In recent years, there has been an increased demand for highly sensitive and selective biosensors for neurotransmitters, owing to advancements in science and technology. Real-time sensing is crucial for effective prevention of neurological and cardiovascular diseases. In this review, we summarise the latest progress in aptamer-based biosensor technology, which offers the aforementioned advantages. Our focus is on various biomaterials utilised to ensure the optimal performance and high selectivity of aptamer-based biosensors. Overall, this review aims to further aptamer-based biosensor technology. Neurotransmitters are molecules responsible for transmitting signals between nerve cells and play crucial roles in the central nervous system and the cardiovascular system ,2. SinceAptamers are peptides or oligo-nucleic acids with high sensitivity and selectivity for the detection of various types of analytes ranging from nucleotides, peptides, proteins, and small molecules to cells ,27,28. AAptamer sensors based on various new biomaterials have been developed. For example, an aptamer sensor based on a gold material can be freely immobilised using various chemical conjugations ,41,42,43In this review, aptamer-based sensors are classified into five categories depending on the material used to detect the neurotransmitter: (1) gold-based, (2) gold/metal-hybrid-based, (3) graphene-based, (4) graphene/gold-hybrid-based, and (5) polymer/metal-hybrid-based . AccordiGold nanoparticles (GNPs) can be stably synthesised via simple methods. Additionally, they are biocompatible and have excellent electrical conductivity, high surface-to-volume ratios, and unique optical properties, making them suitable for use in biosensors ,74. FurtRecently, a GNP-based aptamer has successfully been used to detect serotonin (5-HT) by virtue of the optical characteristics of the GNPs . Gold ioIn studies, GNPs have been synthesised in a variety of forms, which have then benefitted from testing by a variety of analytical methods . For exaIn addition to 3D nanostructures, aptamer sensors in the form of gold-film electrodes have been studied. In a study by Zhao et al., DA was successfully detected using a dual-nanopore aptamer sensor with a gold-film deposition . In suchPlasmodium falciparum (pf) glutamate dehydrogenase in serum samples using an aptamer sensor in which FETs were structurally interlocked with gold electrodes [The use of physically interdigitated gold-based electrodes and field-effect transistors (FETs) has been shown to be effective in the sensitive detection of analytes. In 2019, a group reported the detection of ectrodes . The senGold nanostructures have unlimited potential depending on their application. They can be grown, attached by chemical bonding, or deposited onto the sensor surface. Similarly, the sensitivity of the sensor to detect an analyte can be fine-tuned. Modification of gold in the aptamer sensor improves the fundamental properties of the metal and aptamer binding performance, which is an important advantage of this biomaterial in that it does not damage the sensor.Recently, various metals, such as Au, Pt, Ag, and Cu, have been used for biosensor development ,78,79,80. Three-dimensional bimetallic Au/Pt nanoflowers were synthesised by anchoring a Au spike with improved conductivity, adding a catalytic layer of Pt on top, and finally adding the aptamer. The LOD and linear range were estimated at 2.5 μM and 2.5–447 μM, respectively , with large internal surface areas and various configurations and adjustable cavity sizes, were used as materials for catalysis [4. The detection results were measured using SERS. The linear range and LOD were 0.01–0.25 nM and 0.008 nM, respectively. High selectivity was demonstrated by detecting DA in human serum samples, and excellent reproducibility was also confirmed. These results suggest that MOF-type metal-hybrid aptamer sensors are suitable for sensitive detection of DA.In 2022, a successful report was published on the detection of DA using an aptamer sensor based on a Ni/Pt hybrid . An aptaectively B. These ectivity C. Only natalysis ,83. Shi atalysis . After tHybrid forms with two or more metals exhibit high sensitivity to analytes due to the synergistic effect of the metals. Moreover, hybridism circumvents the drawbacks of sensors that are based on a single metal and provides high selectivity. Combinations of metals in multiple phases may be particularly effective candidates for sensing a range of analytes, given that their sensing properties can vary depending on the metal types and proportions.Graphene is a carbon allotrope with a hexagonal honeycomb-shaped two-dimensional planar structure and has attracted much attention due to its excellent electrical conductivity, thermal conductivity, chemical and physical stability, and biocompatibility ,85.In 2021, Hwang et al. successfully detected DA at the fM level using crumpled graphene . Using gThere has also been an attempt to detect multiple neurotransmitters using graphene. Gao et al. successfully detected DA and 5-HT by arranging graphene with different aptamers on a single substrate in such a way that the circuits did not overlap . After fIn 2022, a group succeeded in quantitating DA using a graphene multi-transistor array (gMTA) functionalised with a selective DNA aptamer . Micron-The above studies suggest that graphene-based aptamer sensors have various advantages over other neurotransmitter sensors. Graphene has proven to be an easily implementable substrate for aptamer immobilisation that does not induce damage to biological samples. Moreover, the facile handling and superior analyte adsorption properties of graphene are expected to advance the development of aptamer sensors based on this biomaterial.It has been reported that metals, such as Al, Cu, Au, and Mo, used in sensors have high biocompatibility and excellent electron transfer characteristics, enabling them to be used as electrochemical sensors ,87,88. IMahmoud et al. developed an aptamer sensor decorated with GNPs on carboxylated carbon nanotubes (CNT) and succeeded in sensing histamine (HA) sensitively and selectively . To cons2 and rGO was developed to monitor DA [Reduced graphene oxide (rGO), Al, and Cu are widely used as electrochemical sensors because of their high chemical stability and ability to synergistically interact with various materials . In one nitor DA . rGO wasnitor DA ,96. In anitor DA ,100,101.nitor DA . The higMetal/graphene hybrids can improve the signal between aptamers and analytes. Additionally, the properties of graphene can be exploited to use biosensors with immunoassays for simpler adsorption of metals or aptamers. This type of aptamer sensor, combining the advantages of metals and graphene, has efficient sensing performance. Moreover, it has better sensing performance than sensors that are based solely on graphene or metal. Nevertheless, additional research on the hybrid technology and the factors affecting detection performance is needed to achieve optimum performance.Since polymers are composed of repeatedly connected units, they can be fabricated so as to have flexible forms ,104,105.2O3 and Au/Ti electrodes through spin coating and oxygen plasma etching on a Si substrate  are crosslinked polymers, which are synthesised based on the template molecule, and in which removal of the template generates the target-specific binding site . Like otIt has been proven that the combination of polymer and metal not only improves sensing functionalisation through flexible adsorption and penetration in vivo but also maximises the sensing performance of the aptamer sensor alone. A polymer/metal-based-hybrid aptamer sensor can be an excellent candidate to effectively detect various targets by taking advantage of the fact that results vary depending on how the material and composition are utilised.This review summarised the recent research on aptamer-based biosensors for detecting and monitoring neurotransmitters in various materials. All the biomaterials reported above have demonstrated excellent efficacy for neurotransmitter detection. Metal-based aptamer sensors have excellent electron-transfer and signal-amplification properties, which vary according to the structural arrangement of the aptamer, and thus such sensors can be freely applied to electrochemical or optical systems. Graphene-based aptamer sensors feature excellent stability and high adsorption of analytes and chemicals. Likewise, the sensing performance of the metal/graphene hybrid is amplified by the synergistic effect of the strengths of each material. In addition, aptamer sensors based on polymer/metal hybrids can be used in various environments, and their high biocompatibility allows stable sensing in biological samples.Since an increasing number of human nervous system diseases are being reported every year, researchers need to develop sensors that can easily detect various types of neurotransmitters. A particular problem is that in many situations the analyte of interest is present at low concentrations in a complex medium. Therefore, further research on the materials and technologies that can improve the sensitivity, accuracy, specificity, and reliability of biosensors is needed. In addition, although the sensing performance of biosensors with rigid or complex structures is usually stable and efficient, they are generally not suitable for real-time or sub-cellular monitoring. Therefore, in addition to increasing the sensing performance, efforts should be made to improve the biocompatibility and reproducibility of biosensors, and to prevent potential problems that may be experienced during on-site performance.


