Intrinsic nonlinear Hall effect and gate-switchable Berry curvature sliding in twisted bilayer graphene

Though the observation of quantum anomalous Hall effect and nonlocal transport response reveals nontrivial band topology governed by the Berry curvature in twisted bilayer graphene, some recent works reported nonlinear Hall signals in graphene superlattices which are caused by the extrinsic disorder scattering rather than the intrinsic Berry curvature dipole moment. In this work, we report a Berry curvature dipole induced intrinsic nonlinear Hall effect in high-quality twisted bilayer graphene devices. We also find that the application of the displacement field substantially changes the direction and amplitude of the nonlinear Hall voltages, as a result of a field-induced sliding of the Berry curvature hotspots. Our work not only proves that the Berry curvature dipole could play a dominant role in generating the intrinsic nonlinear Hall signal in graphene superlattices with low disorder densities, but also demonstrates twisted bilayer graphene to be a sensitive and fine-tunable platform for second harmonic generation and rectification

Receptor compaction and GTPase rearrangement drive SRP-mediated cotranslational protein translocation into the ER

The conserved signal recognition particle (SRP) cotranslationally delivers ~30% of the proteome to the eukaryotic endoplasmic reticulum (ER). The molecular mechanism by which eukaryotic SRP transitions from cargo recognition in the cytosol to protein translocation at the ER is not understood. Here, structural, biochemical, and single-molecule studies show that this transition requires multiple sequential conformational rearrangements in the targeting complex initiated by guanosine triphosphatase (GTPase)–driven compaction of the SRP receptor (SR). Disruption of these rearrangements, particularly in mutant SRP54G226E linked to severe congenital neutropenia, uncouples the SRP/SR GTPase cycle from protein translocation. Structures of targeting intermediates reveal the molecular basis of early SRP-SR recognition and emphasize the role of eukaryote-specific elements in regulating targeting. Our results provide a molecular model for the structural and functional transitions of SRP throughout the targeting cycle and show that these transitions provide important points for biological regulation that can be perturbed in genetic diseases

On the Road with GPT-4V(ision): Early Explorations of Visual-Language Model on Autonomous Driving

The pursuit of autonomous driving technology hinges on the sophisticated integration of perception, decision-making, and control systems. Traditional approaches, both data-driven and rule-based, have been hindered by their inability to grasp the nuance of complex driving environments and the intentions of other road users. This has been a significant bottleneck, particularly in the development of common sense reasoning and nuanced scene understanding necessary for safe and reliable autonomous driving. The advent of Visual Language Models (VLM) represents a novel frontier in realizing fully autonomous vehicle driving. This report provides an exhaustive evaluation of the latest state-of-the-art VLM, GPT-4V(ision), and its application in autonomous driving scenarios. We explore the model's abilities to understand and reason about driving scenes, make decisions, and ultimately act in the capacity of a driver. Our comprehensive tests span from basic scene recognition to complex causal reasoning and real-time decision-making under varying conditions. Our findings reveal that GPT-4V demonstrates superior performance in scene understanding and causal reasoning compared to existing autonomous systems. It showcases the potential to handle out-of-distribution scenarios, recognize intentions, and make informed decisions in real driving contexts. However, challenges remain, particularly in direction discernment, traffic light recognition, vision grounding, and spatial reasoning tasks. These limitations underscore the need for further research and development. Project is now available on GitHub for interested parties to access and utilize: \url{https://github.com/PJLab-ADG/GPT4V-AD-Exploration

Network pharmacology and experimental verification reveal the mechanism of safranal against glioblastoma (GBM)

IntroductionSafranal is an active component of the traditional Tibetan medicine (TTM) saffron, which has potential anticancer activity.Methods and resultsHere, we studied the therapeutic effect and mechanism of safranal on GBM. CCK-8, GBM-brain organoid coculture experiments and 3D tumour spheroid invasion assays showed that safranal inhibited GBM cell proliferation and invasion in vitro. Network pharmacology, RNA-seq, molecular docking analysis, western blotting, apoptosis, and cell cycle assays predicted and verified that safranal could promote GBM cell apoptosis and G2/M phase arrest and inhibit the PI3K/AKT/mTOR axis. In vivo experiments showed that safranal could inhibit GBM cell growth alone and in combination with TMZ.ConclusionThis study revealed that safranal inhibits GBM cell growth in vivo and in vitro, promotes GBM cell apoptosis and G2/M phase arrest, inhibits the PI3K/AKT/mTOR axis and cooperate with TMZ

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Green credit and market expansion strategy of high pollution enterprises-Evidence from China.

