bluuebunny/crossref_metadata_2025 huggingface dataset:
Size effect in the resistance of a point contact with point defects
Authors: Kolesnichenko Yu. A. , Omel’yanchuk A. N. , Tuluzov I. G.
Published: January 2025

The effect of point defects on the conductivity of ballistic point contacts is investigated theoretically. It is shown that the size dependence of the resistance R(d) is determined by the relation between the contact diameter d and the characteristic distance r0 between impurities. For d ≲r0, the value of R(d) is sensitive to the spatial arrangement of scatterers in the contact region. The numerical modelling of the contact conductivity is carried out for random distributions of impurities.
Peculiarities of thermodynamics of phase transitions in a system with two ordering channels
Authors: Sukharevskiĭ B. Ya. , Zavadskiĭ È. A.
Published: January 2025

A Landau model potential taking into account the presence of interaction of two ordering channels is proposed. This potential corresponds to a phase diagram which is a common fragment of phase diagrams for many experimentally studied systems. It is shown that the existence of the second channel and the interaction of order parameters determining the ordering in the two channels are necessary conditions for a radical change in the thermodynamic parameters of a phase transition, such as the sign of curvature of the equilibrium transition line and of the lability boundaries of the ordered and disordered phases in the main order parameter of the phases, and the sign reversal of the thermal effect (which is single on the phase equilibrium curve and double on the lability boundaries). Some of these peculiarities are observed in the experimental phase diagrams, while others are predicted and can be detected in experimentally refined phase diagrams.
Ultrafast laser frequency tuning based on equivalent optical phase sampling and accumulation
Authors: Lyu Weiqiang , Tian Huan , Fu Zhenwei , Zhang Lingjie , Zeng Zhen , Zhang Yaowen , Li Heping , Zhang Zhiyao , Liu Yong
Published: January 2025

Ultrafast laser frequency tuning is a crucial function in numerous applications, including light detection and ranging (LiDAR), optical coherence tomography (OCT), and spectroscopy. In general, laser frequency tuning is realized via the motion of mechanical structures, frequency-swept optical filters, or the Pockels effect in the laser cavity. Nevertheless, the maximum frequency tuning rate and sweep rate are smaller than 107 THz/s and 1 GHz, respectively, due to the inherent speed limitation of the existing tuning mechanisms. Here, we propose and demonstrate a brand-new concept for ultrafast laser frequency tuning, which is realized based on equivalent optical phase sampling and accumulation in the laser cavity. By inserting an electro-optic phase modulator (PM) into the laser cavity and properly setting the period of the driving signal applied to the PM to make its integer multiple slightly deviate from the round trip time of the laser cavity, a linear mapping from the voltage of the driving signal to the output laser frequency is realized via equivalent optical phase sampling and accumulation. This remarkable feature provides a rapid way to manipulate the laser frequency, breaking the frequency tuning speed limitation of the existing approaches. In the experiment, a record-breaking frequency tuning rate of 1.522 × 109 THz/s and a sweep rate of 2223.97 MHz are simultaneously realized. Moreover, the center wavelength and the frequency tuning range can be easily reconfigured. This work paves the way for ultrafast laser frequency tuning in a customized wavelength range.
Targeting EPHB2/ABL1 restores antitumor immunity in preclinical models of ependymoma
Authors: Ren Jun , Amoozgar Zohreh , Uccello Taylor P. , Lei Pin-Ji , Zhao Yuhui , Ho William W. , Huang Peigen , Kardian Alisha , Mack Stephen C. , Duda Dan G. , Xu Lei , Jain Rakesh K.
Published: January 2025

Ependymoma (EPN) is a common form of brain tumor in children, often resistant to available cytotoxic therapies. Molecular profiling studies have led to a better understanding of EPN subtypes and revealed a critical role of oncogenes ZFTA–RELA fusion and EPHB2 in supratentorial ependymoma (ST-EPN). However, the immune system’s role in tumor progression and response to therapy remains poorly understood. New treatments for various molecular subtypes of EPN are desperately needed. Using ST-EPN-ZFTA subtype-specific syngeneic mouse models, we found an increased frequency of M2-like tumor-associated macrophages (TAMs), which proportionally increased with tumor size during tumor progression. Transcriptomic profiling of ST-EPN-ZFTA and analysis of a human EPN dataset revealed multiple protein kinases as potential druggable targets. By matching transcriptomic signatures with the target spectrum of FDA-approved drugs, we found that the multikinase inhibitor dasatinib potently inhibited the growth of EPN both in vitro and in vivo, mainly through blocking EPHB2 and ABL1. Treatment with dasatinib reprogrammed the EPN immune microenvironment by polarizing TAMs toward an M1-like phenotype and increasing CD8 T cell activation. Furthermore, dasatinib treatment induced complete regression of established EPN tumors in 78% of the animals and protected survivors against tumor recurrence. Depletion of CD8 cells compromised the durability of EPN responses and reduced overall survival. These data indicate that dasatinib has the potential to be an effective therapy for ST-EPN-ZFTA molecular subgroup of EPN and support further investigation of dasatinib in clinical trials.
BCL6 coordinates muscle mass homeostasis with nutritional states
Authors: Wang Hui J. , Fan Weiwei , Liu Sihao , Kim Kyeongkyu , Matsushima Ayami , Ogawa Satoshi , Kang Hyun Gyu , Zhu Jonathan , Estepa Gabriela , He Mingxiao , Crossley Lillian , Liddle Christopher , Kim Minseok S. , Truitt Morgan L. , Yu Ruth T. , Atkins Annette R. , Downes Michael , Evans Ronald M.
Published: January 2025

