Karenia mikimotoi cause devastation to marine life, including declines of fitness and population recruitment. However, little is known about the effects of them on benthic copepods. Here, we assessed the acute and chronic effects of K. mikimotoi on the marine benthic copepod Tigriopus japonicus. Results showed that adult females maintained high survival (>85%) throughout 14-d incubation, but time-dependent reduction of survival was detected in the highest K. mikimotoi concentration, and nauplii and copepodites were more vulnerable compared to adults. Ingestion of K. mikimotoi depressed the grazing of copepods but significantly induced the generation of reactive oxygen species (ROS), total antioxidant capacity, activities of antioxidant enzymes , and acetylcholinesterase. Under sublethal concentrations for two generations, K. mikimotoi reduced the fitness of copepods by prolonging development time and decreasing successful development rate, egg production, and the number of clutches. Our findings suggest that the bloom of K. mikimotoi may threaten copepod population recruitment, and its adverse effects are associated with oxidative stress.Blooms of the toxic dinoflagellate  Karenia mikimotoi is a worldwide HAB-forming species that has damaged the aquaculture industry and threatened ecosystems for decades [K. mikimotoi seems harmless to humans, since no shellfish poisons such as paralytic shellfish poisoning, diarrheic shellfish poisoning, or brevetoxin produced by other species of the genus Karenia have yet been identified [K. mikimotoi blooms are associated with massive fish or shellfish mortality, and this is commonly considered to be caused by haemolytic and cytotoxic effects [K. mikimotoi could generate reactive oxygen species, which is also speculated to be involved in K. mikimotoi-induced toxicity [K. mikimotoi on the antioxidant enzyme activity of algae, fish, and shellfish have been reported [K. mikimotoi remains elusive, multiple studies have shown that its toxicity relies on direct contact with intact algal cells [Harmful algal blooms (HABs) have become a global environmental issue in aquatic ecosystems with increasing frequency, intensity, and geographic distribution . High bi decades ,5,6. Unlentified ,6. Howev effects ,8,9,10. toxicity ,12,13, areported ,16,17,18reported ,16. Althal cells ,20 and cal cells ,11.K. mikimotoi may cause decline of fitness and population recruitment. Adverse effects include reduction of survival, feeding behavior and rate, motility, egg production, and egg-hatch success , originally isolated from the South China Sea, was provided by the Research Center for Red Tide and Marine Biology of Jinan University, Guangzhou, China. The nontoxic control Isochrysis galbana was obtained from the Algal Culture Center of the Institute of Oceanology, Chinese Academy of Sciences . Both algal strains were cultured in L1 seawater medium [−2·s−1. K. mikimotoi was maintained at 25.0 ± 1.0 °C under a 14/10 h light/dark regime, and I. galbana was maintained at 20.0 ± 1.0 °C under a 12/12 h light/dark regime. Copepods T. japonicus were originally collected in rocky intertidal pools on the coast of Qingdao, China and maintained at a temperature of 20.0 ± 1.0 °C, salinity 30.0 ± 1.0, under a 14/10 h light/dark regime, and fed with a mixture of Platymonas helgolandica (1.0 × 105 cells·mL−1) and I. galbana (2.0 × 105 cells·mL−1). All seawater used was taken from offshore Shazikou, Qingdao, China and filtered through a 0.45-μm polycarbonate membrane and sterilized.r medium  at a salT. japonicus. Copepods were fed on K. mikimotoi of the exponential phase at the concentrations (cell density) of 10,000, 20,000, 30,000, 40,000, and 50,000 cells·mL−1. The series of cell densities was chosen based on the abundance in natural blooms and the results of preliminary experiments in which differential survival rates were observed. I. galbana, with a concentration of 2.0 × 105 cells·mL−1, was used as control prey. Triplicate 100-mL glass beakers containing 10 adult females and 50 mL test solution were set up for each algal concentration and control. The copepods were incubated at 20 ± 1 °C under a 14/10 h light/dark photoperiod. Every 48 h, mortality was recorded, and the test solutions were renewed with fresh algal prey.A 14-day acute test was conducted using adult females 50 was determined by fitting to a sigmoidal dose–response curve.An acute test for nauplii and copepodites was conducted for 4 days. For each algal concentration and control, triplicates were set up. For each replicate, 25 nauplii or 15 copepodites were transferred to one well of a 6-well tissue culture plate. Each well contained 8 mL test solution. These nauplii and copepodites were raised under the same conditions mentioned above. Every 24 h, mortality was recorded and the test solutions renewed with fresh algal prey. Finally, 96-h LCK. mikimotoi are of particular concern.Previous studies indicate that feeding on toxic algae can alter the oxidative status in grazers and disturb their antioxidant system ,11. ThusT. japonicus with dual egg sacs were used for biochemical assays for each treatment and homogenized on ice in 100 μL 0.9% ice-cold sodium chloride solution.Following the 14-day acute test, biochemical assays were conducted in the surviving adult female copepods of each treatment and control. One hundred active adult females of g for 10 min at 4 °C and the supernatant was collected for reactive oxygen species (ROS) assays. The rest of the homogenate was centrifuged at 825× g for 10 min at 4 °C, and the supernatant was collected for biochemical assays of T-AOC, SOD, CAT, GPx, and AChE. ROS and enzyme activity were measured using detection kits following the manufacturer’s instructions . The level of ROS was indicated by the fluorescence of dichlorofluorescein (DCF), measured by F-4700 fluorescence spectrophotometer  with a 500 nm excitation wavelength and 525 nm emission wavelength. Micro Plate Reader Model ST-360  was used for measuring the enzyme activities and total protein concentrations. The ROS levels and enzyme activities were normalized to total protein concentration. Water-soluble protein concentration (μg·mL−1) was measured by the bicinchoninic acid assay (BCA), following the manufacturer’s instructions for microtiter assays . A standard curve was prepared using six bovine serum albumin (BSA) concentrations ranging from 50 to 2000 μg·mL−1.A portion of the homogenate was centrifuged at 10,000× K. mikimotoi: 100, 200, 400, 600, 800, 1.0 × 103, 2.0 × 103 cells·mL−1; I. galbana: 0.3 × 105, 0.7 × 105, 1.4 × 105, 2.1 × 105, 3.0 × 105, 3.7 × 105, 7.4 × 105 cells·mL−1). Incubation took place for 24 h under the conditions described above with beakers wrapped in foil. Prey concentrations were determined before and after incubation. Algal suspensions were preserved in 2% neutral Lugol’s solution and cell abundance was determined by counting cells per sample using Sedgewick Rafter counting slides.Prior to the experiment, mature and healthy adult females were randomly sorted and starved in sterilized filtered seawater for 24 h. Triplicate 100-mL glass beakers containing 10 adult females and 50 mL test solution with diets were set up for each algal concentration and control (F is clearance rate (mL·ind−1·h−1), which refers to the volume of ambient medium filtered by individual copepod per unit time; I is the ingestion rate (cells· ind−1·h−1), representing the number of algal cells filtered by individual copepod per unit time; V represents the volume of medium (mL); N is the number of copepods in each beaker; tC indicates the final prey concentration in the control beaker (×104 cells·mL−1); tfC represents the final prey concentration in the grazer beaker (×104 cells·mL−1); C0 represents the initial prey concentration (×104 cells·mL−1); and T is feeding time (h). Carbon-based rates were calculated using cell size and estimated carbon content per cell.Clearance and ingestion rates were determined following Frost (1972) :(1)F=VN×K. mikimotoi and I. galbana, respectively, was calculated according to the Menden-Deuer and Lessard equation [C represents the carbon content of individual cells (×10−6 µg·C·cell−1), and S represents the volume of individual cells (µm3·cell−1). Cell size, cell volume, and carbon content for each algal species were listed in The carbon content of equation .(3)C=0.Imax is the maximum ingestion rate, Km is the half-saturation constant, and C0 is the prey concentration. The functional response data were fitted to Holling Type III models as follows:I. galbana (2.0 × 105 cells·mL−1) as control and K. mikimotoi with sublethal concentrations of 500, 1000, 2000, and 4000 cells·mL−1. The culture conditions were the same as those described above. Larval/juvenile development and adult reproduction were investigated in a chronic test, in which copepods were fed on Newly hatched nauplii (<24 h after hatch) were transferred to 6-well tissue culture plates and each well contained 10 nauplii and 8 mL test solution. Test solution was renewed every 48 h, whereas the mortality, development stage, and development time (nauplii to copepodite and copepodite to adult) were monitored every day. Dead individuals were removed. Individuals that developed into copepodite were selected for further cultivation. These nauplii are reared under the above conditions until the adult female forms an egg sac. For the second generation (F2), 10 nauplii (F2) produced by an F1 female from each treatment or control were transferred to new 6-well plates and maintained under the same conditions. Triplicates for each treatment or control were set up. Survival, developmental time for the nauplius phase, and developmental time for the copepodite phase were recorded. T. japonicus with dual egg sacs were transferred to 6-well tissue culture plates, with each well containing one individual and 8 mL test solution. For each exposure concentration or control, six replicates were set up and maintained under the same conditions described above for 10 d. The total egg production in 10 days, individual egg production, and the number of clutches were recorded. To investigate adult reproduction, healthy and active adult females of 50, dose–response curves were fitted by sigmoidal algorithms using the mean values of each group (n = 6). One-way analysis of variance (ANOVA) and Fisher’s Least Significant Difference (LSD) test was used to evaluate the difference among groups. Prior to ANOVA, data were log-transformed to meet the assumption of normality and homogeneity of variance. Two-way ANOVA followed by Tukey’s test for post hoc multiple comparison was performed to test the difference among treatments and generations. Degrees of freedom (df) for each variable and the F ratio  were calculated. Correlation analysis was performed using Pearson’s test. In all tests, p < 0.05 was considered as significant. Data were plotted using Origin 2017.All measurements were carried out in triplicate, and the data are given as mean value ± standard deviation (SD). Statistical analysis was performed using IBM SPSS 21.0 . To calculate 96-LCT. japonicus was induced by K. mikimotoi during the first 4-d incubation, and the survival rates remained high (>85%) throughout the 14-d incubation at concentrations below 50,000 cells·mL−1, with no significant difference compared to control  was only detected at the highest algal concentration , and the survival rates decreased with time, reaching 6.67% at day 14. Due to the high tolerance of adult copepod to K. mikimotoi, we further assessed the acute effects of K. mikimotoi on nauplii and copepodite , whereas that for copepodite was about two-fold higher at 21,630 cells·mL−1 . No mortality of adult female pepodite . SurvivaK. mikimotoi and I. galbana was ca. 44 and 6207 cells per hour, respectively, with half-saturation prey concentration as 430.0 and 127,351.5 cells·mL−1. Clearance rate peaked at intermediate prey concentrations. Carbon-based functional responses showed that copepod ingested non-toxic I. galbana at a significantly higher rate (p < 0.01), whereas copepod had a higher clearance rate on K. mikimotoi, which peaked at higher prey concentrations (278 μg C·L−1) in comparison with that of control prey I. galbana. Concentration-dependent grazing was found on both toxic and non-toxic prey, resembling a typical Holling Type III functional response . The max−1K. mikimotoi. The T-AOC increased by a factor of 2.2~2.5 in