Enteral nutrition (EN) is an important treatment for burn patients. However, severe gastrointestinal damage caused by major burns often leads to EN intolerance. Trophic EN solves this problem basically, but how to transition from trophic EN to standard EN smoothly is still a challenge in burn clinical nutrition. The aim of this study is to investigate the effects of EN with different energy supplies on metabolic changes, organ damage and prognosis in burned rats.Different feeding regimens were designed based on the continuous monitoring of resting energy expenditure in rats. Thirty-two Sprague–Dawley rats were randomly divided into a normal control group, burn +50% REE group, burn +75% REE group and burn +100% REE group. At the end of a nutritional treatment cycle (14th day), nuclear magnetic resonance spectroscopy, blood biochemistry analysis and quantification of subscab bacteria were performed to explore the differences in metabolic changes, degrees of organ damage and prognoses between the groups.Sixteen metabolites involving seven metabolic pathways were identified from the different energy supply groups. After burn injury, resting energy consumption and body weight loss increased obviously. Meanwhile, weight loss was inversely related to energy supply. The greatest changes in the degree of organ damage, the level of plasma proteins, lipids and endotoxins, as well as the quantification of subscab bacteria were observed in the 50% REE group, followed by the 75 and 100% groups.Achieving an early balance between energy supply and expenditure is conducive to mitigating metabolic disorders and improving prognosis after burn injury. HighlightsDifferent energy supplies have an obvious effect on metabolic changes and organ damage in burned rats.An adequate energy supply is the key factor for alleviating organ damage and reducing the extent of wound infection and mortality.Seventy-five percent REE supply in the first week can reduce overfeeding and 100% REE supply in the second week can avoid underfeeding effectively after burns, providing a reasonable energy supply strategy for burned rats.Uncontrolled and persistent hypermetabolism is the most notable metabolic feature of severe burn patients. On the one hand, these patients persistently experience a hypercatabolic state, with increased body consumption and an urgent need for nutrition supplementation; on the other hand, they suffer impaired nutrient utilization, i.e. nutrition intolerance . Therefoet al.  × 1440 × 4.184.REE was measured using indirect calorimetry by measuring respiratory gas exchange with equipment from Columbus Instruments . Rats were placed in a Plexiglas metabolic chamber (4 l volume). The air inlet and outlet contained a calcium sulfate column to desiccate the inhaled and exhaled air. The airflow rate was monitored continuously for 10 min, which covered six cycles (lasting for 60 min), and OIndividual animals were weighed every morning using an electronic balance with 1/1000 precision  and the values were recorded.On day 14 after injury, the rats were sacrificed, the back scab was cut and ~0.3 g of the subscab tissue on the back of each animal was cut with a sterile scalpel. After weighing, the tissue was placed in a bacterial culture gel tube for quantitative analysis of bacteria.During the 14-day period of animal observation, the time point of death was recorded and a death–time curve was obtained. Mortality rate (%) = the number of dead animals/the number of participating experimental animals in each group × 100%.On day 14 after injury, 5–6 ml of blood was drawn from the abdominal aorta under anesthesia and analgesia, 1 ml of the blood was anticoagulated with sodium citrate for nuclear magnetic resonance (NMR) spectroscopy detection and the remaining 4–5 ml was transferred to Ethylene Diamine Tetraacetic Acid (EDTA) tubes for anticoagulation. The tubes were held at room temperature for 30 min and then centrifuged at 4°C at 3000 rpm for 10 min. The serum was collected and stored at −80°C for centralized detection of liver and kidney function, myocardial enzyme spectrum, blood lipids, protein content and endotoxin levels. Testing indicators included the following. Kidney damage: blood urea nitrogen (BUN), creatinine (CrEAT) and uric acid (UA); myocardial damage: lactate dehydrogenase (LDH), α-hydroxybutyrate dehydrogenase (α-HBDH) and creatine kinase isoenzyme MB (CK-MB); liver damage: alanine aminotransferase (AST), aspartate aminotransferase (ALT), glutamyltransferase (GGT), alkaline phosphatase (ALP), total bilirubin (TBIL) and total bile acid (TBA); blood lipids and protein levels: total cholesterol (Tch), triglycerides (TGs), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), albumin (Alb) and total protein (TP); and endotoxin levels: lipopolysaccharide (LPS), which was quantified by the limulus amebocyte lysate (LAL) test according to the manufacturer’s instructions. Briefly, 100 μl of each sample was added to 100 μl of the limulus reagent  and the mixture was dissolved in LPS-free water and the reaction was allowed to proceed at 37°C for 60 min in an ATI 320-06 Kinetic Tube Reader . The dynamic turbidity of the limulus reagent was measured to quantify LPS levels.2O) and thorough shaking for 120 s. Next, the specimen was allowed to stand for 10 min and then placed in a 600-MHz NMR spectroscopy device  for measurement and analysis.To observe the effect of different energy supplies on changes in the metabolic pattern of the body after burn, metabolites in rat plasma were detected by NMR spectroscopy and differences between different groups were determined by multivariate statistical analysis. After 14 days of burn, 1 ml of anticoagulant blood was taken from each of the above four groups of rats and centrifuged at 4°C and 16 000 rpm for 10 min, and then 450 μl of plasma was placed into an NMR tube, followed by the addition of 50 μl of heavy water  for analysis. Before assigning chemical shifts, all spectra were subjected to baseline and phase correction. Chemical shifts of the plasma metabolite spectrum were determined by referring to the methyl resonance peak of lactic acid at δ 1.32. The chemical shift region between 0 and 8 ppm was subdivided into 2000 intervals with a width of 0.004 ppm. The absorption spectrum of water with a chemical shift between 4.7 and 5.1 ppm was removed [Plasma  removed . FinallyR2 and Q2 were calculated for evaluation. The characteristics of metabolites with intergroup differences were determined based on the S-plot curve of the OPLS-DA model and the score for variable importance in projection (VIP > 1) [The data obtained were imported into SIMCA-P 14.1  software for principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) . The OPLVIP > 1) . The chaVIP > 1) ,30. The U test . One-way analysis of variance (ANOVA) with Bonferroni correction was performed for comparisons between multiple groups. The changes in the repeated measures were statistically analyzed using two-way repeated measures ANOVA and Bonferroni’s test for multiple comparisons. Categorical variables were expressed as frequencies and percentages compared using Fisher’s exact test. Kaplan–Meier curves were used to analyze the survival time for each group and were further analyzed with the log-rank test. In all analyses, p < 0.05 was considered to indicate statistical significance. All analyses were performed using SPSS 25.0, GraphPad 8.0 and R, version 4.0.Shapiro–Wilk tests were performed to determine if continuous variables were normally distributed. Normally distributed continuous variables are reported as mean ± standard deviation and non-normally distributed continuous variables are reported as median with interquartile ranges. The two groups were compared using an independent samples t-test and Bonferroni correction  or Mann–Whitney vs 75%, 75 vs 100% and 50 vs 100% all showed clear separation  were performed to evaluate the stability of the OPLS-DA models . The S-pquadrant . The siges <0.05 . The metes <0.05 . These dMetaboAnalyst 5.0 was used to investigate the metabolic pathways involved in the functional mechanisms of different energy supplies. Seven potential functional pathways, summarized in The results showed that REE increased obviously in the three burned groups and all were higher than that of group C . Two-wayFourteen days after burn injury, plasma levels of Tch, TGs, HDL-C, LDL-C, Alb and TP were remarkably lower in the burned rats than in the normal controls, suggesting that severe burn injury can cause abnormalities in lipid and protein metabolism . In addiThe experimental results showed that the organs of the rats were remarkably damaged after burn, and the indexes reflecting damage of the kidney, myocardium and liver were significantly higher than those in the normal group. Different energy supplies had different effects on organ damage in burned rats. The 100% energy supply significantly reduced BUN, CrEAT, and UA  levels aThe experimental results showed that energy supply had an obvious impact on the mortality rate of rats. No deaths were noted in the 75% and 100% REE-Sup groups, while the mortality rate in the 50% group was 25%. However, there was no significant survival difference between the 50%, 75% and 100% REE-Sup groups analyzed with the log-rank test . CorrespNutrition therapy is an important component of medical treatment in burn care ,31,32. HMetabolomics studies have found that different energy supply methods significantly influence metabolic patterns after burn injury. Sixteen metabolites involved in seven metabolic pathways were identified from different energy supply groups, including the metabolic pathways of proteolysis, gluconeogenesis, glycolysis and ketone bodies; the most significant differences were observed in the proteolysis pathway. In the three energy supply groups, the 50% REE-Sup group had remarkably higher plasma levels of branched-chain amino acids  than the control group and the other two burn groups. The amino acids released from skeletal muscle proteolysis after burn are mainly used for synthesizing acute-phase protein and glucose (gluconeogenesis), which is the body’s protective response to trauma . HoweverThis study further found that low energy intake exacerbated organ damage post-burn, with the most extensive myocardial, liver and kidney damage observed in the 50% REE-Sup group and the least extensive damage observed in the 100% REE-Sup group among the three energy supply groups. Burn stress, ischemia/hypoxia and uncontrolled inflammation are major contributors to organ damage; additionally, malnutrition can exacerbate organ damage and inhibit tissue repair ,39. ClinThe nutritional program of burn patients should be adjusted over time, based on the burn course and the patient’s status ,44. The Although this study determined the optimal protocol of energy supply for burned rats, another important issue of clinical nutrition, the nutritional formula, was not explored. Thus, to determine the optimal energy supply scheme, we will next explore the optimal nutritional formula. In addition, whether a nutritional regimen optimized for animal models is suitable for human burn patients still requires verification through prospective randomized controlled trials.Different energy supply methods can markedly affect metabolic patterns and burn prognosis. A higher energy supply is conducive to mitigating metabolic disorders after burn injury, reducing weight loss and organ damage and improving burn patient prognosis. In the three dose groups in this study, the optimal EN regimen was to supply rats with energy at 75% of REE in the first week post-burn and 100% of REE in the second week.Alb: Albumin; ALP: Alkaline phosphatase; ALT: Alanine aminotransferase; AST: Aspartate aminotransferase; BUN: Blood urea nitrogen; CrEAT: Creatinine; CK-MB: Creatine kinase isoenzyme MB; GGT: Glutamyltransferase; α-HBDH: α-Hydroxybutyrate dehydrogenase; HDL-C: High-density lipoprotein cholesterol; LAL: Limulus amebocyte lysate; LDH, Lactate dehydrogenase; LDL-C: Low-density lipoprotein cholesterol; LPS: Lipopolysaccharide; NAG: N-Acetylated glycoproteins; NMR: Nuclear magnetic resonance; OPLS-DA: Orthogonal partial least-squares discriminant analysis; PCA: Principal component analysis; REE: Resting energy expenditure; TBA: Total bile acid; TBIL: Total bilirubin; TP: Total protein; Tch: Total cholesterol; TGs: Triglycerides, UA: Uric acid; VIP: variable importance in projection; EDTA: Ethylene Diamine Tetraacetic Acid; ANOVA: Analysis of Variance；CFU: colony-forming unit.All animal experiments were performed according to the National Animal Welfare Guidelines and approved by the Institutional Animal Ethics Committee of the Third Military Medical University, Approved Agreement Number AMUWEC2020014. This work was supported by the National Natural Science Foundation of China (No. 81971838), Clinical Research Foundation of TMMU (No. 2018XLC2006) and Innovative Leading Talents Project of Chongqing (NO. CQYC20210303 286).XP designed the trial and control the process. YJY, SS and YZ participated in relevant animal experiments and obtained specimens and data. YZ, SS, DW, YW and YJY obtained test data. YJY and SS participated in statistical analysis and drafted the manuscript. All authors discussed the results and commented on the manuscript.The authors declare no conflict of interest.Supporting_Information_tkac042Click here for additional data file.


