Abnormal long noncoding RNA (lncRNA) expression plays an important role in tumor invasion and metastasis. Here, we show that lncRNA LY6E divergent transcript (LY6E-DT) levels are increased in breast cancer (BC) tissues. Transcription factor SP3 binds directly to the LY6E-DT promoter, activating its transcription. Moreover, LY6E-DT N6-methyladenosine modification by methyltransferase-like protein 14 (METTL14) promotes its expression, dependent on the “reader” insulin-like growth factor 2 mRNA binding protein 1(IGF2BP1)-dependent pathway. Notably, we discovered that the lncRNA LY6E-DT encodes a conserved 153-aa protein, “Metastatic-Related Protein” (MRP). Both LY6E-DT and MRP promote BC invasion and metastasis, and MRP expression could distinguish BC patients with lymph node metastasis from those without. Mechanistically, MRP binds heterogeneous nuclear ribonucleoproteins C1/C2 (HNRNPC), enhancing the interaction between HNRNPC and epidermal growth factor receptor (EGFR) mRNA, increasing EGFR mRNA stability and protein expression and subsequently activating the phosphatidylinositol 3‑kinase/protein kinase B signaling (PI3K) pathway. LncRNA LY6E-DT promotes the interaction between Y box binding protein 1 (YBX1) and importin α1 and increases YBX1 protein entry into the nucleus, where it transcriptionally activates zinc finger E-box-binding homeobox 1(ZEB1). Our findings uncover a novel regulatory mechanism underlying BC invasion orchestrated by LY6E-DT and its encoded MRP.

Potential evapotranspiration (PET) is a crucial variable for implementing adaptation measures to mitigate the potential impacts of climate change on water resources. In the context of global warming, PET is essential for predicting water resource supply and demand, guiding irrigation and water management decisions. However, there is limited understanding of the spatiotemporal changes in PET and its driving factors in the hyper-arid regions of Northwest China. In this study, the Hargreaves model was employed to estimate PET in the Hami region from 1991 to 2020. By combining relevant climate data and partial correlation analysis, we investigated the spatiotemporal distribution patterns of PET within the study area and analyzed the factors influencing these patterns. The results showed the following: (1) From 1991 to 2020, the overall PET in the Hami region demonstrated a tendency to rise. The interannual trend rates of PET for the full year, spring, summer, autumn, and winter were 0.933, 2.744, 0.906, 0.488, and −0.406 mm·a-1, respectively. Despite a decreasing trend in winter PET, the other seasonal PET values and the annual PET values exhibited an increasing trend. (2) The spatial distribution of both annual and seasonal PET showed significant regional heterogeneity, following a consistent pattern marked by lower values in the central part and higher values in the surrounding areas. The southern region tended to have relatively high PET, while the northwestern region experienced comparatively low PET. (3) Partial correlation analysis indicated significant differences in the impact of various climatic factors on PET. The maximum temperature emerged as the dominant factor influencing annual PET variation, while precipitation played a leading role in influencing autumn PET variation. This study underscores the influence of climate change on PET in the Hami region, contributing to an enhanced comprehension of PET variations.

Water resources are a key constraint on sustainable development in arid regions, especially for agricultural production where water use is intensive. To assess the sustainability of agricultural water use in such environments, this study utilizes 2010–2020 agricultural data from the Turpan–Hami Basin and is among the first to integrate the water footprint (WF) theory with the DPSIR (driver–pressure–state–impact–response) model into a comprehensive framework for evaluating water resource sustainability in arid agricultural systems. The agricultural blue, green, and grey WF in the Turpan–Hami Basin were quantified for 2010–2020, followed by a sustainability assessment under the DPSIR framework using a comprehensive weighting method. The results showed a continuous increase in the WF, dominated by the blue WF (>60%), largely due to crops like cotton and grapes, intensifying regional water stress. Turpan experienced prolonged resource overload, while Hami exhibited slightly higher sustainability. DPSIR analysis revealed stronger policy responses in Turpan and significant ecological investments in Hami. Key influencing factors included the crop yield, WF modulus, per capita WF, and water quality shortage index. Overall, sustainability in the basin fluctuated between “Basically Sustainable (Level III)” and “Insufficiently Sustainable (Level IV)”, with slight improvement in 2020. The findings highlight the need for region-specific agricultural optimization, strengthened ecological governance, and improved water-saving strategies to enhance water use efficiency and sustainability in arid regions.

