• Humans
• Female
• Obesity/complications
• Obesity/metabolism
• Obesity/epidemiology
• Middle Aged
• Body Mass Index
• Phenotype
• Aged
• Risk Factors
• Neoplasms/epidemiology
• Neoplasms/etiology
• Neoplasms/metabolism
• Women's Health
• Insulin Resistance
• Follow-Up Studies
• Biomarkers
• Postmenopause

• 5R00CA218694-03 Division of Cancer Prevention, National Cancer Institute (DCP, NCI)
• R00 CA218694 NCI NIH HHS
• F99 CA264400 NCI NIH HHS
• K00 CA264400 NCI NIH HHS
• P30CA040214 Huntsman Cancer Institute, University of Utah (HCI)
• K00 CA253745 NCI NIH HHS
• R01 HL170575 NHLBI NIH HHS
• F99CA264400 Division of Cancer Prevention, National Cancer Institute (DCP, NCI)
• U01 CA272529 NCI NIH HHS
• R01 DK130296 NIDDK NIH HHS
• K07 CA222060 NCI NIH HHS
• 001 World Health Organization
• K00CA253745 Division of Cancer Prevention, National Cancer Institute (DCP, NCI)

• Cardiac plexus
• Fibrosis
• Heart
• Inflammation
• Neurons
• Oxidative stress

• Animals
• Fluorouracil/toxicity
• Rats, Wistar
• Cardiotoxicity
• Oxidative Stress/drug effects
• Male
• Inflammation Mediators/metabolism
• Antimetabolites, Antineoplastic/toxicity
• Heart/innervation
• Heart Diseases/chemically induced
• Heart Diseases/pathology
• Heart Diseases/metabolism
• Disease Models, Animal
• Antioxidants/metabolism
• Rats

• cardiovascular disease
• gut permeability
• inflammation
• metabolically healthy obesity
• normal-weight obesity

• Humans
• Male
• Female
• Biomarkers/blood
• Permeability
• Adult
• Middle Aged
• Inflammation/metabolism
• Acute-Phase Proteins/metabolism
• Gastrointestinal Microbiome
• Obesity, Metabolically Benign/blood
• Obesity, Metabolically Benign/physiopathology
• Intestinal Mucosa/metabolism
• Carrier Proteins/metabolism
• Carrier Proteins/blood
• Lipopolysaccharide Receptors/blood
• Lipopolysaccharide Receptors/metabolism
• Membrane Glycoproteins/blood
• C-Reactive Protein/metabolism
• Obesity/metabolism
• Obesity/physiopathology
• Obesity/microbiology
• Obesity/blood
• Case-Control Studies
• Adiposity
• Feces/microbiology
• Feces/chemistry
• Intestinal Barrier Function

• 909438 American Heart Association (AHA)
• N/A American Society for Nutrition (ASN)
• Barbara K. Pass Nutritional Sciences Research Grant
• HHS | National Institutes of Health (NIH)

• Korean women
• across generations
• body composition
• normal weight obesity
• physical fitness

• metabolic dysfunction-associated fatty liver disease
• obesity
• phenotypes
• treatment
• type 2 diabetes mellitus
• weight loss

• Logistics University of PAP (WHB201517)

• Mediterranean diet
• gene expression
• nutrigenomics
• sex difference

• Humans
• Male
• Female
• Diet, Mediterranean
• Pilot Projects
• Nutrigenomics
• Sex Characteristics
• Oxidative Stress

• T5-AN-08, n259, 03/02/2023 Ministero della Salute

• body fat percentage
• body mass index
• cardiometabolic disease
• cardiovascular disease
• normal-weight obesity
• obesity

• Mediterranean Diet
• anti-inflammatory activity
• antioxidant
• gene expression
• nutrigenomics
• polyphenols

• Humans
• Antioxidants
• Superoxide Dismutase-1
• PPAR gamma/genetics
• Inflammation/genetics
• Inflammation/complications
• Oxidative Stress
• Diet, Mediterranean
• Superoxide Dismutase/genetics
• Gene Expression

• Adiposity
• Liver fat
• Regional fat distribution
• Sulfur amino acids

• CRP
• NWO
• inflammation
• inflammatory markers
• interleukin
• normal weight obesity

• diseases
• iron homeostasis
• mitochondrial dysfunction

• Humans
• Mitochondria/metabolism
• Iron/metabolism
• Iron Overload/metabolism
• Iron Deficiencies
• Homeostasis

