Miracle-dz/UniFAR-FTUs huggingface dataset:
Sickle Cell Anemia Patients in Use of Hydroxyurea: Association between Polymorphisms in Genes Encoding Metabolizing Drug Enzymes and Laboratory Parameters

This study investigated associations between SNPs in genes encoding metabolizing drug enzymes and laboratory parameters in sickle cell anemia patients under hydroxyurea (SCA-HU+). We evaluated hematologic and biochemical parameters by electronic methods and SNPs by PCR-RFLP and multiplex PCR in 35 SCA-HU+ patients and 67 SCA-HU− patients. The HbS, total cholesterol, lactate dehydrogenase, aspartate aminotransferase, total bilirubin and fractions levels, and leukocyte, eosinophil, monocyte, and erythroblast counts were reduced in SCA-HU+ patients (p < 0.05). Moreover, they presented higher HbF, C-reactive protein, and ferritin levels and elevated MCH and MCV values (p < 0.05). Genotype frequencies of variants GA + AA of MPO −463G>A and c1c2 + c2c2 of CYP2E1 −1293G>C/−1053C>T were higher in SCA-HU+ patients (p < 0.05). Independent associations were found between the variant A allele and lower total cholesterol, between c2 allele and low alpha-1 antitrypsin and between the null GSTT1 variant and high indirect and total bilirubin in SCA-HU+ patients. In SCA-HU− patients, independent associations were found between the variant A allele and high uric acid and between c2 allele and high urea. Our results suggest that SNPs MPO −463G>A, CYP2E1 −1293G>C/−1053C>T, and GSTT1 can be associated with alterations in lipid, inflammatory, renal, hemolytic, and hepatic profiles. However, further studies are needed to elucidate these associations.
Experimental-Numerical Study of Manufacture Induced 3D Rail Residual Stress

The purpose of this research was to investigate the changing patterns of the 3D rail residual stress as it accumulates on different portions of the rail manufacturing process. These patterns are of interest for manufacturers and railroad companies but also could serve as initial fields for various further numerical analyses of actual residual stress states in rails, wear and crack formation/development. Examined were four rail samples taken directly from manufacturing: 1. an air cooled rail; 2. an air cooled and roller straightened rail; 3. a head hardened rail; 4. a head hardened and roller straightened rail. An advanced experimental-numerical hybrid technique was developed and applied to perform all the required data reduction tasks. It comprises of an sectioning scheme called as the transverse/oblique slicing (T/O-S) technique and of a physically reasonable data reduction/smoothing procedure called as the global method (GM). Destructive experimental examinations were performed with the neutron diffraction method on thin rail slices at atomic reactor facility of US DOC, NIST Center for Neutron Research in Gaithersburg, MD. In the paper presented and discussed are results of the performed analyses.
Relay selection and link scheduling in cooperative free-space optical backhauling of 5G small cells

With the explosive growth in the number of various small cells in the forthcoming fifth-generation (5G) wireless networks, it is a great challenge to schedule the 5G backhaul traffic in an effective way. In this paper, we investigate the feasibility of a 5G backhaul framework based on Free-Space Optical (FSO) communication system to design a high-rate, but also reliable and resource-efficient backhaul solution. We focus on the problem of throughput maximization in the cooperative FSO relay channel and propose a relay selection algorithm using back-pressure theory to boost transmission quality. Then, a link scheduling algorithm is further put forward to improve the resource utilization by making full use of the idle FSO links. Simulation results demonstrate that the proposed algorithms can significantly enhance the performance of cooperative FSO-backhaul system in reliability and resource utilization, especially for data-intensive transmission scenarios.
CONCURRENT DETECTION AND TRACKING FOR GMTI

