LINC00606 promotes glioblastoma progression through sponge miR-486-3p and interaction with ATP11B.

BACKGROUND: LncRNAs regulate tumorigenesis and development in a variety of cancers. We substantiate for the first time that LINC00606 is considerably expressed in glioblastoma (GBM) patient specimens and is linked with adverse prognosis. This suggests that LINC00606 may have the potential to regulate glioma genesis and progression, and that the biological functions and molecular mechanisms of LINC00606 in GBM remain largely unknown. METHODS: The expression of LINC00606 and ATP11B in glioma and normal brain tissues was evaluated by qPCR, and the biological functions of the LINC00606/miR-486-3p/TCF12/ATP11B axis in GBM were verified through a series of in vitro and in vivo experiments. The molecular mechanism of LINC00606 was elucidated by immunoblotting, FISH, RNA pulldown, CHIP-qPCR, and a dual-luciferase reporter assay. RESULTS: We demonstrated that LINC00606 promotes glioma cell proliferation, clonal expansion and migration, while reducing apoptosis levels. Mechanistically, on the one hand, LINC00606 can sponge miR-486-3p; the target gene TCF12 of miR-486-3p affects the transcriptional initiation of LINC00606, PTEN and KLLN. On the other hand, it can also regulate the PI3K/AKT signaling pathway to mediate glioma cell proliferation, migration and apoptosis by binding to ATP11B protein. CONCLUSIONS: Overall, the LINC00606/miR-486-3p/TCF12/ATP11B axis is involved in the regulation of GBM progression and plays a role in tumor regulation at transcriptional and post-transcriptional levels primarily through LINC00606 sponging miR-486-3p and targeted binding to ATP11B. Therefore, our research on the regulatory network LINC00606 could be a novel therapeutic strategy for the treatment of GBM.

LncRNA SLC1A5-AS/MZF1/ASCT2 Axis Contributes to Malignant Progression of Hepatocellular Carcinoma.

BACKGROUND: Hypoxia is a pivotal factor influencing cellular gene expression and contributing to the malignant progression of tumors. Metabolic anomalies under hypoxic conditions are predominantly mediated by mitochondria. Nonetheless, the exploration of hypoxia-induced long noncoding RNAs (lncRNAs) associated with mitochondria remains largely uncharted. METHODS: We established hypoxia cell models using primary human hepatocytes (PHH) and hepatocellular carcinoma (HCC) cell lines. We isolated mitochondria for high-throughput sequencing to investigate the roles of candidate lncRNAs in HCC progression. We employed in vitro and in vivo assays to evaluate the functions of solute carrier family 1 member 5 antisense lncRNA (SLC1A5-AS). RNA-seq was utilized to scrutinize the comprehensive genome profile regulated by SLC1A5-AS in HCC. Subsequently, quantitative real-time polymerase chain reaction (qRT-PCR) and western blot analysis were utilized to validate the expression of alanine-serine-cysteine transporter 2 (ASCT2, encoded by the SLC1A5 gene), and a glutamine uptake assay was employed to estimate the glutamine uptake capacity of Huh-7 cells after SLC1A5-AS overexpression. To delve into the mechanisms governing the regulation of SLC1A5 expression by SLC1A5-AS, we employed a biotin-labeled SLC1A5-AS probe in conjunction with a western blot assay to confirm the interactions between SLC1A5-AS and candidate transcription factors. Luciferase reporter assays and chromatin immunoprecipitation (ChIP) were utilized to authenticate the effects of the predicted transcription factors on SLC1A5 promoter activity. RESULTS: Following the screening, we identified CTB-147N14.6, derived from the antisense strand of the SLC1A5 gene, which we have named SLC1A5-AS. SLC1A5-AS exhibited significantly elevated expression levels in HCC tissue and was associated with poor prognosis in HCC patients. In vitro and in vivo assays revealed that the overexpression of SLC1A5-AS significantly heightened cell invasion and metastasis. RNA-seq data unveiled SLC1A5-AS involvement in glutamine metabolism, left-handed amino (L-amino) acid transmembrane transporter activity, and the nuclear factor kappa-B (NF-κB) signaling pathway. Overexpression of SLC1A5-AS markedly increased ASCT2 mRNA/protein levels, thereby enhancing glutamine uptake and promoting the growth and metastasis of HCC cells. Mechanistically, higher RNA levels of SLC1A5-AS directly bound with myeloid zinc finger 1 (MZF1), acting as a transcriptional repressor, thus diminishing its binding to the SLC1A5 promoter region. CONCLUSIONS: Our findings unveil a novel role for the lncRNA SLC1A5-AS in glutamine metabolism, suggesting that targeting SLC1A5-AS/MZF1, in conjunction with ASCT2 inhibitor treatment, could be a potential therapeutic strategy for this disease.

