Miracle-dz/UniFAR-FTUs huggingface dataset:
Stratification according to recursive partitioning analysis predicts outcome in newly diagnosed glioblastomas

Glioblastoma accounts for more than half of diffuse gliomas. The prognosis of patients with glioblastoma remains poor despite comprehensive and intensive treatments. Furthermore, the clinical significance of molecular parameters and routinely available clinical variables for the prognosis prediction of glioblastomas remains limited. The authors describe a novel model may help in prognosis prediction and clinical management of glioblastoma patients. We performed a recursive partitioning analysis to generate three independent prognostic classes of 103 glioblastomas patients from TCGA dataset. Class I (MGMT promoter methylated, age <58), class II (MGMT promoter methylation, age ≥58; MGMT promoter unmethylation, age <54, KPS ≥70; MGMT promoter unmethylation, age >59, KPS ≥70), class III (MGMT promoter unmethylation, age 54-58, KPS ≥70; MGMT promoter unmethylation, KPS <70). Age, KPS and MGMT promoter methylation were the most significant prognostic factors for overall survival. The results were validated in CGGA dataset. This was the first study to combine various molecular parameters and clinical factors into recursive partitioning analysis to predict the prognosis of patients with glioblastomas. We included MGMT promoter methylation in our study, which could give better suggestion to patients for their chemotherapy. This clinical study will serve as the backbone for the future incorporation of molecular prognostic markers currently in development. Thus, our recursive partitioning analysis model for glioblastomas may aid in clinical prognosis evaluation.
Microwave-Assisted Synthesis of Alumina Nanoparticles Using Some Plants Extracts

In present study we used five green plants for microwave assisted synthesis of Alumina nanoparticles from Aluminum nitrate. Structural characterization was studied using x-ray diffraction that showed semi- crystalline and possibly, amorphous structure. Fourier infrared spectroscopy was used to determine Al-O bond and functional groups responsible for synthesis of nanoparticles. FTIR confirmed existence of Al-O band and bio-functional groups, originated from plant extract. Morphology and size of nanoparticles were investigated using scanning electron microscopy, transmission electron microscopy and atomic force microscopy techniques. It was observed that nanoparticles have near-spherical shape. Average size of clusters of nanoparticles varied with different routes from of 60 nm to 300 nm. AFM images showed that Individual nanoparticles were less than 10 nm.
PySeqLab: an open source Python package for sequence labeling and segmentation

Motivation Text and genomic data are composed of sequential tokens, such as words and nucleotides that give rise to higher order syntactic constructs. In this work, we aim at providing a comprehensive Python library implementing conditional random fields (CRFs), a class of probabilistic graphical models, for robust prediction of these constructs from sequential data. Results Python Sequence Labeling (PySeqLab) is an open source package for performing supervised learning in structured prediction tasks. It implements CRFs models, that is discriminative models from (i) first‐order to higher‐order linear‐chain CRFs, and from (ii) first‐order to higher‐order semi‐Markov CRFs (semi‐CRFs). Moreover, it provides multiple learning algorithms for estimating model parameters such as (i) stochastic gradient descent (SGD) and its multiple variations, (ii) structured perceptron with multiple averaging schemes supporting exact and inexact search using ‘violation‐fixing’ framework, (iii) search‐based probabilistic online learning algorithm (SAPO) and (iv) an interface for Broyden‐Fletcher‐Goldfarb‐Shanno (BFGS) and the limited‐memory BFGS algorithms. Viterbi and Viterbi A* are used for inference and decoding of sequences. Using PySeqLab, we built models (classifiers) and evaluated their performance in three different domains: (i) biomedical Natural language processing (NLP), (ii) predictive DNA sequence analysis and (iii) Human activity recognition (HAR). State‐of‐the‐art performance comparable to machine‐learning based systems was achieved in the three domains without feature engineering or the use of knowledge sources. Availability and implementation PySeqLab is available through https://bitbucket.org/A_2/pyseqlab with tutorials and documentation. Contact ahmed.allam@yale.edu or michael.krauthammer@yale.edu Supplementary information Supplementary data are available at Bioinformatics online.
WizHaul: On the Centralization Degree of Cloud RAN Next Generation Fronthaul

