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ObjectivesGut-produced trimethylamine N-oxide (TMAO) is postulated as a possible link between red meat intake and poor cardiometabolic health. We investigated whether gut microbiome could modify associations of dietary precursors with TMAO concentrations and cardiometabolic risk markers among free-living individuals.DesignWe collected up to two pairs of faecal samples (n=925) and two blood samples (n=473), 6 months apart, from 307 healthy men in the Men’s Lifestyle Validation Study. Diet was assessed repeatedly using food-frequency questionnaires and diet records. We profiled faecal metagenome and metatranscriptome using shotgun sequencing and identified microbial taxonomic and functional features.ResultsTMAO concentrations were associated with the overall microbial compositions (permutational analysis of variance (PERMANOVA) test p=0.001). Multivariable taxa-wide association analysis identified 10 bacterial species whose abundance was significantly associated with plasma TMAO concentrations (false discovery rate , P-interaction=0.003; for choline, P-interaction=0.03). Among abundant TMAO-predicting species, Alistipes shahii significantly strengthened the positive association between red meat intake and HbA1c levels (P-interaction=0.01). Secondary analyses revealed that some functional features, including choline trimethylamine-lyase activating enzymes, were associated with TMAO concentrations.ConclusionWe identified microbial taxa that were associated with TMAO concentrations and modified the associations of red meat intake with TMAO concentrations and cardiometabolic risk markers. Our data underscore the interplay between diet and gut microbiome in producing potentially bioactive metabolites that may modulate cardiometabolic health.

IMPORTANCE: The 2015-2020 Dietary Guidelines for Americans recommend multiple healthy eating patterns. However, few studies have examined the associations of adherence to different dietary patterns with long-term risk of cardiovascular disease (CVD). OBJECTIVE: To examine the associations of dietary scores for 4 healthy eating patterns with risk of incident CVD. DESIGN, SETTING, AND PARTICIPANTS: Prospective cohort study of initially healthy women from the Nurses’ Health Study (NHS) (1984-2016) and the NHS II (1991-2017) and men from the Health Professionals Follow-up Study (HPFS) (1986-2012). The dates of analysis were July 25 to December 4, 2019. EXPOSURES: Healthy Eating Index–2015 (HEI-2015), Alternate Mediterranean Diet Score (AMED), Healthful Plant-Based Diet Index (HPDI), and Alternate Healthy Eating Index (AHEI). MAIN OUTCOMES AND MEASURES: Cardiovascular disease events, including fatal and nonfatal coronary heart disease (CHD) and stroke. RESULTS: The final study sample included 74 930 women in the NHS (mean [SD] baseline age, 50.2 [7.2] years), 90 864 women in the NHS II (mean [SD] baseline age, 36.1 [4.7] years), and 43 339 men in the HPFS (mean [SD] baseline age, 53.2 [9.6] years). During a total of 5 257 190 person-years of follow-up, 23 366 incident CVD cases were documented (18 092 CHD and 5687 stroke) (some individuals were diagnosed as having both CHD and stroke). Comparing the highest with the lowest quintiles, the pooled multivariable-adjusted hazard ratios (HRs) of CVD were 0.83 (95% CI, 0.79-0.86) for the HEI-2015, 0.83 (95% CI, 0.79-0.86) for the AMED, 0.86 (95% CI, 0.82-0.89) for the HPDI, and 0.79 (95% CI, 0.75-0.82) for the AHEI (P for trend

Covalent bonded carbon nitride (CN) has stimulated extensive attentions from photosynthesis to optoelectronics. However, the acquisition of correct numbers beyond stoichiometry and composition remains indefinable. Moreover, the electronic coupling by the substrates to the photoexcitation processes in value-added oxidation reactions is essential, but still poorly understood. Herein, we report by far the minimum active structure of CN by constructing fragments consisting of melem (M1) and its incomplete condensed form with cyanide termination (M2). Surprisingly, such configuration endowed a boosted activity of 11 times of traditional bulk CN in photocatalytic oxidation of tetracycline as a showcase application of water cleaning and sanitation. The mechanism studies disclosed that M1 and M2 were primarily responsible for light absorption and charge separation, respectively; meanwhile the electronic coupling by the O2 substrate participated the photoexcited processes thus synergistically enhanced the photocatalytic reactions.

