nils-herrmann/clean_scirepeval huggingface dataset:
Advanced glycation end products induce skeletal muscle atrophy and dysfunction in diabetic mice via a RAGE mediated, AMPK down regulated, Akt pathway
Venue: The Journal of pathology

Diabetic myopathy, a less studied complication of diabetes, exhibits the clinical observations characterized by a less muscle mass, muscle weakness and a reduced physical functional capacity. Accumulation of advanced glycation end products (AGEs) known to play a role in diabetic complications, has been identified in ageing human skeletal muscles. However, the role of AGEs in diabetic myopathy remains unclear. Here, we investigated the effects of AGEs on myogenic differentiation and muscle atrophy in vivo and in vitro. We also evaluated the therapeutic potential of alagebrium chloride (Ala Cl) an inhibitor of AGEs. Muscle fibre atrophy and immunoreactivity for AGEs, Atrogin 1 (a muscle atrophy marker) and phosphorylated AMP activated protein kinase (AMPK) expressions were markedly increased in human skeletal muscles from patients with diabetes as compared with control subjects. Moreover, in diabetic mice we found increased blood AGEs, less muscle mass, lower muscular endurance, atrophic muscle size and poor regenerative capacity, and increased levels of muscle AGE and receptor for AGE (RAGE) Atrogin 1 and phosphorylated AMPK, which could be significantly ameliorated by Ala Cl. Furthermore, in vitro, AGEs (in a dose dependent manner) reduced myotube diameters (myotube atrophy) and induced Atrogin 1 protein expression in myotubes differentiated from both mouse myoblasts and primary human skeletal muscle derived progenitor cells. AGEs exerted a negative regulation of myogenesis of mouse and human myoblasts. Ala Cl significantly inhibited the effects of AGEs on myotube atrophy and myogenesis. We further demonstrated that AGEs induced muscle atrophy/myogenesis impairment via a RAGE mediated AMPK down regulation of the Akt signalling pathway. Our findings support that AGEs play an important role in diabetic myopathy, and that an inhibitor of AGEs may offer a therapeutic strategy for managing the dysfunction of muscle due to diabetes or ageing.
Fecal Bacteria Act as Novel Biomarkers for Noninvasive Diagnosis of Colorectal Cancer
Venue: Clinical Cancer Research

Gut microbiota have been implicated in the development of colorectal cancer. We evaluated the utility of fecal bacterial marker candidates identified by our metagenome sequencing analysis for colorectal cancer diagnosis.  Subjects (total 439; 203 colorectal cancer and 236 healthy subjects) from two independent Asian cohorts were included. Probe based duplex quantitative PCR (qPCR) assays were established for the quantification of bacterial marker candidates.  Candidates identified by metagenome sequencing, including Fusobacterium nucleatum (Fn) Bacteroides clarus (Bc) Roseburia intestinalis (Ri) Clostridium hathewayi (Ch) and one undefined species (labeled as m7) were examined in fecal samples of 203 colorectal cancer patients and 236 healthy controls by duplex qPCR. Strong positive correlations were demonstrated between the quantification of each candidate by our qPCR assays and metagenomics approach (r 0.801 0.934, all P 0.0001) Fn was significantly more abundant in colorectal cancer than controls (P 0.0001) with AUROC of 0.868 (P 0.0001) At the best cut off value maximizing sum of sensitivity and specificity, Fn discriminated colorectal cancer from controls with a sensitivity of 77.7% and specificity of 79.5% in cohort I. A simple linear combination of four bacteria (Fn Ch m7 Bc) showed an improved diagnostic ability compared with Fn alone (AUROC 0.886, P 0.0001) in cohort I. These findings were further confirmed in an independent cohort II. In particular, improved diagnostic performances of Fn alone (sensitivity 92.8% specificity 79.8% and four bacteria (sensitivity 92.8% specificity 81.5% were achieved in combination with fecal immunochemical testing for the detection of colorectal cancer.  Stool based colorectal cancer associated bacteria can serve as novel noninvasive diagnostic biomarkers for colorectal cancer.
A Zebrafish Genetic Screen Identifies Neuromedin U as a Regulator of Sleep/Wake States
Venue: Neuron

Neuromodulation of arousal states ensures that an animal appropriately responds to its environment and engages in behaviors necessary for survival. However, the molecular and circuit properties underlying neuromodulation of arousal states such as sleep and wakefulness remain unclear. To tackle this challenge in a systematic and unbiased manner, we performed a genetic overexpression screen to identify genes that affect larval zebrafish arousal. We found that the neuropeptide neuromedin U (Nmu) promotes hyperactivity and inhibits sleep in zebrafish larvae, whereas nmu mutant animals are hypoactive. We show that Nmu induced arousal requires Nmu receptor 2 and signaling via corticotropin releasing hormone (Crh) receptor 1. In contrast to previously proposed models, we find that Nmu does not promote arousal via the hypothalamic pituitary adrenal axis, but rather probably acts via brainstem crh expressing neurons. These results reveal an unexpected functional and anatomical interface between the Nmu system and brainstem arousal systems that represents a novel wake promoting pathway.
Employing intergroup competition in multitouch design based learning to foster student engagement, learning achievement, and creativity
Venue: Comput. Educ.

