Miracle-dz/UniFAR-FTUs huggingface dataset:
Ouabain’s Influence on TRPV4 Channels of Epithelial Cells: An Exploration of TRPV4 Activity, Expression, and Signaling Pathways

Ouabain, a substance originally obtained from plants, is now classified as a hormone because it is produced endogenously in certain animals, including humans. However, its precise effects on the body remain largely unknown. Previous studies have shown that ouabain can influence the phenotype of epithelial cells by affecting the expression of cell–cell molecular components and voltage-gated potassium channels. In this study, we conducted whole-cell clamp assays to determine whether ouabain affects the activity and/or expression of TRPV4 channels. Our findings indicate that ouabain has a statistically significant effect on the density of TRPV4 currents (dITRPV4), with an EC50 of 1.89 nM. Regarding treatment duration, dITRPV4 reaches its peak at around 1 h, followed by a subsequent decline and then a resurgence after 6 h, suggesting a short-term modulatory effect related to on TRPV4 channel activity and a long-term effect related to the promotion of synthesis of new TRPV4 channel units. The enhancement of dITRPV4 induced by ouabain was significantly lower in cells seeded at low density than in cells in a confluent monolayer, indicating that the action of ouabain depends on intercellular contacts. Furthermore, the fact that U73122 and neomycin suppress the effect caused by ouabain in the short term suggests that the short-term induced enhancement of dITRPV4 is due to the depletion of PIP2 stores. In contrast, the fact that the long-term effect is inhibited by PP2, wortmannin, PD, FR18, and IKK16 suggests that cSrc, PI3K, Erk1/2, and NF-kB are among the components included in the signaling pathways.
Pure optical detection photoacoustic microfluidic chip for studying two-phase flow droplets

A simple, low-cost and new all-optical photoacoustic droplet microfluidic detection system is proposed by combining the pure optical photoacoustic detection technology based on polarized light reflection with droplet microfluidic chip technology. In this work, we first use Matlab and Comsol to carry out theoretical calculation and simulation of polarized light reflection, the theory and simulation results are highly consistent. In the experiment, a simple and practical microfluidic chip was prepared by the molding method, and the application range of the polarization based pure light photoacoustic microfluidic detection technology was expanded. Firstly, the photoacoustic signals of black tape in microfluidic chips with different pipe heights are tested to verify the feasibility of our system. Then the suitable flow rate and the flow rate ratio of the two-phase flow were adjusted, and a large number of homogeneous droplets were generated. Methylene blue as one of the samples, the photoacoustic signal of methylene blue droplets was detected. The results show that the polarized light based total internal reflection optical system combined with microfluidic chips has great application potential in microfluidic detection.
How the latent geometry of a biological network provides information on its dynamics: the case of the gene network of chronic myeloid leukaemia

Background: The concept of the latent geometry of a network that can be represented as a graph has emerged from the classrooms of mathematicians and theoretical physicists to become an indispensable tool for determining the structural and dynamic properties of the network in many application areas, including contact networks, social networks, and especially biological networks. It is precisely latent geometry that we discuss in this article to show how the geometry of the metric space of the graph representing the network can influence its dynamics. Methods: We considered the transcriptome network of the Chronic Myeloid Laeukemia K562 cells. We modelled the gene network as a system of springs using a generalization of the Hooke’s law to n-dimension (n ≥ 1). We embedded the network, described by the matrix of spring’s stiffnesses, in Euclidean, hyperbolic, and spherical metric spaces to determine which one of these metric spaces best approximates the network’s latent geometry. We found that the gene network has hyperbolic latent geometry, and, based on this result, we proceeded to cluster the nodes according to their radial coordinate, that in this geometry represents the node popularity. Results: Clustering according to radial coordinate in a hyperbolic metric space when the input to network embedding procedure is the matrix of the stiffnesses of the spring representing the edges, allowed to identify the most popular genes that are also centres of effective spreading and passage of information through the entire network and can therefore be considered the drivers of its dynamics. Conclusion: The correct identification of the latent geometry of the network leads to experimentally confirmed clusters of genes drivers of the dynamics, and, because of this, it is a trustable mean to unveil important information on the dynamics of the network. Not considering the latent metric space of the network, or the assumption of a Euclidean space when this metric structure is not proven to be relevant to the network, especially for complex networks with hierarchical or modularised structure can lead to unreliable network analysis results.
The Role of Apolipoproteins in the Commonest Cancers: A Review

