Influence of seed varieties and harvesting regimes on growth indices, yields and nutritional values of hydroponics maize fodder

This study was conducted to assess the influence of seed varieties and harvesting regimes on growth indices, yields and nutritional values of hydroponics maize fodder in other to ensure sustainable fodder for livestock production. The experiment was 2 x 3 factorial scheme fitted into a completely randomized design (CRD), comprising of two (2) varieties of maize seeds (OBA 98 and Local white maize) and three (3) harvesting regimes (6th, 8th and 10th day). Growth indices, yields, nutritional values were assessed. Results shows a significant (P<0.05) effects of maize seed varieties and harvesting regimes on the growth indices, yields, nutritional values. The OBA 98 maize hydroponic fodder (OHF) had the highest (P<0.05) agronomic indices, yields, nutrients (CP (16.36 %), EE (4.41), CF (7.23), ash (7.13) and NFE (64.88)) than Local maize hydroponic fodder (LHF). The highest significant (P<0.05) contents of the nutrients was observed at 10th day harvesting, while least (P<0.05) was obtained at 6th day harvesting except NFE. The OHF had higher (P<0.05) neutral detergent fibre (NDF), acid detergent fibre (ADF), acid detergent lignin (ADL) and hemicellulose (HEM). The cellulose (CEL) were similar (P>0.05) in OHF and LHF. Similar (P>0.05) ADL, HEM and CEL were recorded across the harvesting regimes. The OHF and 10th day harvesting regime had highest (P<0.05) mineral, tannin, phytate and oxalate contents. Conclusively, OHF had superior growth indices, yields and nutritional values, 10th day harvesting was better than 6th and 8th day. Hence, OBA 98 seed variety and 10th day harvesting regime is recommended for better hydroponics maize fodder production

Variabilidade e tendencias interanuais no fitoplancto mariño das costas de Galicia

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Serum Uric Acid as a Predictor for Development of Diabetic Nephropathy in Type 1 Diabetes: An Inception Cohort Study

OBJECTIVE—Experimental and clinical studies have suggested that uric acid may contribute to the development of hypertension and kidney disease. Whether uric acid has a causal role in the development of diabetic nephropathy is not known. The objec-tive of the present study is to evaluate uric acid as a predictor of persistent micro- and macroalbuminuria. RESEARCH DESIGN AND METHODS—This prospective ob-servational follow-up study consisted of an inception cohort of 277 patients followed from onset of type 1 diabetes. Of these, 270 patients had blood samples taken at baseline. In seven cases, uric acid could not be determined; therefore, 263 patients (156 men) were available for analysis. Uric acid was measured 3 years after onset of diabetes and before any patient developed microalbuminuria. RESULTS—During a median follow-up of 18.1 years (rang

Capítulo 7. Biomasa y producción primaria.

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Lack of increases in methylation at three CpG-rich genomic loci in non-mitotic adult tissues during aging

<p>Abstract</p> <p>Background</p> <p>Cell division occurs during normal human development and aging. Despite the likely importance of cell division to human pathology, it has been difficult to infer somatic cell mitotic ages (total numbers of divisions since the zygote) because direct counting of lifetime numbers of divisions is currently impractical. Here we attempt to infer relative mitotic ages with a molecular clock hypothesis. Somatic genomes may record their mitotic ages because greater numbers of replication errors should accumulate after greater numbers of divisions. Mitotic ages will vary between cell types if they divide at different times and rates.</p> <p>Methods</p> <p>Age-related increases in DNA methylation at specific CpG sites (termed "epigenetic molecular clocks") have been previously observed in mitotic human epithelium like the intestines and endometrium. These CpG rich sequences or "tags" start unmethylated and potentially changes in methylation during development and aging represent replication errors. To help distinguish between mitotic versus time-associated changes, DNA methylation tag patterns at 8–20 CpGs within three different genes, two on autosomes and one on the X-chromosome were measured by bisulfite sequencing from heart, brain, kidney and liver of autopsies from 21 individuals of different ages.</p> <p>Results</p> <p>Levels of DNA methylation were significantly greater in adult compared to fetal or newborn tissues for two of the three examined tags. Consistent with the relative absence of cell division in these adult tissues, there were no significant increases in tag methylation after infancy.</p> <p>Conclusion</p> <p>Many somatic methylation changes at certain CpG rich regions or tags appear to represent replication errors because this methylation increases with chronological age in mitotic epithelium but not in non-mitotic organs. Tag methylation accumulates differently in different tissues, consistent with their expected genealogies and mitotic ages. Although further studies are necessary, these results suggest numbers of divisions and ancestry are at least partially recorded by epigenetic replication errors within somatic cell genomes.</p

