Autosomal dominant mutations in α-synuclein, TDP-43 and tau are thought to predispose to neurodegeneration by enhancing protein aggregation. While a subset of α-synuclein, TDP-43 and tau mutations has been shown to increase the structural propensity of these proteins toward self-association, rates of aggregation are also highly dependent on protein steady state concentrations, which are in large part regulated by their rates of lysosomal degradation. Previous studies have shown that lysosomal proteases operate precisely and not indiscriminately, cleaving their substrates at very specific linear amino acid sequences. With this knowledge, we hypothesized that certain coding mutations in α-synuclein, TDP-43 and tau may lead to increased protein steady state concentrations and eventual aggregation by an alternative mechanism, that is, through disrupting lysosomal protease cleavage recognition motifs and subsequently conferring protease resistance to these proteins.To test this possibility, we first generated comprehensive proteolysis maps containing all of the potential lysosomal protease cleavage sites for α-synuclein, TDP-43 and tau. In silico analyses of these maps indicated that certain mutations would diminish cathepsin cleavage, a prediction we confirmed utilizing in vitro protease assays. We then validated these findings in cell models and induced neurons, demonstrating that mutant forms of α-synuclein, TDP-43 and tau are degraded less efficiently than wild type despite being imported into lysosomes at similar rates.Together, this study provides evidence that pathogenic mutations in the N-terminal domain of α-synuclein , low complexity domain of TDP-43  and R1 and R2 domains of tau  directly impair their own lysosomal degradation, altering protein homeostasis and increasing cellular protein concentrations by extending the degradation half-lives of these proteins. These results also point to novel, shared, alternative mechanism by which different forms of neurodegeneration, including synucleinopathies, TDP-43 proteinopathies and tauopathies, may arise. Importantly, they also provide a roadmap for how the upregulation of particular lysosomal proteases could be targeted as potential therapeutics for human neurodegenerative disease.The online version contains supplementary material available at 10.1186/s13024-023-00621-8. SNCA triplication and quadruplication leading to familial Parkinson's disease has shown [SNCA, TARDBP and MAPT genes that alter specific amino acids also increase the risk for neurodegenerative disease and are thought to do so by increasing the rate of protein self-association [Despite symptomatic and anatomical differences, neurodegenerative diseases such as Parkinson’s disease (PD), amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are all characterized by the neuropathological finding of proteinaceous intraneuronal aggregates on which disease nosology is based and genetic cohorts have been identified . The mecas shown , 8. Mutaociation –11. Howeociation –14 and yociation , 16. ThuGBA, PGRN and CTSD implicated in PD, FTD and AD, respectively [Lysosomes play major roles in cellular protein homeostasis –20. As tectively , 22. Defectively . Althougectively –26, pastectively –30. To dIn this study, we investigated the normal lysosomal clearance of α-syn, TDP-43 and tau and found that a subset of disease mutations extended protein half-life and increased steady-state protein levels. These insights arose following the generation and analysis of comprehensive maps of protease cleavage of these proteins. The maps revealed that areas dense with cleavage sites often overlapped with areas where disease mutations are concentrated. They also predicted mutations that were likely to interfere with protease cleavage. Systematic testing of a subset of these “disruptive” mutations validated these predictions in vitro as well as in cell and iPSC-derived neuronal (iNeuron) models. Disease mutations prolonged α-syn, TDP-43 and tau half-life and increase steady-state protein levels, even when similar rates of lysosomal import of mutant versus wild type protein were observed. Together, this study offers a novel, shared pathobiological mechanism by which genetic and potentially sporadic forms of age-related neurodegenerative disease may develop and implicates lysosomal proteases as therapeutically targetable contributors in neurodegeneration.Cathepsin E (CTSE) (R&D #1294-AS), cathepsin D (CTSD) (R&D #1014-AS), cathepsin G (CTSG) , cathepsin A (CTSA) (R&D #1049-SE), cathepsin L (CSTL) , cathepsin B (CTSB) , cathepsin K (CTSK) , (CTSS) cathepsin S (R&D #1183-CY), cathepsin V (CTSV) (R&D #1080-CY), asparagine endopeptidase (AEP) (R&D #2199-CY), cathepsin H (CTSH) (R&D #7516-CY-010), cathepsin C (CTSC) (R&D #1071-CY), cathepsin O (CTSO) (Abcam #ab267932), cathepsin F (CTSF) (Abcam #ab240858), and cathepsin X (CTSX) (R&D #934-CY).The following primary antibodies  were used: 1) monoclonal mouse anti-GAPDH , 2) mouse anti-FLAG antibody , 3) mouse anti-α-synuclein , 4) mouse anti-TDP-43 , 5) mouse anti-Tau , 6) anti-rabbit anti-Lamp1 antibody , 7) rabbit anti-Cathepsin D , 8) mouse anti-Actin-C4 antibody , 9) rabbit anti-LC3b antibody , and 10) rabbit anti-TFEB antibody .Novel doxycycline-inducible, FLAG-tagged, full-length WT Tau, TDP-43, and α-syn lentiviral plasmid constructs were first designed and synthesized (Epoch Life Sciences) using a puromycin resistant plasmid backbone, pTet-O-Ngn2-Puro . Using these 3 WT plasmid constructs, individual constructs containing single pathogenic point mutations were also generated: Α-syn A30P, E46K, H50Q, G51D and A53T; TDP-43 G298S, A315T, A321G, Q331K and M337V; and tau K257T, N279K, P301S and S305N. With these constructs, lentivirus was made using the psPAX2 packing  and pCMV-VSV-G envelope (Addgene #8454) plasmids. To generate stable lines, SH-SY5Y cells already containing the pLenti CMV rtTA3 Blast construct  were infected and stable lines  were generated using Puromycin 1 mg/mL selection.For in vitro cleavage assays, 1 µg of recombinant full-length human α-syn (Abcam #ab51189), TDP-43 (R&D #AP-190) or 4N2R tau (rPeptide #T-1001–1) was incubated with or without 1 µM of each protease. Proteases requiring pre-activation were performed, as mentioned in Table MSP-MS was performed as previously published by O’Donoghue et al. 2012 . A substMSP-MS reactions were prepared with proteases at 1–70 nM concentration with a library concentration of 500 nM for each peptide (except CTSF at 1 µM) and incubated at 37 °C. Buffers were sodium acetate buffer (50 mM) containing 5 mM DTT and 1 mM EDTA for pH 4.5 and pH 5.5 or sodium citrate (50 mM) containing 5 mM DTT and 1 mM EDTA at pH 3.5. Reactions were monitored at two time points in an end point screening format. Each aliquot taken at a given time point was immediately desalted with C18 zip tips (Millipore-Sigma) and then freeze-dried. Samples were re-suspended in 0.1% formic acid in HPLC-grade water for LC–MS/MS analysis.Reaction conditions for each protease followed manufacturer recommendations for pre-activation and then were assayed at the concentrations and pH buffer conditions mentioned in Table http://prospector.ucsf.edu/prospector/mshome.htm, UCSF) using published methods [Peptide sequencing by LC–MS/MS was performed on a QExactive Plus mass spectrometer (Thermo) equipped with a nanoACQUITY (Waters) ultraperformance LC (UPLC) system and an EASY-Spray ion source (Thermo). Reversed-phase chromatography was carried out with an EASY-Spray PepMap C18 column . Chromatography was performed at a 600-nl/min flow rate during sample loading for 14 min and then at a 400-nl/min flow rate for peptide separation over 90 min with a linear gradient of 2 to 35% (vol/vol) acetonitrile in 0.1% formic acid. Peptide fragmentation was performed by higher-energy collisional dissociation (HCD) on the six most intense precursor ions with a minimum of 2,000 counts, with an isolation width of 2.0 m/z and a minimum normalized collision energy of 25. Data were analyzed using Protein Prospector software, v.6.2.1 ( methods . The pephttps://seaborn.pydata.org/index.html).The percentage contribution of each enzyme to the total number of cleavages in each protein was calculated by dividing the number of cleavage sites for each enzyme with the sum of all enzyme cleavage sites. Since our substrates α-syn, TDP-43 and tau have different amino acid lengths, in order to compare the cleavage patterns, we next normalized the percentage contribution of enzyme cleavages for each substrate with the mean of total percentage contribution for each enzyme across all substrates. Using these mean-normalized values for each enzyme within each substrate, we then performed an unsupervised hierarchical clustering in Python using the clustermap function within the data visualization library called “seaborn”  [https://www.ebi.ac.uk/merops/), assessing the amino acid frequency at the P4’-P4 positions, where all known cathepsins  were previously found to cleave [The resulting peptide identifications via MSP-MS were assessed for specific cleavage in the enzyme-treated sample by subtracting the results from a no-enzyme control incubation. Both endopeptidase and exopeptidase cleavage sites were readily identified. Using these sites, we generated full sequence cleavage maps of α-syn, TDP-43 and tau. We also created diagrams of each cathepsin to identify which amino acids were favored at the P4’ through P4 positions of each enzyme’s specific cleavage motif, using the IceLogos algorithm (iomics.ugent.be/icelogoserver) . We furtedu.au/) . To deteo cleave . Using tFluorescence-based protease activity assays were performed in triplicates in black, flat-bottom 384-well plates  using custom designed fluorescent α-syn, TDP-43 and tau peptide substrates , A53T α-syn (ab256149), WT 2N4R tau (ab199583) and N279K 2N4R tau (ab269006) were purchased from Abcam. Full-length WT TDP-43 and Q331K TDP-43 were synthesized, purified, and obtained from GenScript. Each of these proteins were incubated with 50 μg of human liver lysosomes (Xenotech #H0610.L) in a 50 mM sodium acetate (pH 4.5) buffer buffer containing 2 mM DTT and 1 mM EDTA. Each reaction was allowed to run for 30 min with samples taken at 0-, 10-, 20-, and 30-min time points. Results were then analyzed via Western blot.SH-SY5Y human neuroblastoma cells were obtained from ATCC (CRL-2266) and maintained 1:1 EMEM/F12 media  supplemented with 10% FBS and 1% Penicillin–Streptomycin . Stable lines of all 17 aforementioned constructs were generated by lentiviral infection followed by both blasticidin (5 µg/mL) and puromycin (1 mg/mL) selection. Cells were seeded at 30,000 cells per cm^2 and allowed to grow until ~ 70% confluent. To terminally differentiate into neuron-like cells, SH-SY5Y cells were then treated with retinoic acid as previously published . Once diAll iPSC lines  were obtained from the NIH’s iPSC Neurodegenerative Disease Initiative (iNDI) in association with the Jackson Laboratory . IPSCs wTo confirm trafficking of WT and mutant α-syn, TDP-43 and tau into the lysosomes of our SH-SY5Y cells, we performed a series of lysosome isolation experiments. SH-SY5Y cells were differentiated and treated with MG132 as previously described , 38. Cel34. Briefly, 40 µg of protein were separated on 4–12% SDS-PAGE (Thermo) and then transferred onto nitrocellulose membranes (Bio-Rad). Membranes were blocked at room temperature with Odyssey Blocking Buffer  and incubated at 4 °C overnight with primary antibodies and 1 h at room temperature with appropriate fluorescent secondary antibodies (1:5000) (LI-COR). Immunoreactive bands were visualized using a LI-COR Odyssey CLx image scanner and quantified using ImageJ software.Western blotting was performed as previously describedp value. All data is represented as mean ± SD. Statistical analysis was performed using GraphPad Prism 9 . Western blot quantifications for Figs. p-value < 0.05 was considered significant.Details of the statistical test used for each experiment is in figure legends along with n and Although prior studies have demonstrated that α-syn, TDP-43 and tau can be shuttled to the lysosome for degradation -26, the We first assayed the largest