Miracle-dz/UniFAR-FTUs huggingface dataset:
Machine learning-based prediction of cerebral hemorrhage in patients with hemodialysis: A multicenter, retrospective study

Background Intracerebral hemorrhage (ICH) is one of the most serious complications in patients with chronic kidney disease undergoing long-term hemodialysis. It has high mortality and disability rates and imposes a serious economic burden on the patient's family and society. An early prediction of ICH is essential for timely intervention and improving prognosis. This study aims to build an interpretable machine learning-based model to predict the risk of ICH in patients undergoing hemodialysis. Methods The clinical data of 393 patients with end-stage kidney disease undergoing hemodialysis at three different centers between August 2014 and August 2022 were retrospectively analyzed. A total of 70% of the samples were randomly selected as the training set, and the remaining 30% were used as the validation set. Five machine learning (ML) algorithms, namely, support vector machine (SVM), extreme gradient boosting (XGB), complement Naïve Bayes (CNB), K-nearest neighbor (KNN), and logistic regression (LR), were used to develop a model to predict the risk of ICH in patients with uremia undergoing long-term hemodialysis. In addition, the area under the curve (AUC) values were evaluated to compare the performance of each algorithmic model. Global and individual interpretive analyses of the model were performed using importance ranking and Shapley additive explanations (SHAP) in the training set. Results A total of 73 patients undergoing hemodialysis developed spontaneous ICH among the 393 patients included in the study. The AUC of SVM, CNB, KNN, LR, and XGB models in the validation dataset were 0.725 (95% CI: 0.610 ~ 0.841), 0.797 (95% CI: 0.690 ~ 0.905), 0.675 (95% CI: 0.560 ~ 0.789), 0.922 (95% CI: 0.862 ~ 0.981), and 0.979 (95% CI: 0.953 ~ 1.000), respectively. Therefore, the XGBoost model had the best performance among the five algorithms. SHAP analysis revealed that the levels of LDL, HDL, CRP, and HGB and pre-hemodialysis blood pressure were the most important factors. Conclusion The XGB model developed in this study can efficiently predict the risk of a cerebral hemorrhage in patients with uremia undergoing long-term hemodialysis and can help clinicians to make more individualized and rational clinical decisions. ICH events in patients undergoing maintenance hemodialysis (MHD) are associated with serum LDL, HDL, CRP, HGB, and pre-hemodialysis SBP levels.
Severe acute respiratory syndrome coronavirus-2 accessory proteins ORF3a and ORF7a modulate autophagic flux and Ca2+ homeostasis in yeast

Virus infection involves the manipulation of key host cell functions by specialized virulence proteins. The Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) small accessory proteins ORF3a and ORF7a have been implicated in favoring virus replication and spreading by inhibiting the autophagic flux within the host cell. Here, we apply yeast models to gain insights into the physiological functions of both SARS-CoV-2 small open reading frames (ORFs). ORF3a and ORF7a can be stably overexpressed in yeast cells, producing a decrease in cellular fitness. Both proteins show a distinguishable intracellular localization. ORF3a localizes to the vacuolar membrane, whereas ORF7a targets the endoplasmic reticulum. Overexpression of ORF3a and ORF7a leads to the accumulation of Atg8 specific autophagosomes. However, the underlying mechanism is different for each viral protein as assessed by the quantification of the autophagic degradation of Atg8-GFP fusion proteins, which is inhibited by ORF3a and stimulated by ORF7a. Overexpression of both SARS-CoV-2 ORFs decreases cellular fitness upon starvation conditions, where autophagic processes become essential. These data confirm previous findings on SARS-CoV-2 ORF3a and ORF7a manipulating autophagic flux in mammalian cell models and are in agreement with a model where both small ORFs have synergistic functions in stimulating intracellular autophagosome accumulation, ORF3a by inhibiting autophagosome processing at the vacuole and ORF7a by promoting autophagosome formation at the ER. ORF3a has an additional function in Ca2+ homeostasis. The overexpression of ORF3a confers calcineurin-dependent Ca2+ tolerance and activates a Ca2+ sensitive FKS2-luciferase reporter, suggesting a possible ORF3a-mediated Ca2+ efflux from the vacuole. Taken together, we show that viral accessory proteins can be functionally investigated in yeast cells and that SARS-CoV-2 ORF3a and ORF7a proteins interfere with autophagosome formation and processing as well as with Ca2+ homeostasis from distinct cellular targets.
Factors influencing bioequivalence evaluation of insulin biosimilars based on a structural equation model

