Miracle-dz/UniFAR-FTUs huggingface dataset:
Isozyme Analysis in Fungal Taxonomy, Genetics, and Population Biology

Isozyme analysis is a powerful technique for assaying genetic variation within and among populations. This versatile approach has been used on bacteria, fungi, plants, and most major groups of animals, from insects and other invertebrates to fish and mammals. The appeal of isozyme analysis stems from its ease of use, low cost, and speed. DNA-based technologies can provide a higher level of polymorphism with concomitantly greater resolution. However, when sufficient variation is present, isozymes provide the fastest, easiest answers to biological questions at a significantly lower cost compared to other available techniques. Isozyme analysis has a long history in the fungi. Differences among general protein patterns of species of Neurospora and Pythium were first noted during the early 1960s (Chang et al. 1962; Clare 1963). This approach developed into isozyme analysis with the application of methods for detection of specific enzyme activities. Since the mid 1960s, the technique has been applied to questions of fungal taxonomy, genetics, population biology, and species or strain identification (Micales et al. 1986; 1992) but it is only during the past 15 years that the true potential of the technique has been realized. The purpose of this chapter is to introduce the concept of isozyme analysis in fungi. Strategies for developing new isozyme systems and for addressing particular questions about fungal taxonomy, genetics, and population biology will be discussed. Particular emphasis will be placed on identifying common pitfalls and barriers to successful implementation of new isozyme systems, especially interpretation of banding patterns, preparation of tissue samples, and methods and approaches to data analysis. Specific examples of isozyme analysis for the major groups of fungi will be discussed to illustrate the many potential applications of this extremely useful and powerful technique.
A DISSERTATION SUBMITTED TO THE GRADUATE DIVISION OF THE UNIVERSITY OF HAWAI‘I AT MĀNOA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

iv List of tables.vii List of figures.viii List of abbreviations.ix Chapter One: Background and Literature Review.1 1.1 Background.1 1.2 Methods . 2 1.3 Results . 3 1.4 Discussion . 12 Chapter Two: A randomized controlled trial of patient-centered non-pharmacologic pain management techniques . 15 2.
Hepatoprotective Effect of Garlic Aqueous Extract against Hepatotoxicity Induced By Ciprofibrate in Male Albino Rats

The liver plays a central role in transforming and clearing chemicals and is susceptible to the toxicity from these agents. Certain medicinal agents, when taken in overdoses and sometimes even when introduced within therapeutic ranges, may injure the organ. When the liver works normally, the various metabolic processes within the body are balanced and regular, but the use of certain drugs may cause liver problems. The liver is a specific target for drug toxicity because of its role in the removal and metabolism of chemicals, the drug enters the body by many ways, including oral, intramuscular injection, intra venous, dermal absorption, and nose [1]. It is known that the main function of the liver is elimination of toxins that may enter the body, thus becoming ABSTRACT
In vitro genotoxic study reinforces the use of titanium-35niobium alloy in biomedical implants

The applications of titanium based alloys are widely used as orthopedic implants due to their excellent combination of mechanical properties, corrosion resistance and outstanding biocompatibility. Recently studies have been demonstrated titanium-niobium alloys do not present cytotoxicity, exhibit corrosion resistance similar or superior to titanium and have elastic modulus significantly lower than other titanium alloys. These characteristics make these materials an alternative for several biomedical applications, mainly implants. Previous studies demonstrated that Ti-35Nb alloy exhibits the closest elastic modulus of bone, and have good performance in key parameters of osteogenesis, which means that this alloy has an excellent biological profile and shows a great potential for biomedical application. In the present study it was demonstrated that Ti-35Nb alloy did not present DNA damage. Thus, these results consolidate this alloy has a promising material to substitution to the materials currently used in orthopedics and in dentistry, with absence of cytotoxity and genotoxity.
Mode detection in on-line pen drawing and handwriting recognition