all treatments , but the level fluctuated across concentrations  detected in the copepods fed with 40,000 cells·mLeatments b and wastrations . SOD andectively c,e. The trations d. In therameters . −1 to 4000 cells·mL−1. Development time and survival were investigated for two consecutive generations. Exposure to K. mikimotoi significantly delayed the development of both nauplii and copepodites in F1 but did not significantly affect the survival rate except for the highest concentration (4000 cells·mL−1), at which the survival rate decreased to 85% and 80% for nauplii and copepodites, respectively (K. mikimotoi on development was more pronounced in F2. An average of 25.9% of nauplii developed into copepodites in a longer time (8 days) compared to control (5 days), and the development time for copepodite to adult increased by a factor of 2.2–2.5. The survival rate of copepodite decreased to 70–80% at concentrations below 4000 cells·mL−1, whereas at 4000 cells·mL−1, no copepodite successfully grew up into a adult . Two-way ANOVA , and there was a significant interaction between treatment and generation, except for the developmental time of the nauplius stage (p < 0.01).A chronic test was conducted at lower exposure concentrations ranging from 500 cells·mLectively . The advay ANOVA  further K. mikimotoi (K. mikimoti concentration (4000 cells·mL−1). The number of clutches reduced to 46.5–65.1% of the control. No data were available for F2 egg production due to the extremely low number of successfully developed adult females in F2. In addition, deformed and/or detached egg sacs with extremely low egg production were observed in T. japonicus exposed to highest K. mikimotoi concentration.Remarkably, egg production and the number of clutches for F1 were strongly depressed under all tested concentrations of ikimotoi , Table 6K. mikimotoi has been documented in many marine organisms, such as fish, shellfish, rotifers, and crustaceans, with copepods being one of the less sensitive lineages [K. mikimotoi varies among species, and the benthic harpacticoid copepod T. japonicus tested in this study seems more tolerant to K. mikimoti than the pelagic calanoid copepods [T. japonicus within 96 h at all tested concentrations of K. mikimotoi, ranging from 10,000 to 50,000 cells·mL−1, and they retained a high survival rate (>90%) during 14-d incubation at concentrations <50,000 cells·mL−1  and Calanus sinicus  fed with less or comparable concentrations of K. mikimotoi [K. mikimotoi is target-species-specific and algal-strain-specific [T. japonicus exposed to various environmental stressors [The lethal effect of lineages ,32. Withcopepods ,29,31,32lls·mL−1 a. Contraspecific , which cspecific ,41,42. Htressors ,44,45. TT. japonicus were more vulnerable compared to adults . Although a neurotoxin has not been identified in K. mikimotoi, they produced brevetoxin-like polyethers [K. mikimotoi neurotoxicity in zebrafish larvae and found an association between AChE, SOD, and CAT activity and the differential expression of neurodevelopment genes. Whether K. mikimotoi exerts neurotoxicity in copepods needs further experimental validation. However, given the remarkable diversity of AChE functions [Interestingly, a strongly positive correlation was also found between AChE and all oxidative-status-related variables (ROS level and antioxidant activity). We found that with the increase of decrease . Activatlyethers ,10,62,63lyethers . Niu et lyethers  investigunctions , the altunctions .K. mikimotoi in copepods has not been covered in previous studies [K. mikimotoi at concentrations < 4000 cells·mL−1 could support both nauplii and copepodites of T. japonicus to complete their development with high survival, the development time of both stages were significantly prolonged under all tested concentrations , and the inhibitory impact of K. mikimotoi on development increased in F2, indicating the potential accumulation effect with generations. Remarkably, 70% of F2 nauplii exposed to 4000 cells·mL−1K. mikimotoi successfully developed to copepodite, none of which could survive to adult stage. This suggests that copepodite could be more vulnerable under continuous exposure, in accordance with the results of chronic test in T. japonicus exposed to the biocide triphenyltin [50 for nauplii being about half of that for copepodite. Such inconsistency may be due to the cumulative damage from repeated or long-term continual exposure, which could ultimately produce more severe effects in the late juvenile stage.It has been commonly found that toxic algae and their toxins exert adverse effects on the development and reproduction of copepods, but multigeneration toxicity of  studies ,30,31. Wtrations . In agreerations . Survivahenyltin . ContrasK. mikimotoi significantly reduced the egg production and number of clutches in T. japonicus, which is in concert with previous reports in the calanoid copepods A. omorii, C. helgolandicus, C. sinicus, P. marinus, and T. longicornis [K. mikimotoi [Nodularia spumigena and Colichlodinium polykrikoides may be beneficial to copepod reproduction and development [K. mikimotoi suppressed the reproduction of T. japonicus, even at the lowest tested concentration (500 cells·mL−1). Copepods exposed to toxic algae for a long period may lack enough energy and nutrients to complete their development and reproduction, due to the high maintenance cost for detoxification [K. mikimotoi [T. japonicus can protect eggs from external environmental disturbances, the detrimental effect of K. mikimotoi on the reproduction of benthic copepods is comparable to that on pelagic copepods. Moreover, the number of successfully developed adult females in F2 was too low to conduct subsequent evaluation on egg production, which indicates that K. mikimotoi may also affect the sex determination of copepods. Sex determination in copepods is under strong environmental control [K. mikimotoi in both parents and offspring may have disturbed the sex determination in F2, and the decreased number of adult females was also observed in F2 T. japonicus exposed to biocide [T. japonicus collectively demonstrate that population recruitment of copepods could be adversely affected by K. mikimotoi, particularly in long-lasting blooms.We further found that the exposure to gicornis ,30,31. Aikimotoi , and dueikimotoi , low conelopment ,75, our fication ,76. The ikimotoi ,31, and ikimotoi . Althougikimotoi  argued t control , such as control , food qu control , and tox control . In our  biocide . The proT. japonicus showed high tolerance to toxic dinoflagellate K. mikimotoi with significant reduction of survival only detected at the highest algal concentration. But nauplii and copepodites were more vulnerable compared to adults, and survival rate decreased with time and concentrations. Exposure to K. mikimotoi depressed the grazing of copepods but significantly elevated oxidative stress and the level of AChE. Strong positive correlations among biochemical parameters highlighted the cooperation in the antioxidant defense system of T. japonicus to counteract K. mikimotoi, and oxidative stress may be associated with other physiological stress induced by K. mikimotoi. Moreover, K. mikimotoi exerted detrimental effects on development and reproduction in T. japonicus. Our findings suggest that the bloom of K. mikimotoi may threaten copepod population recruitment, and its adverse effects are associated with oxidative stress.Adult


The criteria for PD‐MCI allow the use of global cognitive tests. Their predictive value for conversion from PD‐MCI to PDD, especially compared to comprehensive neuropsychological assessment, is unknown.The MDS PD‐MCI Study Group combined four datasets containing global cognitive tests as well as a comprehensive neuropsychological assessment to define PD‐MCI (n = 467). Risk for developing PDD was examined using a Cox model. Global cognitive tests were compared to neuropsychological test batteries (Level I&II) in determining risk for PDD.P = 0.001; HR = 4.14, P = <0.001). The C‐statistics for MMSE (0.72) and MoCA (0.70) were lower than those based on neuropsychological tests . Sensitivity, specificity and diagnostic accuracy balance was best in Level II.PD‐MCI based on a global cognitive test (MMSE or MoCA) increases the hazard for developing PDD (respectively HR = 2.57, MMSE and MoCA predict conversion to PDD. However, Level II neuropsychological assessment seems the preferred assessment for PD‐MCI. The MDS PD Mild Cognitive Impairment (PD‐MCI) diagnostic criteriaPrior analyses using Level I‐NPA and Level II methods showed that PD‐MCI diagnosed in these ways increases the hazard of PDD and aids in the prediction of PDD (Level I‐NPA Hazard Ratio (HR) 2.02–11.25; Level II HR 2.69–14.10: depending on cut‐off used).This study is based on data from the MDS Study Group Mild Cognitive Impairment in Parkinson's Disease.This retrospective study combined four datasets containing global cognitive tests and additional data suitable for both Level I and Level II PD‐MCI assessment based on neuropsychological tests. Individual studies were included if they allowed Level II PD‐MCI assessment , either one test per cognitive domain (Level I‐NPA) or two tests per cognitive domain (Level II) were used. PD‐MCI based on the NPA was defined as scores −1.5SD below the normative data for at least two tests (respectively out of five or ten).Multiple imputation (MI) was used to account for incomplete data. Cox proportional hazards models were used to evaluate whether Level I‐CGT PD‐MCI at baseline compared to no PD‐MCI adds to the risk of PDD as estimated by age, gender, level of education, disease duration, UPDRS‐III, and depression. Time was measured from PD symptom onset until PDD or censoring.To compare various operationalizations of the criteria, C‐statistics (bootstrap‐corrected) which indicate discriminative ability between models as a measure of goodness‐of‐fit were calculated. PDD risk factors, like time since symptom onset, were taken into consideration. Two patients who develop PDD can be ordered by their time to event (PDD). If the model rightly predicts a shorter time to PDD for the one who developed PDD first, the C‐statistic increases. Two patients, one of which develops PDD, can be ordered as well. If the model rightly predicts a shorter time to PDD for the one who developed PDD, the C statistic also increases.In addition, at baseline we determined sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and diagnostic accuracy (DA) for PDD. This was done for Level I‐CGT as well as for Level I‐NPA and Level II PD‐MCI assessment.A total of 467 patients were included Table . Sixty‐nMMSE scores were available in all four datasets; MoCA scores were available in three datasets. A total of 172 out of 467 (36.8%) patients fulfilled the criteria for PD‐MCI based on the MMSE. A total of 111 out of 365 (30.4%) patients fulfilled the criteria for PD‐MCI based on the MoCA. Applying Level II resulted in 120/467 PD‐MCI patients (25.7%), while level I‐NPA based on 5 tests resulted in 46/467 PD‐MCI patients (9.9%). Compared to Level I NPA, both Level II and Level I‐GCT identified more PD‐MCI cases.The Cox proportional hazards models indicated a significant contribution of PD‐MCI as defined by MMSE and MoCA cutoff scores to the hazard of PDD  than did the neuropsychological assessment . Global cognitive tests seemed to identify PD‐MCI cases who do not develop PDD, possibly “false positive,” leading to lower C‐statistics as well as a lower balance in sensitivity and specificity. On the other hand, Level I‐NPA seems to be too limited and strict, as scores on 2 out of 5 tests need to be below the cut‐off, and therefore may miss patients who actually have PD‐MCI.Overall we determined the sensitivity, specificity and DA in the same patients. For the MMSE these values are sufficient but limited, which corresponds with Hoops et al. (2009).Strengths of our study include the use of a large multicenter, international sample, uniform application of the MDS PD‐MCI criteria, and direct comparison of the different prevailing operationalizations of PD‐MCI. Furthermore, while the relation between PD‐MCI, demographic and clinical characteristics, and PDD has been reported separately in previous studies,In conclusion, PD‐MCI assessed by global cognitive tests increases the hazard ratio for the development of PDD after taking age, sex, education, PD motor symptom severity, and depression into account. This finding supports PD‐MCI being a risk factor for PDD. PD‐MCI assessed by neuropsychological assessment (both Level I and Level II) had higher predictive value over PD‐MCI assessed by MMSE or MoCA. Given better balance of sensitivity and specificity and Diagnostic Accuracy compared to the use of global cognitive tests and Level I neuropsychological assessment, Level II neuropsychological assessment seems the optimal method for detecting PD‐MCI.