Simple Summary Apolipoproteins (APOs) are crucial components in our blood that are responsible for fat management. Recent scientific discoveries suggest a provocative link between APOs and a range of cancers, including, but not limited to, breast, lung, and prostate cancer. The specific role of some APOs in causing cancer remains enigmatic. In this review, we summarize evidence from the literature supporting the potential involvement of APOs in the onset of cancer. We also highlight promising avenues for treatment through the inhibition of APOs. Abstract Apolipoproteins (APOs) are vital structural components of plasma lipoproteins that are involved in lipid metabolism and transport. Recent studies have reported an association between apolipoprotein dysregulation and the onset of a variety of human cancers; however, the role of certain APOs in cancer development remains unknown. Based on recent work, we hypothesize that APOs might be involved in the onset of cancer, with a focus on the most common cancers, including breast, lung, gynecological, colorectal, thyroid, gastric, pancreatic, hepatic, and prostate cancers. This review will focus on the evidence supporting this hypothesis, the mechanisms linking APOs to the onset of cancer, and the potential clinical relevance of its various inhibitors.
An Exploration of Tri-Axial Accelerometers in Assessing the Therapeutic Efficacy of Constraint-Induced Movement Therapy in Children with Unilateral Cerebral Palsy

This study aimed to elucidate the role of tri-axial accelerometers in assessing therapeutic interventions, specifically constraint-induced movement therapy (CIMT), in children with unilateral cerebral palsy (UCP). The primary focus was understanding the correlation between the actigraphy metrics recorded during CIMT sessions and the resultant therapeutic outcomes. Children with UCP, aged between 4 and 12 years, participated in this study from July 2021 to December 2022. In conjunction with in-clinic sessions, during which participants wore tri-axial accelerometers on both limbs, we analyzed actigraphy data over three days of routine activities pre- and post-CIMT. While not all metrics derived from the accelerometers indicated significant improvements post-intervention, there was a clear trend towards a more balanced usage of both limbs, particularly evident in Axis 3, associated with vertical movement (p = 0.017). Additionally, a discernible correlation was observed between changes in the magnitude ratio derived from actigraphy data during CIMT (Δweek3–week1) and variations in traditional assessments pre- and post-intervention (ΔT0–T1), specifically the Assisting Hand Assessment grasp and release. Using tri-axial accelerometers has helped clarify the potential impacts of CIMT on children with UCP. The preliminary results suggest a possible link between actigraphy metrics taken during CIMT and the subsequent therapeutic outcomes determined by standardized tests.
Cardiovascular Prognosis in Patients with Peripheral Artery Disease and Approach to Therapy

Peripheral artery disease (PAD), the pathophysiologic narrowing of the arterial blood vessels of the lower limbs due to atherosclerosis, is estimated to affect more than 200 million people worldwide and its prevalence ranges from 0.9 to 31.3% in people aged ≥50 years. It is an established marker of systemic obstructive atherosclerosis, which depicts patients at higher risk of myocardial infarction and stroke, due to the involvement of coronary and cerebral arteries in the atherosclerotic process. Therefore, identifying PAD, particularly in patients with coronary artery disease, is important to assess the cardiovascular risk score and implement specific therapies and prevention strategies. Since PAD emerged as an important clinical cardiovascular predictor, even more than other typical cardiovascular risk factors, an aggressive strategy to identify and treat PAD patients should be pursued by general practitioners, cardiologists, and vascular surgeons; similarly, preventive strategies should be implemented to improve prognosis and outcomes, particularly in patients suffering from both coronary artery disease and PAD. In this review, we describe the pathophysiology, including limb vasoconstriction after coronary angioplasty, the diagnosis of PAD, prognosis according to cardiovascular events, coronary artery disease, and heart failure. Furthermore, a large section of this review is on management, which spans from risk factors’ modification to antithrombotic therapy, and revascularization is provided. Finally, considerations about newer therapeutic options for the “desert foot” are discussed, including gene therapy.
Hepadnavirus Infection in a Cat with Chronic Liver Disease: A Multi-Disciplinary Diagnostic Approach