On-line pen input benefits greatly from mode detection when the user is in a free writing situation, where he is allowed to write, to draw, and to generate gestures. Mode detection is performed before recognition to restrict the classes that a classifier has to consider, thereby increasing the performance of the overall recognition. In this paper we present a hybrid system which is able to achieve a mode detection performance of 95.6% on seven classes; handwriting, lines, arrows, ellipses, rectangles, triangles, and diamonds. The system consists of three kNN classifiers which use global and structural features of the pen trajectory and a fitting algorithm for verifying the different geometrical objects. Results are presented on a significant amount of data, acquired in different contexts like scribble matching and design applications.
Determining familial resemblances from face images

Looking for similarity in faces of people is a difficult and broad task. The subjectivity might stem from varying degrees of similarity between facial features. Identifying the same individual person in different circumstances can be viewed as a stricter similarity problem, whereas determing if a child resembles either or both parents is a wider similarity problem. Assessing whether two people share the same ancestry is an even wider similarity problem. In all cases the solution can be challenged by obscuration or evolving facial features, e.g. with age. Engineered features or metrics have been used in the past [4]. In recent works [3] [2] deep neural networks have been used. In this project, the objective is to explore and improve upon current methods in deep learning on facial images to asses similarity between family members. The scope will be limited to the classification problem spanning one generation: whether a child resembles his/her biological parents ? A further extension of the solution will be to assess similarities between persons in same ancestry. Development in this area can be helpful in biometric or forensic verifications, anthropological studies, social media tagging, etc. A more ambitious application would be to understand how subtle genetic or environmental factors manifest as variations in facial features.
Pleasant Communication as an Integral Part of Women’s Quality of Life: A Qualitative Study

ObjectivesThe communication is not just being able to verbally pronounce words and sentences, but it includes understanding information through inspiration, inner instinct, or external guidance. To achieve a better quality of life (QoL), there is a need for determining pleasant communication. The current study aimed to explore the women’s perception about different aspects of communication in their life.Materials and MethodsThis qualitative content analysis aimed to understand the meaning of communication as a key factor in Iranian women’s QoL, which was conducted on 40 women. The data were gathered through depth interviews from May to November 2016 in Tehran, Iran. The interviews were transcribed verbatim and analyzed using conventional qualitative content analysis in 8 stages recommended by Zhang.ResultsTwo categories were identified based on the interviews, including constructive spiritual and pleasant peripheral communication and each theme consisted of some categories.ConclusionsOverall, awareness about different aspects of communication in women’s life must be considered by politicians and health care providers in Iran. In addition, efforts would be made to improve nurses’ understanding of different aspects of the QoL, especially pleasant communication in women’s life which could help their health promotion.
Effects of Visual Distinctiveness on Learning and Retrieval in Icon Toolbars

Learnability is important in graphical interfaces because it supports the user’s transition to expertise. One aspect of GUI learnability is the degree to which the icons in toolbars and ribbons are identiﬁable and memorable – but current “ﬂat” and “subtle” designs that promote strong visual consistency could hinder learning by reducing visual distinctiveness within a set of icons. There is little known, however, about the effects of visual distinctiveness of icons on selection performance and memorability. To address this gap, we carried out two studies using several icon sets with different degrees of visual distinctiveness, and compared how quickly people could learn and retrieve the icons. Our ﬁrst study found no evidence that increasing colour or shape distinctiveness improved learning, but found that icons with concrete imagery were easier to learn. Our second study found similar results: there was no effect of increasing either colour or shape distinctiveness, but there was again a clear improvement for icons with recognizable imagery. Our results show that visual characteristics appear to affect UI learnability much less than the meaning of the icons’ representations.
DeepTennis: Mid-Match Tennis Predictions CS230-Fall 2019

