Alzheimer's disease: using gene/protein network machine learning for molecule discovery in olive oil.

Alzheimer's disease (AD) poses a profound human, social, and economic burden. Previous studies suggest that extra virgin olive oil (EVOO) may be helpful in preventing cognitive decline. Here, we present a network machine learning method for identifying bioactive phytochemicals in EVOO with the highest potential to impact the protein network linked to the development and progression of the AD. A balanced classification accuracy of 70.3 ± 2.6% was achieved in fivefold cross-validation settings for predicting late-stage experimental drugs targeting AD from other clinically approved drugs. The calibrated machine learning algorithm was then used to predict the likelihood of existing drugs and known EVOO phytochemicals to be similar in action to the drugs impacting AD protein networks. These analyses identified the following ten EVOO phytochemicals with the highest likelihood of being active against AD: quercetin, genistein, luteolin, palmitoleate, stearic acid, apigenin, epicatechin, kaempferol, squalene, and daidzein (in the order from the highest to the lowest likelihood). This in silico study presents a framework that brings together artificial intelligence, analytical chemistry, and omics studies to identify unique therapeutic agents. It provides new insights into how EVOO constituents may help treat or prevent AD and potentially provide a basis for consideration in future clinical studies.

High-fat diet consumption by male rat offspring of obese mothers exacerbates adipose tissue hypertrophy and metabolic alterations in adult life.

Obese mothers' offspring develop obesity and metabolic alterations in adulthood. Poor postnatal dietary patterns also contribute to obesity and its comorbidities. We aimed to determine whether in obese mothers' offspring an adverse postnatal environment, such as high-fat diet (HFD) consumption (second hit) exacerbates body fat accumulation, metabolic alterations and adipocyte size distribution. Female Wistar rats ate chow (C-5 %-fat) or HFD (maternal obesity (MO)-25 %-fat) from weaning until the end of lactation. Male offspring were weaned on either control (C/C and MO/C, maternal diet/offspring diet) or HFD (C/HF and MO/HF) diet. At 110 postnatal days, offspring were killed. Fat depots were excised to estimate adiposity index (AI). Serum glucose, triglyceride, leptin, insulin, insulin resistance index (HOMA-IR), corticosterone and dehydroepiandrosterone (DHEA) were determined. Adipocyte size distribution was evaluated in retroperitoneal fat. Body weight was similar in C/C and MO/C but higher in C/HF and MO/HF. AI, leptin, insulin and HOMA-IR were higher in MO/C and C/HF v. C/C but lower than MO/HF. Glucose increased in MO/HF v. MO/C. C/HF and MO/C had higher triglyceride and corticosterone than C/C, but lower corticosterone than MO/HF. DHEA and the DHEA/corticosterone ratio were lower in C/HF and MO/C v. C/C, but higher than MO/HF. Small adipocyte proportion decreased while large adipocyte proportions increased in MO/C and C/HF v. C/C and exacerbated in MO/HF v. C/HF. Postnatal consumption of a HFD by the offspring of obese mothers exacerbates body fat accumulation as well as the decrease of small and the increase of large adipocytes, which leads to larger metabolic abnormalities.

Renal Glucose Release after Unilateral Renal Denervation during a Hypoglycemic Clamp in Pigs with an Altered Hypothalamic Pituitary Adrenal Axis after Late-Gestational Dexamethasone Injection.

Previously, we demonstrated in pigs that renal denervation halves glucose release during hypoglycaemia and that a prenatal dexamethasone injection caused increased ACTH and cortisol concentrations as markers of a heightened hypothalamic pituitary adrenal axis (HPAA) during hypoglycaemia. In this study, we investigated the influence of an altered HPAA on renal glucose release during hypoglycaemia. Pigs whose mothers had received two late-gestational dexamethasone injections were subjected to a 75 min hyperinsulinaemic-hypoglycaemic clamp (<3 mmol/L) after unilateral surgical denervation. Para-aminohippurate (PAH) clearance, inulin, sodium excretion and arterio-venous blood glucose difference were measured every fifteen minutes. The statistical analysis was performed with a Wilcoxon signed-rank test. PAH, inulin, the calculated glomerular filtration rate and plasma flow did not change through renal denervation. Urinary sodium excretion increased significantly (p = 0.019). Side-dependent renal net glucose release (SGN) decreased by 25 ± 23% (p = 0.004). At 25 percent, the SGN decrease was only half of that observed in non-HPAA-altered animals in our prior investigation. The current findings may suggest that specimens with an elevated HPAA undergo long-term adaptations to maintain glucose homeostasis. Nonetheless, the decrease in SGN warrants further investigations and potentially caution in performing renal denervation in certain patient groups, such as diabetics at risk of hypoglycaemia.