To address how the microbiome might modify the interaction between diet and cardiometabolic health, we analyzed longitudinal microbiome data from 307 male participants in the Health Professionals Follow-Up Study, together with long-term dietary information and measurements of biomarkers of glucose homeostasis, lipid metabolism and inflammation from blood samples. Here, we demonstrate that a healthy Mediterranean-style dietary pattern is associated with specific functional and taxonomic components of the gut microbiome, and that its protective associations with cardiometabolic health vary depending on microbial composition. In particular, the protective association between adherence to the Mediterranean diet and cardiometabolic disease risk was significantly stronger among participants with decreased abundance of Prevotella copri. Our findings advance the concept of precision nutrition and have the potential to inform more effective and precise dietary approaches for the prevention of cardiometabolic disease mediated through alterations in the gut microbiome.

Background: The relation of red meat to risk of coronary heart disease (CHD) is of great interest, but this is likely to depend on the foods to which red meat is compared. Objective: We investigated the associations between total, processed and unprocessed red meat consumption and CHD risk and also estimated the effects of substituting other protein sources for red meat. Methods: We prospectively followed 43,259 men in the Health Professionals Follow up Study (1986-2012) who had no known history of cancer or cardiovascular disease. Diet was assessed by a standardized and validated food frequency questionnaire that was updated every 4 years. Multivariate Cox models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI) of CHD risk across categories of red meat consumption. Substitution analyses were done by comparing coefficients in models including alternative foods as continuous variables. Results: During 932,968 person-years of follow-up, we documented 4,148 incident CHD cases of which 1,680 were fatal CHD cases. After multivariate adjustment for dietary and nondietary risk factors, both total and processed red meat intake were associated with a modestly higher risk of CHD (HR for a one serving/day increment: 1.08; 95% CI, 1.01-1.14 for total and HR=1.13; 95% CI, 1.03-1.22 for processed red meat). Substitutions of 1-serving per day of other foods (including nuts, legumes, soy, whole grains, low- and high-fat dairy) for 1-serving per day of total red meat were associated with a 10%-47% lower CHD risk. Stronger inverse associations were observed between some of these substitutions for red meat and risk of fatal CHD [substituting nuts (-17%, -27% to -6%) or whole grains (-48%, -60% to -32%), and were more pronounced when replacing processed red meat. Conclusions: Our results suggest that red meat consumption, particularly processed red meat, is associated with higher risk of CHD. Substituting high-quality plant foods such as legumes, nuts, soy, and whole grains for red meat may substantially lower CHD risk.

Background and Study Purpose: The conversion of plant lignans to enterolignans for absorption is mediated through the gut microbiota. We explored the interconnections between the intake of dietary lignans, circulating concentrations of plasma enterolignans, the gut microbiome, and cardio-metabolic risk factors (LDL-cholesterol, HDL-cholesterol, & triglycerides). Design and method: The study was a repeated cross-sectional survey of up to 4 stool samples. Dietary lignan intake was assessed by two 7 day weighed records administered to coincide with fecal sample collection. DNA was extracted from 916 samples provided by 301 participants, and RNA was extracted from 369 samples from a subgroup of 96 participants. P Results: A high ratio of plasma enterolactone to dietary lignan was significantly associated with the relative abundance of 35 species (24 enriched and 11 depleted species), including 8 Bacteroidetes and 13 Firmicutes species. Greater dietary lignan was only significantly associated with a lower plasma ratio of triglyceride to HDL when plasma enterolactone was high. The association between dietary lignans and ratio of TG to HDL was mainly mediated by plasma enterolactone level (mediation effect: 74.3%, P=0.002), which was partially captured by the weighted species score (mediation effect: 28.6%, P=0.02). We observed several significant interactions between dietary lignans and presence of species on ratio of TG to HDL, suggesting that the protective effect of dietary lignans on CVD risk factor depends on the presence/abundance of certain microbiota. The relative abundance of microbial pathways involved in I-isoleucine biosynthesis and glutaryl-coa degradation pathways were significantly greater in in participants with a higher level of plasma enterolactone. Conclusion: The health benefits of dietary lignans on lipid levels may be modified by the greater enrichment of biologically relevant microbiota species. FIGURE

