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This study attempted to investigate relationship between rheumatoid arthritis and serum vitamin C levels using data from National Health and Nutrition Examination Survey (NHANES).The NHANES database aims to collect health, nutrition, biological, and behavioral data from a nationally representative sample of the population. This study utilizes NHANES data from three cycles: 2003–2004, 2005–2006, and 2017–2018, extracting data on the prevalence of rheumatoid arthritis and serum vitamin C levels. A generalized linear model is used to evaluate the association between the two.A total of 12,665 participants were included in the final analysis. Serum vitamin C levels were significantly higher in the non-rheumatoid arthritis group compared to the rheumatoid arthritis group (0.63 vs. 0.59, P = 0.042). Generalized linear model analysis showed that higher serum vitamin C levels were associated with a decreased risk of rheumatoid arthritis (OR = 0.62, 95 %CI: 0.40–0.98, P = 0.034). Stratified analysis revealed a significant interaction between non-hypertensive individuals and rheumatoid arthritis with serum vitamin C levels (P

Prostate adenocarcinoma (PCa) is the most common cause of death due to malignancy among men, and bone metastasis is the leading cause of mortality in patients with PCa. Therefore, identifying the causes and molecular mechanism of bone metastasis is important for early detection, diagnosis and personalized therapy. In this study, we systematically analyzed molecular correlates of bone metastasis by bioinformatics analysis. A total of 12 differentially expressed microRNAs (miRNAs) and 102 differentially expressed genes were identified. Five miRNAs had prognostic significance in biochemical recurrence‐free survival (miR‐636, miR‐491‐5p, miR‐199b‐5p, miR‐199b‐3p, miR‐28‐3p). The differentially expressed genes were significantly enriched in extracellular matrix, cell‐substrate adhesion, collagen and integrin. Seven hub genes (VCAN, COL3A1, COL1A1, APOE, COL1A2, SDC1, THY1) with worse biochemical recurrence‐free survival and one hub gene (MMP9) with worse overall survival were detected. miR‐636, a novel oncogene, was found to be up‐regulated in bone metastatic PCa tissues and also predominately up‐regulated in human PCa cell lines. miR‐636 promoted cellular invasion and migration, and may promote bone metastasis via targeting MBNL2, TNS1 and STAB1. In conclusion, we have successfully defined molecular signatures of bone metastasis in PCa.

Study region: National Sustainable Development Agenda Innovation Demonstration Zone in Lincang City, Southwest China Study focus: Revealing the current water quality status in rivers and reservoirs and its drivers is crucial to achieving the United Nations Sustainable Development Goal 6 (SDG 6). We assessed the spatial-temporal dynamics and influence of natural and socioeconomic factors on the water quality index (WQI) and water quality parameters of rivers and reservoirs using redundancy analysis (RDA) and the partial least squares path model (PLSPM). New hydrological insights for the region: The results indicate the following. (1) The annual average values of the WQI in Lincang City from 2018 to 2020 were 92.26, 92.06, and 92.45, respectively. The WQI values in spring, summer, autumn, and winter were 92.48, 90.38, 92.68, and 93.49, respectively. The annual and seasonal water quality levels were good or higher. However, spatial heterogeneity exists for some water quality parameters in Lincang City. (2) The influence of natural and socioeconomic factors on the WQI and water quality parameters is highly complex. The landscape composition, landscape configuration, and pollutant discharges are key factors affecting the water quality of rivers and reservoirs annually and seasonally, and a spatial scale dependence is observed. (3) Chemical and physical factors directly affect the WQI, particularly at small scales (100 m and 500 m buffer zones). Chemical factors have a strong inhibitory effect on the WQI of reservoirs (−0.79, −0.78) and rivers (−0.56, −0.72), whereas physical factors have a weak promoting effect (0.05–0.13). Landscape composition and landscape configuration and indirectly affect the WQI. In contrast, socioeconomic factors and pollution discharge indirectly impact the WQI of rivers and reservoirs through their influence on chemical and physical factors. These findings demonstrate that natural and social factors interact in multiple ways, impacting the water quality of rivers and reservoirs. This interaction depends on the spatial scale. Therefore, it is crucial to consider the appropriate distance from rivers and reservoirs in future land use planning, particularly in the landscape design and planning in Lincang City. Moreover, controlling wastewater discharge from industrial and agricultural activities and domestic water usage is vital for ensuring high water quality.

