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Astrocytes play a pivotal role in maintaining brain homeostasis. Recent research has highlighted the significance of palmitic acid (PA) in triggering pro-inflammatory pathways contributing to neurotoxicity. Furthermore, Genomic-scale metabolic models and control theory have revealed that metabolic switches (MSs) are metabolic pathway regulators by potentially exacerbating neurotoxicity, thereby offering promising therapeutic targets. Herein, we characterized these enzymatic MSs in silico as potential therapeutic targets, employing protein-protein and drug-protein interaction networks alongside structural characterization techniques. Our findings indicate that five MSs (P00558, P04406, Q08426, P09110, and O76062) were functionally linked to nervous system drug targets and may be indirectly regulated by specific neurological drugs, some of which exhibit polypharmacological potential (e.g., Trifluperidol, Trifluoperazine, Disulfiram, and Haloperidol). Furthermore, four MSs (P00558, P04406, Q08426, and P09110) feature ligand-binding or allosteric cavities with druggable potential. Our results advocate for a focused exploration of P00558 (phosphoglycerate kinase 1), P04406 (glyceraldehyde-3-phosphate dehydrogenase), Q08426 (peroxisomal bifunctional enzyme, enoyl-CoA hydratase, and 3-hydroxyacyl CoA dehydrogenase), P09110 (peroxisomal 3-ketoacyl-CoA thiolase), and O76062 (Delta(14)-sterol reductase) as promising targets for the development or repurposing of pharmacological compounds, which could have the potential to modulate lipotoxic-altered metabolic pathways, offering new avenues for the treatment of related human diseases such as neurological diseases.

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Parkinson's disease (PD) is a chronic and progressive neurodegenerative disease with the major symptoms comprising loss of movement coordination (motor dysfunction) and non-motor dysfunction, including gastrointestinal symptoms. Alterations in the gut microbiota composition have been reported in PD patients vs. controls. However, it is still unclear how these compositional changes contribute to disease etiology and progression. Furthermore, most of the available studies have focused on European, Asian, and North American cohorts, but the microbiomes of PD patients in Latin America have not been characterized. To address this problem, we obtained fecal samples from Colombian participants (n = 25 controls, n = 25 PD idiopathic cases) to characterize the taxonomical community changes during disease via 16S rRNA gene sequencing. An analysis of differential composition, diversity, and personalized computational modeling was carried out, given the fecal bacterial composition and diet of each participant. We found three metabolites that differed in dietary habits between PD patients and controls: carbohydrates, trans fatty acids, and potassium. We identified six genera that changed significantly in their relative abundance between PD patients and controls, belonging to the families Lachnospiraceae, Lactobacillaceae, Verrucomicrobioaceae, Peptostreptococcaceae, and Streptococcaceae. Furthermore, personalized metabolic modeling of the gut microbiome revealed changes in the predicted production of seven metabolites (Indole, tryptophan, fructose, phenylacetic acid, myristic acid, 3-Methyl-2-oxovaleric acid, and N-Acetylneuraminic acid). These metabolites are associated with the metabolism of aromatic amino acids and their consumption in the diet. Therefore, this research suggests that each individual's diet and intestinal composition could affect host metabolism. Furthermore, these findings open the door to the study of microbiome-host interactions and allow us to contribute to personalized medicine.

