Miracle-dz/UniFAR-FTUs huggingface dataset:
Geographic Variation and Risk Factor Association of Early Versus Late Onset Colorectal Cancer

Simple Summary While the incidence of late-onset colorectal cancer (LOCRC) has steadily decreased, the incidence of early-onset colorectal cancer (EOCRC) has continued to increase in the US. This study aims to uncover geographic disparities in EOCRC and understand how risk factors between EOCRC and LOCRC differ. The geographic analysis revealed regions with relatively low LOCRC rates and high EOCRC rates, identifying regions with a disproportionate burden of EOCRC. We then evaluated and compared community-level risk factors associated with incidence rates of EOCRC and LOCRC using the random forest machine learning method. The analysis identified a set of risk factors most predictive of EOCRC and LOCRC, such as diabetes prevalence and physical inactivity, but the importance of these risk factors varied between EOCRC and LORC. Collectively, these findings can help facilitate future studies that further uncover actionable interventions to reduce EOCRC and guide where targeted interventions to reduce EOCRC burden should be deployed. Abstract The proportion of patients diagnosed with colorectal cancer (CRC) at age < 50 (early-onset CRC, or EOCRC) has steadily increased over the past three decades relative to the proportion of patients diagnosed at age ≥ 50 (late-onset CRC, or LOCRC), despite the reduction in CRC incidence overall. An important gap in the literature is whether EOCRC shares the same community-level risk factors as LOCRC. Thus, we sought to (1) identify disparities in the incidence rates of EOCRC and LOCRC using geospatial analysis and (2) compare the importance of community-level risk factors (racial/ethnic, health status, behavioral, clinical care, physical environmental, and socioeconomic status risk factors) in the prediction of EOCRC and LOCRC incidence rates using a random forest machine learning approach. The incidence data came from the Surveillance, Epidemiology, and End Results program (years 2000–2019). The geospatial analysis revealed large geographic variations in EOCRC and LOCRC incidence rates. For example, some regions had relatively low LOCRC and high EOCRC rates (e.g., Georgia and eastern Texas) while others had relatively high LOCRC and low EOCRC rates (e.g., Iowa and New Jersey). The random forest analysis revealed that the importance of community-level risk factors most predictive of EOCRC versus LOCRC incidence rates differed meaningfully. For example, diabetes prevalence was the most important risk factor in predicting EOCRC incidence rate, but it was a less important risk factor of LOCRC incidence rate; physical inactivity was the most important risk factor in predicting LOCRC incidence rate, but it was the fourth most important predictor for EOCRC incidence rate. Thus, our community-level analysis demonstrates the geographic variation in EOCRC burden and the distinctive set of risk factors most predictive of EOCRC.
The steady Navier–Stokes/energy system with temperature‐dependent viscosity—Part 2: The discrete problem and numerical experiments

In this second part, we analyse the associated discrete problem arising from a conforming finite element method formulation of the mathematical model presented in the first part. Thus, existence and uniqueness of the discrete solution when using small enough data are stated following the same strategy used in the continuous case, with a Cea's type error estimate established as the main result. Some numerical experiments, steady and unsteady, are performed, which allow us to validate the previous mathematical model and its discrete approximation. Copyright © 2007 John Wiley & Sons, Ltd.
Dissipation of isotropic turbulence and length‐scale measurements through the wave roller in laboratory spilling waves

[1] The measurement of turbulence dissipation rates and length scales associated with three-dimensional isotropic structures under spilling waves breaking in a laboratory surf zone is presented. Dissipation rates were estimated from the spectral characteristics of the turbulence velocities in the inertial subrange, and length scales were estimated using measurements of the turbulent kinetic energy and dissipation rate. The spatial velocity flow fields for the above analysis were measured using digital correlation image velocimetry. A unique set of measurements that spans the entire water column, including the aerated portion near the crest of the wave, is presented. Dissipation rates were found to reach a maximum above the effective trough level, with over 80% of the depth integrated dissipation occurring in this upper zone. The total depth integrated turbulence dissipation rate is found to be up to an order of magnitude smaller than the local rate of wave energy dissipation due to breaking, the primary turbulence production source. The length scale is found to increase in magnitude below the surface, consistent with the idea that turbulence production occurs above the trough level in the vicinity of the wave roller and is transported downward toward the bed.
An Intelligent Two-Stage Energy Dispatch Management System for Hybrid Power Plants: Impact of Machine Learning Deployment

