rate was set to 0.01 and then linearly decreased to 0.001 in 100 epochs. The batch size was set to 32. For molecular subtypes and PD-L1 status recognition, the optimization objective function was computed by the Cross-Entropy Loss Function. For p53 status recognition, in consideration of the extremely imbalanced sample distribution in p53 status, focal loss  was emplpt can be defined in formula (2). α is the weight of classt, γ is a parameter to control the weight and generally set to 2. An appropriate α could make imbalance problem solved more easily, we set α to 0.25 in our experiment.Where The testing set was annotated by three experienced pathologists  and checked by two senior pathologists  as the ground truth for evaluation. The instance classifier was evaluated on the testing set, the accuracy and AUC of the model are 0.9958 and 0.98 . Then thtpN, tnN, fpN, and fnN are the number of pixels for true positive, true negative, false positive, and false negative.where As shown in 1 was used to select useful features from pathomics features and build the prediction models for molecular information recognition. In total, 154 pathomics features, such as pixel intensity, morphology, and nuclear texture for each ROI, were extracted with the CellProfiler platform (version 2.2.1).2 The results in To evaluate the performance of molecular information recognition, the result of the testing set is reported in Bladder cancer is one of the most common malignant tumors of the urinary system, with approximately 400,000 new cases diagnosed each year. The traditional chemotherapy regimen has limited efficacy and is prone to relapse and metastasis with a poor overall prognosis . Unfortu3 is complex and expensive to use. Our computer-aided diagnosis system is implemented in an end-to-end manner. Postoperative specimens from 119 patients with MIBC were used for the training and tests. A weakly supervised method was adopted to segment tumor area from WSI using only image-level labels. With only image-level labels, our method can segment tumor area with high Dice score, pixel accuracy, and Jaccard score . Then three independent ResNet-50 were trained for the recognition of molecular subtype, PD-L1 status, and p53 status. All ResNet-50 were fine-tuned with the pre-trained model on ImageNet. Focal loss was further introduced to alleviate the extreme imbalance between positive and negative samples in p53 status. For molecular subtype recognition, the accuracy is 0.94, the sensitivity is 1.00, the specificity is 0.909. For PD-L1 status recognition, the accuracy is 0.897, the sensitivity is 0.875, and the specificity is 0.913. For p53 status recognition, the accuracy is 0.846, the sensitivity is 0.857, and the specificity is 0.750. These results verify the effectiveness of our system.There is some software available for molecular analysis. However, the available software, such as HALO,To further demonstrate the effectiveness of our proposed method, we visualize the probability heatmaps in Although the proposed method achieved excellent performance, this study still had several limitations. First, our proposed method was trained and tested on a relatively small dataset from a single large hospital, lacking multi-center or external data validation. Future research is needed to incorporate more data from multi-hospital. Second, this study was retrospective, and more prospective data are expected to be included in this study in the future. Third, without the pixel-level labels in training data, the performance of tumor segmentation is not ideal and needs to be improved. In addition, finally, the double-negative type was eliminated for the molecular subtype in this study. We hope we can collect more datasets to implement the recognition of the double-negative. Therefore, these limitations will be overcome in our future work.This study developed a computer-aided diagnosis system that achieved high performance in the recognition of molecular subtypes, PD-L1 status, and p53 status directly from pathological images based on deep learning. Our computer-aided diagnosis system can provide a novel and simple assistant tool to obtain the molecular subtype, PD-L1 status, and p53 status. It can reduce the workload of pathologists and the medical cost.The raw data supporting the conclusions of this manuscript will be made public by the author after approval by the Ethics Committee.YB, HW, and XT: study conception and design. YB, XW, MW, QH, LX, HZ, and CC: acquisition of data. YB, HW, CJ, and MC: analysis and interpretation of data. YB and HW: drafting of the manuscript. HW, CJ, MC, and XT: critical revision of the manuscript for important intellectual content. YB, XW, MW, and KL: statistical analysis. HW: administrative, technical, or material support. XT: supervision. All authors were involved in writing the manuscript and had final approval of the submitted and published versions.HW, CJ, MC, and KL were employed by Hithink RoyalFlush Information Network Co., Ltd. The remaining 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.


Subependymal heterotopia (SEH) is a rare neuronal migration disorder consisting of gray matter nodules along the lateral ventricular walls and is often associated with other brain malformations. Despite most SEH cases showing epilepsy during their lifetimes, very few patients with asymptomatically familial SEH tend to cause misdiagnosis or missed diagnosis. We present four familial SEH cases without any positive symptoms and medical history, including two fetuses, who were diagnosed by MRI and confirmed by genetic testing with mutation of filamin A. This report emphasizes the role of MRI in the recognition of SEH at an early age of gestation and in asymptomatically familial SEH. MRI provides a fast, repeatable, reliable, and cheap choice for detecting and screening familial SEH. Subependymal heterotopia (SEH) is the most common subtype of Gray matter heterotopia (GMH) characterized by nodules of gray matter along the lateral ventricular walls . GMH canA 34-year-old primigravid woman had an uneventful pregnancy until 26 weeks of gestation when she was admitted to our hospital due to abnormalities detected during fetal ultrasonography (FUS) examination. FUS suggested a widened posterior cranial fossa , and matA year later, the woman got pregnant again. At 24 gestational weeks, FUS showed a narrowing cavum septum pellucidum of the fetus . Fetal MSubependymal heterotopia showed a strong association with other structural anomalies including Chiari malformation, cerebral cortical malformations, callosal anomalies, etc. . When SEMRI is excellent for the detection and characterization of SEH nodules . The emeIn our cases, the pregnant woman, her mother, and family members have no clinical abnormalities or other underlying etiology, which is consistent with the previous reports that some patients with SEH are neurologically and developmentally normal . The negThe raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.This study was reviewed and approved by the local ethics committee of West China Hospital of Sichuan University. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.BL and BC: designing and writing the original draft. BC, JZ, and YZ: substantively revising the manuscript. LW, FZ, HC, XL, YS, MX, and ZD: data collection. BC: reviewing the final manuscript. All authors have read and approved the manuscript.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. The handling editor JW declared a shared affiliation with the authors BC, ZD, and MX at the time of review.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.


