Miracle-dz/UniFAR-FTUs huggingface dataset:
Hypermethylation of collagen α2 (I) gene (COL1A2) is an independent predictor of survival in head and neck cancer.

OBJECTIVES Collagen production plays a role in the development of tumors from cancer cells. The aim of the present study is to examine the involvement of epigenetic alteration of Collagen α2 (I) (COL1A2) gene expression in cases of head and neck squamous cell carcinoma (HNSCC). METHODS COL1A2 expression was examined in a panel of cell lines using RT-PCR. The methylation status of the COL1A2 promoter was studied using bisulfate sequencing and methylation-specific PCR (MSP). RESULTS COL1A2 expression was absent in 6 of 11 (54.5%) UM-SCC cell lines, whereas three nonmalignant cell lines had stable expressions. MSP analysis showed that 46/98 (46.9%) contained methylated alleles. COL1A2 methylation was significantly correlated with tumor size (P = 0.041), lymph node status (P = 0.008), tumor stage (P = 0.011), H-cadherin methylation (P = 0.039) and disease-free survival (P = 0.005). On multivariate Cox proportional hazard regression, which included age, sex, smoking status, and alcohol exposure, both tumor stage and COL1A2 methylation remained independent prognostic factors. CONCLUSIONS This study suggests that CpG hypermethylation is a likely mechanism of COL1A2 gene inactivation, supporting the hypothesis that the COL1A2 gene may play a role in the tumorigenesis of HNSCC and may serve as an important biomarker.
Vitamin D Status, Disease Activity, and Endothelial Dysfunction in Early Rheumatoid Arthritis Patients

Cardiovascular diseases represent important complications in rheumatoid arthritis (RA) patients, generated by an accelerated atherosclerosis. The aim of this study is represented by the assessment of the correlations between serum levels of vitamin D, disease activity, and endothelial dysfunction in patients with early RA. Material and Methods. The study was performed on a group of 35 patients with early RA and 35 healthy subjects matched for age and gender, as controls. In all studied subjects, the following were determined: inflammatory markers, insulin resistance, vitamin D levels, and endothelial dysfunction. Statistical analysis were performed using the Student's t-test and the Pearson's test. p values of less than 0.05 were considered statistically significant. Results. The group of patients with RA patients presented inflammation, low levels of vitamin D, elevated insulin resistance, and reduced flow-mediated vasodilation, statistically significant compared to the control group (p < 0.00001). Significant inverse correlations between the levels of 25(OH) vitamin D and DAS28, respective insulin resistance, and significant positive correlation between 25(OH) vitamin D and endothelial function were demonstrated. Conclusion. In early RA patients with moderate and high disease activity, low serum levels of vitamin D were associated with disease activity, increased insulin resistance, and endothelial dysfunction.
Natural Image Bases to Represent Neuroimaging Data

Visual inspection of neuroimagery is susceptible to human eye limitations. Computerized methods have been shown to be equally or more effective than human clinicians in diagnosing dementia from neuroimages. Nevertheless, much of the work involves the use of domain expertise to extract handcrafted features. The key technique in this paper is the use of cross-domain features to represent MRI data. We used a sparse autoencoder to learn a set of bases from natural images and then applied convolution to extract features from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. Using this new representation, we classify MRI instances into three categories: Alzheimer's Disease (AD), Mild Cognitive Impairment (MCI) and Healthy Control (HC). Our approach, in spite of being very simple, achieved high classification performance, which is competitive with or better than other approaches.
Joint Contention and Sleep Control for Lifetime Maximization in Wireless Sensor Networks

In this paper, we propose a joint control scheme to maximize network lifetime in wireless sensor networks with joint contention and sleep control. For the contention resolution of sensor nodes in the network, we consider the p-persistent contention protocol. Also, the sleep control is introduced with the probability of turning off the transceiver of a sensor node. Using the probabilities of contention and sleep, we formulate the network lifetime maximization problem to satisfy the throughput requirement and each link's signal to noise interference ratio (SINR) requirement. Finally, we demonstrate that the proposed scheme improves the lifetime of wireless sensor networks compared to the existing schemes.
Celastrol Inhibits Lung Infiltration in Differential Syndrome Animal Models by Reducing TNF-α and ICAM-1 Levels while Preserving Differentiation in ATRA-Induced Acute Promyelocytic Leukemia Cells