Nutritional status is a determining factor for growth during development and homeostatic maintenance in adulthood. In the context of muscle, growth hormone (GH) coordinates growth with nutritional status; however, the detailed mechanisms remain to be fully elucidated. Here, we show that the transcriptional repressor B cell lymphoma 6 (BCL6) maintains muscle mass by sustaining GH action. Muscle-specific genetic deletion of BCL6 at either perinatal or adult stages profoundly reduces muscle mass and compromises muscle strength. Conversely, muscle-directed viral overexpression of BCL6 significantly reverses the loss of muscle mass and strength. Mechanistically, we show that BCL6 transcriptionally represses the suppressor of cytokine signaling 2 to sustain the anabolic actions of GH in muscle. Additionally, we find that GH itself transcriptionally inhibits BCL6 through the Janus kinase and signal transducer and activator of transcription 5 (JAK/STAT5) pathway. Supporting the physiologic relevance of this feedback regulation, we show the coordinated suppression of muscle
Bcl6
expression with the induction of GH in the fasted state. These findings reveal the complexity of the feedback controls modulating GH signaling and identify BCL6 as a key homeostatic regulator coordinating muscle mass with nutrient availability. Moreover, these studies open avenues for targeted therapeutic strategies to combat muscle-wasting conditions.
NuMA is a mitotic adaptor protein that activates dynein and connects it to microtubule minus ends
Authors: Colombo Sabina , Michel Christel , Speroni Silvia , Ruhnow Felix , Gili Maria , Brito Cláudia , Surrey Thomas
Published: January 2025

Nuclear mitotic apparatus protein (NuMA) is indispensable for the mitotic functions of the major microtubule minus-end directed motor cytoplasmic dynein 1. NuMA and dynein are both essential for correct spindle pole organization. How these proteins cooperate to gather microtubule minus ends at spindle poles remains unclear. Here, we use microscopy-based in vitro reconstitutions to demonstrate that NuMA is a dynein adaptor, activating processive dynein motility together with dynein’s cofactors dynactin and Lissencephaly-1 (Lis1). Additionally, we find that NuMA binds and stabilizes microtubule minus ends, allowing dynein/dynactin/NuMA to transport microtubule minus ends as cargo to other minus ends. We further show that the microtubule-nucleating γ-tubulin ring complex (γTuRC) hinders NuMA binding and that NuMA only caps minus ends of γTuRC-nucleated microtubules after γTuRC release. These results provide new mechanistic insight into how dynein, dynactin, NuMA, and Lis1 together with γTuRC and uncapping proteins cooperate to organize spindle poles in cells.
Modelling bagpipes: numerical simulation exercise for distributed parameter system
Authors: Tužil Josef , Šlégr Jan
Published: January 2025

Bagpipes are an ancient folk musical instrument, used as far back as ancient Greece. To this day, they are part of folk music in many countries and cultures. This paper deals with the modelling of the reed and melodic pipe (chanter) for bagpipes, focusing on tuning of the instrument. We present a theoretical model in the Geogebra software, which allows for qualitative simulating and visualizing the interaction between the reed blade and the air column of the pipe.
High-speed pulsing circuit for continuous wave laser beams
Authors: Murray Andrew James
Published: January 2025

Tunable continuous wave (CW) lasers produce the highest optical resolution for pumping and probing atomic and molecular transitions. These lasers adopt sophisticated electronic control of optical components within the cavity to set the wavelength and ensure a narrow bandwidth. The low-cost circuit described here gates a CW laser beam on and off for high resolution timing experiments, using an electro-optic modulator that acts as a switchable waveplate between linear polarizers. The switch can operate at rates of up to 100 kHz with a minimum pulse width of 650 ns, or it can be configured to deliver laser pulses with widths

⩾

35 ns at lower rates. Multiple laser pulses of equal or non-equal widths can also be delivered within each repetition cycle.
Targeted therapy for glioblastoma utilizing hyaluronic acid-engineered liposomes for adriamycin delivery
Authors: Wang Yanping , Qi Peiyan , Shi Shenbao , Pang Cong , Wang Weijie , Fang Dazhao
Published: January 2025

