Prostate cancer (PCa) is the second most prevalent cancer among men worldwide when assessing age-standardized incidence rates. The primary method for early PCa diagnosis involves measuring the... Show moreProstate cancer (PCa) is the second most prevalent cancer among men worldwide when assessing age-standardized incidence rates. The primary method for early PCa diagnosis involves measuring the serum concentration of prostate-specific antigen (PSA), with elevated levels (> 3 ng/mL in the Netherlands) indicating the potential presence of PCa. However, the conventional PSA test exhibits a low specificity. Thus, clinical challenges persist, including the differentiation between PCa and benign prostatic hyperplasia and distinguishing indolent PCa from aggressive forms. This underscores the need for a more specific biomarker for early PCa detection and stratification. Previous studies have reported altered glycosylation features in two prostate-secreted glycoproteins, PSA and prostatic acid phosphatase (PAP) in PCa patients, e.g. variation in sialylation, fucosylation and the level of LacdiNAc . The aim of this thesis was to identify PCa biomarkers for early detection and to improve patient stratification, focusing specifically on the glycomic profiles of PSA and PAP. In addition, as PSA plays an important role with regard to fertility, its glycosylation -in relation to male infertility- was also touched upon. For this purpose, mass spectrometry (MS) based glycoproteomic methods were established to map the glycoprofiles of PSA and PAP derived from various biofluids. Show less
Wang, W.; Nier, C.R. de; Wuhrer, M.; Lageveen-Kammeijer, G.S.M. 2023
Prostate-specific antigen (PSA) is a well-known clinical biomarker in prostate cancer (PCa) diagnosis, but a better test is still needed, as the serum-level-based PSA quantification exhibits... Show moreProstate-specific antigen (PSA) is a well-known clinical biomarker in prostate cancer (PCa) diagnosis, but a better test is still needed, as the serum-level-based PSA quantification exhibits limited specificity and comes with poor predictive value. Prior to PSA, prostatic acid phosphatase (PAP) was used, but it was replaced by PSA because PSA improved the early detection of PCa. Upon revisiting PAP and its glycosylation specifically, it appears to be a promising new biomarker candidate. Namely, previous studies have indicated that PAP glycoforms differ between PCa and non-PCa individuals. However, an in-depth characterization of PAP glycosylation is still lacking. In this study, we established an in-depth glycoproteomic assay for urinary PAP by characterizing both the micro- and macroheterogeneity of the PAP glycoprofile. For this purpose, PAP samples were analyzed by capillary electrophoresis coupled to mass spectrometry after affinity purification from urine and proteolytic digestion. The developed urinary PAP assay was applied on a pooled DRE (digital rectal examination) urine sample from nine individuals. Three glycosylation sites were characterized, namely N-94, N-220, and N-333, via N-glycopeptide analysis. Taking sialic acid linkage isomers into account, a total of 63, 27, and 4 N-glycan structures were identified, respectively. The presented PAP glycoproteomic assay will enable the determination of potential glycomic biomarkers for the early detection and prognosis of PCa in cohort studies. Show less
Ketodeoxynononic acid (Kdn) is a rather uncommon class of sialic acid in mammals. However, associations have been found between elevated concentrations of free or conjugated Kdn in relation to... Show moreKetodeoxynononic acid (Kdn) is a rather uncommon class of sialic acid in mammals. However, associations have been found between elevated concentrations of free or conjugated Kdn in relation to human cancer progression. Hitherto, there has been a lack of conclusive evidence that Kdn occurs on (specific) human glycoproteins (conjugated Kdn). Here, we report for the first time that Kdn is expressed on prostate-specific antigen (PSA) N-linked glycans derived from human seminal plasma and urine. Interestingly, Kdn was found only in an α2,3-linkage configuration on an antennary galactose, indicating a highly specific biosynthesis. This unusual glycosylation feature was also identified in a urinary PSA cohort in relation to prostate cancer (PCa), although no differences were found between PCa and non-PCa patients. Further research is needed to investigate the occurrence, biosynthesis, biological role, and biomarker potential of both free and conjugated Kdn in humans. Show less
