Miracle-dz/UniFAR-FTUs huggingface dataset:
Systematic Analysis of Genetic and Pathway Determinants of Eribulin Sensitivity across 100 Human Cancer Cell Lines from the Cancer Cell Line Encyclopedia (CCLE)

Simple Summary Despite decades of clinical use and detailed understandings of their mechanisms of action, clinically useful predictive biomarkers for approved microtubule targeting agents such as eribulin, paclitaxel and vinorelbine have eluded development. Our results now provide the basis for gene expression-based, drug-specific predictive biomarkers for eribulin and vinorelbine, as well as deeper understandings of the molecular pathways associated with eribulin and vinorelbine response. Abstract Eribulin, a natural product-based microtubule targeting agent with cytotoxic and noncytotoxic mechanisms, is FDA approved for certain patients with advanced breast cancer and liposarcoma. To investigate the feasibility of developing drug-specific predictive biomarkers, we quantified antiproliferative activities of eribulin versus paclitaxel and vinorelbine against 100 human cancer cell lines from the Cancer Cell Line Encyclopedia, and correlated results with publicly available databases to identify genes and pathways associated with eribulin response, either uniquely or shared with paclitaxel or vinorelbine. Mean expression ratios of 11,985 genes between the most and least sensitive cell line quartiles were sorted by p-values and drug overlaps, yielding 52, 29 and 80 genes uniquely associated with eribulin, paclitaxel and vinorelbine, respectively. Further restriction to minimum 2-fold ratios followed by reintroducing data from the middle two quartiles identified 9 and 13 drug-specific unique fingerprint genes for eribulin and vinorelbine, respectively; surprisingly, no gene met all criteria for paclitaxel. Interactome and Reactome pathway analyses showed that unique fingerprint genes of both drugs were primarily associated with cellular signaling, not microtubule-related pathways, although considerable differences existed in individual pathways identified. Finally, four-gene (C5ORF38, DAAM1, IRX2, CD70) and five-gene (EPHA2, NGEF, SEPTIN10, TRIP10, VSIG10) multivariate regression models for eribulin and vinorelbine showed high statistical correlation with drug-specific responses across the 100 cell lines and accurately calculated predicted mean IC50s for the most and least sensitive cell line quartiles as surrogates for responders and nonresponders, respectively. Collectively, these results provide a foundation for developing drug-specific predictive biomarkers for eribulin and vinorelbine.
Novel design of honeycomb hybrid sandwich structures under air-blast

In this study, dynamic explicit analysis was performed to examine the air-blast performance of various hybrid sandwich designs in terms of face plate deflections and energy dissipation capacity under the conventional weapons effects program (CONWEP) air-blast loads ranging from 3 kg to 8 kg trinitrotoluene for stand-off distance ranges from 150 mm to 200 mm. The blast resistance of honeycomb sandwich configurations was evaluated using steel honeycomb with different core topologies, crushable Al foam-filled steel honeycomb, and steel or steel with 3D Kevlar/polypropylene laminate employing fiber metal laminate (FML) front face. For an accurate prediction of the deformation mechanism of all steel parts, the Johnson-Cook (J-C) model was used. The composite failure criteria of Hashin, Puck, and Matzenmiller were implemented to accurately examine the fiber and matrix damage behavior. The novel hybrid design of the honeycomb sandwich structure’s blast resistance is improved by the employment of foam-filled honeycomb, an FML front face, and a circular honeycomb core. In comparison to other sandwich configurations, a novel designed hybrid sandwich construction composed of foam filled circular honeycomb with FML front facing and steel back facing (FCH-1KP0.5) achieved the highest blast resistance due to its lowest face deflection with the smallest plastic dissipation energy.
Amplitude and Frequency Modulation With an On-Chip Graphene-Based Plasmonic Terahertz Nanogenerator

