Serum Hydroxysteroid (17beta) dehydrogenase 1 concentration in pregnant women correlates with pregnancy-associated plasma protein a but does not serve as an independent marker for preeclampsia.

Hydroxysteroid (17beta) dehydrogenase 1 (HSD17B1) is a steroid synthetic enzyme expressed in ovarian granulosa cells and placental syncytiotrophoblasts. Here, HSD17B1 serum concentration was measured with a validated immuno assay during pregnancy at three time points (12-14, 18-20 and 26-28 weeks of gestation). The concentration increased 2.5-fold (p < 0.0001) and 1.7-fold (p = 0.0019) during the follow-up period for control women and women who later developed preeclampsia (PE), respectively, and a significant difference was observed at weeks 26-28 (p = 0.0266). HSD17B1 concentration at all the three time points positively correlated with serum PAPPA measured at the first time point (first time point r = 0.38, p = 1.1x10-10; second time point r = 0.27, p = 5.9x10-6 and third timepoint r = 0.26, p = 2.3x10-5). No correlation was observed between HSD17B1 and placental growth factor (PLGF). Serum HSD17B1, furthermore, negatively correlated with the mother's weight and body mass index (BMI), mirroring the pattern observed for PAPPA. The univariable logistic regression identified a weak association between HSD17B1 at 26-28 weeks and later development of PE (P = 0.04). Also, the best multivariable model obtained using penalized logistic regression with stable iterative variable selection at 26-28 weeks included HSD17B1, together with PLGF, PAPPA and the mother's BMI. While the area under the ROC curve of the model was higher than that of the adjusted PLGF, the difference was not statistically significant. In summary, the serum concentration of HSD17B1 correlated with PAPPA, another protein expressed in syncytiotrophoblasts, and with mother's weight and BMI but could not be considered as an independent marker for PE.

Deep Learning Enables Automatic Detection of Joint Damage Progression in Rheumatoid Arthritis-Model Development and External Validation.

OBJECTIVES: Although deep learning has demonstrated substantial potential in automatic quantification of joint damage in rheumatoid arthritis (RA), evidence for detecting longitudinal changes at an individual patient level is lacking. Here, we introduce and externally validate our automated RA scoring algorithm (AuRA), and demonstrate its utility for monitoring radiographic progression in a real-world setting. METHODS: The algorithm, originally developed during the Rheumatoid Arthritis 2-Dialogue for Reverse Engineering Assessment and Methods (RA2-DREAM) challenge, was trained to predict expert-curated Sharp-van der Heijde total scores in hand and foot radiographs from two previous clinical studies (n = 367). We externally validated AuRA against data (n = 205) from Turku University Hospital and compared the performance against two top-performing RA2-DREAM solutions. Finally, for 54 patients, we extracted additional radiograph sets from another control visit to the clinic (average time interval of 4.6 years). RESULTS: In the external validation cohort, with a root-mean-square-error (RMSE) of 23.6, AuRA outperformed both top-performing RA2-DREAM algorithms (RMSEs 35.0 and 35.6). The improved performance was explained mostly by lower errors at higher expert-assessed scores. The longitudinal changes predicted by our algorithm were significantly correlated with changes in expert-assessed scores (Pearson's R = 0.74, p< 0.001). CONCLUSION: AuRA had the best external validation performance and demonstrated potential for detecting longitudinal changes in joint damage. Available in https://hub.docker.com/r/elolab/aura, our algorithm can easily be applied for automatic detection of radiographic progression in the future, reducing the need for laborious manual scoring.

Development and validation of a weight-loss predictor to assist weight loss management.

