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Abstract The BP neural network optimized by the Adam algorithm was used to predict the defect formation energy of Al−P co‐doped ZnO systems with different concentrations of P replacing O under the presence of different concentrations of VZn. It was found that the easily formed AlZnPo‐1VZn, AlZnPO‐2VZn, and AlZn2PO‐1VZn systems. The first principles of density function were used to study the geometric, electronic, and optical properties of each system. The simulation results show that the bandgap values of the three systems have decreased relative to the intrinsic ZnO, among which AlZnPO‐1VZn and AlZnPO‐2VZn is still a p‐type conductive system, AlZnPO‐2VZn has the highest conductivity. From the analysis of reflectivity, absorption rate, and light transmittance, AlZn2PO‐1VZn has the most relatively excellent optical properties, followed by AlznPo‐2VZn.

Abstract Background Patients with disorders of consciousness (DoC) exhibit varied revival outcomes based on different etiologies and diagnoses, the mechanisms of which remain largely unknown. The fluctuating clinical presentations in DoC pose challenges in accurately assessing consciousness levels and prognoses, often leading to misdiagnoses. There is an urgent need for a deeper understanding of the physiological changes in DoC and the development of objective diagnostic and prognostic biomarkers to improve treatment guidance. Methods To explore biomarkers and understand the biological processes, we conducted a comprehensive untargeted metabolomic analysis on serum samples from 48 patients with DoC. Patients were categorized based on etiology (TBI vs. non-TBI), CRS-R scores, and prognosis. Advanced analytical techniques, including PCA and OPLS-DA models, were employed to identify differential metabolites. Results Our analysis revealed a distinct separation in metabolomic profiles among the different groups. The primary differential metabolites distinguishing patients with varying etiologies were predominantly phospholipids, with a notable decrease in glycerophospholipids observed in the TBI group. Patients with higher CRS-R scores exhibited a pattern of impaired carbohydrate metabolism coupled with enhanced lipid metabolism. Notably, serum concentrations of both LysoPE and PE were reduced in patients with improved outcomes, suggesting their potential as prognostic biomarkers. Conclusions Our study underscores the critical role of phospholipid metabolism in the brain’s metabolic alterations in patients with DoC. It identifies key biomarkers for diagnosis and prognosis, offering insights that could lead to novel therapeutic targets. These findings highlight the value of metabolomic profiling in understanding and potentially treating DoC.

Abstract Background Currently, noninvasive imaging techniques and circulating biomarkers are still insufficient to accurately assess carotid plaque stability, and an in-depth understanding of the molecular mechanisms that contribute to plaque instability is still lacking. Methods We established a clinical study cohort containing 182 patients with carotid artery stenosis. After screening, 39 stable and 49 unstable plaques were included in the discovery group, and quantitative proteomics analysis based on data independent acquisition was performed for these plaque samples. Additionally, 35 plaques were included in the validation group to validate the proteomics results by immunohistochemistry analysis. Results A total of 397 differentially expressed proteins were identified in stable and unstable plaques. These proteins are primarily involved in ferroptosis and lipid metabolism-related functions and pathways. Plaque validation results showed that ferroptosis- and lipid metabolism-related proteins had different expression trends in stable plaques versus unstable fibrous cap regions and lipid core regions. Ferroptosis- and lipid metabolism-related mechanisms in plaque stability were discussed. Conclusions Our results may provide a valuable strategy for revealing the mechanisms affecting plaque stability and will facilitate the discovery of specific biomarkers to broaden the therapeutic scope.

Abstract Objective Seizures are a common clinical presentation in patients with glioma and substantially impact patients' quality of life. Hyperhomocysteinemia is defined as abnormally high serum levels of homocysteine (Hcy) and is reportedly linked to susceptibility to various nervous system diseases. However, it remains unclear whether and how hyperhomocysteinemia and its associated genetic polymorphisms promote seizures in glioma patients. Methods We retrospectively reviewed all medical data from 127 patients with malignant gliomas, who underwent initial tumor resection by our team between July 2019 and June 2021 and had preoperative measurements of serum Hcy levels. According to whether they had at least one seizure before surgery, they were divided into the seizure and nonseizure groups. We also detected polymorphisms in the methylenetetrahydrofolate reductase (MTHFR) gene and measured intratumoral Hcy levels in these patients. Results Hyperhomocysteinemia was a susceptibility factor for preoperative seizures in glioma patients according to both univariate analyses (P

Abstract Introduction Medical management of disorders of consciousness (DoC) is a growing issue imposing a major burden on families and societies. Recovery rates vary widely among patients with DoC, and recovery predictions strongly influence decisions on medical care. However, the specific mechanisms underlying different etiologies, consciousness levels, and prognoses are still unclear. Methods We analyzed the comprehensive cerebrospinal fluid (CSF) metabolome through liquid chromatography‐mass spectrometry. Metabolomic analyses were used to identify the metabolic differences between patients with different etiologies, diagnoses, and prognoses. Results We found that the CSF levels of multiple acylcarnitines were lower in patients with traumatic DoC, suggesting mitochondrial function preservation in the CNS, which might contribute to the better consciousness outcomes of these patients. Metabolites related to glutamate and GABA metabolism were altered and showed a good ability to distinguish the patients in the minimally conscious state and the vegetative state. Moreover, we identified 8 phospholipids as potential biomarkers to predict the recovery of consciousness. Conclusions Our findings shed light on the differences in physiological activities underlying DoC with different etiologies and identified some potential biomarkers used for DoC diagnosis and prognosis.

