Objective: This study examined the correlations between trust in government and the public’s protective behaviors regarding food safety, focusing on the mediating role of risk perception.Methods: The 2013  and 2019  Taiwan Social Change Survey data were analyzed using ordinary least squares regression models. The bootstrap method was used to examine the mediating effect of risk perception.Results: Perceived integrity of government regarding food safety issues influences all four types of food protective behaviors directly and indirectly via risk perceptions. The four protective behaviors were “not eating that food,” “preparing food kit,” “preferring organic food,” and “overall behaviors.” Trust in government directly influences part of the protective food behaviors, while no mediating effects of risk perception were found.Conclusion: The results of this study will deepen our understanding of food consumption behavior, identify key factors that influence public food protective behaviors, and inform food safety management to implement strategies necessary to improve food consumption. Food safety is one of the most complex and concerned social issues in China . In 2008Understanding the public’s food consumption and self-protective behaviors in the face of food risk is particularly important for food safety management and risk regulation in the food industry. Therefore, it is essential to investigate the protective behaviors concerning food consumption from the behavioral science perspective. Generally, models such as the health belief model, the theory of planned behavior, the social-cognitive model –10, and The attributes of the information that individuals receive and their comprehension of the information can influence their risk perceptions and their self-protective actions . The attIn the food safety context, the perception of food safety risks as consumers’ beliefs determine the consumers’ intentions and behaviors of purchasing those food products , 25–27. H1Trust in government directly predicts the degree of taking food protective behaviors. With a higher trust degree of government, people would have a larger likelihood to take protective behaviors to protect themselves.Similarly, many aspects of life have been taken out of the control of the individual, including access to the food production system, which requires reliance on and trust in external institutions . DecisioH2The perceived integrity of government regarding food safety issues directly influences the public’s adoption of food protective behaviors. With less fear that the government hides food safety information, people would have less willingness to take protective behaviors.Risk perception also significantly influences people’s food consumption behaviors . It may H3Risk perception of food safety mediates the relationship between trust and “not eating” (H3a), “preparing food kit” (H3b), “preferring organic food” (H3c), and “overall behaviors” (H3d).H4Risk perception of food safety mediates the relationship between the perceived integrity of government regarding food safety issues and “not eating” (H4a), “preparing food kit” (H4b), “preferring organic food” (H4c), “overall behaviors” (H4d).Additionally, individuals’ socioeconomic and demographic factors were incorporated into the hypothesized model as control variables. This paper analyzed the 2013 and 2019 Taiwan Social Change Survey (TSCS) risk society module data, respectively. The TSCS survey is a representative repeated cross-sectional survey conducted annually by the Institute of Social Science of Academia Sinica in collaboration with the Humanities and Social Sciences Research Center in Taiwan. The data is collected by face-to face interviews and publicly available from the Academia Sinica’s Survey Research Data Archive website and open to registered researchers.Risk society modules were included in the 2013 and 2019 surveys. According to the reports of both surveys, the stratified three-stage  probability and proportional-to-size sampling method were employed for both, and the 2013 data included 2,005 individuals, while the 2019 data covered 1,933 samples. 1,432 observations from the 2013 data and 1,276 samples from the 2019 data were included in the models because the ones with missing values were dropped directly in the analysis.The intentions for adopting protective behaviors are used as the proxy of actual behaviors because it is very difficult to measure the actual behaviors in reality , 55. FouThe trust in the government concept was measured in two dimensions. The first one was directly captured by the question, “In general, do you trust the government?” The “central/provincial government,” “county government,” and “town government” were listed as different levels of government. The trust in each type of government was represented on a 5-point Likert scale . The average of the three variables was used as the degree of trust in government .The perceived integrity of government in the food safety area was used as the second dimension of the trust in government, and it was measured by the question, “Are you concerned that the government hides food safety information?” A 5-point Likert scale measured the answers , indicating an increased degree of integrity of government regarding food safety issues.The risk perception for food safety was calculated from the responses collected from three questions: “How do you concern about possible pollution from heavy metal or plasticizers?,” “How do you concern about the pesticide residue in fruit, vegetables, and grocery?” and “How do you concern humans using biotechnology to alter the genes of plants and animals?” A 5-scale Likert scale measured the responses to each of the three questions , indicating the increased degree of concern. The sum of the responses to all three questions was used as the risk perception score in this analysis .In reference to prior studies on risk perception and food protective behaviors –63, the via risk perceptions, were assessed  regression models were employed when the protective behaviors were used separately. Simple mediation models regarding trust in government and perceived integrity of government regarding food safety which affects food safety protective behaviors assessed . All the1,432 respondents were included in the 2013 TSCS, 54.1% were male, 79.7% had religious beliefs, and 41.1% had a child(ren) at home. In the 2019 data, 1,276 respondents were included, 54.4% were male, 73.3% had religious beliefs, and 34.8% had a child(ren) at home, respectively. Respondents generally had lower perceived integrity of government regarding food safety issues, both in 2013  and 2019 . Nevertheless, they had a relatively higher level of trust in the government, reaching 3.3 in both the 2013 and 2019 surveys. Risk perception maintained similar levels in 2013 and 2019. Regarding the three food protective behaviors, the percentage of “definitely not,” “probability not,” “probability will,” and “definitely will” eating the food if a news report about the food safety issue were 5.8%, 15.0%, 37.7%, 41.5% in the 2013 survey, while these distributions in the 2019 survey were 3.8%, 14.0%, 39.6%, 42.7% in the 2019 survey. Similarly, the “preparing food kit” choices from “definitely not” to “definitely will” were 14.5%, 29.0%, 33.1%, and 23.4% in the 2013 survey, while they were 15.8%, 23.4%, 34.5%, 26.4% in the 2019 survey. The shares of “preferring organic food” in the 2013 survey were 7.9% (definitely not), 33.8% (probability not), 44.3% (probability will), and 14.0% (definitely will), and these percentages in the 2019 survey were 8.6%, 31.4%, 46.6%, 13.5%, respectively. β = 0.08, p < 0.01 in 2013; β = 0.09, p < 0.01 in 2019), “preparing food kit” , “preferring organic food” , and “overall behaviors”  (in 2019) , 3. ThusThe bootstrapping method  was usedTests of indirect effects to assess mediation revealed that risk perception did not mediate the correlations between trust in government and any type of protective behaviors, either in 2013 or 2019. Hence, H3a, H3b, H3c, and H3d were not supported .β = −0.09, 95% CI =  in 2013; β = −0.05, 95% CI =  in 2019), “preparing food kit” , “preferring organic food” , and “overall behaviors” , indicating that perceived integrity influences food protective behaviors both directly and indirectly. Therefore, H4a, H4b, H4c, and H4d were supported.Risk perception mediated the relationship between perceived integrity on “not eating that food” , which may have an impact on the final results. Last but not least, although the relationship between information credibility and risk perception is certainly longstanding, the circumstances in which this relationship is expressed today, present great challenges and as such, an opportunity for future researches. The mechanisms linking credibility, information processing, and risk perception are likely to be located in motivation, issue involvement, information-holding, and the effect of message cues . More ev


