Immune checkpoint inhibitors (ICI) have become standard treatment in different tumor entities. However, safe treatment with ICI targeting the PD-1/PD-L1 axis requires early detection of immune-related adverse events (irAE). There exist different questionnaires of drug manufacturers for the detection of irAE that have not been validated so far.The prospective non-interventional ST-ICI trial studied treatment with PD-1/PD-L1 ICI alone or combined with radiotherapy. In the current analysis, the detection rate of self-reported irAE with a patient questionnaire containing 41 different questions was compared to clinician-reported irAE.Between April 2017 and August 2019, a total of 104 patients were prospectively enrolled. NSCLC (44%) and HNSCC (42%) were the most frequent tumor entities. A total of 784 questionnaires were collected. A total of 29 irAE were reported by clinicians. The most frequent irAE was hypothyroidism (9%), followed by skin reactions (5%), hepatitis (4%), diarrhea (3%), and pneumonitis (3%). Questions that became significantly more often positive at time points of clinician-reported irAE were “weight change”, “difficulty to grip things”, “bloody or mucous stool” and “insomnia”. Self-reported organ-specific questions detected at least 50% of clinician-reported irAE of gastrointestinal, lung, endocrine, and skin irAE. It was not possible to detect hepatic irAE with the questionnaire.Questionnaires can help to detect gastrointestinal, lung, endocrine, or skin irAE, but not hepatic irAE. Questions on “weight change” and “insomnia” may help to increase the detection rate of irAE, besides organ-specific questions. These results are a valuable contribution to the future development of a specific and practicable questionnaire for early self-reported detection of irAE during ICI therapy in cancer patients.NCT03453892. Registered on 05 March 2018.ClinicalTrials.gov, The online version contains supplementary material available at 10.1186/s12885-021-08006-0. Over the last decade, treatment with immune checkpoint inhibitors (ICI) against programmed cell death protein 1 (PD-1) and one of its ligands PD-L1 have become one of the most promising approaches in the field of cancer therapy. Consequently, their application in oncologic treatment is continuously increasing . HoweverThere exist different questionnaires of drug manufacturers for the detection of irAE that have not been validated so far. Adapted from these questionnaires an own questionnaire was developed for patients’ self-reported detection of irAE. The aim of the current analysis is to compare the patients’ self-reported irAE to clinician-reported irAE.Patients with non-melanoma solid tumors and the indication for ICI treatment with either a PD-1 or PD-L1 inhibitor were eligible for the trial. Concomitant radiotherapy was not obligatory. To represent an unselected cohort, there was no restriction concerning baseline Eastern Cooperative Oncology Group (ECOG) performance status, pre-existing diseases, tumor entity, or blood parameters.ST-ICI is a prospective non-interventional, non-randomized trial in tumor patients treated with ICI. Patients receive either immunotherapy in combination with radiotherapy or immunotherapy alone. A secondary endpoint of the current interim analysis is the detection rate of irAE using a newly developed questionnaire. All treatment decisions are made by treating physicians based on clinical standards and national guidelines. Any EMA-approved PD-1 or PD-L1 inhibitor treatment was allowed within the trial. Dose and the treatment indication of the ICI were according to the EMA marketing authorization. Radiotherapy was delivered either as stereotactic radiosurgery or fractionated radiotherapy.The current analyses focus on a secondary endpoint of the ST-ICI trial. In this explorative interim analysis the detection of different irAE with a newly developed 41 item irAE questionnaire is studied . Furthermore, questions concerning any irAE have been analyzed independently from their specific irAE, to identify general screening-questions for any irAE. This should help to identify appropriate questions for the development of a specific questionnaire on irAE, which can enter a future questionnaire validation process.The registration of the ST-ICI trial is allocated in Clinical Trails.gov (identifier: NCT03453892). The leading institutional review board at the Friedrich-Alexander-Universität Erlangen-Nürnberg approved the study (number: 2_17 B). The written informed consent of all patients has been obtained. The study had no external funding. All methods were performed in accordance with the relevant guidelines and the Declaration of Helsinki.P-values below 0.05 level are expected to be statistically significant. The statistical analysis was done for all irAE, the types of irAE were not analyzed separately.Due to the very low prevalence of irAE compared to the number of questionnaires the frequency of positively answered questions at time points of clinician reported irAE will be presented descriptively. Due to this imbalance of the high number of questionnaires and low number of irAE classical parameters as sensitivity, specificity, positive and negative predictive values were waived. It is the aim of this explorative analysis of this prospective trial to identify appropriate questions for the development of a specific questionnaire that can enter a classical validation process. IBM SPSS Statistics version 24 was used for performing all statistical tests. Fisher’s exact test was used to study differences in the frequency of positively answered questions in the subgroups with and without irAE. The ST-ICI trial registered 104 patients between April 2017 and August 2019. Baseline characteristics of the patients are given in Table Twenty-nine out of one hundred four surveyed patients developed any irAE Table . The medA total of 784 questionnaires were collected. Out of the 104 surveyed patients, 96 patients 92%) completed at least one questionnaire. The median number of completed questionnaires per patient was 6 (range 0–40). Figure % completClinician-reported gastrointestinal irAE were detected by different questions at a rate of ≥50% as “feeling unwell”, “nausea or vomiting”, “differing bowel movements”, “nocturnal defecation”, “thin or foul-smelling stool”, “abdominal pain” and “bloody or mucous stool” Fig. a. QuestiClinician-reported pulmonary irAE were detected at a rate of ≥50% by the questions “shortness of breath” and “difficulty in breathing” Fig. b. PatienClinician-reported endocrine irAE were identified in at least ≥50% of cases by the question on “insomnia”. The question on “fatigue” increased in endocrine irAE to 70%, whereas it was also answered positively in 49% of patients without irAE Fig. c. QuestiClinician-reported skin irAE were detected at a rate of ≥50% by the questions “skin rash”, “itchiness” and “deterioration of skin diseases”, whereas the question “hair loss” was not increased in skin irAE Fig. d. Hepatip = 0.041), “difficulty to grip things” (p = 0.036), bloody or mucous stool” (p = 0.039), and “insomnia” (p = 0.012) in the self-reporting questionnaire  and close monitoring of patients is in favor of the presented results. The extremely high rate of completed questionnaires (92% of included patients) is unique. This also proves the suitability of this questionnaire for daily routine use. As mentioned above, the identification of irAE is essential for the patients’ safety. There exists a mild correlation between a reduction of quality of life during radiochemotherapy and prolonged survival, which is probably a marker for treatment intensity [A potential bias of the ST-ICI trial may be that patients filled in the questionnaire before their contact with the physician. This may have encouraged them to report their symptoms to the physician and increased the correlation between patient- and clinician-reported irAE. Clinician-reported irAE were diagnosed according to clinical standards, there was no standardized diagnostic workup. A further limitation of the ST-ICI cohort is that the used questionnaire was adapted from questionnaires of drug manufacturers and has not been validated before. However, there exist no validated questionnaires on self-reported irAE detection so far. Thus, the presented analysis is a first step to identify appropriate questions for the development of a specific irAE questionnaire that can enter a validation process. Due to the high number of collected questionnaires and low number of irAE the results are presented only descriptively. In the current trial the calculation of sensitivity, specificity, and positive/negative predictive value was not the aim of the trial and is not possible within this study design. The number of included patients and clinician-reported irAE is too low for such analyses. Altogether 29 irAEs were reported, including three cases of diarrhoea. This underrepresentation of the irAE diarrhoea might also be a consequence of the low patient number. The mixed patient cohort including several tumor entities might be rated as a further limitation. However, the development of irAE does not depend on the treated tumor entity. The inclusion of different tumor entities is probably a strength as in a patient cohort with a single tumor entity, special organ-specific symptoms might be overrepresented (e.g. breathing problems in NSCLC). The major strength of the ST-ICI trial is its prospective design. Furthermore, the collection of a high number of questionnaires (ntensity . Howeverntensity –17.Questionnaires can help to detect gastrointestinal, lung, endocrine, or skin irAE, but not hepatic irAE. Questions on “weight change” and “insomnia” may help to increase the detection rate of irAE, besides organ-specific questions. These results are a valuable contribution to the future development of a specific and practicable questionnaire for early self-reported detection of irAE during ICI therapy in cancer patients.Additional file 1: Supplementary Table 1. Location of radiotherapy in patients with irAE.


