Search

Although there have been many recent taxonomic revisions and large-scale faunistic surveys focusing on spiders from Jiangxi Province, many taxa still remain unknown, such as the Anyphaenidae spiders. Therefore, none of the anyphaenid species has been recorded from this Province.Anyphaenidae spiders were collected from Jinggangshan National Nature Reserve, Jiangxi Province, China, during the past ten years. A new tube spider species, Anyphaena leidashi Yao & Liu, sp. nov. is diagnosed, described and illustrated. Moreover, three species including A. mogan Song & Chen, 1987, A. wuyi Zhang, Zhu & Song, 2005 and Rathalos xiushanensis (Song & Zhu, 1991) are recorded from Jiangxi Province for the first time. Distributions records are given for all investigated species.

Salinization is a severe threat to agriculture and the environment in many areas, and the same in Qaidam Basin, Qinghai Province, Northwestern China. Microorganisms have an important influence on regulating the biochemical cycles of ecosystems; however, systematic research exploring microbial diversity and interactions with saline-soil ecosystems’ environmental variables remains scarce. Thus, 16 S rRNA high-throughput sequencing was performed in this paper to characterize microbial diversity under different levels of salinized soils: non-salinized (NS, 2.25 g/L), moderately salinized (MS, 6.14 g/L) and highly salinized (HS, 9.82 g/L). The alpha diversity results showed that the HS soil was significantly different from the NS and MS soils. An analysis of similarity (ANOSIM) and a principal co-ordinates analysis (PCoA) indicated that NS and MS clustered closely while HS separated from the other two. Significant differences in microbial composition were observed at the taxonomic level. Proteobacteria (42.29–79.23 %) were the most abundant phyla in the studied soils. Gammaproteobacteria (52.49 and 66.61 %) had higher abundance in the MS and HS soils at the class level; Methylophaga and Pseudomonas were the predominant bacteria in the HS soil; and Azotobacter and Methylobacillus were abundant in the MS soil. Most genera belonging to Proteobacteria and Actinobacteria were detected via a linear discriminate analysis (LDA) effect size (LEfSe) analysis, which indicated that microbes with the ability to degrade organic matter and accomplish nutrient cycling can be well-adapted to salt conditions. Further analyses (redundancy analysis and Mantel test) showed that the microbial communities were mainly related to the soil salinity, electrical conductivity (EC1:5), total phosphorus (TP) and ammonia nitrogen (NH4+-N). Overall, the findings of the study can provide insights for better understanding the dominant indigenous microbes and their roles in biochemical cycles in different saline soils in the Qaidam Basin, Qinghai Province, China. The researches related to microbial community under typical poplar species should further clarify the mechanism of plant-microbial interaction and benefit for microbial utilization in salt soil remediation.

ObjectiveThis study explored the utility of NLR (neutrophil-to-lymphocyte ratio) as a marker to predict Lower Extremity Peripheral Artery Disease (PAD) in the Chinese population, as well as to assess its consistency and diagnostic value with digital subtraction angiography.MethodsPatients were distributed into three groups according to the angiography in lower limb arterial: group L1, plaque with no stenosis; group L2, plaque with luminal stenosis and group L3, total vascular occlusion. Changes in the neutrophil-to-lymphocyte ratio were documented and compared among groups.ResultsCompared to group L1, NLR was significantly increased in L2 (1.76 vs 2.35, p=0.037) and L3 (1.76 vs 3.60, p70%) increased to 2.075 times for every 1 increase in NLR, while it was 46.8% for every 0.1 increase in ABI. The optimal NLR cut-off value to predict severe stenosis in PAD was 2.73. Receiver operating characteristic curve analysis of the inflammatory biomarkers and severe stenosis prediction displayed an area under the curve of 0.81.ConclusionNLR could serve as a new noninvasive and accurate marker in predicting PAD.

Background: We assessed the response to sulfonylureas and the functional characteristics of HNF1A mutations in patients with maturity-onset diabetes of the young type 3 (MODY3). Methods: We recruited a family with suspected MODY in this study, and gene sequencing (whole-exome sequencing) was used to screen germline mutations. Luciferase reporter assays were used to evaluate the activity of the mutated genes. Results: Heterozygous HNF1A variant (NM_000545.8:c.1330_1331del, p.Gln444fs) was identified in the proband and was not found in his father, grandmother, and nonrelated healthy controls. The mutant protein had 552 amino acids, 110 fewer than the wild type protein. Furthermore, the amino acid sequence was completely different between the mutant protein and the wild type protein starting from the 444th amino acid. Luciferase reporter assays revealed that the variant had impaired HNF4A promoter–regulation activity. The patient did not achieve good hypoglycemic effects during long-term treatment with insulin and metformin. The effect of hypoglycemic treatment was highly significant after the addition of sulfonylurea drugs. Conclusions: The HNF1A p.Gln444fs variant associated with MODY3, and most likely a truncated protein, impaired HNF1A transcriptional activity. The variant carrier experienced an enhanced response to sulfonylureas.

