Miracle-dz/UniFAR-FTUs huggingface dataset:
Res 2 Vec : Amino acid vector embeddings from 3 d-protein structure

The 20 naturally-occurring amino acids are the building blocks of all proteins. These residues confer distinct physicochemical properties to proteins based on features like atomic composition, size, and charge. Here, inspired by recent work in NLP, we create vector embeddings of each amino acid based on their contexts of neighboring residues within folded proteins. We then test the utility of these embeddings in a data-scarce supervised task, classifying amino acid mutations as “neutral” or “destabilizing” to T4 lysozyme.
Mutations in the GW-repeat protein SUO reveal a developmental function for microRNA-mediated translational repression in Arabidopsis

Plant microRNAs (miRNAs) typically mediate RNA cleavage, but examples of miRNA-mediated translational repression have also been reported. However, the functional significance of this latter process is unknown. We identified SUO in a screen for Arabidopsis mutations that increase the accumulation of the miR156-regulated gene SPL3. suo has a loss-of-function phenotype characteristic of plants with reduced Argonaute (AGO)1 activity. An analysis of RNA and protein levels in suo mutants demonstrated that this phenotype is a consequence of a defect in miRNA-mediated translational repression; the effect of suo on vegetative phase change is attributable to a reduction in miR156/miR157 activity. SUO encodes a large protein with N-terminal bromo-adjacent homology (BAH) and transcription elongation factor S-II (TFS2N) domains and two C-terminal GW (glycine and tryptophan) repeats. SUO is present in the nucleus, and colocalizes with the processing-body component DCP1 in the cytoplasm. Our results reveal that SOU is a component of the miRNA pathway in Arabidopsis and demonstrate that translational repression is a functionally important aspect of miRNA activity in plants.
Minimum clinically important difference in the Positive and Negative Syndrome Scale with data from the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE).

CONTEXT Establishing the minimum clinically important difference in the Positive and Negative Syndrome Scale (PANSS) is important to the interpretation of the research and clinical work conducted with this scale. METHOD This study employed both anchor-based and distributive methods to estimate the minimum clinically important difference for the PANSS by using data from the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) schizophrenia trial, a large, multicenter trial for patients with schizophrenia. By using an equipercentile method, data from 1,442 individuals linked PANSS scores with both clinician and patient ratings on the Clinical Global Impressions scale (CGI). Data were also used to investigate the magnitude of the standard error of measurement (SEM), offering another estimate of the minimum clinically important difference. RESULTS Cross-sectional, clinician-rated CGI-Severity of illness scores of 1 through 7 linked to PANSS scores of 32.4, 42.2, 57.5, 74.5, 93.0, 110.9, and 131.0, respectively. The minimum clinically important difference for PANSS scores using this scale equaled a 15.3-point (34.0%) change from baseline. A 1.96 SEM on the PANSS corresponded to a 16.5-point (36.2%) change from baseline. The minimum clinically important difference for a subsample with above-median baseline PANSS scores was 38% higher than a sample with lower baseline scores. With the patient-rated CGI as the anchor, PANSS scores were higher for CGI scores of 1 through 4, and the minimum clinically important difference was lower, 11.2 points (24.6%). CONCLUSION Minimum clinically important difference estimates from a longer-term effectiveness trial were consistent with previous efforts from shorter-term efficacy trials. Minimum clinically important difference estimates can help clinicians and researchers design future studies and interpret treatment change in future research and clinical work.
EFFICIENTLY GENERATING THOUSANDS OF TIME-SERIES PRODUCT DEMAND FORECASTS USING R

This study identifies and tests a promising open-source framework for efficiently creating thousands of univariate time-series demand forecasts and reports interesting insights that could help improve other product demand forecasting initiatives. The investigation is motivated by the fact that retailers routinely require forecasts to be generated for planning purposes. Moreover, most retailers have expensive commercial inventory planning systems that automatically generate forecasts that a practitioner may use. While such systems exist, practitioners will often create their own forecasts, as well as, try and gain better insight about their products which can be a daunting task. Using a national retailer’s data we implement this forecasting solution in R. We show that many of the forecasts are reliable, but also discuss issues we have found generating forecasts. We discuss our current efforts to identify and account for these issues and to improve the predictive performance of our models.
Performance evaluation of multipoint routing algorithms

