Soil Organic Carbon Prediction Based on Vis-NIR Spectral Classification Data Using GWPCA-FCM Algorithm.

Soil visible and near-infrared reflectance spectroscopy is an effective tool for the rapid estimation of soil organic carbon (SOC). The development of spectroscopic technology has increased the application of spectral libraries for SOC research. However, the direct application of spectral libraries for SOC prediction remains challenging due to the high variability in soil types and soil-forming factors. This study aims to address this challenge by improving SOC prediction accuracy through spectral classification. We utilized the European Land Use and Cover Area frame Survey (LUCAS) large-scale spectral library and employed a geographically weighted principal component analysis (GWPCA) combined with a fuzzy c-means (FCM) clustering algorithm to classify the spectra. Subsequently, we used partial least squares regression (PLSR) and the Cubist model for SOC prediction. Additionally, we classified the soil data by land cover types and compared the classification prediction results with those obtained from spectral classification. The results showed that (1) the GWPCA-FCM-Cubist model yielded the best predictions, with an average accuracy of R2 = 0.83 and RPIQ = 2.95, representing improvements of 10.33% and 18.00% in R2 and RPIQ, respectively, compared to unclassified full sample modeling. (2) The accuracy of spectral classification modeling based on GWPCA-FCM was significantly superior to that of land cover type classification modeling. Specifically, there was a 7.64% and 14.22% improvement in R2 and RPIQ, respectively, under PLSR, and a 13.36% and 29.10% improvement in R2 and RPIQ, respectively, under Cubist. (3) Overall, the prediction accuracy of Cubist models was better than that of PLSR models. These findings indicate that the application of GWPCA and FCM clustering in conjunction with the Cubist modeling technique can significantly enhance the prediction accuracy of SOC from large-scale spectral libraries.

Changes in total organic carbon and organic carbon fractions of reclaimed minesoils in response to the filling of different substrates.

Soil organic carbon (SOC) of reclaimed minesoil (RMS) is regarded as an important part of terrestrial SOC, and SOC losses of RMSs occur during the substantial soil compaction and the removal, storage and backfilling of the topsoil, which lead to poor soil structure. The filling of alternative soil substrates is considered to disturb the soil structure of RMSs, however, how SOC pool changes in the RMSs filled with various substrates and the mechanisms are less clearly understood. Therefore, a study on reclaimed area filled with three typical alternative soil substrates, including mining waste reclamation (MWR), river sand reclamation (RSR) and river mud reclamation (RMR), was started in mining area of Eastern China, where total SOC, labile SOC fractions, stable SOC fraction and soil physicochemical properties were measured. The results showed that (1) the total SOC, labile SOC fractions (microbial biomass carbon (MBC), readily oxidizable organic carbon (ROOC), light fraction organic carbon (LFOC) and particulate organic carbon (POC)) and stable SOC fraction (humic acids carbon (HAC)) contents of RMSs were lower than those of non-subsided cultivated land (NCL), the filling of alternative soil substrates had a significant effect on the SOC composition of RMSs, and the backfilling layer of RSR and the filling layer of MWR were more similar with NCL than other treatments in SOC composition; (2) In backfilling layer, bulk density (BD), connectivity index (τ), available phosphorus (AP), available potassium (AK) and soil urease (URE) were strong predictors for dissimilarities of SOC composition, and the difference in soil physics and soil fertility had more direct and indirect effects on the contents of SOC and SOC fractions; (3) In filling layer, water content (WC), macropore number (MN), microporosity (Φmac), available nitrogen (AN), electronic conductivity (EC), soil urease (URE) and sucrase (SUC) were strong predictors for dissimilarities of SOC composition, and the substrate texture and soil physics had more direct and indirect effects on the contents of SOC and SOC fractions. Easing the compactness and strengthening fertilizing management of backfilling layer, while improving the texture of filling substrates benefit the increasing of the SOC content of RMSs.

Evaluation of Machine Learning Approaches to Predict Soil Organic Matter and pH Using vis-NIR Spectra.