We develop a technique for performing multitarget tracking from GMTI radar data using dynamic logic (DL). The approach is specifically designed for target-rich, high-clutter, scenarios in which state-of-the-art trackers will have impractically high computational complexity during data association. DL provides a way to perform data association without combinatorial explosion, so that the complexity scales only linearly with additional data and/or targets. Thus, since we can operate with large amounts of clutter, we can push down the pre-detect thresholds and track in very low signal to clutter ratio environments. We begin by introducing parameter estimation for generic Gaussian mixtures. We then proceed to show that multi-target tracking using DL is a straightforward variation of this generic case. We present tracking results based upon realistic synthetic data at S/C as low as -6dB in both Doppler and RCS. This represents several orders of magnitude improvement over the rule-of-thumb required S/C for existing trackers.
Magnetothermal genetic deep brain stimulation of motor behaviors in awake, freely moving mice

Establishing how neurocircuit activation causes particular behaviors requires modulating the activity of specific neurons. Here, we demonstrate that magnetothermal genetic stimulation provides tetherless deep brain activation sufficient to evoke motor behavior in awake mice. The approach uses alternating magnetic fields to heat superparamagnetic nanoparticles on the neuronal membrane. Neurons, heat-sensitized by expressing TRPV1 are activated with magnetic field application. Magnetothermal genetic stimulation in the motor cortex evoked ambulation, deep brain stimulation in the striatum caused rotation around the body-axis, and stimulation near the ridge between ventral and dorsal striatum caused freezing-of-gait. The duration of the behavior correlated tightly with field application. This approach provides genetically and spatially targetable, repeatable and temporarily precise activation of deep-brain circuits without the need for surgical implantation of any device.
Radiation-Induced Gene Expression Changes in High and Low Grade Breast Cancer Cell Types

Background: There is extensive scientific evidence that radiation therapy (RT) is a crucial treatment, either alone or in combination with other treatment modalities, for many types of cancer, including breast cancer (BC). BC is a heterogeneous disease at both clinical and molecular levels, presenting distinct subtypes linked to the hormone receptor (HR) status and associated with different clinical outcomes. The aim of this study was to assess the molecular changes induced by high doses of ionizing radiation (IR) on immortalized and primary BC cell lines grouped according to Human epidermal growth factor receptor (HER2), estrogen, and progesterone receptors, to study how HR status influences the radiation response. Our genomic approach using in vitro and ex-vivo models (e.g., primary cells) is a necessary first step for a translational study to describe the common driven radio-resistance features associated with HR status. This information will eventually allow clinicians to prescribe more personalized total doses or associated targeted therapies for specific tumor subtypes, thus enhancing cancer radio-sensitivity. Methods: Nontumorigenic (MCF10A) and BC (MCF7 and MDA-MB-231) immortalized cell lines, as well as healthy (HMEC) and BC (BCpc7 and BCpcEMT) primary cultures, were divided into low grade, high grade, and healthy groups according to their HR status. At 24 h post-treatment, the gene expression profiles induced by two doses of IR treatment with 9 and 23 Gy were analyzed by cDNA microarray technology to select and compare the differential gene and pathway expressions among the experimental groups. Results: We present a descriptive report of the substantial alterations in gene expression levels and pathways after IR treatment in both immortalized and primary cell cultures. Overall, the IR-induced gene expression profiles and pathways appear to be cell-line dependent. The data suggest that some specific gene and pathway signatures seem to be linked to HR status. Conclusions: Genomic biomarkers and gene-signatures of specific tumor subtypes, selected according to their HR status and molecular features, could facilitate personalized biological-driven RT treatment planning alone and in combination with targeted therapies.
VARIABILITY TO ASSESS POTENTIAL FOR CARBON SEQUESTRATION

Accurate measurements of soil organic carbon (SOC) levels are essential to assess changes in C sequestration rates. To this end we conducted studies to evaluate laboratory variability in SOC concentration measured at USDA-ARS laboratories in Akron, CO, Cheyenne, WY, and Lincoln, NE. At the Akron laboratory we also evaluated field spatial variability within common cropping treatments in order to assess the potential to quantify significant changes in SOC content associated with rotations of varying cropping intensities. Our data showed very low coefficients of variation for SOC values from each of the three laboratories, and the same average SOC values for soils from each treatment. For mitigating spatial variability, the data showed that a 10-ha field required 10 cores, the 0.2-ha field, 2 cores, and the 0.02-ha field, one core, in order to achieve a difference of #10% from the mean
Phase analysis of endoatrial electrograms for 3D rotor detection in atrial fibrillation

