Miracle-dz/UniFAR-FTUs huggingface dataset:
Study of Dickkopf-1 (DKK-1) in patients with chronic viral hepatitis C-related liver cirrhosis with and without hepatocellular carcinoma

Aim of the study Dickkopf-1 (DKK-1) is a secreted protein which acts as an inhibitor of Wnt/β-catenin signaling. DKK-1 was found to be a helpful biomarker for many cancers including hepatocellular carcinoma (HCC). HCC is multifactorial in origin and its main etiology in Egypt is attributed to chronic hepatitis C virus (HCV) infection. Objectives: To assess the serum level and diagnostic performance of DKK-1 and α-fetoprotein (AFP) in Egyptian patients with chronic HCV-related liver cirrhosis with and without HCC. Material and methods 80 subjects were divided into: a control group (group I, 20 healthy volunteers) and two patient groups: group II (HCV with liver cirrhosis, 30 patients), and group III, (HCV-related liver cirrhosis with HCC, 30 patients). Thorough physical examination, triphasic computed tomography, calculation of Child-Pugh score, laboratory investigations (complete blood picture, liver profile, hepatitis B surface antigen, anti-HCV antibodies, AFP (chemiluminometry) and DKK-1 (ELISA) were performed. Results There was a significant decrease in DKK-1 level in HCV patients with liver cirrhosis (group II) and HCV patients with HCC (group III) compared to the control group (group I) (p < 0.001). However, there was a significant increase in DKK-1 level in HCV patients with HCC (group III) compared to HCV patients with liver cirrhosis (group II) (p < 0.033). The ROC curve showed that DKK-1 has less sensitivity but higher specificity in HCV patients with HCC (group III) compared with HCV patients with liver cirrhosis (group II). Conclusions The combination of DKK-1 and AFP could further improve the diagnostic accuracy of HCV-related cirrhosis with or without HCC.
Prognostic Value of Admission Mean Corpuscular Volume for Major Adverse Cardiovascular Events following Stent Implantation in Nondiabetic and Diabetic Patients with Acute Coronary Syndrome

Background One of the key concerns of the clinician is to identify and manage risk factors for major adverse cardiovascular events (MACEs) in nondiabetic and diabetic patients with acute coronary syndrome (ACS) undergoing stent implantation. Mean corpuscular volume (MCV) is a marker of erythrocyte size and activity and is associated with prognosis of cardiovascular disease. However, the role of admission MCV in predicting MACEs following stent implantation in diabetes mellitus (DM), non-DM, or whole patients with ACS remains largely unknown. Methods and Results A total of 437 ACS patients undergoing stent implantation, including 294 non-DM (59.08 ± 10.24 years) and 143 DM (63.02 ± 9.92 years), were analyzed. Admission MCV was higher in non-DM than DM patients. During a median of 31.93 months follow-up, Kaplan-Meier curve demonstrated that higher admission MCV level was significantly associated with increased MACEs in whole and non-DM, but not in DM patients. In Cox regression analysis, the highest MCV tertile was associated with higher MACEs in whole ([HR] 1.870, 95% CI 1.113-3.144, P = 0.018), especially those non-DM ([HR] 2.089, 95% CI 1.077-4.501, P = 0.029) patients after adjustment of several cardiovascular risk factors. MCV did not predict MACEs in DM patients. During landmark analysis, admission MCV showed better predictive value for MACEs in the first 32 months of follow-up than in the subsequent period. Finally, the receiver operating characteristic (ROC) curve was conducted to confirmed the value of admission MCV within 32 months. Conclusion In patients with ACS, elevated admission MCV is an important and independent predictor for MACEs following stent implantation, especially amongst those without DM even after adjusting for lifestyle and clinical risk factors. However, as the follow-up period increased, the admission MCV lost its ability to predict MACEs.
Sinogram-Affirmed Iterative Reconstruction Negatively Impacts the Risk Category Based on Agatston Score: A Study Combining Coronary Calcium Score Measurement and Coronary CT Angiography

