Bamboo vinegar regulates the phytoremediation efficiency of Perilla frutescens (L.) Britt. by reducing membrane lipid damage and increasing cadmium retention.

The gap between serious soil heavy metals pollution and inefficient soil remediation threatens human health. This study proposed a method to improve the phytoremediation efficiency using bamboo vinegar (BV) solution and the potential mechanism was discussed. The results demonstrated that the application of BV increases the content of cadmium (Cd) in vacuole and cell wall hemicellulose 2 in leaves of Perilla frutescens. Simultaneously, it enhanced enzyme activities of superoxide dismutase and catalase in leaves. Therefore, this process alleviated the damage of Cd to functional tissues of Perilla frutescens, thus improving the tolerance of plants to Cd. Moreover, the BV application reduced the Cd content bound by root cell wall pectin fractions and insoluble phosphate, subsequently improving the ability of oxalic acids to carry Cd to the aerial parts. Consequently, the aerial parts obtained a larger amount of Cd enrichment. Overall, the Transfer Factor of Cd from roots to stems and enrichment of Cd in Perilla frutescens were maximally increased by 57.70 % and 54.03 % with the application of 50-fold and 300-fold diluted BV under 2 mg·L-1 Cd stress, respectively. The results can provide a theoretical basis for the promotion of phytoremediation of Cd-contaminated soil treatment technology.

Deep learning for MRI lesion segmentation in rectal cancer.

Rectal cancer (RC) is a globally prevalent malignant tumor, presenting significant challenges in its management and treatment. Currently, magnetic resonance imaging (MRI) offers superior soft tissue contrast and radiation-free effects for RC patients, making it the most widely used and effective detection method. In early screening, radiologists rely on patients' medical radiology characteristics and their extensive clinical experience for diagnosis. However, diagnostic accuracy may be hindered by factors such as limited expertise, visual fatigue, and image clarity issues, resulting in misdiagnosis or missed diagnosis. Moreover, the distribution of surrounding organs in RC is extensive with some organs having similar shapes to the tumor but unclear boundaries; these complexities greatly impede doctors' ability to diagnose RC accurately. With recent advancements in artificial intelligence, machine learning techniques like deep learning (DL) have demonstrated immense potential and broad prospects in medical image analysis. The emergence of this approach has significantly enhanced research capabilities in medical image classification, detection, and segmentation fields with particular emphasis on medical image segmentation. This review aims to discuss the developmental process of DL segmentation algorithms along with their application progress in lesion segmentation from MRI images of RC to provide theoretical guidance and support for further advancements in this field.

Global transboundary transmission path and risk of Mpox revealed with Least Cost Path model.

OBJECTIVES: The recent surge of Mpox outbreaks in multiple countries has garnered global attention. As of July 12, 2023, there have been 88,288 reported cases of Mpox worldwide. Although genetic variation was not found to be the cause of the epidemic outbreak, the reasons for its rapid spread remain unclear. METHODS: Using the niche method, this study identified high-risk regions for Mpox and determined that human factors are the primary contributors to global risks. To further investigate, a travel network resistance surface was created based on various modes of transportation and was combined with sea, airline, highway, and railway routes to construct the least cost path for human travel networks in different risk areas. RESULTS: The results indicated that high-risk regions for Mpox are mainly concentrated in Europe and the United States, with large risk ranges and high-risk values. The least cost path revealed three primary transmission paths rely on developed transportation networks, including internal transmission in North America, Europe-Africa, and Europe-Asia-Africa. These findings suggest that human activities, facilitated by developed travel networks, remain the main contributing factor to the spread. CONCLUSIONS: In summary, based on the Mpox epidemic report, this study conducted risk prediction and driving factor analysis on Mpox. The research results indicate that human use of transportation for long-distance activities is a key factor leading to the rapid spread of the virus. Subsequently, we focused on studying the global transmission pathways of Mpox and revealed several transmission pathways with high global population migration rates by constructing the LCPs between different high-risk areas. This study also emphasizes the importance of applying early monitoring data of Mpox to model risk prediction in controlling emerging infectious diseases, providing a new perspective for controlling Mpox and similar diseases.

A rapid and sensitive fluorescent chromatography with cloud system for MPXV point-of-care diagnosis.

