Enhancement of biogas potential of primary sludge by co-digestion with cow manure and brewery sludge

Anaerobic digestion (AD) has long been used to treat different types of organic wastes especially in the developed world. However, organic wastes are still more often considered as a waste instead of a resource in the developing world, which contributes to environmental pollution arising from their disposal. This study has been conducted at Bugolobi Sewage Treatment Plant (BSTP), where two organic wastes, cow manure and brewery sludge were co-digested with primary sludge in different proportions. This study was done in lab-scale reactors at mesophilic temperature and sludge retention time of 20 d. The main objective was to evaluate the biodegradability of primary sludge generated at BSTP, Kampala, Uganda and enhance its ability of biogas production. When the brewery sludge was added to primary STP sludge at all proportions, the biogas production rate increased by a factor of 3. This was significantly (p<0.001) higher than observed gas yield (337 +/- 18 mL/(L.d)) in the control treatment containing (only STP sludge). Co-digesting STP sludge with cow manure did not show different results compared to the control treatment. In conclusion, Bugolobi STP sludge is poorly anaerobically degradable with low biogas production but co-digestion with brewery sludge enhanced the biogas production rate, while co-digestion with cow manure was not beneficial

Tick parasitism classification from noisy medical records

Much of the health information in the medical domain comes in the form of clinical narratives. The rich semantic information contained in these notes can be modeled to make inferences that assist the decision making process for medical practitioners, which is particularly important under time and resource constraints. However, the creation of such assistive tools is made difficult given the ubiquity of misspellings, unsegmented words and morphologically complex or rare medical terms. This reduces the coverage of vocabulary terms present in commonly used pretrained distributed word representations that are passed as input to parametric models that makes such predictions. This paper presents an ensemble architecture that combines indomain and general word embeddings to overcome these challenges, showing best performance on a binary classification task when compared to various other baselines. We demonstrate our approach in the context of the veterinary domain for the task of identifying tick parasitism from small animals. The best model shows 84.29% test accuracy, showing some improvement over models, which only use pretrained embeddings that are not specifically trained for the medical sub-domain of interest

Characteristics associated with quality of life among people with drug-resistant epilepsy

Quality of Life (QoL) is the preferred outcome in non-pharmacological trials, but there is little UK population evidence of QoL in epilepsy. In advance of evaluating an epilepsy self-management course we aimed to describe, among UK participants, what clinical and psycho-social characteristics are associated with QoL. We recruited 404 adults attending specialist clinics, with at least two seizures in the prior year and measured their self-reported seizure frequency, co-morbidity, psychological distress, social characteristics, including self-mastery and stigma, and epilepsy-specific QoL (QOLIE-31-P). Mean age was 42 years, 54% were female, and 75% white. Median time since diagnosis was 18 years, and 69% experienced ≥10 seizures in the prior year. Nearly half (46%) reported additional medical or psychiatric conditions, 54% reported current anxiety and 28% reported current depression symptoms at borderline or case level, with 63% reporting felt stigma. While a maximum QOLIE-31-P score is 100, participants’ mean score was 66, with a wide range (25–99). In order of large to small magnitude: depression, low self-mastery, anxiety, felt stigma, a history of medical and psychiatric comorbidity, low self-reported medication adherence, and greater seizure frequency were associated with low QOLIE-31-P scores. Despite specialist care, UK people with epilepsy and persistent seizures experience low QoL. If QoL is the main outcome in epilepsy trials, developing and evaluating ways to reduce psychological and social disadvantage are likely to be of primary importance. Educational courses may not change QoL, but be one component supporting self-management for people with long-term conditions, like epilepsy

Host allometry influences the evolution of parasite host-generalism: theory and meta-analysis

Parasites vary widely in the diversity of hosts they infect: some parasite species are specialists - infecting just a single host species, while others are generalists, capable of infecting many. Understanding the factors that drive parasite host-generalism is of basic biological interest, but also directly relevant to predicting disease emergence in new host species, identifying parasites that are likely to have unidentified additional hosts, and assessing transmission risk. Here, we use mathematical models to investigate how variation in host body size and environmental temperature affect the evolution of parasite host-generalism. We predict that parasites are more likely to evolve a generalist strategy when hosts are large-bodied, when variation in host body size is large, and in cooler environments. We then explore these predictions using a newly updated database of over 20,000 fish-macroparasite associations. Within the database we see some evidence supporting these predictions, but also highlight mismatches between theory and data. By combining these two approaches, we establish a theoretical basis for interpreting empirical data on parasites' host specificity and identify key areas for future work that will help untangle the drivers of parasite host-generalism

Integrating Sequencing Technologies in Personal Genomics: Optimal Low Cost Reconstruction of Structural Variants

The goal of human genome re-sequencing is obtaining an accurate assembly of an individual's genome. Recently, there has been great excitement in the development of many technologies for this (e.g. medium and short read sequencing from companies such as 454 and SOLiD, and high-density oligo-arrays from Affymetrix and NimbelGen), with even more expected to appear. The costs and sensitivities of these technologies differ considerably from each other. As an important goal of personal genomics is to reduce the cost of re-sequencing to an affordable point, it is worthwhile to consider optimally integrating technologies. Here, we build a simulation toolbox that will help us optimally combine different technologies for genome re-sequencing, especially in reconstructing large structural variants (SVs). SV reconstruction is considered the most challenging step in human genome re-sequencing. (It is sometimes even harder than de novo assembly of small genomes because of the duplications and repetitive sequences in the human genome.) To this end, we formulate canonical problems that are representative of issues in reconstruction and are of small enough scale to be computationally tractable and simulatable. Using semi-realistic simulations, we show how we can combine different technologies to optimally solve the assembly at low cost. With mapability maps, our simulations efficiently handle the inhomogeneous repeat-containing structure of the human genome and the computational complexity of practical assembly algorithms. They quantitatively show how combining different read lengths is more cost-effective than using one length, how an optimal mixed sequencing strategy for reconstructing large novel SVs usually also gives accurate detection of SNPs/indels, how paired-end reads can improve reconstruction efficiency, and how adding in arrays is more efficient than just sequencing for disentangling some complex SVs. Our strategy should facilitate the sequencing of human genomes at maximum accuracy and low cost

Physicochemical property distributions for accurate and rapid pairwise protein homology detection

<p>Abstract</p> <p>Background</p> <p>The challenge of remote homology detection is that many evolutionarily related sequences have very little similarity at the amino acid level. Kernel-based discriminative methods, such as support vector machines (SVMs), that use vector representations of sequences derived from sequence properties have been shown to have superior accuracy when compared to traditional approaches for the task of remote homology detection.</p> <p>Results</p> <p>We introduce a new method for feature vector representation based on the physicochemical properties of the primary protein sequence. A distribution of physicochemical property scores are assembled from 4-mers of the sequence and normalized based on the null distribution of the property over all possible 4-mers. With this approach there is little computational cost associated with the transformation of the protein into feature space, and overall performance in terms of remote homology detection is comparable with current state-of-the-art methods. We demonstrate that the features can be used for the task of pairwise remote homology detection with improved accuracy versus sequence-based methods such as BLAST and other feature-based methods of similar computational cost.</p> <p>Conclusions</p> <p>A protein feature method based on physicochemical properties is a viable approach for extracting features in a computationally inexpensive manner while retaining the sensitivity of SVM protein homology detection. Furthermore, identifying features that can be used for generic pairwise homology detection in lieu of family-based homology detection is important for applications such as large database searches and comparative genomics.</p