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Small nucleolar RNA host gene 15 (SNHG15) is a long noncoding RNA (lncRNA), which promotes progression of multiple cancers. Its specific function in hepatocellular carcinoma (HCC), however, is uncertain. The aims of our study were, therefore, to explore the role of SNHG15 in HCC. SNHG15 and miR-141-3p expression were assessed via quantitative real-time PCR (qRT-PCR) in 58 paired HCC samples and adjacent matched adjacent normal tissues. CCK-8 assay, flow cytometric examination, and wound healing/invasion assays were used to respectively assess how SNHG15 influences cell proliferation, the cell cycle, and the migratory and invasive potential of HCC cells. MicroRNA (miRNAs) that targeted SNHG15 was screened by Starbase2.0 and identified by RNA immunoprecipitation and luciferase reporter assays. SNHG15 expression was markedly increased, whereas miR-141-3p expression was substantially reduced in HCC cells and tissue samples relative to normal controls. When SNHG15 was knocked down, this resulted in a significant disruption to the proliferation, as well as the invasive and migratory ability of these HCC cells. miR-141-3p was also found to be an SNHG15 target in HCC cells. Furthermore, miR-141-3p inhibitor partially reversed the observed SNHG15 depletion-mediated reduction in HCC proliferation, migration, and invasion. By repressing miR-141-3p, SNHG15 could modulate zinc finger E-box binding homeobox 2 (ZEB2) and E2F transcription factor 3 (E2F3) expression, both of which are miR-141-3p targets. These finding suggested that SNHG15 promoted HCC progression via negative regulation of miR-141-3p, thus identifying a potential novel HCC treatment pathway.

Ongoing global climate change greatly alters the distribution of species, and such impacts are even amplified on the Tibetan Plateau. The black-necked crane (Grus nigricollis) is perceived as an environmental indicator and flagship species in the alpine wetland ecosystems. However, scientifically, sound knowledge about global change impact on its breeding habitats is still lacking. Therefore, based on the best available species data further linked with powerful machine learning methods (ensemble random forest model), we predicted the breeding distribution of the black-necked crane under 2070 climate scenarios and provided associated conservation solutions. Our models for 2070 showed that its breeding range would expand in the hinterland of the Tibetan Plateau, with the current breeding habitats slightly shrinking from exterior margins, and in 2070, the overall habitat suitability would be jeopardized by the dwindling high-suitability habitats. Furthermore, conservation prioritization analyses indicated that global change would impact future-focused conservation and management, whereas the conservation effectiveness of the existing reserve networks would be instead improved with aggravating climate change and that the missing high conservation value areas are also spatially consistent on the Tibetan Plateau. Consequently, one elaborately designed reserve network could be feasible to secure this unique alpine crane lineage as well as the overwhelming majority of water birds on the Tibetan Plateau, despite the serious climate change impacts in the next realizable 50 years.

Natural chalcopyrite (NCP) was used as a low-cost and efficient activator of peroxymonosulfate (PMS) to repair groundwater polluted by aged landfill leachate. The optimal remediation effect of polluted groundwater was achieved at pH 8, PMS concentration 25 mM and NCP dosage 10 g/L via response surface method. The excellent performance of NCP was mainly Fe3+/Fe2+ and Cu2+/Cu+ cycles promoted by sulfur species, which was investigated via XPS analysis. Furthermore, the transformation of SO4•─, •OH and O2•─ were clarified by quenching experiments and ESR. The conversion of organics was revealed by UV–vis spectra and three-dimensional fluorescence spectra. Moreover, the toxicity of polluted groundwater after remediation was significantly reduced through the growth of Chlorella pyrenoidosa. Finally, the flowing experiment using NCP/sand column showed that NCP could effectively activate PMS and thereby restore polluted groundwater.

The introduction of long non-coding RNAs (lncRNAs) has revolutionized the treatment of hepatocellular carcinoma (HCC). Thus, in the present study, we aimed to evaluate the effect of a newly found lncRNA, LINC00160, on autophagy and drug resistance of HCC. Interaction among LINC00160, miR-132 and PIK3R3 was verified by dual luciferase reporter gene assay. Loss- and gain-of function experiments were conducted in HCC cells to explore the roles of LINC00160, miR-132 and PIK3R3 in HCC by determining cell viability, autophagy and apoptosis. Finally, tumorigenicity in nude mice was established to confirm the in vitro findings. LINC00160 and PIK3R3 were up-regulated but miR-132 was down-regulated in HCC tissues and cells. LINC00160 may regulate miR-132 and PIK3R3 was the target gene of miR-132. LINC00160 increased the expression of LC3I/LC3II and Atg5 but decreased the p62 expression, while silencing of LINC00160 or over-expression of miR-132 suppressed HCC cell viability, autophagy, drug-resistance and tumorigenicity in nude mice but promoted HCC cell apoptosis by inhibiting the PIK3R3 expression. Taken together, silencing of LINC00160 suppresses autophagy and drug resistance in HCC by regulating miR-132-targeted PIK3R3.

The black-necked crane (Grus nigricollis) is the only alpine crane species and is endemic to the Tibetan Plateau. The breeding habitats of this species are poorly understood, which greatly hampers practical research and conservation work. Using machine learning methods and the best-available data from our 7,000-kilometer mega-transect survey and open access data, we built the first species distribution model (SDM) to analyze the black-necked crane’s breeding habitats. Our model showed that current conservation gaps account for 26.7% of its predicted breeding habitats. Specifically, the northern parts of the Hengduan Mountains and the southeastern Tibet Valley, the northern side of the middle Kunlun Mountains, parts of the Pamir Plateau, the northern Pakistan Highlands and the western Hindu Kush should be considered as its main potential breeding areas. Additionally, our model suggested that the crane prefers to breed in alpine meadows at an elevation over 2,800 m, a maximum temperature of the warmest month below 20.5 °C, and a temperature seasonality above 7,800 units. The identified conservation gaps and potential breeding areas can aid in clearly prioritizing future conservation and research, but more attention and study should be directed to the unassessed Western Development of China to secure this endangered crane lineage and other wildlife on the Tibetan Plateau.

Species distribution models (SDMs) have become an essential tool in ecology, biogeography, evolution and, more recently, in conservation biology. How to generalize species distributions in large undersampled areas, especially with few samples, is a fundamental issue of SDMs. In order to explore this issue, we used the best available presence records for the Hooded Crane (Grus monacha,n = 33), White-naped Crane (Grus vipio,n = 40), and Black-necked Crane (Grus nigricollis,n = 75) in China as three case studies, employing four powerful and commonly used machine learning algorithms to map the breeding distributions of the three species: TreeNet (Stochastic Gradient Boosting, Boosted Regression Tree Model), Random Forest, CART (Classification and Regression Tree) and Maxent (Maximum Entropy Models). In addition, we developed an ensemble forecast by averaging predicted probability of the above four models results. Commonly used model performance metrics (Area under ROC (AUC) and true skill statistic (TSS)) were employed to evaluate model accuracy. The latest satellite tracking data and compiled literature data were used as two independent testing datasets to confront model predictions. We found Random Forest demonstrated the best performance for the most assessment method, provided a better model fit to the testing data, and achieved better species range maps for each crane species in undersampled areas. Random Forest has been generally available for more than 20 years and has been known to perform extremely well in ecological predictions. However, while increasingly on the rise, its potential is still widely underused in conservation, (spatial) ecological applications and for inference. Our results show that it informs ecological and biogeographical theories as well as being suitable for conservation applications, specifically when the study area is undersampled. This method helps to save model-selection time and effort, and allows robust and rapid assessments and decisions for efficient conservation.