nils-herrmann/clean_scirepeval huggingface dataset:
Mechanisms linking circadian clocks, sleep, and neurodegeneration
Venue: Science

Disruptions of normal circadian rhythms and sleep cycles are consequences of aging and can profoundly affect health. Accumulating evidence indicates that circadian and sleep disturbances, which have long been considered symptoms of many neurodegenerative conditions, may actually drive pathogenesis early in the course of these diseases. In this Review, we explore potential cellular and molecular mechanisms linking circadian dysfunction and sleep loss to neurodegenerative diseases, with a focus on Alzheimer's disease. We examine the interplay between central and peripheral circadian rhythms, circadian clock gene function, and sleep in maintaining brain homeostasis, and discuss therapeutic implications. The circadian clock and sleep can influence a number of key processes involved in neurodegeneration, suggesting that these systems might be manipulated to promote healthy brain aging.
Circadian Rhythm and Sleep Disruption: Causes, Metabolic Consequences, and Countermeasures
Venue: Endocrine reviews

Circadian ~24 hour) timing systems pervade all kingdoms of life and temporally optimize behavior and physiology in humans. Relatively recent changes to our environments, such as the introduction of artificial lighting, can disorganize the circadian system, from the level of the molecular clocks that regulate the timing of cellular activities to the level of synchronization between our daily cycles of behavior and the solar day. Sleep/wake cycles are intertwined with the circadian system, and global trends indicate that these, too, are increasingly subject to disruption. A large proportion of the world's population is at increased risk of environmentally driven circadian rhythm and sleep disruption, and a minority of individuals are also genetically predisposed to circadian misalignment and sleep disorders. The consequences of disruption to the circadian system and sleep are profound and include myriad metabolic ramifications, some of which may be compounded by adverse effects on dietary choices. If not addressed, the deleterious effects of such disruption will continue to cause widespread health problems; therefore, implementation of the numerous behavioral and pharmaceutical interventions that can help restore circadian system alignment and enhance sleep will be important.
Circadian Rhythm Disruption Promotes Lung Tumorigenesis.
Venue: Cell metabolism

Circadian rhythms are 24 hr oscillations that control a variety of biological processes in living systems, including two hallmarks of cancer, cell division and metabolism. Circadian rhythm disruption by shift work is associated with greater risk for cancer development and poor prognosis, suggesting a putative tumor suppressive role for circadian rhythm homeostasis. Using a genetically engineered mouse model of lung adenocarcinoma, we have characterized the effects of circadian rhythm disruption on lung tumorigenesis. We demonstrate that both physiologic perturbation (jet lag) and genetic mutation of the central circadian clock components decreased survival and promoted lung tumor growth and progression. The core circadian genes Per2 and Bmal1 were shown to have cell autonomous tumor suppressive roles in transformation and lung tumor progression. Loss of the central clock components led to increased c Myc expression, enhanced proliferation, and metabolic dysregulation. Our findings demonstrate that both systemic and somatic disruption of circadian rhythms contribute to cancer progression.
The Circadian Clock and Human Health
Venue: Current Biology

Epidemiological studies provided the first evidence suggesting a connection between the circadian clock and human health. Mutant mice convincingly demonstrate the principle that dysregulation of the circadian system leads to a multitude of pathologies. Chrono medicine is one of the most important upcoming themes in the field of circadian biology. Although treatments counteracting circadian dysregulation are already being applied (e.g. prescribing strong and regular zeitgebers) we need to comprehend entrainment throughout the body's entire circadian network before understanding the mechanisms that tie circadian dysregulation to pathology. Here, we attempt to provide a systematic approach to understanding the connection between the circadian clock and health. This taxonomy of (mis)alignments on one hand exposes how little we know about entrainment within any organism and which 'eigen zeitgeber' signals are used for entrainment by the different cells and tissues. On the other hand, it provides focus for experimental approaches and tools that will logically map out how circadian systems contribute to disease as well as how we can treat and prevent them.
Circadian System and Glucose Metabolism: Implications for Physiology and Disease
Venue: Trends in Endocrinology Metabolism

The circadian system serves one of the most fundamental properties present in nearly all organisms: it generates 24 h rhythms in behavioral and physiological processes and enables anticipating and adapting to daily environmental changes. Recent studies indicate that the circadian system is important in regulating the daily rhythm in glucose metabolism. Disturbance of this circadian control or of its coordination relative to the environmental/behavioral cycle, such as in shift work, eating late, or due to genetic changes, results in disturbed glucose control and increased type 2 diabetes risk. Therefore, an in depth understanding of the mechanisms underlying glucose regulation by the circadian system and its disturbance may help in the development of therapeutic interventions against the deleterious health consequences of circadian disruption.
Sex differences in the circadian regulation of sleep and waking cognition in humans
Venue: Proceedings of the National Academy of Sciences