Anxious individuals selectively attend to threatening information, but it remains unclear whether attentional bias can be generalized to traumatic events, such as the COVID-19 pandemic. Previous studies suggested that specific threats related to personal experiences can elicit stronger attentional bias than general threats. The current study aimed to investigate the relationship between content-specific attentional bias and trait anxiety during the COVID-19 pandemic.Attentional bias was assessed using the dot-probe task with COVID-19-related, general threat-related, and neutral words at two exposure times, 200 and 500 ms.We found participants with high trait anxiety exhibited attentional bias toward COVID-19- related stimuli and attentional bias away from general threat-related stimuli, while participants with low trait anxiety showed attentional bias away from both types of stimuli.Results suggest that individuals with high trait anxiety show a content-specific attentional bias to COVID-19-related information during the COVID-19 pandemic. Apart from the innate attentional bias toward biological threats, individuals with high trait anxiety may also learn from trauma and develop trauma-specific attentional bias. The COVID-19 pandemic has had a profound impact on multiple aspects of life, causing widespread traumatic stress for many people , but intPrevious studies have suggested that there was a positive association between attentional bias toward COVID-19-related stimuli and anxiety symptoms. For example, Cannito et al.  found leA prior meta-analysis indicates that specific threatening stimuli which is related to individuals’ anxiety type  can elicit a stronger attentional bias than general threat-related stimuli . This smIndividuals with high levels of trait anxiety have been shown to process and react differently to threat-related resources compared to those with low levels of trait anxiety . Trait aCOVID-19 stimuli are distinct from ordinary disease stimuli as they have a comprehensive impact on multiple domains of life. As proposed by Taylor , the psyRegarding the temporal mechanisms underlying attentional bias, there has been consistent debate on whether anxiety symptoms are linked with elevated orienting toward, or impaired disengagement from, threatening stimuli. The vigilance-avoidance model and the attention maintenance model emerged as two dominant views. In the vigilance-avoidance model, anxious individuals demonstrate an initial vigilance toward threatening stimuli and a subsequent avoidance away from the stimuli . In contA range of experimental paradigms have been developed to measure attentional bias, including the widely-used dot-probe task. In this task, a neutral stimulus and a threat-related stimulus are presented simultaneously on a computer screen . SubsequA previous meta-analysis suggested that stimuli types (words or pictures) may also be an important factor in the dot-probe task . SpecifiDue to the inconsistent results in previous COVID-19-related attentional bias studies and the lack of evidence regarding how trait anxiety is associated with COVID-19 attentional bias, further research is needed. According to evolutionary models, all humans possess an innate ability to rapidly detect environmental threats of survival significance, regardless of their susceptibility to anxiety . HoweverA priori power analysis using G*power 3.1.9.7 . The participants were all right-handed, without physical disease, had normal or corrected-to-normal vision and had no color blindness or color weakness. Participants were also evaluated using the Chinese version of the Mini International Neuropsychiatric Interview by phone calls , Is there a limit on your outdoor activities  and How long have you been quarantined . A general score for the extent of exposure to the COVID-19 pandemic was computed by summing the three item scores.M = 20.82, SD = 1.10) to rate the valence and arousal of these word stimuli using a 9-point Likert scale . There was a significant difference between the valence of COVID-19-related words  and neutral words , t (28) = 15.48, p < 0.001, and between general threat-related words  and neutral words, t (28) = 17.35, p < 0.001, but there was no significant difference between the valence of COVID-19-related words and general threat-related words, t (18) = 0.43, p = 0.68. There was a significant difference between the arousal of COVID-19-related words  and neutral words , t (28) = 20.25, p < 0.001, and between general threat-related words  and neutral words, t (28) = 19.49, p < 0.001, but there was no significant difference between the arousal of COVID-19-related words and general threat-related words, t (18) = 1.05, p = 0.31.The current study used word stimuli including COVID-19-related words, general threat-related words, and neutral words. COVID-19-related words were selected from the COVID-19 vocabulary approved by China International Publishing Group. General threat-related words and neutral words were taken from word lists used in previous studies examining attentional biases toward general threats  and the www.naodao.com. During the experiment, participants needed to share their computer screens with the researcher via an online meeting software to avoid distraction. The experiment adopted the dot-probe task. In each trial, a cross fixation “ + ” appeared in the center of the screen for 500 ms. After the fixation disappeared, one emotional word  and one neutral word were simultaneously presented on the left and the right parts of the screen. Emotional words and neutral words were presented at random positions on the left and right parts of the screen. The two words were colored white, spaced 12 cm apart, and were presented for 200 or 500 ms. After the words disappeared, a target dot (“※”) randomly appeared at one of the previous positions occupied by the two words. Participants needed to press the key “F” or “J” to judge whether “※” was on the left or the right of the screen. After participants pressed the key, the trial terminated, and the next trial commenced after a 1,000 ms blank screen  data were analyzed after removing incorrect responses (3%). Median RTs were used to reduce the effect of outliers in the dot-probe task , 39. ForM = 45.03, SD = 8.40). In the current study, participants who had an STAI-T score below 43.5 were assigned to the low anxiety group  and participants who had an STAI-T score above 43.5 were assigned to the high anxiety group . The independent samples t-test showed there was a significant difference in the scores on STAI-T between the low anxiety group  and the high anxiety group , t (60) = 10.97, p < 0.001.The median STAI-T score was 43.5 . We adopted an exclusion criterion on error rates above 20% used by Fani et al.  = 1.68, p = 0.20, ηp2 = 0.03. Exposure Time had no main effect on the attentional bias index, F  = 0.02, p = 0.90, ηp2 = 0.00. Stimuli Type had no main effect on attentional bias index, F  = 0.54, p = 0.47, ηp2 = 0.01.We conducted a 2 × 2 × 2 mixed design analysis of variance (ANOVA) on attentional bias index with Anxiety Group (low and high) as a between-participant factor and Exposure Time (200 ms and 500 ms) and Stimuli Type  as within-participant factors. Anxiety Group had no main effect on the attentional bias index, F  = 4.40, p = 0.040, ηp2 = 0.07. Further simple effect analysis of the interaction revealed that participants in the high anxiety group paid more attention to COVID-19-related words  than general threat-related words , p = 0.050. For participants in the low anxiety group, there was no significant difference between COVID-19-related words  and general threat-related words , p = 0.349.There was a significant Anxiety Group × Stimuli Type interaction on the attentional bias index see , F  = 3.09, p = 0.08, ηp2 = 0.05. There was no significant Exposure Time × Stimuli Type interaction, F  = 1.42, p = 0.24, ηp2 = 0.02. There was no significant three-way Anxiety Group × Exposure Time × Stimuli Type interaction, F  = 0.25, p = 0.62, ηp2 = 0.00.There was no significant Anxiety Group × Exposure Time interaction, The present study is the first to examine the differences between attentional bias toward COVID-19-related and general threat-related stimuli in trait anxiety. Participants with high trait anxiety exhibited an attentional bias toward COVID-19-related stimuli and an attentional bias away from general threat-related stimuli, while participants with low trait anxiety showed an attentional bias away from both types of stimuli. The results indicate that individuals with high trait anxiety are more susceptible to chronic stress exposure and show specific attentional bias toward threatening information corresponding to their current worries.We found the attentional bias toward COVID-19-related stimuli among individuals with high trait anxiety. This result aligned with previous studies which found a positive association between attentional bias toward COVID-19 stimuli and health anxiety  and COVINotably, we did not find an attentional bias toward general threat-related stimuli among individuals with high trait anxiety. This result was inconsistent with a previous meta-analysis which indicated a stable pattern of anxiety-linked attentional bias toward threats . The incWe did not find an attentional bias toward either COVID-19-related or general threat-related stimuli among individuals with low trait anxiety. This result is consistent with previous studies . AlthougAbout the components of attentional bias, we did not find a significant effect of exposure time on the attentional bias index. Participants with high trait anxiety showed attentional bias toward COVID-19-related stimuli and then maintained their attention, within the time course from 200 ms to 500 ms. In contrast, they at first biased away from general threat-related stimuli and then directed their attention to general threat-related stimuli. Participants with low trait anxiety showed an opposite pattern. These results align with a meta-analysis that found attentional bias in a wide range of exposure times among anxious individuals . HoweverThe current study has implications for increasing intervention efficacy, particularly for ABMT and post-disaster interventions. Prior meta-analyses examining ABMT have demonstrated small-to-medium effect sizes for reducing anxiety symptoms , 55. To Despite the valuable contributions of the present study, certain limitations should be acknowledged. First, the sample size of the current study is only 62, which may be the reason why there is no significant correlation between trait anxiety and attentional bias. Previous studies which found a significant correlation between trait anxiety scores and attentional bias indexes had a larger sample size. For example, Salemink et al.’s study (2007) recruited 133 participants and Rudaizky et al.’s study (2014) recruited 72 participants. A larger sample size is needed to explore the linear relationship between trait anxiety and attentional bias. Second, the cross-sectional design precluded the ability to establish causal relationships between trait anxiety and attentional bias. To address this limitation, future investigations may consider implementing a longitudinal design to explore whether a bidirectional and mutually facilitating causality exists between anxiety and attentional bias , whereasThe present study contributes to the field by providing evidence on content-specific attentional bias toward COVID-19-related stimuli in trait anxiety. Participants with high trait anxiety exhibited an attentional bias toward COVID-19-related stimuli and attentional bias away from general threat-related stimuli, while participants with low trait anxiety showed attentional bias away from both types of stimuli. Our findings suggest several theoretical implications. We contribute to the field of content specificity by investigating personalized specificity in a group of individuals who shared similar chronic stress exposure. The current study also has clinical implications for ABMT and post-disaster intervention. The use of content-specific stimuli which are related to participants’ personal experiences could improve intervention efficacy.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving humans were approved by the University Committee on Human Research Protection of East China Normal University. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.YZ: Data curation, Writing−original draft. XJ: Investigation, Methodology, Writing−review and editing. SP: Software, Visualization, Writing−review and editing. HJ: Writing−review and editing. YW: Conceptualization, Funding acquisition, Methodology, Project administration, Resources, Supervision, Writing−review and editing.