Monkeypox (mpox) is spreading around the world, and its rapid diagnosis is of great significance. In the present study, a rapid and sensitive fluorescent chromatography assisted with cloud system was developed for point-of-care diagnosis of mpox. To screen high affinity antibodies, nanoparticle antigen AaLS-A29 was generated by conjugating A29 onto scaffold AaLS. Immunization with AaLS-A29 induced significantly higher antibody titers and monoclonal antibodies were generated with the immunized mice. A pair of monoclonal antibodies, MXV 14 and MXV 15, were selected for fluorescence chromatography development. The Time-Resolved Fluorescence Immunoassay (TRFIA) was used to develop the chromatography assay. After optimization of the label and concentration of antibodies, a sensitive TRFIA assay with detection limit of 20 pg/mL and good repeatability was developed. The detection of the surrogate Vaccinia virus (VACA) strain Tian Tan showed that the TRFIA assay was more sensitive than the SYBR green I based quantitative PCR. In real samples, the detection result of this assay were highly consistent with the judgement of Quantitative Real-Time PCR (Concordance Rate = 90.48%) as well as the clinical diagnosis (Kappa Value = 0.844, P < 0.001). By combining the portable detection and online cloud system, the detection results could be uploaded and shared, making this detection system an ideal system for point-of-care diagnosis of mpox both in field laboratory and outbreak investigation.

Brown planthopper infestation on rice reduces plant susceptibility to Meloidogyne graminicola by reducing root sugar allocation.

Plants are simultaneously attacked by different pests that rely on sugars uptake from plants. An understanding of the role of plant sugar allocation in these multipartite interactions is limited. Here, we characterized the expression patterns of sucrose transporter genes and evaluated the impact of targeted transporter gene mutants and brown planthopper (BPH) phloem-feeding and oviposition on root sugar allocation and BPH-reduced rice susceptibility to Meloidogyne graminicola. We found that the sugar transporter genes OsSUT1 and OsSUT2 are induced at BPH oviposition sites. OsSUT2 mutants showed a higher resistance to gravid BPH than to nymph BPH, and this was correlated with callose deposition, as reflected in a different effect on M. graminicola infection. BPH phloem-feeding caused inhibition of callose deposition that was counteracted by BPH oviposition. Meanwhile, this pivotal role of sugar allocation in BPH-reduced rice susceptibility to M. graminicola was validated on rice cultivar RHT harbouring BPH resistance genes Bph3 and Bph17. In conclusion, we demonstrated that rice susceptibility to M. graminicola is regulated by BPH phloem-feeding and oviposition on rice through differences in plant sugar allocation.

Rapid and highly potent humoral responses to mpox nanovaccine candidates adjuvanted by thermostable scaffolds.

Monkeypox (mpox) is a zoonotic disease caused by monkeypox virus (MPXV) of the orthopoxvirus genus. The emergence and global spread of mpox in 2022 was declared as a public health emergency by World Health Organization. This mpox pandemic alarmed us that mpox still threaten global public health. Live vaccines could be used for immunization for this disease with side effects. New alternative vaccines are urgently needed for this re-emerging disease. Specific antibody responses play key roles for protection against MPXV, therefore, vaccines that induce high humoral immunity will be ideal candidates. In the present study, we developed thermostable nanovaccine candidates for mpox by conjugating MPXV antigens with thermostable nanoscafolds. Three MPXV protective antigens, L1, A29, and A33, and the thermostable Aquafex aeolicus lumazine synthase (AaLS), were expressed in E. coli and purified by Ni-NTA methods. The nanovaccines were generated by conjugation of the antigens with AaLS. Thermal stability test results showed that the nanovaccines remained unchanged after one week storage under 37℃ and only partial degradation under 60℃, indicating high thermostability. Very interesting, one dose immunization with the nanovaccine could induce high potent antibody responses, and two dose induced 2-month high titers of antibodes. In vitro virus neutralization test showed that nanovaccine candidates induced significantly higher levels of neutralization antibodies than monomers. These results indicated that the AaLS conjugation nanovaccines of MPXV antigens are highly thermostable in terms of storage and antigenic, being good alternative vaccine candidates for this re-emerging disease.

Identification of neuropeptides and their G protein-coupled receptors in the predatory stink bug, Arma custos (Hemiptera: Pentatomidae).