Parathyroidectomy and survival in a cohort of Italian dialysis patients: results of a multicenter, observational, prospective study

Background: Severe secondary hyperparathyroidism (SHPT)&nbsp;is associated with mortality in end stage kidney disease (ESKD). Parathyroidectomy (PTX) becomes necessary when medical therapy fails, thus highlighting the interest to compare biochemical and clinical outcomes of patients receiving either medical treatment or surgery. Methods: We aimed to compare overall survival and biochemical control of hemodialysis patients with severe hyperparathyroidism, treated by surgery or medical&nbsp;therapy&nbsp;followed-up for 36&nbsp;months.&nbsp;Inclusion criteria were age older than 18&nbsp;years, renal failure requiring dialysis treatment (hemodialysis or peritoneal dialysis) and ability to sign the consent form. A control group of&nbsp;418 patients treated in the same centers,&nbsp;who did not undergo parathyroidectomy was selected after matching&nbsp;for&nbsp;age, sex, and dialysis vintage. Results: From 82 Dialysis units in Italy, we prospectively collected data of 257 prevalent patients&nbsp;who underwent parathyroidectomy (age&nbsp;58.2 ± 12.8 years; M/F: 44%/56%, dialysis&nbsp;vintage: 15.5 ± 8.4 years) and of 418 control patients who did not undergo parathyroidectomy (age&nbsp;60.3 ± 14.4 years; M/F 44%/56%; dialysis vintage 11.2 ± 7.6 y). The survival rate was higher in the group&nbsp;that underwent&nbsp;parathyroidectomy (Kaplan–Meier log rank test = 0.002). Univariable analysis (HR 0.556, CI: 0.387–0.800, p = 0.002) and multivariable analysis (HR 0.671, CI:0.465–0.970, p = 0.034), identified parathyroidectomy as a&nbsp;protective factor of overall survival. The prevalence of patients at KDOQI targets for PTH was lower in patients&nbsp;who underwent parathyroidectomy&nbsp;compared to controls (PTX vs non-PTX: PTH &lt; 150&nbsp;pg/ml: 59% vs 21%, p = 0.001; PTH at target: 18% vs 37% p = 0.001; PTH &gt; 300&nbsp;pg/ml 23% vs 42% p = 0.001). The control group received more intensive medical treatment&nbsp;with higher prevalence of vitamin D (65% vs 41%, p = 0.0001), calcimimetics (34% vs 14%, p = 0.0001) and phosphate binders (77% vs 66%,&nbsp;p = 0.002). Conclusions: Our data suggest that parathyroidectomy is associated with survival rate&nbsp;at 36 months, independently of biochemical control. Lower exposure to high PTH levels could represent an advantage in the long term. Graphical abstract: [Figure not available: see fulltext.]

Metabolomic Analysis in Severe Childhood Pneumonia in The Gambia, West Africa: Findings from a Pilot Study

Pneumonia remains the leading cause of death in young children globally and improved diagnostics are needed to better identify cases and reduce case fatality. Metabolomics, a rapidly evolving field aimed at characterizing metabolites in biofluids, has the potential to improve diagnostics in a range of diseases. The objective of this pilot study is to apply metabolomic analysis to childhood pneumonia to explore its potential to improve pneumonia diagnosis in a high-burden setting. and Random Forests (RF). ‘Unsupervised’ (blinded) data were analyzed by Principal Component Analysis (PCA), while ‘supervised’ (unblinded) analysis was by Partial Least Squares-Discriminant Analysis (PLS-DA) and Orthogonal Projection to Latent Structures (OPLS). Potential markers were extracted from S-plots constructed following analysis with OPLS, and markers were chosen based on their contribution to the variation and correlation within the data set. The dataset was additionally analyzed with the machine-learning algorithm RF in order to address issues of model overfitting and markers were selected based on their variable importance ranking. Unsupervised PCA analysis revealed good separation of pneumonia and control groups, with even clearer separation of the groups with PLS-DA and OPLS analysis. Statistically significant differences (p<0.05) between groups were seen with the following metabolites: uric acid, hypoxanthine and glutamic acid were higher in plasma from cases, while L-tryptophan and adenosine-5′-diphosphate (ADP) were lower; uric acid and L-histidine were lower in urine from cases. The key limitation of this study is its small size.Metabolomic analysis clearly distinguished severe pneumonia patients from community controls. The metabolites identified are important for the host response to infection through antioxidant, inflammatory and antimicrobial pathways, and energy metabolism. Larger studies are needed to determine whether these findings are pneumonia-specific and to distinguish organism-specific responses. Metabolomics has considerable potential to improve diagnostics for childhood pneumonia

