Precise, fast and comprehensive analysis of intact glycopeptides and modified glycans with pGlyco3.

Great advances have been made in mass spectrometric data interpretation for intact glycopeptide analysis. However, accurate identification of intact glycopeptides and modified saccharide units at the site-specific level and with fast speed remains challenging. Here, we present a glycan-first glycopeptide search engine, pGlyco3, to comprehensively analyze intact N- and O-glycopeptides, including glycopeptides with modified saccharide units. A glycan ion-indexing algorithm developed for glycan-first search makes pGlyco3 5-40 times faster than other glycoproteomic search engines without decreasing accuracy or sensitivity. By combining electron-based dissociation spectra, pGlyco3 integrates a dynamic programming-based algorithm termed pGlycoSite for site-specific glycan localization. Our evaluation shows that the site-specific glycan localization probabilities estimated by pGlycoSite are suitable to localize site-specific glycans. With pGlyco3, we confidently identified N-glycopeptides and O-mannose glycopeptides that were extensively modified by ammonia adducts in yeast samples. The freely available pGlyco3 is an accurate and flexible tool that can be used to identify glycopeptides and modified saccharide units.

Synthesis Strategies, Preparation Methods, and Applications of Chiral Metal-Organic Frameworks.

Chiral Metal-Organic Frameworks (CMOFs) is a kind of material with great application value in recent years. Formed by the coordination of metal ions or metal clusters with organic ligands. It has ordered and adjustable pores, multi-dimensional network structure, large specific surface area and excellent adsorption properties. This material structure combines the properties of metal-organic frameworks (MOFs) with the chiral properties of chiral molecules. It has great advantages in catalysis, adsorption, separation and other fields. Therefore, it has a wide range of applications in chemistry, biology, medicine and materials science. In this paper, various synthesis strategies and preparation methods of chiral metal-organic frameworks are reviewed from different perspectives, and the advantages of each method are analyzed. In addition, the applications of chiral metal-organic framework materials in enantiomer recognition and separation, circular polarization luminescence and asymmetric catalysis are systematically summarized, and the corresponding mechanisms are discussed. Finally, the challenges and prospects of the development of chiral metal-organic frame materials are analyzed in detail.

Preclinical Evaluation and a Pilot Clinical Positron Emission Tomography Imaging Study of [68Ga]Ga-FAPI-FUSCC-II.

Fibroblast activation protein (FAP), a type II integral membrane serine protease, is a promising target for tumor diagnosis and therapy. OncoFAP has been recently discovered for PET imaging procedures for various solid malignancies. In this study, we presented the development of manual radiolabeling procedures for the preparation of OncoFAP-based radiopharmaceuticals for cancer imaging. A novel series of [68Ga/177Lu]Ga/Lu-FAPI-FUSCC-I/II were produced with high radiochemical yields. [68Ga]Ga-FAPI-FUSCC-I/II and [177Lu]Lu-FAPI-FUSCC-I/II were stable in phosphate-buffered saline, fetal bovine serum, and human serum for at least 3 h. In vitro cellular uptake and blocking experiments implied that they had specificity to FAP. Additionally, the low nanomolar IC50 values of FAPI-FUSCC-II indicated that it had a high target affinity to FAP. The in vivo biodistribution and blocking study in mice bearing HT-1080-FAP tumors showed that both exhibited specific tumor uptake. [68Ga]Ga-FAPI-FUSCC-II showed a higher tumor uptake and a higher tumor/nontarget ratio than [68Ga]Ga-FAPI-FUSCC-I and [68Ga]Ga-FAPI-04. The results of ex vivo biodistribution were in accordance with the biodistribution results. Clinical [68Ga]Ga-FAPI-FUSCC-II-PET/CT imaging further demonstrated its favorable biodistribution and kinetics with elevated and reliable uptake by primary tumors (maximum standardized uptake value (SUVmax), 12.17 ± 6.67) and distant metastases (SUVmax, 9.24 ± 4.28). In summary, [68Ga]Ga-FAPI-FUSCC-II displayed increased tumor uptake and retention compared to [68Ga]Ga-FAPI-04, giving it potential as a promising tracer for the diagnostic imaging of malignant tumors with positive FAP expression.

Enantioseparation Membranes: Research Status, Challenges, and Trends.