Atrial fibrillation (AF) is the most common type of arrhythmia encountered in clinical practice but its maintaining mechanisms remain elusive. Over the last years, various theories have been proposed to target AF mechanisms. Recently, there has been an increasing interest in understanding how spiral waves and rotors sustain AF and how they might be therapeutic targets for catheter-based ablation. Phase mapping has recently been used as a robust method to characterize the spatiotemporal variability of electrical activities. In this study, we propose an independent approach for basket catheter electrogram (EGM) processing to detect rotors in AF. An improved version of the sinusoidal recomposition method for the local activation timings (LATs) has been developed and 3D phase maps have been reconstructed. An algorithm able to detect stable and meandering rotors on the left atrium (LA) surface was then developed. This workflow has been validated on synthetic EGMs and in silico showing excellent results. On in vivo data, we found 4.0±3.4 and 4.6±5.0 localized and meandering rotors with a persistence in time: 303.2 ±58.2ms and 302.3±52.0ms respectively.
Role of COL6A3 in colorectal cancer

Public transcriptome databases provide a valuable resource for genome-wide co-expression network analysis and investigation of the molecular mechanisms that underlie pathogenesis. To discover genes that may affect patient survival, a large-scale analysis of human colorectal cancer (CRC) datasets that were retrieved from the NCBI Gene Expression Omnibus was performed. A gene co-expression network was constructed using weighted gene co-expression network analysis (WGCNA). A total of 18 co-expressed gene modules were identified, of which two genes corresponded to cell migration and the cell cycle, two genes were involved in immune responses, two genes corresponded to mitochondrial function, and one gene corresponded to RNA splicing. A total of eight hub genes in the cell migration/extracellular matrix module were associated with poor prognosis in CRC, and the P-value for collagen type VI α3 chain (COL6A3) was the lowest. In silico analysis of cell type-specific gene expression and COL6A3 knockout experiments indicated the clinical relevance of COL6A3 in the development of CRC. In summary, the present analysis provides a basis for understanding the molecular characterization of CRC at the transcription level. COL6A3 may be a promising biomarker or target for the prognosis and treatment of CRC.
Behaviour of geocell reinforced soft clay bed subjected to incremental cyclic loading

The paper deals with the results of the laboratory cyclic plate load tests performed on the reinforced soft clay beds. The performances of the clay bed reinforced with geocells and geocells with additional basal geogrid cases are compared with the performance of the unreinforced clay beds. From the cyclic plate load test results, the coefficient of elastic uniform compression (C-u) was calculated for the different cases. The Cu value was found to increase in the presence of geocell reinforcement. The maximum increase in the Cu value was observed in the case of the clay bed reinforced with the combination of geocell and geogrid. In addition, 3 times increase in the strain modulus, 10 times increase in the bearing capacity, 8 times increase in the stiffness and 90% reduction in the settlement was observed in the presence of the geocell and geogrid. Based on the laboratory test results, a hypothetical case of a prototype foundation subjected to cyclic load was analyzed. The results revealed that the natural frequency of the foundation-soil system increases by 4 times and the amplitude of the vibration reduces by 92% in the presence of the geocells and the geogrids.
Retroperitoneal laparoscopic nephroureterectomy with distal and intramural ureter resection for a tuberculous non - functional kidney