Background: Trimethylamine N-oxide (TMAO) is proposed as a possible culprit linking red meat intake and poor cardiovascular health. The relationship between diet, microbial metabolism, circulating TMAO levels, and cardiometabolic health in free-living individuals, is yet to be elucidated. Hypothesis: Specific microbial taxa may modulate associations of choline/L-carnitine and red meat intake with plasma TMAO levels and cardiometabolic traits. Method: We collected 2 pairs of fecal samples (n=925) and, simultaneously, 2 blood samples (n=473), 6 months apart, from 307 healthy men in the Men’s Lifestyle Validation Study in 2012. We performed Shotgun metagenomic sequencing using fecal samples and identified microbial taxonomic features using MetaPhlAn2. We measured hemoglobin A1c (HBA1c), and plasma levels of TMAO, lipids, and other cardiometabolic risk markers. Diet was assessed repeatedly using validated food-frequency questionnaires and dietary records. Results: Multivariable random-effect linear regressions identified 10 bacterial species that were significantly associated with TMAO levels ( FDR Figure A ), and these species significantly modified the associations of dietary choline/L-carnitine and/or red meat intake with TMAO levels ( P interaction Alistipes s hahii and Clostridium c itroniae significantly strengthened the association between red meat intake and TMAO levels, whereas Eubacterium b iforme attenuated this association ( P interaction A. s hahii and C. c itroniae or in the absence of E. b ifome ( Figure B ). Conclusions: We identified microbial taxa that modify the associations of red meat intake with circulating TMAO levels and cardiometabolic traits, in free-living men, suggesting an interplay between diet and microbial metabolism in producing TMAO and affecting cardiometabolic health.

BackgroundGleason score (GS) is a histologic prognostic factor and the basis of treatment decision-making for prostate cancer (PCa). Treatment regimens between lower-grade (GS ≤7) and high-grade (GS >7) PCa differ largely and have great effects on cancer progression.PurposeTo investigate the use of different sequences in biparametric MRI (bpMRI) of the prostate gland for noninvasively distinguishing high-grade PCa.Study typeRetrospective.PopulationIn all, 489 patients (training cohort: N = 326; test cohort: N = 163) with PCa between June 2008 and January 2018.Field strength/sequence3.0T, pelvic phased-array coils, bpMRI including T2 -weighted imaging (T2 WI) and diffusion-weighted imaging (DWI); apparent diffusion coefficient map extracted from DWI.AssessmentThe whole prostate gland was delineated. Radiomic features were extracted and selected using the Kruskal-Wallis test, the minimum redundancy-maximum relevance, and the sequential backward elimination algorithm. Two single-sequence radiomic (T2 WI, DWI) and two combined (T2 WI-DWI, T2 WI-DWI-Clinic) models were respectively constructed and validated via logistic regression.Statistical testsThe Kruskal-Wallis test and chi-squared test were utilized to evaluate the differences among variable groups. P ResultAll radiomic models showed significant (P 2 WI-DWI models acquired an AUC of 0.788, which was almost the same with DWI in the test cohort, and no significant difference was found between them (training cohort: P = 0.199; test cohort: P = 0.924).Data conclusionRadiomics based on bpMRI can noninvasively identify high-grade PCa before the operation, which is helpful for individualized diagnosis of PCa.Level of evidence4 TECHNICAL EFFICACY STAGE: 2 J. Magn. Reson. Imaging 2020;52:1102-1109.

