Miracle-dz/UniFAR-FTUs huggingface dataset:
Designing phase I oncology dose escalation using dose–exposure–toxicity models as a complementary approach to model‐based dose–toxicity models

One of the objectives of oncology phase I dose‐escalation studies has been to determine the maximum tolerated dose (MTD). Although MTD is no longer set as the dose for further development in contemporary oncology drug development, MTD determination is still important for informing the therapeutic index. Bayesian adaptive model‐based designs are becoming mainstream in oncology first‐in‐human trials. Herein, we illustrate via simulations the use of systemic exposure in Bayesian adaptive dose–toxicity models to estimate MTD. We extend traditional dose–toxicity models to incorporate pharmacokinetic exposure, which provides information on exposure–toxicity relationships. We pursue dose escalation until the maximum tolerated exposure (corresponding to the MTD) is reached. By leveraging pharmacokinetics, dose escalation considers exposure and interindividual variability on a continuous rather than discrete domain, offering additional information for dose‐escalation decisions. To demonstrate this, we generated 1000 simulations (starting dose of 1/25th the reference dose and six dose levels) for several different scenarios. Both rule‐based and model‐based designs were compared using metrics of potential safety, accuracy, and reliability. The mean results over simulations and different toxicity scenarios showed that model‐based designs were better than rule‐based methods and that exposure–toxicity model‐based methods have the potential to valuably complement dose–toxicity model‐based methods. Exposure–toxicity model‐based methods had decreased underdose risk accompanied by a relatively smaller increase in overdose risk, resulting in improved net reliability. MTD estimation accuracy was compromised when exposure variability was large, emphasizing the importance of appropriate control of pharmacokinetic variability in phase I dose‐escalation studies.
Preoperative function‐specific connectome analysis predicts surgery‐related aphasia after glioma resection

Glioma resection within language‐eloquent regions poses a high risk of surgery‐related aphasia (SRA). Preoperative functional mapping by navigated transcranial magnetic stimulation (nTMS) combined with diffusion tensor imaging (DTI) is increasingly used to localize cortical and subcortical language‐eloquent areas. This study enrolled 60 nonaphasic patients with left hemispheric perisylvian gliomas to investigate the prediction of SRA based on function‐specific connectome network properties under different fractional anisotropy (FA) thresholds. Moreover, we applied a machine learning model for training and cross‐validation to predict SRA based on preoperative connectome parameters. Preoperative connectome analysis helps predict SRA development with an accuracy of 73.3% and sensitivity of 78.3%. The current study provides a new perspective of combining nTMS and function‐specific connectome analysis applied in a machine learning model to investigate language in neurooncological patients and promises to advance our understanding of the intricate networks.
Numerical experiments for a mechanics of materials course

In recent years, the increased exposure to computers have made it possible for students to: 1) solve more complex problems; and 2) gain additional insight into the fundamentals through numerical experimentation and visualization. This paper is devoted to the analysis of strains, stresses and deformation of some structural members through such experimentation. The numerical experiments reported here will introduce students to the importance of boundary conditions, force equilibrium conditions, the stress/strain relationship for a given material, axial loading, stress concentration, pure bending, transverse loading and combined loading. ANSYS and parametric programming are used to set up these experiments.
The active form of Helicobacter pylori vacuolating cytotoxin induces decay‐accelerating factor CD55 in association with intestinal metaplasia in the human gastric mucosa

