Pathway of Actin Folding Directed by the Eukaryotic Chaperonin TRiC.

The hetero-oligomeric chaperonin of eukarya, TRiC, is required to fold the cytoskeletal protein actin. The simpler bacterial chaperonin system, GroEL/GroES, is unable to mediate actin folding. Here, we use spectroscopic and structural techniques to determine how TRiC promotes the conformational progression of actin to the native state. We find that actin fails to fold spontaneously even in the absence of aggregation but populates a kinetically trapped, conformationally dynamic state. Binding of this frustrated intermediate to TRiC specifies an extended topology of actin with native-like secondary structure. In contrast, GroEL stabilizes bound actin in an unfolded state. ATP binding to TRiC effects an asymmetric conformational change in the chaperonin ring. This step induces the partial release of actin, priming it for folding upon complete release into the chaperonin cavity, mediated by ATP hydrolysis. Our results reveal how the unique features of TRiC direct the folding pathway of an obligate eukaryotic substrate.

GroEL Ring Separation and Exchange in the Chaperonin Reaction.

The bacterial chaperonin GroEL and its cofactor, GroES, form a nano-cage for a single molecule of substrate protein (SP) to fold in isolation. GroEL and GroES undergo an ATP-regulated interaction cycle to close and open the folding cage. GroEL consists of two heptameric rings stacked back to back. Here, we show that GroEL undergoes transient ring separation, resulting in ring exchange between complexes. Ring separation occurs upon ATP-binding to the trans ring of the asymmetric GroEL:7ADP:GroES complex in the presence or absence of SP and is a consequence of inter-ring negative allostery. We find that a GroEL mutant unable to perform ring separation is folding active but populates symmetric GroEL:GroES2 complexes, where both GroEL rings function simultaneously rather than sequentially. As a consequence, SP binding and release from the folding chamber is inefficient, and E. coli growth is impaired. We suggest that transient ring separation is an integral part of the chaperonin mechanism.

A universal description of stochastic oscillators.

Many systems in physics, chemistry, and biology exhibit oscillations with a pronounced random component. Such stochastic oscillations can emerge via different mechanisms, for example, linear dynamics of a stable focus with fluctuations, limit-cycle systems perturbed by noise, or excitable systems in which random inputs lead to a train of pulses. Despite their diverse origins, the phenomenology of random oscillations can be strikingly similar. Here, we introduce a nonlinear transformation of stochastic oscillators to a complex-valued function [Formula: see text](x) that greatly simplifies and unifies the mathematical description of the oscillator's spontaneous activity, its response to an external time-dependent perturbation, and the correlation statistics of different oscillators that are weakly coupled. The function [Formula: see text] (x) is the eigenfunction of the Kolmogorov backward operator with the least negative (but nonvanishing) eigenvalue λ1 = µ1 + iω1. The resulting power spectrum of the complex-valued function is exactly given by a Lorentz spectrum with peak frequency ω1 and half-width µ1; its susceptibility with respect to a weak external forcing is given by a simple one-pole filter, centered around ω1; and the cross-spectrum between two coupled oscillators can be easily expressed by a combination of the spontaneous power spectra of the uncoupled systems and their susceptibilities. Our approach makes qualitatively different stochastic oscillators comparable, provides simple characteristics for the coherence of the random oscillation, and gives a framework for the description of weakly coupled oscillators.

PI(3,4,5)P3 Engagement Restricts Akt Activity to Cellular Membranes.