This study aims to develop and validate a modeling framework to predict long-term weight change on the basis of self-reported weight data. The aim is to enable focusing resources of health systems on individuals that are at risk of not achieving their goals in weight loss interventions, which would help both health professionals and the individuals in weight loss management. The weight loss prediction models were built on 327 participants, aged 21-78, from a Finnish weight coaching cohort, with at least 9 months of self-reported follow-up weight data during weight loss intervention. With these data, we used six machine learning methods to predict weight loss after 9 months and selected the best performing models for implementation as modeling framework. We trained the models to predict either three classes of weight change (weight loss, insufficient weight loss, weight gain) or five classes (high/moderate/insufficient weight loss, high/low weight gain). Finally, the prediction accuracy was validated with an independent cohort of overweight UK adults (n = 184). Of the six tested modeling approaches, logistic regression performed the best. Most three-class prediction models achieved prediction accuracy of > 50% already with half a month of data and up to 97% with 8 months. The five-class prediction models achieved accuracies from 39% (0.5 months) to 89% (8 months). Our approach provides an accurate prediction method for long-term weight loss, with potential for easier and more efficient management of weight loss interventions in the future. A web application is available: https://elolab.shinyapps.io/WeightChangePredictor/ .The trial is registered at clinicaltrials.gov/ct2/show/NCT04019249 (Clinical Trials Identifier NCT04019249), first posted on 15/07/2019.

Macro- and Microrheological Properties of Mucus Surrogates in Comparison to Native Intestinal and Pulmonary Mucus.

Mucus is a complex hydrogel that acts as a protective barrier in various parts of the human body. Both composition and structural properties play a crucial role in maintaining barrier properties while dictating diffusion of molecules and (nano)materials. In this study, we compare previously described mucus surrogates with the native human airway and pig intestinal mucus. Oscillatory shear rheology was applied to characterize mucus on the bulk macrorheological level, revealing that the artificial airway surrogate deviates from the elastic-dominant behavior of native mucus samples. We circumvented this limitation through the addition of a cross-linking polymer to the surrogate, adjusting the rheological properties closer to those of native mucus. Applying particle tracking microrheology, we further demonstrated that the mechanical properties at the microscale differ significantly between artificial and native mucus. We conclude that proper characterization of mucus and its surrogates is vital for a reliable investigation of nanoparticle-based mucosal drug delivery.

Kinetics of mRNA delivery and protein translation in dendritic cells using lipid-coated PLGA nanoparticles.

BACKGROUND: Messenger RNA (mRNA) has gained remarkable attention as an alternative to DNA-based therapies in biomedical research. A variety of biodegradable nanoparticles (NPs) has been developed including lipid-based and polymer-based systems for mRNA delivery. However, both systems still lack in achieving an efficient transfection rate and a detailed understanding of the mRNA transgene expression kinetics. Therefore, quantitative analysis of the time-dependent translation behavior would provide a better understanding of mRNA's transient nature and further aid the enhancement of appropriate carriers with the perspective to generate future precision nanomedicines with quick response to treat various diseases. RESULTS: A lipid-polymer hybrid system complexed with mRNA was evaluated regarding its efficiency to transfect dendritic cells (DCs) by simultaneous live cell video imaging of both particle uptake and reporter gene expression. We prepared and optimized NPs consisting of poly (lactid-co-glycolid) (PLGA) coated with the cationic lipid 1, 2-di-O-octadecenyl-3-trimethylammonium propane abbreviated as LPNs. An earlier developed polymer-based delivery system (chitosan-PLGA NPs) served for comparison. Both NPs types were complexed with mRNA-mCherry at various ratios. While cellular uptake and toxicity of either NPs was comparable, LPNs showed a significantly higher transfection efficiency of ~ 80% while chitosan-PLGA NPs revealed only ~ 5%. Further kinetic analysis elicited a start of protein translation after 1 h, with a maximum after 4 h and drop of transgene expression after 48 h post-transfection, in agreement with the transient nature of mRNA. CONCLUSIONS: Charge-mediated complexation of mRNA to NPs enables efficient and fast cellular delivery and subsequent protein translation. While cellular uptake of both NP types was comparable, mRNA transgene expression was superior to polymer-based NPs when delivered by lipid-polymer NPs.

Farnesylated Glycol Chitosan as a Platform for Drug Delivery: Synthesis, Characterization, and Investigation of Mucus-Particle Interactions.