Forecasting actual evapotranspiration without climate data based on stacked integration of DNN and meta-heuristic models across China from 1958 to 2021.

As a non-linear phenomenon that varies along with agro-climatic conditions alongside many other factors, Evapotranspiration (ET) process represents a complexity when be assessed especially if there is a data scarcity in the weather data. However, even under such a data scarcity, the accurate estimates of ET values remain necessary for precise irrigation. So, the present study aims to: i) evaluate the performance of six hybrid machine learning (ML) models in estimating the monthly actual ET values under different agro-climatic conditions in China for seven provinces (Shandong, Jiangsu, Zhejiang, Fujian, Jiangxi, Hubei, and Henan), and ii) select the best-developed model based on statistical metrics and reduce errors between predicted and actual ET (AET) values. AET datasets were divided into 78% for model training (from 1958 to 2007) and the remaining was used for testing (from 2008 to 2021). Deep Neural Networks (DNN) was used as a standalone model at first then the stacking method was applied to integrate DNN with data-driven models such as Additive regression (AR), Random Forest (RF), Random Subspace (RSS), M5 Burned Tree (M5P) and Reduced Error Purning Tree (REPTree). Partial Auto-Correlation Function (PACF) was used for selection of the best lags inputs to the developed models. Results have revealed that DNN-based hybrid models held better performance than non-hybrid DNN models, such that the DNN-RF algorithm outperformed others during both training and testing stages, followed by DNN-RSS. This model has acquired the best values of every statistical measure [MAE (10.8, 12.9), RMSE (15.6, 17.4), RAE (31.9%, 41.4%), and RRSE (39.3%, 47.2%)] for training and testing, respectively. In contrast, the DNN model held the worst performance [MAE (14.9, 13.7), RMSE (20.1, 18.2), RAE (43.9%, 43.7%), and RRSE (50.6%, 49.3%)], for training and testing, respectively. Results from the study presented have revealed the capability of DNN-based hybrid models for long-term predictions of the AET values. Moreover, the DNN-RF model has been suggested as the most suitable model to improve future investigation for AET predictions, which could benefit the enhancement of the irrigation process and increase crop yield.

FlyDetector-Automated Monitoring Platform for the Visual-Motor Coordination of Honeybees in a Dynamic Obstacle Scene Using Digital Paradigm.

Vision plays a crucial role in the ability of compound-eyed insects to perceive the characteristics of their surroundings. Compound-eyed insects (such as the honeybee) can change the optical flow input of the visual system by autonomously controlling their behavior, and this is referred to as visual-motor coordination (VMC). To analyze an insect's VMC mechanism in dynamic scenes, we developed a platform for studying insects that actively shape the optic flow of visual stimuli by adapting their flight behavior. Image-processing technology was applied to detect the posture and direction of insects' movement, and automatic control technology provided dynamic scene stimulation and automatic acquisition of perceptual insect behavior. In addition, a virtual mapping technique was used to reconstruct the visual cues of insects for VMC analysis in a dynamic obstacle scene. A simulation experiment at different target speeds of 1-12 m/s was performed to verify the applicability and accuracy of the platform. Our findings showed that the maximum detection speed was 8 m/s, and triggers were 95% accurate. The outdoor experiments showed that flight speed in the longitudinal axis of honeybees was more stable when facing dynamic barriers than static barriers after analyzing the change in geometric optic flow. Finally, several experiments showed that the platform can automatically and efficiently monitor honeybees' perception behavior, and can be applied to study most insects and their VMC.

Spatio-temporal evolution and influencing factors of synergizing the reduction of pollution and carbon emissions - Utilizing multi-source remote sensing data and GTWR model.

Grasping current circumstances and influencing components of the synergistic degree regarding reducing pollution and carbon has been recognized as a crucial part of China in response to the protection of the environment and climate mitigation. With the introduction of remote sensing night-time light, CO2 emissions at multi-scale have been estimated in this study. Accordingly, an upward trend of "CO2-PM2.5" synergistic reduction was discovered, which was indicated by an increase of 78.18% regarding the index constructed of 358 cities in China from 2014 to 2020. Additionally, it has been confirmed that the reduction in pollution and carbon emissions could coordinate with economic growth indirectly. Lastly, it has identified the spatial discrepancy of influencing factors and the results have emphasized the rebound effect of technological progress and industrial upgrades, whilst the development of clean energy can offset the increase in energy consumption thus contributing to the synergy of pollution and carbon reduction. Moreover, it has been highlighted that environmental background, industrial structure, and socio-economic characteristics of different cities should be considered comprehensively in order to better achieve the goals of "Beautiful China" and "Carbon Neutrality".