The utilization of renewable energy sources such as PV and wind power has become imperative due to the increase of carbon dioxide emissions, which leads to the increase in global temperature and the negative consequences of climate change. As a result, renewable energy sources are constantly gaining popularity to be integrated in power systems to create hybrid power plants (HPPs). However, HPPs come with great complications due to the uncertainty in renewable energy output, which has given rise to the need for a reliable and effective energy dispatch management system for HPPs. In this paper, a two-stage machine learning (ML) based energy dispatch management system for HPPs is designed to control renewable energy sources (PV and wind power), reserve energy sources (energy storage systems) and backup energy sources (diesel, fuel cells, auxiliary loads, etc.). The system aims to minimize the power variance in the HPPs to achieve peak shaving and valley filling. The first stage aims to forecast the power output of renewable energy sources, as well as the load demand. The second stage aims to coordinate the energy output of the reserve and backup sources to achieve the required objective. Different ML techniques were compared to find the highest performing ML algorithm to achieve the required objective of the system, where long short-term memory (LSTM) provided the highest results with an average mean squared error of 0.005 and an average explained variance score of 0.9. The results of the management system verify the effectiveness of the system for the management of the energy dispatch in HPPs, through the successful flattening of the load curve of the HPP, which increases the reliability of the power system with the integration of renewable energy sources. Also, the system was shown to be robust against the uncertainty of the PV and wind power output, and the load demand.
Muscle Pathology in Dystrophic Rats and Zebrafish Is Unresponsive to Taurine Treatment, Compared to the mdx Mouse Model for Duchenne Muscular Dystrophy

Inflammation and oxidative stress are strongly implicated in the pathology of Duchenne muscular dystrophy (DMD), and the sulphur-containing amino acid taurine ameliorates both and decreases dystropathology in the mdx mouse model for DMD. We therefore further tested taurine as a therapy using dystrophic DMDmdx rats and dmd zebrafish models for DMD that have a more severe dystropathology. However, taurine treatment had little effect on the indices of dystropathology in both these models. While we and others have previously observed a deficiency in taurine in mdx mice, in the current study we show that the rat and zebrafish models had increased taurine content compared with wild-type, and taurine treatment did not increase muscle taurine levels. We therefore hypothesised that endogenous levels of taurine are a key determinate in potential taurine treatment efficacy. Because of this, we felt it important to measure taurine levels in DMD patient plasma samples and showed that in non-ambulant patients (but not in younger patients) there was a deficiency of taurine. These data suggest that taurine homeostasis varies greatly between species and may be influenced by age and disease progression. The potential for taurine to be an effective therapy may depend on such variables.
Continuous Exposure to Terrorism during the COVID-19 Pandemic: A Moderated Mediation Model in the Israeli Context

This study tested the role of perceived social support as a moderating factor in the mediation of COVID-19-related concerns in the association between continuous traumatic stress (CTS) and depression. The study participants were 499 college students who responded to an anonymous online questionnaire. Measures included the assessment of prior continuous exposure to threats of terrorism, COVID-19-related distress, perceived social support and depressive symptoms. The results demonstrated that COVID-19-related concerns mediated the relationship between continuous exposure to threats of terrorism and depression symptoms, and that perceived social support moderated the association between COVID-19-related concerns and depression. The implications of the study highlight the role of prior exposure to traumatic stress as a risk factor for depression and the role of social support as a protective factor. These results point to the need to develop accessible and non-stigmatic mental health services for populations exposed to other types of continuous traumatic stress.
Systemic Cytokines in Retinopathy of Prematurity

