Miracle-dz/UniFAR-FTUs huggingface dataset:
Dendritic Cell Infiltration in Colon Cancer

We quantitatively evaluated dendritic cell (DC) infiltration in primary colorectal cancers from 44 patients and metastatic colorectal tumors from 13 patients using immunohistochemistry for the DC marker CD83, HLA-DR, and the DC activation molecules CD40 and CD86. Nearly all CD83+ cells were also HLA-DR+, CD40+, and CD86+, indicating that the DCs that infiltrate colon cancer in vivo express the activation and costimulatory molecules associated with a mature DC phenotype. The density of DCs in colorectal cancer primaries was three times lower than that seen in normal colonic mucosa (0.29 versus 0.84 CD83+ cells/ high-power field (hpf), p < 0.001). Dendritic cells were rarely observed in metastatic tumors: DC density in metastases was sixfold lower than in colorectal primary tumors (0.05 versus 0.29 CD83+ cells/hpf, p < 0.001). Because cytokines have been shown, in vitro, to exert potent effects on DCs, we also evaluated the relationship between intratumor DC density and the expression of cytokines by tumor-infiltrating lymphocytes (TILs) and tumor cells. Expression of interleukin-10 and transforming growth factor &bgr; by either TIL or tumor cells was not associated with decreased DC density or decreased expression of CD40 or CD86 on DCs. Tumor expression of vascular endothelial growth factor was associated with a more than twofold increase in DC density (p = 0.01). Patients who had a high proportion of TILs expressing tumor necrosis factor (TNF) had a greater intratumor mature DC density than patients with a low proportion of TNF + TIL (0.54 versus 0.21 CD83+ cells/hpf, p < 0.01).
Hover widgets: using the tracking state to extend the capabilities of pen-operated devices

We present Hover Widgets, a new technique for increasing the capabilities of pen-based interfaces. Hover Widgets are implemented by using the pen movements above the display surface, in the tracking state. Short gestures while hovering, followed by a pen down, access the Hover Widgets, which can be used to activate localized interface widgets. By using the tracking state movements, Hover Widgets create a new command layer which is clearly distinct from the input layer of a pen interface. In a formal experiment Hover Widgets were found to be faster than a more traditional command activation technique, and also reduced errors due to divided attention.
A retrospective clinicopathological study of 59 osteogenic sarcoma of jaw bone archived in a stomatology unit.

OBJECTIVES To determine the clinicopathological features of osteogenic sarcomas of the mandible and maxilla. MATERIALS AND METHODS A retrospective study was carried out on all osteosarcoma from the jaw diagnosed in the Stomatology Unit, Institute for Medical Research, Kuala Lumpur from 1967 to 2008. All data regarding the age at presentation, gender, race, clinical presentation, radiographical findings and diagnoses were retrieved from computerized records. RESULTS There were 59 cases (36 males and 23 females) with ages ranging from 7 to 68 years. The patients comprised 28 Malays, 16 Chinese, 2 Indians and 13 of other ethnicity. Forty cases involved the mandible and 19 the maxilla. The main complaint was painless or painful bony swelling. Nine cases presented with numbness of the associated region. Four patients had history of prior radiotherapy. The radiographic findings which varied from radiolucent to radiopaque lesions were mentioned in only 26 cases. Histologically, the majority (30) were osteoblastic, 19 chondroblastic, 6 fibroblastic and 4 telangiectatic in type. No small cell type osteosarcoma was identified. CONCLUSION Osteogenic sarcoma of the jaws is a rare malignant bone tumour. Over 40 years, there were only 59 cases diagnosed by our institution and to date this is the first report of jaw osteosarcoma in Malaysia.
Heritable strategies for controlling insect vectors of disease

Mosquito-borne diseases are causing a substantial burden of mortality, morbidity and economic loss in many parts of the world, despite current control efforts, and new complementary approaches to controlling these diseases are needed. One promising class of new interventions under development involves the heritable modification of the mosquito by insertion of novel genes into the nucleus or of Wolbachia endosymbionts into the cytoplasm. Once released into a target population, these modifications can act to reduce one or more components of the mosquito population's vectorial capacity (e.g. the number of female mosquitoes, their longevity or their ability to support development and transmission of the pathogen). Some of the modifications under development are designed to be self-limiting, in that they will tend to disappear over time in the absence of recurrent releases (and hence are similar to the sterile insect technique, SIT), whereas other modifications are designed to be self-sustaining, spreading through populations even after releases stop (and hence are similar to traditional biological control). Several successful field trials have now been performed with Aedes mosquitoes, and such trials are helping to define the appropriate developmental pathway for this new class of intervention.
Direct Visual Odometry in Low Light Using Binary Descriptors