Amphiphilic polymer-based drug delivery systems hold potential in enhancing pharmacokinetics and therapeutic efficacy due to their ability to simultaneously codeliver different drugs in a controlled manner. We propose here a facile method for synthesizing a new amphiphilic polymer, farnesylated glycol chitosan (FGC), which self-assembles into nanoparticles upon being dispersed in aqueous media. The characteristics of FGC nanoparticles, in particular the size, could be tuned in a range from 200 to 500 nm by modulating the degree of farnesylation and the pH and polymer concentration during particle preparation. Carrier capacity, release kinetics, and surface modification of the established system were investigated using different model compounds. The colloids were biocompatible and stable at biologically relevant pH values. The interactions between the carriers and human mucus were examined by multiple particle tracking, which revealed that ∼80% of the particles remain immobilized within the mucus matrix. These results postulate FGC as a versatile drug delivery platform.

PreTIS: A Tool to Predict Non-canonical 5' UTR Translational Initiation Sites in Human and Mouse.

Translation of mRNA sequences into proteins typically starts at an AUG triplet. In rare cases, translation may also start at alternative non-AUG codons located in the annotated 5' UTR which leads to an increased regulatory complexity. Since ribosome profiling detects translational start sites at the nucleotide level, the properties of these start sites can then be used for the statistical evaluation of functional open reading frames. We developed a linear regression approach to predict in-frame and out-of-frame translational start sites within the 5' UTR from mRNA sequence information together with their translation initiation confidence. Predicted start codons comprise AUG as well as near-cognate codons. The underlying datasets are based on published translational start sites for human HEK293 and mouse embryonic stem cells that were derived by the original authors from ribosome profiling data. The average prediction accuracy of true vs. false start sites for HEK293 cells was 80%. When applied to mouse mRNA sequences, the same model predicted translation initiation sites observed in mouse ES cells with an accuracy of 76%. Moreover, we illustrate the effect of in silico mutations in the flanking sequence context of a start site on the predicted initiation confidence. Our new webservice PreTIS visualizes alternative start sites and their respective ORFs and predicts their ability to initiate translation. Solely, the mRNA sequence is required as input. PreTIS is accessible at http://service.bioinformatik.uni-saarland.de/pretis.

Analysis of 101 nuclear transcriptomes reveals 23 distinct regulons and their relationship to metabolism, chromosomal gene distribution and co-ordination of nuclear and plastid gene expression.

Post-endosymbiotic evolution of the proto-chloroplast was characterized by gene transfer to the nucleus. Hence, most chloroplast proteins are nuclear-encoded and the regulation of chloroplast functions includes nuclear transcriptional control. The expression profiles of 3292 nuclear Arabidopsis genes, most of them encoding chloroplast proteins, were determined from 101 different conditions and have been deposited at the GEO database (http://www.ncbi.nih.gov/geo/) under . The 1590 most-regulated genes fell into 23 distinct groups of co-regulated genes (regulons). Genes of some regulons are not evenly distributed among the five Arabidopsis chromosomes and pairs of adjacent, co-expressed genes exist. Except regulons 1 and 2, regulons are heterogeneous and consist of genes coding for proteins with different subcellular locations or contributing to several biochemical functions. This implies that different organelles and/or metabolic pathways are co-ordinated at the nuclear transcriptional level, and a prototype for this is regulon 12 which contains genes with functions in amino acid and carbohydrate metabolism, as well as genes associated with transport or transcription. The co-expression of nuclear genes coding for subunits of the photosystems or encoding proteins involved in the transcription/translation of plastome genes (particularly ribosome polypeptides) (regulons 1 and 2, respectively) implies the existence of a novel mechanism that co-ordinates plastid and nuclear gene expression and involves nuclear control of plastid ribosome abundance. The co-regulation of genes for photosystem and plastid ribosome proteins escapes a previously described general control of nuclear chloroplast proteins imposed by a transcriptional master switch, highlighting a mode of transcriptional regulation of photosynthesis which is different compared to other chloroplast functions. From the evolutionary standpoint, the results provided indicate that functional integration of the proto-chloroplast into the eukaryotic cell was associated with the establishment of different layers of nuclear transcriptional control.

The role of [Delta]1-pyrroline-5-carboxylate dehydrogenase in proline degradation.