The emitters were positioned in front of the atmospheric pressure interface of a Fourier transform-ion cyclotron resonance (FT-ICR) mass spectrometer by means of a slightly modified nano-electrospray ionization (nanoESI) source. The entrance electrode of the interface was set to positive high voltage with respect to the emitter at ground potential. Under these conditions, negative-ion desorption was achieved. The surfactant anions, organic sulfates and organic sulfonates, were characterized by accurate mass-based formula assignments, and in part, by tandem mass spectrometry. The negative-ion APFD spectra were compared to results by negative-ion electrospray ionization (ESI) either obtained using the FT-ICR mass spectrometer or by using a trapped ion mobility-quadrupole-time-of-flight (TIMS-Q-TOF) instrument when product ions of low m/z needed to be detected in tandem MS.Recent work has shown that field desorption (FD) and field ionization (FI) using activated field emitters may be performed at atmospheric pressure, too. While some limitations apply to atmospheric pressure field desorption (APFD) mass spectrometry (MS), the method can deliver both positive and negative even electron ions of highly polar or ionic compounds. Furthermore, APFD even permits the generation of positive molecular ions of polycyclic aromatic compounds. Here, an application of negative-ion APFD for the analysis of anionic surfactants contained in commercial detergent products for body care, household, and technical uses is presented. The samples include liquid soaps and shower gels, dishwashing liquids, and cooling lubricants. Surfactant solutions in methanol/water or pure methanol at 2–10 µl mlThe online version contains supplementary material available at 10.1007/s00216-023-04917-y. The last two decades brought various innovative approaches to ion generation at atmospheric pressure, many of them exploiting the effect of strong electric fields to generate or at least desorb ions from tips, edges, and most importantly sharp pins or needles. Some prominent examples are presented by paper spray ionization , tissue −1 are field ionization (FI) and field desorption (FD) +, and/or alkali ion adducts, [M + alkali]+ + –17. Ionialkali]+ , 18, 19.alkali]+ –24. The emitters –27. Actiemitters –33 additemitters , 34–38.Especially among those in the community with long experience in FI, FD, and later also LIFDI, it had become manifest that these ionization techniques had to be performed in high vacuum. Nonetheless, the majority of recent mass spectrometers comes with atmospheric pressure interfaces. It therefore deemed advantageous to transfer FD to these platforms. Thus, attempts have been made to permit FD in a non-vacuum environment, preferably at atmospheric pressure. Thus, FD has been performed at superatmospheric pressure (6 bar), thereby allowing for emitter potentials in the order of 10 kV while suppressing electric discharges to the counter electrode . From baDrosophila flies +•, were detected − cluster ions for the m/z 150–1200 range ..m/z 444.m/z 265 and leads up to m/z 749 in steps of 44 u while series B starts at nominal m/z 293 and leads to m/z 693, also in increments of 44 u. Upon zooming in at the isotopic patterns, all of these signals reveal the presence of one sulfur atom at the M + 2 peaks due to separation of the 13C2 ions (Δ(m/z)calc = 2 × 1.0033) and the 34S ions (Δ(m/z)calc = 1.9958). Combined with accurate mass data, the formulas of the corresponding ions can be assigned. The first ones of series A are [C12H25O4S]− , [C14H29O5S]− , [C16H33O6S]− , and [C18H37O7S]− , the latter being the most abundant ion. For series B, one obtains [C14H29O4S]− , [C16H33O5S]− , [C18H37O6S]− , and [C20H41O7S]− , also with the latter being the most abundant one , fragment ions at nominal m/z 80 and m/z 97 appeared as the only fragment ion species formed of any of these ions  and to [SO4H]− , respectively. Thus, the tandem mass spectra confirmed the assumption that the surfactant anions either belong to organic sulfates  or sulfonates , respectively. More detailed information on the position of poly-ethyleneglycol moieties was not available as there were no fragment ions related to this part of the molecules.Furthermore, because the fragment ions were expected below ons Fig. . Based om/z 265 or m/z 309 as the base peak, the other being centered around m/z 397 or m/z 441 as the base peak. Among these, Today Seife aqua has been taken as another candidate for tandem MS of a series of precursor ions  using the timsTOFflex instrument. Unsurprisingly, the resulting spectra all corresponded to organic sulfates Below is the link to the electronic supplementary material.


After adjusting for clinical variables, an eGFR ≤ 30 mL/min/1.73 m2  and a medical history of CAD  were independent risk factors for developing PICM. A medical history of CAD and low eGFR are independent risk factors for PICM in patients with preserved LVEF at baseline. These results could be helpful in predicting a decreased LVEF by ventricular pacing before PMI. Close follow-up by echocardiography is recommended to avoid a delay in upgrading to physiological pacing, such as cardiac resynchronization therapy or conduction system pacing.Clinical predictors for pacemaker-induced cardiomyopathy (PICM)  have been reported. However, factors involved in the development of PICM in patients with preserved left ventricular ejection fraction (LVEF) remain unknown. This study aimed to determine the risk factors for PICM in patients with preserved LVEF. The data of 113 patients  who had echocardiography before and after pacemaker implantation (PMI) among 465 patients undergoing dual-chamber PMI were retrospectively analyzed. Thirty-three patients were diagnosed with PICM . A univariate Cox regression analysis showed that an estimated glomerular filtration rate (eGFR) ≤ 30 mL/min/1.73 m A combination of electrical and mechanical dyssynchrony leads to adverse LV remodeling, which promotes heart failure (HF), atrial fibrillation (AF), and mortality4.Chronic right ventricular (RV) pacing sometimes leads to a deterioration in the left ventricular ejection fraction (LVEF) because RV pacing provokes interventricular dyssynchrony and intraventricular dyssynchronous contraction in the left ventricle (LV)6. Previous studies have used different LVEF thresholds to define PICM. Therefore, there is currently no internationally accepted definition of PICM. The following three definitions of PICM have been used in past clinical studies: (1) an LVEF ≤ 40% if the baseline LVEF is ≥ 50% or an absolute reduction in the LVEF ≥ 5% if the baseline is < 50%; (2) an LVEF ≤ 40% if the baseline LVEF is ≥ 50% or an absolute reduction in the LVEF ≥ 10% if the baseline is < 50%; and (3) an absolute reduction in the LVEF ≥ 10%, regardless of baseline LV function9.A deterioration in LV systolic function related to pacemaker implantation (PMI) is termed pacemaker-induced cardiomyopathy (PICM)11. The highest prevalence was reported to be 39% according to the definition of an absolute reduction in the LVEF ≥ 10% during a follow-up of 3–4 years2. Furthermore, a worldwide survey showed that the number of patients undergoing PMI had increased12. Therefore, the number of patients with PICM should also be increased.There is wide variation in the published prevalence of the development of PICM (5–27%)9, male sex13, a history of myocardial infarction13, a lower baseline LVEF15, a wider intrinsic QRS duration16, left bundle branch block (LBBB)13, a history of AF17, and a chronic higher RV pacing burden8 could be risk factors for PICM. However, the precise mechanism and established risk factors for PICM have not been fully identified18. Therefore, the present study aimed to identify additional risk factors for PICM.Identifying risk factors for PICM before PMI is beneficial for preventing PICM-associated heart diseases, such as HF. It is reported that an older ageIn this study, PICM was defined as follows: (1) exclusion of alternative causes of heart diseases, such as acute myocardial ischemia, uncontrollable tachyarrhythmia, frequent premature contractions, and untreated hypertension; and (2) an absolute reduction in the LVEF ≥ 10% as measured by transthoracic echocardiography (TTE) after PMI compared with before PMI. TTE data were collected within six months before PMI and from three months to three years after PMI. All TTE data were over-read by cardiovascular experts.All data were retrospectively acquired at the University of Tokyo Hospital, Tokyo, Japan, from patients who underwent de novo PMI between December 2006 and November 2018. PMI was performed in patients with sick sinus syndrome (SSS) or atrioventricular block (AVB). A total of 465 patients undergoing PMI were included in this study. To identify the risk factors for PICM, the medical history and clinical data were retrospectively collected from all patients. The flow of data collection for the study is shown in Fig. The inclusion criteria were as follows: (1) age of ≥ 20 years; (2) de novo PMI; and (3) available data of TTE before and after PMI. The exclusion criteria were as follows: (1) implantation of a prior cardiac implantable electronic device; (2) lack of TTE before and/or after PMI; (3) congenital heart diseases; (4) heart transplantation; and (5) alternative cause of a reduction in the LVEF, such as acute myocardial ischemia, valvular heart disease, uncontrollable tachyarrhythmia, frequent premature contractions, and untreated hypertension. In addition, all of the patients’ laboratory data were obtained upon admission to our hospital and at a follow-up LVEF examination after discharge.