Delta-radiomics Analysis Based on Multi-phase Contrast-enhanced MRI to Predict Early Recurrence in Hepatocellular Carcinoma After Percutaneous Thermal Ablation.

RATIONALE AND OBJECTIVES: It is critical to predict early recurrence (ER) after percutaneous thermal ablation (PTA) for hepatocellular carcinoma (HCC). We aimed to develop and validate a delta-radiomics nomogram based on multi-phase contrast-enhanced magnetic resonance imaging (MRI) to preoperatively predict ER of HCC after PTA. MATERIALS AND METHODS: We retrospectively enrolled 164 patients with HCC and divided them into training, temporal validation, and other-scanner validation cohorts (n = 110, 29, and 25, respectively). The volumes of interest of the intratumoral and/or peritumoral regions were delineated on preoperative multi-phase MR images. Original radiomics features were extracted from each phase, and delta-radiomics features were calculated. Logistic regression was used to train the corresponding radiomics models. The clinical and radiological characteristics were evaluated and combined to establish a clinical-radiological model. A fusion model comprising the best radiomics scores and clinical-radiological risk factors was constructed and presented as a nomogram. The performance of each model was evaluated and recurrence-free survival (RFS) was assessed. RESULTS: Child-Pugh grade B, high-risk tumor location, and an incomplete/absent tumor capsule were independent predictors of ER. The optimal radiomics model comprised 12 delta-radiomics features with areas under the curve (AUCs) of 0.834, 0.795, and 0.769 in the training, temporal validation, and other-scanner validation cohorts, respectively. The nomogram showed the best predictive performance with AUCs as 0.893, 0.854, and 0.827 in the three datasets. There was a statistically significant difference in RFS between the risk groups calculated using the delta-radiomics model and nomogram. CONCLUSIONS: The nomogram combined with the delta-radiomic score and clinical-radiological risk factors could non-invasively predict ER of HCC after PTA.

Investigating the three-dimensional myocardial micro-architecture in the laminar structure using X-ray phase-contrast microtomography.

A comprehensive grasp of the myocardial micro-architecture is essential for understanding diverse heart functions. This study aimed to investigate three-dimensional (3D) cardiomyocyte arrangement in the laminar structure using X-ray phase-contrast microtomography. Using the ID-19 beamline at the European Synchrotron Radiation Facility, we imaged human left ventricular (LV) wall transparietal samples and reconstructed them with an isotropic voxel edge length of 3.5 µm. From the reconstructed volumes, we extracted different regions to analyze the orientation distribution of local cardiomyocyte aggregates, presenting findings in terms of helix and intrusion angles. In regions containing one sheetlet population, we observed cardiomyocyte aggregates running along the local LV wall's radial direction at the border of sheetlets, branching and merging into a complex network around connecting points of different sheetlets, and bending to accommodate vessel passages. In regions with two sheetlet populations, the helix angle of local cardiomyocyte aggregates experiences a nonmonotonic change, and some cardiomyocyte aggregates run along the local radial direction. X-ray phase-contrast microtomography is a valuable technique for investigating the 3D local myocardial architecture at microscopic level. The arrangement of local cardiomyocyte aggregates in the LV wall proves to be both regional and complex, intricately linked to the local laminar structure.

Enhanced lactic acid production through enzymatic hydrolysis: Assessing impact of varied enzyme loadings on co-fermentation of swine manure and apple waste.

Anaerobic co-fermentation of swine manure (SM) and apple waste (AW) restricts by the slow hydrolysis of substrates with complex structures, which subsequently leads to low lactic acid (LA) production. Therefore, a novel strategy based on enzymatic pretreatment for improving LA production from anaerobic co-fermentation of SM and AW was proposed in this study. The results indicated that the maximal LA concentration increased from 35.89 ± 1.84 to 42.70 ± 2.18 g/L with the increase of enzyme loading from 0 to 300 U/g VSsubstrate. Mechanism exploration indicated that enzymatic pretreatment significantly promoted the release and hydrolysis of insoluble organic matter from fermentation substrate, thus providing an abundance of reaction intermediates that were directly available for LA production. Additionally, bacteria analysis revealed that the high concentration of LA was associated with the prevalence of Lactobacillus. This study offered an environmental-friendly strategy for promoting SM and AW hydrolysis and provided a viable approach for recovering valuable products.