In response to stress, plants accumulate Pro, requiring degradation after release from adverse conditions. Delta1-Pyrroline-5-carboxylate dehydrogenase (P5CDH), the second enzyme for Pro degradation, is encoded by a single gene expressed ubiquitously. To study the physiological function of P5CDH, T-DNA insertion mutants in AtP5CDH were isolated and characterized. Although Pro degradation was undetectable in p5cdh mutants, neither increased Pro levels nor an altered growth phenotype were observed under normal conditions. Thus AtP5CDH is essential for Pro degradation but not required for vegetative plant growth. External Pro application caused programmed cell death, with callose deposition, reactive oxygen species production, and DNA laddering, involving a salicylic acid signal transduction pathway. p5cdh mutants were hypersensitive toward Pro and other molecules producing P5C, such as Arg and Orn. Pro levels were the same in the wild type and mutants, but P5C was detectable only in p5cdh mutants, indicating that P5C accumulation may be the cause for Pro hypersensitivity. Accordingly, overexpression of AtP5CDH resulted in decreased sensitivity to externally supplied Pro. Thus, Pro and P5C/Glu semialdehyde may serve as a link between stress responses and cell death.

Root phloem-specific expression of the plasma membrane amino acid proton co-transporter AAP3.

Amino acids are regarded as the nitrogen 'currency' of plants. Amino acids can be taken up from the soil directly or synthesized from inorganic nitrogen, and then circulated in the plant via phloem and xylem. AtAAP3, a member of the Amino Acid Permease (AAP) family, is mainly expressed in root tissue, suggesting a potential role in the uptake and distribution of amino acids. To determine the spatial expression pattern of AAP3, promoter-reporter gene fusions were introduced into Arabidopsis. Histochemical analysis of AAP3 promoter-GUS expressing plants revealed that AAP3 is preferentially expressed in root phloem. Expression was also detected in stamens, in cotyledons, and in major veins of some mature leaves. GFP-AAP3 fusions and epitope-tagged AAP3 were used to confirm the tissue specificity and to determine the subcellular localization of AtAAP3. When overexpressed in yeast or plant protoplasts, the functional GFP-AAP3 fusion was localized in subcellular organelle-like structures, nuclear membrane, and plasma membrane. Epitope-tagged AAP3 confirmed its localization to the plasma membrane and nuclear membrane of the phloem, consistent with the promoter-GUS study. In addition, epitope-tagged AAP3 protein was localized in endodermal cells in root tips. The intracellular localization suggests trafficking or cycling of the transporter, similar to many metabolite transporters in yeast or mammals, for example, yeast amino acid permease GAP1. Despite the specific expression pattern, knock-out mutants did not show altered phenotypes under various conditions including N-starvation. Microarray analyses revealed that the expression profile of genes involved in amino acid metabolism did not change drastically, indicating potential compensation by other amino acid transporters.

Functional specialization amongst the Arabidopsis Toc159 family of chloroplast protein import receptors.

The initial stages of preprotein import into chloroplasts are mediated by the receptor GTPase Toc159. In Arabidopsis thaliana, Toc159 is encoded by a small gene family: atTOC159, atTOC132, atTOC120, and atTOC90. Phylogenetic analysis suggested that at least two distinct Toc159 subtypes, characterized by atToc159 and atToc132/atToc120, exist in plants. atTOC159 was strongly expressed in young, photosynthetic tissues, whereas atTOC132 and atTOC120 were expressed at a uniformly low level and so were relatively prominent in nonphotosynthetic tissues. Based on the albino phenotype of its knockout mutant, atToc159 was previously proposed to be a receptor with specificity for photosynthetic preproteins. To elucidate the roles of the other isoforms, we characterized Arabidopsis knockout mutants for each one. None of the single mutants had strong visible phenotypes, but toc132 toc120 double homozygotes appeared similar to toc159, indicating redundancy between atToc132 and atToc120. Transgenic complementation studies confirmed this redundancy but revealed little functional overlap between atToc132/atToc120 and atToc159 or atToc90. Unlike toc159, toc132 toc120 caused structural abnormalities in root plastids. Furthermore, when proteomics and transcriptomics were used to compare toc132 with ppi1 (a receptor mutant that is specifically defective in the expression, import, and accumulation of photosynthetic proteins), major differences were observed, suggesting that atToc132 (and atToc120) has specificity for nonphotosynthetic proteins. When both atToc159 and the major isoform of the other subtype, atToc132, were absent, an embryo-lethal phenotype resulted, demonstrating the essential role of Toc159 in the import mechanism.