Rheumatoid arthritis (RA) patients often exhibit finger/wrist joint symptoms and reduced grip strength. This study aimed to validate grip strength as a measure of frailty in RA patients. Subjects were 424 female RA patients . Frailty was defined as a score of ≥ 8 points on the Kihon Checklist (KCL). Finger/wrist joint symptoms were defined based on tender or swollen joints. Associations between frailty and grip strength were determined using receiver operating characteristic (ROC) curve analysis and multivariable logistic regression analysis. There were 179 subjects with frailty (42.2%). Multivariable logistic regression analysis revealed that frailty was significantly associated with grip strength independently of finger/wrist joint symptoms. In ROC curves, cut-off scores of grip strength for frailty in subjects without and with finger/wrist joint symptoms were 17 kg  and 14 kg , respectively. The results of the present study suggest that grip strength in female RA patients is associated with frailty, with a cut-off score of 17 kg  when RA patients have no finger/wrist joint symptoms. However, when RA patients have finger/wrist joint symptoms, it may be considered to reduce the cut-off score of grip strength. Frailty is a condition that leads to an increased need for long-term care and defined as the intermediate stages of health and disability with age-related declines in physical and cognitive function3. Various negative health outcomes, including COVID-19-related mortality are significantly associated with frailty5. Frailty can reduce healthy life expectancy, however, it can also be recovered with proper interventions since it is clinically considered as the condition of predisability3.In a rapidly advancing aging society, a general goal for reducing nursing costs and improving quality of life is to maintain and improve physical function6. The proportion of RA patients with frailty is estimated to be higher than that of the general population7, and the aging of RA patients is progressing9. As RA treatment has advanced significantly with the introduction of methotrexate, biologics, and Janus kinases inhibitors, the survival rate of RA patients has also improved in tandem10. In an aging society, especially in one like that of Japan, the extension of health life expectancy is important also for RA patients.Rheumatoid arthritis (RA) is a chronic systemic inflammatory autoimmune disease which can lead to joint destruction and physical dysfunction due to synovial inflammation, as well as physical frailty11. It has been reported that a decline in grip strength was associated with mortality, and monitoring grip strength may improve the identification of women at greatest risk of death12. Decreased function and muscle weakness have also been evaluated by grip strength in cancer patients13. Reduced grip strength is one of the Cardiovascular Health Study (CHS) criteria for diagnosing frailty14. A major benefit of grip strength is that it is easy to measure in clinical settings.Grip strength reflects upper limb function as well as whole body physical functionFindings from previous studies have highlighted the importance of detecting frailty early and preventing it in order to promote good health outcomes. However, RA patients often exhibit finger/wrist joint symptoms and reduced grip strength. Accordingly, this study aimed to validate the use of grip strength as a measure of frailty in RA patients, taking into consideration disease activity, especially finger/wrist joint symptoms.15. This study targeted only female RA patients. Cut-off scores of CHS criteria for males and females differ 14. Since this study aimed to confirm the validity of the cut-off score of grip strength, we first targeted females given the small number of male patients in the source population. Comorbidities were defined as diseases that were currently or previously treated by other medical specialists and included diabetes mellitus, hypertension, osteoporosis, interstitial pneumonia, and ever or current malignancy.This study included the RA patients who consecutively visited Japanese Red Cross Nagoya Daiichi Hospital, Japan Community Health Care Organization Kani Tono Hospital, and Yokkaichi Municipal Hospital between June and August 2021. All patients fulfilled the 2010 American College of Rheumatology (ACR)/European League Against Rheumatism (EULAR) classification criteriaThis retrospective study was approved by the Ethics Committees of Nagoya University School of Medicine (2017-0271), Japanese Red Cross Nagoya Daiichi Hospital (2020-451), Japan Community Health Care Organization Kani Tono Hospital (20110901), and Yokkaichi Municipal Hospital (2017-29). We disclosed information pertaining to the study at the cooperating facilities according to the procedure stipulated by the respective Ethics Committees. Informed consent was obtained from all subjects. The study was conducted in accordance with the World Medical Association of Helsinki ethical principles for medical research involving human subjects. Patients’ individual information was anonymized.16), which is a widely used instrument developed by the Ministry of Health, Labour and Welfare in Japan to identify older people at risk of requiring care/support17. KCL consists of 25 self-reporting yes/no questions in total, including seven domains: activities of daily living, physical strength, nutrition, oral function, isolation, cognitive function, and depressive mood17. KCL was reported to be significantly correlated with Fried’s Cardiovascular Health Study criteria, and its validity as a screening tool to assess frailty has been demonstrated16.Frailty categories were defined based on Kihon Checklist (KCL) scores . Measurements were carried out twice with the right hand and the left hand respectively, and the higher value was used for analysis, according to Asian Working Group for Sarcopenia19. Tender and swollen 28-joint count meant the number of tender and swollen joints out of 28 joints 20, and were incorporated into Disease Activity Score 28- C-reactive protein (DAS28-CRP): DAS28-CRP = 0.56*√(tender 28-joint count) + 0.28*√(swollen 28-joint count) + 0.014* + 0.36*ln(CRP + 1) + 0.9621. DAS28-CRP was categorized as follows: clinical remission (DAS28-CRP < 2.3); low disease activity ; moderate disease activity ; and high disease activity 23.First, we defined the dominant side as the higher value of grip strength. Then, finger/wrist joint symptoms were defined as tender and/or swollen joints on the dominant side. Tender and swollen joints referred to articular and periarticular manifestations including joint tenderness and swelling to palpation respectively24. HAQ-DI is calculated as the average of the highest score of questions in each category, and response coding scores of questions are as follows: “without any difficulty” = 0, “with some difficulty” = 1, “with much difficulty” = 2, and “unable to do” = 324. HAQ-DI ≤ 0.5 is defined as functional remission25.HAQ-DI is 20 self-reporting questions consisting of eight categories , and widely used as an index of physical function in RA patientst-test. Ordinal variables and categorical variables are expressed as percentages and were analyzed using Fisher’s exact test. For the purpose of clarifying the associations between HAQ-DI and grip strength, and DAS28-CRP and finger/wrist joint symptoms, linear regression analyses adjusted for age and duration of disease were performed. Multivariable logistic regression analyses were performed to confirm the independent impact of related variables  on frailty. Receiver operating characteristic (ROC) curves were generated to assess the associations between frailty, clinical remission (DAS28-CRP < 2.3)23, functional remission (HAQ-DI ≤ 0.5)25, and grip strength with or without finger/wrist joint symptoms. The point closest to the upper left corner was identified as the best cut-off point. Univariate analysis of variance was performed, and estimated marginal means of grip strength were calculated with age, duration of disease, and BMI as covariates, and stratifying by frailty and finger/wrist joint symptoms.Continuous variables are expressed as mean and standard deviation (SD) and were analyzed using the unpaired http://www.jichi.ac.jp/saitama-sct/SaitamaHP.files/statmed.html), a graphical user interface for R 26, and SPSS version 28.0.0 software . P < 0.05 was considered statistically significant.Statistical analyses were performed with EZR  25 in subjects without finger/wrist joint symptoms and with finger/wrist joint symptoms were 16 kg  and 14 kg , respectively, which were similar to cut-off scores of grip strength corresponding to frailty. When subjects were dichotomized according to CHS grip strength criteria to diagnose frailty 14, the proportion of those with frailty was 58.5/26.7% (grip strength < 18 kg / ≥ 18 kg), the proportion of those with finger/wrist joint symptoms was 43.5/27.6%, and mean grip strength (SD) was 11.2 (4.5)/23.2 (4.4) kg, which were all significantly different between those with grip strength < 18 kg vs those with grip strength ≥ 18 kg.In ROC curve analysis, cut-off scores of grip strength for clinical remission (DAS28-CRP < 2.3)27, as well as finger/wrist joint symptoms. While the cut-off score of grip strength corresponding to frailty in RA patients without finger/wrist joint symptoms was 17 kg, which was similar to one of the CHS criteria for diagnosing frailty 14, the cut-off score of grip strength in RA patients with finger/wrist joint symptoms was 14 