Simple Summary Domestic cat hepadnavirus (DCH) is a newly identified virus, similar to the hepatitis B virus (HBV). The pathogenicity of DCH in its host needs further investigation. In this report, a case of DCH infection was described in a cat with clinical signs and serum chemistry markers indicative of chronic hepatic disease using a multi-disciplinary diagnostic approach, combining clinical, pathological, virological, and serological information, mirroring the diagnostic approach used for HBV in human patients. Improving the intra-vitam diagnostics for DCH will be useful in developing specific treatment and control strategies. Abstract A 3-year-old female stray, shorthair cat, with clinical signs and serum chemistry markers indicative of hepatic disease, was diagnosed with domestic cat hepadnavirus (DCH) infection. Coupling molecular and serological data, the infection was seemingly contextualized into a chronic phase, since IgM anti-core antibodies, a marker of early-stage Hepatitis B Virus (HBV) infection, were not detected. However, the cat possessed IgG anti-core, a common indicator of chronic HBV infection in human patients and did not show seroconversion to the anti-DCH surface antigen, considered protective during HBV infection and associated with long-term protective immunity. On genome sequencing, the DCH strain showed 98.3% nucleotide identity to strains previously identified in Italy.
Optimization of Artificial Neural Network Transfer Function for Hydrological Modelling: A Review

Hydrological modeling is crucial for understanding and predicting water-related processes. Artificial Neural Networks (ANN) have emerged as powerful tools for this purpose, utilizing the structure and functions of the biological brain to model complex patterns and forecast hydrological issues. Hence, this study reviews the optimization of artificial neural networks for hydrological modeling. Data obtained reveals that the choice of transfer function significantly impacts the performance of hydrological models, and optimizing it can improve accuracy, precision, and reliability. More so, an optimized transfer function provides interpretability, aligning with the physical understanding of the hydrological system and making the model outputs more meaningful. By optimizing artificial neural network transfer functions and employing other optimization strategies, hydrological models can better simulate and predict water-related processes. This advancement can lead to more effective water resource management and decision-making.
Optimizing measurement configuration for x-ray critical dimension metrology based on condition number

In X-ray critical dimension metrology (XCD), it is a common practice to select an appropriate measurement configuration, including incidence angle, azimuth angle, exposure time, etc., to improve measurement results. This is crucial as the quality of the obtained signature is impacted not just by the instrument's precision, but also by the specific chosen measurement configuration. This is known as the measurement configuration optimization (MCO) problem. This paper proposes a general MCO method based on the theory of error propagation and error estimation techniques using condition numbers. Finally, the MCO problem in XCD is framed as optimizing the "max-min" condition number of the coefficient matrix within the context of linear error estimation. The proposed method is showcased on "virtual experiments" conducted via simulations to determine the optimal combinations of rotation angles along two coordinate axes. The method's feasibility is substantiated through a comparison with the distributions of parameter uncertainty. The results suggest that the proposed method holds promise as an alternative approach for comprehensive evaluation in the context of the MCO problem in XCD and various measurement scenarios.
Significance of kernel moisture content in determination of Hagberg Falling Number in wheat