Predicting anticancer hyperfoods with graph convolutional networks.

BACKGROUND: Recent efforts in the field of nutritional science have allowed the discovery of disease-beating molecules within foods based on the commonality of bioactive food molecules to FDA-approved drugs. The pioneering work in this field used an unsupervised network propagation algorithm to learn the systemic-wide effect on the human interactome of 1962 FDA-approved drugs and a supervised algorithm to predict anticancer therapeutics using the learned representations. Then, a set of bioactive molecules within foods was fed into the model, which predicted molecules with cancer-beating potential.The employed methodology consisted of disjoint unsupervised feature generation and classification tasks, which can result in sub-optimal learned drug representations with respect to the classification task. Additionally, due to the disjoint nature of the tasks, the employed approach proved cumbersome to optimize, requiring testing of thousands of hyperparameter combinations and significant computational resources.To overcome the technical limitations highlighted above, we represent each drug as a graph (human interactome) with its targets as binary node features on the graph and formulate the problem as a graph classification task. To solve this task, inspired by the success of graph neural networks in graph classification problems, we use an end-to-end graph neural network model operating directly on the graphs, which learns drug representations to optimize model performance in the prediction of anticancer therapeutics. RESULTS: The proposed model outperforms the baseline approach in the anticancer therapeutic prediction task, achieving an F1 score of 67.99%±2.52% and an AUPR of 73.91%±3.49%. It is also shown that the model is able to capture knowledge of biological pathways to predict anticancer molecules based on the molecules' effects on cancer-related pathways. CONCLUSIONS: We introduce an end-to-end graph convolutional model to predict cancer-beating molecules within food. The introduced model outperforms the existing baseline approach, and shows interpretability, paving the way to the future of a personalized nutritional science approach allowing the development of nutrition strategies for cancer prevention and/or therapeutics.

Network machine learning maps phytochemically rich "Hyperfoods" to fight COVID-19.

In this paper, we introduce a network machine learning method to identify potential bioactive anti-COVID-19 molecules in foods based on their capacity to target the SARS-CoV-2-host gene-gene (protein-protein) interactome. Our analyses were performed using a supercomputing DreamLab App platform, harnessing the idle computational power of thousands of smartphones. Machine learning models were initially calibrated by demonstrating that the proposed method can predict anti-COVID-19 candidates among experimental and clinically approved drugs (5658 in total) targeting COVID-19 interactomics with the balanced classification accuracy of 80-85% in 5-fold cross-validated settings. This identified the most promising drug candidates that can be potentially "repurposed" against COVID-19 including common drugs used to combat cardiovascular and metabolic disorders, such as simvastatin, atorvastatin and metformin. A database of 7694 bioactive food-based molecules was run through the calibrated machine learning algorithm, which identified 52 biologically active molecules, from varied chemical classes, including flavonoids, terpenoids, coumarins and indoles predicted to target SARS-CoV-2-host interactome networks. This in turn was used to construct a "food map" with the theoretical anti-COVID-19 potential of each ingredient estimated based on the diversity and relative levels of candidate compounds with antiviral properties. We expect this in silico predicted food map to play an important role in future clinical studies of precision nutrition interventions against COVID-19 and other viral diseases.

Screening of Natural Products Inhibitors of SARS-CoV-2 Entry.