Protein kinase B/Akt regulates cellular metabolism, survival, and proliferation in response to hormones and growth factors. Hyperactivation of Akt is frequently observed in cancer, while Akt inactivation is associated with severe diabetes. Here, we investigated the molecular and cellular mechanisms that maintain Akt activity proportional to the activating stimulus. We show that binding of phosphatidylinositol-3,4,5-trisphosphate (PIP3) or PI(3,4)P2 to the PH domain allosterically activates Akt by promoting high-affinity substrate binding. Conversely, dissociation from PIP3 was rate limiting for Akt dephosphorylation, dependent on the presence of the PH domain. In cells, active Akt associated primarily with cellular membranes. In contrast, a transforming mutation that uncouples kinase activation from PIP3 resulted in the accumulation of hyperphosphorylated, active Akt in the cytosol. Our results suggest that intramolecular allosteric and cellular mechanisms cooperate to restrict Akt activity to cellular membranes, thereby enhancing the fidelity of Akt signaling and the specificity of downstream substrate phosphorylation.

Colocalization by cross-correlation, a new method of colocalization suited for super-resolution microscopy.

BACKGROUND: A common goal of scientific microscopic imaging is to determine if a spatial correlation exists between two imaged structures. This is generally accomplished by imaging fluorescently labeled structures and measuring their spatial correlation with a class of image analysis algorithms known as colocalization. However, the most commonly used methods of colocalization have strict limitations, such as requiring overlap in the fluorescent markers and reporting requirements for accurate interpretation of the data, that are often not met. Due to the development of novel super-resolution techniques, which reduce the overlap of the fluorescent signals, a new colocalization method is needed that does not have such strict requirements. RESULTS: In order to overcome the limitations of other colocalization algorithms, I developed a new ImageJ/Fiji plugin, Colocalization by cross-correlation (CCC). This method uses cross-correlation over space to identify spatial correlations as a function of distance, removing the overlap requirement and providing more comprehensive results. CCC is compatible with 3D and time-lapse images, and was designed to be easy to use. CCC also generates new images that only show the correlating labeled structures from the input images, a novel feature among the cross-correlating algorithms. CONCLUSIONS: CCC is a versatile, powerful, and easy to use colocalization and spatial correlation tool that is available through the Fiji update sites. Full and up to date documentation can be found at https://imagej.net/plugins/colocalization-by-cross-correlation . CCC source code is available at https://github.com/andmccall/Colocalization_by_Cross_Correlation .

Detecting heart failure from B-mode ultrasound characterization of arterial pulse waves.

This study investigated the sensitivity and specificity of identifying heart failure with reduced ejection fraction (HFrEF) from measurements of the intensity and timing of arterial pulse waves. Previously validated methods combining ultrafast B-mode ultrasound, plane-wave transmission, singular value decomposition (SVD), and speckle tracking were used to characterize the compression and decompression ("S" and "D") waves occurring in early and late systole, respectively, in the carotid arteries of outpatients with left ventricular ejection fraction (LVEF) < 40%, determined by echocardiography, and signs and symptoms of heart failure, or with LVEF ≥ 50% and no signs or symptoms of heart failure. On average, the HFrEF group had significantly reduced S-wave intensity and energy, a greater interval between the R wave of the ECG and the S wave, a reduced interval between the S and D waves, and an increase in the S-wave shift (SWS), a novel metric that characterizes the shift in timing of the S wave away from the R wave of the ECG and toward the D wave (all P < 0.01). Receiver operating characteristics (ROCs) were used to quantify for the first time how well wave metrics classified individual participants. S-wave intensity and energy gave areas under the ROC of 0.76-0.83, the ECG-S-wave interval gave 0.85-0.88, and the S-wave shift gave 0.88-0.92. Hence the methods, which are simple to use and do not require complex interpretation, provide sensitive and specific identification of HFrEF. If similar results were obtained in primary care, they could form the basis of techniques for heart failure screening.NEW & NOTEWORTHY We show that heart failure with reduced ejection fraction can be detected with excellent sensitivity and specificity in individual patients by using B-mode ultrasound to detect altered pulse wave intensity and timing in the carotid artery.

Computational exploration of compounds in Xylocarpus granatum as a potential inhibitor of Plasmodium berghei using docking, molecular dynamics, and DFT studies.