Abstract Background Insulin resistance (IR) is one of the risk factors for chronic kidney disease (CKD) and diabetes. The triglyceride–glucose (TyG) index is considered a reliable alternative marker of IR. We investigated the correlation between the TyG index and the severity of CKD in patients with latent autoimmune diabetes in adults (LADA). Methods This cross-sectional study included 288 patients with LADA in the department of endocrinology at our hospital between January 2018 and January 2022. The TyG index was calculated as Ln [TG (mg/dl) × fasting blood glucose (FBG) (mg/dl) / 2]. All individuals were divided into either a LADA + CKD group or a LADA + non-CKD group according to the presence or absence of CKD. A correlation analysis, logistic regression analysis and receiver operating characteristics curve analysis were performed. Results A total of 130 (45.1%) participants were identified as having CKD. Compared with the non-CKD group, the CKD group had a longer disease duration and a higher proportion of smokers; patients were more likely to have hypertension and higher serum creatinine, triglyceride, cholesterol, low-density lipoprotein cholesterol, FBG, uric acid estimated glomerular filtration rates (eGFR) and TyG levels as well as lower high-density lipoprotein cholesterol levels (all P

Abstract Background Type 2 diabetes (T2D) is an independent risk factor for Alzheimer's disease (AD). Exendin-4 (Ex-4), a widely used glucagon-like peptide-1 receptor agonist drug in the treatment of T2D, has been demonstrated the therapeutic effects on diabetic encephalopathy (DE). Especially, the Ex-4 ameliorates the tau hyperphosphorylation and cognitive impairment in DE. And these crucial alterations are also important bridge between T2D and AD. However, its unique mechanism is unclear. Methods The db/db mice, high-fat-diet (HFD) / streptozotocin (STZ)—induced diabetic (HF-diabetic) mice, and high-glucose-damaged (HGD) HT-22 hippocampal cells were enrolled to examine the effects of Ex-4 on AD-like changes in T2D. The Novel object recognition test (NORT) and Morris water maze test (MWMT) were conducted to evaluate the cognitive impairment. The Dickkopf-1 (DKK1) was employed to weaken the activation of the Wnt/β-catenin pathway to explore the mechanism of Ex-4 in protecting the brain functions. The JASPAR was based to predict the interaction between NeuroD1 and the promoter region of Ins2. Moreover, the chromatin immunoprecipitation coupled with quantitative polymerase chain reaction (ChIP-qPCR) and luciferase reporter assays were performed. Results Ex-4 alleviated the tau hyperphosphorylation, increased the brain-derived insulin, and improved the PI3K/AKT/GSK3-β signalling in db/db mice, HF-diabetic mice, and HGD HT-22 hippocampal neuronal cells. The NORT and MWMT indicated that Ex-4 alleviated the learning and memory deficits in HF-diabetic mice. The inhibitor Dickkopf-1 (DKK1) of the Wnt/β-catenin pathway significantly blocked the protective effects of Ex-4. Regarding further molecular mechanisms, NeuroD1 was affected by Ex-4 in vivo and in vitro, and the knockdown or overexpression of NeuroD1 suggested its crucial role in promoting the brain insulin by Ex-4. Meanwhile, the ChIP‒qPCR and luciferase reporter assays confirmed the combination between NeuroD1 and the promoter region of the insulin-encoding gene Ins2. And this interaction could be promoted by Ex-4. Conclusions Our study proposes that Ex-4 alleviates tau hyperphosphorylation and cognitive dysfunction by increasing Ins2-derived brain insulin through the Wnt/β-catenin/NeuroD1 signaling in T2D. And its also show new lights on part of the progress and mechanism on treatment targets for the DE in T2D.

