We demonstrate that the conductivity of graphene on thin-film polymer substrates can be accurately determined by reflection-mode air-plasma-based THz time-domain spectroscopy (THz-TDS). The phase uncertainty issue associated with reflection measurements is discussed, and our implementation is validated by convincing agreement with graphene electrical properties extracted from more conventional transmission-mode measurements. Both the reflection and transmission THz-TDS measurements reveal strong non-linear and instantaneous conductivity depletion across an ultra-broad bandwidth (1–9 THz) under relatively high incident THz electrical field strengths (up to 1050 kV/cm). Graphene holds high promise as a key base material for next-generation electronics. In recent years, the development in graphene growth and transfer has been on the fast track, as exciting progresses such as chemical vapor deposition (CVD), graphene growth, and scalable roll-to-roll techniques have been achieved and are maturing ,2,3. ForTo date, most of the THz-TDS characterizations of graphene have been carried out in transmission mode (T-mode). For T-mode measurements, THz waves transmitted through graphene and its substrate are acquired. Various substrate materials have been applied, such as high-resistivity silicon (Si) ,6,7,8, qFurthermore, due to its Dirac-type electronic band structure, graphene is a very non-linear material under the electrical field of THz radiation. Strong THz-induced transparency of CVD-grown graphene was reported with time-resolved THz pump/THz probe studies , as wellIn this report, we will show that the conductivity of graphene/thin-film polymer samples can be accurately measured with a reflection-mode air-plasma-based THz-TDS setup. The removal of the phase uncertainty associated with reflection-mode spectroscopy will be discussed. We will show that the ultra-broad spectral bandwidth can greatly improve the accuracy of such analysis and thus significantly suppresses the uncertainty often seen in standard reflection-mode measurements. The extracted graphene electrical properties are validated by transmission-mode measurements from the same sample. Both T-mode and R-mode measurements show strong non-linear and instantaneous conductivity depletion of graphene under relatively high incident THz electrical field strengths, representing the first non-linear graphene conductivity investigation with an ultra-broadband air-plasma-based THz source.N is the number of wafers inserted in the beam. With zero attenuation wafers, the THz pulse energy was 0.51 µJ at the sample location, and the calculated peak THz electrical field strength was 1050 kV/cm, based on measurement of the beam profile and the time trace detected by ABCD [The air-plasma-based THz-TDS setup is shown in  by ABCD . The inc2). The results are shown in 2 sample  film with a thickness of 230 µm. The PET film was partially covered by graphene, and the bare film surface served as a reference for the THz-TDS measurements. Prior to THz measurements, Raman spectroscopy was employed to check the quality of the graphene sample. Due to the fact that organic PET substrates tend to heavily pollute the Raman signal from graphene, Raman characterizations were performed after transferring the graphene onto a high-resistivity silicon substrate with a 90 nm thin oxidized surface layer (SiOinset in b. The blThe measured THz waveform and spectrum without insertion of samples (air transmission) are shown as the red curves in In order to benchmark the reflection-mode characterization, the sheet conductivity of the graphene/thin-film PET sample was first characterized with standard transmission-mode THz-TDS. The transmitted THz waveforms through the bare PET substrate and through the graphene-covered substrate were sequentially obtained for the extraction of the graphene electrical properties as functions of the frequency Transmission-mode measurements at the low THz field , the strong non-linear response observed in this investigation indicates that the graphene electronic state can be non-linearly modulated by a strong transient electrical field in a time scale as short as few 10 s of femtoseconds.The extracted conductance spectra can be well fitted with the Drude model, shown in f, howeveigations ,19, the c is the speed of light. Since the actual physical phase shift due to the graphene-THz response is rather small, a tiny amount of Reflection geometry THz-TDS offers unique advantages in many spectroscopic application scenarios. However, there is one major obstacle that is commonly associated with reflection-mode THz spectroscopy: the phase difference uncertainty between the reference and sample waveform measurements due to small but in practice unavoidable errors in positioning of the sample reflection plane with respect to the reference reflection plane. Similar to T-mode THz spectroscopy, the reflection function To tackle the phase offset uncertainty issues, a great deal of effort has been made in the THz spectroscopy community. For instance, Pashkin et al. designed a special THz reflection spectrometer where the optical probe and THz beams maintain the same beam path lengths and thus introduce minimal phase shift uncertainty . Window When translating between the bare substrate surface and the graphene-covered surface on the large-size CVD graphene/thin-film PET samples, the artificial time delays, The red curve (Ref) in By implementing the above-mentioned phase correction procedure, graphene properties can be extracted from the R-mode THz-TDS measurements. We show the results in It is evident that, compared to the T-mode, the same graphene film leads to a much larger Ref-Sam contrast in the reflection-mode measurements. In the 1050 kV/cm case when the graphene conductivity is significantly suppressed, the R-mode measurements still have a reference-sample contrast of a maximum of 28%, whereas it is only 7% from the T-mode measurements. It is reasonable to assume that the much larger signal contrast in the R-mode would lead to a more convincing extraction.It is worth noting that the observed peak THz field strength for the onset of non-linear graphene conductivity responses in this study (approximately 60 kV/cm) is higher than what was reported in previous studies . This iTo summarize, we report on the first sheet conductivity measurements of graphene on thin-film polymer samples with reflection-mode THz time-domain spectroscopy. The correction of the phase uncertainty associated with reflection-mode spectroscopy is discussed, and it is shown that the ultra-broad bandwidth available from the air-plasma-based THz-TDS significantly improves the accuracy of phase correction and enables the quantitative extraction of the DC conductance and electron scattering time of graphene. The extracted graphene electrical properties are directly compared with transmission-mode measurements from the same sample. Both the T-mode and R-mode measurements show strong non-linear conductivity suppression of graphene under high incident THz electrical field strengths, which represents the first non-linear graphene conductivity investigation with an ultra-broadband air-plasma-based THz source. Due to the much faster time scale involved, the reported graphene non-linear conductivity response is different from the thermodynamic non-linearity observed under the excitation of sub-ps THz pulses.


The United States Medical Licensing Examination (USMLE) has been a subject of performance study for artificial intelligence (AI) models. However, their performance on questions involving USMLE soft skills remains unexplored. This study aimed to evaluate ChatGPT and GPT-4 on USMLE questions involving communication skills, ethics, empathy, and professionalism. We used 80 USMLE-style questions involving soft skills, taken from the USMLE website and the AMBOSS question bank. A follow-up query was used to assess the models’ consistency. The performance of the AI models was compared to that of previous AMBOSS users. GPT-4 outperformed ChatGPT, correctly answering 90% compared to ChatGPT’s 62.5%. GPT-4 showed more confidence, not revising any responses, while ChatGPT modified its original answers 82.5% of the time. The performance of GPT-4 was higher than that of AMBOSS's past users. Both AI models, notably GPT-4, showed capacity for empathy, indicating AI's potential to meet the complex interpersonal, ethical, and professional demands intrinsic to the practice of medicine. LLMs have proven proficient in diverse tasks, but their performance in areas requiring empathy and human judgment remains relatively unexplored.Artificial intelligence (AI) is revolutionizing patient care and medical research. AI algorithms are being rapidly introduced and integrated into medical practice, enhancing human capacity and efficiency. Large language models (LLMs), specifically ChatGPT and GPT-4, have gained large scientific attention, with an increasing number of publications evaluating these models’ performance in medicine7. These ‘soft skills’ are critical to the effective and empathetic practice of medicine, enabling physicians to resonate with their patients and contribute positively to the healthcare system. Until March 2020, the Step2 Clinical Skills (CS) exam was the standard for assessing communication and interpersonal skills8. However, its suspension due to the COVID-19 pandemic underscored the need for an effective validation of these vital skills11. While the pandemic led to the discontinuation of the Step2 CS, its core elements of clinical communication are now integrated into the other Steps12, and the USMLE remains, for now, the official benchmark for assessing physicians’ communication abilities. Notably, USMLE Step2CK scores have been found to be predictive of performance across various residency performance domains, including patient care, teamwork, professionalism and communication13.The United States Medical Licensing Examination (USMLE) is a pivotal series of examinations that assess a wide range of skills indispensable for the practice of medicine. It not only measures a candidate's cognitive acuity and medical knowledge but also their ability to navigate complex interpersonal and system-based scenarios, uphold patient safety, and exercise professional legal and ethical judgmentsArtificial cognitive empathy, or AI’s ability to mimic human empathy, is an emerging area of interest. Accurate perception and response to patients’ emotional states are vital in effective healthcare delivery. Understanding AI’s capacity for this is particularly relevant in telemedicine and patient-centered care. Thus, the aim of this study was to evaluate the performance of ChatGPT and GPT-4 in responding to USMLE-style questions that test empathy, human judgment, and