class of lysosomal proteases, the cysteine protease family . Under oCTSD mutations [Next, we tested the serine proteases, cathepsin A (CTSA) and cathepsin G (CTSG). While CTSG was able to digest all three substrates at more neutral pHs, CTSA did not demonstrate any clear protease activity against any of our substrates in this assay Fig. . Lastly,utations . ConsistAlthough most of the enzymes tested are endopeptidases , cathepsins A, C, H, and X are primarily exopeptidases, hydrolyzing mainly N- or C-terminal peptide bonds and exhibiting limited endopeptidase activity. Within the context of our assay, we noted that cathepsins A, H, and X (exopeptidases) as well as the endopeptidase cathepsin O (CTSO) did not demonstrate any detectable activity against α-syn, TDP-43 or tau Fig. b. To conTo map the specific locations at which lysosomal proteases cleave α-syn, TDP-43 and tau, we took advantage of MSP-MS, a rapid, quantitative, reproducible and unbiased method of direct substrate cleavage site identification . To aid At 140 amino acids, α-syn is the smallest of the three proteins assessed. In total, there were 82 cleavages in α-syn by 9 of the 12 proteases tested  contains 441 amino acids. Other than previously reported cleavage by CTSD and CTSS, little is known regarding lysosomal proteases that can digest tau , 50. AllR containe.g., PD versus ALS). Therefore, we performed comparative analysis of the proteases in regards to proteolysis of α-syn, TDP-43 and tau. To do so in proteins of different sizes, we normalized the number of cathepsin cleavages for each substrate relative to their amino acid number. Among these proteases, we found that two cysteine cathepsins, CTSL and CTSS, demonstrated the highest proportion of cleavage sites in α-syn, TDP-43 and tau  P4 to P1 found on the amino (N)-terminal side of the cleavage site and P1’ to P4’ found on the C-terminal side. When expressed in this fashion, many of the cysteine proteases  prefer hydrophobic residues at P2  while AEHaving generated cathepsin cleavage maps for α-syn, TDP-43 and tau, we overlaid the known disease-associated variants onto the maps  [Since it was not feasible to test every mutation against every protease, we utilized two approaches to identify a subset of mutations mostly likely to abrogate cathepsin cleavage. First, we performed in silico comparisons of WT versus mutant protein sequences in the PROSPER database (edu.au/) . This anedu.au/) . The iceedu.au/) , 31, 60 edu.au/)   to test for altered proteolytic cleavage activity as well as non-damaging “control” mutations with lower probability of altering protease cleavage activity Table . We thenUsing this activity assay, the maximal velocities (Vmax) at which each enzyme cleaved the WT and mutant peptides were calculated Fig. . Using tTo better quantify the summed impact of these changes over many different proteases, we assigned “damage points” for each instance in which a mutation decreased a protease’s Vmax for peptide cleavage by 0–25% (1 point), 25–75% (2 points) or greater than 75% 3 points). In contrast, mutations that increased the rate of cleavage of mutant peptides were given a score of -1 point. By summing the point values, we were able to calculate a “Damage Score” for each mutation . When tested within our in vitro protease assays, this mutation decreased CTSE, CTSL and CTSS cleavage of the mutant peptide . Through the NIH’s iPSC Neurodegenerative Disease Initiative (iNDI), we obtained 3 CRISPR-edited, homozygous mutant lines, α-syn A53T, TDP-43 Q331K, and tau N279K, as well as their parent isogenic WT iPSC line . These aAs α-syn, TDP-43 and tau are all intrinsically disordered proteins that are found in disease inclusions and whose mutations are causally linked to neurodegeneration , understAlthough we did observe a significant degree of redundancy in the activity of the lysosomal proteases on the degradation of α-syn, TDP-43 and tau, we were surprised to find that 1) certain proteases, such as CTSB and AEP, had relatively specific non-redundant activity and 2) certain mutations disrupted multiple proteases and likely undercut a significant degree of the redundancy present among the lysosomal proteases. Our correlation analyses also raise the question of whether certain cathepsins are regulated in a coordinated fashion, such as through the TFEB-mediated CLEAR pathway or via an alternative mechanism, in response to these specific lysosomal substrates .While the increased steady-state levels of mutant α-syn, TDP-43 and tau were modest in the cell-based assays, these assays spanned only a few days. In some respects, it is remarkable that point mutations could detectably alter steady state levels of α-syn, TDP-43 and tau at all. Over weeks, years and decades, the impact of half-life extending mutations in α-syn, TDP-43 or tau would likely be compounded. They could be further exaggerated by age-associated declines in lysosome function –68 or the.g., chaperone upregulation, proteasome and autophagy induction, lysosomal secretion, ER and mitochondrial unfolded protein responses, aggregate formation, etc.). As such, it may only be when these compensatory mechanisms are exhausted that neurodegeneration occurs.This model complements and builds upon the idea that certain disease mutations can increase steady state levels of protein directly by enhancing fibril formation while others, like the ones we identify here, do so indirectly via impaired lysosomal degradation. As such, aberrant protein homeostasis and a steady state increase in these proteins may be the unifying feature of these diseases. As terminally differentiated cells that cannot dilute protein concentrations through cell division, neurons have developed many cooperative strategies to deal with aberrant protein homeostasis  impairing the proteolytic cleavage of these proteins in the lysosome could play a role in sporadic cases as well. The practical and disease implications of these findings are multifold. First, they provide a molecular basis by which disease mutations in  regions  and coul regions –72 and p regions , 74. Sim regions . FinallyAlthough our efforts were designed to be comprehensive, there are limitations to our study. Moreover, while the MSP-MS and in vitro fluorescent protease assays are complimentary , on occasion we observed slight discrepancies. For example, in the in vitro protease assay CTSB cleaved the TDP-43 fluorescent peptides spanning the 294–302 region, which we did not observe in MSP-MS. This is likely because the MSP-MS results were limited to two collection time-points, which may miss both the earliest cleavages as well as very late events, although the latter may be less relevant given the multi-protease environment inside the lysosome. Additionally, cell-based experiments were limited to relatively short time intervals and involved differentiated neuronal cells which lack certain aging-hallmarks and whose age-related declines in proteasome function had to be simulated using a proteasomal inhibitor. Future work should address longer-term, in vivo contexts , where the association of end-stage disease hallmarks, such as protein aggregates, in response to cathepsin inhibition can be studied. The contributions of post-translational modifications, which can impact both lysosomal targeting and proteolytic processing , could aThis study comprehensively identifies the arsenal of lysosomal proteases that degrade α-syn, TDP-43 and tau, demonstrating that these proteases have highly specific cleavage patterns and optimal pH settings. This work also provides compelling experimental evidence that certain pathogenic mutations in each of these three proteins can disrupt this lysosomal protease activity, prolong protein half-life, and increase steady state levels in neuronal cell models. Fascinatingly, this novel, alternative mechanism by which disease-causing mutations in α-syn, TDP-43 and tau may lead to neurodegeneration also appears to be shared. These findings therefore enhance our understanding of α-syn, TDP-43 and tau metabolism as well as their impact on normal protein homeostasis and neurodegenerative disease pathobiology. In the future, this work could be leveraged to promote neuronal health by upregulating specific lysosomal proteases.Additional file 1: Figure S1. Proteases that do not cleave α-syn, TDP-43, or tau are active against a fluorogenic casein substrate. Fluorogenic protease activity assays using casein at pH 4.5 was performed on all enzymes that do not cleave α-syn, TDP-43, or tau. The values obtained were normalized to timepoint t = 0 and plotted relative to activity. All enzymes, including both cysteine and serine proteases, show activity against the optimized fluorogenic peptides compared to the substrate only control. Figure S2. PROSPER analysis predicts multiple cathepsin cleavage sites with α-syn, TDP-43, and tau. Cathepsins Gand K, the lysosomal proteases available in the PROSPER database, demonstrate many sites of cleavage throughout the α-syn, TDP-43, and tau substrates. Yellow highlighted amino acids represent the P1 site of predicted CTSK cleavage. Light blue highlighted amino acids represent the P1 of predicted CTSG cleavage. Figure S3. Cathepsin activity assay Vmax tables of α-syn, TDP-43, and tau wild type versus mutant substrates. a, α-Syn, b, TDP-43, and c, tau. Vmax values are listed in nM/min. An arbitrary value of 2000 value was given to protease-enzyme substrate interactions that were too fast to be modeled. Figure S4. Doxycycline-induced expression of mutant α-syn, TDP-43, and tau in differentiated SHSY-5Y cells. a, α-Syn; b, TDP-43; and c, tau. Western blot images demonstrating induced expression of each FLAG-tagged protein by our plasmid constructs with 24 h of doxycycline treatment results in measurable protein whose half-life can be readily quantified over days. These results also demonstrate minimal leakiness of these constructs in the absence of doxycycline. Figure S5. Proteasomal inhibitor, MG132, upregulates markers of autophagy. a., Western blot images demonstrating that Lamp1, cathepsin D, LCBIIb, and TFEB are all upregulated after MG132 treatment at 24, 72, and 120 h, compared to the no treatment condition. b., Quantification of the results of A. Experiments were performed in triplicate. Figure S6. Full Western blots of differentiated SH-SY5Y and iNeuron protein half-life experiments. a. Western blot images demonstrating induced expression of each FLAG-tagged protein whose half-lives were quantified over 5 days. The green channel was used to measure each FLAG tagged protein. The red channel was used to measure GAPDH, which was used as the loading control and method by which protein quantification was normalized. b. Western blot images demonstrating iNeurons whose protein levels were quantified at day 0 and day 5 of MG132 treatment. The green channel was used to measure either α-syn, TDP-43, or tau expression. The red channel was used to measure GAPDH, which was used as the loading control and method by which protein quantification was normalized. Figure S7.Table S1. α-Syn, TDP-43, and tau peptide library. Amino acid sequences for all peptides within the library tested in the described MSP-MS experiments in Figs. 2, 3, 4 and 5. Table S2. Pre-activation steps, protease concentrations, tested pHs, and timepoints for in vitro and mass spectrometry experiments. Cathepsin A, C, H, and X required pre-activation for all experiments in Figs. 1, 2, 3, 4, 5 and Fig. S1. Protease concentration and mass spectrometry timepoints were chosen and optimized based on the known rate of cleavage for each protease. Table S3. WT and mutant α-syn, TDP-43, and tau sequences with high rank order prediction scores of cleavage for select cathepsins. Each mutation and companion wild-type sequences for a, α-Syn; c, TDP-43, and c, tau are represented alongside the rank order prediction scores of PROSPER predicted sites of cleavage for the available cathepsins B, K, L, S, D and E. Table S4. Fluorogenic peptide sequences for WT and mutant α-syn, TDP-43, and tau. A, α-Syn; B, TDP-43, and C, tau amino acid sequences tested in the described fluorogenic protease activity assays in Figs. 2, 3, and 4.Additional file 2.Additional file 3.