Feature descriptors are powerful tools for photometrically and geometrically invariant image matching. To date, however, their use has been tied to sparse interest point detection, which is susceptible to noise under adverse imaging conditions. In this letter, we propose to use binary feature descriptors in a direct tracking framework without relying on sparse interest points. This novel combination of feature descriptors and direct tracking is shown to achieve robust and efficient visual odometry with applications to poorly lit subterranean environments.
Feature sensitive mesh segmentation

Segmenting meshes into natural regions is useful for model understanding and many practical applications. In this paper, we present a novel, automatic algorithm for segmenting meshes into meaningful pieces. Our approach is a clustering-based top-down hierarchical segmentation algorithm. We extend recent work on feature sensitive isotropic remeshing to generate a mesh hierarchy especially suitable for segmentation of large models with regions at multiple scales. Using integral invariants for estimation of local characteristics, our method is robust and efficient. Moreover, statistical quantities can be incorporated, allowing our approach to segment regions with different geometric characteristics or textures.
Monocular road segmentation using slow feature analysis

In this paper a novel approach for road detection with a monocular camera is introduced. We propose a two step approach, combining a patch-based segmentation with additional boundary detection. We use Slow Feature Analysis (SFA) which leads to improved appearance descriptors for road and non-road parts on patch level. From the slow features a low order feature set is formed which is used together with color and Walsh Hadamard texture features to train a patch-based GentleBoost classifier. This allows extracting areas from the image that correspond to the road with a certain confidence. Typically the border regions between road and non-road have the highest classification error rates, because the appearance is hard to distinguish on the patch level. Therefore we propose a post-processing step with a specialized classifier applied to the boundary region of the image to improve the segmentation results. In order to evaluate the quality of road segmentation we propose an application-based quality measurement applying an inverse perspective mapping on the image to obtain a Birds Eye View (BEV). The advantage of this approach is that the important distant parts and boundaries of the road in the real world, which are only a low fraction in the perspective image, can be assessed in this metric measure significantly better than on the pixel level. In addition, we estimate the driving corridor width and boundary error, because for Advanced Driver Assistant Systems (ADAS) metric information is needed. For all evaluations in different road and weather conditions, our system shows an improved performance of the two step approach compared to the basic segmentation.
Covariance-Matrix Modeling and Detecting Various Flooding Attacks

This paper presents a covariance-matrix modeling and detection approach to detecting various flooding attacks. Based on the investigation of correlativity changes of monitored network features during flooding attacks, this paper employs statistical covariance matrices to build a norm profile of normal activities in information systems and directly utilizes the changes of covariance matrices to detect various flooding attacks. The classification boundary is constrained by a threshold matrix, where each element evaluates the degree to which an observed covariance matrix is different from the norm profile in terms of the changes of correlation between the monitored network features represented by this element. Based on Chebyshev inequality theory, we give a practical (heuristic) approach to determining the threshold matrix. Furthermore, the result matrix obtained in the detection serves as the second-order features to characterize the detected flooding attack. The performance of the approach is examined by detecting Neptune and Smurf attacks-two common distributed Denial-of-Service flooding attacks. The evaluation results show that the detection approach can accurately differentiate the flooding attacks from the normal traffic. Moreover, we demonstrate that the system extracts a stable set of the second-order features for these two flooding attacks
Comparison Between Linear and Non-parametric Regression Models for Genome-Enabled Prediction in Wheat

In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The linear models were linear on marker effects and included the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B. The non-linear models (this refers to non-linearity on markers) were reproducing kernel Hilbert space (RKHS) regression, Bayesian regularized neural networks (BRNN), and radial basis function neural networks (RBFNN). These statistical models were compared using 306 elite wheat lines from CIMMYT genotyped with 1717 diversity array technology (DArT) markers and two traits, days to heading (DTH) and grain yield (GY), measured in each of 12 environments. It was found that the three non-linear models had better overall prediction accuracy than the linear regression specification. Results showed a consistent superiority of RKHS and RBFNN over the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B models.
Modeling the 802.11 distributed coordination function in non-saturated conditions

Analysis of the 802.11 CSMA/CA mechanism has received considerable attention recently. Bianchi (2000) presents an analytic model under a saturated traffic assumption. Bianchi's model is accurate, but typical network conditions are non-saturated. This paper presents an extension of Bianchi's model to a non-saturated environment. Its predictions are validated against simulation and are found to accurately capture many interesting features of non-saturated operation.
Do supermarkets contribute to the obesity pandemic in developing countries?

