A good correlation  and concordance  between predicted and observed 1-year post-donation eGFR were observed. The area under the ROC curve showed a good discriminative ability of the formula in predicting observed CKD at 1-year post-donation  with optimal cutoff corresponding to a predicted eGFR of 65.25 mL/min/1.73 m2 in which the sensibility and specificity to predict CKD were respectively 77% and 75%. The model was successfully validated in our cohort, a different European population. It represents a simple and accurate tool to assist in evaluating potential donors.A predictive model to estimate post-donation glomerular filtration rate (eGFR) and risk of CKD at 1-year was developed from a Toulouse-Rangueil cohort in 2017 and showed an excellent correlation to the observed 1-year post-donation eGFR. We retrospectively analyzed all living donor kidney transplants performed at a single center from 1998 to 2020. Observed eGFR using CKD-EPI formula at 1-year post-donation was compared to the predicted eGFR using the formula eGFR (CKD-EPI, mL/min/1.73 m  Living donor kidney transplant is the best treatment for ESRD patients eligible for transplant , 2. LiviThe evaluation of a living donor candidate is a multidisciplinary task to minimize the risk for the donor while ensuring the organ’s suitability for the recipient , 5. DespCurrent Clinical practice guidelines on the evaluation and care of living kidney donors from Kidney Disease Improving Global Outcomes (KDIGO) recommend a comprehensive approach to risk assessment that should replace decisions based on assessments of single risk factors evaluation . TransplA predictive model to estimate the donor 1-year post-donation estimated glomerular filtration rate (eGFR) and risk of CKD was developed from a Toulouse-Rangueil cohort in 2017 . Benoit We sought to externally validate this predictive tool in a different, large European cohort of patients who underwent a living donor kidney transplant at our center.This external validation study was conducted according to the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnostics (TRIPOD) guidelines .n = 366) the donors who underwent nephrectomy for living donor kidney transplantation at our institution between 1998 and December 2019. After excluding 33 donors, in whom eGFR at 1 year was missing, the remaining 333 donors were included in this study.We retrospectively reviewed the clinical data of all  after donation.Data are presented as mean (and standard deviations for continuous variables and frequency (and percentages) for categorical variables.2) = 31.71 + (0.521 × preoperative eGFR) − (0.314 × age).Observed eGFR using CKD-EPI formula at 1-year post-donation was compared to the predicted eGFR using the formula developed in Toulouse-Rangueil: postoperative eGFR  curve and using sensitivity, specificity, and positive, or negative predictive values (PPV or NPV). Furthermore, the accuracy of the predictive model was depicted by constructing a calibration plot and assessed through the calibration slope and the calibration in the large.p-value < 0.05 was considered as statistically significant. Statistical calculations were performed using STATA/MP, version 15.1 .A 2-sided 2. Fifty donors (15%) were hypertensive pre-donation, and fifty-one (15%) had smoking habits. Pre-donation mean eGFR was 100.3 ± 14.7 mL/min/1.73 m2, while the mean 1-year post-donation eGFR was 71.4 ± 16.2 mL/min/1.73 m2. The mean predicted 1-year post-donation GFR was 69.1 ± 10.0 mL/min/1.73 m2.The baseline donors’ characteristics for the cohort of 333 patients are presented in Eighty-five donors (25.5%) reached the definition of CKD at 1-year after donation as depicted in p < 0.001; Pearson R = 0.67), as shown in 2   .p < 0.001), as shown in 2 , for which the sensibility and specificity to predict CKD were respectively 77% and 75% , for which the sensibility and specificity to predict CKD were respectively 66% and 85%. For the male sex, the optimal cutoff was similar to the global cohort, for which the sensibility and specificity to predict CKD were 77% and 82%, respectively.Furthermore, the model showed a good discriminative ability of the formula in predicting observed CKD at 1-year post-donation, with the area under the receiver operating characteristic (ROC) curve of 0.83 , and for the prediction of CKD  at 1 year after donation, the model presented an AUROC of 0.83, which represents an excellent performance. Benoit et al. (r = 0.66), and for the prediction of CKD at 1 year, the model presented an AUROC of 0.86. We must emphasize that the optimal value of predicted eGFR was around 5 mL/min higher than the equality cutoff for CKD detection at 1 year, an outcome that was correctly predicted (both its presence and absence) in every 3 out of 4 donors. This tool represents a non-invasive, low cost and readily available tool that can be joined to the living donor evaluation routine consultation, improving the living donor risk estimation and the informed consent process. The predicted eGFR value ≥ 65.25 mL/min was associated with a very high NPV (90%), identifying donors that are clearly admissible concerning renal function . Women are more likely than men to become living kidney donors , 25. In We must recognize the limitations associated with this study, beginning with its retrospective and observational design. Thirty-one donors were excluded from the study because 1-year serum creatinine was unavailable to calculate eGFR. Still, later creatinine values were available and were not different from the rest of the cohort. We assume it would not compromise the results of our validation cohort. All patients were Caucasians, but they were representative of the Portuguese population. Other races and ethnic origins are not represented. We used CKD-EPI to calculate eGFR and not an isotopic method. However, we must point out the unsuitability of the latter in clinical practice, as it is not recommended as a standard of care by current guidelines , and theThe primary goal in assessing a living donor candidate must ensure minimal risk to the donor. Hence, the prediction of postoperative renal function is a critical point in their evaluation and, in our population, can be achieved with this tool. Furthermore, the required variables are low-cost and easily assessed, so its potential as a counseling tool is undeniable. We recall, however, that validation out of Europe is lacking and that further studies are necessary to validate prognostic models for longer-term prediction of donor kidney function.The formula developed in Toulouse-Rangueil was successfully validated in our cohort, a different European population than previously described. We must, anyway, emphasize that the optimal value of predicted eGFR was around 5 mL/min higher than the equality cutoff for CKD detection at 1 year. This model represents a simple and accurate tool that may be used to assist in the evaluation of potential donors, particularly in the current setting of increasing donor age, donors with minor comorbidities, or renal function close to the accepted threshold.


Viral and autoimmune encephalitis may present with similar symptoms, but require different treatments. Thus, there is a need for biomarkers to improve diagnosis and understanding of pathogenesis. We hypothesized that virus-host cell interactions lead to different changes in central nervous system (CNS) metabolism than autoimmune processes and searched for metabolite biomarkers in cerebrospinal fluid (CSF) to distinguish between the two conditions.We applied a targeted metabolomic/lipidomic analysis to CSF samples from patients with viral CNS infections , autoimmune neuroinflammation , and non-inflamed controls . 85 metabolites passed quality screening and were evaluated as biomarkers. Standard diagnostic CSF parameters were assessed for comparison.ρ = 0.41 and 0.44), indicating that their increase is not primarily driven by inflammation.Of the standard CSF parameters, the best biomarkers were: CSF cell count for viral infections vs. controls , Q-albumin for viral infections vs. autoimmune neuroinflammation (AUC = 0.86), and IgG index for autoimmune neuroinflammation vs. controls (AUC = 0.90). Concentrations of 2 metabolites differed significantly (p < 0.05) between autoimmune neuroinflammation and controls, with proline being the best biomarker (AUC = 0.77). In contrast, concentrations of 67 metabolites were significantly higher in viral infections than controls, with SM.C16.0 being the best biomarker (AUC = 0.94). Concentrations of 68 metabolites were significantly higher in viral infections than in autoimmune neuroinflammation, and the 10 most accurate metabolite biomarkers (AUC = 0.89–0.93) were substantially better than Q-albumin (AUC = 0.86). These biomarkers comprised six phosphatidylcholines (AUC = 0.89–0.92), two sphingomyelins , and acylcarnitines isobutyrylcarnitine  and isovalerylcarnitine . Elevated C4 and C5 concentrations suggested dysfunctional mitochondrial β-oxidation and correlated only moderately with CSF cell count (Spearman Changes in CNS metabolism differ substantially between viral CNS infections and autoimmune neuroinflammation and reveal CSF metabolites as pathophysiologically relevant diagnostic biomarkers for the differentiation between the two conditions. In viral CNS infections, the observed higher concentrations of free phospholipids are consistent with disruption of host cell membranes, whereas the elevated short-chain acylcarnitines likely reflect compromised mitochondrial homeostasis and energy generation.The online version contains supplementary material available at 10.1186/s12967-023-04637-y. Encephalitis continues to exert a strong disease burden and to present diagnostic challenges. The incidence of encephalitis is about 10–20 per 100,000 in the United States , but 20–Despite the sequelae evoked by the primary virus infection itself, viral relapses can occur as well as secondary autoimmune processes leading to autoimmune neuroinflammation. In the case of HSV encephalitis, about 25% of all patients experience a relapse either by virus reactivation or, in 15–20% by an autoimmune anti-n-methyl-D-aspartate-receptor (NMDAr) encephalitis , 7. In aAdvances in diagnostics have enabled us to identify several well-characterized autoantibodies that cause autoimmune encephalitis, but the results are not available in the acute setting, as turnaround time may be up to 1–2 weeks depending on work flows in diagnostic laboratories. Moreover, about 50% of encephalitis patients remain without etiological diagnosis and it is unknown how many of these actually suffer from an autoimmune encephalitis. Considering that viral and autoimmune encephalitis require completely different treatments , there is a clear need for diagnostic biomarkers to distinguish between these two entities as soon as possible after lumbar puncture. Apart from the detection of a viral pathogen or a specific