The Brodmann area (BA)-based map is one of the most widely used cortical maps for studies of human brain functions and in clinical practice; however, the molecular architecture of BAs remains unknown. The present study provided a global multiregional proteomic map of the human cerebral cortex by analyzing 29 BAs. These 29 BAs were grouped into 6 clusters based on similarities in proteomic patterns: the motor and sensory cluster, vision cluster, auditory and Broca’s area cluster, Wernicke’s area cluster, cingulate cortex cluster, and heterogeneous function cluster. We identified 474 cluster-specific and 134 BA-specific signature proteins whose functions are closely associated with specialized functions and disease vulnerability of the corresponding cluster or BA. The findings of the present study could provide explanations for the functional connections between the anterior cingulate cortex and sensorimotor cortex and for anxiety-related function in the sensorimotor cortex. The brain transcriptome and proteome comparison indicates that they both could reflect the function of cerebral cortex, but show different characteristics. These proteomic data are publicly available at the Human Brain Proteome Atlas (www.brain-omics.com). Our results may enhance our understanding of the molecular basis of brain functions and provide an important resource to support human brain research.

More sensitive and specific non-invasive biomarkers are desired for early detection of cancer. Here, the authors show a protein signature in the urine that increases sensitivity for colorectal cancer detection when combined with fecal immunochemical tests and corrects diagnosis in some fecal immunochemical tests-negative patients.

Aim IgA nephropathy (IgAN) is one of the leading causes of end-stage renal disease (ESRD). Urine testing is a non-invasive way to track the biomarkers used for measuring renal injury. This study aimed to analyse urinary complement proteins during IgAN progression using quantitative proteomics. Methods In the discovery phase, we analysed 22 IgAN patients who were divided into three groups (IgAN 1-3) according to their estimated glomerular filtration rate (eGFR). Eight patients with primary membranous nephropathy (pMN) were used as controls. Isobaric tags for relative and absolute quantitation (iTRAQ) labelling, coupled with liquid chromatography-tandem mass spectrometry, was used to analyse global urinary protein expression. In the validation phase, western blotting and parallel reaction monitoring (PRM) were used to verify the iTRAQ results in an independent cohort (N = 64). Results In the discovery phase, 747 proteins were identified in the urine of IgAN and pMN patients. There were different urine protein profiles in IgAN and pMN patients, and the bioinformatics analysis revealed that the complement and coagulation pathways were most activated. We identified a total of 27 urinary complement proteins related to IgAN. The relative abundance of C3, the membrane attack complex (MAC), the complement regulatory proteins of the alternative pathway (AP), and MBL (mannose-binding lectin) and MASP1 (MBL associated serine protease 2) in the lectin pathway (LP) increased during IgAN progression. This was especially true for MAC, which was found to be involved prominently in disease progression. Alpha-N-acetylglucosaminidase (NAGLU) and α-galactosidase A (GLA) were validated by western blot and the results were consistent with the iTRAQ results. Ten proteins were validated in a PRM analysis, and these results were also consistent with the iTRAQ results. Complement factor B (CFB) and complement component C8 alpha chain (C8A) both increased with the progression of IgAN. The combination of CFB and mucosal addressin cell adhesion molecule-1 (MAdCAM-1) also showed potential as a urinary biomarker for monitoring IgAN development. Conclusion There were abundant complement components in the urine of IgAN patients, indicating that the activation of AP and LP is involved in IgAN progression. Urinary complement proteins may be used as biomarkers for evaluating IgAN progression in the future.

Abstract Pheochromocytoma/paraganglioma (PPGL) is an endocrine tumor of the chromaffin cells in the adrenal medulla or the paraganglia. Currently, about 70% of PPGLs can be explained by germline or somatic mutations in several broadly expressed susceptibility genes including RET, VHL, and SDHB, while for the remaining, mainly sporadic cases, the pathogenesis is still unclear. Even for known susceptible genes, how mutations in these mostly ubiquitous genes result in tissue-specific pathogenesis remains unanswered, and why RET-mutated tumors almost always occur in the adrenal while SDHB-mutated tumors mostly occur extra-adrenal remains a mystery. By analyzing 22 sporadic PPGLs using SNP 6.0 genotyping arrays combined with expression profiling of 4 normal and 4 tumor tissues, we identified GIPC2, a gene located at 1p31.1 with preferential expression in adrenal and inducible by adrenal glucocorticoid, as a novel putative tumor suppressor gene for PPGLs. Copy number deletion and GIPC2 promoter hypermethylation but not GIPC2 mutation, accompanied with reduced GIPC2 expression, were observed in 39 of 55 PPGLs in our cohort. Examination of a published expression database consisting of 188 PPGLs found little GIPC2 expression in Cluster 1A (SDHx-associated) and Cluster 2A (NF1/RET-associated) tumors, but less pronounced reduction of GIPC2 expression in Cluster 1B (VHL-associated) and Cluster 2B/2C tumors. GIPC2 induced p27, suppressed MAPK/ERK and HIF-1ɑ pathways as well as cancer cell proliferation. Overexpressing GIPC2 in PC12 cells inhibited tumor growth in nude mice. We found GIPC2 interacted with the nucleoprotein NONO and both proteins regulated p27 transcription through the same GGCC box on p27 promoter. Significantly, low expression of both GIPC2 and p27 was associated with shorter disease-free survival time of PPGLs patients in the TCGA database. We found that PPGL-causing mutations in RET and in SDHB could lead to primary rat adrenal chromaffin cell proliferation, ERK activation, and p27 downregulation, all requiring downregulating GIPC2. Notably, the RET-mutant effect required the presence of dexamethasone while the SDHB-mutant effect required its absence, providing a plausible explanation for the tumor location preference. In contrast, the PPGL-predisposing VHL mutations had no effect on proliferation and GIPC2 expression but caused p53 downregulation and reduced apoptosis in chromaffin cells compared with wild-type VHL. Thus, our study raises the importance of cortical hormone in PPGL development, and GIPC2 as a novel tumor suppressor provides a unified molecular mechanism for the tumorigenesis of both sporadic and hereditary tumors of Clusters 1A and 2A concerning SDHB and RET, but not tumors of Cluster 1B concerning VHL and other clusters.

