In conclusion, this data favours the sole cystatin C equation rather than the creatinine or combined equations when estimating GFR for risk prediction purposes in critically ill patients.Decreased glomerular filtration rate (GFR) is linked to poor survival. The predictive value of creatinine estimated GFR (eGFR) and cystatin C eGFR in critically ill patients may differ substantially, but has been less studied. This study compares long-term mortality risk prediction by eGFR using a creatinine equation (CKD-EPI), a cystatin C equation (CAPA) and a combined creatinine/cystatin C equation (CKD-EPI), in 22,488 patients treated in intensive care at three University Hospitals in Sweden, between 2004 and 2015. Patients were analysed for both creatinine and cystatin C on the same blood sample tube at admission, using accredited laboratory methods. During follow-up (median 5.1 years) 8401 (37%) patients died. Reduced eGFR was significantly associated with death by all eGFR-equations in Cox regression models. However, patients reclassified to a lower GFR-category by using the cystatin C-based equation, as compared to the creatinine-based equation, had significantly higher mortality risk compared to the referent patients not reclassified. The cystatin C equation increased C-statistics for death prediction ( Creatinine is the most frequently used biomarker for eGFR. Yet, creatinine may vary with factors not related to kidney function per se such as muscle mass, gender, ethnicity, and dietary factors3. Cystatin C is an alternative biomarker for eGFR-estimation which does not depend on muscle mass and thus fairly constant with age and gender5. Still, creatinine is the most frequently used estimate of eGFR in critically ill patients7. Patients in intensive care are often bedfast and may have loss of muscle mass and altered distribution volumes due to severe illness. An ongoing loss of muscle mass and low protein intake may possibly lead to a decrease in creatinine in plasma, leading to potential risk of eGFR overestimation8. It may therefore be hypothesized that creatinine is a less informative biomarker in the estimation of eGFR than cystatin C. Cystatin C may on the other hand be influenced by cortisol, obesity and other traditional risk factors or possibly inflammation13, which varies in critically ill. The performance of creatinine and cystatin C in estimating long-term mortality is less studied in critically ill patients.Glomerular filtration rate (GFR) is the best routinely available estimate for kidney function and essential for detection and management of both acute kidney injury (AKI) and chronic kidney disease (CKD). Loss of kidney function by decreased estimated glomerular filtration rate (eGFR) is associated with poor survivalThe aim of this study was to study the predictive value of creatinine and cystatin C in critically ill patients by investigating if cystatin C improves the association between eGFR and mortality, compared to creatinine, in this particular patient group using reclassification and model discrimination with C-statistics. The study includes a large number of intensive care patients from three Swedish University Hospitals and compares eGFR calculated by creatinine and cystatin C, respectively, and mortality risk at a median follow-up of 5 years.Out of the 22,488 included patients, 10,392 (46%) were admitted to a general intensive care unit, 2597 (11%) to a neurosurgical intensive care unit, 5132 (23%) to a cardiothoracic intensive care unit and 4367 (19%) were admitted to a coronary care unit. Table 2 are shown in cubic spline curves  for Cox regression models predicting mortality was 0.640 (0.631–0.649) for eGFRCr, 0.664  for eGFRComb and 0.667  for eGFRCyst. Thus, the equation with only Cystatin C significantly increased the C-statistics for the prediction of death as compared to the equations with Creatinine, both sole and combined.During follow-up  8401 (37%) participants died. Hazard ratios with 95% confidence intervals for mortality of all causes for each equation versus the reference point at 95 ml/min/1.73 m2, defined by respective equation, are presented in Table Incidence rates for mortality according to the eGFR categories > 60, 60–30, 30–20 and < 20 mL/min/1.73mP < 0.001, indicating improved reclassification by the cystatin C equation.Overall, patients reclassified to a lower GFR-category by using the cystatin C-based equation, as compared to the creatinine-based equation, had significantly higher mortality risk Table  comparedP < 0.001, indicating an improved reclassification.Generally, patients reclassified to a lower GFR-category by using the cystatin C-based equation, as compared to the combined equation, had significantly higher mortality risk Table  comparedP < 0.001, indicating improved reclassification.Patients reclassified to a lower GFR-category by using the combined equation, as compared to the sole creatinine equation, had significantly higher mortality risk Table  comparedThis study includes intensive care patient data from three Swedish University Hospitals and shows that eGFR estimated with cystatin C, alone or in combination with creatinine, was more closely associated with risk of death of all causes as compared to creatinine-based eGFR. More specifically, the sole cystatin C eGFR equation predicted mortality better than the combined equation. The associations were found in the whole sample as well as in the more critically ill subgroup at the general ICU. The underlying mechanisms for these associations are uncertain but may relate to either the a superiority of cystatin C as a GFR-biomarker in this setting or possible non-GFR effects of cystatin C associated with mortality or a combination of the two.14 or altered distribution volume due to fluid accumulation i.e. increased total water volume15. Other factors may include impared liver function, low meat intake, trauma or fever. All together these factors may potentially lead to a risk of falsely low creatinine values and hence eGFR overestimation in the critically ill patients17. Theoretically, Cystatin C may have advantages over creatinine in estimating eGFR. Cystatin C is produced by all nucleated cells and is not dependent of muscle mass18. Further Cystatin C is freely filtered in glomeruli and not affected by malnutrition19. One concern is that cystatin C generally may have a high turnover in critical illnesses such as sepsis and/or inflammation causing falsely too high concentrations possibly leading to underestimating eGFR11. However, a causal role between inflammation and cystatin C has been under debate and is difficult to establish20. Despite the theoretical advantages that cystatin C may have over creatinine as an eGFR-biomarker in critically ill patients, it has not been convincingly shown that cystatin C alone is more accurately related to golden standard measured GFR with iohexol clearance than creatinine alone. A study by Delanaye et al. showed that cystatin C was more closely related to measured GFR than creatinine alone in critically ill patients21. Another study showed that combined creatinine-cystatin C eGFR-equations or a mean of cystatin C eGFR and creatinine eGFR show the highest agreement with iohexol clearance in critically ill17. This high agreement between the combined equation and measured GFR has also been reported by the CKD-EPI group in patients with chronic kidney disease and in the general population23. Thus, these findings do not point out cystatin C alone as the most accurate biomarker for eGFR so this is not the whole explanation for the superior performance of cystatin C in prognosticating mortality.The theory of cystatin C being a more suitable GFR-biomarker than creatinine in critically ill patients arises from the well-known disadvantages of creatinine as a biomarker of GFR. The production rate of creatinine is mainly determined by the patients muscle mass. Generally, the reliability of creatinine as an accurate GFR-biomarker assumes a steady-state production, distribution and clearance of creatinine. Critically ill, bedfast, patients may for several reasons not be in steady-state due to ongoing loss of muscle mass24 but according to our data even one single measurement of Cystatin C at admission indicated a long-term mortality risk. Could non-GFR related factors underlie the strong association between cystatin C and long-term mortality? Cystatin C has been correlated with mortality independently of renal function in ICU patients8, a finding which is in line with this theory. Another study corroborates with this finding and found that cystatin C was correlated to all-cause mortality despite normal creatinine levels25. Traditional cardiovascular risk factors such as diabetes, obesity, smoking, hypertension, insulin resistance and inflammation and also non-traditional risk factors (symmetric dimetylarginine) have been linked to cystatin C13, and these diseases were highly prevalent as discharge diagnoses in this patient cohort. It cannot be ruled out that the reason why cystatin C predicts mortality better than creatinine is probably, at least in part, due to non-GFR related CVD factors affecting cystatin C. Similar results that the sole cystatin C equation outperformes combined equations or sole creatinine equations for mortality estimation have been shown for other patient groups than critically ill such as unselected patients seeking health care26. Further, a meta-analysis of community-based and CKD cohorts by the CKD-prognosis consortium, where cystatin C-based eGFR equations, alone or in combination with creatinine, strengthened the association between eGFR and death at all different levels of eGFR. However, despite the consistent superiority of cystatin C based eGFR over creatinine based GFR in previous studies, a recent large scale Mendelian randomization analyses, predominantly based on community based studies, did not support a causal role of circulating cystatin C in the development of cardiovascular disease27. Additional studies are warranted to provide further insights into the underlying mechanisms of these associations.Temporary acute kidney injury is common in critically ill patients and clearly related to fatal outcome28. Hence, the creatinine methods used in this study are sufficiently comparable for the included subjects and for the study aim. There were no loss to follow up due to the high quality of Swedish registry data29. We are not aware of any larger study comparing creatinine and cystatin C for risk prediction purposes in critically ill patients and we believe that since three large University Hospitals contributed with data the generalizability to critically ill patients in general increase. We did not include the factor for African-Americans in the formulas in this study based on the knowledge that study participants are predominantly Caucasian. This should not have biased our results but we acknowledge however that the study results may have limited generalizability to other ethnicities than Caucasian. Charlson