Nutrient-based strategies to enhance docosahexaenoic acid (DHA) utilization in the piglet brain

Using the piglet as a model for the human infant, the goal of this study was to compare dietary lipid matrices found in infant formula and maternal milk on post-natal neurodevelopmental patterns. Over a 25-day feeding study, piglets (n=9-10 per treatment, 1.5 ± 0.2 kg initial BW) were either sow-reared (SR) with ad libitum intake, or artificially-reared (AR) receiving 1 of 3 milk replacers modified to mimic the nutritional profile and intake pattern of sow’s milk. Our AR treatments included: T1, artificially-reared (AR) control formula; T2, T1 + 45% total dietary fat replaced with pre-digested fat (PDF); T3, T2 + 10% lecithin + 0.4% cholesterol. Sow-reared animals were used as a positive control for study outcomes. Piglets were weighed daily, serum samples were collected at d 0, d 14, and d 25 of study, and fecal samples were collected, and pooled from d 13-27. At 3 weeks of age, piglets were subjected to a standardized set of magnetic resonance imaging (MRI) procedures to identify macro- and micro-structural characteristics of the brain. At study conclusion, piglets were euthanized and tissues were collected for further analysis. For the duration of the study, SR piglets exhibited higher BW gain and heavier extracted whole brain weights compared with AR piglets. Analysis of fecal fat suggested greater (P < 0.05) excretion of dietary fat with addition of PDF along with lecithin and cholesterol. Serum lipid profiling at d 14 and d 25 of study revealed serum triglycerides (TAG) concentrations to be higher (P = 0.176, P = 0.164) in T3-fed piglets when compared with T1- and T2-fed piglets. Furthermore, serum cholesterol concentrations were higher (P < 0.05) in T3-fed piglets when compared with T1- and T2-fed piglets on d 25 of study. Furthermore, hippocampal tissue analysis revealed neutral lipid (NL) docosahexaenoic acid (DHA) concentrations were greater (P < 0.05) in T3-fed pigs compared with T1-fed and SR pigs. Hippocampal phospholipid (PL) DHA concentrations of T2- or T3-fed pigs were intermediate to T1-fed and SR piglets. Diffusion tensor imaging, a MRI sequence that characterizes brain microstructure, revealed that SR piglets had greater (P < 0.05) average whole-brain fractional anisotropy (FA) values compared with AR piglets, suggesting differences in white matter organization. Although global analysis did not reveal differences within AR treatments for DTI outcomes, FA values of the internal capsule were not different between SR and T3-fed piglets, suggesting a modulatory effect of PDF + lecithin + cholesterol fat system on white matter maturation. Higher fecal fat excretion, partnered with higher serum TAG concentrations in T3-fed piglets as compared with other AR treatments, suggested higher bioavailability of the PDF when supplemented with lecithin and cholesterol. Elevated serum cholesterol at d 25 of study, partnered with elevated hippocampal DHA concentrations of T3-fed animals suggested higher bioavailability of the PDF, especially when supplemented with lecithin and cholesterol. Higher FA values in the internal capsule of T3-fed piglets indicate higher myelination of this early maturing white matter rich region as compared with other AR treatments, and may be impacted by elevated serum cholesterol concentrations. As the animal matures in age, the 2-fold elevation of hippocampal DHA seen in T3-fed piglets, as compared with control or SR animals, may produce similar elevations white matter maturation in the hippocampus as seen in the IC. Overall, our results indicate differential patterns of white matter development between AR and SR animals, and replacing part of formula TAG with PDF, and addition of lecithin and cholesterol, may elicit preferential accretion of brain DHA due to compositional manipulations of the dietary lipid matrix

CSF Biomarkers for Alzheimer's Disease Diagnosis

Alzheimer's disease (AD) is the most common form of dementia that affects several million people worldwide. The major neuropathological hallmarks of AD are the presence of extracellular amyloid plaques that are composed of Aβ40 and Aβ42 and intracellular neurofibrillary tangles (NFT), which is composed of hyperphosphorylated protein Tau. While the amyloid plaques and NFT could define the disease progression involving neuronal loss and dysfunction, significant cognitive decline occurs before their appearance. Although significant advances in neuroimaging techniques provide the structure and physiology of brain of AD cases, the biomarker studies based on cerebrospinal fluid (CSF) and plasma represent the most direct and convenient means to study the disease progression. Biomarkers are useful in detecting the preclinical as well as symptomatic stages of AD. In this paper, we discuss the recent advancements of various biomarkers with particular emphasis on CSF biomarkers for monitoring the early development of AD before significant cognitive dysfunction

