Miracle-dz/UniFAR-FTUs huggingface dataset:
Marginalized kernels for biological sequences

MOTIVATION Kernel methods such as support vector machines require a kernel function between objects to be defined a priori. Several works have been done to derive kernels from probability distributions, e.g., the Fisher kernel. However, a general methodology to design a kernel is not fully developed. RESULTS We propose a reasonable way of designing a kernel when objects are generated from latent variable models (e.g., HMM). First of all, a joint kernel is designed for complete data which include both visible and hidden variables. Then a marginalized kernel for visible data is obtained by taking the expectation with respect to hidden variables. We will show that the Fisher kernel is a special case of marginalized kernels, which gives another viewpoint to the Fisher kernel theory. Although our approach can be applied to any object, we particularly derive several marginalized kernels useful for biological sequences (e.g., DNA and proteins). The effectiveness of marginalized kernels is illustrated in the task of classifying bacterial gyrase subunit B (gyrB) amino acid sequences.
Profiling Flavonoid Cytotoxicity in Human Breast Cancer Cell Lines: Determination of Structure-Function Relationships

Flavonoids have been shown to be cytotoxic to cancer cells. However, the mechanism of cytotoxicity has not been clearly defined. It has previously been reported that HER2/ERBB2, the estrogen receptor, progesterone receptor, and p53 were required for flavonoid induced cytotoxicity in breast cancer cell lines. We have used a panel of breast cancer cell lines, known to contain as well as be deficient in these signaling pathways, to screen fourteen different flavonoids. Comparing the cytotoxicity for all flavonoids allows us to determine if a structure-functional relationship exists between cytotoxicity and flavonoid, and if a particular signaling pathway is required for cytotoxicity. We show that several flavonoids are cytotoxic to all cell lines including primary mammary epithelial cells tested. The cytotoxic flavonoids are also able to inhibit Mitochondrial Outer Membrane Permeability while at the same time stimulate ATP levels whereas the non-cytotoxic flavonoids are not able to do this. We also show that both cytotoxic and non-cytotoxic flavonoids can transverse the cell membrane to enter MDA-MB-231 cells at different levels. Finally, all flavonoids regardless of their cytotoxicity were able to induce some form of cell cycle arrest. We conclude that for flavonoids to be strongly cytotoxic, they must possess the 2,3-double bond in the C-ring and we believe the cytotoxicity occurs through mitochondrial poisoning in both cancer and normal cells.
Wolbachia Infection Modifies the Profile, Shuttling and Structure of MicroRNAs in a Mosquito Cell Line

MicroRNAs (miRNAs) are small non-coding RNAs that play important roles in many biological processes such as development, cell signaling and immune response. Small RNA deep sequencing technology provided an opportunity for a thorough survey of the miRNA profile of a mosquito cell line from Aedes aegypti. We characterized the miRNA composition of the nucleus and the cytoplasm of uninfected cells and compared it with the one of cells infected with the endosymbiotic bacterium Wolbachia strain wMelPop-CLA. We found an overall increase of small RNAs between 18 and 28 nucleotides in both cellular compartments in Wolbachia-infected cells and identified specific miRNAs induced and/or suppressed by the Wolbachia infection. We discuss the mechanisms that the cell may use to shuttle miRNAs between the cytoplasm and the nucleus. In addition, we identified piRNAs that changed their abundance in response to Wolbachia infection. The miRNAs and piRNAs identified in this study provide promising leads for investigations into the host-endosymbiont interactions and for better understanding of how Wolbachia manipulates the host miRNA machinery in order to facilitate its persistent replication in infected cells.
Educating Families of Children Newly Diagnosed With Cancer: Insights of a Delphi Panel of Expert Clinicians From the Children’s Oncology Group

Parents/caregivers require specialized education in order to care for their child with a newly diagnosed cancer. Currently, no evidence-based guidelines exist to identify content essential for inclusion in patient/family education prior to a child’s initial discharge home; this study used Delphi methodology to obtain multidisciplinary consensus regarding essential content amongst pediatric oncology experts from the Children’s Oncology Group. Three questionnaire rounds were employed to identify essential content, evaluate the importance of the educational topics identified, and gain expert consensus regarding the final ranking of topics identified and whether or not each topic was considered mandatory for inclusion in education for newly diagnosed patients. Disease-specific topics were also identified for patients with leukemia, solid tumors, and central nervous system tumors. The results of this study provide, for the first time, multidisciplinary expert consensus regarding key content essential for inclusion in discharge education for newly diagnosed pediatric oncology patients.
Childhood IQ, Social Class, Deprivation, and Their Relationships with Mortality and Morbidity Risk in Later Life: Prospective Observational Study Linking the Scottish Mental Survey 1932 and the Midspan Studies

