Miracle-dz/UniFAR-FTUs huggingface dataset:
Associations of obesity and circulating insulin and glucose with breast cancer risk: a Mendelian randomization analysis.

Background In addition to the established association between general obesity and breast cancer risk, central obesity and circulating fasting insulin and glucose have been linked to the development of this common malignancy. Findings from previous studies, however, have been inconsistent, and the nature of the associations is unclear. Methods We conducted Mendelian randomization analyses to evaluate the association of breast cancer risk, using genetic instruments, with fasting insulin, fasting glucose, 2-h glucose, body mass index (BMI) and BMI-adjusted waist-hip-ratio (WHRadj BMI). We first confirmed the association of these instruments with type 2 diabetes risk in a large diabetes genome-wide association study consortium. We then investigated their associations with breast cancer risk using individual-level data obtained from 98 842 cases and 83 464 controls of European descent in the Breast Cancer Association Consortium. Results All sets of instruments were associated with risk of type 2 diabetes. Associations with breast cancer risk were found for genetically predicted fasting insulin [odds ratio (OR) = 1.71 per standard deviation (SD) increase, 95% confidence interval (CI) = 1.26-2.31, p = 5.09 × 10-4], 2-h glucose (OR = 1.80 per SD increase, 95% CI = 1.3 0-2.49, p = 4.02 × 10-4), BMI (OR = 0.70 per 5-unit increase, 95% CI = 0.65-0.76, p = 5.05 × 10-19) and WHRadj BMI (OR = 0.85, 95% CI = 0.79-0.91, p = 9.22 × 10-6). Stratified analyses showed that genetically predicted fasting insulin was more closely related to risk of estrogen-receptor [ER]-positive cancer, whereas the associations with instruments of 2-h glucose, BMI and WHRadj BMI were consistent regardless of age, menopausal status, estrogen receptor status and family history of breast cancer. Conclusions We confirmed the previously reported inverse association of genetically predicted BMI with breast cancer risk, and showed a positive association of genetically predicted fasting insulin and 2-h glucose and an inverse association of WHRadj BMI with breast cancer risk. Our study suggests that genetically determined obesity and glucose/insulin-related traits have an important role in the aetiology of breast cancer.
Dyspnea and the Varying Pathophysiologic Manifestations of Chronic Obstructive Pulmonary Disease Evaluated by Cardiopulmonary Exercise Testing With Arterial Blood Analysis

Background: Patients with chronic obstructive pulmonary disease (COPD) show varying mechanisms of exertional dyspnea with different exercise capacities. Methods: To investigate the pathophysiologic conditions related to exertional dyspnea, 294 COPD patients were evaluated using cardiopulmonary exercise testing (CPET) with arterial blood analyses, with the patients classified into two groups according to their exercise limitation: the leg fatigue group (n = 58) and the dyspnea group (n = 215). The dyspnea group was further subdivided into four groups based on peak oxygen uptake (V°O2 in mL/min/kg): group A (< 11), group B (11 to < 15), group C (15 to < 21), and group D (≥21). Results: In the dyspnea group, group A (n = 28) showed the following findings: (i) the forced expiratory volume in 1 s was not correlated with the peak V°O2 (p = 0.288), (ii) the arterial oxygen tension (PaO2) slope (peak minus resting PaO2/ΔV°O2) was the steepest (p < 0.0001) among all subgroups, (iii) reduced tidal volume (VT) was negatively correlated with respiratory frequency at peak exercise (p < 0.0001), and (iv) a break point in exertional VT curve was determined in 17 (61%) patients in group A. In these patients, there was a significant negative correlation between bicarbonate ion (HCO3-) levels at peak exercise and VT level when the VT-break point occurred (p = 0.032). In group D (n = 46), HCO3- levels were negatively correlated with plasma lactate levels (p < 0.0001). In all subgroups, the HCO3- level was negatively correlated with minute ventilation. The dyspnea subgroups showed no significant differences in the overall mean pH [7.363 (SD 0.039)] and Borg scale scores [7.4 (SD, 2.3)] at peak exercise. Conclusions: During exercise, ventilation is stimulated to avoid arterial blood acidosis and hypoxemia, but ventilatory stimulation is restricted in the setting of reduced respiratory system ability. These conditions provoke the exertional dyspnea in COPD. Although symptom levels were similar, the exertional pathophysiologic conditions differed according to residual exercise performance; moreover, COPD patients showed great inter-individual variability. An adequate understanding of individual pathophysiologic conditions using CPET is essential for proper management of COPD patients.
Experimental Evaluation of Travoprost-Induced Changes in Biomechanical Behavior of Ex-Vivo Rabbit Corneas