Under the background of global climate change, characterizing correlations between vegetation dynamics and bioclimatic indices (calculations based on temperature, precipitation, and reference evapotranspiration) are important for vegetation conservation and the restoration of fragile ecosystems. The Southwest China (SWC), which is a hotspot of global biodiversity with complex and diverse terrain, stereoscopic climatic characteristics, and pronounced spatial heterogeneity. Here, spatial–temporal changes in bioclimatic factors and annual normalized difference vegetation index (NDVI) and the effects of bioclimatic factors on the NDVI of different vegetation types at different elevations in SWC were examined during 1961(1982)–2019. Temperature-related bioclimatic indices had significant positive and negative effects on the NDVI of different types of vegetation, and the effects of temperature-related bioclimatic indices were stronger than those of precipitation and reference evapotranspiration-related indices in the three subregions. The effects of changes in temperature and reference evapotranspiration-related bioclimatic indices on the NDVI of different types of vegetation were significant in different elevation bins in the three subregions. The rate of change in high-value and low-value NDVI pixels of different types of vegetation significantly increased and decreased over the study period in the three subregions, respectively. The NDVI of grass vegetation significantly increased in the three subregions with elevation, and it was highest in the higher elevation bins. The interaction effects of several bioclimatic factors on the NDVI of different vegetation types varied, and the responses of the same vegetation type to interactions between different bioclimatic factors also varied. These findings provide new insights into the complex mechanisms underlying the relationships between bioclimatic indices and vegetation dynamics and have implications for the conservation of vegetation and the restoration of fragile ecosystems.

Southwest China (SWC) is a critical hotspot of biodiversity and highly sensitive to climate change. To better protect biodiversity, many National Nature Reserves have been established to maintain viable populations of species and minimize their habitat loss. However, the response of the normalized difference vegetation index (NDVI) in National Nature Reserves to extreme climate events has not been described. We analyzed NDVI changes and made several key observations: (1) from 1998 to 2019, annual average NDVI trends of 0.00421 yr−1, 0.00514 yr−1, and 0.00529 yr−1 were significantly increasing and NDVI values more than 0.8 were mainly concentrated at 1049–2349 m, 947–2547 m, 617–2817 m, in the National Nature Reserves of Hengduan Mountain (NNRHDM), Sichuan basin (NNRSCB), and Yunnan-Guizhou Plateau (NNRYGP), respectively. The change trends in different altitude bins were more significant in the NNRYGP; (2) extreme cold (warm) indices significantly decreased (increased) in the NNRHDM, NNRSCB and NNRYGP, extreme precipitation indices increased in the NNRHDM, and decreased in the NNRSCB and NNRYGP; (3) the combination of extreme temperature indices can better explain NDVI change in the NNRSCB and NNRYGP, and the combination of extreme temperature and precipitation indices can better explain the NDVI change in the NNRHDM on the monthly scale. Overall, the NDVI green trend is more obvious in the NNRYGP than in the NNRHDM and NNRSCB, and is more sensitive to extreme climate change, especially extreme temperature. Our findings showed that although the National Nature Reserves have achieved remarkable results in conservation, future work should focus on the development of adaptation and alleviation strategies to prevent extreme climate events (especially extreme temperature events) that could promote vegetation degradation in these sensitive areas.

Background: Circular RNAs (circRNAs) are key modulators in carcinogenesis and radioresistance in multiple kinds of human cancers. Aims: To explore the role of circ_0010235 in non-small cell lung cancer (NSCLC). Study Design: Cell culture study and animal study. Methods: The detection of circ_0010235, microRNA-588 (miR-588), and homeobox protein A10 (HOXA10) was implemented via reverse transcription-quantitative polymerase chain reaction (RT-qPCR). CCK-8, EdU, flow cytometry, transwell, and wound healing assays. These strategies were applied to evaluate cell functions. The western blot technique was employed for protein examination. The colony formation assay was used to determine cell survival after radiation treatment. In vivo research was performed by tumor xenograft assay. The binding analysis was also carried out through dual-luciferase reporter and RNA immunoprecipitation studies. Results: Circ_0010235 had an enhanced expression in NSCLC. Circ_0010235 deficiency inhibited cell proliferation, invasiveness, and migratory ability but promoted apoptosis and radiosensitivity. Downregulation of circ_0010235 decelerated tumor growth and promoted radiation sensitivity in vivo. Circ_0010235 was controlled biologically in NSCLC cells by combining with miR-588 and targeting miR-588. HOXA10 acted as a target of miR-588. MiR-588 upregulation inhibited NSCLC cell malignant phenotypes and elevated radiosensitivity via downregulating HOXA10. Circ_0010235 could regulate the level of HOXA10 by sponging miR-588. Conclusion: Circ_0010235 contributed to the malignant progression of NSCLC, but suppressed the radiation sensitivity via targeting miR-588 to induce HOXA10 upregulation.