Glioblastoma (GBM) is a malignant tumor with highly heterogeneous and invasive characteristics leading to a poor prognosis. The CD44 molecule, which is highly expressed in GBM, has emerged as a highly sought-after biological marker. Therapeutic strategies targeting the cell membrane protein CD44 have emerged, demonstrating novel therapeutic potential. In this study, we constructed a nanodrug system (HA-Liposome@Dox) based on hyaluronic acid-engineered liposomes delivering adriamycin to target GBM. The system efficiently encapsulated Dox inside the liposomes through a hydrophilic-hydrophobic interaction mechanism, and the resulting HA-Liposome@Dox exhibited excellent loading efficacy, attributed to its uniform particle size distribution and negatively charged surface. Further evaluation revealed that HA-Liposome@Dox possessed excellent stability and safety and could promote the effective uptake of drug particles by CD44-overexpressing tumor cells, thus exerting a more potent cell-killing effect. Notably, in the treatment of GBM, HA-Liposome@Dox demonstrated significantly greater tumor growth inhibition compared to free Dox and prolonged the survival of tumor-bearing mice. Taken together, the present study not only verified the feasibility of HA-Liposome@Dox as an effective therapeutic tool against GBM and other CD44-positively expressing tumors, but also opened a promising new avenue for the clinical treatment of this type of refractory malignancies.
Characterization of uncertainties in electron-argon collision cross sections
Authors: Chung Seung Whan , Oliver Todd A , Raja Laxminarayan L , Moser Robert D
Published: January 2025

The predictive capability of a plasma discharge model depends on accurate representations of electron-impact collision cross sections, which determine the corresponding reaction rates and electron transport properties. The values of cross sections can be known only approximately either through experiments or simulations and are thus subject to uncertainties. Quantifying the uncertainties in plasma simulations allows us to assess the reliability of simulations and to provide a basis for interpreting discrepancies between simulations and experiments. For such uncertainty quantification of plasma simulations, it is essential to quantify the uncertainties of the underlying cross sections. Although much effort has been committed to calibrate the cross section values, their uncertainties are not well investigated. We characterize uncertainties in electron-argon atom collision cross sections using a Bayesian framework. Six collision processes—elastic momentum transfer, ionization, and four excitations—are characterized with semi-empirical models, which effectively capture the features important to the macroscopic properties of the plasma. A probability model for the uncertain parameters of these semi-empirical models is developed. Specifically, a Gaussian-process likelihood model is proposed to capture discrepancies among data sets, as well as the model-form inadequacies of the semi-empirical models. Two other likelihood models are compared with the proposed Gaussian-process model, to illustrate the importance of the choice of the likelihood model. The cross section models are calibrated using the electron-beam experiments and ab-inito quantum simulations. The resulting calibrated uncertainties capture well the scattering among the data sets. The calibrated cross section models are further validated against swarm-parameter experiments and zero-dimensional Boltzmann equation simulations of widely used cross section datasets.
Optical inline interferometer for enhanced low-field detection via electric-field induced second harmonic generation
Authors: Billeau Jean-Baptiste , Cusson Patrick , Seletskiy Denis V. , Reuter Stephan
Published: January 2025

Nonlinear optical methods, such as Electric-Field Induced Second Harmonic (E-FISH) generation, have emerged as powerful tools for diagnosing electric fields in plasma environments. The E-FISH technique depends quadratically on the electric field under study, which results in complete insensitivity to its polarity and diminished sensitivity to its low amplitudes. Both of these challenges have been recently resolved in a Local Oscillator Electric-Field Induced Second Harmonic (LOE-FISH) technique, introducing coherent homodyne amplification of a weak E-FISH signal using of an optical local oscillator field. Early LOE-FISH demonstrations relied on a delay line, resulting in decreased accuracy due to the higher sensitivity of the interferometer to environmental noise. In this work, we introduce an "inline" design of the interferometer with maximally shared common paths and a balanced photodetection system, thus greatly reducing sensitivity to environmental noise and laser technical noise and hence improving the robustness of the technique. To this end, we achieve a factor of 143 increase in signal-to-noise ratio (SNR) when LOE-FISH is compared to E-FISH. Furthermore, we successfully measured an electric field as low as 32 V/cm with an SNR of 7.4 during 0.15 s measurement time, estimating an unprecedented detection limit of 12.1 V/(cm √Hz). Our work represents a significant step toward real-time, high-precision diagnostics of electric fields in complex plasma environments, electric field amplitude fluctuations can influence reactive species' generation and overall process efficiency.
Simulation of a pulsed CO2 plasma based on a six-temperature energy approach
Authors: Tsonev I , Biondo O , Bogaerts A
Published: January 2025