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Huntington's disease (HD) is a genetic disorder caused by a CAG trinucleotide expansion in the huntingtin (HTT) gene. Juan de Acosta, Atlántico, a city located on the Caribbean coast of Colombia, is home to the world's second-largest HD pedigree. Here, we include 291 descendants of this pedigree with at least one family member with HD. Blood samples were collected, and genomic DNA was extracted. We quantified the HTT CAG expansion using an amplicon sequencing protocol. The genetic heterogeneity was measured as the ratio of the mosaicism allele's read peak and the slippage ratio of the allele's read peak from our sequence data. The statistical and bioinformatic analyses were performed with a significance threshold of p < 0.05. We found that the average HTT CAG repeat length in all participants was 21.91 (SD = 8.92). Of the 291 participants, 33 (11.3%, 18 females) had a positive molecular diagnosis for HD. Most affected individuals were adults, and the most common primary and secondary alleles were 17/7 (CAG/CCG) and 17/10 (CAG/CCG), respectively. The mosaicism increased with age in the participants with HD, while the slippage analyses revealed differences by the HD allele type only for the secondary allele. The slippage tended to increase with the HTT CAG repeat length in the participants with HD, but the increase was not statistically significant. This study analyzed the genetic and molecular features of 291 participants, including 33 with HD. We found that the mosaicism increased with age in the participants with HD, particularly for the secondary allele. The most common haplotype was 17/7_17/10. The slippage for the secondary allele varied by the HD allele type, but there was no significant difference in the slippage by sex. Our findings offer valuable insights into HD and could have implications for future research and clinical management.

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Neurodegenerative diseases (NDs) are characterized by a progressive deterioration of neuronal function, leading to motor and cognitive damage in patients. Astrocytes are essential for maintaining brain homeostasis, and their functional impairment is increasingly recognized as central to the etiology of various NDs. Such impairment can be induced by toxic insults with palmitic acid (PA), a common fatty acid, that disrupts autophagy, increases reactive oxygen species, and triggers inflammation. Although the effects of PA on astrocytes have been addressed, most aspects of the dynamics of this fatty acid remain unknown. Additionally, there is still no model that satisfactorily explains how astroglia goes from being neuroprotective to neurotoxic. Current incomplete knowledge needs to be improved by the growing field of non-coding RNAs (ncRNAs), which is proven to be related to NDs, where the complexity of the interactions among these molecules and how they control other RNA expressions need to be addressed. In the present study, we present an extensive competing endogenous RNA (ceRNA) network using transcriptomic data from normal human astrocyte (NHA) cells exposed to PA lipotoxic conditions and experimentally validated data on ncRNA interaction. The obtained network contains 7 lncRNA transcripts, 38 miRNAs, and 239 mRNAs that showed enrichment in ND-related processes, such as fatty acid metabolism and biosynthesis, FoxO and TGF-ß signaling pathways, prion diseases, apoptosis, and immune-related pathways. In addition, the transcriptomic profile was used to propose 22 potential key controllers lncRNA/miRNA/mRNA axes in ND mechanisms. The relevance of five of these axes was corroborated by the miRNA expression data obtained in other studies. MEG3 (ENST00000398461)/hsa-let-7d-5p/ATF6B axis showed importance in Parkinson's and late Alzheimer's diseases, while AC092687.3/hsa-let-7e-5p/[SREBF2, FNIP1, PMAIP1] and SDCBP2-AS1 (ENST00000446423)/hsa-miR-101-3p/MAPK6 axes are probably related to Alzheimer's disease development and pathology. The presented network and axes will help to understand the PA-induced mechanisms in astrocytes, leading to protection or injury in the CNS under lipotoxic conditions as part of the intricated cellular regulation influencing the pathology of different NDs. Furthermore, the five corroborated axes could be considered study targets for new pharmacologic treatments or as possible diagnostic molecules, contributing to improving the quality of life of millions worldwide.