Introduction: The 2015-2020 Dietary Guidelines for Americans (DGAs) recommend three major healthy dietary patterns: the Healthy US-Style Eating Pattern, the Healthy Mediterranean-Style Eating Pattern, and the Healthy Vegetarian Eating Pattern, for all Americans with diverse cultural and personal food traditions. However, few studies have systematically examined the potential differences in associations of adherence to these recommended dietary patterns with long-term risk of cardiovascular disease (CVD). Hypothesis: We hypothesized that all three DGA-recommended dietary patterns were associated with lower risk of CVD, coronary heart disease (CHD), and stroke. Method: We evaluated data on 74 661 women in the Nurses’ Health Study (NHS), 90 864 women in NHS II, and 41 837 men in the Health Professionals Follow-Up Study (HPFS), who had repeated dietary data and had no history of type 2 diabetes, CVD, or cancer at baseline. Using the food and nutrient components, we calculated the Healthy Eating Index (HEI)-2015, Alternate Mediterranean Diet score (AMED), Healthful Plant-based Diet Index (HPDI), to measure adherence to the Healthy US-Style Eating Pattern, Healthy Mediterranean-Style Eating Pattern, and Healthy Vegetarian Eating Pattern, respectively. Multivariable Cox proportional-hazards regression was used to assess the associations of healthy eating index with CVD risk. Results: We documented 9 262 incident CVD cases (6 628 CHD and 2 701 stroke) during 1 976 026 person years of follow-up in the NHS, 1 916 CVD cases (1 267 CHD and 660 stroke) during 2 173 162 person years of follow-up in NHS II, and 10 203 CVD cases (8 750 CHD and 1 775 stroke) during 873 053 person years of follow-up in HPFS. When comparing the highest to the lowest quintiles, the pooled HRs (95% CIs) of CVD were 0.80 (0.77 to 0.84) for HEI-2015, 0.83 (0.79 to 0.87) for AMED, and 0.85 (0.81 to 0.89) for HPDI (all P for trend Conclusions: In three large prospective cohorts with up to 32 years of follow-up, higher adherence to various healthy eating patterns was associated with lower risk of CVD, CHD, and stroke. Our findings support the DGA recommendations for multiple healthy eating patterns.

Introduction: Little is known about whether the effect of a healthy diet on diabetes mellitus (DM) is modified by the gut microbiome in human. Hypothesis: We hypothesize that the gut microbiome modifies the inverse association between the Mediterranean diet (MedDiet) and risk of DM. Methods: This study included 543 DM cases, 805 with impaired glucose tolerance (IGT) and 394 with normal glucose regulation (NGR) in adults 23-83yrs old from the HCHS/SOL. Fecal samples were profiled using 16s rRNA gene sequencing. We applied QIIME 2 to cluster sequences into OTUs and assign taxonomies, and PICRUSt to predict metagenomic gene functions. Adherence to the MedDiet was evaluated by a MedDiet index using the average of two 24-hr dietary recalls. We applied MaAsLin2 to quantify associations between the MedDiet index and microbial features with adjustment for confounding factors listed in the caption of Fig. 1. Results: MedDiet was associated with phylogenetically diverse, rare, and abundant gut microbes (Fig. 1a). For example, a higher MedDiet index was associated with a higher relative abundance of Faecalibacterium Prausnitzii [FDR-adjusted p (q) =0.002], but a lower relative abundance of Collinsella aerofaciens ( q =0.009). We found that several microbial functions related to plant-derived polysaccharide degradation such as fructuronate reductase ( q =0.02), and short-chain fatty acid fermentation such as butyryl-CoA dehydrogenase ( q =0.002) were enriched in participants with higher MedDiet index. We found that the inverse association between MedDiet and risk of DM was more pronounced in participants with greater abundance of Prevotella copri , but weaker in participants whose gut microbial communities were dominated by Bacteroides ( P interaction =0.02 for IGT/DM vs NGR, Fig. 1b). Conclusions: Adherence to the MedDiet is associated with diverse gut microorganisms and microbial functions. The inverse association between MedDiet and risk of DM might be modified by gut microbiome composition. 1