High‐level expression of decay‐accelerating factor, CD55, has previously been found in human gastric cancer (GC) and intestinal metaplasia (IM) tissues. Therapeutic effects of CD55 inhibition in cancer have been reported. However, the role of Helicobacter pylori infection and virulence factors in the induction of CD55 and its association with histological changes of the human gastric mucosa remain incompletely understood. We hypothesised that CD55 would be increased during infection with more virulent strains of H. pylori, and with more marked gastric mucosal pathology. RT‐qPCR and immunohistochemical analyses of gastric biopsy samples from 42 H. pylori‐infected and 42 uninfected patients revealed that CD55 mRNA and protein were significantly higher in the gastric antrum of H. pylori‐infected patients, and this was associated with the presence of IM, but not atrophy, or inflammation. Increased gastric CD55 and IM were both linked with colonisation by vacA i1‐type strains independently of cagA status, and in vitro studies using isogenic mutants of vacA confirmed the ability of VacA to induce CD55 and sCD55 in gastric epithelial cell lines. siRNA experiments to investigate the function of H. pylori‐induced CD55 showed that CD55 knockdown in gastric epithelial cells partially reduced IL‐8 secretion in response to H. pylori, but this was not due to modulation of bacterial adhesion or cytotoxicity. Finally, plasma samples taken from the same patients were analysed for the soluble form of CD55 (sCD55) by ELISA. sCD55 levels were not influenced by IM and did not correlate with gastric CD55 mRNA levels. These results suggest a new link between active vacA i1‐type H. pylori, IM, and CD55, and identify CD55 as a molecule of potential interest in the management of IM as well as GC treatment. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
DDCNN: A Deep Learning Model for AF Detection From a Single-Lead Short ECG Signal

With the popularity of the wireless body sensor network, real-time and continuous collection of single-lead electrocardiogram (ECG) data becomes possible in a convenient way. Data mining from the collected single-lead ECG waves has therefore aroused extensive attention worldwide, where early detection of atrial fibrillation (AF) is a hot research topic. In this paper, a two-channel convolutional neural network combined with a data augmentation method is proposed to detect AF from single-lead short ECG recordings. It consists of three modules, the first module denoises the raw ECG signals and produces 9-s ECG signals and heart rate (HR) values. Then, the ECG signals and HR rate values are fed into the convolutional layers for feature extraction, followed by three fully connected layers to perform the classification. The data augmentation method is used to generate synthetic signals to enlarge the training set and increase the diversity of the single-lead ECG signals. Validation experiments and the comparison with state-of-the-art studies demonstrate the effectiveness and advantages of the proposed method.
Ethanol Production from Cassava Pulp by a Newly Isolated Thermotolerant Pichia kudriavzevii LC375240

A total of 500 thermotolerant fermenting yeast isolates (100 from palm-wine and 400 from spoilt fruits) were screened for ethanol production at high temperatures. The best isolate that produced up to 4% ethanol from 10% glucose at 45°C was selected for further experiments. The optimum pH for ethanol production by the isolate was pH 6 at both 30°C and 42°C. The isolate was identified as Pichia kudriavzevii base on the 18s ribosomal DNA. Ethanol production from 200 g/L cassava pulp using Simultaneous Saccharification and Fermentation (SSF) method at 30°C and 42°C by the isolate was investigated. At 30°C, an ethanol concentration of 30 g/L was produced. This represents an ethanol yield of 0.15 g/g of cassava pulp and 58.8% of the theoretical yield. However at 42°C, the concentration of ethanol produced increased to 42 g/L representing an ethanol yield of 0.21 g/g of cassava pulp and 82.4% of the theoretical yield. The isolate produced slightly higher ethanol than the two typed strains NCYC 587 and NCYC 2791 at 42°C. This isolate has a good potential to be used for commercial bioethanol production since it can produce ethanol at 45°C without a significant drop in ethanol yield.
Microkinetic Analysis of the Oxygen Evolution Performance at Different Stages of Iridium Oxide Degradation

The microkinetics of the electrocatalytic oxygen evolution reaction substantially determines the performance in proton-exchange membrane water electrolysis. State-of-the-art nanoparticulated rutile IrO2 electrocatalysts present an excellent trade-off between activity and stability due to the efficient formation of intermediate surface species. To reveal and analyze the interaction of individual surface processes, a detailed dynamic microkinetic model approach is established and validated using cyclic voltammetry. We show that the interaction of three different processes, which are the adsorption of water, one potential-driven deprotonation step, and the detachment of oxygen, limits the overall reaction turnover. During the reaction, the active IrO2 surface is covered mainly by *O, *OOH, and *OO adsorbed species with a share dependent on the applied potential and of 44, 28, and 20% at an overpotential of 350 mV, respectively. In contrast to state-of-the-art calculations of ideal catalyst surfaces, this novel model-based methodology allows for experimental identification of the microkinetics as well as thermodynamic energy values of real pristine and degraded nanoparticles. We show that the loss in electrocatalytic activity during degradation is correlated to an increase in the activation energy of deprotonation processes, whereas reaction energies were marginally affected. As the effect of electrolyte-related parameters does not cause such a decrease, the model-based analysis demonstrates that material changes trigger the performance loss. These insights into the degradation of IrO2 and its effect on the surface processes provide the basis for a deeper understanding of degrading active sites for the optimization of the oxygen evolution performance.
Gut Microbiota in Monozygotic Twins Discordant for Parkinson's Disease