An NMR‐based biosensor to measure stereo‐specific methionine sulfoxide reductase (MSR) activities in vitro and in vivo

Oxidation of protein methionines to methionine-sulfoxides (MetOx) is associated with several age-related diseases. In healthy cells, MetOx is reduced to methionine by two families of conserved methionine sulfoxide reductase enzymes, MSRA and MSRB that specifically target the S- or R-diastereoisomers of methionine-sulfoxides, respectively. To directly interrogate MSRA and MSRB functions in cellular settings, we developed an NMR-based biosensor that we call CarMetOx to simultaneously measure both enzyme activities in single reaction setups. We demonstrate the suitability of our strategy to delineate MSR functions in complex biological environments, including cell lysates and live zebrafish embryos. Thereby, we establish differences in substrate specificities between prokaryotic and eukaryotic MSRs and introduce CarMetOx as a highly sensitive tool for studying therapeutic targets of oxidative stress-related human diseases and redox regulated signaling pathways.Fil: Sanchez Lopez, Carolina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Biología Molecular y Celular de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Biología Molecular y Celular de Rosario; ArgentinaFil: Labadie, Natalia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Biología Molecular y Celular de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Biología Molecular y Celular de Rosario; ArgentinaFil: Lombardo, Veronica Andrea. Universidad Nacional de Rosario. Centro de Estudios Interdisciplinarios; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Biología Molecular y Celular de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Biología Molecular y Celular de Rosario; ArgentinaFil: Biglione, Franco Agustín. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Biología Molecular y Celular de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Biología Molecular y Celular de Rosario; ArgentinaFil: Manta, Bruno. Harvard Medical School; Estados UnidosFil: Jacob, Reeba. Weizmann Institute Of Science.; IsraelFil: Gladyshev, Vadim. Harvard Medical School; Estados UnidosFil: Abdelilah Seyfried, Salim. Universitat Potsdam; Alemania. Leibniz Universitat Hannover; AlemaniaFil: Selenko, Philipp. Weizmann Institute Of Science.; IsraelFil: Binolfi, Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Biología Molecular y Celular de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Biología Molecular y Celular de Rosario; Argentin

Analyzing Technology Adoption - The Case of Kerala Home Gardens

Homegardens are traditional agroforestry system with a unique structure and function. It is the predominant farming system in Kerala. The study was undertaken in Thiruvananthapuram district covering a sample of 100 homegardens farmers from all the five agro-ecological units with an aim to assess the level of adoption of selected Kerala Agricultural University (KAU) production practices in homegardens. Results of the study identified that majority of the farmers (63%) belonged to medium level of adoption. Adoption quotient was worked out and compared with standard Rogers curve. Correlation analysis of the independent variables with the dependent variable viz., level of adoption indicated that age, farming experience, knowledge, evaluative perception, mass media contribution, livestock possession and extension contribution had direct significant effect on level of adoption of KAU production practices by homegarden farmers

Influence of retinoic acid on mesenchymal stem cell differentiation in amyloid hydrogels

This paper presents data related to the research article “Self healing hydrogels composed of amyloid nano fibrils for cell culture and stem cell differentiation” [1]. Here we probed the collective influence of all-trans retinoic acid (RA) and substrate properties (amyloid hydrogel) on human mesenchymal stem cell (hMSC) differentiation. Stem cells were cultured on soft amyloid hydrogels [1,2] in the presence and absence of matrix encapsulated RA. The cell morphology was imaged and assessed via quantification of circularity. Further immunostaining and quantitative real time PCR was used to quantify various markers of differentiation in the neuronal lineage

