This systematic review aimed to identify early pregnancy measures of adiposity associated with adverse maternal health outcomes. Searches included six databases, reference lists, citations, and contacting authors. Screening and quality assessment were carried out by two authors independently. Random effects meta‐analysis and narrative synthesis were conducted. Seventy studies were included with a pooled sample of 89,588 women. Meta‐analysis showed significantly increased odds of gestational diabetes mellitus (GDM) with higher waist circumference (WC) categories  and per unit increase in WC . Women with GDM had higher WC than controls . WC was significantly associated with hypertensive disorders, delivery‐related outcomes, metabolic syndrome, and composite pregnancy outcomes. Waist to hip ratio was significantly associated with GDM, hypertensive disorders, and delivery‐related outcomes. Fat mass, neck circumference, skinfolds, and visceral fat were significantly associated with adverse outcomes, although limited data were available. Our findings identify the need to explore how useful adiposity measures are at predicting risk in pregnancy, compared with BMI, to direct care to women with the greatest need.Maternal obesity increases pregnancy‐related risks. Women with a body mass index (BMI) ≥ 30 kg/m BMIbody mass indexCIconfidence intervalFFMfat‐free massFMfat massGDMgestational diabetes mellitusMDmean differenceMOOSEMeta‐analysis Of Observational Studies in EpidemiologyORodds ratioSFTskinfold thicknessWCwaist circumferenceWHRwaist to hip ratio12, has increased in recent decades. In the United Kingdom, recent data published in 2021 suggest that 22% of women start their pregnancy with a BMI in the obese range,2 for GDM, primarily due to lack of capacity to do so given the high prevalence of maternal obesity.The prevalence of maternal obesity, usually defined as a pre‐pregnancy body mass index (BMI) ≥ 30 kg/m2 will not experience an adverse pregnancy outcome, while a substantial proportion of women with a BMI < 30 kg/m2 will.2) did develop pregnancy complications.Available evidence suggests that the risk of adverse pregnancy outcome associated with obesity has increased over recent years. A large US study using National Center for Health Statistics birth certificate data found the risk of adverse outcomes associated with obesity had increased between 2013 and 2018. In women from all ethnicities studied, odds ratios (ORs) ranged from 1.27  in non‐Hispanic Black to 1.94  in non‐Hispanic white women.The intervention and observational evidence base to date suggests that BMI is not a useful tool to use to predict which women are at high risk of an obesity‐related adverse outcome of pregnancy and therefore require additional care. Body fat distribution was first identified as being important for health in the 1940s,2The systematic review was registered on PROSPERO (CRD42017064464) and the Meta‐analysis Of Observational Studies in Epidemiology (MOOSE) guidelines were followed.2.1A rigorous search strategy was implemented to limit the effect of publication bias, as database searches alone for systematic reviews of observational studies are insufficiently rigorous.Inclusion criteria were peer‐reviewed studies reporting the association between maternal pre‐ or early‐pregnancy measures of adiposity measured before 20 weeks' gestation and any pregnancy outcomes relating to maternal health, in singleton pregnancies. For the purpose of this review, we classed maternal health outcomes as those that were primarily diagnosed as being a risk to maternal health and well‐being , while recognizing that these outcomes also incur risks to the fetus. Mode of delivery outcomes were also classed as being maternal outcomes in this review. Any outcomes that we classified as being primarily a risk to the fetus or new‐born's health, such as gestational age at birth or birthweight‐related outcomes, will be reported elsewhere. Studies restricted to specific sub‐populations  were excluded, with the exception of those who had BMI inclusion criteria as we wanted to explore associations across a range of BMIs. There were no restrictions applied to the country of study or date of publication. Results of screening are reported using the PRISMA statement.Data extractions were carried out by one researcher using a standardized data extraction protocol  and pregnancy outcomes  was assessed for ability to pool data in a meta‐analysis. Meta‐analysis was carried out when there were at least three studies reporting data suitable for pooling. Studies that reported binary or continuous exposure variables were synthesized into separated pooled effect meta‐analyses. Similarly, studies that reported mean differences of the adiposity exposure variable within the pregnancy outcome levels were synthesized into a single meta‐analysis. When a categorical adiposity variable had more than two levels , the method proposed by Greenland and LongneckerWhen meta‐analysis was not possible due to heterogeneity in reporting data, or too few studies, a narrative synthesis was performed following recommendations by Popay et al.3n = 63, 90.0%) published between 2011 and 2021. Sample sizes ranged from 30 to 22,223 women, with a pooled sample size across all studies of 89,588 , North America , Europe , Australia (n = 6), Africa , South America , and one multi‐continent  (Table 2),2),2.n = 35 studies), followed by waist to hip ratio (WHR) (n = 19), measures of fat mass (FM) and fat‐free mass (FFM) (n = 15), visceral fat (n = 13), subcutaneous fat (n = 11), hip circumference (n = 7), neck circumference (n = 7), arm circumference and skinfold thickness (SFT) (n = 5 each), waist to height ratio (n = 4), total adipose fat (n = 3), leg/thigh circumference and visceral to subcutaneous fat ratio (n = 2), and n = 1 each for visceral adiposity index, FM index, FFM index, wrist circumference, neck to thigh ratio, waist to thigh ratio, ratio of visceral fat thickness to subcutaneous fat thickness, FM to FFM ratio, combined WC and BMI, combined WHR and BMI, the presence of maternal hepatic fat, and/or the upper quartile of either visceral adipose tissue or total adipose tissue (Table n = 45 studies), followed by hypertensive disorders , measures of insulin and glucose , maternal lipids (n = 6), caesarean delivery (n = 5), composite outcomes (n = 4), induction or assisted deliveries (n = 3), metabolic syndrome (n = 2), non‐spontaneous labor (n = 1), and gestational weight gain (n = 1)  Table . Ten of ue Table . The maj1) Table .The quality of studies ranged from a score of five to eight for both cohort and case control study designs Table . No stud3.1There were 45 studies reporting a diagnosis of GDM3.1.1I2 99.8%)  Figure . The stu) Figure .I2 96.4%)  and evidence of publication bias    Figure . One stu) Figure . Eight s) Figure . Meta‐an) Figure .3.1.3I2 91.5%)  Figure . Two stu) Figure . One stu) Figure .3.1.42), and FM to FFM ratio (Table I2 89.8%)  for FM percent and GDM.Eight studiesio Table . The majio Table . Data fr) Figure . Six stuo Table I2 89.8%   Figure . One stu) Figure . However) Figure .3.1.6I2 84.4%)  Figure . Five st) Figure . Three s3.1.7I2 73.8%)  Figure . However) Figure .Additional GDM data that could not be pooled in meta‐analysis were reported for circumference measures , type of fat/mass , ratios , SFT , and composite adiposity measure .3.1.8Two studies3.1.9Five studies3.1.10Two studies3.1.11Two studies reported significantly increased SFT associated with GDM including increased odds per 1‐mm increase sum of SFT 3.1.12One study3.1.13Seven studies3.2There were 20 studies reporting data relating to hypertensive disorders of pregnancy including preeclampsia, pregnancy‐induced hypertension, and systolic and diastolic blood pressure,3.2.1I2 38.1%)  Figure . One stu) Figure . There w) Figure . One stu) Figure .I2 79.5%)  Figure .3.2.2I2 79.3%)   Figure . One stu) Figure . Five st) Figure . Additio3.2.3One study3.2.4Three studies3.2.5One study3.2.6One study3.3I2 79.1% to 99.8%). However, given that in most of the analyses there were very few studies, no further analyses were performed to identify factors explaining observed heterogeneity. Sensitivity analyses were performed for meta‐analyses comprising at least 10 studies. The analyses showed that none of the studies did substantially influence the overall direction of association, effect size, statistical significance, or heterogeneity. There was evidence of publication bias in the analyses of WC (mean differences) and GDM (p = 0.024).There was heterogeneity in 10 out of the 14 meta‐analyses .Seven studies3.4.2Six studies reported data for maternal lipids  and waist and neck circumference, subcutaneous and visceral fat, and WHR.3.4.3Two studies reported case control data for maternal metabolic syndrome during pregnancy and in the immediate postpartum period3.4.4There were four studies that reported composite outcomes3.4.5r −0.24, p < 0.0001)  Table .4This systematic review has identified a large body of existing evidence that reports the associations between early pregnancy adiposity measures and maternal health outcomes. Early pregnancy WC was the most frequently reported adiposity measure. Meta‐analysis and narrative synthesis suggest that this is a strong potential predictor variable for adverse maternal health outcomes. WC was consistently significantly associated with GDM, hypertensive disorders, delivery‐related outcomes, metabolic syndrome, and composite adverse pregnancy outcomes. Similarly, WHR shows potential as it was significantly associated with GDM, hypertensive disorders, and delivery‐related outcomes. FM, neck circumference, SFT, measures of visceral fat, arm circumference, and waist to height ratio were also significantly associated with a range of adverse outcomes, although not as frequently reported in the included studies. However, the evidence base was generally conflicting or suggestive of no strong association between subcutaneous fat, FFM, or hip circumference and adverse maternal pregnancy outcomes suggesting that these may have limited use in predicting individual risk.2. A recent consensus statement from the International Atherosclerosis Society and International Chair on Cardio‐metabolic Risk working group on visceral obesity summarizes the evidence base on risk prediction models (in non‐pregnant populations) using WC and BMI. They suggest that the use of WC as a continuous variable, adjusted for BMI, works better than BMI alone to identify individuals with a high‐risk obesity phenotype and that this is partially explained by the ability of WC to identify adults with increased visceral fat mass.There was some, albeit limited, evidence that certain measures may or may not be associated with adverse pregnancy outcomes depending on the maternal pre‐pregnancy BMI. For example, arm circumference was significantly associated with hypertensive disorders among women with a recommended BMI but not for those with an obese BMI, while FM appeared to have the reverse association. Current UK guidelines for obesity in the general populationAlthough this review identified a wealth of existing data that could be used to examine how useful early pregnancy adiposity measures are at predicting risk of adverse pregnancy outcomes relating to maternal health, there were some limitations in being able to conduct thorough meta‐analysis. The data reported by the included studies were heterogeneous with a high degree of variation in the way results were presented including ORs, correlations, means, medians, and AUROC. There was also heterogeneity between studies reporting adiposity measures as continuous variables, applying inconsistent category definitions, and a combination of unadjusted and multivariable models that adjusted for a wide range of factors. There was also heterogeneity in the use of adiposity measures that could be combined, for example, some studies collecting WC and height data but not reporting waist to height ratio. There were also differences between studies in the criteria they applied to define the outcomes. In particular, studies reporting GDM prior to the widespread adoption of the IADPSG criteria for diagnosing GDM in 2010 used a range of different diagnostic criteria, which are likely to have identified different groups of women as having GDM.This systematic review has strengths and limitations. The development and implementation of the rigorous search strategy involved experienced information scientists, database searches were supplemented with additional searches, and we contacted authors for additional information when required to maximize the number of studies possible to include in the meta‐analyses. Procedures to minimize human error and subjectivity included duplicate independent screening and quality assessment, and validation of all data extraction. We also transformed data where possible to increase the number of studies possible to be pooled in meta‐analysis. However, a key limitation relates to the significant heterogeneity that was present in all but four meta‐analyses. We had a limited number of studies in each meta‐analysis, which meant we were not able to explore sources of heterogeneity using meta‐regression as was planned. The low number of studies that could be pooled in each individual meta‐analysis also meant that the usefulness of exploring publication bias and performing sensitivity analysis was limited. Finally, although we did not limit our search by type of pregnancy outcome, we identified only a few studies reporting associations between maternal adiposity and delivery outcomes or gestational weight gain, and no studies reporting maternal mental health, hemorrhage, infection, or breastfeeding outcomes, which are all significantly associated with maternal BMI. Future adiposity studies should explore a wider range of outcomes relating to maternal health and well‐being.The evidence base to date shows that large‐scale behavioral interventions that aim to reduce the risks associated with maternal obesity have been successful at improving maternal behavior and weight‐related outcomes,2. Yet BMI is used in the clinical context as a screening tool to determine individual risk and which women need additional antenatal care. This could result in unnecessary clinical intervention and reduced birth and care choices for these women. Importantly, this also potentially overlooks women with a BMI < 30 kg/m2 who have high adiposity but are not currently deemed to need additional care. This systematic review and meta‐analysis has identified a number of potential early pregnancy adiposity measures that could be used in routine clinical care to identify women at increased risk of adiposity‐related adverse outcomes. Our meta‐analysis has identified some promising evidence to help inform clinical practice, for example, relating to WC and WHR and the risk of GDM. However, further research is needed to explore whether these measures work better than BMI at predicting risk of adverse pregnancy outcomes, or if they could be used in combination with BMI or other predictor variables in a risk prediction model. It is essential that future studies prioritize adiposity measures that can be easily implemented into routine maternity care. Further research should compare these measures to determine which could be used most effectively to direct early intervention to women who need it most, to support the best chance of good pregnancy outcomes.A primary aim of prenatal care is to improve health outcomes for both mother and baby. Clinicians have a role to assess the degree of risk for each pregnant woman they see and plan patient centered and individualized care with them. Current clinical guidelines use BMI to determine individual risk in pregnancy, which does not provide an accurate measure of adiposity or individual health risks, and this practice is unlikely to be cost‐effective at preventing adverse outcomes. A large proportion of women will not experience the adverse pregnancy outcomes that population studies show they are significantly at risk of developing with a BMI ≥ 30 kg/mThere are no conflicts of interest for any of the authors.Supplement Information 1. Data extraction.Supplement Information 2. Method of managing duplicate data.Supplement Information 3. Narrative synthesis methodsFigure S1. PRISMA Flow‐chart of the study selection process.Figure S2.Funnel plot for publication bias.Figure S3. Meta‐analysis of the association between waist hip ratio (WHR) categories and GDM.Figure S4. Meta‐analysis of the association between waist hip ratio (WHR) (mean difference) and GDM.Figure S5. Meta‐analysis of the association between continuous measures of subcutaneous fat thickness and GDM.Figure S6. Meta‐analysis of the association between fat mass percent (mean differences) and GDM.Figure S7. Meta‐analysis of the association between fat free mass  and GDM.Figure S8. Meta‐analysis of the association between neck circumference (mean differences) and GDM.Figure S9. Meta‐analysis of the association between hip circumference (mean differences) and GDM.Figure S10. Meta‐analysis of the association between waist hip ratio categories and hypertensive disorders.Figure S11. Meta‐analysis of the association between waist hip ratio (mean differences) and hypertensive disorders.Table S1A. Search strategies.Table S1B. Search strategies‐CINAHL Translation.Table S2. Contacting authors for additional information.Table S3. Table of included studies/ study characteristics.Table S4. Summary of maternal adiposity exposures and maternal outcomes reported.Table S5. Newcastle Ottawa scale for quality assessment of A) cohort studies; B) case control studies; C) Adapted Newcastle‐Ottawa Scale for Cohort Studies; D) Adapted Newcastle‐Ottawa Scale for Case‐Control Studies.Table S6. Gestational mellitus diabetes (A for association data and B for case control data reported).Table S7. Insulin‐ and glucose‐related outcomes (association data) for studies not reporting a GDM diagnosis outcome.Table S8. Hypertensive disorders of pregnancy (A for association data and B for case control data reported).Table S9. Delivery‐related outcomes.Table S10. Maternal lipids.Table S11. Metabolic syndrome.Table S12. Composite adverse pregnancy outcomes (A for association data and B for case control data reported)Table S13. Gestational weight gain.Click here for additional data file.


Enterobacteriaceae (CRE) susceptible to CAZ/AVI. However, increased clinical application of CAZ/AVI has resulted in the development of resistant strains. Mechanisms of resistance in most of these strains have been attributed to blaKPC mutations, which lead to amino acid substitutions in β‐lactamase and changes in gene expression. Resistance to CAZ/AVI is also associated with reduced expression and loss of outer membrane proteins or overexpression of efflux pumps. In this review, the prevalence of CAZ/AVI‐resistance bacteria, resistance mechanisms, and selection of detection methods of CAZ/AVI are demonstrated, aiming to provide scientific evidence for the clinical prevention and treatment of CAZ/AVI resistant strains, and provide guidance for the development of new drugs.Ceftazidime/avibactam (CAZ/AVI), a combination of ceftazidime and a novel β‐lactamase inhibitor (avibactam) that has been approved by the U.S. Food and Drug Administration, the European Union, and the National Regulatory Administration in China. CAZ/AVI is used mainly to treat complicated urinary tract infections and complicated intra‐abdominal infections in adults, as well as to treat patients infected with Carbapenem‐resistant Infectious Diseases > Molecular and Cellular PhysiologyThis article is categorized under: The molecular mechanisms to ceftazidime/avibactam resistance. These bacteria have been associated with high morbidity and mortality rates, posing a serious threat to public health worldwide , which undergoes an additional reaction to form free enzyme (E) and hydrolyzed clavulanic acid (I*), which is known as a “suicide enzyme inhibitor”. These classical BLIs are active against many class A β‐lactamases but do not interact with class B, C, and D β‐lactamases. With the emergence of other carbapenemases, some new non‐β‐lactam inhibitors have been recently approved for clinical use  is the first drug approved by the U.S. Food and Drug Administration for the treatment of CRE. Although CAZ is easily hydrolyzed by β‐lactamase when used alone Figure , this co22.1Enterobacteriaceae to CAZ/AVI was less than 2.2%, with 0.2% for Escherichia coli, 1.2% for K. pneumoniae, and 2.2% for Enterobacter cloacae. While among CRE, the resistance rate of Carbapenem‐resistant