The purity of enantiomers plays a critical role in human health and safety. Enantioseparation is an effective way and necessary process to obtain pure chiral compounds. Enantiomer membrane separation is a new chiral resolution technique, which has the potential for industrialization. This paper mainly summarizes the research status of enantioseparation membranes including membrane materials, preparation methods, factors affecting membrane properties, and separation mechanisms. In addition, the key problems and challenges to be solved in the research of enantioseparation membranes are analyzed. Last but not least, the future development trend of the chiral membrane is expected.

Enhanced antitumor immune responses via a new agent [131I]-labeled dual-target immunosuppressant.

Radionuclides theranostic are ideal "partners" for bispecific antibodies to explore the immune response of patients and synergistic treatment. A bispecific single-domain antibody-Fc fusion protein, KN046, exhibits a good treatment effect by binding to programmed cell death-ligand 1 (PD-L1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4). An ionizing-radiation stimulus mediated by a low-dose of [131I] may be used for immunopotentiation. In this study, we established [131I]-labeled KN046 as a novel radioimmunotherapy agent to treat malignant melanoma and explored the mechanism. METHODS: After intravenous injection of [131I]-KN046, SPECT/CT imaging was applied to identify candidate targets for KN046 immunotherapy. [18F]-FDG and [68 Ga]-NOTA-GZP (granzyme B-specific PET imaging agent) micro-PET/CT imaging was used to assess the immune response in vivo after [131I]-KN046 treatment. The synergistic treatment effect of [131I]-KN046 was evaluated by exploring the [131I]-based radionuclide-induced release of tumor immunogenicity-related antigens as well as the histology and survival of tumor-bearing mice after treatment. RESULTS: The constructed [131I]-KN046 exhibited high affinity and specificity for PD-L1/CTLA-4 immune targets and had excellent in vivo intratumoral retention capability so as to achieve good antitumor efficacy. More importantly, the combination of low-dose [131I] and KN046-enhanced immunosensitivity increased the immunotherapy response rates significantly. Exposure of tumor cells to [131I]-KN046 led to upregulated expression of MHC-I and Fas surface molecules and significant increases in the degree of T-cell activation and counts of tumor-infiltrating immunocytes. CONCLUSION: Use of low-dose [131I] combined with a dual-target immunosuppressant could be exploited to identify the subset of treatment responders but also exhibited great potential for enhancing antitumor immune responses.

PET imaging of PARP expression using 68Ga-labelled inhibitors.

PURPOSE: Imaging the PARP expression using 18F probes has been approved in clinical trials. Nevertheless, hepatobiliary clearance of both 18F probes hindered their application in monitoring abdominal lesions. Our novel 68Ga-labelled probes aim for fewer abdominal signals while ensuring PARP targeting by optimizing the pharmacokinetic properties of radioactive probes. METHODS: Three radioactive probes targeted PARP were designed, synthesized, and evaluated based on the PARP inhibitor Olaparib. These 68Ga-labelled radiotracers were assessed in vitro and in vivo. RESULTS: Precursors that did not lose binding affinity for PARP were designed, synthesized, and then labelled with 68Ga in high radiochemical purity (> 97%). The 68Ga-labelled radiotracers were stable. Due to the increased expression of PARP-1 in SK-OV-3 cells, the uptake of the three radiotracers by SK-OV-3 cells was significantly greater than that by A549 cells. PET/CT imaging of the SK-OV-3 models indicated that the tumor uptake of 68Ga-DOTA-Olaparib (0.5 h: 2.83 ± 0.55%ID/g; 1 h: 2.37 ± 0.64%ID/g) was significantly higher than that of the other 68Ga-labelled radiotracers. There was a significant difference in the T/M (tumor-to-muscle) ratios between the unblocked and blocked groups as calculated from the PET/CT images (4.07 ± 1.01 vs. 1.79 ± 0.45, P = 0.0238 < 0.05). Tumor autoradiography revealed high accumulation in tumor tissues, further confirming the above data. PARP-1 expression in the tumor was confirmed by immunochemistry. CONCLUSION: As the first 68Ga-labelled PARP inhibitor, 68Ga-DOTA-Olaparib displayed high stability and quick PARP imaging in a tumor model. This compound is thus a promising imaging agent that can be used in a personalized PARP inhibitor treatment regimen.