Lactic acid production with two types of feedstocks from food waste: Effect of inoculum, temperature, micro-oxygen, and initial pH.

Lactic acid (LA) is an important chemical with broad market applications. To optimize LA production, food waste has been explored as feedstock. Due to the wide variety of food waste types, most current research studies have obtained different conclusions. This study focuses on carbohydrate-rich fruit and vegetable waste (FVW) and lipid-rich kitchen waste (KW), and the effect of inoculum, temperature, micro-oxygen, and initial pH were compared. FVW has a greater potential for LA production than KW. As an inoculum, lactic acid bacteria (LAB) significantly increased the maximum LA concentration (27.6 g/L) by 50.8 % compared with anaerobic sludge (AS). FVW exhibited optimal LA production at 37 °C with micro-oxygen. Adjustment of initial pH from 4 to 8 alleviated the inhibitory effect of accumulated LA, resulting in a 46.2 % increase in maximum LA production in FVW. The expression of functional genes associated with metabolism, genetic information processing, and environmental information processing was higher at 37 °C compared to 50 °C.

Identification and Functional Verification of the Glycosyltransferase Gene Family Involved in Flavonoid Synthesis in Rubus chingii Hu.

Glycosylation is catalyzed by UDP-glycosyltransferase (UGT) and plays an important role in enriching the diversity of flavonoids. Rubus plants contain a lot of natural flavonoid glycosides, which are important plants with a homology of medicine and food. However, information about the Rubus UGT gene family is very limited. In this study, we carried out genome-wide analysis and identified the 172, 121, 130, 121 UGT genes in R. chingii, R. corchorifolius, R. idaeus, and R. occidentalis, respectively, and divided them into 18 groups. The analysis of the protein motif and gene structure showed that there were structural and functional conservations in the same group, but there were differences among different groups. Gene replication analysis showed that raspberry and dicotyledons had a higher homology. The expansion of the UGTs gene family was mainly driven by tandem replication events, and experienced purified selection during the long evolution of the raspberry. Cis-acting element analysis showed that they were related to plant growth and development, hormone regulation, and stress response. In addition, according to a comprehensive analysis of the co-expression network constructed by transcriptome data and phylogenetic homology, RchUGT169 was identified as a flavonoid glucosyltransferase. Through the transient expression in tobacco, it was verified that RchUGT169 could catalyze the conversion of kaempferol and quercetin to the corresponding flavonoid glycosides. In conclusion, this research enriched the understanding of the diversity of UGTs in Rubus and determined that RcUGT169 can catalyze flavonoids.

Highly Polarization-Deep-Ultraviolet-Sensitive ß-Ga2O3 Epitaxial Films by Disrupting Rotational Symmetry and Encrypted Solar-Blind Optical Communication Application.

Ultrawide bandgap semiconductor ß-Ga2O3 (4.9 eV), with its monoclinic crystal structure, exhibits distinct anisotropic characteristics both optically and electrically, making it an ideal material for solar-blind polarization photodetectors. In this work, ß-Ga2O3 epitaxial films were deposited on sapphire substrates with different orientations, and the mechanisms underlying the anisotropy of these epitaxial films were investigated. Compared to c-plane sapphire, the lattice mismatch between m- or r-plane sapphire and ß-Ga2O3 is more pronounced, disrupting the rotational symmetry of the films and rendering them anisotropic. Thanks to the improved anisotropy, the polarization ratio of the photodetector based on ß-Ga2O3 films grown on r-plane substrates is 0.24, nearly ten times higher than that on c-plane substrates. Finally, by utilizing these polarization-sensitive photodetectors, we developed an encrypted solar-blind ultraviolet optical communication system. Our work provides a new approach to facilitate the fabrication and application of high-performance polarization-sensitive solar-blind photodetectors.

