Protein-Protein Affinity Determination by Quantitative FRET Quenching.

The molecular dissociation constant, Kd, is a well-established parameter to quantitate the affinity of protein-protein or other molecular interactions. Recently, we reported the theoretical basis and experimental procedure for Kd determination using a quantitative FRET method. Here we report a new development of Kd determination by measuring the reduction in donor fluorescence due to acceptor quenching in FRET. A new method of Kd determination was developed from the quantitative measurement of donor fluorescence quenching. The estimated Kd values of SUMO1-Ubc9 interaction based on this method are in good agreement with those determined by other technologies, including FRET acceptor emission. Thus, the acceptor-quenched approach can be used as a complement to the previously developed acceptor excitation method. The new methodology has more general applications regardless whether the acceptor is an excitable fluorophore or a quencher. Thus, these developments provide a complete methodology for protein or other molecule interaction affinity determinations in solution

A Non-Equilibrium Sediment Transport Model for Dam Break Flow over Moveable Bed Based on Non-Uniform Rectangular Mesh

The use of multiple-level non-uniform rectangular mesh in coupled flow and sediment transport modeling is preferred to achieve high accuracy in important region without increasing computational cost greatly. Here, a robust coupled hydrodynamic and non-equilibrium sediment transport model is developed on non-uniform rectangular mesh to simulate dam break flow over movable beds. The enhanced shallow water and sediment transport equations are adopted to consider the mass and momentum exchange between the flow phase and sediment phase. The flux at the interface is calculated by the positivity preserving central upwind scheme, which belongs to Godunov-type Riemann-problem-solver-free central schemes and is less expensive than other popular Riemann solvers while still capable of tracking wet/dry fronts accurately. The nonnegative water depth reconstruction method is used to achieve second-order accuracy in space. The model was first verified against two laboratory experiments of dam break flow over irregular fixed bed. Then the quantitative performance of the model was further investigated by comparing the computational results with measurement data of dam break flow over movable bed. The good agreements between the measurements and the numerical simulations are found for the flow depth, velocity and bed changes

Analysis of waves observed by synthetic aperture radar across ocean fronts

In this study, synthetic aperture radar (SAR) imaging of waves across ocean fronts was investigated using C-band Sentinel-1 VV-polarized SAR imagery collected over the Yangtze and the Zhujiang estuaries. The presence of ocean fronts in the study area was confirmed by collocated sea surface temperature (SST) data provided by the Advanced Very High Resolution Radiometer (AVHRR) and sea surface current information from the National Ocean Partnership Program (NOPP) based on the HYbrid Coordinate Ocean Model (HYCOM). The experimental results revealed that as the current speed increased, the cut-off wavelength (λc) increased as well. The effect of the increasing azimuth cut-off wavelength, however, was relatively weak in terms of variations of the normalized radar cross-section (NRCS), i.e., it was within 2 dB for λc ≤ 60 m. Hence, it was weaker than the NRCS variation related to SST. Larger NRCS variations (i.e., within 5 dB) occurred for λc values up to 120 m. In addition, the experimental results also demonstrated that the parameterized first-guess spectrum method (PFSM) wave retrieval performance was affected by ocean fronts. In particular, overestimations occurred when ocean fronts were present and λc was < 100

Identification and validation of SERPINE1 as a prognostic and immunological biomarker in pan-cancer and in ccRCC

