Improving biomedical named entity recognition by dynamic caching inter-sentence information.

MOTIVATION: Biomedical Named Entity Recognition (BioNER) aims to identify biomedical domain-specific entities (e.g. gene, chemical and disease) from unstructured texts. Despite deep learning-based methods for BioNER achieving satisfactory results, there is still much room for improvement. Firstly, most existing methods use independent sentences as training units and ignore inter-sentence context, which usually leads to the labeling inconsistency problem. Secondly, previous document-level BioNER works have approved that the inter-sentence information is essential, but what information should be regarded as context remains ambiguous. Moreover, there are still few pre-training-based BioNER models that have introduced inter-sentence information. Hence, we propose a cache-based inter-sentence model called BioNER-Cache to alleviate the aforementioned problems. RESULTS: We propose a simple but effective dynamic caching module to capture inter-sentence information for BioNER. Specifically, the cache stores recent hidden representations constrained by predefined caching rules. And the model uses a query-and-read mechanism to retrieve similar historical records from the cache as the local context. Then, an attention-based gated network is adopted to generate context-related features with BioBERT. To dynamically update the cache, we design a scoring function and implement a multi-task approach to jointly train our model. We build a comprehensive benchmark on four biomedical datasets to evaluate the model performance fairly. Finally, extensive experiments clearly validate the superiority of our proposed BioNER-Cache compared with various state-of-the-art intra-sentence and inter-sentence baselines. AVAILABILITYAND IMPLEMENTATION: Code will be available at https://github.com/zgzjdx/BioNER-Cache. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Population Genomic Analyses Suggest a Hybrid Origin, Cryptic Sexuality, and Decay of Genes Regulating Seed Development for the Putatively Strictly Asexual Kingdonia uniflora (Circaeasteraceae, Ranunculales).

Asexual lineages are perceived to be short-lived on evolutionary timescales. Hence, reports for exceptional cases of putative 'ancient asexuals' usually raise questions about the persistence of such species. So far, there have been few studies to solve the mystery in plants. The monotypic Kingdonia dating to the early Eocene, contains only K. uniflora that has no known definitive evidence for sexual reproduction nor records for having congeneric sexual species, raising the possibility that the species has persisted under strict asexuality for a long period of time. Here, we analyze whole genome polymorphism and divergence in K. uniflora. Our results show that K. uniflora is characterized by high allelic heterozygosity and elevated πN/πS ratio, in line with theoretical expectations under asexual evolution. Allele frequency spectrum analysis reveals the origin of asexuality in K. uniflora occurred prior to lineage differentiation of the species. Although divergence within K. uniflora individuals exceeds that between populations, the topologies of the two haplotype trees, however, fail to match each other, indicating long-term asexuality is unlikely to account for the high allele divergence and K. uniflora may have a recent hybrid origin. Phi-test shows a statistical probability of recombination for the conflicting phylogenetic signals revealed by the split network, suggesting K. uniflora engages in undetected sexual reproduction. Detection of elevated genetic differentiation and premature stop codons (in some populations) in genes regulating seed development indicates mutational degradation of sexuality-specific genes in K. uniflora. This study unfolds the origin and persistence mechanism of a plant lineage that has been known to reproduce asexually and presents the genomic consequences of lack of sexuality.

Genomic convergence underlying high-altitude adaptation in alpine plants.

Evolutionary convergence is one of the most striking examples of adaptation driven by natural selection. However, genomic evidence for convergent adaptation to extreme environments remains scarce. Here, we assembled reference genomes of two alpine plants, Saussurea obvallata (Asteraceae) and Rheum alexandrae (Polygonaceae), with 37,938 and 61,463 annotated protein-coding genes. By integrating an additional five alpine genomes, we elucidated genomic convergence underlying high-altitude adaptation in alpine plants. Our results detected convergent contractions of disease-resistance genes in alpine genomes, which might be an energy-saving strategy for surviving in hostile environments with only a few pathogens present. We identified signatures of positive selection on a set of genes involved in reproduction and respiration (e.g., MMD1, NBS1, and HPR), and revealed signatures of molecular convergence on genes involved in self-incompatibility, cell wall modification, DNA repair and stress resistance, which may underlie adaptation to extreme cold, high ultraviolet radiation and hypoxia environments. Incorporating transcriptomic data, we further demonstrated that genes associated with cuticular wax and flavonoid biosynthetic pathways exhibit higher expression levels in leafy bracts, shedding light on the genetic mechanisms of the adaptive "greenhouse" morphology. Our integrative data provide novel insights into convergent evolution at a high-taxonomic level, aiding in a deep understanding of genetic adaptation to complex environments.