TDP-43 inclusions are found in many Alzheimer’s disease (AD) patients presenting faster disease progression and greater brain atrophy. Previously, we showed full-length TDP-43 forms spherical oligomers and perturbs amyloid-β (Aβ) fibrillization. To elucidate the role of TDP-43 in AD, here, we examined the effect of TDP-43 in Aβ aggregation and the attributed toxicity in mouse models. We found TDP-43 inhibited Aβ fibrillization at initial and oligomeric stages. Aβ fibrillization was delayed specifically in the presence of N-terminal domain containing TDP-43 variants, while C-terminal TDP-43 was not essential for Aβ interaction. TDP-43 significantly enhanced Aβ’s ability to impair long-term potentiation and, upon intrahippocampal injection, caused spatial memory deficit. Following injection to AD transgenic mice, TDP-43 induced inflammation, interacted with Aβ, and exacerbated AD-like pathology. TDP-43 oligomers mostly colocalized with intracellular Aβ in the brain of AD patients. We conclude that TDP-43 inhibits Aβ fibrillization through its interaction with Aβ and exacerbates AD pathology. TDP-43 inclusions are observed in Alzheimer’s disease. Here the authors show that TDP-43 interacts with amyloid-β and inhibits fibrillization in vitro and exacerbates Alzheimer’s disease pathology in animal models. Aβ, mainly consists of 40 or 42 amino acids, is a proteolytic cleavage product of amyloid precursor protein by sequential cleavages of β- and γ-secretases. Aβ42 is considered more toxic as evidenced from both in vitro3 and in vivo studies4, where Aβ42 to Aβ40 ratio implicated in some familial AD cases is also important6. Aβ spontaneously aggregates into amyloid fibrils with a cross β-sheet structure, where prefibrillar Aβ oligomers are considered the most toxic species and attributed to neuronal dysfunction and cognitive impairment7. Amyloid fibrillization adopts a nucleation-dependent polymerization mechanism in which amyloid fibrils serve as a nucleus to seed soluble species and skip the nucleation8. Aβ deposits extracellularly to form amyloid plaques, but also accumulate intracellularly as shown in human patients and transgenic mice9.Alzheimer’s disease (AD) is the most common type of dementia in which the two pathological hallmarks are senile plaques comprising amyloid-β (Aβ) and neurofibrillary tangles composed of hyperphosphorylated tau10. TDP-43 inclusions were also reported in the brain of AD patients with a prevalence of ~30 to ~57%13. The AD patients with TDP-43 inclusions have more severe memory loss and hippocampal atrophy14. The highly significant pathological role of TDP-43 is further suggested by a recently proposed diagnostic entity called limbic-predominant age-related TDP-43 encephalopathy (LATE), which predominantly occurs in cognitively impaired oldest-old individuals with co-existing medial temporal amyloid plaques and tauopathy15. TDP-43 is a highly conserved RNA/DNA-binding nuclear protein consisting of 414 amino acids with a molecular mass of 44,740 Da16. Full-length TDP-43 is constitutively expressed in many tissues, including brain, heart, lung, kidney, and muscle18. TDP-43 contains two RNA binding domains (RRM1 and RRM2), which are flanked by an N-terminal domain and a C-terminal glycine-rich region. The N-terminal region was shown to dimerize that facilitates nucleotide binding and splicing20, whereas, C-terminal regions are highly prone to aggregation21. Recombinant full-length TDP-43 forms stable spherical oligomers, which are toxic to neurons in primary culture and in mouse brain following intrahippocampal injection22. In our previous study, we generated a conformational-specific polyclonal antibody namely poly TDP-O that specifically recognizes TDP-43 oligomers and used it to confirm the existence of TDP-43 oligomers in the brain of patients with FTLD-TDP22.TDP-43 pathology was first found in cytosolic inclusions in patients with amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD-TDP)23. In lentiviral TDP-43-injected rat, TDP-43 expression induced neuroinflammation and increased β-secretase activity, accelerating the production of Aβ and APP-C-terminal fragments24. Previously, we have shown that full-length TDP-43 forms toxic spherical oligomers readily , an elongation phase, and a plateau phase. In the absence of TDP-43, Aβ possessed a lag time of ~25 h, whereas the lag time was significantly prolonged to ~75 h in the presence of TDP-43. The final ThT signal of Aβ with TDP-43 was reduced to ~50% compared with the signal of Aβ alone. No ThT signal was found in TDP-43 alone. Next, we employed two conformation-specific antibodies, namely A11 and OC, to facilitate the understanding of the aggregation process  assay to monitor the fibrillization kinetics of Aβ Fig. . ThT caness Fig. . The timTo understand how TDP-43 hinders Aβ aggregation, we added TDP-43 to different Aβ aggregation states and monitored the ThT signals. Aβ monomers, oligomers, and preformed fibrils were prepared and validated via TEM 22. Here, we aimed to clarify the prerequisite structural regions of TDP-43 for inhibiting Aβ fibrillization. We constructed and purified different structural regions of TDP-43, including TDP-43 with a C-terminal region truncated , an N-terminal region , and the RNA recognition region . The calculated molecular weights of each variant were 32.5 kDa for TDP-43_265, 12.5 kDa for TDP-43_N-term, and 20.4 kDa for TDP-43_RRM1 + 2. The assembly of these truncated proteins was first characterized in SEC , and a C-terminal glycine-rich region Fig. . TDP-43 Next, we tested the potency of TDP-43 variants in inhibiting Aβ fibrillization Fig. . As expeThe end-products of aggregation study were further examined by western blot Fig. . The samConsidering that TDP-43 variants inhibited Aβ aggregation to different degrees, we examined the molecular interaction between TDP-43 variants and Aβ. We first employed enzyme-linked immunosorbent assay (ELISA) to detect the binding of Aβ to TDP-43 proteins Fig. . In thiskon, koff, and KD were calculated . For TDP-43_265, the dissociation constant is 9.87 × 10-8 M.We further performed biolayer interferometry analysis to examine the on and off kinetic binding rates of TDP-43 variants . However, no significant difference in the fEPSP slope was induced by the buffer control, Aβ40 alone (1 μM), and TDP-43 alone (0.01 μM) . In Aβ42 experiments, we prepared Aβ42 following previous literature32 and incubated with or without TDP-43 as described in Fig. F = 50.21, df 1/17, p < 0.0001; Buffer v.s. Aβ42-125 nM, F = 10.95, df 1/16, p = 0.004; Buffer v.s. Aβ42-62.5 nM, F = 0.5199, df 1/12, p = 0.485)). We found that Aβ42 at 250 and 125 nM were toxic, but not at 62.5 nM. To address TDP-43 effect, the samples were diluted to a non-toxic Aβ concentration at 62.5 nM to minimize Aβ42 toxicity. The same molar ratio of TDP-43 at 0.625 nM to Aβ were kept (1%). Similarly, TDP-43-induced Aβ42 significantly inhibited hippocampal LTP compared with that of the buffer control  . The result indicated that TDP-43-induced Aβ species significantly impair synapse function to a greater extent than Aβ alone or TDP-43 alone did.LTP is an important cellular mechanism related to learning and memory functionice Fig.  showed t32) Fig. . No signF = 54.47; df 1/26; p < 0.001; treatment factor, F = 2.875; df 3/26; p = 0.055; for Aβ42 study, time factor: F = 25.60, df 1/15, p = 0.0001, treatment factor: F = 0.82, df 3/15, p = 0.505). The swimming velocity for each group was unchanged .Next, to investigate the detrimental effect of TDP-43-induced Aβ species on the hippocampus-related spatial learning and memory in vivo, we injected the aggregation samples to the hippocampi of wild-type mice and examined the mouse behavior by Morris water maze (MWM) paradigm 1 month after the injection Fig. . Two micF = 5.25, df 1/13, p = 0.039; for Aβ42 study, F = 11.07, df 1/8, p = 0.010). More importantly, the escape latency time of the TDP-43-induced Aβ was significantly increased compared with that of Aβ alone  and TDP-43 alone . In the probe test with the platform removed, the mice injected with TDP-43-induced Aβ40 . The result indicated that TDP-43-induced Aβ significantly impaired spatial learning and memory of mice to a greater extent than Aβ or TDP-43 does.In the training phase, the escape latency time of the TDP-43-induced Aβ40 Fig.  or Aβ42 β40 Fig.  or Aβ42 β40 Fig.  spent siF = 35.26; df 1/27; p < 0.001; treatment factor, F = 1.964; df 3/27; p = 0.143). The swim speeds did not differ among the groups . The results demonstrated that the visual ability and navigated motivation of all the groups were not impaired. In the training phase, the escape latency time of TDP-43-injected APP/PS1ΔE9 group was significantly increased compared with that of the buffer-injected group . No difference was observed in the TDP-43-injected and buffer-injected wild-type mice . In the probe test after the platform was removed, the mice in the TDP-43-injected APP/PS1ΔE9 or WT group spent significantly less time in the target quadrant than the buffer control group did. Furthermore, the memory function of the TDP-43-injected APP/PS1ΔE9 mice was more significantly impaired than that of the TDP-43-injected wild-type mice . The time spent of the TDP-43-injected APP/PS1ΔE9 in the opposite quadrant was longer than that of the other groups . Altogether, the results demonstrated that TDP-43 worsens the spatial memory in APP/PS1ΔE9 mice. In the pathological examination, we first analyzed the amyloid plaque burden in different brain areas. The Aβ level was quantified by immunostaining with Aβ antibody 4G8/6E10. The results showed that TDP-43 injection significantly increased the amyloid plaque burden in the olfactory bulb, the amygdala, the prefrontal cortex, the motor cortex, and the somatosensory cortex . We further analyzed TDP-43 oligomers and Aβ localization in the hippocampus dentate gyrus. We found that TDP-43 oligomers probed by poly TDP-O antibody were mostly intracellular and colocalized majorly with intraneuronal Aβ (~94%) and a few with amyloid plaques (~6%) . Overall, these results showed that TDP-43 impairs spatial memory, increases amyloid burden, interacts with Aβ, and induces microgliosis in APP/PS1ΔE9 mice.To further investigate the effect of TDP-43 on AD-related pathology, we bilaterally injected TDP-43 protein into the hippocampus of APP/PS1ΔE9 mice and examined the resulting behavior and pathology. We first performed the MWM for 6-month-old APP/PS1ΔE9 mice and their wild-type littermates that received TDP-43 injection at the age of 5 months. In the pre-training phase, all the groups exhibited a similar time-dependent decrease in escape latency, demonstrating that the sample had no injection effect  Fig. . We furt6%) Fig.  in TDP-433. Thus, we investigated whether the injected TDP-43 affects Aβ assembly. We employed western blot analysis to examine the Aβ assembly in different fractions from APP/PS1ΔE9 mouse brains with or without TDP-43 injection. In the extracellular-enriched fraction, we detected Aβ species, including monomer, tetramer, hexamer, dodecamer, and hexadecamer detected by a mixture of 6E10 and 4G8 antibodies. We found that the level of Aβ hexadecamer was significantly increased in the TDP-43-injected group , whereas, the Aβ monomer decreased . The levels of other Aβ assemblies were not changed . In the Triton-soluble fraction, we detected Aβ hexamer, dodecamer, and hexadecamer. Again, the level of Aβ hexadecamer was significantly increased in TDP-43-injected group . The levels of the other detectable Aβ assemblies were not changed . We were unable to perform IP and western blot from the GdnHCl fractions because the high concentration of GdnHCl strongly affected the experiments. The result indicated that TDP-43 alters Aβ assembly in APP/PS1ΔE9 mice.Aβ assembly has been strongly implicated in AD pathogenesisPreviously, we found that TDP-43 oligomers are present in FTLD and ALS brains but not in age-matched controls. Above in vitro and in vivo studies showed that TDP-43 species, including TDP-43 oligomers interacted and colocalized with Aβ in the mouse brain. Therefore, to examine whether TDP-43 oligomers exist and colocalize with Aβ in AD patients, we applied immunostaining by poly TDP-O antibody or TDP-43 C-terminal antibody and Aβ antibody in the entorhinal cortex of four AD patients  with a mean age of 75.5 ± 5.6 years old and a Braak stage of IV or V. In immunostaining analysis by poly TDP-O antibody Fig. , we founn = 3) were lower and their levels of Aβ oligomers were higher than those of AD patients but without TDP-43 pathology (n = 5). Aβ oligomer at 50 kDa was significantly higher in AD patients with TDP-43 pathology than in AD patients but without TDP-43 pathology. These results were consistent with those observed in APP/PS1ΔE9 mice injected with TDP-43.We further used the hippocampal tissues of several cases with AD to examine their TDP-43 pathology as indicated by hyperphosphorylated TDP-43  forms soluble amyloid oligomers that inhibit Aβ aggregation more potently than monomeric