Miracle-dz/UniFAR-FTUs huggingface dataset:
Childhood trauma and negative memory bias as shared risk factors for psychopathology and comorbidity in a naturalistic psychiatric patient sample

The authors would like to apologize for the errors in the original paper of Vrijsen et al. (2017). Due to mislabeling of one of the childhood trauma variables, the childhood trauma index scores of some participants were incorrect. Upon correction of the error, the pattern of results remained the same, resulting in the same conclusions. The description of the labeling of the childhood trauma variables on page 3 should be as follows: “The frequency per type of childhood trauma was scored on a five‐point Likert scale: 0 = not, 1 = once, 2 = sometimes, 3 = regularly, 4 = often, 5 = very often. Only ‘emotional neglect’ was scored on a four‐ point Likert scale (0‐4, without the answer option ‘once’). ” This also altered the range of the childhood trauma frequency score, resulting in a correction on page 5, “the diversity variable was the sum of the types of childhood trauma (possible range 0‐4) an in‐ dividual experienced and the frequency variable represented the total frequency rating across types of childhood trauma (possible range 0‐19). ” In the “Mediation model for presence of comorbidity” section on page 4, the results now read “The standardized indirect effect ‘ab’ was 0.01. The ratio of the indirect effect to the direct effect was 0.17 (referred to as PM). The PM value provides an indication of the effect size. The bootstrapped unstandardized indirect effect 95% confidence interval ranged from 0.005 to 0.03, indicating a sig‐ nificant indirect effect. ” In the “Associations between childhood trauma, negative mem‐ ory bias, and number of psychiatric disorders diagnosed” section on page 5, the results now read: “The relationship between childhood trauma and number of current psychiatric disorders diagnosed was mediated by negative memory bias with a standardized indirect ef‐ fect ‘ab’ of 0.02, and a PM value of 0.12. The bootstrapped unstan‐ dardized indirect effect 95% confidence interval ranged from 0.01 to 0.06. ” Furthermore, the corrected footnote on page 5 reads: “The standardized indirect effect ‘ab’ was still 0.02 and the PM value was 0.12. ” In Table 2, the variable of “Negative memory bias” mean should be “0.3” instead of “0.8”. Figures 1, 2 have also been corrected accordingly, below are the updated figures.
Family physicians' utility of social media: a survey comparison among family medicine residents and physicians

Introduction Social media has become ubiquitous and has brought a dramatic change in health services. Little is known about its use by family physicians and residents for personal or professional purpose. The aim of the current study was to evaluate the utility of social media among family medicine residents and consultants. Methods The collection of data was through the use of a five part questionnaire developed by researchers. The questionnaire was delivered to 70 physicians and 100 residents, out of which 132questionnaires were completed, representing a 78 percent response rate. Results Our findings demonstrate that there was an overall high use of social media. Females used social media more for general education and professional purposes. Men, by contrast, used it more frequently for personal purposes. The participants in this study appeared to consider social media as having several useful dimensions, such as: enabling them to accomplish job tasks, improve job performance, productivity and more effective patient care when using social media. Conclusions To date, limited studies have compared social media use among family physicians and residents. This study may serve as an initial step for future studies explaining the pattern of use among physicians.
Relation of hemoglobin level to no-reflow in patients with ST-segment elevation myocardial infarction undergoing primary coronary intervention