This study developed an intergroup competition mechanism and integrated it into a multitouch platform for collaborative design based learning (DBL) to enhance elementary school students' engagement, learning achievement, and creativity. A total of 58 elementary school students in 2 sixth grade classes participated in the study over a period of 9 weeks. A quasi experiment was conducted to examine the effects of the intergroup competition mechanism. The two classes were divided into an experimental group (a class of 28 students in collaboration with intergroup competition) and a comparison group (another class of 30 students in collaboration without intergroup competition) and the students in both groups were required to carry out a tessellation design project with their partners on the multitouch platform. Statistical analyses revealed that students under the intergroup competition condition had significantly better student engagement, learning achievement, and creativity than those under the no competition condition. The results suggest that the computerized intergroup competition mechanism is effective in enhancing student engagement, learning achievement, and creativity. On the basis of the results, considerations in relation to the intergroup competition mechanism and the enhanced cognitive processes in multitouch DBL are discussed. We propose an intergroup competition mechanism for multitouch DBL.The intergroup competition mechanism can foster students' engagement.The intergroup competition mechanism can enhance students' achievement.The intergroup competition mechanism can facilitate students' creativity.
Motif based embedding for graph clustering

Community detection in complex networks is a fundamental problem that has been extensively studied owing to its wide range of applications. However, because community detection methods typically rely on the relations between vertices in networks, they may fail to discover higher order graph substructures, called the network motifs. In this paper, we propose a novel embedding method for graph clustering that considers higher order relationships involving multiple vertices. We show that our embedding method, which we call motif based embedding, is more effective in detecting communities than existing graph embedding methods, spectral embedding and force directed embedding, both theoretically and experimentally.
Motif based embedding for graph clustering

Community detection in complex networks is a fundamental problem that has been extensively studied owing to its wide range of applications. However, because community detection methods typically rely on the relations between vertices in networks, they may fail to discover higherorder graph substructures, called the network motifs. In this paper, we propose a novel embedding method for graph clustering that considers higher order relationships involving multiple vertices. We show that our embedding method, which we call motif based embedding, is more eective in detecting communities than existing graph embedding methods, spectral embedding and force directed embedding, both theoretically and experimentally.
Comparison of Clinicopathological Features and Prognosis in Triple Negative and Non Triple Negative Breast Cancer
Venue: Journal of Cancer

Triple negative breast cancer (TNBC) has attracted more attention both clinically and experimentally because of its high risk biological characteristics and lacking of effective treatment method. The purpose of this retrospective study was to find out the incidence of triple negative breast cancer (TNBC) in all kinds of breast cancers and to compare and analyze the clinicopathological features, recurrence, metastasis and prognosis of patients with TNBC and non triple negative breast cancer (non TNBC)  A total of 1578 female patients with primary breast cancer were diagnosed and treated at the department of General Surgery, the Chinese PLA General Hospital, China, from Jan. 2004  The 1578 breast cancer patients were divided into two groups: the TNBC group and the non TNBC group. The clinical features and prognosis of the two groups were compared.  The incidence of TNBC was 20.41% Compared with the non TNBC, the TNBC were characterized as younger age, higher histological grade, higher rate of positive lymph node, bigger tumor size, higher clinical stage at diagnosis, higher histological grade, quicker and easier recurrence and metastasis and lower 5 year DFS rate and 5 year OS rate. The metastasis of TNBC had obvious organic tendency. The lungs, liver and brain were the first three most common sites of metastases. The information of age, the tumor size, lymph node status, clinical stage, histological grade, pathological types and operation method, especially the age and lymph node status play the important roles in judging the prognosis of TNBC.  According to this study we found that TNBC was a distinct subgroup of breast cancer with particular clinicopathologic behavior. Compared with the non TNBC, TNBC was characterized by more aggressive behavior, and lower DFS and OS rate. The metastasis of TNBC had obvious organic tendency. The information of age, the maximum diameter of the tumor, lymph node status, clinical stage, histological grade, pathological types and operation method, especially the age and lymph node status played the important roles in judging the prognosis of TNBC patients.
Disease named entity recognition by combining conditional random fields and bidirectional recurrent neural networks
Venue: Database J. Biol. Databases Curation