Malaria remains a global health concern, with the emergence of resistance to the antimalarial drug atovaquone through cytochrome b (cyt b) being well-documented. This study was prompted by the presence of this mutation in cyt b to enable new drug candidates capable of overcoming drug resistance. Our objective was to identify potential drug candidates from compounds of Xylocarpus granatum by computationally assessing their interactions with Plasmodium berghei cyt b. Using computational methods, we modeled cyt b (GenBank: AF146076.1), identified the binding cavity, and analyzed the Ramachandran plot against cyt b. Additionally, we conducted drug-likeness and absorption, distribution, metabolism, excretion, and toxicity (ADMET) studies, along with density functional theory (DFT) analysis of the compounds. Molecular docking and molecular dynamics simulation (MDS) were used to evaluate the binding energy and stability of the cyt b-ligand complex. Notably, our investigation highlighted kaempferol as a promising compound due to its high binding energy of 7.67 kcal/mol among all X. granatum compounds, coupled with favorable pharmacological properties (ADMET) and antiprotozoal properties at Pa 0.345 > Pi 0.009 (PASS value). DFT analysis showed that kaempferol has an energy gap of 4.514 eV. MDS indicated that all tested ligands caused changes in bonding and affected the structural conformation of cyt b, as observed before MDS (0 ns) and after MDS (100 ns). The most notable differences were observed in the types of hydrogen bonds between 0 and 100 ns. Nevertheles, MDS results from a 100 ns simulation revealed consistent behavior for kaempferol across various parameters including root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), solvent-accessible surface area (SASA), molecular mechanics-Poisson Boltzmann surface area (MM-PBSA), and hydrogen bonds. The cyt b-kaempferol complex demonstrated favorable energy stability, as supported by the internal energy distribution values observed in principal component analysis (PCA), which closely resembled those of the atovaquone control. Additionally, trajectory stability analysis indicated structural stability, with a cumulative eigenvalue of 24.7 %. Dynamic cross-correlation matrix (DCCM) analysis revealed a positive correlation among catalytic cytochrome residues within the amino acid residues range 119-268. The results of our research indicate that the structure of kaempferol holds promise as a potential candidate against Plasmodium.

Mood regulation in euthymic patients with a history of antidepressant-induced mania.

INTRODUCTION: The use of antidepressants in bipolar disorder (BD) remains contentious, in part due to the risk of antidepressant-induced mania (AIM). However, there is no information on the architecture of mood regulation in patients who have experienced AIM. We compared the architecture of mood regulation in euthymic patients with and without a history of AIM. METHODS: Eighty-four euthymic participants were included. Participants rated their mood, anxiety and energy levels daily using an electronic (e-) visual analog scale, for a mean (SD) of 280.8(151.4) days. We analyzed their multivariate time series by computing each variable's auto-correlation, inter-variable cross-correlation, and composite multiscale entropy of mood, anxiety, and energy. Then, we compared the data features of participants with a history of AIM and those without AIM, using analysis of covariance, controlling for age, sex, and current treatment. RESULTS: Based on 18,103 daily observations, participants with AIM showed significantly stronger day-to-day auto-correlation and cross-correlation for mood, anxiety, and energy than those without AIM. The highest cross-correlation in participants with AIM was between mood and energy within the same day (median (IQR), 0.58 (0.27)). The strongest negative cross-correlation in participants with AIM was between mood and anxiety series within the same day (median (IQR), -0.52 (0.34)). CONCLUSION: Patients with a history of AIM have a different underlying mood architecture compared to those without AIM. Their mood, anxiety and energy stay the same from day-to-day; and their anxiety is negatively correlated with their mood.

DNA base order parameter determination without influence of chemical exchange.