other soft skills.https://openai.com). As language models, they are designed to process and generate text that mirrors human-like conversation. They achieve this by predicting what next word (token) should come next given an input, allowing them to generate coherent, contextually relevant responses. ChatGPT, an earlier version, has been widely used in a variety of applications due to its ability to generate coherent and contextually relevant responses. GPT-4, a newer paid version, is similar in design but much larger in scale, meaning it has been trained on more data and can understand and generate text with even greater accuracy.In this study, we assessed the performance of the AI models ChatGPT (GPT-3.5-turbo) and GPT-4, developed by OpenAI (https://www.usmle.org/prepare-your-exam).To assess ChatGPT and GPT-4 we used a set of 80 multiple-choice questions designed to mirror the requirements of the USMLE examinations. This question set was compiled from two reputable sources. The first is a set of sample test questions for Step1, Step2CK, and Step3, released between June 2022 and March 2023, available at the official USMLE website , from which we selected an additional 59 questions. The chosen questions include Step1, Step2CK, and Step3-type questions, dealing with ethical scenarios, comparable to the questions chosen from the USMLE sample test questions. AMBOSS provides performance statistics from its past users, allowing a comparative analysis of LLMs’ performance against that of medical students and physicians.The second source is AMBOSS, a widely recognized question bank for medical practitioners and students (Both ChatGPT and GPT-4 were tasked with responding to all the 80 questions included in this study, and their responses and performance were subsequently compared.In line with standard methodological practices for assessing AI language models, we formatted a prompt structure which included the question text followed by the multiple-choice answers separated by a new line. Following the model’s response, we asked a follow-up question “Are you sure?”, which allowed us to evaluate the consistency and stability of the model and to elicit potential reevaluation of its initial response. If a model changes its answer, it may indicate that it possesses some level of 'uncertainty' about its initial response. Tracking how often and under what circumstances the model changes its answer can provide valuable insights into the model's capacity for self-revision, which is an important aspect of learning and decision-making systems. Prompt examples are shown in Supplementary items In this study, a total of 80 multiple-choice USMLE soft-skills questions were included, and the different subjects are detailed in Table Table When comparing AI performance to human performance, AMBOSS’s user statistics reported an average correct response rate of 78% by its users for the same questions we utilized in our study. ChatGPT showed lower accuracy than human users, 61%, while GPT-4 had a higher accuracy rate of 86.4%.This study evaluated ChatGPT and GPT-4 performance on USMLE multiple-choice questions assessing soft-skills such as empathy, ethics and judgment. There are several key findings. Both ChatGPT and GPT-4 answered correctly in the majority of the questions. GPT-4 outperformed ChatGPT, answering 90% of questions correctly compared to ChatGPT’s 62.5%. Additionally, GPT-4 demonstrated complete confidence in its responses, unlike ChatGPT, which displayed confidence in 17.5% of its answers.15, whereas GPT4 had an average score of 86%16. These previous studies evaluated the AI models across a spectrum of USMLE questions without specific focus on topics or distinguishing between medical knowledge-based queries and soft skill questions.Previous studies have demonstrated the ability of LLMs such as ChatGPT and GPT-4 to successfully pass the USMLE, with significantly better performance of GPT4. ChatGPT was shown to have 41–65% accuracy across Step1, Step2CK, and Step3 questionsIn our study, we focused on questions that require “human” qualities like empathy, communication, professionalism, and ethical judgment. We showed that LLMs demonstrate impressive results in these questions that test soft skills required from physicians. The superiority of GPT-4 was further confirmed in our study, with the model correctly answering 90% of the soft skill questions, in contrast to ChatGPT's accuracy of 62.5%. These results indicate that GPT-4 displays a greater capacity to effectively tackle not just medical knowledge-based questions but also those requiring a degree of empathy, ethical judgment, and professionalism.14. These are lower accuracy rates than the 61% accuracy ChatGPT demonstrated in our study. The difference may arise from the use of different questions from AMBOSS’s large database, but might also be because we focused on specific type of questions and did not include the whole span of topics covered in the USMLE.Regarding the specific question datasets used in our study, a previous study that tested the performance of ChatGPT with a subset of 200 Step1 and Step2CK questions from AMBOSS reported accuracy of 44% and 42% respectively15. In our study, ChatGPT showed similar but slightly higher results, with accuracy of 66.6%.The same study also tested ChatGPT on USMLE example test questions, out of which we selected questions for our study, and found that ChatGPT was accurate in 64.4% for Step1 and 57.8% for Step2. Another study that tested ChatGPT on the USMLE example test questions reported accuracies up to 55.8%, 59.1% and 61.3% for Step1, 2CK and 3, respectivelyBeyond question types, it's also noteworthy to address the behavioral tendencies of the two models. ChatGPT's inclination to adjust its initial responses may suggest a design emphasis on adaptability and flexibility, possibly favoring diverse interactions in conversational contexts. On the other hand, GPT-4's consistency could point to its robust training or a sampling mechanism predisposed to stability. This distinction is significant as it highlights the difference between a model's inherent adaptability for dynamic settings versus consistent output in more stable contexts.When comparing AI performance to human performance, AMBOSS's user statistics provide an invaluable benchmark. AMBOSS reported an average correct response rate of 78% by its users for the same questions we utilized in our study. ChatGPT showed lower accuracy than human users, implying a shortage of relevant soft skills compared to medical students and doctors. GPT-4 surpassed this human performance metric, suggesting its capabilities in solving complicated ethical dilemmas, demonstrating empathy, and managing patients and their families in a professional manner that physicians are required to exhibit.17.The potential of AI to display empathetic responses is a topic of increasing interest. A notable recent study compared responses from ChatGPT and physicians to patient inquiries on a social media platform and found that ChatGPT's responses were viewed as more empathetic, emphasizing AI's potential to emulate human-like empathyThere are several limitations to our study. First, the question pool used in this study was limited, including only 80 multiple-choice questions from two different sources, with potential introduction of selection bias. These may not accurately reflect the actual USMLE questions and may not encompass all aspects of 'soft skills' that are essential to medical practice. In addition, consistency levels of the two models were assessed based on an opportunity to revise their answers. However, this mechanism for potential reevaluation might not translate to human cognition understanding of ‘uncertainty’, as these models operate based on calculated probabilities for an output, rather than human-like confidence. This simplification potentially limits the depth of our understanding of the models' decision-making processes.To conclude, our findings underscore the potential role of LLMs in augmenting human capacity in healthcare, especially in areas requiring empathy and judgment. GPT-4's performance surpassed the human performance benchmark, emphasizing its potential in handling complex ethical dilemmas that involve empathy, which are critical for patient management.Future research should consider larger and more diverse question pools and ethical scenarios to better represent the full range of soft skills important to medical practice. Such studies would provide a more comprehensive understanding of LLMs' capabilities in these areas and explore the applicability of these LLMs in real-world clinical settings.Supplementary Information 1.Supplementary Information 2.


Patient characteristics, lung function, CO diffusion (DLCO), arterial blood gases, 6-min walk test, laboratory parameters and high-resolution (HR)CT pattern were assessed. In stable IPF, PGRN levels did not differ from healthy controls; however, serum PGRN levels were significantly higher in non-IPF ILD patients compared to healthy subjects and IPF . The HRCT pattern of usual interstitial pneumonia (UIP) was associated with normal PGRN level, while for non-UIP patterns, significantly elevated PGRN level was measured. Elevated serum PGRN levels may be associated with non-IPF ILD, especially non-UIP patterns and might be helpful in cases of unclear radiological patterns in the differentiation between IPF and other ILDs.Diagnosing interstitial lung disease (ILD) can be a challenging process. New biomarkers may support diagnostic decisions. Elevated serum progranulin (PGRN) levels have been reported in liver fibrosis and dermatomyositis-associated acute interstitial pneumonia. Our aim was to assess the role of PGRN in the differential diagnosis of idiopathic pulmonary fibrosis (IPF) and other ILDs. Serum levels of PGRN were measured by enzyme-linked immunosorbent assay in stable IPF ( Interstitial lung diseases (ILD) are a large heterogeneous group of lung diseases, including more than 150 entities that have many clinical and pathophysiological features in common but differ significantly in etiology, therapy and prognosis [Idiopathic pulmonary fibrosis (IPF) is the most common form of ILDs, with a progressive course and with an almost invariably poor prognosis . It mainProgranulin (PGRN) is a 593 amino acids long, highly glycosylated secretory protein that is a precursor molecule to granulins that modulate cell growth and proliferation . PGRN itOur aim was to examine the role of PGRN in ILDs with different etiologies and to assess its significance as a potential serum biomarker in the differential diagnosis of ILDs of possible autoimmune background.The study participants’ characteristics are shown in LCO and KLCO values were confirmed in IPF. Non-IPF ILD was associated