Cloud Radio Access Network (C-RAN) will become a main building block for 5G. However, the stringent requirements of current fronthaul solutions hinder its large-scale deployment. In order to introduce C-RAN widely in 5G, the next generation fronthaul interface (NGFI) will be based on a cost-efficient packet-based network with higher path diversity. In addition, NGFI shall support a flexible functional split of the RAN to adapt the amount of centralization to the capabilities of the transport network. In this paper we question the ability of standard techniques to route NGFI traffic while maximizing the centralization degree—the goal of C-RAN. We propose two solutions jointly addressing both challenges: (<inline-formula><tex-math notation="LaTeX">$i$</tex-math><alternatives> <inline-graphic xlink:href="garciasaavedra-ieq1-2793859.gif"/></alternatives></inline-formula>) a nearly-optimal backtracking scheme, and (<inline-formula><tex-math notation="LaTeX">$ii$</tex-math><alternatives> <inline-graphic xlink:href="garciasaavedra-ieq2-2793859.gif"/></alternatives></inline-formula>) a low-complex greedy approach. We first validate the feasibility of our approach in an experimental proof-of-concept, and then evaluate both algorithms via simulations in large-scale (real and synthetic) topologies. Our results show that state-of-the-art techniques fail at maximizing the centralization degree and that the achievable C-RAN centralization highly depends on the underlying topology structure.
Neighborhood Preserving Nonnegative Matrix

Nonnegative Matrix Factorization (NMF) has been widely used in computer vision and pattern recognition. It aims to find two nonnegative matrices whose product can well approximate the nonnegative data matrix, which naturally leads to parts-based and non-subtractive representation. In this paper, we present a neighborhood preserving nonnegative matrix factorization (NPNMF) for dimensionality reduction. It imposes an additional constraint on NMF that each data point can be represented as a linear combination of its neighbors. This constraint preserves the local geometric structure, and is good at dimensionality reduction on manifold. An iterative multiplicative updating algorithm is proposed to optimize the objective, and its convergence is guaranteed theoretically. Experiments on benchmark face recognition data sets demonstrate that the proposed method outperforms NMF as well as many state of the art dimensionality reduction methods.
Rotating Radio Transients and their place among pulsars

Abstract Six years ago, the discovery of Rotating Radio Transients (RRATs) marked what appeared to be a new type of sparsely-emitting pulsar. Since 2006, more than 70 of these objects have been discovered in single-pulse searches of archival and new surveys. With a continual inflow of new information about the RRAT population in the form of new discoveries, multi-frequency follow ups, coherent timing solutions, and pulse rate statistics, a view is beginning to form of the place in the pulsar population RRATs hold. Here we review the properties of neutron stars discovered through single pulse searches. We first seek to clarify the definition of the term RRAT, emphasising that “the RRAT population” encompasses several phenomenologies. A large subset of RRATs appears to represent the tail of an extended distribution of pulsar nulling fractions and activity cycles; these objects present several key open questions remaining in this field.
β-Catenin Defines Head Versus Tail Identity During Planarian Regeneration and Homeostasis

After amputation, freshwater planarians properly regenerate a head or tail from the resulting anterior or posterior wound. The mechanisms that differentiate anterior from posterior and direct the replacement of the appropriate missing body parts are unknown. We found that in the planarian Schmidtea mediterranea, RNA interference (RNAi) of β-catenin or dishevelled causes the inappropriate regeneration of a head instead of a tail at posterior amputations. Conversely, RNAi of the β-catenin antagonist adenomatous polyposis coli results in the regeneration of a tail at anterior wounds. In addition, the silencing of β-catenin is sufficient to transform the tail of uncut adult animals into a head. We suggest that β-catenin functions as a molecular switch to specify and maintain anteroposterior identity during regeneration and homeostasis in planarians.
A crisis of meaning: can ‘schizophrenia’ survive in the 21st century?

