p70S6K1 (S6K1)-Mediated Phosphorylation Regulates Phosphatidylinositol 4-Phosphate 5-Kinase Type I \u3cem\u3eγ\u3c/em\u3e Degradation and Cell Invasion

Phosphatidylinositol 4-phosphate 5-kinase type I γ (PIPKIγ90) ubiquitination and subsequent degradation regulate focal adhesion assembly, cell migration, and invasion. However, it is unknown how upstream signals control PIPKIγ90 ubiquitination or degradation. Here we show that p70S6K1 (S6K1), a downstream target of mechanistic target of rapamycin (mTOR), phosphorylates PIPKIγ90 at Thr-553 and Ser-555 and that S6K1-mediated PIPKIγ90 phosphorylation is essential for cell migration and invasion. Moreover, PIPKIγ90 phosphorylation is required for the development of focal adhesions and invadopodia, key machineries for cell migration and invasion. Surprisingly, substitution of Thr-553 and Ser-555 with Ala promoted PIPKIγ90 ubiquitination but enhanced the stability of PIPKIγ90, and depletion of S6K1 also enhanced the stability of PIPKIγ90, indicating that PIPKIγ90 ubiquitination alone is insufficient for its degradation. These data suggest that S6K1-mediated PIPKIγ90 phosphorylation regulates cell migration and invasion by controlling PIPKIγ90 degradation

TCN-GAT multivariate load forecasting model based on SHAP value selection strategy in integrated energy system

Load forecasting is an important prerequisite and foundation for ensuring the rational planning and safe operation of integrated energy systems. In view of the interactive coupling problem among multivariate loads, this paper constructs a TCN-GAT multivariate load forecasting model based on SHAP (Shapley Additive Explanation) value selection strategy. The model uses temporal convolutional networks (TCN) to model the multivariate load time series of the integrated energy system, and applies the global attention mechanism (GAT) to process the output of the network hidden layer state, thereby increasing the weight of key features that affect load changes. The input variables are filtered by calculating the SHAP values of each feature, and then returned to the TCN-GAT model for training to obtain multivariate load forecasting results. This can remove the interference of features with low correlation to the model and improve the forecasting effect. The analysis results of practical examples show that compared with other models, the TCN-GAT multivariate load forecasting model based on SHAP value selection strategy proposed in this paper can further reduce the forecasting error and has better forecasting accuracy and application value

On the Responses of Mesosphere and Lower Thermosphere Temperatures to Geomagnetic Storms at Low and Middle Latitudes

Observations from lidars and satellites have shown that large neutral temperature increases and decreases occur in the middle and low latitudes of the mesosphere and lower thermosphere region during geomagnetic storms. Here we undertake first-principles simulations of mesosphere and lower thermosphere temperature responses to storms using the Thermosphere Ionosphere Mesosphere Electrodynamics General Circulation Model to elucidate the nature and causes of these changes. Temperature variations were not uniform; instead, nighttime temperatures changed earlier than daytime temperatures, and temperatures changed earlier at high latitudes than at low ones. Furthermore, temperatures increased in some places/times and decreased in others. As the simulation behaves similar to observations, it provides an opportunity to understand physical processes that drive the observed changes. Our analysis has shown that they were produced mainly by adiabatic heating/cooling that was associated with vertical winds resulting from general circulation changes, with additional contributions from vertical heat advection

Operation Optimization of Multi-District Integrated Energy System Considering Flexible Demand Response of Electric and Thermal Loads

Multi-district integrated energy system (IES) can make full use of the complementary characteristics of district power and thermal system, and loads in different districts. It can improve the flexibility and economy of system operation, which has a good development prospect. Firstly, based on the general energy transfer model of the district heating network (DHN), the DHN system is described by the basic equations of the heating network and nodes considering the characteristics of the transmission time delay and heat loss in pipelines. A coupling model of DHN and multi-district IES is established. Secondly, the flexible demand response (FDR) model of electric and thermal loads is established. The load characteristics of each district in IES are studied. A shiftable load model based on the electric quantity balance is constructed. Considering the flexibility of the heat demand, a thermal load adjustment model based on the comfort constraint is constructed to make the thermal load elastic and controllable in time and space. Finally, a mixed integer linear programming (MILP) model for operation optimization of multi-district IES with the DHN considering the FDR of electric and thermal loads is established based on the supply and demand sides. The result shows that the proposed model makes full use of the complementary characteristics of electric and thermal loads in different districts. It realizes the coordinated distribution of thermal energy among different districts and improves the efficiency of thermal energy utilization through the DHN. FDR effectively reduces the peak-valley difference of loads. It further reduces the total operating cost by the coordinated operation of the DHN and multi-district IES. Document type: Articl

High CRLF2 expression associates with IKZF1 dysfunction in adult acute lymphoblastic leukemia without CRLF2 rearrangement.