Abstract Background The human brain is the most complex organ in the body, and it is important to have a better understanding of how the protein composition in the brain regions contributes to the pathogenesis of associated neurological disorders. Methods In this study, a comparative analysis of the frontal and temporal cortex proteomes was conducted by isobaric tags of relative and absolute quantification (iTRAQ) labeling and two-dimensional liquid chromatography-tandem mass spectrometry (2D LC-MS/MS). Brain protein was taken from relatively normal tissue that could not be avoided of damage during emergent surgery of the TBI (traumatic brain injury) patients admitted in Beijing Tiantan Hospital from 2014 to 2017. Eight cases were included. Four frontal lobes and 4 temporal lobes proteome were analyzed and the proteins were quantitated. Gene Ontology (GO), Ingenuity Pathway Analysis (IPA), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were used to analyze the biological function of identified proteins, unchanged proteins, and differentially expressed proteins (DEPs). Results A total number of 2127 protein groups were identified in the frontal and temporal lobe proteomes. A total of 1709 proteins could be quantitated in both the frontal and temporal cortex. Among 90 DEPs, 14 proteins were screened highly expressed in the temporal cortex, including MAPT, SNCG, ATP5IF1, GAP43, HSPE1, STMN1, NDUFS6, LDHB, SNCB, NDUFA7, MRPS36, EPDR1, CISD1, and RALA. In addition, compared to proteins expressed in the frontal cortex, 14 proteins including EDC4, NIT2, VWF, ASTN1, TGM2, SSB, CLU, HBA1, STOM, CRP, LRG1, SAA2, S100A4, and VTN were a low expression in the temporal cortex. The biological process enrichment showed that unchanged proteins between the frontal and temporal cortex mainly take part in regulated exocytosis, axon guidance, and vesicle-mediated transport. The KEGG pathway analysis showed that unchanged proteins between the frontal and temporal cortex mainly take part in oxidative phosphorylation, carbon metabolism, Huntington’s disease, and Parkinson’s disease. Conclusions The majority of proteins are unchanged between the frontal and temporal cortex, and unchanged proteins are closely related to its function. Among DEPs, MATP (tau) is upregulated in the temporal cortex, closely related to Alzheimer’s disease (AD), and is one of the targets for the treatment of AD. CLU is downregulated in the temporal cortex which functions as an extracellular chaperone that prevents aggregation of non-native proteins. It was suggested that the temporal lobe may not be the “functional dumb area” of the traditional view, but could be involved in important neural metabolic circuits.

Right ventricular failure (RVF) is the independent and strongest predictor of mortality in pulmonary arterial hypertension (PAH), but, at present, there are no preventive and therapeutic strategies directly targeting the failing right ventricle (RV). The underlying mechanism of RV hypertrophy (RVH) and dysfunction needs to be explored in depth. In this study, we used myocardial proteomics combined with metabolomics to elucidate potential pathophysiological changes of RV remodeling in a monocrotaline (MCT)-induced PAH rat model. The proteins and metabolites extracted from the RV myocardium were identified using label-free liquid chromatography–tandem mass spectrometry (LC-MS/MS). The bioinformatic analysis indicated that elevated intracellular Ca2+ concentrations and inflammation may contribute to myocardial proliferation and contraction, which may be beneficial for maintaining the compensated state of the RV. In the RVF stage, ferroptosis, mitochondrial metabolic shift, and insulin resistance are significantly involved. Dysregulated iron homeostasis, glutathione metabolism, and lipid peroxidation related to ferroptosis may contribute to RV decompensation. In conclusion, we depicted a proteomic and metabolomic profile of the RV myocardium during the progression of MCT-induced PAH, and also provided the insights for potential therapeutic targets facilitating the retardation or reversal of RV dysfunction in PAH.

Previous studies reported that sex and age could influence urine metabolomics, which should be considered in biomarker discovery. As a consequence, for the baseline of urine metabolomics characteristics, it becomes critical to avoid confounding effects in clinical cohort studies. In this study, we provided a comprehensive lifespan characterization of urine metabolomics in a cohort of 348 healthy children and 315 adults, aged 1 to 78 years, using liquid chromatography coupled with high resolution mass spectrometry. Our results suggest that sex-dependent urine metabolites are much greater in adults than in children. The pantothenate and CoA biosynthesis and alanine metabolism pathways were enriched in early life. Androgen and estrogen metabolism showed high activity during adolescence and youth stages. Pyrimidine metabolism was enriched in the geriatric stage. Based on the above analysis, metabolomic characteristics of each age stage were provided. This work could help us understand the baseline of urine metabolism characteristics and contribute to further studies of clinical disease biomarker discovery.