The COVID-19 pandemic has led to the search for new molecules with antiviral activity against SARS-CoV-2. The entry of the virus into the cell is one of the main targets for inhibiting SARS-CoV-2 infection. Natural products are an important source of new therapeutic alternatives against diseases. Pseudotyped viruses allow the study of SARS-CoV-2 viral entry inhibitors, and due to their simplicity, they allow the screening of a large number of antiviral candidates in Biosafety Level 2 facilities. We used pseudotyped HIV-1 with the D614G SARS-CoV-2 spike glycoprotein to test its ability to infect ACE2-expressing HEK 293T cells in the presence of diverse natural products, including 21 plant extracts, 7 essential oils, and 13 compounds from plants and fungi. The 50% cytotoxic concentration (CC50) was evaluated using the resazurin method. From these analyses, we determined the inhibitory activity of the extract of Stachytarpheta cayennensis, which had a half-maximal inhibitory concentration (IC50) of 91.65 µg/mL, a CC50 of 693.5 µg/mL, and a selectivity index (SI) of 7.57, indicating its potential use as an inhibitor of SARS-CoV-2 entry. Moreover, our work indicates the usefulness of the pseudotyped-virus system in the screening of SARS-CoV-2 entry inhibitors.

Developmental programming and ageing of male reproductive function.

Developmental programming predisposes offspring to metabolic, behavioural and reproductive dysfunction in adult life. Evidence is accumulating that ageing phenotype and longevity are in part developmentally programmed in each individual. Unfortunately, there are few studies addressing the effects of developmental programming by maternal nutrition on the rate of ageing of the male reproductive system. This review will discuss effects of foetal exposure to maternal environmental challenges on male offspring fertility and normal ageing of the male reproductive system. We focus on several key factors involved in reproductive ageing such as decreased hormone production, DNA fragmentation, oxidative stress, telomere shortening, epigenetics, maternal lifestyle and nutrition. There is compelling evidence that ageing of the male reproductive system is developmentally programmed. Both maternal over- or undernutrition accelerate ageing of male offspring reproductive function through similar mechanisms such as decreased serum testosterone levels, increase in oxidative stress biomarkers in both the testes and sperm and changes in sperm quality. Importantly, even in adult life, exercise in male offspring of obese mothers improves adverse effects of programming on reproductive function. Maternal consumption of a low-protein diet causes transgenerational effects in progeny via the paternal line. The seminal fluid has effects on the intrauterine environment. Programming by male factors may involve more than just the sperm. Improving knowledge on developmental programming ageing interactions will improve not only male health and life span but also the health of future generations by reducing programming via the paternal line.

The Extracellular Vesicles from the Commensal Staphylococcus Epidermidis ATCC12228 Strain Regulate Skin Inflammation in the Imiquimod-Induced Psoriasis Murine Model.

Extracellular vesicles (EVs) are evaginations of the cytoplasmic membrane, containing nucleic acids, proteins, lipids, enzymes, and toxins. EVs participate in various bacterial physiological processes. Staphylococcus epidermidis interacts and communicates with the host skin. S. epidermidis' EVs may have an essential role in this communication mechanism, modulating the immunological environment. This work aimed to evaluate if S. epidermidis' EVs can modulate cytokine production by keratinocytes in vitro and in vivo using the imiquimod-induced psoriasis murine model. S. epidermidis' EVs were obtained from a commensal strain (ATC12228EVs) and a clinical isolated strain (983EVs). EVs from both origins induced IL-6 expression in HaCaT keratinocyte cultures; nevertheless, 983EVs promoted a higher expression of the pro-inflammatory cytokines VEGF-A, LL37, IL-8, and IL-17F than ATCC12228EVs. Moreover, in vivo imiquimod-induced psoriatic skin treated with ATCC12228EVs reduced the characteristic psoriatic skin features, such as acanthosis and cellular infiltrate, as well as VEGF-A, IL-6, KC, IL-23, IL-17F, IL-36γ, and IL-36R expression in a more efficient manner than 983EVs; however, in contrast, Foxp3 expression did not significantly change, and IL-36 receptor antagonist (IL-36Ra) was found to be increased. Our findings showed a distinctive immunological profile induction that is dependent on the clinical or commensal EV origin in a mice model of skin-like psoriasis. Characteristically, proteomics analysis showed differences in the EVs protein content, dependent on origin of the isolated EVs. Specifically, in ATCC12228EVs, we found the proteins glutamate dehydrogenase, ornithine carbamoyltransferase, arginine deiminase, carbamate kinase, catalase, superoxide dismutase, phenol-soluble ß1/ß2 modulin, and polyglycerol phosphate α-glucosyltransferase, which could be involved in the reduction of lesions in the murine imiquimod-induced psoriasis skin. Our results show that the commensal ATCC12228EVs have a greater protective/attenuating effect on the murine imiquimod-induced psoriasis by inducing IL-36Ra expression in comparison with EVs from a clinical isolate of S. epidermidis.