K. pneumoniae (CRKP), Carbapenem‐resistant E. coli (CREC) and Carbapenem‐resistant E. cloacae were 14.4%, 27.7%, and 57.7%, respectively. The overall resistance rate of P. aeruginosa to CAZ/AVI was significantly higher than that of Enterobacteriaceae at 8.1%; Carbapenem‐resistant P. aeruginosa (CRPA) showed 25.5% resistance to CAZ/AVI. In addition, the resistance rate of CAZ/AVI varied greatly among Enterobacteriaceae and P. aeruginosa producing different carbapenemases: among Enterobacteriaceae, KPC‐producing strains were resistant to CAZ/AVI at 1.5%, and NDM‐producing strains at 99.6%, while among P. aeruginosa, KPC‐producing strains were resistant to CAZ/AVI at 35.7% and NDM‐producing strains at 97% , Global Resistance Surveillance reported that the overall resistance rate of Gram‐negative bacteria to CAZ/AVI was low (0.2%–8.1%). The resistance rate of 7% Table .2.2Enterobacteriaceae to CAZ/AVI was low in different regions of the world, with resistance rates in Latin America and Europe is only 0.3%, while the resistance rate in the Asia Pacific is relatively higher, at 1.0% , Africa‐Middle East (49.2%), Europe (23.2%), and the lowest resistance rate was found in Latin America  resistance monitoring system showed that the overall resistance rate of VI Table .2.3Pseudomonas aeruginosa has a higher resistance rate to CAZ/AVI compared to Enterobacteriaceae. INFORM resistance surveillance system in 2012–2015 showed the highest resistance rate to CAZ/AVI in Latin America at 12.6%, followed by Europe (7.6%) and the Asia Pacific , including 60.7% of CREC strains. In addition, 1.6% of K. pneumoniae strains were resistant to CAZ/AVI , including 8.3% of CRKP strains . Also, 2.8% of P. aeruginosa strains were resistant to CAZ/AVI , including 11.6% of CRPA strains  and 13.5% , respectively. The CAZ/AVI resistance rate was higher for CRE, at 24.7% , among which the resistance rate of CREC to CAZ/AVI was up to 71.4%  for CRPA and 90.9% for CREC  at their active site; the latter are called serine β‐lactamases. The most common groups of MBLs are the Verona integrin‐encoded MBLs (VIMs), imipenemases (IMPs), and New Delhi MBLs (NDMs). MBL‐producing bacteria are naturally resistant to CAZ/AVI because their MBLs do not contain a serine at their active site (Centers for Disease Control and Prevention (CDC), Enterobacteriaceae and P. aeruginosa collected from 42 medical centers in nine countries in the Asia‐Pacific region by the INFORM during the years 2012–2015 showed that 1% (91/9149) and 7.4% (151/2038), respectively, were resistant to CAZ/AVI, with MBL‐positive strains accounting for 80.2% (73/91) and 48.3% (73/151), respectively, of these CAZ/AVI‐resistant strains  contained blaNDM, whereas of the 30 CAZ/AVI‐resistant CREC, 21 (70%) were positive for NDM  β‐lactamase variants; (2) changes in bacterial membrane permeability; (3) increased expression of efflux pumps; and (4) mutation of PBPs . Evaluation of the Ki app and K2/K values of the Arg164Ala and Asp179Asn variants showed that similar concentrations of AVI were needed to fully inhibit both. These findings suggested that increased affinity for CAZ may prevent the binding of AVI to enzymes with Ω‐loop substitutions, thereby increasing MIC values for CAZ/AVI rather than reducing AVI inhibition  to reduced resistance to CAZ/AVI  for CAZ/AVI ranged from 0.03 to >128 mg/L, with 7.5% of these strains being resistant to CAZ/AVI . Compared with VEB‐1, which had a MIC value for CAZ/AVI of 0.25/4 mg/L, this variant, VEB‐25, with a Lys234Arg amino acid substitution, had a MIC value of 16/4 mg/L. Resistance to CAZ/AVI was due to interference by Arg of the ability of AVI to bind to the active site of the enzyme, thereby attenuating the inhibitory effect of AVI  and deletions  reduces the MIC values of some strains of P. aeruginosa for CAV/AZI, from >32/4 to <0.06/4 mg/L  as the result of gene duplication, which could affect the entry of CAZ , involving a 3 h incubation with Andrade solution, can rapidly detect bacterial resistance to CAZ/AVI, thereby enabling timely treatment. The ASAT reagent contains NaCl, peptone, and Andrade indicator, with a pH adjusted to 7.4 ± 0.2. Each reaction contains 175 μl of ASAT reagent and a certain concentration of CAZ/AVI, to which is added 25 μl of bacterial suspension, followed by incubation at 37°C for 3 h. Gram‐negative bacteria are detected by fermentation of glucose medium. The presence of a purple‐red color indicates a CAZ/AVI‐resistant strain, whereas a light pink color indicates a CAZ/AVI‐susceptible strain. A selective medium called SuperCAZ/AVI has also been developed to screen for CAZ/AVI‐resistant Gram‐negative bacteria. This assay was based on findings showing that the resistance breakpoints of 5P. aeruginosa to CAZ/AVI was significantly higher than that of Enterobacteriaceae. In addition, the resistance rate of CAZ/AVI in carbapenem‐resistant Gram‐negative bacteria was significantly increased. And the resistance rate of CAZ/AVI was significantly different among different continents. By summarizing the mechanisms of resistance to CAZ/AVI, we find that β‐lactamase variants, especially those associated with blaKPC gene mutations, are the most widely reported. Other possible mechanisms associated with CAZ/AVI resistance include overexpression of efflux pumps, reduced expression of outer membrane proteins, and gene mutations leading to loss of outer membrane proteins. Finally, we summarized the detection methods of CAZ/AVI resistance.CAZ/AVI, a combination of β‐lactam and a novel β‐lactamase inhibitor (AVI), has been listed since 2015, which is an important drug used to treat complicated urinary tract infections and complicated intra‐abdominal infections caused by carbapenem‐resistant Gram‐negative bacterial infections. Increases in its clinical use have led to the development of bacterial resistance. According to the global resistance surveillance reports in recent years, the overall resistance rate of Gram‐negative bacteria to CAZ/AVI was low. The resistance rate of These studies on the resistance mechanisms to CAZ/AVI will help guide clinical drug use. Currently, Combination drug therapy is mostly used to prevent and treat the emergence of resistant strains to CAZ/AVI in clinical practice, but the treatment lacks specificity. At present, broad‐spectrum metal β‐lactamase inhibitors have been developed for the strains which are natural resistance to CAZ/AVI. As for the treatment of CAZ/AVI non‐naturally resistant strains, research and development of specific medicine may be the trend of future development. Additionally, the development of new methods to detect CAZ/AVI resistance may be beneficial for the treatment and control of drug‐resistant bacterial infections.Luying Xiong: Writing – original draft (lead); writing – review and editing (lead). Xueting Wang: Writing – original draft (supporting). Yuan Wang: Conceptualization (lead). Wei Yu: Writing – review and editing (supporting). Yanzi Zhou: Supervision (lead). Xiaohui Chi: Resources (lead). Tingting Xiao: Visualization (lead). Yonghong Xiao: Data curation (supporting); supervision (supporting).This work was supported by the National Key Research and Development Program of China (2021YFC2300300) and the National Nature Science Foundation of China (No. 81971984) and the Key research and development program of Zhejiang Province (No. 2021C03068).The authors have declared no conflicts of interest for this article.Nanoparticle approaches against bacterial infections


The aim of this study was to explore predictors and construct a nomogram for risk stratification in primary extragastric mucosa‐associated lymphoid tissue (MALT) lymphoma.Extragastric MALT lymphoma cases newly diagnosed between November 2010 and April 2020 were assessed to construct a progression‐free survival (PFS)‐related nomogram. We also performed external validation of the nomogram in an independent cohort.p < 0.001). The overall survival (OS) could also be effectively distinguished by the nomogram, resulting in an OS of 100% for the low‐risk group and 94.6% for the high‐risk group (p = 0.01). These results were validated and confirmed in an independent cohort with 165 patients from another three hospitals. The 5‐year PFS rates were 94.8% and 66.7% for the low‐risk and high‐risk groups, respectively (p < 0.001). The 5‐year OS rates were 97.9% and 88.4%, respectively (p = 0.016).We performed multivariate analyses of 174 patients from 3 hospitals who were included in the training cohort. Stage, hepatitis B virus surface antigen (HBsAg) status, and Ki67 expression were significantly associated with PFS. These three factors were used to construct a nomogram, which was shown to have a C‐index of 0.89. Two risk groups (low risk and high risk) were identified by the prognostic model. The 5‐year PFS was 98.9% for the low‐risk group and 69.3% for the high‐risk group (The nomogram could well distinguish the prognosis of low‐ and high‐risk patients with extragastric MALT lymphoma and is thus recommended for clinical use. Extragastric MALT lymphoma is a rare subtype of NHL lymphoma, and without specific prognostic model. The prognostic model was constructed from the largest cohort of extragastric MALT lymphoma cases and it was the first study to establish a prognostic model in extragastric MALT lymphoma. The novel nomogram index could stratify extragastric MALT lymphoma patients into two risk groups which have significantly different prognosis, both in PFS and OS. For gastric MALT lymphoma, two‐thirds of patients have chronic Helicobacter pylori (HP) infection. Approximately 75%–80% of patients will achieve regression after HP eradication treatment.The prognostic index of MZL (MZLPI) is a useful prognostic index for non‐gastric MZL, but it is not suitable for the unique MALT subtype.22.1From November 2010 to April 2020, patients diagnosed with extragastric MALT lymphoma at three cancer centers  were screened as the training cohort for nomogram construction. The validation cohort was recruited from another three hospitals . The inclusion criteria were as follows: histologically proven MALT lymphoma according to the WHO Classification of Tumors of Hematopoietic and Lymphoid Tissue2.2We collected data regarding the following clinical features: sex, age, Ann Arbor stage, Eastern Cooperative Oncology Group performance