Objective: This study aimed to explore the factors affecting the bioequivalence of test and reference insulin preparations so as to provide a scientific basis for the consistency evaluation of the quality and efficacy of insulin biosimilars. Methods: A randomized, open, two-sequence, single-dose, crossover design was used in this study. Subjects were randomly divided into TR or RT groups in equal proportion. The glucose infusion rate and blood glucose were measured by a 24-h glucose clamp test to evaluate the pharmacodynamic parameters of the preparation. The plasma insulin concentration was determined by liquid chromatography–mass spectrometry (LC-MS/MS) to evaluate pharmacokinetic parameters. WinNonlin 8.1 and SPSS 23.0 were applied for PK/PD parameter calculation and statistical analysis. The structural equation model (SEM) was constructed to analyze the influencing factors of bioequivalence by using Amos 24.0. Results: A total of 177 healthy male subjects aged 18–45 years were analyzed. Subjects were assigned to the equivalent group (N = 55) and the non-equivalent group (N = 122) by bioequivalence results, according to the EMA guideline. Univariate analysis showed statistical differences in albumin, creatinine, Tmax, bioactive substance content, and adverse events between the two groups. In the structural equation model, adverse events (β = 0.342; p < 0.001) and bioactive substance content (β = −0.189; p = 0.007) had significant impacts on the bioequivalence of two preparations, and the bioactive substance content significantly affected adverse events (β = 0.200; p = 0.007). Conclusion: A multivariate statistical model was used to explore the influencing factors for the bioequivalence of two preparations. According to the result of the structural equation model, we proposed that adverse events and bioactive substance content should be optimized for consistency evaluation of the quality and efficacy of insulin biosimilars. Furthermore, bioequivalence trials of insulin biosimilars should strictly obey inclusion and exclusion criteria to ensure the consistency of subjects and avoid confounding factors affecting the equivalence evaluation.
Assessment of Acute Rejection in a Lung Transplant Recipient Using a Sentinel Skin Flap

Division of Plastic and Reconstructive Surgery, Department of Surgery, University Healthy Network, Toronto, ON, Canada, Division of Medicine, Division of Respirology, University Healthy Network, Toronto, ON, Canada, Department of Dermatology, University Healthy Network, Toronto, ON, Canada, Department of Pathology, University Healthy Network, Toronto, ON, Canada, Division of Thoracic Surgery, Department of Surgery, University Healthy Network, Toronto, ON, Canada
Towards a New 3Rs Era in the construction of 3D cell culture models simulating tumor microenvironment

Three-dimensional cell culture technology (3DCC) sits between two-dimensional cell culture (2DCC) and animal models and is widely used in oncology research. Compared to 2DCC, 3DCC allows cells to grow in a three-dimensional space, better simulating the in vivo growth environment of tumors, including hypoxia, nutrient concentration gradients, micro angiogenesis mimicism, and the interaction between tumor cells and the tumor microenvironment matrix. 3DCC has unparalleled advantages when compared to animal models, being more controllable, operable, and convenient. This review summarizes the comparison between 2DCC and 3DCC, as well as recent advances in different methods to obtain 3D models and their respective advantages and disadvantages.
Synthetic oleanane triterpenoids suppress MYB oncogene activity and sensitize T-cell acute lymphoblastic leukemia cells to chemotherapy