Relationship of vitamin D blood concentration with muscle mass and cognitive function in postmenopausal women.

INTRODUCTION: Low levels of vitamin D have been associated with muscle mass loss and cognitive function alteration. OBJECTIVE: To find out the relationship of vitamin D blood levels with muscle mass and cognitive function in postmenopausal women. MATERIALS AND METHODS: Ninety-nine postmenopausal women aged ≥ 50 years were studied. Calf circumference, and tricipital, bicipital, subscapular and suprailiac skinfolds were measured. Arm muscle area, bone-free arm muscle area, and muscle mass were calculated. The short physical performance battery (SPPB) was performed, and the sarcopenia rapid diagnostic questionnaire (SARC-F), as well as the Mini Mental State Examination (MMSE) were applied. A blood sample was taken to measure vitamin D blood concentration. For statistical analysis, Mann-Whitney's U-test and Spearman's correlation analysis were used. RESULTS: It was found that, the older the age, the higher the vitamin D levels, as well as higher SARC-F score. Vitamin D levels were negatively correlated with grip strength and SPPB. There was a negative correlation between vitamin D levels and MMSE global score. CONCLUSIONS: Vitamin D did not have a positive influence on muscle mass. A better MMSE performance was observed in those with lower vitamin D levels.

INTRODUCCIÓN: Las concentraciones bajas de vitamina D se han asociado con la pérdida de masa muscular y la alteración de la función cognitiva. OBJETIVO: Conocer la relación de la concentración sanguínea de vitamina D con la masa muscular y la función cognitiva en mujeres posmenopáusicas. MATERIALES Y MÉTODOS: Se estudiaron 99 mujeres posmenopáusicas ≥ 50 años. Se midió la circunferencia de la pantorrilla, los pliegues cutáneos tricipital, bicipital, subescapular y suprailíaco. Se calcularon: el área muscular del brazo, el área muscular libre de hueso y la masa muscular total. Se realizó la prueba corta de desempeño físico (PCDF), se aplicó el cuestionario de diagnóstico rápido de sarcopenia (SARC-F) y el Mini Examen del Estado Mental (MMSE). Se tomó una muestra de sangre para medir la concentración de vitamina D en sangre. Para el análisis estadístico se utilizó la prueba U de Mann-Whitney y análisis de correlación de Spearman. RESULTADOS: Se encontró que a mayor edad hubieron mayores concentraciones de vitamina D y mayor puntaje SARC-F. Las concentraciones de vitamina D se correlacionaron negativamente con la fuerza de agarre, la PCDF y la puntuación total del MMSE. CONCLUSIONES: La vitamina D no tuvo una influencia positiva sobre la masa muscular. Se observó un mejor desempeño en el MMSE en aquellas con concentraciones más bajas de vitamina D.

Neurocognitive predictors of self-reported reward responsivity and approach motivation in depression: A data-driven approach.

BACKGROUND: Individual differences in reward-related processes, such as reward responsivity and approach motivation, appear to play a role in the nature and course of depression. Prior work suggests that cognitive biases for valenced information may contribute to these reward processes. Yet there is little work examining how biased attention, processing, and memory for positively and negatively valenced information may be associated with reward-related processes in samples with depression symptoms. METHODS: We used a data-driven, machine learning (elastic net) approach to identify the best predictors of self-reported reward-related processes using multiple tasks of attention, processing, and memory for valenced information measured across behavioral, eye tracking, psychophysiological, and computational modeling approaches (n = 202). Participants were adults (ages 18-35) who ranged in depression symptom severity from mild to severe. RESULTS: Models predicted between 5.0-12.2% and 9.7-28.0% of held-out test sample variance in approach motivation and reward responsivity, respectively. Low self-referential processing of positively valenced information was the most robust, albeit modest, predictor of low approach motivation and reward responsivity. CONCLUSIONS: Self-referential processing of positive information is the strongest predictor of reward responsivity and approach motivation in a sample ranging from mild to severe depression symptom severity. Experiments are now needed to clarify the causal relationship between self-referential processing of positively valenced information and reward processes in depression.