All-trans retinoic acid (ATRA) is a revolutionary agent for acute promyelocytic leukemia (APL) treatment via differentiation induction. However, ATRA treatment also increases cytokine, chemokine, and adhesive molecule (mainly ICAM-1) expression, which can cause clinical complications, including a severe situation known as differentiation syndrome (DS) which can cause death. Therefore, it is of clinical significance to find a strategy to specifically blunt inflammatory effects while preserving differentiation. Here we report that the natural compound, celastrol, could effectively block lung infiltrations in DS animal models created by loading ATRA-induced APL cell line NB4. In ATRA-treated NB4 cells, celastrol could potently inhibit ICAM-1 elevation and partially reduce TNF-α and IL-1β secretion, though treatment showed no effects on IL-8 and MCP-1 levels. Celastrol’s effect on ICAM-1 in ATRA-treated NB4 was related to reducing MEK1/ERK1 activation. Strikingly and encouragingly, celastrol showed no obvious effects on ATRA-induced NB4 differentiation, as determined by morphology, enzymes, and surface markers. Our results show that celastrol is a promising and unique agent for managing the side effects of ATRA application on APL, and suggest that hyper-inflammatory ability is accompanied by, but not necessary for, APL differentiation. Thus we offered an encouraging novel strategy to further improve differentiation therapy.
[Early identification of developmental language disorders--predictive value of the German version of the CDI--infant form (ELFRA-1)].

BACKGROUND Early identification of developmental language disorders is a precondition for early intervention and therefore of high clinical relevance. The ELFRA-1 was constructed to identify children at risk for language disorders in the context of the routine examination of children at the age of 12 months. The aim of the study was to determine the predictive validity of this screening tool. SUBJECTS AND METHOD 121 parents completed the questionnaire for their 12 months old children. One year later the language development was assessed by means of the ELFRA-2, the German version of the CDI for two year old children. RESULTS 63% of the children were correctly classified. The sensitivity amounted to 52% and the specificity to 65%. The RATZ-index (relative improvement of the hit rate in comparison to the random hit rate) was 23%, which has to be considered as unsatisfying. Improvement of language abilities were less likely in boys compared to girls and in cases of low educational background of the mother. CONCLUSIONS The prognostic validity of the ELFRA-1 is insufficient and too low to identify children at risk for later language impairment. The screening overlooked too many late talkers and classified too many normally developed children as language impaired. The ELFRA-1 can not be recommended as a useful method for the early identification of language impaired children at the age of 12 months.
Base station polarization diversity reception for mobile radio

Base station polarization diversity reception in which signals are received by dual polarization (ex. ±45° polarization) is discussed. A theoretical analysis is presented on correlation coefficient ρ between diversity branches, and received signal level decrease L caused by polarization difference at the base and mobile station. The generalized expressions of ρ and L are then derived. Measurements were also carried out at 900 MHz in an urban area. Consequently, it was found that the ρ and L values are expressed by three factors, ρ is lower than 0.6 and L is smaller than 2.5 dB. It is concluded that this polarization diversity reception can be used as an effective diversity reception.
A Blended Model of Electronic Medical Record System Adoption in Canadian Medical Practices

In this paper, we develop and validate a comprehensive theoretical model of electronic medical record (EMR) system adoption in Canadian medical practices. Canada lags other developed countries in the adoption of information technology (IT) in healthcare, and medical practice adoption of EMRs is particularly low. Most Canadian medical practices have the distinct feature of blending characteristics of both individual physicians and small clinics in private practice. We built a theoretical model combining individual-type and organizational-type perceptions (from one point of view) and opportunities and barriers (from another point of view) and tested it with 119 physicians from across Canada. Results show a reasonably valid model explaining 55.3 percent of the physicians’ intent to adopt EMRs in their clinics. We found that physicians would adopt EMRs if they saw these systems as first being easy to use and second as being useful. Physicians’ innovativeness regarding the use of new IT was an additional favoring factor. Conversely, physicians would choose not to adopt EMRs if they feared such systems would not perform as expected, would involve possible legal and privacy risks, would affect clinics’ productivity, and would not be a justified adoption altogether. Overall, we found that physicians saw more opportunities than obstacles in using EMRs in their practices.
To BLOB or Not To BLOB: Large Object Storage in a Database or a Filesystem?

Application designers often face the question of whether to store large objects in a filesystem or in a database. Often this decision is made for application design simplicity. Sometimes, performance measurements are also used. This paper looks at the question of fragmentation - one of the operational issues that can affect the performance and/or manageability of the system as deployed long term. As expected from the common wisdom, objects smaller than 256KB are best stored in a database while objects larger than 1M are best stored in the filesystem. Between 256KB and 1MB, the read:write ratio and rate of object overwrite or replacement are important factors. We used the notion of "storage age" or number of object overwrites as way of normalizing wall clock time. Storage age allows our results or similar such results to be applied across a number of read:write ratios and object replacement rates.
Benford's Law and Its Application to Lightning Data