Abstract Objective Many developing countries are undergoing a nutrition transition with rising rates of overweight and obesity. This nutrition transition coincides with a rapid expansion of supermarkets. The objective of the present research is to study whether supermarkets directly contribute to overweight and other changes in nutritional status. Design This research builds on cross-sectional observational data. Household- and individual-level data were collected in Kenya using a quasi-experimental survey design. Instrumental variable regressions were employed to analyse the impact of supermarket purchase on nutritional status. Causal chain models were estimated to examine pathways through which supermarkets affect nutrition. Setting Small towns in Central Province of Kenya with and without supermarkets. Subjects A total of 615 adults and 216 children and adolescents. Results Controlling for other factors, buying in a supermarket is associated with a significantly higher BMI (P=0·018) and a higher probability of overweight (P=0·057) among adults. This effect is not observed for children and adolescents. Instead, buying in a supermarket seems to reduce child undernutrition measured by height-for-age Z-score (P=0·017). Impacts of supermarkets depend on many factors including people’s initial nutritional status. For both adults and children, the nutrition effects occur through higher food energy consumption and changes in dietary composition. Conclusions Supermarkets and their food sales strategies contribute to changing food consumption habits and nutritional outcomes. Yet the types of outcomes differ by age cohort and initial nutritional status. Simple conclusions on whether supermarkets are good or bad for nutrition and public health are not justified.
On the Communication Complexity of Approximate Fixed Points

We study the two-party communication complexity of finding an approximate Brouwer fixed point of a composition of two Lipschitz functions g o f: [0,1]n → [0,1]n, where Alice holds f and Bob holds g. We prove an exponential (in n) lower bound on the deterministic communication complexity of this problem. Our technical approach is to adapt the Raz-McKenzie simulation theorem (FOCS 1999) into geometric settings, thereby "smoothly lifting" the deterministic query lower bound for finding an approximate fixed point (Hirsch, Papadimitriou and Vavasis, Complexity 1989) from the oracle model to the two-party model. Our results also suggest an approach to the well-known open problem of proving strong lower bounds on the communication complexity of computing approximate Nash equilibria. Specifically, we show that a slightly "smoother" version of our fixed-point computation lower bound (by an absolute constant factor) would imply that: The deterministic two-party communication complexity of finding an ∈ = Ω(1/log2 N)-approximate Nash equilibrium in an N × N bimatrix game (where each player knows only his own payoff matrix) is at least Nγ for some constant γ > 0. (In contrast, the nondeterministic communication complexity of this problem is only O(log6 N)). ; The deterministic (Number-In-Hand) multiparty communication complexity of finding an ∈ = Ω(1)-Nash equilibrium in a k-player constant-action game is at least 2Ω(k/log k) (while the nondeterministic communication complexity is only O(k)).
State-dependencies of learning across brain scales

Learning is a complex brain function operating on different time scales, from milliseconds to years, which induces enduring changes in brain dynamics. The brain also undergoes continuous “spontaneous” shifts in states, which, amongst others, are characterized by rhythmic activity of various frequencies. Besides the most obvious distinct modes of waking and sleep, wake-associated brain states comprise modulations of vigilance and attention. Recent findings show that certain brain states, particularly during sleep, are essential for learning and memory consolidation. Oscillatory activity plays a crucial role on several spatial scales, for example in plasticity at a synaptic level or in communication across brain areas. However, the underlying mechanisms and computational rules linking brain states and rhythms to learning, though relevant for our understanding of brain function and therapeutic approaches in brain disease, have not yet been elucidated. Here we review known mechanisms of how brain states mediate and modulate learning by their characteristic rhythmic signatures. To understand the critical interplay between brain states, brain rhythms, and learning processes, a wide range of experimental and theoretical work in animal models and human subjects from the single synapse to the large-scale cortical level needs to be integrated. By discussing results from experiments and theoretical approaches, we illuminate new avenues for utilizing neuronal learning mechanisms in developing tools and therapies, e.g., for stroke patients and to devise memory enhancement strategies for the elderly.
Smooth s-cobordisms of elliptic 3-manifolds

The main result of this paper states that a symplectic s-cobordism of elliptic 3-manifolds is diffeomorphic to a product (assuming a canonical contact structure on the boundary). Based on this theorem, we conjecture that a smooth s-cobordism of elliptic 3-manifolds is smoothly a product if its universal cover is smoothly a product. We explain how the conjecture fits naturally into the program of Taubes of constructing symplectic structures on an oriented smooth 4-manifold with b + ≥ 1 from generic self-dual harmonic forms. The paper also contains an auxiliary result of independent interest, which generalizes Taubes’ theorem “SW ⇒ Gr” to the case of symplectic 4-orbifolds.
Resveratrol, a natural product derived from grape, exhibits antiestrogenic activity and inhibits the growth of human breast cancer cells

