Miracle-dz/UniFAR-FTUs huggingface dataset:
Usefulness of a new parameter in functional assessment in patients with idiopathic pulmonary fibrosis: desaturation - distance ratio from the six-minute walk test

Background and aim: New parameters in the 6-minute walk test (6MWT) are needed for assessing exercise capacity in patients with idiopathic pulmonary fibrosis (IPF). To our knowledge, no previous study has investigated the potential of using the desaturation distance ratio (DDR) to assess exercise capacity specifically in patients with IPF. This study aimed to investigate whether DDR is a potential tool for assessing the exercise capacity of patients with IPF. Methods: This study conducted with 33 subjects with IPF. Pulmonary function tests and a 6MWT were performed. To calculate the DDR, first, the difference between the patient’s SpO2 at each minute and the SpO2 of 100% was summed together to determine the desaturation area (DA). Next, DDR was calculated using dividing DA by the 6-minute walk test distance (6MWD) (i.e., DA/6MWD). Results: When correlations of 6MWD and DDR with changes (Δ) in the severity of perceived dyspnea were examined, 6MWD did not significantly correlate with ΔBorg. Conversely, there was a significant correlation between the DDR and ΔBorg (r= 0.488, p=0.004). There were significant correlations between 6MWD and FVC % (r=0.370, p=0.034), and FEV1 % (r=0.465, p=0.006). However, DDR was significantly more correlated with FVC % (r= -0.621, p< 0.001), FEV1 % (r= -0.648, p< 0.001). Moreover, there was a significant correlation between DDR and DLCO % (r= -0.342, p=0.052). Conclusions: The findings of this study suggest that DDR is a promising and more useful parameter for assessing patients with IPF.
Confirmation of PSMA expression measured on [68Ga]Ga-PSMA PET/CT by immunohistochemistry in prostate adenocarcinoma.

BACKGROUND Our aim is to determine the accuracy of [68Ga]Ga-PSMA PET/CT in showing PSMA expression in primary prostate cancer and to investigate the relationship between SUVmax and immunohistochemical PSMA expression, Gleason score, and PSA value. MATERIAL AND METHODS We retrospectively analyzed 66 male patients who were diagnosed with primary prostate adenocarcinoma, underwent pre-treatment [68Ga]Ga-PSMA PET/CT examination for staging, and performed radical prostatectomy between March 2018-August 2020. Immunohistochemical staining was applied to the radical prostatectomy specimens of all patients to detect PSMA expression. The results were evaluated as an immunoreactive score (IRS) and a modified IRS was obtained. Gleason score groups and prostate-specific antigen (PSA) serum values of the patients were obtained from the patient files. RESULTS The high SUVmax of primary prostate tumors was significantly correlated with a high modified IRS score (score 2; 3), high PSA value, high Gleason score, and metastasis. In correlation analysis, a positive correlation was found between SUVmax and PSA value and modified IRS score (r = 0.69, p = 0.001; r = 0.39, p = 0.001). In addition, there was a statistically significant weak correlation between PSA serum concentration and modified IRS scores (r = 0.267; p = 0.03). In regression analysis, the percentage of positive cells had a statistically significant and increasing effect on SUVmax (p = 0.031; std beta = 0.268; 95% CI = 0.231-4.596). CONCLUSIONS In prostate adenocarcinoma, SUVmax of the primary tumor in [68Ga]Ga-PSMA PET/CT correlates with immunohistochemical PSMA expression. In addition, high SUVmax is associated with markers of poor prognoses, such as high PSMA expression, PSA value, and Gleason score.
The urine-to-plasma urea concentration ratio is associated with eGFR and eGFR decline over time in a population cohort