Benford's law applies to a wide variety of natural and man-made datasets and it has been successfully applied to test the integrity of data and to detect possible fraud and anomalous results in economy, politics, and management studies. In this paper, we investigate the applicability of Benford's law to lightning data. To do this, we use lightning data in Switzerland obtained using the European Cooperation for Lightning Detection (EUCLID) network. The considered dataset consists of the cloud-to-ground flashes in Switzerland for the period from 1999 till 2007. First the total number of negative and positive flashes per day is considered in the analysis. It is shown that the obtained distribution is in very good agreement with Benford's law. The same analysis is repeated considering in the dataset only the flashes containing return strokes with absolute peak currents lower than 5 kA, for which the detection efficiency of the lightning location network is expected to be lower. The resulting distribution shows less agreement with Benford's law. The obtained results suggest that Benford's law may find an interesting application in the evaluation of the detection efficiency of a given lightning location network.
Emotional reactions in moral decision-making are influenced by empathy and alexithymia

ABSTRACT The role of emotional processes in driving moral choices remains debated. In particular, diminished emotional processing and reduced empathy have been associated with unusual high rates of utilitarian responses in moral judgments while, to date, the effects of diminished emotional processing and empathy on moral decision-making have been only partially considered. In this study, we investigated the influence of empathy and alexithymia on behavior and emotional responses while participants performed a moral decision task. Self-report (valence and arousal ratings) and physiological (skin conductance and heart rate) measures were collected during the task. Results showed that empathy and alexithymia shaped emotional reactions to moral decisions but did not bias moral choices. The more empathic the participants, the more dilemmas were perceived as unpleasant and arousing, and the greater the increase in skin conductance. Conversely, alexithymia was characterized by a reduced physiological activation during moral decisions, but normal self-report ratings. Heart rate was not modulated by empathy or alexithymia. These results add new evidence to the field of moral decision showing that empathy and alexithymia modulate emotional reactions to moral decision.
Human Nature Prepares for a Momentous Leap.

Readers should know that Dr. Graves was not entirely satisfied with this piece, though it is by far the most popular of the articles and quite readable as an introduction to the theory. Helixes one and two are reversed in later papers so that problems of existence come first as A, B, C, etc., rather than N, O, P, etc., as in this writing. Graves was also not happy with some of the depictions of GT and HU characteristics. Human Nature Prepares for a Momentous Leap
Growth hormone secretagogues prevent dysregulation of skeletal muscle calcium homeostasis in a rat model of cisplatin‐induced cachexia

Cachexia is a wasting condition associated with cancer types and, at the same time, is a serious and dose‐limiting side effect of cancer chemotherapy. Skeletal muscle loss is one of the main characteristics of cachexia that significantly contributes to the functional muscle impairment. Calcium‐dependent signaling pathways are believed to play an important role in skeletal muscle decline observed in cachexia, but whether intracellular calcium homeostasis is affected in this situation remains uncertain. Growth hormone secretagogues (GHS), a family of synthetic agonists of ghrelin receptor (GHS‐R1a), are being developed as a therapeutic option for cancer cachexia syndrome; however, the exact mechanism by which GHS interfere with skeletal muscle is not fully understood.
Influence Estimation and Maximization in Continuous-Time Diffusion Networks

If a piece of information is released from a set of media sites, can it spread, in 1 month, to a million web pages? Can we efficiently find a small set of media sites among millions that can maximize the spread of the information, in 1 month? The two problems are called influence estimation and maximization problems respectively, which are very challenging since both the time-sensitive nature of the problems and the issue of scalability need to be addressed simultaneously. In this article, we propose two algorithms for influence estimation in continuous-time diffusion networks. The first one uses continuous-time Markov chains to estimate influence exactly on networks with exponential, or, more generally, phase-type transmission functions, but does not scale to large-scale networks, and the second one is a highly efficient randomized algorithm, which estimates the influence of every node in a network with general transmission functions, |ν| nodes and |ε| edges to an accuracy of ε using n = O(1/ε2) randomizations and up to logarithmic factors O(n|ε|+n|ν| computations. We then show that finding the set of most influential source nodes in a continuous time diffusion network is an NP-hard problem and develop an efficient greedy algorithm with provable near-optimal performance. When used as subroutines in the influence maximization algorithm, the exact influence estimation algorithm is guaranteed to find a set of C nodes with an influence of at least (1 − 1/e)OPT and the randomized algorithm is guaranteed to find a set with an influence of at least 1 − 1/e)OPT − 2Cε, where OPT is the optimal value. Experiments on both synthetic and real-world data show that the proposed algorithms significantly improve over previous state-of-the-art methods in terms of the accuracy of the estimated influence and the quality of the selected nodes to maximize the influence, and the randomized algorithm can easily scale up to networks of millions of nodes.
The Immediate Usability of Graffiti