Clostridioides difficile infection (rCDI) substantially diminishes patients’ health-related quality of life (HRQL). The gut microbiome is known to play an important role in rCDI, but little is known about its relationship with HRQL. In this study, we assessed the relationship between the gut microbiome and HRQL in patients with rCDI from REBYOTA’s  phase 3 PUNCH CD3 trial (NCT03244644).Recurrence of C. difficile Quality of Life Survey (Cdiff32) via its total score and physical, mental, and social domain scores .HRQL and relative abundance  of gut microbiota at the class level were collected at baseline and weeks 1, 4, and 8. The Microbiome Health Index , defined as (Bacteroidia + Clostridia) / (Gammaproteobacteria + Bacilli), was analyzed using log transformation and as a binary indicator with MHI > 7.2 indicating a healthy microbiome. HRQL was measured using the disease-specific Correlations between microbiota data  and Cdiff32 scores were estimated. Associations of Cdiff32 scores with microbiota data and MHI > 7.2 were estimated using mixed effects analyses adjusted for baseline patient characteristics. Analyses used all available data . P-values were adjusted for multiple testing via the Benjamini-Hochberg procedure; correlations were interpreted as moderate if ≥ 0.3 and large if ≥ 0.5 .Table 1). Significant associations of microbial relative abundances and log MHI with all Cdiff32 scores were found in mixed effects analyses  (Table 2). MHI > 7.2  was associated with an improvement of 14.2 to 18.4 points in Cdiff32 scores (vs. MHI ≤ 7.2).A total of 176 out of 262 (67.2%) patients had Cdiff32 and microbiota data  in PUNCH CD3. All four Cdiff32 scores correlated positively with log MHI (∼0.6), Clostridia (∼0.5) and Bacteroidia (∼0.3), and negatively with Gammaproteobacteria (∼−0.5) and Bacilli (∼−0.3) (Our study found moderate to large and statistically significant associations between a healthy gut microbiome and improved HRQL in patients with rCDI.Paul Feuerstadt, MD, FACG, AGAF, Ferring/Rebiotix Pharmaceuticals: Advisor/Consultant|Ferring/Rebiotix Pharmaceuticals: Grant/Research Support|Merck and Co.: Advisor/Consultant|Seres Therapeutics: Advisor/Consultant|Seres Therapeutics: Grant/Research Support|Takeda Pharmaceuticals: Advisor/Consultant Ken Blount, PhD, Ferring Pharmaceuticals: Employee Amy Guo, PhD, Ferring Pharmaceuticals: Employee Min Yang, MD, PhD, Analysis Group, Inc.: I am an employee of Analysis Group, Inc., which has received consulting fees from Ferring for the conduct of this study. Viviana García-Horton, PhD, Analysis Group, Inc.: I am an employee of Analysis Group, Inc., which has received consulting fees from Ferring for the conduct of this study. Mirko Fillbrunn, PhD, Analysis Group, Inc.: I am an employee of Analysis Group, Inc., which has received consulting fees from Ferring for the conduct of this study. Glenn S. Tillotson, PhD, Dynavax: Advisor/Consultant|Ferring Pharmaceuticals: Advisor/Consultant|Peggy Lillis Foundation: Honoraria|Spero Therapeutics: Advisor/Consultant Yipeng Gao, PhD, Merck and Co.: Grant/Research Support Erik R. Dubberke, MD, MSPH, Abbott: Advisor/Consultant|AstraZeneca: Advisor/Consultant|Ferring Pharmaceuticals: Advisor/Consultant|Ferring Pharmaceuticals: Grant/Research Support|Merck and Co.: Advisor/Consultant|Pfizer: Advisor/Consultant|Pfizer: Grant/Research Support|Seres Therapeutics: Advisor/Consultant|Summit: Advisor/Consultant|Theriva Biologics: Grant/Research Support Kevin W. Garey, PharmD, MS, Acurx: Grant/Research Support|Ferring: Advisor/Consultant|Paratek: Grant/Research Support


Harvesting largely ignored and wasted electromagnetic (EM) energy released by electronic devices and converting it into direct current (DC) electricity is an attractive strategy not only to reduce EM pollution but also address the ever-increasing energy crisis. Here we report the synthesis of nanoparticle-templated graphene with monodisperse and staggered circular nanopores enabling an EM–heat–DC conversion pathway. We experimentally and theoretically demonstrate that this staggered nanoporous structure alters graphene’s electronic and phononic properties by synergistically manipulating its intralayer nanostructures and interlayer interactions. The staggered circular nanoporous graphene exhibits an anomalous combination of properties, which lead to an efficient absorption and conversion of EM waves into heat and in turn an output of DC electricity through the thermoelectric effect. Overall, our results advance the fundamental understanding of the structure–property relationships of ordered nanoporous graphene, providing an effective strategy to reduce EM pollution and generate electric energy. The electromagnetic (EM) energy released by electronic devices in the environment is largely wasted and contributes to EM pollution. Here, the authors report the synthesis of staggered circular nanoporous graphene enabling the absorption and conversion of EM waves into electricity via the thermoelectric effect. However, only 20–30% of EM waves  are utilized in telecommunications4. The rest are largely ignored and wasted, causing high levels of EM pollution in the surrounding environment and leading to health concerns, signal interference in device-to-device communications, and heat generation in electronic devices (known as overheating)6. Therefore, harvesting the freely available EM radiation and converting it into usable direct current (DC) electricity is an attractive strategy to not only reduce EM pollution but also address the ever-increasing energy crisis. To date, no single-component material system can convert EM waves to DC electricity because of contradictory material requirements9. For example, EM absorbing and shielding materials require a high permittivity, which is typically associated with a high thermal conductivity, while thermoelectric materials require a low thermal conductivity and fail to absorb EM radiation11. To overcome this challenge, we sought to design a single-component material system that enables EM–heat–DC conversion: (i) efficiently absorbing and converting low-frequency EM waves into heat, creating an associated temperature gradient, and (ii) outputting DC electricity via the Seebeck effect.The recent breakthroughs in information and communication technologies  have led to an astronomical rise in electronic device usage and the release of particularly low-frequency electromagnetic (EM) waves, mainly ranging from 2 to 5 GHz (L- and C-band), into the surrounding environment13. However, the intrinsically high thermal conductivity, low Seebeck coefficient, and zero bandgap structure prevent heat–DC conversion15. Element doping and the creation of graphene nanostructures  have been widely used to alter graphene’s electronic and phononic structure by covalently tuning the intralayer atomic bonding18. While not fully understood yet, recent research has shown that the manipulation of the interlayer interactions between different graphene layers  by stacking two sheets of graphene that are twisted by a small angle (known as the magic angle of graphene superlattices) enables a variety of material properties and functions20. In order to achieve our goal, we sought to tune the electronic and phononic structure of graphene via a combination of both intralayer and interlayer strategies – specifically, the creation of ordered nanopores in graphene surfaces  and the formation of partially overlapped nanopores on different graphene layers . Current methods for creating ordered porous graphene, such as electron beams, can only achieve micrometer-sized, completely overlapped pores, which usually display a limited density of carbon atoms located at the pore edges and thus a weak intralayer effect23. Therefore, the synthesis of monodisperse, nanometer-sized pores (<10 nm) with a staggered porous structure across different graphene layers remains challenging.Graphene, with its characteristic high permittivity, has been demonstrated to possess remarkable EM dissipation abilities To overcome this challenge, this work reports a method to create monodisperse, nanometer-sized circular pores with well-controlled pore sizes and shapes on graphene templated by transition metal oxide nanoparticles formed in-situ. In graphene with more than one layer, the nanopores on different graphene layers partially overlap with each other, resulting in a desirable staggered nanoporous structure. We found that the formed non-graphitized carbon at the edge of the graphene nanopores serves as dipoles to improve the EM–heat conversion through dipole polarization relaxation at relatively low EM frequencies . Furthermore, the pore edges promote phonon scattering to reduce the thermal conductivity of the graphene and confine the electron transport by splitting the Dirac point and breaking up the Fermi energy surfaces, which significantly enhances the Seebeck effect of graphene. As a result, the synergy of the high permittivity, the reduced thermal conductivity and the enhanced Seebeck coefficient makes this class of staggered, ordered nanoporous graphene a promising material to achieve the proposed EM–heat–DC conversion.3O4) nanoparticles were grown in-situ on the surface of the graphene nanosheets via a thermal decomposition process. Fe3O4 nanoparticles oxidized the underlying graphene during the subsequent annealing treatment to locally generate nanopores. Finally, the remaining Fe3O4 nanoparticles were removed using hydrochloric acid, revealing these monodisperse nanometer-sized pores in the graphene surfaces as shown in the representative transmission electron microscopy (TEM) images in Fig. 3O4 nanoparticles, respectively , as evidenced in the inset in Fig. Besides tuning the shape and size of the nanopores in the graphene surface, we have also created nanopores in multilayer structures of graphene. Representative TEM images show bilayer, trilayer, and multilayer (six layers on average) graphene with circular nanopores Fig. . In partη). The heat (W) generated by the EM dissipation can be calculated as24:D is a coefficient associated with the volume of EM dissipation materials, and E and f represent the power and frequency of the applied EM wave, respectively. η can be written as25:εr is the relative complex permittivity and tanδe is the dielectric loss tangent, defined as the ratio of the imaginary and real part of the permittivity (ε“/ε‘). The permittivity and η of graphene with different structures are shown in Fig. η of monolayer and bilayer nanoporous graphene is larger than their trilayer and multilayer counterparts. In addition, the η of graphene with circular nanopores is higher than that of pristine graphene, which is attributed to the excellent EM wave incident angle-independence of the circular pores. We note here that the highest η values among the ordered nanoporous graphene, 160.8 for bilayer graphene with staggered circular pores, is higher than that of nonporous graphene (116.9) and a majority of the