Soil temperature change has considerable impact on land surface energy and water balances, and hence on changes in weather/climate, surface/subsurface hydrology, and ecosystems. However, little is known regarding the spatiotemporal variations and influencing factors of changes in hourly soil temperature (depth: 5–320 cm) in low-latitude highland areas. This study analyzed the hourly soil temperature at each hour during 2004–2020 and at 08:00, 14:00, and 20:00 (Beijing Time) during 1961–2020. The results revealed the following. 1) As soil depth increased, average soil temperature increased in autumn and winter, and decreased annually and in spring and summer. It exhibited significant increase during 00:00–23:00 annually, seasonally, and monthly, especially at depths of 40–320 cm during 2004–2020. Average soil temperature increased at 08:00 and decreased at 14:00 and 20:00 with increasing soil depth, but the opposite trend was found annually, seasonally, and monthly at 08:00, 14:00, and 20:00 during 1961–2020. 2) With increasing elevation, average soil temperature decreased at 08:00, 14:00, and 20:00 at depths of 5–20 cm, and showed significant increase trend at 08:00 and 14:00 at depths of 10–20 cm (except at 14:00 at 10-cm depth). 3) At 5-cm depth, the critical accumulated soil temperature of ≥12°C and 14°C extended the potential growing season during 1961–2020. 5) Significant uptrend of hourly soil temperature annually, seasonally, and monthly potentially leads to additional release of carbon to the atmosphere and increased soil respiration, reinforcing climate warming. These findings contribute to better understanding of the variation of shallow soil temperatures and land–atmosphere interactions in low-latitude highland areas.

Gauge-measured precipitation data have long been recognized to underestimate actual precipitation due to wind-induced error, trace precipitation, and wetting loss, which affects the spatial and temporal characteristics of precipitation. In this study, we examined spatial and temporal differences in wet and dry spell indices based on original (Po) and corrected (Pc) precipitation data and their correlations with large-scale circulation indices (LSCIs) in Southwest China during 1961–2019. The main conclusions were: (1) Pc-based trends in wet/dry spell indices were generally more pronounced than Po-based. Specifically, when Pc-based, more stations had significant changes in the MWS, MLWS, MPWS, PWS95, FWW, FDW, MDS, MLDS, NLDS, and DDS95 indices, while fewer had significant changes in the NWS, NDS, FDD, and FWD indices. (2) Spearman’s results showed that more LSCIs were significantly related to the Pc-based wet/dry spell indices than Po-based. Po-based and Pc-based MWS, Po-based MDS, and Pc-based NLDS were significantly related to the most LSCIs. Therefore, taking them as examples, wavelet transform coherence (WTC) and partial wavelet coherence (PWC) were used to explore the coherence with LSCIs. WTC results showed South Asian Summer Monsoon Index (SASMI) + Po-based MWS, Arctic Oscillation (AO) + Po-based MDS, SASMI + Pc-based MWS, Asia Polar Vortex Intensity Index (APVI) + Pc-based NLDS exhibited the most obvious periodic resonance with main resonance periods of 2.13~7.8 year, 2.19~10.41 year, 2.13~12.13 year, 2.75~18.56 year, respectively. Since WTC may arbitrarily ignore the interaction between LSCIs, PWC is adopted for further analysis. PWC results showed the coherence of AO +Po-based MDS significantly increased after eliminating the Nino Eastern Pacific index (NEP) influence, with the main resonance period of 6.56~18.56 year. This study clearly demonstrated that corrected precipitation data should be used to improve the accuracy of drought assessments, climate models, eco-hydrological models, etc.