• 2021JJ20044 the Natural Science Foundation of Hunan Province
• kq2009020 the Changsha Natural Science Funds for Distinguished Young Scholar
• 2022RC1159 The Science and Technology Innovation Program of Hunan Province
• CARS-35 China Agriculture Research System of MOF and MARA

• BMI
• DXA
• body composition
• body fat
• normal body weight
• obesity
• sarcopenia
• sarcopenic obesity

• Female
• Male
• Humans
• Sarcopenia/epidemiology
• Body Mass Index
• Obesity/complications
• Obesity/epidemiology
• Body Composition
• Syndrome
• Risk Factors

• Ageing
• BMI
• Exercise
• Exercise therapy
• Interleukin-15
• Physical activity

• Cardiovascular disease
• Endothelial function
• Inflammation
• Metabolic syndrome
• Normal-weight obesity
• Postprandial triglycerides

The purpose of this umbrella review is to bring together the most recent reviews concerning the role of immunonutrients for male and female infertility.

Regarding immunonutrients and fertility, the authors have analyzed reviews, systematic reviews, and meta-analyses published between 2011 and June 2021. All reviews on animal or in vitro studies were excluded. Relevant keywords to term micronutrients were analyzed alone or in association with other terms such as “gamete competence,” “male OR female fertility,” “male OR female infertility,” “fertile, “folliculogenesis,” “spermatogenesis,” “immunomodulation,” “immune system,” “oxidative stress.”

The primary research has included 108 results, and after screening by title, abstract. and not topic-related, 41 studies have been included by full texts. The results show the molecular mechanisms and the immunonutrients related impact on gamete formation, development. and competence. In particular, this review focused on arginine, glutamine, vitamin C, vitamin D, vitamin E, omega-3, selenium, and zinc.

Inflammation and oxidative stress significantly impact human reproduction. For this reason, immunonutrients may play an important role in the treatment of infertile patients. However, due to the lack of consistent clinical trials, their application is limited. Therefore, the development of clinical trials is necessary to define the correct supplementation, in case of deficiency.

• Antioxidant system
• Gamete competence
• Immunonutrients
• Infertility
• Inflammation
• Oxidative stress
• Supplementation

Vaccines are among the most effective health measures and have contributed to eradicating some diseases. Despite being very effective, response rates are low in some individuals. Different factors have been proposed to explain why some people are not as responsive as others, but what appears to be of critical importance is the presence of a healthy functioning immune system. In this respect, a key factor in modulating the immune system, both in its adaptive and innate components, is the microbiota. While microbiota can be modulated in different ways (i.e., antibiotics, probiotics, prebiotics), an effective and somewhat obvious mechanism is via nutrition. The science of nutrients and their therapeutic application is called immunonutrition, and it is increasingly being considered in several conditions. Our review will focus on the importance of nutrition and microbiota modulation in promoting a healthy immune system while also discussing the overall impact on vaccination response.

• coding-non-coding gene co-expression
• competing endogenous RNA
• hyposalivation
• obesity
• protein
• protein interaction

A significant proportion of adults have normal weight obesity (NWO), defined as a normal body mass index (BMI) but disproportionately high body fat percentage. Individuals with NWO may have increased risk of cardiometabolic disorders and lower exercise tolerance, but it is unclear if this obesity phenotype is linked with dysregulated production of adipokines or myokines such as adiponectin and apelin, respectively.

This cross-sectional, secondary analysis included 177 working adults (mean age 49.6 ± 9.9 yrs, 64% female). Plasma high-molecular weight adiponectin and apelin levels were measured by ELISA. Body composition and fat distribution were assessed using dual energy X-ray absorptiometry. Exercise tolerance (VO₂ maximum) was determined by treadmill testing. NWO was defined as a BMI <25 kg/m² and body fat >30% for women or >23% for men. Participants were categorized as lean, NWO, or overweight-obese.

A total of 14.7% of subjects were categorized as lean, 23.7% as having NWO, and 61.6% as having overweight-obesity. Plasma adiponectin levels were elevated in the overweight-obesity group (P < 0.05) compared to the lean and NWO groups, which did not differ from each other (P > 0.05). Adiponectin concentrations were inversely associated with BMI, fat mass, fat mass percent, visceral fat, and trunk to leg fat ratio and positively associated with leg fat mass (all P < 0.001). Plasma apelin levels were similar between the three body composition groups (P < 0.05) and were not significantly associated with any body composition indices. Apelin concentrations were inversely related to VO₂ maximum (β = −0.03 ± 0.01, p = 0.002).