with higher pO2 and lower pCO2 values. No difference between groups in functional performance assessed by 6MWT was present. The HRCT patterns did significantly differ between groups, UIP/pUIP being the main pattern in IPF, while NSIP in CTD-ILD and other patterns in the other ILD subgroups.Lung function parameters confirmed mild restrictive ventilator patterns in IPF patients . SignifiThe PGRN serum level in healthy controls was 40.99 ± 5.33 ng/mL, and the upper limit of normal (ULN) was set at mean ± 2SD representing the value: 51.65 ng/mL. All patients’ PGRN level was significantly higher as compared to controls. The IPF patients had similar PGRN levels as the healthy controls, while significantly lower as in non-IPF ILD patients .When CTD-ILD and other ILD subgroups were additionally analyzed, they both showed significantly higher values than controls, but only the other ILD subgroup differed from IPF patients .Patients above ULN were more often patients with non-UIP HRCT morphology, and in the presence of UIP patterns, normal PGRN levels were more common .No correlation was found between PGRN level and lung function, blood gases, 6MWT parameters, GAP stage or laboratory parameters . Five-step multivariate linear regression analysis showed that higher age and male sex predicts higher PGRN levels and confirmed that IPF diagnosis is associated with lower PRGN levels than non-IPF; however, based on step 5, we can assume that the UIP pattern is more strongly associated with lower PGRN levels than an IPF diagnosis. Immunosuppressive and antifibrotic treatment did not influence the PGRN values .This cross-sectional study was the first to investigate the serum levels of PGRN in patients with stable IPF and other non-IPF ILDs, including CTD-ILD. PGRN, as a pleiotropic growth factor, has been shown to mediate immune response and tissue regeneration in addition to many other biological processes. It was shown to be involved in the pathogenesis of liver fibrosis , acute IThe PGRN concentrations determined in our study were similar to those measured by Tanaka et al. and Xie et al. in DM and in IPF ,15.The age distribution of our patient population is in line with previous studies and clinical practice. Patients with IPF were older than non-IPF ILD patients; this difference was even more pronounced compared to the CTD-ILD subgroup. The mean age of 68.5 years in IPF patients is consistent with literature data and our former studies on IPF patients ,17,18. TAccording to previous studies, the proportion of men with IPF was higher as compared to non-IPF ILD patients ,17,18. A2 was also higher in this population. This may be due to the fact that the majority of non-IPF ILD patients had limited lung involvement, which in the vast majority of cases was below 20%. Overall, the functional condition of the examined patients was stable at the time of the study, with good 6MWT performance in all subjects.IPF patients were characterized by mild restrictive ventilation disorder. Although the majority of patients with IPF had a mild to moderate disease according to the GAP index, the non-IPF ILD group performed significantly better in terms of CO diffusion parameters than IPF patients and the pOPGRN concentrations were significantly higher in patients with non-IPF ILD compared to patients with IPF, while the PGRN levels of the IPF group were comparable to those in healthy controls. The similarity between the IPF patients and the healthy group may be explained by the fact that all patients were stable, and the majority received antifibrotic therapy. On the other hand, previous research suggests a stronger role for PGRN in acute and rapidly progressive ILDs. Examining ILD associated with DM, significantly higher serum PGRN concentrations were measured in patients with acute and subacute interstitial pneumonia than in those with DM with chronic interstitial pneumonia . In thisThe PGRN levels were higher in the non-IPF patients than in the healthy group, which may indicate a possible pathogenetic role of PGRN in this population. For a more accurate understanding of these results, an individual study of each ILD would be required. We distinguished patients with CTD-ILDs from other non-IPF ILDs because serum PGRN has been described as a promising biomarker in DM-associated ILD in a previous study . MoreoveElevated PGRN levels in CTD-ILD compared to healthy controls may be explained by the presence of systemic autoimmune disease itself, as several of PGRN’s functions are known to play a role in autoimmune processes . This miIn the other ILD subgroup, PGRN levels were also elevated compared to healthy subjects. As this group was quite heterogeneous , none of the diseases represented themselves with an evaluable number of elements; therefore, conclusions specific to each ILD cannot be drawn. However, the pathogenesis of these diseases, similarly to CTD-ILDs, is driven by inflammatory mechanisms and consequent activation of the immune system. Since PGRN is reported to take an important part in the inflammatory response , in thisThere are potential factors such as IL-6 ,26 and tThe elevated PGRN levels seen in non-IPF ILD compared to the IPF group may provide a new opportunity for the differential diagnosis of IPF from other ILDs. The difference can be explained by the different pathogenesis of the diseases. IPF is a chronic, relentlessly irreversible disease where epithelial cell activation and aberrant epithelial cell repair predominate over inflammatory processes. However, the level of PGRN may rise in acute exacerbation, indicating the altered pathomechanism, as mentioned above.Although the UIP HRCT pattern is characteristic of IPF, non-IPF ILDs, including CTD-ILDs, can also present with UIP; therefore, the differentiation is often difficult not only clinically but also radiologically . The assA limitation of our study is the low numbers in the specific ILD subgroups, the cross-sectional design, the homogenous Caucasian population and the possible treatment effect of antifibrotics in the IPF group.In summary, serum PGRN level may be a useful biomarker in the differential diagnosis of IPF and non-IPF ILDs, especially in cases where a clear decision cannot be made due to an uncertain HRCT pattern and sufficient clinical information or histological confirmation is not available.We performed a cross-sectional study of serum PGRN levels in 88 patients diagnosed with ILD and 17 healthy controls at the Department of Pulmonology Semmelweis University between October 2016 and October 2018. Consecutive patients presenting at the ILD care unit, giving their consent for the analysis, were enrolled. Each ILD diagnosis was made by the ILD MDD team at Semmelweis University. Our MDD team consists of 3 pulmonologists, expert radiologists, clinical immunologists with expertise in ILD and a pathologist if histology was present, according to international guidelines ,28. All 1), FEV1/FVC and total lung capacity (TLC) were performed by electronic spirometer according to the current guidelines at the Department of Pulmonology as previously described [LCO), and the transfer coefficient of the lung for CO (KLCO) was also calculated . Exercise capacity was determined using the 6MWT: 6-min walk distance (6MWD) in meters, baseline and post-exercise oxygen saturation (SpO2), heart rate and the Borg scale referring to dyspnea were assessed. ABG was measured from arterialized capillary blood .Analyses of forced vital capacity (FVC), forced expiratory volume in 1 s , the pattern of the ILD was determined by radiology experts.n = 40) and non-IPF ILD (n = 48) patients. The non-IPF ILD group was separated into 2 subgroups: CTD-ILD (n = 20) and other ILD (n = 28). CTDs included systemic sclerosis (n = 8), idiopathic inflammatory myopathies including PM/DM (n = 5), SLE (n = 2), rheumatoid arthritis (n = 1), Sjögren’s syndrome (n = 1), mixed connective tissue disease (n = 1) and overlap cases (n = 2). Other ILD group consisted of subjects with sarcoidosis (n = 9), hypersensitive pneumonitis , drug-induced ILD , granulomatosis with polyangiitis , cryptogenic organizing pneumonia , idiopathic nonspecific interstitial pneumonia , acute interstitial pneumonia , lymphangioleiomyomatosis  and other rare forms of ILD (n = 3).The ILD population was divided into 2 main groups as being IPF —a quantitative sandwich enzyme-linked immunosorbent assay (ELISA)—according to the user manual.Blood samples were kept at room temperature until clot formation (30 min), then centrifuged at 1800× The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethical Committees of Semmelweis University (Study No. 16/2018) and ETT TUKEB (Study No. 69/2015). Written informed consent was obtained from all subjects prior to the sampling.®  and IBM SPSS® Statistics 28.0  were used for statistical analysis. Data were expressed as mean ± SD for the Gaussian distribution and as median (interquartile range) for non-normally distributed variables. The normality of the data distribution was determined by the D’Agostino-Pearson test. The clinical parameters of the groups were compared by t-test or Mann-Whitney test, ANOVA and Chi2 test. Welch’s ANOVA was used for multiple comparisons of PGRN levels between the groups since the studied populations’ data had unequal variances. The relationship between PGRN levels and functional parameters was analyzed with Pearson’s correlation analysis in the case of normally distributed data. Spearman’s rank-order correlation was used when a nonparametric test was needed. After performing the univariate tests, in order to assess the role of possible confounding factors on the PGRN levels, we performed a stepwise multivariate linear regression analysis on the univariate data that proved to be significant according to the following steps: Step 1. Age and sex; Step 2. Medication included; Step 3. The presence of ILD included; Step 4. IPF or non-IPF diagnosis included; Step 5. HRCT pattern included (p < 0.05 was considered statistically significant.GraphPad Prism 9included . p < 0.0Differentiating IPF from non-IPF ILDs can be a difficult task due to similar clinical features and often unclear radiological patterns, especially when invasive tests cannot be performed to support the diagnosis histologically. Measuring serum PGRN levels may help the decision-making in such uncertain cases, as our results showed that elevated progranulin levels are associated with non-IPF ILD and non-UIP HRCT patterns. It may be worthwhile to investigate the role of PGRN in different non-IPF ILDs in larger studies. Future research on the association between serum PGRN and the activity of ILDs and the therapeutic response would be warranted for a better understanding of the multifaceted functions of this protein in the pathomechanism of ILDs.