status (ECOG PS), lactate dehydrogenase (LDH), β2‐microglobulin, erythrocyte sedimentation rate (ESR), platelet (PLT), hemoglobin (Hb), lymphocytes, neutrophils, monocytes, neutrophil‐to‐lymphocyte ratio (NLR), lymphocyte‐to‐monocyte ratio (LMR), IPI, MALT‐IPI, Ki67 level, extranodal involvement status, and hepatitis B virus surface antigen (HBsAg) status at diagnosis. Other clinical indicators included the curative effect of the first‐line treatment and treatment type information . The indicators above were included according to prognostic indicators recommended in the guidelines or reported in previous studies. The NLR was defined as the ratio of the absolute neutrophil count (ANC) to the absolute lymphocyte count (ALC). The LMR was the ratio between the ALC and the monocyte count. Progression‐free survival (PFS) was defined as the time from diagnosis to disease progression, relapse, or death from any cause, with censoring at the time of the last follow‐up. OS was defined as the time from diagnosis to death from any cause, with censoring at the time of the last follow‐up.2.3p‐values were two‐sided, and p < 0.05 was considered to indicate statistical significance. Data analysis was performed with R version 4.0.2 via the survival and design packages.In the design of the nomogram, univariate analysis was applied to identify prognostic indicators. These factors included all the factors mentioned above. Each factor was defined as binary/categorical type and input. Kaplan–Meier analysis was used to check the proportional hazard assumption required for Cox regression. PFS was used as the endpoint in the construction of the nomogram model. The chained equations approach was used to input the data. Missing values are unavoidable in retrospective studies. For missing values, multiple imputation method was used. The method had been used in a previous study.33.1In the training cohort, 174 patients were enrolled. The median age was 65 years, ranging from 18 to 80 years; 80 (46%) patients were male, and 94 (54%) were female. A majority of the patients  had a good ECOG PS score of 0–1. Sixty‐seven patients (38%) had stage III or IV disease. Most patients  were at low risk or low intermediate risk according to the IPI, while 99 patients (56.9%) were at low risk according to the MALT‐IPI. Sixty‐eight (39.1%) patients had involvement of ≥2 extranodal sites. Thirty‐two patients (13.2%) had HBsAg positivity. A total of 107 (61.5%) patients achieved complete remission (CR) after first‐line treatment. Among all patients, 101 (58%) received surgery, 55 (31.6%) received immunotherapy, and 80 (46%) received radiotherapy. The details of the training cohort are shown in Table 3.2p < 0.05); the LMR cut‐off was 2.1, which provided an AUC of 0.704 ; and the Ki67 cut‐off was 10%, which provided an AUC of 0.7 . In the univariate analysis, the following variables were statistically significant in predicting recurrence: stage, ECOG PS, radiotherapy, NLR, IPI, MALT‐IPI, Ki67 level, HBsAg status, and curative effect. In the multivariate analysis, three independent factors were found: stage , HBsAg status  and Ki67 level   and a 5‐year OS of 100% versus 98.9% (p = 0.01) . The 5‐year OS was 97.9% versus 88.4% (p = 0.0016)  Figure .p < 0.001). However, the MALT‐IPI was unable to discriminate the high‐ and intermediate‐risk groups . In the OS analysis, neither the MZLPI nor the MALT‐IPI had the power to discriminate between the high‐ and intermediate‐risk groups .Further analysis of the overall cohort, including both the training cohort and validation cohort, also showed that the low‐risk group had better PFS and OS Figure . We then4This was the first study to establish a prognostic model in extragastric MALT lymphoma. To our knowledge, this model was constructed from the largest cohort of extragastric MALT lymphoma cases. Stage, Ki67 level, and HBsAg status were assessed and used to construct the nomogram, which has a good C‐index compared with the IPI and MALT‐IPI. Patients were stratified into two risk groups, the low‐risk group, and the high‐risk group, based on the nomogram. After prognostic analysis, we found that the nomogram had good reliability in determining extragastric MALT prognosis and patient stratification in both the internal and external cohorts.Recently, other prognostic indices for MALT lymphoma have also been reported. A Korean retrospective study reported a prognostic index for MZL patients. This prognostic index included all MZL subtypes ; however, these subtypes have nonuniform treatment, and thus, the model is not suitable for MALT lymphoma.Staging considers disease location and extent and thus suggests prognostic information and provides baseline data. Stage is an independent factor for many subtypes of lymphoma that is being increasingly used in prognostic indices for pretreatment risk stratification and selection of therapy. Patients with early‐stage disease have a better prognosis and lower recurrence rate than those with advanced‐stage disease. The same result was obtained in our study. It has been proposed that hepatitis B virus (HBV) may be an etiologic agent of NHL, especially in B cell lymphoma, which has an HBV infection rate of 8.5%–30.2%.For extragastric MALT lymphoma, the incidence of death is low. Patients who suffer relapse can still have long‐term survival after second‐line treatment. According to this, PFS is a good alternative endpoint. Some studies for indolent lymphoma also use PFS as the endpoint.5This study clarified the different outcomes of extragastric MALT lymphoma in terms of PFS and OS using a prognostic nomogram. The nomogram showed a good level of discrimination and can provide an individual estimation of risk.The authors declare that they have no conflicts of interest.Design the study, Tongyu Lin and Xiaoqian Li; methodology, Xiaoqian Li and He Huang; analysis, Xiaoqian Li and Huangming Hong; investigation, Xiaojie Fang, Hongqiang Guo, Ke Xie, Ying Tian, Suxia Lin, Yungchang Chen, Wei Zhang, Yuyi Yao; data curation, Xiaoqian Li, Zegeng Chen, Fei Pan, and Huawei Weng; writing‐original draft preparation, Xiaoqian Li; writing‐review and editing, Xiaoqian Li, Huangming Hong, and Liqun Zou; supervision, Zhihui Zhang and Liling Zhang. All authors have read and agreed to the published version of the manuscript.This study was approved by the ethics committee of Sun Yat‐sen University Cancer Center. This study was conducted in accordance with the principles of the Declaration of Helsinki. We did not obtain formal consent from the patients because of the nature of the retrospective observational study.Figure S1Click here for additional data file.Figure S2Click here for additional data file.Figure S3Click here for additional data file.


To explore the prognosis predicting ability of the combined factors, Epstein–Barr virus DNA change level (EBVCL) and tumor volume reduction ratio (TVRR) after inductive chemotherapy (IC), in locally advanced nasopharyngeal carcinoma (LANPC).From 2010 to 2018, 299 LANPC patients were included in this retrospective study. Receiver operating characteristic (ROC) curve analysis was performed to acquire the best critical values. According to the best critical values of EBVCL and TVRR, patients were stratified into low‐ and high‐risk groups. Kaplan–Meier and ROC curve analyses were utilized to verify the prognostic ability of the new predictor (EBVCL+TVRR). The prognostic values among EBVCL+TVRR, EBVCL, TVRR, TNM stage, and the RECIST 1.1 criteria were compared by ROC curve. The primary end points were overall survival (OS), progression‐free survival (PFS), distant metastasis‐free survival (DMFS), and locoregional failure‐free survival (LRFFS).p < 0.0001), 91.1% versus 60.9% , 94.2% versus 68.7%  and 97.8% versus 77.9% , respectively. The maximal area under ROC curve of EBVCL+TVRR, EBVCL, TVRR, TNM stage, and RECIST 1.1 criteria for three‐year OS was 0.829, 0.750, 0.711, 0.555, and 0.605, respectively.ROC curve analyses of TVRR on three‐year survival showed the best critical values of TVRR was 32.72% for OS, 30.21% for PFS and LRFFS, 29.87% for DMFS. The best critical value of EBVCL was 127 copies/ml for OS, and 87.7 copies/ml for PFS, DMFS, and LRFFS. The three‐year OS, PFS, DMFS, and LRFFS for low‐ and high‐risk groups were 97.7% versus 78.3%  could better predict the LANPC patient's survival after IC compared with TNM stage system or RECIST 1.1 criteria. EBVCL+TVRR could effectively screen out the high‐risk population after inductive chemotherapy for LANPC. EBVCL+TVRR was identified as a better independent prognostic indicator for LANPC compared with TNM stage system or RECIST 1.1 criteria. In 2018, a total of 129,000 new NPC cases were reported by the International Agency for Research on Cancer.Currently, TNM (tumor‐node‐metastasis) stage system proposed by Union for International Cancer Control/American Joint Committee on Cancer (UICC/AJCC) is used to classify NPC and predict the patient's prognosis. But this anatomy‐based only TNM stage system is too inadequate to forecast the prognosis, hence, many studies have explored whether there exists other significant clinical factors combining with TNM system would better predict the survival. The plasma Epstein–Barr virus (EBV) is maybe the most frequently studied risk factor for NPC. For EBV DNA occurs in almost all undifferentiated or poorly differentiated NPC.In addition, more and more attention has been paid to the tumor volume's prognosis ability in NPC, for which can more directly reflect the tumor's load. Studies have revealed that tumor volume could effectively predict the prognosis of NPC.Herein, we explored the prognosis predicting ability of combined EBV DNA change level (EBVCL) with tumor volume reduction ratio (TVRR) after IC in LANPC for the first time, aiming to complement the TNM staging system with additional prognostic predicting information.22.1This retrospective analysis enrolled patients who have received 2–3 cycles of IC combined with cisplatin‐based CCRT at West China Hospital of Sichuan University from July 2010 to June 2018. Before conducting this study, we acquired ethical approval from the Biomedical Ethics Committee of West China Hospital, Sichuan University, and the written informed consent was exempted (No. 2021–1341). Inclusion criteria were as follows: Age ≤70 