−1.094 × (age)−0.287 × 0.739 19. Chronic kidney disease (CKD) was defined as an eGFR < 60 mL/min/1.73 m2.The primary outcome was an incidence of a reduced ejection fraction, which was defined as a ≥ 10% reduction in the LVEF in a follow-up TTE after PMI. The New York Heart Association (NYHA) class was categorized on the basis of symptoms and evaluation of a medical examination on admission by expert cardiologists. AF was diagnosed by an electrocardiogram on admission. Diabetes mellitus was diagnosed as a glycated hemoglobin value ≥ 6.5% or determined by a history of taking oral hypoglycemic agents or insulin injections. Hypertension (HT) was diagnosed as a systolic blood pressure ≥ 140 mmHg or diastolic blood pressure ≥ 90 mmHg. A history of antihypertensive agents was also used to determine HT. The estimated glomerular filtration rate (eGFR) was calculated as 194 × (serum creatinine)t-test or Mann–Whitney U test for continuous variables and the Chi-square test for categorical variables, as appropriate. The incidence rate of PICM and its 95% confidence interval (CI) were calculated in person-years with the assumption of Poisson distribution for the total patients. The cumulative rates of PICM were calculated with the Kaplan–Meier method, and time-to-event data are shown in Kaplan–Meier curves. Cox univariate and multivariate analyses were performed to estimate hazard ratios (HRs) of clinical variables for developing PICM. All statistical analyses were performed using IBM SPSS version 28.0.0.0 , and a two-tailed P value < 0.05 indicated statistical significance.The patients were divided into two groups, the PICM group and the non-PICM group, on the basis of the definition of PICM as previously described. The differences in baseline characteristics were compared between the two groups by Student’s This study was approved by the University of Tokyo institutional ethics committee . All patient information was deidentified and the requirement for written informed consent was waived by the University of Tokyo institutional ethics committee. The study protocol was conducted in accordance with the Declaration of Helsinki.2. All patients underwent implantation of the dual-chamber pacemakers, and 77 (68.1%) underwent PMI for SSS and 36 (31.9%) for AVB. Of the 36 patients diagnosed with atrioventricular block (AVB), the following classifications were observed: 26 patients, or 72.2%, exhibited complete AVB; six patients, representing 16.7%, had 2:1 AVB; and the remaining four patients, accounting for 11.1%, were diagnosed with advanced AVB.One hundred and thirteen patients who underwent de novo PMI and had TTE data before and after PMI were enrolled. The patients’ characteristics are shown in Table P = 0.03) and a history of previous PCI , lower eGFR , higher rate of eGFR ≤ 30 mL/min/1.73 m2 , lower rate of LBBB , and shorter QRS duration  than the non-PICM group. There were no significant differences in other background factors between the two groups.Among the enrolled patients, 44 (38.9%) had a medical history of coronary artery disease (CAD), and those of 33 (29.2%) patients had undergone percutaneous coronary intervention (PCI). Patients in the PICM group had a more prevalent medical history of CAD  and RV pacing frequencies in patients in the PICM and non-PICM groups after PMI were investigated retrospectively. Pacemaker interrogation data were obtained at the closest date of the TTE examination. There were no significant differences in RA or RV pacing frequencies between the two groups Table .Table 2R2, (B) eGFR ≥ 60 mL/min/1.73 m2 and < 90 mL/min/1.73 m2, (C) eGFR > 30 mL/min/1.73 m2 and < 60 mL/min/1.73 m2, and (D) eGFR ≤ 30 mL/min/1.73 m2. There was a significant difference in the incidence of PICM between the four groups by the eGFR . Additionally, there were marked differences in the incidence of PICM between groups B and D, as well as between groups C and D, with log-rank values of P = 0.02 and P < 0.01, respectively. These findings are detailed in Table 2 showed a higher incidence of PICM than those with an eGFR ≥ 30 mL/min/1.73 m2.During a mean follow-up of 1.6 ± 0.9 years, 33 29.2%) patients developed PICM, and the incidence rate was 18.0/100 person-years (95% CI 12.8–25.2) in the total follow-up of 184 person-years. Kaplan–Meier curves for the rates of developing PICM are shown in Figs. 9.2% pati). Every 10 mL/min/1.73 m2 decrease in the eGFR , an eGFR ≤ 30 mL/min/1.73 m2 , and a medical history of CAD  were significantly related to the development of PICM. However, neither LBBB nor every 10-ms prolongation of the QRS duration was significantly associated with PICM .A univariate Cox regression analysis of clinical features that were associated with the prediction of PICM was performed Table . Every 12, and a medical history of CAD, the multivariate Cox regression analysis showed that an eGFR ≤ 30 mL/min/1.73 m2 and CAD were significant independent risk factors for PICM   in patients with PICM, in other words, a total of 11.5% of patients had a low GFR < 30 ml/min/1.73 m2.The frequencies of PICM have been reported to be 5.1–26.8% at follow-up, with a mean period of 1–15 years24, increasing mortality in patients with HF25. In particular, moderate/severe renal impairment has a high risk of developing HF26. Various mechanistic insights have been proposed for this finding. Renal impairment can upregulate the renin–angiotensin–aldosterone system and enhance basal sympathetic nerve discharge, increasing pro-inflammatory factors and oxidative stress. Additionally, endothelial dysfunction27, exacerbation of underlying anemia, and worsening of LV hypertrophy and myocyte contractility are related to the incidence of HF and impairment of ventricular systolic function.Renal impairment confers a high risk for poor cardiovascular outcomes28. Atherosclerosis and CKD affect cardiac function through their interaction that worsens with each other.The high phosphorus status associated with CKD also promotes the calcification of cardiac vessels and valves, further accelerating a reduced LVEF31. However, these possibilities have still not been proven.Metabolic causality has also been reported as the cause of PICM. Several studies have proposed that RV pacing can induce abnormal myocardial metabolism and altered regional perfusion, increase fibrosis, and cause myofibrillar disarray33. In addition, they showed that the inhibition of the liver X receptor/retinoid X receptor pathway, which regulates lipid metabolism, inflammation, and cholesterol to bile acid catabolism, was associated with pacing32.Recently, Lin et al. suggested a mechanism of PICM by which intracellular lipid accumulation induced by pacing increases fibrosis in the LV myocardium in some animal models, including pigs and rats33. These results suggest a causative role of lipid accumulation in PICM. Even in non-pacemaker-implanted patients, such as patients with diabetes mellitus and obesity, abnormal intramyocardial lipid accumulation has been frequently observed owing to metabolic changes in the heart. In addition, cardiac lipid accumulation is positively correlated with cardiac dysfunction, which is called lipotoxic cardiomyopathy34. Taking these findings into consideration, we believe that cardiac metabolic modulation due to RV pacing plays an important role in the impairment of cardiac function.Moreover, the lipid-lowering and pleiotropic effects of treatment with statins are attributed to preventing PICM and reducing HF hospitalization, cardiovascular death, and all-cause mortality in patients with AVBOur results could help to identify patients who develop PICM before PMI. Severe renal dysfunction and a history of CAD could be independent risk factors for PICM. Therefore, patients with these risk factors require closer follow-up by TTE to avoid missing the appropriate timing for upgrading to cardiac resynchronization therapy. Furthermore, conduction system pacing, such as His-bundle pacing and left-bundle pacing, are alternative options in patients with AVB and high-risk factors when they undergo PMI.Our study has some limitations. First, this was a retrospective study from a single center with a comparatively small number of participants, and it did not reflect direct causation. Second, measurement with TTE was performed among not all patients with pacemaker, and the time window for performing follow-up TTE was unclear. Our observational periods for the occurrence of PICM were not long term but medium term instead. Third, PMI procedures in the current study likely included some older materials and methods, and our data lacked information on the lead tip position. Finally, further studies regarding the effects of CAD and CKD on the incidence of PICM after PMI are required to confirm our findings.A past medical history of CAD and severe stage CKD, stage 4 or 5, at PMI are newly discovered risk factors of PICM. Therefore, intensive follow-up is required to detect a deterioration in the LVEF at an early stage.Supplementary Table 1.