Maternal obesity accelerates rat offspring metabolic ageing in a sex-dependent manner.

KEY POINTS: Maternal obesity predisposes to metabolic dysfunction in male and female offspring Maternal high-fat diet consumption prior to and throughout pregnancy and lactation accelerates offspring metabolic ageing in a sex-dependent manner This study provides evidence for programming-ageing interactions ABSTRACT: Human epidemiological studies show that maternal obesity (MO) shortens offspring life and health span. Life course cellular mechanisms involved in this developmental programming-ageing interaction are poorly understood. In a well-established rat MO model, female Wistar rats ate chow (controls (C)) or high energy, obesogenic diet to induce MO from weaning through pregnancy and lactation. Females were bred at postnatal day (PND) 120. Offspring (F1 ) of mothers on control diet (CF1 ) and MO diet (MOF1 ) delivered spontaneously at terms. Both CF1 and MOF1 ate C diet from weaning throughout the study. Offspring were killed at PND 36, 110, 450 and 650. We determined body and liver weights, liver and serum metabolite concentrations, hormones and oxidative stress biomarkers. Male and female CF1 body weight, total fat, adiposity index, serum leptin, insulin, insulin resistance, and liver weight, fat, triglycerides, malondialdehyde, reactive oxygen species and nitrotyrosine all rose with differing ageing trajectories. Female CF1 triglycerides were unchanged with age. Age-related increases were greater in MOF1 than CF1 in both sexes for all variables except glucose in males and females and cholesterol in males. Cholesterol fell in CF1 females but not MOF1 . Serum corticosterone levels were higher in male and female MOF1 than CF1 and declined with age. DHEA serum levels were lower in male and female MOF1 than CF1 . Liver antioxidant enzymes decreased with age (CF1 and MOF1 ). CONCLUSIONS: exposure to the developmental challenge of MO accelerates progeny ageing metabolic and endocrine profiles in a sex specific manner, providing evidence for programming-ageing interactions.

Maternal obesity has sex-dependent effects on insulin, glucose and lipid metabolism and the liver transcriptome in young adult rat offspring.

KEY POINTS: Maternal high-fat diet consumption predisposes to metabolic dysfunction in male and female offspring at young adulthood. Maternal obesity programs non-alcoholic fatty liver disease (NAFLD) in a sex-dependent manner. We demonstrate sex-dependent liver transcriptome profiles in rat offspring of obese mothers. In this study, we focused on pathways related to insulin, glucose and lipid signalling. These results improve understanding of the mechanisms by which a maternal high-fat diet affects the offspring. ABSTRACT: Maternal obesity (MO) predisposes offspring (F1) to obesity, insulin resistance (IR) and non-alcoholic fatty liver disease (NAFLD). MO's effects on the F1 liver transcriptome are poorly understood. We used RNA-seq to determine the liver transcriptome of male and female F1 of MO and control-fed mothers. We hypothesized that MO-F1 are predisposed to sex-dependent adult liver dysfunction. Female Wistar rat mothers ate a control (C) or obesogenic (MO) diet from the time they were weaned through breeding at postnatal day (PND) 120, delivery and lactation. After weaning, all male and female F1 ate a control diet. At PND 110, F1 serum, liver and fat were collected to analyse metabolites, histology and liver differentially expressed genes. Male and female MO-F1 showed increased adiposity index, triglycerides, insulin and homeostatic model assessment vs. C-F1 with similar body weight and glucose serum concentrations. MO-F1 males presented greater physiological and histological NAFLD characteristics than MO-F1 females. RNA-seq revealed 1365 genes significantly changed in male MO-F1 liver and only 70 genes in female MO-F1 compared with controls. GO and KEGG analysis identified differentially expressed genes related to metabolic processes. Male MO-F1 liver showed the following altered pathways: insulin signalling (22 genes), phospholipase D signalling (14 genes), NAFLD (13 genes) and glycolysis/gluconeogenesis (7 genes). In contrast, few genes were altered in these pathways in MO-F1 females. In summary, MO programs sex-dependent F1 changes in insulin, glucose and lipid signalling pathways, leading to liver dysfunction and insulin resistance.