year‐old, histopathologically diagnosed with LANPC, without distant metastasis, III‐IVA stage (8th edition stage‐classification of UICC/AJCC), Karnofsky performance scores ≥70, previously untreated, treated with curative intent, with both 3.0 mm scanning layer thickness enhanced computed tomography (CT) localisations or both magnetic resonance imaging (MRI) localisations within 2 weeks before and after IC, with detectable EBV DNA before IC, sufficient functional reserve of liver, renal, and bone marrow. Patients with the following situations were excluded: pregnant or lactation, previously suffered from malignancy, serious coexisting sickness, treated with palliative intent, or previously treated with chemotherapy, radiotherapy, or surgery.Pretreatment evaluations were as follows: Complete case history, physical examination, laboratory examination, plasma EBV DNA level detection, nasopharyngoscopy, histologic biopsy, enhanced MRI and CT of the cervical and nasopharyngeal region, chest CT, abdominal CT and ultrasonography, and a body bone SPECT imaging scan. The 18F‐fluorodeoxyglucose‐positron‐emission tomography was conducted when necessary.2.22 on day 1, cisplatin 60–75 mg/m2 on day 1 or within 3 days, 5‐fluorouracil 600 mg/m2 per day on day 1–5) and GP , the others were TP  and PF ; all patients received 3 cycles of cisplatin‐based chemotherapy (cisplatin 75–100 mg/m2 on day 1 or within 3 days) during radiotherapy. Either IC or concurrent chemotherapy was administered every other 3 weeks.All patients completed 2–3 cycles of IC, the majority of regimens were TPF , progression‐free survival , DMFS (the time from treatment to distant metastasis or death), and locoregional failure‐free survival .2.63) and post‐GTVsum (cm3), respectively. The TVRR after IC was calculated by the following formula:TVRR was acquired according to the following steps. The two CT or two MRI localisations before and after IC were delivered to the radiotherapy planning system MIM Vista software . Two experienced radiation oncologists in our department confirmed the target lesion delineation. The primary target lesions and positive cervical lymphonodus were determined in the light of the consensus.Plasma EBV DNA was detected through a quantitative polymerase chain reaction. EBV DNA levels before and after IC were defined as pre‐EBV and post‐EBV (copies/ml), respectively, which were acquired from the electronic medical record system in our hospital. The EBVCL after IC was calculated by the following formula:The tumor's response to IC was estimated in accordance with the RECIST 1.1.2.7p value <0.05 was regarded as significant. The Medcalc (version 18.2.1) and Statistical Package for Social Sciences (SPSS) software version 23.0 (SPSS Inc.) were used to perform the statistical analyses.The best critical values of EBVCL and TVRR for 3‐year OS, PFS, DMFS, and LRFFS were analyzed by the receiver operating characteristic (ROC) curve. When the maximal area under ROC curve (AUC) was more than 50%, it was considered that there existed clinical significance. Spearman's method was used to analyze the correlation between the best critical value of TVRR and EBVCL. The prognostic values among EBVCL+TVRR, EBVCL, TVRR, TNM stage, and the tumor's response to IC (RECIST 1.1 criteria) were compared by ROC curve. According to the best critical values of EBVCL and TVRR (EBVCL+TVRR), participants were classified into three categories: Group A , Group B , and Group C . And then, on the basis of the survival differences among these three groups, the participants were divided as low‐ and high‐risk groups Figure . The Kap3Finally, there were 299 participants were enrolled in this study. Table p = 0.0020]), PFS , DMFS  and LRFFS   after IC. The ROC curve analysis of TVRR on three‐year survival showed that the best critical values of TVRR was 32.72% for OS, 30.21% for PFS and LRFFS, and 29.87% for DMFS Figure D. TVRR >) Figure ; Table 2p = 0.0028]), PFS , DMFS , and LRFFS   copies/ml after IC. The ROC curve analysis of EBVCL on three‐year survival showed that the best critical value of EBVCL was 127 copies/ml for OS and 87.7 copies/ml for PFS, DMFS, LRFFS Figure H. EBVCL ) Figure ; Table 2p = 0.017), 0.140 (p = 0.016), 0.110 (p = 0.058), and 0.140 (p = 0.016) for OS, PFS, DMFS, and LRFFS, respectively. Although there existed positive correlation between the best critical value of EBVCL and TVRR, the correlation coefficient was pretty low .The Spearman correlation coefficient between the best critical value of TVRR and EBVCL was 0.138 . And finally, we found that EBVCL+TVRR was the most powerful predictor for three‐year OS, PFS, DMFS, and LRFFS Figure . And thep < 0.0001]), PFS , DMFS , and LRFFS   Figure ; Table 2) Figure .Besides, the patients' survival comparision stratified by TNM stage (III vs. IVA) and tumor's response to IC according to RECIST 1.1 criteria (PR vs. SD) were also performed, the 3‐year survival differences of III versus IVA Figure  or PR veUnivariate analyses revealed EVBCL, TVRR, EBVCL+TVRR, T category, N category, TNM stage, and RECIST1.1 were all prognostic indicators for OS; EVBCL, TVRR, EBVCL+TVRR, T category, TNM stage, and RECIST1.1 were all prognostic indicators for PFS; EVBCL, TVRR, EBVCL+TVRR and TNM stage were all prognostic factors for DMFS; EVBCL, TVRR, EBVCL+TVRR, T category, TNM stage, and RECIST1.1 were all prognostic factors for LRFFS Table . AlthougTo identify whether EBVCL + TVRR could boost the predictive value of TNM stage, we also explored the prognostic value of EBVCL + TVRR + TNM stage, and found that the AUC values of EBVCL + TVRR + TNM stage were all significantly larger than that of TNM stage alone for OS, PFS, DMFS and LRFFS .4In the present study, we explored the prognosis predicting ability of EBV DNA change level combined with tumor volume reduction ratio after inductive chemotherapy in LANPC for the first time, and finally developed a new prognostic predictor (EVBCL+TVRR), which stratified LANPC patients into low‐ and high‐risk group and could better indicate the patient's prognosis compared with other factors commonly used in the clinical practice, such as TNM stage system or RECIST 1.1 criteria.p > 0.05), we further explored the prognostic value of the combined factor (EBVCL+TVRR), and finally revealed the combined factor possessed the most powerful prognosis predicting ability for OS, PFS, DMFS, and LRFFS when compared with EBVCL, TVRR, TNM stage or RECIST 1.1 . But the best critical value of EBVCL for OS was larger than that of PFS, DMFS, and LRFFS , which to certain extent revealed that only a relatively larger EBV‐DNA decrease after IC could guarantee a long overall survival time.There also exists some other studies who developed predictive models of prognosis for LANPC patients who received IC + CCRT. A recent research conducted by Fo‐Ping Chen et al. developed a circulating EBV DNA level based prognostication predicting system for LANPC.Besides, Qiu‐Yan Chen et al. combined the pretreatment EBV DNA with tumor volume to predict the early stage NPC patient's prognosis in the IMRT era, they divided patients into low‐ and high‐risk groups based on the tumor volume and EBV DNA level, and found that low‐risk group possessed higher three‐year PFS, LRFFS, and DMFS ratios compared with high‐risk group.As the tumor could shrink in different degrees after IC, and it has been validated that the addition of IC to CCRT could improve the survival of LANPC patients.Our study exists some limitations. First, there may be selective bias due to the retrospective nature of this research, and we strictly included eligible patients according to the inclusion criteria to minimize this bias. Secondly, objectively speaking, obtaining TVRR is relatively complex according to the present technical level, which may bring obstacles to the wide use of our combined prognostic predictor, but as the artificial intelligence (AI) has been being rapidly improved, the automatic target lesion's delineation maybe come true someday in the future, which might make the acquirement of TVRR more easier. Li Lin et al constructed an AI contouring tool to automatically delineate the primary gross tumor volume of NPC, which could effectively improve the target delineation accuracy with a reduced contouring time by 39.4%.In conclusion, the newly developed indicator (EBVCL + TVRR), with a great potential clinical applications under the development of artificial intelligence, possessed more powerful prognosis predicting ability than TNM stage or RECIST 1.1 criteria, which could better predict the LANPC patient's survival after inductive chemotherapy, thus providing some guidance for the following treatment in clinical practice to achieve a more personalized precision medicine. For instance, for high‐risk population, a more aggressive therapeutic regimen such as complementary radiation dose for primary tumor or addition of adjuvant chemotherapy after CCRT might be considered, which may further prolong the survival time on the basis of IC followed by CCRT; and for low‐risk population, the reduced target volumes/radiation doses IMRT based on the post‐IC tumor volume might be appropriate. And in the future, we will further explore the specific guidance ability of the new indicator in the formulation of the subsequent treatment strategies after IC for LANPC patients.Zhong‐zheng Xiang, and Lei Liu had complete access to the whole data in this research and were responsible for the integrality and correctness of the data and analyses. Drs Zhong‐zheng Xiang, Tao He and Yuan‐yuan Zeng contributed equally to this study. Concept and design: Lei Liu, Zhong‐zheng Xiang, Tao He. Drafting of the manuscript: Zhong‐zheng Xiang, Tao He. Critical revision of the manuscript for important intellectual content: Lei Liu, Fang Liu, Bian‐fei Shao. Statistical analysis: Tao He, Zhong‐zheng Xiang, Tian Yang, Jia‐chun Ma, Xi‐ran Wang, Si‐ting Yu. Supervision: Lei Liu.None.No conflict of interest was declared by the authors.Figure S1Click here for additional data file.Figure S2Click here for additional data file.Figure S3Click here for additional data file.Figure S4Click here for additional data file.Figure S5Click here for additional data file.Table S1Click here for additional data file.Table S2Click here for additional data file.Table S3Click here for additional data file.