Terahertz communication is envisioned as a key technology not only for the next generation of macro-scale networks (e.g., 6G), but also for transformative networking applications at the nanoscale (e.g., wireless nanosensor networks and wireless networks on chip). In this paper, an on-chip THz nano-generator with amplitude and frequency modulation capabilities is presented. The proposed device uses and leverages the tunability of the Dyakonov-Shur instability for the growth and modulation of plasmonic oscillations in the two-dimensional electron gas channel of a graphene-based high-electron-mobility transistor. An in-house developed finite-element-methods platform, which self-consistently solves the hydrodynamic model and Maxwell's equations, is utilized to provide extensive numerical results demonstrating the device's functionality along with ultra-wide bandwidth and high modulation index capabilities.
Single quasiparticle and electron emitter in the fractional quantum Hall regime

We propose a device consisting of an antidot periodically driven in time by a magnetic field as a fractional quantum Hall counterpart of the celebrated mesoscopic capacitor-based single-electron source. We fully characterize the setup as an ideal emitter of individual quasiparticles and electrons into fractional quantum Hall edge channels of the Laughlin sequence. Our treatment relies on a master equation approach and identifies the optimal regime of operation for both types of sources. The quasiparticle/quasihole emission regime involves in practice only two charge states of the antidot, allowing for an analytic treatment. We show the precise quantization of the emitted charge, we determine its optimal working regime, and we compute the phase-noise/shot-noise crossover as a function of the escape time from the emitter. The emission of electrons, which calls for a larger amplitude of the drive, requires a full numerical treatment of the master equations as more quasiparticle charge states are involved. Nevertheless, in this case the emission of one electron charge followed by one hole per period can also be achieved, and the overall shape of the noise spectrum is similar to that of the quasiparticle source, but the presence of additional quasiparticle processes enhances the noise amplitude.
Convergent evolution in silico reveals shape and dynamic principles of directed locomotion on the ground

Renata Biaggi Biazzi. Convergent evolution in silico reveals shape and dynamic principles of directed locomotion on the ground. Thesis (Master’s). Institute of Mathematics and Statistics, University of São Paulo, São Paulo, 2022. Active, directed locomotion on the ground is present in many phylogenetically distant species. Bilateral symmetry and modularity of the body are common traits often associated with improved directed locomotion. Nevertheless, both features result from natural selection, which is contingent (history-dependent) and multifactorial (several factors interact simultaneously). Hence, it is difficult to show that bilateral symmetry and modularity of the body are necessary traits for an improved locomotion ability as they can be a result of chance or related to other body functions. We propose using evolutionary physical simulations of 3D voxel-based soft robots to test the necessity of both traits for efficient directed locomotion on the ground. We found that an intermediate number of body modules (appendages) and high body symmetry are evolutionarily selected regardless of gravitational environments, robot sizes, and genotype encoding. Therefore, we conclude that both traits are strong candidates for universal principles related to efficient directed locomotion.
Quantifying evapotranspiration from dominant Arctic vegetation types using lysimeters

The thermal and hydraulic properties of the moss and organic layer regulate energy fluxes, permafrost stability, and hydrologic function in Arctic tundra. Our goal was to quantify evapotranspiration (ET) from dominant vegetation types in Arctic tundra. We designed and deployed a network of electronic automated weighing micro‐lysimeters (n = 58, area = 0.06 m2). We selectively clipped groups of plants from a subset of lysimeters to isolate ET from moss, tussocks, and mixed vascular plants. High rates of evaporation (E) recorded during the study period in the moss E lysimeters (64 mm) and high ET in the tussock ET lysimeters (60 mm) show that mosses and sedge tussocks (Eriophorum vaginatum) are the major constituents of local tundra ET. Moss E was consistently higher than ET from mixed vascular species with moss understory indicating that moss E dominates tundra water efflux at sites with moss understory. The ET partitioning presented here will allow for improved prediction of changes in water flux associated with observed and future vegetation change. Future changes in the composition and cover of mosses and vascular plants will not only alter partitioning of tundra ET but may also affect the significant role plants play in the moisture regime and thermodynamics of Arctic permafrost soils.
Opera De Cribro