(1) Research project: A. Conception, B. Organization, C. Execution; (2) Statistical Analysis: A. Design, B. Execution, C. Review and Critique; (3) Manuscript: A. Writing of the first draft, B. Review and Critique.JAB: 1A, 1B, 1C, 2A, 2B, 2C, 2A, 2B, 2C.RMAB: 1A, 3A, 3B.BAS: 1A, 1B, 2C, 3A, 3B.JDA: 1A, 1B, 3B.CM: 1A, 3B.CHA: 1A, 3B.JGG: 1A, 3B.AIT: 1A, 3B.DJB: 1A, 3B.IL: 1A, 3B.GJG: 1A, 1B, 1C, 2A, 2C, 3A, 3B.Ethical Compliance Statement: The Medical Ethics Committee of the University of Amsterdam stated that the approval of an institutional review board was not required for this work (reference number W12_3–1 # 13.17.0003). Each study site obtained informed consent obtained. We confirm that we have read the Journal's position on issues involved in ethical publication and affirm that this work is consistent with those guidelines.Funding Sources and Conflicts of Interest: Funding was received from the Michael J. Fox Foundation. The authors have no conflicts of Interest for this study.Financial Disclosures for the Previous 12 Months: Judith A. Boel, Rob M.A. de Bie, Ben A. Schmand, Jennifer G. Goldman, Alexander I. Tröster, David J. Burn, and Gert J. Geurtsen have no disclosures to report. John C. Dalrymple‐Alford, None, only grants from Tertiary Education Commission, New Zealand, Health Research Council of New Zealand, Canterbury Medical Research Foundation and Neurological Foundation of New Zealand. Connie Marras is a consultant for Gray Matter Technologies and receives financial compensation as a steering committee member from the Michael J Fox Foundation. She received grants from The Michael J Fox Foundation, Canadian Institutes of Health Research, Parkinson's Foundation (US), International Parkinson and Movement Disorders Society, Weston Brain Institute, Theravance Inc, Centogene. Charles H. Adler has Stock Ownership in medically‐related fields: Cionic; Consultancies: Avion, CND Life Science, Jazz Pharm, Neurocrine; Grants: NIH, Michael J. Fox Foundation, Arizona Biomedical Research Commission. Irene Litvan's research is supported by the National Institutes of Health grants: 2R01AG038791‐06A, U01NS100610, U01NS80818, R25NS098999; U19 AG063911‐1 and 1R21NS114764‐01A1; the Michael J Fox Foundation, Parkinson Foundation, Lewy Body Association, CurePSP, Roche, Abbvie, Biogen, Centogene. EIP‐Pharma, Biohaven Pharmaceuticals, Novartis, Brain Neurotherapy Bio and United Biopharma SRL—UCB. She was a member of the Scientific Advisory Board of Lundbeck and is a Scientific advisor for Amydis. She receives her salary from the University of California San Diego and as Chief Editor of Frontiers in Neurology.Supplementary Figure S1. Flowchart showing the data inclusion processSupplementary Table S1. Cohort details of the included studies.Supplementary Table S2. Hazard ratios of models containing MMSE and MoCA.Click here for additional data file.Supplementary Text S1. Members of the International Parkinson and Movement Disorders Society Mild Cognitive Impairment (MCI) Study Group.Click here for additional data file.


The method’s selectivity, precision (coefficient of variation of intra-day and inter-day ≤ 6.1%), accuracy (95.8–105.2%), matrix effect (92.3–106.0%), extraction recovery, and stability results were acceptable according to the guidelines. The linear ranges were 5–500 ng·mL−1, 2–500 ng·mL−1, and 0.5–200 ng·mL−1 for osimertinib, aumolertinib, and furmonertinib, respectively. The results show that the method was sensitive, reliable, and simple and that it could be successfully applied to simultaneously determine the osimertinib, aumolertinib, and furmonertinib blood concentrations in patients. These findings support using the method for TDM, potentially reducing the incidence of dosing blindness and adverse effects due to empirical dosing and inter-patient differences.The third-generation epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs), osimertinib, aumolertinib, and furmonertinib represent a new treatment option for patients with EGFR p.Thr790 Met (T790 M)-mutated non-small cell lung cancer (NSCLC). Currently, there are no studies reporting the simultaneous quantification of these three drugs. A simple ultra-performance liquid chromatography–tandem mass spectrometry (UPLC-MS/MS) method was developed and validated for the simultaneous quantitative determination of osimertinib, aumolertinib, and furmonertinib concentrations in human plasma, and it was applied for therapeutic drug monitoring (TDM). Plasma samples were processed using the protein precipitation method (acetonitrile). A positive ion monitoring mode was used for detecting analytes. D Lung cancer, which is classified broadly as non-small cell lung cancer (NSCLC) or small cell lung cancer (SCLC), is the primary cause of cancer death worldwide and remains a major challenge . NSCLC iOsimertinib , is a stTherapeutic drug monitoring (TDM) is an important technique for formulating dosing regimens for drugs with strong toxic effects, and great individual differences measured by drug concentrations in biological samples can identify inter-patient differences and improve the therapeutic effects of drugs while reducing AEs ,23,24. SWe developed a rapid, sensitive, and efficient UPLC-MS/MS method to simultaneously determine osimertinib, aumolertinib, and furmonertinib concentrations in human plasma. A protein precipitation method was used for sample pretreatment, and gradient elution was used to separate the analytes, which effectively reduced the measurement time and improved the detection efficiency for the target drugs. A quantitative analysis of patient plasma samples was performed to provide a basis for rational clinical drug use.+ was used as the parent ion for analytes because it had the best response. The target ion transitions obtained after the screening of osimertinib, aumolertinib, furmonertinib, and IS were as follows: 500.1→72.2, 526.1→72.2, 569.1→72.1, and 468.2→255.4  was added to the organic phase to obtain distinct symmetric peaks and minimal background noise, and the final choice was acetonitrile (containing 0.1% formic acid) and water. The optimization of the mass spectrometry conditions revealed a higher response for the analytes in the positive ion mode. [M + H].2→255.4 . Other M3-sorafenib was selected as the internal standard (IS) in this study. No significant matrix effects were observed at the retention times of the analytes. Compared to liquid–liquid extraction and solid-phase extraction, the protein precipitation method has the advantages of simplicity, speed, low cost, and reduced environmental pollution and is more suitable for TDM. Therefore, acetonitrile was selected as the protein precipitant in this study.Isotope-labeled internal standards are most commonly used in tandem mass spectrometry to eliminate errors due to matrix interference and differential ionization properties of the analytes. In previous studies ,30, the The retention times for osimertinib, aumolertinib, furmonertinib, and IS were 1.29 min, 1.72 min, 1.80 min, and 2.34 min, respectively. At the retention times of the analytes and the IS, endogenous substances in the plasma did not interfere with the detection of each analyte, demonstrating the good selectivity and specificity of the method .−1, respectively. The corresponding calibration curve equations for the three analytes were: y = 0.0454 x − 0.00374 (r = 0.9995), y = 0.0935 x − 0.00211 (r = 0.9978), and y = 0.0868 x + 0.0129 (r = 0.9994), respectively. Each calibration curve showed good linearity over its respective concentration range. The lower limit of quantitation (LLOQ) concentrations for osimertinib, aumolertinib, and furmonertinib were 5 ng·mL−1, 2 ng·mL−1, and 0.5 ng·mL−1, respectively. Six consecutive LLOQ samples for each analyte were analyzed with the required precision and accuracy.The concentration ranges tested for osimertinib, aumolertinib, and furmonertinib were as follows: 5–500 ng·mL−1, 2–500 ng·mL−1, and 0.5–200 ng·mLThe intra-day precision, inter-day precision, and accuracy of the quality control (QC) samples and LLOQ samples for all analytes met the requirements, and the results are within acceptable limits, as shown in The validation results for the matrix effect and extraction recovery for each compound are shown in The stability of each analyte was examined under various storage conditions using QC plasma samples for osimertinib, aumolertinib, and furmonertinib. The results indicate the acceptable stability of the QC samples for all analytes under the storage conditions tested .The carry-over effect was assessed by analyzing a blank matrix sample after an upper limit of quantification (ULOQ) sample had been injected. At the retention time of the analyte, the peak areas of interfering peaks in the blank matrix sample were less than 20% of that of the LLOQ sample. Furthermore, there were no significant interfering peaks at the retention time of the IS, indicating that the high concentration sample had no carry-over effect on the determination of the low concentration sample.The validated method was successfully used in our laboratory to measure the plasma drug concentration at steady states of osimertinib (n = 10) and aumolertinib (n = 2) in patients with NSCLC .min) of osimertinib at a steady state were highly variable (6.19–380 ng/mL), and the mean Cmin was 139.98 ng/mL at the steady state. Compared to the methods previously reported, our newly developed method was more simple and convenient.Consistent with previous publications ,31, the min of aumolertinib and furmonertinib in patients with NSCLC. Phase I clinical trial data show that steady-state Cmin is 193 ng/mL after the administration of 110 mg of aumolertinib, and 29.1 ng/mL after the administration of 80 mg of furmonertinib [min of aumolertinib was 155.5 ng/mL, which is consistent with the published clinical trial data.There are limited data on the CBrown et al.  did not 3-Sorafenib , was also purchased from Shanghai Zhenzhun Biotechnology Co., Ltd. . HPLC-grade acetonitrile and formic acid were obtained from Fisher Scientific . Ultrapure water was acquired from Wahaha Group Co., Ltd. .Standard reference samples of osimertinib , aumolertinib , furmonertinib  were purchased from Shanghai Zhenzhun Biotechnology Co., Ltd. . IS, dXP, 2.1 mm × 100 mm, 2.5 µm, Waters, Milford, MA, USA) at 40 °C. The mobile phase consisted of water (A) and acetonitrile . The elution procedure was carried out in the following order: 0–0.5 min, 30% B; 0.5–1.5 min, 30%→90% B; 1.5–3.5 min, 90% B; 3.5–3.6 min, 90%→30% B; 3.6–4.1 min, 30% B. The flow rate was 0.5 mL·min−1, and the injection volume was 8 μL.Chromatographic separation was performed using an ultra-high performance liquid chromatography system . Chromatographic separation was achieved by gradient elution on a C18 analytical column (XSelect HSS m/z 500.1→ 72.2(quantifier transition) and 500.1→455.3  for osimertinib, m/z 526.1→72.2 (quantifier transition) and 526.1→453.2  for aumolertinib, m/z 569.1→72.1 (quantifier transition) and 569.1→441.2  for furmonertinib, m/z 468.2→255.4 (quantifier transition) and 468.2→273.1  for IS (Mass spectrometry was performed using an AB Sciex Triple Quad 4500 tandem triple quadrupole mass spectrometer equipped with an electrospray ionization source (ESI) interface. The positive ion mode with multi-reaction detection was used, and the multiple reaction monitoring transitions of the analytes were as follows: ) for IS . Other p−1. The appropriate volume of the standard stock solution was diluted with 50% acetonitrile into working solutions with concentrations of 50, 100, 500, 1000, 2000, 3000, and 5000 ng·mL−1 (osimertinib), 20, 50, 100, 500, 1000, 2000, 3000, and 5000 ng·mL−1 (aumolertinib), and 5, 10, 50, 200, 400, 800, 1000, and 2000 ng·mL−1 (furmonertinib). The same method was used to prepare QC working solutions with concentrations of 150, 1500, and 3750 ng·mL−1 (osimertinib), 60, 1500, and 3750 ng·mL−1 (aumolertinib), and 15, 500, and 1500 ng·mL−1 (furmonertinib). The IS was also dissolved in DMSO to obtain a stock solution at a concentration of 1 mg·mL−1. The IS stock solution was diluted with 50% acetonitrile to obtain a working solution at 500 ng·mL−1. All stock solutions and working solutions were stored at −20 °C.The osimertinib, aumolertinib, and furmonertinib standards were precisely weighed and dissolved in dimethyl sulfoxide solution (DMSO) to make standard stock solutions with final concentrations of 1 mg·mL−1) were added to 100 μL of plasma sample ). Then, 300 μL of acetonitrile were added, vortexed for 1 min, and centrifuged at 12,000 rpm for 10 min. The supernatant (100 µL) was added to 300 μL of 50% acetonitrile, vortexed and mixed, and finally transferred to an autosampler vial for sample analysis.Plasma samples were processed using the protein precipitation method. Ten microliters of IS  to blank plasma from different sources (n = 6). The samples were processed as described in The method’s selectivity was determined by assessing the interference of other components in plasma. Plasma samples containing 2 ng·mLx), the peak area ratio of the analyte to the IS as the vertical coordinate (y), and 1/2x as the weighting factor, a weighted least squares method was used to obtain the regression equation and generate the calibration curve. The linear ranges of the standard curves for osimertinib, aumolertinib, and furmonertinib were 5–500 ng·mL−1, 2–500 ng·mL−1, and 0.5–200 ng·mL−1, respectively. The difference between the back-calculated and the nominal concentrations for each standard in the calibration curve had an acceptable range (<15%). For LLOQ, the difference should be less than 20%.Using the concentration of the analyte as the horizontal coordinate  samples and LLOQ samples. Intra-day and inter-day precision and accuracy were calculated by repeating the measurements six times a day for three consecutive days for samples at each concentration level. Precision was expressed by calculating the relative standard deviation (RSD) of the samples from six parallel measurements. Accuracy was expressed by the relative error (RE) of the samples. The RSD and RE were within ±15% for the QC samples and within ±20% for the LLOQ samples.The matrix effect for the analyte was determined by comparing the analyte peak area in the blank plasma samples from six different donors at LQC and HQC levels (n = 6 for each level) with the analyte peak area in pure solution. The extraction recovery was assessed by comparing the analyte peak area in extracted plasma samples at LQC, MQC, and HQC levels (n = 6 for each level), with the analyte peak area of a blank plasma extract spiked at the same level.The stability of the samples under different storage or handling conditions was assessed by analyzing the QC samples at different levels . The short-term stability was assessed after placing the plasma samples at room temperature for 8 h. Quality control samples were stored at −20 °C for 7 d to assess the long-term stability. We also examined the stability of the samples stored in a refrigerator at 4 °C for 24 h. The stability of the processed samples was assessed by storing the samples in an autosampler at 4 °C for 24 h. The samples stored at −20 °C were thawed at room temperature, and three freeze–thaw cycles were performed to investigate the freeze–thaw stability of the samples.The carry-over of this method was investigated by sequentially injecting the LLOQ and the ULOQ samples, followed by a blank biological matrix sample. The area of interfering peaks at the retention time of the analyte in the blank plasma sample should be less than 20% of the LLOQ and 5% of the IS peak areas.All the experimental procedures were approved by the Ethics Committee of Hebei General Hospital (No. 2022094).Plasma samples from patients who had been administered osimertinib, aumolertinib, or furmonertinib for at least two weeks and were within half an hour before re-administration were analyzed to demonstrate the applicability of the assay. The clinical blood samples were residual blood samples obtained from patients for other routine clinical measurements at Hebei General Hospital. Blood was collected in EDTA-containing anticoagulation tubes, and the supernatant was separated by centrifugation at 3000 rpm for 10 min at 4 °C. Then, the supernatant was transferred to 1.5 mL EP tubes and stored at −20 °C until analysis.We have developed a simple, rapid, and sensitive UPLC/MS/MS method to simultaneously determine osimertinib, aumolertinib, and furmonertinib concentrations in human plasma. The validated method may also be a useful tool for the TDM of the third-generation EGFR-TKIs for NSCLC patients in clinical practice.


The results showed that when wheat, maize, cassava, mung bean and sweet potato amylopectins were mixed with ASG, the disulfide bond contents of alkali-soluble glutenin increased from 0.04 to 0.31, 0.24, 0.08, 0.18 and 0.29 μmol/g, respectively. However, after cold storage, they changed to 0.55, 0.16, 0.26, 0.07 and 0.19 μmol/g, respectively. The addition of wheat amylopectin promoted the most significant disulfide bond formation of ASG. Hydroxyproline only existed in the wheat amylopectin, indicating that it had an important effect on the disulfide bond formation of ASG. Glutathione disulfides were present, as mung bean and sweet potato amylopectin were mixed with ASG, and they were reduced during cold storage. Positive/negative correlations between the peak intensity of the angles at 2θ = 20°/23° and the disulfide bond contents of ASG existed. The high content of hydroxyproline could be used as a marker for breeding high-quality wheat.Wheat, maize, cassava, mung bean and sweet potato starches have often been added to dough systems to improve their hardness. However, inconsistent effects of these starches on the dough quality have been reported, especially in refrigerated dough. The disulfide bond contents of alkali-soluble glutenin (ASG) have direct effects on the hardness of dough. In this paper, the disulfide bond contents of ASG were determined. ASG was mixed and retrograded with five kinds of amylopectins from the above-mentioned botanical sources, and a possible pathway of disulfide bond formation in ASGs by amylopectin addition was proposed through molecular weight, chain length distribution, FT-IR,  It can increase the viscoelasticity of cooked wheat-based food at a low cost in the food industry . Accordi07 g/mol . Further07 g/mol . Regardi07 g/mol . Further07 g/mol  showed tChen et al. 2021) reported that higher temperatures increased sulfhydryl–disulfide bond (SH-SS) interchange to promote the aggregation of gluten 021 repor, thus pr13C solid-state NMR, IR and X-ray diffraction analyses.In this paper, the effects of mixing different amylopectins from wheat, maize, mung bean, tapioca and sweet potato starches with alkali-soluble glutenin on disulfide bond formation before and after retrogradation were investigated. The objective of the present study was to determine which amylopectin promotes the most significant glutenin disulfide bond formation and to deduce the possible interaction mechanism by comparing the results of molecular weight, chain length distribution, Wheat and maize starches were purchased from He Nan Enmiao Food Co., Ltd.  sweet potato starch was purchased from the Beijing Gusong Economic and Trade Company , mung bean starch was purchased from Hengshui Fuqiao Starch Co., Ltd.  and cassava starch was purchased from Guangxi Napoheshan Starch Co., Ltd. . Bacillus subtilis thermostable and mid-temperature α-amylase (12000 U/mL), microbial lipase  and neutral protease  were all produced by Beijing Solarbio Science & Technology Co. Ltd. . Sodium hydroxide, sodium chloride and hydrochloric acid were obtained from Tianjin Fengchuan Chemical Reagents Co., Ltd. . Sodium chloride  was purchased from Tianjin Hengxing Chemical Reagent Manufacturing Co., Ltd. . Pullulanase  was obtained from Beijing Solarbio Science & Technology Co., Ltd. The dialysis bags , MWCO 14,000 Da) were produced by the Union Carbide Corporation . Tris, glycine, disodium EDTA, urea, guanidine hydrochloride and DTNB reagents were all obtained from Beijing Soleibo Science & Technology Co. Ltd. The P120H Ultrasonic Cleaner was produced by Elma Schmidbauer GmbH in Germany.g for 3 min) to obtain the precipitates. Those precipitates were dissolved in 1% sodium chloride solution under constant stirring for 10 min to dissolve the amylose, and the precipitation (crude amylopectin) was obtained by centrifugation (4000× g for 5 min), and the supernatant fraction was discarded. Crude amylopectin (21~26 g) was isolated by repeated dissolution in 1% NaCl solution and centrifuged several times, as mentioned above, until no blue color appeared in the precipitation–iodine complex.Crude amylopectin was produced according to basic principle in the literature ,14, acco−1 NaOH. Finally, both the lipase and alkali proteases were inactivated by boiling for 10 min. The solutions were centrifuged (4000× g for 10 min) to obtain the precipitates. The purified amylopectins  were prepared by washing the precipitates using deionized water several times until there was no turbidity when a drop in AgNO3 was added. The amylopectins for the IR, 13C solid-state NMR and X-ray diffraction analyses were obtained after the samples had been dried at 60 °C in an oven to obtain a constant weight.In order to completely remove a small amount of co-extracted or associated compounds, such as protein or lipid, from the crude amylopectins, the crude amylopectins were hydrolyzed by lipase and alkali protease in sequence, according to . After bg for 10 min. Again, the gliadin in the precipitate was extracted by above-mentioned method several times until no viscous gliadin was clearly present. Finally, the glutenin, at the weight of 114 g (wet weight)/49 g (dry weight), was obtained by centrifugation. Approximately 20 g of wet glutenin (8.5 g dry weight) was added to 200 mL of 0.1% NaOH and stirred to extract the ASG for 120 min at room temperature. Then, the solution was centrifugated at 4000× g for 5 min to remove the alkali-insoluble glutenin. The above-mentioned supernatant was gently placed in beaker to obtain coagulation precipitates at 50 °C for 12 h. The coagulation precipitation was isolated by centrifugation at 4000× g for 5 min. This precipitation was dialyzed to remove the sodium and hydroxide ions, and 21.5 g wet/2.2 g dry weight of ASG was obtained.Glutenin was separated from gluten using a reference method, with certain modification . Further13C solid-state NMR and X-ray diffraction were dried to a constant weight at 60 °C in an oven.The wheat, maize, potato, mung bean and cassava starches, at a wet weight of 1g, corresponding to dry weights of 0.090, 0.062, 0.075, 0.205 and 0.135 g, respectively, were mixed with ASG at a wet weight of 0.3 g (0.03g dry weight). The mixtures were stirred with a small bamboo skewer at 37 °C for 2 h. The wet mixtures were used to determine the contents of disulfide bonds, and the samples for IR, 3C solid-state 1NMR and X-ray diffraction were dried to a constant weight at 60 °C in an oven.The wet mixtures mentioned in The disulfide bond contents were determined according to the method described by Zhu et al. 2019) , with so , with s1) contents:Determining the free sulfhydryl group (SHg) for 10 min, and the supernatants were collected to determine the absorbance at 412 nm.The wet samples described in 2) contents:Determining the total sulfhydryl group (SHg) for 10 min, and the supernatants were gathered to determine the absorbance at 412 nm.The wet samples described in 1 and SH2 contents of each sample were calculated as shown in Formula 1, and the disulfide bond contents were calculated as shown in Formula (2):412 is the absorbance at 412 nm, D is the dilution factor, C is the sample concentration (mg/mL) and 73.53 is derived from 106/1.36 × 104, where 1.36 × 104 is the molar extinction coefficient.The SH®® HMW 6E DMF 250 and 1000, 7.8 mm × 300 mm, Waters, Milford, MA, USA) at 45 °C. Dimethyl sulfoxide (DMSO) with 50 mM NaNO3 was used as the mobile phase at a flow rate of 0.6 mL/min. The MALLS detector was calibrated by Dextran standards (T40 and T2000). Astra software  was used to handle the data in order to determine the molecular characteristics of the molecular weight.The molecular weight distribution of the five amylopectins was determined by high-performance