The predatory stink bug Arma custos has been selected as an effective biological control agent and has been successfully massly bred and released into fields for the control of a diverse insect pests. As a zoophytophagous generalist, A. custos relies on a complex neuropeptide signaling system to prey on distinct food and adapt to different environments. However, information about neuropeptide signaling genes in A. custos has not been reported to date. In the present study, a total of 57 neuropeptide precursor transcripts and 41 potential neuropeptide G protein-coupled receptor (GPCR) transcripts were found mainly using our sequenced transcriptome data. Furthermore, a number of neuropeptides and their GPCR receptors that were enriched in guts and salivary glands of A. custos were identified, which might play critical roles in feeding and digestion. Our study provides basic information for an in-depth understanding of biological and ecological characteristics of the predatory bug and would aid in the development of better pest management strategies based on the effective utilization and protection of beneficial natural enemies.

Spatial risk of Haemaphysalis longicornis borne Dabieshan tick virus (DBTV) in China.

The uncertainty and unknowability of emerging infectious diseases have caused many major public health and security incidents in recent years. As a new tick-borne disease, Dabieshan tick virus (DBTV) necessitate systematic epidemiological and spatial distribution analysis. In this study, tick samples from Liaoning Province were collected and used to evaluate distribution of DBTV in ticks. Outbreak points of DBTV and the records of the vector Haemaphysalis longicornis in China were collected and used to establish a prediction model using niche model combined with environmental factors. We found that H. longicornis and DBTV were widely distributed in Liaoning Province. The risk analysis results showed that the DBTV in the eastern provinces of China has a high risk, and the risk is greatly influenced by elevation, land cover, and meteorological factors. The risk geographical area predicted by the model is significantly larger than the detected positive areas, indicating that the etiological survey is seriously insufficient. This study provided molecular and important epidemiological evidence for etiological ecology of DBTV. The predicted high-risk areas indicated the insufficient monitoring and risk evaluation and the necessity of future monitoring and control work.

Rare presentation of esophageal squamous cell carcinoma with rectal metastasis: A case report.

Esophageal cancer is usually diagnosed at an advanced stage, resulting in poor survival. The common sites of distant metastasis include lung, liver and bones. The present study reports a rare case of esophageal squamous cell carcinoma (SCC) with rectal metastasis. A 65-year-old man was diagnosed with middle thoracic esophageal SCC with multiple lymph node metastasis. The patient achieved good response after chemoradiotherapy and adjuvant chemotherapy. During following up, the computed tomography and magnetic resonance scans showed a mass in front of the rectum with intact mucosa. Biopsies were performed and histopathological findings showed SCC, consistent with metastasis from primary esophageal SCC. The patient subsequently received palliative chemoradiotherapy to the rectal tumour and survived for 5 months. To the best of our knowledge, the present case is the first report of metastatic rectal SCC from the esophagus. It is important to take a biopsy of this unexpected lesion for histological analysis, which can help to discriminate metastatic from primary cancer. The goal of treatment is palliative therapy to improve quality of life and survival for this metastatic disease.

Risk transboundary transmission areas and driving factors of brucellosis along the borders between China and Mongolia.

OBJECTIVE: Brucellosis is a common and neglected zoonotic infectious disease worldwide caused by Brucella. However, transboundary transmissions among countries, particularly those with high incidences, are seldom investigated. In the present study, by taking China and Mongolia as examples, we aim to identify transboundary transmission risk and driving factors of brucellosis along borders. METHODS: 167 brucellosis outbreak locations along the border between China and Mongolia were collected. Wildlife distribution and cross-border activities were mapped. Maximum entropy approach modeling was conducted to predict the potential risk of prevalence of brucellosis with meteorological factors, geographical environment, economic development, living habits et al. The accuracy of the models was assessed by the area under the receiver operating characteristic (ROC) curve (AUC), Kappa test, and correctly classified instances (CCI). RESULTS: The spatial model performed excellent predictive performance with the predictor variables of soils, pastures, goat density, mean precipitation of the wettest month, temperature seasonality, and population density, which with the contribution and permutation important in 27.2 %, 31.9; 23.3 %, 6.8; 18.0 %, 17.2; 11.2 %, 18.1; 10. 3 %, 15.2; 10.0 %, 10.8. The calculated AUC, SD, Kappa, and CCI are 0.870, 0.001, 0.882, and 0.883, respectively. The distribution map of brucellosis showed high-risk areas along the borders. CONCLUSIONS: Our study identified high-risk areas and the driving effect of brucellosis along the borders between China and Mongolia. Moreover, there is the possibility of cross-border wildlife activities in high-risk areas, which increases the risk of cross-border brucellosis transmission. The funding provides clues for cooperative prevention and control of brucellosis by reducing transboundary transmission.

