Miracle-dz/UniFAR-FTUs huggingface dataset:
AUTO-EPIZOISM IN SOUTH AFRICAN HYDROIDS

The term 'auto-epizoism' has been coined for species which live epizootically on the same or closely related species. Examples from South African Hydroida are described. In all of these some form of stunting occurs. The origin of certain obligatory epizoites can be postulated by extrapolating from the stunted form. It is suggested that this process may have evolutionary significance and present a parallel to the evolution of parasitism. Two epizootic species previously allocated to Zygophylax are transferred to Hydrodendron in the light of further knowledge, namely H. cornucopia and H. enigmatica (=gracilis). It is a well-known phenomenon that certain species of hydroids live epizootically on other animals and sometimes show a marked host preference. Examples such as Hydractinia on hermit-crabs, Proboscidactyla (Lar) on tubicolous polychaets and Merona on bivalve molluscs spring to mind. There are also various small species which live epizootically on other hydro ids; to mention only a few, species of Campanularia, Hebella and Filellum. Generally this is a chance association, the smaller species simply using the larger one as a favourable substratum, but occasionally there appears to be some host selection; for instance, in South Africa Campanularia laminacarpa MILLARD, 1966, occurs only on Thyroscyphus aequalis WARREN, 1908, and Hebellafurax MILLARD, 1957, only on Plumularians, mainly Lytocarpus . filamentosus (LAMARCK, 1816). Even more interesting and curious are certain forms which are restricted to hosts of the same or closely related species. For these the term 'auto-epizoism' has been coined. Examples are found among the South African hydroid fauna and will be described in the following pages and their significance discussed. The first three examples are species of Gymnangium (Plumulariidae, Aglaopheniinae ). In all of them the normal form of the species has an erect, pinnate stem bearing a double series of hydrocladia, which in turn bear the hydrothecae. The epizootic form occurs either on the same species or on another member of the Aglaopheniinae and usually has no upright stem at all, but instead a number of solitary hydrocladia arising directly from a hydrorhiza creeping on the stem of the host. In none of these three have gonothecae been found on the epizootic form. Gymnangium arcuatum (LAMOUROUX, 1816) is a common species round the South African coast, extending from South West Africa on the west to Natal on the east, and
Gender Differences in Frontotemporal Lobar Degeneration (FTLD) Support an Estrogenic Model of Delayed Onset

Gender differences in frontotemporal lobar degeneration (FTLD) have been reported in the literature but not well characterized or explored. In the present work, we propose that steroid hormone estrogens delay the onset of FTLD in pre-menopausal women compared to age equivalent men, and may provide neuroprotection in the early postmenopausal period. We present a model wherein estrogens serve a regulatory role in attenuating the microglia conversion from the benign to active form in response to cell stress that might otherwise trigger an inflammatory response. Via microglia stabiliza- tion, estrogens preserve the homeostasis of both the ubiquitin-proteosome degradation system and lysosome-autophagy recycling system. Both systems have been implicated in the genetic forms of FTLD, with the latter system recognized to be associated with the majority of them. estrogen but not progesterone shown to attenuate microglial superoxide release and phagocytotic activity as well as iNOS expression These effects are transmitted through an estrogen receptor-dependent activation of the MAP-kinase signaling system. Using a transient focal ischemia animal model, investigators that estrogen and progesterone prevent the hypoxia-induced attrac-tion and activation of local microglia and their morphological transition into an activated phe-notype in the cortical penumbra [ 109 ]. The reduced stimulation of microglia is considered to result from diminished cytokine and interleukin expression and release in local astroglia, consequent to the close concerted communication between these two glial cell types during tissue stress. Focal ischemic mouse model experiments further diminution of the penumbra of estrogen/progesterone-treated animals, along with reduction in chemokine levels, central microglia, and recruited monocytes. Ischemic mouse model data are confirmed by several other studies, which have demonstrated that these steroid hormones affect local cytokine production during brain inflammation in microglia [53, 76, 110 ], in astroglia [ 111 , 112 ], and in unidentified cell types [ 113
Phytochemical and antimicrobial activity screening of Gnetum africanum leaf extracts