TMPRSS6 gene which encodes Matriptase2 (MT2). An altered MT2 cannot appropriately suppress hepatic BMP6/SMAD signaling in case of low iron, hence hepcidin excess blocks dietary iron absorption, leading to a form of anemia resistant to oral iron supplementation. In this study, using the IRIDA mouse model Mask, we characterized homozygous (msk/msk) compared to asymptomatic heterozygous (msk/wt) mice, assessing the major parameters of iron status in different organs, at different ages in both sexes. The effect of carbonyl iron diet was analyzed as control iron supplementation being used for many studies in mice. It resulted effective in both anemic control and msk/msk mice, as expected, even if there is no information about its mechanism of absorption. Then, we mainly compared two forms of oral iron supplement, largely used for humans: ferrous sulfate and Sucrosomial iron. In anemic control mice, the two oral formulations corrected hemoglobin levels from 11.40 ± 0.60 to 15.38 ± 1.71 g/dl in 2–4 weeks. Interestingly, in msk/msk mice, ferrous sulfate did not increase hemoglobin likely due to ferroportin/hepcidin‐dependent absorption, whereas Sucrosomial iron increased it from 11.50 ± 0.60 to 13.53 ± 0.64 g/dl mainly in the first week followed by a minor increase at 4 weeks with a stable level of 13.30 ± 0.80 g/dl, probably because of alternative absorption. Thus, Sucrosomial iron, already used in other conditions of iron deficiency, may represent a promising option for oral iron supplementation in IRIDA patients.Iron‐refractory iron deficiency anemia (IRIDA) is an autosomal recessive disorder caused by genetic mutations on  There are three available mouse models of IRIDA, showing similar phenotypes with truncal alopecia, iron‐deficiency anemia and elevated expression of hepcidin.In the present work, we studied the homozygous (msk/msk) and heterozygous (msk/wt) Mask mouse strain22.1msk/Mmucd mice (number 016987‐UCD) were obtained from MMRRC, a NCRR‐NIH funded strain repository.The C57BL/6J‐Tmprss62.22.2.1The msk/msk or msk/wt mice  were kept in iron balance  or on iron‐rich diet . After 10 days, Hb and Ht were analyzed, then mice were sacrificed and tissues collected for analysis.2.2.2All msk/msk mice  were kept at an iron balance diet and treated daily with 0.5 or 4 mg of elemental iron per kg/body weight contained in ferrous sulfate and Sucrosomial iron  or vehicle , erythroferrone (ERFE) in serum; peripheral blood smear staining; histochemistry and immunostaining on paraffin‐embedded duodenal sections. The detailed procedures are reported in 2.4Comparison between heterozygous and homozygous mice matched for age and sex were performed by two‐way ANOVA. Multiple comparisons were corrected by Sidak's test. For treatments, comparisons between vehicle versus iron formulations were performed using One‐way ANOVA with multiple comparisons corrected by Tukey's test. Data are shown as dot plot, with Mean ± SD.33.1The Mask miceSpecifically, at 3 weeks the Hb and Ht values were similar in msk/msk and control msk/wt mice, the difference among them became apparent with age particularly at 9–15 weeks. The msk/wt mice showed a fast increase of Hb levels between 3 and 6 weeks, and then it leveled off at 17.54 ± 0.84 g/dl, in both sexes. The msk/msk mice showed a steady but minor increase in Hb levels up to 28 weeks, to reach a plateau value of 13.95 ± 0.87 g/dl, with similar kinetics in the females and in males, making a significant difference between them only at 6 weeks Figure . The Ht The Id1 mRNA showed the same trend of hepcidin ). Liver Serum iron strongly decreased from 179.50 ± 29.30 to 123.94 ± 15.34 μg/dl in the msk/wt mice at 3–9 weeks that corresponds to the period of Hb increase, then it leveled off at 125.24 ± 17.95 μg/dl at 15–28 weeks. In the msk/msk mice the serum iron remained remarkably stable at 71.25 ± 17.91 μg/dl during the whole period, and always lower than that of the control mice Figure  with a sThe effect of hepcidin on the iron status of tissues is unclear, and the Mask mice offer the opportunity to elucidate it. In the brain, the iron content showed a tendency to increase with age in both sexes and maintained a significant difference between the two mice strains, ranging from 6.72 ± 0.62 to 9.33 ± 0.65 ng/mg in the msk/msk mice and from 7.02 ± 0.94 to 13.16 ± 1.07 ng/mg in msk/wt mice ). Simila3.2The above data showed that in the Mask mice, anemia was maximal during the 9–15 weeks period in correspondence of the highest serum hepcidin levels (maintained till about 28 weeks), suggesting this as the best interval of time for studying the effects of iron treatments.The high levels of hepcidin are expected to inhibit intestinal iron absorption by inducing FPN degradation, making anemia refractory to oral iron supplementation. However, it was shown that when Mask mice receive an iron‐rich diet (2% of carbonyl iron) for 1 to 3 weeks, anemia is partially reverted with an increase of Hb from about 8 to 9–12 g/dl, respectively.Confirming the already published data, we fed 9‐week‐old mice (both msk/wt and msk/msk) with an iron‐rich diet (8.3 g/kg carbonyl iron) for 10 days. In both female and male msk/wt mice, the iron‐rich diet did not increase Hb and Ht level Figure  but causThen, we analyzed two oral iron formulations, ferrous sulfate and Sucrosomial iron, already largely used in humans, administering them in Mask mice as exactly the same amount of elemental iron. We choose female mice since, even if we did not observe any significant differences between the two sexes, the females presented a more constant level of Hb than males, between the 9 and 28 weeks of age, the period selected for the iron administration  Table . The twoThe groups treated with ferrous sulfate showed an increase of hepcidin Figures ) that isSerum iron showed higher values only in some mice treated with Sucrosomial iron (mainly with 4 mg/kg) compared to the vehicle or ferrous sulfate treated groups Figure . The TSaHematoxilin and eosin staining of duodenum samples showed no differences in the morphology of intestinal villi from mice treated with vehicles or with Sucrosomial iron and ferrous sulfate at both concentrations (0.5 and 4 mg/kg), with no visible areas of erosion and atrophy . The treImmunohistochemical analysis for CD3 positive intraepithelial lymphocytes showed an increase of these cells in duodenal villi in mice treated with both Sucrosomial iron and ferrous sulfate compared to the vehicles  without Interestingly, the alopecia, evident in all Mask mice before the treatments, was not changed in the vehicle‐treated animals and even less in the ferrous sulfate mice, while a substantial recover was observed in the Sucrosomial iron group , T = 0 vAs a further analysis, we put the control msk/wt female mice on an iron‐deficient (ID) diet for 6 weeks to make them anemic . This reduced both liver mRNA and serum hepcidin level, as expected (comparing mice in IB with ID diet) ), withouThe two formulations caused an increase of serum iron, Tsat ), liver 4So, IRIDA is an autosomal recessive rare disease caused by non‐functional MT2, that is unable to cut HJV and suppress the hepatic BMP6/SMAD signaling, leading to a constantly expression of high levels of hepcidin and consequently FPN degradation, with impaired iron absorption from the gut and reduced iron stores in the body. Besides increased hepcidin levels, the main features of IRIDA typically include moderate/severe microcytic anemia, low transferrin saturation and paradoxically normal to slightly increased ferritin levels, without signs of inflammation. Because of refractoriness to oral iron, the current treatment in IRIDA syndrome is based on parenteral iron supplementation, although its efficacy is often incomplete, requiring repeated lifelong administrations.The Mask mouseWe analyzed homozygous Mask (msk/msk) mice in comparison with heterozygous (msk/wt) mice, as controls, to characterize their systemic iron status. Mask mice had lower serum iron levels and lower iron content in different organs across all age groups and in both sexes, confirming the essential role of hepcidin as the regulator of systemic iron homeostasis. Accordingly, they showed lower Hb levels (12.19 ± 1.64 g/dl) compared to heterozygous (16.41 ± 1.92 g/dl), a difference evident just before the weaning and that persisted during aging in both sexes. In particular, we observed more severe anemia and reduced amount of liver and spleen iron content in male Mask mice than in females, although their hepcidin levels were comparable. Moreover, we found decreased muscle iron content in the Mask mice compared to controls, in accordance with a previous study.As expected, in the Mask model, the duodenum was the only tissue in which iron content was higher than in controls, as a consequence of the hepcidin‐mediated FPN degradation. On the contrary, no iron accumulation has been detected in spleen, suggesting that anemia in IRIDA mice cannot be solved by mobilizing iron, but rather by overcoming the block of intestinal iron absorption, through FPN‐independent mechanisms.We confirmed that the Mask mice treated with an iron‐rich diet, increased Hb and serum iron levels indicating that carbonyl iron could be absorbed even in high hepcidin expression status, probably bypassing the hepcidin‐ferroportin axis block. Thus, it could be an effective iron formulation to solve the anemia in IRIDA patients, but more studies are needed and the actual mechanism of its absorption remains to be elucidated.2+) and pyrophosphate iron in the form of sucrosomial particles . The histological evaluation of duodenum did not show evident differences between the two iron formulations both in terms of duodenal villi morphology and CD3+ infiltrated lymphocytes apart from an increase of iron accumulation in duodenal villi in mice treated with 4 mg/kg of ferrous sulfate. It is known that iron supplementation can induce alterations in jejunum,In the present study, we mainly compared the same amount of elemental iron of two different oral iron formulations: ferrous sulfate in the form of ionic iron , Hematocrit (Ht) and weight of C57BL/6J wild‐type, heterozygous (msk/wt) and homozygous (msk/msk) Mask mice during the age.Click here for additional data file.Table S2 Mean levels of Red Blood Cells (RBC), Mean Corpuscular Volume (MCV), Reticulocytes (RET) and Reticulocytes‐Hemoglobin (Ret‐He) of heterozygous (msk/wt) and homozygous (msk/msk) Mask mice, both male (upper table) and female (lower table) during the age.Click here for additional data file.Appendix S1: Supplementary Information.Click here for additional data file.