The problem of developing efficient multipoint routing algorithms for asynchronous transfer mode (ATM) networks is considered. Emphasis is placed on practical algorithms that have efficient distributed implementation. In particular, the weighted greedy algorithm (WGA) is investigated. This algorithm is of particular interest since one version can be implemented as a simple extension of point-to-point routing and since a straightforward distributed implementation is possible. The performance of the WGA is studied by means of computer simulations and compared to that of a theoretically good algorithm. Experiments are conducted under realistic conditions involving different connection types, including point-to-point and dynamic multipoint connections. Performance is evaluated in terms of an algorithm's load carrying potential. The goal is to find algorithms that maximize the load carrying ability of a network. <<ETX>>
Increased concentrations of human β-defensins in plasma and bronchoalveolar lavage fluid of patients with diffuse panbronchiolitis

Background: Human β-defensin (HBD)-1 and -2 are antimicrobial peptides present in the respiratory tract. Recent reports have indicated reduced activity of β-defensins in cystic fibrosis, suggesting that β-defensins may play an important role in the pathological process of chronic respiratory tract infection. Diffuse panbronchiolitis (DPB) is a progressive disease characterised by frequent episodes of superimposed infection, typically caused by Pseudomonas aeruginosa. The aim of this study was to elucidate the role of these antimicrobial peptides in this disease. Methods: The concentrations of HBD-1 and HBD-2 in plasma and bronchoalveolar lavage (BAL) fluid from 33 patients with DPB and 30 normal adults were measured by radioimmunoassay. Localisation of HBD-2 was investigated immunohistochemically in an open lung biopsy specimen obtained from a patient with DPB. Results: High concentrations of HBD-1 and HBD-2 were noted in BAL fluid from DPB patients. Increased plasma concentrations of HBD-2, but not HBD-1, were found in patients with DPB compared with control subjects. In patients with DPB the HBD-2 concentration in BAL fluid correlated significantly with the numbers of cells recovered from the BAL fluid (total cells, neutrophils, and lymphocytes) and with the BAL fluid concentration of IL-1β. Synthetic HBD-2, but not HBD-1, had dose dependent bactericidal activity against P aeruginosa. Treatment of 14 patients with macrolides significantly reduced BAL fluid concentrations of HBD-2 but not HBD-1 or plasma concentrations of HBD-1 and HBD-2. Immunohistochemistry of lung tissue showed localisation of HBD-2 in the epithelia of the distal bronchioles. Conclusions: These results indicate that β-defensins, particularly HBD-2, participate in antimicrobial defence in the respiratory tract in DPB, and that the BAL fluid concentration of HBD-2 may be a useful marker of airway inflammation in patients with DPB.
Cocaine delivery via driverless vehicles OR Scaling physical-proximity attacks on driverless vehicles using structured graph analysis

Driverless vehicles are expected to form the foundation of future connected transport infrastructure. A key weakness of connected vehicles is their vulnerability to physical-proximity attacks such as sensor saturation attacks. It is natural to study whether such attacks can be used to disrupt swarms of autonomous vehicles used as part of a large fleet providing taxi and courier delivery services. In this paper, we start to examine the strategic options available to attackers and defenders (autonomous-fleet operators) in such conflicts. We propose the adversarial Traveling Salesperson Problem, and analyse the salesperson’s efficiency in the face of attackers launching coordinated physicalproximity attacks on the courier’s vehicle. We find that currently attackers have the upper hand in most cases and are able to carry out crippling denial-of-service attacks on fleets, by leveraging the inherent deficiencies of road networks identified by techniques from graph analysis. Experimental results on ten cities using real-world courier traces shows that most cities will require upgraded infrastructure to defend driverless vehicles against denial-of-service attacks. We found several hidden costs that impact equipment designers and operators of driverless vehicles — not least, that entire sections of roadways may need to be redesigned for robustness against attacks.
Construction of a Multidimensional Scale of Job Satisfaction