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Chronic intake of a high-fat diet increases saturated fatty acids in the brain causing the progression of neurodegenerative diseases. Palmitic acid is a free fatty acid abundant in the diet that at high concentrations may penetrate the blood-brain barrier and stimulate the production of pro-inflammatory cytokines, leading to inflammation in astrocytes. The use of the synthetic neurosteroid tibolone in protection against fatty acid toxicity is emerging, but its transcriptional effects on palmitic acid-induced lipotoxicity remain unclear. Herein, we performed a transcriptome profiling of normal human astrocytes to investigate the molecular mechanisms by which palmitic acid causes cellular damage to astrocytes, and whether tibolone could reverse its detrimental effects. Astrocytes undergo a profound transcriptional change at 2 mM palmitic acid, affecting the expression of 739 genes, 366 upregulated and 373 downregulated. However, tibolone at 10 nM does not entirely reverse palmitic acid effects. Additionally, the protein-protein interaction reveals two novel gene clustering modules. The first module involves astrocyte defense responses by upregulation of pathways associated with antiviral innate immunity, and the second is linked to lipid metabolism. Our data suggest that activation of viral response signaling pathways might be so far, the initial molecular mechanism of astrocytes in response to a lipotoxic insult by palmitic acid, triggered particularly upon increased expression levels of IFIT2, IRF1, and XAF1. Therefore, this novel approach using a global gene expression analysis may shed light on the pleiotropic effects of palmitic acid on astrocytes, and provide a basis for future studies addressed to elucidate these responses in neurodegenerative conditions, which is highly valuable for the design of therapeutic strategies.

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Multipotent mesenchymal stromal cells (MSCs) have been described as bone marrow stromal cells, which can form cartilage, bone or hematopoietic supportive stroma. In 2006, the International Society for Cell Therapy (ISCT) established a set of minimal characteristics to define MSCs. According to their criteria, these cells must express CD73, CD90 and CD105 surface markers; however, it is now known they do not represent true stemness epitopes. The objective of the present work was to determine the surface markers for human MSCs associated with skeletal tissue reported in the literature (1994-2021). To this end, we performed a scoping review for hMSCs in axial and appendicular skeleton. Our findings determined the most widely used markers were CD105 (82.9%), CD90 (75.0%) and CD73 (52.0%) for studies performed in vitro as proposed by the ISCT, followed by CD44 (42.1%), CD166 (30.9%), CD29 (27.6%), STRO-1 (17.7%), CD146 (15.1%) and CD271 (7.9%) in bone marrow and cartilage. On the other hand, only 4% of the articles evaluated in situ cell surface markers. Even though most studies use the ISCT criteria, most publications in adult tissues don't evaluate the characteristics that establish a stem cell (self-renewal and differentiation), which will be necessary to distinguish between a stem cell and progenitor populations. Collectively, MSCs require further understanding of their characteristics if they are intended for clinical use.

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Control theory, a well-established discipline in engineering and mathematics, has found novel applications in systems biology. This interdisciplinary approach leverages the principles of feedback control and regulation to gain insights into the complex dynamics of cellular and molecular networks underlying chronic diseases, including neurodegeneration. By modeling and analyzing these intricate systems, control theory provides a framework to understand the pathophysiology and identify potential therapeutic targets. Therefore, this review examines the most widely used control methods in conjunction with genomic-scale metabolic models in the steady state of the multi-omics type. According to our research, this approach involves integrating experimental data, mathematical modeling, and computational analyses to simulate and control complex biological systems. In this review, we find that the most significant application of this methodology is associated with cancer, leaving a lack of knowledge in neurodegenerative models. However, this methodology, mainly associated with the Minimal Dominant Set (MDS), has provided a starting point for identifying therapeutic targets for drug development and personalized treatment strategies, paving the way for more effective therapies.

