Dietary Patterns and Non-Communicable Disease Biomarkers: A Network Meta-Analysis and Nutritional Geometry Approach.

Quantitative rankings of multiple dietary patterns for their effects on non-communicable disease (NCD) biomarkers is lacking and would inform primary prevention strategies. Accordingly, a network meta-analysis (NMA) was conducted to compare and rank the effects of different dietary patterns on NCD biomarkers, and associations of dietary patterns' underlying macronutrient composition with NCD biomarkers were determined by a nutritional geometry approach. Randomised controlled trials (RCTs) were eligible for inclusion if they enrolled healthy participants, employed food-based dietary pattern interventions without energy restriction, and reported NCD biomarker outcomes. NCD biomarkers were included as an outcome if ≥10 trials were available. A systematic search of five electronic databases identified 4008 records. Sixty-eight articles from 59 RCTs reporting lipids, glycemic, and inflammatory biomarkers were included for quantitative syntheses. Risk-of-bias was predominantly categorized as low or having some concerns, and confidence-of-evidence low. Relative to western habitual diet, the Mediterranean, Dietary Approaches to Stop Hypertension (DASH), dietary guidelines-based, plant-based, and low-fat diets reduced low-density lipoprotein cholesterol (mean difference range: −0.29 to −0.17 mmol/L), total cholesterol (−0.36 to −0.24 mmol/L), and apolipoprotein B (−0.11 to −0.07 g/L) (all p < 0.05); the Paleo, plant-based and dietary guidelines-based diets reduced homeostasis model assessment of insulin resistance (−0.95 to −0.35, all p < 0.05). No dietary pattern ranked consistently highest. The Paleo diet received the highest all-outcomes-combined average Surface Under the Cumulative Ranking Curve value (67%), followed by DASH (62%) and Mediterranean diets (57%), whereas western habitual diet was lowest (36%). Our findings were independent of macronutrient composition, highlighting the significance of dietary pattern-level analysis.

The Carbohydrate Threshold in Pregnancy and Gestational Diabetes: How Low Can We Go?

The original nutrition approach for the treatment of gestational diabetes mellitus (GDM) was to reduce total carbohydrate intake to 33-40% of total energy (EI) to decrease fetal overgrowth. Conversely, accumulating evidence suggests that higher carbohydrate intakes (60-70% EI, higher quality carbohydrates with low glycemic index/low added sugars) can control maternal glycemia. The Institute of Medicine (IOM) recommends ≥175 g/d of carbohydrate intake during pregnancy; however, many women are consuming lower carbohydrate (LC) diets (<175 g/d of carbohydrate or <40% of EI) within pregnancy and the periconceptual period aiming to improve glycemic control and pregnancy outcomes. This report systematically evaluates recent data (2018-2020) to identify the LC threshold in pregnancy in relation to safety considerations. Evidence from 11 reports suggests an optimal carbohydrate range of 47-70% EI supports normal fetal growth; higher than the conventionally recognized LC threshold. However, inadequate total maternal EI, which independently slows fetal growth was a frequent confounder across studies. Effects of a carbohydrate intake <175 g/d on maternal ketonemia and plasma triglyceride/free fatty acid concentrations remain unclear. A recent randomized controlled trial (RCT) suggests a higher risk for micronutrient deficiency with carbohydrate intake ≤165 g/d in GDM. Well-controlled prospective RCTs comparing LC (<165 g/d) and higher carbohydrate energy-balanced diets in pregnant women are clearly overdue.

Medium-Chain Triglyceride Oil and Blood Lipids: A Systematic Review and Meta-Analysis of Randomized Trials.

BACKGROUND: Dietary saturated fat raises total cholesterol and LDL cholesterol levels. It is unclear whether these effects differ by the fatty acid chain lengths of saturated fats; particularly, it is unclear whether medium-chain fatty acids increase lipid levels. OBJECTIVES: We conducted a systematic review to determine the effects of medium-chain triglyceride (MCT) oil, consisting almost exclusively of medium-chain fatty acids (6:0-10:0), on blood lipids. METHODS: We searched Medline and Embase through March 2020 for randomized trials with a minimum 2-week intervention period that compared MCT oil with another fat or oil. Outcomes were total cholesterol, LDL cholesterol, HDL cholesterol, and triglyceride levels. Included studies were restricted to adults above 18 years of age. Studies conducted in populations receiving enteral or parenteral nutrition were excluded. Data were pooled using a random-effects meta-analysis. RESULTS: Seven articles were included in the meta-analysis; LDL cholesterol and HDL cholesterol were reported in 6 studies. MCT oil intake did not affect total cholesterol (0.04 mmol/L; 95% CI, -0.11 to 0.20; I2 = 33.6%), LDL cholesterol (0.02 mmol/L; 95% CI, -0.13 to 0.17; I2 = 28.7%), or HDL cholesterol (-0.01 mmol/L; 95% CI, -0.10 to 0.09; I2 = 74.1%) levels, but did increase triglycerides (0.14 mmol/L; 95% CI, 0.01-0.27; I2 = 42.8%). Subgroup analyses showed that the effects of MCT oil on total cholesterol and LDL cholesterol differed based on the fatty acid profile of the control oil (Pinteraction = 0.003 and 0.008, respectively), with MCT oil increasing total cholesterol and LDL cholesterol when compared to a comparator consisting predominantly of unsaturated fatty acids, and with some evidence for reductions when compared to longer-chain SFAs. CONCLUSIONS: MCT oil does not affect total cholesterol, LDL cholesterol, or HDL cholesterol levels, but does cause a small increase in triglycerides.