A comprehensive, multidimensional scale measuring job satisfaction was constructed for use in a major project concerned with personnel recruitment and retention of health professionals. 11 dimensions relating to opinions of immediate supervisors, physical working conditions, satisfaction with coworkers and with pay, aspects related to promotion and work motivation, are identified. These dimensions are shown to distinguish among health professionals on sex and between locations and different occupations. The scale also has high internal validity, producing a multiple R of . 78 with over-all job satisfaction.
Support Vector Machines for Syndromic Surveillance

OBJECTIVE This paper depicts a novel method for reliable detection of disease outbreaks. The methodology and initial results obtained on ESSENCE data are presented. BACKGROUND Early and reliable detection of anomalies is a critical challenge in disease surveillance. Most surveillance systems collect data from multiple data streams but the majority of monitoring is performed at univariate time series level. Purely statistical methods used in disease surveillance look at each time series separately and tend to generate a large number of false alarms. Support Vector Machines (SVM) can be used to develop rich multivariate models that allow detecting abnormal relationships between different time series leading to greatly reduced number of false alarms. METHOD At a high level our anomaly detection approach consists of: 1) Learning the model of normalcy; 2) Detecting anomalies based on their dissimilarity from regular behavior. For learning the normal behavior we use the SVM algorithm based on statistical learning theory [1]. We use the one-class SVM extension to the algorithm [2] that requires only positive training examples, in our case the normal (no outbreak) data. The method (Figure 1) has the following steps: o Exponential Weighted Moving Average (EWMA) smoothing of each of the syndrome/ subsyndrome/ gender/ age time series with counts. o Computing the descriptor: each of 3021 numbers is a value of test statistic [3] regularly used in biosurveillance for time series of counts. Value of 3 or more signifies an alert in statistical approaches. o The descriptor constitutes an input to several SVMs that classify it as normal or anomalous. Each SVM puts a different emphasis on different parts of the descriptor, e.g. GI SVM puts a high emphasis on about 250 numbers in the descriptor related to GI subsyndromes. o Each of SVM produces a decision whether the data presented to it is normal or anomalous. The Decision Fusion Center combines decisions from the individual classifiers and produces the final decision (alert/ no alert) presented to the epidemiologist. INITIAL RESULTS The training was performed on ESSENCE data with disease outbreaks removed. Testing was performed on both normal ESSENCE data and ESSENCE data with superimposed simulated outbreaks (3-7 day long). Initial results show 94.7% specificity and 54.8% sensitivity of the SVM method. This compares very favorably with pulling univariate EWMA results (94% specificity for 29% sensitivity, and 68.9% specificity for 54.8% sensitivity). CONCLUSIONS A multivariate SVM-based approach for disease outbreak detection shows promising initial results for reducing false alarms abundant in purely statistical methods. REFERENCES
Searching for the Perfect Fit between Organizational Structure, Problem types and Group Decision Support Systems Usage

there is a high adoption of information technology in organizations. However the adoption of Group Decision Support Systems (GDSS) does not follow this trend. This lack of GDSS usage is surprising since organizations face increasingly complex problems in present day's globalized economy. This study aims to improve GDSS adoption by creating a theoretical model and testing this with current practices, to find out if mismatches occur between organizational structure, problem type and use of GDSS problem solving methods. The model is developed based on a literature review, after which it is tested by conducting a questionnaire and analyzing usage data from the customers of Spilter, a GDSS vendor willing to participate in this study. The study results show that practices suggested by the theoretical model are currently not always followed. This means that GDSS facilitators can potentially improve GDSS sessions, by stimulating usage that corresponds to practices suggested by the theoretical model. KeywordsDecision Support System, GDSS, Organizational structure, Problem types, GDSS methods, Perfect fit, Theoretical model.
White matter injury induced by diabetes in acute stroke is clinically relevant: A preliminary study