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Diagnosis of neurodegenerative disease (NDD) is complex, therefore simpler, less invasive, more accurate biomarkers are needed. small non-coding RNA (sncRNA) dysregulates in NDDs and sncRNA signatures have been explored for the diagnosis of NDDs, however, the performance of previous biomarkers is still better. Astrocyte dysfunction promotes neurodegeneration and thus derived scnRNA signatures could provide a more precise way to identify of changes related to NDD course and pathogenesis, and it could be useful for the dissection of mechanistic insights operating in NDD. Often sncRNA are transported outside the cell by the action of secreted particles such as extracellular vesicles (EV), which protect sncRNA from degradation. Furthermore, EV associated sncRNA can cross the BBB to be found in easier to obtain peripheral samples, EVs also inherit cell-specific surface markers that can be used for the identification of Astrocyte Derived Extracellular Vesicles (ADEVs) in a peripheral sample. By the study of the sncRNA transported in ADEVs it is possible to identify astrocyte specific sncRNA signatures that could show astrocyte dysfunction in a more simpler manner than previous methods. However, sncRNA signatures in ADEV are not a copy of intracellular transcriptome and methodological aspects such as the yield of sncRNA produced in ADEV or the variable amount of ADEV captured after separation protocols must be considered. Here we review the role as signaling molecules of ADEV derived sncRNA dysregulated in conditions associated with risk of neurodegeneration, providing an explanation of why to choose ADEV for the identification of astrocyte-specific transcriptome. Finally, we discuss possible limitations of this approach and the need to improve the detection limits of sncRNA for the use of ADEV derived sncRNA signatures.

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Potato (Solanum tuberosum L.) is the third largest source of antioxidants in the human diet, after maize and tomato. Potato landraces have particularly diverse contents of antioxidant compounds such as anthocyanins. We used this diversity to study the evolutionary and genetic basis of anthocyanin pigmentation. Specifically, we analyzed the transcriptomes and anthocyanin content of tubers from 37 landraces with different colorations. We conducted analyses of differential expression between potatoes with different colorations and used weighted correlation network analysis to identify genes whose expression is correlated to anthocyanin content across landraces. A very significant fraction of the genes identified in these two analyses had annotations related to the flavonoid-anthocyanin biosynthetic pathway, including 18 enzymes and 5 transcription factors. Importantly, the causal genes at the D, P and R loci governing anthocyanin accumulation in potato cultivars also showed correlations to anthocyanin production in the landraces studied here. Furthermore, we found that 60% of the genes identified in our study were located within anthocyanin QTLs. Finally, we identified new candidate enzymes and transcription factors that could have driven the diversification of anthocyanins. Our results indicate that many anthocyanins biosynthetic genes were manipulated in ancestral potato breeding and can be used in future breeding programs.

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The importance of miRNAs in cellular processes and their dysregulation has taken significant importance in understanding different pathologies. Due to the constant increase in the prevalence of neurodegenerative diseases (ND) worldwide and their economic impact, mild cognitive impairment (MCI), considered a prodromal phase, is a logical starting point to study this public health problem. Multiple studies have established the importance of miRNAs in MCI, including astrocyte regulation during stressful conditions. Additionally, the protection mechanisms exerted by astrocytes against some damage in the central nervous system (CNS) lead to astrocytic reactivation, in which a differential expression of miRNAs has been shown. Nevertheless, excessive reactivation can cause neurodegeneration, and a clear pattern defining the equilibrium point between a neuroprotective or detrimental astrocytic phenotype is unknown. Therefore, the miRNA expression has gained significant attention to understand the maintenance of brain balance and improve the diagnosis and treatment at earlier stages in the ND. Here, we provide a comprehensive review of the emerging role of miRNAs in cellular processes that contribute to the loss of cognitive function, including lipotoxicity, which can induce chronic inflammation, also considering the fundamental role of astrocytes in brain homeostasis.