The surface functionalization influences the morphology, surface wettability, mechanical properties, and thermal stability of PGO nanofibers. PGO-M1 and PGO-M2 exhibit good antibacterial activity against Staphylococcus aureus and Escherichia coli, whereas PGO-M3 tends to reduce their antibacterial properties compared to PGO nanofibers. The highest proportion of dead bacteria cells is found on the surface of hydrophilic PGO-M1, whereas live cells are colonized on the surface of hydrophobic PGO-M3. Likewise, PGO-M1 shows a good interaction with L929, which is confirmed by the high levels of adhesion and proliferation with respect to the control. All the results confirm that surface functionalization can be strategically used as a tool to engineer PGO nanofibers with controlled antibacterial properties for the fabrication of highly versatile devices suitable for different applications .The emergence of resistance to pathogenic bacteria has resulted from the misuse of antibiotics used in wound treatment. Therefore, nanomaterial-based agents can be used to overcome these limitations. In this study, polycaprolactone (PCL)/gelatin/graphene oxide electrospun nanofibers (PGO) are functionalized via plasma treatment with the monomeric groups diallylamine (PGO-M1), acrylic acid (PGO-M2), and  According to the Centre for Disease Control, CDC 2019), antibiotic-resistant bacteria have caused at least 2,868,700 infections with 35,900 reported deaths 9, antibi,5. Thus,activity ,15,16. Pactivity ,18,19. Dactivity . In compactivity . These fIn recent years, great efforts have been made in the fabrication of nanostructured scaffold materials with antimicrobial properties . In partS. aureus to their surfaces [Over the years, the electrospinning technique has been used to fabricate polymeric nanofibers for various applications. The unique characteristics of nanofibers, such as their high surface area, high porosity, and small pore size, make them suitable for biomedical applications ,49,50,51surfaces ,59. In csurfaces . Positivsurfaces ,62,63. Psurfaces ,66,67,68surfaces ,70. tert-butyl acrylate), and optimized to validate its antibacterial activity against S. aureus and E. coli. The surface functionalization is realized with the support of plasma treatment. The functionalized nanofibers are characterized by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), and thermogravimetric analysis (TGA). The contact angle is measured via the drop method to determine the wettability of the nanofibers. In addition, the antibacterial activity and cell viability of the functionalized nanofibers are evaluated.Herein, GO is synthesized and blended with PCL/gelatin nanofibers, functionalized by monomer moieties  and E.coli (ATCC25922) were received from the Department of Biotechnology, Kulliyah of Science, International Islamic University, Pahang, Malaysia. Polycaprolactone, PCL (MW = 80 kDa), gelatin from bovine skin (CAS 9000-70-8), and tert-butyl acrylate were purchased from Sigma Aldrich, Milan, Italy. Graphite, sulfuric acid, phosphoric acid, hydrogen peroxide, hydrochloric acid, chloroform, methanol, 1,1,1,3,3,3-hexafluoro-2-propanol (HFIP), acrylic acid, diallylamine, nutrient broth, nutrient agar, and sodium chloride (NaCl) were purchased from Merck, Darmstadt, Germany. Potassium permanganate was obtained from Bendosen Laboratory Chemicals, Johor Malaysia. The Live/Dead Baclight Bacterial Viability Kit (L7007) was purchased from Thermo Fisher Scientific, Bleiswijk, The Netherlands. The bacterial strains of 2SO4) and ortho-phosphoric acid (H3PO4) at a 9:1 (v/v) ratio and stirred for 2 h until homogeneous in an ice bath. Then, 6 g potassium permanganate (KMnO4) was added slowly with continuous stirring for 1 h. The solution was sonicated for 15 min until homogeneous. Next, 80 mL of deionized water was added and the solution was stirred at 40 °C for 30 min. Then, the solution was stirred for another 40 min at 80 °C to speed up the rate of reaction. The solution was left to cool to room temperature before 100 mL of hydrogen peroxide (H2O2) was added to the solution to stop the reaction and the solution was stirred vigorously. The obtained solution was separated by decantation, followed by several steps of centrifugation for 7 min at 5000 rpm. The solid residue was re-suspended three times in 40 mL of 20 % (v/v) hydrochloric acid (HCl) and another three times in distilled water and further centrifuged for purification. The obtained graphene oxide was kept at –80 °C and then freeze-dried for 24 h and stored in a desiccator for further analysis.Graphene oxide (GO) was synthesized using the modified Hummers method with slight modifications ,72. Brie–1. The Raman spectra of the GO were measured at room temperature with a DXR Raman microscope at an excitation wavelength of 532 nm and a Raman shift range of 1000–30000 cm–1 to study the structural properties of the GO sheets including the layer, disorder, and defect level.The morphology of the GO sheets was examined using transmission electron microscopy, TEM . A small amount of GO was dispersed in distilled water and dropped on the grid. The sample was viewed using TEM at 10,000× magnification. The morphological surface features and roughness of the graphene oxide were studied using atomic force microscopy  at 5 and 10 µm dimensions. The images obtained were analyzed using XEI software . The possible chemical interactions of the GO samples were analyzed using attenuated total reflection Fourier transform infrared , spectroscopy at a spectral range of 600–4000 cmw/v PCL was dissolved in chloroform: methanol (3:1 v/v) solution and stirred for 24 h at room temperature [w/w gelatin was dissolved in HFIP and stirred for 24 h. The PCL/gelatin (PG) solution was mixed at a 1:1 (v/v) solvent ratio and stirred for 24 h. Next, 1.0% (w/v) of GO, was added to the solution and stirred for another 24 h before electrospinning. The electrospinning of the polymer solution was performed using a custom-built electrospinning setup consisting of KD Scientific Flow Rate apparatus and ES 50P-10W Gamma High Voltage (ES 50P-10W) with pre-optimized parameters at a 0.8 mL/h flow rate, 15 kV voltage, 12 cm tip-to-collector distance with a 20 G (0.91 mm) needle.Briefly, 10% perature ,74. Meantert-butyl acrylate (M3)—with a recognized ability to influence bacteria attachment to polymer surfaces [The surface functionalization of the nanofibers was performed by direct current plasma treatment method or glow discharge plasma. This modified the fibers’ surfaces for grafting three different kinds of monomers—diallylamine (M1), acrylic acid (M2), and surfaces ,76. Thre–1. The wettability of the nanofibers was determined by water contact angle measurements using the drop method, where deionized water was dropped onto the nanofibers’ surfaces. The measurements were performed in triplicate and the average contact angle was determined. The elemental scan of XPS was performed to study the surface chemistry of the nanofibers using a Kratos Axis Ultra DLD. The spectra were scanned at the range of 0–1200 eV and survey scans of C1s, O1s, and N1s were obtained. The atomic ratios were analyzed and calculated using Casa XPS Software (Version. 2.3.25). The thermal stability of the nanofibers was examined by thermogravimetric analysis using 2–5 mg nanofibers at a temperature range of 35–500 °C and a heating rate of 10 °C/min under a nitrogen atmosphere. The mechanical properties of the functionalized nanofibers were measured by an axial tensile testing machine (Omron ZR-RX25 Ver1.06). The sample was cut into 20 × 20 mm and mounted between two clamps. The gauge length was measured over time until the total failure of the sample at room temperature. The stress–strain curve of the sample was obtained using Sigmaplot software (ver.14.5).The surface morphologies of the nanofibers before and after treatment were examined using scanning electron microscopy, SEM . Briefly, a small section of a nanofiber sample was mounted on a brass stub using double adhesive tape and sputter-coated with a gold–palladium mixture under vacuum using a Sputter Coater . The samples were analyzed at 2000× magnification. The diameters were measured from 100 nanofibers randomly using ImageJ Software . The functional groups of the nanofiber samples were identified using ATR-FTIR  at a spectral range of 600–4000 cmThe E. coli and S. aureus bacteria were cultured overnight for five consecutive days to obtain a single colony of bacteria. The isolated colony was then transferred into a 10 mL nutrient broth of a 0.5 McFarland standard. The optical density of OD 600 nm was obtained at 0.0870. Next, 1000 µL of the bacteria suspension was transferred into 9 mL fresh broth to make up a total of 10 mL of bacteria suspension. The nanofiber sample was sterilized under a UV light for 30 min before being added to the bacterial suspension and incubated at 37 °C for 24 h.