Background:SERPINE1, a serine protease inhibitor involved in the regulation of the plasminogen activation system, was recently identified as a cancer-related gene. However, its clinical significance and potential mechanisms in pan-cancer remain obscure.Methods: In pan-cancer multi-omics data from public datasets, including The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx), and online web tools were used to analyze the expression of SERPINE1 in different cancers and its correlation with prognosis, genetic alteration, DNA promoter methylation, biological processes, immunoregulator expression levels, immune cell infiltration into tumor, tumor mutation burden (TMB), microsatellite instability (MSI), immunotherapy response and drug sensitivity. Further, two single-cell databases, Tumor Immune Single-cell Hub 2 (TISCH2) and CancerSEA, were used to explore the expression and potential roles of SERPINE1 at a single-cell level. The aberrant expression of SERPINE1 was further verified in clear cell renal cell carcinoma (ccRCC) through qRT-PCR of clinical patient samples, validation in independent cohorts using The Gene Expression Omnibus (GEO) database, and proteomic validation using the Clinical Proteomic Tumor Analysis Consortium (CPTAC) database.Results: The expression of SERPINE1 was dysregulated in cancers and enriched in endothelial cells and fibroblasts. Copy number amplification and low DNA promoter methylation could be partly responsible for high SERPINE1 expression. High SERPINE1 expression was associated with poor prognosis in 21 cancers. The results of gene set enrichment analysis (GSEA) indicated SERPINE1 involvement in the immune response and tumor malignancy. SERPINE1 expression was also associated with the expression of several immunoregulators and immune cell infiltration and could play an immunosuppression role. Besides, SERPINE1 was found to be related with TMB, MSI, immunotherapy response and sensitivity to several drugs in cancers. Finally, the high expression of SERPINE1 in ccRCC was verified using qRT-PCR performed on patient samples, six independent GEO cohorts, and proteomic data from the CPTAC database.Conclusion: The findings of the present study revealed that SERPINE1 exhibits aberrant expression in various types of cancers and is associated with cancer immunity and tumor malignancy, providing novel insights for individualized cancer treatment

UV RESISTANCE LOCUS 8 From Chrysanthemum morifolium Ramat (CmUVR8) Plays Important Roles in UV-B Signal Transduction and UV-B-Induced Accumulation of Flavonoids

UV Resistance Locus 8 (UVR8), an ultraviolet-B (UV-B; 280–315 nm) photoreceptor, participates in the regulation of various plant growth and developmental processes. UV-B radiation is an important factor enhancing the production of active components in medicinal plants. To-date, however, studies on UV-B photoreceptors have largely focused on Arabidopsis, and the functions of UVR8 in medicinal plants are still largely unknown. In the present study, a homolog of Arabidopsis UVR8, CmUVR8, was isolated from Chrysanthemum morifolium Ramat, and its structure and function were analyzed in detail. Protein sequence analysis showed that CmUVR8 contained nine conserved regulators of chromosome condensation 1 repeats, seven conserved bladed propellers, one C27 region, three “GWRHT” motifs and several crucial amino acid residues (such as 14 Trps and 2 Args), similar to AtUVR8. 3-D structural analysis of CmUVR8 indicated that its structure was similar to AtUVR8. Heterologous expression of CmUVR8 could rescued the deficient phenotype of uvr8-6, a mutant of UVR8 in Arabidopsis, indicating the role of CmUVR8 in the regulation of hypocotyl elongation and HY5 gene expression under UV-B irradiation. Moreover, CmUVR8 regulates UV-B-induced expression of four flavonoids biosynthesis-related genes and the UV-B-induced accumulation of flavonoids. Furthermore, the interaction between CmUVR8 and CmCOP1 were confirmed using a yeast two-hybrid assay. These results indicated that CmUVR8 plays important roles in UV-B signal transduction and the UV-B-induced accumulation of flavonoids, as a counterpart of AtUVR8

Age-related differences in risk factors, clinical characteristics, and outcomes for intracerebral hemorrhage