Objectives: To investigate the association between a plant-based diet index and microbial composition and functionality, as well as the inter-relationships between plant-based diets, gut microbiome, and cardiometabolic risk markers. Design and method: Metagenomic profiling was performed on 916 fecal samples collected among 301 men who participated in the Men’s Lifestyle Validation Study. Using data from a food frequency questionnaire, a Plant-based Diet Index (PDI) was derived to assess the adherence to a plant-based diets. The associations between PDI adherence and the relative abundance of microbial species and pathways were evaluated using Multivariate Association with Linear Models (MaAsLin2). P values below 0.25 after false discovery rate correction following the Benjamini-Hochberg method were considered statistically significant. Results: After multivariate adjustment, the value of the PDI score was significantly and positively associated with the ratio of Firmicutes to Bacteroidetes (Spearman r=0.10, P=0.005). Specifically, the PDI was significantly associated with the relative abundance of 77 taxa (including 39 species) out of 506 filtered taxa and 15 pathways (out of 80 filtered features). In particular, a higher adherence to the PDI was significantly, positively, associated with of the relative abundance of Firmicutes and of pathways involving degradation of complex plant carbohydrates. It was also inversely associated with the relative abundance of Bacteroidetes and Proteobacteria, as well as pathways involved in the urea cycle and amino acid biosynthesis. We also found that 14 species significantly interacted with PDI in modulating plasma ratio of TG to HDL-C. The association of PDI with lower TG to HDL ratio was significantly strengthened in the presence of the species positively correlated with the PDI score, such as Ruminococcus lactaris , Haemophilus parainfluenzae, and Methanobrevibacter smithii or in the absence of the species inversely correlated with the PDI score, such as Paraprevotella spp. Conclusions: A greater adherence to a plant-based diet was associated with a microbial profile featured by higher abundance of species in Firmicutes and depletion of species in Bacteroidetes and Proteobacteria, and such a profile may further strengthen the favorable associations between plant-based diets and human cardiometabolic risk.

International audience; Background & aims: We evaluated the efficacy and safety of diet-modulated autologous fecal microbiota transplantation (aFMT) for treatment of weight regain after the weight-loss phase.Methods: In the DIRECT PLUS (Dietary Intervention Randomized Controlled Trial Polyphenols-Unprocessed) weight-loss trial (May 2017 through July 2018), abdominally obese or dyslipidemic participants in Israel were randomly assigned to healthy dietary guidelines, Mediterranean diet, and green-Mediterranean diet weight-loss groups. All groups received free gym membership and physical activity guidelines. Both isocaloric Mediterranean groups consumed 28 g/d walnuts (+440 mg/d polyphenols provided). The green-Mediterranean dieters also consumed green tea (3-4 cups/d) and a Wolffia globosa (Mankai strain, 100 g/d) green shake (+800 mg/d polyphenols provided). After 6 months (weight-loss phase), 90 eligible participants (mean age, 52 years; mean weight loss, 8.3 kg) provided a fecal sample that was processed into aFMT by frozen, opaque, and odorless capsules. The participants were then randomly assigned to groups that received 100 capsules containing their own fecal microbiota or placebo until month 14. The primary outcome was regain of the lost weight over the expected weight-regain phase (months 6-14). Secondary outcomes were gastrointestinal symptoms, waist circumference, glycemic status, and changes in the gut microbiome, as measured by metagenomic sequencing and 16s ribosomal RNA. We validated the results in a parallel in vivo study of mice specifically fed with Mankai compared with control chow diet.Results: Of the 90 participants in the aFMT trial, 96% ingested at least 80 of 100 oral aFMT or placebo frozen capsules during the transplantation period. No aFMT-related adverse events or symptoms were observed. For the primary outcome, although no significant differences in weight regain were observed among the participants in the different lifestyle interventions during months 6-14 (aFMT, 30.4% vs placebo, 40.6%; P = .28), aFMT significantly attenuated weight regain in the green-Mediterranean group (aFMT, 17.1%, vs placebo, 50%; P = .02), but not in the dietary guidelines (P = .57) or Mediterranean diet (P = .64) groups (P for the interaction = .03). Accordingly, aFMT attenuated waist circumference gain (aFMT, 1.89 cm vs placebo, 5.05 cm; P = .01) and insulin rebound (aFMT, -1.46 ± 3.6 μIU/mL vs placebo, 1.64 ± 4.7 μIU/mL; P = .04) in the green-Mediterranean group but not in the dietary guidelines or Mediterranean diet (P for the interaction = .04 and .03, respectively). The green-Mediterranean diet was the only intervention to induce a significant change in microbiome composition during the weight-loss phase, and to prompt preservation of weight-loss-associated specific bacteria and microbial metabolic pathways (mainly microbial sugar transport) after the aFMT. In mice, Mankai-modulated aFMT in the weight-loss phase compared with control diet aFMT, significantly prevented weight regain and resulted in better glucose tolerance during a high-fat diet-induced regain phase (all, P < .05).Conclusions: Autologous FMT, collected during the weight-loss phase and administrated in the regain phase, might preserve weight loss and glycemic control, and is associated with specific microbiome signatures. A high-polyphenols, green plant-based or Mankai diet better optimizes the microbiome for an aFMT procedure. ClinicalTrials.gov number, NCT03020186.