kg, which was lower than that in those without finger/wrist joint symptoms. Furthermore, the upper limit of 95% CI for mean grip strength in subjects with frailty and no finger/wrist joint symptoms was 17.3 kg, and that for those with frailty and finger/wrist joint symptoms was 14.7 kg, indicating that RA patients with no finger/wrist joint symptoms having a grip strength less than 18 kg or RA patients with finger/wrist joint symptoms having a grip strength less than 15 kg are frailty. These findings suggest that grip strength in RA patients reflects frailty regardless of finger/wrist joint symptoms and disease activity. The cut-off score of grip strength corresponding to frailty is < 18 kg  when RA patients have no finger/wrist joint symptoms. However, when RA patients have finger/wrist joint symptoms, it may be considered to reduce the cut-off score of grip strength.The present study, to our knowledge, is the first attempt to investigate the association between grip strength and frailty in RA patients, with a specific focus on finger/wrist joint symptoms  and disease activity (DAS28-CRP). Frailty was significantly associated with grip strength independently of age, comorbidities, and disease activity, which were previously reported to be factors related to frailty28. Moreover, grip strength can be measured more easily than lower limb muscle strength and done in a shorter time than answering the questions of KCL, and finger/wrist joint symptoms can be identified immediately. Accordingly, it will be important to clarify which RA patients can be evaluated for frailty using grip strength, and when necessary, to lower the grip strength cut-off score when the patients have finger/wrist joint symptoms. The significance of our present findings is that it reveals the need to reduce the cut-off score of grip strength to predict frailty in RA patients with finger/wrist joint symptoms.Finger/wrist joint symptoms were significantly associated with DAS28-CRP. In daily clinical practice, compared to the calculations of DAS28-CRP, information on finger/wrist joint symptoms can be obtained simply. We also found that grip strength was significantly associated with HAQ-DI. Based on the results of this study, we propose a screening method for evaluating frailty that uses grip strength in combination with finger/wrist joint symptoms. Actually, it is better to calculate DAS28-CRP and HAQ-DI to evaluate the condition of RA patients in detail. However, according to one report, grip strength of RA patients in remission of disease activity was almost equivalent to that of the healthy population27 and HAQ29. Notably, maintaining grip strength from the perspective of preventing frailty may lead to also aiming for clinical and functional remission, which can be the underlying goal of care in RA patients.Cut-off scores of grip strength corresponding to clinical remission (DAS28-CRP < 2.3) and functional remission (HAQ-DI ≤ 0.5) were 16 kg (without finger/wrist joint symptoms) and 14 kg (with finger/wrist joint symptoms), respectively, which were similar to the cut-off score of grip strength corresponding to frailty. It was reported that frailty had significant association with disease activity30 and disease activity31. In this study, even when adjusting for these factors, grip strength was significantly associated with frailty. Furthermore, reduced grip strength may also result from sarcopenia in RA patients32. While higher grip strength is reportedly associated with lower levels of inflammation, leading to lower mortality33, hand involvement in early inflammatory arthritis has been shown to be a strong predictor of a poor long-term disease outcome34. These results suggest that regular follow-up of grip strength and finger/wrist joint symptoms in RA patients may allow for the determination that disease activity is changing (worsening) and the prevention of frailty and the negative health outcomes. Adequate exercise can reduce pain in RA patients35 and improve grip strength36. From the perspective of preventing frailty, exercise may have a synergistic effect when performed in combination with RA drug therapy.Factors that may influence grip strength in RA patients include age37. Finally, physical factors of lower limb function such as walking time and psychosocial factors such as depression, anxiety, and social support, which are related to frailty38, were not evaluated in detail. Since some RA patients do not have frailty despite having poor grip strength, evaluating frailty based only on upper limb function is insufficient. Nonetheless, upper limb function measurements are simple to perform and may serve as a screening index for evaluating frailty in daily clinical practice.This study has several limitations. First, radiographic evaluations were not performed. However, we believe our findings are valid because tender and swollen joints could lead to reduced grip strength regardless of radiographic changes. Second, this study targeted only Japanese female RA patients. It will be important to conduct a study with a larger male RA patient population to confirm the cut-off score for males. Third, we did not obtain information regarding the history of upper limb surgery, which can affect grip strengthIn conclusion, we investigated the association between grip strength and frailty in RA patients. Frailty was significantly associated with grip strength, independently of age, disease activity, and finger/wrist joint symptoms. Measuring grip strength and checking finger/wrist joint symptoms offer a useful and simple way to assess frailty in daily clinical practice. Our findings serve as a foundation for the development of methods to detect and screen for frailty, as well as interventions.


Sorbus domestica at its northern range margin, in western Switzerland. New microsatellite data were combined with published data from across the European distribution of the species. Analyses revealed the presence of mainly one of two species-wide ancestral clusters, i.e., the western European cluster, with evidence that it consists of two cryptic sub-clusters. Average pairwise FST of 0.118 was low across the range, and only allelic richness was reduced in the northern margin compared to more southern and southeastern areas of Europe. Based on our finding of considerable genetic diversity of the species in western and northern Switzerland, we suggest that a national propagation program should focus on collecting seeds from natural, high-density tree stands and propagate locally. More generally, our study shows that rare tree species in marginal areas of their distributions do not necessarily have low genetic diversity or heightened levels of inbreeding, and in those cases probably need no assisted migration in efforts to propagate them.Climate change has aroused interest in planting warm- and drought-adapted trees in managed forests and urban areas. An option is to focus on tree species that occur naturally, but have centers of distribution in warmer and drier areas. However, in order to protect the species pool of genetic diversity, efforts of planting and promotion should be informed by knowledge on the local genetic diversity. Here, we studied the macro- and micro-scale population genetic structure of the rare European fruit tree  The service tree is a Mediterranean species occurring from Spain to northwestern Turkey, reaching its northern distribution limit in central Europe  and an eastern (Austria) cluster  and northwestern Switzerland (N = 73) were collected in 2020 (2) in liquid nitrogen, followed by immediate DNA extraction using the DNeasy Plant Mini Kit . We genotyped all individuals at the seven microsatellite loci used by i.e., MSS5, MSS16, CH01h10, CH01h01, CH02c09, BGT23b and MS14H03  among all European localities with 10’000 permutations. We estimated allelic richness (AR) by rarefaction for each locality with at least 10 individuals with FSTAT 2.9.4 (Ho) and expected heterozygosity (He), the number of alleles, the inbreeding coefficient (FIS) and the number of private alleles by using GenAlEx. Finally, we tested for isolation-by-distance by performing a Mantel test between pairwise geographic and Euclidean genetic distances among individuals within Switzerland. Testing was performed using the package vegan  as the best supported scenario for the complete dataset , separat as the bThe two leading principal component (PC) axes for the complete dataset accounted for 13.0% and 9.0% of the total variation, respectively. While populations generally sorted out by longitude along PC1, there was substantial variation within populations . NeverthFST) being 0.118 , consistent with the presence of both genetic clusters in this region  and localities of the southern and southeastern species range (N = 10), with northern localities having lower allelic richness . The number of alleles identified across the seven loci was 88  are highlighted in bold. The full names of localities are presented in Table 2.Significant Click here for additional data file.10.7717/peerj.14397/supp-5Figure S1A—Allele frequencies for all newly genotyped individuals from CH NW. B—Allele frequencies of the three re-genotyped individuals used by Click here for additional data file.10.7717/peerj.14397/supp-6Figure S2A—Optimum at K=2 for the dataset including all European samples . B—Optimum at K=2 for the dataset including samples from Switzerland and surrounding areas . C—Optimum at K=2 for the dataset including Swiss samples only .Click here for additional data file.