The menace of antibiotic resistance and the antecedent evolution of innocuous microbes into superbugs is an epidemic of global concern. This study investigated the antimicrobial activity of water and ethanol extracts of Gnetum africanum leaves, a commonly consumed vegetable in most parts of Sub-Saharan Africa, on Staphylococcus aureus, Escherichia coli and Candida albicans. Leaves of G. africanum were extracted with water and ethanol using cold maceration technique; standardized chemical tests were employed for phytochemical screening and the disc-diffusion method used for antimicrobial analysis. Findings indicate that both extracts had dose-dependent inhibitory effect on the growth of S. aureus, with maximum inhibition zones of 13.30 and 13.10 mm at 200 mg/ml for aqueous and ethanolic extracts, respectively. For C. albicans, the ethanol extract proved to be more potent with a maximum inhibition zone of 13.30 mm at extract dose of 100 mg/ mL. However, the extracts did not show any activity against E. coli, suggesting its impotence against gram negative bacteria. The observed antimicrobial activity may be as a consequence of the rich phytochemistry of the leaves, as preliminary phytochemical screening revealed the leaves to contain saponin, flavonoid, cardiac glycoside, alkaloids, tannin and anthraquinones. The findings of this study further reinforces the importance of G. africanum leaves in traditional healthcare practice and its use in culinary. Further investigation is however needed to isolate and purify the bioactive antimicrobial principles for potential development into generic antimicrobials.
Are data on missed nursing care useful for nursing leaders? The RN4CAST@IT cross-sectional study.

AIM To describe nurses' reported missed nursing care activities among hospitalized adult patients medical and surgical wards and explore gaps in service provision. BACKGROUND In 2015, Italy replicated the RN4CAST study, which heralded the exposition of missed care as an international phenomenon. In Italy nurse-patient workload is high, with high levels of burnout and dissatisfaction reported, all factors associated with missed care. METHODS A cross-sectional study (n= 3,590) was conducted using the 13-item online Task Left Undone Tool aimed at collecting data on missed nursing care. RESULTS The frequency of omission of activities ranged between 7% and 50%. There were significant differences between morning, afternoon and night shifts and the various clinical settings. Oral care was the most frequently missed care activity. CONCLUSIONS This study takes step forward in identifying and reducing missed care on medical and surgical wards, both in Italy but also internationally, which needs to take into account the specific organizational characteristics of each setting. IMPLICATIONS FOR NURSING MANAGERS Although more essential activities are missed less frequently, much is known about the relational deficits such as information giving, education, communication and discharge advice, which managers ought to spearhead through local initiatives to improve these practices.
Strategic Information Transmission Models Preliminary Lecture Notes

1 Cheap Talk 3 1.1 Model Setting . 3 1.2 A Motivating Example . 4 1.3 Continuous State Space . 8 1.4 Enhancing Communication . 11 1.4. 1 Different Communication Procedures . 12 1.4. 2 Multiple Senders . 15 1.5 Optimal Communication Mechanism . 16
Eating Disorder Risk and Common Mental Disorders in British Servicewomen: A Cross-Sectional Observational Study

ABSTRACT Purpose Servicewomen are at increased risk of common mental disorders compared with servicemen and their female civilian counterparts. The prevalence of eating disorder risk and common mental disorders, and associated risk factors in British servicewomen are poorly understood. Methods All women younger than 45 yr in the UK Armed Forces were invited to complete a survey about demographics, exercise behaviors, eating behaviors, and common mental disorders. Results A total of 3022 women participated; 13% of participants were at high risk of an eating disorder based on Brief Eating Disorder in Athletes Questionnaire and Female Athlete Screening Tool scores. Twenty-five percent of participants had symptoms of anxiety (seven-item Generalized Anxiety Disorder Assessment score ≥10), and 26% had symptoms of depression (nine-item Patient Health Questionnaire score ≥10). Older age was associated with a lower risk, and heavier body mass was associated with a higher risk, of eating disorders (P ≤ 0.043). Older age and higher rank were associated with a lower risk of symptoms of anxiety and depression (P ≤ 0.031), and a heavier body mass was associated with a higher risk of symptoms of depression (P ≤ 0.012). Longer habitual sleep duration was associated with a lower risk of eating disorders and symptoms of anxiety and depression (P ≤ 0.028). A higher volume of field exercise was associated with a lower risk, and a higher volume of military physical training and personal physical training was associated with a higher risk, of eating disorders (P ≤ 0.024). Job role and deployment history were not associated with any outcome. Conclusions Sleeping and training habits provide potential novel targets for exploring how common mental disorders can be managed in British servicewomen.
Computational Modeling Reveals that a Combination of Chemotaxis and Differential Adhesion Leads to Robust Cell Sorting during Tissue Patterning