comorbidity index only records prior hospital care, comorbidity treated in primary care may therefore have been missed which is a disadvantage. Given the possible non-GFR related connection between inflammation and cystatin C that has been proposed it is a disadvantage that the study lacks an inflammatory variable as a covariate in the models. Concerns have been raised that the net reclassification index may provide false positive findings during certain circumstances30, however, given the consistency of the superiority of cystatin C based GFR throughout the full range of eGFR provide support for the validity of our findings.All analyses were performed at accredited University Hospital laboratories with methods traceble to the international standard calibration which is a strength in this study. One laboratory changed the creatinine method from Jaffe to enzymatic during the study period. Jaffe methods are known to potentially overestimate creatinine, however at the time of the study inclusion the Jaffe methods at Swedish hospital laboratories were recalibrated to harmonize with enzymatic methodsA sole cystatin C equation for eGFR consistently predicted mortality risk better as compared to the sole creatinine-based equation or the combined creatinine/cystatin C equation in patients at intensive care units. Thus, our data favours the use of the sole cystatin C equation rather than the combined cystatin C-creatinine equation when estimating GFR for risk prediction purposes in critically ill patients.The retrospective observational study is based on simultaneous measurements of plasma creatinine and cystatin C on adult patients at admission to intensive care units at Uppsala, Karolinska and Lund University Hospitals, Sweden, from 2004 to 2015. These hospitals perform the vast majority of all cystatin C analyses in Sweden. The patients’ samples were analysed at Uppsala, Karolinska and Lund University Hospital Laboratories, respectively, on the same fresh plasma sample tube. Valid quantitative result of creatinine, cystatin C, age and gender were extracted from the laboratory information systems. All Swedish citizens and those with residence permit have personal identity numbers. Only patients with a complete personal identity number, 16 years of age and older, were included. If participants had more than one measurement only the first measurement was included in the study. In total, 22,488 unique patients with simultaneous measurements of plasma creatinine and cystatin C were included. Swedish Ethical Review Authority in Uppsala approved the research protocol, Dnr 2013/441. All methods were carried out in accordance with relevant guidelines and regulations and reporting followed the STROBE Statement. Informed consent from subjects was waived by the Swedish Ethical Review Authority in Uppsala since only anonymised registry data was analysed.Cr, in mL/min/1.73 m2, was estimated using The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) creatinine equation from 200931. Plasma cystatin C was analysed with reagents from Dade Behring on a BN ProSpec analyzer  at Uppsala and Karolinska University Hospitals until 2007 and thereafter with an assay from Gentian , traceable to the international calibrator ERM-DA471/IFCC, on Architect ci8200 in Uppsala33, and on UniCel DXC800 at Karolinska. Cystatin C was analysed with reagents from Roche, traceable to the international calibrator ERM-DA471/IFCC34, on Roche Cobas c501 in Lund. eGFRCyst in mL/min/1.73 m2 was calculated from plasma cystatin C using CAPA35. The international IFCC-equation Caucasian, Asian, Pediatric, and Adult cohorts (CAPA) is practically assay-independent since ERM-DA471/IFCC calibrated cystatin C-assays from 7 diagnostic companies are used. Further, the equation is based on Caucasian and Asian, both pediatric and adult cohorts. eGFRComb in mL/min/1.73m2 was calculated using the CKD-EPI combined creatinine/cystatin C equation (2012)22.Plasma creatinine (µmol/L) was analysed with a modified kinetic Jaffe method 2004–2008 and an enzymatic method 2009–2015 on Architect ci8200  in Uppsala, modified kinetic Jaffe method on UniCel DXC800  at Karolinska and an enzymatic method on Roche Cobas c501  in Lund. All methods were IDMS calibrated by the manufacturer and all three hospital laboratories were accredited. eGFR36. In brief, the CCI categorizes comorbidities of patients based on the ICD-10 diagnosis codes and sorted into categories. Included categories were myocardial infarction, congestive heart failure, peripheral vascular disease, cerebrovascular disease, chronic pulmonary disease, rheumatic disease, lever disease, diabetes with complications, diabetes without complication, hemiplegia or paraplegia, renal disease and HIV/AIDS. Each comorbidity category weights from 1 to 6  and the sum of all the weights is the comorbidity score for a patient. A score of zero indicates no comorbidities. A higher score is associated with a higher mortality risk. Three thousand five hundred and ten patients (16%) had no prior hospital care recorded in the National Patient Register. The endpoint mortality was defined using the Swedish Cause of Death Register for all participants and there was no loss to follow up. Both registers are administered by the Swedish National Board of Health and Welfare and records data for all Swedish residents.Comorbidity data from 2004 and forward for calculating the Charlson Comorbidity Index (CCI) i.e. in hospital care prior to the study intensive unit care was collected from the National Patient Register that collects data from all in-patient hospital visits in Sweden. CCI is described in detail in Quan et al.Cr, eGFRCyst and eGFRComb and mortality, respectively, were analysed in Cox proportional hazard regression models. The univariate hazard ratio was computed for each 1 ml/min/1.73 m2 of eGFR from 15 to 120 using a reference point at 95 ml/min/1.73 m237 and shown as regression spline curves. The Harrell´s C statistics38, 95% confidence intervals and p-values were calculated using the “somersd” package with the “lincom” command by splitting the study population randomly into a training set and a test set. We also divided the participants into risk categories according to the European Society of Cardiology (ESC) clinical cardiovascular prevention guidelines39 and the clinical decision limit for dialysis in the intensive care unit 20 ml/min/1.73 m2. Thus, the variables were entered into the models in the eGFR categories > 60, 60–30, 30–20 and < 20 mL/min/1.73 m2. The study population were classified to an eGFR category by the creatinine equation and the combined equation and proportion of participants who were reclassified to a higher or lower eGFR category by the cystatin C CAPA equation was assessed for mortality risk compared to the participants not reclassified using Cox proportional hazards models. Models were adjusted for the potential confounding variables age, gender and CCI since the patients who reclassified to a higher risk category with cystatin C were generally older, of male gender and had higher CCI.The associations of eGFR2 was evaluated using net reclassification improvement (NRI) according to Pencina et al.40P values < 0.05 were regarded as statistically significant. Calculations were performed with Stata 13 .Overall improvement in reclassification based the eGFR categories > 60, 60–30, 30–20 and < 20 mL/min/1.73 m


Animal populations are often comprised of both foraging specialists and generalists. For instance, some individuals show higher foraging site fidelity  than others. Such individual differences in degree of specialization can persist over time‐scales of months or even years in long‐lived animals, but the mechanisms leading to these different individual strategies are not fully understood.There is accumulating evidence that individual variation in foraging behaviour is shaped by animal personality traits, such as boldness. Despite this, the potential for boldness to drive differences in the degree of specialization is unknown.Rissa tridactyla) breeding at four colonies in Svalbard and deployed GPS loggers to examine their at‐sea foraging behaviour. We estimated the repeatability of foraging trips and used a hidden Markov model to identify locations of foraging sites in order to quantify individual foraging site fidelity.In this study, we used novel object tests to measure boldness in black‐legged kittiwakes , bolder individuals were more site‐faithful. Birds exhibited these differences while showing high spatial similarity in foraging areas, indicating that site selection was not driven by personality‐dependent spatial partitioning.We instead suggest that a relationship between boldness and site fidelity may be driven by differences in behavioural flexibility between bold and shy individuals. Together, these results provide a potential mechanism by which widely reported individual differences in foraging specialization may emerge. This paper reports the influence of animal personality on foraging specializations in black‐legged kittiwakes, finding that bolder birds show higher repeatability in their foraging behaviour and, during incubation, higher foraging site fidelity. The results indicate that bold individuals are more highly specialized in their foraging behaviour than their shy conspecifics. Kittiwakes are surface‐feeding seabirds which breed in socially monogamous pairs and exhibit biparental care, with both parents incubating eggs and provisioning for chicks until fledging at around 40 days , Krykkjefjellet (78°53′N 12°11′E) and Observasjonholmen (78°56′N 12°16′E) in Kongsfjorden, and Grumant (78°10′N 15°05′E) in Isfjorden. Kittiwakes build cup‐shaped nests from mud and vegetation Coulson, . At Grum2.2jwatcher v1.0 , a subset of which were refitted with a smaller battery to reduce mass  contained no evidence of ARS and were consequently removed from all analyses. All 10 trips were considerably shorter than the mean trip duration (1.5 hr vs. 10 hr), which supported that these movements were likely not foraging trips. In total, we recorded 111 foraging trips from 50 individuals during incubation, in 31 of which more than one trip was recorded for, and 212 foraging trips from 54 individuals during chick rearing, in 45 of which more than one trip was recorded for. All individuals with multiple trips recorded were personality tested . To standardize data resolution and to account for occasional missing GPS points, we used adehabitatLT . Hidden Markov models are a type of state‐space model, which decompose observed time‐series data  into an observed sequence of discrete behavioural states. Hidden Markov models were fitted using the moveHMM function from the 2.4r v3.5.1  to collapse the five behaviour variables into a single test score (PC1). We estimated adjusted repeatability , but single‐trip birds were retained as between‐individual pairs, to compare the focal individual with the full tracked population. The similarity index was then the proportion of between‐individual paired