Both within clinical and wider societal discourses, the term ‘schizophrenia’ has achieved considerable potency as a signifier, privileging particular conceptual frames for understanding and responding to mental distress. However, its status has been subject to instability, as it has lacked indisputable biological correlates that would anchor its place within the canon of medical diagnosis. Informed by a semiotic perspective, this paper focuses on its recent history: how ‘schizophrenia’ has been claimed, appropriated and contested—and how this connects with its earlier history of signification. It also explores how the dominance of this signifier has influenced the ways in which people with the diagnosis may find themselves constructed in their interactions with professionals, family and wider society, and hence how they may come to see themselves. It is argued that, from a point in the 1990s when ‘schizophrenia’ had achieved an almost iconic status, the term is now subject to greater instability, with concerns and challenges being raised from both within and outside psychiatry. On the one hand, this uncertainty has triggered a ‘calls to arms' from those within the psychiatric establishment who see diagnoses such as ‘schizophrenia’ as crucial to their professional identity and status. On the other hand, this has created spaces for new conversations and alliances between elements within neurology, psychiatry, social work and other professions, and between these and service users. Some of these conversations are casting doubt on the validity and utility of ‘schizophrenia’ as a construct, and are beginning to posit alternative regimes of signification.
Newborn Infants' Preference for Attractive Faces: The Role of Internal and External Facial Features.

Several previous experiments have found that newborn and young infants will spend more time looking at attractive faces when these are shown paired with faces judged by adults to be unattractive. Two experimental conditions are described with the aim of finding whether the "attractiveness effect" results from attention to internal or external facial features, or both. Pairs of attractive and less attractive faces (as judged by adults) were shown to newborn infants (mean age 2 days, 9 hours), where each pair had either identical internal features (and different external features) or identical external features (and different internal features). In the latter, but not the former, condition the infants looked longer at the attractive faces. These findings are clear evidence that newborn infants use information about internal facial features in making preferences based on attractiveness. It is suggested that when newborn (and older) infants are presented with facial stimuli, whether dynamic or static, they are able to attend both to internal and external facial features.
Highly Pathogenic New World Arenavirus Infection Activates the Pattern Recognition Receptor Protein Kinase R without Attenuating Virus Replication in Human Cells

ABSTRACT The arenavirus family consists of several highly pathogenic viruses, including the Old World (OW) arenavirus Lassa fever virus (LASV) and the New World (NW) Junin virus (JUNV) and Machupo virus (MACV). Host response to infection by these pathogenic arenaviruses is distinct in many aspects. JUNV and MACV infections readily induce an interferon (IFN) response in human cells, while LASV infection usually triggers an undetectable or weak IFN response. JUNV induces an IFN response through RIG-I, suggesting that the host non-self RNA sensor readily detects JUNV viral RNAs (vRNAs) during infection and activates IFN response. Double-stranded-RNA (dsRNA)-activated protein kinase R (PKR) is another host non-self RNA sensor classically known for its vRNA recognition activity. Here we report that infection with NW arenaviruses JUNV and MACV, but not OW LASV, activated PKR, concomitant with elevated phosphorylation of the translation initiation factor α subunit of eukaryotic initiation factor 2 (eIF2α). Host protein synthesis was substantially suppressed in MACV- and JUNV-infected cells but was only marginally reduced in LASV-infected cells. Despite the antiviral activity known for PKR against many other viruses, the replication of JUNV and MACV was not impaired but was slightly augmented in wild-type (wt) cells compared to that in PKR-deficient cells, suggesting that PKR or PKR activation did not negatively affect JUNV and MACV infection. Additionally, we found an enhanced IFN response in JUNV- or MACV-infected PKR-deficient cells, which was inversely correlated with virus replication. IMPORTANCE The detection of viral RNA by host non-self RNA sensors, including RIG-I and MDA5, is critical to the initiation of the innate immune response to RNA virus infection. Among pathogenic arenaviruses, the OW LASV usually does not elicit an interferon response. However, the NW arenaviruses JUNV and MACV readily trigger an IFN response in a RIG-I-dependent manner. Here, we demonstrate for the first time that pathogenic NW arenaviruses JUNV and MACV, but not the OW arenavirus LASV, activated the dsRNA-dependent PKR, another host non-self RNA sensor, during infection. Interestingly, the replication of JUNV and MACV was not restricted but was rather slightly augmented in the presence of PKR. Our data provide new evidence for a distinct interplay between host non-self RNA sensors and pathogenic arenaviruses, which also provides insights into the pathogenesis of arenaviruses and may facilitate the design of vaccines and treatments against arenavirus-caused diseases.
Child Art Psychotherapy Proposed as Adjunctive Therapy for Adolescents with Type 1 Diabetes Mellitus