Introduction The primary goal in the management of acute ST segment elevation myocardial infarction (STEMI) is to open the occluded artery at an early stage. The development of no-reflow is multifactorial, and the etiology is not fully understood. There is accumulating evidence that anemia is related to a series of severe complications in cardiovascular disease (CVD) such as thromboembolic events, bleeding complications, uncontrolled hypertension, and inflammation characterized by elevated levels of inflammatory cytokines. Aim We investigated the relationship between hemoglobin level and the no-reflow of infarct-related artery (IRA) in patients with STEMI undergoing primary percutaneous coronary intervention (PPCI). Material and methods A total of 3804 patients with acute STEMI who underwent PPCI were enrolled. The patients were divided into two groups according to thrombolysis in myocardial infarction (TIMI) flow grades after PPCI. Hematological parameters were measured on admission. Univariate and multivariate logistic regression analyses were conducted to assess the association between hemoglobin level and no-reflow. Results In the current study, 471 (12.4%) patients presented with no-reflow after PPCI. The patients in the no-reflow group had a significantly lower hemoglobin level (12.1 ±1.9 g/dl vs. 13.8 ±1.8 g/dl, p < 0.001). The multivariate logistic regression models revealed that hemoglobin level (OR = 0.564, 95% CI: 0.526–0.605; p < 0.001) was an independent predictor of development of no-reflow. The cutoff value for hemoglobin level was 11.5 g/dl with sensitivity of 83.0% and specificity of 80.0% (AUC = 0.844, 95% CI: 0.821–0.867; p < 0.001). Conclusions Our results suggest that hemoglobin level showed a moderate diagnostic performance regarding the prediction of no-reflow in patients with STEMI undergoing PPCI.
Pancreatic carcinoma cells colonizing the liver modulate the expression of their extracellular matrix genes

Liver is the main target of pancreatic ductal adenocarcinoma (PDAC) metastasis. Here, a rat model was used for analysing gene expression modulations during liver colonization. ASML PDAC cells were injected to isogenic rats and re-isolated at various stages of liver colonization for RNA isolation or re-cultivation. Microarrays were used for analysing mRNA and miRNA profiles of expression. The results were partially confirmed by (q) RT-PCR and western blot. Selected genes were knocked down by siRNA transfection and the resulting cell behaviour was analysed. The ratio of up- and down regulated genes decreased from 20:1 (early stage) to 1.2:1 (terminal stage). Activation of cancer relevant gene categories varied between stages of liver colonization, with a nadir in the intermediate stage. The cells' environment triggered up to hundredfold changed expression for collagens, matrix metalloproteinases and chemokines. These modulations in mRNA expression were related to respective changes at miRNA levels. Gene expression knockdown of Mmp2 and Ccl20, which were highly modulated in vivo, was correlated with reduced proliferation and migration in vitro. Thus, target genes and temporal alterations in expression were identified, which can serve as basis for future therapeutic or diagnostic purposes.
A New Method for Detecting P300 Signals by Using Deep Learning: Hyperparameter Tuning in High-Dimensional Space by Minimizing Nonconvex Error Function

Background: P300 signal detection is an essential problem in many fields of Brain-Computer Interface (BCI) systems. Although deep neural networks have almost ubiquitously used in P300 detection, in such networks, increasing the number of dimensions leads to growth ratio of saddle points to local minimums. This phenomenon results in slow convergence in deep neural network. Hyperparameter tuning is one of the approaches in deep learning, which leads to fast convergence because of its ability to find better local minimums. In this paper, a new adaptive hyperparameter tuning method is proposed to improve training of Convolutional Neural Networks (CNNs). Methods: The aim of this paper is to introduce a novel method to improve the performance of deep neural networks in P300 signal detection. To reach this purpose, the proposed method transferred the non-convex error function of CNN) into Lagranging paradigm, then, Newton and dual active set techniques are utilized for hyperparameter tuning in order to minimize error of objective function in high dimensional space of CNN. Results: The proposed method was implemented on MATLAB 2017 package and its performance was evaluated on dataset of Ecole Polytechnique Fédérale de Lausanne (EPFL) BCI group. The obtained results depicted that the proposed method detected the P300 signals with 95.34% classification accuracy in parallel with high True Positive Rate (i.e., 92.9%) and low False Positive Rate (i.e., 0.77%). Conclusions: To estimate the performance of the proposed method, the achieved results were compared with the results of Naive Hyperparameter (NHP) tuning method. The comparisons depicted the superiority of the proposed method against its alternative, in such way that the best accuracy by using the proposed method was 6.44%, better than the accuracy of the alternative method.
The Empirical Mode Decomposition-Decision Tree Method to Recognize the Steady-State Visual Evoked Potentials with Wide Frequency Range