and dimeric CysC do34. Transthyretin tetramer suppresses Aβ aggregation and ameliorates AD phenotype by interacting with Aβ35. TDP-43 possibly formed a complex with Aβ and caused detrimental effects although only 1% TDP-43 was present in the Aβ samples under our experimental conditions. However, we encountered a technical difficulty in separating a defined aggregated species and maintaining the original property because TDP-43 and Aβ both form oligomers. We further found that the inhibition of Aβ fibrillization by TDP-43 only occurs in the early and intermediate stages of Aβ fibrillization, but not in the fibrillar stage and the seeding reaction. The result demonstrated that TDP-43 does not affect mature Aβ fibrils and cannot block fibril growth once the fibril nucleus was added. It also suggests that TDP-43 cannot block secondary nucleation in Aβ fibrillization. For the discrepancy found in the inhibitory effect of TDP-43 on Aβ40 and Aβ42, Aβ42 may not be effectively inhibited by TDP-43 because Aβ42 initially forms several oligomers with few monomers and rapidly fibrillizes38. Furthermore, Aβ40 and Aβ42 oligomerize through distinct pathways38. Freshly prepared Aβ40 predominantly forms monomers38, forms a monomer-added mixture after crosslinking36, and slowly fibrillizes39. By contrast, freshly prepared Aβ42 forms paranuclei37 or tetramers38 in equilibrium with monomer, and rapidly aggregates. Therefore, the potential interaction site and species of Aβ40 and Aβ42 for TDP-43 can vary.Aβ progressively aggregates into amyloid fibril via a nucleation-elongation mechanism. In this study, we found that TDP-43 oligomers affected the conformational change in Aβ and prevented the formation of Aβ fibrils. This condition may be attributed to the amyloidogenic properties of TDP-43 since a similar phenomenon has also been observed in other amyloidogenic protein-protein interaction40 and calpain-cleaved TDP-43 was found in the brain and spinal cord of ALS patients41.In the characterization of the specificity and interaction of TDP-43 and Aβ, we found full-length TDP-43, TDP-43_265, and TDP-43_N-term, not TDP-43_RRM 1 + 2, potently inhibited Aβ fibrillization; however, TDP-43_RRM1 + 2 has strong interaction with Aβ. Since full-length TDP-43 formed oligomers and TDP-43_265 and N-term formed dimeric species, the result might indicate that oligomerization/dimerization is required for the inhibitory activity, where the interaction may be majorly attributed from RRM1 + 2 and minorly, if any, from N-terminal region. Therefore, we hypothesized that TDP-43 mainly interacted with Aβ through RRM domains and required dimeric/oligomeric TDP-43 to inhibit Aβ fibrillization. This inhibition resulted in the retention of Aβ oligomers. TDP-43_265 was likely present because of the calpain cleavage of TDP-43 in the brain of AD patients, considering that calpain is implicated in AD24 and that depletion of TDP-43 in APP/PS1ΔE9 mice decreases the amyloid plaque burden in hippocampus and cortex42. Although we found TDP-43 inhibits Aβ fibrilization in vitro, we suggest that brain inflammation induced by TDP-43 injection leads to an increase of the amyloid plaques in vivo. Our studies showed that TDP-43 plays multiple roles in AD; for example, TDP-43 induces more Aβ oligomers by directly interacting with Aβ, leading to synaptic dysfunction and memory impairment; TDP-43 increases brain inflammation that worsens spatial memory and causes an increase in amyloid burden44. TDP-43 also affects APP metabolism45. These events could occur in the same periods, but they affected AD pathology to different degrees.In the animal studies, we demonstrated that the modification of Aβ aggregation by TDP-43 increased neurotoxicity by impairment of synapse transmission in LTP reduction ex vivo and spatial memory in wild-type mice in vivo. In TDP-43-injected APP/PS1ΔE9 mice, TDP-43 impaired spatial memory and increases Aβ-related pathologies, including amyloid plaque burden, Aβ assembly, and microgliosis. The result was consistent with previous studies showing that TDP-43 overexpression induces neuroinflammation in a lentiviral gene transfer rat model47 and was reported to be an early event in AD and in Down syndrome preceding extracellular Aβ48. The interaction site for TDP-43 and Aβ in cell could be in cytoplasm and/or lysosome. Aβ and TDP-43 have been reported to influence endosomal-lysosomal pathways50 where both aggregates can be cleared by autophagy mechanism52. Extracellular Aβ can be re-internalized and found inside endosomal/lysosomal compartments53. Cytosolic Aβ can also be found without vesicle structure54. Passive leakage along the pathways and active uptake of extracellular Aβ by several cell surface receptors, leading to intracellular accumulation have been reported9. Intracellular Aβ has been reported to bind to several cytosolic chaperons like Hsp70 and small heat shock proteins55, cytosolic enzymes such as SOD156, and directly interact with amyloid binding alcohol dehydrogenase in mitochondria57.We showed that TDP-43 oligomers colocalized largely with intraneuronal Aβ and some with amyloid plaques in APP/PS1ΔE9 mice and AD brain. TDP-43 interacted with Aβ in both the extracellular-enriched and Triton-solution fractions of APP/PS1ΔE9 mouse brain after TDP-43 injection. We suggest that soluble Aβ oligomers in the extracellular-enriched and Triton-solution fractions interacted with TDP-43 since amyloid plaques were retained in GdnHCl fractions. Intracellular Aβ has been observed in both sporadic and familial AD patients33, and Aβ dimers isolated from AD brains impair synaptic plasticity and memory58. These studies have highlighted the importance of specific oligomeric Aβ for memory impairment. Thus, we propose that the spatial memory impairment in TDP-43-injected APP/PS1ΔE9 mice is due to increased inflammation and accumulation of Aβ oligomers, which is considered more toxic than Aβ fibrils and monomers7. However, although we showed that TDP-43 induced both Aβ40 and Aβ42 toxicity in LTP and in water maze study in the injection mice model and demonstrated that both Aβ40 and Aβ42 colocalized in brain of post mortem AD patients, the exact molecular interaction of TDP-43 to Aβ40 and Aβ42 needs to be further investigated to elucidate potential differences resided in Aβ40 and Aβ42. Overall, our results demonstrated that TDP-43 inhibited Aβ fibrillization by interacting with Aβ and exacerbated AD-related pathology.Furthermore, in our TDP-43-injected APP/PS1ΔE9 mice, a specific Aβ assembly hexadecamer is significantly increased. Previous studies showed that injection of Aβ dodecamers impairs the memory of young rats22. TDP- 43_265 was cloned by deletion mutagenesis of full-length TDP-43 with forward primer and reverse primer listed in Supplementary Table 59. The pET14b plasmids were transformed into E. coli strain Rosetta 2 , and the pQE30 plasmids were transformed into E. coli strain M15. All TDP- 43 proteins contain His-tag in the N-terminal region. Full-length TDP-43 and TDP- 43_265 contain extra N-terminal residues MGSSHHHHHHSSGLVPRGSHMLE. TDP-43_N-term and TDP-43_ RRM1 + RRM2 contained extra N-terminal residues MRGSHHHHHHGS. E. coli were grown in LB medium with 50 µg/ml ampicillin at 37 °C to OD600 around 0.4 and induced by 0.5 mM IPTG at 16 oC. After 22 h, the cells were harvested and lysed in 30 mM Tris-HCl buffer, pH 8, containing 500 mM NaCl, 10% glycerol, 1 mM dithiothreitol (DTT), 2% RNase A, 2% DNase I, and protease inhibitor cocktail . The supernatant was collected after centrifugation and loaded onto a Ni- NTA affinity column . The column was first equilibrated using a buffer containing 30 mM Tris, pH 8, 500 mM NaCl, 1 mM DTT, 20 mM imidazole, and 10% glycerol. Proteins were eluted with a step gradient of imidazole in the same running buffer. The purity of His-tagged TDP-43 protein was checked on SDS–PAGE and identified by Coomassie blue staining. Proteins were stored at −20 oC freezer and further dialyzed with 10 mM Tris at pH 8 right before the experiments. The dialyzed protein was centrifuged at 17,000 × g at 4 oC for 30 min to remove all precipitates. Protein concentration was quantified by micro BCA protein assay kit .For TDP-43 proteins, the plasmids used for expression are TDP-43_FL, a pET14b vector containing cDNA of full-length TDP-43, TDP-43_265 (a pET14b vector containing cDNA of TDP-43 aa. 1–265), TDP-43_N-term (a pQE30 vector containing the cDNA of TDP-43 aa. 1–101), and TDP-43_RRM1 + 2 (a pQE30 vector containing the cDNA of TDP-43 aa. 101-265). Full-length TDP-43 was cloned previously60. No additional amino acid was generated. The purified Aβ peptide was lyophilized and stored at −80 oC. Biotinylated Aβ was purchased from Biopeptide Inc. .Recombinant Aβ expression and purification were performed following our previous studyoC. The selected time point samples were collected for ThT measurement at 25 oC.For ThT assay shown in Fig. oC with continuous shaking at 300 rpm to prepare Aβ oligomers or with continuous shaking at 1000 rpm for 24 h to prepare Aβ fibrils. The Aβ species were validated in TEM. TDP- 43 and control buffer were added to Aβ oligomer or fibrils and subjected to ThT assay. For seeding experiment, the 2.5 μM Aβ fibrils solution was added at the beginning of aggregation assay of Aβ at 25 µM. The samples were incubated in a 384-well opaque microtiter plate, sealed with a transparent film, and monitored by a microplate reader  at 25 °C. The ThT signals were measured every hour with a 60-s mixing before the measurement. ThT fluorescence was excited at 442 nm, and the emission spectrum was collected at 485 nm by software SoftMax Pro 6.3 in SpectraMax M5. Data were plotted and analyzed in GraphPad Prism 7.0.For ThT assay shown in Fig. 1 (1:4000 in blocking solution) and anti-rabbit horseradish peroxidase (HRP)-conjugated secondary antibodies .To probe the conformational change of Aβ40 during fibrillization, 2 μL of Aβ samples with and without TDP-43 were collected from different time points from the ThT study shown Fig. The time-course samples collected for CD measurement were prepared in the same condition as for the ThT assay in Fig. 22 but with primary antibody using anti-TDP-43 N-term rabbit antibody . In the end, the grids were incubated with an 18 nm gold-conjugated secondary anti-rabbit IgG antibody  at RT for 1 h. The unbound antibody was heavily washed by high-salt Tween and PBS. The grids were then fixed by 1% glutaraldehyde in PBS at RT for 10 min and washed six times by double-distilled H2O. Finally, the grids were negatively stained using 2% uranyl acetate.Five microliters of TDP-43 proteins or Aβ samples from ThT assay were deposited onto 400-mesh Formvar carbon-coated copper grids  for 1 min. The grids were blotted, washed with droplets of Milli-Q water, and stained with 2% uranyl acetate. The samples were examined with a FEI Tecnai G2 F20 Super TWIN transmission electron microscope with an accelerating voltage of 120 kV. For immunogold labeling, 5 µl Aβ fibrils with TDP-43 was placed on grids for 5 min, then washed, blocked, and probed following previous protocolThe concentration of freshly purified TDP-43_FL and truncation proteins were quantified by Bradford protein assay (Thermo Fisher Scientific) and the same mole number of each variant at 1 μM (200 pmole in 200 μL) was immobilized in 96-well ELISA microplates  by incubation overnight at 4 °C. HFIP and NaOH-treated biotin-labeled Aβ40 was prepared in 10 mM Tris at pH 7.8 to make a series of Aβ solution with concentrations ranging from 0 to 38 μM. After immobilization, the plate was blocked for 2 h at RT with 5% skim milk in TBST . The plates were washed and probed by biotin-Aβ40 solution for 2 h at RT. After wash, the plates were subjected to HRP-conjugated Streptavidin  for 1 h at RT. After another wash, the color was developed by adding 100 μL 3,3, 5,5 -tetramethyl benzidine (Merck Millipore). The reaction was stopped with 100 μL 250 mM HCl and the absorbance was recorded at 450 nm by software SoftMax Pro 6.3 in SpectraMax M5 (Molecular Device). Data were plotted and analyzed in GraphPad Prism 7.0.KD value was obtained by fitting the data using the Data Analysis Software (ForteBio).HFIP- and NaOH-treated N-terminally biotinylated Aβ40 was dissolved in 10 mM Tris, pH 7.8 with 0.005% Tween-20 to make a concentration of 10 μM solution. The sensors used are streptavidin-coated . The sample sensors and reference sensors were also pre-incubated in the same buffer before loading. The biotinylated Aβ40 was immobilized to sensors and then the sensors were subjected to TDP-43_FL or TDP-43 variants solution to probe the interaction between Aβ and TDP- 43 proteins. In general, all steps were performed at 37 °C with continuous agitation at 1,000 rpm. The association and dissociation time were both 300 s. The regeneration buffer was 10 mM glycine at pH 1.5. The sensorgrams were measured with double references (reference buffer and reference sensor) using an Octet Red96 and The ThT assays were stopped by adding SDS-PAGE sample buffer and then the samples