Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatial and temporal heterogeneity of Daphnia in Lake Constance; intra- and interspecific comparisons.

Allozymic surveys of the Daphnia galeata-hyalina species complex in Lake Constance (Bodensee) examined seasonal variation in daytime vertical distributions of Daphnia galeata (G), Daphnia hyalina (H), and G x H hybrids. During summer and early autumn, G was the dominant taxon in the upper 20 m of the water column, while H and G x H were most abundant below 30 m. From November until April, all three taxa were homogeneously distributed in the water. Seventeen distinct G clones were detected during the study, while six G x H clones and five H clones were detected. Single clones of G × H and H accounted for 93% (400/431 and 400/434, respectively) of the total number sampled. Results reconfirm previous studies, which observed spatial (vertical) separation of G and H, and confirm previous suspicions as to the existence of G x H hybrids in the lake.
Long-Term Outcomes and Risk Factors of Renal Failure Requiring Dialysis after Heart Transplantation: A Nationwide Cohort Study

Acute kidney injury and renal failure are common after heart transplantation. We retrospectively reviewed a national cohort and identified 1129 heart transplant patients. Patients receiving renal replacement therapy after heart transplantation were grouped into the dialysis cohort. The long-term survival and risk factors of dialysis were investigated. Patients who had undergone dialysis were stratified to early or late dialysis for subgroup analysis. The mean follow-up was five years, the incidence of dialysis was 28.4% (21% early dialysis and 7.4% late dialysis). The dialysis cohort had higher overall mortality compared with the non-dialysis cohort. The hazard ratios of mortality in patients with dialysis were 3.44 (95% confidence interval (CI), 2.73–4.33) for all dialysis patients, 3.58 (95% CI, 2.74–4.67) for early dialysis patients, and 3.27 (95% CI, 2.44–4.36; all p < 0.001) for late dialysis patients. Patients with diabetes mellitus, chronic kidney disease, acute kidney injury, and coronary artery disease were at higher risk of renal failure requiring dialysis. Cardiomyopathy, hepatitis B virus infection, and hyperlipidemia treated with statins were associated with a lower risk of renal dysfunction requiring early dialysis. The use of Sirolimus and Mycophenolate mofetil was associated with a lower incidence of late dialysis. Renal dysfunction requiring dialysis after heart transplantation is common in Taiwan. Early and late dialysis were both associated with an increased risk of mortality in heart transplant recipients.
Development of a Ratiometric Fluorescent Glucose Sensor Using an Oxygen-Sensing Membrane Immobilized with Glucose Oxidase for the Detection of Glucose in Tears

Glucose concentration is an important parameter in biomedicine since glucose is involved in many metabolic pathways in organisms. Many methods for glucose detection have been developed for use in various applications, particularly in the field of healthcare in diabetics. In this study, ratiometric fluorescent glucose-sensing membranes were fabricated based on the oxygen levels consumed in the glucose oxidation reaction under the catalysis of glucose oxidase (GOD). The oxygen concentration was measured through the fluorescence quenching effect of an oxygen-sensitive fluorescent dye like platinum meso-tetra (pentafluorophenyl) porphyrin (PtP) by oxygen molecules. Coumarin 6 (C6) was used as a reference dye in the ratiometric fluorescence measurements. The glucose-sensing membrane consisted of two layers: The first layer was the oxygen-sensing membrane containing polystyrene particles (PS) doped with PtP and C6 (e.g., PS@C6^PtP) in a sol–gel matrix of aminopropyltrimethoxysilane and glycidoxypropyltrimethoxysilane (GA). The second layer was made by immobilizing GOD onto one of three supporting polymers over the first layer. These glucose-sensing membranes were characterized in terms of their response, reversibility, interferences, and stability. They showed a wide detection range to glucose concentration in the range of 0.1 to 10 mM, but high sensitivity with a linear detection range of 0.1 to 2 mM glucose. This stable and sensitive ratiometric fluorescent glucose biosensor provides a reliable way to determine low glucose concentrations in blood serum by measuring tear glucose.
The Effects of Salinity Acclimation on the Osmotic Properties of Mitochondria from the Gill Of Crassostrea Virginica