autoantibody, there are several biomarkers that aid to differentiate viral from autoimmune encephalitis. CSF leukocyte count is one of the best-known CSF markers, and together with clinical parameters  the absence of inflammatory changes in CSF has been used to generate a risk score for autoimmune encephalitis  . CSF oliQuantifying metabolites in cerebrospinal fluid (CSF) is a promising approach to identify novel biomarkers for infectious and inflammatory CNS disorders, as CSF is in intimate contact with the target organ and has been evaluated as “liquid biopsy” for CNS pathology essentially since development of lumbar puncture in the nineteenth century. Moreover, small molecules can potentially be developed to rapid diagnostics that can be performed after lumbar puncture at the bedside or in an acute services lab and thus have the potential to provide shorter turn-around time than detection of pathogenic viruses and autoantibodies. We have previously applied a targeted metabolomics approach to measure 188 small molecules in CSF from 221 patients with infectious, autoimmune, and non-inflammatory CNS disorders. In previous publications we reported the identification of accurate biomarkers for CNS involvement in varicella-zoster virus reactivation , for entWe present a subtotal analysis of a cohort of CSF samples from 221 patients, which were collected between 2005 and 2013. The study was approved by the Ethics Committee of Hannover Medical School (file no. 2413–2014). Other findings in this cohort relating to CSF biomarkers have been described in . For theThe following standard CSF parameters were determined: cell count, protein concentration, lactate concentration, Q-albumin , and IgG index . Blood-CSF-barrier (BCB) dysfunction was scored from 0 (no dysfunction) to 3 (severe dysfunction), using age-corrected Q-albumin as described in . LeukocyCSF metabolite concentrations of the entire cohort were measured in 2015 in one batch using a triple-quadrupole mass spectrometer  with an electrospray-ionization ion source coupled to a high-performance liquid chromatography system  and the AbsoluteIDQ™ p180 kit and MetIDQ™ software  as described in detail in . The folAs in our recent study of CSF metabolite biomarkers for bacterial vs. viral CNS infections , we onlywww.metaboanalyst.ca). R package “ROCR version 1.0.11” [Considering the non-normal distribution of the data, correlations were determined with the Spearman method, differences in median values between groups with the Mann–Whitney U test, and differences across groups with the Kruskall-Wallis test. Differences in categorical variables were assessed with the Chi – squared test. Biostatistical and bioinformatics analyses were carried out using R version 4.2.2. unless stated otherwise. Principal component analysis (PCA) was carried out with the R package "FactoMineR version 2.8"  and the  1.0.11”  was used 1.0.11” , 24. We  1.0.11” . Sensiti 1.0.11” .Sociodemographic and clinical data of the three groups are summarized in Table We used principle component analysis (PCA) to obtain an overview over differences in CSF metabolites among the three groups. Indeed, there was a tendency toward separation between viral CNS infections and autoimmune neuroinflammation, which was about as pronounced as the separation between viral CNS infections and controls, whereas autoimmune neuroinflammation and controls overlapped considerably Fig. A-C. For Considering the lack of an external validation cohort, we performed a HAUCA curve analysis to estimate the likelihood of identifying false positive biomarkers by ROC analysis  fulfilled these criteria for the differentiation between viral CNS infections vs. autoimmune neuroinflammation, and 37 (44%) for the differentiation between viral CNS infections vs. controls. There were no accurate biomarkers for autoimmune neuroinflammation vs. controls, as the highest AUC was 0.77. Consistent with the heat map shown in Fig. We then applied ROC curve analysis to screen the metabolite data set for accurate biomarker candidates Fig. . We defiUsing trade-off values in the ROC curves at the maximal Youden index values, we then determined sensitivity, specificity, and positive and negative predictive value  of the same standard parameters and the six CSF metabolites with the highest AUC for the differentiation between viral CNS infections and autoimmune neuroinflammation Table . Even thWe then tested whether concentrations of the top 6 biomarkers differed by diagnostic subgroup within each of the three supergroups Fig. . Among tρ) were modest, ranging from -0.25 (arginine) to 0.65 (proline). The correlation coefficients of the six top biomarkers ranged from 0.28 to 0.58, indicating that the observed changes in their concentrations were only partially driven by CNS inflammation and may, for instance, reflect alterations in CNS resident cells.We then tested to what extent concentrations of CSF metabolites across all samples correlated with CSF leukocyte count as a measure of neuroinflammation Fig. . Most coWe performed a targeted metabolomic analysis of CSF samples from patients with viral CNS infections, autoimmune neuroinflammation, and noninflamed controls and found that CSF metabolites were more accurate biomarkers than standard diagnostic CSF parameter for the differentiation between viral CNS infections and autoimmune neuroinflammation, whereby the short-chain acylcarnitines C4 (isobutyrylcarnitine) and C5  were among the best metabolite biomarkers.Acylcarnitines are intermediates of beta-oxidation, i. e. the metabolism of fatty acids to acetyl-CoA, which is fed into the tricarboxylic acid cycle as energy source and building block. Elevated extracellular levels of short-chain acylcarnitines usually reflect a dysfunction of beta-oxidation of saturated fatty acids in mitochondria, which leads to the conjugation of accumulating fatty acid fragments to the carrier molecule carnitine. These acylcarnitine complexes are then extruded into the cytoplasm and subsequently into the extracellular environment . In our All other accurate biomarkers for viral CNS infections vs. autoimmune neuroinflammation were membrane phospholipids, and their concentrations were always higher in viral CNS infections. This agrees well with our previous observations that, even though the highest phospholipid levels in CSF are found in bacterial meningitis , elevateUsing LC–MS/MS analysis of the same cohort, we have previously reported that CSF kynurenine and the tryptophan/kynurenine ratio constitute biomarkers for the differentiation between viral CNS infections and autoimmune neuroinflammation , which wBorrelia sp. or VZV [The diagnosis of Bell’s palsy is made in individuals with acute onset of paralysis of the facial nerve after excluding known causes of facial neuritis including infections with, e.g., . or VZV . Major r. or VZV . Taken tOur study is limited in that the samples were collected at a single center and we could, therefore, not perform an external validation, which would provide stronger evidence for the validity of the biomarkers. The results should, therefore, be replicated in an independent cohort before further development to a clinical diagnostic can be considered. In addition, the exact molecular identity of some of the identified phosphatidylcholines needs to be defined further, as some of them correspond to more than one isobar or isomer. This metabolomics analysis targeted only a selection of metabolite classes, and other markers for mitochondrial function  or membrane perturbation  were not included. The Human Metabolome Database (hmdb.ca) lists 468 endogenous CSF metabolites, and a broader screen might detect additional biomarkers. On the other hand, a clear strength of the study is that all specimens were collected using a standardized protocol and that definitive diagnoses according to viral pathogen and inflammatory disorder were available.Additional file 1: Fig. S1. Quality screen used to identify analytes to be included in the analysis. Analytes were included that were detected ≥ LOD in ≥ 80% of all samples. The numbers on top of the bars state the number of analytes that passed this screen divided by the total number of analytes in the respective metabolite subgroup. Detection efficiency was highest for amino acids, but phosphatidylcholines constituted the largest group of included analytes. Abbreviations: AA, amino acids; AAM, amino acid metabolites; AC, acylcarnitines; lysoPC, lysophosphatidylcholines; PC, phosphatidylcholines; SM, sphingomyelins; Hex, sum of hexoses. Fig. S2. Phospholipids make the greatest contributions to variance in the CSF metabolite populations. A, C, E. Scree plots illustrating the contribution of each dimension to overall variance in 85 metabolites in the PCA shown in Fig. Fig. S3. Correlations among concentrations of the 85 CSF metabolites across all samples. Correlations among all analytes were determined using Pearson correlation analysis. The resulting Pearson correlation coefficients (ρ) were then used as input into a hierarchical clustering analysis. The correlation coefficient values are indicated by the color scheme shown in the legend. The arrows point to short-chain acylcarnitines C4 and C5. Fig. S4. HAUCA curve analysis to assess the likelihood of false positive biomarker identification. The number of biomarkers exceeding a given AUC value in ROC analysis is plotted on the x-axis. The analysis compares the number of biomarkers identified in the real data set (blue curve) to those identified in a random data set of the same variance (black curve), indicating the number of biomarkers expected by chance alone. The red curve delineates the upper bound 95% CI of the random data set. An AUC of 0.8 was used as AUC cut-off to define accurate biomarkers in the ROC curve analysis shown in Fig.  Table S1. Diagnostic criteria and clinical information. Table S2. Demographic and clinical laboratory characteristics of the seven subgroups. Table S3: Differences among the metabolite classes in biomarker potential. Table S4. Comparison of standard parameters and the 10 most robust CSF metabolite biomarkers to differentiate between viral CNS infections and controls. Table S5. Comparison of standard parameters and the 10 most robust CSF metabolite biomarkers to differentiate between autoimmune neuroinflammation and controls. Table S6. Comparison of common blood and CSF standard diagnostic parameters and the top five CSF metabolite biomarkers: sensitivity, specificity, PPV, and NPV for viral CNS infections vs. controls. Table S7. Comparison of common blood and CSF standard diagnostic parameters and the top five CSF metabolite biomarkers: sensitivity, specificity, PPV, and NPV for autoimmune neuroinflammation vs. controls. Table S8. Sex-specific concentrations in Bell’s palsy CSF samples of the top 6 CSF metabolite biomarkers for the differentiation between viral CNS infections and autoimmune inflammation.