ClinicalTrials.gov databases were searched until April 2022. The effect size was computed by the mean changes from the beginning for intervention and comparison groups and their standard deviation. In the case of significant heterogeneity, DerSimonian and Laird random‐effects model was used. Six and five clinical trials were selected for the systematic review and meta‐analysis, respectively. The overall estimate indicated that soy isoflavones in combination with soy protein did not significantly change serum adiponectin level (weighted mean differences (WMD) = 0.36 μg/ml; 95% confidence interval (CI): −0.26, 0.99; p = .25), but significantly increased serum resistin level . In combination with soy protein, soy isoflavones nonsignificantly increased serum adiponectin levels, but significantly increased resistin levels. New intervention studies with a high dose of soy isoflavones and soy protein in different parts of the world and an updated meta‐analysis are needed to confirm the results of our study.Some studies proposed the anti‐inflammatory effect of soy protein and soy isoflavones by changing the serum adiponectin and resistin levels. The purpose of this research was to determine the impact of soy isoflavones and soy protein on blood adiponectin and resistin levels in adults. Scopus, PubMed, Cochrane Library, ISI Web of Science, and  Soy isoflavones in combination with soy protein non‐significantly increased serum adiponectin levels, but significantly increased resistin levels. It is the source of various bioactive and endocrine compounds known as adipokines , obesity, metabolic syndrome, type 2 diabetes mellitus (T2DM), and atherosclerosis  can affect the function or expression of these adipokines  on the effect of soy protein and soy isoflavones on resistin level, which produce contradictory results  guidelines were used for all stages of design, implementation, and reporting in this study . We also used parentheses, quotation marks, and asterisks for searching group search terms, the exact word, and all words made of one word, respectively  after removing duplicate papers, the titles and abstracts were read by two independent reviewers . Moreover, we reviewed the reference lists of all relevant reviews on this issue and all included RCTs to round up our search. We contacted the appropriate authors to get clarity on any confusing material. A group discussion was used to settle disagreements.2.2Inclusion criteria were outlined in terms of PICOS framework: (1) Population: Participants aged more than 18 years old with no gender‐based and health restriction; (2) Intervention: the combination of soy isoflavones and soy protein; (3) Comparator: Comparison group; (4) Outcomes: Measuring adiponectin and resistin; (5) Study design: RCTs.2.3Papers were excluded from this study as follows: (1) unclear information for serum concentration of adiponectin and resistin; (2) measuring postprandial levels of adiponectin or resistin; (3) not reporting the intervention duration; (4) taking food supplements besides soy isoflavones plus soy proteins; (5) not having a comparison group; (6) not having data for the dose of soy isoflavones and soy protein, and (7) non‐English articles.2.4After finalizing RCTs eligibility to be included, the following information was extracted by two independent reviewers : first author's last name, soy isoflavones dose, study design, soy protein dose, study duration, health status, number of subjects in intervention and comparison groups, the country where RCTs was conducted, participants' sex, age, body mass index (BMI), RCT publication year, mean and standard deviation (SD) of serum concentration of adiponectin and resistin. We converted all units for adiponectin and resistin into the same unit (μg/ml for adiponectin and ng/ml for resistin). RCTs with more than one group as a comparison group and more than one group as an intervention group were divided into two or more RCTs. If any discrepancy was found on extracted information, researchers consulted again and MH sent an email to corresponding authors to clarify unclear information.2.5According to the items of Cochrane Collaboration's tool, the quality of eligible RCTs was assessed by two independent reviewers   and their SDs for adiponectin and resistin through extracting data from included articles.p‐value ≤ .10 and value ≥50% were considered as significant heterogeneity for the Cochran's Q test and the I‐squared statistic, respectively , without any comparison group (n = 2), measuring postprandial levels of adiponectin or resistin (n = 1), measuring the serum concentration of other adipokines (n = 15), using only soy isoflavones as intervention (n = 5), and using only soy protein as intervention (n = 2). Finally, 6 RCTs were selected for the systematic reviews . There was a significant heterogeneity among the included studies , and even it was found in most subgroup analyses except for study duration >56 days , and baseline adiponectin ≤10 μg/ml  (Table p = .002) (three effect sizes), soy protein dose >21 g/day  (four effect sizes), studies with parallel design  (five effect sizes), study duration >56 days  (two effect sizes), Americas  (seven effect sizes), participants' age > 57 year  (three effect sizes), BMI ≤29  (three effect sizes), and good quality studies  (five effect sizes)  Table . Dependi%) Table . Subgroup = .001). There was a significant heterogeneity among the studies . In subgroup analysis, the heterogeneity among the studies was significant in the following subgroups: soy isoflavones dose ≤89.3 mg/day , soy protein dose >22 g/day , studies with cross‐over design , study duration≤56 days , baseline resistin ≤10.92 ng/ml , at risk individuals , sample size >37 , Americas , both sexes , age ≤ 57 years old , BMI > 29 , studies with good quality  and Publication year >2010  , soy protein dose ≤22 g/day (p < .001), studies with parallel design (p <.001), study duration ≤56 days (p = .033), baseline resistin ≤10.92 ng/ml (p = .002), healthy individuals (p < .001), sample size ≤37 (p < .001), Americas (p = .001), females (p < .001), age ≤ 57 years old (p = 0.022), unknown BMI (p < .001), studies with good quality (p = .034), studies with weak quality (p < .001), publication year ≤2010 (p < .001), and publication year >2010 (p = .015) .The funnel plots for studies on soy isoflavones in combination with soy protein on serum levels of both adiponectin and resistin were not visually symmetric Figures  & 7. How4Our findings showed that soy isoflavones in combination with soy protein had no significant effect on adiponectin levels; however, studies with a parallel design, sample size ≤44, and good quality, studies on the American population, participants aged >57 years old, and BMI ≤29 showed significant incremental effects of soy isoflavones in combination with soy protein. A significant increase in adiponectin levels was observed in studies in which the dose of soy protein and soy isoflavones was more than the median .κB)  compared with normal Western diets in which mean intake is almost 2 mg/day  although adipokines were secreted from adipose tissue. Fourthly, there was only one article that studied the effect of soy isoflavones in combination with soy protein on adiponectin concentration in Asian participants and no article was on resistin levels among this population. Therefore, the effect of this combination on adiponectin and resistin levels in the Asian population remained unknown.This research has many strengths: we conducted the search using a wide phrase. This investigation was conducted in accordance with the Cochrane Collaboration's principles for systematic reviews and meta‐analyses. We included studies that only used soy isoflavones combined to soy protein as an intervention. Therefore, we excluded the confounding effects. We have limited the effect of baseline adiponectin and resistin levels, soy isoflavones dose, design, soy protein dose, intervention duration, health status, sex, region, quality assessment, sample size, age, BMI, and publication year of the article on our results by subgroup analysis. We have conducted our systematic search with no time limitation.5The overall results of present review did not support the useful effect of soy isoflavones in combination with soy protein on serum adiponectin levels, but our study revealed that this combination could significantly increase the serum concentration of resistin. However, it appeared that this combination significantly increased the serum concentration of adiponectin in RCTs in which subjects took a higher dose of soy isoflavones and soy protein. Furthermore, high‐quality publications and articles among the American population indicated that this combination had a beneficial impact on the blood concentration of adiponectin. On the other hand, it seems that the dose of soy protein and soy isoflavones, RCTs quality, and the region of participants are strong predictors for this combination effect on serum adiponectin levels. In terms of the impact of this combination on resistin levels, further well‐designed intervention trials and studies conducted in diverse regions of the globe are needed to validate the rising effects of soy isoflavones in conjunction with soy protein on resistin levels.This study was financially supported by Neyshabur University of Medical Sciences.No conflict of interest.Table S1Click here for additional data file.