Nuclear magnetic resonance (NMR) spectroscopy is a versatile tool used to investigate the dynamic properties of biological macromolecules and their complexes. NMR relaxation data can provide order parameters S2, which represent the mobility of bond vectors reorienting within a molecular frame. Determination of S2 parameters typically involves the use of transverse NMR relaxation rates. However, the accuracy in S2 determination can be diminished by elevation of the transverse relaxation rates through conformational or chemical exchange involving protonation/deprotonation or non-Watson-Crick base-pair states of nucleic acids. Here, we propose an approach for determination of S2 parameters without the influence of exchange processes. This approach utilizes transverse and longitudinal 13C chemical shift anisotropy (CSA) - dipole-dipole (DD) cross-correlation rates instead of 13C transverse relaxation rates. Anisotropy in rotational diffusion is taken into consideration. An application of this approach to nucleotide base CH groups of a uniformly 13C/15N-labeled DNA duplex is demonstrated.

Cross-correlation analysis of X-ray photon correlation spectroscopy to extract rotational diffusion coefficients.

Coefficients for translational and rotational diffusion characterize the Brownian motion of particles. Emerging X-ray photon correlation spectroscopy (XPCS) experiments probe a broad range of length scales and time scales and are well-suited for investigation of Brownian motion. While methods for estimating the translational diffusion coefficients from XPCS are well-developed, there are no algorithms for measuring the rotational diffusion coefficients based on XPCS, even though the required raw data are accessible from such experiments. In this paper, we propose angular-temporal cross-correlation analysis of XPCS data and show that this information can be used to design a numerical algorithm (Multi-Tiered Estimation for Correlation Spectroscopy [MTECS]) for predicting the rotational diffusion coefficient utilizing the cross-correlation: This approach is applicable to other wavelengths beyond this regime. We verify the accuracy of this algorithmic approach across a range of simulated data.

A-Mode Ultrasound Bladder Volume Estimation Algorithm Based on Wavelet Energy Ratio Adaptive Denoising.

Assessing bladder function is pivotal in urological health, with bladder volume a critical indicator. Traditional devices, hindered by high costs and cumbersome sizes, are being increasingly supplemented by portable alternatives; however, these alternatives often fall short in measurement accuracy. Addressing this gap, this study introduces a novel A-mode ultrasound-based bladder volume estimation algorithm optimized for portable devices, combining efficient, precise volume estimation with enhanced usability. Through the innovative application of a wavelet energy ratio adaptive denoising method, the algorithm significantly improves the signal-to-noise ratio, preserving critical signal details amidst device and environmental noise. Ultrasonic echoes were employed to acquire positional information on the anterior and posterior walls of the bladder at several points, with an ellipsoid fitted to these points using the least squares method for bladder volume estimation. Ultimately, a simulation experiment was conducted on an underwater porcine bladder. The experimental results indicate that the bladder volume estimation error of the algorithm is approximately 8.3%. This study offers a viable solution to enhance the accuracy and usability of portable devices for urological health monitoring, demonstrating significant potential for clinical application.

Accurate Localization of First and Second Heart Sounds via Template Matching in Forcecardiography Signals.

Cardiac auscultation is an essential part of physical examination and plays a key role in the early diagnosis of many cardiovascular diseases. The analysis of phonocardiography (PCG) recordings is generally based on the recognition of the main heart sounds, i.e., S1 and S2, which is not a trivial task. This study proposes a method for an accurate recognition and localization of heart sounds in Forcecardiography (FCG) recordings. FCG is a novel technique able to measure subsonic vibrations and sounds via small force sensors placed onto a subject's thorax, allowing continuous cardio-respiratory monitoring. In this study, a template-matching technique based on normalized cross-correlation was used to automatically recognize heart sounds in FCG signals recorded from six healthy subjects at rest. Distinct templates were manually selected from each FCG recording and used to separately localize S1 and S2 sounds, as well as S1-S2 pairs. A simultaneously recorded electrocardiography (ECG) trace was used for performance evaluation. The results show that the template matching approach proved capable of separately classifying S1 and S2 sounds in more than 96% of all heartbeats. Linear regression, correlation, and Bland-Altman analyses showed that inter-beat intervals were estimated with high accuracy. Indeed, the estimation error was confined within 10 ms, with negligible impact on heart rate estimation. Heart rate variability (HRV) indices were also computed and turned out to be almost comparable with those obtained from ECG. The preliminary yet encouraging results of this study suggest that the template matching approach based on normalized cross-correlation allows very accurate heart sounds localization and inter-beat intervals estimation.