The importance of white matter injury induced by diabetes in stroke severity and prognosis is largely unknown. We aimed to investigate the relationship between diabetes-related white matter injury beyond stroke lesions with acute neurological deficits and clinical outcome after stroke. In total, 36 stroke patients within 3–7 days after onset were enrolled. Neurological deficits on admission were assessed by National Institute of Health Stroke Score, and poor outcome at 3 months was defined as modified Rankin score >2. White matter tracts were compared between patients with diabetic and non-diabetic stroke using fractional anisotropy from diffusion tensor imaging. Regional white matter abnormality with decreased fractional anisotropy was observed in diabetic patients (n = 18) when compared to non-diabetic patients (n = 18). Decreased fractional anisotropy in ipsilesional distal corticospinal tract was independently associated with higher National Institute of Health Stroke Score motor component score (β = −0.444, p = 0.005), and decreased fractional anisotropy in contralesional superior longitudinal fasciculus I was independently related to poor outcome (odds ratio, 0.900; p = 0.033). Our findings suggested that only white matter injury induced by diabetes in specific tracts like corticospinal tract and superior longitudinal fasciculus beyond stroke lesions has clinically relevant, providing insight into the mechanism of stroke recovery under the diabetic condition.
Sub-100 nm2 Cobalt Interconnects

Co has elicited a strong interest to replace Cu for future interconnect applications in microelectronic circuits due to its potentially lower resistivity and better reliability at scaled dimensions. Here, we demonstrate Co wires with electrical cross-sectional areas as small as 34 nm2 using a simple subtractive patterning technique. Semiclassical resistivity modeling of the wire resistivity indicates that grain boundary scattering is the dominant contribution for cross-sectional areas of the order of 100 nm2, while the contribution of surface scattering increases drastically below 50 nm2. Furthermore, wafer-level reliability tests of the Co wires show the high fusing current densities and a strong resistance to thermoelectric stress demonstrating the potential for robust reliability. The resistivity and the reliability of the Co wires are comparable with those of Ru wires.
Inhibition of TNF-α-Induced Neutrophil Apoptosis by Crystals of Calcium Pyrophosphate Dihydrate Is Mediated by the Extracellular Signal-Regulated Kinase and Phosphatidylinositol 3-Kinase/Akt Pathways Up-Stream of Caspase 31

The role of protein kinases in the inhibition of TNF-α associated apoptosis of human neutrophils by crystals of calcium pyrophosphate dihydrate (CPPD) (25 mg/ml) was investigated. We monitored the activities of the p44 extracellular signal-regulated kinase 1 (ERK1) and p42 ERK2 mitogen-activated protein (MAP) kinases and phosphatidylinositol 3-kinase (PI3-K)-regulated protein kinase B (Akt) in neutrophils incubated with TNF-α and CPPD crystals, separately and in combination, in parallel with the endogenous caspase 3 activity and DNA fragmentation. CPPD crystals were observed to induce a robust and transient activation of ERK1, ERK2, and Akt, whereas TNF-α produced only a modest and delayed activation of Akt. In the presence of TNF-α, Akt activity was enhanced, and CPPD crystal-induced activation of ERK1 and ERK2 was more sustained than with CPPD crystals alone, but TNF-α itself reduced the basal phosphotransferase activities of these MAP kinases. Preincubation with the MAP kinase kinase (MEK1) inhibitors PD98059 (20 ng/ml) and U0126 (250 nM), or the PI3-K inhibitors wortmannin (100 nM) and LY294002 (50 μM) repressed the activation of ERK1, ERK2, and Akt in association with CPPD crystal incubation, in the absence or presence of TNF-α. Furthermore, the inhibition of the Mek1/Mek2→ERK1/ERK2 or PI3-K/Akt pathways reversed CPPD crystal-associated suppression of TNF-α-induced caspase 3 activation and neutrophil apoptosis. Together, these results indicate that CPPD crystals function to induce acute inflammatory responses through ERK1/ERK2 and PI3-K/Akt-mediated stimulation of neutrophil activation and repression of apoptosis.
Molecular dynamics and free energy analyses of cathepsin D-inhibitor interactions: insight into structure-based ligand design.