size-exclusion chromatography (HPSEC) using a multi-angle laser light-scattering detector  and a refractive-index detector  . A totalg. The above-mentioned solutions were injected into the HPAEC-PAD system  after being filtered through a 0.5 μm membrane filter. Data were collected and managed using Chromeleon software .High-performance anion-exchange chromatography with pulsed amperometric detection (HPAEC-PAD) was used to determine the chain length distribution of the five amylopectins . The amyw/w) at the rate of 1:60 (w/w). The mixtures were pressed into sheets using a tablet press. Then, Fourier-transform infrared spectroscopy  was used to obtain the data in the transmission mode at 27 °C.KBr (spectroscopic grade) was dried at 120 °C for 2h and kept in the dryer after being cooled to room temperature. Then, every sample was blended with KBr  in the IR spectra, were calculated according to [−1, β-sheets at 1625–1642 cm−1, α-helices at 1650–1660 cm−1, β-turns at 1670–1680 cm−1 and antiparallel β-sheets at 1680–1695 cm−1. The content of each secondary structure of ASG was obtained by processing Csv-format infrared data with the Peakfit software.The secondary structures of glutenin in the samples, characterized by the amide I band  was from 3° to 60°, and the step size was 0.02°. The counting time was 0.8 s.The XRD patterns of dried samples were obtained using a D/MAX-2500 Advance diffractometer . The diffractometer was operated at 200 mA and 40 kV. The scanning region of the diffraction angle (2p < 0.05).The data presented in the paper are all expressed as the mean ± S.D. The statistical significance of differences between the control and treated samples was evaluated by two-sample t-tests of variance with Excel. Every sample was determined in triplicate. The significant differences between the means of all samples were calculated using a Dunnett’s test  and 3298 cm−1  in −1 in the field for any of the samples. The smooth degrees of the infrared absorption peak at ~3301 cm−1 are reduced for the wheat, maize and sweet potato groups, increased for the cassava group and unchanged for the mung bean group.−1 and amide II  at ~1529 cm−1 are all very weak, and bands only appear at around ~1644 cm−1. Such bands are assigned to the H-O-H bending mode of water [The typical protein bands for amide I  at ~1633 cmof water , becauseof water . These a−1 are characteristic of aggregations with the β-sheet, extended β-sheet, α-helical, β-turn and extended β-sheet conformation structures, respectively [The secondary structure of protein can be determined by the analysis of the Fourier-deconvoluted data. Five bands at approximately 1605, 1632, 1652, 1680 and 1695 cmectively . The chaectively . ASG con−1 (trans-gauche-trans conformation), respectively [We therefore focused our attention on the symmetrical stretching vibration of the disulfide bonds at 500–510 (assigned to gauche-gauche-gauche conformation), 515–525 (gauche-gauche-trans conformation) and 535–545 cmectively . There a−1 (marked with a dashed black arrow) in The characteristic band at ~432 cm13C solid-state NMR spectra of ASG mixed with and without different amylo-pectins, and those of mixed samples before and after retrogradation. 13C solid-state NMR spectra of the different amylopectins mixed with and without ASG. According to [The original intention of this paper was to explore the mechanism by which wheat amylopectin promotes the formation of disulfide bonds in gluten. The chemical bonds newly formed and certain secondary structure of ASG to enhance disulfide bonds would be identified by comparing the results of the rding to , resonanrding to .δ), 172 ppm (backbone C=O), 60 ppm , 52 ppm , 48 ppm (Pδ), 42 ppm , 30 ppm  and 25 ppm  and the shoulders at 19–21 ppm  are all very weak or absent with respect to ASG, as shown in δ linked with N-glycosidic bond), 172.2 ppm (backbone C=O), 132.6 ppm (Yδ), 131.4 ppm (Yγ), 128.5 ppm (Yε), 103.4 + 95.1 and 82.1 ppm (C1 and C4 of the oligosaccharides in the amorphous region), as well as 31.9 ppm (Gln Cβ). The resonances for C2, 3, 5, 6 of the oligosaccharides in all the samples, as shown in δ linked with an N-glycosidic bond without Tyr), 171.5 ppm (hydrogen-bonded backbone C=O), 32.6 ppm (Gln Cγ) and 31.5 ppm (hydroxyproline (HYP) Cβ) show that, compared to ASG, wheat amylopectin combines with a kind of protein containing no Tyr and having a HYP in the side chains. When ASG is mixed with wheat amylopectin, as shown in δ and C=O shift to the lower and higher fields, respectively, and those of Yγ (131.4 ppm) in ASG and HYP Cβ (31.5 ppm) in the wheat amylopectin disappear. The former may be caused by the formation of hydrogen bonds, and the latter may form a covalent bond between the two amino acids. Dough formation is a hydration process, and hydrogen bonds should form between the Qδ/backbone C=O and water. According to the results in ζ of ASG and HYP Cγ in wheat amylopectin promote α-helix formation. The Yγ of ASG and HYP Cβ are buried in the α-helix structures, which leads to the loss of their resonances. This is an important step through which wheat amylopectin promotes the disulfide bond formation of ASG. The resonances at 161.7/160.3/159.6/158.8ppm are assigned to Tyr Cζ (Yζ) [δ linked with the N-glycosidic bond shifts to a higher field, indicating that the hydrogen bonds between Qδ and water disappeared during retrogradation. This can also be proved by the precipitation of the water on the surface of the sample after retrogradation. The reappearance of resonances at 131.4 ppm (Yγ) and loss of resonances at 132.5 ppm (Yδ) suggest that they probably combine with sulfhydryl and are involved in disulfide bond formation. The resonance for the hydrogen-bonded backbone C=O at 171.3 ppm is always present, showing that the hydrogen bonds between C=O and water remain unchanged. It is noteworthy that the increase in the resonances for Yζ at 159.6/158.8 ppm appears in the retrograded wheat amylopectin + ASG group in ζ that were originally involved in the formation of the covalent bonds return to their original hydroxyl state. The cleavage of the covalent bonds in the dough is probably caused by the autoclaving treatment before retrogradation. Compared with wheat amylopectin, maize amylopectin also combines with protein containing Gln, but no resonance at 31.5 ppm for HYP Cγ appears in γ, but there is an absence of resonance at 132.6 ppm for Yδ, indicating that -S of the sulfhydryl of cysteine might combine with Yδ, unlike that of wheat amylopectin, Yγ. The change degree of the secondary structure of ASG in the maize amylopectin + ASG group is lower than that of the wheat amylopectin group, except for the β-turn contents. During the retrogradation of the maize amylopectin + ASG, the procedure leads to reductions in the disulfide bond contents from 0.24% to 0.16%, as shown in ζ in this group, as shown in  Cζ (Yζ) , and theζ of ASG are converted to free ones. The sharply reduced content of intra-molecular aggregation extended β-sheet secondary structure for mung bean amylopectin + ASG from 60.47% to 48.32% before and after retrogradation implies that the formation of covalent bonds between tyrosines is a prerequisite for the formation of intramolecular disulfide bonds in ASG, which agrees well with the findings of [Whether in mixture or in retrogradation, the absence of resonances for Tyr shows that they are all buried in the secondary structures of the complexes. The enhancement of the resonances at 160.3 and 161.7 ppm for the retrograded mung bean amylopectin + ASG and sweet potato amylopectin + ASG groups, respectively, shows that the hydroxyls of the Ydings of . The finθ at ~15o (strong), ~17° (unresolved), ~18° (unresolved) and ~23° (strong); the B-type 2θ at ~5.6°, ~15° , ~17o (strong), ~20° , ~22°  and ~24° ; and the C-type 2θ at ~17° (strong), ~23° (strong)~, 5.6°  and 15°  [θ 13.32°, 15.58°, 17.74°, 18.16°, 20.16° and 22.96°, and those of the wheat amylopectin are located at 2θ 15.76°, 17.46° and 20.16° in θ 17.38° and 20.10° remain, and retrogradation has little effect on them. For the maize amylopectin in θ 15.62°, 17.50° and 20.28°, and the same results as those of wheat amylopectin upon mixture and retrogradation are obtained. The cassava amylopectin in θ 17.44° and 23.00°, which are same as those of the sweet potato amylopectin purified by the hydrolysis of proteases and lipases [θ 20.12°. For the mung bean amylopectin in θ 17.14° and 22.42°. After being mixed and retrograded with ASG, the diffraction angles for the complexes converted to 2θ~17.14°, ~19.86° and ~22.34°. Compared with the diffraction angles of ASG, the most obvious change is the absence of angles at 2θ 13.32° and 15.58°. For the sweet potato amylopectin in θ~15°, and retrogradation causes it to disappear. If only the groups with significant differences are considered, there is a positive/negative correlation between the peak intensity at the diffraction angle of 2θ~20°/23° in It is well-known that the crystal patterns of different granules can be classified into A-, B- and C-types using XRD spectra, and the typical patterns have their own characteristic diffraction angles, with the A-type 2  . A- and   . Figure  lipases . Thus, i lipases . The mix13C solid-state NMR and IR results during the mixing and retrogradation of the different amylopectins and ASG, we speculated on the possible mechanism of the influence of wheat amylopectin on the disulfide bond formation of ASG, as shown in ζ of the Tyr in glutenin and Cγ of the Hyp in wheat amylopectin, as shown in γ-Cδ, and this binding may be accomplished with the help of a certain thioltransferase. Based on this, disulfide bonds are formed at this binding site under the combined action of the mixing forces and the movement of the water molecules. These disulfide bonds should be formed in the structure of intra-molecular aggregation extended β-sheets and β-turns at this stage, because the increase in their contents coincides with the increase in the contents of the disulfide bonds. Additionally, we can thus speculate that, with the help of water movement, the newly formed α-helix structure of ASG originates from a random coil structure, which is pulled by the helix of the wheat amylopectin attached to ASG in a spiral movement, as shown in ζ of Tyr in glutenin and Cγ of Hyp in wheat amylopectin, as shown in δ of Tyr in glutenin. This difference is highly worthy of in-depth study. The increase in the intermolecular β-sheet and β-turn structure of ASG at the retrogradation stage is perfectly understandable, because the hydrogen bonds between the glutenin and wheat amylopectin molecules replace those between the glutenin/amylopectin and water. The straightening of these protein molecules provides the cysteine with a greater opportunity to oxidize and form disulfide bonds. The main limiting factors that determine the content of disulfide bonds include the activities of sulfhydryl transferase and sulfhydryl oxidase, the spatial distance between intramolecular or intermolecular cysteines, environmental pH, etc. High-molecular-weight amylopectin can promote and stabilize the formation of disulfide bond during retrogradation, while low-molecular-weight amylopectin may activate disulfide bond reductase in the stage, resulting in a sharp decrease in the disulfide bond contents, as shown in After the comprehensive analysis of the changes in disulfide bond formation, the distribution characteristics of the starch molecular weight and chain length and the changes in the For the mung bean and sweet potato amylopectins, being two commonly used starches, a surprising discovery is that their addition promotes the generation of glutathione dimers in ASG during the mixing treatment. However, these dimers depolymerize during starch retrogradation, as shown in Wheat amylopectin is the starch that promotes the most significant disulfide bond formation of ASG among the five amylopectins, and it is characterized by the presence of hydroxyproline, a molecular weight greater than 1.3 million Da, and the highest proportion of side chains with chain lengths of 9–12 glucose residues. The disulfide bonds formed by the interaction of ASG and mung bean or sweet potato amylopectin due to glutathione polymer linked by disulfide bonds in the mixing process will be partially reduced during cold storage. The characteristic crystal types of different starches are correlated with the amylopectin + glutenin complexes.