Soil organic matter (SOM) and pH are essential soil fertility indictors of paddy soil in the middle-lower Yangtze Plain. Rapid, non-destructive and accurate determination of SOM and pH is vital to preventing soil degradation caused by inappropriate land management practices. Visible-near infrared (vis-NIR) spectroscopy with multivariate calibration can be used to effectively estimate soil properties. In this study, 523 soil samples were collected from paddy fields in the Yangtze Plain, China. Four machine learning approaches-partial least squares regression (PLSR), least squares-support vector machines (LS-SVM), extreme learning machines (ELM) and the Cubist regression model (Cubist)-were used to compare the prediction accuracy based on vis-NIR full bands and bands reduced using the genetic algorithm (GA). The coefficient of determination (R²), root mean square error (RMSE), and ratio of performance to inter-quartile distance (RPIQ) were used to assess the prediction accuracy. The ELM with GA reduced bands was the best model for SOM (SOM: R² = 0.81, RMSE = 5.17, RPIQ = 2.87) and pH (R² = 0.76, RMSE = 0.43, RPIQ = 2.15). The performance of the LS-SVM for pH prediction did not differ significantly between the model with GA (R² = 0.75, RMSE = 0.44, RPIQ = 2.08) and without GA (R² = 0.74, RMSE = 0.45, RPIQ = 2.07). Although a slight increase was observed when ELM were used for prediction of SOM and pH using reduced bands (SOM: R² = 0.81, RMSE = 5.17, RPIQ = 2.87; pH: R² = 0.76, RMSE = 0.43, RPIQ = 2.15) compared with full bands (R² = 0.81, RMSE = 5.18, RPIQ = 2.83; pH: R² = 0.76, RMSE = 0.45, RPIQ = 2.07), the number of wavelengths was greatly reduced (SOM: 201 to 44; pH: 201 to 32). Thus, the ELM coupled with reduced bands by GA is recommended for prediction of properties of paddy soil (SOM and pH) in the middle-lower Yangtze Plain.

PKM2 regulates neural invasion of and predicts poor prognosis for human hilar cholangiocarcinoma.

BACKGROUND: The therapeutic and prognostic value of the glycolytic enzymes hexokinase, phosphofructokinase, and pyruvate kinase (PK) has been implicated in a variety of cancers, while their roles in treatment of and prognosis for hilar cholangiocarcinoma (HC) remain unclear. In this study, we determined the expression of PKM2 in and its impact on biology and clinical outcome of human HC. METHODS: The regulation and function of PKM2 in HC pathogenesis was evaluated using human tissues, molecular and cell biology, and animal models, and its prognostic significance was determined according to its impact on patient survival. RESULTS: We found that expression of hexokinase 1 and the M2 splice isoform of PK (PKM2) was upregulated in HC tissues and that this expression correlated with tumor recurrence and outcome. PKM2 expression was increased in HC cases with chronic cholangitis as demonstrated by isobaric tags for relative and absolute quantification. High PKM2 expression was highly correlated with high syndecan 2 (SDC2) expression and neural invasion. PKM2 downregulation led to a decrease in SDC2 expression. Treatment with metformin markedly suppressed PKM2 and SDC2 expression at both the transcriptional and posttranscriptional levels and inhibited HC cell proliferation and tumor growth. CONCLUSIONS: PKM2 regulates neural invasion of HC cells at least in part via regulation of SDC2. Inhibition of PKM2 and SDC2 expression contributes to the therapeutic effect of metformin on HC. Therefore, PKM2 is an independent prognostic factor and potential therapeutic target for human HC.

Differential expression of ANXA1 in benign human gastrointestinal tissues and cancers.

BACKGROUND: Annexin-1 contributes to the pathological consequence and sequelae of most serious human diseases including cardiovascular disease and cancer. Although diverse roles in carcinogenesis have been postulated, its role in human gastrointestinal cancers still remains controversial. METHODS: The mRNA and protein expression profiles of ANXA1 were studied in human esophageal, gastric, pancreatic, colorectal, liver, and bile duct cancers using Real-Time PCR, western blotting, and immunohistochemistry. Gain/loss-of-function by pcDNA3.1-ANXA1 and ANXA1-shRNA was performed in gastric cancer cells. RESULTS: ANXA1 was widely expressed in adult gastrointestinal tissue. All methods showed that ANXA1 was down-regulated in esophageal, gastric, and bile duct cancers, but up-regulated in pancreatic cancer. Forced ANXA1 expression in gastric cancer cells leads to cell growth inhibition and concomitantly modulates COX-2 expression. We confirm loss of ANXA1 and overexpression of COX-2 in clinical gastric cancer, suggesting that the anti-proliferative function of ANXA1 against COX-2 production might be lost. CONCLUSIONS: ANXA1 expression is "tumor-specific" and might play a multifaceted role in cancer development and progression. ANXA1 was widely expressed in normal gastrointestinal epithelium, suggesting its role in the maintenance of cellular boundaries. Furthermore, ANXA1 regulates GC cell viability via the COX-2 pathway.