ABSTRACT Purpose: To assess the effects of prostaglandin F2α analogues travoprost on the biomechanical behavior of ex-vivo rabbit cornea. Materials and Methods: 18 Japanese white rabbits were included in the study. The left eye (treated group, Tr) of each rabbit was preserved for 10 days in storage medium Eusol-C solution with 1:10 travoprost diluent, while the contralateral eye (control group, Co) was preserved in a similar but travoprost-free medium. Strips of corneal tissue were dissected and tested under cyclic load conditions with up to 0.1 N uniaxial tension force. The resulting load-elongation data were used to derive the stress–strain behavior and the tangent modulus (Et) of the tissue. Differences in Et between the treated (Et-Tr) and control group (Et-Co) were assessed statistically to determine the biomechanical effects of travoprost on the cornea. Results: Central corneal thickness (CCT) in the two groups was similar before (P = 0.073) and remained similar after storage (P = 0.303) although it became significantly thicker in both groups after preservation (P < 0.01). Compared with the control group, the travoprost treated corneas exhibited lower Et values but the differences reduced and became insignificant with rises in stress to which the tissue was subjected (1 - Et-Tr/Et-Co = −11.7 ± 41.8%, P < 0.05 at 10 kPa stress; −9.2 ± 36.1%, P > 0.05 at 20 kPa; −7.3 ± 35.4%, P > 0.05 at 30 kPa). Conclusions: Significant reductions in corneal stiffness, that are associated with the use of travoprost, were observed experimentally under low applied stresses. This stiffness-reduction effect should be considered in clinical management, especially in primary open angle glaucoma treatment.
Simultaneous zygotic inactivation of multiple genes in mouse through CRISPR/Cas9-mediated base editing

ABSTRACT In vivo genetic mutation has become a powerful tool for dissecting gene function; however, multi-gene interaction and the compensatory mechanisms involved can make findings from single mutations, at best difficult to interpret, and, at worst, misleading. Hence, it is necessary to establish an efficient way to disrupt multiple genes simultaneously. CRISPR/Cas9-mediated base editing disrupts gene function by converting a protein-coding sequence into a stop codon; this is referred to as CRISPR-stop. Its application in generating zygotic mutations has not been well explored yet. Here, we first performed a proof-of-principle test by disrupting Atoh1, a gene crucial for auditory hair cell generation. Next, we individually mutated vGlut3 (Slc17a8), otoferlin (Otof) and prestin (Slc26a5), three genes needed for normal hearing function. Finally, we successfully disrupted vGlut3, Otof and prestin simultaneously. Our results show that CRISPR-stop can efficiently generate single or triple homozygous F0 mouse mutants, bypassing laborious mouse breeding. We believe that CRISPR-stop is a powerful method that will pave the way for high-throughput screening of mouse developmental and functional genes, matching the efficiency of methods available for model organisms such as Drosophila. Highlighted Article: Compound homozygous mutants are typically achieved through laborious breeding but the novel CRISPR-stop approach can rapidly generate F0 mice with homozygous zygotic mutations in multiple genes.
Biomarkers for acute diagnosis and management of stroke in neurointensive care units