conventional EM dissipating materials  due to a comparable relaxation time of their dipoles with respect to the frequency of the applied EM field  and not at low frequencies (2–5 GHz), as shown in Supplementary Fig. η of ordered porous graphene  of ordered nanoporous graphene lies between 3000 and 1000 S/cm over a temperature range of 300–500 K, which is ~20–30% that of nonporous bilayer graphene, as shown in Fig. The presence of a high density of dipoles at the pore edges in the graphene lowers the number of graphitized carbon atoms and affects the transport of electrons. As shown in Fig. κT) is desired to maintain the temperature profile in the ordered nanoporous graphene to drive the directional diffusion of charge carriers from the hot side to the cold side. However, pristine (nonporous) graphene is well known for its ultrahigh κT, preventing the formation of a sufficient temperature gradient for the generation of DC electricity via the Seebeck effect30. In the next set of experiments, we sought to investigate the effect of the nanoporous structure on κT. As evidenced in Fig. κT of bilayer graphene with circular nanopores lies between 3.5 and 2.1 W/m·K over a temperature range of 300–500 K, which is two orders of magnitude lower than that of nonporous bilayer graphene. We also observed that κT decreases with an increase in the number of graphene layers. We note here that the κT of bilayer graphene with circular nanopores is almost two orders of magnitude lower than graphene nanoribbons, other two-dimensional materials , and porous nanomaterials , as listed in Supplementary Table κT of graphene with different layers is also compared in Supplementary Fig. Upon dissipating the EM waves into heat, an ultralow thermal conductivity  and that κe is proportional to σ31. To elucidate the role of the nanoporous structure in the reduced κT, we measured the κe, and κL of the ordered nanoporous graphene as a function of temperature  divided by the strip length (25 mm)) as a function of time was determined using an infrared thermometer. As shown in Fig. Next, we sought to design an ordered porous graphene-based device to generate a temperature gradient upon EM radiation. We fabricated 25 mm long, 5 mm wide, and 10 μm thick graphene strips and coated one end of the strip with a 690 nm thick adiabatic parylene-c layer using CVD. Upon radiating the strips with EM waves with a frequency of 2.45 GHz using a homemade EM emitting cavity with a 100 W magnetron, the temperature profile and temperature gradient  of ordered nanoporous graphene is comparable with conventional thermoelectric materials and larger than other modified graphene , with the |S | of monolayer and trilayer graphene being ~50% and ~15% smaller, respectively. The negative sign of S indicates an n-type semiconducting behavior for the ordered porous graphene, in which electrons are the predominant carriers36. We further evaluated the thermoelectric conversion ability of ordered porous graphene by calculating the largest dimensionless figure of merit, otherwise known as the ZT value (ZT =  σS2T/κT) and the thermoelectric coefficient37. As shown in Fig. ZT value to be 0.33 over a temperature range of 300‒500 K. We note that both the ZT value and the thermoelectric coefficient of the bilayer graphene with ordered circular nanopores are about three orders of magnitude higher than that of bilayer nonporous graphene, significantly higher than other graphene-based composites, and comparable to current state-of-the-art thermoelectric materials , we performed temperature-dependent Hall carrier measurement analysis of ordered nanoporous graphene at different temperatures. As shown in Supplementary Fig. S | value of a series of modified graphene with different effective masses and Hall carrier densities, including sulfur or nitrogen-doped graphene, graphene with polydisperse pore structures, and reduced graphene oxide, are less than 30 μV/K  indicates that the Dirac points split and shift from their original positions  to regions between G–M and K–G, resulting in an open bandgap structure with a bandgap of ~0.13 eV , the staggered pore structure with a partial overlap ratio facilitates the splitting of the Dirac points and thus generates higher intensity van Hoff singularity points, which are beneficial to the enhancement of the Seebeck effect of graphene  of the graphene-based device was measured to increase to ~17.7 mV over about 180 s before decreasing with continued EM radiation. In contrast, the Uoc of a nonporous graphene-based device was only 0.8% of that  and EM radiation time Fig. , we measZT values. As a result, the ordered nanoporous graphene enables the efficient generation of DC electricity through the absorption and dissipation of EM waves into heat, followed by a simultaneous thermoelectric process. Our results advance the fundamental understanding of the structure–property relationship of ordered nanoporous graphene and provide a design strategy to efficiently absorb and convert low-frequency EM waves and waste heat from the environment into usable electricity. This class of multifunctional ordered nanoporous graphene may expand the potential utility of graphene in energy harvesting, thermal management, EM shielding and absorption, thermoelectrics, and photocatalytic water splitting. Future efforts will seek to experimentally control the overlap ratio of nanopores on different graphene layers to study its influence on the graphene properties. In addition, the self-powering and self-charging of wearable electronics, building on the success of emerging 5G communications, using ordered porous graphene-based devices are being investigated.In this work, we report a facile method to create staggered, monodisperse nanometer-sized circular pores on the surface of graphene. It was observed that the presence of these nanopores and the staggered porous structure alter the electronic and phononic structure of the graphene , resulting in desirable functionalities, such as a high permittivity, low thermal conductivity, and high Seebeck coefficient and Iron acetylacetonate, oleic acid, oleyl amine, ammonia (28 wt %), hydrogen peroxide (30 wt %), sodium molybdate dehydrate, thiourea, ferrous chloride, cobalt acetate, ethylene glycol, zinc acetate, lanthanum oxide, cobalt nitrate, tetraethyl orthosilicate, sodium hydroxide, oxalic acid, strontium carbonate, cobalt oxalates, bismuth nitrate pentahydrate, tellurium powder, 1-butyl-3-methylimidazolium bromide, silver nitrate, stannous chloride, sulfur powder, ethylenediaminetetraacetic acid disodium, copper nitrate, hexadecyltrimethylammonium bromide, formaldehyde, cyclohexane, isopropanol, iron pentacarbonyl, 1,3-dimethylimidazoline-2-selenone, hydrochloric acid (38 wt %), and parylene-c monomer were bought from Sigma-Aldrich. Raw graphene and multiwall carbon nanotubes were obtained from XF-NANO tech. Co. All chemical reagents are analytical pure reagents and were used without further purification. Polydimethylsiloxane film was bought from Shanghai Muke Technol. Co. Water used in all the experiments was purified using a Milli-Q water purification system (Simplicity C9210).First, iron acetylacetonate, raw graphene, prepared by chemical vapor deposition (CVD), oleic acid, and oleyl amine were mixed and ultrasonicated for 30 min. Afterward, the mixture was heated between 110 and 120 °C with vigorous stirring for 2 h under a nitrogen flow. Next, the mixture was heated to 220 °C and kept at this temperature for 30 min, followed by heating up to 300 °C at a heating rate of 2 °C/min where it stayed for another 30 min. After cooling to room temperature, the graphene decorated with iron oxide nanoparticles was collected via centrifugation after dispersing it in cyclohexane and isopropanol.The iron oxide nanoparticle-coated graphene was kept at 300 °C for 60 min under a constant nitrogen flow to remove residual organics. Next, the temperature was increased to 900 °C at a rate of 1 °C/min and maintained at this temperature for 2 h to create nanopores on the graphene. After cooling to room temperature, the graphene was dispersed into a hydrochloric acid solution with a pH between 1.5 and 2.0 to remove the residual nanoparticles, resulting in the formation of nanometer-sized pores on the graphene surface. The nanopore shapes can be tuned by forming nanoparticles with different geometries  and was ultrasonicated for 30 min. Afterward, the solution was heated to 80 °C and kept at this temperature for 1.2 h under magnetic stirring. Finally, the nanoporous graphene with pore diameters <3 nm was collected using centrifugation and dried at 80 °C for 24 h.In total, 0.1 g of the bilayer graphene prepared by CVD was added to 100 mL of hydrogen peroxide , and 0.1 mL of hydrochloric acid . Next, the solution was transferred to an autoclave and heated at 150 °C for 10 h. The S-doped graphene was washed using distilled water and dried at 60 °C for 24 h under a vacuum.100 mg of thioacetamide and 10 mg of bilayer graphene prepared by CVD were dispersed into a solvent mixture consisting of 30 mL of distilled water, 0.1 mL of HA thin film of ordered nanoporous graphene with a thickness of ~10.0 ± 0.8 μm was spin-coated on a silicon substrate and later cut into several 25 mm long and 5 mm wide strips. Next, 20 mm of each strip was covered, and the exposed region (5 mm) of the graphene was coated with parylene-c using a CVD process involving four steps at 120, 130, 140, and 150 °C with corresponding times of 20, 20, 40, and 0–120 min, respectively. The temperature of the CVD deposition chamber was set to 650 °C, and the parylene-c monomer was placed in the CVD evaporation chamber set at 120 °C. The thickness of the parylene-c coating was tuned by the chemical deposition time. After deposition, six parylene-c-coated graphene strips were assembled onto a 20 μm-thick polydimethylsiloxane film, with ~5 mm spacing between each strip. Finally, all the strips were connected in series using conductive copper paste.The phase identification of graphene materials was performed using a Bruker D8 ADVANCE X-ray diffractometer (XRD) with Cu Kα radiation (λ = 0.15406 nm). A Joel JEM 2100 F transmission electron microscope (TEM) with a 200 kV field emission was employed to investigate the morphology of the nanoparticles and graphene. X-ray photoelectron spectroscopy analyses were performed using an Escalab 250Xi spectrometer. The graphitization level of the ordered nanoporous graphene was measured using a Jobin Yvon HR 800 confocal Raman spectroscope.44ygraphene and ysilicon represent the volume fraction of the graphene and silicone resin, respectively. εmixture, εgraphene, and εsilicon represent the permittivity of the silicone resin/graphene mixture, pure graphene, and pure silicone resin, respectively. After εsilicon was measured, εgraphene was calculated based on Eq.  of graphene materials was measured according to a four-probe method using a Keithley 4200-SCS electrometer. The thickness of the graphene film was measured using a Tencor profilometer. The surface morphology of the graphene sample was characterized using a Park NX10 atomic force microscope. The graphene’s temperature-dependent σ and Seebeck coefficient (S) were measured using an Ulvac-Riko ZEM-3 system. The graphene was hot-pressed into a pellet with a length of ~12 mm and a width of ~3 mm. The thermal conductivity (κT) of graphene can be calculated as45:D is the density, Cp is the specific heat value, and λ is the thermal diffusivity. κT was measured using a Netzsch LFA-467 laser flash system according to the laser flash diffusivity method with a pyroceram disk as reference. In addition, the specific heat values were collected using a Pyroceram 9606 system. Hall carrier density was measured using a physical property measurement system. We note here that the uncertainty of the electrical output value is about 15–25% due to the error in the measurement of σ, κT, and S. The error of the temperature is around 1 K.The electric conductivity (Supplementary InformationPeer Review File