ObjectivesKnowledge of the urinary metabolomic profiles of healthy children and adolescents plays a promising role in the field of pediatrics. Metabolomics has also been used to diagnose disease, discover novel biomarkers, and elucidate pathophysiological pathways. Attention-deficit/hyperactivity disorder (ADHD) is one of the most common psychiatric disorders in childhood. However, large-sample urinary metabolomic studies in children with ADHD are relatively rare. In this study, we aimed to identify specific biomarkers for ADHD diagnosis in children and adolescents by urinary metabolomic profiling.MethodsWe explored the urine metabolome in 363 healthy children aged 1–18 years and 76 patients with ADHD using high-resolution mass spectrometry.ResultsMetabolic pathways, such as arachidonic acid metabolism, steroid hormone biosynthesis, and catecholamine biosynthesis, were found to be related to sex and age in healthy children. The urinary metabolites displaying the largest differences between patients with ADHD and healthy controls belonged to the tyrosine, leucine, and fatty acid metabolic pathways. A metabolite panel consisting of FAPy-adenine, 3-methylazelaic acid, and phenylacetylglutamine was discovered to have good predictive ability for ADHD, with a receiver operating characteristic area under the curve (ROC–AUC) of 0.918. A panel of FAPy-adenine, N-acetylaspartylglutamic acid, dopamine 4-sulfate, aminocaproic acid, and asparaginyl-leucine was used to establish a robust model for ADHD comorbid tic disorders and controls with an AUC of 0.918.

Background: Aberrant O-glycosylation of IgA1 plays an important role in IgA nephropathy pathogenesis. Previous proteomic studies analyzed O-glycans of the circulating IgA1 hinge region and found that the N-acetylgalactosamine (GalNAc) and galactose numbers in the hinge region of IgA1 of patients with IgA nephropathy were lower than those in healthy participants. However, the diagnostic performance of the O-glycosylation traits in the hinge region of plasma IgA1 for IgA nephropathy remains unelucidated. The present study aimed to determine the difference in plasma IgA1 hinge region O-glycoforms among IgA nephropathy, non-IgA nephropathy disease controls, and healthy participants, and to further evaluate the diagnostic performance of plasma IgA1 glycosylation traits.Methods: Sixty-two patients with biopsy-proven primary IgA nephropathy, 30 age- and sex-matched non-IgA nephropathy disease controls (10 patients with membranous nephropathy, 10 with focal segmental glomerulosclerosis, and 10 with minimal change disease), and 30 healthy participants were prospectively recruited. Plasma galactose deficient-IgA1 levels were measured using a KM55 kit. Plasma IgA was extracted using IgA immunoaffinity beads. After de-N-glycosylation, reduction, alkylation, trypsin digestion, and O-glycopeptide enrichment via hydrophilic interaction liquid chromatography, liquid chromatography tandem mass spectrometry (LC-MS/MS) was applied to analyze the IgA1 O-glycosylation patterns and we derived the plasma IgA1 O-glycosylation traits.Results: Plasma IgA1 O-glycosylation patterns were significantly changed in IgA nephropathy patients compared to those with non-IgA nephropathy disease controls and healthy participants. The GalNAc number was lowest in IgA nephropathy patients. In addition, a similar result was observed for the galactose number in the IgA1 hinge region. These values showed moderate potential for discriminating between IgA nephropathy and the controls. When these values were combined, the area under the curve increased compared to when they were considered individually. When further adding a clinical indicator, the area under the curve of the GalNAc-galactose-IgA panel exceed 0.9 in discriminating IgA nephropathy from the controls.Conclusion: The amount of GalNAc and galactose in plasma IgA1 hinge region identified by glycoproteomics could be used as a diagnostic biomarker for IgA nephropathy. The panel containing GalNAc, galactose, and circulating IgA displayed excellent diagnostic performance and is promising for practical clinical applications.

Abstract Background To discover biomarker panels that could distinguish cancers (BC and RCC) from healthy controls (HCs) and bladder cancers (BC) from renal cell carcinoma (RCC), regardless of whether the patients have haematuria. In addition, we also explored the altered metabolomic pathways of BC and RCC. Methods In total, 403 participants were enrolled in our study, which included 146 BC patients (77 without haematuria and 69 with haematuria), 115 RCC patients (94 without haematuria and 21 with haematuria) and 142 sex- and age-matched HCs. Their midstream urine samples were collected and analysed by performing UPLC-MS. The statistical methods and pathway analyses were applied to discover potential biomarker panels and altered metabolic pathways. Results The panel of α-CEHC, β-cortolone, deoxyinosine, flunisolide, 11b,17a,21-trihydroxypreg-nenolone and glycerol tripropanoate could distinguish the patients with cancer from the HCs (the AUC was 0.950) and the external validation also displayed a good predictive ability (the AUC was 0.867). The panel of 4-ethoxymethylphenol, prostaglandin F2b, thromboxane B3, hydroxybutyrylcarnitine, 3-hydroxyphloretin and N′-formylkynurenine could differentiate BC from RCC without haematuria. The AUC was 0.829 in the discovering group and 0.76 in the external validation. The metabolite panel comprising 1-hydroxy-2-oxopropyl tetrahydropterin, 1-acetoxy-2-hydroxy-16-heptadecyn-4-one, 1,2-dehydrosalsolinol and L-tyrosine could significantly discriminate BC from RCC with haematuria (AUC was 0.913). Pathway analyses revealed altered lipid and purine metabolisms between cancer patients and HCs, together with disordered amino acid and purine metabolisms between BC and RCC with haematuria. Conclusions UPLC-MS urine metabolomic analyses could not only differentiate cancers from HCs but also discriminate BC from RCC. In addition, pathway analyses demonstrated a deeper metabolic mechanism of BC and RCC.