Association between nutrient patterns and hyperuricemia: mediation analysis involving obesity indicators in the NHANES.

BACKGROUND: Diet has long been hypothesized to play an important role in hyperuricemia, and weight gain is a factor that is strongly associated with the rise in serum urate. We aimed to clarify the mediating role of obesity in the relationship between diet and hyperuricemia and to determine whether a weight-loss diet is an effective way to prevent hyperuricemia. METHODS: This cross-sectional study analysed representative samples of United States (n = 20,081; NHANES 2007-2016) adults. Nutrient patterns were derived with two methods: principal component analysis (PCA) and reduced rank regression (RRR) with obesity. Logistic regression and multivariable linear regression were applied to analyse the association between nutrient patterns in obesity and hyperuricemia. Mediation analyses were used to determine whether four obesity indicators, including body mass index (BMI), waist circumference (WC), visceral adiposity index (VAI) and lipid accumulation product index (LAP), mediated the relationship between nutrient patterns and hyperuricemia. RESULTS: PCA revealed three nutrient patterns (including "Low energy diet", "Lower vitamin A, C, K pattern" and "Vitamin B group"), and only Vitamin B group had a total effect on hyperuricemia. RRR revealed one main nutrient pattern associated with obesity, which was characterized by High fat and low vitamin levels and was significantly associated with hyperuricemia. Mediation analysis showed that obesity mostly or even completely mediated the relationship between nutrient patterns and hyperuricemia, especially traditional obesity indicators, which played a key intermediary effect. The proportions of indirect effects for BMI and WC were as high as 53.34 and 59.69, respectively. CONCLUSIONS: Our findings suggest that the direct effect of diet on hyperuricemia is weak, and obesity plays a critical mediating role in the relationship between diet and hyperuricemia, which confirms that a weight-loss diet such as a "Low fat and high vitamin diet" may be useful in preventing hyperuricemia.

Prevalence, correlates, and trajectory of screen viewing among Chinese children in Changsha: a birth cohort study.

BACKGROUND: High screen viewing time has detrimental effects on children's health, development, and behavior developing. Children are being exposed to more and more media devices at an earlier age. This study was aimed to determine the amount of daily screen time and its variation and to assess potential factors of screen time by identifying the trajectory of screen time among children aged 1 to 5 years. METHOD: This study was based on a representative sample of Changsha young children from a cohort study during 2015-2020. The demographic information and children's screen viewing time were collected by parents or caregivers through face-to-face interviews. The Latent growth model was used to test the effects of outdoor play on screen viewing time at eight time points, meanwhile, unconditional and conditional models were examined sequentially. RESULT: After excluding respondents with missing key variables, we included 953 children in the final analysis. Children's outdoor play was slightly increased at 18 months and subsequently declined at 24-60 months, with a maximum duration of 2.96 h per day. Children's average screen time was increased at 18-36 months, and decreased at 42-54 months, with a slight increase at 60 months. The duration of media exposure peaked at 1.4 h/d at age of 36 months and 60 months. Standardized coefficients of the outdoor play at age of 12 months showed negative effects on the screen time in children, but with positive influence at age of 24, 36, and 42 months (P <  0.01). CONCLUSION: High proportions of young Chinese children in Changsha had more screen time than the AAP recommended according to our analysis. Significant predictors of screen time included pregnancy computer use, paternal educational level, and outdoor play in this study, however, further understanding of risk factors is needed to promote great public health efforts to reduce children's screen exposure.

Influence of Clones on Relationship between Natural Rubber and Size of Rubber Particles in Latex.

IAN873, Dongfang93114 and Reyan73397, created through vegetative propagation for their high yield and excellent cold resistance, are major clones planted in China. In this work, latexes with rubber particles of the same size from these clones are separated from fresh natural rubber latex, and corresponding rubber films are prepared from each latex. The structure and components of each film are measured. This indicates that the characteristics of the rubbers obtained from latexes with similar particle sizes show some resembling trends among different clones, while for specific samples, those characteristics vary depending on the clone. The molecular weight is generally highest in IAN873 and lowest in Reyan73397. Rubber chains in small rubber particles are longer, and large rubber particles show a wider molecular weight distribution. The gel content of every sample from Reyan73397 is lower than the other two clones. The nitrogen content increases with the size of rubber particles in all clones. The ester content of small rubber particles in IAN873 and Reyan73397 is almost zero. Large rubber particles have more branching points formed via esters. This study provides a new perspective on the influence of clones on the relationship between characteristics of natural rubber and the size of rubber particles in natural rubber latex.

pDeepXL: MS/MS Spectrum Prediction for Cross-Linked Peptide Pairs by Deep Learning.