Glutamate oxidation in mitochondria from the gills of oysters ( Crassostrea virginica Gmelin) acclimated to sea water (SW) is sensitive to assay medium osmolanty. Compared to a medium of the osmolarity of sea water, decreasing osmolarity stimulates glutamate oxidation and increasing osmolarity inhibits glutamate oxidation. Glutamate oxidation by mitochondria from oysters acclimated to dilute sea water (DSW) is 2.5-fold greater than in SW animals when each is assayed under isosmotic conditions. The maximal rates obtained in both acclimation groups are equal. Although the DSW animals were acclimated to an osmolarity approximately 660 mosmol 1 −1 lower than SW animals, the osmotic optimum was only 100–200 mosmol 1 −1 lower in the former group. Isolation medium osmolarity does not affect the osmolarity at which the maximum rate of glutamate oxidation is observed in either acclimation group. A low-osmolarity isolation medium reduces the oxidation rates and quality of the mitochondria, as assessed by the respiratory control ratio in both acclimation groups. These data suggest that an optimal matrix solute concentration or ionic strength is required for maximal rates of glutamate oxidation rather than an optimal mitochondrial volume. The optimal mitochondrial matrix milieu can be achieved both by acclimation to dilute sea water and by incubation in hypo-osmotic media.
Knowledge of Contraceptive Use among Secondary School Adolescents in Uvwie L.G.A of Delta State

Promotion of family planning aims to help female adolescents and youths maintain a strategic distance from undesirable pregnancy. It is imperative to the World Health Organization (WHO) in dealing with the improvement in maternal health and is central to accomplishing the sustainable development goal. This study was carried out to assess the knowledge of contraception among adolescents in Uvwie L.G. A of Delta State, Nigeria. Three hundred secondary school adolescents (12-18) were selected using the multi-stage sampling technique. A semi-structured questionnaire was administered to 300 students and Chi-square was used to determine the association between identified factors and contraceptive use in the study population at a 95% confidence interval and pvalue of 0.05 was considered statistically significant.The study showed that more than 50% (208) of the research participants have an existing knowledge of contraceptives, 133(63.9%) of them got the information from their friends/peers. One hundred and thirty six (45.33%) of the respondents were reported to be sexually active. However, most of them said contraceptives were used for preventing Pregnancy and STI's. The study showed that their knowledge about contraception was relatively poor. Teaching on Health care, Health Education and Reproductive health should be improved. Original Research Article Neville and Moore; AJPCB, 1(1): 1-8, 2018; Article no.AJPCB. 45423 2
Crosstalk between Tumor and Stromal Cells in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) remains a lethal cancer. The poor prognosis calls for a more detailed understanding of disease biology in order to pave the way for the development of effective therapies. Typically, the pancreatic tumor is composed of a minority of malignant cells within an excessive tumor microenvironment (TME) consisting of extracellular matrix (ECM), fibroblasts, immune cells, and endothelial cells. Research conducted in recent years has particularly focused on cancer-associated fibroblasts (CAFs) which represent the most prominent cellular component of the desmoplastic stroma. Here, we review the complex crosstalk between CAFs, tumor cells, and other components of the TME, and illustrate how these interactions drive disease progression. We also discuss the emerging field of CAF heterogeneity, their tumor-supportive versus tumor-suppressive capacity, and the consequences for designing stroma-targeted therapies in the future.
Mechanisms Protecting Acinetobacter baumannii against Multiple Stresses Triggered by the Host Immune Response, Antibiotics and Outside-Host Environment