Circadian rhythms affect our physiology and psychology, in health and disease. Most of our knowledge about the human circadian timing system is based on research in men. Some circadian characteristics, such as the intrinsic frequency of the circadian clock and the amplitude of the melatonin rhythm, have been shown to differ between men and women. Whether the circadian regulation of mental functions differs between men and women is unknown. Here we show that circadian rhythmicity in mental functions exhibits sex differences so that the night time impairment in cognitive performance is greater in women than in men. These findings are significant in view of shift work related cognitive deficits and disturbances of mood, which are more prevalent in women. The sleep wake cycle and circadian rhythmicity both contribute to brain function, but whether this contribution differs between men and women and how it varies across cognitive domains and subjective dimensions has not been established. We examined the circadian and sleep wake dependent regulation of cognition in 16 men and 18 women in a forced desynchrony protocol and quantified the separate contributions of circadian phase, prior sleep, and elapsed time awake on cognition and sleep. The largest circadian effects were observed for reported sleepiness, mood, and reported effort; the effects on working memory and temporal processing were smaller. Although these effects were seen in both men and women, there were quantitative differences. The amplitude of the circadian modulation was larger in women in 11 of 39 performance measures so that their performance was more impaired in the early morning hours. Principal components analysis of the performance measures yielded three factors, accuracy, effort, and speed, which reflect core performance characteristics in a range of cognitive tasks and therefore are likely to be important for everyday performance. The largest circadian modulation was observed for effort, whereas accuracy exhibited the largest sex difference in circadian modulation. The sex differences in the circadian modulation of cognition could not be explained by sex differences in the circadian amplitude of plasma melatonin and electroencephalographic slow wave activity. These data establish the impact of circadian rhythmicity and sex on waking cognition and have implications for understanding the regulation of brain function, cognition, and affect in shift work, jetlag, and aging.
Circadian misalignment increases cardiovascular disease risk factors in humans
Venue: Proceedings of the National Academy of Sciences

Shift work is a risk factor for hypertension, inflammation, and cardiovascular disease, even after controlling for traditional risk factors. Shift workers frequently undergo circadian misalignment (i.e. misalignment between the endogenous circadian system and 24 h environmental/behavioral cycles) This misalignment has been proposed to explain, in part, why shift work is a risk factor for hypertension, inflammation, and cardiovascular disease. However, the impact of circadian misalignment per se on 24 h blood pressure and inflammatory markers is poorly understood. We show under highly controlled laboratory conditions that short term circadian misalignment increases 24 h blood pressure and inflammatory markers in healthy adults. Our findings may help explain why shift work increases hypertension, inflammation, and cardiovascular disease risk. Shift work is a risk factor for hypertension, inflammation, and cardiovascular disease. This increased risk cannot be fully explained by classic risk factors. One of the key features of shift workers is that their behavioral and environmental cycles are typically misaligned relative to their endogenous circadian system. However, there is little information on the impact of acute circadian misalignment on cardiovascular disease risk in humans. Here we show by using two 8 d laboratory protocols that short term circadian misalignment (12 h inverted behavioral and environmental cycles for three days) adversely affects cardiovascular risk factors in healthy adults. Circadian misalignment increased 24 h systolic blood pressure (SBP) and diastolic blood pressure (DBP) by 3.0 mmHg and 1.5 mmHg, respectively. These results were primarily explained by an increase in blood pressure during sleep opportunities (SBP, +5.6 mmHg; DBP, +1.9 mmHg) and, to a lesser extent, by raised blood pressure during wake periods (SBP, +1.6 mmHg; DBP, +1.4 mmHg) Circadian misalignment decreased wake cardiac vagal modulation by 8 15% as determined by heart rate variability analysis, and decreased 24 h urinary epinephrine excretion rate by 7% without a significant effect on 24 h urinary norepinephrine excretion rate. Circadian misalignment increased 24 h serum interleukin 6, C reactive protein, resistin, and tumor necrosis factor a levels by 3 29% We demonstrate that circadian misalignment per se increases blood pressure and inflammatory markers. Our findings may help explain why shift work increases hypertension, inflammation, and cardiovascular disease risk.
Diversity of tea (Camellia sinensis) grown in Vietnam based on morphological characteristics and inter primer binding sites (iPBS) marker.