In cross-linking mass spectrometry, the identification of cross-linked peptide pairs heavily relies on the ability of a database search engine to measure the similarities between experimental and theoretical MS/MS spectra. However, the lack of accurate ion intensities in theoretical spectra impairs the performance of search engines, in particular, on proteome scales. Here we introduce pDeepXL, a deep neural network to predict MS/MS spectra of cross-linked peptide pairs. To train pDeepXL, we used the transfer-learning technique because it facilitated the training with limited benchmark data of cross-linked peptide pairs. Test results on more than ten data sets showed that pDeepXL accurately predicted the spectra of both noncleavable DSS/BS3/Leiker cross-linked peptide pairs (>80% of predicted spectra have Pearson's r values higher than 0.9) and cleavable DSSO/DSBU cross-linked peptide pairs (>75% of predicted spectra have Pearson's r values higher than 0.9). pDeepXL also achieved the accurate prediction on unseen data sets using an online fine-tuning technique. Lastly, integrating pDeepXL into a database search engine increased the number of identified cross-link spectra by 18% on average.

A core-shell Au@Cu2-xSe heterogeneous metal nanocomposite for photoacoustic and computed tomography dual-imaging-guided photothermal boosted chemodynamic therapy.

Chemodynamic therapy (CDT) has aroused extensive attention for conquering cancers because of its high specificity and low invasiveness. Quick generation of hydroxyl radicals (·OH) during CDT could induce more irreparable damage to cancer cells. The generation rate of ·OH could be magnified via the selection of suitable nanocatalysts or under the assistance of exogenous thermal energy from photothermal therapy (PTT). Here, we construct a kind of monodisperse core-shell Au@Cu2-xSe heterogeneous metal nanoparticles (NPs) for PTT boosted CDT synergistic therapy. Due to the localized surface plasmon resonance (LSPR) coupling effect in the core-shell structure, the photothermal conversion efficiency of Au@Cu2-xSe NPs is up to 56.6%. The in situ generated heat from photothermal can then accelerate the Fenton-like reaction at Cu+ sites to produce abundant ·OH, which will induce apoptotic cell death by attacking DNA, contributing to a heat-boosted CDT. Both in vitro and in vivo results showed that after this synergistic therapy, tumors could be remarkably suppressed. Guided by photoacoustic (PA) and computed tomography (CT) imaging, the therapeutic effects were more specified. Our results revealed that PA and CT dual-imaging-guided PTT boosted CDT synergistic therapy based on core-shell Au@Cu2-xSe NPs is an effective cancer treatment strategy.

Precision De Novo Peptide Sequencing Using Mirror Proteases of Ac-LysargiNase and Trypsin for Large-scale Proteomics.

De novo peptide sequencing for large-scale proteomics remains challenging because of the lack of full coverage of ion series in tandem mass spectra. We developed a mirror protease of trypsin, acetylated LysargiNase (Ac-LysargiNase), with superior activity and stability. The mirror spectrum pairs derived from the Ac-LysargiNase and trypsin treated samples can generate full b and y ion series, which provide mutual complementarity of each other, and allow us to develop a novel algorithm, pNovoM, for de novo sequencing. Using pNovoM to sequence peptides of purified proteins, the accuracy of the sequence was close to 100%. More importantly, from a large-scale yeast proteome sample digested with trypsin and Ac-LysargiNase individually, 48% of all tandem mass spectra formed mirror spectrum pairs, 97% of which contained full coverage of ion series, resulting in precision de novo sequencing of full-length peptides by pNovoM. This enabled pNovoM to successfully sequence 21,249 peptides from 3,753 proteins and interpreted 44-152% more spectra than pNovo+ and PEAKS at a 5% FDR at the spectrum level. Moreover, the mirror protease strategy had an obvious advantage in sequencing long peptides. We believe that the combination of mirror protease strategy and pNovoM will be an effective approach for precision de novo sequencing on both single proteins and proteome samples.

