Radiation-cooled Dew Water Condensers Studied by Computational Fluid Dynamic (CFD)

Harvesting condensed atmospheric vapour as dew water can be an alternative or complementary potable water resource in specific arid or insular areas. Such radiation-cooled condensing devices use already existing flat surfaces (roofs) or innovative structures with more complex shapes to enhance the dew yield. The Computational Fluid Dynamic - CFD - software PHOENICS has been programmed and applied to such radiation cooled condensers. For this purpose, the sky radiation is previously integrated and averaged for each structure. The radiative balance is then included in the CFD simulation tool to compare the efficiency of the different structures under various meteorological parameters, for complex or simple shapes and at various scales. It has been used to precise different structures before construction. (1) a 7.32 m^2 funnel shape was studied; a 30 degree tilted angle (60 degree cone half-angle) was computed to be the best compromise for funnel cooling. Compared to a 1 m^2 flat condenser, the cooling efficiency was expected to be improved by 40%. Seventeen months measurements in outdoor tests presented a 138 % increased dew yield as compared to the 1 m^2 flat condenser. (2) The simulation results for 5 various condenser shapes were also compared with experimental measurement on corresponding pilots systems: 0.16 m^2 flat planar condenser, 1 m^2 and 30 degree tilted planar condenser, 30 m^2 and 30 degree tilted planar condenser, 255 m^2 multi ridges, a preliminary construction of a large scale dew plant being implemented in the Kutch area (Gujarat, India)

Magnitude and Causes of Maternal Deaths at Health Facilities in Eritrea in 2007.

Objective: To measure the level of maternal mortality in health facilities as well as the magnitude and proportion of obstetric complications in health facilities in Eritrea. Methods: The study was a cross-sectional survey of all hospitals and health centers in Eritrea and a random sample of around a third of health stations. Medical records of all patients who encountered obstetric complications in 2007 were reviewed. Findings: The main causes of obstetric complications among hospital admissions in 2007 were abortion complications (45.6%), obstructed/prolonged labor (18.4%), abnormal fetal presentation (10.3%) and preeclampsia/ eclampsia (7.7%). The number of maternal deaths at facilities was relatively small. Out of the 6,315 patients who were admitted for obstetric complications in 2007, 41 were classified as maternal deaths. The leading causes of maternal deaths included pre-eclampsia/ eclampsia in 22.0 percent of the cases, abortion complications in 19.5 percent of the cases and postpartum sepsis in 17.1 percent of the cases and post-partum hemorrhage in 14.6 percent of cases. The case-fatality rate for obstetric complications was low at 0.75 percent. The majority of maternal deaths (65 percent) occurred in the post-partum period, while 32 percent occurred during the ante-partum period, and 3 percent during intra-partum or during labor or delivery Conclusion: Over all it can be concluded that the Eritrean health system is performing well with the current demand for services. The issue of abortion requires special attention because it is the leading obstetric complication, which accounts for 46 percent of maternal complications and is responsible for one fifth of maternal deaths. Although the case fatality rate of all obstetric complications combined is not high (0.75 percent), the cause specific case fatality rates for the leading causes of maternal mortality was high Keywords: Maternal mortality, obstetric complications, abortion, case fatality rat

CLINICAL PROFILE, PRESCRIPTION PATTERNS, AND ADVERSE DRUG REACTIONS IN PATIENTS WITH VITILIGO: A PROSPECTIVE STUDY

Objectives: The objectives of the study were to assess clinical profile (age of onset, age of presentation, gender, site of involvement, severity (stage), type of vitiligo, triggering factors, and associated diseases), prescription patterns (monotherapy, combination therapy, oral, topical, and therapeutic categories of drugs prescribed) and to monitor and report adverse drug reactions (based on World Health Organization [WHO] causality assessment scale) in vitiligo patients. Methods: A hospital-based prospective observational study was carried out by evaluating and assessing the clinical profile and prescription patterns of 85 patients who attended dermatology venereology and leprosy (DVL) outpatient department at Sri Padmavathi Medical College for Women, SVIMS, Tirupati, over a period of 6 months from June 2019 to December 2019. Results: In our study, forty four (51.77%) patients were female, vitiligo vulgaris is the most common morphological type observed in twenty seven (31.76%) patients. 31–50 years was the predominant age group. The mean age of onset and presentation was 38.35 (standard deviation of 18.37) and 43.27 (standard deviation of 17.96) years, respectively. Forty-one (48.23%) patients were having Stage 1 vitiligo. Fifty (58.85%) patients were having vitiligo at more than 1 site. Twelve (14.11%) patients were having a positive family history of vitiligo. Thirty-seven (43.53%) patients had triggering factors. Associated diseases were found in thirty (35%) patients. Combination therapy was given to sixty one (71.77%) patients. Topical medications were given to fifty two (61.18%) patients. During the study, we did not have a single patient complaining of any adverse drug reaction. Conclusion: Longer the time after appearance of vitiligo, lesser the number of patients attending follow-up. If vitiligo is diagnosed at the earliest stage, more are the chances for complete repigmentation. Patients with a poor economic background are less bothered about their skin condition and are not using medications properly