Plant Small Secreted Peptides (SSPs) play an important role in plant growth, development, and plant–microbe interactions. Therefore, the identification of SSPs is essential for revealing the functional mechanisms. Over the last few decades, machine learning-based methods have been developed, accelerating the discovery of SSPs to some extent. However, existing methods highly depend on handcrafted feature engineering, which easily ignores the latent feature representations and impacts the predictive performance.in silicomutagenesis experiment, ExamPle can discover sequential characteristics and identify the contribution of each amino acid for the predictions. The key novel principle learned by our model is that the head region of the peptide and some specific sequential patterns are strongly associated with the SSPs’ functions. Thus, ExamPle is expected to be a useful tool for predicting plant SSPs and designing effective plant SSPs.Here, we propose ExamPle, a novel deep learning model using Siamese network and multi-view representation for the explainable prediction of the plant SSPs. Benchmarking comparison results show that our ExamPle performs significantly better than existing methods in the prediction of plant SSPs. Also, our model shows excellent feature extraction ability. Importantly, by utilizing https://github.com/Johnsunnn/ExamPle.Our codes and datasets are available at  Plant Small Secreted Peptides (SSPs) are crucial intercellular messenger molecules that regulate a multitude of processes . SSPs arArabidopsis thaliana plant  by liquid chromatography–mass spectrometry analysis  to discover SSPs. For example, a novel 15-aa SSP named CEP1 encoded by AT1G47485 is identified in Arabidopsis thaliana  was proposed by The Siamese network can be used to quantify the similarity of two sequences. For example, aiming to finding matching and non-matching pairs of images, After gaining the hidden state output Aiming to decrease the distance between representation vectors of peptide sequences with the same label and increase the distance between representation vectors of peptide sequences with the different label, we use contrastive loss  L1 as thIn this way, we can use gradient descent algorithm to optimize the parameters of the network and generate unified representation for each inputs pair. Also, we need a discriminator To be mentioned, if the FNN and the discriminator are connected directly, the parameters will be updated jointly, which will result in the catastrophic forgetting . In ordeRefer to previous works, we use following classification metrics to evaluate our model: accuracy (ACC), specificity (SP), sensitivity (SE), and Matthew correlation coefficient (MCC). The formulas of these metrics are as follows:In the formulas, TP is the number of true-positive samples, FP is the number of false-positive samples, TN is the number of true-negative samples, and FN is the number of false-negative samples. Accuracy is the ratio of the correctly classified samples to the total samples, which is the most intuitive performance measurement. Specificity measures the proportion of the negative samples which are classified correctly, and Sensitivity measures the proportion of the positive samples which are classified correctly. MCC takes into account positives and negatives, so that it is generally regarded as a balanced metric to measure the overall performance of a model.To evaluate the performance of ExamPle, we adopted several classic comparative models including Naive Bayes , LogistiIn order to verify the effectiveness of the feature representation learned by ExamPle, we compared the performance of different handcrafted feature methods with our model. With the help of iLearnPlus , 2021, wAs shown in It is rarely clear how the deep learning model works during the training process. For a more transparent understanding, we reduced our model’s latent space to a 2D space using principal component analysis (PCA)  and t-diGiven the excellent performance of our complex neural network architecture, we are targeting further exploration of the sequential characteristics of plant SSPs from a computation perspective. To this end, we performed in silico mutagenesis (ISM) interpretation method for every peptide in our dataset and mutated each reference amino acid of a peptide into other nineteen alternative amino acids to evaluate the predicted probability change. Moreover, we conducted amino acid statistical probability for each position on SSPs dataset and the non-SSPs dataset respectively in Glutamine), and P (Proline) have a significant inhibitory effect on the prediction score. To be specific, in the position between 10 and 16, when the amino acid is mutated with Q or P, the prediction score is significantly reduced. The possible reason for this is that Q and P are frequently present in the non-SSPs and are present less frequently in the SSPs, as illustrated in the L-Cysteine) is frequently present in the tail of the non-SSPs. And observations from l-isoleucine), L (Leucine), and F  have a stimulative effect on the prediction score in most positions of the sequence. The possible reason for this is that, as shown in Here, we select one 59-bp-length sequence as the sample to generate the heat map in Glycine) in the SSPs is smaller than that in the non-SSPs, but our model considers that G contributes more to the prediction score in the SSPs, showing our model can mine features that cannot be counted by traditional statistical methods. To sum up, these experiments indicate that our model can mine the sequential characteristics of SSPs.Then, to make the results more statistically meaningful, we computed the contribution of each amino acid on the whole dataset. For each peptide of SSPs and non-SSPs, we calculated amino acid scores by accumulating each position score from the ISM results. In detail, we can sum the score of one row in Methionine) has a more functional impact on the central region, while amino acid C (Cysteine) has a more functional impact in the tail region, which are both meaningful points to be noticed in the peptide design. Next, to further intuitively illustrate which region is more important, we divided each peptide in the dataset into 25 parts and accumulated the amino acid scores to get the comprehensive score of the position. In We next seek to understand the connection between the functional impact and the sequence region. To this end, regardless of the positive or negative effect of one position, we utilized the absolute value subtracted from the ISM experiment as the importance scores to evaluate how the contextual region affects the plant SSPs’ function. To unify all the sequences into one fixed length, we split the sequence into 50 parts. Here, each part is referred as a position ratio. In To better verify the phenomenon in P-value. The lower P-value indicates a higher degree of motif consistency. After we utilize importance scores to intuitively find which region is important for the peptide function, it is very natural to explore the motif of this region from a computation perspective. In In this study, we present a novel explainable contrastive hybrid-view dual Siamese framework ExamPle for predicting the plant SSPs and discovering the sequential pattern of the SSPs. The experiment results demonstrate that the Siamese framework with secondary structure information can learn discriminative feature information and effectively enhance the performance of our model for the plant SSPs prediction. Besides, by adopting dimension reduction methods, the visualization of latent space clearly shows the great learning ability of our model and outperforms traditional handcrafted feature engineering. Utilizing ISM interpretation methods, ExamPle can discover sequence characteristics and identify the contribution function of each amino acid, which are mostly consistent with the statistical results. In addition, by accumulating functional differences between the variant and original sequences, the key novel principle learned by our model is that the head region in peptides and some specific sequential patterns are strongly associated with the SSP function. Thus, our well-trained model ExamPle can not only provide the prediction for plant SSPs but also pave the way for effective and stable plant SSPs design.btad108_Supplementary_DataClick here for additional data file.


Streptococcus mutans BSI (33% [9/27]) followed by S. sanguinis (31% [20/64]), S. gordonii (23% [5/22]), S. gallolyticus (16% [12/77]), and S. oralis (12% [14/115]). In multivariate analysis, previous IE, high-grade BSI, native valve disease, prosthetic valve, congenital heart disease, and community-onset BSI were independent risk factors for IE. After adjusting for these factors, S. sanguinis , S. mutans , and S. gallolyticus  were significantly associated with higher risk of IE, whereas S. pneumoniae  and S. constellatus  were associated with lower risk of IE. Age, hospital-acquired BSI, ischemic heart disease, and chronic kidney disease were independent risk factors for mortality in streptococcal IE. Our study points to significant differences in the prevalence of IE in streptococcal BSI according to species.This study aimed to identify which streptococcal species are closely associated with infective endocarditis (IE) and to evaluate risk factors for mortality in patients with streptococcal IE. We performed a retrospective cohort study of all patients with streptococcal bloodstream infection (BSI) from January 2010 to June 2020 in a tertiary hospital in South Korea. We compared clinical and microbiological characteristics of streptococcal BSIs according to the diagnosis of IE. We performed multivariate analysis to evaluate the risk of IE according to streptococcal species and risk factors for mortality in streptococcal IE. A total of 2,737 patients were identified during the study period, and 174 (6.4%) were diagnosed with IE. The highest IE prevalence was in patients with IMPORTANCE Our study of risk of infective endocarditis in patients with streptococcal bloodstream infection demonstrated that Streptococcus sanguinis, S. mutans, and S. gallolyticus were significantly associated with higher risk of infective endocarditis. However, when we evaluated the performance of echocardiography in patients with streptococcal bloodstream infection, patients with S. mutans and S. gordonii bloodstream infection had a tendency of low performance in echocardiography. There are significant differences in the prevalence of infective endocarditis in streptococcal bloodstream infection according to species. Therefore, performing echocardiography in streptococcal bloodstream infection with a high prevalence of, and significant association with, infective endocarditis is desirable. Streptococcus species is one of the most common causes of infective endocarditis (IE) after Staphylococcus aureus . Of the 2,737 patients, 1,177 (43%) underwent echocardiography within 1 month of streptococcal BSI, and 174  were diagnosed with IE. As shown in Table S1, older patients (P = 0.008) and those with high-grade BSI (P < 0.001), a history of IE (P < 0.001), and underlying heart disease were more likely to undergo echocardiography; those with community-onset BSI (P < 0.001) and polymicrobial BSI (P < 0.001) were less likely to undergo echocardiography. In terms of streptococcal species, patients with BSIs caused by S. mitis (P < 0.001), S. oralis (P < 0.001), S. gallolyticus (P = 0.011), and S. sanguinis (P = 0.015) were significantly more likely than other patients to undergo echocardiography, while those with BSIs with S. anginosus (P = 0.009), S. pneumoniae (P < 0.001), and S. constellatus (P = 0.047) were significantly less likely.A total of 2,985 patients with streptococcal BSI were identified during the study period. Of these, 249 patients with streptococcal bacteremia due to unidentified species were excluded from the analysis, leaving 2,737 patients with streptococcal BSI included in the analysis. 