The ﬁeld of sports analytics has experienced major growth in the past decade, including the area of match prediction. In comparison to pre-match predictions, the task of producing mid-match live predictions remains an area open to emergent study. We investigate the use of a recurrent neural network utilizing the Long Short-Term Memory (LSTM) model infrastructure to compute ’live’ win probabilities for tennis matches from mid-game data. Using a detailed point-by-point dataset [1] for the four Grand Slam tennis tournaments, our model is intended to learn deep relationships amongst the sequential data and to classify the probability of winning the match for each player after any given point. In combination with traditional pre-match prediction priors, our model obtains an average accuracy of 79.5% across all given points, roughly 3 percentage points higher than traditional statistical point-by-point models [2].
An Exploratory Study of Middle Manager’s Roles in Continuous Improvement

Floyd and Wooldridge have developed a widely used model regarding the middle managers’ contribution to strategic change, in which four strategic roles for middle managers are considered: championing, synthesizing, facilitating and implementing. Although there is an extensive body of knowledge about the roles and influence of middle managers in implementing strategy, insight in which roles are activated in continuous improvement (CI) initiatives is underdeveloped and highly dispersed. Therefore, in this study we seek to understand which middle management roles (i.e. championing, synthesizing, facilitating, implementing) contribute to accomplishing CI. To explore which of these roles are activated when middle managers are confronted with a CI initiative, we developed a scenario experiment. Our findings indicate that the implementing and synthesizing roles appear to be of key importance in the context of CI initiatives, while the facilitating and championing roles appear to be less relevant.
Effect of Liquidity Decisions on Financial Performance of Dairy Farms in Nakuru County, Kenya

The main aim of the study was to determine the effect of liquidity decisions on financial performance of dairy farms in Nakuru County, Kenya. This is a study carried out on management, accounts and finance employees working with dairy farms in Nakuru County, Kenya with daily milk production of at least 1,000 litres. A Sample of 62 respondents was obtained from the population using both purposive and stratified random sampling methods. Data was analyzed with the facilitation of the Statistical Package for Social Sciences software. Descriptive statistics which included frequencies, percentages, means, and standard deviations were used in the analysis. Inferential statistics employed in the analysis included Pearson’s Product Moment Correlation Coefficient and simple regression analysis. It was found that, there existed significant correlation between liquidity decisions and financial performance (r = 0.425; p < 0.05). It was concluded that farms had established liquidity policies, effective management of current assets and systems which detected warning signals of liquidity risk. The study inferred that liquidity decisions were important aspects since they influenced financial performance.
The association of pretreatment neutrophil to lymphocyte ratio with overall survival in patients with glioblastoma multiforme (GBM).

2062 Background: GBM is the most common and aggressive primary brain tumor. The neutrophil to lymphocyte ratio (NLR) gives a measure of systemic inflammatory response and lymphopenia, both of which are poor prognostic factors in many malignancies. No published study has assessed the prognostic impact of NLR in GBM. Methods: Patients treated for GBM at our regional referral centre with assessable complete blood count at first presentation (prior to corticosteroid therapy or surgery) were identified. Medical notes were reviewed to extract demographic and treatment data. Survival curves were estimated via Kaplan-Meier method and compared via log-rank method. Multivariate analysis was performed via Cox proportional hazards regression modelling. Results: A total of 86 patients were identified, of which 65(76%) were male. Median age at diagnosis was 58 years (range: 18–76). At the time of analysis all patients still alive had ≥ 2 years follow-up. Median overall survival (OS) was 9.3 months (range: 1-82). 57% co.
Yet Another Matcher

Discovering correspondences between schema elements is a crucial task for data integration. Most matching tools are semi-automatic, e.g. an expert must tune some parameters (thresholds, weights, etc.). They mainly use several methods to combine and aggregate similarity measures. However, their quality results often decrease when one requires to integrate a new similarity measure or when matching particular domain schemas. This paper describes YAM (Yet Another Matcher), which is a matcher factory. Indeed, it enables the generation of a dedicated matcher for a given schema matching scenario, according to user inputs. Our approach is based on machine learning since schema matchers can be seen as classifiers. Several bunches of experiments run against matchers generated by YAM and traditional matching tools show how our approach (i) is able to generate the best matcher for a given scenario and (ii) easily integrates user preferences, namely recall and precision tradeoff.
Plant diversity effects on grassland productivity are robust to both nutrient enrichment and drought