Сучасні досягнення розвитку наукових досліджень з отримання in vitro ембріонів овець

New literature data on research aimed at improving the in vitro production of sheep embryos presents in the article. An analysis of the achievements of scientists from different countries to increase the efficiency of the main stages of embryo production in vitro: maturation of oocytes in vitro, their in vitro fertilization and in vitro embryo culture. In the literature experience has shown that the efficiency of oocyte maturation in vitro is significantly influenced by the experience and qualifications of scientists, the age of the egg donor, the improvement of the environment by adding roscovitin to inhibit meiosis, α-linolenic acid, cerium dioxide nanoparticles (CeO2 NPs) and sericin to accelerate nuclear maturation and increase the number of oocytes of the second meiotic metaphase (MII). The main factors influencing the effectiveness of in vitro fertilization have been identified, and the parameters of the limited time of fertilization ability of sperm and the ability of oocytes to fertilize, which is called the “fertile span”, have been determined. The main effective medium that increases the effectiveness of in vitro fertilization – synthetic oviduct fluid (SOF) with the addition of heparin and serum of cattle or sheep. The main parameters of sheep embryo culture in vitro are presented with the definition of the most commonly used media and their influence on embryonic development. Potential ways to improve the production of sheep embryos in vitro with the determination of morphological evaluation of categories of oocytes, methods of synchronization of their maturation in vitro are also highlighted. At the same time, literature data on the synchronization of oocyte-cumulus complexes with the use of a large number of inhibitors of meiotic division are presented, which according to many scientists may be a key factor in improving the efficiency of sheep embryo production in vitro. In addition, the results of studies of many scientists on the expansion of the fertile gap of oocytes of sheep cultured in vitro using certain biologically active substances were analyzed. In conclusion, the prospect of using the technology of in vitro production of sheep embryos in biomedical research is highlighted.У статті наведено нові літературні дані щодо досліджень з удосконалення виробництва in vitro ембріонів овець. Проаналізовано досягнення науковців різних країн з підвищення ефективності основних етапів продукції ембріонів in vitro: дозрівання ооцитів in vitro, їх запліднення in vitro та культивування ембріонів in vitro. У джерелах літератури експериментально доведено, що на ефективність дозрівання ооцитів in vitro значний вплив мають досвід і кваліфікація науковців, вік донора яйцеклітини, поліпшення середовища додаванням росковітину для гальмування мейозу, α-лінолевої кислоти, наночастинок діоксиду церію (CeO2 NPs) та серицину для прискорення ядерного дозрівання і збільшення кількості ооцитів другої мейотичної метафази (МІІ). Встановлено основні чинники, які впливають на результативність запліднення in vitro, визначено параметри обмеженого часу запліднювальної здатності сперміїв і здатності ооцитів до запліднення, який називають “фертильним проміжком”. Визначено основне ефективне середовище, яке підвищує результативність запліднення in vitro – синтетична яйцепровідна рідина (SOF) з додаванням гепарину та сироватки великої рогатої худоби або овець. Наведено основні параметри культивування ембріонів овець in vitro з визначенням найбільш вживаних середовищ та їх вплив на ембріональний розвиток. Також висвітлено потенційні шляхи поліпшення продукції ембріонів овець in vitro з визначенням за морфологічною оцінкою категорій ооцитів, методів синхронізації їх дозрівання in vitro. Водночас наведено літературні дані щодо синхронізації ооцит-кумулюсних комплексів з використанням великої кількості інгібіторів мейотичного поділу, що, на думку багатьох вчених, може бути ключовим чинником для підвищення ефективності виробництва ембріонів овець in vitro. Крім того, проаналізовано результати досліджень багатьох науковців з розширення фертильного проміжку ооцитів овець культивованих in vitro використанням окремих біологічно активних речовин. На завершення висвітлена перспектива використання технології виробництва in vitro ембріонів овець у біомедичних дослідженнях