Plasmodium falciparum malaria was investigated.The contribution of artefenomel to the clinical and parasiticidal activity of ferroquine and artefenomel in combination in uncomplicated This Phase 2a, randomized, open-label, parallel-group study was conducted from 11th September 2018 to 6th November 2019 across seven centres in Benin, Burkina Faso, Gabon, Kenya, and Uganda. Patients aged ≥ 14–69 years with microscopically confirmed infection  were randomized 1:1:1:1 to 400 mg ferroquine, or 400 mg ferroquine plus artefenomel 300, 600, or 1000 mg, administered as a single oral dose. The primary efficacy analysis was a logistic regression evaluating the contribution of artefenomel exposure to Day 28 PCR-adjusted adequate clinical and parasitological response (ACPR). Safety was also evaluated.0–∞ to Day 28 PCR-adjusted ACPR was not demonstrated when accounting for ferroquine AUC0–d28, baseline parasitaemia, and other model covariates: odds ratio 1.1 . In the per-protocol population, Day 28 PCR-adjusted ACPR was 80.8%  with ferroquine alone and 90.3% , 90.9%  and 87.1%  with 300, 600, and 1000 mg artefenomel, respectively. Median time to parasite clearance (Kaplan–Meier) was 56.1 h with ferroquine, more rapid with artefenomel, but similar for all doses (30.0 h). There were no deaths. Adverse events (AEs) of any cause occurred in 51.4% (18/35) of patients with ferroquine 400 mg alone, and 58.3% (21/36), 66.7% (24/36), and 72.7% (24/33) with 300, 600, and 1000 mg artefenomel, respectively. All AEs were of mild-to-moderate severity, and consistent with the known profiles of the compounds. Vomiting was the most reported AE. There were no cases of QTcF prolongation ≥ 500 ms or > 60 ms from baseline.The randomized population included 140 patients. For the primary analysis in the pharmacokinetic/pharmacodynamic efficacy population (N = 121), the contribution of artefenomel AUCThe contribution of artefenomel exposure to the clinical and parasitological activity of ferroquine/artefenomel could not be demonstrated in this study. Parasite clearance was faster with ferroquine/artefenomel versus ferroquine alone. All treatments were well tolerated.Trial registration: ClinicalTrials.gov, NCT03660839 .The online version contains supplementary material available at 10.1186/s12936-022-04420-2. Plasmodium falciparum malaria. However, the emergence and spread of parasite strains resistant to both the artemisinin and partner components in the Greater Mekong region has undermined clinical efficacy for several approved ACT options [P. falciparum malaria [P. falciparum strains harbouring Pfkelch13 (k13) mutations indicative of artemisinin resistance have been found in travellers returning from Africa [P. falciparum associated with the A675V k13 mutation has been reported [Artemisinin-based combination therapy (ACT) is the current first-line treatment for uncomplicated  options , 2. In A malaria –5. Howevm Africa , 7, and m Africa . The emem Africa , 9, and m Africa , Angola m Africa , and Burm Africa . Importam Africa . Similarreported . HoweverConsidering the emergence of clinical resistance to ACT, new treatment options are clearly required. Ferroquine and artefenomel are novel anti-malarial drug candidates and a combination of these two drugs has been proposed as a treatment for uncomplicated malaria. New anti-malarial therapeutics should be developed as fixed-dose combinations as this is expected to improve patient adherence and reduce the risk of parasite resistance developing to either drug, particularly if they have contrasting modes of action. When developing fixed-dose anti-malarial drug combinations, it is necessary to demonstrate the contribution of each component to overall efficacy and establish the safety and tolerability profile with co-administration –18.P. falciparum and was well tolerated [Artefenomel  is a synthetic peroxide, with a similar mechanism of action to artemisinin , 20. In olerated . In healolerated , and an olerated .P. falciparum [Ferroquine is a 4-aminoquinoline analog, and a strong inhibitor of hemozoin formation, with high efficacy against chloroquine-resistant and ACT-resistant lciparum –28. Singlciparum , and potlciparum . Pharmaclciparum . AlthougPlasmodium falciparum malaria’ (FALCI) Phase 2 study, investigating artefenomel (800 mg) plus ferroquine  in African and Asian patients aged > 6 months to < 70 years with uncomplicated falciparum malaria [k13 C580Y mutation known to be associated with artemisinin resistance [The efficacy and safety of ferroquine/artefenomel was evaluated in the ‘Ferroquine and Artefenomel in adults and children with  malaria . Efficacsistance .P. falciparum malaria.FALCI was designed with only one dose level of artefenomel, and so there was a risk that the study would not be able to identify the contribution of artefenomel. Consequently, this parallel investigation was designed to specifically evaluate the artefenomel contribution to the efficacy of the combination in African adolescents and adults with uncomplicated This Phase 2a, randomized, open-label, parallel-group study was conducted from 11th September 2018 to 6th November 2019 across seven study centres in Benin (Cotonou), Burkina Faso (Banfora and Nanoro), Gabon (Libreville and Lambaréné), Kenya (Kisumu), and Uganda . The primary objective was to show the contribution of artefenomel to the clinical and parasitological activity of artefenomel and ferroquine in combination by analysing the exposure–response of artefenomel in patients with uncomplicated falciparum malaria. To achieve its objective, some patients would receive a sub-therapeutic dosing regimen, and this was considered in the design by using dedicated risk minimization activities, i.e., selection of a patient population at low risk of severe malaria, hospitalization for at least 48 h or longer based upon the investigator’s judgment, and administration of rescue therapy as soon as there was evidence of treatment failure or systematically on Day 29. The study protocol is provided as Additional file Investigational products were ferroquine 100 mg capsules  and artefenomel 300/400/600 mg granules formulation  presented in a sachet with alpha tocopherol polyethylene glycol 1000 succinate formulation and sucrose. Dose selection aimed to characterize the anti-malarial contribution of artefenomel to the combination. Artefenomel has been evaluated to doses up to 1200 mg with no safety concerns, and a wide range of doses (0–1000 mg) was selected to evaluate the exposure–response. The 400 mg ferroquine dose was selected as a sub-therapeutic dose so as not to mask the contribution of artefenomel. Details of the dose selection methods are in Additional file Patients were randomized centrally using interactive response technology in a ratio of 1:1:1:1 to 400 mg ferroquine alone, or 400 mg ferroquine plus artefenomel 300, 600, or 1000 mg. The administration of treatments was open label as a single oral dose on Day 0 and was directly observed. Ferroquine was administered in a fasted condition. Artefenomel was prepared as a suspension in sterile water and given approximately 15 min after ferroquine. If vomiting occurred after ferroquine, the patient was not re-dosed, artefenomel was not administered, and the patient received rescue therapy. If the artefenomel dose was vomited within 5 min of administration, the patient was re-dosed. Vomiting within 5–35 min of artefenomel administration did not prompt redosing, but any remaining drug was given. Rescue anti-malarial therapy as per local recommendations was administered to patients before Day 28 if clinically indicated, if the ferroquine dose was vomited, or at Day 29 if not given previously.P. falciparum malaria  plus fever or a history of fever in the previous 24 h. All participants were required to use effective contraception and pregnant or lactating women were excluded. Key exclusion criteria were severe malaria [Plasmodium infection, clinically important medical conditions, severe vomiting or diarrhoea, severe malnutrition [To evaluate exposure–response, a sub-therapeutic dosing regimen was to be administered. Thus, the study population was selected to be at low risk of severe malaria. Eligible participants were aged 14 to 69 years, body weight 35–95 kg, of either sex, presenting with microscopically confirmed uncomplicated  malaria , mixed Putrition , splenecScreening procedures included physical examination, medical history, 12-lead electrocardiogram (ECG), vital signs, clinical laboratory tests, viral hepatitis serology, and a pregnancy test. Patients were hospitalized for at least the first 48 h following treatment administration and longer if malaria symptoms or parasitaemia persisted. Patients were followed up on Days 3, 4, 5, 6, 7, 10, 14, 21 and 28. All patients received definitive approved anti-malarial treatment on Day 29 if they had not already received rescue therapy.P. falciparum marker genes msp1, msp2 and glurp, new infection was assumed when all the alleles in parasites from the post-treatment sample were different from those in the baseline sample, for one or more loci tested. Recrudescence was defined as at least one allele at each locus common to paired samples from baseline and at recurrence [Blood samples for parasite assessments were taken at screening, every 6 h until 36 h post-dose, at hours 48, 72, 96, 120, 144, and 168 post-dose, on Days 10, 14, 21, and 28, and at any time if clinically indicated. Giemsa-stained thick and thin blood films were prepared, and parasites identified and enumerated independently by two trained microscopists using standard procedures . ParasitAdverse events were assessed throughout the study. Additional post-treatment safety assessments were 12-lead ECGs, vital signs, haematology, and clinical laboratory tests  and ferroquine (11 sample time points)  at Day 28, defined as the absence of parasitaemia without previous treatment failure or rescue therapy, adjusted for re-infection using PCR genotyping .24, PRR48, and PRR72); parasite clearance rate; and time to parasite reduction by 50% (PC50) and 99% (PC99) of baseline parasitaemia, time for parasitaemia to reduce by 50% (TPC50) and 90% (TPC90) independent of baseline parasitaemia, and the estimated parasite reduction ratio at 24, 48 and 72 h post-dose  ; parasitaemia at baseline then every 6 h during the first 36 h post-dose, then at 48 h and every 24 h until Day 7; parasite clearance time; time to parasitaemia re-emergence, recrudescence, or reinfection; time elapsed below the LLQ of parasitaemia; fever clearance time; observed parasite reduction ratio at 24, 48 and 72 h post-dose , the frequency of serious adverse events, clinically important changes in clinical laboratory data, ECGs, vital signs, or physical examination. Adverse events of special interest were pregnancy, symptomatic overdose, increase in ALT ≥ 3xULN , QTcF ≥ 500 ms, or QTcF prolongation > 60 ms from baseline.Cmax), concentration at Day 7 post-dose (Cd7), area under the concentration–time curve from time 0 to infinity (AUC0–∞) for artefenomel and ferroquine, and AUC from time 0 to Day 28 (AUC0–d28) for ferroquine and desmethyl-ferroquine only.Pharmacokinetic assessments were secondary endpoints, but also supported the primary analysis evaluating the exposure–response for artefenomel  population was a sub-set of the mITT population who were evaluable for Day 28 ACPR with no major protocol violations. The