This is a truly comprehensive account of sieves and their applications, by two of the world's greatest authorities. Beginners will find a thorough introduction to the subject, with plenty of helpful motivation. The more practised reader will appreciate the authors' insights into some of the more mysterious parts of the theory, as well as the wealth of new examples. No analytic number theorist should be without this volume, but it will not have a place on my bookshelves--it will be permanently on my desk! --Roger Heath-Brown, University of Oxford, Fellow of Royal Society . This is a comprehensive and up-to-date treatment of sieve methods. The theory of the sieve is developed thoroughly with complete and accessible proofs of the basic theorems. Included is a wide range of applications, both to traditional questions such as those concerning primes, and to areas previously unexplored by sieve methods, such as elliptic curves, points on cubic surfaces and quantum ergodicity. New proofs are given also of some of the central theorems of analytic number theory; these proofs emphasize and take advantage of the applicability of sieve ideas. The book contains numerous comments which provide the reader with insight into the workings of the subject, both as to what the sieve can do and what it cannot do. The authors reveal recent developments by which the parity barrier can be breached, exposing golden nuggets of the subject, previously inaccessible. The variety in the topics covered and in the levels of difficulty encountered makes this a work of value to novices and experts alike, both as an educational tool and a basic reference.
Investigation of dust lifting by a moving shock wave based on compressible multiphase particle-in-cell method

The dust lifting process by shock waves performs high complexity and is of significance for industrial safety. To develop an in-depth understanding of inherent physical mechanism of dust lifting, this study presents a detailed consideration regarding particle force models. Firstly, a set of compressive force models those may affect lifting are distinguished, which afterwards is integrated to the original compressible multiphase particle-in-cell (CMP-PIC) method. Secondly, the value of the restitution coefficient is determined using the sensitivity analysis method. Good agreements of dust lifting height are achieved between the numerical and different experimental results, which demonstrates the reliability of the CMP-PIC method. Then, the contributions of different kinds of forces to dust lifting are qualitatively and quantitatively analyzed. Flow field analysis shows that the the shock-induced flow produces downward drag and pressure gradient forces on the particles to inhibit the rise of the particles, while the Magnus and Saffman forces perform a promoting role. Additionally, the compression wave and its reflected wave in the granular medium are clearly observed. Specially, when the reflected wave reaches the surface, huge collision forces on the particles and significantly promotes the initial lifting of particles. Moreover, the histories of forces acting on the particles at different layers of dust are discussed. Results show that different kinds of forces perform intense space-time dependent characteristics and the dominant forces at different stages of dust lifting are identified. A dimensionless analysis of the force model qualitatively justifies the simulation results. The influence of shock strength is also discussed.
Optimal control of nonlinear systems with integer‐valued control inputs and stochastic constraints

Practical industrial process is usually a dynamic process including uncertainty. Stochastic constraints can be used for industrial process modeling, when system sate and/or control input constraints cannot be strictly satisfied. Thus, optimal control of nonlinear systems with stochastic constraints can be available to address practical industrial process problems with integer‐valued control inputs. In general, obtaining an analytical solution of this optimal control problem is very difficult due to the discrete nature of the control inputs and the complexity of stochastic constraints. To obtain a numerical solution, this problem is formulated as a finite dimensional static constrained optimization problem. First, the integer‐valued control input is relaxed into a continuous‐valued control input by imposing a penalty term on the objective function. Convergence results show that the relaxed solution obtained is an integer solution as long as the penalty parameter is sufficiently large. In addition, it should be noted that no any constraint is introduced in the novel relaxation technique, which can effectively avoid introducing any extra extreme point for the original optimal control problem. Next, a novel smooth approximation function is used to construct a subset of feasible region for this optimal control problem. It is proved that the smooth approximation can converge uniformly to the stochastic constraints as the adjusting parameter reduces. Following that, a numerical computation method is proposed for solving the original optimal control problem. Finally, in order to illustrate the effectiveness of the proposed method, an electric vehicle energy management problem is extended by considering some stochastic constraints. The numerical results show that the proposed method is less conservative compared with the existing typical approaches and can obtain a stable and robust performance when considering the initial condition small perturbations.
Integrins Increase Sarcoplasmic Reticulum Activity for Excitation—Contraction Coupling in Human Stem Cell-Derived Cardiomyocytes