without heating were loaded onto a 13.3% Tris/tricine separating gel with 10% and 4% stacking portions. Separated Aβ species on the gel were electrophoretically transferred to a nitrocellulose membrane at 250 mA for 75 min at 4 °C. The membrane was blocked with 5% skim milk in TBST. Aβ samples were probed by 6E10 antibody  and anti-mouse IgG secondary antibody. The signals were visualized by ECL detection kit (Merck Millipore).All experiments were done in accordance with the National Institutes of Health Guideline for Animal Research  and Taiwan Animal Protection Law and were approved by the Academia Sinica Institutional Animal Care and Utilization Committee (IUCAC 16-02-939). C57BL/6 mice were obtained from the National Laboratory Animal Center  and the APP/PS1ΔE9 85Dbo/Mmjax) mice were obtained from the Jackson Laboratory . All of the APP/PS1ΔE9 mice were genotyped using a protocol provided by the Jackson Laboratory. All of the mice were housed (4–5 per cage) at a stable temperature (23 ± 1 °C), humidity 55 ± 5%, and unrestricted access to food and water with a light cycle from 7 am to 7 pm during the experimental period. We used 3-4 mice per group for the electrophysiology study, 5-9 C57/BL6JNarl mice per group and 6–8 APP/PS1ΔE9 mice per group for the Morris Water Maze (MWM), 3 APP/PS1ΔE9 mice per group for the immunostaining staining, 9–10 APP/PS1ΔE9 mice per group for microgliosis staining, and 6–10 APP/PS1ΔE9 mice per group were used for Aβ western blotting.61. The 12-week-old C57BL/6JNarl male mice were anaesthetized by isoflurane and decapitated, then the mice brain was quickly removed and placed into the ice-cold artificial cerebrospinal fluid . The hippocampus was removed and then cut into 450 μm thickness by vibratome . The hippocampal slices were recovered for 2 h at room temperature in a chamber with aCSF, which bubbled with a mixture of 95% O2 and 5% CO2. For extracellular recordings, the hippocampal slices were placed at the center of a MED–P515A/5 (1 mm) probe  with 64 embedded recording electrodes containing with circulating aCSF and 100 μM picrotoxin bubbled with a mixture of 95% O2 and 5% CO2. The fEPSP was recorded from the Schaffer collaterals fibers on the stratum radiatum layer of hippocampal CA1 area by using MED64 multichannel recording system in Neuro- electrophysiology core, Academia Sinica. Test stimuli were given every 30 s (0.033 Hz), and the stimulus intensity was set to produce 40% of the maximum spike-free response. A stable baseline was recorded for at least 30 min before treatment with aCSF containing Aβ, full-length TDP-43, or TDP-43-induced Aβ at indicated concentrations. The samples were prepared following Aβ preparation for ThT assay for Fig. 232 and collected at ~50 h of incubation. After treatment with protein or respective buffer control for 30 min, LTP was induced by theta burst stimulation  given at baseline intensity according to our previous publication61. The fEPSP slope was measured from ~10–90% of the rising phase using a least squares regression. The data were quantified by normalization to the baseline slope and mean ± SEM are shown. Repeated two-way ANOVA was used for statistical analysis. The respective buffer control was performed on the same mice but different brain slice to exclude individual bias.Hippocampal slice for field excitatory postsynaptic potential (fEPSP) was prepared as previously describedFive-month-old male C57BL/6JNarl mice or APP/PS1ΔE9 male mice were anaesthetized by intraperitoneal injection of a mixture of tranquilizer , analgesics . The C57BL/6JNarl mice received bilateral intrahippocampal injection of 2 μL recombinant Aβ40 or Aβ42 (25 μM), full-length TDP-43 (0.25 μM), or TDP-43-induced Aβ (25 μM Aβ40 or Aβ42 with 0.25 μM TDP- 43). APP/PS1ΔE9 mice received bilateral intrahippocampal injection of 2 μL recombinant full-length TDP-43 (2.5 μM). The stereotaxic coordinates of the injection site are in relation to bregma as follows: Posterior 2 mm; mediolateral 1 mm; ventral 2 mm. The injection needle was slowly approached to the desired depth and the mentioned protein was injected using a microsyringe . The needle left in place for an additional 5 min to limit the diffusion of the injected protein.The MWM was performed in a custom-made circular pool with a diameter of 154 cm and a wall height of 60 cm, which was filled with opaque water (diluted milk) at a temperature of 20 ± 2 °C and depth of 32 cm. During the pre-training trials, the circular escape platform made of transparent Plexiglas (diameter 13 cm) was emerged 0.3 cm above the water surface and kept location constant for 2 days. In the training trial, the escape platform was submerged 0.5 cm below the water surface and the location of the hidden platform was moved to another place and kept constant for five days. Animals were given a session training  per day during pre- and training trails. Each session consisted of four swim trials  with different quadrant starting positions for each trial. After the last day of training, the mice were given a probe test. During the probe test, animals were placed in the center position of the pool, and the mice were allowed to swim for 60 s without the platform presented. The whole process was recorded by a charge-coupled device camera and the escape latency , time spending in target quadrant of probe test, path length and swim speed (cm/s) were analyzed by EthoVision video tracking system .The mice were anesthetized by intraperitoneal injection of a mixture of tranquilizer , analgesics  and perfused from the left ventricle with ice-cold PBS, and their brains were quickly removed. The left hemispheres were stored in −80 °C immediately. The right hemispheres were fixed in 10% formalin at 4 °C for frozen section and subjected to immunostaining. The brain was cut into an average of 130 pieces of 30-μm coronal sections. For analysis of amyloid plaque burden or TDP-43 oligomer signals, the brain sections were measured in every 12th section of the brain from anterior (stereotaxic reference: bregma 2.5 ± 0.2 mm) to posterior part (stereotaxic reference: bregma −6.5 ± 0.2 mm).33. For extracellular-enriched protein fraction, 25% (w/v) lysis buffer containing 50 mM Tris-HCl (pH 7.6), 0.01% NP-40, 150 mM NaCl, 2 mM EDTA, 0.1% SDS, protease and phosphatase inhibitor  was used to homogenize the frozen brain tissues with a 1 ml syringe, gauge 19 needle. The homogenates were centrifuged for 10 min at 1,000 × g and the supernatant was collected. The pellet was washed by repeating the homogenizing step again. For Triton-soluble fraction, 25% (w/v) lysis buffer containing 50 mM Tris-HCl (pH 7.6), 150 mM NaCl, 1% Triton X-100  was added to the pellet from the previous centrifugation and pipetted to homogenize the pellet. The homogenates were further centrifuged for 90 min at 16,000 × g and the supernatant was collected. The pellet was washed by repeating the homogenizing step again. For guanidine HCl soluble fraction, 25% (w/v) lysis buffer containing 5 M guanidine HCl (GdnHCl) in 50 mM Tris-HCl  was added to the pellet obtained after centrifugation of the Triton-soluble fraction and pipetted to homogenize the pellet.The left hemispheres were collected, homogenized, and subjected to different fractionations following previous literature63. In short, coronal sections (30 μm thickness) were mounted on poly-l lysine coated slides . The coronal section was antigen retrieved by citric acid buffer  at 80 °C for 30 min, then blocked with 3% BSA in PBS containing 0.5% Triton X-100 for 1 h. For immunofluorescence, the coronal section was probed with the primary antibodies: a mixture of 6E10  and 4G8  or polyclonal TDP- 43 oligomer antibody, poly TDP-O22 (1:1000). The secondary antibody used for 4G8 and 6E10 is goat anti-mouse Alexa Fluor 488  and for poly TDP-O is goat anti-rabbit Alexa Fluor 594 . Fluorescence images were taken by Aperio FL Digital Pathology Scanner . The signals were measured by ImageJ  and a given background threshold was subtracted. The background intensity threshold was fixed and applied to all sections. For immunohistochemistry, rabbit anti-ionized calcium-binding adaptor molecule 1  antibody was used. The Iba1 signal was then developed using an immunohistochemistry kit  and the secondary antibody  provided in the kit. The 3, 3´-diaminobenzidine (DAB) was used as the substrate to develop immunohistochemistry signal. To analyze protein expression level, the slide images were taken by Aperio AT2 Digital Pathology Scanner . All of the quantitative signals were obtained by calculating the signal intensities within the area that were higher than a background threshold with the aid of ImageJ 1.8.0_60 . To prevent the injection injury effect, the brain slice from the injection side anterior to posterior 0.5 mm would not be used for quantification. The intensity threshold of background was fixed and applied to all images.The detailed procedure for immunohistochemistry was described in previous studiesCo-IP was performed to examine the interaction between Aβ and TDP-43. The buffer and TDP-43 injected APP/PS1ΔE9 mice brain samples were taken for analysis as described in brain tissue preparation and fractionation. The extracellular-enriched, Triton-soluble, and GdnHCl fractions were taken for BCA assay to measure the total protein concentration. Two hundred micrograms of the sample was used for co-IP and 100 µg for the input. The fractions were diluted with filtered TBS-T to a total volume of 200 µl. Two microliters of mouse monoclonal 4G8 antibody against Aβ aa. 17–24  and 2 µl of mouse monoclonal 6E10 antibody against Aβ aa. 1–17  was added to the samples for IP study. Mouse IgG2a  was served as IgG control for this experiment. The samples with the antibodies were mixed overnight in a vertical rotator . On the second day, 10 µl of Protein A Mag  was added to the sample and mixed in the vertical rotator for about 4 h in 4 °C. Then, the samples were washed with TBS-T for three times in a magnetic rack  and eluted with a 6x loading buffer , then heated for 10 min at 95 °C. Next, the samples were subjected to western blot with gradient gels  in mini gel tanks  using MES running buffer  and transferred to PVDF membrane . The membrane was blocked with 5% non-fat milk and the TDP-43 antibodies, a mixture of rabbit polyclonal TDP-43 antibody  and TDP-43 C-terminal antibody , were applied for detection. The images were obtained by Imagequant LAS4000 system .Western blot was performed to observe the changes in Aβ assembly after injecting TDP-43 to the APP/PS1ΔE9 mice. The concentration of the extracellular-enriched fraction and Triton-soluble fraction were determined and adjusted to the same protein concentration (48 μg in 20 μL). The samples were mixed with 6x loading buffer and heated in 95 °C for 10 min, then loaded into a 4–15% Tris-glycine gel and resolved at 100 V for 120 min. The separated proteins were transferred to a PVDF membrane  and blocked with 5% non-fat milk. The mouse monoclonal 6E10 antibody  and mouse monoclonal 4G8 antibody  were mixed and used for Aβ detection. A mouse monoclonal GAPDH antibody  was used for loading control. The secondary antibody used for 6E10/4G8 mixture is goat anti-mouse IgG-HRP  and for GAPDH is goat anti-rabbit IgG-HRP . Immobilon Western Chemiluminescent HRP substrate  was used for developing. The detection was carried out with Imagequant LAS4000 system  and analyzed using ImageJ .2O. Then, the specimens were immersed in citric acid buffer  and heated for antigen retrieval at 80 °C for 30 min, and then blocked with 3% BSA in PBS with 0.5% Triton X-100 for 1 h. To observe the amyloid plaque and TDP-43, TDP-43 C-terminal antibody , poly TDP-O1 (1:1000), Aβ antibody / 4G8 ), Aβ40-specific antibody 11A50 , Aβ42-specific antibody 12F4  and neuronal marker MAP-2  were applied to the slides for 2 h in room temperature. After that, the primary antibodies were washed out by PBS/0.5% Triton X-100 and probed with the secondary antibodies for 2 h in room temperature. The secondary antibodies used were goat anti-rabbit Alexa Fluor 594  for TDP-43 C-terminal antibody and poly TDP-O, goat anti-mouse Alexa Fluor 488  for Aβ, and goat anti-guinea pig Alexa Fluor 647  for MAP-2. Subsequently, the nuclei were stained with Hoechst Stain solution . Lastly, glycerol gelatin  was applied to mount each tissue slides. After the staining procedure, the human brain slide images were captured by Aperio CS2 Digital Pathology Scanner (Leica Biosystem).All of the human tissue-related procedures and usage were approved by the Human Subjects Research Ethics, Academia Sinica, Taiwan. Participants were recruited and consented in the Alzheimer’s Disease Center at University of California, Davis, Sacramento, California. To investigate the interaction of the TDP-43 oligomer and Aβ in Alzheimer’s disease patient, the 5 μm-thickness paraffin-embedded sections were deparaffinized with xylene. To remove xylene and rehydrate the slides, the specimens were washed through graded ethanol in water and ending with pure ddHFurther information on research design is available in the Supplementary InformationPeer Review FileReporting Summary