The effectiveness of current management of critically ill stroke patients depends on rapid assessment of the type of stroke, ischemic or hemorrhagic, and on a patient′s general clinical status. Thrombolytic therapy with recombinant tissue plasminogen activator (r-tPA) is the only effective treatment for ischemic stroke approved by the Food and Drug Administration (FDA), whereas no treatment has been shown to be effective for hemorrhagic stroke. Furthermore, a narrow therapeutic window and fear of precipitating intracranial hemorrhage by administering r-tPA cause many clinicians to avoid using this treatment. Thus, rapid and objective assessments of stroke type at admission would increase the number of patients with ischemic stroke receiving r-tPA treatment and thereby, improve outcome for many additional stroke patients. Considerable literature suggests that brain-specific protein biomarkers of glial [i.e. S100 calcium-binding protein B (S100B), glial fibrillary acidic protein (GFAP)] and neuronal cells [e.g., ubiquitin C-terminal hydrolase-L1 (UCH-L1), neuron-specific enolase (NSE), αII-spectrin breakdown products SBDP120, SBDP145, and SBDP150, myelin basic protein (MBP), neurofilament light chain (NF-L), tau protein, visinin-like protein-1 (VLP 1), NR2 peptide] injury that could be detected in the cerebrospinal fluid (CSF) and peripheral blood might provide valuable and timely diagnostic information for stroke necessary to make prompt management and decisions, especially when the time of stroke onset cannot be determined. This information could include injury severity, prognosis of short-term and long-term outcomes, and discrimination of ischemic or hemorrhagic stroke. This chapter reviews the current status of the development of biomarker-based diagnosis of stroke and its potential application to improve stroke care.
Analysis of Multifrequency and Phase Keying Strategies for Focusing Ultrasound to the Human Vertebral Canal

Focused ultrasound has been shown to increase the permeability of the blood–brain barrier and its feasibility for opening the blood–spinal cord barrier has also been demonstrated in small animal models, with great potential to impact the treatment of spinal cord (SC) disorders. For clinical translation, challenges to transvertebral focusing of ultrasound energy on the human spinal canal, such as a focal depth of field and standing-wave formation, must be addressed. A dual-aperture approach using multifrequency and phase-shift keying (PSK) strategies for achieving a controlled focus in human thoracic vertebrae was investigated through numerical simulations and benchtop experiments in ex vivo human vertebrae. An ~85% reduction in the focal depth of field was achieved compared to a single-aperture approach at 564 kHz. Short-burst (two-cycle) excitations in combination with PSK were found to suppress the formation of standing waves in ex vivo human thoracic vertebrae when focusing through the vertebral laminae. The results make an important contribution toward the development of a clinical-scale approach for targeting ultrasound therapy to the SC.
High Prevalence of Hereditary Cancer Syndromes and Outcomes in Adults with Early-Onset Pancreatic Cancer

Introduction: We aimed to determine the prevalence and landscape of germline mutations among patients with young-onset pancreatic ductal adenocarcinoma (PDAC) as well as their influence in prognosis. Methods: Patients from two cohorts were studied, the high-risk cohort (HRC), which included 584 PDAC patients who received genetic counseling at The University of Texas MD Anderson Cancer Center, and a general cohort (GC) with 233 metastatic PDAC patients. We defined germline DNA sequencing on 13 known pancreatic cancer susceptibility genes. The prevalence and landscape of mutations were determined, and clinical characteristics including survival were analyzed. Results: A total of 409 patients underwent genetic testing (277 from HRC and 132 from GC). As expected, the HRC had higher prevalence of germline mutations compared with the GC: 17.3% versus 6.81%. The most common mutations in both cohorts were in BRCA1/2 and mismatch-repair (MMR) genes. Patients younger than 60 years old had significantly higher prevalence of germline mutations in both the HRC [odds ratios (OR), 1.93 ± 1.03–3.70, P = 0.039] and GC (4.78 ± 1.10–32.95, P = 0.036). Furthermore, PDAC patients with germline mutations in the GC had better overall survival than patients without mutations (HR, 0.44; 95% CI of HR, 0.25–0.76, P = 0.030). Discussion: Germline mutations are highly prevalent in patients with PDAC of early onset and can be predictive of better outcomes. Considering emerging screening strategies for relatives carrying susceptibility genes as well as impact on therapy choices, genetic counseling and testing should be encouraged in PDAC patients, particularly those of young onset. Cancer Prev Res; 11(11); 679–86. ©2018 AACR.
NICE: Noise Injection and Clamping Estimation for Neural Network Quantization