The graphene was a chemical vapor deposited on copper foil and transferred wet-chemically to the SiO2 films. On the top of the graphene layer, either continuous HfO2 or SiO2 films were grown by plasma-assisted atomic layer deposition or by electron beam evaporation, respectively. Micro-Raman spectroscopy confirmed the integrity of the graphene after the deposition processes of both the HfO2 and SiO2. Stacked nanostructures with graphene layers intermediating the SiO2 and either the SiO2 or HfO2 insulator layers were devised as the resistive switching media between the top Ti and bottom TiN electrodes. The behavior of the devices was studied comparatively with and without graphene interlayers. The switching processes were attained in the devices supplied with graphene interlayers, whereas in the media consisting of the SiO2-HfO2 double layers only, the switching effect was not observed. In addition, the endurance characteristics were improved after the insertion of graphene between the wide band gap dielectric layers. Pre-annealing the Si/TiN/SiO2 substrates before transferring the graphene further improved the performance.SiO All TEMAHf pulses were separated by 0.9 s long purge periods. The exposure to the sequence of TEMAHf pulses was, again, followed by 0.1 s long H2O pulses repeated 120 times, whereby the pulses were separated by 0.9 s long purge periods. The buffer layer was, thus, formed similarly to the cycling sequence exploited in our earlier study 4-purge-O2 plasma–purge pulses.To protect graphene against oxygen plasma and promote the growth of the upper HfO2/graphene stacks were coated with electron beam evaporated (EBE), thin SiO2 layers using a SiO2 pellet . The process vacuum in the chamber was about 2 × 10−6 mbar at a rate of growth of 2 Å/s.In parallel, selected Si/TiN/SiO2 layers on Si/TiN/substrates was performed at 1000 °C in an Ar gas  environment for 10 min (after the temperature was ramped up from 500 to 1000 °C for 90 min) or at 600 °C in a vacuum (1.5 × 10−5 mbar) for 30 min.Annealing of selected ALD samples with SiO2 films before and after annealing (at 600 °C). The spectra were collected at normal emissions using a SPECSGROUP  Phoibos150 hemispherical analyzer and a Prevac RS40B1 non-monochromatic dual anode X-ray source (Al-Kα/Mg-Kα). The minor sample charging was corrected by adjusting the adventitious carbon  C 1s peak to 285.2 eV. Spectral components were fitted, and elemental content from survey spectra was estimated using CasaXPS software [X-ray photoelectron spectroscopy (XPS) was exploited to evaluate the composition of SiOsoftware .2 and HfO2 films were evaluated by X-ray reflectometry (XRR) using Cu Kα radiation , as well as by a spectroscopic ellipsometer using GES-5E  with a micro-spot option where light is focused on a film surface via a telescope. The converging angle of the beam in the ellipsometer was about 4°, and the spot size was about 0.35 mm × 0.8 mm for a 65° angle of incidence. Fitting was performed using the program SEA . Fit quality was characterized using a correlation function between the measured and computed spectra, R2.The thicknesses of the deposited SiO−1, and the Si reference was used for calibration. Raman spectra were measured after transferring graphene to SiO2 dielectrics and after deposition of the upper layer (SiO2 or HfO2) dielectrics on top of the graphene. All graphene band values were fitted by the Lorentz function.To characterize the formation and integrity of graphene, a micro-Raman spectroscopic system Renishaw  inVia at an excitation wavelength of 514 nm was used. The spectral resolution reached 1.5–2 cmThe surface morphology of the graphene and dielectrics, as well as the cross-sectional investigation of the deposited films, were performed by high-resolution scanning electron microscopy . In order to perform cross-sectional studies, a thin lamella was prepared by a focused ion beam (FIB) in the same microscope. It was further studied in a scanning transmission electron microscopy (STEM) mode of SEM.−6 mbar at a growth rate of 2 Å/s. Finally, the lift-off procedure was carried out in a warm acetone bath. The Ti electrodes used in the measurement had diameters of either 50 or 250 µm. To provide ohmic contact, the backside of the silicon substrate was etched with a 7% hydrogen fluoride solution and covered with a thermally evaporated aluminum layer with a thickness of 100 nm at RT.For the electrical measurements, an about 2 µm-thick positive photoresist  was spin-coated  on the top of cleaned stack structures and then softly baked at 100 °C. Maskless photolithography , with the dose control of the light source at 390 nm, was used. After the exposition, the samples were chemically developed following a method analogous to that described earlier . ThereafThe samples were electrically characterized at a probe station, at a Cascade Microtech  probe station MPS150, using a Keithley 2636A source meter . The measurements were carried out in a light-proof and electrically shielded box. CVD-grown large-area graphene was inserted in order to separate two different dielectric layers. Graphene might act as a source of defects for the upper functional dielectric layer, which is necessary for resistive switching or, alternatively, graphene could act as an ion-blocking layer, which may provide opportunities to control ionic dynamics at the nanoscale, reported earlier .2/HfO2 and ALD-grown SiO2/EBE-grown SiO2 dielectrics. The electrodes, i.e., TiN and Ti, allowing one to examine the appearance and stability of resistive switching, are also denoted.2 dielectrics onto the Si/TiN substrates. A similar phenomenon has been observed before [Some of the graphene films tended to break, i.e., delaminate when transferred to the ALD of the SiOd before ,32.SEM images of both the as-deposited a and tra2 layer grown on the graphene exhibited a granular structure, which is indicative of a tendency for nucleation at spatially separated adsorption sites, probably structural defects, to be followed by the further growth of grains 6 and ozone were used as the cation and anion precursors, respectively. The precursor chemistry described in the latter study was also exploited in the present study to grow the base SiO2 film prior to transferring the graphene. However, the attempts to grow SiO2 films on top of the transferred graphene occurred unsuccessfully. The graphene was severely damaged in this process, as no G and 2D bands could be detected in the Raman spectra (not shown). Evidently, if the ALD temperature exceeds 40 °C, the ozone as the oxygen precursor is able to completely destroy the graphene in such a process. Similarly, the destructive effects of ozone on graphene have been observed in some earlier studies [2/graphene nanostructures could be coated with evaporated physical vapor, i.e., EBE-grown SiO2 dielectrics, instead of ALD-grown SiO2. After the EBE of the SiO2 on the top of the graphene, only a low-intensity D-band emerged in the Raman spectra  measurements, with the results depicted in 2 layer was noticeably densified upon annealing at 1000 °C, i.e., the layer thickness was decreased from 7.9 to 6.3 nm, and the density was increased from 1.76 to 2.26 g/cm3 (2 (10.75 nm) and EBE-grown SiO2 (14.7 nm) films were obtained from ellipsometry measurements  photoelectron spectra are virtually identical, with a dominant oxide peak just below 104 eV of binding energy, which is in agreement with the literature’s values  but is a2 .2/graphene/HfO2 , SiO2/HfO2 , and SiO2/graphene/SiO2 (Sample 5) layered stacks, as described in The devices subjected to resistive switching measurements were built on solid media consisting of SiO2/HfO2/Ti (Sample 2 in The graphene-free TiN/SiO2/graphene/HfO2/Ti (Sample 1) stacks containing non-annealed SiO2 layers was markedly different compared to the devices without graphene. 2 (Sample 1). One can see that the currents still remained in the order of 1–10 pA, at voltages ranging from 0.5 to 1.5 V, towards both polarities in a high resistivity state (HRS). Further, the switching SET events could be recorded in the voltage range of 2.0–4.5 V, followed by the current–voltage envelope curves remotely characteristic of a switching device. The difference between low- and high-resistivity states  could extend even over 4 orders of magnitude . The switching mechanism was bipolar. However, the switching SET and also RESET events, as well as the LRS and HRS levels, occurred rather irregularly, suffering from abrupt changes in the switching direction . At the same time, the current–voltage curves implied possible multilevel RS performance. Such a “butterfly-like” appearance of the RS behavior is likely indicative of considerable structural and chemical inhomogeneities in the solid medium subjected to switching. It is possible that the irregular switching behavior is related to the defective structure of graphene, as revealed by the Raman spectrum from the same stacked medium  cell structures built on the TiN/SiO2 base substrate annealed at 1000 °C but without intermediate graphene layers transferred onto the SiO2 film. The switching current–voltage curves, characteristic of an electrode-defined resistive switching memory cell, could repeatedly be recorded  upon application of sequential switching voltage pulses had already approached an order of magnitude after few tens of the switching cycles.Further measurements were performed on the TiN/SiOrecorded a. Howeverecorded b reveale2 damaged the graphene layer, as mentioned above, the EBE of SiO2 on the graphene could still provide cells containing graphene between the SiO2 layers. Electrical measurements demonstrated that TiN/SiO2/graphene/(EBE)SiO2/Ti  devices disilane, and ozone could be used as base substrates for transferring graphene monolayers. X-ray spectroscopy on these silicon oxide films has revealed a negligible role for impurities and groups containing hydrogen or carbon in both as-deposited and annealed states. Graphene grown by chemical vapor deposition using methane and hydrogen can, upon a transfer process, be layered densely on silicon oxide as continuous films exhibiting only moderate, small-scale rupturing. Characteristic Raman bands as fingerprints of graphene have pointed to the appreciable integrity of the graphene film lacking bands, which are indicative of marked structural defect densities. Notably, the insulating dielectric material, hafnium oxide, can be grown using hafnium tetrakis(ethylmethyl)amide and oxygen plasma on top of the transferred graphene in the form of continuous layers to well-controlled thicknesses. The growth of homogeneous top oxide layers became favored after the pretreatment procedure of the graphene surface by a sequence of water pulses, followed by a sequence of metal precursor pulses at lowered temperatures. Remarkably, the plasma-assisted deposition did not destroy the integrity of graphene layers, although Raman bands referring to the creation of structural defects appeared in the spectra. At the same time, ozone-assisted deposition of silicon oxide on top of the graphene essentially damaged the graphene layer. In order to grow continuous silicon oxide on graphene non-destructively, electron beam evaporation had to be applied.The stacks consisting of either silicon and hafnium oxide layers below and on top of the graphene or silicon oxide layers below and on top of the graphene demonstrated functionality in terms of their resistive switching behavior. The stacks mounted as switching media between the bottom titanium nitride and top titanium electrodes exhibited hysteretic current–voltage curves with a clear distinction between the high- and low-resistivity states. The endurance and retention tests allowed one to conclude that after additional optimization, the research can further confirm the utility of graphene in such devices. It is important to recall that the stacks of silicon and hafnium oxides, drawn up without an intermediate graphene layer, did not switch, plausibly due to their insulating capabilities and high breakdown fields.


