Biomass stocks in Ghanaian cocoa ecosystems: the effects of region, management and stand age of cocoa trees

Determination of biomass produced in cocoa ecosystems is an important step towards quantifying the carbon sequestration potential of cocoa production systems. This study provides data on the biomass of cocoa systems being influenced by management, cocoa stand ages and region. Eight cocoa farms were sampled on the basis of three variables: region (Eastern, Western region), shade management (shaded, unshaded) and stand age (15 years). Allometric equations (R2 > 0.94) were developed to estimate the biomass of live cocoa trees, while the biomass of non-cocoa trees was estimated using an existing equation by FAO. Generally, biomass stocks were higher in the Eastern than Western region, shaded than unshaded, and in stands >15 years than those <15 years. The total cocoa ecosystem biomass range was, 48.1 ± 6.5 to 101.6 ± 12.6 Mg/ha. The high biomass estimates reveals a potential of system to restore appreciable biomass losses resulting from deforestation and forest degradation in Ghana

Essential guidelines for computational method benchmarking

In computational biology and other sciences, researchers are frequently faced with a choice between several computational methods for performing data analyses. Benchmarking studies aim to rigorously compare the performance of different methods using well-characterized benchmark datasets, to determine the strengths of each method or to provide recommendations regarding suitable choices of methods for an analysis. However, benchmarking studies must be carefully designed and implemented to provide accurate, unbiased, and informative results. Here, we summarize key practical guidelines and recommendations for performing high-quality benchmarking analyses, based on our experiences in computational biology.Comment: Minor update

Essential guidelines for computational method benchmarking

In computational biology and other sciences, researchers are frequently faced with a choice between several computational methods for performing data analyses. Benchmarking studies aim to rigorously compare the performance of different methods using well-characterized benchmark datasets, to determine the strengths of each method or to provide recommendations regarding suitable choices of methods for an analysis. However, benchmarking studies must be carefully designed and implemented to provide accurate, unbiased, and informative results. Here, we summarize key practical guidelines and recommendations for performing high-quality benchmarking analyses, based on our experiences in computational biology

Leaf Litter Decomposition and Mitigation of CO₂ Emissions in Cocoa Ecosystems

Studies simultaneously quantifying litter weight losses and rates of CO2-C evolved are few, though essential for accurate estimates of forest carbon budgets. A 120-day dry matter loss and a 130-day carbon emission experiments were concurrently conducted at the soil laboratory of the University of Reading, UK. Leaf litters of tree species comprising cocoa (Theobroma cacao), Newbouldia laevis (dominant shade tree in Eastern region (ER)) and Persea americana (dominant shade tree in Western region (WR)) of Ghana were incubated using a single tree leaf litter and/or a 1:1 mixed species leaf litters to determine and predict the litter decomposition and C dynamics in cocoa systems with or without the shade trees. Decomposition and C release trends in the ER systems followed: shade > mixed cocoa-shade = predicted mixed litter > cocoa; and in the WR, the order was: cocoa = mixed cocoa-shade > predicted mixed > shade. Differences between released C estimated from litter weight loss and CO2-C evolution measurement methods were not consistent. Regression analysis revealed a strong (R2 = 0.71) relationship between loss of litter C and the CO2-C evolution during litter decomposition. The large C pool for shaded cocoa systems indicates the potential to store more C and thus, its promotion could play a significant role in atmospheric CO2 mitigations

Controllability analysis to identify manipulated variables for a glycosylation control strategy

N-linked glycans affect important end-use characteristics such as the bioactivity and efficacy of many therapeutic proteins, (including monoclonal antibodies), in vivo. However, achieving a precise glycan distribution during manufacturing can be challenging because glycosylation is a non-template driven cellular process, with the potential for significant uncontrolled variability in glycan distributions. As important as the glycan distribution is to the end-use performance of biopharmaceuticals, to date, no strategy exists for controlling glycosylation on-line. In this work, we present a controllability analysis for glycosylation as a first step toward establishing an online glycosylation control strategy. We first assessed the theoretically achievable extent to which the very complex process of glycosylation is controllable. Once theoretic controllability was established, we performed experiments to identify appropriate manipulated variables that can be used to direct the glycan distribution of an IgG1 to a desired state. We found that bioreactor process variables such as glucose and glutamine media concentration, temperature, pH, agitation rate, and dissolved oxygen (DO) had significant but small effects on the relative percentage of various glycans. This indicated that the IgG1 glycan distribution was generally robust to even large perturbations of typical bioreactor variables. Conversely, we found that media supplementation with manganese, galactose, and ammonia had significant and large effects on certain glycans. From this work, we determined that manganese can be used as a manipulated variable to increase the relative abundance of M5 and decrease FA2 glycans simultaneously, and galactose can be used as a manipulated variable to increase the relative abundance of FA2G1 and decrease FA2 and A2 simultaneously. As a final test, we applied machine learning algorithms to validate and enrich these findings from a data-centric point of view. The machine learning algorithms provided an avenue to discover unknown relationships and patterns that refined our findings and provided a framework to explore more variables

High Mass Triple Systems: The Classical Cepheid Y Car

We have obtained an HST STIS ultraviolet high dispersion Echelle mode spectrum the binary companion of the double mode classical Cepheid Y Car. The velocity measured for the hot companion from this spectrum is very different from reasonable predictions for binary motion, implying that the companion is itself a short period binary. The measured velocity changed by 7 km/ s during the 4 days between two segments of the observation confirming this interpretation. We summarize "binary" Cepheids which are in fact members of triple system and find at least 44% are triples. The summary of information on Cepheids with orbits makes it likely that the fraction is under-estimated.Comment: accepted by A