Purpose To assess the impact of sinogram-affirmed iterative reconstruction (SAFIRE) on risk category for coronary artery disease by combining coronary calcium score measurement and coronary CT angiography (CCTA). Materials and Methods Eighty-nine patients (64.0% male) older than 18 years (64.4 ± 10.3 years) underwent coronary artery calcium scanning and prospectively ECG-triggered sequential CCTA examination. All raw data acquired in coronary artery calcium scanning were reconstructed by both filtered back projection (FBP) and SAFIRE algorithms with 5 different levels. Objective image quality and calcium quantification were evaluated and compared between FBP and all SAFIRE levels by the Sphericity Assumed test or Greenhouse-Geisser ε correction coefficient. Coronary artery stenosis was assessed in CCTA. Risk categories of all patients and of the patients with coronary artery stenosis in CCTA were compared between FBP and all SAFIRE levels by the Friedman test. Results The reconstruction protocol from traditional FBP to SAFIRE 5 was associated with a gradual reduction in CT value and image noise (P < 0.001) but associated with a gradual improvement in the signal-to-noise ratio (P < 0.001). There was a gradual reduction in coronary calcification quantification (Agatston score: from 73.5 in FBP to 38.1 in SAFIRE 5, P < 0.001) from traditional FBP to SAFIRE 5. There was a significant difference for the risk category between FBP and all levels of SAFIRE in all patients (from 3.5 in FBP to 3.2 in SAFIRE 5, P < 0.001) and in the patients with coronary artery stenosis in CCTA (from 4.0 in FBP to 3.6 in SAFIRE 5, P < 0.001). Conclusions SAFIRE significantly reduces coronary calcification quantification compared to FBP, resulting in the reduction of risk categories based on the Agatston score. The risk categories of the patients with coronary artery stenosis in CCTA may also decline. Thus, SAFIRE may lead risk categories to underestimate the existence of significant coronary artery stenosis.
Cited Articles Citing Articles E-mail Alerts Estrogen Receptors a and B Are Inhibitory Modifiers of Apc- Dependent Tumorigenesis in the Proximal Colon of Min/+ Mice

Apc Are Inhibitory Modifiers of β and α Estrogen Receptors Abstract Estrogen replacement therapy in postmenopausal women is associated with a reduction in colorectal cancer risk, potentially via interactions between 17B-estradiol (E 2) and the estrogen receptors (ER) A and B. To study the role of E 2 in intestinal tumor inhibition, we separately crossed C57BL/ 6J-Min/+ (Min/+) mice with Era +/À and Erb +/À mice to generate ER-deficient Min/+ progeny. We found an increased incidence of visible colon tumors and dysplastic micro-adenomas in ER-deficient Min/+ relative to Er +/+ Min/+ controls. Small intestinal tumor numbers were unaffected. Invasive carcinomas were found only in Era +/À Min/+ mice, suggesting that ERA plays additional non–cell autonomous roles that limit tumor progression. Histologic analyses of ER-deficient Min/+ colons, as well as colons from ovariecto-mized Min/+ mice (OvxMin/+) and E 2-treated OvxMin/+ mice (OvxMin/+ +E 2), revealed significant differences in crypt architecture , enterocyte proliferation, and goblet cell differentiation relative to Min/+ and Er +/+ Apc +/+ (wild-type) controls. The expression of ERA and ERB was regionally compartmen-talized along the colonic crypt axis, suggesting functional antagonism. Our results indicate that ERa and ERb are inhibitory modifiers of Apc-dependent colon tumorigenesis. As a result, loss of E 2 and ER signaling in postmenopausal women may contribute to colorectal cancer development.
The mole's sensory apparatus

Attention is drawn to a number of unusual ecological problems posed by the special character of the mole's natural habitat. An account is given of what has been learnt about the mode of function of the animal's sense organs from behavioural observations carried out in the field and in captivity. An attempt is made to show how the neurohistological design of the various receptors is adapted to enable the mole, in the most efficient manner, to perform those special tasks that are appropriate to its subterranean environment.
Technical Sound Event Classification Applying Recurrent and Convolutional Neural Networks