–2, 10–4, and 10–6 serial dilutions. Each tube was vortexed for 1 min and incubated at 37 °C for 15 min before being diluted. Afterward, 100 µL of the 10–6 solution was transferred to the nutrient agar plate and spread using a sterile cotton swab. The agar was incubated at 37 °C for 24 h and the colonies formed on the plate were counted using the Formula (1), –6 and the volume of the culture plate is 2 mL [After 24 h, the sample was taken out and rinsed three times with sterile phosphate buffer saline  to remove the excess suspension and unattached bacteria. The sample was immersed in a 10 mL sterile PBS solution. The suspension was further diluted by transferring 100 µL of the cultured PBS solution to a 9.9 mL sterile PBS solution to make 10 is 2 mL .600nm of the bacterial suspension was taken using a UV-Vis spectrometer at 600 nm (OD600nm = 0.3). Then, 100 µL of the broth culture was spread on the agar plate using a sterile cotton swab. The plate was incubated at 37 °C for 18 h until the entire plate was covered with bacteria biofilm. After 18 h, the sterile nanofiber sample was incubated on the plate facing down for another 1 h at 37 °C. After the incubation, the sample was rinsed with a sterile 0.85% NaCl solution to remove unattached bacteria for further staining and characterization [The live/dead bacteria cell assay was performed to study the bacterial attachment on the different surface chemistries of the plasma-treated nanofibers. Briefly, the bacteria were sub-cultured for five consecutive days to obtain a single colony. The single colony was transferred from the agar plate to a 5 mL sterile nutrient broth and incubated at 37 °C for 24 h. The ODrization . The staining solutions were prepared according to the manufacturer’s instructions. Briefly, two dyes, SYTO 9 dye with 1.67 mM/Propidium iodide and 1.67 mM (component A) and SYTO 9 dye with 1.67 mM/Propidium iodide and 18.3 mM (component B), were used for staining. The two components (A and B) were mixed thoroughly at a 1:1 ratio in a microfuge tube. Then, 6 µL of the pre-mixed staining solution was added into 2 mL of sterile 0.85% NaCl solution. Afterward, the nanofiber sample was immersed in the staining solution for 30 min at 37 °C in a dark room. The staining was removed and the sample was rinsed once with a 0.85% NaCl solution and viewed under a fluorescence microscope (Olympus BX53) at 40× magnification. Selected filters were used: UMWB2 (excitation at 460–490 nm) and UMWG2 (excitation at 510–550 nm).v/v) for 30 min for bacterial fixation [The morphological characteristics of the attached bacteria were studied using SEM analysis. Briefly, the samples were incubated with bacteria using the same method described in fixation . Afterwa2 cell culture flasks containing Dulbecco’s Modified Eagle Medium  supplemented with 10% fetal bovine serum , 2 mM L-glutamine, and antibiotic solution . The cell cultures were incubated in a 100% humidified environment at 37 °C in 95% air and 5% CO2. Before the biological assays, the nanofibers were placed in a 96-well culture plate and sterilized with 70% ethanol solution for 30 min. After sterilization, the nanofibers were rinsed with PBS three times and air-dried.To evaluate the biological response of the nanofibers, L929 cells derived from mice  were used. The L929 cells were cultured in 75 cm3 cells/well onto the nanofibers. During the experimental time, the culture medium was exchanged every third day. After the prescribed time points, the culture media was changed by 100 μL of fresh medium containing 50 μL of XTT working solution and incubated for 4 h under standard conditions. Then, the supernatant was removed and placed in a microplate reader (ELISA) and the absorbance was quantified by spectrophotometry  at 450 nm. The cell viability of L929 onto nanofibers was analyzed after 1, 3, 7, and 14 days of culture. First, the viability was verified by the XTT assay (Roche) based on the cleavage of the yellow tetrazolium salt XTT to form an orange formazan dye by metabolically active cells. The concentration of the formazan product is directly proportional to the number of metabolically active cells. The L929 cells were seeded at 5 × 10p < 0.05 was considered to determine the statistically significant differences.All data in this study are expressed as average ± standard deviation. Data analysis was performed using OriginPro Software , and CasaXPS (Version 2.3.25PR1.0). ImageJ Software  was used to measure the average fiber diameters. For the cell viability tests, the results are presented as the mean ± standard error (n = 3). Analysis of variance (ANOVA) with Tukey’s post hoc test was used to detect the differences between the groups. A value of A major recent study of carbon materials, i.e., nanotubes, nano blades, and nano spikes, concentrated on the development of an antibiotic-independent treatment for antibiotic-resistant bacteria ,80,81. TIn this study, the GO was synthesized from pure graphite using a modified Hummers method as a green approach to prevent the release of toxic gases ,91,92. T–1, which corresponds to the OH stretching vibration, whereas the band at 1713 cm–1 indicates the C=O vibration of the carbonyl group. The absorption band at 1616 cm−1 represents the C-C graphitic backbones of GO, whereas the peak at 1395 cm−1 represents the C-OH of carboxylic groups. The appearance of the C-O-C epoxy groups is shown at 1221 cm−1, and the band at 1029 cm−1 represents the C-O vibrations [−1 due to the disorder of the carbon lattice and a graphitic G band at 1589 cm−1 due to the stretching sp2 carbon atoms (D/IG) is used to quantify the defect density in the graphene sheets [D/IG ratio for the GO was 0.93 (ID/IG < 1), indicating the reduction in the sp2 domain of the GO surface due to the high contact potential difference between the GO and carboxyl functionalities on its surface [The FTIR spectra of the GO sheets d show a brations ,99. The on atoms e [100,10 surface . The num surface . These f surface ,105,106.w/v GO increased fiber diameters by 5%, signifying that the GO is well blended with the PG nanofibers. The increase in the fiber diameters may be due to the increase in the solution’s viscosity due to the interaction of GO with PCL/gelatin. In addition, the agglomeration of GO during the electrospinning process may also lead to the wide distribution of nanofibers of various sizes [The resulting GO was loaded into the blended PG nanofibers. The surface morphologies of the PG and PGO (1% GO) nanofibers a,b show us sizes ,110. tert-butyl acrylate (M3). The SEM images of the PGO nanofibers’ surfaces functionalized with the three monomers , carboxyl (-COO), and hydroxyl (-OH) groups of monomers by glow-discharge N plasma treatment to improve the wettability of the nanofibers’ surfaces for bacterial attachment . The tremonomers d,f show −1 (hydroxyl group), 2944 cm−1 (CH2 stretching), 1720 cm−1 (carbonyl stretching), 1642 cm−1 , 1545 cm−1 (N-H stretching), and 1169 cm−1 (asymmetric C-O-C stretching), corresponding to the functional groups possessed by PCL, gelatin, and GO [The IR spectra of the functionalized nanofibers and the PG, PGO, PGO-M1, PGO-M2, and PGO-M3 nanofibers are shown in , and GO ,115. The−1 and 1210 cm−1, corresponding to imine (C=N) and ether (C-O) stretching, respectively. The results indicate that M1 was covalently bonded to the PGO nanofibers via the interaction between the secondary amine in diallylamine and the PGO, forming imine and enamine bonds, as illustrated by the reaction mechanism in −1 (carbonyl group) and the observed 1641 cm−1 (C=C stretching) band confirm the presence of acrylic acid. The peak intensity at 1720 cm−1 and 1169 cm−1 increased slightly due to the hydrogen bonding interactions between the COOH and COC functionalities of the acrylic acid and PGO nanofibers (−1 (carbonyl group) and 1210 cm−1 (C-O stretching) in the PGO-M3 spectrum , 1640 cm−1 , and 1545 cm−1 (N-H stretching) due to the strong hydrogen bonding interactions between the carbonyl group of the tert-butyl acrylate and the N-H bonds in the PGO nanofibers  displayed a water contact angle measurement of 127.03 ± 17.5° due to the hydrophobic surface provided by the tert-butyl acrylate [The wettability of the functionalized nanofibers was analyzed