A stable and magnetic graphene oxide (GO) foam–polyethyleneimine–iron nanoparticle (GO–PEI–FeNPs) composite has been fabricated for removal of endocrine disruptors—bisphenol A, progesterone and norethisterone—from aqueous solution. The foam with porous and hierarchical structures was synthesized by reduction of graphene oxide layers coupled with co-precipitation of iron under a hydrothermal system using polyethyleneimine as a cross linker. The presence of magnetic iron nanoparticles facilitates the separation process after decontamination. The foam was fully characterized by surface and structural scanning electron microscopy, Fourier transform infrared spectroscopy, Raman spectroscopy and X-ray photoelectron spectroscopy. The foam exhibits a high adsorption capacity, and the maximum adsorption percentages are 68%, 49% and 80% for bisphenol A, progesterone and norethisterone, respectively. The adsorption process of bisphenol A is explained according to the Langmuir model, whereas the Freundlich model was used for progesterone and norethisterone adsorption. Endocrine disruptors are substances affecting the primary communication network of the body, which is responsible for controlling multiple body functions. This network is named the endocrine system and includes different organs such as ovaries, testes, adrenal glands, pituitary gland, thyroid, and the pancreas. These chemicals harm human and wildlife by causing tumors, birth defects and disorders in development of the fetus. In addition to these effects on the human body, these disruptors can also mimic or interfere with the function of hormones in the body due to similarity in their structure and activity by influencing sexual development of humans or wildlife. The best example is feminization of males or masculinization effects on females ,2,3. One2/Ti to degrade BPA in a soil matrix [−1, an issue remains in terms of recyclability [Various techniques have been developed throughout the years to adsorb and remove BPA and other endocrine disruptors from water. Yuan and Al used composite electrodes such as Pd/Ti and RuOl matrix ,5. Anothlability ,7,8.2.g−1, outstanding mechanical properties with a high Young’s modulus (1 TPa), a high thermal conductivity (5000 W mK−1) and an electron mobility higher than those of most semi-conductor materials (2.5 × 105 cm2 V−1 s−1) [Graphene is one of the most studied carbon nanomaterials, discovered in 2004 by Novoselov and Geim . This twV−1 s−1) ,12.One method to produce high-quality graphene is chemical vapor deposition (CVD); however, this method only gives a few layers of graphene. Therefore, researchers have developed alternative synthesis methods for large-scale production of graphene via chemical exfoliation of graphite. Multiple synthesis paths have been developed since the 19th century, starting with Brodie who was able to oxidize graphite  and thenMany applications have been developed based on graphene material such as preparation of nanocomposites with polymers fillers, e.g., polyvinyl alcohol (PVA), poly(methyl methacrylate) (PMMA) or polyethyleneimine (PEI) ,18,19. TIn this paper, fabrication of a magnetic reduced graphene oxide 3D foam is presented. Graphene oxide was synthesized using a modified Hummers method. The composite material was fabricated using PEI as a polymer binder and iron nanoparticles under hydrothermal condition. The iron nanoparticles (FeNPs) were included in the composite material to introduce magnetic properties. After synthesis, the material was characterized by scanning electron microscopy, X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD) and Raman spectroscopy. The foam is structurally stable and exhibits magnetic properties. The material was used to adsorb endocrine disruptors such as BPA, progesterone and norethisterone, and a comparison of adsorption behavior between the former molecules is presented. Evaluation of the adsorption ability of the GO composite foam toward endocrine disruptor compounds was carried out using UV–VIS spectroscopy. It is capable of attracting and adsorbing large molecules through π–π stacking, van der Waals forces or hydrogen bonding. This is the first attempt to adsorb high molecular weight molecules with a graphene-based membrane in an aqueous medium, showing that these types of material are good candidates for these types of application.−1), iron nanoparticles (FeNPs) [Natural flakes of graphite with an average particle diameter of 300 μm (99 wt% purity), sulfuric acid (98 wt%), hydrogen peroxide (30 wt%), phosphoric acid, potassium permanganate, hydrochloric acid (37 wt%), ethanol (100 wt%), ethyl ether, PEI  , bisphen2SO4 and 40 mL of H3PO4 were put into a 1 L flask. The mixture was stirred for 30 min at 55 °C. After this step, 18 g of KMnO4 was added in small portions to prevent rapid temperature rise. The mixture was stirred continuously for 4.30 h and the temperature was kept at 55 °C. Several ultrasonication periods of 30 min were applied during the stirring time to exfoliate graphite oxide into graphene oxide sheets [2 into soluble MnSO4 by adding it to a mixture of H2O2  and water (600 mL) at 0 °C and stirred. The resulting suspension had a bright yellow color. This suspension was further cleaned with water, and a mixture of water, 37% HCl and 100% ethanol. The mixture was then washed with ethyl ether and filtrated on a Teflon filter. The obtained GO is dried in an oven at 30 °C under vacuum. Then the GO was resuspended in water at a concentration of 1.76 mg mL−1 and the obtained yellow-brown aqueous suspension of GO was stored at room temperature for further use. Graphene oxide was prepared using natural graphite powder through a modified Hummers method . In a tye sheets . The susFabrication of 3D porous GO–PEI–FeNPs was adapted from Han and co-workers . Next 5 The GO–PEI–FeNPs composite was imaged with a JEOL JSM7600F  scanning electron microscope (SEM). Raman spectroscopy was conducted using a Renishaw InVia Raman microscope  with a 488 nm laser to confirm the integrity of the GO structure. Attenuated total reflectance–Fourier transform infrared spectra (ATR–FTIR) were recorded with a Nicolet 6700  to identify bonding between PEI and GO. X-ray diffraction (XRD) with a Bruker D8 Advance (D-5000)  was performed to study the phase composition of the iron nanoparticles. The chemical composition of the sample was investigated by X-ray photoelectron spectroscopy using XPS . The adsorption behavior of endocrine disruptors from the GO–PEI–FeNPs composite was studied by measuring unabsorbed amounts of analyte in solution via UV–VIS with a LAMBDA 750 UV/Vis/NIR spectrometer .i and Cf (mg∙L−1) represent the initial and final concentrations, respectively, at a determined time, t, of BPA, progesterone and norethisterone aqueous solutions.The adsorption capacity of the foam for BPA, progesterone and norethisterone was studied in aqueous solution. In a typical experiment, the GO–PEI–FeNPs foam was immersed in a beaker containing 100 mL of 15 ppm of each analyte solution: BPA, progesterone and norethisterone. Adsorption was carried out at room temperature. The solution was sampled at various adsorption times and the adsorption ability of the foam was quantified with UV–VIS spectroscopy. The effects of immersion time and concentration of the analyte were studied by calculating the percentage of compounds (%) adsorbed by the graphene-based membrane using Equation (1) for each GO–PEI–FeNPs foam immersion into a specific analyte solution at a determined time.max) for each analyte through non-linear regression analysis. The k’ is a constant related to desorption [As the adsorption of analyte onto GO–PEI–FeNPs foam obeys a binding isotherm, the % removal for each set of incubations was plotted vs. the time (t) of each incubation. Later the rectangular hyperbola function form in Equation (2) was used to determine the maximum % adsorbed compounds  ratio is proportional to the number of structural defects, this ratio was evaluated as 0.81, 0.97 and 0.98 for GO, GO–PEI and GO–PEI–FeNPs, respectively. The increase in ID/IG ratio with addition of PEI and FeNPs into the foam matrix involves a reduction of the graphene oxide material. Reduction of the GO nanosheets in the foam was confirmed by comparing the ATR–FTIR spectra of GO, GO–PEI and GO–PEI–FeNPs  and (4) and their linear equations are shown in Equations (5) and (6):Langmuir model:e is the adsorption capacity at equilibrium, K is the Freundlich constant related to the adsorption capacity, n is the adsorption intensity, qmax (mg∙g−1) indicates the saturated adsorption capacity, b (L∙mg−1) is the Langmuir constant related to the adsorption free energy and Ce is the concentration at equilibrium [max, b, K and n are found by linear regression analysis:Freundlich model:ilibrium ,33,42,432 for BPA follows the Langmuir adsorption model. The constant n from the Freundlich model gives information on the adsorption capacity. In the case where n = 1, the adsorption is linear, but if n < 1 then the adsorption is governed by a chemical process, and finally if n > 1 then the adsorption is governed by a physical process [2) regarding the Freundlich model and different values of n. Progesterone has a n value < 1, suggesting that adsorption involves a chemical process. However, norethisterone has an n value higher than 1, indicating that this hormone exhibited favorable physisorption behavior on the GO foam.  process . In the  process . Progest2 of graphene and the H-bonding of the different remaining oxygenated groups present on the graphene surface, which agrees with previous studies [In this paper, a magnetic graphene-based foam was prepared. The composite material is stable and presents a macroporous structure which helps adsorption of large molecules with a significant removal percentage, more than 80% for some contaminants. The membrane had better affinity with BPA and norethisterone compared to progesterone due to different interactions occurring between the Csp studies . The mag


Introduction: Giant slalom is the core discipline of alpine skiing, and each race has its own specific course and terrain characteristics. These variations may explain differences in the speed and time per turn profiles, which are essential for performance development and injury prevention. This study aims to address the differences in course setting and steepness of the different course sections (flat—medium—steep) and compare them to the performance parameters among young  and older  male athletes.Methods: The study examined a total sample size of 57 male athletes; 7 from elite level, 11 from U21, 13 from U18, 6 from U16, 13 from U14, and 7 from U12. The athletes wore a portable global navigation satellite system (GNSS) sensor to extract performance parameters. The course profiles and gate positions of nine runs were measured with differential GNSS. The runs were divided into flat, medium and steep sections. From the performance parameters  and the course setting variables, the mean value per section was calculated and used for the further analysis.Results: In total, 192 run sections from 88 runs were recorded and analyzed. Comparisons between course settings in young and older classes showed no significant differences. However, the turning angles and horizontal gate distances were smaller in flat sections. Average speed (49.77 vs. 65.33 km/h) and time per turn (1.74 vs. 1.41 s) differed significantly between young and U21/elite categories. In medium terrain sections U21 and elite athletes spent more time in the gliding phase compared to all other athletes.Discussion: It seems to be a reasonable that, given similar course setting and steepness, speed increases concurrently with the technical and tactical skills of the athlete. Moreover, the finding that the elite athletes spent more time in the gliding phase could be crucial for understanding technique and performance development in young athletes. The four main disciplines of the World Cup of Alpine Ski Racing are slalom, giant slalom (GS), super-G and downhill. Because GS is the core discipline of alpine skiing, it was the exclusive focus of this study. Each race has its own specific course and terrain characteristics regulated by the International Ski Federation (FIS). Nevertheless, the course setting can vary greatly since the FIS only defines certain boundaries, such as the number of gates and vertical drop (VD). For example, the horizontal distance between two successive gates is not defined and appears to increase with terrain inclination  encompasses the number of directional changes for elite races  and Fédération Internationale de Ski (FIS), The National Federation of Switzerland has established specific rules regarding the course setting for young athletes. Before entering the elite competition, skiers are divided into the following age groups: U12, U14, U16, U18, and U21. It should be noted that there are no differences in course setting applied to these groups  and