Sea buckthorn wine (SW) and distilled liquor (DL) are fruit wines with beneficial health effects. However, their unpleasant flavour limits their development and widespread acceptance. Therefore, it is necessary to analyse their flavour composition and changes. In this study, differential metabolites of sea buckthorn DL during processing were analysed, and the relationships between E–nose sensor values and key volatile organic compounds (VOCs) were established. The results show that 133 VOCs were identified, with 22 aroma–contributing components. Fermentation significantly increased the content of VOCs, especially esters. A total of seven and 51 VOCs were significantly upregulated after fermentation and distillation, respectively. Meanwhile, seven sensors were positively correlated with the increased level of alcohols and esters, and reflected the increasing trends of 10 key VOCs. Hippophae rhamnoides), classified as a medicine food homology (MFH) plant, contains large amounts of vitamin C, carotene, flavones, linoleic acid and other bioactive substances [Actinidia deliciosa) [Sea buckthorn  . Sea bucliciosa) . HoweverSea buckthorn wine is obtained by fermentation of SJ with yeast or koji after acid reduction and sugar adjustment. Negi  developeH. rhamnoides populations from China were analysed by GC–MS and 44 compounds were detected, and the main compounds included tetracosane (10–40%), hexadecanoic acid (<0.1–11%), octadecatrienol (5–27%), tetracosene (3–11%), eicosanol (<0.1–13%) and others [Many methods and instruments are available for the determination of volatile organic compounds (VOCs) in food, including gas chromatography (GC), gas chromatography–mass spectrometry (GC–MS), electronic nose (E–nose), electronic tongue (E–tongue), etc. VOCs in food have complex compositions and uneven distributions, making it difficult to elucidate flavour information using a single analytical technique ,7. GC–MScid <0.1–%, octaded others . Furthernol <0.1–% and othd others ,15.Lactobacillus plantarum LP56 (SBJLp) could be easily identified by sensors sensitive to aromatic substances. Its advantage is that it is fast and convenient, but its disadvantage is that the sensor response value cannot accurately reflect the content of a specific substance. Conversely, GC–MS metabolome analysis is good at qualitative and quantitative analysis of flavour compounds. Therefore, correlation analysis between key VOCs identified by GC–MS metabolomics and E–nose data is useful, as the changes in key VOCs can be quickly verified based on the corresponding values of specific sensors [E–nose is an instrument used for the rapid detection of VOCs in food. The E–nose sensor converts the smells of odour substances into electrical signals, and the responses of multiple sensors constitute the response spectrum of the sensor array to a given smell. Different odours can be distinguished by their characteristic response spectrum . At pres sensors .Here, we compared changes in the flavour of sea buckthorn DL among different stages of processing, analysed the flavour profiles of SW and its DL, identified differential metabolites and key metabolic pathways, and then established the relationships between E–nose data and key VOCs to provide a basis for flavour optimisation of SW.3 and glucose, respectively . Additionally, 30 mg/L potassium metabisulfite was added to SJ to sterilise and improve stability. The samples were inoculated with 0.2% (w/v) Saccharomyces cerevisiae  that had been activated in 2% glucose solution at 37 °C (water bath) for 30 min, and then underwent fermentation at 28 °C for 7 days (the CO2 produced by fermentation can be discharged into the water with the hose) to obtain SW (SW1–SW3) with an alcohol content of 13  ±  2% (v/v). Finally, 1L SW was distilled, producing 500 mL distillate for the first time , and 250 mL distillate liquor (DL1–DL3) with an alcohol content of 40  ±  2% (v/v) was obtained by second distillation. The whole research process is shown in According to the method of He , frozen 4 solution and 2 mL of 6 mmol/L H2O2 solution, followed by shaking. The mixture was allowed to stand for 10 min at room temperature. Then, 2 mL of 6 mmol/L salicylic acid was added and allowed to stand for 30 min at room temperature. Each sample was determined three times in parallel. Ascorbic acid was used as a positive control. The OH· radical scavenging rate was determined using the following formula:i is the absorbance of the sample at 510 nm, Aj is the absorbance measured after replacement of H2O2 with distilled water, and A0 is the absorbance measured in the blank control group with distilled water instead of the sample.Based on the method of Xu et al. , 1 mL sai is the absorbance of the supernatant at 517 nm, Aj is the absorbance measured after replacement of DPPH solution with anhydrous ethanol, and A0 is the absorbance of the reference consisting of 2 mL 0.04 mg/mL DPPH and 2 mL of anhydrous ethanol reactant.According to the method of Liu, Ooi and Chang , 2 mL ofAccording to the method of Kaewnarin et al. , 1 mL sam/z was recorded at a rate of one scan per second. Each sample was determined three times in parallel.According to the method of Xia et al. , with miData were analysed using GC–MS software  and identified based on the NIST 2017 database. Only compounds with a matching degree ≥80 were retrieved and recorded. The NIST database was used to automatically retrieve mass spectral data of each component for qualitative analysis. A semiquantitative method was used to determine relative contents by calculating the ratio of the internal standard substance (3–octanol) to the peak area of each component. Principal component analysis was used to analyse the differences in the flavour of the compounds among the three types of samples . Odour activity value (OAV) was obtained by the ratio of the concentration of the substance to the threshold value.In accordance with the method of Cui et al. , E–nose p < 0.05 represented significant difference, p < 0.01 represented extremely significant difference, and the experimental results were expressed as the mean ± standard deviation. Each index was repeated three times. Principal component analysis was performed using SIMCA–P software, line charts and bar charts were constructed in Origin 9, and R language was used for the generation of Venn diagrams, volcano diagrams, and correlation heat maps.SPSS17.0 software was used for variance analysis. A value of The physicochemical indices and antioxidant activities of SJ, SW and DL are shown in The comparison of VOCs of SJ, SW and DL is shown in n–decanoic acid (ac8), tridecane , and 5–tetradecene  , α–murolene (t3), oxaloacetic acid (ac6), e  B. FermenOAV is an index reflecting the contribution of one aroma to the overall flavour of samples. Hanseniaspora uvarum yeast fermentation to produce sea buckthorn wine, and phenylethanol accounted for 3.6% of the overall aroma, indicating that phenylethanol is a stable flavour component in sea buckthorn wine. 4–Ethylphenol is usually present in rum and whiskey, and can be used as an essence in the preparation of wine and liquor [Five VOCs increased in SW after fermentation, including benzeneacetic acid ethyl ester (OAV 2.610), geranyl acetone , heptanal (OAV 1.500), heptanoic acid ethyl ester (OAV 1.182) and furfural (OAV 1.020). 4–Ethylphenol (OAV 25.400), phenylethyl alcohol (OAV 20.800) and nonanal (OAV 17.600) were added as important VOCs of SW. Phenylethanol with a rose fragrance is commonly found in wine, mangosteen and other fruit wines, and has been identified as a characteristic flavour compound. Ma  found thd liquor ,36. Nonad liquor .DL also showed increased levels of five aroma components, i.e., β–damascenone –2–buten–1–one, OAV 132,666.667), benzenepropanoic acid ethyl ester (OAV 488.889), decanoic acid ethyl ester (OAV 61.650), 3–methyl–1–butanol acetate OAV 39.333) and dodecanoic acid ethyl ester (OAV 3.364); these were also characteristic VOCs of DL. It is worth noting that the contributions of 5–methyl–2–furancarboxaldehyde (OAV 0.300) and heptanal were significantly reduced in DL, while heptanal was not detected. β–Damascenone, which imparts berry and rose scents, is commonly detected in grape , acai be.333 and p < 0.05 and an FC value greater than 2 were selected as differential metabolites [2FC values of infinity (Inf). 2,3–Butanediol imparts a sweet scent, and gave the wine a mellow and natural flavour. Seo et al. [The flavour compounds with abolites ,41. The o et al.  also repo et al. .Prunus dulcis [In total, 51 significantly upregulated VOCs were found in SW after distillation C, includs dulcis , tomato s dulcis , tea [45s dulcis , and nots dulcis . Overalls dulcis ,49.SJ, SW and DL samples were easily distinguished from each other by E–nose A. FermenAlpinia officinarum based on the results of correlation analysis.E–nose is not commonly used in flavour detection of sea buckthorn wine. Yu et al.  used E–nCorrelation analysis was further conducted between the changes in response values of E–nose and 22 key flavour compounds D. W5S, WCompared with sea buckthorn juice, seven significantly upregulated substances were found, which, although seemingly small in number, were important aroma substances; these substances were 3–octanone, phenylethyl alcohol, 2,3–butanediol, tridecane, octanoic acid ethyl ester, 6–methyl–5–hepten–2–one and acetoin. In addition, there were in fact 10 important flavour compounds that were newly produced after fermentation in SW, including 2–methyl–propanol, 3–ethoxy–1–propanol, 1–heptanol, benzyl alcohol and so on. All these VOCs contributed greatly to the overall flavour of sea buckthorn wine.The OAV of phenylethanol in sea buckthorn juice was 10, and the OAV of phenylethanol in sea buckthorn wine increased to 20.8, indicating that phenylethanol occupied an increasing proportion in the overall flavour of sea buckthorn wine with the fermentation. Phenylethanol is formed by phenylalanine transamination of phenylpyruvate, followed by decarboxylation to phenylaldehyde, and phenylaldehyde in the presence of oxidative dehydrogenase generates β–phenylethanol . PhenyleThe OAV of octanoic acid ethyl ester in sea buckthorn juice was 1370, and the OAV of octanoic acid ethyl ester in sea buckthorn wine increased to 4110, indicating that octanoic acid ethyl ester was one of the key flavour compounds of sea buckthorn juice and wine, and its contribution was more obvious after fermentation. Ma  and Lukš2FC  >  1). The most obviously upregulated pathway was butanoate metabolism, followed by biosynthesis of cofactors, toluene degradation, furfural degradation, etc. (2FC = Inf), of which five had VIP values > 1 , three alcohols  and 14 esters . The relevant differential metabolites included 3–methyl–butanoic acid, 2–butanol, 2,3–butanediol, 3–methyl–butanoic acid ethyl ester, 3–methyl–butanoic acid hexyl ester. These substances are important components of wine flavour. 3–Methyl butanoic acid was identified as a key aroma compound in fermented Forastero cocoa beans, and gave them a sweaty odour [Yang et al.  also fouty odour . The spety odour , 2,3–butty odour , butanoity odour  and Qingty odour .Microbial metabolism in diverse environments and metabolic pathways are complex metabolic systems. Microbial metabolism in diverse environments includes carbohydrate metabolism, energy metabolism, metabolism of cofactors and vitamins and xenobiotic biodegradation. Metabolic pathways include carbohydrate metabolism, energy metabolism, lipid metabolism, nucleotide metabolism, amino acid metabolism, glycan metabolism, biosynthesis of terpenoids and polyketides, biosynthesis of other secondary metabolites and xenobiotic biodegradation.Compared with the fermentation, the distillation process formed more flavour compounds. In total, 51 significantly upregulated and 14 downregulated VOCs were found in SW after distillation C. In theYang et al.  found thGC–MS and E–nose were used and analysed in combination to establish associations between sensors and specific flavour substances. Seven sensors, including W5S, W6S, W1S, W1W, W2S, W2W and W3S, were positively correlated with 10 key flavour compounds –2–buten–1–one), indicating that the seven sensors can effectively reflect the strong aroma of SW and DL.Chrysanthemum nankingense and the response value of the E–nose sensor. Sensor W1C had a good correlation with C62 , sensor W5C had a good correlation with C136 (phenanthrene), and sensor W3C had a close correlation with C109 . The sensor W1W had high sensitivity to alkenes, and had good correlation with various terpenes, such as C117 (caryophyllene) and C130 .The association of GC–MS and E–nose needs to be an effective method to detect food flavour, considering that the detection accuracy of GC–MS is high, but it takes a long time, while E–nose detection is fast, but it cannot determine the specific substance. Huang et al.  integratIn this study, changes in the flavour of SW and DL at different processing stages were compared, the differential metabolites were analysed, and relationships between E–nose sensor values and key flavour compounds were established. A total of 133 VOCs were detected in the three groups, with 76, 79 and 99 VOCs identified in SJ, SW and DL, respectively. Sixteen and 17 VOCs contributed to the flavour of SW and DL, respectively. Fermentation significantly increased the contents of VOCs, especially esters. 3–Octanone and phenylethyl alcohol were the most significantly upregulated VOCs. E–nose data showed that seven sensors could reflect the increases in contents of alcohols, esters and 10 key flavour compounds.