by water contact angle measurements . The watacrylate . tert-butyl acrylate on the nanofibers. Hence, the higher concentration of the polar N atom in PGO-M1 makes it slightly more hydrophilic compared to the PGO-M3 nanofibers, which agrees with the contact angle measurement , which can affect the nanofibers’ elasticity [The PGO nanofibers recorded a strength, strain break, and Young’s modulus of 2.87 ± 0.81 MPa, 26.22 ± 7.31%, and 66.96 ± 6.42 MPa, respectively. The value of Young’s modulus indicates the high stiffness of the samples, which is inversely proportional to the elasticity. The blending of GO further improved the tensile strength of the PG nanofibers due to the hydrogen bonding interactions between GO and the nanofibers ,136,138.asticity ,141. S. aureus and E. coli before and after the plasma surface treatment, with the PG nanofibers as the control. The results are represented in E. coli colony growth observed on the plate, whereas a small amount of S. aureus colonies (9.0 × 10–6 CFU/mL) were detected on the agar plate. Previous studies reported that the sharp edges of GO in nanofibers could induce membrane stress and destroy the phospholipid bilayers of bacteria, leading to physical damage to the bacterial membrane integrity [E. coli compared to the Gram-positive bacteria S. aureus. This may be due to the rigid cell walls of Gram-positive bacteria, which prevent GO from penetrating the bacterial membrane [The plate-counting assay was performed to evaluate the antimicrobial efficiency of the nanofibers against ntegrity ,143,144.membrane ,146. S. aureus. However, the PGO-M3 antibacterial activity was reduced, with the highest colony count compared to PGO, PGO-M1, and PGO-M2. The presence of a positively charged amino group in M1 may have induced toxicity to the bacteria cells [The nanofibers retained their antibacterial activity after being treated with M1 and M2, with a slightly increased effectiveness against ia cells ,147. On ia cells  and disria cells . As for ia cells . Howeveria cells ,152,153.S. aureus  via plasma treatment to improve the surface properties of antibacterial nanofibers. The fabrication of the functionalized nanofibers was confirmed by SEM, FTIR, XPS, wettability measurements, TGA studies, and tensile strength measurements. The functional groups possessed by each monomer affected the surface wettability, with PGO-M2 as the most hydrophilic and PGO-M3 as the most hydrophobic. The hydrophilic behavior of the surfaces, strictly related to the chemical functionalization on the nanofibers, significantly influenced in vitro cell and antibacterial properties: higher S. aureus colony growth was observed in PGO-M3 than in PGO-M1 and PGO-M2. Meanwhile, L929 tended to better adhere and proliferate to PGO-M1. Accordingly, it was found that antimicrobial activity against E. coli bacteria was the highest in PGO-M1, followed by PGO-M2 and PGO-M3, thus confirming the selective interaction of functional groups and different bacteria populations. GO-PCL/gelatin electrospun nanofibers were successfully functionalized by grafting diallylamine (M1), acrylic acid (M2), or Further studies could create a better understanding of the mechanisms and efficiency of bactericidal interaction. This may pave the way for the design of innovative non-antibiotic treatments that are suitable for efficiently reducing the formation of biofilms, leading to the development of new solutions for current health and environmental problems.


The molecular wires with ionic channels presented here have potential as an alternative to proton conductors operating under anhydrous conditions at both low and high temperatures.Supramolecular assemblies are vital for biological systems. This phenomenon in artificial materials is directly related to their numerous properties and their performance. Here, a simple approach to supramolecular assemblies is employed to fabricate highly efficient proton conducting molecular wires for fuel cell applications. Small molecule-based molecular assembly leading to a discotic columnar architecture is achieved, simultaneously with proton conduction that can take place efficiently in the absence of water, which otherwise is very difficult to obtain in interconnected ionic channels. High boiling point proton facilitators are incorporated into these columns possessing central ionic channels, thereby increasing the conduction multifold. Larger and asymmetrical proton facilitators disintegrated the self-assembly, resulting in low proton conduction efficiency. The highest conductivity was found to be approaching 10 Nature has taught us how noncovalent interactions, such as hydrogen bonds and ionic interactions, play a key role in controlling the order within the molecules via self-assembly, thus affecting the biological functions ,2,3,4. BProton conductors, for instance, Nafion, have been reported to have interconnected ionic channels that are directly responsible for their higher proton conductivity as a result of the participation of carrier molecules ,10. HoweHerein, we report an innovative and simplified approach to engineer long range and unidirectional ionic channels with increased proton conduction in the absence of water. These ionic channels are formed simultaneously upon the self-assembly and co-assembly of the proton facilitators, while the proton conduction is raised tremendously in a ‘cooperative’ manner. A schematic presentation of our current innovation and its impact is given in The obtained molecular wires are stable up to a higher temperature and conduct protons efficiently and ‘cooperatively’, without the requirement of water. Although the proton facilitators have their own network for proton conduction, they lack any well-defined architecture, thus they cooperate with the phosphonic acid groups of the parent molecules forming the discotic columns. This results in the formation of molecular wires with ionic channels and increased proton conductivity. The major attributes of these molecular wires with unidirectional and interconnected ionic channels are: (1) they conduct protons efficiently in one dimension (1D) without any disruption of their pathway, (2) the molecular columns in these wires are stable in a range of temperatures; thus, the proton conductivity can be associated directly with the columnar morphology and ionic channels, and (3) these molecular wires can be fabricated easily on an electrode surface without any disintegration of the supramolecular assembly. Proton facilitators such as pyrazole and benzimidazole conduct protons via a similar process, e.g., proton hopping occurring in the phosphonated proton conductors  18,19].,19.18,191 with long alkyl chains, a rigid core and an ionic group has the ability to undergo phase separation, evolving as the molecular columns form via noncovalent interactions such as hydrogen bonds and pi–pi bonds  of the organophosphonic acid which disappeared in the spectrum upon mixing of the acid and the proton facilitator. Additionally, the absorption bands at 939 and 1030 cm−1, corresponding to a symmetric and an asymmetric vibration of P-O in the organophosphonic acid, also decreased. Furthermore, the absorption band at ca. 3120 cm−1 which was associated with the stretching band of N-H group decreased relative to the pure pyrazole unit. These observations indicate that the P-OH group interacts with the pyrazole unit through hydrogen bond formation. Obviously, a rather broad peak at 1700–2500 cm−1 for the acid-base complex was also noted, due to the non-covalent interactions between the nitrogen and oxygen atom of pyrazole and organic phosphonic acid, respectively [S1]. The rapid proton conduction is achieved by the proton facilitator, whereas the molecular columns with ionic channels are born from the organic phosphonic acid . The forAs described earlier, the proton conductivity in these molecular wires predominantly depends upon the extended hydrogen bond network between the proton facilitators and molecular columns formed during the process. Therefore, it is necessary to study any change or modification in proton conduction mechanism as it can provide us with an insight into proton sites and the presence of a charge carrier, if any.1. For the blend of the organic phosphonic acid 1 and pyrazole, an increased value for the conductivity, approaching up to 4.8 × 10−2 S/cm, was observed above 90 °C  and the higher resultant activation energy (−2 S/cm at 90 °C) for the molecular wires of organophosphonic acid 1 and pyrazole. The possible reason for this could be that pyrazole molecules in the dynamic phase