SCOPE: The plasma metabolomics profiles of protein intake has been rarely investigated. We aimed to identify the distinct plasma metabolomics profiles associated with overall intakes of protein as well as with intakes from animal and plant protein sources. METHODS AND RESULTS: Cross-sectional analysis using data from 1,833 participants at high risk of cardiovascular disease. Plasma metabolomics analysis was performed using LC-MS. Associations between 385 identified metabolites and the intake of total, animal protein (AP) and plant protein (PP), and plant-to-animal ratio (PR) were assessed using elastic net continuous regression analyses. A double 10-cross-validation (CV) procedure was used and Pearson correlations coefficients between multi-metabolite weighted models and reported protein intake in each pair of training-validation datasets were calculated. A wide set of metabolites was consistently associated with each protein source evaluated. These metabolites mainly consisted of amino acids and their derivatives, acylcarnitines, different organic acids and lipid species. Few metabolites overlapped among protein sources (i.e. C14:0 SM, C20:4 carnitine, GABA and allantoin) but none of them towards the same direction. Regarding AP and PP approaches, C20:4 carnitine and dimethylglycine were positively associated with PP but negatively associated with AP. However, allantoin, C14:0 SM, C38:7 PE plasmalogen, GABA, metronidazole and trigonelline (N-methylnicotinate) behaved contrary. Ten-CV Pearson correlations coefficients between self-reported protein intake and plasma metabolomics profiles ranged from 0.21 for PR to 0.32 for total protein. CONCLUSIONS: Different sets of metabolites were associated with total, animal and plant protein intake. Further studies are needed to assess the contribution of these metabolites in protein biomarkers’ discovery and prediction of cardiometabolic alterations.