ABSTRACT Objective: To evaluate the safety and feasibility of total retroperitoneal laparoscopic nephroureterectomy with urinary-bladder junction resection for a tuberculous nonfunctional kidney. Materials and Methods: A total of 27 individuals diagnosed with unilateral nonfunctional kidney secondary to tuberculosis were treated between June 2011 and June 2015. All patients had normal renal function on the contralateral side and underwent the standard four-drug anti-tuberculosis treatment for at least four weeks before surgery. Total retroperitoneal laparoscopic nephroureterectomy was performed in all patients, and the urinary-bladder junction of distal ureter was managed using different auto-suture techniques. Results: Nineteen male and 8 female patients with an average age of 47.3 years (range, 36-64 years) underwent surgery. All the operations were successfully performed without conversion. The median operative time was 109.3 min (range, 75-138 min), the median blood loss was 157.5 mL (range, 70-250 mL), and the median hospitalization time was 3.7 days (range, 3-6 days). No serious perioperative complications occurred. Anti-tuberculosis chemotherapy was prescribed to all patients, with the entire course of treatment lasting six months. No recurrence of tuberculosis of the bladder or the contralateral kidney was observed during the median follow-up period of 26.7 months (range, 6-54 months). Conclusion: Retroperitoneal laparoscopic nephroureterectomy with urinary-bladder junction resection is a safe and feasible approach for the treatment of tuberculous non-functional kidneys.
The Strategic Role of Private Labels on Retail Competition

We investigate the strategic role of private labels in limiting retail competition. Private labels are unique differentiators for retailers. By launching and credibly committing to a strong private label program, a strong retailer can limit the market potential for competing retailers. Consequently, weaker retailers may not be able to meet threshold profits and exit the market. We derive the private label shares needed to induce exit. A model implication is that the private label share required to induce exit increases with increasing national brand margins. We also conduct an empirical analysis and find evidence supporting the propositions. Combining Dominick’s store level data with Zip Code Business Patterns data, we find that at the zip code level, the private label share affects the number of stores competing in the market.
Integrative deep models for alternative splicing

Advancements in sequencing technologies have highlighted the role of alternative splicing (AS) in increasing transcriptome complexity. This role of AS, combined with the relation of aberrant splicing to malignant states, motivated two streams of research, experimental and computational. The First involves a myriad of techniques such as RNA-Seq and CLIP-Seq to identify splicing regulators and their putative targets. The second involves probabilistic models, also known as splicing codes, which infer regulatory mechanisms and predict splicing outcome directly from genomic sequence. To date, these models have utilized only expression data. In this work we address two related challenges: Can we improve on previous models for AS outcome prediction and can we integrate additional sources of data to improve predictions for AS regulatory factors. We perform a detailed comparison of two previous modeling approaches, Bayesian and Deep Neural networks, dissecting the confounding effects of datasets and target functions. We then develop a new target function for AS prediction and show that it significantly improves model accuracy. Next, we develop a modeling framework to incorporate CLIP-Seq, knockdown and over-expression experiments, which are inherently noisy and suffer from missing values. Using several datasets involving key splice factors in mouse brain, muscle and heart we demonstrate both the prediction improvements and biological insights offered by our new models. Overall, the framework we propose offers a scalable integrative solution to improve splicing code modeling as vast amounts of relevant genomic data become available. Availability: code and data will be available on Github following publication.
Alcohol Brief Intervention in a university setting: A small-scale experimental study

Alcohol misuse among university students is commonplace. This study aimed to assess whether Alcohol Brief Intervention would be effective in reducing hazardous alcohol consumption in students compared to an alcohol information leaflet. Participants (n = 125) assessed as higher risk drinkers using the Alcohol Use Disorders Identification Test Consumption were randomly assigned to receive an Alcohol Brief Intervention (n = 67) or an information leaflet (n = 58), with 82 (66%) completing a follow-up assessment. Alcohol consumption (F(1, 80) = 14.52, p < 0.001) and the Alcohol Use Disorders Identification Test Consumption scores (F(1, 80) = 23.63, p < 0.001) significantly decreased in both groups post-intervention; however, the groups did not significantly differ. Further research is recommended.
Heart rate asymmetry in response to colored light