Plasma adiponectin and apelin levels did not distinguish between lean and NWO groups. Positive relationships with leg fat mass and adiponectin suggest the importance of assessing body composition and fat distribution when studying adipokines and cardiometabolic disorders. Further investigations are needed to understand relationships between exercise, body composition, and apelin secretion.

• Adipose
• Cytokines
• Fat distribution
• Fitness
• Metabolic
• Obesity phenotype

• Exercise
• Fat distribution
• Nutrition
• Overweight

• Absorptiometry, Photon
• Adipose Tissue/physiopathology
• Adult
• Biomarkers/analysis
• Body Composition
• Body Mass Index
• Body Weight/physiology
• Cardiometabolic Risk Factors
• Cross-Sectional Studies
• Diet Surveys
• Diet, Healthy/statistics & numerical data
• Diet, Mediterranean/statistics & numerical data
• Dietary Approaches To Stop Hypertension/statistics & numerical data
• Eating/physiology
• Exercise Test
• Female
• Humans
• Ideal Body Weight
• Linear Models
• Male
• Middle Aged
• Obesity/physiopathology
• Overweight/physiopathology
• Oxygen Consumption/physiology
• Physical Fitness/physiology

• K01 DK102851 NIDDK NIH HHS
• R38 AI140299 NIAID NIH HHS
• K24 DK096574 NIDDK NIH HHS
• U54 AG062334 NIA NIH HHS
• UL1 TR002378 NCATS NIH HHS
• P30 ES019776 NIEHS NIH HHS

Cardiometabolic disorders are frequently observed among those who have obesity as measured by body mass index (BMI). However, there is limited data available on the cardiometabolic profile of those who are non-obese by BMI but with a high body fat percentage (BFP), a phenotype frequently observed in the Indian population. We examined the prevalence of individuals with normal weight obesity (NWO) and the cardiometabolic profile of NWO individuals at high risk for type 2 diabetes(T2D) in a south Asian population.

In the Kerala Diabetes Prevention Program, individuals aged between 30 to 60 years were screened using the Indian Diabetes Risk Score(IDRS) in 60 rural communities in the Indian state of Kerala. We used data from the baseline survey of this trial for this analysis which included 1147 eligible high diabetes risk individuals(IDRS >60). NWO was defined as BMI within the normal range and a high BFP (as per Asia-pacific ethnicity based cut-off); Non-obese (NO) as normal BMI and BFP and overtly obese (OB) as BMI ≥25 kg/m² irrespective of the BFP. Data on demographic, clinical and biochemical characteristics were collected using standardized questionnaires and protocols. Body fat percentage was assessed using TANITA body composition analyser (model SC330), based on bioelectrical impedance.

The mean age of participants was 47.3 ± 7.5 years and 46% were women. The proportion with NWO was 32% (n = 364; 95% CI: 29.1 to 34.5%), NO was 17% (n = 200) and OB was 51% (n = 583). Among those with NWO, 19.7% had T2D, compared to 18.7% of those who were OB (p value = 0.45) and 8% with NO (p value = 0.003). Among those with NWO, mean systolic and diastolic blood pressure were 129 ± 20; 78 ± 12 mmHg, compared to 127 ± 17; 78±11 mmHg among those with OB (p value = 0.12;0.94) and 120 ± 16; 71±10 mmHg among with NO (p value<0.001; 0.001), respectively. A similar pattern of association was observed for LDL cholesterol and triglycerides. After adjusting for other risk factors, the odds of having diabetes (OR:2.72[95% CI:1.46–5.08]) and dyslipidemia (2.37[1.55–3.64]) was significantly more in individuals with NWO as compared to non-obese individuals.

Almost one-third of this South Asian population, at high risk for T2D, had normal weight obesity. The significantly higher cardiometabolic risk associated with increased adiposity even in lower BMI individuals has important implications for recognition in clinical practice.