The influence of using different types of modified vermiculite cover on ammonia mitigation from animal slurry storage: The role of sulfuric acid.

Animal slurry storage is an important ammonia (NH3) emission source. Sulfuric acid (H2SO4)-modified vermiculite coverage is a new promising technology for controlling NH3 emission from slurry storage. However, the underlying mechanisms in controlling the mitigation effect remain unclear. Here, a series of experiments to determine the effect of H2SO4 on the modified vermiculite properties, floating persistence, and NH3 mitigation effect was conducted. Results showed that abundant H2SO4 and sulfate remained on the outer surface and in the extended inner pores of the vermiculite with acidifying H+ concentrations higher than 5 M. An initial strong instantaneous acidification of surface slurry released rich carbon dioxide bubbles, strengthening cover floating performance. An acidification in the vermiculite cover layer and a good coverage inhibition interacted, being the two leading mechanisms for mitigating NH3 during initial 40-50 days of storage. The bacterial-amoA gene dominated the conversion of NH3 to nitrous oxide after 50 days of storage. Vermiculite with 5 M H+ modification reduced the NH3 emissions by 90 % within the first month of slurry storage and achieved a 64 % mitigation efficiency throughout the 84 days period. With the development of the aerial spraying equipment such as agricultural drones, acidifying vermiculite coverage hold promise as an effective method for reducing NH3 emission while absorbing nutrients from liquid slurry storage tank or lagoon. This design should now be tested under field conditions.

Enzyme enhanced lactic acid fermentation of swine manure and apple waste: Insights from organic matter transformation and functional bacteria.

Anaerobic co-fermentation is a favorable way to convert agricultural waste, such as swine manure (SM) and apple waste (AW), into lactic acid (LA) through microbial action. However, the limited hydrolysis of organic matter remains a main challenge in the anaerobic co-fermentation process. Therefore, this work aims to deeply understand the impact of cellulase (C) and protease (P) ratios on LA production during the anaerobic co-fermentation of SM with AW. Results showed that the combined use of cellulase and protease significantly improved the hydrolysis during the enzymatic pretreatment, thus enhancing the LA production in anaerobic acidification. The highest LA reached 41.02 ± 2.09 g/L within 12 days at the ratio of C/P = 1:3, which was approximately 1.26-fold of that in the control. After a C/P = 1:3 pretreatment, a significant SCOD release of 45.34 ± 2.87 g/L was achieved, which was 1.13 times the amount in the control. Moreover, improved LA production was also attributed to the release of large amounts of soluble carbohydrates and proteins with enzymatic pretreated SM and AW. The bacterial community analysis revealed that the hydrolytic bacteria Romboutsia and Clostridium_sensu_stricto_1 were enriched after enzyme pretreatment, and Lactobacillus was the dominant bacteria for LA production. This study provides an eco-friendly technology to enhance hydrolysis by enzymatic pretreatment and improve LA production during anaerobic fermentation.

Use of the intrusion angle to describe the radial orientation of local cardiomyocytes in the left ventricle.

The projected transverse angle and the nonprojected intrusion angle can be used to describe the radial orientation of local cardiomyocytes in the left ventricle wall, although to date their descriptive relevance has not been demonstrated. This paper compares the evolution of the transverse angle and the intrusion angle in five left ventricle wall samples, and investigates in more detail their respective behaviors when the nonprojected helical angle varies. We show that the intrusion angle avoids the "projection" effect, and contrary to the transverse angle, it remains stable whatever the values taken by the nonprojected helical angle, even when this approaches 90°. The intrusion angle is the better choice, rather than the transverse angle, in describing the radial orientation of local cardiomyocytes. Furthermore, the oscillation of the intrusion angle in the samples is assessed, whose results indicate that the intrusion angle's oscillation amplitude and period are regional and related to the local tissue architecture.