Rho GTPase gene expression and breast cancer risk:A Mendelian randomization analysis

The Rho GTPase family consists of 20 genes encoding intracellular signalling proteins that influence cytoskeletal dynamics, cell migration and cell cycle progression. They are implicated in breast cancer progression but their role in breast cancer aetiology is unknown. As aberrant Rho GTPase activity could be associated with breast cancer, we aimed to determine the potential for a causal role of Rho GTPase gene expression in breast cancer risk, using two-sample Mendelian randomization (MR). MR was undertaken in 122,977 breast cancer cases and 105,974 controls, including 69,501 estrogen receptor positive (ER+) cases and 105,974 controls, and 21,468 ER negative (ER−) cases and 105,974 controls. Single nucleotide polymorphisms (SNPs) underlying expression quantitative trait loci (eQTLs) obtained from normal breast tissue, breast cancer tissue and blood were used as genetic instruments for Rho GTPase expression. As a sensitivity analysis, we undertook co-localisation to examine whether findings reflected shared causal variants or genomic confounding. We identified genetic instruments for 14 of the 20 human Rho GTPases. Using eQTLs obtained from normal breast tissue and normal blood, we identified evidence of a causal role of RHOD in overall and ER+ breast cancers (overall breast cancer: odds ratio (OR) per standard deviation (SD) increase in expression level 1.06; (95% confidence interval (CI) 1.03, 1.09; P = 5.65 × 10(–5)) and OR 1.22 (95% CI 1.11, 1.35; P = 5.22 × 10(–5)) in normal breast tissue and blood respectively). There was a consistent direction of association for ER− breast cancer, although the effect-estimate was imprecisely estimated. Using eQTLs from breast cancer tissue and normal blood there was some evidence that CDC42 was negatively associated with overall and ER + breast cancer risk. The evidence from colocalization analyses strongly supported our MR results particularly for RHOD. Our study suggests a potential causal role of increased RHOD gene expression, and, although the evidence is weaker, a potential protective role for CDC42 gene expression, in overall and ER+ breast cancers. These finding warrant validation in independent samples and further biological investigation to assess whether they may be suitable targets for drug targeting

Bull terrier hereditary nephritis: A model for autosomal dominant Alport syndrome

Bull terrier hereditary nephritis: A model for autosomal dominant Alport syndrome. Bull terrier hereditary nephritis is inherited as an autosomal dominant disease and causes renal failure at variable ages in affected dogs. The aims of this study were to compare the clinical, ultrastructural and immunohistochemical features of bull terrier hereditary nephritis with the characteristics of the human forms of Alport syndrome. Many animals with bull terrier hereditary nephritis have hematuria, and some have anterior lenticonus. However, deafness is not associated with the renal disease, and affected dogs do not have the large platelets that are occasionally seen in patients with autosomal Alport syndrome. The glomerular capillary basement membrane (GCBM) in affected bull terriers has an identical ultrastructural appearance to that seen in X-linked Alport syndrome, with lamellations and intramembranous electron-dense deposits. However, both the Goodpasture and the Alport antigens, which represent parts of the alpha 3(IV) and alpha 5 (IV) collagen chains, respectively, are present in the GCBM of affected dogs. Bull terrier hereditary nephritis represents an animal model for autosomal dominant Alport syndrome, and can be used to further examine how genetic mutations affect a basement membrane protein and the corresponding membrane structure

Measurement of low‐density lipoprotein cholesterol levels in primary and secondary prevention patients: Insights from the PALM registry

Background The 2013 American College of Cardiology/American Heart Association Guideline on the Treatment of Blood Cholesterol to Reduce Atherosclerotic Cardiovascular Risk in Adults recommended testing low-density lipoprotein cholesterol ( LDL -C) to identify untreated patients with LDL -C ≥190 mg/dL, assess lipid-lowering therapy adherence, and consider nonstatin therapy. We sought to determine whether clinician lipid testing practices were consistent with these guidelines. Methods and Results The PALM (Patient and Provider Assessment of Lipid Management) registry enrolled primary and secondary prevention patients from 140 US cardiology, endocrinology, and primary care offices in 2015 and captured demographic data, lipid treatment history, and the highest LDL -C level in the past 2 years. Core laboratory lipid levels were drawn at enrollment. Among 7627 patients, 2787 (36.5%) had no LDL -C levels measured in the 2 years before enrollment. Patients without chart-documented LDL -C levels were more often women, nonwhite, uninsured, and non-college graduates (all P\u3c0.01). Patients without prior lipid testing were less likely to receive statin treatment (72.6% versus 76.0%; P=0.0034), a high-intensity statin (21.5% versus 24.3%; P=0.016), nonstatin lipid-lowering therapy (24.8% versus 27.3%; P=0.037), and had higher core laboratory LDL -C levels at enrollment (median 97 versus 92 mg/dL; P\u3c0.0001) than patients with prior LDL -C testing. Of 166 individuals with core laboratory LDL -C levels ≥190 mg/dL, 36.1% had no LDL -C measurement in the prior 2 years, and 57.2% were not on a statin at the time of enrollment. Conclusions In routine clinical practice, LDL -C testing is associated with higher-intensity lipid-lowering treatment and lower achieved LDL -C level