The recognition of disease and chemical named entities in scientific articles is a very important subtask in information extraction in the biomedical domain. Due to the diversity and complexity of disease names, the recognition of named entities of diseases is rather tougher than those of chemical names. Although there are some remarkable chemical named entity recognition systems available online such as ChemSpot and tmChem, the publicly available recognition systems of disease named entities are rare. This article presents a system for disease named entity recognition (DNER) and normalization. First, two separate DNER models are developed. One is based on conditional random fields model with a rule based post processing module. The other one is based on the bidirectional recurrent neural networks. Then the named entities recognized by each of the DNER model are fed into a support vector machine classifier for combining results. Finally, each recognized disease named entity is normalized to a medical subject heading disease name by using a vector space model based method. Experimental results show that using 1000 PubMed abstracts for training, our proposed system achieves an F1 measure of 0.8428 at the mention level and 0.7804 at the concept level, respectively, on the testing data of the chemical disease relation task in BioCreative V. Database URL: http:/219.223.252.210:8080/SS/cdr.html
First things first? Top down influences on event apprehension
Venue: CogSci

Not much is known about event apprehension, the earliest stage of information processing in elicited language production studies, using pictorial stimuli. A reason for our lack of knowledge on this process is that apprehension happens very rapidly <350 ms after stimulus onset, Griffin Bock 2000) making it difficult to measure the process directly. To broaden our understanding of apprehension, we analyzed landing positions and onset latencies of first fixations on visual stimuli (pictures of real world events) given short stimulus presentation times, presupposing that the first fixation directly results from information processing during apprehension.
Can a continuous mineral foam explain the stiffening of aged bone tissue? A micromechanical approach to mineral fusion in musculoskeletal tissues.
Venue: Bioinspiration biomimetics

Recent experimental data revealed a stiffening of aged cortical bone tissue, which could not be explained by common multiscale elastic material models. We explain this data by incorporating the role of mineral fusion via a new hierarchical modeling approach exploiting the asymptotic (periodic) homogenization (AH) technique for three dimensional linear elastic composites. We quantify for the first time the stiffening that is obtained by considering a fused mineral structure in a softer matrix in comparison with a composite having non fused cubic mineral inclusions. We integrate the AH approach in the Eshelby based hierarchical mineralized turkey leg tendon model (Tiburtius et al 2014 Biomech. MODEL Mechanobiol. 13 1003 23) which can be considered as a base for musculoskeletal mineralized tissue modeling. We model the finest scale compartments, i.e. the extrafibrillar space and the mineralized collagen fibril, by replacing the self consistent scheme with our AH approach. This way, we perform a parametric analysis at increasing mineral volume fraction, by varying the amount of mineral that is fusing in the axial and transverse tissue directions in both compartments. Our effective stiffness results are in good agreement with those reported for aged human radius and support the argument that the axial stiffening in aged bone tissue is caused by the formation of a continuous mineral foam. Moreover, the proposed theoretical and computational approach supports the design of biomimetic materials which require an overall composite stiffening without increasing the amount of the reinforcing material.
Do Strict Land Use Regulations Make Metropolitan Areas More Segregated by Income?
Venue: Journal of the American Planning Association. American Planning Association

Problem, research strategy, and findings: Income segregation has risen in each of the last four decades in U.S. metropolitan areas, which can have lifelong impacts on the health, economic productivity, and behaviors of residents. Although it is widely assumed that local land use regulations such as minimum lot sizes and growth controls exclude low income households from wealthier neighborhoods, the empirical research is surprisingly limited. We examine the relationship between land use regulation and segregation by income using new measures for the 95 biggest cities in the United States. We find that density restrictions are associated with the segregation of the wealthy and middle income, but not the poor. We also find that more local pressure to regulate land use is linked to higher rates of income segregation, but that more state control is connected to lower income segregation. Takeaway for practice: Density restrictions do drive urban income segregation of the rich, not the poor, but should be addressed because rich enclaves create significant metropolitan problems. Planners at the local level need assistance from regional and state efforts to ameliorate income segregation. Inclusionary housing requirements have a greater potential to reduce income segregation than bringing higher income households into lower income parts of the city. Finally, comprehensive and consistent data on the impacts of local land use regulations should be collected to inform future research and planning practice.
The politics of land supply and affordable housing: Auckland's Housing Accord and Special Housing Areas

Increasingly, planning for housing development involves political conflict between local government planning practices, based on urban sustainability and housing intensification, and central government housing policies, centred on land supply and housing affordability. This paper examines a key historical moment in the politics of housing supply and planning in New Zealand. Drawing upon a discourse analysis of a range of housing policy documents and urban plans, this paper traces the dynamic of local and central government negotiations and conflict arising from the development of Auckland's spatial plan, the development of the Auckland Housing Accord (a central and local government agreement to fast track planning permission for new housing) and the implementation of the Housing Accords and Special Housing Areas Act. The paper focuses on the manner in which certain policy knowledge is prioritised and applied in the construction of affordable housing policies and how this process, which is presented as objective evidence based policy formation, is inherently political. It is argued that the legislation supporting housing accords alters central/local government power relations and represents a challenge to the existing planning system.
Leveraging Evolution Dynamics to Generate Benchmark Complex Networks with Community Structures