generated by heat energy can interact strongly with the phosphonic acid groups and thus enhance the proton conductivity by lowering the proximity between two phosphonic acid groups. Such proximity of the nearby protons of phosphonic acid groups is also minimized by the orientation of pyrazole molecules in ionic channels. It is assumed that due to the planarity and symmetry of pyrazole molecules, their position in ionic channels was thermodynamically favorable for exchanging protons with phosphonic acid groups. Additionally, the orientation of pyrazole molecules within the ionic channels may have also prevented phosphonic acid from suffering proton loss due to the formation of P-O-P bonds (anhydride) at high temperatures, as has been reported for phosphonated proton conductors [1  value of the corresponding organic proton facilitator can also affect the proton transfer and thus influence proton conduction [pKa = 2.2) is much more acidic than pyrazole (pKa = 2.5) and benzimidazole (pKa = 8.52), which further accounts for the high proton conductivity of the organophosphonic acid 1-pyrazole in the temperature range of 30–90 °C (1 with pyrazole have shown high conductivity at 180 °C due to the fast proton transfer process. Bio-inspired anhydrous proton conductors such as self-assembled acid-base complexes of mono-dodecylphosphate (MDP) and 2-undecylimidazole (UI) with long hydrophobic chains have been reported in the literature [Ea) for these composites were reported to be 0.22–0.34 eV. The activation energies (Ea) for these molecular wires were estimated by the slope of Arrhenius plots from the proton conductivity data and by employing the Arrhenius equation as follows:In ve 90 °C A. In addnductors ,25,26. Inductors . For molctors [1 . For thectors [1 . From thnduction . As show30–90 °C A. The prterature . These aterature ,32. The The estimated activation energies for all four different samples are given in the 1 and the proton facilitators, where long range ionic channels act as a tunnel allowing the hopping of protons in a cooperative manner. In the literature, some materials with similar ionic channels have been reported with comparable proton efficiencies. However, on the contrary, the proton conduction in these materials seems to be taking place in three dimensions (S2) [It is evident from the conductivity measurements that the rapid dynamics of protons was facilitated by the supramolecular assembly and co-assembly of organic phosphonic acid ons (S2) ,34. 1 nor any of the proton facilitators  exhibit high proton conductivity when existing as separate entities. Only their self-assembly into molecular columns can endow them with the ability to exchange protons in a holistic and cooperative way, where the protons are assisting the self-assembly as well as raising the conductivity significantly via a hydrogen bonded network.It should be noted that neither the organic phosphonic acid 1 and its self-assembly with different proton facilitators, along with the illustration of bundles of the columns or molecular wire containing ionic pores are given in 1 at 30 °C point toward a greater extent of crystalline order in the molecular assembly  can disturb the packing of the columns significantly. Nevertheless, the proton conductivity at 30–80 °C was found to increase for the mixture of organic phosphonic acid 1 and pyrazole, this could be related to the tendency of the proton facilitator such as pyrazole to fit in the axis of the columns due to its small size. On the other hand, the large proton facilitator, i.e., benzimidazole, has shown the propensity to disturb the organization of the molecules due to its chemical structure  of benzimidazole and thereby further supports our view that its assembly with organic phosphonic acid 1 is weak and its corresponding proton conductivity is the lowest  for proton transportation occurring within the ionic channels in which no carrier moiety is involved. The formation of a columnar morphology containing ionic channels is evidenced by 2DWAXS and is associated with one-dimensional (1D) proton conduction taking place in these molecular wires. These molecular wires have demonstrated a precise correlation between the increased proton conduction and columnar morphology. These molecular wires offer further prospects for developing proton conducting membranes containing fabricated and stable interconnected ionic channels for energy applications. In the future, further focus will be on freezing these molecular wires in a free-standing film for achieving the proton conductivity of 10−1 S/cm in a dry state, as needed for commercial applications. In addition, a contrasting molecular system in which long chain alkylated and symmetrical proton facilitators will be used as phase separators to generate similar molecular columns and assemblies together with the organic phosphonic acid will be explored.In conclusion, thermally stable molecular wires are fabricated via self-assembly and co–assembly of two different small molecules, namely organic phosphonic acid and proton facilitators, producing a columnar morphology enabling rapid proton conduction in a dry state. In these molecular columns or wires, the proton conduction is increased as a result of long range ionic channels containing the molecules of proton facilitators that take part in a ‘cooperative’ proton exchange, even at high temperature (>100 °C). The proton conductivity of 10All materials were purchased from Fluka  and Sigma Aldrich . 1, 2, 4-Triazole , pyrazole  and benzimidazole .1) and the preparation of the blend with 1 and proton facilitator Synthesis of 3, 4, 5-tris(dodecyloxy) benzyl phosphonic acid  benzyl phosphonic acid terature . The comThe film or membrane of these molecular wires with columnar structures was deposited on the electrode surface directly by following the drop-casting process. In this process, a certain concentration of these supramolecular assemblies was taken into a suitable solvent such as dichloromethane. From the solution, the film was cast on the electrode surface by the drop-casting method. The film was dried for several hours at room temperature and then in a vacuum oven to remove any residual solvent. These films fabricated on the surface of the electrode were then utilized for the proton conducting analysis. 2. The thickness of the sample and the area of the electrodes were also measured for use in calculating the proton conductivity. The temperature dependence of conductivity was measured in the frequency range from 10−1 to 106 Hz with the temperature ranging from 20 to 160 °C with an increment of 10 °C.For the proton conductivity measurements, the samples for all complexes were prepared as follows. About 80 mg of the complex was placed above the electrode and was melted. Four glass fibers with the thickness of 0.1 mm were also placed along with the samples to avoid the contact with the electrodes. Afterwards, the second electrode was placed above this. The electrodes were connected with an impedance instrument. All proton conductivity measurements were done under dry NThermal stability of all complexes was evaluated by thermogravimetric analysis (TGA) on a Perkin Elmer TGA 7 thermogravimetric analyzer (10 K/min heating rate in nitrogen atmosphere). All TGA trace data were obtained from 80 to 500 °C.