While greater body mass index (BMI) is associated with increased risk of developing atrial fibrillation (AF), the impact of BMI on outcomes in newly diagnosed AF is unclear. We examine the influence of BMI on outcomes and whether this is modified by sex and evaluate the effect of non-vitamin K oral anticoagulants (NOACs) in patients with high BMI.2), 13 095 normal (BMI=18.5–24.9 kg/m2), 15 043 overweight (BMI=25.0–29.9 kg/m2), 7560 obese (BMI=30.0–34.9 kg/m2) and 4081 extremely obese (BMI ≥35.0 kg/m2). Restricted cubic splines quantified the association of BMI with outcomes. Comparative effectiveness of NOACs and vitamin K antagonists (VKAs) by BMI was performed using propensity score overlap-weighted Cox models.GARFIELD-AF is a prospective registry of 52 057 newly diagnosed AF patients. The study population comprised 40 482 participants: 703 underweight , and 55.6% were male. Those with high BMI were younger, more often had vascular disease, hypertension and diabetes. Within 2-year follow-up, a U-shaped relationship between BMI and all-cause mortality was observed, with BMI of ~30 kg/mIn the GARFIELD-AF registry, underweight and extremely obese AF patients have increased risk of mortality and new/worsening heart failure compared with normal or obese patients. Evidence supports an association between high body mass index and risk of atrial fibrillation (AF). However, the evidence of an association between BMI and AF-related outcomes remains unclear.A U-shaped association between BMI and all-cause mortality and heart failure in AF patients is revealed, indicating that underweight or extremely obese patients have a significantly higher risk of mortality and heart failure in comparison with those with normal body weight, overweight or obese patients. BMI, however, does not significantly impact the benefits of non-vitamin K oral anticoagulants (NOACs) versus vitamin K antagonists therapy.In clinical practise, BMI should be measured and considered as a risk factor for outcomes in AF. NOACs could be considered for the treatment of all patients regardless of associated BMI.Atrial fibrillation (AF) is a common arrhythmia associated with significant risk of mortality, cardioembolic stroke and heart failure.Significant sex-based differences exist for both the incidence of AF and the risk of AF-related outcomes.Given the higher risk of non-haemorrhagic stroke in patients with AF, treatment with oral anticoagulation is often recommended.This study evaluates a large international cohort of participants with new-onset AF in GARFIELD-AF. The three principal aims were to: (1) assess associations between BMI, weight and height and the risk of AF-associated outcomes; (2) explore sex-based differences in these associations; and (3) examine the association of obesity with the impact of NOAC therapy in patients with AF.The GARFIELD-AF design has been previously published .2 or >60 kg/m2 were excluded due to likely measurement error in the calculation of height or weight.Patients <20 years of age, without BMI data or for whom follow-up information was unavailable were omitted from the analysis. Those with a BMI of <15 kg/mData were collected using electronic case report forms that were securely submitted electronically to the registry-coordinating centre Dendrite Clinical Systems Ltd . Accuracy and completeness of data was ensured by the coordinating centre, the Thrombosis Research Institute . Data were extracted from the study data base on 30 June 2019.The GARFIELD-AF registry is conducted in accordance with the principles of the Declaration of Helsinki, local regulatory requirements and International Conference on Harmonization–Good Pharmacoepidemiological and Clinical Practice guidelines.Written informed consent was obtained from all study participants. There was no public or patient involvement in the design or execution of the GARFIELD-AF study design. Investigators from representative investigator sites in each participating country were involved in data collection. Confidentiality and anonymity were maintained through assigned unique identifiers. Independent ethics committee and hospital-based institutional review board approvals were obtained. A full list of ethics committees is provided in the 10.1136/openhrt-2022-002038.supp1Supplementary data2), normal (18.5–24.9 kg/m2), overweight (25.0–29.9 kg/m2), obese (30–34.9 kg/m2) and extremely obese (≥35.0 kg/m2).Patients were categorised into five BMI groups according to the WHO definitions: underweight , major bleeding and new/worsening heart failure according to BMI. These outcomes were also analysed according to BMI and sex. Major bleeding was defined as clinically overt bleeding associated with a critical site, a fall in haemoglobin (≥2 g/dL), transfusion of packed red blood cells (≥2 units), haemorrhagic stroke or fatal outcome.2DS2-VASc and HAS-BLED risk scores were collected; the latter was calculated excluding labileinternational normalized ratios (INRs) as this was not recorded at baseline. Clinical outcomes are described by number of events, event rate per 100 person-years estimated via a Poisson model and 95% CIs. Only the first occurrence of each event was considered. Survival differences across BMI groups were examined using Kaplan-Meier curves.Continuous variables are reported using medians and IQR. Categorical variables are presented as percentages and frequency counts. Data for the CHATo identify non-linear association between the continuous variables BMI, weight and height with outcome events, analyses of restricted cubic splines were performed by generating restricted cubic splines with four knots and applying a separate Cox multivariable model for each studied endpoint.Covariate adjustments for Cox models were selected by avoiding the inclusion of factors in the mediating pathway between BMI and clinical outcomes. Apart from the selected demographic characteristic, smoking status and alcohol consumption were included because of their established relationship with BMI. Chronic kidney disease (CKD) was also considered a possible confounder, as CKD often causes weight loss in later stages.Three sensitivity analyses were performed; the first analysed the rate of new/worsening heart failure in patients without baseline heart failure. The second examined the association of BMI and AF outcomes in patients with ≥6 months of follow-up. The third adjusted associations for a broader range of covariates.2DS2-VASc score ≥2 (excluding sex) enrolled in GARFIELD-AF cohorts 3–5 (NOACs were not widely available for patients enrolled in earlier cohorts). Analyses were performed for patients with a normal/overweight BMI (18.5–29.9 kg/m2) and separately for those with an obese/extremely obese BMI (≥30 kg/m2). Patients with a BMI <18.5 were not included. HRs for NOAC versus VKA were obtained using a Cox proportional hazards model via a propensity method of overlap weighting to balance covariates in the population. Treatment was defined as the first treatment received at the time of enrolment, approximating ‘intention-to-treat’. Absolute standardised differences for NOAC versus VKA comparison before and after propensity score weighting among normal weight or overweight patients (BMI 18.5–29.9 kg/m2) and obese or extremely obese patients (BMI ≥30 kg/m2) have been presented in Comparative effectiveness analyses of NOAC versus VKA were performed in a study population restricted to anticoagulated patients at baseline with a CHAOnly complete cases are presented in descriptive tables. Multiple imputation was applied in the derivation for the modelling process for the estimation of the BMI effect; coefficients and SEs for the risk models were obtained by combining estimates across five imputed datasets. Single imputation was applied for the NOAC versus VKA comparison. P<0.05 were considered statistically significant. Statistical analyses were carried out using SAS (V.9.4).2), and median weight was 75.0 kg . Those with higher BMI were generally younger, more often had diabetes mellitus, hypertension and vascular disease at enrolment and were more likely to have been diagnosed with permanent AF. Baseline demographic characteristics are provided in2DS2-VASc≥2, 62.1% vs 70.1%, p<0.0001, A total of 40 482 participants were eligible for inclusion within the main analysis: underweight (n=703), normal weight (n=13 095), overweight , obese (n=7560) and extremely obese (n=4081). The median age of participants was 71.0 years  and slightly over half of the participants were male . Median BMI was 26.9 kg/m2  died, 770 (1.9%) suffered a non-haemorrhagic stroke/SE, 730 (1.8%) had a major bleeding event and 589 (1.5%) had a new or worsening heart failure event . Cumulat2. Below 30 kg/m2, there was a 32% higher risk of mortality per 5 kg/m2 lower BMI (95% CI 25% to 40%). Above 30 kg/m2, there was a 16% higher risk of mortality per 5 kg/m2 higher BMI (95% CI 9% to 23%). The lowest risk of new/worsening heart failure was at ~25 kg/m2. Above 25 kg/m2, each 5 kg/m2 higher BMI was associated with a 23% higher risk (95% CI 14% to 33%). For major bleeding, there was a positive association only in those with low BMI. There was no association between non-haemorrhagic stroke and BMI.After adjustment, restricted cubic spline regression demonstrated a U-shaped relationship between BMI and all-cause mortality and new/worsening heart failure; both low and high BMI were positively associated with events . The lowAs with BMI, weight showed similar associations with AF outcomes. A U-shaped relationship was observed between weight and all-cause mortality and new/worsening heart failure, with both low and high weight being positively associated . The low2 higher BMI above 30 kg/m2) compared with men , the difference in this specific BMI range was not significant (p-interaction 0.32). Conversely, lower BMI (<30 kg/m2) was similarly associated with risk of all-cause mortality in women  and men .BMI showed similar association in both men and women with all-cause mortality; however, there were apparent differences in the strengths of association, p value for interaction assuming a linear trend: 0.01 . While hIn patients without baseline heart failure, the association between BMI and weight and risk of new heart failure (330 events) was similar . No assoLimiting the analysis to participants with at ≥6 months of follow-up (n=39 081) did not affect the association between BMI and AF outcomes . Further2 increase). Conversely, there was no meaningful difference in the negative association between low BMI (<30 kg/m2) and all-cause mortality  included suspected mediators of the association between higher BMI and risk of AF outcomes. This led to a substantial attenuation of the association between higher BMI and risk of all-cause mortality  and those with an obese/extremely obese BMI . No significant difference was observed in the effect of NOAC therapy between BMI groups  and ORBIT-AF participants (n=9513).et al2. Above this level, a strong positive association existed. While not in keeping with most studies examining AF patients, it is consistent with the association between BMI and mortality in the general population.Previously, an inverse relationship has been demonstrated between BMI and mortality in AF. Post hoc analysis of 21 028 ENGAGE TIMI-48 trial participants showed a ~10% lower risk of death and stroke per 5 kg/met al demonstrated a 6% higher risk of heart failure per 1 kg/m2 higher BMI in those with AF (AF cases=725).The association of BMI with the risk of heart failure in AF has not been well established. Schnabel 2), suggesting that over adjustment may have produced the previously reported negative association between BMI and mortality.Reasoning for the difference in our findings compared with prior groups is unclear. This study was limited to new-onset AF. Inclusion of participants previously diagnosed with AF, such as in ORBIT-AF and AFFIRM,The mechanisms underlying the association between BMI and AF outcomes are not clearly established. Greater BMI has been associated with higher risk of hypertension,Trend differences were observed in the BMI association with outcomes between sexes; high BMI was more strongly associated with mortality among women. However, the observed differences were numerically small, and more research is required to identify significant effect modifications between sexes.Despite a strong association between height and risk of AF, there has been limited assessment of the association of height with AF-related outcomes. Height has previously been shown to be inversely associated with risk of stroke and cardiovascular disease.The causal relevance of this association between BMI and AF outcomes is not clear. However, previous trials of weight loss in patients with AF have demonstrated substantial improvements in symptoms and AF burden.et alThe potential detrimental effects of raised BMI on the efficacy of NOAC therapy have been raised previously.This study has several strengths, including its large size, data on a broad range of major potential confounders and excellent participant follow-up. However, observational associations can be subject to uncontrolled residual confounding. Additionally, the lack of more detailed anthropometric measures limits our ability to make mechanistic inferences. As AF development is casually linked to BMI and a series of clinical endpoints, by restricting enrolment to AF patients, the obtained associations between BMI and clinical endpoints are possibly subject to collider stratification bias. Studies that collect longitudinal BMI measurements preceding AF incidence and the application of time-varying exposure methods would help quantify the magnitude of this bias.Our findings from this large-scale observational cohort suggest important associations between both high and low BMI and risk of mortality and new/worsening heart failure in those with AF. These findings are not in line with the so-called ‘obesity paradox’ and suggest that further investigation of weight management strategies in those with AF may reduce mortality and heart failure risk.