The effect of early termination of kernel filling (early harvest) on the Hagberg Falling Number (HFN) was investigated over a four-year period. Selected South African wheat cultivars were harvested at different stages of kernel development, determined by kernel moisture content (KMC). HFN was determined at each stage of development. Difficulty in obtaining sufficient data points at each KMC necessitated the creation of two KMC ranges: 10–13.1% and 13.2–16.9%. Alpha-amylase activity was determined for each of the cultivars at the various KMCs during the 2003/04 and 2004/05 seasons. Data generated with three wheat cultivars (Elands, Gariep and Tugela-DN) over a four-year period indicated that the effect of KMC with harvest on the HFN of wheat is season dependant. Tugela-DN produced significantly (P≤0.05) higher HFN at the lower KMC range (10–13.1%) for two (2001/02 and 2004/05) of the four seasons during this study. Gariep showed similar results to Tugela-DN for the 2001/02 season. For Elands, the HFN remained constant over the four seasons at the various KMCs. Although there were no statistically significant differences between cultivars, it was observed that higher HFNs occurred at the lower KMC range. The effect of alpha-amylase activity at the KMC investigated in the study could not be successfully linked to reduced HFN measured at the higher KMC range. Late maturity alpha-amy-lase (LMA) was also excluded as a possible reason for reduced HFN. The current study indicated that some cultivars are prone to produce higher HFNs at lower KMCs but that the effect is limited to specific seasons.
Three-segment fiber transmission dispersion management method for femtosecond lasers in terahertz time-domain spectroscopy systems

In terahertz (THz) time-domain spectroscopy, the excitation of THz waves by fiber optic transmission of femtosecond pulsed lasers can provide great convenience for nondestructive testing of large and medium-sized aircraft. However, due to the high peak power characteristics of the femtosecond laser, the pulse spreading and distortion caused by fiber dispersion and nonlinearity can seriously affect the output laser pulse quality and the excitation of THz waves. In this paper, a three-segment femtosecond laser transmission scheme using asymmetric dual-core fiber (ADCF)-single-mode fiber (SMF)-dispersion-compensated fiber (DCF) is proposed. The simulation study results show that the strong dispersion using a 2.8-cm-long ADCF can reduce the 1 kW peak power to 8.03 W and extend the 50 fs pulse width to 3.74 ps, respectively. The spreading pulse can be restored to the peak power of 987.20 W and pulse width of 51.80 fs after the 10m-long SMF and then transmitted by the 66.9 cm-long DCF. This shows that the proposed femtosecond laser transmission scheme can achieve good pulse recompression and simultaneous recovery of pulse waveform and power, which lays the foundation for the construction of further THz time-domain spectroscopy systems using longer fibers for femtosecond laser transmission.
Adaptive PID Controller for Active Suspension Using Radial Basis Function Neural Networks

Suspension systems are critical parts of modern cars. In this study, a radial basis function neural networks-based adaptive PID optimal method is presented for vehicle suspension systems. To avoid the shortcoming that the parameters of PID control are determined by experience in the traditional method, to avoid the local optimality problem and the slow rate of convergence in the modern intelligence method, radial basis function neural networks are applied in this paper. First, a quarter-car suspension is presented. Then, the radial basis function neural networks are employed to obtain the parameters of proportional, integral, and derivate components that are used in PID control. The simulation is conducted later. Next, a comparison of the progress between uncontrolled suspension, the radial basis function-based PID control, the H∞ control method, and the FPM control method is presented. According to the simulation results, the proposed control method performs better than the others. This contrast reveals the superior characteristics of the suggested control strategy.
Threshold of Sediment Motion in Coastal Environments