To evaluate the diagnostic accuracy of coronary computed tomography angiography (CCTA) for the evaluation of obstructive coronary artery disease (CAD) in patients referred for transcatheter aortic valve implantation (TAVI).EMBASE, PubMed/MEDLINE, and CENTRAL were searched for studies reporting accuracy of CCTA for the evaluation of obstructive CAD compared with invasive coronary angiography (ICA) as the reference standard. QUADAS-2 tool was used to assess the risk of bias. A bivariate random effects model was used to analyze, pool, and plot the diagnostic performance measurements across studies. Pooled sensitivity, specificity, positive ( + LR) and negative (−LR) likelihood ratio, diagnostic odds ratio (DOR), and hierarchical summary ROC curve (HSROC) were evaluated. Prospero registration number: CRD42021252527.p = 0.37), whereas the specificity of single-heartbeat scanners was higher (82% (95% CI: 66–92%) vs. 60% (95% CI: 46 – 72%) respectively; p < 0.0001). Routine CCTA in the pre-TAVI workup could save 41% (95% CI: 34 – 47%) of ICAs if a disease prevalence of 40% is assumed.Fourteen studies (2533 patients) were included. In the intention-to-diagnose patient-level analysis, sensitivity and specificity for CCTA were 97% (95% CI: 94–98%) and 68% (95% CI: 56–68%), respectively, and + LR and −LR were 3.0 (95% CI: 2.1–4.3) and 0.05 (95% CI: 0.03 – 0.09), with DOR equal to 60 (95% CI: 30–121). The area under the HSROC curve was 0.96 (95% CI: 0.94–0.98). No significant difference in sensitivity was found between single-heartbeat and other CT scanners (96% (95% CI: 90 – 99%) vs. 97% (95% CI: 94–98%) respectively; CCTA proved an excellent diagnostic accuracy for assessing obstructive CAD in patients referred for TAVI; the use of single-heartbeat CT scanners can further improve these findings.CCTA proved to have an excellent diagnostic accuracy for assessing obstructive CAD in patients referred for TAVI.• Routine CCTA in the pre-TAVI workup could save more than 40% of ICAs.• Single-heartbeat CT scanners had higher specificity than others in the assessment of obstructive CAD in patients referred for TAVI.• The online version contains supplementary material available at 10.1007/s00330-022-08603-y. Transcatheter aortic valve implantation (TAVI) represents the gold standard for treatment of severe aortic stenosis in patients at high and intermediate surgical risk . CandidaCurrent guidelines recommend pre-procedural screening for CAD before valvular intervention . ComputeTo the best of our knowledge, only two meta-analyses , 4 have In this framework, the incorporation of coronary artery assessment into pre-TAVI CT evaluation has the potential to reduce the need for unnecessary ICA and total amount of contrast medium applied, making pre-procedural evaluation safer and faster with reduced cost , 10.The aim of this systematic review and meta-analysis is to provide an updated overview of the diagnostic accuracy of CCTA for the evaluation of obstructive CAD among patients referred for TAVI.This systematic review and meta-analysis was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) extension for Diagnostic Test Accuracy (DTA) Studies . The proThe primary aim of this study was to evaluate the diagnostic accuracy of CCTA for obstructive coronary stenosis among patients referred for TAVI. Studies reporting data on CCTA for the evaluation of obstructive CAD were deemed eligible if all the following inclusion criteria were respected: (1) CCTA performed with at least a 64-slice CT scanner; (2) ICA performed in all patients and used as the reference standard; (3) sensitivity and specificity were reported or assessed by the published data. Obstructive CAD was defined in the meta-analysis as a narrowing of the coronary lumen by more than 50% on CCTA and a lumen diameter reduction of more than 50% on ICA.The primary endpoint was the patient-level accuracy of CCTA to identify obstructive CAD. For the purpose of this analysis, non-evaluable segments were considered positive based on an intention to diagnose approach . SecondaExcerpta Medica dataBASE (EMBASE), Medical Literature Analysis and Retrieval System Online (PubMed/MEDLINE), and Cochrane Central Register of Controlled Trials (CENTRAL) were searched up to May 1, 2021. The string used is reported in the Two researchers (F.B. and A.S.) independently searched for studies fulfilling the inclusion criteria in a two-stage process: first by using title and abstract of the papers and then the full text. The reasons for excluding studies in this second phase were recorded. The results from both searches were compared and the discrepancies were discussed. In some cases of disagreement, the decision was reached by consultation with a third researcher (G.G.). All selected articles were automatically downloaded, imported, and de-duplicated in Microsoft Excel (Microsoft).General characteristics included total number of patients, age, sex, body mass index, cardiovascular risk factor , known CAD, previous percutaneous coronary intervention or CABG and atrial fibrillation. Moreover, main CT scanner characteristics were recorded: number of detector rows, dual-energy techniques, tube voltage tube current, contrast media concentration, contrast media volume, heart rate during acquisition, and mean dose-to-length product.The quality assessment of diagnostic accuracy studies 2 (QUADAS-2) tool  was usedQ and Higgins I2 statistics. Deeks’ funnel plot was used to assess publication bias. The patient-level clinical accuracy of CCTA was evaluated using the likelihood ratios to calculate post-test probability based on Bayes’ theorem with the use of Fagan’s nomograms, Likelihood ratio scattergram, and probability modifying plot.Two-by-two contingency tables were extracted from each study and used to calculate sensitivity, specificity, positive (+LR) and negative (−LR) likelihood ratio, and diagnostic odds ratio (DOR) with 95% confidence interval (CI) of CCTA for the detection of significant coronary artery stenosis . A bivap value of less than 0.05 was considered statistically significant.The analyses were performed with STATA  using the MIDAS module  and MetaThe PRISMA 2020 flow diagram  for systThe QUADAS-2 Domain assessment is reported in Figure A total of 2228 patients were included in the analysis. For the purpose of this analysis, performed at the patient level, non-evaluable segments were considered positive based on an intention-to-diagnose approach. The pooled sensitivity and specificity for CCTA were 97% (94–98%) and 68% (56–68%), respectively, and the + LR and −LR were 3.0 (2.1–4.3) and 0.05 (0.03–0.09), with a DOR of 60 (30–121). The HSROC had an AUC = 0.96 (0.94–0.98). Table The per-patient analysis revealed a + LR of 3.03 (2.12–4.33) and a −LR of 0.05 (0.03–0.09) .Fagan’s nomograms, with estimated pretest probability of 40% and 15%, Likelihood ratio scattergram and probability modifying plot are reported in Figure Table Q and I2, which indicates the presence of heterogeneity in the studies. As a result, we visually assessed the forest plot and HSROC and a significant heterogeneity in specificity was found, particularly in the forest plot  but did not affect sensitivity (p = 0.26); the use of high temporal resolution scanners increased sensitivity (p = 0.02) but decreased specificity (p < 0.001); and the use of single-heartbeat scanners increased specificity (p < 0.001) with no effect on sensitivity (p = 0.37).In summary, the use of a whole-heart coverage CT increased specificity  ICAs, a high temporal resolution CT scanner could correctly avoid 357 (95% CI 259–444) ICAs, and a single-heartbeat CT scanner could correctly avoid 494 (95% CI 398–550) ICAs Figure .Fig. 6Ip = 0.019). The percentage of non-evaluable patients using high temporal resolution CT scanners was 45.1% (368/815) compared to 19.5% (83/425) using other CTs (p = 0.001).Furthermore, the percentage of non-evaluable patients with a whole-heart coverage CT scanner or a single-heartbeat CT scanner was 21.7% (13/60) compared to 37.1% (438/1180) with other CTs  with a good −LR (0.05).This result highlights the effectiveness of CCTA to rule out significant CAD and to reduce unnecessary ICA procedures by 40.9%, aspiring its potential role as a gatekeeper test in this subgroup of patients. Furthermore, the use of new CT scanners, particularly single-heartbeat CT, has the potential to save the number of ICAs by up to 49.4%.A recent meta-analysis on the same topic by van den Boogert et al  with incAnother meta-analysis on the performance of CCTA in patients with aortic stenosis undergoing surgery or transcatheter intervention by Chaikriangkrai et al  was perfIn accordance with the European Society of Cardiology (ESC) guidelines , CCTA wiHowever, our data seem to support a slightly broader usefulness and feasibility of CCTA even for patients with intermediate risk of CAD. In fact, on the basis of our findings, a patient with a pre-test probability of 40% , in case of CCTA negativity, has a post-test probability of about 3%. This last finding is supported by a recent meta-analysis  of prospThe European Society of Cardiovascular Radiology (ESCR) consensus document  recentlyThe abovementioned meta-analyses on a similar population , 4, publIn the period between those meta-analyses and our study, seven more papers using these technologies were published –24, 29. p = 0.002) and specificity  in ruling out or confirming CAD patients with a pretest probability of CAD ranging from 7 to 67%.Single-heartbeat CT scanners in the evaluation of obstructive CAD prior to TAVI could correctly avoid up to 49.4% of ICAs. This data may be at least partially related to the increased number of segments, which allows accurate assessment of coronary arteries even in challenging population. The non-assessable segments were considered positive, leading to higher sensitivity and lower specificity