This review article covers all types of paper-based humidity sensor, such as capacitive, resistive, impedance, fiber-optic, mass-sensitive, microwave, and RFID (radio-frequency identification) humidity sensors. The parameters of these sensors and the materials involved in their research and development, such as carbon nanotubes, graphene, semiconductors, and polymers, are comprehensively detailed, with a special focus on the advantages/disadvantages from an application perspective. Numerous technological/design approaches to the optimization of the performances of the sensors are considered, along with some non-conventional approaches. The review ends with a detailed analysis of the current problems encountered in the development of paper-based humidity sensors, supported by some solutions. The first part of this literature review  primaril2), M-Liner (cardboard) (230 g/m2), and PackPro (food-packaging paper) (50 g/m2), and Andersson et al. [2), Wawrzynek et al. [2) from Stora Enso .A wide variety of paper types have been tested to manufacture capacitive humidity sensors. In particular, Courbat et al.  used p_en et al.  tested Hn et al.  employedk et al.  fabricatk et al.  suggestek et al.  fabricat2), respectively. Metalized paper (MP) is a commodity in which a thin layer of aluminum offers both a decorative appearance and protective/controlled gas permeation. Rahimi et al. [2-based laser-ablation process.Although parallel-plate (PP) capacitive sensors generally have a higher sensitivity than IDE-based capacitive sensors , these si et al.  found thIn general, the humidity-sensing materials employed in PB sensors might be classified into two types: (i) the paper itself, and (ii) non-paper hydrophilic humidity-sensing materials, such as ceramics, polymers, carbon materials, and their composites. Below, we summarize the development status of PB humidity sensors according to the types of the materials used in their design.0) and sensitivity (ΔC/ΔRH) are usually used, which describe the change in capacitance upon interaction with humid air, as well as the response time (τres) and recovery time (τrec), which characterize the kinetics of the sensory response. The response/recovery time is usually defined as the time taken to reach 90% of the final equilibrium value. A parameter such as hysteresis is also used, which characterizes the possible differences between sensor readings when measuring in conditions of increasing or decreasing humidity. The methods for measuring these parameters do not differ from the methods used in the testing of gas sensors and described in many publications, including [ncluding ,5,6,9,10The typical characteristics of humidity sensors employing paper-based sensing elements are shown in It was also found that the capacitive response is reversible a, and th0) above 10%), low sensitivity , and slow response/recovery  [0) at 1 kHz, and a maximum change of 411.4% at 10 kHz, using robust and precise screen- and gravure-printing technologies. The sensors were highly repeatable, exhibiting a standard deviation in sensitivity of 1.05% for three continuous runs, stable, and insensitive to mild temperature changes (15–30 °C). It is worth noting their fast response, of ca. 0.8 s, and recovery, of ca. 0.78 s. To achieve these results, Zhang et al. [However, the analysis of published results indicates that despite the significant progress in paper-based humidity sensors, most sensors still exhibit poor repeatability, high drift  ,22. In aminutes) , developg et al.  subjecteg et al. , remarkag et al. , also shHowever, the information given in Some solid-state materials, such as carbon nanotubes (CNTs), graphene oxide (GO), porous silicon (PSi), and alumina oxide (AO), have been applied to produce capacitive paper-based humidity sensors. The parameters of these sensors are listed in 2O3-based detectors [2O3 and PSi encourage the capillary condensation of water vapor, which has a significant effect on the material capacitance (or dielectric permittivity) compared to the adsorption of H2O molecules on the surfaces of GO and CNTs only. Regarding the sensors developed by Song et al. [As can be seen from the results presented in etectors  and PSi etectors . Howeverg et al. , high se2O molecules. In addition, CNCs have large specific surface areas and high mechanical strength, which are important for sensing units. Cellulose nanocrystals are mainly derived from naturally occurring cellulose fibers by removing amorphous segments through strong-acid hydrolysis. In the study, to form a GO/CNC composite, the GO suspension was mixed with the CNC composite at the desired ratio, of 5 wt.% and 10 wt.% of CNC, followed by homogenization. Further, an electrode with an interdigital transducer (IDT) pattern was deposited on a PET substrate using a conventional lift-off process. Next, the CNC/GO solution was poured dropwise onto the patterned electrode and dried in an oven at 60 °C. It should be noted that no paper substrate was used in the manufacturing of this sensor, which distinguishes it from those considered above.Recently, a remarkably high sensitivity to humidity was reported for sensors based on GO/CNC composites; the data are displayed in 2O content of less than 5% RH. However, it was also clear that the sensors had a limited sensitivity range because the sensory response was rather low, in the RH < 70% range. In addition, these sensors had long response and recovery times. It was also found that the sensors had significant hysteresis characteristics.Previously, Jalkanen et al.  showed t2) was used. The ID-electrode capacitor was fabricated by an evaporation of 300-nm-thick aluminum onto the top of a thin AAO film through a Pt mask  or current (I/I0) to changes in humidity, the sensitivity calculated as the ratio of changes in resistance to changes in humidity (ΔR/ΔRH), and the response/recovery time determined as mentioned earlier in The parameters of humidity sensors which employ a paper as a detector element are presented in 2O vapors and can vary over a wide range, which makes it possible to develop highly sensitive conductometric (resistive) humidity sensors. However, the conductivity of paper normally appears to be very low, which makes the resistance of the corresponding sensors excessively high for ordinary electronic readout circuits. The conductivity begins to noticeably increase only at humidity levels above 40–50% RH [−2 and 185 g·m−2, respectively. Standard carbon paper has a density of 80 g·m−2. Gooder et al. [2O vapors below 20% RH. The Whatman 1 Chr had the lowest sensitivity and did not give a noticeable signal below 65% RH. The Whatman 3MM Chr was significantly more sensitive than the Whatman 1 Chr and detected the humidity at RH > 30%. Gooder et al. [The research data presented in 0–50% RH ,38. Thisr et al. ,41,44. Sr et al.  are draw3, making these sensors suitable for the accurate detection of H2O vapors in a given environment. As shown in According to Duane et al. , the con3NOH hydrogel film in 4 wt% KOH solution for over 6 h. To prepare the cellulose/BzMe3NOH hydrogel film, the cellulose sample was dispersed in an aqueous BzMe3NOH solution at room temperature following centrifugation. The as-prepared cellulose/KOH composite hydrogel film was air-dried at room temperature overnight. The cellulose substrate was fabricated through a water-evaporation-induced dense-packing strategy. As demonstrated in To expand the sensitivity range of PB humidity sensors, Wang et al.  suggeste−1. However, these sensors also had slow responses. The response and recovery times were about 60 s and 500 s, respectively. Notably, relatively long recovery times are a common problem for sensors employing paper as the humidity-detecting element. This is due to the hydrophilic nature of cellulose, which takes longer to desorb water molecules. Moreover, regularity is frequently observed regarding the effect of paper density: the greater the density of the paper, the slower the sensory response  in the HP paper and AlO(OH) in the Canon paper. Additionally, no differences in porosity were observed through the Hg-porosimetry measurements. Moreover, the HP paper was found to have significantly higher resistance in a dry environment  of the humidity sensor gradually reduced as the distance between the electrodes increased. This effect was also observed by Zhao et al. [2O molecules on paper surfaces creates a discontinuous layer when the gap between two electrodes is excessively large, breaking the percolation conduction channel even at high relative humidity values, which contributes to reductions in sensory response.It was also been found  that theo et al. . Accordio et al. , the adsWith regard to the bendability of resistive humidity sensors on paper, tests carried by Duan et al.  suggesteIn the manufacturing of paper-based humidity sensors using carbon-based materials as detecting elements, carbon nanotubes (CNTs or MWCNTs), graphene, graphene oxide (GO), reduced graphene (rG), and composites, including carbon and cellulose, have been applied. The parameters of these sensors are listed in The analysis of the presented results indicates that these sensors have (i) unique electrical and mechanical properties, (ii) high aspect ratios, and (iii) nanoscale structures due to carbon-based nanomaterials. However, they exhibit sensitivity that is significantly inferior to those of sensors employing paper only. This difference is usually explained by the inherent hydrophobicity of carbon nanomaterials and the very high conductivity of these materials. As shown in Studies have shown that the characteristics of conductometric humidity sensors, as well as capacitive humidity sensors, depend on the paper used. Beniwal et al.  compared2O vapors. The effects of the paper type and CNT-oxidation mode on sensor performance are presented in Recently, many efforts have been undertaken to improve the sensitivity of carbon-based