Profiling bodily fluids is crucial for monitoring and discovering metabolic markers of disease. In this study, a comprehensive analysis approach based on 1D-LC-MS/MS and 2D-LC-MS/MS was applied to profile normal human urine metabolites from 348 children and 315 adults. A total of 2357 metabolites were identified, including 1831 endogenous metabolites and 526 exogenous ones. In total, 1005 metabolites were identified in urine for the first time. The urinary metabolites were mainly involved in amino acid metabolism, small molecule biochemistry, lipid metabolism and cellular compromise. The comparison of adult’s and children’s urine metabolomes showed adults urine had more metabolites involved in immune response than children’s, but the function of binding of melatonin, which belongs to the endocrine system, showed a higher expression in children. The urine metabolites detected by the 1D-LC-MS/MS method were mainly related to amino acid metabolism and lipid metabolism, and the 2D-LC-MS/MS method not only explored metabolites from 1D-LC-MS/MS but also metabolites related to cell signaling, cell function and maintenance, etc. Our analysis comprehensively profiled and functionally annotated the metabolome of normal human urine, which would benefit the application of urinary metabolome to clinical research.

Aqueous humor (AH) proteins are involved in many physiological and pathological processes of the eye. The proteome analysis of AH is important to understand its physiological and pathophysiological functions. In the present study, AH samples obtained from 21 cataract volunteers were pooled together. After high-pH RPLC offline separation, the pooled sample was analyzed by LC-MS/MS to provide a comprehensive profile of AH proteome. The function analysis was provided by the GO and IPA annotation. In order to determine whether the AH proteome can reflect the pathophysiological changes of the disease, DIA technology was used to analyze the AH samples obtained from three neovascular glaucoma (NVG) patients (six samples) before and after drug treatment. The differential proteins were validated by PRM technology in an independent group (14 samples). In the AH proteome database, 802 proteins were identified, and 318 proteins were identified for the first time. Furthermore, 480 proteins were quantified based on the peak intensity-based semiquantification (iBAQ), which ranged by approximately 7 orders of magnitude. These proteins are primarily involved in immunity- and inflammation-related pathways. The differential AH proteomic analysis in NVG treatment revealed that the AH proteome can reflect the pathophysiological changes of drug treatment. Angiogenesis and thrombus coagulation progression are deeply involved in NVG treatment. The present experiment provided a comprehensive AH proteome analysis and expanded the profile of human AH proteome. The differential AH proteomic analysis of NVG treatment indicated that AH proteome can reflect the pathophysiological changes in drug intervention.

Plasma metabolomics and lipidomics have been commonly used for biomarker discovery. Studies in white and Japanese populations suggested that gender and age can affect circulating plasma metabolite profiles; however, the metabolomics characteristics in Chinese population has not been surveyed. In our study, we applied liquid chromatography-mass spectrometry-based approach to analyze Chinese plasma metabolome and lipidome in a cohort of 534 healthy adults (aging from 15 to 79). Fatty-acid metabolism was found to be gender- and age-dependent in Chinese, similar with metabolomics characteristics in Japanese and white populations. Differently, lipids, such as TGs and DGs, were found to be gender-independent in Chinese population. Moreover, nicotinate and nicotinamide metabolism was found to be specifically age-related in Chinese. The application of plasma metabolome and lipidome for renal cell carcinoma diagnosis (143 RCC patients and 34 benign kidney tumor patients) showed good accuracy, with an area under the curve (AUC) of 0.971 for distinction from healthy control, and 0.839 for distinction from the benign. Bile acid metabolism was found to be related to RCC probably combination with intestinal microflora. Definition of the variation and characteristics of Chinese normal plasma metabolome and lipidome might provide a basis for disease biomarker analysis.

Bladder cancer (BC) and Renal cell carcinoma(RCC) are the two most frequent genitourinary cancers in China. In this study, a comprehensive liquid chromatography—mass spectrometry (LC-MS) based method, which utilizes both plasma metabolomics and lipidomics platform, has been carried out to discriminate the global plasma profiles of 64 patients with BC, 74 patients with RCC, and 141 healthy controls. Apparent separation was observed between cancer (BC and RCC) plasma samples and controls. The area under the receiving operator characteristic curve (AUC) was 0.985 and 0.993 by plasma metabolomics and lipidomics, respectively (external validation group: AUC was 0.944 and 0.976, respectively). Combined plasma metabolomics and lipidomics showed good predictive ability with an AUC of 1 (external validation group: AUC = 0.99). Then, separation was observed between the BC and RCC samples. The AUC was 0.862, 0.853 and 0.939, respectively, by plasma metabolomics, lipidomics and combined metabolomics and lipidomics (external validation group: AUC was 0.802, 0.898, and 0.942, respectively). Furthermore, we also found eight metabolites that showed good predictive ability for BC, RCC and control discrimination. This study indicated that plasma metabolomics and lipidomics may be effective for BC, RCC and control discrimination, and combined plasma metabolomics and lipidomics showed better predictive performance. This study would provide a reference for BC and RCC biomarker discovery, not only for early detection and screening, but also for differential diagnosis.