ABSTRACT Background Evaluation of renal function and of factors associated with its decline are important public health issues. Besides markers of glomerular function [e.g. glomerular filtration rate (GFR)], those of tubular functions are rarely evaluated. Urea, the most abundant urinary solute, is markedly concentrated in urine when compared with plasma. We explored the urine-to-plasma ratio of urea concentrations (U/P urea ratio) as a marker of tubular functions. Methods We evaluated the relationship of the U/P urea ratio with eGFR at baseline in 1043 participants (48 ± 17 years) from the Swiss Kidney Project on Genes in Hypertension (SKIPOGH) population-based cohort, using mixed regression. In 898 participants, we assessed the relation between U/P urea ratio and renal function decline between two study waves 3 years apart. We studied U/P ratios for osmolarity, Na, K and uric acid for comparison. Results In a transversal study at baseline, estimated GFR (eGFR) was positively associated with U/P-urea ratio [βscaled = 0.08, 95% CI (0.04; 0.13)] but not with the U/P ratio of osmolarity. Considering separately participants with renal function >90 or ≤90 mL/min × 1.73 m2, this association was observed only in those with reduced renal function. In the longitudinal study, eGFR declined at a mean rate of 1.2 mL/min per year. A significant association was observed between baseline U/P urea ratio and eGFR decline [βscaled = 0.08, 95% CI (0.01; 0.15)]. A lower baseline U/P urea ratio was associated with a greater eGFR decline. Conclusion This study provides evidence that the U/P urea ratio is an early marker of kidney function decline in the general adult population. Urea is easy to measure with well-standardized techniques and at low cost. Thus, the U/P urea ratio could become an easily available tubular marker for evaluating renal function decline.
How entanglements determine the morphology of semicrystalline polymers

Significance The majority of polymers used in the solid state as construction or packaging materials are semicrystalline. Their typical microscopic structure consists of nanoscopically thin yet stiff crystalline layers separated by rubbery amorphous layers. This specific morphology is responsible for the advantageous mechanical properties of these materials. Decisive parameters are the thicknesses of the crystalline and amorphous layers that together determine the crystallinity and the entanglement concentration in the amorphous layers. While the factors determining the crystal thickness are well investigated, there is a lack of understanding for the amorphous layers. Using a model polymer for which the entanglements are retained during crystallization, we show that their thickness is controlled by the entanglement concentration that attains a specific maximum value.
FMRP expression in primary breast tumor cells correlates with recurrence and specific site of metastasis

Breast cancer is the most common cancer among women worldwide. Molecular and clinical evidence indicated that Fragile X Messenger Ribonucleoprotein 1 (FMRP) plays a role in different types of cancer, including breast cancer. FMRP is an RNA binding protein that regulates the metabolism of a large group of mRNAs coding for proteins involved in both neural processes and in epithelial-mesenchymal transition, a pivotal mechanism that in cancer is associated to tumor progression, aggressiveness and chemoresistance. Here, we carried out a retrospective case-control study of 127 patients, to study the expression of FMRP and its correlation with metastasis formation in breast cancer. Consistent with previous findings, we found that FMRP levels are high in tumor tissue. Two categories have been analyzed, tumor with no metastases (referred as control tumors, 84 patients) and tumor with distant metastatic repetition, (referred as cases, 43 patients), with a follow-up of 7 years (mean). We found that FMRP levels were lower in both the nuclei and the cytoplasm in the cases compared to control tumors. Next, within the category cases (tumor with metastases) we evaluated FMRP expression in the specific sites of metastasis revealing a nuclear staining of FMRP. In addition, FMRP expression in both the nuclear and cytoplasmic compartment was significantly lower in patients who developed brain and bone metastases and higher in hepatic and pulmonary sites. While further studies are required to explore the underlying molecular mechanisms of FMRP expression and direct or inverse correlation with the secondary metastatic site, our findings suggest that FMRP levels might be considered a prognostic factor for site-specific metastasis.
Sensitivity of the 1D shallow water equations with source terms: Solution method for discontinuous flows

A finite volume‐based numerical technique is presented concerning the sensitivity of the solution of the one‐dimensional Shallow Water Equations with scalar transport. An approximate Riemann solver is proposed for direct sensitivity calculation even in the presence of discontinuous solutions. The Shallow Water Sensitivity Equations are first derived as well as the expressions of the sensitivity source terms, initial and boundary conditions. The numerical technique is then detailed and application examples are provided to assess the method's efficiency in estimating the sensitivity to different parameters (friction coefficient and initial and boundary conditions). The application of the dam‐break problem to a trapezoidal channel is also provided. The comparison with the analytical solution and the classical empirical approach illustrates the usefulness of the direct sensitivity calculation. Copyright © 2010 John Wiley & Sons, Ltd.
CT findings in “Post-Covid”: residua from acute pneumonia or “Post-Covid-ILD”?