humidity sensors. In particular, treating CNTs with a mixture of acids, such as nitric and sulfuric acids, oxidization, or plasma processing to increase their hydrophilicity have become universal methods for increasing the sensitivity of sensors based on CNTs to HChu et al.  proposed2O sensitivity of the sensor, albeit to a limited degree.As a result of the research, it was found that a more effective approach to optimizing the parameters of carbon-based humidity sensors is the application of composite structures. In particular, it was found that the formation of composites based on CNTs and cellulose nanofibers (CNFs) or nanofibrillated cellulose (NFC) can improve the performances of carbon-based sensors ,56. For A further study by Zhu et al.  showed t−1, and (iv) folding resistance, up to at least 50 times. As shown in 2O molecules. The presence of an additional sensitive layer on the surface of the paper substrate slows down this process even further. This conclusion is consistent with the observations above regarding the development of PB sensors with additional humidity-sensitive materials, according to which the simplest way to reduce the response/recovery time is to passivate the paper surface before applying the humidity-sensitive layer. This passivation layer should isolate the paper from contact with the atmosphere. Various methods can be used in this processing to supply the paper with superhydrophobic properties, such as laser ablation [According to Zhu et al. ,55,56, tablation , the useablation , coatingablation ,70, and ablation ,72.0, is linear, reaching 250% (It is interesting that humidity sensors based on graphene nanoplatelets (GNPs) have a much higher sensitivity to moisture than CNT-based sensors . The chaing 250% c, and thing 250% d. FurtheThe comparative data from the tests of resistive humidity sensors that employ solid materials as the detector elements are brought together in 2O molecules. For the conductivity of ZnO to efficiently control the resistance of the sensors, it is necessary to significantly reduce the resistance of ZnO, which can be achieved through doping or by changing the deposition technology.It can be seen that the conductometric responses of sensors can vary over a very wide range, depending on the material used and the method of processing. Sensors using CdS  and ZnO 2O in a wider range of relative humidity, albeit with a rather low response  groups are attached to long molecular chains of cellulose. Upon exposure to H2O, the molecular bonds in these acetyl groups are broken, releasing acetic acid [2 in this process is indicated by the fact that the current magnitude observed without the SiO2 NPs film is 30 times less than that with the SiO2 NPs film, at a relative humidity of 40%. Kano et al. [2 NP film under bending. However, the sensor remained functional even after a 500-fold bending test at r = 1.3 mm.In principle, SiOo et al.  develope0–93% RH a, with a0–93% RH b. The retic acid . This seo et al.  showed tThe characteristics of paper-based humidity sensors with polymer detector elements are listed in 2O vapors, the effective resistance of PANI films changes due to the appearance of hydrogen bonds between the water molecules and nitrogen present in the amino group [It can be seen that most of the studies were carried out using polyaniline (PANI) ,82. Amonno group . In addino group  and polyno group  were tesStudies have shown that polymer-based humidity sensors exhibit higher sensitivity than those based on carbon-based materials  sensors, surface acoustic wave (SAW) sensors, capacitive micromachined ultrasonic transducers (CMUTs), and microcantilevers. Mass-sensitive moisture detection is mainly based on the piezoelectric effect, which converts the change in mass of a humidity-sensitive material after the absorption of water molecules into a change in frequency. The sensitivity of these sensors largely depends on the properties of the paper used as a humidity sensitive material, namely the density of the paper and its adsorption capacity. Most studies consider cellulose nanocrystals (CNC) as humidity-sensitive materials in QCM devices ,108,109.2O vapors interact with a detector material deposited on the surface of the optical fiber [In principle, fiber-optic humidity sensors should be of increased interest because fiber sensors are cheaper than conventional electrical sensors and better suited to use in hazardous or explosive environments, or when immunity to electromagnetic interference is required . They alal fiber . Fiber-oal fiber ,115, caral fiber , liquid al fiber , or cellal fiber   technologies have been applied in many industries to automatically identify and track objects such as packaged goods during storage, handling, and transport in the supply chain. Radio-frequency identification with an additional sensory function  allow the improved monitoring of goods with more diverse and newer technologies. Therefore, they have received significant attention in both industry and academia ,125. OneD method ,132.The structures and principles of operation of RFID sensor tags, as well as the method used to perform humidity measurements, are discussed in detail elsewhere . The mos2O molecules more efficiently if a faster response is required.As sensitive elements in RFID sensor tags, electric LC-resonators are ordinarily employed; a typical structure of these resonators is shown in 2O input, while the external dipole arm was applied for chipless identification.Another variation of the paper-based resistive humidity sensors developed by Quddious et al.  for use 2, 88 μm thick) and Ag-based ID electrodes. The area of the designed sensor was 2 × 2 cm2. The width and the spacing of the ID electrodes were both 300 μm. A copper coil, 2 cm in diameter, was used as a readout antenna.The parameters of other RFID humidity-sensor tags are listed in In the literature, there are further examples of the design of humidity sensors beyond those reviewed above. Here, we survey some of the more remarkable cases, which are worthy of discussion.One of the non-traditional approaches to the development of PB humidity sensors is the use of shape deformation under the influence of moisture ,138. The−1 to 0.260 cm−1 when the relative humidity changed from 25% to 85%, and the response time was only 3–5 s. The excellent humidity response was due to the addition of GO, which actively interacted with the water, increasing the flexibility and sensitivity of the composite films to moisture.Research has shown that this simple shape-deformation-based humidity-detection method can be implemented using inexpensive paper materials. Various approaches can be used for this purpose. For example, one side of a paper-based cantilever may be coated with a moisture-swellable polymer . The mec−1). The thickness of the CNT-paper/BOPP composite film was 76 μm. The CNT-paper/BOPP actuator was manufactured at 60% RH and, therefore, the actuator was not bent at this humidity. When the relative humidity decreased to 14%, the actuator bent towards the CNT-paper. The curvature rapidly enlarged in the first 60 s. When the relative humidity increased to 60%, the CNT-paper/BOPP drive returned to its initial flat state. In addition, the relative humidity continued to enhance rapidly in the first 60 s. Cao et al. [3C2Tx) and polydopamine (PDA) (G-MXCP) is also sensitive to moisture. To form this structure, a layer-by-layer assembly method was employed, which was based on a vacuum-filtration process. Cao et al. [Zhou et al.  developeo et al.  showed to et al.  found thAn interesting approach to the development of a humidity sensor was proposed by Wu et al. . They ab2O levels with the naked eye. An example of the implementation of these sensors is shown in It is worth noting that the bending of sensors that are optimally designed is reversible and directional, and allows cyclicity. In addition, the bending of the cantilever can be controlled by the thickness of the films applied in the sensor. In very thick films, bending is not observed. It is clear that such sensors are not very accurate. However, it is an extremely simple method that allows the monitoring of humidity without external equipment or interface electronics. Thus, with the help of these devices, it is possible to control HAnother unusual approach to developing paper-based humidity sensors was proposed by He et al. . They usThe functional sensing characteristics of the devices were measured by applying an AC voltage. They are presented in Moist indicators are not strictly sensors. However, the basis of these indicators is usually paper. Therefore, we decided to include a description of moisture indicators in this review article.On some occasions, it is desirable to detect only the appearance of moisture in a sample, while the exact concentration is only of secondary importance. This situation can occur during the operation of drying chambers, in which a moisture breakthrough indicates a need for the regeneration of the dryers. In other cases, for example, it is necessary to ensure that the relative humidity does not exceed 30–35%. In many cases, humidity above 30–35% RH is of concern because the corrosion of various materials can occur at this humidity level. Studies have shown that this problem of qualitative and, sometimes, quantitative control over humidity levels can be solved by using cellulose paper impregnated with certain salt crystals that change color when wet. The use of this effect has been found to be the most economical method for detecting changes in humidity levels . ExperimAs the humidity increases further, the crystal structure changes again, this time rearranging to allow four more water molecules to surround each cobalt atom, forming the hexahydrate:Heating the hydrated forms of cobalt chloride reverses the above reactions, returning the cobalt chloride to its blue or anhydrous state. Water is “released” in these processes, which are known as dehydration reactions. Thus, this property makes it possible to create a color-changing indicator, which changes from blue to lavender and pink when the humidity increases, and becomes blue again when the humidity reduces. This characteristic has been found to allow these indicators to be reused if they are not exposed to humidity levels higher than 90% RH for 36 h or longer. With these treatments, cobalt chloride is washed out.Generally, cellulose and cellulose-acetate substrates form the basis of moisture indicators. However, other cobalt-impregnation materials can also be used . GeneralPaper-based moisture indicators are inexpensive, easy to store, and difficult to damage, and they can be used in many fields. The moisture indication can be performed by printing a comparative color guide next to the color-spot indication for ease of reading. Typically, a series of plots is labeled with values of relative humidity, typically in 10% increments from 10% RH to 80% RH, and various combinations of these humidity values.It has been established that irreversible moisture indicators can be also produced based on cobalt chloride. For these purposes, ammonia salts are added to the element. In the presence of ammonia vapor, the elements lose their color reversibility. These irreversible elements, frequently referred to as maximum-humidity-indicator cards, are necessary, for instance, to show when certain levels of humidity are exceeded or the recharging/replacement of a desiccant. These indicators can mark the highest humidity level encountered by cargo during a voyage regardless of current  humidity levels. Maximum moisture indicator cards provide a clear and unmistakable means of determining whether goods are exposed to harmful levels of humidity during their journey.As stated above, cobalt salts are water-soluble and, therefore, should not be in direct contact with water or steam, nor should they be exposed to extremely high humidity for extended periods of time. If these indicators are stored in a humid environment, they may become inaccurate. They are damaged by excessive moisture or condensation, which dilutes cobalt salt and results in nonuniform chemical distribution and inconsistent color response . Strong It should be noted that other salts can be used in humidity indicators, in addition to cobalt salts. Their development primarily followed a directive issued by the European Community (EC), in 1998, which classified products containing cobalt (II) chloride from 0.01 wt.