Abstract Engagement of the sarcoplasmic reticulum (SR) Ca2+ stores for excitation–contraction (EC)-coupling is a fundamental feature of cardiac muscle cells. Extracellular matrix (ECM) proteins that form the extracellular scaffolding supporting cardiac contractile activity are thought to play an integral role in the modulation of EC-coupling. At baseline, human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) show poor utilisation of SR Ca2+ stores, leading to inefficient EC-coupling, like developing or human CMs in cardiac diseases such as heart failure. We hypothesised that integrin ligand–receptor interactions between ECM proteins and CMs recruit the SR to Ca2+ cycling during EC-coupling. hiPSC-CM monolayers were cultured on fibronectin-coated glass before 24 h treatment with fibril-forming peptides containing the integrin-binding tripeptide sequence arginine–glycine–aspartic acid (2 mM). Micropipette application of 40 mM caffeine in standard or Na+/Ca2+-free Tyrode’s solutions was used to assess the Ca2+ removal mechanisms. Microelectrode recordings were conducted to analyse action potentials in current-clamp. Confocal images of labelled hiPSC-CMs were analysed to investigate hiPSC-CM morphology and ultrastructural arrangements in Ca2+ release units. This study demonstrates that peptides containing the integrin-binding sequence arginine–glycine–aspartic acid (1) abbreviate hiPSC-CM Ca2+ transient and action potential duration, (2) increase co-localisation between L-type Ca2+ channels and ryanodine receptors involved in EC-coupling, and (3) increase the rate of SR-mediated Ca2+ cycling. We conclude that integrin-binding peptides induce recruitment of the SR for Ca2+ cycling in EC-coupling through functional and structural improvements and demonstrate the importance of the ECM in modulating cardiomyocyte function in physiology.
Ultralow-frequency flexural wave attenuation in a beam with periodically attached quasi-zero-stiffness resonators

Ultralow-frequency band gaps are realized to suppress the ultralow-frequency flexural wave propagation in the beams with periodically attached quasi-zero-stiffness (QZS) resonators, which are designed by inserting quasi-zero-stiffness systems into the mass-in-mass structures. The band structure and the transfer matrix of the QZS locally resonant beam are derived by the transfer matrix method to quantify the wave attenuation performance of band gaps. Then, the effect of the stiffness ratio on the bandgap characteristic is studied. It is shown that, thanks to the introduction of the QZS system, the band gaps can be easily transferred to lower frequency or even ultralow frequency without weakening the static stiffness of the resonators. Finally, the flexural wave propagation in locally resonant beam consisting of multiple periodic arrays of QZS resonators is investigated. The result shows that differential design of the bandgap frequencies can be easily realized by adjusting the negative stiffness coefficient of the QZS resonators, so as to obtain broadband flexural wave suppression performance.
Predicting Retention for a Diverse and Inclusive Child Welfare Workforce

ABSTRACT Retaining staff remains a challenge for public and private child welfare organizations, and current research does not explain the underrepresentation of workers of Color in leadership and supervisory positions. This study used data from a multi-site survey of child welfare staff to compare factors associated with intention to remain employed between caseworkers of Color and White caseworkers using path analysis. Factors associated with job satisfaction, the strongest predictor of intention to remain employed for both groups in our path analysis, differed slightly between workers of Color and White workers. Age and job stress were significantly more influential for workers of Color, while work related burnout was more more influential for White workers. For workers of Color, perception of leadership was significantly more influential on workers’ of Color intention to remain employed, compared to White workers, and having an MSW was a significant predictor of intent to remain employed for White workers, but not for workers of Color. Implications for agency practice and policy, including suggested strategies to address retention of workers at the caseworker level, are discussed.
Excitonic Bose-Einstein condensation in Ta 2 NiSe 5 above room temperature