Abstract Background IgA nephropathy (IgAN) is one of the most common forms of idiopathic glomerular diseases and might lead to end-stage kidney disease. Accurate and non-invasive biomarkers for early diagnosis are required for early intervention and consequent therapy for IgAN patients. Because variance in the disease incidence and predisposing genes of IgAN has been detected among different ethnicities, the ethnicity factor should be considered in IgAN biomarker discovery. The differences in the protein profiles and pathological mechanisms of IgAN in patients of Uygur ethnicity need to be clearly illustrated. Methods In this study, we used urinary proteomics to discover candidate biomarkers of IgAN in patients of Uygur ethnicity. The urinary proteins from Uygur normal control and Uygur IgAN patients were extracted and analyzed using 2D-LC-MS/MS and isobaric tags for relative and absolute quantitation (iTRAQ) analysis. Results A total of 277 proteins were found to be differentially represented in Uygur IgAN compared with the respective normal controls. The bioinformatics analysis revealed that the immune response, cell survival, and complement system were activated in Uygur IgAN. Many differentially expressed proteins were found to be related to nephropathy and kidney injuries. Four candidate biomarkers were validated by Western blot, and these results were consistent with the iTRAQ results. ICAM1, TIMP1, SERPINC1 and ADIPOQ were upregulated in Uygur IgAN. Bioinformatic analysis revealed that the increase of ICAM1 and TIMP1 might be caused by IgAN, but the increase of SERPINC1 and ADIPOQ might be caused by proteinuria. SERPINC1 and ICAM1 were identified as the candidate biomarkers with excellent area-under-the-curve (AUC) values (0.84) for distinguishing Uygur IgAN from normal controls. Conclusions Using urinary proteomic analysis, we identified several candidate biomarkers for IgAN in patients of Uygur ethnicity. These results will prove helpful for exploring the pathological mechanism of IgAN in patients of Uygur ethnicity and for developing better treatments for these patients.

Abstract Biomarkers are measurable changes associated with the disease. Urine can reflect the changes of the body while blood is under control of the homeostatic mechanisms; thus, urine is considered an important source for early and sensitive disease biomarker discovery. A comprehensive profile of the urinary proteome will provide a basic understanding of urinary proteins. In this paper, we present an in-depth analysis of the urinary proteome based on different separation strategies, including direct one dimensional liquid chromatography–tandem mass spectrometry (LC/MS/MS), two dimensional LC/MS/MS, and gel-eluted liquid fraction entrapment electrophoresis/liquid-phase isoelectric focusing followed by two dimensional LC/MS/MS. A total of 6085 proteins were identified in healthy urine, of which 2001 were not reported in previous studies and the concentrations of 2571 proteins were estimated (spanning a magnitude of 106) with an intensity-based absolute quantification algorithm. The urinary proteins were annotated by their tissue distribution. Detailed information can be accessed at the “Human Urine Proteome Database” (www.urimarker.com/urine).

Objective: To investigate a proteomics analysis of liver proteins from rats with spleen-deficiency syndrome (SDS) induced by chronic improper diet consumption and fatigue. Methods: This study used a liver proteomic profiling method to identify differentially expressed proteins and altered pathways involved in SDS rats. Specifically, we collected liver samples from a control group and a group with SDS induced by chronic improper diet consumption and fatigue for 4 weeks. The pooled liver proteins in each group were labeled with 8-plex isobaric tags for relative and absolute quantitation reagents. The labeled control and SDS group samples were pooled together and separated by high-pH reverse-phase liquid chromatography. The differentially expressed proteins from the liver proteomes were analyzed to identify potential biomarkers of SDS. Differentially expressed proteins were selected in conjunction with gene ontology and ingenuity pathway analysis. Results: We identified 2176 protein clusters with more than two peptides in the SDS group, with 141 proteins quantified as differentially expressed proteins. Of these, 75 proteins were up-regulated, and 66 were down-regulated. Three activated signaling pathways, the thrombin, CXCR4 and synaptic long term depression signaling pathways, and a large multi-protein complex within the network were revealed in the liver proteomic analysis of SDS rats. Conclusions: This is the first report of a differential liver proteome under SDS conditions. The results suggest that the liver proteome partially reflects the pathological changes involved in SDS. The findings provide important information for comprehensively understanding the mechanisms of dysfunction or injury in the liver at the molecular level as a result of SDS. Furthermore, they provide a novel understanding of the connotation of SDS in the field of traditional Chinese Medicine.

Renal cell carcinoma (RCC) is the second most lethal urinary cancer. RCC is frequently asymptomatic and it is already metastatic at diagnosis. There is an urgent necessity for RCC specific biomarkers selection for diagnostic and prognostic purposes. In present study, we applied liquid chromatography—mass spectrometry (LC-MS) based metabolomics to analyze urine samples of 100 RCC, 34 benign kidney tumors and 129 healthy controls. Differential metabolites were analyzed to investigate if urine metabolites could differentiate RCC from non-RCC. A panel consisting of 9 metabolites showed the best predictive ability for RCC from the health controls with an area under the curve (AUC) values of 0.905 for the training dataset and 0.885 for the validation dataset. Separation was observed between the RCC and benign samples with an AUC of 0.816. RCC clinical stages (T1 and T2 vs. T3 and T4) could be separated using a panel of urine metabolites with an AUC of 0.813. One metabolite, N-formylkynurenine, was discovered to have potential value for RCC diagnosis from non-RCC subjects with an AUC of 0.808. Pathway enrichment analysis indicated that tryptophan metabolism was an important pathway in RCC. Our data concluded that urine metabolomics could be used for RCC diagnosis and would provide candidates for further targeted metabolomics analysis of RCC.

White adipose tissue (WAT) plays a significant role in energy metabolism and the obesity epidemic. In this study, we sought to (1) profile the mouse WAT proteome with advanced 2DLC/MS/MS approach, (2) provide insight into WAT function based on protein functional annotation, and (3) predict potentially secreted proteins. A label-free 2DLC/MS/MS proteomic approach was used to identify the WAT proteome from female mouse WAT. A total of 6,039 proteins in WAT were identified, among which 5,160 were quantified (spanning a magnitude of 106) using an intensity-based absolute quantification algorithm, and 3,117 proteins were reported by proteomics technology for the first time in WAT. To comprehensively analyze the function of WAT, the proteins were divided into three quantiles based on abundance and we found that proteins of different abundance performed different functions. High-abundance proteins (the top 90%, 1,219 proteins) were involved in energy metabolism; middle-abundance proteins (90–99%, 2,273 proteins) were involved in the regulation of protein synthesis; and low-abundance proteins (99–100%, 1,668 proteins) were associated with lipid metabolism and WAT beiging. Furthermore, 800 proteins were predicted by SignalP4.0 to have signal peptides, 265 proteins had never been reported, and five have been reported as adipokines. The above results provide a large dataset of the normal mouse WAT proteome, which might be useful for WAT function research.