Retinopathy of prematurity (ROP), a vasoproliferative vitreoretinal disorder, is the leading cause of childhood blindness worldwide. Although angiogenic pathways have been the main focus, cytokine-mediated inflammation is also involved in ROP etiology. Herein, we illustrate the characteristics and actions of all cytokines involved in ROP pathogenesis. The two-phase (vaso-obliteration followed by vasoproliferation) theory outlines the evaluation of cytokines in a time-dependent manner. Levels of cytokines may even differ between the blood and the vitreous. Data from animal models of oxygen-induced retinopathy are also valuable. Although conventional cryotherapy and laser photocoagulation are well established and anti-vascular endothelial growth factor agents are available, less destructive novel therapeutics that can precisely target the signaling pathways are required. Linking the cytokines involved in ROP to other maternal and neonatal diseases and conditions provides insights into the management of ROP. Suppressing disordered retinal angiogenesis via the modulation of hypoxia-inducible factor, supplementation of insulin-like growth factor (IGF)-1/IGF-binding protein 3 complex, erythropoietin, and its derivatives, polyunsaturated fatty acids, and inhibition of secretogranin III have attracted the attention of researchers. Recently, gut microbiota modulation, non-coding RNAs, and gene therapies have shown promise in regulating ROP. These emerging therapeutics can be used to treat preterm infants with ROP.
Ozoile Reduces the LPS-Induced Inflammatory Response in Colonic Epithelial Cells and THP-1 Monocytes

Inappropriate activation of immune functions in intestinal epithelial cells can lead to inflammation that is characterized also by infiltration into intestinal tissue of monocytes/macrophages. Current therapies for intestinal inflammation include anti-inflammatory, immunosuppressive and biological drugs. Ozoile (stable ozonides) has been reported to exert anti-inflammatory effects. However, ozonated oil has been used mainly for topical applications and no data are available about its effects on intestinal cells or immune cells. In this study, we evaluated Ozoile effects on human HT-29 colonic cells and THP-1 monocytic cells stimulated with LPS to induce inflammation. HT-29 and THP-1 cells were treated with LPS in the presence/absence of Ozoile for 4 h. Biomarkers of inflammation, some members of tight junctions and the adhesion molecule ICAM were assessed by qRT-PCR. Protein expression was analyzed by Western blotting. The release of TNF-α and IL-1β was measured by ELISA. In HT-29, Ozoile inhibited LPS-induced expression of TNF-α, IL-1β, ZO-1, CLDN1, NOS2 and MMP-2 and increased the expression of Nrf2 and SOD2 antioxidant proteins. In THP-1 cells, the LPS induction of TNF-α, IL-1β and ICAM was counteracted by Ozoile treatment. Our in vitro results demonstrate the effectiveness of Ozoile in reducing the inflammatory response in intestinal and monocytic cells. Further in vivo studies are necessary to confirm its possible use for intestinal inflammatory conditions.
Metabolic risk score as a predictor in a nomogram for assessing myometrial invasion for endometrial cancer

The purpose of the present study was to investigate the predictive value of metabolic syndrome in evaluating myometrial invasion (MI) in patients with endometrial cancer (EC). The study retrospectively included patients with EC who were diagnosed between January 2006 and December 2020 at the Department of Gynecology of Nanjing First Hospital (Nanjing, China). The metabolic risk score (MRS) was calculated using multiple metabolic indicators. Univariate and multivariate logistic regression analyses were performed to determine significant predictive factors for MI. A nomogram was then constructed based on the independent risk factors identified. A calibration curve, a receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were used to evaluate the effectiveness of the nomogram. A total of 549 patients were randomly assigned to a training or validation cohort, with a 2:1 ratio. Data was then gathered on significant predictors of MI in the training cohort, including MRS [odds ratio (OR), 1.06; 95% confidence interval (CI), 1.01-1.11; P=0.023], histological type (OR, 1.98; 95% CI, 1.11-3.53; P=0.023), lymph node metastasis (OR, 3.15; 95% CI, 1.61-6.15; P<0.001) and tumor grade (grade 2: OR, 1.71; 95% CI, 1.23-2.39; P=0.002; Grade 3: OR, 2.10; 95% CI, 1.53-2.88; P<0.001). Multivariate analysis indicated that MRS was an independent risk factor for MI in both cohorts. A nomogram was generated to predict a patient's probability of MI based on the four independent risk factors. ROC curve analysis showed that, compared with the clinical model (model 1), the combined model with MRS (model 2) significantly improved the diagnostic accuracy of MI in patients with EC (area under the curve in model 1 vs. model 2: 0.737 vs. 0.828 in the training cohort and 0.713 vs. 0.759 in the validation cohort). Calibration plots showed that the training and validation cohorts were well calibrated. DCA showed that a net benefit is obtained from the application of the nomogram. Overall, the present study developed and validated a MRS-based nomogram predicting MI in patients with EC preoperatively. The establishment of this model may promote the use of precision medicine and targeted therapy in EC and has the potential to improve the prognosis of patients affected by EC.
Ground State and Staggered Susceptibility of the Two-Impurity Problem