: In many intelligent technical assistance systems (especially diagnostics), the sound classiﬁcation is a signiﬁcant and useful input for intelligent diagnostics. A high performance classiﬁcation of the heterogeneous sounds of any mechanical components can support the diagnostic experts with a lot of information. Classical pattern recognition methods fail because of the complex features and the heterogeneous state noise. Because of no explicit human knowledge about the characteristic representation of the classes, classical feature generation is impossible. A new approach by generation of a concept for neural networks and realization by especially convolutional networks shows the power of technical sound classiﬁcation methods. After the concept ﬁnding a parametrized network model is devised and realized. First results show the power of the RNNs and CNNs. Dependent on the parametrized conﬁguration of the net architecture and the training sets an enhancement of the sound event classiﬁcation is possible.
Beyond Black and White: Combining the Benefits of Regular and Incognito Browsing Modes

: As an increasing number of users seem to be concerned about the sophisticated tracking approaches that web sites employ, most modern browsers provide a privacy-preserving browsing mode. This so called “Incognito” mode enables users to browse web sites with sensitive (e.g., medical-, religious-, and substance-abuse-related) content by providing them with a clean-state and disposable browser session. Although incognito-mode browsing is useful, users will eventually need to switch back to regular web browsing as they need to log in to their favorite web sites (e.g., Gmail, Facebook, etc.). However, whenever they want to access another unfamiliar or sensitive web site, they are forced to switch back to Incognito mode, and so on and so forth. Pretty soon, users ﬁnd themselves switching all the time back and forth between regular and incognito mode. Unfortunately, such a chain of actions, is not only tiresome, but may also turn out to be error-prone as well, since users may accidentally use regular browsing mode to visit web sites they intended to access in incognito mode. To provide users with a convenient and privacy-preserving browsing experience, in this paper we propose G RISEO : a new browsing mode that aims to act as a middle-ground, thus enabling users to get the best of both words: the privacy of incognito mode along with the convenience of the regular browsing mode. Our approach is founded on a whitelist-based solution where users “whitelist” the sites they trust and from which they are willing to receive cookies that will persist even after a single browsing section is over. The rest of the sites are considered black-listed and are allowed to plant only ephemeral cookies: cookies that will be deleted at the end of the browsing session. Our preliminary performance results of our prototype, show that for the average web page access, the rendering time while browsing in G RISEO mode is just 5.9% more than while in Chrome’s Regular Browsing mode. We believe that the overhead of G RISEO is very small and it will be hardly noticeable by most users.
An Identity-matching Process to Strengthen Trust in Federated-identity Architectures

To smoothly counteract privilege escalation in federated-identity architectures, the cross-checking of asserted Personally Identifiable Information (PII) among different sources is highly recommended and advisable. Identity matching is thus a key component for supporting the automated PII cross-checking process. This paper proposes an efficient identity-matching solution, adapted to a chosen User-Relationship Management (URM) platform, relying on a French Territorial Collectivities and Public Administrations (TCPA) use case. The originality of the paper is threefold. (1) It presents an original solution to identity-matching issues raised by a concrete use case from the Territorial Collectivities and the Public Administration (TCPA), formalizing concepts such as information completeness, PII normalization and Levenshtein-distance matrix generation. (2) Implementation guidelines are given to deploy the solution on an operational Publik platform. (3) A precise security analysis is provided, relying on an original attacker model.
Filling in the Flyover Zone: High Phosphorus in Midwestern (USA) Reservoirs Results in High Phytoplankton Biomass but Not High Primary Productivity

