Study on the trade-off/synergy spatiotemporal benefits of ecosystem services and its influencing factors in hilly areas of southern China

IntroductionThis study aims to investigate the factors influencing ecosystem service trade-offs/synergies (TOSs) in major agricultural production areas in the southern hilly region and to propose optimization strategies to promote ecosystem sustainability in agricultural areas.MethodsThe study used a geographical detector to analyze the determinants influencing the ecosystem service trade-offs as well as correlation analysis, geographically weighted regression (GWR), and a geographical detector to analyze the spatial and temporal evolution of ecosystem service and TOS relationships from 2000 to 2020 in Hunan Province.ResultsThe results showed that the comprehensive value of ecosystem services in Hunan Province showed an increasing trend from 2000 to 2020. With spatial heterogeneity, the areas with high values were mainly distributed in the hilly areas in the west, south, and east of Hunan Province, and the areas with low values were mainly distributed in the Dongting Lake Plain and the Xiangzhong Hilly Basin. There was a trade-off relationship between food production (FP) and all other ecosystem services, of which FP has the strongest trade-off effect with habitat quality (HQ). The synergy effect between HQ, water yield (WY), carbon storage (CS), and soil conservation (SC) shows an increasing trend. Gross domestic product (GDP) and SLOPE are the dominant factors for the strength of trade-offs between food supply and other ecosystem services, and Digital Elevation Model (DEM) and Normalized Difference Vegetation Index (NDVI) are the dominant factors for the strength of synergy effects among ecosystem services. The strength of TOS effects of ecosystem services is determined by interactions or co-influences between the two services rather than by a single component.DiscussionThe results of this study can provide a reference basis for the enhancement of ecosystem services and the sustainable planning of agricultural landscapes in the southern hilly areas

Hepatotoxicity induced by zoledronic acid in an aged woman with primary osteoporosis

Zoledronic acid, a bisphosphonate, has been approved for treatment and prevention of osteoporosis. This case describes a 73-year-old woman with primary osteoporosis who developed transient hepatotoxicity after zoledronic acid (ZOL) treatment. Three days after ZOL infusion, aspartate aminotransferase (AST), alanine aminotransferase (ALT), and gamma-glutamyltransferase (GGT) were increased by 9.9, 8.1, and 3.7 times, respectively, compared with pretreatment values. Liver protective agents were administered. The aminotransferase returned within normal ranges 12 days post-infusion. Currently, the relationship of ZOL and liver damage is not quite clear, which cannot be explained by its pharmacokinetics. The aim of this case report is to increase the clinician’s awareness of the possible adverse effect on the liver, and ZOL should be cautiously administered in patients with liver disease

Vigilin interacts with signal peptide peptidase.

BACKGROUND: Signal peptide peptidase (SPP), a member of the presenilin-like intra-membrane cleaving aspartyl protease family, migrates on Blue Native (BN) gels as 100 kDa, 200 kDa and 450 kDa species. SPP has recently been implicated in other non-proteolytic functions such as retro-translocation of MHC Class I molecules and binding of misfolded proteins in the endoplasmic reticulum (ER). These high molecular weight SPP complexes might contain additional proteins that regulate the proteolytic activity of SPP or support its non-catalytic functions. RESULTS: In this study, an unbiased iTRAQ-labeling mass spectrometry approach was used to identify SPP-interacting proteins. We found that vigilin, a ubiquitous multi-KH domain containing cytoplasmic protein involved in RNA binding and protein translation control, selectively enriched with SPP. Vigilin interacted with SPP and both proteins co-localized in restricted intracellular domains near the ER, biochemically co-fractionated and were part of the same 450 kDa complex on BN gels. However, vigilin does not alter the protease activity of SPP, suggesting that the SPP-vigilin interaction might be involved in the non-proteolytic functions of SPP. CONCLUSIONS: We have identified and validated vigilin as a novel interacting partner of SPP that could play an important role in the non-proteolytic functions of SPP. This data adds further weight to the idea that intramembrane-cleaving aspartyl proteases, such as presenilin and SPPs, could have other functions besides the proteolysis of short membrane stubs.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Quantum Neuronal Sensing of Quantum Many-Body States on a 61-Qubit Programmable Superconducting Processor

Classifying many-body quantum states with distinct properties and phases of matter is one of the most fundamental tasks in quantum many-body physics. However, due to the exponential complexity that emerges from the enormous numbers of interacting particles, classifying large-scale quantum states has been extremely challenging for classical approaches. Here, we propose a new approach called quantum neuronal sensing. Utilizing a 61 qubit superconducting quantum processor, we show that our scheme can efficiently classify two different types of many-body phenomena: namely the ergodic and localized phases of matter. Our quantum neuronal sensing process allows us to extract the necessary information coming from the statistical characteristics of the eigenspectrum to distinguish these phases of matter by measuring only one qubit. Our work demonstrates the feasibility and scalability of quantum neuronal sensing for near-term quantum processors and opens new avenues for exploring quantum many-body phenomena in larger-scale systems.Comment: 7 pages, 3 figures in the main text, and 13 pages, 13 figures, and 1 table in supplementary material

Experimental quantum computational chemistry with optimised unitary coupled cluster ansatz

Simulation of quantum chemistry is one of the most promising applications of quantum computing. While recent experimental works have demonstrated the potential of solving electronic structures with variational quantum eigensolver (VQE), the implementations are either restricted to nonscalable (hardware efficient) or classically simulable (Hartree-Fock) ansatz, or limited to a few qubits with large errors for the more accurate unitary coupled cluster (UCC) ansatz. Here, integrating experimental and theoretical advancements of improved operations and dedicated algorithm optimisations, we demonstrate an implementation of VQE with UCC for H_2, LiH, F_2 from 4 to 12 qubits. Combining error mitigation, we produce high-precision results of the ground-state energy with error suppression by around two orders of magnitude. For the first time, we achieve chemical accuracy for H_2 at all bond distances and LiH at small bond distances in the experiment. Our work demonstrates a feasible path towards a scalable solution to electronic structure calculation, validating the key technological features and identifying future challenges for this goal.Comment: 8 pages, 4 figures in the main text, and 29 pages supplementary materials with 16 figure