Objective To investigate how childhood mental ability (IQ) is related to mortality and morbidity risk, when socioeconomic factors are also considered. Methods Participants were from the Midspan studies conducted on adults in the 1970s; 938 Midspan participants were successfully matched with the Scottish Mental Survey 1932 in which children born in 1921 and attending Scottish schools on June 1, 1932, took a cognitive ability test. Mortality, hospital admissions, and cancer incidence in the 25 years after the Midspan screening were investigated in relation to childhood IQ, social class, and deprivation. Results The risk of dying in 25 years was 17% higher for each standard deviation disadvantage in childhood IQ. Adjustment for social class and deprivation category accounted for some, but not all, of this higher risk, reducing it to 12%. Analysis by IQ quartile showed a substantial increased risk of death for the lowest-scoring quarter only. Structural equation modeling indicated that the effect of childhood IQ on mortality was partly indirectly influenced by social factors. Cause-specific mortality or hospital admission showed that lower IQ was associated with higher risks for all cardiovascular disease and coronary heart disease. Cause-specific mortality or cancer incidence risk was higher with decreasing IQ for lung cancer. Conclusions Lower childhood IQ was related to higher mortality risk and some specific causes of death or morbidity. Childhood IQ may be considered as a marker for risk of death or illness in later life in similar and complementary ways to social class or deprivation category.
Learning to predict trajectories of cooperatively navigating agents

The problem of modeling the navigation behavior of multiple interacting agents arises in different areas including robotics, computer graphics, and behavioral science. In this paper, we present an approach to learn the composite navigation behavior of interacting agents from demonstrations. The decision process that ultimately leads to the observed continuous trajectories of the agents often also comprises discrete decisions, which partition the space of composite trajectories into homotopy classes. Therefore, our method uses a mixture probability distribution that consists of a discrete distribution over the homotopy classes and continuous distributions over the composite trajectories for each homotopy class. Our approach learns the model parameters of this distribution that match, in expectation, the observed behavior in terms of user-defined features. To compute the feature expectations over the high-dimensional continuous distributions, we use Hamiltonian Markov chain Monte Carlo sampling. We exploit that the distributions are highly structured due to physical constraints and guide the sampling process to regions of high probability. We apply our approach to learning the behavior of pedestrians and demonstrate that it outperforms state-of-the-art methods.
Bayesian Estimation of a DSGE Model with Inventories

This paper introduces inventories in an otherwise standard dynamic stochastic general equilibrium model. Based on U.S. data we estimate the parameters of our model using Bayesian methods. We find that inventories enter the Phillips curve as an additional and significant driving variable and make the inflation process less backward-looking. Moreover, our analysis reveals that the impulse responses and the contribution of structural shocks to variations in the observable variables change significantly when allowing for inventories. In contrast to previous studies, we can attest only a subordinated role to technology shocks in explaining the forecast error variance of real variables.
A Program of Yersinia enterocoliticaType III Secretion Reactions Is Activated by Specific Signals

ABSTRACT Successful establishment of Yersinia infections requires the type III machinery, a protein transporter that injects virulence factors (Yops) into macrophages. It is reported here that theYersinia type III pathway responds to environmental signals by transporting proteins to distinct locations. Yersinia enterocolitica cells sense an increase in extracellular amino acids (glutamate, glutamine, aspartate, and asparagine) that results in the activation of the type III pathway. Another signal, provided by serum proteins such as albumin, triggers the secretion of YopD into the extracellular medium. The third signal, a decrease in calcium concentration, appears to be provided by host cells and causesY. enterocolitica to transport YopE and presumably other virulence factors across the eukaryotic plasma membrane. Mutations in several genes encoding regulatory molecules (lcrG,lcrH, tyeA, yopD,yopN, yscM1, andyscM2) bypass the signal requirement of the type III pathway. Together these results suggest that yersiniae may have evolved distinct secretion reactions in response to environmental signals.
A Multi-scale Phase Method for Content Based Image Retrieval

In this paper, we present a method using phase features for content based image retrieval (CBIR). Two related key issues of CBIR are feature extraction and similarity measure. However, most traditional methods treat them respectively and prevent further performance improvement. The method proposed here is based on the multi-scale local phase feature (MLPF) and local weighted phase correlation which combines the above two issues together by phase. And phase data is often locally stable with respect to noise, scale change and common illumination change. Moreover, we implement steerable filters to obtain rotation invariant. Finally, experiments have been conducted on image retrieval to show the effectiveness of the proposed method.
An exploratory study of the effect of animal-assisted therapy on nonverbal communication in three schizophrenic patients