The composite dielectric also showed high breakdown strength (78.60 kV/mm), high dielectric constant (8.23), low dielectric loss (<0.015) and low AC conductivity (<10−11 S·m−1). Moreover, the composite demonstrated high thermal stability and strong mechanical strength. It is believed that the F-graphene/epoxy composite has outstanding performance in various aspects and can enable the development and manufacturing of advanced electric power and electronic equipment devices.The demand for high-performance dielectrics has increased due to the rapid development of modern electric power and electronic technology. Composite dielectrics, which can overcome the limitations of traditional single polymers in thermal conductivity, dielectric properties and mechanical performance, have received considerable attention. In this study, we report a multifunctional nanocomposite material fabricated by blending fluorinated graphene (F-graphene) with epoxy resin. The F-graphene/epoxy composite exhibited a high thermal conductivity of 0.3304 W·m When the GR content was 0.134 wt.%, the thermal conductivity of the composite was 54.8% higher than that of pure epoxy. Meanwhile, the product’s thermal stability and dynamic thermomechanical properties were enhanced [−1·K−1 at 12.96 vol% filler doping after compositing with an epoxy matrix, while the composite maintained strong electrical insulation performance [Polymer dielectrics have extensive applications in advanced electronic devices and power systems because of their characteristics of electrical insulation, easy processing and low density ,2,3,4,5.obtained ,16,17,18lectrics . Zhang electrics . Furtherxy resin . Lin et xy resin . The epoenhanced . Hu et aenhanced . The theformance . Mostovoformance . The pre−11 S/cm) and high stability, which is mainly due to the invasion of fluorine that transforms the structure of C-C bonds from sp2 to sp3 [bE) by 39.4% and simultaneously reduce the dielectric loss [−9 S/m and a high thermal conductivity of 3.57 W·m−1·K−1 [9 Ω/m) [In addition to high thermal conductivity as well as good physicochemical and mechanical properties, polymer dielectrics also require strong insulation and outstanding dielectric performance, especially for applications such as power electronic device packaging, insulation, support, etc. However, graphene as a carbon material has high electrical conductivity, which hinders its application in scenarios that demand high insulation and low dielectric loss . In this2 to sp3 ,31,32,33ric loss . Zhang e·m−1·K−1 . Mani et [9 Ω/m) . In addi [9 Ω/m) ,35,36.Here, we report a method of preparing F-graphene/epoxy composites with high thermal conductivity and outstanding dielectric properties by blending fluorinated graphene as a nanofiller with epoxy resin. Systematic studies were carried out on the thermal conductivity, dielectric and mechanical properties of the obtained F-graphene/epoxy composites. The results show that the introduction of F-graphene enhances the thermal conductivity of the epoxy resin matrix while exhibiting synergistic improvement in dielectric properties, insulation properties, mechanical strength and other aspects. The preparation method of blending F-graphene nanofillers with an epoxy matrix also introduces the practical advantages of a simple and non-polluting process. We believe that the composite developed in this work can provide new options for future power electronic device insulation, packaging and other needs.F-graphene was produced and provided by Nanjing Jicang Nano technology Co., Ltd. . Bisphenol A diglycidyl ether (E-51 epoxy resin), with an epoxy equivalent of 184, Methyltetrahydrophthalic anhydride (epoxy curing agent), with a relative molecular mass of 168, and dimethylaminomethylphenol  were purchased from Nantong Xingchen Synthetic Material Co., Ltd. . Other materials, such as anhydrous ethanol, acetone, deionized water, etc., were provided by Chengdu Kelong Chemical Co., Ltd. . The use and disposal of all materials in experiments were strictly in accordance with relevant instructions and specifications.F-graphene/epoxy composites were prepared by solid–liquid co-mixing followed by high-temperature curing. Firstly, F-graphene powder was weighed according to different filler mass fractions  and added to 10–15 mL of acetone liquid. The F-graphene/acetone suspension was ultrasonically dispersed at 40 kHz (200 W) for 10 min to obtain a stable dispersion. Then, E-51 epoxy resin, curing agent and catalyst were added to the obtained dispersion at a weight ratio of 100:80:2. The required amount of E-51 epoxy resin was added to the dispersion first, and the mixture was continuously stirred at 400 rpm for 1 h at 50 °C under atmospheric pressure to allow acetone to fully evaporate and F-graphene to disperse well. Then, the curing agent and catalyst were added, and the mixture was further stirred at 450 rpm for 1 h to make the E-51 epoxy resin, curing agent, catalyst and F-graphene filler evenly mixed. Then, the obtained mixture was placed in a vacuum oven, kept at 60 °C and vacuumed (1 bar) for 1 h to remove the large amount of air mixed in during the preparation process. Finally, the degassed mixture liquid was carefully poured into a preheated steel mold (60 °C), placed in a vacuum oven and heated to 80 °C while maintaining vacuum (1 bar) for 1 h to completely remove the residual trace gas in the mixture liquid. Finally, under standard atmospheric pressure, the temperature was raised to 120 °C for 2 h, then continued heating to 130 °C for 2 h and finally cured. After curing and waiting for natural cooling, the composite material was demolded and the surface was polished smooth and flat with fine sandpaper to obtain composite material samples. The preparation procedure of the composite material is shown in 2) were observed and characterized by scanning electron microscopy . The SEM sample of F-graphene nanostructures was prepared by dispersing the powders in anhydrous ethanol (G.R.) under sonication (80 W) for 5 min and then dropping them onto holey copper grids. Prior to observation, the sample surface for SEM was sputtered with a thin layer of gold. In order to eliminate the sample surface bump caused by the surface tension of liquid epoxy resin during the heat curing process, the surfaces of the samples used for the dielectric properties and thermal conductivity test were sanded flat with 1000 grit sandpaper. The dielectric response of epoxy/F-graphene composites in the frequency range of 102–106 Hz was characterized by a broadband dielectric relaxation spectrometer Concept 50 . The breakdown strength of the samples under a power frequency alternating current (50 Hz) at 25 °C was measured by a ZJC-100 kV computer-controlled voltage breakdown tester . The dynamic thermo-mechanical properties of the composites were analyzed by DMAQ800 , using the three-point bending method in the temperature range of 25–235 °C. The tensile tests of the dumbbell-shaped composite samples at 25 °C were conducted with an Instron 5967 universal material tester  with a fixture movement speed of 1 mm/min. Thermogravimetric analysis of the samples was performed using a TGA/DSC2  in the temperature range of 20~600 °C with a heating rate of 10 °C/min and under a nitrogen atmosphere with a flow rate of 15 mL/min. Considering the differences in absorption and reflection of the laser by the polished surface, the steady-state method was employed to measure the thermal conductivity of the sample. The thermal conductivity of the composites at room temperature (25 °C) was measured by the planar heat flow method , with high thermal conductivity silver silicone grease applied on the sample surface.The microstructure and morphology of the F-graphene and the characterization of the cross-sections of the composites brittlely fractured by liquid nitrogen , the thermal conductivity of the composites achieved a significant improvement compared to pure epoxy resin. As expected, the thermal conductivity of the composites showed a significant positive correlation with the filler content. It is worth noting that at low (≤0.25 wt.%) and high (≥0.75 wt.%) filler contents, the increase in magnitude of the thermal conductivity of the composites was relatively slow. This trend was clearly indicated by the slope of the enhancement rate line in −1·K−1, which was 10.30% higher than that of pure epoxy (0.1971 W·m−1·K−1); when the filler content was 0.5 wt.%, the thermal conductivity of the composites reached 0.2725 W·m−1·K−1, which was 38.25% higher than that of pure epoxy; and when the filler content was 1.0 wt.%, a thermal conductivity of 0.3304 W·m−1·K−1 was measured, which was 67.63% higher than that of pure epoxy. This phenomenon can be explained by the structure and random distribution of the filler in the polymer matrix. As illustrated in E is the experimental breakdown strength obtained from the high-voltage breakdown test; EB is the Weibull characteristic breakdown strength, which corresponds to the electric field strength at 63.2% statistical breakdown probability; and the shape parameter β indicates the slope of the fitted line and is inversely proportional to the dispersion of the experimental breakdown strength E, i.e., the larger β is, the steeper the line and the more reliable the Weibull characteristic breakdown strength EB is. As shown in β = 6.14) at 0.75 wt.%, which was enhanced to 140.58% of pure epoxy ; but when the filler content reached 1.0 wt.%, the breakdown resistance deteriorated , and the reliability of the Weibull characteristic breakdown strength (EB) decreased  with the increase in F-graphene content, which might be affected by the internal insulation defects of the composite materials caused by the incomplete dispersion of F-graphene at high loadings. Thanks to the significantly improved breakdown strength at low filler loadings (0.5 wt.% ~ 0.75 wt.