We show that finite temperature variational cluster approximation (VCA) calculations on an extended Falicov-Kimball model can reproduce angle-resolved photoemission spectroscopy (ARPES) results on Ta2NiSe5 across a semiconductor-to-semiconductor structural phase transition at 325 K. We demonstrate that the characteristic temperature dependence of the flat-top valence band observed by ARPES is reproduced by the VCA calculation on the realistic model for an excitonic insulator only when the strong excitonic fluctuation is taken into account. The present calculations indicate that Ta2NiSe5 falls in the Bose-Einstein condensation regime of the excitonic insulator state.
High-Energy Ball Milling for High Productivity of Nanobiochar from Oil Palm Biomass

The current production method of nanobiochar (NBC), an emerging, environmentally friendly nanocarbon material, is tedious and lengthy. Therefore, in this study we aimed to improve the productivity of NBC via high-energy ball milling by manipulating the grinding media and processing time. The particle size distribution of the resulting NBC measured using dynamic light scattering showed that grinding media with steel balls of different sizes were more effective at producing NBC than small uniform steel balls, which failed to produce NBC even after 90 min of milling. Average NBC particles of around 95 nm were achieved after only 30 min of ball milling, and the size was further reduced to about 30 nm when the milling was prolonged to 150 min. Further prolonging the milling duration led to agglomeration, which increased the size of the biochar nanoparticles. The thermogravimetric analysis (TGA) data showed that the duration of milling and particle size did not cause noticeable differences in the thermal stability of the NBC. Based on the FTIR analysis, the chemical structure of the NBC was not affected by the ball milling. The results showed that 60 min of high-energy ball milling is sufficient to produce NBC particles of 75 nm, with a large surface area and high thermal stability. This could prove beneficial in a myriad of applications, ranging from agriculture to composite fabrication.
Chemical fingerprints and bioactivities of 12 Anatolian Achillea species by LC-MS/MS with chemometric approach: Novel phytonutrients, natural food preservatives and chlorogenic acid sources

Recommended Citation YILMAZ, MUSTAFA ABDULLAH; ERTAŞ, ABDULSELAM; YENER, İSMAİL; TÜRKMENOĞLU, FATMA PINAR; ÖLMEZ, ÖZGE TOKUL; ÖZTÜRK, MEHMET; ALTUN, MUHAMMED; ÇAKIR, OĞUZ; TARHAN, ABBAS; BOĞA, MEHMET; DEMİRTAŞ, İBRAHİM; ALMA, MEHMET HAKKI; and TEMEL, HAMDİ (2022) "Chemical fingerprints and bioactivities of 12 Anatolian Achillea species by LC-MS/MS with chemometric approach: Novel phytonutrients, natural food preservatives and chlorogenic acid sources," Turkish Journal of Botany: Vol. 46: No. 5, Article 5. https://doi.org/10.55730/1300-008X.2723 Available at: https://journals.tubitak. gov.tr/botany/vol46/iss5/5
Development of an Imaging and Impedance Flow Cytometer Based on a Constriction Microchannel and Deep Neural Pattern Recognition

This article presents an imaging and impedance flow cytometer based on a constriction microchannel with corresponding cell-type classification based on deep neural pattern recognition. When an incoming cell reached the entrance of the constriction microchannel, the image of the nucleus labeled with fluorescence was captured by a high-speed camera without the concern of losing focus, whereas when the cell deformed through the constriction microchannel by effectively blocking electrical lines, large impedance variations were sampled by an impedance analyzer. Six key biostructural and bioelectrical parameters (e.g., cell diameter, nuclear roundness, and cytoplasmic conductivity) from thousands of single cells were extracted, producing a successful rate of 88.3% in classifying A549 versus Jurkat versus K562 cells based on the feedforward neural network. In addition, multilayer neural networks of deep learning (e.g., VGG16 of CNN and LSTM of RNN) were also used to process fluorescent images and impedance profiles, producing an almost 100% successful rate in cell-type classification. In summary, the microfluidic flow cytometer reported in this article could characterize single-cell biostructural and bioelectrical properties in a high throughput manner, realizing high successful rates of cell-type classification.