Swiss-Ski, In addition to injury prevention, a progressive transition for young athletes to the elite level is important; therefore, specific data on each age category are necessary for coaches and race organizers. Since course setting has a major influence on the athlete's speed, it is essential to thoroughly examine these characteristics  according to the aforementioned rules in young vs older athletes. Neither a study which focuses on the differences on the performance  of young vs. older athletes. Therefore, the aim of the present study was to identify differences in sections of the runs  and performance parameters  among young and older athletes. The application of these procedures is predicted to improve knowledge about performance development and injury prevention in the context of GS.Measurements were taken for six age levels, which included a total sample size of 57 male athletes; seven were from the elite level , 11 were from the U21 level, 13 were from U18, 6 were from U16, 13 were from U14, and 7 were from U12. The elite skiers were born in 1992 ± 2.18 y and had a mean world ranking of 49 ± 69.02 . In accordance with the rules of the international federation  and Fédération Internationale de Ski (FIS), The measurements were taken at three different locations during the 2018–2019 and 2019–2020 winter seasons. In Hoch-Ybrig  at the Swiss National Championships on March 23–24, 2019 and a FIS race on January 14, 2020. The VD for this hill is officially recorded as 295 m. In Les Diablerets  at a FIS race on February 8, 2020 with a VD of 340 m. In Meiringen  at regional races from January 19, 2019 and January 26, 2020 and the VD for this hill is 264 m. With the exception of the race in Meiringen on January 26, 2020, all races consisted of two runs. Each gate was measured with a global navigation satellite system (GNSS) device in differential mode , minimal turn radius (m) and time of the end of the turn (s)] were calculated. Based on these defined points, the per-turn calculations could be conducted for the following variables: (a) the decrease in speed during the initiation phase and (b) the speed increase from the minimal turn radius to the beginning of the next turn. Both were expressed as a percentage of the start speed in the specific turn.In total, 88 runs were measured, and each run was analyzed as an individual measurement. Twenty-six athletes performed one run, 31 athletes performed two runs. At each of the nine races, the track profile was analyzed. According to conspicuous terrain transitions the sections of the run were divided into three different categories  .The Levene's test assessed the equality of variances. Afterwards, for all results, a one-way analysis of variance (ANOVA) was performed to identify any significant differences. Finally, as In total, 192 run sections from 88 runs were recorded and analyzed. Comparisons in course setting between JO and the older classes were only made in the medium sections, due to the different number of observations. No significant difference was found between the JO and the older group.The average values of the different section categories for all competitions are shown in Regarding U18, U21 and elite competitions in steep terrain ; the gatThe JO group only had medium terrain sections and in order to obtain comparability among the younger and older athletes, they are compared in the medium terrain section. The older athletes are compared in all three sections.The time needed per turn  differedThe average speed range  was betwSpeed gain and speed decrease between two turn phases are displayed in Relative time spent in the different turn phases of all groups are shown in Zoomed in on the older group, no significant differences were found in the initiation phase in the three terrain sections . In the The main finding of the study was that average course settings in young classes  did not differ in comparison with the older classes . However, compared to the medium and steep sections, the turning angles and horizontal gate distances were shorter in the flat sections. Average speed for the medium terrain section was between 49.77 km/h (U12) and 65.33 km/h (U21) and time per turn differed significantly between 1.74 s (U12) and 1.41 s (elite). Additionally, differences were found in the mean speed and turn phase parameters, more precisely in the gliding and completion phases. In medium terrain sections U21 and elite athletes spent more time in the gliding phase compared to all other athletes.A “high skiing speed” is commonly called a major course-related injury factor  should be more clearly differentiated in order to achieve a skill transfer and to reduce injury risk. Furthermore, it can be discussed whether interventions should be taken to adjust the course setting in both levels. In the elite's course setting our results support Spörri et al. , that a Gilgien et al.  measuredThe horizontal gate distance for the older groups in flat conditions (5.81 ± 0.51 m) was smaller than in medium (6.89 ± 0.35 m) and steep conditions (7.36 ± 0.55 m), where gates were set with a larger horizontal distance. The turning angle is described as the gate-gate distance, the vertical gate distance and the horizontal gate distance. Since there were neither significant differences in the gate distance, nor in the vertical gate distance, it can be stated that the turning angle is mainly influenced by the horizontal distance.Besides differences in the course profile, the time the athletes needed per turn in the medium terrain section decreased with higher age groups . The U12The difference in speed gain and speed decrease in the medium terrain section was not significant between any group but there seemed to be a tendency in elite athletes to brake less hard to the center of the turn and then take more speed out of the turn than all younger athletes . HoweverIt is notable that the elite athletes did not have the highest speed of all groups in the medium terrain section. The lowest average speed was reached by the U12 athletes, the highest speed by the U21 athletes and in between there was an increasing trend . ImportaThe changes in speed during turns in the medium terrain section was not significant between the groups . NeverthThe gliding phase  was longThis study is the first to calculate tactical parameters, such as relative time in each turn phase, in this way. Spörri et al. defined the segments of the turn differently (Spörri et al., All terrain sections in the course of the JO group were labeled as medium which restricted us to make comparisons between JO and the older groups in the flat and steep terrain sections. Overall, the findings of this pilot study should be confirmed by observing identical athletes in a repeated measurement design. This would lead to a greater number of measurements and allow a turn by turn analysis to confirm these outcomes.Course setting and performance parameters were measured with a GNSS device. The use of a geodetic, multi-frequency receiver providing differential position solutions could result in greater accuracy. Due to the limited amount of time between the runs and the time-consuming aspect of acquiring data for the course setting parameters, this was not applicable in the present study. Gløersen et al.  comparedThe current study showed no differences in course setting between young and older groups. However, differences were found in the mean speed and turn phase parameters, more precisely in the completion and gliding phases. Results of this analysis form a basis to critically discuss the course setting, because they directly influence relevant performance parameters like speed and turning angles in the different age categories. Additionally, steepness influences the tactical strategy of young and older athletes in GS, which is important within the context of skills development. The tactics used within a turn were different between young and older athletes which gives coaches new areas to work on with their athletes. Moreover, the finding that the older athletes spent more time in the gliding phase could be crucial for understanding technique and performance development in young athletes.The datasets generated for this study are available on request to the corresponding author.The studies involving human participants were reviewed and approved by swissethics. Written informed consent from the participants' legal guardian/next of kin was not required to participate in this study in accordance with the national legislation and the institutional requirements.SL and SG advised in planning the experimental setup and selection of the methods and materials. BB and MG did the YOUNG experiment. BB and RJ carried out the ELITE experiment. BB and RJ wrote the manuscript with the help of MR. FO did the main part of the data analysis. MR and SL supervised the project. BB and RJ contributed equally to this manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Notably, carbonaceous species, highly interconnected to MOS nanoparticles, enhance the sensor responses by (i) increasing the surface area and the pore content, (ii) favoring the electron migration, the transfer efficiency (spillover effect) and gas diffusion rate, (iii) promoting the active sites concomitantly limiting the nanopowders agglomeration; and (iv) forming nano-heterojunctions. Herein, the aim of the present review is to highlight the above-mentioned hybrid features in order to engineer novel flexible, miniaturized and low working temperature sensors, able to detect specific VOC biomarkers of a human’s disease.Nowadays, the detection of volatile organic compounds (VOCs) at trace levels (down to ppb) is feasible by exploiting ultra-sensitive and highly selective chemoresistors, especially in the field of medical diagnosis. By coupling metal oxide semiconductors (MOS e.g., SnO The remaining small fraction consists of more than 1000 different volatile organic compounds (VOCs) at parts per million (ppm) to parts per trillion (ppt) [Wearable electronics is expected to be one of the most active research areas in the near future. Hence, materials possessing elevated electronic, optical, and mechanical features alongside desired flexibility and lightweight are required ,2. Thus,on (ppt) ,13. Compon (ppt) . Alongsi2 [3 [2 [In this context, the development of novel solid-state sensors for the selective detection of ultra-low concentrations of specific gas molecules has become increasingly mandatory and more feasible due to the recent progress in nanofabrication approaches, which are capable of providing atomic-level control of the surface composition in high surface-area/porosity detectors . Common 2 ,29,30, Z2 ,32, WO3 2 [3  and TiO22 [3 [2 ,35 have 2 [3 [2 ,37, scar2 [3 [2 ,38 repre2 [3 [2 ,40, thei2 [3 [2  and/or t2 [3 [2 ,41 can bIn recent years, graphene and its derivatives, such as like pristine graphene (PG), graphene oxide (GO) and reduced graphene oxide (RGO), have been reported to enhance sensing properties ,42,43. HThere are already several reviews aimed at highlighting the recent advancements in gas sensors based on functional materials, such as conducting polymers , 2D compAlong with the noteworthy experimental outcomes in terms of enhanced sensitivity, selectivity and room temperature operating conditions, mechanisms underneath the sensing behavior will be thoroughly described for each class of carbon-based supports. Finally, the remaining challenging issues to develop next-generation flexible sensors for wearable technology will be also touched on.2, H2O etc.) or an electron donor . Moreover, the interactions between graphene sheets and the adsorbates could vary from weak Van der Waals to strong covalent bonds [Over the past few decades, the research interest in graphene materials has drastically risen and a plethora of studies about its use in several applications have been reported so far ,47,48. Ant bonds . Thus, ant bonds ,26). In nt bonds ,53 do en2O3 nanoparticles on graphene substrate, tailoring the G content in the MOS matrix. In particular, the α-Fe2O3@(2 wt%) graphene exhibited a three-fold higher response to 1000 ppm of ethanol than the pure iron oxide material, when operating at 280 °C. In both cases, very short response and recovery times within seconds were recorded, resulting in very useful chemoresistors for practical applications. The authors ascribed this sensing enhancement to several reasons: (i) the high surface area in a 2D network that may facilitate the diffusion of ethanol molecules, thus improving the reaction with surface adsorbed oxygen, namely ionosorption model [2O3; (iii) the graphene outstanding electrical conductivity resulting in quick electron spreading in the semiconductor surface, showing faster response and recovery times; (iv) finally, graphene might create a Schottky contact at the interface with MOS nanoparticles, favoring α-Fe2O3 to G electron migration. As such, an enhancement of the sensing performances was attained. Always considering alcohols as target molecules, Qin et al. [3-graphene composite prepared through