in case of a high number of non-assessable segments. Our results confirm in a larger population the findings of Meier et al , who repFrom a clinical point of view, it has been reported that patients with a large area of myocardium at ischemic risk may benefit the most from revascularization intervention prior to TAVI, and the proximal segment stenosis is prognostically more important than distal . UnfortuFurther studies are needed to evaluate the real impact of CCTA in clinical practice; a randomized controlled trial could be proposed to evaluate the prognostic impact of patients undergoing CCTA pre-TAVI vs. a group not undergoing CCTA; also, the actual potential of CCTA in the study of proximal segments in such a selected population remains to be explored.This meta-analysis has some limitations. First of all, a relatively low number of studies met the selection criteria. Unfortunately, only a fraction of the studies reported the analyses at patient level, either by considering non-analyzable segments as positive or by excluding them, and therefore it was not possible to create 3 × 2 tables . MoreoveIn conclusion, CCTA proved to have excellent diagnostic accuracy for assessing obstructive CAD in patients referred for TAVI. Routine CCTA assessment of coronary arteries as part of the pre-TAVI workup could save more than 40% of ICAs. The use of single-heartbeat CT scanners, which provide higher specificity, can further improve these findings.ESM 1(DOCX 871 kb)


Coreopsis tinctoria Nutt., and its main activities include antioxidant, hypoglycemic, and hypotensive. After oral administration of marein, the blood concentration of marein is low. The metabolites of marein have not been reported systematically. In this study, a rapid and systematic method based on ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS/MS) was established to detect metabolites of marein in vivo (plasma and urine) after oral administration and injection. Sixty-one metabolites were identified. The metabolites are formed through a wide range of metabolic reactions, including hydroxylation, glucuronidation, methylation, hydrolysis, and desorption of hydrogen. The liver microsome incubation was further used to investigate the metabolic rate of marein. Network pharmacology was applied to study the targets and pathways of marein and its metabolites. Marein and its metabolites act on the same targets to enhance the therapeutic effect. This research illuminates the metabolites and metabolic reaction of marein and establishes a basis for the development and rational utilization of C. tinctoria. Meanwhile, the analysis of prototype and metabolites together by network pharmacology techniques could provide a methodology for the study of component activity.Marein is the main active compound of  Coreopsis tinctoria Nutt. (C. tinctoria), also known as “snow chrysanthemum,” is native to North America and is currently grown worldwide −m/z = 449.1077, and product ions are m/z = 287.0553 [M-H-Glu]−, 269.0440 [M-H-Glu-H2O]−, 151.0025 [M-H-Glu-H2O-C8H6O]−, and 135.0441 [M-H-Glu-H2O-C8H6O-O]−. The cleavage of marein is shown in The MS and MS/MS chromatogram of the marein were recorded. Under the chromatographic conditions used, the molecular formula is C− is m/z 495.0780 in the negative ion mass spectrum, and its molecular formula is predicted to be C21H20O14. In the MS/MS spectrum of M1, the m/z of the product ions are 151.0034 [M-H-Glu-H2O-C8H4O4]− and 135.0426 [M-H-Glu-H2O-C8H4O4-O]−. It is consistent with the product ions at 151 and 135 of marein. Combined with the molecular formula, it is speculated that it has 3 more hydroxyl groups. Therefore, it is preliminarily determined to be a dehydrogenation and hydroxylation metabolite.The metabolite M1 is eluted at 5.62 min, and the quasimolecular ion peak [M-H]− is m/z 495.0708, and its molecular formula is predicted to be C21H20O14. Fragment ions m/z 301.0352, 151.0022, and 135.0445 can be seen by secondary mass spectrometry. Like M1, it suggests dehydrogenated and hydroxylated metabolites.The retention time of metabolite M2 is 6.37 min. The anion first-order mass spectrometry shows that the excimer ion peak [M-H]− is m/z 479.0831 in negative ion first-order mass spectrometry, and its molecular formula is predicted to be C21H20O13. Characteristic ion fragments m/z 269.0442, 151.0031, 135.0438 are generated by secondary scanning lysis. The molecular weight is 16 less than that of M1 and M2. It is judged that there is one less hydroxyl group, and it is speculated that the dehydroxylation products of M1 and M2.The retention time of metabolite M3 is 5.65 min, and the excimer ion peak [M-H]− of the metabolite M4 eluted at 6.34 min is m/z 479.0831, and its molecular formula is predicted to be C21H20O13, which is an isomer with M3. The MS mass spectrum correspondingly produces characteristic fragment ions m/z 151.0033 and 135.0438. It is also the dehydrogenation and hydroxylation metabolites of marein.The excimer ion peak [M-H]− of metabolite M5-M10 is m/z 463.0882, eluted at 5.58, 5.99, 7.17, 7.55, 7.85, and 8.13 min, respectively. Its molecular formula is predicted to be C21H20O12. The main secondary fragment ions include m/z 301.0709 [M-H-Glu]−, 287.0552 [M-H-Glu-O]−, 269.0445 [M-H-Glu-O-H2O]−, 151.0028 [M-H-Glu-O-H2O-C8H6O]−, and 135.0444 [M-H-Glu-O-H2O-C8H6O-O]−. The molecular weight is 14 higher than that of marein and 16 less than that of M3 and M4. Combined with the predicted molecular formula, both of them are dehydroxylated metabolites of M3 and M4.The excimer ion peak [M-H]− is m/z 479.1195, and the retention time is 8.47 and 9.27 min, respectively. Its molecular formula is predicted to be C22H22O12. The MS-MS information of the metabolite M11 is m/z 303.0871 [M-H-Glu-O-CH3]−, 269.0457 [M-H-Glu-O-CH3-H2O]−, and 151.0028 [M-H-Glu-O-CH3-H2O-C8H6O]−. The secondary mass spectrum of the metabolite M12 shows fragment ions m/z 303.0870, 151.0027, and 135.0443 [M-H-Glu-O-CH3-H2O-C8H6O-O]−. Therefore, it is identified as hydroxylated and methylated metabolites.The metabolite M11-M12 is an isomer, and its excimer ion peak [M-H]− is m/z 447.0932. Its molecular formula is predicted to be C21H20O11. The characteristic fragment ions m/z 285.0395 [M-Glu]−, 151.0025 [M-Glu-H2O-C8H6O]−, and 135.0444 [M-Glu-H2O-C8H6O-O]− are generated by the secondary mass spectrometry. Its molecular weight is 2 less than that of marein, and it may lose 2 hydrogens. So it is presumed to be the dehydrogenation product of marein.The metabolite M13 is eluted at 7.32 min, and the eximolecular ion peak [M-H]− of the metabolite M14-M19 is m/z 491.1195, eluted at 7.52, 7.94, 8.13, 9.33, 9.77, and 10.26 min, respectively. Its molecular formula is predicted to be C23H24O12. The main secondary fragment ions are m/z 315.0865, 269.0443 [M-H-Ac-Glu-H2O]−, 151.0021 [M-H-Ac-Glu-H2O-C8H6O]−, and 135.0441 [M-H-Ac-Glu-H2O-C8H6O-O]−. It is determined that M14-M19 are isomers of the acetylated product of marein.The excimer ion peak [M-H]− is m/z 641.1359. The molecular formula is predicted to be C27H30O18. Fragment ions m/z 465.1017 [M-H-Glu-CH3]−, 303.0866 [M-H-2Glu-CH3-O-H2O-C8H6O]−, 151.0028 [M-H-2Glu-CH3-O-H2O-C8H6O]−, and 135.0442 [M-H-2Glu-CH3-O-H2O-C8H6O-O]− are observed by the secondary mass spectrometry, 162 more than the metabolite M11, which is speculated to be the glucose acidification product of M11.The retention times of the metabolites M20-M21 are 6.36 and 6.74 min, respectively. The anion first-order mass spectrometry shows that the excimer ion peak [M-H]– are both m/z 625.1410, eluted at 5.07 and 6.73 min, respectively. They are isomers, whose molecular formula is predicted to be C27H30O17. Its molecular weight is 162 higher than that of marein, so it is presumed to be the product of marein glucuronidation. The secondary mass spectra generate the characteristic fragment ions m/z 449.1058 [M-H-Glu]−, 287.0553[M-H-2Glu]−, 269.0461[M-H-2Glu-H2O]−, 151.0025[M-H-2Glu-H2O-C8H6O]−, and 135.0447[M-H-2Glu-H2O-C8H6O-O]−.The metabolite M22-M23 excimer ion peak [M-H]− is m/z 287.0561 in anion first-order mass spectrometry. Its molecular formula is predicted to be C15H12O6. Its relative molecular weight is 162 less than that of marein, suggesting the removal of a molecule of glucose group metabolite. The MS mass spectrum shows the fragment ion m/z 135.0447 [M-H2O-C8H6O-O]−. It is confirmed that M24 is the product of marein aglycone.The metabolite M24 is eluted at 9.15 min, and the eximolecular ion peak [M-H]− of the metabolite M25-M30 is m/z 477.1038, and the retention time is 6.16, 6.80, 7.46, 8.56, 9.07, and 9.70 