10-year trends of streptococcal BSI according to species are presented in Fig. S1 in the supplemental material. The annual number of streptococcal BSI did not change significantly (P < 0.001), underlying heart disease (P < 0.001), high-grade BSI (P < 0.001), and history of IE (P < 0.001). The highest IE prevalence was found in patients with Streptococcus mutans BSI (33% [9/27]) followed by S. sanguinis (31% [20/64]), S. gordonii (23% [5/22]), S. gallolyticus (16% [12/77]), and S. oralis (12% [14/115])  . Mitis g14/115]) . When beS. sanguinis , S. mutans , and S. gallolyticus  remained risk factors for IE, whereas S. pneumoniae  and S. constellatus  were associated with lower risk of IE , have hospital-acquired BSI (P = 0.021), a prosthetic valve (P = 0.030), heart failure (P = 0.003), ischemic heart disease (P = 0.011), diabetes mellitus (P = 0.006), a solid cancer (P < 0.001), and chronic kidney disease (P = 0.001). They were less likely to have congenital heart disease (P = 0.041), undergo valve surgery within 3 months of BSI (P < 0.001), or have a BSI with S. mitis (P = 0.032) or mitis group bacteria (P = 0.026).One-year mortality due to streptococcal IE was 23% (40/174). Comparisons of the clinical and microbiological characteristics of deceased and surviving streptococcal IE patients are shown in P = 0.001), hospital-acquired BSI , ischemic heart disease , and chronic kidney disease  were independent risk factors for mortality in patients with streptococcal IE.Because of the strong correlation between heart failure and ischemic heart diseases, we retained only ischemic heart disease in the multivariate analysis for mortality . In addiMortality rates in patients with streptococcal IE were significantly lower than in those with non-IE streptococcal BSI , the prevalence of S. parasanguinis in the present study was only 2.5%. In the present study, S. mutans, S. sanguinis, and S. gallolyticus were independent risk factors for IE in streptococcal BSI. However, when we compared patients with streptococcus BSI according to the use of echocardiography, patients with S. mutans or S. gordonii BSI were not more likely to undergo echocardiography than other patients. Based on these results, it seems desirable to perform routine echocardiography in streptococcal BSI caused by species with a high prevalence of, and significant association with, IE .In the present study, infections with d et al.  who obsestreptococcus in the anginosus group were less likely to undergo echocardiography. Although the prevalence of IE among infections with streptococci in the anginosus group was low in our study, the absolute number of anginosus group patients with IE was the second largest due to the large proportion of the streptococcal BSI cases due to members of the anginosus group. Furthermore, the absolute number of pyogenic group patients with IE was the third largest. This was mainly attributed to S. agalactiae IE accounting for the third largest IE cases following S. mitis and S. anginosus. In a recent U.S. study of 296 patients with streptococcal IE, the pyogenic group accounted for 17% of streptococcal IE, and S. agalactiae was the most common pathogen (78%) in this pyogenic group . Informed consent was waived by the ethics committee of Asan Medical Center because no intervention was involved, and no patient-identifying information was included. To protect personal privacy, identifying information in the electronic database was encrypted.Streptococcus from one or more blood cultures. Community-onset BSI was classified as blood culture obtained within 48 h of hospitalization  were diagnosed based on clinical data and echocardiographic results according to the modified Duke criteria, and cases with Duke-possible IE who had no evidence of vegetation on echocardiography were not classified as IE . Species and antimicrobial susceptibilities were determined with a Vitek  or Microscan  in accordance with the standard criteria of the Clinical and Laboratory Standards Institute . MALDI-Tt test or the Mann-Whitney U test was used to compare continuous variables, and the Pearson chi-squared test or Fisher’s exact test was used to compare the respective categorical ones, as appropriate. We performed multivariate analysis to identify risk factors for IE in patients with streptococcal BSI using logistic regression. To evaluate the risk factors for mortality in streptococcal IE, we performed a Cox regression analysis. A two-tailed P value of <0.05 was considered statistically significant. All statistical analyses were performed with R software, version 3.3.3 .Trends in frequency of streptococcal BSI according to streptococcal species were evaluated with the Mann-Kendall trend test. Prevalences of IE at the streptococcal species level were calculated as number of IE cases due to each species divided by total number of BSI caused by that streptococcal species during the study period . Student


Three-dimensional (3D) printing, alternatively known as additive manufacturing, is a transformative technology enabling precise, customized, and efficient manufacturing of components with complex structures. It revolutionizes traditional processes, allowing rapid prototyping, cost-effective production, and intricate designs. The 3D printed graphene-based materials combine graphene’s exceptional properties with additive manufacturing’s versatility, offering precise control over intricate structures with enhanced functionalities. To gain comprehensive insights into the development of 3D printed graphene and graphene/polymer composites, this review delves into their intricate fabrication methods, unique structural attributes, and multifaceted applications across various domains. Recent advances in printable materials, apparatus characteristics, and printed structures of typical 3D printing techniques for graphene and graphene/polymer composites are addressed, including extrusion methods (direct ink writing and fused deposition modeling), photopolymerization strategies  and powder-based techniques. Multifunctional applications in energy storage, physical sensor, stretchable conductor, electromagnetic interference shielding and wave absorption, as well as bio-applications are highlighted. Despite significant advancements in 3D printed graphene and its polymer composites, innovative studies are still necessary to fully unlock their inherent capabilities. In recent years, the exploration of innovative materials and advanced manufacturing techniques has become pivotal in addressing the growing demand for multifunctional materials with tailored properties across a multitude of applications. Among these materials, graphene has garnered exceptional attention due to its remarkable mechanical strength, high thermal and electrical conductivity, and impressive surface area . GraphenThree-dimensional 3D) printing, or additive manufacturing, is a process of creating 3D objects by adding materials layer by layer based on a digital design or model, which allows for the creation of complex and customized shapes directly from a digital file without the need for traditional subtractive methods such as cutting or drilling D printin,5. The aOver the last decade, the field of 3D printing has witnessed a surge in research focused on graphene-based materials, resulting in a diverse array of hierarchical structures with remarkable properties. The extrusion-based, photopolymerization-based, and powder-based 3D printing techniques have been confirmed to be effective in fabricating graphene and graphene/polymer composites ,10,11,12Typically, the process of 3D printing involves several routines: (i) preparing printable materials; (ii) designing the structures using 3D modeling software, such as computer-aided design software and a 3D scanner; (iii) slicing the 3D model into 2D layers; and (iv) printing materials layer by layer ,14. SeveThe extrusion techniques (DIW and FDM) involve the deposition of material in a controlled manner through a nozzle or extrusion system, building objects layer by layer via extruding and depositing materials in a semi-liquid or molten state. Extrusion techniques offer versatility in terms of material compatibility, as they can accommodate a range of materials such as thermoplastics , thermosDIW enables the precise deposition of functional inks to create complex and customizable 3D structures. In DIW, a viscous ink is dispensed through a nozzle or similar extrusion system and is directly written onto a substrate or previously printed layers . Inks fo−1 σysh≥Though GO dispersions are widely applied as inks for DIW, not all of them are suitable. Several techniques have been developed for the optimization of GO inks, including strengthening GO networks by (i) increasing strengths of inks with a higher concentration and larger lateral size, (ii) gelling induced by inter-sheet crosslinking, and (iii) adding rheology modifying additive . By care4 and 100 Pa, respectively, which are suitable for DIW-based 3D printing.The mechanical properties and viscosity of colloidal GO dispersions are related to the colloid volume concentration. Generally, four different states of GO suspensions were observed with different GO concentrations: viscoelastic liquid, transition region, viscoelastic soft solid, and liquid crystalline gel, as shown in 2+ acts as crosslinkers of GO sheets, turning the GO sol into a viscous hydrogel, as shown in 2+ ions lead to changes in the rheological behaviors of the GO solution, increasing its viscosity and storage modulus. This allows the hydrogel to maintain stability and flow, making it suitable for use in DIW for 3D printing , G, G88], G0.01 wt% . The per0.01 wt% ,90,91,92The apparatus of SLA mainly consists of a laser source that generate UV lasers for polymerization of photopolymers, a lens and an XY coordination mirror system to control the moving of the UV laser, a build platform that can move up and down to accumulate photopolymerized composites layer by layer, as shown in Different from the extrusion-based techniques discussed before, SLA-printed objects generally show relatively layerless and continuous build. SLA is a form of vat photopolymerization, where a liquid photopolymer resin is selectively cured by a focused UV laser to solidify it into the desired shape. This process results in objects with smooth and homogeneous surfaces c,d, lackDLP utilizes a digital micromirror device (DMD) and photopolymer resins to create three-dimensional objects, which shares similarities with SLA in terms of using photopolymerization to solidify liquid resin . HoweverIn addition to the DLP printing system, the graphene/photopolymer is critical to the final DLP printed objects . The genBy taking advantage of the solubility of GO in ethanol as well as the miscibility of ethanol and acrylic resins, a concentrated GO liquid crystal ethanol solution with sufficient viscosity was prepared by Tilve-Martinez and coworkers for DLP printing, as shown in Sharing similar printing mechanisms with SLA (despite the different UV light sources), DLP printing selectively cure an entire layer of liquid resin on the latest cured layer. As a result, the transitions between layers are generally smoother and less pronounced compared to methods that build objects through the incremental deposition of material, such as DIW and FDM. The continuous and smooth surfaces of DLP-printed objects are clearly shown in The SLS is a typical powder-based additive manufacturing process that is suitable for the fabrication of graphene/polymer composites. Selective laser melting is another commonly used powder-based 3D printing, while it is more applicable for metallic materials . In the As described, the SLS is based on the manufacturing of powders; therefore, the quality of the building powders directly influences the final 3D printed objects. Spherical polyvinylidene fluoride (PVDF) powders (average diameter of 200 nm) and GO powders (average diameter of 0.5–3 μm and average thickness of 0.55–1.2 nm) were blended in ethanol which can disperse GO sheets but do not dissolve PVDF powders . After u2 laser on carbon-containing material, such as polyimide (PI), cloth, paper, and food, in ambient atmosphere [The SLS was integrated with the laser-induced graphene (LIG) process to print neat graphene objects. The LIG is a 3D porous material prepared by direct lase writing with a COmosphere ,124. A Lmosphere . On the The morphology of graphene nanocomposites fabricated through SLS is highly diverse, intricately influenced by factors such as powder characteristics, sintering parameters, and post-processing treatments. However, similarly, within the SLS procedure, where layers of material are meticulously fused by a precision laser, the graphene sheet-coated polymer powders coalesce to unveil a distinctive segregated distribution . As showWhile each section of 3D printing techniques briefly touched upon the post-processing of 3D printed graphene and graphene/polymer composites, this section aims to offer a more comprehensive exploration of the pivotal post-processing steps. It is recognized that diverse 3D printing methods demand distinct post-processing approaches to optimize material properties and end-product quality. Recognizing the unique attributes of each 3D printing technique, this section will delve