Abstract Animal-assisted therapy has been used in the treatment and rehabilitation of several physical and mental disorders, but its effectiveness for chronic schizophrenic patients has been evaluated in only a few studies. Our purpose was to introduce animal-assisted group therapy in the rehabilitation of severely disabled chronic schizophrenic patients, in order to enhance their communication skills. Five patients diagnosed with schizophrenia (three females, two males, ages ranging from 32 to 71 years), four human members (one therapist, one co-therapist, and the owners of the dogs) and two therapy dogs (a five-year-old, female Boxer and a two-year-old, female Bichon Frise) participated in the therapy on a weekly basis, for a six-month period. The therapy was oriented toward improving non-specific (i.e., general well-being) and specific (i.e., communication patterns) areas of the patients' daily activities. The outcome measure was the change in the patients' nonverbal communication, as measured by an analysis of standardized, video-recorded scenarios registered at the beginning of the therapy, and six month's later, at the end of it. Because two patients completed less than half of the sessions, we analyzed the data of only three patients. Positive changes occurred in some post-treatment nonverbal parameters compared with pre-treatment parameters. All three patients improved in the usage of space during communication, while partial improvement in other domains of nonverbal communication (anatomy of movements, dynamics of gestures, regulator gestures) was also observed. Animal-assisted therapy can improve certain aspects of nonverbal communication in schizophrenic patients. The results of our exploratory study show a need for further investigation, using controlled studies with a larger number of patients.
Predicting Successful Global Online Group Projects from Online Discussion

This study aims to analyze 13 collaborative teams in a global web-based student design project in terms of participation activity levels, participation characteristics and the use of the three types of communication: cognitive, emotional, and social. Furthermore, it examines the association between 1) participation and communication characteristics and 2) design outcomes, in order to identify potential key factors that predict successful global online group projects. The analysis results indicate that 1) the teams that have a higher percentage of students with language barriers tend to post longer messages; 2) the teams that use a higher frequency of use of cognitive, social, and emotional words tend to post a higher number of messages; 3) the teams that have potential success factors, such as higher student participation levels, students' more evenly distributed participation patterns and a higher proportion of female (or male) students, are not necessarily associated with more successful team outcomes.
Virus Adaptation and Treatment The impact of hypoxia on oncolytic virotherapy

Correspondence: Z Sheng Guo University of Pittsburgh Cancer Institute, 5117 Centre Avenue, Suite 1.46, Pittsburgh, PA 15213, USA Tel +1 412 623 7711 Fax +1 412 623 7709 Email guozs@upmc.edu Abstract: The hypoxic tumor microenvironment plays significant roles in tumor cell metabolism and survival, tumor growth, and progression. Hypoxia modulates target genes in target cells mainly through an oxygen-sensing signaling pathway mediated by hypoxia-inducible factor of transcription factors. As a result, hypoxic tumor cells are resistant to conventional therapeutics such as radiation and chemotherapy. Oncolytic virotherapy may be a promising novel therapeutic for hypoxic cancer. Some oncolytic viruses are better adapted than others to the hypoxic tumor environment. Replication of adenoviruses from both groups B and C is inhibited, yet replication of herpes simplex virus is enhanced. Hypoxia seems to exert little or no effect on the replication of other oncolytic viruses. Vaccinia virus displayed increased cytotoxicity in some hypoxic cancer cells even though viral protein synthesis and transgene expression were not affected. Vesicular stomatitis virus replicated to similar levels in both hypoxic and normoxic conditions, and is effective for killing hypoxic cancer cells. However, vesicular stomatitis virus and reovirus, but not encephalomyocarditis virus, are sensitive to elevated levels of hypoxia-inducible factor-1α in renal cancer cells with the loss of von Hippel–Lindau tumor suppressor protein, because elevated hypoxia-inducible factor activity confers dramatically enhanced resistance to cytotoxicity mediated by vesicular stomatitis virus or reovirus. A variety of hypoxia-selective and tumor-type-specific oncolytic adenoviruses, generated by incorporating hypoxia-responsive elements into synthetic promoters to control essential genes for viral replication or therapeutic genes, have been shown to be safe and efficacious. Hypoxic tumor-homing macrophages can function effectively as carrier cells to deliver an oncolytic adenovirus to the hypoxic/necrotic areas of the tumor. It is envisioned that further improved oncolytic viruses will be highly effective against hypoxic tumor, especially when combined with other therapeutic regimens such as immunotherapy, radiation therapy, and/or chemotherapy.
DEMOCRACY REMIXED: BLACK YOUTH AND THE FUTURE OF AMERICAN POLITICS