Background: Glycolysis/gluconeogenesis and tricarboxylic acid (TCA) cycle metabolites have been associated with type 2 diabetes (T2D). However, the associations of these metabolites with T2D incidence and the potential effect of dietary interventions remain unclear. Objectives: We aimed to evaluate the association of baseline and 1-y changes in glycolysis/gluconeogenesis and TCA cycle metabolites with insulin resistance and T2D incidence, and the potential modifying effect of Mediterranean diet (MedDiet) interventions. Methods: We included 251 incident T2D cases and 638 noncases in a nested case-cohort study within the PREDIMED Study during median follow-up of 3.8 y. Participants were allocated to MedDiet + extra-virgin olive oil, MedDiet + nuts, or control diet. Plasma metabolites were measured using a targeted approach by LC-tandem MS. We tested the associations of baseline and 1-y changes in glycolysis/gluconeogenesis and TCA cycle metabolites with subsequent T2D risk using weighted Cox regression models and adjusting for potential confounders. We designed a weighted score combining all these metabolites and applying the leave-one-out cross-validation approach. Results: Baseline circulating concentrations of hexose monophosphate, pyruvate, lactate, alanine, glycerol-3 phosphate, and isocitrate were significantly associated with higher T2D risk (17-44% higher risk for each 1-SD increment). The weighted score including all metabolites was associated with a 30% (95% CI: 1.12, 1.51) higher relative risk of T2D for each 1-SD increment. Baseline lactate and alanine were associated with baseline and 1-y changes of homeostasis model assessment of insulin resistance. One-year increases in most metabolites and in the weighted score were associated with higher relative risk of T2D after 1 y of follow-up. Lower risks were observed in the MedDiet groups than in the control group although no significant interactions were found after adjusting for multiple comparisons. Conclusions: We identified a panel of glycolysis/gluconeogenesis-related metabolites that was significantly associated with T2D risk in a Mediterranean population at high cardiovascular disease risk. A MedDiet could counteract the detrimental effects of these metabolites.This trial was registered at controlled-trials.com as ISRCTN35739639. Supported by NIH research grant NIDDK-R01DK 102896 (to FBH). The PREDIMED trial was supported by the official funding agency for biomedical research of the Spanish government, Instituto de Salud Carlos III, through grants provided to research networks specifically developed for the trial (RTIC G03/140, to RE during 2003–2005; RTIC RD 06/0045, to MAM-G during 2006–2013; and through Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición); by Centro Nacional de Investigaciones Cardiovasculares grant CNIC 06/2007; Fondo de Investigación Sanitaria—Fondo Europeo de Desarrollo Regional grants PI04–2239, PI 05/2584, CP06/00100, PI07/0240, PI07/1138, PI07/0954, PI 07/0473, PI10/01407, PI10/02658, PI11/01647, P11/02505, PI13/00462, and JR17/00022; Ministerio de Ciencia e Innovación grants AGL-2009–13906-C02, AGL2010–22319-C03, and SAF2016–80532-R; Fundación Mapfre 2010; Consejería de Salud de la Junta de Andalucía grant PI0105/2007; Public Health Division of the Department of Health of the Autonomous Government of Catalonia, Generalitat Valenciana grants ACOMP06109, GVA-COMP2010–181, GVACOMP2011–151, CS2010-AP-111, PROMETEO 17/2017, and CS2011-AP-042; Fundació La Marató-TV3 grants 294/C/2015 and 538/U/2016; and by Regional Government of Navarra grant P27/2011. MG-F was supported by American Diabetes Association grant #1-18-PMF-029. JLS was supported by Fondo Nacional de Desarrollo Científico y Tecnológico (FONDECYT) grant 1150416.

OBJECTIVE Specific lipid molecular changes leading to type 2 diabetes (T2D) are largely unknown. We assessed lipidome factors associated with future occurrence of T2D in a population at high cardiovascular risk. RESEARCH DESIGN AND METHODS We conducted a case-cohort study nested within the PREDIMED trial, with 250 incident T2D cases diagnosed during 3.8 years of median follow-up, and a random sample of 692 participants (639 noncases and 53 overlapping cases) without T2D at baseline. We repeatedly measured 207 plasma known lipid metabolites at baseline and after 1 year of follow-up. We built combined factors of lipid species using principal component analysis and assessed the association between these lipid factors (or their 1-year changes) and T2D incidence. RESULTS Baseline lysophosphatidylcholines and lysophosphatidylethanolamines (lysophospholipids [LPs]), phosphatidylcholine-plasmalogens (PC-PLs), sphingomyelins (SMs), and cholesterol esters (CEs) were inversely associated with risk of T2D (multivariable-adjusted P for linear trend ≤0.001 for all). Baseline triacylglycerols (TAGs), diacylglycerols (DAGs), and phosphatidylethanolamines (PEs) were positively associated with T2D risk (multivariable-adjusted P for linear trend CONCLUSIONS Two plasma lipid profiles made up of different lipid classes were found to be associated with T2D in participants at high cardiovascular risk. A profile including LPs, PC-PLs, SMs, and CEs was associated with lower T2D risk. Another profile composed of TAGs, DAGs, and PEs was associated with higher T2D risk.