into the tailored post-processing strategies for each method.2/rGO aerogel lattices via post-electrodeposition of MnO2 nanosheets, thereby conferring exceptional supercapacitive performances upon the printed lattice [Upon completion of the DIW printing process, the removal of residual solvents from the printed objects becomes imperative. To achieve this, three primary strategies have been developed, namely freeze drying, supercritical fluid drying, and ambient-temperature drying, all aiming to preserve structural integrity while facilitating effective drying . Freeze  lattice .The characteristic “staircase effect” in FDM printed materials is readily discernible, presenting a distinct layer-by-layer morphology. To address this, thermal annealing emerges as a critical intervention, facilitating an advanced level of fusion and bonding amidst the sequentially deposited layers . This trComparable post-processing steps are requisite subsequent to SLA and DLP processes which both employ the solidification of liquid resin layer by layer via UV exposure. Upon the completion of printing, the object typically undergoes immersion in a solvent bath, which is essential to eradicate surplus uncured resin . This stUpon the completion of the SLS process, the printed object is carefully extracted from the surrounding loose powder, followed by elimination of surplus powders by either precise brushing or controlled blowing . As discBased on the above review on 3D printing techniques for graphene and graphene/polymer composite, comparisons of the above-discussed five methods are shown in Supercapacitors, also known as ultracapacitors or electrochemical capacitors, are a type of energy storage device that store and release electrical energy quickly and efficiently. They operate on the basis of electrostatic charge storage within the electrochemical double layer at the electrode–electrolyte interface, offering high power density, a long cycle life, and quick charging. This makes them suitable for various applications such as electric vehicles, renewable energy systems, and consumer electronics . TherefoThe 3D printed graphene structures show superiority over traditional thick-film electrodes in terms of supercapacity, as shown in Many efforts have been made to optimize the supercapacitance of 3D printed graphene ,140,141.3 solution at a potential of 1.9 V versus saturated calomel electrode [2 at an ultrahigh power density of 164.5 mW/cm2. A graphene aerogel microlattice fabricated by Ca2+ crosslinking-assisted DIW exhibited wrinkled porous structure and coherent conductive network, showing gravimetric capacitance of 213 F/g at 0.5 A/g and 183 F/g at 100 A/g, as well as a retention over 90% after 50,000 cycles [2 was developed by DIW-based printing of GO ink followed by freeze drying, thermal annealing and electrodeposition of MnO2 nanosheets, as shown in 2 (182.2 mg/cm2) on the 3D printed graphene aerogel electrode yielded high areal capacitance , excellent conductivity, and efficient ion diffusion. Through the symmetric arrangement of two 4 mm-thick electrodes the resultant device exhibited a notable energy density of 1.56 mW h/cm2. Moreover, this electrode, comprising a 3D-printed MnO2-deposited graphene aerogel, achieved exceptional capacitance values normalized to area, mass, and volume simultaneously, overcoming the typical trade-offs associated with most electrode materials.The supercapacitive properties of 3D printed graphene aerogels were further enhanced by surface functionalization of graphene sheets using electrochemical oxidation in 0.5 M KNOlectrode . With an0 cycles . A 3D-pr2), high energy density (4.17 μW h/cm2) and power density (0.22 mW/cm2). When printed on a flexible substrate, flexible supercapacitors are fabricated [In-plane microsupercapacitors with a compact size are a type of microscale energy storage device designed to be integrated into electronic circuits or systems. The addition of spacers of carbon sphere and a self-sacrificing template of ethyl cellulose in graphene inks enabled the 3D printing process of a graphene-based interdigital-structured microsupercapacitors, as shown in bricated ,148.3D printing for graphene-based batteries represents an innovative approach to fabricate advanced energy storage devices that harness the unique properties of graphene . Graphen2 batteries [2 batteries [2 when considering the total battery area. This configuration yielded initial charge and discharge capacities of 117 and 91 mA h/g, respectively, while maintaining commendable cycling stability.3D printing allows for intricate and complex battery designs, which can be tailored to specific applications. 3D printed GO framework with thermal shock synthesized nanoparticles for Li-COatteries  and holyatteries  are typiatteries . 3D prinatteries . An all-atteries . A metic2 plasma treatment. The 3D porous anode structure with high surface areas decreased the local current density and inhibited the growth of sodium dendrites. The N doping through controllable plasma treatment reduced the nucleation potential and promoted uniform sodium ion flux, which make additional contributions to the uniform deposition of sodium metal  into the 3D printed graphene microlattices was also beneficial to reduce the local current density and enhance the uniform nucleation and deposition of sodium metals [Another contribution of the 3D porous graphene-based architecture is its ability to inhibit the growth of metallic dendrites during charge and discharge cycling. As shown in m metals . Similarm metals .Working as substantial intermediates for collecting external mechanical signals, flexible strain sensors are regarded as indispensable components in flexible integrated electronic systems. Graphene-based strain sensors is an emerging and promising application that leverages the exceptional electrical properties of graphene to create highly sensitive and customizable sensors for measuring mechanical deformation or strain. The 3D printing technique has recently been used to fabricate flexible sensors due to its high accuracy, simplicity, and rapid prototyping ,158. GO Hybrid filler are applied to construct the conductive networks for optimization of 3D printed graphene-based strain sensor. FDM-printed high-performance flexible strain sensors using CNT and graphene nanoplatelet-filled TPU composite filaments showed a high sensitivity , a wide detectable strain range (0–250%) and good stability . In addiThe printing resolution of additive manufacturing plays an important role in determining performances of 3D printed strain sensors. A higher printing resolution results in more functional units exist per unit area, which can accurately sense deformations of objects (such as robot hand) in the form of resistance changes. Chen et al.  developeThe combination of artificial intelligence and robotics has become one of the fast-growing research fields and is considered to have a profound impact on human soci-ety. The development of robotic skin capable of perceiving external pressure environments, or the pressure sensing, is highly desirable for intelligent robots. Besides, pressure sensors find extensive applications in various industries, including automotive, aerospace, medi-cal, industrial automation, consumer electronics, and environmental monitoring. Based on the electrically conductive nature of graphene sheets, the graphene or gra-phene/polymer composite pressure sensors are generally piezoresistive, which directly convert the external pressure to an electrical signal  ,171,172.Taking advantages of the flexibility of structural design by 3D printing, different conductive networks  can be designed, showing different pressure sensing capacities ,176. HigLaser-induced graphene with a layered alignment and porous structure is suitable for pressure sensing. With careful adjustment of the laser power, a laser-induced graphene on-skin sensor for on-body monitoring, robotic hand control, and embedded machine learning for signal classification was designed . 3D prin−1. Extrusion-printed CNT/graphene lines using hybrid inks with different ratios of CNT and graphene exhibited temperature-dependent resistance with a significantly large negative temperature coefficient of resistance, showing an averaged resistance drop (per unit temperature) of −3.5 Ω/°C [−1, and it can be integrated using all-printed all-in-one configuration composed of a asymmetric microsupercapacitor and the temperature sensor [3D printing techniques also show great significance in temperature sensing ,181,182.3.5 Ω/°C . A 3D pr3.5 Ω/°C . A tandee sensor .−1 (0–60 kPa) and a high temperature sensitivity of 30.8 μV/K [By constructing complex geometries of graphene/polymer composite by 3D printing, flexible pressure– or strain–temperature dual parameter sensors utilizing independent piezoresistive and thermoelectric sensing mechanisms, respectively, can be achieved. A graphene-coated carbon nanofiber (CNF)/TPU architectures endowed the sensor with a high pressure sensitivity of 0.14 kPa0.8 μV/K . This se0.8 μV/K .Flexible temperature sensors often grapple with the challenge of sensing material deformation, leading to complications in maintaining sensing accuracy and reliability due to external strain-induced resistance fluctuations. Wang and colleagues addressed this issue by utilizing DIW to create graphene/PDMS composites with intricate geometries such as grids, triangles, and hexagons for strain-insensitive temperature sensing . the celThe addition of electrically conductive graphene sheets into a polymer matrix is a common strategy to make the intrinsically insulating polymer conductive . To achi3, an electrical conductivity of 278 S/m and a super-compressibility up to 90% compressive strain. DIW printing of electrically conductive graphene aerogel monolith using large-size GO sheets precursors enhanced the compressibility (up to 80% compressive strain), electrical conductivity (41.1 S/m), specific strength (10.7 × 103 N m/kg) and lowered density (12.8 mg/cm3) [2+ gelled GO/CNT hybrid inks were used for DIW printing of aerogels, followed by pre-buckled reduction, to produce highly stretchable graphene/CNT hybrid aerogels [With rational design, DIW printed graphene aerogel lattices can serve as flexible conductors, either stretchable or compressible. Zhu et al.  develope mg/cm3) . Ca2+ geaerogels . The higaerogels .The incorporation of elastomer matrices significantly enhances the mechanical robust, flexibility and stability of printed objects. Robust, flexible and conductive multilayer 3D printed graphene/polycaprolactone composites containing 10 wt% graphene were fabricated by the DIW process . Highly 3D graphene monoliths with controlled macrostructures can be fabricated through DIW using GO inks , but genCoating graphene nanosheets or graphene-based hybrid conductive materials on 3D-printed porous structure is another effective approach to combine carbon nanomaterial with 3D porous polymer substrates and thus to manufacture high-performance stretchable conductive materials. The eco-friendly and easy-moving PLA was firstly 3D printed to form a designed structure with spacing between neighboring skeletons being 200 μm, followed by backfilling PDMS with the assistant of vacuum and subsequent PLA etching . The porOwing to the fast development of modern electronics, communications, and industries, the spatial environment in earth is constantly exposed to electromagnetic radiations which are hazardous to our health and safe operation of electronic devices. To minimize the negative effects of electromagnetic radiations, electromagnetic interference (EMI) shielding and wave absorbing materials are developed. Mechanisms behind the EMI shielding of a material mainly includes reflection , absorption attenuation , and multiple reflection (negligible when absorption-induced shielding effectiveness (SE) is larger than 10 dB) of electromagnetic waves ,202. The2/g) in the frequency range of 8.2–12.4 GHz. A local enrichment strategy was developed to fabricate graphene/PLA nanocomposites for FDM printing by precisely manipulating the selective distribution of fillers, obtaining segregated graphene sheets in the printed object [The FDM method is widely used for the fabrication of 3D printed EMI shielding materials . The stud object . The resd object . The cord object .3O4 functionalized graphene/polymer nanocomposites achieved a high electrical conductivity of ~580 S/m and an EMI SE of over 50 dB in the X-band [3, the DIW printed and frozen dried scaffold achieved an ultrahigh normalized surface specific SE of up to 19,270 dB cm2/g.In situ reduction of GO in PDMS