The aim of this study was to evaluate if CT findings in patients with pulmonary Post Covid syndrome represent residua after acute pneumonia or if SARS-CoV 2 induces a true ILD. Consecutive patients with status post acute Covid-19 pneumonia and persisting pulmonary symptoms were enrolled. Inclusion criteria were availability of at least one chest CT performed in the acute phase and at least one chest CT performed at least 80 days after symptom onset. In both acute and chronic phase CTs 14 CT features as well as distribution and extent of opacifications were independently determined by two chest radiologists. Evolution of every single CT lesion over time was registered intraindividually for every patient. Moreover, lung abnormalities were automatically segmented using a pre-trained nnU-Net model and volume as well as density of parenchymal lesions were plotted over the entire course of disease including all available CTs. 29 patients (median age 59 years, IQR 8, 22 men) were enrolled. Follow-up period was 80-242 days (mean 134). 152/157 (97%) lesions in the chronic phase CTs represented residua of lung pathology in the acute phase. Subjective and objective evaluation of serial CTs showed that CT abnormalities were stable in location and continuously decreasing in extent and density. The results of our study support the hypothesis that CT abnormalities in the chronic phase after Covid-19 pneumonia represent residua in terms of prolonged healing of acute infection. We did not find any evidence for a Post Covid ILD.
Shape Parameterization and Optimization of a Two-Stroke Engine

We demonstrate a procedure for designing and optimizing the scavenging properties of a two-stroke engine. A method of surface design, known as the partial differential equation method, is used to represent the internal geometryoftheengine.Wethenrunsteady-statecomputationale uiddynamicscalculationstoassessthescavenging e ow inside the engine. To quantify the scavenging, the trapping efe ciency is used, and calculated values of this measure are obtained for different geometrical designs. We use a locally weighted regression-smoothing model to e t the data, and then we optimize the resulting response surface. The optimization captured two local minima, one of which corresponds to accepted manufacturing practice and the other one is a new and counter-intuitive way of scavenging the engine, having optimum scavenging characteristics. Nomenclature C = contour M = mass of air n = number of particles r0 = bore of the cylinder u, v = surface parametric coordinates V = volume of air X = vector of Cartesian coordinates of surface points Xn = normal derivative along the boundary x, y, z = Cartesian coordinates xsu = derivative parameter of the transfer port, in x direction, on C0 ysl = derivative parameter of the transfer port, in y direction, on C1 ysu = derivative parameter of the transfer port, in y direction, on C0 zsu = derivative parameter of the transfer port, in z direction, on C0 a = smoothing parameter q = density Subscripts s = supplied t = trapped 0, 1 = upper and lower surface boundaries, respectively
LncRNA NRON promotes tumorigenesis by enhancing MDM2 activity toward tumor suppressor substrates

The E3 ligase MDM2 promotes tumor growth and progression by inducing ubiquitin‐mediated degradation of P53 and other tumor‐suppressing proteins. Here, we identified an MDM2‐interacting lncRNA NRON, which promotes tumor formation by suppressing both P53‐dependent and independent pathways. NRON binds to MDM2 and MDMX (MDM4) via two different stem‐loops, respectively, and induces their heterogenous dimerization, thereby enhancing the E3 ligase activity of MDM2 toward its tumor‐suppressing substrates, including P53, RB1, and NFAT1. NRON knockdown dramatically inhibits tumor cell growth in vitro and in vivo. More importantly, NRON overexpression promotes oncogenic transformation by inducing anchorage‐independent growth in vitro and facilitating tumor formation in immunocompromised mice. Clinically, NRON expression is significantly associated with poor clinical outcome in breast cancer patients. Together, our data uncover a pivotal role of lncRNA that induces malignant transformation of epithelial cells by inhibiting multiple tumor suppressor proteins.
Organization of Cancer Specialists in US Physician Practices and Health Systems