pharmacokinetic/pharmacodynamic (PK/PD) efficacy population was the primary efficacy analysis population and included patients in both the PK and mITT populations who had at least one evaluable PK sample for both artefenomel and ferroquine. Thus, patients who vomited or who did not receive a complete dose of study drug were not excluded from the PK/PD efficacy population.The safety population included all randomized patients who received one dose or a partial dose of the investigational drugs. The PK population was a sub-set of the safety population with at least one evaluable PK blood sample for either artefenomel or ferroquine. The microbiological intention-to-treat population (mITT) included all randomized patients who received the investigational drugs, had microscopically confirmed Sample size was based on the estimated efficacy for artefenomel  plus ferroquine (400 mg) derived from clinical trial simulations assuming a parasitaemia > 3000 parasites/µL  combined with MONOLIX (MLX2019R1) and the IQR package (v1.1.1) developed by IntiQuan  to support the entire workflow of a PK and logistic regression analysis from estimations to simulations. For simulations, IQR uses the library SUNDIALS (v2.9.0) from Computation (USA)  and ferroquine/desmethyl-ferroquine (AUC0–d28) as covariates as well as baseline parasitaemia, age, body weight, sex, vomit status, and study centre  and P values were calculated for covariates. As a secondary efficacy analysis, the relationship between the estimated exposure of artefenomel and ferroquine and Day 28 crude ACPR was evaluated as described for Day 28 PCR-adjusted ACPR.The base model included ferroquine AUCFor other secondary efficacy outcomes and safety outcomes, statistical analysis was done using SAS (version 9.4). Day 28 PCR-adjusted and crude ACPR were summarized for the PP and mITT populations, with Clopper–Pearson 95% CI. All other secondary efficacy outcomes were evaluated in the mITT population. Parasite clearance parameters were calculated using the WorldWide Antimalarial Resistance Network parasite clearance estimator (WWARN PCE) based on the linear portion of the individual natural logarithm parasitaemia–time profiles . The timPharmacokinetic analysis was performed using non-linear mixed effect modelling as implemented in Monolix (version 2019R1), applying previously developed population PK models , 5.6% (2/36), and 3.0% (1/33) of patients in the 300 mg, 600 mg, and 1000 mg arms, respectively. After 35 min following dosing, vomiting was noted for 8.3% (3/36) of patients with 300 mg, 11.1% (4/36) with 600 mg, 24.2% (8/33) with 1000 mg artefenomel. No patients were given rescue medication because of vomiting.The PK/PD efficacy population included 132 patients, but five cases of reinfection and six with undetermined PCR results were considered missing for the Day 28 PCR-adjusted ACPR analysis, with 121 patients evaluable. Baseline demographic and clinical characteristics, drug exposure, and Day 28 PCR-adjusted ACPR outcome for this population are shown in Additional file 0–∞ and ferroquine AUC0–d28 are shown in Fig. Details of the PK analysis supporting the primary endpoint including concentration–time profiles and summaries of estimated exposures for artefenomel, ferroquine and desmethyl-ferroquine relative to dosing are provided in Additional file Day 28 PCR-adjusted ACPR was achieved by 94.4% 34/36) of patients who had an estimated AUC for both artefenomel and ferroquine above the median value, 92.0% (23/25) of patients when only exposure to artefenomel was above its median value, 88.0% (22/25) when only ferroquine exposure was above its median value, and 77.1% (27/35) when exposure to both drugs was below the median value , whereas artefenomel exposure was not. Univariate analysis indicated no effect on Day 28 PCR-adjusted ACPR of desmethyl-ferroquine exposure (P = 0.113), age (P = 0.192), sex (P = 0.0524), or body weight (P = 0.158). As exploring the contribution of artefenomel exposure to Day 28 PCR-adjusted ACPR was the primary objective, this covariate was included for the backward elimination analysis. The backward elimination suggested only the removal of artefenomel exposure.Full details of the exposure–response analysis are provided in Additional file 0–∞ for Day 28 PCR-adjusted ACPR was 1.1    with ferroquine monotherapy. There was a trend for higher efficacy with artefenomel co-administration, though efficacy was similar across the artefenomel doses: 90.3%  with 300 mg, 90.9%  with 600 mg, and 87.1%  with 1000 mg  patients with reinfection in the ferroquine group, and 1/33 (3.0%), 2/36 (5.6%) and 0/32 (0%) with artefenomel 300, 600 and 1000 mg, respectively. Six of the recurrences had undetermined PCR results.Day 28 crude ACPR was 64.5%  for ferroquine alone, with a trend for higher efficacy in the artefenomel arms: 81.8%  with 300 mg, 77.8%  with 600 mg, and 78.1%  with 1000 mg . However, there was a trend over the 28-day study period for a lower probability of re-emergence and recrudescence with the combination arms versus ferroquine alone Fig. .Fig. 6TiThe estimated median time to parasite clearance (Kaplan–Meier) was 56.1 h  with ferroquine alone, but was more rapid in the combination arms, without an effect of artefenomel dose: 30.0 h  with 300 mg, 30.0 h  with 600 mg, and 30.0 h  with 1000 mg artefenomel  was 4.08 (SD 1.59) with ferroquine alone and ranged between 7.46 and 8.26 in the combination arms. Similarly, mean PC50 was 14.07 (SD5.6) compared with 7.74 to 9.47 for the combination arms  of patients in the ferroquine only group, and in the combination arms for 58.3% (21/36) with 300 mg, 66.7% (24/36) with 600 mg, and 72.7% (24/33) with 1000 mg artefenomel. The most common adverse events were malaria  with ferroquine alone, malaria and headache  with artefenomel 300 mg, malaria  with artefenomel 600 mg, and vomiting  with 1000 mg artefenomel  of patients with ferroquine, most commonly vomiting 3.6%; 5/140)  observed in a female patient with baseline elevations of ALT (1.1xULN), alkaline phosphatase (ALP) (3.2xULN), and total bilirubin (1.2xULN), and no history of hepato-biliary disorders. From Day 5, ALT increased to a maximum of 3.3xULN on Day 15, with concurrent ALP 5.4xULN, AST 1.3xULN, and total bilirubin 1.2xULN. Total bilirubin continued to rise, peaking at 3.4xULN on Day 25 with direct bilirubin at 4.7xULN and ALP at 5xULN. There were no symptoms, and ALT, AST, and total bilirubin values had returned to normal by Day 42 without intervention. Further elevations in ALT (1.7xULN), AST (1.5xULN), total bilirubin (1.3xULN), and ALP (2.6xULN) were noted on Day 96, but all measures had resolved to baseline levels by Day 141.There was no difference in the maximum post-baseline change in haematology parameters between treatment groups, which were consistent with recovery from malaria  to the clinical and parasiticidal activity of the artefenomel/ferroquine combination, defined as Day 28 PCR-adjusted ACPR, could not be identified in this study. The study also failed to identify the contribution of artefenomel exposure to the effect of the artefenomel/ferroquine combination for Day 28 crude ACPR. This occurred even though clinical trial simulations were performed to support the dose selection and sample size, and even though a wide range of individual artefenomel exposures (0–13.05 µg*h/ml) were observed.The contribution of artefenomel exposure , whereas the observed response with ferroquine alone (80.8%) was close to the upper limit of predicted efficacy. With a lower than predicted number of treatment failures across all treatment arms, it was statistically more difficult to detect a significant contribution of artefenomel.The reasons for a higher-than-expected response to ferroquine are unclear. However, this does not appear to result from higher than anticipated ferroquine or active metabolite exposures in this study population. Notably, limited exposure–response data were available for ferroquine to inform the clinical trial simulations and no efficacy data for the artefenomel/ferroquine combination were available. Consequently, there was considerable uncertainty associated with the predictions for ferroquine exposure–response. However, this uncertainty in the predicted ferroquine response was not considered in the clinical trial simulations.The upper limit for parasitaemia for enrolment in this study was 50,000 parasites/µL for ethical reasons, considerably lower than the maximum parasitaemia level used in the clinical trial simulations . Both in this study and in FALCI, higher baseline parasitaemia was shown to significantly decrease the odds of Day 28 PCR-adjusted ACPR . The lowIn FALCI, there was evidence that age influenced baseline parasitaemia . AfricanP. falciparum parasitaemia of ≥ 3,000 to ≤ 50,000 parasites/µL blood. Given that the ferroquine only arm was not expected to achieve clinical cure rates > 72%, this population was selected to minimize the risk of developing severe malaria. Note that data from Burkina Faso indicate that asymptomatic carriage of malaria is rare at parasite densities ≥ 2,500 parasites/µL blood, occurring at a rate of 5.3% (7/133) in patients aged > 15 years [Overall, eligible participants were aged 14 to 69 years, with 15 years . Similar15 years . Thus, aNo new safety signals were identified, and the safety findings were consistent with previous clinical studies , 40–43. Although there was one case of increased ALT, there was no suggestion of a relationship between artefenomel dosing and ALT increases. No patient had a QTcB or QTcF > 500 ms or an increase from baseline > 60 ms. These findings contrast with FALCI, as increased ALT was reported in 2.1% (8/373) of patients and appeared to be associated with ferroquine . There wThis study illustrates the challenges in designing clinical trials to demonstrate the contribution of individual drugs to the overall efficacy of a combination therapy in a disease which if not rapidly treated can progress to a serious and life-threatening condition. To explore the contribution of the individual drugs, sub-therapeutic doses must be administered. However, the risk to the patients from disease progression must also be minimized. Consequently, in this study the patient population excluded children < 14 years of age who are most at risk of severe malaria, restricted baseline parasitaemia to the range ≥ 3000 to ≤ 50,000 parasites/µL blood and used drug doses that were not substantially sub-therapeutic.The contribution of artefenomel exposure to Day 28 PCR-adjusted ACPR could not be demonstrated. The main reason was likely the higher than anticipated efficacy with ferroquine alone which reduced the power of the study to identify the contribution of artefenomel to the drug combination, rather than a true lack of contribution. More rapid parasite clearance was demonstrated with the artefenomel/ferroquine combination compared to ferroquine alone, clearly showing the contribution of both drugs to parasite clearance. The combination was generally well tolerated, and the safety profile was consistent with the known profiles of the two compounds.Additional file 1: Study protocol.Additional file 2: Clinical trial simulation to determine the dose and sample sizes.Additional file 3: Pharmacokinetic analysis supporting the primary analysis.Additional file 4: Exposure–response pharmacokinetic/pharmacodynamic analysis.Additional file 5. Supplementary tables and figures.