Background and purposeIntracerebral hemorrhage (ICH) is a severe form of stroke that remains understudied in the young adults. We aimed to investigate the clinical presentation, and risk factors associated with ICH in this age group and compare them to older patients.MethodsOur study included ICH patients admitted between March 2016 and December 2021 in the First Affiliated Hospital of Chongqing Medical University from our ongoing prospective cohort database. Demographic characteristics, etiology, risk factors, and clinical outcomes were compared between elderly and young patients. Furthermore, logistic regression analysis was employed to explore risk factors associated with the functional outcome at 3-months.ResultsWe selected 1,003 patients (mean age, 59.9 ±13.8 years old), 746 (74.4%) patients were aged &gt;50 years. The logistic regression analysis showed young patients have a higher proportion of secondary ICH, higher white blood cell count and higher body mass index (BMI), but less diabetes mellitus. Of all patients, predictors of 3-month functional independence was first-ever ICH and age ≤50 years. The history of nephropathy and stroke, higher baseline NIHSS score, larger hematoma volume, and the presence of hydrocephalus were associated with poor outcomes. And the white blood cell count could significantly influence the prognosis among young ICH patients. Three-month functional outcome based on modified Rankin scale score was better in young patients than the elderly (OR, 1.232; 95% CI, 1.095–1.388; p &lt; 0.001).ConclusionsThe highest incidence of ICH occurs in the age groups of 50–59 and 60–69. ICH in young adults had higher white blood cell and BMI compared to the elderly, and differs in etiological distribution. The young patients also had similar short-term mortality but more favorable functional outcomes than the elderly. Furthermore, NIHSS score and larger hematoma volumes were associated with poor outcome in all patients

Enhanced metabolic flux of methylerythritol phosphate (MEP) pathway by overexpression of Ginkgo biloba 1-Hydroxy-2-methyl-2-(E)-butenyl 4-diphosphate Reductase 1 (GbHDR1) gene in poplar

Terpenoids are of great interests in a broad range of health-beneficial biological activities and various industrial applications. In plants, terpenoids are synthesized by two distinct pathways, methylerythritol phosphate (MEP) and mevalonate pathways in a separate location. MEP pathway supplies isoprene precursors isopentenyl diphosphate (IPP) and its isomer dimethylallyl diphosphate (DMAPP) of terpenoid biosynthesis in plant plastids. The MEP pathway has been an engineering target to increase the metabolic flux towards higher terpenoid production in plants. 1-Hydroxy-2-methyl-2-(E)-butenyl-4-diphosphate reductase (HDR) is the terminal step of the MEP pathway to regulate the terpenoid biosynthesis and is encoded by three paralogous genes in Ginkgo biloba. In this study, we assessed the effect of overexpression of GbHDR1 on terpenoid metabolism in poplar plants. Overexpression of GbHDR1 in poplar plants accelerated growth and delayed winter-bud formation. Transcript levels of gibberellin, chlorophylls, and carotenoid biosynthetic genes in GbHDR1-overexpressing (GbHDR1ox) poplars were up-regulated, suggesting metabolic flux enhancement. Moreover, enhanced contents of chlorophylls and carotenoids in the leaves of the GbHDR1ox plants resulted in a higher photosynthetic rate as a consequence. Therefore, we expect the GbHDR1 overexpression will be a desirable engineering point of the MEP pathway for enhancing terpenoid metabolic flux and production in plants.This work was supported by the National Research Foundation of Korea (NRF) grant (2021R1A5A8029490); the Korea Foundation for Women In Science, Engineering and Technology (WISET) Returners into R&D Program grant; the intramural grant (2Z06670) from the Korea Institute of Science and Technology (KIST), Republic of Korea

Result of a year-long animal survey in a state-owned forest farm in Beijing, China