Global change drivers are rapidly altering resource availability and biodiversity. While there is consensus that greater biodiversity increases the functioning of ecosystems, the extent to which biodiversity buffers ecosystem productivity in response to changes in resource availability remains unclear. We use data from 16 grassland experiments across North America and Europe that manipulated plant species richness and one of two essential resources—soil nutrients or water—to assess the direction and strength of the interaction between plant diversity and resource alteration on above-ground productivity and net biodiversity, complementarity, and selection effects. Despite strong increases in productivity with nutrient addition and decreases in productivity with drought, we found that resource alterations did not alter biodiversity–ecosystem functioning relationships. Our results suggest that these relationships are largely determined by increases in complementarity effects along plant species richness gradients. Although nutrient addition reduced complementarity effects at high diversity, this appears to be due to high biomass in monocultures under nutrient enrichment. Our results indicate that diversity and the complementarity of species are important regulators of grassland ecosystem productivity, regardless of changes in other drivers of ecosystem function.
Red Blood Cell Homeostasis: Pharmacological Interventions to Explore Biochemical, Morphological and Mechanical Properties

During their passage through the circulation, red blood cells (RBCs) encounter severe physiological conditions consisting of mechanical stress, oxidative damage and fast changes in ionic and osmotic conditions. In order to survive for 120 days, RBCs adapt to their surroundings by subtle regulation of membrane organization and metabolism. RBC homeostasis depends on interactions between the integral membrane protein band 3 with other membrane and cytoskeletal proteins, and with key enzymes of various metabolic pathways. These interactions are regulated by the binding of deoxyhemoglobin to band 3, and by a signaling network revolving around Lyn kinase and Src family kinase-mediated phosphorylation of band 3. Here we show that manipulation of the interaction between the lipid bilayer and the cytoskeleton, using various pharmacological agents that interfere with protein-protein interactions and membrane lipid organization, has various effects on: (1) morphology, as shown by high resolution microscopy and quantitative image analysis; (2) organization of membrane proteins, as indicated by immunofluorescence confocal microscopy and quantitative as well as qualitative analysis of vesicle generation; (3) membrane lipid organization, as indicated by flow cytometric analysis of phosphatidylserine exposure; (4) deformability, as assessed in capillary-mimicking circumstances using a microfluidics system; (5) deformability as determined using a spleen-mimicking device; (6) metabolic activity as indicated by metabolomics. Our data show that there is a complex relationship between red cell morphology, membrane organization and deformability. Also, our data show that red blood cells have a relatively high resistance to disturbance of membrane organization in vitro, which may reflect their capacity to withstand mechanical, oxidative and osmotic stress in vivo.
Salivary bacterial fingerprints of established oral disease revealed by the Human Oral Microbe Identification using Next Generation Sequencing (HOMINGS) technique

Background and objective The composition of the salivary microbiota, as determined using various molecular methods, has been reported to differentiate oral health from diseases. Thus, the purpose of this study was to utilize the newly developed molecular technique HOMINGS (Human Oral Microbe Identification using Next Generation Sequencing) for comparison of the salivary microbiota in patients with periodontitis, patients with dental caries, and orally healthy individuals. The hypothesis was that this method could add on to the existing knowledge on salivary bacterial profiles in oral health and disease. Design Stimulated saliva samples (n=30) were collected from 10 patients with untreated periodontitis, 10 patients with untreated dental caries, and 10 orally healthy individuals. Salivary microbiota was analyzed using HOMINGS and statistical analysis was performed using Kruskal–Wallis test with Benjamini–Hochberg's correction. Results From a total of 30 saliva samples, a mean number of probe targets of 205 (range 120–353) were identified, and a statistically significant higher mean number of targets was registered in samples from patients with periodontitis (mean 220, range 143–306) and dental caries (mean 221, range 165–353) as compared to orally healthy individuals (mean 174, range 120–260) (p=0.04 and p=0.04). Nine probe targets were identified with a different relative abundance between groups (p<0.05). Conclusions Cross-sectional comparison of salivary bacterial profiles by means of HOMINGS analysis showed that different salivary bacterial profiles were associated with oral health and disease. Future large-scale prospective studies are needed to evaluate if saliva-based screening for disease-associated oral bacterial profiles may be used for identification of patients at risk of acquiring periodontitis and dental caries.
The Effect of Rosuvastatin on Markers of Immune Activation in Treatment-Naive Human Immunodeficiency Virus-Patients