% to 1 wt.% as toxic. Studies have shown that there is a fairly large range of materials that can also change color when exposed to a moisture ,166,167.Research has shown that humidity indicators can be developed on other principles. In particular, numerous studies have been carried out on cellulose nanocrystals (CNC), with the aim of studying reflection-color changes under the influence of air humidity. 3). This combination of polyelectrolytes, CHI and CMC, was chosen as the building material because CHI and CMC contain amino groups and carboxyl groups, respectively, which are charged in aqueous solutions and are easily chemically modified. These CHI/CMC-N3 films can swell/de-swell at various humidity levels. Due to the excellent hygroscopic swelling properties of cellulose, the thickness of the cellulose-derived hydrogel layer enhanced with increasing ambient humidity  PB humidity sensors usually have a fairly high sensitivity, with RH > 40% range. Sensors capable of operating in this sensitivity range are suitable for most applications. However, for special applications, it is desirable for sensors to operate effectively in the 10–40% RH range. Another limiting factor of most PB humidity sensors is their slow response and recovery. Consequently, PB humidity sensors cannot completely return to their original state within such certain time intervals (≈3–5 s) at room temperature, which reduces the accuracy of their measurements during cyclic changes in humidity . Therefo(2) Paper is sensitive to the state of the surrounding atmosphere, so PB devices require harsh storage conditions. Failure to comply with these conditions significantly reduces the period of storage and operation . This al(3) Various applications have specific paper requirements. Therefore, the ability to use paper with distinctive properties to meet the requirements of individual applications can be an effective approach to optimizing the performance of PB humidity sensors. For example, the use of hydrophobic paper makes it possible to reduce the influence of the paper substrate on the characteristics of humidity sensors see a when us(4) It is necessary to adapt the technology used to manufacture paper-based humidity sensors as much as possible to the requirements of mass production . In addi(5) The technologies used to manufacture flexible electrodes on paper substrates require further improvement. The electrodes used in PB humidity sensors should generally meet the following requirements: (i) good electrical conductivity; (ii) excellent mechanical flexibility; (iii) good adhesion to paper; (iv) a manufacturing process involving technologies compatible with mass-scale production; (v) low cost; and (vi) non-toxicity/low toxicity. Unfortunately, many of these requirements for electrodes in PB sensors are not met. The development of printable conductive inks and the use of advanced printing technologies  for the 2O molecules and the parameters of both humidity-sensitive materials and the electrodes formed on their surfaces. Furthermore, the stability of the parameters of bent sensors depends on the mechanical flexibility of the paper used. Stress–strain dependencies are crucial for studying the flexibility of materials, but they can only be determined for solid materials, while the structure of paper is characterized by heterogeneity and randomness [(6) Further challenges include the durability and stretchability of paper. The stretching properties of paper are generally poor. Therefore, great efforts should be undertake to conduct studies on this topic ,199,200,ndomness . In addindomness .(7) When developing PB humidity sensors, various humidity-sensitive materials can be used. However, they do not always determine the characteristics of humidity sensors, especially those of the resistive type. Very often, the resistance of humidity-sensitive materials is either excessively low resistance or excessively high. In the first case, the range of resistance changes is narrow, and in the second, the sensory response is controlled not by a sensitive material, but by a paper substrate. Neither case is optimal for achieving the best performance of sensors that use additional humidity-sensitive materials. Therefore, technologies for the synthesis and formation of humidity-sensitive layers with the required electrical parameters, which are optimal for use in humidity sensors, are urgently required. Paper-surface-passivation technologies are also necessary to reduce the influence of paper on the parameters of PB humidity sensors with additional humidity-sensitive materials.(8) New sensitive materials for PB humidity sensors need to be explored. At present, carbon and its derivatives  are the main sensing materials for PB humidity sensors. It is expected that the use of new materials will improve the performances of these sensors . Further(9) The impact of mechanical flexibility on PB humidity sensors must be reduced ,208. PapBased on the results obtained by Liu et al. , it was Regarding the AgNW-GO-ink electrodes, it is believed that their flexibility was mainly associated with two factors b. Firstl(10) Despite the great importance of multifunctional PB sensors, their development faces significant challenges ,215,216.Multifunctional PB sensors can be obtained by searching for materials specifically designed to detect gas, humidity, temperature, and strain ,220,221.According to the perceptual characteristics of different stimuli, cross-sensitivity effects can be reduced by means of various signal-conditioning modes, e.g., resistance, capacitance, frequency, and current.Multifunctional BP sensors can be implemented by combining a number of data-processing techniques, e.g., pattern recognition, principal component analysis, and machine learning.An example of a multifunctional paper-based testing system, developed for a healthcare monitoring , is prov2O molecules, as well as ionic diffusion in humidity-sensitive materials, are dependent on temperature. As the temperature rises, the conductivity of the materials used in the sensor increases in turn. Furthermore, the absolute humidity content, calculated as ordinary values in ppm (particles per million), increases as the temperature rises at a certain RH. This means that the characteristics of humidity sensors are also turn affected by the ambient temperature [(11) Notably, such processes as the adsorption and desorption of Hperature ,224, whiTwo solutions to this problem are possible. One (i) is to stabilize the temperature of the sensor, which is an energy-consuming method and increases the size of the measuring device. The other (ii) is to control the temperature, alongside the measurement of the humidity, and to automatically make appropriate corrections to the sensor readings ,226,227.(12) It is necessary to consider the development of integrated and automated systems based on paper platforms with multiple functions, such as sample preparation, separation, reaction, detection, processing, and the transmission of information . For rea13) The final issue is the ability to develop self-powered humidity sensors for wearable electronics ,245,246. The fina2 solution and maintained for 6 h, so that the cobalt-chloride solution could fully penetrate into its pores. A conductive tape was used as electrodes, equipped with a hole for penetrating water vapors. 2@FP sensor was placed in each humidity environment for 10 min to obtain the open-circuit voltage in the stationary state. At low humidity levels, of 11–33% RH, the voltage of the sensor approached 0 V (2@FP sensor for electric humidity sensors are long (143 s) and short (45 s), respectively. Kan et al. [Examples of the implementation of self-powered chemoelectric PB humidity sensors were presented in works by Kan et al.  and Li eched 0 V b. When tn et al.  stated tn et al.  found thn et al. , the PPyAnother solution is to drive a fast-response PB humidity sensor with another powered system. For example, microbial fuel cells (MFCs) , fluidicWhile paper offers significant potential as a development platform for humidity sensors, further improvements in fabrication and analysis methods are still needed to match the performance of the conventional humidity sensors currently on the market. The development of paper-based sensors is still in its infancy; therefore, currently, limitations remain regarding the sensitivity, accuracy, repeatability, and stability of paper-based sensors.After reviewing the parameters of paper-based humidity sensors, it is clear that extensive developments have taken place in recent years that have significantly improved the performances of these sensors, and there is no doubt that further advances will be made in this growing field in the future. This means that adequate sensor properties  will be achieved, and that these sensors will be used in the same areas as sensors on solid substrates and flexible polymer substrates. However, this requires further research related to the improvement of conventional methods and the search for new methods for the deposition of functional humidity-sensitive and electrode materials on paper surfaces, in order to overcome the concerns described in this study and to design better and more stable devices. Further in-depth and detailed research on paper-based sensors will also play a positive role in promoting their future maturity and commercialization. However, of course, when solving these problems, the simplicity and cost advantages of paper-based sensors must not be sacrificed .