We study the two-impurity Anderson model by the exact diagonalization method in small systems and the variational method. With varying of the exchange coupling J between two impurities, we evaluate the staggered susceptibility χ s to investigate the competition between the Kondo effect and the RKKY interaction effect. The staggered susceptibility in our calculations shows no anomalous behavior in contrast to the recent numerical renormalization group calculations. In order to study this further, we introduce the even-parity-mixing Anderson model. This model appears to show singularities in χ s and the ground-state energy at a point J = J c . We show that at this point, the ground state changes suddenly; the localized spins form a triplet for J J c . In the original two-impurity Anderson model, a crossover occurs around J c without singularity.
Antiviral Activity of Micafungin and Its Derivatives against SARS-CoV-2 RNA Replication

Echinocandin antifungal drugs, including micafungin, anidulafungin, and caspofungin, have been recently reported to exhibit antiviral effects against various viruses such as flavivirus, alphavirus, and coronavirus. In this study, we focused on micafungin and its derivatives and analyzed their antiviral activities against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The micafungin derivatives Mi-2 and Mi-5 showed higher antiviral activity than micafungin, with 50% maximal inhibitory concentration (IC50) of 5.25 and 6.51 µM, respectively (3.8 to 4.7-fold stronger than micafungin) and 50% cytotoxic concentration (CC50) of >64 µM in VeroE6/TMPRSS2 cells. This high anti-SARS-CoV-2 activity was also conserved in human lung epithelial cell-derived Calu-3 cells. Micafungin, Mi-2, and Mi-5 were suggested to inhibit the intracellular virus replication process; additionally, these compounds were active against SARS-CoV-2 variants, including Delta (AY.122, hCoV-19/Japan/TY11-927/2021), Omicron (BA.1.18, hCoV-19/Japan/TY38-873/2021), a variant resistant to remdesivir (R10/E796G C799F), and a variant resistant to casirivimab/imdevimab antibody cocktail (E406W); thus, our results provide basic evidence for the potential use of micafungin derivatives for developing antiviral agents.
Quantitative Trait Loci for Genotype and Genotype by Environment Interaction Effects for Seed Yield Plasticity to Terminal Water-Deficit Conditions in Canola (Brassica napus L.)