Transcriptome analysis reveals salivary gland-specific neuropeptide signaling genes in the predatory stink bug, Picromerus lewisi.

Predatory stink bugs derive from phytophagous stink bugs and evolved enhanced predation skills. Neuropeptides are a diverse class of ancient signaling molecules that regulate physiological processes and behavior in animals, including stink bugs. Neuropeptide evolution might be important for the development of predation because neuropeptides can be converted to venoms that impact prey. However, information on neuropeptide signaling genes in predatory stink bugs is lacking. In the present study, neuropeptide signaling genes of Picromerus lewisi, an important predatory stink bug and an effective biological agent, were comprehensively identified by transcriptome analysis, with a total of 59 neuropeptide precursor genes and 58 potential neuropeptide receptor genes found. In addition, several neuropeptides and their receptors enriched in salivary glands of P. lewisi were identified. The present study and subsequent functional research contribute to an in-depth understanding of the biology and behavior of the predatory bugs and can provide basic information for the development of better pest management strategies, possibly including neuropeptide receptors as insecticide targets and salivary gland derived venom toxins as novel killing moleculars.

Identification of metabolizing enzyme genes associated with xenobiotics and odorants in the predatory stink bug Arma custos based on transcriptome analysis.

The predatory stink bug, Arma custos, is a highly effective beneficial predator of crop pests. The lack of gene information related to xenobiotic detoxification and odorant degrading enzymes in the predator stink bugs to date has limited our ability for more in-depth studies of biological control. Hence, we conducted de novo assembly of the A. custos transcriptome from guts, antennae, and other tiussue samples of 5th instar larvae using Illumina sequencing technology. A total of 91, 50 and 23 genes of cytochrome P450 monooxygenases (CYPs), carboxyl/choline esterases (CCEs) and glutathione S-transferases (GSTs) genes were identified, respectively. Gene expansions of CYP3 and CYP4 clans and the hormone and pheromone processing CCE class were found in A. custos. Analysis of tissue-specific expression patterns showed that 37 CYPs, 14 CCEs and 8 GSTs were enriched in guts, and 6 CYPs, 5 CCEs and 2 GSTs were up-regulated in antennae, suggesting their potential roles on xenobiotics detoxification and ordorant degradation. Gene information data presented here could be useful for a deeper understanding of the ecology, physiology and behavior of this beneficial species and could be helpful to improve their bio-control efficiency.

Learning-based near-optimal tracking control for industrial processes with slow and fast modes.

This paper devotes to solving the optimal tracking control (OTC) problem of singular perturbation systems in industrial processes under the framework of reinforcement learning (RL) technology. The encountered challenges include the different time scales in system operations and an unknown slow process. The immeasurability of slow process states especially increases the difficulty of finding the optimal tracking controller. To overcome these challenges, a novel off-policy ridge RL method is developed after decomposing the singular perturbed systems using the singular perturbation (SP) theory and replacing unmeasured states using important mathematical manipulations. Theoretical analysis of approximate equivalence of the sum of solutions of subproblems to the solution of the OTC problem is presented. Finally, a mixed separation thickening process (MSTP) and a numerical example are used to verify the effectiveness.

Does Internet use connect smallholder farmers to a healthy diet? Evidence from rural China.

Introduction: Undernutrition and micronutrient malnutrition remain problems of significant magnitude among small-scale subsistence farmers, posing a serious threat to their health and well-being. Developing a healthy diet can effectively reduce this threat. Fortunately, the Internet can speed up the process. Methods: Based on survey data from 5,114 farm households in nine provinces in China, this study quantitatively assesses the impact of Internet use on the dietary quality of smallholder farmers using OLS regression models and PSM models. Results/Discussion: (1) Internet use can significantly contribute to dietary diversity and dietary rationality among smallholder farmers, thus optimizing their dietary structure. (2) Internet use significantly increased the average consumption amounts of milk and its products (2.9 g), fruits (21.5 g), eggs (7.5 g), and vegetables (27.1 g), while also decreasing the intake of salts (1.5 g) and oil (3.8 g). (3) The pull of internet use to improve diet quality is more significant for smallholder households with lower levels of education, older heads of households, and higher household incomes. (4) A possible mechanism is that Internet use increases household income and information access skills of rural residents, thus improving their dietary quality. In summary, governments should further promote Internet penetration in rural areas for health purposes.