In lakes and reservoirs, climate change increases surface water temperatures, promotes thermal stability, and decreases hypolimnetic oxygen. Increased anthropogenic land-use and precipitation enhance nutrient and sediment supply. Together, these effects alter the light and nutrient dynamics constraining phytoplankton biomass and productivity. Given that lake and reservoir processes differ, and that globally, reservoir numbers are increasing to meet water demands, reservoir-centric studies remain underrepresented. In the agricultural Midwest (United States), ubiquitous reservoirs experience eutrophy and hypolimnetic anoxia. Here, we explore influences of eutrophication and land-use on the proximate light and nutrient status of phytoplankton communities in 32 Missouri reservoirs. Light and nutrient status indicators include mixed layer irradiance, phosphorus (P) and nitrogen (N) stoichiometry/debts, photosynthetic efficiency, and photosynthetic-irradiance parameters. Contributing to the ongoing P vs. N and P management debate, we evaluate if phytoplankton biomass and productivity are constrained by light, P, N, or a combination thereof, across gradients of trophic status and land-use during two contrasting wet and dry summers. Despite agricultural prevalence, P-deficiency is more prominent than either N- or light-deficiency. In 2018, ∼46% of samples were P-deficient with ∼36% indicating neither light nor nutrient deficiency. Gross primary productivity per unit chlorophyll-a (GPPB) demonstrates negative relationships with nutrients, biomass, and turbidity, and positive relationships with light availability. GPPB is highest in oligotrophic reservoirs where light utilization efficiency is also highest. Overall, phytoplankton biomass and productivity appear constrained by P and light, respectively. If Midwestern reservoirs are precursors of future inland waters affected by climate change and eutrophication, our crystal ball indicates that both P and light will be important regulators of phytoplankton dynamics and subsequent water quality.
Towards Designing Asynchronous Microprocessors: From Specification to Tape-Out

Proceeding miniaturization in the VLSI circuits continues to pose challenges to the conventionally used synchronous design style in microprocessors. These include the distribution of clock in the GHz range, robustness to delay variations, reduction in electromagnetic interference, and energy conservation, to name a few. The asynchronous logic has been known for its ability to address the aforementioned challenges by means of the closed-loop handshake protocols, instead of notorious clock signals. Because of these advantages, there have been numerous attempts on building general and special purpose microprocessors during the last three decades. Still, however, the number of asynchronous processors commercially available is scarce, mainly due to an insufficient electronic design and automation tools support, an ambiguous design flow and testing mechanisms for asynchronous logic and, most importantly, absence of a forum to look for relevant works, explaining the design steps and tools for such microprocessors. This paper is intended to bridge this gap by 1) reviewing the design principles of asynchronous logic, including classification, signaling conventions, and pipelining approaches; 2) presenting the complete design flow and available electronic design and automation tools; 3) developing an encyclopedia of various general and special purpose microprocessors proposed by far; and 4) presenting an evaluation of those works in terms of area on the die and performance metrics. This paper will also serve as guidelines for the asynchronous microprocessor design and implementation in all phases from specification to tape-out.
Enhanced Blood Supply Through Lower Body Negative Pressure During Slow-Paced, High Load Leg Press Exercise Alters the Response of Muscle AMPK and Circulating Angiogenic Factors

Lower body negative pressure (LBNP) is an established method of simulating the gravitational effects of orthostasis on the cardiovascular system during space flight or at supine body position on Earth. We hypothesized that LBNP added onto leg press exercise would promote leg muscle perfusion, stimulate oxygen consumption, and modify acute molecular responses. Eighteen subjects performed fifteen slow-paced concentric (4 s) and eccentric contractions (4 s) without or with 40 mmHg LBNP. Force corresponding to 6% of the one-repetition maximum (1-RM) at knee flexion gradually increased to 60% 1-RM within the first half of the range of motion, thereafter remaining constant. AMPK and P-AMPK protein expression was determined in biopsies of vastus lateralis. Venous blood samples were used to measure angiogenic factors. Physiological responses to LBNP included an elevated EMG amplitude, higher heart rate and doubling of the cardiac output compared to control (p < 0.001). Muscle total hemoglobin was increased by around 20 μmol/l vs. control (p < 0.001), accompanied by decreasing tissue oxygen saturation and elevated oxygen uptake (p < 0.05). MMP-2 levels were reduced, and the ratio of P-AMPK to AMPK elevated after exercise with LBNP (p < 0.05). MMP-9 similarly increased in both groups, whereas endostatin was only elevated in the control group (p < 0.05). Our results indicate facilitated peripheral blood supply and higher oxygen exploitation leading to activation of the energy sensor AMPK and differential regulation of angiogenic factors involved in muscle tissue remodeling and capillary growth. Simulating orthostasis with LBNP might promote beneficial structural adaptations of skeletal muscles during resistance exercise and contribute to future exercise countermeasures achieving increased muscle strength and endurance during space flight.
Dealing with Interdependencies and Uncertainty in Multi-Channel Advertising Campaigns Optimization