Novel poly (PVA)/poly (P(VB-VA)) films with improved hydrophobicity were prepared from poly(vinyl acetate) (PVAc)/poly (PVB) blend films with various mass ratios by saponification in a heterogeneous medium. The successful conversion of PVAc to PVA and PVAc/PVB to PVA/P(VB-VA) films was confirmed by Fourier transform infrared spectrometry, X-ray diffraction, and proton nuclear magnetic resonance analysis. This study also shows that the degree of saponification (DS) depends on the saponification time. The maximum DS of 99.99% was obtained at 96 h of saponification for all films, and the presence of PVB did not affect the DS at saponification times of 48–96 h. The effects of the PVAc/PVB blend ratio before and after saponification were determined by contact angle measurement, and the hydrophobicity was found to increase in both cases with increasing PVB content. Additionally, all the films exhibited improved mechanical properties after saponification, and the treated films possessed an unusual porous and uneven surface, in contrast with the untreated films. The prepared films with improved hydrophobicity can be used for various applications, such as biomaterials, filters, and medical devices. Polymeric matrices are important in biomedicine, particularly for dialysis and cardiac treatment. The materials applied in biomedical devices must have certain characteristics, including low cost and biocompatibility . PolymerPoly (PVB) is thought to be an acetal, and is prepared by reacting an aldehyde and alcohol . Figure Among various polymers, PVAc exhibits good mechanical stability, and PVAc films are easily prepared . This syPVAc has also been applied in medicine because of its biocompatibility. Because it is an inert polymer, it does not cause harmful reactions in living tissue ,19. PVA PVA with improved properties can be prepared by heterogeneous saponification. For example, Yang et al.  preparedOur group has conducted the majority of the work on heterogeneous saponification. We have generated nanocomposite microspheres ,23, nanoSimilarly, in this study, we prepared saponified PVA/PVB blend films from PVAc/PVB blend films using our unique saponification method. Due to the hydrophobicity of PVB and the hydrophilicity of PVA, these blend films are generally difficult to fabricate owing to the variations in the solubility of cosolvents, poor compatibility between the hydrophobic matrix and hydrophilic polymer, and phase separation may occur during the film production process ,35. The 4 solution and distilled water. Next, anhydrous CaCl2 was used to dry the VAc. Finally, the VAc was distilled in a nitrogen atmosphere at reduced pressure. PVB  was purchased from Sigma-Aldrich. An initiator, 2,2′-azobis (ADMVN), was acquired from Wako Co. ; before use, it was recrystallized twice. PVA  was also purchased from Sigma-Aldrich. The NaOH, Na2SO4, and methyl alcohol (MeOH) needed for the saponification reaction were obtained from Duksan Co. . MeOH was used as a solvent to prepare the blend films.Vinyl acetate (VAc) was purchased from Sigma-Aldrich . First, it was cleaned using an aqueous NaHSOPVAc powder was prepared by suspension polymerization as described in our previous publication . In a chFilm solutions of neat PVAc and PVAc/PVB with blend ratios of 90/10 and 80/20 were prepared successfully using methanol according to the solution weight. The polymer solution was kept at 10 wt. %. The prepared PVAc/PVB blend solution (10 g) was then cast in a Teflon Petri dish (100 mm × 10 mm). After casting, the Petri dish was placed in a vacuum oven at 35 °C to obtain a smooth surface. The prepared PVAc/PVB blend films were then converted to PVA/P(VB-VA) films by heterogenous saponification .Heterogeneous saponification of PVAc/P(VB-VA) films was carried out in a flask equipped with a reflux condenser, a thermocouple, a dropping funnel, and a stirring device to synthesize PVA/P(VB-VA) nanocomposite films. In total, 10 g of sodium hydroxide, 10 g of sodium sulfate, 10 g of methanol, and 100 g of water was required to induce the saponification of the alkali solution. To prevent floating and twisting in the solution, rectangular pieces of each PVAc/PVB film (size varied depending on characterization method) were wrapped in mesh fabric by sewing. They were then placed into the flask comprising the alkali solution. After the saponification reaction, they were taken out of the flask, submerged in cold water, and left to precipitate for 1 min. After that, the saponified film was completely water washed. The saponified film was then thoroughly rinsed with water and dried at room temperature until completely dry. Except for NMR, where 0–96-h-saponified films are utilized, all characterization was conducted using film saponified for 72 h. PVB saponification is supported by another report, which showed the effect of alkaline treatment on PVB by NMR analysis .−1. A fixed load (500 kgf) and displacement (200 mm) were used. For each condition, three samples (2 cm × 8 cm) were prepared, and the mean values of the three samples were calculated. The elongation and tensile strength were calculated according to the literature [The film thickness  was calcterature .The surface topography of the films was examined using optical microscopy , and the surface roughness was measured using atomic force microscopy . The water contact angle (WCA) was measured according to the literature  using a 1H-NMR) analysis  by dissolution in d6-dimethyl sulfoxide. After analysis, the DS was calculated from the 1H-NMR results according to the literature [−1 at a resolution of 4 cm−1. To confirm that PVAc/PVB was converted to PVA/P(VB–VA), X-ray diffraction (XRD) analysis  was performed. During scanning, the pressure and voltage were 40 mPa and 40 kV, respectively, and the scanning speed was 4 °C min−1. Thermogravimetric analysis (TGA)  was performed to study the thermal properties of the saponified and unsaponified films. TGA was performed under a nitrogen atmosphere over a temperature range of 20–600 °C, at a heating rate of 10 °C min−1.PVAc/PVB samples were prepared for proton nuclear magnetic resonance (terature . To conf1H-NMR measurements). At higher PVB contents, agglomeration occurred, which caused voids to form in the polymer matrix. These voids and agglomeration resulted in poor interfacial adhesion between the two components. As a result, the tensile strength decreased [The optical microscopy images of the blend films in ecreased .−1 and other peaks at 1433–1435 cm−1 (C–H), 1371–1372 cm−1 (C–H), 1227–1235 cm−1 (C–O), and 1019–1021 cm−1 [−1 decreases gradually with increasing PVB content in the blends; however, no distinct peak corresponding to PVB, for example, the –OH peak at 3486 cm−1, is identified, possibly because of the relatively low PVB content compared to PVAc in the PVAc/PVB 90/10 blend film. However, the vibration energy of –OH stretching is suppressed by steric hindrance in the 80/20 blend film, which may be attributed to the crosslinked network structure of PVB [−1 because of O–H stretching induced by both intermolecular and intramolecular hydrogen bonds [The structure of films with various blending ratios was evaluated using FTIR, as shown in 021 cm−1 . The spee of PVB . By conten bonds . −1 are also attributed to the formation of a PVA/P(VB–VA) film from a PVAc/PVB film. The conversion of PVAc/PVB to PVA/P(VB–VA) caused the observed changes in vibration bands. Minor changes in peak position and intensity at 500–2000 cmThe XRD patterns of the saponified and unsaponified films are shown in 1H-NMR spectra of the unsaponified and saponified pure PVAc film and PVAc/PVB 90/10 and 80/20 blend films obtained at various saponification times. The spectra reveal the conformational changes of PVAc to PVA and PVAc/PVB to PVA/P(VB–VA), in good agreement with the FTIR results shown in 1H-NMR spectra using the Mnova NMR program . At saponification times of 48, 72, and 96 h, the presence of PVB did not affect the DS of any of the films. For all the films, the methyl peak was clearly absent, and the methylene peak appeared after saponification, indicating the successful conversion of PVAc to PVA and PVAc/PVB to PVA/P(VB-VA)  . That isponified ,55.The effect of saponification on the thermal stability of the pure PVAc film and PVAc/PVB blend films with different ratios were examined by TGA and derivative thermogravimetry (DTG), and the results are shown in T10% and Tmax, possibly because of the increase in water-insoluble polymer network structure with increasing PVB content.The conversion of the methyl group of PVAc to the methylene group of PVA significantly decreased the thermal stability of the films. For the neat PVAc films, 10% weight loss occurred at approximately 296.85 °C; however, the value decreased to 219.45 °C after saponification. The PVAc/PVB 90/10 and 80/20 blend films exhibited similar behavior. In addition, the PVAc/PVB 80/20 films show slightly better thermal stability than the films with other blend ratios in terms of Tmax was 315.78 °C, and the maximum weight loss rate was 2.05% min−1. For the saponified PVAc, the values were 234.03 °C and 1.54% min−1, respectively. All the saponified film had similar Tmax values.For the neat PVAc films, As shown in εb), ultimate tensile strength (σu), and tensile stress at break (σb) of the treated and untreated PVAc/PVB blends and pure PVAc films were estimated. Materials are expected to undergo different types of stresses during application; thus, it is necessary to measure the mechanical properties to predict the performance of materials.2S hybrid polymer film [The stress–strain curve of the saponified pure PVAc film shows strain hardening and necking. Strain hardening indicates increased resistance to distortion after extension and the alignment of polymer chains in the saponified PVAc film; it is also affected by