Chirality parameter sensing based on surface plasmon resonance D-type photonic crystal fiber sensors.

We report a method to sense a surrounding chiral drug based on D-type single-mode photonic crystal fiber (PCF) sensors in this paper. The electromagnetic theory of surface plasmon resonance on metal-chiral drug structure is derived. The wave equation containing constitutive relations of a chiral drug is given and integrated into the finite element method to compute the effective refractive index, confinement loss, and plasmon resonance wavelength for a D-type PCF sensor immersed in the chiral drug. The effects of the chirality parameter on resonance behaviors are displayed. The wavelength sensitivities of the chirality parameter for the sensor changing with different kinds of metal film layers, side-polished depth, and thickness of metal film layer are calculated. The wavelength sensitivity can reach a maximum of 17,580 nm/chirality as the refractive index and chirality parameter of the drug are 1.36 and 0.08, respectively. Furthermore, simultaneous dual-parameter detection of the chirality parameter and refractive index is realized by using two different D-type PCF sensors with gold and silver metal film layers, respectively. This study may provide sufficient guidelines to the field of biochemical sensing.

pNovo 3: precise de novo peptide sequencing using a learning-to-rank framework.

MOTIVATION: De novo peptide sequencing based on tandem mass spectrometry data is the key technology of shotgun proteomics for identifying peptides without any database and assembling unknown proteins. However, owing to the low ion coverage in tandem mass spectra, the order of certain consecutive amino acids cannot be determined if all of their supporting fragment ions are missing, which results in the low precision of de novo sequencing. RESULTS: In order to solve this problem, we developed pNovo 3, which used a learning-to-rank framework to distinguish similar peptide candidates for each spectrum. Three metrics for measuring the similarity between each experimental spectrum and its corresponding theoretical spectrum were used as important features, in which the theoretical spectra can be precisely predicted by the pDeep algorithm using deep learning. On seven benchmark datasets from six diverse species, pNovo 3 recalled 29-102% more correct spectra, and the precision was 11-89% higher than three other state-of-the-art de novo sequencing algorithms. Furthermore, compared with the newly developed DeepNovo, which also used the deep learning approach, pNovo 3 still identified 21-50% more spectra on the nine datasets used in the study of DeepNovo. In summary, the deep learning and learning-to-rank techniques implemented in pNovo 3 significantly improve the precision of de novo sequencing, and such machine learning framework is worth extending to other related research fields to distinguish the similar sequences. AVAILABILITY AND IMPLEMENTATION: pNovo 3 can be freely downloaded from http://pfind.ict.ac.cn/software/pNovo/index.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

WITHDRAWN: Characterization of heterogeneity of hypoxia with 18FMISO PET/CT, BOLD fMRI and immunohistochemistry in human breast tumor xenograft: initial study.

Ahead of Print article withdrawn by publisher.

pValid: Validation Beyond the Target-Decoy Approach for Peptide Identification in Shotgun Proteomics.

As the de facto validation method in mass spectrometry-based proteomics, the target-decoy approach determines a threshold to estimate the false discovery rate and then filters those identifications beyond the threshold. However, the incorrect identifications within the threshold are still unknown and further validation methods are needed. In this study, we characterized a framework of validation and investigated a number of common and novel validation methods. We first defined the accuracy of a validation method by its false-positive rate (FPR) and false-negative rate (FNR) and, further, proved that a validation method with lower FPR and FNR led to identifications with higher sensitivity and precision. Then we proposed a validation method named pValid that incorporated an open database search and a theoretical spectrum prediction strategy via a machine-learning technology. pValid was compared with four common validation methods as well as a synthetic peptide validation method. Tests on three benchmark data sets indicated that pValid had an FPR of 0.03% and an FNR of 1.79% on average, both superior to the other four common validation methods. Tests on a synthetic peptide data set also indicated that the FPR and FNR of pValid were better than those of the synthetic peptide validation method. Tests on a large-scale human proteome data set indicated that pValid successfully flagged the highest number of incorrect identifications among all five methods. Further considering its cost-effectiveness, pValid has the potential to be a feasible validation tool for peptide identification.

MS/MS Spectrum Prediction for Modified Peptides Using pDeep2 Trained by Transfer Learning.