min, respectively. Its molecular formula is predicted to be C22H22O12. The main secondary fragment ions are m/z 301 [M-Glu-CH3]−, 151 [M-Glu-CH3-O-H2O-C8H6O]−, and 135 [M-Glu-CH3-O-H2O-C8H6O-O]−. It is 14 more than the metabolites M5-M10, and it is determined that M25-M30 are the methylation products of M5-M10.The excimer ion peak [M-H]The prototype compounds and metabolites in the urine and blood samples of rats after the tail vein injection of marein were analyzed. By comparing the retention time in the chromatograms of the administration group and the blank group to track the metabolites, 31 metabolites were detected in injection, and 23 and 26 were detected in plasma and urine separately.Among them, M′0 is the prototype marein. And M′1 has the same molecular weight as M′0, which may be presumed to be the hydrogenation product after dehydrogenation. M′2 and M′3 can be inferred to be hydroxylated and sulfated metabolites according to their molecular weight and molecular formula. M′4 and M′5 have a molecular weight of 80 more than that of M′0. M′6 and M′7 are the hydroxylated products after the dehydrogenation of 2 hydrogens. Compared with M′0, the molecular weight of M′8, M′9, and M′10 are 2 less, which is supposed to be the removal of 2 hydrogens. The molecular weight of M′11, M′12, and M′13 are 16 less, so they may be dehydroxylated products. M′14-M′16 are 14 more than M′0 and are methylated products. M′17 is inferred to be the removal of 2 hydroxy groups after the addition of 2 hydrogens. M′18-M′21 is presumed to be a glycosylation metabolite, and M′22 is presumed to be a deglycosylation product and an aglycone of marein. M′23-M′27 may be the methylation products of M′6-M′7. And M′28-M′31 may be the sulfuration products of M′14-M′16. The detailed metabolites information after injection of marein was summarized in More interestingly, the prototype components were detected after the tail vein injection, and isomerization also occurred, that is, the two isomers marein and flavanomarein. The structure was shown in The possible metabolic pathways of marein via oral administration and injection were shown in Figures In vivo, 30 marein metabolites were observed in oral administration, while 31 marein metabolites were observed in injection. Among them, 9 shared metabolites were found in oral and injectable administration, including M5, M13, M22, M23, M24, M26, M27, M28, and M30 in oral administration, which correspond to M′6, M′10, M′18, M′21, M′22, M′23, M′24, M′25, and M′27 in injection administration one by one. And we marked it with ∗ in Tables in vivo, and its aglycone M25  could be further metabolized. Studies on the metabolism of components with similar structures have been reported. For example, after intragastric administration of isoliquiritin  and isobavachalcone  in rats, metabolic pathways in vivo include glucuronidation, hydrolysis, isomerization, sulfation, hydrogenation, hydroxylation, and other metabolic reactions [Marein belongs to chalcone glycoside. According to the results of oral and injection studies, it can be hydrolyzed into its aglycones eactions . The metBy comparing the experimental results of oral and injection of marein, it is found that their metabolic pathways include hydroxylation, glucuronidation, methylation, hydrolysis, and dehydrogenation. The difference is that after oral administration, marein was not detected in the original form, and mainly existed in the form of metabolites in blood. While injection administration, that is, in the absence of gastrointestinal absorption and liver first-pass effect, the prototype component of the glycoside can be detected in the body. It can be seen that the first-pass effect of the gastrointestinal tract and the liver plays an important role in the oral metabolism of marein, which makes the metabolites different between the two administration methods.in vitro incubation system for rat liver microsomes was established. The UPLC-Q-TOF-MS/MS method was used to identify the metabolites of marein in liver microsomes and to study the metabolic stability in vitro. The data of Ln (area%) and the time of incubation were shown in int, CL′int, CLH, and ER were shown in in vitro metabolic half-life t1/2 of marein in liver microsomes is 177.69 min and the liver extraction rate is 0.15. It shows that the metabolic stability of marein in liver microsomes is good, indicating that liver microsomes have no significant effect on the metabolism of marein. Since the prototype components of marein were not detected in the body after intragastric administration, we speculate that liver metabolism is not the main reason for the low bioavailability of marein. According to existing research, the gastrointestinal tract may play a key role in the metabolism of marein. The study of rutin gives us some enlightenment. Rutin can be combined with enzymes in the intestine after oral administration. The enzymes in the intestine hydrolyze most of the rutin into quercetin, and only a small part of the rutin can be absorbed into the blood. Given the similar structure of marein, flavanomarein, and rutin, it is speculated that after oral administration of marein in rats; the enzymes in the intestinal tract will hydrolyze marein; and its metabolites are absorbed into the blood.Liver microsomes can effectively evaluate the influence of metabolic enzymes on compound metabolism. In this experiment, an Homo sapiens,” and set a score greater than 0.700 as the basis for high confidence in the interaction, hiding the disconnected nodes. Export the tsv format file and import it into Cytoscape 3.6.1 for network visualization and topological attributes analysis. The higher the degrees of nodes are, the more important the nodes are to maintain the stability of the entire network. We sorted the degree values and selected the core targets with the corresponding degree values greater than four times the median value as the potential key targets related to activity and visualized them  and flavanomarein . Two hundred and sixty-five targets were obtained. Then input the obtained targets into STRING to predict the interaction relationship between protein and protein. The species was selected as “zed them . The nodIn P < 0.01 and count ≥5, which were mainly related to signal transduction, negative regulation of the apoptotic process, cell proliferation, and positive regulation of transcription from RNA polymerase II promoter. In cell components, it was mostly related to the nucleus, cytosol, plasma membrane, and cytoplasm. Among the molecular function, P < 0.01 and count ≥5 were enriched in a total of 4 biological processes, which were related to protein binding and ATP binding, enzyme binding, and identical protein binding. See In the GO function analysis, a total of 177 biological processes were enriched. The results showed that the key targets are closely related to the regulation of biological functions such as the ERBB2 signaling pathway, positive regulation of nitric oxide biosynthetic process, phosphatidylinositol-mediated signaling, and protein autophosphorylation. Regarding biological processes, a total of 8 processes were enriched with A network relationship diagram of “components-core targets-important pathways” using Cytoscape software visualization analysis was constructed. As shown in Marein and its metabolites may act on the same target to exert a similar activity. The intersection of the core targets of the three components shows that they may act on the six common targets GSTP1, PTPN1, SRC, ME2, HMGCR, and CASP3, and SRC are the core targets in the whole network. SRC; a proto-oncogene that is a member of the protein tyrosine kinase family, is one of the key factors leading to the increase of malignancy in many tumors .in vivo. The results remind us that when studying the efficacy and toxicity of flavonoids, the actual form of the flavonoids in vivo must be considered. The component-target-pathway network of marein, its aglycones, and flavanomarein was further established to illustrate their activity, and we found that marein and its metabolites act on key targets of EGFR, AKT1, SRC, HRAS, CASP3, and so on. It mainly involves pathways such as proteoglycans in cancer, pathways in cancer, estrogen signaling pathway, and Ras signaling pathway. The study provides a scientific basis for future research on the route of administration of flavonoids, the mechanism of action, and the discovery of lead compounds from active metabolites.A rapid and reliable UPLC-Q-TOF-MS/MS method was established for the first time to identify the metabolites of marein