Canola plants suffer severe crop yield and oil content reductions when exposed to water-deficit conditions, especially during the reproductive stages of plant development. There is a pressing need to develop canola cultivars that can perform better under increased water-deficit conditions with changing weather patterns. In this study, we analysed genetic determinants for the main effects of quantitative trait loci (QTL), (Q), and the interaction effects of QTL and Environment (QE) underlying seed yield and related traits utilising 223 doubled haploid (DH) lines of canola in well-watered and water-deficit conditions under a rainout shelter. Moderate water-deficit at the pre-flowering stage reduced the seed yield to 40.8%. Multi-environmental QTL analysis revealed 23 genomic regions associated with days to flower (DTF), plant height (PH) and seed yield (SY) under well-watered and water-deficit conditions. Three seed yield QTL for main effects were identified on chromosomes A09, C03, and C09, while two were related to QE interactions on A02 and C09. Two QTL regions were co-localised to similar genomic regions for flowering time and seed yield (A09) and the second for plant height and chlorophyll content. The A09 QTL was co-located with a previously mapped QTL for carbon isotope discrimination (Δ13C) that showed a positive relationship with seed yield in the same population. Opposite allelic effects for plasticity in seed yield were identified due to QE interactions in response to water stress on chromosomes A02 and C09. Our results showed that QTL’s allelic effects for DTF, PH, and SY and their correlation with Δ13C are stable across environments (field conditions, previous study) and contrasting water regimes (this study). The QTL and DH lines that showed high yield under well-watered and water-deficit conditions could be used to manipulate water-use efficiency for breeding improved canola cultivars.
Manipulation of magnetic state in phosphorene layer by non-magnetic impurity doping

Using the full-potential linearized augmented plane wave method, we have explored the structural, electronic band structure, binding energy, and magnetic properties of a non-magnetic impurity (Al, Si, S, and Cl) doped phosphorene layer. The binding energy showed a tendency to decrease with increasing atomic number. Nonetheless, we still found large binding energies of 5.1 eV ∼ 8.3 eV. We observed that the electronic band structure and magnetic property were strongly dependent on the specific impurity atom. For instance, we propose that the Al doped system will show a semiconducting transport property. In all other systems, we found metallic band structures. We predict that the Al and Si impurity act as donor elements whereas the S and Cl impurities behave as acceptor elements. Interestingly, the magnetic state appeared in Si, S, and Cl doped systems while the Al impurity induced no spin polarized state. In the Si doped system, the major contribution to a magnetic moment originated from Si impurity itself, while the presence of dangling bonds at a neighboring P atom near the impurity site plays a crucial role for magnetism in S and Cl doped systems. On the other hand, interestingly, we observed a half metallic feature in the S doped layer. Overall, we have found that the magnetic state can be manipulated by even non-magnetic impurity doping in a phosphorene layer.
Micromachined array of electrostatic energy analyzers for charged particles

The design, fabrication techniques, and first test results of a new type of micromachined energy analyzer for charged particles are presented. The novel design is based on a Bessel Box straight‐line geometry with focusing in one dimension. The problem of small acceptance area due to the drastically reduced overall dimensions is accounted for by the use of a parallel array of small analyzers simultaneously. We describe the fabrication of a proof‐of‐concept micromachined Bessel Box array by means of anisotropic wet etching of 〈110〉 silicon, and we present ray‐tracing simulations for a simple geometry. Finally, we show some test results of Auger electrons and discuss possible applications of generic small charged particle analyzers.
On the mixing properties of piecewise expanding maps under composition with permutations

We consider the effect on the mixing properties of a piecewise smooth interval map $f$ when its domain is divided into $N$ equal subintervals and $f$ is composed with a permutation of these. The case of the stretch-and-fold map $f(x)=mx \bmod 1$ for integers $m \geq 2$ is examined in detail. We give a combinatorial description of those permutations $\sigma$ for which $\sigma \circ f$ is still (topologically) mixing, and show that the proportion of such permutations tends to $1$ as $N \to \infty$. We then investigate the mixing rate of $\sigma \circ f$ (as measured by the modulus of the second largest eigenvalue of the transfer operator). In contrast to the situation for continuous time diffusive systems, we show that composition with a permutation cannot improve the mixing rate of $f$, but typically makes it worse. Under some mild assumptions on $m$ and $N$, we obtain a precise value for the worst mixing rate as $\sigma$ ranges through all permutations; this can be made arbitrarily close to $1$ as $N → ∞$ (with $m$ fixed). We illustrate the geometric distribution of the second largest eigenvalues in the complex plane for small $m$ and $N$, and propose a conjecture concerning their location in general. Finally, we give examples of other interval maps $f$ for which composition with permutations produces different behaviour than that obtained from the stretch-and-fold map.