Evaluating the quality of the processes of care and clinical outcomes of premature newborns admitted to neonatal intensive care units in Mexico.

OBJECTIVES: To develop quality of care (QoC) indicators, evaluate the quality of the processes of care (QPC) and clinical outcomes, and analyze the association between the QPC and severe clinical outcomes of preterm newborns admitted to neonatal intensive care units (NICUs). DESIGN: Mixed methods approach: (1) development of QoC indicators via modified RAND/UCLA method; (2) cross-sectional study of QoC evaluation and (3) multiple logistic regression analysis to ascertain the association between the QPC and severe clinical outcomes. SETTING: Two NICUs belonged to the Mexican Institute of Social Security in Mexico City. PARTICIPANTS: About 489 preterm neonates (<37 weeks of gestation) without severe congenital anomalies. MAIN OUTCOME MEASURE(S): The QoC indicators; ≥60% of recommended QPC and severe clinical outcomes. RESULTS: The QoC included 10 QPC indicators across four domains: respiratory, nutrition and metabolism, infectious diseases, and screening, and five outcome indicators. The lower QPC indicators were for the nutrition and metabolism domain (17.8% started enteral feeding with human milk, and 20.7% received sodium bicarbonate appropriately). The higher QPC indicator was for the screening domain (97.6% of neonates <30 weeks gestation underwent early (≤14 days) transfontanelar ultrasound). The mean recommended QPC that neonates received was 47.5%. Only 26.6% of neonates received ≥60% of recommended QPC. About 60.7% of neonates developed severe clinical outcomes including mortality and healthcare-related major morbidity. Receiving ≥60% of recommended QPC was associated with a decrease of nearly half of odds of severe clinical outcomes. CONCLUSION: The evaluation of the QoC in NICUs is essential to address modifiable gaps in quality.

Giant left ventricular rhabdomyoma treated successfully with everolimus: case report and review of literature.

IntroductionIntracardiac rhabdomyomas can cause severe ventricular dysfunction and outflow tract obstruction.Case reportA term newborn infant with antenatal diagnosis of giant left ventricle rhabdomyoma presented with cardiac failure and duct-dependent systemic circulation after birth. She was treated successfully with everolimus, showing decrease in tumour size and improvement in left ventricular ejection fraction.DiscussionTumour regression rate was 0.32 cm2/day and improved to 0.80 cm2/day with the use of everolimus. Herein we report a newborn with inoperable giant left ventricular cardiac rhabdomyoma and significant regression of the tumour. To our knowledge, this is the largest left ventricular rhabdomyoma reported. A review of the literature was undertaken for comparison. CONCLUSION: Everolimus has proven to be efficacious in size reduction of cardiac rhabdomyomas in cases when surgical resection is not possible.

Adipokines, insulin resistance, and adiposity as a predictors of metabolic syndrome in child survivors of lymphoma and acute lymphoblastic leukemia of a developing country.

BACKGROUND: There is a growing body of evidence indicating that pediatric survivors of cancer are at a greater risk of developing metabolic syndrome. This study evaluated some probable predictors of metabolic syndrome (MS), such as leptin and adiponectin concentrations, the leptin/adiponectin ratio, insulin resistance, and adiposity, in a sample of child survivors of lymphoma and leukemia in Mexico City. METHODS: Fifty two children (leukemia n = 26, lymphoma n = 26), who were within the first 5 years after cessation of therapy, were considered as eligible to participate in the study. Testing included fasting insulin, glucose, adipokines and lipids; body fat mass was measured by DXA. The MS components were analyzed according to tertiles of adipokines, insulin resistance, and adiposity. Comparisons between continuous variables were performed according to the data distribution. The MS components were analyzed according to tertiles of adipokines, insulin resistance, and adiposity. With the purpose of assessing the risk of a present MS diagnosis, odds ratios (OR) with a 95% confidence interval (95% IC) were obtained using logistic regression analysis according to the various metabolic markers. RESULTS: The median children age was 12.1 years, and the interval time from the completion of therapy to study enrollment was 4 years. Among the MS components, the prevalence of HDL-C low was most common (42%), followed by central obesity (29%). The HOMA-IR (OR 9.0, 95% CI 2.0; 41.1), body fat (OR 5.5, 95% CI 1.6; 19.3), leptin level (OR 5.7, 95% CI 1.6; 20.2) and leptin/adiponectin ratio (OR 9.4, 95% CI 2.0; 49.8) in the highest tertile, were predictive factors of developing MS; whereas the lowest tertile of adiponectin was associated with a protective effect but not significant. CONCLUSIONS: Biomarkers such as HOMA-IR, leptin and leptin/adiponectin are associated with each of the components of the MS and with a heightened risk of suffering MS among children survivors of cancer. Given the close relationship between MS with risk of developing type 2 diabetes and cardiovascular disease, it is imperative to implement prevention measures in this population and especially in developing countries where these pathologies have become the leading cause of death.