the presence of PVB in the saponified PVAc/PVB blend films. The same behavior was also observed in a PVA–polyethylene glycol–Agmer film .To evaluate the wettability of the saponified and unsaponified films, the WCA was measured. As shown in 1H-NMR. All the saponified films showed an unusual porous and uneven surface, which is expected to be useful for medical applications. Additionally, saponification improved the mechanical properties of all the studied films. The saponified PVAc film showed the maximum breaking stress (45.53 ± 0.25 MPa); however, the breaking stress was reduced by the presence of PVB in the saponified PVAc/PVB 90/10 and 80/20 blend films . Because the –OCOCH3 of PVAc was converted to the –OH of PVA, the thermal stability of the films was significantly lower after saponification; however, the saponified films showed greater thermal stability compared to the unsaponified films above the degradation temperature of 330.50 °C. The enhanced thermal properties of the prepared saponified PVA/PVB films were also revealed by the lower maximum weight loss rate (1.54 to 1.06% min−1) compared to unsaponified PVA/PVB films (2.05–1.87% min−1). The experimental results indicate that DS (81.98–99.99%) varies with reaction time under the same saponification conditions, and the detailed structure of PVA film can be established using XRD studies. The characteristic O-H peak at 2θ = 19.8° and broad bands appearing at 3600–3200 cm−1 in XRD pattern and FTIR spectra provide further evidence of the conversion of the PVAc/PVB to PVA/P(VB-VA). The WCA values of the prepared saponified PVA/PVB films (27.41–49.14°) compared to prepared unsaponified PVA/PVB films (57.68–76.54°) reveal that hydrophilicity increased after saponification because of the conversion of PVAc to PVA; however, the hydrophobicity increased with increasing PVB content. Finally, the saponified PVA and PVA/P(VB-VA) films with increased hydrophobicity show promise for applications in drug delivery, biomaterials, tissue engineering, filtration, food packaging, and medical devices.Saponified PVA and PVA/PVB films with blend ratios of 90/10 and 80/20 and various DSs (81.98–99.99%) were prepared from PVAc/PVB films at saponification times of 24, 48, 72, and 96 h at 50 °C. The conversion of PVAc/PVB to PVA/P(VB-VA) was confirmed by


Early identification of axillary lymph node metastasis (ALNM) in breast cancer (BC) is still a clinical difficulty. There is still no good method to replace sentinel lymph node biopsy (SLNB). The purpose of our study was to develop and validate a nomogram to predict the probability of ALNM preoperatively based on ultrasonography (US) and clinicopathological features of primary tumors.From September 2019 to April 2022, the preoperative US) and clinicopathological data of 1076 T1-T2 BC patients underwent surgical treatment were collected. Patients were divided into a training set (875 patients from September 2019 to October 2021) and a validation set (201 patients from November 2021 to April 2022). Patients were divided into positive and negative axillary lymph node (ALN) group according pathology of axillary surgery. Compared the US and clinicopathological features between the two groups. The risk factors for ALNM were determined using multivariate logistic regression analysis, and a nomogram was constructed. AUC and calibration were used to assess its performance.p = 0.009), histologic grades (p = 0.000), molecular subtypes (p = 0.000), tumor location (p = 0.000), maximum diameter (p = 0.000), spiculated margin (p = 0.000) and distance from the skin (p = 0.000) were independent risk factors of ALNM. Then a nomogram was developed. The model was good discriminating with an AUC of 0.705 and 0.745 for the training and validation set, respectively. And the calibration curves demonstrated high agreement. However, in further predicting a heavy nodal disease burden (> 2 nodes), none of the variables were significant.By univariate and multivariate logistic regression analysis, age . Breast cancer (BC) is the most common cancer in women and the second most common cause of death from cancer among women in the world . AxillarAt present, imaging examination is used as non-invasive method to confirm the ALN status in preoperative, such as Mammography (MG), Ultrasonography (US), Positron Emission Tomography-Computed Tomography (PET-CT) and Magnetic Resonance Imaging (MRI). Among the various imaging techniques, US is the primary method to preoperative evaluate the axilla in women with newly diagnosed BC, because it is economical, simple and widely used , and manRecently, based on the development of artificial intelligence, particularly deep learning, people have begun to shift their attention from axillary US to the US features of primary tumor in early-stage BC, and found that the features of the primary tumor are also of good value for the prediction of ALNM , 10. ArtCollected US and clinical features of 2001 BC patients who underwent surgical treatment in Cancer Center, Wuhan Union Hospital from September 2019 to April 2022. The inclusion criteria included female, clinical stageT1-T2, complete ultrasound and clinicopathological data. The excluded criteria were male, clinical stage greater than T2, incomplete record of clinical or ultrasound data, axillary US found suspicious lymph nodes and confirmed by puncture before surgery or undergoing neoadjuvant chemotherapy. Axillary US findings of suspicious lymph nodes include diffuse cortical thickness, asymmetric cortical thickness, and complete or near-complete absence of fatty hilum. Finally, a total of 1076 patients were included and 925 cases were excluded, the patient selection process was illustrated in Fig. This retrospective study was conducted in accordance with the ethical standards of Declaration of Helsinki and was approved by the Ethics Committee of Tongji Medical College, Huazhong University of Science and Technology. The need for written informed consent to participate was waived by the Ethics Committee of Tongji Medical College, Huazhong University of Science and Technology due to retrospective nature of the study.Patients' medical data were obtained from the medical records, all US images of the mass were digitally stored and retrospectively reviewed, three radiologists (with 6–10 years of experience in breast US) blinded to the axillary surgery results independently reviewed the US images. First, they independently analyze US images, when they encounter differences, they discuss together to reach a consensus. Only preoperative US performed before treatment is considered. US features of tumor included: multifocality or unifocal, maximum diameter of lesion, quadrant, shape, orientation, angular margin, spiculated margin and distance from the skin. If patients had multiple tumors on US, the largest tumor was selected for analysis. The clinicopathological features, including histologic types, histologic grades, hormonal receptors and molecular subtypes, were obtained by preoperative US-guided coarse needle biopsy (CNB).Lymph nodes metastasis was classified as macro-metastases(> 2 mm), micro-metastases (0.2-2 mm) or isolated tumor cells (ITC) (< 0.2 mm) based on pathologic examination. We described the nodal stage according to the TNM staging system from the eighth edition of the American Joint Committee on Cancer staging manual . ITC werThe status of estrogen receptor(ER), progesterone receptor(PR) and human epidermal growth factor receptor 2(HER2) were was determined by immunohistochemical (IHC) staining. ER or PR was considered positive if there are at least 1% positive of the nuclear-staining cancer cells. Fluorescence in situ hybridization (FISH) was used to determine HER2 status in cases of IHC staining 2 + . According to the St Gallen International Expert Consensus 2013 , breast t-test was used by continuous data. χ2 test and fisher exact tests were used to evaluate data from categorical variables.Statistical analysis was performed using SPSS 22.0 and R Software ver.4.1.0. continuous data were presented as mean ± SD. Categorical variables were expressed as numbers and percentages of the group from which they were derived. Student’s p values. The p < 0.05 was considered statistically significant. Post hoc analysis was conducted using the Bonferroni method to distinguish the differences among molecular subtypes and histologic grades.Variables had statistically significant in the univariate analysis were used to fit the logistic regression model employing a ‘‘stepwise’’ variable selection procedure. Estimated parameters were reported as Odds Ratios with 95% confidence intervals and p < 0.05 was considered statistically significant.The multiple logistic regression model was builted, and the representative nomogram of the model was constructed in the training set. The internal and external validation of our predictive model was assessed in both training set and validation set. For the validation, the calibration and discrimination were evaluated with Hosmer–Lemeshow goodness-of-fit test and the area under the curve (AUC). In the part of predicting a heavy nodal disease burden (> 2 nodes). χ2 test and fisher exact tests were used for data analysis, The n = 875) and validation set (n = 201) was listed in Table Of these 1076 patients, the mean age of selected patients was 52.0 ± 10.7 years (from 21 to 85 years), 510 (47.4%) of them had pathological positive axillary nodes (pN +), and other 566 (52.6%) of them had pathological negative axillary nodes (pN0). Among the 510 positive ALNs, patients with pN1, pN2 disease were 395(77.5%),115(22.5%)respectively. 