[This corrects the article DOI: 10.1371/journal.pone.0133270.].

Background: Clinical outcomes of bladder cancer (BC) are tightly associated with the stage and grade of the initial diagnosis of BC because early detection is clearly important for patients with BC. However, the diagnostic capability of current detection methods, such as urinary cytology, cystoscopy, imageology method, and several urine-based tests, is inadequate for early detection of BC. The objective of our study is to discover novel biomarkers for detecting BC at an early stage, called non-muscle invasive (NMI) BC, using liquid chromatography-high resolution mass spectrometry (LC-HRMS)-based metabolomics.Methods: First, morning midstream urine samples were collected from healthy adult and NMIBC patients. The LC-HRMS-based metabolomics were applied to distinguish the NMIBC group without hematuria from the controls (gender- and age-matched volunteers with normal clinically healthy index), low-grade NMIBC from the controls, and high-grade from low-grade NMIBC.Results: A total of 284 subjects were enrolled in our study including 117 healthy adults, 80 NMIBC patients without hematuria, and 87 NMIBC patients with hematuria. The metabolite panel including dopamine 4-sulfate, MG00/1846Z,9Z,12Z,15Z/00, aspartyl-histidine, and tyrosyl-methionine was found in a discovery set, which showed the predictive ability to distinguish the NMIBC group from the control group with an area under the curve (AUC) of 0.838 in an external validation set. The AUC of the panel for low-grade NMIBC samples, which consisted of 3-hydroxy-cis-5-tetradecenoylcarnitine, 6-ketoestriol, beta-cortolone, tetrahydrocorticosterone, and heptylmalonic acid, was 0.899. The sensitivity and specificity were 0.881 and 0.786, respectively. The AUC of the panel for distinction of low-grade NMIBC with and without hematuria against high-grade NMIBC with and without hematuria were 0.827 and 0.755, respectively. In addition, metabolites involved in tryptophan metabolism were upregulated in the urine of high-grade NMIBC patients when compared with low-grade NMIBC patients with the presence or absence of hematuria.Conclusion: The NMIBC urine metabolic profiling was able to assist in the early detection of BC. Panels of metabolites were discovered to have a potential value for high-grade NMIBC and low-grade NMIBC diagnosis as well as for NMIBC grading distinction.

Knowledge about the normal human cerebrospinal fluid (CSF) proteome serves as a baseline reference for CSF biomarker discovery and provides insight into CSF physiology. In this study, high-pH reverse-phase liquid chromatography (hp-RPLC) was first integrated with a TripleTOF 5600 mass spectrometer to comprehensively profile the normal CSF proteome. A total of 49,836 unique peptides and 3256 non-redundant proteins were identified. To obtain high-confidence results, 2513 proteins with at least 2 unique peptides were further selected as bona fide CSF proteins. Nearly 30% of the identified CSF proteins have not been previously reported in the normal CSF proteome. More than 25% of the CSF proteins were components of CNS cell microenvironments, and network analyses indicated their roles in the pathogenesis of neurological diseases. The top canonical pathway in which the CSF proteins participated was axon guidance signaling. More than one-third of the CSF proteins (788 proteins) were related to neurological diseases, and these proteins constitute potential CSF biomarker candidates. The mapping results can be freely downloaded at http://122.70.220.102:8088/csf/, which can be used to navigate the CSF proteome. For more information about the data, please refer to the related original article [1], which has been recently accepted by Journal of Proteomics.

Urine and cerebrospinal fluid (CSF) are two important biofluids used for disease biomarker discovery. For differential proteomic analysis, it is essential to evaluate individual and gender variations. In this study, we characterized urinary and CSF proteomes of 14 healthy volunteers with regard to individual and gender variations using 2DLC-MS/MS analysis and 8-plex iTRAQ quantification. A total of 968/512 urinary/CSF proteins were identified, with 406/280 quantified in all individuals. The median inter-individual coefficients of variation (CVs) were 0.262 and 0.183 for urinary and CSF proteomes, respectively. Cluster analysis showed that male and female urinary proteomes exhibited different patterns, though CSF proteome showed no remarkable gender differences. In comparison with CSF proteome, urinary proteome showed higher individual variation. Further analysis revealed that individual variation was not correlated with protein abundance. The minimum sample size for proteomic analysis with a 2-fold change was 10 (4/5 for males/females using iTRAQ quantification) for urinary or 8 for CSF proteome. Intracellular proteins leaked from exfoliative cells tended to have higher CVs, and extracellular proteins secreted from urinary tract or originating from plasma tended to have lower CVs. The above results might be beneficial for differential proteomic analysis and biomarker discovery.