The past decade has seen tremendous growth in the field of Complex Social Networks. Several network generation models have been extensively studied to develop an understanding of how real world networks evolve over time. Two important applications of these models are to study the evolution dynamics and processes that shape a network, and to generate benchmark networks with known community structures. Research has been conducted in both these directions, relatively independent of the other. This creates a disjunct between real world networks and the networks generated as benchmarks to study community detection algorithms. In this paper, we propose to study both these application areas together. We introduce a network generation model which is based on evolution dynamics of real world networks and, it can generate networks with community structures that can be used as benchmark graphs. We study the behaviour of different community detection algorithms based on the proposed model and compare it with other models to generate benchmark graphs. Results suggest that the proposed model can generate networks which are not only structurally similar to real world networks but can be used to generate networks with varying community sizes and topologies.
Network Generation Model Based on Evolution Dynamics To Generate Benchmark Graphs
Venue: ArXiv

Network generation models provide an understanding of the dynamics behind the formation and evolution of different networks including social networks, technological networks and biological networks. Two important applications of these models are to study the evolution dynamics of network formation and to generate benchmark networks with known community structures. Research has been conducted in both these directions relatively independent of the other application area. This creates a disjunct between real world networks and the networks generated to study community detection algorithms. In this paper, we propose to study both these application areas together i.e. introduce a network generation model based on evolution dynamics of real world networks and generate networks with community structures that can be used as benchmark graphs to study community detection algorithms. The generated networks possess tunable modular structures which can be used to generate networks with known community structures. We study the behaviour of different community detection algorithms based on the proposed model and compare it with other models to generate benchmark graphs. Results suggest that the networks generated using the proposed model present tougher challenges for community detection algorithms due to the topological structure introduced by evolution dynamics.
Enterprise Architecture Adoption Challenges: An exploratory Case Study of the Norwegian Higher Education Sector

IT is a challenge to implement Enterprise Architecture (EA) in an organisation. This is also the case in the public sector, like public universities and colleges. There is a very limited research on such issues. It is therefore important to investigate how AE is implemented in various sectors, which benefits are realised and which challenges are most prominent. This interpretive case study investigates the efforts taken towards a common EA in the Norwegian higher education sector. We find that the progress was severely impeded by the lack of top level directions from the ministry, the lack of an overarching architecture council, and the lack of EA competence at the top management level at the individual institutions. The perceived most important benefits were business agility, economies of scale and better decision making.
Pharmacological cyclin dependent kinase inhibitors: Implications for colorectal cancer.
Venue: World journal of gastroenterology

Colorectal cancer accounts for a significant proportion of cancer deaths worldwide. The need to develop more chemotherapeutic agents to combat this disease is critical. Cyclin dependent kinases (CDKs) along with its binding partner cyclins, serve to control the growth of cells through the cell cycle. A new class of drugs, termed CDK inhibitors, has been studied in preclinical and now clinical trials. These inhibitors are believed to act as an anti cancer drug by blocking CDKs to block the uncontrolled cellular proliferation that is hallmark of cancers like colorectal cancer. CDK article provides overview of the emerging drug class of CDK inhibitors and provides a list of ones that are currently in clinical trials.
The Efficacy of Shihogayonggolmoryo tang in Combating Excessive Sweating in Heart Disease Syndrome, Called Xin Bing in Korean Medicine

The purpose of this study was to investigate the efficacy of Shihogayonggolmoryo tang (SYT) in combatting excessive sweating.  The electronic medical records (EMR) of patients who attended the Department of Korean Internal Medicine, Stroke and Neurological Disorders Center from December 2014 to April 2016 were reviewed. Excessive sweating was graded and compared before and after the administration of SYT in 32 patients.  The average grade for excessive sweating of the 32 patients significantly decreased from 2.47+ 0.62 to 1.03+ 0.86 after the SYT treatment.  These results provide evidence that SYT may be effective in combatting excessive sweating.
Excessive Sweating: Are Patients Suffering Unnecessarily?

Primary axillary hyperhidrosis is a disorder characterized by excessive axillary sweating. An underdiagnosed and underreported issue, this disorder affects almost 8 million people in the United States. The condition often impacts an individual's occupation and emotional well being and can even cause physical impairment. The purpose of this study is to educate primary care providers about the need for routine screening during annual physical exams, which will allow referral for appropriate treatment. We also describe options for management such as noninvasive, temporary topical solutions, oral medication, botulinum toxin A injections, surgery, and microwave energy.