Acinetobacter baumannii is considered one of the most persistent pathogens responsible for nosocomial infections. Due to the emergence of multidrug resistant strains, as well as high morbidity and mortality caused by this pathogen, A. baumannii was placed on the World Health Organization (WHO) drug-resistant bacteria and antimicrobial resistance research priority list. This review summarizes current studies on mechanisms that protect A. baumannii against multiple stresses caused by the host immune response, outside host environment, and antibiotic treatment. We particularly focus on the ability of A. baumannii to survive long-term desiccation on abiotic surfaces and the population heterogeneity in A. baumannii biofilms. Insight into these protective mechanisms may provide clues for the development of new strategies to fight multidrug resistant strains of A. baumannii.
A New Model for A Complex Computer Network Reliability Design and Its Solution Using Trust Region Method

1) Arab Academy for Science and Technology, College of Engineering and Technology, Computer Engineering Department Alexandria, Egypt, 2) Department of Mathematics, Faculty of Sciences, Alexandria University, Alexandria Egypt, 3) Arab Academy for Science and Technology, College of Engineering and Technology Electronics and Communication Department Alexandria Egypt, (This author would like to thank Prof. M.Saeb for his useful suggestion). Abstract A model that maximizes the reliability and minimizes the cost for a complex computer network reliability design is introduced. The model takes in to its consideration, for the first time to the best of our knowledge, the criticality of network links. The model problem is formed as a nonlinear optimization problem. The model problem is solved using an efficient algorithm that uses trust-region active-set approach to ensure convergence from any starting point. Our numerical experiments show that our approach is promising especially for complex computer networks. Introduction The ultimate objective of this paper is to give design engineers procedures to enhance their ability to design network for which reliability is an important consideration. Ideally, one would like to generate network design algorithms that take as input the characteristics of network components as well as network criteria, and produce as output an optimal network design. This is known as network synthesis, and it is very difficult to achieve. Instead, we consider a network that is already designed then try to improve this design by maximizing the link reliability, which will maximize the overall network reliability In the most theoretical reliability problems the two basic methods of improving the reliability of systems are improving the reliability of each component or adding redundant components. Of course, the second method is more expensive than the first. Our paper considers the first method, in which, addition to being cheaper, can be converted when needed to the second method. We present a new model, which considers the measure of criticality for each link. The model involves only probability of success to the links as a variable. Our aim is to obtain the optimal system design with the following constraints: 1. basic cost reliability data to links. We use a linear-cost-reliability relation for each component [2]. 2. criticality of links. The designer should take this in to account before building a reliable network because of its importance in saving money and arranging the priority of maximizing link reliability.
Commentary on Ditch, Stitch and Pitch: the niche is here to stay

A recent set of discussion papers in the Journal of Biogeography by McInerny and Etienne (henceforth M&E) questions the value of niche concepts in relation to a diverse group of practices collectively labelled species distribution modelling (SDM), and specifically the usefulness of the idea of a fundamental niche. In this Correspondence, I argue that certain types of SDM may indeed dispense with niche concepts, but that such is not the case for an important class of SDM‐based activities, including transferring predictions in space and time. Using a single term (SDM) to denote diverse objectives and practices does not help to clarify issues; I discuss this point. I also review several criticisms raised by M&E about the use of the concept of fundamental niche in the context of modelling species' distributions and their environments.
Antithrombotic therapy for stroke prevention in patients with atrial fibrillation in Japan

ABSTRACT Introduction Stroke remains one of the major public health problems in Japan. The number of patients with atrial fibrillation (AF) has been steadily increasing with the aging of the Japanese population. Appropriate oral antithrombotic therapy is necessary to prevent AF-related stroke and bleeding complications. Areas covered The authors summarize the Japanese guidelines for antithrombotic therapy, as well as the current status of antithrombotic therapy, and future perspectives for antithrombotic therapy for patients with AF in Japan. Expert opinion Further improvement in adherence to guideline-recommended warfarin therapy may be difficult to achieve. After the introduction of direct oral anticoagulants (DOACs) into clinical practice, the proportion of patients with AF receiving oral anticoagulant therapy has increased in Japan. However, the proportion of patients treated with inappropriately reduced doses of DOACs has also been increasing. Inappropriate dose reduction of DOACs simply because of advanced age should be avoided to reduce stroke events in patients with AF. Among patients with AF receiving anticoagulant therapy who have coronary artery disease, inappropriately prolonged triple therapy or dual therapy should be avoided to reduce major bleeding complications. Shortening the duration of triple therapy or dual therapy may be promoted by simplified recommendations in the 2020-updated guidelines supported by solid evidence.
LR-SDiscr: a novel and scalable merging and splitting discretization framework using a lexical generator