Abstract Aims The objective of this study is to explore the relationship between red blood cell distribution and islet β-cell function indexes in patients with Latent Autoimmune Diabetes in Adults. Methods A total of 487 LADA patients were enrolled in this cross-sectional study. Patients were divided into three groups according to RDW tertiles. Clinical and laboratory measurements of age, height, weight, duration of diabetes, blood pressure, RDW, glycosylated hemoglobin A1c (HbA1c), C-peptide and blood lipids were performed. Homeostasis model assessment of insulin resistance (HOMA-IR) and homeostasis model assessment of β-cell function (HOMA-β) were assessed using homeostasis model assessment (HOMA) based on fasting blood glucose (FBG) and fasting C-peptide index (FCP). Correlations and multiple linear regressions were implemented to determine the association of RDW and islet function indexes. Results As the increase of serum RDW level, the presence of β-cell secretion increased(P

Key Clinical Message Maternally inherited diabetes and deafness (MIDD) is often caused by the m.3243A > G mutation in mitochondrial DNA. Unfortunately, the characteristics of MIDD, especially long‐term outcomes and heteroplasmic changes, have not been well described previously. The purpose of this study was to describe the clinical and genetic features of a family with MIDD after 10 years of follow‐up.A 33‐year‐old male patient with typical characteristics of MIDD, including early‐onset diabetes, deafness, and low body mass index, was admitted to our department. Further investigation revealed that the vast majority of his maternal relatives suffered from diabetes with or without deafness. A detailed family history was then requested from the patient and a pedigree was constructed. The patient suspected of MIDD was screened for mutations using whole mitochondrial DNA sequencing. Candidate pathogenic variants were then validated in other family members through Sanger sequencing. The patient was diagnosed with MIDD, with inherited m.3243A > G mutation in the mitochondrially encoded tRNA leucine 1 (MT‐TL1) gene, after 10 years of symptom onset. The patient was then treated with insulin and coenzyme Q10 to improve mitochondrial function. During the follow‐up period, his fasting blood glucose and HbA1c levels were improved and the incidence of diabetic ketoacidosis was significantly reduced. Our findings indicate that whole mitochondrial DNA sequencing should be considered for patients suspected of MIDD to improve the efficiency of diagnosis and prognosis.

Dunes are among the most abundant aeolian landforms found on Earth and other planets. The automatic mapping of dunes over large-scale areas is crucial for predicting, monitoring, and managing lands threatened by sand encroachment. However, the spectral similarity between dune and inter-dune areas, as well as the diverse presentations of dunes of the same type, have made it challenging to automatically classify and map dunes. In this study, we propose a two-step 'detect-then-classify' framework that enables the automatic identification of heterogeneous dune types. The first step involves dune detection. We introduce a newly developed convolutional neural network called SandUnet, which is adapted from Attention U-Net. This network is designed to preserve uncompressed input signals ensuring that minor differences in the color and texture of the dunes are retained. The second step focuses on dune-type classification. To classify dunes, a fine-tuned MobileNet was constructed to integrate the wealth of knowledge ingrained in MobileNet's pre-trained layers with the adaptations tailored specifically for the sand dune images. Subsequently, each dune image is automatically classified into six different types using this framework. By applying this framework to all the bare sand areas of the Taklamakan (or Taklimakan) Desert using Landsat-8 imagery, the final classification of dune types of the desert was achieved. Testing on randomly selected 10% image patches of whole desert, the overall accuracy of the dune-type classification is 70%. This study presents an automatic and economical solution for identifying dunes in large-scale areas.

We adopted a spectral clustering algorithm to divide the document co-citation network of 1,776 papers in the field of Lancang-Mekong water, and 14 clusters were identified. For each cluster, the top-cited references construct the knowledge base, and the most-coverage cities are taken as the research frontier. Three indicators, namely betweenness centrality, citation burstness strength, and Sigma, were used to identify the research outputs with pioneering and transformative value. The changes in the research topics and hotspots are closely related to the planning, construction, and operation progress of hydropower engineering, that affected by the gaming results of all parties. The 2009–2010 is an important time boundary, with the original research hotspots including the impact of upstream reservoirs on the hydrological regime and sediment (Clu#3) and arsenic contamination of groundwater in the Lower Mekong (Clu#4) that obtained periodical achievements and reached consensus to some extent around 2008, and the new research boom turns to the Tonle Sap Lake and flood pulse (Clu#2) in short-term characterized literatures with the highest burstness strength mainly concentrated around 2012. HIGHLIGHTS The intellectual bases and research frontiers of 14 identified topics were analyzed based on Document Co-citation Network analysis.; Vietnamese Mekong Delta is the topic with the largest size and arsenic contamination is the cluster with the longest time span.; Evolution of research hotspots is related to the widespread controversy over the planned dams in the Lower Mekong mainstream and the progress of the multi-party games.;