221 (43.3%) of them had a heavy nodal disease burden (> 2 nodes), and other 289 (56.7%) of them had a low nodal disease burden (≤ 2 nodes). Among all patients, 355 (33.0%) patients received SLNB alone, 398 (37.0%) patients received ALND alone, and 323 (30.0%) patients received SLNB followed by ALND. Among the patients receiving SLNB alone, 15 patients with positive SLNB were omitted ALND, and 11 of them had one micro-metastasis; 2 of them had two micro-metastases; 2 of them had one macro-metastases. The comparison of the US and clinicopathological features of patients between our training set (P < 0.05), but there is no statistically significant difference between grade II and III. In molecular subtypes, the ALNM rates were 72.0% for luminal B HER2 ( +), 51.9% for luminal B, 50.0% for TN, 48.1% for HER2-enriched, and 37.4% for luminal A. Luminal B HER2 ( +) was more prone to ALNM, with a statistically significant difference compared to all other types . There was a statistically significant difference between luminal B HER2 (-) and luminal A (p < 0.05). But there were no statistically significant difference between HER2-enriched and TN compared with luminal B HER2 (-) or luminal A .Univariate analysis was conducted in the training set Table . In histCombining US and clinicopathological features of the tumor, binary logistic regression analysis as shown in Table A nomogram to predict the likelihood of ALNM was developed based on the results of the multivariate logistic regression, points were assigned to each variable, then summed to yield the total number of points Fig. . The modAmong the 437 positive ALN patients in the training set, 179 (41.0%) of them had a heavy nodal disease burden (> 2 nodes), and other 258 (59.0%) of them had a low nodal disease burden (≤ 2 nodes). Univariate analysis showed that, of all preoperative ultrasound and clinicopathological features, no variable was associated with a heavy nodal disease burden (> 2 nodes),  and 0.745 (95% CI: 0.679–0.812) for the training and the validation set, respectively. Two studies had also established nomograms to predict ALNM based on US and clinicopathological features , 17. BotIn the predictive model of this study, histological grades were the most important variable. Histological grade III showcased the highest predictive value, compared with patients with grade I, the OR is 4.742. In previous studies, histological grade was also demonstrated a significantly risk factors for ALNM , 12, 16.Molecular subtypes were also an important factor in ALNM, but the controversy regarding the relationship between molecular subtypes and ALNM is existing. Jones et al.  found thOur study showed that molecular type was associated with ALNM, and the nomogram showed it was the second important variable in the prediction model. The ALNM rate of patients with luminal B HER2 ( +) was the highest (72.0%), and significantly higher than other subtypes. This is consistent with some research –22, 25. In this study, spiculated margin was the third important variables in the prediction model. spiculated margin is one of the important characteristics of tumor invasive growth, and is more prone to ALNM. The reason may be the over expression of VEGF and MMP-9 in BC patients with burr sign . VEGF caLocation and size of primary tumor are also important indicator of prognosis , 32. SomDistance from the skin was found a risk factor of ALNM in our study. The natural dominant drainage for the outflow of lymph from the superficial areas of the breast is to the ALNs. This pathway plays a primary role in the initial stages of breast cancer. The superficial lymphatic drainage, as described by Sappey, was located from the skin to a 3 mm depth , 36. OurAge of onset also was associated with ALNM . In our Our study had several limitations. First, our study was a single-center retrospective study which was limited by the deficient collection of risk factors related to BC, such as menstruation and fertility. Second, there were subtle differences between training and validation set which may reduce the reliability of validation. Further research focused on validation will extend the generalized use of the nomogram. At last, studies had shown that elasticity was associated with ALN status , howeverIn conclusion, the clinical approach to ALN management of BC patients is becoming more and more conservative. So, accurate assessment or/and prediction of ALN status before opreation are helpful to determine the best treatment plan. Our study developed and validated a prognostic nomogram with preoperative US and clinicopathological features, for the prediction of ALNM in patients with T1-T2 breast cancer. This nomogram performed well and might be helpful in risk stratification and decision-making for early BC patients. However, this study is poor prediction in a heavy nodal disease burden (> 2 nodes).


Although anxiety disorders are one of the most prevalent mental disorders, their underlying biological mechanisms have not yet been fully elucidated. In recent years, genetically determined metabolites (GDMs) have been used to reveal the biological mechanisms of mental disorders. However, this strategy has not been applied to anxiety disorders. Herein, we explored the causality of GDMs on anxiety disorders through Mendelian randomization study, with the overarching goal of unraveling the biological mechanisms.P < 1.03 × 10–4). Furthermore, metabolic pathways analysis was performed using the web-based MetaboAnalyst 5.0 software. All statistical analysis were performed in R software. The STROBE-MR checklist for the reporting of MR studies was used in this study.A two-sample Mendelian randomization (MR) analysis was implemented to assess the causality of GDMs on anxiety disorders. A genome-wide association study (GWAS) of 486 metabolites was used as the exposure, whereas four different GWAS datasets of anxiety disorders were the outcomes. Notably, all datasets were acquired from publicly available databases. A genetic instrumental variable (IV) was used to explore the causality between the metabolite and anxiety disorders for each metabolite. The MR Steiger filtering method was implemented to examine the causality between metabolites and anxiety disorders. The standard inverse variance weighted (IVW) method was first used for the causality analysis, followed by three additional MR methods  methods) for sensitivity analyses in MR analysis. MR-Egger intercept, and Cochran’s Q statistical analysis were used to evaluate possible heterogeneity and pleiotropy. Bonferroni correction was used to determine the causative association features  was the most reliable causal metabolite. Our results were robust even without a single SNP because of a “leave-one-out” analysis. The MR-Egger intercept test indicated that genetic pleiotropy had no effect on the results . No heterogeneity was detected by Cochran’s Q test . A directionality test conducted by MR Steiger confirmed our estimation of potential causal direction (P < 0.001). In addition, two significant pathways, the “primary bile acid biosynthesis” pathway (P = 0.008) and the “valine, leucine, and isoleucine biosynthesis” pathway (P = 0.03), were identified through metabolic pathway analysis.In MR analysis, 85 significant causative relationship GDMs were identified. Among them, 11 metabolites were overlapped in the four different datasets of anxiety disorders. Bonferroni correction showing1-linoleoylglycerophosphoethanolamine (ORThis study provides new insights into the causal effects of GDMs on anxiety disorders by integrating genomics and metabolomics. The metabolites that drive anxiety disorders may be suited to serve as biomarkers and also will help to unravel the biological mechanisms of anxiety disorders.The online version contains supplementary material available at 10.1186/s12967-022-03691-2. Anxiety disorders are a significant health problem widespread and are the leading psychiatric causes of the global burden of diseases . The WorIn recent years, modern omics-based technologies, including metabolomics, have made a positive contribution to the exploration of disease mechanisms. Specifically, metabolomics can provide novel information into the biological mechanisms of diseases by revealing the intermediate metabolites and altered metabolic pathways , 10. A rMendelian randomization (MR) analysis is a useful epidemiological research strategy in which genetic variants are used to connect exposure with outcome as instrumental variables (IV) for assessing causal relationships. Compared to other epidemiological research strategies, MR can provide unbiased estimates on how genotypes are decided at conception, and are commonly not susceptible to confounding factors and reverse causation . Given tHerein, we speculated that this GDMs atlas could be used to infer the causality of GDMs on anxiety disorders. Consequently, we implemented a two-sample MR approach to: (1) assess the causal effects of human serum metabolites on anxiety disorders; (2) identify the GDMs that have causal effects on four different GWASs of anxiety disorders; and (3) identify potential metabolic pathways which might help to understand the mechanism of anxiety disorders.http://metabolomics.helmholtz-muenchen.de/gwas/). Notably, Shin et al. [https://www.metabolon.com/). After strict quality control, 486 metabolites in total were analyzed, including 309 known metabolites and 177 unknown metabolites. Moreover, the 309 known metabolites were further classified into eight biochemical classes  in conformity to the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Notably, genotyping information for the two cohorts are described detailly in previous research [The general design of this MR research was stated in Additional file n et al.  reportedresearch , 25. FinP < 1 × 10–5, which are mostly used in MR analysis to elucidate a greater variation when few SNPs are available for exposure. Second, independent variants were identified using a clumping procedure implemented in R software, in which a linkage-disequilibrium threshold of r2 < 0.5 