Although a bone tumor, significant differences in the extent of bone invasion exist in skull base chordoma, which directly affect the extent of surgical resection, and have an impact on its prognosis. However, the underlying mechanism of the phenomenon is not clearly understood. Therefore, we used an iTRAQ-based quantitative proteomics strategy to identify potential molecular signatures, and to find predictive markers of discrepancy in bone invasion of clivus chordoma. According to bone invasive classification criteria, 35 specimens of clivus chordoma were calssified to be either endophytic type (Type I) or exophytic type (Type II). An initial screening of six specimens of endophytic type and six of exophytic was performed, and 250 differentially expressed proteins were identified. Through the GO and IPA analysis, we found evidence that the expression of inflammatory activity-associated proteins up-regulated in endophytic type, whereas the expression of cell motility-associated proteins up-regulated in exophytic ones. Moreover, TGFβ1 and mTOR signal pathway seemed to be related with bone invasion. Thus, TGFβ1, PI3K, Akt, mTOR, and PTEN were validated in the following 23 samples by immune histochemistry and Western blot. The expression levels of TGFβ1 and PTEN were significantly lower in the endophytic type than in the exophytic ones. It was found that TGFβ1 may play an important role in its bone invasion. The mechanisms may be related with conducting an increased inflammatory cell response and a decline in cytoskeletal protein expression. PTEN is confirmed to be associated with the degree of bone invasion. The PI3K/AKT/mTOR signaling pathway might be associated with the bone invasion, but still needs a larger sample size to be verified These results, for the first time, not only demonstrate the biological changes that occur in different growth patterns from the perspective of proteomics, but also provide novel markers that may help to reveal the mechanisms behind clivus chordomas.

The present work is mainly concerned with the Dullin-Gottwald-Holm (DGH) equation with strong dissipative term. We establish some sufficient conditions to guarantee finite time blow-up of strong solutions.

This paper is concerned with blow-up phenomena and persistence properties for an integrable two-component Dullin-Gottwald-Holm shallow water system. We give sufficient conditions on the initial data which guarantee blow-up phenomena of solutions in finite time for both periodic and nonperiodic cases, respectively. Furthermore, the persistence properties of solutions to the system are investigated.

We discuss blowup phenomena for a modified two-component Dullin-Gottwald-Holm shallow water system. In this paper, some new blowup criteria of strong solutions involving the density and suitable integral form of the momentum are established.

The use of targeted proteomics to identify urinary biomarkers of kidney disease in urine can avoid the interference of serum proteins. It may provide better sample throughput, higher sensitivity, and specificity. Knowing which urinary proteins to target is essential. By analyzing the urine from perfused isolated rat kidneys, 990 kidney origin proteins with human analogs were identified in urine. Of these proteins, 128 were not found in normal human urine and may become biomarkers with zero background. A total of 297 proteins were not found in normal human plasma. These proteins will not be influenced by other normal organs and will be kidney specific. The levels of 33 proteins increased during perfusion with an oxygen-deficient solution compared to those perfused with oxygen. The 75 proteins in the perfusion-driven urine have a significantly increased abundance ranking compared to their ranking in normal human urine. When compared with existing candidate biomarkers, over ninety percent of the kidney origin proteins in urine identified in this study have not been examined as candidate biomarkers of kidney diseases.

It is shown that a strong solution of the Degasperis-Procesi equation possesses persistence property in the sense that the solution with algebraically decaying initial data and its spatial derivative must retain this property. Moreover, we give estimates of measure for the momentum support.

We investigate the traveling wave solutions in a reaction-diffusion epidemic model. The existence of the wave solutions is derived through monotone iteration of a pair of classical upper and lower solutions. The traveling wave solutions are shown to be unique and strictly monotonic. Furthermore, we determine the critical minimal wave speed.

Ubiquitin ligases (E3s) determine specificity of ubiquitination by recognizing target substrates. However, most of their substrates are unknown. Most known substrates have been identified using distinct approaches in different laboratories. We developed a high-throughput strategy using a live phage display library as E3 substrates in in vitro screening. His-ubiquitinated phage, enriched with Ni-beads, could effectively infect E. coli for amplification. Sixteen natural potential substrates and many unnatural potential substrates of E3 MDM2 were identified through 4 independent screenings. Some substrates were identified in different independent experiments. Additionally, 10 of 12 selected candidates were ubiquitinated by MDM2 in vitro, and 3 novel substrates, DDX42, TP53RK and RPL36a were confirmed ex vivo. The whole strategy is rather simple and efficient. Non-degradation substrates can be discovered. This strategy can be extended to any E3s as long as the E3 does not ubiquitinate the empty phage.

We investigate the spatiotemporal dynamics induced by Allee effect in a reaction-diffusion predator-prey model. In the case without Allee effect, there is nonexistence of diffusion-driven instability for the model. And in the case with Allee effect, the positive equilibrium may be unstable under certain conditions. This instability is induced by Allee effect and diffusion together. Furthermore, via numerical simulations, the model dynamics exhibits both Allee effect and diffusion controlled pattern formation growth to holes, stripes-holes mixture, stripes, stripes-spots mixture, and spots replication, which shows that the dynamics of the model with Allee effect is not simple, but rich and complex.

We consider a novel two-component rod system which is closely connected to the shallow water theory. The present work is mainly concerned with the blow-up mechanism of strong solutions; we establish new conditions in view of some special classes of initial value to guarantee finite time blow-up of solutions.

We present a theoretical analysis of the processes of pattern formation that involves organisms distribution and their interaction of spatially distributed population with self- as well as cross-diffusion in a Holling-Tanner predator-prey model; the sufficient conditions for the Turing instability with zero-flux boundary conditions are obtained; Hopf and Turing bifurcation in a spatial domain is presented, too. Furthermore, we present novel numerical evidence of time evolution of patterns controlled by self- as well as cross-diffusion in the model, and find that the model dynamics exhibits a cross-diffusion controlled formation growth not only to spots, but also to strips, holes, and stripes-spots replication. And the methods and results in the present paper may be useful for the research of the pattern formation in the cross-diffusive model.