Patterns of Seed-to-Seedling Transmission of Xanthomonas citri pv. malvacearum, the Causal Agent of Cotton Bacterial Blight.

Cotton bacterial blight (CBB), caused by Xanthomonas citri pv. malvacearum, was a major disease of cotton in the United States in the early part of the twentieth century. The reemergence of CBB revealed many gaps in our understanding of this important disease. In this study, we employed a wild-type (WT) field isolate of X. citri pv. malvacearum from Georgia (U.S.A.) to generate a nonpathogenic hrcV mutant lacking a functional type-III secretion system (T3SS-). We tagged the WT and T3SS- strains with an auto-bioluminescent Tn7 reporter and compared colonization patterns of CBB-susceptible and CBB-resistant cotton seedlings using macroscopic image analysis and bacterial load enumeration. WT and T3SS- X. citri pv. malvacearum strains colonized cotton cotyledons of CBB-resistant and CBB-susceptible cotton cultivars. However, X. citri pv. malvacearum populations were significantly higher in CBB-susceptible seedlings inoculated with the WT strain. Additionally, WT and T3SS- X. citri pv. malvacearum strains systemically colonized true leaves, although at different rates. Finally, we observed that seed-to-seedling transmission of X. citri pv. malvacearum may involve systemic spread through the vascular tissue of cotton plants. These findings yield novel insights into potential X. citri pv. malvacearum reservoirs for CBB outbreaks.

Effects of a modestly lower carbohydrate diet in gestational diabetes: a randomized controlled trial.

BACKGROUND: Lower carbohydrate diets have the potential to improve glycemia but may increase ketonemia in women with gestational diabetes (GDM). We hypothesized that modestly lower carbohydrate intake would not increase ketonemia. OBJECTIVE: To compare blood ketone concentration, risk of ketonemia, and pregnancy outcomes in women with GDM randomly assigned to a lower carbohydrate diet or routine care. METHODS: Forty-six women aged (mean ± SEM) 33.3 ± 0.6 y and prepregnancy BMI 26.8 ± 0.9 kg/m2 were randomly assigned at 28.5 ± 0.4 wk to a modestly lower carbohydrate diet (MLC, ∼135 g/d carbohydrate) or routine care (RC, ∼200 g/d) for 6 wk. Blood ketones were ascertained by finger prick test strips and 3-d food diaries were collected at baseline and end of the intervention. RESULTS: There were no detectable differences in blood ketones between completers in the MLC group compared with the RC group (0.1 ± 0.0 compared with 0.1 ± 0.0 mmol/L, n = 33, P = 0.31, respectively), even though carbohydrate and total energy intake were significantly lower in the intervention group (carbohydrate 165 ± 7 compared with 190 ± 9 g, P = 0.04; energy 7040 ± 240 compared with 8230 ± 320 kJ, P <0.01, respectively). Only 20% of participants in the MLC group met the target intake compared with 65% in the RC group (P <0.01). There were no differences in birth weight, rate of large-for-gestational-age infants, percent fat mass, or fat-free mass between groups. CONCLUSIONS: An intervention to reduce carbohydrate intake in GDM did not raise ketones to clinical significance, possibly because the target of 135 g/d was difficult to achieve in pregnancy. Feeding studies with food provision may be needed to assess the benefits and risks of low-carbohydrate diets. This trial was registered at www.anzctr.org.au as ACTRN12616000018415.

A systematic review and metaanalysis of energy intake and weight gain in pregnancy.

BACKGROUND: Gestational weight gain within the recommended range produces optimal pregnancy outcomes, yet many women exceed the guidelines. Official recommendations to increase energy intake by ∼ 1000 kJ/day in pregnancy may be excessive. OBJECTIVE: To determine by metaanalysis of relevant studies whether greater increments in energy intake from early to late pregnancy corresponded to greater or excessive gestational weight gain. DATA SOURCES: We systematically searched electronic databases for observational and intervention studies published from 1990 to the present. The databases included Ovid Medline, Cochrane Library, Excerpta Medica DataBASE (EMBASE), Cumulative Index to Nursing and Allied Health Literature (CINAHL), and Science Direct. In addition we hand-searched reference lists of all identified articles. STUDY ELIGIBILITY CRITERIA: Studies were included if they reported gestational weight gain and energy intake in early and late gestation in women of any age with a singleton pregnancy. Search also encompassed journals emerging from both developed and developing countries. STUDY APPRAISAL AND SYNTHESIS METHODS: Studies were individually assessed for quality based on the Quality Criteria Checklist obtained from the Evidence Analysis Manual: Steps in the academy evidence analysis process. Publication bias was plotted by the use of a funnel plot with standard mean difference against standard error. Identified studies were meta-analyzed and stratified by body mass index, study design, dietary methodology, and country status (developed/developing) by the use of a random-effects model. RESULTS: Of 2487 articles screened, 18 studies met inclusion criteria. On average, women gained 12.0 (2.8) kg (standardized mean difference = 1.306, P < .0005) yet reported only a small increment in energy intake that did not reach statistical significance (∼475 kJ/day, standard mean difference = 0.266, P = .016). Irrespective of baseline body mass index, study design, dietary methodology, or country status, changes in energy intake were not significantly correlated to the amount of gestational weight gain (r = 0.321, P = .11). CONCLUSION: Despite rapid physiologic weight gain, women report little or no change in energy intake during pregnancy. Current recommendations to increase energy intake by ∼ 1000 kJ/day may, therefore, encourage excessive weight gain and adverse pregnancy outcomes.