Pulse Accumulation Approach Based on Signal Phase Estimation for Doppler Wind Lidar.

Coherent Doppler wind lidar (CDWL) uses transmitted laser pulses to measure wind velocity distribution. However, the echo signal of CDWL is easily affected by atmospheric turbulence, which can decrease the signal-to-noise ratio (SNR) of lidar. To improve the SNR, this paper proposes a pulse accumulation method based on the cross-correlation function to estimate the phase of the signal. Compared with incoherent pulse accumulation, the proposed method significantly enhances the correlation between signals from different periods to obtain high SNR gains that arise from pulse accumulation. Using simulation, the study evaluates the effectiveness of this phase estimation method and its robustness against noise in algorithms which analyze Doppler frequency shifts. Furthermore, a CDWL is developed for measuring the speed of an indoor motor turntable and the outdoor atmospheric wind field. The phase estimation method yielded SNR gains of 28.18 dB and 32.03 dB for accumulation numbers of 500 and 1500, respectively. The implementation of this method in motor turntable speed measurements demonstrated a significant reduction in speed error-averaging 9.18% lower than that of incoherent accumulation lidar systems. In experiments that measure atmospheric wind fields, the linear fit curve slope between the measured wind speed and the wind speed measured via a commercial wind-measuring lidar can be reduced from 1.146 to 1.093.

A Method for Correcting Signal Aberrations in Ultrasonic Indoor Positioning.

The increasing focus on the development of positioning techniques reflects the growing interest in applications and services based on indoor positioning. Many applications necessitate precise indoor positioning or tracking of individuals and assets, leading to rapid growth in products based on these technologies in certain market sectors. Ultrasonic systems have already proven effective in achieving the desired positioning accuracy and refresh rates. The typical signal used in ultrasonic positioning systems for estimating the range between the target and reference points is the linear chirp. Unfortunately, it can undergo shape aberration due to the effects of acoustic diffraction when the aperture exceeds a certain limit. The extent of the aberration is influenced by the shape and size of the transducer, as well as the angle at which the transducer is observed by the receiver. This aberration also affects the shape of the cross-correlation, causing it to lose its easily detectable characteristic of a single global peak, which typically corresponds to the correct lag associated with the signal's time of arrival. In such instances, cross-correlation techniques yield results with a significantly higher error than anticipated. In fact, the correct lag no longer corresponds to the peak of the cross-correlation. In this study, an alternative technique to global peak detection is proposed, leveraging the inherent symmetry observed in the shape of the aberrated cross-correlation. The numerical simulations, performed using the academic acoustic simulation software Field II, conducted using a typical ultrasonic chirp and ultrasonic emitter, compare the classical and the proposed range techniques in a standard office room. The analysis includes the effects of acoustical reflection in the room and of the acoustic noise at different levels of power. The results demonstrate that the proposed technique enables accurate range estimation even in the presence of severe cross-correlation shape aberrations and for signal-to-noise ratio levels common in office and room environments, even in presence of typical reflections. This allows the use of emitting transducers with a much larger aperture than that allowed by the classical cross-correlation technique. Consequently, it becomes possible to have greater acoustic power available, leading to improved signal-to-noise ratio (SNR).

Newest Methods and Approaches to Enhance the Performance of Optical Frequency-Domain Reflectometers.