• body composition
• body fat
• cardiometabolic risk
• normal-weight obesity
• young adults

• Adiposity
• Adolescent
• Adult
• Body Fat Distribution
• Body Mass Index
• Body Weight
• Cardiovascular Diseases/etiology
• Colombia/epidemiology
• Cross-Sectional Studies
• Female
• Hand Strength
• Humans
• Male
• Obesity/complications
• Obesity/epidemiology
• Obesity/metabolism
• Obesity/physiopathology
• Prevalence
• Risk Factors
• Waist Circumference
• Young Adult

• Body fat distribution
• Cardiometabolic risk
• Metabolic disease
• Metabolically abnormal lean
• Metabolically obese normal weight

• Body Mass Index
• Body Weight/physiology
• Diabetes Mellitus, Type 2/etiology
• Diabetes Mellitus, Type 2/physiopathology
• Humans
• Life Style
• Metabolic Syndrome/physiopathology
• Obesity
• Phenotype
• Risk Factors
• Waist Circumference

• Obesity
• adiposopathy
• body composition
• gut microbiota
• inflammation
• metabolic disease.

• bioimpedance
• body fat
• normal weight obesity
• risk factor of cardiovascular disease
• skinfolds

The aim of the present study was to establish whether markers of oxidative stress and the enzymatic defense system of the blood are related to moderate physical activity in younger old and the oldest old men. They were divided into four groups according to the age and level of physical activity (groups YN and YA—inactive and active younger old men aged 65-74 years, groups ON and OA—inactive and active oldest old men aged 90-99 years). Venous blood was collected from the subjects in the morning before breakfast. MDA concentration and antioxidant enzyme activities (SOD, CAT, GPx, and GR) in erythrocyte hemolysates were assayed. The concentration of isoprostanes (8-iso-PGF2α) and carbonyl groups in protein (CP) was measured in plasma and serum. All assayed antioxidant enzyme activities and the SOD/GPx ratios were significantly higher in the active younger old males than in all the inactive ones. In the group of oldest old active participants, only the GPx activity was significantly higher compared to the inactive oldest old males. The activity of CAT and GPx in the younger old inactive men was significantly lower than that in the oldest old inactive subjects. However, SOD, CAT, and GR activities and SOD/GPx ratio were significantly higher in the younger old active men compared to the oldest old active participants. The concentrations of isoprostanes, protein carbonyls, and MDA were significantly lower in both active and inactive younger old males than in the respective groups of the oldest old men and in both groups of active men, independently of age, compared to the respective inactive subjects. The present study confirmed that oxidative stress is related to age. Physical activity caused a decrease of oxidative stress markers independently of age and resulted in an increase of GPx activity in both younger old and the oldest old active groups.

Background: This study aimed at assessing the effect of a low-fat diet (LFD) in obese mice lacking toll–like receptors (Tlr) and understanding the expression and regulation of microRNAs during weight reduction. Methods: C57BL/6, Tlr5^−/−, Tlr2^−/− and Tlr4^−/− mice were used in this study. A group of mice were fed with a high-fat diet (HFD) (58% kcal) for 12 weeks to induce obesity (diet-induced obesity, DIO). Another group that had been fed with HFD for eight weeks (obese mice) were switched to a low-fat diet (LFD) (10.5% kcal) for the next four weeks to reduce their body weight. The control mice were fed with a standard AIN-76A diet for the entire 12 weeks. The body weight of the mice was measured weekly. At the end of the experiment, epididymal fat weight and adipocyte size were measured. The differentially expressed miRNAs in the fat tissue was determined by next-generation sequencing with real-time quantitative reverse transcription polymerase chain reaction (RT–qPCR). Target prediction and functional annotation of miRNAs were performed using miRSystem database. Results: Switching to LFD significantly reduced the body weight and epididymal fat mass in the HFD-fed C57BL/6 and Tlr5^−/− mice but not in Tlr2^−/− and Tlr4^−/− mice. Weight reduction significantly decreased the size of adipocytes in C57BL/6 but not in the Tlr knockout mice. In Tlr2^−/− and Tlr4^−/− mice, feeding with HFD and the subsequent weight reduction resulted in an aberrant miRNA expression in the epididymal fat tissue unlike in C57BL/6 and Tlr5^−/−. However, target prediction and functional annotation by miRSystem database revealed that all the top 10 Kyoto Encyclopedia of Genes and Genomes (KEGG) database pathways of the dysregulated miRNAs during weight reduction in the C57BL/6 mice were also found in the regulated pathways of Tlr5^−/−, Tlr2^−/−, and Tlr4^−/− strains. However, among these pathways, gene sets involved in arginine and proline metabolism and glutathione metabolism were mainly involved in the Tlr knockout mice but not in the C57BL/6 mice. Conclusions: In this study, we demonstrated that feeding of LFD leads to significant body weight reduction in C57BL/6 and Tlr5^−/− mice, but not in Tlr2^−/− and Tlr4^−/− mice. Significant reduction in the size of adipocytes of epididymal fat was only found in C57BL/6, but not in Tlr5^−/−, Tlr2^−/−, and Tlr4^−/− mice. The dysregulated miRNAs in Tlr2^−/− and Tlr4^−/− mice were different from those in C57BL/6 and Tlr5^−/− strains. Among those miRNA-regulated pathways, arginine and proline metabolism as well as glutathione metabolism may have important roles in the Tlr knockout mice rather than in C57BL/6 mice.