Comparison of brain development in sow-reared and artificially-reared piglets

IntroductionProvision of adequate nutrients is critical for proper growth and development of the neonate, yet the impact of breastfeeding versus formula feeding on neural maturation has yet to be fully determined. Using the piglet as a model for the human infant, our objective was to compare neurodevelopment of piglets that were either sow-reared or reared in an artificial setting. MethodsOver a 25-d feeding study, piglets (1.5 ± 0.2 kg initial bodyweight) were either sow-reared (SR; n = 10) with ad libitum intake, or artificially-reared (AR; n = 29) receiving an infant formula modified to mimic the nutritional profile and intake pattern of sow’s milk. At study conclusion, piglets were subjected to a standardized set of magnetic resonance imaging (MRI) procedures to quantify structure and composition of the brain.ResultsDiffusion tensor imaging, an MRI sequence that characterizes brain microstructure, revealed that SR piglets had greater (P < 0.05) average whole-brain fractional anisotropy, and lower (P < 0.05) mean and radial and axial diffusivity values compared with AR piglets, suggesting differences in white matter organization. Voxel-based morphometric analysis, a measure of white and gray matter volumes concentrations, revealed differences (P < 0.05) in bilateral development of gray matter clusters in the cortical brain regions of the AR piglets compared with SR piglets. Region of interest (ROI) analysis revealed larger (P < 0.05) whole brain volumes in SR animals compared with AR, and subcortical regions to be larger (P < 0.05) as a percentage of whole-brain volume in AR piglets compared with SR animals. Quantification of brain metabolites using magnetic resonance spectroscopy revealed SR piglets had higher (P < 0.05) concentrations of myo-inositol, glycerophosphocholine + phosphocholine, and creatine + phosphocreatine compared with AR piglets. However, glutamate + glutamine levels were higher (P < 0.05) in AR piglets when compared with SR animals. ConclusionOverall, increases in brain metabolite concentrations, coupled with greater FA values in white matter tracts and volume differences in gray matter of specific brain regions, suggest differences in myelin development and cell proliferation in SR vs. AR piglets

What Are the Consequences of Livelihood Diversification, and What Solutions are Suggested? Findings from Tamil Nadu, India

Agriculture is one of the major sectors affected by climate change, and farmers are having to adapt rapidly to overcome the risks. However, farmers face many struggles because of lack of awareness and experience of new methods. Understanding farmers’ constraints and adaptation strategies is very important for the implementation of adequate policies for agricultural and food security. Hence, this research aims to investigate the consequences faced by farmers due to livelihood diversification and suggestions to overcome. Data were collected from 240 respondents in Tamil Nadu, India by a thorough survey method with the help of a pretested, well-structured interview schedule. Percentage analysis is an appropriate method that gives answers to how many respondents give a particular response. The Garratt ranking technique was used to study the preferences and change in priority of consequences encountered by farmers–and the potential advantages–into numerical scores. The Z test was used to determine whether two population means are different with the same variance. Data analysis was done using SPSS software. The results show that the majority of farmers reported concerns regarding constraints such as lack of previous experience, poor family support, and involvement of risk factors. The survey reveals that Tamil Nadu farmers suggested the conducting of specific training, encouraging livestock management and providing subsidies for agricultural and allied enterprise development as strategies to overcome the constraints of livelihood diversification. The Z test results indicated that there is a difference between irrigated and nonirrigated farms with respect to farmers’ age, educational status, level of income, occupation, and awareness of climate change. The suggestions offered help policymakers develop suitable policies

What Are the Consequences of Livelihood Diversification, and What Solutions are Suggested? Findings from Tamil Nadu, India

Agriculture is one of the major sectors affected by climate change, and farmers are having to adapt rapidly to overcome the risks. However, farmers face many struggles because of lack of awareness and experience of new methods. Understanding farmers’ constraints and adaptation strategies is very important for the implementation of adequate policies for agricultural and food security. Hence, this research aims to investigate the consequences faced by farmers due to livelihood diversification and suggestions to overcome. Data were collected from 240 respondents in Tamil Nadu, India by a thorough survey method with the help of a pretested, well-structured interview schedule. Percentage analysis is an appropriate method that gives answers to how many respondents give a particular response. The Garratt ranking technique was used to study the preferences and change in priority of consequences encountered by farmers–and the potential advantages–into numerical scores. The Z test was used to determine whether two population means are different with the same variance. Data analysis was done using SPSS software. The results show that the majority of farmers reported concerns regarding constraints such as lack of previous experience, poor family support, and involvement of risk factors. The survey reveals that Tamil Nadu farmers suggested the conducting of specific training, encouraging livestock management and providing subsidies for agricultural and allied enterprise development as strategies to overcome the constraints of livelihood diversification. The Z test results indicated that there is a difference between irrigated and nonirrigated farms with respect to farmers’ age, educational status, level of income, occupation, and awareness of climate change. The suggestions offered help policymakers develop suitable policies

Fat embolism syndrome

Fat embolism syndrome is an often overlooked cause of breathlessness in trauma wards. Presenting in a wide range of clinical signs of varying severity, fat embolism is usually diagnosed by a physician who keeps a high degree of suspicion. The clinical background, chronology of symptoms and corroborative laboratory findings are instrumental in a diagnosis of fat embolism syndrome. There are a few diagnostic criteria which are helpful in making a diagnosis of fat embolism syndrome. Management is mainly prevention of fat embolism syndrome, and organ supportive care. Except in fulminant fat embolism syndrome, the prognosis is usually good