Comparative Metabolomic Responses of Three Rhododendron Cultivars to the Azalea Lace Bug (Stephanitis pyrioides).

Rhododendron, with its high ornamental value and ecological benefits, is severely impacted by the azalea lace bug (Stephanitis pyrioides), one of its primary pests. This study utilized three Rhododendron cultivars, 'Zihe', 'Yanzhimi', and 'Taile', to conduct a non-targeted metabolomic analysis of leaf samples before and after azalea lace bug stress using headspace solid-phase microextraction combined with gas chromatography-mass spectrometry (HS-SPME/GCMS) and liquid chromatography-mass spectrometry (LCMS). A total of 81 volatile metabolites across 11 categories and 448 nonvolatile metabolites across 55 categories were detected. Significant differences in metabolic profiles were observed among the different cultivars after pest stress. A total of 47 volatile compounds and 49 nonvolatile metabolites were upregulated in the most susceptible cultivar 'Zihe', including terpenes, alcohols, nucleotides, amino acids, and carbohydrates, which are involved in energy production and secondary metabolism. Conversely, 'Yanzhimi' showed a downtrend in both the differential volatiles and metabolites related to purine metabolism and zeatin biosynthesis under pest stress. The resistant cultivar 'Taile' exhibited moderate changes, with 17 volatile compounds and 17 nonvolatile compounds being upregulated and enriched in the biosynthesis of amino acids, pentose, glucuronate interconversions, carbon metabolism, etc. The phenylalanine metabolic pathway played an important role in the pest resistance of different susceptible cultivars, and relevant metabolites such as phenylethyl alcohol, methyl salicylate, and apigenin may be involved in the plant's resistance response. The results of this study provide a new perspective on the metabolomics of Rhododendron-insect interactions and offer references for the development of pest control strategies.

A novel electrochemical sensing method based on an amino-functionalized MXene for the rapid and selective detection of Hg2.

Mercury is a highly toxic element that is widely present in all types of environmental media and can accumulate in living organisms. Prolonged exposure to high levels of mercury can lead to brain damage and death, so the detection of mercury is of great importance. In this study, a cost-effective and easy-to-operate electrochemical sensing method was successfully developed based on an amino-functionalized titanium-based MXene (NH2-Ti3C2Tx) for the rapid and selective detection of Hg2+ that could have a coordination effect with the -NH2 group of NH2-Ti3C2Tx to promote the efficient accumulation of Hg2+. In this strategy, the NH2-Ti3C2Tx was first modified on glassy carbon electrodes (GCE) to fabricate the electrochemical sensor. Benefiting from the excellent electrical conductivity, abundant active sites, and strong adsorption capacity performance of the NH2-Ti3C2Tx, the NH2-Ti3C2Tx modified GCE (NH2-Ti3C2Tx/GCE) exhibited satisfactory selectivity and enhanced square wave anodic stripping voltammetry (SWASV) measurement for the rapid detection of trace amounts of Hg2+ in aqueous solutions. The electrochemical sensor was found to be capable of detecting Hg2+ with a low detection limit of 8.27 nmol L-1 and a linear range of 0.5 µmol L-1 to 50 µmol L-1. The response time of the electrochemical sensing method was 308 s. In addition, the electrochemical sensing method has good selectivity, repeatability and stability, and multiple heavy metal ions have no effect on its detection, with repeatability and stability RSDs of 1.68% and 1.43%, respectively. Furthermore, the analysis of practical water samples demonstrated that the developed method was highly practical for the actual determination of Hg2+ with recoveries in the range of 99.22-101.90%.

Target-triggered 'colorimetric-fluorescence' dual-signal sensing system based on the versatility of MnO2 nanosheets for rapid detection of uric acid.