Oasis vegetation contains a variety of ecological functions and can quickly indicate changes in the environment. According to the vegetation dynamics of natural oasis, this study constructed a natural oasis ecological vulnerability assessment model (NOEV) The model is based on Pressure-Sensitivity-Resilience framework, combined with redundancy analysis, minimum cumulative resistance model, and ecological risk sensitivity index to effectively assess the ecological vulnerability of natural oasis. The results showed that human activities, represented by the expansion of farmland and population growth, were the main factors affecting the vegetation dynamics of natural oasis in the last 30 years, and their contribution to the change of vegetation area is 42.08%. In the temporal dynamics, a serie of economic and environmental policies implemented by the government after the 21st century have promoted the recovery of vegetation. Vulnerability decreased on the whole oasis but increased in some local areas during 2005–2020. In the spatial dynamics, the transition zone of vulnerability from high to low occurred, it a distance of approximately 30 km from an artificial oasis located also in the area. We suggest that the governments should set up an ecological buffer zone in this area and implement different environmental protection policies inside and outside the buffer zone. Few vulnerability assessment models have been constructed for oasis ecosystems, and the NOEV model constructed in this study helps to formulate more direct and effective policy recommendations for the government's ecological protection and restoration work.

Atriplex canescens is widely cultivated as drought and salt-tolerant fodder in arid regions of Northwest China, which is used for photoremediation of degraded land and soil and water conservation. To explore the growth performance of A. canescens when exposed to drought and salt stress, seedlings were treated with a range of drought stress (WC1: 75 ± 3.6%, WC2: 49 ± 2.9% and WC3: 27 ± 2.5% of soil water content) and the corresponding drought stress with additional sodium salt supplementation (NaCl:Na2SO4 = 1:1 with the total concentration of Na+ set to 150 mM). The findings of this paper indicated that moderate sodium salt could stimulate the growth of A. canescens and effectively alleviate the deleterious impact of drought stress by increasing the turgor potential (ψt) and relative water content (RWC) and decreasing the leaf water osmotic potential (ψs). Furthermore, the photosynthetic capacity was improved and the negative effects of drought stress on photosystem II (PSII) were mitigated. The extra 150 mM sodium salt also markedly increased the contribution of Na+ to ψs and the contribution of betaine to ψs. In summary, these results indicate that A. canescens can adapt to drought stress by accumulating enough Na+ for osmotic adjustment (OA). Additionally, this paper is aimed to provide a fundamental basis for the utilization and cultivation of A. canescens as a favored pasture crop in the Qaidam basin, thus increasing the ecological and environmental benefits for arid regions worldwide.

Computing platforms providing cloud simulation services have raised new challenges on the model integration. Unlike calls to the model programs (components) in traditional simulation software, here the models should be dynamically integrated in the “plug and play” mode regardless of the differences in model type and developer. To this end two integration methods have been proposed, i.e., coarse-grained EXE integration and interactive integration. In an EXE integration method, the simulation program is directly called and thus only a data conversion interface is needed while rewriting of the model source code is not required. In contrast, an interactive integration method wraps the model components using the standard wrapper with communication interfaces, and therefore, it can communicate and exchange data with the platform in a real time. The first method is suitable for the integration of legacy models, while the second one can control the progress of simulation schemes and facilitate the scheduling of computing resources. Examples of the model integration and platform application have been presented in hydraulics/hydrodynamics to demonstrate the effectiveness of the integration method and the cloud computing platform.

Maintaining the integrity and stability of oasis ecosystems is an important topic in the field of ecological research. Assessment of ecosystem services and their changes can provide important support for the sustainable development of oases. This study took the Dunhuang oasis in the hyper-arid area as the research object and used 1990, 2010, and 2020 Landsat series satellite images to complete the land use interpretation by random forest classification. Then we estimated the ecosystem services value (ESV) by using benefit transfer method, and predicted the trend of ecosystem service value changes under three scenarios using the Analytic Hierarchy Process method and the patch generation land use simulation model (AHP-PLUS model). The results showed that the vegetation areas of the Dunhuang Oasis first decreased and then increased during 1990–2020. The decrease was largely due to the expansion of built-up land and farmland, and the increase was mainly contributed by the implementation of ecological protection policies. The path of changes in the ESV of the Dunhuang Oasis during 1990–2020 was well consistent with that of vegetation areas, with a maximum of 9068.15×106 yuan (in 1990) and a minimum of 6271.46×106 yuan (in 2010). Spatial autocorrelation analysis showed that urbanization reduced ESV, and the implementation of ecological policies enhanced ESV. The ESV of the Dunhuang Oasis for the year 2030 under the ecological conservation scenario could reach 7631.07×106 yuan, which is 381.1×106 yuan higher that under the economic development scenario. The ecological conservation scenario is the optimal option to achieve sustainable development of the Dunhuang Oasis. We suggested that the government should continuously enhance the protection of forests and waterbodies, reasonably restrict production and domestic water consumption, and efficiently increase the proportion of ecological water consumption. In addition, this study improved the evaluation method of oasis ESV based on the proportion of Normalized Difference Vegetation Index (NDVI) of grasslands with different coverage, which is important for improving the environment in arid areas.