Background: The empirical mode decomposition (EMD) is a technique to analyze the steady-state visual evoked potential (SSVEP) which decomposes the signal into its intrinsic mode functions (IMFs). Although for the limited stimulation frequency range, choosing the effective IMF leads to good results, but extending this range will seriously challenge the method so that even the combination of IMFs is associated with error. Methods: Stimulation frequencies ranged from 6 to 16 Hz with an interval of 0.5 Hz were generated using Psychophysics toolbox of MATLAB. SSVEP signal was recorded from six subjects. The EMD was used to extract the effective IMFs. Two features, including the frequency related to the peak of spectrum and normalized local energy in this frequency, were extracted for each of six conditions (each IMF, the combination of two consecutive IMFs and the combination of all three IMFs). Results: The instantaneous frequency histogram and the recognition accuracy diagram indicate that for wide stimulation frequency range, not only one IMF, but also the combination of IMFs does not have desirable efficiency. Total recognition accuracy of the proposed method was 79.75%, while the highest results obtained from the EMD-fast Fourier transform (FFT) and the CCA were 72.05% and 77.31%, respectively. Conclusion: The proposed method has improved the recognition rate more than 2.4% and 7.7% compared to the CCA and EMD-FFT, respectively, by providing the solution for situations with wide stimulation frequency range.
Passivity and passivity indices of nonlinear systems under operational limitations using approximations

In this paper, we will discuss how operational limitations affect input–output behaviours of the system. In particular, we will provide a formulation for passivity and passivity indices of a nonlinear system given operational limitations on the input and state variables. This formulation is presented in the form of local passivity and indices. We will provide optimisation based formulation to derive passivity properties of the system through polynomial approximations. Two different approaches are taken to approximate the nonlinear dynamics of a system through polynomial functions; namely, Taylor's theorem and a multivariate generalisation of Bernstein polynomials. For each approach, conditions for stability, dissipativity, and passivity of a system, as well as methods to find its passivity indices, are given. Two different methods are also presented to reduce the size of the optimisation problem in Taylor's theorem approach. Examples are provided to show the applicability of the results.
Topology, homogeneity and scale factors for object detection: application of eCognition software for urban mapping using multispectral satellite image

The research scope of this paper is to apply spatial object based image analysis (OBIA) method for processing panchromatic multispectral image covering study area of Brussels for urban mapping. The aim is to map different land cover types and more specifically, built-up areas from the very high resolution (VHR) satellite image using OBIA approach. A case study covers urban landscapes in the eastern areas of the city of Brussels, Belgium. Technically, this research was performed in eCognition raster processing software demonstrating excellent results of image segmentation and classification. The tools embedded in eCognition enabled to perform image segmentation and objects classification processes in a semi-automated regime, which is useful for the city planning, spatial analysis and urban growth analysis. The combination of the OBIA method together with technical tools of the eCognition demonstrated applicability of this method for urban mapping in densely populated areas, e.g. in megapolis and capital cities. The methodology included multiresolution segmentation and classification of the created objects.
Virtual Web Based Personalized PageRank Updating

Growing popularity of social networks demands a highly efficient Personalized PageRank (PPR) updating due to the fast-evolving web graphs of enormous size. While current researches are focusing on PPR updating under link structure modification, efficiently updating PPR when node insertion/ deletion involved remains a challenge. In the previous work called Virtual Web (VW), a few VW architectures are designed, which results in some highly effective initializations to significantly accelerate PageRank updating under both link modification and page insertion/deletion. In the paper, under the general scenario of link modification and node insertion/deletion we tackle the fast PPR updating problem. Specifically, we combine VW with the TrackingPPR method to generate initials, which are then used by the Gauss-Southwell method for fast PPR updating. The algorithm is named VWPPR method. In extensive experiments, three real-world datasets are used that contain 1~5.6M nodes and 6.7M~129M links, while a node perturbation of 40k and link perturbation of 1% are applied. Comparing to the more recent LazyForwardUpdate method, which handles the general PPR updating problem, the VWPPR method is 3~6 times faster in terms of running time, or 4.4~10 times faster in terms of iteration numbers.
Resource-Scalable CNN Synthesis for IoT Applications