PURPOSE To describe the supply of cancer specialists, the organization of cancer care within versus outside of health systems, and the distance to multispecialty cancer centers. METHODS Using the 2018 Health Systems and Provider Database from the National Bureau of Economic Research and 2018 Medicare data, we identified 46,341 unique physicians providing cancer care. We stratified physicians by discipline (adult/pediatric medical oncologists, radiation oncologists, surgical/gynecologic oncologists, other surgeons performing cancer surgeries, or palliative care physicians), system type (National Cancer Institute [NCI] Cancer Center system, non-NCI academic system, nonacademic system, or nonsystem/independent practice), practice size, and composition (single disciplinary oncology, multidisciplinary oncology, or multispecialty). We computed the density of cancer specialists by county and calculated distances to the nearest NCI Cancer Center. RESULTS More than half of all cancer specialists (57.8%) practiced in health systems, but 55.0% of cancer-related visits occurred in independent practices. Most system-based physicians were in large practices with more than 100 physicians, while those in independent practices were in smaller practices. Practices in NCI Cancer Center systems (95.2%), non-NCI academic systems (95.0%), and nonacademic systems (94.3%) were primarily multispecialty, while fewer independent practices (44.8%) were. Cancer specialist density was sparse in many rural areas, where the median travel distance to an NCI Cancer Center was 98.7 miles. Distances to NCI Cancer Centers were shorter for individuals living in high-income areas than in low-income areas, even for individuals in suburban and urban areas. CONCLUSION Although many cancer specialists practiced in multispecialty health systems, many also worked in smaller-sized independent practices where most patients were treated. Access to cancer specialists and cancer centers was limited in many areas, particularly in rural and low-income areas.
A phase 3b, multicenter, open‐label, single‐arm study of roxadustat (ASPEN): Operational learnings within United States dialysis organizations

Roxadustat is an oral hypoxia‐inducible factor prolyl hydroxylase inhibitor approved in several regions for the treatment of anemia of chronic kidney disease (CKD). ASPEN evaluated the efficacy, safety, and feasibility of roxadustat in patients with anemia of CKD in US dialysis organizations.
The evolution of drop spectra due to condensation, coalescence and breakup

Abstract A numerical model of warm rain processes incorporating activation of cloud condensation nuclei, drop growth by condensation and stochastic coalescence, and drop breakup is described. A collisional breakup model is compared to a spontaneous disintegration model and found not only to dominate over the spontaneous disintegration model but to produce an exponential spectrum in fair agreement with average observed drop spectra. The steady-state spectrum was found to be quite insensitive to the number of satellite drops farmed by collision or their size distribution. The effect of the finite-difference solution to the collection and breakup equations is analysed. A properly stochastic formulation for finite time steps is presented but found to differ only slightly from the simpler, “discrete” formulation. Time stops of 5 s and 45 size categories are found adequate to describe the essential quantitative features of more intensive treatments. The model results were found to be somewhat sensitive to value.
Chasing iron bioavailability in the Southern Ocean: Insights from Phaeocystis antarctica and iron speciation

Dissolved iron (dFe) availability limits the uptake of atmospheric CO2 by the Southern Ocean (SO) biological pump. Hence, any change in bioavailable dFe in this region can directly influence climate. On the basis of Fe uptake experiments with Phaeocystis antarctica, we show that the range of dFe bioavailability in natural samples is wider (<1 to ~200% compared to free inorganic Fe′) than previously thought, with higher bioavailability found near glacial sources. The degree of bioavailability varied regardless of in situ dFe concentration and depth, challenging the consensus that sole dFe concentrations can be used to predict Fe uptake in modeling studies. Further, our data suggest a disproportionately major role of biologically mediated ligands and encourage revisiting the role of humic substances in influencing marine Fe biogeochemical cycling in the SO. Last, we describe a linkage between in situ dFe bioavailability and isotopic signatures that, we anticipate, will stimulate future research.
MooseNet: A Trainable Metric for Synthesized Speech with a PLDA Module