Characterization of anatomical features, developmental roadmaps, and key genes of bamboo leaf epidermis.

The exact developmental roadmaps of bamboo leaf epidermis and the regulating genes are largely unknown. In this study, we comprehensively investigated the morphological features of the leaf epidermis of bamboo, Pseudosasa japonica. We also established the developmental roadmaps of the abaxial epidermis along the linearly growing leaf. A variant of P. japonica, P. japonica var. tsutsumiana, with smaller stomata and higher stomata density, was identified. Further analysis revealed that the higher stomata density of the variant was due to the abnormal increase in stomata columns within the single stomata band. This abnormal development of stomata bands was observed as early as the guard mother cell stage in the leaf division zone (DZ). Interestingly, the developmental pattern of the single stomata was similar in P. japonica and the variant. Molecular data showed that PjDLT (Dwarf and Low Tillering) was significantly downregulated in leaves DZ of the variant. Overexpression of PjDLT in Arabidopsis and rice results in smaller plants with lower stomata density, whereas downregulation or mutation of OsDLT results in increased stomata density. Our results highlight the morphological features and developmental schedule of the leaf epidermis of bamboo and provide evidence that DLT plays an important role in regulating stomata in bamboo and rice.

Docetaxel resistance-derived LINC01085 contributes to the immunotherapy of hormone-independent prostate cancer by activating the STING/MAVS signaling pathway.

Acquired docetaxel (doc) resistance, one of the major reasons for unfavorable prognosis in patients with aggressive hormone-independent prostate cancer (HIPC), is a major obstacle for patient treatment. Dysregulation of long non-coding RNAs promotes or suppresses chemoresistance in multiple cancers; however, the specific molecular mechanisms underlying HIPC remain unknown. In this study, we found that the LINC01085, as a tumor-suppressor, which showed significant clinically relevant in HIPC patients with doc-resistance. Mechanistically, in docetaxel-sensitive cells, LINC01085 could specifically bind to both TANK-binding kinase 1 (TBK1) and glycogen synthase kinase 3ß (GSK3ß), and higher LINC01085 RNA levels could inhibit TBK1 dimerization. Whereas, in doc-resistant cells, lower LINC01085 RNA level lost the strong binding with both, meanwhile, the interaction between TBK1 and GSK3ß enhanced which accelerated TBK1 phosphorylation at the Ser-172 site, resulting in decreased expression levels of PD-L1 and NF-κB as well as the secretion of type I/III interferons. Thus, Overexpression of LINC01085 combined with immune checkpoint blockade is an effective strategy for the treatment of HIPC patients.

Machine learning to predict dynamic changes of pathogenic Vibrio spp. abundance on microplastics in marine environment.

Microplastics are widely found in the marine environment. Recent studies have shown that pathogenic microorganisms can hitchhike on microplastics, which might act as a vector for the spread of pathogens. Vibrio spp. are known to be pathogenic to humans and can cause serious foodborne diseases. In this study, using datasets from an estuary and a mariculture zone in China, five machine learning models were established to predict the relative abundance of Vibrio spp. on microplastics. The results showed that deep neural network (DNN) model and RandomForest algorithm achieved the best predictive performance. Different data sources, data sampling, and processing methods had a little impact on the prediction performance of DNN and RandomForest models. SHapley Additive exPlanations (SHAP) indicated that salinity and temperature are the primary factors affecting the relative abundance of Vibrio spp. The prediction performances of the five machine learning models were further improved by feature selection, providing information to support future experimental research. The results of this study could help establish a long-term and dynamic monitoring system for the relative abundance of Vibrio spp. on microplastics in response to environmental factors as well as provide useful information for assessing the potential health impacts of microplastics on marine ecology and humans.

The role of phosphatidylserine on the membrane in immunity and blood coagulation.

The negatively charged aminophospholipid, phosphatidylserine (PtdSer), is located in the inner leaflet of the plasma membrane in normal cells, and may be exposed to the outer leaflet under some immune and blood coagulation processes. Meanwhile, Ptdser exposed to apoptotic cells can be recognized and eliminated by various immune cells, whereas on the surface of activated platelets Ptdser interacts with coagulation factors prompting enhanced production of thrombin which significantly facilitates blood coagulation. In the case where PtdSer fails in exposure or mistakenly occurs, there are occurrences of certain immunological and haematological diseases, such as the Scott syndrome and Systemic lupus erythematosus. Besides, viruses (e.g., Human Immunodeficiency Virus (HIV), Ebola virus (EBOV)) can invade host cells through binding the exposed PtdSer. Most recently, the Corona Virus Disease 2019 (COVID-19) has been similarly linked to PtdSer or its receptors. Therefore, it is essential to comprehensively understand PtdSer and its functional characteristics. Therefore, this review summarizes Ptdser, its eversion mechanism; interaction mechanism, particularly with its immune receptors and coagulation factors; recognition sites; and its function in immune and blood processes. This review illustrates the potential aspects for the underlying pathogenic mechanism of PtdSer-related diseases, and the discovery of new therapeutic strategies as well.

