Adaptation of STIM1 structure-function relationships for optogenetic control of calcium signaling.

In cellular contexts, the oscillation of calcium ions (Ca2+) is intricately linked to various physiological processes, such as cell proliferation, metabolism, and survival. Stromal interaction molecule 1 (STIM1) proteins form a crucial regulatory component in the store-operated calcium entry process. The structural attributes of STIM1 are vital for its functionality, encompassing distinct domains situated in the endoplasmic reticulum lumen and the cytoplasm. The intraluminal domain enables the timely detection of diminishing Ca2+ concentrations, prompting structural modifications that activate the cytoplasmic domain. This activated cytoplasmic domain undergoes conformational alterations and engages with membrane components, opening a channel that facilitates the influx of Ca2+ from the extracellular environment. Given its multiple domains and interaction mechanisms, STIM1 plays a foundational role in cellular biology. This review focuses on the design of optogenetic tools inspired by the structure and function of STIM1. These tools offer a groundbreaking approach for studying and manipulating intracellular Ca2+ signaling with precise spatiotemporal control. We further explore the practical applications of these tools, spanning fundamental scientific research, clinical studies, and their potential for translational research.

Advancements and Challenges in the Integration of Indium Arsenide and Van der Waals Heterostructures.

The strategic integration of low-dimensional InAs-based materials and emerging van der Waals systems is advancing in various scientific fields, including electronics, optics, and magnetics. With their unique properties, these InAs-based van der Waals materials and devices promise further miniaturization of semiconductor devices in line with Moore's Law. However, progress in this area lags behind other 2D materials like graphene and boron nitride. Challenges include synthesizing pure crystalline phase InAs nanostructures and single-atomic-layer 2D InAs films, both vital for advanced van der Waals heterostructures. Also, diverse surface state effects on InAs-based van der Waals devices complicate their performance evaluation. This review discusses the experimental advances in the van der Waals epitaxy of InAs-based materials and the working principles of InAs-based van der Waals devices. Theoretical achievements in understanding and guiding the design of InAs-based van der Waals systems are highlighted. Focusing on advancing novel selective area growth and remote epitaxy, exploring multi-functional applications, and incorporating deep learning into first-principles calculations are proposed. These initiatives aim to overcome existing bottlenecks and accelerate transformative advancements in integrating InAs and van der Waals heterostructures.

Observation of Electronic Strong Correlation in VTe_{2}-2sqrt[3]×2sqrt[3] Monolayer.

Strong electron correlation under two-dimensional limit is intensely studied in the transition metal dichalcogenides monolayers, mostly within their charge density wave (CDW) states that host a star of David period. Here, by using scanning tunneling microscopy and spectroscopy and density functional theory calculations with on-site Hubbard corrections, we study the VTe_{2} monolayer with a different 2sqrt[3]×2sqrt[3] CDW period. We find that the dimerization of neighboring Te-Te and V-V atoms occurs during the CDW transition, and that the strong correlation effect opens a Mott-like full gap at Fermi energy (E_{F}). We further demonstrate that such a Mott phenomenon is ascribed to the combination of the CDW transition and on-site Coulomb interactions. Our work provides a new platform for exploring Mott physics in 2D materials.

Superb microvascular imaging (SMI) compared with conventional ultrasound for evaluating thyroid nodules.

BACKGROUND: Superb microvascular imaging (SMI) for depiction of microvascular flow in thyroid nodules was compared with color/power Doppler imaging (CDI/PDI) and contrast-enhanced ultrasonography (CEUS). In addition, the diagnostic performance of conventional ultrasound combined with SMI for differentiating benign and malignant thyroid nodules was evaluated. METHODS: Preoperative conventional ultrasound consisting of gray-scale ultrasonography and CDI/PDI, followed by SMI and CEUS, was used to record 52 thyroid nodules. Two radiologists analyzed the gray-scale ultrasound signs and nodules' microvascular flow patterns to differentiate between benign (n = 13) and malignant nodules (n = 39). RESULTS: SMI was significantly more effective in the detection of microvascular flow signals than CDI/PDI. In malignant nodules, SMI depicted the presence of incomplete surrounding periphery microvasculature and of disordered heterogeneous internal microvasculature. Benign nodules showed complete surrounding periphery microvasculature (ring sign) and homogeneity internal branching. The accuracies of conventional ultrasound combined with CDI/ PDI, SMI, or CEUS for predicting malignancy were 67.31, 86.54, and 92.31%, respectively. The accuracy of SMI differed significantly from CDI/PDI (P = 0.012), but not from CEUS (P = 0.339). CONCLUSIONS: Microvascular flow and vessel branching in the peripheral and internal microvasculature of thyroid nodules is depicted with greater detail and clarity with SMI compared with conventional ultrasound. SMI offers a safe and low-cost alternative to CEUS for differentiating between benign and malignant thyroid nodules.