Plasma biomarkers have emerged as a promising approach for characterizing pathophysiology in mild cognitive impairment (MCI) and Alzheimer’s disease (AD).We aimed to characterize plasma biomarkers for AD and neurodegeneration across the AD clinical continuum, and to assess their ability to differentiate between AD, MCI, and normal cognition.This population-based study engaged 1,446 rural-dwelling older adults  derived from MIND-China; of these, 402 were defined with MCI and 142 with AD. Plasma amyloid-β (Aβ), total tau (t-tau), and neurofilament light chain (NfL) concentrations were analyzed using the Simoa platform. Data were analyzed using linear and logistic regression models, and receiver operating characteristic (ROC) analysis.40 and NfL increased, whereas Aβ42/Aβ40 ratio decreased. Plasma t-tau was higher in people with AD dementia than those with MCI or normal cognition. Plasma NfL outperformed other biomarkers in differentiating AD from normal cognition (area under the ROC curve [AUC] = 0.75), but all plasma biomarkers performed poorly to distinguish MCI from normal cognition (AUC <0.60). Plasma NfL in combination with age, sex, education, and APOE genotype yielded the AUC of 0.87 for differentiating between AD and normal cognition, 0.79 between AD and MCI, and 0.64 between MCI and normal cognition.Across the AD clinical spectrum, plasma AβAPOE genotype. Plasma Aβ, t-tau, and NfL differ across the AD clinical spectrum, and plasma NfL appears to be superior to plasma Aβ and t-tau for defining the clinical spectrum.In this Chinese population, AD plasma biomarkers vary by age, sex, and  Amyloidneration .40 and NfL, and higher plasma t-tau levels compared to non-Hispanic whites [Several studies have shown that plasma concentrations of AD biomarkers may vary substantially across ethnoracial groups . For exac whites . In addic whites . Howeverc whites . Explorin = 300) showed that plasma Aβ42/Aβ40 ratio, t-tau, and NfL had poor ability to detect clinical AD (AUC <0.6) [The distributions of AD plasma biomarkers across AD clinical spectrum were described in only a few population-based studies. For instance, the Mayo Clinic Study of Aging reported higher plasma t-tau in people with AD than those with normal cognition or MCI, but no difference between normal cognition and MCI . The comUC <0.6) . HoweverAPOE) genotype; 2) examine the associations of these biomarkers with the clinical spectrum from normal cognition through MCI to clinical AD; and 3) evaluate the performance of these biomarkers to differentiate individuals with normal cognition, MCI, and AD.Therefore, in this population-based study of rural-dwelling older adults, we aimed to 1) describe the distribution of plasma Aβ, t-tau, and NfL by demographics and apolipoprotein E  were measured in a subsample of 1,304 dementia-free participants who were living in the 18 villages that were randomly selected from the 52 villages plus 142 persons who had blood samples and were diagnosed with AD in all MIND-China participants  , those in the plasma biomarker substudy  were slightly younger  and more likely to be women , but the two groups did not differ significantly in educational level.This population-based study used data from a subsample of participants in the baseline assessments of the Multimodal Interventions to Delay Dementia and Disability in Rural China (MIND-China) study, as previously described . In brieillages) . CompareThe MIND-China project was approved by the Ethics Committee at Shandong Provincial Hospital affiliated to Shandong University in Jinan, Shandong. Written informed consents were obtained from all participants, or in case of people with severe cognitive impairment, from informants. This study was carried out in accordance with the ethical principles expressed in the Declaration of Helsinki. MIND-China was registered in the Chinese Clinical Trial Registry (Registration No: ChiCTR1800017758).APOE genotype. Definitions, assessments, and categorizations of covariates are described elsewhere [Following a structured questionnaire, the trained medical staff collected data through face-to-face interviews, clinical examinations, neuropsychological testing, and laboratory tests, which included sociodemographic features , behavioral factors , metabolic factors , health conditions , use of medications , and lsewhere  and provCognitive function was evaluated using a neuropsychological test battery, as previously reported . In brieThe diagnostic procedure of AD and MCI in the MIND-China study has been described elsewhere . In brie42 and Aβ40, t-tau (Human Neurology 3-Plex A assay), and NfL (NF-light® advantage Kit) at the laboratory of Wayen Biotechnologies Inc., Shanghai, China. Two quality control plasma samples were run in duplicate on each plate for each analyte. The intra-assay coefficient of variation and the inter-assay coefficient of variation were all below 13.0% for the control sample.After an overnight fast, peripheral blood samples were drawn into ethylene diamine tetraacetic acid (EDTA) citrate vacutainer tubes and centrifuged in a tabletop centrifuge. Plasma samples were then aliquoted and stored at –80°C until retrieved and thawed on ice. Plasma biomarkers were measured using the Single molecule array (Simoa) platform  for Aβ40 and NfL were natural log-transformed to reduce skewness. Outliers (>5 SDs above the mean of the whole sample) were excluded from the main analysis. We compared characteristics of study participants among normal cognition, MCI, and AD groups using Kruskal-Wallis tests for continuous variables with skewed distribution, and chi-square test for categorical variables. Spearman’s rank order correlation was used to assess correlations between plasma biomarkers . We used the general linear regression models to examine the associations of demographic factors and APOE genotype with plasma biomarkers in the total sample and among dementia-free individuals as previously reported [APOEɛ4 allele on the likelihood of MCI and AD. Stratifying analysis was then performed when a statistical interaction was detected. We presented the main results from two models: model 1 was adjusted for age, sex, and education, and model 2 was further adjusted for body mass index, smoking, alcohol drinking, estimated glomerular filtration rate , hypertension, diabetes, dyslipidemia, coronary heart disease, stroke, and APOE genotype. In addition, we used ROC analysis to assess the ability of plasma biomarkers to differentiate between diagnostic groups. Youden index was used to determine optimal sensitivity and specificity. Differences in AUCs were evaluated using Bootstrap test with N = 2000 repetitions [APOE genotype could improve the diagnostic accuracy.We conducted descriptive statistical analysis to report means (SD) for continuous and frequency (%) for categorical variables. Plasma Aβreported . Multinoetitions . We usedWe used SAS version 9.4  and R version 4.1.3 for Windows  