Six iBPS primers and twenty one morphological traits were used to assess the genetic diversity and relationships of 15 tea [Camellia sinensis (L. O. Kuntze] accessions grown in Vietnam. The similarity index matrix generated from Dice coefficient (iPBS analysis) and the dissimilarity index matrix generated from Euclidian distance coefficient (morphological analysis) were used to build the respective un weighted pair group method with arithmetic average (UPGMA) derived dendrograms revealing the genetic relationships among the tested tea accessions. The iPBS analysis showed a slightly different result as compared to the result of morphological analysis which indicated that the group of Shan and Assam type were separate from the group of China type and the hybrids related to China type. Meanwhile, the iPBS analysis clustered 15 tea genotypes into two main groups; the tea genotypes of small leaved China, Assam small leaved China hybrid and Shan large leaved China hybrid type, with small leaf size, came together into one group; the other one was mainly nested by the tea genotypes of Shan, Assam and Shan small leaved China type, with large leaf size. However, the iPBS analysis also shared the same basic agreements with the morphological analysis. All the tea genotypes, which originated from the same parents or the same type of crossing parental couple, revealed close relatedness. The results of morphological analysis are conformable with the conventional classification of tea taxa and give basic relative information among 15 tea genotypes to demonstrate particularly the result of molecular analysis. It could be concluded that iPBS is a useful DNA based marker for evaluation of genetic diversity and relationships of tea.
WIND TUNNEL TESTING OF A MULTIPLE SPAN AEROELASTIC TRANSMISSION LINE SUBJECTED TO DOWNBURST WIND

A 1:50 scale aeroelastic wind tunnel test for a multi span transmission line system is conducted at the WindEEE dome under downburst wind. WindEEE is a novel three dimensional wind testing facility capable of simulating downbursts and tornadoes. This test simulates a transmission line consisting of v shaped guyed towers holding three conductor bundles. Details about the model design, the wind field and the test setup are provided. A downburst loading case that is critical for the line design and causes unbalanced tension load on the conductors is investigated in the current study. Resulting line responses obtained from the test are compared with a previously developed finite element model by the research group at the University of Western Ontario. The comparison shows a good agreement which validates the finite element models. Results obtained from this test will be very useful to understand the behavior of the lines under downburst wind.
Influences of job performance of dental hygienists on emotional labor evaluation

The purpose of the study was to investigate the influences of job performance of dental hygienists on emotional labor evaluation.  A self administered questionnaire was completed by 203 dental hygienists working at dental hospitals and clinics in Gyeongnam and Busan from May 2014 and March 2015. The study instruments comprised general characteristics of the subjects (9 items) job performance competency (44 items) and emotional labor evaluation (29 items) by Likert 5 point scale. Data were analyzed by SPSS 21.0 program and AMOS 18.0 program.  Those who had turnover intention showed higher scores in the dental treatment cooperation category and overall job performance than those who had not. Higher job performance was shown in those who had more work experience and higher salary. The scores of emotional labor evaluation were higher in the group of higher salary and team and department leaders. The job performance had a significant impact of the emotional labor evaluation.  The job performance of dental hygienists had a significant influence on the emotional labor evaluation. Psychologic stress by work caused the dental hygienists to have depression and lower quality of life.
Opioid Abuse in Chronic Pain Misconceptions and Mitigation Strategies.
Venue: The New England journal of medicine

Chronic pain not caused by cancer is among the most prevalent and debilitating medical conditions but also among the most controversial and complex to manage. The urgency of patients' needs, the demonstrated effectiveness of opioid analgesics for the management of acute pain, and the limited therapeutic alternatives for chronic pain have combined to produce an overreliance on opioid medications in the United States, with associated alarming increases in diversion, overdose, and addiction. Given the lack of clinical consensus and research supported guidance, physicians understandably have questions about whether, when, and how to prescribe opioid analgesics for chronic pain without increasing public health risks. Here, we draw on recent research to address common misconceptions regarding the abuse related risks of opioid analgesics and highlight strategies to minimize those risks.
The Development of Coping: Implications for Psychopathology and Resilience