Differences in gut microbiota between Parkinson's disease patients and controls seem to depend on multiple—frequently unmeasured—confounders. Monozygotic twins offer a unique model for controlling several factors responsible for interpersonal variation in gut microbiota. Fecal samples from 20 monozygotic twin pairs (n = 40) discordant for Parkinson's disease were studied (metagenomic shotgun analysis). Paired data analysis detected minimal differences in bacterial taxa abundance at species level (Bacteroides pectinophilus [p = 0.037], Bifidobacterium pseudocatenulatum [p = 0.050], and Bifidobacterium catenulatum [p = 0.025]) and in predicted metabolic pathways (primary bile acid biosynthesis [p = 0.037]). Additional studies are warranted to understand the role of gut microbiota in the pathogenesis of Parkinson's disease. ANN NEUROL 2022;92:631–636
Lifestyle behaviour in adolescence and musculoskeletal pain 11 years later: The Trøndelag Health Study

There is limited knowledge on the association between lifestyle behaviour in adolescence and musculoskeletal pain in young adulthood. This study aimed to investigate whether an accumulation of adverse lifestyle behaviours in adolescents with and without musculoskeletal pain at baseline, was associated with persistent musculoskeletal pain (pain duration ≥3 consecutive months the last year) 11 years later.
Interplay of surface interaction and magnetic torque in single-cell motion of magnetotactic bacteria in microfluidic confinement

Swimming microorganisms often experience complex environments in their natural habitat. The same is true for microswimmers in envisioned biomedical applications. The simple aqueous conditions typically studied in the lab differ strongly from those found in these environments and often exclude the effects of small volume confinement or the influence that external fields have on their motion. In this work, we investigate magnetically steerable microswimmers, specifically magnetotactic bacteria, in strong spatial confinement and under the influence of an external magnetic field. We trap single cells in micrometer-sized microfluidic chambers and track and analyze their motion, which shows a variety of different trajectories, depending on the chamber size and the strength of the magnetic field. Combining these experimental observations with simulations using a variant of an active Brownian particle model, we explain the variety of trajectories by the interplay between the wall interactions and the magnetic torque. We also analyze the pronounced cell-to-cell heterogeneity, which makes single-cell tracking essential for an understanding of the motility patterns. In this way, our work establishes a basis for the analysis and prediction of microswimmer motility in more complex environments.
Two decades of research in dietary acrylamide: What do we know today

Abstract After nearly two decades since acrylamide was first raised as a potential safety issue in foods, significant progress has been made in understanding its formation during cooking, how to reduce levels in the most concerned foods, and the possible cancer risk to humans. Despite the huge wealth of knowledge gathered on this topic over the past years, a few new discoveries in occurrence, mitigation, analysis and risk assessment are worthy to note. This short review highlights the salient novelties pertaining to acrylamide, particularly in the areas of formation & analysis, existing and possible future regulations in the European Union, and finally considerations that may lead to possibly revisiting the toxicity of acrylamide and the main metabolite, glycidamide.
Complete Genome Sequence of Bradyrhizobium sp. Strain C-145, a Nitrogen-Fixing Rhizobacterium Used as a Peanut Inoculant in Argentina