ABSTRACT In this paper, we propose a novel supervised discretization method namely LR-SDiscr. It is based on a Left to Right (LR) scanning technique, which partitions automatically the input stream into intervals. Its originality resides in the fact it handles both merging and division operations in the same process, and hence it benefits of the use of a large spectrum of statistic measures. The second strength of our proposal is the reduction of the discretization complexity by processing the data in only one pass. Extensive experiments were conducted on various cut-point functions using public benchmarks that include small, large and medical datasets. LR-SDiscr outperforms several classical and recent discretization methods.
Heterologous Expression of Poplar WRKY18/35 Paralogs in Arabidopsis Reveals Their Antagonistic Regulation on Pathogen Resistance and Abiotic Stress Tolerance via Variable Hormonal Pathways

WRKY transcription factors (WRKY TFs) are one of the largest protein families in plants, and most of them play vital roles in response to biotic and abiotic stresses by regulating related signaling pathways. In this study, we isolated two WRKY TF genes PtrWRKY18 and PtrWRKY35 from Populus trichocarpa and overexpressed them in Arabidopsis. Expression pattern analyses showed that PtrWRKY18 and PtrWRKY35 respond to salicylic acid (SA), methyl JA (MeJA), abscisic acid (ABA), B. cinereal, and P. syringae treatment. The transgenic plants conferred higher B. cinerea tolerance than wild-type (WT) plants, and real-time quantitative (qRT)-PCR assays showed that PR3 and PDF1.2 had higher expression levels in transgenic plants, which was consistent with their tolerance to B. cinereal. The transgenic plants showed lower P. syringae tolerance than WT plants, and qRT-PCR analysis (PR1, PR2, and NPR1) also corresponded to this phenotype. Germination rate and root analysis showed that the transgenic plants are less sensitive to ABA, which leads to the reduced tolerance to osmotic stress and the increase of the death ratio and stomatal aperture. Compared with WT plants, a series of ABA-related genes (RD29A, ABO3, ABI4, ABI5, and DREB1A) were significantly down-regulated in PtrWRKY18 and PtrWRKY35 overexpression plants. All of these results demonstrated that the two WRKY TFs are multifunctional transcription factors in plant resistance.
DCHap: A Divide-and-Conquer Haplotype Phasing Algorithm for Third-Generation Sequences

The development of DNA sequencing technologies makes it possible to obtain reads originated from both copies of a chromosome (two parental chromosomes, or haplotypes) of a single individual. Reconstruction of both haplotypes (i.e., haplotype phasing) plays a crucial role in genetic analysis and provides relationship information between genetic variation and disease susceptibility. With the emerging third-generation sequencing technologies, most existing approaches for haplotype phasing suffer from performance issues to handle long and error-prone reads. We develop a divide-and-conquer algorithm, DCHap, to phase haplotypes using third-generation reads. We benchmark DCHap against three state-of-the-art phasing tools on both PacBio SMRT data and ONT Nanopore data. The experimental results show that DCHap generates more accurate or comparable results (measured by the switch errors) while being scalable for higher coverage and longer reads. DCHap is a fast and accurate algorithm for haplotype phasing using third-generation sequencing data. As the third-generation sequencing platforms continue improving on their throughput and read lengths, accurate and scalable tools like DCHap are important to improve haplotype phasing from the advances of sequencing technologies. The source code is freely available at https://github.com/yanboANU/Haplotype-phasing.
Serum Iron and Risk of Diabetic Retinopathy