a facile three-step synthetic route comprising the formation of SrWO4/graphene oxide (GO) precursor, its transformation into WO3/GO by acidification, and the further photoreduction to WO3/graphene through UV irradiations. After depositing the as-obtained powder on an alumina tube with gold electrodes, the nanocomposite was tested for different ppm concentrations of alcohols at operating temperatures from 317 to 372 °C. They clearly evidenced that the gas response of the WO3/G nanocomposites is considerably better than those relative to pure WO3 and WO3/GO. Moreover, WO3/G did not show any responses to interfering species such as acetone and gasoline, resulting in a promising selective chemoresistor. Its enhanced features may be ascribable to two factors: the improved conductivity related to the presence of graphene, which is highly conductive and therefore it leads to a low signal noise; secondly, since graphene formed parallel layers, the gas diffusion can occur through channels of its slit-shaped pores, providing more active sites for the sensing reaction.Liang et al.  describeon model ,51,54;  was prepared, in which graphene aerogel (GA) was adopted as a macroporous substrate. Tungsten trioxide material was also adopted by Zhao et al.  for the 3 nanoparticles were homogenously coated on both sides of graphene sheets through a solvent evaporation-induced self-assembly method using a diblock-copolymer as a templating agent. The resultant nanocomposites possess well-interconnected graphene networks covered by mesoporous WO3 layer  or the recovery (ca. 70 s) curves are very sharp denoting quick sensing response, good sensor reversibility and stability. In addition, the signal intensity is much greater for the hybrid mWO3@GA, thus demonstrating that it is the best performing material towards acetone molecules with respect to other VOCs. This improvement is stated to be mainly due to the structure and composition of the chemoresistor. In the mWO3@GA composite, the graphene aerogel forms 2D graphene sheets that are highly conductive, boosting both the electron transfer efficiency and the electron transfer rate. In addition, the high specific surface area and the interconnected regular mesopores would be beneficial to the surface acetone adsorption/desorption, improving the sensing recovery features. Moreover, in the hybrid structure, many additional active sites, such as oxygen vacancies, can be present, thus enhancing the sensing properties. Zhang et al. [a/Rg of about 13, where Ra and Rg are the material resistances in air and with the target gas) to 100 ppm acetone, at the optimal operating temperature of 280 °C to two-times higher with respect to that of pure zinc oxide. Furthermore, 2) species. For the improved sensing performances, the authors hypothesized that the key role is played by, once more, both the very high graphene specific surface area (of 2600 m2 g−1) that could lead to a greater amount of surface active sites for the gas adsorption, and the enhanced electron transfer thanks to the presence of graphene material.Mesoporous WOg et al.  investig2 nanopowders were loaded with different amounts of graphene to unveil the optimal ratio. The presence of G smoothly enhanced the specific surface area since, with its increase, the surface parameter proportionally rose from ca. 100 to 112 m2 g−1. Then, the powders were deposited by spin coating on Au/Al2O3 substrates to evaluate their sensing properties towards acetone molecules. The obtained sensing films showed a significant high thickness of around 12–18 μm  ,41. Due 2O3 nanorod arrays (NRAs) on graphene oxide (GO) sheets, resulting in flexible 3D nanostructures. High-magnification SEM and TEM images  reported in −1 and C–O–C (epoxy) stretching modes at 1052 cm−1; furthermore, the Fe–O vibrational absorption band at 560 and 477 cm−1 are clearly observable. In addition, Raman spectra (−1) and G (~1594 cm−1) bands ascribable to the breathing mode of the k-point photons of A1g symmetry and the E2g vibration mode in GO. Notably, for the Fe2O3–GO (8:1), the relative D/G intensity ratio (ca. 1.07) is slightly higher than that of GO (0.94), confirming the more disordered structure of the nanocomposite, which may be due to the insertion of iron oxide nanoparticles into the GO nanosheets. Finally, the specific surface area of Fe2O3–GO (115 m2 g−1) was around three times greater than that of pure iron oxide. 2O3–GO ratios towards ethanol (at 260 °C), resulting in 8:1 the best sensing material. The authors suggested that the improved performances are strictly connected, once more, to the larger surface area and incremental active sites. Hence, the results reveal that GO is crucial to improve the final gas sensing.In addition, in Jia’s et al. work , the aut spectra h exhibit2 using the one-step electrospinning technique and GO–SnO2 nanotubes (NTs) by dipping SnO2 NTs into a GO solution followed by a suitable annealing treatment. HRTEM images along with the relative Selected Area Electron Diffraction maps of the hybrid sample revealed the effective GO wrapping on the surface of the SnO2 NTs  towards 100 ppm of ethanol with an optimum working temperature of 300 °C in dry atmosphere. A slight decrease in the sensor signal (ca. 52) was obtained in wet atmosphere, performing better than pristine tin dioxide nanotubes. Furthermore, it is very selective towards ethanol with respect to other gaseous species  from different physico-chemical points of view. The structural analyses reported in 2 nanoparticles. Moreover, sensing tests towards ethanol species showed that 16:1 ratio is the optimal one in terms of sensitivity, higher signals intensity, good response linearity by reducing the VOC concentration @GO, and detection at lower operating temperatures .Moreover, in their work, the influence of GO on the ethanol vapor detecting performance of SnO species f. The au species g, highlii et al. . The autntration j,k, even2 nanofiber/nanosheets (NF/NSs) synthesized by electrospinning technique followed by a hydrothermal step  to unravel the possible boosted selectivity of the prepared compounds towards aromatic species. A fine tuning of the Ti content into a SnO2 matrix was obtained, as clearly represented in the XRD patterns, resulting in an increased crystallinity due to a rise in particle size attained at high Ti content, i.e., at the phase transition from cassiterite-like to rutile-like crystal structure  towards 100 ppm of acetone  or on both sides of ZnO-NR (GO/ZnO-NR/GO), like a sandwich. The morphology of the as-obtained materials was deeply studied by SEM analysis. Particularly, from the cross-section image in  acetone h. Moreov acetone j. Remark acetone k. Theref acetone m. IndeedAmong the strategies for developing high-performance sensors, the use of reduced graphene oxide (RGO) can improve the final sensing performances, such as increased sensitivity, selectivity, room temperature operating conditions and low cross-sensitivity to humidity (one of the main interfering species in humans’ breath) ,42,49,85For instance, concerning alcohols detection, Modenes-Junior et al.  succeede+) accumulation layer near the material surface  improved the selectivity of the sensors to ethanol. Since the VOC selectivity is directly connected to the receptor function of the MOS surface, the presence of ideal RGO contents might change the reactivity of the material surface, which, consequently, modifies the final sensitivity. Therefore, the enhanced ethanol sensing performance of RGO-CuO was attributed to the RGO/CuO heterojunction. When p-type CuO is exposed to air at the temperature range of 100–500 °C, molecular oxygen adsorbs and ionizes into different species , deposited onto polyethylene terephthalate (PET) substrate. The materials were synthesized via a combination of the ultrasonic spray nozzle (USN) and microwave-assisted hydrothermal (MAH) methods . Notably, the 5%RGO–WO3⋅0.33H2O showed superior isopropanol-selective sensing performances, with an almost two-fold higher response with respect to the bare compound (3O4 and reduced graphene (RGO) nanosheets by a simple hydrothermal process followed by an annealing step (see scheme in 3N4) nanosheets as a sensitization modifier for zinc oxide (ZnO)/reduced graphene oxide (RGO), rather than the widely studied and already reported noble metal nanoparticles. The nanostructures of 2D GO-hybridized by g-C3N4 were, at first, synthesized by combining ultrasonic dispersion and electrostatic self-assembly. Then, ZnO nanoparticles were hydrothermally coated on GO/g-C3N4: in this step, GO was totally reduced to RGO , as displayed in 3N4 or the extended interfacial contact between RGO and the graphitic carbon nitride.A noteworthy characteristic of graphene-based materials is their flexibility. In this context, Perfecto et al.  engineer methods f to obta methods g. Moreov methods h exhibitcompound i. Furthed to RGO n. XRD pa2 nanosphere (H-SnO2@RGO) composites successfully synthesized via a simple hydrothermal method, without the addition of any templating agents. 2 nanospheres. Moreover, different RGO contents  were investigated, resulting in 1.2% being the best performing chemoresistor. Indeed, this material, together with 0.8%, showed very high sensitivity , even under a 95% humidity atmosphere, to formaldehyde species at 130 °C , selectivity  by the one-pot microwave-assisted hydrothermal method. The authors found that all the materials behave as p-type semiconductors after being exposed to reducing gases, evidencing a 20% greater response for the composite material with respect to pure WO3  fabricated through a one-step route and comprising the decoration with noble metal nanoparticles . The coexisting of tin dioxide and Ag was mainly corroborated by XRD analysis, whereas BET measurements (2 g−1), along with an average pore size distribution centered at around 4 nm.Additionally, concerning aromatic and amino compounds, a couple of studies should be highlighted. Firstly, Zhang et al.  recentlyurements a evidencres of ca. 10 s; 2/rGO nanocomposite. Remarkably, the as-prepared compound revealed a very promising stability over time, i.e., even after 25 days. In addition, Yuan et al. [3O4 nanoparticles and reduced graphene oxide. 3O4/RGO-2  can represent a valuable alternative. Indeed, since the first reports on single-wall carbon nanotubes (SCNTs) by Japanese  and Amer2 sensor was much higher than that of bare tin dioxide material, resulting in 30 ppb, the lowest detectable concentration. In addition, Dai et al. [2O3 nanorods onto MWCNTs. TEM , Wang et al.  investigi et al.  presenteNTs. TEM a,b image2O3 (namely hematite polymorph). Notably, the composites exhibited excellent sensing properties for acetone with high sensitivity, remarkable selectivity and good reproducibility  plane at ca. 26.3°) and the hexagonal α-Fecibility c,d, supet et al.  exploredKwon et al. , instead2 nanocomposites using microwave (MW) irradiation , since a perceivable signal to 1 ppm of ethanol was still detectable even under 81% of relative humidity , and carbon nanotubes (SWCNTs and MWCNTs), have been adopted as new platforms for the design of innovative metal oxide-based chemoresistors showing boosted sensing features. Indeed, thanks to their peculiar properties, such as their unique optical, electrical, mechanical, and thermal properties, they do help the sensitive, selective and lower temperature detection of VOCs. In fact, the current research attention has been focused on the detection of ppm or even ppb concentrations of several volatile organic compounds , since they are believed to be specific biomarkers of certain human diseases. Hence, their quick detection can represent a useful step for early medical diagnosis.Thus, in the present review, we have summarized the main breakthroughs in the engineering of nanocomposites exhibiting excellent sensing behavior in terms of optimal detection limits, selectivity towards specific VOCs, even under humid atmosphere such as a human’s breath. Nevertheless, the majority of the materials recently investigated still have some shortcomings, especially related to the high operating temperatures that hinder their application in portable devices. To overcome this issue, the solutions can include (i) the synthesis of hierarchical, highly porous 3D materials to enhance the active surface area; (ii) the formation of p-n nano-heterojunctions, helping to increase the final signals; (iii) the exploitation of different light sources  to activate the material enabling the sensing at low T; and (iv) the adoption of carbon nanotubes, which have been reported to show very promising performances at low working temperatures. Furthermore, thanks to their flexible structure, CNTs and/or graphene-based materials can be easily implemented in miniaturized hand-held devices. Overall, it is clear from this review that there is a plethora of outbreaks in composite materials to be used in the field of gas sensors; nevertheless, the research will have to continue to go beyond the remaining limits and improve the humans’ health.