We present the complete genome sequence of Bradyrhizobium sp. strain C-145, one of the most widely used nitrogen-fixing rhizobacteria for inoculating peanut crops in Argentina. The genome consists of 9.53 Mbp in a single circular chromosome and was determined using a hybrid long- and short-read assembly approach. ABSTRACT We present the complete genome sequence of Bradyrhizobium sp. strain C-145, one of the most widely used nitrogen-fixing rhizobacteria for inoculating peanut crops in Argentina. The genome consists of 9.53 Mbp in a single circular chromosome and was determined using a hybrid long- and short-read assembly approach.
Child feeding indexes measuring adherence to New Zealand nutrition guidelines: Development and assessment

Abstract New Zealand (NZ) lacks nationally representative or generalisable information on the dietary intakes of pre‐schoolers. We used Growing Up in New Zealand cohort data to i) develop child feeding indexes (CFIs) based on National Food and Nutrition Guidelines for 2‐ and 4.5‐year‐olds; ii) describe the cohort adherence to the guidelines at 2 (n = 6046) and 4.5 years (n = 5889) and; iii) assess the CFIs’ convergent construct validity, by exploring associations with maternal sociodemographic and health behaviours and with child body mass index for age (BMI/age) and the waist‐to‐height ratio at 4.5 years. The CFIs scores ranged from 0 to 11, with 11 representing full adherence to the guidelines. Associations were tested using multiple linear regressions and Poisson regressions with robust variance (risk ratios [RR], 95% confidence intervals, 95% CI). The CFIs mean scores (SD) at 2 and 4.5 years were, respectively, 6.13 (1.21) and 6.22 (1.26) points. Maternal characteristics explained, respectively, 27.2% and 31.9% of the variation in the CFIs scores at 2 and 4.5 years. In the adjusted model at the 4.5‐year interview, in relation to girls ranked in the 5th quintile, those in the 2nd (RR, 95% CI: 1.48; 1.03; 1.24) and 4th (1.53; 1.05; 2.23) quintiles of the CFI were more likely to have BMI/age > +2z (World Health Organization growth standards) at 4.5 years. At 2 and 4.5 years, most children fell short of meeting national guidelines. The associations between the CFIs scores at both time points with maternal characteristics and with children's body size at 4.5 years were in the expected directions, confirming the CFIs’ convergent construct validity among NZ pre‐schoolers.
Recovery of Partially Engorged Haemaphysalis longicornis (Acari: Ixodidae) Ticks from Active Surveillance

Abstract The invasive Asian longhorned tick, Haemaphysalis longicornis, has rapidly spread across the northeastern United States and is associated with pathogens of public health and veterinary concern. Despite its importance in pathogen dynamics, H. longicornis blood-feeding behavior in nature, specifically the likelihood of interrupted feeding, remains poorly documented. Here, we report the recovery of partially engorged, questing H. longicornis from active tick surveillance in Pennsylvania. Significantly more engorged H. longicornis nymphs (1.54%) and adults (3.07%) were recovered compared to Ixodes scapularis nymphs (0.22%) and adults (zero). Mean Scutal Index difference between unengorged and engorged nymph specimens was 0.65 and 0.42 for I. scapularis and H. longicornis, respectively, suggesting the questing, engorged H. longicornis also engorged to a comparatively lesser extent. These data are among the first to document recovery of engorged, host-seeking H. longicornis ticks and provide initial evidence for interrupted feeding and repeated successful questing events bearing implications for pathogen transmission and warranting consideration in vector dynamics models.
A cell penetrating peptide-modified magnetic/fluorescent probe for in vivo tracking of mesenchymal stem cells.

Difficulty in precise tracking of the in vivo distribution and migration of transplanted stem cells in a noninvasive way is a great hurdle in regenerative medicine research. Paramagnetic element-doped upconversion nanoparticles (UCNPs) emerge as a kind of promising dual-modal imaging agents owing to the possibility in combining strong contrast of MR imaging and high efficiency of fluorescence imaging. Herein a kind of Mn-doped NaYF4-based UCNPs (NaYF4: 20%Yb, 2%Er, 30%Mn) was developed and then hydrophilized by various coatings, including cell penetrating peptide, DNA, and SiO2 . The UCNPs were denoted as Pep/UCNPs, DNA/UCNPs, and SiO2 /UCNPs, respectively. Their potential in cell labeling and in vivo tracking applications was comprehensively explored. The results show that the Mn-doped UCNPs possess high biocompatibility, high cell labeling efficiency, high MR resolution, and importantly a single emission at 660 nm, within optical window for in vivo imaging of biological targets. Particularly, mesenchymal stem cells (MSCs) pre-labeled by cell penetrating peptide-modified UCNPs (Pep/UCNPs) can be precisely monitored in terms of their distribution in mice over a long period of time by simultaneous MR and fluorescent imaging, which provided a noninvasive and double-checking tool for investigating the destination of stem cells in tissue regeneration.
Ultrafast Excited-State Dynamics of Carotenoids and the Role of the SX State