within a 5000 kb window in the European 1000 Genomes Project Phase 3 reference panel was set. Instrumental SNPs were selected by removing palindromic SNPs with middle allele frequency (MAF). Palindromic SNPs are those with the A/T or G/C allele, whereas the MAF is from 0.01 to 0.30. SNPs with the incorrect causal direction are excluded by MR Steiger filters. SNPs with an MAF less than 0.01 were also excluded from the original GWAS because of their low confidence level. Next, we used the explained variance (R2) and F statistic parameters to determine whether the identified IVs were powerful enough to represent metabolite levels. The above design formula is presented in Additional file F > 10 is suggested for MR analysis. The mRnd was used to calculate the statistical power for Mendelian randomization (https://cnsgenomics.shinyapps.io/mRnd/).In principle, the instrumental variables used in MR analysis must satisfy the following three assumptions: (1) IVs must be relevant to exposure ; 2) IVs must be associated with outcome  only via exposure ; and (3) IVs must be independent of any confounder . To dete IVs musthttp://app.mrbase.org/) database (20).This study aimed at evaluating the potential causal relationship between metabolites and anxiety disorders with a wide range of impact in both males and females from MRC-IEU. Anxiety disorders are typically diagnosed on the basis of structured clinical interviews for the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) and the tenth edition of the International Classification of Diseases (ICD-10). Anxiety disorders also can be screened with self-report questionnaires. Moreover, providing care for mental health problems including anxiety disorders concerns general practitioners, and psychiatrists , 28. TheP < 0.05 was considered statistically significant. We adopted a multiple-testing-adjusted threshold of P < 1.03 × 10−4 (0.05/486) using the Bonferroni correction to declare a statistically significant, causal relationship [P < 0.05, but were above the Bonferroni-corrected threshold, as suggestive risk predictors for anxiety disorders.The IVW method  was used to assess causal effects for two-sample MR analyses. Notably, the IVW method can provide a consistent assessment of the causality of the exposure when each variant satisfies all three assumptions of valid instrumental variables. An estimate of IVW can be obtained by calculating the slope of the weighted linear regression . Next, stionship . We alsohttps://www.metaboanalyst.ca/) [PIVW < 0.05).Metabolic pathway analysis was performed using the web-based Metaconflict 5.0. (yst.ca/) . Functioyst.ca/)  and the F statistic of these IVs was 10.23, suggesting that all IVs were sufficiently effective for the MR analysis of the 486 metabolites (F statistic > 10).We performed a two-sample MR analysis to evaluate the causality of GDMs on anxiety disorders using four different pairs of GWAS summary data. The generated IVs of 486 metabolites are ranging from 3 to 56 SNPs ; These generated IVs could explain 0.011–0.225% of the variance of their corresponding metabolites . Results found one causal effect feature of metabolites associated with anxiety disorders diagnosed by psychiatrists, namely 1-linoleoylglycerophosphoethanolamine (Pfixed-effect IVW = 4.31 × 10–5)  (Table P = 0.0003), and MR-Egger analysis  indicated consistent results . In addition, we performed a reverse MR analysis, which found no causal relationship between anxiety disorders (exposure) and 1-linoleoylglycerophosphoethanolamine (outcome)  were conformed at P = 0.436). The Cochran's Q statistic was 7.68 (P = 0.742) for the MR-Egger method. The results of Cochran's Q test suggested little heterogeneity. MR-Egger regression was also conducted to examine the horizontal pleiotropy between IVs and results, but no remarkable intercept was discovered . Furthermore, MR-PRESSO results indicated no horizontal pleiotropy in the MR study (P = 0.42). A funnel plot  without horizontal pleiotropy in the 11 overlapped metabolites. MR-Egger regression was also conducted to examine the horizontal pleiotropy of the five association metabolites, no remarkable intercept was discovered. And the results of Cochran's Q test suggested little heterogeneity , whereas “valine, leucine, and isoleucine biosynthesis” pathway was found to be associated with anxiety disorders diagnosed by general practitioners (P = 0.03).Two important metabolic pathways which mainly involved in the anxiety disorders were identified in the metabolic pathways analyses . Primary bile acids have rich functions and are important physiological factors for intestinal nutrient absorption, bile secretion of lipids, toxic metabolites and exotic organisms. At the same time, primary bile acids are signaling molecules and metabolic regulators, which play an important role in activating nuclear receptor and G-protein-coupled receptor (GPCR) signals, regulating liver lipid, glucose and energy homeostasis and maintaining metabolic homeostasis. Studies have proved that primary bile acid metabolites/pathways are involved in several aspects of brain function and behavior . MoreoveValine, leucine, and isoleucine are structurally associated with branched-chain fatty acids and are important members of the family of 9 essential amino acids. Metabolism of valine, leucine and isoleucine have been proved to be associated with cancer progression in numerous studies, and key proteins in metabolic pathways may act as potentially prognostic and diagnostic biomarkers in human cancers . Given tHowever, this study had several limitations. First, given the classification of the original data, we could not further subdivide the pressure type of anxiety disorders in combination with the ICD classification standard, and thus we could only analyze the anxiety disorders as a whole. Second, the power of the IVs depends largely on the sample size of GWASs, therefore, more data are needed to improve the accuracy of the generated GDMs. Third, although Mendelian randomization has been shown to be a powerful method to assess the causality between human blood metabolites and anxiety disorders, the results should be verified by further studies based on experimental data. Fourth, the veracity of the MR analysis relies largely on the explanation of the instrumental variables on exposure. Therefore, it is necessary to expand the sample size to provide a more accurate assessment of the genetic impact on metabolites. Fifth, due to insufficient data, we used metabolites with uncorrected P values for pathway analysis. At last, although this study identified multiple metabolites that contribute to the risk of anxiety disorders, further studies are needed to reveal their roles in the pathogenic mechanism of anxiety disorders.In conclusion, this MR research totally identified 85 metabolites that may have causality on the pathogenesis of anxiety disorders, including 11 known metabolites having causality on more than one type of anxiety disorders. And 1-linoleoylglycerophosphoethanolamine had a robust effect on anxiety disorders among them. Moreover, this study identified two important metabolic pathways that may be relevant to the pathology of anxiety disorders. Collectively, our findings will provide valuable insights on using some metabolites as potential biomarkers to explore the targeted drugs for treating human diseases, but more studies are required to validate the results.Additional file 1: Figure S1. The rationale of Mendelian randomization; Figure S2. Scatter plots of the causal association of 1-linoleoylglycerophosphoethanolamine on the risk of anxiety disorders diagnosed by psychiatrists. Figure S3. Forest plots for 1-linoleoylglycerophosphoethanolamine on anxiety disorders diagnosed by psychiatrists; Figure S4. Leave-one-out plots for 1-linoleoylglycerophosphoethanolamine on anxiety disorders diagnosed by psychiatrists; Figure S5. Funnel plots for 1-linoleoylglycerophosphoethanolamine on anxiety disorders diagnosed by psychiatrists; Figure S6. Scatter plots of the genetic association of six metabolites on the risk of anxiety disorders. Figure S7. Forest plots for six potential metabolites on anxiety disorders; Figure S8. Leave-one-out plots for the six potential metabolites on anxiety disorders; Figure S9. Funnel plots for six potential metabolites on anxiety disorders; Figure S10. The p-value distribution of the Pfixed IVW < 0.05 metabolites on anxiety disorder.Additional file 2: Table S1. The formula used to calculate R2 and F statistic between exposure and outcome; Table S2. Summary statistics of the anxiety disorders; Table S3–S12. Mendelian Randomization estimation for Amino acid(Table S3); Carbohydrate (Table S4); Co-factor or vitamin(Table S5);Energy(Table S6); Lipid(Table S7); Nucleotide (Table S8); Peptide (Table S9); Xenobiotic(Table S10);X(unknow metabolites) (Table S11);known metabolites (Table S12) on the risk of anxiety disorders; Table S13. The characteristics of SNPs and their genetic associations with known metabolites and the anxiety disorders; Table S15. The reverse MR analysis of 1-linoleoylglycerophosphoethanolamine and anxiety disorders using various methods; Table S16. Association of 1linoleoylglycerophosphoethanolamine and additional anxiety disorders GWAS using various methods; Table S14, S17–S21. Summary statistics for the associations of the five metabolites -associated SNPs with these exposures and the anxiety disorders from MRC-IEU Consortium; Table S22. Metabolic Pathway Associated with self-reported anxiety; Table S23. Clinical characteristics of participants involved in the study; Table S24. Characteristics of the KORA population related to antihypertensives and lipid-lowering drugs; Table S25. Characteristics and patterns of anti-hyperglycemic treatment of participants with self-reported type 2 diabetes in the KORA F4 study.