Метаболічний профіль крові корів за лікування гіпофункції яєчників гормональними та фітопрепаратами

Наведено порівняльний аналіз різних схем лікування гіпофункції яєчників у корів української чорно-рябої молочної породи. Встановлено більшу активізацію функціональної активності яєчників за використання ліпосомального препарату на основі фітокомпонентів (радіола рожева, шавлія) та його комбінації з гонадотропін-рилізінг-гормоном (сурфагон). Зростання функціональної активності яєчників супроводжується вірогідним підвищенням концентрації прогестерону та естрадіолу-17? і збільшенням умісту холестеролу, каротину та аскорбінової кислоти в крові корів у процесі лікування гіпофункції яєчників і після його завершення

Associating Genes and Protein Complexes with Disease via Network Propagation

A fundamental challenge in human health is the identification of disease-causing genes. Recently, several studies have tackled this challenge via a network-based approach, motivated by the observation that genes causing the same or similar diseases tend to lie close to one another in a network of protein-protein or functional interactions. However, most of these approaches use only local network information in the inference process and are restricted to inferring single gene associations. Here, we provide a global, network-based method for prioritizing disease genes and inferring protein complex associations, which we call PRINCE. The method is based on formulating constraints on the prioritization function that relate to its smoothness over the network and usage of prior information. We exploit this function to predict not only genes but also protein complex associations with a disease of interest. We test our method on gene-disease association data, evaluating both the prioritization achieved and the protein complexes inferred. We show that our method outperforms extant approaches in both tasks. Using data on 1,369 diseases from the OMIM knowledgebase, our method is able (in a cross validation setting) to rank the true causal gene first for 34% of the diseases, and infer 139 disease-related complexes that are highly coherent in terms of the function, expression and conservation of their member proteins. Importantly, we apply our method to study three multi-factorial diseases for which some causal genes have been found already: prostate cancer, alzheimer and type 2 diabetes mellitus. PRINCE's predictions for these diseases highly match the known literature, suggesting several novel causal genes and protein complexes for further investigation

Probabilistic Random Walk Models for Comparative Network Analysis

Graph-based systems and data analysis methods have become critical tools in many fields as they can provide an intuitive way of representing and analyzing interactions between variables. Due to the advances in measurement techniques, a massive amount of labeled data that can be represented as nodes on a graph (or network) have been archived in databases. Additionally, novel data without label information have been gradually generated and archived. Labeling and identifying characteristics of novel data is an important first step in utilizing the valuable data in an effective and meaningful way. Comparative network analysis is an effective computational means to identify and predict the properties of the unlabeled data by comparing the similarities and differences between well-studied and less-studied networks. Comparative network analysis aims to identify the matching nodes and conserved subnetworks across multiple networks to enable a prediction of the properties of the nodes in the less-studied networks based on the properties of the matching nodes in the well-studied networks (i.e., transferring knowledge between networks). One of the fundamental and important questions in comparative network analysis is how to accurately estimate node-to-node correspondence as it can be a critical clue in analyzing the similarities and differences between networks. Node correspondence is a comprehensive similarity that integrates various types of similarity measurements in a balanced manner. However, there are several challenges in accurately estimating the node correspondence for large-scale networks. First, the scale of the networks is a critical issue. As networks generally include a large number of nodes, we have to examine an extremely large space and it can pose a computational challenge due to the combinatorial nature of the problem. Furthermore, although there are matching nodes and conserved subnetworks in different networks, structural variations such as node insertions and deletions make it difficult to integrate a topological similarity. In this dissertation, novel probabilistic random walk models are proposed to accurately estimate node-to-node correspondence between networks. First, we propose a context-sensitive random walk (CSRW) model. In the CSRW model, the random walker analyzes the context of the current position of the random walker and it can switch the random movement to either a simultaneous walk on both networks or an individual walk on one of the networks. The context-sensitive nature of the random walker enables the method to effectively integrate different types of similarities by dealing with structural variations. Second, we propose the CUFID (Comparative network analysis Using the steady-state network Flow to IDentify orthologous proteins) model. In the CUFID model, we construct an integrated network by inserting pseudo edges between potential matching nodes in different networks. Then, we design the random walk protocol to transit more frequently between potential matching nodes as their node similarity increases and they have more matching neighboring nodes. We apply the proposed random walk models to comparative network analysis problems: global network alignment and network querying. Through extensive performance evaluations, we demonstrate that the proposed random walk models can accurately estimate node correspondence and these can lead to improved and reliable network comparison results