DAT-MT Accelerated Graph Fusion Dependency Parsing Model for Small Samples in Professional Fields.

The rapid development of information technology has made the amount of information in massive texts far exceed human intuitive cognition, and dependency parsing can effectively deal with information overload. In the background of domain specialization, the migration and application of syntactic treebanks and the speed improvement in syntactic analysis models become the key to the efficiency of syntactic analysis. To realize domain migration of syntactic tree library and improve the speed of text parsing, this paper proposes a novel approach-the Double-Array Trie and Multi-threading (DAT-MT) accelerated graph fusion dependency parsing model. It effectively combines the specialized syntactic features from small-scale professional field corpus with the generalized syntactic features from large-scale news corpus, which improves the accuracy of syntactic relation recognition. Aiming at the problem of high space and time complexity brought by the graph fusion model, the DAT-MT method is proposed. It realizes the rapid mapping of massive Chinese character features to the model's prior parameters and the parallel processing of calculation, thereby improving the parsing speed. The experimental results show that the unlabeled attachment score (UAS) and the labeled attachment score (LAS) of the model are improved by 13.34% and 14.82% compared with the model with only the professional field corpus and improved by 3.14% and 3.40% compared with the model only with news corpus; both indicators are better than DDParser and LTP 4 methods based on deep learning. Additionally, the method in this paper achieves a speedup of about 3.7 times compared to the method with a red-black tree index and a single thread. Efficient and accurate syntactic analysis methods will benefit the real-time processing of massive texts in professional fields, such as multi-dimensional semantic correlation, professional feature extraction, and domain knowledge graph construction.

Single-slice rebinning reconstruction method for segmented helical computed tomography.

Recently, to easily extend the helical field-of-view (FOV), the segmented helical computed tomography (SHCT) method was proposed, as well as the corresponding generalized backprojection filtration (G-BPF) type algorithm. Similar to the geometric relationship between helical and circular CT, SHCT just becomes full-scan multiple source-translation CT (F-mSTCT) when the pitch is zero and the number of scan cycles is one. The strategy of G-BPF follows the idea of the generalized Feldkamp approximate cone-beam algorithm for helical CT, i.e., using the F-mSTCT cone-beam BPF algorithm to approximately perform reconstruction for SHCT. The image quality is limited by the pitch size, which implies that satisfactory quality could only be obtained under the conditions of small pitches. To extend the analytical reconstruction for SHCT, an effective single-slice rebinning (SSRB) method for SHCT is investigated here. Transforming the SHCT cone-beam reconstruction into the virtual F-mSTCT fan-beam stack reconstruction task with low computational complexity, and then some techniques are developed to address the challenges involved. By using the basic BPF reconstruction with derivating along the detector (D-BPF), our experiments demonstrate that SSRB has fewer interlayer artifacts, higher z-resolution, more uniform in-plane resolution, and higher reconstruction efficiency compared to G-BPF. SSRB could promote the effective application of deep learning in SHCT reconstruction.

SHCT: segmented helical computed tomography based on multiple slant source-translation.

Micro-computed tomography (Micro-CT) is inevitably required to inspect long large objects with high resolution. It is well known that helical CT solves the so-called "long object" problem, but it requires that the measured object be strictly located in the lateral field of view (FOV). Therefore, developing a novel scanning method to extend the FOV in both the lateral and axial directions (i.e., the large helical FOV) is necessary. Recently, due to the application of linearly distributed source arrays and the characteristics of easy extension of the FOV and engineering implementation, straight-line scanning systems have attracted much attention. In this paper, we propose a segmented helical computed tomography (SHCT) based on multiple slant source-translation. SHCT can readily extend the helical FOV by adjusting the source slant translation (SST) length, pitch (or elevation of the SST trajectory), and number of scanning circles. In SHCT, each projection view is truncated laterally and axially, but the projection data set within the cylindrical FOV region is complete. To ensure reconstruction efficiency and avoid the lateral truncation, we propose a generalized backprojection-filtration (G-BPF) algorithm for SHCT approximate reconstruction. Experimental results verify the effectiveness of the proposed SHCT methods for imaging large and long objects. As the pitch decreases, the proposed SHCT methods can reconstruct competitive, high-quality volumes.