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The association between neurodegenerative diseases (NDs) and obesity has been well studied in recent years. Obesity is a syndrome of multifactorial etiology characterized by an excessive accumulation and release of fatty acids (FA) in adipose and non-adipose tissue. An excess of FA generates a metabolic condition known as lipotoxicity, which triggers pathological cellular and molecular responses, causing dysregulation of homeostasis and a decrease in cell viability. This condition is a hallmark of NDs, and astrocytes are particularly sensitive to it, given their crucial role in energy production and oxidative stress management in the brain. However, analyzing cellular mechanisms associated with these conditions represents a challenge. In this regard, metabolomics is an approach that allows biochemical analysis from the comprehensive perspective of cell physiology. This technique allows cellular metabolic profiles to be determined in different biological contexts, such as those of NDs and specific metabolic insults, including lipotoxicity. Since data provided by metabolomics can be complex and difficult to interpret, alternative data analysis techniques such as machine learning (ML) have grown exponentially in areas related to omics data. Here, we developed an ML model yielding a 93% area under the receiving operating characteristic (ROC) curve, with sensibility and specificity values of 80% and 93%, respectively. This study aimed to analyze the metabolomic profiles of human astrocytes under lipotoxic conditions to provide powerful insights, such as potential biomarkers for scenarios of lipotoxicity induced by palmitic acid (PA). In this work, we propose that dysregulation in seleno-amino acid metabolism, urea cycle, and glutamate metabolism pathways are major triggers in astrocyte lipotoxic scenarios, while increased metabolites such as alanine, adenosine, and glutamate are suggested as potential biomarkers, which, to our knowledge, have not been identified in human astrocytes and are proposed as candidates for further research and validation.

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Lipotoxicity is a metabolic condition resulting from the accumulation of free fatty acids in non-adipose tissues which involves a series of pathological responses triggered after chronic exposure to high levels of fatty acids, severely detrimental to cellular homeostasis and viability. In brain, lipotoxicity affects both neurons and other cell types, notably astrocytes, leading to neurodegenerative processes, such as Alzheimer (AD) and Parkinson diseases (PD). In this study, we performed for the first time, a whole lipidomic characterization of Normal Human Astrocytes cultures exposed to toxic concentrations of palmitic acid and the protective compound tibolone, to establish and identify the set of potential metabolites that are modulated under these experimental treatments. The study covered 3843 features involved in the exo- and endo-metabolome extracts obtained from astrocytes with the mentioned treatments. Through multivariate statistical analysis such as PCA (principal component analysis), partial least squares (PLS-DA), clustering analysis, and machine learning enrichment analysis, it was possible to determine the specific metabolites that were affected by palmitic acid insult, such as phosphoethanolamines, phosphoserines phosphocholines and glycerophosphocholines, with their respective metabolic pathways impact. Moreover, our results suggest the importance of tibolone in the generation of neuroprotective metabolites by astrocytes and may be relevant to the development of neurodegenerative processes.

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One of the most common lipids in the human body is palmitic acid (PA), a saturated fatty acid with essential functions in brain cells. PA is used by cells as an energy source, besides being a precursor of signaling molecules and protein tilting across the membrane. Although PA plays physiological functions in the brain, its excessive accumulation leads to detrimental effects on brain cells, causing lipotoxicity. This mechanism involves the activation of toll-like receptors (TLR) and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) pathways, with the consequent release of pro-inflammatory cytokines, increased production of reactive oxygen species (ROS), endoplasmic reticulum (ER) stress, and autophagy impairment. Importantly, some of the cellular changes induced by PA lead to an augmented susceptibility to the development of Alzheimer's and Parkinson´s diseases. Considering the complexity of the response to PA and the intrinsic differences of the brain, in this review, we provide an overview of the molecular and cellular effects of PA on different brain cells and their possible relationships with neurodegenerative diseases (NDs). Furthermore, we propose the use of other fatty acids, such as oleic acid or linoleic acid, as potential therapeutic approaches against NDs, as these fatty acids can counteract PA's negative effects on cells.