solutions followed by viscosity adjustment and DIW printing provided highly stretchable and conductive graphene/PDMS composite lattices, as shown in e X-band . When ine X-band . The DIWe X-band . The arce X-band . AttribuWave absorption, also known as electromagnetic wave absorption, is a process by which specific materials or structures absorb and dissipate electromagnetic energy in the form of heat. Different from EMI shielding which is about creating a barrier to prevent electromagnetic waves from entering or escaping a device, wave absorption focuses on dissipating electromagnetic energy as heat to reduce the intensity of the waves and reduce the reflection of incident radiations . Wave abThanks to the flexibility and effectiveness of 3D printing in structural design, multilayer rGO/PLA absorbers were designed with a gradient index of characteristic impedance by adjusting the rGO content and the geometric parameters of the unit cell, with the seven-layer material giving an absorption above 90% in a broad bandwidth of 4.5–40 GHz . A funct0.35Zn0.3Fe2.35O4/PMMA as the matching layer and CIG/PMMA as the absorption layer via multi-material DLP, achieving a minimum reflection loss of −46.1 dB at 4.7 GHz and an effective absorption bandwidth of 3.5 GHz (4.15–5.35 and 14.7–17.0 GHz) [2-graphene/PLA double-layer absorber with effectively improved impedance matching using FDM technology [There are many other explorations of 3D printing in wave absorption. For example, the DLP printed CIG/poly (methyl methacrylate) (PMMA) nanocomposites with various compositions presented a minimum reflection loss of −54.4 dB at a thickness of 2.1 mm, along with effective absorption bandwidth of 3.41 GHz . Zuo et 7.0 GHz) . The bal7.0 GHz) . Ye et achnology . A minimco-glycolide were also demonstrated to be able to support human mesenchymal stem cell adhesion, viability, proliferation, and neurogenic differentiation with significant upregulation of glial and neuronal genes [The biocompatible graphene is capable of supporting stem cell growth and osteogenic differentiation as well as adsorbing dexamethasone and β-glycerolphosphate (osteogenic inducers) via π–π stacking, making it beneficial bone tissue engineering . Additival genes . Scaffolal genes . These sS. aureus on the surface of scaffold under direct current [The 3D printed graphene/polymer scaffold are also found to be promising in antibacterial applications. A polymer scaffold that was reinforced with silver nanoparticle decorated GO sheets realized sustained release of Ag ions from the scaffold, demonstrating an antibacterial performance  . The GO  current .Graphene/polymer composite with well-defined structures fabricated by 3D printing have also been explored for many other bio-applications. For example, 3D printed graphene/PMMA composites with customized shape and good antimicrobial, stiffness and strength properties were proposed to be suitable for dental repair . An autoIn this review, we provide an overview of recent advances in 3D printed graphene and graphene/polymer composites. The commonly applied additive manufacturing techniques, including extrusion-based methods (DIW and FDM), photopolymerization strategies (SLS and DLP), and the powder-based technique (SLS), for graphene and its polymer-based composites are comprehensively reviewed. The unique combination of graphene’s exceptional properties and the design flexibility of 3D printing opens up exciting opportunities for the development of advanced materials with a wide range of functionalities. The ability to tailor the structural characteristics and properties of the 3D printed architectures enables the creation of custom-designed components for various fields, including energy storage, sensor, stretchable conductor, EMI shielding and bio-applications. Even though 3D printed graphene and graphene/polymer composites have been demonstrated to be promising in multifunctional applications, there still are important issues as follows to be addressed to unlock their full potential.Owing to the layer-by-layer deposition fabrication process, the interlayer strength of 3D printed materials remains a critical aspect affecting their mechanical integrity and overall performance. Inadequate interlayer adhesion can lead to delamination, reduced strength, and compromised functionality, limiting the practical application of 3D printed graphene composites. More attentions on enhancing the interfacial strength of 3D printed objects are essential. Several strategies can be employed to enhance interlayer adhesion. First, optimizing print parameters, including temperature, layer height, and printing speed, is essential to achieve uniform and strong interlayer bonding. Ensuring consistent printing conditions reduces the risk of weak interfaces and delamination. Second, surface modification of graphene or polymer materials can improve their compatibility, promoting better interfacial bonding between adjacent layers. Third, the incorporation of interlayer bonding agents or adhesion promoters during the printing process can strengthen interlayer connections and enhance the overall adhesion. Additionally, post-processing techniques, such as annealing or surface treatments, are also promise in promoting interlayer bonding and improving the mechanical properties of 3D printed composites. A comprehensive understanding of the factors influencing interlayer strength and the implementation of these strategies will advance the field of 3D printed graphene composites.As for 3D printed graphene-based materials, the diversity in materials, structures and functionalities is not fully explored yet. The 3D printing technique, with its ability to integrate multifunctional materials and complex structures seamlessly, can enable the creation of all-in-one customized devices with unprecedented capabilities. By incorporating different types functional materials, microscopic and macroscopic structures, the 3D printed composites can be endowed with integrated functionalities, meeting several or all specific requirements in a particular application. For example, with rational design of the material and structure, multifunctional sensors capable of detection and discrimination of different physical stimuli  are possibly be integrated by 3D printing techniques. The integration and de-coupling of multifunctional materials provides opportunities for graphene-based materials to be applied in complex situations.In the realm of 3D printed graphene and graphene/polymer composites, the advantages stemming from the flexibility in structural and material design have only scratched the surface of their true potential. While researchers have made significant strides in leveraging this unique capability, there are vast unexplored opportunities awaiting discovery. The ability to tailor the structural characteristics and properties of these composites provides unmatched versatility, allowing the creation of custom-designed components for a wide range of applications. However, the full extent of this design freedom remains untapped. As 3D printing technologies evolve and our understanding of graphene’s behavior improves, we can expect groundbreaking advancements in the field. By exploring innovative material combinations, advanced additive manufacturing techniques, and optimized print parameters, we will witness the emergence of novel multifunctional materials with exceptional mechanical, electrical, thermal, and even biological properties.


Idiopathic pulmonary fibrosis (IPF) is a lung disease that is both chronic and progressive and is characterized by glycolysis. However, glycolysis’s function and its clinical significance in IPF are still not well understood.We accessed the Gene Expression Omnibus database to retrieve mRNA expression information for lung tissue and other samples. We identified genes associated with glycolysis that had differential expression levels between IPF and controls. In this work, we conducted a comprehensive bioinformatic analysis to systematically examine the glycolysis-associated genes with differential expression and subsequently investigated the possible prognostic significance of these genes. Additionally, the expression profiles of the associated prognostic genes were further investigated via quantitative real-time polymerase chain reaction in our cohort. In this investigation, we found that the expression of 16 genes involved in glycolysis was differentially expressed. Among them, 12 were upregulated and 4 were downregulated. We found that 3 glycolysis-related genes  might serve as hub genes for anticipating patient prognosis. The data from these genes were used to generate the prognostic models. The findings confirmed that high-risk IPF patients recorded a shorter overall survival relative to low-risk patients. This prognostic model yielded 1-, 2-, and 3-year survival rates of 0.666, 0.651, and 0.717, correspondingly, based on the area under the curve of the survival-dependent receiver operating characteristic. The GSE27957 and GSE70866 cohorts validated these findings, indicating the model has a good predictive performance. All 3 glycolysis-associated genes were validated to be expressed in our cohort. Finally, we used mRNA levels from 3 genes to produce a nomogram to quantitatively predict the prognosis of IPF individuals. As possible indicators for the prognosis of IPF, the glycolysis-related genes stanniocalcin 2, transketolase like 1, and artemin were shown to be promising candidate markers. The incidence of IPF is low in young people and more common in the elderly. The median survival duration following diagnosis ranges between 2 and 4 years.,3 Due to the development and use of antifibrotic drugs (pirfenidone or nintedanib) in recent years, the prognosis of IPF individuals has improved to some degree. However, IPF is still incurable, in part because its etiology is complex and the mechanism is unclear. Therefore, further comprehension of the molecular basis that underlies IPF is crucial for improving the prognosis, early screening, and diagnosis of IPF patients.Idiopathic pulmonary fibrosis (IPF) has been recognized as a chronic, irreversible, progressive interstitial lung disorder with undetermined etiology and poor clinical prognosis.,7 Fibrosis may develop as a consequence of lung macrophage activation and subsequent inflammation, which might in turn induce a proteolytic phenotype in macrophages and reduce lung elastin levels. Active macrophages rely heavily on glycolysis and high lactate generation to swiftly supply the energy needed to sustain the inflammatory response. Aerobic glycolysis is commonly referred to as the Warburg effect where cells can still carry out glycolysis under the condition of sufficient oxygen, convert glucose into pyruvate, and process it into lactic acid, consequently promoting cell growth and proliferation. Researchers have indicated that in pulmonary fibrosis, aerobic glycolysis is considerably enhanced. It has been shown that inhibiting aerobic glycolysis may alleviate bleomycin-mediated lung fibrosis and reduce the rate of TGF-β-induced collagen formation.,11 The results of Xie et al’s study also showed that lung fibroblasts had enhanced glycolysis and upregulation of glycolysis enzymes in myofibroblasts that have been differentiated in vitro by TGF-β. The findings of Kottmann’s research indicated the presence of lactic acid accumulation in patients with IPF. The above research data suggest that the process of aerobic glycolysis of lung tissue might cause fibrosis by activating TGF- β and other fibrogenic factors through the survival and accumulation of lactic acid. Up to now, the pathogenicity of glycolysis in IPF is still worthy of further study. A better comprehension of the role glycolysis performs in the IPF has led to the accumulation of more data supporting the treatment of patients with the disease. The results of the investigation by Yin et al indicated that when bleomycin-mediated pulmonary fibrosis mice were treated with HK2 inhibitors, the expression of fibrogenic genes was reduced and lung function remained stable. Pulmonary fibrosis is associated with glycolysis, however, the specific molecular mechanisms that underly glycolysis in the lungs are not well characterized. Therefore, the study on the systematic function of glycolysis-associated genes in IPF is warranted to elucidate the function of glucose metabolism in IPF and find novel targets for IPF treatment.Pulmonary fibrosis is also a metabolic-related disease, and the changes in glucose metabolism perform an integral function in the formation of pulmonary fibrosis.This research aimed to examine the