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematologic malignancy with poor prognosis. The MYB oncogene encodes a master transcription factor that is activated in the majority of human T-ALLs. In the present study, we have performed a large-scale screening with small-molecule drugs to find clinically useful inhibitors of MYB gene expression in T-ALL. We identified several pharmacological agents that potentially could be used to treat MYB-driven malignancies. In particular, treatment with the synthetic oleanane triterpenoids (OTs) bardoxolone methyl and omaveloxolone decreased MYB gene activity and expression of MYB downstream target genes in T-ALL cells with constitutive MYB gene activation. Notably, treatment with bardoxolone methyl and omaveloxolone led to a dose-dependent reduction in cell viability and induction of apoptosis at low nanomolar concentrations. In contrast, normal bone marrow-derived cells were unaffected at these concentrations. Bardoxolone methyl and omaveloxolone treatment downregulated the expression of DNA repair genes and sensitized T-ALL cells to doxorubicin, a drug that is part of the standard therapy of T-ALL. OT treatment may thus potentiate DNA-damaging chemotherapy through attenuation of DNA repair. Taken together, our results indicate that synthetic OTs may be useful in the treatment of T-ALL and potentially also in other MYB-driven malignancies.
Addressing maternal medication use during breastfeeding using clinical resources and a novel physiologically based pharmacokinetic model-derived metric: A qualitative study

Introduction Breastfeeding has major benefits to the maternal-infant dyad and yet healthcare providers have expressed uncertainty about advocating breastfeeding when mothers are taking medications. The tendency for some providers to be more cautious in their advising approach is likely a consequence of limited, unfamiliar, and unreliable existing information on medication use during lactation. A novel risk metric termed the Upper Area Under the Curve Ratio (UAR) was developed to overcome existing resource shortcomings. However, the perception and use of the UAR in practice by providers is not known. The aim of this study was to understand existing resource use and potential UAR use in practice, their advantages and disadvantages, and areas of improvement for the UAR. Methods Healthcare providers mainly practicing in California with experience advising on medication use during lactation were recruited. One-on-one semi-structured interviews that included questions on current practices when advising medication use during breastfeeding, and approaches to a given a scenario with and without information about the UAR were conducted. The Framework Method was applied for data analysis to construct themes and codes. Results Twenty-eight providers representing multiple professions and disciplines were interviewed. Six main themes emerged: (1) Current Practice Approaches, (2) Advantages of Existing Resources, (3) Disadvantages of Existing Resources, (4) Advantages of the UAR, (5) Disadvantages of the UAR, and (6) Strategies to Improve the UAR. Overall, 108 codes were identified that illustrated theme topics ranging from a general lack of metric use to the realities of advising. A workflow describing current practice approaches connected all other themes. Almost all disadvantages of existing resources could be overcome by advantages of other resources and the UAR. Several improvements to the UAR were identified to address its shortcomings. Conclusion Through interviews with providers who use resources to advise on medication use during breastfeeding, an improved understanding of current practice approaches and accessed resources was ascertained. Ultimately, it was found that the UAR would confer multiple benefits over existing resources, and improvements of the UAR were identified. Future work should focus on implementing the suggested recommendations to ensure optimal uptake of the UAR to improve advising practices.
Genome-edited HEADING DATE 3a knockout enhances leaf production in Perilla frutescens

Environmental cues regulate the transition of many plants from vegetative to flowering development. Day length, or photoperiod, is one cue that synchronizes flowering by changing seasons. Consequently, the molecular mechanism of flowering control is prominent in Arabidopsis and rice, where essential genes like FLOWERING LOCUS T (FT) homolog, HEADING DATE 3a (Hd3a), have been connected to flowering regulation. Perilla is a nutrient-rich leaf vegetable, and the flowering mechanism remains largely elusive. We identified flowering-related genes under short-day conditions using RNA sequencing to develop an enhanced leaf production trait using the flowering mechanism in the perilla. Initially, an Hd3a-like gene was cloned from the perilla and defined as PfHd3a. Furthermore, PfHd3a is highly rhythmically expressed in mature leaves under short-day and long-day conditions. Ectopic expression of PfHd3a in Atft-1 mutant plants has been shown to complement Arabidopsis FT function, resulting in early flowering. In addition, our genetic approaches revealed that overexpression of PfHd3a in perilla caused early flowering. In contrast, the CRISPR/Cas9 generated PfHd3a-mutant perilla showed significantly late flowering, resulting in approximately 50% leaf production enhancement compared to the control. Our results suggest that PfHd3a plays a vital role in regulating flowering in the perilla and is a potential target for molecular breeding in the perilla.
Numerical analysis of partial differential equations on evolving surfaces