Dew has been considered a supplementary water resource as it constitutes an important water supply in many ecosystems, especially in arid and semiarid areas. Remote sensing allows large-scale surface observations, offering the possibility to estimate dew in such arid and semiarid regions. In this study, by screening and combining different remote sensing variables, we obtained a well-performing monthly scale dew yield estimation model based on the support vector machine (SVM) learning method. Using daytime and nighttime land surface temperatures (LST), the normalized difference vegetation index (NDVI), and three emissivity bands (3.929–3.989 µm, 10.780–11.280 µm, and 11.770–12.270 µm) as the model inputs, the simulated site-scale monthly dew yield achieved a correlation coefficient (CC) of 0.89 and a root mean square error (RMSE) of 0.30 (mm) for the training set, and CC = 0.59 and RMSE = 0.55 (mm) for the test set. Applying the model to the Heihe River Basin (HRB), the results showed that the annual dew yield ranged from 8.83 to 20.28 mm/year, accounting for 2.12 to 66.88% of the total precipitation, with 74.81% of the area having an annual dew amount of 16 to 19 mm/year. We expanded the model application to Northwest China and obtained a dew yield of 5~30 mm/year from 2011 to 2020, indicating that dew is a non-negligible part of the water balance in this arid area. As a non-negligible part of the water cycle, the use of remote sensing to estimate dew can provide better support for future water resource assessment and analysis.

Over the last few decades, China has greatly expanded its scope of stem cell research, generating various scientific advances and medical applications. However, knowledge of the extent and characteristics of domestic stem cell development, particularly medical workers’ opinions, is lacking. This study’s purposes were to analyze the growth trends of China’s stem cell community and identify the knowledge and attitudes held by Chinese medical workers regarding stem cell research. We found that there are currently 13 high-quality stem cell research centers with more than 400 PhD-level researchers across Mainland China. These centers feature many high-caliber scientists from the stem cell research community. From 1997 through 2019, the National Natural Science Foundation of China allocated roughly $576 million to 8,050 stem cell programs at Chinese universities and research institutions. China’s annual publications on stem cells increased from less than 0.6% of the world’s total stem cell publications in 1999 to more than 14.1% in 2014. Our survey also revealed that most participants held positive attitudes toward stem cell research, supported further funding, and had high general awareness about stem cells.

Abstract With the increasing pressure from population growth and economic development, northern China (NC) faces a grand challenge of water scarcity, which can be further exacerbated by climatic and societal changes. The South‐to‐North Water Diversion (SNWD) project is designed to mitigate the water scarcity in NC. However, few studies have quantified the impact of the SNWD on water scarcity within the context of climatic and societal changes and its potential effects on economic and agricultural food in the region. We used water supply stress index (WaSSI) to quantify water scarcity within the context of environmental change in NC and developed a method to estimate the economic and agricultural impacts of the SNWD. Focuses were put on alleviating the water supply shortage and economic and agricultural benefits for the water‐receiving NC. We find that societal changes, especially economic growth, are the major contributors to water scarcity in NC during 2009–2099. To completely mitigate the water scarcity of NC, at least an additional water supply of 13 billion m3/year (comparable to the annual diversion water by SNWD Central Route) will be necessary. Although SNWD alone cannot provide the full solution to NC's water shortage in next few decades, it can significantly alleviate the water supply stress in NC (particularly Beijing), considerably increasing the agricultural production (more than 115 Tcal/year) and bringing economic benefits (more than 51 billion RMB/year) through supplying industrial and domestic water use. Additionally, the transfer project could have impacts on the ecological environment in the exporting regions.