sites that were closer to the focal site than the within‐individual paired site (Appendix x) so that values towards 1 indicate high site fidelity  and towards 0 indicate low site fidelity . We ran 1,000 iterations of the randomization, such that each focal site was randomly paired 1,000 times. For each model iteration, we then fitted a binomial generalized linear model (GLM) with individual ID as a fixed effect to extract a single estimate and standard error of site fidelity for each individual across all of its foraging sites. The time difference (number of days) between paired sites was also included as a fixed effect, to account for variation in temporal proximity between pairs. This resulted in 1,000 estimates of site fidelity per individual. Finally, we examined the predictors of site fidelity using a linear model with the following structure: boldness, sex, colony and date were fitted as fixed effects, and the two‐way interactions between boldness and sex, and boldness and colony were included. Site fidelity was fitted as the response variable, and as the randomization generated 1,000 estimates of site fidelity per individual (one from each iteration of the randomization), the model was run 1,000 times also, using a loop to set the site fidelity estimates produced by each iteration of the randomization  and longitude  of foraging sites using LMMs. Trip ID nested within bird ID was fitted as a random effect to adjust for multiple foraging sites within a trip and multiple trips per individual. Boldness, sex, colony and date were fitted as fixed effects, and the two‐way interactions between boldness and sex, and boldness and colony were included. We additionally tested for a relationship between boldness and the extent to which a bird's foraging distribution overlapped with the colony‐level distribution and found no evidence for a relationship (see Appendix N = 39). These trips were excluded from our calculations of trip distance and duration, and were only included in calculation of maximum range from the colony if the bird had returned within 75% of the maximum distance from the colony before logger failure  mean foraging trip distance (km); (b) mean foraging trip duration (hours); and (c) mean maximum range from the colony (km). Occasionally recordings of foraging trips were incomplete due to logger failure . We detected no difference in boldness between the sexes .PC1 explained 61% of the variance in the response to the novel object  or between boldness and colony  on site fidelity.Site fidelity was variable between birds during both breeding stages  and range . During chick rearing, bold kittiwakes were more repeatable in foraging trip distance , duration  and maximum range , or boldness and colony . Females utilized sites further east than males during incubation  adjust their home ranges in response to increases in sea temperature , shy individuals were more responsive to changes in resource availability  found that bold birds foraged in areas associated with high competition, while shy individuals avoided these regions  were found to quickly develop a routine‐like search pattern of feeding sites and were robust in following routines even when sites have been unprofitable on previous visits, while shy birds were more likely to visit new sites (Verbeek et al., While shy animals typically exhibit flexibility in response to environmental fluctuations, bolder animals are instead thought to rely upon routines when navigating (Benus et al., 5Our study found that a widely studied personality trait, boldness, predicts more specialized foraging behaviour during incubation in four colonies of kittiwakes. Studies of specialized foraging behaviour often overlook variation in individuals' level of specialization (but see Grecian, Lane, Michelot, Wade, & Hamer, S.M.H., S.C.P., S.D. and L.U.S. conceived the study and the methodology. S.M.H. conducted statistical analysis and wrote the manuscript. S.M.H, S.C.P., S.D., P.B. and O.C. conducted the fieldwork. All authors contributed substantially to production of the manuscript. Click here for additional data file.


Drosophila type II neuroblast (NB) lineages prevents the generation of supernumerary type II NBs and premature differentiation of INPs. We show that loss of Six4 leads to supernumerary type II NBs likely due to dedifferentiation of immature INPs (imINPs). We provide data to further demonstrate that Six4 inhibits the expression and activity of PntP1 in imINPs in part by forming a trimeric complex with Earmuff and PntP1. Furthermore, knockdown of Six4 exacerbates the loss of INPs resulting from the loss of PntP1 by enhancing ectopic Prospero expression in imINPs, suggesting that Six4 is also required for preventing premature differentiation of INPs. Taken together, our work identified a novel transcription factor that likely plays important roles in maintaining INP homeostasis.In order to boost the number and diversity of neurons generated from neural stem cells, intermediate neural progenitors (INPs) need to maintain their homeostasis by avoiding both dedifferentiation and premature differentiation. Elucidating how INPs maintain homeostasis is critical for understanding the generation of brain complexity and various neurological diseases resulting from defects in INP development. Here we report that Six4 expressed in  Intermediate neural progenitors (INPs) are descendants of neural stem cells that can proliferate for a short term to amplify the number of nerve cells generated in the brain. INPs play critical roles in determining how big and complex a brain can grow. To perform their function, INPs need to maintain their own population and must not adopt the identity of neural stem cells, a process called dedifferentiation, or acquire the fate of their own daughter cells and stop proliferation too soon, a process called premature differentiation. However, how INPs avoid dedifferentiation and premature differentiation is not fully understood. In this study, we identified a protein called Six4 as a novel factor that plays important roles in preventing the generation of extra neural stem cells and premature differentiation of INPs in developing fruit fly brains. We described how Six4 functionally and physically interacts with other factors that are involved in regulating INP cell fate specification. Our work provides novel insights into the mechanisms regulating INP development and could have important implications in understanding how complex brains are generated during normal development and how abnormal brain development or brain tumor can occur when INPs fail to avoid premature differentiation or dedifferentiation. Intermediate neural progenitor (INP) cells are fate-restricted progenitor cells generated from neural stem cells (NSCs). INPs serve to amplify the diversity and number of neurons generated from NSCs through transit proliferation, thus contributing to the generation of brain complexity ,2. To peDrosophila larval brains, a particular type of NSCs called type II neuroblasts (NBs) produce neurons by generating transit amplifying INPs like NSCs in mammalian brains. These INPs can divide up to 10 rounds in a self-renewing manner to produce terminally dividing ganglion mother cells (GMCs), which further divide once to produce neurons or glia CH322-192H07 BAC clone that contains a ~9.4kb fragment upstream of the transcription start site of six4  and 10–12 type I NBs in each larval brain lobe  and the basal protein Miranda (Mira) during the division of type II NBs. We stained for Phospho-histone H3 (PH3), which is coupled with chromosome segregation and condensation , to deteerm-GAL4(II) and/or erm-GAL4 (III) to knock down Six4 in imINPs specifically. erm-GAL4(II) is expressed in both Ase- and Ase+ imINPs except the newly born imINPs, whereas erm-GAL4(III) is expressed slightly later, mainly in Ase+ imINPs We are sorry that we cannot be more positive about your manuscript at this stage. Please do not hesitate to contact us if you have any concerns or questions.Yours sincerely,ClaudeClaude DesplanAssociate EditorPLOS GeneticsGregory P. CopenhaverEditor-in-ChiefPLOS GeneticsReviewer's Responses to QuestionsComments to the Authors:Please note here if the review is uploaded as an attachment.Reviewer #1: A prominent mechanism of expanding the pool of neural progenitors in the fruit fly brain is the generation of intermediate progenitors by neuroblasts. In the central brain there are several neural lineages (termed type II NBs) that display such a way of proliferation. While much is known on the switch from NB to INP, the mechanism that maintain INPs in their state remain less understood.The authors show first that Six4 RNAi in type II NB lineages  increases the number of NBs. Next they show that Six4 is highly expressed in type II NBs and that expression decreases in INPs. They provide evidence that Six4 knock-down does not affect asymmetric cell division. A set of genetic experiments using specific genetic markers  further supports that the Six4 and Erm are critical for early/immature INPs by regulating PntP1- the authors provide support that this is likely a direct action.In summary I enjoyed reading the manuscript, it’s an intriguing addition to the type II mode of neurogenesis. The data are overall well-presented and of high quality. I only have a couple comments that were unclear to me.>I do see the mechanisms of Six4 and Erm to act within the lineage, but I am not sure how an early defect of splitting or duplicating lineages can be excluded? Among these lines in principle the additional NBs should be observed within a lineage (fig1), however it is unclear to me where individual lineages have their boundaries and where extra NBs are localized.