The threshold of sediment motion is one of the most fundamental quantities for sediment transport and dynamics. It is especially important in coastal and shelf seas, because the wave and current flows are often close to threshold, so that predictions of sediment transport rates depend strongly on the value of threshold bed shear-stress used. The present research extends the work of Shields and others in the following ways: (a) a simple analytical formula has been fitted to the traditional hand-drawn Shields curve for threshold bed shear-stress; (b) a correction has been applied to make the curve fit the experimental data better for very fine grain sizes; (c) the formula has been tested against a large set of data for not only currents, but also waves and combined waves and currents; (d) the formula has been extended from the horizontal-bed case to account for the effect of longitudinally and/or laterally sloping beds on the threshold bed shear-stress. The result is a unified expression to predict the threshold of motion of sands and gravels in coastal environments influenced by waves and currents on beds of any slope.
Enriching the Linguistic Concept Development of English Undergraduates Through Covid-Induced Blended Learning Practices: A Design- Based Research Perspective

This paper investigates the incorporation of blended-learning instructional design into an academia-level linguistic course of Contrastive Phonetics and Phonology as an effective and localised measure to suit the shift from the physical classroom to online learning during the COVID-19 pandemic. This course followed the principle of design-based learning. The research examines the ensuing revision of pedagogical intervention on three subsequent course iterations, taking place both under pandemic restrictions and in the post-pandemic reality, as well as the participants’ opinions and attitudes towards the changed instructional paradigm. Using a mixed quantitative and qualitative methodology, the data were collected from the participants’ final exam marks, their comments in course evaluation surveys and from semi-structured interviews. The findings reveal the multi-aspectual effectiveness of the hybrid design and the participants’ favourable attitude towards the revised course design, thus proving that this could be a new, post-pandemic course formula.
An Ecological Approach to Sustainability Development: Applications of Ecological Anthropology and Organizational Ecology-Sociology to Accounting Education

Sustainability is a subject that has been researched by several interdisciplinary subjects to study the business environment in addressing economic and social development. Anthropology and sociology literature have examined sustainability within the context of evolutionary change processes. The application of the ecological framework in anthropology and sociology is an integrated approach that studies sustainability within the broader context of the environment, and business and society. Ecological anthropology has examined how cultural and social forces have evolved in ecological and land ethics in business education. Organizational ecology has related the resource-based transaction cost approach for the integration of sustainability into the accounting curriculum. The examples from sustainability accounting education from both the emerging and developed economies support the premise that when sustainability is integrated across the accounting curriculum, it can positively influence the attitudes of students, accounting professionals and policy makers. The purpose of this paper is to extend the ecology of sociological and anthropological approaches to study the integration of sustainability into the accounting curriculum in auditing and financial accounting courses, and the professional accounting community.
Akt, IL-4, and STAT Proteins Play Distinct Roles in Prostaglandin Production in Human Follicular Dendritic Cell-like Cells

This study aimed to explore the role of Akt protein in the induction and inhibition of prostaglandin (PG) in human follicular dendritic cell (FDC)-like cells. FDC-like cells and B cells were isolated from human tonsils. PG production was assessed using enzyme immunoassay, while the upstream cyclooxygenase-2 (COX-2) protein levels were measured using immunoblotting with FDC-like cells transfected with Akt siRNA to analyze the impact of Akt knockdown. The COX-2 expression and PG production induced with IL-1β were significantly increased by Akt knockdown. However, IL-1β did not significantly alter either total or phosphorylated Akt protein levels. Akt knockdown resulted in the augmentation of COX-2 expression induced by B cells, although the addition of B cells did not significantly modulate both total and phosphorylated Akt proteins. In contrast, IL-4 specifically exhibited a potent inhibitory effect on COX-2 protein induction and PG production via STAT6. The inhibitory activity of IL-4 was not hampered by Akt knockdown. Interestingly, COX-2 expression levels induced with IL-1β were markedly modulated with STAT1 and STAT3 knockdown. STAT1 silencing resulted in further augmentation of COX-2, whereas STAT3 silencing prohibited IL-1β from stimulating COX-2 expression. The current results suggest that Akt, IL-4, and STAT1 play inhibitory roles in PG production in FDC-like cells and expand our knowledge of the immune inflammatory milieu.