Carotenoids are natural pigments with multiple roles in photosynthesis. They act as accessory pigments by absorbing light where chlorophyll absorption is low, and they quench the excitation energy of neighboring chlorophylls under high-light conditions. The function of carotenoids depends on their polyene-like structure, which controls their excited-state properties. After light absorption to their bright S2 state, carotenoids rapidly decay to the optically dark S1 state. However, ultrafast spectroscopy experiments have shown the signatures of another dark state, termed SX. Here we shed light on the ultrafast photophysics of lutein, a xanthophyll carotenoid, by explicitly simulating its nonadiabatic excited-state dynamics in solution. Our simulations confirm the involvement of SX in the relaxation toward S1 and reveal that it is formed through a change in the nature of the S2 state driven by the decrease in the bond length alternation coordinate of the carotenoid conjugated chain.
High‐dose Vitamin B6 supplementation reduces anxiety and strengthens visual surround suppression

Vitamins B6 and B12 are involved in metabolic processes that decrease neural excitation and increase inhibition. This double‐blind study investigated the effects of supplementation for 1 month with a high‐dose of B6 or B12, compared to placebo, on a range of behavioural outcome measures connected to the balance between neural inhibition and excitation.
IDET: Iterative Difference-Enhanced Transformers for High-Quality Change Detection

Change detection (CD) aims to detect change regions within an image pair captured at different times, playing a significant role in diverse real-world applications. Nevertheless, most of the existing works focus on designing advanced network architectures to map the feature difference to the final change map while ignoring the influence of the quality of the feature difference. In this paper, we study the CD from a different perspective, i.e., how to optimize the feature difference to highlight changes and suppress unchanged regions, and propose a novel module denoted as iterative difference-enhanced transformers (IDET). IDET contains three transformers: two transformers for extracting the long-range information of the two images and one transformer for enhancing the feature difference. In contrast to the previous transformers, the third transformer takes the outputs of the first two transformers to guide the enhancement of the feature difference iteratively. To achieve more effective refinement, we further propose the multi-scale IDET-based change detection that uses multi-scale representations of the images for multiple feature difference refinements and proposes a coarse-to-fine fusion strategy to combine all refinements. Our final CD method outperforms seven state-of-the-art methods on six large-scale datasets under diverse application scenarios, which demonstrates the importance of feature difference enhancements and the effectiveness of IDET.
Control Oriented Modeling of an Automotive Drivetrain for Anti-Jerk Control

Drivability is an important metric during the development of an automobile. Calibration engineers spend a significant amount of time trying to improve the drivability of vehicles for various driving conditions. With an increase in the available computational power in an automobile, novel model-based methods are being implemented for further improving the drivability, while reducing calibration time and effort. Phenomenon known as clunk and shuffle, which are caused due to backlash and compliance in the driveline, are a major cause of issues related to drivability and noise, vibration and harshness (NVH) during tip-in and tip-out scenarios. This thesis focuses on developing a high-fidelity, control-oriented vehicle driveline model, which can be used for developing systems, to improve the drivability of a vehicle, during tip-in and tip-out events. A first principle physics-based model is developed, which includes the engine as a torque generator, backlash elements as discontinuities, and driveshafts as compliant elements. Experimental validation results showed that the accuracy of the developed model, in representing shuffle oscillation frequency, during the tip-in scenarios, with locked torque converter clutch, is approximately 99 %. A parametric analysis is performed to characterize the behavior of the model during