A simple dual-signal assay that combined colorimetric and fluorometric strategy for uric acid (UA) rapid detection was designed based on the versatility of facile synthesized MnO2 nanosheet. The oxidization of 3,3',5,5'-tetramethylbenzidine (TMB) and the fluorescence quenching of quantum dots (QDs) occurred simultaneously in the presence of MnO2 nanosheet. UA could decompose MnO2 nanosheet into Mn2+, resulting in the fluorescence recovery of QDs, along with the fading of the blue color of ox TMB. Based on the principles above, the detection of UA could be realized by the change of the dual signals (colorimetric and fluorometric). The linear range of the colorimetric mode was 5-60 µmol L-1, and the limit of detection (LOD) was 2.65 µmol L-1; the linear range of the fluorescence mode was wide at 5-120 µmol L-1, and the LOD could be as low as 1.33 µmol L-1. The method was successfully used for analyzing UA levels in human serum samples, indicating that this new dual-signal method could be applied in clinical diagnosis.

Avasimibe Dampens Cholangiocarcinoma Progression by Inhibiting FoxM1-AKR1C1 Signaling.

Avasimibe is a bioavailable acetyl-CoA acetyltransferase (ACAT) inhibitor and shows a good antitumor effect in various human solid tumors, but its therapeutic value in cholangiocarcinoma (CCA) and underlying mechanisms are largely unknown. In the study, we proved that avasimibe retard cell proliferation and tumor growth of CCAs and identified FoxM1/AKR1C1 axis as the potential novel targets of avasimibe. Aldo-keto reductase 1 family member C1 (AKR1C1) is gradually increased along with the disease progression and highly expressed in human CCAs. From survival analysis, AKR1C1 could be a vital predictor of tumor recurrence and prognostic factor. Enforced Forkhead box protein M1 (FoxM1) expression results in the upregulation of AKR1C1, whereas silencing FoxM1 do the opposite. FoxM1 directly binds to promoter of AKR1C1 and triggers its transcription, while FoxM1-binding site mutation decreases AKR1C1 promoter activity. Moreover, over-expressing exogenous FoxM1 reverses the growth retardation of CCA cells induced by avasimibe administration, while silencing AKR1C1 in FoxM1-overexpressing again retard cell growth. Furthermore, FoxM1 expression significantly correlates with the AKR1C1 expression in human CCA specimens. Our study demonstrates a novel positive regulatory between FoxM1 and AKR1C1 contributing cell growth and tumor progression of CCA and avasimibe may be an alternative therapeutic option for CCA by targeting this FoxM1/AKR1C1 signaling pathway.

Data fusion for the measurement of potentially toxic elements in soil using portable spectrometers.

Soil contamination posed by potentially toxic elements is becoming more serious under continuously development of industrialization and the abuse of fertilizers and pesticides. The investigation of soil potentially toxic elements is therefore urgently needed to ensure human and other organisms' health. In this study, we investigated the feasibility of the separate and combined use of portable X-ray fluorescence (pXRF) and visible near-infrared reflectance (vis-NIR) sensors for measuring eight potentially toxic elements in soil. Low-level fusion was achieved by the direct combination of the pXRF and vis-NIR spectra; middle-level fusion was achieved by the combination of selected bands of the pXRF and vis-NIR spectra using the Boruta feature selection algorithm; and high-level fusion was conducted by outer-product analysis (OPA) and Granger-Ramanathan averaging (GRA). The estimation accuracy for the eight considered elements were in the following order: Zn > Cu > Ni > Cr > As > Cd > Pb > Hg. The measurement for Cu and Zn could be achieved by pXRF spectra alone with Lin's concordance correlation coefficient (LCCC) values of 0.96 and 0.98, and ratio of performance to interquartile distance (RPIQ) values of 2.36 and 2.69, respectively. The measurement of Ni had the highest model performance for high-level fusion GRA with LCCC of 0.89 and RPIQ of 3.42. The measurements of Cr using middle- and high-level fusion were similar, with LCCC of 0.86 and RPIQ of 2.97. The best estimation accuracy for As, Cd, and Pb were obtained by high-level fusion using OPA, with LCCC >0.72 and RPIQ >1.2. However, Hg measurement by these techniques failed, having an unacceptable performance of LCCC <0.20 and RPIQ <0.75. These results confirm the effectiveness of using portable spectrometers to determine the contents of several potentially toxic elements in soils.

Improvement of Spatial Modeling of Cr, Pb, Cd, As and Ni in Soil Based on Portable X-ray Fluorescence (PXRF) and Geostatistics: A Case Study in East China.