State-of-the-art image recognition systems use sophisticated Convolutional Neural Networks (CNNs) that are designed and trained to identify numerous object classes. Such networks are fairly resource intensive to compute, prohibiting their deployment on resource-constrained embedded platforms. On one hand, the ability to classify an exhaustive list of categories is excessive for the demands of most IoT applications. On the other hand, designing a new custom-designed CNN for each new IoT application is impractical, due to the inherent difficulty in developing competitive models and time-to-market pressure. To address this problem, we investigate the question of: "Can one utilize an existing optimized CNN model to automatically build a competitive CNN for an IoT application whose objects of interest are a fraction of categories that the original CNN was designed to classify, such that the resource requirement is proportionally scaled down? " We use the term resource scalability to refer to this concept, and develop a methodology for automated synthesis of resource scalable CNNs from an existing optimized baseline CNN. The synthesized CNN has sufficient learning capacity for handling the given IoT application requirements, and yields competitive accuracy. The proposed approach is fast, and unlike the presently common practice of CNN design, does not require iterative rounds of training trial and error.
On-line Remote EKG as a Web Service

A 3-leads, non-diagnostic EKG has a role in emergency rescue and homecare. In this paper we introduce the design and a prototype of a service, provided to a doctor and a patient, for the on-line remote visualization of patient's 3-leads EKG. The architecture is based on the HTTP protocol, using commercial off-the-shelf devices to implement the sensor on patient's side, a browser on a laptop PC on the doctor's side as viewer, and a cloud container to connect the two using Websockets. A prototype is built to evaluate signal latency, power consumption of the patient side device, and the quality of the rendering. After some experiments, latency is measured below $1sec$, and power consumption is estimated in the 2A*3.3V range; visualization is comparable to commercial, non-diagnostic products. The prototype patient device is portable, and can be operated using rechargeable battery packs. Its cost is below 100\$, and all the required equipment is commercially available. The architecture is ready for on field evaluation, and we indicate how to improve power consumption while reducing cost.
Association of rs1042522 SNP with Clinicopathologic Factors of Breast Cancer Patients in the Markazi Province of Iran

BACKGROUND: The nucleotide changes in different genetic loci increased the incidence risk of breast cancer. AIM: The aim of present study was to investigate genotype distribution at codon 72 of the TP53 gene (rs1042522) in breast cancer patients to achieve a potential diagnostic marker related to some demographic feathers. METHODS: In our case-control study, blood samples were collected from a total of 34 patients harboured breast cancer. DNA was extracted, and nested-PCR was performed. Products were digested with AccII and subsequently were sequenced. Results were compared with samples characteristics. RESULTS: The PCR results indicated the correct implementation of extraction and amplification protocol. The genotypic distribution at codon 72 of TP53 in control group was 20%, 62.4% and 16.6% for Arg (wildtype), Arg/Pro (heterozygous) and Pro (homozygous variant) respectively. Also, this distribution in the patient group was 23.52% homozygous, 50% heterozygous, and 26.47% another homozygous variant (Adjusted odds ratio: 1.12 and 95%CI = 0.57 to 2.2, P = 0.03). The absence of Arg at codon 72 of TP53 is relevant with age higher than 40 years and metastasis to other organs. CONCLUSION: Polymorphism at codon 72 of TP53 was associated with high-grades of breast cancer risk and different responses to chemotherapy treatment. It is recommended genotype distribution of codon 72 of TP53 before chemotherapy.
A Cross-Sectional Study Examining the Correlation between Nocturnal Melatonin Level and Sleep Quality in Patients Admitted To the Cardiac Care Unit