We present four empirical measures of the immediate usability of Graffiti, a character recognizer for pen-based computers. Since speed is fully controlled by the user, we measured the accuracy attainable after minimal exposure. The first measure, 79%, is the inherent accuracy, or the extent to which Graffiti strokes match letters in the Roman alphabet. The other three measures were obtained in a formal experiment. We asked 25 subjects to enter the alphabet five times into a pen-based computer under three conditions: (a) following one minute studying the Graffiti reference chart, (b) following five minutes practicing with Graffiti, and (c) following a one week lapse with no intervening practice. The accuracy was 86%, 97%, and 97%, respectively. These are very respectable figures given the limited exposure of subjects. The third figure represents complete retention following a one-week lapse. We present analyses of the errors on a character-by-character basis, noting that poor performing characters should be emphasized in tutorials and other learning aids for new users.
Phase Noise and Noise Induced Frequency Shift in Stochastic Nonlinear Oscillators

Phase noise plays an important role in the performances of electronic oscillators. Traditional approaches describe the phase noise problem as a purely diffusive process. In this paper we develop a novel phase model reduction technique for phase noise analysis of nonlinear oscillators subject to stochastic inputs. We obtain analytical equations for both the phase deviation and the probability density function of the phase deviation. We show that, in general, the phase reduced models include non Markovian terms. Under the Markovian assumption, we demonstrate that the effect of white noise is to generate both phase diffusion and a frequency shift, i.e. phase noise is best described as a convection-diffusion process. The analysis of a solvable model shows the accuracy of our theory, and that it gives better predictions than traditional phase models.
Multi-cloud oblivious storage

We present a 2-cloud oblivious storage (ORAM) system that achieves 2.6X bandwidth cost between the client and the cloud. Splitting an ORAM across 2 or more non-colluding clouds allows us to reduce the client-cloud bandwidth cost by at least one order of magnitude, shifting the higher-bandwidth communication to in-between the clouds where bandwidth provisioning is abundant. Our approach makes ORAM practical for bandwidth-constrained clients such as home or mobile Internet connections. We provide a full-fledged implementation of our 2-cloud ORAM system, and report results from a real-world deployment over Amazon EC2 and Microsoft Azure.
Utility of preoperative functional magnetic resonance imaging for identifying language cortices in patients with vascular malformations.

OBJECT The goal of this study was to evaluate the utility of preoperative functional magnetic resonance (fMR) imaging in the prediction of whether a given cortical area would be deemed essential for language processing by electrocortical stimulation mapping (ESM). METHODS The authors studied patients with vascular malformations, specifically arteriovenous malformations (AVMs) and cavernous angiomas, in whom blood-flow patterns are not normal and in whom a perfusion-dependent mapping signal may be questionable. Ten patients were studied (seven harboring AVMs and three with cavernous angiomas). The authors used a battery of linguistic tasks, including visual object naming, word generation, auditory responsive naming, visual responsive naming, and sentence comprehension, to identify brain regions that were consistently activated across expression and comprehension linguistic tasks. In a comparison of ESM and fMR imaging activations, the authors varied the matching criteria (overlapping activations, adjacent activations, and deep activations) and the radii of influence of ESM (2.5, 5, and 10 mm) to determine the effects of these factors on the sensitivity and specificity of fMR imaging. The sensitivity and specificity of fMR imaging were dependent on the task, lobe, and matching criterion. For the population studied, the sensitivity and specificity of fMR imaging activations during expressive linguistic tasks were found to be up to 100 and 66.7%, respectively, in the frontal lobe, and during comprehension linguistic tasks up to 96.2 and 69.8%, respectively, in the temporal and parietal lobes. The sensitivity and specificity of each disease population (patients with AVMs and those with cavernous angiomas) and of individuals were consistent with those values reported for the entire population studied. CONCLUSIONS The authors conclude that preoperative fMR imaging is a highly sensitive preoperative planning tool for the identification of which cortical areas are essential for language and that this imaging modality may play a future role in presurgical planning for patients with vascular malformations.
Pesticide Risk Perception and Biomarkers of Exposure in Florida Female Farmworkers

Objective: To compare workplace characteristics, workplace behaviors, and the health beliefs of female farmworkers of childbearing age with actual biomarkers of exposure to organophosphate pesticides and to the fungicide mancozeb. Methods: Hispanic and Haitian farmworkers between the ages of 18 and 40 years working in nursery or fernery operations were recruited to participate in a cross-sectional survey, examining demographics, work practices, work-related hygiene, and pesticide exposure beliefs. Single-void (spot) urine samples were analyzed for organophosphate and ethylenethiourea metabolites. Results: Women in nurseries worried less frequently about the effects of pesticides on their health than those in fernery operations. In summary, organophosphate and ethylenethiourea levels in nursery workers were significantly higher than levels in fernery workers and the control group. Conclusions: Results showed that perceived pesticide exposure did not correspond to actual metabolite levels within differing agricultural subpopulations.