With the intensification of global climate change and human activities, coniferous species as the main components of natural forests in the Altay Mountains are facing the challenges of aging and regeneration. This study systematically analyzed structural heterogeneity and regeneration of three coniferous stand groups, Larix sibirica Ledeb. stand group, Abies sibirica Ledeb.-Picea obovata Ledeb.-Larix sibirica mixed stand group, and Picea obovata stand group, respectively, across western, central, and eastern forest areas of the Altay Mountains in Northwest China based on field surveys in 2023. Methodologically, we integrated Kruskal–Wallis/Dunn’s post hoc tests, nonlinear power-law modeling (diameter at breast height (DBH)–age relationships, validated via R², root mean square error (RMSE), and F-tests), static life tables (age class mortality and survival curves), and dynamic indices. Key findings revealed structural divergence: the L. sibirica stand group exhibited dominance of large-diameter trees (>30 cm DBH) with sparse seedlings/saplings and limited regeneration; the mixed stand group was dominated by small DBH individuals (<10 cm), showing young age structures and vigorous regeneration; while the P. obovata stand group displayed uniform DBH/height distributions and slow regeneration capacity. Radial growth rates differed significantly—highest in the mixed stand group (average of 0.315 cm/a), intermediate in the P. obovata stand group (0.216 cm/a), and lowest in the L. sibirica stand group (0.180 cm/a). Age–density trends varied among stand groups: unimodal in the L. sibirica and P. obovata stand groups while declining in the mixed stand group. All stand groups followed a Deevey-II survival curve (constant mortality across ages). The mixed stand group showed the highest growth potential but maximum disturbance risk, the L. sibirica stand group exhibited complex variation with lowest risk probability, while the P. obovata stand group had weaker adaptive capacity. These results underscore the need for differentiated management: promoting L. sibirica regeneration via gap-based interventions, enhancing disturbance resistance in the mixed stand group through structural diversification, and prioritizing P. obovata conservation to maintain ecosystem stability. This multi-method framework bridges stand-scale heterogeneity with demographic mechanisms, offering actionable insights for climate-resilient forestry.

The response mechanisms of vegetation dynamics to climate change in arid regions, particularly under extreme low-altitude and high-temperature environments, remain unclear. Focusing on China’s lowest and hottest Turpan-Hami Basin, this study investigates the spatiotemporal evolution of vegetation cover (using MODIS NDVI) and its response to temperature, precipitation, and potential evapotranspiration (PET) based on data from 2001 to 2020. Theil–Sen trend analysis, the Mann–Kendall test, and Pearson correlation were employed. Key findings include the following: (1) NDVI exhibited a significant increasing trend, with the largest rise in winter and peak values in summer. Spatially, high NDVI was concentrated in oasis and mountainous forest-grassland zones, while low values prevailed in desert Gobi regions; 34.2% of the area showed significant improvement, though localized degradation occurred. (2) Temperature showed no significant overall correlation with NDVI, except for strong positive correlations in limited high-altitude cold zones (2.9%). Precipitation had minimal influence (no correlation in 75.4% of the area), with localized positive responses in northwestern foothills linked to runoff. PET exhibited positive correlations (weak or strong) with NDVI across nearly half of the region (46.8%), predominantly in oasis-desert and piedmont transition zones. (3) Human activities, notably irrigation and shelterbelt projects, are key drivers of oasis vegetation restoration. Critically, the positive PET-NDVI correlation challenges the conventional paradigm viewing evapotranspiration solely as water stress. This study elucidates the compound responses of vegetation dynamics to climatic and anthropogenic factors in a low-altitude arid region, providing a scientific basis for ecological restoration and water resource management optimization.

Findings reveal that the majority of studied areas are classified as bare lands, while the lowest amount is covered by lichens and mosses. Grassland and cropland occupy major areas of the region, with highest normalized difference vegetation index (NDVI) value saw in 2020, showing dense vegetation in the western, northwestern and northern regions. Afforestation efforts shown positive results, with a 4% increase in forested area between 2000 and 2022.