FPGA-based burst-error performance analysis and optimization of regular and irregular SD-LDPC codes for 50G-PON and beyond.

We evaluate the burst-error performance of the regular low-density parity-check (LDPC) code and the irregular LDPC code that has been considered for ITU-T's 50G-PON standard via experimental measurements in FPGA. By using intra codeword interleaving and parity-check matrix rearrangement, we demonstrate that the BER performance can be improved under ∼44-ns-duration burst errors for 50-Gb/s upstream signals.

Optical convolutional neural network with atomic nonlinearity.

Due to their high degree of parallelism, fast processing speeds and low power consumption, analog optical functional elements offer interesting routes for realizing neuromorphic computer hardware. For instance, convolutional neural networks lend themselves to analog optical implementations by exploiting the Fourier-transform characteristics of suitable designed optical setups. However, the efficient implementation of optical nonlinearities for such neural networks still represents challenges. In this work, we report on the realization and characterization of a three-layer optical convolutional neural network where the linear part is based on a 4f-imaging system and the optical nonlinearity is realized via the absorption profile of a cesium atomic vapor cell. This system classifies the handwritten digital dataset MNIST with 83.96% accuracy, which agrees well with corresponding simulations. Our results thus demonstrate the viability of utilizing atomic nonlinearities in neural network architectures with low power consumption.

Prognostic nomogram and risk factors for predicting survival in patients with pT2N0M0 esophageal squamous carcinoma.

This study analyzed the impact of factors affecting overall survival in patients with pT2N0M0 esophageal squamous carcinoma (ESCC) and developed a nomogram to predict overall survival (OS). We reviewed the clinical data of 413 patients with pathological T2N0M0 ESCC after radical esophagectomy in two hospitals. Data from one institution was used as the training cohort. A nomogram was established using Cox proportional hazard regression for identifying the prognostic factors affecting for OS in ESCC patients. The area under the curve (AUC), calibration curves and decision curve analysis (DCA) were used to evaluate prognostic efficacy, which was validated in an independent validation cohort. In the training cohort (N = 304), the median OS was 69.33 months, and the 3-, 5- and 10-year OS rates were 76.80%, 67.00% and 56.90%, respectively. The median OS of the validation cohort (N = 109) was 73.50 months, and the 3-, 5- and 10-year OS rates were 77.00%, 67.80% and 55.60%, respectively. According to Cox univariate and multivariate analyses, sex, age, tumor length and the number of resected lymph nodes were identified as predictors of OS. We developed nomograms and performed internal and external validation. The time-dependent receiver operating characteristic (ROC) curve and area under the curve (AUC) value, calibration curve and decision curve analysis (DCA) showed good prediction ability of the nomogram. The developed nomogram can effectively predict OS after esophagectomy in patients with pT2N0M0 ESCC.

Targeting fatty acid synthase modulates sensitivity of hepatocellular carcinoma to sorafenib via ferroptosis.

BACKGROUND: Sorafenib resistance is a key impediment to successful treatment of patients with advanced hepatocellular carcinoma (HCC) and recent studies have reported reversal of drug resistance by targeting ferroptosis. The present study aimed to explore the association of fatty acid synthase (FASN) with sorafenib resistance via regulation of ferroptosis and provide a novel treatment strategy to overcome the sorafenib resistance of HCC patients. METHODS: Intracellular levels of lipid peroxides, glutathione, malondialdehyde, and Fe2+ were measured as indicators of ferroptosis status. Biological information analyses, immunofluorescence assays, western blot assays, and co-immunoprecipitation analyses were conducted to elucidate the functions of FASN in HCC. Both in vitro and in vivo studies were conducted to examine the antitumor effects of the combination of orlistat and sorafenib and CalcuSyn software was used to calculate the combination index. RESULTS: Solute carrier family 7 member 11 (SLC7A11) was found to play an important role in mediating sorafenib resistance. The up-regulation of FASN antagonize of SLC7A11-mediated ferroptosis and thereby promoted sorafenib resistance. Mechanistically, FASN enhanced sorafenib-induced ferroptosis resistance by binding to hypoxia-inducible factor 1-alpha (HIF1α), promoting HIF1α nuclear translocation, inhibiting ubiquitination and proteasomal degradation of HIF1α, and subsequently enhancing transcription of SLC7A11. Orlistat, an inhibitor of FASN, with sorafenib had significant synergistic antitumor effects and reversed sorafenib resistance both in vitro and in vivo. CONCLUSION: Targeting the FASN/HIF1α/SLC7A11 pathway resensitized HCC cells to sorafenib. The combination of orlistat and sorafenib had superior synergistic antitumor effects in sorafenib-resistant HCC cells.