Convolutional Neural Networks (CNNs) are very popular in many fields including computer vision, speech recognition, natural language processing, etc. Though deep learning leads to groundbreaking performance in those domains, the networks used are very computationally demanding and are far from being able to perform in real-time applications even on a GPU, which is not power efficient and therefore does not suit low power systems such as mobile devices. To overcome this challenge, some solutions have been proposed for quantizing the weights and activations of these networks, which accelerate the runtime significantly. Yet, this acceleration comes at the cost of a larger error unless spatial adjustments are carried out. The method proposed in this work trains quantized neural networks by noise injection and a learned clamping, which improve accuracy. This leads to state-of-the-art results on various regression and classification tasks, e.g., ImageNet classification with architectures such as ResNet-18/34/50 with as low as 3 bit weights and activations. We implement the proposed solution on an FPGA to demonstrate its applicability for low-power real-time applications. The quantization code will become publicly available upon acceptance.
Evaluation of IPv6 transition mechanisms using QoS service policies

IPv6 networks are rarely fully IPv6 from end to end particularly when interconnected over other providers core data networks, hence the need for IPv6 transition methods or mechanisms. Previous studies have identified some potential impact on performance where transitions occur. This study considered implementations where Quality of Service (QoS) service policies have been applied in the IPv6 network to determine if the transition mechanisms were able to guarantee the same performance and level of service when the IPv6 traffic transitions over a core IPv4 network. Using a test lab, traffic generators and data capture tools the study was able to fully test the transition mechanisms using data rates and link speeds that replicated equipment and traffic levels used in real world implementations. The study showed that the Quality of Service classes applied were maintained across the transition network providing the service guarantees required for a range of traffic classes. Results indicated that the transition implementations on the devices used (Cisco ISR 4351) translate the QoS settings from IPv6 to IPV4 and vice versa were highly effective and with negligible additional impact on performance occurring due to the additional processing required.
A Deep Learning Framework for Single-Sided Sound Speed Inversion in Medical Ultrasound

Objective: Ultrasound elastography is gaining traction as an accessible and useful diagnostic tool for things such as, cancer detection and differentiation and thyroid disease diagnostics. Unfortunately, state-of-the-art shear wave imaging techniques, essential to promote this goal, are limited to high-end ultrasound hardware due to high-power requirements, and are extremely sensitive to patient and sonographer motion, and generally suffer from low frame rates. Motivated by research and theory showing that longitudinal wave sound speed carries similar diagnostic abilities to shear wave imaging, we present an alternative approach using single-sided pressure-wave sound speed measurements from channel data. Methods: In this paper, we present a single-sided sound speed inversion solution using a fully convolutional deep neural network. We use simulations for training, allowing the generation of limitless ground truth data. Results: We show that it is possible to invert for longitudinal sound speed in soft tissue at high frame rates. We validate the method on simulated data. We present highly encouraging results on limited real data. Conclusion: Sound speed inversion on channel data has made significant potential possible in real time with deep learning technologies. Significance: Specialized shear wave ultrasound systems remain inaccessible in many locations. Longitudinal sound speed and deep learning technologies enable an alternative approach to diagnosis based on tissue elasticity. High frame rates are also possible.
Effect of Branched-Chain Amino Acid Supplementation on Recovery Following Acute Eccentric Exercise