• diet-induced obesity
• high-fat diet
• low-fat diet
• toll-like receptor
• weight reduction

• Adipose tissues
• Cytokines
• Human obesity
• Inflammation

• adiposity
• body mass index
• percent body fat
• selenium
• waist circumference

• Adiposity
• Adult
• Biomarkers/blood
• Body Mass Index
• Cross-Sectional Studies
• Humans
• Linear Models
• Male
• Middle Aged
• Multivariate Analysis
• Nutrition Surveys
• Obesity, Abdominal/blood
• Obesity, Abdominal/diagnosis
• Obesity, Abdominal/epidemiology
• Obesity, Abdominal/physiopathology
• Risk Factors
• Selenium/blood
• Sex Factors
• United States/epidemiology
• Waist Circumference
• Young Adult

• Age-related disorders
• Ageing
• Keystones

Immunotherapy has matured into standard treatment for several cancers, but much remains to be done to extend the reach of its effectiveness particularly to cancers that are resistant within each indication. This review proposes that nutrition can affect and potentially enhance the immune response against cancer. The general mechanisms that link nutritional principles to immune function and may influence the effectiveness of anticancer immunotherapy are examined. This represents also the premise for a research project aimed at identifying the best diet for immunotherapy enhancement against tumours (D.I.E.T project). Particular attention is turned to the gut microbiota and the impact of its composition on the immune system. Also, the dietary patterns effecting immune function are discussed including the value of adhering to a healthy diets such as the Mediterranean, Veg, Japanese, or a Microbiota-regulating diet, the very low ketogenic diet, which have been demonstrated to lower the risk of developing several cancers and reduce the mortality associated with them. Finally, supplements, as omega-3 and polyphenols, are discussed as potential approaches that could benefit healthy dietary and lifestyle habits in the context of immunotherapy.

• Cancer
• Functional supplements
• Healthy diet
• Immunotherapy
• Microbiome

• adipose tissue
• body mass index
• children
• lean mass
• normal weight obesity
• skeletal robustness

• Body composition
• Classical homocystinuria
• Cysteine
• CβS deficiency
• Leptin
• SCD-1

• metabolic health
• metabolically healthy obese
• metabolically unhealthy normal weight
• normal weight central obesity
• obesity
• postmenopausal breast cancer

• feature selection
• metabolic network data
• optimal matching

• Biomarkers
• Body Mass Index
• Chromatography, Liquid/methods
• Computer Simulation
• Data Interpretation, Statistical
• Healthy Volunteers
• Humans
• Machine Learning
• Mass Spectrometry/methods
• Metabolic Networks and Pathways
• Metabolomics/methods
• Metabolomics/statistics & numerical data

• K01 DK102851 NIDDK NIH HHS
• R01 MH105561 NIMH NIH HHS
• L30 DK106709 NIDDK NIH HHS
• RF1 AG051633 NIA NIH HHS
• P20 HL113451 NHLBI NIH HHS

• Adult
• Body Mass Index
• Cardiovascular Diseases/mortality
• Diet, Mediterranean
• Female
• Follow-Up Studies
• Health Surveys
• Humans
• Male
• Metabolic Syndrome/diet therapy
• Metabolic Syndrome/mortality
• Neoplasms/mortality
• Proportional Hazards Models
• Racial Groups
• Sedentary Behavior
• United States/epidemiology

• Canadian Institutes of Health Research
• Réseau de recherche en santé cardiométabolique, diabète et obésité