Maternal obesity in the rat impairs male offspring aging of the testicular antioxidant defence system.

A high-fat diet during intrauterine development predisposes offspring (F1) to phenotypic alterations, such as lipid synthesis imbalance and increased oxidative stress, causing changes in male fertility. The objective of this study was to evaluate the effects of maternal obesity during pregnancy and lactation on antioxidant enzymes in the F1 testes. Female Wistar rats (F0) were fed either a control (C, 5% fat) or an obesogenic (MO, maternal obesity, 25% fat) diet from weaning and throughout subsequent pregnancy and lactation. F1 offspring were weaned to the control diet. Testes were retrieved at 110, 450 and 650 postnatal days (PND) for real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR) and immunohistochemical (IHC) antioxidant enzyme analyses. Catalase was similar between groups by RT-qPCR, whereas by IHC it was higher in the MO group at all ages than in the C group. Superoxide dismutase 1 (SOD1) had lower expression at PND 110 in MO than in C by both techniques; at PND 450 and 650 by immunoanalysis SOD1 was higher in MO than in C. Glutathione peroxidase 1 (GPX1), GPX2 and GPX4 by RT-qPCR were similar between groups and ages; by IHC GPX1/2 was higher in MO than in C, whereas GPX4 showed the opposite result at PND 110 and 450. In conclusion, antioxidant enzymes in the rat testes are modified with age. Maternal obesity negatively affects the F1 testicular antioxidant defence system, which, in turn, can explain the decrease in reproductive capacity.

Effects of Late Gestational Fetal Exposure to Dexamethasone Administration on the Postnatal Hypothalamus-Pituitary-Adrenal Axis Response to Hypoglycemia in Pigs.

BACKGROUND: Prenatal glucocorticoid administration alters the activity of the fetal hypothalamic-pituitary-adrenocortical axis (HPAA), and correspondingly the adenocorticotropic hormone (ACTH) and cortisol levels after birth. The dosages required for these effects are critically discussed. Activation of the HPAA is related to metabolic syndrome and diabetes mellitus. Hypoglycemia is the classic side effect of antidiabetic treatment. We hypothesized that a low dosage of dexamethasone in late pregnancy alters the HPAA response to hypoglycemia in pigs. METHODS: 12 pregnant sows were randomly assigned to two groups which received either a low-dose intramuscular injection (99th and 100th day of gestation) of dexamethasone (0.06 µg/kg body weight) or vehicle. Three months after birth, 18 dexamethasone-treated anaesthetized offspring and 12 control offspring underwent a 75 min hypoglycemic clamp (blood glucose below 4 mmol/L) procedure. Heart rate (HR), blood pressure, ACTH and cortisol levels and body weight (at birth and after three months) were recorded. RESULTS: Dexamethasone-treated animals exhibited significantly elevated ACTH (139.9 ± 12.7 pg/mL) and cortisol (483.1 ± 30.3 nmol/L) levels during hypoglycemia as compared to the control group (41.7 ± 6.5 pg/mL and 257.9 ± 26.7 nmol/L, respectively), as well as an elevated HR (205.5 ± 5.7 bpm) and blood pressure (systolic: 128.6 ± 1.5, diastolic: 85.7 ± 0.7 mmHg) response as compared to the control group (153.2 ± 4.5 bpm; systolic: 118.6 ± 1.6, diastolic: 79.5 ± 1.4 mmHg, respectively; p < 0.001). CONCLUSIONS: Low-dose prenatal administration of dexamethasone not only exerts effects on the HPAA (ACTH and cortisol concentration) and vital parameters (HR and diastolic blood pressure) under baseline conditions, but also on ACTH, HR and systolic blood pressure during hypoglycemia.