We present MooseNet, a trainable speech metric that predicts the listeners' Mean Opinion Score (MOS). We propose a novel approach where the Probabilistic Linear Discriminative Analysis (PLDA) generative model is used on top of an embedding obtained from a self-supervised learning (SSL) neural network (NN) model. We show that PLDA works well with a non-finetuned SSL model when trained only on 136 utterances (ca. one minute training time) and that PLDA consistently improves various neural MOS prediction models, even state-of-the-art models with task-specific fine-tuning. Our ablation study shows PLDA training superiority over SSL model fine-tuning in a low-resource scenario. We also improve SSL model fine-tuning using a convenient optimizer choice and additional contrastive and multi-task training objectives. The fine-tuned MooseNet NN with the PLDA module achieves the best results, surpassing the SSL baseline on the VoiceMOS Challenge data.
Defending Black-box Classifiers by Bayesian Boundary Correction

Classifiers based on deep neural networks have been recently challenged by Adversarial Attack, where the widely existing vulnerability has invoked the research in defending them from potential threats. Given a vulnerable classifier, existing defense methods are mostly white-box and often require re-training the victim under modified loss functions/training regimes. While the model/data/training specifics of the victim are usually unavailable to the user, re-training is unappealing, if not impossible for reasons such as limited computational resources. To this end, we propose a new black-box defense framework. It can turn any pre-trained classifier into a resilient one with little knowledge of the model specifics. This is achieved by new joint Bayesian treatments on the clean data, the adversarial examples and the classifier, for maximizing their joint probability. It is further equipped with a new post-train strategy which keeps the victim intact. We name our framework Bayesian Boundary Correction (BBC). BBC is a general and flexible framework that can easily adapt to different data types. We instantiate BBC for image classification and skeleton-based human activity recognition, for both static and dynamic data. Exhaustive evaluation shows that BBC has superior robustness and can enhance robustness without severely hurting the clean accuracy, compared with existing defense methods.
Periodically and quasiperiodically driven-anisotropic Dicke model

We analyze the anisotropic Dicke model in the presence of a periodic drive and under a quasiperiodic drive. The study of drive-induced phenomena in this experimentally accesible model is important since although it is simpler than full-fledged many-body quantum systems, it is still rich enough to exhibit many interesting features. We show that under a quasiperiodic Fibonacci (Thue-Morse) drive, the system features a prethermal plateau that increases as an exponential (stretched exponential) with the driving frequency before heating to an infinite-temperature state. In contrast, when the model is periodically driven, the dynamics reaches a plateau that is not followed by heating. In either case, the plateau value depends on the energy of the initial state and on the parameters of the undriven Hamiltonian. Surprisingly, this value does not always approach the infinite-temperature state monotonically as the frequency of the periodic drive decreases. We also show how the drive modifies the quantum critical point and discuss open questions associated with the analysis of level statistics at intermediate frequencies.
Building Trust Profiles in Conditionally Automated Driving

Trust is crucial for ensuring the safety, security, and widespread adoption of automated vehicles (AVs), and if trust is lacking, drivers and the public may not be willing to use them. This research seeks to investigate trust profiles in order to create personalized experiences for drivers in AVs. This technique helps in better understanding drivers' dynamic trust from a persona's perspective. The study was conducted in a driving simulator where participants were requested to take over control from automated driving in three conditions that included a control condition, a false alarm condition, and a miss condition with eight takeover requests (TORs) in different scenarios. Drivers' dispositional trust, initial learned trust, dynamic trust, personality, and emotions were measured. We identified three trust profiles (i.e., believers, oscillators, and disbelievers) using a K-means clustering model. In order to validate this model, we built a multinomial logistic regression model based on SHAP explainer that selected the most important features to predict the trust profiles with an F1-score of 0.90 and accuracy of 0.89. We also discussed how different individual factors influenced trust profiles which helped us understand trust dynamics better from a persona's perspective. Our findings have important implications for designing a personalized in-vehicle trust monitoring and calibrating system to adjust drivers' trust levels in order to improve safety and experience in automated driving.