More people than ever seek nutrition information from online sources. The chatbot ChatGPT has seen staggering popularity since its inception and may become a resource for information in nutrition. However, the adequacy of ChatGPT to answer questions in the field of nutrition has not been investigated. Thus, the aim of this research was to investigate the competency of ChatGPT in answering common nutrition questions. N = 18) or nutritionists and experts in the domain of each question (N = 9) to be graded based on scientific correctness, actionability, and comprehensibility. The grades were also averaged to give an overall score, and group means of the answers to each question were compared using permutation tests.  Dieticians were asked to provide their most commonly asked nutrition questions and their own answers to them. We then asked the same questions to ChatGPT and sent both sets of answers to other dieticians ( The overall grades for ChatGPT were higher than those from the dieticians for the overall scores in five of the eight questions we received. ChatGPT also had higher grades on five occasions for scientific correctness, four for actionability, and five for comprehensibility. In contrast, none of the answers from the dieticians had a higher average score than ChatGPT for any of the questions, both overall and for each of the grading components.  Our results suggest that ChatGPT can be used to answer nutrition questions that are frequently asked to dieticians and provide encouraging support for the role of chatbots in offering nutrition support. Over the last few decades, developments have made advanced technologies commonplace in everyday life in the developed world, facilitated by the accessibility and convenience enabled by the Internet and smartphones. This has led to an increased usage of these technologies for the acquisition of knowledge that previously would have only been available from healthcare professionals , 2. Now,Nutrition is one such field that has been particularly exposed to knowledge-seeking behaviour on the Internet. Studies show that a significant proportion of the population relies on the Internet for receiving nutritional information and that the majority of all sources of nutritional information in the developed world come from Internet-based sources, vastly more than books, journals, or other people , 5. WhilAlthough far from extensively studied, chatbots have been researched in a nutrition setting in recent years. Specialized chatbots have been developed for adolescents, the elderly, and for those wanting to manage chronic diseases –8. SinceIn fact, the challenges and opportunities of using ChatGPT in a variety of settings  were recently described . Indeed,Chatbots are also expected to play a role in the growing field of precision nutrition, which aims to provide tailored nutritional recommendations based on personal information , 14. SinThis makes it interesting and important to know if it is capable of adequately answering commonly asked nutrition questions. Successfully doing so prevents the need for nutrition laymen to search for specialized applications that may come with service fees and instead take advantage of the free-to-use, highly accessible, general-purpose ChatGPT offered by OpenAI. Conversely, if ChatGPT is unable to answer such questions to the standard of dietary experts, this too warrants attention since users of the application should be made aware that the information they receive from it may be unreliable.For these reasons, we sought to investigate how answers from ChatGPT compare to answers from human experts. We asked dieticians to list their most frequently asked questions and then answer them, before asking these same questions to ChatGPT. Across eight questions, the answers from ChatGPT outperformed those from dieticians, both overall and across every individual grading component. Our results provide valuable insights into the credibility of answers to commonly asked nutrition questions by the world's most used natural language processing application and can be used to inform the development of future generations of chatbots, particularly those tailored towards offering nutritional support.Our objective was to investigate the capabilities of ChatGPT in answering frequently asked nutrition questions. Registered Dieticians were asked to provide nutrition questions that they most commonly received, as well as provide their professional responses to these questions.We reached out to Registered Dieticians across the Netherlands through contacts within the university and networks of Registered Dieticians. Any questions related to nutrition reported by the dieticians would be included as long as they did not fall under the exclusion criteria. Exclusion criteria included questions that refer to very specific disease states or that afflict only a small portion of the population.In total, we received 20 questions from 7 dieticians. The dieticians had a median age of 31, a mean age of 39, and ranged from 29 to 65. All of the dieticians were female and lived and practiced in the Netherlands, either in private practices or medical centers. Of the 20 questions, 12 were excluded for containing information specific to medical conditions. The remaining 8 questions from three different dieticians thus constituted the final questions used in the study , and theAlthough Question 7 see  was giveThe questions were only asked once and the answer was recorded. Since the questions and answers (Q&As) were in Dutch, we requested that ChatGPT answered the questions in both Dutch and English. In two cases, modifications were necessary to remove one part in two questions that could have compromised blinding in the experiment, but the content and overall meaning of the answer were unaltered. These instances can be seen in The answers to each of the questions were then graded by other dieticians and experts in the field of the questions. A grading system was designed which could be used by multiple adjudicators and allow mean scores to be calculated and compared. Human dieticians and nutritionists must keep in mind key points when delivering nutritional information to their receivers, which the literature reports as including being a skilled listener and reader of emotions, making recommendations that the receiver can act on, tailoring recommendations in a personalized way, the client-dietician relationship, and communicating accurate scientific evidence in a comprehensible way, amongst others , 19. NatBased on these literature findings and the combined expertise of their authors in dietetics and nutrition counselling, three components by which to grade the answers to the questions in our study were selected: “Scientific correctness,” capturing how accurately each answer reflects the current state of knowledge in the scientific domain to which the question belongs; “Comprehensibility,” reflecting how well the answer could be expected to be understood by the layman; and “Actionability,” the degree to which the answers to the questions contain information that is useful and can be acted upon by the hypothetical layman asking the question. The rubric explaining how each component should be scored that was sent to the graders is presented in To further reduce bias in our methodology, we recruited experts in the field of each question and other dieticians  to grade the answers. Each set of answers was graded by 27 graders, which were split according to the nature of the components. One of the three components, scientific correctness, was concerned with specific domain knowledge, and therefore 9 of the 27 graders for each question were domain experts in the field of the question. Experts were recruited from universities or research institutes and were required to have worked with the question topic in their research. The other two components were more generally related to the transmission of information, and thus the remaining 18 graders were dieticians or nutritionists. As with the dieticians providing the Q&As, graders were blinded to the true goals of the study and the involvement of ChatGPT.All participants agreed to have their contributions used for scientific research and shared their contributions voluntarily and were free to withdraw at any time; there was no financial incentive. All participants were informed that their participation would be anonymous and that personal data would not be shared beyond the authors. The study was carried out in compliance with ethical standards and regulations of Wageningen University.p values were approximated from 100 000 simulations to gauge the strength of evidence of a difference between the groups. The study was registered and is described in more detail on Open Science Framework [t-tests in light of the statistical nature of the data obtained.A score of 0–10 was provided for each answer per question by each grader, allowing the evaluation of the answers as a whole and across each grading criterion. The statistical significance of group differences was derived using permutation tests with the function perm.test from the package jmuOutlier in R software  with theramework . The onlAll of the grades for each question can be seen in Figures 2The mean scores for actionability were higher for ChatGPT on four occasions, namely, Question 1 (6.85 for ChatGPT vs. 5.85 for the dieticians), Question 2 (7.93 for ChatGPT vs. 7.07 for the dieticians), Question 6 (8.43 for ChatGPT vs. 6.37 for the dieticians), and Question 8 (7.11 for ChatGPT vs. 6.06 for the dieticians), and there was a trend towards higher scores for ChatGPT in Question 7 (7.30 for ChatGPT vs. 6.37 for the dieticians). There were no clear differences for the remaining questions.Finally, grades were higher for ChatGPT on five occasions in the comprehensibility component, namely, Question 1 (8.04 for ChatGPT vs. 6.96 for the dieticians), Question 2 (8.30 for ChatGPT vs. 6.94 for the dieticians), Question 6 (8.30 for ChatGPT vs. 6.74 for the dieticians), Question 7 (8.04 for ChatGPT vs. 7.07 for the dieticians), and Question 8 (7.61 for ChatGPT vs. 6.35 for the dieticians). No other differences were found for the remaining questions.Neither the overall grades nor any of the individual grades per component were meaningfully higher for the dieticians on any of the questions. This can be seen in This is the first study to investigate the ability of ChatGPT to answer common nutrition questions. There was strong evidence of group differences in favour of ChatGPT, as evidenced by higher scores in five of the eight questions for the overall grades, whereas the dieticians did not have higher overall scores for any of the questions.In addition to averaging the scores of the grading components to give an overall grade, we hypothesized that analyzing the performance of the individual components separately might have revealed how performance differed between ChatGPT and the dieticians. However, no notable differences could be observed in the analysis of the individual components vs. the overall scores, and again ChatGPT had higher average scores for scientific correctness, actionability, and comprehensibility in five, four, and five of the questions, respectively. Strikingly, the average grades of the dieticians were not higher for any of the questions for each individual grading component. Hence, these results suggest that ChatGPT was generally better at answering nutrition questions than human dieticians. Additionally, whilst the dieticians who provided the questions and answers were Dutch, many of the graders were from diverse countries and backgrounds, and we have no reason to believe that the questions, answers, or results would not generalize outside of the Netherlands.Whilst the potential of ChatGPT for answering nutrition questions has not been investigated, chatbots have been experimented with in recent years in nutrition as a means of offering nutrition support –10. ThesIn a more clinical setting, AI-powered chatbots could change the work landscape of dieticians and their relationship with their clients, as was observed in a study of physicians in a healthcare field that has similarities to that of dieticians . It has Although not seen in the results of our study, there are some important issues to consider in using ChatGPT for the acquisition of knowledge. Firstly, ChatGPT provides no confidence about the validity of its own answers. Whilst ChatGPT scored highly in scientific correctness across all questions, it can get things wrong, though this is unbeknownst to itself or the user since there is no indication of the confidence of the answers that it provides. Secondly, a chatbot relies on the user to provide relevant information. Accurate and tailored dietary guidance often requires consideration of specific medical conditions, allergies, or lifestyle factors. Users may lack knowledge regarding the essential details required to deliver these accurate dietary recommendations. Additionally, despite being trained on a large amount of data, the data that ChatGPT was trained on are only available up until September 2021 . Whilst Some important limitations should also be considered when interpreting the results of this study. The answers to the questions were all in the range of around 100–300 words. Whilst this did not feel limiting to the dieticians that submitted the questions, it can also be argued that the topics of the questions could not be adequately answered in such a short space due to the nuances inherent to them. However, both parties—ChatGPT and the dieticians—had the same restrictions imposed, and thus the results are those of a level playing field. Additionally, it is important to contextualize the findings, and in this sense, when the questions require answers that leave out complexities and provide a simple overview that tackles the essence of the question, ChatGPT appears to be superior to human dieticians.The questions we received were loosely categorized into domains within nutrition. Only the question themes “Weight loss” and “Carbohydrates” appeared multiple times, and our sample size of eight questions could not permit an investigation of how ChatGPT performance might differ across subject areas. However, this should be considered in future similar research since the capabilities of ChatGPT appear to be inconsistent across different tasks, meaning its nutrition-specific subject strengths may also vary. This would be valuable to know as it could be taken into account when gauging the reliability of the answers provided by ChatGPT with regard to a specific question.We blinded the dieticians to the aims of the study. Whilst this was done to avoid influencing the Q&As that they provided us with, it should also be admitted that dieticians might have been more careful with their answers and have taken their task more seriously in a professional setting with a client, and so the grades for the answers from the dieticians might be an underestimation of what their true value would be. Additionally, since the analyzed questions were based on suggestions of a random sampling of dieticians, an avenue of future research could be to use the grounded theory approach  based onOverall, these findings may signify important differences in the way that people access nutrition information in the future. ChatGPT is virtually free, accessible at any time, and provides answers almost instantly, which are all advantages over human nutrition experts. Investigating the ability of ChatGPT and similar applications to offer nutrition and health support is imperative given the current trajectory of the use of chatbots in everyday life.We have shown that the general-purpose chatbot ChatGPT is at least as good as human dieticians at answering common nutrition questions that might be asked to a nutrition expert. Future work should investigate the potential of chatbots to provide information to educate and improve the dietary habits of users.