A new measurement of sequence conservation

<p>Abstract</p> <p>Background</p> <p>Understanding sequence conservation is important for the study of sequence evolution and for the identification of functional regions of the genome. Current studies often measure sequence conservation based on every position in contiguous regions. Therefore, a large number of functional regions that contain conserved segments separated by relatively long divergent segments are ignored. Our goal in this paper is to define a new measurement of sequence conservation such that both contiguously conserved regions and discontiguously conserved regions can be detected based on this new measurement. Here and in the following, conserved regions are those regions that share similarity higher than a pre-specified similarity threshold with their homologous regions in other species. That is, conserved regions are good candidates of functional regions and may not be always functional. Moreover, conserved regions may contain long and divergent segments.</p> <p>Results</p> <p>To identify both discontiguously and contiguously conserved regions, we proposed a new measurement of sequence conservation, which measures sequence similarity based only on the conserved segments within the regions. By defining conserved segments using the local alignment tool CHAOS, under the new measurement, we analyzed the conservation of 1642 experimentally verified human functional non-coding regions in the mouse genome. We found that the conservation in at least 11% of these functional regions could be missed by the current conservation analysis methods. We also found that 72% of the mouse homologous regions identified based on the new measurement are more similar to the human functional sequences than the aligned mouse sequences from the UCSC genome browser. We further compared BLAST and discontiguous MegaBLAST with our method. We found that our method picks up many more conserved segments than BLAST and discontiguous MegaBLAST in these regions.</p> <p>Conclusions</p> <p>It is critical to have a new measurement of sequence conservation that is based only on the conserved segments in one region. Such a new measurement can aid the identification of better local "orthologous" regions. It will also shed light on the identification of new types of conserved functional regions in vertebrate genomes <abbrgrp><abbr bid="B1">1</abbr></abbrgrp>.</p

Research on the Construction of Agro-Ecological Park Under the Background of Smart Agriculture - Take Zengcheng Chuangxian Smart Agriculture Model Park as an Example

[EN] In the process of agricultural modernization in China, smart. agriculture is the new direction of rural development, and scientific development of agroecological parks is an important starting point to promote agricultural transformation and upgrading, as well as an effective way to promote rural revitalization. At present, the application of smart agriculture in agricultural ecological parks in China is still in the experimental stage, and the pilots have been carried out in various regions, but most of them are almost stagnant at the level of agricultural production, failing to maximize the use of smart agricultural resources to build agroecological parks. This paper analyzes the case of Zengcheng Chuangxian Smart Agriculture Model Park on the basis of describing its current development and the existing problems after the introduction of smart agriculture, and puts forward relevant suggestions.Chen, J.; Cai, Y.; Gaoge, Y.; Lv, H. (2022). Research on the Construction of Agro-Ecological Park Under the Background of Smart Agriculture - Take Zengcheng Chuangxian Smart Agriculture Model Park as an Example. En 4th International Conference on Advanced Research Methods and Analytics (CARMA 2022). Editorial Universitat Politècnica de València. 283-283. http://hdl.handle.net/10251/18976228328

Integrated Sensing, Computation, and Communication: System Framework and Performance Optimization

Integrated sensing, computation, and communication (ISCC) has been recently considered as a promising technique for beyond 5G systems. In ISCC systems, the competition for communication and computation resources between sensing tasks for ambient intelligence and computation tasks from mobile devices becomes an increasingly challenging issue. To address it, we first propose an efficient sensing framework with a novel action detection module. It can reduce the overhead of computation resource by detecting whether the sensing target is static. Subsequently, we analyze the sensing performance of the proposed framework and theoretically prove its effectiveness with the help of the sampling theorem. Then, we formulate a sensing accuracy maximization problem while guaranteeing the quality-of-service (QoS) requirements of tasks. To solve it, we propose an optimal resource allocation strategy, in which the minimal resource is allocated to computation tasks, and the rest is devoted to sensing tasks. Besides, a threshold selection policy is derived. Compared with the conventional schemes, the results further demonstrate the necessity of the proposed sensing framework. Finally, a real-world test of action recognition tasks based on USRP B210 is conducted to verify the sensing performance analysis, and extensive experiments demonstrate the performance improvement of our proposal by comparing it with some benchmark schemes