The Configuration of GRB2 in Protein Interaction and Signal Transduction.

Growth-factor-receptor-binding protein 2 (GRB2) is a non-enzymatic adaptor protein that plays a pivotal role in precisely regulated signaling cascades from cell surface receptors to cellular responses, including signaling transduction and gene expression. GRB2 binds to numerous target molecules, thereby modulating a complex cell signaling network with diverse functions. The structural characteristics of GRB2 are essential for its functionality, as its multiple domains and interaction mechanisms underpin its role in cellular biology. The typical signaling pathway involving GRB2 is initiated by the ligand stimulation to its receptor tyrosine kinases (RTKs). The activation of RTKs leads to the recruitment of GRB2 through its SH2 domain to the phosphorylated tyrosine residues on the receptor. GRB2, in turn, binds to the Son of Sevenless (SOS) protein through its SH3 domain. This binding facilitates the activation of Ras, a small GTPase, which triggers a cascade of downstream signaling events, ultimately leading to cell proliferation, survival, and differentiation. Further research and exploration into the structure and function of GRB2 hold great potential for providing novel insights and strategies to enhance medical approaches for related diseases. In this review, we provide an outline of the proteins that engage with domains of GRB2, along with the function of different GRB2 domains in governing cellular signaling pathways. This furnishes essential points of current studies for the forthcoming advancement of therapeutic medications aimed at GRB2.

Comprehensive Review of the Determination and Reduction of the Minimum Miscibility Pressure during CO2 Flooding.

With the increasing oil demand, more attention has been paid to enhancing oil recovery in old oil fields. CO2 flooding is popular due to its high oil displacement efficiency and ability to reduce greenhouse gas emissions. Laboratory experiments and on-site application cases have shown that the minimum miscibility pressure has a greater impact on CO2 flooding than other factors. If the reservoir pressure is below the minimum miscible pressure, then there is CO2 immiscible flooding. Both theoretical analysis and experimental results show that the recovery rate of CO2 miscible flooding is 2-5 times higher than that of immiscible flooding. If the reservoir pressure is increased by water flooding before CO2 injection, it is easily limited by the physical property parameters. Therefore, accurately determining and effectively reducing the minimum mixing pressure has become the focus of research. Currently, there are two types of methods for determining the minimum miscible pressure: experimental and theoretical methods. The experimental method is generally considered more accurate, including the slim tube test, rising bubble apparatus, and vanishing interfacial tension, etc. However, it is worth noting that the minimum miscibility pressure is dynamically changing, and there will be high economic costs if measured repeatedly through experimental methods during reservoir development. Therefore, it is recognized that the minimum mixing pressure can be determined at any time using theoretical calculation of initial data, which will reduce economic and time costs to a high degree. In this paper, the theoretical calculation method is divided into empirical correlation, state equation, and artificial intelligence algorithm. The techniques for reducing the minimum miscibility pressure can be classified into two categories: miscible solvents and surfactant methods. The miscible solvent method can be further divided into monocomponent and polycomponent methods. This paper compares the advantages and disadvantages of the existing techniques for measuring and reducing MMP and selects the best method.

Realization of monolayer ZrTe5 topological insulators with wide band gaps.