Analytical reconstructions of full-scan multiple source-translation computed tomography under large field of views.

This paper is to investigate the high-quality analytical reconstructions of multiple source-translation computed tomography (mSTCT) under an extended field of view (FOV). Under the larger FOVs, the previously proposed backprojection filtration (BPF) algorithms for mSTCT, including D-BPF and S-BPF (their differences are different derivate directions along the detector and source, respectively), make some errors and artifacts in the reconstructed images due to a backprojection weighting factor and the half-scan mode, which deviates from the intention of mSTCT imaging. In this paper, to achieve reconstruction with as little error as possible under the extremely extended FOV, we combine the full-scan mSTCT (F-mSTCT) geometry with the previous BPF algorithms to study the performance and derive a suitable redundancy-weighted function for F-mSTCT. The experimental results indicate FS-BPF can get high-quality, stable images under the extremely extended FOV of imaging a large object, though it requires more projections than FD-BPF. Finally, for different practical requirements in extending FOV imaging, we give suggestions on algorithm selection.

Multivariate and multi-interface insights into carbon and energy recovery and conversion characteristics of hydrothermal carbonization of biomass waste from duck farm.

High lipid, high nitrogen duck manure (DM) with high lipid, high lignocellulosic litter materials (LM) are the main wet biomass wastes from duck farms and both are naturally abundant carbon resources. The synthesis of duck farming biomass waste into carbon-rich materials for high value utilization by hydrothermal carbonization (HTC), which can directly treat wet biomass, has not been investigated. In this study, the physicochemical properties of hydrochar derived from co-HTC of DM and LM and its carbon and energy recovery patterns were systematically investigated under multivariate conditions of raw materials ratios, solids contents, temperatures and residence times. The application of synchrotron-based near-edge X-ray adsorption fine structure technique (C K-edge NEXAFS) combined with gas chromatography-mass spectrometry (GC-MS) to the hydrochar and hydrothermal liquid, respectively. At multiple interfaces provided an in-depth analysis of the important material transformations of the co-HTC process and the structure of the hydrochar. Extending residence time (180 min) and increasing LM ratio (M@4%) in co-HTC reaction of DM and LM is beneficial to achieve hydrochar containing higher carbon content (44.84%) at lower reaction temperatures (180 °C). The heating value (HHV) of the hydrochar ranges between 17.12 and 25.05 MJ/kg. The carbon recovery rate of the co-HTC of DM and LM all exceeded 55% and was more closely related to the carbon content of the hydrochar than to its yield. Additionally, the model ERR=0.97±0.01CRR+2.40±0.71 (R2 = 0.99, P < 0.01) was developed to predict energy recovery rate (ERR) based on carbon recovery rate (CRR). Esters were an important intermediate during co-HTC of DM and LM, and the derived hydrochar consisted of a wide range of polycyclic aromatic hydrocarbons, alkanes and N-aromatic heterocycles as well as polyfuran, pyrrole and pyridine structures.

A Method for Obtaining 3D Point Cloud Data by Combining 2D Image Segmentation and Depth Information of Pigs.