To verify the feasibility of portable X-ray fluorescence (PXRF) for rapidly analyzing, assessing and improving soil heavy metals mapping, 351 samples were collected from Fuyang District, Hangzhou City, in eastern China. Ordinary kriging (OK) and co-ordinary kriging (COK) combined with PXRF measurements were used to explore spatial patterns of heavy metals content in the soil. The Getis-Ord index was calculated to discern hot spots of heavy metals. Finally, multi-variable indicator kriging was conducted to obtain a map of multi-heavy metals pollution. The results indicated Cd is the primary pollution element in Fuyang, followed by As and Pb. Application of PXRF measurements as covariates in COK improved model accuracy, especially for Pb and Cd. Heavy metals pollution hot spots were mainly detected in northern Fuyang and plains along the Fuchun River in southern Fuyang because of mining, industrial and traffic activities, and irrigation with polluted water. Area with high risk of multi-heavy metals pollution mainly distributed in plain along the Fuchun River and the eastern Fuyang. These findings certified the feasibility of using PXRF as an efficient and reliable method for soil heavy metals pollution assessment and mapping, which could contribute to reduce the cost of surveys and pollution remediation.

Pyrophosphatase 1 expression is associated with future recurrence and overall survival in Chinese patients with intrahepatic cholangiocarcinoma.

The inorganic pyrophosphatase gene (PPA1) encodes inorganic pyrophosphatase, an enzyme that catalyzes the hydrolysis of inorganic pyrophosphate to orthophosphate, and has been revealed to be dysregulated in several types of human cancer. However, the role of PPA1 in intrahepatic cholangiocarcinoma (ICC) has not yet been determined. The present study detected PPA1 expression and investigated its clinical significance in ICC. Tissue microarray blocks containing 93 ICC specimens were constructed. The protein expression of PPA1 in these specimens was detected by immunohistochemistry. PPA1 was overexpressed in 49.5% of the ICC specimens and was significantly associated with large tumor size, positive margins, T stage, lymph nodal metastases, poorly differentiated tumors and advanced disease stage. Furthermore, PPA1 expression was an indicator of future recurrence and poor survival in patients with ICC. Increased expression of PPA1 is a common event in human ICC and is significantly associated with a poor outcome in patients with ICC, suggesting a potential role for PPA1 in the development and progression of ICC.

De novo RNA sequencing transcriptome of Rhododendron obtusum identified the early heat response genes involved in the transcriptional regulation of photosynthesis.

Rhododendron spp. is an important ornamental species that is widely cultivated for landscape worldwide. Heat stress is a major obstacle for its cultivation in south China. Previous studies on rhododendron principally focused on its physiological and biochemical processes, which are involved in a series of stress tolerance. However, molecular or genetic properties of rhododendron's response to heat stress are still poorly understood. The phenotype and chlorophyll fluorescence kinetics parameters of four rhododendron cultivars were compared under normal or heat stress conditions, and a cultivar with highest heat tolerance, "Yanzhimi" (R. obtusum) was selected for transcriptome sequencing. A total of 325,429,240 high quality reads were obtained and assembled into 395,561 transcripts and 92,463 unigenes. Functional annotation showed that 38,724 unigenes had sequence similarity to known genes in at least one of the proteins or nucleotide databases used in this study. These 38,724 unigenes were categorized into 51 functional groups based on Gene Ontology classification and were blasted to 24 known cluster of orthologous groups. A total of 973 identified unigenes belonged to 57 transcription factor families, including the stress-related HSF, DREB, ZNF, and NAC genes. Photosynthesis was significantly enriched in the Kyoto Encyclopedia of Genes and Genomes pathway, and the changed expression pattern was illustrated. The key pathways and signaling components that contribute to heat tolerance in rhododendron were revealed. These results provide a potentially valuable resource that can be used for heat-tolerance breeding.

Assessment of Heavy Metal Pollution and Health Risks in the Soil-Plant-Human System in the Yangtze River Delta, China.

