Impact of Opinions and Relationships Coevolving on Self-Organization of Opinion Clusters

In a social network, individual opinions and interpersonal relationships always interact and coevolve. This continuously leads to self-organization of opinion clusters in the whole network. In this article we study how the coevolution on the two kinds of complex networks and the self-organization of opinion clusters are differently affected by the dynamic parameters, the structural parameters and the propagating parameters. It is found that the two dynamic parameters are homogeneous bringing about the strong and weak relations, while the two structural parameters are heterogeneous having equivalent relations. Moreover, the impact of the propagating parameter has been found only above its threshold

Error-mitigated Quantum Approximate Optimization via Learning-based Adaptive Optimization

Combinatorial optimization problems are ubiquitous and computationally hard to solve in general. Quantum computing is envisioned as a powerful tool offering potential computational advantages for solving some of these problems. Quantum approximate optimization algorithm (QAOA), one of the most representative quantum-classical hybrid algorithms, is designed to solve certain combinatorial optimization problems by transforming a discrete optimization problem into a classical optimization problem over a continuous circuit parameter domain. QAOA objective landscape over the parameter variables is notorious for pervasive local minima and barren plateaus, and its viability in training significantly relies on the efficacy of the classical optimization algorithm. To enhance the performance of QAOA, we design double adaptive-region Bayesian optimization (DARBO), an adaptive classical optimizer for QAOA. Our experimental results demonstrate that the algorithm greatly outperforms conventional gradient-based and gradient-free optimizers in terms of speed, accuracy, and stability. We also address the issues of measurement efficiency and the suppression of quantum noise by successfully conducting the full optimization loop on the superconducting quantum processor. This work helps to unlock the full power of QAOA and paves the way toward achieving quantum advantage in practical classical tasks.Comment: Main text: 11 pages, 4 figures, SI: 5 pages, 5 figure

The value of surgery in the patients with de novo stage Ⅳ breast cancer

Breast cancer is one of the common malignant tumors in the world. About 6% of the patients are de novo stage Ⅳ breast cancer, which is incurable. Traditionally, the role of surgery has been confined to relieving symptoms, improving quality of life and reducing tumor load. Nowadays, a multidisciplinary team is a prerequisite for optimal management, and patients with oligometastatic lesion always live for a long time. R0 resection of the primary and metastatic foci can extend the time of progression-free survival (PFS), which may bring survival benefits. Therefore, whether to perform surgery has become a hot clinical issue. This article deeply discussed extensively the surgical value in de novo stage Ⅳ breast cancer patients

Computational modelling of optical tweezers with many degrees of freedom using dynamic simulation: cylinders, nanowires, and multiple particles

Computational tasks such as the calculation and characterization of the optical force acting on a sphere are relatively straightforward in a Gaussian beam trap. Resulting properties of the trap such as the trap strength, spring constants, and equilibrium position can be easily determined. More complex systems with non-spherical particles or multiple particles add many more degrees of freedom to the problem. Extension of the simple methods used for single spherical particles could result in required computational time of months or years. Thus, alternative methods must be used. One powerful tool is to use dynamic simulation: model the dynamics and motion of a particle or particles within the trap. We demonstrate the use of dynamic simulation for non-spherical particles and multi-particle systems. Using a hybrid discrete dipole approximation (DDA) and T-matrix method, we find plausible equilibrium positions and orientations of cylinders of varying size and aspect ratio. Orientation landscapes revealing different regimes of behaviour for micro-cylinders and nanowires with different refractive indices trapped with beams of differing polarization are also presented. This investigation provides a solid background in both the function and properties of micro-cylinders and nanowires trapped in optical tweezers. This method can also be applied to particles with other shapes. We also investigate multiple-particle trapping, which is quite different from single particle systems, as they can include effects such as optical binding. We show that equilibrium positions, and the strength of interactions between particles can be found in systems of two and more particles

Super-multiplex vibrational imaging

The ability to visualize directly a large number of distinct molecular species inside cells is increasingly essential for understanding complex systems and processes. Even though existing methods have successfully been used to explore structure–function relationships in nervous systems, to profile RNA in situ, to reveal the heterogeneity of tumour microenvironments and to study dynamic macromolecular assembly, it remains challenging to image many species with high selectivity and sensitivity under biological conditions. For instance, fluorescence microscopy faces a ‘colour barrier’, owing to the intrinsically broad (about 1,500 inverse centimetres) and featureless nature of fluorescence spectra that limits the number of resolvable colours to two to five (or seven to nine if using complicated instrumentation and analysis). Spontaneous Raman microscopy probes vibrational transitions with much narrower resonances (peak width of about 10 inverse centimetres) and so does not suffer from this problem, but weak signals make many bio-imaging applications impossible. Although surface-enhanced Raman scattering offers high sensitivity and multiplicity, it cannot be readily used to image specific molecular targets quantitatively inside live cells. Here we use stimulated Raman scattering under electronic pre-resonance conditions to image target molecules inside living cells with very high vibrational selectivity and sensitivity (down to 250 nanomolar with a time constant of 1 millisecond). We create a palette of triple-bond-conjugated near-infrared dyes that each displays a single peak in the cell-silent Raman spectral window; when combined with available fluorescent probes, this palette provides 24 resolvable colours, with the potential for further expansion. Proof-of-principle experiments on neuronal co-cultures and brain tissues reveal cell-type-dependent heterogeneities in DNA and protein metabolism under physiological and pathological conditions, underscoring the potential of this 24-colour (super-multiplex) optical imaging approach for elucidating intricate interactions in complex biological systems