Background. Immune activation has been implicated in the excess mortality in human immunodeficiency virus (HIV)-infected patients, due to cardiovascular diseases and malignancies. Statins may modulate this immune activation. We assessed the capacity of rosuvastatin to mitigate immune activation in treatment-naive HIV-infected patients. Methods. In a randomized double-blind placebo-controlled crossover study, we explored the effects of 8 weeks of rosuvastatin 20 mg in treatment-naive male HIV-infected patients (n = 28) on immune activation markers: neopterin, soluble Toll-like receptor (TLR)2, sTLR4, interleukin (IL)-6, IL-1Ra, IL-18, d-dimer, highly sensitive C-reactive protein, and CD38 and/or human leukocyte antigen-DR expression on T cells. Baseline data were compared with healthy male controls (n = 10). Furthermore, the effects of rosuvastatin on HIV-1 RNA, CD4/CD8 T-cell count, and low-density lipoprotein cholesterol were examined and side effects were registered. Results. T-cell activation levels were higher in patients than in controls. Patients had higher levels of circulating IL-18, sTLR2, and neopterin (all P < .01). Twenty patients completed the study. Rosuvastatin increased the CD4/CD8 T-cell ratio (P = .02). No effect on other markers was found. Conclusions. Patients infected with HIV had higher levels of circulating neopterin, IL-18, sTLR2, and T-cell activation markers. Rosuvastatin had a small but significant positive effect on CD4/CD8 T-cell ratio, but no influence on other markers of T-cell activation and innate immunity was identified (The Netherlands National Trial Register [NTR] NTR 2349, http://www.trialregister.nl/trialreg/index.asp).
Imaging of viral neuroinvasion in the zebrafish reveals that Sindbis and chikungunya viruses favour different entry routes

ABSTRACT Alphaviruses, such as chikungunya virus (CHIKV) and Sindbis virus (SINV), are vector-borne pathogens that cause acute illnesses in humans and are sometimes associated with neuropathies, especially in infants and elderly patients. Little is known about their mechanism of entry into the central nervous system (CNS), even for SINV, which has been used extensively as a model for viral encephalopathies. We previously established a CHIKV infection model in the optically transparent zebrafish larva; here we describe a new SINV infection model in this host. We imaged in vivo the onset and progression of the infection caused by intravenous SINV inoculation. Similar to that described for CHIKV, infection in the periphery was detected early and was transient, whereas CNS infection started at later time points and was persistent or progressive. We then tested the possible mechanisms of neuroinvasion by CHIKV and SINV. Neither virus relied on macrophage-mediated transport to access the CNS. CHIKV, but not SINV, always infects endothelial cells of the brain vasculature. By contrast, axonal transport was much more efficient with SINV than CHIKV, both from the periphery to the CNS and between neural tissues. Thus, the preferred mechanisms of neuroinvasion by these two related viruses are distinct, providing a powerful imaging-friendly system to compare mechanisms and prevention methods of encephalopathies. Summary: Imaging of neuroinvasion in zebrafish shows that chikungunya virus first infects the blood-brain barrier, whereas Sindbis virus relies on axonal transport.