In this review, we summarize the latest advances in the design of optical frequency-domain reflectometers (OFDRs), digital signal processing, and sensors based on special optical fibers. We discuss state-of-the-art approaches to improving metrological characteristics, such as spatial resolution, SNR, dynamic range, and the accuracy of determining back reflection coefficients. We also analyze the latest achievements in the OFDR-based sensors: the accuracy of spatial localization of the impact, the error in detecting temperatures, deformation, and other quantities, and the features of separate measurement of various physical quantities. We also pay attention to the trend of mutual integration of frequency-domain optical reflectometry methods with time-domain optical reflectometry, which provides completely new sensing possibilities. We believe that this review may be useful to engineers and scientists focused on developing a lab setup, complete measurement instrument, or sensing system with specific requirements.

Spatial Localization of Transformer Inspection Robot Based on Adaptive Denoising and SCOT-ß Generalized Cross-Correlation.

In the detection process of the internal defects of large oil-immersed transformers, due to the huge size of large transformers and metal-enclosed structures, the positional localization of miniature inspection robots inside the transformer faces great difficulties. To address this problem, this paper proposes a three-dimensional positional localization method based on adaptive denoising and the SCOT weighting function with the addition of the exponent ß (SCOT-ß) generalized cross-correlation for L-type ultrasonic arrays of transformer internal inspection robots. Aiming at the strong noise interference in the field, the original signal is decomposed by an improved Empirical Mode Decomposition (EMD) method, and the optimal center frequency and bandwidth of each mode are adaptively searched. By extracting the modes in the frequency band of the positional localization signal, suppressing the modes in the noise frequency band, and reconstructing the Intrinsic Mode Function (IMF) of the independently selected superior modal components, a signal with a high signal-to-noise ratio is obtained. In addition, for the traditional mutual correlation algorithm with a large delay estimation error at a low signal-to-noise ratio, this paper adopts an improved generalized joint weighting function, SCOT-ß, which improves the anti-jamming ability of the generalized mutual correlation method at a low signal-to-noise ratio by adding an exponential function to the denominator term of the SCOT weighting function's generalized cross-correlation. Finally, the accurate positional localization of the transformer internal inspection robot is realized based on the quadratic L-array and search-based maximum likelihood estimation method. Simulation and experimental results show the following: the improved EMD denoising method better improves the signal-to-noise ratio of the positional localization signal with a lower distortion rate; in the transformer test tank, which is 120 cm in length, 100 cm in width, and 100 cm in height, based on the positional localization method in this paper, the average relative positional localization error of the transformer internal inspection robot in three-dimensional space is 2.27%, and the maximum positional localization error is less than 2 cm, which meets the requirements of engineering positional localization.

Spatial Localization of a Transformer Robot Based on Ultrasonic Signal Wavelet Decomposition and PHAT-ß-γ Generalized Cross Correlation.

Because large oil-immersed transformers are enclosed by a metal shell, the on-site localization means it is difficult to achieve the accurate location of the patrol micro-robot inside a given transformer. To address this issue, a spatial ultrasonic localization method based on wavelet decomposition and PHAT-ß-γ generalized cross correlation is proposed in this paper. The method is carried out with a five-element stereo ultrasonic array for the location of a transformer patrol robot. Firstly, the localization signal is decomposed into wavelet coefficients of different scales, which would realize the adaptive decomposition of the frequency of the localization signal from low frequencies to high frequencies. Then, the wavelet coefficients are denoised and reconstructed by using the semi-soft threshold function. Second, a modified phase transform-beta-gamma (PHAT-ß-γ) method is used to calculate the exact time delay between different sensors by increasing the weights of the PHAT weighting function and introducing a correlation function. Finally, by using the proposed method, the accurate localization of the transformer patrol micro-robot is achieved with a five-element stereo ultrasonic array. The simulation and test results show that inside a transformer experimental oil tank (120 cm × 100 cm × 100 cm, L × W × H), the relative error of transformer patrol micro-robot spatial localization is within 4.1%, and the maximum localization error is less than 3 cm, which meets the requirement of engineering localization.