GOAL OF THE CHAPTER 486 TRANSACTIONAL PERSPECTIVES: COPING AS INDIVIDUAL DIFFERENCES IN APPRAISAL AND COPING PROCESSES AND RESOURCES 487 Stress, Appraisals, and Coping Associated with Adjustment and Psychopathology 488 Links between Broad Categories of Coping and Psychopathology 489 Do Subjective Appraisals of Stressful Encounters also Play a Role in Psychopathology? 493 Strategies for Emotion Regulation, Coping, and Psychopathology 495 Patterns or Profiles of Coping as Correlates of Psychopathology 496 Transactional Models of the Links between Stress, Coping, and Psychopathology 497 Critique of Individual Differences Research on Coping and Psychopathology 501 NORMATIVE DEVELOPMENTAL PERSPECTIVES: COPING AS A SET OF BASIC ADAPTIVE PROCESSES THAT ARE REORGANIZED WITH AGE 502 Normative Development of Coping during Infancy: Implicit Coping 505 Normative Development of Coping during Early Childhood: Voluntary Coping 507 Normative Development of Coping during Middle Childhood: Reflective Coping 509 Normative Development of Coping during Adolescence: Proactive Coping 512 Conclusion 514 Normative Development of Coping and Developmental Psychopathology 515 DEVELOPMENTAL SYSTEMS PERSPECTIVES: COPING AS PART OF DEVELOPMENTAL CASCADES TOWARD PSYCHOPATHOLOGY AND RESILIENCE 516 Temperament, Differential Pathways of Maladaptive Coping, and Psychopathology 517 Attachment, Differential Pathways of Maladaptive Coping, and Psychopathology 521 Parenting, Differential Pathways of Maladaptive Coping, and Psychopathology 525 Family Stress, Differential Pathways of Maladaptive Coping, and Psychopathology 527 FUTURE RESEARCH AND TRANSLATION OF RESEARCH INTO ACTION 528 The Role of Coping in Developmental Cascades toward Psychopathology and Resilience 528 Translation of Basic Research on Coping into Action 530 SUMMARY AND CONCLUSION 532
Multiple Kernel k Means Clustering with Matrix Induced Regularization
Venue: AAAI

Multiple kernel k means (MKKM) clustering aims to optimally combine a group of pre specified kernels to improve clustering performance. However, we observe that existing MKKM algorithms do not sufficiently consider the correlation among these kernels. This could result in selecting mutually redundant kernels and affect the diversity of information sources utilized for clustering, which finally hurts the clustering performance. To address this issue, this paper proposes an MKKM clustering with a novel, effective matrix induced regularization to reduce such redundancy and enhance the diversity of the selected kernels. We theoretically justify this matrix induced regularization by revealing its connection with the commonly used kernel alignment criterion. Furthermore, this justification shows that maximizing the kernel alignment for clustering can be viewed as a special case of our approach and indicates the extendability of the proposed matrix induced regularization for designing better clustering algorithms. As experimentally demonstrated on five challenging MKL benchmark data sets, our algorithm significantly improves existing MKKM and consistently outperforms the state of the art ones in the literature, verifying the effectiveness and advantages of incorporating the proposed matrix induced regularization.
ELM based multiple kernel k means with diversity induced regularization
Venue: 2016 International Joint Conference on Neural Networks (IJCNN)

Multiple kernel k means (MKKM) clustering has demonstrated good clustering performance by combining pre specified kernels. In this paper, we argue that deep relationships within data and the complementary information among them can improve the performance of MKKM. To illustrate this idea, we propose a diversity induced MKKM algorithm with extreme learning machine (ELM) based feature extracting method. First, ELM, which has randomly chosen weights of hidden and output nodes, is applied to thoroughly extract features from data by generating different numbers of hidden nodes and using different functions. Second, an MKKM algorithm with diversity induced regularization is utilized to explore the complementary information among kernels constructed from features. The problem could be solved efficiently by alternating optimization. Experimental results demonstrate that the proposed method outperforms state of the art kernel methods.
Joint diversity regularization and graph regularization for multiple kernel k means clustering via latent variables
Venue: Neurocomputing

Multiple kernel k means (MKKM) clustering algorithm is widely used in many machine learning and computer vision tasks. This algorithm improves clustering performance by extending the traditional kernel k means (KKM) clustering algorithm to a multiple setting by combining a group of pre specified kernels. In this paper, we develop and propose a multiple kernel k means clustering via latent variables (MKKLV) algorithm, in which base kernels can be adaptively adjusted with respect to each sample. To improve the effectiveness of the kernel specific and sample specific characteristics of the data, joint diversity regularization and graph regularization are utilized in the MKKLV algorithm. An efficient three step iterative algorithm is employed to jointly optimize the kernel specific and sample specific coefficients. Experiments validate that our algorithm outperforms state of the art techniques on several different benchmark datasets.
Co regularized kernel k means for multi view clustering
Venue: 2016 23rd International Conference on Pattern Recognition (ICPR)

In clustering applications, multiple views of the data are often available. Although clustering could be done within each view independently, exploiting information across views is promising to gain clustering accuracy improvement. A common assumption in the field of multi view learning is that the clustering results from multiple views should be consistent with a latent clustering. However, the potential noise among some views would make this assumption difficult to be satisfied, which finally hurts the clustering performance. To address this issue, we propose a novel clustering algorithm where the intrinsic clustering is found by maximizing the sum of weighted similarities between clusterings of different views. Weights that indicate the qualities of views are learned simultaneously along with the latent clustering and clusterings of different views. A three step alternative algorithm is designed to solve the problem efficiently. Empirical comparisons with a number of baselines on various datasets confirm the efficacy of our approach.