BACKGROUND: Quality of sleep, as a basic need, is an important factor for surviving patients in hospitals. Many factors may contribute to disturbing patients sleep, such as continuous ambient light, is required for healthcare providers to monitor patients. Ambient light can influence patients’ quality of sleep due to melatonin secretion. AIM: Study aimed to determine the correlation between nocturnal melatonin levels and sleep quality in patients admitted to the Cardiac Care Units (CCU). MATERIAL AND METHODS: This cross-sectional study was done on inpatients of CCUs at Amir-Almomenin Hospital in Kordkoy city, a cardiac referral hospital in the northeastern of Iran in 2015. Sixty-eight inpatients were selected through convenience sampling. Before data gathering light level of CCUs was measured every one hour in 2 days, the quality of nocturnal sleep was investigated through Verran and Snyder-Halpern (VSH) Sleep Scale at the second night of admission urinary melatonin level was measured at the same night in all urine excreted between 22:00 pm and 07:00 am. RESULTS: The mean and standard deviation (SD) score of sleep quality in three dimensions of sleep disturbance, sleep effectiveness and sleep supplementation were 336.6 ± 149.9, 269.0 ± 82.2, and 175.2 ± 30.7, respectively. Also, the mean and SD of nocturnal urinary melatonin levels was 323.02 ± 136.21 pg/ml. There was not a significant correlation between level of nocturnal melatonin and three domains of sleep quality; sleep disturbance (r = 0.005, P = 0.968), sleep effectiveness (r = 0.090, P = 0.464), and sleep supplementation (r = -0.037, P = 0.763). CONCLUSION: According to the result, most CCUs patients suffer from sleep disturbance. However, there was no correlation between the level of melatonin and sleep quality. There is a need for recognising the reasons for sleep disturbances in Cardiac Care Units. It is imperative for care providers to be able to recognise the causes of sleep disturbances and to modify environmental factors such as ambient light to improve sleep quality in hospitalised patients.
Streptomyces Levis ABRIINW111 Inhibits SW480 Cells Growth by Apoptosis Induction

Purpose: Streptomyces sp. , a dominant genus in Actinomycetes, is the source of a wide variety of secondary metabolites. Microbial metabolites can be utilized as novel anticancer agents; with fewer side effects. The present article illustrated the anti-carcinogenic effect of the ether extracted organic metabolites derived from Streptomyces bacteria on SW480 colon cancer cell line. Methods: MTT assay was performed in order to investigate the cytotoxicity effect of metabolites on SW480 cells. Apoptosis and cell cycle arrests were measured by flowcytometry. Morphological changes were indicated by Propidium iodide staining andP53 gene expression was evaluated by real-time PCR. Results: Streptomyces Levis ABRIINW111 inhibited cell growth, increased Caspases 3 and reduced Ki67 expression in a concentration/time-dependent manner in SW40 cells. Metabolites increased subG1 phase (apoptosis) and also cell cycle arrest in G1, G2/M and S phase. P53 gene expression followed Sw480 cells treatment significantly. Conclusion: Streptomyces sp. metabolites have anti-carcinogenic effect on colon cancer cells. Streptomyces Levis ABRIINW111 metabolites are a candidate for Colon cancer treatment.
Behavioral Pain Indicators in Patients with Traumatic Brain Injury Admitted to an Intensive Care Unit

Introduction: A consistent approach to pain assessment for patients admitted to intensive care unit (ICU) is a major difficulty for health practitioners due to some patients’ inability, to express their pain verbally. This study aimed to assess pain behaviors (PBs) in traumatic brain injury (TBI) patients at different levels of consciousness. Methods: This study used a repeated-measure, within-subject design with 35 patients admitted to an ICU. The data were collected through observations of nociceptive and non-nociceptive procedures, which were recorded through a 47-item behavior-rating checklist. The analyses were performed by SPSS ver.13 software. Results: The most frequently observed PBs during nociceptive procedures were facial expression levator contractions (65.7%), sudden eye openings (34.3%), frowning (31.4%), lip changes (31.4%), clear movement of extremities (57.1%), neck stiffness (42.9%), sighing (31.4%), and moaning (31.4%). The number of PBs exhibited by participants during nociceptive procedures was significantly higher than those observed before and 15 minutes after the procedures. Also, the number of exhibited PBs in patients during nociceptive procedures was significantly greater than that of exhibited PBs during the non-nociceptive procedure. The results showed a significant difference between different levels of consciousness and also between the numbers of exhibited PBs in participants with different levels of traumatic brain injury severity. Conclusion: The present study showed that most of the behaviors that have been observed during painful stimulation in patients with traumatic brain injury included facial expressions, sudden eye opening, frowning, lip changes, clear movements of extremities, neck stiffness, and sighing or moaning.