Resveratrol is a natural phytoalexin compound found in grapes and other food products. In this study, the effect of resveratrol on the growth of human breast cancer cells was examined. Results show that resveratrol inhibits the growth of estrogen receptor(ER)‐positive MCF‐7 cells in a dose‐dependent fashion. Detailed studies with MCF‐7 cells demonstrate that resveratrol antagonized the growth‐promoting effect of 17‐β‐estradiol (E2) in a dose‐dependent fashion at both the cellular (cell growth) and the molecular (gene activation) levels. At 5 × 10−6 M, resveratrol abolished the growth‐stimulatory effect mediated by concentrations of E2 up to 10−9 M. The antiestrogenic effect of resveratrol could be observed at a concentration of 10−6 M and above. The antiestrogenic effect of resveratrol was also demonstrated at the molecular level. Resveratrol in a dose‐dependent fashion antagonized the stimulation by E2 of progesterone receptor gene expression in MCF‐7 cells. Moreover, expression of transforming growth factor‐α and insulin‐like growth factor I receptor mRNA was inhibited while the expression of transforming growth factor β2 mRNA was significantly elevated in MCF‐7 cells cultivated in the presence of resveratrol (10−5 M). In summary, our results show that resveratrol, a partial ER agonist itself, acts as an ER antagonist in the presence of estrogen leading to inhibition of human breast cancer cells. J. Cell. Physiol. 179:297–304, 1999. © 1999 Wiley‐Liss, Inc.
A novel circuit overrides Adr 1p control during expression of Saccharomyces cerevisiae 2-trans-enoyl-ACP reductase Etr 1p of mitochondrial type 2 fatty acid synthase

The significance of the chronicled role of the yeast transcription factor Adr1p in regulating ETR1 was examined in wild type and isogenic adr1Δ mutant cells. An ETR1-lacZ reporter construct was used to verify Adr1p-dependent gene expression. On solid glycerol medium containing X-gal, wild-type cells expressing the reporter turned blue, whereas the adr1Δ mutants remained white. β-Galactosidase activity measurements following 24-h cell growth in liquid glycerol medium revealed a 6.5-fold greater expression level of the reporter gene in the wild type compared with the adr1Δ mutant. In contrast, immunoblotting showed that Etr1p abundance was essentially indistinguishable between the two strains whereas Cta1p, whose expression depends on Adr1p, was present in the wild-type cells, but not in the mutants. Moreover, enzyme assays conducted on transformed wild-type and adr1Δ mutant cells expressing a plasmid-borne ETR1 tethered behind the native promoter revealed similar levels of reductase activity, and the lipoic acid content in the two parental strains was equivalent. Hence, while Adr1p influenced the transcription levels of ETR1, it did not alter the abundance of Etr1p, the level of reductase activity, or the cellular amount of lipoic acid. The results point toward a potentially novel layer of control for maintaining physiological levels of lipoic acid.
Phenotypic and Functional Characterization of Long-Term Cultured Rhesus Macaque Spleen-Derived NKT Cells 1

Natural killer T cells are immunoregulatory cells, which have important roles in tolerance and autoimmunity, as demonstrated primarily in mice and humans. In this study, we define the phenotype and function of Vα24+ T cells derived from the spleens of rhesus macaques, a species increasingly used in models of immune tolerance. Vα24+ cells were isolated and expanded with monocyte-derived immature dendritic cells in the presence of α-galactosylceramide, IL-2, and IL-15. Rhesus NKT cells were stained with mAbs against both Vα24 and the invariant complementarity-determining region 3 epitope of the human Vα24/JαQ TCR. The cells were CD4, CD8 double negative and expressed CD56. Rhesus NKT cells also exhibited moderate to high expression of CD95, CD45RO, CD11a, and β7 integrin, but did not express CD45 RA, CD62L, CCR7, CD28, and other activation, costimulatory molecules (CD69 and CD40L). By intracellular staining, >90% of unstimulated rhesus NKT cells expressed IL-10, but not IFN-γ. However, the latter was strongly expressed after stimulation. Rhesus NKT secreted large amounts of TGF-β, IL-13, and IL-6, and modest levels of IFN-γ, whereas IL-10 secretion was negligible and no detectable IL-4 was observed either intracellularly or in culture supernatants. Functionally, the NKT cells and their supernatants suppressed T cell proliferation in allogeneic MLR. We conclude that long-term cultured rhesus macaque spleen-derived Vα24+ T cells are semi-invariant double-negative cells with effector memory phenotype. These cells are semianergic, polarized to a uniquely Th3 > T regulatory-1 regulatory cell phenotype, and have regulatory/suppressive function in vitro.