for all the data analyses.42/Aβ40 ratio, and higher plasma Aβ40 and NfL concentrations (p < 0.05)   were defined with MCI and 142 (9.8%) were diagnosed with AD dementia. The mean age of all participants was 70.22 years (SD 5.30), 61.0% were women, and 40.3% were illiterate . Compare < 0.05) . In addi < 0.05) . The thr40 with Aβ42 (r = 0.57), t-tau (r = 0.30), and NfL (r = 0.27), of plasma Aβ42 with t-tau (r = 0.15) and NfL (r = 0.20), of plasma Aβ42/Aβ40 ratio with t-tau (r = –0.14) and NfL (r = –0.07), and of plasma t-tau with NfL (r = 0.20)   .40, Aβ42, t-tau, and NfL, but not Aβ42/Aβ40 ratio, increased with advanced age   . In addied model . Educati factors .40, Aβ42, and NfL with increased age remained statistically significant, but the correlation between plasma t-tau and advanced age became statistically non-significant  (p < 0.01). In addition, participants with MCI showed higher plasma Aβ40 and NfL, and a lower Aβ42/Aβ40 ratio than those with normal cognition (demographic-adjusted p < 0.01)  had higher plasma Aβ < 0.01) . Partici < 0.01) . Same re40 and NfL, and a lower Aβ42/Aβ40 ratio were significantly related to a higher likelihood of MCI after controlling for demographic factors , such that a higher Aβ42/Aβ40 ratio was significantly associated with a lower odds ratio of AD among APOEɛ4 allele non-carriers , but not among APOEɛ4 allele carriers .In addition, we detected statistical interactions of plasma AβOf all the examined plasma biomarkers, plasma NfL showed the highest AUC value for differentiating between AD and the combined non-dementia groups  , normal cognition , and MCI  , but not for differentiating between MCI and normal cognition (p for bootstrap test >0.05)  .APOE genotype such that older age was associated with higher plasma Aβ40, Aβ42, t-tau, and NfL; that women had higher plasma Aβ42 but lower NfL than men; and that APOEɛ4 carriers had lower plasma Aβ42 and Aβ42/Aβ40 ratio than non-carriers; 2) plasma Aβ40, t-tau, and NfL concentrations increased while the Aβ42/Aβ40 ratio decreased from normal cognition through MCI to AD; and 3) plasma NfL outperformed all other examined biomarkers in distinguishing people with AD dementia from those with MCI or with normal cognition.In this population-based study of rural-dwelling older adults in China, we characterized the plasma biomarkers of amyloid and neurodegeneration associated with the cognitive continuum from normal cognition through MCI to AD and further evaluated diagnostic performance of the plasma biomarkers. The main findings can be summarized as follows: 1) plasma Aβ, t-tau, and NfL varied by age, sex, or 40, Aβ42, t-tau, and NfL with advanced age was consistent with the reports from the Mayo Clinic Study of Aging [The increase in plasma Aβof Aging  and the of Aging . From thof Aging . The ageof Aging .Previously, the population-based studies and the meta-analysis revealed higher plasma and CSF NfL concentrations in men than in women , which wAPOEɛ4 allele was associated with lower plasma Aβ42 and Aβ42/Aβ40 ratio but not with plasma Aβ40, consistent with the findings from the Rotterdam study [42, the primary component of amyloid plaque, is more likely to aggregate than Aβ40. In addition, the apoE4 protein, coded by the ɛ4 allele variant of the APOE gene, is known to influence the Aβ aggregation or clearance process rather than the process of Aβ peptide production [In addition, we found that am study  and a geam study . The Aβ4oduction .40 increased and the Aβ42/Aβ40 ratio decreased, whereas there was no difference in plasma Aβ42. This was consistent with the Atherosclerosis Risk in Communities Neurocognitive study, which reported that higher plasma Aβ40 and lower plasma Aβ42/Aβ40 ratio in midlife and late-life were associated with MCI and dementia and that lower plasma Aβ42 at midlife, but not late-life, was related to MCI or dementia [42 levels were reported in people with cognitive impairment [42 levels might increase in the pre-pathological stage of AD and then decrease with progression of the disease [42 levels may decline into normal ranges in the clinical phase. Thus, plasma Aβ measured at different stages of AD may partly interpret the discrepancies. Furthermore, we found that plasma t-tau concentration was higher in people with AD than those with MCI or normal cognition, which was in line with the report from the Mayo Clinic Study of Aging [We found that across the AD clinical spectrum, plasma Aβdementia . Howeverpairment . In addiof Aging . This suof Aging . Our datof Aging , which s42/Aβ40 ratio might reflect more Aβ aggregation in the brain. Indeed, recent cohort studies showed that plasma Aβ42/Aβ40 ratio could be used to identify people with abnormal CSF or PET amyloid status [42/Aβ40 ratio was associated with a high load of cerebral AD pathology [42/Aβ40 ratio was not sensitive in differentiating cognitive phenotypes in old age. This may be related to the very low effect size (fold change) in amyloid positive versus negative individuals, resulting in a low robustness for this blood biomarker [42/Aβ40 ratio when detecting Aβ pathology in the brain [APOE genotype appeared to be powerful in differentiating AD from normal cognition, which is in line with the reports from the ADNI study [A lower plasma Aβathology . Howeveriomarker . Indeed,iomarker . In addiiomarker , and thehe brain . Plasma he brain , probablhe brain . Plasma NI study  and a coNI study .In this population-based study, we characterized plasma amyloid and neurodegenerative biomarkers across the AD clinical spectrum and assessed their accuracy for differentiating between normal cognition, MCI, and AD among rural-dwelling older adults in China, a sociodemographic group that has been largely ignored in Alzheimer research. Furthermore, we used the state-of-the-art Simoa platform to measure plasma biomarkers. However, our study also has limitations. First, we did not have data of highly sensitive and specific plasma biomarkers for tau pathology . Furthermore, we did not have data on biomarkers related to amyloid, tau, and neurodegeneration (ATN) in central nervous system, which are more reliable than peripheral AD-related biomarkers to define pathological features of AD. Finally, our study sample was derived only from only one rural area in China, which should be kept in mind when generalizing the study findings to different populations.APOE genotype and across the AD clinical spectrum. Notably, plasma NfL increased across the continuum from normal cognition to prodromal and clinical AD dementia and could be a valuable biomarker for detecting AD in older adults. Further longitudinal studies are required to evaluate the trajectory of these plasma biomarkers in defining the AD cognitive continuum and their prognostic ability in predicting dynamic evolution of cognitive traits.In conclusion, plasma amyloid, t-tau, and NfL concentrations vary with age, sex, and Click here for additional data file.