Robust tissue patterning is crucial to many processes during development. The "French Flag" model of patterning, whereby naïve cells in a gradient of diffusible morphogen signal adopt different fates due to exposure to different amounts of morphogen concentration, has been the most widely proposed model for tissue patterning. However, recently, using time-lapse experiments, cell sorting has been found to be an alternative model for tissue patterning in the zebrafish neural tube. But it remains unclear what the sorting mechanism is. In this article, we used computational modeling to show that two mechanisms, chemotaxis and differential adhesion, are needed for robust cell sorting. We assessed the performance of each of the two mechanisms by quantifying the fraction of correct sorting, the fraction of stable clusters formed after correct sorting, the time needed to achieve correct sorting, and the size variations of the cells having different fates. We found that chemotaxis and differential adhesion confer different advantages to the sorting process. Chemotaxis leads to high fraction of correct sorting as individual cells will either migrate towards or away from the source depending on its cell type. However after the cells have sorted correctly, there is no interaction among cells of the same type to stabilize the sorted boundaries, leading to cell clusters that are unstable. On the other hand, differential adhesion results in low fraction of correct clusters that are more stable. In the absence of morphogen gradient noise, a combination of both chemotaxis and differential adhesion yields cell sorting that is both accurate and robust. However, in the presence of gradient noise, the simple combination of chemotaxis and differential adhesion is insufficient for cell sorting; instead, chemotaxis coupled with delayed differential adhesion is required to yield optimal sorting.
Elsevier Editorial System(tm) for Journal of Affective Disorders Manuscript Draft Title: Abnormal Amplitude Low-frequency Oscillations in Medication-naive, First-episode Patients with Major Depressive Disorder: a Resting-state Fmri Study

Background: Recent resting-state fMRI studies on major depressive disorder (MDD) have found altered temporal correlation between low-frequency oscillations (LFOs). However, changes on the amplitudes of these LFOs remain largely unknown. Methods: Twenty-two medication-naive, first-episode patients with MDD and 19 age-, sex-, education-matched healthy controls were recruited. Resting-state fMRI was obtained by using a gradient-echo echo-planar imaging sequence and the fractional amplitude of low-frequency fluctuations (fALFF) was calculated to investigate the amplitude of LFOs in the resting state. Results: Compared with control subjects, patients with MDD showed significantly decreased fALFF in right cerebellum posterior lobe, left parahippocampal gyrus and right middle frontal gyrus and increased fALFF in left superior occipital gyrus/cuneus (p<0.05, corrected for multiple comparisons). Further receiver operating characteristic curves (ROC) analyses suggested that the alterations of fALFF in these regions might be used as markers to classify patients with MDD from healthy controls. Conclusions: These findings indicated LFOs abnormalities in MDD and the fALFF analysis might be a potential approach in further exploration of this disorder.
Information Integration using Entity-Relations across Bioinformatics Sources

Project Summary The functional analysis of genes using genomes is a major research issue in modern biology. Functional analysis is the study of how a biological entity is functionally related to other biological entities. Typical questions might include: does gene X encode chemical Y in organism Z? Does gene X regulate behavior B? Which other genes regulate the same behavior in other organisms? Information integration is necessary to perform successful functional analysis, since biologists must compare data from multiple sources of different types to answer such questions. Such data integration for functional analysis is still extremely difficult. It is carried out largely by hand, in a labor intensive and error prone process, in literature citations and genome annotations. Expert database curators can tag the necessary entities and relations, but the scale of such human efforts is far less than even the current scale of the available information. A typical search query for bioinformatics sources today is at the level of words and phrases. This is not a high enough level conceptually to enable the comparisons across sources necessary for functional analysis. Most bioin-formatics research is focused upon this data level, trying to find patterns directly within the genome sources such as sequences or within the biomedical literature. Most of the rest of bioinformatics research is focused upon jumping directly to the knowledge level, trying to find patterns using hand-encoded special purpose knowledge. Expert users of expert systems can easily retrieve facts, but the human labor involved in developing such expert systems limits the number of such systems to a small fraction of the available biological knowledge. Information integration can support search queries at far more deeper level than data integration across a far broader set of sources than knowledge integration. That is, information management aims to be close to as scalable as database management, while at the same time being as close to semantic as knowledge management. There is a very wide range of user needs in this middle ground of information in-between data and knowledge. The same technologies will be applicable across many other subject areas in science and beyond. The information level for text documents is focused around entities, in-between words for data and facts for knowledge. That is, we will base our technologies upon automatic techniques to extract phrases from general texts and to tag the entities represented by these phrases. For biology, the entities are objects …
NetSchd : The Virtue of Channel and Load Awareness in Alleviating Cellular Congestion

Cellular networks, while being provisioned according to the peak demand, usually experience large fluctuations in both traffic load and channel conditions. Embracing these two dimensions of dynamics allows us to exploit the delay-tolerance of data traffic to alleviate network congestion, and thus reduce the peak. Existing approaches in the literature have considered how to schedule delay-tolerant traffic based on either load-variations or channel-variations alone. However, loadawareness and channel-awareness have never been studied jointly, partly due to the high complexity of the resulting network-wide scheduling problem. Further, the relative performance of the different approaches needs to be compared in a unified framework. Our first contribution in this paper is to develop an optimal solution to the problem of jointly considering load-and channel-awareness to reduce peak demand subject to deadline constraints. We also present a distributed algorithm that is practical to implement. Second, we use trace-driven simulations to carefully compare the performance of the load-only, channel-only, and joint approaches. Our simulation studies reveal the critical role of channel-awareness in wireless systems and the virtue of the joint approach, especially in multi-cell scenarios. To the best of our knowledge, this paper is the first work in the literature that studies loadand channel-awareness in a unified and rigorous manner. September 5, 2013 DRAFT
Eurasip Journal on Applied Signal Processing Distributed Coding of Highly Correlated Image Sequences with Motion-compensated Temporal Wavelets