Deep transfer learning of structural magnetic resonance imaging fused with blood parameters improves brain age prediction.

Machine learning has been applied to neuroimaging data for estimating brain age and capturing early cognitive impairment in neurodegenerative diseases. Blood parameters like neurofilament light chain are associated with aging. In order to improve brain age predictive accuracy, we constructed a model based on both brain structural magnetic resonance imaging (sMRI) and blood parameters. Healthy subjects (n = 93; 37 males; aged 50-85 years) were recruited. A deep learning network was firstly pretrained on a large set of MRI scans (n = 1,481; 659 males; aged 50-85 years) downloaded from multiple open-source datasets, to provide weights on our recruited dataset. Evaluating the network on the recruited dataset resulted in mean absolute error (MAE) of 4.91 years and a high correlation (r = .67, p <.001) against chronological age. The sMRI data were then combined with five blood biochemical indicators including GLU, TG, TC, ApoA1 and ApoB, and 9 dementia-associated biomarkers including ApoE genotype, HCY, NFL, TREM2, Aß40, Aß42, T-tau, TIMP1, and VLDLR to construct a bilinear fusion model, which achieved a more accurate prediction of brain age (MAE, 3.96 years; r = .76, p <.001). Notably, the fusion model achieved better improvement in the group of older subjects (70-85 years). Extracted attention maps of the network showed that amygdala, pallidum, and olfactory were effective for age estimation. Mediation analysis further showed that brain structural features and blood parameters provided independent and significant impact. The constructed age prediction model may have promising potential in evaluation of brain health based on MRI and blood parameters.

Molecular phylogeography and species distribution modelling evidence of 'oceanic' adaptation for Actinidia eriantha with a refugium along the oceanic-continental gradient in a biodiversity hotspot.

BACKGROUND: Refugia is considered to be critical for maintaining biodiversity; while discerning the type and pattern of refugia is pivotal for our understanding of evolutionary processes in the context of conservation. Interglacial and glacial refugia have been studied throughout subtropical China. However, studies on refugia along the oceanic-continental gradient have largely been ignored. We used a liana Actinidia eriantha, which occurs across the eastern moist evergreen broad-leaved forests of subtropical China, as a case study to test hypotheses of refugia along the oceanic-continental gradient and 'oceanic' adaptation. RESULTS: The phylogeographic pattern of A. eriantha was explored using a combination of three cpDNA markers and 38 nuclear microsatellite loci, Species distribution modelling and dispersal corridors analysis. Our data showed intermediate levels of genetic diversity [haplotype diversity (hT) = 0.498; unbiased expected heterozygosity (UHE) = 0.510] both at the species and population level. Microsatellite loci revealed five clusters largely corresponding to geographic regions. Coalescent time of cpDNA lineages was dated to the middle Pliocene (ca. 4.03 Ma). Both geographic distance and climate difference have important roles for intraspecific divergence of the species. The Zhejiang-Fujian Hilly Region was demonstrated to be a refugium along the oceanic-continental gradient of the species and fit the 'refugia in refugia' pattern. Species distribution modelling analysis indicated that Precipitation of Coldest Quarter (importance of 44%), Temperature Seasonality (29%) and Mean Temperature of Wettest Quarter (25%) contributed the most to model development. By checking the isolines in the three climate layers, we found that A. eriantha prefer higher precipitation during the coldest quarter, lower seasonal temperature difference and lower mean temperature during the wettest quarter, which correspond to 'oceanic' adaptation. Actinidia eriantha expanded to its western distribution range along the dispersal corridor repeatedly during the glacial periods. CONCLUSIONS: Overall, our results provide integrated evidence demonstrating that the Zhejiang-Fujian Hilly Region is a refugium along the oceanic-continental gradient of Actinidia eriantha in subtropical China and that speciation is attributed to 'oceanic' adaptation. This study gives a deeper understanding of the refugia in subtropical China and will contribute to the conservation and utilization of kiwifruit wild resources in the context of climate change.

Proteomic Profiling of Cerebrum Mitochondria, Myelin Sheath, and Synaptosome Revealed Mitochondrial Damage and Synaptic Impairments in Association with 3 × Tg-AD Mice Model.