> the main point of Figure 2 is to show Six4 expression, however while I agree that a triple/quadruple staining is informative, the way the wildtype data is represented is a bit confusing. Some image without the linage-depiction lines should be provided.Some expression remains in the RNAi knock-down. It would be helpful if the authors could comment on this.Reviewer #2: The manuscript by Rui Chen and colleagues addresses a very interesting question in neural development; namely, the mechanisms by which neural stem cells regulate the ultimate number of neurons and glial cells that are produced. These cells must prevent themselves from remaining stem cells to long but at the same time must prevent them from differentiating too quickly. When I read the abstract and introduction, I was very excited about his paper. The topic is very interesting and the authors had proposed a very nice mechanism.However, I have significant concerns about the results section. I had a very hard time matching the text of the results with the figures.1. My most significant issue is that had the authors had not placed arrows on each panel I would have not been able to see the results that they described in the text. I personally think that phenotypes should be displayed in an unbiased manner for the reviewer to evaluate. I don’t think our attention should be drawn to any particular region of an image. This paper is pretty egregious example – each panel with the main figures are littered with arrows – Figure 6K is a good example of what I am talking about. I tried to imaging what the figures would look like without the arrows. I concluded that I would not have been able to see what the authors are describing.2. In most of the images, the authors have placed arrows on cells that look identical to neighboring cells that do not have arrows. Thus it is difficult for me to agree with many of the conclusions in the text.3. The figures (at least the version that I downloaded) are of pretty poor quality. In many cases, I cannot even use the arrows as a guide. It looks like they are not pointing to any particular cell type.4. There are some quantifications that do not match the figures. For example, in figure 3 the expression of 2 copies of UAS-Six4 RNAi using erm-GAL4 is supposed to generate 1-2 additional type II NBs – however in figure 3B the authors are pointing to the same number of type II NBs as there are in the wild type shown in figure 3A. The chart in figure 3E indicates that there are 9 type II NBs on average in the mutant genotype.5. I think images need to be presented in a completely unbiased manner. Use arrows sparingly and allow the reviewer to make up his or her own mind without guidance on the panels. You might need to provide higher magnification images as many of the cells that you are pointing too are too small to us to analyze. And you might consider altering the color combinations to make your results easier to see. The differences between magenta and red cells is sometimes not clear in the present images.6. You might also consider generating a new figure (figure 1) in which you provide the readers with a set of schematics that describe the neuroanatomy of the brain – something akin to figure 3G. Start with a zoomed out view of the entire brain and make a series of successive schematics that progressively zoom into the area of the brain that we will be looking at in each panel.Reviewer #3: In this manuscript Chen et al. explore the mechanisms involved in the integrity and homeostasis of intermediate neural precursors (INPs). For that, they use a multitude of genetic and biochemical tools to disclose the mechanisms regulating fate-fidelity in neural stem cells and progenitor cells, using Drosophila’s neuroblasts (NBs) and immature precursor progenitors (INPs) as their model. In order to identify genes that are necessary for proper INP development, the authors conducted a screen where they specifically abolish the levels of transcription factors within type II NBs and then described how it affected proper lineage formation, in terms of number of NB, immature INPs (imINPs) and mature INPs (mINPs) within the central brain lobes. From this screen, they identified that downregulation of Six4  resulted in supernumerary NBs (from 8 to an average of 16 NBs per brain lobe), without affecting the number of mINPs. Also, they properly show that overexpression of Six4 in a RNAi background successfully rescues the phenotype. Thus, the authors conclude that Six4 is required to prevent supernumerary type II NBs in the larval brain. Then, it is excluded that supernumerary NBs arise from defective asymmetric division, while induction of Six4 RNAi expression in imINPs through an earmuffGal4 driver results in a mild but consistent increase in the number of NBs present (from 8 to 9-10). After, they show that abrogation of Six4 within NBs results in similar levels of PntP1 within NBs and imINPs, but that expression persisted in mINPs, indicating delayed suppression of PntP1. Not only that, but persistent levels of PntP1 promoted by Six4 depletion does not affect levels of Erm. Altogether, this indicates that both Six4 and Erm are involved in PntP1 repression in INPs. In line with the previous finding, overexpression of Six4 within NBs results in type II to type I transformation in 25% of the cases and Pntp1 decreased expression. Also, type II that retained their identity generated fewer INPs. Furthermore, the authors show that, like Erm, Six4 is capable of suppressing PntP1 expression and antagonize the activity of the latter. Hence, by ensuring proper inhibition of PntP1, Six4 is capable of granting imINP to become fate committed. To further elucidate the regulatory role of Six4, the authors show that (i) Six4 is capable of functionally replace Erm to prevent imINP dedifferentiation; (ii) Six4 and Erm independently co-immunoprecipitate with PntP1; (iii) Six4 and Erm coimmunoprecipitate with each other, indicating that these proteins interact with each other. While authors show that Six4 is capable of inhibiting PntP1 during INP maturation, the role of Six4 in NBs is still unclear. While overexpression of Six4 in NBs is capable of inhibiting PntP1, what is its physiological role in NBs? For that, authors co-inhibit PntP1 and Six4 in NBs in hopes that by silencing Six4 it would be possible to restore levels of PntP1 and rescue of the phenotype observed in single PntP1 knockdown (supernumerary Asense-positive NBs and mINP depletion). Nevertheless, the phenotype remained the same in terms of Ase-positive NBs. On the other hand, mINPs were completely depleted in this scenario and the supernumerary phenotype of type II NBs was also inhibited. Nevertheless, the authors show that, at a physiological level, Six4 may in part contribute to the suppression of prospero in newly-generated imINP, such as PntP1 does.Overall, the authors show great knowledge in terms of the field and the literature available for the full comprehension of this topic. Not only that, but it is possible to observe that the experiments have been well thought out, well-executed, and with a strong rationale to support them. Moreover, the manuscript is well written and can be understood by someone in the field. Due to the nature of the work, the manuscript can be a bit more difficult to follow by a non-specialist. Altogether, these novel results increment the knowledge we have today regarding NBs and INPs homeostasis and contribute greatly to the field.Point-by-point comments:It would be very interesting to also include the cell-type counts per lineage, so the reader has the understanding on whether there are supernumerary NBs within one lineage or if the supernumerary NBs form their independent lineages . This would corroborate that supernumerary NBs do not form by incorrect asymmetric division, but it would also not be evident that they would form by INP fate-reversion;Possibly, the image could be simplified: maybe just keep the arrows/arrow heads in one of the lineages and/or just keep them in the image with the merged channels;(line 157)Some CB type I NBs and respective newly-formed GMC and GMCs from the VNC (but not NB) express Six4. This is very interesting in terms of neural stem cell heterogeneity and eventual adult neuronal diversity. Are always the type I NBs and/or GMCs spatially located in the same regions of the brain?;While the experiments are consistently well designed throughout the manuscript, it is unclear what type of control it is used. For instance, in this case (mostly because the phenotype is so subtle), it would be important that the control animals also express two copies of a non-targeting RNAi (like a UAS-mcherry RNAi). Also, in this case, it would be important to know the number of NBs per lineage to understand where the extra NBs formed are located. This would be interesting, considering that the phenotype might arise early in development, during NBs specification (resulting in more NBs and more lineages), or if later during larval stages . It would also be interesting to further dissect the mechanisms of fate reversion by the absence of Six4 through the use of reporter lines (targeting fate-associated proteins) and long-term live cell and/or whole-brain imaging. Figure 3A is missing the scale bar;For simplification, reduce the number of arrows (maybe just keep them in some of the panels);For simplification, reduce the number of arrows (maybe just keep them in some of the panels);(line 334)While it is a strong possibility that Six4 binds directly to Erm, these experiments do not necessarily allow us to conclude that. Instead, it is possible to conclude that both are in close proximity/interact within the same complex/interact within the same chromatin context. Also, related to Figure 6P, it would be interesting to see whether you would see PntP1 being coIPed with Six4-HA or Myc-Erm, since none of the coIP experiments show that the three proteins are coIPed together: the upper panel shows that when Six4-HA is IPed it brings down Myc-Erm with it and, similarly, when Myc-Erm is IPed, it brings down Six4-HA. In addition, to better understand these questions, it would interesting to test the coIP using higher salt concentrations, to have a better idea how strong of an interaction it is. Also, it would be interesting to further address this question (not necessarily for the scope of this specific paper), like doing chromatinIP or targeted-DamID to address the chromatin binding of Six4/Erm/PntP1, to further dissect this regulatory axis at the molecular level;(line 334-336)The authors suggest that inhibition of PntP1 in imINPs putatively occurs via physical interaction with Six4 and Erm. Because this would take place after protein translation, as a post-translational mechanism, it does not justify how transcript levels of PntP1 drastically decrease over lineage progression (unless there is a positive feedback loop where PntP1 regulates its own expression);Just like previously suggested, for simplification purposes arrows can be removed;(line 418-424)Would it be possible to use an erm-Gal4 in the II chromosome in combination with erm-Gal4 on the III chromosome? Both are expressed in imINPs, but in slightly different stages  – or in Ase-positive imINPs – R9D11-Gal4 (III)). Maybe this strategy would enlarge the timeframe of expression of the RNAi. Also, the second hypothesis could be easily addressed by using the modERN line expressing Six4-GFP, to see whether induction of the RNAi against Six4 with erm-Gal4 is not enough to decrease levels of Six4 in INPs;(line 463 onwards)https://doi.org/10.1101/2020.02.03.931972). This could be a good strategy to do this same experiment in a Drosophila brain context;Authors discuss whether the presence of Erm and Six4 is required for complex stability. First, while results are very convincing and well curated, I think it is too premature to state that they form a proper complex. It seems too strong of a statement given the results available. From their IP studies, when they express Six4-HA or Myc-Erm, the interaction with PntP1 is of the same extent . By performing a salt gradient, maybe it would be possible to study the stability of this complex. Also, it has been shown that transient overexpression of Insensible in a brat null induces supernumerary type II NBs to synchronously transition into INPs, thus leading to an enrichment of INPs within the brain There is a typo .