Heart rate asymmetry (HRA) quantifies imbalance of heart rate acceleration and deceleration. The impact of different colored lights on autonomic nervous system captured by HRA was studied in this paper. Using electrocardiogram (ECG) data for 16 female volunteers exposed to four different colored lights (red, green, blue, and yellow), three common HRA indices (Porta Index-PI, Guzik Index-GI, and Slope Index-SI) were calculated. Analysis of data revealed a statistically significant difference in PI (p<0.001), GI (p=0.006), and SI (p=0.001) depending on which colored light was used as visual stimuli. These results propose that HRA can be used as a complementary measure along with heart rate and heart rate variability to quantify heart response to colored light stimulation.
Distributed deep learning networks among institutions for medical imaging

Abstract Objective Deep learning has become a promising approach for automated support for clinical diagnosis. When medical data samples are limited, collaboration among multiple institutions is necessary to achieve high algorithm performance. However, sharing patient data often has limitations due to technical, legal, or ethical concerns. In this study, we propose methods of distributing deep learning models as an attractive alternative to sharing patient data. Methods We simulate the distribution of deep learning models across 4 institutions using various training heuristics and compare the results with a deep learning model trained on centrally hosted patient data. The training heuristics investigated include ensembling single institution models, single weight transfer, and cyclical weight transfer. We evaluated these approaches for image classification in 3 independent image collections (retinal fundus photos, mammography, and ImageNet). Results We find that cyclical weight transfer resulted in a performance that was comparable to that of centrally hosted patient data. We also found that there is an improvement in the performance of cyclical weight transfer heuristic with a high frequency of weight transfer. Conclusions We show that distributing deep learning models is an effective alternative to sharing patient data. This finding has implications for any collaborative deep learning study.
A Pharmacogenetic Approach to the Treatment of Patients With PPARG Mutations

Loss-of-function mutations in PPARG cause familial partial lipodystrophy type 3 (FPLD3) and severe metabolic disease in many patients. Missense mutations in PPARG are present in ∼1 in 500 people. Although mutations are often binarily classified as benign or deleterious, prospective functional classification of all missense PPARG variants suggests that their impact is graded. Furthermore, in testing novel mutations with both prototypic endogenous (e.g., prostaglandin J2 [PGJ2]) and synthetic ligands (thiazolidinediones, tyrosine agonists), we observed that synthetic agonists selectively rescue function of some peroxisome proliferator–activated receptor-γ (PPARγ) mutants. We report on patients with FPLD3 who harbor two such PPARγ mutations (R308P and A261E). Both PPARγ mutants exhibit negligible constitutive or PGJ2-induced transcriptional activity but respond readily to synthetic agonists in vitro, with structural modeling providing a basis for such differential ligand-dependent responsiveness. Concordant with this finding, dramatic clinical improvement was seen after pioglitazone treatment of a patient with R308P mutant PPARγ. A patient with A261E mutant PPARγ also responded beneficially to rosiglitazone, although cardiomyopathy precluded prolonged thiazolidinedione use. These observations indicate that detailed structural and functional classification can be used to inform therapeutic decisions in patients with PPARG mutations.
Airborne LIDAR borsight error calibration based on surface coincide

Light Detection and Ranging (LIDAR) is a system which can directly collect three-dimensional coordinate information of ground point and laser reflection strength information. With the wide application of LIDAR system, users hope to get more accurate results. Boresight error has an important effect on data accuracy and thus, it is thought that eliminating the error is very important. In recent years, many methods have been proposed to eliminate the error. Generally, they can be categorized into tie point method and surface matching method. In this paper, we propose another method called try value method based on surface coincide that is used in actual production by many companies. The method is simple and operable. Further, the efficacy of the method was demonstrated by analyzing the data from Zhangye city.
Draft Genome Sequence of the Basidiomycete White-Rot Fungus Phlebia centrifuga

ABSTRACT Here, we report the genome sequence of wood-decaying white-rot fungus Phlebia centrifuga strain FBCC195, isolated from Norway spruce (Picea abies) in Finnish Lapland. The 34.66-Mb genome containing 13,785 gene models is similar to the genome length reported for other saprobic white-rot species.