The aim was to conduct a systematic review and meta-analysis for assessing the effectiveness and safety of dietary polyphenol curcumin supplement on metabolic, inflammatory, and oxidative stress indices in patients with metabolic syndrome (MetS).A comprehensive search for clinical trials was conducted in the following scientific databases: PubMed, SCOPUS, Cochrane Library, EMBASE, Web of Science, and China Biological Medicine. Randomized controlled trials (RCTs) evaluating the efficacy and safety of curcumin supplement for MetS were identified. A random-effects meta-analysis was performed using inverse variance, and efficacy was expressed as mean difference (MD) with 95% confidence interval (CI). The metabolic syndrome markers that were evaluated in the present study included waist circumference (WC), fasting blood sugar (FBS), systolic blood pressure (SBP), diastolic blood pressure (DBP), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), tumor necrosis factor-a (TNF-a), interleukin 6 (IL-6), C-reactive protein (CRP), ultrasensitive c-reactive protein (hsCRP), and malondialdehyde (MDA). By employing the Cochrane tool, RCTs were assessed for bias risk.p = 0.009, seven studies), FBS , DBP , HDL-C , TNF-a , CRP , and MDA . These improvements were statistically significant. Meanwhile, there was no significant improvement in SBP , TG , IL-6 , or hsCRP . FBS, SBP, HDL-C, IL-6, CRP, hsCRP, and MDA had a relatively high heterogeneity.A total of 785 participants from 13 RCTs were included, with intervention durations ranging from 4 to 12 weeks. Compared with the control group, the curcumin group had positive effects on WC (MD = -2.16, 95% CI: -3.78 to -0.54, Curcumin exhibited promising potential in enhancing markers associated with metabolic syndrome, including inflammation. However, additional studies are required to confirm such findings since the included evidence is limited and has a relatively high heterogeneity.https://www.crd.york.ac.uk/prospero, identifier CRD42022362553. The National Cholesterol Education Program Adult Treatment Panel III (NCEP: ATPIII) and the International Diabetes Federation (IDF) are prominent organizations dedicated to addressing issues related to cholesterol and diabetes. At present, the two most extensively adopted definitions are those of the IDF and NCEP: ATP III . The criAbdominal adiposity is highly correlated to increased morbidity and mortality . AdditioCurcumin, a natural plant-based dietary polyphenol, is an active ingredient derived from turmeric from the ginger family. Curcumin has anti-inflammatory, anti-oxidant, anti-diabetic, and anti-atherosclerotic properties –10, whicIn previous research, curcumin supplementation has been reported to improve obesity-related indices, fasting glucose, and lipids in metabolic diseases such as obesity, fatty liver, and MetS –18. A pr2The Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) 2020  standard2.1From the outset through June 2022, six electronic databases—PubMed, SCOPUS, Cochrane Library, EMBASE, Web of Science, and China Biological Medicine (CBM)—were thoroughly searched. The terms used included the following: “curcumin” or “turmeric yellow” or “yellow, turmeric” or “curcumin phytosome” or “curcuminoid” or “curcuma” or “curcuminoid supplement” or “curcumin extract” and “metabolic syndrome” or “metabolic syndromes” or “syndrome, metabolic” or “syndromes, metabolic” or “metabolic syndrome X” or “insulin resistance syndrome X” or “syndrome X, metabolic” or “syndrome X, insulin resistance” or “metabolic X syndrome” or “syndrome, metabolic X” or “X Syndrome, metabolic” or “dysmetabolic syndrome X” or “Reaven syndrome X” or “syndrome X, Reaven” or “metabolic cardiovascular syndrome” or “cardiovascular syndrome, metabolic” or “syndrome, metabolic cardiovascular” or “cardiometabolic syndrome” or “cardiometabolic syndromes” or “syndrome, cardiometabolic” or “insulin resistance syndrome x” or “insulin resistance” or “metabolic diseases” or “plurimetabolic syndrome” or “syndrome x plus”, and “randomized controlled trial” or “randomized” or “placebo” or “RCTs”. In order to include any relevant studies that may not have been captured in the initial database search, a thorough examination of the reference lists of potentially eligible literature was conducted.2.2The studies included in the present analysis met the following inclusion criteria (1): participants of both genders aged 18 years or older, (2) diagnosed with metabolic syndrome according to either NCEP-ATP III or IDF guidelines , (3) evaThe following exclusion criteria were applied: (1) trials without specific restrictions, (2) studies with a duration of less than 4 weeks, (3) participants taking antihypertensive, antidyslipidemic, or antidiabetic medications, (4) insufficient data reported in the included studies, and (5) participants with malignancies or other systemic or chronic diseases unrelated to diabetes.2.3After removing any duplicate entries, two reviewers individually evaluated the remaining records for qualification using the titles and abstracts. Subsequently, the reviewers individually selected potentially eligible literature in full text for inclusion in the present study. The title of the initial author, the publishing year, the location, the number of participants (in the intervention and placebo arms), the MetS diagnostic criteria, the participants’ ages and genders, the intervention dose, the length of the study, the reported side effects, and the results were all extracted by two reviewers.Using the method suggested by the Cochrane Handbook V.5.1.0 , two wri2.4p-value less than 0.05 was regarded as statistically significant. The heterogeneity was assessed by inconsistency(I2) and chi-square tests. High heterogeneity between studies was considered when the heterogeneity p <0.1 and I2 ≥ 50%. Conversely, low heterogeneity was considered when these criteria were not met. By removing one study at a time and redoing the analysis, a sensitivity analysis was performed. Subgroup analyses were also conducted by sample size and intervention duration based on the features of the included studies.Review Manager was used for every analysis  . In comp33.1The explicit research screening process is shown in 3.2n = 10) accounted for the majority of the trials, followed by Pakistan (n = 1), China (n = 1), and Italy (n = 1). The total sample size included 785 MetS participants . Two cohorts contained exclusively male ; hence, a fixed-effects model was used. The outcomes demonstrated that, as a consequence of reducing WC, the intervention group surpassed the control group   Figure 33.4.2p = 0.0005, I2 = 71%) and therefore used a random-effects model. The findings demonstrated that the experimental group fared better in decreasing the FBS than the placebo group   Figure 43.4.3p = 0.002) .A fixed-effects model was used to analyze the results, which revealed that the intervention group outperformed the control group in lowering the diastolic blood pressure  Figure 5= 0.002) , 39, 41 p = 0.0004, I2 = 78%) and therefore used a random-effects model. According to the findings, curcumin had a negligible impact on SBP   Figure 63.4.4p = 0.21, I2 = 27%). As such, the results of a fixed-effects model demonstrated that curcumin’s influence did not significantly lower the TG   Figure 73.4.5p = 0.001, I2 = 71%). By employing a random-effects model, the data indicated that the intervention group had a more pronounced effect in increasing HDL cholesterol levels compared with the placebo group   Figure 83.4.6p = 0.02, I2 = 81%). Thus, the results of a model with random effects showed that curcumin had no discernible impact on IL-6  . After employing a model with random effects, the outcomes revealed that the intervention group surpassed the control group in lowering the TNF-a  (The tumor necrosis factor-a (TNF-a) results from two trials , 40 repop = 0.58, I2 = 0%), a fixed-effects model was used. The findings indicated that the intervention group exhibited a greater reduction in CRP levels compared with the control group   in the results for ultrasensitive C-reactive protein (hsCRP). After employing a model with random effects, the findings revealed that the effect of curcumin did not significantly alter the hsCRP   in the results for malondialdehyde (MDA). Using a random-effects model, the results showed that the intervention group was superior to the control group in reducing MDA   had a notable influence on the heterogeneity of the FBS and SBP outcomes. However, after removing the study from the analysis, the heterogeneity became non-significant . The evidence was categorized as “moderate”, “low”, or “very low” based on specific reasons for downgrading, such as a high risk of bias, inconsistency, and imprecision. The detailed ratings and reasons for downgrading can be found in 4The effects of curcumin supplementation on WC, FBS, BP, TG, and HDL levels and inflammatory markers  in MetS patients were assessed by analyzing 13 randomized controlled trials. The minimum duration of the studies was 4 weeks, and the maximum duration was 12 weeks. The results of the present study show significant improvements in WC, FBS, DBP, HDL, and inflammatory markers (TNF-a and CRP) levels. However, there were no significant changes observed in SBP, TG levels, IL-6, and hsCRP.In comparison with a previous systematic evaluation , the preFurthermore, the impact of curcumin administration on MetS inflammatory and oxidative stress biomarkers was thoroughly examined. A previous systematic review found that curcumin supplementation improved the inflammation and oxidative stress in obesity, diabetes, and NAFLD . HoweverCurcumin is significant for the improvement of inflammatory and oxidative stress indicators. While the exact pathophysiology of metabolic syndrome remains unclear, there are widely acknowledged potential pathways that contribute to its development. Such pathways include insulin resistance and the presence of chronic low-grade inflammation, which are commonly associated with central obesity , 54. Chr2), among others, which, in turn, regulate local and systemic inflammation  was not excluded. Fifth, the limited amount of research available did not allow for a breakdown of the dosage of curcumin utilized in the smaller groups. Sixth, one of the studies included in the analysis used a combination of curcumin and black seed extract. Nigella sativa seed extract had a beneficial effect on MetS, which may have caused a bias in the analysis.5The present meta-analysis demonstrates that curcumin supplementation has a positive impact on MetS patients. Future randomized controlled studies should focus on addressing the limitations identified in the present analysis. Future research should aim to include larger sample sizes that encompass diverse ethnic groups, consider gender differences, and explore various forms of curcumin supplements to ensure high bioavailability. In addition, more thorough research is required to determine how curcumin affects inflammatory and oxidative stress indicators in metabolic syndrome. Further exploration is needed to better understand the mechanisms by which curcumin may be effective in treating metabolic syndrome.LQ and JZ conceptualized the research question. CG and YR participated in drafting and writing the review. CG, HW, and YR participated in the formulation of retrieval strategies, data acquisition, data analysis, and quality assessment. JL and ML participated in the drawing of tables and figures. XD and WL participated in the critical revision of the manuscript. All authors contributed to the article and approved the submitted version.