Inactivation of the chloroplast ATP synthase gamma subunit results in high non-photochemical fluorescence quenching and altered nuclear gene expression in Arabidopsis thaliana.

The nuclear atpC1 gene encoding the gamma subunit of the plastid ATP synthase has been inactivated by T-DNA insertion mutagenesis in Arabidopsis thaliana. In the seedling-lethal dpa1 (deficiency of plastid ATP synthase 1) mutant, the absence of detectable amounts of the gamma subunit destabilizes the entire ATP synthase complex. The expression of a second gene copy, atpC2, is unaltered in dpa1 and is not sufficient to compensate for the lack of atpC1 expression. However, in vivo protein labeling analysis suggests that assembly of the ATP synthase alpha and beta subunits into the thylakoid membrane still occurs in dpa1. As a consequence of the destabilized ATP synthase complex, photophosphorylation is abolished even under reducing conditions. Further effects of the mutation include an increased light sensitivity of the plant and an altered photosystem II activity. At low light intensity, chlorophyll fluorescence induction kinetics is close to those found in wild type, but non-photochemical quenching strongly increases with increasing actinic light intensity resulting in steady state fluorescence levels of about 60% of the minimal dark fluorescence. Most fluorescence quenching relaxed within 3 min after dark incubation. Spectroscopic and biochemical studies have shown that a high proton gradient is responsible for most quenching. Thylakoids of illuminated dpa1 plants were swollen due to an increased proton accumulation in the lumen. Expression profiling of 3292 nuclear genes encoding mainly chloroplast proteins demonstrates that most organelle functions are down-regulated. On the contrary, the mRNA expression of some photosynthesis genes is significantly up-regulated, probably to compensate for the defect in dpa1.

Covariations in the nuclear chloroplast transcriptome reveal a regulatory master-switch.

The evolution of the endosymbiotic progenitor into the chloroplast organelle was associated with the transfer of numerous chloroplast genes into the nucleus. Hence, inter-organellar signalling, and the co-ordinated expression of sets of nuclear genes, was set up to control the metabolic and developmental status of the chloroplast. Here, we show by the differential-expression analysis of 3,292 genes, that most of the 35 environmental and genetic conditions tested, including plastid signalling mutations, elicit only three main classes of response from the nuclear chloroplast transcriptome. Two classes, probably involving GUN (genomes uncoupled)-type plastid signalling, are characterized by alterations, in opposite directions, in the expression of largely overlapping sets of genes.

Gene-sequence-tag expression analyses of 1,800 genes related to chloroplast functions.

Quantification of the expression levels of nuclear genes encoding plastid proteins under different genetic or environmental conditions can contribute to the genetic dissection of plastid functions. To facilitate such measurements, a set of 1,827 Arabidopsis thaliana genes coding for plastid proteins was PCR-amplified from genomic DNA and spotted on nylon membranes to generate an array of chloroplast-specific gene-sequence-tags (GSTs). The sensitivity and reliability of the experimental system was evaluated and a procedure was developed for detecting differential gene expression. The GST array was found to serve as a reliable monitor of changes in gene expression induced by environmental and genetic alteration of chloroplast functions. Based on comparisons of dark- versus light-grown seedlings, and wild-type versus prpl11-1 plants, lists of differentially expressed genes are provided which include 193/7 and 25/42 up/down-regulated genes, respectively. The cut-off values for differential expression were 2.5-times (up) and 0.40 (down). Additional up-regulated genes with relatively low expression ratios (from 1.5- to 2.5-times) or down-regulated with relatively high ratios (0.4-0.67) can be accessed at the website: http://www.mpiz-koeln.mpg.de/~richly/GST-array.html. A sample of genes analysed by quantitative reverse transcription PCR confirmed the expression profiles monitored by the GST array. Differential hybridisation experiments with the prpl11-1 mutant revealed the existence of regulatory networks sensing the protein state of the chloroplast and transmitting the signal to the nucleus.