Air/soil temperatures play important roles in land–atmosphere interactions. The three-dimensional (temporal, spatial, and vertical) variations of maximum, mean, and minimum ground soil temperature at 0 cm (GSTx, GSTm, and GSTn, respectively), surface air temperature at 2 m (SATx, SATm, and SATn, respectively), and soil–air temperature difference (SATDx, SATDm, and SATDn, respectively) and their potential linkages with large-scale indexes in Southwest China during 1980–2019 were analyzed. Variations of GST and SAT at the majority of stations (pixels) exhibited significant (p ≤ 0.05) warming, albeit at different rates; consequently, SATD exhibited different variation. Moreover, the period of GST, SAT, and SATD was similar in intra-annual and interannual oscillation but was different in interdecadal oscillation. The variation rate of GST, SAT, and SATD exhibited significant (p ≤ 0.05) correlation with elevation, but with different variation gradient. Notably, asymmetric variation of SATDx (downward trend) and of SATDn (upward trend) with elevation was found at elevations >3 km. Wavelet coherence showed that the Atlantic Multidecadal Oscillation is the dominant factor affecting GST and SAT, whereas the Pacific Decadal Oscillation and the North Atlantic Oscillation make the greatest contributions to SATD. It was found that GST, SAT, and SATD exhibit different variations under the effects of global warming, the driving mechanism of which requires further study.

Fewer studies on ecological security (ES) in border areas limit the synergistic development of border areas in the context of rapid globalization. The study of ES in border areas of southwest China can enrich the evaluation methods, summarize the knowledge related to ES in border areas, and provide references for similar areas in the world. Therefore, twenty-five international border counties in Yunnan Province were selected to establish a system to evaluate ES; an entropy weight TOPSIS model was used to evaluate the changes in ES from 2004 to 2019. Then, an obstacle degree model was used to diagnose the factors affecting ES. The state of ES was predicted by a gray prediction model (GM) (1,1) in 2025 and 2030. The results show that an improving ES situation presented a spatial distribution pattern of high to low from the southwest to the west and east. Various factors, including fixed assets investment, per-capita fiscal revenue, per-capita GDP, food production, and water regulation, created obstacles to a desirable ES in the study area. Although the ES of border areas will maintain an upward trend under the existing development model, the number of counties that will reach a secure state of ES in 2025 and 2030 is predicted to only be 1 and 2, respectively.

The high-quality development in the Yunnan–Guizhou region (YGR) is a significant support for the high-quality development of China. It will help shape a new pattern of regional coordinated development. Referring to a Beautiful China and the United Nations Sustainable Development Goals (SDGs) evaluation indexes, we built an evaluation index system that puts the high-quality development at its heart. This system includes the resource load, economic development, ecological environment protection, and social progress. Taking 25 prefecture-level cities of the YGR as study subjects, the authors used the entropy weight–TOPSIS model to evaluate high-quality development and evolution. Then, the authors used the Geographical Detector (GD) method and a Geographic-Weighted Regression (GWR) model to analyze factors and mechanisms of the evolution of high-quality development. The results suggest that the changes of urban built-up area, per capita GDP, total foreign trade value, tourism revenue, and total investment of fixed assets investment are the primary factors of spatial differentiation of this evolution. The influence and direction of each factor are different in different periods, with apparent spatio-temporal heterogeneity. From 2005 to 2018, the synergistic effect of changes in total foreign trade value and tourism revenue is the leading force in shaping the evolution pattern. The high-quality development of the YGR generally presents the spatial pattern of “central Yunnan–central Guizhou core dual drive”, “high in east and low in west”, and the evolution speed presents a development characteristic of “low speed–relatively high speed–high speed”. The research can provide a reference for high-quality and precise development and decision-making in the YGR.

Understanding the evolution and propagation of different drought types is crucial to reduce drought hazards in arid and semiarid regions. Here, Standardized Precipitation Index (SPI), Streamflow Drought Index (SDI), and Vegetation Condition Index (VCI) were used to investigate the spatiotemporal variation of different drought types and correlations between Pre (Pre-R)/post (Pos-R)-reservoir. Results showed that the average peak/intensity/duration/severity of meteorological droughts (MD) were greater in the Pre-R than in the Pos-R period in the upstream Heihe River Basin (UHRB), while there was little change between the Pre-R and Pos-R periods in the midstream Heihe River Basin (MHRB). The average peak/intensity/duration/severity of hydrological drought (HD) decreased in the mainstream for Yingluoxia (Ylx) but increased for Zhengyixia (Zyx) station in the Pos-R period. Propagation time decreased by 3 months (negative effect) in Ylx and increased by 8 months (positive effect) in Zyx compared with the Pre-R period. In the Pos-R period, propagation time increased (1–3 months) for tributaries (positive effect). Propagation times for the mainstream and tributaries varied for different seasons and time periods. Pearson’s correlation coefficient values were lower at short timescales (1–3 months) but higher at long timescales for the Pos-R period in Ylx and Zyx for SDI-1 with different timescales of SPI. The SDI and SPI had no lag in the UHRB and MHRB. However, VCI with SPI had a significant lag correlation at short timescales in the UHRB (lag 6 months) and MHRB (lag 4 months), and the VCI with SDI had a significant lag correlation for 1 month in the MHRB. The propagation time from MD to HD has been reduced for Pos-R in the UHRB. There was a positive effect (prolonged MD propagation HD time) in Pos-R but still faces serious drought stress in the MHRB.