We wish to draw your attention to the challenges experienced by adolescents with Type 1 Diabetes Mellitus (T1DM) and propose Child Art Psychotherapy (CAP) as an innovative and effective asset to the multidisciplinary team in their endeavour to facilitate optimum glycaemic control in their clients. Type 1 Diabetes is an auto-immune, lifelong condition with a marked impact on the lifestyle of sufferers. It carries the threat of complications, including blindness, kidney and heart disease, amputations, neuropathy, coma and death. Adolescents, in particular struggle to balance the demands of diabetes care tasks with a fulfilling lifestyle, and clinicians endeavor to provide a range of supports that reinforce good management and improve quality of life. It is estimated that 2,750 people under 20 years of have T1DM in Ireland and this number is increasing [1].
Network representation of protein interactions—Experimental results

A graph theoretical analysis of nuclear magnetic resonance (NMR) data of six different protein interactions has been presented. The representation of the protein interaction data as a graph or network reveals that all of the studied interactions are based on a common functional concept. They all involve a single densely packed hub of functionally correlated residues that mediate the ligand binding events. This is found independent of the kind of protein (folded or unfolded) or ligand (protein, polymer or small molecule). Furthermore, the power of the graph analysis is demonstrated at the examples of the Calmodulin (CaM)/Calcium and the Cold Shock Protein A (CspA)/RNA interaction. The presented approach enables the precise determination of multiple binding sites for the respective ligand molecules.
Hyperthermic chemotherapy intra-abdominal laparoscopic approach: development of a laparoscopic model using CO2 recirculation system and clinical translation in peritoneal carcinomatosis

Abstract Introduction: Hyperthermic intraperitoneal chemotherapy (HIPEC) is an effective treatment for peritoneal carcinomatosis (PC). Laparoscopic surgery is performed in the treatment of colorectal and appendiceal cancer, and PC from diverse origin in selected patients. HIPEC management by laparoscopic approach after cytoreductive surgery (CRS) completed locoregional treatment of PC, and may be feasible and safe after appropriate patient selection. Objective: Development of an experimental model of HIPEC by laparoscopic approach, with CO2 recirculation. Clinical translation in two patients with PC and low peritoneal cancer index. Material and methods: We performed CRS in a porcine model of 5 pigs (35–38 kg) by laparoscopic approach. Laparoscopic HIPEC by CO2 recirculation system was performed; laparoscopic access was used for catheter input and output placement (Paclitaxel 175 mg/m2 for 60 min at 42 °C). The experimental variables were: blood gases, haemodynamic and intra-abdominal and central temperature. Clinical model application was performed in three cases with PC from colorectal origin. Results: No statistically significant differences was found in blood gases, haemodynamic or temperature in the experimental study. In clinical study, there were no technical complications during laparoscopic-HIPEC approach, and we observed no changes in haemodynamic variables during the procedure. Conclusions: CRS and HIPEC laparoscopic model by CO2 recirculation system is safe and feasible technique in selected patients, that include low PC index, local and accessible tumour recurrences or high-risk of PC tumours.
MAC layer design for concurrent transmissions in millimeter wave WLANs