Immunoglobulin detection is important for immunoassays, such as diagnosing infectious diseases, evaluating immune status, and determining neutralizing antibody concentrations. However, since most immunoassays rely on labeling methods, there are limitations on determining the limit of detection (LOD) of biosensors. In addition, although the antigen must be immobilized via complex chemical treatment, it is difficult to precisely control the immobilization concentration. This reduces the reproducibility of the biosensor. In this study, we propose a label-free method for antibody detection using microcantilever-based nanomechanical resonators functionalized with erythrocyte membrane (EM). This label-free method focuses on the phenomenon of antibody binding to oligosaccharides (blood type antigen) on the surface of the erythrocyte. We established a method for extracting the EM from erythrocytes and fabricated an EM-functionalized microcantilever (MC), termed EMMC, by surface-coating EM layers on the MC. When the EMMC was treated with immunoglobulin M (IgM), the bioassay was successfully performed in the linear range from 2.2 pM to 22 nM, and the LOD was 2.0 pM. The EMMC also exhibited excellent selectivity compared to other biomolecules such as serum albumin, γ-globulin, and IgM with different paratopes. These results demonstrate that EMMC-based nanotechnology may be utilized in criminal investigations to identify blood types with minimal amounts of blood or to evaluate individual immunity through virus-neutralizing antibody detection. Immunoglobulin (Ig), also known as an antibody, is a glycoprotein that binds to an antigenic epitope . Ig playImmunoassay is based on a biological method that analyzes a specific reaction between an antigen and an antibody ,15. An iω) of the MC is inversely proportional to the square root of the mass of the MC. That is, an increase in the mass of the MC due to molecular adsorption decreases the ω of the MC. Using the ω shift (Δω), defined as ω − ω0, it is possible to assay biomolecules such as viruses [MC-based sensors have been widely used in immunoassays due to their advantages of high sensitivity , low cos viruses , bacteri viruses ,41,42, a viruses , and pro viruses . Further viruses ,47,48,49 viruses ,51. Spec viruses .Herein, inspired by IgM-induced hemolysis, we have fabricated a novel EM-functionalized MC (EMMC) for IgM detection a,b. EM wAdvanced PAP pen , distilled water (DW), deionized water (DIW), phosphate buffer saline , human serum, human serum albumin (HSA), and γ-globulin were purchased from Sigma Aldrich . Additionally, 18:1 PE CF fluorescent lipid was purchased from Avanti Polar Lipid . Anti-A (ABO1) and Anti-B (ABO2) were purchased from DIAGAST .k = 45 N/m; Probes, Seoul, Korea) was mounted on to an AFM aqua head . The laser voltage before MC tuning was about 2.0V. Next, the ω of the MC was calibrated using the ‘Auto Tune’ method in the ezAFM v10.20 software. All the MCs were mounted on to AFM aqua heads after they were completely dried.Morphology and fluorescence images of the MCs were characterized by microscopy . An MC  and stored in the refrigerator for 1 h. Then, to obtain pure EM, they were centrifuged under specific conditions  and washed 3 times with 1× PBS. The obtained clear ruby-colored EM was stored in a freezer (−80 °C). Before use, each EM solution was diluted with DW, and then sonicated and vortexed for 5 min.EM was extracted from human whole blood using the previously mentioned method . The bloSeveral steps were taken to functionalize the EM in the device. First, a liquid blocker was coated only on the base of the AFM probe (PR-T190) and dried at 23 °C for 5 min. Coating the base with a liquid blocker allows the EM to selectively functionalize only on the MC surface. Specifically, the MCs were functionalized by slowly pipetting 60 μL of EM solution (1%) and washing them 100 times to resolve EM residues.ω) in dry air follows the elastic continuum model [MCL, EI, MCρ, A, MCK, and MCM are the MC’s length, bending rigidity, density, cross-sectional area, the MC’s effective stiffness, and the MC’s effective mass, respectively. In detail, MCK = β4EI/MCL3 and MCM = MCA.ρ The β satisfies the transcendental equation such that cosβcoshβ + 1 = 0. Here, the dimensions of the MC are given by MCL × MCW × MCT (length × width × thickness), where MCL = 215 μm, MCW = 37.5 μm, and MCT = 8 μm. Following this equation, our MC’s ω is 149.54 kHz. The average of ω was experimentally obtained to be 153.25 ± 1.58 kHz. This shows that our MC satisfies the elastic continuum model. Because the MCT of the MC is much larger than that of the molecular layer, the mass is the main factor causing the resonant frequency shift (Δω) [ω in the air as follows:ω is the resonant frequency shift measured in air, and ΔM is the total mass of the molecule, including molecular interactions. The EMMC can detect IgM using this Δω.The MC’s resonance frequency (um model .(1)ω=βLift (Δω) . Therefoω was measured through frequency sweeping  were dispensed on to the EMMC. Afterward, the EMMC was shaken at 60 rpm for two hours at 23 °C. The IgM-bound EMMC was carefully washed with PBS and fully dried. The EMMC’s ping see .ω of the MC, we compared the ω of the MC before and after the liquid blocker coating was applied. The ω of the MC with the liquid-blocker-coated base was slightly different from that of the bare MC. Subsequently, EM was functionalized on the MC. In order to fabricate the EMMC, it is important to coat only a single layer of the EM on the MC surface. The two variables of EM concentration and the number of washes are very important. If high EM concentration was treated on the bare MC, the number of washes of the EMMC should be increased to remove excessive EM residues. These variables will depend on the type of materials and the shape of the MC. We can only describe the conditions for fabricating an EMMC based on the MC : agitate 100 times by repetitively pipetting with 1% EM solution (60 μL), and subsequently wash 100 times. As shown in During the EM functionalization process, it is difficult to coat only the MC surface and not the MC base. To solve this problem, scientists use microinjection or microcapillary technology, which is considered to be a major limitation in the mass production of EMMCs ,64. To pω occurs due to EM coating, the MC’s ω was measured before and after the EM coating was applied. The ω for the bare MCs and the EMMCs are 153.25 ± 1.58 and 153.06 ± 1.56 kHz (mean ± standard deviation); a 0.17 ± 0.06 kHz decrease was observed after EM functionalization on the MC surface . This suggests that IgM binds proportionally to antigens present on the EM surface. This plot also shows that Δω and log(IgM) are linearly related. The analyzed semi-log regression analysis was ‘Δω = 0.05 × log(X) + 0.08′, and the limit of detection (LOD) calculated as 3.3 × (σ/S) was 2.04 pM. The σ is the standard deviation of the response, and S is the slope of the linear fit. According to Equation (2), 2.04 pM LOD corresponds to 17.32 pg IgM, which can be considered the resolution of the EMMC in IgM detection  dissolved in 1× PBS (pH 7.4). Here, Δetection .ω values of the EMMC treated with IgM (Anti-A), HSA, and γ-globulin were 0.05 ± 0.01, 0.05 ± 0.03, and 0.05 ± 0.02 kHz, respectively (ω for IgM (Anti-A), HSA, and γ-globulin normalized by Δω values in the IgM (Anti-B) condition were 14.79 ± 3.05, 14.90 ± 9.04, and 17.17 ± 6.41%, respectively , whereas blood type B contains antigens (Type B) only on erythrocytes. Therefore, type B erythrocytes do not interact with IgM (Anti-A) and bind selectively to IgM (Anti-B). Note that our EMMC was fabricated with erythrocytes from blood type B. The selectivity of the EMMC sensor was verified by measuring high concentrations of major proteins present in the blood, such as IgM (Anti-A), HSA, and γ-globulin . The treectively a. The inectively b. These ω of the EMMC decays sharply at high concentrations of IgM (>220 nM) and remains almost unchanged. Specifically, the Δω of EMMCs exposed to 220 nM and 22 μM IgM were 0.07 ± 0.04 and 0.05 ± 0.03. This implies that the EMMC will normally operate below 22 nM IgM, but may malfunction above 220 nM . This is indeed challenging and would be a desirable research theme for future work.We investigated the detection ability of the EMMC at high IgM concentrations. Interestingly, the e 220 nM a. This he 220 nM b. Moreove 220 nM c. From tω and IgM concentration (0–22 nM) under a semi-logarithmic scale , HSA, and γ-globulin. Our results prove that the EMMCs are highly sensitive and can selectively detect antibodies with a simple procedure and a label-free method. Although the EMMC successfully detected IgM in PBS and serum, further investigation is required for IgM detection in patient samples. We expect that our approach to EMMC fabrication and biosensing performance will shed light on the development of highly sensitive and selective label-free biosensors capable of detecting target molecules by single-step cell membrane functionalization.