Recent time-resolved measurements of gas and vibrational temperatures in pulsed glow discharges have fostered the development and validation of detailed kinetic models to understand the underlying heating dynamics. The models published so far have been successful in identifying the fundamental processes underlying vibrational and gas heating in pure CO2 discharges; however, this has come at the cost of including vibrational kinetics with thousands of reactions. This makes these models not compatible with self-consistent computational fluid dynamics (CFDs) codes, which are needed to develop new plasma reactors operating at high pressures or with complex flow patterns and capture the relevant dynamics in multi-dimension. In this work, we solve separate energy balance equations for the asymmetric and symmetric vibrational modes of CO2, as well as for the vibrational modes of CO and O2, the gas temperature, and the electron temperature, making it a six-temperature (6 T) plasma model. This eliminates the need to include a vast array of vibrational levels as separate species, drastically reducing the number of reactions in the model. The model is compared with experimental measurements conducted in a pulsed CO2 glow discharge at 6.7 mbar. Excellent agreement is observed for the temporal evolution of the vibrational and gas temperatures, confirming that our approach is suitable for modeling systems under significant non-equilibrium conditions, paving the way for coupling detailed CO2/CO/O2/O kinetics with CFD codes.
Distribution of flux states in a hysteretic dc SQUID
Authors: He Kaiyong , Yang Liangliang , Dai Genting , Liu Jianshe , Chen Wei
Published: January 2025

This work investigates the distribution of flux states of hysteretic dc superconducting quantum interference devices (SQUIDs) obtained from standard current ramp measurement at 2.50 and 0.35 K. Each flux state corresponds to a specific number of flux quanta trapped in the superconducting loop, associated with a metastable state in the two-dimensional potential energy of the hysteretic SQUID. The flux states can be distinguished by the multiple switching currents. The observed distribution is different from the distribution caused only by thermal excitation at a specific temperature. There are notable systematic deviations between the measurement results of three samples and the standard Boltzmann distribution, which can be clearly identified from the ratios between the proportions of different flux states. A formula resembling the Boltzmann distribution, involving multiple effective temperatures, is proposed to provide a better fit to the measured results. The finding suggests that the observed distribution of flux states is established during the SQUID’s transition from the dissipative state to the zero-voltage state, and multiple equivalent temperatures may be involved in the process.
Experimental and numerical analysis of Carbon/Glass fiber reinforced thermoplastic wind turbine blade prepared by VARIM
Authors: Abhilash H N , Raghunandana K , Bhat Subraya Krishna , Prabhu Aruna , Amar Murthy A
Published: January 2025

The output of wind energy, a vital renewable resource, has increased from 94 GW to 591 GW globally in the last ten years. Weight and cost are important considerations in wind turbine blade (WTB) design, as rotor blades make up 40%–80% of the overall weight, to fulfill the growing need for energy. Even though thermosetting composites are frequently used to make blades, they have several drawbacks, most notably that they cannot be recycled. As more blades approach the end of their lives and become unreformable once cured, recycling and disposal become more difficult, and environmental concerns increase. The main objective of the present work is to manufacture thermoplastic composites reinforced with fibers using the Vacuum Assisted Resin Infusion Moulding (VARIM) technique and assess their mechanical characteristics. The finite element analysis of the WTB incorporates the material parameters calculated for the thermoplastic resin. Test coupons are produced by shaping thermoplastic resin and fiber reinforcement using VARIM. The mechanical characteristics, including flexural and impact strength, are then assessed utilizing destructive testing techniques. Thermoset resins have good flexural properties while thermoplastic resins have better impact properties. The wind turbine blade (WTB) is simulated in ANSYS ACP based on the designated stacking sequence and fiber orientation. Static structure analysis is performed for the thermoplastic and thermosetting composites under various operating circumstances. Identification and analysis of the critical section susceptible to mechanical failure are conducted under different loading conditions, and the obtained outcome is verified. Based on the results, it is concluded that thermoplastic composites are viable materials for manufacturing wind turbine blades.
Onshore and offshore seawater exchange off northeast Taiwan driven by the combined effects of Kuroshio intrusion and tidal currents
Authors: Lin Jia-Yi , Zheng Zhe-Wen , Gopalakrishnan Ganesh , Chen Yi-Rui , Ho Chung-Ru , Zheng Quanan , Huang Chen-Fen
Published: January 2025

The exchange of materials and energy between boundary currents and the surrounding marginal seas largely influences the environment of those seas. In addition to the reported currents over the continental shelf northeast of Taiwan, a process of onshore and offshore water exchange (OOWE) across the northeast-southwest-oriented shelf break is newly introduced in this study. This exchange is constituted by the synergy of Kuroshio intrusion (northwestward) and ebb tide (southeastward). The total velocity obtained by combining Copernicus Marine Service (CMS) satellite geostrophic currents and modeled Ekman currents through the GLOBCURRENT project, along with numerical modeling based on the Regional Ocean Modeling System (ROMS), are used to describe the spatiotemporal characteristics of OOWE and explain its generation dynamics. OOWE occurs in a highly dynamic active area, sandwiched between two current jets: the Kuroshio Current (KC) and the Taiwan Strait Current (TSC). The seaward increase of northward currents off northeast Taiwan (due to a stronger KC and a weaker TSC) provides a favorable environment of positive vorticity that steers the Kuroshio onto the shelf, constituting the north branch of OOWE. Additionally, the ebb tide drives water away from the shore, producing a southeastward current along the north coast of Taiwan, forming the southern branch of OOWE. Uneven wind forcing in the spatial domain slightly modulates the OOWE pattern, though it plays only a secondary role in its generation. Given the potential to induce vigorous exchange and mixing between continental shelf waters and the Kuroshio, the OOWE identified in this study warrants further attention.
Enhanced bearing capacity prediction using hybrid tree-based ensemble learning with advanced meta-heuristic optimization
Authors: Ibrahim Awaisu Shafiu , Idris Ahmad , Umar Ibrahim Haruna , Lin Hang , Shehu Hamza Tijjani
Published: January 2025