Alzheimer's disease (AD) is the most common age-associated dementia with complex pathological hallmarks. Mitochondrion, synaptosome, and myelin sheath appear to be vulnerable and play a key role in the pathogenesis of AD. To clarify the early mechanism associated with AD, followed by subcellular components separation, we performed iTRAQ (isobaric tags for relative and absolute quantification)-based proteomics analysis to simultaneously investigate the differentially expressed proteins (DEPs) within the mitochondria, synaptosome, and myelin sheath in the cerebrum of the 6-month-old triple transgenic AD (3 × Tg-AD) and 6-month-old wild-type (WT) mice. A large number of DEPs between the AD and WT mice were identified. Most of them are related to mitochondria and synaptic dysfunction and cytoskeletal protein change. Differential expressions of Lrpprc, Nefl, and Sirpa were verified by Western blot analysis. The results suggest that decreased energy metabolism, impaired amino acid metabolism and neurotransmitter synthesis, increase compensatory fatty acid metabolism, up-regulated cytoskeletal protein expression, and oxidative stress are the early events of AD. Among these, mitochondrial damage, synaptic dysfunction, decreased energy metabolism, and abnormal amino acid metabolism are the most significant events. The results indicate that it is feasible to separate and simultaneously perform proteomics analysis on the three subcellular components.

Ultrasensitive Detection of Exosome Using Biofunctionalized Gold Nanorods on a Silver-Island Film.

Exosomes are often a promising source of biomarkers for cancer diagnosis in the early stages. Therefore, it is important to develop a sensitive and low-cost detection method. Here, we introduce a new substrate using gold nanorods (GNRs) on a silver-island film that produces a 360-fold AF647 molecule fluorescence enhancement compared to glass. The amplified fluorescence was proven theoretically by using finite difference time-domain simulation (FDTD). Utilizing the enhanced fluorescence from the substrate, GNRs attached with the biomolecules and created a sandwich immunoassay that can significantly detect human CD63 antigen on the exosome. By applying the method, the detection limit of mouse IgG goes down to 0.3 ng/mL, which is considerably better than the existing methods. Moreover, the sensitivity and accuracy for clinical plasma from six patients confirm its diagnostic feasibility. The proposed substrate can be uniformly extended to the identification of other biomarkers by modifying the antibodies on the surfaces of the GNRs.

Investigating the Neurotoxic Impacts of Arsenic and the Neuroprotective Effects of Dictyophora Polysaccharide Using SWATH-MS-Based Proteomics.

Arsenic (As) is one of the most important toxic elements in the natural environment. Currently, although the assessment of the potential health risks of chronic arsenic poisoning has received great attention, the research on the effects of arsenic on the brain is still limited. It has been reported that dictyophora polysaccharide (DIP), a common bioactive natural compound found in dietary plants, could reduce arsenic toxicity. Following behavioral research, comparative proteomics was performed to explore the molecular mechanism of arsenic toxicity to the hippocampi of SD (Sprague Dawley) rats and the protective effect of DIP. The results showed that exposure to arsenic impaired the spatial learning and memory ability of SD rats, while DIP treatment improved both the arsenic-exposed rats. Proteomic analysis showed that arsenic exposure dysregulated the expression of energy metabolism, apoptosis, synapse, neuron, and mitochondria related proteins in the hippocampi of arsenic-exposed rats. However, DIP treatment reversed or restored the expression levels of these proteins, thereby improving the spatial learning and memory ability of arsenic-exposed rats. This study is the first to use high-throughput proteomics to reveal the mechanism of arsenic neurotoxicity in rats as well as the protective mechanism of DIP against arsenic neurotoxicity.

Targeted metabolomics study of early pathological features in hippocampus of triple transgenic Alzheimer's disease male mice.

Alzheimer's disease (AD) is a serious neurodegenerative disease in people of age 65 or above. The detailed etiology and pathogenesis of AD have not been elucidated yet. In this study, the hippocampi of 2- and 6-month-old triple transgenic Alzheimer's disease male mice and age-sex-matched wild-type (WT) mice were analyzed by using targeted metabolomics approach. Compared with WT mice, 24 and 60 metabolites were found with significant differences in 2- and 6-month-old AD mice. Among these, 14 metabolites were found common while 10 metabolites showed consistent variable trends in both groups. These differential metabolites are found associated with amino acid, lipid, vitamin, nucleotide-related base, neurotransmitter and energy metabolisms, and oxidative stress. The results suggest that these differential metabolites might play a critical role in AD pathophysiology, and may serve as potential biomarkers for AD. Moreover, the results highlight the involvement of abnormal purine, pyrimidine, arginine, and proline metabolism, along with glycerophospholipid metabolism in early pathology of AD. For the first time, several differential metabolites are found to be associated with AD in this study. Targeted metabolomics can be used for rapid and accurate quantitative analysis of specific target metabolites associated with AD.