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Objective: Angiopoietin-like protein 3(ANGPTL3) is an important regulator of lipoprotein metabolism in the fed state by inhibiting the enzyme lipoprotein lipase in oxidative tissues. However, the possible role of ANGPTL3 throughout gestation and its relationship with hormonal and biochemical variables are still unknown. The aim of this study was to determinate serum ANGPTL3 level in healthy non-pregnant women, during healthy and preeclamptic pregnancy and postpartum. Methods: Serum ANGPTL3 was analyzed by enzyme-linked immunosorbent assay (ELISA), in a prospective cohort of healthy pregnant women (n = 52) and women with mild preeclampsia (n = 21), and women at three months postpartum (n = 20) and healthy non-pregnant women (n = 20). The results obtained were correlated with biochemical, hormonal and anthropometric variables and insulin resistance indices. Results: Levels of ANGPTL3 were not different between the follicular and the luteal phases of the cycle in healthy non-pregnant women. There was a significant reduction in serum ANGPTL3 levels from the first to the third trimester in healthy pregnant women compared with healthy non-pregnant and postpartum women (p <0.01). ANGPTL3 levels do not differ significantly during the three trimesters of pregnancy neither in healthy women nor in preeclamptic women. The serum levels of ANGPTL3 in women who developed preeclampsia are not statistically different from those observed in healthy pregnant women in each trimester of pregnancy. A significant lineal positive correlation was observed between serum ANGPTL3 levels and triglyceride (P =0.0186, r =0.52), very low-density lipoprotein cholesterol (P =0.0224, r =0.50), and total cholesterol levels (P =0.0220, r =0.50) in healthy non-pregnant women (P 0.05). Besides, there were no significant correlations between serum ANGPTL3 and body mass index (BMI), high-density lipoprotein cholesterol, glucose, insulin, leptin, or HOMA-IR (P >0.05). Conclusions: We describe for the first time the profile of ANGPTL3 throughout pregnancy and postpartum as well as and discussed about explore their potential contribution interactions with lipoprotein metabolism throughout pregnancy and postpartum. Thus, low levels of ANGPTL3 during pregnancy might favor lipid uptake in oxidative tissues as the main maternal energy source, while may helping to preserve glucose for use by the fetus and placenta.

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Parkinson's Disease (PD) is a neurodegenerative disease, leading to motor and non-motor complications. Autonomic alterations, including gastrointestinal symptoms, precede motor defects and act as early warning signs. Chronic exposure to dietary, environmental heavy metals impacts the gastrointestinal system and host-associated microbiome, eventually affecting the central nervous system. The correlation between dysbiosis and PD suggests a functional and bidirectional communication between the gut and the brain. The bioaccumulation of metals promotes stress mechanisms by increasing reactive oxygen species, likely altering the bidirectional gut-brain link. To better understand the differing molecular mechanisms underlying PD, integrative modeling approaches are necessary to connect multifactorial perturbations in this heterogeneous disorder. By exploring the effects of gut microbiota modulation on dietary heavy metal exposure in relation to PD onset, the modification of the host-associated microbiome to mitigate neurological stress may be a future treatment option against neurodegeneration through bioremediation. The progressive movement towards a systems toxicology framework for precision medicine can uncover molecular mechanisms underlying PD onset such as metal regulation and microbial community interactions by developing predictive models to better understand PD etiology to identify options for novel treatments and beyond. Several methodologies recently addressed the complexity of this interaction from different perspectives; however, to date, a comprehensive review of these approaches is still lacking. Therefore, our main aim through this manuscript is to fill this gap in the scientific literature by reviewing recently published papers to address the surrounding questions regarding the underlying molecular mechanisms between metals, microbiota, and the gut-brain-axis, as well as the regulation of this system to prevent neurodegeneration.

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The growing importance of astrocytes in the field of neuroscience has led to a greater number of computational models devoted to the study of astrocytic functions and their metabolic interactions with neurons. The modeling of these interactions demands a combined understanding of brain physiology and the development of computational frameworks based on genomic-scale reconstructions, system biology, and dynamic models. These computational approaches have helped to highlight the neuroprotective mechanisms triggered by astrocytes and other glial cells, both under normal conditions and during neurodegenerative processes. In the present review, we evaluate some of the most relevant models of astrocyte metabolism, including genome-scale reconstructions and astrocyte-neuron interactions developed in the last few years. Additionally, we discuss novel strategies from the multi-omics perspective and computational models of other glial cell types that will increase our knowledge in brain metabolism and its association with neurodegenerative diseases.