MTBR-tau243 was most strongly associated with tau-positron emission tomography (PET) and cognition, whereas showing the lowest association with amyloid-PET. In combination with p-tau205, MTBR-tau243 explained most of the total variance in tau-PET burden (0.58 ≤ R2 ≤ 0.75) and the performance in predicting cognitive measures (0.34 ≤ R2 ≤ 0.48) approached that of tau-PET (0.44 ≤ R2 ≤ 0.52). MTBR-tau243 levels longitudinally increased with insoluble tau aggregates, unlike CSF p-tau species. CSF MTBR-tau243 is a specific biomarker of tau aggregate pathology, which may be utilized in interventional trials and in the diagnosis of patients. Based on these findings, we propose to revise the A/T/(N) criteria to include MTBR-tau243 as representing insoluble tau aggregates (‘T’).Aggregated insoluble tau is one of two defining features of Alzheimer’s disease. Because clinical symptoms are strongly correlated with tau aggregates, drug development and clinical diagnosis need cost-effective and accessible specific fluid biomarkers of tau aggregates; however, recent studies suggest that the fluid biomarkers currently available cannot specifically track tau aggregates. We show that the microtubule-binding region (MTBR) of tau containing the residue 243 (MTBR-tau243) is a new cerebrospinal fluid (CSF) biomarker specific for insoluble tau aggregates and compared it to multiple other phosphorylated tau measures  in two independent cohorts (BioFINDER-2,  CSF MTBR-tau243 is more related to tau tangles and clinical cognitive impairment in Alzheimer’s disease than phospho-tau biomarkers, which are more related to amyloid plaques. PET with radio ligands that bind to fibrillar forms of tau reflect the burden of insoluble AD-specific tau aggregates in the brain, including neurofibrillary tangles (NFTs) and neuropil threads6. Tau-PET imaging studies have shown that insoluble tau aggregates are strongly associated with cognitive decline even during the early pre-symptomatic stages of AD7 and tau-PET is the most accurate prognostic marker of AD available today8; however, PET imaging is highly expensive and needs a complex infrastructure, which reduces its use to only highly specialized centers. In contrast, fluid biomarkers are less expensive and are more clinically accessible. The most widely used fluid biomarkers of tau are N-terminal or mid-domain total tau (t-tau) and phosphorylated tau species resulting from cleavage near residue 224 of tau10, including tau phosphorylated at residues 181, 217 and 231  (refs. 17). But, these biomarkers are strongly associated with increasing burden of amyloid plaques more than insoluble tau aggregates20. For instance, plasma and CSF concentrations of these p-tau species are already increased in preclinical AD many years before widespread insoluble tau aggregates in the neocortex are observed24. Further, recent clinical trials have demonstrated substantial reductions of CSF or plasma concentrations of t-tau, p-tau181 and p-tau217 (refs. 28) in response to anti-amyloid passive immunotherapies, which substantially remove amyloid plaques. Neuropathological and imaging studies have also reported strong associations between these fluid biomarkers and amyloid plaques29. In addition, animal studies have found that CSF t-tau and p-tau are increased in mouse models with amyloid β (Aβ) pathology, even when no aggregated tau pathology is observed32. Taken together, these findings indicate that plasma and CSF concentrations of N-terminal to mid-domain t-tau and p-tau do not directly represent insoluble tau aggregates, but rather reflect a response to amyloid plaque pathology. Thus, there is currently no fluid biomarker that specifically reflects AD-related tau pathology.Given the growing interest in tau-targeted therapeutics for Alzheimer’s disease (AD), there is a critical need for reliable and specific biomarkers of insoluble, aggregated tau to understand AD pathophysiology and to evaluate the effects of treatments37, but these fragments have been poorly investigated as candidate biomarkers. In an initial study, with a small sample size of controls and AD patients (n = 35), we showed preliminary results that MTBR-tau was present in human CSF and that a specific MTBR-tau species containing residue 243 (MTBR-tau243) was strongly associated with tau-PET and disease progression33. Here, we expanded these results to two large independent sporadic AD cohorts, the Swedish BioFINDER-2 study and the Charles F and Joanne Knight Alzheimer Disease Research Center (Knight ADRC), covering the whole AD continuum, with available amyloid-PET and tau-PET images. In this study, we compared the performance of MTBR-tau243 to other CSF phosphorylated tau measures, including p-tau181, p-tau205, p-tau217 and p-tau231 phosphorylation occupancies , which are also reported as biomarkers to recapitulate AD pathologies29 and we showed that MTBR-tau243 was the fluid biomarker most strongly associated with tau-PET. We also investigated the proportion of variation in CSF biomarker levels explained by amyloid-PET and tau-PET measures of pathology. Then, we evaluated longitudinal CSF biomarker changes to investigate their rate of change based on the presence or absence of amyloid and tau pathologies to indicate which are increasing with amyloid versus tau pathologies. Finally, we assessed whether prediction of continuous AD-related measures could be improved by the combination of multiple biomarkers and found that MTBR-tau243, together with p-tau205, could optimally predict tau-PET measures and cognitive impairment.In this study, we therefore evaluated a new CSF biomarker of insoluble tau aggregates. Notably, tau species that contain MTBR-tau are a major component of insoluble tau aggregates in the brainAPOE ε4 carriers. The Knight ADRC cohort included 219 individuals, most of whom were cognitively unimpaired : 83 CU−, 88 CU+, 35 very mild AD and 13 AD+. The average age was 71.2 ± 6.6 years, 112 (51.1%) were women and 96 (43.8%) were APOE ε4 carriers : 81 cognitively unimpaired Aβ negative (CU−), 79 cognitively unimpaired Aβ positive (CU+), 90 Aβ positive with mild cognitive impairment (MCI+), 102 Aβ positive with AD dementia (AD+) and 96 with other dementias (non-AD)  and in amyloid-positive participants  in all participants and in amyloid-positive particip = ants , temporal (Braak III–IV) and neocortical (Braak V–VI)) were also investigated as an additional analysis. Comparisons in the amyloid-positive only group demonstrated that CSF MTBR-tau243 had the highest correlations with all Braak regions  = 0.57, 74.7% R2 versus tau, pR2 = 0.19, 24.7% R2, Pcomp < 0.001; Fig. R2 = 0.46, 76.0% R2; tau, pR2 = 0.02, 3.3% R2, Pcomp < 0.001) and pT181/T181  were also significantly better explained by Aβ pathology. In contrast, variance in CSF MTBR-tau243 concentrations were significantly better explained by tau pathology . The contribution of tau and amyloid to CSF pT205/T205 was similar, with the difference between both being non-significant .Next, we evaluated the proportion of variation in CSF biomarkers explained by amyloid and tau pathologies. CSF biomarker levels were included as the outcome and amyloid-PET and tau-PET were both included as predictors controlling for age and sex, in our models. In the BioFINDER-2 cohort, variance in CSF pT217/T217 levels was significantly better explained by Aβ pathology as assessed with amyloid-PET, than tau  were tau-PET positive). CSF pT217/T217 , pT181/T181  and pT231/T231  were better explained by Aβ pathology. In contrast, tau pathology was the major contributor on explaining variance in CSF MTBR-tau243 levels . Of note, pT205/T205 levels were explained similarly by both tau and amyloid . CSF Aβ42/40 continued to be the major factor associated with CSF pT231/T231  and pT181/T181 . In these models, tau pathology remained the major factor explaining variance in MTBR-tau243 levels . For pT205/T205, the major contributor was tau pathology  although the difference was not significant in Knight ADRC .Because dementia patients of BioFINDER-2 did not undergo amyloid-PET, analyses were repeated in both cohorts with all participants using CSF Aβ42/40 rather than amyloid-PET as the measure of Aβ pathology , whereas the rate of increase in pT205/T205 was not significantly different in the A+T+ and A+T− groups  and tau (T) pathology status (+ and −). Characteristics of the 220 participants with longitudinal CSF measurements are described in Supplementary Table 39. We found that the longitudinal trajectories for all CSF biomarkers were replicated, with pT205/T205, but especially MTBR-tau243, rates of change increasing with progressing A/T status and the rest of biomarkers having the highest rate of change at A+T− status  and amyloid-positive participants  and amyloid-positive participants ; however, tau-PET was more strongly associated with MMSE than any CSF biomarker . Scatter-plots for each CSF biomarker are shown in Extended Data Fig. We assessed associations of CSF and PET biomarkers with a common clinical assessment of dementia, the Mini Mental State Examination (MMSE)Finally, we aimed to determine whether combinations of CSF biomarkers could be used as accurate quantitative surrogates for amyloid-PET, tau-PET or cognitive measures. We first evaluated the variance explained by each individual biomarker for each outcome. Next, we used the least absolute shrinkage and selection operator (LASSO) procedure to select which combination of CSF biomarkers were optimal for each outcome and then, we compared this new model to the ones from the individual biomarkers.R2 = 0.73, corrected Akaike information criterion (AICc) = 404.5; Knight ADRC, R2 = 0.73, AICc = 265.2; Fig. R2 = 0.77, AICc = 370.2, F = 20.974, P < 0.001; Knight ADRC, R2 = 0.73, AICc = 261.7, F = 5.266, P = 0.006; Extended Data Table CSF pT217/T217 was the individual biomarker that best predicted amyloid-PET , which indicates its potential utility in the clinical setting. Further, we found that CSF MTBR-tau243 is the biomarker with the largest rate of increase in participants that are already positive for both amyloid and tau pathologies, suggesting that CSF MTBR-tau243 best reflects disease progression in late stages. We further extended these findings by combining CSF MTBR-tau243 with phosphorylated tau measures to predict Aβ pathology, tau pathology and cognitive measures in the AD continuum. We found that CSF MTBR-tau243 in combination with pT205/T205 can accurately predict continuous tau-PET measures and has similar predictive accuracy for cognitive measures as tau-PET. Based on these results, our study suggests that CSF MTBR-tau243 may be a viable alternative to tau-PET for use as a pre-screening tool or a tau pathology end point surrogate for clinical trials and also as an accurate diagnostic measure of tau pathology.43, and by being more tightly associated with amyloid-PET than tau-PET44 or to actual amyloid pathology in postmortem studies45. Finally, we found that MTBR-tau243 was particularity increased in two cases of MAPT R406W mutation carriers that were amyloid negative but had high tau-PET binding. Tau pathology on MAPT R406W mutation carriers is known to be similar to AD tau pathology47 and reactive to AD tau-PET tracers50, further supporting our finding that MTBR-tau243 is a specific biomarker to AD-like tau pathology.Our first objective was to characterize MTBR-tau243 concentration and compare it to four phosphorylated tau measures by looking at their associations with Aβ and tau pathologies measured by PET. Notably, MTBR-tau243 was the tau biomarker that demonstrated the highest correlation with tau-PET and the lowest correlation with amyloid-PET, not only in the whole group, but also in Aβ-positive group. This suggests that MTBR-tau243 is a biomarker that specifically reflects aggregated tau pathology independent of amyloid pathology. Although pT217/T217 was also well correlated with tau-PET, there was a nonlinear relationship and a substantial increase in pT217/T217 before tau-PET pathology was elevated, which plateaued once the tau-PET threshold was exceeded. This may indicate that pT217/T217 is primarily associated with tau pathology through its quantitative relationship with the amount of Aβ pathology. This is further supported by the observation that Aβ pathology explained a significantly larger proportion of variation of pT217/T217 levels than tau, when including both amyloid-PET and tau-PET measures in the model. Notably, while pT205/T205 levels demonstrated a high correlation with tau-PET, they also showed the second highest correlation with amyloid-PET, after pT217/T217. In combined models, both amyloid-PET and tau-PET explained similar proportion of variation of pT205/T205 levels, suggesting that it is an intermediate biomarker