Epidemiological Characteristics of Rifampicin-Resistant Tuberculosis in Students - China, 2015-2019.

What is already known about this topic? The number of students with tuberculosis (TB) has been increasing since 2015. However, the prevalence of rifampicin-resistant tuberculosis (RR-TB) among student population is unclear. What is added by the report? The number of students with RR-TB has significantly increased from 2015 to 2019, especially in the western region of China. The majority of patients were college students. Students with RR-TB were mainly new patients. What are the implications for public health practice? The following measures are recommended: strengthening TB surveillance in schools, promoting the application of convenient and rapid molecular drug susceptibility testing tools, and actively carrying out drug resistance screening and follow ups for cohabiting children of adult RR-TB patients.

Characteristics of rifampicin-resistant tuberculosis detection in China, 2015-2019.

BACKGROUND: The very high burden of rifampicin resistance tuberculosis (RR-TB) and the very low detection of RR-TB cases are a major challenge that China has been facing. This study analyzed the characteristics of RR-TB detection in China after the change of RR-TB detection strategy since 2015, aiming to provide reference and evidence for the development of more precise national drug resistance tuberculosis prevention and control policy. METHODS: We extracted data related to rifampicin resistance screening from the national Tuberculosis Information Management System (TBIMS) from 2015 to 2019, and used descriptive research methods to analyze the screening rate of presumptive RR-TB, the number and duration of RR-TB patients detected and drug resistance testing methods in each year. Chi-square test was used to compare the differences in component ratio or rate between years, and Kruskal Wallis test was used to compare the differences in median days for detection of RR-TB patients in each year. RESULTS: A total of 68,200 RR-TB cases were detected during 2015-2019, of which 48.1% were new cases. The number and detection rate of RR-TB cases increased year by year, from 10 019 and 14.3% in 2015 to 18 623 and 28.7% in 2019, respectively. Of the bacteriologically confirmed TB cases, 81.9% were tested for RR in 2019, a considerable increase from 29.5% in 2015. In 2019, only 41.0% of RR-TB cases had fluoroquinolones (FQs) susceptibility testing performed, and this proportion has been declining year by year since 2016. The proportion of application of rapid molecular tools increased from 24.0% in 2015 to 67.1% in 2019, and the median days to obtain RR results was significantly shortened. In 2019, 76.0% of RR-TB cases were diagnosed as presumptive RR-TB in county-level hospitals. CONCLUSIONS: After China modified the RR-TB detection strategy, the screening rate of RR and the number of RR-TB cases increased significantly. The RR testing methods now predominantly utilize rapid molecular tools. However, comprehensive measures should be implemented to close the gap in the detection of RR-TB cases. It is imperative to take FQs susceptibility testing seriously and effectively strengthen the laboratory capacity of county-level hospitals.

Novel overlapping subgraph clustering for the detection of antigen epitopes.

Motivation: Antigens that contain overlapping epitopes have been occasionally reported. As current algorithms mainly take a one-antigen-one-epitope approach to the prediction of epitopes, they are not capable of detecting these multiple and overlapping epitopes accurately, or even those multiple and separated epitopes existing in some other antigens. Results: We introduce a novel subgraph clustering algorithm for more accurate detection of epitopes. This algorithm takes graph partitions as seeds, and expands the seeds to merge overlapping subgraphs based on the term frequency-inverse document frequency (TF-IDF) featured similarity. Then, the merged subgraphs are each classified as an epitope or non-epitope. Tests of our algorithm were conducted on three newly collected datasets of antigens. In the first dataset, each antigen contains only a single epitope; in the second, each antigen contains only multiple and separated epitopes; and in the third, each antigen contains overlapping epitopes. The prediction performance of our algorithm is significantly better than the state-of-art methods. The lifts of the averaged f-scores on top of the best existing methods are 60, 75 and 22% for the single epitope detection, the multiple and separated epitopes detection, and the overlapping epitopes detection, respectively. Availability and implementation: The source code is available at github.com/lzhlab/glep/. Supplementary information: Supplementary data are available at Bioinformatics online.