Heavy metal (HM) contamination and accumulation is a serious problem around the world due to the toxicity, abundant sources, non-biodegradable properties, and accumulative behaviour of HMs. The degree of soil HM contamination in China, especially in the Yangtze River Delta, is prominent. In this study, 1822 pairs of soil and crop samples at corresponding locations were collected from the southern Yangtze River Delta of China, and the contents of Ni, Cr, Zn, Cd, As, Cu, Hg, and Pb were measured. The single pollution index in soil (SPI) and Nemerow composite pollution index (NCPI) were used to assess the degree of HM pollution in soil, and the crop pollution index (CPI) was used to explore the degree of HM accumulation in crops. The bioaccumulation factor (BAF) was used to investigate the translocation of heavy metals in the soil-crop system. The health risks caused by HMs were calculated based on the model released by the U.S. Environmental Protection Agency. The SPIs of all elements were at the unpolluted level. The mean NCPI was at the alert level. The mean CPIs were in the following decreasing order: Ni (1.007) > Cr (0.483) > Zn (0.335) > Cd (0.314) > As (0.232) > Cu (0.187) > Hg (0.118) > Pb (0.105). Only the mean content of Ni in the crops exceeded the national standard value. The standard exceeding rates were used to represent the percentage of samples whose heavy metal content is higher than the corresponding national standard values. The standard exceeding rates of Cu, Hg, and Cd in soil were significantly higher than corresponding values in crops. Meanwhile, the standard exceeding rates of Ni, As, and Cr in crops were significantly higher than corresponding values in soil. The chronic daily intake (CDI) of children (13.8 × 10-3) was the largest among three age groups, followed by adults (6.998 × 10-4) and seniors (5.488 × 10-4). The bioaccumulation factors (BAFs) of all crops followed the order Cd (0.249) > Zn (0.133) > As (0.076) > Cu (0.064) > Ni (0.018) > Hg (0.011) > Cr (0.010) > Pb (0.001). Therefore, Cd was most easily absorbed by crops, and different crops had different capacities to absorb HMs. The hazard quotient (HQ) represents the potential non-carcinogenic risk for an individual HM and it is an estimation of daily exposure to the human population that is not likely to represent an appreciable risk of deleterious effects during a lifetime. All the HQs of the HMs for the different age groups were significantly less than the alert value of 1.0 and were at a safe level. This indicated that citizens in the study area face low potential non-carcinogenic risk caused by HMs. The total carcinogens risks (TCRs) for children, adults, and seniors were 5.24 × 10-5, 2.65 × 10-5, and 2.08 × 10-5, respectively, all of which were less than the guideline value but at the alert level. Ingestion was the main pathway of carcinogen risk to human health.

Overexpression of metabolic markers HK1 and PKM2 contributes to lymphatic metastasis and adverse prognosis in Chinese gastric cancer.

Hexokinase 1 (HK1) and pyruvate kinase M2 (PKM2) are two key regulators in glycosis and oncogenic markers in cancers. In the present study, we investigated the expression profile by Western blotting and immunohistochemistry and determined their prognostic values in the gastric cancer. Expression of HK1 and PKM2 was remarkably increased in gastric cancer tissues and was significantly associated lymphatic metastasis and advanced TNM staging. In the COX regression model, HK1 and TNM stage were analyzed as adverse prognostic indicators in gastric cancer. Furthermore, patients with HK1 expression showed remarkable shorter survival duration in both lymphatic metastasis cohort and advanced staging cohort. Our results suggest that overexpression of PKM2 and HK1, especially the latter, significantly associates with lymphatic metastasis, advanced clinical staging and unfavorable prognosis in gastric cancer.

Overexpression of Sig1R is closely associated with tumor progression and poor outcome in patients with hilar cholangiocarcinoma.

Nonopioid Sigma1 receptor (Sig1R), which regulates various metabolism functions, has been implicated in cancers; yet, its role in hilar cholangiocarcinoma remains unclear. In the present study, we examined Sig1R expression in hilar cholangiocarcinoma (HC) tissues and explored its possible clinical values. Tissue microarray blocks containing 92 HC tissues and matched non-cancerous bile duct tissues were examined immunohistochemically for expression of Sig1R protein. Overexpression of Sig1R was found in 43 (46.7%) of the 92 primary tumor tissues. Overexpression of Sig1R was significantly associated with poor/undifferentiation (P = 0.011), tumor invasion (P = 0.001), lymph node metastasis (P = 0.047), and advanced disease stage (P = 0.024) of HC patients. Kaplan-Meier analysis showed that patients overexpressing Sig1R had an earlier recurrence and worse overall survival than those not overexpressing Sig1R. Cox regression analysis revealed that Sig1R was an independent factor to predict HC recurrence and prognosis of HC patients. Our results suggest that Sig1R is frequently activated in human HC tissue and overexpression of Sig1R might serve as a predictor for tumor recurrence and a prognostic biomarker for HC patients.