This dissertation addresses the numerical study of full discretization methods for linear parabolic equations as well as wave equations on evolving surfaces. It is the first work able to give rigorous proofs concerning error bounds for numerical schemes on evolving surfaces with time integrators of order two and higher. We believe that the developed analytical tools and achieved results in this thesis can be applied or extended to more complicated linear or nonlinear partial differential equations on or of surfaces. In the first part of this thesis, two fully discrete schemes for a linear parabolic equation on evolving surfaces are studied. The spatial discretization is realized with the evolving surface finite element method. This leads to a system of ordinary differential equations involving time dependent mass and stiffness matrices. For these matrices, basic but nevertheless important estimates are proven in order to study the stability of the time discretization schemes in an abstract framework. Two different methods are considered, namely, the implicit Runge–Kutta method, and the backward difference formulas (BDF). For algebraically stable and stiffly accurate implicit Runge–Kutta methods such as Radau IIA, the unconditional stability in the matrix-vector formulation is proven. In the same framework, using results from Dahlquist’s G-stability theory and Nevanlinna–Odeh’s multiplier technique together with the properties of the spatial semi-discretization, unconditional stability for the BDF methods up to order five is shown. These stability results, combined with an appropriately chosen Ritz projection and estimates arising from the approximation of the geometry, enable us to derive optimal-order error estimates for the fully discrete schemes. Numerical experiments are presented to confirm the theoretical results. In the second part, a linear wave equation on evolving surfaces is derived by using Hamilton’s principle of stationary action. This variational principle is first discretized in space by piecewise linear evolving surface finite elements. For the time discretization, two variational integrators – a version of the leapfrog or Stormer-Verlet method and Gaus– Runge–Kutta (GRK) methods – are studied. Working on the matrix-vector level, stability estimates for the leapfrog scheme are shown under the same Courant–Friedrichs–Lewy (CFL) condition which would be required for a fixed surface. Concerning the GRK method, its algebraic stability and coercivity property are joined with basic estimates for the evolving mass and stiffness matrices in order to prove unconditional stability for this time discretization scheme. As in the first part, the thus obtained stability results are strong enough to yield convergence of the fully discrete methods in the natural time-dependent norms. It is worth noticing that in order to obtain optimal-order error estimates, the Ritz
Early Postnatal Home Visit Coverage by Health Extension Workers and Associated Factors Among Postpartum Women in Gidan District, Northeast Ethiopia

Objectives: To determine the coverage and associated factors of early postnatal home visits (PNHVs) by health extension workers (HEWs) among postpartum women in Gidan district, Northeast Ethiopia. Methods: A community-based, cross-sectional study was conducted between 30 March and 29 April 2021 in the Gidan district, Northeast Ethiopia. A multistage sampling technique was employed to select 767 postpartum women participants. Interviewer-administered questionnaires were used to collect the data. A binary logistic regression model was fitted to identify factors associated with early PNHVs by HEWs. Results: The coverage of early postnatal home visits was 15.13% [95% confidence interval (CI): 12.75, 17.87]. Women’s education, institutional delivery, time to reach health posts, and participation in pregnant women forums were significantly associated with early PNHVs by HEWs. Conclusion: In the current study, the coverage of early postnatal home visits by HEWs remains low in the study area. The concerned bodies should consider interventions that promote women’s education and institutional delivery, and more efforts should be made to improve community-based participation and links with HEWs.
On comparing coherent systems with heterogeneous components