Background: Diabetic retinopathy (DR) is indicated as a major cause of blindness in the world. Emerging evidence supports the interaction of iron metabolism with diabetes. However, little research is available concerning the relationship between iron metabolism and DR. The intent of this paper is to describe the correlation between serum iron and the occurrence of DR. Methods: A total of 5321 participants who underwent related examinations as part of the National Health and Nutrition Examination Survey (2005–2008) were included. DR was defined by the criteria of the Early Treatment for Diabetic Retinopathy Study based on nonmydriatic fundus photography. The cutoff point of serum iron for DR was explored by the receiver operating characteristics curve. The relationship of serum iron with the occurrence of DR was explored by multivariate logistic regression models. Results: Participants with DR had significantly lower serum iron than the control group. Serum iron was negatively correlated with the occurrence of DR after the adjustment of pertinent variables (an odds ratio (OR) of 0.995 (95% CI: 0.992–0.999)). After dividing serum iron into quartiles, the third quartile was associated with DR with an OR of 0.601 (95% CI: 0.418–0.863). Furthermore, the cutoff point of serum iron had an inverse relationship for the occurrence of DR with an OR of 0.766 (95% CI: 0.597–0.984). Conclusion: Serum iron has an inverse association with the occurrence of DR in diabetic adults. The assessment of serum iron levels might be a part of follow-up visits with diabetic patients.
A method for determining information diffusion cascades on social networks

Information diffusion on social networks has many potential real-world applications such as online marketing, e-government campaigns, and predicting large social events. Modeling information diffusion is therefore a crucial task in order both to understand its diffusion mechanism and to better control it. Our research aims at finding what factors might influence people in adopting a piece of information that is being shared on a social network. In this study, the traditional independent cascade model for information diffusion is extended with discrete time steps. The proposed model is capable of incorporating three different sources of diffusion influence: user-user influence, user-content preference, and external influence. Specifically, these sources of influence are quantified into real values of diffusion probability. To calculate user-user influence, we adopt and extend the disease transmission model according to the role of the user who diffuses the content. User-content preference, which measures the correlation between user preference and the adopted contents, is calculated based on a topic-based model. External influence is detected in a diffusion time step and is quantified and incorporated into our model for the next diffusion time step by applying and solving a logistic function. Moreover, the process of information diffusion is characterized by constructing a tree of information adoption and the diffusion scale is quantified by predicting the number of infected nodes. It is found that these sources of influence, especially external influence, play a significant role in information diffusion and eventually affect the shape and size of the diffusion cascade. The model is validated on both synthetic and real-world datasets. Experimental results confirm the advantage of our proposed method, which significantly improves over the previous models in terms of prediction accuracy
A Novel Hybrid Model Based on a Feedforward Neural Network and One Step Secant Algorithm for Prediction of Load-Bearing Capacity of Rectangular Concrete-Filled Steel Tube Columns

In this study, a novel hybrid surrogate machine learning model based on a feedforward neural network (FNN) and one step secant algorithm (OSS) was developed to predict the load-bearing capacity of concrete-filled steel tube columns (CFST), whereas the OSS was used to optimize the weights and bias of the FNN for developing a hybrid model (FNN-OSS). For achieving this goal, an experimental database containing 422 instances was firstly gathered from the literature and used to develop the FNN-OSS algorithm. The input variables in the database contained the geometrical characteristics of CFST columns, and the mechanical properties of two CFST constituent materials, i.e., steel and concrete. Thereafter, the selection of the appropriate parameters of FNN-OSS was performed and evaluated by common statistical measurements, for instance, the coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MAE). In the next step, the prediction capability of the best FNN-OSS structure was evaluated in both global and local analyses, showing an excellent agreement between actual and predicted values of the load-bearing capacity. Finally, an in-depth investigation of the performance and limitations of FNN-OSS was conducted from a structural engineering point of view. The results confirmed the effectiveness of the FNN-OSS as a robust algorithm for the prediction of the CFST load-bearing capacity.