affected by both Aβ and tau pathologies. Regarding the other p-tau measures, pT181/T181 and pT231/T231 were highly correlated with amyloid-PET, while the correlations with tau-PET were significantly lower than the other three CSF tau biomarkers, suggesting that they mainly reflect Aβ-pathology. These results are in line with several recent studies suggesting that p-tau181, p-tau217 and p-tau231 may be more related to amyloid pathology than tau. This is supported by their increased levels, both measured in CSF or in plasma, in early stages51. Of note, here we found either no significant increase in the rate of change of phosphorylated tau occupancy during the transition from A+T− to A+T+ or a significant decrease in the rate of change, consistent with previous reports21. These results suggest that rate of change in these phosphorylated tau measures may plateau or decline at advanced disease stages, when insoluble tau aggregates are depositing in the neocortex, indicating they are discordant longitudinally and that the classic p-tau measures are not direct measures of AD tau pathology52. Altogether, the findings of CSF p-tau measures are consistent with previous clinical observational studies and preclinical mouse models32, where these biomarkers seem to be driven by Aβ pathology. These results further support recent proposals to revise the A/T/(N) criteria system, in which any p-tau biomarker can be used as a tau (T) marker53.Longitudinal CSF biomarkers changes were also investigated to understand how these biomarkers change at different stages of the disease. Most notably, among the five CSF tau biomarkers, only MTBR-tau243 exhibited a significant increase in the rate of change between A+T− and A+T+ groups, suggesting that it enables longitudinal disease tracking during the phase of the disease characterized by neocortical tau aggregates, which mainly occurs in the symptomatic phase of AD. On the other hand, there was no major difference in the rate of change between A+T− and A+T+ for pT205/T205, although it still demonstrated a positive rate of changes at this late stage, suggesting a lower but still significant increase after tau deposition. Notably, for the other phosphorylated tau measures , there was a pronounced increase in the rate of change during the transition from A−T− to A+T−, consistent with a previous report showing that phosphorylated tau  is an optimal marker for disease monitoring during the very early  stages of the diseaseAs a relevant question for clinical practice, we also investigated the relationship between these CSF biomarkers and a cognitive measure. As expected by the observed associations with tau pathology, MTBR-tau243 was the measure most strongly associated with MMSE, a cognitive test frequently used in the clinical setting. Notably, this association was not significantly different from tau-PET, thus supporting the idea that CSF MTBR-tau243 could be a viable alternative to tau-PET for clinical purposes. Although pT205/T205 had a lower correlation with MMSE than MTBR-tau243, pT205/T205 was also well correlated with MMSE and not significantly different from tau-PET. In contrast, other CSF biomarkers such as pT217/T217 or pT181/T181 showed significantly lower associations.An unmet need is to determine not just who has amyloid or tau pathology, but if the symptoms are due to those pathologies. Because tau pathology is most highly correlated with cognitive and clinical impairment, an important question is how well CSF biomarkers can predict tau pathology or cognitive impairment. Thus, we next examined whether combining CSF biomarkers would improve prediction of Aβ or tau pathologies or cognitive measures. Based on a data-driven approach, we observed that the combination of pT205/T205, Aβ42/40 and pT217/T217 was optimal for predicting amyloid-PET continuous measures and significantly improved the performance of any individual measure. We also found that the combination of MTBR-tau243 and pT205/T205 in a single model improved prediction of tau-PET burden compared to any other single-fluid biomarker. The fact that such high predictive accuracy for both amyloid-PET and tau-PET imaging can be achieved by CSF biomarkers indicates that CSF assays can potentially be an alternative to PET measures, which are costly and have limited accessibility. Notably, MTBR-tau243 and pT205/T205 were also the optimal combination for predicting a cognitive measure (MMSE), suggesting potential clinical applications of this biomarker combination in predicting not only tau pathology but also cognitive impairment. For broader use, the translation of these biomarkers into blood-based biomarkers will be of utmost importance.57. Future studies using animal models and neuropathological measures will be important to further validate the results here presented.The main strength of this study is that we replicated our key findings in two large independent cohorts that represented different types of populations, used different PET tracers and also that we measured collected samples prospectively together with predefined outcome measures. Although further research is needed in a more diverse and generalizable population to implement our findings in the clinic, it is important to highlight that BioFINDER-2 participants were consecutively recruited from a secondary Clinical Memory in Sweden. As such, this cohort is a representative of memory clinical patients in Sweden and include both AD and also non-AD dementia patients. Limitations include that the magnitude of the trend differed between the two cohorts in some analyses although similar trends were shown. Potential reasons include that the BioFINDER-2 cohort includes more tau-PET-positive participants with AD dementia than the Knight ADRC cohort, as well as more participants in advanced stages of the disease, which may have affected the results with tau-PET and MMSE. Another limitation is that relatively few participants with AD dementia in the BioFINDER-2 cohort had an amyloid-PET scan per study design, although these participants all had CSF Aβ42/40. Thus, we used CSF Aβ42/40 instead of amyloid-PET as a marker of Aβ pathology in a sensitivity analysis and confirmed that this limitation did not affect the overall results and interpretations. Further, we acknowledge that our measures of Aβ and tau pathologies are only surrogate biomarkers and not actual measures of pathology, but both amyloid-PET and tau-PET markers have been validated against neuropathological measures of insoluble Aβ and tau aggregates, respectively52. As such, MTBR-tau243 could be used to assess AD tauopathy and track the effects of drug treatment independent of amyloid effects. The combination of CSF MTBR-tau243 and pT205/T205 is nearly equivalent to tau-PET measures and predicts MMSE almost as accurately as tau-PET, which indicates clinical utility of a biomarker panel containing MTBR-tau243. Compared to biomarkers altered by amyloidosis that are often abnormal in older cognitively normal individuals, CSF MTBR-tau243 could enable confirmation of tau pathology and provide greater certainty that cognitive symptoms are due to AD, as proposed in the latest clinical AD criteria requiring biomarker evidence of both amyloid and tau pathology to diagnose AD with high likelihood58. These findings add to the improving biomarker diagnostic accuracy for AD and to strategies to develop new AD therapies.In conclusion, these findings confirm that CSF MTBR-tau243 specifically reflects changes in aggregated tau pathology that occur at a late stage of AD progression and are associated with clinical and cognitive symptoms. Thus, we suggest that MTBR-tau243 should replace the commonly used p-tau measures as the fluid biomarker representing insoluble tau aggregate pathology (T) in defining AD pathology and in future versions of the commonly used A/T/(N) criteria for ADNCT03174938) (ref. 13) at Lund University  and the Knight ADRC from Washington University. The BioFINDER-2 cohort included cognitively unimpaired participants ), patients with MCI, patients with AD dementia and patients with a non-AD neurodegenerative disease. Participants were recruited at Skåne University Hospital and the Hospital of Ängelholm in Sweden. Details on recruitment, exclusion and inclusion criteria have been presented before13. All participants underwent lumbar puncture at baseline and at the follow-up after 2 years for CSF sampling. Participants underwent cognitive testing, including MMSE. The Knight ADRC cohort consisted of community-dwelling volunteers enrolled in studies of memory and aging at Washington University in St Louis. All Knight ADRC participants underwent a comprehensive clinical assessment that included a detailed interview of a collateral source, a neurological examination of the participant, the Clinical Dementia Rating® (CDR)59 and the MMSE40. Individuals with a CDR of 0.5 or greater were considered to have a dementia syndrome and the probable etiology of the dementia syndrome was formulated by clinicians based on clinical features in accordance with standard criteria and methods60.Participants were included from two cohorts: the Swedish BioFINDER-2 , patients with MCI Aβ positive (MCI+), patients with AD dementia Aβ positive (AD+) or patients with non-AD neurodegeneration, regardless of their Aβ status. Two participants (one in CU− and the other in non-AD) were MAPT R406W mutation carriers with Aβ negative and tau positive. In the Knight ADRC cohort, participants were divided in CU with CDR of 0 either Aβ negative or positive , patients with very mild AD with CDR of 0.5 Aβ positive and patients with AD dementia with CDR ≥ 1 Aβ positive (AD+). In accordance with the research framework by the National Institute on Aging-Alzheimer’s Association study, patients with SCD and cognitively normal controls were considered the CU groupAntibodies HJ32.11 and HJ34.8 were generated by immunizing tau knockout mice (The Jackson Laboratory) with either keyhole limpet hemocyanin (KLH) fused to amino acids 225-242 of tau to generate antibody HJ32.11 or to KLH fused to amino acids 226–264 to generate antibody HJ34.8. Spleen cells from immunized mice were fused with P3 hybridoma cells and expanded. Clones were screened by direct ELISA.21).Measurement of CSF tau species, including p-tau and MTBR-tau243 was performed at Washington University in both cohorts using the newly developed immunoprecipitation/mass spectrometry (IP/MS) method. We developed two new monoclonal antibodies to immune-purify CSF MTBR-tau243 . The procedure of CSF tau analysis is described in Supplementary Fig. 13. A threshold of 0.080, based on a Gaussian mixture modeling, determined Aβ positivity39. In the Knight ADRC cohort, CSF Aβ42/40 levels were measured as explained previously61. The threshold (0.0673) had the maximum combined sensitivity and specificity in distinguishing amyloid-PET status.Additionally, CSF Aβ42/40 levels were used in both cohorts to assess Aβ positivity. In the BioFINDER-2 cohort, CSF levels of Aβ42/40 were measured as previously explained13. Briefly, amyloid-PET was acquired using [18F]flutemetamol and tau-PET using [18F]RO948. Of note, most of the patients with AD did not undergo amyloid-PET in BioFINDER-2, due to the study design. In the Knight ADRC cohort, participants underwent amyloid-PET using either [18F]florbetapir ([18F]AV45) or [11C]PiB and tau-PET with [18F]flortaucipir ([18F]AV1451) as previously explained33. Amyloid-PET was measured in a neocortical meta-ROI using cerebellar gray as a reference region. In the BioFINDER-2 cohort, Centiloids were calculated using the Computational Analysis of PET from AIBL (CapAIBL) pipeline62. For tau-PET, SUVRs were calculated using the inferior cerebellum cortex as reference region and binding from a temporal meta-ROI were used for main analyses (Braak I–IV), to capture the regions most affected by tau. In supplementary analyses, we also quantified tau-PET in early (Braak I), intermediate (Braak III–IV) and late (Braak V–VI) regions of tau deposition63. Tau positivity was assessed based on tau-PET in all cases. In the Braak I–IV region, cutoff for positivity was set at SUVR > 1.32 both in BioFINDER-2 and in the Knight ADRC cohorts65.In the BioFINDER-2 cohort, amyloid and tau-PET acquiring methods have been previously reportedMMSE was used as a measure of global cognition in both cohorts.n = 500) with the boot package. Proportion of variation of CSF levels by amyloid and tau measures were assessed using linear regression models with both amyloid and tau as predictors, CSF levels as outcomes and age and sex as covariates. We calculated the partial R2 of amyloid and tau, raw and as a percentage of the total R2 of the model using the rsq package. This was used as a measure of proportion of variance