Macroevolutionary pattern of Saussurea (Asteraceae) provides insights into the drivers of radiating diversification.

Evolutionary radiations have intrigued biologists for more than a century, yet our understanding of the drivers of radiating diversification is still limited. We investigate the roles of environmental and species-intrinsic factors in driving the rapid radiation of Saussurea (Asteraceae) by deploying a number of palaeoenvironment-, diversity- and trait-dependent models, as well as ecological distribution data. We show that three main clades of Saussurea began to diversify in the Miocene almost simultaneously, with increasing diversification rates (DRs) negatively dependent on palaeotemperature but not dependent on species diversity. Our trait-dependent models detect some adaptive morphological innovations associated with DR shifts, while indicating additional unobserved traits are also likely driving diversification. Accounting for ecological niche data, we further reveal that accelerations in DRs are correlated with niche breadth and the size of species' range. Our results point out a macroevolutionary scenario where both adaptive morphological evolution and ecological opportunities provided by palaeoenvironmental fluctuations triggered an exceptionally radiating diversification. Our study highlights the importance of integrating phylogenomic, morphological, ecological and model-based approaches to illustrate evolutionary dynamics of lineages in biodiversity hotspots.

Metabolic characteristics of plasma bile acids in patients with intrahepatic cholestasis of pregnancy-mass spectrometric study.

INTRODUCTION: Intrahepatic cholestasis of pregnancy (ICP) is one of the more common complications in the middle and late stages of pregnancy, which requires early detection and intervention. OBJECTIVE: The aim of the study is to investigate the changes in the metabolic profile of bile acids (BAs) in plasma of pregnant women with ICP and to look biomarkers for the diagnosis and grading of ICP, and to explore the disease mechanism. METHODS: The targeted metabolomics based on high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) was used to analyze plasma BAs. RESULTS: Twenty-seven BAs can be quantified in all participants. Among them, 22 BAs were identified as differential BAs between ICP and control groups. Five BAs include 3ß-CA, 3ß-DCA, CDCA-3Gln, NCA, and Tß-MCA, were found to be associated with ICP for the first time. Nine BAs include NCA, GCA, GCDCA, GHCA, GUDCA, HCA, TCA, TCDCA and THCA, can be used as possible ICP diagnostic biomarkers. Four BAs, i.e., GLCA, THCA, GHCA and TLCA-3S may be used as potential biomarkers for ICP grading. CONCLUSION: There were significant differences in plasma BA profiles between ICP patients and the control. The BA profiles of mild ICP group and severe ICP group partially overlapped. Potential diagnostic and grading BA markers were identified. A significant characteristic of ICP group was the increase of conjugated BAs. A mechanism to sustain the equilibrium of BA metabolism and adaptive response has been developed in ICP patients to accelerate excretion and detoxification.

Potential biomarkers identified in plasma of patients with gestational diabetes mellitus.

INTRODUCTION: Gestational diabetes mellitus (GDM) is a common complication during pregnancy. Looking for reliable diagnostic markers for early diagnosis can reduce the impact of the disease on the fetus OBJECTIVE: The present study is designed to find plasma metabolites that can be used as potential biomarkers for GDM, and to clarify GDM-related mechanisms METHODS: By non-target metabolomics analysis, compared with their respective controls, the plasma metabolites of GDM pregnant women at 12-16 weeks and 24-28 weeks of pregnancy were analyzed. Multiple reaction monitoring (MRM) analysis was performed to verify the potential marker RESULTS: One hundred and seventy-two (172) and 478 metabolites were identified as differential metabolites in the plasma of GDM pregnant women at 12-16 weeks and 24-28 weeks of pregnancy, respectively. Among these, 40 metabolites were overlapped. Most of them are associated with the mechanism of diabetes, and related to short-term and long-term complications in the perinatal period. Among them, 7 and 10 differential metabolites may serve as potential biomarkers at the 12-16 weeks and 24-28 weeks of pregnancy, respectively. By MRM analysis, compared with controls, increased levels of 17(S)-HDoHE and sebacic acid may serve as early prediction biomarkers of GDM. At 24-28 weeks of pregnancy, elevated levels of 17(S)-HDoHE and L-Serine may be used as auxiliary diagnostic markers for GDM CONCLUSION: Abnormal amino acid metabolism and lipid metabolism in patients with GDM may be related to GDM pathogenesis. Several differential metabolites identified in this study may serve as potential biomarkers for GDM prediction and diagnosis.