Abstract Background We recently identified a role for the muscle-specific ubiquitin ligase MuRF1 in right-sided heart failure secondary to pulmonary hypertension induced by chronic hypoxia (CH). MuRF1−/− mice exposed to CH are resistant to right ventricular (RV) dysfunction whereas MuRF1 Tg + mice exhibit impaired function indicative of heart failure. The present study was undertaken to understand the underlying transcriptional alterations in the RV of MuRF1−/− and MuRF1 Tg + mice. Methods Microarray analysis was performed on RNA isolated from the RV of MuRF1−/−, MuRF1 Tg+, and wild-type control mice exposed to CH. Results MuRF1−/− RV differentially expressed 590 genes in response to CH. Analysis of the top 66 genes (> 2-fold or 3-fold or

The Qaidam Basin is a unique and complex ecosystem, wherein elevation gradients lead to high spatial heterogeneity in vegetation dynamics and responses to environmental factors. Based on the remote sensing data of Moderate Resolution Imaging Spectroradiometer (MODIS), Tropical Rainfall Measuring Mission (TRMM) and Global Land Data Assimilation System (GLDAS), we analyzed the spatiotemporal variations of vegetation dynamics and responses to precipitation, accumulative temperature (AT) and soil moisture (SM) in the Qaidam Basin from 2001 to 2016. Moreover, the contribution of those factors to vegetation dynamics at different altitudes was analyzed via an artificial neural network (ANN) model. The results indicated that the Normalized Difference Vegetation Index (NDVI) values in the growing season showed an overall upward trend, with an increased rate of 0.001/year. The values of NDVI in low-altitude areas were higher than that in high-altitude areas, and the peak values of NDVI appeared along the elevation gradient at 4400–4600 m. Thanks to the use of ANN, we were able to detect the relative contribution of various environmental factors; the relative contribution rate of AT to the NDVI dynamic was the most significant (35.17%) in the low-elevation region (

Lakes and reservoirs are essential elements of the hydrological and biochemical cycles, considered sentinels of global climate change. However, comprehensive quantifications of their water storage changes (∆V) at a large spatiotemporal scale are still rare. Here, we integrated a global surface water dataset and SRTM digital elevation models, both available from Google Earth Engine platform at a spatial resolution of 30 m, to evaluate ∆V for a total of 760 lakes and reservoirs across China at an annual timescale since 1984. The results indicated that (1) the aggregated water storage went through a slight increase of 41.5 Gt (1.7 Gt/yr) during 1985−2005, a significant decrease of 100 Gt (−20.6 Gt/yr) during 2005−2009, and then increased by 136.3 Gt (21.3 Gt/yr) during 2009−2015. (2) The increasing trend was largely attributed to lakes and reservoirs in the Tibetan Plateau Lake Zone, and the decreasing trend was mainly due to the North and Northwest Lake Zone, with little variations observed for the Northeast and Southwest Lake Zones. (3) Qinghai lake was associated with the largest increase (18.3 Gt) and Poyang lake presented the largest decline (−9.2 Gt). The results can help advance our understanding of the impact of climate change and improve future projection.

Focusing on water resources assessment in ungauged or sparse gauged areas, a comparative evaluation of areal precipitation was conducted by remote sensing data, limited gauged data, and a fusion of gauged data and remote sensing data based on machine learning. The artificial neural network (ANN) model was used to fuse the remote sensing precipitation and ground gauge precipitation. The correlation coefficient, root mean square deviation, relative deviation and consistency principle were used to evaluate the reliability of the remote sensing precipitation. The case study in the Qaidam Basin, northwest of China, shows that the precision of the original remote sensing precipitation product of Tropical Precipitation Measurement Satellite (TRMM)-3B42RT and TRMM-3B43 was 0.61, 72.25 mm, 36.51%, 27% and 0.70, 64.24 mm, 31.63%, 32%, respectively, comparing with gauged precipitation. The precision of corrected TRMM-3B42RT and TRMM-3B43 improved to 0.89, 37.51 mm, −0.08%, 41% and 0.91, 34.22 mm, 0.11%, 42%, respectively, which indicates that the data mining considering elevation, longitude and latitude as the main influencing factors of precipitation is efficient and effective. The evaluation of areal precipitation in the Qaidam Basin shows that the mean annual precipitation is 104.34 mm, 186.01 mm and 174.76 mm based on the gauge data, corrected TRMM-3B42RT and corrected TRMM-3B43. The results show many differences in the areal precipitation based on sparse gauge precipitation data and fusion remote sensing data.