explained by amyloid and tau. Next, prediction of amyloid and tau continuous measures was assessed with linear regression models, where amyloid-PET and tau-PET measures were used as outcomes in independent models and individual CSF biomarkers as predictors. A basic model was also created with only covariates (age and sex) as predictors. Additionally, a parsimonious model was constructed to optimally predict (highest accuracy with lower number of predictors) each of these measures, independently for each cohort. To this aim, LASSO regression models were used (glmnet package), initially including all CSF biomarkers and covariates. Only those predictors selected by the LASSO regression and with a significant contribution (P < 0.1) in the model were finally included in the parsimonious model. Similar methods were used for predicting cognition (MMSE in the two cohorts and CDR in Knight ADRC) additionally including years of education as covariate. In these cases, we compared the parsimonious model to one including only tau-PET as predictor. F-tests were used to compare nested models (including the same subset of predictors). When comparing models with different predictors we used the Vuong’s test using the nonnest2 package. Finally, CSF longitudinal changes by baseline amyloid and tau status were assessed in the BioFINDER-2 cohort. Individual participant slopes were calculated using linear regression models to calculate rate of change differences (mean percentage change) and compare them between groups using a Kruskal–Wallis test. Further, we created group trajectories with linear mixed models using the lme4 package for visualization. Here, CSF biomarkers were used as outcome, interaction between time and baseline amyloid and tau status as predictor and age and sex main effects as covariates, using random intercepts and fixed time slopes due to low number of time points. CSF and amyloid-PET and tau-PET measures were log-transformed in linear regression analyses. A two-sided P value < 0.05 was considered statistically significant. R v.4.1.0 was used for all statistical analyses.Differences in CSF biomarker levels by diagnostic groups were tested using ANCOVA adjusted for age and sex. Post hoc analyses were performed using the Tuckey test. Linear regression models were used to assess the association between amyloid-PET and tau-PET (independent variable) and each of the CSF biomarkers (dependent variable), after adjusting for age and sex. For cognition, we additionally used years of education as covariate in the linear regression models. All standardized β values were compared to the highest for each outcome and cohort, by building a distribution of the β values’ difference and using that to infer significance using a bootstrapping approach (Further information on research design is available in the Any methods, additional references, Nature Portfolio reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at 10.1038/s41591-023-02443-z.Supplementary InformationSupplementary Figs. 1–5 and Supplementary Tables 1–7.Reporting summary


A simple, novel, and less cost yellow (Erythrosine) modified pencil graphite electrode (Po-ERY/MGPE) was successfully fabricated via electropolymerization method using cyclic voltammetric techniques. The fabricated Po-ERY/MGPE opted as a sensor for the detection of Adrenaline (ADR) in 0.2 M PBS (7.4 pH). This reported senor displayed excellent electrocatalytic activity, increased sensitivity, high stability, superior electron transfer kinetics in the oxidation of ADR once relative to BGPE. The significance of pH, scan rate, and impact of concentration was assessed at the sensor. As per the pH and scan rate study, redox routes carry the same number of electrons and protons, and electro-oxidation of ADR was adsorption controlled respectively. The LOD of ADR was found to be 0.499 µM. The DPV data indicate that there is a significant peak divergence among ADR and uric acid (UA) which could make it easier to determine them alone and simultaneously on the sensor. The described method has been employed for the determination of ADR in injection sample. Good recovery values indicate the efficacy and applicability of the sensor in detecting ADR. It has good properties that are equivalent to glassy carbon and carbon paste electrode. GPE has extra advantages for the sensing of bioactive compounds by its lower costs, viability, mechanical robustness, high conductivity, renewability, easy disposability, low background current, wide potential range8.In contemporary electro analytical chemistry, Graphite pencil electrodes (GPEs) are versatile analytical tools. GPE has gotten a lot of attention as a form of carbon electrode. GPEs has been employed in an expanding array of applications, primarily as sensors and biosensors, since the modern era, despite the fact that they were initially published in 196010. ADR content in blood is linked to a slew of physiological activities11. Aberrant ADR levels are linked to a various disease, including Alzheimer’s disease, Sclerosis, hypoglycemia, stress, thyroid hormone disorders, and Parkin’s disease14. It stiffens blood vessels, raising heart rate, dilates lungs, and is known to activate the sympathetic nervous system’s flight or fight mechanism16. ADR is a drug used to treat alleviate bronchiolitis, cardiac surgery, heart attack, heart blockage, hyper tension, asthma and anaphylaxis19. ADR and UA are biological substances that plays a vital function in human metabolism. They often reside in the central nervous system’s extracellular fluid and body fluids. Therefore, both in life science and in pathological research, the individual or simultaneous determination of ADR inexistence of UA is a crucial issue20.Adrenaline (ADR) is a neurotransmitter, a hormone, and a prescription drug. ADR is a well-known catecholamine secreted by the endocrine system21, fluorimetry23, liquid chromatography24, spectrophotometry25, chemiluminescence26 etc. These approaches are not only costly, and moreover time intensive and inconvenient. The electrochemical approach, on the other hand, has long been known as a simple, quick, low cost, high efficiency, and convenient method of analysis and it employs electrodes. The employ of bare electrodes, on the other hand, is reported to be plagued by low sensitivity and selectivity, making selective and simultaneous detection of compounds in a sample matrix problematic. The major solution to these problems related with bare electrodes has been electrode modification. Dyes have indeed been widely employed for electrode modification by electro polymerization method in this regard27.To date, a lot of techniques have been used, including capillary electrophoresis28. The fabricated novel, simple and less cost Po-ERY/MGPE sensor plays a critical role in detecting ADR. Various parameters were analyzed, including pH effect, scan rate effect, and ADR concentration.In this work, Erythrosine (ERY) Fig. , a xanth2PO4.H2O, NaOH, and Na2HPO4. The Camlin lead pencil rods with dimensions of 0.5 mm and 6 cm in length were purchased from the local book depot. The 25 × 10–4 M stock solutions of ERY, ADR, and UA were prepared in distilled water, 0.1 M perchloric acid, and 0.1 M NaOH respectively. A supporting electrolyte, 0.2 M PBS (7.4 pH) was prepared from Na2HPO4 and NAH2PO4·H2O. All the chemicals employed were analytical grade and were utilized without further refining.ADR and UA were provided by Himedia. ERY was procured from Sigma-Aldrich. Nice chemicals provided perchloric acid, NaHAll voltammetric (CVs and DPVs) assessments were obtained using CH instrument type 660 (CHI-660c model). The electrode setup consists of three electrodes: a working electrode (bare GPE or Po-ERY/MGPE), a counter electrode (Platinum), and a reference electrode . All voltammetric data were recorded at room temperature.As bare GPE, lead pencil rod with a dimension of 0.5 mm and a length of 6 cm was employed. Copper wire was used to make the electrical connection at the pencil lead’s one end, and the surface was subsequently polished by rubbing it against weighing paper.−1 over 10 cycles. As the number of cycles increased, the voltammogram reduced and eventually became relatively steady, reflecting the accumulation of a uniform thin layer of ERY on the surface of bare GPE29. The thickness of the adherent film, which can be varied by adjusting the number of scan intervals during electropolymerization is strongly attributable to the modified electrode’s catalytic performance30. As indicated in the inset Fig. 231.2), and sweep speed respectively. F, R, and T are scientific terms.The Po-ERY/MGPE was produced by electropolymerized a bare GPE (0.5 mm diameter) in 1 mM aqueous ERY prepared with 0.1 M NaOH (supporting electrolyte) in an electrochemical cell using the CV method. Figure 4[Fe (CN)6] was employed as a redox probe in the CV technique to characterize the electrochemical performance of a produced electrode. The CVs for the electrochemical activity of K4[Fe (CN)6] at bare GPE (dashed line: curve ‘a’) and Po-ERY/MGPE (solid line curve ‘b’) in 1 M KCl as a supporting electrolyte with a scan rate of 50 mVs−1 was displayed in Fig. 2) and Po-ERY/MGPE (0.053 cm2) was estimated using Randles-Sevick’s Eq.  and Po-ERY/MGPE (curve ‘b’) in 0.2 M PBS 7.4 pH) at potential ranging from − 0.2 to 0.6 V with scan rate of 50 mVs pH at po−1) = 0.703–0.058 (pH), (R2 = 0.997) and slope of 0.058 V/pH, confirming that the oxidation of ADR comprises the same number of electrons and protons33.The contribution of supporting electrolytes in the development of sensors is critical for the analytes. At modified electrodes, pH has been shown to have a considerable influence on electron transport performance. As a result, it is often crucial to investigate the effect of buffer solution pH on analyte perception at modified electrode. Figure −1 on electrochemical analysis of 10 µM ADR in 0.2 M PBS (7.4 pH) was explored using the CV technique, as seen in Fig. −1) + 2.06 (R2 = 0.998) and Ipa (µA) = 39.48 ʋ1/2 (Vs1) − 5.96 (R2 = 0.994)34.The influence of scan rate from 50 to 500mVs.2 M PBS .4 pH was.2 M PBS .4 pH was.2 M PBS .4 pH was−1 with a progressive increase in ADR levels from 10 to 60 µM achieved at Po-ERY/MGPE. Ipa of ADR increases as the ADR levels rise , it offers better linearity. Equations   −1 with −1 at bare GPE (curve ‘a’) and Po-ERY/MGPE (curve ‘b’) in 0.2 M PBS (7.4 pH) for a mixture of ADR (0.1 µM) and UA (0.1 µM) are illustrated in Fig. The goal of this analysis was to utilize the developed electrode to assess ADR in the presence of UA in a selective and sensitive manner. The CVs obtained at sweep speed of 50 mVs2 = 0.999) and Ipa (nA) = 0.020 (µM) + 3.76 (R2 = 0.997), respectively. According to the above-mentioned experimental data, as the level of one analyte was increased, the Ipa climbed wonderfully, but the Ipa and Epa of constant analyte remained unchanged. Because the oxidation of ADR does not influence the variance of the other analytes, our data suggest that the accurate and precise estimation of ADR at Po-ERY/MGPE is achievable.The interference analysis was most significant in deciding the efficacy of the fabricated electrode and the DPV method was used for the study. The DPVs curve is depicted in Fig. −1 by CV method. The computed percentage of degradation indicates 93.72% of the primary peak current signal, indicating adequate stability. The reproducibility of the MGPE was examined by fabricating four separate MGPE under the same circumstances. The RSD value obtained to be 4.7% validates the good reproducibility.To examine the sensor’s stability, the Po-ERY/MGPE was subjected to 10 successive cycles for 10 µM ADR in 0.2 M PBS with scan rate of 50 mVsIn addition to the aforementioned studies, the Po-ERY/MGPE sensing potential towards ADR in an injection sample was assessed using the standard addition method. The injection sample was procured from Harson Laboratories, which had a defined concentration of 1.8 mg/mL ADR and was used after a sufficient dilution in 0.1 M perchloric acid. Table In conclusion, we proposed a simple and efficient way for fabricating of Po-ERY/MGPE. The core attractive features of Po-ERY/MGPE include the prompt modification process, increased sensitivity, and low detection limits. The developed sensor was used for specific and simultaneous detection of ADR and UA. According to DPV studies, highly distinct and defined peak separation between ADR and UA could be enabling both individual and simultaneous determination of each compound on the sensor. Po-ERY/MGPE exhibits good sensitivity, stability and reproducibility. In real sample analysis, the developed sensor recovered ADR with high accuracy. As a result, Po-ERY/MGPE will have a high opportunity in sensor field.