The Mediterranean area is especially rich in old, both sweet and pungent, varieties of onion. The synthesis of phytochemicals takes place concurrently with the overall development and maturation of vegetables; however, it is unclear whether there is a correlation between onion bulb size and antioxidant compound content, antioxidant capacity, and nutritional parameters and what the origin of these variations is. The aim of this work was to investigate the biochemical and nutritional aspects of the sweet onion landrace “Premanturska kapula”, as well as to investigate the influence of onion bulb size on onion phytochemical and nutritional profile. The sweet onion landrace “Premanturska kapula” has a high soluble sugar content, a high antioxidant capacity, and a high phenolic compound content. Quercetin-3,4′-diglucoside and quercetin-4′-glucoside were the major flavonols, while protocatehuic acid was the major phenolic acid detected. The choice of onion bulb size can impact the profile of the sugars present, with large bulb sizes favoring higher sucrose and fructooligosaccharides content compared to small bulb sizes which were more abundant in glucose. The total sugars or bulb dry matter were not affected by bulb size. Phenolic compounds were more abundant in smaller bulb sizes, thus indicating a link between bulb development and phenolic compound allocation within the plant. This link possibly derived from agronomic practices such as bare-root transplants, or even open pollination which causes a broader genetic variability. From a consumer perspective, it can be a choice between the small and medium bulb sizes on one hand, which are more abundant in polyphenolics and simple sugars, or on the other hand, the larger bulbs which are more abundant in fructooligosaccharides known to carry excellent health benefits. Allium cepa L.) is a biennial plant and the bulb that it produces serves as an overwintering stage in its life cycle [Allium is large and consists of many wild and edible species besides onion, such as garlic, leek, chive, and shallots [Onion yl-L-cysteine sulfoxides into other organosulfur compounds, pyruvic acid, and ammonia during tissue damage . The balO-glucoside was the main form of isorhamnetin found in onions [p-coumaric, ferulic, caffeic, syringic, p-hydroxybenzoic, and vanillic acids [Onions are a rich source of dietary flavonoids and phenolic acids, which are a part of the polyphenols family and possess effective antioxidant activity and metal chelating properties ,17,18. Fn onions . Phenoliic acids . The redBulb size and maturity are important characteristics of onion crops. Previous studies have reported that during the period of bulb development and maturation, glucose, fructose, and sucrose content increased ,25. LeveThe synthesis of many phytochemicals takes place concurrently with the overall development and maturation of vegetables ; howeverConsumers are showing preference for locally produced crops which are characterized by particular sensory or quality characteristics, such as sweet onions. The sweet onion landrace “Premanturska kapula” is traditionally produced in a niche geographical area at the very south end of the Istrian peninsula in Croatia, Cape Kamenjak. The name, “Premanturska kapula” comes from its geographical place of origin, village “Premantura”. According to the locals, this sweet onion landrace was cultivated in the mentioned area for more than 60 years and is characterized by a sweet and mild flavor and large bulbs. It is usually grown as an over-wintering crop without irrigation . Therefore, the aim of this work was to investigate the differences in the phytochemical and nutritional profile between small, medium, and large sized onion bulbs, as well as the biochemical and nutritional aspects of the sweet onion landrace “Premanturska kapula”.Onion bulbs were kindly provided by a local producer situated in the area of Premantura, Istarska County, Croatia.Twelve bulbs, without signs of pests and disease damage or physiological disorders, were selected from approximately fifty provided bulbs of each size and divided into three groups consisting of four bulbs. The groups were divided, according to bulb size, into large , medium , and small bulbs .Allium spp. [Alongside the chemical analyses made in this study, a morphological description was also made on the same 12 bulbs, using ECPGR descriptor for ium spp. . SeveralBulb shape was described as flat or flat globe (50% and 50%); bulb skin color was mostly a mixture of violet and brown color (66% of bulbs regardless of size); bulb skin thickness was thin (100%); the observed bulb flesh color was a mixture of violet and white in all bulbs (100%); and 92% of observed bulbs had 2–3 bulb hearts. Furthermore, bulbs were weighed, and bulb height and diameter were measured using a digital caliper.Based on the evaluation of the morphological characteristics of the bulbs collected in the area of Premantura, they were classified as the sweet onion variety “Istarski crveni”(Istrian red), which is listed as a Protected Variety on the Variety List of the Republic of Croatia. However, given the specific agro-pedological conditions that prevail in the area of Premantura and the long tradition of cultivation, producers consider it a local landrace and specific product.® EZ 4500 Portable Spectrophotometer . Color measurements were analyzed by considering the CIE  L*a*b* color spaces. In the three-dimensional color space, L* represents lightness . The coordinate a* represents redness, i.e., the red to green axis, with positive a* being red, and negative a* green. Coordinate b*, i.e., yellowness, represents the yellow to blue axis with positive b* being yellow, and negative b* being blue. Color evaluation was performed on each bulb size group on different layers of the onion bulb. Firstly, the outer dry onion peel from each bulb was removed, put on white paper so that the rest of the onion bulb layers do not interfere with the color values due to the transparency of the dry layers, and captured with the device five times,. The first outer bulb flesh layer was measured two times for each bulb. The inner bulb flesh color was measured in horizontal cross section, three times for each bulb.Onion bulb color was measured by a MiniScang for 10 min  and subsequently filtered through a 0.22 µm nylon filter into HPLC vials. The extracts were kept at −80 °C until further analysis. Dry matter was determined gravimetrically in triplicate by drying the samples in an oven  at 105 °C until a consistent weight was obtained.The selected bulbs were flash frozen in liquid nitrogen, lyophilized , and milled to 0.2 mm with an ultra-centrifugal mill . The extraction was performed according to Major et al.  by sonic2 = 0.9999) and expressed as mg GAE/g DW.The Folin–Ciocalteu assay  was usedTotal antioxidant activity was evaluated using the DPPH radical scavenging activity assay  and the Both DPPH and FRAP values were calculated against a Trolox calibration curve  and expressed as µmol TEQ/g DW.The content of inulin, sucrose, glucose, and fructose in onion bulbs was determined by HPLC, which consisted of an autosampler , a solvent delivery unit , a thermostatic column compartment , and a refractive index detector . Sugar separation was achieved by injecting 10 µL of the sample into a calcium ion exchange column  held at 80 °C using deionized water as the mobile phase . The identification and quantification of the investigated sugars were performed by comparing retention times and peak areas to analytical standards. The calibration curves were created by injecting serial dilutions of the investigated sugars .The phenolic profile was analyzed on an LC-MS/MS, which consisted of an autosampler , two solvent delivery units , a thermostatic column compartment  and a triple quadrupole mass spectrometer . The separation was performed on a C18, 2.1 mm × 150 mm, 2.7 µm core–shell column  held at 37 °C by injecting 1 µL of the sample using a linear gradient