A study of the two body decays $B^\pm\rightarrow X_{c\bar c}K^\pm$, where X$_{c\bar c}$ refers to one charmonium state, is reported by BaBar collaboration using a data sample of 424 fb$^{-1}$. The absolute determination of branching fractions for these decays are significantly improved compared to previous BaBaR measurements. Evidence is found for the decay $B^+\rightarrow X(3872)K^+$ at the $3\sigma$ level. The absolute branching fraction ${\cal B}(B^+\rightarrow X(3872)K^+) = (2.1\pm0.6({\rm stat})\pm0.3({\rm syst}))\times 10^{-4}$ is measured for the first time. It follows that ${\cal B}(X(3872)\rightarrow J/\psi\pi^+\pi^-)=(4.1\pm1.3)\%$, supporting the hypothesis of a molecular component for this resonance., Comment: 8 pages 6 figures

Summary Precision nutrition aims to prevent and manage chronic diseases by tailoring dietary interventions or recommendations to one or a combination of an individual's genetic background, metabolic profile, and environmental exposures. Recent advances in genomics, metabolomics, and gut microbiome technologies have offered opportunities as well as challenges in the use of precision nutrition to prevent and manage type 2 diabetes. Nutrigenomics studies have identified genetic variants that influence intake and metabolism of specific nutrients and predict individuals' variability in response to dietary interventions. Metabolomics has revealed metabolomic fingerprints of food and nutrient consumption and uncovered new metabolic pathways that are potentially modified by diet. Dietary interventions have been successful in altering abundance, composition, and activity of gut microbiota that are relevant for food metabolism and glycaemic control. In addition, mobile apps and wearable devices facilitate real-time assessment of dietary intake and provide feedback which can improve glycaemic control and diabetes management. By integrating these technologies with big data analytics, precision nutrition has the potential to provide personalised nutrition guidance for more effective prevention and management of type 2 diabetes. Despite these technological advances, much research is needed before precision nutrition can be widely used in clinical and public health settings. Currently, the field of precision nutrition faces challenges including a lack of robust and reproducible results, the high cost of omics technologies, and methodological issues in study design as well as high-dimensional data analyses and interpretation. Evidence is needed to support the efficacy, cost-effectiveness, and additional benefits of precision nutrition beyond traditional nutrition intervention approaches. Therefore, we should manage unrealistically high expectations and balance the emerging field of precision nutrition with public health nutrition strategies to improve diet quality and prevent type 2 diabetes and its complications.

Jun Hu,1 Dong Dong,2 Dandan Lu3 1Research Centre of Biomedical Technology Co., Ltd., Jiangsu Vocational College of Medicine, Yancheng, Jiangsu, 2Department of Pharmacy, Women and Infants Hospital of Zhengzhou, Zhengzhou, Henan, 3Department of Dermatology, The Third Hospital of Jinan, Jinan, Shandong, China Background: Although the associations between common single nucleotide polymorphisms (SNPs) of EFEMP1 gene and glioma risk have been investigated in Chinese population-based case–control studies, investigation results for several SNPs are inconsistent. In addition, the single-center study has a poor statistical power due to finite sample size. Therefore, a meta-analysis was conducted to comprehensively determine the associations.Methods: All eligible case–control studies were obtained by searching PubMed, EMBASE, Web of Science, and Chinese National Knowledge Infrastructure. Pooled odds ratio (OR) with 95% confidence interval (CI) was used to assess the strength of the associations in fixed- or random-effects model.Results: EFEMP1 rs1346787 polymorphism was significantly associated with glioma risk in Chinese population under all genetic models (GG vs AA, OR =2.22, 95% CI =1.46–3.36; AG vs AA, OR =1.54, 95% CI =1.27–1.87; (GG+AG) vs AA, OR =1.60, 95% CI =1.34–1.93; GG vs (AG+AA), OR =1.86, 95% CI =1.24–2.78; G vs A, OR =1.54, 95% CI =1.32–1.79). However, the significant association of EFEMP1 rs1346786 with glioma risk in Chinese population was observed only under heterozygous model of AG vs AA (OR =1.34, 95% CI=1.10–1.62), dominant model of (GG+AG) vs AA (OR =1.36, 95% CI =1.13–1.63), and allelic model of G vs A (OR =1.28, 95% CI =1.10–1.50).Conclusion: Our study demonstrated that EFEMP1 polymorphisms, especially rs1346787 and rs1346786, might predict glioma risk in Chinese population. However, high-quality case–control studies with larger sample sizes are warranted to confirm the above-mentioned findings. Keywords: polymorphism, glioma, risk, meta-analysis