functions of glycolysis in IPF and assess the prospective clinical value of differentially expressed glycolysis-associated genes for prognostic stratifications. In particular, the Gene Expression Omnibus (GEO) database was searched for data on mRNA expression and clinicopathological characteristics. We conducted bioinformatics analysis to identify genes involved in glycolysis with differential expression between individuals with IPF and healthy controls and extensively analyzed the possible biochemical processes and functions of these genes. Lastly, we combined glycolysis-related gene expression data with clinical data to examine the possible influence of these genes on prognosis.http://www.broad.mit.edu/gsea/msigdb/) is a repository of annotated gene sets for Gene Set Enrichment Analysis. Four glycolysis-associated gene sets were extracted, containing KEGG GLYCOLYSIS GLUCONEOGENESIS, BIOCARTA GLYCOLYSIS PATHWAY, HALLMARK GLYCOLYSIS, and REACTOME GLYCOLYSIS . An aggregate of 255 glycolysis-associated genes was retrieved from MSigDB, which offers gene annotations in great depth. We retrieved the Next Generation Sequencing data of 103 IPF and 103 control lung tissues with corresponding clinical data from GSE 150910. Information on patients in the GSE150910 dataset is displayed in Table https://bioconductor.org/packages/limma/) was utilized to execute the negative binomial distribution technique with the absolute value of log2(fold change) > 1.0 and false discovery rate < 0.05 to find differentially expressed glycolysis-associated genes between IPF and control lung tissues. The most common recursive feature-removal algorithm, support vector machine-recursive feature elimination (SVM-RFE), was utilized to choose the features for removal. The differentially expressed genes were used to complete SVM-RFE analysis, which could be used to screen the optimal feature genes in the GSE150910 dataset.The molecular signature dataset  for anticipating the PPI network. In the meantime, the R software  was employed to visualize the PPI network.The glycolysis-associated genes showing differential expression were imported into the Search Tool for the Retrieval of Interacting Genes .where β signifies the coefficient value and Exp indicates the levels of gene expression. Subsequently, the median approximated risk scores were applied to classify IPF patients into low- and high-risk groups (categories). The “prcomp” function included in the “stats” R package was applied to conduct the principal component analysis of the 3-gene signature. Next, the log-rank test was conducted to contrast the prognostic results of the 2 cohorts. We investigated the predictive power of the aforementioned model via receiver operating characteristic (ROC) analysis utilizing the SurvivalROC R package ( and GSE70866(176 IPF patient samples with matching prognosis) datasets were employed to verify the estimated findings and assess the model’s prognostic performance. The information on the genechip is shown in Table The GSE27957(45 IPF patient samples with matching prognosis)Ethical approval was obtained from the ethics committee of the First Affiliated Hospital of Chengdu Medical College (IRB ID:2021CYFYIRB-BA-32–01). Each subject signed the informed consent. The TRIzol reagent  was used for the extraction of total RNA from PBMCs. After the determination of total RNA purity and concentration, reverse transcription of the total RNA into cDNA was done utilizing the PrimeScript RT reagent kit . SYBR Green Premix Ex Taq II was utilized to execute the qRT-PCR. The PCR parameters were as illustrated below: 95°C for 30 seconds, ensued by 40 cycles of 95°C for 5 seconds, and 60°C for 30 seconds for each particular primer. Lastly, the 2−△△Ct method was applied to derive the relative mRNA expression profiles of the 3 genes. Table P values < .05 denoted the significance criterion.We likewise utilized real-time PCR to verify the expression of the 3 prognostic genes in the research cohort. Beginning July 2021 to September 2022, we acquired 15 peripheral blood mononuclear cells (PBMCs) from IPF patients and 15 PBMCs from healthy individuals at the First Affiliated Hospital of Chengdu Medical College in Sichuan, China. The eligible subjects for this research included adult patients clinically diagnosed with IPF as per the European Respiratory Society guidelines/American Thoracic Society/(2011).To elucidate a quantitative method to predict an IPF patient’s probability of glycolysis-related genes, we constructed a nomogram based on the “rms” R program.Genes involved in glycolysis were systematically analyzed to determine their potential predictive performance and key roles in IPF. The investigation was carried out exactly as planned, as illustrated in Figure To find glycolysis-associated genes that have a significant link to overall survival (OS), a univariate analysis that was based on hub glycolysis-related genes was conducted. As per the hazard ratio forest map, there was a strong link between the expression of 8 glycolysis-associated genes and the IPF patients’ prognoses Fig. A. The 8 The glycolysis-related prediction model was built using the 3-hub glycolysis-associated genes discovered in the preceding analysis. Each IPF patient’s risk score was determined as illustrated below:Risk score = (−0.561*ExpSTC2) + (−0.247*ExpTKTL1) + (0.177*ExpARTN).Subsequently, we performed a survival analysis to evaluate how well this model predicted patient outcomes. By using the median of their risk scores, 75 individuals with IPF were categorized into high- or low-risk categories. The principal component analysis illustrated that patients exposed to varying risks were grouped into 2 cohorts . These findings suggested that this predictive model predicated on glycolysis-related genes exhibited good specificity and sensitivity. Additionally, we validated the expression of the 3 key genes in the study sample. As projected, STC2 and TKTL1 were significantly decreased in IPF patients, while ARTN was increased  in mammals exhibit a widespread expression in various tissues.,30 On the human chromosome, the STC2 gene is found at position 5q35.1. In both humans and mice, STC2 is made up of 4 exons that span 13kb of DNA. Upregulation of STC2 in N2a mice neuroblastoma cell lines after being subjected to thapsigargin- and tunicamycin-stimulated estrogen receptor stress was the first piece of evidence for STC2’s cytoprotective role, presented by Thinakaran et al. An upregulation of STC2 was also observed following hypoxia and oxidative stress mediated by H2O2. When STC2 was overexpressed, it protected cells against thapsigargin-stimulated cell death in both HeLa and N2a cell lines. Kim et al demonstrated that the overexpression of STC2 triggered the pERK1/2 and pAKT signaling pathways, protecting cells from oxidative stress-triggered cell injury. In our study, bioinformatics analysis and qRT-PCR results suggested that STC2 was lowly expressed in IPF. Cox univariate regression analysis showed that the hazard ratio value of STC2 was 0.570, suggesting that STC2 was a protective factor. We hypothesized that after STC2 expression was reduced, the protective effect on alveolar epithelial cells was lost, and alveolar epithelial cells were over-repaired after repeated injury and converted to fibroblasts, which finally led to the formation of pulmonary fibrosis. It is still worthwhile to investigate STC2’s function in pulmonary fibrosis.STC, which is a hormone containing a glycosylated peptide, initially identified in a bony fish was previously demonstrated as having an integral function in phosphate and calcium homeostasis. In the pentose phosphate pathway, TKTL1 is a rate-limiting enzyme that is abundantly expressed in epithelial-derived normal and tumor cells. Consequently, TKTL1 performs an integral function in the survival, growth, proliferation, migration, and differentiation of cells, and participates in the incidence and advancement of numerous human illnesses.–37 At present, extensive research points to a strong association between TKTL1 and malignant growth. Although TKTL1 is overexpressed in non-small cell lung cancer, it is unrelated to patient outcomes in terms of OS, disease-free survival, or tumor node metastasis stages. In this study, TKTL1 is a protective factor in IPF. Verified by qRT-PCR, TKTL1 is lowly expressed in PMBCs of IPF patients. There is currently no investigation conducted on the link between TKTL1 and IPF. Whether TKTL1 participates in the formation and development of IPF is worthy of further study.TKTL1 is one of the 3 members of the human TKT gene family . Ceyhan et al showed that in chronic pancreatitis, GFRalpha3 and ARTN exhibited a substantial overexpression and were sited in neural ganglia, Schwann cells, and smooth muscle cells of arteries. Also, the elevated ARTN mRNA levels were found to correlate with hypertrophy, neural density, perineural inflammatory cell infiltration, inflammation, and pain severity. In addition, both ARTN expression and neural alteration exhibited a positive link to the severity of fibrosis. Pancreatic fibrosis and pulmonary fibrosis have some similarities in pathological features and mechanisms, which are caused by repeated damage of epithelial cells, leading to the formation of scars in tissue. The results of bioinformatics analysis in this research illustrated that ARTN was increasingly expressed in IPF tissues, and ARTN had a negative correlation with the prognosis of IPF. Combined with the previous literature, we speculate that ARTN might be implicated in the inflammatory cell infiltration in pulmonary fibrosis and promote the formation of IPF. Song et al illustrated that ARTN may enhance lung cancer cell migration and invasion, which might be related to hypoxia-induced ARTN-promoting epithelial-mesenchymal transition (EMT) through AKT signaling. In addition to being related to tumor invasion and metastasis, EMT is also involved in typical wound healing and performs a function in the excessive repair of tissues in IPF.,43 Therefore, we believe that ARTN might be implicated in the EMT process of IPF. This research verified the high expression of ARTN in PBMCs of IPF patients by qRT-PCR, but further research is needed to improve the mechanism.ARTN is a well-recognized affiliate of the glial cell line-derived neurotrophic factor ligand family . Its signal transduction mainly regulates intracellular signal transduction by combining with the co-receptor GFR α 3-RET to regulate intracellular signal transduction, thus affecting neural system development and cell homeostasis. also developed a nomogram using the 3 inflammation-associated genes in IPF. We employ several bioinformatics analytic approaches that are similar to some of the procedures used by Lu et al.Following that, a risk model for predicting IPF prognosis was developed utilizing multiple stepwise Cox regression analyses of 3 glycolysis-related genes, which was then validated using the GSE27957 and GSE70866 cohorts. The ROC curve analysis illustrated that the 3 glycolysis-related genes signature was fitted for forecasting dismal prognosis in IPF patients. Furthermore, the 1, 2, and 3-year OS rates were intuitively predicted using a nomogram. This predictive model centered on these 3 glycolysis-related genes is both monetarily cost-effective and clinically advantageous. Lu et alThis prediction method, however, was discovered to have some limitations. Firstly, the model was built using the GEO dataset; thus, it needed to be validated in a clinical patient population. Also, the number of patients included in our study was small. Further expansion of the sample size is required to validate this model in the future. Secondly, because this was retrospective research, more prospective studies are required to confirm the findings. Lastly, functional studies are required to additionally uncover the possible mechanism of glycolysis-related genes that might be important in IPF.Ultimately, following a thorough bioinformatics analysis of the GEO database, our investigation discovered 3 IPF prognostic glycolysis-related genes. The findings provided new insights into the functions performed by glycolysis in IPF pathogenesis, perhaps paving the way for the creation of prognostic indicators.Conceptualization: Yu Li, Yaju Deng, Jie He.Data curation: Yu Li, Jie He.Formal analysis: Yaju Deng, Jie He.Investigation: Jie He.Methodology: Jie He.Project administration: Yaju Deng, Jie He.Resources: Yu Li, Yaju Deng, Jie He.Software: Yu Li, Jie He.Supervision: Jie He.Validation: Yu Li, Jie He.Writing – original draft: Yu Li, Yaju Deng.Writing – review & editing: Yu Li, Yaju Deng.