This paper proposes a method for automatic pig detection and segmentation using RGB-D data for precision livestock farming. The proposed method combines the enhanced YOLOv5s model with the Res2Net bottleneck structure, resulting in improved fine-grained feature extraction and ultimately enhancing the precision of pig detection and segmentation in 2D images. Additionally, the method facilitates the acquisition of 3D point cloud data of pigs in a simpler and more efficient way by using the pig mask obtained in 2D detection and segmentation and combining it with depth information. To evaluate the effectiveness of the proposed method, two datasets were constructed. The first dataset consists of 5400 images captured in various pig pens under diverse lighting conditions, while the second dataset was obtained from the UK. The experimental results demonstrated that the improved YOLOv5s_Res2Net achieved a mAP@0.5:0.95 of 89.6% and 84.8% for both pig detection and segmentation tasks on our dataset, while achieving a mAP@0.5:0.95 of 93.4% and 89.4% on the Edinburgh pig behaviour dataset. This approach provides valuable insights for improving pig management, conducting welfare assessments, and estimating weight accurately.

Single-atom catalysts: promotors of highly sensitive and selective sensors.

Sensors, the underlying technology that supports the Internet of Things, are undergoing multi-disciplinary integration development to constantly improve the efficiency of human production and life. Simultaneously, the application scenarios in emerging fields such as medical diagnosis, environmental monitoring and industrial safety put forward higher requirements for sensing capabilities. Over the last decade, single-atom catalysts (SACs) have attracted tremendous attention in fields such as environment and energy due to their high atom utilization efficiencies, controllable active sites, tailorable coordination environments and structural/chemical stability. These extraordinary characteristics extend the sensitivity and selectivity of sensors beyond their current limitations. Here, we start with the working principles of SAC-based sensors, and summarize the relationship between sensor performance and intrinsic properties of SACs, followed by an overview of the design strategy development. We then review the recent advances in SAC-based sensors in different fields and highlight the future opportunities and challenges in their exciting applications.

Bandgap Engineering and Oxygen Vacancy Defect Electroactivity Inhibition in Highly Crystalline N-Alloyed Ga2O3 Films through Plasma-Enhanced Technology.

Previous research has shown that the hybridization of N 2p and O 2p orbitals effectively suppresses the electrical activity of oxygen vacancies in oxide semiconductors. However, achieving N-alloyed Ga2O3 films, known as GaON, poses a significant challenge due to nitrogen's limited solubility in the material. In this study, a new method utilizing plasma-enhanced chemical vapor deposition with high-energy nitrogen plasma was explored to enhance the nitrogen solubility in the material. By adjusting the N2 and O2 carrier gas ratio, we could tune the thin film's bandgap from 4.64 to 3.25 eV, leading to a reduction in the oxygen vacancy density from 32.89% to 19.87%. GaON-based photodetectors exhibited superior performance compared to that of Ga2O3-based devices, with a lower dark current and a faster photoresponse speed. This investigation presents an innovative approach to achieving high-performance devices based on Ga2O3.

Comparative transcriptome sequencing analysis to postulate the scheme of regulated leaf coloration in Perilla frutescens.

Perilla as herb, ornamental, oil and edible plant is widely used in East Asia. Until now, the mechanism of regulated leaf coloration is still unclear. In this study, four different kinds of leaf colors were used to measure pigment contents and do transcriptome sequence to postulate the mechanism of leaf coloration. The measurements of chlorophyll, carotenoid, flavonoid, and anthocyanin showed that higher contents of all the aforementioned four pigments were in full purple leaf 'M357', and they may be determined front and back leaf color formation with purple. Meanwhile, the content of anthocyanin was controlled back leaf coloration. The chromatic aberration analysis and correlative analysis between different pigments and L*a*b* values analysis also suggested front and back leaf color change was correlated with the above four pigments. The genes involved in leaf coloration were identified through transcriptome sequence. The expression levels of chlorophyll synthesis and degradation related genes, carotenoid synthesis related genes and anthocyanin synthesis genes showed up-/down-regulated expression in different color leaves and were consistent of accumulation of these pigments. It was suggested that they were the candidate genes regulated perilla leaf color formation, and genes including F3'H, F3H, F3',5'H, DFR, and ANS are probably important for regulating both front and back leaf purple formation. Transcription factors involved in anthocyanin accumulation, and regulating leaf coloration were also identified. Finally, the probable scheme of regulated both full green and full purple leaf coloration and back leaf coloration was postulated.