This study investigated the effect of branched-chain amino acid (BCAA) supplementation on recovery from eccentric exercise. Twenty males ingested either a BCAA supplement or placebo (PLCB) prior to and following eccentric exercise. Creatine kinase (CK), vertical jump (VJ), maximal voluntary isometric contraction (MVIC), jump squat (JS) and perceived soreness were assessed. No significant (p > 0.05) group by time interaction effects were observed for CK, soreness, MVIC, VJ, or JS. CK concentrations were elevated above baseline (p < 0.001) in both groups at 4, 24, 48 and 72 hr, while CK was lower (p = 0.02) in the BCAA group at 48 hr compared to PLCB. Soreness increased significantly from baseline (p < 0.01) in both groups at all time-points; however, BCAA supplemented individuals reported less soreness (p < 0.01) at the 48 and 72 hr time-points. MVIC force output returned to baseline levels (p > 0.05) at 24, 48 and 72 hr for BCAA individuals. No significant difference between groups (p > 0.05) was detected for VJ or JS. BCAA supplementation may mitigate muscle soreness following muscle-damaging exercise. However, when consumed with a diet consisting of ~1.2 g/kg/day protein, the attenuation of muscular performance decrements or corresponding plasma CK levels are likely negligible.
Crop Classification Based on Differential Characteristics of  $H/\alpha$  Scattering Parameters for Multitemporal Quad- and Dual-Polarization SAR Images

Crop-type classification is one of the most significant applications in polarimetric synthetic aperture radar (PolSAR) imagery. As a remote sensing technique, PolSAR has been proved to have the ability to provide high-resolution information of illustrated objects. However, single-temporal PolSAR data are restricted to provide sufficient information for crop identification due to the complicated condition of varying morphology within various growing stages. With an increasing number of spaceborne PolSAR systems launched, a large amount of real PolSAR data are being generated and used to provide great opportunities for multitemporal analysis. The main contribution of this paper is to improve crop classification accuracy with various features of classical <inline-formula> <tex-math notation="LaTeX">$H$ </tex-math></inline-formula>/<inline-formula> <tex-math notation="LaTeX">$\alpha$ </tex-math></inline-formula> parameters. First, in order to deal with dual-PolSAR data, <inline-formula> <tex-math notation="LaTeX">$H$ </tex-math></inline-formula>/<inline-formula> <tex-math notation="LaTeX">$\alpha$ </tex-math></inline-formula> decomposition algorithm for quad-PolSAR is modified to suit to the case of dual polarization. Second, according to the differential scattering characteristics of main crops, a new parameter is innovatively defined to measure the differential characteristics in the <inline-formula> <tex-math notation="LaTeX">$H$ </tex-math></inline-formula>/<inline-formula> <tex-math notation="LaTeX">$\alpha$ </tex-math></inline-formula> classification plane. Third, crop types are discriminated by applying a supervised classification method with the newly defined parameter. Furthermore, the correctness of the parameter is verified with simulated and real Sentinel-1 data as well as AirSAR data. Finally, the performances of the classification method are investigated by the comparison with complex Wishart, Freeman–Wishart, and support vector machine (SVM) classifiers. Hence, the experimental results show that the proposed method and SVM classifier with the newly defined parameter have the ability to improve crop classification accuracy.
Data-Based Optimal Control of Multiagent Systems: A Reinforcement Learning Design Approach

This paper studies an optimal consensus tracking problem of heterogeneous linear multiagent systems. By introducing tracking error dynamics, the optimal tracking problem is reformulated as finding a Nash-equilibrium solution to multiplayer games, which can be done by solving associated coupled Hamilton–Jacobi equations. A data-based error estimator is designed to obtain the data-based control for the multiagent systems. Using the quadratic functional to approximate every agent’s value function, we can obtain the optimal cooperative control by the input–output (I/O) ${Q}$ -learning algorithm with a value iteration technique in the least-square sense. The control law solves the optimal consensus problem for multiagent systems with measured I/O information, and does not rely on the model of multiagent systems. A numerical example is provided to illustrate the effectiveness of the proposed algorithm.