Two-dimensional topological insulators hosting the quantum spin Hall effect have application potential in dissipationless electronics. To observe the quantum spin Hall effect at elevated temperatures, a wide band gap is indispensable to efficiently suppress bulk conduction. Yet, most candidate materials exhibit narrow or even negative band gaps. Here, via elegant control of van der Waals epitaxy, we have successfully grown monolayer ZrTe5 on a bilayer graphene/SiC substrate. The epitaxial ZrTe5 monolayer crystalizes in two allotrope isomers with different intralayer alignments of ZrTe3 prisms. Our scanning tunneling microscopy/spectroscopy characterization unveils an intrinsic full band gap as large as 254 meV and one-dimensional edge states localized along the periphery of the ZrTe5 monolayer. First-principles calculations further confirm that the large band gap originates from strong spin-orbit coupling, and the edge states are topologically nontrivial. These findings thus provide a highly desirable material platform for the exploration of the high-temperature quantum spin Hall effect.

Does green finance improve carbon emission efficiency? Experimental evidence from China.

As a noteworthy initiative of financial supply-side reform to precisely support the green development system, can green finance (GF) help achieve the dual goals of "carbon peaking" and "carbon neutrality"? Using data from China's provincial panel between 2007 and 2019, this paper measured the green finance index by the entropy method and the carbon emission efficiency (CEE) with carbon emission as the non-desired output by the Super-SBM model. Then, the influence of GF on CEE was empirically investigated by the dynamic panel model and the spatial Durbin model. The findings show that GF can significantly improve CEE and has a positive spillover impact on CEE in provinces with close economic ties; the upgrading of the industrial structure is a key mediator in the transmission of GF to CEE; and regional heterogeneity analysis finds that GF notably improves CEE in eastern, high development levels of economic and GF regions. The research can offer some theoretical and empirical references for green finance to contribute to low-carbon economic growth.

Physics-Guided Generative Adversarial Networks for Sea Subsurface Temperature Prediction.

Sea subsurface temperature, an essential component of aquatic wildlife, underwater dynamics, and heat transfer with the sea surface, is affected by global warming in climate change. Existing research is commonly based on either physics-based numerical models or data-based models. Physical modeling and machine learning are traditionally considered as two unrelated fields for the sea subsurface temperature prediction task, with very different scientific paradigms (physics-driven and data-driven). However, we believe that both methods are complementary to each other. Physical modeling methods can offer the potential for extrapolation beyond observational conditions, while data-driven methods are flexible in adapting to data and are capable of detecting unexpected patterns. The combination of both approaches is very attractive and offers potential performance improvement. In this article, we propose a novel framework based on a generative adversarial network (GAN) combined with a numerical model to predict sea subsurface temperature. First, a GAN-based model is used to learn the simplified physics between the surface temperature and the target subsurface temperature in the numerical model. Then, observation data are used to calibrate the GAN-based model parameters to obtain a better prediction. We evaluate the proposed framework by predicting daily sea subsurface temperature in the South China Sea. Extensive experiments demonstrate the effectiveness of the proposed framework compared to existing state-of-the-art methods.

Can new energy demonstration city policy reduce carbon emissions? A quasi-natural experiment from China.

Against achieving carbon peaking by 2030 and carbon neutrality by 2060 context in China, the new energy demonstration city policy (NEDCP) has a crucial function to perform in promoting resource utilization efficiency, building the green development policy system, and facilitating carbon emission reduction. However, existing research has rarely investigated the contribution of NEDCP on carbon reduction. To investigate the policy effect of NEDCP, the differences-in-differences (DID) model is introduced to quantify the influence of NEDCP on carbon reduction, taking a statistical sample of 285 Chinese cities over the period 2005-2017 on the basis of exploring the intrinsic mechanism of NEDCP on carbon emissions. The statistical results reveal that NEDCP significantly inhibits carbon emissions. NEDCP's dampening impact on carbon reduction is more pronounced in the eastern area but not in other areas. City size and resource endowment heterogeneity results suggest that NEDCP significantly inhibits the output of carbon emissions in non-resource-based and large cities but insignificantly in resource-based and small- and medium-sized cities. Finally, we conclude that policy-makers should not only broaden the scope of NEDCP implementation continuously but also design relevant policy combination tools following the basic characteristics of each city to provide institutional guarantees for achieving carbon emission reduction.