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Joints enable the relative movement between the connected bones. The shape of the joint is important for the joint movements since they facilitate and smooth the relative displacement of the joint's parts. The process of how the joints obtain their final shape is yet not well understood. Former models have been developed in order to understand the joint morphogenesis leaning only on the mechanical environment; however, the obtained final anatomical shape does not match entirely with a realistic geometry. In this study, a computational model was developed with the aim of explaining how the morphogenesis of joints and shaping of ossification structures are achieved. For this model, both the mechanical and biochemical environments were considered. It was assumed that cartilage growth was controlled by cyclic hydrostatic stress and inhibited by octahedral shear stress. In addition, molecules such as PTHrP and Wnt promote chondrocyte proliferation and therefore cartilage growth. Moreover, the appearance of the primary and secondary ossification centers was also modeled, for which the osteogenic index and PTHrP-Ihh concentrations were taken into account. The obtained results from this model show a coherent final shape of an interphalangeal joint, which suggest that the mechanical and biochemical environments are crucial for the joint morphogenesis process.

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BACKGROUND: Phytophthora infestans is a plant pathogen that causes an important plant disease known as late blight in potato plants (Solanum tuberosum) and several other solanaceous hosts. This disease is the main factor affecting potato crop production worldwide. In spite of the importance of the disease, the molecular mechanisms underlying the compatibility between the pathogen and its hosts are still unknown. RESULTS: To explain the metabolic response of late blight, specifically photosynthesis inhibition in infected plants, we reconstructed a genome-scale metabolic network of the S. tuberosum leaf, PstM1. This metabolic network simulates the effect of this disease in the leaf metabolism. PstM1 accounts for 2751 genes, 1113 metabolic functions, 1773 gene-protein-reaction associations and 1938 metabolites involved in 2072 reactions. The optimization of the model for biomass synthesis maximization in three infection time points suggested a suppression of the photosynthetic capacity related to the decrease of metabolic flux in light reactions and carbon fixation reactions. In addition, a variation pattern in the flux of carboxylation to oxygenation reactions catalyzed by RuBisCO was also identified, likely to be associated to a defense response in the compatible interaction between P. infestans and S. tuberosum. CONCLUSIONS: In this work, we introduced simultaneously the first metabolic network of S. tuberosum and the first genome-scale metabolic model of the compatible interaction of a plant with P. infestans.

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This study aimed to characterize a commercial lamb finishing system using animals of undefined breed from production to slaughter by analyzing performance, carcass traits, yield of commercial cuts, and the quality and meat acceptance of different slaughter groups, as to evaluate whether this system provides the market with a standardized product. The lots were not homogeneous for yield of commercial cuts and performance and morphometric traits evaluated in vivo. The groups were heterogeneous to 75% of the 13 carcass traits evaluated, among them, hot and cold carcass weights, hot and cold carcass yields, carcass grade finishing and biological yield. There was also no uniformity for the proportion of non-carcass components, morphometry of carcass, visual appraisals, and loin traits. On the other hand, homogeneity was achieved in physico-chemical and sensory traits, except for hardness and proportion of saturated, monounsaturated and polyunsaturated fatty acids. We conclude that the commercial finishing system with the use of undefined crossbred lambs does not produce carcass and cuts standardized to the market.

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Loggerhead sea turtle Caretta caretta is widely distributed in the oceans of tropical and subtropical latitude. This turtle is an endangered species due to anthropic and natural factors that have decreased their population levels. In this study, RNA sequencing and de-novo assembly of genes expressed in blood were performed. The raw FASTQ files have been deposited on NCBI's SRA database with accession number SRX2629512. A total of 5.4 Gb raw sequence data were obtained, corresponding to 48,257,019 raw reads. Trinity pipeline was used to perform a de-novo assembly, we were able to identify 64,930 transcripts for female loggerhead turtle transcriptome with an N50 of 1131 bp. The obtained transcriptome data will be useful for further studies of the physiology, biochemistry and evolution in this species.