Feature Selection Approaches for Optimising Music Emotion Recognition Methods

The high feature dimensionality is a challenge in music emotion recognition. There is no common consensus on a relation between audio features and emotion. The MER system uses all available features to recognize emotion; however, this is not an optimal solution since it contains irrelevant data acting as noise. In this paper, we introduce a feature selection approach to eliminate redundant features for MER. We created a Selected Feature Set (SFS) based on the feature selection algorithm (FSA) and benchmarked it by training with two models, Support Vector Regression (SVR) and Random Forest (RF) and comparing them against with using the Complete Feature Set (CFS). The result indicates that the performance of MER has improved for both Random Forest (RF) and Support Vector Regression (SVR) models by using SFS. We found using FSA can improve performance in all scenarios, and it has potential benefits for model efficiency and stability for MER task

Imaging diagnosis of chronic encapsulated intracerebral hematoma : a comparison of computed tomography (CT) and magnetic resonance imaging (MRI) characteristics

Background: Chronic encapsulated intracerebral hematoma (CEICH) is a rare type of intracerebral hematoma that is often misdiagnosed. To explore the characteristics of CEICH on computerized tomography (CT) and magnetic resonance imaging (MRI). Material/Methods: Clinical, CT, MRI, and susceptibility weighted imaging (SWI) data of 5 patients who were diagnosed with CEICH on surgery and pathology were retrospectively analyzed. Results: CT showed quasi-circular or elliptical lesions with clear borders in all 5 cases and iso-density or low-density in the center of lesions that were surrounded by peripheral edema in 2 cases. CT showed mass effect in 5 patients. On contrast-enhanced CT, 2 cases exhibited mild ring enhancement, and 3 cases exhibited moderate ring enhancement. MRI showed cystic lesions with high uniform signal on T1-weighted images (T1WI) and T2-weighted images (T2WI), a lowsignal ring sign on the coated cystic lesions on T2WI, a lower signal ring sign on SWI, and ring enhancement after administration of contrast. Conclusions: CT imaging of CEICH did not reveal any typical characteristics in the studied patients. MRI showed an envelope with a "ring" an

MiR-20a-5p represses multi-drug resistance in osteosarcoma by targeting the KIF26B gene

BACKGROUND: Chemoresistance hinders curative cancer chemotherapy in osteosarcoma (OS), resulting in only an approximately 20 % survival rate in patients with metastatic disease at diagnosis. Identifying the mechanisms responsible for regulating chemotherapy resistance is crucial for improving OS treatment. METHODS: This study was performed in two human OS cell lines (the multi-chemosensitive OS cell line G-292 and the multi-chemoresistant OS cell line SJSA-1). The levels of miR-20a-5p and KIF26B mRNA expression were determined by quantitative real-time PCR. KIF26B protein levels were determined by western blot analysis. Cell viability was assessed by MTT assay. Apoptosis was evaluated by flow cytometry. RESULTS: We found that miR-20a-5p was more highly expressed in G-292 cells than in SJSA-1 cells. Forced expression of miR-20a-5p counteracted OS cell chemoresistance in both cell culture and tumor xenografts in nude mice. One of miR-20a-5p's targets, kinesin family member 26B (KIF26B), was found to mediate the miR-20a-5p-induced reduction in OS chemoresistance by modulating the activities of the MAPK/ERK and cAMP/PKA signaling pathways. CONCLUSIONS: In addition to providing mechanistic insights, our study revealed that miR-20a-5p and KIF26B contribute to OS chemoresistance and determined the roles of these genes in this process, which may be critical for characterizing drug responsiveness and overcoming chemoresistance in OS patients