%), the results of this paper have important significance and are expected to meet the high insulation requirements of modern power electronic devices. Furthermore, the employment of F-graphene had a significant impact on the dielectric properties of epoxy resin, as shown in 5 Hz) (5 Hz) was higher than that with 0.75 wt.% filler loading, while it was reversed when the frequency exceeded about 105 Hz. Such a change in the dielectric constant at high frequency might be attributed to the fact that at this time, the electric field polarity changed too fast, and it was difficult for micro-capacitors formed by interfacial polarization to charge and discharge in time, and this situation became more serious with a higher filler content [−11 S·cm−1), which was conducive to reducing the leakage conduction loss of the obtained dielectric [In addition to good thermal conductivity, excellent insulation and dielectric performance are also crucial for the application of polymer dielectrics in electric power and electronic industries. The power frequency (50 Hz) AC breakdown strength of F-graphene/epoxy composites at different filler loadings is shown in in 5 Hz) b. The dielectric , and thiT5%). The T5% of neat epoxy is 353.50 °C, while for the composite containing 1.0 wt.% F-graphene, the T5% decreases to 334.83 °C, which may be due to the absence of covalent bonds between the nano-inorganic filler and the epoxy matrix. However, at the same time, it can be seen from the decrease of about 5.28% in T5% that the introduction of F-graphene does not cause serious adverse effects on the initial thermal decomposition temperature of the epoxy matrix. In addition, the heat resistance performance of the composites can be calculated and measured by the following formula [THRI is the heat resistance index temperature, which characterizes the heat resistance performance of the material; T5% is the initial thermal decomposition temperature as mentioned above; and T30% is the temperature corresponding to 30% weight loss of the sample. THRI between the composite and neat epoxy resin, indicating that the doping of F-graphene does not have a negative impact on the heat resistance performance of epoxy composites, which deserves excessive attention. formula .(2)THRITg = 154.19 °C) of the composites is higher than that of pure epoxy (Tg = 147.84 °C) . G in Equation (3) can be obtained from Equation (4)E is the modulus of elasticity, while V is the Poisson’s ratio of the material, for epoxy resin V takes the value of 0.38. After substituting the value of V into Equation (4) and further bringing it into Equation (3), we can obtain the crosslinking density calculation Formula (5)From the stress–strain curves of tensile tests shown in 7.84 °C) c, and th7.84 °C) d. This c formula ,67.(3)υE can be equated with the storage modulus E’ at low frequencies. The low-frequency storage modulus E of the sample, the temperature T and the calculated crosslink density Tg and material stiffness .Here, the value of the elastic modulus −1·K−1 for the composite. The high resistivity of F-graphene enhanced the breakdown resistance and AC resistivity of the composite material. The abundant interfaces caused by the nanofillers introduced considerable interfacial polarization effects, which increased the dielectric constant of the composite and reduced the dielectric loss by trapping electrons. Moreover, the crosslinking of epoxy resin molecules became more compact with the addition of F-graphene, which improved the mechanical performance of the composite. Benefiting from the excellent thermal conductivity and insulating and dielectric properties, the F-graphene/epoxy composite provided in this study is expected to be widely used as a thermal management material or insulating and dielectric medium in the present-day advanced power electronic devices and integrated devices with high heat generation density and high integration. Its excellent mechanical properties and stability will also boost the application of this composite in the field of power equipment packaging and support, such as for grid reactors. The preparation method of blending the filler with the epoxy matrix has the advantage of simple and convenient preparation while avoiding the possibility of environmental pollution by surface modifiers and the like. Herein, we strongly believe that the results of this study provide a meaningful reference for the preparation of epoxy composite dielectrics with outstanding thermal conductivity and dielectric properties.In conclusion, by introducing F-graphene nanofillers, which combine the advantages of high thermal conductivity, wide bandgap, low conductivity and high stability, into the development of epoxy-based polymer dielectrics, a nanocomposite dielectric with excellent performance was successfully fabricated in this study, and the synergistic optimization of the important characteristics was effectively achieved. Thanks to the extremely high thermal conductivity and planar structure of F-graphene, efficient and robust heat transfer channels were constructed in the F-graphene/epoxy composite, resulting in a thermal conductivity of 0.3304 W·m


Dai et al. used bioinformatics methods to analyze the differentially expressed genes in both healthy and IPF patients, and to elucidate the signaling pathways and key gene targets closely related to IPF development. The Authors found 43 distinctly expressed genes in IPF and suggested that CRTAC1, COL10A1, COMP, IGFL2, NECAB1, SCG5, and SLC6A4 E SPP1  may be used as diagnostic markers for IPF. Li et al. investigated the role of ferroptosis-related genes (FRGs) in bronchoalveolar lavage (BAL) fluid as prognostic biomarkers in IPF. Ferroptosis is a previously unrecognized non-apoptotic form of regulated cell death that is iron-dependent and characterized by increased lipid-peroxidation. Elevated iron levels have been described in IPF patients, along with airway fibrosis and altered pulmonary function. It has, therefore, been hypothesized that ferroptosis may be involved in IPF pathogenesis . Within these, five genes were identified as a high risk signature. Patients with a high risk signature showed an overall survival rate that was significantly lower when compared to patients with a low risk profile.Idiopathic pulmonary fibrosis is a rare disease with a chronic progressive course that invariably leads to respiratory failure and death . Many asThe development of IPF is also linked to exposure to smoke and pollution as being external triggers for lung injury, inflammation, and abnormal repair mechanisms. Recently, dyslipidemia has been associated with the pathogenesis of inflammation, interstitial lung injury, and fibrosis , thus suSeenak et al., in a study on an animal model, showed a protective effect of atorvastatin and ezetimibe treatment against hypercholesterolemia-induced pulmonary fibrosis in rats.The combined simvastatin and ezetimibe therapy demonstrated a significant reduction in the secretion of the pro-inflammatory cytokine IL-1b from monocytes in hypercholesterolemia patients . Seenak Sesé et al. performed a multicenter national prospective cohort study with a 5-year follow-up to analyze gender differences in IPF. The authors found 236 patients with a new diagnosis of IPF between 2007 and 2010, 78% of whom were males . In this study, women were diagnosed at an early stage of the disease with a more preserved lung function, and radiologically showed less honeycombing and emphysema as compared to men. Women showed less frequent exposure to smoke and inhaled aerocontaminants, and were more likely to be over 65 years of age. Disease progression and overall survival remained comparable regardless of gender in this study, but this aspect is debated in the literature  not treated with antifibrotics were included in this study and showed a 50% all-cause mortality and a 42% cumulative incidence rate of acute respiratory-related hospitalization at 3 years. This observation confirms the poor prognosis and outcome of IPF. Another relevant issue relates to the influence of a diagnostic path on IPF epidemiology. Di Bidino et al. performed a retrospective, population-based longitudinal 5-year study that involved all four IPF reference centers in the Lazio region  to assess whether the hub-based model is effective in the early diagnosis and therapeutic management of the disease. An early, correct, and timely diagnosis and subsequent treatment of IPF are fundamental in order to improve outcomes in this complex disease. The Authors found that the number of new diagnoses of IPF significantly increased during the study period and that the number of patients eligible for antifibrotic treatment increased, suggesting that the patients were diagnosed at an early stage of the disease . The study demonstrated that this model of care significantly increases the ability to detect IPF cases, and to identify the key players of disease management based on the four qualified IPF centers. The protagonists of this care system are general practitioners, pulmonologists, and IPF centers supported by telemedicine. This represents the first case of a regional Diagnostic-Therapeutic Care Pathways involving different health professionals, including those external to the IPF centers, supported by digital solutions, and represents a possible model for future disease management.IPF is characterized by a male predominance. In different real-life data, males account for 60–70% of total cases . In a rePan et al. investigated the prognostic impact of marital status on malignant pleural mesothelioma (MPM), a rare neoplastic disease, and found that marital status is an independent favorable prognostic factor. In this study of 3,997 patients with MPM, the Authors observed that married groups had a lower risk of death and, after adjustment for demographic and tumor features, had a 13% reduction of death compared with unmarried patients. This study outlined that social conditions are also important factors in the management of disease and its outcome.All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.