BackgroundArtificial forest can have great potential in serving as habitat to wildlife, depending on different management methods. As the state-owned forest farms now play a new role in ecological conservation in China, the biological richness of this kind of land-use type is understudied. Once owned by a mining company, a largest state-owned forest farm, Jingxi Forest Farm, has been reformed to be a state-owned forest farm with the purpose of conservation since 2017. Although this 116.4 km2 forest farm holds a near-healthy montaine ecosystem very representative in North China, a large proportion of artificial coniferous forest in the forest farm has been proven to hold less biodiversity than natural vegetation. This situation, however, provides a great opportunity for ecological restoration and biodiversity conservation. Therefore, from November 2019 to December 2020, we conducted a set of biodiversity surveys, whose results will serve as a baseline for further restoration and conservation.New informationHere, we report the result of a multi-taxa fauna diversity survey conducted in Jingxi Forest Farm mainly in year 2020 with explicit spatial information. It is the first survey of its kind conducted in this area, revealing a total of 19 species of mammals, 86 birds, four reptiles, two amphibians and one fish species, as well as 101 species of insects. Four species of mammals are identified as data-poor species as they have less than 100 occurrence records with coordination in the GBIF database. One species of insect, representing one new provincial record genus of Beijing, is reported

Modeling Mixed Freeway Traffic: Human-driven and Self-driven Cars

Connected automated vehicles (CAVs) are typically equipped with communication devices (e.g., dedicated short range communications (DSRC)) and on-board sensors (e.g., Radar, Lidar, Camera, etc.). Communication devices would enable the exchange of real-time information between vehicles and infrastructures via vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) channels. Sensors equipped in vehicles are providing various vehicle sensor data (VSD) such as the CAV’s GPS location, speed and moving direction (trajectory). Existing studies have shown the effectiveness of using CAV trajectories as input in many traffic control models. However, it can be expected that CAVs and human-driven vehicles (HVs) will co-exist on the transportation network in a long period. Hence, to support various traffic control tasks, it is critical to develop a reliable model to understand the real-time traffic pattern in a mixed CAV and HV environment. To satisfy such needs, this project firstly introduces a novel macroscopic traffic flow model which treats CAVs and HVs as separate groups, where a new set of factors are introduced to represent the speed change of HVs due to following CAVs in the traffic stream. Then grounded on the traffic flow model, an optimization function will make real-time adjustment of CAVs’ desired speeds for minimizing the total freeway travel delays. Selecting a segment of I-15 in Salt Lake City as the study site, the research team conducts extensive simulation experiments to evaluate highway performance under different demand levels and CAV penetration rates. Corresponding data analysis reveals that there should exist a critical CAV ratio that can greatly reduce the speed difference between CAVs and HVs in the traffic stream, given the demand pattern. Further discussions have highlighted the need of setting up guidance on highway capacity analysis under the CAV environment

Vehicle Sensor Data (VSD) Based Traffic Control in Connected Automated Vehicle (CAV) Environment

Connected automated vehicles (CAVs) are typically equipped with communication devices (e.g., dedicated short range communications (DSRC)) and on-board sensors (e.g., Radar, Lidar, Camera, etc.). Communication devices would enable the exchange of real-time information between vehicles and infrastructures via vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) channels. Sensors equipped in vehicles are providing various vehicle sensor data (VSD) such as the CAV’s GPS location, speed and moving direction (trajectory). Existing studies have shown the effectiveness of using CAV trajectories as input in many traffic control models. However, it can be expected that CAVs and human-driven vehicles (HVs) will co-exist on the transportation network in a long period. Hence, to support various traffic control tasks, it is critical to develop a reliable model to understand the real-time traffic pattern in a mixed CAV and HV environment. To satisfy such needs, this project firstly introduces a novel macroscopic traffic flow model which treats CAVs and HVs as separate groups, where a new set of factors are introduced to represent the speed change of HVs due to following CAVs in the traffic stream. Then grounded on the traffic flow model, an optimization function will make real-time adjustment of CAVs’ desired speeds for minimizing the total freeway travel delays. Selecting a segment of I-15 in Salt Lake City as the study site, the research team conducts extensive simulation experiments to evaluate highway performance under different demand levels and CAV penetration rates. Corresponding data analysis reveals that there should exist a critical CAV ratio that can greatly reduce the speed difference between CAVs and HVs in the traffic stream, given the demand pattern. Further discussions have highlighted the need of setting up guidance on highway capacity analysis under the CAV environment