Overexpression of cytokine receptor-like factor 2 (CRLF2) due to chromosomal rearrangement has been observed in acute lymphoblastic leukemia (ALL) and reported to contribute to oncogenesis and unfavorable outcome in ALL. We studied B-ALL and T-ALL patients without CRLF2 rearrangement and observed that CRLF2 is significantly increased in a subset of these patients. Our study shows that high CRLF2expression correlates with high-risk ALL markers, as well as poor survival. We found that the IKZF1-encoded protein, Ikaros, directly binds to the CRLF2 promoter and regulates CRLF2 expression in leukemia cells. CK2 inhibitor, which can increase Ikaros activity, significantly increases Ikaros binding in ALL cells and suppresses CRLF2 expression in an Ikaros-dependent manner. CRLF2 expression is significantly higher in patients with IKZF1 deletion as compared to patients without IKZF1 deletion. Treatment with CK2 inhibitor also results in an increase in IKZF1 binding to the CRLF2 promoter and suppression of CRLF2 expression in primary ALL cells. We further observed that CK2 inhibitor induces increased H3K9me3 histone modifications in the CRLF2 promoter in ALL cell lines and primary cells. Taken together, our results demonstrate that high expression of CRLF2 correlates with high-risk ALL and short survival in patients without CRLF2 rearrangement. Our results are the first to demonstrate that the IKZF1-encoded Ikaros protein directly suppresses CRLF2 expression through enrichment of H3K9me3 in its promoter region. Our data also suggest that high CRLF2 expression works with the IKZF1 deletion to drive oncogenesis of ALL and has significance in an integrated prognostic model for adult high-risk ALL

Prediction of Antimicrobial Peptides Based on Sequence Alignment and Feature Selection Methods

Antimicrobial peptides (AMPs) represent a class of natural peptides that form a part of the innate immune system, and this kind of ‘nature's antibiotics’ is quite promising for solving the problem of increasing antibiotic resistance. In view of this, it is highly desired to develop an effective computational method for accurately predicting novel AMPs because it can provide us with more candidates and useful insights for drug design. In this study, a new method for predicting AMPs was implemented by integrating the sequence alignment method and the feature selection method. It was observed that, the overall jackknife success rate by the new predictor on a newly constructed benchmark dataset was over 80.23%, and the Mathews correlation coefficient is 0.73, indicating a good prediction. Moreover, it is indicated by an in-depth feature analysis that the results are quite consistent with the previously known knowledge that some amino acids are preferential in AMPs and that these amino acids do play an important role for the antimicrobial activity. For the convenience of most experimental scientists who want to use the prediction method without the interest to follow the mathematical details, a user-friendly web-server is provided at http://amp.biosino.org/

Pengaruh Pendekatan Pembelajaran Matematika Realistik Terhadap Prestasi Belajar Matematika Ditinjau Dari Kemampuan Numerik Siswa Kelas VIII SMP Negeri 2 Amlapura