**********Have all data underlying the figures and results presented in the manuscript been provided?PLOS Geneticsdata availability policy, and numerical data that underlies graphs or summary statistics should be provided in spreadsheet form as supporting information.Large-scale datasets should be made available via a public repository as described in the Reviewer #1: YesReviewer #2: YesReviewer #3: Yes**********what does this mean?). 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CopenhaverEditor-in-ChiefPLOS GeneticsReviewer's Responses to QuestionsComments to the Authors:Please note here if the review is uploaded as an attachment.Reviewer #2: I appreciate the authors efforts to address the comments of myself and the other two reviewers. The additional schematic drawings are very helpful. I also appreciate the authors taking the suggestion of two of us and removing many of the arrows and arrowheads from various figures. As I mentioned in my first review, I find the topic of this paper very interesting and it is addressing a very important question – namely how are intermediate neural progenitors prevented from either dedifferentiating or differentiating too quickly. As the authors point out, maintaining the balance of INPs is critical for producing a brain of the right size and cell numbers.I read the paper several times and I still am having trouble seeing the phenotype just from the images. I have downloaded the original files and while they are of very high resolution it is really difficult for me to see the difference among the different genotypes. In my initial review I had requested that the authors remove the arrows and arrowheads since I wanted to see if I could look at the brain images and see if I came to the same conclusion as the authors. Without the graphs documenting the quantifications, I would not be able to see the difference between many of the panels. For a non-expert it is not clear why some cells are counted while others are not. For example, in panels 2B,C,D the authors place arrows on certain cells. But there are other cells that show the same expression profile that are not marked with arrows. This is true of many of the panels throughout the paper. I think this is going to be problematic for the non-expert and will reduce the enthusiasm for the paper.I think the quantifications that are presented throughout the paper suggest that Six4 is playing an essential role in this maintaining INP balance in numbers. It is just very hard for me to see it without the arrows/arrowheads and charts. I guess I am struggling with understanding how the authors selected some cells and not others even though both cells express the same set of markers.I also feel that some of the images are very small. This was a problem with the first version. Even looking at the high resolution images does not help. It is still very hard to see what is being pointed to in figure 7A,B,F,G,H.The authors mention that Six4 is functioning after larval hatching. Using a tub-GAL80ts, the authors allowed for expression of the RNAi line only after larval hatching and see that each brain lobe had one extra type II NB. This is in contrast to flies that don’t have the tub-GAL80ts, which results in 16 NBs per brain lobe. The authors conclude that since they see one extra NB it must mean that Six4 is functioning after larval hatching. I would think that since most of the extra NBs are not generated when the RNAi line is expressed after larval hatching it would mean that Six4 is actually functioning during embryonic stages.The manuscript would also be helped if the authors could include a molecular model of how NB progress to imINPs to mINPs to GMCs. There is a lot going on in this pathway and the authors do an excellent job of describing it within the introduction. A diagram would really help the reader.Reviewer #3: First of all, I appreciate the efforts the authors made to address all the comments, questions, and suggestions proposed by all the reviewers. Overall, while the manuscript was very well written in its initial version, in some instances the figures were a bit difficult to interpret, thus making difficult the understanding of the results. By simplifying and clarifying their meaning, it was clearer what the authors report in the text. Also, in their point-by-point answers to the reviewers, the authors were objective and up-front, addressing most of the questions appropriately. In addition, as suggested by another reviewer, the authors included a much-appreciated schematization of the larval brain, incredibly useful for those that are non-specialists.I have a number of concerns regarding some of the pivotal findings (some of them serving as the main premise of the paper). For instance, and related to the results depicted in Figure 1, one of the things that was not clear in the initial version of the manuscript, was whether the supernumerary neuroblasts arising upon Six4 depletion were: (i) neuroblast forming independent lineages and those lineages were virtually identical to a wildtype one  or; (ii) the ectopic neuroblasts would co-exist withing the same lineage thus supporting the idea of defective asymmetric division (which the authors do not observe) or dedifferentiation/fate reversion of INPs. According to the answer provided by the authors “4% of Six4 knockdown type II NB lineages had multiple type II NBs, while the other 96% of NBs formed independent lineages (…)”. First, if the phenotype is promoted by dedifferentiation of INPs, one would expect lineages with ectopic NBs, that is only verified in 4% of the cases . Also, if the NBs are formed at the expense of INPs, one would expect decreased numbers of this cell type (and GMCs) along the affected lineages, which is not really the case .Another concern regards the claims that the phenotype takes place after larval hatching, thus excluding that NBs specification during embryonic stages would not be affected. In fact, this was one of the interrogations that I and other reviewers had when looking at the figures provided during the initial submission of the paper. To tackle this problem, the authors controlled the expression of the Six4 RNAi with tubGal80ts, initially rearing the animals at the restrictive temperature and only shifting them to the permissive temperature after larval hatching. In this context, as shown in Figure S1, the authors observed the appearance of one more NB per lobe (in average) in opposition to the 16 NBs they observe when animals without expression of tugGal80ts. Because the phenotype is completely distinct and much stronger in one case versus the other , these results indicate that the Six4 is actually exerting its activity during embryonic stages. Having that, and while it is not excluded that Six4 exerts a regulatory role during larva stages, it should not be excluded that the phenotype (supernumerary neuroblasts caused by NB duplication or unfaithful specification during embryonic stages).Later, to investigate whether Six4 generates supernumerary NBs through dedifferentiation of INPs, the authors decide to abolish Six4 levels within INPs and address the number of NBs. Again, as previously, the phenotype is extremely discreet . The phenotype was slightly stronger when Six4 RNAi was performed in erm heterozygous background , but still very variable . Not only that, but from what is possible to understand from Figure S4 D, E, levels of Six4 within INPs are virtually the same as the control, indicating that the RNAi is not effective when its expression is driven by ermGal4 .At this point, I would not advise the execution of complementary experiments. Instead, I think that the text can be reorganized/re-written in order to better reflect the results in a completely unbiased way. Taking that into consideration, I believe that the manuscript is of interest to the field and I recommend its publication if the authors address the critical concerns described previously and described one-by-one bellow:- I would recommend a change in the title, in order to reflect better the results shown in the manuscript.- From line 128 to 130, the authors claim that “Co-existence of multiple type II NBs in single lineages indicates that these extra type II NBs could be just generated late during larval development and did not have enough time to establish their own independent lineages yet.”. Wouldn’t you expect that, after each round of NB division, the newly formed INP  would fail to commit to its fate and revert back to a NB-like state? If so, shouldn’t there be even more NBs per lobe and per lineage? And why would this occur on such a relatively small scale? Considering that you have 16 NBIIs per lobe upon Six4 depletion, it means that, on average, only one 1 INP per lineage dedifferentiated? Why that only one INP would be affected? Are these newly formed NBs any different from the primary ones? These questions are in the context of INP dedifferentiation upon knockdown of Six4.- From line 154 to 156 the authors conclude that knockdown of Six4 during larval stages  supports that the supernumerary neuroblasts arise during larval development and not during NB specification. Unfortunately, these results do not necessarily support that statement. In no place in the paper should be excluded the embryonic contribution of Six4  initially through regulation of NB specification and (ii) later in the maintenance of INP pool). This should be clearly stated in the results section and, if appropriate, the authors could develop on this in the discussion section.- From line 204 to 205 the authors conclude that “Although the phenotype is weak, the consistent generation of extra type II NBs and the existence of multiple type II NBs in single lineages indicate that the supernumerary type II NB phenotype likely results from dedifferentiation of imINPs.”. This is clearly an overstatement and the sentence/section should be changed in order to factually report what is observed. From the image provided, it is not clear the co-existence of 2 or more NBIIs per lineage and, indeed, the phenotype is very weak (likely due to the inefficiency of the RNAi in INPs). At this point, and without any further experiments, it is difficult to say that, by itself, abrogation of Six4 leads to dedifferentiation of INPs (you would require further experimentation to appropriately test this).- From line 207 to 210. I do think that this result is more indicative (but not conclusive) regarding the role of Six4 in INP dedifferentiation. Since the idea is that ectopic NBs are formed at the expense of INPs, it would be interesting to determine the number of mINP in this specific experiment .- When pntp1 and erm start to be introduced in the results section (namely regarding synergistic role with Six4), it would be interesting to include a scheme depicting the molecular pathway through which a type II lineage progresses .