Equus caballus PV (EcPV) has been identified using Next Generation Sequencing, and it was further confirmed with genome-walking PCR and Sanger sequencing. The complete circular genome 7607 bp long shares 67% average percentage of identity with EcPV9, EcPV2, EcPV1, and EcPV6, justifying a new classification as Equus caballus PV 10 (EcPV10). All EcPV genes are conserved in EcPV10, and phylogenetic analysis indicates that EcPV10 is closely related to EcPV9 and EcPV2, genus Dyoiota 1. A preliminary EcPV10 genoprevalence study, carried out on 216 horses using Real Time PCRs, suggested a low incidence of this isolate (3.7%) compared to EcPVs of the same genus such as EcPV2 and EcPV9 in the same horse population. We hypothesize a transmission mechanism different from the one observed in the closely related EcPV9 and EcPV2 that particularly infect Thoroughbreds. This horse breed is usually submitted to natural mating, thus indicating a possible sexual diffusion. No differences were detected for breeds in terms of susceptibility to EcPV10. Further studies are needed to investigate the molecular mechanisms behind the host and EcPV10 infection to explain the reduced viral spread.Papillomaviruses (PVs) are small, non-enveloped viruses, ubiquitous across the animal kingdom. PVs induce diverse forms of infection, such as cutaneous papillomas, genital papillomatosis, and carcinomas. During a survey on the fertility status of a mare, a novel  Papillomaviruses (PVs) are small, non-enveloped DNA viruses, able to infect a wide variety of vertebrates. More than 240 types of PVs have been described in mammals . In humaBos taurus papillomavirus 1 (BPV1), 2 (BPV2), and 13 (BPV13)), two Equus asinus PVs 1–2 (EaPV1 and EaPV2), and nine Equus caballus PVs 1–9 (EcPV1–9) [Chelonia mydas papillomavirus type 1, CmPV1) to 8607 bp  [To date, 14 species of PVs have been reported to infect equines such as horses and donkeys: three bovine PVs EcPV1–9) . As it oEcPV1–9) . In partEcPV1–9) ,7; EcPV2EcPV1–9) ; EcPV1,  . As it EcPV1–9) . FurtherEcPV1–9) ,12,13. P1, CPV1) . L1 and 1, CPV1) . Hence, In this study, we report the identification of a new EcPV type named EcPV10, isolated from a vaginal cytobrush of an infertile mare, and provide its completely assembled genome. This sequence has been compared to closely related PVs, and the genoprevalence of this virus has been tested in 216 samples obtained from horse genital tracts.Chlamydia spp. detection [A Thoroughbred of seven years old from Chillivani  was admitted in February 2021 to the Veterinary Teaching Hospital (OVU) of the University of Turin  for subfertility. During the previous breeding season, she was subjected to natural mating four times with a proven fertility stallion but failed to become pregnant. However, clinical signs of endometritis were not observed during any cycle . Therefore, after the admission, the mare was submitted to a complete reproductive tract examination, including transrectal palpation, ultrasound examination , and vaginal speculum examination. Furthermore, all the procedures routinely used to diagnose uterine illnesses in the mare were performed , includiIn light of these results, screening for EcPV2 infection was performed, following the protocol described in Cappelli et al. (2022) . CytobruEquus caballus genome  as reference with BWA v 0.7.12 aligner and samtools v1.13 [Total DNA was extracted from three biological replicates using a QIAamp DNA Mini Kit , according to manufacturer’s instructions, and sequenced independently with an Illumina NovaSeq 6000 machine using paired-end sequencing methods at the Institute of Applied Genomics . Raw reads quality was evaluated with FastQC , and thels v1.13 . De novols v1.13  with defTo check the presence of any possible EcPV, assembled contigs were compared using BLASTn algorithm against an in-house built database that included the EcPV genomes available on NCBI database at the time of this analysis . Contigshttp://tree.bio.ed.ac.uk/software/figtree (accessed on 21 September 2022) and edited with Inkscape v0.92 www.inkscape.org (accessed on 22 September 2022). The amino acid (aa) sequences were aligned with BLASTp to investigate similarity with closely related oncoproteins.Viral ORFs were identified through the NCBI ORF Finder, Gatu , and PuMA genome walking approach was developed by designing overlapping PCR primers, listed in Papillomaviridae (taxid:151340) NCBI database. qPCR reactions were prepared with 1× iTAQ universal probes supermix , 1 μM of both forward and reverse primers, 0.2 μM of the probe, and 2 μL of DNA, in a final volume of 25 μL of double sterile water. Thermal cycling parameters consisted of an initial preheating step for 5 min at 95 °C followed by 40 cycles at 95 °C for 15 s, 60 °C for 45 s, performed in a Rotor-gene Q machine (QIAGEN). The acquisition of the fluorescent signal occurred at the end of each cycle, and the threshold to consider the sample positive was set at cycle 38.To develop a Real Time PCR assay specific to the newly assembled EcPV genome, primers and a probe targeting the L1 gene were designed . Their sFrom January 2021 to July 2022, genital brushes were collected at the Didactic Veterinary University Hospital (OVUD) of Perugia and Turin for reproductive reasons, with the following inclusion criteria: (i) no sign of neoplastic disease, (ii) no lesions were associated to PVs infection. Penile and vulvar swabs were collected through sampling with cytobrushes  as previously described . BrushesBreed and origin information were obtained from medical records. Descriptive statistics analysis was performed with Microsoft Excel (2016). STATA16.1  software was used to fit a logistic regression model assessing the association, expressed as Odds Ratio (OR) between the positivity or negativity to EcPV10 L1 (dependent variable) and four classes of age  and two of breed (Thoroughbred vs. the others) (independent variable). Statistical analysis was restricted to mares; the OR was assessed through logistic regression using as dependent variables the positivity/negativity to EcPV10 L1, artificial insemination/natural service, and pluriparous/maiden, while breed and age were considered as independent variables. Finally, a third logistic regression model was fit to assess the OR between being pregnant vs. being empty (dependent variable) and the positivity/negativity to EcPV-10 L1 and fertility/hypo-fertility (independent variables).A survey was conducted on the fertility status of a seven-year-old Thoroughbred mare from Chillivani . Several tests to evaluate the mare fertility were carried out, such as transrectal palpation, ultrasound examination, and vaginal speculum examination, as detailed in DNA from three different brush replicates was sequenced and analyzed independently with Next Generation Sequencing (NGS) using Illumina technology. The total amount of raw and filtered reads, as well as the total number of assembled contigs, are summarized in Furthermore, in each replicate, several shorter contigs were related to EcPV2, even with more than 99% of identity highlighted in light green in The genome sequence for this new PV genotype, named EcPV10, was further validated through Sanger sequencing using a genome walking approach. Primers for overlapping PCR amplicons  are scheThe ML phylogenetic analysis based on the concatenated sequences of E1, E2, L2, and L1 showed clustering of EcPV10 among an equine (including horses and donkeys) PV group and a subgroup of bovine PVs . Within Next, we performed aa pairwise alignments using BLASTp of the six viral ORFs against most closely related PVs . EcPV10 To investigate the EcPV10 genoprevalence, a total of 216 horses  were sampled during clinical examination at OVUD (Perugia) and OVU (Turin) and tested for EcPV10 infection using our designed quantitative Real-Time PCR see . The ageThe following breeds were analyzed: 91 Standardbred (42.1%), 83 Thoroughbred (38.4%), 12 Italian Sport Horse (5.6%), 8 Arabian (3.7%), 4 Shire (1.9%), 3 Quarter Horse (1.4%), 2 Belgian Sport Horse (0.9%), 1 Appaloosa (0.5%), 1 Maremmano (0.5%), 1 Half Breed (0.5%), and 1 Selle Français (0.5%). The breed has not been reported for 9 animals that were tested.The samples were obtained from horses from various Italian regions: 144 (67.6%) were from Piedmont, 18 (8.5%) from Umbria, 12 (5.6%) from Tuscany, 9 (4.2%) from Lazio, 4 (2.8%) from Marche, 5 (2.3%) from Emilia Romagna, 5 (2.3%) from Lombardy, 4 (1.8) from Sardinia, 2 (0.9%) from Campania, and 1 (0.5%) from Abruzzo. Additionally, we also examined one sample of horses from France and the USA. The geographical origin was unknown for eight (3.7%) samples.EcPV10 DNA was found in 3.7% (8 out of 216) of the examined horses, including the first one from Sardinia, with Cq from 30 to 38.7. Seven of the positive subjects were mares, whilst one was a stallion. The age of the positive subjects ranged from 7 to 19 years. Most positive subjects were found in Piedmont (six horses), while the other two were from Sardinia and Tuscany, respectively . RegardiThe logistic regression model did not show any correlation between viral infection risk and age class or breed. Similarly, the presence/absence of the virus did not appear to be related to sex and did not influence fertility in the investigated horses. A larger number of subjects should be examined in future studies in order to confirm our observations.Equus Caballus Papillomavirus type 10. The complete circular genome of 7607 bp has been deposited on the GenBank database under the accession number OP870083. Total DNA was isolated from a vaginal cytobrush of a mare affected by infertility in triplicate and subjected to different tests, including the screening of EcPV2. Screening for EcPV2 was performed since a recent study [In this study, we report the discovery, full genome sequence, and classification of EcPV10, a novel nt study  suggesteOur phylogenetic analysis demonstrates that EcPV10 is a novel species within the genus DyoiotaPV, most closely related to EcPV2 and EcPV9, and classified as DyoiotaPV1. PVs are classified on the basis of L1, the most conserved gene, but diversity between PV types is enhanced in the E6–E7 oncogene regions . In thisOut of the 216 examined horses using the EcPV10-specific Real Time assay, only 7 mares and 1 stallion tested positive. Despite EcPV10 belonging to Dyoiota 1, the genus that includes the most prevalent PVs within the Italian horse population, i.e., EcPV2 and EcPV9 ,13, our Indeed, EcPV2 and EcPV9 showed a higher infection risk associated with breed compared to EcPV10, with the Thoroughbred being significantly more infected by EcPV2 and EcPV9 compared to other breeds. This finding may be the consequence of natural mating, making sexual transmission the probable way of EcPV2 and EcPV9 diffusion. Risk of spreading EcPV10 was not associated with breed, likely suggesting a different way of transmission for this PV and suggesting no impact on breed upon infection. In this preliminary study, we tested a moderate number of samples (216 horses), which was, however, considered representative enough to suggest a low occurrence of EcPV10 in Italy. Low prevalence of EcPV10 among the Italian horse population could be attributed to several features related to the viral proteins and the capability of the host’s immune response to recognize and eliminate the virus. However, further studies are needed to better understand other possible host–EcPV10 interactions due to the diversity we encountered in its viral proteins. Deeper analyses are also needed in order to shed light into the transmission mechanisms and disease incidence of this new PV isolate.