The accurate prediction of soil bearing capacity remains a critical challenge in geotechnical engineering, particularly given the complex non-linear relationships between soil properties and foundation performance. Traditional analytical methods often struggle to capture these complexities, leading to potential overestimation or underestimation of bearing capacity across different footing types. This study investigates the application of machine learning techniques for predicting soil bearing capacity across different footing types. The research utilized 200 datasets, comprising 175 institutional sources and 25 laboratory direct shear test experiments, with an 80–20 split ratio for model development and validation. A hybrid tree-based ensemble learning (HTBEL) methodology was developed and compared against conventional models (M5P, CatBoost, AdaBoost, SVR, and Decision Tree) and Terzaghi analytical equation. The HTBEL model demonstrated superior predictive accuracy with R2 values exceeding 0.96 across all footing types, maintaining errors below 5% throughout the sample range. Square footings showed the highest bearing capacity (median ∼3,400 kN m−2) due to favorable area-to-depth ratio, followed by circular footings (∼3,200 kN m−2) benefiting from symmetrical stress transmission, while strip footings (∼2,000 kN m−2) showed lower performance due to concentrated stress distribution along their length. Clustering analysis identified optimal configurations at 3 clusters (Silhouette Score: 0.5236) and 10 clusters (0.5315). This research establishes HTBEL as a robust methodology for bearing capacity prediction in geotechnical engineering applications.
Development of a biaxial fibre Bragg grating (FBG) extensometer with axis misalignment error compensation and cloud integration for advanced slope monitoring
Authors: Ramalingam Nimalrajh , Tan Daryl , Lim Kok-Sing , Mohd Sa'ad Muhammad Syamil , Ahmad H
Published: January 2025

In the paper, an FBG-based biaxial extensometer is presented to detect ground movement, which is a crucial element in slope monitoring systems. Multiple FBGs were used as displacement sensors to establish sensing nodes at various locations along an HDPE pipe. Each sensing node comprises two FBGs for biaxial displacement measurement. A numerical model based on characterization matrix equation is formulated to estimate the lateral displacement vectors using the displacement data obtained from all FBG sensors. The inclusion of torsion effects in the characteristic matrix equation addresses the misalignment error in the principal axis at each sensing node, thereby enhancing estimation accuracy. Through characterization tests, there is a notable enhancement in the accuracy of the displacement vector estimation. Finally, the proposed extensometer is being examined to determine if it can be integrated with the cloud network for remote monitoring. Various random displacement shapes and curvature angles have been tested. The results demonstrate a strong similarity between the shapes reconstructed by the model and the actual ones.
An integrated toolbox for creating neuromorphic edge applications
Authors: Niedermeier Lars , Dutt Nikil , Krichmar Jeffrey L
Published: January 2025

spiking neural networks (SNNs) and neuromorphic models are believed to be more efficient in general and have more biological realism than the activation functions typically used in deep neural networks, transformer models and generative AI. SNNs have local learning rules, are able to learn on small data sets, and can adapt through neuromodulation. Although research has shown their advantages, there are still few compelling practical applications, especially at the edge where sensors and actuators need to be processed in a timely fashion. One reason for this might be that SNNs are much more challenging to understand, build, and operate due to their intrinsic properties. For instance, the mathematical foundation involves differential equations rather than basic activation functions. To address these challenges, we have developed CARLsim++, an integrated toolbox that facilitates the creation of neuromorphic applications. It extends the highly efficient CARLsim open-source SNN simulator. CARLsim++ encapsulates the mathematical intrinsics and low-level C++ programming by providing a graphical user interface for users to easily create their SNNs and a means to configure sensors and actuators for robotics and other edge devices. These can be accurately simulated before deploying on physical devices. CARLsim++ can lead to rapid development of neuromorphic applications for simulation or edge processing. We introduce CARLsim++ with a closed loop robotic demonstration using neuromorphic computing.
An admissibility approach to nonuniform exponential dichotomies
Authors: Backes Lucas , Dragičević Davor , Xia Yonghui
Published: January 2025

Recently, Wu and Xia [Proc. Amer. Math. Soc. 151 (2023), pp. 4389-4403] presented a characterization of nonuniform exponential dichotomy via admissibility for difference equations. They have improved previously known results by removing the use of Lyapunov norms and the assumption of bounded growth of the system. However, they have restricted their attention to the case of finite dimensional and invertible dynamics. In the present work we go one step further and extend their results to the case of possibly noninvertible and infinite dimensional dynamical systems. We emphasize that our method of proof is different and significantly simpler than the one presented in the aforementioned work.
Anillin tunes contractility and regulates barrier function during Rho flare–mediated tight junction remodeling
Authors: Craig Zie , Arnold Torey R. , Walworth Kelsey , Walkon Alexander , Miller Ann L.
Published: January 2025