**********Have all data underlying the figures and results presented in the manuscript been provided?PLOS Geneticsdata availability policy, and numerical data that underlies graphs or summary statistics should be provided in spreadsheet form as supporting information.Large-scale datasets should be made available via a public repository as described in the Reviewer #2: YesReviewer #3: Yes**********what does this mean?). 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Also, and upon analysis of the answers provided by the authors , the authors were very pragmatic and comprehensive, allowing us to better understand the data and their point of view. Overall, I believe that the manuscript significantly increments the knowledge of the field and, for that reason, I believe it meets the publication standards required by the journal.**********Have all data underlying the figures and results presented in the manuscript been provided?PLOS Geneticsdata availability policy, and numerical data that underlies graphs or summary statistics should be provided in spreadsheet form as supporting information.Large-scale datasets should be made available via a public repository as described in the Reviewer #2: YesNo: Reviewer #3: **********what does this mean?). 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The use of parasites or their products for treating chronic inflammation associated diseases (CIADs) has generated significant attention recently. Findings from basic and clinical research have provided valuable information on strengthening the notion that parasites’ molecules can be developed as biotherapeutic agents. Completion of the genome, secreotome, and proteome of the parasites has provided an excellent platform for screening and identifying several host immunomodulatory molecules from the parasites and evaluate their therapeutic potential for CIADs. One of the widely studied host immunomodulatory molecules of the parasites is the cysteine protease inhibitor (cystatin), which is primarily secreted by the parasites to evade host immune responses. In this review, we have attempted to summarize the findings to date on the use of helminth parasite-derived cystatin as a therapeutic agent against CIADs. Although several studies suggest a role for alternatively activated macrophages, other regulatory cells, and immunosuppressive molecules, in this immunoregulatory activity of the parasite-derived cystatin, there is still no clear demonstration as to how cystatin induces its anti-inflammatory effect in suppressing CIADs. Incidences of chronic inflammation associated diseases (CIADs) are surging worldwide . CIADs iSchistosoma mansoni, Ancylostoma caninum, Anisakis, Trichuris suis, and Brugia malayi are shown to inhibit immune responses in experimental colitis, rheumatoid arthritis, multiple sclerosis, and type-1 diabetes . T. T42]. TType-3 cystatins (kininogens) are the most complex cystatins consisting of three type 2 domains. Kininogens are about 350 amino acid residues long, mostly glycosylated, and consist of eight disulfide bonds C 33]. K. K33]. KParasite cystatins, including other immunomodulatory molecules, are critically involved in the establishment of active parasitism in the hosts . AmongstOnchocerca volvulus, Ascaris lumbricoides, and Heligmosomoides polygyrus can reduce the surface expression of HLA-DR, CD40, and CD86 co-stimulatory molecules on human monocytes, which are critical for antigen presentation . Th. Th56]. entation ,62,63,64and CD86 ,66,67.B. malayi filarial parasite, also possess an additional asparginyl endopeptidase (AEP) inhibitory site that may also interfere with the MHC Class II antigen processing in human APCs by inhibiting asparginyl endopeptidase [Few parasite cystatins, such as CPI-2 from eptidase . AEP inheptidase . Thus, ieptidase . Cystatins may also interfere with the processing of pattern recognition receptors (PRR) . PRR areB. malayi cystatin has been shown to induce IL-10 in human monocytes and macrophages via the p38 dependent pathway in monocytes and also the ERK-dependent pathway in macrophages [A. viteae cystatin also mediates IL-10 production in murine macrophages via the tyrosine kinase pathway and is dependent on the activation of mitogen-activated protein kinases (MAPK) [A. viteae cystatin induces the expression of DUSP1 and DUSP2 [A. viteae cystatin also induced phospho-ERK regulated phosphorylation of STAT3 [IL-10, an anti-inflammatory cytokine is responsible for optimally modulating Th1 immune responses, APCs, and T cells . IL-10 lrophages . A. vites (MAPK) ,81. The s (MAPK) . Both thof STAT3 .B. malayi, O. volvulus, A. viteae, and Angiostrongylus cantonensis are shown to induce NO secretion from IFN-γ primed macrophages, a response partly dependent on TNF-α and IL-10 [Litomosoides sigmodontis and S. japonicum appears to reduce NO secretion from murine peritoneal macrophages [B. malayi cystatin could induce alternative activation of murine peritoneal macrophages with decreased NO and increased arginase activity [Like IL-10, NO is another physiologic key molecule modulated by some parasite cystatins. NO is released by activated macrophages to inhibit parasitic invasion and induce host-protective immune responses, a common phenomenon against infections . Howevernd IL-10 ,87. The rophages ,88. Thisrophages ,87. Thisrophages ,90. Our activity . HoweverAcanthocheilonema viteae cystatin can inhibit murine T cell proliferation in vitro [O. volvulus CPI-2 reduces polyclonal and antigen-specific T cell proliferation [L. sigmodontis cystatin reduced antigen-specific splenocyte responses in mice [Filarial cystatins also showed suppression of T-cell proliferation . Acanthoin vitro . O. volvferation ,92. L. s in mice . These TExperimental studies in animal models for CIADs have provided valuable information on the beneficial effects of parasite cystatins (summarized in A. viteae (Av17) in murine models of dextran sodium sulfate (DSS)-induced colitis. Av17-treated colitis animals showed a significant reduction in the colitis inflammatory index and also improved pathology of the colon with less inflammatory cell infiltrations. Another study using AvCystatin, highlighted the role of IL-10 from regulatory macrophages (Mregs) in the suppression of the colitis conditions [E. coli Nissle 1917 to secrete A. viteae cystatin has shown extraordinary effects in reducing intestinal inflammation in both mice and pigs [Inflammatory bowel disease (IBD) is a chronic and relapsing inflammatory condition of the gastrointestinal tract. According to the Centers for disease control and prevention (CDC), about 1.3% of United States’ adults have been diagnosed with IBD. Therapeutic effects of cystatins are widely tested in various chemically induced and knockout animal models for IBD. Schnoeller et al.  were thenditions . Transfeand pigs .B. malayi (rBmaCys) in both acute and chronic colitis. rBmaCys-treatment given to DSS-induced colitis mice reduced the clinical and pathological severity of disease conditions in mice [BmaCys [Our group has shown the therapeutic capabilities of cystatin from filarial a parasite  in mice ,99,100.  [BmaCys . FurtherS. japonicum has also been widely tested against experimental colitis. rSjcystatin administration significantly ameliorated the tri-nitrobenzene sulfonic acid (TNBS)-induced colitis with increased Tregs in mesenteric lymph nodes (MLN) and lamina propria mononuclear cells (LPMC) of the treated mice [Cystatin from ted mice . The obsted mice ,103,106.Ascaris lumbricoides and Clonorchis sinensis, have also shown potential ameliorative effects on DSS-induced colitis in experimental animals [C. sinensis Stefin-1, the IL-10 levels were significantly increased in the spleen and MLN along with an increase in IL-10+ F4/80+ macrophages. These studies demonstrate the potential of parasite cystatin as a biotherapeutic for colitis.Cystatins from other parasites, such as  animals ,106. In A. viteae cystatin (Av17) in a murine model of OVA-induced allergic airway responsiveness significantly inhibited the eosinophil recruitment into the lungs of treated mice, lowered the levels of antigen-specific and total IgE, thereby reducing sensitization to mast cells and basophils [A. viteae cystatin treated mice followed by the induction of the allergen challenge resulted in the suppression of allergen-specific IgE and reduced the infiltration of eosinophils into the lungs of mice with suppression of generalized Th2 immune responses in the lungs [A. viteae cystatin treatment also alleviated the timothy grass pollen-induced allergic responses in a mouse model [A. viteae cystatin treated mice. This increased IFN-γ seems to have beneficial effects in suppressing allergen-specific Th2 immune cells, a response observed in atopic patients after immunotherapy [A. viteae cystatin induces both IL-10 and IFN-γ to reduce allergic condition is not clear yet and needs further investigation. A recent study showed A. lumbricoides cystatin (rAl-CPI) treatment significantly reduced house dust mite-induced allergic airway inflammation [About 10–30% of the world’s population is affected by allergies . Allergiasophils . A predoasophils . Subsequhe lungs . A. vitese model . Surprisotherapy . Howeverammation . After eammation . These fB. malayi cystatin could suppress the severity of mBSA-induced arthritis [Rheumatoid arthritis is a chronic inflammatory condition of joints. This disease affects approximately 54.4 million (25%) people in the United States and is estimated to affect over 78 million by 2040 . Severalrthritis ,98. Trearthritis ,98. Collrthritis . The mecrthritis . RANKL irthritis . AdditioIn addition to these three diseases , cystatin treatment has been found to be highly effective in other immune-mediated disorders, such as sepsis and type-1 diabetes ,104. SjCImmune-mediated conditions are complex, and the incidence of these disorders is overwhelmingly increasing. Better therapies and cure are urgently needed. Epidemiological and experimental evidences support the principle of helminth therapy (HT). Given the limitations of the use of HT, much attention has been recently focused on identifying specific immunomodulatory molecules of the parasites and evaluating their biotherapeutic potential in various CIADs. Among the various molecules identified, cystatins of helminth parasites are the most extensively studied immunomodulatory molecules with demonstrated activity as a biotherapeutic molecule for CIADs. Studies in various experimental animal models confirm the therapeutic potential of this molecule. Several studies attempted to identify the mechanism by which cystatin induces its immunomodulatory activity. These studies identified a role for macrophages, IL-10, regulatory cells, and several receptors and signaling molecules. Nevertheless, there is a need to identify the comprehensive mechanism by which parasite cystatin induces the generalized immunosuppression, which can be harnessed to develop this molecule further as a therapeutic molecule for treating autoimmune conditions including CIADs.