S-LIGHT: Synthetic Dataset for the Separation of Diffuse and Specular Reflection Images.

Several studies in computer vision have examined specular removal, which is crucial for object detection and recognition. This research has traditionally been divided into two tasks: specular highlight removal, which focuses on removing specular highlights on object surfaces, and reflection removal, which deals with specular reflections occurring on glass surfaces. In reality, however, both types of specular effects often coexist, making it a fundamental challenge that has not been adequately addressed. Recognizing the necessity of integrating specular components handled in both tasks, we constructed a specular-light (S-Light) DB for training single-image-based deep learning models. Moreover, considering the absence of benchmark datasets for quantitative evaluation, the multi-scale normalized cross correlation (MS-NCC) metric, which considers the correlation between specular and diffuse components, was introduced to assess the learning outcomes.

Disrupting EGFR-HER2 Transactivation by Pertuzumab in HER2-Positive Cancer: Quantitative Analysis Reveals EGFR Signal Input as Potential Predictor of Therapeutic Outcome.

Pertuzumab (Perjeta®), a humanized antibody binding to the dimerization arm of HER2 (Human epidermal growth factor receptor-2), has failed as a monotherapy agent in HER2 overexpressing malignancies. Since the molecular interaction of HER2 with ligand-bound EGFR (epidermal growth factor receptor) has been implied in mitogenic signaling and malignant proliferation, we hypothesized that this interaction, rather than HER2 expression and oligomerization alone, could be a potential molecular target and predictor of the efficacy of pertuzumab treatment. Therefore, we investigated static and dynamic interactions between HER2 and EGFR molecules upon EGF stimulus in the presence and absence of pertuzumab in HER2+ EGFR+ SK-BR-3 breast tumor cells using Förster resonance energy transfer (FRET) microscopy and fluorescence correlation and cross-correlation spectroscopy (FCS/FCCS). The consequential activation of signaling and changes in cell proliferation were measured by Western blotting and MTT assay. The autocorrelation functions of HER2 diffusion were best fitted by a three-component model corrected for triplet formation, and among these components the slowly diffusing membrane component revealed aggregation induced by EGFR ligand binding, as evidenced by photon-counting histograms and co-diffusing fractions. This aggregation has efficiently been prevented by pertuzumab treatment, which also inhibited the post-stimulus interaction of EGFR and HER2, as monitored by changes in FRET efficiency. Overall, the data demonstrated that pertuzumab, by hindering post-stimulus interaction between EGFR and HER2, inhibits EGFR-evoked HER2 aggregation and phosphorylation and leads to a dose-dependent decrease in cell proliferation, particularly when higher amounts of EGF are present. Consequently, we propose that EGFR expression on HER2-positive tumors could be taken into consideration as a potential biomarker when predicting the outcome of pertuzumab treatment.

Weighted Signed Networks Reveal Interactions between US Foreign Exchange Rates.

Correlations between exchange rates are valuable for illuminating the dynamics of international trade and the financial dynamics of countries. This paper explores the changing interactions of the US foreign exchange market based on detrended cross-correlation analysis. First, we propose an objective way to choose a time scale parameter appropriate for comparing different samples by maximizing the summed magnitude of all DCCA coefficients. We then build weighted signed networks under this optimized time scale, which can clearly display the complex relationships between different exchange rates. Our study shows negative cross-correlations have become pyramidally rare in the past three decades. Both the number and strength of positive cross-correlations have grown, paralleling the increase in global interconnectivity. The balanced strong triads are identified subsequently after the network centrality analysis. Generally, while the strong development links revealed by foreign exchange have begun to spread to Asia since 2010, Europe is still the center of world finance, with the euro and Danish krone consistently maintaining the closest balanced development relationship. Finally, we propose a fluctuation propagation algorithm to investigate the propagation pattern of fluctuations in the inferred exchange rate networks. The results show that, over time, fluctuation propagation patterns have become simpler and more predictable.