Food security and sustainable development of agriculture has been a key challenge for decades. To support this, nanotechnology in the agricultural sectors increases productivity and food security,... Show moreFood security and sustainable development of agriculture has been a key challenge for decades. To support this, nanotechnology in the agricultural sectors increases productivity and food security, while leaving complex environmental negative impacts including pollution of the human food chains by nanoparticles. Here we model the effects of silver nanoparticles (Ag-NPs) in a food chain consisting of soil-grown lettuce Lactuca sativa and snail Achatina fulica. Soil-grown lettuce were exposed to sulfurized Ag-NPs via root or metallic Ag-NPs via leaves before fed to snails. We discover an important biomagnification of silver in snails sourced from plant root uptake, with trophic transfer factors of 2.0–5.9 in soft tissues. NPs shifts from original size (55–68 nm) toward much smaller size (17–26 nm) in snails. Trophic transfer of Ag-NPs reprograms the global metabolic profile by down-regulating or up-regulating metabolites for up to 0.25- or 4.20- fold, respectively, relative to the control. These metabolites control osmoregulation, phospholipid, energy, and amino acid metabolism in snails, reflecting molecular pathways of biomagnification and pontential adverse biological effects on lower trophic levels. Consumption of these Ag-NP contaminated snails causes non-carcinogenic effects on human health. Global public health risks decrease by 72% under foliar Ag-NP application in agriculture or through a reduction in the consumption of snails sourced from root application. The latter strategy is at the expense of domestic economic losses in food security of $177.3 and $58.3 million annually for countries such as Nigeria and Cameroon. Foliar Ag-NP application in nano-agriculture has lower hazard quotient risks on public health than root application to ensure global food safety, as brought forward by the United Nations Sustainable Development Goals. Show less
Shi, Y.; Wang, W.; Zhao, G.; Zhai, M.; Chen, G.; Jiang, Z.; ... ; Esteves, L. 2023
In this thesis, we focus on novel proteins/mechanisms that regulate integrin-adhesion mediated mechano-transduction. We characterized the role of integrin α6β4/HD and caskin2 in force generation... Show moreIn this thesis, we focus on novel proteins/mechanisms that regulate integrin-adhesion mediated mechano-transduction. We characterized the role of integrin α6β4/HD and caskin2 in force generation via FA, investigated the underlying crosstalk between adhesions and cytoskeletons. Moreover, we also explored the mechanism that drives the integrin αVβ5 clustering in FCLs, in which cell tension is also involved. Last but not the least, we investigated the role of an unexplored protein, caskin2, in the regulation of cellular mechanics. Show less
Deep learning for fine-grained image retrieval in an incremental context is less investigated. In this paper, we explore this task to realize the model's continuous retrieval ability. That means,... Show moreDeep learning for fine-grained image retrieval in an incremental context is less investigated. In this paper, we explore this task to realize the model's continuous retrieval ability. That means, the model enables to perform well on new incoming data and reduce forgetting of the knowledge learned on preceding old tasks. For this purpose, we distill semantic correlations knowledge among the representations extracted from the new data only so as to regularize the parameters updates using the teacher-student framework. In particular, for the case of learning multiple tasks sequentially, aside from the correlations distilled from the penultimate model, we estimate the representations for all prior models and further their semantic correlations by using the representations extracted from the new data. To this end, the estimated correlations are used as an additional regularization and further prevent catastrophic forgetting over all previous tasks, and it is unnecessary to save the stream of models trained on these tasks. Extensive experiments demonstrate that the proposed method performs favorably for retaining performance on the already-trained old tasks and achieving good accuracy on the current task when new data are added at once or sequentially. Show less