elution of mobile phase A (water/0.1% acetic acid) and mobile phase B (methanol/0.1% acetic acid) at 0.35 mL/minute, for 0 min to 0.75 min: 98%A; 0.75 min to 15 min: 98%A to 50%A; 15 min to 15.1 min: 50%A to 0%A; 15.1 min to 20 min: 0%A; 20 min to 20.1 min: 0%A to 98%A; and 20.1 min to 25 min: 98%A. The polyphenolic compounds were identified and quantified by using analytical standards, except for quercetin-3,7-diglucoside, and isorhamnetin-4′-glucoside which were tentatively identified by LC-MS/MS, using the characteristic precursor/product ions obtained by the fragmentation of quercetin-3,4′-glucoside and isorhamnetin-3-glucoside analytical standards, respectively. Quercetin-3,7,4′-triglucoside was identified using theoretical precusor/product ions.p ≤ 0.05 and homogenous group means were compared by Fischer’s Least Significant Difference post hoc test. The developed PLS-DA model was employed to investigate the discrimination power of individual phytochemical and nutritional parameters in onion bulb size differentiation.The analyses in this study were performed in three biological repetitions. The obtained data were analyzed by analysis of variance (ANOVA) and Partial Least Square Discriminant Analysis (PLS-DA) using Statistica 13.4 . Significant differences were determined at The sweet onion landrace “Premanturska kapula” was characterized by an average dry matter content of 7.33 ± 0.13 g/100 g of fresh bulb . The aveThe total bulb phenolic content was on average 3270 ± 327 µg GAE/g DW with an antioxidant capacity of 3.00 ± 0.66 µmol TE/g DW, 4.86 ± 0.50 µmol TE/g DW, and 79.8 ± 7.1 µmol TE/g DW for DPPH radical scavenging, FRAP, and ORAC, respectively.The calculated sum of total phenolics from individual phenolic compounds was, on average, 4572 ± 703 µg/g DW with a minimum of 3587 and the maximum of 5392 µg/g DW. The most abundant flavonoid compounds were quercetin-3,4′diglucoside and quercetin-4′-glucoside with average values of 2272 ± 306 µg/g DW and 1210 ± 205 µg/g DW, respectively. Another important flavonoid compound in the investigated sweet onion landrace is isorhamnetin-4′-glucoside with an average content of 271 µg/g DW. The most abundant phenolic acid was protocatehuic acid with an average value of 729 ± 151 µg/g DW. Minor phenolic compounds detected in the investigated sweet onion cultivar were quercetin-3-glucoside (50.2 ± 10.2 µg/g DW), quercetin-3.7-diglucoside (26.4 ± 4.4 µg/g DW), vanillic acid (2.55 ± 0.44 µg/g DW), and quercetin (2.46 ± 0.35 µg/g DW).The dry matter, total sugars, or bulb fructose content were not influenced by bulb size . On the The total phenolic content was significantly higher in the medium compared to large or small bulb sizes, as was the antioxidant capacity measured by the DPPH radical scavenging assay. The FRAP or ORAC assays for antioxidant capacity did not show differences between bulb sizes.The sum of the targeted phenolic compounds was, on the other hand, significantly lower in the large compared to medium and small bulb sizes, as was the case with the most abundant flavonoid compounds quercetin-3,4′-diglucoside and quercetin-4′-glucoside . Other mThe lightness (L) of the sweet onion bulb was significantly lower in the medium onion bulb size compared to the large or small bulb sizes . The greThe developed PLS-DA model showed that the most important parameters in the discrimination between the investigated bulb sizes in descending order of importance were total phenolic content, sucrose, isorhamnetin-4′-glucoside, sum of phenolics, quercetin-3-glucoside, vanillic acid, quercetin-3,7,4′-triglucoside, and glucose . The totThere are many well-known sweet onion varieties and cultivars used in agriculture worldwide, such as the best-known variety “Vidalia Sweet Onion” and its cultivars “Nirvana”, “DPS 1032”, “Yellow 2025”, “king-Midas”, and “SBO 133” .Common onion bulbs have dry matter values ranging from 6 to 25%, with values lower than 15% being characteristic for sweet onion cultivars . The CroAccording to the USDA , sweet oAccording to Loredana et al. , the fouThe average total phenolic content obtained via colorimetric assay (TPC) for the “Premanturska kapula” was 3270 µg GAE/g DW. Several authors ,43,44 reAs the content of flavonoids in plants is affected by the combination of genotype, environmental conditions, and agronomic practices, different strategies can be applied in order to obtain foods enriched in antioxidant compounds, thus increasing their functional value . Color iThe identified flavonoids in our study are in line with the findings of Vågen and Slimestad , and HedIn the study by Vågen and Slimestad , the sweQuercetin-3,7-diglucoside and quercetin-3,7.4′-triglucoside have been identified in onions and are considered to be minor flavonols ,52,53. OSharma et al.  reportedProtocatehuic acid content for “Premanturska kapula” averaged at 729 µg/g DW, while the white onion variety “Armstrong” used in the study by Gorinstein et al.  averagedSellapan and Akoh  reportedThe maturity and bulb size is dependent on several factors, including the onion genotype, photoperiod sensitivity, planting density, nutrient and water availability, temperature, agronomic practices such as planting density or stalk removal, as well as the harvest time ,59,60. ADuring the early stages of onion bulb development, the primary source of carbon and energy for growth comes from leaf photosynthesis . Sugars Onion bulbs are well known for their abundance in phytochemical compounds which have high antioxidant capacity. Our results showed that the antioxidant capacity measured by the DPPH radical scavenging assay, as well as all the investigated phenolic compounds except for quercetin and vanillic acid, were significantly lower in content on dry weight basis in the large compared to medium or small bulb size. Antioxidant capacity measured by ORAC and FRAP did not differ between onion bulb sizes. Lachowitz et al. investigated the antioxidant capacity of wild garlic and showed that although bulb total phenolic content increases with bulb maturity the antioxidant capacity is actually lower in more mature bulbs . Lee et According to Golubkina and Caruso , geneticThe difference in phenolic compounds content between large and smaller bulb size could be explained by the initial bioaccumulation of polyphenolic compounds in the bulb and the subsequent unequal development in bulb size. As shown by Cheng et al., the highest polyphenol content in both yellow and red onion cultivars is located in the older, outer bulb layers  indicatiSweet onion varieties, known also as mild onions, are very popular for fresh consumption and the demand for these onions has increased in recent years. At the same time, the food market is constantly searching for new onion varieties, and domestic varieties have quality parameters that can meet consumer demand. The sweet onion landrace “Premanturska kapula” has a high soluble sugar content as well as a high antioxidant capacity and phenolic compound content compared to similar cultivars. Quercetin-3,4′-diglucoside and quercetin-4′-glucoside were the major flavonols, while protocatehuic acid was the major phenolic acid detected. The choice of onion bulb size can impact the profile of the sugars present, with the large bulb size favouring a higher sucrose and fructooligosaccharides content compared to small bulb sizes which were more abundant in glucose. However, the total sugars or bulb dry matter were not affected by bulb size. Phenolic compounds were more abundant in smaller bulb sizes, thus indicating a link between bulb development and phenolic compound allocation within the plant. From a consumer perspective it can be a choice between the small or medium bulb size, which are higher in polyphenolic content and simple sugars, or the larger sized bulbs which offer the same polyphenolic profile but are less abundant, with a reduced simple sugar content in favor for soluble fructooligosaccharides which are known to carry excellent health benefits.