Resveratrol partially prevents oxidative stress and metabolic dysfunction in pregnant rats fed a low protein diet and their offspring.

Protein restriction in pregnancy produces maternal and offspring metabolic dysfunction potentially as a result of oxidative stress. Data are lacking on the effects of inhibition of oxidative stress. We hypothesized that maternal resveratrol administration decreases oxidative stress, preventing, at least partially, maternal low protein-induced maternal and offspring metabolic dysfunction. In the present study, pregnant wistar rats ate control (C) (20% casein) or a protein-restricted (R) (10% casein) isocaloric diet. Half of each group received resveratrol orally, 20 mg kg(-1) day(-1), throughout pregnancy. Post-delivery, mothers and offspring ate C. Oxidative stress biomarkers and anti-oxidant enzymes were measured in placenta, maternal and fetal liver, and maternal serum corticosterone at 19 days of gestation (dG). Maternal (19 dG) and offspring (postnatal day 110) glucose, insulin, triglycerides, cholesterol, fat and leptin were determined. R mothers showed metabolic dysfunction, increased corticosterone and oxidative stress and reduced anti-oxidant enzyme activity vs. C. R placental and fetal liver oxidative stress biomarkers and anti-oxidant enzyme activity increased. R offspring showed higher male and female leptin, insulin and corticosterone, male triglycerides and female fat than C. Resveratrol decreased maternal leptin and improved maternal, fetal and placental oxidative stress markers. R induced offspring insulin and leptin increases were prevented and other R changes were offspring sex-dependent. Resveratrol partially prevents low protein diet-induced maternal, placental and sex-specific offspring oxidative stress and metabolic dysfunction. Oxidative stress is one mechanism programming offspring metabolic outcomes. These studies provide mechanistic evidence to guide human pregnancy interventions when fetal nutrition is impaired by poor maternal nutrition or placental function.

Adult exercise effects on oxidative stress and reproductive programming in male offspring of obese rats.

Exercise improves health but few data are available regarding benefits of exercise in offspring exposed to developmental programming. There is currently a worldwide epidemic of obesity. Obesity in pregnant women predisposes offspring to obesity. Maternal obesity has well documented effects on offspring reproduction. Few studies address ability of offspring exercise to reduce adverse outcomes. We observed increased oxidative stress and impaired sperm function in rat offspring of obese mothers. We hypothesized that regular offspring exercise reverses adverse effects of maternal obesity on offspring sperm quality and fertility. Female Wistar rats ate chow (C) or high-energy, obesogenic diet (MO) from weaning through lactation, bred at postnatal day (PND) 120, and ate their pregnancy diet until weaning. All offspring ate C diet from weaning. Five male offspring (different litters) ran on a wheel for 15 min, 5 times/week from PND 330 to 450 and were euthanized at PND 450. Average distance run per session was lower in MO offspring who had higher body weight, adiposity index, and gonadal fat and showed increases in testicular oxidative stress biomarkers. Sperm from MO offspring had reduced antioxidant enzyme activity, lower sperm quality, and fertility. Exercise in MO offspring decreased testicular oxidative stress, increased sperm antioxidant activity and sperm quality, and improved fertility. Exercise intervention has beneficial effects on adiposity index, gonadal fat, oxidative stress markers, sperm quality, and fertility. Thus regular physical exercise in male MO offspring recuperates key male reproductive functions even at advanced age: it's never too late.

On knowing a gene: A distributional hypothesis of gene function.

As words can have multiple meanings that depend on sentence context, genes can have various functions that depend on the surrounding biological system. This pleiotropic nature of gene function is limited by ontologies, which annotate gene functions without considering biological contexts. We contend that the gene function problem in genetics may be informed by recent technological leaps in natural language processing, in which representations of word semantics can be automatically learned from diverse language contexts. In contrast to efforts to model semantics as "is-a" relationships in the 1990s, modern distributional semantics represents words as vectors in a learned semantic space and fuels current advances in transformer-based models such as large language models and generative pre-trained transformers. A similar shift in thinking of gene functions as distributions over cellular contexts may enable a similar breakthrough in data-driven learning from large biological datasets to inform gene function.