Simultaneous Optimization of Both Node and Edge Conservation in Network Alignment via WAVE

Network alignment can be used to transfer functional knowledge between conserved regions of different networks. Typically, existing methods use a node cost function (NCF) to compute similarity between nodes in different networks and an alignment strategy (AS) to find high-scoring alignments with respect to the total NCF over all aligned nodes (or node conservation). But, they then evaluate quality of their alignments via some other measure that is different than the node conservation measure used to guide the alignment construction process. Typically, one measures the amount of conserved edges, but only after alignments are produced. Hence, a recent attempt aimed to directly maximize the amount of conserved edges while constructing alignments, which improved alignment accuracy. Here, we aim to directly maximize both node and edge conservation during alignment construction to further improve alignment accuracy. For this, we design a novel measure of edge conservation that (unlike existing measures that treat each conserved edge the same) weighs each conserved edge so that edges with highly NCF-similar end nodes are favored. As a result, we introduce a novel AS, Weighted Alignment VotEr (WAVE), which can optimize any measures of node and edge conservation, and which can be used with any NCF or combination of multiple NCFs. Using WAVE on top of established state-of-the-art NCFs leads to superior alignments compared to the existing methods that optimize only node conservation or only edge conservation or that treat each conserved edge the same. And while we evaluate WAVE in the computational biology domain, it is easily applicable in any domain.Comment: 12 pages, 4 figure

Bridging topological and functional information in protein interaction networks by short loops profiling

Protein-protein interaction networks (PPINs) have been employed to identify potential novel interconnections between proteins as well as crucial cellular functions. In this study we identify fundamental principles of PPIN topologies by analysing network motifs of short loops, which are small cyclic interactions of between 3 and 6 proteins. We compared 30 PPINs with corresponding randomised null models and examined the occurrence of common biological functions in loops extracted from a cross-validated high-confidence dataset of 622 human protein complexes. We demonstrate that loops are an intrinsic feature of PPINs and that specific cell functions are predominantly performed by loops of different lengths. Topologically, we find that loops are strongly related to the accuracy of PPINs and define a core of interactions with high resilience. The identification of this core and the analysis of loop composition are promising tools to assess PPIN quality and to uncover possible biases from experimental detection methods. More than 96% of loops share at least one biological function, with enrichment of cellular functions related to mRNA metabolic processing and the cell cycle. Our analyses suggest that these motifs can be used in the design of targeted experiments for functional phenotype detection.This research was supported by the Biotechnology and Biological Sciences Research Council (BB/H018409/1 to AP, ACCC and FF, and BB/J016284/1 to NSBT) and by the Leukaemia & Lymphoma Research (to NSBT and FF). SSC is funded by a Leukaemia & Lymphoma Research Gordon Piller PhD Studentship

Detection of regulator genes and eQTLs in gene networks

Genetic differences between individuals associated to quantitative phenotypic traits, including disease states, are usually found in non-coding genomic regions. These genetic variants are often also associated to differences in expression levels of nearby genes (they are "expression quantitative trait loci" or eQTLs for short) and presumably play a gene regulatory role, affecting the status of molecular networks of interacting genes, proteins and metabolites. Computational systems biology approaches to reconstruct causal gene networks from large-scale omics data have therefore become essential to understand the structure of networks controlled by eQTLs together with other regulatory genes, and to generate detailed hypotheses about the molecular mechanisms that lead from genotype to phenotype. Here we review the main analytical methods and softwares to identify eQTLs and their associated genes, to reconstruct co-expression networks and modules, to reconstruct causal Bayesian gene and module networks, and to validate predicted networks in silico.Comment: minor revision with typos corrected; review article; 24 pages, 2 figure