This paper uses the Difference-in-Differences method to test the impact of the promulgation of Green Credit Guidelines, a market-oriented environmental regulation, on the enterprise market expansion strategy, based on the panel data of Chinese A-share listed companies from 2008 to 2015. We find that the promulgation of Green Credit Guidelines significantly inhibited the market expansion strategy of high pollution enterprises. Two channels through which the Green Credit Guidelines affect the market expansion strategies of high polluters are increasing the cost of financing and promoting green R&D. Heterogeneity analysis finds that the impact of Green Credit Guidelines on the market expansion of highly polluting enterprises is more significant in non-state-owned enterprises and enterprises without equity incentive. Further analysis shows that the promulgation of Green Credit Guidelines damages the corporate image and profitability of high polluting enterprises, but it doesn't increase the risk of high polluting enterprises. The results of this research could help relevant government departments to formulate practical environmental regulations and promote sustainable economic development

Pore engineering of ZIF-8 with ionic liquids for membrane-based CO2 separation: bearing functional group effect

CO2 separation performance of polymer membranes can be significantly enhanced by selecting porous fillers with high CO2 affinity. Ionic liquids incorporation has been recognized as an effective strategy for improving the separation ability of pristine porous fillers. However, the influence of the specific functional groups of ILs in IL@MOF composites on separation performance of MMMs still remains unclear. Herein, we designed three microenvironment-tuned IL@ZIF-8 composites in which the three ILs contain different functional groups (-CH3, –SO3H, and –NH2). Molecular simulation results showed that the NH2-IL@ZIF-8 has a commendable CO2 adsorption capacity and CO2/CH4 adsorptive selectivity, and the results were well confirmed by the following experimental data. More importantly, the prepared NH2-IL@ZIF-8 based MMMs also exhibit superior CO2 separation performance among the three IL@ZIF-8 based MMMs owning to its high CO2 affinity. Thus, this work can provide guidance for designing IL@MOF composites for MMMs fabrication towards gas separation, and the research mode combining molecular simulation prediction and experimental verification can afford valuable reference for material development in membrane separation field

Enhancement of 2,3-Butanediol Production by <i>Klebsiella pneumoniae</i>: Emphasis on the Mediation of sRNA-SgrS on the Carbohydrate Utilization

The demand for renewable energy is increasing. Klebsiella pneumoniae is one of the most promising strains to produce 2,3-butanediol (2,3-BD). Compared with chemical methods, the biological production of 2,3-BD has the characteristics of substrate safety, low cost, and low energy consumption. However, excessive glucose concentrations can cause damage to cells. Therefore, this study investigated the effect of sRNA-SgrS as a sugar transport regulator on the fermentative production of 2,3-BD by K. pneumoniae in response to sugar stress. We designed multiple mutants of K. pneumoniae HD79 to redistribute its carbon flux to produce 2,3-BD. It was found that the 2,3-BD yield of sgrS overexpressed strain decreased by 44% compared with the original strain. The results showed that a high concentration of sRNA-SgrS could accelerate the degradation of ptsG mRNA (encoding the glucose transporter EIICBGlc) and downregulate the expression levels of the budA gene (encoding the α-acetyllactate decarboxylase) and the budB gene (encoding the α-acetyllactate synthase) and budC gene (encoding the 2,3-BD dehydrogenase) but had no effect on the ack gene (encoding the acetate kinase) and the ldh gene (encoding the lactate dehydrogenase). It provides a theoretical basis and a technical reference for understanding the complex regulation mechanism of sRNA in microorganisms and the genetics and breeding in industrial fermentation engineering

Genome-Wide Identification of GRAS Gene Family and Their Responses to Abiotic Stress in Medicago sativa

Alfalfa (Medicago sativa) is a high-quality legume forage crop worldwide, and alfalfa production is often threatened by abiotic environmental stresses. GRAS proteins are important transcription factors that play a vital role in plant development, as well as in response to environmental stress. In this study, the availability of alfalfa genome “Zhongmu No.1” allowed us to identify 51 GRAS family members, i.e., MsGRAS. MsGRAS proteins could be classified into nine subgroups with distinct conserved domains, and tandem and segmental duplications were observed as an expansion strategy of this gene family. In RNA-Seq analysis, 14 MsGRAS genes were not expressed in the leaf or root, 6 GRAS genes in 3 differentially expressed gene clusters were involved in the salinity stress response in the leaf. Moreover, qRT-PCR results confirmed that MsGRAS51 expression was induced under drought stress and hormone treatments (ABA, GA and IAA) but down-regulated in salinity stress. Collectively, our genome-wide characterization, evolutionary, and expression analysis suggested that the MsGRAS proteins might play crucial roles in response to abiotic stresses and hormonal cues in alfalfa. For the breeding of alfalfa, it provided important information on stress resistance and functional studies on MsGRAS and hormone signaling