To preserve barrier function, cell-cell junctions must dynamically remodel during cell shape changes. We have previously described a rapid tight junction repair pathway characterized by local, transient activations of RhoA, termed “Rho flares,” which repair leaks in tight junctions via promoting local actomyosin-mediated junction remodeling. In this pathway, junction elongation is a mechanical trigger that initiates RhoA activation through an influx of intracellular calcium and recruitment of p115RhoGEF. However, mechanisms that tune the level of RhoA activation and Myosin II contractility during the process remain uncharacterized. Here, we show that the scaffolding protein Anillin localizes to Rho flares and regulates RhoA activity and actomyosin contraction at flares. Knocking down Anillin results in Rho flares with increased intensity but shorter duration. These changes in active RhoA dynamics weaken downstream F-actin and Myosin II accumulation at the site of Rho flares, resulting in decreased junction contraction. Consequently, tight junction breaks are not reinforced following Rho flares. We show that Anillin-driven RhoA regulation is necessary for successfully repairing tight junction leaks and protecting junctions from repeated barrier damage. Together, these results uncover a novel regulatory role for Anillin during tight junction repair and barrier function maintenance.
Introduction: Listening Intersectionally to the Chocolate City
Authors: Martin Allie
Published: January 2025

The introduction explores the theoretical and historical framing for the rest of the book. In this chapter the author outlines the history of gentrification and Black life in DC, as well as introducing the theoretical framework that undergirds the book, “intersectional listening.” Intersectional listening is a theoretical approach that considers sound to be a speculative method, considering a multiple of axes of identity and being. This kind of listening practice is intended to support the complexity of stories about gentrification and sound in Washington, DC. In doing so, the chapter also considers the emancipatory potential of listening to gentrification in DC.
Toward a comprehensive understanding of the phenological responses of non-native plants to climate warming: a review
Authors: Dawson-Glass Emma , Schiafo Rory , Miller Chelsea N , Kuebbing Sara E , Stuble Katharine L
Published: January 2025

Background

Plants often shift their phenology in response to climate warming, with potentially important ecological consequences. Relative differences in the abilities of native and non-native plants to track warming temperatures by adjusting their phenologies could have cascading consequences for ecosystems. Our general understanding of non-native species leads us to believe these species may be more phenologically sensitive than native species, but evidence for this has been mixed, likely due, in part, to the myriad of diverse ecological contexts in which non-natives have been studied.

Scope

Here, we review the current state of knowledge on non-native plant phenological responses to climate warming. From observational and experimental studies, we synthesize: (1) the ways in which non-native plant phenology shifts with increased temperature, (2) the relative differences between natives and non-natives in phenological timing and sensitivity to warming, (3) the contingencies driving variable non-native phenological responses to warming, and (4) the ecological consequences of warming-induced phenological shifts in non-natives.

Conclusions

Early-season phenophases tend to advance with warming, sometimes (but not always) more so in non-native species relative to native species. Late-season phenophases, on the other hand, tend to be more variable: advancing, delaying, or remaining unchanged. Similarly, relative differences in phenological sensitivity between native and non-native plants were less consistent for late-season phenophases. However, our ability for inference is limited by the scope of studies done to date, which best represent temperate ecosystems in the Northern Hemisphere. We found phenological shifts in non-native species to be driven by various factors, including their evolutionary histories and the environmental context of the invaded system. Shifts in non-native phenologies result in varied ecological consequences, from shifting demographics of the non-native species themselves to changes in ecosystem level processes such as carbon cycling. Additional study addressing key gaps is vital to improving understanding of non-native phenological responses to warming.
Introducing TEC-LncMir for prediction of lncRNA-miRNA interactions through deep learning of RNA sequences
Authors: Yang Tingpeng , He Yonghong , Wang Yu
Published: January 2025

The interactions between long noncoding RNA (lncRNA) and microRNA (miRNA) play critical roles in life processes, highlighting the necessity to enhance the performance of state-of-the-art models. Here, we introduced TEC-LncMir, a novel approach for predicting lncRNA-miRNA interaction using Transformer Encoder and convolutional neural networks (CNNs). TEC-LncMir treats lncRNA and miRNA sequences as natural languages, encodes them using the Transformer Encoder, and combines representations of a pair of microRNA and lncRNA into a contact tensor (a three-dimensional array). Afterward, TEC-LncMir treats the contact tensor as a multi-channel image, utilizes a four-layer CNN to extract the contact tensor’s features, and then uses these features to predict the interaction between the pair of lncRNA and miRNA. We applied a series of comparative experiments to demonstrate that TEC-LncMir significantly improves lncRNA-miRNA interaction prediction, compared with existing state-of-the-art models. We also trained TEC-LncMir utilizing a large training dataset, and as expected, TEC-LncMir achieves unprecedented performance. Moreover, we integrated miRanda into TEC-LncMir to show the secondary structures of high-confidence interactions. Finally, we utilized TEC-LncMir to identify microRNAs interacting with lncRNA NEAT1, where NEAT1 performs as a competitive endogenous RNA of the microRNAs’ targets (mRNAs) in brain cells. We also demonstrated the regulatory mechanism of NEAT1 in Alzheimer’s disease via transcriptome analysis and sequence alignment analysis. Overall, our results demonstrate the effectivity of TEC-LncMir, suggest a potential regulation of miRNAs by NEAT1 in Alzheimer’s disease, and take a significant step forward in lncRNA-miRNA interaction prediction.
TransBic: bucket trend-preserving biclustering for finding local and interpretable expression patterns
Authors: Li Jing , Mei Qinglin , Yang Chaoxia , Zhu Naibo , Li Guojun
Published: January 2025