A novel prognostic and therapeutic target biomarker based on complement-related gene signature in gastric cancer.

Background: Gastric cancer (GC) is one of the most prevalent cancer types that reduce human life expectancy. The current tumor-node-metastasis (TNM) staging system is inadequate in identifying higher or lower risk of GC patients because of tumor heterogeneity. Research shows that complement plays a dual role in the tumor development and progression of GC. Methods: We downloaded GC data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). A complement-related risk signature was constructed through bioinformatics analysis. Subsequently, the predictive ability of this signature was validated with GSE84437 dataset, and a nomogram integrating risk score and common clinical factors was established. Besides, we evaluated the association of risk score with the immune and stromal cell infiltration in TCGA. Furthermore, immunotherapy response prediction and drug susceptibility analysis were conducted to access the ability of the risk signature in predicting the therapeutic effect. Results: A complement-related gene (CRG) signature, based on six genes (SPLG, C9, ITIH1, ZFPM2, CD36, and SERPINE1), was established. In both the training and validation sets, the overall survival of GC patients in the high-risk group was lower than that of the low-risk group, and the nomogram to predict the 1-, 2-, and 3-year survival rates of GC patients was developed. In addition, CIBERSORT algorithm showed the high-risk patients had higher levels of immune cell infiltration than low-risk patients, and the ESTIMATE results implied that the high-risk group had more stromal component in tumor microenvironment. Besides, compared to the low-risk group, there were higher expressions of most immune checkpoint genes and HLA genes in the high-risk group, and the high-risk patients showed higher sensitivity to the chemotherapy and targeted drugs (axitinib, dasatinib, pazopanib, saracatinib, sunitinib and temsirolimus). Conclusions: The novel CRG signature may act as a reliable, efficient tool for prognostic prediction and treatment guidance in future clinical practice.

Patterns of care and prognostic evaluation for stage I-III upper esophageal squamous cell carcinoma: a population-based study.

Background: There is no strong evidence regarding the optimal treatment and specific prognosis prediction model for upper esophageal squamous cell carcinoma (UESCC). This study aimed to investigate the real-world treatment patterns and develop models to predict overall survival (OS) and esophageal cancer-specific survival (ECSS) in patients with stage I-III UESCC. Methods: Patients with T1-4N0-3M0 UESCC in the Surveillance, Epidemiology, and End Results (SEER) database were identified from 2010 to 2017, and randomized to a training cohort and a validation cohort. The effect of treatment patterns on survival were comprehensively analyzed. Nomograms were developed by incorporating independent prognostic factors analyzed by Cox regression in the training cohort and evaluated by the concordance index (C-index), receiver operating characteristic (ROC) curves, calibration curves, and decision curve analyses (DCA) in two cohorts. Results: A total of 677 patients were identified, including 452 in the training cohort and 225 in the validation cohort. Among all populations, 71.9% (487) received chemoradiotherapy without surgery, and chemoradiotherapy or/and surgery showed better survival than other treatments. However, surgery was rarely carried out for patients with stage II-III. T stage, N stage, surgery, chemotherapy, and radiotherapy were independent risks for both OS and ECSS, while age was also an independent risk for OS. The C-indexes for nomograms to predict OS (0.71 and 0.72) and ECSS (0.70 and 0.73) were greater than 7th AJCC staging system to predict OS (0.61 and 0.64) and ECSS (0.64 and 0.64) in both the training cohort and the validation cohort. Time-dependent ROC curves and DCA also suggested that nomograms performed consistently better than 7th AJCC staging system. The calibration curves demonstrated good consistency in predicting survival. Conclusions: Chemoradiotherapy was a major treatment with preferable survival for patients with stage I-III UESCC. We have firstly developed and validated prognostic nomograms in patients with stage I-III UESCC, which would play a supplementary role in the current staging system.