Penelitian ini bertujuan untuk mengetahui dan mendeskripsikan pengaruh pendekatan pembelajaran matematika realistik terhadap prestasi belajar matematika ditinjau dari kemampuan numerik siswa. Penelitian ini merupakan eksperimen semu dilaksanakan dengan menggunakan rancangan the post test only control group design. Populasinya adalah seluruh siswa kelas VIII SMP Negeri 2 Amlapura tahun pelajaran 2013-2014. Dari delapan kelas yang ada, empat kelas dipilih sebagai sampel yakni dua kelas sebagai kelas eksperimen dan dua kelas sebagai kelas kontrol yang diambil dengan teknik random. Data penelitian dikumpulkan menggunakan tes, yaitu tes kemampuan numerik dan tes prestasi belajar matematika. Data yang diperoleh dianalisis dengan analisis varians dua jalur dilanjutkan dengan uji Tukey. Berdasarkan hasil analisis data dan pembahasan, dapat disimpulkan, terdapat perbedaan yang signifikan prestasi belajar matematika antara siswa yang mengikuti pendekatan pembelajaran matematika realistik dengan siswa yang mengikuti pendekatan pembelajaran konvensional. Terdapat pengaruh interaksi antara pendekatan pembelajaran matematika realistik dan kemampuan numerik terhadap prestasi belajar matematika. Pada Siswa yang memiliki kemampuan numerik tinggi, prestasi belajar matematika siswa yang mengikuti pendekatan pembelajaran matematika realistik lebih baik daripada pendekatan konvensional. Pada siswa yang memiliki kemampuan numerik rendah, prestasi belajar matematika siswa yang mengikuti pendekatan pembelajaran matematika realistik tetap lebih tinggi dari siswa yang mengikuti pendekatan pembelajaran konvensional.Kata Kunci : pendekatan pembelajaran matematika realistik, kemampuan numerik, dan prestasi belajar matematika The study aimed at finding out and describing the contribution of realistic mathematic instructional approach towards mathematic learning achievement viewed from numeric skills. It was a quasi-experimental research by utilizing the post test only control group design. The study involved all students class VIII SMP Negeri 2 Amlapura in 2013-2014 as the population. Four classes of the students were chosen from eight parallel classes as the samples consisting of two classes as experimental and another two classes as control groups. They were determined based on random technique. The data were collected by testing, involving numeric ability and mathematic achievement tests. They were analysed based on two tailed variant analysis followed by Tukey-test. The results indicated that there was a significant difference between mathematic learning achievement of the students joining realistic mathematic instruction and those joining a conventional approach. There was an interactional contribution of realistic mathematic instructional approach and numeric ability towards mathematic learning achievement. The students having higher numeric skills, when joining realistic mathematic instruction approach their mathematic learning achievement was found better or higher than those joining a conventional approach. The students having lower numeric skills, when joining realistic mathematic instruction approach, their mathematic learning achievement was found better or higher than those joining a conventional approach

The global contribution of soil mosses to ecosystem services

Soil mosses are among the most widely distributed organisms on land. Experiments and observations suggest that they contribute to terrestrial soil biodiversity and function, yet their ecological contribution to soil has never been assessed globally under natural conditions. Here we conducted the most comprehensive global standardized field study to quantify how soil mosses influence 8 ecosystem services associated with 24 soil biodiversity and functional attributes across wide environmental gradients from all continents. We found that soil mosses are associated with greater carbon sequestration, pool sizes for key nutrients and organic matter decomposition rates but a lower proportion of soil-borne plant pathogens than unvegetated soils. Mosses are especially important for supporting multiple ecosystem services where vascular-plant cover is low. Globally, soil mosses potentially support 6.43 Gt more carbon in the soil layer than do bare soils. The amount of soil carbon associated with mosses is up to six times the annual global carbon emissions from any altered land use globally. The largest positive contribution of mosses to soils occurs under a high cover of mat and turf mosses, in less-productive ecosystems and on sandy and salty soils. Our results highlight the contribution of mosses to soil life and functions and the need to conserve these important organisms to support healthy soils.The study work associated with this paper was funded by a Large Research Grant from the British Ecological Society (no. LRB17\1019; MUSGONET). D.J.E. is supported by the Hermon Slade Foundation. M.D.-B. was supported by a Ramón y Cajal grant from the Spanish Ministry of Science and Innovation (RYC2018-025483-I), a project from the Spanish Ministry of Science and Innovation for the I + D + i (PID2020-115813RA-I00 funded by MCIN/AEI/10.13039/501100011033a) and a project PAIDI 2020 from the Junta de Andalucía (P20_00879). E.G. is supported by the European Research Council grant agreement 647038 (BIODESERT). M.B. is supported by a Ramón y Cajal grant from Spanish Ministry of Science (RYC2021-031797-I). A.d.l.R is supported by the AEI project PID2019-105469RB-C22. L.W. and Jianyong Wang are supported by the Program for Introducing Talents to Universities (B16011) and the Ministry of Education Innovation Team Development Plan (2013-373). The contributions of T.G. and T.U.N. were supported by the Research Program in Forest Biology, Ecology and Technology (P4-0107) and the research projects J4-3098 and J4-4547 of the Slovenian Research Agency. The contribution of P.B.R. was supported by the NSF Biological Integration Institutes grant DBI-2021898. J. Durán and A. Rodríguez acknowledge support from the FCT (2020.03670.CEECIND and SFRH/BDP/108913/2015, respectively), as well as from the MCTES, FSE, UE and the CFE (UIDB/04004/2021) research unit financed by FCT/MCTES through national funds (PIDDAC)