Abstract In this paper we investigate different methods that may be used to compare coherent systems having heterogeneous components. We consider both the case of systems with independent components and the case of systems with dependent components. In the first case, the comparisons are based on the new concept of the survival signature due to Coolen and Coolen-Maturi (2012) which extends the well-known concept of system signatures to the case of components with lifetimes that need not be independent and identically distributed. In the second case, the comparisons are based on the concept of distortion functions. A graphical procedure (called an RR-plot) is proposed as an alternative to the analytical methods when there are two types of components.
Visualization Of Ultrasonic CavitationIn Visible And IR Spectra

Ultrasonic cavitation was generated with ultrasound of 33 kHz in a small closed water tank, containing about one liter of water. Cavitation was experimentally observed simultaneously with high-speed cameras in IR and visible spectra. Cameras were capturing images of the same observation area. From the images obtained time-dependent velocity fields were calculated for both cameras. Velocity calculation was based on pattern and similitude recognition between pairs of consecutive images. Images from the visible spectrum were also processed in order to detect the individual graphical objects presumably linked with cavitation collapses. As a result, correlations between velocity fields from each camera and correlations between velocity fields and cavitation collapses were determined. Strong correlations were found in all cases. Additionally, a delay was found for the velocities from the camera in the visible spectrum when compared to the thermographic results. Also the behavior of the correlation between cavitation collapses and velocities was in some cases found to be dependent on whether the velocities were from the images taken in the visible or the IR spectrum.
Stability Analysis of Heston Characteristic Function with Optimal Volatility Parameters

Heston volatility model has received a growing attention amongst academics and practitioners for derivative pricing applications. Yet, the sensibility of the model parameters and instabilities of its analytic characteristic function for large derivatives and complex derivations make the model inconsistent and unreliable. As these parameters and function are defined and used in the complex plane, they potentially include ‘branching’. Therefore, additional parameter restrictions are required. This paper aims at providing insight on the sensitivity of the model parameterization and establishing an algorithm to ensure the stability of the analytic characteristic function under full dimensional and unrestricted parameter space.
Nonlinear Model of the Origin of Endogenous Alternating Electromagnetic Fields and Selfregulation of Metabolic Processes in Biosystems

Electrosolitons that provide charge transport in biological systems (e.g., in respiratory processes) create alternating electromagnetic fields having a characteristic frequency. This frequency is determined by the soliton velocity and is in the microwave range. Because of this radiation the long‐range interaction of solitons results in the synchronization of their motion. This effect can contribute to the self‐regulation of metabolic processes in an organism. In addition, such regulation can be stimulated by external radiation with the same characteristic frequency, thus providing one mechanism to explain microwave resonant therapy.
Investigation on Mechanisms of Polymer Enhanced Oil Recovery by Nuclear Magnetic Resonance and Microscopic Theoretical Analysis

Polymer flooding is an efficient technique to enhance oil recovery over water flooding. There are lots of discussions regarding the mechanisms for polymer flooding enhancing oil recovery. The main focus is whether polymer flooding can increase sweep efficiency alone, or can increase both of sweep efficiency and displacement efficiency. We present a study on this problem. Oil displacement experiments on 4 natural cores show that polymer flooding can increase oil recovery efficiency by more than 12% over water. Moreover, photos are taken by the nuclear magnetic resonance (NMR) method both after water flooding and after polymer flooding, which show remaining oil saturation distribution at the middle cross section and the central longitudinal section. Analyses of these photos demonstrate that polymer flooding can increase both sweep efficiency and displacement efficiency.
Use of nonparametric regression methods for developing a local stem form model.

A local mean stem curve of spruce was represented using regression splines. Abilities of smoothing spline and P-spline to model the mean stem curve were evaluated using data of 85 carefully measured stems of Norway spruce. For both techniques the optimal amount of smoothing was investigated in dependence on the number of training stems using a cross-validation method. Representatives of main groups of parametric models - single models, segmented models and models with variable coefficient - were compared with spline models using five statistic criteria. Both regression splines performed comparably or better as all representatives of parametric models independently of the numbers of stems used as training data.