Eukaryotic cells contain membrane-bound and membrane-lessorganellesthat are often in contact with each other. How the interface propertiesof membrane-less organelles regulate their interactions with membranesremains challenging to assess. Here, we employ graphene-based sensorsto investigate the electrostatic properties of synapsin 1, a majorsynaptic phosphoprotein, either in a single phase or after undergoingphase separation to form synapsin condensates. Using these graphene-basedsensors, we discover that synapsin condensates generate strong electricalresponses that are otherwise absent when synapsin is present as asingle phase. By introducing atomically thin dielectric barriers,we show that the electrical response originates in an electric doublelayer whose formation governs the interaction between synapsin condensatesand graphene. Our data indicate that the interface properties of thesame protein are substantially different when the protein is in asingle phase versus within a biomolecular condensate, unraveling thatcondensates can harbor ion potential differences at their interface. For instance, membranes can locally concentratemacromolecules thereby lowering the threshold concentration necessaryfor their condensation.3 Moreover, recent data show thatcondensates exert capillary forces on membranes yielding to theirremodeling.5 A recent computational study characterizedthe differences among the inside, the outside, and the interface ofcondensates, indicating that the interface of condensates has distinctconformational characteristics.6 Here,we investigate the unique properties of interfaces by asking if thedistinct conformational characteristics contribute to setting up anElectric Double Layer (EDL). This is further motivated by recent dataindicating that the interfacial fields can drive spontaneous redoxreactions.7 Thus, the interface of biomolecularcondensates plays a critical role in regulating cell signaling andintracellular trafficking. However, the electrical properties at theinterface of condensates remain largely elusive. This is due to thelack of techniques to directly measure the electric field gradientat the interface of biomolecular condensates and membranes.8A cell is a complex concoctioncomposed of many biomolecules, ions, and small metabolites, many ofwhich are charged under physiological pH. Despite chemical complexity,a cell is well organized in membrane-bound compartments. Additionally,macromolecules demix from surrounding cyto-/nucleoplasm in membrane-lessorganelles, also known as biomolecular condensates.9 electric potential and chargetransfer gauges based on graphene field effect transistors (Gr FETs)and other two-dimensional (2D) materials have been utilized to probethe interaction with small organic molecules.12 In biosensing,classically optical and plasmonic-based sensors are used to detectbiomolecules and track their transitions and charged states.14 A recent example includes plasmonic-based sensors of vitamin B12that rely on the strong light-matter coupling of graphene nanoholesand nanoribbons.15 However, these are allindirect measures of electrical activity, whereas a pure electricalreadout would allow for enhanced sensitivity and the reduction ofthe sensor complexity, size, and costs. To achieve sufficient sensitivityand desired selectivity many different nanostructured materials havebeen utilized in bioelectronics.16 Especially,2D material-based sensors are well-suited to probe interfacial electricfields and charge transfer due to their capability of fast readoutsand exceptional sensitivity.18 Specifically, Gr FETscan be used label-free because their sensing capabilities depend onthe measurement of the changes in electrical properties of the deviceactive area upon interaction with an analyte.19Inspired by the exceptionally sensitivefield modulation responseof graphene,20 Our data show that synapsin condensates interactwith the membrane interface in a charge-dependent manner. Using GrFETs that allow measurements under physiological conditions, wegain insight into the remarkable ion potential at the interface ofsynapsin condensates that is completely absent in the single-phaseregime of synapsin. Our results indicate EDL formation between synapsinand graphene. Thus, our findings strongly support that biomolecularcondensates form electric field gradients at the interface to themembrane and that they could act as charge centers in the cell.Due to all these unique features, Gr FETs promise to be suitablefor providing key insights into the dynamics of the electric potentialsat the interfaces of biomolecular condensates. Here, we aimed to quantifythe interfacial electric potentials and to determine the interactionmechanism by capitalizing on the unique features of graphene as anelectrostatic charge transfer gauge and a well-described neuronalcondensate of synapsin 1, a major synaptic protein implicated in neurotransmission.22 Synapsin condensates can sequester liposomes and native synapticvesicles,23 presumably due to the specificprotein and lipid interactions.24 To characterizethe interaction of synapsin condensates with membranes, we coincubatedgiant unilamellar vesicles (GUVs) with condensates of synapsin 1.Synapsin condensates exhibited a characteristic interface wettingof membranes  orsynapsin IDR  with GUVs. Indeed, synapsin IDR-mediatedcondensates also wetted the membrane interfaces, despite the absenceof the high-affinity lipid-binding region within its N-terminus , intrinsically disordered region (IDR).embranes 1a,b. Theembranes 1c. The iembranes 1d,e.Eveterminus 1f,g.Given the pronounced charge of synapsin 1, we aimedto explorewhether the presence of negatively charged phospholipid headgroupsin GUVs will affect the extent of synapsin condensate wetting. Infact, the wetting of synapsin condensates was significantly more pronouncedwhen GUVs contained a negatively charged surface 1h,i. Tog9 Unlike spectroscopy-basedtechniques that indirectly measure electrical properties of the interface,26 Gr FETs have their entire volume exposed tothe adsorbed species. Hence, they allow effective counting of thechange in the number of free electrons as the interface to the adsorbateforms.28Asthe increase in salt concentration or affecting the charge stateof GUVs both play a role in the synapsin condensate wetting of themembranes, we set out to determine whether a shift from a one-phaseto a condensed state of synapsin would impact the electrical propertiesat the interface. For this, we designed and employed graphene field-effecttransistors (Gr FETs). An optical micrograph of one device is presentedin VSD) results in the measured currentflow through graphene sheet, drain–source current (ID). The changes in ID are related to the change in the electric field experienced by thegraphene sheet. To quantify this relation, the dependence of the ID upon cyclic sweeping of the source-gate bias(VSG), so-called electrical transfer curve,was measured in air moments before the analyte exposure . The amount of shift that the ID(VSG) curve experiencescan be translated to the change in the electron concentration (Δe–) in graphene.30 Synapsin 1 in the buffer solution shows shifting of the ID(VSG) curves tothe lower VSG values, indicating the accumulationof electrons in graphene as the interface to the analyte forms. Referencemeasurements of the buffer solution and pure deionized water are providedin the Supporting Information . Further, in all cases the slopes of the transfer curves remainmostly unaffected upon the exposure to the analytes. The major changeis observed in shifting of the curves with respect to the applied VSG, indicating the electrostatic origin of themain interaction mechanism. Especially in the case of synapsin 1 FLcondensates (ID(VSG) curves) to the negative VSG values was observed.31 Assynapsin is positively charged, the data suggest that the observedchange is a consequence of the EDL formation between graphene andthe adsorbed synapsin, as illustrated in A scheme of the Gr FET connections and the appliedbiases is providedin Next, we set out to determine whetherthere is a difference inthe electrostatic properties of the interface when a solution containinga single phase or condensates of synapsin 1 is applied to Gr FETs.To trigger the condensation of synapsin, we add a crowding reagent. The comparison of the transfercurves in air and in analyte solutions provides a strong indicationthat synapsin 1 interacts stronger with graphene in a condensate thanin a dilute form 2c,d.ID without an applied gate bias and introducethe analyte. The measured changes in the current, i.e., the interaction kinetics at the interface, are expressed as thechange in the electron concentration Δe–(t) and normalized per unit area ofthe device’s active surface for comparison (e–(t) curves indicatesthe accumulation of electrons in graphene, which is also termed then-type doping or rising of graphene’s Fermi level.However, as both synapsin 1 and its condensateintroduce the samedirection of the CNP shift, a better comparison is achieved by followingthe kinetics of the response as the analytes are introduced and theinterface forms. For this, we record the temporal evolution of mparison 3. An ince–(t) curves was observed (e–(t) between the single phaseand condensate states  curves for the dense and the dilute phases in It is importantto note that the density transitions of synapsin1 to form condensates imply that there will always be some numberof synapsin 1 molecules in the dilute phase as well. While in ourcurrent iteration of the measurement setup it was not possible toprecisely quantify the amount of the unsegregated proteins, the quantitativecomparison between the Δd) rangingfrom 3 to 40 nm. A scheme of the experiment is presented in d .To further support the formation of the EDL and not a direct chargetransfer between the adsorbate and graphene, we performed the experimentswith an atomically thin dielectric separator placed between grapheneand the adsorbates. For this, we have used exfoliated hexagonal boronnitride (hBN) flakes with a thickness (e–(t) curvesfor the experiments with synapsin 1 FL with a varied dielectric separationlayer thickness. Evidently, the response has a trend similar to thatof the experiments carried out without the separation layer (–e onthe dielectric thickness, we plot the saturation values from 1/d dependence of the response, that is, the formation of EDL.on layer 3a, with It is important to note that in comparison to the cellular membrane,graphene and hBN possess different physicochemical properties. Consequently,the precise interaction and binding mode of synapsin 1 could differon graphene and hBN from their behavior on cellular membranes. However,we observe identical trends for both synapsin 1 full-length andsynapsin 1 IDR condensates when comparing the wetting experimentson neutral and charged GUVs, with the electrical response of Gr-FETs,highlighting the functional link between the EDL at the interfaceand the wetting capacity of synapsin condensates on membranes.There are three main implications of these data. First, the dataclearly indicate that the electrical environment at the interfaceto the surroundings of the same protein is substantially differentwhen the protein is in a single phase versus within a condensate.Second, the experiments strongly support the idea that the formationof EDL occurs between synapsin condensates and graphene, indicatingthat the condensation drives the formation of the electric potentialgradient at the interface of biomolecular condensates. Finally, theseexperiments suggest that synapsin/synaptic vesicle condensates couldact as a charge center at the synaptic boutons, which provides a newlayer for the regulation of neurotransmission.


There was an error in the original publication . The secAdolescent girls also mentioned the content of the sessions as one of the reasons that motivated them to come to the sessions. For instance, when asked about what made it easy for her to attend the sessions, Ayat said, “They were teaching us how you will save money, how to fill the deposit slip, and what you supposed to do when you go to a bank…. They were educating us on how a child should live.” She added that she experienced no challenges in attending the sessions. Similarly, Patricia, who never missed a session, shared, “We never missed a session because we know it is something that is going to help us in relation to our family and education”.A correction was also made to the data collection period in the Methods section, Section 2.3, in the first paragraph.Face-to-face semi-structured interviews were conducted with adolescent girls and their caregivers separately following the completion of the ANZANSI intervention, between December 2021 and January 2022.The authors apologize for any inconvenience caused and state that the scientific conclusions are unaffected. The original publication has also been updated.