A detailed theoretical analysis of the Fourier transform of quasiparticle interference images reveals that the induced SOC consists of a valley-Zeeman (λvZ ≈ 2 meV) and a Rashba (λR ≈ 15 meV) term, one order of magnitude larger than what theory predicts, but in excellent agreement with earlier transport experiments. The validity of our analysis is confirmed by measurements on a 30 degree twist angle heterostructure that exhibits no backscattering, as expected from symmetry considerations. Our results demonstrate a viable strategy to determine SOC quantitatively by imaging quasiparticle interference.Inducing and controlling spin-orbit coupling (SOC) in graphene is key to create topological states of matter, and for the realization of spintronic devices. Placing graphene onto a transition metal dichalcogenide is currently the most successful strategy to achieve this goal, but there is no consensus as to the nature and the magnitude of the induced SOC. Here, we show that the presence of backscattering in graphene-on-WSe Graphene has many intriguing electronic properties. One of note is the absence of backscattering of electrons confined to a single valley. Spin-orbit interactions can allow backscattering, and here, Sun et al. use this spin-orbit coupling dependence of backscattering to measure the strength of the spin-orbit interaction in a graphene/tungsten selenide heterostructure. Key in this context is the notion of backscattering—the ability of electrons to precisely reverse their direction of propagation as a result of elastic collisions—because how electrons backscatter is deeply related to the structure of the electronic wavefunctions and to the symmetries present in the system3. For electrons described by scalar wavefunctions in conventional metals, for instance, time reversal symmetry causes constructive interference that enhances backscattering and suppresses conductivity, resulting in the well-known phenomenon of weak-localization4. In the presence of SOC—for which the spinorial structure of wavefunctions needs to be considered—time reversal symmetry instead results in destructive interference that suppresses (rather than enhancing) backscattering, leading to weak antilocalization3.Phase coherent propagation of electrons in solids is a basic quantum mechanical process that determines the low-temperature transport properties of metallic conductors8. The difference is rooted in the two-component, pseudo-spinorial wavefunction of Dirac electrons, which originates from the two inequivalent atoms forming the graphene unit cell10. The Hamiltonian of pseudo-spinorial Dirac fermions in graphene possesses an additional symmetry—so-called chiral symmetry9—which ensures that electrons with opposite momenta have orthogonal pseudospins  measurements, and succeed in relating our observation to the properties of SOC. Images acquired on heterostructures with different twist angles between the SLG and WSe2 lattices give fully consistent results as to the type and magnitude of the SOC imprinted by the WSe2 layer onto SLG. We find that both Rashba and valley-Zeeman (vZ) terms are present, with a magnitude varying between 7 and 16 meV for the Rashba contribution, and between 1 and 3 meV for the vZ. These values are in perfect agreement with the results of earlier magnetotransport studies15, and establish that the strength of the Rashba term is one order of magnitude larger than that predicted by existing ab initio calculations19. We further find that no quasiparticle interference is observed for SLG-on-WSe2 when the twist angle is 30°, in agreement with theoretical expectations20, because for this angle the strength of the vZ coupling vanishes by symmetry and backscattering is only present when both vZ and Rashba are non-zero. Besides settling pending issues about the type and strength of SOC in SLG-on-TMD, our work demonstrates a conceptually new approach to probe spin-orbit coupling quantitatively in 2D materials.Here, we establish the occurrence of backscattering of Dirac electrons in single-layer graphene (SLG)-on-WSe21, the ability to controllably generate SOC artificially, while preserving the basic electronic properties of Dirac electrons, is of interest in different contexts24. A route towards this goal consists in imprinting SOC by placing graphene on semiconducting TMD substrates such as WSe2, which combine a very large SOC strength 26 with a large band gap around the graphene Fermi level. A variety of transport experiments34 exhibiting unambiguous signatures of a strong SOC in graphene show that this route is successful. However, most experiments detect SOC exclusively through a fast spin relaxation33, much faster than that expected in pristine graphene. This unfortunately provides only limited information, since a fast spin relaxation can be understood in terms of spatially random spin-dependent scattering, and does not require that the SOC imprinted by the TMD substrate corresponds to a modification of the graphene band structure. Therefore, most reported studies which analyse fast spin relaxation times, neither give conclusive evidence for the presence of spin-splitting in the dispersion relation of Dirac electrons, nor do they give unambiguous indications as to the type of SOC imprinted in graphene. Only a few experiments indicate that the SOC imprinted by the TMD substrate onto graphene does induce a modification to the band structure15, and attribute the resulting spin-splitting near the Dirac point to two distinct SOC terms. These are a Rashba term (which wants the electron spin to point in the graphene plane) and a valley-Zeeman term (which forces the electron spin to point in the direction perpendicular to the graphene plane). The experiments consistently suggest a strength of the Rashba and vZ terms of ≈15 meV and ≈2 meV, respectively (for graphene on WS2). When compared to ab initio calculations19, these results are only partially in agreement: whereas the observed strength of the vZ term indeed corresponds to the expected one, no calculation has so far found a Rashba term as strong as the one extracted from the experimental data. Whether this deviation originates from the assumptions in the theoretical modeling or from problems with the interpretation of the experiments remains to be established. At this stage, it is crucial to push experiments further, by pursuing alternative strategies to probe SOC in graphene on TMDs, capable of providing quantitative information on the strength of the different SOC terms.Given the very weak (≈50 μeV) SOC naturally present in graphene36. The Fourier transform (FT) of QPI images gives a finite signal at qB in the QPI thus serves as a direct measure of the existence of backscattering.In the presence of elastic scattering, the wave of an incoming electron with momentum mentclass2pt{minimmentclass2pt{minimmentclass2pt{minimmentclass2pt{minimmentclass2pt{minim2 stacked with selected twist angles between 1° and 30°  and the Dirac point, whose shallow depression near −197 mV is consistent with previous studies37. Detecting backscattering by QPI relies on large area high resolution 2 lattice peaks, the corresponding moiré peaks, and their linear combinations. The six ring patterns near the K and K’ points correspond to intervalley scattering sketched in Fig. 39.We measured the QPI images on different heterostructures consisting of mechanically exfoliated SLG and few-layer WSeintravalley scattering contributions around the Γ-point, which are illustrated in full detail in Fig. k = 0. Such a behavior has been observed earlier in bilayer graphene40—where it has been shown to be due to backscattering—but is not expected to occur in pristine SLG, since backscattering is in principle forbidden39. The observed feature is clearly reminiscent of the manifestation of intravalley backscattering introduced in Fig. Figure qB of the ring at which intravalley scattering peaks, decreases with reducing energy from 30 meV to −20 meV. We quantify the precise dependence of qB on energy by analyzing angle-averaged line cuts  of Dirac electrons (as demonstrated by the linear dispersion relation with the correct Fermi velocity). We conclude that in contrast to pristine SLG, where no backscattering is observed, backscattering of Dirac electrons is present in SLG-on-WSe2.The evolution of the ring around the Γ-point with electron energy Fig. a as well2, we proceed with a fully detailed theoretical analysis of the data. To model this, we add to the usual single-valley Dirac Hamiltonian the Rashba term HR = λR(τzσxsy − σysx) and the vZ term HvZ = λvZτzsz, where σ refers to the sublattice pseudospin, τ to the K/s to the physical spin. HvZ acts like a valley-dependent magnetic field, splitting spin up and down in different directions in the K and 2. By symmetry, λvZ must vanish in the heterostructure with a 30° twist angle between graphene and the WSe2 layer19, which has important experimental consequences (see below). The Rashba term couples spin and pseudospin, leading to spin split bands with opposite pseudospin and spin windings. When both vZ and Rashba are present, the pseudospin vectors are mixed with the spin degree of freedom, and these spin/pseudospin vectors are no longer opposite for opposite momenta, so that nothing prevents backscattering. Importantly—since both the vZ and Rashba coupling s have to be non-zero for the argument to hold—backscattering is expected to disappear for a 30° twist angle between SLG and WSe2, when symmetry imposes that λvZ = 0.Having established the presence of intravalley backscattering of Dirac electrons in SLG-on-WSe2 with SOC, in the limit of small disorder. We have also modelled the effect of a mass gap, by adding to the Hamiltonian a spin-independent term of the type HΔ = mσz, because such a term can also induce backscattering in SLG. However, in contrast to SOC, whose presence for SLG-on-TMD is established, there is no earlier experimental indication that a sizable mass gap is present in these heterostructures: a sizable mass gap should lead to an insulating behavior at low-temperature, which has never been reported in transport experiments .Using the model Hamiltonian with the vZ and Rashba terms, we have calculated the theoretical QPI patterns . For the vZ term, the strength is approximately constant upon varying twist angle . The result of the experiments is shown in Fig. 2 and validates our conclusions as to the strength of the vZ and of the Rashba terms.These results demonstrate that the analysis of QPI images in SLG-on-WSegle Fig. c; for thgle Fig. d. The er2 this technique allows a full characterization of the SOC terms present, which is key to establish a firm experimental understanding of the spin-orbit coupling imprinted in graphene by proximity effect. We anticipate that the analysis of similar QPI imaging measurements on other material systems, in conjunction with detailed theoretical modeling, will also enable to obtain detailed information about spin-orbit coupling.Determining what type of SOC is present in the band structure of an electronic system and estimating the magnitude quantitatively are notoriously complex issues. On 2D materials, only a few techniques have been employed so far to extract this information, all based on the study of low-temperature magnetotransport as a function of gate voltage in devices with sufficient high mobility. The use of scanning tunneling spectroscopy to perform quasiparticle interference imaging to achieve this same goal demonstrates a strategy that had not been pursued earlier. It relies on a specific phenomenon—in the present case, whether backscattering occurs or not—that can be probed by careful STM measurements and modeled in detail theoretically. As we have shown here, on SLG-on-WSe44. An exfoliated single-layer graphene and a few-layer thin WSe2 crystal were picked up with a defined twist angle by a propylene carbonate (PC) film coated on polydimethylsiloxane (PDMS) stamps. This stack was subsequently released on a 90 nm SiO2/Si substrate  at 4.5 Kelvin using an electrochemically etched tungsten tip. The tips were further conditioned in situ on Au(111). The bias voltage is applied to the sample, with 0 V corresponding to the Fermi level. To acquire reproducible high-resolution scanning tunneling microscope (STM) images and 13. Second, the devices were annealed at 350 °C for 180 min in a H2/Ar atmosphere before transferring them into the STM chamber. Third, the devices were annealed once more at 350 °C for an hour in ultra-high vacuum. Topographic STM images were acquired in constant-current mode. The Vrms = 2 mV at a frequency f = 429 Hz. The All STM data were acquired in ultra-high vacuum (base pressure < 10Supplementary InformationPeer Review File