Biclustering has emerged as a promising approach for analyzing high-dimensional expression data, offering unique advantages in uncovering localized co-expression patterns that traditional clustering methods often miss and thus facilitating advancements in complex disease research and other biomedical applications. However, state-of-the-art methods identify distinct patterns at the expense of losing information about specific patterns, some of which have been used to define cancer subtypes or reflect the progression of a disease or cellular processes. Additionally, these methods exhibit poor effectiveness in noisy environments. To address these limitations, we propose the bucket trend-preserving (BTP) pattern, a novel generalization of existing patterns. And we have developed an algorithm, TransBic, to extract significant biclusters of BTP-patterns. Specifically, TransBic transforms the problem into identifying common multipartite acyclic tournament subdigraphs shared by distinct subsets of acyclic tournament digraphs derived from a given expression matrix. Compared with prominent tools, TransBic demonstrates superior performance in identifying biclusters of all non-row-constant patterns, especially under noise and data fluctuations. Furthermore, TransBic successfully identifies the most disease-related pathways for type 2 diabetes (T2D), colorectal cancer, hepatocellular carcinoma, and breast cancer, outperforming other tools in this regard. Different from previous generalizations, BTP-patterns capture specific up-regulation and down-regulation dynamics. Through targeted analysis of BTP-patterns in T2D expression data, TransBic uncovers biological processes affected by disease risk factors, extending the application of trend-preserving biclustering in expression data analysis.
Vascraft: new decellularized and re-endothelialized human vascular graft produced by tissue engineering for use in arterial bypass
Authors: Iraola Picornell G , Gálvez-Montón C , Onetti Y , Martorell J , López-Puerto L , Savio A , Castells-Sala C , Muñoz Guijosa C
Published: January 2025

Introduction

Small-diameter vascular grafts are crucial for patients undergoing coronary artery bypass surgery. Inherent comorbidities and the absence of optimal autologous vessels have prompted the development of vascular grafts through tissue engineering. The objective of the study is to develop a human biological substitute, VasCraft, for use as a coronary bypass graft.

Methods

VasCraft is an inter-institutional project carried out in four phases (F1–F4) for the design, development, and production of the bioimplant.F1: Decellularization of human cadaveric saphenous veins. The optimal decellularization protocol was identified by evaluating extracellular matrix (ECM) preservation, residual DNA content, morphohistological structure, and cytotoxicity.F2: Reendothelialization using endothelial cells derived from Wharton’s jelly mesenchymal stem cells (EC-MSC, WJ) in 3D bioreactors.F3: Generation of an Advanced Therapy Medicinal Product (ATMP) under Good Manufacturing Practice (GMP) conditions.F4: Pre-clinical validation of the VasCraft ATMP in the femoro-femoral position in a porcine model. Graft implantation was monitored fluoroscopically, and structural and inflammatory assessments were performed at 30 days post-implantation.

Results

Eleven decellularization protocols were tested. All protocols achieved a DNA concentration of less than 50 ng/mg of dry tissue. Protocol 1 was selected due to its high preservation of the morphology and ECM of the decellularized vein and the low cytotoxicity of the decellularization reagents. Additionally, a 3D bioreactor was developed to facilitate the recellularization of grafts with EC-MSC, WJ under continuous flow conditions.

Conclusion

The VasCraft bioimplant aims to solve an unmet need in the development of artificial vascular grafts. Phases F1 and F2 are well underway, with plans to move into Phases F3 and F4 in the coming months.
Temporal study of myocardial infarction to optimize the application of cardiosphere-derived cells’ secretome as a therapeutic strategy
Authors: Pulido Fresneda M , de Pedro M Á , Álvarez V , Marchena A M , Sánchez-Margallo F M , López E , Crisóstomo Ayala V , Báez Díaz C
Published: January 2025

Introduction

Myocardial infarction (MI) initiates an acute inflammatory response that is crucial for heart repair. However, an exaggerated inflammatory response can lead to adverse left ventricular remodeling and heart failure. The secretome of cardiosphere-derived cells (CDCs) offers promising immunomodulatory properties. This study seeks to determine the optimal timing for CDC secretome application by evaluating CD163 expression in monocytes and plasma levels post-MI to maximize its immunomodulatory properties.