Furthermore, their nonlinear optical (NLO) response and optical limiting (OL) efficiency are studied by means of the Z-scan technique, employing 4 ns laser pulses at 532 and 1064 nm. The results demonstrate that the PVP-Ir/IrO2 and Ir/IrO2 systems exhibit exceptional OL performance, while PVP-IrO2 presents very strong saturable absorption (SA) behavior, indicating that the present Ir-based nanohybrids could be strong competitors to other nanostructured materials for photonic and optoelectronic applications. In addition, the findings denote that the variation in the content of IrO2 nanoparticles by using different synthetic pathways significantly affects the NLO response of the studied Ir-based nanohybrids, suggesting that the choice of the appropriate synthetic method could lead to tailor-made NLO properties for specific applications in photonics and optoelectronics. The present work reports on the synthesis and characterization of iridium (Ir)-based nanohybrids with variable chemical compositions. More specifically, highly stable polyvinylpyrrolidone (PVP) nanohybrids of the PVP-IrO Nanomaterials based on precious metals such as palladium (Pd), platinum (Pt), gold (Au), silver (Ag), rhodium (Rh), ruthenium (Ru) and iridium (Ir) have attracted great attention in recent years due to their unique optical, catalytic and electronic properties. Consequently, such nanomaterials are extensively explored in many diverse areas including catalysis ,2,3, senFrom the aforementioned precious nanomaterials, not as much work has been reported on Ir-based nanosystems compared to other types of precious metals. The fact that Ir-based nanomaterials are usually characterized by extremely small nanoparticle/cluster diameters makes their characterization quite challenging . MoreoveVarious synthetic approaches have been employed in the preparation of Ir-based nanomaterials . These iBased on the above, it becomes obvious that the scientific community has been highly active with regard to the development of Ir-based nanosystems since the latter are considered to be extremely promising in many applications , includis and saturable intensity Is) of low-dimensional nanostructures under ns laser radiation, demonstrating their great prospects for the generation of short laser pulses in Q-switched laser systems [The large optical nonlinearities of metal and semiconducting nanoparticles are undoubtedly a key advantage for their implementation in photonic devices ,36,37,38 systems ,30,31,32 systems ,36,37,38 systems ,40,41,42 systems ,44,45 an systems ,36,37,382 nanoparticles (PVP-IrO2), a mixture of PVP-stabilized Ir/IrO2 nanoparticles with an Ir/IrO2 ratio of ~0.25 (PVP-Ir/IrO2) and a mixture of Ir/IrO2 nanoparticles without polymeric coating and an Ir/ IrO2 ratio of ~1 (Ir/IrO2), were generated by following three different synthetic protocols. PVP was used as a macromolecular steric stabilizer due to its non-toxicity, low cost and high effectiveness in acting as a stabilizing agent for numerous types of inorganic nanomaterials [In that context, solutions of Ir-based nanocolloids, namely polyvinylpyrrolidone-stabilized IrOaterials . Furtheraterials . The afo3·3H2O; Mw = 298.58 gmol−1, anhydrous basis, 99.9% trace metal basis) and polyvinylpyrrolidone  were purchased from Sigma-Aldrich Chemie GmbH, Tauflirchen, Germany. Sodium hydroxide  and methanol  were purchased from Sigma-Aldrich Chemie GmbH, Tauflirchen, Germany and Sharlau Chemicals , respectively. All chemicals were used as received from the manufacturer without further purification. The Millex®-HP 13 mm filter unit (PES 0.45 μm membrane) that was employed in solution filtration was purchased from Sigma-Aldrich Chemie GmbH, Tauflirchen, Germany.Iridium (III) chloride hydrate  A dispersion of IrCl3·3H2O  was prepared in methanol (5 mL) via vigorous stirring (1250 rpm) for 1 h at room temperature. NaOH  dissolved in methanol (5 mL) was then added dropwise (1 mL/min) into the IrCl3·3H2O/methanol dispersion under stirring conditions (500 rpm). The latter was left to stir for additional 2 h under reflux (65 °C) upon stirring (500 rpm), resulting in a clear, black-colored suspension ((I) (Ir/IrOspension . This wa2) PVP  was placed in a 50 mL round-bottom flask, and methanol (5 mL) was added. The resulting mixture was left to stir (500 rpm) for 10 min at room temperature, resulting in a clear, transparent polymer solution. In the meantime, a dispersion of IrCl3·3H2O  was prepared in methanol (5 mL) via vigorous stirring (1250 rpm) for 1 h at room temperature. The latter was added dropwise (1 mL/min) into the methanol solution containing PVP, followed by overnight stirring (500 rpm) at room temperature. The obtained solution was further stirred (500 rpm) for 6 h under reflux at 65 °C to yield a clear, bronze-colored suspension ((II) (PVP-IrOspension . This wa2) PVP  was placed in a 50 mL round-bottom flask and dissolved in a NaOH/methanol solution . The resulting mixture was left to stir (500 rpm) for 10 min at room temperature, resulting in a clear, transparent polymer solution. In the meantime, a dispersion of IrCl3·3H2O  was prepared in methanol (5 mL) via vigorous stirring (1250 rpm) for 1 h at room temperature. The latter was added dropwise (1 mL/min) into the NaOH/methanol solution containing PVP, followed by overnight stirring (500 rpm) at room temperature. The obtained solution was further stirred (500 rpm) for 6 h under reflux at 65 °C, resulting in a clear, black-colored suspension ((III)  using an XPS spectrometer SPECS equipped with a dual-anode X-ray source Al/Mg, a PHOIBOS 150 2D CCD hemispherical energy analyzer and a multi-channeltron detector with vacuum pressure maintained at 1 × 10The size and shape of the Ir-based nanostructures were examined by scanning transmission electron microscopy (STEM) with a Hitachi HD2700 equipped with a cold field emission gun, Dual EDX System (X-Max N100TLE Silicon Drift Detector (SDD)) from Oxford Instruments. For the analysis, the methanolic suspension of Ir-based nanoparticles was first dried, and the sample was resuspended in water. The nanoparticles were then centrifuged in an ultracentrifuge for several hours before being resuspended in water. The centrifugation was repeated again, and a suspension of the samples was sonicated (<10 s) with a UP100H ultrasound finger and deposited using the droplet method on a 400-mesh copper grid coated with a thin carbon layer. For both types of analysis, the nominal operating tension was 200 kV. The size of the nanoparticles was determined using the ImageJ software.The third-order nonlinear optical (NLO) response of the studied Ir-based nanohybrids was investigated by means of the conventional single-beam Z-scan technique. Further information on this technique and the procedures followed for the analysis of the obtained data are reported in detail elsewhere , and onlIn general, the presence of a transmission maximum/minimum in the OA Z-scan reveals saturable absorption (SA)/reverse saturable absorption (RSA) behavior of the sample, corresponding to a negative/positive nonlinear absorption coefficient β. Similarly, the presence of a pre-focal transmission minimum followed by a post-focal maximum or vice versa in the CA Z-scan denotes a self-focusing (γ′ > 0) or self-defocusing (γ′ < 0) behavior, respectively. It is interesting to note that the CA Z-scan measurements can be also affected by the NLO absorption of the sample. In this case, the CA Z-scan recordings are asymmetric with respect to the focal plane. Thus, in order to remove the contribution of NLO absorption on the CA Z-scan recording, the latter is divided by the corresponding OA Z-scan, providing the so-called “divided” Z-scan recording, which is used for the direct determination of the nonlinear refractive index parameter γ′.0 with z and z0 denoting the sample’s position and Rayleigh length, respectively, I0 is the on-axis peak irradiance, Leff is the sample’s effective length and k is the wavenumber at the excitation wavelength. The values of β and γ′ are calculated by fitting the experimental OA and “Divided” Z-scans with Equations (1) and (2), respectively:(3) can be deduced through Equations (3) and (4), respectively:0, the determined NLO parameters ) are divided by the respective absorption α0, providing a figure of merit (FOM) for these quantities.Using the determined values of β and γ′, the real and the imaginary parts of the third-order susceptibility χw/v) were prepared and placed into 1 mm path length quartz cells. The laser beam was focused into the samples by means of a 20 cm focal length quartz lens. The laser beam radii at the focal plane were measured using a CCD camera and found to be about (18 ± 2) and (30 ± 2) μm for the 532 and 1064 nm laser outputs, respectively.The laser source used for the Z-scan experiments was a Q-switched Nd:YAG laser system (EKSPLA NT 342/3/UVE/AW), delivering 4 ns laser pulses at 1064  and 532 nm (SHG) with a variable repetition rate from 1 to 10 Hz. For the Z-scan measurements, two different concentrations of the studied Ir-based colloidal solutions in methanol . For the calculation of the values of Fin(z) at each z-position, the following equation was used:in is the incident laser energy and r(z) is the beam radius at each z-position, the latter given by the relation:To assess the optical limiting (OL) performance of the studied Ir-based nanohybrids, under 4 ns 532 nm laser irradiation, the OA Z-scan recordings were used to plot the variation in the sample’s transmittance as a function of the input laser fluence FTo check for possible contribution of nonlinear scattering (NLS) signal to the OL performance of the samples, a high-precision photodiode was used, which was placed on a goniometric stage, monitoring the scattered laser radiation at different angles with respect to the laser propagation. However, within the range of incident laser intensities used for the Z-scan measurements, no significant NLS signal was detected, indicating a rather negligible contribution of NLS to the OL performance of the studied Ir-based nanohybrids.2), the nanoparticles could only be seen clustered into larger agglomerates overlapping each other , where at least parts of the sample were found in almost perfect monolayers. The individual nanoparticles were uniform and monodisperse, with an average diameter of 1.6 ± 0.28 nm. The presence of Ir in EDX (2), the nanoparticles were much more spread out. The average diameter was slightly smaller, at 1.4 ± 0.24 nm, and exhibited uniformity and good dispersity . The comparatively smaller amount of iridium relative to the amount of carbon  visible in EDX stems from the fact that the nanoparticles are very small and arranged in a monolayer on the carbon grid. The decrease in tendency to agglomerate is likely due to the steric stabilization provided by PVP, which also resulted in a higher stability in suspension—even repeated washing after centrifugation