Integrating machine learning with linguistic features: A universal method for extraction and normalization of temporal expressions in Chinese texts.

BACKGROUND AND OBJECTIVE: With the rapid development of information dissemination technology, the amount of events information contained in massive texts now far exceeds the intuitive cognition of humans, and it is hard to understand the progress of events in order of time. Temporal information runs through the whole process of beginning, proceeding, and ending of events, and plays an important role in many natural language processing applications, such as information extraction, question answering, and text summary. Accurately extracting temporal information from Chinese texts and automatically mapping the temporal expressions in natural language to the time axis are crucial to understanding the development of events and dynamic changes in them. METHODS: This study proposes a method integrating machine learning with linguistic features (IMLLF) for extraction and normalization of temporal expressions in Chinese texts to achieve the above objectives. Linguistic features are constructed by analyzing the expression rules of temporal information, and are combined with machine learning to map the natural language form of time onto a one-dimensional timeline. The web text dataset we build is divided into five parts for five-fold cross-validation, to compare the influence of different combinations of linguistic features and different methods. In the open medical dialog dataset, based on the training model obtained from the web text dataset, 200 disease descriptions are randomly selected each time for three rounds of experiments. RESULTS: The F1 of multi-feature fusion is 95.2%, which is better than the single-feature and double-feature combination. The results of experiments showed that the proposed IMLLF method can improve the accuracy of recognition of temporal information in Chinese to a greater extent than classical methods, with an F1-score of over 95% on the web text dataset and medical conversation dataset. In terms of the normalization of time expressions, the accuracy of the IMLLF method is higher than 93%. CONCLUSIONS: IMLLF has better results in extracting and normalizing time expressions on the web text dataset and the medical conversation dataset, which verifies the universality of IMLLF to identify and quantify temporal information. IMLLF method can accurately map the time information to the time axis, which is convenient for doctors to intuitively see when and what happened to the patient, and helps to make better medical decisions.

Correlation of 3'-phosphoadenosine-5'-phosphosulfate synthase 1 (PAPSS1) expression with clinical parameters and prognosis in esophageal squamous cell carcinoma.

BACKGROUND: In recent years, 3'-phosphoadenosine-5'-phosphosulfate synthase 1 (PAPSS1) has been found to be highly expressed in some cancers and significantly associated with prognosis. Nevertheless, the role of PAPSS1 in esophageal squamous cell carcinoma (ESCC) is poorly understood. METHODS: In this study, PAPSS1 expression in ESCC samples was researched through real-time quantitative polymerase chain reaction (qPCR), immunohistochemistry (IHC), and western blot (WB) techniques. siRNA technology was then used to inhibit PAPSS1 expression in ESCC cells, and cytologic tests were conducted to research gene affection on cell apoptosis, proliferation, and migration. Then, the expression of Bcl2, Ki67, and Snail was detected using qPCR and WB tests. These experimental data were analyzed by GraphPad software, where the P-value<0.05 was statistically significant. RESULTS: The results showed that PAPSS1 expression level in ESCC tissues was higher than in the adjacent tissues. The data also showed that PAPSS1 was significantly correlated with N stage, and that the patients with high expressions had longer survival time. After transfection for 48 hours, the cell apoptosis rate of siRNA-PAPSS1 transfected groups decreased significantly, whereas the cell proliferation rate and migration ability increased relative to the control. At the same time, the expression levels of Bcl2, Ki67 and Snail were all upregulated by siRNA-PAPSS1. PAPSS1, however, was suppressed. CONCLUSIONS: PAPSS1 may be an ESCC suppressor gene, and its specific molecular mechanism in ESCC needs to be further studied.