Liquid phase exfoliation (LPE) has emerged as a promising method for the industrial-scale production of graphene. However, one of its critical steps, namely sonication, has faced challenges due to high power consumption and low efficiency, leading to limited applicability in industrial settings. This study introduces a novel, cost-effective microfluidic sonication device designed to significantly reduce power consumption while efficiently assisting the LPE process for graphene production. By coupling a capillary with a buzzer and applying an appropriate electric signal, simulation and particle tracing experiments reveal the generation of robust shear forces resulting from acoustic streaming and cavitation when the capillary end is immersed in the liquid. For the first time, the capillary-based sonication device was effectively utilized for graphene exfoliation in a DMF  + NaOH liquid phase system. The SEM (Scanning Electron Microscope) and Raman characterization results corroborate the successful exfoliation of 100 nm with thicknesses below 10 nm graphene sheets from graphite flakes using this pioneering device. The values of  Graphene, the first two-dimensional material with a honeycomb lattice of carbon atoms discovered, exists naturally as a stack of multilayer graphene with interlayer forces governed by van der Waals interactions. Since it was mechanically exfoliated from graphite in 2004 , graphenLiquid phase exfoliation (LPE) has proven to be a suitable method for achieving the mass production of graphene ,14,15,16Lab-on-chip and microfluidization techniques present a promising opportunity to meet the demanding requirements of graphene exfoliation ,29,30. FIn addition to hydrodynamic microfluidics, acoustofluidics devices have also been employed for graphene exfoliation. Ahmed et al.  utilizedIn this study, we introduce a novel and highly efficient sonication device designed for exfoliating natural graphite into graphene sheets within a liquid phase system. The device primarily comprises a microneedle (capillary) and a buzzer, securely bonded together using UV light curing glue. Its low cost and ease of assembly render it a practical and promising choice. Through acoustic streaming simulations and fluorescence particle tracing experiments, we have substantiated that the vibrated capillary generates robust acoustic streaming and cavitation effects in the liquid. In the DMF + NaOH liquid system, the capillary-based sonication device with low energy consumption replaces conventional high energy consumption sonication devices (probes and baths) during the sonication process. The characterization of the resulting graphene suspension is performed using Raman and SEM tests, revealing a certain level of effectiveness in the liquid phase exfoliation of graphene by the new device. The miniaturization of the device allows for small-scale production, and its potential for volume production through massive parallelization offers promising avenues for future applications.The graphite powder used in the experiments was purchased from Aladdin  and used without further treatment. DMF  were provided by Macklin . NaOH (Sodium hydroxide) came from SCR . DMF was chosen because its surface tension value is 37.5 the bond . NaOH wathe bond .The novel capillary-based liquid phase exfoliation system a consistAs illustrated in During the exfoliation process, graphene can be peeled from the pristine graphite layer by layer. As the complex acoustic streaming generated from the capillary tip, shear force produced and overcame the van der Waals force between layers, in which FLG (Few Layers Graphene) could be peeled down due to their lateral self-lubricating ability. On the other hand, the cavitation-induced bubble can result in shock waves, which will produce normal and shear forces in graphite, and some microbubbles may come into the space between layers and expand the interlayer spacing ,43. All The acoustic streaming simulation was conducted for better understanding and for the optimization of the sonication process. The detailed calculation process based on the perturbation method is provided below, which provides a theoretical foundation for the subsequent simulation.With the external acoustic actuation, liquid perturbations can be described by three variables: temperature The acoustic source is molded as the boundary condition using the first order velocity D is the thermal diffusivity, The first-order acoustic field can be obtained by employing the thermos-viscous acoustic module in the frequency domain. The first order equation can be expressed as:The second-order acoustic can be obtained by employing the laminar flow module based on the calculated The vibration-induced acoustic streaming flow fields around the capillary tip were simulated using a finite element analysis software COMSOL Multiphysics 6.0. Based on necessary assumptions for simplification, we considered the capillary tip to be a rigid oscillating cone with base radius a = 10 μm. The surrounding fluid domain was large enough (radius = 30 a) to avoid the boundary effect.The first order acoustic fields are assumed to be time-harmonic and calculated with the thermos-viscous acoustic module. The capillary tip boundary is prescribed as a Dirichlet boundary condition with a known displacement profile. Once the first order flow fields have been solved, the source terms in second-order equations are identified and a laminar flow module with a steady state can be studied. We refer the reader to a prior study  for furtThe related particle tracing experiments were studied using inverted fluorescent microscopy . The device was characterized by immersing the capillary tip into a cylindrical liquid chamber containing 5 μm blue fluorescence tracer particles  mixed with DIW: F127 (0.6 wt%) in a volume ratio of 1:100. The tip was positioned at the chamber’s center to avoid boundary effects as much as possible during the characterization of the particle trace. The continual image was captured using a high-resolution camera . U presents Gor’kov force potential and is expressed using the acoustic pressure and velocity as:The working principle of the particle tracing behavior is based on the acoustic radiation force, arising from the scattering of acoustic waves on the microparticle, and the drag force induced by acoustic streaming. For the situation of the manipulation of microparticles smaller than the acoustic wavelength (a << λ), the ARF on particles can be expressed as:The suspended particles in the fluid will also experience a drag force from the acoustic streaming, which is given by:Graphite powder was added into DMF with NaOH as the surfactant to assist the exfoliation. The initial concentration of graphite was 30 mg/mL, and the concentration of NaOH was 10 mg/mL . The exfoliation process was performed via sonication over 9 h. The capillary-based sonication device with a 3 μm tip was immersed in the 2 mL solution. The excitation signal from the function generator was 18.8 kHz and 1 The surface morphology of the natural graphite and the FLG sheets were characterized using a Scanning Electron Microscope  at a voltage of 2 kV . The samFor the Raman test, the graphene dispersions were drop-casted onto a 285 nm In this section, we will describe the acoustic streaming developed near the capillary tip. At first, a 3D acoustofluidics simulation model was built, and the streaming pattern and velocity under different vibration mode was simulated. To display the streaming under the acoustic field, blue fluorescence microparticles were diluted and suspended in 0.6% wt F127 buffered solution and placed into a reservoir (~200 μL). The capillary tip was close to the reservoir bottom for clearer characterization using an inverted fluorescence microscope.The acoustic streaming phenomenon was initially simulated under a frequency of 18.1 kHz, with the vibration direction along the y-axis. As depicted in The strength of the flow field produced by the capillary is determined by the intensity of the acoustic wave, which was demonstrated by adjusting the frequency applied to the capillary in the simulation. In the simulation model, the vibration velocity of the capillary is governed by the frequency, as the amplitude of the capillary boundary remains fixed for simplicity. This implies that the frequency exhibits a positive correlation with the intensity of the acoustic wave. The streaming velocity distribution simulation results for 18.1 kHz a, 100 kHIn addition to the unidirectional vibration, simulations were conducted with x- and y-direction vibrations with a 90° phase difference, as depicted in As mentioned before, we analyzed simulation and experimental results about acoustic streaming and cavitation generating from a vibration-based capillary end effector. By choosing appropriate excitation signals, the shear force from strong acoustic streaming and cavitation can be applied in a small container for graphene liquid phase exfoliation. Detailed experiments have already been mentioned in Raman spectroscopy was deployed for scrutinizing the quality of graphene, including defects, layer count and exfoliation evidence . The mai (ID/IG) . Princip (ID/IG) ,46.Along with these experiments, we proved that graphene sheets can be extraordinarily exfoliated in solution by using a vibration-based capillary effector. Through acoustic streaming simulation and particle tracing experiments, we found that strong mechanical shearing, acoustic cavitation, and microbubbles can be generated by a vibration-based capillary effector in a small container. To give the pros and cons of the new microfluidic device clearly, we compared commonly used assist devices in the LPE process in As in (1)By coupling a low-cost buzzer and microcapillary using UV curing glue and applying a low-consumption electric signal, a promising simple yet effective sonication device was developed.(2)Acoustic streaming simulations and particle tracing experiments were conducted by immersing the capillary tip in the liquid, revealing significant acoustic streaming generated near the capillary tip, which increased with the intensity of the acoustic waves.(3)Additionally, at 18.1 kHz, cavitation phenomena were observed in the liquid chamber, characterized by the generation of microbubbles that followed the streaming. These phenomena induced shear force and cavitation, and are considered to be the key mechanisms underlying the sonication-assisted graphene exfoliation process.(4)Sonication-assisted LPE was conducted for 9 h using DMF + NaOH, and the resulting sheets were subjected to analysis using various characterization techniques. SEM and Raman results revealed the production of 100 nm graphene sheets with a thin thickness.This study introduces a novel method for graphene liquid phase exfoliation, employing a capillary-based sonication approach for the first time. The main conclusions are listed as follows:The capillary-based sonication device demonstrated low power consumption and affordability, making it an attractive option for industrial-scale graphene production through the implementation of automatic parallelization devices in the LPE system.