Activation of GPR4 by Acidosis Increases Endothelial Cell Adhesion through the cAMP/Epac Pathway

Endothelium-leukocyte interaction is critical for inflammatory responses. Whereas the tissue microenvironments are often acidic at inflammatory sites, the mechanisms by which cells respond to acidosis are not well understood. Using molecular, cellular and biochemical approaches, we demonstrate that activation of GPR4, a proton-sensing G protein-coupled receptor, by isocapnic acidosis increases the adhesiveness of human umbilical vein endothelial cells (HUVECs) that express GPR4 endogenously. Acidosis in combination with GPR4 overexpression further augments HUVEC adhesion with U937 monocytes. In contrast, overexpression of a G protein signaling-defective DRY motif mutant (R115A) of GPR4 does not elicit any increase of HUVEC adhesion, indicating the requirement of G protein signaling. Downregulation of GPR4 expression by RNA interference reduces the acidosis-induced HUVEC adhesion. To delineate downstream pathways, we show that inhibition of adenylate cyclase by inhibitors, 2′,5′-dideoxyadenosine (DDA) or SQ 22536, attenuates acidosis/GPR4-induced HUVEC adhesion. Consistently, treatment with a cAMP analog or a Gi signaling inhibitor increases HUVEC adhesiveness, suggesting a role of the Gs/cAMP signaling in this process. We further show that the cAMP downstream effector Epac is important for acidosis/GPR4-induced cell adhesion. Moreover, activation of GPR4 by acidosis increases the expression of vascular adhesion molecules E-selectin, VCAM-1 and ICAM-1, which are functionally involved in acidosis/GPR4-mediated HUVEC adhesion. Similarly, hypercapnic acidosis can also activate GPR4 to stimulate HUVEC adhesion molecule expression and adhesiveness. These results suggest that acidosis/GPR4 signaling regulates endothelial cell adhesion mainly through the Gs/cAMP/Epac pathway and may play a role in the inflammatory response of vascular endothelial cells

Influencing of serum inflammatory factors on IVF/ICSI outcomes among PCOS patients with different BMI

IntroductionOverweight and obese are important factors leading to the occurrence of long-term complications in women with polycystic ovary syndrome (PCOS). There has been controversy over whether dissatisfaction with pregnancy outcomes in PCOS patients is influenced by chronic inflammatory status or obesity. This retrospective study analyzed the levels of inflammatory factors in PCOS patients with different body mass index (BMI) groups and effective predictors of in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) pregnancy outcomes.MethodsThere were 273 women with PCOS diagnosed who completed serum inflammatory factors test between January 2017 and June 2022 were selected. The data of 7,649 infertility PCOS patients who received their first IVF/ICSI treatment in the Reproductive Center of Peking University Third Hospital during the period of the study were collected. Finally, 92 PCOS patients were included in the high BMI group, while 97 patients were included in the normal BMI group. Baseline characteristics were collected and the pregnancy outcomes were compared among the two groups. Then, serum inflammatory factors’ effect on IVF/ICSI pregnancy outcomes were analyzed with age, anti-Mullerian Hormone (AMH) and BMI adjusted.ResultsPCOS patients in the high BMI group significantly had a lower number of oocytes retrieved and good quality embryos. The high BMI group PCOS patients had higher levels of IL-6 and lower cumulative clinical pregnancy and live birth rates. The level of GM-CSF was higher in the first cycle transfer and cumulative miscarriage group. High TNF-α was negatively correlated with the first transfer cycle and cumulative clinical pregnancy rates after age, AMH and high BMI adjusted. In addition, the cumulative live birth rate was negatively correlated with high IL-6, but the first cycle transfer and cumulative live birth rates were positively correlated with high IL-1β.DiscussionFor PCOS patients, in addition to BMI, attention should also be paid to inflammatory indicators. High levels of TNF-α and IL-6 were negatively correlated with pregnancy outcomes, but high IL-1β was positively correlated with live birth rates among PCOS patients. The level of GM-CSF was higher in miscarriage PCOS patients