Debugging is an essential part of parallel and distributed processing. However, developing parallel and distributed debugger is difficult. This is especially true for cluster computing where heterogeneity presents. In this paper, we first give a survey of the current debugging techniques and existing tools, and then present a client–server debugging model. Based on this model, we discuss the design and development of a practical scalable distributed debugging system for cluster computing in detail, and give two case studies to show how the distributed debugging system efficiently supports debugging message-passing programs such as various MPI and PVM programs. The newly developed distributed debugger is based on the sequential debugger gdb and dbx. It has the capability of scaling to handle hundreds of processes. Its interfaces are completely implemented in Java, and its graphical user interface is the same on all computing platforms. In addition, it is portable, easy to learn and use. [ABSTRACT FROM AUTHOR]

Guizhou Province, China, experienced several severe drought events over the period from 1960 to 2013, causing great economic loss and intractable conflicts over water. In this study, the spatial and temporal characteristics of droughts are analyzed with the standard precipitation index (SPI), comprehensive meteorological drought index (CI), and reconnaissance drought index (RDI). Meanwhile, historical drought records are used to test the performance of each index at identifying droughts. All three indices show decreasing annual and autumn trends, with the latter particularly prominent. 29, 30, and 32 drought events were identified during 1960–2013 by the SPI, CI, and RDI, respectively. Continuous drought is more frequent in winter–spring and summer–autumn. There is a significant increasing trend in drought event frequency, peak, and strength since the start of the 21st century. Drought duration indicated by CI shows longer durations in the higher-elevation region of central and western Guizhou. The corresponding drought severity is high in these regions. SPI and RDI indicate longer drought durations in the lower elevation central and eastern regions of Guizhou Province, where the corresponding drought severity is also very strong. SPI shows an increasing trend in drought duration and drought severity across most of the regions of Guizhou. In general, SPI and RDI show an increasing trend in the western Guizhou Province and a decreasing trend in central and eastern Guizhou. Comparing these three drought indices with historical records, the RDI is found to be more objective and reliable than the SPI and CI when identifying the periods of drought in Guizhou.

Changes in precipitation are critical indicators of climate change. In this study, the daily precipitation records from 10 meteorological stations in the Heihe River Basin, Northwest China from 1961−2016, precipitation indices, climate indices, and the normalized differential vegetation index (NDVI) were investigated using the Pearson, Kendall, and Spearman correlation coefficients; Theil-Sen Median; Mann−Kendall test; and wavelet coherence. The results indicated that the occurrences (fractional contributions) of 1−2-day wet periods were 81.3% (93.9%) and 55.3% (82.1%) in the upper (UHRB) and middle (MHRB) reaches of the Heihe River Basin, respectively. The spatial distribution of the occurrences (fractional contributions) was almost consistent with non-significant increases/decreases at stations. The ATP, ATD, API, and AMRD increased, while precipitation regimes suggest that dry seasons are getting wetter, and wet seasons are getting drier, although these changes were not significant. Wavelet coherence analyses showed that climate indices influenced precipitation, mainly its concentration, on a 4- to 78.6-month timescale. The Pearson, Kendall, and Spearman correlation coefficients showed weak lagged linkages between precipitation and the North Arctic Oscillation (NAO), Pacific Decadal Oscillation (PDO), and Atlantic Multidecadal Oscillation (AMO). The NDVI of grasslands, meadows and coniferous forests was significantly and positively correlated with precipitation, while the NDVI of alpine vegetation, swamps and shrubs was negatively and significantly correlated with precipitation in the UHRB. The NDVI of grasslands was significantly and positively correlated, but the NDVI of shrubs, coniferous forests and cultivated vegetation was negatively and significantly correlated with precipitation in the MHRB. The correlation between cultivated vegetation and natural precipitation in the MHRB may have been weakened by human activities.