— This paper discusses robust coding of visual content for a distributed multimedia system. We investigate how scene analysis at the decoder can improve the coding efficiency. The distributed system encodes independently two correlated video signals and reconstructs them jointly at a central decoder. The video signals are captured from a dynamic scene where each signal is temporally decorrelated by a motion-compensated Haar wavelet. The two cameras operate independently, however, the central decoder is able to exploit the coded information from all cameras to achieve the best reconstruction of the correlated video signals. The coding system utilizes nested lattice codes for the transform coefficients and exploits side information at the decoder. In addition, a disparity analysis of the first image pair of the sequences is performed at the decoder. The efficiency of the decoder is improved by disparity compensation of one video signal at the decoder. When compared to decoding without side information, decoding of the quantized transform coefficients with side information reduces bit-rate. Additional bit-rate savings can be obtained with disparity compensation at the decoder and decoding of transform coefficients with side information. Further, we address the theoretical problem of distributed coding of video signals in the presence of correlated video side information. The correlated video signals are disparity compensated and originate from cameras that monitor the same scene from different view points. We utilize a motion-compensated spatiotemporal transform to decorrelate the video signals. One camera signal will provide the disparity-compensated side information to improve the coding of the second camera signal. We derive the optimal motion-compensated spatiotemporal transform for video coding with video side information at high rates. For our video signal model, we can show that the motion-compensated Haar wavelet is an optimal transform at high rates. Given the correlation of the video side information, we also investigate the theoretical bit-rate reduction for the distributed coding scheme. Interestingly, the efficiency of multi-view side information is dependent on the level of temporal decorrelation: For a given correlation-SNR of the side information, bit-rate savings due to side information are decreasing with improved temporal decorrelation.
Smart albumin-loaded Rose Bengal and doxorubicin nanoparticles for breast cancer therapy

Abstract Objective: To synthesise HSA-RB-DOX nanoparticles, measure its characteristics and preliminarily evaluate its anti-cancer effects. Methods: Doxorubicin (DOX) and Rose Bengal (RB) were co-delivered using albumin as a carrier. HSA-RB-DOX nanoparticles were prepared by RB-induced self-assembly of albumin. Its characteristics were measured and anti-cancer effects were tested in MCF-7 cells and tumour-bearing mice. Results: HSA-RB-DOX nanoparticle with a mean size of 42 nm was stable in different medium and behaved controlled release characteristic. It was well took in MCF-7 cells and inhibited MCF-7 cells proliferation by inducing reactive oxygen species (ROS) production. It retained a much higher blood concentration up to 12 h and accumulated more in tumour tissues. In tumour-bearing mice, HSA-RB-DOX nanoparticles inhibited tumour growth and even decreased its volume from 100 to 50 mm3, with barely no influence on body weight. Conclusions: HSA-RB-DOX nanoparticles may be potentially used for enhanced treatment of breast cancer.
Formal Methods for Exact Analysis of Approximate Circuits

Approximate circuits are digital circuits that are intentionally designed in such a way that the specification is violated in terms of functionality in order to obtain some improvements in power consumption, performance or area, in comparison with fully functional circuits. To design the approximate circuits, the synthesis tools rely on the availability of a procedure checking, whether the synthesized circuits meet a specification and/or provides information about circuit quality. Compared to the traditional circuit design flow, the nature of the approximate circuits involves replacing the strict functional equivalence checking with a more advanced approach that enables us to quantify or guarantee the degree of similarity. The most common technique is to employ a circuit simulator for analysing responses for all input vectors. This approach allows us to simultaneously perform checking and quality assessment, but the exhaustive enumeration of the input vectors is tractable only for a small number of inputs. To avoid excessive run-times, a subset of all possible input vectors is typically used for complex circuits. This causes us, however, to lose the ability to guarantee that the quality of the synthesized circuits is within an acceptable range given in the specification. The main goal of this paper is to show how to adopt formal methods such as binary decision diagrams and satisfiability solvers for exhaustive analysis of approximate circuits without explicit enumeration of all input vectors. We survey the methods for exact computation of the most important error parameters used in the context of approximate computing, propose improved algorithms and provide a detailed analysis of their performance. The methods are benchmarked on a large set of key approximate circuits consisting of nearly 2,000 unique arithmetic instances with 8-, 12-, 16-, and 32-bit operands which helps us to identify the best algorithm and method for computation of a desired error parameter.