In 2017, Internet ad spending reached 209 billion USD worldwide, while, e.g., TV ads brought in 178 billion USD. An Internet advertising campaign includes up to thousands of sub-campaigns on multiple channels, e.g., search, social, display, whose parameters (bid and daily budget) need to be optimized every day, subject to a (cumulative) budget constraint. Such a process is often unaffordable for humans and its automation is crucial. As also shown by marketing funnel models, the sub-campaigns are usually interdependent, e.g., display ads induce awareness, increasing the number of impressions-and, thus, also the number of conversions-of search ads. This interdependence is widely exploited by humans in the optimization process, whereas, to the best of our knowledge, no algorithm takes it into account. In this paper, we provide the first model capturing the sub-campaigns interdependence. We also provide the IDIL algorithm, which, employing Granger Causality and Gaussian Processes, learns from past data, and returns an optimal stationary bid/daily budget allocation. We prove theoretical guarantees on the loss of IDIL w.r. t. the clairvoyant solution, and we show empirical evidence of its superiority in both realistic and real-world settings when compared with existing approaches.
The Effects of Computer-Based and Motor-Imagery Training on Scoring Ability in Lacrosse

Previous studies have confirmed that the temporal attentional control created by the repetition of stimulus–response compatibility (SRC) tasks was transferred to shooting skills in lacrosse players. In the current study, we investigated whether combining motor imagery training with SRC tasks could enhance the scoring ability of lacrosse players. We grouped 33 male lacrosse players into three groups: an SRC task and motor imagery group (referred as to SRC + Image), an SRC task group, and a control group. Players in the first two groups underwent five sessions of 200 SRC task trials. In addition, the SRC + Image group completed five sessions of motor-imagery training. The control group underwent no training interventions. All three groups performed a lacrosse shooting test and a Simon task before and after training sessions to assess the magnitude of the interference effects of the various types of training they underwent. The results of the Simon task showed that repetition of 1,000 trials was enough to create a short-term representation with the incompatible special mapping being transferred to a dynamic activity like lacrosse shooting. Moreover, a combination of a computer-based Type 2 task and motor-imagery training could effectively increase players’ scoring abilities in a field of large spatial conflict.
Real-Time Grasp Detection Using Improved FMM and Cascaded Neural Networks

The successful grasping task for the robotic arm requires precise grasping posture. In this paper, we use the cascading depth network to predict the optimal object grasping pose. The model is mainly divided into two steps: i) generating a set of candidates that contain the regions of objects; ii) getting the optimal capture position by detecting the candidate region, and combining the depth image to obtain the three-dimensional coordinates of the capture position for objects. Due to flaws and edge noise in the depth image of Kinect, an improved FMM (Fast Marching Method) algorithm is used to repair the depth image hole, and then the joint bilateral filtering algorithm is employed to recover the edge noise of the depth image. Experimental results in public dataset and real scenes have demonstrated the effectiveness of the proposed method.
Automatic Detection of Gait Asymmetry

: Gait analysis, and gait symmetry assessment in particular, are commonly adopted in clinical settings to determine sensorimotor ﬁtness reﬂecting body’s ability to integrate multi-sensory stimuli, and use this information to induce ongoing motor commands. Inter-limb deviation can serve as a non-invasive marker of gait function to identify health conditions and monitor the effects of rehabilitation regimen. This paper examines the performance of machine learning methods (decision trees, k-NN, SVMs, ANNs) to learn and predict gait symmetry from kinetic and kinematic data of 42 participants walking across a range of speeds on treadmill. Classiﬁcation was conducted for each speed independently with several feature extraction techniques applied. Subjects elicited gait asymmetry, yet ground reaction forces were more discriminative than joint angles. Walking speed affected gait symmetry with larger discrepancies registered at slower speeds; the highest F1 scores were noted at the slowest condition (decision trees: 87.35%, k-NN: 91.46%, SVMs: 88.88%, ANNs: 87.22%). None of the existing research has yet addressed ML-assisted assessment of gait symmetry across a range of walking speeds using both, kinetic and kinematic information. The proposed methodology was sufﬁciently sensitive to discern subtle deviations in healthy subjects, hence could facilitate an early diagnosis when anomalies in gait patterns emerge.