Overall, our study developed a biobetter antibody of omalizumab, AB1904Am15, which has the potential to show improved clinical benefit in the treatment of allergic diseases.The critical role of IgE in allergic diseases is well-documented and clinically proven. Omalizumab, a humanized anti-IgE antibody, was the first approved antibody for the treatment of allergic diseases. Nevertheless, omalizumab still has some limitations, such as product instability and dosage restriction in clinical application. In this study, we attempted to develop an omalizumab biobetter antibody with the potential to overcome its limitations. We removed two aspartic acid isomerization hotspots in CDRs of omalizumab to improve antibody candidate’s stability. Meanwhile, several murine amino acids in the framework region of omalizumab were replaced with human source to reduce the potential immunogenicity. Yeast display technology was then applied to screen antibody candidates with high binding affinity to IgE. Moreover, YTE mutation in Fc fragment was introduced into the candidates for extending their serum half-life. A lead candidate, AB1904Am15, was screened out, which showed desired biophysical properties and improved stability, high binding affinity and elevated potency  Allergic diseases, such as allergic asthma, atopic dermatitis, allergic rhinitis and food allergy, represent a chronic disorder of the immune system to various environmental allergens, for example, house dust mites, pollens and animal dander. Moreover, the incidence of allergic diseases is rising all over the world , 2. Amonvia interaction with its two receptors, namely the high-affinity receptor FcϵRI and the low-affinity receptor CD23 for IgE  is a humanized IgG1 antibody containing approximately 5% murine and 95% human sequences. It is the first and the only anti-IgE monoclonal antibody approved in several countries for the treatment of severe or moderate-to-severe persistent allergic asthma , 16. Fur; Xolair Despite showing efficacy against allergic diseases, in particular against allergic asthma, omalizumab still has some limitations –31. FirsIn this study, we sought to develop an omalizumab biobetter antibody candidate with the potential to overcome above mentioned challenges. Firstly, we applied antibody engineering technology to optimize omalizumab sequence to reduce the potential immunogenicity risk, and remove the two typical Asp isomerization hotspots in CDRs to improve stability. Secondly, affinity mature was carried out by yeast surface display platform using above optimized sequence as a template to screen for higher affinity antibody candidates. Finally, the crystallizable fragment (Fc) engineering technology was applied to extend serum half-life of antibody. The biophysical properties, stability profile and biological activity as well as efficacy of candidates were also evaluated.Omalizumab was purchased from Novartis . L0H0 was an in-house produced omalizumab biosimilar antibody. MEM medium, FBS, Formic acid and acetonitrile were obtained from Thermo Fisher Scientific . Iodoacetamide (IAM), dithiothreitol (DTT), urea, β-mercaptoethanol, HRP-labeled streptavidin, guanidine hydrochloride and ammonium carbonate were obtained from Sigma-Aldrich .2 incubator at 37°C.ExpiCHO-S™ cells were obtained from Thermo Fisher Scientific  and cultured in ExpiCHO medium according to manufactory’s instruction. Yeast cells were acquired from American Type Culture Collection  and cultured according to manufactory’s introduction. RBL-2H3/FcεRI cells were generated by Shanghai GeneChem  and cultured in MEM medium supplemented with 15% FBS in a 5% COAt first, we selected the most homologous germline antibody genes from IMGT database for humanization of omalizumab to minimize possibility of immunogenicity in human, and removed two Asp isomerization hotspots in CDR-L1 at L32–33 and in CDR-H2 at H55–56 for improving candidate stability. And then, we took this engineered candidate molecule as template, designed mutation library of each CDR in variable domains, displayed Fab on the surface of yeast cells  and sortCandidates were expressed in ExpiCHO-S™ cells. The VH and VL variable regions of antibody candidates were subcloned into expression vectors containing constant regions of IgG1 isotype. The candidates’ heavy chain and light chain expression vectors were co-transfected into ExpiCHO-S™ cells. After 8 days of growth, the supernatant was harvested and passed over AmMag™ Protein A Magnetic Beadsaccording to the manufacturer’s instruction. Yields of purified antibody candidates were determined based on their UV absorbance at 280 nm by a Nanodrop instrument .XL column . The mobile phase was 200 mM sodium phosphate (pH 6.8) at the flow rate of 0.5 ml/min. Samples were measured by UV absorbance at the wavelength of 280 nm. Data were analyzed by Waters Empower 3 Enterprise software .SEC-HPLC was performed to quantify monomer purity of candidates on a Waters Alliance 2695 HPLC system with TOSOH TSKgel G3000WHIC-HPLC was performed to evaluate hydrophobicity of candidates on a Waters Alliance 2695 HPLC system with Thermo MAbPacHIC-10 column . The mobile phase A consisted of 1 M ammonium sulfate with 50 mM sodium phosphate (pH 7.0), and the mobile phase B consisted of 50 mM sodium phosphate (pH 7.0). Samples were injected and eluted in a linear gradient at the flow rate of 0.8 ml/min, measured by UV absorbance at the wavelength of 214 nm. Data was analyzed by Waters Empower 3 Enterprise software.CE-SDS was conducted on Beckman PA800 Plus Pharmaceutical Analysis system  to separate candidates’ size variants under reduced or non-reduced conditions. For non-reduced condition, samples were diluted by SDS-MW sample buffer and incubated with IAM at 70°C for 10 min. For reduced condition, β-mercaptoethanol was mixed with samples and incubated at 70°C for 10 min. And then, both non-reduced and reduced samples were injected and separated according to the instruction of IgG Purity and Heterogeneity Kit . Acquired data were processed by 32 Karat software .2O until a final protein concentration of 0.2 mg/ml was reached. Samples were pre-focused at 1,500 V for 1 min and focused at 3,000 V for 10 min with detection at 280 nm. Data were acquired and analyzed by Chrom Perfect software.Isoelectric point and charge variants were characterized on iCE3 system. Samples were mixed with pharmalytes, 1% methyl cellulose, pI marker and ddHProtein Thermal Shift™ Dye kit  was applied to evaluated the melting temperature (Tm) value of candidates. According to manufactory’s instruction, samples were mixed with protein thermal shift™ buffer and protein thermal shift™ dye solution. Protein melt reactions were run on an Applied Biosystems Real-Time PCR System . Data was collected and transferred to Protein Thermal Shift Software (Version 1.3) to calculate the Tm value of candidates from the melt curve.For identification of PTMs induced in forced degradation study, samples were assessed by peptide mapping using Waters ACQUITY UPLC H-ClassBio System coupled with Waters Xevo G2-XS QTOF mass spectrometer. Samples were denatured by 6 M guanidine hydrochloride, and reduced and alkylated with 60 mM DTT and 150 mM IAM, respectively. And then, the reduced alkylated samples were desalted and buffer exchanged to 50 mM ammonium carbonate buffer (pH 8.0) for digesting with trypsin . The digested samples were injected onto a Waters ACQUITY UPLC BEH300 C18 column  coupled online to Waters Xevo G2-XS Q-TOF mass system for separation and detection. Data were collected and analyzed by Waters UNIFI Scientific Information System software.A series of stress conditions were applied to evaluate the stability of antibody candidates. Samples were expressed, purified and buffer exchanged into the formulation buffer, which contained 5 mM histidine, 85 mM sucrose, and 0.01% polysorbate 20 (pH 6.0). After putting on the stress conditions for several times, samples were analyzed by SE-HPLC, CE-SDS, and iCIEF for obtaining stability proﬁling. To identify degradation variants, peptide mapping was used to characterize the stressed samples by LC–MS/MS.D value was evaluated by Biacore Evaluation software .The binding affinity of antibody candidates to IgE was evaluated by Biacore 8K  instrument. The Biotin CAPture reagent was captured on Sensor Chip CAP , followed by capturing 2 μg/ml of biotinylated full length human IgE  with a flow rate of 10 μl/min for 60 s. Kinetic measurements were executed by injecting serially diluted antibodies with a flow rate of 30 μl/min for 180 s, followed by measuring dissociation for 400 s. The data was globally ﬁtted using a 1:1 binding model. The KThe ability of antibodies to block human IgE binding to its receptor FcϵRI was measured by a competitive ELISA. The ELISA plate was coated with 0.5 μg/ml recombinant soluble FcϵRI protein  overnight at 4°C. The plates were blocked with blocking buffer (2% BSA in PBST) at 37°C for 1 h after washing with PBST (PBS/0.05% Tween-20). Biotinylated human IgE was mixed with serially diluted candidates and incubated at 37°C for 2 h, then added to the plate for further incubation at 37°C for 1 h. The plate was washed and HRP-labeled streptavidin was added to detect IgE bound to FcϵRI. After incubation for 1 h, the plate was washed and TMB solution  was added to detect the optical density at 450 nm. Data was analyzed by GraphPad Prism (Version 8).2 overnight. The cells were washed and the 1 μg/ml of polyclonal anti-human IgE  was added to the cells, following by incubation at 37°C for 30 min. The supernatant was collected and the histamine concentration was determined by Histamine Dynamic kit  according to the manufacturer’s instruction.FcϵRI-expressing RBL-2H3 cells were cultured with serially diluted antibodies and human IgE  to a final IgE concentration of 1.2 μg/ml at 37°C, 5% COvia subcutaneous administration (n = 4/group). Serum samples were collected from submandibular vein by cheek puncture at the following time points: pre-dose, 2, 6, and 24 h post dose; and 2, 3, 4,7, 10, 14, 21, 28, 35, and 42 days post dose. Serum concentrations of the antibody were measured by an ELISA method. Briefly, anti-human IgG1  antibody was used as the capture reagent and the mouse anti-human Fab  conjugated to HRP was used for detection. Data was analyzed using GraphPad Prism (Version 8) and pharmacokinetics parameters were determined using Phoenix WinNonlin 6.3 .A pharmacokinetic study was conducted in human FcRn (hFcRn) transgenic mice and the study protocol was approved by Institutional Animal Care and Use Committee (IACUC). Human FcRn transgenic mice were purchased from Biocytogen , 6–8 weeks old male mice were used. Mice received a single dose of 10 mg/kg test antibody In vivo efficacy study was conducted in a cynomolgus monkey model of asthma and the study protocol was approved by IACUC. Cynomolgus monkeys were purchased from Hainan Lingzhang Experimental Animal Development Co., Ltd . 