High frequency and very high throughput wireless local area networks have turned to be an essential need due to the likely substantial world increase of the WiFi public hotspots and the existing internet traffic. Due to the these challenges, an efficient solution is required for the current IEEE 802.11 standards to meet the predicted growth of wireless traffic and the number of WiFi networks in the world. In this paper, practical and efficient concurrent downlink transmission medium access control (MAC) layer design is proposed for the millimeter wave wireless local area networks (WLANs) based on both the IEEE 802.11ad system and spatial multiplexing technique. Particularly, a pre-defined virtual grouping (PDVG) scheduling approach is designed to schedule concurrent downlink links based on the analog beamforming information of the IEEE 802.11ad. The PDVG approach can attain and select concurrent stations (STNs) with no additional computational overhead. We demonstrate via simulations that the proposed algorithm can enhance the throughput and save the available time of the service period (SP) for the IEEE 802.11ad, without adding extra feedback overhead to the beamforming operation time in the system.
Recolonisation of Acropora hyacinthus following climate-induced coral bleaching on the Great Barrier Reef

Given projected increases in the frequency and/or severity of climatic disturbances, the persistence of corals may be more a function of their capacity for regeneration than resistance to such episodic disturbances. If so, climate change may favour those corals that regenerate fastest following acute disturbance. The tabular coral Acropora hyacinthus is fast-growing and typically dominates shallow wave-exposed habitats on the Great Barrier Reef, but it is extremely vulnerable to climate-induced coral bleaching and other disturbances (e.g. cyclones and outbreaks of crown-of-thorns starfish). The present study explores temporal changes in percentage cover and size structure of A. hyacinthus on reefs affected by the 2001−2002 bleaching event. Annual surveys conducted at 3 mid-shelf reefs from 2008 to 2010 revealed rapid, but very patchy, recovery of A. hyacinthus. Following extensive coral loss, local cover of A. hyacinthus increased due to growth of established colonies as well as addition and subsequent growth of new colonies. At one reef, recovery was mostly due to increased abundance of small colonies, assumed to have recruited since the bleaching, whereas recovery at the 2 other study reefs (<5 km away) was the sustained growth of established colonies. These results show that resilience of A. hyacinthus populations may be due to either recolonisation or ­persistence, but that, either way, these corals are well suited to rapid recovery following acute ­disturbance.
Sensitivity of White and Opaque Candida albicans Cells to Antifungal Drugs

ABSTRACT White and opaque cells of Candida albicans have the same genome but differ in gene expression patterns, metabolic profiles, and host niche preferences. We tested whether these differences, which include the differential expression of drug transporters, resulted in different sensitivities to 27 antifungal agents. The analysis was performed in two different strain backgrounds; although there was strain-to-strain variation, only terbinafine hydrochloride and caspofungin showed consistent, 2-fold differences between white and opaque cells across both strains.
Folding Clothes Autonomously: A Complete Pipeline

This work presents a complete pipeline for folding a pile of clothes using a dual-armed robot. This is a challenging task both from the viewpoint of machine vision and robotic manipulation. The presented pipeline is comprised of the following parts: isolating and picking up a single garment from a pile of crumpled garments, recognizing its category, unfolding the garment using a series of manipulations performed in the air, placing the garment roughly flat on a work table, spreading it, and, finally, folding it in several steps. The pile is segmented into separate garments using color and texture information, and the ideal grasping point is selected based on the features computed from a depth map. The recognition and unfolding of the hanging garment are performed in an active manner, utilizing the framework of active random forests to detect grasp points, while optimizing the robot actions. The spreading procedure is based on the detection of deformations of the garment's contour. The perception for folding employs fitting of polygonal models to the contour of the observed garment, both spread and already partially folded. We have conducted several experiments on the full pipeline producing very promising results. To our knowledge, this is the first work addressing the complete unfolding and folding pipeline on a variety of garments, including T-shirts, towels, and shorts.