could not completely remove the polymeric coating. In sample II (PVP-IrO2), the separation of nanoparticles by centrifugation was unsuccessful. As a result, the presence of a large amount of the polymer coating prevented the acquisition of clear images of the Ir-based nanoparticles, and hence the nanoparticles shown in STEM was performed on samples I–III . For samsee also , unlike r in EDX  confirme2,), III (PVP-Ir/IrO2) and I (Ir/IrO2) evidence differences in their chemical composition. The survey spectra for the three samples are given in The XPS investigation of samples II  prepared in methanol (0.5% w/v) are presented. As shown, all the Ir-based nanohybrids exhibited an absorption maximum at 300 nm, ascribed to the Ir-monomer precursor [2 also displayed three shoulders at ~330, 380 nm and 540 nm. More specifically, the absorbance peaks of PVP-IrO2 at ~330 and 380 nm are most likely attributed to the iridium (III) chloride salt [3+ to Ir4+ transitions, is typical of IrO2 nanoparticles [In recursor , while tide salt , while tarticles . The UV-0, i.e., of about 1.8 cm−1, at 532 nm. The solid lines correspond to the best fits of the experimental data points (solid symbols) according to Equation (1). Similar OA Z-scan measurements performed under 4 ns 1064 nm laser excitation revealed insignificant NLO absorption for all samples. In addition, the possible contribution of the solvent  and polymer  to the NLO absorptive response of the solutions was checked and found to be insignificant within the range of laser intensities used  for the Z-scan measurements. Therefore, the presented OA Z-scans of 2 revealed a maximum at the focal plane , indicative of a typical saturable absorption  behavior. In addition, this transmission maximum was found to increase with incident laser intensity, retaining, however, a clear transmission maximum even for the highest laser intensity used, implying that a one-photon absorption (1PA)-related nonlinearity occurs under 532 nm laser excitation. However, since the bandgap energy of the studied IrO2 semiconducting nanoparticles, evaluated to be ~2.7 eV , where the laser intensity is sufficiently strong, the interband optical transitions become more efficient, resulting in the depletion of all the available states in the conduction band of IrO2. Consequently, any further excitation of electrons is blocked due to the Pauli exclusion principle, giving rise to the appearance of SA behavior (β < 0). From the fitting of the OA Z-scans of PVP-IrO2 presented in −11 m/W.In V see in , is largt phases ,52. In ps and low saturable intensity Isat. For the determination of the αs and Isat values of PVP-IrO2, the experimentally obtained values of normalized transmittance (solid points) have been plotted as a function of the incident laser intensity ), the modulation depth αs and the saturable intensity Isat) have been compared to those of other metal and semiconducting nanoparticles reported to exhibit exceptional SA response, including silver (Ag), gold (Au), platinum (Pt), palladium (Pd), zinc oxide (ZnO), vanadium pentoxide (V2O5), iron oxide (γ-Fe2O3), copper oxide (CuO) and copper hydroxide (Cu(OH)2) [(3) /α0) as well as the values of αs and Isat of PVP-IrO2 are comparable to those of other nanomaterials, emphasizing the efficiency of the studied IrO2 nanoparticles for saturable absorption applications. Besides their large values of the nonlinear absorption coefficient β, materials suitable for saturable absorption applications are characterized by high modulation depth αsity see b and fitCu(OH)2) ,30,31,322 nanoparticles, i.e., the PVP-Ir/IrO2 and Ir/IrO2 nanohybrid solutions, presented a deep focus, increasing with the laser pulse intensity, implying a positive absorptive nonlinearity . From the fitting of these OA Z-scans with Equation (1), the average values of the nonlinear absorption coefficient β of PVP-Ir/IrO2 and Ir/IrO2 were determined to be (13.8 ± 2.0) × 10−11 and (24.2 ± 2.0) × 10−11 m/W, respectively, suggesting that the increase in the IrO2 content leads to significant enhancement of the NLO absorption of these nanohybrids. The same conclusion can also be drawn from the comparison of the β value of the PVP-IrO2 solution, containing only IrO2 nanoparticles, with the corresponding values of PVP-Ir/IrO2 and Ir/IrO2. In particular, as mentioned above, the β value of PVP-IrO2 was found to be (−115.6 ± 18.0) × 10−11 m/W, that is, ~5 and 10 times larger than those of Ir/IrO2 and PVP-Ir/IrO2, respectively.As shown in 2 and Ir/IrO2 solutions, it should be considered that the optical bandgap of the IrO2 semiconducting nanoparticles, estimated for the sample containing only IrO2 nanoparticles (PVP-IrO2), is about 2.7 eV (see 2 nanoparticles lies above the sum of energy of two photons at 532 nm (~2.33 eV), only 2PA can occur in IrO2. On the other hand, the zero bandgap of Ir nanoparticles facilitates the manifestation of ESA under 532 nm laser excitation. However, as discussed above, the irradiation of PVP-IrO2 nanohybrids at 532 nm leads to SA behavior. As a result, it is reasonable to assume that the photo-response mechanism causing the NLO absorption of the present nanohybrids can be assigned to ESA due to the presence of Ir nanoparticles.In general, the RSA behavior of the studied nanostructures can be explained in terms of different physical processes, such as excited state absorption (ESA), two-photon absorption (2PA), nonlinear scattering (NLS), and thermal cumulative effects . The pre7 eV see  and thaton), is usually used for the assessment of the OL efficiency of a material. Materials exhibiting strong RSA behavior are promising candidates for OL-related applications, such as the protection of human retinal and delicate optical sensors from high-power laser radiation. These materials should exhibit high transmittance, obeying the linear Beer–Lambert law, for low incident laser intensities or fluences and a decreasing transmittance for higher incident fluences. The value of input fluence at which the transmittance begins to deviate from the Beer–Lambert regime, defined as the optical limiting onset ) and OLon have been compared to those of other semiconducting nanoparticles reported as efficient OL materials, such as zinc oxide (ZnO), indium zinc oxide (InZnO), titanium dioxide (TiO2), nickel oxide (NiO), chromium oxide (Cr2O3), tungsten trioxide (WO3), antimony selenide (Sb2Se3), cadmium sulfide (CdS) and silver sulfide (Ag2S) [on values to those corresponding to other nanostructured materials included in For a more comprehensive picture of the OL efficiency of PVP-Ir/IrOe (Ag2S) ,36,37,382, PVP-Ir/IrO2 and Ir/ IrO2 colloidal solutions prepared in methanol, obtained using 4 ns laser pulses at 532  according to Equation (2). As can be seen, all solutions displayed a peak–valley configuration under both excitation wavelengths, denoting a self-defocusing behavior . Moreover, PVP and methanol did not exhibit measurable NLO refraction under the present excitation conditions. Therefore, the nonlinear refractive index parameter γ′ of the studied nanohybrids can be straightforwardly obtained from the “Divided” Z-scans shown in 2, PVP-Ir/IrO2 and Ir/IrO2 were determined to be about (−89.8 ± 16.0) × 10−21, (−20.0 ± 2.0) × 10−21 and (−28.8 ± 2.0) × 10−21 m2/W, respectively, at 532 nm, and about (−28 ± 4) × 10−21, (−7.8 ± 0.4) × 10−21, (−13.3 ± 2.0) × 10−21 m2/W at 1064 nm. The above values demonstrate nicely that the increase in IrO2 concentration results in the enhancement of the NLO refraction of the samples.In s at 532 a and 106s at 532 b, are shAt this point, it is interesting to note that during ns laser excitation, free carrier refraction and thermal lensing are the most sizable contributions to the observed refractive nonlinearity. The former process is attributed to the more efficient electronic transitions that occur, while the latter is due to the increase in the thermal energy accumulated in the sample ,55. Howe(3), have been calculated and are summarized in 0, the quantity χ(3)/α0 is also included in By following the standard procedures used for the analysis of the obtained Z-scan recordings , the val(3)/α0 values shown in 2 nanoparticles significantly affects the NLO response of the present Ir-based nanohybrids. More specifically, the NLO response of PVP-IrO2, containing only IrO2 nanoparticles, was found to be enhanced by factors of ~10 and 5 compared to PVP-Ir/IrO2 and Ir/IrO2, respectively, for visible (532 nm) laser excitation and by factors of ~4 and 2.5 for infrared (1064 nm) excitation. In addition, among the solutions containing a mixture of Ir and IrO2 nanoparticles, Ir/IrO2 (Ir/IrO2 ratio ~1) revealed ~2 and 1.5 times larger χ(3)/α0 values than PVP-Ir/IrO2 (Ir/IrO2 ratio ~0.25) under 532 and 1064 laser excitation, respectively. Therefore, the present findings indicate that the modification of atomic content of Ir-based nanohybrids through the choice of the suitable synthesis method can be used in the tailoring of their NLO response.From the χ2 revealed saturable absorption (β < 0), while both PVP-Ir/IrO2 and Ir/IrO2 exhibited reverse saturable absorption (β > 0). This sign alternation of the nonlinear absorption coefficient β indicates that they can be used either as saturable absorbers or optical limiters by modifying the content of IrO2 nanoparticles. Concerning the NLO refraction, all the studied nanoparticles exhibited large values of γ′  under both excitation wavelengths, which are comparable and even larger than those of other metal and semiconducting nanoparticles (see In addition, PVP-IrOcles see , suggest2 nanoparticles. Their NLO response and OL efficiency was investigated under 4 ns laser excitation at 532 and 1064 nm. The obtained results reveal that the choice of different synthetic strategies significantly affects the NLO properties of the Ir-based nanohybrids, especially their NLO absorption. More specifically, the nanocolloidal system containing only IrO2 nanoparticles, exhibits strong saturable absorption. On the other hand, highly stable solutions containing a mixture of Ir and IrO2 nanoparticles with different ratios reveal very efficient OL performance for visible laser excitation. In addition, it was found that the IrO2 content of the solutions has a great impact on their NLO absorptive and refractive response, with the solutions having a higher Ir/IrO2 ratio revealing larger values of nonlinear absorption coefficient β and nonlinear refractive index parameter. The findings of the present study demonstrate that the variation in the Ir//IrO2 ratio of Ir-based nanohybrid solutions by choosing the appropriate synthetic strategy can result in at-will NLO response in view of specific photonic and optoelectronic applications. In summary, Ir-based nanocolloids were synthesized in methanol, in the presence and absence of PVP, by following three different synthetic procedures, affording solutions with different ratios of Ir and IrO