In this study, we compare the calculated and experimental binding free energies for a combinatorial library of inhibitors of cathepsin D (CatD), an aspartyl protease. Using a molecular dynamics (MD)-based, continuum solvent method (MM-PBSA), we are able to reproduce the experimental binding affinity for a set of seven inhibitors with an average error of ca. 1 kcal/mol and a correlation coefficient of 0.98. By comparing the dynamical conformations of the inhibitors complexed with CatD with the initial conformations generated by CombiBuild (University of California, San Francisco, CA, 1995), we have found that the docking conformation observed in an X-ray structure of one peptide inhibitor bound to CatD (Proc. Natl. Acad. Sci. U.S.A. 1993, 90, 6796-6800) is in good agreement with our MD simulation. However, the DOCK scoring function, based on intermolecular van der Waals and electrostatics, using a distance-dependent dielectric constant (J. Comput. Chem. 1992, 13, 505-524), poorly reproduces the trend of experimental binding affinity for these inhibitors. Finally, the use of PROFEC (J. Comput.-Aided Mol. Des. 1998, 12, 215-227) analysis allowed us to identify two possible substitutions to improve the binding of one of the better inhibitors to CatD. This study offers hope that current methods of estimating the free energy of binding are accurate enough to be used in a multistep virtual screening protocol.
Scrub Typhus in Uttar Pradesh, India-A Prospective Study

Scrub typhus is an acute infectious disease caused by Orientia tsutsugamushi, a Gramnegative intracellular coccobacillus. The larvae of trombiculid mites are the implicated vector and reservoir of the bacteria and can efficiently transmit it to their offspring transovarially (Mahajan, 2005; Nakayama et al., 2010). It presents as either as nonspecific febrile illness with legitimate symptoms such as fever, rash, myalgias, headache, lymphadenopathy, hepatospleno-megaly, rash and an eschar or with organ dysfunctions involving organs such as kidney (acute renal failure; ARF), liver (hepatitis), lungs (acute respiratory distress syndrome, ARDS), central nervous system (meningitis), or with International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 6 Number 4 (2017) pp. 977-986 Journal homepage: http://www.ijcmas. com
THE IMPACT AND DETECTION OF NON-MOTOR SYMPTOMS IN PARKINSON’S DISEASE

In the end of the twentieth century, neurology focused on motor symptoms as the primary source of disability in Parkinson’s disease (PD). Studies were designed to reduce the frequency and severity of motor complications such as motor fluctuations and dyskinesias. Physicians became accustomed to strategies to delay the initiation of levodopa to this end. The twenty-first century may be thought of as a revolution in the philosophy of PD care. We acknowledge that PD is not just an illness of dopamine depletion, but a complex illness with impacts throughout and beyond the central nervous system. This dawn of non-motor discovery only reaffirms the first description by James Parkinson that did include the non-motor features that were discounted for their impact and significance to our patients’ lives. Despite this, let me first emphasize that no study has asked patients about values for eliminating disability from motor or non-motor symptoms. Would a patient tolerate all the non-motor symptoms in order to retain mobility? Or would they choose a wheelchair bound state to be rid of the non-motor complications that plague them? Therefore, caring for people with PD requires attention to motor symptoms, non-motor features and vigilance for the complications that our treatments may cause.
Array-based analysis of the effects of trichostatin A and CG-1521 on cell cycle and cell death in LNCaP prostate cancer cells

Previous studies comparing the effects of two histone deacetylase (HDAC) inhibitors, trichostatin A (TSA) and CG-1521, have shown that these compounds selectively inhibit HDAC and induce differentially acetylated p53 isoforms and assembly of mutually exclusive transcriptional complexes on the p21 promoter. To determine whether the differential transcriptional regulation seen in p21 gene is unique or whether it is representative of the genome-wide effects of these two HDAC inhibitors, we have used microarray and Ingenuity pathway analysis to compare the effects of TSA and CG-1521 on gene expression on LNCaP cells. Gene array analysis confirmed by quantitative real-time PCR shows that CG-1521 modulates the expression of a highly circumscribed group of genes involved in cell cycle progression and cell death. In contrast, TSA appears to induce widespread transrepression of many genes and does not modulate the expression of the same cohort as CG-1521. These data show that the selective effects of CG-1521 and TSA on the assembly of transcription complexes are not unique to the p21 gene and suggest that selective inhibition of HDAC can lead to significant changes in gene expression through the acetylation of transcription factors including but not limited to p53. [Mol Cancer Ther 2008;7(7):1931–9]