In recent years a vast amount of visual content has been generated and shared from various fields, such as social media platforms, medical images, and robotics. This abundance of content creation... Show moreIn recent years a vast amount of visual content has been generated and shared from various fields, such as social media platforms, medical images, and robotics. This abundance of content creation and sharing has introduced new challenges. In particular, searching databases for similar content, i.e.content based image retrieval (CBIR), is a long-established research area, and more efficient and accurate methods are needed for real time retrieval. Artificial intelligence has made progress in CBIR and has significantly facilitated the process of intelligent search. In this survey we organize and review recent CBIR works that are developed based on deep learning algorithms and techniques, including insights and techniques from recent papers. We identify and present the commonly-used benchmarks and evaluation methods used in the field. We collect common challenges and propose promising future directions. More specifically, we focus on image retrieval with deep learning and organize the state of the art methods according to the types of deep network structure, deep features, feature enhancement methods, and network fine-tuning strategies. Our survey considers a wide variety of recent methods, aiming to promote a global view of the field of instance-based CBIR. Show less
Wang, W.; Kaluza, A.; Nouta, J.; Nicolardi, S.; Ferens-Sieczkowska, M.; Wuhrer, M.; ... ; Haan, N. de 2021
An altered total seminal plasma glycosylation has been associated with male infertility, and the highly abundant seminal plasma glycoprotein prostate-specific antigen (PSA) plays an important role... Show moreAn altered total seminal plasma glycosylation has been associated with male infertility, and the highly abundant seminal plasma glycoprotein prostate-specific antigen (PSA) plays an important role in fertilization. However, the exact role of PSA glycosylation in male fertility is not clear. To understand the involvement of PSA glycosylation in the fertilization process, analytical methods are required to study the glycosylation of PSA from seminal plasma with a high glycoform resolution and in a protein-specific manner. In this study, we developed a novel, high-throughput PSA glycopeptide workflow, based on matrix-assisted laser desorption/ionization-mass spectrometry, allowing the discrimination of sialic acid linkage isomers via the derivatization of glycopeptides. The method was successfully applied on a cohort consisting of seminal plasma from infertile and fertile men (N = 102). Forty-four glycopeptides were quantified in all samples, showing mainly complex-type glycans with high levels of fucosylation and sialylation. In addition, N,N-diacetyllactosamine (LacdiNAc) motives were found as well as hybrid-type and high mannose-type structures. Our method showed a high intra- and interday repeatability and revealed no difference in PSA glycosylation between fertile and infertile men. Next to seminal plasma, the method is also expected to be of use for studying PSA glycopeptides derived from other biofluids and/or in other disease contexts. Show less
Shift work causes circadian misalignment and is a risk factor for obesity. While some characteristics of the human circadian system and energy metabolism differ between males and females, little is... Show moreShift work causes circadian misalignment and is a risk factor for obesity. While some characteristics of the human circadian system and energy metabolism differ between males and females, little is known about whether sex modulates circadian misalignment effects on energy homeostasis. Here we show-using a randomized crossover design with two 8-d laboratory protocols in 14 young healthy adults (6 females)-that circadian misalignment has sex-specific influences on energy homeostasis independent of behavioral/environmental factors. First, circadian misalignment affected 24-h average levels of the satiety hormone leptin sex-dependently (P < 0.0001), with a similar to 7% decrease in females (P < 0.05) and an similar to 11% increase in males (P < 0.0001). Consistently, circadian misalignment also increased the hunger hormone ghrelin by similar to 8% during wake periods in females (P < 0.05) without significant effect in males. Females reported reduced fullness, consistent with their appetite hormone changes. However, males reported a rise in cravings for energy-dense and savory foods not consistent with their homeostatic hormonal changes, suggesting involvement of hedonic appetite pathways in males. Moreover, there were significant sex-dependent effects of circadian misalignment on respiratory quotient (P < 0.01), with significantly reduced values (P < 0.01) in females when misaligned, and again no significant effects in males, without sex-dependent effects on energy expenditure. Changes in sleep, thermoregulation, behavioral activity, lipids, and catecholamine levels were also assessed. These findings demonstrate that sex modulates the effects of circadian misalignment on energy metabolism, indicating possible sex-specific mechanisms and countermeasures for obesity in male and female shift workers. Show less