Plastome phylogenomic study of Gentianeae (Gentianaceae): widespread gene tree discordance and its association with evolutionary rate heterogeneity of plastid genes.

BACKGROUND: Plastome-scale data have been prevalent in reconstructing the plant Tree of Life. However, phylogenomic studies currently based on plastomes rely primarily on maximum likelihood inference of concatenated alignments of plastid genes, and thus phylogenetic discordance produced by individual plastid genes has generally been ignored. Moreover, structural and functional characteristics of plastomes indicate that plastid genes may not evolve as a single locus and are experiencing different evolutionary forces, yet the genetic characteristics of plastid genes within a lineage remain poorly studied. RESULTS: We sequenced and annotated 10 plastome sequences of Gentianeae. Phylogenomic analyses yielded robust relationships among genera within Gentianeae. We detected great variation of gene tree topologies and revealed that more than half of the genes, including one (atpB) of the three widely used plastid markers (rbcL, atpB and matK) in phylogenetic inference of Gentianeae, are likely contributing to phylogenetic ambiguity of Gentianeae. Estimation of nucleotide substitution rates showed extensive rate heterogeneity among different plastid genes and among different functional groups of genes. Comparative analysis suggested that the ribosomal protein (RPL and RPS) genes and the RNA polymerase (RPO) genes have higher substitution rates and genetic variations among plastid genes in Gentianeae. Our study revealed that just one (matK) of the three (matK, ndhB and rbcL) widely used markers show high phylogenetic informativeness (PI) value. Due to the high PI and lowest gene-tree discordance, rpoC2 is advocated as a promising plastid DNA barcode for taxonomic studies of Gentianeae. Furthermore, our analyses revealed a positive correlation of evolutionary rates with genetic variation of plastid genes, but a negative correlation with gene-tree discordance under purifying selection. CONCLUSIONS: Overall, our results demonstrate the heterogeneity of nucleotide substitution rates and genetic characteristics among plastid genes providing new insights into plastome evolution, while highlighting the necessity of considering gene-tree discordance into phylogenomic studies based on plastome-scale data.

Genomic insights into adaptation to heterogeneous environments for the ancient relictual Circaeaster agrestis (Circaeasteraceae, Ranunculales).

Investigating the interaction between environmental heterogeneity and local adaptation is critical for understanding the evolutionary history of a species, providing the premise for studying the response of organisms to rapid climate change. However, for most species how exactly the spatial heterogeneity promotes population divergence and how genomic variations contribute to adaptive evolution remain poorly understood. We examine the contributions of geographical and environmental variables to population divergence of the relictual, alpine herb Circaeaster agrestis, as well as the genetic basis of local adaptation using RAD-seq and plastome data. We detected significant genetic structure with an extraordinary disequilibrium of genetic diversity among regions, and signals of isolation-by-distance along with isolation-by-resistance. The populations were estimated to begin diverging in the late Miocene, along with a possible ancestral distribution of the Hengduan Mountains and adjacent regions. Both environmental gradient and redundancy analyses revealed significant association between genetic variation and temperature variables. Genome-environment association analyses identified 16 putatively adaptive loci related mainly to biotic and abiotic stress resistance. Our genome-wide data provide new insights into the important role of environmental heterogeneity in shaping genetic structure, and access the footprints of local adaptation in an ancient relictual species, informing future conservation efforts.

Plastome phylogenomics of Saussurea (Asteraceae: Cardueae).

BACKGROUND: Saussurea DC. is one of the largest and most morphologically heterogeneous genera in Asteraceae. The relationships within Saussurea have been poorly resolved, probably due an early, rapid radiation. To examine plastome evolution and resolve backbone relationships within Saussurea, we sequenced the complete plastomes of 17 species representing all four subgenera. RESULTS: All Saussurea plastomes shared the gene content and structure of most Asteraceae plastomes. Molecular evolutionary analysis showed most of the plastid protein-coding genes have been under purifying selection. Phylogenomic analyses of 20 Saussurea plastomes that alternatively included nucleotide or amino acid sequences of all protein-coding genes, vs. the nucleotide sequence of the entire plastome, supported the monophyly of Saussurea and identified three clades within it. Three of the four traditional subgenera were recovered as paraphyletic. Seven plastome regions were identified as containing the highest nucleotide variability. CONCLUSIONS: Our analyses reveal both the structural conservatism and power of the plastome for resolving relationships in congeneric taxa. It is very likely that differences in topology among data sets is due primarily to differences in numbers of parsimony-informative characters. Our study demonstrates that the current taxonomy of Saussurea is likely based at least partly on convergent morphological character states. Greater taxon sampling will be necessary to explore character evolution and biogeography in the genus. Our results here provide helpful insight into which loci will provide the most phylogenetic signal in Saussurea and Cardueae.