A genome-wide association study for survival from a multi-centre European study identified variants associated with COVID-19 risk of death

The clinical manifestations of SARS-CoV-2 infection vary widely among patients, from asymptomatic to life-threatening. Host genetics is one of the factors that contributes to this variability as previously reported by the COVID-19 Host Genetics Initiative (HGI), which identified sixteen loci associated with COVID-19 severity. Herein, we investigated the genetic determinants of COVID-19 mortality, by performing a case-only genome-wide survival analysis, 60&nbsp;days after infection, of 3904 COVID-19 patients from the GEN-COVID and other European series (EGAS00001005304 study of the COVID-19 HGI). Using imputed genotype data, we carried out a survival analysis using the Cox model adjusted for age, age2, sex, series, time of infection, and the first ten principal components. We observed a genome-wide significant (P-value &lt; 5.0 × 10−8) association of the rs117011822 variant, on chromosome 11, of rs7208524 on chromosome 17, approaching the genome-wide threshold (P-value = 5.19 × 10−8). A total of 113 variants were associated with survival at P-value &lt; 1.0 × 10−5 and most of them regulated the expression of genes involved in immune response (e.g., CD300 and KLR genes), or in lung repair and function (e.g., FGF19 and CDH13). Overall, our results suggest that germline variants may modulate COVID-19 risk of death, possibly through the regulation of gene expression in immune response and lung function pathways

Host genetics and COVID-19 severity: increasing the accuracy of latest severity scores by Boolean quantum features

The impact of common and rare variants in COVID-19 host genetics has been widely studied. In particular, in Fallerini et al. (Human genetics, 2022, 141, 147–173), common and rare variants were used to define an interpretable machine learning model for predicting COVID-19 severity. First, variants were converted into sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. After that, the Boolean features, selected by these logistic models, were combined into an Integrated PolyGenic Score (IPGS), which offers a very simple description of the contribution of host genetics in COVID-19 severity. IPGS leads to an accuracy of 55%–60% on different cohorts, and, after a logistic regression with both IPGS and age as inputs, it leads to an accuracy of 75%. The goal of this paper is to improve the previous results, using not only the most informative Boolean features with respect to the genetic bases of severity but also the information on host organs involved in the disease. In this study, we generalize the IPGS adding a statistical weight for each organ, through the transformation of Boolean features into “Boolean quantum features,” inspired by quantum mechanics. The organ coefficients were set via the application of the genetic algorithm PyGAD, and, after that, we defined two new integrated polygenic scores ((Formula presented.) and (Formula presented.)). By applying a logistic regression with both IPGS, ((Formula presented.) (or indifferently (Formula presented.)) and age as inputs, we reached an accuracy of 84%–86%, thus improving the results previously shown in Fallerini et al. (Human genetics, 2022, 141, 147–173) by a factor of 10%

Ultra-rare RTEL1 gene variants associate with acute severity of COVID-19 and evolution to pulmonary fibrosis as a specific long COVID disorder

Background: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a novel coronavirus that caused an ongoing pandemic of a pathology termed Coronavirus Disease 19 (COVID-19). Several studies reported that both COVID-19 and RTEL1 variants are associated with shorter telomere length, but a direct association between the two is not generally acknowledged. Here we demonstrate that up to 8.6% of severe COVID-19 patients bear RTEL1 ultra-rare variants, and show how this subgroup can be recognized. Methods: A cohort of 2246 SARS-CoV-2-positive subjects, collected within the GEN-COVID Multicenter study, was used in this work. Whole exome sequencing analysis was performed using the NovaSeq6000 System, and machine learning methods were used for candidate gene selection of severity. A nested study, comparing severely affected patients bearing or not variants in the selected gene, was used for the characterisation of specific clinical features connected to variants in both acute and post-acute phases. Results: Our GEN-COVID cohort revealed a total of 151 patients carrying at least one RTEL1 ultra-rare variant, which was selected as a specific acute severity feature. From a clinical point of view, these patients showed higher liver function indices, as well as increased CRP and inflammatory markers, such as IL-6. Moreover, compared to control subjects, they present autoimmune disorders more frequently. Finally, their decreased diffusion lung capacity for carbon monoxide after six months of COVID-19 suggests that RTEL1 variants can contribute to the development of SARS-CoV-2-elicited lung fibrosis. Conclusion: RTEL1 ultra-rare variants can be considered as a predictive marker of COVID-19 severity, as well as a marker of pathological evolution in pulmonary fibrosis in the post-COVID phase. This notion can be used for a rapid screening in hospitalized infected people, for vaccine prioritization, and appropriate follow-up assessment for subjects at risk. Trial Registration NCT04549831 (www.clinicaltrial.org