Methods

CD163 expression in monocytes was evaluated under basal conditions and after MI at 24, 48, 72 hours, and one week post-MI. Plasma protein levels were also assessed at the same time points.

Results

The results indicate a decrease in CD163 expression in monocytes immediately following MI, with a progressive increase observed over the subsequent 72 hours. Plasma protein analysis revealed elevated levels of TNF-α and IL-6 within the first 24 hours post-MI, which then gradually declined. These findings suggest that the inflammatory response is most acute within the first 24 hours post-MI, characterized by high pro-inflammatory cytokine levels and reduced CD163 expression.

Conclusion

The application of CDC-derived secretome treatment could be more beneficial during the first 24 hours post-MI. This study highlights the importance of timing in the application of CDC-based therapies to optimize their immunomodulatory effects and improve outcomes in MI patients.
Artificial intelligence applications for learning in robotic surgery
Authors: Caballero Jorna D , Sánchez Margallo J A , Sánchez Margallo F M
Published: January 2025

Introduction

Robot-assisted surgery (RAS) has become the standard surgical technique in several specialties due to its many advantages. Furthermore, artificial intelligence (AI) has seen an exponential increase in its applications over recent years, leading to the development of numerous algorithms designed to assist in decision support. The primary objective of this study is to evaluate the current applications of AI in the learning process of RAS.

Methods

An exhaustive search was conducted in various scientific databases, including PubMed, Scopus, and WoS. A set of studies that met the search criteria was selected, and from these, the key current applications of AI in learning in RAS were extracted.

Results

The key current applications of AI in learning in RAS include:Providing feedback to surgeons through algorithms that assist in improving the surgical procedure, offering virtual assistants with useful recommendations, and highlighting common errors.Enhancing the realism of simulation textures, thereby improving the quality of visual environments.Planning optimal trajectories for learning in laparoscopic activities, automating trajectory calculation from preoperative imaging studies.Adapting and optimizing the learning process by self-adjusting based on the surgeon’s progress, common errors, strengths, and weaknesses.

Conclusion

AI applications in learning for RAS remain an evolving research field, with significant potential for future advancements. The synergy between technical and clinical aspects offers exciting opportunities for enhancing surgical training.
Cell-type-specific networks during hippocampal seizures at the micro- and macroscale
Authors: Wang Jiaoyang , Yan Jiaqing , Li Donghong , He Shipei , Li Xiaonan , Xing Yue , Lai Huanling , Gui Yue , Zhang Nannan , Huang Wenyao , Yang Xiaofeng
Published: January 2025

Epilepsy is a network disorder, involving neural circuits at both the micro- and macroscale. While local excitatory-inhibitory imbalances are recognized as a hallmark at the microscale, the dynamic role of distinct neuron types during seizures remain poorly understood. At the macroscale, interactions between key nodes within the epileptic network, such as the central median thalamic nucleus (CMT), are critical to the, hippocampal epileptic process. However, precise mechanisms underlying these interactions remain unclear. In this study, we investigated the microcircuit dynamics within the seizure onset zone and secondary spreading regions, as well as the network connectivity between the hippocampus and the CMT, using a 4-aminopyridine (4-AP) induced hippocampal seizure model.

Rats were allocated into three experimental groups. The first group used a 3D tetrode array to monitor hippocampal seizure activity and microcircuit dynamics, including seizure propagation across the macroscale network. In the second group, a chemical lesion was induced in the CMT to assess its impact on hippocampal seizures. In the third group, chemogenetic techniques were used to selectively suppress pyramidal neurons in the CMT and observe changes in neural network connectivity between the CMT and hippocampus during seizures. Offline single-unit sorting was performed using KlustaKwik and further analysis was conducted with CellExplorer.

At seizure onset, the narrow interneurons exhibited increased firing rates, initiating recruitment of other neurons, followed by increased activity in pyramidal neuron. Wide interneurons also showed heightened activity subsequent to pyramidal neurons. Interneurons played a more prominent role in the microcircuit during seizures compared to baseline. The CMT exhibited characteristic seizure activity and a decrease in narrow interneuron activity, whereas the cortex did not display seizure activity during hippocampal seizures. Lesioning the CMT resulted in the loss of the tonic component of hippocampal seizures and reduced overall neuronal activity in the hippocampal. Selective suppression of CMT pyramidal neurons resulted in shortened hippocampal seizures while preserving the tonic component. Narrow interneuron activity remained unchanged, while pyramidal neuron and wide interneuron activity significantly decreased.

Our findings underscore the critical role of interneurons in the micronetwork of the seizure onset zone and secondary spreading region. Narrow interneurons were particularly vital in seizure initiation, whereas wide interneurons may contribute to seizure termination within the onset zone but not in the secondary spreading region. Pyramidal neurons in the CMT influence hippocampal seizures by modulating of both hippocampal pyramidal neurons and wide interneurons.