Advances in Biomarker Studies in Autism Spectrum Disorders.

Autism spectrum disorder (ASD) is a neurological and developmental condition that begins early in childhood and lasts throughout life. The epidemiology of ASD is continuously increasing all over the world with huge social and economical burdens. As the etiology of autism is not completely understood, there is still no medication available for the treatment of this disorder. However, some behavioral interventions are available to improve the core and associated symptoms of autism, particularly when initiated at an early stage. Thus, there is an increasing demand for finding biomarkers for ASD. Although diagnostic biomarkers have not yet been established, research efforts have been carried out in neuroimaging and biological analyses including genomics and gene testing, proteomics, metabolomics, transcriptomics, and studies of the immune system, inflammation, and microRNAs. Here, we will review the current progress in these fields and focus on new methods, developments, research strategies, and studies of blood-based biomarkers.

A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG) Pattern Recognition.

Performance degradation will be caused by a variety of interfering factors for pattern recognition-based myoelectric control methods in the long term. This paper proposes an adaptive learning method with low computational cost to mitigate the effect in unsupervised adaptive learning scenarios. We presents a particle adaptive classifier (PAC), by constructing a particle adaptive learning strategy and universal incremental least square support vector classifier (LS-SVC). We compared PAC performance with incremental support vector classifier (ISVC) and non-adapting SVC (NSVC) in a long-term pattern recognition task in both unsupervised and supervised adaptive learning scenarios. Retraining time cost and recognition accuracy were compared by validating the classification performance on both simulated and realistic long-term EMG data. The classification results of realistic long-term EMG data showed that the PAC significantly decreased the performance degradation in unsupervised adaptive learning scenarios compared with NSVC (9.03% ± 2.23%, p < 0.05) and ISVC (13.38% ± 2.62%, p = 0.001), and reduced the retraining time cost compared with ISVC (2 ms per updating cycle vs. 50 ms per updating cycle).

[Influence of photoselective vaporization of the prostate on the sexual function of the patient].

n recent years, photoselective vaporization of the prostate (PVP) has gained a wide clinical application in the treatment of benign prostatic hyperplasia (BPH) for its satisfactory effect, high safety, and low incidence of complications. With the improvement of living conditions, BPH patients are paying more attention to their sexual function, especially erectile function and ejaculatory problems instead of just focusing on the alleviation of lower urinary tract symptoms. Few studies of PVP, however, relate to its association with the sexual function of the patient and there is a certain controversy over the influence of PVP on it in the existing literature. Prevailing views hold that the uprated power in PVP does not affect erectile function or increase the risk of retrograde ejaculation (REj) and that PVP is even better than transurethral resection of the prostate (TURP) in avoiding the risk of REj.

L-Rhamnose Enhances the Immunogenicity of Melanoma-Associated Antigen A3 for Stimulating Antitumor Immune Responses.

Vaccines based on melanoma-associated antigens (MAGEs) present a promising strategy for tumor immunotherapy, albeit with weak immunogenicity. In this study, the xenoantigen L-rhamnose (Rha) was chemically conjugated with truncated MAGE-A3 (tMAGE-A3) to generate Rha-tMAGE-A3. The product showed good antigenicity with anti-Rha antibodies purified from human serum. FITC-labeled Rha-tMAGE-A3 was detected in THP-1 human macrophage cells via the anti-Rha antibody-dependent antigen uptake process. Furthermore, peripheral blood mononuclear cells (PBMCs) stimulated with Rha-tMAGE-A3 in the presence of anti-Rha antibodies showed better cytotoxicity toward A375 human melanoma cells surfaced by MAGE-A3 antigen compared to PBMCs stimulated with tMAGE-A3. All data reveal that linking of Rha epitopes to MAGE enhances the immunogenicity of MAGE by harnessing the immune effector functions of human naturally existing anti-Rha antibodies. Rha epitopes could become immunogenicity enhancers of tumor associated antigens in the development of tumor immunotherapies.