3–7 years old male cynomolgus monkeys weighing between 3 and 7 kg were used. To develop the allergic asthma models, monkeys were sensitized with dinitrophenyl-Ascaris suum (DNP-As) allergen following the procedure as previously described (via subcutaneous administration (n = 4/group) for 3 weeks. Humanized IgG1 antibody was used as isotype control. Omalizumab was used as a positive control. Airway resistance (RL) and lung dynamic compliance (Cdyn) were measured at 24 h post 1st and 3rd dosing.escribed . After mvia GraphPad Prim 8. The data was expressed as mean ± standard deviations (SD) .Statistical analysis was performed by two-way analysis of variance (ANOVA) D values of AB1904Am3, AB1904Am5 and AB1904Am10 were significantly lower than L0H0, an in-house generated omalizumab biosimilar antibody, while the value of AB1904Am6 was almost the same as L0H0. The results also showed the KD values of AB1904Am1 and AB1904Am8 were higher than L0H0, which indicating the lower affinity of AB1904Am1 and AB1904Am8 to L0H0. Therefore, AB1904Am3, AB1904Am5, AB1904Am6 as well as AB1904Am10, which had higher or similar affinity compared with L0H0, were chosen as candidates for the further evaluation.To improve the antigen affinity of antibody candidates, yeast surface display technology was used for affinity maturation. At first, we removed two aspartic acid isomerization hotspots in CDR-L1 at L32 and in CDR-H2 at H55 for improving antibody stability of omalizumab. In addition, seven murine amino acids in the framework region of omalizumab were replaced with human source to minimize the possibility of immunogenicity  and non-reduced CE-SDS (nrCE-SDS) to detect molecular size variants, by HIC-HPLC to evaluate hydrophobicity property, by DSF to detect thermal stability, and by iCIEF to detect pI value and charge variants. L0H0 was an in-house generated omalizumab biosimilar antibody. The comparability study including biophysical properties and biological activity was evaluated between L0H0 and omalizumab. Our results demonstrated that L0H0 had the high similarity both in biophysical characteristics and biological activities compared with original omalizumab antibody . As to the findings of iCIEF method, the main peak of L0H0 decreased more obviously than those of other candidates during 28 days . With the reduction of the main peak, the acidic peak of all four samples increased sharply from about 10% up to about 35%, while the basic peak of AB1904Am13, AB1904Am15 and AB1904Am16 remained stable at approximately 10% and the basic peak of L0H0 went up to about 25% in the 7th day and then maintained at this level for two weeks before descending . On the basis of above results, both AB1904Am13 and AB1904Am15 were more stable than L0H0 at high temperature of 40°C.As indicated in Under the forced degradation condition of low pH (pH 5.0/40°C), the results analyzed by SEC-HPLC, nrCE-SDS and rCE-SDS demonstrated that both AB1904Am15 and L0H0 were extremely stable during 72 h . The prime mechanism of action of anti-IgE antibody was to inhibit the IgE-mediated various allergic symptoms by inhibition of IgE interacting with FcϵRI on basophils and mast cells. Therefore, AB1904Am15 and L0H0 were assessed for their ability to prevent IgE binding to FcϵRI in protein-based receptor binding inhibition assay and cell-based functional assay. AB1904Am15 showed elevated potency in blocking the interaction of IgE with FcϵRI protein  and dynamic lung compliance (Cdyn) were measured. As shown in L and in Cdyn compared with the isotype control group at 24 h post 1st and 3rd dosing. Because of variability among monkeys, the P value of AB1904Am15 vs. omalizumab was slightly higher than 0.05. However, the mean values of change in RL and Cdyn demonstrated that there was a sharp decline in change in RL and Cdyn of the AB1904Am15 group when compared with omalizumab group, indicating that AB1904Am15 was more potent than omalizumab.To verify the in vivo efficacy optimization, AB1904Am15 (with YTE mutation in Fc region) and its wild type antibody (without YTE mutation in Fc region), which had same Fab regions, were included, and their suppression of free IgE were evaluated in cynomolgus monkeys compared with L0H0 to probe if the improved in vivo efficacy was resulted from the engineered Fab regions or YTE mutation in Fc regions, or both , suggesting the YTE mutation also contributed to the improved efficacy. Collectively, the results demonstrated that the improved in vivo efficacy of AB1904Am15 was mediated by both engineered Fab regions and YTE mutation in Fc regions.To further elucidate the underlying mechanism of in vivo efficacy suggested that AB1904Am15 had better pharmacokinetic profiles and efficacy than omalizumab, and its enhanced in vivo efficacy was resulted from the engineered Fab regions and YTE mutation in Fc regions.In conclusion, the results of the pharmacokinetics and The discovery of IgE and the identification of its key role in the pathogenesis of allergic disease have laid the foundation for the development of therapeutic anti-IgE approaches. Omalizumab, a humanized monoclonal antibody, was the only approved anti-IgE antibody on the market for clinical use till now. Since there are some limitations associated with omalizumab –31, a loOver the last decades, several anti-IgE antibodies have been generated and assessed in pre-clinical studies or clinical trials , 42–44. Based on the lessons learned from the previous studies , 42–44, For stability, we removed two Asp isomerization hotspots in CDRs to improve its chemical stability. Meanwhile, we replaced several murine amino acids in the framework region of omalizumab with human source to reduce the potential risk of generating human anti-mouse antibody response. However, our assumption of minimizing the potential risk of immunogenicity was still needed to be verified by clinical trials in the future.For limitation of clinical application, the clinical dosing of omalizumab was based on the body weight and serum total IgE level. Individuals with high body weight (>150 kg) or with higher free IgE levels (>700 IU/ml) may be excluded from dosing table or require frequent injections or high dosage , 30. Thein vivo efficacy study demonstrated that AB1904Am15 was more potent than omalizumab. To our current knowledge, this is the first reported study showing the in vivo efficacy of anti-IgE antibody in cynomolgus monkey asthma model. To elucidate whether the improved in vivo efficacy was mediated by either the engineered Fab regions or YTE mutation in Fc regions, or both, the suppression of free IgE induced by AB1904Am15 (with YTE mutation in Fc region) and its wild type antibody (without YTE mutation in Fc region) was evaluated in cynomolgus monkeys compared with L0H0. The results indicated that both the engineered Fab regions and YTE mutation in Fc regions contributed to the enhanced in vivo efficacy of AB1904Am15. Enhanced in vitro biological activities and in vivo efficacy as well as prolonged serum half-life may bring about the following clinical benefits: lower volume of injection required, lower doses required to achieve clinical benefits, decreased frequency of drug administration.Moreover, AB1904Am15 showed higher affinity to IgE than L0H0, and demonstrated a correspondingly enhanced inhibition of IgE binding to FcϵRI and enhanced suppression of IgE induced histamine release in FcϵRI-expressing RBL-2H3 cells compared with L0H0. Previous studies have reported that superior IgE suppression may translate to better clinical outcomes , 42, 45.Previous studies have reported that omalizumab is effective in treating asthma patients with chronic obstructive pulmonary disease (COPD) overlap syndrome or with cardiovascular complications by decreasing coagulant proteins (D-Dimer) and proinflammatory cytokine levels , 51. In in vitro and in vivo, and prolonged serum half-life in comparison with omalizumab. Our preclinical studies suggested that AB1904Am15 might be a more potent anti-IgE monoclonal antibody for the treatment of allergic diseases in the future.In summary, an integrated antibody engineering approach was applied to generate AB1904Am15 (The original contributions presented in the study are included in the article/The animal study was reviewed and approved by the Institutional Animal Care and Use Committee.in vivo efficacy study. XL analyzed the sequencing data. CG carried out the affinity maturation. XC performed the in vitro activity evaluation. JZ performed the PK analysis. ZX assisted in the data analysis. PL carried out the biophysical analysis, stability study, processed the experimental data, drafted the manuscript, and designed the figures. All authors contributed to the article and approved the submitted version.SD designed and directed the project. DJ, HG, and XW provided technical guidance and reviewed the manuscript. ZP designed the PL, ZP, CG, XC, XL, JZ, ZX, XW, HG, and S-JD were employed by Shanghai Jemincare Pharmaceuticals Co., Ltd.The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.