is not provided with the more clear-cut exposition of patterns that would have been yielded had a more systematic comparative approach been used in which information on each case or country is tabulated. Most readily the book could have been extended to deal with the Australasian extension of Anglo-American indigenous situations, because their circumstances and context are broadly similar and their literatures are intertwined. Extension to the rather more different and/or complex indigenous situations of Asian, Africa and even Europe would have been a much larger task. Perhaps, too, the book is too drily documentary based so that the social circumstances of the people involved seldom breaks through, nor is the institutional arrangements of the international legal arena fleshed out, let alone how the institutions of the host settler societies affect their fate. Engel shows that several polarities are oddly linked, as in a Mobius strip. Highly localized indigenous groups appeal for assistance and support from international actors and despite their low technology level deploy the Internet. Diversity and uniqueness are pursued in the languages and styles of the West. Emphases on culture and the economic intertwine. Global and local fascinatingly blend. These complexly linked polarities give her narrative a haunting grandeur.
Blood vessel feature description for detection of Alzheimers disease

We describe how image analysis can be used to detect the presence of Alzheimer's disease. The data are images of brain tissue collected from subjects with and without Alzheimer's disease. The analysis concentrates on the shape and structure of the blood vessels which are known to be affected by amyloid beta, whose drainage is affected by Alzheimer's disease. The structure is analysed by a new approach which measures the Influence of the blood vessels' branching structures. Their density and tortuosity are analysed in conjunction with a boundary description derived using Fourier descriptors. These measures form a feature vector which is derived from the images of brain tissue, and the discrimination capability shows that it is possible to detect the presence of Alzheimer's disease using these measures and in an automated way. These measures also show that shape information is influenced by the vessels' branching structure, as known to be consistent with Alzheimer's disease evolution.
Lamin A/C Haploinsufficiency Modulates the Differentiation Potential of Mouse Embryonic Stem Cells

Background Lamins are structural proteins that are the major determinants of nuclear architecture and play important roles in various nuclear functions including gene regulation and cell differentiation. Mutations in the human lamin A gene cause a spectrum of genetic diseases that affect specific tissues. Most available mouse models for laminopathies recapitulate disease symptoms for muscle diseases and progerias. However, loss of human lamin A/C also has highly deleterious effects on fetal development. Hence it is important to understand the impact of lamin A/C expression levels on embryonic differentiation pathways. Methodology and Principal Findings We have investigated the differentiation potential of mouse embryonic stem cells containing reduced levels of lamin A/C by detailed lineage analysis of embryoid bodies derived from these cells by in vitro culture. We initially carried out a targeted disruption of one allele of the mouse lamin A/C gene (Lmna). Undifferentiated wild-type and Lmna+/− embryonic stem cells showed similar expression of pluripotency markers and cell cycle profiles. Upon spontaneous differentiation into embryoid bodies, markers for visceral endoderm such as α-fetoprotein were highly upregulated in haploinsufficient cells. However, neuronal markers such as β-III tubulin and nestin were downregulated. Furthermore, we observed a reduction in the commitment of Lmna+/− cells into the myogenic lineage, but no discernible effects on cardiac, adipocyte or osteocyte lineages. In the next series of experiments, we derived embryonic stem cell clones expressing lamin A/C short hairpin RNA and examined their differentiation potential. These cells expressed pluripotency markers and, upon differentiation, the expression of lineage-specific markers was altered as observed with Lmna+/− embryonic stem cells. Conclusions We have observed significant effects on embryonic stem cell differentiation to visceral endoderm, neuronal and myogenic lineages upon depletion of lamin A/C. Hence our results implicate lamin A/C level as an important determinant of lineage-specific differentiation during embryonic development.
The education of Australian school students with the most severe intellectual disabilities: Where have we been and where could we go?: A discussion primer

The education of Australian students with the most severe intellectual disabilities continues to present substantial challenges to policymakers, practitioners and families. These are complex and involve philosophy and ethics generally, and curriculum assessment and pedagogy specifically. In light of the various phases of development for an Australian Curriculum, the authors advocate for broad-based debate about the nature of education for these students. To prime discussion, this paper looks at the past, present and possible futures with respect to the education of Australian students with the most severe intellectual disabilities.
A Hybrid System for Prediction of Protein Subcellular Localization

Protein subcellular localization prediction is important to functional annotation of protein. In this study, a hybrid system based on the sorting mechanism of protein was proposed to predict protein subcellular localization. At first, an unknown protein sequence was divided into two sub-sequences at certain position, then features were extracted from them and combined into a fusion feature vector to describe the whole protein sequence. Secondly, an optimal sub-classifier was searched out to discriminate each kind of protein from the others through iterative searching strategy. Finally, all of the sub-classifiers were combined into a hybrid system to predict subcellular localization of unknown protein. Experimental results on two public datasets showed that our hybrid system is an effective way for the prediction of protein subcellular localization, and it has higher accuracy than others.