Fibroblast dysfunction is the main pathogenic mechanism underpinning idiopathic pulmonary fibrosis (IPF). Potassium voltage-gated channel subfamily J member 2 (KCNJ2) plays critical roles in the proliferation of myofibroblasts and in the development of cardiac fibrosis.  This study aimed to evaluate the role of KCNJ2 in IPF. KCNJ2 mRNA expression was measured using real-time PCR in fibroblasts from IPF patients and normal controls (NCs). Protein concentrations were measured by ELISA in bronchoalveolar lavage (BAL) fluid obtained from NCs (n = 30), IPF (n = 30), IPF (n = 30), IPF (n = 30), IPF (n = 30), IPF . Protein concentrations were measured by ELISA in bronchoalveolar lavage (BAL) fluid obtained from NCs (n = 30), IPF (n = 30), IPF (p < 0.001). KCNJ2 protein levels in BAL fluid were significantly higher in IPF (6.587 [1.441–26.01] ng/mL) than in NCs . KCNJ2 protein levels in BAL fluid were significantly higher in IPF (6.587 [1.441–26.01] ng/mL) than in NCs . KCNJ2 protein levels in BAL fluid were significantly higher in IPF (6.587 [1.441–26.01] ng/mL) than in NCs . KCNJ2 protein levels in BAL fluid were significantly higher in IPF (6.587 [1.441–26.01] ng/mL) than in NCs . KCNJ2 protein levels in BAL fluid were significantly higher in IPF (6.587 [1.441–26.01] ng/mL) than in NCs (0.084 [0.00–0.260] ng/mL,  KCNJ2 may participate in the development of IPF, and its protein level may be a candidate diagnostic and therapeutic molecule for IPF. MUC5B, SFTPC, SFTPA2, RTEL1, TERT, and hTR is altered in the lungs of IPF patients compared with healthy subjects and those with other lung diseases [Idiopathic interstitial pneumonia is a group of lung diseases of unknown etiology characterized by complex interactions among cells involved in inflammation and fibrosis. Idiopathic pulmonary fibrosis (IPF) is a well-known type of idiopathic interstitial pneumonia with a poor prognosis . Althougdiseases –9. We aldiseases . Among t+) more readily into the cell than out of the cell [2+ influx and proliferative activity of atrial fibroblasts [+, which induces hyperpolarization, enhanced the proliferation and survival of myofibroblasts; in contrast, exposure to elevated K+ caused depolarization [As an inward rectifier potassium channel, KCNJ2 transports potassium ions  after approval of the study protocol by the Ethics Committee of Soonchunhyang University Hospital (SCHBC-IRB-2015-08-25). Informed written consent for study participation and sample donation was obtained from each subject. The diagnostic criteria for IPF, HP, NSIP, and sarcoidosis were based on an international consensus statement –30. All Pathological recognition of the NSIP pattern included two major aspects: (1) exclusion of other patterns of interstitial lung diseases and (2) categorization of the histological features according to the ATS/ERS 2002 classification , 31 and n = 4), group 1 (n = 12), group 2 (n = 16), group 3 (n = 15), group 4 (n = 15), group 5 (n = 12), group 6 (n = 6), and group 7 (n = 4). DLCO was not measured in eight subjects with IPF and thus was excluded from the determination of their GAP scores.The total GAP score was calculated using the method suggested by Ley et al. . The folLung fibroblasts were cultured from the surgical lung specimens of 14 IPF patients and 10 subjects who underwent surgery for stage I or II lung cancer, as described previously .μg) was suspended in diethylpyrocarbonate-treated water with 0.5 μg 10 mM dNTPs and oligodeoxythymidine, heated at 65°C for 5 min, and then cooled on ice. PCR amplification was performed for 30 cycles  with a final extension at 72°C for 7 min. The PCR mixture (20 μL) contained 1 μg cDNA, 10 μL 2 × Power SYBR Green PCR Master Mix , and 1 μL 10 pmol forward and reverse primers. The following primer sequences were used: KCNJ2 (sense) 5′-CACTCCATGTCCCCATGCTC-3′ and (antisense) 5′-CCGCTACAGCATCGTCTCTT-3′; β-actin (sense) 5′-GGACTTCGAGCAAGAGATGG-3′ and (antisense) 5′-AGCACTGTGTTGGCGTACAG-3′. The PCR products were separated on a 1.0% agarose gel containing ethidium bromide in Tris-borate EDTA buffer at 100 V for 40 min and visualized under ultraviolet light. The KCNJ2 band intensities were normalized to those of β-actin. Real-time PCR was executed using the StepOne™ Real-Time PCR System (Applied Biosystems) in a two-step procedure: denaturation at 95°C for 15 s and 60°C for 1 min, followed by melting at 95°C for 15 s, 60°C for 1 min, and 95°C for 15 s. Expression levels were calculated using the 2−ΔΔCT method [The extracted RNA was treated using the Turbo DNA-Free™ Kit (Ambion). The resulting total RNA  analysis was performed, and the area under the ROC curve (AUC) and cutoff values were determined using MedCalc statistical software. Comparisons of the KCNJ2 level between groups were performed using the Kruskal–Wallis test and post hoc Mann–Whitney n = 84), NSIP (n = 9), hypersensitivity pneumonitis (n = 8), and sarcoidosis (n = 10), and the clinical characteristics of these patients are summarized in p < 0.05). The IPF group included 40 clinical and 44 surgical IPF patients, and their clinical characteristics were also summarized in our previous study [Fibroblast cultures were obtained from 14 IPF patients and 10 NCs who underwent lung surgery, and the clinical information and laboratory data of these subjects were summarized in our previous study [p < 0.001; Figures p=0.03; Figures r = 0.755, p=0.005; Fibroblasts from the lungs of the 14 IPF patients and 10 NCs were used to evaluate KCNJ2 levels. The KCNJ2 mRNA level in fibroblasts was two-fold higher in the IPF patients than in the NCs according to RT-PCR (p < 0.001), NSIP patients , HP patients , and sarcoidosis patients  (n = 27)  than those in NCs  . The ROC< 0.001)  and betwThere were no differences in the KCNJ2 protein levels according to the GAP stage , even though KCNJ2 is expressed mainly in skeletal and cardiac muscle cells. Lung fibroblasts may express KCNJ2 upon activation, as in chronic inflammation and fibrosis in IPF, but this is still uncertain. Additionally, KCNJ2 is localized mainly near the plasma membrane [We did not evaluate the cellular source of KCNJ2 production in BAL fluid, which is one of the limitations of the present study. Thus, it is uncertain whether fibroblasts or other cell types are the major source of KCNJ2 expression. Kmembrane . Thus, K+ flow. Although the ionic basis of the membrane potential of fibroblasts in IPF has not been fully elucidated, KCNJ2 is thought to affect the proliferation and membrane functions of these cells as well. This is supported by the finding that alterations in membrane potential by K+ currents modulated both the proliferation and morphology of cardiac myofibroblasts [+ concentrations induced hyperpolarization and enhanced myofibroblast proliferation and survival, whereas exposure to high concentrations enhanced myofibroblast contractility, according to collagen I gel deformation assays [KCNJ2 is associated with the gene ontology categories of G-protein-activated inward rectifier potassium channel activity and regulation of Kroblasts  in that n assays .+ currents appear to be essential for maintaining the cellular functions of astrocytes [+ currents inhibited proliferation [+ concentrations [KCNJ2 may also contribute to the high incidence of atrial arrhythmias in IPF patients. Thus, we assessed the arrhythmia incidence in our 84 study subjects using electrocardiography (n = 80) and Holter monitoring (n = 5). Among them, six subjects had atrial fibrillation or flutter. There was no difference in the KCNJ2 genotype frequency or BALF protein level between those with and those without atrial arrhythmia (Supplemental In noncardiac fibroblasts and myofibroblasts, Ktrocytes , oligodetrocytes , and fibtrocytes . In eachferation . Depolartrations . KCNJ2 etrations . The postrations . However