In the past decade, tandem mass spectrometry (MS/MS)-based bottom-up proteomics has become the method of choice for analyzing post-translational modifications (PTMs) in complex mixtures. The key to the identification of the PTM-containing peptides and localization of the PTM-modified residues is to measure the similarities between the theoretical spectra and the experimental ones. An accurate prediction of the theoretical MS/MS spectra of the modified peptides will improve the similarity measurement. Here, we proposed the deep-learning-based pDeep2 model for PTMs. We used the transfer learning technique to train pDeep2, facilitating the training with a limited scale of benchmark PTM data. Using the public synthetic PTM data sets, including the synthetic phosphopeptides and 21 synthetic PTMs from ProteomeTools, we showed that the model trained by transfer learning was accurate (>80% Pearson correlation coefficients were higher than 0.9), and was significantly better than the models trained without transfer learning. We also showed that accurate prediction of the fragment ion intensities of the PTM neutral loss, for example, the phosphoric acid loss (-98 Da) of the phosphopeptide, will improve the discriminating power to distinguish the true phosphorylated residue from its adjacent candidate sites. pDeep2 is available at https://github.com/pFindStudio/pDeep/tree/master/pDeep2 .

pSite: Amino Acid Confidence Evaluation for Quality Control of De Novo Peptide Sequencing and Modification Site Localization.

MS-based de novo peptide sequencing has been improved remarkably with significant development of mass-spectrometry and computational approaches but still lacks quality-control methods. Here we proposed a novel algorithm pSite to evaluate the confidence of each amino acid rather than the full-length peptides obtained by de novo peptide sequencing. A semi-supervised learning approach was used to discriminate correct amino acids from random one; then, an expectation-maximization algorithm was used to adaptively control the false amino-acid rate (FAR). On three test data sets, pSite recalled 86% more amino acids on average than PEAKS at the FAR of 5%. pSite also performed superiorly on the modification site localization problem, which is essentially a special case of amino acid confidence evaluation. On three phosphopeptide data sets, at the false localization rate of 1%, the average recall of pSite was 91% while those of Ascore and phosphoRS were 64 and 63%, respectively. pSite covered 98% of Ascore and phosphoRS results and contributed 21% more phosphorylation sites. Further analyses show that the use of distinct fragmentation features in high-resolution MS/MS spectra, such as neutral loss ions, played an important role in improving the precision of pSite. In summary, the effective and universal model together with the extensive use of spectral information makes pSite an excellent quality control tool for both de novo peptide sequencing and modification site localization.

Modeling Protein Excited-state Structures from "Over-length" Chemical Cross-links.

Chemical cross-linking coupled with mass spectroscopy (CXMS) provides proximity information for the cross-linked residues and is used increasingly for modeling protein structures. However, experimentally identified cross-links are sometimes incompatible with the known structure of a protein, as the distance calculated between the cross-linked residues far exceeds the maximum length of the cross-linker. The discrepancies may persist even after eliminating potentially false cross-links and excluding intermolecular ones. Thus the "over-length" cross-links may arise from alternative excited-state conformation of the protein. Here we present a method and associated software DynaXL for visualizing the ensemble structures of multidomain proteins based on intramolecular cross-links identified by mass spectrometry with high confidence. Representing the cross-linkers and cross-linking reactions explicitly, we show that the protein excited-state structure can be modeled with as few as two over-length cross-links. We demonstrate the generality of our method with three systems: calmodulin, enzyme I, and glutamine-binding protein, and we show that these proteins alternate between different conformations for interacting with other proteins and ligands. Taken together, the over-length chemical cross-links contain valuable information about protein dynamics, and our findings here illustrate the relationship between dynamic domain movement and protein function.

Mapping native disulfide bonds at a proteome scale.

We developed a high-throughput mass spectrometry method, pLink-SS (http://pfind.ict.ac.cn/software/pLink/2014/pLink-SS.html), for precise identification of disulfide-linked peptides. Using pLink-SS, we mapped all native disulfide bonds of a monoclonal antibody and ten standard proteins. We performed disulfide proteome analyses and identified 199 disulfide bonds in Escherichia coli and 568 in proteins secreted by human endothelial cells. We discovered many regulatory disulfide bonds involving catalytic or metal-binding cysteine residues.